Modelling of dissolved oxygen content using artificial neural networks: Danube River, North Serbia, case study.

PubMed

Antanasijević, Davor; Pocajt, Viktor; Povrenović, Dragan; Perić-Grujić, Aleksandra; Ristić, Mirjana

2013-12-01

The aims of this study are to create an artificial neural network (ANN) model using non-specific water quality parameters and to examine the accuracy of three different ANN architectures: General Regression Neural Network (GRNN), Backpropagation Neural Network (BPNN) and Recurrent Neural Network (RNN), for prediction of dissolved oxygen (DO) concentration in the Danube River. The neural network model has been developed using measured data collected from the Bezdan monitoring station on the Danube River. The input variables used for the ANN model are water flow, temperature, pH and electrical conductivity. The model was trained and validated using available data from 2004 to 2008 and tested using the data from 2009. The order of performance for the created architectures based on their comparison with the test data is RNN > GRNN > BPNN. The ANN results are compared with multiple linear regression (MLR) model using multiple statistical indicators. The comparison of the RNN model with the MLR model indicates that the RNN model performs much better, since all predictions of the RNN model for the test data were within the error of less than ± 10 %. In case of the MLR, only 55 % of predictions were within the error of less than ± 10 %. The developed RNN model can be used as a tool for the prediction of DO in river waters.

River flow modeling using artificial neural networks in Kapuas river, West Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Herawati, Henny; Suripin, Suharyanto

2017-11-01

Kapuas River is located in the province of West Kalimantan. Kapuas river length is 1,086 km and river basin areas about 100,000 Km2. The availability of river flow data in the Long River and very wide catchments are difficult to obtain, while river flow data are essential for planning waterworks. To predict the water flow in the catchment area requires a lot of hydrology coefficient, so it is very difficult to predict and obtain results that closer to the real conditions. This paper demonstrates that artificial neural network (ANN) could be used to predict the water flow. The ANN technique can be used to predict the incidence of water discharge that occurs in the Kapuas River based on rainfall and evaporation data. With the data available to do training on the artificial neural network model is obtained mean square error (MSE) 0.00007. The river flow predictions could be carried out after the training. The results showed differences in water discharge measurement and prediction of about 4%.

Fluid temperatures: Modeling the thermal regime of a river network

Treesearch

Rhonda Mazza; Ashley Steel

2017-01-01

Water temperature drives the complex food web of a river network. Aquatic organisms hatch, feed, and reproduce in thermal niches within the tributaries and mainstem that comprise the river network. Changes in water temperature can synchronize or asynchronize the timing of their life stages throughout the year. The water temperature fluctuates over time and place,...

Quantifying climatic controls on river network topology across scales

NASA Astrophysics Data System (ADS)

Ranjbar Moshfeghi, S.; Hooshyar, M.; Wang, D.; Singh, A.

2017-12-01

Branching structure of river networks is an important topologic and geomorphologic feature that depends on several factors (e.g. climate, tectonic). However, mechanisms that cause these drainage patterns in river networks are poorly understood. In this study, we investigate the effects of varying climatic forcing on river network topology and geomorphology. For this, we select 20 catchments across the United States with different long-term climatic conditions quantified by climate aridity index (AI), defined here as the ratio of mean annual potential evaporation (Ep) to precipitation (P), capturing variation in runoff and vegetation cover. The river networks of these catchments are extracted, using a curvature-based method, from high-resolution (1 m) digital elevation models and several metrics such as drainage density, branching angle, and width functions are computed. We also use a multiscale-entropy-based approach to quantify the topologic irregularity and structural richness of these river networks. Our results reveal systematic impacts of climate forcing on the structure of river networks.

A hydrogeomorphic river network model predicts where and why hyporheic exchange is important in large basins

USGS Publications Warehouse

Gomez-Velez, Jesus D.; Harvey, Judson

2014-01-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.

A hydrogeomorphic river network model predicts where and why hyporheic exchange is important in large basins

NASA Astrophysics Data System (ADS)

Gomez-Velez, Jesus D.; Harvey, Judson W.

2014-09-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data and by models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bed forms rather than lateral exchange through meanders dominates hyporheic fluxes and turnover rates along river corridors. Per kilometer, low-order streams have a biogeochemical potential at least 2 orders of magnitude larger than higher-order streams. However, when biogeochemical potential is examined per average length of each stream order, low- and high-order streams were often found to be comparable. As a result, the hyporheic zone's intrinsic potential for biogeochemical transformations is comparable across different stream orders, but the greater river miles and larger total streambed area of lower order streams result in the highest cumulative impact from low-order streams. Lateral exchange through meander banks may be important in some cases but generally only in large rivers.

Modeling nutrient retention at the watershed scale: Does small stream research apply to the whole river network?

NASA Astrophysics Data System (ADS)

Aguilera, Rosana; Marcé, Rafael; Sabater, Sergi

2013-06-01

are conveyed from terrestrial and upstream sources through drainage networks. Streams and rivers contribute to regulate the material exported downstream by means of transformation, storage, and removal of nutrients. It has been recently suggested that the efficiency of process rates relative to available nutrient concentration in streams eventually declines, following an efficiency loss (EL) dynamics. However, most of these predictions are based at the reach scale in pristine streams, failing to describe the role of entire river networks. Models provide the means to study nutrient cycling from the stream network perspective via upscaling to the watershed the key mechanisms occurring at the reach scale. We applied a hybrid process-based and statistical model (SPARROW, Spatially Referenced Regression on Watershed Attributes) as a heuristic approach to describe in-stream nutrient processes in a highly impaired, high stream order watershed (the Llobregat River Basin, NE Spain). The in-stream decay specifications of the model were modified to include a partial saturation effect in uptake efficiency (expressed as a power law) and better capture biological nutrient retention in river systems under high anthropogenic stress. The stream decay coefficients were statistically significant in both nitrate and phosphate models, indicating the potential role of in-stream processing in limiting nutrient export. However, the EL concept did not reliably describe the patterns of nutrient uptake efficiency for the concentration gradient and streamflow values found in the Llobregat River basin, posing in doubt its complete applicability to explain nutrient retention processes in stream networks comprising highly impaired rivers.

Accounting for heterogeneity of nutrient dynamics in riverscapes through spatially distributed models

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Stewart, R. J.

2011-12-01

Numerous types of heterogeneity exist within river systems, leading to hotspots of nutrient sources, sinks, and impacts embedded within an underlying gradient defined by river size. This heterogeneity influences the downstream propagation of anthropogenic impacts across flow conditions. We applied a river network model to explore how nitrogen saturation at river network scales is influenced by the abundance and distribution of potential nutrient processing hotspots (lakes, beaver ponds, tributary junctions, hyporheic zones) under different flow conditions. We determined that under low flow conditions, whole network nutrient removal is relatively insensitive to the number of hotspots because the underlying river network structure has sufficient nutrient processing capacity. However, hotspots become more important at higher flows and greatly influence the spatial distribution of removal within the network at all flows, suggesting that identification of heterogeneity is critical to develop predictive understanding of nutrient removal processes under changing loading and climate conditions. New temporally intensive data from in situ sensors can potentially help to better understand and constrain these dynamics.

Dissolved Nutrient Removal in River Networks: When and Where

NASA Astrophysics Data System (ADS)

Ye, S.; Ran, Q.

2017-12-01

Along the river network, water, sediment, and nutrients are transported, cycled, and altered by coupled hydrological and biogeochemical processes. Due to increasing human activities such as urbanization, and fertilizer application associated with agricultural land use, nitrogen and phosphorus inputs to aquatic ecosystems have increased dramatically since the beginning of the 20th century. Meanwhile, our current understanding of the rates and processes controlling the cycling and removal of dissolved inorganic nutrients in river networks is still limited due to a lack of empirical measurements, especially in large rivers. Here, based on the simulation of a coupled hydrological and biogeochemical process model, we track the nutrient uptake at the network scale. The model was parameterized with literature values from headwater streams and empirical measurements made in 15 rivers with varying hydrological, biological, and topographic characteristics. We applied the coupled model to an agricultural catchment in the Midwest to estimate the residence time, reaction time and travel distance of the nutrient exported from different places across watershed. In this work, we explore how to use these temporal and spatial characteristics to quantify the nutrient removal across the river network. We then further investigate the impact of heterogeneous lateral input on network scale nutrient removal. Whether or not this would influence the overall nutrient removal in the watershed, if so, to what extent would this have significant impact?

Graph Theory-Based Technique for Isolating Corrupted Boundary Conditions in Continental-Scale River Network Hydrodynamic Simulation

NASA Astrophysics Data System (ADS)

Yu, C. W.; Hodges, B. R.; Liu, F.

2017-12-01

Development of continental-scale river network models creates challenges where the massive amount of boundary condition data encounters the sensitivity of a dynamic nu- merical model. The topographic data sets used to define the river channel characteristics may include either corrupt data or complex configurations that cause instabilities in a numerical solution of the Saint-Venant equations. For local-scale river models (e.g. HEC- RAS), modelers typically rely on past experience to make ad hoc boundary condition adjustments that ensure a stable solution - the proof of the adjustment is merely the sta- bility of the solution. To date, there do not exist any formal methodologies or automated procedures for a priori detecting/fixing boundary conditions that cause instabilities in a dynamic model. Formal methodologies for data screening and adjustment are a critical need for simulations with a large number of river reaches that draw their boundary con- dition data from a wide variety of sources. At the continental scale, we simply cannot assume that we will have access to river-channel cross-section data that has been ade- quately analyzed and processed. Herein, we argue that problematic boundary condition data for unsteady dynamic modeling can be identified through numerical modeling with the steady-state Saint-Venant equations. The fragility of numerical stability increases with the complexity of branching in river network system and instabilities (even in an unsteady solution) are typically triggered by the nonlinear advection term in Saint-Venant equations. It follows that the behavior of the simpler steady-state equations (which retain the nonlin- ear term) can be used to screen the boundary condition data for problematic regions. In this research, we propose a graph-theory based method to isolate the location of corrupted boundary condition data in a continental-scale river network and demonstrate its utility with a network of O(10^4) elements. Acknowledgement: This research is supported by the National Science Foundation un- der grant number CCF-1331610.

An advanced modelling tool for simulating complex river systems.

PubMed

Trancoso, Ana Rosa; Braunschweig, Frank; Chambel Leitão, Pedro; Obermann, Matthias; Neves, Ramiro

2009-04-01

The present paper describes MOHID River Network (MRN), a 1D hydrodynamic model for river networks as part of MOHID Water Modelling System, which is a modular system for the simulation of water bodies (hydrodynamics and water constituents). MRN is capable of simulating water quality in the aquatic and benthic phase and its development was especially focused on the reproduction of processes occurring in temporary river networks (flush events, pools formation, and transmission losses). Further, unlike many other models, it allows the quantification of settled materials at the channel bed also over periods when the river falls dry. These features are very important to secure mass conservation in highly varying flows of temporary rivers. The water quality models existing in MOHID are base on well-known ecological models, such as WASP and ERSEM, the latter allowing explicit parameterization of C, N, P, Si, and O cycles. MRN can be coupled to the basin model, MOHID Land, with computes runoff and porous media transport, allowing for the dynamic exchange of water and materials between the river and surroundings, or it can be used as a standalone model, receiving discharges at any specified nodes (ASCII files of time series with arbitrary time step). These features account for spatial gradients in precipitation which can be significant in Mediterranean-like basins. An interface has been already developed for SWAT basin model.

Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin; Razavi, Tara; Tapsoba, Dominique; Gobena, Adam; Weber, Frank; Pietroniro, Alain

2018-06-01

Snow has a unique characteristic in the water cycle, that is, snow falls during the entire winter season, but the discharge from snowmelt is typically delayed until the melting period and occurs in a relatively short period. Therefore, reliable observations from an optimal snow monitoring network are necessary for an efficient management of snowmelt water for flood prevention and hydropower generation. The Dual Entropy and Multiobjective Optimization is applied to design snow monitoring networks in La Grande River Basin in Québec and Columbia River Basin in British Columbia. While the networks are optimized to have the maximum amount of information with minimum redundancy based on entropy concepts, this study extends the traditional entropy applications to the hydrometric network design by introducing several improvements. First, several data quantization cases and their effects on the snow network design problems were explored. Second, the applicability the Snow Data Assimilation System (SNODAS) products as synthetic datasets of potential stations was demonstrated in the design of the snow monitoring network of the Columbia River Basin. Third, beyond finding the Pareto-optimal networks from the entropy with multi-objective optimization, the networks obtained for La Grande River Basin were further evaluated by applying three hydrologic models. The calibrated hydrologic models simulated discharges using the updated snow water equivalent data from the Pareto-optimal networks. Then, the model performances for high flows were compared to determine the best optimal network for enhanced spring runoff forecasting.

Mapping the temporary and perennial character of whole river networks

NASA Astrophysics Data System (ADS)

González-Ferreras, A. M.; Barquín, J.

2017-08-01

Knowledge of the spatial distribution of temporary and perennial river channels in a whole catchment is important for effective integrated basin management and river biodiversity conservation. However, this information is usually not available or is incomplete. In this study, we present a statistically based methodology to classify river segments from a whole river network (Deva-Cares catchment, Northern Spain) as temporary or perennial. This method is based on an a priori classification of a subset of river segments as temporary or perennial, using field surveys and aerial images, and then running Random Forest models to predict classification membership for the rest of the river network. The independent variables and the river network were derived following a computer-based geospatial simulation of riverine landscapes. The model results show high values of overall accuracy, sensitivity, and specificity for the evaluation of the fitted model to the training and testing data set (≥0.9). The most important independent variables were catchment area, area occupied by broadleaf forest, minimum monthly precipitation in August, and average catchment elevation. The final map shows 7525 temporary river segments (1012.5 km) and 3731 perennial river segments (662.5 km). A subsequent validation of the mapping results using River Habitat Survey data and expert knowledge supported the validity of the proposed maps. We conclude that the proposed methodology is a valid method for mapping the limits of flow permanence that could substantially increase our understanding of the spatial links between terrestrial and aquatic interfaces, improving the research, management, and conservation of river biodiversity and functioning.

Tokunaga river networks: New empirical evidence and applications to transport problems

NASA Astrophysics Data System (ADS)

Tejedor, A.; Zaliapin, I. V.

2013-12-01

The Tokunaga self-similarity has proven to be an important constraint for the observed river networks. Notably, various Horton laws are naturally satisfied by the Tokunaga networks, which makes this model of considerable interest for theoretical analysis and modeling of environmental transport. Recall that Horton self-similarity is a weaker property of a tree graph that addresses its principal branching; it is a counterpart of the power-law size distribution for system's elements. The stronger Tokunaga self-similarity addresses so-called side branching; it ensures that different levels of a hierarchy have the same probabilistic structure (in a sense that can be rigorously defined). We describe an improved statistical framework for testing self-similarity in a finite tree and estimating the related parameters. The developed inference is applied to the major river basins in continental United States and Iberian Peninsula. The results demonstrate the validity of the Tokunaga model for the majority of the examined networks with very narrow (universal) range of parameter values. Next, we explore possible relationships between the Tokunaga parameter anomalies (deviations from the universal values) and climatic and geomorphologic characteristics of a region. Finally, we apply the Tokunaga model to explore vulnerability of river networks, defined via reaction of the river discharge to a storm.

Application of optimization technique for flood damage modeling in river system

NASA Astrophysics Data System (ADS)

Barman, Sangita Deb; Choudhury, Parthasarathi

2018-04-01

A river system is defined as a network of channels that drains different parts of a basin uniting downstream to form a common outflow. An application of various models found in literatures, to a river system having multiple upstream flows is not always straight forward, involves a lengthy procedure; and with non-availability of data sets model calibration and applications may become difficult. In the case of a river system the flow modeling can be simplified to a large extent if the channel network is replaced by an equivalent single channel. In the present work optimization model formulations based on equivalent flow and applications of the mixed integer programming based pre-emptive goal programming model in evaluating flood control alternatives for a real life river system in India are proposed to be covered in the study.

A spatial model for a stream networks of Citarik River with the environmental variables: potential of hydrogen (PH) and temperature

NASA Astrophysics Data System (ADS)

Bachrudin, A.; Mohamed, N. B.; Supian, S.; Sukono; Hidayat, Y.

2018-03-01

Application of existing geostatistical theory of stream networks provides a number of interesting and challenging problems. Most of statistical tools in the traditional geostatistics have been based on a Euclidean distance such as autocovariance functions, but for stream data is not permissible since it deals with a stream distance. To overcome this autocovariance developed a model based on the distance the flow with using convolution kernel approach (moving average construction). Spatial model for a stream networks is widely used to monitor environmental on a river networks. In a case study of a river in province of West Java, the objective of this paper is to analyze a capability of a predictive on two environmental variables, potential of hydrogen (PH) and temperature using ordinary kriging. Several the empirical results show: (1) The best fit of autocovariance functions for temperature and potential hydrogen (ph) of Citarik River is linear which also yields the smallest root mean squared prediction error (RMSPE), (2) the spatial correlation values between the locations on upstream and on downstream of Citarik river exhibit decreasingly

Building Virtual Watersheds: A Global Opportunity to Strengthen Resource Management and Conservation.

PubMed

Benda, Lee; Miller, Daniel; Barquin, Jose; McCleary, Richard; Cai, TiJiu; Ji, Y

2016-03-01

Modern land-use planning and conservation strategies at landscape to country scales worldwide require complete and accurate digital representations of river networks, encompassing all channels including the smallest headwaters. The digital river networks, integrated with widely available digital elevation models, also need to have analytical capabilities to support resource management and conservation, including attributing river segments with key stream and watershed data, characterizing topography to identify landforms, discretizing land uses at scales necessary to identify human-environment interactions, and connecting channels downstream and upstream, and to terrestrial environments. We investigate the completeness and analytical capabilities of national to regional scale digital river networks that are available in five countries: Canada, China, Russia, Spain, and United States using actual resource management and conservation projects involving 12 university, agency, and NGO organizations. In addition, we review one pan-European and one global digital river network. Based on our analysis, we conclude that the majority of the regional, national, and global scale digital river networks in our sample lack in network completeness, analytical capabilities or both. To address this limitation, we outline a general framework to build as complete as possible digital river networks and to integrate them with available digital elevation models to create robust analytical capabilities (e.g., virtual watersheds). We believe this presents a global opportunity for in-country agencies, or international players, to support creation of virtual watersheds to increase environmental problem solving, broaden access to the watershed sciences, and strengthen resource management and conservation in countries worldwide.

Building Virtual Watersheds: A Global Opportunity to Strengthen Resource Management and Conservation

NASA Astrophysics Data System (ADS)

Benda, Lee; Miller, Daniel; Barquin, Jose; McCleary, Richard; Cai, TiJiu; Ji, Y.

2016-03-01

Modern land-use planning and conservation strategies at landscape to country scales worldwide require complete and accurate digital representations of river networks, encompassing all channels including the smallest headwaters. The digital river networks, integrated with widely available digital elevation models, also need to have analytical capabilities to support resource management and conservation, including attributing river segments with key stream and watershed data, characterizing topography to identify landforms, discretizing land uses at scales necessary to identify human-environment interactions, and connecting channels downstream and upstream, and to terrestrial environments. We investigate the completeness and analytical capabilities of national to regional scale digital river networks that are available in five countries: Canada, China, Russia, Spain, and United States using actual resource management and conservation projects involving 12 university, agency, and NGO organizations. In addition, we review one pan-European and one global digital river network. Based on our analysis, we conclude that the majority of the regional, national, and global scale digital river networks in our sample lack in network completeness, analytical capabilities or both. To address this limitation, we outline a general framework to build as complete as possible digital river networks and to integrate them with available digital elevation models to create robust analytical capabilities (e.g., virtual watersheds). We believe this presents a global opportunity for in-country agencies, or international players, to support creation of virtual watersheds to increase environmental problem solving, broaden access to the watershed sciences, and strengthen resource management and conservation in countries worldwide.

Where and why hyporheic exchange is important: Inferences from a parsimonious, physically-based river network model

NASA Astrophysics Data System (ADS)

Gomez-Velez, J. D.; Harvey, J. W.

2014-12-01

Hyporheic exchange has been hypothesized to have basin-scale consequences; however, predictions throughout river networks are limited by available geomorphic and hydrogeologic data as well as models that can analyze and aggregate hyporheic exchange flows across large spatial scales. We developed a parsimonious but physically-based model of hyporheic flow for application in large river basins: Networks with EXchange and Subsurface Storage (NEXSS). At the core of NEXSS is a characterization of the channel geometry, geomorphic features, and related hydraulic drivers based on scaling equations from the literature and readily accessible information such as river discharge, bankfull width, median grain size, sinuosity, channel slope, and regional groundwater gradients. Multi-scale hyporheic flow is computed based on combining simple but powerful analytical and numerical expressions that have been previously published. We applied NEXSS across a broad range of geomorphic diversity in river reaches and synthetic river networks. NEXSS demonstrates that vertical exchange beneath submerged bedforms dominates hyporheic fluxes and turnover rates along the river corridor. Moreover, the hyporheic zone's potential for biogeochemical transformations is comparable across stream orders, but the abundance of lower-order channels results in a considerably higher cumulative effect for low-order streams. Thus, vertical exchange beneath submerged bedforms has more potential for biogeochemical transformations than lateral exchange beneath banks, although lateral exchange through meanders may be important in large rivers. These results have implications for predicting outcomes of river and basin management practices.

Spatio-temporal statistical models for river monitoring networks.

PubMed

Clement, L; Thas, O; Vanrolleghem, P A; Ottoy, J P

2006-01-01

When introducing new wastewater treatment plants (WWTP), investors and policy makers often want to know if there indeed is a beneficial effect of the installation of a WWTP on the river water quality. Such an effect can be established in time as well as in space. Since both temporal and spatial components affect the output of a monitoring network, their dependence structure has to be modelled. River water quality data typically come from a river monitoring network for which the spatial dependence structure is unidirectional. Thus the traditional spatio-temporal models are not appropriate, as they cannot take advantage of this directional information. In this paper, a state-space model is presented in which the spatial dependence of the state variable is represented by a directed acyclic graph, and the temporal dependence by a first-order autoregressive process. The state-space model is extended with a linear model for the mean to estimate the effect of the activation of a WWTP on the dissolved oxygen concentration downstream.

Streamflow simulation for continental-scale river basins

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Lettenmaier, Dennis P.; Liang, Xu; Wetzel, Suzanne W.; Wood, Eric F.

1997-04-01

A grid network version of the two-layer variable infiltration capacity (VIC-2L) macroscale hydrologic model is described. VIC-2L is a hydrologically based soil- vegetation-atmosphere transfer scheme designed to represent the land surface in numerical weather prediction and climate models. The grid network scheme allows streamflow to be predicted for large continental rivers. Off-line (observed and estimated surface meteorological and radiative forcings) applications of the model to the Columbia River (1° latitude-longitude spatial resolution) and Delaware River (0.5° resolution) are described. The model performed quite well in both applications, reproducing the seasonal hydrograph and annual flow volumes to within a few percent. Difficulties in reproducing observed streamflow in the arid portion of the Snake River basin are attributed to groundwater-surface water interactions, which are not modeled by VIC-2L.

Monitoring groundwater and river interaction along the Hanford reach of the Columbia River

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

Campbell, M.D.

1994-04-01

As an adjunct to efficient Hanford Site characterization and remediation of groundwater contamination, an automatic monitor network has been used to measure Columbia River and adjacent groundwater levels in several areas of the Hanford Site since 1991. Water levels, temperatures, and electrical conductivity measured by the automatic monitor network provided an initial database with which to calibrate models and from which to infer ground and river water interactions for site characterization and remediation activities. Measurements of the dynamic river/aquifer system have been simultaneous at 1-hr intervals, with a quality suitable for hydrologic modeling and for computer model calibration and testing.more » This report describes the equipment, procedures, and results from measurements done in 1993.« less

Sustainable Improvement of Urban River Network Water Quality and Flood Control Capacity by a Hydrodynamic Control Approach-Case Study of Changshu City

NASA Astrophysics Data System (ADS)

Xie, Chen; Yang, Fan; Liu, Guoqing; Liu, Yang; Wang, Long; Fan, Ziwu

2017-01-01

Water environment of urban rivers suffers degradation with the impacts of urban expansion, especially in Yangtze River Delta. The water area in cites decreased sharply, and some rivers were cut off because of estate development, which brings the problems of urban flooding, flow stagnation and water deterioration. The approach aims to enhance flood control capability and improve the urban river water quality by planning gate-pump stations surrounding the cities and optimizing the locations and functions of the pumps, sluice gates, weirs in the urban river network. These gate-pump stations together with the sluice gates and weirs guarantee the ability to control the water level in the rivers and creating hydraulic gradient artificially according to mathematical model. Therefore the flow velocity increases, which increases the rate of water exchange, the DO concentration and water body self-purification ability. By site survey and prototype measurement, the river problems are evaluated and basic data are collected. The hydrodynamic model of the river network is established and calibrated to simulate the scenarios. The schemes of water quality improvement, including optimizing layout of the water distribution projects, improvement of the flow discharge in the river network and planning the drainage capacity are decided by comprehensive Analysis. Finally the paper introduces the case study of the approach in Changshu City, where the approach is successfully implemented.

Inverse modelling of fluvial sediment connectivity identifies characteristics and spatial distribution of sediment sources in a large river network.

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.; Rubin, Z.; Castelletti, A.

2016-12-01

Field and laboratory evidence indicates that the spatial distribution of transport in both alluvial and bedrock rivers is an adaptation to sediment supply. Sediment supply, in turn, depends on spatial distribution and properties (e.g., grain sizes and supply rates) of individual sediment sources. Analyzing the distribution of transport capacity in a river network could hence clarify the spatial distribution and properties of sediment sources. Yet, challenges include a) identifying magnitude and spatial distribution of transport capacity for each of multiple grain sizes being simultaneously transported, and b) estimating source grain sizes and supply rates, both at network scales. Herein, we approach the problem of identifying the spatial distribution of sediment sources and the resulting network sediment fluxes in a major, poorly monitored tributary (80,000 km2) of the Mekong. Therefore, we apply the CASCADE modeling framework (Schmitt et al. (2016)). CASCADE calculates transport capacities and sediment fluxes for multiple grainsizes on the network scale based on remotely-sensed morphology and modelled hydrology. CASCADE is run in an inverse Monte Carlo approach for 7500 random initializations of source grain sizes. In all runs, supply of each source is inferred from the minimum downstream transport capacity for the source grain size. Results for each realization are compared to sparse available sedimentary records. Only 1 % of initializations reproduced the sedimentary record. Results for these realizations revealed a spatial pattern in source supply rates, grain sizes, and network sediment fluxes that correlated well with map-derived patterns in lithology and river-morphology. Hence, we propose that observable river hydro-morphology contains information on upstream source properties that can be back-calculated using an inverse modeling approach. Such an approach could be coupled to more detailed models of hillslope processes in future to derive integrated models of hillslope production and fluvial transport processes, which is particularly useful to identify sediment provenance in poorly monitored river basins.

QUAL-NET, a high temporal-resolution eutrophication model for large hydrographic networks

NASA Astrophysics Data System (ADS)

Minaudo, Camille; Curie, Florence; Jullian, Yann; Gassama, Nathalie; Moatar, Florentina

2018-04-01

To allow climate change impact assessment of water quality in river systems, the scientific community lacks efficient deterministic models able to simulate hydrological and biogeochemical processes in drainage networks at the regional scale, with high temporal resolution and water temperature explicitly determined. The model QUALity-NETwork (QUAL-NET) was developed and tested on the Middle Loire River Corridor, a sub-catchment of the Loire River in France, prone to eutrophication. Hourly variations computed efficiently by the model helped disentangle the complex interactions existing between hydrological and biological processes across different timescales. Phosphorus (P) availability was the most constraining factor for phytoplankton development in the Loire River, but simulating bacterial dynamics in QUAL-NET surprisingly evidenced large amounts of organic matter recycled within the water column through the microbial loop, which delivered significant fluxes of available P and enhanced phytoplankton growth. This explained why severe blooms still occur in the Loire River despite large P input reductions since 1990. QUAL-NET could be used to study past evolutions or predict future trajectories under climate change and land use scenarios.

Connectivity of Secondary Channels in the Floodplain of a Low-Gradient Midwestern U.S. Agricultural River

NASA Astrophysics Data System (ADS)

Czuba, J. A.; David, S. R.; Edmonds, D. A.

2016-12-01

Floodplains of low-gradient Midwestern U.S. agricultural rivers are commonly dissected by a network of secondary channels that convey flow only during flood events. These networks of secondary channels have only recently been revealed by high resolution digital elevation models. Secondary channels, as referred to here, span multiple meander wavelengths and appear fundamentally different from chute channels. While secondary channels have been described to some extent in other river systems, our focus here is on those found in Indiana, which are revealed by state-wide LiDAR data acquired in 2011. In this work, we quantify how the network connectivity of the secondary channels in the floodplain develops as a function of flow stage. Secondary channels begin conveying water at stages just below bankfull, become an interconnected web of flow pathways above bankfull stage, and are completely inundated at higher stages. We construct a two-dimensional numerical model of the river/floodplain system from LiDAR data and from main-channel river bathymetry in order to obtain the extent of floodplain inundation at various flows. The inundated area within the secondary channels is then converted into a river/floodplain flow-channel network and quantified using various network metrics. Future work will explore the morphodynamics of this river/floodplain system extended to 100-1,000 year timescales. The goal is to develop a simple model to test hypotheses about how these floodplain channels evolve. Relevant research questions include: do secondary channels serve as preferential avulsion pathways? Or could secondary channels evolve to create a multi-channeled anabranching system? Furthermore, under what hydrologic and sedimentologic conditions would a river/floodplain system evolve to one state or another?

Simulation of dynamic expansion, contraction, and connectivity in a mountain stream network

NASA Astrophysics Data System (ADS)

Ward, Adam S.; Schmadel, Noah M.; Wondzell, Steven M.

2018-04-01

Headwater stream networks expand and contract in response to changes in stream discharge. The changes in the extent of the stream network are also controlled by geologic or geomorphic setting - some reaches go dry even under relatively wet conditions, other reaches remain flowing under relatively dry conditions. While such patterns are well recognized, we currently lack tools to predict the extent of the stream network and the times and locations where the network is dry within large river networks. Here, we develop a perceptual model of the river corridor in a headwater mountainous catchment, translate this into a reduced-complexity mechanistic model, and implement the model to examine connectivity and network extent over an entire water year. Our model agreed reasonably well with our observations, showing that the extent and connectivity of the river network was most sensitive to hydrologic forcing under the lowest discharges (Qgauge < 1 L s-1), that at intermediate discharges (1 L s-1 < Qgauge < 10 L s-1) the extent of the network changed dramatically with changes in discharge, and that under wet conditions (Qgauge > 10 L s-1) the extent of the network was relatively insensitive to hydrologic forcing and was instead determined by the network topology. We do not expect that the specific thresholds observed in this study would be transferable to other catchments with different geology, topology, or hydrologic forcing. However, we expect that the general pattern should be robust: the dominant controls will shift from hydrologic forcing to geologic setting as discharge increases. Furthermore, our method is readily transferable as the model can be applied with minimal data requirements (a single stream gauge, a digital terrain model, and estimates of hydrogeologic properties) to estimate flow duration or connectivity along the river corridor in unstudied catchments. As the available information increases, the model could be better calibrated to match site-specific observations of network extent, locations of dry reaches, or solute break through curves as demonstrated in this study. Based on the low initial data requirements and ability to later tune the model to a specific site, we suggest example applications of this parsimonious model that may prove useful to both researchers and managers.

The risk assessment of sudden water pollution for river network system under multi-source random emission

NASA Astrophysics Data System (ADS)

Li, D.

2016-12-01

Sudden water pollution accidents are unavoidable risk events that we must learn to co-exist with. In China's Taihu River Basin, the river flow conditions are complicated with frequently artificial interference. Sudden water pollution accident occurs mainly in the form of a large number of abnormal discharge of wastewater, and has the characteristics with the sudden occurrence, the uncontrollable scope, the uncertainty object and the concentrated distribution of many risk sources. Effective prevention of pollution accidents that may occur is of great significance for the water quality safety management. Bayesian networks can be applied to represent the relationship between pollution sources and river water quality intuitively. Using the time sequential Monte Carlo algorithm, the pollution sources state switching model, water quality model for river network and Bayesian reasoning is integrated together, and the sudden water pollution risk assessment model for river network is developed to quantify the water quality risk under the collective influence of multiple pollution sources. Based on the isotope water transport mechanism, a dynamic tracing model of multiple pollution sources is established, which can describe the relationship between the excessive risk of the system and the multiple risk sources. Finally, the diagnostic reasoning algorithm based on Bayesian network is coupled with the multi-source tracing model, which can identify the contribution of each risk source to the system risk under the complex flow conditions. Taking Taihu Lake water system as the research object, the model is applied to obtain the reasonable results under the three typical years. Studies have shown that the water quality risk at critical sections are influenced by the pollution risk source, the boundary water quality, the hydrological conditions and self -purification capacity, and the multiple pollution sources have obvious effect on water quality risk of the receiving water body. The water quality risk assessment approach developed in this study offers a effective tool for systematically quantifying the random uncertainty in plain river network system, and it also provides the technical support for the decision-making of controlling the sudden water pollution through identification of critical pollution sources.

A (very) Simple Model for the Aspect Ratio of High-Order River Basins

NASA Astrophysics Data System (ADS)

Shelef, E.

2017-12-01

The structure of river networks dictates the distribution of elevation, water, and sediments across Earth's surface. Despite its intricate shape, the structure of high-order river networks displays some surprising regularities such as the consistent aspect ratio (i.e., basin's width over length) of river basins along linear mountain fronts. This ratio controls the spacing between high-order channels as well as the spacing between the depositional bodies they form. It is generally independent of tectonic and climatic conditions and is often attributed to the initial topography over which the network was formed. This study shows that a simple, cross-like channel model explains this ratio via a requirement for equal elevation gain between the outlets and drainage-divides of adjacent channels at topographic steady state. This model also explains the dependence of aspect ratio on channel concavity and the location of the widest point on a drainage divide.

A flow-simulation model of the tidal Potomac River

USGS Publications Warehouse

Schaffranek, Raymond W.

1987-01-01

A one-dimensional model capable of simulating flow in a network of interconnected channels has been applied to the tidal Potomac River including its major tributaries and embayments between Washington, D.C., and Indian Head, Md. The model can be used to compute water-surface elevations and flow discharges at any of 66 predetermined locations or at any alternative river cross sections definable within the network of channels. In addition, the model can be used to provide tidal-interchange flow volumes and to evaluate tidal excursions and the flushing properties of the riverine system. Comparisons of model-computed results with measured watersurface elevations and discharges demonstrate the validity and accuracy of the model. Tidal-cycle flow volumes computed by the calibrated model have been verified to be within an accuracy of ? 10 percent. Quantitative characteristics of the hydrodynamics of the tidal river are identified and discussed. The comprehensive flow data provided by the model can be used to better understand the geochemical, biological, and other processes affecting the river's water quality.

Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

NASA Astrophysics Data System (ADS)

Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.

2011-12-01

HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of each timestep and minimize computational overhead. Power generation for each reservoir is estimated using a 2-dimensional regression that accounts for both the available head and turbine efficiency. The object-oriented architecture makes run configuration easy to update. The dynamic model inputs include inflow and meteorological forecasts while static inputs include bathymetry data, reservoir and power generation characteristics, and topological descriptors. Ensemble forecasts of hydrological and meteorological conditions are supplied in real-time by Pacific Northwest National Laboratory and are used as a proxy for uncertainty, which is carried through the simulation and optimization process to produce output that describes the probability that different operational scenario's will be optimal. The full toolset, which includes HydroSCOPE, is currently being tested on the Feather River system in Northern California and the Upper Colorado Storage Project.

Optimal Design of River Monitoring Network in Taizihe River by Matter Element Analysis

PubMed Central

Wang, Hui; Liu, Zhe; Sun, Lina; Luo, Qing

2015-01-01

The objective of this study is to optimize the river monitoring network in Taizihe River, Northeast China. The situation of the network and water characteristics were studied in this work. During this study, water samples were collected once a month during January 2009 - December 2010 from seventeen sites. Futhermore, the 16 monitoring indexes were analyzed in the field and laboratory. The pH value of surface water sample was found to be in the range of 6.83 to 9.31, and the average concentrations of NH4 +-N, chemical oxygen demand (COD), volatile phenol and total phosphorus (TP) were found decreasing significantly. The water quality of the river has been improved from 2009 to 2010. Through the calculation of the data availability and the correlation between adjacent sections, it was found that the present monitoring network was inefficient as well as the optimization was indispensable. In order to improve the situation, the matter element analysis and gravity distance were applied in the optimization of river monitoring network, which were proved to be a useful method to optimize river quality monitoring network. The amount of monitoring sections were cut from 17 to 13 for the monitoring network was more cost-effective after being optimized. The results of this study could be used in developing effective management strategies to improve the environmental quality of Taizihe River. Also, the results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems. PMID:26023785

Consistent initial conditions for the Saint-Venant equations in river network modeling

NASA Astrophysics Data System (ADS)

Yu, Cheng-Wei; Liu, Frank; Hodges, Ben R.

2017-09-01

Initial conditions for flows and depths (cross-sectional areas) throughout a river network are required for any time-marching (unsteady) solution of the one-dimensional (1-D) hydrodynamic Saint-Venant equations. For a river network modeled with several Strahler orders of tributaries, comprehensive and consistent synoptic data are typically lacking and synthetic starting conditions are needed. Because of underlying nonlinearity, poorly defined or inconsistent initial conditions can lead to convergence problems and long spin-up times in an unsteady solver. Two new approaches are defined and demonstrated herein for computing flows and cross-sectional areas (or depths). These methods can produce an initial condition data set that is consistent with modeled landscape runoff and river geometry boundary conditions at the initial time. These new methods are (1) the pseudo time-marching method (PTM) that iterates toward a steady-state initial condition using an unsteady Saint-Venant solver and (2) the steady-solution method (SSM) that makes use of graph theory for initial flow rates and solution of a steady-state 1-D momentum equation for the channel cross-sectional areas. The PTM is shown to be adequate for short river reaches but is significantly slower and has occasional non-convergent behavior for large river networks. The SSM approach is shown to provide a rapid solution of consistent initial conditions for both small and large networks, albeit with the requirement that additional code must be written rather than applying an existing unsteady Saint-Venant solver.

Hydrodynamics and Connectivity of Channelized Floodplains: Insights from the Meandering East Fork White River, Indiana, USA

NASA Astrophysics Data System (ADS)

Czuba, J. A.; David, S. R.; Edmonds, D. A.

2017-12-01

High resolution topography reveals that meandering river floodplains in Indiana commonly have networks of channels. These floodplain channel networks are most prevalent in agricultural, low-gradient, wide floodplains. It appears that these networks are formed when floodplain channels connect oxbows to each other and the main river channel. Collectively, the channels in the floodplain create an interconnected network of pathways that convey water beginning at flows less than bankfull, and as stage increases, more of the floodplain becomes dissected by floodplain channels. In this work, we quantify the hydrodynamics and connectivity of the flow on the floodplain and in the main channel of the East Fork White River near Seymour, Indiana, USA. We constructed a two-dimensional numerical model using HECRAS of the river-floodplain system from LiDAR data and from main-channel river bathymetry to elucidate the behaviour of these floodplain channels across a range of flows. Model calibration and verification data included stage from a USGS gage, high-water marks at a high and medium flow, and an aerial photograph of inundation in the floodplain channels. The numerical model simulated flow depth and velocity, which was used to quantify connectivity of the floodplain channels, exchange between the main channel and floodplain channels, and residence time of water on the floodplain. Model simulations suggest that the floodplain channels convey roughly 50% of the total flow at what is typically considered "bankfull" flow. Overall, we present a process-based approach for analyzing complex floodplain-river systems where an individual floodplain-river system can be distilled down to a set of characteristic curves. Notably, we map the East Fork White River system to exchange-residence time space and argue that this characterization forms the basis for thinking about morphologic evolution (e.g., sediment deposition and erosion) and biogeochemistry (e.g., nitrate removal) in floodplain-river systems.

Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages.

PubMed

Radinger, Johannes; Hölker, Franz; Horký, Pavel; Slavík, Ondřej; Dendoncker, Nicolas; Wolter, Christian

2016-04-01

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts. © 2015 John Wiley & Sons Ltd.

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS

USGS Publications Warehouse

Brakebill, J.W.; Terziotti, S.E.

2011-01-01

A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.

A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1

USGS Publications Warehouse

Brakebill, J.W.; Terziotti, S.E.

2011-01-01

A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.

Nitrogen retention in rivers: Model development and application to watersheds in the northeastern U.S.A.

USGS Publications Warehouse

Seitzinger, S.P.; Styles, R.V.; Boyer, E.W.; Alexander, R.B.; Billen, G.; Howarth, R.W.; Mayer, B.; Van Breemen, N.

2002-01-01

A regression model (RivR-N) was developed that predicts the proportion of N removed from streams and reservoirs as an inverse function of the water displacement time of the water body (ratio of water body depth to water time of travel). When applied to 16 drainage networks in the eastern U.S., the RivR-N model predicted that 37% to 76% of N input to these rivers is removed during transport through the river networks. Approximately half of that is removed in 1st through 4th order streams which account for 90% of the total stream length. The other half is removed in 5th order and higher rivers which account for only about 10% of the total stream length. Most N removed in these higher orders is predicted to originate from watershed loading to small and intermediate sized streams. The proportion of N removed from all streams in the watersheds (37-76%) is considerably higher than the proportion of N input to an individual reach that is removed in that reach (generally <20%) because of the cumulative effect of continued nitrogen removal along the entire flow path in downstream reaches. This generally has not been recognized in previous studies, but is critical to an evaluation of the total amount of N removed within a river network. At the river network scale, reservoirs were predicted to have a minimal effect on N removal. A fairly modest decrease (<10 percentage points) in the N removed at the river network scale was predicted when a third of the direct watershed loading was to the two highest orders compared to a uniform loading.

Denitrification in the Mississippi River network controlled by flow through river bedforms

USGS Publications Warehouse

Gomez-Velez, Jesus D.; Harvey, Judson W.; Cardenas, M. Bayani; Kiel, Brian

2015-01-01

Increasing nitrogen concentrations in the world’s major rivers have led to over-fertilization of sensitive downstream waters. Flow through channel bed and bank sediments acts to remove riverine nitrogen through microbe-mediated denitrification reactions. However, little is understood about where in the channel network this biophysical process is most efficient, why certain channels are more effective nitrogen reactors, and how management practices can enhance the removal of nitrogen in regions where water circulates through sediment and mixes with groundwater - hyporheic zones. Here we present numerical simulations of hyporheic flow and denitrification throughout the Mississippi River network using a hydrogeomorphic model. We find that vertical exchange with sediments beneath the riverbed in hyporheic zones, driven by submerged bedforms, has denitrification potential that far exceeds lateral hyporheic exchange with sediments alongside river channels, driven by river bars and meandering banks. We propose that geomorphic differences along river corridors can explain why denitrification efficiency varies between basins in the Mississippi River network. Our findings suggest that promoting the development of permeable bedforms at the streambed - and thus vertical hyporheic exchange - would be more effective at enhancing river denitrification in large river basins than promoting lateral exchange through induced channel meandering.

Five-minute, 1/2°, and 1° data sets of continental watersheds and river networks for use in regional and global hydrologic and climate system modeling studies

NASA Astrophysics Data System (ADS)

Graham, S. T.; Famiglietti, J. S.; Maidment, D. R.

1999-02-01

A major shortcoming of the land surface component in climate models is the absence of a river transport algorithm. This issue becomes particularly important in fully coupled climate system models (CSMs), where river transport is required to close and realistically represent the global water cycle. The development of a river transport algorithm requires knowledge of watersheds and river networks at a scale that is appropriate for use in CSMs. These data must be derived largely from global digital topographic information. The purpose of this paper is to describe a new data set of watersheds and river networks, which is derived primarily from the TerrainBase 5' Global DTM (digital terrain model) and the CIA World Data Bank II. These data serve as a base map for routing continental runoff to the appropriate coast and therefore into the appropriate ocean or inland sea. Using this data set, the runoff produced in any grid cell, when coupled with a routing algorithm, can easily be transported to the appropriate water body and distributed across that water body as desired. The data set includes watershed and flow direction information, as well as supporting hydrologic data at 5', 1/2°, and 1° resolutions globally. It will be useful in fully coupled land-ocean-atmosphere models, in terrestrial ecosystem models, or in stand-alone macroscale hydrologic-modeling studies.

Modeling Nitrogen Processing in Northeast US River Networks

NASA Astrophysics Data System (ADS)

Whittinghill, K. A.; Stewart, R.; Mineau, M.; Wollheim, W. M.; Lammers, R. B.

2013-12-01

Due to increased nitrogen (N) pollution from anthropogenic sources, the need for aquatic ecosystem services such as N removal has also increased. River networks provide a buffering mechanism that retains or removes anthropogenic N inputs. However, the effectiveness of N removal in rivers may decline with increased loading and, consequently, excess N is eventually delivered to estuaries. We used a spatially distributed river network N removal model developed within the Framework for Aquatic Modeling in the Earth System (FrAMES) to examine the geography of N removal capacity of Northeast river systems under various land use and climate conditions. FrAMES accounts for accumulation and routing of runoff, water temperatures, and serial biogeochemical processing using reactivity derived from the Lotic Intersite Nitrogen Experiment (LINX2). Nonpoint N loading is driven by empirical relationships with land cover developed from previous research in Northeast watersheds. Point source N loading from wastewater treatment plants is estimated as a function of the population served and the volume of water discharged. We tested model results using historical USGS discharge data and N data from historical grab samples and recently initiated continuous measurements from in-situ aquatic sensors. Model results for major Northeast watersheds illustrate hot spots of ecosystem service activity (i.e. N removal) using high-resolution maps and basin profiles. As expected, N loading increases with increasing suburban or agricultural land use area. Network scale N removal is highest during summer and autumn when discharge is low and river temperatures are high. N removal as the % of N loading increases with catchment size and decreases with increasing N loading, suburban land use, or agricultural land use. Catchments experiencing the highest network scale N removal generally have N inputs (both point and non-point sources) located in lower order streams. Model results can be used to better predict nutrient loading to the coastal ocean across a broad range of current and future climate variability.

A Hydrologic Routing Model Based on Geomorphological Characteristics of the River Network

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Quintero, F.; Ghimire, G.; Rojas, M.

2017-12-01

The Iowa Flood Center (IFC) provides streamflow forecasts for about 2000 locations in Iowa using a real-time distributed hydrologic model, forced with radar and raingage rainfall information. The model structure is based on ordinary differential equations that represent the flow of water from the hillslopes to the channels of the river network. The formulation of the routing of water across the rivers constitutes a fundamental aspect of the model, because this component is mostly responsible for providing estimates of the time-to-peak and peak magnitude. The routing model structure of the system is based on the scaling properties of river velocity with the discharge and drainage area of the channel, which can be written in terms of a power-law function. This study examines how this scaling relation is connected to the Horton-Strahler order of the channel network. This evaluation represents a step forward towards formulating model structures that are based on characteristics that are invariant across spatial scales. We proposed a routing model for every different Horton orders of the network, by adjusting a power-law function to available observations of velocity and discharge provided by USGS. The models were implemented into the Hillslope-Link Model (HLM) of the IFC for offline evaluation. Model simulations were compared to discharge observations to assess their performance, and compared to simulations obtained with other hydrologic routing schemes, to determine if the new formulation improves performance of the model.

The role of reservoir storage in large-scale surface water availability analysis for Europe

NASA Astrophysics Data System (ADS)

Garrote, L. M.; Granados, A.; Martin-Carrasco, F.; Iglesias, A.

2017-12-01

A regional assessment of current and future water availability in Europe is presented in this study. The assessment was made using the Water Availability and Adaptation Policy Analysis (WAAPA) model. The model was built on the river network derived from the Hydro1K digital elevation maps, including all major river basins of Europe. Reservoir storage volume was taken from the World Register of Dams of ICOLD, including all dams with storage capacity over 5 hm3. Potential Water Availability is defined as the maximum amount of water that could be supplied at a certain point of the river network to satisfy a regular demand under pre-specified reliability requirements. Water availability is the combined result of hydrological processes, which determine streamflow in natural conditions, and human intervention, which determines the available hydraulic infrastructure to manage water and establishes water supply conditions through operating rules. The WAAPA algorithm estimates the maximum demand that can be supplied at every node of the river network accounting for the regulation capacity of reservoirs under different management scenarios. The model was run for a set of hydrologic scenarios taken from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), where the PCRGLOBWB hydrological model was forced with results from five global climate models. Model results allow the estimation of potential water stress by comparing water availability to projections of water abstractions along the river network under different management alternatives. The set of sensitivity analyses performed showed the effect of policy alternatives on water availability and highlighted the large uncertainties linked to hydrological and anthropological processes.

Exploring 3D optimal channel networks by multiple organizing principles

NASA Astrophysics Data System (ADS)

Mason, Emanuele; Bizzi, Simone; Cominola, Andrea; Castelletti, Andrea; Paik, Kyungrock

2017-04-01

Catchment topography and flow networks are shaped by the interactions of water and sediment across various spatial and temporal scales. The complexity of these processes hinders the development of models able to assess the validity of general principles governing such phenomena. The theory of Optimal Channel Networks (OCNs) proved that it is possible to generate drainage networks statistically comparable to those observed in nature by minimizing the energy spent by the water flowing through them. So far, the OCN theory has been developed for planar 2D domains, assuming equal energy expenditure per unit area of channel and, correspondingly, a constant slope-discharge relationship. In this work, we apply the OCN theory to 3D problems by introducing a multi-principle minimization starting from an artificial digital elevation model of pyramidal shape. The OCN theory assumption of constant slope-area relationship is relaxed and embedded into a second-order principle. The modelled 3D channel networks achieve lower total energy expenditure corresponding to 2D sub-optimal OCNs bound to specific slope-area relationships. This is the first time we are able to explore accessible 3D OCNs starting from a general DEM. By contrasting the modelled 3D OCNs and natural river networks, we found statistical similarities of two indexes, namely the area exponent index and the profile concavity index. Among the wide range of alternative and sub-optimal river networks, a minimum degree of 3D network organization is found to guarantee the indexes values within the natural range. These networks simultaneously possess topological and topographic properties of real river networks. We found a pivotal functional link between slope-area relationship and accessible sub-optimal 2D river network paths, which suggests that geological and climate conditions producing slope-area relationships in natural basins co-determine the degree of optimality of accessible network paths.

A new, accurate, global hydrography data for remote sensing and modelling of river hydrodynamics

NASA Astrophysics Data System (ADS)

Yamazaki, D.

2017-12-01

A high-resolution hydrography data is an important baseline data for remote sensing and modelling of river hydrodynamics, given the spatial scale of river network is much smaller than that of land hydrology or atmosphere/ocean circulations. For about 10 years, HydroSHEDS, developed based on the SRTM3 DEM, has been the only available global-scale hydrography data. However, the data availability at the time of HydroSHEDS development limited the quality of the represented river networks. Here, we developed a new global hydrography data using latest geodata such as the multi-error-removed elevation data (MERIT DEM), Landsat-based global water body data (GSWO & G3WBM), cloud-sourced open geography database (OpenStreetMap). The new hydrography data covers the entire globe (including boreal regions above 60N), and it represents more detailed structure of the world river network and contains consistent supplementary data layers such as hydrologically adjusted elevations and river channel width. In the AGU meeting, the developing methodology, assessed quality, and potential applications of the new global hydrography data will be introduced.

Cumulative Significance of Hyporheic Exchange and Biogeochemical Processing in River Networks

NASA Astrophysics Data System (ADS)

Harvey, J. W.; Gomez-Velez, J. D.

2014-12-01

Biogeochemical reactions in rivers that decrease excessive loads of nutrients, metals, organic compounds, etc. are enhanced by hydrologic interactions with microbially and geochemically active sediments of the hyporheic zone. The significance of reactions in individual hyporheic flow paths has been shown to be controlled by the contact time between river water and sediment and the intrinsic reaction rate in the sediment. However, little is known about how the cumulative effects of hyporheic processing in large river basins. We used the river network model NEXSS (Gomez-Velez and Harvey, submitted) to simulate hyporheic exchange through synthetic river networks based on the best available models of network topology, hydraulic geometry and scaling of geomorphic features, grain size, hydraulic conductivity, and intrinsic reaction rates of nutrients and metals in river sediment. The dimensionless reaction significance factor, RSF (Harvey et al., 2013) was used to quantify the cumulative removal fraction of a reactive solute by hyporheic processing. SF scales reaction progress in a single pass through the hyporheic zone with the proportion of stream discharge passing through the hyporheic zone for a specified distance. Reaction progress is optimal where the intrinsic reaction timescale in sediment matches the residence time of hyporheic flow and is less efficient in longer residence time hyporheic flow as a result of the decreasing proportion of river flow that is processed by longer residence time hyporheic flow paths. In contrast, higher fluxes through short residence time hyporheic flow paths may be inefficient because of the repeated surface-subsurface exchanges required to complete the reaction. Using NEXSS we found that reaction efficiency may be high in both small streams and large rivers, although for different reasons. In small streams reaction progress generally is dominated by faster pathways of vertical exchange beneath submerged bedforms. Slower exchange beneath meandering river banks mainly has importance only in large rivers. For solutes entering networks in proportion to water inputs it is the lower order streams that tend to dominate cumulative reaction progress.

Automatic River Network Extraction from LIDAR Data

NASA Astrophysics Data System (ADS)

Maderal, E. N.; Valcarcel, N.; Delgado, J.; Sevilla, C.; Ojeda, J. C.

2016-06-01

National Geographic Institute of Spain (IGN-ES) has launched a new production system for automatic river network extraction for the Geospatial Reference Information (GRI) within hydrography theme. The goal is to get an accurate and updated river network, automatically extracted as possible. For this, IGN-ES has full LiDAR coverage for the whole Spanish territory with a density of 0.5 points per square meter. To implement this work, it has been validated the technical feasibility, developed a methodology to automate each production phase: hydrological terrain models generation with 2 meter grid size and river network extraction combining hydrographic criteria (topographic network) and hydrological criteria (flow accumulation river network), and finally the production was launched. The key points of this work has been managing a big data environment, more than 160,000 Lidar data files, the infrastructure to store (up to 40 Tb between results and intermediate files), and process; using local virtualization and the Amazon Web Service (AWS), which allowed to obtain this automatic production within 6 months, it also has been important the software stability (TerraScan-TerraSolid, GlobalMapper-Blue Marble , FME-Safe, ArcGIS-Esri) and finally, the human resources managing. The results of this production has been an accurate automatic river network extraction for the whole country with a significant improvement for the altimetric component of the 3D linear vector. This article presents the technical feasibility, the production methodology, the automatic river network extraction production and its advantages over traditional vector extraction systems.

Drainage fracture networks in elastic solids with internal fluid generation

NASA Astrophysics Data System (ADS)

Kobchenko, Maya; Hafver, Andreas; Jettestuen, Espen; Galland, Olivier; Renard, François; Meakin, Paul; Jamtveit, Bjørn; Dysthe, Dag K.

2013-06-01

Experiments in which CO2 gas was generated by the yeast fermentation of sugar in an elastic layer of gelatine gel confined between two glass plates are described and analyzed theoretically. The CO2 gas pressure causes the gel layer to fracture. The gas produced is drained on short length scales by diffusion and on long length scales by flow in a fracture network, which has topological properties that are intermediate between river networks and hierarchical-fracture networks. A simple model for the experimental system with two parameters that characterize the disorder and the intermediate (river-fracture) topology of the network was developed and the results of the model were compared with the experimental results.

Observations and analysis of self-similar branching topology in glacier networks

USGS Publications Warehouse

Bahr, D.B.; Peckham, S.D.

1996-01-01

Glaciers, like rivers, have a branching structure which can be characterized by topological trees or networks. Probability distributions of various topological quantities in the networks are shown to satisfy the criterion for self-similarity, a symmetry structure which might be used to simplify future models of glacier dynamics. Two analytical methods of describing river networks, Shreve's random topology model and deterministic self-similar trees, are applied to the six glaciers of south central Alaska studied in this analysis. Self-similar trees capture the topological behavior observed for all of the glaciers, and most of the networks are also reasonably approximated by Shreve's theory. Copyright 1996 by the American Geophysical Union.

A modelling framework to evaluate human-induced alterations of network sediment connectivity and quantify their unplanned adverse impact

NASA Astrophysics Data System (ADS)

Bizzi, S.; Schmitt, R. J. P.; Giuliani, M.; Castelletti, A.

2016-12-01

World-wide human-induced alterations of sediment transport, e.g. due to dams, sand and gravel mining along rivers and channel maintenance, translated into geomorphic changes, which have had major effects on ecosystem integrity, human livelihoods, ultimately negatively impacting also on the expected benefit from building water infrastructures. Despite considerable recent advances in modelling basin-scale hydrological and geomorphological processes, our ability to quantitatively simulate network sediment transport, foresee effects of alternative scenarios of human development on fluvial morpho-dynamics, and design anticipatory planning adaptation measures is still limited. In this work, we demonstrate the potential of a novel modelling framework called CASCADE (CAtchment SEdiment Connectivity And Delivery (Schmitt et al., 2016)) to characterize sediment connectivity at the whole river network scale, predict the disturbing effect of dams on the sediment transport, and quantify the associated loss with respect to the level of benefits that provided the economic justification for their development. CASCADE allows tracking the fate of a sediment from its source to its multiple sinks across the network. We present the results from two major, transboundary river systems (3S and Red River) in South-East Asia. We first discuss the ability of CASCADE to properly represent sediment connectivity at the network scale using available remote sensing data and information from monitoring networks. Secondly, we assess the impacts on sediment connectivity induced by existing and planned dams in the 3S and Red River basins and compare these alterations with revenues in terms of hydropower production. CASCADE outputs support a broader understanding of sediment connectivity tailored for water management issues not yet available, and it is suitable to enrich assessments of food-energy-water nexus. The model framework can be embedded into the design of optimal siting and sizing of water infrastructures at the river basin scale. This enlarges the scope of the analysis to account for human-induced alterations of network sediment connectivity, and to explore the trade-off with respect to primary operational objectives, such as hydropower production, water supply, and flood control.

Denitrification in the Mississippi River network controlled by flow through river bedforms

USGS Publications Warehouse

Gomez-Velez, Jesus D.; Harvey, Judson W.; Cardenas, M. Bayani; Kiel, Brian

2015-01-01

Increasing nitrogen concentrations in the world’s major rivers have led to over-fertilization of sensitive downstream waters1, 2, 3, 4. Flow through channel bed and bank sediments acts to remove riverine nitrogen through microbe-mediated denitrification reactions5, 6, 7, 8, 9, 10. However, little is understood about where in the channel network this biophysical process is most efficient, why certain channels are more effective nitrogen reactors, and how management practices can enhance the removal of nitrogen in regions where water circulates through sediment and mixes with groundwater - hyporheic zones8, 11, 12. Here we present numerical simulations of hyporheic flow and denitrification throughout the Mississippi River network using a hydrogeomorphic model. We find that vertical exchange with sediments beneath the riverbed in hyporheic zones, driven by submerged bedforms, has denitrification potential that far exceeds lateral hyporheic exchange with sediments alongside river channels, driven by river bars and meandering banks. We propose that geomorphic differences along river corridors can explain why denitrification efficiency varies between basins in the Mississippi River network. Our findings suggest that promoting the development of permeable bedforms at the streambed - and thus vertical hyporheic exchange - would be more effective at enhancing river denitrification in large river basins than promoting lateral exchange through induced channel meandering. 

Contextualizing Wetlands Within a River Network to Assess Nitrate Removal and Inform Watershed Management

NASA Astrophysics Data System (ADS)

Czuba, Jonathan A.; Hansen, Amy T.; Foufoula-Georgiou, Efi; Finlay, Jacques C.

2018-02-01

Aquatic nitrate removal depends on interactions throughout an interconnected network of lakes, wetlands, and river channels. Herein, we present a network-based model that quantifies nitrate-nitrogen and organic carbon concentrations through a wetland-river network and estimates nitrate export from the watershed. This model dynamically accounts for multiple competing limitations on nitrate removal, explicitly incorporates wetlands in the network, and captures hierarchical network effects and spatial interactions. We apply the model to the Le Sueur Basin, a data-rich 2,880 km2 agricultural landscape in southern Minnesota and validate the model using synoptic field measurements during June for years 2013-2015. Using the model, we show that the overall limits to nitrate removal rate via denitrification shift between nitrate concentration, organic carbon availability, and residence time depending on discharge, characteristics of the waterbody, and location in the network. Our model results show that the spatial context of wetland restorations is an important but often overlooked factor because nonlinearities in the system, e.g., deriving from switching of resource limitation on denitrification rate, can lead to unexpected changes in downstream biogeochemistry. Our results demonstrate that reduction of watershed-scale nitrate concentrations and downstream loads in the Le Sueur Basin can be most effectively achieved by increasing water residence time (by slowing the flow) rather than by increasing organic carbon concentrations (which may limit denitrification). This framework can be used toward assessing where and how to restore wetlands for reducing nitrate concentrations and loads from agricultural watersheds.

Exploring biological, chemical and geomorphological patterns in fluvial ecosystems with Structural Equation Modelling

NASA Astrophysics Data System (ADS)

Bizzi, S.; Surridge, B.; Lerner, D. N.:

2009-04-01

River ecosystems represent complex networks of interacting biological, chemical and geomorphological processes. These processes generate spatial and temporal patterns in biological, chemical and geomorphological variables, and a growing number of these variables are now being used to characterise the status of rivers. However, integrated analyses of these biological-chemical-geomorphological networks have rarely been undertaken, and as a result our knowledge of the underlying processes and how they generate the resulting patterns remains weak. The apparent complexity of the networks involved, and the lack of coherent datasets, represent two key challenges to such analyses. In this paper we describe the application of a novel technique, Structural Equation Modelling (SEM), to the investigation of biological, chemical and geomorphological data collected from rivers across England and Wales. The SEM approach is a multivariate statistical technique enabling simultaneous examination of direct and indirect relationships across a network of variables. Further, SEM allows a-priori conceptual or theoretical models to be tested against available data. This is a significant departure from the solely exploratory analyses which characterise other multivariate techniques. We took biological, chemical and river habitat survey data collected by the Environment Agency for 400 sites in rivers spread across England and Wales, and created a single, coherent dataset suitable for SEM analyses. Biological data cover benthic macroinvertebrates, chemical data relate to a range of standard parameters (e.g. BOD, dissolved oxygen and phosphate concentration), and geomorphological data cover factors such as river typology, substrate material and degree of physical modification. We developed a number of a-priori conceptual models, reflecting current research questions or existing knowledge, and tested the ability of these conceptual models to explain the variance and covariance within the dataset. The conceptual models we developed were able to explain correctly the variance and covariance shown by the datasets, proving to be a relevant representation of the processes involved. The models explained 65% of the variance in indices describing benthic macroinvertebrate communities. Dissolved oxygen was of primary importance, but geomorphological factors, including river habitat type and degree of habitat degradation, also had significant explanatory power. The addition of spatial variables, such as latitude or longitude, did not provide additional explanatory power. This suggests that the variables already included in the models effectively represented the eco-regions across which our data were distributed. The models produced new insights into the relative importance of chemical and geomorphological factors for river macroinvertebrate communities. The SEM technique proved a powerful tool for exploring complex biological-chemical-geomorphological networks, for example able to deal with the co-correlations that are common in rivers due to multiple feedback mechanisms.

One-dimensional modelling of the interactions between heavy rainfall-runoff in an urban area and flooding flows from sewer networks and rivers.

PubMed

Kouyi, G Lipeme; Fraisse, D; Rivière, N; Guinot, V; Chocat, B

2009-01-01

Many investigations have been carried out in order to develop models which allow the linking of complex physical processes involved in urban flooding. The modelling of the interactions between overland flows on streets and flooding flows from rivers and sewer networks is one of the main objectives of recent and current research programs in hydraulics and urban hydrology. This paper outlines the original one-dimensional linking of heavy rainfall-runoff in urban areas and flooding flows from rivers and sewer networks under the RIVES project framework (Estimation of Scenario and Risks of Urban Floods). The first part of the paper highlights the capacity of Canoe software to simulate the street flows. In the second part, we show the original method of connection which enables the modelling of interactions between processes in urban flooding. Comparisons between simulated results and the results of Despotovic et al. or Gomez & Mur show a good agreement for the calibrated one-dimensional connection model. The connection operates likes a manhole with the orifice/weir coefficients used as calibration parameters. The influence of flooding flows from river was taken into account as a variable water depth boundary condition.

A stream temperature model for the Peace-Athabasca River basin

NASA Astrophysics Data System (ADS)

Morales-Marin, L. A.; Rokaya, P.; Wheater, H. S.; Lindenschmidt, K. E.

2017-12-01

Water temperature plays a fundamental role in water ecosystem functioning. Because it regulates flow energy and metabolic rates in organism productivity over a broad spectrum of space and time scales, water temperature constitutes an important indicator of aquatic ecosystems health. In cold region basins, stream water temperature modelling is also fundamental to predict ice freeze-up and break-up events in order to improve flood management. Multiple model approaches such as linear and multivariable regression methods, neural network and thermal energy budged models have been developed and implemented to simulate stream water temperature. Most of these models have been applied to specific stream reaches and trained using observed data, but very little has been done to simulate water temperature in large catchment river networks. We present the coupling of RBM model, a semi-Lagrangian water temperature model for advection-dominated river system, and MESH, a semi-distributed hydrological model, to simulate stream water temperature in river catchments. The coupled models are implemented in the Peace-Athabasca River basin in order to analyze the variation in stream temperature regimes under changing hydrological and meteorological conditions. Uncertainty of stream temperature simulations is also assessed in order to determine the degree of reliability of the estimates.

RIVER LEVEL ESTIMATION USING ARTIFICIAL NEURAL NETWORK FOR URBAN SMALL RIVER IN TIDAL REACH

NASA Astrophysics Data System (ADS)

Takasaki, Tadakatsu; Kawamura, Akira; Amaguchi, Hideo

Prediction of water level in small rivers is great interest for flood control in an urban area located in the river mouth. The tidal river water level is affected by not only flood discharge but also tide, atmospheric pressure, wind direction and speed. We propose a method of estimating river water level considering these factors using an artificial neural network model for the Kanda River located in the center of Tokyo. The effects by those factors are quantitatively investigated. As for the effects by the atmospheric pressure, river water level rises about 7cm per 5hPa increase of the pressure regardless of river discharge under the conditions of 1m/s wind speed and north wind direction. The accurate rating curve for the tidal river is finally obtained.

The national stream quality accounting network: A flux-basedapproach to monitoring the water quality of large rivers

USGS Publications Warehouse

Hooper, R.P.; Aulenbach, Brent T.; Kelly, V.J.

2001-01-01

Estimating the annual mass flux at a network of fixed stations is one approach to characterizing water quality of large rivers. The interpretive context provided by annual flux includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean. Since 1995, the US Geological Survey's National Stream Quality Accounting Network (NASQAN) has employed this approach at a network of 39 stations in four of the largest river basins of the USA: The Mississippi, the Columbia, the Colorado and the Rio Grande. In this paper, the design of NASQAN is described and its effectiveness at characterizing the water quality of these rivers is evaluated using data from the first 3 years of operation. A broad range of constituents was measured by NASQAN, including trace organic and inorganic chemicals, major ions, sediment and nutrients. Where possible, a regression model relating concentration to discharge and season was used to interpolate between chemical observations for flux estimation. For water-quality network design, the most important finding from NASQAN was the importance of having a specific objective (that is, estimating annual mass flux) and, from that, an explicitly stated data analysis strategy, namely the use of regression models to interpolate between observations. The use of such models aided in the design of sampling strategy and provided a context for data review. The regression models essentially form null hypotheses for concentration variation that can be evaluated by the observed data. The feedback between network operation and data collection established by the hypothesis tests places the water-quality network on a firm scientific footing.

Flow regulation in the Swiss Alps: a river network modelling approach to investigate the impacts on bed load and grain size distribution

NASA Astrophysics Data System (ADS)

Costa, A.; Molnar, P.; Schmitt, R. J. P.

2017-12-01

The grain size distribution (GSD) of river bed sediment results from the long term balance between transport capacity and sediment supply. Changes in climate and human activities may alter the spatial distribution of transport capacity and sediment supply along channels and hence impact local bedload transport and GSD. The effects of changed flow are not easily inferable due the non-linear, threshold-based nature of the relation between discharge and sediment mobilization, and the network-scale control on local sediment supply. We present a network-scale model for fractional sediment transport to quantify the impact of hydropower (HP) operations on river network GSD. We represent the river network as a series of connected links for which we extract the geometric characteristics from satellite images and a digital elevation model. We assign surface roughness based on the channel bed GSD. Bed shear stress is estimated at link-scale under the assumptions of rectangular prismatic cross sections and normal flow. The mass balance between sediment supply and transport capacity, computed with the Wilcock and Crowe model, determines transport rates of multiple grain size classes and the resulting GSD. We apply the model to the upper Rhone basin, a large Alpine basin in Switzerland. Since 1960s, changed flow conditions due to HP operations and sediment storage behind dams have potentially altered the sediment transport of the basin. However, little is known on the magnitude and spatial distribution of these changes. We force the model with time series of daily discharge derived with a spatially distributed hydrological model for pre and post HP scenarios. We initialize GSD under the assumption that coarse grains (d90) are mobilized only during mean annual maximum flows, and on the basis of ratios between d90 and characteristic diameters estimated from field measurements. Results show that effects of flow regulation vary significantly in space and in time and are grain size dependent. HP operations led to an overall reduction of sediment transport at network scale, especially in summer and for coarser grains, leading to a general coarsening of the river bed sediments at the upstream reaches. The model allows investigating the impact of modified HP operations and climate change projections on sediment dynamics at the network scale.

A hybrid deep neural network and physically based distributed model for river stage prediction

NASA Astrophysics Data System (ADS)

hitokoto, Masayuki; sakuraba, Masaaki

2016-04-01

We developed the real-time river stage prediction model, using the hybrid deep neural network and physically based distributed model. As the basic model, 4 layer feed-forward artificial neural network (ANN) was used. As a network training method, the deep learning technique was applied. To optimize the network weight, the stochastic gradient descent method based on the back propagation method was used. As a pre-training method, the denoising autoencoder was used. Input of the ANN model is hourly change of water level and hourly rainfall, output data is water level of downstream station. In general, the desirable input of the ANN has strong correlation with the output. In conceptual hydrological model such as tank model and storage-function model, river discharge is governed by the catchment storage. Therefore, the change of the catchment storage, downstream discharge subtracted from rainfall, can be the potent input candidate of the ANN model instead of rainfall. From this point of view, the hybrid deep neural network and physically based distributed model was developed. The prediction procedure of the hybrid model is as follows; first, downstream discharge was calculated by the distributed model, and then estimates the hourly change of catchment storage form rainfall and calculated discharge as the input of the ANN model, and finally the ANN model was calculated. In the training phase, hourly change of catchment storage can be calculated by the observed rainfall and discharge data. The developed model was applied to the one catchment of the OOYODO River, one of the first-grade river in Japan. The modeled catchment is 695 square km. For the training data, 5 water level gauging station and 14 rain-gauge station in the catchment was used. The training floods, superior 24 events, were selected during the period of 2005-2014. Prediction was made up to 6 hours, and 6 models were developed for each prediction time. To set the proper learning parameters and network architecture of the ANN model, sensitivity analysis was done by the case study approach. The prediction result was evaluated by the superior 4 flood events by the leave-one-out cross validation. The prediction result of the basic 4 layer ANN was better than the conventional 3 layer ANN model. However, the result did not reproduce well the biggest flood event, supposedly because the lack of the sufficient high-water level flood event in the training data. The result of the hybrid model outperforms the basic ANN model and distributed model, especially improved the performance of the basic ANN model in the biggest flood event.

The carbon commute: Effects of urbanization on dissolved organic carbon quality on a suburban New England river network

NASA Astrophysics Data System (ADS)

Balch, E.; Robison, A.; Wollheim, W. M.

2017-12-01

Understanding anthropogenic influence on the sources and fluxes of carbon is necessary for interpreting the carbon cycle and contaminant transport throughout a river system. As urbanization increases worldwide, it is critical to understand how urbanization affects the carbon cycle so that we may be able to predict future changes. Rivers act as both transporters of terrestrial dissolved organic carbon (DOC) to coastal regions, and active transformers of DOC. The character (lability) of the carbon found within a river network is influenced by its sources and fluxes, as determined by the ecological processes, land use, and discharge, which vary throughout the network. We have characterized DOC quantity and quality throughout a suburban New England river network (Ipswich River, MA) in an attempt to provide a detailed picture of how DOC quality varies within a network, and how urbanization influences these changes. We conducted a synoptic survey of 45 sites over two hydrologically similar days in the Ipswich River network in northeast Massachusetts, USA. We collected discrete grab samples for DOC quantity and quality analyses. We also collected dissolved oxygen, conductivity, and nutrients (major anions and cations) as an extension of the synoptic survey. We plan to determine the source of the DOC by using excitation-emission matrices (EEMs), and specific UV absorption (SUVA) at 254 nm. These analyses will provide us with a detailed picture of how DOC quality varies within a network, and how urbanization influences these changes. Using land use data of the Ipswich River watershed, we are able to model the changes in DOC quality throughout the network. In highly urbanized headwaters, through the progressively more forested and wetland dominated main stem reaches, we expect to see the imprint of urbanization throughout the network due to its decreased lability. Studying the imprint of urbanization on DOC throughout a river network helps us complete our understanding of freshwater carbon processes. Rivers are an important component of the global carbon balance, and monitoring the effect of urbanization on the carbon cycle in freshwater systems is integral to understanding their role in the global carbon system.

A hierarchical pyramid method for managing large-scale high-resolution drainage networks extracted from DEM

NASA Astrophysics Data System (ADS)

Bai, Rui; Tiejian, Li; Huang, Yuefei; Jiaye, Li; Wang, Guangqian; Yin, Dongqin

2015-12-01

The increasing resolution of Digital Elevation Models (DEMs) and the development of drainage network extraction algorithms make it possible to develop high-resolution drainage networks for large river basins. These vector networks contain massive numbers of river reaches with associated geographical features, including topological connections and topographical parameters. These features create challenges for efficient map display and data management. Of particular interest are the requirements of data management for multi-scale hydrological simulations using multi-resolution river networks. In this paper, a hierarchical pyramid method is proposed, which generates coarsened vector drainage networks from the originals iteratively. The method is based on the Horton-Strahler's (H-S) order schema. At each coarsening step, the river reaches with the lowest H-S order are pruned, and their related sub-basins are merged. At the same time, the topological connections and topographical parameters of each coarsened drainage network are inherited from the former level using formulas that are presented in this study. The method was applied to the original drainage networks of a watershed in the Huangfuchuan River basin extracted from a 1-m-resolution airborne LiDAR DEM and applied to the full Yangtze River basin in China, which was extracted from a 30-m-resolution ASTER GDEM. In addition, a map-display and parameter-query web service was published for the Mississippi River basin, and its data were extracted from the 30-m-resolution ASTER GDEM. The results presented in this study indicate that the developed method can effectively manage and display massive amounts of drainage network data and can facilitate multi-scale hydrological simulations.

Dynamic Hydrological Discharge Modelling for Fully Coupled Paleoclimate Runs of the Last Glacial Cycle

NASA Astrophysics Data System (ADS)

Riddick, Thomas; Brovkin, Victor; Hagemann, Stefan; Mikolajewicz, Uwe

2017-04-01

The continually evolving large ice sheets present in the Northern Hemisphere during the last glacial cycle caused significant changes to river pathways both through directly blocking rivers and through glacial isostatic adjustment. These river pathway changes are believed to of had a significant impact on the evolution of ocean circulation through changing the pattern of fresh water discharge into the oceans. A fully coupled ESM simulation of the last glacial cycle thus requires a hydrological discharge model that uses a set of river pathways that evolve with the earth's changing orography while being able to reproduce the known present-day river network given the present-day orography. Here we present a method for dynamically modelling hydrological discharge that meets such requirements by applying relative manual corrections to an evolving fine scale orography (accounting for the changing ice sheets and isostatic rebound) each time the river directions are recalculated. The corrected orography thus produced is then used to create a set of fine scale river pathways and these are then upscaled to a course scale. An existing present-day hydrological discharge model within the JSBACH3 land surface model is run using the course scale river pathways generated. This method will be used in fully coupled paleoclimate runs made using MPI-ESM1 as part of the PalMod project. Tests show this procedure reproduces the known present-day river network to a sufficient degree of accuracy.

Testing statistical self-similarity in the topology of river networks

USGS Publications Warehouse

Troutman, Brent M.; Mantilla, Ricardo; Gupta, Vijay K.

2010-01-01

Recent work has demonstrated that the topological properties of real river networks deviate significantly from predictions of Shreve's random model. At the same time the property of mean self-similarity postulated by Tokunaga's model is well supported by data. Recently, a new class of network model called random self-similar networks (RSN) that combines self-similarity and randomness has been introduced to replicate important topological features observed in real river networks. We investigate if the hypothesis of statistical self-similarity in the RSN model is supported by data on a set of 30 basins located across the continental United States that encompass a wide range of hydroclimatic variability. We demonstrate that the generators of the RSN model obey a geometric distribution, and self-similarity holds in a statistical sense in 26 of these 30 basins. The parameters describing the distribution of interior and exterior generators are tested to be statistically different and the difference is shown to produce the well-known Hack's law. The inter-basin variability of RSN parameters is found to be statistically significant. We also test generator dependence on two climatic indices, mean annual precipitation and radiative index of dryness. Some indication of climatic influence on the generators is detected, but this influence is not statistically significant with the sample size available. Finally, two key applications of the RSN model to hydrology and geomorphology are briefly discussed.

Investigating the Performance of One- and Two-dimensional Flood Models in a Channelized River Network: A Case Study of the Obion River System

NASA Astrophysics Data System (ADS)

Kalyanapu, A. J.; Dullo, T. T.; Thornton, J. C.; Auld, L. A.

2015-12-01

Obion River, is located in the northwestern Tennessee region, and discharges into the Mississippi River. In the past, the river system was largely channelized for agricultural purposes that resulted in increased erosion, loss of wildlife habitat and downstream flood risks. These impacts are now being slowly reversed mainly due to wetland restoration. The river system is characterized by a large network of "loops" around the main channels that hold water either from excess flows or due to flow diversions. Without data on each individual channel, levee, canal, or pond it is not known where the water flows from or to. In some segments along the river, the natural channel has been altered and rerouted by the farmers for their irrigation purposes. Satellite imagery can aid in identifying these features, but its spatial coverage is temporally sparse. All the alterations that have been done to the watershed make it difficult to develop hydraulic models, which could predict flooding and droughts. This is especially true when building one-dimensional (1D) hydraulic models compared to two-dimensional (2D) models, as the former cannot adequately simulate lateral flows in the floodplain and in complex terrains. The objective of this study therefore is to study the performance of 1D and 2D flood models in this complex river system, evaluate the limitations of 1D models and highlight the advantages of 2D models. The study presents the application of HEC-RAS and HEC-2D models developed by the Hydrologic Engineering Center (HEC), a division of the US Army Corps of Engineers. The broader impacts of this study is the development of best practices for developing flood models in channelized river systems and in agricultural watersheds.

