Hydroclimate temporal variability in a coastal Mediterranean watershed: the Tafna basin, North-West Algeria

NASA Astrophysics Data System (ADS)

Boulariah, Ouafik; Longobardi, Antonia; Meddi, Mohamed

2017-04-01

One of the major challenges scientists, practitioners and stakeholders are nowadays involved in, is to provide the worldwide population with reliable water supplies, protecting, at the same time, the freshwater ecosystems quality and quantity. Climate and land use changes undermine the balance between water demand and water availability, causing alteration of rivers flow regime. Knowledge of hydro-climate variables temporal and spatial variability is clearly helpful to plan drought and flood hazard mitigation strategies but also to adapt them to future environmental scenarios. The present study relates to the coastal semi-arid Tafna catchment, located in the North-West of Algeria, within the Mediterranean basin. The aim is the investigation of streamflow and rainfall indices temporal variability in six sub-basins of the large catchment Tafna, attempting to relate streamflow and rainfall changes. Rainfall and streamflow time series have been preliminary tested for data quality and homogeneity, through the coupled application of two-tailed t test, Pettitt test and Cumsum tests (significance level of 0.1, 0.05 and 0.01). Subsequently maximum annual daily rainfall and streamflow and average daily annual rainfall and streamflow time series have been derived and tested for temporal variability, through the application of the Mann Kendall and Sen's test. Overall maximum annual daily streamflow time series exhibit a negative trend which is however significant for only 30% of the station. Maximum annual daily rainfall also e exhibit a negative trend which is intend significant for the 80% of the stations. In the case of average daily annual streamflow and rainfall, the tendency for decrease in time is unclear and, in both cases, appear significant for 60% of stations.

Wavelet-based time series bootstrap model for multidecadal streamflow simulation using climate indicators

NASA Astrophysics Data System (ADS)

Erkyihun, Solomon Tassew; Rajagopalan, Balaji; Zagona, Edith; Lall, Upmanu; Nowak, Kenneth

2016-05-01

A model to generate stochastic streamflow projections conditioned on quasi-oscillatory climate indices such as Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) is presented. Recognizing that each climate index has underlying band-limited components that contribute most of the energy of the signals, we first pursue a wavelet decomposition of the signals to identify and reconstruct these features from annually resolved historical data and proxy based paleoreconstructions of each climate index covering the period from 1650 to 2012. A K-Nearest Neighbor block bootstrap approach is then developed to simulate the total signal of each of these climate index series while preserving its time-frequency structure and marginal distributions. Finally, given the simulated climate signal time series, a K-Nearest Neighbor bootstrap is used to simulate annual streamflow series conditional on the joint state space defined by the simulated climate index for each year. We demonstrate this method by applying it to simulation of streamflow at Lees Ferry gauge on the Colorado River using indices of two large scale climate forcings: Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO), which are known to modulate the Colorado River Basin (CRB) hydrology at multidecadal time scales. Skill in stochastic simulation of multidecadal projections of flow using this approach is demonstrated.

The Global Streamflow Indices and Metadata archive (G-SIM): A compilation of global streamflow time series indices and meta-data

NASA Astrophysics Data System (ADS)

Do, Hong; Gudmundsson, Lukas; Leonard, Michael; Westra, Seth; Senerivatne, Sonia

2017-04-01

In-situ observations of daily streamflow with global coverage are a crucial asset for understanding large-scale freshwater resources which are an essential component of the Earth system and a prerequisite for societal development. Here we present the Global Streamflow Indices and Metadata archive (G-SIM), a collection indices derived from more than 20,000 daily streamflow time series across the globe. These indices are designed to support global assessments of change in wet and dry extremes, and have been compiled from 12 free-to-access online databases (seven national databases and five international collections). The G-SIM archive also includes significant metadata to help support detailed understanding of streamflow dynamics, with the inclusion of drainage area shapefile and many essential catchment properties such as land cover type, soil and topographic characteristics. The automated procedure in data handling and quality control of the project makes G-SIM a reproducible, extendible archive and can be utilised for many purposes in large-scale hydrology. Some potential applications include the identification of observational trends in hydrological extremes, the assessment of climate change impacts on streamflow regimes, and the validation of global hydrological models.

Streamflow variability over the 1881–2011 period in northern Quebec: comparison of hydrological reconstructions based on tree rings and geopotential height field reanalysis

DOE PAGES

Brigode, Pierre; Brissette, Francois; Nicault, Antoine; ...

2016-09-06

Over the last decades, different methods have been used by hydrologists to extend observed hydro-climatic time series, based on other data sources, such as tree rings or sedimentological datasets. For example, tree ring multi-proxies have been studied for the Caniapiscau Reservoir in northern Québec (Canada), leading to the reconstruction of flow time series for the last 150 years. In this paper, we applied a new hydro-climatic reconstruction method on the Caniapiscau Reservoir and compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment and study the natural streamflow variability over themore » 1881–2011 period in that region. This new reconstruction is based not on natural proxies but on a historical reanalysis of global geopotential height fields, and aims firstly to produce daily climatic time series, which are then used as inputs to a rainfall–runoff model in order to obtain daily streamflow time series. The performances of the hydro-climatic reconstruction were quantified over the observed period, and showed good performances, in terms of both monthly regimes and interannual variability. The streamflow reconstructions were then compared to two different reconstructions performed on the same catchment by using tree ring data series, one being focused on mean annual flows and the other on spring floods. In terms of mean annual flows, the interannual variability in the reconstructed flows was similar (except for the 1930–1940 decade), with noteworthy changes seen in wetter and drier years. For spring floods, the reconstructed interannual variabilities were quite similar for the 1955–2011 period, but strongly different between 1880 and 1940. Here, the results emphasize the need to apply different reconstruction methods on the same catchments. Indeed, comparisons such as those above highlight potential differences between available reconstructions and, finally, allow a retrospective analysis of the proposed reconstructions of past hydro-climatological variabilities.« less

Streamflow variability over the 1881–2011 period in northern Quebec: comparison of hydrological reconstructions based on tree rings and geopotential height field reanalysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brigode, Pierre; Brissette, Francois; Nicault, Antoine

Over the last decades, different methods have been used by hydrologists to extend observed hydro-climatic time series, based on other data sources, such as tree rings or sedimentological datasets. For example, tree ring multi-proxies have been studied for the Caniapiscau Reservoir in northern Québec (Canada), leading to the reconstruction of flow time series for the last 150 years. In this paper, we applied a new hydro-climatic reconstruction method on the Caniapiscau Reservoir and compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment and study the natural streamflow variability over themore » 1881–2011 period in that region. This new reconstruction is based not on natural proxies but on a historical reanalysis of global geopotential height fields, and aims firstly to produce daily climatic time series, which are then used as inputs to a rainfall–runoff model in order to obtain daily streamflow time series. The performances of the hydro-climatic reconstruction were quantified over the observed period, and showed good performances, in terms of both monthly regimes and interannual variability. The streamflow reconstructions were then compared to two different reconstructions performed on the same catchment by using tree ring data series, one being focused on mean annual flows and the other on spring floods. In terms of mean annual flows, the interannual variability in the reconstructed flows was similar (except for the 1930–1940 decade), with noteworthy changes seen in wetter and drier years. For spring floods, the reconstructed interannual variabilities were quite similar for the 1955–2011 period, but strongly different between 1880 and 1940. Here, the results emphasize the need to apply different reconstruction methods on the same catchments. Indeed, comparisons such as those above highlight potential differences between available reconstructions and, finally, allow a retrospective analysis of the proposed reconstructions of past hydro-climatological variabilities.« less

Propagation of stage measurement uncertainties to streamflow time series

NASA Astrophysics Data System (ADS)

Horner, Ivan; Le Coz, Jérôme; Renard, Benjamin; Branger, Flora; McMillan, Hilary

2016-04-01

Streamflow uncertainties due to stage measurements errors are generally overlooked in the promising probabilistic approaches that have emerged in the last decade. We introduce an original error model for propagating stage uncertainties through a stage-discharge rating curve within a Bayesian probabilistic framework. The method takes into account both rating curve (parametric errors and structural errors) and stage uncertainty (systematic and non-systematic errors). Practical ways to estimate the different types of stage errors are also presented: (1) non-systematic errors due to instrument resolution and precision and non-stationary waves and (2) systematic errors due to gauge calibration against the staff gauge. The method is illustrated at a site where the rating-curve-derived streamflow can be compared with an accurate streamflow reference. The agreement between the two time series is overall satisfying. Moreover, the quantification of uncertainty is also satisfying since the streamflow reference is compatible with the streamflow uncertainty intervals derived from the rating curve and the stage uncertainties. Illustrations from other sites are also presented. Results are much contrasted depending on the site features. In some cases, streamflow uncertainty is mainly due to stage measurement errors. The results also show the importance of discriminating systematic and non-systematic stage errors, especially for long term flow averages. Perspectives for improving and validating the streamflow uncertainty estimates are eventually discussed.

waterData--An R package for retrieval, analysis, and anomaly calculation of daily hydrologic time series data, version 1.0

USGS Publications Warehouse

Ryberg, Karen R.; Vecchia, Aldo V.

2012-01-01

Hydrologic time series data and associated anomalies (multiple components of the original time series representing variability at longer-term and shorter-term time scales) are useful for modeling trends in hydrologic variables, such as streamflow, and for modeling water-quality constituents. An R package, called waterData, has been developed for importing daily hydrologic time series data from U.S. Geological Survey streamgages into the R programming environment. In addition to streamflow, data retrieval may include gage height and continuous physical property data, such as specific conductance, pH, water temperature, turbidity, and dissolved oxygen. The package allows for importing daily hydrologic data into R, plotting the data, fixing common data problems, summarizing the data, and the calculation and graphical presentation of anomalies.

Scale effects on information theory-based measures applied to streamflow patterns in two rural watersheds

NASA Astrophysics Data System (ADS)

Pan, Feng; Pachepsky, Yakov A.; Guber, Andrey K.; McPherson, Brian J.; Hill, Robert L.

2012-01-01

SummaryUnderstanding streamflow patterns in space and time is important for improving flood and drought forecasting, water resources management, and predictions of ecological changes. Objectives of this work include (a) to characterize the spatial and temporal patterns of streamflow using information theory-based measures at two thoroughly-monitored agricultural watersheds located in different hydroclimatic zones with similar land use, and (b) to elucidate and quantify temporal and spatial scale effects on those measures. We selected two USDA experimental watersheds to serve as case study examples, including the Little River experimental watershed (LREW) in Tifton, Georgia and the Sleepers River experimental watershed (SREW) in North Danville, Vermont. Both watersheds possess several nested sub-watersheds and more than 30 years of continuous data records of precipitation and streamflow. Information content measures (metric entropy and mean information gain) and complexity measures (effective measure complexity and fluctuation complexity) were computed based on the binary encoding of 5-year streamflow and precipitation time series data. We quantified patterns of streamflow using probabilities of joint or sequential appearances of the binary symbol sequences. Results of our analysis illustrate that information content measures of streamflow time series are much smaller than those for precipitation data, and the streamflow data also exhibit higher complexity, suggesting that the watersheds effectively act as filters of the precipitation information that leads to the observed additional complexity in streamflow measures. Correlation coefficients between the information-theory-based measures and time intervals are close to 0.9, demonstrating the significance of temporal scale effects on streamflow patterns. Moderate spatial scale effects on streamflow patterns are observed with absolute values of correlation coefficients between the measures and sub-watershed area varying from 0.2 to 0.6 in the two watersheds. We conclude that temporal effects must be evaluated and accounted for when the information theory-based methods are used for performance evaluation and comparison of hydrological models.

Wavelet-linear genetic programming: A new approach for modeling monthly streamflow

NASA Astrophysics Data System (ADS)

Ravansalar, Masoud; Rajaee, Taher; Kisi, Ozgur

2017-06-01

The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predict the monthly streamflow (Q) in two gauging stations, Pataveh and Shahmokhtar, on the Beshar River at the Yasuj, Iran were used in this study. In the proposed WLGP model, the wavelet analysis was linked to the LGP model where the original time series of streamflow were decomposed into the sub-time series comprising wavelet coefficients. The results were compared with the single LGP, artificial neural network (ANN), a hybrid wavelet-ANN (WANN) and Multi Linear Regression (MLR) models. The comparisons were done by some of the commonly utilized relevant physical statistics. The Nash coefficients (E) were found as 0.877 and 0.817 for the WLGP model, for the Pataveh and Shahmokhtar stations, respectively. The comparison of the results showed that the WLGP model could significantly increase the streamflow prediction accuracy in both stations. Since, the results demonstrate a closer approximation of the peak streamflow values by the WLGP model, this model could be utilized for the simulation of cumulative streamflow data prediction in one month ahead.

Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications.

PubMed

Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan

2015-05-01

Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Analysis of the precipitation and streamflow extremes in Northern Italy using high resolution reanalysis dataset Express-Hydro

NASA Astrophysics Data System (ADS)

Silvestro, Francesco; Parodi, Antonio; Campo, Lorenzo

2017-04-01

The characterization of the hydrometeorological extremes, both in terms of rainfall and streamflow, in a given region plays a key role in the environmental monitoring provided by the flood alert services. In last years meteorological simulations (both near real-time and historical reanalysis) were available at increasing spatial and temporal resolutions, making possible long-period hydrological reanalysis in which the meteo dataset is used as input in distributed hydrological models. In this work, a very high resolution meteorological reanalysis dataset, namely Express-Hydro (CIMA, ISAC-CNR, GAUSS Special Project PR45DE), was employed as input in the hydrological model Continuum in order to produce long time series of streamflows in the Liguria territory, located in the Northern part of Italy. The original dataset covers the whole Europe territory in the 1979-2008 period, at 4 km of spatial resolution and 3 hours of time resolution. Analyses in terms of comparison between the rainfall estimated by the dataset and the observations (available from the local raingauges network) were carried out, and a bias correction was also performed in order to better match the observed climatology. An extreme analysis was eventually carried on the streamflows time series obtained by the simulations, by comparing them with the results of the same hydrological model fed with the observed time series of rainfall. The results of the analysis are shown and discussed.

WaterWatch - Maps, graphs, and tables of current, recent, and past streamflow conditions

USGS Publications Warehouse

Jian, Xiaodong; Wolock, David; Lins, Harry F.

2008-01-01

WaterWatch (http://water.usgs.gov/waterwatch/) is a U.S. Geological Survey (USGS) World Wide Web site that dis­plays maps, graphs, and tables describing real-time, recent, and past streamflow conditions for the United States. The real-time information generally is updated on an hourly basis. WaterWatch provides streamgage-based maps that show the location of more than 3,000 long-term (30 years or more) USGS streamgages; use colors to represent streamflow conditions compared to historical streamflow; feature a point-and-click interface allowing users to retrieve graphs of stream stage (water elevation) and flow; and highlight locations where extreme hydrologic events, such as floods and droughts, are occurring.The streamgage-based maps show streamflow conditions for real-time, average daily, and 7-day average streamflow. The real-time streamflow maps highlight flood and high flow conditions. The 7-day average streamflow maps highlight below-normal and drought conditions.WaterWatch also provides hydrologic unit code (HUC) maps. HUC-based maps are derived from the streamgage-based maps and illustrate streamflow conditions in hydrologic regions. These maps show average streamflow conditions for 1-, 7-, 14-, and 28-day periods, and for monthly average streamflow; highlight regions of low flow or hydrologic drought; and provide historical runoff and streamflow conditions beginning in 1901.WaterWatch summarizes streamflow conditions in a region (state or hydrologic unit) in terms of the long-term typical condition at streamgages in the region. Summary tables are provided along with time-series plots that depict variations through time. WaterWatch also includes tables of current streamflow information and locations of flooding.

Evaluation of meteorological drought indices for streamflow modeling

NASA Astrophysics Data System (ADS)

Haslinger, Klaus; Koffler, Daniel; Blöschl, Günter; Parajka, Juraj; Schöner, Wolfgang; Laaha, Gregor

2013-04-01

In this paper we present a comprehensive analysis which aims to link various meteorological drought indices to streamflow data in Austria and Central Europe. The motivation arises from the fact that discharge time series are usually shorter (beginning in the middle of the 20th century) than meteorological time series. In the European Greater Alpine Region we are fortunate of having a gridded dataset for temperature and solid/liquid precipitation on a monthly time scale that spans from 1801 to 2003 - the HISTALP database. If there is a link between meteorological drought indices and streamflow, a reconstruction of streamflow, with emphasis on low flows, will be possible for the last 200 years. As meteorological drought indices the self-calibrating Palmer Drought Severity Index (scPDSI), the Standardized Precipitation Index (SPI) on various time scales as well as the moisture departure value d from the soil moisture modeling procedure of the scPDSI are used. The analysis focuses on three aspects, (i) temporal co-evolution of meteorological drought and streamflow indices, (ii) their at-site correlation at gauges, and (iii) their regional correlation structure depending on different climate and catchment conditions. The whole analysis is stratified by seasons, what allows us to explore the strength of the link for the dominant low flow generating process. In order to show a connection between these indices and streamflow data the drought event of 2003 serves as a reference. We will show the temporal evolution of the drought indices parallel to streamflow indices like MQ, Q95 and MAM(7) for the period from summer 2002, which encompasses a major flood event in the northern parts of Austria, to fall 2003 when the streamflow drought was most severe. This is carried out for different regions in Austria, representing different climatic and soil-specific characteristics. To quantify the link between drought indices and streamflow indices for the whole time series from 1801-2003, rank correlations are calculated, stratified by three different approaches. First, as mentioned above, a regional assessment is carried out. Second, the correlations are calculated separately for seasons (DJF, MAM, JJA, and SON). Third, different quantiles of the streamflow-data, ranging from Q50 to Q95, will be correlated with the drought indices. The results show that there is definitely a strong connection between the MQ and the scPDSI in one target region in the Northwest of Austria. The results are encouraging for further attempts to reconstruct extreme low flow events from meteorological data only. A statistical model for linking meteorological drought indices with streamflow under dry conditions is currently under development and results will be presented in the near future.

Cross-entropy clustering framework for catchment classification

NASA Astrophysics Data System (ADS)

Tongal, Hakan; Sivakumar, Bellie

2017-09-01

There is an increasing interest in catchment classification and regionalization in hydrology, as they are useful for identification of appropriate model complexity and transfer of information from gauged catchments to ungauged ones, among others. This study introduces a nonlinear cross-entropy clustering (CEC) method for classification of catchments. The method specifically considers embedding dimension (m), sample entropy (SampEn), and coefficient of variation (CV) to represent dimensionality, complexity, and variability of the time series, respectively. The method is applied to daily streamflow time series from 217 gauging stations across Australia. The results suggest that a combination of linear and nonlinear parameters (i.e. m, SampEn, and CV), representing different aspects of the underlying dynamics of streamflows, could be useful for determining distinct patterns of flow generation mechanisms within a nonlinear clustering framework. For the 217 streamflow time series, nine hydrologically homogeneous clusters that have distinct patterns of flow regime characteristics and specific dominant hydrological attributes with different climatic features are obtained. Comparison of the results with those obtained using the widely employed k-means clustering method (which results in five clusters, with the loss of some information about the features of the clusters) suggests the superiority of the cross-entropy clustering method. The outcomes from this study provide a useful guideline for employing the nonlinear dynamic approaches based on hydrologic signatures and for gaining an improved understanding of streamflow variability at a large scale.

Quantifying new water fractions and water age distributions using ensemble hydrograph separation

NASA Astrophysics Data System (ADS)

Kirchner, James

2017-04-01

Catchment transit times are important controls on contaminant transport, weathering rates, and runoff chemistry. Recent theoretical studies have shown that catchment transit time distributions are nonstationary, reflecting the temporal variability in precipitation forcing, the structural heterogeneity of catchments themselves, and the nonlinearity of the mechanisms controlling storage and transport in the subsurface. The challenge of empirically estimating these nonstationary transit time distributions in real-world catchments, however, has only begun to be explored. Long, high-frequency tracer time series are now becoming available, creating new opportunities to study how rainfall becomes streamflow on timescales of minutes to days following the onset of precipitation. Here I show that the conventional formula used for hydrograph separation can be converted into an equivalent linear regression equation that quantifies the fraction of current rainfall in streamflow across ensembles of precipitation events. These ensembles can be selected to represent different discharge ranges, different precipitation intensities, or different levels of antecedent moisture, thus quantifying how the fraction of "new water" in streamflow varies with forcings such as these. I further show how this approach can be generalized to empirically determine the contributions of precipitation inputs to streamflow across a range of time lags. In this way the short-term tail of the transit time distribution can be directly quantified for an ensemble of precipitation events. Benchmark testing with a simple, nonlinear, nonstationary catchment model demonstrates that this approach quantitatively measures the short tail of the transit time distribution for a wide range of catchment response characteristics. In combination with reactive tracer time series, this approach can potentially be extended to measure short-term chemical reaction rates at the catchment scale. High-frequency tracer time series from several experimental catchments will be used to demonstrate the utility of the new approach outlined here.

Multidecadal change in streamflow associated with anthropogenic disturbances in the tropical Andes

NASA Astrophysics Data System (ADS)

Molina, A.; Vanacker, V.; Brisson, E.; Mora, D.; Balthazar, V.

2015-10-01

Andean headwater catchments are an important source of freshwater for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes in these catchments. In this paper, we assess change in streamflow based on long time series of hydrometeorological data (1974-2008) and land cover reconstructions (1963-2009) in the Pangor catchment (282 km2) located in the tropical Andes. Three main land cover change trajectories can be distinguished during the period 1963-2009: (1) expansion of agricultural land by an area equal to 14 % of the catchment area (or 39 km2) in 46 years' time, (2) deforestation of native forests by 11 % (or -31 km2) corresponding to a mean rate of 67 ha yr-1, and (3) afforestation with exotic species in recent years by about 5 % (or 15 km2). Over the time period 1963-2009, about 50 % of the 64 km2 of native forests was cleared and converted to agricultural land. Given the strong temporal variability of precipitation and streamflow data related to El Niño-Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow, which exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term change in precipitation but very likely result from anthropogenic disturbances associated with land cover change.

Sensitivity of monthly streamflow forecasts to the quality of rainfall forcing: When do dynamical climate forecasts outperform the Ensemble Streamflow Prediction (ESP) method?

NASA Astrophysics Data System (ADS)

Tanguy, M.; Prudhomme, C.; Harrigan, S.; Smith, K. A.; Parry, S.

2017-12-01

Forecasting hydrological extremes is challenging, especially at lead times over 1 month for catchments with limited hydrological memory and variable climates. One simple way to derive monthly or seasonal hydrological forecasts is to use historical climate data to drive hydrological models using the Ensemble Streamflow Prediction (ESP) method. This gives a range of possible future streamflow given known initial hydrologic conditions alone. The degree of skill of ESP depends highly on the forecast initialisation month and catchment type. Using dynamic rainfall forecasts as driving data instead of historical data could potentially improve streamflow predictions. A lot of effort is being invested within the meteorological community to improve these forecasts. However, while recent progress shows promise (e.g. NAO in winter), the skill of these forecasts at monthly to seasonal timescales is generally still limited, and the extent to which they might lead to improved hydrological forecasts is an area of active research. Additionally, these meteorological forecasts are currently being produced at 1 month or seasonal time-steps in the UK, whereas hydrological models require forcings at daily or sub-daily time-steps. Keeping in mind these limitations of available rainfall forecasts, the objectives of this study are to find out (i) how accurate monthly dynamical rainfall forecasts need to be to outperform ESP, and (ii) how the method used to disaggregate monthly rainfall forecasts into daily rainfall time series affects results. For the first objective, synthetic rainfall time series were created by increasingly degrading observed data (proxy for a `perfect forecast') from 0 % to +/-50 % error. For the second objective, three different methods were used to disaggregate monthly rainfall data into daily time series. These were used to force a simple lumped hydrological model (GR4J) to generate streamflow predictions at a one-month lead time for over 300 catchments representative of the range of UK's hydro-climatic conditions. These forecasts were then benchmarked against the traditional ESP method. It is hoped that the results of this work will help the meteorological community to identify where to focus their efforts in order to increase the usefulness of their forecasts within hydrological forecasting systems.

Computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data

USGS Publications Warehouse

Rasmussen, Patrick P.; Gray, John R.; Glysson, G. Doug; Ziegler, Andrew C.

2010-01-01

Over the last decade, use of a method for computing suspended-sediment concentration and loads using turbidity sensors—primarily nephelometry, but also optical backscatter—has proliferated. Because an in- itu turbidity sensor is capa le of measuring turbidity instantaneously, a turbidity time series can be recorded and related directly to time-varying suspended-sediment concentrations. Depending on the suspended-sediment characteristics of the measurement site, this method can be more reliable and, in many cases, a more accurate means for computing suspended-sediment concentrations and loads than traditional U.S. Geological Survey computational methods. Guidelines and procedures for estimating time s ries of suspended-sediment concentration and loading as a function of turbidity and streamflow data have been published in a U.S. Geological Survey Techniques and Methods Report, Book 3, Chapter C4. This paper is a summary of these guidelines and discusses some of the concepts, s atistical procedures, and techniques used to maintain a multiyear suspended sediment time series.

Changing characteristics of streamflow in the Midwest and its relation to oceanic-atmospheric oscillations

NASA Astrophysics Data System (ADS)

Thakur, B.; Pathak, P.; Kalra, A.; Ahmad, S.

2016-12-01

The identification of primary drivers of streamflow may prove beneficial in forecasting streamflow in the Midwestern U.S. In the past researches, streamflow in the region have been strongly correlated with El Niño-Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO). The present study takes in to account the pre-defined Pacific and Atlantic Ocean regions (e.g., ENSO, PDO, AMO) along with new regions with an intent to identify new significantly correlated regions. This study assesses the interrelationship between sea surface temperatures (SST) anomalies in the Pacific and Atlantic Ocean and seasonal streamflow in the Midwestern U.S. Average Pacific and Atlantic Ocean SST anomalies, were calculated for 2 different 3 month series: September-November and December-February so as to create a lead time varying from 3 to 9 months. Streamflow were averaged for three seasons: spring (April-June), spring-summer (April-August) and summer (June-August). The correlation between streamflow and SST is analyzed using singular value decomposition for a period of 1960-2013. The result of the study showed several regions-other than the known Pacific and Atlantic Ocean regions- that were significantly correlated with streamflow stations. Higher correlation between the climate indices and streamflow were observed as the lead time decreased. The identification of the associations between SST and streamflow and significant SST regions in the Pacific and Atlantic Ocean may enhance the skill of streamflow predictability and water management in the region.

Simulated hydrologic response to climate change during the 21st century in New Hampshire

USGS Publications Warehouse

Bjerklie, David M.; Sturtevant, Luke P.

2018-01-24

The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services and the Department of Health and Human Services, has developed a hydrologic model to assess the effects of short- and long-term climate change on hydrology in New Hampshire. This report documents the model and datasets developed by using the model to predict how climate change will affect the hydrologic cycle and provide data that can be used by State and local agencies to identify locations that are vulnerable to the effects of climate change in areas across New Hampshire. Future hydrologic projections were developed from the output of five general circulation models for two future climate scenarios. The scenarios are based on projected future greenhouse gas emissions and estimates of land-use and land-cover change within a projected global economic framework. An evaluation of the possible effect of projected future temperature on modeling of evapotranspiration is summarized to address concerns regarding the implications of the future climate on model parameters that are based on climate variables. The results of the model simulations are hydrologic projections indicating increasing streamflow across the State with large increases in streamflow during winter and early spring and general decreases during late spring and summer. Wide spatial variability in changes to groundwater recharge is projected, with general decreases in the Connecticut River Valley and at high elevations in the northern part of the State and general increases in coastal and lowland areas of the State. In general, total winter snowfall is projected to decrease across the State, but there is a possibility of increasing snow in some locations, particularly during November, February, and March. The simulated future changes in recharge and snowfall vary by watershed across the State. This means that each area of the State could experience very different changes, depending on topography or other factors. Therefore, planning for infrastructure and public safety needs to be flexible in order to address the range of possible outcomes indicated by the various model simulations. The absolute magnitude and timing of the daily streamflows, especially the larger floods, are not considered to be reliably simulated compared to changes in frequency and duration of daily streamflows and changes in accumulated monthly and seasonal streamflow volumes. Simulated current and future streamflow, groundwater recharge, and snowfall datasets include simulated data derived from the five general circulation models used in this study for a current reference time period and two future time periods. Average monthly streamflow time series datasets are provided for 27 streamgages in New Hampshire. Fourteen of the 27 streamgages associated with daily streamflow time series showed a good calibration. Average monthly groundwater recharge and snowfall time series for the same reference time period and two future time periods are also provided for each of the 467 hydrologic response units that compose the model.

Statistical downscaling for winter streamflow in Douro River

NASA Astrophysics Data System (ADS)

Jesús Esteban Parra, María; Hidalgo Muñoz, José Manuel; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz Fortis, Sonia; Castro Díez, Yolanda

2015-04-01

In this paper we have obtained climate change projections for winter flow of the Douro River in the period 2071-2100 by applying the technique of Partial Regression and various General Circulation Models of CMIP5. The streamflow data base used has been provided by the Center for Studies and Experimentation of Public Works, CEDEX. Series from gauing stations and reservoirs with less than 10% of missing data (filled by regression with well correlated neighboring stations) have been considered. The homogeneity of these series has been evaluated through the Pettit test and degree of human alteration by the Common Area Index. The application of these criteria led to the selection of 42 streamflow time series homogeneously distributed over the basin, covering the period 1951-2011. For these streamflow data, winter seasonal values were obtained by averaging the monthly values from January to March. Statistical downscaling models for the streamflow have been fitted using as predictors the main atmospheric modes of variability over the North Atlantic region. These modes have been obtained using winter sea level pressure data of the NCEP reanalysis, averaged for the months from December to February. Period 1951-1995 was used for calibration, while 1996-2011 period was used in validating the adjusted models. In general, these models are able to reproduce about 70% of the variability of the winter streamflow of the Douro River. Finally, the obtained statistical models have been applied to obtain projections for 2071-2100 period, using outputs from different CMIP5 models under the RPC8.5 scenario. The results for the end of the century show modest declines of winter streamflow in this river for most of the models. Keywords: Statistical downscaling, streamflow, Douro River, climate change. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Temporal rainfall estimation using input data reduction and model inversion

NASA Astrophysics Data System (ADS)

Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

2016-12-01

Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a demonstration of equifinality. The use of a likelihood function that considers both rainfall and streamflow error combined with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

Streamflow characterization using functional data analysis of the Potomac River

NASA Astrophysics Data System (ADS)

Zelmanow, A.; Maslova, I.; Ticlavilca, A. M.; McKee, M.

2013-12-01

Flooding and droughts are extreme hydrological events that affect the United States economically and socially. The severity and unpredictability of flooding has caused billions of dollars in damage and the loss of lives in the eastern United States. In this context, there is an urgent need to build a firm scientific basis for adaptation by developing and applying new modeling techniques for accurate streamflow characterization and reliable hydrological forecasting. The goal of this analysis is to use numerical streamflow characteristics in order to classify, model, and estimate the likelihood of extreme events in the eastern United States, mainly the Potomac River. Functional data analysis techniques are used to study yearly streamflow patterns, with the extreme streamflow events characterized via functional principal component analysis. These methods are merged with more classical techniques such as cluster analysis, classification analysis, and time series modeling. The developed functional data analysis approach is used to model continuous streamflow hydrographs. The forecasting potential of this technique is explored by incorporating climate factors to produce a yearly streamflow outlook.

Climatic change projections for winter streamflow in Guadalquivir river

NASA Astrophysics Data System (ADS)

Jesús Esteban Parra, María; Hidalgo Muñoz, José Manuel; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz Fortis, Sonia; Castro Díez, Yolanda

2015-04-01

In this work we have obtained climate change projections for winter streamflow of the Guadalquivir River in the period 2071-2100 using the Principal Component Regression (PCR) method. The streamflow data base used has been provided by the Center for Studies and Experimentation of Public Works, CEDEX. Series from gauging stations and reservoirs with less than 10% of missing data (filled by regression with well correlated neighboring stations) have been considered. The homogeneity of these series has been evaluated through the Pettit test and degree of human alteration by the Common Area Index. The application of these criteria led to the selection of 13 streamflow time series homogeneously distributed over the basin, covering the period 1952-2011. For this streamflow data, winter seasonal values were obtained by averaging the monthly values from January to March. The PCR method has been applied using the Principal Components of the mean anomalies of sea level pressure (SLP) in winter (December to February averaged) as predictors of streamflow for the development of a downscaled statistical model. The SLP database is the NCEP reanalysis covering the North Atlantic region, and the calibration and validation periods used for fitting and evaluating the ability of the model are 1952-1992 and 1993-2011, respectively. In general, using four Principal Components, regression models are able to explain up to 70% of the variance of the streamflow data. Finally, the statistical model obtained for the observational data was applied to the SLP data for the period 2071-2100, using the outputs of different GCMs of the CMIP5 under the RPC8.5 scenario. The results found for the end of the century show no significant changes or moderate decrease in the streamflow of this river for most GCMs in winter, but for some of them the decrease is very strong. Keywords: Statistical downscaling, streamflow, Guadalquivir River, climate change. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Conjunction of wavelet transform and SOM-mutual information data pre-processing approach for AI-based Multi-Station nitrate modeling of watersheds

NASA Astrophysics Data System (ADS)

Nourani, Vahid; Andalib, Gholamreza; Dąbrowska, Dominika

2017-05-01

Accurate nitrate load predictions can elevate decision management of water quality of watersheds which affects to environment and drinking water. In this paper, two scenarios were considered for Multi-Station (MS) nitrate load modeling of the Little River watershed. In the first scenario, Markovian characteristics of streamflow-nitrate time series were proposed for the MS modeling. For this purpose, feature extraction criterion of Mutual Information (MI) was employed for input selection of artificial intelligence models (Feed Forward Neural Network, FFNN and least square support vector machine). In the second scenario for considering seasonality-based characteristics of the time series, wavelet transform was used to extract multi-scale features of streamflow-nitrate time series of the watershed's sub-basins to model MS nitrate loads. Self-Organizing Map (SOM) clustering technique which finds homogeneous sub-series clusters was also linked to MI for proper cluster agent choice to be imposed into the models for predicting the nitrate loads of the watershed's sub-basins. The proposed MS method not only considers the prediction of the outlet nitrate but also covers predictions of interior sub-basins nitrate load values. The results indicated that the proposed FFNN model coupled with the SOM-MI improved the performance of MS nitrate predictions compared to the Markovian-based models up to 39%. Overall, accurate selection of dominant inputs which consider seasonality-based characteristics of streamflow-nitrate process could enhance the efficiency of nitrate load predictions.

Long-range properties and data validity for hydrogeological time series: The case of the Paglia river

NASA Astrophysics Data System (ADS)

Ausloos, Marcel; Cerqueti, Roy; Lupi, Claudio

2017-03-01

This paper explores a large collection of about 377,000 observations, spanning more than 20 years with a frequency of 30 min, of the streamflow of the Paglia river, in central Italy. We analyze the long-term persistence properties of the series by computing the Hurst exponent, not only in its original form but also under an evolutionary point of view by analyzing the Hurst exponents over a rolling windows basis. The methodological tool adopted for the persistence is the detrended fluctuation analysis (DFA), which is classically known as suitable for our purpose. As an ancillary exploration, we implement a control on the data validity by assessing if the data exhibit the regularity stated by Benford's law. Results are interesting under different viewpoints. First, we show that the Paglia river streamflow exhibits periodicities which broadly suggest the existence of some common behavior with El Niño and the North Atlantic Oscillations: this specifically points to a (not necessarily direct) effect of these oceanic phenomena on the hydrogeological equilibria of very far geographical zones: however, such an hypothesis needs further analyses to be validated. Second, the series of streamflows shows an antipersistent behavior. Third, data are not consistent with Benford's law: this suggests that the measurement criteria should be opportunely revised. Fourth, the streamflow distribution is well approximated by a discrete generalized Beta distribution: this is well in accordance with the measured streamflows being the outcome of a complex system.

A Linear Dynamical Systems Approach to Streamflow Reconstruction Reveals History of Regime Shifts in Northern Thailand

NASA Astrophysics Data System (ADS)

Nguyen, Hung T. T.; Galelli, Stefano

2018-03-01

Catchment dynamics is not often modeled in streamflow reconstruction studies; yet, the streamflow generation process depends on both catchment state and climatic inputs. To explicitly account for this interaction, we contribute a linear dynamic model, in which streamflow is a function of both catchment state (i.e., wet/dry) and paleoclimatic proxies. The model is learned using a novel variant of the Expectation-Maximization algorithm, and it is used with a paleo drought record—the Monsoon Asia Drought Atlas—to reconstruct 406 years of streamflow for the Ping River (northern Thailand). Results for the instrumental period show that the dynamic model has higher accuracy than conventional linear regression; all performance scores improve by 45-497%. Furthermore, the reconstructed trajectory of the state variable provides valuable insights about the catchment history—e.g., regime-like behavior—thereby complementing the information contained in the reconstructed streamflow time series. The proposed technique can replace linear regression, since it only requires information on streamflow and climatic proxies (e.g., tree-rings, drought indices); furthermore, it is capable of readily generating stochastic streamflow replicates. With a marginal increase in computational requirements, the dynamic model brings more desirable features and value to streamflow reconstructions.

Investigation of the complexity of streamflow fluctuations in a large heterogeneous lake catchment in China

NASA Astrophysics Data System (ADS)

Ye, Xuchun; Xu, Chong-Yu; Li, Xianghu; Zhang, Qi

2018-05-01

The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h( q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h( q). However, the relationship between the width of the singularity spectrum (Δ α) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.

Detecting the hydrological impacts of forest cover change in tropical mountain areas: need for detrending time series of rainfall and streamflow data.

NASA Astrophysics Data System (ADS)

Molina, A.; Vanacker, V.; Brisson, E.; Balthazar, V.

2012-04-01

Interactions between human activities and the physical environment have increasingly transformed the hydrological functioning of Andean ecosystems. In these human-modified landscapes, land use/-cover change may have a profound effect on riverine water and sediment fluxes. The hydrological impacts of land use/-cover change are diverse, as changes in vegetation affect the various components of the hydrological cycle including evapotranspiration, infiltration and surface runoff. Quantitative data for tropical mountain regions are scarce, as few long time series on rainfall, water discharge and land use are available. Furthermore, time series of rainfall and streamflow data in tropical mountains are often highly influenced by large inter- and intra-annual variability. In this paper, we analyse the hydrological response to complex forest cover change for a catchment of 280 km2 located in the Ecuadorian Andes. Forest cover change in the Pangor catchment was reconstructed based on airphotos (1963, 1977), LANDSAT TM (1991) and ETM+ data (2001, 2009). From 1963, natural vegetation was converted to agricultural land and pine plantations: forests decreased by a factor 2, and paramo decreased by 20 km2 between 1963 and 2009. For this catchment, there exists an exceptionally long record of rainfall and streamflow data that dates back from the '70s till now, but large variability in hydrometeorological data exists that is partly related to ENSO events. Given the nonstationary and nonlinear character of the ENSO-related changes in rainfall, we used the Hilbert-Huang transformation to detrend the time series of the river flow data from inter- and intra-annual fluctuations in rainfall. After applying adaptive data analysis based on empirical model decomposition techniques, it becomes apparent that the long-term trend in streamflow is different from the long-term trend in rainfall data. While the streamflow data show a long-term decrease in monthly flow, the rainfall data have a trend of increasing and then decreasing precipitation amounts. These results suggest that the land use changes had an important impact on the total water yield of the catchment. Interestingly, the effect of reforestation in the upper part of the catchment with its associated decrease in water yield seems to be dominant over the effect of deforestation in the lower part of the basin.

Quantifying uncertainties in streamflow predictions through signature based inference of hydrological model parameters

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Reichert, Peter; Kavetski, Dmitri; Albert, Calro

2016-04-01

The calibration of hydrological models based on signatures (e.g. Flow Duration Curves - FDCs) is often advocated as an alternative to model calibration based on the full time series of system responses (e.g. hydrographs). Signature based calibration is motivated by various arguments. From a conceptual perspective, calibration on signatures is a way to filter out errors that are difficult to represent when calibrating on the full time series. Such errors may for example occur when observed and simulated hydrographs are shifted, either on the "time" axis (i.e. left or right), or on the "streamflow" axis (i.e. above or below). These shifts may be due to errors in the precipitation input (time or amount), and if not properly accounted in the likelihood function, may cause biased parameter estimates (e.g. estimated model parameters that do not reproduce the recession characteristics of a hydrograph). From a practical perspective, signature based calibration is seen as a possible solution for making predictions in ungauged basins. Where streamflow data are not available, it may in fact be possible to reliably estimate streamflow signatures. Previous research has for example shown how FDCs can be reliably estimated at ungauged locations based on climatic and physiographic influence factors. Typically, the goal of signature based calibration is not the prediction of the signatures themselves, but the prediction of the system responses. Ideally, the prediction of system responses should be accompanied by a reliable quantification of the associated uncertainties. Previous approaches for signature based calibration, however, do not allow reliable estimates of streamflow predictive distributions. Here, we illustrate how the Bayesian approach can be employed to obtain reliable streamflow predictive distributions based on signatures. A case study is presented, where a hydrological model is calibrated on FDCs and additional signatures. We propose an approach where the likelihood function for the signatures is derived from the likelihood for streamflow (rather than using an "ad-hoc" likelihood for the signatures as done in previous approaches). This likelihood is not easily tractable analytically and we therefore cannot apply "simple" MCMC methods. This numerical problem is solved using Approximate Bayesian Computation (ABC). Our result indicate that the proposed approach is suitable for producing reliable streamflow predictive distributions based on calibration to signature data. Moreover, our results provide indications on which signatures are more appropriate to represent the information content of the hydrograph.

Analysis of streamflow variability in Alpine catchments at multiple spatial and temporal scales

NASA Astrophysics Data System (ADS)

Pérez Ciria, T.; Chiogna, G.

2017-12-01

Alpine watersheds play a pivotal role in Europe for water provisioning and for hydropower production. In these catchments, temporal fluctuations of river discharge occur at multiple temporal scales due to natural as well as anthropogenic driving forces. In the last decades, modifications of the flow regime have been observed and their origin lies in the complex interplay between construction of dams for hydro power production, changes in water management policies and climatic changes. The alteration of the natural flow has negative impacts on the freshwater biodiversity and threatens the ecosystem integrity of the Alpine region. Therefore, understanding the temporal and spatial variability of river discharge has recently become a particular concern for environmental protection and represents a crucial contribution to achieve sustainable water resources management in the Alps. In this work, time series analysis is conducted for selected gauging stations in the Inn and the Adige catchments, which cover a large part of the central and eastern region of the Alps. We analyze the available time series using the continuous wavelet transform and change-point analyses for determining how and where changes have taken place. Although both catchments belong to different climatic zones of the Greater Alpine Region, streamflow properties share some similar characteristics. The comparison of the collected streamflow time series in the two catchments permits detecting gradients in the hydrological system dynamics that depend on station elevation, longitudinal location in the Alps and catchment area. This work evidences that human activities (e.g., water management practices and flood protection measures, changes in legislation and market regulation) have major impacts on streamflow and should be rigorously considered in hydrological models.

Trends in annual, seasonal, and monthly streamflow characteristics at 227 streamgages in the Missouri River watershed, water years 1960-2011

USGS Publications Warehouse

Norton, Parker A.; Anderson, Mark T.; Stamm, John F.

2014-01-01

The Missouri River and its tributaries are an important resource that serve multiple uses including agriculture, energy, recreation, and municipal water supply. Understanding historical streamflow characteristics provides relevant guidance to adaptive management of these water resources. Streamflow records in the Missouri River watershed were examined for trends in time series of annual, seasonal, and monthly streamflow. A total of 227 streamgages having continuous observational records for water years 1960–2011 were examined. Kendall’s tau nonparametric test was used to determine statistical significance of trends in annual, seasonal, and monthly streamflow. A trend was considered statistically significant for a probability value less than or equal to 0.10 that the Kendall’s tau value equals zero. Significant trends in annual streamflow were indicated for 101 out of a total of 227 streamgages. The Missouri River watershed was divided into six watershed regions and trends within regions were examined. The western and the southern parts of the Missouri River watershed had downward trends in annual streamflow (56 streamgages), whereas the eastern part of the watershed had upward trends in streamflow (45 streamgages). Seasonal and monthly streamflow trends reflected prevailing annual streamflow trends within each watershed region.

Bayesian Models for Streamflow and River Network Reconstruction using Tree Rings

NASA Astrophysics Data System (ADS)

Ravindranath, A.; Devineni, N.

2016-12-01

Water systems face non-stationary, dynamically shifting risks due to shifting societal conditions and systematic long-term variations in climate manifesting as quasi-periodic behavior on multi-decadal time scales. Water systems are thus vulnerable to long periods of wet or dry hydroclimatic conditions. Streamflow is a major component of water systems and a primary means by which water is transported to serve ecosystems' and human needs. Thus, our concern is in understanding streamflow variability. Climate variability and impacts on water resources are crucial factors affecting streamflow, and multi-scale variability increases risk to water sustainability and systems. Dam operations are necessary for collecting water brought by streamflow while maintaining downstream ecological health. Rules governing dam operations are based on streamflow records that are woefully short compared to periods of systematic variation present in the climatic factors driving streamflow variability and non-stationarity. We use hierarchical Bayesian regression methods in order to reconstruct paleo-streamflow records for dams within a basin using paleoclimate proxies (e.g. tree rings) to guide the reconstructions. The riverine flow network for the entire basin is subsequently modeled hierarchically using feeder stream and tributary flows. This is a starting point in analyzing streamflow variability and risks to water systems, and developing a scientifically-informed dynamic risk management framework for formulating dam operations and water policies to best hedge such risks. We will apply this work to the Missouri and Delaware River Basins (DRB). Preliminary results of streamflow reconstructions for eight dams in the upper DRB using standard Gaussian regression with regional tree ring chronologies give streamflow records that now span two to two and a half centuries, and modestly smoothed versions of these reconstructed flows indicate physically-justifiable trends in the time series.

Status, trends, and changes in freshwater inflows to bay systems in the Corpus Christi Bay National Estuary Program study area

USGS Publications Warehouse

Asquith, W.H.; Mosier, J. G.; Bush, P.W.

1997-01-01

The watershed simulation model Hydrologic Simulation Program—Fortran (HSPF) was used to generate simulated flow (runoff) from the 13 watersheds to the six bay systems because adequate gaged streamflow data from which to estimate freshwater inflows are not available; only about 23 percent of the adjacent contributing watershed area is gaged. The model was calibrated for the gaged parts of three watersheds—that is, selected input parameters (meteorologic and hydrologic properties and conditions) that control runoff were adjusted in a series of simulations until an adequate match between model-generated flows and a set (time series) of gaged flows was achieved. The primary model input is rainfall and evaporation data and the model output is a time series of runoff volumes. After calibration, simulations driven by daily rainfall for a 26-year period (1968–93) were done for the 13 watersheds to obtain runoff under current (1983–93), predevelopment (pre-1940 streamflow and pre-urbanization), and future (2010) land-use conditions for estimating freshwater inflows and for comparing runoff under the three land-use conditions; and to obtain time series of runoff from which to estimate time series of freshwater inflows for trend analysis.

Evidence for a physical linkage between galactic cosmic rays and regional climate time series

USGS Publications Warehouse

Perry, C.A.

2007-01-01

The effects of solar variability on regional climate time series were examined using a sequence of physical connections between total solar irradiance (TSI) modulated by galactic cosmic rays (GCRs), and ocean and atmospheric patterns that affect precipitation and streamflow. The solar energy reaching the Earth's surface and its oceans is thought to be controlled through an interaction between TSI and GCRs, which are theorized to ionize the atmosphere and increase cloud formation and its resultant albedo. High (low) GCR flux may promote cloudiness (clear skies) and higher (lower) albedo at the same time that TSI is lowest (highest) in the solar cycle which in turn creates cooler (warmer) ocean temperature anomalies. These anomalies have been shown to affect atmospheric flow patterns and ultimately affect precipitation over the Midwestern United States. This investigation identified a relation among TSI and geomagnetic index aa (GI-AA), and streamflow in the Mississippi River Basin for the period 1878-2004. The GI-AA was used as a proxy for GCRs. The lag time between the solar signal and streamflow in the Mississippi River at St. Louis, Missouri is approximately 34 years. The current drought (1999-2007) in the Mississippi River Basin appears to be caused by a period of lower solar activity that occurred between 1963 and 1977. There appears to be a solar "fingerprint" that can be detected in climatic time series in other regions of the world, with each series having a unique lag time between the solar signal and the hydroclimatic response. A progression of increasing lag times can be spatially linked to the ocean conveyor belt, which may transport the solar signal over a time span of several decades. The lag times for any one region vary slightly and may be linked to the fluctuations in the velocity of the ocean conveyor belt.

Characterizing a Century of Climate and Hydrological Variability of a Mediterranean and Mountainous Watersheds: the Durance River Case-Study

NASA Astrophysics Data System (ADS)

Mathevet, T.; Kuentz, A.; Gailhard, J.; Andreassian, V.

2013-12-01

Improving the understanding of mountain watersheds hydrological variability is a great scientific issue, for both researchers and water resources managers, such as Electricite de France (Energy and Hydropower Company). The past and current context of climate variability enhances the interest on this topic, since multi-purposes water resources management is highly sensitive to this variability. The Durance River watershed (14000 km2), situated in the French Alps, is a good example of the complexity of this issue. It is characterized by a variety of hydrological processes (from snowy to Mediterranean regimes) and a wide range of anthropogenic influences (hydropower, irrigation, flood control, tourism and water supply), mixing potential causes of changes in its hydrological regimes. As water related stakes are numerous in this watershed, improving knowledge on the hydrological variability of the Durance River appears to be essential. In this presentation, we would like to focus on a methodology we developed to build long-term historical hydrometeorological time-series, based on atmospheric reanalysis (20CR : 20th Century Reanalysis) and historical local observations. This methodology allowed us to generate precipitation, air temperature and streamflow time-series at a daily time-step for a sample of 22 watersheds, for the 1883-2010 period. These long-term streamflow reconstructions have been validated thanks to historical searches that allowed to bring to light ten long historical series of daily streamflows, beginning on the early 20th century. Reconstructions appear to have rather good statistical properties, with good correlation (greater than 0.8) and limited mean and variance bias (less than 5%). Then, these long-term hydrometeorological time-series allowed us to characterize the past variability in terms of available water resources, droughts or hydrological regime. These analyses help water resources managers to better know the range of hydrological variabilities, which are usually greatly underestimated with classical available time-series (less than 50 years).

Summary of annual mean, maximum, minimum, and L-scale statistics of daily mean streamflow for 712 U.S. Geological Survey streamflow-gaging Stations in Texas Through 2003

USGS Publications Warehouse

Asquith, William H.; Vrabel, Joseph; Roussel, Meghan C.

2007-01-01

Analysts and managers of surface-water resources might have interest in selected statistics of daily mean streamflow for U.S. Geological Survey (USGS) streamflow-gaging stations in Texas. The selected statistics are the annual mean, maximum, minimum, and L-scale of daily meanstreamflow. Annual L-scale of streamflow is a robust measure of the variability of the daily mean streamflow for a given year. The USGS, in cooperation with the Texas Commission on Environmental Quality, initiated in 2006a data and reporting process to generate annual statistics for 712 USGS streamflow-gaging stations in Texas. A graphical depiction of the history of the annual statistics for most active and inactive, continuous-record gaging stations in Texas provides valuable information by conveying the historical perspective of streamflow for the watershed. Each figure consists off our time-series plots of the annual statistics of daily mean streamflow for each streamflow-gaging station. Each of the four plots is augmented with horizontal lines that depict the mean and median annual values of the corresponding statistic for the period of record. Monotonic trends for each of the four annual statistics also are identified using Kendall's T. The history of one or more streamflow-gaging stations could be used in a watershed, river basin, or other regional context by analysts and managers of surface-water resources to guide scientific, regulatory, or other inquiries of streamflow conditions in Texas.

A Nonlinear Dynamical Systems based Model for Stochastic Simulation of Streamflow

NASA Astrophysics Data System (ADS)

Erkyihun, S. T.; Rajagopalan, B.; Zagona, E. A.

2014-12-01

Traditional time series methods model the evolution of the underlying process as a linear or nonlinear function of the autocorrelation. These methods capture the distributional statistics but are incapable of providing insights into the dynamics of the process, the potential regimes, and predictability. This work develops a nonlinear dynamical model for stochastic simulation of streamflows. In this, first a wavelet spectral analysis is employed on the flow series to isolate dominant orthogonal quasi periodic timeseries components. The periodic bands are added denoting the 'signal' component of the time series and the residual being the 'noise' component. Next, the underlying nonlinear dynamics of this combined band time series is recovered. For this the univariate time series is embedded in a d-dimensional space with an appropriate lag T to recover the state space in which the dynamics unfolds. Predictability is assessed by quantifying the divergence of trajectories in the state space with time, as Lyapunov exponents. The nonlinear dynamics in conjunction with a K-nearest neighbor time resampling is used to simulate the combined band, to which the noise component is added to simulate the timeseries. We demonstrate this method by applying it to the data at Lees Ferry that comprises of both the paleo reconstructed and naturalized historic annual flow spanning 1490-2010. We identify interesting dynamics of the signal in the flow series and epochal behavior of predictability. These will be of immense use for water resources planning and management.

Relating streamflow characteristics to specialized insectivores in the Tennessee River Valley: a regional approach

USGS Publications Warehouse

Knight, Rodney R.; Gregory, M. Brian; Wales, Amy K.

2008-01-01

Analysis of hydrologic time series and fish community data across the Tennessee River Valley identified three hydrologic metrics essential to habitat suitability and food availability for insectivorous fish communities in streams of the Tennessee River Valley: constancy (flow stability or temporal invariance), frequency of moderate flooding (frequency of habitat disturbance), and rate of streamflow recession. Initial datasets included 1100 fish community sites and 300 streamgages. Reduction of these datasets to sites with coexisting data yielded 33 sites with streamflow and fish community data for analysis. Identification of critical hydrologic metrics was completed using a multivariate correlation procedure that maximizes the rank correlation between the hydrologic metrics and fish community resemblance matrices. Quantile regression was used to define thresholds of potential ranges of insectivore scores for given values of the hydrologic metrics. Increased values of constancy and insectivore scores were positively correlated. Constancy of streamflow maintains wetted perimeter, which is important for providing habitat for fish spawning and increased surface area for invertebrate colonization and reproduction. Site scores for insectivorous fish increased as the frequency of moderate flooding (3 times the median annual streamflow) decreased, suggesting that insectivorous fish communities respond positively to less frequent disturbance and a more stable habitat. Increased streamflow recession rates were associated with decreased insectivore scores. Increased streamflow recession can strand fish in pools and other areas that are disconnected from flowing water and remove invertebrates as food sources that were suspended during high-streamflow events.

Assessing the Snow Advance Index as potential predictor of winter streamflow of the Iberian Peninsula Rivers

NASA Astrophysics Data System (ADS)

Hidalgo-Muñoz, José Manuel; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2015-04-01

This study examines the ability of the Eurasian snow cover increase during the previous October as potential predictor of winter streamflow in the Iberian Peninsula Rivers. The streamflow data base used has been provided by the Center for Studies and Experimentation of Public Works, CEDEX. Series from gauging stations and reservoirs with less than 10% of missing data (filled by regression with well correlated neighboring stations) have been considered. The homogeneity of these series has been evaluated through the Pettit test and degree of human alteration by the Common Area Index. The application of these criteria led to the selection of 382 streamflow time series homogeneously distributed over the Iberian Peninsula, covering the period 1975-2008. For this streamflow data, winter seasonal values were obtained by averaging the monthly values from January to March. The recently proposed Snow Advance Index (SAI) was employed to monitor the snow cover increase during previous October. The stability of the correlations was the criterion followed to establish if SAI could be considered as potential predictor of winter streamflow at each gauging station. Winter streamflow is predicted using a linear regression model. A leave-one-out cross validation approach was adopted to create calibration and validations subsets. The correlation coefficient (RHO), Root Mean Square Error Skill Score (RMSESS) and the Gerrity Skill Score (GSS) were used to evaluate the forecasting skill. From the 382 stations evaluated, significant and stable correlations with SAI were found in 238 stations, covering most of the IP (except for the Cantabrian and Mediterranean slopes). Some forecasting skill was found in 223 of them, being this skill moderate (RHO>0.44, RMSESS>10%, GSS>0.2) in 141 of them, and particularly good (RHO>0.5, RMSESS>20%, GSS>0.4) in 23. This study shows that the SAI of previous October is a reliable predictor of following winter streamflow for the Iberian Peninsula Rivers, providing useful information, which, in turn, helps in better management of water resources. KEYWORDS Snow Advance Index, streamflow, forecasting, Iberian Peninsula. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Catchment Storage and Transport on Timescales from Minutes to Millennia

NASA Astrophysics Data System (ADS)

Kirchner, J. W.

2017-12-01

Landscapes are characterized by preferential flow and pervasive heterogeneity on all scales. They therefore store and transmit water and solutes over a wide spectrum of time scales, with important implications for contaminant transport, weathering rates, and runoff chemistry. Theoretical analyses predict, and syntheses of age tracer data confirm, that waters in aquifers are older - often by orders of magnitude - than in the rivers that flow from them, and that this disconnect between water ages arises from aquifer heterogeneity. Recent theoretical studies also suggest that catchment transit time distributions are nonstationary, reflecting temporal variability in precipitation forcing, structural heterogeneity in catchments themselves, and the nonlinearity of the mechanisms controlling storage and transport in the subsurface. The challenge of empirically estimating these nonstationary transit time distributions in real-world catchments, however, has only begun to be explored. In recent years, long-term isotope time series have been collected in many research catchments, and new technologies have emerged that allow quasi-continuous measurements of isotopes in precipitation and streamflow. These new data streams create new opportunities to study how rainfall becomes streamflow following the onset of precipitation. Here I present novel methods for quantifying the fraction of current rainfall in streamflow across ensembles of precipitation events. Benchmark tests with nonstationary catchment models demonstrate that this approach quantitatively measures the short tail of the transit time distribution for a wide range of catchment response characteristics. In combination with reactive tracer time series, this approach can potentially be extended to measure short-term chemical reaction rates at the catchment scale. Applications using high-frequency tracer time series from several experimental catchments demonstrate the utility of the new approach outlined here.

Physical habitat simulation system reference manual: version II

USGS Publications Warehouse

Milhous, Robert T.; Updike, Marlys A.; Schneider, Diane M.

1989-01-01

There are four major components of a stream system that determine the productivity of the fishery (Karr and Dudley 1978). These are: (1) flow regime, (2) physical habitat structure (channel form, substrate distribution, and riparian vegetation), (3) water quality (including temperature), and (4) energy inputs from the watershed (sediments, nutrients, and organic matter). The complex interaction of these components determines the primary production, secondary production, and fish population of the stream reach. The basic components and interactions needed to simulate fish populations as a function of management alternatives are illustrated in Figure I.1. The assessment process utilizes a hierarchical and modular approach combined with computer simulation techniques. The modular components represent the "building blocks" for the simulation. The quality of the physical habitat is a function of flow and, therefore, varies in quality and quantity over the range of the flow regime. The conceptual framework of the Incremental Methodology and guidelines for its application are described in "A Guide to Stream Habitat Analysis Using the Instream Flow Incremental Methodology" (Bovee 1982). Simulation of physical habitat is accomplished using the physical structure of the stream and streamflow. The modification of physical habitat by temperature and water quality is analyzed separately from physical habitat simulation. Temperature in a stream varies with the seasons, local meteorological conditions, stream network configuration, and the flow regime; thus, the temperature influences on habitat must be analysed on a stream system basis. Water quality under natural conditions is strongly influenced by climate and the geological materials, with the result that there is considerable natural variation in water quality. When we add the activities of man, the possible range of water quality possibilities becomes rather large. Consequently, water quality must also be analysed on a stream system basis. Such analysis is outside the scope of this manual, which concentrates on simulation of physical habitat based on depth, velocity, and a channel index. The results form PHABSIM can be used alone or by using a series of habitat time series programs that have been developed to generate monthly or daily habitat time series from the Weighted Usable Area versus streamflow table resulting from the habitat simulation programs and streamflow time series data. Monthly and daily streamflow time series may be obtained from USGS gages near the study site or as the output of river system management models.

Simulating the effects of ground-water withdrawals on streamflow in a precipitation-runoff model

USGS Publications Warehouse

Zarriello, Philip J.; Barlow, P.M.; Duda, P.B.

2004-01-01

Precipitation-runoff models are used to assess the effects of water use and management alternatives on streamflow. Often, ground-water withdrawals are a major water-use component that affect streamflow, but the ability of surface-water models to simulate ground-water withdrawals is limited. As part of a Hydrologic Simulation Program-FORTRAN (HSPF) precipitation-runoff model developed to analyze the effect of ground-water and surface-water withdrawals on streamflow in the Ipswich River in northeastern Massachusetts, an analytical technique (STRMDEPL) was developed for calculating the effects of pumped wells on streamflow. STRMDEPL is a FORTRAN program based on two analytical solutions that solve equations for ground-water flow to a well completed in a semi-infinite, homogeneous, and isotropic aquifer in direct hydraulic connection to a fully penetrating stream. One analytical method calculates unimpeded flow at the stream-aquifer boundary and the other method calculates the resistance to flow caused by semipervious streambed and streambank material. The principle of superposition is used with these analytical equations to calculate time-varying streamflow depletions due to daily pumping. The HSPF model can readily incorporate streamflow depletions caused by a well or surface-water withdrawal, or by multiple wells or surface-water withdrawals, or both, as a combined time-varying outflow demand from affected channel reaches. These demands are stored as a time series in the Watershed Data Management (WDM) file. This time-series data is read into the model as an external source used to specify flow from the first outflow gate in the reach where these withdrawals are located. Although the STRMDEPL program can be run independently of the HSPF model, an extension was developed to run this program within GenScn, a scenario generator and graphical user interface developed for use with the HSPF model. This extension requires that actual pumping rates for each well be stored in a unique WDM dataset identified by an attribute that associates each well with the model reach from which water is withdrawn. Other attributes identify the type and characteristics of the data. The interface allows users to easily add new pumping wells, delete exiting pumping wells, or change properties of the simulated aquifer or well. Development of this application enhanced the ability of the HSPF model to simulate complex water-use conditions in the Ipswich River Basin. The STRMDEPL program and the GenScn extension provide a valuable tool for water managers to evaluate the effects of pumped wells on streamflow and to test alternative water-use scenarios. Copyright ASCE 2004.

Reconciling Streamflow Uncertainty Estimation and River Bed Morphology Dynamics. Insights from a Probabilistic Assessment of Streamflow Uncertainties Using a Reliability Diagram

NASA Astrophysics Data System (ADS)

Morlot, T.; Mathevet, T.; Perret, C.; Favre Pugin, A. C.

2014-12-01

Streamflow uncertainty estimation has recently received a large attention in the literature. A dynamic rating curve assessment method has been introduced (Morlot et al., 2014). This dynamic method allows to compute a rating curve for each gauging and a continuous streamflow time-series, while calculating streamflow uncertainties. Streamflow uncertainty takes into account many sources of uncertainty (water level, rating curve interpolation and extrapolation, gauging aging, etc.) and produces an estimated distribution of streamflow for each days. In order to caracterise streamflow uncertainty, a probabilistic framework has been applied on a large sample of hydrometric stations of the Division Technique Générale (DTG) of Électricité de France (EDF) hydrometric network (>250 stations) in France. A reliability diagram (Wilks, 1995) has been constructed for some stations, based on the streamflow distribution estimated for a given day and compared to a real streamflow observation estimated via a gauging. To build a reliability diagram, we computed the probability of an observed streamflow (gauging), given the streamflow distribution. Then, the reliability diagram allows to check that the distribution of probabilities of non-exceedance of the gaugings follows a uniform law (i.e., quantiles should be equipropables). Given the shape of the reliability diagram, the probabilistic calibration is caracterised (underdispersion, overdispersion, bias) (Thyer et al., 2009). In this paper, we present case studies where reliability diagrams have different statistical properties for different periods. Compared to our knowledge of river bed morphology dynamic of these hydrometric stations, we show how reliability diagram gives us invaluable information on river bed movements, like a continuous digging or backfilling of the hydraulic control due to erosion or sedimentation processes. Hence, the careful analysis of reliability diagrams allows to reconcile statistics and long-term river bed morphology processes. This knowledge improves our real-time management of hydrometric stations, given a better caracterisation of erosion/sedimentation processes and the stability of hydrometric station hydraulic control.

Flood of June 22-24, 2006, in North-Central Ohio, With Emphasis on the Cuyahoga River Near Independence

USGS Publications Warehouse

Sherwood, James M.; Ebner, Andrew D.; Koltun, G.F.; Astifan, Brian M.

2007-01-01

Heavy rains caused severe flooding on June 22-24, 2006, and damaged approximately 4,580 homes and 48 businesses in Cuyahoga County. Damage estimates in Cuyahoga County for the two days of flooding exceed $47 million; statewide damage estimates exceed $150 million. Six counties (Cuyahoga, Erie, Huron, Lucas, Sandusky, and Stark) in northeast Ohio were declared Federal disaster areas. One death, in Lorain County, was attributed to the flooding. The peak streamflow of 25,400 cubic feet per second and corresponding peak gage height of 23.29 feet were the highest recorded at the U.S. Geological Survey (USGS) streamflow-gaging station Cuyahoga River at Independence (04208000) since the gaging station began operation in 1922, exceeding the previous peak streamflow of 24,800 cubic feet per second that occurred on January 22, 1959. An indirect calculation of the peak streamflow was made by use of a step-backwater model because all roads leading to the gaging station were inundated during the flood and field crews could not reach the station to make a direct measurement. Because of a statistically significant and persistent positive trend in the annual-peak-streamflow time series for the Cuyahoga River at Independence, a method was developed and applied to detrend the annual-peak-streamflow time series prior to the traditional log-Pearson Type III flood-frequency analysis. Based on this analysis, the recurrence interval of the computed peak streamflow was estimated to be slightly less than 100 years. Peak-gage-height data, peak-streamflow data, and recurrence-interval estimates for the June 22-24, 2006, flood are tabulated for the Cuyahoga River at Independence and 10 other USGS gaging stations in north-central Ohio. Because flooding along the Cuyahoga River near Independence and Valley View was particularly severe, a study was done to document the peak water-surface profile during the flood from approximately 2 miles downstream from the USGS streamflow-gaging station at Independence to approximately 2 miles upstream from the gaging station. High-water marks were identified and flagged in the field. Third-order-accuracy surveys were used to determine elevations of the high-water marks, and the data were tabulated and plotted.

Quantification of fish habitat in selected reaches of the Marmaton and Marais des Cygnes Rivers, Missouri

USGS Publications Warehouse

Heimann, David C.; Richards, Joseph M.; Brewer, Shannon K.; Norman, Richard D.

2005-01-01

The U.S. Geological Survey, in cooperation with the Missouri Department of Conservation, undertook a study to quantify fish habitat by using relations between streamflow and the spatial and temporal distributions of fish habitat at five sites in the Marmaton and Marais des Cygnes Rivers in western Missouri. Twenty-six fish habitat categories were selected for nine species under varying seasonal (spring, summer, and fall), diel (summer day and night), and life-stage (spawning, juvenile, and adult) conditions. Physical habitat characteristics were determined for each category using depth, velocity, and channel substrate criteria. Continuous streamflow data were then combined with the habitat-streamflow relations to compile a habitat time series for each habitat category at each site. Fish habitat categories were assessed as to their vulnerability to habitat alteration based on critical life stages (spawning and juvenile rearing periods) and susceptibility to habitat limitations from dewatering or high flows. Species categories representing critical life stages with physical habitat limitations represent likely bottlenecks in fish populations. Categories with potential bottlenecks can serve as indicator categories and aid managers when determining the flows necessary for maintaining these habitats under altered flow regimes. The relation between the area of each habitat category and streamflow differed greatly between category, season, and stream reach. No single flow maximized selected habitat area for all categories or even for all species/category within a particular season at a site. However, some similarities were noted among habitat characteristics, including the streamflow range for which habitat availability is maximized and the range of streamflows for which a habitat category area is available at the Marmaton River sites. A monthly habitat time series was created for all 26 habitat categories at two Marmaton River sites. A daily habitat time series was created at three Marais des Cygnes River sites for two periods: 1941 through 1963 (pre-regulation) and 1982 through 2003 (post-regulation). The habitat category with the highest median area in spring was paddlefish (Polyodon spathula) with normalized areas of up to 2,000 square meters per 100 meters of stream channel. Flathead catfish (Pylodictis olivaris) habitat area generally was the category area most available in summer and fall. Differences in daily selected habitat area time series between pre- and post-regulation time periods varied by species/category and by site. For instance, whereas there was a decline in the distribution of spring spawning habitat for suckermouth minnow (Phenacobius mirabilis) and slenderhead darter (Percina phoxocephala) from pre- to post-regulation periods at all three sites, the 25 to 75 percentile habitat area substantially increased for paddlefish under post-regulation conditions. Potential habitat area for most species was maximized at the Marmaton River sites at flows of about 1 to 10 cubic meters per second, whereas median monthly streamflows ranged from less than 1 to 20 cubic meters per second depending on site and season. Paddlefish habitat was available beginning at higher flows than other categories (4 to 7 cubic meters per second) and also maximized at higher flows (greater than 50 to 100 cubic meters per second). Selected potential habitat area was maximized for most species at the Marais des Cygnes River sites at flows of about 1 to 50 cubic meters per second, whereas median monthly streamflows ranged from 4 to 55 cubic meters per second depending on site and season. The range of streamflows for which selected habitat area was available in summer and fall was substantially less at the channelized Marais des Cygnes River site when compared to the non-channelized sites, and, therefore, the susceptibility of categories to high-flow habitat limitations was greater at this site. The channelized reach was more unifor

Streamflow Prediction based on Chaos Theory

NASA Astrophysics Data System (ADS)

Li, X.; Wang, X.; Babovic, V. M.

2015-12-01

Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.

Analysis of streambed temperatures in ephemeral channels to determine streamflow frequency and duration

USGS Publications Warehouse

Constantz, James E.; Stonestrom, David A.; Stewart, Amy E.; Niswonger, Richard G.; Smith, Tyson R.

2001-01-01

Spatial and temporal patterns in streamflow are rarely monitored for ephemeral streams. Flashy, erosive streamflows common in ephemeral channels create a series of operational and maintenance problems, which makes it impractical to deploy a series of gaging stations along ephemeral channels. Streambed temperature is a robust and inexpensive parameter to monitor remotely, leading to the possibility of analyzing temperature patterns to estimate streamflow frequency and duration along ephemeral channels. A simulation model was utilized to examine various atmospheric and hydrological upper boundary conditions compared with a series of hypothetical temperature‐monitoring depths within the streambed. Simulation results indicate that streamflow events were distinguished from changing atmospheric conditions with greater certainty using temperatures at shallow depths (e.g., 10–20 cm) as opposed to the streambed surface. Three ephemeral streams in the American Southwest were instrumented to monitor streambed temperature for determining the accuracy of using this approach to ascertain the long‐term temporal and spatial extent of streamflow along each stream channel. Streambed temperature data were collected at the surface or at shallow depth along each stream channel, using thermistors encased in waterproof, single‐channel data loggers tethered to anchors in the channel. On the basis of comparisons with site information, such as direct field observations and upstream flow records, diurnal temperature variations successfully detected the presence and duration of streamflow for all sites.

Streamflow Bias Correction for Climate Change Impact Studies: Harmless Correction or Wrecking Ball?

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chegwidden, O.

2017-12-01

Projections of the hydrologic impacts of climate change rely on a modeling chain that includes estimates of future greenhouse gas emissions, global climate models, and hydrologic models. The resulting streamflow time series are used in turn as input to impact studies. While these flows can sometimes be used directly in these impact studies, many applications require additional post-processing to remove model errors. Water resources models and regulation studies are a prime example of this type of application. These models rely on specific flows and reservoir levels to trigger reservoir releases and diversions and do not function well if the unregulated streamflow inputs are significantly biased in time and/or amount. This post-processing step is typically referred to as bias-correction, even though this step corrects not just the mean but the entire distribution of flows. Various quantile-mapping approaches have been developed that adjust the modeled flows to match a reference distribution for some historic period. Simulations of future flows are then post-processed using this same mapping to remove hydrologic model errors. These streamflow bias-correction methods have received far less scrutiny than the downscaling and bias-correction methods that are used for climate model output, mostly because they are less widely used. However, some of these methods introduce large artifacts in the resulting flow series, in some cases severely distorting the climate change signal that is present in future flows. In this presentation, we discuss our experience with streamflow bias-correction methods as part of a climate change impact study in the Columbia River basin in the Pacific Northwest region of the United States. To support this discussion, we present a novel way to assess whether a streamflow bias-correction method is merely a harmless correction or is more akin to taking a wrecking ball to the climate change signal.

Load estimator (LOADEST): a FORTRAN program for estimating constituent loads in streams and rivers

USGS Publications Warehouse

Runkel, Robert L.; Crawford, Charles G.; Cohn, Timothy A.

2004-01-01

LOAD ESTimator (LOADEST) is a FORTRAN program for estimating constituent loads in streams and rivers. Given a time series of streamflow, additional data variables, and constituent concentration, LOADEST assists the user in developing a regression model for the estimation of constituent load (calibration). Explanatory variables within the regression model include various functions of streamflow, decimal time, and additional user-specified data variables. The formulated regression model then is used to estimate loads over a user-specified time interval (estimation). Mean load estimates, standard errors, and 95 percent confidence intervals are developed on a monthly and(or) seasonal basis. The calibration and estimation procedures within LOADEST are based on three statistical estimation methods. The first two methods, Adjusted Maximum Likelihood Estimation (AMLE) and Maximum Likelihood Estimation (MLE), are appropriate when the calibration model errors (residuals) are normally distributed. Of the two, AMLE is the method of choice when the calibration data set (time series of streamflow, additional data variables, and concentration) contains censored data. The third method, Least Absolute Deviation (LAD), is an alternative to maximum likelihood estimation when the residuals are not normally distributed. LOADEST output includes diagnostic tests and warnings to assist the user in determining the appropriate estimation method and in interpreting the estimated loads. This report describes the development and application of LOADEST. Sections of the report describe estimation theory, input/output specifications, sample applications, and installation instructions.

Practical implementation of a particle filter data assimilation approach to estimate initial hydrologic conditions and initialize medium-range streamflow forecasts

NASA Astrophysics Data System (ADS)

Clark, E.; Wood, A.; Nijssen, B.; Newman, A. J.; Mendoza, P. A.

2016-12-01

The System for Hydrometeorological Applications, Research and Prediction (SHARP), developed at the National Center for Atmospheric Research (NCAR), University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation, is a fully automated ensemble prediction system for short-term to seasonal applications. It incorporates uncertainty in initial hydrologic conditions (IHCs) and in hydrometeorological predictions. In this implementation, IHC uncertainty is estimated by propagating an ensemble of 100 plausible temperature and precipitation time series through the Sacramento/Snow-17 model. The forcing ensemble explicitly accounts for measurement and interpolation uncertainties in the development of gridded meteorological forcing time series. The resulting ensemble of derived IHCs exhibits a broad range of possible soil moisture and snow water equivalent (SWE) states. To select the IHCs that are most consistent with the observations, we employ a particle filter (PF) that weights IHC ensemble members based on observations of streamflow and SWE. These particles are then used to initialize ensemble precipitation and temperature forecasts downscaled from the Global Ensemble Forecast System (GEFS), generating a streamflow forecast ensemble. We test this method in two basins in the Pacific Northwest that are important for water resources management: 1) the Green River upstream of Howard Hanson Dam, and 2) the South Fork Flathead River upstream of Hungry Horse Dam. The first of these is characterized by mixed snow and rain, while the second is snow-dominated. The PF-based forecasts are compared to forecasts based on a single IHC (corresponding to median streamflow) paired with the full GEFS ensemble, and 2) the full IHC ensemble, without filtering, paired with the full GEFS ensemble. In addition to assessing improvements in the spread of IHCs, we perform a hindcast experiment to evaluate the utility of PF-based data assimilation on streamflow forecasts at 1- to 7-day lead times.

Evaluation of statistical and rainfall-runoff models for predicting historical daily streamflow time series in the Des Moines and Iowa River watersheds

USGS Publications Warehouse

Farmer, William H.; Knight, Rodney R.; Eash, David A.; Kasey J. Hutchinson,; Linhart, S. Mike; Christiansen, Daniel E.; Archfield, Stacey A.; Over, Thomas M.; Kiang, Julie E.

2015-08-24

Daily records of streamflow are essential to understanding hydrologic systems and managing the interactions between human and natural systems. Many watersheds and locations lack streamgages to provide accurate and reliable records of daily streamflow. In such ungaged watersheds, statistical tools and rainfall-runoff models are used to estimate daily streamflow. Previous work compared 19 different techniques for predicting daily streamflow records in the southeastern United States. Here, five of the better-performing methods are compared in a different hydroclimatic region of the United States, in Iowa. The methods fall into three classes: (1) drainage-area ratio methods, (2) nonlinear spatial interpolations using flow duration curves, and (3) mechanistic rainfall-runoff models. The first two classes are each applied with nearest-neighbor and map-correlated index streamgages. Using a threefold validation and robust rank-based evaluation, the methods are assessed for overall goodness of fit of the hydrograph of daily streamflow, the ability to reproduce a daily, no-fail storage-yield curve, and the ability to reproduce key streamflow statistics. As in the Southeast study, a nonlinear spatial interpolation of daily streamflow using flow duration curves is found to be a method with the best predictive accuracy. Comparisons with previous work in Iowa show that the accuracy of mechanistic models with at-site calibration is substantially degraded in the ungaged framework.

Effect of monthly areal rainfall uncertainty on streamflow simulation

NASA Astrophysics Data System (ADS)

Ndiritu, J. G.; Mkhize, N.

2017-08-01

Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic monthly rainfalls were 86 and 90% of the mean naturalised streamflow. In calibration, 33% of the naturalised flow located within the streamflow ranges with historic rainfall simulations and using stochastic rainfalls increased this to 66%. In validation the respective percentages of naturalised flows located within the simulated streamflow ranges were 32 and 72% respectively. The analysis reveals that monthly areal rainfall uncertainty is significant and incorporating it into streamflow simulation would add validity to the results.

Extracting Hydrologic Understanding from the Unique Space-time Sampling of the Surface Water and Ocean Topography (SWOT) Mission

NASA Astrophysics Data System (ADS)

Nickles, C.; Zhao, Y.; Beighley, E.; Durand, M. T.; David, C. H.; Lee, H.

2017-12-01

The Surface Water and Ocean Topography (SWOT) satellite mission is jointly developed by NASA, the French space agency (CNES), with participation from the Canadian and UK space agencies to serve both the hydrology and oceanography communities. The SWOT mission will sample global surface water extents and elevations (lakes/reservoirs, rivers, estuaries, oceans, sea and land ice) at a finer spatial resolution than is currently possible enabling hydrologic discovery, model advancements and new applications that are not currently possible or likely even conceivable. Although the mission will provide global cover, analysis and interpolation of the data generated from the irregular space/time sampling represents a significant challenge. In this study, we explore the applicability of the unique space/time sampling for understanding river discharge dynamics throughout the Ohio River Basin. River network topology, SWOT sampling (i.e., orbit and identified SWOT river reaches) and spatial interpolation concepts are used to quantify the fraction of effective sampling of river reaches each day of the three-year mission. Streamflow statistics for SWOT generated river discharge time series are compared to continuous daily river discharge series. Relationships are presented to transform SWOT generated streamflow statistics to equivalent continuous daily discharge time series statistics intended to support hydrologic applications using low-flow and annual flow duration statistics.

Nine Hundred Years of Weekly Streamflows: Stochastic Downscaling of Ensemble Tree-Ring Reconstructions

NASA Astrophysics Data System (ADS)

Sauchyn, David; Ilich, Nesa

2017-11-01

We combined the methods and advantages of stochastic hydrology and paleohydrology to estimate 900 years of weekly flows for the North and South Saskatchewan Rivers at Edmonton and Medicine Hat, Alberta, respectively. Regression models of water-year streamflow were constructed using historical naturalized flow data and a pool of 196 tree-ring (earlywood, latewood, and annual) ring-width chronologies from 76 sites. The tree-ring models accounted for up to 80% of the interannual variability in historical naturalized flows. We developed a new algorithm for generating stochastic time series of weekly flows constrained by the statistical properties of both the historical record and proxy streamflow data, and by the necessary condition that weekly flows correlate between the end of a year and the start of the next. A second innovation, enabled by the density of our tree-ring network, is to derive the paleohydrology from an ensemble of 100 statistically significant reconstructions at each gauge. Using paleoclimatic data to generate long series of weekly flow estimates augments the short historical record with an expanded range of hydrologic variability, including sequences of wet and dry years of greater length and severity. This unique hydrometric time series will enable evaluation of the reliability of current water supply and management systems given the range of hydroclimatic variability and extremes contained in the stochastic paleohydrology. It also could inform evaluation of the uncertainty in climate model projections, given that internal hydroclimatic variability is the dominant source of uncertainty.

On the probability distribution of daily streamflow in the United States

USGS Publications Warehouse

Blum, Annalise G.; Archfield, Stacey A.; Vogel, Richard M.

2017-01-01

Daily streamflows are often represented by flow duration curves (FDCs), which illustrate the frequency with which flows are equaled or exceeded. FDCs have had broad applications across both operational and research hydrology for decades; however, modeling FDCs has proven elusive. Daily streamflow is a complex time series with flow values ranging over many orders of magnitude. The identification of a probability distribution that can approximate daily streamflow would improve understanding of the behavior of daily flows and the ability to estimate FDCs at ungaged river locations. Comparisons of modeled and empirical FDCs at nearly 400 unregulated, perennial streams illustrate that the four-parameter kappa distribution provides a very good representation of daily streamflow across the majority of physiographic regions in the conterminous United States (US). Further, for some regions of the US, the three-parameter generalized Pareto and lognormal distributions also provide a good approximation to FDCs. Similar results are found for the period of record FDCs, representing the long-term hydrologic regime at a site, and median annual FDCs, representing the behavior of flows in a typical year.

A precipitation-runoff model for simulating natural streamflow conditions in the Smith River watershed, Montana, water years 1996-2008

USGS Publications Warehouse

Chase, Katherine J.; Caldwell, Rodney R.; Stanley, Andrea K.

2014-01-01

This report documents the construction of a precipitation-runoff model for simulating natural streamflow in the Smith River watershed, Montana. This Precipitation-Runoff Modeling System model, constructed in cooperation with the Meagher County Conservation District, can be used to examine the general hydrologic framework of the Smith River watershed, including quantification of precipitation, evapotranspiration, and streamflow; partitioning of streamflow between surface runoff and subsurface flow; and quantifying contributions to streamflow from several parts of the watershed. The model was constructed by using spatial datasets describing watershed topography, the streams, and the hydrologic characteristics of the basin soils and vegetation. Time-series data (daily total precipitation, and daily minimum and maximum temperature) were input to the model to simulate daily streamflow. The model was calibrated for water years 2002–2007 and evaluated for water years 1996–2001. Though water year 2008 was included in the study period to evaluate water-budget components, calibration and evaluation data were unavailable for that year. During the calibration and evaluation periods, simulated-natural flow values were compared to reconstructed-natural streamflow data. These reconstructed-natural streamflow data were calculated by adding Bureau of Reclamation’s depletions data to the observed streamflows. Reconstructed-natural streamflows represent estimates of streamflows for water years 1996–2007 assuming there was no agricultural water-resources development in the watershed. Additional calibration targets were basin mean monthly solar radiation and potential evapotranspiration. The model estimated the hydrologic processes in the Smith River watershed during the calibration and evaluation periods. Simulated-natural mean annual and mean monthly flows generally were the same or higher than the reconstructed-natural streamflow values during the calibration period, whereas they were lower during the evaluation period. The shape of the annual hydrographs for the simulated-natural daily streamflow values matched the shape of the hydrographs for the reconstructed-natural values for most of the calibration period, but daily streamflow values were underestimated during the evaluation period for water years 1996–1998. The model enabled a detailed evaluation of the components of the water budget within the Smith River watershed during the water year 1996–2008 study period. During this study period, simulated mean annual precipitation across the Smith River watershed was 16 inches, out of which 14 inches evaporated or transpired and 2 inches left the basin as streamflow. Per the precipitation-runoff model simulations, during most of the year, surface runoff rarely (less than 2 percent of the time during water years 2002–2008) makes up more than 10 percent of the total streamflow. Subsurface flow (the combination of interflow and groundwater flow) makes up most of the total streamflow (99 or more percent of total streamflow for 71 percent of the time during water years 2002–2008).

Streamflow profile classification using functional data analysis: A case study on the Kelantan River Basin

NASA Astrophysics Data System (ADS)

Jamaludin, Suhaila

2017-05-01

Extreme rainfall events such as floods and prolonged dry spells have become common phenomena in tropical countries like Malaysia. Floods are regular natural disasters in Malaysia, and happen nearly every year during the monsoon season. Recently, the magnitude of streamflow seems to have altered frequently, both spatially and temporally. Therefore, in order to have effective planning and an efficient water management system, it is advisable that streamflow data are analysed continuously over a period of time. If the data are treated as a set of functions rather than as a set of discrete values, then this ensures that they are not restricted by physical time. In addition, the derivatives of the functions may themselves be treated as functional data, which provides new information. The objective of this study is to develop a functional framework for hydrological applications using streamflow as the functional data. The daily flow series from the Kelantan River Basin were used as the main input in this study. Seven streamflow stations were employed in the analysis. Classification between the stations was done using the functional principal component, which was based on the results of the factor scores. The results indicated that two stations, namely the Kelantan River (Guillemard Bridge) and the Galas River, have a different flow pattern from the other streamflow stations. The flow curves of these two rivers are considered as the extreme curves because of their different magnitude and shape.

Reference manual for generation and analysis of Habitat Time Series: version II

USGS Publications Warehouse

Milhous, Robert T.; Bartholow, John M.; Updike, Marlys A.; Moos, Alan R.

