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1

Runoff simulation in the Ferghana Valley (Central Asia) using conceptual hydrological HBV-light model  

NASA Astrophysics Data System (ADS)

Glaciers and permafrost on the ranges of the Tien Shan mountain system are primary sources of water in the Ferghana Valley. The water artery of the valley is the Syr Darya River that is formed by confluence of the Naryn and Kara Darya rivers, which originate from the mountain glaciers of the Ak-Shyrak and the Ferghana ranges accordingly. The Ferghana Valley is densely populated and main activity of population is agriculture that heavily depends on irrigation especially in such arid region. The runoff reduction is projected in future due to global temperature rise and glacier shrinkage as a consequence. Therefore, it is essential to study climate change impact on water resources in the area both for ecological and economic aspects. The evaluation of comparative contribution of small upper catchments (n=24) with precipitation predominance in discharge and the large Naryn and Karadarya River basins, which are fed by glacial melt water, to the Fergana Valley water balance under current and future climatic conditions is general aim of the study. Appropriate understanding of the hydrological cycle under current climatic conditions is significant for prognosis of water resource availability in the future. Thus, conceptual hydrological HBV-light model was used for analysing of the water balance of the small upper catchments that surround the Ferghana Valley. Three trial catchments (the Kugart River basin, 1010 km²; the Kurshab River basin, 2010 km2; the Akbura River basin, 2260 km²) with relatively good temporal quality data were chosen to setup the model. Due to limitation of daily temperature data the MODAWEC weather generator, which converts monthly temperature data into daily based on correlation with rainfall, was tested and applied for the HBV-light model.

Radchenko, Iuliia; Breuer, Lutz; Forkutsa, Irina; Frede, Hans-Georg

2013-04-01

2

Sensitivity of Low Flow Simulations by the HBV-EC Hydrological Model to the Choice of Downscaling Algorithm, Climate Predictors, and Global Climate Model  

NASA Astrophysics Data System (ADS)

Hydrological models are one of the main tools used to investigate low flows under future climate change scenarios. Climate data requirements range from high-resolution spatially gridded datasets for distributed hydrological models to site measurements for conceptual hydrological models. In either case, climatological information from coarse resolution Global Climate Models (GCMs) must be used to infer climate series at higher resolutions required by the hydrological models. This is typically done using a procedure known as climate downscaling. The effect of the choice of downscaling algorithm, synoptic-scale predictor dataset, and GCM on the sensitivity of low flow simulations by the HBV-EC hydrological model is the main focus of this study. Different statistical downscaling algorithms (an analog model, a non-parametric weather generator, and a conditional density artificial neural network), predictor datasets (drawn from global atmospheric model reanalyses), and GCMs (the Meteorological Service of Canada's CGCM2, the UK Met Office's HadCM3, and the US Department of Energy sponsored PCM) are used to drive the HBV-EC hydrological model in mountainous watersheds of British Columbia, Canada. The ability of the modeling system to reproduce low flows is validated on historical data and simulated low flows are analyzed for future climate change scenarios.

Cannon, A. J.

2006-12-01

3

Simulation of the water balance in the Elbe River basin using weather forecast data - A comparison of the hydrological models SWIM and HBV  

NASA Astrophysics Data System (ADS)

The ecohydrological model SWIM (Soil and Water Integrated Model) is applied to the German part of the Elbe River basin since 2012 on a semi-operational basis. In this context, semi-operational means that soil water balance, plant growth and runoff is simulated continuously on different spatial scales, using measured meteorological data of the previous day. In order to extend the prediction range and to include the Czech part of the river basin, we implement weather forecast data from the Global Forecast System (GFS), which is available for the years 2012?2014. At the same time we conduct simulations with the hydrological model HBV using the same input data. The consistency of the data allows a comparison of the results, which fosters the evaluation of the models and helps to improve their deficits. Initially, the calibration of both models is carried out with weather data of the last decade from the German weather service (DWD). Different parameter sets are tested and compared; uncertainties of the simulations can be shown. The validity of the results indicates the strength and weaknesses of each model and therefore determines its predictive capacity. A successful calibration and validation of the models is the basis for simulations with GFS-data of the previous two years and the prospective use of the model system for short (day)- to medium-term (week) predictions of high- and low water, of the soil water balance and of the agricultural plant growth in the Elbe river basin.