Comparison of Groundwater Level Models Based on Artificial Neural Networks and ANFIS

PubMed Central

Domazet, Milka; Stricevic, Ruzica; Pocuca, Vesna; Spalevic, Velibor; Pivic, Radmila; Gregoric, Enika; Domazet, Uros

2015-01-01

Water table forecasting plays an important role in the management of groundwater resources in agricultural regions where there are drainage systems in river valleys. The results presented in this paper pertain to an area along the left bank of the Danube River, in the Province of Vojvodina, which is the northern part of Serbia. Two soft computing techniques were used in this research: an adaptive neurofuzzy inference system (ANFIS) and an artificial neural network (ANN) model for one-month water table forecasts at several wells located at different distances from the river. The results suggest that both these techniques represent useful tools for modeling hydrological processes in agriculture, with similar computing and memory capabilities, such that they constitute an exceptionally good numerical framework for generating high-quality models. PMID:26759830

Comparison of Groundwater Level Models Based on Artificial Neural Networks and ANFIS.

PubMed

Djurovic, Nevenka; Domazet, Milka; Stricevic, Ruzica; Pocuca, Vesna; Spalevic, Velibor; Pivic, Radmila; Gregoric, Enika; Domazet, Uros

2015-01-01

Water table forecasting plays an important role in the management of groundwater resources in agricultural regions where there are drainage systems in river valleys. The results presented in this paper pertain to an area along the left bank of the Danube River, in the Province of Vojvodina, which is the northern part of Serbia. Two soft computing techniques were used in this research: an adaptive neurofuzzy inference system (ANFIS) and an artificial neural network (ANN) model for one-month water table forecasts at several wells located at different distances from the river. The results suggest that both these techniques represent useful tools for modeling hydrological processes in agriculture, with similar computing and memory capabilities, such that they constitute an exceptionally good numerical framework for generating high-quality models.

Spatiotemporal interpolation of discharge across a river network by using synthetic SWOT satellite data

NASA Astrophysics Data System (ADS)

Paiva, Rodrigo C. D.; Durand, Michael T.; Hossain, Faisal

2015-01-01

Recent efforts have sought to estimate river discharge and other surface water-related quantities using spaceborne sensors, with better spatial coverage but worse temporal sampling as compared with in situ measurements. The Surface Water and Ocean Topography (SWOT) mission will provide river discharge estimates globally from space. However, questions on how to optimally use the spatially distributed but asynchronous satellite observations to generate continuous fields still exist. This paper presents a statistical model (River Kriging-RK), for estimating discharge time series in a river network in the context of the SWOT mission. RK uses discharge estimates at different locations and times to produce a continuous field using spatiotemporal kriging. A key component of RK is the space-time river discharge covariance, which was derived analytically from the diffusive wave approximation of Saint Venant's equations. The RK covariance also accounts for the loss of correlation at confluences. The model performed well in a case study on Ganges-Brahmaputra-Meghna (GBM) River system in Bangladesh using synthetic SWOT observations. The correlation model reproduced empirically derived values. RK (R2=0.83) outperformed other kriging-based methods (R2=0.80), as well as a simple time series linear interpolation (R2=0.72). RK was used to combine discharge from SWOT and in situ observations, improving estimates when the latter is included (R2=0.91). The proposed statistical concepts may eventually provide a feasible framework to estimate continuous discharge time series across a river network based on SWOT data, other altimetry missions, and/or in situ data.

How has climate change altered network connectivity in a mountain stream network?

NASA Astrophysics Data System (ADS)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.; Johnson, S.

2017-12-01

Connectivity along river networks is broadly recognized as dynamic, with seasonal and event-based expansion and contraction of the network extent. Intermittently flowing streams are particularly important as they define a crucial threshold for continuously connected waters that enable migration by aquatic species. In the Pacific northwestern U.S., changes in atmospheric circulation have been found to alter rainfall patterns and result in decreased summer low-flows in the region. However, the impact of this climate dynamic on network connectivity is heretofore unstudied. Thus, we ask: How has connectivity in the riparian corridor changed in response to observed changes in climate? In this study we take the well-studied H.J. Andrews Experimental Forest as representative of mountain river networks in the Pacific northwestern U.S. First, we analyze 63 years of stream gauge information from a network of 11 gauges to document observed changes in timing and magnitude of stream discharge. We found declining magnitudes of seasonal low-flows and shifting seasonality of water export from the catchment, both of which we attribute to changes in precipitation timing and storage as snow vs. rainfall. Next, we use these discharge data to drive a reduced-complexity model of the river network to simulate network connectivity over 63 years. Model results show that network contraction (i.e., minimum network extent) has decreased over the past 63 years. Unexpectedly, the increasing winter peak flows did not correspond with increasing network expansion, suggesting a geologic control on maximum flowing network extent. We find dynamic expansion and contraction of the network primarily occurs during period of catchment discharge less than about 1 m3/s at the outlet, whereas the network extent is generally constant for discharges from 1 to 300 m3/s. Results of our study are of interest to scientists focused on connectivity as a control on ecological processes both directly (e.g., fish migration) and indirectly (e.g., stream temperature modeling). Additionally, our results inform management and regulatory needs such as estimating connectivity for entire river networks as a basis for regulation, and identifying the complexity of a shifting baseline in identifying a regulatory basis.

Fast neural network surrogates for very high dimensional physics-based models in computational oceanography.

PubMed

van der Merwe, Rudolph; Leen, Todd K; Lu, Zhengdong; Frolov, Sergey; Baptista, Antonio M

2007-05-01

We present neural network surrogates that provide extremely fast and accurate emulation of a large-scale circulation model for the coupled Columbia River, its estuary and near ocean regions. The circulation model has O(10(7)) degrees of freedom, is highly nonlinear and is driven by ocean, atmospheric and river influences at its boundaries. The surrogates provide accurate emulation of the full circulation code and run over 1000 times faster. Such fast dynamic surrogates will enable significant advances in ensemble forecasts in oceanography and weather.

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management.

PubMed

Williams, Bradley S; D'Amico, Ellen; Kastens, Jude H; Thorp, James H; Flotemersch, Joseph E; Thoms, Martin C

2013-09-01

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.

Modeling the BOD of Danube River in Serbia using spatial, temporal, and input variables optimized artificial neural network models.

PubMed

Šiljić Tomić, Aleksandra N; Antanasijević, Davor Z; Ristić, Mirjana Đ; Perić-Grujić, Aleksandra A; Pocajt, Viktor V

2016-05-01

This paper describes the application of artificial neural network models for the prediction of biological oxygen demand (BOD) levels in the Danube River. Eighteen regularly monitored water quality parameters at 17 stations on the river stretch passing through Serbia were used as input variables. The optimization of the model was performed in three consecutive steps: firstly, the spatial influence of a monitoring station was examined; secondly, the monitoring period necessary to reach satisfactory performance was determined; and lastly, correlation analysis was applied to evaluate the relationship among water quality parameters. Root-mean-square error (RMSE) was used to evaluate model performance in the first two steps, whereas in the last step, multiple statistical indicators of performance were utilized. As a result, two optimized models were developed, a general regression neural network model (labeled GRNN-1) that covers the monitoring stations from the Danube inflow to the city of Novi Sad and a GRNN model (labeled GRNN-2) that covers the stations from the city of Novi Sad to the border with Romania. Both models demonstrated good agreement between the predicted and actually observed BOD values.

A software sensor model based on hybrid fuzzy neural network for rapid estimation water quality in Guangzhou section of Pearl River, China.

PubMed

Zhou, Chunshan; Zhang, Chao; Tian, Di; Wang, Ke; Huang, Mingzhi; Liu, Yanbiao

2018-01-02

In order to manage water resources, a software sensor model was designed to estimate water quality using a hybrid fuzzy neural network (FNN) in Guangzhou section of Pearl River, China. The software sensor system was composed of data storage module, fuzzy decision-making module, neural network module and fuzzy reasoning generator module. Fuzzy subtractive clustering was employed to capture the character of model, and optimize network architecture for enhancing network performance. The results indicate that, on basis of available on-line measured variables, the software sensor model can accurately predict water quality according to the relationship between chemical oxygen demand (COD) and dissolved oxygen (DO), pH and NH 4 + -N. Owing to its ability in recognizing time series patterns and non-linear characteristics, the software sensor-based FNN is obviously superior to the traditional neural network model, and its R (correlation coefficient), MAPE (mean absolute percentage error) and RMSE (root mean square error) are 0.8931, 10.9051 and 0.4634, respectively.

Hydroclimatology of Dual-Peak Annual Cholera Incidence: Insights from a Spatially Explicit Model

NASA Astrophysics Data System (ADS)

Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

2012-12-01

Cholera incidence in some regions of the Indian subcontinent may exhibit two annual peaks although the main environmental drivers that have been linked to the disease (e.g. sea surface temperature, zooplankton abundance, river discharge) peak once per year during the summer. An empirical hydroclimatological explanation relating cholera transmission to river flows and to the disease spatial spreading has been recently proposed. We specifically support and substantiate mechanistically such hypothesis by means of a spatially explicit model of cholera transmission. Our framework directly accounts for the role of the river network in transporting and redistributing cholera bacteria among human communities as well as for spatial and temporal annual fluctuations of precipitation and river flows. To single out the single out the hydroclimatologic controls on the prevalence patterns in a non-specific geographical context, we first apply the model to Optimal Channel Networks as a general model of hydrological networks. Moreover, we impose a uniform distribution of population. The model is forced by seasonal environmental drivers, namely precipitation, temperature and chlorophyll concentration in the coastal environment, a proxy for Vibrio cholerae concentration. Our results show that these drivers may suffice to generate dual-peak cholera prevalence patterns for proper combinations of timescales involved in pathogen transport, hydrologic variability and disease unfolding. The model explains the possible occurrence of spatial patterns of cholera incidence characterized by a spring peak confined to coastal areas and a fall peak involving inland regions. We then proceed applying the model to the specific settings of Bay of Bengal accounting for the actual river networks (derived from digital terrain map manipulations), the proper distribution of population (estimated from downscaling of census data based on remotely sensed features) and precipitation patterns. Overall our modeling framework suggests insights on how environmental drivers concert the generation of complex spatiotemporal infections and proposes an explanation for the different cholera patterns (dual or single annual peaks) exhibited by regions that share similar hydroclimatological forcings.

Comparative Analysis of River Flow Modelling by Using Supervised Learning Technique

NASA Astrophysics Data System (ADS)

Ismail, Shuhaida; Mohamad Pandiahi, Siraj; Shabri, Ani; Mustapha, Aida

2018-04-01

The goal of this research is to investigate the efficiency of three supervised learning algorithms for forecasting monthly river flow of the Indus River in Pakistan, spread over 550 square miles or 1800 square kilometres. The algorithms include the Least Square Support Vector Machine (LSSVM), Artificial Neural Network (ANN) and Wavelet Regression (WR). The forecasting models predict the monthly river flow obtained from the three models individually for river flow data and the accuracy of the all models were then compared against each other. The monthly river flow of the said river has been forecasted using these three models. The obtained results were compared and statistically analysed. Then, the results of this analytical comparison showed that LSSVM model is more precise in the monthly river flow forecasting. It was found that LSSVM has he higher r with the value of 0.934 compared to other models. This indicate that LSSVM is more accurate and efficient as compared to the ANN and WR model.

Evaluation of Spatial Pattern of Altered Flow Regimes on a River Network Using a Distributed Hydrological Model

PubMed Central

Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V., Oliver C.

2015-01-01

Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov–Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities. PMID:26207997

Spatial relationships in a dendritic network: the herpetofaunal metacommunity of the Mattole River catchment of northwest California.

Treesearch

Hartwell Welsh; Garth Hodgson

2010-01-01

We investigated the aquatic and riparian herpetofauna in a 789 km² river catchment in northwest California to examine competing theories of biotic community structuring in catchment stream networks. Research in fluvial geomorphology has resulted in multi-scale models of dynamic processes that cyclically create, maintain, and destroy environments in stream...

Comprehensive model-based prediction of micropollutants from diffuse sources in the Swiss river network

NASA Astrophysics Data System (ADS)

Strahm, Ivo; Munz, Nicole; Braun, Christian; Gälli, René; Leu, Christian; Stamm, Christian

2014-05-01

Water quality in the Swiss river network is affected by many micropollutants from a variety of diffuse sources. This study compares, for the first time, in a comprehensive manner the diffuse sources and the substance groups that contribute the most to water contamination in Swiss streams and highlights the major regions for water pollution. For this a simple but comprehensive model was developed to estimate emission from diffuse sources for the entire Swiss river network of 65 000 km. Based on emission factors the model calculates catchment specific losses to streams for more than 15 diffuse sources (such as crop lands, grassland, vineyards, fruit orchards, roads, railways, facades, roofs, green space in urban areas, landfills, etc.) and more than 130 different substances from 5 different substance groups (pesticides, biocides, heavy metals, human drugs, animal drugs). For more than 180 000 stream sections estimates of mean annual pollutant loads and mean annual concentration levels were modeled. This data was validated with a set of monitoring data and evaluated based on annual average environmental quality standards (AA-EQS). Model validation showed that the estimated mean annual concentration levels are within the range of measured data. Therefore simulations were considered as adequately robust for identifying the major sources of diffuse pollution. The analysis depicted that in Switzerland widespread pollution of streams can be expected. Along more than 18 000 km of the river network one or more simulated substances has a concentration exceeding the AA-EQS. In single stream sections it could be more than 50 different substances. Moreover, the simulations showed that in two-thirds of small streams (Strahler order 1 and 2) at least one AA-EQS is always exceeded. The highest number of substances exceeding the AA-EQS are in areas with large fractions of arable cropping, vineyards and fruit orchards. Urban areas are also of concern even without considering wastewater treatment plants. Only a small number of problematic substances are expected from grassland. Landfills and roadways are insignificant within the entire Swiss river network, but may locally lead to considerable water pollution. Considering all substance groups, pesticides and some heavy metals are the main polluters. Many pesticides are expected to exceed AA-EQS and in a substantial percentage of the river network. Modeling a large number of substances from many sources and a huge quantity of stream sections is only possible with a simple model. Nevertheless conclusions are robust and may indicate where and for what kind of substance groups additional efforts for water quality improvements should be undertaken.

Estimating extreme river discharges in Europe through a Bayesian network

NASA Astrophysics Data System (ADS)

Paprotny, Dominik; Morales-Nápoles, Oswaldo

2017-06-01

Large-scale hydrological modelling of flood hazards requires adequate extreme discharge data. In practise, models based on physics are applied alongside those utilizing only statistical analysis. The former require enormous computational power, while the latter are mostly limited in accuracy and spatial coverage. In this paper we introduce an alternate, statistical approach based on Bayesian networks (BNs), a graphical model for dependent random variables. We use a non-parametric BN to describe the joint distribution of extreme discharges in European rivers and variables representing the geographical characteristics of their catchments. Annual maxima of daily discharges from more than 1800 river gauges (stations with catchment areas ranging from 1.4 to 807 000 km2) were collected, together with information on terrain, land use and local climate. The (conditional) correlations between the variables are modelled through copulas, with the dependency structure defined in the network. The results show that using this method, mean annual maxima and return periods of discharges could be estimated with an accuracy similar to existing studies using physical models for Europe and better than a comparable global statistical model. Performance of the model varies slightly between regions of Europe, but is consistent between different time periods, and remains the same in a split-sample validation. Though discharge prediction under climate change is not the main scope of this paper, the BN was applied to a large domain covering all sizes of rivers in the continent both for present and future climate, as an example. Results show substantial variation in the influence of climate change on river discharges. The model can be used to provide quick estimates of extreme discharges at any location for the purpose of obtaining input information for hydraulic modelling.

River network bedload model: a tool to investigate the impact of flow regulation on grain size distribution in a large Alpine catchment

NASA Astrophysics Data System (ADS)

Costa, Anna; Molnar, Peter

2017-04-01

Sediment transport rates along rivers and the grain size distribution (GSD) of coarse channel bed sediment are the result of the long term balance between transport capacity and sediment supply. Transport capacity, mainly a function of channel geometry and flow competence, can be altered by changes in climatic forcing as well as by human activities. In Alpine rivers it is hydropower production systems that are the main causes of modification to the transport capacity of water courses through flow regulation, leading over longer time scales to the adjustment of river bed GSDs. We developed a river network bedload transport model to evaluate the impacts of hydropower on the transfer of sediments and the GSDs of the Upper Rhône basin, a 5,200 km2 catchment located in the Swiss Alps. Many large reservoirs for hydropower production have been built along the main tributaries of the Rhône River since the 1960s, resulting in a complex system of intakes, tunnels, and pumping stations. Sediment storage behind dams and intakes, is accompanied by altered discharge due to hydropower operations, mainly higher flow in winter and lower in summer. It is expected that this change in flow regime may have resulted in different bedload transport. However, due the non-linear, threshold-based nature of the relation between discharge and sediment mobilization, the effects of changed hydraulic conditions are not easily deducible, and because observations of bedload in pre- and post-dam conditions are usually not available, a modelling approach is often necessary. In our modelling approach, the river network is conceptualized as a series of connected links (river reaches). Average geometric characteristics of each link (width, length, and slope of cross section) are extracted from digital elevation data, while surface roughness coefficients are assigned based on the GSD. Under the assumptions of rectangular prismatic cross sections and normal flow conditions, bed shear stress is estimated from available time series of daily discharge distributed along the river network. Potential bedload transport is estimated by the Wilcock and Crowe surface-based model for the entire GSD. Mass balance between transport capacity and sediment supply, applied to each individual grain size, determines the actual transport and the resulting GSD of the channel bed. Channel bed erosion is allowed through a long-term erosion rate. Sediment input from hillslopes is included as lateral sediment flux. Initial and boundary conditions are set based on available data of GSDs, while an approximation of the depth of the mobile bed is selected through sensitivity analysis. With the river network bedload model we aim to estimate the effect of flow regulation, i.e. altered transport capacity, on sediment transport and GSD of the entire Rhône river system. The model can also be applied as a tool to explore possible changes in bedload transport and channel GSDs under different discharge scenarios based, for example, on climate change projections or modified hydropower operation policies.

Open rivers: barrier removal planning and the restoration of free-flowing rivers.

PubMed

O'Hanley, Jesse R

2011-12-01

Restoration of unobstructed, free-flowing sections of river can provide considerable environmental and ecological benefits. It removes impediments to aquatic species dispersal and improves flow, sediment and nutrient transport. This, in turn, can serve to improve environmental quality and abundance of native species, not only within the river channel itself, but also within adjacent riparian, floodplain and coastal areas. In support of this effort, a generic optimization model is presented in this paper for prioritizing the removal of problematic structures, which adversely affect aquatic species dispersal and river hydrology. Its purpose is to maximize, subject to a budget, the size of the single largest section of connected river unimpeded by artificial flow and dispersal barriers. The model is designed to improve, in a holistic way, the connectivity and environmental status of a river network. Furthermore, unlike most previous prioritization methods, it is particularly well suited to meet the needs of potamodromous fish species and other resident aquatic organisms, which regularly disperse among different parts of a river network. After presenting an initial mixed integer linear programming formulation of the model, more scalable reformulation and solution techniques are investigated for solving large, realistic-sized instances. Results from a case-study of the Pike River Watershed, located in northeast Wisconsin, USA, demonstrate the computational efficiency of the proposed model as well as highlight some general insights about systematic barrier removal planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Simulation of Water Levels and Salinity in the Rivers and Tidal Marshes in the Vicinity of the Savannah National Wildlife Refuge, Coastal South Carolina and Georgia

USGS Publications Warehouse

Conrads, Paul; Roehl, Edwin A.; Daamen, Ruby C.; Kitchens, Wiley M.

2006-01-01

The Savannah Harbor is one of the busiest ports on the East Coast of the United States and is located downstream from the Savannah National Wildlife Refuge, which is one of the Nation?s largest freshwater tidal marshes. The Georgia Ports Authority and the U.S. Army Corps of Engineers funded hydrodynamic and ecological studies to evaluate the potential effects of a proposed deepening of Savannah Harbor as part of the Environmental Impact Statement. These studies included a three-dimensional (3D) model of the Savannah River estuary system, which was developed to simulate changes in water levels and salinity in the system in response to geometry changes as a result of the deepening of Savannah Harbor, and a marsh-succession model that predicts plant distribution in the tidal marshes in response to changes in the water-level and salinity conditions in the marsh. Beginning in May 2001, the U.S. Geological Survey entered into cooperative agreements with the Georgia Ports Authority to develop empirical models to simulate the water level and salinity of the rivers and tidal marshes in the vicinity of the Savannah National Wildlife Refuge and to link the 3D hydrodynamic river-estuary model and the marsh-succession model. For the development of these models, many different databases were created that describe the complexity and behaviors of the estuary. The U.S. Geological Survey has maintained a network of continuous streamflow, water-level, and specific-conductance (field measurement to compute salinity) river gages in the study area since the 1980s and a network of water-level and salinity marsh gages in the study area since 1999. The Georgia Ports Authority collected water-level and salinity data during summer 1997 and 1999 and collected continuous water-level and salinity data in the marsh and connecting tidal creeks from 1999 to 2002. Most of the databases comprise time series that differ by variable type, periods of record, measurement frequency, location, and reliability. Understanding freshwater inflows, tidal water levels, and specific conductance in the rivers and marshes is critical to enhancing the predictive capabilities of a successful marsh succession model. Data-mining techniques, including artificial neural network (ANN) models, were applied to address various needs of the ecology study and to integrate the riverine predictions from the 3D model to the marsh-succession model. ANN models were developed to simulate riverine water levels and specific conductance in the vicinity of the tidal marshes for the full range of historical conditions using data from the river gaging networks. ANN models were also developed to simulate the marsh water levels and pore-water salinities using data from the marsh gaging networks. Using the marsh ANN models, the continuous marsh network was hindcasted to be concurrent with the long-term riverine network. The hindcasted data allow ecologists to compute hydrologic parameters?such as hydroperiods and exposure frequency?to help analyze historical vegetation data. To integrate the 3D hydrodynamic model, the marsh-succession model, and various time-series databases, a decision support system (DSS) was developed to support the various needs of regulatory and scientific stakeholders. The DSS required the development of a spreadsheet application that integrates the database, 3D hydrodynamic model output, and ANN riverine and marsh models into a single package that is easy to use and can be readily disseminated. The DSS allows users to evaluate water-level and salinity response for different hydrologic conditions. Savannah River streamflows can be controlled by the user as constant flow, a percentage of historical flows, a percentile daily flow hydrograph, or as a user-specified hydrograph. The DSS can also use output from the 3D model at stream gages near the Savannah National Wildlife Refuge to simulate the effects in the tidal marshes. The DSS is distributed with a two-dimensional (

Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

USGS Publications Warehouse

Brennan, Sean R.; Torgersen, Christian E.; Hollenbeck, Jeff P.; Fernandez, Diego P.; Jensen, Carrie K; Schindler, Daniel E.

2016-01-01

A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

Metapopulation modelling of riparian tree species persistence in river networks under climate change.

PubMed

Van Looy, Kris; Piffady, Jérémy

2017-11-01

Floodplain landscapes are highly fragmented by river regulation resulting in habitat degradation and flood regime perturbation, posing risks to population persistence. Climate change is expected to pose supplementary risks in this context of fragmented landscapes, and especially for river systems adaptation management programs are developed. The association of habitat quality and quantity with the landscape dynamics and resilience to human-induced disturbances is still poorly understood in the context of species survival and colonization processes, but essential to prioritize conservation and restoration actions. We present a modelling approach that elucidates network connectivity and landscape dynamics in spatial and temporal context to identify vital corridors and conservation priorities in the Loire river and its tributaries. Alteration of flooding and flow regimes is believed to be critical to population dynamics in river ecosystems. Still, little is known of critical levels of alteration both spatially and temporally. We applied metapopulation modelling approaches for a dispersal-limited tree species, white elm; and a recruitment-limited tree species, black poplar. In different model steps the connectivity and natural dynamics of the river landscape are confronted with physical alterations (dams/dykes) to species survival and then future scenarios for climatic changes and potential adaptation measures are entered in the model and translated in population persistence over the river basin. For the two tree species we highlighted crucial network zones in relation to habitat quality and connectivity. Where the human impact model already shows currently restricted metapopulation development, climate change is projected to aggravate this persistence perspective substantially. For both species a significant drawback to the basin population is observed, with 1/3 for elm and ¼ for poplar after 25 years already. But proposed adaptation measures prove effective to even bring metapopulation strength and persistence up to a level above the current level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial Statistical Network Models for Stream and River Temperatures in the Chesapeake Bay Watershed

EPA Science Inventory

Numerous metrics have been proposed to describe stream/river thermal regimes, and researchers are still struggling with the need to describe thermal regimes in a parsimonious fashion. Regional temperature models are needed for characterizing and mapping current stream thermal re...

Spatial statistical network models for stream and river temperature in New England, USA

EPA Science Inventory

Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May–September growing ...

Study of ecological compensation in complex river networks based on a mathematical model.

PubMed

Wang, Xiao; Shen, Chunqi; Wei, Jun; Niu, Yong

2018-05-31

Transboundary water pollution has resulted in increasing conflicts between upstream and downstream administrative districts. Ecological compensation is an efficient means of restricting pollutant discharge and achieving sustainable utilization of water resources. The tri-provincial region of Taihu Basin is a typical river networks area. Pollutant flux across provincial boundaries in the Taihu Basin is hard to determine due to complex hydrologic and hydrodynamic conditions. In this study, ecological compensation estimation for the tri-provincial area based on a mathematical model is investigated for better environmental management. River discharge and water quality are predicted with the one-dimensional mathematical model and validated with field measurements. Different ecological compensation criteria are identified considering the notable regional discrepancy in sewage treatment costs. Finally, the total compensation payment is estimated. Our study indicates that Shanghai should be the receiver of payment from both Jiangsu and Zhenjiang in 2013, with 305 million and 300 million CNY, respectively. Zhejiang also contributes more pollutants to Jiangsu, and the compensation to Jiangsu is estimated as 9.3 million CNY. The proposed ecological compensation method provides an efficient way for solving the transboundary conflicts in a complex river networks area and is instructive for future policy-making.

Prediction of dissolved oxygen concentration in hypoxic river systems using support vector machine: a case study of Wen-Rui Tang River, China.

PubMed

Ji, Xiaoliang; Shang, Xu; Dahlgren, Randy A; Zhang, Minghua

2017-07-01

Accurate quantification of dissolved oxygen (DO) is critically important for managing water resources and controlling pollution. Artificial intelligence (AI) models have been successfully applied for modeling DO content in aquatic ecosystems with limited data. However, the efficacy of these AI models in predicting DO levels in the hypoxic river systems having multiple pollution sources and complicated pollutants behaviors is unclear. Given this dilemma, we developed a promising AI model, known as support vector machine (SVM), to predict the DO concentration in a hypoxic river in southeastern China. Four different calibration models, specifically, multiple linear regression, back propagation neural network, general regression neural network, and SVM, were established, and their prediction accuracy was systemically investigated and compared. A total of 11 hydro-chemical variables were used as model inputs. These variables were measured bimonthly at eight sampling sites along the rural-suburban-urban portion of Wen-Rui Tang River from 2004 to 2008. The performances of the established models were assessed through the mean square error (MSE), determination coefficient (R 2 ), and Nash-Sutcliffe (NS) model efficiency. The results indicated that the SVM model was superior to other models in predicting DO concentration in Wen-Rui Tang River. For SVM, the MSE, R 2 , and NS values for the testing subset were 0.9416 mg/L, 0.8646, and 0.8763, respectively. Sensitivity analysis showed that ammonium-nitrogen was the most significant input variable of the proposal SVM model. Overall, these results demonstrated that the proposed SVM model can efficiently predict water quality, especially for highly impaired and hypoxic river systems.

A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain region

NASA Astrophysics Data System (ADS)

He, Zhibin; Wen, Xiaohu; Liu, Hu; Du, Jun

2014-02-01

Data driven models are very useful for river flow forecasting when the underlying physical relationships are not fully understand, but it is not clear whether these data driven models still have a good performance in the small river basin of semiarid mountain regions where have complicated topography. In this study, the potential of three different data driven methods, artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for forecasting river flow in the semiarid mountain region, northwestern China. The models analyzed different combinations of antecedent river flow values and the appropriate input vector has been selected based on the analysis of residuals. The performance of the ANN, ANFIS and SVM models in training and validation sets are compared with the observed data. The model which consists of three antecedent values of flow has been selected as the best fit model for river flow forecasting. To get more accurate evaluation of the results of ANN, ANFIS and SVM models, the four quantitative standard statistical performance evaluation measures, the coefficient of correlation (R), root mean squared error (RMSE), Nash-Sutcliffe efficiency coefficient (NS) and mean absolute relative error (MARE), were employed to evaluate the performances of various models developed. The results indicate that the performance obtained by ANN, ANFIS and SVM in terms of different evaluation criteria during the training and validation period does not vary substantially; the performance of the ANN, ANFIS and SVM models in river flow forecasting was satisfactory. A detailed comparison of the overall performance indicated that the SVM model performed better than ANN and ANFIS in river flow forecasting for the validation data sets. The results also suggest that ANN, ANFIS and SVM method can be successfully applied to establish river flow with complicated topography forecasting models in the semiarid mountain regions.

Impact assessments of water allocation on water environment of river network: Method and application

NASA Astrophysics Data System (ADS)

Wang, Qinggai; Wang, Yaping; Lu, Xuchuan; Jia, Peng; Zhang, Beibei; Li, Chen; Li, Sa; Li, Shibei

2018-02-01

Two types of water allocation scenarios were proposed for reasonably utilizing water resources and improving water quality in a two-river network in Tongzhou District. Water circulation and quality were selected as two important indexes to evaluate the two scenario. Meanwhile, one-dimensional water amount and quality model was set up on the basis of the MIKE11 model to compare the two scenarios in terms of improving water environment. The results showed that both scenarios changed the hydrodynamic conditions, and consequently the river flow reached 0.05 m/s or higher in the central part of river stream. In addition, we also found that the two plans have similar effects on water quality, with first scenario producing larger area of water class III and IV than the second scenario.

Using a novel flood prediction model and GIS automation to measure the valley and channel morphology of large river networks

EPA Science Inventory

Traditional methods for measuring river valley and channel morphology require intensive ground-based surveys which are often expensive, time consuming, and logistically difficult to implement. The number of surveys required to assess the hydrogeomorphic structure of large river n...

A network model to help land managers predict and prevent spread of invasive plants from roads to river systems in Alaska

Treesearch

Matthew J. Macander; Tricia L. Wurtz

2007-01-01

Alaska has relatively few invasive plants, and most of them are found only along the state's limited road system. Melilotus alba, or sweetclover, is one of the most widely distributed invasives in the state. Melilotus has recently moved from roadsides to the flood plains of at least three glacial rivers. We developed a network...

Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling

NASA Astrophysics Data System (ADS)

Chen, Huili; Liang, Qiuhua; Liu, Yong; Xie, Shuguang

2018-04-01

Digital Elevation Model (DEM) is one of the most important controlling factors determining the simulation accuracy of hydraulic models. However, the currently available global topographic data is confronted with limitations for application in 2-D hydraulic modeling, mainly due to the existence of vegetation bias, random errors and insufficient spatial resolution. A hydraulic correction method (HCM) for the SRTM DEM is proposed in this study to improve modeling accuracy. Firstly, we employ the global vegetation corrected DEM (i.e. Bare-Earth DEM), developed from the SRTM DEM to include both vegetation height and SRTM vegetation signal. Then, a newly released DEM, removing both vegetation bias and random errors (i.e. Multi-Error Removed DEM), is employed to overcome the limitation of height errors. Last, an approach to correct the Multi-Error Removed DEM is presented to account for the insufficiency of spatial resolution, ensuring flow connectivity of the river networks. The approach involves: (a) extracting river networks from the Multi-Error Removed DEM using an automated algorithm in ArcGIS; (b) correcting the location and layout of extracted streams with the aid of Google Earth platform and Remote Sensing imagery; and (c) removing the positive biases of the raised segment in the river networks based on bed slope to generate the hydraulically corrected DEM. The proposed HCM utilizes easily available data and tools to improve the flow connectivity of river networks without manual adjustment. To demonstrate the advantages of HCM, an extreme flood event in Huifa River Basin (China) is simulated on the original DEM, Bare-Earth DEM, Multi-Error removed DEM, and hydraulically corrected DEM using an integrated hydrologic-hydraulic model. A comparative analysis is subsequently performed to assess the simulation accuracy and performance of four different DEMs and favorable results have been obtained on the corrected DEM.

Support vector machine-an alternative to artificial neuron network for water quality forecasting in an agricultural nonpoint source polluted river?

PubMed

Liu, Mei; Lu, Jun

2014-09-01

Water quality forecasting in agricultural drainage river basins is difficult because of the complicated nonpoint source (NPS) pollution transport processes and river self-purification processes involved in highly nonlinear problems. Artificial neural network (ANN) and support vector model (SVM) were developed to predict total nitrogen (TN) and total phosphorus (TP) concentrations for any location of the river polluted by agricultural NPS pollution in eastern China. River flow, water temperature, flow travel time, rainfall, dissolved oxygen, and upstream TN or TP concentrations were selected as initial inputs of the two models. Monthly, bimonthly, and trimonthly datasets were selected to train the two models, respectively, and the same monthly dataset which had not been used for training was chosen to test the models in order to compare their generalization performance. Trial and error analysis and genetic algorisms (GA) were employed to optimize the parameters of ANN and SVM models, respectively. The results indicated that the proposed SVM models performed better generalization ability due to avoiding the occurrence of overtraining and optimizing fewer parameters based on structural risk minimization (SRM) principle. Furthermore, both TN and TP SVM models trained by trimonthly datasets achieved greater forecasting accuracy than corresponding ANN models. Thus, SVM models will be a powerful alternative method because it is an efficient and economic tool to accurately predict water quality with low risk. The sensitivity analyses of two models indicated that decreasing upstream input concentrations during the dry season and NPS emission along the reach during average or flood season should be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data and even trimonthly data are available, the SVM methodology developed here can easily be applied to other NPS-polluted rivers.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change

USGS Publications Warehouse

Elliott, Caroline M.; Jacobson, Robert B.; Freeman, Mary C.

2014-01-01

A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia. The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling. The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the benefit of hydrological, soil erosion, and coarser ecological modeling. Reach attributes are summarized for each segment. In six subbasins segments are assigned additional attributes about barriers (usually impoundments) to fish migration and stream isolation. Segments in the six sub-basins are also attributed with percent urban area for the watershed upstream from the stream segment for each decade from 2010–2100 from models of urban growth. On a broader scale, for application in a coarse-scale species-response model, the stream-network information is aggregated and summarized by 256 drainage subbasins (Hydrologic Response Units) used for watershed hydrologic and stream-temperature models. A model of soil erodibility based on the Revised Universal Soil Loss Equation also was developed at this scale to parameterize a model to evaluate stream condition. The reach-scale network was classified using multivariate clustering based on modeled channel width, valley width, and mean reach gradient as variables. The resulting classification consists of a 6-cluster and a 12-cluster classification for every reach in the Apalachicola-Chattahoochee-Flint Basin. We present an example of the utility of the classification that was tested using the occurrence of two species of darters and two species of minnows in the Apalachicola-Chattahoochee-Flint River Basin, the blackbanded darter and Halloween darter, and the bluestripe shiner and blacktail shiner.

Rainfall-Runoff Parameters Uncertainity

NASA Astrophysics Data System (ADS)

Heidari, A.; Saghafian, B.; Maknoon, R.

2003-04-01

Karkheh river basin, located in southwest of Iran, drains an area of over 40000 km2 and is considered a flood active basin. A flood forecasting system is under development for the basin, which consists of a rainfall-runoff model, a river routing model, a reservior simulation model, and a real time data gathering and processing module. SCS, Clark synthetic unit hydrograph, and Modclark methods are the main subbasin rainfall-runoff transformation options included in the rainfall-runoff model. Infiltration schemes, such as exponentioal and SCS-CN methods, account for infiltration losses. Simulation of snow melt is based on degree day approach. River flood routing is performed by FLDWAV model based on one-dimensional full dynamic equation. Calibration and validation of the rainfall-runoff model on Karkheh subbasins are ongoing while the river routing model awaits cross section surveys.Real time hydrometeological data are collected by a telemetry network. The telemetry network is equipped with automatic sensors and INMARSAT-C comunication system. A geographic information system (GIS) stores and manages the spatial data while a database holds the hydroclimatological historical and updated time series. Rainfall runoff parameters uncertainty is analyzed by Monte Carlo and GLUE approaches.

Delta-Flux: An eddy covariance network for a climate-smart lower Mississippi basin

USDA-ARS?s Scientific Manuscript database

Networks of remotely monitored research sites are increasingly the model used to study regional agricultural impacts on carbon and water fluxes. However, key national networks such as the National Ecological Observatory Network and Ameriflux lack contributions from the Lower Mississippi River Basin ...

A deterministic width function model

NASA Astrophysics Data System (ADS)

Puente, C. E.; Sivakumar, B.

Use of a deterministic fractal-multifractal (FM) geometric method to model width functions of natural river networks, as derived distributions of simple multifractal measures via fractal interpolating functions, is reported. It is first demonstrated that the FM procedure may be used to simulate natural width functions, preserving their most relevant features like their overall shape and texture and their observed power-law scaling on their power spectra. It is then shown, via two natural river networks (Racoon and Brushy creeks in the United States), that the FM approach may also be used to closely approximate existing width functions.

An Application of Data Mining Techniques for Flood Forecasting: Application in Rivers Daya and Bhargavi, India

NASA Astrophysics Data System (ADS)

Panigrahi, Binay Kumar; Das, Soumya; Nath, Tushar Kumar; Senapati, Manas Ranjan

2018-05-01

In the present study, with a view to speculate the water flow of two rivers in eastern India namely river Daya and river Bhargavi, the focus was on developing Cascaded Functional Link Artificial Neural Network (C-FLANN) model. Parameters of C-FLANN architecture were updated using Harmony Search (HS) and Differential Evolution (DE). As the numbers of samples are very low, there is a risk of over fitting. To avoid this Map reduce based ANOVA technique is used to select important features. These features were used and provided to the architecture which is used to predict the water flow in both the rivers, one day, one week and two weeks ahead. The results of both the techniques were compared with Radial Basis Functional Neural Network (RBFNN) and Multilayer Perceptron (MLP), two widely used artificial neural network for prediction. From the result it was confirmed that C-FLANN trained through HS gives better prediction result than being trained through DE or RBFNN or MLP and can be used for predicting water flow in different rivers.

Temporal and spatial distribution of isotopes in river water in Central Europe: 50 years experience with the Austrian network of isotopes in rivers.

PubMed

Rank, Dieter; Wyhlidal, Stefan; Schott, Katharina; Weigand, Silvia; Oblin, Armin

2018-05-01

The Austrian network of isotopes in rivers comprises about 15 sampling locations and has been operated since 1976. The Danube isotope time series goes back to 1963. The isotopic composition of river water in Central Europe is mainly governed by the isotopic composition of precipitation in the catchment area; evaporation effects play only a minor role. Short-term and long-term isotope signals in precipitation are thus transmitted through the whole catchment. The influence of climatic changes has become observable in the long-term stable isotope time series of precipitation and surface waters. Environmental 3 H values were around 8 TU in 2015, short-term 3 H pulses up to about 80 TU in the rivers Danube and March were a consequence of releases from nuclear power plants. The complete isotope data series of this network will be included in the Global Network of Isotopes in Rivers database of the International Atomic Energy Agency (IAEA) in 2017. This article comprises a review of 50 years isotope monitoring on rivers and is also intended to provide base information on the (isotope-)hydrological conditions in Central Europe specifically for the end-users of these data, e.g. for modelling hydrological processes. Furthermore, this paper includes the 2006-2015 supplement adding to the Danube isotope set published earlier.

Multi-model ensemble hydrological simulation using a BP Neural Network for the upper Yalongjiang River Basin, China

NASA Astrophysics Data System (ADS)

Li, Zhanjie; Yu, Jingshan; Xu, Xinyi; Sun, Wenchao; Pang, Bo; Yue, Jiajia

2018-06-01

Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.

EFDC1D - A ONE DIMENSIONAL HYDRODYNAMIC AND SEDIMENT TRANSPORT MODEL FOR RIVER AND STREAM NETWORKS: MODEL THEORY AND USERS GUIDE

EPA Science Inventory

This technical report describes the new one-dimensional (1D) hydrodynamic and sediment transport model EFDC1D. This model that can be applied to stream networks. The model code and two sample data sets are included on the distribution CD. EFDC1D can simulate bi-directional unstea...

Hourly runoff forecasting for flood risk management: Application of various computational intelligence models

NASA Astrophysics Data System (ADS)

Badrzadeh, Honey; Sarukkalige, Ranjan; Jayawardena, A. W.

2015-10-01

Reliable river flow forecasts play a key role in flood risk mitigation. Among different approaches of river flow forecasting, data driven approaches have become increasingly popular in recent years due to their minimum information requirements and ability to simulate nonlinear and non-stationary characteristics of hydrological processes. In this study, attempts are made to apply four different types of data driven approaches, namely traditional artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), wavelet neural networks (WNN), and, hybrid ANFIS with multi resolution analysis using wavelets (WNF). Developed models applied for real time flood forecasting at Casino station on Richmond River, Australia which is highly prone to flooding. Hourly rainfall and runoff data were used to drive the models which have been used for forecasting with 1, 6, 12, 24, 36 and 48 h lead-time. The performance of models further improved by adding an upstream river flow data (Wiangaree station), as another effective input. All models perform satisfactorily up to 12 h lead-time. However, the hybrid wavelet-based models significantly outperforming the ANFIS and ANN models in the longer lead-time forecasting. The results confirm the robustness of the proposed structure of the hybrid models for real time runoff forecasting in the study area.

Simulation of stream discharge and transport of nitrate and selected herbicides in the Mississippi River Basin

USGS Publications Warehouse

Broshears, R.E.; Clark, G.M.; Jobson, H.E.

2001-01-01

Stream discharge and the transport of nitrate, atrazine, and metolachlor in the Mississippi River Basin were simulated using the DAFLOW/BLTM hydrologic model. The simulated domain for stream discharge included river reaches downstream from the following stations in the National Stream Quality Accounting Network: Mississippi River at Clinton, IA; Missouri River at Hermann, MO: Ohio River at Grand Chain, IL: And Arkansas River at Little Rock, AR. Coefficients of hydraulic geometry were calibrated using data from water year 1996; the model was validated by favourable simulation of observed discharges in water years 1992-1994. The transport of nitrate, atrazine, and metolachlor was simulated downstream from the Mississippi River at Thebes, IL, and the Ohio River at Grand Chain. Simulated concentrations compared favourably with observed concentrations at Baton Rouge, LA. Development of this model is a preliminary step in gaining a more quantitative understanding of the sources and fate of nutrients and pesticides delivered from the Mississippi River Basin to the Gulf of Mexico.

Artificial neural network modeling of the water quality index using land use areas as predictors.

PubMed

Gazzaz, Nabeel M; Yusoff, Mohd Kamil; Ramli, Mohammad Firuz; Juahir, Hafizan; Aris, Ahmad Zaharin

2015-02-01

This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management.

Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta

NASA Astrophysics Data System (ADS)

Zeng, Y.

2017-09-01

Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

The Influence of Water Conservancy Projects on River Network Connectivity, A Case of Luanhe River Basin

NASA Astrophysics Data System (ADS)

Li, Z.; Li, C.

2017-12-01

Connectivity is one of the most important characteristics of a river, which is derived from the natural water cycle and determine the renewability of river water. The water conservancy project can change the connectivity of natural river networks, and directly threaten the health and stability of the river ecosystem. Based on the method of Dendritic Connectivity Index (DCI), the impacts from sluices and dams on the connectivity of river network are deeply discussed herein. DCI quantitatively evaluate the connectivity of river networks based on the number of water conservancy facilities, the connectivity of fish and geographical location. The results show that the number of water conservancy facilities and their location in the river basin have a great influence on the connectivity of the river network. With the increase of the number of sluices and dams, DCI is decreasing gradually, but its decreasing range is becoming smaller and smaller. The dam located in the middle of the river network cuts the upper and lower parts of the whole river network, and destroys the connectivity of the river network more seriously. Therefore, this method can be widely applied to the comparison of different alternatives during planning of river basins and then provide a reference for the site selection and design of the water conservancy project and facility concerned.

Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China.

PubMed

Wen, Xiaohu; Fang, Jing; Diao, Meina; Zhang, Chuanqi

2013-05-01

Identification and quantification of dissolved oxygen (DO) profiles of river is one of the primary concerns for water resources managers. In this research, an artificial neural network (ANN) was developed to simulate the DO concentrations in the Heihe River, Northwestern China. A three-layer back-propagation ANN was used with the Bayesian regularization training algorithm. The input variables of the neural network were pH, electrical conductivity, chloride (Cl(-)), calcium (Ca(2+)), total alkalinity, total hardness, nitrate nitrogen (NO3-N), and ammonical nitrogen (NH4-N). The ANN structure with 14 hidden neurons obtained the best selection. By making comparison between the results of the ANN model and the measured data on the basis of correlation coefficient (r) and root mean square error (RMSE), a good model-fitting DO values indicated the effectiveness of neural network model. It is found that the coefficient of correlation (r) values for the training, validation, and test sets were 0.9654, 0.9841, and 0.9680, respectively, and the respective values of RMSE for the training, validation, and test sets were 0.4272, 0.3667, and 0.4570, respectively. Sensitivity analysis was used to determine the influence of input variables on the dependent variable. The most effective inputs were determined as pH, NO3-N, NH4-N, and Ca(2+). Cl(-) was found to be least effective variables on the proposed model. The identified ANN model can be used to simulate the water quality parameters.

Watershed Education for Sustainable Development.

ERIC Educational Resources Information Center

Stapp, William B.

2000-01-01

Presents information on the Global Rivers Environmental Education Network (GREEN), which is a global communication system for analyzing watershed usage and monitoring the quality and quantity of river water. Describes GREEN's watershed educational model and strategies and international development. (Contains 67 references.) (Author/YDS)

Fine-resolution Modeling of Urban-Energy Systems' Water Footprint in River Networks

NASA Astrophysics Data System (ADS)

McManamay, R.; Surendran Nair, S.; Morton, A.; DeRolph, C.; Stewart, R.

2015-12-01

Characterizing the interplay between urbanization, energy production, and water resources is essential for ensuring sustainable population growth. In order to balance limited water supplies, competing users must account for their realized and virtual water footprint, i.e. the total direct and indirect amount of water used, respectively. Unfortunately, publicly reported US water use estimates are spatially coarse, temporally static, and completely ignore returns of water to rivers after use. These estimates are insufficient to account for the high spatial and temporal heterogeneity of water budgets in urbanizing systems. Likewise, urbanizing areas are supported by competing sources of energy production, which also have heterogeneous water footprints. Hence, a fundamental challenge of planning for sustainable urban growth and decision-making across disparate policy sectors lies in characterizing inter-dependencies among urban systems, energy producers, and water resources. A modeling framework is presented that provides a novel approach to integrate urban-energy infrastructure into a spatial accounting network that accurately measures water footprints as changes in the quantity and quality of river flows. River networks (RNs), i.e. networks of branching tributaries nested within larger rivers, provide a spatial structure to measure water budgets by modeling hydrology and accounting for use and returns from urbanizing areas and energy producers. We quantify urban-energy water footprints for Atlanta, GA and Knoxville, TN (USA) based on changes in hydrology in RNs. Although water intakes providing supply to metropolitan areas were proximate to metropolitan areas, power plants contributing to energy demand in Knoxville and Atlanta, occurred 30 and 90km outside the metropolitan boundary, respectively. Direct water footprints from urban landcover primarily comprised smaller streams whereas indirect footprints from water supply reservoirs and energy producers included larger river systems. By using projections in urban populations for 2030 and 2050, we estimated scenarios of expansion in water footprints depending on urban growth policies and energy production technology. We provide examples of how this framework can be used to minimize water footprints and impacts to aquatic biodiversity.

Geocode of River Networks in Global Plateaus

NASA Astrophysics Data System (ADS)

Ni, J.; Wang, Y.; Wang, T.

2017-12-01

As typical hierarchical systems, river networks are of great significance to aquatic organisms and its diversity. Different aspects of river networks have been investigated in previous studies such as network structure, formation cause, material transport, nutrient cycle and habitat variation. Nevertheless, river networks function as biological habitat is far from satisfactory in plateau areas. This paper presents a hierarchical method for habitat characterization of plateau river networks with the geocode extracted from abiotic factors including historical geologic period, climate zone, water source and geomorphic process at different spatial scales. As results, characteristics of biological response with vertical differentiation within typical plateau river networks are elucidated. Altitude, climate and landform are of great influence to habitat and thereby structure of aquatic community, while diverse water source and exogenic action would influence biological abundance or spatiotemporal distribution. Case studies are made in the main stream of the Yellow River and the Yangtze River, respectively extended to the river source to Qinghai-Tibet Plateau, which demonstrate high potentials for decision making support to river protection, ecological rehabilitation and sustainable management of river ecosystems.

Tidal impact on the division of river discharge over distributary channels in the Mahakam Delta

NASA Astrophysics Data System (ADS)

Sassi, Maximiliano G.; Hoitink, A. J. F.; de Brye, Benjamin; Vermeulen, Bart; Deleersnijder, Eric

2011-12-01

Bifurcations in tidally influenced deltas distribute river discharge over downstream channels, asserting a strong control over terrestrial runoff to the coastal ocean. Whereas the mechanics of river bifurcations is well-understood, junctions in tidal channels have received comparatively little attention in the literature. This paper aims to quantify the tidal impact on subtidal discharge distribution at the bifurcations in the Mahakam Delta, East Kalimantan, Indonesia. The Mahakam Delta is a regular fan-shaped delta, composed of a quasi-symmetric network of rectilinear distributaries and sinuous tidal channels. A depth-averaged version of the unstructured-mesh, finite-element model second-generation Louvain-la-Neuve Ice-ocean Model has been used to simulate the hydrodynamics driven by river discharge and tides in the delta channel network. The model was forced with tides at open sea boundaries and with measured and modeled river discharge at upstream locations. Calibration was performed with water level time series and flow measurements, both spanning a simulation period. Validation was performed by comparing the model results with discharge measurements at the two principal bifurcations in the delta. Results indicate that within 10 to 15 km from the delta apex, the tides alter the river discharge division by about 10% in all bifurcations. The tidal impact increases seaward, with a maximum value of the order of 30%. In general, the effect of tides is to hamper the discharge division that would occur in the case without tides.

WASP Model Tutorials

EPA Pesticide Factsheets

Contains WASP tutorial videos. WASP Command Line, WASP, Modeling Dissolved Oxygen, Building a Steady State Example, Modeling Nutrients in Rivers, Nutrient Cycles, Interpreting Water Quality Models, Linking with LSPC, WRDB, BASINS, WCS, WASP Network Tool

Sensitivity of New England Stream Temperatures to Air Temperature and Precipitation Under Projected Climate

NASA Astrophysics Data System (ADS)

Huang, T.; Samal, N. R.; Wollheim, W. M.; Stewart, R. J.; Zuidema, S.; Prousevitch, A.; Glidden, S.

2015-12-01

The thermal response of streams and rivers to changing climate will influence aquatic habitat. This study examines the impact that changing climate has on stream temperatures in the Merrimack River, NH/MA USA using the Framework for Aquatic Modeling in the Earth System (FrAMES), a spatially distributed river network model driven by air temperature, air humidity, wind speed, precipitation, and solar radiation. Streamflow and water temperatures are simulated at a 45-second (latitude x longitude) river grid resolution for 135 years under historical and projected climate variability. Contemporary streamflow (Nash-Sutcliffe Coefficient = 0.77) and river temperatures (Nash-Sutcliffe Coefficient = 0.89) matched at downstream USGS gauge data well. A suite of model runs were made in combination with uniformly increased daily summer air temperatures by 2oC, 4 oC and 6 oC as well as adjusted precipitation by -40%, -30%, -20%, -10% and +10% as a sensitivity analysis to explore a broad range of potential future climates. We analyzed the summer stream temperatures and the percent of river length unsuitable for cold to warm water fish habitats. Impacts are greatest in large rivers due to the accumulation of river temperature warming throughout the entire river network. Cold water fish (i.e. brook trout) are most strongly affected while, warm water fish (i.e. largemouth bass) aren't expected to be impacted. The changes in stream temperatures under various potential climate scenarios will provide a better understanding of the specific impact that air temperature and precipitation have on aquatic thermal regimes and habitat.

Risk Assessment and Mapping of Fecal Contamination in the Ohio River Basin

NASA Astrophysics Data System (ADS)

Cabezas, A.; Morehead, D.; Teklitz, A.; Yeghiazarian, L.

2014-12-01

Decisions in many problems in engineering planning are invariably made under conditions of uncertainty imposed by the inherent randomness of natural phenomena. Water quality is one such problem. For example, the leading cause of surface-water impairment in the US is fecal microbial contamination, which can potentially trigger massive outbreaks of gastrointestinal disease. It is well known that the difficulty in prediction of water contamination is rooted in the stochastic variability of microbes in the environment, and in the complexity of environmental systems.To address these issues, we employ a risk-based design format to compute the variability in microbial concentrations and the probability of exceeding the E. Coli target in the Ohio River Basin (ORB). This probability is then mapped onto the basin's stream network within the ArcGIS environment. We demonstrate how spatial risk maps can be used in support of watershed management decisions, in particular in the assessment of best management practices for reduction of E. Coli load in surface water. The modeling environment selected for the analysis is the Schematic Processor (SP), a suite of geoprocessing ArcGIS tools. SP operates on a schematic, link-and-node network model of the watershed. The National Hydrography Dataset (NHD) is used as the basis for this representation, as it provides the stream network, lakes, and catchment definitions. Given the schematic network of the watershed, SP adds the capability to perform mathematical computations along the links and at the nodes. This enables modeling fate and transport of any entity over the network. Data from various sources have been integrated for this analysis. Catchment boundaries, lake locations, the stream network and flow data have been retrieved from the NHDPlus. Land use data come from the National Land Cover Database (NLCD), and microbial observations data from the Ohio River Sanitation Committee. The latter dataset is a result of a 2003-2007 longitudinal study. Samples for E. coli analysis were collected approximately every five miles along the entire length of the Ohio River, with additional samples collected at the mouths of over 125 direct tributaries to the Ohio River.

Regulation causes nitrogen cycling discontinuities in Mediterranean rivers.

PubMed

von Schiller, Daniel; Aristi, Ibon; Ponsatí, Lídia; Arroita, Maite; Acuña, Vicenç; Elosegi, Arturo; Sabater, Sergi

2016-01-01

River regulation has fundamentally altered large sections of the world's river networks. The effects of dams on the structural properties of downstream reaches are well documented, but less is known about their effect on river ecosystem processes. We investigated the effect of dams on river nutrient cycling by comparing net uptake of total dissolved nitrogen (TDN), phosphorus (TDP) and organic carbon (DOC) in river reaches located upstream and downstream from three reservoir systems in the Ebro River basin (NE Iberian Peninsula). Increased hydromorphological stability, organic matter standing stocks and ecosystem metabolism below dams enhanced the whole-reach net uptake of TDN, but not that of TDP or DOC. Upstream from dams, river reaches tended to be at biogeochemical equilibrium (uptake≈release) for all nutrients, whereas river reaches below dams acted as net sinks of TDN. Overall, our results suggest that flow regulation by dams may cause relevant N cycling discontinuities in rivers. Higher net N uptake capacity below dams could lead to reduced N export to downstream ecosystems. Incorporating these discontinuities could significantly improve predictive models of N cycling and transport in complex river networks. Copyright © 2015. Published by Elsevier B.V.

A linked spatial and temporal model of the chemical and biological status of a large, acid-sensitive river network.

PubMed

Evans, Chris D; Cooper, David M; Juggins, Steve; Jenkins, Alan; Norris, Dave

2006-07-15

Freshwater sensitivity to acidification varies according to geology, soils and land-use, and consequently it remains difficult to quantify the current extent of acidification, or its biological impacts, based on limited spot samples. The problem is particularly acute for river systems, where the transition from acid to circum-neutral conditions can occur within short distances. This paper links an established point-based long-term acidification model (MAGIC) with a landscape-based mixing model (PEARLS) to simulate spatial and temporal variations in acidification for a 256 km(2) catchment in North Wales. Empirical relationships are used to predict changes in the probability of occurrence of an indicator invertebrate species, Baetis rhodani, across the catchment as a function of changing chemical status. Results suggest that, at present, 27% of the river network has a mean acid neutralising capacity (ANC) below a biologically-relevant threshold of 20 microeq l(-1). At high flows, this proportion increases to 45%. The model suggests that only around 16% of the stream network had a mean ANC < 20 microeq l(-1) in 1850, but that this increased to 42% at the sulphur deposition peak around 1970. By 2050 recovery is predicted, but with some persistence of acid conditions in the most sensitive, peaty headwaters. Stream chemical suitability for Baetis rhodani is also expected to increase in formerly acidified areas, but for overall abundance to remain below that simulated in 1850. The approach of linking plot-scale process-based models to catchment mixing models provides a potential means of predicting the past and future spatial extent of acidification within large, heterogeneous river networks and regions. Further development of ecological response models to include other chemical predictor variables and the effects of acid episodes would allow more realistic simulation of the temporal and spatial dynamics of ecosystem recovery from acidification.

Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.

PubMed

Chaumot, Arnaud; Charles, Sandrine; Flammarion, Patrick; Auger, Pierre

2003-05-01

We developed a multiregion matrix population model to explore how the demography of a hypothetical brown trout population living in a river network varies in response to different spatial scenarios of cadmium contamination. Age structure, spatial distribution, and demographic and migration processes are taken into account in the model. Chronic or acute cadmium concentrations affect the demographic parameters at the scale of the river range. The outputs of the model constitute population-level end points (the asymptotic population growth rate, the stable age structure, and the asymptotic spatial distribution) that allow comparing the different spatial scenarios of contamination regarding the demographic response at the scale of the whole river network. An analysis of the sensitivity of these end points to lower order parameters enables us to link the local effects of cadmium to the global demographic behavior of the brown trout population. Such a link is of broad interest in the point of view of ecotoxicological management.

Transportation impacts of the Chicago River closure to prevent an asian carp infestation.

DOT National Transportation Integrated Search

2012-07-01

This project develops a simple linear programming model of the Upper Midwest regions rail transportation network to test : whether a closure of the Chicago River to freight traffic would impact the capacity constraint of the rail system. The result :...

Comparing National Water Model Inundation Predictions with Hydrodynamic Modeling

NASA Astrophysics Data System (ADS)

Egbert, R. J.; Shastry, A.; Aristizabal, F.; Luo, C.

2017-12-01

The National Water Model (NWM) simulates the hydrologic cycle and produces streamflow forecasts, runoff, and other variables for 2.7 million reaches along the National Hydrography Dataset for the continental United States. NWM applies Muskingum-Cunge channel routing which is based on the continuity equation. However, the momentum equation also needs to be considered to obtain better estimates of streamflow and stage in rivers especially for applications such as flood inundation mapping. Simulation Program for River NeTworks (SPRNT) is a fully dynamic model for large scale river networks that solves the full nonlinear Saint-Venant equations for 1D flow and stage height in river channel networks with non-uniform bathymetry. For the current work, the steady-state version of the SPRNT model was leveraged. An evaluation on SPRNT's and NWM's abilities to predict inundation was conducted for the record flood of Hurricane Matthew in October 2016 along the Neuse River in North Carolina. This event was known to have been influenced by backwater effects from the Hurricane's storm surge. Retrospective NWM discharge predictions were converted to stage using synthetic rating curves. The stages from both models were utilized to produce flood inundation maps using the Height Above Nearest Drainage (HAND) method which uses the local relative heights to provide a spatial representation of inundation depths. In order to validate the inundation produced by the models, Sentinel-1A synthetic aperture radar data in the VV and VH polarizations along with auxiliary data was used to produce a reference inundation map. A preliminary, binary comparison of the inundation maps to the reference, limited to the five HUC-12 areas of Goldsboro, NC, yielded that the flood inundation accuracies for NWM and SPRNT were 74.68% and 78.37%, respectively. The differences for all the relevant test statistics including accuracy, true positive rate, true negative rate, and positive predictive value were found to be statistically significant. Further research will include a larger segment of the Neuse River to make more confident conclusions on how SPRNT can improve on NWM predictions. An interactive Tethys web application was developed to display and compare the inundation maps.

A regional neural network model for predicting mean daily river water temperature

USGS Publications Warehouse

Wagner, Tyler; DeWeber, Jefferson Tyrell

2014-01-01

Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate and land use changes, thereby providing information that is valuable to management of river ecosystems and biota such as brook trout.

Development of a time-stepping sediment budget model for assessing land use impacts in large river basins.

PubMed

Wilkinson, S N; Dougall, C; Kinsey-Henderson, A E; Searle, R D; Ellis, R J; Bartley, R

2014-01-15

The use of river basin modelling to guide mitigation of non-point source pollution of wetlands, estuaries and coastal waters has become widespread. To assess and simulate the impacts of alternate land use or climate scenarios on river washload requires modelling techniques that represent sediment sources and transport at the time scales of system response. Building on the mean-annual SedNet model, we propose a new D-SedNet model which constructs daily budgets of fine sediment sources, transport and deposition for each link in a river network. Erosion rates (hillslope, gully and streambank erosion) and fine sediment sinks (floodplains and reservoirs) are disaggregated from mean annual rates based on daily rainfall and runoff. The model is evaluated in the Burdekin basin in tropical Australia, where policy targets have been set for reducing sediment and nutrient loads to the Great Barrier Reef (GBR) lagoon from grazing and cropping land. D-SedNet predicted annual loads with similar performance to that of a sediment rating curve calibrated to monitored suspended sediment concentrations. Relative to a 22-year reference load time series at the basin outlet derived from a dynamic general additive model based on monitoring data, D-SedNet had a median absolute error of 68% compared with 112% for the rating curve. RMS error was slightly higher for D-SedNet than for the rating curve due to large relative errors on small loads in several drought years. This accuracy is similar to existing agricultural system models used in arable or humid environments. Predicted river loads were sensitive to ground vegetation cover. We conclude that the river network sediment budget model provides some capacity for predicting load time-series independent of monitoring data in ungauged basins, and for evaluating the impact of land management on river sediment load time-series, which is challenging across large regions in data-poor environments. © 2013. Published by Elsevier B.V. All rights reserved.

Scalable population estimates using spatial-stream-network (SSN) models, fish density surveys, and national geospatial database frameworks for streams

Treesearch

Daniel J. Isaak; Jay M. Ver Hoef; Erin E. Peterson; Dona L. Horan; David E. Nagel

2017-01-01

Population size estimates for stream fishes are important for conservation and management, but sampling costs limit the extent of most estimates to small portions of river networks that encompass 100s–10 000s of linear kilometres. However, the advent of large fish density data sets, spatial-stream-network (SSN) models that benefit from nonindependence among samples,...

Application of chemometric analysis and self Organizing Map-Artificial Neural Network as source receptor modeling for metal speciation in river sediment.

PubMed

Pandey, Mayank; Pandey, Ashutosh Kumar; Mishra, Ashutosh; Tripathi, B D

2015-09-01

Present study deals with the river Ganga water quality and its impact on metal speciation in its sediments. Concentration of physico-chemical parameters was highest in summer season followed by winter and lowest in rainy season. Metal speciation study in river sediments revealed that exchangeable, reducible and oxidizable fractions were dominant in all the studied metals (Cr, Ni, Cu, Zn, Cd, Pb) except Mn and Fe. High pollution load index (1.64-3.89) recommends urgent need of mitigation measures. Self-organizing Map-Artificial Neural Network (SOM-ANN) was applied to the data set for the prediction of major point sources of pollution in the river Ganga. Copyright © 2015 Elsevier Ltd. All rights reserved.

Simulation of stream discharge and transport of nitrate and selected herbicides in the Mississippi River Basin

NASA Astrophysics Data System (ADS)

Broshears, Robert E.; Clark, Gregory M.; Jobson, Harvey E.

2001-05-01

Stream discharge and the transport of nitrate, atrazine, and metolachlor in the Mississippi River Basin were simulated using the DAFLOW/BLTM hydrologic model. The simulated domain for stream discharge included river reaches downstream from the following stations in the National Stream Quality Accounting Network: Mississippi River at Clinton, IA; Missouri River at Hermann, MO; Ohio River at Grand Chain, IL; and Arkansas River at Little Rock, AR. Coefficients of hydraulic geometry were calibrated using data from water year 1996; the model was validated by favourable simulation of observed discharges in water years 1992-1994. The transport of nitrate, atrazine, and metolachlor was simulated downstream from the Mississippi River at Thebes, IL, and the Ohio River at Grand Chain. Simulated concentrations compared favourably with observed concentrations at Baton Rouge, LA. Development of this model is a preliminary step in gaining a more quantitative understanding of the sources and fate of nutrients and pesticides delivered from the Mississippi River Basin to the Gulf of Mexico. Published in 2001 by John Wiley & Sons, Ltd.

Modeling water quality in an urban river using hydrological factors--data driven approaches.

PubMed

Chang, Fi-John; Tsai, Yu-Hsuan; Chen, Pin-An; Coynel, Alexandra; Vachaud, Georges

2015-03-15

Contrasting seasonal variations occur in river flow and water quality as a result of short duration, severe intensity storms and typhoons in Taiwan. Sudden changes in river flow caused by impending extreme events may impose serious degradation on river water quality and fateful impacts on ecosystems. Water quality is measured in a monthly/quarterly scale, and therefore an estimation of water quality in a daily scale would be of good help for timely river pollution management. This study proposes a systematic analysis scheme (SAS) to assess the spatio-temporal interrelation of water quality in an urban river and construct water quality estimation models using two static and one dynamic artificial neural networks (ANNs) coupled with the Gamma test (GT) based on water quality, hydrological and economic data. The Dahan River basin in Taiwan is the study area. Ammonia nitrogen (NH3-N) is considered as the representative parameter, a correlative indicator in judging the contamination level over the study. Key factors the most closely related to the representative parameter (NH3-N) are extracted by the Gamma test for modeling NH3-N concentration, and as a result, four hydrological factors (discharge, days w/o discharge, water temperature and rainfall) are identified as model inputs. The modeling results demonstrate that the nonlinear autoregressive with exogenous input (NARX) network furnished with recurrent connections can accurately estimate NH3-N concentration with a very high coefficient of efficiency value (0.926) and a low RMSE value (0.386 mg/l). Besides, the NARX network can suitably catch peak values that mainly occur in dry periods (September-April in the study area), which is particularly important to water pollution treatment. The proposed SAS suggests a promising approach to reliably modeling the spatio-temporal NH3-N concentration based solely on hydrological data, without using water quality sampling data. It is worth noticing that such estimation can be made in a much shorter time interval of interest (span from a monthly scale to a daily scale) because hydrological data are long-term collected in a daily scale. The proposed SAS favorably makes NH3-N concentration estimation much easier (with only hydrological field sampling) and more efficient (in shorter time intervals), which can substantially help river managers interpret and estimate water quality responses to natural and/or manmade pollution in a more effective and timely way for river pollution management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modelling daily water temperature from air temperature for the Missouri River.

PubMed

Zhu, Senlin; Nyarko, Emmanuel Karlo; Hadzima-Nyarko, Marijana

2018-01-01

The bio-chemical and physical characteristics of a river are directly affected by water temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex problem to accurately estimate water temperature. Modelling of river water temperature is usually based on a suitable mathematical model and field measurements of various atmospheric factors. In this article, the air-water temperature relationship of the Missouri River is investigated by developing three different machine learning models (Artificial Neural Network (ANN), Gaussian Process Regression (GPR), and Bootstrap Aggregated Decision Trees (BA-DT)). Standard models (linear regression, non-linear regression, and stochastic models) are also developed and compared to machine learning models. Analyzing the three standard models, the stochastic model clearly outperforms the standard linear model and nonlinear model. All the three machine learning models have comparable results and outperform the stochastic model, with GPR having slightly better results for stations No. 2 and 3, while BA-DT has slightly better results for station No. 1. The machine learning models are very effective tools which can be used for the prediction of daily river temperature.

Spatial Patterns of Greenhouse Gases Across an Urbanization Gradient in a Suburban River Network

NASA Astrophysics Data System (ADS)

Robison, A.; Balch, E.; Wollheim, W. M.

2017-12-01

River networks are important components of the global carbon cycle, processing significant quantities of terrestrial carbon and are most often sources of greenhouse gases (GHGs) to the atmosphere. While recent investigations have begun to incorporate aquatic systems into continental carbon budgets, our understanding of what drives the variability in space and time of these dynamics is poorly constrained. Meanwhile, urban areas continue to expand rapidly across the globe, with wide ranging effects on aquatic systems. A better understanding of the effect of human activities on aquatic carbon and GHG dynamics at both local and global scales is needed. We address the question: How does urbanization affect GHG dynamics in river networks? To address this question, we conducted a synoptic survey of 45 sites in a suburban river network in New England (Ipswich River, MA), analyzing samples for physical and chemical characteristics, including dissolved GHGs, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Sampling sites were selected across an urbanization gradient (1.4-90% developed) and included headwater streams, major tributaries, the basin mouth, and additional sites along the main stem. Initial results indicate dissolved N2O concentration in headwater streams is related to catchment development, while CO2 and CH4 are not correlated to land use generally. CO2 and CH4 signals from urban areas are likely modified by fluvial wetlands that are abundant along larger tributaries and the mainstem. Developed watersheds are inherently altered and heterogeneous landscapes. To fully quantify the role of urbanized waters in the larger carbon cycle, GHG dynamics must be considered at the river network scale. The work presented here begins this process, allowing for an examination of the interaction between land use and GHG concentrations. Additional analyses will focus on further constraining GHG patterns across the river network, and modeling gas transport through and flux out of the system. This relationship should also be examined across time and under varying flow conditions.

Comparison of unmanned aircraft systems (UAS) to LiDAR for streambank erosion measurement at the site-specific and river network scales

NASA Astrophysics Data System (ADS)

Hamshaw, S. D.; Dewoolkar, M. M.; Rizzo, D.; ONeil-Dunne, J.; Frolik, J.

2016-12-01

Measurement of rates and extent of streambank erosion along river corridors is an important component of many catchment studies and necessary for engineering projects such as river restoration, hazard assessment, and total maximum daily load (TMDL) development. A variety of methods have been developed to quantify streambank erosion, including bank pins, ground surveys, photogrammetry, LiDAR, and analytical models. However, these methods are not only resource intensive, but many are feasible and appropriate only for site-specific studies and not practical for erosion estimates at larger scales. Recent advancements in unmanned aircraft systems (UAS) and photogrammetry software provide capabilities for more rapid and economical quantification of streambank erosion and deposition at multiple scales (from site-specific to river network). At the site-specific scale, the capability of UAS to quantify streambank erosion was compared to terrestrial laser scanning (TLS) and RTK-GPS ground survey and assessed at seven streambank monitoring sites in central Vermont. Across all sites, the UAS-derived bank topography had mean errors of 0.21 m compared to TLS and GPS data. Highest accuracies were achieved in early spring conditions where mean errors approached 10 cm. The cross sectional area of bank erosion at a typical, vegetated streambank site was found to be reliably calculated within 10% of actual for erosion areas greater than 3.5 m2. At the river network-level scale, 20 km of river corridor along the New Haven, Winooski, and Mad Rivers was flown on multiple dates with UAS and used to generate digital elevation models (DEMs) that were then compared for change detection analysis. Airborne LiDAR data collected prior to UAS surveys was also compared to UAS data to determine multi-year rates of bank erosion. UAS-based photogrammetry for generation of fine scale topographic data shows promise for the monitoring of streambank erosion both at the individual site scale and river-network scale in areas that are not densely covered with vegetation year-round.

Dynamic reorganization of river basins.

PubMed

Willett, Sean D; McCoy, Scott W; Perron, J Taylor; Goren, Liran; Chen, Chia-Yu

2014-03-07

River networks evolve as migrating drainage divides reshape river basins and change network topology by capture of river channels. We demonstrate that a characteristic metric of river network geometry gauges the horizontal motion of drainage divides. Assessing this metric throughout a landscape maps the dynamic states of entire river networks, revealing diverse conditions: Drainage divides in the Loess Plateau of China appear stationary; the young topography of Taiwan has migrating divides driving adjustment of major basins; and rivers draining the ancient landscape of the southeastern United States are reorganizing in response to escarpment retreat and coastal advance. The ability to measure the dynamic reorganization of river basins presents opportunities to examine landscape-scale interactions among tectonics, erosion, and ecology.

Predicted effects of future climate warming on thermal habitat suitability for Lake Sturgeon (Acipenser fulvescens, Rafinesque, 1817) in rivers in Wisconsin, USA

USGS Publications Warehouse

Lyons, John D.; Stewart, Jana S.

2015-01-01

The Lake Sturgeon (Acipenser fulvescens, Rafinesque, 1817) may be threatened by future climate warming. The purpose of this study was to identify river reaches in Wisconsin, USA, where they might be vulnerable to warming water temperatures. In Wisconsin, A. fulvescens is known from 2291 km of large-river habitat that has been fragmented into 48 discrete river-lake networks isolated by impassable dams. Although the exact temperature tolerances are uncertain, water temperatures above 28–30°C are potentially less suitable for this coolwater species. Predictions from 13 downscaled global climate models were input to a lotic water temperature model to estimate amounts of potential thermally less-suitable habitat at present and for 2046–2065. Currently, 341 km (14.9%) of the known habitat are estimated to regularly exceed 28°C for an entire day, but only 6 km (0.3%) to exceed 30°C. In 2046–2065, 685–2164 km (29.9–94.5%) are projected to exceed 28°C and 33–1056 km (1.4–46.1%) to exceed 30°C. Most river-lake networks have cooler segments, large tributaries, or lakes that might provide temporary escape from potentially less suitable temperatures, but 12 short networks in the Lower Fox and Middle Wisconsin rivers totaling 93.6 km are projected to have no potential thermal refugia. One possible adaptation to climate change could be to provide fish passage or translocation so that riverine Lake Sturgeon might have access to more thermally suitable habitats.

Simulating fish assemblages in riverine networks

EPA Science Inventory

We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the grain and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

Multi-scale soil moisture model calibration and validation: An ARS Watershed on the South Fork of the Iowa River

USDA-ARS?s Scientific Manuscript database

Soil moisture monitoring with in situ technology is a time consuming and costly endeavor for which a method of increasing the resolution of spatial estimates across in situ networks is necessary. Using a simple hydrologic model, the resolution of an in situ watershed network can be increased beyond...

Analysis of Salinity Intrusion in the Waccamaw River and Atlantic Intracoastal Waterway near Myrtle Beach, South Carolina, 1995-2002

USGS Publications Warehouse

Conrads, Paul; Roehl, Edwin A.

2007-01-01

Six reservoirs in North Carolina discharge into the Pee Dee River, which flows 160 miles through South Carolina to the coastal communities near Myrtle Beach, South Carolina. During the Southeast's record-breaking drought from 1998 to 2003, salinity intrusions inundated a coastal municipal freshwater intake, limiting water supplies. To evaluate the effects of regulated flows of the Pee Dee River on salinity intrusion in the Waccamaw River and Atlantic Intracoastal Waterway, the South Carolina Department of Natural Resources and a consortium of stakeholders entered into a cooperative agreement with the U.S. Geological Survey to apply data-mining techniques to the long-term time series to analyze and simulate salinity dynamics near the freshwater intakes along the Grand Strand of South Carolina. Salinity intrusion in tidal rivers results from the interaction of three principal forces?streamflow, mean tidal water levels, and tidal range. To analyze, model, and simulate hydrodynamic behaviors at critical coastal gages, data-mining techniques were applied to over 20 years of hourly streamflow, coastal water-quality, and water-level data. Artificial neural network models were trained to learn the variable interactions that cause salinity intrusions. Streamflow data from the 18,300-square-mile basin were input to the model as time-delayed variables and accumulated tributary inflows. Tidal inputs to the models were obtained by decomposing tidal water-level data into a 'periodic' signal of tidal range and a 'chaotic' signal of mean water levels. The artificial neural network models were able to convincingly reproduce historical behaviors and generate alternative scenarios of interest. To make the models directly available to all stakeholders along the Pee Dee and Waccamaw Rivers and Atlantic Intracoastal Waterway, an easy-to-use decision support system (DSS) was developed as a spreadsheet application that integrates the historical database, artificial neural network models, model controls, streaming graphics, and model output. An additional feature is a built-in optimizer that dynamically calculates the amount of flow needed to suppress salinity intrusions as tidal ranges and water levels vary over days and months. This DSS greatly reduced the number of long-term simulations needed for stakeholders to determine the minimum flow required to adequately protect the freshwater intakes.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

A high-resolution physically-based global flood hazard map

NASA Astrophysics Data System (ADS)

Kaheil, Y.; Begnudelli, L.; McCollum, J.

2016-12-01

We present the results from a physically-based global flood hazard model. The model uses a physically-based hydrologic model to simulate river discharges, and 2D hydrodynamic model to simulate inundation. The model is set up such that it allows the application of large-scale flood hazard through efficient use of parallel computing. For hydrology, we use the Hillslope River Routing (HRR) model. HRR accounts for surface hydrology using Green-Ampt parameterization. The model is calibrated against observed discharge data from the Global Runoff Data Centre (GRDC) network, among other publicly-available datasets. The parallel-computing framework takes advantage of the river network structure to minimize cross-processor messages, and thus significantly increases computational efficiency. For inundation, we implemented a computationally-efficient 2D finite-volume model with wetting/drying. The approach consists of simulating flood along the river network by forcing the hydraulic model with the streamflow hydrographs simulated by HRR, and scaled up to certain return levels, e.g. 100 years. The model is distributed such that each available processor takes the next simulation. Given an approximate criterion, the simulations are ordered from most-demanding to least-demanding to ensure that all processors finalize almost simultaneously. Upon completing all simulations, the maximum envelope of flood depth is taken to generate the final map. The model is applied globally, with selected results shown from different continents and regions. The maps shown depict flood depth and extent at different return periods. These maps, which are currently available at 3 arc-sec resolution ( 90m) can be made available at higher resolutions where high resolution DEMs are available. The maps can be utilized by flood risk managers at the national, regional, and even local levels to further understand their flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs.

Analysis of Compound Water Hazard in Coastal Urbanized Areas under the Future Climate

NASA Astrophysics Data System (ADS)

Shibuo, Y.; Taniguchi, K.; Sanuki, H.; Yoshimura, K.; Lee, S.; Tajima, Y.; Koike, T.; Furumai, H.; Sato, S.