1990-01-01

The selection of an instream flow requirement for water resource management often requires the review of how the physical habitat changes through time. This review is referred to as 'Time Series Analysis." The Tune Series Library (fSLIB) is a group of programs to enter, transform, analyze, and display time series data for use in stream habitat assessment. A time series may be defined as a sequence of data recorded or calculated over time. Examples might be historical monthly flow, predicted monthly weighted usable area, daily electrical power generation, annual irrigation diversion, and so forth. The time series can be analyzed, both descriptively and analytically, to understand the importance of the variation in the events over time. This is especially useful in the development of instream flow needs based on habitat availability. The TSLIB group of programs assumes that you have an adequate study plan to guide you in your analysis. You need to already have knowledge about such things as time period and time step, species and life stages to consider, and appropriate comparisons or statistics to be produced and displayed or tabulated. Knowing your destination, you must first evaluate whether TSLIB can get you there. Remember, data are not answers. This publication is a reference manual to TSLIB and is intended to be a guide to the process of using the various programs in TSLIB. This manual is essentially limited to the hands-on use of the various programs. a TSLIB use interface program (called RTSM) has been developed to provide an integrated working environment where the use has a brief on-line description of each TSLIB program with the capability to run the TSLIB program while in the user interface. For information on the RTSM program, refer to Appendix F. Before applying the computer models described herein, it is recommended that the user enroll in the short course "Problem Solving with the Instream Flow Incremental Methodology (IFIM)." This course is offered by the Aquatic Systems Branch of the National Ecology Research Center. For more information about the TSLIB software, refer to the Memorandum of Understanding. Chapter 1 provides a brief introduction to the Instream Flow Incremental Methodology and TSLIB. Other chapters in this manual provide information on the different aspects of using the models. The information contained in the other chapters includes (2) acquisition, entry, manipulation, and listing of streamflow data; (3) entry, manipulation, and listing of the habitat-versus-streamflow function; (4) transferring streamflow data; (5) water resources systems analysis; (6) generation and analysis of daily streamflow and habitat values; (7) generation of the time series of monthly habitats; (8) manipulation, analysis, and display of month time series data; and (9) generation, analysis, and display of annual time series data. Each section includes documentation for the programs therein with at least one page of information for each program, including a program description, instructions for running the program, and sample output. The Appendixes contain the following: (A) sample file formats; (B) descriptions of default filenames; (C) alphabetical summary of batch-procedure files; (D) installing and running TSLIB on a microcomputer; (E) running TSLIB on a CDC Cyber computer; (F) using the TSLIB user interface program (RTSM); and (G) running WATSTORE on the USGS Amdahl mainframe computer. The number for this version of TSLIB--Version II-- is somewhat arbitrary, as the TSLIB programs were collected into a library some time ago; but operators tended to use and manage them as individual programs. Therefore, we will consider the group of programs from the past that were only on the CDC Cyber computer as Version 0; the programs from the past that were on both the Cyber and the IBM-compatible microcomputer as Version I; and the programs contained in this reference manual as Version II.

A nonparametric stochastic method for generating daily climate-adjusted streamflows

NASA Astrophysics Data System (ADS)

Stagge, J. H.; Moglen, G. E.

2013-10-01

A daily stochastic streamflow generation model is presented, which successfully replicates statistics of the historical streamflow record and can produce climate-adjusted daily time series. A monthly climate model relates general circulation model (GCM)-scale climate indicators to discrete climate-streamflow states, which in turn control parameters in a daily streamflow generation model. Daily flow is generated by a two-state (increasing/decreasing) Markov chain, with rising limb increments randomly sampled from a Weibull distribution and the falling limb modeled as exponential recession. When applied to the Potomac River, a 38,000 km2 basin in the Mid-Atlantic United States, the model reproduces the daily, monthly, and annual distribution and dynamics of the historical streamflow record, including extreme low flows. This method can be used as part of water resources planning, vulnerability, and adaptation studies and offers the advantage of a parsimonious model, requiring only a sufficiently long historical streamflow record and large-scale climate data. Simulation of Potomac streamflows subject to the Special Report on Emissions Scenarios (SRES) A1b, A2, and B1 emission scenarios predict a slight increase in mean annual flows over the next century, with the majority of this increase occurring during the winter and early spring. Conversely, mean summer flows are projected to decrease due to climate change, caused by a shift to shorter, more sporadic rain events. Date of the minimum annual flow is projected to shift 2-5 days earlier by the 2070-2099 period.

Artificial intelligence based models for stream-flow forecasting: 2000-2015

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

2015-11-01

The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

Wavelet-based variability of Yellow River discharge at 500-, 100-, and 50-year timescales

NASA Astrophysics Data System (ADS)

Su, Lu; Miao, Chiyuan; Duan, Qingyun

2017-04-01

Water scarcity in the Yellow River, China, has become increasingly severe over the past half century. In this paper, wavelet transform analysis was used to detect the variability of observed and reconstructed streamflow in the Yellow River at 500-, 100-, and 50-year timescales. The periodicity of the streamflow series and the co-varying relationships between streamflow and atmospheric circulation indices / sunspot number were assessed via the continuous wavelet transform (CWT) and the wavelet coherence transform (WTC). The CWT results showed intermittent oscillations in streamflow with increasing periodicities of 1-6 years at all timescales. Significant multidecadal and century-scale periodicities were identified in the 500-year streamflow series. The WTC results showed intermittent interannual covariance of streamflow with atmospheric circulation indices and sunspots. At the 50-year timescale, there were significant decadal oscillations between streamflow and the Arctic Oscillation (AO) and the Pacific Decadal Oscillation (PDO), and bidecadal oscillations with the PDO. At the 100-year timescale, there were significant decadal oscillations between streamflow and Niño 3.4, the AO, and sunspots. At the 500-year timescale, streamflow in the middle reaches of the Yellow River showed prominent covariance with the AO with an approximately 32-year periodicity, and with sunspots with an approximately 80-year periodicity. Atmospheric circulation indices modulate streamflow by affecting temperature and precipitation. Sunspots impact streamflow variability by influencing atmospheric circulation, resulting in abundant precipitation. In general, for both the CWT and the WTC results, the periodicities were spatially continuous, with a few gradual changes from upstream to downstream resulting from the varied topography and runoff. At the temporal scale, the periodicities were generally continuous over short timescales and discontinuous over longer timescales.

Wavelet-based Variability of Yellow River Discharge at 500-, 100-, and 50-Year Timescales

NASA Astrophysics Data System (ADS)

Su, L.

2017-12-01

Water scarcity in the Yellow River, China, has become increasingly severe over the past half century. In this paper, wavelet transform analysis was used to detect the variability of natural, observed, and reconstructed streamflow in the Yellow River at 500-, 100-, and 50-year timescales. The periodicity of the streamflow series and the co-varying relationships between streamflow and atmospheric circulation indices/sunspot number were assessed by means of continuous wavelet transform (CWT) and wavelet transform coherence (WTC) analyses. The CWT results showed intermittent oscillations in streamflow with increasing periodicities of 1-6 years at all timescales. Significant multidecadal and century-scale periodicities were identified in the 500-year streamflow series. The WTC results showed intermittent interannual covariance of streamflow with atmospheric circulation indices and sunspots. At the 50-year timescale, there were significant decadal oscillations between streamflow and the Arctic Oscillation (AO) and the Pacific Decadal Oscillation (PDO), and bidecadal oscillations with the PDO. At the 100-year timescale, there were significant decadal oscillations between streamflow and Niño 3.4, the AO, and sunspots. At the 500-year timescale, streamflow in the middle reaches of the Yellow River showed prominent covariance with the AO with an approximately 32-year periodicity, and with sunspots with an approximately 80-year periodicity. Atmospheric circulation indices modulate streamflow by affecting temperature and precipitation. Sunspots impact streamflow variability by influencing atmospheric circulation, resulting in abundant precipitation. In general, for both the CWT and the WTC results, the periodicities were spatially continuous, with a few gradual changes from upstream to downstream resulting from the varied topography and runoff. At the temporal scale, the periodicities were generally continuous over short timescales and discontinuous over longer timescales.

Regional variability in the accuracy of statistical reproductions of historical time series of daily streamflow at ungaged locations

NASA Astrophysics Data System (ADS)

Farmer, W. H.; Archfield, S. A.; Over, T. M.; Kiang, J. E.

2015-12-01

In the United States and across the globe, the majority of stream reaches and rivers are substantially impacted by water use or remain ungaged. The result is large gaps in the availability of natural streamflow records from which to infer hydrologic understanding and inform water resources management. From basin-specific to continent-wide scales, many efforts have been undertaken to develop methods to estimate ungaged streamflow. This work applies and contrasts several statistical models of daily streamflow to more than 1,700 reference-quality streamgages across the conterminous United States using a cross-validation methodology. The variability of streamflow simulation performance across the country exhibits a pattern familiar to other continental scale modeling efforts performed for the United States. For portions of the West Coast and the dense, relatively homogeneous and humid regions of the eastern United States models produce reliable estimates of daily streamflow using many different prediction methods. Model performance for the middle portion of the United States, marked by more heterogeneous and arid conditions, and with larger contributing areas and sparser networks of streamgages, is consistently poor. A discussion of the difficulty of statistical interpolation and regionalization in these regions raises additional questions of data availability and quality, hydrologic process representation and dominance, and intrinsic variability.

Exploring streamflow response to effective rainfall across event magnitude scale

Treesearch

Teemu Kokkonen; Harri Koivusalo; Tuomo Karvonen; Barry Croke; Anthony Jakeman

2004-01-01

Sets of flow events from four catchments were selected to study how dynamics in the conversion of effective rainfall into streamflow depends on the event size. The approach taken was to optimize parameters of a linear delay function and effective rainfall series concurrently from precipitation streamflow data without imposing a functional form of the precipitation...

Applicability of Hydrologic Landscapes for Model Calibration at the Watershed Scale in the Pacific Northwest

EPA Science Inventory

The Pacific Northwest Hydrologic Landscapes (PNW HL) at the assessment unit scale has provided a solid conceptual classification framework to relate and transfer hydrologically meaningful information between watersheds without access to streamflow time series. A collection of tec...

Streamflow loss quantification for groundwater flow modeling using a wading-rod-mounted acoustic Doppler current profiler in a headwater stream

NASA Astrophysics Data System (ADS)

Pflügl, Christian; Hoehn, Philipp; Hofmann, Thilo

2017-04-01

Irrespective of the availability of various field measurement and modeling approaches, the quantification of interactions between surface water and groundwater systems remains associated with high uncertainty. Such uncertainties on stream-aquifer interaction have a high potential to misinterpret the local water budget and water quality significantly. Due to typically considerable temporal variation of stream discharge rates, it is desirable for the measurement of streamflow to reduce the measuring duration while reducing uncertainty. Streamflow measurements, according to the velocity-area method, have been performed along reaches of a losing-disconnected, subalpine headwater stream using a 2-dimensional, wading-rod-mounted acoustic Doppler current profiler (ADCP). The method was chosen, with stream morphology not allowing for boat-mounted setups, to reduce uncertainty compared to conventional, single-point streamflow measurements of similar measurement duration. Reach-averaged stream loss rates were subsequently quantified between 12 cross sections. They enabled the delineation of strongly infiltrating stream reaches and their differentiation from insignificantly infiltrating reaches. Furthermore, a total of 10 near-stream observation wells were constructed and/or equipped with pressure and temperature loggers. The time series of near-stream groundwater temperature data were cross-correlated with stream temperature time series to yield supportive qualitative information on the delineation of infiltrating reaches. Subsequently, as a reference parameterization, the hydraulic conductivity and specific yield of a numerical, steady-state model of groundwater flow, in the unconfined glaciofluvial aquifer adjacent to the stream, were inversely determined incorporating the inferred stream loss rates. Applying synthetic sets of infiltration rates, resembling increasing levels of uncertainty associated with single-point streamflow measurements of comparable duration, the same inversion procedure was run. The volume-weighted mean of the respective parameter distribution within 200 m of stream periphery deviated increasingly from the reference parameterization at increasing deviation of infiltration rates.

From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

2016-02-01

This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the dominant processes associated with different landscape types, and the spatial relations of catchment processes. This article was corrected on 14 MAR 2016. See the end of the full text for details.

HYDRORECESSION: A toolbox for streamflow recession analysis

NASA Astrophysics Data System (ADS)

Arciniega, S.

2015-12-01

Streamflow recession curves are hydrological signatures allowing to study the relationship between groundwater storage and baseflow and/or low flows at the catchment scale. Recent studies have showed that streamflow recession analysis can be quite sensitive to the combination of different models, extraction techniques and parameter estimation methods. In order to better characterize streamflow recession curves, new methodologies combining multiple approaches have been recommended. The HYDRORECESSION toolbox, presented here, is a Matlab graphical user interface developed to analyse streamflow recession time series with the support of different tools allowing to parameterize linear and nonlinear storage-outflow relationships through four of the most useful recession models (Maillet, Boussinesq, Coutagne and Wittenberg). The toolbox includes four parameter-fitting techniques (linear regression, lower envelope, data binning and mean squared error) and three different methods to extract hydrograph recessions segments (Vogel, Brutsaert and Aksoy). In addition, the toolbox has a module that separates the baseflow component from the observed hydrograph using the inverse reservoir algorithm. Potential applications provided by HYDRORECESSION include model parameter analysis, hydrological regionalization and classification, baseflow index estimates, catchment-scale recharge and low-flows modelling, among others. HYDRORECESSION is freely available for non-commercial and academic purposes.

Rainfall-runoff characteristics and effects of increased urban density on streamflow and infiltration in the eastern part of the San Jacinto River basin, Riverside County, California

USGS Publications Warehouse

Guay, Joel R.

2002-01-01

To better understand the rainfall-runoff characteristics of the eastern part of the San Jacinto River Basin and to estimate the effects of increased urbanization on streamflow, channel infiltration, and land-surface infiltration, a long-term (1950?98) time series of monthly flows in and out of the channels and land surfaces were simulated using the Hydrologic Simulation Program- FORTRAN (HSPF) rainfall-runoff model. Channel and land-surface infiltration includes rainfall or runoff that infiltrates past the zone of evapotranspiration and may become ground-water recharge. The study area encompasses about 256 square miles of the San Jacinto River drainage basin in Riverside County, California. Daily streamflow (for periods with available data between 1950 and 1998), and daily rainfall and evaporation (1950?98) data; monthly reservoir storage data (1961?98); and estimated mean annual reservoir inflow data (for 1974 conditions) were used to calibrate the rainfall-runoff model. Measured and simulated mean annual streamflows for the San Jacinto River near San Jacinto streamflow-gaging station (North-South Fork subbasin) for 1950?91 and 1997?98 were 14,000 and 14,200 acre-feet, respectively, a difference of 1.4 percent. The standard error of the mean for measured and simulated annual streamflow in the North-South Fork subbasin was 3,520 and 3,160 acre-feet, respectively. Measured and simulated mean annual streamflows for the Bautista Creek streamflow-gaging station (Bautista Creek subbasin) for 1950?98 were 980 acre-feet and 991 acre-feet, respectively, a difference of 1.1 percent. The standard error of the mean for measured and simulated annual streamflow in the Bautista Creek subbasin was 299 and 217 acre-feet, respectively. Measured and simulated annual streamflows for the San Jacinto River above State Street near San Jacinto streamflow-gaging station (Poppet subbasin) for 1998 were 23,400 and 23,500 acre-feet, respectively, a difference of 0.4 percent. The simulated mean annual streamflow for the State Street gaging station at the outlet of the study basin and the simulated mean annual basin infiltration (combined infiltration from all the channels and land surfaces) were 8,720 and 41,600 acre-feet, respectively, for water years 1950-98. Simulated annual streamflow at the State Street gaging station ranged from 16.8 acre-feet in water year 1961 to 70,400 acre-feet in water year 1993, and simulated basin infiltration ranged from 2,770 acre-feet in water year 1961 to 149,000 acre-feet in water year 1983.The effects of increased urbanization on the hydrology of the study basin were evaluated by increasing the size of the effective impervious and non-effective impervious urban areas simulated in the calibrated rainfall-runoff model by 50 and 100 percent, respectively. The rainfall-runoff model simulated a long-term time series of monthly flows in and out of the channels and land surfaces using daily rainfall and potential evaporation data for water years 1950?98. Increasing the effective impervious and non-effective impervious urban areas by 100 percent resulted in a 5-percent increase in simulated mean annual streamflow at the State Street gaging station, and a 2.2-percent increase in simulated basin infiltration. Results of a frequency analysis of the simulated annual streamflow at the State Street gaging station showed that when effective impervious and non-effective impervious areas were increased 100 percent, simulated annual streamflow increased about 100 percent for low-flow conditions and was unchanged for high-flow conditions. The simulated increase in streamflow at the State Street gaging station potentially could infiltrate along the stream channel further downstream, outside of the model area.

Comparison of two methods for estimating base flow in selected reaches of the South Platte River, Colorado

USGS Publications Warehouse

Capesius, Joseph P.; Arnold, L. Rick

2012-01-01

The Mass Balance results were quite variable over time such that they appeared suspect with respect to the concept of groundwater flow as being gradual and slow. The large degree of variability in the day-to-day and month-to-month Mass Balance results is likely the result of many factors. These factors could include ungaged stream inflows or outflows, short-term streamflow losses to and gains from temporary bank storage, and any lag in streamflow accounting owing to streamflow lag time of flow within a reach. The Pilot Point time series results were much less variable than the Mass Balance results and extreme values were effectively constrained. Less day-to-day variability, smaller magnitude extreme values, and smoother transitions in base-flow estimates provided by the Pilot Point method are more consistent with a conceptual model of groundwater flow being gradual and slow. The Pilot Point method provided a better fit to the conceptual model of groundwater flow and appeared to provide reasonable estimates of base flow.

Evaluating hydrological model performance using information theory-based metrics

USDA-ARS?s Scientific Manuscript database

The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic m...

Streamflow predictions in Alpine Catchments by using artificial neural networks. Application in the Alto Genil Basin (South Spain)

NASA Astrophysics Data System (ADS)

Jimeno-Saez, Patricia; Pegalajar-Cuellar, Manuel; Pulido-Velazquez, David

2017-04-01

This study explores techniques of modeling water inflow series, focusing on techniques of short-term steamflow prediction. An appropriate estimation of streamflow in advance is necessary to anticipate measures to mitigate the impacts and risks related to drought conditions. This study analyzes the prediction of future streamflow of nineteen subbasins in the Alto-Genil basin in Granada (Southeast of Spain). Some of these basin streamflow have an important component of snowmelt due to part of the system is located in Sierra Nevada Mountain Range, the highest mountain of continental Spain. Streamflow prediction models have been calibrated using time series of historical natural streamflows. The available streamflow measurements have been downloaded from several public data sources. These original data have been preprocessed to turn them to the original natural regime, removing the anthropic effects. The missing values in the adopted horizon period to calibrate the prediction models have been estimated by using a Temez hydrological balance model, approaching the snowmelt processes with a hybrid degree day method. In the experimentation, ARIMA models are used as baseline method, and recurrent neural networks ELMAN and nonlinear autoregressive neural network (NAR) to test if the prediction accuracy can be improved. After performing the multiple experiments with these models, non-parametric statistical tests are applied to select the best of these techniques. In the experiments carried out with ARIMA, it is concluded that ARIMA models are not adequate in this case study due to the existence of a nonlinear component that cannot be modeled. Secondly, ELMAN and NAR neural networks with multi-start training is performed with each network structure to deal with the local optimum problem, since in neural network training there is a very strong dependence on the initial weights of the network. The obtained results suggest that both neural networks are efficient for the short term prediction, surpassing the limitations of the ARIMA models and, in general, the experiments showed that NAR networks are the ones with the greatest generalization capability. Therefore, NAR networks are chosen as the starting point for other works, in which we study the streamflow predictions incorporating exogenous variables (as the Snow Cover Area), the sensitivity of the prediction to the initial conditions, multivariate streamflow predictions considering the spatial correlation between the sub-basins streamflow and the synthetic generations to assess droughts statistic. This research has been partially supported by the CGL2013-48424-C2-2-R (MINECO) and the PMAFI/06/14 (UCAM) projects.

Downsizer - A Graphical User Interface-Based Application for Browsing, Acquiring, and Formatting Time-Series Data for Hydrologic Modeling

USGS Publications Warehouse

Ward-Garrison, Christian; Markstrom, Steven L.; Hay, Lauren E.

2009-01-01

The U.S. Geological Survey Downsizer is a computer application that selects, downloads, verifies, and formats station-based time-series data for environmental-resource models, particularly the Precipitation-Runoff Modeling System. Downsizer implements the client-server software architecture. The client presents a map-based, graphical user interface that is intuitive to modelers; the server provides streamflow and climate time-series data from over 40,000 measurement stations across the United States. This report is the Downsizer user's manual and provides (1) an overview of the software design, (2) installation instructions, (3) a description of the graphical user interface, (4) a description of selected output files, and (5) troubleshooting information.

Hydraulic-Geometry Relations for Rivers in Coastal and Central Maine

USGS Publications Warehouse

Dudley, Robert W.

2004-01-01

Hydraulic-geometry relations (curves) were derived for 15 sites on 12 rivers in coastal and central Maine on the basis of site-specific (at-a-station) hydraulic-geometry relations and hydraulic models. At-a-station hydraulic-geometry curves, expressed as well-established power functions, describe the relations between channel geometry, velocity, and flow at a given point on a river. The derived at-a-station hydraulic-geometry curves indicate that, on average, a given increase in flow at a given river cross section in the study area will be nearly equally conveyed by increases in velocity and channel cross-sectional area. Regional curves describing the bankfull streamflow and associated channel geometry as functions of drainage area were derived for use in stream-channel assessment and restoration projects specific to coastal and central Maine. Regional hydraulic-geometry curves were derived by combining hydraulic-geometry information for 15 river cross sections using bankfull flow as the common reference streamflow. The exponents of the derived regional hydraulic-geometry relations indicate that, in the downstream direction, most of the conveyance of increasing contribution of flow is accommodated by an increase in cross-sectional area?with about 50 percent of the increase in flow accommodated by an increase in channel width, and 32 percent by an increase in depth. The remaining 18 percent is accommodated by an increase in streamflow velocity. On an annual-peak-series basis, results of this study indicate that the occurrence of bankfull streamflow for rivers in Maine is more frequent than the 1.5-year streamflow. On a flow-duration basis, bankfull streamflow for rivers in coastal and central Maine is equaled or exceeded approximately 8.1 percent of the time on mean?or about 30 days a year. Bankfull streamflow is roughly three times that of the mean annual streamflow for the sites investigated in this study. Regional climate, snowmelt hydrology, and glacial geology may play important roles in dictating the magnitude and frequency of occurrence of bankfull streamflows observed for rivers in coastal and central Maine.

Monthly streamflow forecasting with auto-regressive integrated moving average

NASA Astrophysics Data System (ADS)

Nasir, Najah; Samsudin, Ruhaidah; Shabri, Ani

2017-09-01

Forecasting of streamflow is one of the many ways that can contribute to better decision making for water resource management. The auto-regressive integrated moving average (ARIMA) model was selected in this research for monthly streamflow forecasting with enhancement made by pre-processing the data using singular spectrum analysis (SSA). This study also proposed an extension of the SSA technique to include a step where clustering was performed on the eigenvector pairs before reconstruction of the time series. The monthly streamflow data of Sungai Muda at Jeniang, Sungai Muda at Jambatan Syed Omar and Sungai Ketil at Kuala Pegang was gathered from the Department of Irrigation and Drainage Malaysia. A ratio of 9:1 was used to divide the data into training and testing sets. The ARIMA, SSA-ARIMA and Clustered SSA-ARIMA models were all developed in R software. Results from the proposed model are then compared to a conventional auto-regressive integrated moving average model using the root-mean-square error and mean absolute error values. It was found that the proposed model can outperform the conventional model.

Spatial patterns of frequent floods in Switzerland

NASA Astrophysics Data System (ADS)

Schneeberger, Klaus; Rössler, Ole; Weingartner, Rolf

2017-04-01

Information about the spatial characteristics of high and extreme streamflow is often needed for an accurate analysis of flood risk and effective co-ordination of flood related activities, such as flood defence planning. In this study we analyse the spatial dependence of frequent floods in Switzerland across different scales. Firstly, we determine the average length of high and extreme flow events for 56 runoff time series of Swiss rivers. Secondly, a dependence measure expressing the probability that streamflow peaks are as high as peaks at a conditional site is used to describe and map the spatial extend of joint occurrence of frequent floods across Switzerland. Thirdly, we apply a cluster analysis to identify groups of sites that are likely to react similarly in terms of joint occurrence of high flow events. The results indicate that a time interval with a length of 3 days seems to be most appropriate to characterise the average length of high streamflow events across spatial scales. In the main Swiss basins, high and extreme streamflows were found to be asymptotically independent. In contrast, at the meso-scale distinct flood regions, which react similarly in terms of occurrence of frequent flood, were found. The knowledge about these regions can help to optimise flood defence planning or to estimate regional flood risk properly.

Trends in selected streamflow and stream-channel characteristics for the Chagrin River at Willoughby, Ohio

USGS Publications Warehouse

Koltun, G.F.; Kunze, Allison E.

2002-01-01

Monotonic upward trends in annual mean streamflows and annual 7-day low flows were identified statistically for the streamflow-gaging station on the Chagrin River at Willoughby, Ohio. No monotonic trends were identified for the annual peak streamflow series or partial-duration series of peak streamflows augmented with annual peak streamflows that did not exceed a base discharge of 4,000 cubic feet per second. A plot of cumulative departure of annual precipitation from the long-term mean annual precipitation for the weather-observation station at Hiram, Ohio, indicates a relatively dry period extending from about 1910 to about 1968, followed by a relatively wet period extending from about 1968 to the late 1990s. A plot of cumulative departure of annual mean streamflow from the mean annual streamflow for the Chagrin River at Willoughby, Ohio, closely mimics the shape of the precipitation departure plot, indicating that the annual mean streamflows increased in concert with annual precipitation. These synchronous trends likely explain why upward trends in annual mean streamflows and annual 7-day low flows were observed. A lack of trend in peak streamflows indicates that the intensity and severity of flood-producing storms did not increase appreciably along with the increases in annual precipitation. An analysis of point-of-zero-flow data indicates that the low-water control of the Chagrin River streamflow-gaging station tended to aggrade over the period 1930?93; however, the magnitude of aggradation is sufficiently small that its effect on stages of moderate to large floods would be negligible. Stage values associated with reference streamflows of 500 and 5,000 cubic feet per second tended to remain fairly stable during the period from about 1950 to 1970 and then decreased slightly during the period from about 1970 to 1980, suggesting that the flood-carrying capacity of the stream increased somewhat during the latter period. Since a large flood on May 26, 1989, significant changes have occurred in the relation between stage and streamflow. The most recent relation indicates that stage values associated with streamflows of 500 and 5,000 cubic feet per second are about 0.5 foot and 0.1 foot higher, respectively, than the pre-1989 levels.

User's manual for the Graphical Constituent Loading Analysis System (GCLAS)

USGS Publications Warehouse

Koltun, G.F.; Eberle, Michael; Gray, J.R.; Glysson, G.D.

2006-01-01

This manual describes the Graphical Constituent Loading Analysis System (GCLAS), an interactive cross-platform program for computing the mass (load) and average concentration of a constituent that is transported in stream water over a period of time. GCLAS computes loads as a function of an equal-interval streamflow time series and an equal- or unequal-interval time series of constituent concentrations. The constituent-concentration time series may be composed of measured concentrations or a combination of measured and estimated concentrations. GCLAS is not intended for use in situations where concentration data (or an appropriate surrogate) are collected infrequently or where an appreciable amount of the concentration values are censored. It is assumed that the constituent-concentration time series used by GCLAS adequately represents the true time-varying concentration. Commonly, measured constituent concentrations are collected at a frequency that is less than ideal (from a load-computation standpoint), so estimated concentrations must be inserted in the time series to better approximate the expected chemograph. GCLAS provides tools to facilitate estimation and entry of instantaneous concentrations for that purpose. Water-quality samples collected for load computation frequently are collected in a single vertical or at single point in a stream cross section. Several factors, some of which may vary as a function of time and (or) streamflow, can affect whether the sample concentrations are representative of the mean concentration in the cross section. GCLAS provides tools to aid the analyst in assessing whether concentrations in samples collected in a single vertical or at single point in a stream cross section exhibit systematic bias with respect to the mean concentrations. In cases where bias is evident, the analyst can construct coefficient relations in GCLAS to reduce or eliminate the observed bias. GCLAS can export load and concentration data in formats suitable for entry into the U.S. Geological Survey's National Water Information System. GCLAS can also import and export data in formats that are compatible with various commonly used spreadsheet and statistics programs.

Influence of groundwater pumping on streamflow restoration following upstream dam removal

USGS Publications Warehouse

Constantz, J.; Essaid, H.

2007-01-01

We compared streamflow in basins under the combined impacts of an upland dam and groundwater pumping withdrawals, by examining streamflow in the presence and absence of each impact. As a qualitative analysis, inter-watersbed streamflow comparisons were performed for several rivers flowing into the east side of the Central Valley, CA. Results suggest that, in the absence of upland dams supporting large reservoirs, some reaches of these rivers might develop ephemeral streamflow in late summer. As a quantitative analysis, we conducted a series of streamflow/ groundwater simulations (using MODFLOW-2000 plus the streamflow routing package, SFR1) for a representative hypothetical watershed, with an upland dam and groundwater pumping in the downstream basin, under humid, semi-arid, and and conditions. As a result of including the impact of groundwater pumping, post-dam removal simulated streamflow was significantly less than natural streamflow. The model predicts extensive ephemeral conditions in the basin during September for both the arid and semi-arid cases. The model predicts continued perennial conditions in the humid case, but spatially weighted, average streamflow of only 71% of natural September streamflow, as a result of continued pumping after dam removal.

Methods used to compute low-flow frequency characteristics for continuous-record streamflow stations in Minnesota, 2006

USGS Publications Warehouse

Winterstein, Thomas A.; Arntson, Allan D.; Mitton, Gregory B.

2007-01-01

The 1-, 7-, and 30-day low-flow series were determined for 120 continuous-record streamflow stations in Minnesota having at least 20 years of continuous record. The 2-, 5-, 10-, 50-, and 100-year statistics were determined for each series by fitting a log Pearson type III distribution to the data. The methods used to determine the low-flow statistics and to construct the plots of the low-flow frequency curves are described. The low-flow series and the low-flow statistics are presented in tables and graphs.

Users Manual for the Geospatial Stream Flow Model (GeoSFM)

USGS Publications Warehouse

Artan, Guleid A.; Asante, Kwabena; Smith, Jodie; Pervez, Md Shahriar; Entenmann, Debbie; Verdin, James P.; Rowland, James

2008-01-01

The monitoring of wide-area hydrologic events requires the manipulation of large amounts of geospatial and time series data into concise information products that characterize the location and magnitude of the event. To perform these manipulations, scientists at the U.S. Geological Survey Center for Earth Resources Observation and Science (EROS), with the cooperation of the U.S. Agency for International Development, Office of Foreign Disaster Assistance (USAID/OFDA), have implemented a hydrologic modeling system. The system includes a data assimilation component to generate data for a Geospatial Stream Flow Model (GeoSFM) that can be run operationally to identify and map wide-area streamflow anomalies. GeoSFM integrates a geographical information system (GIS) for geospatial preprocessing and postprocessing tasks and hydrologic modeling routines implemented as dynamically linked libraries (DLLs) for time series manipulations. Model results include maps that depicting the status of streamflow and soil water conditions. This Users Manual provides step-by-step instructions for running the model and for downloading and processing the input data required for initial model parameterization and daily operation.

Impacts of uncertainties in weather and streamflow observations in calibration and evaluation of an elevation distributed HBV-model

NASA Astrophysics Data System (ADS)

Engeland, K.; Steinsland, I.; Petersen-Øverleir, A.; Johansen, S.

2012-04-01

The aim of this study is to assess the uncertainties in streamflow simulations when uncertainties in both observed inputs (precipitation and temperature) and streamflow observations used in the calibration of the hydrological model are explicitly accounted for. To achieve this goal we applied the elevation distributed HBV model operating on daily time steps to a small catchment in high elevation in Southern Norway where the seasonal snow cover is important. The uncertainties in precipitation inputs were quantified using conditional simulation. This procedure accounts for the uncertainty related to the density of the precipitation network, but neglects uncertainties related to measurement bias/errors and eventual elevation gradients in precipitation. The uncertainties in temperature inputs were quantified using a Bayesian temperature interpolation procedure where the temperature lapse rate is re-estimated every day. The uncertainty in the lapse rate was accounted for whereas the sampling uncertainty related to network density was neglected. For every day a random sample of precipitation and temperature inputs were drawn to be applied as inputs to the hydrologic model. The uncertainties in observed streamflow were assessed based on the uncertainties in the rating curve model. A Bayesian procedure was applied to estimate the probability for rating curve models with 1 to 3 segments and the uncertainties in their parameters. This method neglects uncertainties related to errors in observed water levels. Note that one rating curve was drawn to make one realisation of a whole time series of streamflow, thus the rating curve errors lead to a systematic bias in the streamflow observations. All these uncertainty sources were linked together in both calibration and evaluation of the hydrologic model using a DREAM based MCMC routine. Effects of having less information (e.g. missing one streamflow measurement for defining the rating curve or missing one precipitation station) was also investigated.

Quantifying mountain block recharge by means of catchment-scale storage-discharge relationships

NASA Astrophysics Data System (ADS)

Ajami, Hoori; Troch, Peter A.; Maddock, Thomas, III; Meixner, Thomas; Eastoe, Chris

2011-04-01

Despite the importance of mountainous catchments for providing freshwater resources, especially in semi-arid regions, little is known about key hydrological processes such as mountain block recharge (MBR). Here we implement a data-based method informed by isotopic data to quantify MBR rates using recession flow analysis. We applied our hybrid method in a semi-arid sky island catchment in southern Arizona, United States. Sabino Creek is a 91 km2 catchment with its sources near the summit of the Santa Catalina Mountains northeast of Tucson. Southern Arizona's climate has two distinct wet seasons separated by prolonged dry periods. Winter frontal storms (November-March) provide about 50% of annual precipitation, and summers are dominated by monsoon convective storms from July to September. Isotope analyses of springs and surface water in the Sabino Creek catchment indicate that streamflow during dry periods is derived from groundwater storage in fractured bedrock. Storage-discharge relationships are derived from recession flow analysis to estimate changes in storage during wet periods. To provide reliable estimates, several corrections and improvements to classic base flow recession analysis are considered. These corrections and improvements include adaptive time stepping, data binning, and the choice of storage-discharge functions. Our analysis shows that (1) incorporating adaptive time steps to correct for streamflow measurement errors improves the coefficient of determination, (2) the quantile method is best for streamflow data binning, (3) the choice of the regression model is critical when the stage-discharge function is used to predict changes in bedrock storage beyond the maximum observed flow in the catchment, and (4) the use of daily or night-time hourly streamflow does not affect the form of the storage-discharge relationship but will impact MBR estimates because of differences in the observed range of streamflow in each series.

Technical Manual for the Geospatial Stream Flow Model (GeoSFM)

USGS Publications Warehouse

Asante, Kwabena O.; Artan, Guleid A.; Pervez, Md Shahriar; Bandaragoda, Christina; Verdin, James P.

2008-01-01

The monitoring of wide-area hydrologic events requires the use of geospatial and time series data available in near-real time. These data sets must be manipulated into information products that speak to the location and magnitude of the event. Scientists at the U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center have implemented a hydrologic modeling system which consists of an operational data processing system and the Geospatial Stream Flow Model (GeoSFM). The data processing system generates daily forcing evapotranspiration and precipitation data from various remotely sensed and ground-based data sources. To allow for rapid implementation in data scarce environments, widely available terrain, soil, and land cover data sets are used for model setup and initial parameter estimation. GeoSFM performs geospatial preprocessing and postprocessing tasks as well as hydrologic modeling tasks within an ArcView GIS environment. The integration of GIS routines and time series processing routines is achieved seamlessly through the use of dynamically linked libraries (DLLs) embedded within Avenue scripts. GeoSFM is run operationally to identify and map wide-area streamflow anomalies. Daily model results including daily streamflow and soil water maps are disseminated through Internet map servers, flood hazard bulletins and other media.

Estimating mountain basin-mean precipitation from streamflow using Bayesian inference

NASA Astrophysics Data System (ADS)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Lundquist, Jessica D.

2015-10-01

Estimating basin-mean precipitation in complex terrain is difficult due to uncertainty in the topographical representativeness of precipitation gauges relative to the basin. To address this issue, we use Bayesian methodology coupled with a multimodel framework to infer basin-mean precipitation from streamflow observations, and we apply this approach to snow-dominated basins in the Sierra Nevada of California. Using streamflow observations, forcing data from lower-elevation stations, the Bayesian Total Error Analysis (BATEA) methodology and the Framework for Understanding Structural Errors (FUSE), we infer basin-mean precipitation, and compare it to basin-mean precipitation estimated using topographically informed interpolation from gauges (PRISM, the Parameter-elevation Regression on Independent Slopes Model). The BATEA-inferred spatial patterns of precipitation show agreement with PRISM in terms of the rank of basins from wet to dry but differ in absolute values. In some of the basins, these differences may reflect biases in PRISM, because some implied PRISM runoff ratios may be inconsistent with the regional climate. We also infer annual time series of basin precipitation using a two-step calibration approach. Assessment of the precision and robustness of the BATEA approach suggests that uncertainty in the BATEA-inferred precipitation is primarily related to uncertainties in hydrologic model structure. Despite these limitations, time series of inferred annual precipitation under different model and parameter assumptions are strongly correlated with one another, suggesting that this approach is capable of resolving year-to-year variability in basin-mean precipitation.

Impact of Different Time Series Streamflow Data on Energy Generation of a Run-of-River Hydropower Plant

NASA Astrophysics Data System (ADS)

Kentel, E.; Cetinkaya, M. A.

2013-12-01

Global issues such as population increase, power supply crises, oil prices, social and environmental concerns have been forcing countries to search for alternative energy sources such as renewable energy to satisfy the sustainable development goals. Hydropower is the most common form of renewable energy in the world. Hydropower does not require any fuel, produces relatively less pollution and waste and it is a reliable energy source with relatively low operating cost. In order to estimate the average annual energy production of a hydropower plant, sufficient and dependable streamflow data is required. The goal of this study is to investigate impact of streamflow data on annual energy generation of Balkusan HEPP which is a small run-of-river hydropower plant at Karaman, Turkey. Two different stream gaging stations are located in the vicinity of Balkusan HEPP and these two stations have different observation periods: one from 1986 to 2004 and the other from 2000 to 2009. These two observation periods show different climatic characteristics. Thus, annual energy estimations based on data from these two different stations differ considerably. Additionally, neither of these stations is located at the power plant axis, thus streamflow observations from these two stream gaging stations need to be transferred to the plant axis. This requirement introduces further errors into energy estimations. Impact of different streamflow data and transfer of streamflow observations to plant axis on annual energy generation of a small hydropower plant is investigated in this study.

Unorganized machines for seasonal streamflow series forecasting.

PubMed

Siqueira, Hugo; Boccato, Levy; Attux, Romis; Lyra, Christiano

2014-05-01

Modern unorganized machines--extreme learning machines and echo state networks--provide an elegant balance between processing capability and mathematical simplicity, circumventing the difficulties associated with the conventional training approaches of feedforward/recurrent neural networks (FNNs/RNNs). This work performs a detailed investigation of the applicability of unorganized architectures to the problem of seasonal streamflow series forecasting, considering scenarios associated with four Brazilian hydroelectric plants and four distinct prediction horizons. Experimental results indicate the pertinence of these models to the focused task.

Reinforced two-step-ahead weight adjustment technique for online training of recurrent neural networks.

PubMed

Chang, Li-Chiu; Chen, Pin-An; Chang, Fi-John

2012-08-01

A reliable forecast of future events possesses great value. The main purpose of this paper is to propose an innovative learning technique for reinforcing the accuracy of two-step-ahead (2SA) forecasts. The real-time recurrent learning (RTRL) algorithm for recurrent neural networks (RNNs) can effectively model the dynamics of complex processes and has been used successfully in one-step-ahead forecasts for various time series. A reinforced RTRL algorithm for 2SA forecasts using RNNs is proposed in this paper, and its performance is investigated by two famous benchmark time series and a streamflow during flood events in Taiwan. Results demonstrate that the proposed reinforced 2SA RTRL algorithm for RNNs can adequately forecast the benchmark (theoretical) time series, significantly improve the accuracy of flood forecasts, and effectively reduce time-lag effects.

Changes in the lower boundary condition of water fluxes in the NOAH land surface scheme

NASA Astrophysics Data System (ADS)

Lohmann, D.; Peters-Lidard, C. D.

2002-05-01

One problem with current land surface schemes (LSS) used in weather prediction and climate models is their inabilty to reproduce streamflow in large river basins. This can be attributed to the weak representation of their upper (infiltration) and lower (baseflow) boundary conditions in their water balance / transport equations. Operational (traditional) hydrological models, which operate on the same spatial scale as a LSS, on the other hand, are able to reproduce streamflow time series. Their infiltration and baseflow equations are often empirically based and therefore have been neglected by the LSS community. It must be argued that we need to include a better representation of long time scales (as represented by groundwater and baseflow) into the current LSS to make valuable predictions of streamflow and water resources. This talk concentrates on the lower boundary condition of water fluxes within LSS. It reviews briefly previous attempts to incorporate groundwater and more realistic lower boundary conditions into LSS and summarizes the effect on the runoff (baseflow) production time scales as compared to currently used lower boundary conditions in LSS. The NOAH - LSM in the LDAS and DMIP setting is used to introduce a simplified groundwater model, based on the linearized Boussinesq equation, and the TOPMODEL. The NOAH - LSM will be coupled to a linear routing model to investigate the effects of the new lower boundary condition on the water balance (in particular, streamflow) in small to medium sized catchments in the LDAS / DMIP domain.

Trends in timing, magnitude, and duration of summer and fall/winter streamflows for unregulated coastal river basins in Maine during the 20th century

USGS Publications Warehouse

Dudley, Robert W.; Hodgkins, Glenn A.

2005-01-01

The U.S. Geological Survey (USGS), in cooperation with the Maine Atlantic Salmon Commission (ASC), began a study in 2003 to examine the timing, magnitude, and duration of summer (June through October) and fall/early winter (September through January) seasonal streamflows of unregulated coastal river basins in Maine and to correlate them to meteorological variables and winter/spring (January through May) seasonal streamflows. This study overlapped the summer seasonal window with the fall/early winter seasonal window to completely bracket the low-streamflow period during July, August, and September between periods of high streamflows in June and October. The ASC is concerned with the impacts of potentially changing meteorological and hydrologic conditions on Atlantic salmon survival. Because winter/spring high streamflows appear to have trended toward earlier dates over the 20th century in coastal Maine, it was hypothesized that the spring/summer recession to low streamflows could have a similar trend toward earlier, and possibly lower, longer lasting, late summer/early fall low streamflows during the 20th century. There were few statistically significant trends in the timing, magnitude, or duration of summer low streamflows for coastal river basins in Maine during the 20th century. The hypothesis that earlier winter/spring high streamflows may result in earlier or lower low streamflows is not supported by the data. No statistically significant trends in the magnitude of total runoff volume during the low-streamflow months of August and September were observed. The magnitude and timing of summer low streamflows correlated with the timing of fall/winter high streamflows and the amount of summer precipitation. The magnitude and timing of summer low streamflows did not correlate with the timing of spring snowmelt runoff. There were few correlations between the magnitude and timing of summer low streamflows and monthly mean surface air temperatures. There were few statistically significant trends in the timing or duration of fall/winter high streamflows for coastal river basins in Maine during the 20th century. The timing of the bulk of fall/winter high streamflows correlated with seasonal precipitation. Earlier fall/winter center-of-volume dates correlated with higher September and October precipitation. In general, little evidence was observed of trends in the magnitude of seasonal runoff volume during fall/winter. The magnitude of fall/winter high streamflows positively correlated with November and December precipitation amounts. There were few correlations between the magnitude and timing of fall/winter high streamflows and monthly mean surface air temperatures.

Daily Streamflow Predictions in an Ungauged Watershed in Northern California Using the Precipitation-Runoff Modeling System (PRMS): Calibration Challenges when nearby Gauged Watersheds are Hydrologically Dissimilar

NASA Astrophysics Data System (ADS)

Dhakal, A. S.; Adera, S.

2017-12-01

Accurate daily streamflow prediction in ungauged watersheds with sparse information is challenging. The ability of a hydrologic model calibrated using nearby gauged watersheds to predict streamflow accurately depends on hydrologic similarities between the gauged and ungauged watersheds. This study examines daily streamflow predictions using the Precipitation-Runoff Modeling System (PRMS) for the largely ungauged San Antonio Creek watershed, a 96 km2 sub-watershed of the Alameda Creek watershed in Northern California. The process-based PRMS model is being used to improve the accuracy of recent San Antonio Creek streamflow predictions generated by two empirical methods. Although San Antonio Creek watershed is largely ungauged, daily streamflow data exists for hydrologic years (HY) 1913 - 1930. PRMS was calibrated for HY 1913 - 1930 using streamflow data, modern-day land use and PRISM precipitation distribution, and gauged precipitation and temperature data from a nearby watershed. The PRMS model was then used to generate daily streamflows for HY 1996-2013, during which the watershed was ungauged, and hydrologic responses were compared to two nearby gauged sub-watersheds of Alameda Creek. Finally, the PRMS-predicted daily flows between HY 1996-2013 were compared to the two empirically-predicted streamflow time series: (1) the reservoir mass balance method and (2) correlation of historical streamflows from 80 - 100 years ago between San Antonio Creek and a nearby sub-watershed located in Alameda Creek. While the mass balance approach using reservoir storage and transfers is helpful for estimating inflows to the reservoir, large discrepancies in daily streamflow estimation can arise. Similarly, correlation-based predicted daily flows which rely on a relationship from flows collected 80-100 years ago may not represent current watershed hydrologic conditions. This study aims to develop a method of streamflow prediction in the San Antonio Creek watershed by examining PRMS's model outputs as well as empirically generated flow data for their use in water resources management decisions. PRMS is also being used to better understand the streamflow patterns in the San Antonio Creek watershed for a variety of antecedent soil moisture conditions as the creek is generally dry between late Spring and early Fall.

Progress report on daily flow-routing simulation for the Carson River, California and Nevada

USGS Publications Warehouse

Hess, G.W.

1996-01-01

A physically based flow-routing model using Hydrological Simulation Program-FORTRAN (HSPF) was constructed for modeling streamflow in the Carson River at daily time intervals as part of the Truckee-Carson Program of the U.S. Geological Survey (USGS). Daily streamflow data for water years 1978-92 for the mainstem river, tributaries, and irrigation ditches from the East Fork Carson River near Markleeville and West Fork Carson River at Woodfords down to the mainstem Carson River at Fort Churchill upstream from Lahontan Reservoir were obtained from several agencies and were compiled into a comprehensive data base. No previous physically based flow-routing model of the Carson River has incorporated multi-agency streamflow data into a single data base and simulated flow at a daily time interval. Where streamflow data were unavailable or incomplete, hydrologic techniques were used to estimate some flows. For modeling purposes, the Carson River was divided into six segments, which correspond to those used in the Alpine Decree that governs water rights along the river. Hydraulic characteristics were defined for 48 individual stream reaches based on cross-sectional survey data obtained from field surveys and previous studies. Simulation results from the model were compared with available observed and estimated streamflow data. Model testing demonstrated that hydraulic characteristics of the Carson River are adequately represented in the models for a range of flow regimes. Differences between simulated and observed streamflow result mostly from inadequate data characterizing inflow and outflow from the river. Because irrigation return flows are largely unknown, irrigation return flow percentages were used as a calibration parameter to minimize differences between observed and simulated streamflows. Observed and simulated streamflow were compared for daily periods for the full modeled length of the Carson River and for two major subreaches modeled with more detailed input data. Hydrographs and statistics presented in this report describe these differences. A sensitivity analysis of four estimated components of the hydrologic system evaluated which components were significant in the model. Estimated ungaged tributary streamflow is not a significant component of the model during low runoff, but is significant during high runoff. The sensitivity analysis indicates that changes in the estimated irrigation diversion and estimated return flow creates a noticeable change in the statistics. The modeling for this study is preliminary. Results of the model are constrained by current availability and accuracy of observed hydrologic data. Several inflows and outflows of the Carson River are not described by time-series data and therefore are not represented in the model.

High salmon density and low discharge create periodic hypoxia in coastal rivers

Treesearch

Christopher J. Sergeant; J. Ryan Bellmore; Casey McConnell; Jonathan W. Moore

2017-01-01

Dissolved oxygen (DO) is essential to the survival of almost all aquatic organisms. Here, we examine the possibility that abundant Pacific salmon (Oncorhynchus spp.) and low streamflow combine to create hypoxic events in coastal rivers. Using high-frequency DO time series from two similar watersheds in southeastern Alaska, we summarize DO regimes...

Stochastic Watershed Models for Risk Based Decision Making

NASA Astrophysics Data System (ADS)

Vogel, R. M.

2017-12-01

Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

Assessing uncertainties in superficial water provision by different bootstrap-based techniques

NASA Astrophysics Data System (ADS)

Rodrigues, Dulce B. B.; Gupta, Hoshin V.; Mendiondo, Eduardo Mario

2014-05-01

An assessment of water security can incorporate several water-related concepts, characterizing the interactions between societal needs, ecosystem functioning, and hydro-climatic conditions. The superficial freshwater provision level depends on the methods chosen for 'Environmental Flow Requirement' estimations, which integrate the sources of uncertainty in the understanding of how water-related threats to aquatic ecosystem security arise. Here, we develop an uncertainty assessment of superficial freshwater provision based on different bootstrap techniques (non-parametric resampling with replacement). To illustrate this approach, we use an agricultural basin (291 km2) within the Cantareira water supply system in Brazil monitored by one daily streamflow gage (24-year period). The original streamflow time series has been randomly resampled for different times or sample sizes (N = 500; ...; 1000), then applied to the conventional bootstrap approach and variations of this method, such as: 'nearest neighbor bootstrap'; and 'moving blocks bootstrap'. We have analyzed the impact of the sampling uncertainty on five Environmental Flow Requirement methods, based on: flow duration curves or probability of exceedance (Q90%, Q75% and Q50%); 7-day 10-year low-flow statistic (Q7,10); and presumptive standard (80% of the natural monthly mean ?ow). The bootstrap technique has been also used to compare those 'Environmental Flow Requirement' (EFR) methods among themselves, considering the difference between the bootstrap estimates and the "true" EFR characteristic, which has been computed averaging the EFR values of the five methods and using the entire streamflow record at monitoring station. This study evaluates the bootstrapping strategies, the representativeness of streamflow series for EFR estimates and their confidence intervals, in addition to overview of the performance differences between the EFR methods. The uncertainties arisen during EFR methods assessment will be propagated through water security indicators referring to water scarcity and vulnerability, seeking to provide meaningful support to end-users and water managers facing the incorporation of uncertainties in the decision making process.

Linking Statistically- and Physically-Based Models for Improved Streamflow Simulation in Gaged and Ungaged Areas

NASA Astrophysics Data System (ADS)

Lafontaine, J.; Hay, L.; Archfield, S. A.; Farmer, W. H.; Kiang, J. E.

2014-12-01

The U.S. Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the continental US. The portion of the NHM located within the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) is being used to test the feasibility of improving streamflow simulations in gaged and ungaged watersheds by linking statistically- and physically-based hydrologic models. The GCPO LCC covers part or all of 12 states and 5 sub-geographies, totaling approximately 726,000 km2, and is centered on the lower Mississippi Alluvial Valley. A total of 346 USGS streamgages in the GCPO LCC region were selected to evaluate the performance of this new calibration methodology for the period 1980 to 2013. Initially, the physically-based models are calibrated to measured streamflow data to provide a baseline for comparison. An enhanced calibration procedure then is used to calibrate the physically-based models in the gaged and ungaged areas of the GCPO LCC using statistically-based estimates of streamflow. For this application, the calibration procedure is adjusted to address the limitations of the statistically generated time series to reproduce measured streamflow in gaged basins, primarily by incorporating error and bias estimates. As part of this effort, estimates of uncertainty in the model simulations are also computed for the gaged and ungaged watersheds.

Identification of potential impacts of climate change and anthropogenic activities on streamflow alterations in the Tarim River Basin, China.

PubMed

Xue, Lianqing; Yang, Fan; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Chi, Yixia; Yang, Guang

2017-08-15

Understanding contributions of climate change and human activities to changes in streamflow is important for sustainable management of water resources in an arid area. This study presents quantitative analysis of climatic and anthropogenic factors to streamflow alteration in the Tarim River Basin (TRB) using the double mass curve method (DMC) and the Budyko methods. The time series (1960~2015) are divided into three periods: the prior impacted period (1960~1972) and the two post impacted periods, 1973~1986 and 1987~2015 with trend analysis. Our results suggest that human activities played a dominant role in deduction in the streamflow in TRB with contribution of 144.6% to 120.68% during the post impacted period I and 228.68% to 140.38% during the post impacted period II. Climatic variables accounted for 20.68%~44.6% of the decrease during the post impacted period I and 40.38% ~128.68% during the post impacted period II. Sensitivity analysis indicates that the streamflow alteration was most sensitive to changes in landscape parameters. The aridity index and all the elasticities showed an obvious increasing trend from the upstream to the downstream in the TRB. Our study suggests that it is important to take effective measures for sustainable development of eco-hydrological and socio-economic systems in the TRB.

From Points to Patterns - Functional Relations between Groundwater Connectivity and Catchment-scale Streamflow Response

NASA Astrophysics Data System (ADS)

Rinderer, M.; McGlynn, B. L.; van Meerveld, I. H. J.

2016-12-01

Groundwater measurements can help us to improve our understanding of runoff generation at the catchment-scale but typically only provide point-scale data. These measurements, therefore, need to be interpolated or upscaled in order to obtain information about catchment scale groundwater dynamics. Our approach used data from 51 spatially distributed groundwater monitoring sites in a Swiss pre-alpine catchment and time series clustering to define six groundwater response clusters. Each of the clusters was characterized by distinctly different site characteristics (i.e., Topographic Wetness Index and curvature), which allowed us to assign all unmonitored locations to one of these clusters. Time series modeling and the definition of response thresholds (i.e., the depth of more transmissive soil layers) allowed us to derive maps of the spatial distribution of active (i.e., responding) locations across the catchment at 15 min time intervals. Connectivity between all active locations and the stream network was determined using a graph theory approach. The extent of the active and connected areas differed during events and suggests that not all active locations directly contributed to streamflow. Gate keeper sites prevented connectivity of upslope locations to the channel network. Streamflow dynamics at the catchment outlet were correlated to catchment average connectivity dynamics. In a sensitivity analysis we tested six different groundwater levels for a site to be considered "active", which showed that the definition of the threshold did not significantly influence the conclusions drawn from our analysis. This study is the first one to derive patterns of groundwater dynamics based on empirical data (rather than interpolation) and provides insight into the spatio-temporal evolution of the active and connected runoff source areas at the catchment-scale that is critical to understanding the dynamics of water quantity and quality in streams.

Analysis of stochastic characteristics of the Benue River flow process

NASA Astrophysics Data System (ADS)

Otache, Martins Y.; Bakir, Mohammad; Li, Zhijia

2008-05-01

Stochastic characteristics of the Benue River streamflow process are examined under conditions of data austerity. The streamflow process is investigated for trend, non-stationarity and seasonality for a time period of 26 years. Results of trend analyses with Mann-Kendall test show that there is no trend in the annual mean discharges. Monthly flow series examined with seasonal Kendall test indicate the presence of positive change in the trend for some months, especially the months of August, January, and February. For the stationarity test, daily and monthly flow series appear to be stationary whereas at 1%, 5%, and 10% significant levels, the stationarity alternative hypothesis is rejected for the annual flow series. Though monthly flow appears to be stationary going by this test, because of high seasonality, it could be said to exhibit periodic stationarity based on the seasonality analysis. The following conclusions are drawn: (1) There is seasonality in both the mean and variance with unimodal distribution. (2) Days with high mean also have high variance. (3) Skewness coefficients for the months within the dry season period are greater than those of the wet season period, and seasonal autocorrelations for streamflow during dry season are generally larger than those of the wet season. Precisely, they are significantly different for most of the months. (4) The autocorrelation functions estimated “over time” are greater in the absolute value for data that have not been deseasonalised but were initially normalised by logarithmic transformation only, while autocorrelation functions for i = 1, 2, ..., 365 estimated “over realisations” have their coefficients significantly different from other coefficients.

Simulation of the Quantity, Variability, and Timing of Streamflow in the Dennys River Basin, Maine, by Use of a Precipitation-Runoff Watershed Model

USGS Publications Warehouse

Dudley, Robert W.

2008-01-01

The U.S. Geological Survey (USGS), in cooperation with the Maine Department of Marine Resources Bureau of Sea Run Fisheries and Habitat, began a study in 2004 to characterize the quantity, variability, and timing of streamflow in the Dennys River. The study included a synoptic summary of historical streamflow data at a long-term streamflow gage, collecting data from an additional four short-term streamflow gages, and the development and evaluation of a distributed-parameter watershed model for the Dennys River Basin. The watershed model used in this investigation was the USGS Precipitation-Runoff Modeling System (PRMS). The Geographic Information System (GIS) Weasel was used to delineate the Dennys River Basin and subbasins and derive parameters for their physical geographic features. Calibration of the models used in this investigation involved a four-step procedure in which model output was evaluated against four calibration data sets using computed objective functions for solar radiation, potential evapotranspiration, annual and seasonal water budgets, and daily streamflows. The calibration procedure involved thousands of model runs and was carried out using the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The SCE method reliably produces satisfactory solutions for large, complex optimization problems. The primary calibration effort went into the Dennys main stem watershed model. Calibrated parameter values obtained for the Dennys main stem model were transferred to the Cathance Stream model, and a similar four-step SCE calibration procedure was performed; this effort was undertaken to determine the potential to transfer modeling information to a nearby basin in the same region. The calibrated Dennys main stem watershed model performed with Nash-Sutcliffe efficiency (NSE) statistic values for the calibration period and evaluation period of 0.79 and 0.76, respectively. The Cathance Stream model had an NSE value of 0.68. The Dennys River Basin models make use of limited streamflow-gaging station data and provide information to characterize subbasin hydrology. The calibrated PRMS watershed models of the Dennys River Basin provide simulated daily streamflow time series from October 1, 1985, through September 30, 2006, for nearly any location within the basin. These models enable natural-resources managers to characterize the timing and quantity of water moving through the basin to support many endeavors including geochemical calculations, water-use assessment, Atlantic salmon population dynamics and migration modeling, habitat modeling and assessment, and other resource-management scenario evaluations. Characterizing streamflow contributions from subbasins in the basin and the relative amounts of surface- and ground-water contributions to streamflow throughout the basin will lead to a better understanding of water quantity and quality in the basin. Improved water-resources information will support Atlantic salmon protection efforts.

The cumulative effects of forest disturbance and climate variability on streamflow components in a large forest-dominated watershed

NASA Astrophysics Data System (ADS)

Li, Qiang; Wei, Xiaohua; Zhang, Mingfang; Liu, Wenfei; Giles-Hansen, Krysta; Wang, Yi

2018-02-01

Assessing how forest disturbance and climate variability affect streamflow components is critical for watershed management, ecosystem protection, and engineering design. Previous studies have mainly evaluated the effects of forest disturbance on total streamflow, rarely with attention given to its components (e.g., base flow and surface runoff), particularly in large watersheds (>1000 km2). In this study, the Upper Similkameen River watershed (1810 km2), an international watershed situated between Canada and the USA, was selected to examine how forest disturbance and climate variability interactively affect total streamflow, baseflow, and surface runoff. Baseflow was separated using a combination of the recursive digital filter method and conductivity mass balance method. Time series analysis and modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to each streamflow component. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were 113.3 ± 35.6 mm year-1 and 0.27 for 1954-2013, respectively. Forest disturbance increased annual streamflow, baseflow, and surface runoff of 27.7 ± 13.7 mm, 7.4 ± 3.6 mm, and 18.4 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 27.0 ± 23.0%, 29.2 ± 23.1%, and 25.7 ± 23.4%, respectively. In contrast, climate variability decreased them by 74.9 ± 13.7 mm, 17.9 ± 3.6 mm, and 53.3 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 73.0 ± 23.0%, 70.8 ± 23.1% and 73.1 ± 23.4%, respectively. Despite working in opposite ways, the impacts of climate variability on annual streamflow, baseflow, and surface runoff were of a much greater magnitude than forest disturbance impacts. This study has important implications for the protection of aquatic habitat, engineering design, and watershed planning in the context of future forest disturbance and climate change.

Estimates of natural streamflow at two streamgages on the Esopus Creek, New York, water years 1932 to 2012

USGS Publications Warehouse

Burns, Douglas A.; Gazoorian, Christopher L.

2015-01-01

Natural discharge at the Mount Marion streamgage was estimated by summing the natural discharge estimated for the Coldbrook streamgage and the discharge estimated for the intervening basin area through application of the New York Streamflow Estimation Tool, recently developed for estimating unaltered streamflow at ungaged locations in the State. Estimates of natural daily discharge at the Mount Marion streamgage were about three times greater than gaged daily discharge throughout the moderate- to low-flow range from October 1, 1970, to September 30, 2012, the period of record for full water years at this streamgage. The relative difference between the two discharge time series declined as flow increased beyond the moderate range, but gaged daily discharge was still 25 to 43 percent less than estimated natural daily discharge for the high-flow metrics calculated in this analysis, and the mean relative difference was 43 percent for the annual 1-day maximum discharge. Overall, these estimates of natural discharge reflect the absence of effects of the Shandaken Tunnel and Ashokan Reservoir on flows in the Esopus Creek over broad time frames. However, caution is warranted if one is attempting to apply the natural estimates at short time scales because the regression prediction intervals indicate that uncertainty at a daily time step ranges from about 40 to 80 percent.

Long-term effects of climate and land cover change on freshwater provision in the tropical Andes

NASA Astrophysics Data System (ADS)

Molina, A.; Vanacker, V.; Brisson, E.; Mora, D.; Balthazar, V.

2015-06-01

Andean headwater catchments play a pivotal role to supply fresh water for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes. In this paper, we assess multi-decadal change in freshwater provision based on long time series (1974-2008) of hydrometeorological data and land cover reconstructions for a 282 km2 catchment located in the tropical Andes. Three main land cover change trajectories can be distinguished: (1) rapid decline of native vegetation in montane forest and páramo ecosystems in ~1/5 or 20% of the catchment area, (2) expansion of agricultural land by 14% of the catchment area, (3) afforestation of 12% of native páramo grasslands with exotic tree species in recent years. Given the strong temporal variability of precipitation and streamflow data related to El Niño-Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow that exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term climate change but very likely result from direct anthropogenic disturbances after land cover change. Partial water budgets for montane cloud forest and páramo ecosystems suggest that the strongest changes in evaporative water losses are observed in páramo ecosystems, where progressive colonization and afforestation of high alpine grasslands leads to a strong increase in transpiration losses.

Using 3D dynamic cartography and hydrological modelling for linear streamflow mapping

NASA Astrophysics Data System (ADS)

Drogue, G.; Pfister, L.; Leviandier, T.; Humbert, J.; Hoffmann, L.; El Idrissi, A.; Iffly, J.-F.

2002-10-01

This paper presents a regionalization methodology and an original representation of the downstream variation of daily streamflow using a conceptual rainfall-runoff model (HRM) and the 3D visualization tools of the GIS ArcView. The regionalization of the parameters of the HRM model was obtained by fitting simultaneously the runoff series from five sub-basins of the Alzette river basin (Grand-Duchy of Luxembourg) according to the permeability of geological formations. After validating the transposability of the regional parameter values on five test basins, streamflow series were simulated with the model at ungauged sites in one medium size geologically contrasted test basin and interpolated assuming a linear increase of streamflow between modelling points. 3D spatio-temporal cartography of mean annual and high raw and specific discharges are illustrated. During a severe flooding, the propagation of the flood waves in the different parts of the stream network shows an important contribution of sub-basins lying on impervious geological formations (direct runoff) compared with those including permeable geological formations which have a more contrasted hydrological response. The effect of spatial variability of rainfall is clearly perceptible.

21st Century Projections of High Streamflow Events in the UK and Germany

NASA Astrophysics Data System (ADS)

Cioffi, Francesco; Rosario Conticello, Federico; Lall, Upmanu; Merz, Bruno

2017-04-01

Radiative effects of anthropogenic changes in atmospheric composition are expected to enhance the hydrological cycle leading to more frequent and intense floods. To explore if there will be an increased risk of river flooding in the future, 21st century projections under global warming scenarios of High Streamflow Events (HSEs) for UK and German rivers are carried out, using a model that statistically relates large-scale atmospheric predictors - 850 hPa Geopotential Height (GPH850) and Integrated Water Vapor Transport (IVT) - to the occurrence of HSEs in one or simultaneously in several streamflow gauges. Here, HSE is defined as the streamflow exceeding the 99th percentile of daily flowrate time series measured at streamflow gauges. For the common period 1960-2012, historical data from 57 streamflow gauges in UK and 61 streamflow gauges in Germany, as well as, reanalysis data of GPH850 and IVT fields, bounded from 90W to 70E and from 20N to 80N are used. The link between GPH850 configurations and HSEs, and more precisely, identification of the GPH850 states potentially able to generate HSEs, is performed by a combined Kohonen Networks (Self Organized Map, SOM) and Event Syncronization approach. Complex network and modularity methods are used to cluster streamflow gauges that share common GPH850 configurations. Then a model based on a conditional Poisson distribution, in which the parameter of the Poisson distribution is assumed to be a nonlinear function of GPH850 and IVT, allows for the identification of GPH850 state and threshold of IVT beyond which there is the HSE highest probability. Using that model, projections of 21st century changes in frequency of HSEs occurrence in UK and Germany are estimated using the simulated fields of GPH850 and IVT from selected GCMs belonging to the Coupled Model Inter-comparison Project Phase 5 (CMIP5). Among the different GCMs, those are selected whose retrospective predictor fields have consistent statistics with the corresponding reanalysis data.

Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China

NASA Astrophysics Data System (ADS)

Fang, G. H.; Yang, J.; Chen, Y. N.; Zammit, C.

2015-06-01

Water resources are essential to the ecosystem and social economy in the desert and oasis of the arid Tarim River basin, northwestern China, and expected to be vulnerable to climate change. It has been demonstrated that regional climate models (RCMs) provide more reliable results for a regional impact study of climate change (e.g., on water resources) than general circulation models (GCMs). However, due to their considerable bias it is still necessary to apply bias correction before they are used for water resources research. In this paper, after a sensitivity analysis on input meteorological variables based on the Sobol' method, we compared five precipitation correction methods and three temperature correction methods in downscaling RCM simulations applied over the Kaidu River basin, one of the headwaters of the Tarim River basin. Precipitation correction methods applied include linear scaling (LS), local intensity scaling (LOCI), power transformation (PT), distribution mapping (DM) and quantile mapping (QM), while temperature correction methods are LS, variance scaling (VARI) and DM. The corrected precipitation and temperature were compared to the observed meteorological data, prior to being used as meteorological inputs of a distributed hydrologic model to study their impacts on streamflow. The results show (1) streamflows are sensitive to precipitation, temperature and solar radiation but not to relative humidity and wind speed; (2) raw RCM simulations are heavily biased from observed meteorological data, and its use for streamflow simulations results in large biases from observed streamflow, and all bias correction methods effectively improved these simulations; (3) for precipitation, PT and QM methods performed equally best in correcting the frequency-based indices (e.g., standard deviation, percentile values) while the LOCI method performed best in terms of the time-series-based indices (e.g., Nash-Sutcliffe coefficient, R2); (4) for temperature, all correction methods performed equally well in correcting raw temperature; and (5) for simulated streamflow, precipitation correction methods have more significant influence than temperature correction methods and the performances of streamflow simulations are consistent with those of corrected precipitation; i.e., the PT and QM methods performed equally best in correcting flow duration curve and peak flow while the LOCI method performed best in terms of the time-series-based indices. The case study is for an arid area in China based on a specific RCM and hydrologic model, but the methodology and some results can be applied to other areas and models.

Estimation of streamflow response to wildfire and salvage logging in a snow-dominated catchment using a model-based change detection approach

NASA Astrophysics Data System (ADS)

Moore, R. D.; Mahrlein, M.; Chuang, Y. C. M.

2016-12-01

Forest cover changes associated with natural disturbance and forest management can have significant influences on the magnitude and timing of streamflow. This study quantified the effect of a wildfire that burned over 60% of the catchment of Fishtrap Creek in the southern interior of British Columbia in August 2003. Fishtrap Creek has been gauged from 1970 to present. The catchment drains 158 km2 at the gauging station and has a snow-dominated hydrologic regime. In 2006, about one-third of the burned area was salvage logged. A semi-distributed hydrologic model was calibrated and tested using the pre-fire streamflow data. Simulated daily streamflow based on the "best" parameter set, and assuming pre-fire forest cover, was used as a "virtual" control in a paired-catchment analysis. Each year was divided into 73 five-day periods (pentads), and separate pre-fire regressions were fit for each of the 73 pentad time series. This approach avoids issues with autocorrelation and can address seasonally varying model bias. Statistically significant increases in streamflow were detected in late winter and through the month of April, with no evidence for increased peak flows, which is inferred to reflect a de-synchronization of snowmelt between disturbed and undisturbed areas of the catchment. The results of the model-based change detection are consistent with statistical analyses using climatic variables as covariates, but have the advantage of providing more temporal detail. However, the power of the change detection can be limited by insufficiently long records of streamflow and driving weather variables for both the pre- and post-fire periods and model structural errors (e.g., an inability to reproduce winter baseflow). An interesting side result of the study was the identification of parameter uncertainty associated with uncertainty regarding forest cover during the calibration period.

Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection

PubMed Central

Kirchner, James W.; Neal, Colin

2013-01-01

The chemical dynamics of lakes and streams affect their suitability as aquatic habitats and as water supplies for human needs. Because water quality is typically monitored only weekly or monthly, however, the higher-frequency dynamics of stream chemistry have remained largely invisible. To illuminate a wider spectrum of water quality dynamics, rainfall and streamflow were sampled in two headwater catchments at Plynlimon, Wales, at 7-h intervals for 1–2 y and weekly for over two decades, and were analyzed for 45 solutes spanning the periodic table from H+ to U. Here we show that in streamflow, all 45 of these solutes, including nutrients, trace elements, and toxic metals, exhibit fractal 1/fα scaling on time scales from hours to decades (α = 1.05 ± 0.15, mean ± SD). We show that this fractal scaling can arise through dispersion of random chemical inputs distributed across a catchment. These 1/f time series are non–self-averaging: monthly, yearly, or decadal averages are approximately as variable, one from the next, as individual measurements taken hours or days apart, defying naive statistical expectations. (By contrast, stream discharge itself is nonfractal, and self-averaging on time scales of months and longer.) In the solute time series, statistically significant trends arise much more frequently, on all time scales, than one would expect from conventional t statistics. However, these same trends are poor predictors of future trends—much poorer than one would expect from their calculated uncertainties. Our results illustrate how 1/f time series pose fundamental challenges to trend analysis and change detection in environmental systems. PMID:23842090

Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection

NASA Astrophysics Data System (ADS)

Kirchner, James W.; Neal, Colin

2013-07-01

The chemical dynamics of lakes and streams affect their suitability as aquatic habitats and as water supplies for human needs. Because water quality is typically monitored only weekly or monthly, however, the higher-frequency dynamics of stream chemistry have remained largely invisible. To illuminate a wider spectrum of water quality dynamics, rainfall and streamflow were sampled in two headwater catchments at Plynlimon, Wales, at 7-h intervals for 1-2 y and weekly for over two decades, and were analyzed for 45 solutes spanning the periodic table from H+ to U. Here we show that in streamflow, all 45 of these solutes, including nutrients, trace elements, and toxic metals, exhibit fractal 1/fα scaling on time scales from hours to decades (α = 1.05 ± 0.15, mean ± SD). We show that this fractal scaling can arise through dispersion of random chemical inputs distributed across a catchment. These 1/f time series are non-self-averaging: monthly, yearly, or decadal averages are approximately as variable, one from the next, as individual measurements taken hours or days apart, defying naive statistical expectations. (By contrast, stream discharge itself is nonfractal, and self-averaging on time scales of months and longer.) In the solute time series, statistically significant trends arise much more frequently, on all time scales, than one would expect from conventional t statistics. However, these same trends are poor predictors of future trends-much poorer than one would expect from their calculated uncertainties. Our results illustrate how 1/f time series pose fundamental challenges to trend analysis and change detection in environmental systems.

Effect of initial conditions of a catchment on seasonal streamflow prediction using ensemble streamflow prediction (ESP) technique for the Rangitata and Waitaki River basins on the South Island of New Zealand

NASA Astrophysics Data System (ADS)

Singh, Shailesh Kumar; Zammit, Christian; Hreinsson, Einar; Woods, Ross; Clark, Martyn; Hamlet, Alan

2013-04-01

Increased access to water is a key pillar of the New Zealand government plan for economic growths. Variable climatic conditions coupled with market drivers and increased demand on water resource result in critical decision made by water managers based on climate and streamflow forecast. Because many of these decisions have serious economic implications, accurate forecast of climate and streamflow are of paramount importance (eg irrigated agriculture and electricity generation). New Zealand currently does not have a centralized, comprehensive, and state-of-the-art system in place for providing operational seasonal to interannual streamflow forecasts to guide water resources management decisions. As a pilot effort, we implement and evaluate an experimental ensemble streamflow forecasting system for the Waitaki and Rangitata River basins on New Zealand's South Island using a hydrologic simulation model (TopNet) and the familiar ensemble streamflow prediction (ESP) paradigm for estimating forecast uncertainty. To provide a comprehensive database for evaluation of the forecasting system, first a set of retrospective model states simulated by the hydrologic model on the first day of each month were archived from 1972-2009. Then, using the hydrologic simulation model, each of these historical model states was paired with the retrospective temperature and precipitation time series from each historical water year to create a database of retrospective hindcasts. Using the resulting database, the relative importance of initial state variables (such as soil moisture and snowpack) as fundamental drivers of uncertainties in forecasts were evaluated for different seasons and lead times. The analysis indicate that the sensitivity of flow forecast to initial condition uncertainty is depend on the hydrological regime and season of forecast. However initial conditions do not have a large impact on seasonal flow uncertainties for snow dominated catchments. Further analysis indicates that this result is valid when the hindcast database is conditioned by ENSO classification. As a result hydrological forecasts based on ESP technique, where present initial conditions with histological forcing data are used may be plausible for New Zealand catchments.

Analysis of trends of water quality and streamflow in the Blackstone, Branch, Pawtuxet, and Pawcatuck Rivers, Massachusetts and Rhode Island, 1979 to 2015

USGS Publications Warehouse

Savoie, Jennifer G.; Mullaney, John R.; Bent, Gardner C.

2017-02-21

Trends in long-term water-quality and streamflow data from six water-quality-monitoring stations within three major river basins in Massachusetts and Rhode Island that flow into Narragansett Bay and Little Narragansett Bay were evaluated for water years 1979–2015. In this study, conducted by the U.S. Geological Survey in cooperation with the Rhode Island Department of Environmental Management, the Rhode Island Water Resources Board, and the U.S. Environmental Protection Agency, water-quality and streamflow data were evaluated with a Weighted Regressions on Time, Discharge, and Season smoothing method, which removes the effects of year-to-year variation in water-quality conditions due to variations in streamflow (discharge). Trends in annual mean, annual median, annual maximum, and annual 7-day minimum flows at four continuous streamgages were evaluated by using a time-series smoothing method for water years 1979–2015.Water quality at all monitoring stations changed over the study period. Decreasing trends in flow-normalized nutrient concentrations and loads were observed during the period at most monitoring stations for total nitrogen, nitrite plus nitrate, and total phosphorus. Average flow-normalized loads for water years 1979–2015 decreased in the Blackstone River by up to 46 percent in total nitrogen, 17 percent in nitrite plus nitrate, and 69 percent in total phosphorus. The other rivers also had decreasing flow-normalized trends in nutrient concentrations and loads, except for the Pawtuxet River, which had an increasing trend in nitrite plus nitrate. Increasing trends in flow-normalized chloride concentrations and loads were observed during the study period at all of the rivers, with increases of more than 200 percent in the Blackstone River.Small increasing trends in annual mean daily streamflow were observed in 3 of the 4 rivers, with increases of 1.2 to 11 percent; however, the trends were not significant. All 4 rivers had decreases in streamflow for the annual 7-day minimums, but only 3 of the 4 rivers had decreases that were significant (34 to 54 percent). The Branch River had decreasing annual mean daily streamflow (7.5 percent) and the largest decrease in the annual 7-day minimum streamflow. The Blackstone and Pawtuxet Rivers had the largest increases in annual maximum daily flows but had decreases in the annual 7-day minimum flows.

Rescaled range analysis of streamflow records in the São Francisco River Basin, Brazil

NASA Astrophysics Data System (ADS)

Araujo, Marcelo Vitor Oliveira; Celeste, Alcigeimes B.

2018-01-01

Hydrological time series are sometimes found to have a distinctive behavior known as long-term persistence, in which subsequent values depend on each other even under very large time scales. This implies multiyear consecutive droughts or floods. Typical models used to generate synthetic hydrological scenarios, widely used in the planning and management of water resources, fail to preserve this kind of persistence in the generated data and therefore may have a major impact on projects whose design lives span for long periods of time. This study deals with the evaluation of long-term persistence in streamflow records by means of the rescaled range analysis proposed by British engineer Harold E. Hurst, who first observed the phenomenon in the mid-twentieth century. In this paper, Hurst's procedure is enhanced by a strategy based on statistical hypothesis testing. The case study comprises the six main hydroelectric power plants located in the São Francisco River Basin, part of the Brazilian National Grid. Historical time series of inflows to the major reservoirs of the system are investigated and 5/6 sites show significant persistence, with values for the so-called Hurst exponent near or greater than 0.7, i.e., around 40% above the value 0.5 that represents a white noise process, suggesting that decision makers should take long-term persistence into consideration when conducting water resources planning and management studies in the region.

Identifying streamflow shifts induced by wildfires in mountain basins under summer precipitation

NASA Astrophysics Data System (ADS)

Spade, D. M.; Moreno, H. A.; Gourley, J. J.

2016-12-01

High severity wildfires drastically alter the hydrologic response in headwater catchments, as a consequence of reductions in vegetation cover and modifications of soil hydraulic properties. These changes lead to an increased probability of flash-floods in steep-slope mountain watersheds. This study investigates the changes in hydrologic response for post-fire conditions at two burned basins in Colorado as observed from time series of streamflow, precipitation and remotely sensed vegetation density. We examine the event and seasonal hydrologic shifts as a function of vegetation cover which is measured by the Enhanced Vegetation Index (EVI). First, we compare flow duration curves of 15-min streamflows pre and post fire. Subsequently, we study the event scale changes induced by wildfire as measured by the runoff coefficient (RC), response time (RT) and peak flow (Qpk). At the seasonal scale we explore the yearly evolution of runoff coefficient and peak flow and their relationship with a normalized EVI (NEVI) to identify a recovery hysteresis pathway. Our findings support the idea that for similar burned areas relative to total basin surface, forested watersheds evidence the largest streamflow changes. Flow duration curves depict significant post-fire increases in the high-range streamflows (low probability of exceedence) on the order of 1900% in forested and 500% in shrubland dominated basins with respect to pre-fire conditions. For a similar-precipitation and antecedent soil moisture, burned watersheds significantly showed a decrease in response time and increase in runoff coefficient relative to pre-fire for two isolated hydrologic events. At the seasonal scale, the expected increase in NEVI translates into increases in RC and Qpk with a hysteresis effect driven by vegetation recovery, precipitation volumes and antecedent soil moisture. This study provides new insights to understand the physical processes triggered by fire that influence watershed responses and increase flash-flooding risks.

Practical implementation of a particle filter data assimilation approach to estimate initial hydrologic conditions and initialize medium-range streamflow forecasts

NASA Astrophysics Data System (ADS)

Clark, Elizabeth; Wood, Andy; Nijssen, Bart; Mendoza, Pablo; Newman, Andy; Nowak, Kenneth; Arnold, Jeffrey

2017-04-01

In an automated forecast system, hydrologic data assimilation (DA) performs the valuable function of correcting raw simulated watershed model states to better represent external observations, including measurements of streamflow, snow, soil moisture, and the like. Yet the incorporation of automated DA into operational forecasting systems has been a long-standing challenge due to the complexities of the hydrologic system, which include numerous lags between state and output variations. To help demonstrate that such methods can succeed in operational automated implementations, we present results from the real-time application of an ensemble particle filter (PF) for short-range (7 day lead) ensemble flow forecasts in western US river basins. We use the System for Hydromet Applications, Research and Prediction (SHARP), developed by the National Center for Atmospheric Research (NCAR) in collaboration with the University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation. SHARP is a fully automated platform for short-term to seasonal hydrologic forecasting applications, incorporating uncertainty in initial hydrologic conditions (IHCs) and in hydrometeorological predictions through ensemble methods. In this implementation, IHC uncertainty is estimated by propagating an ensemble of 100 temperature and precipitation time series through conceptual and physically-oriented models. The resulting ensemble of derived IHCs exhibits a broad range of possible soil moisture and snow water equivalent (SWE) states. The PF selects and/or weights and resamples the IHCs that are most consistent with external streamflow observations, and uses the particles to initialize a streamflow forecast ensemble driven by ensemble precipitation and temperature forecasts downscaled from the Global Ensemble Forecast System (GEFS). We apply this method in real-time for several basins in the western US that are important for water resources management, and perform a hindcast experiment to evaluate the utility of PF-based data assimilation on streamflow forecasts skill. This presentation describes findings, including a comparison of sequential and non-sequential particle weighting methods.

A comparison of methods to predict historical daily streamflow time series in the southeastern United States

USGS Publications Warehouse

Farmer, William H.; Archfield, Stacey A.; Over, Thomas M.; Hay, Lauren E.; LaFontaine, Jacob H.; Kiang, Julie E.

2015-01-01

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB). Additional metrics of comparison can easily be incorporated into this type of analysis. By considering such a multifaceted approach, the top-performing models can easily be identified and considered for further research. The top-performing models can then provide a basis for future applications and explorations by scientists, engineers, managers, and practitioners to suit their own needs.

Linking river management to species conservation using dynamic landscape scale models

USGS Publications Warehouse

Freeman, Mary C.; Buell, Gary R.; Hay, Lauren E.; Hughes, W. Brian; Jacobson, Robert B.; Jones, John W.; Jones, S.A.; LaFontaine, Jacob H.; Odom, Kenneth R.; Peterson, James T.; Riley, Jeffrey W.; Schindler, J. Stephen; Shea, C.; Weaver, J.D.

2013-01-01

Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape-scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation.

U.S. Geological Survey groundwater toolbox, a graphical and mapping interface for analysis of hydrologic data (version 1.0): user guide for estimation of base flow, runoff, and groundwater recharge from streamflow data

USGS Publications Warehouse

Barlow, Paul M.; Cunningham, William L.; Zhai, Tong; Gray, Mark

2015-01-01

This report is a user guide for the streamflow-hydrograph analysis methods provided with version 1.0 of the U.S. Geological Survey (USGS) Groundwater Toolbox computer program. These include six hydrograph-separation methods to determine the groundwater-discharge (base-flow) and surface-runoff components of streamflow—the Base-Flow Index (BFI; Standard and Modified), HYSEP (Fixed Interval, Sliding Interval, and Local Minimum), and PART methods—and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater recharge from streamflow data. The Groundwater Toolbox is a customized interface built on the nonproprietary, open source MapWindow geographic information system software. The program provides graphing, mapping, and analysis capabilities in a Microsoft Windows computing environment. In addition to the four hydrograph-analysis methods, the Groundwater Toolbox allows for the retrieval of hydrologic time-series data (streamflow, groundwater levels, and precipitation) from the USGS National Water Information System, downloading of a suite of preprocessed geographic information system coverages and meteorological data from the National Oceanic and Atmospheric Administration National Climatic Data Center, and analysis of data with several preprocessing and postprocessing utilities. With its data retrieval and analysis tools, the Groundwater Toolbox provides methods to estimate many of the components of the water budget for a hydrologic basin, including precipitation; streamflow; base flow; runoff; groundwater recharge; and total, groundwater, and near-surface evapotranspiration.

Attributing uncertainty in streamflow simulations due to variable inputs via the Quantile Flow Deviation metric

NASA Astrophysics Data System (ADS)

Shoaib, Syed Abu; Marshall, Lucy; Sharma, Ashish

2018-06-01

Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.

Identify the dominant variables to predict stream water temperature

NASA Astrophysics Data System (ADS)

Chien, H.; Flagler, J.

2016-12-01

Stream water temperature is a critical variable controlling water quality and the health of aquatic ecosystems. Accurate prediction of water temperature and the assessment of the impacts of environmental variables on water temperature variation are critical for water resources management, particularly in the context of water quality and aquatic ecosystem sustainability. The objective of this study is to measure stream water temperature and air temperature and to examine the importance of streamflow on stream water temperature prediction. The measured stream water temperature and air temperature will be used to test two hypotheses: 1) streamflow is a relatively more important factor than air temperature in regulating water temperature, and 2) by combining air temperature and streamflow data stream water temperature can be more accurately estimated. Water and air temperature data loggers are placed at two USGS stream gauge stations #01362357and #01362370, located in the upper Esopus Creek watershed in Phonecia, NY. The ARIMA (autoregressive integrated moving average) time series model is used to analyze the measured water temperature data, identify the dominant environmental variables, and predict the water temperature with identified dominant variable. The preliminary results show that streamflow is not a significant variable in predicting stream water temperature at both USGS gauge stations. Daily mean air temperature is sufficient to predict stream water temperature at this site scale.