Roers, Michael; Vetter, Tobias; Hoffmann, Peter; Wechsung, Frank

2014-05-01

4

A mouse model for HBV immunotolerance and immunotherapy  

PubMed Central

Lack of an appropriate small animal model remains a major hurdle for studying the immunotolerance and immunopathogenesis induced by hepatitis B virus (HBV) infection. In this study, we report a mouse model with sustained HBV viremia after infection with a recombinant adeno-associated virus (AAV) carrying a replicable HBV genome (AAV/HBV). Similar to the clinical HBV carriers, the mice infected with AAV/HBV were sero-negative for antibodies against HBV surface antigen (HBsAg). Immunization with the conventional HBV vaccine in the presence of aluminum adjuvant failed to elicit an immune response against HBV in these mice. To identify a vaccine that can potentially circumvent this tolerance, the TLR9 agonist CpG was added to HBsAg as an adjuvant. Vaccination of mice with HBsAg/CpG induced not only clearance of viremia, but also strong antibody production and T-cell responses. Furthermore, both the DNA replication and protein expression of HBV were significantly reduced in the livers of AAV/HBV-infected mice. Accordingly, AAV/HBV-infected mice may be used as a robust model for investigating the underlying mechanism(s) of HBV immunotolerance and for developing novel immunotherapies to eradicate HBV infections.

Zhu, Danming; Peng, Hua; Su, Lishan; Fu, Yang-Xin; Zhang, Liguo

2014-01-01

5

Torrential rainfall event in Genoa: Coupled WRF-NMM and HBV model  

NASA Astrophysics Data System (ADS)

On November 4 th, 2011, the city of Genoa was affected by a torrential convective rainfall episode. The finger-shape mesoscale system remained stationary for a significant number of hours on the same area of few square kilometers. About 500 millimeters of rain, one third of the average annual precipitation amount, fell in approximately six hours. A flash flood occurred in the Bisagno river and Fereggiano creek, causing six causalities and the inundation of the Brignole area. For the catchments, where flood events usually occur in a few hours time and peak discharge generally last only a few minutes, it is necessary to use high resolution meteorological data as an input to hydrological model. The effectiveness of flood warning is dependent on the forecast accuracy of certain physical parameters, such as the peak magnitude of the flood, its timing, location and duration. The conceptual HBV rainfall - runoff models enable the estimation of these parameters and provide useful operational forecasts. This paper presents the results of coupled meteorological WRF-NMM and hydrological HBV model. Hourly quantitative precipitation forecasts, for three days ahead, were used as input to the conceptual hydrological model. HBV model was able to predict significant increase of water level with exceedance of regular defence level and exact time of the flood peak on the observed hydrological profile even weather forecast model wasn't successful in the predicition of the hourly amount of precipitation.

Ivkovic, Marija; Dekic, Ljiljana; Mihalovic, Ana

2013-04-01

6

Forecasting river discharge using coupled WRF-NMM meteorological model and HBV runoff model, case studies  

NASA Astrophysics Data System (ADS)

This paper examines two episodes of heavy rainfall and significantly increased water levels. The first case relates to the period including the beginning and the end of the third decade of June 2010 at the Kolubara river basin, where extreme rainfall led to two big flood waves on the Kolubara river, whereat water levels exceeded both regular and extraordinary flood defence and approached their historical maximum. The second case relates to the period including the end of November and the beginning of December 2010 at the Jadar river basin, where heavier precipitation caused the water levels of the basin to reach and surpass the occurrence limit (warning level). The HBV (Hydrological Bureau Waterbalance-section) rainfall/snowmelt - runoff model installed at the RHMSS uses gridded quantitative precipitation and air temperature forecast for 72 hours in advance based on meteorological weather forecast WRF-NMM mesoscale model. Nonhydrostatic Mesoscale Model (NMM) core of the Weather Research and Forecasting (WRF) system is flexible state-of-the-art numerical weather prediction model capable to describe and estimate powerful nonhydrostatic mechanism in convective clouds that cause heavy rain. The HBV model is a semi-distributed conceptual catchment model in which the spatial structure of a catchment area is not explicitly modelled. Instead, the sub-basin represents a primary modelling unit while the basin is characterised by area-elevation distribution and classification of vegetation cover and land use distributed by height zone. WRF-NMM forecast shows very good agreement with observations in terms of timing, location and amount of precipitation. They are used as input for HBV model, forecasted discharges at the output profile of the selected river basin represent model output for consideration. 1 Republic Hydrometeorological Service of Serbia

Deki?, L.; Mihalovi?, A.; Jovi?i?, I.; Vladikovi?, D.; Jerini?, J.; Ivkovi?, M.

2012-04-01

7

Preclinical evaluation of two human anti-hepatitis B virus (HBV) monoclonal antibodies in the HBV-trimera mouse model and in HBV chronic carrier chimpanzees.  