2017-12-01

Several studies indicate the increased frequency and magnitude of heavy rainfalls as well as the sea level rise under the future climate, which implies that coastal low-lying urbanized areas may experience increased risk against flooding. In such areas, where river discharge, tidal fluctuation, and city drainage networks altogether influence urban inundation, it is necessary to consider their potential interference to understand the effect of compound water hazard. For instance, pump stations cannot pump out storm water when the river water level is high, and in the meantime the river water level shall increase when it receives pumped water from cities. At the further downstream, as the tidal fluctuation regulates the water levels in the river, it will also affect the functionality of pump stations and possible inundation from rivers. In this study, we estimate compound water hazard in the coastal low-lying urbanized areas of the Tsurumi river basin under the future climate. We developed the seamlessly integrated river, sewerage, and coastal hydraulic model that can simulate river water levels, water flow in sewerage network, and inundation from the rivers and/or the coast to address the potential interference issue. As a forcing, the pseudo global warming method, which applies the changes in GCM anomaly to re-analysis data, is employed to produce ensemble typhoons to drive the seamlessly integrated model. The results show that heavy rainfalls caused by the observed typhoon generally become stronger under the pseudo global climate condition. It also suggests that the coastal low-lying areas become extensively inundated if the onset of river flooding and storm surge coincides.

Assessment of the environmental significance of nutrients and heavy metal pollution in the river network of Serbia.

PubMed

Dević, Gordana; Sakan, Sanja; Đorđević, Dragana

2016-01-01

In this paper, the data for ten water quality variables collected during 2009 at 75 monitoring sites along the river network of Serbia are considered. The results are alarming because 48% of the studied sites were contaminated by Ni, Mn, Pb, As, and nutrients, which are key factors impairing the water quality of the rivers in Serbia. Special attention should be paid to Zn and Cu, listed in the priority toxic pollutants of US EPA for aquatic life protection. The employed Q-model cluster analysis grouped the data into three major pollution zones (low, moderate, and high). Most sites classified as "low pollution zones" (LP) were in the main rivers, whereas those classified as "moderate and high pollution zones" (MP and HP, respectively) were in the large and small tributaries/hydro-system. Principal component analysis/factor analysis (PCA/FA) showed that the dissolved metals and nutrients in the Serbian rivers varied depending on the river, the heterogeneity of the anthropogenic activities in the basins (influenced primarily by industrial wastewater, agricultural activities, and urban runoff pollution), and natural environmental variability, such as geological characteristics. In LP dominated non-point source pollution, such as agricultural and urban runoff, whereas mixed source pollution dominated in the MP and HP zones. These results provide information to be used for developing better pollution control strategies for the river network of Serbia.

Deformation and evolution of an experimental drainage network subjected to oblique deformation: Insight from chi-maps

NASA Astrophysics Data System (ADS)

Guerit, Laure; Goren, Liran; Dominguez, Stéphane; Malavieille, Jacques; Castelltort, Sébastien

2017-04-01

The morphology of a fluvial landscape reflects a balance between its own dynamics and external forcings, and therefore holds the potential to reveal local or large-scale tectonic patterns. Commonly, particular focus has been cast on the longitudinal profiles of rivers as they constitute sensitive recorders of vertical movements, that can be recovered based on models of bedrock incision. However, several recent studies have suggested that maps of rescaled distance along channel called chi (χ), derived from the commonly observed power law relation between the slope and the drainage area , could reveal transient landscapes in state of reorganization of basin geometry and location of water divides. If river networks deforms in response to large amount of distributed strain, then they might be used to reconstruct the mode and rate of horizontal deformation away from major active structures through the use of the parameter χ. To explore how streams respond to tectonic horizontal deformation, we develop an experimental model for studying river pattern evolution over a doubly-vergent orogenic wedge growing in a context of oblique convergence. We use a series of sprinklers located about the experimental table to activate erosion, sediment transport and river development on the surface of the experimental wedge. At the end of the experiment, the drainage network is statistically rotated clockwise, confirming that rivers can record the distribution of motion along the wedge. However, the amount of rotation does not match with the imposed deformation, and thus we infer that stream networks are not purely passive markers. Based on the comparison between the observed evolution of the fluvial system and the predictions made from χ maps, we show that the plan-view morphology of the streams results from the competition between the imposed deformation and fluvial processes of drainage reorganization.

Identification of drought in Dhalai river watershed using MCDM and ANN models

NASA Astrophysics Data System (ADS)

Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy

2017-03-01

An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

River salinity on a mega-delta, an unstructured grid model approach.

NASA Astrophysics Data System (ADS)

Bricheno, Lucy; Saiful Islam, Akm; Wolf, Judith

2014-05-01

With an average freshwater discharge of around 40,000 m3/s the BGM (Brahmaputra Ganges and Meghna) river system has the third largest discharge worldwide. The BGM river delta is a low-lying fertile area covering over 100,000 km2 mainly in India and Bangladesh. Approximately two-thirds of the Bangladesh people work in agriculture and these local livelihoods depend on freshwater sources directly linked to river salinity. The finite volume coastal ocean model (FVCOM) has been applied to the BGM delta in order to simulate river salinity under present and future climate conditions. Forced by a combination of regional climate model predictions, and a basin-wide river catchment model, the 3D baroclinic delta model can determine river salinity under the current climate, and make predictions for future wet and dry years. The river salinity demonstrates a strong seasonal and tidal cycle, making it important for the model to be able to capture a wide range of timescales. The unstructured mesh approach used in FVCOM is required to properly represent the delta's structure; a complex network of interconnected river channels. The model extends 250 km inland in order to capture the full extent of the tidal influence and grid resolutions of 10s of metres are required to represent narrow inland river channels. The use of FVCOM to simulate flows so far inland is a novel challenge, which also requires knowledge of the shape and cross-section of the river channels.

Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water.

PubMed

Salari, Marjan; Salami Shahid, Esmaeel; Afzali, Seied Hosein; Ehteshami, Majid; Conti, Gea Oliveri; Derakhshan, Zahra; Sheibani, Solmaz Nikbakht

2018-04-22

Today, due to the increase in the population, the growth of industry and the variety of chemical compounds, the quality of drinking water has decreased. Five important river water quality properties such as: dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (ALK) and turbidity (TU) were estimated by parameters such as: electric conductivity (EC), temperature (T), and pH that could be measured easily with almost no costs. Simulate water quality parameters were examined with two methods of modeling include mathematical and Artificial Neural Networks (ANN). Mathematical methods are based on polynomial fitting with least square method and ANN modeling algorithms are feed-forward networks. All conditions/circumstances covered by neural network modeling were tested for all parameters in this study, except for Alkalinity. All optimum ANN models developed to simulate water quality parameters had precision value as R-value close to 0.99. The ANN model extended to simulate alkalinity with R-value equals to 0.82. Moreover, Surface fitting techniques were used to refine data sets. Presented models and equations are reliable/useable tools for studying water quality parameters at similar rivers, as a proper replacement for traditional water quality measuring equipment's. Copyright © 2018 Elsevier Ltd. All rights reserved.

Simulating fish assemblages in riverine networks - September 2013

EPA Science Inventory

We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the grain and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

Nitrous oxide emission from denitrification in stream and river networks

USGS Publications Warehouse

Beaulieu, J.J.; Tank, J.L.; Hamilton, S.K.; Wollheim, W.M.; Hall, R.O.; Mulholland, P.J.; Peterson, B.J.; Ashkenas, L.R.; Cooper, L.W.; Dahm, Clifford N.; Dodds, W.K.; Grimm, N. B.; Johnson, S.L.; McDowell, W.H.; Poole, G.C.; Maurice, Valett H.; Arango, C.P.; Bernot, M.J.; Burgin, A.J.; Crenshaw, C.L.; Helton, A.M.; Johnson, L.T.; O'Brien, J. M.; Potter, J.D.; Sheibley, R.W.; Sobota, D.J.; Thomas, S.M.

2011-01-01

Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N 2O via microbial denitrification that converts N to N2O and dinitrogen (N2). The fraction of denitrified N that escapes as N2O rather than N2 (i.e., the N2O yield) is an important determinant of how much N2O is produced by river networks, but little is known about the N2O yield in flowing waters. Here, we present the results of whole-stream 15N-tracer additions conducted in 72 headwater streams draining multiple land-use types across the United States. We found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3-) concentrations, but that <1% of denitrified N is converted to N2O. Unlike some previous studies, we found no relationship between the N2O yield and stream water NO3-. We suggest that increased stream NO3- loading stimulates denitrification and concomitant N2O production, but does not increase the N2O yield. In our study, most streams were sources of N2O to the atmosphere and the highest emission rates were observed in streams draining urban basins. Using a global river network model, we estimate that microbial N transformations (e.g., denitrification and nitrification) convert at least 0.68 Tg??y -1 of anthropogenic N inputs to N2O in river networks, equivalent to 10% of the global anthropogenic N2O emission rate. This estimate of stream and river N2O emissions is three times greater than estimated by the Intergovernmental Panel on Climate Change.

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.

Modeling Storm Water Runoff and Soil Interflow in a Managed Forest, Upper Coastal Plain of the Southeast US.

Treesearch

T.J. Callahan; J.D. Cook; Mark D. Coleman; Devendra M. Amatya; Carl C. Trettin

2004-01-01

The Forest Service-Savannah River is conducting a hectare-scale monitoring and modeling study on forest productivity in a Short Rotation Woody Crop plantation at the Savannah River Site, which is on Upper Coastal Plain of South Carolina. Detailed surveys, i.e., topography, soils, vegetation, and dainage network, of small (2-5 ha) plots have been completed in a 2 square...

Interaction of Aquifer and River-Canal Network near Well Field.

PubMed

Ghosh, Narayan C; Mishra, Govinda C; Sandhu, Cornelius S S; Grischek, Thomas; Singh, Vikrant V

2015-01-01

The article presents semi-analytical mathematical models to asses (1) enhancements of seepage from a canal and (2) induced flow from a partially penetrating river in an unconfined aquifer consequent to groundwater withdrawal in a well field in the vicinity of the river and canal. The nonlinear exponential relation between seepage from a canal reach and hydraulic head in the aquifer beneath the canal reach is used for quantifying seepage from the canal reach. Hantush's (1967) basic solution for water table rise due to recharge from a rectangular spreading basin in absence of pumping well is used for generating unit pulse response function coefficients for water table rise in the aquifer. Duhamel's convolution theory and method of superposition are applied to obtain water table position due to pumping and recharge from different canal reaches. Hunt's (1999) basic solution for river depletion due to constant pumping from a well in the vicinity of a partially penetrating river is used to generate unit pulse response function coefficients. Applying convolution technique and superposition, treating the recharge from canal reaches as recharge through conceptual injection wells, river depletion consequent to variable pumping and recharge is quantified. The integrated model is applied to a case study in Haridwar (India). The well field consists of 22 pumping wells located in the vicinity of a perennial river and a canal network. The river bank filtrate portion consequent to pumping is quantified. © 2014, National GroundWater Association.

River networks as biodiversity hotlines.

PubMed

Décamps, Henri

2011-05-01

For several years, measures to insure healthy river functions and to protect biodiversity have focused on management at the scale of drainage basins. Indeed, rivers bear witness to the health of their drainage basins, which justifies integrated basin management. However, this vision should not mask two other aspects of the protection of aquatic and riparian biodiversity as well as services provided by rivers. First, although largely depending on the ecological properties of the surrounding terrestrial environment, rivers are ecological systems by themselves, characterized by their linearity: they are organized in connected networks, complex and ever changing, open to the sea. Second, the structure and functions of river networks respond to manipulations of their hydrology, and are particularly vulnerable to climatic variations. Whatever the scale considered, river networks represent "hotlines" for sharing water between ecological and societal systems, as well as for preserving both systems in the face of global change. River hotlines are characterized by spatial as well as temporal legacies: every human impact to a river network may be transmitted far downstream from its point of origin, and may produce effects only after a more or less prolonged latency period. Here, I review some of the current issues of river ecology in light of the linear character of river networks. Copyright © 2011 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Balancing between retention and flushing in river networks--optimizing nutrient management to improve trophic state.

PubMed

Honti, Márk; Istvánovics, Vera; Kovács, Adám S

2010-09-15

River basin management can frequently involve decisive situations, when conflicting interests must be resolved. In the Zala River catchment (Western Hungary) local efforts to improve water quality by reducing algal biomass are not always harmonized with the requirement of sustaining the same objective in its recipient, Lake Balaton. The PhosFate catchment model is a GIS tool designed to estimate the spatial variability and fate of diffuse phosphorus emission during transport. Besides diffuse pollution, a simplified annual hydrologic balance is also calculated. A new module was added to PhosFate that tracked the development of entrained algae during their travel downstream. The extended model was used to simulate the current average algal concentrations in the river network. The numerous small reservoirs and impoundments on the tributaries of the Zala River were identified as the key elements in determining algal biomass, since they fundamentally increase the water residence time (WRT) in the system. Without reservoirs, the short WRT in the drainage network would successfully prevent the development of suspended algal biomass despite the fairly high SRP concentrations. However, the removal of such standing waters is impossible for socio-economic reasons and reducing the overall P load to Lake Balaton would also require increasing WRT in the system. As a resolution to these conflicting interests, a hybrid management strategy was designed to simultaneously reach both goals: (i) switching from WRT to P limitation in reservoirs responsible for most of algal growth, and (ii) optimized deployment of buffer zones and the introduction of best agricultural practices on the remaining majority of the catchment to reduce the overall P load. The suggested management approach could be applied in other river catchments too, due to the extensive presence of reservoirs and impoundments in many stream networks. Copyright 2010 Elsevier B.V. All rights reserved.

Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks

Treesearch

Lindy B. Mullen; H. Arthur Woods; Michael K. Schwartz; Adam J. Sepulveda; Winsor H. Lowe

2010-01-01

The network architecture of streams and rivers constrains evolutionary, demographic and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho...

Quantifying spatial and temporal patterns of flow intermittency using spatially contiguous runoff data

NASA Astrophysics Data System (ADS)

Yu (于松延), Songyan; Bond, Nick R.; Bunn, Stuart E.; Xu, Zongxue; Kennard, Mark J.

2018-04-01

River channel drying caused by intermittent stream flow is a widely-recognized factor shaping stream ecosystems. There is a strong need to quantify the distribution of intermittent streams across catchments to inform management. However, observational gauge networks provide only point estimates of streamflow variation. Increasingly, this limitation is being overcome through the use of spatially contiguous estimates of the terrestrial water-balance, which can also assist in estimating runoff and streamflow at large-spatial scales. Here we proposed an approach to quantifying spatial and temporal variation in monthly flow intermittency throughout river networks in eastern Australia. We aggregated gridded (5 × 5 km) monthly water-balance data with a hierarchically nested catchment dataset to simulate catchment runoff accumulation throughout river networks from 1900 to 2016. We also predicted zero flow duration for the entire river network by developing a robust predictive model relating measured zero flow duration (% months) to environmental predictor variables (based on 43 stream gauges). We then combined these datasets by using the predicted zero flow duration from the regression model to determine appropriate 'zero' flow thresholds for the modelled discharge data, which varied spatially across the catchments examined. Finally, based on modelled discharge data and identified actual zero flow thresholds, we derived summary metrics describing flow intermittency across the catchment (mean flow duration and coefficient-of-variation in flow permanence from 1900 to 2016). We also classified the relative degree of flow intermittency annually to characterise temporal variation in flow intermittency. Results showed that the degree of flow intermittency varied substantially across streams in eastern Australia, ranging from perennial streams flowing permanently (11-12 months) to strongly intermittent streams flowing 4 months or less of year. Results also showed that the temporal extent of flow intermittency varied dramatically inter-annually from 1900 to 2016, with the proportion of intermittent (weakly and strongly intermittent) streams ranging in length from 3% to nearly 100% of the river network, but there was no evidence of an increasing trend towards flow intermittency over this period. Our approach to generating spatially explicit and catchment-wide estimates of streamflow intermittency can facilitate improved ecological understanding and management of intermittent streams in Australia and around the world.

Spatial Statistical Network Models for Stream and River Temperature in the Chesapeake Bay Watershed, USA

EPA Science Inventory

Regional temperature models are needed for characterizing and mapping stream thermal regimes, establishing reference conditions, predicting future impacts and identifying critical thermal refugia. Spatial statistical models have been developed to improve regression modeling techn...

River flow simulation using a multilayer perceptron-firefly algorithm model

NASA Astrophysics Data System (ADS)

Darbandi, Sabereh; Pourhosseini, Fatemeh Akhoni

2018-06-01

River flow estimation using records of past time series is importance in water resources engineering and management and is required in hydrologic studies. In the past two decades, the approaches based on the artificial neural networks (ANN) were developed. River flow modeling is a non-linear process and highly affected by the inputs to the modeling. In this study, the best input combination of the models was identified using the Gamma test then MLP-ANN and hybrid multilayer perceptron (MLP-FFA) is used to forecast monthly river flow for a set of time intervals using observed data. The measurements from three gauge at Ajichay watershed, East Azerbaijani, were used to train and test the models approach for the period from January 2004 to July 2016. Calibration and validation were performed within the same period for MLP-ANN and MLP-FFA models after the preparation of the required data. Statistics, the root mean square error and determination coefficient, are used to verify outputs from MLP-ANN to MLP-FFA models. The results show that MLP-FFA model is satisfactory for monthly river flow simulation in study area.

Evaluation of a landscape evolution model to simulate stream piracies: Insights from multivariable numerical tests using the example of the Meuse basin, France

NASA Astrophysics Data System (ADS)

Benaïchouche, Abed; Stab, Olivier; Tessier, Bruno; Cojan, Isabelle

2016-01-01

In landscapes dominated by fluvial erosion, the landscape morphology is closely related to the hydrographic network system. In this paper, we investigate the hydrographic network reorganization caused by a headward piracy mechanism between two drainage basins in France, the Meuse and the Moselle. Several piracies occurred in the Meuse basin during the past one million years, and the basin's current characteristics are favorable to new piracies by the Moselle river network. This study evaluates the consequences over the next several million years of a relative lowering of the Moselle River (and thus of its basin) with respect to the Meuse River. The problem is addressed with a numerical modeling approach (landscape evolution model, hereafter LEM) that requires empirical determinations of parameters and threshold values. Classically, fitting of the parameters is based on analysis of the relationship between the slope and the drainage area and is conducted under the hypothesis of equilibrium. Application of this conventional approach to the capture issue yields incomplete results that have been consolidated by a parametric sensitivity analysis. The LEM equations give a six-dimensional parameter space that was explored with over 15,000 simulations using the landscape evolution model GOLEM. The results demonstrate that stream piracies occur in only four locations in the studied reach near the city of Toul. The locations are mainly controlled by the local topography and are model-independent. Nevertheless, the chronology of the captures depends on two parameters: the river concavity (given by the fluvial advection equation) and the hillslope erosion factor. Thus, the simulations lead to three different scenarios that are explained by a phenomenon of exclusion or a string of events.

A hybrid least squares support vector machines and GMDH approach for river flow forecasting

NASA Astrophysics Data System (ADS)

Samsudin, R.; Saad, P.; Shabri, A.

2010-06-01

This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

Modeling and management of water in the Klamath River Basin: overcoming politics and conflicts

USGS Publications Warehouse

Flug, Marshall; Scott, John F.; Abt, Steven R.; Young-Pezeshk, Jayne; Watson, Chester C.

1998-01-01

The network flow model MODSIM, which was designed as a water quantity mass balance model for evaluating and selecting water management alternatives, has been applied to the Klamath River basin. A background of conflicting issues in the basin is presented. The complexity of water quantity model development, while satisfying the many stakeholders and involved special interest groups is discussed, as well as the efforts taken to have the technical model accepted and used, and overcome stakeholder criticism, skepticism, and mistrust of the government.

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams

PubMed Central

Jaeger, Kristin L.; Olden, Julian D.; Pelland, Noel A.

2014-01-01

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6–9% over the course of a year and up to 12–18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna. PMID:25136090

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams.

PubMed

Jaeger, Kristin L; Olden, Julian D; Pelland, Noel A

2014-09-23

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6-9% over the course of a year and up to 12-18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna.

Networks of Interacting Processes: Relationships Between Drivers and Deltaic Variables to Understand Water and Sediment Transport in Wax Lake Delta, Coastal Louisiana

NASA Astrophysics Data System (ADS)

Sendrowski, A.; Passalacqua, P.; Wagner, W.; Mohrig, D. C.; Meselhe, E. A.; Sadid, K. M.; Castañeda-Moya, E.; Twilley, R.

2017-12-01

Studying distributary channel networks in river deltaic systems provides important insight into deltaic functioning and evolution. This view of networks highlights the physical connection along channels and can also encompass the structural link between channels and deltaic islands (termed structural connectivity). An alternate view of the deltaic network is one composed of interacting processes, such as relationships between external drivers (e.g., river discharge, tides, and wind) and internal deltaic response variables (e.g., water level and sediment concentration). This network, also referred to as process connectivity, is dynamic across space and time, often comprises nonlinear relationships, and contributes to the development of complex channel networks and ecologically rich island platforms. The importance of process connectivity has been acknowledged, however, few studies have directly quantified these network interactions. In this work, we quantify process connections in Wax Lake Delta (WLD), coastal Louisiana. WLD is a naturally prograding delta that serves as an analogue for river diversion projects, thus it provides an excellent setting for understanding the influence of river discharge, tides, and wind on water and sediment in a delta. Time series of water level and sediment concentration were collected in three channels from November 2013 to February 2014, while water level and turbidity were collected on an island from April 2014 to August 2015. Additionally, a model run on WLD bathymetry generated two years of sediment concentration time series in multiple channels. River discharge, tide, and wind measurements were collected from the USGS and NOAA, respectively. We analyze this data with information theory (IT), a set of statistics that measure uncertainty in signals and communication between signals. Using IT, the timescale, strength, and direction of network links are quantified by measuring the synchronization and direct influence from one variable to another. We compare channel and island process connections, which show distinct differences. Our study captures the temporal evolution of variable transport at multiple locations. While WLD is river dominated, tides and wind show unique transport signatures related to tidal spring and neap transitions and wind events.

Natural and Anthropogenic Water Treatment: How Riverine Ecosystem Services of Nitrogen Removal Interact with Wastewater Treatment Infrastructure in the Northeast U.S.

NASA Astrophysics Data System (ADS)

Stewart, R. J.; Wollheim, W. M.; Whittinghill, K. A.; Mineau, M.; Rosenzweig, B.

2014-12-01

The magnitude and spatial distribution of point and non-point dissolved inorganic nitrogen (N) inputs to river systems greatly influences the potential for eutrophication of downstream water bodies. Wastewater treatment plants (WWTPs), the predominant point source of N in the northeast US, remove some but not all of human waste N they receive. Excess enters rivers, which may further mitigate N concentrations by dilution and denitrification. WWTP effluent combines with upstream flows, which may include non-point sources of N due to agriculture or urbanization. Natural N removal capacities in rivers may however be overwhelmed and become N saturated, which reduces their effectiveness. As a result, natural and man-made services of N removal are intimately linked at the river network scale for provisions of suitable water quality and aquatic habitat. We assessed the summer N mitigation capacity of rivers relative to N removal in WWTPs in the northeastern U.S. using a N removal model developed within the Framework for Aquatic Modeling in the Earth System (FrAMES). The spatially distributed river network model predicts average daily dissolved inorganic nitrogen concentrations at a 3-minute river grid resolution, accounting for the mixing of natural areas, nonpoint sources, WWTP effluent, and instream denitrification, which is simulated as a function of river temperature, water residence time, and biogeochemical activity. Model validation was done using N concentration data from 750 USGS gauges across the northeast during the period 2000-2010. Confidence intervals (90%) are estimated for river N concentrations based on key uncertainties in simulated river width, uptake rates, and N loading rates. Model results suggest WWTPs potentially impact 25,770 km of river length (10.7% of total river length in the northeast) and increase N concentrations an average of 42.3% at the facility locations. The in-stream ecosystem service of N removal accounts for 2.7% of the total cumulative N removed by WWTPs during the summer in the region. Despite providing a relatively small proportion of N removal, the expected deterioration of WWTP infrastructure and associated costs of upgrading existing systems puts the role of this riverine ecosystem service into economic perspective.

Network Robustness: the whole story

NASA Astrophysics Data System (ADS)

Longjas, A.; Tejedor, A.; Zaliapin, I. V.; Ambroj, S.; Foufoula-Georgiou, E.

2014-12-01

A multitude of actual processes operating on hydrological networks may exhibit binary outcomes such as clean streams in a river network that may become contaminated. These binary outcomes can be modeled by node removal processes (attacks) acting in a network. Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. However, the current definition of robustness is only accounting for the connectivity of the nodes unaffected by the attack. Here, we put forward the idea that the connectivity of the affected nodes can play a crucial role in proper evaluation of the overall network robustness and its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and the efficiency of building-up the IN. This approach is motivated by concrete applied problems, since, for example, if we study the dynamics of contamination in river systems, it is necessary to know both the connectivity of the healthy and contaminated parts of the river to assess its ecological functionality. We show that trade-offs between the efficiency of the Active and Idle network dynamics give rise to surprising crossovers and re-ranking of different attack strategies, pointing to significant implications for decision making.

Spatial reasoning to determine stream network from LANDSAT imagery

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Wang, S.; Elliott, D. B.

1983-01-01

In LANDSAT imagery, spectral and spatial information can be used to detect the drainage network as well as the relative elevation model in mountainous terrain. To do this, mixed information of material reflectance in the original LANDSAT imagery must be separated. From the material reflectance information, big visible rivers can be detected. From the topographic modulation information, ridges and valleys can be detected and assigned relative elevations. A complete elevation model can be generated by interpolating values for nonridge and non-valley pixels. The small streams not detectable from material reflectance information can be located in the valleys with flow direction known from the elevation model. Finally, the flow directions of big visible rivers can be inferred by solving a consistent labeling problem based on a set of spatial reasoning constraints.

Hydrologic Connectivity Estimated throughout the Nation's River Corridors

NASA Astrophysics Data System (ADS)

Hunt, R.; Borchardt, M. A.; Bradbury, K. R.

2014-12-01

Hydrologic connectivity is a key concept that integrates longitudinal transport in rivers with vertical and lateral exchanges between rivers and hyporheic zones, riparian wetlands, floodplains, and ponded aquatic ecosystems. Desirable levels of connectivity are thought to be associated with rivers that are well-connected longitudinally while also being well connected vertically and laterally with marginal waters where carbon and nutrients are efficiently transformed, and where aquatic organisms feed, or are reared, or take refuge during floods. But what is the proper balance between longitudinal and vertical and lateral connectivity? We took a step towards quantifying hydrologic connectivity using the model NEXSS (Gomez-Velez and Harvey, 2014, GRL) applied throughout the nation's rivers. NEXSS simulates vertical and lateral connectivity and compares it with longitudinal transport along the river's main axis. It uses as inputs measured network topology for first to eighth order channels, river hydraulic geometry, sediment grain size, bedform types and sizes, estimated hydraulic conductivity of sediments, and estimates of reaction rates such as denitrification. Results indicate that hyporheic flow is large enough to exchange a river's entire volume many times within a river network, which increases biogeochemical opportunities for nutrient processing and attenuation of contaminants. Also, the analysis demonstrated why and where (i.e., in which physiographic regions of the nation) are hyporheic flow and solute reactions the greatest. The cumulative influence of hydrologic connectivity on water quality is expressed by a dimensionless index of reaction significance. Our quantification of hydrologic connectivity adds a physical basis that supports water quality modeling, and also supports scientifically based prioritization of management actions (e.g. stream restoration) and may support other types of actions (e.g. legislative actions) to help conserve healthy functional rivers with proper levels of stream metabolism and diverse food webs. The NEXSS model will be modified to account for variable flow (baseflow to bankfull) and to account for exchange that occurs with overbank flooding of riparian wetlands and floodplains.

Hydrologic Connectivity Estimated throughout the Nation's River Corridors

NASA Astrophysics Data System (ADS)

Harvey, J. W.; Gomez-Velez, J. D.

2015-12-01

Hydrologic connectivity is a key concept that integrates longitudinal transport in rivers with vertical and lateral exchanges between rivers and hyporheic zones, riparian wetlands, floodplains, and ponded aquatic ecosystems. Desirable levels of connectivity are thought to be associated with rivers that are well-connected longitudinally while also being well connected vertically and laterally with marginal waters where carbon and nutrients are efficiently transformed, and where aquatic organisms feed, or are reared, or take refuge during floods. But what is the proper balance between longitudinal and vertical and lateral connectivity? We took a step towards quantifying hydrologic connectivity using the model NEXSS (Gomez-Velez and Harvey, 2014, GRL) applied throughout the nation's rivers. NEXSS simulates vertical and lateral connectivity and compares it with longitudinal transport along the river's main axis. It uses as inputs measured network topology for first to eighth order channels, river hydraulic geometry, sediment grain size, bedform types and sizes, estimated hydraulic conductivity of sediments, and estimates of reaction rates such as denitrification. Results indicate that hyporheic flow is large enough to exchange a river's entire volume many times within a river network, which increases biogeochemical opportunities for nutrient processing and attenuation of contaminants. Also, the analysis demonstrated why and where (i.e., in which physiographic regions of the nation) are hyporheic flow and solute reactions the greatest. The cumulative influence of hydrologic connectivity on water quality is expressed by a dimensionless index of reaction significance. Our quantification of hydrologic connectivity adds a physical basis that supports water quality modeling, and also supports scientifically based prioritization of management actions (e.g. stream restoration) and may support other types of actions (e.g. legislative actions) to help conserve healthy functional rivers with proper levels of stream metabolism and diverse food webs. The NEXSS model will be modified to account for variable flow (baseflow to bankfull) and to account for exchange that occurs with overbank flooding of riparian wetlands and floodplains.

Channel-Island Connectivity Affects Water Exposure Time Distributions in a Coastal River Delta

NASA Astrophysics Data System (ADS)

Hiatt, Matthew; Castañeda-Moya, Edward; Twilley, Robert; Hodges, Ben R.; Passalacqua, Paola

2018-03-01

The exposure time is a water transport time scale defined as the cumulative amount of time a water parcel spends in the domain of interest regardless of the number of excursions from the domain. Transport time scales are often used to characterize the nutrient removal potential of aquatic systems, but exposure time distribution estimates are scarce for deltaic systems. Here we analyze the controls on exposure time distributions using a hydrodynamic model in two domains: the Wax Lake delta in Louisiana, USA, and an idealized channel-island complex. In particular, we study the effects of river discharge, vegetation, network geometry, and tides and use a simple model for the fractional removal of nitrate. In both domains, we find that channel-island hydrological connectivity significantly affects exposure time distributions and nitrate removal. The relative contributions of the island and channel portions of the delta to the overall exposure time distribution are controlled by island vegetation roughness and network geometry. Tides have a limited effect on the system's exposure time distribution but can introduce significant spatial variability in local exposure times. The median exposure time for the WLD model is 10 h under the conditions tested and water transport within the islands contributes to 37-50% of the network-scale exposure time distribution and 52-73% of the modeled nitrate removal, indicating that islands may account for the majority of nitrate removal in river deltas.

Removal of terrestrial DOC in aquatic ecosystems of a temperate river network

USGS Publications Warehouse

Wollheim, W.M.; Stewart, R. J.; Aiken, George R.; Butler, Kenna D.; Morse, Nathaniel B.; Salisbury, J.

2015-01-01

Surface waters play a potentially important role in the global carbon balance. Dissolved organic carbon (DOC) fluxes are a major transfer of terrestrial carbon to river systems, and the fate of DOC in aquatic systems is poorly constrained. We used a unique combination of spatially distributed sampling of three DOC fractions throughout a river network and modeling to quantify the net removal of terrestrial DOC during a summer base flow period. We found that aquatic reactivity of terrestrial DOC leading to net loss is low, closer to conservative chloride than to reactive nitrogen. Net removal occurred mainly from the hydrophobic organic acid fraction, while hydrophilic and transphilic acids showed no net change, indicating that partitioning of bulk DOC into different fractions is critical for understanding terrestrial DOC removal. These findings suggest that river systems may have only a modest ability to alter the amounts of terrestrial DOC delivered to coastal zones.

Artificial neural networks for defining the water quality determinants of groundwater abstraction in coastal aquifer

NASA Astrophysics Data System (ADS)

Lallahem, S.; Hani, A.

2017-02-01

Water sustainability in the lower Seybouse River basin, eastern Algeria, must take into account the importance of water quantity and quality integration. So, there is a need for a better knowledge and understanding of the water quality determinants of groundwater abstraction to meet the municipal and agricultural uses. In this paper, the artificial neural network (ANN) models were used to model and predict the relationship between groundwater abstraction and water quality determinants in the lower Seybouse River basin. The study area chosen is the lower Seybouse River basin and real data were collected from forty five wells for reference year 2006. Results indicate that the feed-forward multilayer perceptron models with back-propagation are useful tools to define and prioritize the important water quality parameters of groundwater abstraction and use. The model evaluation shows that the correlation coefficients are more than 95% for training, verification and testing data. The model aims to link the water quantity and quality with the objective to strengthen the Integrated Water Resources Management approach. It assists water planners and managers to better assess the water quality parameters and progress towards the provision of appropriate quantities of water of suitable quality.

Comparison of Conventional and ANN Models for River Flow Forecasting

NASA Astrophysics Data System (ADS)

Jain, A.; Ganti, R.

2011-12-01

Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. River flow is generally estimated using time series or rainfall-runoff models. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been extensively adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conventional models. In this paper, a comparative study has been carried out for river flow forecasting using the conventional and ANN models. Among the conventional models, multiple linear, and non linear regression, and time series models of auto regressive (AR) type have been developed. Feed forward neural network model structure trained using the back propagation algorithm, a gradient search method, was adopted. The daily river flow data derived from Godavari Basin @ Polavaram, Andhra Pradesh, India have been employed to develop all the models included here. Two inputs, flows at two past time steps, (Q(t-1) and Q(t-2)) were selected using partial auto correlation analysis for forecasting flow at time t, Q(t). A wide range of error statistics have been used to evaluate the performance of all the models developed in this study. It has been found that the regression and AR models performed comparably, and the ANN model performed the best amongst all the models investigated in this study. It is concluded that ANN model should be adopted in real catchments for hydrological modeling and forecasting.

How restructuring river connectivity changes freshwater fish biodiversity and biogeography

USGS Publications Warehouse

Lynch, Heather L.; Grant, Evan H. Campbell; Muneepeerakul, Rachata; Arunachalam, Muthukumarasamy; Rodriguez-Iturbe, Ignacio; Fagan, William F.

2011-01-01

Interbasin water transfer projects, in which river connectivity is restructured via man-made canals, are an increasingly popular solution to address the spatial mismatch between supply and demand of fresh water. However, the ecological consequences of such restructuring remain largely unexplored, and there are no general theoretical guidelines from which to derive these expectations. River systems provide excellent opportunities to explore how network connectivity shapes habitat occupancy, community dynamics, and biogeographic patterns. We apply a neutral model (which assumes competitive equivalence among species within a stochastic framework) to an empirically derived river network to explore how proposed changes in network connectivity may impact patterns of freshwater fish biodiversity. Without predicting the responses of individual extant species, we find the addition of canals connecting hydrologically isolated river basins facilitates the spread of common species and increases average local species richness without changing the total species richness of the system. These impacts are sensitive to the parameters controlling the spatial scale of fish dispersal, with increased dispersal affording more opportunities for biotic restructuring at the community and landscape scales. Connections between isolated basins have a much larger effect on local species richness than those connecting reaches within a river basin, even when those within-basin reaches are far apart. As a result, interbasin canal projects have the potential for long-term impacts to continental-scale riverine communities.

Optimization of the scheme for natural ecology planning of urban rivers based on ANP (analytic network process) model.

PubMed

Zhang, Yichuan; Wang, Jiangping

2015-07-01

Rivers serve as a highly valued component in ecosystem and urban infrastructures. River planning should follow basic principles of maintaining or reconstructing the natural landscape and ecological functions of rivers. Optimization of planning scheme is a prerequisite for successful construction of urban rivers. Therefore, relevant studies on optimization of scheme for natural ecology planning of rivers is crucial. In the present study, four planning schemes for Zhaodingpal River in Xinxiang City, Henan Province were included as the objects for optimization. Fourteen factors that influenced the natural ecology planning of urban rivers were selected from five aspects so as to establish the ANP model. The data processing was done using Super Decisions software. The results showed that important degree of scheme 3 was highest. A scientific, reasonable and accurate evaluation of schemes could be made by ANP method on natural ecology planning of urban rivers. This method could be used to provide references for sustainable development and construction of urban rivers. ANP method is also suitable for optimization of schemes for urban green space planning and design.

Reconstructing paleo-discharge from geometries of fluvial sinuous ridges on Earth and Mars

NASA Astrophysics Data System (ADS)

Hayden, A.; Lamb, M. P.; Mohrig, D. C.; Williams, R. M. E.; Myrow, P.; Ewing, R. C.; Cardenas, B. T.; Findlay, C. P., III

2017-12-01

Sinuous, branching networks of topographic ridges resembling river networks are common across Mars, and show promise for quantifying ancient martian surface hydrology. There are two leading formation mechanisms for ridges with a fluvial origin. Inverted channels are ridges that represent casts (e.g., due to lava fill) of relict river channel topography, whereas exhumed channel deposits are eroded remnants of a more extensive fluvial deposit, such as a channel belt. The inverted channel model is often assumed on Mars; however, we currently lack the ability to distinguish these ridge formation mechanisms, motivating the need for Earth-analog study. To address this issue, we studied the extensive networks of sinuous ridges in the Ebro basin of northeast Spain. The Ebro ridges stand 3-15 meters above the surrounding plains and are capped by a cliff-forming sandstone unit 3-10 meters thick and 20-50 meters in breadth. The caprock sandstone bodies contain bar-scale cross stratification, point-bar deposits, levee deposits, and lenses of mudstone, indicating that these are channel-belt deposits, rather than casts of channels formed from lateral channel migration, avulsion and reoccupation. In plan view, ridges form segments branching outward to the north resembling a distributary network; however, crosscutting relationships indicate that ridges cross at different stratigraphic levels. Thus, the apparent network in planview reflects non-uniform exhumation of channel-belt deposits from multiple stratigraphic positions, rather than an inverted coeval river network. As compared to the inverted channel model, exhumed fluvial deposits indicate persistent fluvial activity over geologic timescales, indicating the potential for long-lived surface water on ancient Mars.

From Shoestring Rills to Dendritic River Networks: Documenting the Evolution of River Basins Towards Geometric Similarity Through Divide Migration, Stream Capture and Lateral Branching

NASA Astrophysics Data System (ADS)

Beeson, H. W.; McCoy, S. W.; Willett, S.

2016-12-01

Erosional river networks dissect much of Earth's surface into drainage basins. Global scaling laws such as Hack's Law suggest that river basins trend toward a particular scale-invariant shape. While erosional instabilities arising from competition between advective and diffusive processes can explain why headwaters branch, the erosional mechanics linking larger scale network branching with evolution towards a characteristic river basin shape remain poorly constrained. We map river steepness and a proxy for the steady-state elevation of river networks, χ, in simulated and real landscapes with a large range in spatial scale (102 -106 m) but with similar inclined, planar surfaces at the time of incipient network formation. We document that the evolution from narrow rill-like networks to dendritic, leaf-shaped river basins follows from drainage area differences between catchments. These serve as instabilities that grow, leading to divide migration, stream capture, lateral branching and network reorganization. As Horton hypothesized, incipient networks formed down gradient on an inclined, planar surface have an unequal distribution of drainage area and nonuniformity in response times such that larger basins erode more rapidly and branch laterally via capture of adjacent streams with lower erosion rates. Positive feedback owing to increase in drainage area furthers the process of branching at the expense of neighboring rivers. We show that drainage area exchange and the degree of network reorganization has a significant effect on river steepness in the Dragon's Back Pressure Ridge, CA, the Sierra Nevada, CA, and the Rocky Mountain High Plains, USA. Similarly, metrics of basin shape reveal that basins are evolving from narrow basins towards more common leaf shapes. Our results suggest that divide migration and stream capture driven by erosional disequilibrium could be fundamental processes by which river basins reach their characteristic geometry and dendritic form.

On the Topologic Properties of River Networks

NASA Astrophysics Data System (ADS)

Sarker, S.; Singh, A.

2017-12-01

River network is an important landscape feature and has been studied extensively from a range of geomorphological and hydrological perspective. However, quantifying topologic dynamics and reorganization of river networks is becoming more and more challenging under changing natural and anthropogenic forcings. Here, we use a graph-theoretical approach to study topologic properties of natural and simulated river networks for a range of climatic and tectonic conditions. Among other metrics, we use betweeness and eigenvector centrality distributions computed using adjacency matrix of river networks and show their dependence on energy exponent γ that characterizes mechanism of erosional processes on a landscape. We further compare these topologic characteristics of landscape to geomorphic features such as slope-area curve and drainage density. Furthermore, we identify locations of critical nodes and links on a network as a function of energy exponent γ to understand network robustness and vulnerability under external attacks.

Effects of Coarse Legacy Sediment on Rivers of the Ozark Plateaus and Implications for Native Mussel Fauna

NASA Astrophysics Data System (ADS)

Erwin, S. O.; Jacobson, R. B.; Eric, A. B.; Jones, J. C.; Anderson, B. W.

2015-12-01

Perturbations to sediment regimes due to anthropogenic activities may have long lasting effects, especially in systems dominated by coarse sediment where travel times are relatively long. Effectively evaluating management alternatives requires understanding the future trajectory of river response at both the river network and reach scales. The Ozark Plateaus physiographic province is a montane region in the interior US composed primarily of Paleozoic sedimentary rock. Historic land-use practices around the turn of the last century accelerated delivery of coarse sediment to river channels. Effects of this legacy sediment persist in two national parks, Ozark National Scenic Riverways, MO and Buffalo National River, AR, and are of special concern for management of native mussel fauna. These species require stable habitat, yet they occupy inherently dynamic environments: alluvial rivers. At the river-network scale, analysis of historical data reveals the signature of sediment waves moving through river networks in the Ozarks. Channel planform alternates between relatively stable, straight reaches, and wider, multithread reaches which have been more dynamic over the past several decades. These alternate planform configurations route and store sediment differently, and translate into different patterns of bed stability at the reach scale, which in turn affects the distribution and availability of habitat for native biota. Geomorphic mapping and hydrodynamic modeling reveal the complex relations between planform (in)stability, flow dynamics, bed mobility, and aquatic habitat in systems responding to increased sediment supply. Reaches that have a more dynamic planform may provide more hydraulic refugia and habitat heterogeneity compared to stable, homogeneous reaches. This research provides new insights that may inform management of sediment and mussel habitat in rivers subject to coarse legacy sediment.

Centers for Environmental Education: Guidelines for Success.

ERIC Educational Resources Information Center

Wilson, Terry; Martin, Joan

This report presents a model of collaborative effort that established a network of 15 university-based and 2 non-university based Centers for Environmental Education (CEE) in the Tennessee River watershed region. The report begins by establishing definitions for a Center for Environmental Education and a network system, both of which are…

Applications of spatial statistical network models to stream data

Treesearch

Daniel J. Isaak; Erin E. Peterson; Jay M. Ver Hoef; Seth J. Wenger; Jeffrey A. Falke; Christian E. Torgersen; Colin Sowder; E. Ashley Steel; Marie-Josee Fortin; Chris E. Jordan; Aaron S. Ruesch; Nicholas Som; Pascal Monestiez

2014-01-01

Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for...

Simulating Fish Assemblages in Riverine Networks: Response to Habitat in the Willamette Watershed

EPA Science Inventory

We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the scale and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

Predicting thermal regimes of stream networks across the northeast United States: Natural and anthropogenic influences

EPA Science Inventory

We used STARS (Spatial Tools for the Analysis of River Systems), an ArcGIS geoprocessing toolbox, to create spatial stream networks. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance...

Groundwater-level prediction using multiple linear regression and artificial neural network techniques: a comparative assessment

NASA Astrophysics Data System (ADS)

Sahoo, Sasmita; Jha, Madan K.

2013-12-01

The potential of multiple linear regression (MLR) and artificial neural network (ANN) techniques in predicting transient water levels over a groundwater basin were compared. MLR and ANN modeling was carried out at 17 sites in Japan, considering all significant inputs: rainfall, ambient temperature, river stage, 11 seasonal dummy variables, and influential lags of rainfall, ambient temperature, river stage and groundwater level. Seventeen site-specific ANN models were developed, using multi-layer feed-forward neural networks trained with Levenberg-Marquardt backpropagation algorithms. The performance of the models was evaluated using statistical and graphical indicators. Comparison of the goodness-of-fit statistics of the MLR models with those of the ANN models indicated that there is better agreement between the ANN-predicted groundwater levels and the observed groundwater levels at all the sites, compared to the MLR. This finding was supported by the graphical indicators and the residual analysis. Thus, it is concluded that the ANN technique is superior to the MLR technique in predicting spatio-temporal distribution of groundwater levels in a basin. However, considering the practical advantages of the MLR technique, it is recommended as an alternative and cost-effective groundwater modeling tool.

Snowmelt runoff in the Green River basin derived from MODIS snow extent

NASA Astrophysics Data System (ADS)

Barton, J. S.; Hall, D. K.

2011-12-01

The Green River represents a vital water supply for southwestern Wyoming, northern Colorado, eastern Utah, and the Lower Colorado River Compact states (Arizona, Nevada, and California). Rapid development in the southwestern United States combined with the recent drought has greatly stressed the water supply of the Colorado River system, and concurrently increased the interest in long-term variations in stream flow. Modeling of snowmelt runoff represents a means to predict flows and reservoir storage, which is useful for water resource planning. An investigation is made into the accuracy of the Snowmelt Runoff Model of Martinec and Rango, driven by Moderate Resolution Imaging Spectroradiometer (MODIS) snow maps for predicting stream flow within the Green River basin. While the moderate resolution of the MODIS snow maps limits the spatial detail that can be captured, the daily coverage is an important advantage of the MODIS imagery. The daily MODIS snow extent is measured using the most recent clear observation for each 500-meter pixel. Auxiliary data used include temperature and precipitation time series from the Snow Telemetry (SNOTEL) and Remote Automated Weather Station (RAWS) networks as well as from National Weather Service records. Also from the SNOTEL network, snow-water equivalence data are obtained to calibrate the conversion between snow extent and runoff potential.

Bathymetry of the Hong and Luoc River Junction, Red River Delta, Vietnam, 2010

USGS Publications Warehouse

Kinzel, Paul J.; Nelson, Jonathan M.; Toan, Duong Duc; Thanh, Mung Dinh; Shimizu, Yasuyuki

2012-01-01

The U.S. Geological Survey, in collaboration with the Water Resources University in Hanoi, Vietnam, conducted a bathymetric survey of the junction of the Hong and Luoc Rivers. The survey was done to characterize the channel morphology of this delta distributary network and provide input for hydrodynamic and sediment transport models. The survey was carried out in December 2010 using a boat-mounted multibeam echo sounder integrated with a global positioning system. A bathymetric map of the Hong and Luoc River junction was produced which was referenced to the datum of the Trieu Duong tide gage on the Luoc River.

The multiple stressor ecological risk assessment for the mercury-contaminated South River and upper Shenandoah River using the Bayesian network-relative risk model.

PubMed

Landis, Wayne G; Ayre, Kimberley K; Johns, Annie F; Summers, Heather M; Stinson, Jonah; Harris, Meagan J; Herring, Carlie E; Markiewicz, April J

2017-01-01

We have conducted a regional scale risk assessment using the Bayesian Network Relative Risk Model (BN-RRM) to calculate the ecological risks to the South River and upper Shenandoah River study area. Four biological endpoints (smallmouth bass, white sucker, Belted Kingfisher, and Carolina Wren) and 4 abiotic endpoints (Fishing River Use, Swimming River Use, Boating River Use, and Water Quality Standards) were included in this risk assessment, based on stakeholder input. Although mercury (Hg) contamination was the original impetus for the site being remediated, other chemical and physical stressors were evaluated. There were 3 primary conclusions from the BN-RRM results. First, risk varies according to location, type and quality of habitat, and exposure to stressors within the landscape. The patterns of risk can be evaluated with reasonable certitude. Second, overall risk to abiotic endpoints was greater than overall risk to biotic endpoints. By including both biotic and abiotic endpoints, we are able to compare risk to endpoints that represent a wide range of stakeholder values. Third, whereas Hg reduction is the regulatory priority for the South River, Hg is not the only stressor driving risk to the endpoints. Ecological and habitat stressors contribute risk to the endpoints and should be considered when managing this site. This research provides the foundation for evaluating the risks of multiple stressors of the South River to a variety of endpoints. From this foundation, tools for the evaluation of management options and an adaptive management tools have been forged. Integr Environ Assess Manag 2017;13:85-99. © 2016 SETAC. © 2016 SETAC.

Development of Water Quality Forecasting Models Based on the SOM-ANN on TMDL Unit Watershed in Nakdong River

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, J.; Baek, J.; Kim, C.; Shin, H.

2013-12-01

It has being happened as flush flood or red/green tide in various natural phenomena due to climate change and indiscreet development of river or land. Especially, water being very important to man should be protected and managed from water quality pollution, and in water resources management, real-time watershed monitoring system is being operated with the purpose of keeping watch and managing on rivers. It is especially important to monitor and forecast water quality in watershed. A study area selected Nak_K as one site among TMDL unit watershed in Nakdong River. This study is to develop a water quality forecasting model connected with making full use of observed data of 8 day interval from Nakdong River Environment Research Center. When forecasting models for each of the BOD, DO, COD, and chlorophyll-a are established considering correlation of various water quality factors, it is needed to select water quality factors showing highly considerable correlation with each water quality factor which is BOD, DO, COD, and chlorophyll-a. For analyzing the correlation of the factors (reservoir discharge, precipitation, air temperature, DO, BOD, COD, Tw, TN, TP, chlorophyll-a), in this study, self-organizing map was used and cross correlation analysis method was also used for comparing results drawn. Based on the results, each forecasting model for BOD, DO, COD, and chlorophyll-a was developed during the short period as 8, 16, 24, 32 days at 8 day interval. The each forecasting model is based on neural network with back propagation algorithm. That is, the study is connected with self-organizing map for analyzing correlation among various factors and neural network model for forecasting of water quality. It is considerably effective to manage the water quality in plenty of rivers, then, it specially is possible to monitor a variety of accidents in water quality. It will work well to protect water quality and to prevent destruction of the environment becoming more and more serious before occurring.

Optimal river monitoring network using optimal partition analysis: a case study of Hun River, Northeast China.

PubMed

Wang, Hui; Liu, Chunyue; Rong, Luge; Wang, Xiaoxu; Sun, Lina; Luo, Qing; Wu, Hao

2018-01-09

River monitoring networks play an important role in water environmental management and assessment, and it is critical to develop an appropriate method to optimize the monitoring network. In this study, an effective method was proposed based on the attainment rate of National Grade III water quality, optimal partition analysis and Euclidean distance, and Hun River was taken as a method validation case. There were 7 sampling sites in the monitoring network of the Hun River, and 17 monitoring items were analyzed once a month during January 2009 to December 2010. The results showed that the main monitoring items in the surface water of Hun River were ammonia nitrogen (NH 4 + -N), chemical oxygen demand, and biochemical oxygen demand. After optimization, the required number of monitoring sites was reduced from seven to three, and 57% of the cost was saved. In addition, there were no significant differences between non-optimized and optimized monitoring networks, and the optimized monitoring networks could correctly represent the original monitoring network. The duplicate setting degree of monitoring sites decreased after optimization, and the rationality of the monitoring network was improved. Therefore, the optimal method was identified as feasible, efficient, and economic.

Artificial neural networks applied to flow prediction scenarios in Tomebamba River - Paute watershed, for flood and water quality control and management at City of Cuenca Ecuador

NASA Astrophysics Data System (ADS)

Cisneros, Felipe; Veintimilla, Jaime

2013-04-01

The main aim of this research is to create a model of Artificial Neural Networks (ANN) that allows predicting the flow in Tomebamba River both, at real time and in a certain day of year. As inputs we are using information of rainfall and flow of the stations along of the river. This information is organized in scenarios and each scenario is prepared to a specific area. The information is acquired from the hydrological stations placed in the watershed using an electronic system developed at real time and it supports any kind or brands of this type of sensors. The prediction works very good three days in advance This research includes two ANN models: Back propagation and a hybrid model between back propagation and OWO-HWO. These last two models have been tested in a preliminary research. To validate the results we are using some error indicators such as: MSE, RMSE, EF, CD and BIAS. The results of this research reached high levels of reliability and the level of error are minimal. These predictions are useful for flood and water quality control and management at City of Cuenca Ecuador

Dissolved Nutrient Retention Dynamics in River Networks: A Modeling Investigation of Transient Flow and Scale Effects

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

Ye, Sheng; Covino, Timothy P.; Sivapalan, Murugesu

In this paper, we use a dynamic network flow model, coupled with a transient storage zone biogeochemical model, to simulate dissolved nutrient removal processes at the channel network scale. We have explored several scenarios in respect of the combination of rainfall variability, and the biological and geomorphic characteristics of the catchment, to understand the dominant controls on removal and delivery of dissolved nutrients (e.g., nitrate). These model-based theoretical analyses suggested that while nutrient removal efficiency is lower during flood events compared to during baseflow periods, flood events contribute significantly to bulk nutrient removal, whereas bulk removal during baseflow periods ismore » less. This is due to the fact that nutrient supply is larger during flood events; this trend is even stronger in large rivers. However, the efficiency of removal during both periods decreases in larger rivers, however, due to (i) increasing flow velocities and thus decreasing residence time, and (ii) increasing flow depth, and thus decreasing nutrient uptake rates. Besides nutrient removal processes can be divided into two parts: in the main channel and in the hyporheic transient storage zone. When assessing their relative contributions the size of the transient storage zone is a dominant control, followed by uptake rates in the main channel and in the transient storage zone. Increasing size of the transient storage zone with downstream distance affects the relative contributions to nutrient removal of the water column and the transient storage zone, which also impacts the way nutrient removal rates scale with increasing size of rivers. Intra-annual hydrologic variability has a significant impact on removal rates at all scales: the more variable the streamflow is, compared to mean discharge, the less nutrient is removed in the channel network. A scale-independent first order uptake coefficient, ke, estimated from model simulations, is highly dependent on the relative size of the transient storage zone and how it changes in the downstream direction, as well as the nature of hydrologic variability.« less

River delta network hydraulic residence time distributions and their role in coastal nutrient biogeochemistry

NASA Astrophysics Data System (ADS)

Hiatt, M. R.; Castaneda, E.; Twilley, R.; Hodges, B. R.; Passalacqua, P.

2015-12-01

River deltas have the potential to mitigate increased nutrient loading to coastal waters by acting as biofilters that reduce the impact of nutrient enrichment on downstream ecosystems. Hydraulic residence time (HRT) is known to be a major control on biogeochemical processes and deltaic floodplains are hypothesized to have relatively long HRTs. Hydrological connectivity and delta floodplain inundation induced by riverine forces, tides, and winds likely alter surface water flow patterns and HRTs. Since deltaic floodplains are important elements of delta networks and receive significant fluxes of water, sediment, and nutrients from distributary channels, biogeochemical transformations occurring within these zones could significantly reduce nutrient loading to coastal receiving waters. However, network-scale estimates of HRT in river deltas are lacking and little is known about the effects of tides, wind, and the riverine input on the HRT distribution. Subsequently, there lacks a benchmark for evaluating the impact of engineered river diversions on coastal nutrient ecology. In this study, we estimate the HRT of a coastal river delta by using hydrodynamic modeling supported by field data and relate the HRT to spatial and temporal patterns in nitrate levels measured at discrete stations inside a delta island at Wax Lake Delta. We highlight the control of the degree of hydrological connectivity between distributary channels and interdistributary islands on the network HRT distribution and address the roles of tides and wind on altering the shape of the distribution. We compare the observed nitrate concentrations to patterns of channel-floodplain hydrological connectivity and find this connectivity to play a significant role in the nutrient removal. Our results provide insight into the potential role of deltaic wetlands in reducing the nutrient loading to near-shore waters in response to large-scale river diversions.

Hydrodynamic modeling of hydrologic surface connectivity within a coastal river-floodplain system

NASA Astrophysics Data System (ADS)

Castillo, C. R.; Guneralp, I.

2017-12-01

Hydrologic surface connectivity (HSC) within river-floodplain environments is a useful indicator of the overall health of riparian habitats because it allows connections amongst components/landforms of the riverine landscape system to be quantified. Overbank flows have traditionally been the focus for analyses concerned with river-floodplain connectivity, but recent works have identified the large significance from sub-bankfull streamflows. Through the use of morphometric analysis and a digital elevation model that is relative to the river water surface, we previously determined that >50% of the floodplain for Mission River on the Coastal Bend of Texas becomes connected to the river at streamflows well-below bankfull conditions. Guided by streamflow records, field-based inundation data, and morphometric analysis; we develop a two-dimensional hydrodynamic model for lower portions of Mission River Floodplain system. This model not only allows us to analyze connections induced by surface water inundation, but also other aspects of the hydrologic connectivity concept such as exchanges of sediment and energy between the river and its floodplain. We also aggregate hydrodynamic model outputs to an object/landform level in order to analyze HSC and associated attributes using measures from graph/network theory. Combining physically-based hydrodynamic models with object-based and graph theoretical analyses allow river-floodplain connectivity to be quantified in a consistent manner with measures/indicators commonly used in landscape analysis. Analyzes similar to ours build towards the establishment of a formal framework for analyzing river-floodplain interaction that will ultimately serve to inform the management of riverine/floodplain environments.

Networks within networks: floods, droughts, and the assembly of algal-based food webs in a Mediterranean river

NASA Astrophysics Data System (ADS)

Power, M. E.; Limm, M.; Finlay, J. C.; Welter, J.; Furey, P.; Lowe, R.; Hondzo, M.; Dietrich, W. E.; Bode, C. A.; National CenterEarth Surface Dynamics

2011-12-01

Riverine biota live within several networks. Organisms are embedded in food webs, whose structure and dynamics respond to environmental changes down river drainages. In sunlit rivers, food webs are fueled by attached algae. Primary producer biomass in the Eel River of Northwestern California, as in many sunlit, temperate rivers worldwide, is dominated by the macroalga Cladophora, which grows as a hierarchical, branched network. Cladophora proliferations vastly amplify the ecological surface area and the diversity microhabitats available to microbes. Environmental conditions (light, substrate age or stability, flow, redox gradients) change in partially predictable ways along both Cladophora fronds and river drainage networks, from the frond tips (or headwaters) to their base (or river mouth). We are interested in the ecological and biogeochemical consequences, at the catchment scale, of cross-scale interactions of microbial food webs on Cladophora with macro-organismal food webs, as these change down river drainages. We are beginning to explore how seasonal, hydrologic and macro-consumer control over the production and fate of Cladophora and its epiphytes could mediate ecosystem linkages of the river, its watershed, and nearshore marine ecosystems. Of the four interacting networks we consider, the web of microbial interactions is the most poorly known, and possibly the least hierarchical due to the prevalence of metabolic processing chains (waste products of some members become resources for others) and mutualisms.

Incorporating food web dynamics into ecological restoration: a modeling approach for river ecosystems

Treesearch

J. Ryan Bellmore; Joseph R. Benjamin; Michael Newsom; Jennifer A. Bountry; Daniel Dombroski

2017-01-01

Restoration is frequently aimed at the recovery of target species, but also influences the larger food web in which these species participate. Effects of restoration on this broader network of organisms can influence target species both directly and indirectly via changes in energy flow through food webs. To help incorporate these complexities into river restoration...

The Caloosahatchee River Estuary: a monitoring partnership between Federal, State, and local governments, 2007-13

USGS Publications Warehouse

Patino, Eduardo

2014-01-01

From 2007 to 2013, the U.S. Geological Survey (USGS), in cooperation with the Florida Department of Environmental Protection (FDEP) and the South Florida Water Management District (SFWMD), operated a flow and salinity monitoring network at tributaries flowing into and at key locations within the tidal Caloosahatchee River. This network was designed to supplement existing long-term monitoring stations, such as W.P. Franklin Lock, also known as S–79, which are operated by the USGS in cooperation with the U.S. Army Corps of Engineers, Lee County, and the City of Cape Coral. Additionally, a monitoring station was operated on Sanibel Island from 2010 to 2013 as part of the USGS Greater Everglades Priority Ecosystem Science initiative and in partnership with U.S. Fish and Wildlife Service (J.N. Ding Darling National Wildlife Refuge). Moving boat water-quality surveys throughout the tidal Caloosahatchee River and downstream estuaries began in 2011 and are ongoing. Information generated by these monitoring networks has proved valuable to the FDEP for developing total maximum daily load criteria, and to the SFWMD for calibrating and verifying a hydrodynamic model. The information also supports the Caloosahatchee River Watershed Protection Plan.

Evolution of continental-scale drainage in response to mantle dynamics and surface processes: An example from the Ethiopian Highlands

NASA Astrophysics Data System (ADS)

Sembroni, Andrea; Molin, Paola; Pazzaglia, Frank J.; Faccenna, Claudio; Abebe, Bekele

2016-05-01

Ethiopia offers an excellent opportunity to study the effects and linkage between mantle dynamics and surface processes on landscape evolution. The Ethiopian Highlands (NW Ethiopia), characterized by a huge basaltic plateau, is part of the African Superswell, a wide region of dynamically-supported anomalously high topography related to the rising of the Afar plume. The initiation and steadiness of dynamic support beneath Ethiopia has been explored in several studies. However the presence, role, and timing of dynamic support beneath Ethiopia and its relationship with continental flood basalts volcanism and surface processes are poorly defined. Here, we present a geomorphological analysis of the Ethiopian Highlands supplying new constraints on the evolution of river network. We investigated the general topographic features (filtered topography, swath profiles, local relief) and the river network (river longitudinal profiles) of the study area. We also apply a knickpoint celerity model in order to provide a chronological framework to the evolution of the river network. The results trace the long-term progressive capture of the Ethiopian Highlands drainage system and confirm the long-term dynamic support of the area, documenting its impact on the contrasting development of the Blue Nile and Tekeze basins.

Evolution of continental-scale drainage in response to mantle dynamics and surface processes: an example from the Ethiopian Highlands.

NASA Astrophysics Data System (ADS)

Sembroni, Andrea; Molin, Paola; Pazzaglia, Frank J.; Faccenna, Claudio; Abebe, Bekele

2016-04-01

Ethiopia offers an excellent opportunity to study the effects and linkage between mantle dynamics and surface processes on landscape evolution. The Ethiopian Highlands (NW Ethiopia), characterized by a huge basaltic plateau, is part of the African Superswell, a wide region of dynamically-supported anomalously high topography related to the rising of the Afar plume. The initiation and steadiness of dynamic support beneath Ethiopia has been explored in several studies. However the presence, role, and timing of dynamic support beneath Ethiopia and its relationship with continental flood basalts volcanism and surface processes are poorly defined. Here, we present a geomorphological analysis of the Ethiopian Highlands supplying new constrains on the evolution of river network. We investigated the general topographic features (filtered topography, swath profiles, local relief) and the river network (river longitudinal profiles) of the study area. We also apply a knickpoint celerity model in order to provide a chronological framework to the evolution of the river network. The results trace the long-term progressive capture of the Ethiopian Highlands drainage system and confirm the long-term dynamic support of the area, documenting its impact on the contrasting development of the Blue Nile and Tekeze basins.

Geographical influences of an emerging network of gang rivalries

NASA Astrophysics Data System (ADS)

Hegemann, Rachel A.; Smith, Laura M.; Barbaro, Alethea B. T.; Bertozzi, Andrea L.; Reid, Shannon E.; Tita, George E.

2011-10-01

We propose an agent-based model to simulate the creation of street gang rivalries. The movement dynamics of agents are coupled to an evolving network of gang rivalries, which is determined by previous interactions among agents in the system. Basic gang data, geographic information, and behavioral dynamics suggested by the criminology literature are integrated into the model. The major highways, rivers, and the locations of gangs’ centers of activity influence the agents’ motion. We use a policing division of the Los Angeles Police Department as a case study to test our model. We apply common metrics from graph theory to analyze our model, comparing networks produced by our simulations and an instance of a Geographical Threshold Graph to the existing network from the criminology literature.

Nitrous oxide emission from denitrification in stream and river networks

PubMed Central

Beaulieu, Jake J.; Tank, Jennifer L.; Hamilton, Stephen K.; Wollheim, Wilfred M.; Hall, Robert O.; Mulholland, Patrick J.; Peterson, Bruce J.; Ashkenas, Linda R.; Cooper, Lee W.; Dahm, Clifford N.; Dodds, Walter K.; Grimm, Nancy B.; Johnson, Sherri L.; McDowell, William H.; Poole, Geoffrey C.; Valett, H. Maurice; Arango, Clay P.; Bernot, Melody J.; Burgin, Amy J.; Crenshaw, Chelsea L.; Helton, Ashley M.; Johnson, Laura T.; O'Brien, Jonathan M.; Potter, Jody D.; Sheibley, Richard W.; Sobota, Daniel J.; Thomas, Suzanne M.

2011-01-01

Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N2O via microbial denitrification that converts N to N2O and dinitrogen (N2). The fraction of denitrified N that escapes as N2O rather than N2 (i.e., the N2O yield) is an important determinant of how much N2O is produced by river networks, but little is known about the N2O yield in flowing waters. Here, we present the results of whole-stream 15N-tracer additions conducted in 72 headwater streams draining multiple land-use types across the United States. We found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3−) concentrations, but that <1% of denitrified N is converted to N2O. Unlike some previous studies, we found no relationship between the N2O yield and stream water NO3−. We suggest that increased stream NO3− loading stimulates denitrification and concomitant N2O production, but does not increase the N2O yield. In our study, most streams were sources of N2O to the atmosphere and the highest emission rates were observed in streams draining urban basins. Using a global river network model, we estimate that microbial N transformations (e.g., denitrification and nitrification) convert at least 0.68 Tg·y−1 of anthropogenic N inputs to N2O in river networks, equivalent to 10% of the global anthropogenic N2O emission rate. This estimate of stream and river N2O emissions is three times greater than estimated by the Intergovernmental Panel on Climate Change. PMID:21173258

Nutrient mitigation in a temporary river basin.

PubMed

Tzoraki, Ourania; Nikolaidis, Nikolaos P; Cooper, David; Kassotaki, Elissavet

2014-04-01

We estimate the nutrient budget in a temporary Mediterranean river basin. We use field monitoring and modelling tools to estimate nutrient sources and transfer in both high and low flow conditions. Inverse modelling by the help of PHREEQC model validated the hypothesis of a losing stream during the dry period. Soil and Water Assessment Tool model captured the water quality of the basin. The 'total daily maximum load' approach is used to estimate the nutrient flux status by flow class, indicating that almost 60% of the river network fails to meet nitrogen criteria and 50% phosphate criteria. We recommend that existing well-documented remediation measures such as reforestation of the riparian area or composting of food process biosolids should be implemented to achieve load reduction in close conjunction with social needs.

Early Mars Climate Revisited With a Global Probability Map of Martian Valley Network Origin and Distribution

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.; Osinski, G. R.

2016-12-01

Valley networks are among the most arresting features on the surface of Mars. Their provocative morphologic resemblance to river valleys on Earth has lead many scientists to argue for Martian river valleys in a "warm and wet" climate scenario, with conditions similar to the terrestrial mid-to-low latitudes. However, this warm scenario is difficult to reconcile with climate models for an Early Mars receiving radiation from a fainter young Sun. Moreover, recent models suggest a colder scenario, with conditions more similar to present day Greenland or Antarctica. Here we use three independent characterization schemes to show quantitative evidence for fluvial, glacial, groundwater sapping and subglacial meltwater channels to build the first global probability map of Martian valley networks. We distinguish a SW-NE corridor of fluvial drainage networks spanning latitudes from 30ºS to 30ºN. We identify additional widespread patterns related to glaciation, subglacial drainage and channels incised by groundwater springs. This global characterization of Martian valleys has profound implications for the average climate of early Mars as well as its variability in space and time.

River network and watershed morphology analysis with potential implications towards basin classification

NASA Astrophysics Data System (ADS)

Bugaets, Andrey; Gartsman, Boris; Bugaets, Nadezhda

2013-04-01

Generally, the investigation of river network composition and watersheds morphology (fluvial geomorphology), constituting one of the key patterns of land surface, is a fundamental question of Earth Sciences. Recent ideas in this research field are the equilibrium and optimal, in the sense of minimum energy expenditure, river network evolution under constant or slowly varying conditions (Rodriguez-Iturbe, Rinaldo, 1997). It follows to such network behavior as self-similarity, self-affinity and self-organization. That is to say, under relatively stable conditions the river systems tend to some "good composed" form and vice-versa. Lately appearing global free available detailed DEM covers involve new possibilities in this research field. We develop new methodology and program package for river network structure and watershed morphology detailed analysis on the base of ArcMap tools. Different characteristics of river network (e.g. ordering, coefficients of Horton's laws, Shannon entropy, fractal dimension) and basin morphology (e.g. diagrams of average elevation, slope, width and energy index against distance to outlet along streams) could be calculated to find a good indicators of intensity and non-equilibrium of watershed evolution. Watersheds are non-conservative systems in which energy is dissipated by transporting water and sediment in geomorphic adjustment of the slopes and channels. The problem of estimating the amount of energy expenditure associated with overcoming surface and system resistance is extremely complicated to solve. A simplification on a river network scale is to consider energy expenditure to be primarily associated with friction of the fluid. We propose a new technique to analyze the catchment landforms based on so-called "energy function" that is a distribution of total energy index against distance from outlet. As potential energy of water on the hillslopes is transformed into kinetic energy of the flowing fluid-sediment mixture in the runoff process, the energy is dissipated from the system. The rate of energy dissipation is defined as the work that a fluid element needs to perform to overcome friction at the unit area. Appling the product of local slope and watershed area, i.e. calculating the total energy index at the different distance from outlet, one gets the watershed "energy function" E(x). Application results indicate that the proposed method could be used for watersheds classification, regionalization and paleoreconstructions. NASA-SRTM DEM of 3" resolution has been employed to analyze the 24 watersheds within Amur River Basin with area 20-70 thousand km2 (7-8 order). The study was carried out, in particular, to assess the limitation of SRTM DEM data, especially in flat terrains. The study also revealed that some of regularities investigated are described satisfactorily by well-known simplest model of drainage networks, so-called Peano's basin.

Synchronisation and stability in river metapopulation networks.

PubMed

Yeakel, J D; Moore, J W; Guimarães, P R; de Aguiar, M A M

2014-03-01

Spatial structure in landscapes impacts population stability. Two linked components of stability have large consequences for persistence: first, statistical stability as the lack of temporal fluctuations; second, synchronisation as an aspect of dynamic stability, which erodes metapopulation rescue effects. Here, we determine the influence of river network structure on the stability of riverine metapopulations. We introduce an approach that converts river networks to metapopulation networks, and analytically show how fluctuation magnitude is influenced by interaction structure. We show that river metapopulation complexity (in terms of branching prevalence) has nonlinear dampening effects on population fluctuations, and can also buffer against synchronisation. We conclude by showing that river transects generally increase synchronisation, while the spatial scale of interaction has nonlinear effects on synchronised dynamics. Our results indicate that this dual stability - conferred by fluctuation and synchronisation dampening - emerges from interaction structure in rivers, and this may strongly influence the persistence of river metapopulations. © 2013 John Wiley & Sons Ltd/CNRS.

Assessing the impacts of climate change and dams on floodplain inundation and wetland connectivity in the wet-dry tropics of northern Australia

NASA Astrophysics Data System (ADS)

Karim, Fazlul; Dutta, Dushmanta; Marvanek, Steve; Petheram, Cuan; Ticehurst, Catherine; Lerat, Julien; Kim, Shaun; Yang, Ang

2015-03-01

Floodplain wetlands and their hydrological connectivity with main river channels in the Australian wet-dry tropics are under increasing pressure from global climate change and water resource development, and there is a need for modelling tools to estimate the time dynamics of connectivity. This paper describes an integrated modelling framework combining conceptual rainfall-runoff modelling, river system modelling and hydrodynamic (HD) modelling to estimate hydrological connectivity between wetlands and rivers in the Flinders and Gilbert river catchments in northern Australia. Three historical flood events ranging from a mean annual flood to a 35-year return period flood were investigated using a two dimensional HD model (MIKE 21). Inflows from upstream catchments were estimated using a river network model. Local runoff within the HD modelling domain was simulated using the Sacramento rainfall-runoff model. The Shuttle Radar Topography Mission (SRTM) derived 30 m DEM was used to reproduce floodplain topography, stream networks and wetlands in the HD model. The HD model was calibrated using stream gauge data and inundation maps derived from satellite (MODIS: MODerate resolution Imaging Spectroradiometer) imagery. An algorithm was developed to combine the simulated water heights with the DEM to quantify inundation and flow connection between wetlands and rivers. The connectivity of 18 ecologically important wetlands on the Flinders floodplain and 7 on the Gilbert floodplain were quantified. The impacts of climate change and water resource development on connectivity to individual wetlands were assessed under a projected dry climate (2nd driest of 15 GCMs), wet climate (2nd wettest of 15 GCMs) and dam conditions. The results indicate that changes in rainfall under a wetter and drier future climate could have large impacts on area, duration and frequency of inundation and connectivity. Topographic relief, river bank elevation and flood magnitude were found to be the key factors contributing to the level of connectivity. Under a wetter future climate the average duration of connection of wetlands to the main river channel increased by 7% and under a drier climate it decreased by 18%. Construction of a 248 GL dam in the Flinders catchment and two (498 and 271 GL capacity) in the Gilbert catchment could reduce the average duration of connectivity by 1% and 2% in the Flinders and Gilbert catchments respectively. This information is potentially useful to future studies on the flood-dependent ecology in this region.

What impact might mitigation of diffuse nitrate pollution have on river water quality in a rural catchment?

PubMed

Hutchins, Michael G

2012-10-30

Observations of river flow, river quality and solar radiation were collated to assess the degree to which light and nutrients may be limiting phytoplankton growth at seven sites in the River Ouse catchment in NE England under average conditions. Hydraulic information derived from river network model applications was then used to determine where river water has sufficient residence time above the tidal limit to facilitate bloom development. A nitrate model (NALTRACES) was developed to estimate the impact of land management change on mean river nitrate concentrations. Applications of this model showed that although agricultural activity contributes substantially to nitrate loads in the Ouse it is likely to have little impact on phytoplankton growth, which could still occur extensively in its absence given favourable sunny and dry conditions. As an example of a means of controlling light availability, establishing full riparian tree cover would appear to be a considerably more effective management scenario than suppressing inputs to the river of nitrate or phosphorus. Any actions should be prioritised in headwater areas such as the upper reaches of the Swale and Ure tributaries. These conclusions are in broad agreement with those arising from more detailed simulations at daily resolution using the QUESTOR river quality model. The combination of simple modelling approaches applied here allows an initial identification of suitable spatially-targeted options for mitigating against phytoplankton blooms which can be applied more widely at a regional or national level. Copyright © 2012 Elsevier Ltd. All rights reserved.

Potential of commercial microwave link network derived rainfall for river runoff simulations

NASA Astrophysics Data System (ADS)

Smiatek, Gerhard; Keis, Felix; Chwala, Christian; Fersch, Benjamin; Kunstmann, Harald

2017-03-01

Commercial microwave link networks allow for the quantification of path integrated precipitation because the attenuation by hydrometeors correlates with rainfall between transmitter and receiver stations. The networks, operated and maintained by cellphone companies, thereby provide completely new and country wide precipitation measurements. As the density of traditional precipitation station networks worldwide is significantly decreasing, microwave link derived precipitation estimates receive increasing attention not only by hydrologists but also by meteorological and hydrological services. We investigate the potential of microwave derived precipitation estimates for streamflow prediction and water balance analyses, exemplarily shown for an orographically complex region in the German Alps (River Ammer). We investigate the additional value of link derived rainfall estimations combined with station observations compared to station and weather radar derived values. Our river runoff simulation system employs a distributed hydrological model at 100 × 100 m grid resolution. We analyze the potential of microwave link derived precipitation estimates for two episodes of 30 days with typically moderate river flow and an episode of extreme flooding. The simulation results indicate the potential of this novel precipitation monitoring method: a significant improvement in hydrograph reproduction has been achieved in the extreme flooding period that was characterized by a large number of local strong precipitation events. The present rainfall monitoring gauges alone were not able to correctly capture these events.

Assessing Impacts of Hydropower Regulation on Salmonid Habitat Connectivity to Guide River Restoration

NASA Astrophysics Data System (ADS)

Buddendorf, Bas; Geris, Josie; Malcolm, Iain; Wilkinson, Mark; Soulsby, Chris

2016-04-01

Anthropogenic activity in riverine ecosystems has led to a substantial divergence from the natural state of many rivers globally. Many of Scotland's rivers have been regulated for hydropower with increasing intensity since the 1890s. At the same time they sustain substantial populations of Atlantic Salmon (Salmo salar L.), which have a range of requirements in terms of flow and access to habitat, depending on the different life-stages. River barriers for hydropower regulation can change the spatial and temporal connectivity within river networks, the impacts of which on salmon habitat are not fully understood. Insight into such changes in connectivity, and the link with the distribution and accessibility of suitable habitat and areas of high productivity, are essential to aid restoration and/or conservation efforts. This is because they indicate where such efforts might have a higher chance of being successful in terms of providing suitable habitat and increasing river productivity. In this study we applied a graph theory approach to assess historic (natural) and contemporary (regulated) in-stream habitat connectivity of the River Lyon, an important UK salmon river that is moderately regulated for hydropower. Historic maps and GIS techniques were used to construct the two contrasting river networks (i.e., natural vs. regulated). Subsequently, connectivity metrics were used to assess the impacts of hydropower infrastructure on upstream and downstream migration possibilities for adults and juveniles, respectively. A national juvenile salmon production model was used to weight the importance of reaches for juvenile salmon production. Results indicate that the impact of barriers in the Lyon on the connectivity indices depends on the type of barrier and its location within the network, but is generally low for both adults and juveniles, and that compared to the historic river network the reduction in the amount of suitable habitat and juvenile production is most marked in the upper reaches of the river. This study represents an improved approach over more commonly applied assessments that focus on the impact of impoundment on wetted area or river length. Simpler approaches often lack ecological and hydrological detail leading to over- or underestimation of the impacts of river regulation on connectivity depending on the relative quality of available habitat. Our work aims to integrate hydrological and ecological aspects into a spatially explicit connectivity framework. Such an approach can help to better identify those areas most important to the conservation of fish habitat, inform sustainable management of hydropower schemes, and aid cost-efficient river restoration and management efforts.