Effects of Uncertainties in Hydrological Modelling. A Case Study of a Mountainous Catchment in Southern Norway

NASA Astrophysics Data System (ADS)

Engeland, Kolbjorn; Steinsland, Ingelin

2016-04-01

The aim of this study is to investigate how the inclusion of uncertainties in inputs and observed streamflow influence the parameter estimation, streamflow predictions and model evaluation. In particular we wanted to answer the following research questions: • What is the effect of including a random error in the precipitation and temperature inputs? • What is the effect of decreased information about precipitation by excluding the nearest precipitation station? • What is the effect of the uncertainty in streamflow observations? • What is the effect of reduced information about the true streamflow by using a rating curve where the measurement of the highest and lowest streamflow is excluded when estimating the rating curve? To answer these questions, we designed a set of calibration experiments and evaluation strategies. We used the elevation distributed HBV model operating on daily time steps combined with a Bayesian formulation and the MCMC routine Dream for parameter inference. The uncertainties in inputs was represented by creating ensembles of precipitation and temperature. The precipitation ensemble were created using a meta-gaussian random field approach. The temperature ensembles were created using a 3D Bayesian kriging with random sampling of the temperature laps rate. The streamflow ensembles were generated by a Bayesian multi-segment rating curve model. Precipitation and temperatures were randomly sampled for every day, whereas the streamflow ensembles were generated from rating curve ensembles, and the same rating curve was always used for the whole time series in a calibration or evaluation run. We chose a catchment with a meteorological station measuring precipitation and temperature, and a rating curve of relatively high quality. This allowed us to investigate and further test the effect of having less information on precipitation and streamflow during model calibration, predictions and evaluation. The results showed that including uncertainty in the precipitation and temperature input has a negligible effect on the posterior distribution of parameters and for the Nash-Sutcliffe (NS) efficiency for the predicted flows, while the reliability and the continuous rank probability score (CRPS) improves. Reduced information in precipitation input resulted in a and a shift in the water balance parameter Pcorr, a model producing smoother streamflow predictions giving poorer NS and CRPS, but higher reliability. The effect of calibrating the hydrological model using wrong rating curves is mainly seen as variability in the water balance parameter Pcorr. When evaluating predictions obtained using a wrong rating curve, the evaluation scores varies depending on the true rating curve. Generally, the best evaluation scores were not achieved for the rating curve used for calibration, but for a rating curves giving low variance in streamflow observations. Reduced information in streamflow influenced the water balance parameter Pcorr, and increased the spread in evaluation scores giving both better and worse scores. This case study shows that estimating the water balance is challenging since both precipitation inputs and streamflow observations have pronounced systematic component in their uncertainties.

Water resources data for Oregon, water year 2004

USGS Publications Warehouse

Herrett, Thomas A.; Hess, Glenn W.; House, Jon G.; Ruppert, Gregory P.; Courts, Mary-Lorraine

2005-01-01

The annual Oregon water data report is one of a series of annual reports that document hydrologic data gathered from the U.S. Geological Survey's surface- and ground-water data-collection networks in each State, Puerto Rico, and the Trust Territories. These records of streamflow, ground-water levels, and quality of water provide the hydrologic information needed by State, local, Tribal, and Federal agencies and the private sector for developing and managing our Nation's land and water resources. This report contains water year 2004 data for both surface and ground water, including discharge records for 209 streamflow-gaging stations, 42 partial-record or miscellaneous streamflow stations, and 9 crest-stage partial-record streamflow stations; stage-only records for 6 gaging stations; stage and content records for 15 lakes and reservoirs; water-level records from 12 long-term observation wells; and water-quality records collected at 133 streamflow-gaging stations and 1 atmospheric deposition station.

Quantifying the Temporal Inequality of Nutrient Loads with a Novel Metric

NASA Astrophysics Data System (ADS)

Gall, H. E.; Schultz, D.; Rao, P. S.; Jawitz, J. W.; Royer, M.

2015-12-01

Inequality is an emergent property of many complex systems. For a given series of stochastic events, some events generate a disproportionately large contribution to system responses compared to other events. In catchments, such responses cause streamflow and solute loads to exhibit strong temporal inequality, with the vast majority of discharge and solute loads exported during short periods of time during which high-flow events occur. These periods of time are commonly referred to as "hot moments". Although this temporal inequality is widely recognized, there is currently no uniform metric for assessing it. We used a novel application of Lorenz Inequality, a method commonly used in economics to quantify income inequality, to quantify the spatial and temporal inequality of streamflow and nutrient (nitrogen and phosphorus) loads exported to the Chesapeake Bay. Lorenz Inequality and the corresponding Gini Coefficient provide an analytical tool for quantifying inequality that can be applied at any temporal or spatial scale. The Gini coefficient (G) is a formal measure of inequality that varies from 0 to 1, with a value of 0 indicating perfect equality (i.e., fluxes and loads are constant in time) and 1 indicating perfect inequality (i.e., all of the discharge and solute loads are exported during one instant in time). Therefore, G is a simple yet powerful tool for providing insight into the temporal inequality of nutrient transport. We will present the results of our detailed analysis of streamflow and nutrient time series data collected since the early 1980's at 30 USGS gauging stations in the Chesapeake Bay watershed. The analysis is conducted at an annual time scale, enabling trends and patterns to be assessed both temporally (over time at each station) and spatially (for the same period of time across stations). The results of this analysis have the potential to create a transformative new framework for identifying "hot moments", improving our ability to temporally and spatially target implementation of best management practices to ultimately improve water quality in the Chesapeake Bay. This method also provides insight into the temporal scales at which hydrologic and biogeochemical variability dominate nutrient export dynamics.

Development of a precipitation-runoff model to simulate unregulated streamflow in the South Fork Flathead River Basin, Montana

USGS Publications Warehouse

Chase, K.J.

2011-01-01

This report documents the development of a precipitation-runoff model for the South Fork Flathead River Basin, Mont. The Precipitation-Runoff Modeling System model, developed in cooperation with the Bureau of Reclamation, can be used to simulate daily mean unregulated streamflow upstream and downstream from Hungry Horse Reservoir for water-resources planning. Two input files are required to run the model. The time-series data file contains daily precipitation data and daily minimum and maximum air-temperature data from climate stations in and near the South Fork Flathead River Basin. The parameter file contains values of parameters that describe the basin topography, the flow network, the distribution of the precipitation and temperature data, and the hydrologic characteristics of the basin soils and vegetation. A primary-parameter file was created for simulating streamflow during the study period (water years 1967-2005). The model was calibrated for water years 1991-2005 using the primary-parameter file. This calibration was further refined using snow-covered area data for water years 2001-05. The model then was tested for water years 1967-90. Calibration targets included mean monthly and daily mean unregulated streamflow upstream from Hungry Horse Reservoir, mean monthly unregulated streamflow downstream from Hungry Horse Reservoir, basin mean monthly solar radiation and potential evapotranspiration, and daily snapshots of basin snow-covered area. Simulated streamflow generally was in better agreement with observed streamflow at the upstream gage than at the downstream gage. Upstream from the reservoir, simulated mean annual streamflow was within 0.0 percent of observed mean annual streamflow for the calibration period and was about 2 percent higher than observed mean annual streamflow for the test period. Simulated mean April-July streamflow upstream from the reservoir was about 1 percent lower than observed streamflow for the calibration period and about 4 percent higher than observed for the test period. Downstream from the reservoir, simulated mean annual streamflow was 17 percent lower than observed streamflow for the calibration period and 12 percent lower than observed streamflow for the test period. Simulated mean April-July streamflow downstream from the reservoir was 13 percent lower than observed streamflow for the calibration period and 6 percent lower than observed streamflow for the test period. Calibrating to solar radiation, potential evapotranspiration, and snow-covered area improved the model representation of evapotranspiration, snow accumulation, and snowmelt processes. Simulated basin mean monthly solar radiation values for both the calibration and test periods were within 9 percent of observed values except during the month of December (28 percent different). Simulated basin potential evapotranspiration values for both the calibration and test periods were within 10 percent of observed values except during the months of January (100 percent different) and February (13 percent different). The larger percent errors in simulated potential evaporation occurred in the winter months when observed potential evapotranspiration values were very small; in January the observed value was 0.000 inches and in February the observed value was 0.009 inches. Simulated start of melting of the snowpack occurred at about the same time as observed start of melting. The simulated snowpack accumulated to 90-100 percent snow-covered area 1 to 3 months earlier than observed snowpack. This overestimated snowpack during the winter corresponded to underestimated streamflow during the same period. In addition to the primary-parameter file, four other parameter files were created: for a "recent" period (1991-2005), a historical period (1967-90), a "wet" period (1989-97), and a "dry" period (1998-2005). For each data file of projected precipitation and air temperature, a single parameter file can be used to simulate a s

Alternative standardization approaches to improving streamflow reconstructions with ring-width indices of riparian trees

USGS Publications Warehouse

Meko, David M.; Friedman, Jonathan M.; Touchan, Ramzi; Edmondson, Jesse R.; Griffin, Eleanor R.; Scott, Julian A.

2015-01-01

Old, multi-aged populations of riparian trees provide an opportunity to improve reconstructions of streamflow. Here, ring widths of 394 plains cottonwood (Populus deltoids, ssp. monilifera) trees in the North Unit of Theodore Roosevelt National Park, North Dakota, are used to reconstruct streamflow along the Little Missouri River (LMR), North Dakota, US. Different versions of the cottonwood chronology are developed by (1) age-curve standardization (ACS), using age-stratified samples and a single estimated curve of ring width against estimated ring age, and (2) time-curve standardization (TCS), using a subset of longer ring-width series individually detrended with cubic smoothing splines of width against year. The cottonwood chronologies are combined with the first principal component of four upland conifer chronologies developed by conventional methods to investigate the possible value of riparian tree-ring chronologies for streamflow reconstruction of the LMR. Regression modeling indicates that the statistical signal for flow is stronger in the riparian cottonwood than in the upland chronologies. The flow signal from cottonwood complements rather than repeats the signal from upland conifers and is especially strong in young trees (e.g. 5–35 years). Reconstructions using a combination of cottonwoods and upland conifers are found to explain more than 50% of the variance of LMR flow over a 1935–1990 calibration period and to yield reconstruction of flow to 1658. The low-frequency component of reconstructed flow is sensitive to the choice of standardization method for the cottonwood. In contrast to the TCS version, the ACS reconstruction features persistent low flows in the 19th century. Results demonstrate the value to streamflow reconstruction of riparian cottonwood and suggest that more studies are needed to exploit the low-frequency streamflow signal in densely sampled age-stratified stands of riparian trees.

Trend and variability in a new, reconstructed streamflow dataset for West and Central Africa, and climatic interactions, 1950-2005

NASA Astrophysics Data System (ADS)

Sidibe, Moussa; Dieppois, Bastien; Mahé, Gil; Paturel, Jean-Emmanuel; Amoussou, Ernest; Anifowose, Babatunde; Lawler, Damian

2018-06-01

Over recent decades, regions of West and Central Africa have experienced different and significant changes in climatic patterns, which have significantly impacted hydrological regimes. Such impacts, however, are not fully understood at the regional scale, largely because of scarce hydroclimatic data. Therefore, the aim of this study is to (a) assemble a new, robust, reconstructed streamflow dataset of 152 gauging stations; (b) quantify changes in streamflow over 1950-2005 period, using these newly reconstructed datasets; (c) significantly reveal trends and variability in streamflow over West and Central Africa based on new reconstructions; and (d) assess the robustness of this dataset by comparing the results with those identified in key climatic drivers (e.g. precipitation and temperature) over the region. Gap filling methods applied to monthly time series (1950-2005) yielded robust results (median Kling-Gupta Efficiency >0.75). The study underlines a good agreement between precipitation and streamflow trends and reveals contrasts between western Africa (negative trends) and Central Africa (positive trends) in the 1950s and 1960s. Homogenous dry conditions of the 1970s and 1980s, characterized by reduced significant negative trends resulting from quasi-decadal modulations of the trend, are replaced by wetter conditions in the recent period (1993-2005). The effect of this rainfall recovery (which extends to West and Central Africa) on increased river flows are further amplified by land use change in some Sahelian basins. This is partially offset, however, by higher potential evapotranspiration rates over parts of Niger and Nigeria. Crucially, the new reconstructed streamflow datasets presented here will be available for both the scientific community and water resource managers.

Does model structure limit the use of satellite data as hydrologic forcing for distributed operational models?

NASA Astrophysics Data System (ADS)

Bowman, A. L.; Franz, K.; Hogue, T. S.

2015-12-01

We are investigating the implications for use of satellite data in operational streamflow prediction. Specifically, the consequence of potential hydrologic model structure deficiencies on the ability to achieve improved forecast accuracy through the use of satellite data. We want to understand why advanced data do not lead to improved streamflow simulations by exploring how various fluxes and states differ among models of increasing complexity. In a series of prior studies, we investigated the use of a daily satellite-derived potential evapotranspiration (PET) estimate as input to the National Weather Service (NWS) streamflow forecast models for watersheds in the Upper Mississippi and Red river basins. Although the spatial PET product appears to represent the day-to-day variability in PET more realistically than current climatological methods used by the NWS, the impact of the satellite data on streamflow simulations results in slightly poorer model efficiency overall. Analysis of the model states indicates the model progresses differently between simulations with baseline PET and the satellite-derived PET input, though variation in streamflow simulations overall is negligible. For instance, the upper zone states, responsible for the high flows of a hydrograph, show a profound difference, while simulation of the peak flows tend to show little variation in the timing and magnitude. Using the spatial PET input, the lower zone states show improvement with simulating the recession limb and baseflow portion of the hydrograph. We anticipate that through a better understanding of the relationship between model structure, model states, and simulated streamflow we will be able to diagnose why simulations of discharge from the forecast model have failed to improve when provided seemingly more representative input data. Identifying model limitations are critical to demonstrating the full benefit of a satellite data for operational use.

Joint pattern of seasonal hydrological droughts and floods alternation in China's Huai River Basin using the multivariate L-moments

NASA Astrophysics Data System (ADS)

Wu, ShaoFei; Zhang, Xiang; She, DunXian

2017-06-01

Under the current condition of climate change, droughts and floods occur more frequently, and events in which flooding occurs after a prolonged drought or a drought occurs after an extreme flood may have a more severe impact on natural systems and human lives. This challenges the traditional approach wherein droughts and floods are considered separately, which may largely underestimate the risk of the disasters. In our study, the sudden alternation of droughts and flood events (ADFEs) between adjacent seasons is studied using the multivariate L-moments theory and the bivariate copula functions in the Huai River Basin (HRB) of China with monthly streamflow data at 32 hydrological stations from 1956 to 2012. The dry and wet conditions are characterized by the standardized streamflow index (SSI) at a 3-month time scale. The results show that: (1) The summer streamflow makes the largest contribution to the annual streamflow, followed by the autumn streamflow and spring streamflow. (2) The entire study area can be divided into five homogeneous sub-regions using the multivariate regional homogeneity test. The generalized logistic distribution (GLO) and log-normal distribution (LN3) are acceptable to be the optimal marginal distributions under most conditions, and the Frank copula is more appropriate for spring-summer and summer-autumn SSI series. Continuous flood events dominate at most sites both in spring-summer and summer-autumn (with an average frequency of 13.78% and 17.06%, respectively), while continuous drought events come second (with an average frequency of 11.27% and 13.79%, respectively). Moreover, seasonal ADFEs most probably occurred near the mainstream of HRB, and drought and flood events are more likely to occur in summer-autumn than in spring-summer.

Drivers of annual to decadal streamflow variability in the lower Colorado River Basin

NASA Astrophysics Data System (ADS)

Lambeth-Beagles, R. S.; Troch, P. A.

2010-12-01

The Colorado River is the main water supply to the southwest region. As demand reaches the limit of supply in the southwest it becomes increasingly important to understand the dynamics of streamflow in the Colorado River and in particular the tributaries to the lower Colorado River. Climate change may pose an additional threat to the already-scarce water supply in the southwest. Due to the narrowing margin for error, water managers are keen on extending their ability to predict streamflow volumes on a mid-range to decadal scale. Before a predictive streamflow model can be developed, an understanding of the physical drivers of annual to decadal streamflow variability in the lower Colorado River Basin is needed. This research addresses this need by applying multiple statistical methods to identify trends, patterns and relationships present in streamflow, precipitation and temperature over the past century in four contributing watersheds to the lower Colorado River. The four watersheds selected were the Paria, Little Colorado, Virgin/Muddy, and Bill Williams. Time series data over a common period from 1906-2007 for streamflow, precipitation and temperature were used for the initial analysis. Through statistical analysis the following questions were addressed: 1) are there observable trends and patterns in these variables during the past century and 2) if there are trends or patterns, how are they related to each other? The Mann-Kendall test was used to identify trends in the three variables. Assumptions regarding autocorrelation and persistence in the data were taken into consideration. Kendall’s tau-b test was used to establish association between any found trends in the data. Initial results suggest there are two primary processes occurring. First, statistical analysis reveals significant upward trends in temperatures and downward trends in streamflow. However, there appears to be no trend in precipitation data. These trends in streamflow and temperature speak to increasing evaporation and transpiration processes. Second, annual variability in streamflow is not statistically correlated with annual temperature variability but appears to be highly correlated with annual precipitation variability. This implies that on a year-to-year basis, changes in streamflow volumes are directly affected by precipitation and not temperature. Future development of a predictive streamflow model will need to take into consideration these two processes to obtain accurate results. In order to extend predictive skill to the multi-year scale relationships between precipitation, temperature and persistent climate indices such as the Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation and El Nino/Southern Oscillation will need to be examined.

Technique for estimation of streamflow statistics in mineral areas of interest in Afghanistan

USGS Publications Warehouse

Olson, Scott A.; Mack, Thomas J.

2011-01-01

A technique for estimating streamflow statistics at ungaged stream sites in areas of mineral interest in Afghanistan using drainage-area-ratio relations of historical streamflow data was developed and is documented in this report. The technique can be used to estimate the following streamflow statistics at ungaged sites: (1) 7-day low flow with a 10-year recurrence interval, (2) 7-day low flow with a 2-year recurrence interval, (3) daily mean streamflow exceeded 90 percent of the time, (4) daily mean streamflow exceeded 80 percent of the time, (5) mean monthly streamflow for each month of the year, (6) mean annual streamflow, and (7) minimum monthly streamflow for each month of the year. Because they are based on limited historical data, the estimates of streamflow statistics at ungaged sites are considered preliminary.

Estimating distribution parameters of annual maximum streamflows in Johor, Malaysia using TL-moments approach

NASA Astrophysics Data System (ADS)

Mat Jan, Nur Amalina; Shabri, Ani

2017-01-01

TL-moments approach has been used in an analysis to identify the best-fitting distributions to represent the annual series of maximum streamflow data over seven stations in Johor, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: Three-parameter lognormal (LN3) and Pearson Type III (P3) distribution. The main objective of this study is to derive the TL-moments ( t 1,0), t 1 = 1,2,3,4 methods for LN3 and P3 distributions. The performance of TL-moments ( t 1,0), t 1 = 1,2,3,4 was compared with L-moments through Monte Carlo simulation and streamflow data over a station in Johor, Malaysia. The absolute error is used to test the influence of TL-moments methods on estimated probability distribution functions. From the cases in this study, the results show that TL-moments with four trimmed smallest values from the conceptual sample (TL-moments [4, 0]) of LN3 distribution was the most appropriate in most of the stations of the annual maximum streamflow series in Johor, Malaysia.

Acute gastro-intestinal illness and its association with hydroclimatic factors in British Columbia, Canada: A time-series analysis

NASA Astrophysics Data System (ADS)

Galway, L. P.; Allen, D. M.

2013-12-01

Rising global temperatures and expected shifts in regional hydroclimatology in a changing climate are likely to influence the risk of infectious waterborne illness. This study examines the role of hydroclimatology as an underlying driver of the epidemiology of waterborne gastro-intestinal illness and contributes to our currently limited understanding of the possible ecosystem-mediated impacts of climate change on health. Using time-series regression analysis, we examine the associations between three hydroclimatic factors (monthly temperature, precipitation, and streamflow) and the monthly occurrence of AGI illness in two communities in the province of British Columbia, Canada. The two communities were selected as study sites to represent the dominant hydroclimatic regimes that characterize the province of BC: the rainfall-dominated hydroclimatic regime and snowmelt-dominated hydroclimatic regime Our results show that the number of monthly cases of AGI increased with increasing temperature, precipitation, and streamflow in the same month in the context of a rainfall-dominated regime and with increasing streamflow in the previous month in the context of a snowfall-dominated regime. These results suggest that hydroclimatic factors play a role in driving the occurrence and variability of AGI illness in this setting. Further, this study has highlighted that the nature and magnitude of the effects of hydroclimatic factors on waterborne illness vary across different hydroclimatic settings. We conclude that the watershed may be an appropriate context within which we can and should enhance our understanding of water-related climate change impacts on health. Examining the role of hydroclimatology as an underlying driver of the epidemiology of infectious disease is key to understanding of the possible ecosystem-mediated impacts of climate change on health and developing appropriate adaptation responses.

Streamflow characteristics of the Colorado River Basin in Utah through September 1981

USGS Publications Warehouse

Christensen, R.C.; Johnson, E.B.; Plantz, G.G.

1987-01-01

 This report summarizes discharge data and other streamflow characteristics developed from gag ing-station records collected through September 1981 at 337 stations in the Colorado River Basin in Utah. Data also are included for 14 stations in adjacent areas of the bordering states of Arizona, Colorado, and Wyoming (fig. 1). The study leading to this report was done in cooperation with the U.S. Bureau of Land Management, which needs the streamflow data in order to evaluate impacts of mining on the hydrologic system. The report also will be beneficial to other Federal, State, and county agencies and to individuals concerned with water supply and water problems in the Colorado River Basin.The streamflow characteristics in the report could be useful in many water-related studies that involve the following:Definition of baseline-hydrologic conditions; studies of the effects of man's activities on streamflow; frequency analyses of low and high flows; regional analyses of streamflow characteristics; design of water-supply systems; water-power studies; forecasting of stream discharge; time-series analyses of streamflow; design of flood-control structures; stream-pollution studies; and water-chemistry transport studies.The basic data used to develop the summaries in this report are records of daily and peak discharge collected by the U.S. Geological Survey and other Federal agencies. Much of the work of the Geological Survey was done in cooperation with Federal, State, and county agencies. Discharge recordsincluded in the report generally were for stations with at least 1 complete water year of record and nearby stations that were on the same stream and had different streamflow characteristics. A water year is a 12-month period ending September 30, and it is designated by the calendar year in which it ends. For streams that have had significant changes in regulation by reservoirs or diversions, the records before and after those changes were used separately to provide streamflow characteristics for each period of homogeneous streamflow and to show the change in the characteristics. Summaries for annual peak discharge are included only for stations with 5 or more years of data. The summaries of annual lowest and highest mean-discharge frequency are reported for stations with 10 or more years of daily-discharge record and for which computer-generated frequency curves provided a reasonable fit of the plotted data.

Reconstruction of missing daily streamflow data using dynamic regression models

NASA Astrophysics Data System (ADS)

Tencaliec, Patricia; Favre, Anne-Catherine; Prieur, Clémentine; Mathevet, Thibault

2015-12-01

River discharge is one of the most important quantities in hydrology. It provides fundamental records for water resources management and climate change monitoring. Even very short data-gaps in this information can cause extremely different analysis outputs. Therefore, reconstructing missing data of incomplete data sets is an important step regarding the performance of the environmental models, engineering, and research applications, thus it presents a great challenge. The objective of this paper is to introduce an effective technique for reconstructing missing daily discharge data when one has access to only daily streamflow data. The proposed procedure uses a combination of regression and autoregressive integrated moving average models (ARIMA) called dynamic regression model. This model uses the linear relationship between neighbor and correlated stations and then adjusts the residual term by fitting an ARIMA structure. Application of the model to eight daily streamflow data for the Durance river watershed showed that the model yields reliable estimates for the missing data in the time series. Simulation studies were also conducted to evaluate the performance of the procedure.

Intercomparison of Streamflow Simulations between WRF-Hydro and Hydrology Laboratory-Research Distributed Hydrologic Model Frameworks

NASA Astrophysics Data System (ADS)

KIM, J.; Smith, M. B.; Koren, V.; Salas, F.; Cui, Z.; Johnson, D.

2017-12-01

The National Oceanic and Atmospheric Administration (NOAA)-National Weather Service (NWS) developed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) framework as an initial step towards spatially distributed modeling at River Forecast Centers (RFCs). Recently, the NOAA/NWS worked with the National Center for Atmospheric Research (NCAR) to implement the National Water Model (NWM) for nationally-consistent water resources prediction. The NWM is based on the WRF-Hydro framework and is run at a 1km spatial resolution and 1-hour time step over the contiguous United States (CONUS) and contributing areas in Canada and Mexico. In this study, we compare streamflow simulations from HL-RDHM and WRF-Hydro to observations from 279 USGS stations. For streamflow simulations, HL-RDHM is run on 4km grids with the temporal resolution of 1 hour for a 5-year period (Water Years 2008-2012), using a priori parameters provided by NOAA-NWS. The WRF-Hydro streamflow simulations for the same time period are extracted from NCAR's 23 retrospective run of the NWM (version 1.0) over CONUS based on 1km grids. We choose 279 USGS stations which are relatively less affected by dams or reservoirs, in the domains of six different RFCs. We use the daily average values of simulations and observations for the convenience of comparison. The main purpose of this research is to evaluate how HL-RDHM and WRF-Hydro perform at USGS gauge stations. We compare daily time-series of observations and both simulations, and calculate the error values using a variety of error functions. Using these plots and error values, we evaluate the performances of HL-RDHM and WRF-Hydro models. Our results show a mix of model performance across geographic regions.

Dynamic linear models to explore time-varying suspended sediment-discharge rating curves

NASA Astrophysics Data System (ADS)

Ahn, Kuk-Hyun; Yellen, Brian; Steinschneider, Scott

2017-06-01

This study presents a new method to examine long-term dynamics in sediment yield using time-varying sediment-discharge rating curves. Dynamic linear models (DLMs) are introduced as a time series filter that can assess how the relationship between streamflow and sediment concentration or load changes over time in response to a wide variety of natural and anthropogenic watershed disturbances or long-term changes. The filter operates by updating parameter values using a recursive Bayesian design that responds to 1 day-ahead forecast errors while also accounting for observational noise. The estimated time series of rating curve parameters can then be used to diagnose multiscale (daily-decadal) variability in sediment yield after accounting for fluctuations in streamflow. The technique is applied in a case study examining changes in turbidity load, a proxy for sediment load, in the Esopus Creek watershed, part of the New York City drinking water supply system. The results show that turbidity load exhibits a complex array of variability across time scales. The DLM highlights flood event-driven positive hysteresis, where turbidity load remained elevated for months after large flood events, as a major component of dynamic behavior in the rating curve relationship. The DLM also produces more accurate 1 day-ahead loading forecasts compared to other static and time-varying rating curve methods. The results suggest that DLMs provide a useful tool for diagnosing changes in sediment-discharge relationships over time and may help identify variability in sediment concentrations and loads that can be used to inform dynamic water quality management.

Trends and variability in streamflow and snowmelt runoff timing in the southern Tianshan Mountains

NASA Astrophysics Data System (ADS)

Shen, Yan-Jun; Shen, Yanjun; Fink, Manfred; Kralisch, Sven; Chen, Yaning; Brenning, Alexander

2018-02-01

Streamflow and snowmelt runoff timing of mountain rivers are susceptible to climate change. Trends and variability in streamflow and snowmelt runoff timing in four mountain basins in the southern Tianshan were analyzed in this study. Streamflow trends were detected by Mann-Kendall tests and changes in snowmelt runoff timing were analyzed based on the winter/spring snowmelt runoff center time (WSCT). Pearson's correlation coefficient was further calculated to analyze the relationships between climate variables, streamflow and WSCT. Annual streamflow increased significantly in past decades in the southern Tianshan, especially in spring and winter months. However, the relations between streamflow and temperature/precipitation depend on the different streamflow generation processes. Annual precipitation plays a vital role in controlling recharge in the Toxkon basin, while the Kaidu and Huangshuigou basins are governed by both precipitation and temperature. Seasonally, temperature has a strong effect on streamflow in autumn and winter, while summer streamflow appears more sensitive to changes in precipitation. However, temperature is the dominant factor for streamflow in the glacierized Kunmalik basin at annual and seasonal scales. An uptrend in streamflow begins in the 1990s at both annual and seasonal scales, which is generally consistent with temperature and precipitation fluctuations. Average WSCT dates in the Kaidu and Huangshuigou basins are earlier than in the Toxkon and Kunmalik basins, and shifted towards earlier dates since the mid-1980s in all the basins. It is plausible that WSCT dates are more sensitive to warmer temperature in spring period compared to precipitation, except for the Huangshuigou basin. Taken together, these findings are useful for applications in flood risk regulation, future hydropower projects and integrated water resources management.

Deep nitrogen acquisition in warming permafrost soils: Contributions of belowground plant traits and fungal symbioses in the permafrost carbon feedback to climate

NASA Astrophysics Data System (ADS)

Hartnett, H. E.; Palta, M. M.; Grimm, N. B.; Ruhi, A.; van Shaijik, M.

2016-12-01

Tempe Town Lake (TTL) is a hydrologically-regulated reservoir in Tempe, Arizona. The lake has high primary production and receives dissolved organic carbon (DOC) from rainfall, storm flow, and upstream river discharge. We applied an ARIMA time-series model to a three-year period for which we have high-frequency chemistry, meteorology, and streamflow data and analyzed external (rainfall, stream flow) and internal (dissolved O2) drivers of DOC content and composition. DOC composition was represented by fluorescence-based indices (fluorescence index, humification index, freshness) related to DOC source (microbially- vs. terrestrially-derived) and reactivity DOC. Patterns in DOC concentration and composition suggest carbon cycling in the lake responds to both meteorological events and to anthropogenic activity. The fluorescence-derived DOC composition is consistent with seasonally-distinct inputs of algal- and terrestrially-derived carbon. For example, Tempe Town Lake is supersaturated in O2 over 70% of the time, suggesting the system is autotrophic and primary productivity (i.e., O2 saturation state) was the strongest driver of DOC concentration. In contrast, external drivers (rainfall pattern, streamflow) were the strongest determinants of DOC composition. Biological processes (e.g., algal growth) generate carbon in the lake during spring and summer, and high Fluorescence Index and Freshness values at this time are indicative of algal-derived material; these parameters generally decrease with rain or flow suggesting algal-derived carbon is diluted by external water inputs. During dry periods, carbon builds up on the land surface and subsequent rainfall events deliver terrestrial carbon to the lake. Further evidence that rain and streamflow deliver land-derived material are increases in the Humification Index (an indicator of terrestrial material) following rain/flow events. Our results indicate that Tempe Town Lake generates autochthonous carbon and has the capacity to process allochthonous carbon from the urban environment. Ongoing work is comparing these results to other periods in the 10-year time series to test if the driver-DOC relationships are robust over longer time-scales and evaluating how changes in lake management and climate have altered DOC over time.

Temporal Patterns in Dissolved Organic Carbon Composition in an Urban Lake

NASA Astrophysics Data System (ADS)

Hartnett, H. E.; Palta, M. M.; Grimm, N. B.; Ruhi, A.; van Shaijik, M.

2017-12-01

Tempe Town Lake (TTL) is a hydrologically-regulated reservoir in Tempe, Arizona. The lake has high primary production and receives dissolved organic carbon (DOC) from rainfall, storm flow, and upstream river discharge. We applied an ARIMA time-series model to a three-year period for which we have high-frequency chemistry, meteorology, and streamflow data and analyzed external (rainfall, stream flow) and internal (dissolved O2) drivers of DOC content and composition. DOC composition was represented by fluorescence-based indices (fluorescence index, humification index, freshness) related to DOC source (microbially- vs. terrestrially-derived) and reactivity DOC. Patterns in DOC concentration and composition suggest carbon cycling in the lake responds to both meteorological events and to anthropogenic activity. The fluorescence-derived DOC composition is consistent with seasonally-distinct inputs of algal- and terrestrially-derived carbon. For example, Tempe Town Lake is supersaturated in O2 over 70% of the time, suggesting the system is autotrophic and primary productivity (i.e., O2 saturation state) was the strongest driver of DOC concentration. In contrast, external drivers (rainfall pattern, streamflow) were the strongest determinants of DOC composition. Biological processes (e.g., algal growth) generate carbon in the lake during spring and summer, and high Fluorescence Index and Freshness values at this time are indicative of algal-derived material; these parameters generally decrease with rain or flow suggesting algal-derived carbon is diluted by external water inputs. During dry periods, carbon builds up on the land surface and subsequent rainfall events deliver terrestrial carbon to the lake. Further evidence that rain and streamflow deliver land-derived material are increases in the Humification Index (an indicator of terrestrial material) following rain/flow events. Our results indicate that Tempe Town Lake generates autochthonous carbon and has the capacity to process allochthonous carbon from the urban environment. Ongoing work is comparing these results to other periods in the 10-year time series to test if the driver-DOC relationships are robust over longer time-scales and evaluating how changes in lake management and climate have altered DOC over time.

A Case Study: Climate Change Decision Support for the Apalachicola, Chattahoochee, Flint Basins

NASA Astrophysics Data System (ADS)

Day, G. N.; McMahon, G.; Friesen, N.; Carney, S.

2011-12-01

Riverside Technology, inc. has developed a Climate Change Decision Support System (DSS) to provide water managers with a tool to explore a range of current Global Climate Model (GCM) projections to evaluate their potential impacts on streamflow and the reliability of future water supplies. The system was developed as part of a National Oceanic and Atmospheric Administration (NOAA) Small Business Innovation Research (SBIR) project. The DSS uses downscaled GCM data as input to small-scale watershed models to produce time series of projected undepleted streamflow for various emission scenarios and GCM simulations. Until recently, water managers relied on historical streamflow data for water resources planning. In many parts of the country, great effort has been put into estimating long-term historical undepleted streamflow accounting for regulation, diversions, and return flows to support planning and water rights administration. In some cases, longer flow records have been constructed using paleohydrologic data in an attempt to capture climate variability beyond what is evident during the observed historical record. Now, many water managers are recognizing that historical data may not be representative of an uncertain climate future, and they have begun to explore the use of climate projections in their water resources planning. The Climate Change DSS was developed to support water managers in planning by accounting for both climate variability and potential climate change. In order to use the information for impact analysis, the projected streamflow time series can be exported and substituted for the historical streamflow data traditionally applied in their system operations models for water supply planning. This paper presents a case study in which climate-adjusted flows are coupled with the U.S. Army Corps of Engineers (USACE) ResSim model for the Apalachicola, Chattahoochee, and Flint (ACF) River basins. The study demonstrates how climate scenarios can be used with existing or proposed operating rules to explore the range of potential climate impacts on lake levels, drought trigger frequency, hydropower generation, and low-flow statistics. Initial system implementation of the Climate Change DSS was focused in the State of Colorado working with water supply agencies in the Front Range to assess local water supply vulnerability to climate change. To facilitate national implementation, the system capitalizes on National Weather Service (NWS) watershed models currently used for operational river forecasting. These models are well calibrated and available for the entire country. The system has been extended to include the ACF and the Sacramento River basins because of the importance of the water resources in these basins. Plans are now being made to expand coverage to include the Baltimore-Washington, D.C. water supply area. The DSS is operational and publicly available (www.climatechangedss.com).

Trends and sensitivities of low streamflow extremes to discharge timing and magnitude in pacific northwest mountain streams

USDA-ARS?s Scientific Manuscript database

Historical streamflow data from the Pacific Northwest indicate that the precipitation amount has been the dominant control on the magnitude of low streamflow extremes compared to the air temperature-affected timing of snowmelt runoff. The relative sensitivities of low streamflow to precipitation and...

Accuracy of time-domain and frequency-domain methods used to characterize catchment transit time distributions

NASA Astrophysics Data System (ADS)

Godsey, S. E.; Kirchner, J. W.

2008-12-01

The mean residence time - the average time that it takes rainfall to reach the stream - is a basic parameter used to characterize catchment processes. Heterogeneities in these processes lead to a distribution of travel times around the mean residence time. By examining this travel time distribution, we can better predict catchment response to contamination events. A catchment system with shorter residence times or narrower distributions will respond quickly to contamination events, whereas systems with longer residence times or longer-tailed distributions will respond more slowly to those same contamination events. The travel time distribution of a catchment is typically inferred from time series of passive tracers (e.g., water isotopes or chloride) in precipitation and streamflow. Variations in the tracer concentration in streamflow are usually damped compared to those in precipitation, because precipitation inputs from different storms (with different tracer signatures) are mixed within the catchment. Mathematically, this mixing process is represented by the convolution of the travel time distribution and the precipitation tracer inputs to generate the stream tracer outputs. Because convolution in the time domain is equivalent to multiplication in the frequency domain, it is relatively straightforward to estimate the parameters of the travel time distribution in either domain. In the time domain, the parameters describing the travel time distribution are typically estimated by maximizing the goodness of fit between the modeled and measured tracer outputs. In the frequency domain, the travel time distribution parameters can be estimated by fitting a power-law curve to the ratio of precipitation spectral power to stream spectral power. Differences between the methods of parameter estimation in the time and frequency domain mean that these two methods may respond differently to variations in data quality, record length and sampling frequency. Here we evaluate how well these two methods of travel time parameter estimation respond to different sources of uncertainty and compare the methods to one another. We do this by generating synthetic tracer input time series of different lengths, and convolve these with specified travel-time distributions to generate synthetic output time series. We then sample both the input and output time series at various sampling intervals and corrupt the time series with realistic error structures. Using these 'corrupted' time series, we infer the apparent travel time distribution, and compare it to the known distribution that was used to generate the synthetic data in the first place. This analysis allows us to quantify how different record lengths, sampling intervals, and error structures in the tracer measurements affect the apparent mean residence time and the apparent shape of the travel time distribution.

Objective Use of Climate Indices to Inform Ensemble Streamflow Forecasts in the Columbia River Basin - An Initial Review

NASA Astrophysics Data System (ADS)

Pytlak, E.; McManamon, A.; Hughes, S. P.; Van Der Zweep, R. A.; Butcher, P.; Karafotias, C.; Beckers, J.; Welles, E.

2016-12-01

Numerous studies have documented the impacts that large scale weather patterns and climate phenomenon like the El Niño Southern Oscillation (ENSO), Pacific-North American (PNA) Pattern, and others can have on seasonal temperature and precipitation in the Columbia River Basin (CRB). While far from perfect in terms of seasonal predictability in specific locations, these intra-annual weather and climate signal do tilt the odds toward different temperature and precipitation outcomes, which in turn can have impacts on seasonal snowpacks, streamflows and water supply in large river basins like the CRB. We hypothesize that intraseasonal climate signals and long wave jet stream patterns can be objectively incorporated into what it is otherwise a climatology-based set of Ensemble Streamflow Forecasts, and can increase the predictive skill and utility of these forecasts used for mid-range hydropower planning. The Bonneville Power Administration (BPA) and Deltares have developed a subsampling-resampling method to incorporate climate mode information into the Ensemble Streamflow Prediction (ESP) forecasts (Beckers, et al., 2016). Since 2015, BPA and Deltares USA have experimented with this method in pre-operational use, using five objective multivariate climate indices that appear to have the greatest predictive value for seasonal temperature and precipitation in the CRB. The indices are used to objectively select historical weather from about twenty analog years in the 66-year (1949-2015) historical ESP set. These twenty scenarios then serve as the starting point to generate monthly synthetic weather and streamflow time series to return to a set of 66 streamflow traces. Our poster will share initial results from the 2015 and 2016 water years, which included large swings in the Quasi-Biennial Oscillation, persistent blocking jet stream patterns, and the development of a strong El Niño event. While the results are very preliminary and for only two seasons, there may be some value in incorporating objectively-identified climate signals into ESP-based streamflow forecasts.Beckers, J. V. L., Weerts, A. H., Tijdeman, E., and Welles, E.: ENSO-Conditioned Weather Resampling Method for Seasonal Ensemble Streamflow Prediction, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-72, in review, 2016.

Historical floods reconstruction using NOAA 20CR global climate reanalysis over the last 150 years

NASA Astrophysics Data System (ADS)

Mathevet, T.; Brigode, P.; Jégonday, S.; Hingray, B.; Gailhard, J.; Wilhelm, B.

2017-12-01

Since several years, climatologists are producing long reanalysis for studying the variability of global climate over the last 150 years. For hydrologists, these datasets offer interesting opportunities for reconstructing historical flood events, and thus increasing the sample size used for flood frequency analysis. In this study, a streamflow reconstruction method based on the analogy of atmospheric situations (using NOAA 20CR reanalysis) for the reconstruction of climatic series and on a rainfall-runoff model for the streamflow reconstruction has been applied over different French catchments at the daily timestep. The studied catchments have been selected because of the availability of long observed streamflow series (used for quantifying the performances of the flood reconstructions) and for their different hydro-climatological regimes. Different methodologies have been tested for the reconstruction of daily climatic series over the 1851-2014 period, using geopotential heights and additional variables available within the 20CR reanalysis (relative humidity, precipitable water, etc.). Long observed climatic series have also been used when available as a reference for the climatic reconstructions. The different reconstruction methods have been finally ranked in terms of their historical flood reconstruction performances, quantified by flood types (autumn or winter floods) and atmospheric genesis (using a weather pattern classification). The obtained results indicate that using additional 20CR variables to the geopotential heights only slightly improve the flood reconstructions, while using observed climatic series improves significantly the flood reconstruction over the different catchments.

The Application of Censored Regression Models in Low Streamflow Analyses

NASA Astrophysics Data System (ADS)

Kroll, C.; Luz, J.

2003-12-01

Estimation of low streamflow statistics at gauged and ungauged river sites is often a daunting task. This process is further confounded by the presence of intermittent streamflows, where streamflow is sometimes reported as zero, within a region. Streamflows recorded as zero may be zero, or may be less than the measurement detection limit. Such data is often referred to as censored data. Numerous methods have been developed to characterize intermittent streamflow series. Logit regression has been proposed to develop regional models of the probability annual lowflows series (such as 7-day lowflows) are zero. In addition, Tobit regression, a method of regression that allows for censored dependent variables, has been proposed for lowflow regional regression models in regions where the lowflow statistic of interest estimated as zero at some sites in the region. While these methods have been proposed, their use in practice has been limited. Here a delete-one jackknife simulation is presented to examine the performance of Logit and Tobit models of 7-day annual minimum flows in 6 USGS water resource regions in the United States. For the Logit model, an assessment is made of whether sites are correctly classified as having at least 10% of 7-day annual lowflows equal to zero. In such a situation, the 7-day, 10-year lowflow (Q710), a commonly employed low streamflow statistic, would be reported as zero. For the Tobit model, a comparison is made between results from the Tobit model, and from performing either ordinary least squares (OLS) or principal component regression (PCR) after the zero sites are dropped from the analysis. Initial results for the Logit model indicate this method to have a high probability of correctly classifying sites into groups with Q710s as zero and non-zero. Initial results also indicate the Tobit model produces better results than PCR and OLS when more than 5% of the sites in the region have Q710 values calculated as zero.

A statistical analysis of the daily streamflow hydrograph

NASA Astrophysics Data System (ADS)

Kavvas, M. L.; Delleur, J. W.

1984-03-01

In this study a periodic statistical analysis of daily streamflow data in Indiana, U.S.A., was performed to gain some new insight into the stochastic structure which describes the daily streamflow process. This analysis was performed by the periodic mean and covariance functions of the daily streamflows, by the time and peak discharge -dependent recession limb of the daily streamflow hydrograph, by the time and discharge exceedance level (DEL) -dependent probability distribution of the hydrograph peak interarrival time, and by the time-dependent probability distribution of the time to peak discharge. Some new statistical estimators were developed and used in this study. In general features, this study has shown that: (a) the persistence properties of daily flows depend on the storage state of the basin at the specified time origin of the flow process; (b) the daily streamflow process is time irreversible; (c) the probability distribution of the daily hydrograph peak interarrival time depends both on the occurrence time of the peak from which the inter-arrival time originates and on the discharge exceedance level; and (d) if the daily streamflow process is modeled as the release from a linear watershed storage, this release should depend on the state of the storage and on the time of the release as the persistence properties and the recession limb decay rates were observed to change with the state of the watershed storage and time. Therefore, a time-varying reservoir system needs to be considered if the daily streamflow process is to be modeled as the release from a linear watershed storage.

A Nonparametric Approach For Representing Interannual Dependence In Monthly Streamflow Sequences

NASA Astrophysics Data System (ADS)

Sharma, A.; Oneill, R.

The estimation of risks associated with water management plans requires generation of synthetic streamflow sequences. The mathematical algorithms used to generate these sequences at monthly time scales are found lacking in two main respects: inability in preserving dependence attributes particularly at large (seasonal to interannual) time lags; and, a poor representation of observed distributional characteristics, in partic- ular, representation of strong assymetry or multimodality in the probability density function. Proposed here is an alternative that naturally incorporates both observed de- pendence and distributional attributes in the generated sequences. Use of a nonpara- metric framework provides an effective means for representing the observed proba- bility distribution, while the use of a Svariable kernelT ensures accurate modeling of & cedil;streamflow data sets that contain a substantial number of zero flow values. A careful selection of prior flows imparts the appropriate short-term memory, while use of an SaggregateT flow variable allows representation of interannual dependence. The non- & cedil;parametric simulation model is applied to monthly flows from the Beaver River near Beaver, Utah, USA, and the Burrendong dam inflows, New South Wales, Australia. Results indicate that while the use of traditional simulation approaches leads to an inaccurate representation of dependence at long (annual and interannual) time scales, the proposed model can simulate both short and long-term dependence. As a result, the proposed model ensures a significantly improved representation of reservoir storage statistics, particularly for systems influenced by long droughts. It is important to note that the proposed method offers a simpler and better alternative to conventional dis- aggregation models as: (a) a separate annual flow series is not required, (b) stringent assumptions relating annual and monthly flows are not needed, and (c) the method does not require the specification of a "water year", instead ensuring that the sum of any sequence of flows lasting twelve months will result in the type of dependence that is observed in the historical annual flow series.

Trends and sensitivities of low streamflow extremes to discharge timing and magnitude in Pacific Northwest mountain streams

Treesearch

Patrick R. Kormos; Charlie Luce; Seth J. Wenger; Wouter R. Berghuijs

2016-01-01

Path analyses of historical streamflow data from the Pacific Northwest indicate that the precipitation amount has been the dominant control on the magnitude of low streamflow extremes compared to the air temperature-affected timing of snowmelt runoff. The relative sensitivities of low streamflow to precipitation and temperature changes have important...

An analysis of annual maximum streamflows in Terengganu, Malaysia using TL-moments approach

NASA Astrophysics Data System (ADS)

Ahmad, Ummi Nadiah; Shabri, Ani; Zakaria, Zahrahtul Amani

2013-02-01

TL-moments approach has been used in an analysis to determine the best-fitting distributions to represent the annual series of maximum streamflow data over 12 stations in Terengganu, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: generalized pareto (GPA), generalized logistic, and generalized extreme value distribution. The influence of TL-moments on estimated probability distribution functions are examined by evaluating the relative root mean square error and relative bias of quantile estimates through Monte Carlo simulations. The boxplot is used to show the location of the median and the dispersion of the data, which helps in reaching the decisive conclusions. For most of the cases, the results show that TL-moments with one smallest value was trimmed from the conceptual sample (TL-moments (1,0)), of GPA distribution was the most appropriate in majority of the stations for describing the annual maximum streamflow series in Terengganu, Malaysia.

Analytical flow duration curves for summer streamflow in Switzerland

NASA Astrophysics Data System (ADS)

Santos, Ana Clara; Portela, Maria Manuela; Rinaldo, Andrea; Schaefli, Bettina

2018-04-01

This paper proposes a systematic assessment of the performance of an analytical modeling framework for streamflow probability distributions for a set of 25 Swiss catchments. These catchments show a wide range of hydroclimatic regimes, including namely snow-influenced streamflows. The model parameters are calculated from a spatially averaged gridded daily precipitation data set and from observed daily discharge time series, both in a forward estimation mode (direct parameter calculation from observed data) and in an inverse estimation mode (maximum likelihood estimation). The performance of the linear and the nonlinear model versions is assessed in terms of reproducing observed flow duration curves and their natural variability. Overall, the nonlinear model version outperforms the linear model for all regimes, but the linear model shows a notable performance increase with catchment elevation. More importantly, the obtained results demonstrate that the analytical model performs well for summer discharge for all analyzed streamflow regimes, ranging from rainfall-driven regimes with summer low flow to snow and glacier regimes with summer high flow. These results suggest that the model's encoding of discharge-generating events based on stochastic soil moisture dynamics is more flexible than previously thought. As shown in this paper, the presence of snowmelt or ice melt is accommodated by a relative increase in the discharge-generating frequency, a key parameter of the model. Explicit quantification of this frequency increase as a function of mean catchment meteorological conditions is left for future research.

Artificial Neural Network Models for Long Lead Streamflow Forecasts using Climate Information

NASA Astrophysics Data System (ADS)

Kumar, J.; Devineni, N.

2007-12-01

Information on season ahead stream flow forecasts is very beneficial for the operation and management of water supply systems. Daily streamflow conditions at any particular reservoir primarily depend on atmospheric and land surface conditions including the soil moisture and snow pack. On the other hand recent studies suggest that developing long lead streamflow forecasts (3 months ahead) typically depends on exogenous climatic conditions particularly Sea Surface Temperature conditions (SST) in the tropical oceans. Examples of some oceanic variables are El Nino Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Identification of such conditions that influence the moisture transport into a given basin poses many challenges given the nonlinear dependency between the predictors (SST) and predictand (stream flows). In this study, we apply both linear and nonlinear dependency measures to identify the predictors that influence the winter flows into the Neuse basin. The predictor identification approach here adopted uses simple correlation coefficients to spearman rank correlation measures for detecting nonlinear dependency. All these dependency measures are employed with a lag 3 time series of the high flow season (January - February - March) using 75 years (1928-2002) of stream flows recorded in to the Falls Lake, Neuse River Basin. Developing streamflow forecasts contingent on these exogenous predictors will play an important role towards improved water supply planning and management. Recently, the soft computing techniques, such as artificial neural networks (ANNs) have provided an alternative method to solve complex problems efficiently. ANNs are data driven models which trains on the examples given to it. The ANNs functions as universal approximators and are non linear in nature. This paper presents a study aiming towards using climatic predictors for 3 month lead time streamflow forecast. ANN models representing the physical process of the system are developed between the identified predictors and the predictand. Predictors used are the scores of Principal Components Analysis (PCA). The models were tested and validated. The feed- forward multi-layer perceptron (MLP) type neural networks trained using the back-propagation algorithms are employed in the current study. The performance of the ANN-model forecasts are evaluated using various performance evaluation measures such as correlation coefficient, root mean square error (RMSE). The preliminary results shows that ANNs are efficient to forecast long lead time streamflows using climatic predictors.

Documenting the stages and streamflows associated with the 2011 activation of the New Madrid Floodway, Missouri: Chapter E in 2011 floods of the central United States

USGS Publications Warehouse

Koenig, Todd A.; Holmes, Robert R.

2013-01-01

The U.S. Geological Survey initiated a substantial effort in the summer of 2011 to measure and document the record-setting floods of the Mississippi and Ohio Rivers, including the reach in and near the New Madrid Floodway. The activation of the floodway, which had not occurred since 1937, provided a rare opportunity to collect a unique dataset describing a flood wave downstream from a levee breach as well as the flow through a large floodway. A total of 42 submersible pressure transducers collected time series of water levels while crews collected hundreds of depth, velocity, and streamflow measurements at selected locations in and near the floodway throughout the period from late April to late June. These data are presented in this chapter.

Integrating remotely sensed surface water extent into continental scale hydrology

NASA Astrophysics Data System (ADS)

Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad

2016-12-01

In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R2, RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that remotely sensed surface water extent holds potential for improving rainfall-runoff streamflow simulations, potentially leading to a better forecast of the peak flow.

Moving horizon estimation for assimilating H-SAF remote sensing data into the HBV hydrological model

NASA Astrophysics Data System (ADS)

Montero, Rodolfo Alvarado; Schwanenberg, Dirk; Krahe, Peter; Lisniak, Dmytro; Sensoy, Aynur; Sorman, A. Arda; Akkol, Bulut

2016-06-01

Remote sensing information has been extensively developed over the past few years including spatially distributed data for hydrological applications at high resolution. The implementation of these products in operational flow forecasting systems is still an active field of research, wherein data assimilation plays a vital role on the improvement of initial conditions of streamflow forecasts. We present a novel implementation of a variational method based on Moving Horizon Estimation (MHE), in application to the conceptual rainfall-runoff model HBV, to simultaneously assimilate remotely sensed snow covered area (SCA), snow water equivalent (SWE), soil moisture (SM) and in situ measurements of streamflow data using large assimilation windows of up to one year. This innovative application of the MHE approach allows to simultaneously update precipitation, temperature, soil moisture as well as upper and lower zones water storages of the conceptual model, within the assimilation window, without an explicit formulation of error covariance matrixes and it enables a highly flexible formulation of distance metrics for the agreement of simulated and observed variables. The framework is tested in two data-dense sites in Germany and one data-sparse environment in Turkey. Results show a potential improvement of the lead time performance of streamflow forecasts by using perfect time series of state variables generated by the simulation of the conceptual rainfall-runoff model itself. The framework is also tested using new operational data products from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) of EUMETSAT. This study is the first application of H-SAF products to hydrological forecasting systems and it verifies their added value. Results from assimilating H-SAF observations lead to a slight reduction of the streamflow forecast skill in all three cases compared to the assimilation of streamflow data only. On the other hand, the forecast skill of soil moisture shows a significant improvement.

Characterizing the Recurrence of Hydrologic Droughts

NASA Astrophysics Data System (ADS)

Cancelliere, A.; Salas, J. D.

2002-12-01

Characterizing periods of deficit and drought has been an important aspect in planning and management of water resources systems for many decades. An extreme drought is a complex phenomenon that evolves through time and space in a random fashion. It may be characterized by its initiation, duration, severity (magnitude or intensity), spatial extent, and termination. These characteristics may be determined by comparing the water supply time series versus the corresponding water demand series in the area of consideration. Because the water supply quantities such as rainfall and streamflow are stochastic variables the ensuing drought characteristics are random and must be described in probabilistic terms. Let us consider a periodic stochastic water supply and a variable water demand series. A drought event is defined as a succession of consecutive periods (run) in which the water supply remains below the water demand. Thus, the drought length L (negative run length) is the number of consecutive time intervals (seasons) in which the water supply remains below the water demand, preceded and followed by (at least one season where) the water supply is equal or greater than the demand. Likewise, the difference between the water demand and the supply at time t is the magnitude of the deficit at time t so that the accumulated deficit D (drought magnitude) is the sum of the deficits over the drought duration L. In the study reported herein, the probability density functions (pdf) of drought length and drought magnitude and their low order moments are derived assuming that the underlying water supply series after is clipped by a constant or periodic water demand results in a periodic dependent binary series that is represented by a periodic two-state Markov chain. The derived pdfs allow estimating the occurrence probabilities of droughts of a given length where either the drought begins in a given season or regardless of the initial season. In addition, the return periods of droughts (based on length and magnitude) are determined. The applicability of the drought formulations is illustrated using several series of precipitation and streamflow in Sicily, Italy and Colorado, USA. The results obtained show an excellent agreement between the observed and theoretical results. In conclusion, the proposed methods appear to be a useful addition for drought analysis and characterization using stochastic methods.

Short-term ensemble streamflow forecasting using operationally-produced single-valued streamflow forecasts - A Hydrologic Model Output Statistics (HMOS) approach

NASA Astrophysics Data System (ADS)

Regonda, Satish Kumar; Seo, Dong-Jun; Lawrence, Bill; Brown, James D.; Demargne, Julie

2013-08-01

We present a statistical procedure for generating short-term ensemble streamflow forecasts from single-valued, or deterministic, streamflow forecasts produced operationally by the U.S. National Weather Service (NWS) River Forecast Centers (RFCs). The resulting ensemble streamflow forecast provides an estimate of the predictive uncertainty associated with the single-valued forecast to support risk-based decision making by the forecasters and by the users of the forecast products, such as emergency managers. Forced by single-valued quantitative precipitation and temperature forecasts (QPF, QTF), the single-valued streamflow forecasts are produced at a 6-h time step nominally out to 5 days into the future. The single-valued streamflow forecasts reflect various run-time modifications, or "manual data assimilation", applied by the human forecasters in an attempt to reduce error from various sources in the end-to-end forecast process. The proposed procedure generates ensemble traces of streamflow from a parsimonious approximation of the conditional multivariate probability distribution of future streamflow given the single-valued streamflow forecast, QPF, and the most recent streamflow observation. For parameter estimation and evaluation, we used a multiyear archive of the single-valued river stage forecast produced operationally by the NWS Arkansas-Red River Basin River Forecast Center (ABRFC) in Tulsa, Oklahoma. As a by-product of parameter estimation, the procedure provides a categorical assessment of the effective lead time of the operational hydrologic forecasts for different QPF and forecast flow conditions. To evaluate the procedure, we carried out hindcasting experiments in dependent and cross-validation modes. The results indicate that the short-term streamflow ensemble hindcasts generated from the procedure are generally reliable within the effective lead time of the single-valued forecasts and well capture the skill of the single-valued forecasts. For smaller basins, however, the effective lead time is significantly reduced by short basin memory and reduced skill in the single-valued QPF.

Development of a Precipitation-Runoff Model to Simulate Unregulated Streamflow in the Salmon Creek Basin, Okanogan County, Washington

USGS Publications Warehouse

van Heeswijk, Marijke

2006-01-01

Surface water has been diverted from the Salmon Creek Basin for irrigation purposes since the early 1900s, when the Bureau of Reclamation built the Okanogan Project. Spring snowmelt runoff is stored in two reservoirs, Conconully Reservoir and Salmon Lake Reservoir, and gradually released during the growing season. As a result of the out-of-basin streamflow diversions, the lower 4.3 miles of Salmon Creek typically has been a dry creek bed for almost 100 years, except during the spring snowmelt season during years of high runoff. To continue meeting the water needs of irrigators but also leave water in lower Salmon Creek for fish passage and to help restore the natural ecosystem, changes are being considered in how the Okanogan Project is operated. This report documents development of a precipitation-runoff model for the Salmon Creek Basin that can be used to simulate daily unregulated streamflows. The precipitation-runoff model is a component of a Decision Support System (DSS) that includes a water-operations model the Bureau of Reclamation plans to develop to study the water resources of the Salmon Creek Basin. The DSS will be similar to the DSS that the Bureau of Reclamation and the U.S. Geological Survey developed previously for the Yakima River Basin in central southern Washington. The precipitation-runoff model was calibrated for water years 1950-89 and tested for water years 1990-96. The model was used to simulate daily streamflows that were aggregated on a monthly basis and calibrated against historical monthly streamflows for Salmon Creek at Conconully Dam. Additional calibration data were provided by the snowpack water-equivalent record for a SNOTEL station in the basin. Model input time series of daily precipitation and minimum and maximum air temperatures were based on data from climate stations in the study area. Historical records of unregulated streamflow for Salmon Creek at Conconully Dam do not exist for water years 1950-96. Instead, estimates of historical monthly mean unregulated streamflow based on reservoir outflows and storage changes were used as a surrogate for the missing data and to calibrate and test the model. The estimated unregulated streamflows were corrected for evaporative losses from Conconully Reservoir (about 1 ft3/s) and ground-water losses from the basin (about 2 ft3/s). The total of the corrections was about 9 percent of the mean uncorrected streamflow of 32.2 ft3/s (23,300 acre-ft/yr) for water years 1949-96. For the calibration period, the basinwide mean annual evapotranspiration was simulated to be 19.1 inches, or about 83 percent of the mean annual precipitation of 23.1 inches. Model calibration and testing indicated that the daily streamflows simulated using the precipitation-runoff model should be used only to analyze historical and forecasted annual mean and April-July mean streamflows for Salmon Creek at Conconully Dam. Because of the paucity of model input data and uncertainty in the estimated unregulated streamflows, the model is not adequately calibrated and tested to estimate monthly mean streamflows for individual months, such as during low-flow periods, or for shorter periods such as during peak flows. No data were available to test the accuracy of simulated streamflows for lower Salmon Creek. As a result, simulated streamflows for lower Salmon Creek should be used with caution. For the calibration period (water years 1950-89), both the simulated mean annual streamflow and the simulated mean April-July streamflow compared well with the estimated uncorrected unregulated streamflow (UUS) and corrected unregulated streamflow (CUS). The simulated mean annual streamflow exceeded UUS by 5.9 percent and was less than CUS by 2.7 percent. Similarly, the simulated mean April-July streamflow exceeded UUS by 1.8 percent and was less than CUS by 3.1 percent. However, streamflow was significantly undersimulated during the low-flow, baseflow-dominated months of November through F

Carolinas Coastal Change Processes Project data report for nearshore observations at Cape Hatteras, North Carolina

USGS Publications Warehouse

Armstrong, Brandy N.; Warner, John C.; Voulgaris, George; List, Jeffrey H.; Thieler, Robert; Martini, Marinna A.; Montgomery, Ellyn T.; McNinch, Jesse E.; Book, Jeffrey W.; Haas, Kevin

2013-01-01

An oceanographic field study conducted in February 2010 investigated processes that control nearshore flow and sediment transport dynamics at Cape Hatteras, North Carolina. This report describes the project background, field program, instrumentation setup, and locations of the sensor deployments. The data collected, and supporting meteorological and streamflow observations, are presented as time-series plots for data visualization. Additionally, the data are available as part of this report.

Climate model assessment of changes in winter-spring streamflow timing over North America

USGS Publications Warehouse

Kam, Jonghun; Knutson, Thomas R.; Milly, Paul C. D.

2018-01-01

Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.

New method for calculating a mathematical expression for streamflow recession

USGS Publications Warehouse

Rutledge, Albert T.

1991-01-01

An empirical method has been devised to calculate the master recession curve, which is a mathematical expression for streamflow recession during times of negligible direct runoff. The method is based on the assumption that the storage-delay factor, which is the time per log cycle of streamflow recession, varies linearly with the logarithm of streamflow. The resulting master recession curve can be nonlinear. The method can be executed by a computer program that reads a data file of daily mean streamflow, then allows the user to select several near-linear segments of streamflow recession. The storage-delay factor for each segment is one of the coefficients of the equation that results from linear least-squares regression. Using results for each recession segment, a mathematical expression of the storage-delay factor as a function of the log of streamflow is determined by linear least-squares regression. The master recession curve, which is a second-order polynomial expression for time as a function of log of streamflow, is then derived using the coefficients of this function.

Reconstruction and analysis of the past five centuries of streamflow on northern slopes on Tianshan Mountains in Northern Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Yuhui; Chen, Yaning; Wang, Minzhong; Sun, Huilan

2017-07-01

We examined the changes in streamflow on the northern slopes of the Tianshan Mountains in northern Xinjiang, China, over two time scales: the past 500 years, based on dendrochronology data; and the past 50 years, based on streamflow data from hydrological stations. The method of artificial neural networks built from the data of the 50-year period was used to reconstruct the streamflow of the 500-year period. The results indicate that streamflow has undergone seven high-flow periods and four low-flow periods during the past 500 years. To identify possible transition points in the streamflow, we applied the Mann-Kendall and running T tests to the 50- and 500-year periods, respectively. During the past 500 years, streamflow has changed significantly from low to high flow about three to four times, and from high to low flow about three to five times. Over the recent 50 years, there have been three phases of variation in river runoff, and the most distinct transition of streamflow occurred in 1996.

Maximum likelihood estimation for periodic autoregressive moving average models

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

A useful class of models for seasonal time series that cannot be filtered or standardized to achieve second-order stationarity is that of periodic autoregressive moving average (PARMA) models, which are extensions of ARMA models that allow periodic (seasonal) parameters. An approximation to the exact likelihood for Gaussian PARMA processes is developed, and a straightforward algorithm for its maximization is presented. The algorithm is tested on several periodic ARMA(1, 1) models through simulation studies and is compared to moment estimation via the seasonal Yule-Walker equations. Applicability of the technique is demonstrated through an analysis of a seasonal stream-flow series from the Rio Caroni River in Venezuela.

Estimating the Exceedance Probability of the Reservoir Inflow Based on the Long-Term Weather Outlooks

NASA Astrophysics Data System (ADS)

Huang, Q. Z.; Hsu, S. Y.; Li, M. H.

2016-12-01

The long-term streamflow prediction is important not only to estimate water-storage of a reservoir but also to the surface water intakes, which supply people's livelihood, agriculture, and industry. Climatology forecasts of streamflow have been traditionally used for calculating the exceedance probability curve of streamflow and water resource management. In this study, we proposed a stochastic approach to predict the exceedance probability curve of long-term streamflow with the seasonal weather outlook from Central Weather Bureau (CWB), Taiwan. The approach incorporates a statistical downscale weather generator and a catchment-scale hydrological model to convert the monthly outlook into daily rainfall and temperature series and to simulate the streamflow based on the outlook information. Moreover, we applied Bayes' theorem to derive a method for calculating the exceedance probability curve of the reservoir inflow based on the seasonal weather outlook and its imperfection. The results show that our approach can give the exceedance probability curves reflecting the three-month weather outlook and its accuracy. We also show how the improvement of the weather outlook affects the predicted exceedance probability curves of the streamflow. Our approach should be useful for the seasonal planning and management of water resource and their risk assessment.

Comparison of detrending methods for fluctuation analysis in hydrology

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Chen, Yongqin David

2011-03-01

SummaryTrends within a hydrologic time series can significantly influence the scaling results of fluctuation analysis, such as rescaled range (RS) analysis and (multifractal) detrended fluctuation analysis (MF-DFA). Therefore, removal of trends is important in the study of scaling properties of the time series. In this study, three detrending methods, including adaptive detrending algorithm (ADA), Fourier-based method, and average removing technique, were evaluated by analyzing numerically generated series and observed streamflow series with obvious relative regular periodic trend. Results indicated that: (1) the Fourier-based detrending method and ADA were similar in detrending practices, and given proper parameters, these two methods can produce similarly satisfactory results; (2) detrended series by Fourier-based detrending method and ADA lose the fluctuation information at larger time scales, and the location of crossover points is heavily impacted by the chosen parameters of these two methods; and (3) the average removing method has an advantage over the other two methods, i.e., the fluctuation information at larger time scales is kept well-an indication of relatively reliable performance in detrending. In addition, the average removing method performed reasonably well in detrending a time series with regular periods or trends. In this sense, the average removing method should be preferred in the study of scaling properties of the hydrometeorolgical series with relative regular periodic trend using MF-DFA.

Streamflow statistics for unregulated and regulated conditions for selected locations on the Yellowstone, Tongue, and Powder Rivers, Montana, 1928-2002

USGS Publications Warehouse

Chase, Katherine J.

2013-01-01

Major floods in 1996 and 1997 on the Yellowstone River in Montana intensified public debate over the effects of human activities on the Yellowstone River. In 1999, the Yellowstone River Conservation District Council was formed to address conservation issues on the river. The Yellowstone River Conservation District Council partnered with the U.S. Army Corps of Engineers to conduct a cumulative-effects study on the main stem of the Yellowstone River. The cumulative-effects study is intended to provide a basis for future management decisions in the watershed. Streamflow statistics, such as flow-frequency and flow-duration data calculated for unregulated and regulated streamflow conditions, are a necessary component of the cumulative effects study. The U.S. Geological Survey, in cooperation with the Yellowstone River Conservation District Council and the U.S. Army Corps of Engineers, calculated streamflow statistics for unregulated and regulated conditions for the Yellowstone, Tongue, and Powder Rivers for the 1928–2002 study period. Unregulated streamflow represents flow conditions that might have occurred during the 1928–2002 study period if there had been no water-resources development in the Yellowstone River Basin. Regulated streamflow represents estimates of flow conditions during the 1928–2002 study period if the level of water-resources development existing in 2002 was in place during the entire study period. Peak-flow frequency estimates for regulated and unregulated streamflow were developed using methods described in Bulletin 17B. High-flow frequency and low-flow frequency data were developed for regulated and unregulated streamflows from the annual series of highest and lowest (respectively) mean flows for specified n-day consecutive periods within the calendar year. Flow-duration data, and monthly and annual streamflow characteristics, also were calculated for the unregulated and regulated streamflows.

Skilful seasonal forecasts of streamflow over Europe?

NASA Astrophysics Data System (ADS)

Arnal, Louise; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; Prudhomme, Christel; Neumann, Jessica; Krzeminski, Blazej; Pappenberger, Florian

2018-04-01

This paper considers whether there is any added value in using seasonal climate forecasts instead of historical meteorological observations for forecasting streamflow on seasonal timescales over Europe. A Europe-wide analysis of the skill of the newly operational EFAS (European Flood Awareness System) seasonal streamflow forecasts (produced by forcing the Lisflood model with the ECMWF System 4 seasonal climate forecasts), benchmarked against the ensemble streamflow prediction (ESP) forecasting approach (produced by forcing the Lisflood model with historical meteorological observations), is undertaken. The results suggest that, on average, the System 4 seasonal climate forecasts improve the streamflow predictability over historical meteorological observations for the first month of lead time only (in terms of hindcast accuracy, sharpness and overall performance). However, the predictability varies in space and time and is greater in winter and autumn. Parts of Europe additionally exhibit a longer predictability, up to 7 months of lead time, for certain months within a season. In terms of hindcast reliability, the EFAS seasonal streamflow hindcasts are on average less skilful than the ESP for all lead times. The results also highlight the potential usefulness of the EFAS seasonal streamflow forecasts for decision-making (measured in terms of the hindcast discrimination for the lower and upper terciles of the simulated streamflow). Although the ESP is the most potentially useful forecasting approach in Europe, the EFAS seasonal streamflow forecasts appear more potentially useful than the ESP in some regions and for certain seasons, especially in winter for almost 40 % of Europe. Patterns in the EFAS seasonal streamflow hindcast skill are however not mirrored in the System 4 seasonal climate hindcasts, hinting at the need for a better understanding of the link between hydrological and meteorological variables on seasonal timescales, with the aim of improving climate-model-based seasonal streamflow forecasting.

Assess Climate Change's Impact on Coastal Rivers using a Coupled Climate-Hydrology Model

NASA Astrophysics Data System (ADS)

Xue, Z. G.; Gochis, D.; Yu, W.; Zang, Z.; Sampson, K. M.; Keim, B. D.

2016-12-01

In this study we present a coupled climate-hydrological model reproducing the water cycle of three coastal river basins along the northern Gulf of Mexico for the past three decades (1985-2014). Model simulated climate condition, surface physics, and streamflow were well validated against in situ data and satellite-derived products, giving us the confidence that the newly developed WRF-Hydro model can be a robust tool for evaluating climate change's impact on hydrological regime. Trend analysis of model simulated monthly and annual time series indicates that local climate is getting hotter and dryer, specifically during the growing season. Wavelet analysis reveals that local evapotranspiration is strongly correlated with temperature, while soil moisture, water surplus, and streamflow are coupled with precipitation. In addition, local climate is closely correlated with large-scale climate dynamics such as AMO and ENSO. A possible change-point is detected around year 2004, after which, the monthly precipitation decreased by 14.2%, evapotranspiration increased by 2.9%, and water surplus decreased by 36.5%. The implication of the difference between the water surplus (runoff) calculated using the classic Thornthwaite method and river discharge estimated using streamflow records to the coastal environment is also discussed.

Estimating ice-affected streamflow by extended Kalman filtering

USGS Publications Warehouse

Holtschlag, D.J.; Grewal, M.S.

1998-01-01

An extended Kalman filter was developed to automate the real-time estimation of ice-affected streamflow on the basis of routine measurements of stream stage and air temperature and on the relation between stage and streamflow during open-water (ice-free) conditions. The filter accommodates three dynamic modes of ice effects: sudden formation/ablation, stable ice conditions, and eventual elimination. The utility of the filter was evaluated by applying it to historical data from two long-term streamflow-gauging stations, St. John River at Dickey, Maine and Platte River at North Bend, Nebr. Results indicate that the filter was stable and that parameters converged for both stations, producing streamflow estimates that are highly correlated with published values. For the Maine station, logarithms of estimated streamflows are within 8% of the logarithms of published values 87.2% of the time during periods of ice effects and within 15% 96.6% of the time. Similarly, for the Nebraska station, logarithms of estimated streamflows are within 8% of the logarithms of published values 90.7% of the time and within 15% 97.7% of the time. In addition, the correlation between temporal updates and published streamflows on days of direct measurements at the Maine station was 0.777 and 0.998 for ice-affected and open-water periods, respectively; for the Nebraska station, corresponding correlations were 0.864 and 0.997.

Flood events across the North Atlantic region - past development and future perspectives

NASA Astrophysics Data System (ADS)

Matti, Bettina; Dieppois, Bastien; Lawler, Damian; Dahlke, Helen E.; Lyon, Steve W.

2016-04-01

Flood events have a large impact on humans, both socially and economically. An increase in winter and spring flooding across much of northern Europe in recent years opened up the question of changing underlying hydro-climatic drivers of flood events. Predicting the manifestation of such changes is difficult due to the natural variability and fluctuations in northern hydrological systems caused by large-scale atmospheric circulations, especially under altered climate conditions. Improving knowledge on the complexity of these hydrological systems and their interactions with climate is essential to be able to determine drivers of flood events and to predict changes in these drivers under altered climate conditions. This is particularly true for the North Atlantic region where both physical catchment properties and large-scale atmospheric circulations have a profound influence on floods. This study explores changes in streamflow across North Atlantic region catchments. An emphasis is placed on high-flow events, namely the timing and magnitude of past flood events, and selected flood percentiles were tested for stationarity by applying a flood frequency analysis. The issue of non-stationarity of flood return periods is important when linking streamflow to large-scale atmospheric circulations. Natural fluctuations in these circulations are found to have a strong influence on the outcome causing natural variability in streamflow records. Long time series and a multi-temporal approach allows for determining drivers of floods and linking streamflow to large-scale atmospheric circulations. Exploring changes in selected hydrological signatures consistency was found across much of the North Atlantic region suggesting a shift in flow regime. The lack of an overall regional pattern suggests that how catchments respond to changes in climatic drivers is strongly influenced by their physical characteristics. A better understanding of hydrological response to climate drivers is essential for example for forecasting purposes.

Water Resources Data for Oregon, Water Year 2002

USGS Publications Warehouse

Herrett, T.A.; Hess, G.W.; House, J.G.; Ruppert, G.P.; Courts, M.L.

2003-01-01

The annual Oregon hydrologic data report is one of a series of annual reports that document hydrologic data gathered from the U.S. Geological Survey's surface- and ground-water data-collection networks in each State, Puerto Rico, and the Trust Territories. These records of streamflow, ground-water levels, and quality of water provide the hydrologic information needed by State, local and Federal agencies, and the private sector for developing and managing our Nation's land and water resources. This report includes records on both surface and ground water in the State and contains discharge records for 181 stream-gaging stations, 47 partial-record or miscellaneous streamflow stations, and 8 crest-stage partial-record streamflow stations; stage-only records for 6 gaging stations; stage and content records for 26 lakes and reservoirs; and water-quality records for 127 streamflow-gaging stations, 2 atmospheric deposition stations, and 11 ground-water sites.

Water Resources Data for Oregon, Water Year 2003

USGS Publications Warehouse

Herrett, T.A.; Hess, G.W.; House, J.G.; Ruppert, G.P.; Courts, M.L.

2004-01-01

The annual Oregon hydrologic data report is one of a series of annual reports that document hydrologic data gathered from the U.S. Geological Survey's surface- and ground-water data-collection networks in each State, Puerto Rico, and the Trust Territories. These records of streamflow, ground-water levels, and quality of water provide the hydrologic information needed by State, local and Federal agencies, and the private sector for developing and managing our Nation's land and water resources. This report includes records on both surface and ground water in Oregon and contains discharge records for 199 stream-gaging stations, 25 partial-record or miscellaneous streamflow stations, and 8 crest-stage partial-record streamflow stations; stage-only records for 6 gaging stations; stage and content records for 26 lakes and reservoirs; and water-quality records collected at 127 streamflow-gaging stations, 2 atmospheric deposition stations, and 11 ground-water sites.

Applying A Multi-Objective Based Procedure to SWAT Modelling in Alpine Catchments

NASA Astrophysics Data System (ADS)

Tuo, Y.; Disse, M.; Chiogna, G.

2017-12-01

In alpine catchments, water management practices can lead to conflicts between upstream and downstream stakeholders, like in the Adige river basin (Italy). A correct prediction of available water resources plays an important part, for example, in defining how much water can be stored for hydropower production in upstream reservoirs without affecting agricultural activities downstream. Snow is a crucial hydrological component that highly affects seasonal behavior of streamflow. Therefore, a realistic representation of snow dynamics is fundamental for water management operations in alpine catchments. The Soil and Water Assessment Tool (SWAT) model has been applied in alpine catchments worldwide. However, during model calibration of catchment scale applications, snow parameters were generally estimated based on streamflow records rather than on snow measurements. This may lead to streamflow predictions with wrong snow melt contribution. This work highlights the importance of considering snow measurements in the calibration of the SWAT model for alpine hydrology and compares various calibration methodologies. In addition to discharge records, snow water equivalent time series of both subbasin scale and monitoring station were also utilized to evaluate the model performance by comparing with the SWAT subbasin and elevation band snow outputs. Comparing model results obtained calibrating the model using discharge data only and discharge data along with snow water equivalent data, we show that the latter approach allows us to improve the reliability of snow simulations while maintaining good estimations of streamflow. With a more reliable representation of snow dynamics, the hydrological model can provide more accurate references for proposing adequate water management solutions. This study offers to the wide SWAT user community an effective approach to improve streamflow predictions in alpine catchments and hence support decision makers in water allocation.

Evaluation of a new satellite-based precipitation dataset for climate studies in the Xiang River basin, Southern China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Hsu, K. L.

2017-12-01

A new satellite-based precipitation dataset, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with long-term time series dating back to 1983 can be one valuable dataset for climate studies. This study investigates the feasibility of using PERSIANN-CDR as a reference dataset for climate studies. Sixteen CMIP5 models are evaluated over the Xiang River basin, southern China, by comparing their performance on precipitation projection and streamflow simulation, particularly on extreme precipitation and streamflow events. The results show PERSIANN-CDR is a valuable dataset for climate studies, even on extreme precipitation events. The precipitation estimates and their extreme events from CMIP5 models are improved significantly compared with rain gauge observations after bias-correction by the PERSIANN-CDR precipitation estimates. Given streamflows simulated with raw and bias-corrected precipitation estimates from 16 CMIP5 models, 10 out of 16 are improved after bias-correction. The impact of bias-correction on extreme events for streamflow simulations are unstable, with eight out of 16 models can be clearly claimed they are improved after the bias-correction. Concerning the performance of raw CMIP5 models on precipitation, IPSL-CM5A-MR excels the other CMIP5 models, while MRI-CGCM3 outperforms on extreme events with its better performance on six extreme precipitation metrics. Case studies also show that raw CCSM4, CESM1-CAM5, and MRI-CGCM3 outperform other models on streamflow simulation, while MIROC5-ESM-CHEM, MIROC5-ESM and IPSL-CM5A-MR behaves better than the other models after bias-correction.

Hydrologic controls on basin-scale distribution of benthic macroinvertebrates

NASA Astrophysics Data System (ADS)

Bertuzzo, E.; Ceola, S.; Singer, G. A.; Battin, T. J.; Montanari, A.; Rinaldo, A.

2013-12-01

The presentation deals with the role of streamflow variability on basin-scale distributions of benthic macroinvertebrates. Specifically, we present a probabilistic analysis of the impacts of the variability along the river network of relevant hydraulic variables on the density of benthic macroinvertebrate species. The relevance of this work is based on the implications of the predictability of macroinvertebrate patterns within a catchment on fluvial ecosystem health, being macroinvertebrates commonly used as sensitive indicators, and on the effects of anthropogenic activity. The analytical tools presented here outline a novel procedure of general nature aiming at a spatially-explicit quantitative assessment of how near-bed flow variability affects benthic macroinvertebrate abundance. Moving from the analytical characterization of the at-a-site probability distribution functions (pdfs) of streamflow and bottom shear stress, a spatial extension to a whole river network is performed aiming at the definition of spatial maps of streamflow and bottom shear stress. Then, bottom shear stress pdf, coupled with habitat suitability curves (e.g., empirical relations between species density and bottom shear stress) derived from field studies are used to produce maps of macroinvertebrate suitability to shear stress conditions. Thus, moving from measured hydrologic conditions, possible effects of river streamflow alterations on macroinvertebrate densities may be fairly assessed. We apply this framework to an Austrian river network, used as benchmark for the analysis, for which rainfall and streamflow time-series and river network hydraulic properties and macroinvertebrate density data are available. A comparison between observed vs "modeled" species' density in three locations along the examined river network is also presented. Although the proposed approach focuses on a single controlling factor, it shows important implications with water resources management and fluvial ecosystem protection.

Evaluating Snow Data Assimilation Framework for Streamflow Forecasting Applications Using Hindcast Verification

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2012-12-01

Snow water equivalent (SWE) estimation is a key factor in producing reliable streamflow simulations and forecasts in snow dominated areas. However, measuring or predicting SWE has significant uncertainty. Sequential data assimilation, which updates states using both observed and modeled data based on error estimation, has been shown to reduce streamflow simulation errors but has had limited testing for forecasting applications. In the current study, a snow data assimilation framework integrated with the National Weather System River Forecasting System (NWSRFS) is evaluated for use in ensemble streamflow prediction (ESP). Seasonal water supply ESP hindcasts are generated for the North Fork of the American River Basin (NFARB) in northern California. Parameter sets from the California Nevada River Forecast Center (CNRFC), the Differential Evolution Adaptive Metropolis (DREAM) algorithm and the Multistep Automated Calibration Scheme (MACS) are tested both with and without sequential data assimilation. The traditional ESP method considers uncertainty in future climate conditions using historical temperature and precipitation time series to generate future streamflow scenarios conditioned on the current basin state. We include data uncertainty analysis in the forecasting framework through the DREAM-based parameter set which is part of a recently developed Integrated Uncertainty and Ensemble-based data Assimilation framework (ICEA). Extensive verification of all tested approaches is undertaken using traditional forecast verification measures, including root mean square error (RMSE), Nash-Sutcliffe efficiency coefficient (NSE), volumetric bias, joint distribution, rank probability score (RPS), and discrimination and reliability plots. In comparison to the RFC parameters, the DREAM and MACS sets show significant improvement in volumetric bias in flow. Use of assimilation improves hindcasts of higher flows but does not significantly improve performance in the mid flow and low flow categories.

Translating Climate Projections for Bridge Engineering

NASA Astrophysics Data System (ADS)

Anderson, C.; Takle, E. S.; Krajewski, W.; Mantilla, R.; Quintero, F.

2015-12-01

A bridge vulnerability pilot study was conducted by Iowa Department of Transportation (IADOT) as one of nineteen pilots supported by the Federal Highway Administration Climate Change Resilience Pilots. Our pilot study team consisted of the IADOT senior bridge engineer who is the preliminary design section leader as well as climate and hydrological scientists. The pilot project culminated in a visual graphic designed by the bridge engineer (Figure 1), and an evaluation framework for bridge engineering design. The framework has four stages. The first two stages evaluate the spatial and temporal resolution needed in climate projection data in order to be suitable for input to a hydrology model. The framework separates streamflow simulation error into errors from the streamflow model and from the coarseness of input weather data series. In the final two stages, the framework evaluates credibility of climate projection streamflow simulations. Using an empirically downscaled data set, projection streamflow is generated. Error is computed in two time frames: the training period of the empirical downscaling methodology, and an out-of-sample period. If large errors in projection streamflow were observed during the training period, it would indicate low accuracy and, therefore, low credibility. If large errors in streamflow were observed during the out-of-sample period, it would mean the approach may not include some causes of change and, therefore, the climate projections would have limited credibility for setting expectations for changes. We address uncertainty with confidence intervals on quantiles of streamflow discharge. The results show the 95% confidence intervals have significant overlap. Nevertheless, the use of confidence intervals enabled engineering judgement. In our discussions, we noted the consistency in direction of change across basins, though the flood mechanism was different across basins, and the high bound of bridge lifetime period quantiles exceeded that of the historical period. This suggested the change was not isolated, and it systemically altered the risk profile. One suggestion to incorporate engineering judgement was to consider degrees of vulnerability using the median discharge of the historical period and the upper bound discharge for the bridge lifetime period.

A method for estimating peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area

USGS Publications Warehouse

Asquith, William H.; Cleveland, Theodore G.; Roussel, Meghan C.

2011-01-01

Estimates of peak and time of peak streamflow for small watersheds (less than about 640 acres) in a suburban to urban, low-slope setting are needed for drainage design that is cost-effective and risk-mitigated. During 2007-10, the U.S. Geological Survey (USGS), in cooperation with the Harris County Flood Control District and the Texas Department of Transportation, developed a method to estimate peak and time of peak streamflow from excess rainfall for 10- to 640-acre watersheds in the Houston, Texas, metropolitan area. To develop the method, 24 watersheds in the study area with drainage areas less than about 3.5 square miles (2,240 acres) and with concomitant rainfall and runoff data were selected. The method is based on conjunctive analysis of rainfall and runoff data in the context of the unit hydrograph method and the rational method. For the unit hydrograph analysis, a gamma distribution model of unit hydrograph shape (a gamma unit hydrograph) was chosen and parameters estimated through matching of modeled peak and time of peak streamflow to observed values on a storm-by-storm basis. Watershed mean or watershed-specific values of peak and time to peak ("time to peak" is a parameter of the gamma unit hydrograph and is distinct from "time of peak") of the gamma unit hydrograph were computed. Two regression equations to estimate peak and time to peak of the gamma unit hydrograph that are based on watershed characteristics of drainage area and basin-development factor (BDF) were developed. For the rational method analysis, a lag time (time-R), volumetric runoff coefficient, and runoff coefficient were computed on a storm-by-storm basis. Watershed-specific values of these three metrics were computed. A regression equation to estimate time-R based on drainage area and BDF was developed. Overall arithmetic means of volumetric runoff coefficient (0.41 dimensionless) and runoff coefficient (0.25 dimensionless) for the 24 watersheds were used to express the rational method in terms of excess rainfall (the excess rational method). Both the unit hydrograph method and excess rational method are shown to provide similar estimates of peak and time of peak streamflow. The results from the two methods can be combined by using arithmetic means. A nomograph is provided that shows the respective relations between the arithmetic-mean peak and time of peak streamflow to drainage areas ranging from 10 to 640 acres. The nomograph also shows the respective relations for selected BDF ranging from undeveloped to fully developed conditions. The nomograph represents the peak streamflow for 1 inch of excess rainfall based on drainage area and BDF; the peak streamflow for design storms from the nomograph can be multiplied by the excess rainfall to estimate peak streamflow. Time of peak streamflow is readily obtained from the nomograph. Therefore, given excess rainfall values derived from watershed-loss models, which are beyond the scope of this report, the nomograph represents a method for estimating peak and time of peak streamflow for applicable watersheds in the Houston metropolitan area. Lastly, analysis of the relative influence of BDF on peak streamflow is provided, and the results indicate a 0:04log10 cubic feet per second change of peak streamflow per positive unit of change in BDF. This relative change can be used to adjust peak streamflow from the method or other hydrologic methods for a given BDF to other BDF values; example computations are provided.