PubMed

Two human monoclonal antibodies (mAbs) against hepatitis B surface antigen (HBsAg) generated in the Trimera mouse system are described. Both mAbs 17.1.41 and 19.79.5 are of the IgG1 isotype and have high affinity constants for HBsAg binding in the range of 10(-10) mol/L. Monoclonal antibody 17.1.41 recognizes a conformational epitope on the a determinant of HBsAg whereas mAb 19.79.5 recognizes a linear one. The 2 mAbs bind to a panel of hepatitis B virus (HBV) subtypes with distinct patterns. The neutralizing activity of these antibodies was tested in 2 different animal model systems. Administration of each mAb to HBV-Trimera mice, a system that provides a mouse model for human hepatitis B infection, reduced the viral load and the percentage of HBV-DNA-positive mice in a dose-dependent manner. These 2 mAbs were more effective than a polyclonal antibody preparation (Hepatect; Biotest Pharma, Dreieich, Germany) in both inhibition of HBV liver infection and reduction of viral load. A single administration of a mixture of these mAbs into HBV chronic carrier chimpanzees resulted in immediate reduction in HBsAg levels followed by recurrence to initial levels within few days. Thus, these mAbs may be potential candidates for preventive therapy or in combination with other antiviral agents against HBV. Further studies in humans are needed to assess these mAbs in various clinical indications. PMID:10960454

Eren, R; Ilan, E; Nussbaum, O; Lubin, I; Terkieltaub, D; Arazi, Y; Ben-Moshe, O; Kitchinzky, A; Berr, S; Gopher, J; Zauberman, A; Galun, E; Shouval, D; Daudi, N; Eid, A; Jurim, O; Magnius, L O; Hammas, B; Reisner, Y; Dagan, S

2000-09-01

8

Inhibition of hepatitis B virus (HBV) gene expression and replication by HBx gene silencing in a hydrodynamic injection mouse model with a new clone of HBV genotype B  

PubMed Central

Background It has been suggested that different hepatitis B virus (HBV) genotypes may have distinct virological characteristics that correlate with clinical outcomes during antiviral therapy and the natural course of infection. Hydrodynamic injection (HI) of HBV in the mouse model is a useful tool for study of HBV replication in vivo. However, only HBV genotype A has been used for studies with HI. Methods We constructed 3 replication-competent clones containing 1.1, 1.2 and 1.3 fold overlength of a HBV genotype B genome and tested them both in vitro and in vivo. Moreover, A HBV genotype B clone based on the pAAV-MCS vector was constructed with the 1.3 fold HBV genome, resulting in the plasmid pAAV-HBV1.3B and tested by HI in C57BL/6 mice. Application of siRNA against HBx gene was tested in HBV genotype B HI mouse model. Results The 1.3 fold HBV clone showed higher replication and gene expression than the 1.1 and 1.2 fold HBV clones. Compared with pAAV-HBV1.2 (genotype A), the mice HI with pAAV-HBV1.3B showed higher HBsAg and HBeAg expression as well as HBV DNA replication level but a higher clearance rate. Application of two plasmids pSB-HBxi285 and pSR-HBxi285 expressing a small/short interfering RNA (siRNA) to the HBx gene in HBV genotype B HI mouse model, leading to an inhibition of HBV gene expression and replication. However, HBV gene expression may resume in some mice despite an initial delay, suggesting that transient suppression of HBV replication by siRNA may be insufficient to prevent viral spread, particularly if the gene silencing is not highly effective. Conclusions Taken together, the HI mouse model with a HBV genotype B genome was successfully established and showed different characteristics in vivo compared with the genotype A genome. The effectiveness of gene silencing against HBx gene determines whether HBV replication may be sustainably inhibited by siRNA in vivo.

2013-01-01

9

Estimation of instantaneous peak flow from simulated maximum daily flow using the HBV model  

NASA Astrophysics Data System (ADS)

Instantaneous peak flow (IPF) data are the foundation of the design of hydraulic structures and flood frequency analysis. However, the long discharge records published by hydrological agencies contain usually only average daily flows which are of little value for design in small catchments. In former research, statistical analysis using observed peak and daily flow data was carried out to explore the link between instantaneous peak flow (IPF) and maximum daily flow (MDF) where the multiple regression model is proved to have the best performance. The objective of this study is to further investigate the acceptability of the multiple regression model for post-processing simulated daily flows from hydrological modeling. The model based flood frequency analysis allows to consider change in the condition of the catchments and in climate for design. Here, the HBV model is calibrated on peak flow distributions and flow duration curves using two approaches. In a two -step approach the simulated MDF are corrected with a priory established regressions. In a one-step procedure the regression coefficients are calibrated together with the parameters of the model. For the analysis data from 18 mesoscale catchments in the Aller-Leine river basin in Northern Germany are used. The results show that: (1) the multiple regression model is capable to predict the peak flows with the simulated MDF data; (2) the calibrated hydrological model reproduces well the magnitude and frequency distribution of peak flows; (3) the one-step procedure outperforms the two-step procedure regarding the estimation of peak flows.