Simulation of river stage using artificial neural network and MIKE 11 hydrodynamic model

NASA Astrophysics Data System (ADS)

Panda, Rabindra K.; Pramanik, Niranjan; Bala, Biplab

2010-06-01

Simulation of water levels at different sections of a river using physically based flood routing models is quite cumbersome, because it requires many types of data such as hydrologic time series, river geometry, hydraulics of existing control structures and channel roughness coefficients. Normally in developing countries like India it is not easy to collect these data because of poor monitoring and record keeping. Therefore, an artificial neural network (ANN) technique is used as an effective alternative in hydrologic simulation studies. The present study aims at comparing the performance of the ANN technique with a widely used physically based hydrodynamic model in the MIKE 11 environment. The MIKE 11 hydrodynamic model was calibrated and validated for the monsoon periods (June-September) of the years 2006 and 2001, respectively. Feed forward neural network architecture with Levenberg-Marquardt (LM) back propagation training algorithm was used to train the neural network model using hourly water level data of the period June-September 2006. The trained ANN model was tested using data for the same period of the year 2001. Simulated water levels by the MIKE 11HD were compared with the corresponding water levels predicted by the ANN model. The results obtained from the ANN model were found to be much better than that of the MIKE 11HD results as indicated by the values of the goodness of fit indices used in the study. The Nash-Sutcliffe index ( E) and root mean square error (RMSE) obtained in case of the ANN model were found to be 0.8419 and 0.8939 m, respectively, during model testing, whereas in case of MIKE 11HD, the values of E and RMSE were found to be 0.7836 and 1.00 m, respectively, during model validation. The difference between the observed and simulated peak water levels obtained from the ANN model was found to be much lower than that of MIKE 11HD. The study reveals that the use of Levenberg-Marquardt algorithm with eight hidden neurons in the hidden layer is sufficient to produce satisfactory results.

An Integrated Decision Support System for Water Quality Management of Songhua River Basin

NASA Astrophysics Data System (ADS)

Zhang, Haiping; Yin, Qiuxiao; Chen, Ling

2010-11-01

In the Songhua River Basin of China, many water resource and water environment conflicts interact. A Decision Support System (DSS) for the water quality management has been established for the Basin. The System is featured by the incorporation of a numerical water quality model system into a conventional water quality management system which usually consists of geographic information system (GIS), WebGIS technology, database system and network technology. The model system is built based on DHI MIKE software comprising of a basin rainfall-runoff module, a basin pollution load evaluation module, a river hydrodynamic module and a river water quality module. The DSS provides a friendly graphical user interface that enables the rapid and transparent calculation of various water quality management scenarios, and also enables the convenient access and interpretation of the modeling results to assist the decision-making.

River suspended sediment estimation by climatic variables implication: Comparative study among soft computing techniques

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Shiri, Jalal

2012-06-01

Estimating sediment volume carried by a river is an important issue in water resources engineering. This paper compares the accuracy of three different soft computing methods, Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Gene Expression Programming (GEP), in estimating daily suspended sediment concentration on rivers by using hydro-meteorological data. The daily rainfall, streamflow and suspended sediment concentration data from Eel River near Dos Rios, at California, USA are used as a case study. The comparison results indicate that the GEP model performs better than the other models in daily suspended sediment concentration estimation for the particular data sets used in this study. Levenberg-Marquardt, conjugate gradient and gradient descent training algorithms were used for the ANN models. Out of three algorithms, the Conjugate gradient algorithm was found to be better than the others.

Establishing a Multi-scale Stream Gaging Network in the Whitewater River Basin, Kansas, USA

USGS Publications Warehouse

Clayton, J.A.; Kean, J.W.

2010-01-01

Investigating the routing of streamflow through a large drainage basin requires the determination of discharge at numerous locations in the channel network. Establishing a dense network of stream gages using conventional methods is both cost-prohibitive and functionally impractical for many research projects. We employ herein a previously tested, fluid-mechanically based model for generating rating curves to establish a stream gaging network in the Whitewater River basin in south-central Kansas. The model was developed for the type of channels typically found in this watershed, meaning that it is designed to handle deep, narrow geomorphically stable channels with irregular planforms, and can model overbank flow over a vegetated floodplain. We applied the model to ten previously ungaged stream reaches in the basin, ranging from third- to sixth-order channels. At each site, detailed field measurements of the channel and floodplain morphology, bed and bank roughness, and vegetation characteristics were used to quantify the roughness for a range of flow stages, from low flow to overbank flooding. Rating curves that relate stage to discharge were developed for all ten sites. Both fieldwork and modeling were completed in less than 2 years during an anomalously dry period in the region, which underscores an advantage of using theoretically based (as opposed to empirically based) discharge estimation techniques. ?? 2010 Springer Science+Business Media B.V.

Statistical self-similarity of width function maxima with implications to floods

USGS Publications Warehouse

Veitzer, S.A.; Gupta, V.K.

2001-01-01

Recently a new theory of random self-similar river networks, called the RSN model, was introduced to explain empirical observations regarding the scaling properties of distributions of various topologic and geometric variables in natural basins. The RSN model predicts that such variables exhibit statistical simple scaling, when indexed by Horton-Strahler order. The average side tributary structure of RSN networks also exhibits Tokunaga-type self-similarity which is widely observed in nature. We examine the scaling structure of distributions of the maximum of the width function for RSNs for nested, complete Strahler basins by performing ensemble simulations. The maximum of the width function exhibits distributional simple scaling, when indexed by Horton-Strahler order, for both RSNs and natural river networks extracted from digital elevation models (DEMs). We also test a powerlaw relationship between Horton ratios for the maximum of the width function and drainage areas. These results represent first steps in formulating a comprehensive physical statistical theory of floods at multiple space-time scales for RSNs as discrete hierarchical branching structures. ?? 2001 Published by Elsevier Science Ltd.

Catchment controls on water temperature and the development of simple metrics to inform riparian zone management

NASA Astrophysics Data System (ADS)

Johnson, Matthew; Wilby, Robert

2015-04-01

Water temperature is a key water quality parameter and is critical to aquatic life Therefore, rising temperatures due to climate and environmental change will have major consequences for river biota. As such, it is important to understand the environmental controls of the thermal regime of rivers. The Loughborough University TEmperature Network (LUTEN) consists of a distributed network of 25 sites along 40 km of two rivers in the English Peak District, from their source to confluence. As a result, the network covers a range of hydrological, sedimentary, geomorphic and land-use conditions. At each site, air and water temperature have been recorded at a 15-minute resolution for over 4 years. Water temperature is spatially patchy and temporally variable in the monitored rivers. For example, the annual temperature range at Beresford Dale is over 18° C, whereas 8 km downstream it is less than 8° C. This heterogeneity leads to some sites being more vulnerable to future warming than others. The sensitivity of sites to climate was quantified by comparing the parameters of logistic regression models, constructed at each site, that relate water temperature to air temperature. These analyses, coupled with catchment modelling suggest that reaches that are surface-water dominated with minimal shade and relatively low water volumes are most susceptible to warming. Such reaches tended to occur at intermediate distances from rivers source in the monitored catchments. Reaches that were groundwater dominated had relatively stable thermal regimes, which were relatively unaffected by inter-annual changes in climatic conditions. Such areas could provide important thermal refuge to many organisms, which is supported by monitoring of the invertebrate community in the catchment. The phenology (i.e. timing of life events) of some species remained consistent between years in a river reach with a stable thermal regime, but changed markedly in other areas of the river. Consequently, areas of thermal refuge could be important in the context of future climate change, potentially maintaining populations of animals excluded from other parts of the river during hot summer months. International management strategies to mitigate rising temperatures tend to focus on the protection, enhancement or creation of riparian shade. Simple metrics derived from catchment landscape models, the heat capacity of water, and modelled solar radiation receipt, suggest that approximately 1 km of deep riparian shading is necessary to offset a 1° C rise in temperature in the monitored catchments. A similar value is likely to be obtained for similar sized rivers at similar latitudes. Trees would take 20 years to attain sufficient height to shade the necessary solar angles. However, 1 km of deep riparian shade will have substantial impacts on the hydrological and geomorphological functioning of the river, beyond simply altering the thermal regime. Consequently, successful management of rising water temperature in rivers will require catchment scale consideration, as part of an integrated management plan.

Explore the impacts of river flow and quality on biodiversity for water resources management by AI techniques

NASA Astrophysics Data System (ADS)

Chang, Fi-John; Tsai Tsai, Wen-Ping; Chang, Li-Chiu

2016-04-01

Water resources development is very challenging in Taiwan due to her diverse geographic environment and climatic conditions. To pursue sustainable water resources development, rationality and integrity is essential for water resources planning. River water quality and flow regimes are closely related to each other and affect river ecosystems simultaneously. This study aims to explore the complex impacts of water quality and flow regimes on fish community in order to comprehend the situations of the eco-hydrological system in the Danshui River of northern Taiwan. To make an effective and comprehensive strategy for sustainable water resources management, this study first models fish diversity through implementing a hybrid artificial neural network (ANN) based on long-term observational heterogeneity data of water quality, stream flow and fish species in the river. Then we use stream flow to estimate the loss of dissolved oxygen based on back-propagation neural networks (BPNNs). Finally, the non-dominated sorting genetic algorithm II (NSGA-II) is established for river flow management over the Shihmen Reservoir which is the main reservoir in this study area. In addition to satisfying the water demands of human beings and ecosystems, we also consider water quality for river flow management. The ecosystem requirement takes the form of maximizing fish diversity, which can be estimated by the hybrid ANN. The human requirement is to provide a higher satisfaction degree of water supply while the water quality requirement is to reduce the loss of dissolved oxygen in the river among flow stations. The results demonstrate that the proposed methodology can offer diversified alternative strategies for reservoir operation and improve reservoir operation strategies for producing downstream flows that could better meet both human and ecosystem needs as well as maintain river water quality. Keywords: Artificial intelligence (AI), Artificial neural networks (ANNs), Non-dominated sorting genetic algorithm II (NSGA-II), Sustainable water resources management, Flow regime, River ecosystem.

Prediction of Suspended Sediment in Rivers Using Artificial Neural Networks: Implications for Development of Sediment Budgets

NASA Astrophysics Data System (ADS)

Hamshaw, S. D.; Underwood, K.; Rizzo, D.; Wemple, B. C.; Dewoolkar, M.

2013-12-01

Over 1,000 river miles in Vermont are either impaired or stressed by excessive sedimentation. The higher streamflows and incised river channels have resulted in increased bed and bank erosion. As the climate in Vermont is expected to feature greater and more frequent precipitation events and winter rainfall, the potential for increased sediment loading from erosion processes in the watershed and along the channel are high and a major concern for water resource managers. Typical sediment monitoring comprises periodic sampling during storm events and is often limited to gauged streams with flow data. Continuous turbidity monitoring enhances our understanding of river dynamics by offering high-resolution, temporal measurements to better quantify the total sediment loading occurring during and between storm events. Artificial neural networks, that mimic learning patterns of the human brain, have been effective at predicting flow in small, ungauged rivers using local climate data. This study advances this technology by using an ANN algorithm known as a counter-propagation neural network (CPNN) to predict discharge and suspended sediment in small streams. The first distributed network of continuous turbidity sensors (DTS-12) was deployed in Vermont in the Mad River Watershed, located in Central Vermont. The Mad River and five tributaries were selected as a test bed because seven years of periodic turbidity sampling data are available, it represents a range of watershed characteristics, and because the watershed is also being used for hydrologic model development using the Distributed-Hydrology-Soils-Vegetation Model (DHSVM). Comparison with the DHSVM simulations will allow estimation of the most-likely sources of sediment from the entire watershed and individual subwatersheds. In addition, recent field studies have commenced the quantification of erosion occurring from unpaved roads and streambanks in the same watershed. Periodic water quality sampling during storm events enabled turbidity versus TSS relationships to be established. Sub-watersheds with monitored turbidity and stage also have 15-minute precipitation, soil moisture and air and water temperature data being collected. Stage sensors and theoretical rating curves developed using HEC-RAS and calibrated with discharge measurements are used to validate the flow predictions from the CPNN. The real-time turbidity data are used to train and test the suspended sediment predictions from the CPNN network at each site. The turbidity data are also used to train the CPNN on a subset of tributaries and test on the remaining subwatersheds. Reasonable estimates of suspended sediment discharged from the tributaries and the main stem of the Mad River are calculated and compared enabling a more accurate foundation for building a sediment budget. Results of this study will assist managers in prioritizing mitigation projects to reduce impacts of sediment loading.

A non-conventional watershed partitioning method for semi-distributed hydrological modelling: the package ALADHYN

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Pagani, Alessandro; Rulli, Maria Cristina; Rosso, Renzo

2002-02-01

The extraction of the river network from a digital elevation model (DEM) plays a fundamental role in modelling spatially distributed hydrological processes. The present paper deals with a new two-step procedure based on the preliminary identification of an ideal drainage network (IDN) from contour lines through a variable mesh size, and the further extraction of the actual drainage network (AND) from the IDN using land morphology. The steepest downslope direction search is used to identify individual channels, which are further merged into a network path draining to a given node of the IDN. The contributing area, peaks and saddles are determined by means of a steepest upslope direction search. The basin area is thus partitioned into physically based finite elements enclosed by irregular polygons. Different methods, i.e. the constant and variable threshold area methods, the contour line curvature method, and a topologic method descending from the Hortonian ordering scheme, are used to extract the ADN from the IDN. The contour line curvature method is shown to provide the most appropriate method from a comparison with field surveys. Using the ADN one can model the hydrological response of any sub-basin using a semi-distributed approach. The model presented here combines storm abstraction by the SCS-CN method with surface runoff routing as a geomorphological dispersion process. This is modelled using the gamma instantaneous unit hydrograph as parameterized by river geomorphology. The results are implemented using a project-oriented software facility for the Analysis of LAnd Digital HYdrological Networks (ALADHYN).

Influence of multi-scale hydrologic controls on river network connectivity and riparian function

EPA Science Inventory

The ecological functions of rivers and streams and their associated riparian zones are strongly influenced by surface and subsurface hydrologic routing of water within river basins and river networks. Hydrologic attributes of the riparian area for a given stream reach are typica...

High-efficient Extraction of Drainage Networks from Digital Elevation Model Data Constrained by Enhanced Flow Enforcement from Known River Map

NASA Astrophysics Data System (ADS)

Wu, T.; Li, T.; Li, J.; Wang, G.

2017-12-01

Improved drainage network extraction can be achieved by flow enforcement whereby information of known river maps is imposed to the flow-path modeling process. However, the common elevation-based stream burning method can sometimes cause unintended topological errors and misinterpret the overall drainage pattern. We presented an enhanced flow enforcement method to facilitate accurate and efficient process of drainage network extraction. Both the topology of the mapped hydrography and the initial landscape of the DEM are well preserved and fully utilized in the proposed method. An improved stream rasterization is achieved here, yielding continuous, unambiguous and stream-collision-free raster equivalent of stream vectors for flow enforcement. By imposing priority-based enforcement with a complementary flow direction enhancement procedure, the drainage patterns of the mapped hydrography are fully represented in the derived results. The proposed method was tested over the Rogue River Basin, using DEMs with various resolutions. As indicated by the visual and statistical analyses, the proposed method has three major advantages: (1) it significantly reduces the occurrences of topological errors, yielding very accurate watershed partition and channel delineation, (2) it ensures scale-consistent performance at DEMs of various resolutions, and (3) the entire extraction process is well-designed to achieve great computational efficiency.

Marginal economic value of streamflow: A case study for the Colorado River Basin

Treesearch

Thomas C. Brown; Benjamin L. Harding; Elizabeth A. Payton

1990-01-01

The marginal economic value of streamflow leaving forested areas in the Colorado River Basin was estimated by determining the impact on water use of a small change in streamflow and then applying economic value estimates to the water use changes. The effect on water use of a change in streamflow was estimated with a network flow model that simulated salinity levels and...

SIMULATING FISH ASSEMBLAGE DYNAMICS IN RIVER NETWORKS

EPA Science Inventory

My recently retired colleague, Joan Baker, and I have developed a prototype computer simulation model for studying the effects of human and non-human alterations of habitats and species availability on fish assemblage populations. The fish assemblage model, written in R, is a sp...

Variation of dissolved organic carbon transported by two Chinese rivers: The Changjiang River and Yellow River.

PubMed

Liu, Dong; Pan, Delu; Bai, Yan; He, Xianqiang; Wang, Difeng; Zhang, Lin

2015-11-15

Real-time monitoring of riverine dissolved organic carbon (DOC) and the associated controlling factors is essential to coastal ocean management. This study was the first to simulate the monthly DOC concentrations at the Datong Hydrometric Station for the Changjiang River and at the Lijin Hydrometric Station for the Yellow River from 2000 to 2013 using a multilayer back-propagation neural network (MBPNN), along with basin remote-sensing products and river in situ data. The average absolute error between the modeled values and in situ values was 9.98% for the Changjiang River and 10.84% for the Yellow River. As an effect of water dilution, the variations of DOC concentrations in the two rivers were significantly negatively affected by discharge, with lower values reported during the wet season. Moreover, vegetation growth status and agricultural activities, represented by the gross primary product (GPP) and cropland area percent (CropPer) in the river basin, respectively, also significantly affected the DOC concentration in the Changjiang River, but not the Yellow River. The monthly riverine DOC flux was calculated using modeled DOC concentrations. In particular, the riverine DOC fluxes were affected by discharge, with 71.06% being reported for the Changjiang River and 90.71% for the Yellow River. Over the past decade, both DOC concentration and flux in the two rivers have not shown significant changes. Copyright © 2015 Elsevier Ltd. All rights reserved.

An expanded role for river networks

Treesearch

Jonathan P. Benstead; David S. Leigh

2012-01-01

Estimates of stream and river area have relied on observations at coarse resolution. Consideration of the smallest and most dynamic streams could reveal a greater role for river networks in global biogeochemical cycling than previously thought.

Patterns in CH4 and CO2 concentrations across boreal rivers: Major drivers and implications for fluvial greenhouse emissions under climate change scenarios.

PubMed

Campeau, Audrey; Del Giorgio, Paul A

2014-04-01

It is now widely accepted that boreal rivers and streams are regionally significant sources of carbon dioxide (CO2), yet their role as methane (CH4) emitters, as well as the sensitivity of these greenhouse gas (GHG) emissions to climate change, are still largely undefined. In this study, we explore the large-scale patterns of fluvial CO2 and CH4 partial pressure (pCO2 , pCH4) and gas exchange (k) relative to a set of key, climate-sensitive river variables across 46 streams and rivers in two distinct boreal landscapes of Northern Québec. We use the resulting models to determine the direction and magnitude of C-gas emissions from these boreal fluvial networks under scenarios of climate change. River pCO2 and pCH4 were positively correlated, although the latter was two orders of magnitude more variable. We provide evidence that in-stream metabolism strongly influences the dynamics of surface water pCO2 and pCH4 , but whereas pCO2 is not influenced by temperature in the surveyed streams and rivers, pCH4 appears to be strongly temperature-dependent. The major predictors of ambient gas concentrations and exchange were water temperature, velocity, and DOC, and the resulting models indicate that total GHG emissions (C-CO2 equivalent) from the entire network may increase between by 13 to 68% under plausible scenarios of climate change over the next 50 years. These predicted increases in fluvial GHG emissions are mostly driven by a steep increase in the contribution of CH4 (from 36 to over 50% of total CO2 -equivalents). The current role of boreal fluvial networks as major landscape sources of C is thus likely to expand, mainly driven by large increases in fluvial CH4 emissions. © 2013 John Wiley & Sons Ltd.

CREST v2.1 Refined by a Distributed Linear Reservoir Routing Scheme

NASA Astrophysics Data System (ADS)

Shen, X.; Hong, Y.; Zhang, K.; Hao, Z.; Wang, D.

2014-12-01

Hydrologic modeling is important in water resources management, and flooding disaster warning and management. Routing scheme is among the most important components of a hydrologic model. In this study, we replace the lumped LRR (linear reservoir routing) scheme used in previous versions of the distributed hydrological model, CREST (coupled routing and excess storage) by a newly proposed distributed LRR method, which is theoretically more suitable for distributed hydrological models. Consequently, we have effectively solved the problems of: 1) low values of channel flow in daily simulation, 2) discontinuous flow value along the river network during flood events and 3) irrational model parameters. The CREST model equipped with both the routing schemes have been tested in the Gan River basin. The distributed LRR scheme has been confirmed to outperform the lumped counterpart by two comparisons, hydrograph validation and visual speculation of the continuity of stream flow along the river: 1) The CREST v2.1 (version 2.1) with the implementation of the distributed LRR achieved excellent result of [NSCE(Nash coefficient), CC (correlation coefficient), bias] =[0.897, 0.947 -1.57%] while the original CREST v2.0 produced only negative NSCE, close to zero CC and large bias. 2) CREST v2.1 produced more naturally smooth river flow pattern along the river network while v2.0 simulated bumping and discontinuous discharge along the mainstream. Moreover, we further observe that by using the distributed LRR method, 1) all model parameters fell within their reasonable region after an automatic optimization; 2) CREST forced by satellite-based precipitation and PET products produces a reasonably well result, i.e., (NSCE, CC, bias) = (0.756, 0.871, -0.669%) in the case study, although there is still room to improve regarding their low spatial resolution and underestimation of the heavy rainfall events in the satellite products.

An Investigation on the Spatial Variability of Manning Roughness Coefficients in Continental-scale River Routing Simulations

NASA Astrophysics Data System (ADS)

Luo, X.; Hong, Y.; Lei, X.; Leung, L. R.; Li, H. Y.; Getirana, A.

2017-12-01

As one essential component of the Earth system modeling, the continental-scale river routing computation plays an important role in applications of Earth system models, such as evaluating the impacts of the global change on water resources and flood hazards. The streamflow timing, which depends on the modeled flow velocities, can be an important aspect of the model results. River flow velocities have been estimated by using the Manning's equation where the Manning roughness coefficient is a key and sensitive parameter. In some early continental-scale studies, the Manning coefficient was determined with simplified methods, such as using a constant value for the entire basin. However, large spatial variability is expected in the Manning coefficients for the numerous channels composing the river network in distributed continental-scale hydrologic modeling. In the application of a continental-scale river routing model in the Amazon Basin, we use spatially varying Manning coefficients dependent on channel sizes and attempt to represent the dominant spatial variability of Manning coefficients. Based on the comparisons of simulation results with in situ streamflow records and remotely sensed river stages, we investigate the comparatively optimal Manning coefficients and explicitly demonstrate the advantages of using spatially varying Manning coefficients. The understanding obtained in this study could be helpful in the modeling of surface hydrology at regional to continental scales.

Development and Evaluation of an Integrated Hydrological Modeling Framework for Monitoring and Understanding Floods and Droughts

NASA Astrophysics Data System (ADS)

Yang, Z. L.; Wu, W. Y.; Lin, P.; Maidment, D. R.

2017-12-01

Extreme water events such as catastrophic floods and severe droughts have increased in recent decades. Mitigating the risk to lives, food security, infrastructure, energy supplies, as well as numerous other industries posed by these extreme events requires informed decision-making and planning based on sound science. We are developing a global water modeling capability by building models that will provide total operational water predictions (evapotranspiration, soil moisture, groundwater, channel flow, inundation, snow) at unprecedented spatial resolutions and updated frequencies. Toward this goal, this talk presents an integrated global hydrological modeling framework that takes advantage of gridded meteorological forcing, land surface modeling, channeled flow modeling, ground observations, and satellite remote sensing. Launched in August 2016, the National Water Model successfully incorporates weather forecasts to predict river flows for more than 2.7 million rivers across the continental United States, which transfers a "synoptic weather map" to a "synoptic river flow map" operationally. In this study, we apply a similar framework to a high-resolution global river network database, which is developed from a hierarchical Dominant River Tracing (DRT) algorithm, and runoff output from the Global Land Data Assimilation System (GLDAS) to a vector-based river routing model (The Routing Application for Parallel Computation of Discharge, RAPID) to produce river flows from 2001 to 2016 using Message Passing Interface (MPI) on Texas Advanced Computer Center's Stampede system. In this simulation, global river discharges for more than 177,000 rivers are computed every 30 minutes. The modeling framework's performance is evaluated with various observations including river flows at more than 400 gauge stations globally. Overall, the model exhibits a reasonably good performance in simulating the averaged patterns of terrestrial water storage, evapotranspiration and runoff. The system is appropriate for monitoring and studying floods and droughts. Directions for future research will be outlined and discussed.

Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks.

PubMed

Mullen, Lindy B; Arthur Woods, H; Schwartz, Michael K; Sepulveda, Adam J; Lowe, Winsor H

2010-03-01

The network architecture of streams and rivers constrains evolutionary, demographic and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho giant salamander, Dicamptodon aterrimus, in stream networks of Idaho and Montana, USA. We used microsatellite data to test population structure models by (i) examining hierarchical partitioning of genetic variation in stream networks; and (ii) testing for genetic isolation by distance along stream corridors vs. overland pathways. Replicated sampling of streams within catchments within three river basins revealed that hierarchical scale had strong effects on genetic structure and gene flow. amova identified significant structure at all hierarchical scales (among streams, among catchments, among basins), but divergence among catchments had the greatest structural influence. Isolation by distance was detected within catchments, and in-stream distance was a strong predictor of genetic divergence. Patterns of genetic divergence suggest that differentiation among streams within catchments was driven by limited migration, consistent with a stream hierarchy model of population structure. However, there was no evidence of migration among catchments within basins, or among basins, indicating that gene flow only counters the effects of genetic drift at smaller scales (within rather than among catchments). These results show the strong influence of stream networks on population structure and genetic divergence of a salamander, with contrasting effects at different hierarchical scales.

Understanding Coupled Earth-Surface Processes through Experiments and Models (Invited)

NASA Astrophysics Data System (ADS)

Overeem, I.; Kim, W.

2013-12-01

Traditionally, both numerical models and experiments have been purposefully designed to ';isolate' singular components or certain processes of a larger mountain to deep-ocean interconnected source-to-sink (S2S) transport system. Controlling factors driven by processes outside of the domain of immediate interest were treated and simplified as input or as boundary conditions. Increasingly, earth surface processes scientists appreciate feedbacks and explore these feedbacks with more dynamically coupled approaches to their experiments and models. Here, we discuss key concepts and recent advances made in coupled modeling and experimental setups. In addition, we emphasize challenges and new frontiers to coupled experiments. Experiments have highlighted the important role of self-organization; river and delta systems do not always need to be forced by external processes to change or develop characteristic morphologies. Similarly modeling f.e. has shown that intricate networks in tidal deltas are stable because of the interplay between river avulsions and the tidal current scouring with both processes being important to develop and maintain the dentritic networks. Both models and experiment have demonstrated that seemingly stable systems can be perturbed slightly and show dramatic responses. Source-to-sink models were developed for both the Fly River System in Papua New Guinea and the Waipaoa River in New Zealand. These models pointed to the importance of upstream-downstream effects and enforced our view of the S2S system as a signal transfer and dampening conveyor belt. Coupled modeling showed that deforestation had extreme effects on sediment fluxes draining from the catchment of the Waipaoa River in New Zealand, and that this increase in sediment production rapidly shifted the locus of offshore deposition. The challenge in designing coupled models and experiments is both technological as well as intellectual. Our community advances to make numerical model coupling more straightforward through common interfaces and standardization of time-stepping, model domains and model parameters. At the same time major steps forward require an interdisciplinary approach, wherein the source to sink system contains ecological feedbacks and human actors.

A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay watershed

USGS Publications Warehouse

Brakebill, J.W.; Preston, S.D.

2003-01-01

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agency's digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.

Functional Topology of Evolving Urban Drainage Networks

NASA Astrophysics Data System (ADS)

Yang, Soohyun; Paik, Kyungrock; McGrath, Gavan S.; Urich, Christian; Krueger, Elisabeth; Kumar, Praveen; Rao, P. Suresh C.

2017-11-01

We investigated the scaling and topology of engineered urban drainage networks (UDNs) in two cities, and further examined UDN evolution over decades. UDN scaling was analyzed using two power law scaling characteristics widely employed for river networks: (1) Hack's law of length (L)-area (A) [L∝Ah] and (2) exceedance probability distribution of upstream contributing area (δ) [P>(A≥δ>)˜aδ-ɛ]. For the smallest UDNs (<2 km2), length-area scales linearly (h ˜ 1), but power law scaling (h ˜ 0.6) emerges as the UDNs grow. While P>(A≥δ>) plots for river networks are abruptly truncated, those for UDNs display exponential tempering [P>(A≥δ>)=aδ-ɛexp⁡>(-cδ>)]. The tempering parameter c decreases as the UDNs grow, implying that the distribution evolves in time to resemble those for river networks. However, the power law exponent ɛ for large UDNs tends to be greater than the range reported for river networks. Differences in generative processes and engineering design constraints contribute to observed differences in the evolution of UDNs and river networks, including subnet heterogeneity and nonrandom branching.

Dynamic coupling of three hydrodynamic models

NASA Astrophysics Data System (ADS)

Hartnack, J. N.; Philip, G. T.; Rungoe, M.; Smith, G.; Johann, G.; Larsen, O.; Gregersen, J.; Butts, M. B.

2008-12-01

The need for integrated modelling is evidently present within the field of flood management and flood forecasting. Engineers, modellers and managers are faced with flood problems which transcend the classical hydrodynamic fields of urban, river and coastal flooding. Historically the modeller has been faced with having to select one hydrodynamic model to cover all the aspects of the potentially complex dynamics occurring in a flooding situation. Such a single hydrodynamic model does not cover all dynamics of flood modelling equally well. Thus the ideal choice may in fact be a combination of models. Models combining two numerical/hydrodynamic models are becoming more standard, typically these models combine a 1D river model with a 2D overland flow model or alternatively a 1D sewer/collection system model with a 2D overland solver. In complex coastal/urban areas the flood dynamics may include rivers/streams, collection/storm water systems along with the overland flow. The dynamics within all three areas is of the same time scale and there is feedback in the system across the couplings. These two aspects dictate a fully dynamic three way coupling as opposed to running the models sequentially. It will be shown that the main challenges of the three way coupling are time step issues related to the difference in numerical schemes used in the three model components and numerical instabilities caused by the linking of the model components. MIKE FLOOD combines the models MIKE 11, MIKE 21 and MOUSE into one modelling framework which makes it possible to couple any combination of river, urban and overland flow fully dynamically. The MIKE FLOOD framework will be presented with an overview of the coupling possibilities. The flood modelling concept will be illustrated through real life cases in Australia and in Germany. The real life cases reflect dynamics and interactions across all three model components which are not possible to reproduce using a two-way coupling alone. The models comprise 2D inundation modelling, river networks with multiple structures (pumps, weirs, culverts), urban drainage networks as well as dam break modelling. The models were used to quantify the results of storm events or failures (dam break, pumping failures etc) coinciding with high discharge in river system and heavy rainfall. The detailed representation of the flow path through the city allowed a direct assessment of flood risk Thus it is found that the three-way coupled model is a practical and useful tool for integrated flood management.

Assessment of Flood Mitigation Solutions Using a Hydrological Model and Refined 2D Hydrodynamic Simulations

NASA Astrophysics Data System (ADS)

Khuat Duy, B.; Archambeau, P.; Dewals, B. J.; Erpicum, S.; Pirotton, M.

2009-04-01

Following recurrent inundation problems on the Berwinne catchment, in Belgium, a combined hydrologic and hydrodynamic study has been carried out in order to find adequate solutions for the floods mitigation. Thanks to detailed 2D simulations, the effectiveness of the solutions can be assessed not only in terms of discharge and height reductions in the river, but also with other aspects such as the inundated surfaces reduction and the decrease of inundated buildings and roads. The study is carried out in successive phases. First, the hydrological runoffs are generated using a physically based and spatially distributed multi-layer model solving depth-integrated equations for overland flow, subsurface flow and baseflow. Real floods events are simulated using rainfall series collected at 8 stations (over 20 years of available data). The hydrological inputs are routed through the river network (and through the sewage network if relevant) with the 1D component of the modelling system, which solves the Saint-Venant equations for both free-surface and pressurized flows in a unified way. On the main part of the river, the measured river cross-sections are included in the modelling, and existing structures along the river (such as bridges, sluices or pipes) are modelled explicitely with specific cross sections. Two gauging stations with over 15 years of continuous measurements allow the calibration of both the hydrologic and hydrodynamic models. Second, the flood mitigation solutions are tested in the simulations in the case of an extreme flooding event, and their effects are assessed using detailed 2D simulations on a few selected sensitive areas. The digital elevation model comes from an airborne laser survey with a spatial resolution of 1 point per square metre and is completed in the river bed with a bathymetry interpolated from cross-section data. The upstream discharge is extracted from the 1D simulation for the selected rainfall event. The study carried out with this methodology allowed to assess the suggested solutions with multiple effectiveness criteria and therefore constitutes a very useful support for decision makers.

Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment

NASA Astrophysics Data System (ADS)

Vivoni, Enrique R.; Mascaro, Giuseppe; Mniszewski, Susan; Fasel, Patricia; Springer, Everett P.; Ivanov, Valeriy Y.; Bras, Rafael L.

2011-10-01

SummaryA major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.

Distributed and localized horizontal tectonic deformation as inferred from drainage network geometry and topology: A case study from Lebanon

NASA Astrophysics Data System (ADS)

Goren, Liran; Castelltort, Sébastien; Klinger, Yann

2016-04-01

Partitioning of horizontal deformation between localized and distributed modes in regions of oblique tectonic convergence is, in many cases, hard to quantify. As a case study, we consider the Dead Sea Fault System that changes its orientation across Lebanon and forms a restraining bend. The oblique deformation along the Lebanese restraining bend is characterized by a complex suite of tectonic structures, among which, the Yammouneh fault, is believed to be the main strand that relays deformation from the southern section to the northern section of the Dead Sea Fault System. However, uncertainties regarding slip rates along the Yammouneh fault and strain partitioning in Lebanon still prevail. In the current work we use the geometry and topology of river basins together with numerical modeling to evaluate modes and rates of the horizontal deformation in Mount Lebanon that is associated with the Arabia-Sinai relative plate motion. We focus on river basins that drain Mount Lebanon to the Mediterranean and originate close to the Yammouneh fault. We quantify a systematic counterclockwise rotation of these basins and evaluate drainage area disequilibrium using an application of the χ mapping technique, which aims at estimating the degree of geometrical and topological disequilibrium in river networks. The analysis indicates a systematic spatial pattern whereby tributaries of the rotated basins appear to experience drainage area loss or gain with respect to channel length. A kinematic model that is informed by river basin geometry reveals that since the late Miocene, about a quarter of the relative plate motion parallel to the plate boundary has been distributed along a wide band of deformation to the west of the Yammouneh fault. Taken together with previous, shorter-term estimates, the model indicates little variation of slip rate along the Yammouneh fault since the late Miocene. Kinematic model results are compatible with late Miocene paleomagnetic rotations in western Mount Lebanon. A numerical landscape evolution experiment demonstrates the emergence of a similar χ pattern of drainage area disequilibrium in response to progressive distributed shear deformation of river basins with relatively minor drainage network reorganization.

Suspended sediment flux modeling with artificial neural network: An example of the Longchuanjiang River in the Upper Yangtze Catchment, China

NASA Astrophysics Data System (ADS)

Zhu, Yun-Mei; Lu, X. X.; Zhou, Yue

2007-02-01

Artificial neural network (ANN) was used to model the monthly suspended sediment flux in the Longchuanjiang River, the Upper Yangtze Catchment, China. The suspended sediment flux was related to the average rainfall, temperature, rainfall intensity and water discharge. It is demonstrated that ANN is capable of modeling the monthly suspended sediment flux with fairly good accuracy when proper variables and their lag effect on the suspended sediment flux are used as inputs. Compared with multiple linear regression and power relation models, ANN can generate a better fit under the same data requirement. In addition, ANN can provide more reasonable predictions for extremely high or low values, because of the distributed information processing system and the nonlinear transformation involved. Compared with the ANNs that use the values of the dependent variable at previous time steps as inputs, the ANNs established in this research with only climate variables have an advantage because it can be used to assess hydrological responses to climate change.

Assessing sufficiency of thermal riverscapes for resilient ...

EPA Pesticide Factsheets

Resilient salmon populations require river networks that provide water temperature regimes sufficient to support a diversity of salmonid life histories across space and time. Efforts to protect, enhance and restore watershed thermal regimes for salmon may target specific locations and features within stream networks hypothesized to provide disproportionately high-value functional resilience to salmon populations. These include relatively small-scale features such as thermal refuges, and larger-scale features such as entire watersheds or aquifers that support thermal regimes buffered from local climatic conditions. Quantifying the value of both small and large scale thermal features to salmon populations has been challenged by both the difficulty of mapping thermal regimes at sufficient spatial and temporal resolutions, and integrating thermal regimes into population models. We attempt to address these challenges by using newly-available datasets and modeling approaches to link thermal regimes to salmon populations across scales. We will describe an individual-based modeling approach for assessing sufficiency of thermal refuges for migrating salmon and steelhead in large rivers, as well as a population modeling approach for assessing large-scale climate refugia for salmon in the Pacific Northwest. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

NASA Astrophysics Data System (ADS)

Beaufort, Aurélien; Lamouroux, Nicolas; Pella, Hervé; Datry, Thibault; Sauquet, Eric

2018-05-01

Headwater streams represent a substantial proportion of river systems and many of them have intermittent flows due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate over time the daily probability of drying (defined at the regional scale). Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater-level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence. The robustness of the models was tested using an independent, dense regional dataset of intermittence observations and observations of the year 2017 excluded from the calibration. The resulting models were used to extrapolate the daily regional probability of drying in France: (i) over the period 2011-2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989-2017, using a reduced input dataset, to analyse temporal variability of flow intermittence at the national level. The two empirical regression models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest. Conversely, the worst performances were obtained in mountainous regions. Finally, temporal projections (1989-2016) suggested the highest probabilities of intermittence (> 35 %) in 1989-1991, 2003 and 2005. A high density of intermittence observations improved the information provided by gauging stations and piezometers to extrapolate the temporal variability of intermittent rivers and ephemeral streams.

Application of transit data analysis and artificial neural network in the prediction of discharge of Lor River, NW Spain.

PubMed

Astray, G; Soto, B; Lopez, D; Iglesias, M A; Mejuto, J C

2016-01-01

Transit data analysis and artificial neural networks (ANNs) have proven to be a useful tool for characterizing and modelling non-linear hydrological processes. In this paper, these methods have been used to characterize and to predict the discharge of Lor River (North Western Spain), 1, 2 and 3 days ahead. Transit data analyses show a coefficient of correlation of 0.53 for a lag between precipitation and discharge of 1 day. On the other hand, temperature and discharge has a negative coefficient of correlation (-0.43) for a delay of 19 days. The ANNs developed provide a good result for the validation period, with R(2) between 0.92 and 0.80. Furthermore, these prediction models have been tested with discharge data from a period 16 years later. Results of this testing period also show a good correlation, with R(2) between 0.91 and 0.64. Overall, results indicate that ANNs are a good tool to predict river discharge with a small number of input variables.

Drifters for New Measurements Along River Networks

NASA Astrophysics Data System (ADS)

Davies, J. L.; Niemeier, J. J.; Kruger, A.; Mantilla, R. G.; Ceynar, D. L.

2008-12-01

Inexpensive floating devices and techniques have been developed for a variety of river measurements, including surface flow velocity, water temperature, and light measurements, which serve as a proxy for turbidity. These devices, called Drifters, provide measurements in a Lagrangian reference frame. A Drifter consists of an inexpensive microcontroller, sensors, on-board data storage, a temperature-controlled clock, low-power radio transceiver, two AA batteries, all housed in a small plastic boat hull. As a Drifter floats down a river, the microcontroller periodically awakens and performs a series of measurements. Radio beacons placed on the riverbank transmit location information to the Drifters for georeferencing. Drifters are collected downstream where the data are downloaded for analysis. Drifters can also transmit collected data to the beacons in real time, but at the cost of higher power consumption. The design of the Drifters recognizes the need for accurate determination of travel times along the river network to an outlet of interest. Drifters have the potential to provide a full picture of the spatial distribution of travel times in a basin, opening the door to new understanding of the runoff transport phenomena, and removing the need of calibrated parameters in runoff transport equations of hydrological models. Acquired measurements are overlaid on maps, which provide a new perspective of the spatial distribution of water quality, temperature and velocity in large regions. Drifters have been used to make measurements over a 3-mile stretch of the Iowa River in Iowa City, Iowa, as preparation for a large-scale experiment on the river network of the Clear Creek basin in Iowa.

A Continental-scale River Corridor Model to Synthesize Understanding and Prioritize Management of Water Purification Functions and Ecological Services in Large Basins

NASA Astrophysics Data System (ADS)

Harvey, J. W.; Gomez-Velez, J. D.; Scott, D.; Boyer, E. W.; Schmadel, N. M.; Alexander, R. B.; Eng, K.; Golden, H. E.; Kettner, A.; Konrad, C. P.; Moore, R. B.; Pizzuto, J. E.; Schwarz, G. E.; Soulsby, C.

2017-12-01

The functional values of rivers depend on more than just wetted river channels. Instead, the river channel exchanges water and suspended materials with adjacent riparian, floodplain, hyporheic zones, and ponded waters such as lakes and reservoirs. Together these features comprise a larger functional unit known as the river corridor. The exchange of water, solutes, and sediments within the river corridor alters downstream water quality and ecological functions, but our understanding of the large-scale, cumulative impacts is inadequate and has limited advancements in sustainable management practices. A problem with traditional watershed, groundwater, and river water quality models is that none of them explicitly accounts for river corridor storage and processing, and the exchanges of water, solutes, and sediments that occur many times between the channel and off-channel environments during a river's transport to the sea. Our River Corridor Working Group at the John Wesley Powell Center is quantifying the key components of river corridor functions. Relying on foundational studies that identified floodplain, riparian, and hyporheic exchange flows and resulting enhancement of chemical reactions at river reach scales, we are assembling the datasets and building the models to upscale that understanding onto 2.6 million river reaches in the U.S. A principal goal of the River Corridor Working group is to develop a national-scale river corridor model for the conterminous U.S. that will reveal, perhaps for the first time, the relative influences of hyporheic, riparian, floodplain, and ponded waters at large spatial scales. The simple but physically-based models are predictive for changing conditions and therefore can directly address the consequences and effectiveness of management actions in sustaining valuable river corridor functions. This presentation features interpretation of useful river corridor connectivity metrics and ponded water influences on nutrient and sediment processing in river networks of the Mid-Atlantic and Northeastern U.S. This research is a product of the John Wesley Powell Center River Corridor Working Group https://powellcenter.usgs.gov/view-project

Export of earthquake-triggered landslides in active mountain ranges: insights from 2D morphodynamic modelling.

NASA Astrophysics Data System (ADS)

Croissant, Thomas; Lague, Dimitri; Davy, Philippe; Steer, Philippe

2016-04-01

In active mountain ranges, large earthquakes (Mw > 5-6) trigger numerous landslides that impact river dynamics. These landslides bring local and sudden sediment piles that will be eroded and transported along the river network causing downstream changes in river geometry, transport capacity and erosion efficiency. The progressive removal of landslide materials has implications for downstream hazards management and also for understanding landscape dynamics at the timescale of the seismic cycle. The export time of landslide-derived sediments after large-magnitude earthquakes has been studied from suspended load measurements but a full understanding of the total process, including the coupling between sediment transfer and channel geometry change, still remains an issue. Note that the transport of small sediment pulses has been studied in the context of river restoration, but the magnitude of sediment pulses generated by landslides may make the problem different. Here, we study the export of large volumes (>106 m3) of sediments with the 2D hydro-morphodynamic model, Eros. This model uses a new hydrodynamic module that resolves a reduced form of the Saint-Venant equations with a particle method. It is coupled with a sediment transport and lateral and vertical erosion model. Eros accounts for the complex retroactions between sediment transport and fluvial geometry, with a stochastic description of the floods experienced by the river. Moreover, it is able to reproduce several features deemed necessary to study the evacuation of large sediment pulses, such as river regime modification (single-thread to multi-thread), river avulsion and aggradation, floods and bank erosion. Using a synthetic and simple topography we first present how granulometry, landslide volume and geometry, channel slope and flood frequency influence 1) the dominance of pulse advection vs. diffusion during its evacuation, 2) the pulse export time and 3) the remaining volume of sediment in the catchment. The model is then applied to a high resolution (5-10 m) digital elevation model of the Poerua catchment in New Zealand which has been impacted by the effect of a large landslide during the last 15 years. We investigate several plausible Alpine Faults earthquake scenarios to study the propagation of the sediment along a complex river network. We characterize and quantify the sediment pulse export time and mechanism for this river configuration and show its impact on the alluvial plain evolution. Our findings have strong implications for the understanding of aggradation rates and the temporal persistence of induced hazards in the alluvial plain as well as of sediment transfers in active mountain belts.

Suwannee River flow variability 1550-2005 CE reconstructed from a multispecies tree-ring network

NASA Astrophysics Data System (ADS)

Harley, Grant L.; Maxwell, Justin T.; Larson, Evan; Grissino-Mayer, Henri D.; Henderson, Joseph; Huffman, Jean

2017-01-01

Understanding the long-term natural flow regime of rivers enables resource managers to more accurately model water level variability. Models for managing water resources are important in Florida where population increase is escalating demand on water resources and infrastructure. The Suwannee River is the second largest river system in Florida and the least impacted by anthropogenic disturbance. We used new and existing tree-ring chronologies from multiple species to reconstruct mean March-October discharge for the Suwannee River during the period 1550-2005 CE and place the short period of instrumental flows (since 1927 CE) into historical context. We used a nested principal components regression method to maximize the use of chronologies with varying time coverage in the network. Modeled streamflow estimates indicated that instrumental period flow conditions do not adequately capture the full range of Suwannee River flow variability beyond the observational period. Although extreme dry and wet events occurred in the gage record, pluvials and droughts that eclipse the intensity and duration of instrumental events occurred during the 16-19th centuries. The most prolonged and severe dry conditions during the past 450 years occurred during the 1560s CE. In this prolonged drought period mean flow was estimated at 17% of the mean instrumental period flow. Significant peaks in spectral density at 2-7, 10, 45, and 85-year periodicities indicated the important influence of coupled oceanic-atmospheric processes on Suwannee River streamflow over the past four centuries, though the strength of these periodicities varied over time. Future water planning based on current flow expectations could prove devastating to natural and human systems if a prolonged and severe drought mirroring the 16th and 18th century events occurred. Future work in the region will focus on updating existing tree-ring chronologies and developing new collections from moisture-sensitive sites to improve understandings of past hydroclimate in the region.

Basin-scale characterization of river hydromorphology by map derived information: A case study on the Red River (Sông Hông), Vietnam

NASA Astrophysics Data System (ADS)

Schmitt, R. J.; Bizzi, S.; Castelletti, A.

2012-12-01

The understanding of river hydromorphological processes has been recognized in the last decades as a priority of modern catchment management, since fluvial geomorphic processes shape physical habitat, affect river infrastructures and influence freshwater ecological processes. Characterization of river hydromorphological features is commonly location specific and highly demanding in terms of field-works, resource and expertise required. Therefore, its routine application at regional or national scales, although an urgent need of catchment management, is infeasible at present. Recently available high-resolution data, such as DEM or LIDAR, opens up novel potential for basin-wide analysis of fluvial processes at limited effort and cost. Specifically, in this study we assess the feasibility of characterizing river hydromorphology from specific map derived geomorphic controls namely: channel gradient, bankfull flow, specific stream power, and degree of channel confinement. The river network, extracted from a digital elevation model and validated with available network shape-files and optical satellite imagery, available flow gauging stations and GIS processing allow producing continuous values of geomorphic drivers defined over given length segments at catchment or regional scales. This generic framework was applied to the Red River (Sông Hông) basin, the second largest basin (87,800 km2) in Vietnam. Besides its economic importance, the river since few years is experiencing severe river bed incisions due to the building of new dams in the upstream part of the catchment and sand mining in the surrounding of the capital city Hanoi. In this context, characterized by an high developing rate, current efforts to increase water productivity by infrastructure and management measures require a thorough understanding of fluvial system and, in particular, of the basin-wide river hydromorphology. The framework proposed has allowed producing high-dimensional samples of spatially distributed geomorphic drivers at catchment scale for the Red River basin. This novel dataset has been then analysed using self-organizing maps (SOM) an artificial neural network model that is capable of learning from complex, multidimensional data without specification of what the outputs should be, and of generating a nonlinear classification of visually decipherable clusters. The use of the above framework allowed to analyze the spatial distribution of geomorphic features at catchment scale, reviling patterns of similarities and dissimilarities within the catchment and allowing classification of river reaches characterized by similar geomorphic drivers and then likely (but still to be validated) fluvial processes. The paper proposes an innovative and promising technique to produce hydromorphological classifications at catchment scale opening the way towards regional or national scale hydromorphological assessments through automatic GIS and statistical procedures with moderate effort, an urgent requirement of modern catchment management.

An integrated multiscale river basin observing system in the Heihe River Basin, northwest China

NASA Astrophysics Data System (ADS)

Li, X.; Liu, S.; Xiao, Q.; Ma, M.; Jin, R.; Che, T.

2015-12-01

Using the watershed as the unit to establish an integrated watershed observing system has been an important trend in integrated eco-hydrologic studies in the past ten years. Thus far, a relatively comprehensive watershed observing system has been established in the Heihe River Basin, northwest China. In addition, two comprehensive remote sensing hydrology experiments have been conducted sequentially in the Heihe River Basin, including the Watershed Allied Telemetry Experimental Research (WATER) (2007-2010) and the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) (2012-2015). Among these two experiments, an important result of WATER has been the generation of some multi-scale, high-quality comprehensive datasets, which have greatly supported the development, improvement and validation of a series of ecological, hydrological and quantitative remote-sensing models. The goal of a breakthrough for solving the "data bottleneck" problem has been achieved. HiWATER was initiated in 2012. This project has established a world-class hydrological and meteorological observation network, a flux measurement matrix and an eco-hydrological wireless sensor network. A set of super high-resolution airborne remote-sensing data has also been obtained. In addition, there has been important progress with regard to the scaling research. Furthermore, the automatic acquisition, transmission, quality control and remote control of the observational data has been realized through the use of wireless sensor network technology. The observation and information systems have been highly integrated, which will provide a solid foundation for establishing a research platform that integrates observation, data management, model simulation, scenario analysis and decision-making support to foster 21st-century watershed science in China.

The role of interactions along the flood process chain and implications for risk assessment

NASA Astrophysics Data System (ADS)

Vorogushyn, Sergiy; Apel, Heiko; Viet Nguyen, Dung; Guse, Björn; Kreibich, Heidi; Lüdtke, Stefan; Schröter, Kai; Merz, Bruno

2017-04-01

Floods with their manifold characteristics are shaped by various processes along the flood process chain - from triggering meteorological extremes through catchment and river network process down to impacts on societies. In flood risk systems numerous interactions and feedbacks along the process chain may occur which finally shape spatio-temporal flood patterns and determine the ultimate risk. In this talk, we review some important interactions in the atmosphere-catchment, river-dike-floodplain and vulnerability compartments of the flood risk system. We highlight the importance of spatial interactions for flood hazard and risk assessment. For instance, the role of spatial rainfall structure or wave superposition in river networks is elucidated with selected case studies. In conclusion, we show the limits of current methods in assessment of large-scale flooding and outline the approach to more comprehensive risk assessment based on our regional flood risk model (RFM) for Germany.

Multilayer perceptron neural network-based approach for modeling phycocyanin pigment concentrations: case study from lower Charles River buoy, USA.

PubMed

Heddam, Salim

2016-09-01

This paper proposes multilayer perceptron neural network (MLPNN) to predict phycocyanin (PC) pigment using water quality variables as predictor. In the proposed model, four water quality variables that are water temperature, dissolved oxygen, pH, and specific conductance were selected as the inputs for the MLPNN model, and the PC as the output. To demonstrate the capability and the usefulness of the MLPNN model, a total of 15,849 data measured at 15-min (15 min) intervals of time are used for the development of the model. The data are collected at the lower Charles River buoy, and available from the US Environmental Protection Agency (USEPA). For comparison purposes, a multiple linear regression (MLR) model that was frequently used for predicting water quality variables in previous studies is also built. The performances of the models are evaluated using a set of widely used statistical indices. The performance of the MLPNN and MLR models is compared with the measured data. The obtained results show that (i) the all proposed MLPNN models are more accurate than the MLR models and (ii) the results obtained are very promising and encouraging for the development of phycocyanin-predictive models.

Modeling multi-process connectivity in river deltas: extending the single layer network analysis to a coupled multilayer network framework

NASA Astrophysics Data System (ADS)

Tejedor, A.; Longjas, A.; Foufoula-Georgiou, E.

2017-12-01

Previous work [e.g. Tejedor et al., 2016 - GRL] has demonstrated the potential of using graph theory to study key properties of the structure and dynamics of river delta channel networks. Although the distribution of fluxes in river deltas is mostly driven by the connectivity of its channel network a significant part of the fluxes might also arise from connectivity between the channels and islands due to overland flow and seepage. This channel-island-subsurface interaction creates connectivity pathways which facilitate or inhibit transport depending on their degree of coupling. The question we pose here is how to collectively study system connectivity that emerges from the aggregated action of different processes (different in nature, intensity and time scales). Single-layer graphs as those introduced for delta channel networks are inadequate as they lack the ability to represent coupled processes, and neglecting across-process interactions can lead to mis-representation of the overall system dynamics. We present here a framework that generalizes the traditional representation of networks (single-layer graphs) to the so-called multi-layer networks or multiplex. A multi-layer network conceptualizes the overall connectivity arising from different processes as distinct graphs (layers), while allowing at the same time to represent interactions between layers by introducing interlayer links (across process interactions). We illustrate this framework using a study of the joint connectivity that arises from the coupling of the confined flow on the channel network and the overland flow on islands, on a prototype delta. We show the potential of the multi-layer framework to answer quantitatively questions related to the characteristic time scales to steady-state transport in the system as a whole when different levels of channel-island coupling are modulated by different magnitudes of discharge rates.

Evaporation loss and evaporation/transpiration partitioning from isotope-based monitoring of Canada's provincial and national river networks

NASA Astrophysics Data System (ADS)

Gibson, J. J.; Birks, S. J.; Stadnyk, T.; Delavau, C. J.

2017-12-01

Stable isotopes of water have been measured since the 1990's as part of hydrometric monitoring programs within Canada's Water Survey of Canada gauging network and Alberta's Long-Term River Network. These datasets are being applied for hydrograph separation of streamflow sources, including rain, snow, groundwater, and surface water, as well as for estimation of watershed evaporation losses and evaporation/transpiration partitioning. Here we describe an innovative isotope mass balance approach, discuss benefits and limitations of the method, and present selected results that illustrate important regional trends in the contemporary hydrology of Canada. Overall, isotopes are shown to be useful for constraining water balance variations across regions with low monitoring density. Recommendations for future activities are identified, including regional comparisons with outputs from isotope-capable distributed hydrologic models.

The significance of small streams

NASA Astrophysics Data System (ADS)

Wohl, Ellen

2017-09-01

Headwaters, defined here as first- and secondorder streams, make up 70%‒80% of the total channel length of river networks. These small streams exert a critical influence on downstream portions of the river network by: retaining or transmitting sediment and nutrients; providing habitat and refuge for diverse aquatic and riparian organisms; creating migration corridors; and governing connectivity at the watershed-scale. The upstream-most extent of the channel network and the longitudinal continuity and lateral extent of headwaters can be difficult to delineate, however, and people are less likely to recognize the importance of headwaters relative to other portions of a river network. Consequently, headwaters commonly lack the legal protections accorded to other portions of a river network and are more likely to be significantly altered or completely obliterated by land use.

Modeling of wind gap formation and development of sedimentary basins during fold growth: application to the Zagros Fold Belt, Iran.

NASA Astrophysics Data System (ADS)

Collignon, Marine; Yamato, Philippe; Castelltort, Sébastien; Kaus, Boris

2016-04-01

Mountain building and landscape evolution are controlled by the interactions between river dynamics and tectonic forces. Such interactions have been largely studied but a quantitative evaluation of tectonic/geomorphic feedbacks remains required for understanding sediments routing within orogens and fold-and-thrust belts. Here, we employ numerical simulations to assess the conditions of uplift and river incision necessary to deflect an antecedent drainage network during the growth of one or several folds. We propose that a partitioning of the river network into internal (endorheic) and longitudinal drainage arises as a result of lithological differences within the deforming crustal sedimentary cover. We show with examples from the Zagros Fold Belt (ZFB) that drainage patterns can be linked to the incision ratio R between successive lithological layers, corresponding to the ratio between their relative erodibilities or incision coefficients. Transverse drainage networks develop for uplift rates smaller than 0.8 mm.yr-1 and -10 < R < 10. Intermediate drainage network are obtained for uplift rates up to 2 mm.yr-1 and incision ratios of 20. Parallel drainage networks and formation of sedimentary basins occur for large values of incision ratio (R >20) and uplift rates between 1 and 2 mm.yr-1. These results have implications for predicting the distribution of sediment depocenters in fold-and-thrust belts, which can be of direct economic interest for hydrocarbon exploration.

Models based on "out-of Kilter" algorithm

NASA Astrophysics Data System (ADS)

Adler, M. J.; Drobot, R.

2012-04-01

In case of many water users along the river stretches, it is very important, in case of low flows and droughty periods to develop an optimization model for water allocation, to cover all needs under certain predefined constraints, depending of the Contingency Plan for drought management. Such a program was developed during the implementation of the WATMAN Project, in Romania (WATMAN Project, 2005-2006, USTDA) for Arges-Dambovita-Ialomita Basins water transfers. This good practice was proposed for WATER CoRe Project- Good Practice Handbook for Drought Management, (InterregIVC, 2011), to be applied for the European Regions. Two types of simulation-optimization models based on an improved version of out-of-kilter algorithm as optimization technique have been developed and used in Romania: • models for founding of the short-term operation of a WMS, • models generically named SIMOPT that aim to the analysis of long-term WMS operation and have as the main results the statistical WMS functional parameters. A real WMS is modeled by an arcs-nodes network so the real WMS operation problem becomes a problem of flows in networks. The nodes and oriented arcs as well as their characteristics such as lower and upper limits and associated costs are the direct analog of the physical and operational WMS characteristics. Arcs represent both physical and conventional elements of WMS such as river branches, channels or pipes, water user demands or other water management requirements, trenches of water reservoirs volumes, water levels in channels or rivers, nodes are junctions of at least two arcs and stand for locations of lakes or water reservoirs and/or confluences of river branches, water withdrawal or wastewater discharge points, etc. Quantitative features of water resources, water users and water reservoirs or other water works are expressed as constraints of non-violating the lower and upper limits assigned on arcs. Options of WMS functioning i.e. water retention/discharge in/from the reservoirs or diversion of water from one part of WMS to the other in order to meet water demands as well as the water user economic benefit or loss related to the degree of water demand, are the defining elements of the objective function and are conventionally expressed by the means of costs attached to the arcs. The problem of optimizing the WMS operation is formulated like a flow in networks problem as following: to find the flow that minimize the cost in the whole network while meeting the constraints of continuity in nodes and the constraints of non-exceeding lower and upper flow limits on arcs. Conversion of WMS in the arcs-nodes network and the adequate choice of costs and limits on arcs are steps of a unitary process and depend on the goal of the respective model.

Response of dissolved trace metals to land use/land cover and their source apportionment using a receptor model in a subtropic river, China.

PubMed

Li, Siyue; Zhang, Quanfa

2011-06-15

Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River. Our results revealed that land use was an important factor in water metals in the snow melt flow period and land use in the riparian zone was not a better predictor of metals than land use away from the river. Urbanization in a watershed and vegetation along river networks could better explain metals, and agriculture, regardless of its relative location, however slightly explained metal variables in the upper Han River. FA-MLR analysis identified five source types of metals, and mining, fossil fuel combustion, and vehicle exhaust were the dominant pollutions in the surface waters. The results demonstrated great impacts of human activities on metal concentrations in the subtropical river of China. Copyright © 2011 Elsevier B.V. All rights reserved.

Antarctic ice shelf potentially stabilized by export of meltwater in surface river.

PubMed

Bell, Robin E; Chu, Winnie; Kingslake, Jonathan; Das, Indrani; Tedesco, Marco; Tinto, Kirsty J; Zappa, Christopher J; Frezzotti, Massimo; Boghosian, Alexandra; Lee, Won Sang

2017-04-19

Meltwater stored in ponds and crevasses can weaken and fracture ice shelves, triggering their rapid disintegration. This ice-shelf collapse results in an increased flux of ice from adjacent glaciers and ice streams, thereby raising sea level globally. However, surface rivers forming on ice shelves could potentially export stored meltwater and prevent its destructive effects. Here we present evidence for persistent active drainage networks-interconnected streams, ponds and rivers-on the Nansen Ice Shelf in Antarctica that export a large fraction of the ice shelf's meltwater into the ocean. We find that active drainage has exported water off the ice surface through waterfalls and dolines for more than a century. The surface river terminates in a 130-metre-wide waterfall that can export the entire annual surface melt over the course of seven days. During warmer melt seasons, these drainage networks adapt to changing environmental conditions by remaining active for longer and exporting more water. Similar networks are present on the ice shelf in front of Petermann Glacier, Greenland, but other systems, such as on the Larsen C and Amery Ice Shelves, retain surface water at present. The underlying reasons for export versus retention remain unclear. Nonetheless our results suggest that, in a future warming climate, surface rivers could export melt off the large ice shelves surrounding Antarctica-contrary to present Antarctic ice-sheet models, which assume that meltwater is stored on the ice surface where it triggers ice-shelf disintegration.

Antarctic Ice Shelf Potentially Stabilized by Export of Meltwater in Surface River

NASA Technical Reports Server (NTRS)

Bell, Robin E.; Chu, Winnie; Kingslake, Jonathan; Das, Indrani; Tedesco, Marco; Tinto, Kirsty J.; Zappa, Christopher J.; Frezzotti, Massimo; Boghosian, Alexandra; Lee, Won Sang

2017-01-01

Meltwater stored in ponds and crevasses can weaken and fracture ice shelves, triggering their rapid disintegration. This ice-shelf collapse results in an increased flux of ice from adjacent glaciers and ice streams, thereby raising sea level globally. However, surface rivers forming on ice shelves could potentially export stored meltwater and prevent its destructive effects. Here we present evidence for persistent active drainage networks-interconnected streams, ponds and rivers-on the Nansen Ice Shelf in Antarctica that export a large fraction of the ice shelf's meltwater into the ocean. We find that active drainage has exported water off the ice surface through waterfalls and dolines for more than a century. The surface river terminates in a 130-metre-wide waterfall that can export the entire annual surface melt over the course of seven days. During warmer melt seasons, these drainage networks adapt to changing environmental conditions by remaining active for longer and exporting more water. Similar networks are present on the ice shelf in front of Petermann Glacier, Greenland, but other systems, such as on the Larsen C and Amery Ice Shelves, retain surface water at present. The underlying reasons for export versus retention remain unclear. Nonetheless our results suggest that, in a future warming climate, surface rivers could export melt off the large ice shelves surrounding Antarctica-contrary to present Antarctic ice-sheet models, which assume that meltwater is stored on the ice surface where it triggers ice-shelf disintegration.

Geostatistical screening of flood events in the groundwater levels of the diverted inner delta of the Danube River: implications for river bed clogging

NASA Astrophysics Data System (ADS)

Trásy, Balázs; Garamhegyi, Tamás; Laczkó-Dobos, Péter; Kovács, József; Hatvani, István Gábor

2018-04-01

The efficient operation of shallow groundwater (SGW) monitoring networks is crucial to water supply, in-land water protection, agriculture and nature conservation. In the present study, the spatial representativity of such a monitoring network in an area that has been thoroughly impacted by anthropogenic activity (river diversion/damming) is assessed, namely the Szigetköz adjacent to the River Danube. The main aims were to assess the spatial representativity of the SGW monitoring network in different discharge scenarios, and investigate the directional characteristics of this representativity, i.e. establish whether geostatistical anisotropy is present, and investigate how this changes with flooding. After the subtraction of a spatial trend from the time series of 85 shallow groundwater monitoring wells tracking flood events from 2006, 2009 and 2013, variography was conducted on the residuals, and the degree of anisotropy was assessed to explore the spatial autocorrelation structure of the network. Since the raw data proved to be insufficient, an interpolated grid was derived, and the final results were scaled to be representative of the original raw data. It was found that during floods the main direction of the spatial variance of the shallow groundwater monitoring wells alters, from perpendicular to the river to parallel with it for over a period of about two week. However, witht the passing of the flood, this returns to its original orientation in 2 months. It is likely that this process is related first to the fast removal of clogged riverbed strata by the flood, then to their slower replacement. In addition, the study highlights the importance of assessing the direction of the spatial autocorrelation structure of shallow groundwater monitoring networks, especially if the aim is to derive interpolated maps for the further investigation or modeling of flow.

Evaluating GCM land surface hydrology parameterizations by computing river discharges using a runoff routing model: Application to the Mississippi basin

NASA Technical Reports Server (NTRS)

Liston, G. E.; Sud, Y. C.; Wood, E. F.

1994-01-01

To relate general circulation model (GCM) hydrologic output to readily available river hydrographic data, a runoff routing scheme that routes gridded runoffs through regional- or continental-scale river drainage basins is developed. By following the basin overland flow paths, the routing model generates river discharge hydrographs that can be compared to observed river discharges, thus allowing an analysis of the GCM representation of monthly, seasonal, and annual water balances over large regions. The runoff routing model consists of two linear reservoirs, a surface reservoir and a groundwater reservoir, which store and transport water. The water transport mechanisms operating within these two reservoirs are differentiated by their time scales; the groundwater reservoir transports water much more slowly than the surface reservior. The groundwater reservior feeds the corresponding surface store, and the surface stores are connected via the river network. The routing model is implemented over the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project Mississippi River basin on a rectangular grid of 2 deg X 2.5 deg. Two land surface hydrology parameterizations provide the gridded runoff data required to run the runoff routing scheme: the variable infiltration capacity model, and the soil moisture component of the simple biosphere model. These parameterizations are driven with 4 deg X 5 deg gridded climatological potential evapotranspiration and 1979 First Global Atmospheric Research Program (GARP) Global Experiment precipitation. These investigations have quantified the importance of physically realistic soil moisture holding capacities, evaporation parameters, and runoff mechanisms in land surface hydrology formulations.

A stakeholder project to model water temperature under future climate scenarios in the Satus and Toppenish watersheds of the Yakima River Basinin Washington, USA

USGS Publications Warehouse

Graves, D.; Maule, A.

2014-01-01

The goal of this study was to support an assessment of the potential effects of climate change on select natural, social, and economic resources in the Yakima River Basin. A workshop with local stakeholders highlighted the usefulness of projecting climate change impacts on anadromous steelhead (Oncorhynchus mykiss), a fish species of importance to local tribes, fisherman, and conservationists. Stream temperature is an important environmental variable for the freshwater stages of steelhead. For this study, we developed water temperature models for the Satus and Toppenish watersheds, two of the key stronghold areas for steelhead in the Yakima River Basin. We constructed the models with the Stream Network Temperature Model (SNTEMP), a mechanistic approach to simulate water temperature in a stream network. The models were calibrated over the April 15, 2008 to September 30, 2008 period and validated over the April 15, 2009 to September 30, 2009 period using historic measurements of stream temperature and discharge provided by the Yakama Nation Fisheries Resource Management Program. Once validated, the models were run to simulate conditions during the spring and summer seasons over a baseline period (1981–2005) and two future climate scenarios with increased air temperature of 1°C and 2°C. The models simulated daily mean and maximum water temperatures at sites throughout the two watersheds under the baseline and future climate scenarios.

Similarity of Stream Width Distributions Across Headwater Systems

NASA Astrophysics Data System (ADS)

Allen, G. H.; Pavelsky, T.; Barefoot, E. A.; Tashie, A.; Butman, D. E.

2016-12-01

The morphology and abundance of streams control the rates of hydraulic and biogeochemical exchange between streams, groundwater, and the atmosphere. In large river systems, studies have used remote sensing to quantify river morphology, and have found that the relationship between river width and abundance is fractal, such that narrow rivers are proportionally more common than wider rivers. However, in headwater systems (stream order 1-3), where many biogeochemical reactions are most rapid, the relationship between stream width and abundance is unknown, reducing the certainty of biogeochemical flux estimates. To constrain this uncertainty, we surveyed two components of stream morphology (wetted stream width and length) in seven physiographically contrasting stream networks in Kings Creek in Konza Prarie, KS; Sagehen Creek in the N. Sierra Nevada Mtns., CA; Elder Creek in Angelo Coast Range Preserve, CA; Caribou Creek in the Caribou Poker Creek Research Watershed, AK; V40 Stream, NZ; Blue Duck Creek, NZ; Stony Creek in Duke Forest, NC. To assess temporal variations, we also surveyed stream geometry in a subcatchment of Stony Creek six times over a range of moderate streamflow conditions (discharge less than 90 percentile of gauge record). Here we show a strikingly consistent gamma statistical distribution of stream width in all surveys and a characteristic most abundant stream width of 32±7 cm independent of flow conditions or basin size. This consistency is remarkable given the substantial physical diversity among the studied catchments. We propose a model that invokes network topology theory and downstream hydraulic geometry to show that, as active drainage networks expand and contract in response to changes in streamflow, the most abundant stream width remains approximately static. This framework can be used to better extrapolate stream size and abundance from large rivers to small headwater streams, with significant impact on understanding of the hydraulic, ecological, and biogeochemical functions of stream networks.

Quantitative metrics that describe river deltas and their channel networks

NASA Astrophysics Data System (ADS)

Edmonds, Douglas A.; Paola, Chris; Hoyal, David C. J. D.; Sheets, Ben A.

2011-12-01

Densely populated river deltas are losing land at an alarming rate and to successfully restore these environments we must understand the details of their morphology. Toward this end we present a set of five metrics that describe delta morphology: (1) the fractal dimension, (2) the distribution of island sizes, (3) the nearest-edge distance, (4) a synthetic distribution of sediment fluxes at the shoreline, and (5) the nourishment area. The nearest-edge distance is the shortest distance to channelized or unchannelized water from a given location on the delta and is analogous to the inverse of drainage density in tributary networks. The nourishment area is the downstream delta area supplied by the sediment coming through a given channel cross section and is analogous to catchment area in tributary networks. As a first step, we apply these metrics to four relatively simple, fluvially dominated delta networks. For all these deltas, the average nearest-edge distances are remarkably constant moving down delta suggesting that the network organizes itself to maintain a consistent distance to the nearest channel. Nourishment area distributions can be predicted from a river mouth bar model of delta growth, and also scale with the width of the channel and with the length of the longest channel, analogous to Hack's law for drainage basins. The four delta channel networks are fractal, but power laws and scale invariance appear to be less pervasive than in tributary networks. Thus, deltas may occupy an advantageous middle ground between complete similarity and complete dissimilarity, where morphologic differences indicate different behavior.

An operational methodology for riparian land cover fine scale regional mapping for the study of landscape influence on river ecological status

NASA Astrophysics Data System (ADS)

Tormos, T.; Kosuth, P.; Souchon, Y.; Villeneuve, B.; Durrieu, S.; Chandesris, A.

2010-12-01

Preservation and restoration of river ecosystems require an improved understanding of the mechanisms through which they are influenced by landscape at multiple spatial scales and particularly at river corridor scale considering the role of riparian vegetation for regulating and protecting river ecological status and the relevance of this specific area for implementing efficient and realistic strategies. Assessing correctly this influence over large river networks involves accurate broad scale (i.e. at least regional) information on Land Cover within Riparian Areas (LCRA). As the structure of land cover along rivers is generally not accessible using moderate-scale satellite imagery, finer spatial resolution imagery and specific mapping techniques are needed. For this purpose we developed a generic multi-scale Object Based Image Analysis (OBIA) scheme able to produce LCRA maps in different geographic context by exploiting information available from very high spatial resolution imagery (satellite or airborne) and/or metric to decametric spatial thematic data on a given study zone thanks to fuzzy expert knowledge classification rules. A first experimentation was carried out on the Herault river watershed (southern of France), a 2650 square kilometers basin that presents a contrasted landscape (different ecoregions) and a total stream length of 1150 Km, using high and very high multispectral remotely-sensed images (10m Spot5 multispectral images and 0.5m aerial photography) and existing spatial thematic data. Application of the OBIA scheme produced a detailed (22 classes) LCRA map with an overall accuracy of 89% and a Kappa index of 83% according to a land cover pressures typology (six categories). A second experimentation (using the same data sources) was carried out on a larger test zone, a part of the Normandy river network (25 000 square kilometers basin; 6000 km long river network; 155 ecological stations). This second work aimed at elaborating a robust statistical eco-regional model to study links between land cover spatial indicators calculated at local and watershed scales, and river ecological status assessed with macroinvertebrate indicators. Application of the OBIA scheme produced a detailed (62 classes) LCRA map which allowed the model to highlight influence of specific land use patterns: (i) the significant beneficial effect of 20-m riparian tree vegetation strip near a station and 20-m riparian grassland strip along the upstream network of a station and (ii) the negative impact on river ecological status of urban areas and roads on the upstream flood plain of a station. Results of these two experimentations highlight that (i) the application of an OBIA scheme using multi-source spatial data provides an efficient approach for mapping and monitoring LCRA that can be implemented operationally at regional or national scale and (ii) and the interest of using LCRA-maps derived from very high spatial resolution imagery (satellite or airborne) and/or metric spatial thematic data to study landscape influence on river ecological status and support managers in the definition of optimized riparian preservation and restoration strategies.

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

NASA Astrophysics Data System (ADS)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

Aquatic Nitrate Retention at River Network Scales Across Flow Conditions Determined Using Nested In Situ Sensors

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Mulukutla, G. K.; Cook, C.; Carey, R. O.

2017-11-01

Nonpoint pollution sources are strongly influenced by hydrology and are therefore sensitive to climate variability. Some pollutants entering aquatic ecosystems, e.g., nitrate, can be mitigated by in-stream processes during transport through river networks. Whole river network nitrate retention is difficult to quantify with observations. High frequency, in situ nitrate sensors, deployed in nested locations within a single watershed, can improve estimates of both nonpoint inputs and aquatic retention at river network scales. We deployed a nested sensor network and associated sampling in the urbanizing Oyster River watershed in coastal New Hampshire, USA, to quantify storm event-scale loading and retention at network scales. An end member analysis used the relative behavior of reactive nitrate and conservative chloride to infer river network fate of nitrate. In the headwater catchments, nitrate and chloride concentrations are both increasingly diluted with increasing storm size. At the mouth of the watershed, chloride is also diluted, but nitrate tended to increase. The end member analysis suggests that this pattern is the result of high retention during small storms (51-78%) that declines to zero during large storms. Although high frequency nitrate sensors did not alter estimates of fluxes over seasonal time periods compared to less frequent grab sampling, they provide the ability to estimate nitrate flux versus storm size at event scales that is critical for such analyses. Nested sensor networks can improve understanding of the controls of both loading and network scale retention, and therefore also improve management of nonpoint source pollution.

Causes and consequences of habitat fragmentation in river networks.

PubMed

Fuller, Matthew R; Doyle, Martin W; Strayer, David L

2015-10-01

Increases in river fragmentation globally threaten freshwater biodiversity. Rivers are fragmented by many agents, both natural and anthropogenic. We review the distribution and frequency of these major agents, along with their effects on connectivity and habitat quality. Most fragmentation research has focused on terrestrial habitats, but theories and generalizations developed in terrestrial habitats do not always apply well to river networks. For example, terrestrial habitats are usually conceptualized as two-dimensional, whereas rivers often are conceptualized as one-dimensional or dendritic. In addition, river flow often leads to highly asymmetric effects of barriers on habitat and permeability. New approaches tailored to river networks can be applied to describe the network-wide effects of multiple barriers on both connectivity and habitat quality. The net effects of anthropogenic fragmentation on freshwater biodiversity are likely underestimated, because of time lags in effects and the difficulty of generating a single, simple signal of fragmentation that applies to all aquatic species. We conclude by presenting a decision tree for managing freshwater fragmentation, as well as some research horizons for evaluating fragmented riverscapes. © 2015 New York Academy of Sciences.

Dynamic Channel Network Extraction from Satellite Imagery of the Jamuna River

NASA Astrophysics Data System (ADS)

Addink, E. A.; Marra, W. A.; Kleinhans, M. G.

2010-12-01

Evolution of the largest rivers on Earth is poorly understood while their response to global change is dramatic, such as severe drought and flooding problems. Rivers with high annual dynamics, like the Jamuna, allow us to study their response to changing conditions. Most remote-sensing work so far focused only on pixel-based analysis of channels and change detection or manual digitisation of channels, which is far from urgently needed quantifiers of pattern and pattern change. Using a series of Landsat TM images taken at irregular intervals showing inter- and intra-annual variation, we demonstrate that braided rivers can be represented as nearly chain-like directional networks. These can be studied with novel methods gleaned from neurology. These networks provide an integral spatial description of the network and should not be confused with hierarchical hydrological stream network descriptions developed in the ’60s to describe drainage basins. The images were first classified into water, bare sediment and vegetation. The contiguous water body of the river was then selected and translated into a network description with bifurcations and confluences at the nodes, and interconnecting channels. Along the entire river the well-known braiding indices were derived from the network. The channel width is a crucial attribute of the channel network as this allows the calculation of bifurcation asymmetry. The width was also used with channel length as weights to all the elements in the network in the calculation of more advanced measures for the nature and evolution of the channel network. The key step here is to describe river network evolution by identifying the same node in multiple subsequent images as well as new and abandoned nodes, in order to distinguish migration of bifurcations from avulsion processes. Once identified through time, the changes in node position and the changes in the connected channels can be quantified. These changes can potentially be linked to channel migration and vegetation cover along the channels. A network evolves in time by adding or removing channels and their bifurcation- and confluence couples. Using the network topology, we quantified network properties such as `centrality’, which provides a measure for the overall importance of individual channels in a network. This is a novel and robust indicator to assess the effect of a change or engineering measure in a channel on the entire network. The physical basis for downstream propagation of information through a fluvial network is the flood conveyance and sediment transport, and for upstream propagation it is the backwater effect. Using the dynamic network description we can start quantifying the effects of local changes in the network on the entire upstream and downstream network. We conclude that the developed workflow allows the use of novel and useful measures borrowed from other sciences in river network analysis, and provides, e.g., the assessment of the importance of individual branches in a large complicated network.

A framework for human-hydrologic system model development integrating hydrology and water management: application to the Cutzamala water system in Mexico

NASA Astrophysics Data System (ADS)

Wi, S.; Freeman, S.; Brown, C.

2017-12-01

This study presents a general approach to developing computational models of human-hydrologic systems where human modification of hydrologic surface processes are significant or dominant. A river basin system is represented by a network of human-hydrologic response units (HHRUs) identified based on locations where river regulations happen (e.g., reservoir operation and diversions). Natural and human processes in HHRUs are simulated in a holistic framework that integrates component models representing rainfall-runoff, river routing, reservoir operation, flow diversion and water use processes. We illustrate the approach in a case study of the Cutzamala water system (CWS) in Mexico, a complex inter-basin water transfer system supplying the Mexico City Metropolitan Area (MCMA). The human-hydrologic system model for CWS (CUTZSIM) is evaluated in terms of streamflow and reservoir storages measured across the CWS and to water supplied for MCMA. The CUTZSIM improves the representation of hydrology and river-operation interaction and, in so doing, advances evaluation of system-wide water management consequences under altered climatic and demand regimes. The integrated modeling framework enables evaluation and simulation of model errors throughout the river basin, including errors in representation of the human component processes. Heretofore, model error evaluation, predictive error intervals and the resultant improved understanding have been limited to hydrologic processes. The general framework represents an initial step towards fuller understanding and prediction of the many and varied processes that determine the hydrologic fluxes and state variables in real river basins.