Ethiopia's Grand Renaissance Dam: Implications for Downstream Riparian Countries

NASA Astrophysics Data System (ADS)

Zhang, Y.; Block, P. J.; Hammond, M.; King, A.

2013-12-01

Ethiopia has begun seriously developing their significant hydropower potential by launching construction of the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile River to facilitate local and regional growth. Although this has required substantial planning on Ethiopia's part, no policy dictating the reservoir filling rate strategy has been publicly issued. This filling stage will have clear implications on downstream flows in Sudan and Egypt, complicated by evaporative losses, climate variability, and climate change. In this study, various filling policies and future climate states are simultaneously explored to infer potential streamflow reductions at Lake Nasser, providing regional decision-makers with a set of plausible, justifiable, and comparable outcomes. Schematic of the model framework Box plots of 2017-2032 percent change in annual average streamflow at Lake Nasser for each filling policy constructed from the 100 time-series and weighted precipitation changes. All values are relative to the no dam policy and no changes to future precipitation.

Evidence from 12-year study links ecosystem changes in the Gulf of Maine with climate change

USGS Publications Warehouse

Aiken, George R.; Huntington, Thomas G.; Balch, William; Drapeau, David; Bowler, Bruce

2012-01-01

Investigators at the Bigelow Laboratory for Ocean Sciences (East Boothbay, Maine) and the U.S. Geological Survey collaborated to study ecosystem changes in the Gulf of Maine. As part of the Gulf of Maine North Atlantic Time Series (GNATS), a comprehensive long-term study of hydrographic, biological, optical and chemical properties, multiple cruises have been conducted each year since 2001 by using a portable laboratory aboard different vessels (figure 1) and occasionally a remotely controlled glider (figure 2). Data collected during these cruises, when analyzed within the context of a century of climatological and streamflow data, document changes in temperature, salinity, and coastal ocean productivity that appear to be related to recent increases in precipitation and streamflow. These results are evidence of a link between changing hydrologic conditions on land and changes in coastal ocean productivity.

Updated streamflow reconstructions for the Upper Colorado River Basin

USGS Publications Warehouse

Woodhouse, Connie A.; Gray, Stephen T.; Meko, David M.

2006-01-01

Updated proxy reconstructions of water year (October–September) streamflow for four key gauges in the Upper Colorado River Basin were generated using an expanded tree ring network and longer calibration records than in previous efforts. Reconstructed gauges include the Green River at Green River, Utah; Colorado near Cisco, Utah; San Juan near Bluff, Utah; and Colorado at Lees Ferry, Arizona. The reconstructions explain 72–81% of the variance in the gauge records, and results are robust across several reconstruction approaches. Time series plots as well as results of cross‐spectral analysis indicate strong spatial coherence in runoff variations across the subbasins. The Lees Ferry reconstruction suggests a higher long‐term mean than previous reconstructions but strongly supports earlier findings that Colorado River allocations were based on one of the wettest periods in the past 5 centuries and that droughts more severe than any 20th to 21st century event occurred in the past.

Updated streamflow reconstructions for the Upper Colorado River Basin

NASA Astrophysics Data System (ADS)

Woodhouse, Connie A.; Gray, Stephen T.; Meko, David M.

2006-05-01

Updated proxy reconstructions of water year (October-September) streamflow for four key gauges in the Upper Colorado River Basin were generated using an expanded tree ring network and longer calibration records than in previous efforts. Reconstructed gauges include the Green River at Green River, Utah; Colorado near Cisco, Utah; San Juan near Bluff, Utah; and Colorado at Lees Ferry, Arizona. The reconstructions explain 72-81% of the variance in the gauge records, and results are robust across several reconstruction approaches. Time series plots as well as results of cross-spectral analysis indicate strong spatial coherence in runoff variations across the subbasins. The Lees Ferry reconstruction suggests a higher long-term mean than previous reconstructions but strongly supports earlier findings that Colorado River allocations were based on one of the wettest periods in the past 5 centuries and that droughts more severe than any 20th to 21st century event occurred in the past.

Trends in precipitation and streamflow and changes in stream morphology in the Fountain Creek watershed, Colorado, 1939-99

USGS Publications Warehouse

Stogner, Sr., Robert W.

2000-01-01

The Fountain Creek watershed, located in and along the eastern slope of the Front Range section of the southern Rocky Mountains, drains approximately 930 square miles of parts of Teller, El Paso, and Pueblo Counties in eastern Colorado. Streamflow in the watershed is dominated by spring snowmelt runoff and storm runoff during the summer monsoon season. Flooding during the 1990?s has resulted in increased streambank erosion. Property loss and damage associated with flooding and bank erosion has cost area residents, businesses, utilities, municipalities, and State and Federal agencies millions of dollars. Precipitation (4 stations) and streamflow (6 stations) data, aerial photographs, and channel reconnaissance were used to evaluate trends in precipitation and streamflow and changes in channel morphology. Trends were evaluated for pre-1977, post-1976, and period-of-record time periods. Analysis revealed the lack of trend in total annual and seasonal precipitation during the pre-1977 time period. In general, the analysis also revealed the lack of trend in seasonal precipitation for all except the spring season during the post-1976 time period. Trend analysis revealed a significant upward trend in long-term (period of record) total annual and spring precipitation data, apparently due to a change in total annual precipitation throughout the Fountain Creek watershed. During the pre-1977 time period, precipitation was generally below average; during the post- 1976 time period, total annual precipitation was generally above average. During the post- 1976 time period, an upward trend in total annual and spring precipitation was indicated at two stations. Because two of four stations evaluated had upward trends for the post-1976 period and storms that produce the most precipitation are isolated convection storms, it is plausible that other parts of the watershed had upward precipitation trends that could affect trends in streamflow. Also, because of the isolated nature of convection storms that hit some areas of the watershed and not others, it is difficult to draw strong conclusions on relations between streamflow and precipitation. Trends in annual instantaneous peak streamflow, 70th percentile, 90th percentile, maximum daily-mean streamflow (100th percentile), 7-, 14-, and 30-day high daily-mean stream- flow duration, minimum daily-mean streamflow (0th percentile), 10th percentile, 30th percentile, and 7-, 14-, 30-day low daily-mean streamflow duration were evaluated. In general, instantaneous peak streamflow has not changed significantly at most of the stations evaluated. Trend analysis revealed the lack of a significant upward trend in streamflow at all stations for the pre-1977 time period. Trend tests indicated a significant upward trend in high and low daily-mean streamflow statistics for the post-1976 period. Upward trends in high daily-mean streamflow statistics may be an indication that changes in land use within the watershed have increased the rate and magnitude of runoff. Upward trends in low daily-mean 2 Trends in Precipitation and Streamflow and Changes in Stream Morphology in the Fountain Creek Watershed, Colorado, 1939-99 streamflow statistics may be related to changes in water use and management. An analysis of the relation between streamflow and precipitation indicated that changes in water management have had a marked effect on streamflow. Observable change in channel morphology and changes in distribution and density of vegetation varied with magnitude, duration, and frequency of large streamflow events, and increases in the magnitude and duration of low streamflows. Although more subtle, low stream- flows were an important component of day-to-day channel erosion. Substantial changes in channel morphology were most often associated with infrequent large or catastrophic streamflow events that erode streambed and banks, alter stream course, and deposit large amounts of sediment in the flood plain.

Changes in seasonality and timing of peak streamflow in snow and semi-arid climates of the north-central United States, 1910–2012

USGS Publications Warehouse

Ryberg, Karen R.; Akyüz, F. Adnan; Wiche, Gregg J.; Lin, Wei

2015-01-01

Changes in the seasonality and timing of annual peak streamflow in the north-central USA are likely because of changes in precipitation and temperature regimes. A source of long-term information about flood events across the study area is the U.S. Geological Survey peak streamflow database. However, one challenge of answering climate-related questions with this dataset is that even in snowmelt-dominated areas, it is a mixed population of snowmelt/spring rain generated peaks and summer/fall rain generated peaks. Therefore, a process was developed to divide the annual peaks into two populations, or seasons, snowmelt/spring, and summer/fall. The two series were then tested for the hypotheses that because of changes in precipitation regimes, the odds of summer/fall peaks have increased and, because of temperature changes, snowmelt/spring peaks happen earlier. Over climatologically and geographically similar regions in the north-central USA, logistic regression was used to model the odds of getting a summer/fall peak. When controlling for antecedent wet and dry conditions and geographical differences, the odds of summer/fall peaks occurring have increased across the study area. With respect to timing within the seasons, trend analysis showed that in northern portions of the study region, snowmelt/spring peaks are occurring earlier. The timing of snowmelt/spring peaks in three regions in the northern part of the study area is earlier by 8.7– 14.3 days. These changes have implications for water interests, such as potential changes in lead-time for flood forecasting or changes in the operation of flood-control dams.

A time-corrector device for adjusting streamflow records

Treesearch

Raymond W. Lavigne

1960-01-01

The first job in compiling streamflow data from streamflow charts is to mark storm rises and storm peaks, make corrections as necessary for time and stage height, and account for irregularities on the chart. Errors in the time scale can result from faulty clock operation, irregularities in chart take-up by the drum, or expansion of the paper. This note suggests a...

Understanding similarity of groundwater systems with empirical copulas

NASA Astrophysics Data System (ADS)

Haaf, Ezra; Kumar, Rohini; Samaniego, Luis; Barthel, Roland

2016-04-01

Within the classification framework for groundwater systems that aims for identifying similarity of hydrogeological systems and transferring information from a well-observed to an ungauged system (Haaf and Barthel, 2015; Haaf and Barthel, 2016), we propose a copula-based method for describing groundwater-systems similarity. Copulas are an emerging method in hydrological sciences that make it possible to model the dependence structure of two groundwater level time series, independently of the effects of their marginal distributions. This study is based on Samaniego et al. (2010), which described an approach calculating dissimilarity measures from bivariate empirical copula densities of streamflow time series. Subsequently, streamflow is predicted in ungauged basins by transferring properties from similar catchments. The proposed approach is innovative because copula-based similarity has not yet been applied to groundwater systems. Here we estimate the pairwise dependence structure of 600 wells in Southern Germany using 10 years of weekly groundwater level observations. Based on these empirical copulas, dissimilarity measures are estimated, such as the copula's lower- and upper corner cumulated probability, copula-based Spearman's rank correlation - as proposed by Samaniego et al. (2010). For the characterization of groundwater systems, copula-based metrics are compared with dissimilarities obtained from precipitation signals corresponding to the presumed area of influence of each groundwater well. This promising approach provides a new tool for advancing similarity-based classification of groundwater system dynamics. Haaf, E., Barthel, R., 2015. Methods for assessing hydrogeological similarity and for classification of groundwater systems on the regional scale, EGU General Assembly 2015, Vienna, Austria. Haaf, E., Barthel, R., 2016. An approach for classification of hydrogeological systems at the regional scale based on groundwater hydrographs EGU General Assembly 2016, Vienna, Austria. Samaniego, L., Bardossy, A., Kumar, R., 2010. Streamflow prediction in ungauged catchments using copula-based dissimilarity measures. Water Resources Research, 46. DOI:10.1029/2008wr007695

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.

2012-01-01

The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft3/s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft3/s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft3/s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft3/s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.

A hydrogeologic framework for characterizing summer streamflow sensitivity to climate warming in the Pacific Northwest, USA

NASA Astrophysics Data System (ADS)

Safeeq, M.; Grant, G. E.; Lewis, S. L.; Kramer, M. G.; Staab, B.

2014-09-01

Summer streamflows in the Pacific Northwest are largely derived from melting snow and groundwater discharge. As the climate warms, diminishing snowpack and earlier snowmelt will cause reductions in summer streamflow. Most regional-scale assessments of climate change impacts on streamflow use downscaled temperature and precipitation projections from general circulation models (GCMs) coupled with large-scale hydrologic models. Here we develop and apply an analytical hydrogeologic framework for characterizing summer streamflow sensitivity to a change in the timing and magnitude of recharge in a spatially explicit fashion. In particular, we incorporate the role of deep groundwater, which large-scale hydrologic models generally fail to capture, into streamflow sensitivity assessments. We validate our analytical streamflow sensitivities against two empirical measures of sensitivity derived using historical observations of temperature, precipitation, and streamflow from 217 watersheds. In general, empirically and analytically derived streamflow sensitivity values correspond. Although the selected watersheds cover a range of hydrologic regimes (e.g., rain-dominated, mixture of rain and snow, and snow-dominated), sensitivity validation was primarily driven by the snow-dominated watersheds, which are subjected to a wider range of change in recharge timing and magnitude as a result of increased temperature. Overall, two patterns emerge from this analysis: first, areas with high streamflow sensitivity also have higher summer streamflows as compared to low-sensitivity areas. Second, the level of sensitivity and spatial extent of highly sensitive areas diminishes over time as the summer progresses. Results of this analysis point to a robust, practical, and scalable approach that can help assess risk at the landscape scale, complement the downscaling approach, be applied to any climate scenario of interest, and provide a framework to assist land and water managers in adapting to an uncertain and potentially challenging future.

Trends in snowmelt-related streamflow timing in the conterminous United States

NASA Astrophysics Data System (ADS)

Dudley, R. W.; Hodgkins, G. A.; McHale, M. R.; Kolian, M. J.; Renard, B.

2017-04-01

Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940-2014 and 1960-2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (<1600 m) basins in the West, predominantly located in the Northwest, had median earlier WSCVD by 6.8 days (1940-2014, 0.9 days/decade) and 3.4 days (1960-2014, 0.6 days/decade). Streamflow timing at high-elevation (⩾1600 m) basins in the West had median earlier WSCVD by 4.0 days (1940-2014, 0.5 days/decade) and 5.2 days (1960-2014, 0.9 days/decade). Trends toward earlier WSCVD in the Northwest were not statistically significant, differing from previous studies that observed many large and (or) significant trends in this region. Much of this difference is likely due to the sensitivity of trend tests to the time period being tested, as well as differences in the streamflow timing metrics used among the studies. Mean February-May air temperature was significantly correlated with WSCVD at 100 percent of the study gages (field significant, p < 0.0001), demonstrating the sensitivity of WSCVD to air temperature across snowmelt dominated basins in the U.S. WSCVD in high elevation basins in the West, however, was related to both air temperature and precipitation yielding earlier snowmelt-related streamflow timing under warmer and drier conditions.

Hydrologic data for water years 1933-97 used in the River and Reservoir Operations Model, Truckee River basin, California and Nevada

USGS Publications Warehouse

Berris, Steven N.; Hess, Glen W.; Bohman, Larry R.

2000-01-01

Title II of Public Law 101-618, the Truckee?Carson?Pyramid Lake Water Rights Settlement Act of 1990, provides direction, authority, and a mechanism for resolving conflicts over water rights in the Truckee and Carson River Basins. The Truckee Carson Program of the U.S. Geological Survey, to support implementation of Public Law 101-618, has developed an operations model to simulate lake/reservoir and river operations for the Truckee River Basin including diversion of Truckee River water to the Truckee Canal for transport to the Carson River Basin. Several types of hydrologic data, formatted in a chronological order with a daily time interval called 'time series,' are described in this report. Time series from water years 1933 to 1997 can be used to run the operations model. Auxiliary hydrologic data not currently used by the model are also described. The time series of hydrologic data consist of flow, lake/reservoir elevation and storage, precipitation, evaporation, evapotranspiration, municipal and industrial (M&I) demand, and streamflow and lake/reservoir level forecast data.

Recent tree die-off has little effect on streamflow in contrast to expected increases from historical studies

NASA Astrophysics Data System (ADS)

Biederman, Joel A.; Somor, Andrew J.; Harpold, Adrian A.; Gutmann, Ethan D.; Breshears, David D.; Troch, Peter A.; Gochis, David J.; Scott, Russell L.; Meddens, Arjan J. H.; Brooks, Paul D.

2015-12-01

Recent bark beetle epidemics have caused regional-scale tree mortality in many snowmelt-dominated headwater catchments of western North America. Initial expectations of increased streamflow have not been supported by observations, and the basin-scale response of annual streamflow is largely unknown. Here we quantified annual streamflow responses during the decade following tree die-off in eight infested catchments in the Colorado River headwaters and one nearby control catchment. We employed three alternative empirical methods: (i) double-mass comparison between impacted and control catchments, (ii) runoff ratio comparison before and after die-off, and (iii) time-trend analysis using climate-driven linear models. In contrast to streamflow increases predicted by historical paired catchment studies and recent modeling, we did not detect streamflow changes in most basins following die-off, while one basin consistently showed decreased streamflow. The three analysis methods produced generally consistent results, with time-trend analysis showing precipitation was the strongest predictor of streamflow variability (R2 = 74-96%). Time-trend analysis revealed post-die-off streamflow decreased in three catchments by 11-29%, with no change in the other five catchments. Although counter to initial expectations, these results are consistent with increased transpiration by surviving vegetation and the growing body of literature documenting increased snow sublimation and evaporation from the subcanopy following die-off in water-limited, snow-dominated forests. The observations presented here challenge the widespread expectation that streamflow will increase following beetle-induced forest die-off and highlight the need to better understand the processes driving hydrologic response to forest disturbance.

Timing and Duration of Flow in Ephemeral Streams of the Sierra Vista Subwatershed of the Upper San Pedro Basin, Cochise County, Southeastern Arizona

USGS Publications Warehouse

Gungle, Bruce

2006-01-01

Frequency, timing, and duration of streamflow were monitored in 20 ephemeral-stream channels across the Sierra Vista Subwatershed of the Upper San Pedro Basin, southeastern Arizona, during an 18-month period. One channel (Walnut Gulch) had Agricultural Research Service streamflow-gaging stations in place. The sediments of the remaining 19 ephemeral-stream channels were instrumented with multiple temperature loggers along the channel lengths. A thermograph-interpretation technique was developed in order to determine frequency, timing, and duration of streamflow in these channels. Streamflow onset was characterized by exceedance of a critical minimum drop in temperature within the channel sediments during any 15-minute interval, whereas streamflow cessation was identified by the local temperature minimum that immediately followed the critical temperature drop. All data for the 18-month period from December 1, 2000, to May 31, 2002, were analyzed in terms of monsoon (June 1 to September 19) and nonmonsoon (September 20 to May 31) periods. Nonmonsoon precipitation during the 2000-2002 study period (excludes October and November 2000) was 82 percent and 39 percent of the 30-year average, respectively, whereas monsoon precipitation during 2001 was 99 percent of the 30-year average. Ephemeral streamflow was detected at least once during the monitoring period at 87 percent of the monitoring sites (45 of the 52 sites that returned useful data; includes 4 streamflow-gaging stations). The summer monsoon period accounted for 82 percent of all streamflow events by number and 71 percent of all events by total streamflow duration. Nonmonsoon streamflow events peaked in number, total streamflow duration, and mean streamflow duration midway between the Huachuca Mountains and the San Pedro River on the west side of the subwatershed. These three streamflow parameters dropped off sharply about 10 kilometers from the mountain front. The number and total duration of nonmonsoon streamflows on the east side of the subwatershed trended downward with increased distance from the mountain fronts. Monsoon streamflow events were more evenly distributed across the subwatershed than nonmonsoon events, and the number and duration of streamflows generally trended upward with distance from the mountain fronts. Additional years of data are needed to determine whether these patterns are consistent year to year, or were due to randomness in the spatial distribution of precipitation. Streamflows in three ephemeral-stream channels were analyzed in detail. More than two-thirds of the streamflow events detected in each of these channels occurred at no more than one monitoring site along the channel length. In only one of the three channels-Garden Canyon-was a streamflow event detected at all logger sites along its length. Five temperature loggers provided data from urbanized areas, and these loggers detected streamflow more than 50 percent more often and of a duration nearly three times greater than did temperature loggers across the rural parts of the subwatershed. Because historical records do not indicate that more precipitation occurs in the urbanized area than in the rural areas, the increased frequency of flow detection in the urban area is attributed to an increase in runoff from the impervious surfaces throughout the urbanized area.

The CAMELS data set: catchment attributes and meteorology for large-sample studies

NASA Astrophysics Data System (ADS)

Addor, Nans; Newman, Andrew J.; Mizukami, Naoki; Clark, Martyn P.

2017-10-01

We present a new data set of attributes for 671 catchments in the contiguous United States (CONUS) minimally impacted by human activities. This complements the daily time series of meteorological forcing and streamflow provided by Newman et al. (2015b). To produce this extension, we synthesized diverse and complementary data sets to describe six main classes of attributes at the catchment scale: topography, climate, streamflow, land cover, soil, and geology. The spatial variations among basins over the CONUS are discussed and compared using a series of maps. The large number of catchments, combined with the diversity of the attributes we extracted, makes this new data set well suited for large-sample studies and comparative hydrology. In comparison to the similar Model Parameter Estimation Experiment (MOPEX) data set, this data set relies on more recent data, it covers a wider range of attributes, and its catchments are more evenly distributed across the CONUS. This study also involves assessments of the limitations of the source data sets used to compute catchment attributes, as well as detailed descriptions of how the attributes were computed. The hydrometeorological time series provided by Newman et al. (2015b, https://doi.org/10.5065/D6MW2F4D) together with the catchment attributes introduced in this paper (https://doi.org/10.5065/D6G73C3Q) constitute the freely available CAMELS data set, which stands for Catchment Attributes and MEteorology for Large-sample Studies.

Streamflow changes in the Sierra Nevada, California, simulated using a statistically downscaled general circulation model scenario of climate change

USGS Publications Warehouse

Wilby, Robert L.; Dettinger, Michael D.

2000-01-01

Simulations of future climate using general circulation models (GCMs) suggest that rising concentrations of greenhouse gases may have significant consequences for the global climate. Of less certainty is the extent to which regional scale (i.e., sub-GCM grid) environmental processes will be affected. In this chapter, a range of downscaling techniques are critiqued. Then a relatively simple (yet robust) statistical downscaling technique and its use in the modelling of future runoff scenarios for three river basins in the Sierra Nevada, California, is described. This region was selected because GCM experiments driven by combined greenhouse-gas and sulphate-aerosol forcings consistently show major changes in the hydro-climate of the southwest United States by the end of the 21st century. The regression-based downscaling method was used to simulate daily rainfall and temperature series for streamflow modelling in three Californian river basins under current-and future-climate conditions. The downscaling involved just three predictor variables (specific humidity, zonal velocity component of airflow, and 500 hPa geopotential heights) supplied by the U.K. Meteorological Office couple ocean-atmosphere model (HadCM2) for the grid point nearest the target basins. When evaluated using independent data, the model showed reasonable skill at reproducing observed area-average precipitation, temperature, and concomitant streamflow variations. Overall, the downscaled data resulted in slight underestimates of mean annual streamflow due to underestimates of precipitation in spring and positive temperature biases in winter. Differences in the skill of simulated streamflows amongst the three basins were attributed to the smoothing effects of snowpack on streamflow responses to climate forcing. The Merced and American River basins drain the western, windward slope of the Sierra Nevada and are snowmelt dominated, whereas the Carson River drains the eastern, leeward slope and is a mix of rainfall runoff and snowmelt runoff. Simulated streamflow in the American River responds rapidly and sensitively to daily-scale temperature and precipitation fluctuations and errors; in the Merced and Carson Rivers, the response to the same short-term influences is much less. Consequently, the skill of simulated flows was significantly lower in the American River model than in the Carson and Merced. The physiography of the three basins also accounts for differences in their sensitivities to future climate change. Increases in winter precipitation exceeding +100% coupled with mean temperature rises greater than +2°C result in increased winter streamflows in all three basins. In the Merced and Carson basins, these streamflow increases reflect large changes in winter snowpack, whereas the streamflow changes in the lower elevation American basin are driven primarily by rainfall runoff. Furthermore, reductions in winter snowpack in the American River basin, owing to less precipitation falling as snow and earlier melting of snow at middle elevations, lead to less spring and summer streamflow. Taken collectively, the downscaling results suggest significant changes to both the timing and magnitude of streamflows in the Sierra Nevada by the end of the 21st Century. In the higher elevation basins, the HadCM2 scenario implies more annual streamflow and more streamflow during the spring and summer months that are critical for water-resources management in California. Depending on the relative significance of rainfall runoff and snowmelt, each basin responds in its own way to regional climate forcing. Generally, then, climate scenarios need to be specified — by whatever means — with sufficient temporal and spatial resolution to capture subtle orographic influences if projections of climate-change responses are to be useful and reproducible.

A novel framework to simulating non-stationary, non-linear, non-Normal hydrological time series using Markov Switching Autoregressive Models

NASA Astrophysics Data System (ADS)

Birkel, C.; Paroli, R.; Spezia, L.; Tetzlaff, D.; Soulsby, C.

2012-12-01

In this paper we present a novel model framework using the class of Markov Switching Autoregressive Models (MSARMs) to examine catchments as complex stochastic systems that exhibit non-stationary, non-linear and non-Normal rainfall-runoff and solute dynamics. Hereby, MSARMs are pairs of stochastic processes, one observed and one unobserved, or hidden. We model the unobserved process as a finite state Markov chain and assume that the observed process, given the hidden Markov chain, is conditionally autoregressive, which means that the current observation depends on its recent past (system memory). The model is fully embedded in a Bayesian analysis based on Markov Chain Monte Carlo (MCMC) algorithms for model selection and uncertainty assessment. Hereby, the autoregressive order and the dimension of the hidden Markov chain state-space are essentially self-selected. The hidden states of the Markov chain represent unobserved levels of variability in the observed process that may result from complex interactions of hydroclimatic variability on the one hand and catchment characteristics affecting water and solute storage on the other. To deal with non-stationarity, additional meteorological and hydrological time series along with a periodic component can be included in the MSARMs as covariates. This extension allows identification of potential underlying drivers of temporal rainfall-runoff and solute dynamics. We applied the MSAR model framework to streamflow and conservative tracer (deuterium and oxygen-18) time series from an intensively monitored 2.3 km2 experimental catchment in eastern Scotland. Statistical time series analysis, in the form of MSARMs, suggested that the streamflow and isotope tracer time series are not controlled by simple linear rules. MSARMs showed that the dependence of current observations on past inputs observed by transport models often in form of the long-tailing of travel time and residence time distributions can be efficiently explained by non-stationarity either of the system input (climatic variability) and/or the complexity of catchment storage characteristics. The statistical model is also capable of reproducing short (event) and longer-term (inter-event) and wet and dry dynamical "hydrological states". These reflect the non-linear transport mechanisms of flow pathways induced by transient climatic and hydrological variables and modified by catchment characteristics. We conclude that MSARMs are a powerful tool to analyze the temporal dynamics of hydrological data, allowing for explicit integration of non-stationary, non-linear and non-Normal characteristics.

Integrating remotely sensed surface water extent into continental scale hydrology.

PubMed

Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad

2016-12-01

In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R 2 , RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that remotely sensed surface water extent holds potential for improving rainfall-runoff streamflow simulations, potentially leading to a better forecast of the peak flow.

33 CFR 236.4 - Background.

Code of Federal Regulations, 2010 CFR

2010-07-01

... streamflow; preservation and restoration of certain cultural resources, and the preservation or creation of wetlands. (c) The 1105-2-200 series of Engineer Regulations describe the procedures to be followed in...

33 CFR 236.4 - Background.

Code of Federal Regulations, 2011 CFR

2011-07-01

... streamflow; preservation and restoration of certain cultural resources, and the preservation or creation of wetlands. (c) The 1105-2-200 series of Engineer Regulations describe the procedures to be followed in...

Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

NASA Astrophysics Data System (ADS)

Zhao, T.; Cai, X.; Yang, D.

2010-12-01

Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover, streamflow variability and reservoir capacity can change the magnitude of the effects of forecast uncertainty, but not the relative merit of DSF, DPSF, and ESF. Schematic diagram of the increase in forecast uncertainty with forecast lead-time and the dynamic updating property of real-time streamflow forecast

Jordan recurrent neural network versus IHACRES in modelling daily streamflows

NASA Astrophysics Data System (ADS)

Carcano, Elena Carla; Bartolini, Paolo; Muselli, Marco; Piroddi, Luigi

2008-12-01

SummaryA study of possible scenarios for modelling streamflow data from daily time series, using artificial neural networks (ANNs), is presented. Particular emphasis is devoted to the reconstruction of drought periods where water resource management and control are most critical. This paper considers two connectionist models: a feedforward multilayer perceptron (MLP) and a Jordan recurrent neural network (JNN), comparing network performance on real world data from two small catchments (192 and 69 km 2 in size) with irregular and torrential regimes. Several network configurations are tested to ensure a good combination of input features (rainfall and previous streamflow data) that capture the variability of the physical processes at work. Tapped delayed line (TDL) and memory effect techniques are introduced to recognize and reproduce temporal dependence. Results show a poor agreement when using TDL only, but a remarkable improvement can be obtained with JNN and its memory effect procedures, which are able to reproduce the system memory over a catchment in a more effective way. Furthermore, the IHACRES conceptual model, which relies on both rainfall and temperature input data, is introduced for comparative study. The results suggest that when good input data is unavailable, metric models perform better than conceptual ones and, in general, it is difficult to justify substantial conceptualization of complex processes.

Predicting Geomorphic and Hydrologic Risks after Wildfire Using Harmonic and Stochastic Analyses

NASA Astrophysics Data System (ADS)

Mikesell, J.; Kinoshita, A. M.; Florsheim, J. L.; Chin, A.; Nourbakhshbeidokhti, S.

2017-12-01

Wildfire is a landscape-scale disturbance that often alters hydrological processes and sediment flux during subsequent storms. Vegetation loss from wildfires induce changes to sediment supply such as channel erosion and sedimentation and streamflow magnitude or flooding. These changes enhance downstream hazards, threatening human populations and physical aquatic habitat over various time scales. Using Williams Canyon, a basin burned by the Waldo Canyon Fire (2012) as a case study, we utilize deterministic and statistical modeling methods (Fourier series and first order Markov chain) to assess pre- and post-fire geomorphic and hydrologic characteristics, including of precipitation, enhanced vegetation index (EVI, a satellite-based proxy of vegetation biomass), streamflow, and sediment flux. Local precipitation, terrestrial Light Detection and Ranging (LiDAR) scanning, and satellite-based products are used for these time series analyses. We present a framework to assess variability of periodic and nonperiodic climatic and multivariate trends to inform development of a post-wildfire risk assessment methodology. To establish the extent to which a wildfire affects hydrologic and geomorphic patterns, a Fourier series was used to fit pre- and post-fire geomorphic and hydrologic characteristics to yearly temporal cycles and subcycles of 6, 4, 3, and 2.4 months. These cycles were analyzed using least-squares estimates of the harmonic coefficients or amplitudes of each sub-cycle's contribution to fit the overall behavior of a Fourier series. The stochastic variances of these characteristics were analyzed by composing first-order Markov models and probabilistic analysis through direct likelihood estimates. Preliminary results highlight an increased dependence of monthly post-fire hydrologic characteristics on 12 and 6-month temporal cycles. This statistical and probabilistic analysis provides a basis to determine the impact of wildfires on the temporal dependence of geomorphic and hydrologic characteristics, which can be incorporated into post-fire mitigation, management, and recovery-based measures to protect and rehabilitate areas subject to influence from wildfires.

Exploring changes in the spatial distribution of stream baseflow generation during a seasonal recession

USGS Publications Warehouse

Payn, R.A.; Gooseff, M.N.; McGlynn, B.L.; Bencala, K.E.; Wondzell, S.M.

2012-01-01

Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores detailed surveys of stream base flow across a gauged, 23 km2 mountain watershed. Research objectives were (1) to relate spatial variability in base flow to fundamental elements of watershed structure, primarily topographic contributing area, and (2) to assess temporal changes in the spatial patterns of those relationships during a seasonal base flow recession. We analyzed spatiotemporal variability in base flow using (1) summer hydrographs at the study watershed outlet and 5 subwatershed outlets and (2) longitudinal series of discharge measurements every ~100 m along the streams of the 3 largest subwatersheds (1200 to 2600 m in valley length), repeated 2 to 3 times during base flow recession. Reaches within valley segments of 300 to 1200 m in length tended to demonstrate similar streamflow generation characteristics. Locations of transitions between these segments were consistent throughout the recession, and tended to be collocated with abrupt longitudinal transitions in valley slope or hillslope-riparian characteristics. Both within and among subwatersheds, correlation between the spatial distributions of streamflow and topographic contributing area decreased during the recession, suggesting a general decrease in the influence of topography on stream base flow contributions. As topographic controls on base flow evidently decreased, multiple aspects of subsurface structure were likely to have gained influence.

Hazard function theory for nonstationary natural hazards

NASA Astrophysics Data System (ADS)

Read, L.; Vogel, R. M.

2015-12-01

Studies from the natural hazards literature indicate that many natural processes, including wind speeds, landslides, wildfires, precipitation, streamflow and earthquakes, show evidence of nonstationary behavior such as trends in magnitudes through time. Traditional probabilistic analysis of natural hazards based on partial duration series (PDS) generally assumes stationarity in the magnitudes and arrivals of events, i.e. that the probability of exceedance is constant through time. Given evidence of trends and the consequent expected growth in devastating impacts from natural hazards across the world, new methods are needed to characterize their probabilistic behavior. The field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (x) with its failure time series (t), enabling computation of corresponding average return periods and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose PDS magnitudes are assumed to follow the widely applied Poisson-GP model. We derive a 2-parameter Generalized Pareto hazard model and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard event series x, with corresponding failure time series t, should have application to a wide class of natural hazards.

Onset of snowmelt and streamflow in 2004 in the Western Unites States: How shading may affect spring streamflow timing in a warmer world

USGS Publications Warehouse

Lundquist, J.D.; Flint, A.L.

2006-01-01

Historic streamflow records show that the onset of snowfed streamflow in the western United States has shifted earlier over the past 50 yr, and March 2004 was one of the earliest onsets on record. Record high temperatures occurred throughout the western United States during the second week of March, and U.S. Geological Survey (USGS) stream gauges throughout the area recorded early onsets of streamflow at this time. However, a set of nested subbasins in Yosemite National Park, California, told a more complicated story. In spite of high air temperatures, many streams draining high-elevation basins did not start flowing until later in the spring. Temperatures during early March 2004 were as high as temperatures in late March 2002, when streams at all of the monitored Yosemite basins began flowing at the same time. However, the March 2004 onset occurred before the spring equinox, when the sun was lower in the sky. Thus, shading and solar radiation differences played a much more important role in 2004, leading to differences in streamflow timing. These results suggest that as temperatures warm and spring melt shifts earlier in the season, topographic effects will play an even more important role than at present in determining snowmelt timing. ?? 2006 American Meteorological Society.

Georgia's Surface-Water Resources and Streamflow Monitoring Network, 2006

USGS Publications Warehouse

Nobles, Patricia L.; ,

2006-01-01

The U.S. Geological Survey (USGS) network of 223 real-time monitoring stations, the 'Georgia HydroWatch,' provides real-time water-stage data, with streamflow computed at 198 locations, and rainfall recorded at 187 stations. These sites continuously record data on 15-minute intervals and transmit the data via satellite to be incorporated into the USGS National Water Information System database. These data are automatically posted to the USGS Web site for public dissemination (http://waterdata.usgs.gov/ga/nwis/nwis). The real-time capability of this network provides information to help emergency-management officials protect human life and property during floods, and mitigate the effects of prolonged drought. The map at right shows the USGS streamflow monitoring network for Georgia and major watersheds. Streamflow is monitored at 198 sites statewide, more than 80 percent of which include precipitation gages. Various Federal, State, and local agencies fund these streamflow monitoring stations.

Changes toward earlier streamflow timing across western North America

USGS Publications Warehouse

Stewart, I.T.; Cayan, D.R.; Dettinger, M.D.

2005-01-01

The highly variable timing of streamflow in snowmelt-dominated basins across western North America is an important consequence, and indicator, of climate fluctuations. Changes in the timing of snowmelt-derived streamflow from 1948 to 2002 were investigated in a network of 302 western North America gauges by examining the center of mass for flow, spring pulse onset dates, and seasonal fractional flows through trend and principal component analyses. Statistical analysis of the streamflow timing measures with Pacific climate indicators identified local and key large-scale processes that govern the regionally coherent parts of the changes and their relative importance. Widespread and regionally coherent trends toward earlier onsets of springtime snowmelt and streamflow have taken place across most of western North America, affecting an area that is much larger than previously recognized. These timing changes have resulted in increasing fractions of annual flow occurring earlier in the water year by 1-4 weeks. The immediate (or proximal) forcings for the spatially coherent parts of the year-to-year fluctuations and longer-term trends of streamflow timing have been higher winter and spring temperatures. Although these temperature changes are partly controlled by the decadal-scale Pacific climate mode [Pacific decadal oscillation (PDO)], a separate and significant part of the variance is associated with a springtime warming trend that spans the PDO phases. ?? 2005 American Meteorological Society.

Testing hypotheses of velocity and celerity at the catchment scale using ensemble hydrograph separation

NASA Astrophysics Data System (ADS)

Kirchner, James

2017-04-01

Making hydrological models more realistic requires both better physical understanding of their underlying processes, and more rigorous tests of the hypotheses that they embody. In the current model-testing paradigm, multiple interdependent hypotheses are combined to generate model predictions, which are then compared with observational time series that reflect multiple interdependent forcings. This approach is problematic in several respects. If the modeled time series does not match the observations, which of the model's many embedded hypotheses is falsified? Conversely, even if the model matches the data, how many of its underlying hypotheses could still be wrong, perhaps in offsetting ways? The essence of the problem is that if model simulations depend on many interacting hypotheses, and if observational data reflect many different environmental forcings, then comparisons of simulations against data will rarely be diagnostic tests of specific hypotheses in the model. For this reason, I have long argued for a different approach to hypothesis testing, in which key signatures of behavior are extracted from both model and data before they are compared (Kirchner et al., 1996; Kirchner, 2006). This approach allows one to isolate the model/data comparison as much as possible from potentially confounding factors in both the model and the data. One key signature of catchment behavior, which has challenged many hydrologic models, is the contrast between the relatively short timescales of hydrologic response to precipitation events, reflecting the celerity of hydraulic potentials, and the much longer timescales of water transport through the landscape, reflecting the velocity of water movement as tracked by passive tracers (Kirchner, 2003). Here I show how both the velocity and celerity of transport at the catchment scale can be quantified from hydrologic and isotopic time series. The conventional formula used for hydrograph separation can be converted into an equivalent linear regression equation that quantifies the fraction of current rainfall in streamflow across ensembles of precipitation events. These ensembles can be selected to represent different discharge ranges, different precipitation intensities, or different levels of antecedent moisture, thus quantifying how the fraction of "new water" in streamflow varies with forcings such as these. This approach can be generalized to determine the contributions of precipitation inputs to streamflow across a range of time lags. In this way the short-term tail of the transit time distribution can be directly quantified for an ensemble of precipitation events, for direct comparison with the unit hydrograph, which quantifies the distribution of hydraulic celerities. High-frequency tracer time series from several experimental catchments will be used to demonstrate how this approach can be used to generate distinctive signatures of catchment behavior for testing model hypotheses. Kirchner, J.W., R.P. Hooper, C. Kendall, C. Neal, and G. Leavesley, Testing and validating environmental models, Science of the Total Environment, 183, 33-47, 1996. Kirchner, J.W., A double paradox in catchment hydrology and geochemistry, Hydrological Processes, 17, 871-874, 2003. Kirchner, J.W., Getting the right answers for the right reasons: linking measurements, analyses, and models to advance the science of hydrology, Water Resources Research, 42, Art. No. WR004362, 2006.

Coupling study of the Variable Infiltration Capacity (VIC) model with WRF model to simulate the streamflow in the Guadalquivir Basin

NASA Astrophysics Data System (ADS)

García-Valdecasas Ojeda, Matilde; De Franciscis, Sebastiano; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Esteban-Parra, María Jesus

2016-04-01

Variable Infiltration Capacity (VIC) model is a large-scale, semi-distributed hydrologic model [1]. Its most important properties are related to the land surface, modeled as a grid of large and uniform cells with sub-grid heterogeneity (e.g. land cover), as well as to the local water influx (i.e. water can only enter a grid cell via the atmosphere and the channel flow between grid cells is ignored). The portions of surface and subsurface water runoff that reach the local channel network, are assumed to stay in the channel, and cannot flow back into the soil. In a second step, routing of streamflow is performed separately from the land surface simulation, using a separate model, the Routing Model, described in [2]. The final goal of our research consists into set an optimal hydrological and climate model to study the evolution of the streamflow of Guadalquivir Basin with different future land use, land cover and climate scenarios. In this work we study the coupling between VIC model, Routing model and Weather Research and Forecasting (WRF) model in order to perform the evolution of the streamflow for the Guadalquivir Basin (Spain). For this end, a calibration of the most relevant VIC model parameters using real streamflow daily time series, obtained from CEDEX (Centro de Estudios y Experimentación de Obras Públicas, Spain) database [3] was performed. In the time period under study, i.e. the decades 1988-1997 (calibration step) and 1998-2007 (verification step), the VIC model has been coupled with observational climate data, obtained from SPAIN02 database [4]. Additionally, we carried out a sensitivity analysis of WRF model to different parameterizations using different cumulus, microphysics and surface/planetary boundary layer schemes for the period 1995-1996. WRF runs were carried over a domain encompassing the Iberian Peninsula and nested in the coarser EURO-CORDEX domain [5]. The optimal parameters set resulting from such analysis have been used to obtain a high-resolution 35 yr period (1980-2014) dataset, driven by Interim ECMWF Re-Analysis (ERA-Interim) data [6]. Finally, the real streamflow daily time series were compared with the ones obtained by the previously calibrated VIC with SPAIN02 dataset and with WRF dataset, using different groups of meteorological variables. This last analysis allows us to check the robustness of VIC and WRF coupling, and to find the most relevant meteorological inputs for Guadalquivir streamflow system. Key words: Regional Climate Models, VIC, WRF, calibration, meteorological variables Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER). [1] http://vic.readthedocs.org/en/master/ [2] Lohmann D, Raschke E, Nijssen B, Lettenmaier D P, 1998: Regional scale hydrology: I. Formulation of the VIC-2L model coupled to a routing model, Hydrolog. Sci. J., 43(1), 131-141. [3] www.cedex.es [4] http://www.meteo.unican.es/en/datasets/spain02 [5] EUROCORDEX: http://www.euro-cordex.net/ [6] Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm E V, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally A P, Monge-Sanz B M, Morcrette J-J, Park B-K, Peubey C, de Rosnay P, Tavolato C, Thépaut J-N, Vitart F, 2011: The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. Roy. Meteor. Soc. 137:553-597.

Can we use Earth Observations to improve monthly water level forecasts?

NASA Astrophysics Data System (ADS)

Slater, L. J.; Villarini, G.

2017-12-01

Dynamical-statistical hydrologic forecasting approaches benefit from different strengths in comparison with traditional hydrologic forecasting systems: they are computationally efficient, can integrate and `learn' from a broad selection of input data (e.g., General Circulation Model (GCM) forecasts, Earth Observation time series, teleconnection patterns), and can take advantage of recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). Recent efforts to develop a dynamical-statistical ensemble approach for forecasting seasonal streamflow using both GCM forecasts and changing land cover have shown promising results over the U.S. Midwest. Here, we use climate forecasts from several GCMs of the North American Multi Model Ensemble (NMME) alongside 15-minute stage time series from the National River Flow Archive (NRFA) and land cover classes extracted from the European Space Agency's Climate Change Initiative 300 m annual Global Land Cover time series. With these data, we conduct systematic long-range probabilistic forecasting of monthly water levels in UK catchments over timescales ranging from one to twelve months ahead. We evaluate the improvement in model fit and model forecasting skill that comes from using land cover classes as predictors in the models. This work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards from space using data science techniques.

Measuring real-time streamflow using emerging technologies: Radar, hydroacoustics, and the probability concept

NASA Astrophysics Data System (ADS)

Fulton, John; Ostrowski, Joseph

2008-07-01

SummaryForecasting streamflow during extreme hydrologic events such as floods can be problematic. This is particularly true when flow is unsteady, and river forecasts rely on models that require uniform-flow rating curves to route water from one forecast point to another. As a result, alternative methods for measuring streamflow are needed to properly route flood waves and account for inertial and pressure forces in natural channels dominated by nonuniform-flow conditions such as mild water surface slopes, backwater, tributary inflows, and reservoir operations. The objective of the demonstration was to use emerging technologies to measure instantaneous streamflow in open channels at two existing US Geological Survey streamflow-gaging stations in Pennsylvania. Surface-water and instream-point velocities were measured using hand-held radar and hydroacoustics. Streamflow was computed using the probability concept, which requires velocity data from a single vertical containing the maximum instream velocity. The percent difference in streamflow at the Susquehanna River at Bloomsburg, PA ranged from 0% to 8% with an average difference of 4% and standard deviation of 8.81 m 3/s. The percent difference in streamflow at Chartiers Creek at Carnegie, PA ranged from 0% to 11% with an average difference of 5% and standard deviation of 0.28 m 3/s. New generation equipment is being tested and developed to advance the use of radar-derived surface-water velocity and instantaneous streamflow to facilitate the collection and transmission of real-time streamflow that can be used to parameterize hydraulic routing models.

Measuring real-time streamflow using emerging technologies: Radar, hydroacoustics, and the probability concept

USGS Publications Warehouse

Fulton, J.; Ostrowski, J.

2008-01-01

Forecasting streamflow during extreme hydrologic events such as floods can be problematic. This is particularly true when flow is unsteady, and river forecasts rely on models that require uniform-flow rating curves to route water from one forecast point to another. As a result, alternative methods for measuring streamflow are needed to properly route flood waves and account for inertial and pressure forces in natural channels dominated by nonuniform-flow conditions such as mild water surface slopes, backwater, tributary inflows, and reservoir operations. The objective of the demonstration was to use emerging technologies to measure instantaneous streamflow in open channels at two existing US Geological Survey streamflow-gaging stations in Pennsylvania. Surface-water and instream-point velocities were measured using hand-held radar and hydroacoustics. Streamflow was computed using the probability concept, which requires velocity data from a single vertical containing the maximum instream velocity. The percent difference in streamflow at the Susquehanna River at Bloomsburg, PA ranged from 0% to 8% with an average difference of 4% and standard deviation of 8.81 m3/s. The percent difference in streamflow at Chartiers Creek at Carnegie, PA ranged from 0% to 11% with an average difference of 5% and standard deviation of 0.28 m3/s. New generation equipment is being tested and developed to advance the use of radar-derived surface-water velocity and instantaneous streamflow to facilitate the collection and transmission of real-time streamflow that can be used to parameterize hydraulic routing models.

SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

USGS Publications Warehouse

Kiang, Julie E.; Flynn, Kate; Zhai, Tong; Hummel, Paul; Granato, Gregory

2018-03-07

This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

Web services in the U.S. geological survey streamstats web application

USGS Publications Warehouse

Guthrie, J.D.; Dartiguenave, C.; Ries, Kernell G.

2009-01-01

StreamStats is a U.S. Geological Survey Web-based GIS application developed as a tool for waterresources planning and management, engineering design, and other applications. StreamStats' primary functionality allows users to obtain drainage-basin boundaries, basin characteristics, and streamflow statistics for gaged and ungaged sites. Recently, Web services have been developed that provide the capability to remote users and applications to access comprehensive GIS tools that are available in StreamStats, including delineating drainage-basin boundaries, computing basin characteristics, estimating streamflow statistics for user-selected locations, and determining point features that coincide with a National Hydrography Dataset (NHD) reach address. For the state of Kentucky, a web service also has been developed that provides users the ability to estimate daily time series of drainage-basin average values of daily precipitation and temperature. The use of web services allows the user to take full advantage of the datasets and processes behind the Stream Stats application without having to develop and maintain them. ?? 2009 IEEE.

Water balance models in one-month-ahead streamflow forecasting

USGS Publications Warehouse

Alley, William M.

1985-01-01

Techniques are tested that incorporate information from water balance models in making 1-month-ahead streamflow forecasts in New Jersey. The results are compared to those based on simple autoregressive time series models. The relative performance of the models is dependent on the month of the year in question. The water balance models are most useful for forecasts of April and May flows. For the stations in northern New Jersey, the April and May forecasts were made in order of decreasing reliability using the water-balance-based approaches, using the historical monthly means, and using simple autoregressive models. The water balance models were useful to a lesser extent for forecasts during the fall months. For the rest of the year the improvements in forecasts over those obtained using the simpler autoregressive models were either very small or the simpler models provided better forecasts. When using the water balance models, monthly corrections for bias are found to improve minimum mean-square-error forecasts as well as to improve estimates of the forecast conditional distributions.

Climate, streamflow, and legacy effects on growth of riparian Populus angustifolia in the arid San Luis Valley, Colorado

USGS Publications Warehouse

Andersen, Douglas

2016-01-01

Knowledge of the factors affecting the vigor of desert riparian trees is important for their conservation and management. I used multiple regression to assess effects of streamflow and climate (12–14 years of data) or climate alone (up to 60 years of data) on radial growth of clonal narrowleaf cottonwood (Populus angustifolia), a foundation species in the arid, Closed Basin portion of the San Luis Valley, Colorado. I collected increment cores from trees (14–90 cm DBH) at four sites along each of Sand and Deadman creeks (total N = 85), including both perennial and ephemeral reaches. Analyses on trees <110 m from the stream channel explained 33–64% of the variation in standardized growth index (SGI) over the period having discharge measurements. Only 3 of 7 models included a streamflow variable; inclusion of prior-year conditions was common. Models for trees farther from the channel or over a deep water table explained 23–71% of SGI variability, and 4 of 5 contained a streamflow variable. Analyses using solely climate variables over longer time periods explained 17–85% of SGI variability, and 10 of 12 included a variable indexing summer precipitation. Three large, abrupt shifts in recent decades from wet to dry conditions (indexed by a seasonal Palmer Drought Severity Index) coincided with dramatically reduced radial growth. Each shift was presumably associated with branch dieback that produced a legacy effect apparent in many SGI series: uncharacteristically low SGI in the year following the shift. My results suggest trees in locations distant from the active channel rely on the regional shallow unconfined aquifer, summer rainfall, or both to meet water demands. The landscape-level differences in the water supplies sustaining these trees imply variable effects from shifts in winter-versus monsoon-related precipitation, and from climate change versus streamflow or groundwater management.

Comprehensive, Process-based Identification of Hydrologic Models using Satellite and In-situ Water Storage Data: A Multi-objective calibration Approach

NASA Astrophysics Data System (ADS)

Abdo Yassin, Fuad; Wheater, Howard; Razavi, Saman; Sapriza, Gonzalo; Davison, Bruce; Pietroniro, Alain

2015-04-01

The credible identification of vertical and horizontal hydrological components and their associated parameters is very challenging (if not impossible) by only constraining the model to streamflow data, especially in regions where the vertical processes significantly dominate the horizontal processes. The prairie areas of the Saskatchewan River basin, a major water system in Canada, demonstrate such behavior, where the hydrologic connectivity and vertical fluxes are mainly controlled by the amount of surface and sub-surface water storages. In this study, we develop a framework for distributed hydrologic model identification and calibration that jointly constrains the model response (i.e., streamflows) as well as a set of model state variables (i.e., water storages) to observations. This framework is set up in the form of multi-objective optimization, where multiple performance criteria are defined and used to simultaneously evaluate the fidelity of the model to streamflow observations and observed (estimated) changes of water storage in the gridded landscape over daily and monthly time scales. The time series of estimated changes in total water storage (including soil, canopy, snow and pond storages) used in this study were derived from an experimental study enhanced by the information obtained from the GRACE satellite. We test this framework on the calibration of a Land Surface Scheme-Hydrology model, called MESH (Modélisation Environmentale Communautaire - Surface and Hydrology), for the Saskatchewan River basin. Pareto Archived Dynamically Dimensioned Search (PA-DDS) is used as the multi-objective optimization engine. The significance of using the developed framework is demonstrated in comparison with the results obtained through a conventional calibration approach to streamflow observations. The approach of incorporating water storage data into the model identification process can more potentially constrain the posterior parameter space, more comprehensively evaluate the model fidelity, and yield more credible predictions.

Attribution of hydrological change using the Method of Multiple Working Hypotheses

NASA Astrophysics Data System (ADS)

Harrigan, Shaun

2017-04-01

The methods we have developed for managing our long-term water supply and protection from extreme hydrological events such as droughts and floods have been founded on the assumption that the hydrological cycle operates under natural conditions. However, it increasingly recognised that humans have the potential to induce significant change in almost every component of the hydrological cycle, for example, climate change, land-use change, and river engineering. Statistical detection of change in streamflow, outside that of natural variability, is an important scientific endeavour, but it does not tell us anything about the drivers of change. Attribution is the process of establishing the most likely cause(s) of a detected change - the why. Attribution is complex due to the integrated nature of streamflow and the proliferation of multiple possible drivers. It is perhaps this complexity, combined with few proven theoretical approaches to this problem in hydrology that has led to others to call for "more efforts and scientific rigour" (Merz et al., 2012). It is easier to limit the cause of a detected change to a single driver, or use simple correlation analysis alone as evidence of causation. It is convenient when the direction of a change in streamflow is consistent with what is expected from a well-known driver such as climate change. Over a century ago, Thomas Chamberlin argued these types of issues were common in many disciplines given how the scientific method is approached in general. His 1890 article introduces the Method of Multiple Working Hypotheses (MMWH) in an attempt to limit our confirmation bias and strives for increased objectivity. This presentation will argue that the MMWH offers an attractive theoretical approach to the attribution of hydrological change in modern hydrology as demonstrated through a case study of a well-documented change point in streamflow within the Boyne Catchment in Ireland. Further Reading Chamberlin, T. C.: The Method of Multiple Working Hypotheses, Science (old series), 15(366), 92-96, doi:10.1126/science.ns-15.366.92, 1890. Harrigan, S., Murphy, C., Hall, J., Wilby, R. L. and Sweeney, J.: Attribution of detected changes in streamflow using multiple working hypotheses, Hydrol. Earth Syst. Sci., 18(5), 1935-1952, doi:10.5194/hess-18-1935-2014, 2014. Merz, B., Vorogushyn, S., Uhlemann, S., Delgado, J. and Hundecha, Y.: HESS Opinions "More efforts and scientific rigour are needed to attribute trends in flood time series," Hydrol. Earth Syst. Sci., 16(5), 1379-1387, doi:10.5194/hess-16-1379-2012, 2012.

Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

NASA Astrophysics Data System (ADS)

Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

2016-12-01

One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

Hydrologic and hydraulic flood forecasting constrained by remote sensing data

NASA Astrophysics Data System (ADS)

Li, Y.; Grimaldi, S.; Pauwels, V. R. N.; Walker, J. P.; Wright, A. J.

2017-12-01

Flooding is one of the most destructive natural disasters, resulting in many deaths and billions of dollars of damages each year. An indispensable tool to mitigate the effect of floods is to provide accurate and timely forecasts. An operational flood forecasting system typically consists of a hydrologic model, converting rainfall data into flood volumes entering the river system, and a hydraulic model, converting these flood volumes into water levels and flood extents. Such a system is prone to various sources of uncertainties from the initial conditions, meteorological forcing, topographic data, model parameters and model structure. To reduce those uncertainties, current forecasting systems are typically calibrated and/or updated using ground-based streamflow measurements, and such applications are limited to well-gauged areas. The recent increasing availability of spatially distributed remote sensing (RS) data offers new opportunities to improve flood forecasting skill. Based on an Australian case study, this presentation will discuss the use of 1) RS soil moisture to constrain a hydrologic model, and 2) RS flood extent and level to constrain a hydraulic model.The GRKAL hydrological model is calibrated through a joint calibration scheme using both ground-based streamflow and RS soil moisture observations. A lag-aware data assimilation approach is tested through a set of synthetic experiments to integrate RS soil moisture to constrain the streamflow forecasting in real-time.The hydraulic model is LISFLOOD-FP which solves the 2-dimensional inertial approximation of the Shallow Water Equations. Gauged water level time series and RS-derived flood extent and levels are used to apply a multi-objective calibration protocol. The effectiveness with which each data source or combination of data sources constrained the parameter space will be discussed.

HydroClimATe: hydrologic and climatic analysis toolkit

USGS Publications Warehouse

Dickinson, Jesse; Hanson, Randall T.; Predmore, Steven K.

2014-01-01

The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.

Simulation of groundwater and surface-water resources and evaluation of water-management alternatives for the Chamokane Creek basin, Stevens County, Washington

USGS Publications Warehouse

Ely, D. Matthew; Kahle, Sue C.

2012-01-01

A three-dimensional, transient numerical model of groundwater and surface-water flow was constructed for Chamokane Creek basin to better understand the groundwater-flow system and its relation to surface-water resources. The model described in this report can be used as a tool by water-management agencies and other stakeholders to quantitatively evaluate the effects of potential increases in groundwater pumping on groundwater and surface-water resources in the basin. The Chamokane Creek model was constructed using the U.S. Geological Survey (USGS) integrated model, GSFLOW. GSFLOW was developed to simulate coupled groundwater and surface-water resources. The model uses 1,000-foot grid cells that subdivide the model domain by 102 rows and 106 columns. Six hydrogeologic units in the model are represented using eight model layers. Daily precipitation and temperature were spatially distributed and subsequent groundwater recharge was computed within GSFLOW. Streamflows in Chamokane Creek and its major tributaries are simulated in the model by routing streamflow within a stream network that is coupled to the groundwater-flow system. Groundwater pumpage and surface-water diversions and returns specified in the model were derived from monthly and annual pumpage values previously estimated from another component of this study and new data reported by study partners. The model simulation period is water years 1980-2010 (October 1, 1979, to September 30, 2010), but the model was calibrated to the transient conditions for water years 1999-2010 (October 1, 1998, to September 30, 2010). Calibration was completed by using traditional trial-and-error methods and automated parameter-estimation techniques. The model adequately reproduces the measured time-series groundwater levels and daily streamflows. At well observation points, the mean difference between simulated and measured hydraulic heads is 7 feet with a root-mean-square error divided by the total difference in water levels of 4.7 percent. Simulated streamflow was compared to measured streamflow at the USGS streamflow-gaging station-Chamokane Creek below Falls, near Long Lake (12433200). Annual differences between measured and simulated streamflow for the site ranged from -63 to 22 percent. Calibrated model output includes a 31-year estimate of monthly water budget components for the hydrologic system. Five model applications (scenarios) were completed to obtain a better understanding of the relation between groundwater pumping and surface-water resources. The calibrated transient model was used to evaluate: (1) the connection between the upper- and middle-basin groundwater systems, (2) the effect of surface-water and groundwater uses in the middle basin, (3) the cumulative impacts of claims registry use and permit-exempt wells on Chamokane Creek streamflow, (4) the frequency of regulation due to impacted streamflow, and (5) the levels of domestic and stockwater use that can be regulated. The simulation results indicated that streamflow is affected by existing groundwater pumping in the upper and middle basins. Simulated water-management scenarios show streamflow increased relative to historical conditions as groundwater and surface-water withdrawals decreased.

Statistical analysis of hydrological response in urbanising catchments based on adaptive sampling using inter-amount times

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-Claire; Schleiss, Marc

2017-04-01

In this study, we introduced an alternative approach for analysis of hydrological flow time series, using an adaptive sampling framework based on inter-amount times (IATs). The main difference with conventional flow time series is the rate at which low and high flows are sampled: the unit of analysis for IATs is a fixed flow amount, instead of a fixed time window. We analysed statistical distributions of flows and IATs across a wide range of sampling scales to investigate sensitivity of statistical properties such as quantiles, variance, skewness, scaling parameters and flashiness indicators to the sampling scale. We did this based on streamflow time series for 17 (semi)urbanised basins in North Carolina, US, ranging from 13 km2 to 238 km2 in size. Results showed that adaptive sampling of flow time series based on inter-amounts leads to a more balanced representation of low flow and peak flow values in the statistical distribution. While conventional sampling gives a lot of weight to low flows, as these are most ubiquitous in flow time series, IAT sampling gives relatively more weight to high flow values, when given flow amounts are accumulated in shorter time. As a consequence, IAT sampling gives more information about the tail of the distribution associated with high flows, while conventional sampling gives relatively more information about low flow periods. We will present results of statistical analyses across a range of subdaily to seasonal scales and will highlight some interesting insights that can be derived from IAT statistics with respect to basin flashiness and impact urbanisation on hydrological response.

Beyond annual streamflow reconstructions for the Upper Colorado River Basin: a paleo-water-balance approach

USGS Publications Warehouse

Gangopadhyay, Subhrendu; McCabe, Gregory J.; Woodhouse, Connie A.

2015-01-01

In this paper, we present a methodology to use annual tree-ring chronologies and a monthly water balance model to generate annual reconstructions of water balance variables (e.g., potential evapotrans- piration (PET), actual evapotranspiration (AET), snow water equivalent (SWE), soil moisture storage (SMS), and runoff (R)). The method involves resampling monthly temperature and precipitation from the instrumental record directed by variability indicated by the paleoclimate record. The generated time series of monthly temperature and precipitation are subsequently used as inputs to a monthly water balance model. The methodology is applied to the Upper Colorado River Basin, and results indicate that the methodology reliably simulates water-year runoff, maximum snow water equivalent, and seasonal soil moisture storage for the instrumental period. As a final application, the methodology is used to produce time series of PET, AET, SWE, SMS, and R for the 1404–1905 period for the Upper Colorado River Basin.

Characterization of sediment transport upstream and downstream from Lake Emory on the Little Tennessee River near Franklin, North Carolina, 2014–15

USGS Publications Warehouse

Huffman, Brad A.; Hazell, William F.; Oblinger, Carolyn J.

2017-09-06

Federal, State, and local agencies and organizations have expressed concerns regarding the detrimental effects of excessive sediment transport on aquatic resources and endangered species populations in the upper Little Tennessee River and some of its tributaries. In addition, the storage volume of Lake Emory, which is necessary for flood control and power generation, has been depleted by sediment deposition. To help address these concerns, a 2-year study was conducted in the upper Little Tennessee River Basin to characterize the ambient suspended-sediment concentrations and suspended-sediment loads upstream and downstream from Lake Emory in Franklin, North Carolina. The study was conducted by the U.S. Geological Survey in cooperation with Duke Energy. Suspended-sediment samples were collected periodically, and time series of stage and turbidity data were measured from December 2013 to January 2016 upstream and downstream from Lake Emory. The stage data were used to compute time-series streamflow. Suspended-sediment samples, along with time-series streamflow and turbidity data, were used to develop regression models that were used to estimate time-series suspended-sediment concentrations for the 2014 and 2015 calendar years. These concentrations, along with streamflow data, were used to compute suspended-sediment loads. Selected suspended-sediment samples were collected for analysis of particle-size distribution, with emphasis on high-flow events. Bed-load samples were also collected upstream from Lake Emory.The estimated annual suspended-sediment loads (yields) for the upstream site for the 2014 and 2015 calendar years were 27,000 short tons (92 short tons per square mile) and 63,300 short tons (215 short tons per square mile), respectively. The annual suspended-sediment loads (yields) for the downstream site for 2014 and 2015 were 24,200 short tons (75 short tons per square mile) and 94,300 short tons (292 short tons per square mile), respectively. Overall, the suspended-sediment load at the downstream site was about 28,300 short tons greater than the upstream site over the study period.As expected, high-flow events (the top 5 percent of daily mean flows) accounted for the majority of the sediment load; 80 percent at the upstream site and 90 percent at the downstream site. A similar relation between turbidity (the top 5 percent of daily mean turbidity) and high loads was also noted. In general, when instantaneous streamflows at the upstream site exceeded 5,000 cubic feet per second, increased daily loads were computed at the downstream site. During low to moderate flows, estimated suspended-sediment loads were lower at the downstream site when compared to the upstream site, which suggests that sediment deposition may be occurring in the intervening reach during those conditions. During the high-flow events, the estimated suspended-sediment loads were higher at the downstream site; however, it is impossible to say with certainty whether the increase in loading was due to scouring of lake sediment, contributions from the additional source area, model error, or a combination of one or more of these factors. The computed loads for a one-week period (December 24–31, 2015), during which the two largest high-flow events of the study period occurred, were approximately 52 percent of the 2015 annual sediment load (36 percent of 2-year load) at the upstream site and approximately 72 percent of the 2015 annual sediment load (57 percent of 2-year load) at the downstream site. Six bedload samples were collected during three events; two high-flow events and one base-flow event. The contribution of bedload to the total sediment load was determined to be insignificant for sampled flows. In general, streamflows for long-term streamgages in the study area were below normal for the majority of the study period; however, flows during the last 3 months of the study period were above normal, including the extreme events during the last week of the study period.

Flood-rich and flood-poor periods in Spain in 1942-2009

NASA Astrophysics Data System (ADS)

Mediero, Luis; Santillán, David; Garrote, Luis

2016-04-01

Several studies to detect trends in flood series at either national or trans-national scales have been conducted. Mediero et al. (2015) studied flood trends by using the longest streamflow records available in Europe. They found a decreasing trend in the Atlantic, Continental and Scandinavian regions. More specifically, Mediero et al. (2014) found a general decreasing trend in flood series in Spain in the period 1959-2009. Trends in flood series are usually detected by the Mann-Kendall test applied to a given period. However, the result of the Mann-Kendall test can change in terms of the starting and ending year of the series. Flood oscillations can occur and flood-rich and flood-poor periods could condition the results, especially when they are located at the beginning or end of the series. A methodology to identify statistically significant flood-rich and flood-poor periods is developed, based on the comparison between the expected sampling variability of floods when stationarity is assumed and the observed variability of floods in a given series. The methodology is applied to the longest series of annual maximum floods, peaks over threshold and counts of annual occurrences in peaks over threshold series observed in Spain in the period 1942-2009. A flood-rich period in 1950-1970 and a flood-poor period in 1970-1990 are identified in most of the selected sites. The generalised decreasing trend in flood series found by Mediero et al. (2014) could be explained by a flood-rich period placed at the beginning of the series and a flood-poor period located at the end of the series. References: Mediero, L., Kjeldsen, T.R., Macdonald, N., Kohnova, S., Merz, B., Vorogushyn, S., Wilson, D., Alburquerque, T., Blöschl, G., Bogdanowicz, E., Castellarin, A., Hall, J., Kobold, M., Kriauciuniene, J., Lang, M., Madsen, H., Onuşluel Gül, G., Perdigão, R.A.P., Roald, L.A., Salinas, J.L., Toumazis, A.D., Veijalainen, N., Óðinn Þórarinsson. Identification of coherent flood regions across Europe using the longest streamflow records, Journal of Hydrology, 528, 341-360, 2015. Mediero, L., Santillán, D., Garrote, L., Granados, A. Detection and attribution of trends in magnitude, frequency and timing of floods in Spain, Journal of Hydrology, 517, 1072-1088, 2014.

Tree-ring indicators of rainfall and streamflow for the Ili-Balkhash Basin, Central Asia since CE 1560

NASA Astrophysics Data System (ADS)

Chen, Feng; Yuan, Yujiang; Yu, Shulong

2017-09-01

We reconstructed previous July - current April total precipitation in the upper Ili-Balkhash Basin of Central Asia, using a transfer equation based on the correlation between regional tree-ring width series and local precipitation data. Dry periods were identified from 1586-1612, 1637-1669, 1695-1721, 1759-1782, 1804-1864, 1907-1930 and 1974-1993, while wet periods occurred from 1560-1585, 1613-1636, 1670-1694, 1722-1758, 1783-1803, 1865-1906, 1931-1973 and 1994-2006. Spatial correlation analysis indicates that our precipitation reconstruction is broadly representative of precipitation in the entire Ili-Balkhash Basin. The precipitation timeseries is also strongly related to streamflow measurements, revealing that variations in precipitation in the upper Ili-Balkhash Basin have a dramatic influence on streamflow into Lake Balkhash. The precipitation reconstruction also compares well with various streamflow reconstructions from the Tien Shan, and exhibits an increasing streamflow trend in the 1980s through 2000s. Spectral analysis showed significant 60-, 33-, 11-, 2.8- and 2.1-year cycles over the past 447 years. Our 447-year precipitation reconstruction provides the basis for comparing past and present hydroclimate changes, which will be important for detection and attribution of hydroclimate variation in the Ili-Balkhash Basin.

Joint modelling of annual maximum drought severity and corresponding duration

NASA Astrophysics Data System (ADS)

Tosunoglu, Fatih; Kisi, Ozgur

2016-12-01

In recent years, the joint distribution properties of drought characteristics (e.g. severity, duration and intensity) have been widely evaluated using copulas. However, history of copulas in modelling drought characteristics obtained from streamflow data is still short, especially in semi-arid regions, such as Turkey. In this study, unlike previous studies, drought events are characterized by annual maximum severity (AMS) and corresponding duration (CD) which are extracted from daily streamflow of the seven gauge stations located in Çoruh Basin, Turkey. On evaluation of the various univariate distributions, the Exponential, Weibull and Logistic distributions are identified as marginal distributions for the AMS and CD series. Archimedean copulas, namely Ali-Mikhail-Haq, Clayton, Frank and Gumbel-Hougaard, are then employed to model joint distribution of the AMS and CD series. With respect to the Anderson Darling and Cramér-von Mises statistical tests and the tail dependence assessment, Gumbel-Hougaard copula is identified as the most suitable model for joint modelling of the AMS and CD series at each station. Furthermore, the developed Gumbel-Hougaard copulas are used to derive the conditional and joint return periods of the AMS and CD series which can be useful for designing and management of reservoirs in the basin.

Effects of urban development in the Puget Lowland, Washington, on interannual streamflow patterns: Consequences for channel form and streambed disturbance

USGS Publications Warehouse

Konrad, Christopher P.; Booth, Derek B.; Burges, Stephen J.

2005-01-01

Recovery and protection of streams in urban areas depend on a comprehensive understanding of how human activities affect stream ecosystems. The hydrologic effects of urban development and the consequences for stream channel form and streambed stability were examined in 16 streams in the Puget Lowland, Washington, using three streamflow metrics that integrate storm‐scale effects of urban development over annual to decadal timescales: the fraction of time that streamflow exceeds the mean streamflow (TQmean), the coefficient of variation of annual maximum streamflow (CVAMF), and the fraction of time that streamflow exceeds the 0.5‐year flood (T0.5). Urban streams had low interannual variability in annual maximum streamflow and brief duration of frequent high flows, as indicated by significant correlations between road density and both CVAMFand T0.5. The broader distribution of streamflow indicated by TQmean may be affected by urban development, but differences in TQmean between streams are also likely a result of other physiographic factors. The increase in the magnitude of frequent high flows due to urban development but not their cumulative duration has important consequences for channel form and bed stability in gravel bed streams because geomorphic equilibrium depends on moderate duration streamflow (e.g., exceeded 10% of the time). Streams with low values of TQmean and T0.5 are narrower than expected from hydraulic geometry. Dimensionless boundary shear stress (t*) for the 0.5‐year flood was inversely related to T0.5 among the streams, indicating frequent and extensive bed disturbance in streams with low values of T0.5. Although stream channels expand and the size of bed material increases in response to urban streamflow patterns, these adjustments may be insufficient to reestablish the disturbance regime in urban streams because of the differential increase in the magnitude of frequent high flows causing disturbance relative to any changes in longer duration, moderate flows that establish a stable channel.

Long-term variation analysis of a tropical river's annual streamflow regime over a 50-year period

NASA Astrophysics Data System (ADS)

Seyam, Mohammed; Othman, Faridah

2015-07-01

Studying the long-term changes of streamflow is an important tool for enhancing water resource and river system planning, design, and management. The aim of this work is to identify the long-term variations in annual streamflow regime over a 50-year period from 1961 to 2010 in the Selangor River, which is one of the main tropical rivers in Malaysia. Initially, the data underwent preliminary independence, normality, and homogeneity testing using the Pearson correlation coefficient and Shapiro-Wilk and Pettitt's tests, respectively. The work includes a study and analysis of the changes through nine variables describing the annual streamflow and variations in the yearly duration of high and low streamflows. The analyses were conducted via two time scales: yearly and sub-periodic. The sub-periods were obtained by segmenting the 50 years into seven sub-periods by two techniques, namely the change-point test and direct method. Even though analysis revealed nearly negligible changes in mean annual flow over the study period, the maximum annual flow generally increased while the minimum annual flow significantly decreased with respect to time. It was also observed that the variables describing the dispersion in streamflow continually increased with respect to time. An obvious increase was detected in the yearly duration of danger level of streamflow, a slight increase was noted in the yearly duration of warning and alert levels, and a slight decrease in the yearly duration of low streamflow was found. The perceived changes validate the existence of long-term changes in annual streamflow regime, which increase the probability of floods and droughts occurring in future. In light of the results, attention should be drawn to developing water resource management and flood protection plans in order to avert the harmful effects potentially resulting from the expected changes in annual streamflow regime.

How important is the spatiotemporal structure of a rainfall field when generating a streamflow hydrograph? An investigation using Reverse Hydrology

NASA Astrophysics Data System (ADS)

Kretzschmar, Ann; Tych, Wlodek; Beven, Keith; Chappell, Nick

2017-04-01

Flooding is the most widely occurring natural disaster affecting thousands of lives and businesses worldwide each year, and the size and frequency of flood-events are predicted to increase with climate change. The main input-variable for models used in flood prediction is rainfall. Estimating the rainfall input is often based on a sparse network of raingauges, which may or may not be representative of the salient rainfall characteristics responsible for generating of storm-hydrographs. A method based on Reverse Hydrology (Kretzschmar et al 2014 Environ Modell Softw) has been developed and is being tested using the intensively-instrumented Brue catchment (Southwest England) to explore the spatiotemporal structure of the rainfall-field (using 23 rain gauges over the 135.2 km2 basin). We compare how well the rainfall measured at individual gauges, or averaged over the basin, represent the rainfall inferred from the streamflow signal. How important is it to get the detail of the spatiotemporal rainfall structure right? Rainfall is transformed by catchment processes as it moves to streams, so exact duplication of the structure may not be necessary. 'True' rainfall estimated using 23 gauges / 135.2 km2 is likely to be a good estimate of the overall-catchment-rainfall, however, the integration process 'smears' the rainfall patterns in time, i.e. reduces the number of and lengthens rain-events as they travel across the catchment. This may have little impact on the simulation of stream-hydrographs when events are extensive across the catchment (e.g., frontal rainfall events) but may be significant for high-intensity, localised convective events. The Reverse Hydrology approach uses the streamflow record to infer a rainfall sequence with a lower time-resolution than the original input time-series. The inferred rainfall series is, however, able simulate streamflow as well as the observed, high resolution rainfall (Kretzschmar et al 2015 Hydrol Res). Most gauged catchments in the UK of a similar size would only have data available for 1 to 3 raingauges. The high density of the Brue raingauge network allows a good estimate of the 'True' catchment rainfall to be made and compared with data from an individual raingauge as if that was the only data available. In addition the rainfall from each raingauge is compared with rainfall inferred from streamflow using data from the selected individual raingauge, and also inferred from the full catchment network. The stochastic structure of the rainfall from all of these datasets is compared using a combination of traditional statistical measures, i.e., the first 4 moments of rainfall totals and its residuals; plus the number, length and distribution of wet and dry periods; rainfall intensity characteristics; and their ability to generate the observed stream hydrograph. Reverse Hydrology, which utilises information present in both the input rainfall and the output hydrograph, has provided a method of investigating the quality of the information each gauge adds to the catchment-average (Kretzschmar et al 2016 Procedia Eng.). Further, it has been used to ascertain how important reproducing the detailed rainfall structure really is, when used for flow prediction.

Water Resources Data, Puerto Rico and the U.S. Virgin Islands, Water Year 2002

USGS Publications Warehouse

Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Garcia, Rene; Sanchez, Ana V.

2004-01-01

The Water Resources Division of the U.S. Geological Survey, in cooperation with local and Federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 2002.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 95 streamflow gaging stations, daily sediment records for 28 streamflow stations, 27 partial-record or miscellaneous streamflow stations, stage records for 17 reservoirs, and (2) water-quality records for 17 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 102 observation wells.

Water Resources Data, Puerto Rico and the U.S. Virgin Islands, Water Year 2001

USGS Publications Warehouse

Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Garcia, Rene; Sanchez, Ana V.

2002-01-01

The Water Resources Division of the U.S. Geological Survey, in cooperation with local and Federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 2001.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 95 streamflow gaging stations, daily sediment records for 23 streamflow stations, 20 partial-record or miscellaneous streamflow stations, stage records for 18 reservoirs, and (2) water-quality records for 17 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 103 observation wells.

Water Resources Data, Puerto Rico and the U.S. Virgin Islands, Water Year 2000

USGS Publications Warehouse

Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Vachier, Ricardo J.; Sanchez, Ana V.

2001-01-01

The Water Resources Division of the U.S. Geological Survey, in cooperation with local and federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 2000.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 85 streamflow gaging stations, daily sediment records for 26 streamflow stations, 21 partial-record or miscellaneous streamflow stations, stage records for 18 reservoirs, and (2) water-quality records for 16 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 108 observation wells.

Water resources data, Puerto Rico and the U.S. Virgin Islands, Water Year 1998

USGS Publications Warehouse

Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Vachier, Ricardo J.; Sanchez, Ana V.

1999-01-01

The Water Resources Division of the U.S. Geological Survey, in cooperation with local and federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 1998.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 76 streamflow gaging stations, daily sediment records for 27 streamflow stations, 99 partial-record or miscellaneous streamflow stations, stage records for 17 reservoirs, and (2) water-quality records for 16 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 97 observation wells.

Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill

NASA Technical Reports Server (NTRS)

Koster, R.; Mahanama, S.; Livneh, B.; Lettenmaier, D.; Reichle, R.

2011-01-01

in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer.

Effects of urbanization and stormwater control measures on streamflows in the vicinity of Clarksburg, Maryland, USA

USGS Publications Warehouse

Rhea, Lee; Jarnagin, Taylor; Hogan, Dianna; Loperfido, J. V.; Shuster, William

2015-01-01

Understanding the efficacy of revised watershed management methods is important to mitigating the impacts of urbanization on streamflow. We evaluated the influence of land use change, primarily as urbanization, and stormwater control measures on the relationship between precipitation and stream discharge over an 8-year period for five catchments near Clarksburg, Montgomery County, Maryland, USA. A unit-hydrograph model based on a temporal transfer function was employed to account for and standardize temporal variation in rainfall pattern, and properly apportion rainfall to streamflow at different time lags. From these lagged relationships, we quantified a correction to the precipitation time series to achieve a hydrograph that showed good agreement between precipitation and discharge records. Positive corrections appeared to include precipitation events that were of limited areal extent and therefore not captured by our rain gages. Negative corrections were analysed for potential causal relationships. We used mixed-model statistical techniques to isolate different sources of variance as drivers that mediate the rainfall–runoff dynamic before and after management. Seasonal periodicity mediated rainfall–runoff relationships, and land uses (i.e. agriculture, natural lands, wetlands and stormwater control measures) were statistically significant predictors of precipitation apportionment to stream discharge. Our approach is one way to evaluate actual effectiveness of management efforts in the face of complicating circumstances and could be paired with cost data to understand economic efficiency or life cycle aspects of watershed management. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

A Comparison of Turbidity-Based and Streamflow-Based Estimates of Suspended-Sediment Concentrations in Three Chesapeake Bay Tributaries

USGS Publications Warehouse

Jastram, John D.; Moyer, Douglas; Hyer, Kenneth

2009-01-01

Fluvial transport of sediment into the Chesapeake Bay estuary is a persistent water-quality issue with major implications for the overall health of the bay ecosystem. Accurately and precisely estimating the suspended-sediment concentrations (SSC) and loads that are delivered to the bay, however, remains challenging. Although manual sampling of SSC produces an accurate series of point-in-time measurements, robust extrapolation to unmeasured periods (especially highflow periods) has proven to be difficult. Sediment concentrations typically have been estimated using regression relations between individual SSC values and associated streamflow values; however, suspended-sediment transport during storm events is extremely variable, and it is often difficult to relate a unique SSC to a given streamflow. With this limitation for estimating SSC, innovative approaches for generating detailed records of suspended-sediment transport are needed. One effective method for improved suspended-sediment determination involves the continuous monitoring of turbidity as a surrogate for SSC. Turbidity measurements are theoretically well correlated to SSC because turbidity represents a measure of water clarity that is directly influenced by suspended sediments; thus, turbidity-based estimation models typically are effective tools for generating SSC data. The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program and Virginia Department of Environmental Quality, initiated continuous turbidity monitoring on three major tributaries of the bay - the James, Rappahannock, and North Fork Shenandoah Rivers - to evaluate the use of turbidity as a sediment surrogate in rivers that deliver sediment to the bay. Results of this surrogate approach were compared to the traditionally applied streamflow-based approach for estimating SSC. Additionally, evaluation and comparison of these two approaches were conducted for nutrient estimations. Results demonstrate that the application of turbidity-based estimation models provides an improved method for generating a continuous record of SSC, relative to the classical approach that uses streamflow as a surrogate for SSC. Turbidity-based estimates of SSC were found to be more accurate and precise than SSC estimates from streamflow-based approaches. The turbidity-based SSC estimation models explained 92 to 98 percent of the variability in SSC, while streamflow-based models explained 74 to 88 percent of the variability in SSC. Furthermore, the mean absolute error of turbidity-based SSC estimates was 50 to 87 percent less than the corresponding values from the streamflow-based models. Statistically significant differences were detected between the distributions of residual errors and estimates from the two approaches, indicating that the turbidity-based approach yields estimates of SSC with greater precision than the streamflow-based approach. Similar improvements were identified for turbidity-based estimates of total phosphorus, which is strongly related to turbidity because total phosphorus occurs predominantly in particulate form. Total nitrogen estimation models based on turbidity and streamflow generated estimates of similar quality, with the turbidity-based models providing slight improvements in the quality of estimations. This result is attributed to the understanding that nitrogen transport is dominated by dissolved forms that relate less directly to streamflow and turbidity. Improvements in concentration estimation resulted in improved estimates of load. Turbidity-based suspended-sediment loads estimated for the James River at Cartersville, VA, monitoring station exhibited tighter confidence interval bounds and a coefficient of variation of 12 percent, compared with a coefficient of variation of 38 percent for the streamflow-based load.

Streamflow characteristics of small tributaries of Rock Creek, Milk River basin, Montana, base period water years 1983-87

USGS Publications Warehouse

Parrett, Charles; Hull, J.A.

1990-01-01

Five streamflow-gaging stations were installed in the Rock Creek basin north of the Milk River near Hinsdale, Montana. Streamflow was monitored at these stations and at an existing gaging station upstream on Rock Creek from May 1983 through September 1987. The data collected were used to describe the flow characteristics of four small tributary streams. Annual mean streamflow ranges from 2.8 to 57 cu ft/sec in the mainstem and from 0 to 0.60 cu ft/sec in the tributaries. Monthly mean streamflow ranged from 0 to 528 cu ft/sec in Rock Creek and from zero to 5.3 cu ft/sec in the four tributaries. The six gaged sites show similar patterns of daily mean streamflow during periods of large runoff, but substantial individual variations during periods of lesser runoff. During periods of lesser runoff , the small tributaries may have small daily mean streamflows. At other times, daily mean streamflow at the two mainstem sites decreased downstream. Daily mean streamflow in the tributaries appears to be closely related to daily mean streamflow in the mainstem only during periods of substantial area-wide runoff. Thus, streamflow in the tributaries resulting from local storms or local snowmelt may not contribute to streamflow in the mainstem. (USGS)

Where does streamwater come from in low-relief forested watersheds? A dual-isotope approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klaus, J.; McDonnell, J. J.; Jackson, C. R.

The time and geographic sources of streamwater in low-relief watersheds are poorly understood. This is partly due to the difficult combination of low runoff coefficients and often damped streamwater isotopic signals precluding traditional hydrograph separation and convolution integral approaches. Here we present a dual-isotope approach involving 18O and 2H of water in a low-angle forested watershed to determine streamwater source components and then build a conceptual model of streamflow generation. We focus on three headwater lowland sub-catchments draining the Savannah River Site in South Carolina, USA. Our results for a 3-year sampling period show that the slopes of the meteoricmore » water lines/evaporation water lines (MWLs/EWLs) of the catchment water sources can be used to extract information on runoff sources in ways not considered before. Our dual-isotope approach was able to identify unique hillslope, riparian and deep groundwater, and streamflow compositions. Thus, the streams showed strong evaporative enrichment compared to the local meteoric water line (δ 2H = 7.15 · δ 18O +9.28‰) with slopes of 2.52, 2.84, and 2.86. Based on the unique and unambiguous slopes of the EWLs of the different water cycle components and the isotopic time series of the individual components, we were able to show how the riparian zone controls baseflow in this system and how the riparian zone "resets" the stable isotope composition of the observed streams in our low-angle, forested watersheds. Although this approach is limited in terms of quantifying mixing percentages between different end-members, our dual-isotope approach enabled the extraction of hydrologically useful information in a region with little change in individual isotope time series.« less

Where does streamwater come from in low-relief forested watersheds? A dual-isotope approach

DOE PAGES

Klaus, J.; McDonnell, J. J.; Jackson, C. R.; ...

2015-01-08

The time and geographic sources of streamwater in low-relief watersheds are poorly understood. This is partly due to the difficult combination of low runoff coefficients and often damped streamwater isotopic signals precluding traditional hydrograph separation and convolution integral approaches. Here we present a dual-isotope approach involving 18O and 2H of water in a low-angle forested watershed to determine streamwater source components and then build a conceptual model of streamflow generation. We focus on three headwater lowland sub-catchments draining the Savannah River Site in South Carolina, USA. Our results for a 3-year sampling period show that the slopes of the meteoricmore » water lines/evaporation water lines (MWLs/EWLs) of the catchment water sources can be used to extract information on runoff sources in ways not considered before. Our dual-isotope approach was able to identify unique hillslope, riparian and deep groundwater, and streamflow compositions. Thus, the streams showed strong evaporative enrichment compared to the local meteoric water line (δ 2H = 7.15 · δ 18O +9.28‰) with slopes of 2.52, 2.84, and 2.86. Based on the unique and unambiguous slopes of the EWLs of the different water cycle components and the isotopic time series of the individual components, we were able to show how the riparian zone controls baseflow in this system and how the riparian zone "resets" the stable isotope composition of the observed streams in our low-angle, forested watersheds. Although this approach is limited in terms of quantifying mixing percentages between different end-members, our dual-isotope approach enabled the extraction of hydrologically useful information in a region with little change in individual isotope time series.« less

A comparison of four streamflow record extension techniques

USGS Publications Warehouse

Hirsch, Robert M.