Ding, Jie; Haberlandt, Uwe

2014-05-01

10

Assimilating H-SAF and MODIS Snow Cover Data into the Conceptual Models HBV and SRM  

NASA Astrophysics Data System (ADS)

Conceptual hydrological models are widely used for operational and scientific water resources management applications in mountain catchments. However, current model-based forecasting approaches are jeopardized by input data and model uncertainties. Data assimilation provides a suitable tool to merge information from remotely sensed observations and hydrological model predictions for improving the lead time performance of streamflow forecasts in the context of operational hydrological forecasting systems. In this study, we present a novel variational approach based on Moving Horizon Estimation (MHE). It includes a highly flexible formulation of distance metrics for penalizing the introduction of noise into the model and enforcing the agreement between simulated and observed variables. Furthermore, the MHE setup shows a high robustness regarding non-equidistant, noisy and sometimes missing data and enables the modification of model input as well as state variables. In situ snowpack measurements are sparsely distributed in mountainous regions. Therefore the data limitations in combination with snowpack heterogeneity prevent a detailed understanding of the variability of snow cover and melt. Remotely sensed images offer an opportunity to supplement ground measurements for performing runoff predictions during the snowmelt season. In this context, EUMETSAT initiated the H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) project for deriving novel products from satellite data and applying it to operational hydrology. This research contributes to the H-SAF product validation by applying a generic data assimilation test bed for H-SAF snow products in comparison to snow cover data of MODIS. A preliminary performance assessment of the data assimilation framework using the conceptual models HBV and SRM with satellite derived snow data is evaluated for a snow dominated test site of 10250 km2 at the headwaters of Euphrates River in Turkey.

Sensoy, Aynur; Schwanenberg, Dirk; Sorman, Arda; Akkol, Bulut; Alvarado Montero, Rodolfo; Uysal, Gokcen

2014-05-01

11

Electroporation-mediated HBV DNA vaccination in primate models.  

PubMed

Electroporation has been shown to be an effective method to improve the efficiency of gene expression and the immunogenicity of DNA vaccines. To optimize the procedure and test for its efficacy in more clinically relevant large animal models, we studied the effects of electroporation-mediated DNA vaccination with different electro-pulse parameters in rhesus macaques. Plasmid DNA encoding the HBV preS2-S and an adjuvant plasmid encoding a fused gene of IL-2 and IFN-gamma were injected intramuscularly followed by electroporation once a month for several months. The humoral as well as cellular immune responses were closely followed for more than a year. The different electro-pulse parameters resulted in considerably different intensities in immune responses, suggesting that optimization of electroporation parameters is important in developing clinical application of DNA vaccination. PMID:18370224

Zhao, Yong-Gang; Xu, Yuhong

2008-01-01

12

A comparison of SRM and HBV models for real time runoff forecasting in the Upper Euphrates Basin, Turkey  

NASA Astrophysics Data System (ADS)

Predicting snowmelt runoff in the mountainous eastern part of Turkey at a daily time step is important in water resource management as it constitutes nearly 2/3 in volume of the total yearly runoff during spring and early summer months. Keeping track of snow dynamics as well as forecasting the amount and timing of snowmelt runoff in the headwaters of the trans-boundary Euphrates River, where large dams are located, is a crucial and challenging task concerning the practical importance and great demand for real time forecasting of melt water. In mountainous regions, data limitations prevent detailed understanding of the variability of snow cover and melt. In situ snowpack measurements are sparsely distributed relative to snowpack heterogeneity therefore, to supplement ground measurement networks, remotely sensed images of snow covered area (SCA) provide useful information for runoff prediction during the snowmelt season. SCA has been used as a direct input to hydrological models such as Snowmelt Runoff Model (SRM) or as a means of assimilating hydrologic model snowpack and checking the internal validity as in the case of HBV model. Alternative ways of handling melt water modeling using satellite derived SCA is discussed, with emphasis on the contrasting treatments in two widely used hydrologic models, SRM and HBV. The greatest similarity between the two models is that each uses a temperature index method to predict melt rate whereas the greatest difference lies in the way snow cover is handled. Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products with 500 m spatial resolution are used to derive SCA data in this study. Since the cloud obscuring problem degrades the use of satellites with optical sensors, a special combination and filtering methodology is utilized to reduce cloud coverage of the product. Both models are used to simulate runoff for the years 2001-2010 with model efficiency above 0.86 and volume difference less than 2.5%. Finally, operational snowmelt runoff forecasting is carried out for 2011 ablation season using numerical weather prediction (Mesoscale Model 5) data as forcing input variables. Discussion of results are supervised to reflect the general debates in hydrologic modeling in terms of parameters and calibration, internal validation, the value and limitations of using satellite derived and numerical weather prediction data. Key words: snow, SRM, HBV, forecasting, Upper Euphrates Basin

Sorman, A. A.; Sensoy, A.; Yamankurt, E.; Gozel, E.