Groundwater Discharge of Legacy Nitrogen to River Networks: Linking Regional Groundwater Models to Streambed Groundwater-Surface Water Exchange and Nitrogen Processing

NASA Astrophysics Data System (ADS)

Barclay, J. R.; Helton, A. M.; Briggs, M. A.; Starn, J. J.; Hunt, A.

2017-12-01

Despite years of management, excess nitrogen (N) is a pervasive problem in many aquatic ecosystems. More than half of surface water in the United States is derived from groundwater, and widespread N contamination in aquifers from decades of watershed N inputs suggest legacy N discharging from groundwater may contribute to contemporary N pollution problems in surface waters. Legacy N loads to streams and rivers are controlled by both regional scale flow paths and fine-scale processes that drive N transformations, such as groundwater-surface water exchange across steep redox gradients that occur at stream bed interfaces. Adequately incorporating these disparate scales is a challenge, but it is essential to understanding legacy N transport and making informed management decisions. We developed a regional groundwater flow model for the Farmington River, a HUC-8 basin that drains to the Long Island Sound, a coastal estuary that suffers from elevated N loads despite decades of management, to understand broad patterns of regional transport. To evaluate and refine the regional model, we used thermal infrared imagery paired with vertical temperature profiling to estimate groundwater discharge at the streambed interface. We also analyzed discharging groundwater for multiple N species to quantify fine scale patterns of N loading and transformation via denitrification at the streambed interface. Integrating regional and local estimates of groundwater discharge of legacy N to river networks should improve our ability to predict spatiotemporal patterns of legacy N loading to and transformation within surface waters.

Capability of applying morphometric parameters of relief in river basins for geomorphological zoning of a territory

NASA Astrophysics Data System (ADS)

Ivanov, M. A.; Yermolaev, O. P.

2018-01-01

Information about morphometric characteristics of relief is necessary for researches devoted to geographic characteristics of territory, its zoning, assessment of erosion processes, geoecological condition and others. For the Volga Federal District for the first time a spatial database of geomorphometric parameters 1: 200 000 scale was created, based on a river basin approach. Watersheds are used as a spatial units created by semi-automated method using the terrain and hydrological modeling techniques implemented in the TAS GIS and WhiteBox GIS. As input data DEMs SRTM and Aster GDEM and hydrographic network vectorized from topographic maps were used. Using DEM highlighted above for each river basin, basic morphometric relief characteristics such as mean height, slope steepness, slope length, height range, river network density and factor LS were calculated. Basins belonging to the geomorphological regions and landscape zones was determined, according to the map of geomorphological zoning and landscape map. Analysis of variance revealed a statistically significant relationship between these characteristics and geomorphological regions and landscape zones. Consequently, spatial trends of changes of analyzed morphometric characteristics were revealed.

River rehabilitation for the delivery of multiple ecosystem services at the river network scale.

PubMed

Gilvear, David J; Spray, Chris J; Casas-Mulet, Roser

2013-09-15

This paper presents a conceptual framework and methodology to assist with optimising the outcomes of river rehabilitation in terms of delivery of multiple ecosystem services and the benefits they represent for humans at the river network scale. The approach is applicable globally, but was initially devised in the context of a project critically examining opportunities and constraints on delivery of river rehabilitation in Scotland. The spatial-temporal approach highlighted is river rehabilitation measure, rehabilitation scale, location on the stream network, ecosystem service and timescale specific and could be used as initial scoping in the process of planning rehabilitation at the river network scale. The levels of service delivered are based on an expert-derived scoring system based on understanding how the rehabilitation measure assists in reinstating important geomorphological, hydrological and ecological processes and hence intermediate or primary ecosystem function. The framework permits a "total long-term (>25 years) ecosystem service score" to be calculated which is the cumulative result of the combined effect of the number of and level of ecosystem services delivered over time. Trajectories over time for attaining the long-term ecosystem service score for each river rehabilitation measures are also given. Scores could also be weighted according to societal values and economic valuation. These scores could assist decision making in relation to river rehabilitation at the catchment scale in terms of directing resources towards alternative scenarios. A case study is presented of applying the methodology to the Eddleston Water in Scotland using proposed river rehabilitation options for the catchment to demonstrate the value of the approach. Our overall assertion is that unless sound conceptual frameworks are developed that permit the river network scale ecosystem services of river rehabilitation to be evaluated as part of the process of river basin planning and management, the total benefit of river rehabilitation may well be reduced. River rehabilitation together with a 'vision' and framework within which it can be developed, is fundamental to future success in river basin management. Copyright © 2013 Elsevier Ltd. All rights reserved.

Methane emissions from a human-dominated lowland coastal river network (Shanghai, China)

NASA Astrophysics Data System (ADS)

Wang, D.; Yu, Z.

2017-12-01

Evasion of methane (CH4) in streams and rivers play a critical role in global carbon (C) cycle, offsetting the C uptake by terrestrial ecosystems. However, little is known about CH4 emissions from lowland coastal rivers profoundly modified by anthropogenic perturbations. Here, we report results from a long-term, large-scale study of CH4 partial pressures (pCH4) and evasion rates in the Shanghai river network. The spatiotemporal variability of pCH4 was examined along a land-use gradient and the annual CH4 evasion were estimated to assess its role in regional C budget. During the study period, the median pCH4 from 87 surveyed rivers was 241 μatm. CH4 was oversaturated throughout the river network, CH4 hotpots were concentrated in the small urban rivers and highly discharge-dependent. The annual median fCH4 for each site ranged from 3.1 mg C•m-2•d-1 to 296.6 mg C•m-2•d-1. The annual CH4 evasion were 105 Gg CO2-eq•yr-1 and 96 Gg CO2-eq•yr-1 for the entire river network and the mainland rivers, respectively. Given the rapid urbanization in global coastal areas, more research is needed to quantify the role of lowland coastal rivers as a major landscape C source in global C budget.

A network model shows the importance of coupled processes in the microbial N cycle in the Cape Fear River Estuary

NASA Astrophysics Data System (ADS)

Hines, David E.; Lisa, Jessica A.; Song, Bongkeun; Tobias, Craig R.; Borrett, Stuart R.

2012-06-01

Estuaries serve important ecological and economic functions including habitat provision and the removal of nutrients. Eutrophication can overwhelm the nutrient removal capacity of estuaries and poses a widely recognized threat to the health and function of these ecosystems. Denitrification and anaerobic ammonium oxidation (anammox) are microbial processes responsible for the removal of fixed nitrogen and diminish the effects of eutrophication. Both of these microbial removal processes can be influenced by direct inputs of dissolved inorganic nitrogen substrates or supported by microbial interactions with other nitrogen transforming pathways such as nitrification and dissimilatory nitrate reduction to ammonium (DNRA). The coupling of nitrogen removal pathways to other transformation pathways facilitates the removal of some forms of inorganic nitrogen; however, differentiating between direct and coupled nitrogen removal is difficult. Network modeling provides a tool to examine interactions among microbial nitrogen cycling processes and to determine the within-system history of nitrogen involved in denitrification and anammox. To examine the coupling of nitrogen cycling processes, we built a nitrogen budget mass balance network model in two adjacent 1 cm3 sections of bottom water and sediment in the oligohaline portion of the Cape Fear River Estuary, NC, USA. Pathway, flow, and environ ecological network analyses were conducted to characterize the organization of nitrogen flow in the estuary and to estimate the coupling of nitrification to denitrification and of nitrification and DNRA to anammox. Centrality analysis indicated NH4+ is the most important form of nitrogen involved in removal processes. The model analysis further suggested that direct denitrification and coupled nitrification-denitrification had similar contributions to nitrogen removal while direct anammox was dominant to coupled forms of anammox. Finally, results also indicated that partial nitrification-anammox may play an important role in anammox nitrogen removal in the Cape Fear River Estuary.

Fluvial archives, a valuable record of vertical crustal deformation

NASA Astrophysics Data System (ADS)

Demoulin, A.; Mather, A.; Whittaker, A.

2017-06-01

The study of drainage network response to uplift is important not only for understanding river system dynamics and associated channel properties and fluvial landforms, but also for identifying the nature of crustal deformation and its history. In recent decades, geomorphic analysis of rivers has proved powerful in elucidating the tectonic evolution of actively uplifting and eroding orogens. Here, we review the main recent developments that have improved and expanded qualitative and quantitative information about vertical tectonic motions (the effects of horizontal deformation are not addressed). Channel long profiles have received considerable attention in the literature, and we briefly introduce basic aspects of the behaviour of bedrock rivers from field and numerical modelling perspectives, before describing the various metrics that have been proposed to identify the information on crustal deformation contained within their steady-state characteristics. Then, we review the literature dealing with the transient response of rivers to tectonic perturbation, through the production of knickpoints propagating through the drainage network. Inverse modelling of river profiles for uplift in time and space is also shown to be very effective in reconstructing regional tectonic histories. Finally, we present a synthetic morphometric approach for deducing the tectonic record of fluvial landscapes. As well as the erosional imprint of tectonic forcing, sedimentary deposits, such as fluvial terrace staircases, are also considered as a classical component of tectonic geomorphology. We show that these studies have recently benefited from rapid advances in dating techniques, allowing more reliable reconstruction of incision histories and estimation of incision rates. The combination of progress in the understanding of transient river profiles and larger, more rigorous data sets of terrace ages has led to improved understanding of river erosion and the implications for terrace profile correlation, i.e., extrapolation of local data to entire profiles. Finally, planform changes in fluvial systems are considered at the channel scale in alluvial rivers and regional level in terms of drainage reorganisation. Examples are given of how numerical modelling can efficiently combine with topographic data to shed new light on the (dis)equilibrium state of drainage systems across regional drainage divides.

Bedrock river networks of the Sierra Nevada, USA record westward tilting, large-scale drainage area loss, and distinct patterns and causes of stream incision between the northern and southern Sierra

NASA Astrophysics Data System (ADS)

Beeson, H. W.; McCoy, S. W.

2017-12-01

The timing, rates, and spatial patterns of elevation change in the Sierra Nevada, California, USA, has been the subject of vigorous debate with multiple lines of evidence supporting the contrasting hypotheses that (1) the Sierra has been topographically high throughout the Cenozoic and (2) that the range has experienced a pulse of late Cenozoic uplift. We combined 2-D landscape evolution modeling with topographic analysis of the Sierra Nevada to investigate whether river networks dissecting the range record a change in tectonic forcing during the late Cenozoic. Specifically, we quantify basin geometry, including its area-channel length scaling relationship, fluvial channel steepness, and the spatial distributions of knickzones. We show that, throughout the Sierra, short equilibrated reaches near the mountain front are consistent with an ongoing westward tilt. However, the disequilibrium forms of river profiles north of the Kaweah River reflect large-scale drainage area loss due to network beheading by the Sierra Frontal Fault and/or reestablishment of a fluvial network on an inclined planar surface. Despite these similarities along the length of the range, river network analysis reveals striking differences north and south of approximately 37° N. In the northern Sierra, topographic asymmetry of drainage divides and large differences in cross-divide steady-state elevation suggest mobile divides. Additionally, the broad distribution of normalized knickzone locations, variability in channel steepness and basin shape, and the prevalence of anomalous topology, narrow basins, unadjusted captured reaches, and wind gaps is consistent with large-scale drainage reorganization following incision into an inclined planar surface. In contrast, in the southern Sierra, drainage divides appear more stable and knickzone locations are tightly distributed. We suggest that, although the northern Sierra may currently be tilting westward, the presence of large knickzones and deeply incised valleys in the northern Sierra does not require a recent increase in uplift, but rather could largely reflect the reestablishment of a fluvial network after mid-late Miocene volcanism filled and smoothed preexisting topography. In contrast, it appears that the southern Sierras are responding to a pulse of localized rapid uplift.

Growth laws for delta crevasses in the Mississippi River Delta: observations and modeling

NASA Astrophysics Data System (ADS)

Yocum, T. A.; Georgiou, I. Y.

2016-02-01

River deltas are accumulations of sedimentary deposits delivered by rivers via a network of distributary channels. Worldwide they are threatened by environmental changes, including subsidence, global sea level rise and a suite of other local factors. In the Mississippi River Delta (MRD) these impacts are exemplified, and have led to proposed solutions to build land that include sediment diversions, thereby reinitiating the delta cycle. While economically efficient, there are too few analogs of small deltas aside from laboratory studies, numerical modeling studies, theoretical approaches, and limited field driven observations. Anthropogenic crevasses in the modern delta are large enough to overcome limitations of laboratory deltas, and small enough to allow for "rapid" channel and wetland development, providing an ideal setting to investigate delta development mechanics. Crevasse metrics were obtained using a combination of geospatial tools, extracting key parameters (bifurcation length and width, channel order and depth) that were non-dimensionalized and compared to river-dominated delta networks previously studied. Analysis showed that most crevasses in the MRD appear to obey delta growth laws and delta allometry relationships, suggesting that crevasses do exhibit similar planform metrics to larger Deltas; the distance to mouth bar versus bifurcation order demonstrated to be a very reasonable first order estimate of delta-top footprint. However, some crevasses exhibited different growth metrics. To better understand the hydrodynamic and geomorphic controls governing crevasse evolution in the MRD, we assess delta dynamics via a suite of field observations and numerical modeling in both well-established and newly constructed crevasses. Our analysis suggests that delta development is affected by the relative influence of external (upstream and downstream) and internal controls on the hydrodynamic and sediment transport patterns in these systems.

Real-time flood forecasts & risk assessment using a possibility-theory based fuzzy neural network

NASA Astrophysics Data System (ADS)

Khan, U. T.

2016-12-01

Globally floods are one of the most devastating natural disasters and improved flood forecasting methods are essential for better flood protection in urban areas. Given the availability of high resolution real-time datasets for flood variables (e.g. streamflow and precipitation) in many urban areas, data-driven models have been effectively used to predict peak flow rates in river; however, the selection of input parameters for these types of models is often subjective. Additionally, the inherit uncertainty associated with data models along with errors in extreme event observations means that uncertainty quantification is essential. Addressing these concerns will enable improved flood forecasting methods and provide more accurate flood risk assessments. In this research, a new type of data-driven model, a quasi-real-time updating fuzzy neural network is developed to predict peak flow rates in urban riverine watersheds. A possibility-to-probability transformation is first used to convert observed data into fuzzy numbers. A possibility theory based training regime is them used to construct the fuzzy parameters and the outputs. A new entropy-based optimisation criterion is used to train the network. Two existing methods to select the optimum input parameters are modified to account for fuzzy number inputs, and compared. These methods are: Entropy-Wavelet-based Artificial Neural Network (EWANN) and Combined Neural Pathway Strength Analysis (CNPSA). Finally, an automated algorithm design to select the optimum structure of the neural network is implemented. The overall impact of each component of training this network is to replace the traditional ad hoc network configuration methods, with one based on objective criteria. Ten years of data from the Bow River in Calgary, Canada (including two major floods in 2005 and 2013) are used to calibrate and test the network. The EWANN method selected lagged peak flow as a candidate input, whereas the CNPSA method selected lagged precipitation and lagged mean daily flow as candidate inputs. Model performance metric show that the CNPSA method had higher performance (with an efficiency of 0.76). Model output was used to assess the risk of extreme peak flows for a given day using an inverse possibility-to-probability transformation.

Insights and issues with simulating terrestrial DOC loading of Arctic river networks

USGS Publications Warehouse

Kicklighter, David W.; Hayes, Daniel J.; McClelland, James W.; Peterson, Bruce J.; McGuire, A. David; Melillo, Jerry M.

2013-01-01

Terrestrial carbon dynamics influence the contribution of dissolved organic carbon (DOC) to river networks in addition to hydrology. In this study, we use a biogeochemical process model to simulate the lateral transfer of DOC from land to the Arctic Ocean via riverine transport. We estimate that, over the 20th century, the pan-Arctic watershed has contributed, on average, 32 Tg C/yr of DOC to river networks emptying into the Arctic Ocean with most of the DOC coming from the extensive area of boreal deciduous needle-leaved forests and forested wetlands in Eurasian watersheds. We also estimate that the rate of terrestrial DOC loading has been increasing by 0.037 Tg C/yr2 over the 20th century primarily as a result of climate-induced increases in water yield. These increases have been offset by decreases in terrestrial DOC loading caused by wildfires. Other environmental factors (CO2 fertilization, ozone pollution, atmospheric nitrogen deposition, timber harvest, agriculture) are estimated to have relatively small effects on terrestrial DOC loading to Arctic rivers. The effects of the various environmental factors on terrestrial carbon dynamics have both offset and enhanced concurrent effects on hydrology to influence terrestrial DOC loading and may be changing the relative importance of terrestrial carbon dynamics on this carbon flux. Improvements in simulating terrestrial DOC loading to pan-Arctic rivers in the future will require better information on the production and consumption of DOC within the soil profile, the transfer of DOC from land to headwater streams, the spatial distribution of precipitation and its temporal trends, carbon dynamics of larch-dominated ecosystems in eastern Siberia, and the role of industrial organic effluents on carbon budgets of rivers in western Russia.

Can spatial statistical river temperature models be transferred between catchments?

NASA Astrophysics Data System (ADS)

Jackson, Faye L.; Fryer, Robert J.; Hannah, David M.; Malcolm, Iain A.

2017-09-01

There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax) within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS_Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax. However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable. The LS_Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable. These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across multiple catchments and larger spatial scales.

Impacts of the Indian Rivers Inter-link Project on Sediment Transport to River Deltas

NASA Astrophysics Data System (ADS)

Higgins, S.; Overeem, I.; Syvitski, J. P.

2015-12-01

The Indian Rivers Inter-link project is a proposal by the Indian government to link several of India's major rivers via a network of reservoirs and canals. Variations of the IRI have been discussed since 1980, but the current plan has recently received increased support from the Indian government. Construction on three canals has controversially begun. If the Inter-link project moves forward, fourteen canals will divert water from tributaries of the Ganges and Brahmaputra rivers to areas in the west, where fresh water is needed for irrigation. Additional canals would transport Himalayan sediments 500 km south to the Mahanadi delta and more than 1000 km south to the Godavari and Krishna deltas. We investigate the impacts of the proposed diversions on sediment transport to the Mahanadi/Brahmani, Godavari, and Krishna deltas in India and the Ganges-Brahmaputra Delta in Bangladesh. We map the entire river network and the proposed new nodes and connections. Changing watersheds are delineated using the Terrain Analysis Using Digital Elevation Models (TauDEM) Suite. Climate data comes from interpolation between observed precipitation stations located in China, Nepal, India, Bhutan and Bangladesh. Changes in water discharge due to the proposed canals are simulated using HydroTrend, a climate-driven hydrological water balance and transport model that incorporates drainage area, discharge, relief, temperature, basin-average lithology, and anthropogenic influences. Simulated river discharge is validated against observations from gauging stations archived by the Global Runoff Data Center (GRDC). HydroTrend is then used to investigate sediment transport changes that may result from the proposed canals. We also quantify changes in contributing areas for the outlets of nine major Indian rivers, showing that more than 50% of the land in India will contribute a portion of its runoff to a new outlet should the entire canal system be constructed.

An Emergent Bifurcation Angle on River Deltas

NASA Astrophysics Data System (ADS)

Shaw, J.; Coffey, T.

2017-12-01

Distributary channel bifurcations on river deltas are important features that control water, sediment, and nutrient routing and can dictate large-scale stratigraphic heterogeneity. We use theory originally developed for a special case of tributary networks to understand the dynamics of distributary channel bifurcations. Interestingly, bifurcations in groundwater-fed tributary networks have been shown to evolve dependent on the diffusive flow field outside the network. These networks possess a characteristic bifurcation angle of 72°, due to Laplacian flow in the groundwater flow field near tributary channel tips (gradient2h2=0, where h is water surface elevation). We develop and test the hypothesis that bifurcation angles in distributary channel networks are likewise dictated by the external flow field, in this case the shallow surface water surrounding the subaqueous portion of distributary channel bifurcations in a deltaic setting. We measured 130 unique distributary channel bifurcations in a single experimental delta and in 10 natural deltas, yielding a mean angle of 70.35°±2.59° (95% confidence interval), in line with the theoretical prediction. These data and hydrodynamic scaling arguments convince us that distributary network formation can result simply from the coupling of (Laplacian) extra-channel flow to channels along subaqueous channel networks. The simplicity of this model provides new insight into distributary network formation and its geomorphic and stratigraphic consequences.

Snow mass and river flows modelled using GRACE total water storage observations

NASA Astrophysics Data System (ADS)

Wang, S.

2017-12-01

Snow mass and river flow measurements are difficult and less accurate in cold regions due to the hash environment. Floods in cold regions are commonly a result of snowmelt during the spring break-up. Flooding is projected to increase with climate change in many parts of the world. Forecasting floods from snowmelt remains a challenge due to scarce and quality issues in basin-scale snow observations and lack of knowledge for cold region hydrological processes. This study developed a model for estimating basin-level snow mass (snow water equivalent SWE) and river flows using the total water storage (TWS) observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. The SWE estimation is based on mass balance approach which is independent of in situ snow gauge observations, thus largely eliminates the limitations and uncertainties with traditional in situ or remote sensing snow estimates. The model forecasts river flows by simulating surface runoff from snowmelt and the corresponding baseflow from groundwater discharge. Snowmelt is predicted using a temperature index model. Baseflow is predicted using a modified linear reservoir model. The model also quantifies the hysteresis between the snowmelt and the streamflow rates, or the lump time for water travel in the basin. The model was applied to the Red River Basin, the Mackenzie River Basin, and the Hudson Bay Lowland Basins in Canada. The predicted river flows were compared with the observed values at downstream hydrometric stations. The results were also compared to that for the Lower Fraser River obtained in a separate study to help better understand the roles of environmental factors in determining flood and their variations with different hydroclimatic conditions. This study advances the applications of space-based time-variable gravity measurements in cold region snow mass estimation, river flow and flood forecasting. It demonstrates a relatively simple method that only needs GRACE TWS and temperature data for river flow or flood forecasting. The model can be particularly useful for regions with spare observation networks, and can be used in combination with other available methods to help improve the accuracy in river flow and flood forecasting over cold regions.

Nitrate removal in deep sediments of a nitrogen-rich river network: A test of a conceptual model

USGS Publications Warehouse

Stelzer, Robert S.; Bartsch, Lynn

2012-01-01

Many estimates of nitrogen removal in streams and watersheds do not include or account for nitrate removal in deep sediments, particularly in gaining streams. We developed and tested a conceptual model for nitrate removal in deep sediments in a nitrogen-rich river network. The model predicts that oxic, nitrate-rich groundwater will become depleted in nitrate as groundwater upwelling through sediments encounters a zone that contains buried particulate organic carbon, which promotes redox conditions favorable for nitrate removal. We tested the model at eight sites in upwelling reaches of lotic ecosystems in the Waupaca River Watershed that varied by three orders of magnitude in groundwater nitrate concentration. We measured denitrification potential in sediment core sections to 30 cm and developed vertical nitrate profiles to a depth of about 1 m with peepers and piezometer nests. Denitrification potential was higher, on average, in shallower core sections. However, core sections deeper than 5 cm accounted for 70%, on average, of the depth-integrated denitrification potential. Denitrification potential increased linearly with groundwater nitrate concentration up to 2 mg NO3-N/L but the relationship broke down at higher concentrations (> 5 mg NO3-N/L), a pattern that suggests nitrate saturation. At most sites groundwater nitrate declined from high concentrations at depth to much lower concentrations prior to discharge into the surface water. The profiles suggested that nitrate removal occurred at sediment depths between 20 and 40 cm. Dissolved oxygen concentrations were much higher in deep sediments than in pore water at 5 cm sediment depth at most locations. The substantial denitrification potential in deep sediments coupled with the declines in nitrate and dissolved oxygen concentrations in upwelling groundwater suggest that our conceptual model for nitrate removal in deep sediments is applicable to this river network. Our results suggest that nitrate removal rates can be high in deep sediments of upwelling stream reaches, which may have implications for efforts to understand and quantify nitrogen transport and removal at larger scales.

Coupled modelling of groundwater flow-heat transport for assessing river-aquifer interactions

NASA Astrophysics Data System (ADS)

Engeler, I.; Hendricks Franssen, H. J.; Müller, R.; Stauffer, F.

2010-05-01

A three-dimensional finite element model for coupled variably saturated groundwater flow and heat transport was developed for the aquifer below the city of Zurich. The piezometric heads in the aquifer are strongly influenced by the river Limmat. In the model region, the river Limmat looses water to the aquifer. The river-aquifer interaction was modelled with the standard linear leakage concept. Coupling was implemented by considering temperature dependence of the hydraulic conductivity and of the leakage coefficient (via water viscosity) and density dependent transport. Calibration was performed for isothermal conditions by inverse modelling using the pilot point method. Independent model testing was carried out with help of the available dense monitoring network for piezometric heads and groundwater temperature. The model was tested by residuals analysis with the help of measurements for both groundwater temperature and head. The comparison of model results and measurements showed high accuracy for temperature except for the Southern part of the model area, where important geological heterogeneity is expected, which could not be reproduced by the model. The comparison of simulated and measured head showed that especially in the vicinity of river Limmat model results were improved by a temperature dependent leakage coefficient. Residuals were reduced up to 30% compared to isothermal leakage coefficients. This holds particularly for regions, where the river stage is considerably above the groundwater level. Furthermore additional analysis confirmed prior findings, that seepage rates during flood events cannot be reproduced with the implemented linear leakage-concept. Infiltration during flood events is larger than expected, which can be potentially attributed to additional infiltration areas. It is concluded that the temperature dependent leakage concept improves the model results for this study area significantly, and that we expect that this is also for other areas the case.

Monitoring-well network and sampling design for ground-water quality, Wind River Indian Reservation, Wyoming

USGS Publications Warehouse

Mason, Jon P.; Sebree, Sonja K.; Quinn, Thomas L.

2005-01-01

The Wind River Indian Reservation, located in parts of Fremont and Hot Springs Counties, Wyoming, has a total land area of more than 3,500 square miles. Ground water on the Wind River Indian Reservation is a valuable resource for Shoshone and Northern Arapahoe tribal members and others who live on the Reservation. There are many types of land uses on the Reservation that have the potential to affect the quality of ground-water resources. Urban areas, rural housing developments, agricultural lands, landfills, oil and natural gas fields, mining, and pipeline utility corridors all have the potential to affect ground-water quality. A cooperative study was developed between the U.S. Geological Survey and the Wind River Environmental Quality Commission to identify areas of the Reservation that have the highest potential for ground-water contamination and develop a comprehensive plan to monitor these areas. An arithmetic overlay model for the Wind River Indian Reservation was created using seven geographic information system data layers representing factors with varying potential to affect ground-water quality. The data layers used were: the National Land Cover Dataset, water well density, aquifer sensitivity, oil and natural gas fields and petroleum pipelines, sites with potential contaminant sources, sites that are known to have ground-water contamination, and National Pollutant Discharge Elimination System sites. A prioritization map for monitoring ground-water quality on the Reservation was created using the model. The prioritization map ranks the priority for monitoring ground-water quality in different areas of the Reservation as low, medium, or high. To help minimize bias in selecting sites for a monitoring well network, an automated stratified random site-selection approach was used to select 30 sites for ground-water quality monitoring within the high priority areas. In addition, the study also provided a sampling design for constituents to be monitored, sampling frequency, and a simple water-table level observation well network.

A stacking ensemble learning framework for annual river ice breakup dates

NASA Astrophysics Data System (ADS)

Sun, Wei; Trevor, Bernard

2018-06-01

River ice breakup dates (BDs) are not merely a proxy indicator of climate variability and change, but a direct concern in the management of local ice-caused flooding. A framework of stacking ensemble learning for annual river ice BDs was developed, which included two-level components: member and combining models. The member models described the relations between BD and their affecting indicators; the combining models linked the predicted BD by each member models with the observed BD. Especially, Bayesian regularization back-propagation artificial neural network (BRANN), and adaptive neuro fuzzy inference systems (ANFIS) were employed as both member and combining models. The candidate combining models also included the simple average methods (SAM). The input variables for member models were selected by a hybrid filter and wrapper method. The performances of these models were examined using the leave-one-out cross validation. As the largest unregulated river in Alberta, Canada with ice jams frequently occurring in the vicinity of Fort McMurray, the Athabasca River at Fort McMurray was selected as the study area. The breakup dates and candidate affecting indicators in 1980-2015 were collected. The results showed that, the BRANN member models generally outperformed the ANFIS member models in terms of better performances and simpler structures. The difference between the R and MI rankings of inputs in the optimal member models may imply that the linear correlation based filter method would be feasible to generate a range of candidate inputs for further screening through other wrapper or embedded IVS methods. The SAM and BRANN combining models generally outperformed all member models. The optimal SAM combining model combined two BRANN member models and improved upon them in terms of average squared errors by 14.6% and 18.1% respectively. In this study, for the first time, the stacking ensemble learning was applied to forecasting of river ice breakup dates, which appeared promising for other river ice forecasting problems.

February 2012 workshop jumpstarts the Mekong Fish Monitoring Network

USGS Publications Warehouse

Andersen, Matthew E.; Ainsley, Shaara M.

2012-01-01

The Mekong River in Southeast Asia travels through a basin rich in natural resources. The river originates on the northern slope of the world's tallest mountains, the Himalaya Range, and then drops elevation quickly through steep mountain gorges, tumbling out of China into Myanmar (Burma) and the Lao People's Democratic Republic (Lao PDR). The precipitous terrain of Lao PDR and Thailand generates interest in the river and its tributaries for hydropower development. The terrain, soils, water, and climate make it one of the world's most biologically rich regions. The Mekong's bounty is again on display in the Mekong River Delta, where rice production has successfully been increased to high levels making Vietnam second only to Thailand as the world's largest rice exporters. At least 800 fish species contribute to the natural resource bounty of the Mekong River and are the basis for one of the world's most productive fisheries that provide the primary protein source to more than 50 million people. Against this backdrop of rich natural resources, the U.S. Geological Survey (USGS) is working with the consulting firm FISHBIO, colleagues from the international Delta Research and Global Observation Network (DRAGON) Institute, and a broad contingent of Southeast Asian representatives and partners from abroad to increase knowledge of the Mekong River fisheries and to develop the capacity of permanent residents to investigate and understand these fisheries resources. With the Lower Mekong Basin (LMB) region facing the likelihood of significant environmental changes as a result of both human activities and global climate change, enhancing environmental understanding is critical. To encourage cooperation among the LMB scientists and managers in the study of the Mekong River's fisheries, FISHBIO and the USGS, with generous support from the U.S. State Department, hosted a workshop in Phnom Penh, Cambodia, in February 2012. Workshop participants were from Lao PDR, Thailand, Cambodia, and Vietnam. Representatives from the governments, universities, nongovernmental organizations, and the Mekong River Commission discussed current and potential methods and mechanisms of the Mekong Fish Monitoring Network. The goals of the workshop were to determine if the Network and associated databases were of interest and value to the LMB nations, to determine if future fisheries monitoring data would be comparable among the nations, and to establish methods and an organizational structure for collaborating on future monitoring and research. The participants in this international workshop agreed that the Network would be useful but would require additional funding to secure their full participation. The USGS and FISHBIO are collaboratively seeking additional funding to expand research participation and projects in all four LMB nations. If the Network can facilitate cooperation among many fisheries researchers in the LMB, the basin would become a model of cooperative international fishery studies and would increase the understanding of a river basin rich in natural resources.

Research on the exponential growth effect on network topology: Theoretical and empirical analysis

NASA Astrophysics Data System (ADS)

Li, Shouwei; You, Zongjun

Integrated circuit (IC) industry network has been built in Yangtze River Delta with the constant expansion of IC industry. The IC industry network grows exponentially with the establishment of new companies and the establishment of contacts with old firms. Based on preferential attachment and exponential growth, the paper presents the analytical results in which the vertices degree of scale-free network follows power-law distribution p(k)˜k‑γ (γ=2β+1) and parameter β satisfies 0.5≤β≤1. At the same time, we find that the preferential attachment takes place in a dynamic local world and the size of the dynamic local world is in direct proportion to the size of whole networks. The paper also gives the analytical results of no-preferential attachment and exponential growth on random networks. The computer simulated results of the model illustrate these analytical results. Through some investigations on the enterprises, this paper at first presents the distribution of IC industry, composition of industrial chain and service chain firstly. Then, the correlative network and its analysis of industrial chain and service chain are presented. The correlative analysis of the whole IC industry is also presented at the same time. Based on the theory of complex network, the analysis and comparison of industrial chain network and service chain network in Yangtze River Delta are provided in the paper.

Hybrid Multiscale Simulation of Hydrologic and Biogeochemical Processes in the River-Groundwater Interaction Zone

NASA Astrophysics Data System (ADS)

Yang, X.; Scheibe, T. D.; Chen, X.; Hammond, G. E.; Song, X.

2015-12-01

The zone in which river water and groundwater mix plays an important role in natural ecosystems as it regulates the mixing of nutrients that control biogeochemical transformations. Subsurface heterogeneity leads to local hotspots of microbial activity that are important to system function yet difficult to resolve computationally. To address this challenge, we are testing a hybrid multiscale approach that couples models at two distinct scales, based on field research at the U. S. Department of Energy's Hanford Site. The region of interest is a 400 x 400 x 20 m macroscale domain that intersects the aquifer and the river and contains a contaminant plume. However, biogeochemical activity is high in a thin zone (mud layer, <1 m thick) immediately adjacent to the river. This microscale domain is highly heterogeneous and requires fine spatial resolution to adequately represent the effects of local mixing on reactions. It is not computationally feasible to resolve the full macroscale domain at the fine resolution needed in the mud layer, and the reaction network needed in the mud layer is much more complex than that needed in the rest of the macroscale domain. Hence, a hybrid multiscale approach is used to efficiently and accurately predict flow and reactive transport at both scales. In our simulations, models at both scales are simulated using the PFLOTRAN code. Multiple microscale simulations in dynamically defined sub-domains (fine resolution, complex reaction network) are executed and coupled with a macroscale simulation over the entire domain (coarse resolution, simpler reaction network). The objectives of the research include: 1) comparing accuracy and computing cost of the hybrid multiscale simulation with a single-scale simulation; 2) identifying hot spots of microbial activity; and 3) defining macroscopic quantities such as fluxes, residence times and effective reaction rates.

Explore the Impacts of River Flow and Water Quality on Fish Communities

NASA Astrophysics Data System (ADS)

Tsai, W. P.; Chang, F. J.; Lin, C. Y.; Hu, J. H.; Yu, C. J.; Chu, T. J.

2015-12-01

Owing to the limitation of geographical environment in Taiwan, the uneven temporal and spatial distribution of rainfall would cause significant impacts on river ecosystems. To pursue sustainable water resources development, integrity and rationality is important to water management planning. The water quality and the flow regimes of rivers are closely related to each other and affect river ecosystems simultaneously. Therefore, this study collects long-term observational heterogeneity data, which includes water quality parameters, stream flow and fish species in the Danshui River of norther Taiwan, and aims to explore the complex impacts of water quality and flow regime on fish communities in order to comprehend the situations of the eco-hydrological system in this river basin. First, this study improves the understanding of the relationship between water quality parameters, flow regime and fish species by using artificial neural networks (ANNs). The Self-organizing feature map (SOM) is an unsupervised learning process used to cluster, analyze and visualize a large number of data. The results of SOM show that nine clusters (3x3) forms the optimum map size based on the local minimum values of both quantization error (QE) and topographic error (TE). Second, the fish diversity indexes are estimated by using the Adapted network-based fuzzy inference system (ANFIS) based on key input factors determined by the Gamma Test (GT), which is a useful tool for reducing model dimension and the structure complexity of ANNs. The result reveals that the constructed models can effectively estimate fish diversity indexes and produce good estimation performance based on the 9 clusters identified by the SOM, in which RMSE is 0.18 and CE is 0.84 for the training data set while RMSE is 0.20 and CE is 0.80 for the testing data set.

Lithologic controls on landscape dynamics and aquatic species evolution in post-orogenic mountains

NASA Astrophysics Data System (ADS)

Gallen, Sean F.

2018-07-01

Determining factors that modify Earth's topography is essential for understanding continental mass and nutrient fluxes, and the evolution and diversity of species. Contrary to the paradigm of slow, steady topographic decay after orogenesis ceases, nearly all ancient mountain belts exhibit evidence of unsteady landscape evolution at large spatial scales. External forcing from uplift from dynamic mantle processes or climate change is commonly invoked to explain the unexpected dynamics of dead orogens, yet direct evidence supporting such inferences is generally lacking. Here I use quantitative analysis of fluvial topography in the southern Appalachian Mountains to show that the exhumation of rocks of variable erosional resistance exerts a fundamental, autogenic control on the evolution of post-orogenic landscapes that continually reshapes river networks. I characterize the spatial pattern of erodibility associated with individual rock-types, and use inverse modeling of river profiles to document a ∼150 m base level fall event at 9 ± 3 Ma in the Upper Tennessee drainage basin. This analysis, combined with existing geological and biological data, demonstrates that base level fall was triggered by capture of the Upper Tennessee River basin by the Lower Tennessee River basin in the Late Miocene. I demonstrate that rock-type triggered changes in river network topology gave rise to the modern Tennessee River system and enhanced erosion rates, changed sediment flux and dispersal patterns, and altered bio-evolutionary pathways in the southeastern U.S.A., a biodiversity hotspot. These findings suggest that variability observed in the stratigraphic, geomorphic, and biologic archives of tectonically quiescent regions does not require external drivers, such as geodynamic or climate forcing, as is typically the interpretation. Rather, my findings lead to a new model of inherently unsteady evolution of ancient mountain landscapes due to the geologic legacy of plate tectonics.

Synthetic river valleys: Creating prescribed topography for form-process inquiry and river rehabilitation design

NASA Astrophysics Data System (ADS)

Brown, R. A.; Pasternack, G. B.; Wallender, W. W.

2014-06-01

The synthesis of artificial landforms is complementary to geomorphic analysis because it affords a reflection on both the characteristics and intrinsic formative processes of real world conditions. Moreover, the applied terminus of geomorphic theory is commonly manifested in the engineering and rehabilitation of riverine landforms where the goal is to create specific processes associated with specific morphology. To date, the synthesis of river topography has been explored outside of geomorphology through artistic renderings, computer science applications, and river rehabilitation design; while within geomorphology it has been explored using morphodynamic modeling, such as one-dimensional simulation of river reach profiles, two-dimensional simulation of river networks, and three-dimensional simulation of subreach scale river morphology. To date, no approach allows geomorphologists, engineers, or river rehabilitation practitioners to create landforms of prescribed conditions. In this paper a method for creating topography of synthetic river valleys is introduced that utilizes a theoretical framework that draws from fluvial geomorphology, computer science, and geometric modeling. Such a method would be valuable to geomorphologists in understanding form-process linkages as well as to engineers and river rehabilitation practitioners in developing design surfaces that can be rapidly iterated. The method introduced herein relies on the discretization of river valley topography into geometric elements associated with overlapping and orthogonal two-dimensional planes such as the planform, profile, and cross section that are represented by mathematical functions, termed geometric element equations. Topographic surfaces can be parameterized independently or dependently using a geomorphic covariance structure between the spatial series of geometric element equations. To illustrate the approach and overall model flexibility examples are provided that are associated with mountain, lowland, and hybrid synthetic river valleys. To conclude, recommended advances such as multithread channels are discussed along with potential applications.

Hydrologic analysis of Mojave River Basin, California, using electric analog model

USGS Publications Warehouse

Hardt, W.F.

1971-01-01

The water needs of the Mojave River basin will increase because of population and industrial growth. The Mojave Water Agency is responsible for providing sufficient water of good quality for the full economic development of the area. The U.S. Geological Survey suggested an electric analog model of the basin as a predictive tool to aid management. About 1,375 square miles of the alluvial basin was simulated by a passive resistor-capacitor network. The Mojave River, the main source of recharge, was simulated by subdividing the river into 13 reaches, depending on intermittent or perennial flow and on phreatophytes. The water loss to the aquifer was based on records at five gaging stations. The aquifer system depends on river recharge to maintain the water table as most of the ground-water pumping and development is adjacent to the river. The accuracy and reliability of the model was assessed by comparing the water-level changes computed by the model for the period 1930-63 with the changes determined from field data for the same period. The model was used to predict the effects on the physical system by determining basin-wide water-level changes from 1930-2000 under different pumping rates and extremes in flow of the Mojave River. Future pumping was based on the 1960-63 rate, on an increase of 20 percent from this rate, and on population projections to 2000 in the Barstow area. For future predictions, the Mojave River was modeled as average flow based on 1931-65 records and also as high flow, 1937-46, and low flow, 1947-65. Other model runs included water-level change 1930-63 assuming aquifer depletion only and no recharge, effects of a well field pumping 10,000 acre-feet in 4 months north of Victorville and southeast of Yermo, and effects of importing 10,000, 35,000, and 50,800 acre-feet of water per year from the California Water Project into the Mojave River for conveyance downstream.

Assessment of global nitrogen pollution in rivers using an integrated biogeochemical modeling framework.

PubMed

He, Bin; Kanae, Shinjiro; Oki, Taikan; Hirabayashi, Yukiko; Yamashiki, Yosuke; Takara, Kaoru

2011-04-01

This study has analyzed the global nitrogen loading of rivers resulting from atmospheric deposition, direct discharge, and nitrogenous compounds generated by residential, industrial, and agricultural sources. Fertilizer use, population distribution, land cover, and social census data were used in this study. A terrestrial nitrogen cycle model with a 24-h time step and 0.5° spatial resolution was developed to estimate nitrogen leaching from soil layers in farmlands, grasslands, and natural lands. The N-cycle in this model includes the major processes of nitrogen fixation, nitrification, denitrification, immobilization, mineralization, leaching, and nitrogen absorption by vegetation. The previously developed Total Runoff Integrating Pathways network was used to analyze nitrogen transport from natural and anthropogenic sources through river channels, as well as the collecting and routing of nitrogen to river mouths by runoff. Model performance was evaluated through nutrient data measured at 61 locations in several major world river basins. The dissolved inorganic nitrogen concentrations calculated by the model agreed well with the observed data and demonstrate the reliability of the proposed model. The results indicate that nitrogen loading in most global rivers is proportional to the size of the river basin. Reduced nitrate leaching was predicted for basins with low population density, such as those at high latitudes or in arid regions. Nitrate concentration becomes especially high in tropical humid river basins, densely populated basins, and basins with extensive agricultural activity. On a global scale, agriculture has a significant impact on the distribution of nitrogenous compound pollution. The map of nitrate distribution indicates that serious nitrogen pollution (nitrate concentration: 10-50 mg N/L) has occurred in areas with significant agricultural activities and small precipitation surpluses. Analysis of the model uncertainty also suggests that the nitrate export in most rivers is sensitive to the amount of nitrogen leaching from agricultural lands. Copyright © 2011 Elsevier Ltd. All rights reserved.

Improving Simulations of Extreme Flows by Coupling a Physically-based Hydrologic Model with a Machine Learning Model

NASA Astrophysics Data System (ADS)

Mohammed, K.; Islam, A. S.; Khan, M. J. U.; Das, M. K.

2017-12-01

With the large number of hydrologic models presently available along with the global weather and geographic datasets, streamflows of almost any river in the world can be easily modeled. And if a reasonable amount of observed data from that river is available, then simulations of high accuracy can sometimes be performed after calibrating the model parameters against those observed data through inverse modeling. Although such calibrated models can succeed in simulating the general trend or mean of the observed flows very well, more often than not they fail to adequately simulate the extreme flows. This causes difficulty in tasks such as generating reliable projections of future changes in extreme flows due to climate change, which is obviously an important task due to floods and droughts being closely connected to people's lives and livelihoods. We propose an approach where the outputs of a physically-based hydrologic model are used as an input to a machine learning model to try and better simulate the extreme flows. To demonstrate this offline-coupling approach, the Soil and Water Assessment Tool (SWAT) was selected as the physically-based hydrologic model, the Artificial Neural Network (ANN) as the machine learning model and the Ganges-Brahmaputra-Meghna (GBM) river system as the study area. The GBM river system, located in South Asia, is the third largest in the world in terms of freshwater generated and forms the largest delta in the world. The flows of the GBM rivers were simulated separately in order to test the performance of this proposed approach in accurately simulating the extreme flows generated by different basins that vary in size, climate, hydrology and anthropogenic intervention on stream networks. Results show that by post-processing the simulated flows of the SWAT models with ANN models, simulations of extreme flows can be significantly improved. The mean absolute errors in simulating annual maximum/minimum daily flows were minimized from 4967 cusecs to 1294 cusecs for Ganges, from 5695 cusecs to 2115 cusecs for Brahmaputra and from 689 cusecs to 321 cusecs for Meghna. Using this approach, simulations of hydrologic variables other than streamflow can also be improved given that a decent amount of observed data for that variable is available.

Assessment of climate change impacts on streamflow dynamics in the headwaters of the Amazon River basin

NASA Astrophysics Data System (ADS)

Yoon, Y.; Beighley, E.

2015-12-01

The Amazon River basin is the largest watershed in the world containing thousands of tributaries. Although the mainstream and its larger tributaries have been the focus on much research, there has been few studies focused on the hydrodynamics of smaller rivers in the foothills of the Andes Mountains. These smaller rivers are of particular importance for the fishery industry because fish migrate up these headwater rivers to spawn. During the rainy season, fish wait for storm event to increase water depths to a sufficient level for their passage. Understanding how streamflow dynamics will change in response to future conditions is vital for the sustainable management of the fishery industry. In this paper, we focus on improving the accuracy of river discharge estimates on relatively small-scale sub-catchments (100 ~ 40,000 km2) in the headwaters of the Amazon River basin. The Hillslope River Routing (HRR) hydrologic model and remotely sensed datasets are used. We provide annual runoff, seasonal patterns, and daily discharge characteristics for 81 known migration reaches. The model is calibrated for the period 2000-2014 and climate forecasts for the period 2070-2100 are used to assess future changes in streamflow dynamics. The forecasts for the 2070 to 2100 period were obtained by selecting 5 climate models from IPCC's Fifth Assessment Report (AR5) Coupled Model Intercomparison Project Phase 5 (CMIP5) based on their ability to represent the main aspects of recent (1970 to 2000) Amazon climate. The river network for the HRR model is developing using surface topography based on the SRTM digital elevation model. Key model forcings include precipitation (TRMM 3B42) and evapotranspiration (MODIS ET, MOD16). Model parameters for soil depth, hydraulic conductivity, runoff coefficients and lateral routing were initially approximated based on literature values and adjusted during calibration. Measurements from stream gauges located near the reaches of interest were used for calibration. Model calibration results and simulated changes in future streamflow dynamics for the 81 river reaches are presented.

Upper Washita River Experimental Watersheds: Physiography Data

USDA-ARS?s Scientific Manuscript database

Physiographic data such as digital elevation models (DEMs), soils, geology, stream channel network characteristics, and channel stability data are essential for understanding the complex hydrologic cycle and chemical transport processes of any given study area. This paper describes physiographic dat...

Using Deep Learning to Assess Future Flood Magnitude and Frequency in the Semi-arid and Snowmelt-dominated Missouri River Headwater Catchments

NASA Astrophysics Data System (ADS)

Francois, B.; Wi, S.; Brown, C.

2017-12-01

There has been growing interest for hydrologists and water resources managers about the emergence of non-stationarities associated with the hydro-meteorological processes driving floods. Among the potential causes of non-stationarity, climate change is deemed a major one. Understanding the effects of climate change on hydrological regimes of the Missouri River is challenging. In this region, floods are mainly triggered by snow melting, either when temperatures get mild in spring/summer, or when rain falls over snow in early spring and fall. The sparsely gauged and topographically complex area degrades the value of hydrological modeling that otherwise might foreshadow the evolution of hydro-meteorological interactions between precipitation, temperature and snow. In this work, we explore the utility of Deep Learning (DL) for assessing flood magnitude change under climate change. By using multiple hidden layers within artificial neural networks (ANNs), DL allows modeling complex interactions between inputs (i.e. precipitation, temperature and snow water equivalent) and outputs (i.e. water discharge). The objective is to develop a parsimonious model of the flood processes that maintain the contribution of nonstationary factors and their potential evolution under climate change, while reducing extraneous factors not central to flood generation. By comparing ANN's performance with outputs from two hydrological models of differing complexity (i.e. VIC, SAC-SMA), we evaluate the modeling capability of ANNs for three snow-dominated catchments that represent different flood regimes (Yellowstone River at Billings (MT; USGS 06214500), Powder River near Locate (MT; USGS 06326500) and James River near Scotland (SD; USGS 06478500)). Nonstationary inputs for each flood process model are derived from dynamically downscaled climate projections (from the NARCCAP experiment) to project floods in the three selected catchments. The uncertainty of future snow projections as well as its impact on spring flooding are explored. Future flood frequency obtained with ANNs is compared with the one obtained thanks to hydrological models and with the traditional approach as described in Bulletin 17C. Keywords: Flood, Climate-change, Snow, Neural Networks

Applications of a New England stream temperature model to evaluate distribution of thermal regimes and sensitivity to change in riparian condition

EPA Science Inventory

We have applied a statistical stream network (SSN) model to predict stream thermal metrics (summer monthly medians, growing season maximum magnitude and timing, and daily rates of change) across New England nontidal streams and rivers, excluding northern Maine watersheds that ext...

Introduction to stream network habitat analysis

USGS Publications Warehouse

Bartholow, John M.; Waddle, Terry J.

1986-01-01

Increasing demands on stream resources by a variety of users have resulted in an increased emphasis on studies that evaluate the cumulative effects of basinwide water management programs. Network habitat analysis refers to the evaluation of an entire river basin (or network) by predicting its habitat response to alternative management regimes. The analysis principally focuses on the biological and hydrological components of the riv er basin, which include both micro- and macrohabitat. (The terms micro- and macrohabitat are further defined and discussed later in this document.) Both conceptual and analytic models are frequently used for simplifying and integrating the various components of the basin. The model predictions can be used in developing management recommendations to preserve, restore, or enhance instream fish habitat. A network habitat analysis should begin with a clear and concise statement of the study objectives and a thorough understanding of the institutional setting in which the study results will be applied. This includes the legal, social, and political considerations inherent in any water management setting. The institutional environment may dictate the focus and level of detail required of the study to a far greater extent than the technical considerations. After the study objectives, including species on interest, and institutional setting are collectively defined, the technical aspects should be scoped to determine the spatial and temporal requirements of the analysis. A macro level approach should be taken first to identify critical biological elements and requirements. Next, habitat availability is quantified much as in a "standard" river segment analysis, with the likely incorporation of some macrohabitat components, such as stream temperature. Individual river segments may be aggregated to represent the networkwide habitat response of alternative water management schemes. Things learned about problems caused or opportunities generated may be fed back to the design of new alternatives, which themselves may be similarly tested. One may get as sophisticated an analysis as the decisionmaking process demands. Figure 1 shows a decision point that asks whether the results from the micro- or macrohabitat models display cumulative or synergistic effects. If they do, then network habitat analysis is the appropriate tool. We are left, however, in a difficult bind. We may not know a priori whether the effects are cumulative or synergistic unless some network-type questions are investigated as part of the scoping process. The next several sections raise issues designed to alert the modeler to relevant questions necessary to address this paradox.

Delineating riparian zones for entire river networks using geomorphological criteria

NASA Astrophysics Data System (ADS)

Fernández, D.; Barquín, J.; Álvarez-Cabria, M.; Peñas, F. J.

2012-03-01

Riparian zone delineation is a central issue for riparian and river ecosystem management, however, criteria used to delineate them are still under debate. The area inundated by a 50-yr flood has been indicated as an optimal hydrological descriptor for riparian areas. This detailed hydrological information is, however, not usually available for entire river corridors, and is only available for populated areas at risk of flooding. One of the requirements for catchment planning is to establish the most appropriate location of zones to conserve or restore riparian buffer strips for whole river networks. This issue could be solved by using geomorphological criteria extracted from Digital Elevation Models. In this work we have explored the adjustment of surfaces developed under two different geomorphological criteria with respect to the flooded area covered by the 50-yr flood, in an attempt to rapidly delineate hydrologically-meaningful riparian zones for entire river networks. The first geomorphological criterion is based on the surface that intersects valley walls at a given number of bankfull depths above the channel (BFDAC), while the second is based on the surface defined by a~threshold value indicating the relative cost of moving from the stream up to the valley, accounting for slope and elevation change (path distance). As the relationship between local geomorphology and 50-yr flood has been suggested to be river-type dependant, we have performed our analyses distinguishing between three river types corresponding with three valley morphologies: open, shallow vee and deep vee valleys (in increasing degree of valley constrainment). Adjustment between the surfaces derived from geomorphological and hydrological criteria has been evaluated using two different methods: one based on exceeding areas (minimum exceeding score) and the other on the similarity among total area values. Both methods have pointed out the same surfaces when looking for those that best match with the 50-yr flood. Results have shown that the BFDAC approach obtains an adjustment slightly better than that of path distance. However, BFDAC requires bankfull depth regional regressions along the considered river network. Results have also confirmed that unconstrained valleys require lower threshold values than constrained valleys when deriving surfaces using geomorphological criteria. Moreover, this study provides: (i) guidance on the selection of the proper geomorphological criterion and associated threshold values, and (ii) an easy calibration framework to evaluate the adjustment with respect to hydrologically-meaningful surfaces.

Generalized regression neural network (GRNN)-based approach for colored dissolved organic matter (CDOM) retrieval: case study of Connecticut River at Middle Haddam Station, USA.

PubMed

Heddam, Salim

2014-11-01

The prediction of colored dissolved organic matter (CDOM) using artificial neural network approaches has received little attention in the past few decades. In this study, colored dissolved organic matter (CDOM) was modeled using generalized regression neural network (GRNN) and multiple linear regression (MLR) models as a function of Water temperature (TE), pH, specific conductance (SC), and turbidity (TU). Evaluation of the prediction accuracy of the models is based on the root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (CC), and Willmott's index of agreement (d). The results indicated that GRNN can be applied successfully for prediction of colored dissolved organic matter (CDOM).

A statistical model for water quality predictions from a river discharge using coastal observations

NASA Astrophysics Data System (ADS)

Kim, S.; Terrill, E. J.

2007-12-01

Understanding and predicting coastal ocean water quality has benefits for reducing human health risks, protecting the environment, and improving local economies which depend on clean beaches. Continuous observations of coastal physical oceanography increase the understanding of the processes which control the fate and transport of a riverine plume which potentially contains high levels of contaminants from the upstream watershed. A data-driven model of the fate and transport of river plume water from the Tijuana River has been developed using surface current observations provided by a network of HF radar operated as part of a local coastal observatory that has been in place since 2002. The model outputs are compared with water quality sampling of shoreline indicator bacteria, and the skill of an alarm for low water quality is evaluated using the receiver operating characteristic (ROC) curve. In addition, statistical analysis of beach closures in comparison with environmental variables is also discussed.

Patterns and processes of drainage network evolution on Mars

NASA Astrophysics Data System (ADS)

Stucky de Quay, G.; Roberts, G. G.

2017-12-01

Large, complex drainage networks exist on the surface of Mars. These drainage patterns suggest that base level change, fluvial erosion, and deposition of sedimentary rock have played important roles in determining the shape of Martian topography. On Earth, base-level change plays the most important role in determining shapes of river profiles at wavelengths greater than a few kilometers. Wavelet transforms of Martian drainage patterns indicate that the same is true for most Martian drainage. For example, rivers in the Warrego Valles system have large convex-upward elevation profiles, with broad knickzones spanning more than 100 kilometers in length and few kilometers in height. More than 90% of the spectra power of rivers in this system resides at wavelengths greater than 10 kilometers. We examine the source of this long wavelength spectra power by jointly inverting suites of Martian river profiles for damped spatio-temporal histories of base-level change. Drainage networks were extracted from the High Resolution Stereo Camera (HRSC) topographic dataset using flow-routing algorithms. Calculated uplift rate histories indicate that regional uplift at wavelengths greater than 100 kilometers play an important role in determining the history of landscape evolution in Warrego Valles. In other regions (e.g. Holden and Eberswalde craters) joint inversion of families of rivers draining craters helps to constrain values of erosional parameters in a simplified version of the stream power erosional model. Integration of calculated incision rates suggest that we can perform a simple mass balance between eroded and deposited rock in regions where both depositional and erosional landforms exist.

A model for simulation of flow in singular and interconnected channels

USGS Publications Warehouse

Schaffranek, Raymond W.; Baltzer, R.A.; Goldberg, D.E.

1981-01-01

A one-dimensional numerical model is presented for simulating the unsteady flow in singular riverine or estuarine reaches and in networks of reaches composed of interconnected channels. The model is both general and flexible in that it can be used to simulate a wide range of flow conditions for various channel configurations. The channel geometry of the network to be modeled should be sufficiently simple so as to lend itself to characterization in one spatial dimension. The flow must be substantially homogenous in density, and hydrostatic pressure must prevail everywhere in the network channels. The slope of each channel bottom ought to be mild and reasonably constant over its length so that the flow remains subcritical. The model accommodates tributary inflows and diversions and includes the effects of wind shear on the water surface as a forcing function in the flow equations. Water-surface elevations and flow discharges are computed at channel junctions, as well as at specified intermediate locations within the network channels. The one-dimensional branch-network flow model uses a four-point, implicit, finite-difference approximation of the unsteady-flow equations. The flow equations are linearized over a time step, and branch transformations are formulated that describe the relationship between the unknowns at the end points of the channels. The resultant matrix of branch-transformation equations and required boundary-condition equations is solved by Gaussian elimination using maximum pivot strategy. Five example applications of the flow model are illustrated. The applications cover such diverse conditions as a singular upland river reach in which unsteady flow results from hydropower regulations, coastal rivers composed of sequentially connected reaches subject to unsteady tide-driven flow, and a multiply connected network of channels whose flow is principally governed by wind tides and seiches in adjoining lakes. The report includes a listing of the FORTRAN IV computer program and a description of the input data requirements. Model supporting programs for the processing and input of initial and boundary-value data are identified, various model output formats are illustrated, and instructions are given to permit the production of graphical output using the line printer, electromechanical pen plotters, cathode-ray-tube display units, or microfilm recorders.

The concept of entropy in landscape evolution

USGS Publications Warehouse

Leopold, Luna Bergere; Langbein, Walter Basil

1962-01-01

The concept of entropy is expressed in terms of probability of various states. Entropy treats of the distribution of energy. The principle is introduced that the most probable condition exists when energy in a river system is as uniformly distributed as may be permitted by physical constraints. From these general considerations equations for the longitudinal profiles of rivers are derived that are mathematically comparable to those observed in the field. The most probable river profiles approach the condition in which the downstream rate of production of entropy per unit mass is constant. Hydraulic equations are insufficient to determine the velocity, depths, and slopes of rivers that are themselves authors of their own hydraulic geometries. A solution becomes possible by introducing the concept that the distribution of energy tends toward the most probable. This solution leads to a theoretical definition of the hydraulic geometry of river channels that agrees closely with field observations. The most probable state for certain physical systems can also be illustrated by random-walk models. Average longitudinal profiles and drainage networks were so derived and these have the properties implied by the theory. The drainage networks derived from random walks have some of the principal properties demonstrated by the Horton analysis; specifically, the logarithms of stream length and stream numbers are proportional to stream order.

An ECOMAG-based Regional Hydrological Model for the Mackenzie River basin

NASA Astrophysics Data System (ADS)

Motovilov, Yury; Kalugin, Andrey; Gelfan, Alexander

2017-04-01

A physically-based distributed model of runoff generation has been developed for the Mackenzie River basin (the catchment area is 1 660 000 km2). The model is based on the ECOMAG (ECOlogical Model for Applied Geophysics) hydrological modeling platform and describes processes of interception of rainfall/snowfall by the canopy, snow accumulation and melt, soil freezing and thawing, water infiltration into unfrozen and frozen soil, evapotranspiration, thermal and water regime of soil, overland, subsurface and ground flow, flow routing through a channel network accounting for flow regulation by lakes and reservoirs. The governing model's equations are derived from integration of the basic hydro- and thermodynamics equations of water and heat vertical transfer in snowpack, frozen/unfrozen soil, horizontal water flow under and over catchment slopes, etc. The Mackenzie basin's schematization was performed on the basis of the global DEM data (1-km resolution) from the HYDRO1K database of the U.S. Geological Survey. Most of the model parameters are physically meaningful and derived through the global datasets of the basin characteristics: FAO/IIASA Harmonized World Soil Database, USGS EROS Global Land Cover Characteristics project, etc. The 0.5ox0.5o WATCH reanalysis daily precipitation, air temperature and air humidity data were used as the model input for the period of 1971-2002. The daily discharge data provided by the Water Survey of Canada for 10 streamflow gauges, which are located at the Mackenzie River and the main tributaries (Peel River, Great Bear River, Liard River, Slave River and Athabasca River), were used for calibration (1991-2001) and validation (1971-1990) of the model. The gauges' catchment areas vary from 70600 km2 (Peel River above Fort Mopherson) to 1 660 000 km2 (Mackenzie River at Arctic Red River). The model demonstrated satisfactory performance in terms of Nash-and Sutcliffe efficiency (NSE(daily)0.60 and NSE(monthly)0.70) and percent bias (PBIAS15%) for 8 gauges of 10. Weaker results were obtained for Great Bear River at outlet of Great Bear Lake and Peace River at Peace Point. Possibilities of a model approach for the construction of mean annual hydrological fields (maps) using meteorological data for the large river basins are shown. Spatial fields of the 32-year mean annual runoff and evaporation (1971-2002) for the Mackenzie River basin were simulated by the distributed model and the corresponding maps were compared with that provided by Hydrological Atlas of Canada (1972) for 30-year period (1941-1970). Analysis of fields conformity is made and possible sources of errors are discussed.

River water quality management considering agricultural return flows: application of a nonlinear two-stage stochastic fuzzy programming.

PubMed

Tavakoli, Ali; Nikoo, Mohammad Reza; Kerachian, Reza; Soltani, Maryam

2015-04-01

In this paper, a new fuzzy methodology is developed to optimize water and waste load allocation (WWLA) in rivers under uncertainty. An interactive two-stage stochastic fuzzy programming (ITSFP) method is utilized to handle parameter uncertainties, which are expressed as fuzzy boundary intervals. An iterative linear programming (ILP) is also used for solving the nonlinear optimization model. To accurately consider the impacts of the water and waste load allocation strategies on the river water quality, a calibrated QUAL2Kw model is linked with the WWLA optimization model. The soil, water, atmosphere, and plant (SWAP) simulation model is utilized to determine the quantity and quality of each agricultural return flow. To control pollution loads of agricultural networks, it is assumed that a part of each agricultural return flow can be diverted to an evaporation pond and also another part of it can be stored in a detention pond. In detention ponds, contaminated water is exposed to solar radiation for disinfecting pathogens. Results of applying the proposed methodology to the Dez River system in the southwestern region of Iran illustrate its effectiveness and applicability for water and waste load allocation in rivers. In the planning phase, this methodology can be used for estimating the capacities of return flow diversion system and evaporation and detention ponds.

Creating a water depth map from Earth Observation-derived flood extent and topography data

NASA Astrophysics Data System (ADS)

Matgen, Patrick; Giustarini, Laura; Chini, Marco; Hostache, Renaud; Pelich, Ramona; Schlaffer, Stefan

2017-04-01

Enhanced methods for monitoring temporal and spatial variations of water depth in rivers and floodplains are very important in operational water management. Currently, variations of water elevation can be estimated indirectly at the land-water interface using sequences of satellite EO imagery in combination with topographic data. In recent years high-resolution digital elevation models (DEM) and satellite EO data have become more readily available at global scale. This study introduces an approach for efficiently converting remote sensing-derived flood extent maps into water depth maps using a floodplain's topography information. For this we make the assumption of uniform flow, that is the depth of flow with respect to the drainage network is considered to be the same at every section of the floodplain. In other words, the depth of water above the nearest drainage is expected to be constant for a given river reach. To determine this value we first need the Height Above Nearest Drainage (HAND) raster obtained by using the area of interest's DEM as source topography and a shapefile of the river network. The HAND model normalizes the topography with respect to the drainage network. Next, the HAND raster is thresholded in order to generate a binary mask that optimally fits, over the entire region of study, the flood extent map obtained from SAR or any other remote sensing product, including aerial photographs. The optimal threshold value corresponds to the height of the water line above the nearest drainage, termed HANDWATER, and is considered constant for a given subreach. Once the HANDWATER has been optimized, a water depth map can be generated by subtracting the value of the HAND raster at the each location from this parameter value. These developments enable large scale and near real-time applications and only require readily available EO data, a DEM and the river network as input data. The approach is based on a hierarchical split-based approach that subdivides a drainage network into segments of variable length with evidence of uniform flow. The method has been tested with remote sensing data and DEM data that differ in terms of spatial resolution and accuracy. A comprehensive evaluation of the obtained water depth maps with hydrodynamic modelling results and in situ measured water level recordings was carried out on a reach of the river Severn located in the United Kingdom. First results show that the obtained root mean squared difference is 10 cm when using high resolution high precision data sets (i.e. aerial photographs of flood extent and a LiDAR-derived DEM) and amount to 50 cm when using as inputs moderate resolution SAR imagery from ENVISAT and a SRTM-derived DEM.

The Hydroclimatic Response of the Whitewater River Basin: Influence of Groundwater Time Scales

NASA Astrophysics Data System (ADS)

Beeson, P. C.; Springer, E. P.; Duffy, C. J.

2003-12-01

A near-surface groundwater model was developed to assess the impact of land use and climate variability on the overall water budget of the Whitewater River Basin. The watershed is located in southeastern Kansas within the ARM-SGP as part of the DOE Water Cycle Pilot Study. The Whitewater River Basin has an area of 1,100 square-kilometers, an elevation range of 380 - 470m (amsl), and an average annual precipitation of 858 millimeters. The approach presented here attempts to examine the importance of groundwater in the water budget and hydroclimatic response at the river basin scale. In order to identify the time scales of groundwater in this system, time series and geospatial analyses were used to identify significant spatial structure and dominant temporal modes in the climate, runoff and groundwater response. In this research, we show that the time scales of groundwater baseflow to the river network are proportional to drainage density and position in the hydrologic landscape. The concept of a hydrologic landscape (Winter, JAWRA, April 2001) defines three zones: recharge (upland), translation (intervening steep slopes), and discharge (lowland), and the hydrologic landscape is useful for standardizing the evaluation of physical properties within any watershed. Singular spectrum analysis was used for a 50-year simulation to determine dominant modes and time scales for the hydrologic landscape units in the Whitewater River Basin. We found that the time scale of groundwater baseflow response increases with increasing drainage density. The sensitivity of this response is important to understand and close the water budget for a river basin through observation network design. The effects of climate forcing, both precipitation and evapotranspiration, can be seen through the hydrologic landscapes and channel networks by changes in the baseflow response time. Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is operated by the University of California for the U.S. Department of Energy under contract W-7405-ENG-36.

Geomorphology and Landscape Evolution Model for the natural and human-impacted regions of the Ganges-Brahmaputra-Meghna Delta

NASA Astrophysics Data System (ADS)

Wilson, C.; Goodbred, S. L.; Wallace Auerbach, L.; Ahmed, K.; Paola, C.; Reitz, M. D.; Pickering, J.

2013-12-01

The Ganges-Brahmaputra-Meghna delta (GBMD) in south Asia is generally considered a tide-dominated system, but much of the subaerial delta plain is geomorphically similar to river-dominated systems such as the Mississippi River delta, with a well-developed distributary network separated by low-lying, organic-rich interdistributary basins. By contrast, the lower GBMD is dominated by tidal processes and comprises a 100-km wide coastal plain with dense, interconnected tidal channels that are amalgamated to the seaward edge of the river-dominated portion of the delta. These distinct river- and tide-dominated geomorphic regions are simultaneously sustained by the enormous sediment load of the GBM rivers and its efficient dispersal via the distributary channel network and onshore advection by tides. Together these processes have resulted in the ability of the GBMD to keep pace with sea-level rise throughout the Holocene, with comparatively little shoreline transgression. However, topographic data from the Shuttle Radar Topography Mission (SRTM) highlight low-lying regions of the delta that are located at the interface of the river- and tide-dominated portions of the delta, where the transport energy of small distributaries and the upper tidal zone go to zero. As a result, these are the most sediment-starved regions of the delta and those most at risk to flooding by the summer monsoon and storm surges. Compounding the slow rates of sedimentation and high local organic content, these regions have been strongly affected by the construction of embankments (polders) that artificially de-water the soils and accelerate organic decomposition during the dry season, and further starve the land surface of sediment. Here, we present an integrated conceptual model for the geomorphic evolution of the GBMD that incorporates river- and tide-dominated regions in conjunction with channel-avulsion processes and delta-lobe construction. Each of these is also overprinted by tectonic deformation and human-landscape modifications. A key goal of this model is to explain the wide-scale distribution of coarse-grained river-borne sediment (predominantly sand) that forms the underlying architecture of the GBMD, with only localized preservation of fine-grained (silt and clay) deposits. Finally, analysis of the channel networks in the tidal delta plain reveal that constructed embankments have significantly decreased the density of naturally functioning tidal channels, inducing locally rapid bank migration and affiliated changes in sinuosity. These rapid landscape changes suggest that there has been a resultant change in hydrodynamics of the tidal delta plain following widespread construction of the embankments. With concern to assess landscape vulnerabilities to environmental change and renewed efforts to rehabilitate and stabilize the embankments, this information is needed to support the successful outcome of coastal defense initiatives.

Integrating Sediment Connectivity into Water Resources Management Trough a Graph Theoretic, Stochastic Modeling Framework.

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Castelletti, A.; Bizzi, S.

2014-12-01

Understanding sediment transport processes at the river basin scale, their temporal spectra and spatial patterns is key to identify and minimize morphologic risks associated to channel adjustments processes. This work contributes a stochastic framework for modeling bed-load connectivity based on recent advances in the field (e.g., Bizzi & Lerner, 2013; Czubas & Foufoulas-Georgiu, 2014). It presents river managers with novel indicators from reach scale vulnerability to channel adjustment in large river networks with sparse hydrologic and sediment observations. The framework comprises three steps. First, based on a distributed hydrological model and remotely sensed information, the framework identifies a representative grain size class for each reach. Second, sediment residence time distributions are calculated for each reach in a Monte-Carlo approach applying standard sediment transport equations driven by local hydraulic conditions. Third, a network analysis defines the up- and downstream connectivity for various travel times resulting in characteristic up/downstream connectivity signatures for each reach. Channel vulnerability indicators quantify the imbalance between up/downstream connectivity for each travel time domain, representing process dependent latency of morphologic response. Last, based on the stochastic core of the model, a sensitivity analysis identifies drivers of change and major sources of uncertainty in order to target key detrimental processes and to guide effective gathering of additional data. The application, limitation and integration into a decision analytic framework is demonstrated for a major part of the Red River Basin in Northern Vietnam (179.000 km2). Here, a plethora of anthropic alterations ranging from large reservoir construction to land-use changes results in major downstream deterioration and calls for deriving concerted sediment management strategies to mitigate current and limit future morphologic alterations.

Project W.A.T.E.R.

ERIC Educational Resources Information Center

EnviroTeach, 1992

1992-01-01

Introduces networking projects for studying rivers and water quality. Describes two projects in South Africa (Project W.A.T.E.R and SWAP) associated with the international network, Global Rivers Environmental Education Network. Discusses water test kits and educational material developed through Project W.A.T.E.R. (Water Awareness through…

Metacommunity theory as a multispecies, multiscale framework for studying the influence of river network structure on riverine communities and ecosystems

USGS Publications Warehouse

Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.

2011-01-01

Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

Stochastic Modeling of Sediment Connectivity for Reconstructing Sand Fluxes and Origins in the Unmonitored Se Kong, Se San, and Sre Pok Tributaries of the Mekong River

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Bizzi, S.; Castelletti, A. F.; Kondolf, G. M.

2018-01-01

Sediment supply to rivers, subsequent fluvial transport, and the resulting sediment connectivity on network scales are often sparsely monitored and subject to major uncertainty. We propose to approach that uncertainty by adopting a stochastic method for modeling network sediment connectivity, which we present for the Se Kong, Se San, and Sre Pok (3S) tributaries of the Mekong. We quantify how unknown properties of sand sources translate into uncertainty regarding network connectivity by running the CASCADE (CAtchment Sediment Connectivity And DElivery) modeling framework in a Monte Carlo approach for 7,500 random realizations. Only a small ensemble of realizations reproduces downstream observations of sand transport. This ensemble presents an inverse stochastic approximation of the magnitude and variability of transport capacity, sediment flux, and grain size distribution of the sediment transported in the network (i.e., upscaling point observations to the entire network). The approximated magnitude of sand delivered from each tributary to the Mekong is controlled by reaches of low transport capacity ("bottlenecks"). These bottlenecks limit the ability to predict transport in the upper parts of the catchment through inverse stochastic approximation, a limitation that could be addressed by targeted monitoring upstream of identified bottlenecks. Nonetheless, bottlenecks also allow a clear partitioning of natural sand deliveries from the 3S to the Mekong, with the Se Kong delivering less (1.9 Mt/yr) and coarser (median grain size: 0.4 mm) sand than the Se San (5.3 Mt/yr, 0.22 mm) and Sre Pok (11 Mt/yr, 0.19 mm).

Quantifying present and future glacier melt-water contribution to runoff in a Central Himalayan river basin

NASA Astrophysics Data System (ADS)

Prasch, M.; Mauser, W.; Weber, M.

2012-10-01

Water supply of most lowland cultures heavily depends on rain and melt-water from the upstream mountains. Especially melt-water release of alpine mountain ranges is usually attributed a pivotal role for the water supply of large downstream regions. Water scarcity is assumed as consequence of glacier shrinkage and possible disappearance due to Global Climate Change, particular for large parts of Central and South East Asia. In this paper, the application and validation of a coupled modeling approach with Regional Climate Model outputs and a process-oriented glacier and hydrological model is presented for a Central Himalayan river basin despite scarce data availability. Current and possible future contributions of ice-melt to runoff along the river network are spatially explicitly shown. Its role among the other water balance components is presented. Although glaciers have retreated and will continue to retreat according to the chosen climate scenarios, water availability is and will be primarily determined by monsoon precipitation and snow-melt. Ice-melt from glaciers is and will be a minor runoff component in summer monsoon-dominated Himalayan river basins.

Prediction of mean monthly river discharges in Colombia through Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Carmona, A. M.; Poveda, G.

2015-04-01

The hydro-climatology of Colombia exhibits strong natural variability at a broad range of time scales including: inter-decadal, decadal, inter-annual, annual, intra-annual, intra-seasonal, and diurnal. Diverse applied sectors rely on quantitative predictions of river discharges for operational purposes including hydropower generation, agriculture, human health, fluvial navigation, territorial planning and management, risk preparedness and mitigation, among others. Various methodologies have been used to predict monthly mean river discharges that are based on "Predictive Analytics", an area of statistical analysis that studies the extraction of information from historical data to infer future trends and patterns. Our study couples the Empirical Mode Decomposition (EMD) with traditional methods, e.g. Autoregressive Model of Order 1 (AR1) and Neural Networks (NN), to predict mean monthly river discharges in Colombia, South America. The EMD allows us to decompose the historical time series of river discharges into a finite number of intrinsic mode functions (IMF) that capture the different oscillatory modes of different frequencies associated with the inherent time scales coexisting simultaneously in the signal (Huang et al. 1998, Huang and Wu 2008, Rao and Hsu, 2008). Our predictive method states that it is easier and simpler to predict each IMF at a time and then add them up together to obtain the predicted river discharge for a certain month, than predicting the full signal. This method is applied to 10 series of monthly mean river discharges in Colombia, using calibration periods of more than 25 years, and validation periods of about 12 years. Predictions are performed for time horizons spanning from 1 to 12 months. Our results show that predictions obtained through the traditional methods improve when the EMD is used as a previous step, since errors decrease by up to 13% when the AR1 model is used, and by up to 18% when using Neural Networks is combined with the EMD.

Representing macropore flow at the catchment scale: a comparative modeling study

NASA Astrophysics Data System (ADS)

Liu, D.; Li, H. Y.; Tian, F.; Leung, L. R.

2017-12-01

Macropore flow is an important hydrological process that generally enhances the soil infiltration capacity and velocity of subsurface water. Up till now, macropore flow is mostly simulated with high-resolution models. One possible drawback of this modeling approach is the difficulty to effectively represent the overall typology and connectivity of the macropore networks. We hypothesize that modeling macropore flow directly at the catchment scale may be complementary to the existing modeling strategy and offer some new insights. Tsinghua Representative Elementary Watershed model (THREW model) is a semi-distributed hydrology model, where the fundamental building blocks are representative elementary watersheds (REW) linked by the river channel network. In THREW, all the hydrological processes are described with constitutive relationships established directly at the REW level, i.e., catchment scale. In this study, the constitutive relationship of macropore flow drainage is established as part of THREW. The enhanced THREW model is then applied at two catchments with deep soils but distinct climates, the humid Asu catchment in the Amazon River basin, and the arid Wei catchment in the Yellow River basin. The Asu catchment has an area of 12.43km2 with mean annual precipitation of 2442mm. The larger Wei catchment has an area of 24800km2 but with mean annual precipitation of only 512mm. The rainfall-runoff processes are simulated at a hourly time step from 2002 to 2005 in the Asu catchment and from 2001 to 2012 in the Wei catchment. The role of macropore flow on the catchment hydrology will be analyzed comparatively over the Asu and Wei catchments against the observed streamflow, evapotranspiration and other auxiliary data.

Hydrograph simulation models of the Hillsborough and Alafia Rivers, Florida: a preliminary report

USGS Publications Warehouse

Turner, James F.

1972-01-01

Mathematical (digital) models that simulate flood hydrographs from rainfall records have been developed for the following gaging stations in the Hillsborough and Alafia River basins of west-central Florida: Hillsborough River near Tampa, Alafia River at Lithia, and north Prong Alafia River near Keysville. These models, which were developed from historical streamflow and and rainfall records, are based on rainfall-runoff and unit-hydrograph procedures involving an arbitrary separation of the flood hydrograph. These models assume the flood hydrograph to be composed of only two flow components, direct (storm) runoff, and base flow. Expressions describing these two flow components are derived from streamflow and rainfall records and are combined analytically to form algorithms (models), which are programmed for processing on a digital computing system. Most Hillsborough and Alafia River flood discharges can be simulated with expected relative errors less than or equal to 30 percent and flood peaks can be simulated with average relative errors less than 15 percent. Because of the inadequate rainfall network that is used in obtaining input data for the North Prong Alafia River model, simulated peaks are frequently in error by more than 40 percent, particularly for storms having highly variable areal rainfall distribution. Simulation errors are the result of rainfall sample errors and, to a lesser extent, model inadequacy. Data errors associated with the determination of mean basin precipitation are the result of the small number and poor areal distribution of rainfall stations available for use in the study. Model inadequacy, however, is attributed to the basic underlying theory, particularly the rainfall-runoff relation. These models broaden and enhance existing water-management capabilities within these basins by allowing the establishment and implementation of programs providing for continued development in these areas. Specifically, the models serve not only as a basis for forecasting floods, but also for simulating hydrologic information needed in flood-plain mapping and delineating and evaluating alternative flood control and abatement plans.