1982-01-01

One approach to developing time series of streamflow, which may be used for simulation and optimization studies of water resources development activities, is to extend an existing gage record in time by exploiting the interstation correlation between the station of interest and some nearby (long-term) base station. Four methods of extension are described, and their properties are explored. The methods are regression (REG), regression plus noise (RPN), and two new methods, maintenance of variance extension types 1 and 2 (MOVE.l, MOVE.2). MOVE.l is equivalent to a method which is widely used in psychology, biometrics, and geomorphology and which has been called by various names, e.g., ‘line of organic correlation,’ ‘reduced major axis,’ ‘unique solution,’ and ‘equivalence line.’ The methods are examined for bias and standard error of estimate of moments and order statistics, and an empirical examination is made of the preservation of historic low-flow characteristics using 50-year-long monthly records from seven streams. The REG and RPN methods are shown to have serious deficiencies as record extension techniques. MOVE.2 is shown to be marginally better than MOVE.l, according to the various comparisons of bias and accuracy.

A Comparison of Four Streamflow Record Extension Techniques

NASA Astrophysics Data System (ADS)

Hirsch, Robert M.

1982-08-01

One approach to developing time series of streamflow, which may be used for simulation and optimization studies of water resources development activities, is to extend an existing gage record in time by exploiting the interstation correlation between the station of interest and some nearby (long-term) base station. Four methods of extension are described, and their properties are explored. The methods are regression (REG), regression plus noise (RPN), and two new methods, maintenance of variance extension types 1 and 2 (MOVE.l, MOVE.2). MOVE.l is equivalent to a method which is widely used in psychology, biometrics, and geomorphology and which has been called by various names, e.g., `line of organic correlation,' `reduced major axis,' `unique solution,' and `equivalence line.' The methods are examined for bias and standard error of estimate of moments and order statistics, and an empirical examination is made of the preservation of historic low-flow characteristics using 50-year-long monthly records from seven streams. The REG and RPN methods are shown to have serious deficiencies as record extension techniques. MOVE.2 is shown to be marginally better than MOVE.l, according to the various comparisons of bias and accuracy.

Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

2016-12-01

In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

Manipulating Environmental Time Series in Python/Numpy: the Scikits.Timeseries Package and its Applications.

NASA Astrophysics Data System (ADS)

Gerard-Marchant, P. G.

2008-12-01

Numpy is a free, open source C/Python interface designed for the fast and convenient manipulation of multidimensional numerical arrays. The base object, ndarray, can also be easily be extended to define new objects meeting specific needs. Thanks to its simplicity, efficiency and modularity, numpy and its companion library Scipy have become increasingly popular in the scientific community over the last few years, with application ranging from astronomy and engineering to finances and statistics. Its capacity to handle missing values is particularly appealing when analyzing environmental time series, where irregular data sampling might be an issue. After reviewing the main characteristics of numpy objects and the mechanism of subclassing, we will present the scikits.timeseries package, developed to manipulate single- and multi-variable arrays indexed in time. We will illustrate some typical applications of this package by introducing climpy, a set of extensions designed to help analyzing the impacts of climate variability on environmental data such as precipitations or streamflows.

Improving the performance of streamflow forecasting model using data-preprocessing technique in Dungun River Basin

NASA Astrophysics Data System (ADS)

Khai Tiu, Ervin Shan; Huang, Yuk Feng; Ling, Lloyd

2018-03-01

An accurate streamflow forecasting model is important for the development of flood mitigation plan as to ensure sustainable development for a river basin. This study adopted Variational Mode Decomposition (VMD) data-preprocessing technique to process and denoise the rainfall data before putting into the Support Vector Machine (SVM) streamflow forecasting model in order to improve the performance of the selected model. Rainfall data and river water level data for the period of 1996-2016 were used for this purpose. Homogeneity tests (Standard Normal Homogeneity Test, the Buishand Range Test, the Pettitt Test and the Von Neumann Ratio Test) and normality tests (Shapiro-Wilk Test, Anderson-Darling Test, Lilliefors Test and Jarque-Bera Test) had been carried out on the rainfall series. Homogenous and non-normally distributed data were found in all the stations, respectively. From the recorded rainfall data, it was observed that Dungun River Basin possessed higher monthly rainfall from November to February, which was during the Northeast Monsoon. Thus, the monthly and seasonal rainfall series of this monsoon would be the main focus for this research as floods usually happen during the Northeast Monsoon period. The predicted water levels from SVM model were assessed with the observed water level using non-parametric statistical tests (Biased Method, Kendall's Tau B Test and Spearman's Rho Test).

Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection

USGS Publications Warehouse

Poole, Sandra; Vis, Marc; Knight, Rodney; Seibert, Jan

2017-01-01

Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.

Computing Real-time Streamflow Using Emerging Technologies: Non-contact Radars and the Probability Concept

NASA Astrophysics Data System (ADS)

Fulton, J. W.; Bjerklie, D. M.; Jones, J. W.; Minear, J. T.

2015-12-01

Measuring streamflow, developing, and maintaining rating curves at new streamgaging stations is both time-consuming and problematic. Hydro 21 was an initiative by the U.S. Geological Survey to provide vision and leadership to identify and evaluate new technologies and methods that had the potential to change the way in which streamgaging is conducted. Since 2014, additional trials have been conducted to evaluate some of the methods promoted by the Hydro 21 Committee. Emerging technologies such as continuous-wave radars and computationally-efficient methods such as the Probability Concept require significantly less field time, promote real-time velocity and streamflow measurements, and apply to unsteady flow conditions such as looped ratings and unsteady-flood flows. Portable and fixed-mount radars have advanced beyond the development phase, are cost effective, and readily available in the marketplace. The Probability Concept is based on an alternative velocity-distribution equation developed by C.-L. Chiu, who pioneered the concept. By measuring the surface-water velocity and correcting for environmental influences such as wind drift, radars offer a reliable alternative for measuring and computing real-time streamflow for a variety of hydraulic conditions. If successful, these tools may allow us to establish ratings more efficiently, assess unsteady flow conditions, and report real-time streamflow at new streamgaging stations.

Uncertainty estimation with bias-correction for flow series based on rating curve

NASA Astrophysics Data System (ADS)

Shao, Quanxi; Lerat, Julien; Podger, Geoff; Dutta, Dushmanta

2014-03-01

Streamflow discharge constitutes one of the fundamental data required to perform water balance studies and develop hydrological models. A rating curve, designed based on a series of concurrent stage and discharge measurements at a gauging location, provides a way to generate complete discharge time series with a reasonable quality if sufficient measurement points are available. However, the associated uncertainty is frequently not available even though it has a significant impact on hydrological modelling. In this paper, we identify the discrepancy of the hydrographers' rating curves used to derive the historical discharge data series and proposed a modification by bias correction which is also in the form of power function as the traditional rating curve. In order to obtain the uncertainty estimation, we propose a further both-side Box-Cox transformation to stabilize the regression residuals as close to the normal distribution as possible, so that a proper uncertainty can be attached for the whole discharge series in the ensemble generation. We demonstrate the proposed method by applying it to the gauging stations in the Flinders and Gilbert rivers in north-west Queensland, Australia.

Predicting streamflow regime metrics for ungauged streamsin Colorado, Washington, and Oregon

NASA Astrophysics Data System (ADS)

Sanborn, Stephen C.; Bledsoe, Brian P.

2006-06-01

Streamflow prediction in ungauged basins provides essential information for water resources planning and management and ecohydrological studies yet remains a fundamental challenge to the hydrological sciences. A methodology is presented for stratifying streamflow regimes of gauged locations, classifying the regimes of ungauged streams, and developing models for predicting a suite of ecologically pertinent streamflow metrics for these streams. Eighty-four streamflow metrics characterizing various flow regime attributes were computed along with physical and climatic drainage basin characteristics for 150 streams with little or no streamflow modification in Colorado, Washington, and Oregon. The diverse hydroclimatology of the study area necessitates flow regime stratification and geographically independent clusters were identified and used to develop separate predictive models for each flow regime type. Multiple regression models for flow magnitude, timing, and rate of change metrics were quite accurate with many adjusted R2 values exceeding 0.80, while models describing streamflow variability did not perform as well. Separate stratification schemes for high, low, and average flows did not considerably improve models for metrics describing those particular aspects of the regime over a scheme based on the entire flow regime. Models for streams identified as 'snowmelt' type were improved if sites in Colorado and the Pacific Northwest were separated to better stratify the processes driving streamflow in these regions thus revealing limitations of geographically independent streamflow clusters. This study demonstrates that a broad suite of ecologically relevant streamflow characteristics can be accurately modeled across large heterogeneous regions using this framework. Applications of the resulting models include stratifying biomonitoring sites and quantifying linkages between specific aspects of flow regimes and aquatic community structure. In particular, the results bode well for modeling ecological processes related to high-flow magnitude, timing, and rate of change such as the recruitment of fish and riparian vegetation across large regions.

A Winter Precipitation Reconstruction (CE 1810-2012) in the Southeastern Tibetan Plateau and Its Relationship to Salween River Streamflow Variations

NASA Astrophysics Data System (ADS)

Chen, Feng; Yuan, Yujiang; Fan, Zexin; Yu, Shulong

2018-01-01

We established a tree-ring width series from one Yunnan Douglas fir (Pseudotsuga forrestii) stand near the Mingyong glacier terminus of Meili Snow Mountain, southeastern Tibetan Plateau. Correlation analyses indicated that radial growth of Yunnan Douglas firs is largely controlled by variations in winter (November-March) precipitation. The precipitation reconstruction model accounts for 37% of the actual precipitation variance during the common period 1954-2012. Spatial correlations with the gridded precipitation data reveal that the winter precipitation reconstruction represents regional precipitation changes over the southeastern Tibetan Plateau. By comparing our results with other regional tree-ring records, a distinctive amount of common dry and humid periods were found. Our winter precipitation reconstruction shows profound similarities with Salween river streamflow signals as well as regional glacial activity. Cross-wavelet analysis reveals solar and ENSO influences on precipitation and streamflow variations in the southeastern Tibetan Plateau.

Streamflow monitoring and statistics for development of water rights claims for Wild and Scenic Rivers, Owyhee Canyonlands Wilderness, Idaho, 2012

USGS Publications Warehouse

Wood, Molly S.; Fosness, Ryan L.

2013-01-01

The U.S. Geological Survey, in cooperation with the Bureau of Land Management (BLM), collected streamflow data in 2012 and estimated streamflow statistics for stream segments designated "Wild," "Scenic," or "Recreational" under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. The streamflow statistics were used by BLM to develop and file a draft, federal reserved water right claim in autumn 2012 to protect federally designated "outstanding remarkable values" in the stream segments. BLM determined that the daily mean streamflow equaled or exceeded 20 and 80 percent of the time during bimonthly periods (two periods per month) and the bankfull streamflow are important streamflow thresholds for maintaining outstanding remarkable values. Prior to this study, streamflow statistics estimated using available datasets and tools for the Owyhee Canyonlands Wilderness were inaccurate for use in the water rights claim. Streamflow measurements were made at varying intervals during February–September 2012 at 14 monitoring sites; 2 of the monitoring sites were equipped with telemetered streamgaging equipment. Synthetic streamflow records were created for 11 of the 14 monitoring sites using a partial‑record method or a drainage-area-ratio method. Streamflow records were obtained directly from an operating, long-term streamgage at one monitoring site, and from discontinued streamgages at two monitoring sites. For 10 sites analyzed using the partial-record method, discrete measurements were related to daily mean streamflow at a nearby, telemetered “index” streamgage. Resulting regression equations were used to estimate daily mean and annual peak streamflow at the monitoring sites during the full period of record for the index sites. A synthetic streamflow record for Sheep Creek was developed using a drainage-area-ratio method, because measured streamflows did not relate well to any index site to allow use of the partial-record method. The synthetic and actual daily mean streamflow records were used to estimate daily mean streamflow that was exceeded 80, 50, and 20 percent of the time (80-, 50-, and 20-percent exceedances) for bimonthly and annual periods. Bankfull streamflow statistics were calculated by fitting the synthetic and actual annual peak streamflow records to a log Pearson Type III distribution using Bulletin 17B guidelines in the U.S. Geological Survey PeakFQ program. The coefficients of determination (R2) for the regressions between the monitoring and index sites ranged from 0.74 for Wickahoney Creek to 0.98 for the West Fork Bruneau River and Deep Creek. Confidence in computed streamflow statistics is highest among other sites for the East Fork Owyhee River and the West Fork Bruneau River on the basis of regression statistics, visual fit of the related data, and the range and number of streamflow measurements. Streamflow statistics for sites with the greatest uncertainty included Big Jacks, Little Jacks, Cottonwood, Wickahoney, and Sheep Creeks. The uncertainty in computed streamflow statistics was due to a number of factors which included the distance of index sites relative to monitoring sites, relatively low streamflow conditions that occurred during the study, and the limited number and range of streamflow measurements. However, the computed streamflow statistics are considered the best possible estimates given available datasets in the remote study area. Streamflow measurements over a wider range of hydrologic and climatic conditions would improve the relations between streamflow characteristics at monitoring and index sites. Additionally, field surveys are needed to verify if the streamflows selected for the water rights claims are sufficient for maintaining outstanding remarkable values in the Wild and Scenic rivers included in the study.

Trends in streamflow of the San Pedro River, southeastern Arizona, and regional trends in precipitation and streamflow in southeastern Arizona and southwestern New Mexico

USGS Publications Warehouse

Thomas, Blakemore E.; Pool, Don R.

2006-01-01

This study was done to improve the understanding of trends in streamflow of the San Pedro River in southeastern Arizona. Annual streamflow of the river at Charleston, Arizona, has decreased by more than 50 percent during the 20th century. The San Pedro River is one of the few remaining free-flowing perennial streams in the arid Southwestern United States, and the riparian forest along the river supports several endangered species and is an important habitat for migratory birds. Trends in seasonal and annual precipitation and streamflow were evaluated for surrounding areas in southeastern Arizona and southwestern New Mexico to provide a regional perspective for the trends of the San Pedro River. Seasonal and annual streamflow trends and the relation between precipitation and streamflow in the San Pedro River Basin were evaluated to improve the understanding of the causes of trends. There were few significant trends in seasonal and annual precipitation or streamflow for the regional study area. Precipitation and streamflow records were analyzed for 11 time periods ranging from 1930 to 2002; no significant trends were found in 92 percent of the trend tests for precipitation, and no significant trends were found in 79 percent of the trend tests for streamflow. For the trends in precipitation that were significant, 90 percent were positive and most of those positive trends were in records of winter, spring, or annual precipitation that started during the mid-century drought in 1945-60. For the trends in streamflow that were significant, about half were positive and half were negative. Trends in precipitation in the San Pedro River Basin were similar to regional precipitation trends for spring and fall values and were different for summer and annual values. The largest difference was in annual precipitation, for which no trend tests were significant in the San Pedro River Basin, and 23 percent of the trend tests were significantly positive in the rest of the study area. Streamflow trends for the San Pedro River were different from regional streamflow trends. All seasonal flows for the San Pedro River, except winter flows, had significant decreasing trends, and seasonal flows for most streams in the rest of the study area had either no trend or a significant increasing trend. Two streams adjacent to the San Pedro River Basin (Whitewater Draw and Santa Cruz River), however, had significant decreasing trends in summer streamflow. Factors that caused the decreasing trends in streamflow of the San Pedro River at Charleston were investigated. Possible factors were fluctuations in precipitation and air temperature, changes in watershed characteristics, human activities, or changes in seasonal distribution of bank storage. This study statistically removed or accounted for the variation in streamflow caused by fluctuations in precipitation. Thus, the remaining variation or trend in streamflow was caused by factors other than precipitation. Two methods were used to partition the variation in streamflow and to determine trends in the partitioned variation: (1) regression analysis between precipitation and streamflow using all years in the record and evaluation of time trends in regression residuals, and (2) development of regression equations between precipitation and streamflow for three time periods (early, middle, and late parts of the record) and testing to determine if the three regression equations were significantly different. The methods were applied to monthly values of total flow (average flow) and storm runoff (maximum daily mean flow) for 1913-2002, and to monthly values of low flow (3-day low flow) for 1931-2002. Statistical tests provide strong evidence that factors other than precipitation caused a decrease in streamflow of the San Pedro River. Factors other than precipitation caused significant decreasing trends in streamflows for late spring through early winter and did not cause significant trends f

Streamflow gain-loss characteristics of Elkhead Creek downstream from Elkhead Reservoir near Craig, Colorado, 2009

USGS Publications Warehouse

Ruddy, Barbara C.

2010-01-01

The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board, the Upper Colorado River Endangered Fish Recovery Program (UCREFRP), Colorado Division of Water Resources, and City of Craig studied the gain-loss characteristics of Elkhead Creek downstream from Elkhead Reservoir to the confluence with the Yampa River during August through October 2009. Earlier qualitative interpretation of streamflow data downstream from the reservoir indicated that there could be a transit loss of nearly 10 percent. This potential loss could be a significant portion of the releases from Elkhead Reservoir requested by UCREFRP during late summer and early fall for improving critical habitat for endangered fish downstream in the Yampa River. Information on the gain-loss characteristics was needed for the effective management of the reservoir releases. In order to determine streamflow gain-loss characteristics for Elkhead Creek, eight measurement sets were made at four strategic instream sites and at one diversion from August to early October 2009. An additional measurement set was made after the study period during low-flow conditions in November 2009. Streamflow measurements were made using an Acoustic Doppler Velocimeter to provide high accuracy and consistency, especially at low flows. During this study, streamflow ranged from about 5 cubic feet per second up to more than 90 cubic feet per second with step increments in between. Measurements were made at least 24 hours after a change in reservoir release (streamflow) during steady-state conditions. The instantaneous streamflow measurements and the streamflow volume comparisons show the reach of Elkhead Creek immediately downstream from Elkhead Reservoir to the streamflow-gaging station 09246500, Elkhead Creek near Craig, CO, is neither a gaining nor losing reach. The instantaneous measurements immediately downstream from the dam and the combined measurements of Norvell ditch plus streamflow-gaging station 09246500 are mostly within the plus or minus 5-percent measurement error of each other. The variability of data is such that sometimes the streamflow is greater upstream than downstream and sometimes the streamflow is greater downstream than upstream. Streamflow volumes were calculated for multiple time periods as determined by a change in release from the reservoir. Streamflow volumes were greater downstream than upstream for all but one time period. The predominance of greater streamflows downstream is due to the difference between the USGS instantaneous measurements and record computation with the Supervisory Control and Data Acquisition (SCADA) record at the dam. Immediately following an increase in streamflow from the reservoir, the downstream volume was smaller than the upstream volume, but this was an artifact of the traveltime between the two sites and possibly small amounts of water entering the streambank. Traveltimes were shorter at higher streamflows and when streamflow was increasing.

Mississippi River streamflow measurement techniques at St. Louis, Missouri

USGS Publications Warehouse

Wastson, Chester C.; Holmes, Robert R.; Biedenham, David S.

2013-01-01

Streamflow measurement techniques of the Mississippi River at St. Louis have changed through time (1866–present). In addition to different methods used for discrete streamflow measurements, the density and range of discrete measurements used to define the rating curve (stage versus streamflow) have also changed. Several authors have utilized published water surface elevation (stage) and streamflow data to assess changes in the rating curve, which may be attributed to be caused by flood control and/or navigation structures. The purpose of this paper is to provide a thorough review of the available flow measurement data and techniques and to assess how a strict awareness of the limitations of the data may affect previous analyses. It is concluded that the pre-1930s discrete streamflow measurement data are not of sufficient accuracy to be compared with modern streamflow values in establishing long-term trends of river behavior.

Streamflow Modification Through Management of Eastern Forests

Treesearch

James E. Douglass; Wayne T. Swank

1972-01-01

Protection of the water resource was a primary objective in establishing the National Forest System in America, and improving quantity, quality, and timing of streamflow is an important objective of forest management in certain regions of the United States.Effective management of the forest for increased streamflow presupposes that impact of various management...

Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system

USGS Publications Warehouse

Bera, Maitreyee; Ortel, Terry W.

2018-01-12

The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.

Precipitation and streamflow data from the Fort Carson Military Reservation and precipitation, streamflow, and suspended-sediment data from the Piñon Canyon Maneuver Site, Southeastern Colorado, 2008-2012

USGS Publications Warehouse

Brown, Christopher R.

2014-01-01

In 2013, the U.S. Geological Survey (USGS), in cooperation with the U. S. Department of the Army, compiled available precipitation and streamflow data for the years of 2008–2012 from the Fort Carson Military Reservation (Fort Carson) near Colorado Springs, Colo., and precipitation, streamflow, and suspended-sediment loads from the Piñon Canyon Maneuver Site (PCMS) near Trinidad, Colo. Graphical representations of the data presented herein are a continuation of work completed by the USGS in 2008 to gain a better understanding of spatial and temporal trends within the hydrologic data. Precipitation stations at Fort Carson and the PCMS were divided into groups based on their land-surface altitude (LSA) to determine if there is a spatial difference in precipitation amounts based on LSA for either military facility. Two-sample t-tests and Wilcoxon rank-sum tests indicated statistically significant differences exist between precipitation values at different groups for Fort Carson but not for the PCMS. All five precipitation stations at Fort Carson exhibit a decrease in median daily total precipitation from years 2002–2007 to 2008–2012. For the PCMS, median precipitation values decreased from the first study period to the second for the 13 stations monitored year-round except for Burson and Big Hills. Mean streamflow for 2008–2012 is less than mean streamflow for 1983–2007 for all stream-gaging stations at Fort Carson and at the PCMS. During the study period, each of the stream-gaging stations within the tributary channels at the PCMS accounted for less than three percent of the total streamflow at the Purgatoire River at Rock Crossing gage. Peak streamflow for 2008–2012 is less than peak streamflow for 2002–2007 at both Fort Carson and the PCMS. At the PCMS, mean suspended-sediment yield for 2008–2012 increased by 54 percent in comparison to the mean yield for 2002–2007. This increase is likely related to the destruction of groundcover by a series of wildfires within the PCMS in 2008 and 2011.

Regime Behavior in Paleo-Reconstructed Streamflow: Attributions to Atmospheric Dynamics, Synoptic Circulation and Large-Scale Climate Teleconnection Patterns

NASA Astrophysics Data System (ADS)

Ravindranath, A.; Devineni, N.

2017-12-01

Studies have shown that streamflow behavior and dynamics have a significant link with climate and climate variability. Patterns of persistent regime behavior from extended streamflow records in many watersheds justify investigating large-scale climate mechanisms as potential drivers of hydrologic regime behavior and streamflow variability. Understanding such streamflow-climate relationships is crucial to forecasting/simulation systems and the planning and management of water resources. In this study, hidden Markov models are used with reconstructed streamflow to detect regime-like behaviors - the hidden states - and state transition phenomena. Individual extreme events and their spatial variability across the basin are then verified with the identified states. Wavelet analysis is performed to examine the signals over time in the streamflow records. Joint analyses of the climatic data in the 20th century and the identified states are undertaken to better understand the hydroclimatic connections within the basin as well as important teleconnections that influence water supply. Compositing techniques are used to identify atmospheric circulation patterns associated with identified states of streamflow. The grouping of such synoptic patterns and their frequency are then examined. Sliding time-window correlation analysis and cross-wavelet spectral analysis are performed to establish the synchronicity of basin flows to the identified synoptic and teleconnection patterns. The Missouri River Basin (MRB) is examined in this study, both as a means of better understanding the synoptic climate controls in this important watershed and as a case study for the techniques developed here. Initial wavelet analyses of reconstructed streamflow at major gauges in the MRB show multidecadal cycles in regime behavior.

Ground-water/surface-water relations along Honey Creek, Washtenaw County, Michigan, 2003

USGS Publications Warehouse

Healy, Denis F.

2005-01-01

The U.S. Geological Survey (USGS), in cooperation with the city of Ann Arbor, Mich., investigated the ground-water/ surface-water relations along the lower reaches of Honey Creek, Washtenaw County, Mich., and an unnamed tributary to Honey Creek (the discharge tributary) from June through October 2003. Streamflow in these reaches was artificially high during a naturally low-flow period due to an anthropogenic discharge. Ground-water/surface-water relations were examined by seepage runs (series of streamflow measurements for the computation of streams gains or losses) and measurements of the difference in head between the stream surface and shallow aquifer. Specific conductance and water-temperature measurements were used as ancillary data to help identify gaining and losing reaches. Three seepage runs and four runs in which hydraulic-head differences between the stream and shallow aquifer were measured (piezometer runs) were made during periods of base flow. Streamflow measurements were made at 18 sites for the seepage runs. Instream piezometers were installed at 16 sites and bank piezometers were installed at 2 sites. Two deeper instream piezometers were installed at site 13 on September 4, 2003 to collect additional data on the ground-water/surface-water relations at that site. The seepage runs indicate that the main stem of Honey Creek and the discharge tributary in the study area are overall gaining reaches. The seepage runs also indicate that smaller reaches of Honey Creek and the discharge tributary may be losing reaches and that this relation may change over time with changing hydraulic conditions. The piezometer-run measurements support the seepage-run results on the main stem, whereas piezometer-run measurements both support and conflict with seepage-run measurements on the discharge tributary. Seepage runs give an average for the reach, whereas piezometer head-difference measurements are for a specific area around the piezometer. Data that may appear to be conflicting actually may be showing that within a gaining reach there are localized areas that lose streamflow. The overall gain in streamflow along with specific measurements of head differences, specific conductance, and water temperature indicate that ground water is discharging to Honey Creek and the discharge tributary. Although reaches and areas that lose streamflow have been identified, data collected during this study cannot confirm or disprove that the loss is to the regional ground-water system.

Improving Streamflow Forecasts Using Predefined Sea Surface Temperature

NASA Astrophysics Data System (ADS)

Kalra, A.; Ahmad, S.

2011-12-01

With the increasing evidence of climate variability, water resources managers in the western United States are faced with greater challenges of developing long range streamflow forecast. This is further aggravated by the increases in climate extremes such as floods and drought caused by climate variability. Over the years, climatologists have identified several modes of climatic variability and their relationship with streamflow. These climate modes have the potential of being used as predictor in models for improving the streamflow lead time. With this as the motivation, the current research focuses on increasing the streamflow lead time using predefine climate indices. A data driven model i.e. Support Vector Machine (SVM) based on the statistical learning theory is used to predict annual streamflow volume 3-year in advance. The SVM model is a learning system that uses a hypothesis space of linear functions in a Kernel induced higher dimensional feature space, and is trained with a learning algorithm from the optimization theory. Annual oceanic-atmospheric indices, comprising of Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), El Niño-Southern Oscillations (ENSO), and a new Sea Surface Temperature (SST) data set of "Hondo" Region for a period of 1906-2005 are used to generate annual streamflow volumes. The SVM model is applied to three gages i.e. Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the western United States. Based on the performance measures the model shows very good forecasts, and the forecast are in good agreement with measured streamflow volumes. Previous research has identified NAO and ENSO as main drivers for extending streamflow forecast lead-time in the UCRB. Inclusion of "Hondo Region" SST information further improve the model's forecasting ability. The overall results of this study revealed that the annual streamflow of the UCRB is significantly influenced by predefine climate modes and the proposed SVM modeling technique incorporating oceanic-atmospheric oscillations is expected to be useful to water managers in the long-term management of the water resources within the UCRB.

PERIODIC AUTOREGRESSIVE-MOVING AVERAGE (PARMA) MODELING WITH APPLICATIONS TO WATER RESOURCES.

USGS Publications Warehouse

Vecchia, A.V.

1985-01-01

Results involving correlation properties and parameter estimation for autogressive-moving average models with periodic parameters are presented. A multivariate representation of the PARMA model is used to derive parameter space restrictions and difference equations for the periodic autocorrelations. Close approximation to the likelihood function for Gaussian PARMA processes results in efficient maximum-likelihood estimation procedures. Terms in the Fourier expansion of the parameters are sequentially included, and a selection criterion is given for determining the optimal number of harmonics to be included. Application of the techniques is demonstrated through analysis of a monthly streamflow time series.

Deep groundwater mediates streamflow response to climate warming in the Oregon Cascades

Treesearch

Christina Tague; Gordon Grant; Mike Farrell; Janet Choate; Anne Jefferson

2008-01-01

Recent studies predict that projected climate change will lead to significant reductions in summer streamflow in the mountainous regions of the Western United States. Hydrologic modeling directed at quantifying these potential changes has focused on the magnitude and timing of spring snowmelt as the key control on the spatial temporal pattern of summer streamflow. We...

Using oceanic-atmospheric oscillations for long lead time streamflow forecasting

NASA Astrophysics Data System (ADS)

Kalra, Ajay; Ahmad, Sajjad

2009-03-01

We present a data-driven model, Support Vector Machine (SVM), for long lead time streamflow forecasting using oceanic-atmospheric oscillations. The SVM is based on statistical learning theory that uses a hypothesis space of linear functions based on Kernel approach and has been used to predict a quantity forward in time on the basis of training from past data. The strength of SVM lies in minimizing the empirical classification error and maximizing the geometric margin by solving inverse problem. The SVM model is applied to three gages, i.e., Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the western United States. Annual oceanic-atmospheric indices, comprising Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and El Nino-Southern Oscillations (ENSO) for a period of 1906-2001 are used to generate annual streamflow volumes with 3 years lead time. The SVM model is trained with 86 years of data (1906-1991) and tested with 10 years of data (1992-2001). On the basis of correlation coefficient, root means square error, and Nash Sutcliffe Efficiency Coefficient the model shows satisfactory results, and the predictions are in good agreement with measured streamflow volumes. Sensitivity analysis, performed to evaluate the effect of individual and coupled oscillations, reveals a strong signal for ENSO and NAO indices as compared to PDO and AMO indices for the long lead time streamflow forecast. Streamflow predictions from the SVM model are found to be better when compared with the predictions obtained from feedforward back propagation artificial neural network model and linear regression.

Preliminary assessment of streamflow characteristics for selected streams at Fort Gordon, Georgia, 1999-2000

USGS Publications Warehouse

Stamey, Timothy C.

2001-01-01

In 1999, the U.S. Geological Survey, in cooperation with the U.S. Army Signal Center and Fort Gordon, began collection of periodic streamflow data at four streams on the military base to assess and estimate streamflow characteristics of those streams for potential water-supply sources. Simple and reliable methods of determining streamflow characteristics of selected streams on the military base are needed for the initial implementation of the Fort Gordon Integrated Natural Resources Management Plan. Long-term streamflow data from the Butler Creek streamflow gaging station were used along with several concurrent discharge measurements made at three selected partial-record streamflow stations on Fort Gordon to determine selected low-flow streamflow characteristics. Streamflow data were collected and analyzed using standard U.S. Geological Survey methods and computer application programs to verify the use of simple drainage area to discharge ratios, which were used to estimate the low-flow characteristics for the selected streams. Low-flow data computed based on daily mean streamflow include: mean discharges for consecutive 1-, 3-, 7-, 14-, and 30-day period and low-flow estimates of 7Q10, 30Q2, 60Q2, and 90Q2 recurrence intervals. Flow-duration data also were determined for the 10-, 30-, 50-, 70-, and 90-percent exceedence flows. Preliminary analyses of the streamflow indicate that the flow duration and selected low-flow statistics for the selected streams averages from about 0.15 to 2.27 cubic feet per square mile. The long-term gaged streamflow data indicate that the streamflow conditions for the period analyzed were in the 50- to 90-percent flow range, or in which streamflow would be exceeded about 50 to 90 percent of the time.

Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal adjustment scale

NASA Astrophysics Data System (ADS)

Lee, H.; Seo, D.-J.; Liu, Y.; Koren, V.; McKee, P.; Corby, R.

2012-01-01

State updating of distributed rainfall-runoff models via streamflow assimilation is subject to overfitting because large dimensionality of the state space of the model may render the assimilation problem seriously under-determined. To examine the issue in the context of operational hydrology, we carry out a set of real-world experiments in which streamflow data is assimilated into gridded Sacramento Soil Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM) with the variational data assimilation technique. Study basins include four basins in Oklahoma and five basins in Texas. To assess the sensitivity of data assimilation performance to dimensionality reduction in the control vector, we used nine different spatiotemporal adjustment scales, where state variables are adjusted in a lumped, semi-distributed, or distributed fashion and biases in precipitation and potential evaporation (PE) are adjusted hourly, 6-hourly, or kept time-invariant. For each adjustment scale, three different streamflow assimilation scenarios are explored, where streamflow observations at basin interior points, at the basin outlet, or at both interior points and the outlet are assimilated. The streamflow assimilation experiments with nine different basins show that the optimum spatiotemporal adjustment scale varies from one basin to another and may be different for streamflow analysis and prediction in all of the three streamflow assimilation scenarios. The most preferred adjustment scale for seven out of nine basins is found to be the distributed, hourly scale, despite the fact that several independent validation results at this adjustment scale indicated the occurrence of overfitting. Basins with highly correlated interior and outlet flows tend to be less sensitive to the adjustment scale and could benefit more from streamflow assimilation. In comparison to outlet flow assimilation, interior flow assimilation at any adjustment scale produces streamflow predictions with a spatial correlation structure more consistent with that of streamflow observations. We also describe diagnosing the complexity of the assimilation problem using the spatial correlation information associated with the streamflow process, and discuss the effect of timing errors in a simulated hydrograph on the performance of the data assimilation procedure.

Contribution of human and climate change impacts to changes in streamflow of Canada.

PubMed

Tan, Xuezhi; Gan, Thian Yew

2015-12-04

Climate change exerts great influence on streamflow by changing precipitation, temperature, snowpack and potential evapotranspiration (PET), while human activities in a watershed can directly alter the runoff production and indirectly through affecting climatic variables. However, to separate contribution of anthropogenic and natural drivers to observed changes in streamflow is non-trivial. Here we estimated the direct influence of human activities and climate change effect to changes of the mean annual streamflow (MAS) of 96 Canadian watersheds based on the elasticity of streamflow in relation to precipitation, PET and human impacts such as land use and cover change. Elasticities of streamflow for each watershed are analytically derived using the Budyko Framework. We found that climate change generally caused an increase in MAS, while human impacts generally a decrease in MAS and such impact tends to become more severe with time, even though there are exceptions. Higher proportions of human contribution, compared to that of climate change contribution, resulted in generally decreased streamflow of Canada observed in recent decades. Furthermore, if without contributions from retreating glaciers to streamflow, human impact would have resulted in a more severe decrease in Canadian streamflow.

Compilation of regional ground water monitoring data to investigate 60 years of ground water dynamics in New England

NASA Astrophysics Data System (ADS)

Boutt, D. F.; Weider, K. M.

2010-12-01

Theory suggests that ground water systems at shallow depths are sensitive to climate system dynamics but respond at differing rates due to primarily hydrogeologic characteristics of the aquifer. These rates are presumably to a first order controlled by the transmissivity and hydrogeologic settings of aquifer systems. Regional scale modeling and understanding of the impact of this behavior is complicated by the fact that aquifer systems in glaciated regions of the North American continent often possess high degrees of heterogeneity as well as disparate hydraulic connections between aquifer systems. In order to investigate these relationships we present the results of a regional compilation of groundwater hydraulic head data across the New England states together with corresponding atmospheric (precipitation and temperature) and streamflow data for a 60 year period (1950-2010). Ground water trends are calculated as normalized anomalies, and analyzed with respect to regional compiled precipitation, temperature, and streamflow. Anomalies in ground water levels are analyzed together with hydrogeologic variables such as aquifer thickness, topographic setting, and distance from coast. The time-series display decadal patterns with ground water levels being highly variable and lagging that of precipitation and streamflow pointing to site specific and non-linear response to changes in climate. Sites with deeper water tables respond slower and with larger anomalies compared to shallow water table sites. Tills consistently respond quicker and have larger anomalies compared to outwash and stratified glacial deposits. The data set suggests that while regional patterns in ground water table response are internally consistent, the magnitude and timing of the response to wet or dry periods is extremely sensitive to hydrogeologic characteristics of the host aquifer.

Temporal changes in aquatic-invertebrate and fish assemblages in streams of the north-central and northeastern U.S.

USGS Publications Warehouse

Kennen, Jonathan G.; Sullivan, Daniel J.; May, Jason T.; Bell, Amanda H.; Beaulieu, Karen M.; Rice, Donald E.

2012-01-01

Many management agencies seek to evaluate temporal changes in aquatic assemblages at monitoring sites, but few have sites with ecological time series that are long enough for this purpose. Trends in aquatic-invertebrate and fish assemblage composition were assessed at 27 long-term monitoring sites in the north-central and northeastern United States. Temporal changes were identified using serial trend analysis. Sites with significant serial trends were further evaluated by relating explanatory environmental variables (e.g., streamflow, habitat, and water chemistry) to changes in assemblage composition. Significant trends were found at 19 of 27 study sites; however, differences in the sensitivity of the aquatic fauna to environmental stressors were identified. For example, significant trends in fish assemblages were found at more sites (15 of 27) than for aquatic-invertebrate assemblages (10 of 27 sites). In addition, trends in the invertebrate assemblage were most often explained by changes in streamflow processes (e.g., duration and magnitude of low- and high-flows, streamflow variability, and annual rates of change), whereas trends in the fish assemblage were more related to changes in water chemistry. Results illustrate the value of long-term monitoring for the purpose of assessing temporal trends in aquatic assemblages. The ability to detect trends in assemblage composition and to attribute these changes to environmental factors is necessary to understand mechanistic pathways and to further our understanding of how incremental anthropogenic alterations modify aquatic assemblages over time. Finally, this study's approach to trends analysis can be used to better inform the design of monitoring programs as well as support the ongoing management needs of stakeholders, water-resource agencies, and policy makers.

Understanding drought propagation in the UK in the context of climatology and catchment properties

NASA Astrophysics Data System (ADS)

Barker, Lucy; Hannaford, Jamie; Bloomfield, John; Marchant, Ben

2017-04-01

Droughts are a complex natural phenomena that are challenging to plan and prepare for. The propagation of droughts through the hydrological cycle is one of many factors which contribute to this complexity, and a thorough understanding of drought propagation is crucial for informed drought management, particularly in terms of water resources management in both the short and long term. Previous studies have found that both climatological and catchment factors cause lags in drought propagation from meteorological to hydrological and hydrogeological droughts. There are strong gradients in both climatology and catchment properties across the UK. Catchments in the north and west of the UK are relatively impermeable, upland catchments with thin soils and receive the highest annual precipitation with relatively low mean annual temperatures. Conversely, in the south and east of the UK, characterised by higher mean temperatures and lower annual precipitation, catchments are underlain by a number of major aquifers (e.g. Chalk, limestone) and are typically associated with high baseflow rivers. Here we explore the effects of these gradients in climatology and catchments on the propagation of droughts. Using standardised drought indices (the Standardised Precipitation Index; the Standardised Streamflow Index; and the Standardised Groundwater Index) we analyse drought propagation characteristics for selected catchment-borehole pairs across the UK using reconstructed time series back to the 19th century. We investigate how the timing, nature and predictability of drought propagation changes across the UK, given gradients in climatology and catchment characteristics. We use probability of detection methods, usually used for forecast verification, to investigate how well precipitation and streamflow deficits predict deficits in streamflow and groundwater levels and how this varies across the UK.

Trends in selected streamflow statistics at 19 long-term streamflow-gaging stations indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico, 1922-2009

USGS Publications Warehouse

Barbie, Dana L.; Wehmeyer, Loren L.

2012-01-01

Trends in selected streamflow statistics during 1922-2009 were evaluated at 19 long-term streamflow-gaging stations considered indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico. The U.S. Geological Survey, in cooperation with the Texas Water Development Board, evaluated streamflow data from streamflow-gaging stations with more than 50 years of record that were active as of 2009. The outflows into Arkansas and Louisiana were represented by 3 streamflow-gaging stations, and outflows into the Gulf of Mexico, including Galveston Bay, were represented by 16 streamflow-gaging stations. Monotonic trend analyses were done using the following three streamflow statistics generated from daily mean values of streamflow: (1) annual mean daily discharge, (2) annual maximum daily discharge, and (3) annual minimum daily discharge. The trend analyses were based on the nonparametric Kendall's Tau test, which is useful for the detection of monotonic upward or downward trends with time. A total of 69 trend analyses by Kendall's Tau were computed - 19 periods of streamflow multiplied by the 3 streamflow statistics plus 12 additional trend analyses because the periods of record for 2 streamflow-gaging stations were divided into periods representing pre- and post-reservoir impoundment. Unless otherwise described, each trend analysis used the entire period of record for each streamflow-gaging station. The monotonic trend analysis detected 11 statistically significant downward trends, 37 instances of no trend, and 21 statistically significant upward trends. One general region studied, which seemingly has relatively more upward trends for many of the streamflow statistics analyzed, includes the rivers and associated creeks and bayous to Galveston Bay in the Houston metropolitan area. Lastly, the most western river basins considered (the Nueces and Rio Grande) had statistically significant downward trends for many of the streamflow statistics analyzed.

Assessment of the timing of daily peak streamflow during melt season in a snow dominated watershed

USDA-ARS?s Scientific Manuscript database

Previous studies have shown that gauge-observed daily streamflow peak times (DPT) during spring snowmelt can exhibit distinct temporal shifts through the season. These shifts have been attributed to three processes that affect the timing of snowmelt arrival: 1) melt flux translation through the snow...

Yosemite Hydroclimate Network: Distributed stream and atmospheric data for the Tuolumne River watershed and surroundings

NASA Astrophysics Data System (ADS)

Lundquist, Jessica D.; Roche, James W.; Forrester, Harrison; Moore, Courtney; Keenan, Eric; Perry, Gwyneth; Cristea, Nicoleta; Henn, Brian; Lapo, Karl; McGurk, Bruce; Cayan, Daniel R.; Dettinger, Michael D.

2016-09-01

Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002-2015, as well as a quality-controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970-2015. This paper describes data collected using low-visibility and low-impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.

Yosemite Hydroclimate Network: Distributed stream and atmospheric data for the Tuolumne River watershed and surroundings

USGS Publications Warehouse

Lundquist, Jessica D.; Roche, James W.; Forrester, Harrison; Moore, Courtney; Keenan, Eric; Perry, Gwyneth; Cristea, Nicoleta; Henn, Brian; Lapo, Karl; McGurk, Bruce; Cayan, Daniel R.; Dettinger, Michael D.

2016-01-01

Regions of complex topography and remote wilderness terrain have spatially varying patterns of temperature and streamflow, but due to inherent difficulties of access, are often very poorly sampled. Here we present a data set of distributed stream stage, streamflow, stream temperature, barometric pressure, and air temperature from the Tuolumne River Watershed in Yosemite National Park, Sierra Nevada, California, USA, for water years 2002–2015, as well as a quality-controlled hourly meteorological forcing time series for use in hydrologic modeling. We also provide snow data and daily inflow to the Hetch Hetchy Reservoir for 1970–2015. This paper describes data collected using low-visibility and low-impact installations for wilderness locations and can be used alone or as a critical supplement to ancillary data sets collected by cooperating agencies, referenced herein. This data set provides a unique opportunity to understand spatial patterns and scaling of hydroclimatic processes in complex terrain and can be used to evaluate downscaling techniques or distributed modeling. The paper also provides an example methodology and lessons learned in conducting hydroclimatic monitoring in remote wilderness.

Floods of January and February 1980 in California

USGS Publications Warehouse

Wahl, Kenneth L.; Crippen, John R.; Knott, J.M.

1980-01-01

During January and February 1980, storms caused substantial rises in streamflow throughout much of California. In mid-January flooding occurred in the foothills of the Sierra Nevada and in the central coast area. In late January and mid-February, high floodflows in streams in coastal southern California caused much damage and several deaths. The Tijuana River in northern Baja California (Mexico) and southern San Diego County flooded many square miles of lowlands as its flow during two separate flooding episodes exceeded all records. Most reservoirs in San Diego County spilled, several for the first time since their completion. Lake Elsinore, in eastern Riverside County, caused much damage to lakeside property as it filled to an elevation not reached since 1916. The February flooding in southern California was caused by a series of storms separated by short intervals. Some peaks of record were observed, and streamflow throughout the area remained high for a relatively long period. In many streams, the volumes of sustained flow for periods of 7 and 15 consecutive days were the greatest that have occurred during the period of record.

Spatial Correlation Of Streamflows: An Analytical Approach

NASA Astrophysics Data System (ADS)

Betterle, A.; Schirmer, M.; Botter, G.

2016-12-01

The interwoven space and time variability of climate and landscape properties results in complex and non-linear hydrological response of streamflow dynamics. Understanding how meteorologic and morphological characteristics of catchments affect similarity/dissimilarity of streamflow timeseries at their outlets represents a scientific challenge with application in water resources management, ecological studies and regionalization approaches aimed to predict streamflows in ungauged areas. In this study, we establish an analytical approach to estimate the spatial correlation of daily streamflows in two arbitrary locations within a given hydrologic district or river basin at seasonal and annual time scales. The method is based on a stochastic description of the coupled streamflow dynamics at the outlet of two catchments. The framework aims to express the correlation of daily streamflows at two locations along a river network as a function of a limited number of physical parameters characterizing the main underlying hydrological drivers, that include climate conditions, precipitation regime and catchment drainage rates. The proposed method portrays how heterogeneity of climate and landscape features affect the spatial variability of flow regimes along river systems. In particular, we show that frequency and intensity of synchronous effective rainfall events in the relevant contributing catchments are the main driver of the spatial correlation of daily discharge, whereas only pronounced differences in the drainage rate of the two basins bear a significant effect on the streamflow correlation. The topological arrangement of the two outlets also influences the underlying streamflow correlation, as we show that nested catchments tend to maximize the spatial correlation of flow regimes. The application of the method to a set of catchments in the South-Eastern US suggests the potential of the proposed tool for the characterization of spatial connections of flow regimes in the absence of discharge measurements.

Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting

NASA Astrophysics Data System (ADS)

Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.

2017-12-01

Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.

Potential predictability of a Colombian river flow

NASA Astrophysics Data System (ADS)

Córdoba-Machado, Samir; Palomino-Lemus, Reiner; Quishpe-Vásquez, César; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In this study the predictability of an important Colombian river (Cauca) has been analysed based on the use of climatic variables as potential predictors. Cauca River is considered one of the most important rivers of Colombia because its basin supports important productive activities related with the agriculture, such as the production of coffee or sugar. Potential relationships between the Cauca River seasonal streamflow anomalies and different climatic variables such as sea surface temperature (SST), precipitation (Pt), temperature over land (Tm) and soil water (Sw) have been analysed for the period 1949-2009. For this end, moving correlation analysis of 30 years have been carried out for lags from one to four seasons for the global SST, and from one to two seasons for South America Pt, Tm and Sw. Also, the stability of the significant correlations have been also studied, identifying the regions used as potential predictors of streamflow. Finally, in order to establish a prediction scheme based on the previous stable correlations, a Principal Component Analysis (PCA) applied on the potential predictor regions has been carried out in order to obtain a representative time series for each predictor field. Significant and stable correlations between the seasonal streamflow and the tropical Pacific SST (El Niño region) are found for lags from one to four (one-year) season. Additionally, some regions in the Indian and Atlantic Oceans also show significant and stable correlations at different lags, highlighting the importance that exerts the Atlantic SST on the hydrology of Colombia. Also significant and stable correlations are found with the Pt, Tm and Sw for some regions over South America, at lags of one and two seasons. The prediction of Cauca seasonal streamflow based on this scheme shows an acceptable skill and represents a relative improvement compared with the predictability obtained using the teleconnection indices associated with El Niño. Keywords: Streamflow, predictability, Cauca, Colombia. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

How soil moisture mediates the influence of transpiration on streamflow at hourly to interannual scales in a forested catchment

Treesearch

G.W. Moore; J.A. Jones; B.J. Bond

2011-01-01

The water balance equation dictates that streamflow may be reduced by transpiration. Yet temporal disequilibrium weakens the relationship between transpiration and streamflow in many cases where inputs and outputs are unbalanced. We address two critical knowledge barriers in ecohydrology with respect to time, scale dependence and lags. Study objectives were to...

Relation of nitrate concentrations to baseflow in the Raccoon River, Iowa

USGS Publications Warehouse

Schilling, K.E.; Lutz, D.S.

2004-01-01

Excessive nitrate-nitrogen (nitrate) export from the Raccoon River in west central Iowa is an environmental concern to downstream receptors. The 1972 to 2000 record of daily streamflow and the results from 981 nitrate measurements were examined to describe the relation of nitrate to streamflow in the Raccoon River. No long term trends in streamflow and nitrate concentrations were noted in the 28-year record. Strong seasonal patterns were evident in nitrate concentrations, with higher concentrations occurring in spring and fall. Nitrate concentrations were linearly related to streamflow at daily, monthly, seasonal, and annual time scales. At all time scales evaluated, the relation was improved when baseflow was used as the discharge variable instead of total streamflow. Nitrate concentrations were found to be highly stratified according to flow, but there was little relation of nitrate to streamflow within each flow range. Simple linear regression models developed to predict monthly mean nitrate concentrations explained as much as 76 percent of the variability in the monthly nitrate concentration data for 2001. Extrapolation of current nitrate baseflow relations to historical conditions in the Raccoon River revealed that increasing baseflow over the 20th century could account for a measurable increase in nitrate concentrations.

Real-time streamflow conditions

USGS Publications Warehouse

Graczyk, David J.; Gebert, Warren A.

1996-01-01

Would you like to know streamflow conditions before you go fishing in Wisconsin or in more distant locations? Real-time streamflow data throughout Wisconsin and the United States are available on the Internet from the U.S. Geological Survey. You can see if the stream you are interested in fishing is high due to recent rain or low because of an extended dry spell. Flow conditions at more than 100 stream-gaging stations located throughout Wisconsin can be viewed by accessing the Wisconsin District Home Page at: http://wwwdwimdn.er.usgs.gov

Adjusting Wavelet-based Multiresolution Analysis Boundary Conditions for Robust Long-term Streamflow Forecasting Model

NASA Astrophysics Data System (ADS)

Maslova, I.; Ticlavilca, A. M.; McKee, M.

2012-12-01

There has been an increased interest in wavelet-based streamflow forecasting models in recent years. Often overlooked in this approach are the circularity assumptions of the wavelet transform. We propose a novel technique for minimizing the wavelet decomposition boundary condition effect to produce long-term, up to 12 months ahead, forecasts of streamflow. A simulation study is performed to evaluate the effects of different wavelet boundary rules using synthetic and real streamflow data. A hybrid wavelet-multivariate relevance vector machine model is developed for forecasting the streamflow in real-time for Yellowstone River, Uinta Basin, Utah, USA. The inputs of the model utilize only the past monthly streamflow records. They are decomposed into components formulated in terms of wavelet multiresolution analysis. It is shown that the model model accuracy can be increased by using the wavelet boundary rule introduced in this study. This long-term streamflow modeling and forecasting methodology would enable better decision-making and managing water availability risk.

On the effectiveness of recession analysis methods for capturing the characteristic storage-discharge relation: An intercomparison study

NASA Astrophysics Data System (ADS)

Chen, X.; Kumar, M.; Basso, S.; Marani, M.

2017-12-01

Storage-discharge (S-Q) relations are widely used to derive watershed properties and predict streamflow responses. These relations are often obtained using different recession analysis methods, which vary in recession period identification criteria and Q vs. -dQ/dt fitting scheme. Although previous studies have indicated that different recession analysis methods can result in significantly different S-Q relations and subsequently derived hydrological variables, this observation has often been overlooked and S-Q relations have been used in as is form. This study evaluated the effectiveness of four recession analysis methods in obtaining the characteristic S-Q relation and reconstructing the streamflow. Results indicate that while some methods generally performed better than others, none of them consistently outperformed the others. Even the best-performing method could not yield accurate reconstructed streamflow time series and its PDFs in some watersheds, implying that either derived S-Q relations might not be reliable or S-Q relations cannot be used for hydrological simulations. Notably, accuracy of the methods is influenced by the extent of scatter in the ln(-dQ/dt) vs. ln(Q) plot. In addition, the derived S-Q relation was very sensitive to the criteria used for identifying recession periods. This result raises a warning sign against indiscriminate application of recession analysis methods and derived S-Q relations for watershed characterizations or hydrologic simulations. Thorough evaluation of representativeness of the derived S-Q relation should be performed before it is used for hydrologic analysis.

A physically based analytical model of flood frequency curves

NASA Astrophysics Data System (ADS)

Basso, S.; Schirmer, M.; Botter, G.

2016-09-01

Predicting magnitude and frequency of floods is a key issue in hydrology, with implications in many fields ranging from river science and geomorphology to the insurance industry. In this paper, a novel physically based approach is proposed to estimate the recurrence intervals of seasonal flow maxima. The method links the extremal distribution of streamflows to the stochastic dynamics of daily discharge, providing an analytical expression of the seasonal flood frequency curve. The parameters involved in the formulation embody climate and landscape attributes of the contributing catchment and can be estimated from daily rainfall and streamflow data. Only one parameter, which is linked to the antecedent wetness condition in the watershed, needs to be calibrated on the observed maxima. The performance of the method is discussed through a set of applications in four rivers featuring heterogeneous daily flow regimes. The model provides reliable estimates of seasonal maximum flows in different climatic settings and is able to capture diverse shapes of flood frequency curves emerging in erratic and persistent flow regimes. The proposed method exploits experimental information on the full range of discharges experienced by rivers. As a consequence, model performances do not deteriorate when the magnitude of events with return times longer than the available sample size is estimated. The approach provides a framework for the prediction of floods based on short data series of rainfall and daily streamflows that may be especially valuable in data scarce regions of the world.

Modeling a densely urbanized watershed with an artificial neural network, weather radar and telemetric data

NASA Astrophysics Data System (ADS)

Pereira Filho, Augusto José; dos Santos, Cláudia Cristina

2006-02-01

Artificial neural networks (ANN) are widely used in a myriad of fields of research and development, including the predictability of time series. This work is concerned with one of such applications to simulate and to forecast stage level and streamflow at the Tamanduateí river watershed, one of the main tributaries of the Alto Tietê river watershed in São Paulo State, Brazil. This heavily urbanized watershed is within the Metropolitan Area of São Paulo (MASP) where recurrent flash floods affect a population of more than 17 million inhabitants. Flash floods events between 1991 and 1995 were selected and divided up into three groups for training, verification and forecasting purposes. Weather radar rainfall estimation and telemetric stage level and streamflow data were input to a three-layer feed forward ANN trained with the Linear Least Square Simplex training algorithm (LLSSIM) by Hsu et al. [Hsu, K.L., Gupta, H.V., Sorooshian, S., 1996. A superior training strategy for three-layer feed forward artificial neural networks. Tucson, University of Arizona. (Technique report, HWR no. 96-030, Department of Hydrology and Water Resources)]. The performance of the ANN is improved by 40% when either streamflow or stage level were input together with the rainfall. The ANN simulated flood waves tend to be dominated by phase errors. The ANN showed slightly better results then a multi-parameter auto-regression model and indicates its usefulness in flash flood forecasting.

Evaluation of Streamflow Gain-Loss Characteristics of Hubbard Creek, in the Vicinity of a Mine-Permit Area, Delta County, Colorado, 2007

USGS Publications Warehouse

Ruddy, Barbara C.; Williams, Cory A.

2007-01-01

In 2007, the U.S. Geological Survey, in cooperation with Bowie Mining Company, initiated a study to characterize the streamflow and streamflow gain-loss in a reach of Hubbard Creek in Delta County, Colorado, in the vicinity of a mine-permit area planned for future coal mining. Premining streamflow characteristics and streamflow gain-loss variation were determined so that pre- and postmining gain-loss characteristics could be compared. This report describes the methods used in this study and the results of two streamflow-measurement sets collected during low-flow conditions. Streamflow gain-loss measurements were collected using rhodamine WT and sodium bromide tracers at four sites spanning the mine-permit area on June 26-28, 2007. Streamflows were estimated and compared between four measurement sites within three stream subreaches of the study reach. Data from two streamflow-gaging stations on Hubbard Creek upstream and downstream from the mine-permit area were evaluated. Streamflows at the stations were continuous, and flow at the upstream station nearly always exceeded the streamflow at the downstream station. Furthermore, streamflow at both stations showed similar diurnal patterns with traveltime offsets. On June 26, streamflow from the gain-loss measurements was greater at site 1 (most upstream site) than at site 4 (most downstream site); on June 27, streamflow was greater at site 4 than at site 2; and on June 27, there was no difference in streamflow between sites 2 and 3. Data from streamflow-gaging stations 09132940 and 09132960 showed diurnal variations and overall decreasing streamflow over time. The data indicate a dynamic system, and streamflow can increase or decrease depending on hydrologic conditions. The streamflow within the study reach was greater than the streamflows at either the upstream or downstream stations. A second set of gain-loss measurements was collected at sites 2 and 4 on November 8-9, 2007. On November 8, streamflow was greater at site 4 than at site 2, and on the following day, November 9, streamflow was greater at site 2 than at site 4. Data collection on November 8 occurred while the streamflow was increasing due to contributions from stream ice melting throughout different parts of the basin. Data collection on November 9 occurred earlier in the day with less stream ice melting and more steady-state conditions, so the indication that streamflow decreased between sites 2 and 4 may be more accurate. Diurnal variations in streamflow are common at both the upper and the lower streamflow-gaging stations. The upper streamflow-gaging station shows a melt-freeze influence from tributaries to Hubbard Creek during the winter season. Downstream from the study reach, observed diurnal variation is likely due to evapotranspiration associated with dense flood-plain vegetation, which consumes water from the creek during the middle of the day. Varying diurnal patterns in streamflow, combined with possible variations in tributary inflows to Hubbard Creek in the study reach, probably account for the observed variations in streamflow at the tracer measurement sites. During both sampling periods in June and November 2007, conditions were less than ideal and not steady state. The June 27 sampling indicates that the streamflow was increasing between measurement sites 2 and 4, and the November 9 sampling indicates that the streamflow was decreasing between measurement sites 2 and 4. The data collected during the diurnal and day-to-day variations in streamflow indicated that the streamflow reach is dynamic and can be gaining, losing, or constant.

Geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin

NASA Astrophysics Data System (ADS)

Vibhava, F.; Graham, W. D.; Maxwell, R. M.

2012-12-01

Streamflow at any given location and time is representative of surface and subsurface contributions from various sources. The ability to fully identify the factors controlling these contributions is key to successfully understanding the transport of contaminants through the system. In this study we developed a fully integrated 3D surface water-groundwater-land surface model, PARFLOW, to evaluate geologic and climatic controls on streamflow generation processes in a complex eogenetic karst basin in North Central Florida. In addition to traditional model evaluation criterion, such as comparing field observations to model simulated streamflow and groundwater elevations, we quantitatively evaluated the model's predictions of surface-groundwater interactions over space and time using a suite of binary end-member mixing models that were developed using observed specific conductivity differences among surface and groundwater sources throughout the domain. Analysis of model predictions showed that geologic heterogeneity exerts a strong control on both streamflow generation processes and land atmospheric fluxes in this watershed. In the upper basin, where the karst aquifer is overlain by a thick confining layer, approximately 92% of streamflow is "young" event flow, produced by near stream rainfall. Throughout the upper basin the confining layer produces a persistent high surficial water table which results in high evapotranspiration, low groundwater recharge and thus negligible "inter-event" streamflow. In the lower basin, where the karst aquifer is unconfined, deeper water tables result in less evapotranspiration. Thus, over 80% of the streamflow is "old" subsurface flow produced by diffuse infiltration through the epikarst throughout the lower basin, and all surface contributions to streamflow originate in the upper confined basin. Climatic variability provides a secondary control on surface-subsurface and land-atmosphere fluxes, producing significant seasonal and interannual variability in these processes. Spatial and temporal patterns of evapotranspiration, groundwater recharge and streamflow generation processes reveal potential hot spots and hot moments for surface and groundwater contamination in this basin.

Streamflow characteristics at hydrologic bench-mark stations

USGS Publications Warehouse

Lawrence, C.L.

1987-01-01

The Hydrologic Bench-Mark Network was established in the 1960's. Its objectives were to document the hydrologic characteristics of representative undeveloped watersheds nationwide and to provide a comparative base for studying the effects of man on the hydrologic environment. The network, which consists of 57 streamflow gaging stations and one lake-stage station in 39 States, is planned for permanent operation. This interim report describes streamflow characteristics at each bench-mark site and identifies time trends in annual streamflow that have occurred during the data-collection period. The streamflow characteristics presented for each streamflow station are (1) flood and low-flow frequencies, (2) flow duration, (3) annual mean flow, and (4) the serial correlation coefficient for annual mean discharge. In addition, Kendall's tau is computed as an indicator of time trend in annual discharges. The period of record for most stations was 13 to 17 years, although several stations had longer periods of record. The longest period was 65 years for Merced River near Yosemite, Calif. Records of flow at 6 of 57 streamflow sites in the network showed a statistically significant change in annual mean discharge over the period of record, based on computations of Kendall's tau. The values of Kendall's tau ranged from -0.533 to 0.648. An examination of climatological records showed that changes in precipitation were most likely the cause for the change in annual mean discharge.

Montana StreamStats—A method for retrieving basin and streamflow characteristics in Montana: Chapter A in Montana StreamStats

USGS Publications Warehouse

McCarthy, Peter M.; Dutton, DeAnn M.; Sando, Steven K.; Sando, Roy

2016-04-05

The U.S. Geological Survey (USGS) provides streamflow characteristics and other related information needed by water-resource managers to protect people and property from floods, plan and manage water-resource activities, and protect water quality. Streamflow characteristics provided by the USGS, such as peak-flow and low-flow frequencies for streamflow-gaging stations, are frequently used by engineers, flood forecasters, land managers, biologists, and others to guide their everyday decisions. In addition to providing streamflow characteristics at streamflow-gaging stations, the USGS also develops regional regression equations and drainage area-adjustment methods for estimating streamflow characteristics at locations on ungaged streams. Regional regression equations can be complex and often require users to determine several basin characteristics, which are physical and climatic characteristics of the stream and its drainage basin. Obtaining these basin characteristics for streamflow-gaging stations and ungaged sites traditionally has been time consuming and subjective, and led to inconsistent results.StreamStats is a Web-based geographic information system application that was created by the USGS to provide users with access to an assortment of analytical tools that are useful for water-resource planning and management. StreamStats allows users to easily obtain streamflow and basin characteristics for USGS streamflow-gaging stations and user-selected locations on ungaged streams. The USGS, in cooperation with Montana Department of Transportation, Montana Department of Environmental Quality, and Montana Department of Natural Resources and Conservation, completed a study to develop a StreamStats application for Montana, compute streamflow characteristics at streamflow-gaging stations, and develop regional regression equations to estimate streamflow characteristics at ungaged sites. Chapter A of this Scientific Investigations Report describes the Montana StreamStats application and the datasets, streamflow-gaging stations, streamflow characteristics, and regression equations (as described fully in Chapters B through G of this report) that are used for development of the StreamStats application for Montana.

Spatial patterns of March and September streamflow trends in Pacific Northwest Streams, 1958-2008

USGS Publications Warehouse

Chang, Heejun; Jung, Il-Won; Steele, Madeline; Gannett, Marshall

2012-01-01

Summer streamflow is a vital water resource for municipal and domestic water supplies, irrigation, salmonid habitat, recreation, and water-related ecosystem services in the Pacific Northwest (PNW) in the United States. This study detects significant negative trends in September absolute streamflow in a majority of 68 stream-gauging stations located on unregulated streams in the PNW from 1958 to 2008. The proportion of March streamflow to annual streamflow increases in most stations over 1,000 m elevation, with a baseflow index of less than 50, while absolute March streamflow does not increase in most stations. The declining trends of September absolute streamflow are strongly associated with seven-day low flow, January–March maximum temperature trends, and the size of the basin (19–7,260 km2), while the increasing trends of the fraction of March streamflow are associated with elevation, April 1 snow water equivalent, March precipitation, center timing of streamflow, and October–December minimum temperature trends. Compared with ordinary least squares (OLS) estimated regression models, spatial error regression and geographically weighted regression (GWR) models effectively remove spatial autocorrelation in residuals. The GWR model results show spatial gradients of local R 2 values with consistently higher local R 2 values in the northern Cascades. This finding illustrates that different hydrologic landscape factors, such as geology and seasonal distribution of precipitation, also influence streamflow trends in the PNW. In addition, our spatial analysis model results show that considering various geographic factors help clarify the dynamics of streamflow trends over a large geographical area, supporting a spatial analysis approach over aspatial OLS-estimated regression models for predicting streamflow trends. Results indicate that transitional rain–snow surface water-dominated basins are likely to have reduced summer streamflow under warming scenarios. Consequently, a better understanding of the relationships among summer streamflow, precipitation, snowmelt, elevation, and geology can help water managers predict the response of regional summer streamflow to global warming.

Changes in the long-term hydrological regimes and the impacts of human activities in the main Wei River, China

NASA Astrophysics Data System (ADS)

Zhang, Hongbo; Huang, Qiang; Zhang, Qiang; Gu, Lei; Chen, Keyu; Yu, Qijun

2016-03-01

Under the combined influence of climate changes and human activities, the hydrological regime of the Wei River shows remarkable variations which have caused many issues in the Wei River in recent decades, such as a lack of freshwater, water pollution, disastrous flooding and channel sedimentation. Hence, hydrological regime changes and potential human-induced impacts have been drawing increasing attention from local government and hydrologists. This study investigates hydrological regime changes in the natural and measured runoff series at four hydrological stations on the main Wei River and quantifies features of their long-term change by analysing their historical annual and seasonal runoff data using several approaches, i.e., continuous wavelet transform, cross-wavelet, wavelet coherence, trend-free pre-whitening Mann-Kendall test and detrended fluctuation analysis. By contrasting two different analysis results between natural and measured river runoff series, the impacts of human activities on the long-term hydrological regime were investigated via the changes of spatio-temporal distribution in dominant periods, the trends and long-range memory of river runoff. The results show : (a) that periodic properties of the streamflow changes are the result of climate, referring to precipitation changes in particular, while human activities play a minor role; (b) a significant decreasing trend can be observed in the natural streamflow series along the entire main stream of the Wei River and the more serious decrease emerging in measured flow should result from human-induced influences in recent decades; and (c) continuous decreasing streamflow in the Wei River will trigger serious shortages of freshwater in the future, which may challenge the sustainability and safety of water resources development in the river basin, and should be paid great attention before 2020.

Ensemble reconstruction of severe low flow events in France since 1871

NASA Astrophysics Data System (ADS)

Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

2016-04-01

This work presents a study of severe low flow events that occurred from 1871 onwards for a large number of near-natural catchments in France. It aims at assessing and comparing their characteristics to improve our knowledge on historical events and to provide a selection of benchmark events for climate change adaptation purposes. The historical depth of streamflow observations is generally limited to the last 50 years and therefore offers too small a sample of severe low flow events to properly explore the long-term evolution of their characteristics and associated impacts. In order to overcome this limit, this work takes advantage of a 140-year ensemble hydrometeorological dataset over France based on: (1) a probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France (Caillouet et al., 2015), and (2) a continuous hydrological modelling that uses the high-resolution meteorological reconstructions as forcings over the whole period. This dataset provides an ensemble of 25 equally plausible daily streamflow time series for a reference network of stations in France over the whole 1871-2012 period. Severe low flow events are identified based on a combination of a fixed threshold and a daily variable threshold. Each event is characterized by its deficit, duration and timing by applying the Sequent Peak Algorithm. The procedure is applied to the 25 simulated time series as well as to the observed time series in order to compare observed and simulated events over the recent period, and to characterize in a probabilistic way unrecorded historical events. The ensemble aspect of the reconstruction leads to address specific issues, for properly defining events across ensemble simulations, as well as for adequately comparing the simulated characteristics to the observed ones. This study brings forward the outstanding 1921 and 1940s events but also older and less known ones that occurred during the last decade of the 19th century. For the first time, severe low flow events are qualified in a homogeneous way over 140 years on a large set of near-natural French catchments, allowing for detailed analyses of the effect of climate variability and anthropogenic climate change on low flow hydrology. Caillouet, L., Vidal, J.-P., Sauquet, E., and Graff, B. (2015) Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France, Clim. Past Discuss., 11, 4425-4482, doi:10.5194/cpd-11-4425-2015

Decomposition of Sources of Errors in Seasonal Streamflow Forecasts in a Rainfall-Runoff Dominated Basin

NASA Astrophysics Data System (ADS)

Sinha, T.; Arumugam, S.

2012-12-01

Seasonal streamflow forecasts contingent on climate forecasts can be effectively utilized in updating water management plans and optimize generation of hydroelectric power. Streamflow in the rainfall-runoff dominated basins critically depend on forecasted precipitation in contrast to snow dominated basins, where initial hydrological conditions (IHCs) are more important. Since precipitation forecasts from Atmosphere-Ocean-General Circulation Models are available at coarse scale (~2.8° by 2.8°), spatial and temporal downscaling of such forecasts are required to implement land surface models, which typically runs on finer spatial and temporal scales. Consequently, multiple sources are introduced at various stages in predicting seasonal streamflow. Therefore, in this study, we addresses the following science questions: 1) How do we attribute the errors in monthly streamflow forecasts to various sources - (i) model errors, (ii) spatio-temporal downscaling, (iii) imprecise initial conditions, iv) no forecasts, and (iv) imprecise forecasts? and 2) How does monthly streamflow forecast errors propagate with different lead time over various seasons? In this study, the Variable Infiltration Capacity (VIC) model is calibrated over Apalachicola River at Chattahoochee, FL in the southeastern US and implemented with observed 1/8° daily forcings to estimate reference streamflow during 1981 to 2010. The VIC model is then forced with different schemes under updated IHCs prior to forecasting period to estimate relative mean square errors due to: a) temporally disaggregation, b) spatial downscaling, c) Reverse Ensemble Streamflow Prediction (imprecise IHCs), d) ESP (no forecasts), and e) ECHAM4.5 precipitation forecasts. Finally, error propagation under different schemes are analyzed with different lead time over different seasons.

Limits on characteristics of invertebrate assemblages associated with streamflow patterns in the western United States

NASA Astrophysics Data System (ADS)

Konrad, C.; Brasher, A.; May, J.

2007-12-01

River restoration depends on re-establishment of the range of physical and biological processes that comprise the river ecosystem. Streamflow is the definitive physical processes for river ecosystems, so hydrologic alteration represents a potentially significant issue to be addressed by restoration efforts. Given adaptation of lotic species to naturally variable streamflow patterns over evolutionary time scales, however, lotic communities are resilient to at least some forms of hydrologic variability. As a result, river restoration may be successful despite limited but biologically insignificant hydrologic alteration. The responses of benthic invertebrate assemblages to variation in streamflow patterns across the western United States were investigated to identify biologically important forms and magnitudes of hydrologic variability. Biological responses to streamflow patterns were analyzed in terms of ceilings and floors on invertebrate assemblage diversity and structure using a non-parametric screening procedure and quantile regression. Variability at daily and monthly time scales was the most common streamflow pattern associated with broad metrics of invertebrate assemblages including abundance; richness and relative abundance of Ephemeroptera, Plecoptera, Trichoptera and non-insects; dominance; and diversity. Low flow magnitude and annual variability were associated with richness and trophic structure. The frequency, magnitude, and duration of high flows were associated with abundance and richness. Longer term streamflow metrics (calculated over at least 5 years) were more important than recent flows (30 and 100 days prior to invertebrate sampling). The results can be used as general guidance about when hydrologic alteration is likely to be an important factor and what streamflow patterns may need to be re-established for successful river restoration.

Water quality, streamflow conditions, and annual flow-duration curves for streams of the San Juan–Chama Project, southern Colorado and northern New Mexico, 1935-2010

USGS Publications Warehouse

Falk, Sarah E.; Anderholm, Scott K.; Hafich, Katya A.

2013-01-01

The Albuquerque–Bernalillo County Water Utility Authority supplements the municipal water supply for the Albuquerque metropolitan area, in central New Mexico, with water diverted from the Rio Grande. Water diverted from the Rio Grande for municipal use is derived from the San Juan–Chama Project, which delivers water from streams in the southern San Juan Mountains in the Colorado River Basin in southern Colorado to the Rio Chama watershed and the Rio Grande Basin in northern New Mexico. The U.S. Geological Survey, in cooperation with Albuquerque–Bernalillo County Water Utility Authority, has compiled historical streamflow and water-quality data and collected new water-quality data to characterize the water quality and streamflow conditions and annual flow variability, as characterized by annual flow-duration curves, of streams of the San Juan–Chama Project. Nonparametric statistical methods were applied to calculate annual and monthly summary statistics of streamflow, trends in streamflow conditions were evaluated with the Mann–Kendall trend test, and annual variation in streamflow conditions was evaluated with annual flow-duration curves. The study area is located in northern New Mexico and southern Colorado and includes the Rio Blanco, Little Navajo River, and Navajo River, tributaries of the San Juan River in the Colorado River Basin located in the southern San Juan Mountains, and Willow Creek and Horse Lake Creek, tributaries of the Rio Chama in the Rio Grande Basin. The quality of water in the streams in the study area generally varied by watershed on the basis of the underlying geology and the volume and source of the streamflow. Water from the Rio Blanco and Little Navajo River watersheds, primarily underlain by volcanic deposits, volcaniclastic sediments and landslide deposits derived from these materials, was compositionally similar and had low specific-conductance values relative to the other streams in the study area. Water from the Navajo River, Horse Lake Creek, and Willow Creek watersheds, which are underlain mostly by Cretaceous-aged marine shale, was compositionally similar and had large concentrations of sulfate relative to the other streams in the study area, though the water from the Navajo River had lower specific-conductance values than did the water from Horse Lake Creek above Heron Reservoir and Willow Creek above Azotea Creek. Generally, surface-water quality varied with streamflow conditions throughout the year. Streamflow in spring and summer is generally a mixture of base flow (the component of streamflow derived from groundwater discharged to the stream channel) diluted with runoff from snowmelt and precipitation events, whereas streamflow in fall and winter is generally solely base flow. Major- and trace-element concentrations in the streams sampled were lower than U.S. Environmental Protection Agency primary and secondary drinking-water standards and New Mexico Environment Department surface-water standards for the streams. In general, years with increased annual discharge, compared to years with decreased annual discharge, had a smaller percentage of discharge in March, a larger percentage of discharge in June, an interval of discharge derived from snowmelt runoff that occurred later in the year, and a larger discharge in June. Additionally, years with increased annual discharge generally had a longer duration of runoff, and the streamflow indicators occurred at dates later in the year than the years with less snowmelt runoff. Additionally, the seasonal distribution of streamflow was more strongly controlled by the change in the amount of annual discharge than by changes in streamflow over time. The variation of streamflow conditions over time at one streamflow-gaging station in the study area, Navajo River at Banded Peak Ranch, was not significantly monotonic over the period of record with a Kendall’s tau of 0.0426 and with a p-value of 0.5938 for 1937 to 2009 (a trend was considered statistically significant at a p-value ≤ 0.05). There was a relation, however, such that annual discharge was generally lower than the median during a negative Pacific Decadal Oscillation interval and higher than the median during a positive Pacific Decadal Oscillation interval. Streamflow conditions at Navajo River at Banded Peak Ranch varied nonmonotonically over time and were likely a function of complex climate pattern interactions. Similarly, the monthly distribution of streamflow varied nonmonotonically over time and was likely a function of complex climate pattern interactions that cause variation over time. Study results indicated that the median of the sum of the streamflow available above the minimum monthly bypass requirement from Rio Blanco, Little Navajo River, and Navajo River was 126,240 acre-feet. The results also indicated that diversion of water for the San Juan–Chama Project has been possible for most months of most years.

Long-term (in)stability of the climate-streamflow relationship

NASA Astrophysics Data System (ADS)

Saft, Margarita; Peel, Murray; Coxon, Gemma; Freer, Jim; Parajka, Juraj; Woods, Ross

2017-04-01

Land use changes have long been known to alter streamflow production for a given climatic input. Recently, extended shifts in climate were also shown to be capable of altering catchment internal functioning and streamflow production for a given climatic input. This study investigates the stability of climate-streamflow relationships in natural catchments in different regions of the world for the first time, using datasets of natural/reference catchments from Europe, US, and Australia. Changes in climate-streamflow relationships are investigated statistically on the interannual to interdecadal timescale and related to interdecadal climate variability. We compare the frequency and magnitude of shifts in climate-streamflow relationship between different regions, and discuss what any differences in shift frequency and magnitude might be related to. This study draws attention to the issues of catchment vulnerability to changes in external factors, catchment-climate co-evolution, and long-term catchment memory.

Impact of Fire on Streamflow in Southern California Watersheds

NASA Astrophysics Data System (ADS)

Bart, R. R.; Hope, A. S.

2007-12-01

Post-fire streamflow dynamics in Southern California have primarily been studied using small watershed experiments. These studies have concluded that increases in streamflow are a consequence of an increase in soil hydrophobicity, along with a decrease in transpiration rates associated with less vegetation. Extrapolation of the results from these studies to large watersheds (>50 km2) has been limited because large watersheds may not burn completely and other processes may emerge at these scales. In this study, six paired watersheds were used to test the hypothesis that there is an increase in streamflow following fire in large California watersheds (54-632 km2). The percentage of area burned in these watersheds ranged from 23 to 100%. The effects of fires on streamflow were examined at annual, seasonal, and monthly time-steps for the five years following fire. In addition, this study attempted to address fundamental regression assumptions that are commonly ignored, and create uncertainty bounds for evaluating the changes in streamflow before and after fire. Results of this experiment indicate that differences in pre and post-fire streamflows, at all time scales and in all the test catchments, were generally within the 95% uncertainty bounds of the regression equation. It is uncertain whether the apparent lack of significant difference between the pre and post-fire streamflow reflects no actual change in streamflow or is a consequence of the errors and uncertainties in the streamflow data. Furthermore, persistent drought in the years following fire made it challenging to interpret differences in pre and post-fire flows using the paired watershed methodology. The effects of hydrophobicity on post-fire streamflow may have been reduced by a limited number of storm flow events during these drought years. Under these dry conditions, soil moisture was the dominant control over transpirational losses, minimizing the effects of a reduction in vegetation cover. These results indicate that the consequences of fires are likely to vary depending on the post-fire meteorological conditions. The study addresses the challenges of using non-experimental watersheds for paired watershed studies.

Reconstructing streamflow variation of the Baker River from tree-rings in Northern Patagonia since 1765

NASA Astrophysics Data System (ADS)

Lara, Antonio; Bahamondez, Alejandra; González-Reyes, Alvaro; Muñoz, Ariel A.; Cuq, Emilio; Ruiz-Gómez, Carolina

2015-10-01

The understanding of the long-term variation of large rivers streamflow with a high economic and social relevance is necessary in order to improve the planning and management of water resources in different regions of the world. The Baker River has the highest mean discharge of those draining both slopes of the Andes South of 20°S and it is among the six rivers with the highest mean streamflow in the Pacific domain of South America (1100 m3 s-1 at its outlet). It drains an international basin of 29,000 km2 shared by Chile and Argentina and has a high ecologic and economic value including conservation, tourism, recreational fishing, and projected hydropower. This study reconstructs the austral summer - early fall (January-April) streamflow for the Baker River from Nothofagus pumilio tree-rings for the period 1765-2004. Summer streamflow represents 45.2% of the annual discharge. The regression model for the period (1961-2004) explains 54% of the variance of the Baker River streamflow (R2adj = 0.54). The most significant temporal pattern in the record is the sustained decline since the 1980s (τ = -0.633, p = 1.0144 ∗ 10-5 for the 1985-2004 period), which is unprecedented since 1765. The Correlation of the Baker streamflow with the November-April observed Southern Annular Mode (SAM) is significant (1961-2004, r = -0.55, p < 0.001). The Baker record is also correlated with the available SAM tree-ring reconstruction based on other species when both series are filtered with a 25-year spline and detrended (1765-2004, r = -0.41, p < 0.01), emphasizing SAM as the main climatic forcing of the Baker streamflow. Three of the five summers with the highest streamflow in the entire reconstructed record occurred after the 1950s (1977, 1958 and 1959). The causes of this high streamflow events are not yet clear and cannot be associated with the reported recent increase in the frequency of glacial-lake outburst floods (GLOFs). The decreasing trend in the observed and reconstructed streamflow of the Baker River documented here for the 1980-2004 period is consistent with precipitation decrease associated with the SAM. Conversely, other studies have reported an increase of summer streamflow for a portion of the Baker River for the 1994-2008 period, explained by ice melt associated with temperature increase and glacier retreat and thinning. Future research should consider the development of new tree-ring reconstructions to increase the geographic range and to cover the last 1000 or more years using long-lived species (e.g. Fitzroya cupressoides and Pilgerodendron uviferum). Expanding the network and quality of instrumental weather, streamflow and other monitoring stations as well as the study and modeling of the complex hydrological processes in the Baker basin are necessary. This should be the basis for planning, policy design and decision making regarding water resources in the Baker basin.

Assessing the controls and uncertainties on mean transit times in contrasting headwater catchments

NASA Astrophysics Data System (ADS)

Cartwright, Ian; Irvine, Dylan; Burton, Chad; Morgenstern, Uwe

2018-02-01

Estimating the time required for water to travel through headwater catchments from where it recharges to where it discharges into streams (the transit time) is important for understanding catchment behaviour. This study uses tritium (3H) activities of stream water to estimate the mean transit times of water in the upper Latrobe and Yarra catchments, southeast Australia, at different flow conditions. The 3H activities of the stream water were between 1.26 and 1.99 TU, which are lower than those of local rainfall (2.6 to 3.0 TU). 3H activities in individual subcatchments are almost invariably lowest at low streamflows. Mean transit times calculated from the 3H activities using a range of lumped parameter models are between 7 and 62 years and are longest during low streamflows. Uncertainties in the estimated mean transit times result from uncertainties in the geometry of the flow systems, uncertainties in the 3H input, and macroscopic mixing. In addition, simulation of 3H activities in FEFLOW indicates that heterogeneous hydraulic conductivities increase the range of mean transit times corresponding to a specific 3H activity. The absolute uncertainties in the mean transit times may be up to ±30 years. However, differences between mean transit times at different streamflows in the same catchment or between different subcatchments in the same area are more reliably estimated. Despite the uncertainties, the conclusions that the mean transit times are years to decades and decrease with increasing streamflow are robust. The seasonal variation in major ion geochemistry and 3H activities indicate that the higher general streamflows in winter are sustained by water displaced from shallower younger stores (e.g., soils or regolith). Poor correlations between 3H activities and catchment area, drainage density, mean slope, distance to stream, and landuse, imply that mean transit times are controlled by a variety of factors including the hydraulic properties of the soils and aquifers that are difficult to characterise spatially. The long mean transit times imply that there are long-lived stores of water in these catchments that may sustain streamflow over drought periods. Additionally, there may be considerable delay in contaminants reaching the stream.

Long-term streamflow trends on California’s north coast

Treesearch

J. Eli Asarian; Jeffrey D. Walker

2017-01-01

Using streamflow data from the U.S. Geological Survey, we assessed long-term (1953-2012) trends in streamflow on California’s North Coast including many sites in the redwood region. The study area spans from the Smith River to the Mattole River and includes the Eel and Klamath-Trinity basins. Antecedent Precipitation Index (API) is a time-weighted summary of...

Hazard function theory for nonstationary natural hazards

NASA Astrophysics Data System (ADS)

Read, L. K.; Vogel, R. M.

2015-11-01

Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e. that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (X) with its failure time series (T), enabling computation of corresponding average return periods, risk and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied Generalized Pareto (GP) model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard event series X, with corresponding failure time series T, should have application to a wide class of natural hazards with rich opportunities for future extensions.

Climate Change Impacts for Conterminous USA: An Integrated Assessment Part 2. Models and Validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomson, Allison M.; Rosenberg, Norman J.; Izaurralde, R Cesar C.

As CO{sub 2} and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how a changing climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using a suite of climate change predictions from General Circulation Models (GCMs) as described in Part 1. Here we describe the agriculture model EPIC and the HUMUS water model and validate them with historical crop yields and streamflow data. We compare EPIC simulated grainmore » and forage crop yields with historical crop yields from the US Department of Agriculture and find an acceptable level of agreement for this study. The validation of HUMUS simulated streamflow with estimates of natural streamflow from the US Geological Survey shows that the model is able to reproduce significant relationships and capture major trends.« less

An environmental streamflow assessment for the Santiam River basin, Oregon

USGS Publications Warehouse

Risley, John C.; Wallick, J. Rose; Mangano, Joseph F.; Jones, Krista L.

2012-01-01

The Santiam River is a tributary of the Willamette River in northwestern Oregon and drains an area of 1,810 square miles. The U.S. Army Corps of Engineers (USACE) operates four dams in the basin, which are used primarily for flood control, hydropower production, recreation, and water-quality improvement. The Detroit and Big Cliff Dams were constructed in 1953 on the North Santiam River. The Green Peter and Foster Dams were completed in 1967 on the South Santiam River. The impacts of the structures have included a decrease in the frequency and magnitude of floods and an increase in low flows. For three North Santiam River reaches, the median of annual 1-day maximum streamflows decreased 42–50 percent because of regulated streamflow conditions. Likewise, for three reaches in the South Santiam River basin, the median of annual 1-day maximum streamflows decreased 39–52 percent because of regulation. In contrast to their effect on high flows, the dams increased low flows. The median of annual 7-day minimum flows in six of the seven study reaches increased under regulated streamflow conditions between 60 and 334 percent. On a seasonal basis, median monthly streamflows decreased from February to May and increased from September to January in all the reaches. However, the magnitude of these impacts usually decreased farther downstream from dams because of cumulative inflow from unregulated tributaries and groundwater entering the North, South, and main-stem Santiam Rivers below the dams. A Wilcox rank-sum test of monthly precipitation data from Salem, Oregon, and Waterloo, Oregon, found no significant difference between the pre-and post-dam periods, which suggests that the construction and operation of the dams since the 1950s and 1960s are a primary cause of alterations to the Santiam River basin streamflow regime. In addition to the streamflow analysis, this report provides a geomorphic characterization of the Santiam River basin and the associated conceptual framework for assessing possible geomorphic and ecological changes in response to river-flow modifications. Suggestions for future biomonitoring and investigations are also provided. This study was one in a series of similar tributary streamflow and geomorphic studies conducted for the Willamette Sustainable Rivers Project. The Sustainable Rivers Project is a national effort by the USACE and The Nature Conservancy to develop environmental flow requirements in regulated river systems.

Multi-decadal Decline of Southeast United States Streamflow

NASA Astrophysics Data System (ADS)

Tootle, G. A.; Lakshmi, V.; Therrell, M.; Huffaker, R.; Elliott, E. A.