2012-04-01

13

Mathematical Modeling of Watershed Hydrology  

Microsoft Academic Search

Mathematical modeling of watershed hydrology is employed to address a wide spectrum of environmental and water re- sources problems. A historical perspective of hydrologic modeling is provided, and new developments and challenges in watershed models are discussed. These include data acquisition by remote sensing and space technology, digital terrain and elevation models, chemical tracers, geographic information and data management systems,

Vijay P. Singh

2002-01-01

14

Optimal combinations of specialized conceptual hydrological models  

NASA Astrophysics Data System (ADS)

In hydrological modelling it is a usual practice to use a single lumped conceptual model for hydrological simulations at all regimes. However often the simplicity of the modelling paradigm leads to errors in represent all the complexity of the physical processes in the catchment. A solution could be to model various hydrological processes separately by differently parameterized models, and to combine them. Different hydrological models have varying performance in reproducing catchment response. Generally it cannot be represented precisely in different segments of the hydrograph: some models performed well in simulating the peak flows, while others do well in capturing the low flows. Better performance can be achieved if a model being applied to the catchment using different model parameters that are calibrated using criteria favoring high or low flows. In this work we use a modular approach to simulate hydrology of a catchment, wherein multiple models are applied to replicate the catchment responses and each "specialist" model is calibrated according to a specific objective function which is chosen in a way that forces the model to capture certain aspects of the hydrograph, and outputs of models are combined using so-called "fuzzy committee". Such multi-model approach has been already previously implemented in the development of data driven and conceptual models (Fenicia et al., 2007), but its perfomance was considered only during the calibration period. In this study we tested an application to conceptual models in both calibration and verification period. In addition, we tested the sensitivity of the result to the use of different weightings used in the objective functions formulations, and memberbship functions used in the committee. The study was carried out for Bagamati catchment in Nepal and Brue catchment in United Kingdoms with the MATLAB-based implementation of HBV model. Multi-objective evolutionary optimization genetic algorithm (Deb, 2001) was used to find Pareto-optimal solutions, and Adaptive cluster covering algorithm (Solomatine, 1999) was used to find the globally optimal solution. The study confirmed the validity of the multi-model approach that lead to much better performance in calidation period (compared to the use of a single model), and 1.3-16.7% better performance in validation.

Kayastha, Nagendra; Lal Shrestha, Durga; Solomatine, Dimitri

2010-05-01

15

Complexity regularized hydrological model selection  

NASA Astrophysics Data System (ADS)

Ill-posed hydrological model selection problems (that may be unstable or have non-unique solutions) are regularized with hydrological model complexity as the stabilizer. We propose and apply a notion of model complexity, based on Vapnik-Chervonenkis generalization theory, to complexity regularized hydrologic model selection. Better hydrologic models (better performance on future unseen data) on small sample sizes are identified using complexity regularized model selection than when using traditional model selection (without regularization) while both converge in performance for large samples (i.e. regularized model selection is 'consistent'). Case studies using SAC-SMA, SIXPAR and flexible model structures are used to 1) compute and compare model complexities of different model structures, 2) demonstrate the 'consistency' of complexity regularized model selection and 3) demonstrate that regularized model selection identifies the best model structure (out of a set of competing structures) on small sample sizes better than un-regularized model selection.

Arkesteijn, Liselot; Pande, Saket; Savenije, Hubert

2014-05-01

16

A comparison of SRM and HBV models for real time runoff forecasting in the Upper Euphrates Basin, Turkey  

NASA Astrophysics Data System (ADS)

Predicting snowmelt runoff in the mountainous eastern part of Turkey at a daily timescale is important in water resource management as it constitutes nearly 2/3 in volume of the total yearly runoff during spring and early summer months. Keeping track of snow dynamics and forecasting the amount and the timing of snowmelt runoff in the headwaters of the trans-boundary Euphrates River, where large dams are located, is a crucial and challenging task concerning the practical importance and great demand for real time forecasting of meltwater. In mountainous regions, data limitations prevent detailed understanding of the variability of snow cover and melt. In situ snowpack measurements are sparsely distributed relative to snowpack heterogeneity therefore to supplement ground measurement networks, remotely derived images of snow covered area (SCA) provides useful information for runoff prediction during the snowmelt season. SCA has been used as a direct input to hydrological models such as Snowmelt Runoff Model (SRM) or as a means of updating hydrologic model snowpack simulations and checking the internal validity of snowmelt runoff model as in the case of HBV model. Alternative ways of handling meltwater modeling using satellite derived SCA is discussed, with emphasis on the contrasting treatments in two widely used models, HBV and SRM. The greatest similarity between two models is that each uses a temperature index method to predict melt rate and the greatest difference between the models is in the way snow cover is handled. Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products with 500 m spatial resolution are used to derive SCA data in this study. Since the cloud obscuring problem degrades the use of satellites with optical sensors, a special combination and filtering methodology is used to reduce cloud coverage of the product. Both models are used to simulate runoff for the years 2003-2010 with model efficiency above 0.85 and volume difference around 2.5% and model parameters are calibrated in these applications. Finally, an operational snowmelt runoff forecasting is carried out for 2011 ablation season using numerical weather prediction Mesoscale Model 5 (MM5) data as forcing input variables. Discussion of results are supervised to reflect the general debates in hydrological modeling in terms of parameters and calibration, internal validation, the value and limitations of using satellite derived data.