Numerical Modelling of Freshwater Inputs in the Shelf Area of the Ofanto River (Southern Italy)

NASA Astrophysics Data System (ADS)

Verri, G.; Pinardi, N.; Tribbia, J. J.; Gochis, D.; Bryan, F.; Tseng, Y. H.; Navarra, A.; Coppini, G.

2016-02-01

The aim of this study is to understand and to assess the effects of river freshwater release on the ocean circulation and dynamics focusing on the shelf area near estuaries. A sensitivity study to different modelling approaches, which point to the representation of the dynamics of the river inflow, are presented. The modeling strategy we chose consists of an integrated modeling chain including the atmosphere, the hydrology/hydraulics and the estuarine dynamics in order to force our regional ocean model at the Ofanto outlet in a reliable way. This meteo-hydrological modeling chain allows us to take into account all the physical processes involved in the local water cycle of the Ofanto catchment such as the rainfall, the land surface infiltration/evaporation, the partitioning of total runoff into surface and subsurface runoff and the channel streamflow. In order to achieve our goal, we chose the Ofanto river catchment and its estuary as case study. The Ofanto river is a torrential river flowing across the Southern Italy and ending in the Adriatic Sea; its annual averaged discharge is low (15 m3s-1 following Raicich, 1996) but may significantly increase when heavy rain events occur. In details our regional ocean model is a finite difference numerical model based on NEMO code (Madec, G., 2008) and implemented in the Central Mediterranean Sea with 2km as horizontal resolution. The meteo-hydrological modeling chain consists of: 1) the WRF-ARW model (Skamarock et al., 2008) including NOAH-MP as Land Surface Submodel,; 2) WRF-HYDRO model (Gochis D., et al., 2013) representing the hydrology/hydraulics component with 200m as horizontal resolution, simulating the streamflow discharge along the Ofanto river network.; 3) finally an estuarine box model (Garvine et al., 2006) is inserted downstream of WRF-Hydro and upstream of the regional ocean model. A set of sensitivity experiments has been performed aiming to evaluate the capability of the regional ocean model to decribe the Ofanto river plume by providing hindcast discharge and salinity from the estuary model at the river mouth with different methods. The time window of the simulations covers the first three months of year 2011, since 4 heavy rain events affected the Ofanto catchment in this period.

Combining neural networks and genetic algorithms for hydrological flow forecasting

NASA Astrophysics Data System (ADS)

Neruda, Roman; Srejber, Jan; Neruda, Martin; Pascenko, Petr

2010-05-01

We present a neural network approach to rainfall-runoff modeling for small size river basins based on several time series of hourly measured data. Different neural networks are considered for short time runoff predictions (from one to six hours lead time) based on runoff and rainfall data observed in previous time steps. Correlation analysis shows that runoff data, short time rainfall history, and aggregated API values are the most significant data for the prediction. Neural models of multilayer perceptron and radial basis function networks with different numbers of units are used and compared with more traditional linear time series predictors. Out of possible 48 hours of relevant history of all the input variables, the most important ones are selected by means of input filters created by a genetic algorithm. The genetic algorithm works with population of binary encoded vectors defining input selection patterns. Standard genetic operators of two-point crossover, random bit-flipping mutation, and tournament selection were used. The evaluation of objective function of each individual consists of several rounds of building and testing a particular neural network model. The whole procedure is rather computational exacting (taking hours to days on a desktop PC), thus a high-performance mainframe computer has been used for our experiments. Results based on two years worth data from the Ploucnice river in Northern Bohemia suggest that main problems connected with this approach to modeling are ovetraining that can lead to poor generalization, and relatively small number of extreme events which makes it difficult for a model to predict the amplitude of the event. Thus, experiments with both absolute and relative runoff predictions were carried out. In general it can be concluded that the neural models show about 5 per cent improvement in terms of efficiency coefficient over liner models. Multilayer perceptrons with one hidden layer trained by back propagation algorithm and predicting relative runoff show the best behavior so far. Utilizing the genetically evolved input filter improves the performance of yet another 5 per cent. In the future we would like to continue with experiments in on-line prediction using real-time data from Smeda River with 6 hours lead time forecast. Following the operational reality we will focus on classification of the runoffs into flood alert levels, and reformulation of the time series prediction task as a classification problem. The main goal of all this work is to improve flood warning system operated by the Czech Hydrometeorological Institute.

Experiments with Interaction between the National Water Model and the Reservoir System Simulation Model: A Case Study of Russian River Basin

NASA Astrophysics Data System (ADS)

Kim, J.; Johnson, L.; Cifelli, R.; Chandra, C. V.; Gochis, D.; McCreight, J. L.; Yates, D. N.; Read, L.; Flowers, T.; Cosgrove, B.

2017-12-01

NOAA National Water Center (NWC) in partnership with the National Centers for Environmental Prediction (NCEP), the National Center for Atmospheric Research (NCAR) and other academic partners have produced operational hydrologic predictions for the nation using a new National Water Model (NWM) that is based on the community WRF-Hydro modeling system since the summer of 2016 (Gochis et al., 2015). The NWM produces a variety of hydrologic analysis and prediction products, including gridded fields of soil moisture, snowpack, shallow groundwater levels, inundated area depths, evapotranspiration as well as estimates of river flow and velocity for approximately 2.7 million river reaches. Also included in the NWM are representations for more than 1,200 reservoirs which are linked into the national channel network defined by the USGS NHDPlusv2.0 hydrography dataset. Despite the unprecedented spatial and temporal coverage of the NWM, many known deficiencies exist, including the representation of lakes and reservoirs. This study addresses the implementation of a reservoir assimilation scheme through coupling of a reservoir simulation model to represent the influence of managed flows. We examine the use of the reservoir operations to dynamically update lake/reservoir storage volume states, characterize flow characteristics of river reaches flowing into and out of lakes and reservoirs, and incorporate enhanced reservoir operating rules for the reservoir model options within the NWM. Model experiments focus on a pilot reservoir domain-Lake Mendocino, CA, and its contributing watershed, the East Fork Russian River. This reservoir is modeled using United States Army Corps of Engineers (USACE) HEC-ResSim developed for application to examine forecast informed reservoir operations (FIRO) in the Russian River basin.

Modeling of Valued Fish Species in River Networks

EPA Science Inventory

Riverine fish provide many ecosystem services in support of human well-being, including food, recreation, and biodiversity. Under future drivers of land use and climate change, inland waters are likely to be impaired, and conservation and protection of fish species and services ...

Fat fractal scaling of drainage networks from a random spatial network model

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1992-01-01

An alternative quantification of the scaling properties of river channel networks is explored using a spatial network model. Whereas scaling descriptions of drainage networks previously have been presented using a fractal analysis primarily of the channel lengths, we illustrate the scaling of the surface area of the channels defining the network pattern with an exponent which is independent of the fractal dimension but not of the fractal nature of the network. The methodology presented is a fat fractal analysis in which the drainage basin minus the channel area is considered the fat fractal. Random channel networks within a fixed basin area are generated on grids of different scales. The sample channel networks generated by the model have a common outlet of fixed width and a rule of upstream channel narrowing specified by a diameter branching exponent using hydraulic and geomorphologic principles. Scaling exponents are computed for each sample network on a given grid size and are regressed against network magnitude. Results indicate that the size of the exponents are related to magnitude of the networks and generally decrease as network magnitude increases. Cases showing differences in scaling exponents with like magnitudes suggest a direction of future work regarding other topologic basin characteristics as potential explanatory variables.

Allometric relationships between traveltime channel networks, convex hulls, and convexity measures

NASA Astrophysics Data System (ADS)

Tay, Lea Tien; Sagar, B. S. Daya; Chuah, Hean Teik

2006-06-01

The channel network (S) is a nonconvex set, while its basin [C(S)] is convex. We remove open-end points of the channel connectivity network iteratively to generate a traveltime sequence of networks (Sn). The convex hulls of these traveltime networks provide an interesting topological quantity, which has not been noted thus far. We compute lengths of shrinking traveltime networks L(Sn) and areas of corresponding convex hulls C(Sn), the ratios of which provide convexity measures CM(Sn) of traveltime networks. A statistically significant scaling relationship is found for a model network in the form L(Sn) ˜ A[C(Sn)]0.57. From the plots of the lengths of these traveltime networks and the areas of their corresponding convex hulls as functions of convexity measures, new power law relations are derived. Such relations for a model network are CM(Sn) ˜ ? and CM(Sn) ˜ ?. In addition to the model study, these relations for networks derived from seven subbasins of Cameron Highlands region of Peninsular Malaysia are provided. Further studies are needed on a large number of channel networks of distinct sizes and topologies to understand the relationships of these new exponents with other scaling exponents that define the scaling structure of river networks.

Effect of tides, river flow, and gate operations on entrainment of juvenile salmon into the interior Sacramento–San Joaquin River Delta

USGS Publications Warehouse

Perry, Russell W.; Brandes, Patricia L.; Burau, Jon R.; Sandstrom, Philip T.; Skalski, John R.

2015-01-01

Juvenile Chinook Salmon Oncorhynchus tshawytscha emigrating from natal tributaries of the Sacramento River, California, must negotiate the Sacramento-San Joaquin River Delta (hereafter, the Delta), a complex network of natural and man-made channels linking the Sacramento River with San Francisco Bay. Fish that enter the interior and southern Delta—the region to the south of the Sacramento River where water pumping stations are located—survive at a lower rate than fish that use alternative migration routes. Consequently, total survival decreases as the fraction of the population entering the interior Delta increases, thus spurring management actions to reduce the proportion of fish that are entrained into the interior Delta. To better inform management actions, we modeled entrainment probability as a function of hydrodynamic variables. We fitted alternative entrainment models to telemetry data that identified when tagged fish in the Sacramento River entered two river channels leading to the interior Delta (Georgiana Slough and the gated Delta Cross Channel). We found that the probability of entrainment into the interior Delta through both channels depended strongly on the river flow and tidal stage at the time of fish arrival at the river junction. Fish that arrived during ebb tides had a low entrainment probability, whereas fish that arrived during flood tides (i.e., when the river's flow was reversed) had a high probability of entering the interior Delta. We coupled our entrainment model with a flow simulation model to evaluate the effect of nighttime closures of the Delta Cross Channel gates on the daily probability of fish entrainment into the interior Delta. Relative to 24-h gate closures, nighttime closures increased daily entrainment probability by 3 percentage points on average if fish arrived at the river junction uniformly throughout the day and by only 1.3 percentage points if 85% of fish arrived at night. We illustrate how our model can be used to evaluate the effects of alternative water management actions on fish entrainment into the interior Delta.

Landscape-scale spatial abundance distributions discriminate core from random components of boreal lake bacterioplankton.

PubMed

Niño-García, Juan Pablo; Ruiz-González, Clara; Del Giorgio, Paul A

2016-12-01

Aquatic bacterial communities harbour thousands of coexisting taxa. To meet the challenge of discriminating between a 'core' and a sporadically occurring 'random' component of these communities, we explored the spatial abundance distribution of individual bacterioplankton taxa across 198 boreal lakes and their associated fluvial networks (188 rivers). We found that all taxa could be grouped into four distinct categories based on model statistical distributions (normal like, bimodal, logistic and lognormal). The distribution patterns across lakes and their associated river networks showed that lake communities are composed of a core of taxa whose distribution appears to be linked to in-lake environmental sorting (normal-like and bimodal categories), and a large fraction of mostly rare bacteria (94% of all taxa) whose presence appears to be largely random and linked to downstream transport in aquatic networks (logistic and lognormal categories). These rare taxa are thus likely to reflect species sorting at upstream locations, providing a perspective of the conditions prevailing in entire aquatic networks rather than only in lakes. © 2016 John Wiley & Sons Ltd/CNRS.

SWAT use of gridded observations for simulating runoff - a Vietnam river basin study

NASA Astrophysics Data System (ADS)

Vu, M. T.; Raghavan, S. V.; Liong, S. Y.

2011-12-01

Many research studies that focus on basin hydrology have used the SWAT model to simulate runoff. One common practice in calibrating the SWAT model is the application of station data rainfall to simulate runoff. But over regions lacking robust station data, there is a problem of applying the model to study the hydrological responses. For some countries and remote areas, the rainfall data availability might be a constraint due to many different reasons such as lacking of technology, war time and financial limitation that lead to difficulty in constructing the runoff data. To overcome such a limitation, this research study uses some of the available globally gridded high resolution precipitation datasets to simulate runoff. Five popular gridded observation precipitation datasets: (1) Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE), (2) Tropical Rainfall Measuring Mission (TRMM), (3) Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN), (4) Global Precipitation Climatology Project (GPCP), (5) modified Global Historical Climatology Network version 2 (GHCN2) and one reanalysis dataset National Centers for Environment Prediction/National Center for Atmospheric Research (NCEP/NCAR) are used to simulate runoff over the Dakbla River (a small tributary of the Mekong River) in Vietnam. Wherever possible, available station data are also used for comparison. Bilinear interpolation of these gridded datasets is used to input the precipitation data at the closest grid points to the station locations. Sensitivity Analysis and Auto-calibration are performed for the SWAT model. The Nash-Sutcliffe Efficiency (NSE) and Coefficient of Determination (R2) indices are used to benchmark the model performance. This entails a good understanding of the response of the hydrological model to different datasets and a quantification of the uncertainties in these datasets. Such a methodology is also useful for planning on Rainfall-runoff and even reservoir/river management both at rural and urban scales.

Applications of a New England stream temperature model to ...

EPA Pesticide Factsheets

We have applied a statistical stream network (SSN) model to predict stream thermal metrics (summer monthly medians, growing season maximum magnitude and timing, and daily rates of change) across New England nontidal streams and rivers, excluding northern Maine watersheds that extend into Canada (Detenbeck et al., in review). We excluded stream temperature observations within one kilometer downstream of dams from our model development, so our predictions for those reaches represent potential thermal regimes in the absence of dam effects. We used stream thermal thresholds for mean July temperatures delineating transitions between coldwater, transitional coolwater, and warmwater fish communities derived by Beauchene et al. (2014) to classify expected stream and river thermal regimes across New England. Within the model domain and based on 2006 land-use and air temperatures, the model predicts that 21.8% of stream + river kilometers would support coldwater fish communities (mean July water temperatures 22.3 degrees C mean July temperatures). Application of the model allows us to assess potential condition given full riparian zone restoration as well as potential loss of cold or coolwater habitat given loss of riparian shading. Given restoration of all ripa

Modelling of Reservoir Operations using Fuzzy Logic and ANNs

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Coerver, B.; Rutten, M.

2015-12-01

Today, almost 40.000 large reservoirs, containing approximately 6.000 km3 of water and inundating an area of almost 400.000 km2, can be found on earth. Since these reservoirs have a storage capacity of almost one-sixth of the global annual river discharge they have a large impact on the timing, volume and peaks of river discharges. Global Hydrological Models (GHM) are thus significantly influenced by these anthropogenic changes in river flows. We developed a parametrically parsimonious method to extract operational rules based on historical reservoir storage and inflow time-series. Managing a reservoir is an imprecise and vague undertaking. Operators always face uncertainties about inflows, evaporation, seepage losses and various water demands to be met. They often base their decisions on experience and on available information, like reservoir storage and the previous periods inflow. We modeled this decision-making process through a combination of fuzzy logic and artificial neural networks in an Adaptive-Network-based Fuzzy Inference System (ANFIS). In a sensitivity analysis, we compared results for reservoirs in Vietnam, Central Asia and the USA. ANFIS can indeed capture reservoirs operations adequately when fed with a historical monthly time-series of inflows and storage. It was shown that using ANFIS, operational rules of existing reservoirs can be derived without much prior knowledge about the reservoirs. Their validity was tested by comparing actual and simulated releases with each other. For the eleven reservoirs modelled, the normalised outflow, <0,1>, was predicted with a MSE of 0.002 to 0.044. The rules can be incorporated into GHMs. After a network for a specific reservoir has been trained, the inflow calculated by the hydrological model can be combined with the release and initial storage to calculate the storage for the next time-step using a mass balance. Subsequently, the release can be predicted one time-step ahead using the inflow and storage.

AmeriFlux US-MRf Mary's River (Fir) site

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

Law, Bev

This is the AmeriFlux version of the carbon flux data for the site US-MRf Mary's River (Fir) site. Site Description - The Marys River Fir site is part of the "Synthesis of Remote Sensing and Field Observations to Model and Understand Disturbance and Climate Effects on the Carbon Balance of Oregon and Northern California (ORCA)". Located in the western region of Oregon the Marys River site represents the western extent of the climate gradient that spans eastward into the semi-arid basin of central Oregon. The sites that make up the eastern extent of the ORCA climate gradient is the Metoliusmore » site network (US-Me1, US-ME2, US-ME4, US-Me5) all of which are part of the TERRA PNW project at Oregon State University.« less

Spatial and temporal variation of water temperature regimes on the Snoqualmie River network

Treesearch

Ashley E. Steel; Colin Sowder; Erin E. Peterson

2016-01-01

Although mean temperatures change annually and are highly correlated with elevation, the entire thermal regime on the Snoqualmie River, Washington, USA does not simply shift with elevation or season. Particular facets of the thermal regime have unique spatial patterns on the river network and at particular times of the year. We used a spatially and temporally dense...

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Seasonal predictions of precipitation in the Aksu-Tarim River basin for improved water resources management

NASA Astrophysics Data System (ADS)

Hartmann, Heike; Snow, Julie A.; Su, Buda; Jiang, Tong

2016-12-01

Since the 1950s, the population in the arid to hyperarid Tarim River basin has grown rapidly concurrent with an expansion of irrigated agriculture. This threatens the Tarim River basin's natural ecosystems and causes water shortages, even though increased discharges in the headwaters have been observed more recently. These increases have mainly been attributed to receding glaciers and are projected to cease when the glaciers are unable to provide sufficient amounts of meltwater. Under these circumstances water management will face a serious challenge in adapting its strategies to changes in river discharge, which to a greater extent will depend on changes in precipitation. In this paper, we aim to develop accurate seasonal predictions of precipitation to improve water resources management. Possible predictors of precipitation for the Tarim River basin were either downloaded directly or calculated using NCEP/NCAR Reanalysis 1 and NOAA Extended Reconstructed Sea Surface Temperature (SST) V3b data in monthly resolution. To evaluate the significance of the predictors, they were then correlated with the monthly precipitation dataset GPCCv6 extracted for the Tarim River basin for the period 1961 to 2010. Prior to the Spearman rank correlation analyses, the precipitation data were averaged over the subbasins of the Tarim River. The strongest correlations were mainly detected with lead times of four and five months. Finally, an artificial neural network model, namely a multilayer perceptron (MLP), and a multiple linear regression (LR) model were developed each in two different configurations for the Aksu River subbasin, predicting precipitation five months in advance. Overall, the MLP using all predictors shows the best performance. The performance of both models drops only slightly when restricting the model input to the SST of the Black Sea and the Siberian High Intensity (SHI) pointing towards their importance as predictors.

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

DOE PAGES

Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin; ...

2017-01-10

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Evaluating the streamflow simulation capability of PERSIANN-CDR daily rainfall products in two river basins on the Tibetan Plateau

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

Liu, Xiaomang; Yang, Tiantian; Hsu, Koulin

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks $-$ Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basinsmore » on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. Finally, the evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.« less

Reach-Scale Channel Adjustments to Channel Network Geometry in Mountain Bedrock Streams

NASA Astrophysics Data System (ADS)

Plitzuweit, S. J.; Springer, G. S.

2008-12-01

Channel network geometry (CNG) is a critical determinant of hydrological response and may significantly affect incision processes within the Appalachian Plateau near Richwood, West Virginia. The Williams, Cherry, and Cranberry Rivers share drainage divides and their lower reaches flow atop resistant, quartz-rich sandstones. The lower two-thirds of the Cranberry and Williams Rivers display linear profiles atop the sandstones; whereas the Cherry is concave upwards atop the sandstones. Because lithologies and geological structures are similar among the watersheds, we tested whether differences in CNGs explain the profile shapes and reach-scale channel properties. Specifically, we quantified CNG by calculating reach- specific area-distance functions using DEMs. The area-distance functions were then converted into synthetic hydrographs to model hydrological responses. The Cherry River exhibits a classic dendritic drainage pattern, producing peaked hydrographs and low interval transit times. The Cranberry River displays a trellis-like drainage pattern, which produces attenuated hydrographs and high interval transit times. The upstream reaches of the Williams River have a dendritic drainage pattern, but the lower two-thirds of the watershed transitions into an elongated basin with trellis-like CNG. Reach gradients are steeper in the lower reaches of the Williams and Cranberry Rivers where hydrographs are attenuated. In contrast, peaked hydrographs within the Cherry River are associated with lower reach gradients despite resistant sandstone channel beds. Trellis-like CNG may restrict the ability of downstream reaches within the Williams and Cranberry Rivers to achieve the critical discharge needed to cause incision during floods (all other things being equal). If so, increased reach gradients may be hydraulic adjustments that compensate for comparatively low discharges. We are now applying the synthetic hydrographs to HEC-RAS flow models generated from field channel surveys in order to analyze whether stream power and shear stress are adjusted to reflect CNG at the reach- scale. These models are compared to those with discharges calculated using drainage area and precipitation totals alone. We conclude that gradients in bedrock mountain streams may reflect basin-scale hydrology (CNG) and not simply local geological or geomorphic factors. This challenges the conclusions of others who ascribe local channel adjustments to: i) lithology and structure alone, or ii) local colluvium grain sizes.

A simplified GIS-based model for large wood recruitment and connectivity in mountain basins

NASA Astrophysics Data System (ADS)

Lucía, Ana; Antonello, Andrea; Campana, Daniela; Cavalli, Marco; Crema, Stefano; Franceschi, Silvia; Marchese, Enrico; Niedrist, Martin; Schneiderbauer, Stefan; Comiti, Francesco

2014-05-01

The mobilization of large wood (LW) elements in mountain rivers channels during floods may increase their hazard potential, especially by clogging narrow sections such as bridges. However, the prediction of LW transport magnitude during flood events is a challenging topic. Although some models on LW transport have been recently developed, the objective of this work was to generate a simplified GIS-based model to identify along the channel network the most likely LW-related critical sections during high-magnitude flood events in forested mountain basins. Potential LW contribution generated by landsliding occurring on hillslopes is assessed using SHALSTAB stability model coupled to a GIS-based connectivity index, developed as a modification of the index proposed by Cavalli et al (2013). Connected slope-derived LW volumes are then summed at each raster cell to LW volumes generated by bank erosion along the erodibile part of river corridors, where bank erosion processes are estimated based on user-defined channel widening ratios stemming from observations following recent extreme events in mountain basins. LW volume in the channel is then routed through the stream network applying simple Boolean rules meant to capture the most important limiting transport condition in these high-energy systems at flood stage, i.e. flow width relative to log length. In addition, the role of bridges and retention check-dams in blocking floating logs is accounted for in the model, in particular bridge length and height are used to characterize their clogging susceptibility for different levels of expected LW volumes and size. The model has been tested in the Rienz and Ahr basins (about 630 km2 each), located in the Eastern Italian Alps. Sixty percent of the basin area is forested, and elevations range from 811 m a.s.l. to 3488 m a.s.l.. We used a 2.5 m resolution DTM and DSM, and their difference was used to calculate the canopy height. Data from 35 plots of the National Forest Inventory were used to estimate forest stand volume by a semi-empirical model. Ddatabase on shallow landslides along with precipitation depth was utilized to calibrate the parameters for the SHALSTAB model. Orthophotos (0.5 m pixel resolution) and existing technical maps were used to delimitate the channel banks, which were used to calculate automatically channel width for each grid cell. The model output provided information about the expected volume and mean size of LW recruited and transported during a 300 yr flood event in the test basins, as well as the location of the most probable clogged sections (mostly related to infrastructures) along the channel network. The model thus shows the capability to assist river managers in identifying the most critical sections of river networks and to assess the effectiveness and location of different mitigation options such as wood retention structures or forest management practices.

The nitrogen cycle in highly urbanized tropical regions and the effect of river-aquifer interactions: The case of Jakarta and the Ciliwung River

NASA Astrophysics Data System (ADS)

Costa, Diogo; Burlando, Paolo; Priadi, Cindy; Shie-Yui, Liong

2016-09-01

Groundwater is extensively used in Jakarta to compensate for the limited public water supply network. Recent observations show a rise in nitrate (NO3-) levels in the shallow aquifer, thus pointing at a potential risk for public health. The detected levels are still below national and international regulatory limits for drinking water but a strategy is necessary to contain the growing problem. We combine 3 years of available data in the Ciliwung River, the major river flowing through Jakarta, with a distributed river-aquifer interaction model to characterise the impact of urbanisation on the N-cycle of both surface and groundwater systems. Results show that the N-cycle in the river-aquifer system is heterogeneous in space, seasonal dependent (i.e. flow regime) and strongly affected by urban pollution. Results suggest also that although the main sources of N related groundwater pollution are leaking septic tanks, the aquifer interaction with the Ciliwung River may locally have a strong effect on the concentrations. In the general context of pollution control in urban areas, this study demonstrates how advanced process-based models can be efficiently used in combination with field measurements to bring new insights into complex contamination problems. These are essential for more effective and integrated management of water quality in river-aquifer systems.

The nitrogen cycle in highly urbanized tropical regions and the effect of river-aquifer interactions: The case of Jakarta and the Ciliwung River.

PubMed

Costa, Diogo; Burlando, Paolo; Priadi, Cindy; Shie-Yui, Liong

2016-09-01

Groundwater is extensively used in Jakarta to compensate for the limited public water supply network. Recent observations show a rise in nitrate (NO3(-)) levels in the shallow aquifer, thus pointing at a potential risk for public health. The detected levels are still below national and international regulatory limits for drinking water but a strategy is necessary to contain the growing problem. We combine 3years of available data in the Ciliwung River, the major river flowing through Jakarta, with a distributed river-aquifer interaction model to characterise the impact of urbanisation on the N-cycle of both surface and groundwater systems. Results show that the N-cycle in the river-aquifer system is heterogeneous in space, seasonal dependent (i.e. flow regime) and strongly affected by urban pollution. Results suggest also that although the main sources of N related groundwater pollution are leaking septic tanks, the aquifer interaction with the Ciliwung River may locally have a strong effect on the concentrations. In the general context of pollution control in urban areas, this study demonstrates how advanced process-based models can be efficiently used in combination with field measurements to bring new insights into complex contamination problems. These are essential for more effective and integrated management of water quality in river-aquifer systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatially explicit modeling of particulate nutrient flux in Large global rivers

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Mayorga, E.; Harrison, J. A.

2017-12-01

Water, sediment, nutrient and carbon fluxes along river networks have undergone considerable alterations in response to anthropogenic and climatic changes, with significant consequences to infrastructure, agriculture, water security, ecology and geomorphology worldwide. However, in a global setting, these changes in fluvial fluxes and their spatial and temporal characteristics are poorly constrained, due to the limited availability of continuous and long-term observations. We present results from a new global-scale particulate modeling framework (WBMsedNEWS) that combines the Global NEWS watershed nutrient export model with the spatially distributed WBMsed water and sediment model. We compare the model predictions against multiple observational datasets. The results indicate that the model is able to accurately predict particulate nutrient (Nitrogen, Phosphorus and Organic Carbon) fluxes on an annual time scale. Analysis of intra-basin nutrient dynamics and fluxes to global oceans is presented.

Modelling of faecal indicator bacteria (FIB) in the Red River basin (Vietnam).

PubMed

Nguyen, Huong Thi Mai; Billen, Gilles; Garnier, Josette; Rochelle-Newall, Emma; Ribolzi, Olivier; Servais, Pierre; Le, Quynh Thi Phuong

2016-09-01

Many studies have been published on the use of models to assess water quality through faecal contamination levels. However, the vast majority of this work has been conducted in developed countries and similar studies from developing countries in tropical regions are lacking. Here, we used the Seneque/Riverstrahler model to investigate the dynamics and seasonal distribution of total coliforms (TC), an indicator of faecal contamination, in the Red River (Northern Vietnam) and its upstream tributaries. The results of the model showed that, in general, the overall correlations between the simulated and observed values of TC follow a 1:1 relationship at all examined stations. They also showed that TC numbers were affected by both land use in terms of human and livestock populations and by hydrology (river discharge). We also developed a possible scenario based on the predicted changes in future demographics and land use in the Red River system for the 2050 horizon. Interestingly, the results showed only a limited increase of TC numbers compared with the present situation at all stations, especially in the upstream Vu Quang station and in the urban Ha Noi station. This is probably due to the dominance of diffuse sources of contamination relative to point sources. The model is to our knowledge one of the first mechanistic models able to simulate spatial and seasonal variations of microbial contamination (TC numbers) in the whole drainage network of a large regional river basin covering both urban and rural areas of a developing country.

Parameter Estimation for a Model of Space-Time Rainfall

NASA Astrophysics Data System (ADS)

Smith, James A.; Karr, Alan F.

1985-08-01

In this paper, parameter estimation procedures, based on data from a network of rainfall gages, are developed for a class of space-time rainfall models. The models, which are designed to represent the spatial distribution of daily rainfall, have three components, one that governs the temporal occurrence of storms, a second that distributes rain cells spatially for a given storm, and a third that determines the rainfall pattern within a rain cell. Maximum likelihood and method of moments procedures are developed. We illustrate that limitations on model structure are imposed by restricting data sources to rain gage networks. The estimation procedures are applied to a 240-mi2 (621 km2) catchment in the Potomac River basin.

Physical Heterogeneity and Aquatic Community Function in River Networks

EPA Science Inventory

The geomorphological character of a river network provides the template upon which evolution acts to create unique biological communities. Deciphering commonly observed patterns and processes within riverine landscapes resulting from the interplay between physical and biological...

Which offers more scope to suppress river phytoplankton blooms: reducing nutrient pollution or riparian shading?

PubMed

Hutchins, M G; Johnson, A C; Deflandre-Vlandas, A; Comber, S; Posen, P; Boorman, D

2010-10-01

River flow and quality data, including chlorophyll-a as a surrogate for river phytoplankton biomass, were collated for the River Ouse catchment in NE England, which according to established criteria is a largely unpolluted network. Against these data, a daily river quality model (QUESTOR) was setup and successfully tested. Following a review, a river quality classification scheme based on phytoplankton biomass was proposed. Based on climate change predictions the model indicated that a shift from present day oligotrophic/mesotrophic conditions to a mesotrophic/eutrophic system could occur by 2080. Management options were evaluated to mitigate against this predicted decline in quality. Reducing nutrient pollution was found to be less effective at suppressing phytoplankton growth than the less costly option of establishing riparian shading. In the Swale tributary, ongoing efforts to reduce phosphorus loads in sewage treatment works will only reduce peak (95th percentile) phytoplankton by 11%, whereas a reduction of 44% is possible if riparian tree cover is also implemented. Likewise, in the Ure, whilst reducing nitrate loads by curtailing agriculture in the headwaters may bring about a 10% reduction, riparian shading would instead reduce levels by 47%. Such modelling studies are somewhat limited by insufficient field data but offer a potentially very valuable tool to assess the most cost-effective methods of tackling effects of eutrophication. Copyright 2010 Elsevier B.V. All rights reserved.

Science advancements key to increasing management value of life stage monitoring networks for endangered Sacramento River winter-run Chinook salmon in California

USGS Publications Warehouse

Johnson, Rachel C.; Windell, Sean; Brandes, Patricia L.; Conrad, J. Louise; Ferguson, John; Goertler, Pascale A. L.; Harvey, Brett N.; Heublein, Joseph; Isreal, Joshua A.; Kratville, Daniel W.; Kirsch, Joseph E.; Perry, Russell W.; Pisciotto, Joseph; Poytress, William R.; Reece, Kevin; Swart, Brycen G.

2017-01-01

A robust monitoring network that provides quantitative information about the status of imperiled species at key life stages and geographic locations over time is fundamental for sustainable management of fisheries resources. For anadromous species, management actions in one geographic domain can substantially affect abundance of subsequent life stages that span broad geographic regions. Quantitative metrics (e.g., abundance, movement, survival, life history diversity, and condition) at multiple life stages are needed to inform how management actions (e.g., hatcheries, harvest, hydrology, and habitat restoration) influence salmon population dynamics. The existing monitoring network for endangered Sacramento River winterrun Chinook Salmon (SRWRC, Oncorhynchus tshawytscha) in California’s Central Valley was compared to conceptual models developed for each life stage and geographic region of the life cycle to identify relevant SRWRC metrics. We concluded that the current monitoring network was insufficient to diagnose when (life stage) and where (geographic domain) chronic or episodic reductions in SRWRC cohorts occur, precluding within- and among-year comparisons. The strongest quantitative data exist in the Upper Sacramento River, where abundance estimates are generated for adult spawners and emigrating juveniles. However, once SRWRC leave the upper river, our knowledge of their identity, abundance, and condition diminishes, despite the juvenile monitoring enterprise. We identified six system-wide recommended actions to strengthen the value of data generated from the existing monitoring network to assess resource management actions: (1) incorporate genetic run identification; (2) develop juvenile abundance estimates; (3) collect data for life history diversity metrics at multiple life stages; (4) expand and enhance real-time fish survival and movement monitoring; (5) collect fish condition data; and (6) provide timely public access to monitoring data in open data formats. To illustrate how updated technologies can enhance the existing monitoring to provide quantitative data on SRWRC, we provide examples of how each recommendation can address specific management issues.

Projected climate-induced habitat loss for salmonids in the John Day River network, Oregon, U.S.A.

USGS Publications Warehouse

Ruesch, Aaron S.; Torgersen, Christian E.; Lawler, Joshua J.; Olden, Julian D.; Peterson, Erin E.; Volk, Carol J.; Lawrence, David J.

2012-01-01

Climate change will likely have profound effects on cold-water species of freshwater fishes. As temperatures rise, cold-water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate-driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate-induced changes in summer thermal habitat for 3 cold-water fish species—juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)—in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69–95%, 51–87%, and 86–100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.

The Role of Small Impoundments on Flow Alteration Within River Networks

NASA Astrophysics Data System (ADS)

Brogan, C. O.; Keys, T.; Scott, D.; Burgholzer, R.; Kleiner, J.

2017-12-01

Numerous water quality and quantity models have been established to illustrate the ecologic and hydrologic effects of large reservoirs. Smaller, unregulated ponds are often assumed to have a negligible impact on watershed flow regimes even though they overwhelmingly outnumber larger waterbodies. Individually, these small impoundments impart merely a fraction of the flow alteration larger reservoirs do; however, a network of ponds may act cumulatively to alter the flow regime. Many models have attempted to study smaller impoundments but rely on selectively available rating curves or bathymetry surveys. This study created a generalized process to model impoundments of varying size across a 58 square mile watershed exclusively using satellite imagery and publicly available information as inputs. With information drawn from public Army Corps of Engineers databases and LiDAR surveys, it was found that impoundment surface and drainage area served as useful explanatory variables, capable of predicting both pond bathymetry and outlet structure area across the 37 waterbodies modeled within the study area. Working within a flow routing model with inputs from the Chesapeake Bay HSPF model and verified with USGS gauge data, flow simulations were conducted with increasing number of impoundments to quantify how small ponds affect the overall flow regime. As the total impounded volume increased, simulations showed a notable reduction in both low and peak flows. Medium-sized floods increased as the network of ponds and reservoirs stabilized the catchment's streamflow. The results of this study illustrate the importance of including ponded waters into river corridor models to improve downstream management of both water quantity and quality.

One-dimensional flow model of the river-hyporheic zone system

NASA Astrophysics Data System (ADS)

Pokrajac, D.

2016-12-01

The hyporheic zone is a shallow layer beneath natural streams that is characterized by intense exchange of water, nutrients, pollutants and thermal energy. Understanding these exchange processes is crucial for successful modelling of the river hydrodynamics and morphodynamics at various scales from the river corridor up to the river network scale (Cardenas, 2015). Existing simulation models of hyporheic exchange processes are either idealized models of the tracer movement through the river-hyporheic zone system (e.g. TSM, Bencala and Walters, 1983) or detailed models of turbulent flow in a stream, coupled with a conventional 2D Darcian groundwater model (e.g. Cardenas and Wilson, 2007). This paper presents an alternative approach which involves a simple 1-D simulation model of the hyporheic zone system based on the classical SWE equations coupled with the newly developed porous media analogue. This allows incorporating the effects of flow unsteadiness and non-Darcian parameterization od the drag term in the hyporheic zone model. The conceptual model of the stream-hyporheic zone system consists of a 1D model of the open channel flow in the river, coupled with a 1D model of the flow in the hyporheic zone via volume flux due to the difference in the water level in the river and the hyporheic zone. The interaction with the underlying groundwater aquifer is neglected, but coupling the present model with any conventional groundwater model is straightforward. The paper presents the derivation of the 1D flow equations for flow in the hyporheic zone, the details of the numerical scheme used for solving them and the model validation by comparison with published experimental data. References Bencala, K. E., and R. A. Walters (1983) "Simulation of solute transport in a mountain pool-and-riffle stream- a transient storage model", Water Resources Reseach 19(3): 718-724. Cardenas, M. B. (2015) "Hyporheic zone hydrologic science: A historical account of its emergence and a prospectus", Water Resources Research 51: 3601-3616 Cardenas, M. B., and J. L. Wilson (2007) "Dunes, turbulent eddies, and interfacial exchange with permeable sediments", Water Resour. Res. 43:W08412

A study of anthropogenic and climatic disturbance of the New River Estuary using a Bayesian belief network.

PubMed

Nojavan A, Farnaz; Qian, Song S; Paerl, Hans W; Reckhow, Kenneth H; Albright, Elizabeth A

2014-06-15

The present paper utilizes a Bayesian Belief Network (BBN) approach to intuitively present and quantify our current understanding of the complex physical, chemical, and biological processes that lead to eutrophication in an estuarine ecosystem (New River Estuary, North Carolina, USA). The model is further used to explore the effects of plausible future climatic and nutrient pollution management scenarios on water quality indicators. The BBN, through visualizing the structure of the network, facilitates knowledge communication with managers/stakeholders who might not be experts in the underlying scientific disciplines. Moreover, the developed structure of the BBN is transferable to other comparable estuaries. The BBN nodes are discretized exploring a new approach called moment matching method. The conditional probability tables of the variables are driven by a large dataset (four years). Our results show interaction among various predictors and their impact on water quality indicators. The synergistic effects caution future management actions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event.

PubMed

Knebl, M R; Yang, Z-L; Hutchison, K; Maidment, D R

2005-06-01

This paper develops a framework for regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and a hydrological model (HEC-HMS/RAS). The San Antonio River Basin (about 4000 square miles, 10,000 km2) in Central Texas, USA, is the domain of the study because it is a region subject to frequent occurrences of severe flash flooding. A major flood in the summer of 2002 is chosen as a case to examine the modeling framework. The model consists of a rainfall-runoff model (HEC-HMS) that converts precipitation excess to overland flow and channel runoff, as well as a hydraulic model (HEC-RAS) that models unsteady state flow through the river channel network based on the HEC-HMS-derived hydrographs. HEC-HMS is run on a 4 x 4 km grid in the domain, a resolution consistent with the resolution of NEXRAD rainfall taken from the local river authority. Watershed parameters are calibrated manually to produce a good simulation of discharge at 12 subbasins. With the calibrated discharge, HEC-RAS is capable of producing floodplain polygons that are comparable to the satellite imagery. The modeling framework presented in this study incorporates a portion of the recently developed GIS tool named Map to Map that has been created on a local scale and extends it to a regional scale. The results of this research will benefit future modeling efforts by providing a tool for hydrological forecasts of flooding on a regional scale. While designed for the San Antonio River Basin, this regional scale model may be used as a prototype for model applications in other areas of the country.

Extraction of Martian valley networks from digital topography

NASA Technical Reports Server (NTRS)

Stepinski, T. F.; Collier, M. L.

2004-01-01

We have developed a novel method for delineating valley networks on Mars. The valleys are inferred from digital topography by an autonomous computer algorithm as drainage networks, instead of being manually mapped from images. Individual drainage basins are precisely defined and reconstructed to restore flow continuity disrupted by craters. Drainage networks are extracted from their underlying basins using the contributing area threshold method. We demonstrate that such drainage networks coincide with mapped valley networks verifying that valley networks are indeed drainage systems. Our procedure is capable of delineating and analyzing valley networks with unparalleled speed and consistency. We have applied this method to 28 Noachian locations on Mars exhibiting prominent valley networks. All extracted networks have a planar morphology similar to that of terrestrial river networks. They are characterized by a drainage density of approx.0.1/km, low in comparison to the drainage density of terrestrial river networks. Slopes of "streams" in Martian valley networks decrease downstream at a slower rate than slopes of streams in terrestrial river networks. This analysis, based on a sizable data set of valley networks, reveals that although valley networks have some features pointing to their origin by precipitation-fed runoff erosion, their quantitative characteristics suggest that precipitation intensity and/or longevity of past pluvial climate were inadequate to develop mature drainage basins on Mars.

A finite-element model study of the impact of the proposed I-326 crossing on flood stages of the Congaree River near Columbia, South Carolina

USGS Publications Warehouse

Lee, J.K.; Bennett, C. S.

1981-01-01

A two-dimensional finite element surface water model was used to study the hydraulic impact of the proposed Interstate Route 326 crossing of the Congaree River near Columbia, SC. The finite element model was assessed as a potential operational tool for analyzing complex highway crossings and other modifications of river flood plains. Infrared aerial photography was used to define regions of homogeneous roughness in the flood plain. Finite element networks approximating flood plain topography were designed using elements of three roughness types. High water marks established during an 8-yr flood that occurred in October 1976 were used to calibrate the model. The maximum flood of record, an approximately 100-yr flood that occurred in August 1908, was modeled in three cases: dikes on the right bank, dikes on the left bank, and dikes on both banks. In each of the three cases, simulations were performed both without and with the proposed highway embankments in place. Detailed information was obtained about backwater effects upstream from the proposed highway embankments, changes in flow distribution resulting from the embankments, and local velocities in the bridge openings. On the basis of results from the model study, the South Carolina Department of Highways and Public Transportation changed the design of several bridge openings. A simulation incorporating the new design for the case with dikes on the left bank indicated that both velocities in the bridge openings and backwater were reduced. A major problem in applying the model was the difficulty in predicting the network detail necessary to avoid local errors caused by roughness discontinuities and large depth gradients. (Lantz-PTT)

Fish and fire: Post-wildfire sediment dynamics and implications for the viability of trout populations

NASA Astrophysics Data System (ADS)

Murphy, B. P.; Czuba, J. A.; Belmont, P.; Budy, P.; Finch, C.

2017-12-01

Episodic events in steep landscapes, such as wildfire and mass wasting, contribute large pulses of sediment to rivers and can significantly alter the quality and connectivity of fish habitat. Understanding where these sediment inputs occur, how they are transported and processed through the watershed, and their geomorphic effect on the river network is critical to predicting the impact on ecological aquatic communities. The Tushar Mountains of southern Utah experienced a severe wildfire in 2010, resulting in numerous debris flows and the extirpation of trout populations. Following many years of habitat and ecological monitoring in the field, we have developed a modeling framework that links post-wildfire debris flows, fluvial sediment routing, and population ecology in order to evaluate the impact and response of trout to wildfire. First, using the Tushar topographic and wildfire parameters, as well as stochastic precipitation generation, we predict the post-wildfire debris flow probabilities and volumes of mainstem tributaries using the Cannon et al. [2010] model. This produces episodic hillslope sediment inputs, which are delivered to a fluvial sediment, river-network routing model (modified from Czuba et al. [2017]). In this updated model, sediment transport dynamics are driven by time-varying discharge associated with the stochastic precipitation generation, include multiple grain sizes (including gravel), use mixed-size transport equations (Wilcock & Crowe [2003]), and incorporate channel slope adjustments with aggradation and degradation. Finally, with the spatially explicit adjustments in channel bed elevation and grain size, we utilize a new population viability analysis (PVA) model to predict the impact and recovery of fish populations in response to these changes in habitat. Our model provides a generalizable framework for linking physical and ecological models and for evaluating the extirpation risk of isolated fish populations throughout the Intermountain West to the increasing threat of wildfire.

On neutral metacommunity patterns of river basins at different scales of aggregation

NASA Astrophysics Data System (ADS)

Convertino, Matteo; Muneepeerakul, Rachata; Azaele, Sandro; Bertuzzo, Enrico; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

2009-08-01

Neutral metacommunity models for spatial biodiversity patterns are implemented on river networks acting as ecological corridors at different resolution. Coarse-graining elevation fields (under the constraint of preserving the basin mean elevation) produce a set of reconfigured drainage networks. The hydrologic assumption made implies uniform runoff production such that each link has the same habitat capacity. Despite the universal scaling properties shown by river basins regardless of size, climate, vegetation, or exposed lithology, we find that species richness at local and regional scales exhibits resolution-dependent behavior. In addition, we investigate species-area relationships and rank-abundance patterns. The slopes of the species-area relationships, which are consistent over coarse-graining resolutions, match those found in real landscapes in the case of long-distance dispersal. The rank-abundance patterns are independent of the resolution over a broad range of dispersal length. Our results confirm that strong interactions occur between network structure and the dispersal of species and that under the assumption of neutral dynamics, these interactions produce resolution-dependent biodiversity patterns that diverge from expectations following from universal geomorphic scaling laws. Both in theoretical and in applied ecology studying how patterns change in resolution is relevant for understanding how ecological dynamics work in fragmented landscape and for sampling and biodiversity management campaigns, especially in consideration of climate change.

Surface water - groundwater relationship in the downstream part of the Komadougou Yobe River (Eastern Sahelian Niger)

NASA Astrophysics Data System (ADS)

Hector, B.; Genthon, P.; Luxereau, A.; Descloîtres, M.; Moumouni Moussa, A.; Abdou, H.

2012-04-01

The Komadougou Yobe (KY) is a temporary river meandering on nearly 100 km along the Niger/Nigeria border in its lower part, before reaching the endoreic Lake Chad. There, seasonal flow from July to January is related to rainfall amount on the upstream Jos Plateau, Nigeria. In the semi-arid downstream area (350 mm annual rainfall in Diffa, Niger) the KY is the main source of recharge for the sandy quaternary aquifer which is used both for irrigation and for drinking water supply. The borders of the KY in Niger are subjected to an agricultural development involving intensive irrigated cropping of sweet pepper mainly produced for sale in Nigeria. Irrigation waters are mainly extracted from the KY, and therefore irrigation must stop when the River runs dry, but irrigation from wells is now developing with an increased risk of soil salinization. The flow rate of the KY has been impacted both by the 80s and 90s droughts, also underwent by the entire Sahel, and by the building up of a series of dams starting from the 70s in Nigeria. Therefore the KY and its relations with the underlying groundwaters should be carefully monitored to provide guidelines for policy makers in charge of the development of this area. However, in this remote area, data are scarce and often discontinuous : there are for example no continuous groundwater level data from before the drought. As part of the Lake Chad French IRD project, series of campaigns involving water level, exploration geophysics, gravity, soil sampling and social studies have been carried out between 2008 and 2011. They allowed to build a numerical model for groundwater-river interactions which in some instances has been compared with previously recorded data. This model is then forced with theoretical climatic senarii based on humid 60s data and data from the drought period. This allows discussing the relationships between the river and groundwaters in a changing climate. Our results militate for the setting up of a limited network of continuous groundwater monitoring near the river in conjunction with the existing network of gauging stations on the KY. Given the present day high variability of the climate (2010 was equivalent to one of the most humid years of the 60s, while 2005 was dry) this network could provide a validation for future models involving realistic climate senarii.

Ice flood velocity calculating approach based on single view metrology

NASA Astrophysics Data System (ADS)

Wu, X.; Xu, L.

2017-02-01

Yellow River is the river in which the ice flood occurs most frequently in China, hence, the Ice flood forecasting has great significance for the river flood prevention work. In various ice flood forecast models, the flow velocity is one of the most important parameters. In spite of the great significance of the flow velocity, its acquisition heavily relies on manual observation or deriving from empirical formula. In recent years, with the high development of video surveillance technology and wireless transmission network, the Yellow River Conservancy Commission set up the ice situation monitoring system, in which live videos can be transmitted to the monitoring center through 3G mobile networks. In this paper, an approach to get the ice velocity based on single view metrology and motion tracking technique using monitoring videos as input data is proposed. First of all, River way can be approximated as a plane. On this condition, we analyze the geometry relevance between the object side and the image side. Besides, we present the principle to measure length in object side from image. Secondly, we use LK optical flow which support pyramid data to track the ice in motion. Combining the result of camera calibration and single view metrology, we propose a flow to calculate the real velocity of ice flood. At last we realize a prototype system by programming and use it to test the reliability and rationality of the whole solution.

[Development and Use of Hidrosig

NASA Technical Reports Server (NTRS)

Gupta, Vijay K.; Milne, Bruce T.

2003-01-01

The NASA portion of this joint NSF-NASA grant consists of objective 2 and a part of objective 3. A major effort was made on objective 2, and it consisted of developing a numerical GIs environment called Hidrosig. This major research tool is being developed by the University of Colorado for conducting river-network-based scaling analyses of coupled water-energy-landform-vegetation interactions including water and energy balances, and floods and droughts, at multiple space-time scales.Objective 2: To analyze the relevant remotely sensed products from satellites, radars and ground measurements to compute the transported water mass for each complete Strahler stream using an 'assimilated water balance equation' at daily and other appropriate time scales. This objective requires analysis of concurrent data sets for Precipitation (PPT), Evapotranspiration (ET) and stream flows (Q) on river networks. To solve this major problem, our decision was to develop Hidrosig, a new Open-Source GIs software. A research group in Colombia, South America, developed the first version of Hidrosig, and Ricardo Mantilla was part of this effort as an undergraduate student before joining the graduate program at the University of Colorado in 2001. Hydrosig automatically extracts river networks from large DEMs and creates a "link-based" data structure, which is required to conduct a variety of analyses under objective 2. It is programmed in Java, which is a multi-platform programming language freely distributed by SUN under a GPL license. Some existent commercial tools like Arc-Info, RiverTools and others are not suitable for our purpose for two reasons. First, the source code is not available that is needed to build on the network data structure. Second, these tools use different programming languages that are not most versatile for our purposes. For example, RiverTools uses an IDL platform that is not very efficient for organizing diverse data sets on river networks. Hidrosig establishes a clear data organization framework that allows a simultaneous analysis of spatial fields along river network structures involving Horton- Strahler framework. Software tools for network extraction from DEMs and network-based analysis of geomorphologic and topologic variables were developed during the first year and a part of second year.

Topographic Features of Malyy Naryn River Watershed Based on Different Data

NASA Astrophysics Data System (ADS)

Li, M.; Chen, L.; Cui, Y.; Zhang, M.

2018-04-01

This paper researched the influence on the topographical characteristics of watersheds by setting different catchment area thresholds based on different data sets, namely ZY3 DSM, SRTM DEM and ASTER GDEM. Slope, hypsometric integral, river network density and river network discrepancy are analyzed and compared. The results are as follows: a) Three data sets all can express the same rough terrain characteristics and the same degree of watershed topography development; b) ZY3 DSM can reflect terrain information over the Malyy Naryn River watershed in most detail and it has the best expression effect on the terrain among the three data sets of ZY3 DSM, SRTM DEM and ASTER GDEM, followed by SRTM DEM, and the effect of ASTER GDEM is the worst; c) The similarity of river networks extracted by ZY3 DSM and SRTM DEM is the highest, and the similarity between ZY3 DSM and ASTER GDEM is the lowest one.

Overcoming complexities for consistent, continental-scale flood mapping

NASA Astrophysics Data System (ADS)

Smith, Helen; Zaidman, Maxine; Davison, Charlotte

2013-04-01

The EU Floods Directive requires all member states to produce flood hazard maps by 2013. Although flood mapping practices are well developed in Europe, there are huge variations in the scale and resolution of the maps between individual countries. Since extreme flood events are rarely confined to a single country, this is problematic, particularly for the re/insurance industry whose exposures often extend beyond country boundaries. Here, we discuss the challenges of large-scale hydrological and hydraulic modelling, using our experience of developing a 12-country model and set of maps, to illustrate how consistent, high-resolution river flood maps across Europe can be produced. The main challenges addressed include: data acquisition; manipulating the vast quantities of high-resolution data; and computational resources. Our starting point was to develop robust flood-frequency models that are suitable for estimating peak flows for a range of design flood return periods. We used the index flood approach, based on a statistical analysis of historic river flow data pooled on the basis of catchment characteristics. Historical flow data were therefore sourced for each country and collated into a large pan-European database. After a lengthy validation these data were collated into 21 separate analysis zones or regions, grouping smaller river basins according to their physical and climatic characteristics. The very large continental scale basins were each modelled separately on account of their size (e.g. Danube, Elbe, Drava and Rhine). Our methodology allows the design flood hydrograph to be predicted at any point on the river network for a range of return periods. Using JFlow+, JBA's proprietary 2D hydraulic hydrodynamic model, the calculated out-of-bank flows for all watercourses with an upstream drainage area exceeding 50km2 were routed across two different Digital Terrain Models in order to map the extent and depth of floodplain inundation. This generated modelling for a total river length of approximately 250,000km. Such a large-scale, high-resolution modelling exercise is extremely demanding on computational resources and would have been unfeasible without the use of Graphics Processing Units on a network of standard specification gaming computers. Our GPU grid is the world's largest flood-dedicated computer grid. The European river basins were split out into approximately 100 separate hydraulic models and managed individually, although care was taken to ensure flow continuity was maintained between models. The flood hazard maps from the modelling were pieced together using GIS techniques, to provide flood depth and extent information across Europe to a consistent scale and standard. After discussing the methodological challenges, we shall present our flood hazard maps and, from extensive validation work, compare these against historical flow records and observed flood extents.

Assessing the natural and anthropogenic influences on basin-wide fish species richness.

PubMed

Cheng, Su-Ting; Herricks, Edwin E; Tsai, Wen-Ping; Chang, Fi-John

2016-12-01

Theory predicts that the number of fish species increases with river size in natural free-flowing rivers, but the relationship is lost under intensive exploitation of water resources associated with dams and/or landscape developments. In this paper, we aim to identify orthomorphic issues that disrupt theoretical species patterns based on a multi-year, basin-wide assessment in the Danshuei River Watershed of Taiwan. We hypothesize that multiple human-induced modifications fragment habitat areas leading to decreases of local fish species richness. We integrally relate natural and anthropogenic influences on fish species richness by a multiple linear regression model that is driven by a combination of factors including river network structure controls, water quality alterations of habitat, and disruption of channel connectivity with major discontinuities in habitat caused by dams. We found that stream order is a major forcing factor representing natural influence on fish species richness. In addition to stream order, we identified dams, dissolved oxygen deficiency (DO), and excessive total phosphorus (TP) as major anthropogenic influences on the richness of fish species. Our results showed that anthropogenic influences were operating at various spatial scales that inherently regulate the physical, chemical, and biological condition of fish habitats. Moreover, our probability-based risk assessment revealed causes of species richness reduction and opportunities for mitigation. Risks of species richness reduction caused by dams were determined by the position of dams and the contribution of tributaries in the drainage network. Risks associated with TP and DO were higher in human-activity-intensified downstream reaches. Our methodology provides a structural framework for assessing changes in basin-wide fish species richness under the mixed natural and human-modified river network and habitat conditions. Based on our analysis results, we recommend that a focus on landscape and riverine habitats and maintaining long-term monitoring programs are crucial for effective watershed management and river conservation plans. Copyright © 2016 Elsevier B.V. All rights reserved.

The "normal" elongation of river basins

NASA Astrophysics Data System (ADS)

Castelltort, Sebastien

2013-04-01

The spacing between major transverse rivers at the front of Earth's linear mountain belts consistently scales with about half of the mountain half-width [1], despite strong differences in climate and rock uplift rates. Like other empirical measures describing drainage network geometry this result seems to indicate that the form of river basins, among other properties of landscapes, is invariant. Paradoxically, in many current landscape evolution models, the patterns of drainage network organization, as seen for example in drainage density and channel spacing, seem to depend on both climate [2-4] and tectonics [5]. Hovius' observation [1] is one of several unexplained "laws" in geomorphology that still sheds mystery on how water, and rivers in particular, shape the Earth's landscapes. This narrow range of drainage network shapes found in the Earth's orogens is classicaly regarded as an optimal catchment geometry that embodies a "most probable state" in the uplift-erosion system of a linear mountain belt. River basins currently having an aspect away from this geometry are usually considered unstable and expected to re-equilibrate over geological time-scales. Here I show that the Length/Width~2 aspect ratio of drainage basins in linear mountain belts is the natural expectation of sampling a uniform or normal distribution of basin shapes, and bears no information on the geomorphic processes responsible for landscape development. This finding also applies to Hack's [6] law of river basins areas and lengths, a close parent of Hovius' law. [1]Hovius, N. Basin Res. 8, 29-44 (1996) [2]Simpson, G. & Schlunegger, F. J. Geophys. Res. 108, 2300 (2003) [3]Tucker, G. & Bras, R. Water Resour. Res. 34, 2751-2764 (1998) [4]Tucker, G. & Slingerland, R. Water Resour. Res. 33, 2031-2047 (1997) [5]Tucker, G. E. & Whipple, K. X. J. Geophys. Res. 107, 1-1 (2002) [6]Hack, J. US Geol. Surv. Prof. Pap. 294-B (1957)

An ecohydrologic framework for simulating catchment constraints on smallholder irrigation systems in drylands

NASA Astrophysics Data System (ADS)

Gower, D.; McCord, P. F.; Caylor, K. K.; Dell'Angelo, J.; Evans, T. P.

2016-12-01

Community water projects (CWPs) in the Laikipia region of Central Kenya distribute river water to smallholder farmers who otherwise lack access to municipal systems or private water sources. Participating farmers are better able to withstand climatic conditions commonly found in drylands, including high potential evapotranspiration combined with low and variable rainfall. To provide these benefits, however, CWPs must be able to deliver water in sufficient quantities and with sufficient regularity to all farmers in the network. Factors such as variable river flow, aging infrastructure and increasing membership pose challenges to the CWP management in fulfilling this task. During the dry season, river levels typically decline, reducing water available for CWP and increasing the importance of intake position within the catchment. CWPs with intakes in upstream areas have first access to river water but rely on a smaller drainage network while those in downstream areas are affected by the opposite conditions. Such conditions have pushed CWPs to jointly regulate their water consumption by setting withdrawal limits and coordinating withdrawal schedules with one another. Regulations also ensure that river water is not completely consumed by CWPs, allowing some flow to exit the catchment for human or environmental reasons. This paper uses a simple numerical model to calculate the monetary benefit that individual farmers receive from membership in a CWP. In the model, the CWP provides water to a variable number of farmers in exchange for membership fees while farmers must grow sufficient crops to feed themselves and pay fees. The model shows that, under conditions similar to those in Laikipia, CWP can consistently provide adequate benefits to its members only with intakes at particular locations within the catchment or with specific regulations in place. Otherwise, the economic benefits of CWP membership will gradually fall below the cost of membership. This result may help in developing recommendations as to how CWP should be located and managed in similar areas.

RIPARIAN SHADE CONTROLS ON STREAM TEMPERATURE NOW AND IN THE FUTURE ACROSS TRIBUTARIES OF THE COLUMBIA RIVER, USA

EPA Science Inventory

Future climates may warm stream temperatures altering aquatic communities and threatening socioeconomically-important species. These impacts will vary across large spatial extents and require special evaluation tools. Statistical stream network models (SSNs) account for spatial a...

Extending flood forecasting lead time in large basin by coupling bias-corrected WRF QPF with distributed hydrological model

NASA Astrophysics Data System (ADS)

LI, J.; Chen, Y.; Wang, H. Y.

2016-12-01

In large basin flood forecasting, the forecasting lead time is very important. Advances in numerical weather forecasting in the past decades provides new input to extend flood forecasting lead time in large rivers. Challenges for fulfilling this goal currently is that the uncertainty of QPF with these kinds of NWP models are still high, so controlling the uncertainty of QPF is an emerging technique requirement.The Weather Research and Forecasting (WRF) model is one of these NWPs, and how to control the QPF uncertainty of WRF is the research topic of many researchers among the meteorological community. In this study, the QPF products in the Liujiang river basin, a big river with a drainage area of 56,000 km2, was compared with the ground observation precipitation from a rain gauge networks firstly, and the results show that the uncertainty of the WRF QPF is relatively high. So a post-processed algorithm by correlating the QPF with the observed precipitation is proposed to remove the systematical bias in QPF. With this algorithm, the post-processed WRF QPF is close to the ground observed precipitation in area-averaged precipitation. Then the precipitation is coupled with the Liuxihe model, a physically based distributed hydrological model that is widely used in small watershed flash flood forecasting. The Liuxihe Model has the advantage with gridded precipitation from NWP and could optimize model parameters when there are some observed hydrological data even there is only a few, it also has very high model resolution to improve model performance, and runs on high performance supercomputer with parallel algorithm if executed in large rivers. Two flood events in the Liujiang River were collected, one was used to optimize the model parameters and another is used to validate the model. The results show that the river flow simulation has been improved largely, and could be used for real-time flood forecasting trail in extending flood forecasting leading time.

From mountains to the ocean: quantifying connectivity along the river corridor

NASA Astrophysics Data System (ADS)

Gomez-Velez, J. D.; Harvey, J. W.

2015-12-01

Rivers are the landscape's arteries; they convey water, solutes, energy, and living organisms from the hillslopes, floodplains, aquifers, and atmosphere to the oceans. As water moves along this complex circulatory system, it is continuously exchanged with the surrounding alluvial aquifer, termed hyporheic exchange, which strongly conditions and constrains the biogeochemical evolution of water at the local scale with basin-scale consequences. Over the last two decades, considerable efforts have focused on the use of detailed mathematical models to explore the hydrodynamics and biogeochemical effect of hyporheic exchange at the scale of individual channel morphologies. While these efforts are essential to gain mechanistic understanding, their computational demand makes them impractical for basin applications. In this talk, a parsimonious but physically based model of hyporheic flow for application in large river basins is presented: Networks with EXchange and Subsurface Storage (NEXSS). At the core of NEXSS are the up-scaling of detailed mathematical models and a characterization of the channel geometry, geomorphic features, and related hydraulic drivers based on scaling equations from the literature and readily accessible information such as river discharge, width, grain size, sinuosity, channel slope, and regional groundwater gradients. As a proof-of-concept, we use NEXSS to characterize the spatial and temporal variability of hyporheic exchange and denitrification potential along the Mississippi River basin. This modeling approach allows us to map the location of critical hot spots for biogeochemical transformation, their geomorphic drivers, and cumulative effect. Finally, we discuss new avenues to incorporate exchange with floodplains and ponded waters, which also play a key role in water quality along the river corridor. This new modeling approach is critical to transition from purely empirical continental models of water quality to hybrid approaches that incorporate fundamental physics and take advantage of available hydrogeomorphic data. In particular, hybrid models will be instrumental for predicting outcomes of river basin management practices under present and future socio-economic and climatic conditions.

Modelling Soil Erosion in the Densu River Basin Using RUSLE and GIS Tools.

PubMed

Ashiagbori, G; Forkuo, E K; Laari, P; Aabeyir, R

2014-07-01

Soil erosion involves detachment and transport of soil particles from top soil layers, degrading soil quality and reducing the productivity of affected lands. Soil eroded from the upland catchment causes depletion of fertile agricultural land and the resulting sediment deposited at the river networks creates river morphological change and reservoir sedimentation problems. However, land managers and policy makers are more interested in the spatial distribution of soil erosion risk than in absolute values of soil erosion loss. The aim of this paper is to model the spatial distribution of soil erosion in Densu River Basin of Ghana using RUSLE and GIS tools and to use the model to explore the relationship between erosion susceptibility, slope and land use/land cover (LULC) in the Basin. The rainfall map, digital elevation model, soil type map, and land cover map, were input data in the soil erosion model developed. This model was then categorized into four different erosion risk classes. The developed soil erosion map was then overlaid with the slope and LULC maps of the study area to explore their effects on erosion susceptibility of the soil in the Densu River Basin. The Model, predicted 88% of the basin as low erosion risk and 6% as moderate erosion risk, 3% as high erosion risk and 3% as severe risk. The high and severe erosion areas were distributed mainly within the areas of high slope gradient and also sections of the moderate forest LULC class. Also, the areas within the moderate forest LULC class found to have high erosion risk, had an intersecting high erodibility soil group.

Spatial statistical network models for stream and river temperature in New England, USA

NASA Astrophysics Data System (ADS)

Detenbeck, Naomi E.; Morrison, Alisa C.; Abele, Ralph W.; Kopp, Darin A.

2016-08-01

Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May-September growing season (July or August median temperature, diurnal rate of change, and magnitude and timing of growing season maximum) chosen through principal component analysis of 78 candidate metrics. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance along the flow network and Euclidean distance between points. Calculation of spatial autocorrelation based on travel or retention time in place of network distance yielded tighter-fitting Torgegrams with less scatter but did not improve overall model prediction accuracy. We predicted monthly median July or August stream temperatures as a function of median air temperature, estimated urban heat island effect, shaded solar radiation, main channel slope, watershed storage (percent lake and wetland area), percent coarse-grained surficial deposits, and presence or maximum depth of a lake immediately upstream, with an overall root-mean-square prediction error of 1.4 and 1.5°C, respectively. Growing season maximum water temperature varied as a function of air temperature, local channel slope, shaded August solar radiation, imperviousness, and watershed storage. Predictive models for July or August daily range, maximum daily rate of change, and timing of growing season maximum were statistically significant but explained a much lower proportion of variance than the above models (5-14% of total).

Hydrodynamic Influence Dabanhu River Bridge Holes Widening Based on Two-Dimensional Finite Element Numerical Model

NASA Astrophysics Data System (ADS)

Li, Dong Feng; Bai, Fu Qing; Nie, Hui

2018-06-01

In order to analyze the influence of bridge holes widening on hydrodynamic such as water level, a two-dimensional mathematical model was used to calculate the hydrodynamic factors, river network flow velocity vector distribution is given, water level and difference of bridge widening before and after is calculated and charted, water surface gradient in seven different river sections near the upper reaches of bridges is counted and revealed. The results of hydrodynamic calculation indicate that The Maximum and the minimum deducing numerical value of the water level after bridge widening is 0.028m, and 0.018m respective. the seven sections water surface gradient becomes smaller until it becomes negative, the influence of bridge widening on the upstream is basically over, the range of influence is about 450m from the bridge to the upstream. reach

Hydrological information system based on on-line monitoring--from strategy to implementation in the Brantas River Basin, East Java, Indonesia.

PubMed

Marini, G W; Wellguni, H

2003-01-01

The worsening environmental situation of the Brantas River, East Java, is addressed by a comprehensive basin management strategy which relies on accurate water quantity and quality data retrieved from a newly installed online monitoring network. Integrated into a Hydrological Information System, the continuously measured indicative parameters allow early warning, control and polluter identification. Additionally, long-term analyses have been initiated for improving modelling applications like flood forecasting, water resource management and pollutant propagation. Preliminary results illustrate the efficiency of the installed system.

Global river flood hazard maps: hydraulic modelling methods and appropriate uses

NASA Astrophysics Data System (ADS)

Townend, Samuel; Smith, Helen; Molloy, James

2014-05-01

Flood hazard is not well understood or documented in many parts of the world. Consequently, the (re-)insurance sector now needs to better understand where the potential for considerable river flooding aligns with significant exposure. For example, international manufacturing companies are often attracted to countries with emerging economies, meaning that events such as the 2011 Thailand floods have resulted in many multinational businesses with assets in these regions incurring large, unexpected losses. This contribution addresses and critically evaluates the hydraulic methods employed to develop a consistent global scale set of river flood hazard maps, used to fill the knowledge gap outlined above. The basis of the modelling approach is an innovative, bespoke 1D/2D hydraulic model (RFlow) which has been used to model a global river network of over 5.3 million kilometres. Estimated flood peaks at each of these model nodes are determined using an empirically based rainfall-runoff approach linking design rainfall to design river flood magnitudes. The hydraulic model is used to determine extents and depths of floodplain inundation following river bank overflow. From this, deterministic flood hazard maps are calculated for several design return periods between 20-years and 1,500-years. Firstly, we will discuss the rationale behind the appropriate hydraulic modelling methods and inputs chosen to produce a consistent global scaled river flood hazard map. This will highlight how a model designed to work with global datasets can be more favourable for hydraulic modelling at the global scale and why using innovative techniques customised for broad scale use are preferable to modifying existing hydraulic models. Similarly, the advantages and disadvantages of both 1D and 2D modelling will be explored and balanced against the time, computer and human resources available, particularly when using a Digital Surface Model at 30m resolution. Finally, we will suggest some appropriate uses of global scale hazard maps and explore how this new approach can be invaluable in areas of the world where flood hazard and risk have not previously been assessed.

Delay/Disruption Tolerant Network-Based Message Forwarding for a River Pollution Monitoring Wireless Sensor Network Application.

PubMed

Velásquez-Villada, Carlos; Donoso, Yezid

2016-03-25

Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river's course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas' movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.

Flood forecasting using non-stationarity in a river with tidal influence - a feasibility study

NASA Astrophysics Data System (ADS)

Killick, Rebecca; Kretzschmar, Ann; Ilic, Suzi; Tych, Wlodek

2017-04-01

Flooding is the most common natural hazard causing damage, disruption and loss of life worldwide. Despite improvements in modelling and forecasting of water levels and flood inundation (Kretzschmar et al., 2014; Hoitink and Jay, 2016), there are still large discrepancies between predictions and observations particularly during storm events when accurate predictions are most important. Many models exist for forecasting river levels (Smith et al., 2013; Leedal et al., 2013) however they commonly assume that the errors in the data are independent, stationary and normally distributed. This is generally not the case especially during storm events suggesting that existing models are not describing the drivers of river level in an appropriate fashion. Further challenges exist in the lower sections of a river influenced by both river and tidal flows and their interaction and there is scope for improvement in prediction. This paper investigates the use of a powerful statistical technique to adaptively forecast river levels by modelling the process as locally stationary. The proposed methodology takes information on both upstream and downstream river levels and incorporates meteorological information (rainfall forecasts) and tidal levels when required to forecast river levels at a specified location. Using this approach, a single model will be capable of predicting water levels in both tidal and non-tidal river reaches. In this pilot project, the methodology of Smith et al. (2013) using harmonic tidal analysis and data based mechanistic modelling is compared with the methodology developed by Killick et al. (2016) utilising data-driven wavelet decomposition to account for the information contained in the upstream and downstream river data to forecast a non-stationary time-series. Preliminary modelling has been carried out using the tidal stretch of the River Lune in North-west England and initial results are presented here. Future work includes expanding the methodology to forecast river levels at a network of locations simultaneously. References Hoitink, A. J. F., and D. A. Jay (2016), Tidal river dynamics: Implications for deltas, Rev. Geophys., 54, 240-272 Killick, R., Knight, M., Nason, G.P., Eckley, I.A. (2016) The Local Partial Autocorrelation Function and its Application to the Forecasting of Locally Stationary Time Series. Submitted Kretzschmar, Ann and Tych, Wlodek and Chappell, Nick A (2014) Reversing hydrology: estimation of sub-hourly rainfall time-series from streamflow. Env. Modell Softw., 60. pp. 290-301 D. Leedal, A. H. Weerts, P. J. Smith, & K. J. Beven. (2013). Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales). HESS, 17(1), 177-185. Smith, P., Beven, K., Horsburgh, K., Hardaker, P., & Collier, C. (2013). Data-based mechanistic modelling of tidally affected river reaches for flood warning purposes: An example on the River Dee, UK. , Q.J.R. Meteorol. Soc. 139(671), 340-349.

Branching pattern in natural drainage network

NASA Astrophysics Data System (ADS)

Hooshyar, M.; Singh, A.; Wang, D.

2017-12-01

The formation and growth of river channels and their network evolution are governed by the erosional and depositional processes operating on the landscape due to movement of water. The branching structure of drainage network is an important feature related to the network topology and contain valuable information about the forming mechanisms of the landscape. We studied the branching patterns in natural drainage networks, extracted from 1 m Digital Elevation Models (DEMs) of 120 catchments with minimal human impacts across the United States. We showed that the junction angles have two distinct modes an the observed modes are physically explained as the optimal angles that result in minimum energy dissipation and are linked to the exponent characterizing slope-area curve. Our findings suggest that the flow regimes, debris-flow dominated or fluvial, have distinct characteristic angles which are functions of the scaling exponent of the slope-area curve. These findings enable us to understand the geomorphological signature of hydrological processes on drainage networks and develop more refined landscape evolution models.

A new approach to flow simulation using hybrid models

NASA Astrophysics Data System (ADS)

Solgi, Abazar; Zarei, Heidar; Nourani, Vahid; Bahmani, Ramin

2017-11-01

The necessity of flow prediction in rivers, for proper management of water resource, and the need for determining the inflow to the dam reservoir, designing efficient flood warning systems and so forth, have always led water researchers to think about models with high-speed response and low error. In the recent years, the development of Artificial Neural Networks and Wavelet theory and using the combination of models help researchers to estimate the river flow better and better. In this study, daily and monthly scales were used for simulating the flow of Gamasiyab River, Nahavand, Iran. The first simulation was done using two types of ANN and ANFIS models. Then, using wavelet theory and decomposing input signals of the used parameters, sub-signals were obtained and were fed into the ANN and ANFIS to obtain hybrid models of WANN and WANFIS. In this study, in addition to the parameters of precipitation and flow, parameters of temperature and evaporation were used to analyze their effects on the simulation. The results showed that using wavelet transform improved the performance of the models in both monthly and daily scale. However, it had a better effect on the monthly scale and the WANFIS was the best model.

Analysis of the ecological water diversion project in Wenzhou City

NASA Astrophysics Data System (ADS)

Xu, Haibo; Fu, Lei; Lin, Tong

2018-02-01

As a developed city in China, Wenzhou City has been suffered from bad water quality for years. In order to improve the river network water quality, an ecological water diversion project was designed and executed by the regional government. In this study, an investigation and analysis of the regional ecological water diversion project is made for the purpose of examining the water quality improvements. A numerical model is also established, different water diversion flow rates and sewer interception levels are considered during the simulation. Simulation results reveal that higher flow rate and sewer interception level will greatly improve the river network water quality in Wenzhou City. The importance of the flow rate and interception level has been proved and future work will be focused on increasing the flow rate and upgrading the sewer interception level.

Comparing spatial and temporal patterns of river water isotopes across networks

EPA Science Inventory

A detailed understanding of the spatial and temporal dynamics of water sources across river networks is central to managing the impacts of climate change. Because the stable isotope composition of precipitation varies geographically, variation in surface-water isotope signatures ...

The Regularity of Optimal Irrigation Patterns

NASA Astrophysics Data System (ADS)

Morel, Jean-Michel; Santambrogio, Filippo

2010-02-01

A branched structure is observable in draining and irrigation systems, in electric power supply systems, and in natural objects like blood vessels, the river basins or the trees. Recent approaches of these networks derive their branched structure from an energy functional whose essential feature is to favor wide routes. Given a flow s in a river, a road, a tube or a wire, the transportation cost per unit length is supposed in these models to be proportional to s α with 0 < α < 1. The aim of this paper is to prove the regularity of paths (rivers, branches,...) when the irrigated measure is the Lebesgue density on a smooth open set and the irrigating measure is a single source. In that case we prove that all branches of optimal irrigation trees satisfy an elliptic equation and that their curvature is a bounded measure. In consequence all branching points in the network have a tangent cone made of a finite number of segments, and all other points have a tangent. An explicit counterexample disproves these regularity properties for non-Lebesgue irrigated measures.

Development of a flood-warning network and flood-inundation mapping for the Blanchard River in Ottawa, Ohio

USGS Publications Warehouse

Whitehead, Matthew T.

2011-01-01

Digital flood-inundation maps of the Blanchard River in Ottawa, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service and the Village of Ottawa, Ohio. The maps, which correspond to water levels (stages) at the USGS streamgage at Ottawa (USGS streamgage site number 04189260), were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning Network that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. Flood profiles were computed by means of a step-backwater model calibrated to recent field measurements of streamflow. The step-backwater model was then used to determine water-surface-elevation profiles for 12 flood stages with corresponding streamflows ranging from less than the 2-year and up to nearly the 500-year recurrence-interval flood. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of the Village of Ottawa showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. As part of this flood-warning network, the USGS upgraded one streamgage and added two new streamgages, one on the Blanchard River and one on Riley Creek, which is tributary to the Blanchard River. The streamgage sites were equipped with both satellite and telephone telemetry. The telephone telemetry provides dual functionality, allowing village officials and the public to monitor current stage conditions and enabling the streamgage to call village officials with automated warnings regarding flood stage and/or predetermined rates of stage increase. Data from the streamgages serve as a flood warning that emergency management personnel can use in conjunction with the flood-inundation maps by to determine a course of action when flooding is imminent.

River Networks and Human Activities: Global Fractal Analysis Using Nightlight Data

NASA Astrophysics Data System (ADS)

McCurley, K. 4553; Fang, Y.; Ceola, S.; Paik, K.; McGrath, G. S.; Montanari, A.; Rao, P. S.; Jawitz, J. W.

2016-12-01

River networks hold an important historical role in affecting human population distribution. In this study, we link the geomorphological structure of river networks to the pattern of human activities at a global scale. We use nightlights as a valuable proxy for the presence of human settlements and economic activity, and we employ HydroSHEDS as the main data source on river networks. We test the hypotheses that, analogous to Horton's laws, human activities (magnitude of nightlights) also show scaling relationship with stream order, and that the intensity of human activities decrease as the distance from the basin outlet increase. Our results demonstrate that the distribution of human activities shows a fractal structure, with power-law scaling between human activities and stream order. This relationship is robust among global river basins. Human activities are more concentrated in larger order basins, but show large variation in equivalent order basins, with higher population density emergent in the basins connected with high-order rivers. For all global river basins longer than 400km, the average intensity of human activities decrease as the distance to the outlets increases, albeit with signatures of large cities at varied distances. The power spectrum of human width (area) function is found to exhibit power law scaling, with a scaling exponent that indicates enrichment of low frequency variation. The universal fractal structure of human activities may reflect an optimum arrangement for humans in river basins to better utilize the water resources, ecological assets, and geographic advantages. The generalized patterns of human activities could be applied to better understand hydrologic and biogeochemical responses in river basins, and to advance catchment management.

River bathymetry estimation based on the floodplains topography.