2017-12-01

Unprecedented population growth combined with environmental and energy demands have led to water conflict in the Southeastern United States. The states of Florida, Georgia and Alabama have recently engaged in litigation on minimum in-stream flows to maintain ecosystems, fisheries and energy demands while satisfying a growing thirst in metropolitan Atlanta. A study of Southeastern United States (Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina and Tennessee) streamflow identified a declining pattern of flow over the past 25 years with increased dry periods being observed in the last decade. When evaluating calendar year streamflow for (56) unimpaired streamflow stations, a robust period of streamflow in the 1970's was followed by a consistent decline in streamflow from 1990 to present. In evaluating 20-year, 10-year and 5-year time periods of annual streamflow volume, the past decade reveals historic lows for each of these periods. When evaluating the influence of high frequency (e.g., El Nino-Southern Oscillation - ENSO) and low frequency (e.g., Atlantic Multi-decadal Oscillation - AMO) climatic phenomenon, the shift of the AMO from a cold phase to a warm phase in the 1990's combined with multiple La Nina events may be associated with the streamflow decline.

How Hydroclimate Influences the Effectiveness of Particle Filter Data Assimilation of Streamflow in Initializing Short- to Medium-range Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Clark, E.; Wood, A.; Nijssen, B.; Clark, M. P.

2017-12-01

Short- to medium-range (1- to 7-day) streamflow forecasts are important for flood control operations and in issuing potentially life-save flood warnings. In the U.S., the National Weather Service River Forecast Centers (RFCs) issue such forecasts in real time, depending heavily on a manual data assimilation (DA) approach. Forecasters adjust model inputs, states, parameters and outputs based on experience and consideration of a range of supporting real-time information. Achieving high-quality forecasts from new automated, centralized forecast systems will depend critically on the adequacy of automated DA approaches to make analogous corrections to the forecasting system. Such approaches would further enable systematic evaluation of real-time flood forecasting methods and strategies. Toward this goal, we have implemented a real-time Sequential Importance Resampling particle filter (SIR-PF) approach to assimilate observed streamflow into simulated initial hydrologic conditions (states) for initializing ensemble flood forecasts. Assimilating streamflow alone in SIR-PF improves simulated streamflow and soil moisture during the model spin up period prior to a forecast, with consequent benefits for forecasts. Nevertheless, it only consistently limits error in simulated snow water equivalent during the snowmelt season and in basins where precipitation falls primarily as snow. We examine how the simulated initial conditions with and without SIR-PF propagate into 1- to 7-day ensemble streamflow forecasts. Forecasts are evaluated in terms of reliability and skill over a 10-year period from 2005-2015. The focus of this analysis is on how interactions between hydroclimate and SIR-PF performance impact forecast skill. To this end, we examine forecasts for 5 hydroclimatically diverse basins in the western U.S. Some of these basins receive most of their precipitation as snow, others as rain. Some freeze throughout the mid-winter while others experience significant mid-winter melt events. We describe the methodology and present seasonal and inter-basin variations in DA-enhanced forecast skill.

Application of the Precipitation-Runoff Modeling System (PRMS) in the Apalachicola-Chattahoochee-Flint River Basin in the southeastern United States

USGS Publications Warehouse

LaFontaine, Jacob H.; Hay, Lauren E.; Viger, Roland J.; Markstrom, Steve L.; Regan, R. Steve; Elliott, Caroline M.; Jones, John W.

2013-01-01

A hydrologic model of the Apalachicola–Chattahoochee–Flint River Basin (ACFB) has been developed as part of a U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center effort to provide integrated science that helps resource managers understand the effect of climate change on a range of ecosystem responses. The hydrologic model was developed as part of the Southeast Regional Assessment Project using the Precipitation Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, and land use on basin hydrology. The ACFB PRMS model simulates streamflow throughout the approximately 50,700 square-kilometer basin on a daily time step for the period 1950–99 using gridded climate forcings of air temperature and precipitation, and parameters derived from spatial data layers of altitude, land cover, soils, surficial geology, depression storage (small water bodies), and data from 56 USGS streamgages. Measured streamflow data from 35 of the 56 USGS streamgages were used to calibrate and evaluate simulated basin streamflow; the remaining gage locations were used for model delineation only. The model matched measured daily streamflow at 31 of the 35 calibration gages with Nash-Sutcliffe Model Efficiency Index (NS) greater than 0.6. Streamflow data for some calibration gages were augmented for regulation and water use effects to represent more natural flow volumes. Time-static parameters describing land cover limited the ability of the simulation to match historical runoff in the more developed subbasins. Overall, the PRMS simulation of the ACFB provides a good representation of basin hydrology on annual and monthly time steps. Calibration subbasins were analyzed by separating the 35 subbasins into five classes based on physiography, land use, and stream type (tributary or mainstem). The lowest NS values were rarely below 0.6, whereas the median NS for all five classes was within 0.74 to 0.96 for annual mean streamflow, 0.89 to 0.98 for mean monthly streamflow, and 0.82 to 0.98 for monthly mean streamflow. The median bias for all five classes was within –4.3 to 0.8 percent for annual mean streamflow, –6.3 to 0.5 percent for mean monthly streamflow, and –9.3 to 1.3 percent for monthly mean streamflow. The NS results combined with the percent bias results indicated a good to very good streamflow volume simulation for all subbasins. This simulation of the ACFB provides a foundation for future modeling and interpretive studies. Streamflow and other components of the hydrologic cycle simulated by PRMS can be used to inform other types of simulations; water-temperature, hydrodynamic, and ecosystem-dynamics simulations are three examples. In addition, possible future hydrologic conditions could be studied using this model in combination with land cover projections and downscaled general circulation model results.

Rainfall, streamflow, and peak stage data collected at the Murfreesboro, Tennessee, gaging network, March 1989 through July 1992

USGS Publications Warehouse

Outlaw, G.S.; Butner, D.E.; Kemp, R.L.; Oaks, A.T.; Adams, G.S.

1992-01-01

Rainfall, stage, and streamflow data in the Murfreesboro area, Middle Tennessee, were collected from March 1989 through July 1992 from a network of 68 gaging stations. The network consists of 10 tipping-bucket rain gages, 2 continuous-record streamflow gages, 4 partial-record flood hydrograph gages, and 72 crest-stage gages. Data collected by the gages includes 5minute time-step rainfall hyetographs, 15-minute time-step flood hydrographs, and peak-stage elevations. Data are stored in a computer data base and are available for many computer modeling and engineering applications.

Streamflow alteration at selected sites in Kansas

USGS Publications Warehouse

Juracek, Kyle E.; Eng, Ken

2017-06-26

An understanding of streamflow alteration in response to various disturbances is necessary for the effective management of stream habitat for a variety of species in Kansas. Streamflow alteration can have negative ecological effects. Using a modeling approach, streamflow alteration was assessed for 129 selected U.S. Geological Survey streamgages in the State for which requisite streamflow and basin-characteristic information was available. The assessment involved a comparison of the observed condition from 1980 to 2015 with the predicted expected (least-disturbed) condition for 29 streamflow metrics. The metrics represent various characteristics of streamflow including average flow (annual, monthly) and low and high flow (frequency, duration, magnitude).Streamflow alteration in Kansas was indicated locally, regionally, and statewide. Given the absence of a pronounced trend in annual precipitation in Kansas, a precipitation-related explanation for streamflow alteration was not supported. Thus, the likely explanation for streamflow alteration was human activity. Locally, a flashier flow regime (typified by shorter lag times and more frequent and higher peak discharges) was indicated for three streamgages with urbanized basins that had higher percentages of impervious surfaces than other basins in the State. The combination of localized reservoir effects and regional groundwater pumping from the High Plains aquifer likely was responsible, in part, for diminished conditions indicated for multiple streamflow metrics in western and central Kansas. Statewide, the implementation of agricultural land-management practices to reduce runoff may have been responsible, in part, for a diminished duration and magnitude of high flows. In central and eastern Kansas, implemented agricultural land-management practices may have been partly responsible for an inflated magnitude of low flows at several sites.

Flood frequency analysis - the challenge of using historical data

NASA Astrophysics Data System (ADS)

Engeland, Kolbjorn

2015-04-01

Estimates of high flood quantiles are needed for many applications, .e.g. dam safety assessments are based on the 1000 years flood, whereas the dimensioning of important infrastructure requires estimates of the 200 year flood. The flood quantiles are estimated by fitting a parametric distribution to a dataset of high flows comprising either annual maximum values or peaks over a selected threshold. Since the record length of data is limited compared to the desired flood quantile, the estimated flood magnitudes are based on a high degree of extrapolation. E.g. the longest time series available in Norway are around 120 years, and as a result any estimation of a 1000 years flood will require extrapolation. One solution is to extend the temporal dimension of a data series by including information about historical floods before the stream flow was systematically gaugeded. Such information could be flood marks or written documentation about flood events. The aim of this study was to evaluate the added value of using historical flood data for at-site flood frequency estimation. The historical floods were included in two ways by assuming: (1) the size of (all) floods above a high threshold within a time interval is known; and (2) the number of floods above a high threshold for a time interval is known. We used a Bayesian model formulation, with MCMC used for model estimation. This estimation procedure allowed us to estimate the predictive uncertainty of flood quantiles (i.e. both sampling and parameter uncertainty is accounted for). We tested the methods using 123 years of systematic data from Bulken in western Norway. In 2014 the largest flood in the systematic record was observed. From written documentation and flood marks we had information from three severe floods in the 18th century and they were likely to exceed the 2014 flood. We evaluated the added value in two ways. First we used the 123 year long streamflow time series and investigated the effect of having several shorter series' which could be supplemented with a limited number of known large flood events. Then we used the three historical floods from the 18th century combined with the whole and subsets of the 123 years of systematic observations. In the latter case several challenges were identified: i) The possibility to transfer water levels to river streamflows due to man made changes in the river profile, (ii) The stationarity of the data might be questioned since the three largest historical floods occurred during the "little ice age" with different climatic conditions compared to today.

Assessment of an ensemble seasonal streamflow forecasting system for Australia

NASA Astrophysics Data System (ADS)

Bennett, James C.; Wang, Quan J.; Robertson, David E.; Schepen, Andrew; Li, Ming; Michael, Kelvin

2017-11-01

Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean-land-atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall-runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall-runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall-runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.

Sub-seasonal-to-seasonal Reservoir Inflow Forecast using Bayesian Hierarchical Hidden Markov Model

NASA Astrophysics Data System (ADS)

Mukhopadhyay, S.; Arumugam, S.

2017-12-01

Sub-seasonal-to-seasonal (S2S) (15-90 days) streamflow forecasting is an emerging area of research that provides seamless information for reservoir operation from weather time scales to seasonal time scales. From an operational perspective, sub-seasonal inflow forecasts are highly valuable as these enable water managers to decide short-term releases (15-30 days), while holding water for seasonal needs (e.g., irrigation and municipal supply) and to meet end-of-the-season target storage at a desired level. We propose a Bayesian Hierarchical Hidden Markov Model (BHHMM) to develop S2S inflow forecasts for the Tennessee Valley Area (TVA) reservoir system. Here, the hidden states are predicted by relevant indices that influence the inflows at S2S time scale. The hidden Markov model also captures the both spatial and temporal hierarchy in predictors that operate at S2S time scale with model parameters being estimated as a posterior distribution using a Bayesian framework. We present our work in two steps, namely single site model and multi-site model. For proof of concept, we consider inflows to Douglas Dam, Tennessee, in the single site model. For multisite model we consider reservoirs in the upper Tennessee valley. Streamflow forecasts are issued and updated continuously every day at S2S time scale. We considered precipitation forecasts obtained from NOAA Climate Forecast System (CFSv2) GCM as predictors for developing S2S streamflow forecasts along with relevant indices for predicting hidden states. Spatial dependence of the inflow series of reservoirs are also preserved in the multi-site model. To circumvent the non-normality of the data, we consider the HMM in a Generalized Linear Model setting. Skill of the proposed approach is tested using split sample validation against a traditional multi-site canonical correlation model developed using the same set of predictors. From the posterior distribution of the inflow forecasts, we also highlight different system behavior under varied global and local scale climatic influences from the developed BHMM.

The influence of north Pacific atmospheric circulation on streamflow in the west

USGS Publications Warehouse

Cayan, Daniel R.; Peterson, David H.

1989-01-01

The annual cycle and nonseasonal variability of streamflow over western North America and Hawaii is studied in terms of atmospheric forcing elements. This study uses several decades of monthly average streamflow beginning as early as the late 1800's over a network of 38 stations. In addition to a strong annual cycle in mean streamflow and its variance at most of the stations, there is also a distinct annual cycle in the autocorrelation of anomalies that is related to the interplay between the annual cycles of temperature and precipitation. Of particular importance to these lag effects is the well-known role of water stored as snow pack, which controls the delay between peak precipitation and peak flow and also introduces persistence into the nonseasonal streamflow anomalies, with time scales from 1 month to over 1 year. The degree to which streamflow is related to winter atmospheric circulation over the North Pacific and western North America is tested using correlations with time averaged, gridded sea level pressure (SLP), which begins in 1899. Streamflow fluctuations show significant large-scale correlations for the winter (December through February) mean SLP anomaly patterns over the North Pacific with maximum correlations ranging from 0.3 to about 0.6. For streams along the west coast corridor the circulation pattern associated with positive streamflow anomalies is low pressure centered off the coast to the west or northwest, indicative of increased winter storms and an anomalous westerly-to-southwesterly wind component. For streams in the interior positive streamflow anomalies are associated with a positive SLP anomaly stationed remotely over the central North Pacific, and with negative but generally weaker SLP anomalies locally. One important influence on streamflow variability is the strength of the Aleutian Low in winter. This is represented by the familiar Pacific-North America (PNA) index and also by an index defined herein the “CNP” (Central North Pacific). This index, beginning in 1899, is taken to be the average of the SLP anomaly south of the Aleutians and the western Gulf of Alaska. Correlations between PNA or CNP and regional anomalies reflect streamflow the alternations in strength and position of the mean North Pacific storm track entering North America as well as shifts in the trade winds over the subtropical North Pacific. Regions whose streamflow is best tuned to the PNA or CNP include coastal Alaska, the northwestern United States, and Hawaii; the latter two regions have the opposite sign anomaly as the former. The pattern of streamflow variations associated with El Niño is similar, but the El Niño signal also includes a tendency for greater than normal streamflow in the southwestern United States. These indices are significantly correlated with streamflow at one to two seasons in advance of the December–August period, which may allow modestly skillful forecasts. It is important to note that streamflow variability in some areas, such as British Columbia and California, does not respond consistently to these broad scale Pacific atmospheric circulation indices, but is related to regional atmospheric anomaly features over the eastern North Pacific. Spatially, streamflow anomalies are fairly well correlated over scales of several hundred kilometers. Inspection of the spatial anomalies of stream-flow in this study suggest an asymmetry in the spatial pattern of positive versus negative streamflow anomalies in the western United States: dry patterns have tended to be larger and more spatially coherent than wet patterns.

Past and future changes in streamflow in the U.S. Midwest: Bridging across time scales

NASA Astrophysics Data System (ADS)

Villarini, G.; Slater, L. J.; Salvi, K. A.

2017-12-01

Streamflows have increased notably across the U.S. Midwest over the past century, principally due to changes in precipitation and land use / land cover. Improving our understanding of the physical drivers that are responsible for the observed changes in discharge may enhance our capability of predicting and projecting these changes, and may have large implications for water resources management over this area. This study will highlight our efforts towards the statistical attribution of changes in discharge across the U.S. Midwest, with analyses performed at the seasonal scale from low to high flows. The main drivers of changing streamflows that we focus on are: urbanization, agricultural land cover, basin-averaged temperature, basin-averaged precipitation, and antecedent soil moisture. Building on the insights from this attribution, we will examine the potential predictability of streamflow across different time scales, with lead times ranging from seasonal to decadal, and discuss a potential path forward for engineering design for future conditions.

Reconnaissance of Stream Geomorphology, Low Streamflow, and Stream Temperature in the Mountaintop Coal-Mining Region, Southern West Virginia, 1999-2000

USGS Publications Warehouse

Wiley, Jeffrey B.; Evaldi, Ronald D.; Eychaner, James H.; Chambers, Douglas B.

2001-01-01

The effects of mountaintop removal coal mining and the valley fills created by this mining method in southern West Virginia were investigated by comparing data collected at valley-fill, mined, and unmined sites. Bed material downstream of valley-fill sites had a greater number of particles less than 2 millimeters and a smaller median particle size than the mined and unmined sites. At the 84th percentile of sampled data, however, bed material at each site type had about the same size particles. Bankfull cross-sectional areas at a riffle section were approximately equal at valley-fill and unmined sites, but not enough time has passed and insufficient streamflows since the land was disturbed may have prevented the stream channel at valley-fill sites from reaching equilibrium. The 90-percent flow durations at valley-fill sites generally were 6-7 times greater than at unmined sites. Some valley-fill sites, however, exhibited streamflows similar to unmined sites, and some unmined sites exhibited streamflows similar to valley-fill sites. Daily streamflows from valley-fill sites generally are greater than daily streamflows from unmined sites during periods of low streamflow. Valley-fill sites have a greater percentage of base-flow and a lower percentage of flow from storm runoff than unmined sites. Water temperatures from a valley-fill site exhibited lower daily fluctuations and seasonal variations than water temperatures from an unmined site.

Identification of symmetric and asymmetric responses in seasonal streamflow globally to ENSO phase

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Ward, Philip J.; Block, Paul

2018-04-01

The phase of the El Niño Southern Oscillation (ENSO) has large-ranging effects on streamflow and hydrologic conditions globally. While many studies have evaluated this relationship through correlation analysis between annual streamflow and ENSO indices, an assessment of potential asymmetric relationships between ENSO and streamflow is lacking. Here, we evaluate seasonal variations in streamflow by ENSO phase to identify asymmetric (AR) and symmetric (SR) spatial pattern responses globally and further corroborate with local precipitation and hydrological condition. The AR and SR patterns between seasonal precipitation and streamflow are identified at many locations for the first time. Our results identify strong SR patterns in particular regions including northwestern and southern US, northeastern and southeastern South America, northeastern and southern Africa, southwestern Europe, and central-south Russia. The seasonally lagged anomalous streamflow patterns are also identified and attributed to snowmelt, soil moisture, and/or cumulative hydrological processes across river basins. These findings may be useful in water resources management and natural hazards planning by better characterizing the propensity of flood or drought conditions by ENSO phase.

Substantial proportion of global streamflow less than three months old

NASA Astrophysics Data System (ADS)

Jasechko, Scott; Kirchner, James W.; Welker, Jeffrey M.; McDonnell, Jeffrey J.

2016-02-01

Biogeochemical cycles, contaminant transport and chemical weathering are regulated by the speed at which precipitation travels through landscapes and reaches streams. Streamflow is a mixture of young and old precipitation, but the global proportions of these young and old components are not known. Here we analyse seasonal cycles of oxygen isotope ratios in rain, snow and streamflow compiled from 254 watersheds around the world, and calculate the fraction of streamflow that is derived from precipitation that fell within the past two or three months. This young streamflow accounts for about a third of global river discharge, and comprises at least 5% of discharge in about 90% of the catchments we investigated. We conclude that, although typical catchments have mean transit times of years or even decades, they nonetheless can rapidly transmit substantial fractions of soluble contaminant inputs to streams. Young streamflow is less prevalent in steeper landscapes, which suggests they are characterized by deeper vertical infiltration. Because young streamflow is derived from less than 0.1% of global groundwater storage, we conclude that this thin veneer of aquifer storage will have a disproportionate influence on stream water quality.

Evaluation and trends of land cover, streamflow, and water quality in the North Canadian River Basin near Oklahoma City, Oklahoma, 1968–2009

USGS Publications Warehouse

Esralew, Rachel A.; Andrews, William J.; Smith, S. Jerrod

2011-01-01

The U.S. Geological Survey, in cooperation with the city of Oklahoma City, collected water-quality samples from the North Canadian River at the streamflow-gaging station near Harrah, Oklahoma (Harrah station), since 1968, and at an upstream streamflow-gaging station at Britton Road at Oklahoma City, Oklahoma (Britton Road station), since 1988. Statistical summaries and frequencies of detection of water-quality constituent data from water samples, and summaries of water-quality constituent data from continuous water-quality monitors are described from the start of monitoring at those stations through 2009. Differences in concentrations between stations and time trends for selected constituents were evaluated to determine the effects of: (1) wastewater effluent discharges, (2) changes in land-cover, (3) changes in streamflow, (4) increases in urban development, and (5) other anthropogenic sources of contamination on water quality in the North Canadian River downstream from Oklahoma City. Land-cover changes between 1992 and 2001 in the basin between the Harrah station and Lake Overholser upstream included an increase in developed/barren land-cover and a decrease in pasture/hay land cover. There were no significant trends in median and greater streamflows at either streamflow-gaging station, but there were significant downward trends in lesser streamflows, especially after 1999, which may have been associated with decreases in precipitation between 1999 and 2009 or construction of low-water dams on the river upstream from Oklahoma City in 1999. Concentrations of dissolved chloride, lead, cadmium, and chlordane most frequently exceeded the Criterion Continuous Concentration (a water-quality standard for protection of aquatic life) in water-quality samples collected at both streamflow-gaging stations. Visual trends in annual frequencies of detection were investigated for selected pesticides with frequencies of detection greater than 10 percent in all water samples collected at both streamflow-gaging stations. Annual frequencies of detection of 2,4-dichlorophenoxyacetic acid and bromacil increased with time. Annual frequencies of detection of atrazine, chlorpyrifos, diazinon, dichlorprop, and lindane decreased with time. Dissolved nitrogen and phosphorus concentrations were significantly greater in water samples collected at the Harrah station than at the Britton Road station, whereas specific conductance was greater at the Britton Road station. Concentrations of dissolved oxygen, biochemical oxygen demand, and fecal coliform bacteria were not significantly different between stations. Daily minimum, mean, and maximum specific conductance collected from continuous water-quality monitors were significantly greater at the Britton Road station than in water samples collected at the Harrah station. Daily minimum, maximum, and diurnal fluctuations of water temperature collected from continuous water-quality monitors were significantly greater at the Harrah station than at the Britton Road station. The daily maximums and diurnal range of dissolved oxygen concentrations were significantly greater in water samples collected at the Britton Road station than at the Harrah station, but daily mean dissolved oxygen concentrations in water at those streamflow-gaging stations were not significantly different. Daily mean and diurnal water temperature ranges increased with time at the Britton Road and Harrah streamflow-gaging stations, whereas daily mean and diurnal specific conductance ranges decreased with time at both streamflow-gaging stations from 1988–2009. Daily minimum dissolved oxygen concentrations collected from continuous water-quality monitors more frequently indicated hypoxic conditions at the Harrah station than at the Britton Road station after 1999. Fecal coliform bacteria counts in water decreased slightly from 1988–2009 at the Britton Road station. The Seasonal Kendall's tau test indicated significant downward trends in

Simulated runoff at many stream locations in the Methow River Basin, Washington

USGS Publications Warehouse

Mastin, Mark C.

2015-01-01

Comparisons of the simulated runoff with observed runoff at six selected long-term streamflow-gaging stations showed that the simulated annual runoff was within +15.4 to -9.6 percent of the annual observed runoff. The simulated runoff generally matched the seasonal flow patterns, with bias at some stations indicated by over-simulation of the October–November late autumn season and under-simulation of the snowmelt runoff months of May and June. Sixty-one time series of daily runoff for a 26-year period representative of the long-term runoff pattern, water years 1988–2013, were simulated and provided to the trophic modeling team.

Characterizing the utility of the TMPA real-time product for hydrologic predictions over global river basins across scales

NASA Astrophysics Data System (ADS)

Gao, H.; Zhang, S.; Nijssen, B.; Zhou, T.; Voisin, N.; Sheffield, J.; Lee, K.; Shukla, S.; Lettenmaier, D. P.

2017-12-01

Despite its errors and uncertainties, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time product (TMPA-RT) has been widely used for hydrological monitoring and forecasting due to its timely availability for real-time applications. To evaluate the utility of TMPA-RT in hydrologic predictions, many studies have compared modeled streamflows driven by TMPA-RT against gauge data. However, because of the limited availability of streamflow observations in data sparse regions, there is still a lack of comprehensive comparisons for TMPA-RT based hydrologic predictions at the global scale. Furthermore, it is expected that its skill is less optimal at the subbasin scale than the basin scale. In this study, we evaluate and characterize the utility of the TMPA-RT product over selected global river basins during the period of 1998 to 2015 using the TMPA research product (TMPA-RP) as a reference. The Variable Infiltration Capacity (VIC) model, which was calibrated and validated previously, is adopted to simulate streamflows driven by TMPA-RT and TMPA-RP, respectively. The objective of this study is to analyze the spatial and temporal characteristics of the hydrologic predictions by answering the following questions: (1) How do the precipitation errors associated with the TMPA-RT product transform into streamflow errors with respect to geographical and climatological characteristics? (2) How do streamflow errors vary across scales within a basin?

Event-scale power law recession analysis: quantifying methodological uncertainty

NASA Astrophysics Data System (ADS)

Dralle, David N.; Karst, Nathaniel J.; Charalampous, Kyriakos; Veenstra, Andrew; Thompson, Sally E.

2017-01-01

The study of single streamflow recession events is receiving increasing attention following the presentation of novel theoretical explanations for the emergence of power law forms of the recession relationship, and drivers of its variability. Individually characterizing streamflow recessions often involves describing the similarities and differences between model parameters fitted to each recession time series. Significant methodological sensitivity has been identified in the fitting and parameterization of models that describe populations of many recessions, but the dependence of estimated model parameters on methodological choices has not been evaluated for event-by-event forms of analysis. Here, we use daily streamflow data from 16 catchments in northern California and southern Oregon to investigate how combinations of commonly used streamflow recession definitions and fitting techniques impact parameter estimates of a widely used power law recession model. Results are relevant to watersheds that are relatively steep, forested, and rain-dominated. The highly seasonal mediterranean climate of northern California and southern Oregon ensures study catchments explore a wide range of recession behaviors and wetness states, ideal for a sensitivity analysis. In such catchments, we show the following: (i) methodological decisions, including ones that have received little attention in the literature, can impact parameter value estimates and model goodness of fit; (ii) the central tendencies of event-scale recession parameter probability distributions are largely robust to methodological choices, in the sense that differing methods rank catchments similarly according to the medians of these distributions; (iii) recession parameter distributions are method-dependent, but roughly catchment-independent, such that changing the choices made about a particular method affects a given parameter in similar ways across most catchments; and (iv) the observed correlative relationship between the power-law recession scale parameter and catchment antecedent wetness varies depending on recession definition and fitting choices. Considering study results, we recommend a combination of four key methodological decisions to maximize the quality of fitted recession curves, and to minimize bias in the related populations of fitted recession parameters.

Post-processing ECMWF precipitation and temperature ensemble reforecasts for operational hydrologic forecasting at various spatial scales

NASA Astrophysics Data System (ADS)

Verkade, J. S.; Brown, J. D.; Reggiani, P.; Weerts, A. H.

2013-09-01

The ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in the mean, spread and forecast probabilities, and how these biases propagate to streamflow ensemble forecasts. The forcing ensembles are subsequently post-processed to reduce bias and increase skill, and to investigate whether this leads to improved streamflow ensemble forecasts. Multiple post-processing techniques are used: quantile-to-quantile transform, linear regression with an assumption of bivariate normality and logistic regression. Both the raw and post-processed ensembles are run through a hydrologic model of the river Rhine to create streamflow ensembles. The results are compared using multiple verification metrics and skill scores: relative mean error, Brier skill score and its decompositions, mean continuous ranked probability skill score and its decomposition, and the ROC score. Verification of the streamflow ensembles is performed at multiple spatial scales: relatively small headwater basins, large tributaries and the Rhine outlet at Lobith. The streamflow ensembles are verified against simulated streamflow, in order to isolate the effects of biases in the forcing ensembles and any improvements therein. The results indicate that the forcing ensembles contain significant biases, and that these cascade to the streamflow ensembles. Some of the bias in the forcing ensembles is unconditional in nature; this was resolved by a simple quantile-to-quantile transform. Improvements in conditional bias and skill of the forcing ensembles vary with forecast lead time, amount, and spatial scale, but are generally moderate. The translation to streamflow forecast skill is further muted, and several explanations are considered, including limitations in the modelling of the space-time covariability of the forcing ensembles and the presence of storages.

Decomposition of Sources of Errors in Seasonal Streamflow Forecasting over the U.S. Sunbelt

NASA Technical Reports Server (NTRS)

Mazrooei, Amirhossein; Sinah, Tusshar; Sankarasubramanian, A.; Kumar, Sujay V.; Peters-Lidard, Christa D.

2015-01-01

Seasonal streamflow forecasts, contingent on climate information, can be utilized to ensure water supply for multiple uses including municipal demands, hydroelectric power generation, and for planning agricultural operations. However, uncertainties in the streamflow forecasts pose significant challenges in their utilization in real-time operations. In this study, we systematically decompose various sources of errors in developing seasonal streamflow forecasts from two Land Surface Models (LSMs) (Noah3.2 and CLM2), which are forced with downscaled and disaggregated climate forecasts. In particular, the study quantifies the relative contributions of the sources of errors from LSMs, climate forecasts, and downscaling/disaggregation techniques in developing seasonal streamflow forecast. For this purpose, three month ahead seasonal precipitation forecasts from the ECHAM4.5 general circulation model (GCM) were statistically downscaled from 2.8deg to 1/8deg spatial resolution using principal component regression (PCR) and then temporally disaggregated from monthly to daily time step using kernel-nearest neighbor (K-NN) approach. For other climatic forcings, excluding precipitation, we considered the North American Land Data Assimilation System version 2 (NLDAS-2) hourly climatology over the years 1979 to 2010. Then the selected LSMs were forced with precipitation forecasts and NLDAS-2 hourly climatology to develop retrospective seasonal streamflow forecasts over a period of 20 years (1991-2010). Finally, the performance of LSMs in forecasting streamflow under different schemes was analyzed to quantify the relative contribution of various sources of errors in developing seasonal streamflow forecast. Our results indicate that the most dominant source of errors during winter and fall seasons is the errors due to ECHAM4.5 precipitation forecasts, while temporal disaggregation scheme contributes to maximum errors during summer season.

Selective Tree-ring Models: A Novel Method for Reconstructing Streamflow Using Tree Rings

NASA Astrophysics Data System (ADS)

Foard, M. B.; Nelson, A. S.; Harley, G. L.

2017-12-01

Surface water is among the most instrumental and vulnerable resources in the Northwest United States (NW). Recent observations show that overall water quantity is declining in streams across the region, while extreme flooding events occur more frequently. Historical streamflow models inform probabilities of extreme flow events (flood or drought) by describing frequency and duration of past events. There are numerous examples of tree-rings being utilized to reconstruct streamflow in the NW. These models confirm that tree-rings are highly accurate at predicting streamflow, however there are many nuances that limit their applicability through time and space. For example, most models predict streamflow from hydrologically altered rivers (e.g. dammed, channelized) which may hinder our ability to predict natural prehistoric flow. They also have a tendency to over/under-predict extreme flow events. Moreover, they often neglect to capture the changing relationships between tree-growth and streamflow over time and space. To address these limitations, we utilized national tree-ring and streamflow archives to investigate the relationships between the growth of multiple coniferous species and free-flowing streams across the NW using novel species-and site-specific streamflow models - a term we coined"selective tree-ring models." Correlation function analysis and regression modeling were used to evaluate the strengths and directions of the flow-growth relationships. Species with significant relationships in the same direction were identified as strong candidates for selective models. Temporal and spatial patterns of these relationships were examined using running correlations and inverse distance weighting interpolation, respectively. Our early results indicate that (1) species adapted to extreme climates (e.g. hot-dry, cold-wet) exhibit the most consistent relationships across space, (2) these relationships weaken in locations with mild climatic variability, and (3) some species appear to be strong candidates for predicting high flow events, while others may be better at pridicting drought. These findings indicate that selective models may outperform traditional models when reconstructing distinctive aspects of streamflow.

Streamflow statistics for development of water rights claims for the Jarbidge Wild and Scenic River, Owyhee Canyonlands Wilderness, Idaho, 2013-14: a supplement to Scientific Investigations Report 2013-5212

USGS Publications Warehouse

Wood, Molly S.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the Bureau of Land Management (BLM), estimated streamflow statistics for stream segments designated “Wild,” “Scenic,” or “Recreational” under the National Wild and Scenic Rivers System in the Owyhee Canyonlands Wilderness in southwestern Idaho. The streamflow statistics were used by the BLM to develop and file a draft, federal reserved water right claim to protect federally designated “outstanding remarkable values” in the Jarbidge River. The BLM determined that the daily mean streamflow equaled or exceeded 20, 50, and 80 percent of the time during bimonthly periods (two periods per month) and the bankfull (66.7-percent annual exceedance probability) streamflow are important thresholds for maintaining outstanding remarkable values. Although streamflow statistics for the Jarbidge River below Jarbidge, Nevada (USGS 13162225) were published previously in 2013 and used for the draft water right claim, the BLM and USGS have since recognized the need to refine streamflow statistics given the approximate 40 river mile distance and intervening tributaries between the original point of estimation (USGS 13162225) and at the mouth of the Jarbidge River, which is the downstream end of the Wild and Scenic River segment. A drainage-area-ratio method was used in 2013 to estimate bimonthly exceedance probability streamflow statistics at the mouth of the Jarbidge River based on available streamgage data on the Jarbidge and East Fork Jarbidge Rivers. The resulting bimonthly streamflow statistics were further adjusted using a scaling factor calculated from a water balance on streamflow statistics calculated for the Bruneau and East Fork Bruneau Rivers and Sheep Creek. The final, adjusted bimonthly exceedance probability and bankfull streamflow statistics compared well with available verification datasets (including discrete streamflow measurements made at the mouth of the Jarbidge River) and are considered the best available estimates for streamflow statistics in the Jarbidge Wild and Scenic River segment.

User's Guide, software for reduction and analysis of daily weather and surface-water data: Tools for time series analysis of precipitation, temperature, and streamflow data

USGS Publications Warehouse

Hereford, Richard

2006-01-01

The software described here is used to process and analyze daily weather and surface-water data. The programs are refinements of earlier versions that include minor corrections and routines to calculate frequencies above a threshold on an annual or seasonal basis. Earlier versions of this software were used successfully to analyze historical precipitation patterns of the Mojave Desert and the southern Colorado Plateau regions, ecosystem response to climate variation, and variation of sediment-runoff frequency related to climate (Hereford and others, 2003; 2004; in press; Griffiths and others, 2006). The main program described here (Day_Cli_Ann_v5.3) uses daily data to develop a time series of various statistics for a user specified accounting period such as a year or season. The statistics include averages and totals, but the emphasis is on the frequency of occurrence in days of relatively rare weather or runoff events. These statistics are indices of climate variation; for a discussion of climate indices, see the Climate Research Unit website of the University of East Anglia (http://www.cru.uea.ac.uk/projects/stardex/) and the Climate Change Indices web site (http://cccma.seos.uvic.ca/ETCCDMI/indices.html). Specifically, the indices computed with this software are the frequency of high intensity 24-hour rainfall, unusually warm temperature, and unusually high runoff. These rare, or extreme events, are those greater than the 90th percentile of precipitation, streamflow, or temperature computed for the period of record of weather or gaging stations. If they cluster in time over several decades, extreme events may produce detectable change in the physical landscape and ecosystem of a given region. Although the software has been tested on a variety of data, as with any software, the user should carefully evaluate the results with their data. The programs were designed for the range of precipitation, temperature, and streamflow measurements expected in the semiarid Southwest United States. The user is encouraged to review the examples provided with the software. The software is written in Fortran 90 with Fortran 95 extensions and was compiled with the Digital Visual Fortran compiler version 6.6. The executables run on Windows 2000 and XP, and they operate in a MS-DOS console window that has only very simple graphical options such as font size and color, background color, and size of the window. Error trapping was not written into the programs. Typically, when an error occurs, the console window closes without a message.

Floods of Selected Streams in Arkansas, Spring 2008

USGS Publications Warehouse

Funkhouser, Jaysson E.; Eng, Ken

2009-01-01

Floods can cause loss of life and extensive destruction to property. Monitoring floods and understanding the reasons for their occurrence are the responsibility of many Federal agencies. The National Weather Service, the U.S. Army Corps of Engineers, and the U.S. Geological Survey are among the most visible of these agencies. Together, these three agencies collect and analyze floodflow information to better understand the variety of mechanisms that cause floods, and how the characteristics and frequencies of floods vary with time and location. The U.S. Geological Survey (USGS) has monitored and assessed the quantity of streamflow in our Nation's streams since the agency's inception in 1879. Because of ongoing collection and assessment of streamflow data, the USGS can provide information about a range of surface-water issues including the suitability of water for public supply and irrigation and the effects of agriculture and urbanization on streamflow. As part of its streamflow-data collection activities, the USGS measured streamflow in multiple streams during extreme flood events in Arkansas in the spring of 2008. The analysis of streamflow information collected during flood events such as these provides a scientific basis for decision making related to resource management and restoration. Additionally, this information can be used by water-resource managers to better define flood-hazard areas and to design bridges, culverts, dams, levees, and other structures. Water levels (stage) and streamflow (discharge) currently are being monitored in near real-time at approximately 150 locations in Arkansas. The streamflow-gaging stations measure and record hydrologic data at 15-minute or hourly intervals; the data then are transmitted through satellites to the USGS database and displayed on the internet every 1 to 4 hours. Streamflow-gaging stations in Arkansas are part of a network of over 7,500 active streamflow-gaging stations operated by the USGS throughout the United States in cooperation with other Federal, State, and local government agencies. In Arkansas, the major supporters of the streamflow-gaging network are the U.S. Army Corps of Engineers, Arkansas Natural Resources Commission, Arkansas Department of Environmental Quality, and Arkansas Geological Survey. Many other Federal, State, and local government entities provide additional support for streamflow-gaging stations. It is the combined support of the USGS and all funding partners that make it possible to maintain an adequate streamflow-gaging network in Arkansas. Data collected over the years at streamflow-gaging stations can be used to characterize the relative magnitude of flood events and their statistical frequency of occurrence. These analyses provide water-resource managers with accurate and reliable hydrologic information based on present and historical flow conditions. Continued collection of streamflow data, with consideration of changes in land use, agricultural practices, and climate change, will help scientists to more accurately characterize the magnitude of extreme floods in the future.

Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction

NASA Technical Reports Server (NTRS)

Su, Fengge; Gao, Huilin; Huffman, George J.; Lettenmaier, Dennis P.

2010-01-01

We investigate the potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product, and through evaluation of streamflow simulations over four tributaries of La Plata Basin (LPB) in South America using the two precipitation products. Our assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February, 2005 which include use of additional microwave sensors (AMSR-E and AMSU-B) and implementation of different calibration schemes. Our work suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.

Water-quality trend analysis and sampling design for streams in the Red River of the North Basin, Minnesota, North Dakota, and South Dakota, 1970-2001

USGS Publications Warehouse

Vecchia, Aldo V.

2005-01-01

The Bureau of Reclamation is considering several alternatives to meet the future municipal, rural, and industrial water-supply needs in the Red River of the North (Red River) Basin, and an environmental impact statement is being prepared to evaluate the potential effects of the various alternatives on the water quality and aquatic health in the basin in relation to the historical variability of streamflow and constituent concentration. Therefore, a water-quality trend analysis was needed to determine the amount of natural water-quality variability that can be expected to occur in the basin, to determine if significant water-quality changes have occurred as a result of human activities, to explore potential causal mechanisms for water-quality changes, and to establish a baseline from which to monitor future water-quality trends. This report presents the results of a study conducted by the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, to analyze historical water-quality trends in two dissolved major ions, dissolved solids, three nutrients, and two dissolved trace metals for nine streamflow-gaging stations in the basin. Annual variability in streamflow in the Red River Basin was high during the trend-analysis period (1970-2001). The annual variability affects constituent concentrations in individual tributaries to the Red River and, in turn, affects constituent concentrations in the main stem of the Red River because of the relative streamflow contribution from the tributaries to the main stem. Therefore, an annual concentration anomaly, which is an estimate of the interannual variability in concentration that can be attributed to long-term variability in streamflow, was used to analyze annual streamflow-related variability in constituent concentrations. The concentration trend is an estimate of the long-term systematic changes in concentration that are unrelated to seasonal or long-term variability in streamflow. Concentrations that have both the seasonal and annual variability removed are called standardized concentrations. Numerous changes that could not be attributed to natural streamflow-related variability occurred in the standardized concentrations during the trend-analysis period. During various times from the late 1970's to the mid-1990's, significant increases occurred in standardized dissolved sulfate, dissolved chloride, and dissolved- solids concentrations for eight of the nine stations for which water-quality trends were analyzed. Significant increases also occurred from the early 1980's to the mid-1990's for standardized dissolved nitrite plus nitrate concentrations for the main-stem stations. The increasing concentrations for the main-stem stations indicate the upward trends may have been caused by human activities along the main stem of the Red River. Significant trends for standardized total ammonia plus organic nitrogen concentrations occurred for most stations. The fitted trends for standardized total phosphorus concentrations for one tributary station increased from the late 1970's to the early 1980's and decreased from the early 1980's to the mid-1990's. Small but insignificant increases occurred for two main-stem stations. No trends were detected for standardized dissolved iron or dissolved manganese concentrations. However, the combination of extreme high-frequency variability, few data, and the number of censored values may have disguised the streamflow-related variability for iron. The time-series model used to detect historical concentration trends also was used to evaluate sampling designs to monitor future water-quality trends. Various sampling designs were evaluated with regard to their sensitivity to detect both annual and seasonal trends during three 4-month seasons. A reasonable overall design for detecting trends for all stations and constituents consisted of eight samples per year, with monthly sampling from April to August and bimonthly sampling from October to February.

Streamflow characteristics of a naturally drained forested watershed in southeast Atlantic coastal plain

Treesearch

Devendra M. Amatya; Carl C. Trettin

2010-01-01

Information about streamflow characteristics e.g. runoff-rainfall (R/O) ratio, rate and timing of flow, surface and subsurface drainage (SSD), and response time to rainfall events is necessary to accurately simulate fluxes and for designing best management practices (BMPs). Unfortunately, those data are scarce in the southeastern Atlantic coastal plain, a highly...

Water resources data, Puerto Rico and the U.S. Virgin Islands, water year 2004

USGS Publications Warehouse

Figueroa-Alamo, Carlos; Aquino, Zaida; Guzman-Rios, Senen; Sanchez, Ana V.

2006-01-01

The Caribbean Water Science Center of the U.S. Geological Survey (USGS), in cooperation with local and Federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 89 streamflow-gaging stations, daily sediment records for 13 sediment stations, stage records for 18 reservoirs, and (2) water-quality records for 20 streamflow-gaging stations, and for 38 ungaged stream sites, 13 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 72 observation wells. Water-resources data for Puerto Rico for calendar years 1958-67 were released in a series of reports entitled 'Water Records of Puerto Rico.' Water-resources data for the U.S. Virgin Islands for the calendar years 1962-69 were released in a report entitled 'Water Records of U.S. Virgin Islands.' Included were records of streamflow, ground-water levels, and water-quality data for both surface and ground water. Beginning with the 1968 calendar year, surface-water records for Puerto Rico were released separately on an annual basis. Ground-water level records and water-quality data for surface and ground water were released in companion reports covering periods of several years. Data for the 1973-74 reports were published under separate covers. Water-resources data reports for 1975 to 2003 water years consist of one volume each and contain data for streamflow, water quality, and ground water.

Regional Frequency Analysis of Annual Maximum Streamflow in Gipuzkoa (Spain)

NASA Astrophysics Data System (ADS)

Erro, J.; López, J. J.

2012-04-01

Extreme streamflow events have been an important cause of recent flooding in Gipuzkoa, and any change in the magnitude of such events may have severe impacts upon urban structures such as dams, urban drainage systems and flood defences, and cause failures to occur. So a regional frequency analysis of annual maximum streamflow was developed for Gipuzkoa, using the well known L-moments approach together with the index-flood procedure, and following the four steps that characterize it: initial screening of the data, identification of homogeneous regions, choice of the appropriate frequency distribution and estimation of quantiles for different return periods. The preliminary study, completed in 2009, was based on the observations recorded at 22 stations distributed throughout the area. A primary filtering of the data revealed the absence of jumps, inconsistencies and changes in trends within the series, and the discordancy measures showed that none of the sites used in the analysis had to be considered discordant with the others. Regionalization was performed by cluster analysis, grouping the stations according to eight physical site characteristics: latitude, longitude, drainage basin area, elevation, main channel length of the basin, slope, annual mean rainfall and annual maximum rainfall. It resulted in two groups - one cluster with the 18 sites of small-medium basin area, and a second cluster with the 4 remaining sites of major basin area - in which the homogeneity criteria were tested and satisfied. However, the short lenght of the series together with the introduction of the observations of 2010 and the inclusion of a historic extreme streamflow event occurred in northern Spain in November 2011, completely changed the results. With this consideration and adjustment, all Gipuzkoa could be treated as a homogeneus region. The goodness-of-fit measures indicated that Generalized Logistic (GLO) is the only suitable distribution to characterize Gipuzkoa. Using the regional L-moment algorithm, quantiles associated with return periods of interest were estimated, and Monte Carlo simulation was used to compute RMSE, bias and error bounds for the estimates.

Streamflow properties from time series of surface velocity and stage

USGS Publications Warehouse

Plant, W.J.; Keller, W.C.; Hayes, K.; Spicer, K.

2005-01-01

Time series of surface velocity and stage have been collected simultaneously. Surface velocity was measured using an array of newly developed continuous-wave microwave sensors. Stage was obtained from the standard U.S. Geological Survey (USGS) measurements. The depth of the river was measured several times during our experiments using sounding weights. The data clearly showed that the point of zero flow was not the bottom at the measurement site, indicating that a downstream control exists. Fathometer measurements confirmed this finding. A model of the surface velocity expected at a site having a downstream control was developed. The model showed that the standard form for the friction velocity does not apply to sites where a downstream control exists. This model fit our measured surface velocity versus stage plots very well with reasonable values of the parameters. Discharges computed using the surface velocities and measured depths matched the USGS rating curve for the site. Values of depth-weighted mean velocities derived from our data did not agree with those expected from Manning's equation due to the downstream control. These results suggest that if real-time surface velocities were available at a gauging station, unstable stream beds could be monitored. Journal of Hydraulic Engineering ?? ASCE.

Reconstructed streamflow in the eastern United States: validity, drivers, and challenges

NASA Astrophysics Data System (ADS)

Maxwell, S.; Harley, G. L.; Maxwell, J. T.; Rayback, S. A.; Pederson, N.; Cook, E. R.; Barclay, D. J.; Li, W.; Rayburn, J. A.

2015-12-01

Tree-ring reconstructions of streamflow are uncommon in the eastern US compared to the western US. While the eastern US does not experience severe drought on the scale of the west, multi-year droughts have stressed the water management systems throughout the east. Here, we reconstruct three rivers serving population centers in the northeast (Beaver Kill River serving New York City, NY), mid-Atlantic (Potomac River serving Washington, D.C.), and southeast (Flint River serving Atlanta, GA) to demonstrate the ability to reconstruct in the eastern US. Then, we conducted an interbasin comparison to identify periods of common variability and examined synoptic scale drivers of drought and pluvial events. Finally, we discuss the utility of multi-species reconstructions in the moist, biodiverse eastern US. Our calibration models explained 66 - 68% of the variance in the instrumental record and passed verification tests in all basins to 1675 CE. Drought and pluvial events showed some synchrony across all basins but the mid-Atlantic acted as a hinge, sometimes behaving more like the northeast, and other times like the southeast. Weak correlations with oceanic-atmospheric oscillations made identification of synoptic scale drivers difficult. However, there appears to be a relationship between the position of the western ridge of the North Atlantic Subtropical High and streamflow across the basins of the east. Given the many factors influencing tree growth in closed canopy systems, we have shown that careful standardization of individual tree-ring series, nested regression models, and the use of multiple species can produce robust proxies in the east.

Use of flow-normalization to evaluate nutrient concentration and flux changes in Lake Champlain tributaries, 1990-2009

USGS Publications Warehouse

Medalie, Laura; Hirsch, Robert M.; Archfield, Stacey A.

2012-01-01

The U.S. Geological Survey evaluated 20 years of total phosphorus (P) and total nitrogen (N) concentration data for 18 Lake Champlain tributaries using a new statistical method based on weighted regressions to estimate daily concentration and flux histories based on discharge, season, and trend as explanatory variables. The use of all the streamflow discharge values for a given date in the record, in a process called "flow-normalization," removed the year-to-year variation due to streamflow and generated a smooth time series from which trends were calculated. This approach to data analysis can be of great value to evaluations of the success of restoration efforts because it filters out the large random fluctuations in the flux that are due to the temporal variability in streamflow. Results for the full 20 years of record showed a mixture of upward and downward trends for concentrations and yields of P and N. When the record was broken into two 10-year periods, for many tributaries, the more recent period showed a reversal in N from upward to downward trends and a similar reversal or reduction in magnitude of upward trends for P. Some measures of P and N concentrations and yields appear to be related to intensity of agricultural activities, point-source loads of P, or population density. Total flow-normalized P flux aggregated from the monitored tributaries showed a decrease of 30 metric tons per year from 1991 to 2009, which is about 15% of the targeted reduction established by the operational management plan for the Lake Champlain Basin.

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA) on Streamflow

PubMed Central

Tague, Christina L.; Moritz, Max A.

2016-01-01

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada. PMID:27575592

Effect of Tree-to-Shrub Type Conversion in Lower Montane Forests of the Sierra Nevada (USA) on Streamflow.

PubMed

Bart, Ryan R; Tague, Christina L; Moritz, Max A

2016-01-01

Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada.

Streamflow depletion by wells--Understanding and managing the effects of groundwater pumping on streamflow

USGS Publications Warehouse

Barlow, Paul M.; Leake, Stanley A.

2012-11-02

Groundwater is an important source of water for many human needs, including public supply, agriculture, and industry. With the development of any natural resource, however, adverse consequences may be associated with its use. One of the primary concerns related to the development of groundwater resources is the effect of groundwater pumping on streamflow. Groundwater and surface-water systems are connected, and groundwater discharge is often a substantial component of the total flow of a stream. Groundwater pumping reduces the amount of groundwater that flows to streams and, in some cases, can draw streamflow into the underlying groundwater system. Streamflow reductions (or depletions) caused by pumping have become an important water-resource management issue because of the negative impacts that reduced flows can have on aquatic ecosystems, the availability of surface water, and the quality and aesthetic value of streams and rivers. Scientific research over the past seven decades has made important contributions to the basic understanding of the processes and factors that affect streamflow depletion by wells. Moreover, advances in methods for simulating groundwater systems with computer models provide powerful tools for estimating the rates, locations, and timing of streamflow depletion in response to groundwater pumping and for evaluating alternative approaches for managing streamflow depletion. The primary objective of this report is to summarize these scientific insights and to describe the various field methods and modeling approaches that can be used to understand and manage streamflow depletion. A secondary objective is to highlight several misconceptions concerning streamflow depletion and to explain why these misconceptions are incorrect.

Benefits of prescribed flows for salmon smolt survival enhancement vary longitudinally in a highly managed river system

USGS Publications Warehouse

Courter, Ian; Garrison, Thomas; Kock, Tobias J.; Perry, Russell W.; Child, David; Hubble, Joel

2016-01-01

The influence of streamflow on survival of emigrating juvenile Pacific salmonids Oncorhynchus spp. (smolts) is a major concern for water managers throughout the northeast Pacific Rim. However, few studies have quantified flow effects on smolt survival, and available information does not indicate a consistent flow–survival relationship within the typical range of flows under management control. In the Yakima Basin, Washington, the potential effects of streamflow alterations on smolt survival have been debated for over 20 years. Using a series of controlled flow releases from upper basin reservoirs and radiotelemetry, we quantified the relationship between flow and yearling Chinook salmon smolt survival in the 208 km reach between Roza Dam and the Yakima River mouth. A multistate mark–recapture model accounted for weekly variation in flow conditions experienced by tagged fish in four discrete river segments. Smolt survival was significantly associated with streamflow in the Roza Reach [river kilometre (rkm) 208–189] and marginally associated with streamflow in the Sunnyside Reach (rkm 169–77). However, smolt survival was not significantly associated with flow in the Naches and Prosser Reaches (rkm 189–169 and rkm 77–3). This discrepancy indicates potential differences in underlying flow-related survival mechanisms, such as predation or passage impediments. Our results clarify trade-offs between flow augmentation for fisheries enhancement and other beneficial uses, and our study design provides a framework for resolving uncertainties about streamflow effects on migratory fish survival in other river systems. 

Integrated meteorological and hydrological drought model: A management tool for proactive water resources planning of semi-arid regions

NASA Astrophysics Data System (ADS)

Rad, Arash Modaresi; Ghahraman, Bijan; Khalili, Davar; Ghahremani, Zahra; Ardakani, Samira Ahmadi

2017-09-01

Conventionally, drought analysis has been limited to single drought category. Utilization of models incorporating multiple drought categories, can relax this limitation. A copula-based model is proposed, which uses meteorological and hydrological drought characteristics to assess drought events for ultimate management of water resources, at small scales, i.e., sub-watersheds. The chosen study area is a sub-basin located at Karkheh watershed (western Iran), with five raingauge stations and one hydrometric station, located upstream and at the outlet, respectively, which represent 41-year of data. Prior to drought analysis, time series of precipitation and streamflow records are investigated for possible dependency/significant trend. Considering semi-arid nature of the study area, boxplots are utilized to graphically capture the rainy months, which are used to evaluate the degree of correlation between streamflow and precipitation records via nonparametric correlations. Time scales of 3- and 12-month are considered, which are used to study vulnerability of early vegetation establishment and long-term ecosystem resilience, respectively. Among four common goodness of fit (GOF) tests, Anderson-Darling is found preferable for defining copula distribution functions through GOF measures, i.e., Akaike and Bayesian information criteria and normalized root mean square error. Furthermore, a GOF method is proposed to evaluate the uncertainty associated with different copula models using the concept of entropy. A new bivariate drought modeling approach is proposed through copulas. The proposed index named standardized precipitation-streamflow index (SPSI) unlike common indices which are used in conjunction with station data, can be applied on a regional basis. SPDI is compared with widely applied streamflow drought index (SDI) and standardized precipitation index (SPI). To assess the homogeneity of the dependence structure of SPSI regionally, Kendall-τ and upper tail coefficient relation is investigated for all stations located within the region. According to results, SPSI similar to nonparametric multivariate standardized drought index (NMSDI) was able to detect both onset of droughts dominated by precipitation as is similarly indicated by SPI and persistence of droughts dominated by streamflow as is similarly indicated by SDI. It also captures discordant case of normal period precipitation with dry period streamflow and vice versa. This makes SPSI a powerful tool for estimating a more practical and realistic drought condition. Finally, combination of severity-duration-frequency (SDF) of drought events through copulas resulted in SDF curves that can be used to obtain the recurrence of extreme droughts and assess drought related ecosystem failure or to aid in optimization of water resources allocation. Results indicated that the newly proposed index (SPSI) is able to represent two main characteristics of meteorological and hydrological drought (drought onset and persistency) and also providing an accurate estimation of the recurrence interval of extreme droughts. The procedures can be used to undertake proactive water resource management and planning to assure water security and sustainable agriculture and ecosystem survival for regions experiencing extreme droughts.

Floods of April 1979, Mississippi, Alabama, and Georgia

USGS Publications Warehouse

Edelen, G.W.; Wilson, K.V.; Harkins, J.R.; Miller, J.F.; Chin, E.H.

1986-01-01

A major storm April 11-13, 1979, following a series of storms in March and April, brought large amounts of rainfall over southeastern United States. Heaviest rain fell over north-central Mississippi and Alabama. A maximum of 21.5 inches was observed at Louisville, 14 SE, Mississippi. Floods in Mississippi and Alabama were the maximum of record at 60 streamflow gaging stations in the Coosa, Alabama, Tombigbee, Chickasawhay, Pearl, and Big Black River basins. On the Pearl River, peak discharges at main stem gaging stations generally approached or exceeded those of the great flood of 1874, and recurrence intervals generally were greater than 100 years. Nine lives were reported lost. Estimated damages totaled nearly $400 million. Seventeen thousand people were driven from their homes in Jackson, Mississippi. This report presents analyses of the meterological settings of the storms, summaries of flood stages and discharges at 221 streamflow gaging stations, stages and contents of 10 reservoirs, flood-crest stages and hydrograph data consisting of gage height, discharge, and accumulated runoff at selected times, at 46 gaging stations, groundwater fluctuations in 11 observation wells, and water salinity and temperature at 22 sites along the Intracoastal Waterway in Mobile Bay. (USGS)

Elevated streamflows increase dam passage by juvenile coho salmon during winter: Implications of climate change in the Pacific Northwest

USGS Publications Warehouse

Kock, Tobias J.; Liedtke, Theresa L.; Rondorf, Dennis W.; Serl, John D.; Kohn, Mike; Bumbaco, Karin A.

2012-01-01

A 4-year evaluation was conducted to determine the proportion of juvenile coho salmon Oncorhynchus kisutch passing Cowlitz Falls Dam, on the Cowlitz River, Washington, during winter. River and reservoir populations of coho salmon parr were monitored using radiotelemetry to determine if streamflow increases resulted in increased downstream movement and dam passage. This was of interest because fish that pass downstream of Cowlitz Falls Dam become landlocked in Riffe Lake and are lost to the anadromous population. Higher proportions of reservoir-released fish (0.391-0.480) passed Cowlitz Falls Dam than did river-released fish (0.037-0.119). Event-time analyses demonstrated that streamflow increases were important predictors of dam passage rates during the study. The estimated effect of increasing streamflows on the risk of dam passage varied annually and ranged from 9% to 75% for every 28.3 m3/s increase in streamflow. These results have current management implications because they demonstrate the significance of dam passage by juvenile coho salmon during winter months when juvenile fish collection facilities are typically not operating. The results also have future management implications because climate change predictions suggest that peak streamflow timing for many watersheds in the Pacific Northwest will shift from late spring and early summer to winter. Increased occurrence of intense winter flood events is also expected. Our results demonstrate that juvenile coho salmon respond readily to streamflow increases and initiate downstream movements during winter months, which could result in increased passage at dams during these periods if climate change predictions are realized in the coming decades.

Recent water quality trends in a typical semi-arid river with a sharp decrease in streamflow and construction of sewage treatment plants

NASA Astrophysics Data System (ADS)

Cheng, Peng; Li, Xuyong; Su, Jingjun; Hao, Shaonan

2018-01-01

Identification of the interactive responses of water quantity and quality to changes in nature and human stressors is important for the effective management of water resources. Many studies have been conducted to determine the influence of these stressors on river discharge and water quality. However, there is little information about whether sewage treatment plants can improve water quality in a region where river streamflow has decreased sharply. In this study, a seasonal trend decomposition method was used to analyze long-term (1996-2015) and seasonal trends in the streamflow and water quality of the Guanting Reservoir Basin, which is located in a semi-arid region of China. The results showed that the streamflow in the Guanting Reservoir Basin decreased sharply from 1996-2000 due to precipitation change and human activities (human use and reservoir regulation), while the streamflow decline over the longer period of time (1996-2015) could be attributed to human activities. During the same time, the river water quality improved significantly, having a positive relationship with the capacity of wastewater treatment facilities. The water quality in the Guanting Reservoir showed a deferred response to the reduced external loading, due to internal loading from sediments. These results implied that for rivers in which streamflow has declined sharply, the water quality could be improved significantly by actions to control water pollution control. This study not only provides useful information for water resource management in the Guanting Reservoir Basin, but also supports the implementation of water pollution control measures in other rivers with a sharp decline in streamflow.

Simulation of streamflow, evapotranspiration, and groundwater recharge in the lower San Antonio River Watershed, South-Central Texas, 2000-2007

USGS Publications Warehouse

Lizarraga, Joy S.; Ockerman, Darwin J.

2010-01-01

The U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, the Evergreen Underground Water Conservation District, and the Goliad County Groundwater Conservation District, configured, calibrated, and tested a watershed model for a study area consisting of about 2,150 square miles of the lower San Antonio River watershed in Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties in south-central Texas. The model simulates streamflow, evapotranspiration (ET), and groundwater recharge using rainfall, potential ET, and upstream discharge data obtained from National Weather Service meteorological stations and USGS streamflow-gaging stations. Additional time-series inputs to the model include wastewater treatment-plant discharges, withdrawals for cropland irrigation, and estimated inflows from springs. Model simulations of streamflow, ET, and groundwater recharge were done for 2000-2007. Because of the complexity of the study area, the lower San Antonio River watershed was divided into four subwatersheds; separate HSPF models were developed for each subwatershed. Simulation of the overall study area involved running simulations of the three upstream models, then running the downstream model. The surficial geology was simplified as nine contiguous water-budget zones to meet model computational limitations and also to define zones for which ET, recharge, and other water-budget information would be output by the model. The model was calibrated and tested using streamflow data from 10 streamflow-gaging stations; additionally, simulated ET was compared with measured ET from a meteorological station west of the study area. The model calibration is considered very good; streamflow volumes were calibrated to within 10 percent of measured streamflow volumes. During 2000-2007, the estimated annual mean rainfall for the water-budget zones ranged from 33.7 to 38.5 inches per year; the estimated annual mean rainfall for the entire watershed was 34.3 inches. Using the HSPF model it was estimated that for 2000-2007, less than 10 percent of the annual mean rainfall on the study watershed exited the watershed as streamflow, whereas about 82 percent, or an average of 28.2 inches per year, exited the watershed as ET. Estimated annual mean groundwater recharge for the entire study area was 3.0 inches, or about 9 percent of annual mean rainfall. Estimated annual mean recharge was largest in water-budget zone 3, the zone where the Carrizo Sand outcrops. In water-budget zone 3, the estimated annual mean recharge was 5.1 inches or about 15 percent of annual mean rainfall. Estimated annual mean recharge was smallest in water-budget zone 6, about 1.1 inches or about 3 percent of annual mean rainfall. The Cibolo Creek subwatershed and the subwatershed of the San Antonio River upstream from Cibolo Creek had the largest and smallest basin yields, about 4.8 inches and 1.2 inches, respectively. Estimated annual ET and annual recharge generally increased with increasing annual rainfall. Also, ET was larger in zones 8 and 9, the most downstream zones in the watershed. Model limitations include possible errors related to model conceptualization and parameter variability, lack of data to quantify certain model inputs, and measurement errors. Uncertainty regarding the degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error.

User's manual for SEDCALC, a computer program for computation of suspended-sediment discharge

USGS Publications Warehouse

Koltun, G.F.; Gray, John R.; McElhone, T.J.

1994-01-01

Sediment-Record Calculations (SEDCALC), a menu-driven set of interactive computer programs, was developed to facilitate computation of suspended-sediment records. The programs comprising SEDCALC were developed independently in several District offices of the U.S. Geological Survey (USGS) to minimize the intensive labor associated with various aspects of sediment-record computations. SEDCALC operates on suspended-sediment-concentration data stored in American Standard Code for Information Interchange (ASCII) files in a predefined card-image format. Program options within SEDCALC can be used to assist in creating and editing the card-image files, as well as to reformat card-image files to and from formats used by the USGS Water-Quality System. SEDCALC provides options for creating card-image files containing time series of equal-interval suspended-sediment concentrations from 1. digitized suspended-sediment-concentration traces, 2. linear interpolation between log-transformed instantaneous suspended-sediment-concentration data stored at unequal time intervals, and 3. nonlinear interpolation between log-transformed instantaneous suspended-sediment-concentration data stored at unequal time intervals. Suspended-sediment discharge can be computed from the streamflow and suspended-sediment-concentration data or by application of transport relations derived by regressing log-transformed instantaneous streamflows on log-transformed instantaneous suspended-sediment concentrations or discharges. The computed suspended-sediment discharge data are stored in card-image files that can be either directly imported to the USGS Automated Data Processing System or used to generate plots by means of other SEDCALC options.

A New Streamflow-Routing (SFR1) Package to Simulate Stream-Aquifer Interaction with MODFLOW-2000

USGS Publications Warehouse

Prudic, David E.; Konikow, Leonard F.; Banta, Edward R.

2004-01-01

The increasing concern for water and its quality require improved methods to evaluate the interaction between streams and aquifers and the strong influence that streams can have on the flow and transport of contaminants through many aquifers. For this reason, a new Streamflow-Routing (SFR1) Package was written for use with the U.S. Geological Survey's MODFLOW-2000 ground-water flow model. The SFR1 Package is linked to the Lake (LAK3) Package, and both have been integrated with the Ground-Water Transport (GWT) Process of MODFLOW-2000 (MODFLOW-GWT). SFR1 replaces the previous Stream (STR1) Package, with the most important difference being that stream depth is computed at the midpoint of each reach instead of at the beginning of each reach, as was done in the original Stream Package. This approach allows for the addition and subtraction of water from runoff, precipitation, and evapotranspiration within each reach. Because the SFR1 Package computes stream depth differently than that for the original package, a different name was used to distinguish it from the original Stream (STR1) Package. The SFR1 Package has five options for simulating stream depth and four options for computing diversions from a stream. The options for computing stream depth are: a specified value; Manning's equation (using a wide rectangular channel or an eight-point cross section); a power equation; or a table of values that relate flow to depth and width. Each stream segment can have a different option. Outflow from lakes can be computed using the same options. Because the wetted perimeter is computed for the eight-point cross section and width is computed for the power equation and table of values, the streambed conductance term no longer needs to be calculated externally whenever the area of streambed changes as a function of flow. The concentration of solute is computed in a stream network when MODFLOW-GWT is used in conjunction with the SFR1 Package. The concentration of a solute in a stream reach is based on a mass-balance approach and accounts for exchanges with (inputs from or losses to) ground-water systems. Two test examples are used to illustrate some of the capabilities of the SFR1 Package. The first test simulation was designed to illustrate how pumping of ground water from an aquifer connected to streams can affect streamflow, depth, width, and streambed conductance using the different options. The second test simulation was designed to illustrate solute transport through interconnected lakes, streams, and aquifers. Because of the need to examine time series results from the model simulations, the Gage Package first described in the LAK3 documentation was revised to include time series results of selected variables (streamflows, stream depth and width, streambed conductance, solute concentrations, and solute loads) for specified stream reaches. The mass-balance or continuity approach for routing flow and solutes through a stream network may not be applicable for all interactions between streams and aquifers. The SFR1 Package is best suited for modeling long-term changes (months to hundreds of years) in ground-water flow and solute concentrations using averaged flows in streams. The Package is not recommended for modeling the transient exchange of water between streams and aquifers when the objective is to examine short-term (minutes to days) effects caused by rapidly changing streamflows.

Key landscape and biotic indicators of watersheds sensitivity to forest disturbance identified using remote sensing and historical hydrography data

NASA Astrophysics Data System (ADS)

Buma, Brian; Livneh, Ben

2017-07-01

Water is one of the most critical resources derived from natural systems. While it has long been recognized that forest disturbances like fire influence watershed streamflow characteristics, individual studies have reported conflicting results with some showing streamflow increases post-disturbance and others decreases, while other watersheds are insensitive to even large disturbance events. Characterizing the differences between sensitive (e.g. where streamflow does change post-disturbance) and insensitive watersheds is crucial to anticipating response to future disturbance events. Here, we report on an analysis of a national-scale, gaged watershed database together with high-resolution forest mortality imagery. A simple watershed response model was developed based on the runoff ratio for watersheds (n = 73) prior to a major disturbance, detrended for variation in precipitation inputs. Post-disturbance deviations from the expected water yield and streamflow timing from expected (based on observed precipitation) were then analyzed relative to the abiotic and biotic characteristics of the individual watershed and observed extent of forest mortality. The extent of the disturbance was significantly related to change in post-disturbance water yield (p < 0.05), and there were several distinctive differences between watersheds exhibiting post-disturbance increases, decreases, and those showing no change in water yield. Highly disturbed, arid watersheds with low soil: water contact time are the most likely to see increases, with the magnitude positively correlated with the extent of disturbance. Watersheds dominated by deciduous forest with low bulk density soils typically show reduced yield post-disturbance. Post-disturbance streamflow timing change was associated with climate, forest type, and soil. Snowy coniferous watersheds were generally insensitive to disturbance, whereas finely textured soils with rapid runoff were sensitive. This is the first national scale investigation of streamflow post-disturbance using fused gage and remotely sensed data at high resolution, and gives important insights that can be used to anticipate changes in streamflow resulting from future disturbances.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

USGS Publications Warehouse

Long, Andrew J.

2015-01-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

Managing the uncertainties of the streamflow data produced by the French national hydrological services

NASA Astrophysics Data System (ADS)

Puechberty, Rachel; Bechon, Pierre-Marie; Le Coz, Jérôme; Renard, Benjamin

2015-04-01

The French national hydrological services (NHS) manage the production of streamflow time series throughout the national territory. The hydrological data are made available to end-users through different web applications and the national hydrological archive (Banque Hydro). Providing end-users with qualitative and quantitative information on the uncertainty of the hydrological data is key to allow them drawing relevant conclusions and making appropriate decisions. Due to technical and organisational issues that are specific to the field of hydrometry, quantifying the uncertainty of hydrological measurements is still challenging and not yet standardized. The French NHS have made progress on building a consistent strategy to assess the uncertainty of their streamflow data. The strategy consists of addressing the uncertainties produced and propagated at each step of the data production with uncertainty analysis tools that are compatible with each other and compliant with international uncertainty guidance and standards. Beyond the necessary research and methodological developments, operational software tools and procedures are absolutely necessary to the data management and uncertainty analysis by field hydrologists. A first challenge is to assess, and if possible reduce, the uncertainty of streamgauging data, i.e. direct stage-discharge measurements. Interlaboratory experiments proved to be a very efficient way to empirically measure the uncertainty of a given streamgauging technique in given measurement conditions. The Q+ method (Le Coz et al., 2012) was developed to improve the uncertainty propagation method proposed in the ISO748 standard for velocity-area gaugings. Both empirical or computed (with Q+) uncertainty values can now be assigned in BAREME, which is the software used by the French NHS for managing streamgauging measurements. A second pivotal step is to quantify the uncertainty related to stage-discharge rating curves and their application to water level records to produce continuous discharge time series. The management of rating curves is also done using BAREME. The BaRatin method (Le Coz et al., 2014) was developed as a Bayesian approach of rating curve development and uncertainty analysis. Since BaRatin accounts for the individual uncertainties of gauging data used to build the rating curve, it was coupled with BAREME. The BaRatin method is still undergoing development and research, in particular to address non univocal or time-varying stage-discharge relations, due to hysteresis, variable backwater, rating shifts, etc. A new interface including new options is under development. The next steps are now to propagate the uncertainties of water level records, through uncertain rating curves, up to discharge time series and derived variables (e.g. annual mean flow) and statistics (e.g. flood quantiles). Bayesian tools are already available for both tasks but further validation and development is necessary for their integration in the operational data workflow of the French NHS. References Le Coz, J., Camenen, B., Peyrard, X., Dramais, G., 2012. Uncertainty in open-channel discharges measured with the velocity-area method. Flow Measurement and Instrumentation 26, 18-29. Le Coz, J., Renard, B., Bonnifait, L., Branger, F., Le Boursicaud, R., 2014. Combining hydraulic knowledge and uncertain gaugings in the estimation of hydrometric rating curves: a Bayesian approach, Journal of Hydrology, 509, 573-587.

A precipitation-runoff model for analysis of the effects of water withdrawals on streamflow, Ipswich River basin, Massachusetts

USGS Publications Warehouse

Zarriello, Phillip J.; Ries, Kernell G.

2000-01-01

Water withdrawals from the 155-square-mile Ipswich River Basin in northeastern Massachusetts affect aquatic habitat, water quality, and recreational use of the river. To better understand the effects of these withdrawals on streamflow, particularly low flow, the Hydrological Simulation Program-FORTRAN (HSPF) was used to develop a watershed-scale precipitation-runoff model of the Ipswich River to simulate its hydrology and complex water-use patterns.An analytical solution was used to compute time series of streamflow depletions resulting from ground-water withdrawals at wells. The flow depletions caused by pumping from the wells were summed along with any surface-water withdrawals to calculate the total withdrawal along a stream reach. The water withdrawals, records of precipitation, and streamflow records on the Ipswich River at South Middleton and at Ipswich for the period 1989?93 were used to calibrate the model. Model-fit analysis indicates that the simulated flows matched observed flows over a wide range of conditions; at a minimum, the coefficient of model-fit efficiency indicates that the model explained 79 percent of the variance in the observed daily flow.Six alternative water-withdrawal and land-use scenarios were simulated with the model. Three scenarios were examined for the 1989?93 calibration period, and three scenarios were examined for the 1961?95 period to test alternative withdrawals and land use over a wider range of climatic conditions, and to compute 1-, 7-, and 30-day low-flow frequencies using a log-Pearson Type III analysis. Flow-duration curves computed from results of the 1989?93 simulations indicate that, at the South Middleton and Ipswich gaging stations, streamflows when no water withdrawals are being made are nearly identical to streamflows when no ground-water withdrawals are made. Streamflow under no water withdrawals at both stations are about an order of magnitude larger at the 99.8 percent exceedence probability than simulations with only ground-water withdrawals. Long-term simulations indicate that the differences between streamflow with no water withdrawals and average 1989?93 water withdrawals is similar to the difference between simulations for the same water-use conditions made for the 1989?93 period at both sites. The 7-day, 10-year low-flow (7Q10, a widely used regulatory statistic) at the South Middleton station was 4.1 cubic feet per second (ft3/s) with no water withdrawals and 1991 land use, 5.8 ft3/s no withdrawals and undeveloped land, and 0.54 ft3/s with average 1989?93 water withdrawals and 1991 land use. The 7Q10 at the Ipswich station was about 8.3 ft3/s for simulations with no water withdrawals for both the 1991 land use and the undeveloped land conditions, and 2.7 ft3/s for simulations with average 1989?93 water withdrawals and 1991 land use. Simulation results indicate that surface-water withdrawals have little effect on the duration and frequency of low flows, but the cumulative ground-water withdrawals substantially decrease low flows.

A Combined Atmospheric Rivers and Geopotential Height Analysis for the Detection of High Streamflow Event Probability Occurrence in UK and Germany

NASA Astrophysics Data System (ADS)

Rosario Conticello, Federico; Cioffi, Francesco; Lall, Upmanu; Merz, Bruno

2017-04-01

The role of atmospheric rivers (ARs) in inducing High Streamflow Events (HSEs) in Europe has been confirmed by numerous studies. Here, we assume as HSEs the streamflows exceeding the 99th percentile of daily flowrate time series measured at streamflow gauges. Among the indicators of ARs are: the Integrated Water Vapor (IWV) and Integrated Water Vapor Transport (IVT). For both indicators the literature suggests thresholds in order to identify ARs. Furthermore, local thresholds of such indices are used to assess the occurrence of HSEs in a given region. Recent research on ARs still leaves room for open issues: 1) The literature is not unanimous in defining which of the two indicators is better. 2) The selection of the thresholds is based on subjective assessments. 3) The predictability of HSEs at the local scale associated with these indices seems to be weak and to exist only in the winter months. In order to address these issues, we propose an original methodology: (i) to choose between the two indicators which one is the most suitable for HSEs predictions; (ii) to select IWT and/or IVT (IVT/IWV) local thresholds in a more objective way; (iii) to implement an algorithm able to determine whether a IVT/IWV configuration is inducing HSEs, regardless of the season. In pursuing this goal, besides IWV and IVT fields, we introduce as further predictor the geopotential height at 850 hPa (GPH850) field, that implicitly contains information about the pattern of temperature, direction and intensity of the winds. In fact, the introduction of the GPH850 would help to improve the assessment of the occurrence of HSEs throughout the year. It is also plausible to hypothesize, that IVT/IWV local thresholds could vary in dependence of the GPH850 configuration. In this study, we propose a model to statistically relate these predictors, IVT/IWV and GPH850, to the simultaneous occurrence of HSEs in one or more streamflow gauges in UK and Germany. Historical data from 57 streamflow gauges in UK and 61 streamflow gauges in Germany, as well as reanalysis data of the 850 hPa geopotential fields bounded from 90W to 70E and from 20N to 80N are used. The common period is 1960 to 2012. The link between GPH850 and HSEs, and more precisely, the identification of the GPH850 states potentially able to generate HSEs is performed by a combined Kohonen Networks (Self Organized Map, SOM) and Event Syncronization approach. Complex network and modularity methods are used to cluster streamflow gauges that share common GPH850 configurations. Then a model based on a conditional Poisson distribution is carried out, in which the parameter of the Poisson distribution is assumed to be a nonlinear function of GPH850 state and IVT/ IWV. This model allows for the identification of the threshold of IVT/IWV beyond which there is the HSE highest probability.

Hydrologic Conditions in Northwest Florida: 2006 Water Year

USGS Publications Warehouse

Verdi, Richard Jay

2007-01-01

Introduction National data for streamflow, ground-water levels, and quality of water for the 2006 water year are accessible to the public on the U.S. Geological Survey's (USGS) Site Information Management System (SIMS) website http://web10capp.er.usgs.gov/adr06_lookup/search.jsp. This fact sheet describes data and hydrologic conditions throughout northwest Florida during the 2006 water year (fig. 1), when record-low monthly streamflow conditions were reported at several streamgage locations. Prior to 1960, these data were published in various USGS Water-Supply Papers and included water-related data collected by the USGS during the water year (October 1 to September 30). In 1961, a series of annual reports, 'Water Resources Data-Florida,' was introduced that published surface-water data. In 1964, a similar report was introduced for the purposes of publishing water-quality data. In 1975, the reports were merged to a single volume and were expanded to publish data for surface water, water quality, and ground-water levels. Formal publication of the annual report series was discontinued at the end of the 2005 water year, upon activation of the SIMS website database.

Arkansas StreamStats: a U.S. Geological Survey web map application for basin characteristics and streamflow statistics

USGS Publications Warehouse

Pugh, Aaron L.

2014-01-01

Users of streamflow information often require streamflow statistics and basin characteristics at various locations along a stream. The USGS periodically calculates and publishes streamflow statistics and basin characteristics for streamflowgaging stations and partial-record stations, but these data commonly are scattered among many reports that may or may not be readily available to the public. The USGS also provides and periodically updates regional analyses of streamflow statistics that include regression equations and other prediction methods for estimating statistics for ungaged and unregulated streams across the State. Use of these regional predictions for a stream can be complex and often requires the user to determine a number of basin characteristics that may require interpretation. Basin characteristics may include drainage area, classifiers for physical properties, climatic characteristics, and other inputs. Obtaining these input values for gaged and ungaged locations traditionally has been time consuming, subjective, and can lead to inconsistent results.

User’s guide for the Delaware River Basin Streamflow Estimator Tool (DRB-SET)

USGS Publications Warehouse

Stuckey, Marla H.; Ulrich, James E.

2016-06-09

IntroductionThe Delaware River Basin Streamflow Estimator Tool (DRB-SET) is a tool for the simulation of streamflow at a daily time step for an ungaged stream location in the Delaware River Basin. DRB-SET was developed by the U.S. Geological Survey (USGS) and funded through WaterSMART as part of the National Water Census, a USGS research program on national water availability and use that develops new water accounting tools and assesses water availability at the regional and national scales. DRB-SET relates probability exceedances at a gaged location to those at an ungaged stream location. Once the ungaged stream location has been identified by the user, an appropriate streamgage is automatically selected in DRB-SET using streamflow correlation (map correlation method). Alternately, the user can manually select a different streamgage or use the closest streamgage. A report file is generated documenting the reference streamgage and ungaged stream location information, basin characteristics, any warnings, baseline (minimally altered) and altered (affected by regulation, diversion, mining, or other anthropogenic activities) daily mean streamflow, and the mean and median streamflow. The estimated daily flows for the ungaged stream location can be easily exported as a text file that can be used as input into a statistical software package to determine additional streamflow statistics, such as flow duration exceedance or streamflow frequency statistics.

Analysis of managed aquifer recharge for retiming streamflow in an alluvial river

NASA Astrophysics Data System (ADS)

Ronayne, Michael J.; Roudebush, Jason A.; Stednick, John D.

2017-01-01

Maintenance of low flows during dry periods is critical for supporting ecosystem function in many rivers. Managed aquifer recharge is one method that can be used to augment low flows in rivers that are hydraulically connected to an alluvial groundwater system. In this study, we performed numerical modeling to evaluate a managed recharge operation designed to retime streamflow in the South Platte River, northeastern Colorado (USA). Modeling involved the simulation of spatially and temporally variable groundwater-surface water exchange, as well as streamflow routing in the river. Periodic solutions that incorporate seasonality were developed for two scenarios, a natural base case scenario and an active management scenario that included groundwater pumping and managed recharge. A framework was developed to compare the scenarios by analyzing changes in head-dependent inflows and outflows to/from the aquifer, which was used to interpret the simulated impacts on streamflow. The results clearly illustrate a retiming of streamflow. Groundwater pumping near the river during winter months causes a reduction in streamflow during those months. Delivery of the pumped water to recharge ponds, located further from the river, has the intended effect of augmenting streamflow during low-flow summer months. Higher streamflow is not limited to the target time period, however, which highlights an inefficiency of flow augmentation projects that rely on water retention in the subsurface.

Hazard function theory for nonstationary natural hazards

NASA Astrophysics Data System (ADS)

Read, Laura K.; Vogel, Richard M.

2016-04-01

Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e., that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (X) with its failure time series (T), enabling computation of corresponding average return periods, risk, and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied generalized Pareto model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard random variable X with corresponding failure time series T should have application to a wide class of natural hazards with opportunities for future extensions.

Climate change or climate cycles? Snowpack trends in the Olympic and Cascade Mountains, Washington, USA.

PubMed

Barry, Dwight; McDonald, Shea

2013-01-01

Climate change could significantly influence seasonal streamflow and water availability in the snowpack-fed watersheds of Washington, USA. Descriptions of snowpack decline often use linear ordinary least squares (OLS) models to quantify this change. However, the region's precipitation is known to be related to climate cycles. If snowpack decline is more closely related to these cycles, an OLS model cannot account for this effect, and thus both descriptions of trends and estimates of decline could be inaccurate. We used intervention analysis to determine whether snow water equivalent (SWE) in 25 long-term snow courses within the Olympic and Cascade Mountains are more accurately described by OLS (to represent gradual change), stationary (to represent no change), or step-stationary (to represent climate cycling) models. We used Bayesian information-theoretic methods to determine these models' relative likelihood, and we found 90 models that could plausibly describe the statistical structure of the 25 snow courses' time series. Posterior model probabilities of the 29 "most plausible" models ranged from 0.33 to 0.91 (mean = 0.58, s = 0.15). The majority of these time series (55%) were best represented as step-stationary models with a single breakpoint at 1976/77, coinciding with a major shift in the Pacific Decadal Oscillation. However, estimates of SWE decline differed by as much as 35% between statistically plausible models of a single time series. This ambiguity is a critical problem for water management policy. Approaches such as intervention analysis should become part of the basic analytical toolkit for snowpack or other climatic time series data.

Water Resources Data, Puerto Rico and the U.S. Virgin Islands, Water Year 1999

USGS Publications Warehouse

Diaz, Pedro L.; Aquino, Zaida; Figueroa-Alamo, Carlos; Vachier, Ricardo J.; Sanchez, Ana V.

2000-01-01

The Water Resources Division of the U.S. Geological Survey, in cooperation with local and federal agencies obtains a large amount of data pertaining to the water resources of the Commonwealth of Puerto Rico and the Territory of the U.S. Virgin Islands each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the area. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data for Puerto Rico and the U.S. Virgin Islands, 1999.' This report includes records on both surface and ground water. Specifically, it contains: (1) discharge records for 76 streamflow gaging stations, daily sediment records for 25 streamflow stations, stage records for 18 reservoirs, and (2) water-quality records for 16 streamflow-gaging stations, and for 42 ungaged stream sites, 11 lake sites, 2 lagoons, and 1 bay, and (3) water-level records for 107 observation wells.

Treating pre-instrumental data as "missing" data: using a tree-ring-based paleoclimate record and imputations to reconstruct streamflow in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Ho, M. W.; Lall, U.; Cook, E. R.

2015-12-01

Advances in paleoclimatology in the past few decades have provided opportunities to expand the temporal perspective of the hydrological and climatological variability across the world. The North American region is particularly fortunate in this respect where a relatively dense network of high resolution paleoclimate proxy records have been assembled. One such network is the annually-resolved Living Blended Drought Atlas (LBDA): a paleoclimate reconstruction of the Palmer Drought Severity Index (PDSI) that covers North America on a 0.5° × 0.5° grid based on tree-ring chronologies. However, the use of the LBDA to assess North American streamflow variability requires a model by which streamflow may be reconstructed. Paleoclimate reconstructions have typically used models that first seek to quantify the relationship between the paleoclimate variable and the environmental variable of interest before extrapolating the relationship back in time. In contrast, the pre-instrumental streamflow is here considered as "missing" data. A method of imputing the "missing" streamflow data, prior to the instrumental record, is applied through multiple imputation using chained equations for streamflow in the Missouri River Basin. In this method, the distribution of the instrumental streamflow and LBDA is used to estimate sets of plausible values for the "missing" streamflow data resulting in a ~600 year-long streamflow reconstruction. Past research into external climate forcings, oceanic-atmospheric variability and its teleconnections, and assessments of rare multi-centennial instrumental records demonstrate that large temporal oscillations in hydrological conditions are unlikely to be captured in most instrumental records. The reconstruction of multi-centennial records of streamflow will enable comprehensive assessments of current and future water resource infrastructure and operations under the existing scope of natural climate variability.

Free internet datasets for streamflow modelling using SWAT in the Johor river basin, Malaysia

NASA Astrophysics Data System (ADS)

Tan, M. L.

2014-02-01

Streamflow modelling is a mathematical computational approach that represents terrestrial hydrology cycle digitally and is used for water resources assessment. However, such modelling endeavours require a large amount of data. Generally, governmental departments produce and maintain these data sets which make it difficult to obtain this data due to bureaucratic constraints. In some countries, the availability and quality of geospatial and climate datasets remain a critical issue due to many factors such as lacking of ground station, expertise, technology, financial support and war time. To overcome this problem, this research used public domain datasets from the Internet as "input" to a streamflow model. The intention is simulate daily and monthly streamflow of the Johor River Basin in Malaysia. The model used is the Soil and Water Assessment Tool (SWAT). As input free data including a digital elevation model (DEM), land use information, soil and climate data were used. The model was validated by in-situ streamflow information obtained from Rantau Panjang station for the year 2006. The coefficient of determination and Nash-Sutcliffe efficiency were 0.35/0.02 for daily simulated streamflow and 0.92/0.21 for monthly simulated streamflow, respectively. The results show that free data can provide a better simulation at a monthly scale compared to a daily basis in a tropical region. A sensitivity analysis and calibration procedure should be conducted in order to maximize the "goodness-of-fit" between simulated and observed streamflow. The application of Internet datasets promises an acceptable performance of streamflow modelling. This research demonstrates that public domain data is suitable for streamflow modelling in a tropical river basin within acceptable accuracy.