Sorman, A.; Sensoy, A.; Gozel, E.; Yamankurt, E.; Sorman, U.

2011-12-01

17

Modeling the effects of covalently closed circular DNA and dendritic cells in chronic HBV infection.  

PubMed

The contribution of covalently closed circular DNA (cccDNA) and dendritic cells (DCs) to the progression of chronic hepatitis B virus (HBV) infection remains largely unknown. A dynamic model with seven cell types was proposed based on the biological mechanisms of viral replication and the host immune response. The cccDNA self-amplification rate was found to be closely related to both the basic reproduction number of the virus and the immune response. The combination of the cccDNA self-amplification rate and the initial activated DC count induces rich dynamics. Applying our model to the clinical data of untreated patients, we found that chronic patients have a high cccDNA self-amplification rate. For antiviral treatment, an overall drug effectiveness was introduced and the critical drug effectiveness was obtained. The model predicts that timely long-term therapy is needed to reduce the symptoms of HBV and to maintain the benefits of treatment. PMID:24816182

Li, Qiang; Lu, Furong; Deng, Guohong; Wang, Kaifa

2014-09-21

18

Model Calibration in Watershed Hydrology  

NASA Technical Reports Server (NTRS)

Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh

2009-01-01

19

Effect of Trichinella spiralis infection on the immune response to HBV vaccine in a mouse model.  

PubMed

Vaccination is the most effective and cost-effective way to treat hepatitis B virus (HBV) infection. Collective data suggest that helminth infections affect immune responses to some vaccines. Therefore, it is important to reveal the effects of helminth infections on the efficacy of protective vaccines in countries with highly prevalent helminth infections. In the present work, effects of Trichinella spiralis infection on the protective efficacy of HBV vaccine in a mouse model were investigated. This study demonstrated that the enteric stage of T. spiralis infection could inhibit the proliferative response of spleen lymphocytes to hepatitis B surface antigen (HBsAg) and lead to lower levels of anti-HBsAg antibodies, interferon-?, and interleukin (IL)-2, along with higher levels of IL-4 and IL-5. However, these immunological differences are absent in the muscle stage of T. spiralis infection. The results suggest that the muscle stage of T. spiralis infection does not affect the immune response to HBV vaccination, while the enteric-stage infection results in a reduced immune response to HBsAg. PMID:23883369

Guan, Fei; Hou, Xiao; Nie, Ge; Xiao, Yan; Zhang, Qi; Liu, Wen-qi; Li, Yong-long; Lei, Jia-hui

2013-10-01

20

Hydrological model coupling with ANNs  

NASA Astrophysics Data System (ADS)

Model coupling in general is necessary but complicated. Scientists develop and improve conceptual models to represent physical processes occurring in nature. The next step is to translate these concepts into a mathematical model and finally into a computer model. Problems may appear if the knowledge, encapsulated in a computer model and software program is needed for another purpose. In integrated water management this is often the case when connections between hydrological, hydraulic or ecological models are required. Coupling is difficult for many reasons, related to data formats, compatibility of scales, ability to modify source codes, etc. Hence, there is a need for an efficient and cost effective approach to model-coupling. One solution for model coupling is the use of Artificial Neural Networks (ANNs). The ANN can be used as a fast and effective model simulator which can connect different models. In this paper ANNs are used to couple four different models: a rainfall runoff model, a river channel routing model, an estuarine salt intrusion model, and an ecological model. The coupling as such has proven to be feasible and efficient. However the salt intrusion model appeared difficult to model accurately in an ANN. The ANN has difficulty to represent both short term (tidal) and long term (hydrological) processes.

Kamp, R. G.; Savenije, H. H. G.

2006-12-01

21

Rangeland Hydrology and Erosion Model  

NASA Astrophysics Data System (ADS)

Soil loss rates on rangelands are considered one of the few quantitative indicators for assessing rangeland health and conservation practice effectiveness. An erosion model to predict soil loss specific for rangeland applications has been needed for many years. Most erosion models were developed from croplands where the hydrologic and erosion processes are different, largely due to much higher levels of heterogeneity in soil and plant properties at the plot scale and the consolidated nature of the soils. The Rangeland Hydrology and Erosion Model (RHEM) was designed to fill that need. RHEM is an event-based model that estimates runoff, erosion, and sediment delivery rates and volumes at the spatial scale of the hillslope and the temporal scale of a single rainfall event. It represents erosion processes under normal and fire-impacted rangeland conditions, it adopts a new splash erosion and thin sheet-flow transport equation developed from rangeland data, and it links the model hydrologic and erosion parameters with rangeland plant communities by providing a new system of parameter estimation equations based on 204 plots at 49 rangeland sites distributed across 15 western U.S. states. Recent work on the model is focused on representing intra-storm dynamics, using stream-power as the driver for detachment by flow, and deriving parameters for after-fire conditions.