NASA Astrophysics Data System (ADS)

Bureš, Luděk; Máca, Petr; Roub, Radek; Pech, Pavel; Hejduk, Tomáš; Novák, Pavel

2017-04-01

Topographic model including River bathymetry (bed topography) is required for hydrodynamic simulation, water quality modelling, flood inundation mapping, sediment transport, ecological and geomorphologic assessments. The most common way to create the river bathymetry is to use of the spatial interpolation of discrete points or cross sections data. The quality of the generated bathymetry is dependent on the quality of the measurements, on the used technology and on the size of input dataset. Extensive measurements are often time consuming and expensive. Other option for creating of the river bathymetry is to use the methods of mathematical modelling. In the presented contribution we created the river bathymetry model. Model is based on the analytical curves. The curves are bent into shape of the cross sections. For the best description of the river bathymetry we need to know the values of the model parameters. For finding these parameters we use of the global optimization methods. The global optimization schemes is based on heuristics inspired by the natural processes. We use new type of DE (differential evolution) for finding the solutions of inverse problems, related to the parameters of mathematical model of river bed surfaces. The presented analysis discuss the dependence of model parameters on the selected characteristics. Selected characteristics are: (1) Topographic characteristics (slope and curvature in the left and right floodplains) determined on the base of DTM 5G (digital terrain model). (2) Optimization scheme. (3) Type of used analytical curves. The novel approach is applied on the three parts of Vltava river in Czech Republic. Each part of the river is described on the base of the point field. The point fields was measured with ADCP probe River surveyor M9. This work was supported by the Technology Agency of the Czech Republic, programme Alpha (project TA04020042 - New technologies bathymetry of rivers and reservoirs to determine their storage capacity and monitor the amount and dynamics of sediments) and Internal Grant Agency of Faculty of Environmental Sciences (CULS) (IGA/20164233). Keywords: bathymetry, global optimization, bed topography References: Merwade, Venkatesh. "Effect of spatial trends on interpolation of river bathymetry." Journal of Hydrology, 371.1, 169-181, 2009. Legleiter, Carl J., and Phaedon C. Kyriakidis. Spatial prediction of river channel topography by kriging. Earth Surface Processes and Landforms, 33.6 , 841-867, 2008. P. Maca and P. Pech and and J. Pavlasek. Comparing the Selected Transfer Functions and Local Optimization Methods for Neural Network Flood Runoff Forecast. Mathematical Problems in Engineering, vol. 2014, Article ID 782351, 10 pages, 2014. M. Jakubcova and P. Maca and and P. Pech. A Comparison of Selected Modifications of the Particle Swarm Optimization Algorithm. Journal of Applied Mathematics, vol. 2014, Article ID 293087, 10 pages, 2014.

An integrated modeling approach to predict flooding on urban basin.

PubMed

Dey, Ashis Kumar; Kamioka, Seiji

2007-01-01

Correct prediction of flood extents in urban catchments has become a challenging issue. The traditional urban drainage models that consider only the sewerage-network are able to simulate the drainage system correctly until there is no overflow from the network inlet or manhole. When such overflows exist due to insufficient drainage capacity of downstream pipes or channels, it becomes difficult to reproduce the actual flood extents using these traditional one-phase simulation techniques. On the other hand, the traditional 2D models that simulate the surface flooding resulting from rainfall and/or levee break do not consider the sewerage network. As a result, the correct flooding situation is rarely addressed from those available traditional 1D and 2D models. This paper presents an integrated model that simultaneously simulates the sewerage network, river network and 2D mesh network to get correct flood extents. The model has been successfully applied into the Tenpaku basin (Nagoya, Japan), which experienced severe flooding with a maximum flood depth more than 1.5 m on September 11, 2000 when heavy rainfall, 580 mm in 28 hrs (return period > 100 yr), occurred over the catchments. Close agreements between the simulated flood depths and observed data ensure that the present integrated modeling approach is able to reproduce the urban flooding situation accurately, which rarely can be obtained through the traditional 1D and 2D modeling approaches.

Uranium plume persistence impacted by hydrologic and geochemical heterogeneity in the groundwater and river water interaction zone of Hanford site

NASA Astrophysics Data System (ADS)

Chen, X.; Zachara, J. M.; Vermeul, V. R.; Freshley, M.; Hammond, G. E.

2015-12-01

The behavior of a persistent uranium plume in an extended groundwater- river water (GW-SW) interaction zone at the DOE Hanford site is dominantly controlled by river stage fluctuations in the adjacent Columbia River. The plume behavior is further complicated by substantial heterogeneity in physical and geochemical properties of the host aquifer sediments. Multi-scale field and laboratory experiments and reactive transport modeling were integrated to understand the complex plume behavior influenced by highly variable hydrologic and geochemical conditions in time and space. In this presentation we (1) describe multiple data sets from field-scale uranium adsorption and desorption experiments performed at our experimental well-field, (2) develop a reactive transport model that incorporates hydrologic and geochemical heterogeneities characterized from multi-scale and multi-type datasets and a surface complexation reaction network based on laboratory studies, and (3) compare the modeling and observation results to provide insights on how to refine the conceptual model and reduce prediction uncertainties. The experimental results revealed significant spatial variability in uranium adsorption/desorption behavior, while modeling demonstrated that ambient hydrologic and geochemical conditions and heterogeneities in sediment physical and chemical properties both contributed to complex plume behavior and its persistence. Our analysis provides important insights into the characterization, understanding, modeling, and remediation of groundwater contaminant plumes influenced by surface water and groundwater interactions.

Assimilation of measurement data in hydrodynamic modeling

NASA Astrophysics Data System (ADS)

Karamuz, Emilia; Romanowicz, Renata J.

2016-04-01

This study focuses on developing methods to combine ground-based data from operational monitoring with data from satellite imaging to obtain a more accurate evaluation of flood inundation extents. The distributed flow model MIKE 11 was used to determine the flooding areas for a flood event with available satellite data. Model conditioning was based on the integrated use of data from remote measurement techniques and traditional data from gauging stations. Such conditioning of the model improves the quality of fit of the model results. The use of high resolution satellite images (from IKONOS, QuickBird e.t.c) and LiDAR Digital Elevation Model (DEM) allows information on water levels to be extended to practically any chosen cross-section of the tested section of the river. This approach allows for a better assessment of inundation extent, particularly in areas with a scarce network of gauging stations. We apply approximate Bayesian analysis to integrate the information on flood extent originating from different sources. The approach described above was applied to the Middle River Vistula reach, from the Zawichost to Warsaw gauging stations. For this part of the river the detailed geometry of the river bed and floodplain data were available. Finally, three selected sub-sections were analyzed with the most suitable satellite images of inundation area. ACKNOWLEDGEMENTS This research was supported by the Institute of Geophysics Polish Academy of Sciences through the Young Scientist Grant no. 3b/IGF PAN/2015.

Evaluating the Simulation of MetacommUnities for Riverine Fishes (SMURF) in the Calapooia Basin, OR

EPA Science Inventory

We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the grain and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

Evaluation of Flow Paths and Confluences for Saltwater Intrusion and Its Influence on Fish Species Diversity in a Deltaic River Network

NASA Astrophysics Data System (ADS)

Shao, X.; Cui, B.; Zhang, Z.; Fang, Y.; Jawitz, J. W.

2016-12-01

Freshwater in a delta is often at risk of saltwater intrusion, which has been a serious issue in estuarine deltas all over the world. Salinity gradients and hydrologic connectivity in the deltas can be disturbed by saltwater intrusion, which can fluctuate frequently and locally in time and space to affect biotic processes and then to affect the distribution patterns of the riverine fishes throughout the river network. Therefore, identifying the major flow paths or locations at risk of saltwater intrusion in estuarine ecosystems is necessary for saltwater intrusion mitigation and fish species diversity conservation. In this study, we use the betweenness centrality (BC) as the weighted attribute of the river network to identify the critical confluences and detect the preferential flow paths for saltwater intrusion through the least-cost-path algorithm from graph theory approach. Moreover, we analyse the responses of the salinity and fish species diversity to the BC values of confluences calculated in the river network. Our results show that the most likely location of saltwater intrusion is not a simple gradient change from sea to land, but closely dependent on the river segments' characteristics. In addition, a significant positive correlation between the salinity and the BC values of confluences is determined in the Pearl River Delta. Changes in the BC values of confluences can produce significant variation in the fish species diversity. Therefore, the dynamics of saltwater intrusion are a growing consideration for understanding the patterns and subsequent processes driving fish community structure. Freshwater can be diverted into these major flow paths and critical confluences to improve river network management and conservation of fish species diversity under saltwater intrusion.

Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

NASA Astrophysics Data System (ADS)

Pereira, A. A.; Gironas, J. A.; Passalacqua, P.; Mejia, A.; Niemann, J. D.

2017-12-01

Previous work has shown that lithological, tectonic and climatic processes have a major influence in shaping the geomorphology of river networks. Accordingly, quantitative classification methods have been developed to identify and characterize network types (dendritic, parallel, pinnate, rectangular and trellis) based solely on the self-affinity of their planform properties, computed from available Digital Elevation Model (DEM) data. In contrast, this research aim is to include both horizontal and vertical properties to evaluate a quantitative classification method for river networks. We include vertical properties to consider the unique surficial conditions (e.g., large and steep height drops, volcanic activity, and complexity of stream networks) of the Andes Mountains. Furthermore, the goal of the research is also to explain the implications and possible relations between the hydro-geomorphological properties and climatic conditions. The classification method is applied to 42 basins in the southern Andes in Chile, ranging in size from 208 Km2 to 8,000 Km2. The planform metrics include the incremental drainage area, stream course irregularity and junction angles, while the vertical metrics include the hypsometric curve and the slope-area relationship. We introduce new network structures (Brush, Funnel and Low Sinuosity Rectangular), possibly unique to the Andes, that can be quantitatively differentiated from previous networks identified in other geographic regions. Then, this research evaluates the effect that excluding different Strahler order streams has on the horizontal properties and therefore in the classification. We found that climatic conditions are not only linked to horizontal parameters, but also to vertical ones, finding significant correlation between climatic variables (average near-surface temperature and rainfall) and vertical measures (parameters associated with the hypsometric curve and slope-area relation). The proposed classification shows differences among basins previously classified as the same type, which are not noticeable in their horizontal properties and helps reduce misclassifications within the old clusters. Additional hydro-geomorphological metrics are to be considered in the classification method to improve the effectiveness of it.

MoGIRE: A Model for Integrated Water Management

NASA Astrophysics Data System (ADS)

Reynaud, A.; Leenhardt, D.

2008-12-01

Climate change and growing water needs have resulted in many parts of the world in water scarcity problems that must by managed by public authorities. Hence, policy-makers are more and more often asked to define and to implement water allocation rules between competitive users. This requires to develop new tools aiming at designing those rules for various scenarios of context (climatic, agronomic, economic). If models have been developed for each type of water use however, very few integrated frameworks link these different uses, while such an integrated approach is a relevant stake for designing regional water and land policies. The lack of such integrated models can be explained by the difficulty of integrating models developed by very different disciplines and by the problem of scale change (collecting data on large area, arbitrate between the computational tractability of models and their level of aggregation). However, modelers are more and more asked to deal with large basin scales while analyzing some policy impacts at very high detailed levels. These contradicting objectives require to develop new modeling tools. The CALVIN economically-driven optimization model developed for managing water in California is a good example of this type of framework, Draper et al. (2003). Recent reviews of the literature on integrated water management at the basin level include Letcher et al. (2007) or Cai (2008). We present here an original framework for integrated water management at the river basin scale called MoGIRE ("Modèle pour la Gestion Intégrée de la Ressource en Eau"). It is intended to optimize water use at the river basin level and to evaluate scenarios (agronomic, climatic or economic) for a better planning of agricultural and non-agricultural water use. MoGIRE includes a nodal representation of the water network. Agricultural, urban and environmental water uses are also represented using mathematical programming and econometric approaches. The model then optimizes at each date (10 days step) the allocation of water across agricultural and urban water demands in order to maximize the social surplus derived from water consumption given the constraints imposed by the water network. An application of the model is proposed for the Neste system located in South-West of France. 67 regions competing for water allocation have been identified in the Neste system. Those regions are characterized by specific cropping systems, specific climate and soil characteristics and by their connections to the water network. The model, including the nodal representation of the water network, has been coded using the algebraic modeling language GAMS. We are currently analyzing the robustness of the approach through scenario testing. Keywords : Integrated water management, optimization-simulation model, agronomic-economic modeling, river basin.

Design of a ground-water-quality monitoring network for the Salinas River basin, California

USGS Publications Warehouse

Showalter, P.K.; Akers, J.P.; Swain, L.A.

1984-01-01

A regional ground-water quality monitoring network for the entire Salinas River drainage basin was designed to meet the needs of the California State Water Resources Control Board. The project included phase 1--identifying monitoring networks that exist in the region; phase 2--collecting information about the wells in each network; and phase 3--studying the factors--such as geology, land use, hydrology, and geohydrology--that influence the ground-water quality, and designing a regional network. This report is the major product of phase 3. Based on the authors ' understanding of the ground-water-quality monitoring system and input from local offices, an ideal network was designed. The proposed network includes 317 wells and 8 stream-gaging stations. Because limited funds are available to implement the monitoring network, the proposed network is designed to correspond to the ideal network insofar as practicable, and is composed mainly of 214 wells that are already being monitored by a local agency. In areas where network wells are not available, arrangements will be made to add wells to local networks. The data collected by this network will be used to assess the ground-water quality of the entire Salinas River drainage basin. After 2 years of data are collected, the network will be evaluated to test whether it is meeting the network objectives. Subsequent network evaluations will be done very 5 years. (USGS)

Exhumation Reconstruction of the Xiangcheng Area, SE Tibetan Plateau. Implication on the Evolution of the Yangtze River in the Cenozoic.

NASA Astrophysics Data System (ADS)

Gourbet, L.; Yang, R.; Fellin, M. G.; Gong, J.; Maden, C.

2016-12-01

Geodynamic processes associated with timing of river incision and river network reorganization on the Tibetan plateau margins remain controversial. In particular, hydrographic network modifications in SE Tibet have been interpreted as related with regional-scale uplift or fault motion. The paleocourse of the upper Yangtze river (Jinsha Sha) and the timing of the establishment of its modern course are highly debated, leading to conflicting models of the plateau evolution. For example, estimated ages for the formation of the Yangtze first bend (where the river shifts from flowing southward to northward) range from the Eocene to the Pliocene. River incision can be reconstructed using low-temperature thermochronometry. However, the lack of suitable rocks along the main riverbed of the Yangtze makes it challenging. To address this problem, we perform a local study of the Xiangcheng area, located in Sichuan, about 150 km upstream of the first bend and drained by tributaries of the upper Yangtze. We combine a tectono-geomorphic analysis to a reconstruction of exhumation rates using (U-Th-Sm)/He thermochronometry. The study area is characterized by the NW-SE trending, active left-lateral Xiangcheng fault, which is attested by crustal-depth seismic activity. Importantly, the courses of two tributaries of the Yangtze are deflected along the Xiangcheng fault, suggesting that the fault partly controls the evolution of the upper Yangtze course. Locally, the fault also exhibits triangular facets, suggesting normal motion probably related to the fault segmentation. Granite samples from the Xiangcheng pluton were collected along three altitudinal profiles and analyzed using zircon and apatite (U-Th-Sm)/He thermochronometry. We will discuss the results and their implications on exhumation and on the Yangtze river history during the Cenozoic.

Communicating River Level Data and Information to Stakeholders with Different Interests

NASA Astrophysics Data System (ADS)

Macleod, K.; Sripada, S.; Ioris, A.; Arts, K.; van der Wal, R.

2012-12-01

There is a need to increase the effectiveness of how river level data are communicated to a range of stakeholders with an interest in river level information to increase the use of data collected by regulatory agencies. Currently, river level data is provided to members of the public through a web site without any formal engagement with river users having taken place. In our research project called wikiRivers, we are working with the suppliers of river level data as well as the users of this data to explore and improve from the user perspective how river level data and information is made available online. We are focusing on the application of natural language generation technology to create textual summaries of river level data tailored for specific interest groups. These tailored textual summaries will be presented among other modes of information presentation (e.g. maps and visualizations) with the aim to increase communication effectiveness. Natural language generation involves developing computational models that use non-linguistic input data to produce natural language as their output. Acquiring accurate correct system knowledge for natural language generation is a key step in developing such an effective computer software system. In this paper we set out the needs for this project based on discussions with the stakeholder who supplies the river level data and current cyberinfrastructure and report on what we have learned from those individuals and groups who use river level data. Stages in the wikiRivers stakeholder identification, engagement and cyberinfrastructure development. S1- interviews with collectors and suppliers of river level data. S2- river level data stakeholder analysis, including analysis of their interests in individual river networks in Scotland and what they require from the cyberinfrastructure. S3-5 Iterative development and testing of cyberinfrastructure and modelling of river level data with domain and stakeholder knowledge.

Pesticides in the Lake Kinneret basin: a combined approach towards mircopollutant management

NASA Astrophysics Data System (ADS)

Gaßmann, M.; Friedler, E.; Dubwoski, Y.; Dinerman, E.; Olsson, O.; Bauer, M.

2009-04-01

Lake Kinneret is the only large surface waterbody in Israel, supplying about 27% of the country's freshwater. Water quality in Lake Kinneret is of major concern and improving the ecological status of this large water body is now a national priority. While many studies in the past focused on nutrients inflows and phytoplankton dynamics, less research has been done on assessing the fate and pathways of micropollutants at semi-arid environments in common and Lake Kinneret in particular. Since the watershed area of Lake Kinneret is used primarily for agriculture, it is important to evaluate the fate and dynamic transfer of organic micropollutants such as pesticides and herbicides in the watershed streams and in the lake itself. This study introduces a combined concept of extensive measurements and modelling tools to observe and simulate the pesticide release chain (i) application - (ii) diffuse release to rivers - (iii) transport in the river - (iv) accumulation in the lake. The available information regarding identification of application zones (i) and the amounts of used pesticides is based on stakeholders interviews, a survey of the different crop types and orchards and a comparison to sold amounts of the target pesticides (Melman and Bar-Ilan 2008). In the current research, a single field mass balance of pesticides is carried out to determine the field release to rivers (ii) by an extensive measurement campaign on the different compartments (soil, vegetation, atmosphere) and phases (water, air, solids) of a single field. The mass balance results in a release pattern of pesticide, which will be overtaken into the modelling approach. Transport of pesticides in rivers (iii) is modelled on the base of a recently developed stream network model for ephemeral streams (MOHID River), introducing important instream fate processes of pesticides and supported by six instream measurement stations of hydrological as well as pesticide data in the basin. To determine the final concentration of the pesticides in Lake Kinneret (iv) and therefore the drinking water reservoir, a lake model is fed by the stream network model outputs. However, the most difficult part of the current risk management approach of water resources in the upper Jordan River basin is to produce reliable field data on the environmental fate of pesticides and to evaluate their impact on the local water supply. The introduced combined approach aims at providing useful information and arguments for the decision making process and supporting water managers in revision of management strategies and planning of new infrastructure projects.

Estimating Nitrogen Loading in the Wabash River Subwatershed Using a GIS Schematic Processing Network in Support of Sustainable Watershed Management Planning

EPA Science Inventory

The Wabash River is a tributary of the Ohio River. This river system consists of headwaters and small streams, medium river reaches in the upper Wabash watershed, and large river reaches in the lower Wabash watershed. A large part of the river system is situated in agricultural a...

IN-STREAM AND WATERSHED PREDICTORS OF GENETIC DIVERSITY, EFFECTIVE POPULATION SIZE AND IMMIGRATION ACROSS RIVER-STREAM NETWORKS

EPA Science Inventory

The influence of spatial processes on population dynamics within river-stream networks is poorly understood. Utilizing spatially explicit analyses of temporal genetic variance, we examined whether persistence of Central Stonerollers (Campostoma anomalum) reflects differences in h...

A hybrid model to assess the impact of climate variability on streamflow for an ungauged mountainous basin

NASA Astrophysics Data System (ADS)

Wang, Chong; Xu, Jianhua; Chen, Yaning; Bai, Ling; Chen, Zhongsheng

2018-04-01

To quantitatively assess the impact of climate variability on streamflow in an ungauged mountainous basin is a difficult and challenging work. In this study, a hybrid model combing downscaling method based on earth data products, back propagation artificial neural networks (BPANN) and weights connection method was developed to explore an approach for solving this problem. To validate the applicability of the hybrid model, the Kumarik River and Toshkan River, two headwaters of the Aksu River, were employed to assess the impact of climate variability on streamflow by using this hybrid model. The conclusion is that the hybrid model presented a good performance, and the quantitative assessment results for the two headwaters are: (1) the precipitation respectively increased by 48.5 and 41.0 mm in the Kumarik catchment and Toshkan catchment, and the average annual temperature both increased by 0.1 °C in the two catchments during each decade from 1980 to 2012; (2) with the warming and wetting climate, the streamflow respectively increased 1.5 × 108 and 3.3 × 108 m3 per decade in the Kumarik River and the Toshkan River; and (3) the contribution of the temperature and precipitation to the streamflow, which were 64.01 ± 7.34, 35.99 ± 7.34 and 47.72 ± 8.10, 52.26 ± 8.10%, respectively in the Kumarik catchment and Toshkan catchment. Our study introduced a feasible hybrid model for the assessment of the impact of climate variability on streamflow, which can be used in the ungauged mountainous basin of Northwest China.

Carbon fate in a large temperate human-impacted river system: Focus on benthic dynamics

NASA Astrophysics Data System (ADS)

Vilmin, Lauriane; Flipo, Nicolas; Escoffier, Nicolas; Rocher, Vincent; Groleau, Alexis

2016-07-01

Fluvial networks play an important role in regional and global carbon (C) budgets. The Seine River, from the Paris urban area to the entrance of its estuary (220 km), is studied here as an example of a large human-impacted river system subject to temperate climatic conditions. We assess organic C (OC) budgets upstream and downstream from one of the world's largest wastewater treatment plants and for different hydrological conditions using a hydrobiogeochemical model. The fine representation of sediment accumulation on the river bed allows for the quantification of pelagic and benthic effects on OC export toward the estuary and on river metabolism (i.e., net CO2 production). OC export is significantly affected by benthic dynamics during the driest periods, when 25% of the inputs to the system is transformed or stored in the sediment layer. Benthic processes also substantially affect river metabolism under any hydrological condition. On average, benthic respiration accounts for one third of the total river respiration along the studied stretch (0.27 out of 0.86 g C m-2 d-1). Even though the importance of benthic processes was already acknowledged by the scientific community for headwater streams, these results stress the major influence of benthic dynamics, and thus of physical processes such as sedimentation and resuspension, on C cycling in downstream river systems. It opens the door to new developments in the quantification of C emissions by global models, whereby biogeochemical processing and benthic dynamics should be taken into account.

One-dimensional and two-dimensional hydrodynamic modelling derived flow properties: Impacts on aquatic habitat quality predictions

Treesearch

Rohan Benjankar; Daniele Tonina; James McKean

2014-01-01

Studies of the effects of hydrodynamic model dimensionality on simulated flow properties and derived quantities such as aquatic habitat quality are limited. It is important to close this knowledge gap especially now that entire river networks can be mapped at the microhabitat scale due to the advent of point-cloud techniques. This study compares flow properties, such...

SWANN: The Snow Water Artificial Neural Network Modelling System

NASA Astrophysics Data System (ADS)

Broxton, P. D.; van Leeuwen, W.; Biederman, J. A.

2017-12-01

Snowmelt from mountain forests is important for water supply and ecosystem health. Along Arizona's Mogollon Rim, snowmelt contributes to rivers and streams that provide a significant water supply for hydro-electric power generation, agriculture, and human consumption in central Arizona. In this project, we are building a snow monitoring system for the Salt River Project (SRP), which supplies water and power to millions of customers in the Phoenix metropolitan area. We are using process-based hydrological models and artificial neural networks (ANNs) to generate information about both snow water equivalent (SWE) and snow cover. The snow-cover data is generated with ANNs that are applied to Landsat and MODIS satellite reflectance data. The SWE data is generated using a combination of gridded SWE estimates generated by process-based snow models and ANNs that account for variations in topography, forest cover, and solar radiation. The models are trained and evaluated with snow data from SNOTEL stations as well as from aerial LiDAR and field data that we collected this past winter in northern Arizona, as well as with similar data from other sites in the Southwest US. These snow data are produced in near-real time, and we have built a prototype decision support tool to deliver them to SRP. This tool is designed to provide daily-to annual operational monitoring of spatial and temporal changes in SWE and snow cover conditions over the entire Salt River Watershed (covering 17,000 km2), and features advanced web mapping capabilities and watershed analytics displayed as graphical data.

Improving Shade Modelling in a Regional River Temperature Model Using Fine-Scale LIDAR Data

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Loicq, P.; Moatar, F.; Beaufort, A.; Melin, E.; Jullian, Y.

2015-12-01

Air temperature is often considered as a proxy of the stream temperature to model the distribution areas of aquatic species water temperature is not available at a regional scale. To simulate the water temperature at a regional scale (105 km²), a physically-based model using the equilibrium temperature concept and including upstream-downstream propagation of the thermal signal was developed and applied to the entire Loire basin (Beaufort et al., submitted). This model, called T-NET (Temperature-NETwork) is based on a hydrographical network topology. Computations are made hourly on 52,000 reaches which average 1.7 km long in the Loire drainage basin. The model gives a median Root Mean Square Error of 1.8°C at hourly time step on the basis of 128 water temperature stations (2008-2012). In that version of the model, tree shadings is modelled by a constant factor proportional to the vegetation cover on 10 meters sides the river reaches. According to sensitivity analysis, improving the shade representation would enhance T-NET accuracy, especially for the maximum daily temperatures, which are currently not very well modelized. This study evaluates the most efficient way (accuracy/computing time) to improve the shade model thanks to 1-m resolution LIDAR data available on tributary of the LoireRiver (317 km long and an area of 8280 km²). Two methods are tested and compared: the first one is a spatially explicit computation of the cast shadow for every LIDAR pixel. The second is based on averaged vegetation cover characteristics of buffers and reaches of variable size. Validation of the water temperature model is made against 4 temperature sensors well spread along the stream, as well as two airborne thermal infrared imageries acquired in summer 2014 and winter 2015 over a 80 km reach. The poster will present the optimal length- and crosswise scale to characterize the vegetation from LIDAR data.

Coupling a basin erosion and river sediment transport model into a large scale hydrological model: an application in the Amazon basin

NASA Astrophysics Data System (ADS)

Buarque, D. C.; Collischonn, W.; Paiva, R. C. D.

2012-04-01

This study presents the first application and preliminary results of the large scale hydrodynamic/hydrological model MGB-IPH with a new module to predict the spatial distribution of the basin erosion and river sediment transport in a daily time step. The MGB-IPH is a large-scale, distributed and process based hydrological model that uses a catchment based discretization and the Hydrological Response Units (HRU) approach. It uses physical based equations to simulate the hydrological processes, such as the Penman Monteith model for evapotranspiration, and uses the Muskingum Cunge approach and a full 1D hydrodynamic model for river routing; including backwater effects and seasonal flooding. The sediment module of the MGB-IPH model is divided into two components: 1) prediction of erosion over the basin and sediment yield to river network; 2) sediment transport along the river channels. Both MGB-IPH and the sediment module use GIS tools to display relevant maps and to extract parameters from SRTM DEM (a 15" resolution was adopted). Using the catchment discretization the sediment module applies the Modified Universal Soil Loss Equation to predict soil loss from each HRU considering three sediment classes defined according to the soil texture: sand, silt and clay. The effects of topography on soil erosion are estimated by a two-dimensional slope length (LS) factor which using the contributing area approach and a local slope steepness (S), both estimated for each DEM pixel using GIS algorithms. The amount of sediment releasing to the catchment river reach in each day is calculated using a linear reservoir. Once the sediment reaches the river they are transported into the river channel using an advection equation for silt and clay and a sediment continuity equation for sand. A sediment balance based on the Yang sediment transport capacity, allowing to compute the amount of erosion and deposition along the rivers, is performed for sand particles as bed load, whilst no erosion or deposition is allowed for silt and clay. The model was first applied on the Madeira River basin, one of the major tributaries of the Amazon River (~1.4*106 km2) accounting for 35% of the suspended sediment amount annually transported for the Amazon river to the ocean. Model results agree with observed data, mainly for monthly and annual time scales. The spatial distribution of soil erosion within the basin showed a large amount of sediment being delivered from the Andean regions of Bolivia and Peru. Spatial distribution of mean annual sediment along the river showed that Madre de Dios, Mamoré and Beni rivers transport the major amount of sediment. Simulated daily suspended solid discharge agree with observed data. The model is able to provide temporaly and spatialy distributed estimates of soil loss source over the basin, locations with tendency for erosion or deposition along the rivers, and to reproduce long term sediment yield at several locations. Despite model results are encouraging, further effort is needed to validate the model considering the scarcity of data at large scale.

Seasonal Dynamics of River Corridor Exchange Across the Continental United States

NASA Astrophysics Data System (ADS)

Gomez-Velez, J. D.; Harvey, J. W.; Scott, D.; Boyer, E. W.; Schmadel, N. M.

2017-12-01

River corridors store and convey mass and energy from landscapes to the ocean, altering water quality and ecosystem functioning at the local, reach, and watershed scales. As water moves through river corridors from headwaters streams to coastal estuaries, dynamic exchange between the river channel and its adjacent riparian, floodplain, and hyporheic zones, combined with ponded waters such as lakes and reservoirs, results in the emergence of hot spots and moments for biogeochemical transformations. In this work, we used the model Networks with EXchange and Subsurface Storage (NEXSS) to estimate seasonal variations in river corridor exchange fluxes and residence times along the continental United States. Using a simple routing scheme, we translate these estimates into a cumulative measure of river corridor connectivity at the watershed scale, differentiating the contributions of hyporheic zones, floodplains, and ponded waters. We find that the relative role of these exchange subsystems changes seasonally, driven by the intra-seasonal variability of discharge. In addition, we find that seasonal variations in discharge and the biogeochemical potential of hyporheic zones are out of phase. This behavior results in a significant reduction in hyporheic water quality functions during high flows and emphasizes the potential importance of reconnecting floodplains for managing water quality during seasonal high flows. Physical parameterizations of river corridor processes are critical to model and predict water quality and to sustainably manage water resources under present and future socio-economic and climatic conditions. Parsimonious models like NEXSS can play a key role in the design, implementation, and evaluation of sustainable management practices that target both water quantity and quality at the scale of the nation. This research is a product of the John Wesley Powell Center River Corridor Working Group.

Hydrological and Climate Controls on Hyporheic Contributions to River Net Ecosystem Productivity

NASA Astrophysics Data System (ADS)

Newcomer, M. E.; Hubbard, S. S.; Fleckenstein, J. H.; Maier, U.; Schmidt, C.; Laube, G.; Chen, N.; Ulrich, C.; Dwivedi, D.; Steefel, C. I.; Rubin, Y.

2016-12-01

Hyporheic zone contributions to river net ecosystem productivity (NEP) can represent a substantial source or sink for organic and inorganic carbon (C). Hyporheic zone processes are estimated to vary with network location as a function of river-aquifer interactions as well as with climatic factors supporting riverbed gross primary productivity (GPP) and ecosystem respiration. Even though hyporheic zone NEP is hypothesized to be a significant budgetary component to river-aquifer biogeochemical cycling, models of river NEP often parameterize hyporheic zone contributions as a space-time constant input of CO2 to rivers, leading to overestimation of hyporheic zone NEP and underestimation of C storage. This assumption is problematic during the summer growing season, when GPP is largest and C is stored in surface and subsurface biomass. We investigated the dynamic role of hyporheic zone NEP using the MIN3P flow and reactive transport model with surface water GPP and ecosystem respiration simulated as a function of light, depth, temperature, pH, and atmospheric CO2. We simulated hyporheic zone NEP for low-order and high-order streams, which collectively represent a range of characteristic flow paths and subsurface residence times. Downscaled climate predictions of temperature and atmospheric CO2 representing carbon emission futures were used to force the models and to compare future and current hyporheic zone NEP. Our results show that river-aquifer flow conditions determine the relative role of the river as either a store or sink of C through direct contributions of O2 and dissolved organic content from river GPP. Modeled results show that high discharge, high order rivers are net stores of CO2 from the atmosphere; however this is dependent on perturbation events that allow stored C from summer GPP to be released (i.e. rising water tables during winter storms). Lacking a perturbation event, C remains in pore-water storage as dissolved CO2 and biomass. Conversely, low-discharge mountainous streams with continuous hyporheic zone flow represent a net source of CO2, with future temperature rises stimulating additional heterotrophic activity. Our work contributes to a better understanding of how river and hyporheic zone processes significantly influence biogeochemical cycling under changing climate conditions.

Student Experiments on the Effects of Dam Removal on the Elwha River

NASA Astrophysics Data System (ADS)

Sandland, T. O.; Grack Nelson, A. L.

2006-12-01

The National Center for Earth Surface Dynamics (NCED) is an NSF funded Science and Technology Center devoted to developing a quantitative, predictive science of the ecological and physical processes that define and shape rivers and river networks. The Science Museum of Minnesota's (SMM) Earthscapes River Restoration classes provide k-12 students, teachers, and the public opportunities to explore NCED concepts and, like NCED scientists, move from a qualitative to a quantitative-based understanding of river systems. During a series of classes, students work with an experimental model of the Elwha River in Washington State to gain an understanding of the processes that define and shape river systems. Currently, two large dams on the Elwha are scheduled for removal to restore salmon habitat. Students design different dam removal scenarios to test and make qualitative observations describing and comparing how the modeled system evolves over time. In a following session, after discussing the ambiguity of the previous session's qualitative data, student research teams conduct a quantitative experiment to collect detailed measurements of the system. Finally, students interpret, critique, and compare the data the groups collected and ultimately develop and advocate a recommendation for the "ideal" dam removal scenario. SMM is currently conducting a formative evaluation of River Restoration classes to improve their educational effectiveness and guide development of an educator's manual. As of August 2006, pre- and post-surveys have been administered to 167 students to gauge student learning and engagement. The surveys have found the program successful in teaching students why scientists use river models and what processes and phenomena are at work in river systems. Most notable is the increase in student awareness of sediment in river systems. A post-visit survey was also administered to 20 teachers who used the models in their classrooms. This survey provided feedback about teachers' experience with the program and will help inform the development of a future educator's manual. All teachers found the program to be effective at providing opportunities for students to make qualitative observations and most (95%) found the program effective at providing students opportunities to make quantitative measurements. A full summary of evaluation results will be shared at the meeting.

Effects of slope smoothing in river channel modeling

NASA Astrophysics Data System (ADS)

Kim, Kyungmin; Liu, Frank; Hodges, Ben R.

2017-04-01

In extending dynamic river modeling with the 1D Saint-Venant equations from a single reach to a large watershed there are critical questions as to how much bathymetric knowledge is necessary and how it should be represented parsimoniously. The ideal model will include the detail necessary to provide realism, but not include extraneous detail that should not exert a control on a 1D (cross-section averaged) solution. In a Saint-Venant model, the overall complexity of the river channel morphometry is typically abstracted into metrics for the channel slope, cross-sectional area, hydraulic radius, and roughness. In stream segments where cross-section surveys are closely spaced, it is not uncommon to have sharp changes in slope or even negative values (where a positive slope is the downstream direction). However, solving river flow with the Saint-Venant equations requires a degree of smoothness in the equation parameters or the equation set with the directly measured channel slopes may not be Lipschitz continuous. The results of non-smoothness are typically extended computational time to converge solutions (or complete failure to converge) and/or numerical instabilities under transient conditions. We have investigated using cubic splines to smooth the bottom slope and ensure always positive reference slopes within a 1D model. This method has been implemented in the Simulation Program for River Networks (SPRNT) and is compared to the standard HEC-RAS river solver. It is shown that the reformulation of the reference slope is both in keeping with the underlying derivation of the Saint-Venant equations and provides practical numerical stability without altering the realism of the simulation. This research was supported in part by the National Science Foundation under grant number CCF-1331610.

Nutrient delivery to Lake Winnipeg from the Red-Assiniboine River Basin – A binational application of the SPARROW model

USGS Publications Warehouse

Benoy, Glenn A.; Jenkinson, R. Wayne; Robertson, Dale M.; Saad, David A.

2016-01-01

Excessive phosphorus (TP) and nitrogen (TN) inputs from the Red–Assiniboine River Basin (RARB) have been linked to eutrophication of Lake Winnipeg; therefore, it is important for the management of water resources to understand where and from what sources these nutrients originate. The RARB straddles the Canada–United States border and includes portions of two provinces and three states. This study represents the first binationally focused application of SPAtially Referenced Regressions on Watershed attributes (SPARROW) models to estimate loads and sources of TP and TN by jurisdiction and basin at multiple spatial scales. Major hurdles overcome to develop these models included: (1) harmonization of geospatial data sets, particularly construction of a contiguous stream network; and (2) use of novel calibration steps to accommodate limitations in spatial variability across the model extent and in the number of calibration sites. Using nutrient inputs for a 2002 base year, a RARB TP SPARROW model was calibrated that included inputs from agriculture, forests and wetlands, wastewater treatment plants (WWTPs) and stream channels, and a TN model was calibrated that included inputs from agriculture, WWTPs and atmospheric deposition. At the RARB outlet, downstream from Winnipeg, Manitoba, the majority of the delivered TP and TN came from the Red River Basin (90%), followed by the Upper Assiniboine River and Souris River basins. Agriculture was the single most important TP and TN source for each major basin, province and state. In general, stream channels (historically deposited nutrients and from bank erosion) were the second most important source of TP. Performance metrics for the RARB SPARROW model are similarly robust compared to other, larger US SPARROW models making it a potentially useful tool to address questions of where nutrients originate and their relative contributions to loads delivered to Lake Winnipeg.

Numerical representation of rainfall field in the Yarmouk River Basin

NASA Astrophysics Data System (ADS)

Shentsis, Isabella; Inbar, Nimrod; Magri, Fabien; Rosenthal, Eliyahu

2017-04-01

Rainfall is the decisive factors in evaluating the water balance of river basins and aquifers. Accepted methods rely on interpolation and extrapolation of gauged rain to regular grid with high dependence on the density and regularity of network, considering the relief complexity. We propose an alternative method that makes up to those restrictions by taking into account additional physical features of the rain field. The method applies to areas with (i) complex plain- and mountainous topography, which means inhomogeneity of the rainfall field and (ii) non-uniform distribution of a rain gauge network with partial lack of observations. The rain model is implemented in two steps: 1. Study of the rainfall field, based on the climatic data (mean annual precipitation), its description by the function of elevation and other factors, and estimation of model parameters (normalized coefficients of the Taylor series); 2. Estimation of rainfall in each historical year using the available data (less complete and irregular versus climatic data) as well as the a-priori known parameters (by the basic hypothesis on inter-annual stability of the model parameters). The proposed method was developed by Shentsis (1990) for hydrological forecasting in Central Asia and was later adapted to the Lake Kinneret Basin. Here this model (the first step) is applied to the Yarmouk River Basin. The Yarmouk River is the largest tributary of the Jordan River. Its transboundary basin (6,833 sq. km) extends over Syria (5,257 sq.km), Jordan (1,379 sq. km) and Israel (197 sq. km). Altitude varies from 1800 m (and more) to -235 m asl. The total number of rain stations in use is 36 (17 in Syria, 19 in Jordan). There is evidently lack and non-uniform distribution of a rain gauge network in Syria. The Yarmouk Basin was divided into five regions considering typical relationship between mean annual rain and elevation for each region. Generally, the borders of regions correspond to the common topographic, geomorphologic and climatic division of the basin. Difference between regional curves is comparable with amplitude of rainfall variance within the regions. In general, rainfall increases with altitude and decreases from west to east (south-east). It should be emphasized that (i) Lake Kinneret Basin (2,490 sq. km) was earlier divided into seven "orographic regions" and (ii) the Lake Kinneret Basin and the Yarmouk River Basin are presented by the system of regional curves X = f (Z) as one whole rainfall field in the Upper Jordan River Basin, where the mean annual rain (X) increases with altitude (Z) and decreases from west to east and from north to south. In the Yarmouk Basin there is much less rainfall (344 mm) than in the Lake Kinneret Basin (749 mm), wherein mean annual rain (2,352 MCM versus 1,865 MCM) is shared between Syria, Jordan and Israel as 80%, 15% and 5%, respectively. The provided rainfall data allow more precise estimations of surface water balances and of recharge to the regional aquifers in the Upper Jordan River Basin. The derived rates serve as fundamental input data for numerical modeling of groundwater flow. This method can be applied to other areas at different temporal and spatial scales. The general applicability makes it a very useful tool in several hydrological problems connected with assessment, management and policy-making of water resources, as well as their changes due to climate and anthropogenic factors. Reference: I. Shentsis (1990). Mathematical models for long-term prediction of mountainous river runoff: methods, information and results, Hydrological Sciences Journal, 35:5, 487-500, DOI: 10.1080/02626669009492453

Role of Unchannelized Flow in Determining Bifurcation Angle in Distributary Channel Networks

NASA Astrophysics Data System (ADS)

Coffey, T.

2016-02-01

Distributary channel bifurcations on river deltas are important features in both actively prograding river deltas and in lithified deltas within the stratigraphic record. Attributes of distributary channels have long been thought to be defined by flow velocity, grain size and channel aspect ratio where the channel enters the basin. Interestingly, bifurcations in groundwater-fed tributary networks have been shown to grow and bifurcate independent of flow within the exposed channel network. These networks possess a characteristic bifurcation angle of 72°, based on Laplacian flow (water surface concavity equals zero) in the groundwater flow field near tributary channel tips. Based on the tributary channel model, we develop and test the hypothesis that bifurcation angles in distributary channels are likewise dictated by the external flow field, in this case the surface water surrounding the subaqueous portion of distributary channel tips in a deltaic setting. We measured 64 unique distributary bifurcations in an experimental delta, yielding a characteristic angle of 70.2°±2.2° (95% confidence interval), in line with the theoretical prediction for tributary channels. This similarity between bifurcation angles suggests that (A) flow directly outside of the distributary network is Laplacian, (B) the external flow field controls the bifurcation dynamics of distributary channels, and (C) that flow within the channel plays a secondary role in network dynamics.

Uncertainties in simulating river/groundwater exchanges over the Upper Rhine Graben hydrosystem

NASA Astrophysics Data System (ADS)

Vergnes, Jean-Pierre; Habets, Florence

2014-05-01

The Upper Rhine alluvial aquifer is an important transboundary water resource which is particularly vulnerable to pollution from the rivers due to anthropogenic activities. A realistic simulation of the groundwater-river exchanges is therefore of crucial importance for an effective management of water resources. Characterization of these fluxes in term of quantity and spatio-temporal variability depends on choices made to represent the river water stage in the model as well as on the hydrogeological parameters. Recently, a coupled surface-subsurface model has been applied to the whole aquifer basin (Thierion et al., 2012). The present study aims at improving the estimation of the river/groundwater exchange, and thus, of the hydrodynamic of the alluvial aquifer, and at getting an idea of the associated uncertainty by performing a set of simulations that best take advantage of the different kinds of observed data. The general modeling strategy is based on the Eau-Dyssée modeling platform which couples existing specialized models to address water resources quantity and quality in small to regional scale river basins. In this study, Eau-Dyssée includes the ISBA surface scheme that estimates the water balance, the RAPID river routing model and the SAM hydrogeological model. In addition, the QtoZ module (Saleh et al., 2011) is used to calculate the river stage from simulated river discharges, which is then used to calculate the exchanges between aquifer units and river, according to three different approaches that are compared: a control experiment with constant river water stage, a rating curves approach derived from observed river discharges and river stages, and the Manning's formula, for which Manning's parameters are defined according to geomorphological parameterizations and topographic data based on Digital Elevation Model (DEM). Supplementary sensitivity tests are also performed by using different hydrogeological parameter datasets (porosity and transmissivity). Two sources of DEM were used for this part. Additionally, sensitivity to the time step of the estimation (daily versus monthly) was studied. The evaluation is made against observed water levels and river discharges collected both from the french and german riversides of the alluvial plain. A heavy network of water table depth observations is also available to evaluate the simulated piezometric heads. Preliminary results show that the primary source of errors when simulating river stage - and hence groundwater-river interactions - is the uncertainties associated with the topographic data used to define the riverbed elevation. It confirms the need to access to more accurate DEM for estimating riverbed elevation and studying groundwater-river interactions, at least at regional scale. References Saleh, F., Flipo, N., Habets, F., Ducharne, A., Oudin, L., Viennot, P., Ledoux, E. Modeling the impact of in-stream water level fluctuations on stream-aquifer interactions at the regional scale (2011)Journal of Hydrology, 400 (3-4) pp 490-500 Thierion C., Longuevergne L., Habets F. Ledoux E., Ackerer P., Majdalani S., Leblois E., Lecluse S., Martin E, Queguiner S., Viennot P., Assessing the water balance of the Upper Rhine Graben hydrosystem, Journal of Hydrology 424-425 , pp. 68-83

ARPA LOMBARDIA river gauging network: a great daily effort

NASA Astrophysics Data System (ADS)

Cislaghi, Matteo; Calabrese, Michele; Condemi, Leonardo; Di Priolo, Sara; Parravicini, Paola; Rondanini, Chiara; Russo, Michele; Cazzuli, Orietta; Mussin, Mauro; Serra, Roberto

2017-04-01

ARPA Lombardia is the Environmental Protection Agency of Lombardy, a wide region in northern Italy. ARPA is in charge of river monitoring either for Civil Protection or water balance purposes. Lombardy is characterized by a very complex territory; rivers start from the alpine areas and end in the Po river plain. Each mountain or plain area has specific hydrological features that has to be considered when planning a monitoring network. Moreover, human activities (such as lake regulation, agriculture diversions, hydropower plants with regulation structure etc) add anthropic interferences on the natural river system and can invalidate the collected data. In the last 10 years ARPA performed a major revision of the river gauging network. Each station was analysed using well defined criteria based on the required information (water balance or flood monitoring) and on the suitability of the gauging site (hydraulic characteristic or accessibility for spot measures). In the end more than 30% of the network was revised, many stations were closed and other installed. Particular attention was given to the discharge estimation. Many sites are characterized by backflow effect due to river confluences or to hydropower plants with water regulation structures. In these cases the classic rating curve approach can not be applied. Thus, for the first time in Italy, water velocity side looking doppler sensors were installed on natural rivers and the discharge is estimated with the index velocity method. The Italian Civil Protection Agency requires high transmission standards. No data can be lost for transmission failures and data has to be available every 30 minutes. For these reasons ARPA implemented a double transmission system: the first is based on the existing GPRS network managed by private operators, the second is based on a radio network directly installed by ARPA and totally dedicated to data transmission. This double approach ensures a very robust transmission and it allows ARPA to collect and publish data every 10 minutes. ARPA also decided to freely publish all hydrological data on its web site (http://idro.arpalombardia.it). Since 2010 either real time data or historical long series have been made available to everyone over a webgis platform. Every day ARPA employs check if the network is working correctly and validate the data. The aim is to follow the whole process of data management from its collection on the field to its open publication; this requires a great daily effort from the people in charge of the network maintenance.

Path selection in the growth of rivers

DOE PAGES

Cohen, Yossi; Devauchelle, Olivier; Seybold, Hansjörg F.; ...

2015-11-02

River networks exhibit a complex ramified structure that has inspired decades of studies. But, an understanding of the propagation of a single stream remains elusive. In this paper, we invoke a criterion for path selection from fracture mechanics and apply it to the growth of streams in a diffusion field. We show that, as it cuts through the landscape, a stream maintains a symmetric groundwater flow around its tip. The local flow conditions therefore determine the growth of the drainage network. We use this principle to reconstruct the history of a network and to find a growth law associated withmore » it. Finally, our results show that the deterministic growth of a single channel based on its local environment can be used to characterize the structure of river networks.« less

Demonstrating the value of community-based ('citizen science') observations for catchment modelling and characterisation

NASA Astrophysics Data System (ADS)

Starkey, Eleanor; Parkin, Geoff; Birkinshaw, Stephen; Large, Andy; Quinn, Paul; Gibson, Ceri

2017-05-01

Despite there being well-established meteorological and hydrometric monitoring networks in the UK, many smaller catchments remain ungauged. This leaves a challenge for characterisation, modelling, forecasting and management activities. Here we demonstrate the value of community-based ('citizen science') observations for modelling and understanding catchment response as a contribution to catchment science. The scheme implemented within the 42 km2 Haltwhistle Burn catchment, a tributary of the River Tyne in northeast England, has harvested and used quantitative and qualitative observations from the public in a novel way to effectively capture spatial and temporal river response. Community-based rainfall, river level and flood observations have been successfully collected and quality-checked, and used to build and run a physically-based, spatially-distributed catchment model, SHETRAN. Model performance using different combinations of observations is tested against traditionally-derived hydrographs. Our results show how the local network of community-based observations alongside traditional sources of hydro-information supports characterisation of catchment response more accurately than using traditional observations alone over both spatial and temporal scales. We demonstrate that these community-derived datasets are most valuable during local flash flood events, particularly towards peak discharge. This information is often missed or poorly represented by ground-based gauges, or significantly underestimated by rainfall radar, as this study clearly demonstrates. While community-based observations are less valuable during prolonged and widespread floods, or over longer hydrological periods of interest, they can still ground-truth existing traditional sources of catchment data to increase confidence during characterisation and management activities. Involvement of the public in data collection activities also encourages wider community engagement, and provides important information for catchment management.

A River Runs Under It: Modeling the Distribution of Streams and Stream Burial in Large River Basins

NASA Astrophysics Data System (ADS)

Elmore, A. J.; Julian, J.; Guinn, S.; Weitzell, R.; Fitzpatrick, M.

2011-12-01

Stream network density exerts a strong control on hydrologic processes in watersheds. Over land and through soil and bedrock substrate, water moves slowly and is subject to chemical transformations unique to conditions of continuous contact with geologic materials. In contrast, once water enters stream channels it is efficiently transported out of watersheds, reducing the amount of time for biological uptake and stream nutrient processing. Therefore, stream network density dictates both the relative importance of terrestrial and aquatic influences to stream chemistry and the residence time of water in watersheds, and is critical to modeling and empirical studies aimed at understanding the impact of land use on stream water quantity and quality. Stream network density is largely a function of the number and length of the smallest streams. Methods for mapping and measuring these headwater streams range from simple measurement of stream length from existing maps, to detailed field mapping efforts, which are difficult to implement over large areas. Confounding the simplest approaches, many headwater stream reaches are not included in hydrographical maps, such as the U.S. National Hydrography Dataset (NHD), either because they were buried during the course of urban development or because they were seen as smaller than the minimum mapping size at the time of map generation. These "missing streams" severely limit the effective analyses of stream network density based on the NHD, constituting a major problem for many efforts to understand land-use impacts on streams. Here we report on research that predicts stream presence and absence by coupling field observations of headwater stream channels with maximum entropy models (MaxEnt) commonly implemented in biogeographical studies to model species distributions. The model utilizes terrain variables that are continuously accumulated along hydrologic flowpaths derived from a 10-m digital elevation model. In validation, the model correctly predicts the presence of 91% of all 10-m stream segments, and rarely miscalculates tributary numbers. We apply this model to the entire Potomac River Basin (37,800 km2) and several adjacent basins to map stream channel density and compare our results with NHD flowline data. We find that NHD underestimates stream channel density by a factor of two in most sub watersheds and this effect is strongest in the densely urbanized cities of Washington, DC and Baltimore, MD. We then apply a second predictive model based on impervious surface area data to map the extent of stream burial. Results demonstrate that the extent of stream burial increases with decreasing stream catchment area. When applied at four time steps (1975, 1990, 2001, and 2006), we find that although stream burial rates have slowed in the recent decade, streams that are not mapped in NHD flowline data continue to be buried during development. This work is the most ambitious attempt yet to map stream network density over a large region and will have lasting implications for modeling and conservation efforts.

River discharge estimation from synthetic SWOT-type observations using variational data assimilation and the full Saint-Venant hydraulic model

NASA Astrophysics Data System (ADS)

Oubanas, Hind; Gejadze, Igor; Malaterre, Pierre-Olivier; Mercier, Franck

2018-04-01

The upcoming Surface Water and Ocean Topography satellite mission, to be launched in 2021, will measure river water surface elevation, slope and width, with an unprecedented level of accuracy for a remote sensing tool. This work investigates the river discharge estimation from synthetic SWOT observations, in the presence of strong uncertainties in the model inputs, i.e. the river bathymetry and bed roughness. The estimation problem is solved by a novel variant of the standard variational data assimilation, the '4D-Var' method, involving the full Saint-Venant 1.5D-network hydraulic model SIC2. The assimilation scheme simultaneously estimates the discharge, bed elevation and bed roughness coefficient and is designed to assimilate both satellite and in situ measurements. The method is tested on a 50 km-long reach of the Garonne River during a five-month period of the year 2010, characterized by multiple flooding events. First, the impact of the sampling frequency on discharge estimation is investigated. Secondly, discharge as well as the spatially distributed bed elevation and bed roughness coefficient are determined simultaneously. Results demonstrate feasibility and efficiency of the chosen combination of the estimation method and of the hydraulic model. Assimilation of the SWOT data results into an accurate estimation of the discharge at observation times, and a local improvement in the bed level and bed roughness coefficient. However, the latter estimates are not generally usable for different independent experiments.

Carbon dioxide and methane dynamics in a human-dominated lowland coastal river network (Shanghai, China)

NASA Astrophysics Data System (ADS)

Yu, Zhongjie; Wang, Dongqi; Li, Yangjie; Deng, Huanguang; Hu, Beibei; Ye, Mingwu; Zhou, Xuhui; Da, Liangjun; Chen, Zhenlou; Xu, Shiyuan

2017-07-01

Evasion of carbon dioxide (CO2) and methane (CH4) in streams and rivers play a critical role in global carbon (C) cycle, offsetting the C uptake by terrestrial ecosystems. However, little is known about CO2 and CH4 dynamics in lowland coastal rivers profoundly modified by anthropogenic perturbations. Here we report results from a long-term, large-scale study of CO2 and CH4 partial pressures (pCO2 and pCH4) and evasion rates in the Shanghai river network. The spatiotemporal variabilities of pCO2 and pCH4 were examined along a land use gradient, and the annual CO2 and CH4 evasion were estimated to assess its role in regional C budget. During the study period (August 2009 to October 2011), the overall mean pCO2 and median pCH4 from 87 surveyed rivers were 5846 ± 2773 μatm and 241 μatm, respectively. Internal metabolic CO2 production and dissolved inorganic carbon input via upstream runoff were the major sources sustaining the widespread CO2 supersaturation, coupling pCO2 to biogeochemical and hydrological controls, respectively. While CH4 was oversaturated throughout the river network, CH4 hot spots were concentrated in the small urban rivers and highly discharge-dependent. The Shanghai river network played a disproportionately important role in regional C budget, offsetting up to 40% of the regional terrestrial net ecosystem production and 10% of net C uptake in the river-dominated East China Sea fueled by anthropogenic nutrient input. Given the rapid urbanization in global coastal areas, more research is needed to quantify the role of lowland coastal rivers as a major landscape C source in global C budget.

Delineation and validation of river network spatial scales for water resources and fisheries management.

PubMed

Wang, Lizhu; Brenden, Travis; Cao, Yong; Seelbach, Paul

2012-11-01

Identifying appropriate spatial scales is critically important for assessing health, attributing data, and guiding management actions for rivers. We describe a process for identifying a three-level hierarchy of spatial scales for Michigan rivers. Additionally, we conduct a variance decomposition of fish occurrence, abundance, and assemblage metric data to evaluate how much observed variability can be explained by the three spatial scales as a gage of their utility for water resources and fisheries management. The process involved the development of geographic information system programs, statistical models, modification by experienced biologists, and simplification to meet the needs of policy makers. Altogether, 28,889 reaches, 6,198 multiple-reach segments, and 11 segment classes were identified from Michigan river networks. The segment scale explained the greatest amount of variation in fish abundance and occurrence, followed by segment class, and reach. Segment scale also explained the greatest amount of variation in 13 of the 19 analyzed fish assemblage metrics, with segment class explaining the greatest amount of variation in the other six fish metrics. Segments appear to be a useful spatial scale/unit for measuring and synthesizing information for managing rivers and streams. Additionally, segment classes provide a useful typology for summarizing the numerous segments into a few categories. Reaches are the foundation for the identification of segments and segment classes and thus are integral elements of the overall spatial scale hierarchy despite reaches not explaining significant variation in fish assemblage data.

InSAR observations of aseismic slip associated with an earthquake swarm in the Columbia River flood basalts

USGS Publications Warehouse

Wicks, Charles; Thelen, W.; Weaver, C.; Gomberg, J.; Rohay, A.; Bodin, P.

2011-01-01

In 2009 a swarm of small shallow earthquakes occurred within the basalt flows of the Columbia River Basalt Group (CRBG). The swarm occurred within a dense seismic network in the U.S. Department of Energys Hanford Site. Data from the seismic network along with interferometric synthetic aperture radar (InSAR) data from the European Space Agencys (ESA) ENVISAT satellite provide insight into the nature of the swarm. By modeling the InSAR deformation data we constructed a model that consists of a shallow thrust fault and a near horizontal fault. We suggest that the near horizontal lying fault is a bedding-plane fault located between basalt flows. The geodetic moment of the modeled fault system is about eight times the cumulative seismic moment of the swarm. Precise location estimates of the swarm earthquakes indicate that the area of highest slip on the thrust fault, ???70mm of slip less than ???0.5km depth, was not located within the swarm cluster. Most of the slip on the faults appears to have progressed aseismically and we suggest that interbed sediments play a central role in the slip process. Copyright 2011 by the American Geophysical Union.

Trophic network model of exposed sandy coast: Linking continental and marine water ecosystems

NASA Astrophysics Data System (ADS)

Razinkovas-Baziukas, Artūras; Morkūnė, Rasa; Bacevičius, Egidijus; Gasiūnaitė, Zita Rasuolė

2017-08-01

A macroscopic food web network for the exposed sandy coastal zone of the south-eastern Baltic Sea was reconstructed using ECOPATH software to assess the matter and energy balance in the ecosystem. The model incorporated 40 living functional groups representing the Baltic Sea coastal system of Lithuania during the first decade of 21rst century. The overall pedigree index of our model was relatively high (0.66) as much of the input data originated from the study area. The results indicate net heterotrophy of the coastal zone due to strong influences from the nearby river - lagoon system (Curonian Lagoon). The majority of fish species and waterbirds were present in the coastal system on a seasonal basis and their migrations contributed to heterotrophic conditions. Among fish, the freshwater stragglers possibly contribute to the reversal of flow in biomass and energy from the coastal zone to the river-lagoon system. Top predators such as breeding and wintering piscivorous waterbirds and large pike-perch were identified as keystone species. There was a clear negative balance for the biomass of small marine pelagic fishes such as smelt, sprat and Baltic herring which represent the main prey items in this system.

SCIMAP: Modelling Diffuse Pollution in Large River Basins

NASA Astrophysics Data System (ADS)

Milledge, D.; Heathwaite, L.; Lane, S. N.; Reaney, S. M.

2009-12-01

Polluted rivers are a problem for the plants and animals that require clean water to survive. Watershed scale processes can influence instream aquatic ecosystems by delivering fine sediment, solutes and organic matter from diffuse sources. To improve our rivers we need to identify the pollution sources. Models can help us to do this but these rarely address the extent to which risky land uses are hydrologically-connected, and hence able to deliver, to the drainage network. Those that do tend to apply a full hydrological scheme, which is unfeasible for large watersheds. Here we develop a risk-based modelling framework, SCIMAP, for diffuse pollution from agriculture (Nitrate, Phosphate and Fine Sediment). In each case the basis of the analysis is the joint consideration of the probability of a unit of land (25 m2 cell) producing a particular environmental risk and then of that risk reaching the river. The components share a common treatment of hydrological connectivity but differ in their treatment of each pollution type. We test and apply SCIMAP using spatially-distributed instream water quality data for some of the UK’s largest catchments to infer the processes and the associated process parameters that matter in defining their concentrations. We use these to identify a series of risky field locations, where this land use is readily connected to the river system by overland flow.

Modelling algae growth and dissolved oxygen in the Seine River downstream the Paris urban area: contribution of high frequency measurements

NASA Astrophysics Data System (ADS)

Vilmin, Lauriane; Escoffier, Nicolas; Groleau, Alexis; Poulin, Michel; Flipo, Nicolas

2014-05-01

Dissolved oxygen is a key variable in the hydro-ecological functioning of river systems. The accurate representation of the different biogeochemical processes affecting algal blooms and dissolved oxygen in the water column in hydro-ecological models is crucial for the use of these models as reliable management tools. This study focuses on the water quality of the Seine River along a 225 km stretch, from Paris to the Seine estuary. The study area is highly urbanized and located downstream France's largest agricultural area, and therefore receives large amounts of nutrients. During the last decades, nutrient inputs have been significantly reduced, especially with the implementation of new sewage water treatment technologies. Even though the frequency and the intensity of observed algal blooms have decreased, blooms were observed in 2011 and 2012. These blooms are generally followed by a period of high organic matter accumulation, leading to high mineralization fluxes and potential oxygen depletion. The hydrodynamics and the water quality of the Seine River are simulated for the 2011-2012 period with the distributed process-based hydro-ecological model ProSe (Even et al., 1998). The simulated chlorophyll a and dissolved oxygen concentrations are compared to high frequency measurements at the Bougival monitoring station (50 km downstream from Paris), which is part of the CarboSeine monitoring network. The high frequency continuous dataset allows calibrating of primary producers' physiological parameters. New growth parameters are defined for the diatom community. The blooms occur at the end of the winter period (march 2011 and march 2012) and the optimal temperature for diatom growth is calibrated at 10°C, based on an analysis of the physiological response of the diatom community. One of the main outcomes of the modelling exercise is that the precise identification of the constituting communities of algal blooms must be achieved prior to the modelling itself. With the new growth parameters and by considering additional communities, as dinoflagellates, in the model, chlorophyll a peak values (over 60 µg/L in 2011 and over 30 in 2012) are accurately simulated. Moreover, the production rate of the communities constituting an algal bloom can be estimated by interpreting the high frequency diel dissolved oxygen curves (Escoffier et al., 2013). The modelled production rate during the 2011 bloom is of the same order of magnitude as the one estimated with this method (0.5 to 2 g/m3/day of oxygen), which validates the representation of photosynthesis in the model. Therefore the simulated oxygen response is also improved. References: Even S., Poulin M., Garnier J., Billen G., Servais P., Chesterikoff A., Coste M., 1998. River ecosystem modelling: Application of the ProSe model to the Seine river (France). Hydrobiologia 373, 27-37. Escoffier N., Bensoussan N., Métivier F., Rocher V., Bernard C., Arnaud D., Vilmin L., Poulin M., Flipo N., Groleau A., 2013. Intergrating large river trophic functioning from real time sensors network measurements. American Society of Limnology and Oceanography Congress. New Orleans, February 2013.

Export Time of Earthquake-Derived Landslides in Active Mountain Ranges

NASA Astrophysics Data System (ADS)

Croissant, T.; Lague, D.; Steer, P.; Davy, P.

2016-12-01

In active mountain ranges, large earthquakes (Mw > 5-6) trigger numerous landslides that impact river dynamics. These landslides bring local and sudden sediment deposits which are eroded and transported along the river network, causing downstream changes in river geometry, transport capacity and erosion efficiency. The progressive removal of landslide materials has implications for downstream hazards management and for landscape dynamics at the timescale of the seismic cycle. Although the export time of suspended sediments from landslides triggered by large-magnitude earthquakes has been extensively studied, the processes and time scales associated to bedload transport remains poorly studied. Here, we study the sediment export of large landslides with the 2D morphodynamic model, Eros. This model combines: (i) an hydrodynamic model, (ii) a sediment transport and deposition model and (iii) a lateral erosion model. Eros is particularly well suited for this issue as it accounts for the complex retro-actions between sediment transport and fluvial geometry for rivers submitted to external forcings such as abrupt sediment supply increase. Using a simplified synthetic topography we systematically study the influence of pulse volume (Vs) and channel transport capacity (QT) on the export time of landslides. The range of simulated river behavior includes landslide vertical incision, its subsequent removal by lateral erosion and the river morphology modifications induced by downstream sediment propagation. The morphodynamic adaptation of the river increases its transport capacity along the channel and tends to accelerate the landslide evacuation. Our results highlight two regimes: (i) the export time is linearly related to Vs/QT when the sediment pulse introduced in the river does not affect significantly the river hydrodynamic (low Vs/QT) and (ii) the export time is a non-linear function of Vs/QT when the pulse undergoes significant morphodynamic modifications during its evacuation (high Vs/QT). By combining our newly derived export time functions with the frequency-magnitude of earthquake intensity and the induced sediment production, we investigate the sediment export of several plausible earthquake scenarii in different mountain ranges (New Zealand, Taiwan, Nepal).

Design and development of a wireless sensor network to monitor snow depth in multiple catchments in the American River basin, California: hardware selection and sensor placement techniques

NASA Astrophysics Data System (ADS)

Kerkez, B.; Rice, R.; Glaser, S. D.; Bales, R. C.; Saksa, P. C.

2010-12-01

A 100-node wireless sensor network (WSN) was designed for the purpose of monitoring snow depth in two watersheds, spanning 3 km2 in the American River basin, in the central Sierra Nevada of California. The network will be deployed as a prototype project that will become a core element of a larger water information system for the Sierra Nevada. The site conditions range from mid-elevation forested areas to sub-alpine terrain with light forest cover. Extreme temperature and humidity fluctuations, along with heavy rain and snowfall events, create particularly challenging conditions for wireless communications. We show how statistics gathered from a previously deployed 60-node WSN, located in the Southern Sierra Critical Zone Observatory, were used to inform design. We adapted robust network hardware, manufactured by Dust Networks for highly demanding industrial monitoring, and added linear amplifiers to the radios to improve transmission distances. We also designed a custom data-logging board to interface the WSN hardware with snow-depth sensors. Due to the large distance between sensing locations, and complexity of terrain, we analyzed network statistics to select the location of repeater nodes, to create a redundant and reliable mesh. This optimized network topology will maximize transmission distances, while ensuring power-efficient network operations throughout harsh winter conditions. At least 30 of the 100 nodes will actively sense snow depth, while the remainder will act as sensor-ready repeaters in the mesh. Data from a previously conducted snow survey was used to create a Gaussian Process model of snow depth; variance estimates produced by this model were used to suggest near-optimal locations for snow-depth sensors to measure the variability across a 1 km2 grid. We compare the locations selected by the sensor placement algorithm to those made through expert opinion, and offer explanations for differences resulting from each approach.

Spatial properties of snow cover in the Upper Merced River Basin: implications for a distributed snow measurement network

NASA Astrophysics Data System (ADS)

Bouffon, T.; Rice, R.; Bales, R.

2006-12-01

The spatial distributions of snow water equivalent (SWE) and snow depth within a 1, 4, and 16 km2 grid element around two automated snow pillows in a forested and open- forested region of the Upper Merced River Basin (2,800 km2) of Yosemite National Park were characterized using field observations and analyzed using binary regression trees. Snow surveys occurred at the forested site during the accumulation and ablation seasons, while at the open-forest site a survey was performed only during the accumulation season. An average of 130 snow depth and 7 snow density measurements were made on each survey, within the 4 km2 grid. Snow depth was distributed using binary regression trees and geostatistical methods using the physiographic parameters (e.g. elevation, slope, vegetation, aspect). Results in the forest region indicate that the snow pillow overestimated average SWE within the 1, 4, and 16 km2 areas by 34 percent during ablation, but during accumulation the snow pillow provides a good estimate of the modeled mean SWE grid value, however it is suspected that the snow pillow was underestimating SWE. However, at the open forest site, during accumulation, the snow pillow was 28 percent greater than the mean modeled grid element. In addition, the binary regression trees indicate that the independent variables of vegetation, slope, and aspect are the most influential parameters of snow depth distribution. The binary regression tree and multivariate linear regression models explain about 60 percent of the initial variance for snow depth and 80 percent for density, respectively. This short-term study provides motivation and direction for the installation of a distributed snow measurement network to fill the information gap in basin-wide SWE and snow depth measurements. Guided by these results, a distributed snow measurement network was installed in the Fall 2006 at Gin Flat in the Upper Merced River Basin with the specific objective of measuring accumulation and ablation across topographic variables with the aim of providing guidance for future larger scale observation network designs.

Hydrological Controls of Riverine Ecosystems of the Napo River (Amazon Basin): Implications for the Management and Conservation of Biodiversity

NASA Astrophysics Data System (ADS)

Celi, J. E.; Hamilton, S. K.

2013-12-01

Scientific understanding of neotropical floodplains comes mainly from work on large rivers with predictable seasonal flooding regimes. Less studied rivers and floodplains on the Andean-Amazon interface are distinct in their hydrology, with more erratic flow regimes, and thus ecological roles of floodplain inundation differ in those ecosystems. Multiple and unpredictable flooding events control inundation of floodplains, with important implications for fish and wildlife, plant communities, and human activities. Wetlands along the river corridor exist across a continuum from strong river control to influence only by local waters, with the latter often lying on floodplain paleoterraces. The goal of this study was to understand the hydrological interactions and habitat diversity of the Napo River, a major Amazon tributary that originates in the Andes and drains exceptionally biodiverse Andean foreland plains. This river system is envisioned by developers as an industrial waterway that would require hydrological alterations and affect floodplain ecosystems. Water level regimes of the Napo River and its associated environments were assessed using networks of data loggers that recorded time under water across transects extending inland from the river across more than 100 sites and for up to 5 years. These networks also included rising stage samplers that collected flood water samples for determination of their origin (i.e., Andean rivers vs. local waters) based on hydrochemical composition. In addition, this work entails a classification of aquatic environments of the Napo Basin using an object-oriented remote sensing approach to simultaneously analyze optical and radar satellite imagery and digital elevation models to better assess the extent and diversity of flooded environments. We found out a continuum of hydrological regimes and aquatic habitats along the Napo River floodplains that are linked to the river hydrology in different degrees. Overall, environments that are proximal or that have high hydrological connectivity are riverine controlled versus systems that are distal or that have less or no connectivity that rely on rainwater or local runoff as a source of flooding. Outcomes of this research gave us insight on the extent and diversity of aquatic habitats of the Napo River, the role that the river has on their ecohydrology, the potential effects of different hydrologic scenarios on these ecosystems, and the management measures that need to be considered to support conservation in the region.

Nitrous oxide emission from denitrification in stream and river networks

Treesearch

J.J. Beaulieu; J.L. Tank; S.K. Hamilton; W.M. Wollheim; R.O. Hall; P.J. Mulholland; B.J. Peterson; L.R. Ashkenas; L.W. Cooper; C.N. Dahm; W.K. Dodds; N.B. Grimm; S.L. Johnson; W.H. McDowell; G.C. Poole; H.M. Valett; C.P. Arango; M.J. Bernot; A.J. Burgin; C.L. Crenshaw; A.M. Helton; L.T. Johnson; J.M. O' Brien; J.D. Potter; R.W. Sheibley; D.J. Sobota; S.M. Thomas

2011-01-01

Nitrous oxide (N20) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N20 via microbial denitrification that converts N to N20 and dinitrogen (N2...

Nitrous oxide emission from denitrification in stream and river networks

EPA Science Inventory

Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N2O via microbial denitrification which converts N to N2O and dinitrog...

Envisioning, quantifying, and managing thermal regimes on river networks

Treesearch

E. Ashley Steel; Timothy J. Beechie; Christian E. Torgersen; Aimee H. Fullerton

2017-01-01

Water temperatures fluctuate in time and space, creating diverse thermal regimes on river networks. Temporal variability in these thermal landscapes has important biological and ecological consequences because of nonlinearities in physiological reactions; spatial diversity in thermal landscapes provides aquatic organisms with options to maximize growth and survival....

From theoretical fixed return period events to real flooding impacts: a new approach to set flooding scenarios, thresholds and alerts

NASA Astrophysics Data System (ADS)

Parravicini, Paola; Cislaghi, Matteo; Condemi, Leonardo

2017-04-01

ARPA Lombardia is the Environmental Protection Agency of Lombardy, a wide region in the North of Italy. ARPA is in charge of river monitoring either for Civil Protection or water balance purposes. It cooperates with the Civil Protection Agency of Lombardy (RL-PC) in flood forecasting and early warning. The early warning system is based on rainfall and discharge thresholds: when a threshold exceeding is expected, RL-PC disseminates an alert from yellow to red. The conventional threshold evaluation is based on events at a fixed return period. Anyway, the impacts of events with the same return period may be different along the river course due to the specific characteristics of the affected areas. A new approach is introduced. It defines different scenarios, corresponding to different flood impacts. A discharge threshold is then associated to each scenario and the return period of the scenario is computed backwards. Flood scenarios are defined in accordance with National Civil Protection guidelines, which describe the expected flood impact and associate a colour to the scenario from green (no relevant effects) to red (major floods). A range of discharges is associated with each scenario since they cause the same flood impact; the threshold is set as the discharge corresponding to the transition between two scenarios. A wide range of event-based information is used to estimate the thresholds. As first guess, the thresholds are estimated starting from hydraulic model outputs and the people or infrastructures flooded according to the simulations. Eventually the model estimates are validated with real event knowledge: local Civil Protection Emergency Plans usually contain very detailed local impact description at known river levels or discharges, RL-PC collects flooding information notified by the population, newspapers often report flood events on web, data from the river monitoring network provide evaluation of actually happened levels and discharges. The methodology allows to give a return period for each scenario. The return period may vary along the river course according to the discharges associated with the scenario. The values of return period may show the areas characterized by higher risk and can be an important basis for civil protection emergency planning and river monitoring. For example, considering the Lambro River, the red scenario (major flood) shows a return period of 50 years in the northern rural part of the catchment. When the river crosses the city of Milan, the return period drops to 4 years. Afterwards it goes up to more than 100 years when the river flows in the agricultural areas in the southern part of the catchment. In addition, the knowledge gained with event-based analysis allows evaluating the compliance of the monitoring network with early warning requirements and represents the starting point for further development of the network itself.

Dynamic Floodplain representation in hydrologic flood forecasting using WRF-Hydro modeling framework

NASA Astrophysics Data System (ADS)

Gangodagamage, C.; Li, Z.; Maitaria, K.; Islam, M.; Ito, T.; Dhondia, J.

2016-12-01

Floods claim more lives and damage more property than any other category of natural disaster in the Continental United States. A system that can demarcate local flood boundaries dynamically could help flood prone communities prepare for and even prevent from catastrophic flood events. Lateral distance from the centerline of the river to the right and left floodplains for the water levels coming out of the models at each grid location have not been properly integrated with the national hydrography dataset (NHDPlus). The NHDPlus dataset represents the stream network with feature classes such as rivers, tributaries, canals, lakes, ponds, dams, coastlines, and stream gages. The NHDPlus dataset consists of approximately 2.7 million river reaches defining how surface water drains to the ocean. These river reaches have upstream and downstream nodes and basic parameters such as flow direction, drainage area, reach slope etc. We modified an existing algorithm (Gangodagamage et al., 2007) to provide lateral distance from the centerline of the river to the right and left floodplains for the flows simulated by models. Previous work produced floodplain boundaries for static river stages (i.e. 3D metric: distance along the main stem, flow depth, lateral distance from river center line). Our new approach introduces the floodplain boundary for variable water levels at each reach with the fourth dimension, time. We use modeled flows from WRF-Hydro and demarcate the right and left lateral boundaries of inundation dynamically by appropriately mapping discharges into hydraulically corrected stages. Backwater effects from the mainstem to tributaries are considered and proper corrections are applied for the tributary inundations. We obtained river stages by optimizing reach level channel parameters using newly developed stream flow routing algorithm. Non uniform inundations are mapped at each NHDplus reach (upstream and downstream nodes) and spatial interpolation is carried out on a normalized digital elevation model (always streams are at zero elevations) to obtain the smooth flood boundaries between adjacent reaches. The validation of the dynamic inundation boundaries is performed using multi-temporal satellite datasets as well as HEC-RAS hydrodynamic model results for selected streams for previous flood events.

Can Computational Sediment Transport Models Reproduce the Observed Variability of Channel Networks in Modern Deltas?

NASA Astrophysics Data System (ADS)

Nesvold, E.; Mukerji, T.

2017-12-01

River deltas display complex channel networks that can be characterized through the framework of graph theory, as shown by Tejedor et al. (2015). Deltaic patterns may also be useful in a Bayesian approach to uncertainty quantification of the subsurface, but this requires a prior distribution of the networks of ancient deltas. By considering subaerial deltas, one can at least obtain a snapshot in time of the channel network spectrum across deltas. In this study, the directed graph structure is semi-automatically extracted from satellite imagery using techniques from statistical processing and machine learning. Once the network is labeled with vertices and edges, spatial trends and width and sinuosity distributions can also be found easily. Since imagery is inherently 2D, computational sediment transport models can serve as a link between 2D network structure and 3D depositional elements; the numerous empirical rules and parameters built into such models makes it necessary to validate the output with field data. For this purpose we have used a set of 110 modern deltas, with average water discharge ranging from 10 - 200,000 m3/s, as a benchmark for natural variability. Both graph theoretic and more general distributions are established. A key question is whether it is possible to reproduce this deltaic network spectrum with computational models. Delft3D was used to solve the shallow water equations coupled with sediment transport. The experimental setup was relatively simple; incoming channelized flow onto a tilted plane, with varying wave and tidal energy, sediment types and grain size distributions, river discharge and a few other input parameters. Each realization was run until a delta had fully developed: between 50 and 500 years (with a morphology acceleration factor). It is shown that input parameters should not be sampled independently from the natural ranges, since this may result in deltaic output that falls well outside the natural spectrum. Since we are interested in studying the patterns occurring in nature, ideas are proposed for how to sample computer realizations that match this distribution. By establishing a link between surface based patterns from the field with the associated subsurface structure from physics-based models, this is a step towards a fully Bayesian workflow in subsurface simulation.

Upper Washita River experimental watersheds: Multiyear stability of soil water content profiles

USDA-ARS?s Scientific Manuscript database

Scaling in situ soil water content time series data to a large spatial domain is a key element of watershed environmental monitoring and modeling. The primary method of estimating and monitoring large-scale soil water content distributions is via in situ networks. It is critical to establish the s...

Statistical Analysis of Regional Surface Water Quality in Southeastern Ontario.

ERIC Educational Resources Information Center

Bodo, Byron A.

1992-01-01

Historical records from Ontario's Provincial Water Quality Monitoring Network for rivers and streams were analyzed to assess the feasibility of mapping regional water quality patterns in southeastern Ontario, spanning the Precambrian Shield and the St. Lawrence Lowlands. The study served as a model for much of Ontario. (54 references) (Author/MDH)

Residence times in river basins as determined by analysis of long-term tritium records

USGS Publications Warehouse

Michel, R.L.