Changes in snowmelt runoff timing in western North America under a 'business as usual' climate change scenario

USGS Publications Warehouse

Stewart, I.T.; Cayan, D.R.; Dettinger, M.D.

2004-01-01

Spring snowmelt is the most important contribution of many rivers in western North America. If climate changes, this contribution may change. A shift in the timing of springtime snowmelt towards earlier in the year already is observed during 1948-2000 in many western rivers. Streamflow timing changes for the 1995-2099 period are projected using regression relations between observed streamflow-timing responses in each river, measured by the temporal centroid of streamflow (CT) each year, and local temperature (TI) and precipitation (PI) indices. Under 21st century warming trends predicted by the Parallel Climate Model (PCM) under business-as-usual greenhouse-gas emissions, streamflow timing trends across much of western North America suggest even earlier springtime snowmelt than observed to date. Projected CT changes are consistent with observed rates and directions of change during the past five decades, and are strongest in the Pacific Northwest, Sierra Nevada, and Rocky Mountains, where many rivers eventually run 30-40 days earlier. The modest PI changes projected by PCM yield minimal CT changes. The responses of CT to the simultaneous effects of projected TI and PI trends are dominated by the TI changes. Regression-based CT projections agree with those from physically-based simulations of rivers in the Pacific Northwest and Sierra Nevada.

Normal streamflows and water levels continue—Summary of hydrologic conditions in Georgia, 2014

USGS Publications Warehouse

Knaak, Andrew E.; Ankcorn, Paul D.; Peck, Michael F.

2016-03-31

The U.S. Geological Survey (USGS) South Atlantic Water Science Center (SAWSC) Georgia office, in cooperation with local, State, and other Federal agencies, maintains a long-term hydrologic monitoring network of more than 350 real-time, continuous-record, streamflow-gaging stations (streamgages). The network includes 14 real-time lake-level monitoring stations, 72 real-time surface-water-quality monitors, and several water-quality sampling programs. Additionally, the SAWSC Georgia office operates more than 204 groundwater monitoring wells, 39 of which are real-time. The wide-ranging coverage of streamflow, reservoir, and groundwater monitoring sites allows for a comprehensive view of hydrologic conditions across the State. One of the many benefits this monitoring network provides is a spatially distributed overview of the hydrologic conditions of creeks, rivers, reservoirs, and aquifers in Georgia.Streamflow and groundwater data are verified throughout the year by USGS hydrographers and made available to water-resource managers, recreationists, and Federal, State, and local agencies. Hydrologic conditions are determined by comparing the statistical analyses of data collected during the current water year to historical data. Changing hydrologic conditions underscore the need for accurate, timely data to allow informed decisions about the management and conservation of Georgia’s water resources for agricultural, recreational, ecological, and water-supply needs and in protecting life and property.

Real-time demonstration and evaluation of over-the-loop short to medium-range ensemble streamflow forecasting

NASA Astrophysics Data System (ADS)

Wood, A. W.; Clark, E.; Newman, A. J.; Nijssen, B.; Clark, M. P.; Gangopadhyay, S.; Arnold, J. R.

2015-12-01

The US National Weather Service River Forecasting Centers are beginning to operationalize short range to medium range ensemble predictions that have been in development for several years. This practice contrasts with the traditional single-value forecast practice at these lead times not only because the ensemble forecasts offer a basis for quantifying forecast uncertainty, but also because the use of ensembles requires a greater degree of automation in the forecast workflow than is currently used. For instance, individual ensemble member forcings cannot (practically) be manually adjusted, a step not uncommon with the current single-value paradigm, thus the forecaster is required to adopt a more 'over-the-loop' role than before. The relative lack of experience among operational forecasters and forecast users (eg, water managers) in the US with over-the-loop approaches motivates the creation of a real-time demonstration and evaluation platform for exploring the potential of over-the-loop workflows to produce usable ensemble short-to-medium range forecasts, as well as long range predictions. We describe the development and early results of such an effort by a collaboration between NCAR and the two water agencies, the US Army Corps of Engineers and the US Bureau of Reclamation. Focusing on small to medium sized headwater basins around the US, and using multi-decade series of ensemble streamflow hindcasts, we also describe early results, assessing the skill of daily-updating, over-the-loop forecasts driven by a set of ensemble atmospheric outputs from the NCEP GEFS for lead times from 1-15 days.

Climate and streamflow characteristics for selected streamgages in eastern South Dakota, water years 1945–2013

USGS Publications Warehouse

Hoogestraat, Galen K.; Stamm, John F.

2015-11-02

For the streamgages with significant trends in residual streamflow (such as the streamgage on the Whetstone River and streamgages in the Big Sioux River Basin), land-use changes likely are minor factors, with the main factors probably being changes in the timing and frequency of large precipitation events and persistently wetter antecedent conditions. Changes in the relation between precipitation and streamflow since 1945 were evident when considering the runoff efficiency of the watershed. For example, the streamflow response to annual precipitation of 25 inches for the James River near Scotland increased from approximately 1,000 cubic feet per second for WYs 1945–1990 to about 2,500 cubic feet per second for WYs 1991–2013. The importance of antecedent conditions on annual mean streamflow also was indicated by the significance of the multiple linear regression coefficients of annual mean streamflow and precipitation from preceding water years for all but one streamgage. In addition, rising groundwater levels are present in wells in eastern South Dakota, particularly since the 1980s.

Precipitation-Runoff Modeling System (PRMS) and Streamflow Response to Spatially Distributed Precipitation in Two Large Watersheds in Northern California

NASA Astrophysics Data System (ADS)

Dhakal, A. S.; Adera, S.; Niswonger, R. G.; Gardner, M.

2016-12-01

The ability of the Precipitation-Runoff Modeling System (PRMS) to predict peak intensity, peak timing, base flow, and volume of streamflow was examined in Arroyo Hondo (180 km2) and Upper Alameda Creek (85 km2), two sub-watersheds of the Alameda Creek watershed in Northern California. Rainfall-runoff volume ratios vary widely, and can exceed 0.85 during mid-winter flashy rainstorm events. Due to dry antecedent soil moisture conditions, the first storms of the hydrologic year often produce smaller rainfall-runoff volume ratios. Runoff response in this watershed is highly hysteretic; large precipitation events are required to generate runoff following a 4-week period without precipitation. After about 150 mm of cumulative rainfall, streamflow responds quickly to subsequent storms, with variations depending on rainstorm intensity. Inputs to PRMS included precipitation, temperature, topography, vegetation, soils, and land cover data. The data was prepared for input into PRMS using a suite of data processing Python scripts written by the Desert Research Institute and U.S. Geological Survey. PRMS was calibrated by comparing simulated streamflow to measured streamflow at a daily time step during the period 1995 - 2014. The PRMS model is being used to better understand the different patterns of streamflow observed in the Alameda Creek watershed. Although Arroyo Hondo receives more rainfall than Upper Alameda Creek, it is not clear whether the differences in streamflow patterns are a result of differences in rainfall or other variables, such as geology, slope and aspect. We investigate the ability of PRMS to simulate daily streamflow in the two sub-watersheds for a variety of antecedent soil moisture conditions and rainfall intensities. After successful simulation of watershed runoff processes, the model will be expanded using GSFLOW to simulate integrated surface water and groundwater to support water resources planning and management in the Alameda Creek watershed.

Documentation of a computer program to simulate stream-aquifer relations using a modular, finite-difference, ground-water flow model

USGS Publications Warehouse

Prudic, David E.

1989-01-01

Computer models are widely used to simulate groundwater flow for evaluating and managing the groundwater resource of many aquifers, but few are designed to also account for surface flow in streams. A computer program was written for use in the US Geological Survey modular finite difference groundwater flow model to account for the amount of flow in streams and to simulate the interaction between surface streams and groundwater. The new program is called the Streamflow-Routing Package. The Streamflow-Routing Package is not a true surface water flow model, but rather is an accounting program that tracks the flow in one or more streams which interact with groundwater. The program limits the amount of groundwater recharge to the available streamflow. It permits two or more streams to merge into one with flow in the merged stream equal to the sum of the tributary flows. The program also permits diversions from streams. The groundwater flow model with the Streamflow-Routing Package has an advantage over the analytical solution in simulating the interaction between aquifer and stream because it can be used to simulate complex systems that cannot be readily solved analytically. The Streamflow-Routing Package does not include a time function for streamflow but rather streamflow entering the modeled area is assumed to be instantly available to downstream reaches during each time period. This assumption is generally reasonable because of the relatively slow rate of groundwater flow. Another assumption is that leakage between streams and aquifers is instantaneous. This assumption may not be reasonable if the streams and aquifers are separated by a thick unsaturated zone. Documentation of the Streamflow-Routing Package includes data input instructions; flow charts, narratives, and listings of the computer program for each of four modules; and input data sets and printed results for two test problems, and one example problem. (Lantz-PTT)

Climate change streamflow scenarios designed for critical period water resources planning studies

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.

2003-04-01

Long-range water planning in the United States is usually conducted by individual water management agencies using a critical period planning exercise based on a particular period of the observed streamflow record and a suite of internally-developed simulation tools representing the water system. In the context of planning for climate change, such an approach is flawed in that it assumes that the future climate will be like the historic record. Although more sophisticated planning methods will probably be required as time goes on, a short term strategy for incorporating climate uncertainty into long-range water planning as soon as possible is to create alternate inputs to existing planning methods that account for climate uncertainty as it affects both supply and demand. We describe a straight-forward technique for constructing streamflow scenarios based on the historic record that include the broad-based effects of changed regional climate simulated by several global climate models (GCMs). The streamflow scenarios are based on hydrologic simulations driven by historic climate data perturbed according to regional climate signals from four GCMs using the simple "delta" method. Further data processing then removes systematic hydrologic model bias using a quantile-based bias correction scheme, and lastly, the effects of random errors in the raw hydrologic simulations are removed. These techniques produce streamflow scenarios that are consistent in time and space with the historic streamflow record while incorporating fundamental changes in temperature and precipitation from the GCM scenarios. Planning model simulations based on these climate change streamflow scenarios can therefore be compared directly to planning model simulations based on the historic record of streamflows to help planners understand the potential impacts of climate uncertainty. The methods are currently being tested and refined in two large-scale planning exercises currently being conducted in the Pacific Northwest (PNW) region of the US, and the resulting streamflow scenarios will be made freely available on the internet for a large number of sites in the PNW to help defray the costs of including climate change information in other studies.

SnowCloud - a Framework to Predict Streamflow in Snowmelt-dominated Watersheds Using Cloud-based Computing

NASA Astrophysics Data System (ADS)

Sproles, E. A.; Crumley, R. L.; Nolin, A. W.; Mar, E.; Lopez-Moreno, J. J.

2017-12-01

Streamflow in snowy mountain regions is extraordinarily challenging to forecast, and prediction efforts are hampered by the lack of timely snow data—particularly in data sparse regions. SnowCloud is a prototype web-based framework that integrates remote sensing, cloud computing, interactive mapping tools, and a hydrologic model to offer a new paradigm for delivering key data to water resource managers. We tested the skill of SnowCloud to forecast monthly streamflow with one month lead time in three snow-dominated headwaters. These watersheds represent a range of precipitation/runoff schemes: the Río Elqui in northern Chile (200 mm/yr, entirely snowmelt); the John Day River, Oregon, USA (635 mm/yr, primarily snowmelt); and the Río Aragon in the northern Spain (850 mm/yr, snowmelt dominated). Model skill corresponded to snowpack contribution with Nash-Sutcliffe Efficiencies of 0.86, 0.52, and 0.21 respectively. SnowCloud does not require the user to possess advanced programming skills or proprietary software. We access NASA's MOD10A1 snow cover product to calculate the snow metrics globally using Google Earth Engine's geospatial analysis and cloud computing service. The analytics and forecast tools are provided through a web-based portal that requires only internet access and minimal training. To test the efficacy of SnowCloud we provided the tools and a series of tutorials in English and Spanish to water resource managers in Chile, Spain, and the United States. Participants assessed their user experience and provided feedback, and the results of our multi-cultural assessment are also presented. While our results focus on SnowCloud, they outline methods to develop cloud-based tools that function effectively across cultures and languages. Our approach also addresses the primary challenges of science-based computing; human resource limitations, infrastructure costs, and expensive proprietary software. These challenges are particularly problematic in developing countries.

Exploring the Link Between Streamflow Trends and Climate Change in Indiana, USA

NASA Astrophysics Data System (ADS)

Kumar, S.; Kam, J.; Thurner, K.; Merwade, V.

2007-12-01

Streamflow trends in Indiana are evaluated for 85 USGS streamflow gaging stations that have continuous unregulated streamflow records varying from 10 to 80 years. The trends are analyzed by using the non-parametric Mann-Kendall test with prior trend-free pre-whitening to remove serial correlation in the data. Bootstrap method is used to establish field significance of the results. Trends are computed for 12 streamflow statistics to include low-, medium- (median and mean flow), and high-flow conditions on annual and seasonal time step. The analysis is done for six study periods, ranging from 10 years to more than 65 years, all ending in 2003. The trends in annual average streamflow, for 50 years study period, are compared with annual average precipitation trends from 14 National Climatic Data Center (NCDC) stations in Indiana, that have 50 years of continuous daily record. The results show field significant positive trends in annual low and medium streamflow statistics at majority of gaging stations for study periods that include 40 or more years of records. In seasonal analysis, all flow statistics in summer and fall (low flow seasons), and only low flow statistics in winter and spring (high flow seasons) are showing positive trends. No field significant trends in annual and seasonal flow statistics are observed for study periods that include 25 or fewer years of records, except for northern Indiana where localized negative trends are observed in 10 and 15 years study periods. Further, stream flow trends are found to be highly correlated with precipitation trends on annual time step. No apparent climate change signal is observed in Indiana stream flow records.

A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin

NASA Astrophysics Data System (ADS)

Saleh, Firas; Ramaswamy, Venkatsundar; Georgas, Nickitas; Blumberg, Alan F.; Pullen, Julie

2016-07-01

This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ˜ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.

Identifying a base network of federally funded streamgaging stations

USGS Publications Warehouse

Ries, Kernell G.; Kolva, J.R.; Stewart, D.W.

2004-01-01

The U.S. Geological Survey (USGS) has completed a preliminary analysis to identify streamgaging stations needed in a base network that would satisfy five primary Federal goals for collecting streamflow information. The five goals are (1) determining streamflow at interstate and international borders and at locations mandated by court decrees, (2) determining the streamflow component of water budgets for the major river basins of the Nation, (3) providing real-time streamflow information to the U.S. National Weather Service to support flood-forecasting activities, (4) providing streamflow information at locations of monitoring stations included in USGS national water-quality networks, and (5) providing streamflow information necessary for regionalization of streamflow characteristics and assessing potential long-term trends in streamflow associated with changes in climate. The analysis was done using a Geographic Information System. USGS headquarters staff made initial selections of stations that satisfied at least one of the five goals, and then staff in each of the 48 USGS district offices reviewed the selections, making suggestions for additions or changes based on detailed local knowledge of the streams in the area. The analysis indicated that 4,242 streamgaging stations are needed in the base network to meet the 5 Federal goals for streamflow information. Of these, 2,692 stations (63.5 percent) are currently operated by the USGS, 277 stations (6.5 percent) are currently operated by other agencies, 865 (20.4 percent) are discontinued USGS stations that need to be reactivated, and 408 (9.6 percent) are locations where new stations are needed. Copyright ASCE 2004.

Determination of Baseline Periods of Record for Selected Streamflow-Gaging Stations in New Jersey for Determining Ecologically Relevant Hydrologic Indices (ERHI)

USGS Publications Warehouse

Esralew, Rachel A.; Baker, Ronald J.

2008-01-01

Hydrologic changes in New Jersey stream basins resulting from human activity can affect the flow and ecology of the streams. To assess future changes in streamflow resulting from human activity an understanding of the natural variability of streamflow is needed. The natural variability can be classified using Ecologically Relevant Hydrologic Indices (ERHIs). ERHIs are defined as selected streamflow statistics that characterize elements of the flow regime that substantially affect biological health and ecological sustainability. ERHIs are used to quantitatively characterize aspects of the streamflow regime, including magnitude, duration, frequency, timing, and rate of change. Changes in ERHI values can occur as a result of human activity, and changes in ERHIs over time at various stream locations can provide information about the degree of alteration in aquatic ecosystems at or near those locations. New Jersey streams can be divided into four classes (A, B, C, or D), where streams with similar ERHI values (determined from cluster analysis) are assigned the same stream class. In order to detect and quantify changes in ERHIs at selected streamflow-gaging stations, a 'baseline' period is needed. Ideally, a baseline period is a period of continuous daily streamflow record at a gaging station where human activity along the contributing stream reach or in the stream's basin is minimal. Because substantial urbanization and other development had already occurred before continuous streamflow-gaging stations were installed, it is not possible to identify baseline periods that meet this criterion for many reaches in New Jersey. Therefore, the baseline period for a considerably altered basin can be defined as a period prior to a substantial human-induced change in the drainage basin or stream reach (such as regulations or diversions), or a period during which development did not change substantially. Index stations (stations with minimal urbanization) were defined as streamflow-gaging stations in basins that contain less than 15 percent urban land use throughout the period of continuous streamflow record. A minimum baseline period of record for each stream class was determined by comparing the variability of selected ERHIs among consecutive 5-, 10-, 15-, and 20-year time increments for index stations. On the basis of this analysis, stream classes A and D were assigned a minimum of 20 years of continuous record as a baseline period and stream classes B and C, a minimum of 10 years. Baseline periods were calculated for 85 streamflow-gaging stations in New Jersey with 10 or more years of continuous daily streamflow data, and the values of 171 ERHIs also were calculated for these baseline periods for each station. Baseline periods were determined by using historical streamflow-gaging station data, estimated changes in impervious surface in the drainage basin, and statistically significant changes in annual base flow and runoff. Historical records were reviewed to identify years during which regulation, diversions, or withdrawals occurred in the drainage basins. Such years were not included in baseline periods of record. For some sites, the baseline period of record was shorter than the minimum period of record specified for the given stream class. In such cases, the baseline period was rated as 'poor'. Impervious surface was used as an indicator of urbanization and change in streamflow characteristics owing to increases in storm runoff and decreases in base flow. Percentages of impervious surface were estimated for 85 streamflow-gaging stations from available municipal population-density data by using a regression model. Where the period of record was sufficiently long, all years after the impervious surface exceeded 10 to 20 percent were excluded from the baseline period. The percentage of impervious surface also was used as a criterion in assigning qualitative ratings to baseline periods. Changes in trends of annual base fl

Estimation of daily mean streamflow for ungaged stream locations in the Delaware River Basin, water years 1960–2010

USGS Publications Warehouse

Stuckey, Marla H.

2016-06-09

The ability to characterize baseline streamflow conditions, compare them with current conditions, and assess effects of human activities on streamflow is fundamental to water-management programs addressing water allocation, human-health issues, recreation needs, and establishment of ecological flow criteria. The U.S. Geological Survey, through the National Water Census, has developed the Delaware River Basin Streamflow Estimator Tool (DRB-SET) to estimate baseline (minimally altered) and altered (affected by regulation, diversion, mining, or other anthropogenic activities) and altered streamflow at a daily time step for ungaged stream locations in the Delaware River Basin for water years 1960–2010. Daily mean baseline streamflow is estimated by using the QPPQ method to equate streamflow expressed as a percentile from the flow-duration curve (FDC) for a particular day at an ungaged stream location with the percentile from a FDC for the same day at a hydrologically similar gaged location where streamflow is measured. Parameter-based regression equations were developed for 22 exceedance probabilities from the FDC for ungaged stream locations in the Delaware River Basin. Water use data from 2010 is used to adjust the baseline daily mean streamflow generated from the QPPQ method at ungaged stream locations in the Delaware River Basin to reflect current, or altered, conditions. To evaluate the effectiveness of the overall QPPQ method contained within DRB-SET, a comparison of observed and estimated daily mean streamflows was performed for 109 reference streamgages in and near the Delaware River Basin. The Nash-Sutcliffe efficiency (NSE) values were computed as a measure of goodness of fit. The NSE values (using log10 streamflow values) ranged from 0.22 to 0.98 (median of 0.90) for 45 streamgages in the Upper Delaware River Basin and from -0.37 to 0.98 (median of 0.79) for 41 streamgages in the Lower Delaware River Basin.

Analysis of trends in climate, streamflow, and stream temperature in north coastal California

USGS Publications Warehouse

Madej, Mary Ann; Medley, C. Nicholas; Patterson, Glenn; Parker, Melanie J.

2011-01-01

As part of a broader project analyzing trends in climate, streamflow, vegetation, salmon, and ocean conditions in northern California national park units, we compiled average monthly air temperature and precipitation data from 73 climate stations, streamflow data from 21 river gaging stations, and limited stream temperature data from salmon-bearing rivers in north coastal California. Many climate stations show a statistically significant increase in both average maximum and average minimum air temperature in early fall and midwinter during the last century. Concurrently, average September precipitation has decreased. In many coastal rivers, summer low flow has decreased and summer stream temperatures have increased, which affects summer rearing habitat for salmonids. Nevertheless, because vegetative cover has also changed during this time period, we cannot ascribe streamflow changes to climate change without first assessing water budgets. Although shifts in the timing of the centroid of runoff have been documented in snowmelt-dominated watersheds in the western United States, this was not the case in lower elevation coastal rivers analyzed in this study.

Groundwater similarity across a watershed derived from time-warped and flow-corrected time series

NASA Astrophysics Data System (ADS)

Rinderer, M.; McGlynn, B. L.; van Meerveld, H. J.

2017-05-01

Information about catchment-scale groundwater dynamics is necessary to understand how catchments store and release water and why water quantity and quality varies in streams. However, groundwater level monitoring is often restricted to a limited number of sites. Knowledge of the factors that determine similarity between monitoring sites can be used to predict catchment-scale groundwater storage and connectivity of different runoff source areas. We used distance-based and correlation-based similarity measures to quantify the spatial and temporal differences in shallow groundwater similarity for 51 monitoring sites in a Swiss prealpine catchment. The 41 months long time series were preprocessed using Dynamic Time-Warping and a Flow-corrected Time Transformation to account for small timing differences and bias toward low-flow periods. The mean distance-based groundwater similarity was correlated to topographic indices, such as upslope contributing area, topographic wetness index, and local slope. Correlation-based similarity was less related to landscape position but instead revealed differences between seasons. Analysis of variance and partial Mantel tests showed that landscape position, represented by the topographic wetness index, explained 52% of the variability in mean distance-based groundwater similarity, while spatial distance, represented by the Euclidean distance, explained only 5%. The variability in distance-based similarity and correlation-based similarity between groundwater and streamflow time series was significantly larger for midslope locations than for other landscape positions. This suggests that groundwater dynamics at these midslope sites, which are important to understand runoff source areas and hydrological connectivity at the catchment scale, are most difficult to predict.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2014-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2015-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

Evaluation of model-based seasonal streamflow and water allocation forecasts for the Elqui Valley, Chile

NASA Astrophysics Data System (ADS)

Delorit, Justin; Cristian Gonzalez Ortuya, Edmundo; Block, Paul

2017-09-01

In many semi-arid regions, multisectoral demands often stress available water supplies. Such is the case in the Elqui River valley of northern Chile, which draws on a limited-capacity reservoir to allocate 25 000 water rights. Delayed infrastructure investment forces water managers to address demand-based allocation strategies, particularly in dry years, which are realized through reductions in the volume associated with each water right. Skillful season-ahead streamflow forecasts have the potential to inform managers with an indication of future conditions to guide reservoir allocations. This work evaluates season-ahead statistical prediction models of October-January (growing season) streamflow at multiple lead times associated with manager and user decision points, and links predictions with a reservoir allocation tool. Skillful results (streamflow forecasts outperform climatology) are produced for short lead times (1 September: ranked probability skill score (RPSS) of 0.31, categorical hit skill score of 61 %). At longer lead times, climatological skill exceeds forecast skill due to fewer observations of precipitation. However, coupling the 1 September statistical forecast model with a sea surface temperature phase and strength statistical model allows for equally skillful categorical streamflow forecasts to be produced for a 1 May lead, triggered for 60 % of years (1950-2015), suggesting forecasts need not be strictly deterministic to be useful for water rights holders. An early (1 May) categorical indication of expected conditions is reinforced with a deterministic forecast (1 September) as more observations of local variables become available. The reservoir allocation model is skillful at the 1 September lead (categorical hit skill score of 53 %); skill improves to 79 % when categorical allocation prediction certainty exceeds 80 %. This result implies that allocation efficiency may improve when forecasts are integrated into reservoir decision frameworks. The methods applied here advance the understanding of the mechanisms and timing responsible for moisture transport to the Elqui Valley and provide a unique application of streamflow forecasting in the prediction of water right allocations.

Optimising seasonal streamflow forecast lead time for operational decision making in Australia

NASA Astrophysics Data System (ADS)

Schepen, Andrew; Zhao, Tongtiegang; Wang, Q. J.; Zhou, Senlin; Feikema, Paul

2016-10-01

Statistical seasonal forecasts of 3-month streamflow totals are released in Australia by the Bureau of Meteorology and updated on a monthly basis. The forecasts are often released in the second week of the forecast period, due to the onerous forecast production process. The current service relies on models built using data for complete calendar months, meaning the forecast production process cannot begin until the first day of the forecast period. Somehow, the bureau needs to transition to a service that provides forecasts before the beginning of the forecast period; timelier forecast release will become critical as sub-seasonal (monthly) forecasts are developed. Increasing the forecast lead time to one month ahead is not considered a viable option for Australian catchments that typically lack any predictability associated with snowmelt. The bureau's forecasts are built around Bayesian joint probability models that have antecedent streamflow, rainfall and climate indices as predictors. In this study, we adapt the modelling approach so that forecasts have any number of days of lead time. Daily streamflow and sea surface temperatures are used to develop predictors based on 28-day sliding windows. Forecasts are produced for 23 forecast locations with 0-14- and 21-day lead time. The forecasts are assessed in terms of continuous ranked probability score (CRPS) skill score and reliability metrics. CRPS skill scores, on average, reduce monotonically with increase in days of lead time, although both positive and negative differences are observed. Considering only skilful forecast locations, CRPS skill scores at 7-day lead time are reduced on average by 4 percentage points, with differences largely contained within +5 to -15 percentage points. A flexible forecasting system that allows for any number of days of lead time could benefit Australian seasonal streamflow forecast users by allowing more time for forecasts to be disseminated, comprehended and made use of prior to the commencement of a forecast season. The system would allow for forecasts to be updated if necessary.

Watershed reliability, resilience and vulnerability analysis under uncertainty using water quality data.

PubMed

Hoque, Yamen M; Tripathi, Shivam; Hantush, Mohamed M; Govindaraju, Rao S

2012-10-30

A method for assessment of watershed health is developed by employing measures of reliability, resilience and vulnerability (R-R-V) using stream water quality data. Observed water quality data are usually sparse, so that a water quality time-series is often reconstructed using surrogate variables (streamflow). A Bayesian algorithm based on relevance vector machine (RVM) was employed to quantify the error in the reconstructed series, and a probabilistic assessment of watershed status was conducted based on established thresholds for various constituents. As an application example, observed water quality data for several constituents at different monitoring points within the Cedar Creek watershed in north-east Indiana (USA) were utilized. Considering uncertainty in the data for the period 2002-2007, the R-R-V analysis revealed that the Cedar Creek watershed tends to be in compliance with respect to selected pesticides, ammonia and total phosphorus. However, the watershed was found to be prone to violations of sediment standards. Ignoring uncertainty in the water quality time-series led to misleading results especially in the case of sediments. Results indicate that the methods presented in this study may be used for assessing the effects of different stressors over a watershed. The method shows promise as a management tool for assessing watershed health. Copyright © 2012 Elsevier Ltd. All rights reserved.

Simulation of streamflow, evapotranspiration, and groundwater recharge in the Lower Frio River watershed, south Texas, 1961-2008

USGS Publications Warehouse

Lizarraga, Joy S.; Ockerman, Darwin J.

2011-01-01

The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; the City of Corpus Christi; the Guadalupe-Blanco River Authority; the San Antonio River Authority; and the San Antonio Water System, configured, calibrated, and tested a watershed model for a study area consisting of about 5,490 mi2 of the Frio River watershed in south Texas. The purpose of the model is to contribute to the understanding of watershed processes and hydrologic conditions in the lower Frio River watershed. The model simulates streamflow, evapotranspiration (ET), and groundwater recharge by using a numerical representation of physical characteristics of the landscape, and meteorological and streamflow data. Additional time-series inputs to the model include wastewater-treatment-plant discharges, surface-water withdrawals, and estimated groundwater inflow from Leona Springs. Model simulations of streamflow, ET, and groundwater recharge were done for various periods of record depending upon available measured data for input and comparison, starting as early as 1961. Because of the large size of the study area, the lower Frio River watershed was divided into 12 subwatersheds; separate Hydrological Simulation Program-FORTRAN models were developed for each subwatershed. Simulation of the overall study area involved running simulations in downstream order. Output from the model was summarized by subwatershed, point locations, reservoir reaches, and the Carrizo-Wilcox aquifer outcrop. Four long-term U.S. Geological Survey streamflow-gaging stations and two short-term streamflow-gaging stations were used for streamflow model calibration and testing with data from 1991-2008. Calibration was based on data from 2000-08, and testing was based on data from 1991-99. Choke Canyon Reservoir stage data from 1992-2008 and monthly evaporation estimates from 1999-2008 also were used for model calibration. Additionally, 2006-08 ET data from a U.S. Geological Survey meteorological station in Medina County were used for calibration. Streamflow and ET calibration were considered good or very good. For the 2000-08 calibration period, total simulated flow volume and the flow volume of the highest 10 percent of simulated daily flows were calibrated to within about 10 percent of measured volumes at six U.S. Geological Survey streamflow-gaging stations. The flow volume of the lowest 50 percent of daily flows was not simulated as accurately but represented a small percent of the total flow volume. The model-fit efficiency for the weekly mean streamflow during the calibration periods ranged from 0.60 to 0.91, and the root mean square error ranged from 16 to 271 percent of the mean flow rate. The simulated total flow volumes during the testing periods at the long-term gaging stations exceeded the measured total flow volumes by approximately 22 to 50 percent at three stations and were within 7 percent of the measured total flow volumes at one station. For the longer 1961-2008 simulation period at the long-term stations, simulated total flow volumes were within about 3 to 18 percent of measured total flow volumes. The calibrations made by using Choke Canyon reservoir volume for 1992-2008, reservoir evaporation for 1999-2008, and ET in Medina County for 2006-08, are considered very good. Model limitations include possible errors related to model conceptualization and parameter variability, lack of data to better quantify certain model inputs, and measurement errors. Uncertainty regarding the degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error. A sensitivity analysis was performed for the Upper San Miguel subwatershed model to show the effect of changes to model parameters on the estimated mean recharge, ET, and surface runoff from that part of the Carrizo-Wilcox aquifer outcrop. Simulated recharge was most sensitive to the changes in the lower-zone ET (LZ

Changes in Streamflow and the Flux of Nutrients in the Mississippi-Atchafalaya River Basin, USA, 1980-2007

USGS Publications Warehouse

Battaglin, William A.; Aulenbach, Brent T.; Vecchia, Aldo; Buxton, Herbert T.

2010-01-01

Nutrients and freshwater delivered by the Mississippi and Atchafalaya Rivers drive algal production in the northern Gulf of Mexico, which eventually results in the widespread occurrence of hypoxic bottom waters along the Louisiana and Texas coast. Researchers have demonstrated a relation between the extent of the hypoxic zone and the magnitude of streamflow, nutrient fluxes, and nutrient concentrations in the Mississippi River, with springtime streamflows and fluxes being the most predictive. In 1999 the U.S. Geological Survey (USGS) estimated the flux of nitrogen, phosphorus, and silica at selected sites in the Mississippi Basin and to the Gulf of Mexico for 1980-1996. These flux estimates provided the baseline information used by the Mississippi River/Gulf of Mexico Watershed Nutrient Task Force to develop an Action Plan for reducing hypoxia in the northern Gulf of Mexico. The primary goal of the Action Plan was to achieve a reduction in the size (areal extent) of the hypoxic zone from an average of approximately 14,000 square kilometers in 1996-2000 to a 5-year moving average of less than 5,000 square kilometers by 2015. Improved statistical models and adjusted maximum likelihood estimation using USGS Load Estimator (LOADEST) software were used to estimate annual and seasonal nutrient fluxes for 1980-2007 at selected sites on the Mississippi River and its tributaries. These data provide a means to evaluate the influence of natural and anthropogenic effects on delivery of water and nutrients to the Gulf of Mexico; to define subbasins that are the most important contributors of nutrients to the gulf; and to investigate the relations among streamflow, nutrient fluxes, and the size and duration of the Gulf of Mexico hypoxic zone. A comparative analysis between the baseline period of 1980-1996 and 5-year moving averages thereafter indicate that the average annual streamflow and fluxes of total nitrogen, nitrate, orthophosphate, and silica to the Gulf of Mexico have decreased. However, the flux of total phosphorus between the baseline period and subsequent 5-year periods has increased. The average spring (April, May, and June) streamflow and fluxes of silica, total nitrogen, nitrate, and orthophosphate to the Gulf of Mexico also decreased, whereas the spring flux of total phosphorus has increased. Similar changes in streamflow and nutrient flux were observed at many sites Buxtonwithin the basin. The inputs of water, total nitrogen, and total phosphorus from the major subbasins of the Mississippi-Atchafalaya River Basin as a percentage of the to-the-gulf totals have increased from the Ohio River Basin, decreased from the Missouri River Basin, and remained relatively unchanged from the Upper Mississippi, Red, and Arkansas River Basins. Changes in streamflow and nutrient fluxes are related, but short-term variations in sources of streamflow and nutrients complicate the interpretation of factors that affect nutrient delivery to the Gulf of Mexico. Parametric time-series models are used to try and separate natural variability in nutrient flux from changes due to other causes. Results indicate that the decrease in annual nutrient fluxes that has occurred between the 1980-1996 baseline period and more recent years can be largely attributed to natural causes (climate and streamflow) and not management actions or other human controlled activities in the Mississippi-Atchafalaya River Basin. The downward trends in total nitrogen, nitrate, ammonium, and orthophosphate that were detected at either the Mississippi River near St. Francisville, La., or the Atchafalaya River at Melville, La., occurred prior to 1995. In spite of the general decrease in nutrient flux, the average size of the Gulf of Mexico hypoxic zone has increased between 1997 and 2007. The reasons for this are not clear but could be due to the type or nature of nutrient delivery. Whereas the annual flux of total nitrogen to the Gulf of Mexico has decreased, the proporti

Simulation of streamflow and estimation of recharge to the Edwards aquifer in the Hondo Creek, Verde Creek, and San Geronimo Creek watersheds, south-central Texas, 1951-2003

USGS Publications Warehouse

Ockerman, Darwin J.

2005-01-01

The U.S. Geological Survey, in cooperation with the San Antonio Water System, constructed three watershed models using the Hydrological Simulation Program—FORTRAN (HSPF) to simulate streamflow and estimate recharge to the Edwards aquifer in the Hondo Creek, Verde Creek, and San Geronimo Creek watersheds in south-central Texas. The three models were calibrated and tested with available data collected during 1992–2003. Simulations of streamflow and recharge were done for 1951–2003. The approach to construct the models was to first calibrate the Hondo Creek model (with an hourly time step) using 1992–99 data and test the model using 2000–2003 data. The Hondo Creek model parameters then were applied to the Verde Creek and San Geronimo Creek watersheds to construct the Verde Creek and San Geronimo Creek models. The simulated streamflows for Hondo Creek are considered acceptable. Annual, monthly, and daily simulated streamflows adequately match measured values, but simulated hourly streamflows do not. The accuracy of streamflow simulations for Verde Creek is uncertain. For San Geronimo Creek, the match of measured and simulated annual and monthly streamflows is acceptable (or nearly so); but for daily and hourly streamflows, the calibration is relatively poor. Simulated average annual total streamflow for 1951–2003 to Hondo Creek, Verde Creek, and San Geronimo Creek is 45,400; 32,400; and 11,100 acre-feet, respectively. Simulated average annual streamflow at the respective watershed outlets is 13,000; 16,200; and 6,920 acre-feet. The difference between total streamflow and streamflow at the watershed outlet is streamflow lost to channel infiltration. Estimated average annual Edwards aquifer recharge for Hondo Creek, Verde Creek, and San Geronimo Creek watersheds for 1951–2003 is 37,900 acrefeet (5.04 inches), 26,000 acre-feet (3.36 inches), and 5,940 acre-feet (1.97 inches), respectively. Most of the recharge (about 77 percent for the three watersheds together) occurs as streamflow channel infiltration. Diffuse recharge (direct infiltration of rainfall to the aquifer) accounts for the remaining 23 percent of recharge. For the Hondo Creek watershed, the HSPF recharge estimates for 1992–2003 averaged about 22 percent less than those estimated by the Puente method, a method the U.S. Geological Survey has used to compute annual recharge to the Edwards aquifer since 1978. HSPF recharge estimates for the Verde Creek watershed average about 40 percent less than those estimated by the Puente method.

Estimating retention potential of headwater catchment using Tritium time series

NASA Astrophysics Data System (ADS)

Hofmann, Harald; Cartwright, Ian; Morgenstern, Uwe

2018-06-01

Headwater catchments provide substantial streamflow to rivers even during long periods of drought. Documenting the mean transit times (MTT) of stream water in headwater catchments and therefore the retention capacities of these catchments is crucial for water management. This study uses time series of 3H activities in combination with major ion concentrations, stable isotope ratios and radon activities (222Rn) in the Lyrebird Creek catchment in Victoria, Australia to provide a unique insight into the mean transit time distributions and flow systems of this small temperate headwater catchment. At all streamflows, the stream has 3H activities (<2.4 TU) that are significantly below those of rainfall (∼3.2 TU), implying that most of the water in the stream is derived from stores with long transit times. If the water in the catchment can be represented by a single store with a continuum of ages, mean transit times of the stream water range from ∼6 up to 40 years, which indicates the large retention potential for this catchment. Alternatively, variations of 3H activities, stable isotopes and major ions can be explained by mixing between of young recent recharge and older water stored in the catchment. While surface runoff is negligible, the variation in stable isotope ratios, major ion concentrations and radon activities during most of the year is minimal (±12%) and only occurs during major storm events. This suggests that different subsurface water stores are activated during the storm events and that these cease to provide water to the stream within a few days or weeks after storm events. The stores comprise micro and macropore flow in the soils and saprolite as well as the boundary between the saprolite and the fractured bed rock. Hydrograph separations from three major storm events using Tritium, electrical conductivity and selected major ions as well a δ18O suggest a minimum of 50% baseflow at most flow conditions. We demonstrate that headwater catchments can have a significant storage capacity and that the relationship between long-water stores and fast storm event subsurface flow is complex. The study also illustrates that using 3H to determine mean transit times is probably only valid for baseflow conditions where the catchment can be represented as a single store. The results of this study reinforce the need to protect headwater catchments from contamination and extreme land use changes.

Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē-Atbara river basin, Ethiopia

NASA Astrophysics Data System (ADS)

Gebremicael, Tesfay G.; Mohamed, Yasir A.; Zaag, Pieter v.; Hagos, Eyasu Y.

2017-04-01

The Upper Tekezē-Atbara river sub-basin, part of the Nile Basin, is characterized by high temporal and spatial variability of rainfall and streamflow. In spite of its importance for sustainable water use and food security, the changing patterns of streamflow and its association with climate change is not well understood. This study aims to improve the understanding of the linkages between rainfall and streamflow trends and identify possible drivers of streamflow variabilities in the basin. Trend analyses and change-point detections of rainfall and streamflow were analysed using Mann-Kendall and Pettitt tests, respectively, using data records for 21 rainfall and 9 streamflow stations. The nature of changes and linkages between rainfall and streamflow were carefully examined for monthly, seasonal and annual flows, as well as indicators of hydrologic alteration (IHA). The trend and change-point analyses found that 19 of the tested 21 rainfall stations did not show statistically significant changes. In contrast, trend analyses on the streamflow showed both significant increasing and decreasing patterns. A decreasing trend in the dry season (October to February), short season (March to May), main rainy season (June to September) and annual totals is dominant in six out of the nine stations. Only one out of nine gauging stations experienced significant increasing flow in the dry and short rainy seasons, attributed to the construction of Tekezē hydropower dam upstream this station in 2009. Overall, streamflow trends and change-point timings were found to be inconsistent among the stations. Changes in streamflow without significant change in rainfall suggests factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the basin. Further studies are needed to verify and quantify the hydrological changes shown in statistical tests by identifying the physical mechanisms behind those changes. The findings from this study are useful as a prerequisite for studying the effects of catchment management dynamics on the hydrological variabilities in the basin.

How do extreme streamflow due to hurricane IRMA compare during 1938-2017 in South Eastern US?

NASA Astrophysics Data System (ADS)

Anandhi, A.

2017-12-01

The question related to Irma, Harvey, Maria, and other hurricanes is: are hurricane more frequent and intense than they have been in the past. Recent hurricanes were unusually strong hitting the US Coastline or territories as a category 4 or 5, dropping unusually large amounts of precipitation on the affected areas creating extreme high-flow events in rivers and streams in affected areas. The objective of the study is to determine how extreme are streamflows from recent hurricanes (e.g. IRMA) when compared to streamflow's during 1938-2017 time-period. Additionally, in this study, the extreme precipitations are also compared during IRMA. Extreme high flows are selected from Indicators of Hydrologic Alteration (IHA). They are distributions, timing, duration, frequency, magnitude, pulses, and days of extreme events in rivers of the southeastern United States and Gulf of Mexico Hydrologic Region—03. Streamflow data from 30 stations in the region with at least 79 years of record (1938-2017) are used. Historical precipitation changes is obtained from meta-analysis of published literature. Our preliminary results indicate the extremeness of streamflow from recent hurricanes vary with the IHA indicator selected. Some potential implications of these extreme events on the region's ecosystem are also discussed using causal chains and loops.

Being an honest broker of hydrology: Uncovering, communicating and addressing model error in a climate change streamflow dataset

NASA Astrophysics Data System (ADS)

Chegwidden, O.; Nijssen, B.; Pytlak, E.

2017-12-01

Any model simulation has errors, including errors in meteorological data, process understanding, model structure, and model parameters. These errors may express themselves as bias, timing lags, and differences in sensitivity between the model and the physical world. The evaluation and handling of these errors can greatly affect the legitimacy, validity and usefulness of the resulting scientific product. In this presentation we will discuss a case study of handling and communicating model errors during the development of a hydrologic climate change dataset for the Pacific Northwestern United States. The dataset was the result of a four-year collaboration between the University of Washington, Oregon State University, the Bonneville Power Administration, the United States Army Corps of Engineers and the Bureau of Reclamation. Along the way, the partnership facilitated the discovery of multiple systematic errors in the streamflow dataset. Through an iterative review process, some of those errors could be resolved. For the errors that remained, honest communication of the shortcomings promoted the dataset's legitimacy. Thoroughly explaining errors also improved ways in which the dataset would be used in follow-on impact studies. Finally, we will discuss the development of the "streamflow bias-correction" step often applied to climate change datasets that will be used in impact modeling contexts. We will describe the development of a series of bias-correction techniques through close collaboration among universities and stakeholders. Through that process, both universities and stakeholders learned about the others' expectations and workflows. This mutual learning process allowed for the development of methods that accommodated the stakeholders' specific engineering requirements. The iterative revision process also produced a functional and actionable dataset while preserving its scientific merit. We will describe how encountering earlier techniques' pitfalls allowed us to develop improved methods for scientists and practitioners alike.

Time series analysis of the long-term hydrologic impacts of afforestation in the Águeda watershed of north-central Portugal

NASA Astrophysics Data System (ADS)

Hawtree, D.; Nunes, J. P.; Keizer, J. J.; Jacinto, R.; Santos, J.; Rial-Rivas, M. E.; Boulet, A.-K.; Tavares-Wahren, F.; Feger, K.-H.

2015-07-01

The north-central region of Portugal has undergone significant land cover change since the early 1900s, with large-scale replacement of natural vegetation types with plantation forests. This transition consisted of an initial conversion primarily to Pinus pinaster, followed by a secondary transition to Eucalyptus globulus. This land cover change is likely to have altered the hydrologic functioning of this region; however, these potential impacts are not fully understood. To contribute to a better understanding of the potential hydrologic impacts of this land cover change, this study examines the temporal trends in 75 years of data from the Águeda watershed (part of the Vouga Basin) over the period of 1936-2010. A number of hydrometeorological variables were analyzed using a combined Thiel-Sen/Mann-Kendall trend-testing approach, to assess the magnitude and significance of patterns in the observed data. These trend tests indicated that there have been no significant reductions in streamflow over either the entire test period, or during sub-record periods, despite the large-scale afforestation which has occurred. This lack of change in streamflow is attributed to the specific characteristics of the watershed and land cover change. By contrast, a number of significant trends were found for baseflow index, with positive trends in the early data record (primarily during Pinus pinaster afforestation), followed by negative trends later in the data record (primarily during Eucalyptus globulus afforestation). These trends are attributed to land use and vegetation impacts on streamflow generating processes, both due to species differences and to alterations in soil properties (i.e., infiltration capacity, soil water repellency). These results highlight the importance of considering both vegetation types/dynamics and watershed characteristic when assessing hydrologic impacts, in particular with respect to soil properties.

User manuals for the Delaware River Basin Water Availability Tool for Environmental Resources (DRB–WATER) and associated WATER application utilities

USGS Publications Warehouse

Williamson, Tanja N.; Lant, Jeremiah G.

2015-11-18

The Water Availability Tool for Environmental Resources (WATER) is a decision support system (DSS) for the nontidal part of the Delaware River Basin (DRB) that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that have been parameterized using three hydrologic response units—forested, agricultural, and developed land cover. It is this integration that enables the regional hydrologic-modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model. The DSS provides a “historical” database, ideal for simulating streamflow for 2001–11, in addition to land-cover forecasts that focus on 2030 and 2060. The WATER Application Utilities are provided with the DSS and apply change factors for precipitation, temperature, and potential evapotranspiration to a 1981–2011 climatic record provided with the DSS. These change factors were derived from a suite of general circulation models (GCMs) and representative concentration pathway (RCP) emission scenarios. These change factors are based on 25-year monthly averages (normals) that are centere on 2030 and 2060. The WATER Application Utilities also can be used to apply a 2010 snapshot of water use for the DRB; a factorial approach enables scenario testing of increased or decreased water use for each simulation. Finally, the WATER Application Utilities can be used to reformat streamflow time series for input to statistical or reservoir management software. 

USGS tethered ACP platforms: New design means more safety and accuracy

USGS Publications Warehouse

Morlock, S.E.; Stewart, J.A.; Rehmel, M.S.

2004-01-01

The US Geological Survey has developed an innovative tethered platform that supports an Acoustic Current Profiler (ACP) in making stream-flow measurements (use of the term ACP in this article refers to a class of instruments and not a specific brand name or model). The tethered platform reduces the hazards involved in conventional methods of stream-flow measurement. The use of the platform reduces or eliminates time spent by personnel in streams and boats or on bridges and cableway and stream-flow measurement accuracy is increased.

Map showing selected surface-water data for the Manti 30 x 60-minute Quadrangle, Utah

USGS Publications Warehouse

Price, Don

1984-01-01

This is one of a series of maps that describe the geology and related natural resources of the Manti 30 x 60 minute quadrangle. Streamflow records used to compile this map were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Transportation. The principal runoff-producing areas shown on the map were delineated from a work map (scale 1:250,000) compiled to estimate water yields in Utah (Bagley and others, 1964). Sources of information about recorded floods resulting from cloudbursts included Woolley (1946) and Butler and Marsell (1972); sources of information about the chemical quality of streamflow included Hahl and Cabell (1965) and Mundorff and Thompson (1982).

Map showing selected surface-water data for the Huntington 30 x 60-minute quadrangle, Utah

USGS Publications Warehouse

Price, Don

1984-01-01

This is one of a series of maps that describe the geology and related natural resources of the Huntington 30 x 60-minute quadrangle, Utah. Streamflow records used to compile this map were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Transportation. The principal runoff-producing area shown on the map was delineated from a work map (scale 1:250,000) compiled to estimate water yields in Utah (Bagley and others, 1964). Sources of information about recorded floods resulting from cloudbursts included Woolley (1946) and Butler and Marsell (1972); sources of information about the chemical quality of streamflow included Mundorff (1972) and Mundorff and Thompson (1982).

Map showing selected surface-water data for the Price 30 x 60-minute Quadrangle, Utah

USGS Publications Warehouse

Price, Don

1984-01-01

This is one of a series of maps that describe the geology and related natural resources of the Price 30 x 60-minute quadrangle, Utah. Streamflow records used to compile this map were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Transportation. The principal runoff-producing areas shown on the map were delineated from a work map (scale 1:250,000) compiled to estimate water yields in Utah (Bagley and others, 1964). Sources of information about recorded floods resulting from cloudbursts included Woolley (1946) and Butler and Marsell (1972); sources of information about the chemical quality of streamflow included Mundorff (1972; 1977), and Waddell and others (1982).

Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation

NASA Astrophysics Data System (ADS)

Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno

2014-05-01

A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides further validation of FSD, the next steps include an extension of the study to different catchments and other hydrological models with a similar structure.

Hydrogeologic controls on streamflow sensitivity to climate variation

Treesearch

Anne Jefferson; Anne Nolin; Sarah Lewis; Christina Tague

2008-01-01

Climate models project warmer temperatures for the north-west USA, which will result in reduced snowpacks and decreased summer streamflow. This paper examines how groundwater, snowmelt, and regional climate patterns control discharge at multiple time scales, using historical records from two watersheds with contrasting geological properties and drainage efficiencies....

The relationship between groundwater ages, streamflow ages, and storage selection functions under stationary conditions

NASA Astrophysics Data System (ADS)

Berghuijs, W.; Kirchner, J. W.

2017-12-01

Waters in aquifers are often much older than the streamwaters that drain them. Simple physically based reasoning suggests that these age contrasts should be expected wherever catchments are heterogeneous. However, a general quantitative catchment-scale explanation of these age contrasts remains elusive. We show that under stationary conditions conservation of mass and age dictate that the age distribution of water stored in a catchment can be directly estimated from the age distribution of its outflows, and vice versa. This in turn implies that the catchment's preference for the release or retention of waters of different ages can be estimated directly from the age distribution of outflow under stationary conditions. Using simple models of transit times, we show that the mean age of stored water can range from half as old as the mean age of streamflow (for plug flow conditions) to almost infinitely older (for strongly preferential flow). Streamflow age distributions reported in the literature often have long upper tails, consistent with preferential flow and implying that storage ages are substantially older than streamflow ages. Mean streamflow ages reported in the literature imply that most streamflow originates from a thin veneer of total groundwater storage. This preferential release of young streamflow implies that most groundwater is exchanged only slowly with the surface, and consequently must be very old. Where information is available for both storage ages and streamflow ages, our analysis establishes consistency relationships through which each could be used to better constrain the other. By quantifying the relationship between groundwater and streamflow ages, our analysis provides tools to jointly assess both of these important catchment properties.

Streamflow measurements, basin characteristics, and streamflow statistics for low-flow partial-record stations operated in Massachusetts from 1989 through 1996

USGS Publications Warehouse

Ries, Kernell G.

1999-01-01

A network of 148 low-flow partial-record stations was operated on streams in Massachusetts during the summers of 1989 through 1996. Streamflow measurements (including historical measurements), measured basin characteristics, and estimated streamflow statistics are provided in the report for each low-flow partial-record station. Also included for each station are location information, streamflow-gaging stations for which flows were correlated to those at the low-flowpartial-record station, years of operation, and remarks indicating human influences of stream-flowsat the station. Three or four streamflow measurements were made each year for three years during times of low flow to obtain nine or ten measurements for each station. Measured flows at the low-flow partial-record stations were correlated with same-day mean flows at a nearby gaging station to estimate streamflow statistics for the low-flow partial-record stations. The estimated streamflow statistics include the 99-, 98-, 97-, 95-, 93-, 90-, 85-, 80-, 75-, 70-, 65-, 60-, 55-, and 50-percent duration flows; the 7-day, 10- and 2-year low flows; and the August median flow. Characteristics of the drainage basins for the stations that theoretically relate to the response of the station to climatic variations were measured from digital map data by use of an automated geographic information system procedure. Basin characteristics measured include drainage area; total stream length; mean basin slope; area of surficial stratified drift; area of wetlands; area of water bodies; and mean, maximum, and minimum basin elevation.Station descriptions and calculated streamflow statistics are also included in the report for the 50 continuous gaging stations used in correlations with the low-flow partial-record stations.

Water-quality trends for selected sampling sites in the upper Clark Fork Basin, Montana, water years 1996-2010

USGS Publications Warehouse

Sando, Steven K.; Vecchia, Aldo V.; Lorenz, David L.; Barnhart, Elliott P.

2014-01-01

A large-scale trend analysis was done on specific conductance, selected trace elements (arsenic, cadmium, copper, iron, lead, manganese, and zinc), and suspended-sediment data for 22 sites in the upper Clark Fork Basin for water years 1996–2010. Trend analysis was conducted by using two parametric methods: a time-series model (TSM) and multiple linear regression on time, streamflow, and season (MLR). Trend results for 1996–2010 indicate moderate to large decreases in flow-adjusted concentrations (FACs) and loads of copper (and other metallic elements) and suspended sediment in Silver Bow Creek upstream from Warm Springs. Deposition of metallic elements and suspended sediment within Warm Springs Ponds substantially reduces the downstream transport of those constituents. However, mobilization of copper and suspended sediment from floodplain tailings and stream banks in the Clark Fork reach from Galen to Deer Lodge is a large source of metallic elements and suspended sediment, which also affects downstream transport of those constituents. Copper and suspended-sediment loads mobilized from within this reach accounted for about 40 and 20 percent, respectively, of the loads for Clark Fork at Turah Bridge (site 20); whereas, streamflow contributed from within this reach only accounted for about 8 percent of the streamflow at Turah Bridge. Minor changes in FACs and loads of copper and suspended sediment are indicated for this reach during 1996–2010. Clark Fork reaches downstream from Deer Lodge are relatively smaller sources of metallic elements than the reach from Galen to Deer Lodge. In general, small decreases in loads and FACs of copper and suspended sediment are indicated for Clark Fork sites downstream from Deer Lodge during 1996–2010. Thus, although large decreases in FACs and loads of copper and suspended sediment are indicated for Silver Bow Creek upstream from Warm Springs, those large decreases are not translated to the more downstream reaches largely because of temporal stationarity in constituent transport relations in the Clark Fork reach from Galen to Deer Lodge. Unlike metallic elements, arsenic (a metalloid element) in streams in the upper Clark Fork Basin typically is mostly in dissolved phase, has less variability in concentrations, and has weaker direct relations with suspended-sediment concentrations and streamflow. Arsenic trend results for 1996–2010 indicate generally moderate decreases in FACs and loads in Silver Bow Creek upstream from Opportunity. In general, small temporal changes in loads and FACs of arsenic are indicated for Silver Bow Creek and Clark Fork reaches downstream from Opportunity during 1996–2010. Contribution of arsenic (from Warm Springs Ponds, the Mill-Willow bypass, and groundwater sources) in the Silver Bow Creek reach from Opportunity to Warm Springs is a relatively large source of arsenic. Arsenic loads originating from within this reach accounted for about 11 percent of the load for Clark Fork at Turah Bridge; whereas, streamflow contributed from within this reach only accounted for about 2 percent of the streamflow at Turah Bridge.

StreamStats: a U.S. geological survey web site for stream information

USGS Publications Warehouse

Kernell, G. Ries; Gray, John R.; Renard, Kenneth G.; McElroy, Stephen A.; Gburek, William J.; Canfield, H. Evan; Scott, Russell L.

2003-01-01

The U.S. Geological Survey has developed a Web application, named StreamStats, for providing streamflow statistics, such as the 100-year flood and the 7-day, 10-year low flow, to the public. Statistics can be obtained for data-collection stations and for ungaged sites. Streamflow statistics are needed for water-resources planning and management; for design of bridges, culverts, and flood-control structures; and for many other purposes. StreamStats users can point and click on data-collection stations shown on a map in their Web browser window to obtain previously determined streamflow statistics and other information for the stations. Users also can point and click on any stream shown on the map to get estimates of streamflow statistics for ungaged sites. StreamStats determines the watershed boundaries and measures physical and climatic characteristics of the watersheds for the ungaged sites by use of a Geographic Information System (GIS), and then it inserts the characteristics into previously determined regression equations to estimate the streamflow statistics. Compared to manual methods, StreamStats reduces the average time needed to estimate streamflow statistics for ungaged sites from several hours to several minutes.

Escherichia coli bacteria density in relation to turbidity, streamflow characteristics, and season in the Chattahoochee River near Atlanta, Georgia, October 2000 through September 2008—Description, statistical analysis, and predictive modeling

USGS Publications Warehouse

Lawrence, Stephen J.

2012-01-01

Regression analyses show that E. coli density in samples was strongly related to turbidity, streamflow characteristics, and season at both sites. The regression equation chosen for the Norcross data showed that 78 percent of the variability in E. coli density (in log base 10 units) was explained by the variability in turbidity values (in log base 10 units), streamflow event (dry-weather flow or stormflow), season (cool or warm), and an interaction term that is the cross product of streamflow event and turbidity. The regression equation chosen for the Atlanta data showed that 76 percent of the variability in E. coli density (in log base 10 units) was explained by the variability in turbidity values (in log base 10 units), water temperature, streamflow event, and an interaction term that is the cross product of streamflow event and turbidity. Residual analysis and model confirmation using new data indicated the regression equations selected at both sites predicted E. coli density within the 90 percent prediction intervals of the equations and could be used to predict E. coli density in real time at both sites.

Sustainability of water uses in managed hydrosystems: human- and climate-induced changes for the mid-21st century

DOE PAGES

Fabre, Julie; Ruelland, Denis; Dezetter, Alain; ...

2016-08-02

This paper assesses the sustainability of planned water uses in mesoscale river basins under multiple climate change scenarios, and contributes to determining the possible causes of unsustainability. We propose an assessment grounded in real-world water management issues, with water management scenarios built in collaboration with local water agencies. Furthermore, we present an analysis through indicators that relate to management goals and present the implications of climate uncertainty for our results, furthering the significance of our study for water management. A modeling framework integrating hydro-climatic and human dynamics and accounting for interactions between resource and demand was applied in two basinsmore » of different scales and with contrasting water uses: the Herault (2500 km 2, France) and the Ebro (85 000 km 2, Spain) basins. Natural streamflow was evaluated using a conceptual hydrological model. A demand-driven reservoir management model was designed to account for streamflow regulations from the main dams. Human water demand was estimated from time series of demographic, socioeconomic and climatic data. Environmental flows were accounted for by defining streamflow thresholds under which withdrawals were strictly limited. Finally indicators comparing water availability to demand at strategic resource and demand nodes were computed. This framework was applied under different combinations of climatic and water use scenarios for the mid-21st to differentiate the impacts of climate- and human-induced changes on streamflow and water balance. Results showed that objective monthly environmental flows would be guaranteed in current climate conditions in both basins, yet in several areas this could imply limiting human water uses more than once every 5 years. The impact of the tested climate projections on both water availability and demand could question the water allocations and environmental requirements currently planned for the coming decades. Water shortages for human use could become more frequent and intense, and the pressure on water resources and aquatic ecosystems could intensify. Furthermore, the causes of unsustainability vary across sub-basins and scenarios, and in most areas results are highly dependent on the climate change scenario.« less

Sustainability of water uses in managed hydrosystems: human- and climate-induced changes for the mid-21st century

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fabre, Julie; Ruelland, Denis; Dezetter, Alain

This paper assesses the sustainability of planned water uses in mesoscale river basins under multiple climate change scenarios, and contributes to determining the possible causes of unsustainability. We propose an assessment grounded in real-world water management issues, with water management scenarios built in collaboration with local water agencies. Furthermore, we present an analysis through indicators that relate to management goals and present the implications of climate uncertainty for our results, furthering the significance of our study for water management. A modeling framework integrating hydro-climatic and human dynamics and accounting for interactions between resource and demand was applied in two basinsmore » of different scales and with contrasting water uses: the Herault (2500 km 2, France) and the Ebro (85 000 km 2, Spain) basins. Natural streamflow was evaluated using a conceptual hydrological model. A demand-driven reservoir management model was designed to account for streamflow regulations from the main dams. Human water demand was estimated from time series of demographic, socioeconomic and climatic data. Environmental flows were accounted for by defining streamflow thresholds under which withdrawals were strictly limited. Finally indicators comparing water availability to demand at strategic resource and demand nodes were computed. This framework was applied under different combinations of climatic and water use scenarios for the mid-21st to differentiate the impacts of climate- and human-induced changes on streamflow and water balance. Results showed that objective monthly environmental flows would be guaranteed in current climate conditions in both basins, yet in several areas this could imply limiting human water uses more than once every 5 years. The impact of the tested climate projections on both water availability and demand could question the water allocations and environmental requirements currently planned for the coming decades. Water shortages for human use could become more frequent and intense, and the pressure on water resources and aquatic ecosystems could intensify. Furthermore, the causes of unsustainability vary across sub-basins and scenarios, and in most areas results are highly dependent on the climate change scenario.« less

Improving groundwater predictions utilizing seasonal precipitation forecasts from general circulation models forced with sea surface temperature forecasts

USGS Publications Warehouse

Almanaseer, Naser; Sankarasubramanian, A.; Bales, Jerad

2014-01-01

Recent studies have found a significant association between climatic variability and basin hydroclimatology, particularly groundwater levels, over the southeast United States. The research reported in this paper evaluates the potential in developing 6-month-ahead groundwater-level forecasts based on the precipitation forecasts from ECHAM 4.5 General Circulation Model Forced with Sea Surface Temperature forecasts. Ten groundwater wells and nine streamgauges from the USGS Groundwater Climate Response Network and Hydro-Climatic Data Network were selected to represent groundwater and surface water flows, respectively, having minimal anthropogenic influences within the Flint River Basin in Georgia, United States. The writers employ two low-dimensional models [principle component regression (PCR) and canonical correlation analysis (CCA)] for predicting groundwater and streamflow at both seasonal and monthly timescales. Three modeling schemes are considered at the beginning of January to predict winter (January, February, and March) and spring (April, May, and June) streamflow and groundwater for the selected sites within the Flint River Basin. The first scheme (model 1) is a null model and is developed using PCR for every streamflow and groundwater site using previous 3-month observations (October, November, and December) available at that particular site as predictors. Modeling schemes 2 and 3 are developed using PCR and CCA, respectively, to evaluate the role of precipitation forecasts in improving monthly and seasonal groundwater predictions. Modeling scheme 3, which employs a CCA approach, is developed for each site by considering observed groundwater levels from nearby sites as predictands. The performance of these three schemes is evaluated using two metrics (correlation coefficient and relative RMS error) by developing groundwater-level forecasts based on leave-five-out cross-validation. Results from the research reported in this paper show that using precipitation forecasts in climate models improves the ability to predict the interannual variability of winter and spring streamflow and groundwater levels over the basin. However, significant conditional bias exists in all the three modeling schemes, which indicates the need to consider improved modeling schemes as well as the availability of longer time-series of observed hydroclimatic information over the basin.

Variability and predictability of the streamflows in Coastal and Andean Ecuador

NASA Astrophysics Data System (ADS)

Quishpe-Vásquez, César; Córdoba-Machado, Samir; Palomino-Lemus, Reiner; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

The main objective of this study is to examine the variability and the predictability in available water resources in Coastal and Andean Ecuador. For this aim, we use the streamflow data from a network of hydrological stations, provided by the National Institute of Meteorology and Hydrology of Ecuador (IHNAMI), distributed over the Ecuadorian territory and strategically located in the watersheds of its main rivers. A number of 20 stations with a continuous period of daily data covering a period of 42 years (1973-2015) were selected. To analyze the spatio-temporal variability of streamflow in Ecuador, principal component analysis (PCA) along with a study of trends have been applied to the streamflow data at monthly time scales. The significance and magnitude of trends have been analyzed using Man-Kendall test and Sen slope. Moreover, to analyze the predictability of the streamflow, the spatio-temporal effects of the ENSO phenomenon on the country have been evaluated through a correlation analysis using different lags between different El Niño indices (Niño 1+2, Niño Modoki, Trans-Niño and Niño 3.4) and the seasonal streamflow. The results show two main regions that differ in terms of variability. We found that the variations in water resources have a close relationship between the magnitude and the seasonal distribution of the streamflow and the ENSO. However, each index shows a different impact on the streamflow depending on the season and the region. In general, the higher correlations between the ENSO indices and the streamflow are observed in the stations closer to the coast. KEY WORDS: Ecuador streamflow; trends; PCA; variability; predictability; ENSO. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Estimates of monthly streamflow characteristics at selected sites in the upper Missouri River basin, Montana, base period water years 1937-86

USGS Publications Warehouse

Parrett, Charles; Johnson, D.R.; Hull, J.A.

1989-01-01

Estimates of streamflow characteristics (monthly mean flow that is exceeded 90, 80, 50, and 20 percent of the time for all years of record and mean monthly flow) were made and are presented in tabular form for 312 sites in the Missouri River basin in Montana. Short-term gaged records were extended to the base period of water years 1937-86, and were used to estimate monthly streamflow characteristics at 100 sites. Data from 47 gaged sites were used in regression analysis relating the streamflow characteristics to basin characteristics and to active-channel width. The basin-characteristics equations, with standard errors of 35% to 97%, were used to estimate streamflow characteristics at 179 ungaged sites. The channel-width equations, with standard errors of 36% to 103%, were used to estimate characteristics at 138 ungaged sites. Streamflow measurements were correlated with concurrent streamflows at nearby gaged sites to estimate streamflow characteristics at 139 ungaged sites. In a test using 20 pairs of gages, the standard errors ranged from 31% to 111%. At 139 ungaged sites, the estimates from two or more of the methods were weighted and combined in accordance with the variance of individual methods. When estimates from three methods were combined the standard errors ranged from 24% to 63 %. A drainage-area-ratio adjustment method was used to estimate monthly streamflow characteristics at seven ungaged sites. The reliability of the drainage-area-ratio adjustment method was estimated to be about equal to that of the basin-characteristics method. The estimate were checked for reliability. Estimates of monthly streamflow characteristics from gaged records were considered to be most reliable, and estimates at sites with actual flow record from 1937-86 were considered to be completely reliable (zero error). Weighted-average estimates were considered to be the most reliable estimates made at ungaged sites. (USGS)

Hydroecology of Intermittent and Ephemeral Streams: Will Landscape Connectivity Sustain Aquatic Organisms in a Changing Climate?

DTIC Science & Technology

2015-07-24

Huachuca. ........... 16 Table 2.1 Number of samples collected per year , season, and hydrological category from each of the 7 streams...reaches are reaches with streamflow during all times of the year . Ephemeral reaches are characterized by short duration streamflow events occurring...continuously for only certain times of the year and are supported by sources such as bedrock springs, melting snow or repeated monsoon events

Spatial and temporal patterns of precipitation and stream flow variations in Tigris-Euphrates river basin.

PubMed

Daggupati, Prasad; Srinivasan, Raghavan; Ahmadi, Mehdi; Verma, Deepa

2017-01-01

Tigris and Euphrates river basin (TERB) is one of the largest river basins in the Middle East, and the precipitation (in the form of snowfall) is a major source of streamflow. This study investigates the spatial and temporal variability of precipitation and streamflow in TERB to better understand the hydroclimatic variables and how they varied over time. The precipitation shows a decreasing trend with 1980s being wetter and 2000s being drier. A total of 55 and 40% reduction in high flows in Tigris and Euphrates rivers at T20 and E3 was seen in post-reservoir period. A lag time of 3 to 4 and 5 to 6 months was estimated between peak snowfall and runoff time periods. Decreasing precipitation and streamflow along with several planned dams could hamper the sustainability of several Mesopotamian marshlands that completely depend on the water from the Tigris and Euphrates rivers.

A proposed streamflow-data program for Utah

USGS Publications Warehouse

Whitaker, G.L.

1970-01-01

An evaluation of the streamflow data available in Utah was made to provide guidelines for planning future programs. The basic steps in the evaluation procedure were (1) definition of the long- term goals of the streamflow-data program in quantitative form, (2) examination and analysis of all available data to determine which goals have already been met, and (3) consideration of alternate programs and techniques to meet the remaining objectives. The principal goals are (1) to provide current streamflow data where needed for water management and (2) to define streamflow characteristics at any point on any stream within a specified accuracy. It was found that the first goal generally is being satisfied but that flow characteristics at ungaged sites cannot be estimated within the specified accuracy by regression analysis with the existing data and model now available. This latter finding indicates the need for some changes in the present data program so that the accuracy goals can be approached by alternate methods. The regression method may be more successful at a future time if a more suitable model can be developed, and if an adequate sample of streamflow records can be obtained in all areas. In the meantime, methods of transferring flow characteristics which require some information at the ungaged site may be used. A modified streamflow-data program based on this study is proposed.

Evaluation of streamflow forecast for the National Water Model of U.S. National Weather Service

NASA Astrophysics Data System (ADS)

Rafieeinasab, A.; McCreight, J. L.; Dugger, A. L.; Gochis, D.; Karsten, L. R.; Zhang, Y.; Cosgrove, B.; Liu, Y.

2016-12-01

The National Water Model (NWM), an implementation of the community WRF-Hydro modeling system, is an operational hydrologic forecasting model for the contiguous United States. The model forecasts distributed hydrologic states and fluxes, including soil moisture, snowpack, ET, and ponded water. In particular, the NWM provides streamflow forecasts at more than 2.7 million river reaches for three forecast ranges: short (15 hr), medium (10 days), and long (30 days). In this study, we verify short and medium range streamflow forecasts in the context of the verification of their respective quantitative precipitation forecasts/forcing (QPF), the High Resolution Rapid Refresh (HRRR) and the Global Forecast System (GFS). The streamflow evaluation is performed for summer of 2016 at more than 6,000 USGS gauges. Both individual forecasts and forecast lead times are examined. Selected case studies of extreme events aim to provide insight into the quality of the NWM streamflow forecasts. A goal of this comparison is to address how much streamflow bias originates from precipitation forcing bias. To this end, precipitation verification is performed over the contributing areas above (and between assimilated) USGS gauge locations. Precipitation verification is based on the aggregated, blended StageIV/StageII data as the "reference truth". We summarize the skill of the streamflow forecasts, their skill relative to the QPF, and make recommendations for improving NWM forecast skill.

Streamflow gains and losses along San Francisquito Creek and characterization of surface-water and ground-water quality, southern San Mateo and northern Santa Clara counties, California, 1996-97

USGS Publications Warehouse

Metzger, Loren F.

2002-01-01

San Francisquito Creek is an important source of recharge to the 22-square-mile San Francisquito Creek alluvial fan ground-water subbasin in the southern San Mateo and northern Santa Clara Counties of California. Ground water supplies as much as 20 percent of the water to some area communities. Local residents are concerned that infiltration and consequently ground-water recharge would be reduced if additional flood-control measures are implemented along San Francisquito Creek. To improve the understanding of the surface-water/ground-water interaction between San Francisquito Creek and the San Francisquito Creek alluvial fan, the U.S. Geological Survey (USGS) estimated streamflow gains and losses along San Francisquito Creek and determined the chemical quality and isotopic composition of surface and ground water in the study area.Streamflow was measured at 13 temporary streamflow-measurement stations to determine streamflow gains and losses along a 8.4-mile section of San Francisquito Creek. A series of five seepage runs between April 1996 and May 1997 indicate that losses in San Francisquito Creek were negligible until it crossed the Pulgas Fault at Sand Hill Road. Streamflow losses increased between Sand Hill Road and Middlefield Road where the alluvial deposits are predominantly coarse-grained and the water table is below the bottom of the channel. The greatest streamflow losses were measured along a 1.8-mile section of the creek between the San Mateo Drive bike bridge and Middlefield Road; average losses between San Mateo Drive and Alma Street and from there to Middlefield Road were 3.1 and 2.5 acre-feet per day, respectively.Downstream from Middlefield Road, streamflow gains and losses owing to seepage may be masked by urban runoff, changes in bank storage, and tidal effects from San Francisco Bay. Streamflow gains measured between Middlefield Road and the 1200 block of Woodland Avenue may be attributable to urban runoff and (or) ground-water inflow. Water-level measurements from nearby wells indicate that the regional water table may coincide with the channel bottom along this reach of San Francisquito Creek, particularly during the winter and early spring when water levels usually reach their maximum. Streamflow losses resumed below the 1200 block of Woodland Avenue, extending downstream to Newell Road. Discharge from a large storm drain between Newell Road and East Bayshore Road may account for the streamflow gains measured between these sites. Streamflow gains were measured between East Bayshore Road and the Palo Alto Municipal Golf Course, but this reach is difficult to characterize because of the probable influence of high tides.Estimated average streamflow losses totaled approximately 1,050 acre-feet per year for the reaches between USGS stream gage 11164500 at Stanford University (upstream of Junipero Serra Boulevard) and the Palo Alto Municipal Golf Course, including approximately 595 acre-feet per year for the 1.8-mile section between San Mateo Drive and Middlefield Road. Approximately 58 percent, or 550 acre-feet, of the total estimated average annual recharge from San Francisquito Creek occurs between the San Mateo Drive and Middlefield Road sites.The chemical composition of San Francisquito Creek water varies as a function of seasonal changes in hydrologic conditions. Measurements of specific conductance indicate that during dry weather and low flow, the dissolved-solids concentrations tends to be high, and during wet weather, the concentration tends to be low owing to dilution by surface water. Compared with water samples from upstream sites at USGS stream gage 11164500 and San Mateo Drive, the samples from the downstream sites at Alma Street and Woodland Avenue had low specific conductance; low concentrations of magnesium, sodium, sulfate, chloride, boron, and total dissolved solids; high nutrient concentrations; and light isotopic compositions indicating that urban runoff constitutes most of the streamflow

Relations of surface-water quality to streamflow in the Hackensack, Passaic, Elizabeth, and Rahway River basins, New Jersey, water years 1976-93

USGS Publications Warehouse

Buxton, Debra E.; Hunchak-Kariouk, Kathryn; Hickman, R. Edward

1998-01-01

Relations of water quality to streamflow were determined for 18 water-quality constituents at 19 surface-water-quality stations within the drainage basins of the Hackensack, Passaic, Elizabeth, and Rahway Rivers in New Jersey for water years 1976-93. Surface-waterquality and streamflow data were evaluated for trends (through time) in constituent concentrations during high and low flows, and relations between constituent concentration and streamflow, and constituent load and streamflow, were determined. Median concentrations were calculated for the entire period of study (water years 1976-93) and for the last 5 years of the period of study (water years 1989-93) to determine whether any large variation in concentration exists between the two periods. Medians also were used to determine the seasonal Kendall’s tau statistic, which was then used to evaluate trends in concentrations during high and low flows.Trends in constituent concentrations during high and low flows were evaluated to determine whether the distribution of the observations changes over time for intermittent (nonpoint storm runoff) or constant (point sources and ground water) sources, respectively. Highand low-flow concentration trends were determined for some constituents at 11 of the 19 waterquality stations; 8 stations have insufficient data to determine trends. Seasonal effects on the relations of concentration to streamflow are evident for 16 of the 18 constituents. Negative slopes of relations of concentration to streamflow, which indicate a decrease in concentration at high flows, predominate over positive slopes because of dilution of instream concentrations from storm runoff.The slopes of the regression lines of load to streamflow were determined in order to show the relative contributions to the instream load from constant (point sources and ground water) and intermittent sources (storm runoff). Greater slope values suggest larger contributions from storm runoff to instream load, which most likely indicate an increased relative importance of nonpoint sources. Load-to-streamflow relations along a stream reach that tend to increase in a downstream direction indicate the increased relative importance of contributions from storm runoff. Likewise, load-to-streamflow relations along a stream reach that tend to decrease in a downstream direction indicate the increased relative importance of point sources and ground-water discharge. For most of the 18 constituents, load-to-streamflow relations at stations along a river reach remain constant or decrease in a downstream direction. The slopes increase in the downstream direction for some or all of the nutrient species at the Ramapo, lower Passaic, and Rahway Rivers; for dissolved solids, dissolved sodium, and dissolved chloride at the lower Passaic River; and for alkalinity and hardness at the Rahway River.

Simultaneous Semi-Distributed Model Calibration Guided by ...

EPA Pesticide Factsheets

Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a solid conceptual classification framework based on our understanding of dominant processes. A Hydrologic Landscape code (5 letter descriptor based on physical and climatic properties) describes each assessment unit area, and these units average area 60km2. The core function of these HL codes is to relate and transfer hydrologically meaningful information between watersheds without the need for streamflow time series. We present a novel approach based on the HL framework to answer the question “How can we calibrate models across separate watersheds simultaneously, guided by our understanding of dominant processes?“. We should be able to apply the same parameterizations to assessment units of common HL codes if 1) the Hydrologic Landscapes contain hydrologic information transferable between watersheds at a sub-watershed-scale and 2) we use a conceptual hydrologic model and parameters that reflect the hydrologic behavior of a watershed. In this study, This work specifically tests the ability or inability to use HL-codes to inform and share model parameters across watersheds in the Pacific Northwest. EPA’s Western Ecology Division has published and is refining a framework for defining la

The hydrologic bench-mark program; a standard to evaluate time-series trends in selected water-quality constituents for streams in Georgia

USGS Publications Warehouse

Buell, G.R.; Grams, S.C.

1985-01-01

Significant temporal trends in monthly pH, specific conductance, total alkalinity, hardness, total nitrite-plus-nitrite nitrogen, and total phosphorus measurements at five stream sites in Georgia were identified using a rank correlation technique, the seasonal Kendall test and slope estimator. These sites include a U.S. Geological Survey Hydrologic Bench-Mark site, Falling Creek near Juliette, and four periodic water-quality monitoring sites. Comparison of raw data trends with streamflow-residual trends and, where applicable, with chemical-discharge trends (instantaneous fluxes) shws that some of these trends are responses to factors other than changing streamflow. Percentages of forested, agricultural, and urban cover with each basin did not change much during the periods of water-quality record, and therefore these non-flow-related trends are not obviously related to changes in land cover or land use. Flow-residual water-quality trends at the Hydrologic Bench-Mark site and at the Chattooga River site probably indicate basin reponses to changes in the chemical quality of atmospheric deposition. These two basins are predominantly forested and have received little recent human use. Observed trends at the other three sites probably indicate basin responses to various land uses and water uses associated with agricultural and urban land or to changes in specific uses. (USGS)

River rating complexity

USGS Publications Warehouse

Holmes, Robert R.

2016-01-01

Accuracy of streamflow data depends on the veracity of the rating model used to derive a continuous time series of discharge from the surrogate variables that can readily be collected autonomously at a streamgage. Ratings are typically represented as a simple monotonic increasing function (simple rating), meaning the discharge is a function of stage alone, however this is never truly the case unless the flow is completely uniform at all stages and in transitions from one stage to the next. For example, at some streamflow-monitoring sites the discharge on the rising limb of the hydrograph is discernably larger than the discharge at the same stage on the falling limb of the hydrograph. This is the so-called “loop rating curve” (loop rating). In many cases, these loops are quite small and variation between rising- and falling-limb discharge measurements made at the same stage are well within the accuracy of the measurements. However, certain hydraulic conditions can produce a loop that is large enough to preclude use of a monotonic rating. A detailed data campaign for the Mississippi River at St. Louis, Missouri during a multi-peaked flood over a 56-day period in 2015 demonstrates the rating complexity at this location. The shifting-control method used to deal with complexity at this site matched all measurements within 8%.

Flood of April 1975 at Lansing, Michigan

USGS Publications Warehouse

Miller, John B.; Swallow, L.A.

1975-01-01

On April 18 between 5 p.m. and 12 p.m. an intense rainstorm fell in the Lansing area resulting in extensive flooding.  The Federal Disaster Assistance Administration estimated that 175 homes were damaged to at least half their value, 4,500 received some damage, with additional losses to schools, utilities, hospitals, and transportation systems.  Early estimates indicated that damages may be as high as $20 million.During the time of flooding the U.S. Geological Survey obtained aerial photography and streamflow data to document the disaster.  This report shows on photomosaic base maps the extent of flooding in the Lansing area.  Areas included are the lower reaches of the Red Cedar River and Sycamore Creek and the Grand River downstream from the confluence of the Red Cedar River.  Little flooding occurred on the Grand River upstream from the Red Cedar so, although aerial photography was obtained for that reach, photomosaics were not prepared.  Streamflow data collected at five gaging stations near Lansing are given.  Information on the magnitude of the flood should be useful in making decisions regarding use of flood plains in the area.  It is one of a series of reports on the April 1975 flood in the Lansing metropolitan area.

Hazard function theory for nonstationary natural hazards

DOE PAGES

Read, Laura K.; Vogel, Richard M.

2016-04-11

Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e., that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field ofmore » hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series ( X) with its failure time series ( T), enabling computation of corresponding average return periods, risk, and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied generalized Pareto model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. As a result, our theoretical analysis linking hazard random variable  X with corresponding failure time series  T should have application to a wide class of natural hazards with opportunities for future extensions.« less

Hazard function theory for nonstationary natural hazards

DOE Office of Scientific and Technical Information (OSTI.GOV)

Read, Laura K.; Vogel, Richard M.

Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e., that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field ofmore » hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series ( X) with its failure time series ( T), enabling computation of corresponding average return periods, risk, and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied generalized Pareto model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. As a result, our theoretical analysis linking hazard random variable  X with corresponding failure time series  T should have application to a wide class of natural hazards with opportunities for future extensions.« less

Parameterisation of rainfall-runoff models for forecasting low and average flows, I: Conceptual modelling

NASA Astrophysics Data System (ADS)

Castiglioni, S.; Toth, E.

2009-04-01

In the calibration procedure of continuously-simulating models, the hydrologist has to choose which part of the observed hydrograph is most important to fit, either implicitly, through the visual agreement in manual calibration, or explicitly, through the choice of the objective function(s). Changing the objective functions it is in fact possible to emphasise different kind of errors, giving them more weight in the calibration phase. The objective functions used for calibrating hydrological models are generally of the quadratic type (mean squared error, correlation coefficient, coefficient of determination, etc) and are therefore oversensitive to high and extreme error values, that typically correspond to high and extreme streamflow values. This is appropriate when, like in the majority of streamflow forecasting applications, the focus is on the ability to reproduce potentially dangerous flood events; on the contrary, if the aim of the modelling is the reproduction of low and average flows, as it is the case in water resource management problems, this may result in a deterioration of the forecasting performance. This contribution presents the results of a series of automatic calibration experiments of a continuously-simulating rainfall-runoff model applied over several real-world case-studies, where the objective function is chosen so to highlight the fit of average and low flows. In this work a simple conceptual model will be used, of the lumped type, with a relatively low number of parameters to be calibrated. The experiments will be carried out for a set of case-study watersheds in Central Italy, covering an extremely wide range of geo-morphologic conditions and for whom at least five years of contemporary daily series of streamflow, precipitation and evapotranspiration estimates are available. Different objective functions will be tested in calibration and the results will be compared, over validation data, against those obtained with traditional squared functions. A companion work presents the results, over the same case-study watersheds and observation periods, of a system-theoretic model, again calibrated for reproducing average and low streamflows.

ModABa Model: Annual Flow Duration Curves Assessment in Ephemeral Basins

NASA Astrophysics Data System (ADS)

Pumo, Dario; Viola, Francesco; Noto, Leonardo V.

2013-04-01

A representation of the streamflow regime for a river basin is required for a variety of hydrological analyses and engineering applications, from the water resource allocation and utilization to the environmental flow management. The flow duration curve (FDC) represents a comprehensive signature of temporal runoff variability often used to synthesize catchment rainfall-runoff responses. Several models aimed to the theoretical reconstruction of the FDC have been recently developed under different approaches, and a relevant scientific knowledge specific to this topic has been already acquired. In this work, a new model for the probabilistic characterization of the daily streamflows in perennial and ephemeral catchments is introduced. The ModABa model (MODel for Annual flow duration curves assessment in intermittent BAsins) can be thought as a wide mosaic whose tesserae are frameworks, models or conceptual schemes separately developed in different recent studies. Such tesserae are harmoniously placed and interconnected, concurring together towards a unique final aim that is the reproduction of the FDC of daily streamflows in a river basin. Two separated periods within the year are firstly identified: a non-zero period, typically characterized by significant streamflows, and a dry period, that, in the cases of ephemeral basins, is the period typically characterized by absence of streamflow. The proportion of time the river is dry, providing an estimation of the probability of zero flow occurring, is empirically estimated. Then, an analysis concerning the non-zero period is performed, considering the streamflow disaggregated into a slow subsuperficial component and a fast superficial component. A recent analytical model is adopted to derive the non zero FDC relative to the subsuperficial component; this last is considered to be generated by the soil water excess over the field capacity in the permeable portion of the basin. The non zero FDC relative to the fast streamflow component is directly derived from the precipitation duration curve through a simple filter model. The fast component of streamflow is considered to be formed by two contributions that are the entire amount of rainfall falling onto the impervious portion of the basin and the excess of rainfall over a fixed threshold, defining heavy rain events, falling onto the permeable portion. The two obtained FDCs are then overlapped, providing a unique non-zero FDC relative to the total streamflow. Finally, once the probability that the river is dry and the non zero FDC are known, the annual FDC of the daily total streamflow is derived applying the theory of total probability. The model is calibrated on a small catchment with ephemeral streamflows using a long period of daily precipitation, temperature and streamflow measurements, and it is successively validated in the same basin using two different time periods. The high model performances obtained in both the validation periods, demonstrate how the model, once calibrated, is able to accurately reproduce the empirical FDC starting from easily derivable parameters arising from a basic ecohydrological knowledge of the basin and commonly available climatic data such as daily precipitation and temperatures. In this sense, the model reveals itself as a valid tool for streamflow predictions in ungauged basins.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

NASA Astrophysics Data System (ADS)

Long, A. J.