Nearing, Mark; Pierson, Fred; Hernandez, Mariano; Al-Hamdan, Osama; Weltz, Mark; Spaeth, Ken; Wei, Haiyan; Stone, Jeff

2013-04-01

22

Incorporating hydrologic semantic information for interoperable GIS with hydrologic model  

Microsoft Academic Search

Component-based approach has been identified as an efficient way to integrate GIS and hydrologic models. Current existing specifications such as OpenGIS or IOS\\/TC 211 provide a vessel to achieve this goal. However, there is a gap between what is provided in these specifications and what is needed for GIS-hydrologic model integration. Existing specifications provide general semantics for spatial domain, while

Chen-Chieh Feng; Alexandre Sorokine

2001-01-01

23

Hydrological model coupling with ANNs  

NASA Astrophysics Data System (ADS)

There is an increasing need for model coupling. However, model coupling is complicated. Scientists develop and improve models to represent physical processes occurring in nature. These models are built in different software programs required to run the model. A software program or application represents part of the system knowledge. This knowledge is however encapsulated in the program and often difficult to access. In integrated water resources management it is often necessary to connect hydrological, hydraulic or ecological models. Model coupling can in practice be difficult for many reasons related to data formats, compatibility of scales, ability to modify source codes, etc. Hence, there is a need for an efficient and cost effective approach to model-coupling. Artificial neural networks (ANNs) can be used as an alternative to replace a model and simulate the model's output and connect it to other models. In this paper, we investigate an alternative to traditional model coupling techniques. ANNs are four different models: a rainfall runoff model, a river channel routing model, an estuarine salt intrusion model, and an ecological model. The output results of each model is simulated by a neural network that is trained on corresponding input and output data sets. The models are connected in cascade and their input and output variables are connected. To test the results of the coupled neural network also a coupled system of four sub-system models has been set-up. These results have been compared to the results of the coupled neural networks. The results show that it is possible to train neural networks and connect these models. The results of the salt intrusion model was however not very accurate. It was difficult for the neural network to represent both short term (tidal) and long term (hydrological) processes.

Kamp, R. G.; Savenije, H. H. G.

2007-12-01

24

Exploring the effect of spatial disaggregation of conceptual hydrologic models for improved flow forecasting  

NASA Astrophysics Data System (ADS)

The availability of gridded climatic data, high resolution Digital Elevation Maps (DEM), soil, land-use and land-cover data has motivated researchers to exploit these data for more accurate distributed hydrologic modeling. However, with increased disaggregation there is the introduction of numerous parameters and conceptualized processes that are unobservable. In this study we explore the advantage of employing spatially distributed climatic and geographic information in the context of a disaggregated conceptual hydrologic modeling framework by developing distributed model versions for three hydrologic models: HYMOD (Hydrologic Model), HBV (Hydrologiska Byrans Vattenbalansavdelning), and SAC-SMA (Sacramento Soil Moisture Accounting). This study proposes a general framework for building a distributed conceptual hydrological model by coupling a rainfall-runoff model to a routing model which is based on the formularized sub-basin unit hydrograph and the linearized Saint-Venant equation. To deal with a very large number of model parameters resulting from the distributed system modeling approach, hydrological similarity and landscape classification derived from the geospatial database is used to reduce the complexity in the process of model parameter estimation. Tests for the Iowa River basin show that three distributed models outperform lumped model versions in terms of reproducing observed streamflow for both calibration and validation periods. Model calibration strategies informed by geospatial information yield flow predictions comparable to the fully distributed model simulations. Results from this study are encouraging and indicate that the proposed framework holds promise for making improved predictions of hydrologic system response.

Wi, S.; Brown, C. M.

2013-12-01

25

Hydrological Modeling of Continental-Scale Basins  

NASA Astrophysics Data System (ADS)

Hydrological models at continental scales are traditionally used for water resources planning. However, continental-scale hydrological models may be useful in assessing the impacts from future climate change on catchment hydrology and water resources or from human activity on hydrology and biogeochemical cycles at large scales. Development of regional-scale terrestrial hydrological models will further our understanding of the Earth's water cycle. Continental scales allow for better understanding of the geographic distribution of land-atmospheric moisture fluxes, improved water management at continental scales, better quantification of the impact of human activity and climate change on the water cycle, and improved simulation of weather and climate.