1992-01-01

The US Geological Survey has maintained a network of stations to collect samples for the measurement of tritium concentrations in precipitation and streamflow since the early 1960s. Tritium data from outflow waters of river basins draining 4500-75000 km2 are used to determine average residence times of water within the basins. The basins studied are the Colorado River above Cisco, Utah; the Kissimmee River above Lake Okeechobee, Florida; the Mississippi River above Anoka, Minnesota; the Neuse River above Streets Ferry Bridge near Vanceboro, North Carolina; the Potomac River above Point of Rocks, Maryland; the Sacramento River above Sacramento, California; the Susquehanna River above Harrisburg, Pennsylvania. The basins are modeled with the assumption that the outflow in the river comes from two sources-prompt (within-year) runoff from precipitation, and flow from the long-term reservoirs of the basin. Tritium concentration in the outflow water of the basin is dependent on three factors: (1) tritium concentration in runoff from the long-term reservoir, which depends on the residence time for the reservoir and historical tritium concentrations in precipitation; (2) tritium concentrations in precipitation (the within-year runoff component); (3) relative contributions of flow from the long-term and within-year components. Predicted tritium concentrations for the outflow water in the river basins were calculated for different residence times and for different relative contributions from the two reservoirs. A box model was used to calculate tritium concentrations in the long-term reservoir. Calculated values of outflow tritium concentrations for the basin were regressed against the measured data to obtain a slope as close as possible to 1. These regressions assumed an intercept of zero and were carried out for different values of residence time and reservoir contribution to maximize the fit of modeled versus actual data for all the above rivers. The final slopes of the fitted regression lines ranged from 0.95 to 1.01 (correlation coefficient > 0.96) for the basins studied. Values for the residence time of waters within the basins and average relative contributions of the within-year and long-term reservoirs to outflow were obtained. Values for river basin residence times ranged from 2 years for the Kissimmee River basin to 20 years for the Potomac River basin. The residence times indicate the time scale in which the basin responds to anthropogenic inputs. The modeled tritium concentrations for the basins also furnish input data for urban and agricultural settings where these river waters are used. ?? 1992.

Challenges, developments and perspectives in intermittent river ecology

EPA Science Inventory

Although more than half the world's river networks comprise channels that periodically cease to flow and dry [intermittent rivers (IRs)], river ecology was largely developed from and for perennial systems. Ecological knowledge of IRs is rapidly increasing, so there is a need to s...

Comparative Performance Evaluation of Rainfall-runoff Models, Six of Black-box Type and One of Conceptual Type, From The Galway Flow Forecasting System (gffs) Package, Applied On Two Irish Catchments

NASA Astrophysics Data System (ADS)

Goswami, M.; O'Connor, K. M.; Shamseldin, A. Y.

The "Galway Real-Time River Flow Forecasting System" (GFFS) is a software pack- age developed at the Department of Engineering Hydrology, of the National University of Ireland, Galway, Ireland. It is based on a selection of lumped black-box and con- ceptual rainfall-runoff models, all developed in Galway, consisting primarily of both the non-parametric (NP) and parametric (P) forms of two black-box-type rainfall- runoff models, namely, the Simple Linear Model (SLM-NP and SLM-P) and the seasonally-based Linear Perturbation Model (LPM-NP and LPM-P), together with the non-parametric wetness-index-based Linearly Varying Gain Factor Model (LVGFM), the black-box Artificial Neural Network (ANN) Model, and the conceptual Soil Mois- ture Accounting and Routing (SMAR) Model. Comprised of the above suite of mod- els, the system enables the user to calibrate each model individually, initially without updating, and it is capable also of producing combined (i.e. consensus) forecasts us- ing the Simple Average Method (SAM), the Weighted Average Method (WAM), or the Artificial Neural Network Method (NNM). The updating of each model output is achieved using one of four different techniques, namely, simple Auto-Regressive (AR) updating, Linear Transfer Function (LTF) updating, Artificial Neural Network updating (NNU), and updating by the Non-linear Auto-Regressive Exogenous-input method (NARXM). The models exhibit a considerable range of variation in degree of complexity of structure, with corresponding degrees of complication in objective func- tion evaluation. Operating in continuous river-flow simulation and updating modes, these models and techniques have been applied to two Irish catchments, namely, the Fergus and the Brosna. A number of performance evaluation criteria have been used to comparatively assess the model discharge forecast efficiency.

[Mapping environmental vulnerability from ETM + data in the Yellow River Mouth Area].

PubMed

Wang, Rui-Yan; Yu, Zhen-Wen; Xia, Yan-Ling; Wang, Xiang-Feng; Zhao, Geng-Xing; Jiang, Shu-Qian

2013-10-01

The environmental vulnerability retrieval is important to support continuing data. The spatial distribution of regional environmental vulnerability was got through remote sensing retrieval. In view of soil and vegetation, the environmental vulnerability evaluation index system was built, and the environmental vulnerability of sampling points was calculated by the AHP-fuzzy method, then the correlation between the sampling points environmental vulnerability and ETM + spectral reflectance ratio including some kinds of conversion data was analyzed to determine the sensitive spectral parameters. Based on that, models of correlation analysis, traditional regression, BP neural network and support vector regression were taken to explain the quantitative relationship between the spectral reflectance and the environmental vulnerability. With this model, the environmental vulnerability distribution was retrieved in the Yellow River Mouth Area. The results showed that the correlation between the environmental vulnerability and the spring NDVI, the September NDVI and the spring brightness was better than others, so they were selected as the sensitive spectral parameters. The model precision result showed that in addition to the support vector model, the other model reached the significant level. While all the multi-variable regression was better than all one-variable regression, and the model accuracy of BP neural network was the best. This study will serve as a reliable theoretical reference for the large spatial scale environmental vulnerability estimation based on remote sensing data.

The Contribution of the Future SWOT Mission to Improve Simulations of River Stages and Stream-Aquifer Interactions at Regional Scale

NASA Astrophysics Data System (ADS)

Saleh, Firas; Filipo, Nicolas; Biancamaria, Sylvain; Habets, Florence; Rodriguez, Enersto; Mognard, Nelly

2013-09-01

The main objective of this study is to provide a realistic simulation of river stage in regional river networks in order to improve the quantification of stream-aquifer exchanges and better assess the associated aquifer responses that are often impacted by the magnitude and the frequency of the river stage fluctuations. This study extends the earlier work to improve the modeling of the Seine basin with a focus on simulating the hydrodynamics behavior of the Bassée alluvial wetland, a 120 km reach of the Seine River valley located south- east of Paris. The Bassée is of major importance for the drinking-water supply of Paris and surroundings, in addition to its particular hydrodynamic behavior due to the presence of a number of gravels. In this context, the understanding of stream-aquifer interactions is required for water quantity and quality preservation. A regional distributed process-based hydro(geo)logical model, Eau-Dyssée, is used. It aims at the integrated modeling of the hydrosystem to manage the various elements involved in the quantitative and qualitative aspects of water resources. Eau-Dyssée simulates pseudo 3D flow in aquifer systems solving the diffusivity equation with a finite difference numerical scheme. River flow is simulated with a Muskingum model. In addition to the in-stream discharge, a river stage estimate is needed to calculate the water exchange at the stream-aquifer interface using a conductance model. In this context, the future SWOT mission and its high-spatial resolution imagery can provide surface water level measurements at the regional scale that will permit to better characterize the Bassée complex hydro(geo)logical system and better assess soil water content. Moreover, the Bassée is considered as a potential target for the framework of the AirSWOT airborne campaign in France, 2013.

Parameterization of a complex landscape for a sediment routing model of the Le Sueur River, southern Minnesota

NASA Astrophysics Data System (ADS)

Belmont, P.; Viparelli, E.; Parker, G.; Lauer, W.; Jennings, C.; Gran, K.; Wilcock, P.; Melesse, A.

2008-12-01

Modeling sediment fluxes and pathways in complex landscapes is limited by our inability to accurately measure and integrate heterogeneous, spatially distributed sources into a single coherent, predictive geomorphic transport law. In this study, we partition the complex landscape of the Le Sueur River watershed into five distributed primary source types, bluffs (including strath terrace caps), ravines, streambanks, tributaries, and flat,agriculture-dominated uplands. The sediment contribution of each source is quantified independently and parameterized for use in a sand and mud routing model. Rigorous modeling of the evolution of this landscape and sediment flux from each source type requires consideration of substrate characteristics, heterogeneity, and spatial connectivity. The subsurface architecture of the Le Sueur drainage basin is defined by a layer cake sequence of fine-grained tills, interbedded with fluvioglacial sands. Nearly instantaneous baselevel fall of 65 m occurred at 11.5 ka, as a result of the catastrophic draining of glacial Lake Agassiz through the Minnesota River, to which the Le Sueur is a tributary. The major knickpoint that was generated from that event has propagated 40 km into the Le Sueur network, initiating an incised river valley with tall, retreating bluffs and actively incising ravines. Loading estimates constrained by river gaging records that bound the knick zone indicate that bluffs connected to the river are retreating at an average rate of less than 2 cm per year and ravines are incising at an average rate of less than 0.8 mm per year, consistent with the Holocene average incision rate on the main stem of the river of less than 0.6 mm per year. Ongoing work with cosmogenic nuclide sediment tracers, ground-based LiDAR, historic aerial photos, and field mapping will be combined to represent the diversity of erosional environments and processes in a single coherent routing model.

Results and evaluation of a pilot primary monitoring network, San Francisco Bay, California, 1978

USGS Publications Warehouse

Bradford, W.L.; Iwatsubo, R.T.

1980-01-01

A primary monitoring network of 12 stations, with measurements at 1-meter depth intervals every 2 weeks during periods of high inflow from the Sacramento-San Joaquin River delta, and every 4-6 weeks during seasonal low delta inflows, appears adequate to observe major changes in ambient water quality in San Francisco Bay. A 1-year study tested the network operation and determined that analysis of the data could demonstrate the major changes in salinity, temperature, and light-attenuation distributions known to occur, based on earlier research, in response to variations of delta inflow and to other physical processes. Observations of eddies at two stations, of the influence of water from a river flooding in the extreme south bay, and of difference in salinity and temperature laterally across the entrance to the south bay are all new but are consistent with existing models. The pH, dissolved oxygen, and light-attenuation measurements, while adequate to observe small-scale vertical variations, are not sufficiently sensitive to detect the effects of phytoplankton blooms. (USGS)

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

U.S. Geological Survey Real-Time River Data Applications

USGS Publications Warehouse

Morlock, Scott E.

1998-01-01

Real-time river data provided by the USGS originate from streamflow-gaging stations. The USGS operates and maintains a network of more than 7,000 such stations across the nation (Mason and Wieger, 1995). These gaging stations, used to produce records of stage and streamflow data, are operated in cooperation with local, state, and other federal agencies. The USGS office in Indianapolis operates a statewide network of more than 170 gaging stations. The instrumentation at USGS gaging stations monitors and records river information, primarily river stage (fig. 1). As technological advances are made, many USGS gaging stations are being retrofitted with electronic instrumentation to monitor and record river data. Electronic instrumentation facilitates transmission of real-time or near real-time river data for use by government agencies in such flood-related tasks as operating flood-control structures and ordering evacuations.

Channel-conveyance capacity, channel change, and sediment transport in the lower Puyallup, White, and Carbon Rivers, western Washington

USGS Publications Warehouse

Czuba, Jonathan A.; Czuba, Christiana R.; Magirl, Chistopher S.; Voss, Frank D.

2010-01-01

Draining the volcanic, glaciated terrain of Mount Rainier, Washington, the Puyallup, White, and Carbon Rivers convey copious volumes of water and sediment down to Commencement Bay in Puget Sound. Recent flooding in the lowland river system has renewed interest in understanding sediment transport and its effects on flow conveyance throughout the lower drainage basin. Bathymetric and topographic data for 156 cross sections were surveyed in the lower Puyallup River system by the U.S. Geological Survey (USGS) and were compared with similar datasets collected in 1984. Regions of significant aggradation were measured along the Puyallup and White Rivers. Between 1984 and 2009, aggradation totals as measured by changes in average channel elevation were as much as 7.5, 6.5, and 2 feet on the Puyallup, White, and Carbon Rivers, respectively. These aggrading river sections correlated with decreasing slopes in riverbeds where the rivers exit relatively confined sections in the upper drainage and enter the relatively unconstricted valleys of the low-gradient Puget Lowland. Measured grain-size distributions from each riverbed showed a progressive fining downstream. Analysis of stage-discharge relations at streamflow-gaging stations along rivers draining Mount Rainier demonstrated the dynamic nature of channel morphology on river courses influenced by glaciated, volcanic terrain. The greatest rates of aggradation since the 1980s were in the Nisqually River near National (5.0 inches per year) and the White River near Auburn (1.8 inches per year). Less pronounced aggradation was measured on the Puyallup River and the White River just downstream of Mud Mountain Dam. The largest measured rate of incision was measured in the Cowlitz River at Packwood (5.0 inches per year). Channel-conveyance capacity estimated using a one-dimensional hydraulic model decreased in some river reaches since 1984. The reach exhibiting the largest decrease (about 20-50 percent) in channel-conveyance capacity was the White River between R Street Bridge and the Lake Tapps return, a reach affected by recent flooding. Conveyance capacity also decreased in sections of the Puyallup River. Conveyance capacity was mostly unchanged along other study reaches. Bedload transport was simulated throughout the entire river network and consistent with other observations and analyses, the hydraulic model showed that the upper Puyallup and White Rivers tended to accumulate sediment. Accuracy of the bedload-transport modeling, however, was limited due to a scarcity of sediment-transport data sets from the Puyallup system, mantling of sand over cobbles in the lower Puyallup and White Rivers, and overall uncertainty in modeling sediment transport in gravel-bedded rivers. Consequently, the output results from the model were treated as more qualitative in value, useful in comparing geomorphic trends within different river reaches, but not accurate in producing precise predictions of mass of sediment moved or deposited. The hydraulic model and the bedload-transport component were useful for analyzing proposed river-management options, if surveyed cross sections adequately represented the river-management site and proposed management options. The hydraulic model showed that setback levees would provide greater flood protection than gravel-bar scalping after the initial project construction and for some time thereafter, although the model was not accurate enough to quantify the length of time of the flood protection. The greatest hydraulic benefit from setback levees would be a substantial increase in the effective channel-conveyance area. By widening the distance between levees, the new floodplain would accommodate larger increases in discharge with relatively small incremental increases in stage. Model simulation results indicate that the hydraulic benefit from a setback levee also would be long-lived and would effectively compensate for increased deposition within the setback reach

American River Hydrologic Observatory

NASA Astrophysics Data System (ADS)

Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2016-12-01

We have set up fourteen large wireless sensor networks to measure hydrologic parameters over physiographical representative regions of the snow-dominated portion of the river basin. This is perhaps the largest wireless sensor network in the world. Each network covers about a 1 km2 area and consists of about 45 elements. We measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in real time at ten locations per site, as opposed to the traditional once-a-month snow course. As part of the multi-PI SSCZO, we have installed a 62-node wireless sensor network to measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in real time. This network has been operating for approximately six years. We are now installing four large wireless sensor networks to measure snow depth, temperature humidity soil moisture and temperature, and solar radiation in East Branch of the North Fork of the Feather River, CA. The presentation will discuss the planning and operation of the networks as well as some unique results. It will also present information about the networking hardware designed for these installations, which has resulted in a start-up, Metronome Systems.

Digital hydrologic networks supporting applications related to spatially referenced regression modeling

USGS Publications Warehouse

Brakebill, John W.; Wolock, David M.; Terziotti, Silvia

2011-01-01

Digital hydrologic networks depicting surface-water pathways and their associated drainage catchments provide a key component to hydrologic analysis and modeling. Collectively, they form common spatial units that can be used to frame the descriptions of aquatic and watershed processes. In addition, they provide the ability to simulate and route the movement of water and associated constituents throughout the landscape. Digital hydrologic networks have evolved from derivatives of mapping products to detailed, interconnected, spatially referenced networks of water pathways, drainage areas, and stream and watershed characteristics. These properties are important because they enhance the ability to spatially evaluate factors that affect the sources and transport of water-quality constituents at various scales. SPAtially Referenced Regressions On Watershed attributes (SPARROW), a process-based ⁄ statistical model, relies on a digital hydrologic network in order to establish relations between quantities of monitored contaminant flux, contaminant sources, and the associated physical characteristics affecting contaminant transport. Digital hydrologic networks modified from the River Reach File (RF1) and National Hydrography Dataset (NHD) geospatial datasets provided frameworks for SPARROW in six regions of the conterminous United States. In addition, characteristics of the modified RF1 were used to update estimates of mean-annual streamflow. This produced more current flow estimates for use in SPARROW modeling.

Reconstructing the paleo-topography and paleo-environmental features of the Sarno River plain (Italy) before the AD 79 eruption of Somma-Vesuvius volcanic complex

NASA Astrophysics Data System (ADS)

Vogel, Sebastian; Märker, Michael

2010-05-01

SSP1.4 Understanding mixed siliciclastic-volcaniclastic depositional systems and their relationships with geodynamics or GD2.3/CL4.14/GM5.8/MPRG22/SSP3.5 Reconstruction of ancient continents: Dating and characterization of paleosurfaces Reconstructing the paleo-topography and paleo-environmental features of the Sarno River plain (Italy) before the AD 79 eruption of Somma-Vesuvius volcanic complex Sebastian Vogel[1] & Michael Märker[1] [1] Heidelberg Academy of Sciences and Humanities c/o University of Tübingen, Rümelinstraße 19-23, D-72070 Tübingen, Germany. Within the geoarchaeological research project "Reconstruction of the Ancient Cultural Landscape of the Sarno River Plain" undertaken by the German Archaeological Institute in cooperation with the Heidelberg Academy of Sciences and Humanities/University of Tübingen a methodology was developed to model the spatial dispersion of volcanic deposits of Somma-Vesuvius volcanic complex since its Plinian eruption AD 79. Eventually, this was done to reconstruct the paleo-topography and paleo-environment of the Sarno River plain before the eruption AD 79. We collected, localized and digitized more than 1,800 core drillings to gain a representative network of stratigraphical information covering the entire plain. Besides other stratigraphical data including the characteristics of the pre-AD 79 stratum, the depth to the pre-AD 79 paleo-surface was identified from the available drilling documentation. Instead of applying a simple interpolation of the drilling data, we reconstructed the pre-AD 79 paleo-surface with a sophisticated geostatistical methodology using a machine based learning approach based on classification and regression trees. We hypothesize that the present-day topography reflects the ancient topography, because the eruption of AD 79 coated the ancient topography, leaving ancient physiographic elements of the Sarno River plain still recognizable in the present-day topography. Therefore, a high resolution, present-day digital elevation model (DEM) was generated. A detailed terrain analysis yielded 15 different primary and secondary topographic indices of the present-day DEM. Then, a classification and regression model was generated combining the present-day topographic indices to predict the depth of the pre-AD 79 surface. This model was calibrated with the measured depth of the pre-AD 79 surface from the drilling data. To gain a pre-AD 79 digital elevation model (DEM) the modeled depth of the pre-AD 79 surface was subtracted from the present-day DEM. To reconstruct some paleo-environmental features, such as the paleo-coast and the paleo-river network and its flood plain, the modeled pre-AD 79 DEM was compared with the classified characteristic of the pre-AD 79 stratum, identified from the drilling documentation. It is the first time that the paleo-topography and paleo-environmental features of the Sarno River basin were systematically reconstructed using a detailed database of input variables and sophisticated data mining technologies. Keywords: Sarno River Basin, Roman paleo-topography, paleo-environment, stratigraphical core drillings, Classification and Regression Trees

Framework for developing hybrid process-driven, artificial neural network and regression models for salinity prediction in river systems

NASA Astrophysics Data System (ADS)

Hunter, Jason M.; Maier, Holger R.; Gibbs, Matthew S.; Foale, Eloise R.; Grosvenor, Naomi A.; Harders, Nathan P.; Kikuchi-Miller, Tahali C.

2018-05-01

Salinity modelling in river systems is complicated by a number of processes, including in-stream salt transport and various mechanisms of saline accession that vary dynamically as a function of water level and flow, often at different temporal scales. Traditionally, salinity models in rivers have either been process- or data-driven. The primary problem with process-based models is that in many instances, not all of the underlying processes are fully understood or able to be represented mathematically. There are also often insufficient historical data to support model development. The major limitation of data-driven models, such as artificial neural networks (ANNs) in comparison, is that they provide limited system understanding and are generally not able to be used to inform management decisions targeting specific processes, as different processes are generally modelled implicitly. In order to overcome these limitations, a generic framework for developing hybrid process and data-driven models of salinity in river systems is introduced and applied in this paper. As part of the approach, the most suitable sub-models are developed for each sub-process affecting salinity at the location of interest based on consideration of model purpose, the degree of process understanding and data availability, which are then combined to form the hybrid model. The approach is applied to a 46 km reach of the Murray River in South Australia, which is affected by high levels of salinity. In this reach, the major processes affecting salinity include in-stream salt transport, accession of saline groundwater along the length of the reach and the flushing of three waterbodies in the floodplain during overbank flows of various magnitudes. Based on trade-offs between the degree of process understanding and data availability, a process-driven model is developed for in-stream salt transport, an ANN model is used to model saline groundwater accession and three linear regression models are used to account for the flushing of the different floodplain storages. The resulting hybrid model performs very well on approximately 3 years of daily validation data, with a Nash-Sutcliffe efficiency (NSE) of 0.89 and a root mean squared error (RMSE) of 12.62 mg L-1 (over a range from approximately 50 to 250 mg L-1). Each component of the hybrid model results in noticeable improvements in model performance corresponding to the range of flows for which they are developed. The predictive performance of the hybrid model is significantly better than that of a benchmark process-driven model (NSE = -0.14, RMSE = 41.10 mg L-1, Gbench index = 0.90) and slightly better than that of a benchmark data-driven (ANN) model (NSE = 0.83, RMSE = 15.93 mg L-1, Gbench index = 0.36). Apart from improved predictive performance, the hybrid model also has advantages over the ANN benchmark model in terms of increased capacity for improving system understanding and greater ability to support management decisions.

Modeling the Space-Time Destiny of Pan-Arctic Permafrost DOC in a Global Land Surface Model: Feedback Implications

NASA Astrophysics Data System (ADS)

Bowring, S.; Lauerwald, R.; Guenet, B.; Zhu, D.; Ciais, P.

2017-12-01

Most global climate models do not represent the unique permafrost soil environment and its respective processes. This significantly contributes to uncertainty in estimating their responses, and that of the planet at large, to warming. Here, the production, transport and atmospheric release of dissolved organic carbon (DOC) from high-latitude permafrost soils into inland waters and the ocean is explicitly represented for the first time in the land surface component (ORCHIDEE-MICT) of a CMIP6 global climate model (IPSL). This work merges two models that are able to mechanistically simulate complex processes for 1) snow, ice and soil phenomena in high latitude environments, and 2) DOC production and lateral transport through soils and the river network, respectively, at 0.5° to 2° resolution. The resulting model is subjected to a wide range of input forcing data, parameter testing and contentious feedback phenomena, including microbial heat generation as the active layer deepens. We present results for the present and future Pan-Arctic and Eurasia, with a focus on the Lena and Mackenzie River basins, and show that soil DOC concentrations, their riverine transport and atmospheric evasion are reasonably well represented as compared to observed stocks, fluxes and seasonality. We show that most basins exhibit large increases in DOC transport and riverine CO2 evasion across the suite of RCP scenarios to 2100. We also show that model output is strongly influenced by choice of input forcing data. The riverine component of what is known as the `boundless carbon cycle' is little-recognized in global climate modeling. Hydrological mobilization to the river network results either in sedimentary settling or atmospheric `evasion', presently amounting to 0.5-1.8 PgC yr-1. Our work aims at filling in these knowledge gaps, and the response of these DOC-related processes to thermal forcing. Potential feedbacks owing to such a response are of particular relevance, given the magnitude of the permafrost carbon pool.

Modern space/time geostatistics using river distances: data integration of turbidity and E. coli measurements to assess fecal contamination along the Raritan River in New Jersey.

PubMed

Money, Eric S; Carter, Gail P; Serre, Marc L

2009-05-15

Escherichia coli (E. coli) is a widely used indicator of fecal contamination in water bodies. External contact and subsequent ingestion of bacteria coming from fecal contamination can lead to harmful health effects. Since E. coli data are sometimes limited, the objective of this study is to use secondary information in the form of turbidity to improve the assessment of E. coli at unmonitored locations. We obtained all E. coli and turbidity monitoring data available from existing monitoring networks for the 2000-2006 time period for the Raritan River Basin, New Jersey. Using collocated measurements, we developed a predictive model of E. coli from turbidity data. Using this model, soft data are constructed for E. coli given turbidity measurements at 739 space/time locations where only turbidity was measured. Finally, the Bayesian Maximum Entropy (BME) method of modern space/time geostatistics was used for the data integration of monitored and predicted E. coli data to produce maps showing E. coli concentration estimated daily across the river basin. The addition of soft data in conjunction with the use of river distances reduced estimation error by about 30%. Furthermore, based on these maps, up to 35% of river miles in the Raritan Basin had a probability of E coli impairment greater than 90% on the most polluted day of the study period.

Spatio-temporal variability in movement, age, and growth of mountain whitefish (Prosopium williamsoni) in a river network based upon PIT tagging and otolith chemistry

USGS Publications Warehouse

Benjamin, Joseph R.; Wetzel, Lisa A.; Martens, Kyle D.; Larsen, Kimberly; Connolly, Patrick J.

2013-01-01

Connectivity of river networks and the movements among habitats can be critical for the life history of many fish species, and understanding of the patterns of movement is central to managing populations, communities, and the landscapes they use. We combined passive integrated transponder tagging over 4 years and strontium isotopes in otoliths to demonstrate that 25% of the mountain whitefish (Prosopium williamsoni) sampled moved between the Methow and Columbia rivers, Washington, USA. Seasonal migrations downstream from the Methow River to the Columbia River to overwinter occurred in autumn and upstream movements in the spring. We observed migration was common during the first year of life, with migrants being larger than nonmigrants. However, growth between migrants and nonmigrants was similar. Water temperature was positively related to the proportion of migrants and negatively related to the timing of migration, but neither was related to discharge. The broad spatio-temporal movements we observed suggest mountain whitefish, and likely other nonanadromous fish, require distant habitats and also suggests that management and conservation strategies to keep connectivity of large river networks are imperative.

Design of a monitoring network and assessment of the pollution on the Lerma river and its tributaries by wastewaters disposal.

PubMed

Fall, C; Hinojosa-Peña, A; Carreño-de-León, M C

2007-02-01

While the 2005 progress report of the United Nations Millennium Development Goals stresses out the need of a dramatic increase in investment to meet the sanitation target in the third world, it is important to anticipate about some parallel negative impacts that may have this optimistic programme (extension of sewer networks without sufficient treatment works). Research was initiated on Lerma River (Mexico), subjected to many rejects disposal, to design a monitoring network and evaluate the impact of wastewaters on its water quality. The discharges was inventorized, geo-positioned with a GPS and mapped, while the physico-chemical characteristics of the river water, its tributaries and main rejects were evaluated. Microtox system was used as an additional screening tool. Along the 60 km of the High Course of Lerma River (HCLR), 51 discharges, with a diameter or width larger than 0.3 m (including 7 small tributaries) were identified. Based on the inventory, a monitoring network of 21 sampling stations in the river and 13 in the important discharges (>2 m) was proposed. A great similitude was found between the average characteristics of the discharges and the river itself, in both the wet and dry seasons. Oxygen was found exhausted (<0.5 mg/L) almost all along the high course of the river, with COD and TDS average levels of 390 and 1980 mg/L in the dry season, against 150 and 400 mg/L in the wet season. In the dry season, almost all the sites along the river revealed some toxicity to the bacteria test species (2.9 to 150 TU, with an average of 27 TU). Same septic conditions and toxicity levels were observed in many of the discharges. Four of the six evaluated tributaries, as well as the lagoon (origin of the river), were relatively in better conditions (2 to 8 mg/L D.O., TU<1) than for the Lerma, acting as diluents and renewal of the HCLR flow rate. The river was shown to be quite a main sewer collector. The high surface water contamination by untreated wastewaters that is depicted in this research should be taken into account in the Millennium Goals strategies, by promoting treatment plan works simultaneously, when sewer networks in the third world would extend.

Reconstructing Sediment Supply, Transport and Deposition Behind the Elwha River Dams

NASA Astrophysics Data System (ADS)

Beveridge, C.

2017-12-01

The Elwha River watershed in Olympic National Park of Washington State, USA is predominantly a steep, mountainous landscape where dominant geomorphic processes include landslides, debris flows and gullying. The river is characterized by substantial variability of channel morphology and fluvial processes, and alternates between narrow bedrock canyons and wider alluvial reaches for much of its length. Literature suggests that the Elwha watershed is topographically and tectonically in steady state. The removal of the two massive hydropower dams along the river in 2013 marked the largest dam removal in history. Over the century long lifespan of the dams, approximately 21 million cubic meters of sediment was impounded behind them. Long term erosion rates documented in this region and reservoir sedimentation data give unprecedented opportunities to test watershed sediment yield models and examine dominant processes that control sediment yield over human time scales. In this study, we aim to reconstruct sediment supply, transport and deposition behind the Glines Canyon Dam (most upstream dam) over its lifespan using a watershed modeling approach. We developed alternative models of varying complexity for sediment production and transport at the network scale driven by hydrologic forcing. We simulate sediment supply and transport in tributaries upstream of the dam. The modeled sediment supply and transport dynamics are based on calibrated formulae (e.g., bedload transport is simulated using Wilcock-Crowe 2003 with modification based on observed bedload transport in the Elwha River). Observational data that aid in our approach include DEM, channel morphology, meteorology, and streamflow and sediment (bedload and suspended load) discharge. We aim to demonstrate how the observed sediment yield behind the dams was influenced by upstream transport supply and capacity limitations, thereby demonstrating the scale effects of flow and sediment transport processes in the Elwha River watershed.

Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Onfroy, T.; Leblois, E.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2013-07-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible but not yet occurred flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2012 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90% of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of CCR claim database has shown that approximately 45% of the insured flood losses are located inside the floodplains and 45% outside. 10% other percent are due to seasurge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: generation of fictive river flows based on the historical records of the river gauge network and generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (MACIF) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

The morphodynamics and sedimentology of large river confluences

NASA Astrophysics Data System (ADS)

Nicholas, Andrew; Sambrook Smith, Greg; Best, James; Bull, Jon; Dixon, Simon; Goodbred, Steven; Sarker, Mamin; Vardy, Mark

2017-04-01

Confluences are key locations within large river networks, yet surprisingly little is known about how they migrate and evolve through time. Moreover, because confluence sites are associated with scour pools that are typically several times the mean channel depth, the deposits associated with such scours should have a high potential for preservation within the rock record. However, paradoxically, such scours are rarely observed, and the sedimentological characteristics of such deposits are poorly understood. This study reports results from a physically-based morphodynamic model, which is applied to simulate the evolution and resulting alluvial architecture associated with large river junctions. Boundary conditions within the model simulation are defined to approximate the junction of the Ganges and Jamuna rivers, in Bangladesh. Model results are supplemented by geophysical datasets collected during boat-based surveys at this junction. Simulated deposit characteristics and geophysical datasets are compared with three existing and contrasting conceptual models that have been proposed to represent the sedimentary architecture of confluence scours. Results illustrate that existing conceptual models may be overly simplistic, although elements of each of the three conceptual models are evident in the deposits generated by the numerical simulation. The latter are characterised by several distinct styles of sedimentary fill, which can be linked to particular morphodynamic behaviours. However, the preserved characteristics of simulated confluence deposits vary substantial according to the degree of reworking by channel migration. This may go some way towards explaining the confluence scour paradox; while abundant large scours might be expected in the rock record, they are rarely reported.

Regional assessment of the hydropower potential of rivers in West Africa

NASA Astrophysics Data System (ADS)

Kling, Harald; Stanzel, Philipp; Fuchs, Martin

2016-04-01

The 15 countries of the Economic Community of West African States (ECOWAS) face a constant shortage of energy supply, which limits sustained economic growth. Currently there are about 50 operational hydropower plants and about 40 more are under construction or refurbishment. The potential for future hydropower development - especially for small-scale plants in rural areas - is assumed to be large, but exact data are missing. This study supports the energy initiatives of the "ECOWAS Centre for Renewable Energy and Energy Efficiency" (ECREEE) by assessing the hydropower potential of all rivers in West Africa. For more than 500,000 river reaches the hydropower potential was computed from channel slope and mean annual discharge. In large areas there is a lack of discharge observations. Therefore, an annual water balance model was used to simulate discharge. The model domain covers 5 Mio km², including e.g. the Niger, Volta, and Senegal River basins. The model was calibrated with observed data of 410 gauges, using precipitation and potential evapotranspiration data as inputs. Historic variations of observed annual discharge between 1950 and 2010 are simulated well by the model. As hydropower plants are investments with a lifetime of several decades we also assessed possible changes in future discharge due to climate change. To this end the water balance model was driven with bias-corrected climate projections of 15 Regional Climate Models for two emission scenarios of the CORDEX-Africa ensemble. The simulation results for the river network were up-scaled to sub-areas and national summaries. This information gives a regional quantification of the hydropower potential, expected climate change impacts, as well as a regional classification for general suitability (or non-suitability) of hydropower plant size - from small-scale to large projects.

An epidemic model for the interactions between thermal regime of rivers and transmission of Proliferative Kidney Disease in salmonid fish

NASA Astrophysics Data System (ADS)

Carraro, Luca; Bertuzzo, Enrico; Mari, Lorenzo; Gatto, Marino; Strepparava, Nicole; Hartikainen, Hanna; Rinaldo, Andrea

2015-04-01

Proliferative kidney disease (PKD) affects salmonid populations in European and North-American rivers. It is caused by the endoparasitic myxozoan Tetracapsuloides bryosalmonae, which exploits freshwater bryozoans (Fredericella sultana) and salmonids as primary and secondary hosts, respectively. Incidence and mortality, which can reach up to 90-100%, are known to be strongly related to water temperature. PKD has been present in brown trout population for a long time but has recently increased rapidly in incidence and severity causing a decline in fish catches in many countries. In addition, environmental changes are feared to cause PKD outbreaks at higher latitude and altitude regions as warmer temperatures promote disease development. This calls for a better comprehension of the interactions between disease dynamics and the thermal regime of rivers, in order to possibly devise strategies for disease management. In this perspective, a spatially explicit model of PKD epidemiology in riverine host metacommunities is proposed. The model aims at summarizing the knowledge on the modes of transmission of the disease and the life-cycle of the parasite, making the connection between temperature and epidemiological parameters explicit. The model accounts for both local population and disease dynamics of bryozoans and fish and hydrodynamic dispersion of the parasite spores and hosts along the river network. The model is time-hybrid, coupling inter-seasonal and intra-seasonal dynamics, the former being described in a continuous time domain, the latter seen as time steps of a discrete time domain. In order to test the model, a case study is conducted in river Wigger (Cantons of Aargau and Lucerne, Switzerland), where data about water temperature, brown trout and bryozoan populations and PKD prevalence are being collected.

Multi-agent modelling framework for water, energy and other resource networks

NASA Astrophysics Data System (ADS)

Knox, S.; Selby, P. D.; Meier, P.; Harou, J. J.; Yoon, J.; Lachaut, T.; Klassert, C. J. A.; Avisse, N.; Mohamed, K.; Tomlinson, J.; Khadem, M.; Tilmant, A.; Gorelick, S.

2015-12-01

Bespoke modelling tools are often needed when planning future engineered interventions in the context of various climate, socio-economic and geopolitical futures. Such tools can help improve system operating policies or assess infrastructure upgrades and their risks. A frequently used approach is to simulate and/or optimise the impact of interventions in engineered systems. Modelling complex infrastructure systems can involve incorporating multiple aspects into a single model, for example physical, economic and political. This presents the challenge of combining research from diverse areas into a single system effectively. We present the Pynsim 'Python Network Simulator' framework, a library for building simulation models capable of representing, the physical, institutional and economic aspects of an engineered resources system. Pynsim is an open source, object oriented code aiming to promote integration of different modelling processes through a single code library. We present two case studies that demonstrate important features of Pynsim's design. The first is a large interdisciplinary project of a national water system in the Middle East with modellers from fields including water resources, economics, hydrology and geography each considering different facets of a multi agent system. It includes: modelling water supply and demand for households and farms; a water tanker market with transfer of water between farms and households, and policy decisions made by government institutions at district, national and international level. This study demonstrates that a well-structured library of code can provide a hub for development and act as a catalyst for integrating models. The second focuses on optimising the location of new run-of-river hydropower plants. Using a multi-objective evolutionary algorithm, this study analyses different network configurations to identify the optimal placement of new power plants within a river network. This demonstrates that Pynsim can be used to evaluate a multitude of topologies for identifying the optimal location of infrastructure investments. Pynsim is available on GitHub or via standard python installer packages such as pip. It comes with several examples and online documentation, making it attractive for those less experienced in software engineering.

Application of experimental design for the optimization of artificial neural network-based water quality model: a case study of dissolved oxygen prediction.

PubMed

Šiljić Tomić, Aleksandra; Antanasijević, Davor; Ristić, Mirjana; Perić-Grujić, Aleksandra; Pocajt, Viktor

2018-04-01

This paper presents an application of experimental design for the optimization of artificial neural network (ANN) for the prediction of dissolved oxygen (DO) content in the Danube River. The aim of this research was to obtain a more reliable ANN model that uses fewer monitoring records, by simultaneous optimization of the following model parameters: number of monitoring sites, number of historical monitoring data (expressed in years), and number of input water quality parameters used. Box-Behnken three-factor at three levels experimental design was applied for simultaneous spatial, temporal, and input variables optimization of the ANN model. The prediction of DO was performed using a feed-forward back-propagation neural network (BPNN), while the selection of most important inputs was done off-model using multi-filter approach that combines a chi-square ranking in the first step with a correlation-based elimination in the second step. The contour plots of absolute and relative error response surfaces were utilized to determine the optimal values of design factors. From the contour plots, two BPNN models that cover entire Danube flow through Serbia are proposed: an upstream model (BPNN-UP) that covers 8 monitoring sites prior to Belgrade and uses 12 inputs measured in the 7-year period and a downstream model (BPNN-DOWN) which covers 9 monitoring sites and uses 11 input parameters measured in the 6-year period. The main difference between the two models is that BPNN-UP utilizes inputs such as BOD, P, and PO 4 3- , which is in accordance with the fact that this model covers northern part of Serbia (Vojvodina Autonomous Province) which is well-known for agricultural production and extensive use of fertilizers. Both models have shown very good agreement between measured and predicted DO (with R 2  ≥ 0.86) and demonstrated that they can effectively forecast DO content in the Danube River.

Modeling the contribution of point sources and non-point sources to Thachin River water pollution.

PubMed

Schaffner, Monika; Bader, Hans-Peter; Scheidegger, Ruth

2009-08-15

Major rivers in developing and emerging countries suffer increasingly of severe degradation of water quality. The current study uses a mathematical Material Flow Analysis (MMFA) as a complementary approach to address the degradation of river water quality due to nutrient pollution in the Thachin River Basin in Central Thailand. This paper gives an overview of the origins and flow paths of the various point- and non-point pollution sources in the Thachin River Basin (in terms of nitrogen and phosphorus) and quantifies their relative importance within the system. The key parameters influencing the main nutrient flows are determined and possible mitigation measures discussed. The results show that aquaculture (as a point source) and rice farming (as a non-point source) are the key nutrient sources in the Thachin River Basin. Other point sources such as pig farms, households and industries, which were previously cited as the most relevant pollution sources in terms of organic pollution, play less significant roles in comparison. This order of importance shifts when considering the model results for the provincial level. Crosschecks with secondary data and field studies confirm the plausibility of our simulations. Specific nutrient loads for the pollution sources are derived; these can be used for a first broad quantification of nutrient pollution in comparable river basins. Based on an identification of the sensitive model parameters, possible mitigation scenarios are determined and their potential to reduce the nutrient load evaluated. A comparison of simulated nutrient loads with measured nutrient concentrations shows that nutrient retention in the river system may be significant. Sedimentation in the slow flowing surface water network as well as nitrogen emission to the air from the warm oxygen deficient waters are certainly partly responsible, but also wetlands along the river banks could play an important role as nutrient sinks.

Inter-relationship between scaling exponents for describing self-similar river networks

NASA Astrophysics Data System (ADS)

Yang, Soohyun; Paik, Kyungrock

2015-04-01

Natural river networks show well-known self-similar characteristics. Such characteristics are represented by various power-law relationships, e.g., between upstream length and drainage area (exponent h) (Hack, 1957), and in the exceedance probability distribution of upstream area (exponent ɛ) (Rodriguez-Iturbe et al., 1992). It is empirically revealed that these power-law exponents are within narrow ranges. Power-law is also found in the relationship between drainage density (the total stream length divided by the total basin area) and specified source area (the minimum drainage area to form a stream head) (exponent η) (Moussa and Bocquillon, 1996). Considering that above three scaling relationships all refer to fundamental measures of 'length' and 'area' of a given drainage basin, it is natural to hypothesize plausible inter-relationship between these three scaling exponents. Indeed, Rigon et al. (1996) demonstrated the relationship between ɛ and h. In this study, we expand this to a more general ɛ-η-h relationship. We approach ɛ-η relationship in an analytical manner while η-h relationship is demonstrated for six study basins in Korea. Detailed analysis and implications will be presented. References Hack, J. T. (1957). Studies of longitudinal river profiles in Virginia and Maryland. US, Geological Survey Professional Paper, 294. Moussa, R., & Bocquillon, C. (1996). Fractal analyses of tree-like channel networks from digital elevation model data. Journal of Hydrology, 187(1), 157-172. Rigon, R., Rodriguez-Iturbe, I., Maritan, A., Giacometti. A., Tarboton, D. G., & Rinaldo, A. (1996). On Hack's Law. Water Resources Research, 32(11), 3367-3374. Rodríguez-Iturbe, I., Ijjasz-Vasquez, E. J., Bras, R. L., & Tarboton, D. G. (1992). Power law distributions of discharge mass and energy in river basins. Water Resources Research, 28(4), 1089-1093.

Simulating the Effects of Drainage and Agriculture on Hydrology and Sediment in the Minnesota River Basin

NASA Astrophysics Data System (ADS)

Downer, C. W.; Pradhan, N. R.; Skahill, B. E.; Banitt, A. M.; Eggers, G.; Pickett, R. E.

2014-12-01

Throughout the Midwest region of the United States, slopes are relatively flat, soils tend to have low permeability, and local water tables are high. In order to make the region suitable for agriculture, farmers have installed extensive networks of ditches to drain off excess surface water and subsurface tiles to lower the water table and remove excess soil water in the root zone that can stress common row crops, such as corn and soybeans. The combination of tiles, ditches, and intensive agricultural land practices radically alters the landscape and hydrology. Within the watershed, tiles have outlets to both the ditch/stream network as well as overland locations, where the tile discharge appears to initiate gullies and exacerbate overland erosion. As part of the Minnesota River Basin Integrated Study we are explicitly simulating the tile and drainage systems in the watershed at multiple scales using the physics-based watershed model GSSHA (Gridded Surface Subsurface Hydrologic Analysis). The tile drainage system is simulated as a network of pipes that collect water from the local water table. Within the watershed, testing of the methods on smaller basins shows the ability of the model to simulate tile flow, however, application at the larger scale is hampered by the computational burden of simulating the flow in the complex tile drain networks that drain the agricultural fields. Modeling indicates the subsurface drains account for approximately 40% of the stream flow in the Seven Mile Creek sub-basin account in the late spring and early summer when the tile is flowing. Preliminary results indicate that agricultural tile drains increase overland erosion in the Seven Mile Creek watershed.

Ecohydraulics of Strings and Beads in Bedrock Rivers

NASA Astrophysics Data System (ADS)

Wohl, E.

2016-12-01

Twenty years ago, Jack Stanford and others described rivers in bedrock canyons as resembling beads on a string when viewed in planform. The beads are relatively wide, low gradient river segments with floodplains, whereas the strings are the intervening steep, narrow river segments with minimal floodplain development. This pattern of longitudinal variations in channel and valley morphology along bedrock canyon rivers is very common, from small channels to major rivers such as the Colorado. Basic understanding of river ecosystems, as well as limited studies, indicates that the beads are more retentive and biologically productive. Although both strings and beads can provide habitat for diverse organisms, strings are more likely to serve as migration corridors, whereas beads provide spawning and nursery habitat, facilitate lateral (channel-floodplain) and vertical (channel-hyporheic) exchanges and associated habitat diversity, and retain dissolved and particulate organic matter. Recognition of the different characteristics and functions of strings and beads can be used to identify their spatial distribution along a river or within a river network and the hydraulically driven processes that sustain channel form, water quality, and biota within strings and beads. Diverse modeling approaches can then be used to quantify the fluxes of water and sediment needed to maintain these hydraulically driven processes. This conceptual framework is illustrated using examples from mountain streams in the Southern Rockies and canyon rivers in the southwestern United States.

Marginal Economic Value of Streamflow: A Case Study for the Colorado River Basin

NASA Astrophysics Data System (ADS)

Brown, Thomas C.; Harding, Benjamin L.; Payton, Elizabeth A.

1990-12-01

The marginal economic value of streamflow leaving forested areas in the Colorado River Basin was estimated by determining the impact on water use of a small change in streamflow and then applying economic value estimates to the water use changes. The effect on water use of a change in streamflow was estimated with a network flow model that simulated salinity levels and the routing of flow to consumptive uses and hydroelectric dams throughout the Basin. The results show that, under current water management institutions, the marginal value of streamflow in the Colorado River Basin is largely determined by nonconsumptive water uses, principally energy production, rather than by consumptive agricultural or municipal uses. The analysis demonstrates the importance of a systems framework in estimating the marginal value of streamflow.

The patterns of organisation and structure of interactions in a fish-parasite network of a neotropical river.

PubMed

Bellay, Sybelle; Oliveira, Edson F de; Almeida-Neto, Mário; Abdallah, Vanessa D; Azevedo, Rodney K de; Takemoto, Ricardo M; Luque, José L

2015-07-01

The use of the complex network approach to study host-parasite interactions has helped to improve the understanding of the structure and dynamics of ecological communities. In this study, this network approach is applied to evaluate the patterns of organisation and structure of interactions in a fish-parasite network of a neotropical Atlantic Forest river. The network includes 20 fish species and 73 metazoan parasite species collected from the Guandu River, Rio de Janeiro State, Brazil. According to the usual measures in studies of networks, the organisation of the network was evaluated using measures of host susceptibility, parasite dependence, interaction asymmetry, species strength and complementary specialisation of each species as well as the network. The network structure was evaluated using connectance, nestedness and modularity measures. Host susceptibility typically presented low values, whereas parasite dependence was high. The asymmetry and species strength were correlated with host taxonomy but not with parasite taxonomy. Differences among parasite taxonomic groups in the complementary specialisation of each species on hosts were also observed. However, the complementary specialisation and species strength values were not correlated. The network had a high complementary specialisation, low connectance and nestedness, and high modularity, thus indicating variability in the roles of species in the network organisation and the expected presence of many specialist species. Copyright © 2015 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

The influence of branch order on optimal leaf vein geometries: Murray's law and area preserving branching.

PubMed

Price, Charles A; Knox, Sarah-Jane C; Brodribb, Tim J

2013-01-01

Models that predict the form of hierarchical branching networks typically invoke optimization based on biomechanical similitude, the minimization of impedance to fluid flow, or construction costs. Unfortunately, due to the small size and high number of vein segments found in real biological networks, complete descriptions of networks needed to evaluate such models are rare. To help address this we report results from the analysis of the branching geometry of 349 leaf vein networks comprising over 1.5 million individual vein segments. In addition to measuring the diameters of individual veins before and after vein bifurcations, we also assign vein orders using the Horton-Strahler ordering algorithm adopted from the study of river networks. Our results demonstrate that across all leaves, both radius tapering and the ratio of daughter to parent branch areas for leaf veins are in strong agreement with the expectation from Murray's law. However, as veins become larger, area ratios shift systematically toward values expected under area-preserving branching. Our work supports the idea that leaf vein networks differentiate roles of leaf support and hydraulic supply between hierarchical orders.

NewAge: a semi-distributed hydrological model as a dynamical system, and something more.

NASA Astrophysics Data System (ADS)

Rigon, Riccardo; Franceschi, Silvia; Antonello, Andrea; Endrizzi, Stefano; Formetta, Giuseppe

2010-05-01

We describe and analyse the performances of the semi-distributed hydrological model NewAGE. This model itself is made-up of five main parts: the radiation budget estimation, the snow modelling, the evapotranspiration part, the hillslope runoff budget and the runoff aggregation in the river network, and finally the flood propagation. The model concept is based on the idea the elementary units are the hillslopes for each one the model gives the estimates of the prognostic simulated variables (one estimate for variable). Each "hillslope" does not need to coincide to the real hillslope, and can actually cover a small basin, up to some square kilometres. It constitutes the elementary "grid" element of the model. Each "hillslope" is connected to the others by the channel network. In turn, this is represented by an oriented graph, whose links are numbered through a generalisation of the Pfafstetter ordering. The topological partition of the basin is performed by a proper set of tools in JGrass. The mass budget for each hillslope is performed according to a suitable modification of Duffy (1996) dynamical model of hillslope runoff. Discharge in each link of the river network is evaluated according to Cuencas (2005). Radiation is calculated accounting for the sub-hillslope-variability in accord to a suitable scheme described in this contribution. Evapotranspiration estimation uses the Penman-Monteith formula, and includes hillslope variability in land use, soil cover and hydrological state. Flood wave propagation for the main streams can be estimated with a solver of the 1D de Saint Venant equation. Snow is modelled by a custom implementation of the Utah Energy Balance concepts. This model can simulate all the parts of the hydrological cycle, but besides being also a model of the physical processes, it also implements the infrastructure dealing with human works and reservoirs. These modelling parts are supported by appropriate ancillary modules for the treatment of the meteorological data. The various pieces of NewAGE are implemented as code components according the the OpenMI 1.4 standard, and interface to the users by means of the GIS system JGrass. It is distributed under the GPL3 license. Here we report here about two case studies made up of the model regarding the two rivers Passirio and Adige with outlet in Bozen, and covering respectively the discharge and the snow cover estimation. This last is compared to MODIS product.

River Networks As Ecological Corridors for Species, Populations and Pathogens of Water-Borne Disease

NASA Astrophysics Data System (ADS)

Rinaldo, A.

2014-12-01

River basins are a natural laboratory for the study of the integration of hydrological, ecological and geomorphological processes. Moving from morphological and functional analyses of dendritic geometries observed in Nature over a wide range of scales, this Lecture addresses essential ecological processes that take place along dendritic structures, hydrology-driven and controlled, like e.g.: population migrations and human settlements, that historically proceeded along river networks to follow water supply routes; riparian ecosystems composition that owing to their positioning along streams play crucial roles in their watersheds and in the loss of biodiversity proceeding at unprecedented rates; waterborne disease spreading, like epidemic cholera that exhibits epidemic patterns that mirror those of watercourses and of human mobility and resurgences upon heavy rainfall. Moreover, the regional incidence of Schistosomiasis, a parasitic waterborne disease, and water resources developments prove tightly related, and proliferative kidney disease in fish thrives differently in pristine and engineered watercourses: can we establish quantitatively the critical linkages with hydrologic drivers and controls? How does connectivity within a river network affect community composition or the spreading mechanisms? Does the river basin act as a template for biodiversity or for species' persistence? Are there hydrologic controls on epidemics of water-borne disease? Here, I shall focus on the noteworthy scientific perspectives provided by spatially explicit eco-hydrological studies centered on river networks viewed as ecological corridors for species, populations and pathogens of waterborne disease. A notable methodological coherence is granted by the mathematical description of river networks as the support for reactive transport. The Lecture overviews a number of topics idiosyncratically related to my own research work but ideally aimed at a coherent body of materials and methods. A theory is thus argued to emerge on the role of dendritic geometries as environmental support for ecological dynamics and processes - a fun and possibly even instructive novel research field, possibly a hotspot of eco-hydrologic research in the years to come.

Soil erosion and sediment yield, a double barrel problem in South Africa's only large river network without a dam

NASA Astrophysics Data System (ADS)

Le Roux, Jay

2016-04-01

Soil erosion not only involves the loss of fertile topsoil but is also coupled with sedimentation of dams, a double barrel problem in semi-arid regions where water scarcity is frequent. Due to increasing water requirements in South Africa, the Department of Water and Sanitation is planning water resource development in the Mzimvubu River Catchment, which is the only large river network in the country without a dam. Two dams are planned including a large irrigation dam and a hydropower dam. However, previous soil erosion studies indicate that large parts of the catchment is severely eroded. Previous studies, nonetheless, used mapping and modelling techniques that represent only a selection of erosion processes and provide insufficient information about the sediment yield. This study maps and models the sediment yield comprehensively by means of two approaches over a five-year timeframe between 2007 and 2012. Sediment yield contribution from sheet-rill erosion was modelled with ArcSWAT (a graphical user interface for SWAT in a GIS), whereas gully erosion contributions were estimated using time-series mapping with SPOT 5 imagery followed by gully-derived sediment yield modelling in a GIS. Integration of the sheet-rill and gully results produced a total sediment yield map, with an average of 5 300 t km-2 y-1. Importantly, the annual average sediment yield of the areas where the irrigation dam and hydropower dam will be built is around 20 000 t km-2 y-1. Without catchment rehabilitation, the life expectancy of the irrigation dam and hydropower dam could be 50 and 40 years respectively.

Neural network river forecasting through baseflow separation and binary-coded swarm optimization

NASA Astrophysics Data System (ADS)

Taormina, Riccardo; Chau, Kwok-Wing; Sivakumar, Bellie

2015-10-01

The inclusion of expert knowledge in data-driven streamflow modeling is expected to yield more accurate estimates of river quantities. Modular models (MMs) designed to work on different parts of the hydrograph are preferred ways to implement such approach. Previous studies have suggested that better predictions of total streamflow could be obtained via modular Artificial Neural Networks (ANNs) trained to perform an implicit baseflow separation. These MMs fit separately the baseflow and excess flow components as produced by a digital filter, and reconstruct the total flow by adding these two signals at the output. The optimization of the filter parameters and ANN architectures is carried out through global search techniques. Despite the favorable premises, the real effectiveness of such MMs has been tested only on a few case studies, and the quality of the baseflow separation they perform has never been thoroughly assessed. In this work, we compare the performance of MM against global models (GMs) for nine different gaging stations in the northern United States. Binary-coded swarm optimization is employed for the identification of filter parameters and model structure, while Extreme Learning Machines, instead of ANN, are used to drastically reduce the large computational times required to perform the experiments. The results show that there is no evidence that MM outperform global GM for predicting the total flow. In addition, the baseflow produced by the MM largely underestimates the actual baseflow component expected for most of the considered gages. This occurs because the values of the filter parameters maximizing overall accuracy do not reflect the geological characteristics of the river basins. The results indeed show that setting the filter parameters according to expert knowledge results in accurate baseflow separation but lower accuracy of total flow predictions, suggesting that these two objectives are intrinsically conflicting rather than compatible.

Nitrous oxide emissions in the Shanghai river network: implications for the effects of urban sewage and IPCC methodology.

PubMed

Yu, Zhongjie; Deng, Huanguang; Wang, Dongqi; Ye, Mingwu; Tan, Yongjie; Li, Yangjie; Chen, Zhenlou; Xu, Shiyuan

2013-10-01

Global nitrogen (N) enrichment has resulted in increased nitrous oxide (N(2)O) emission that greatly contributes to climate change and stratospheric ozone destruction, but little is known about the N(2)O emissions from urban river networks receiving anthropogenic N inputs. We examined N(2)O saturation and emission in the Shanghai city river network, covering 6300 km(2), over 27 months. The overall mean saturation and emission from 87 locations was 770% and 1.91 mg N(2)O-N m(-2) d(-1), respectively. Nitrous oxide (N(2)O) saturation did not exhibit a clear seasonality, but the temporal pattern was co-regulated by both water temperature and N loadings. Rivers draining through urban and suburban areas receiving more sewage N inputs had higher N(2)O saturation and emission than those in rural areas. Regression analysis indicated that water ammonium (NH(4)(+)) and dissolved oxygen (DO) level had great control on N(2)O production and were better predictors of N(2)O emission in urban watershed. About 0.29 Gg N(2)O-N yr(-1) N(2)O was emitted from the Shanghai river network annually, which was about 131% of IPCC's prediction using default emission values. Given the rapid progress of global urbanization, more study efforts, particularly on nitrification and its N(2)O yielding, are needed to better quantify the role of urban rivers in global riverine N(2)O emission. © 2013 John Wiley & Sons Ltd.

Metabolic principles of river basin organization.

PubMed

Rodriguez-Iturbe, Ignacio; Caylor, Kelly K; Rinaldo, Andrea

2011-07-19

The metabolism of a river basin is defined as the set of processes through which the basin maintains its structure and responds to its environment. Green (or biotic) metabolism is measured via transpiration and blue (or abiotic) metabolism through runoff. A principle of equal metabolic rate per unit area throughout the basin structure is developed and tested in a river basin characterized by large heterogeneities in precipitation, vegetation, soil, and geomorphology. This principle is suggested to have profound implications for the spatial organization of river basin hydrologic dynamics, including the minimization of energy expenditure known to control the scale-invariant characteristics of river networks over several orders of magnitude. Empirically derived, remarkably constant rates of average transpiration per unit area through the basin structure lead to a power law for the probability distribution of transpiration from a randomly chosen subbasin. The average runoff per unit area, evaluated for subbasins of a wide range of topological magnitudes, is also shown to be remarkably constant independently of size. A similar result is found for the rainfall after accounting for canopy interception. Allometric scaling of metabolic rates with size, variously addressed in the biological literature and network theory under the label of Kleiber's law, is similarly derived. The empirical evidence suggests that river basin metabolic activity is linked with the spatial organization that takes place around the drainage network and therefore with the mechanisms responsible for the fractal geometry of the network, suggesting a new coevolutionary framework for biological, geomorphological, and hydrologic dynamics.

Modeling a network of turloughs in lowland karst

NASA Astrophysics Data System (ADS)

Gill, L. W.; Naughton, O.; Johnston, P. M.

2013-06-01

In lowland karst areas of Ireland topographic depressions which get intermittently flooded on an annual cycle via groundwater sources are termed turloughs. These are sites of high ecological interest as they have communities and substrate characteristic of wetlands. The flooding in many turlough basins is due to insufficient capacity of the underground karst system to take increased flows following excessive precipitation events, causing the conduit-type network to surcharge. Continuous water level measurements have been taken in five linked turloughs in the lowland karst area of south Galway over a 3 year period. These water level fluctuations, in conjunction with river inputs and precipitation, were then used to elucidate the hydrogeological controls forming the hydraulic system beneath the ground. A model of the karst network has been developed using a pipe network model with the turloughs represented as ponds. The contribution to the karst network from diffuse flow through the epikarst via the matrix and fracture flow has also been modeled using a combination of an infiltration module and network of permeable pipes. The final model was calibrated against two separate hydrological years and in general provided a good simulation for all of the turloughs water levels particularly for the year with one main filling event. The model also accurately picked up the tidal response observed in these turloughs at shallow depths. The model has been used to predict the groundwater discharge to the coast via the main spring which had not heretofore been possible to measure, being below the sea level.

Tidal river dynamics: Implications for deltas

NASA Astrophysics Data System (ADS)

Hoitink, A. J. F.; Jay, D. A.

2016-03-01

Tidal rivers are a vital and little studied nexus between physical oceanography and hydrology. It is only in the last few decades that substantial research efforts have been focused on the interactions of river discharge with tidal waves and storm surges into regions beyond the limit of salinity intrusion, a realm that can extend inland hundreds of kilometers. One key phenomenon resulting from this interaction is the emergence of large fortnightly tides, which are forced long waves with amplitudes that may increase beyond the point where astronomical tides have become extinct. These can be larger than the linear tide itself at more landward locations, and they greatly influence tidal river water levels and wetland inundation. Exploration of the spectral redistribution and attenuation of tidal energy in rivers has led to new appreciation of a wide range of consequences for fluvial and coastal sedimentology, delta evolution, wetland conservation, and salinity intrusion under the influence of sea level rise and delta subsidence. Modern research aims at unifying traditional harmonic tidal analysis, nonparametric regression techniques, and the existing understanding of tidal hydrodynamics to better predict and model tidal river dynamics both in single-thread channels and in branching channel networks. In this context, this review summarizes results from field observations and modeling studies set in tidal river environments as diverse as the Amazon in Brazil, the Columbia, Fraser and Saint Lawrence in North America, the Yangtze and Pearl in China, and the Berau and Mahakam in Indonesia. A description of state-of-the-art methods for a comprehensive analysis of water levels, wave propagation, discharges, and inundation extent in tidal rivers is provided. Implications for lowland river deltas are also discussed in terms of sedimentary deposits, channel bifurcation, avulsion, and salinity intrusion, addressing contemporary research challenges.

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.

Implementations of Riga city water supply system founded on groundwater sources

NASA Astrophysics Data System (ADS)

Lāce, I.; Krauklis, K.; Spalviņš, A.; Laicāns, J.

2017-10-01

Drinking water for Riga city is provided by the groundwater well field complex “Baltezers, Zakumuiza, Rembergi” and by the Daugava river as a surface water source. Presently (2016), the both sources jointly supply 122 thous.metre3day-1 of drinking water. It seems reasonable to use in future only groundwater, because river water is of low quality and its treatment is expensive. The research on this possibility was done by scientists of Riga Technical university as the task drawn up by the company “Aqua-Brambis”. It was required to evaluate several scenario of the groundwater supply for Riga city. By means of hydrogeological modelling, it was found out that groundwater well fields could provide 120-122 thous.metre3day-1 of drinking water for the Riga city and it is possible further not to use water of the Daugava river. However, in order to provide more extensive use of groundwater sources, existing water distribution network shall be adapted to the change of the water sources and supply directions within the network. Safety of water supply shall be ensured. The publication may be of interest for specialists dealing with problems of water supply for large towns.

Distinctive fingerprints of erosional regimes in terrestrial channel networks

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.

2017-12-01

Satellite imagery and digital elevation maps capture the large scale morphology of channel networks attributed to long term erosional processes, such as fluvial, glacial, groundwater sapping and subglacial erosion. Characteristic morphologies associated with each of these styles of erosion have been studied in detail, but there exists a knowledge gap related to their parameterization and quantification. This knowledge gap prevents a rigorous analysis of the dominant processes that shaped a particular landscape, and a comparison across styles of erosion. To address this gap, we use previous morphological descriptions of glaciers, rivers, sapping valleys and tunnel valleys to identify and measure quantitative metrics diagnostic of these distinctive styles of erosion. From digital elevation models, we identify four geometric metrics: The minimum channel width, channel aspect ratio (longest length to channel width at the outlet), presence of undulating longitudinal profiles, and tributary junction angle. We also parameterize channel network complexity in terms of its stream order and fractal dimension. We then perform a statistical classification of the channel networks using a Principal Component Analysis on measurements of these six metrics on a dataset of 70 channelized systems. We show that rivers, glaciers, groundwater seepage and subglacial meltwater erode the landscape in rigorously distinguishable ways. Our methodology can more generally be applied to identify the contributions of different processes involved in carving a channel network. In particular, we are able to identify transitions from fluvial to glaciated landscapes or vice-versa.

Assessing river-groundwater exchange fluxes of the Wairau River, New Zealand

NASA Astrophysics Data System (ADS)

Wilson, Scott; Woehling, Thomas; Davidson, Peter

2014-05-01

Allocation limits in river-recharged aquifers have traditionally been based on static observations of river gains and losses undertaken when river flow is low. This approach to setting allocation limits does not consider the dynamic relationship between river flows and groundwater levels. Predicting groundwater availability based on a better understanding of coupled river - aquifer systems opens the possibility for dynamic groundwater allocation approaches. Numerical groundwater models are most commonly used for regional scale allocation assessments. Using these models for predicting future system states is challenging, particularly under changing management and climate scenarios. The large degree of uncertainty associated with these predictions is caused by insufficient knowledge about the heterogeneity of subsurface flow characteristics, ineffective monitoring designs, and the inability to confidently predict the spatially and temporally varying river - groundwater exchange fluxes. These uncertainties are characteristic to many coupled surface water - groundwater systems worldwide. Braided river systems, however, create additional challenges due to their highly dynamic morphological character and mobile beds which also make river flow measurements extremely difficult. This study focuses on the characterization of river - groundwater exchange fluxes along a section of the Wairau River in the Northwest of the South Island of New Zealand. The braided river recharges the Wairau Aquifer which is an important source for irrigation and municipal water requirements of the city of Blenheim. The Wairau Aquifer is hosted by the highly permeable Rapaura Formation gravels that extend to a depth of about 20 to 30 m. However, the overall thickness of the alluvial sequence forming the Wairau Plain may be up to 500 m. The landuse in the area is mainly grapes but landsurface recharge to the aquifer is considered to be considerably smaller than the recharge from the Wairau river. This study aims at the assessment of river-groundwater exchange fluxes and presents first results from data mining and analysis of river flow records, stage gaugings, groundwater head data, pumping test, and the sampling of spring flows. In addition, a methodology is presented that will allow the prediction of transient river exchange fluxes by using a Modflow model, global optimisation techniques, and techniques for quantifying predictive uncertainty which have been recently developed (Wöhling et al 2013). A long-term goal of the study is the reduction of predictive uncertainty of model predictions by optimal design of sensor networks as well as the assessment of this utility by different observation types. Preliminary results indicate that about 7 cumec from the Wairau River is recharged to the aquifer under low flow conditions. A similar volume of groundwater re-emerges as springs where groundwater is forced upwards by the confining Dillons Point Formation. References Wöhling, Th., Gosses, M.J., Leyes Pérez, M., Geiges, A., Moore, C.R., Osenbrück, K., Scott, D.M. (2013). Optimizing monitoring design to increase predictive reliability of groundwater flow models at different scales. Geophysical Research Abstracts Vol. 15, EGU2013-3981, EGU General Assembly 2013.

Nutrient inputs and hydrology together determine biogeochemical status of the Loire River (France): Current situation and possible future scenarios.

PubMed

Garnier, Josette; Ramarson, Antsiva; Billen, Gilles; Théry, Sylvain; Thiéry, Dominique; Thieu, Vincent; Minaudo, Camille; Moatar, Florentina

2018-10-01

The Grafs-Seneque/Riverstrahler model was implemented for the first time on the Loire River for the 2002-2014 period, to explore eutrophication after improvement of wastewater treatments. The model reproduced the interannual levels and seasonal trends of the major water quality variables. Although eutrophication has been impressively reduced in the drainage network, a eutrophication risk still exists at the coast, as shown by the N-ICEP indicator, pointing out an excess of nitrogen over silica and phosphorus. From maximum biomass exceeding 120 μgChla l -1 in the 1980's, we observed decreasing maximum values from 80 to 30 μgChla l -1 during the period studied. Several scenarios were explored. Regarding nutrient point sources, a low wastewater treatment scenario, similar to the situation in the 1980's, was elaborated, representing much greater pollution than the reference period (2002-2014). For diffuse sources, two agricultural scenarios were elaborated for reducing nitrogen, one with a strict application of the agricultural directives and another investigating the impact of radical structural changes in agriculture and the population's diet. Although reduced, a risk of eutrophication would remain, even with the most drastic scenario. In addition, a pristine scenario, with no human activity within the basin, was devised to assess water quality in a natural state. The impact of a change in hydrology on the Loire biogeochemical functioning was also explored according to the effect of climate change by the end of the 21st century. The EROS hydrological model was used to force Riverstrahler, considering the most pessimistic SRES A2 scenario run with the ARPEGE model. Nutrient fluxes all decreased due to a >50% reduction in the average annual discharge, overall reducing the risk of coastal eutrophication, but worsening the water quality status of the river network. The Riverstrahler model could be useful to help water managers contend with future threats in the Loire River, at the scale of its basin and at smaller nested scales. Copyright © 2018 Elsevier B.V. All rights reserved.

SE Asian freshwater fish population and networks: the impacts of climatic and environmental change on a vital resource

NASA Astrophysics Data System (ADS)

Santos, Rita; Parsons, Daniel; Cowx, Ian

2016-04-01

The Mekong River is the 10th largest freshwater river in the world, with the second highest biodiversity wealth, behind the much larger Amazon basin. The fisheries activity in the Lower Mekong countries counts for 2.7 million tons of fish per year, with an estimated value worth up to US 7 billion. For the 60 million people living in the basin, fish represent their primary source of economic income and protein intake, with an average per capita consumption estimated at 45.4 Kg. The proposed hydropower development in the basin is threatening its sustainability and resilience. Such developments affect fish migration patterns, hydrograph flood duration and magnitudes and sediment flux. Climate change is also likely to impact the basin, exacerbating the issues created by development. As a monsoonal system, the Mekong River's pronounced annual flood pulse cycle is important in creating variable habitat for fish productivity. Moreover, the annual flood also triggers fish migration and provides vital nutrients carried by the sediment flux. This paper examines the interactions between both dam development and climate change scenarios on fish habitat and habitat connectivity, with the aim of predicting how these will affect fish species composition and fisheries catch. The project will also employ Environmental DNA (eDNA) to quantify and understand the species composition of this complex and large freshwater system. By applying molecular analysis, it is possible to trace species abundance and migration patterns of fish and evaluate the ecological networks establish between an inland system. The aim of this work is to estimate, using process-informed models, the impacts of the proposed dam development and climate change scenarios on the hydrological and hydraulic conditions of habitat availability for fish. Furthermore, it will evaluate the connectivity along the Mekong and its tributaries, and the importance of maintaining these migration pathways, used by a great diversity of fish species. It will also present the preliminary findings on eDNA analysis for species composition and the ecological networks established along the river and particularly on the fish hotspot place for biodiversity, the Tonle Sap system in Cambodia. Keywords: Mekong River, climate change, fish production, dams, eDNA analysis, numerical modelling.

CrossWater - Modelling micropollutant loads from different sources in the Rhine basin

NASA Astrophysics Data System (ADS)

Moser, Andreas; Bader, Hans-Peter; Fenicia, Fabrizio; Scheidegger, Ruth; Stamm, Christian

2016-04-01

The pressure on rivers from micropollutants (MPs) originating from various sources is a growing environmental issue and requiring political regulations. The challenges for the water management are numerous, particularly for international water basins. Spatial knowledge of MP sources and the water quality are prerequisites for an effective water quality policy. In this study we analyze the sources of MPs in the international Rhine basin in Europe, and model their transport to the streams. The spatial patterns of MP loads and concentrations from different use classes are investigated with a mass flow analysis and compared to the territorial jurisdictions that shape the spatial arrangement of water management. The source area of MPs depends on the specific use of a compound. Here, we focus on i) herbicides from agricultural land use, ii) biocides from material protection on buildings and iii) human pharmaceuticals from households. The total mass of MPs available for release to the stream network is estimated from statistical application and consumption data. The available mass of MPs is spatially distributed to the catchments areas based on GIS data of agricultural land use, vector data of buildings and wastewater treatment plant (WWTP) locations, respectively. The actual release of MPs to the stream network is calculated with empirical loss rates related to river discharge for agricultural herbicides and to precipitation for biocides. For the pharmaceuticals the release is coupled to the human metabolism rates and elimination rates in WWTP. The released loads from the catchments are propagated downstream with hydraulic routing. Water flow, transport and fate of the substances are simulated within linked river reaches. Time series of herbicide concentrations and loads are simulated for the main rivers in the Rhine basin. Accordingly the loads from the primary catchments are aggregated and constitute lateral or upstream input to the simulated river reaches. Pronounced differences in the spatial patterns of concentrations in the aquatic system are observed between the different compounds. The comparison with measurements from monitoring stations along the Rhine yield satisfactory results.

Quantitative design of emergency monitoring network for river chemical spills based on discrete entropy theory.

PubMed

Shi, Bin; Jiang, Jiping; Sivakumar, Bellie; Zheng, Yi; Wang, Peng

2018-05-01

Field monitoring strategy is critical for disaster preparedness and watershed emergency environmental management. However, development of such is also highly challenging. Despite the efforts and progress thus far, no definitive guidelines or solutions are available worldwide for quantitatively designing a monitoring network in response to river chemical spill incidents, except general rules based on administrative divisions or arbitrary interpolation on routine monitoring sections. To address this gap, a novel framework for spatial-temporal network design was proposed in this study. The framework combines contaminant transport modelling with discrete entropy theory and spectral analysis. The water quality model was applied to forecast the spatio-temporal distribution of contaminant after spills and then corresponding information transfer indexes (ITIs) and Fourier approximation periodic functions were estimated as critical measures for setting sampling locations and times. The results indicate that the framework can produce scientific preparedness plans of emergency monitoring based on scenario analysis of spill risks as well as rapid design as soon as the incident happened but not prepared. The framework was applied to a hypothetical spill case based on tracer experiment and a real nitrobenzene spill incident case to demonstrate its suitability and effectiveness. The newly-designed temporal-spatial monitoring network captured major pollution information at relatively low costs. It showed obvious benefits for follow-up early-warning and treatment as well as for aftermath recovery and assessment. The underlying drivers of ITIs as well as the limitations and uncertainty of the approach were analyzed based on the case studies. Comparison with existing monitoring network design approaches, management implications, and generalized applicability were also discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison of three artificial intelligence techniques for discharge routing

NASA Astrophysics Data System (ADS)

Khatibi, Rahman; Ghorbani, Mohammad Ali; Kashani, Mahsa Hasanpour; Kisi, Ozgur

2011-06-01

SummaryThe inter-comparison of three artificial intelligence (AI) techniques are presented using the results of river flow/stage timeseries, that are otherwise handled by traditional discharge routing techniques. These models comprise Artificial Neural Network (ANN), Adaptive Nero-Fuzzy Inference System (ANFIS) and Genetic Programming (GP), which are for discharge routing of Kizilirmak River, Turkey. The daily mean river discharge data with a period between 1999 and 2003 were used for training and testing the models. The comparison includes both visual and parametric approaches using such statistic as Coefficient of Correlation (CC), Mean Absolute Error (MAE) and Mean Square Relative Error (MSRE), as well as a basic scoring system. Overall, the results indicate that ANN and ANFIS have mixed fortunes in discharge routing, and both have different abilities in capturing and reproducing some of the observed information. However, the performance of GP displays a better edge over the other two modelling approaches in most of the respects. Attention is given to the information contents of recorded timeseries in terms of their peak values and timings, where one performance measure may capture some of the information contents but be ineffective in others. Thus, this makes a case for compiling knowledge base for various modelling techniques.

A modeling assessment of the thermal regime for an urban sport fishery

USGS Publications Warehouse

Bartholow, John M.

1991-01-01

Water temperature is almost certainly a limiting factor in the maintenance of a self-sustaining rainbow trout (Oncorhynchus mykiss, formerly Salmo gairdneri) and brown trout (Salmo trutta) fishery in the lower reaches of the Cache la Poudre River near Fort Collins, Colorado, USA. Irrigation diversions dewater portions of the river, but cold reservoir releases moderate water temperatures during some periods. The US Fish and Wildlife Service’s Stream Network Temperature Model (SNTEMP) was applied to a 31-km segment of the river using readily available stream geometry and hydrological and meteorological data. The calibrated model produced satisfactory water temperature predictions (R2=0.88,P3/sec would be needed to maintain suitable summer temperatures throughout most of the study area. Such flows would be especially beneficial during weekends when current irrigation patterns reduce flows. The model indicated that increasing the riparian shade would result in little improvement in water temperatures but that decreasing the stream width would result in significant temperature reductions. Introduction of a more thermally tolerant redband trout (Oncorhynchus sp.), or smallmouth bass (Micropterus dolomieui) might prove beneficial to the fishery. Construction of deep pools for thermal refugia might also be helpful.

A coupled modelling effort to study the fate of contaminated sediments downstream of the Coles Hill deposit, Virginia, USA

NASA Astrophysics Data System (ADS)

Castro-Bolinaga, C. F.; Zavaleta, E. R.; Diplas, P.

2015-03-01

This paper presents the preliminary results of a coupled modelling effort to study the fate of tailings (radioactive waste-by product) downstream of the Coles Hill uranium deposit located in Virginia, USA. The implementation of the overall modelling process includes a one-dimensional hydraulic model to qualitatively characterize the sediment transport process under severe flooding conditions downstream of the potential mining site, a two-dimensional ANSYS Fluent model to simulate the release of tailings from a containment cell located partially above the local ground surface into the nearby streams, and a one-dimensional finite-volume sediment transport model to examine the propagation of a tailings sediment pulse in the river network located downstream. The findings of this investigation aim to assist in estimating the potential impacts that tailings would have if they were transported into rivers and reservoirs located downstream of the Coles Hill deposit that serve as municipal drinking water supplies.

Water-quality characteristics of Montana streams in a statewide monitoring network, 1999-2003

USGS Publications Warehouse

Lambing, John H.; Cleasby, Thomas E.

2006-01-01

A statewide monitoring network of 38 sites was operated during 1999-2003 in cooperation with the Montana Department of Environmental Quality to provide a broad geographic base of water-quality information on Montana streams. The purpose of this report is to summarize and describe the water-quality characteristics for those sites. Samples were collected at U.S. Geological Survey streamflow-gaging stations in the Missouri, Yellowstone, and Columbia River basins for stream properties, nutrients, suspended sediment, major ions, and selected trace elements. Mean annual streamflows were below normal during the period, which likely influenced water quality. Continuous water-temperature monitors were operated at 26 sites. The median of daily mean water temperatures for the June-August summer period ranged from 12.5 degC at Kootenai River below Libby Dam to 23.0 degC at Poplar River near Poplar and Tongue River at Miles City. In general, sites in the Missouri River basin commonly had the highest water temperatures. Median daily mean summer water temperatures at four sites (Jefferson River near Three Forks, Missouri River at Toston, Judith River near Winifred, and Poplar River near Poplar) classified as supporting or marginally supporting cold-water biota exceeded the general guideline of 19.4 degC for cold-water biota. Median daily mean temperatures at sites in the network classified as supporting warm-water biota did not exceed the guideline of 26.7 degC for warm-water biota, although several sites exceeded the warm-water guideline on several days during the summer. More...

The contribution of headwater streams to biodiversity in river networks

Treesearch

Judy L. Meyer; David L. Strayer; J. Bruce Wallace; Sue L. Eggert; Gene S. Helfman; Norman E. Leonard

2007-01-01

The diversity of life in headwater streams (intermittent, first and second order) contributes to the biodiversity of a river system and its riparian network. Small streams differ widely in physical, chemical, and biotic attributes, thus providing habitats for a range of unique species. Headwater species include permanent residents as well as migrants that travel to...

Spatial identification of tributary impacts in river networks

Treesearch

Christian E. Torgersen; Robert E. Gresswell; Douglas S. Bateman; Kelly M. Burnett

2008-01-01

The ability to assess spatial patterns of ecological conditions in river networks has been confounded by difficulties of measuring and perceiving features that are essentially invisible to observers on land and to aircraft and satellites from above. The nature of flowing water, which is opaque or at best semi-transparent, makes it difficult to visualize fine-scale...

Tests of peak flow scaling in simulated self-similar river networks

USGS Publications Warehouse

Menabde, M.; Veitzer, S.; Gupta, V.; Sivapalan, M.

2001-01-01

The effect of linear flow routing incorporating attenuation and network topology on peak flow scaling exponent is investigated for an instantaneously applied uniform runoff on simulated deterministic and random self-similar channel networks. The flow routing is modelled by a linear mass conservation equation for a discrete set of channel links connected in parallel and series, and having the same topology as the channel network. A quasi-analytical solution for the unit hydrograph is obtained in terms of recursion relations. The analysis of this solution shows that the peak flow has an asymptotically scaling dependence on the drainage area for deterministic Mandelbrot-Vicsek (MV) and Peano networks, as well as for a subclass of random self-similar channel networks. However, the scaling exponent is shown to be different from that predicted by the scaling properties of the maxima of the width functions. ?? 2001 Elsevier Science Ltd. All rights reserved.