2015-03-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

The missing mountain water: Slower westerlies decrease orographic enhancement in the Pacific Northwest USA

Treesearch

C. H. Luce; J. T. Abatzoglou; Z. A. Holden

2013-01-01

Trends in streamflow timing and volume in the Pacific Northwest United States have been attributed to increased temperatures because trends in precipitation at lower elevation stations were negligible. We demonstrate that observed streamflow declines likely are associated with declines in mountain precipitation, revealing previously unexplored differential trends....

Quantification of surface water and groundwater flows to open‐ and closed‐basin lakes in a headwaters watershed using a descriptive oxygen stable isotope model

USGS Publications Warehouse

Stets, Edward G.; Winter, Thomas C.; Rosenberry, Donald O.; Striegl, Robert G.

2010-01-01

Accurate quantification of hydrologic fluxes in lakes is important to resource management and for placing hydrologic solute flux in an appropriate biogeochemical context. Water stable isotopes can be used to describe water movements, but they are typically only effective in lakes with long water residence times. We developed a descriptive time series model of lake surface water oxygen‐18 stable isotope signature (δL) that was equally useful in open‐ and closed‐basin lakes with very different hydrologic residence times. The model was applied to six lakes, including two closed‐basin lakes and four lakes arranged in a chain connected by a river, located in a headwaters watershed. Groundwater discharge was calculated by manual optimization, and other hydrologic flows were constrained by measured values including precipitation, evaporation, and streamflow at several stream gages. Modeled and observed δL were highly correlated in all lakes (r = 0.84–0.98), suggesting that the model adequately described δL in these lakes. Average modeled stream discharge at two points along the river, 16,000 and 11,800 m3d−1, compares favorably with synoptic measurement of stream discharge at these sites, 17,600 and 13,700 m3 d−1, respectively. Water yields in this watershed were much higher, 0.23–0.45 m, than water yields calculated from gaged streamflow in regional rivers, approximately 0.10 m, suggesting that regional groundwater discharge supports water flux through these headwaters lakes. Sensitivity and robustness analyses also emphasized the importance of considering hydrologic residence time when designing a sampling protocol for stable isotope use in lake hydrology studies.

Basin characteristics, history of stream gaging, and statistical summary of selected streamflow records for the Rapid Creek basin, western South Dakota

USGS Publications Warehouse

Driscoll, Daniel G.; Zogorski, John S.

1990-01-01

The report presents a summary of basin characteristics affecting streamflow, a history of the U.S. Geological Survey 's stream-gaging program, and a compilation of discharge records and statistical summaries for selected sites within the Rapid Creek basin. It is the first in a series which will investigate surface-water/groundwater relations along Rapid Creek. The summary of basin characteristics includes descriptions of the geology and hydrogeology, physiography and climate, land use and vegetation, reservoirs, and water use within the basin. A recounting of the U.S. Geological Survey 's stream-gaging program and a tabulation of historic stream-gaging stations within the basin are furnished. A compilation of monthly and annual mean discharge values for nine currently operated, long-term, continuous-record, streamflow-gaging stations on Rapid Creek is presented. The statistical summary for each site includes summary statistics on monthly and annual mean values, correlation matrix for monthly values, serial correlation for 1 year lag for monthly values, percentile rankings for monthly and annual mean values, low and high value tables, duration curves, and peak-discharge tables. Records of monthend contents for two reservoirs within the basin also are presented. (USGS)

Remotely sensed soil moisture input to a hydrologic model

NASA Technical Reports Server (NTRS)

Engman, E. T.; Kustas, W. P.; Wang, J. R.

1989-01-01

The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing in the Wind River Range, Wyoming

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.

2010-01-01

MODIS-derived snow cover measured on 30 April in any given year explains approximately 89 % of the variance in stream discharge for maximum monthly streamflow in that year. Observed changes in streamflow appear to be related to increasing maximum air temperatures over the last four decades causing lower spring snow-cover extent. The majority (>70%) of the water supply in the western United States comes from snowmelt, thus analysis of the declining spring snowpack (and resulting declining stream discharge) has important implications for streamflow management in the drought-prone western U.S.

Effects of rapid urbanization on streamflow, erosion, and sedimentation in a desert stream in the American Southwest

USGS Publications Warehouse

Whitney, John W.; Glancy, Patrick A.; Buckingham , Susan E.; Ehrenberg, Arthur C.

2015-01-01

Rapid urbanization has resulted in a series of sequential effects on a desert stream in the American Southwest. Lower Las Vegas Wash was a dry wash characterized by infrequent flood deposition when Las Vegas, Nevada was established in 1905. Wastewater effluent was discharged into the wash in low volumes for over 3 decades. Wastewater volumes increased commensurably with accelerated population growth during the late 20th century and created a sequence of feedback effects on the floodplain. Initially slow saturation of the valley fill created a desert oasis of dense floodplain vegetation and wetlands. Annual streamflow began in 1958 and erosion began a decade later with shallow incision in discontinuous channel segments. Increasing baseflow gradually enlarged channels; headcutting was active during the 1970s to 1984. The incised channels concentrated storm runoff, which accelerated local channel erosion, and in 1984 the headcuts were integrated during a series of monsoon floods. Wetlands were drained and most floodplain vegetation destroyed. Channel erosion continued unabated until engineering interventions began in the 21st century. No natural channel recovery occurred after initial urbanization effects because streamflow never stabilized in the late 20th century. A 6.6 M m3 sediment slug, eroded from the wash in ∼25 years, was deposited in Las Vegas Bay in Lake Mead. Falling reservoir levels during the 21st century are responsible for sediment redistribution and infilling of the bay. Close monitoring of impacts is recommended when urban wastewater and storm runoff are discharged on a desert wash. Channel interventions, when necessary, are advised in order to prevent costly engineering schemes of channel stabilization, flood control, and floodplain restoration.

The Use of Oceanic Indices Variations Due to Climate Change to Predict Annual Discharge Variations in Northeastern United States

NASA Astrophysics Data System (ADS)

Berton, R.; Shaw, S. B.; Chandler, D. G.; Driscoll, C. T.

2014-12-01

Climatic change affects streamflow in watersheds with winter snowpack and an annual snowmelt hydrograph. In the northeastern US, changes in streamflow are driven by both the advanced timing of snowmelt and increasing summer precipitation. Projections of climate for the region in the 21st century is for warmer winters and wetter summers. Water planners need to understand future changes in flow metrics to determine if the current water resources are capable of fulfilling future demands or adapting to future changes in climate. The study of teleconnection patterns between oceanic indices variations and hydrologic variables may help improve the understanding of future water resources conditions in a watershed. The purpose of this study is to evaluate the correlation between oceanic indices and discharge variations in the Merrimack Watershed. The Merrimack Watershed is the fourth largest basin in New England which drains much of New Hampshire and northeastern portions of Massachusetts, USA. Variations in sea surface temperature (SST) and sea level pressure (SLP) are defined by the Atlantic Multi-decadal Oscillation (AMO) and the North Atlantic Oscillation (NAO), respectively. We hypothesize that temporal changes in discharge are related to AMO and NAO variations since precipitation and discharge are highly correlated in the Merrimack. The Merrimack Watershed consists of undisturbed (reference) catchments and disturbed (developed) basins with long stream gauge records (> 100 years). Developed basins provide an opportunity to evaluate the impacts of river regulation and land development on teleconnection patterns as well as changing climate. Time series of AMO and NAO indices over the past 150 years along with Merrimack annual precipitation and discharge time series have shown a 1 to 2-year watershed hydrologic memory; higher correlation between Merrimack‎ annual precipitation and discharge with AMO and NAO are observed when a 1 to 2-year lag is given to AMO and NAO indices. For instance, the mean correlation of AMO with precipitation/discharge for a zero-year lag was 0.16/0.09 and increased to 0.26/0.23 for a 1-year lag. Our study provides an insight on the lagged hydrologic response of reference catchments and developed basins to variations in oceanic indices.

Acoustic systems for the measurement of streamflow

USGS Publications Warehouse

Laenen, Antonius; Smith, Winchell

1983-01-01

The acoustic velocity meter (AVM), also referred to as an ultrasonic flowmeter, has been an operational tool for the measurement of streamflow since 1965. Very little information is available concerning AVM operation, performance, and limitations. The purpose of this report is to consolidate information in such a manner as to provide a better understanding about the application of this instrumentation to streamflow measurement. AVM instrumentation is highly accurate and nonmechanical. Most commercial AVM systems that measure streamflow use the time-of-travel method to determine a velocity between two points. The systems operate on the principle that point-to-point upstream travel-time of sound is longer than the downstream travel-time, and this difference can be monitored and measured accurately by electronics. AVM equipment has no practical upper limit of measurable velocity if sonic transducers are securely placed and adequately protected. AVM systems used in streamflow measurement generally operate with a resolution of ?0.01 meter per second but this is dependent on system frequency, path length, and signal attenuation. In some applications the performance of AVM equipment may be degraded by multipath interference, signal bending, signal attenuation, and variable streamline orientation. Presently used minicomputer systems, although expensive to purchase and maintain, perform well. Increased use of AVM systems probably will be realized as smaller, less expensive, and more conveniently operable microprocessor-based systems become readily available. Available AVM equipment should be capable of flow measurement in a wide variety of situations heretofore untried. New signal-detection techniques and communication linkages can provide additional flexibility to the systems so that operation is possible in more river and estuary situations.

On the sensitivity of annual streamflow to air temperature

USGS Publications Warehouse

Milly, Paul C.D.; Kam, Jonghun; Dunne, Krista A.

2018-01-01

Although interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration ( ), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness ( /P) at an annual time scale is identical to that linking interbasin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently.

Global analysis of seasonal streamflow predictability using an ensemble prediction system and observations from 6192 small catchments worldwide

NASA Astrophysics Data System (ADS)

van Dijk, Albert I. J. M.; Peña-Arancibia, Jorge L.; Wood, Eric F.; Sheffield, Justin; Beck, Hylke E.

2013-05-01

Ideally, a seasonal streamflow forecasting system would ingest skilful climate forecasts and propagate these through calibrated hydrological models initialized with observed catchment conditions. At global scale, practical problems exist in each of these aspects. For the first time, we analyzed theoretical and actual skill in bimonthly streamflow forecasts from a global ensemble streamflow prediction (ESP) system. Forecasts were generated six times per year for 1979-2008 by an initialized hydrological model and an ensemble of 1° resolution daily climate estimates for the preceding 30 years. A post-ESP conditional sampling method was applied to 2.6% of forecasts, based on predictive relationships between precipitation and 1 of 21 climate indices prior to the forecast date. Theoretical skill was assessed against a reference run with historic forcing. Actual skill was assessed against streamflow records for 6192 small (<10,000 km2) catchments worldwide. The results show that initial catchment conditions provide the main source of skill. Post-ESP sampling enhanced skill in equatorial South America and Southeast Asia, particularly in terms of tercile probability skill, due to the persistence and influence of the El Niño Southern Oscillation. Actual skill was on average 54% of theoretical skill but considerably more for selected regions and times of year. The realized fraction of the theoretical skill probably depended primarily on the quality of precipitation estimates. Forecast skill could be predicted as the product of theoretical skill and historic model performance. Increases in seasonal forecast skill are likely to require improvement in the observation of precipitation and initial hydrological conditions.

Impacts of climate change on forest phenology and implications for streamflow in the central Appalachian Mountains region, United States

NASA Astrophysics Data System (ADS)

Zegre, N.; Gaertner, B. A.; Fernandez, R.

2016-12-01

The timing of phenological parameters such as spring onset and autumn senescence are important controls on the partitioning of water into evaporation and streamflow. Climate largely drives seasonal characteristics of plants and changes in phenological timing can be used to detect the impacts of climate change on water balance controls. However, limited phenological research is available for regions dominated by forest cover such as the central Appalachian Mountains region of the United States. To quantify the impacts of climate change on phenological timing and streamflow in this region, we used GIMMS AVHRR NDVI 13g data from 1982-2012 and the TIMESAT program to extract seasonality parameters. Results show that spring onset has advanced by 9 days, autumn senescence has been delayed by 11 days, and growing season has lengthened by 20 days. Above 500 m elevation, spring onset occurs 2-3 days later; fall senescence arrives 1-2 days earlier, and growing season shortens by 3-5 days. Streamflow has decreased during the growing season over the 31-year study period throughout the region, with the most pronounced effects for the Tennessee River watershed, the southernmost reach of the study area. The elevation patterns are in general agreement with Hopkins law, which states a one-day delay in spring onset for every 30-meter increase in elevation. Streamflow patterns suggest that the southern central Appalachian region is sensitive to changes in climate and are becoming drier, having important implications for drinking water supply, forest ecosystem management, ecosystem services including drinking water supply, and overall forest health.

Monthly streamflow forecasting in the Rhine basin

NASA Astrophysics Data System (ADS)

Schick, Simon; Rössler, Ole; Weingartner, Rolf

2017-04-01

Forecasting seasonal streamflow of the Rhine river is of societal relevance as the Rhine is an important water way and water resource in Western Europe. The present study investigates the predictability of monthly mean streamflow at lead times of zero, one, and two months with the focus on potential benefits by the integration of seasonal climate predictions. Specifically, we use seasonal predictions of precipitation and surface air temperature released by the European Centre for Medium-Range Weather Forecasts (ECMWF) for a regression analysis. In order to disentangle forecast uncertainty, the 'Reverse Ensemble Streamflow Prediction' framework is adapted here to the context of regression: By using appropriate subsets of predictors the regression model is constrained to either the initial conditions, the meteorological forcing, or both. An operational application is mimicked by equipping the model with the seasonal climate predictions provided by ECMWF. Finally, to mitigate the spatial aggregation of the meteorological fields the model is also applied at the subcatchment scale, and the resulting predictions are combined afterwards. The hindcast experiment is carried out for the period 1982-2011 in cross validation mode at two gauging stations, namely the Rhine at Lobith and Basel. The results show that monthly forecasts are skillful with respect to climatology only at zero lead time. In addition, at zero lead time the integration of seasonal climate predictions decreases the mean absolute error by 5 to 10 percentage compared to forecasts which are solely based on initial conditions. This reduction most likely is induced by the seasonal prediction of precipitation and not air temperature. The study is completed by bench marking the regression model with runoff simulations from ECMWFs seasonal forecast system. By simply using basin averages followed by a linear bias correction, these runoff simulations translate well to monthly streamflow. Though the regression model is only slightly outperformed, we argue that runoff out of the land surface component of seasonal climate forecasting systems is an interesting option when it comes to seasonal streamflow forecasting in large river basins.

Computer programs for describing the recession of ground-water discharge and for estimating mean ground-water recharge and discharge from streamflow records-update

USGS Publications Warehouse

Rutledge, A.T.

1998-01-01

The computer programs included in this report can be used to develop a mathematical expression for recession of ground-water discharge and estimate mean ground-water recharge and discharge. The programs are intended for analysis of the daily streamflow record of a basin where one can reasonably assume that all, or nearly all, ground water discharges to the stream except for that which is lost to riparian evapotranspiration, and where regulation and diversion of flow can be considered to be negligible. The program RECESS determines the master reces-sion curve of streamflow recession during times when all flow can be considered to be ground-water discharge and when the profile of the ground-water-head distribution is nearly stable. The method uses a repetitive interactive procedure for selecting several periods of continuous recession, and it allows for nonlinearity in the relation between time and the logarithm of flow. The program RORA uses the recession-curve displacement method to estimate the recharge for each peak in the streamflow record. The method is based on the change in the total potential ground-water discharge that is caused by an event. Program RORA is applied to a long period of record to obtain an estimate of the mean rate of ground-water recharge. The program PART uses streamflow partitioning to estimate a daily record of base flow under the streamflow record. The method designates base flow to be equal to streamflow on days that fit a requirement of antecedent recession, linearly interpolates base flow for other days, and is applied to a long period of record to obtain an estimate of the mean rate of ground-water discharge. The results of programs RORA and PART correlate well with each other and compare reasonably with results of the corresponding manual method.

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

USGS Publications Warehouse

Dudley, Robert W.; Nielsen, Martha G.

2011-01-01

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature resulting from changes forecast for air temperature and precipitation.

Groundwater Pumping and Streamflow in the Yuba Basin, Sacramento Valley, California

NASA Astrophysics Data System (ADS)

Moss, D. R.; Fogg, G. E.; Wallender, W. W.

2011-12-01

Water transfers during drought in California's Sacramento Valley can lead to increased groundwater pumping, and as yet unknown effects on stream baseflow. Two existing groundwater models of the greater Sacramento Valley together with localized, monitoring of groundwater level fluctuations adjacent to the Bear, Feather, and Yuba Rivers, indicate cause and effect relations between the pumping and streamflow. The models are the Central Valley Hydrologic Model (CVHM) developed by the U.S. Geological Survey and C2VSIM developed by Department of Water Resources. Using two models which have similar complexity and data but differing approaches to the agricultural water boundary condition illuminates both the water budget and its uncertainty. Water budget and flux data for localized areas can be obtained from the models allowing for parameters such as precipitation, irrigation recharge, and streamflow to be compared to pumping on different temporal scales. Continuous groundwater level measurements at nested, near-stream piezometers show seasonal variations in streamflow and groundwater levels as well as the timing and magnitude of recharge and pumping. Preliminary results indicate that during years with relatively wet conditions 65 - 70% of the surface recharge for the groundwater system comes from irrigation and precipitation and 30 - 35% comes from streamflow losses. The models further indicate that during years with relatively dry conditions, 55 - 60% of the surface recharge for the groundwater system comes from irrigation and precipitation while 40 - 45% comes from streamflow losses. The models irrigation water demand, surface-water and groundwater supply, and deep percolation are integrated producing values for irrigation pumping. Groundwater extractions during the growing season, approximately between April and October, increase by almost 200%. The effects of increased pumping seasonally are not readily evident in stream stage measurements. However, during dry time periods net streamflow gains are about half of the gains seen during wet period.

Hydrograph separation techniques in snowmelt-dominated watersheds

NASA Astrophysics Data System (ADS)

Miller, S.; Miller, S. N.

2017-12-01

This study integrates hydrological, geochemical, and isotopic data for a better understanding of different streamflow generation pathways and residence times in a snowmelt-dominated region. A nested watershed design with ten stream gauging sites recording sub-hourly stream stage has been deployed in a snowmelt-dominated region in southeastern Wyoming, heavily impacted by the recent bark beetle epidemic. LiDAR-derived digital elevation models help elucidate effects from topography and watershed metrics. At each stream gauging site, sub-hourly stream water conductivity and temperature data are also recorded. Hydrograph separation is a useful technique for determining different sources of runoff and how volumes from each source vary over time. Following previous methods, diurnal cycles from sub-hourly recorded streamflow and specific conductance data are analyzed and used to separate hydrographs into overland flow and baseflow components, respectively. A final component, vadose-zone flow, is assumed to be the remaining water from the total hydrograph. With access to snowmelt and precipitation data from nearby instruments, runoff coefficients are calculated for the different mechanisms, providing information on watershed response. Catchments are compared to understand how different watershed characteristics translate snowmelt or precipitation events into runoff. Portable autosamplers were deployed at two of the gauging sites for high-frequency analysis of stream water isotopic composition during peak flow to compare methods of hydrograph separation. Sampling rates of one or two hours can detect the diurnal streamflow cycle common during peak snowmelt. Prior research suggests the bark beetle epidemic has had little effect on annual streamflow patterns; however, several results show an earlier shift in the day of year in which peak annual streamflow is observed. The diurnal cycle is likely to comprise a larger percentage of daily streamflow during snowmelt in post-epidemic forests, as more solar radiation is available to penetrate to the ground surface and induce snowmelt, contributing to the effect of an earlier observed peak annual streamflow.

A Statistical Weather-Driven Streamflow Model: Enabling future flow predictions in data-scarce headwater streams

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.

2014-12-01

Predicting streamflow in headwaters and over a broad spatial scale pose unique challenges due to limited data availability. Flow observation gages for headwaters streams are less common than for larger rivers, and gages with records lengths of ten year or more are even more scarce. Thus, there is a great need for estimating streamflows in ungaged or sparsely-gaged headwaters. Further, there is often insufficient basin information to develop rainfall-runoff models that could be used to predict future flows under various climate scenarios. Headwaters in the northeastern U.S. are of particular concern to aquatic biologists, as these stream serve as essential habitat for native coldwater fish. In order to understand fish response to past or future environmental drivers, estimates of seasonal streamflow are needed. While there is limited flow data, there is a wealth of data for historic weather conditions. Observed data has been modeled to interpolate a spatially continuous historic weather dataset. (Mauer et al 2002). We present a statistical model developed by pairing streamflow observations with precipitation and temperature information for the same and preceding time-steps. We demonstrate this model's use to predict flow metrics at the seasonal time-step. While not a physical model, this statistical model represents the weather drivers. Since this model can predict flows not directly tied to reference gages, we can generate flow estimates for historic as well as potential future conditions.

Surface-Water Techniques: On Demand Training Opportunities

USGS Publications Warehouse

,

2007-01-01

The U.S. Geological Survey (USGS) has been collecting streamflow information since 1889 using nationally consistent methods. The need for such information was envisioned by John Wesley Powell as a key component for settlement of the arid western United States. Because of Powell?s vision the nation now has a rich streamflow data base that can be analyzed with confidence in both space and time. This means that data collected at a stream gaging station in Maine in 1903 can be compared to data collected in 2007 at the same gage in Maine or at a different gage in California. Such comparisons are becoming increasingly important as we work to assess climate variability and anthropogenic effects on streamflow. Training employees in proper and consistent techniques to collect and analyze streamflow data forms a cornerstone for maintaining the integrity of this rich data base.

The influence of major dams on hydrology through the drainage network of the Sacramento River basin, California

USGS Publications Warehouse

Singer, M.B.

2007-01-01

This paper reports basinwide patterns of hydrograph alteration via statistical and graphical analysis from a network of long-term streamflow gauges located various distances downstream of major dams and confluences in the Sacramento River basin in California, USA. Streamflow data from 10 gauging stations downstream of major dams were divided into hydrologic series corresponding to the periods before and after dam construction. Pre- and post-dam flows were compared with respect to hydrograph characteristics representing frequency, magnitude and shape: annual flood peak, annual flow trough, annual flood volume, time to flood peak, flood drawdown time and interarrival time. The use of such a suite of characteristics within a statistical and graphical framework allows for generalising distinct strategies of flood control operation that can be identified without any a priori knowledge of operations rules. Dam operation is highly dependent on the ratio of reservoir capacity to annual flood volume (impounded runoff index). Dams with high values of this index generally completely cut off flood peaks thus reducing time to peak, drawdown time and annual flood volume. Those with low values conduct early and late flow releases to extend the hydrograph, increasing time to peak, drawdown time and annual flood volume. The analyses reveal minimal flood control benefits from foothill dams in the lower Sacramento River (i.e. dissipation of the down-valley flood control signal). The lower part of the basin is instead reliant on a weir and bypass system to control lowland flooding. Data from a control gauge (i.e. with no upstream dams) suggest a background signature of global climate change expressed as shortened flood hydrograph falling limbs and lengthened flood interarrival times at low exceedence probabilities. This research has implications for flood control, water resource management, aquatic and riparian ecosystems and for rehabilitation strategies involving flow alteration and/or manipulation of sediment supplies. Copyright ?? 2006 John Wiley & Sons, Ltd.

Map showing selected surface-water data for the Nephi 30 x 60-minute quadrangle, Utah

USGS Publications Warehouse

Price, Don

1984-01-01

This is one of a series of maps that describe the geology and related natural resources of the Nephi 30 x 60 minute quadrangle, Utah. Streamflow records used to compile this map were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Transportation. The principal runoff-producing areas shown on the map were delineated from a work map (scale 1:250,000) compiled to estimate water yields in Utah (Bagley and others, 1964). Sources of information about recorded floods resulting from cloudbursts included Woolley (1946) and Butler and Marsell (1972); sources of information about the chemical quality of streamflow included Hahl and Cabell (1965) Mundorff (1972 and 1974), and Waddell and others (1982).

The intrinsic dependence structure of peak, volume, duration, and average intensity of hyetographs and hydrographs

NASA Astrophysics Data System (ADS)

Serinaldi, Francesco; Kilsby, Chris G.

2013-06-01

The information contained in hyetographs and hydrographs is often synthesized by using key properties such as the peak or maximum value Xp, volume V, duration D, and average intensity I. These variables play a fundamental role in hydrologic engineering as they are used, for instance, to define design hyetographs and hydrographs as well as to model and simulate the rainfall and streamflow processes. Given their inherent variability and the empirical evidence of the presence of a significant degree of association, such quantities have been studied as correlated random variables suitable to be modeled by multivariate joint distribution functions. The advent of copulas in geosciences simplified the inference procedures allowing for splitting the analysis of the marginal distributions and the study of the so-called dependence structure or copula. However, the attention paid to the modeling task has overlooked a more thorough study of the true nature and origin of the relationships that link Xp,V,D, and I. In this study, we apply a set of ad hoc bootstrap algorithms to investigate these aspects by analyzing the hyetographs and hydrographs extracted from 282 daily rainfall series from central eastern Europe, three 5 min rainfall series from central Italy, 80 daily streamflow series from the continental United States, and two sets of 200 simulated universal multifractal time series. Our results show that all the pairwise dependence structures between Xp,V,D, and I exhibit some key properties that can be reproduced by simple bootstrap algorithms that rely on a standard univariate resampling without resort to multivariate techniques. Therefore, the strong similarities between the observed dependence structures and the agreement between the observed and bootstrap samples suggest the existence of a numerical generating mechanism based on the superposition of the effects of sampling data at finite time steps and the process of summing realizations of independent random variables over random durations. We also show that the pairwise dependence structures are weakly dependent on the internal patterns of the hyetographs and hydrographs, meaning that the temporal evolution of the rainfall and runoff events marginally influences the mutual relationships of Xp,V,D, and I. Finally, our findings point out that subtle and often overlooked deterministic relationships between the properties of the event hyetographs and hydrographs exist. Confusing these relationships with genuine stochastic relationships can lead to an incorrect application of multivariate distributions and copulas and to misleading results.

A precipitation-runoff model for the analysis of the effects of water withdrawals and land-use change on streamflow in the Usquepaug-Queen River Basin, Rhode Island

USGS Publications Warehouse

Zarriello, Phillip J.; Bent, Gardner C.

2004-01-01

The 36.1-square-mile UsquepaugQueen River Basin in south-central Rhode Island is an important water resource. Streamflow records indicate that withdrawals may have diminished flows enough to affect aquatic habitat. Concern over the effect of withdrawals on streamflow and aquatic habitat prompted the development of a Hydrologic Simulation ProgramFORTRAN (HSPF) model to evaluate the water-management alternatives and land-use change in the basin. Climate, streamflow, and water-use data were collected to support the model development. A logistic-regression equation was developed for long-term simulations to predict the likelihood of irrigation, the primary water use in the basin, from antecedent potential evapotranspiration and precipitation for generating irrigation demands. The HSPF model represented the basin by 13 pervious-area and 2 impervious-area land-use segments and 20 stream reaches. The model was calibrated to the period January 1, 2000 to September 30, 2001, at three continuous streamflow-gaging stations that monitor flow from 10, 54, and 100 percent of the basin drainage area. Hydrographs and flow-duration curves of observed and simulated discharges, along with statistics compiled for various model-fit metrics, indicate a satisfactory model performance. The calibrated HSPF model was modified to evaluate streamflow (1) under no withdrawals to streamflow under current (200001) withdrawal conditions under long-term (19602001) climatic conditions, (2) under withdrawals by the former Ladd School water-supply wells, and (3) under fully developed land use. The effects of converting from direct-stream withdrawals to ground-water withdrawals were evaluated outside of the HSPF model by use of the STRMDEPL program, which calculates the time delayed response of ground-water withdrawals on streamflow depletion. Simulated effects of current withdrawals relative to no withdrawals indicate about a 20-percent decrease in the lowest mean daily streamflows at the basin outlet, but withdrawals have little effect on flows that are exceeded less than about 90 percent of the time. Tests of alternative model structures to evaluate model uncertainty indicate that the lowest mean daily flows ranged between 3 and 5 cubic feet per second (ft3/s) without withdrawals and 2.2 to 4 ft3/s with withdrawals. Changes in the minimum daily streamflows are more pronounced, however; at the upstream streamflow-gaging station, a minimum daily flow of 0.2 ft3/s was sustained without withdrawals, but simulations with withdrawals indicate that the reach would stop flowing part of a day about 5 percent of the time. The effect on streamflow of potential ground-water withdrawals of 0.20, 0.90, and 1.78 million gallons per day (Mgal/d) at the former Ladd School near the central part of the basin were evaluated. The lowest daily mean flows in model reach 3, the main stem of the Queen River closest to the pumped wells, decreased by about 50 percent for withdrawals of 0.20 Mgal/d (from about 0.4 to 0.2 ft3/s) in comparison to current withdrawals. Reach 3 would occasionally stop flowing during part of the day at the 0.20-Mgal/d withdrawal rate because of diurnal fluctuation in streamflow. The higher withdrawal rates (0.90 and 1.78 Mgal/d) would cause reach 3 to stop flowing about 10 to 20 percent of the time, but the effects of pumping rapidly diminished downstream because of tributary inflows. Simulation results indicate little change in the annual 1-, 7-, and 30-day low flows at the 0.20 Mgal/d pumping rate, but at the 1.78 Mgal/d pumping rate, reach 3 stopped flowing for nearly a 7-day period every year and for a 30-day period about every other year. At the 0.90 Mgal/d pumping rate, reach 3 stopped flowing about every other year for a 7-day period and about once every 5 years for a 30-day period. Land-use change was simulated by converting model hydrologic-response units (HRUs) representing undeveloped areas to HRUs representing developed areas o

Running dry: Where will the West get its water?

Treesearch

J. Thompson

2007-01-01

Late summer streamflow in western and central Oregon and northern California is almost exclusively due to immense groundwater storage in the Cascade Range. The volume of water stored in permeable lava flows in the Cascades is seven times that stored as snow. Nonetheless, until recently, virtually all examinations of streamflow trends under future climates in the West...

2011 Souris River flood—Will it happen again?

USGS Publications Warehouse

Nustad, Rochelle A.; Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

2016-09-29

The Souris River Basin is a 61,000 square kilometer basin in the provinces of Saskatchewan and Manitoba and the state of North Dakota. Record setting rains in May and June of 2011 led to record flooding with peak annual streamflow values (762 cubic meters per second [m3/s]) more than twice that of any previously recorded peak streamflow and more than five times the estimated 100 year postregulation streamflow (142 m3/s) at the U.S. Geological Survey (USGS) streamflow-gaging station above Minot, North Dakota. Upstream from Minot, N. Dak., the Souris River is regulated by three reservoirs in Saskatchewan (Rafferty, Boundary, and Alameda) and Lake Darling in North Dakota. During the 2011 flood, the city of Minot, N. Dak., experienced devastating damages with more than 4,000 homes flooded and 11,000 evacuated. As a result, the Souris River Basin Task Force recommended the U.S. Geological Survey (in cooperation with the North Dakota State Water Commission) develop a model for estimating the probabilities of future flooding and drought. The model that was developed took on four parts: (1) looking at past climate, (2) predicting future climate, (3) developing a streamflow model in response to certain climatic variables, and (4) combining future climate estimates with the streamflow model to predict future streamflow events. By taking into consideration historical climate record and trends in basin response to various climatic conditions, it was determined flood risk will remain high in the Souris River Basin until the wet climate state ends.

Surface-Water Data, Georgia, Water Year 1999

USGS Publications Warehouse

Alhadeff, S. Jack; Landers, Mark N.; McCallum, Brian E.

1999-01-01

Water resources data for the 1999 water year for Georgia consists of records of stage, discharge, and water quality of streams; and the stage and contents of lakes and reservoirs published in one volume in a digital format on a CD-ROM. This volume contains discharge records of 121 gaging stations; stage for 13 gaging stations; stage and contents for 18 lakes and reservoirs; continuous water quality records for 10 stations; and the annual peak stage and annual peak discharge for 75 crest-stage partial-record stations. These data represent that part of the National Water Data System collected by the U.S. Geological Survey and cooperating State and Federal agencies in Georgia. Records of discharge and stage of streams, and contents or stage of lakes and reservoirs were first published in a series of U.S. Geological water-supply papers entitled, 'Surface-Water Supply of the United States.' Through September 30, 1960, these water-supply papers were in an annual series and then in a 5-year series for 1961-65 and 1966-70. Records of chemical quality, water temperature, and suspended sediment were published from 1941 to 1970 in an annual series of water-supply papers entitled, 'Quality of Surface Waters of the United States.' Records of ground-water levels were published from 1935 to 1974 in a series of water-supply papers entitled, 'Ground-Water Levels in the United States.' Water-supply papers may be consulted in the libraries of the principal cities in the United States or may be purchased from the U.S. Geological Survey, Branch of Information Services, Federal Center, Box 25286, Denver, CO 80225. For water years 1961 through 1970, streamflow data were released by the U.S. Geological Survey in annual reports on a State-boundary basis prior to the two 5-year series water-supply papers, which cover this period. The data contained in the water-supply papers are considered the official record. Water-quality records for water years 1964 through 1970 were similarly released either in separate reports or in conjunction with streamflow records. Beginning with the 1971 water year, water data for streamflow, water quality, and ground water are published in official Survey reports on a State-boundary basis. These official Survey reports carry an identification number consisting of the two-letter State abbreviation, the last two digits of the water year, and the volume number. For example, this volume is identified as 'U.S. Geological Survey Water-Data Report GA-99-1.' These water-data reports are for sale in various formats, by the National Technical Information Service, U.S. Department of Commerce, Springfield, VA 22161.

Presenting the master of all conductivity meters, and how it tastes streamflow

NASA Astrophysics Data System (ADS)

Weijs, S. V.; Parlange, M. B.

2012-04-01

For measuring streamflow in small Alpine streams, the salt dilution method is suitable and often used. By injecting a known mass of salt in the stream and measuring the downstream salt concentration as a function of time, we can obtain the streamflow by integration of the time signal. The underlying assumption is that the salt is well mixed within the stream cross-section. In this method, the salt concentration us usually measured through its relation with conductivity. Several commercial systems exist to do these conductivity measurements and automatically process the results. The problem we encountered when using these systems, however, is that uncertainty is often hidden under the hood. Because the processing happens onboard, researchers may be tempted to put too much trust in the final measurement outcomes. This is somewhat remediated by using a system with two probes which are individually processed to a streamflow outcome. We found that the salt-wave was differently shaped for the faster part of the stream compared to the sides, and therefore gave different readings for the discharge. To come a more probabilistic characterization of streamflow, and to know what is under the hood, we decided to build our own conductivity meter, equipped with eight probes covering the cross section. This enables quantifying some of the uncertainty in the streamflow measurements, which is important for testing hydrological models. This poster shows the first results and the hardware setup. We based our hardware on the open source hardware platform Arduino, and believe that by sharing both the design and the drawbacks, we contribute to the evolution of better measurement equipment or at least better understanding of its shortcomings.

Comparison of Strategies for Climate Change Adaptation of Water Supply and Flood Control Reservoirs

NASA Astrophysics Data System (ADS)

Ng, T. L.; Yang, P.; Bhushan, R.

2016-12-01

With climate change, streamflows are expected to become more fluctuating, with more frequent and intense floods and droughts. This complicates reservoir operation, which is highly sensitive to inflow variability. We make a comparative evaluation of three strategies for adapting reservoirs to climate-induced shifts in streamflow patterns. Specifically, we examine the effectiveness of (i) expanding the capacities of reservoirs by way of new off-stream reservoirs, (ii) introducing wastewater reclamation to augment supplies, and (iii) improving real-time streamflow forecasts for more optimal decision-making. The first two are hard strategies involving major infrastructure modifications, while the third a soft strategy entailing adjusting the system operation. A comprehensive side-by-side comparison of the three strategies is as yet lacking in the literature despite the many past studies investigating the strategies individually. To this end, we developed an adaptive forward-looking linear program that solves to yield the optimal decisions for the current time as a function of an ensemble forecast of future streamflows. Solving the model repeatedly on a rolling basis with regular updating of the streamflow forecast simulates the system behavior over the entire operating horizon. Results are generated for two hypothetical water supply and flood control reservoirs of differing inflows and demands. Preliminary findings suggest that of the three strategies, improving streamflow forecasts to be most effective in mitigating the effects of climate change. We also found that, in average terms, both additional reservoir capacity and wastewater reclamation have potential to reduce water shortage and downstream flooding. However, in the worst case, the potential of the former to reduce water shortage is limited, and similarly so the potential of the latter to reduce downstream flooding.

Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900-2099 *

USGS Publications Warehouse

Dettinger, M.D.; Cayan, D.R.; Meyer, M.K.; Jeton, A.

2004-01-01

Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5??C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.

Using Coupled Groundwater-Surface Water Models to Simulate Eco-Regional Differences in Climate Change Impacts on Hydrological Drought Regimes in British Columbia

NASA Astrophysics Data System (ADS)

Dierauer, J. R.; Allen, D. M.

2016-12-01

Climate change is expected to lead to an increase in extremes, including daily maximum temperatures, heat waves, and meteorological droughts, which will likely result in shifts in the hydrological drought regime (i.e. the frequency, timing, duration, and severity of drought events). While many studies have used hydrologic models to simulate climate change impacts on water resources, only a small portion of these studies have analyzed impacts on low flows and/or hydrological drought. This study is the first to use a fully coupled groundwater-surface water (gw-sw) model to study climate change impacts on hydrological drought. Generic catchment-scale gw-sw models were created for each of the six major eco-regions in British Columbia using the MIKE-SHE/MIKE-11 modelling code. Daily precipitation and temperature time series downscaled using bias-correction spatial disaggregation for the simulated period of 1950-2100 were obtained from the Pacific Climate Institute Consortium (PCIC). Streamflow and groundwater drought events were identified from the simulated time series for each catchment model using the moving window quantile threshold. The frequency, timing, duration, and severity of drought events were compared between the reference period (1961-2000) and two future time periods (2031-2060, 2071-2100). Results show how hydrological drought regimes across the different British Columbia eco-regions will be impacted by climate change.

Determination of streamflow of the Arkansas River near Bentley in south-central Kansas

USGS Publications Warehouse

Perry, Charles A.

2012-01-01

The Kansas Department of Agriculture, Division of Water Resources, requires that the streamflow of the Arkansas River just upstream from Bentley in south-central Kansas be measured or calculated before groundwater can be pumped from the well field. When the daily streamflow of the Arkansas River near Bentley is less than 165 cubic feet per second (ft3/s), pumping must be curtailed. Daily streamflow near Bentley was calculated by determining the relations between streamflow data from two reference streamgages with a concurrent record of 24 years, one located 17.2 miles (mi) upstream and one located 10.9 mi downstream, and streamflow at a temporary gage located just upstream from Bentley (Arkansas River near Bentley, Kansas). Flow-duration curves for the two reference streamgages indicate that during 1988?2011, the mean daily streamflow was less than 165 ft3/s 30 to 35 percent of the time. During extreme low-flow (drought) conditions, the reach of the Arkansas River between Hutchinson and Maize can lose flow to the adjacent alluvial aquifer, with streamflow losses as much as 1.6 cubic feet per second per mile. Three models were developed to calculate the streamflow of the Arkansas River near Bentley, Kansas. The model chosen depends on the data available and on whether the reach of the Arkansas River between Hutchinson and Maize is gaining or losing groundwater from or to the adjacent alluvial aquifer. The first model was a pair of equations developed from linear regressions of the relation between daily streamflow data from the Bentley streamgage and daily streamflow data from either the Arkansas River near Hutchinson, Kansas, station (station number 07143330) or the Arkansas River near Maize, Kansas, station (station number 07143375). The standard error of the Hutchinson-only equation was 22.8 ft3/s, and the standard error of the Maize-only equation was 22.3 ft3/s. The single-station model would be used if only one streamgage was available. In the second model, the flow gradient between the streamflow near Hutchinson and the streamflow near Maize was used to calculate the streamflow at the Bentley streamgage. This equation resulted in a standard error of 26.7 ft3/s. In the third model, a multiple regression analysis between both the daily streamflow of the Arkansas River near Hutchinson, Kansas, and the daily streamflow of the Arkansas River near Maize, Kansas, was used to calculate the streamflow at the Bentley streamgage. The multiple regression equation had a standard error of 21.2 ft3/s, which was the smallest of the standard errors for all the models. An analysis of the number of low-flow days and the number of days when the reach between Hutchinson and Maize loses flow to the adjacent alluvial aquifer indicates that the long-term trend is toward fewer days of losing conditions. This trend may indicate a long-term increase in water levels in the alluvial aquifer, which could be caused by one or more of several conditions, including an increase in rainfall, a decrease in pumping, a decrease in temperature, and an increase in streamflow upstream from the Hutchinson-to-Maize reach of the Arkansas River.

Snow Cover and Precipitation Impacts on Dry Season Streamflow in the Lower Mekong Basin

NASA Technical Reports Server (NTRS)

Cook, Benjamin I.; Bell, A. R.; Anchukaitis, K. J.; Buckley, B. M.

2012-01-01

Climate change impacts on dry season streamflow in the Mekong River are relatively understudied, despite the fact that water availability during this time is critically important for agricultural and ecological systems. Analyses of two gauging stations (Vientiane and Kratie) in the Lower Mekong Basin (LMB) show significant positive correlations between dry season (March through May, MAM) discharge and upper basin snow cover and local precipitation. Using snow cover, precipitation, and upstream discharge as predictors, we develop skillful regression models for MAM streamflow at Vientiane and Kratie, and force these models with output from a suite of general circulation model (GCM) experiments for the twentieth and twenty-first centuries. The GCM simulations predict divergent trends in snow cover (decreasing) and precipitation (increasing) over the twenty-first century, driving overall negligible long-term trends in dry season streamflow. Our study demonstrates how future changes in dry season streamflow in the LMB will depend on changes in snow cover and precipitation, factors that will need to be considered when assessing the full basin response to other climatic and non-climatic drivers.

Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagener, Thorsten; Mann, Michael; Crane, Robert

2014-04-29

This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach tomore » establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.« less

Stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural streamflow

USGS Publications Warehouse

Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

2016-02-24

The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.A water-balance model was developed for simulating monthly natural (unregulated) mean streamflow based on precipitation, temperature, and potential evapotranspiration at select streamflow-gaging stations. The model was calibrated using streamflow data from the U.S. Geological Survey and Environment Canada, along with natural (unregulated) streamflow data from the U.S. Army Corps of Engineers. Correlation coefficients between simulated and natural (unregulated) flows generally were high (greater than 0.8), and the seasonal means and standard deviations of the simulated flows closely matched the means and standard deviations of the natural (unregulated) flows. After calibrating the model for a monthly time step, monthly streamflow for each subbasin was disaggregated into three values per month, or an approximately 10-day time step, and a separate routing model was developed for simulating 10-day streamflow for downstream gages.The stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration was combined with the water-balance model to simulate potential future sequences of 10-day mean streamflow for each of the streamflow-gaging station locations. Flood risk, as determined by equilibrium flow-frequency distributions for the dry (1912–69) and wet (1970–2011) climate states, was considerably higher for the wet state compared to the dry state. Future flood risk will remain high until the wet climate state ends, and for several years after that, because there may be a long lag-time between the return of drier conditions and the onset of a lower soil-moisture storage equilibrium.

National Streamflow Information Program: Implementation Status Report

USGS Publications Warehouse

Norris, J. Michael

2009-01-01

The U.S. Geological Survey (USGS) operates and maintains a nationwide network of about 7,500 streamgages designed to provide and interpret long-term, accurate, and unbiased streamflow information to meet the multiple needs of many diverse national, regional, state, and local users. The National Streamflow Information Program (NSIP) was initiated in 2003 in response to Congressional and stakeholder concerns about (1) the decrease in the number of operating streamgages, including a disproportionate loss of streamgages with a long period of record; (2) the inability of the USGS to continue operating high-priority streamgages in an environment of reduced funding through partnerships; and (3) the increasing demand for streamflow information due to emerging resource-management issues and new data-delivery capabilities. The NSIP's mission is to provide the streamflow information and understanding required to meet national, regional, state, and local needs. Most of the existing streamgages are funded through partnerships with more than 850 other Federal, state, tribal, and local agencies. Currently, about 90 percent of the streamgages send data to the World Wide Web in near-real time (some information is transmitted within 15 minutes, whereas some lags by about 4 hours). The streamflow information collected at USGS streamgages is used for many purposes: *In water-resource appraisals and allocations - to determine how much water is available and how it is being allocated; *To provide streamflow information required by interstate agreements, compacts, and court decrees; *For engineering design of reservoirs, bridges, roads, culverts, and treatment plants; *For the operation of reservoirs, the operation of locks and dams for navigation purposes, and power production; *To identify changes in streamflow resulting from changes in land use, water use, and climate; *For streamflow forecasting, flood planning, and flood forecasting; *To support water-quality programs by allowing determination of constituent loads and fluxes; and *For characterizing and evaluating instream conditions for habitat assessments, instream-flow requirements, and recreation.

Relations of surface-water quality to streamflow in the Atlantic Coastal, lower Delaware River, and Delaware Bay basins, New Jersey, water years 1976-93

USGS Publications Warehouse

Hunchak-Kariouk, Kathryn; Buxton, Debra E.; Hickman, R. Edward

1999-01-01

Relations of water quality to streamflow were determined for 18 water-quality constituents at 28 surface-water-quality stations within the drainage area of the Atlantic Coastal, lower Delaware River, and Delaware Bay Basins for water years 1976-93. Surface-water-quality and streamflow data were evaluated for trends (through time) in constituent concentrations during high and low flows, and relations between constituent concentration and streamflow, and between constituent load and streamflow, were determined. Median concentrations were calculated for the entire period of study (water years 1976-93) and for the last 5 years of the period of study (water years 1989-93) to determine whether any large variation in concentration exists between the two periods. Medians also were used to determine the seasonal Kendall\\'s tau statistic, which was then used to evaluate trends in concentrations during high and low flows. Trends in constituent concentrations during high and low flows were evaluated to determine whether the distribution of the observations changes through time for intermittent (nonpoint storm runoff) and constant (point sources and ground water) sources, respectively. High- and low-flow trends in concentrations were determined for some constituents at 26 of the 28 water-quality stations. Seasonal effects on the relations of concentration to streamflow are evident for 10 constituents at 14 or more stations. Dissolved oxygen shows seasonal dependency at all stations. Negative slopes of relations of concentration to streamflow, which indicate a decrease in concentration at high flows, predominate over positive slopes because of dilution of instream concentrations from storm runoff. The slopes of the regression lines of load to streamflow were determined in order to show the relative contributions to the instream load from constant (point sources and ground water) and intermittent sources (storm runoff). Greater slope values indicate larger contributions from storm runoff to instream load, which most likely indicate an increased relative importance of nonpoint sources. Load-to-streamflow relations along a stream reach that tend to increase in a downstream direction indicate the increased relative importance of contributions from storm runoff. Likewise, load-to-streamflow relations along a stream reach that tend to decrease in a downstream direction indicate the increased relative importance of point sources and ground-water discharge. The magnitudes of the load slopes for five constituents increase in the downstream direction along the Great Egg Harbor River, indicating an increased relative importance of storm runoff for these constituents along the river. The magnitudes of the load slopes for 11 constituents decrease in the downstream direction along the Assunpink Creek and for 5 constituents along the Maurice River, indicating a decreased relative importance of storm runoff for these constituents along the rivers.

Winter cyclone frequency and following freshet streamflow formation on the rivers in Belarus

NASA Astrophysics Data System (ADS)

Partasenok, Irina S.; Groisman, Pavel Ya; Chekan, Grigoriy S.; Melnik, Viktor I.

2014-09-01

We studied long-term fluctuations of streamflow and occurrence of extreme phenomena on the rivers of Belarus during the post-World War II period. It was found that formation of annual runoff within the nation has no constant tendencies and varies from year to year. At the same time, analysis of intra-annual distribution of streamflow reveals significant changes since the 1970s, first of all, increase of winter and decrease of spring streamflow. As a result, the frequency of extreme floods has decreased. These changes in water regime are associated with climatic anomalies (increase of the surface air temperatures) caused by large-scale alterations in atmospheric circulation, specifically in trajectories of cyclones. During the last two decades, the frequency of Atlantic and southern cyclones has changed and caused decreasing of cold season storms and extreme phenomena on the rivers.

Midwestern streamflow, precipitation, and atmospheric vorticity influenced by Pacific sea-surface temperatures and total solar-irradiance variations

USGS Publications Warehouse

Perry, C.A.

2006-01-01

A solar effect on streamflow in the Midwestern United States is described and supported in a six-step physical connection between total solar irradiance (TSI), tropical sea-surface temperatures (SSTs), extratropical SSTs, jet-stream vorticity, surface-layer vorticity, precipitation, and streamflow. Variations in the correlations among the individual steps indicate that the solar/hydroclimatic mechanism is complex and has a time element (lag) that may not be constant. Correct phasing, supported by consistent spectral peaks between 0.092 and 0.096 cycles per year in all data sets within the mechanism is strong evidence for its existence. A significant correlation exists between total solar irradiance and the 3-year moving average of annual streamflow for Iowa (R = 0.67) and for the Mississippi River at St Louis, Missouri (R = 0.60), during the period 1950-2000. Published in 2005 by John Wiley & Sons, Ltd.

In Brief: Online database for instantaneous streamflow data

NASA Astrophysics Data System (ADS)

Showstack, Randy

2007-11-01

Access to U.S. Geological Survey (USGS) historical instantaneous streamflow discharge data, dating from around 1990, is now available online through the Instantaneous Data Archive (IDA), the USGS announced on 14 November. In this new system, users can find streamflow information reported at the time intervals at which it is collected, typically 15-minute to hourly intervals. Although instantaneous data have been available for many years, they were not accessible through the Internet. Robert Hirsch, USGS Associate Director of Water, said, ``A user-friendly archive of historical instantaneous streamflow data is important to many different users for such things as floodplain mapping, flood modeling, and estimating pollutant transport.''The site currently has about 1.5 billion instantaneous data values from 5500 stream gages in 26 states. The number of states and stream gages with data will continue to increase, according to the USGS. For more information, visit the Web site: http://ida.water.usgs.gov/ida/.

Robust, low-cost data loggers for stream temperature, flow intermittency, and relative conductivity monitoring

USGS Publications Warehouse

Chapin, Thomas; Todd, Andrew S.; Zeigler, Matthew P.

2014-01-01

Water temperature and streamflow intermittency are critical parameters influencing aquatic ecosystem health. Low-cost temperature loggers have made continuous water temperature monitoring relatively simple but determining streamflow timing and intermittency using temperature data alone requires significant and subjective data interpretation. Electrical resistance (ER) sensors have recently been developed to overcome the major limitations of temperature-based methods for the assessment of streamflow intermittency. This technical note introduces the STIC (Stream Temperature, Intermittency, and Conductivity logger); a robust, low-cost, simple to build instrument that provides long-duration, high-resolution monitoring of both relative conductivity (RC) and temperature. Simultaneously collected temperature and RC data provide unambiguous water temperature and streamflow intermittency information that is crucial for monitoring aquatic ecosystem health and assessing regulatory compliance. With proper calibration, the STIC relative conductivity data can be used to monitor specific conductivity.

Historical Causes and Future Projections of Hydrological Drought Change over a Semi-arid Watershed in the Yellow River Basin

NASA Astrophysics Data System (ADS)

Jiao, Y.; Yuan, X.; Yang, D.

2017-12-01

During the past five decades, significant decreasing trends in streamflow records were observed at many hydrological gauges within the middle reaches of the Yellow River basin, China, leading to an intensified water resource shortage and a rising hydrological drought risk. This phenomenon is generally considered as a consequence of climate changes and human interventions, such as greenhouse gas emissions, regional land use/cover changes, dam and reservoir constructions and direct water withdrawals. There are many studies on the attribution of streamflow decline and hydrological drought change in this region, while a consolidated conclusion is missing.In this study, we focus on historical and future hydrological drought characteristics over a semi-arid watershed located in the middle reaches of the Yellow River basin. Daily climate simulations from several IPCC CMIP5 models were collected to drive a newly developed eco-hydrological model CLM-GBHM with detailed description of river network and sub-basin topological relationship, to simulate streamflow series under different forcings and scenarios. The standard streamflow index was calculated and used to figure out the characteristics (e.g., frequency, duration and severity) of both historical and future hydrological droughts. The causes and contributions in terms of natural and anthropogenic influences will be investigated based on an optimal fingerprinting method, and the relative importance of internal variability, model and scenario uncertainties for future projections will also be estimated using a separation method. This study will facilitate the implementation of adaptation strategies for hydrological drought over the semi-arid watershed in a changing environment.

Role of surface-water and groundwater interactions on projected summertime streamflow in snow dominated regions : An integrated modeling approach

USGS Publications Warehouse

Huntington, Justin L.; Niswonger, Richard G.

2012-01-01

Previous studies indicate predominantly increasing trends in precipitation across the Western United States, while at the same time, historical streamflow records indicate decreasing summertime streamflow and 25th percentile annual flows. These opposing trends could be viewed as paradoxical, given that several studies suggest that increased annual precipitation will equate to increased annual groundwater recharge, and therefore increased summertime flow. To gain insight on mechanisms behind these potential changes, we rely on a calibrated, integrated surface and groundwater model to simulate climate impacts on surface water/groundwater interactions using 12 general circulation model projections of temperature and precipitation from 2010 to 2100, and evaluate the interplay between snowmelt timing and other hydrologic variables, including streamflow, groundwater recharge, storage, groundwater discharge, and evapotranspiration. Hydrologic simulations show that the timing of peak groundwater discharge to the stream is inversely correlated to snowmelt runoff and groundwater recharge due to the bank storage effect and reversal of hydraulic gradients between the stream and underlying groundwater. That is, groundwater flow to streams peaks following the decrease in stream depth caused by snowmelt recession, and the shift in snowmelt causes a corresponding shift in groundwater discharge to streams. Our results show that groundwater discharge to streams is depleted during the summer due to earlier drainage of shallow aquifers adjacent to streams even if projected annual precipitation and groundwater recharge increases. These projected changes in surface water/groundwater interactions result in more than a 30% decrease in the projected ensemble summertime streamflow. Our findings clarify causality of observed decreasing summertime flow, highlight important aspects of potential climate change impacts on groundwater resources, and underscore the need for integrated hydrologic models in climate change studies.

Simulating long-term landcover change and water yield dynamics in a forested, snow-dominated Rocky Mountain watershed

Treesearch

R. S. Ahl; S. W. Woods

2006-01-01

Changes in the extent, composition, and configuration of forest cover over time due to succession or disturbance processes can result in measurable changes in streamflow and water yield. Removal of forest cover generally increases streamflow due to reduced canopy interception and evapotranspiration. In watersheds where snow is the dominant source of water, yield...

A review of methods for monitoring streamflow for sustainable water resource management

NASA Astrophysics Data System (ADS)

Dobriyal, Pariva; Badola, Ruchi; Tuboi, Chongpi; Hussain, Syed Ainul

2017-10-01

Monitoring of streamflow may help to determine the optimum levels of its use for sustainable water management in the face of climate change. We reviewed available methods for monitoring streamflow on the basis of six criteria viz. their applicability across different terrains and size of the streams, operational ease, time effectiveness, accuracy, environmental impact that they may cause and cost involve in it. On the basis of the strengths and weaknesses of each of the methods reviewed, we conclude that the timed volume method is apt for hilly terrain having smaller streams due to its operational ease and accuracy of results. Although comparatively expensive, the weir and flume methods are suitable for long term studies of small hill streams, since once the structure is put in place, it yields accurate results. In flat terrain, the float method is best suited for smaller streams for its operational ease and cost effectiveness, whereas, for larger streams, the particle image velocimetry may be used for its accuracy. Our review suggests that the selection of a method for monitoring streamflow may be based on volume of the stream, accuracy of the method, accessibility of the terrain and financial and physical resources available.

Spatial and Temporal Dynamics of Carbon Fluxes in Glacial Meltwater Streams, Antarctica

NASA Astrophysics Data System (ADS)

Torrens, C.; Lyons, W. B.; McKnight, D. M.; Welch, K. A.; Gooseff, M. N.

2017-12-01

In the McMurdo Dry Valleys [MDV], Antarctica, glacial meltwater streams are the primary biogeochemical connectors linking glaciers, soils and lakes. These streams control the supply of nutrients and carbon to their terminal lakes, yet little is known about the magnitude, timing or distribution of these fluxes. The McMurdo Long Term Ecological Research project [MCM LTER] has collected over 20 years of sample data on dissolved organic and inorganic carbon in Taylor Valley streamwater; this is the first spatial and temporal analysis of this data. MDV streams are characterized by strong diel pulses in streamflow, specific electrical conductance, and temperature. Unlike temperate stream systems, there is no terrestrial vegetation, lateral overland flow or deep groundwater connection in MDV streams. As a result, the organic carbon is autochthonous, originating from stream microbial mats. Inorganic carbon is primarily bicarbonate; its source is hyporheic zone weathering. The carbonate system is in atmospheric equilibrium, reflecting the wide and shallow stream channels. Preliminary data show that the DOC flux varies with streamflow and is greater on the rising limb of the diel flow pulse. This pattern is more distinct in longer streams. DIC data does not show the same pattern, although the response may be blurred by a lag in hyporheic response to flood pulses and the lack of time-series data for alkalinity. Stream flood pulse dynamics control carbon loading to MDV lakes. As the climate changes, so will the timing and magnitude of diel flood pulses. This is likely to increase carbon loading to the Dry Valley lakes, altering the ecosystem carbon balance. This study increases our understanding of past and current patterns of carbon fluxes from streams to lakes; understanding past patterns will improve predictions of future changes.

Exploring landscapes and ecosystems by studying their streams

NASA Astrophysics Data System (ADS)

Kirchner, J. W.

2016-12-01

Streams integrate fluxes of water, solutes, and sediment from their catchments, and thus they act as mirrors of the surrounding landscape. Patterns of streamflow, chemistry, and sediment flux can therefore shed light on physical, chemical, and biological processes at the scale of whole ecosystems. However, landscapes also exhibit preferential flow and pervasive heterogeneity on all scales, and therefore store waters over a wide spectrum of time scales, complicating efforts to interpret hydrological and geochemical signals in streamwaters. Here I review current and recent research exploring how landscapes store, mix, and release water and solutes to streams. Groundwater levels and stream flows exhibit diurnal cycles in response to snowmelt in springtime and transpiration during the growing season. These cycles vividly illustrate how aquifers and streams mirror ecological processes in their surrounding landscapes. Stream networks extend and retract, both seasonally and in response to individual rainfall events, dynamically mapping out variations in subsurface transmissivity and in the balance between precipitation and transpiration. Water quality time series spanning the periodic table, from H+ to U, exhibit universal fractal scaling on time scales from hours to decades. This scaling behavior is a temporal expression of the spatial heterogeneity that pervades the subsurface, and it confounds efforts to identify water quality trends. Isotope tracers such as 18O, 2H, 3H, and 14C can used to quantify water ages over seven orders of magnitude, from hours to thousands of years. These tracers show that substantial fractions of streamflow are hours, days, and months old, even in streams fed by aquifers with significant proportions of pre-Holocene groundwater. Examples such as these will be presented to illustrate the close coupling between landscapes and the waters that drain them, and to demonstrate how streams can be used as windows into landscape processes.

Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana

USGS Publications Warehouse

McCarthy, Peter M.

2009-01-01

The Yellowstone River is a vital natural resource to the residents of southeastern Montana and is a primary source of water for irrigation and recreation and the primary source of municipal water for several cities. The Yellowstone River valley is the primary east-west transportation corridor through southern Montana. This complex of infrastructure makes the Yellowstone River especially vulnerable to accidental spills from various sources such as tanker cars and trucks. In 2008, the U.S. Geological Survey (USGS), in cooperation with the Montana Department of Environmental Quality, initiated a dye-tracer study to determine instream travel times, streamflow velocities, and dispersion rates for the Yellowstone River from Lockwood to Glendive, Montana. The purpose of this report is to describe the results of this study and summarize data collected at each of the measurement sites between Lockwood and Glendive. This report also compares the results of this study to estimated travel times from a transport model developed by the USGS for a previous study. For this study, Rhodamine WT dye was injected at four locations in late September and early October 2008 during reasonably steady streamflow conditions. Streamflows ranged from 3,490 to 3,770 cubic feet per second upstream from the confluence of the Bighorn River and ranged from 6,520 to 7,570 cubic feet per second downstream from the confluence of the Bighorn River. Mean velocities were calculated for each subreach between measurement sites for the leading edge, peak concentration, centroid, and trailing edge at 10 percent of the peak concentration. Calculated velocities for the centroid of the dye plume for subreaches that were completely laterally mixed ranged from 1.83 to 3.18 ft/s within the study reach from Lockwood Bridge to Glendive Bridge. The mean of the completely mixed centroid velocity for the entire study reach, excluding the subreach between Forsyth Bridge and Cartersville Dam, was 2.80 ft/s. Longitudinal dispersion rates of the dye plume for this study ranged from 0.06 ft/s for the subreach upstream from Forsyth Bridge to 2.25 ft/s for the subreach upstream from Calyspo Bridge for subreaches where the dye was completely laterally mixed. A relation was determined between travel time of the peak concentration and time for the dye plume to pass a site (duration). This relation can be used to estimate when the receding concentration of a potential contaminant reaches 10 percent of its peak concentration for accidental spills into the Yellowstone River. Data from this dye-tracer study were used to evaluate velocity and concentration estimates from a transport model developed as part of an earlier USGS study. Comparison of the estimated and calculated velocities for the study reach indicate that the transport model estimates the velocities of the Yellowstone River between Huntley Bridge and Glendive Bridge with reasonable accuracy. Velocities of the peak concentration of the dye plume calculated for this study averaged 10 percent faster than the most probable velocities and averaged 12 percent slower than the maximum probable velocities estimated from the transport model. Peak Rhodamine WT dye concentrations were consistently lower than the transport model estimates except for the most upstream subreach of each dye injection. The most upstream subreach of each dye injection is expected to have a higher concentration because of incomplete lateral mixing. Lower measured peak concentrations for all other sites were expected because Rhodamine WT dye deteriorates when exposed to sunlight and will sorb onto the streambanks and stream bottom. Velocity-streamflow relations developed by using routine streamflow measurements at USGS gaging stations and the transport model can be used to estimate mean streamflow velocities throughout a range of streamflows. The variation in these velocity-streamflow relations emphasizes the uncertainty in estimating the mean streamflow veloc

Impacts of land use change on watershed streamflow and sediment yield: An assessment using hydrologic modelling and partial least squares regression

NASA Astrophysics Data System (ADS)

Yan, B.; Fang, N. F.; Zhang, P. C.; Shi, Z. H.

2013-03-01

SummaryUnderstanding how changes in individual land use types influence the dynamics of streamflow and sediment yield would greatly improve the predictability of the hydrological consequences of land use changes and could thus help stakeholders to make better decisions. Multivariate statistics are commonly used to compare individual land use types to control the dynamics of streamflow or sediment yields. However, one issue with the use of conventional statistical methods to address relationships between land use types and streamflow or sediment yield is multicollinearity. In this study, an integrated approach involving hydrological modelling and partial least squares regression (PLSR) was used to quantify the contributions of changes in individual land use types to changes in streamflow and sediment yield. In a case study, hydrological modelling was conducted using land use maps from four time periods (1978, 1987, 1999, and 2007) for the Upper Du watershed (8973 km2) in China using the Soil and Water Assessment Tool (SWAT). Changes in streamflow and sediment yield across the two simulations conducted using the land use maps from 2007 to 1978 were found to be related to land use changes according to a PLSR, which was used to quantify the effect of this influence at the sub-basin scale. The major land use changes that affected streamflow in the studied catchment areas were related to changes in the farmland, forest and urban areas between 1978 and 2007; the corresponding regression coefficients were 0.232, -0.147 and 1.256, respectively, and the Variable Influence on Projection (VIP) was greater than 1. The dominant first-order factors affecting the changes in sediment yield in our study were: farmland (the VIP and regression coefficient were 1.762 and 14.343, respectively) and forest (the VIP and regression coefficient were 1.517 and -7.746, respectively). The PLSR methodology presented in this paper is beneficial and novel, as it partially eliminates the co-dependency of the variables and facilitates a more unbiased view of the contribution of the changes in individual land use types to changes in streamflow and sediment yield. This practicable and simple approach could be applied to a variety of other watersheds for which time-sequenced digital land use maps are available.

A spatially distributed isotope sampling network in a snow-dominated catchment for the quantification of snow meltwater

NASA Astrophysics Data System (ADS)

Rücker, Andrea; Boss, Stefan; Von Freyberg, Jana; Zappa, Massimiliano; Kirchner, James

2017-04-01

In mountainous catchments with seasonal snowpacks, river discharge in downstream valleys is largely sustained by snowmelt in spring and summer. Future climate warming will likely reduce snow volumes and lead to earlier and faster snowmelt in such catchments. This, in turn, may increase the risk of summer low flows and hydrological droughts. Improved runoff predictions are thus required in order to adapt water management to future climatic conditions and to assure the availability of fresh water throughout the year. However, a detailed understanding of the hydrological processes is crucial to obtain robust predictions of river streamflow. This in turn requires fingerprinting source areas of streamflow, tracing water flow pathways, and measuring timescales of catchment storage, using tracers such as stable water isotopes (18O, 2H). For this reason, we have established an isotope sampling network in the Alptal, a snowmelt-dominated catchment (46.4 km2) in Central-Switzerland, as part of the SREP-Drought project (Snow Resources and the Early Prediction of hydrological DROUGHT in mountainous streams). Precipitation and snow cores are analyzed for their isotopic signature at daily or weekly intervals. Three-week bulk samples of precipitation are also collected on a transect along the Alptal valley bottom, and along an elevational transect perpendicular to the Alptal valley axis. Streamwater samples are taken at the catchment outlet as well as in two small nested sub-catchments (< 2 km2). In order to catch the isotopic signature of naturally-occurring snowmelt, a fully automatic snow lysimeter system was developed, which also facilitates real-time monitoring of snowmelt events, system status and environmental conditions (air and soil temperature). Three lysimeter systems were installed within the catchment, in one forested site and two open field sites at different elevations, and have been operational since November 2016. We will present the isotope time series from our regular sampling network, as well as initial results from our snowmelt lysimeter sites. Our data set will allow for detailed hydrograph separation based on stable water isotopes and geochemical components, which we use to identify source areas and to quantify snowmelt contributions to streamflow.

Evaluating CONUS-Scale Runoff Simulation across the National Water Model WRF-Hydro Implementation to Disentangle Regional Controls on Streamflow Generation and Model Error Contribution

NASA Astrophysics Data System (ADS)

Dugger, A. L.; Rafieeinasab, A.; Gochis, D.; Yu, W.; McCreight, J. L.; Karsten, L. R.; Pan, L.; Zhang, Y.; Sampson, K. M.; Cosgrove, B.

2016-12-01

Evaluation of physically-based hydrologic models applied across large regions can provide insight into dominant controls on runoff generation and how these controls vary based on climatic, biological, and geophysical setting. To make this leap, however, we need to combine knowledge of regional forcing skill, model parameter and physics assumptions, and hydrologic theory. If we can successfully do this, we also gain information on how well our current approximations of these dominant physical processes are represented in continental-scale models. In this study, we apply this diagnostic approach to a 5-year retrospective implementation of the WRF-Hydro community model configured for the U.S. National Weather Service's National Water Model (NWM). The NWM is a water prediction model in operations over the contiguous U.S. as of summer 2016, providing real-time estimates and forecasts out to 30 days of streamflow across 2.7 million stream reaches as well as distributed snowpack, soil moisture, and evapotranspiration at 1-km resolution. The WRF-Hydro system permits not only the standard simulation of vertical energy and water fluxes common in continental-scale models, but augments these processes with lateral redistribution of surface and subsurface water, simple groundwater dynamics, and channel routing. We evaluate 5 years of NLDAS-2 precipitation forcing and WRF-Hydro streamflow and evapotranspiration simulation across the contiguous U.S. at a range of spatial (gage, basin, ecoregion) and temporal (hourly, daily, monthly) scales and look for consistencies and inconsistencies in performance in terms of bias, timing, and extremes. Leveraging results from other CONUS-scale hydrologic evaluation studies, we translate our performance metrics into a matrix of likely dominant process controls and error sources (forcings, parameter estimates, and model physics). We test our hypotheses in a series of controlled model experiments on a subset of representative basins from distinct "problem" environments (Southeast U.S. Coastal Plain, Central and Coastal Texas, Northern Plains, and Arid Southwest). The results from these longer-term model diagnostics will inform future improvements in forcing bias correction, parameter calibration, and physics developments in the National Water Model.

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to constrain model uncertainty for an - assumed to be - ungauged basin. This shows that our method is promising for reconstructing long-term flow data for ungauged catchments on the Pacific side of Central America, and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

A historical perspective on precipitation, drought severity, and streamflow in Texas during 1951-56 and 2011

USGS Publications Warehouse

Winters, Karl E.

2013-01-01

Annual mean streamflow and streamflow-duration curves for the 1951–56 and 2011 water years were assessed for 19 unregulated U.S. Geological Survey (USGS) streamflow-gaging stations. At eight of these streamflow-gaging stations, the annual mean streamflow was lower in 2011 than for any year during 1951–56; many of these stations are located in eastern Texas. Annual mean streamflows for streamflow-gaging stations in the Guadalupe, Blanco, and upper Frio River Basins were lower in 1956 than in 2011. The streamflow-duration curves for many streamflow-gaging stations indicate a lack of (or diminished) storm runoff during 2011. Low streamflows (those exceeded 90 to 95 percent of days) were lower for 1956 than for 2011 at seven streamflow-gaging stations. For most of these stations, the lowest of the low streamflows during 1951–56 occurred in 1956. During March to September 2011, record daily lows were measured at USGS streamflow-gaging station 08041500 Village Creek near Kountze, Tex., which has more than 70 years of record. Many other USGS streamflow-gaging stations in Texas started the 2011 water year with normal streamflow but by the end of the water year were flowing at near-record lows.

Land Use Change Increases Streamflow Across the Arc of Deforestation in Brazil

NASA Astrophysics Data System (ADS)

Levy, M. C.; Lopes, A. V.; Cohn, A.; Larsen, L. G.; Thompson, S. E.

2018-04-01

Nearly half of recent decades' global forest loss occurred in the Amazon and Cerrado (tropical savanna) biomes of Brazil, known as the arc of deforestation. Despite prior analysis in individual river basins, a generalizable empirical understanding of the effect of deforestation on streamflow across this region is lacking. We frame land use change in Brazil as a natural experiment and draw on in situ and remote sensing evidence in 324 river basins covering more than 3 × 106 km2 to estimate streamflow changes caused by deforestation and agricultural development between 1950 and 2013. Deforestation increased dry season low flow by between 4 and 10 percentage points (relative to the forested condition), corresponding to a regional- and time-averaged rate of increase in specific streamflow of 1.29 mm/year2, equivalent to a 4.08 km3/year2 increase, assuming a stationary climate. In conjunction with rainfall and temperature variations, the net (observed) average increase in streamflow over the same period was 0.76 mm/year2, or 2.41 km3/year2. Thus, net increases in regional streamflow in the past half century are 58% of those that would have been experienced with deforestation given a stationary climate. This study uses a causal empirical analysis approach novel to the water sciences to verify the regional applicability of prior basin-scale studies, provides a proof of concept for the use of observational causal identification methods in the water sciences, and demonstrates that deforestation masks the streamflow-reducing effects of climate change in this region.

Effects of climate change on streamflow extremes and implications for reservoir inflow in the United States

NASA Astrophysics Data System (ADS)

Naz, Bibi S.; Kao, Shih-Chieh; Ashfaq, Moetasim; Gao, Huilin; Rastogi, Deeksha; Gangrade, Sudershan

2018-01-01

The magnitude and frequency of hydrometeorological extremes are expected to increase in the conterminous United States (CONUS) over the rest of this century, and their increase will significantly impact water resource management. In this study, we evaluated the large-scale climate change effects on extreme hydrological events and their implications for reservoir inflows in 138 headwater subbasins located upstream of reservoirs across CONUS using the Variable Infiltration Capacity (VIC) hydrologic model. The VIC model was forced with a 10-member ensemble of global circulation models under the Representative Concentration Pathway 8.5 that were dynamically downscaled using a regional climate model (RegCM4) and bias-corrected to 1/24° grid cell resolution. Four commonly used indices, including mean annual flow, annual center timing, 100-year daily high streamflow, and 10-year 7-day average low streamflow were used for evaluation. The results projected an increase in the high streamflow by 44% for a majority of subbasins upstream of flood control reservoirs in the central United States (US) and a decrease in the low streamflow by 11% for subbasins upstream of hydropower reservoirs across the western US. In the eastern US, frequencies of both high and low streamflow were projected to increase in the majority of subbasins upstream of both hydropower and flood control reservoirs. Increased frequencies of both high and low streamflow events can potentially make reservoirs across CONUS more vulnerable to future climate conditions. This study estimates reservoir inflow changes over the next several decades, which can be used to optimize water supply management downstream.

Streamflow record extension for selected streams in the Susitna River Basin, Alaska

USGS Publications Warehouse

Curran, Janet H.

2012-01-01

Daily streamflow records for water years 1950–2010 in the Susitna River Basin range in length from 4 to 57 years, and many are distributed within that period in a way that might not adequately represent long-term streamflow conditions. Streamflow in the basin is affected by the Pacific Decadal Oscillation (PDO), a multi-decadal climate pattern that shifted from a cool phase to a warm phase in 1976. Records for many streamgages in the basin fell mostly within one phase of the PDO, such that monthly and annual statistics from observed records might not reflect streamflow conditions over a longer period. Correlations between daily discharge values sufficed for extending streamflow records at 11 of the 14 streamgages in the basin on the basis of relatively long-term records for one or more of the streamgages within the basin, or one outside the basin, that were defined as index stations. Streamflow at the index stations was hydrologically responsive to glacier melt and snowmelt, and correlated well with flow from similar high-elevation, glaciated basins, but flow in low-elevation basins without glaciers could not be correlated to flow at any of the index stations. Kendall-Theil Robust Line multi-segment regression equations developed for one or more index stations were used to extend daily discharge values to the full 61-year period for all 11 streamgages. Monthly and annual statistics prepared for the extended records show shifts in timing of breakup and freeze-up and magnitude of snowmelt peaks largely predicted by the PDO phase.

South Fork Shenandoah River habitat-flow modeling to determine ecological and recreational characteristics during low-flow periods

USGS Publications Warehouse

Krstolic, Jennifer L.; Ramey, R. Clay

2012-01-01

The ecological habitat requirements of aquatic organisms and recreational streamflow requirements of the South Fork Shenandoah River were investigated by the U.S. Geological Survey in cooperation with the Central Shenandoah Valley Planning District Commission, the Northern Shenandoah Valley Regional Commission, and Virginia Commonwealth University. Physical habitat simulation modeling was conducted to examine flow as a major determinant of physical habitat availability and recreation suitability using field-collected hydraulic habitat variables such as water depth, water velocity, and substrate characteristics. Fish habitat-suitability criteria specific to the South Fork Shenandoah River were developed for sub-adult and adult smallmouth bass (Micropterus dolomieu), juvenile and sub-adult redbreast sunfish (Lepomis auritus), spotfin or satinfin shiner (Cyprinella spp), margined madtom (Noturus insignis),and river chub (Nocomis micropogon). Historic streamflow statistics for the summer low-flow period during July, August, and September were used as benchmark low-flow conditions and compared to habitat simulation results and water-withdrawal scenarios based on 2005 withdrawal data. To examine habitat and recreation characteristics during droughts, daily fish habitat or recreation suitability values were simulated for 2002 and other selected drought years. Recreation suitability during droughts was extremely low, because the modeling demonstrated that suitable conditions occur when the streamflows are greater than the 50th percentile flow for July, August, and September. Habitat availability for fish is generally at a maximum when streamflows are between the 75th and 25th percentile flows for July, August, and September. Time-series results for drought years, such as 2002, showed that extreme low-flow conditions less than the 5th percentile of flow for July, August, and September corresponded to below-normal habitat availability for both game and nongame fish in the upper section of the river. For the middle section near Luray, margined madtom and river chub habitat area were below normal, whereas adult and sub-adult smallmouth bass habitat area remained near the median expected available habitat. In the lower section near Front Royal, time-series results for adult smallmouth bass, sub-adult smallmouth bass, and margined madtom habitat were below normal when streamflows were below the 10th percentile flow for July, August, and September. All other species of fish had habitat availability within the normal range for July, August, and September. Water-conservation scenarios representing a 50 percent water-withdrawal reduction resulted in game fish habitat availability within the normal range for habitat in upper and middle river sections, instead of below normal conditions which were observed during the 2002 drought. The 50 percent water-withdrawal reduction had no measurable effect on recreation. For nongame fish such as river chub, a 20 percent withdrawal reduction resulted in habitat availability within the normal range for habitat in the upper and middle river sections. Increased water-use scenarios representing a 5 percent increase in water withdrawals resulted in a slight reduction in habitat availability; however, increased withdrawals of 20 and 50 percent resulted in habitat availability substantially less than the 25th habitat percentile, or below normal. Habitat reductions were more pronounced when flows were lower than the 10th percentile flow for July, August, and September. The results show that for normal or wet years, increased water withdrawals are not likely to correspond with extensive habitat loss for game fish or nongame fish. During drought years, however, a 20 to 50 percent increase in water withdrawals may result in below normal habitat availability for game fish throughout the river and nongame fish in the upper and middle sections of the river. These simulations of rare historic drought conditions, such as those observed in 2002, serve as a baseline for development of ecological flow thresholds for drought planning.

Water-resources investigations in Tennessee; programs and activities of the U.S. Geological Survey, 1988-1989

USGS Publications Warehouse

Quinones, Ferdinand; Balthrop, B.H.; Baker, E.G.

1989-01-01

This report contains a summation of water resources projects which were active in the Tennessee District during 1988 or 1989. Given in each summary is the name of the project chief, the objective of the project, the progress of results of the study to date, and the name of the cooperator. The basic data programs conducted by the Tennessee District provide streamflow, quality of water, and groundwater levels information essential to the assessment and management of the State 's water resources. Long-term streamflow, quality of water, and groundwater levels networks are operated as part of the Hydrologic Data Section. Field operations are about equally divided among field offices in Memphis, Nashville, and Knoxville. The data collected as part of the networks are published in the series of annual data reports entitled ' Water Resources Data for Tennessee'. (USGS)

Applications of multiple change point detections to monthly streamflow and rainfall in Xijiang River in southern China, part II: trend and mean

NASA Astrophysics Data System (ADS)

Chen, Yongqin David; Jiang, Jianmin; Zhu, Yuxiang; Huang, Changxing; Zhang, Qiang

2018-05-01

This article, as part II, illustrates applications of other two algorithms, i.e., the scanning F test of change points in trend and the scanning t test of change points in mean, to both series of the normalized streamflow index (NSI) at Makou section in the Xijiang River and the normalized precipitation index (NPI) over the watershed of Xijiang River. The results from these two tests show mainly positive coherency of changes between the NSI and NPI. However, some minor negative coherency patches may expose somewhat impacts of human activities, but they were often associated with nearly normal climate periods. These suggest that the runoff still depends upon well the precipitation in the Xijiang catchment. The anthropogenic disturbances have not yet reached up to violating natural relationship on the whole in this river.

Streamflow characteristics based on data through water year 2009 for selected streamflow-gaging stations in or near Montana: Chapter E in Montana StreamStats

USGS Publications Warehouse

McCarthy, Peter M.

2016-04-05

Chapter E of this Scientific Investigations Report documents results from a study by the U.S. Geological Survey, in cooperation with the Montana Department of Environmental Quality and the Montana Department of Natural Resources and Conservation, to provide an update of statewide streamflow characteristics based on data through water year 2009 for streamflow-gaging stations in or near Montana. Streamflow characteristics are presented for 408 streamflow-gaging stations in Montana and adjacent areas having 10 or more years of record. Data include the magnitude and probability of annual low and high streamflow, the magnitude and probability of low streamflow for three seasons (March–June, July–October, and November–February), streamflow duration statistics for monthly and annual periods, and mean streamflows for monthly and annual periods. Streamflow is considered to be regulated at streamflow-gaging stations where dams or other large-scale human modifications affect 20 percent or more of the contributing drainage basin. Separate streamflow characteristics are presented for the unregulated and regulated periods of record for streamflow-gaging stations with sufficient data.

Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

2015-09-01

Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

Modeling the effect of glacier recession on streamflow response using a coupled glacio-hydrological model

DOE PAGES

Frans, Chris D.; Clarke, Garry K. C.; Burns, P.; ...

2014-02-27

Here, we describe an integrated spatially distributed hydrologic and glacier dynamic model, and use it to investigate the effect of glacier recession on streamflow variations for the Upper Bow River basin, a tributary of the South Saskatchewan River. Several recent studies have suggested that observed decreases in summer flows in the South Saskatchewan River are partly due to the retreat of glaciers in the river's headwaters. Modeling the effect of glacier changes on streamflow response in river basins such as the South Saskatchewan is complicated due to the inability of most existing physically-based distributed hydrologic models to represent glacier dynamics.more » We compare predicted variations in glacier extent, snow water equivalent and streamflow discharge made with the integrated model with satellite estimates of glacier area and terminus position, observed streamflow and snow water equivalent measurements over the period of 1980 2007. Simulations with the coupled hydrology-glacier model reduce the uncertainty in streamflow predictions. Our results suggested that on average, the glacier melt contribution to the Bow River flow upstream of Lake Louise is about 30% in summer. For warm and dry years, however, the glacier melt contribution can be as large as 50% in August, whereas for cold years, it can be as small as 20% and the timing of glacier melt signature can be delayed by a month.« less

Connecting Snowmelt Runoff Timing Changes to Watershed Characteristics in California

NASA Astrophysics Data System (ADS)

Stewart, I. T.; Peterson, D. H.

2008-12-01

Shifts in the timing of snowmelt runoff are an expected consequence of climatic changes and have been observed throughout western North America for the past several decades. While the snowmelt runoff has in general come earlier, the magnitude, and sometimes direction, of streamflow timing trends has varied throughout the region in a manner that is not explained by the differences in location or gauge elevation alone. The gauge-to-gauge differences in the observed streamflow timing trends, which have not been systematically explored, are investigated in this study by linking the hydrologic response of a stream to the physical characteristics of the watershed above the gauge. To this end, the very recent trends in streamflow timing measures (such as the timing of the start of the spring snowmelt pulse, the timing of the center of mass for flow, the annual flow, and the timing of the day when maximum flow occurs) for approximately 60 snowmelt-dominated gauges in California were analyzed in conjunction with a GIS-based data base of the watershed characteristics (such as elevation distribution, slope, aspect, and vegetation) through the 2008 runoff season. The improved knowledge of how a watershed has reacted to recent climatic changes can aid in the development of future adaptive strategies in managing water resources in California.

Ongoing drought-induced uplift in the western United States.

USGS Publications Warehouse

Borsa, Adrian Antal; Agnew, Duncan Carr; Cayan, Daniel R.

2014-01-01

The western United States has been experiencing severe drought since 2013. The solid earth response to the accompanying loss of surface and near-surface water mass should be a broad region of uplift. We use seasonally adjusted time series from continuously operating global positioning system stations to measure this uplift, which we invert to estimate mass loss. The median uplift is 5 millimeters (mm), with values up to 15 mm in California’s mountains. The associated pattern of mass loss, ranging up to 50 centimeters (cm) of water equivalent, is consistent with observed decreases in precipitation and streamflow. We estimate the total deficit to be ~240 gigatons, equivalent to a 10-cm layer of water over the entire region, or the annual mass loss from the Greenland Ice Sheet.

The European 2015 drought from a hydrological perspective

NASA Astrophysics Data System (ADS)

Laaha, Gregor; Gauster, Tobias; Tallaksen, Lena M.; Vidal, Jean-Philippe; Stahl, Kerstin; Prudhomme, Christel; Heudorfer, Benedikt; Vlnas, Radek; Ionita, Monica; Van Lanen, Henny A. J.; Adler, Mary-Jeanne; Caillouet, Laurie; Delus, Claire; Fendekova, Miriam; Gailliez, Sebastien; Hannaford, Jamie; Kingston, Daniel; Van Loon, Anne F.; Mediero, Luis; Osuch, Marzena; Romanowicz, Renata; Sauquet, Eric; Stagge, James H.; Wong, Wai K.

2017-06-01

In 2015 large parts of Europe were affected by drought. In this paper, we analyze the hydrological footprint (dynamic development over space and time) of the drought of 2015 in terms of both severity (magnitude) and spatial extent and compare it to the extreme drought of 2003. Analyses are based on a range of low flow and hydrological drought indices derived for about 800 streamflow records across Europe, collected in a community effort based on a common protocol. We compare the hydrological footprints of both events with the meteorological footprints, in order to learn from similarities and differences of both perspectives and to draw conclusions for drought management. The region affected by hydrological drought in 2015 differed somewhat from the drought of 2003, with its center located more towards eastern Europe. In terms of low flow magnitude, a region surrounding the Czech Republic was the most affected, with summer low flows that exhibited return intervals of 100 years and more. In terms of deficit volumes, the geographical center of the event was in southern Germany, where the drought lasted a particularly long time. A detailed spatial and temporal assessment of the 2015 event showed that the particular behavior in these regions was partly a result of diverging wetness preconditions in the studied catchments. Extreme droughts emerged where preconditions were particularly dry. In regions with wet preconditions, low flow events developed later and tended to be less severe. For both the 2003 and 2015 events, the onset of the hydrological drought was well correlated with the lowest flow recorded during the event (low flow magnitude), pointing towards a potential for early warning of the severity of streamflow drought. Time series of monthly drought indices (both streamflow- and climate-based indices) showed that meteorological and hydrological events developed differently in space and time, both in terms of extent and severity (magnitude). These results emphasize that drought is a hazard which leaves different footprints on the various components of the water cycle at different spatial and temporal scales. The difference in the dynamic development of meteorological and hydrological drought also implies that impacts on various water-use sectors and river ecology cannot be informed by climate indices alone. Thus, an assessment of drought impacts on water resources requires hydrological data in addition to drought indices based solely on climate data. The transboundary scale of the event also suggests that additional efforts need to be undertaken to make timely pan-European hydrological assessments more operational in the future.