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

26

Committee of machine learning predictors of hydrological models uncertainty  

NASA Astrophysics Data System (ADS)

In prediction of uncertainty based on machine learning methods, the results of various sampling schemes namely, Monte Carlo sampling (MCS), generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), particle swarm optimization (PSO) and adaptive cluster covering (ACCO)[1] used to build a predictive models. These models predict the uncertainty (quantiles of pdf) of a deterministic output from hydrological model [2]. Inputs to these models are the specially identified representative variables (past events precipitation and flows). The trained machine learning models are then employed to predict the model output uncertainty which is specific for the new input data. For each sampling scheme three machine learning methods namely, artificial neural networks, model tree, locally weighted regression are applied to predict output uncertainties. The problem here is that different sampling algorithms result in different data sets used to train different machine learning models which leads to several models (21 predictive uncertainty models). There is no clear evidence which model is the best since there is no basis for comparison. A solution could be to form a committee of all models and to sue a dynamic averaging scheme to generate the final output [3]. This approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model HBV in the Nzoia catchment in Kenya. [1] N. Kayastha, D. L. Shrestha and D. P. Solomatine. Experiments with several methods of parameter uncertainty estimation in hydrological modeling. Proc. 9th Intern. Conf. on Hydroinformatics, Tianjin, China, September 2010. [2] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013. [3] N., Kayastha, J. Ye, F. Fenicia, V. Kuzmin, and D. P. Solomatine. Fuzzy committees of specialized rainfall-runoff models: further enhancements and tests. Hydrol. Earth Syst. Sci., 17, 4441-4451, 2013

Kayastha, Nagendra; Solomatine, Dimitri

2014-05-01

27

Integration of Local Hydrology into Regional Hydrologic Simulation Model  

NASA Astrophysics Data System (ADS)

South Florida hydrology is dominated by the Central and South Florida (C&SF) Project that is managed to provide flood protection, water supply and environmental protection. A complex network of levees canals and structures provide these services to the individual drainage basins. The landscape varies widely across the C&SF system, with corresponding differences in the way water is managed within each basin. Agricultural areas are managed for optimal crop production. Urban areas maximize flood protection while maintaining minimum water levels to protect adjacent wetlands and local water supplies. "Natural" areas flood and dry out in response to the temporal distribution of rainfall. The evaluation of planning, regulation and operational issues require access to a simulation model that captures the effects of both regional and local hydrology. The Regional Simulation Model (RSM) uses a "pseudo-cell" approach to integrate local hydrology within the context of a regional hydrologic system. A 2-dimensional triangulated mesh is used to represent the regional surface and ground water systems and a 1-dimensional canal network is superimposed onto this mesh. The movement of water is simulated using a finite volume formulation with a diffusive wave approximation. Each cell in the triangulated mesh has a "pseudo-cell" counterpart, which represents the same area as the cell, but it is conceptualized such that it simulates the localized hydrologic conditions Protocols have been established to provide an interface between a cell and its pseudo-cell counterpart. . A number of pseudo-cell types have already been developed and tested in the simulation of Water Conservation Area 1 and several have been proposed to deal with specific local issues in the Southwest Florida Feasibility Study. This presentation will provide an overview of the overall RSM design, describe the relationship between cells and pseudo-cells, and illustrate how pseudo-cells are be used to simulate agriculture, urban and wetland hydrology.

Van Zee, R. J.; Lal, W. A.

2002-05-01

28

Multiscale Parameter Regionalization of a Grid-based Hydrologic Model  

NASA Astrophysics Data System (ADS)

Integrated water resources planning and management at the mesoscale requires, among other things of a parsimonious and distributed hydrologic model able to reproduce not only the discharge hydrograph at any gauged or ungauged location but also the spatio-temporal distribution of state variables such as soil moisture. Furthermore, this model should be able to take into account changes in land cover and climate as well as management practices. The state-of-the-art with respect to these issues, however, is not yet satisfactory. More specifically, existing models suffer from overparametrization; the lack of an effective technique to integrate the spatial heterogeneity of soils, vegetation, and topography; the non-transferability of model parameters to ungauged basins; and a considerably large execution time. The main goal of this study is to present and validate a multiscale regionalization technique integrated into a grid-based mesoscale hydrologic model (mHM) aiming to address these issues simultaneously. mHM is based on accepted hydrological conceptualizations and require three levels of spatial information: level-2 for the climatic information, level-1 for the state variables of the model, and level-0 for physiographic input data such as soil textures, land cover, elevation, and geological formations. Their spatial resolution varies from (1000-5000)m, (500-1000)m, and (50-100)m respectively. Model parameters at level-1 are location and time dependent. They are estimated through upscaling operators that link level-0 information with global transfer-function parameters, which in turn are found through optimization. The functional relationships constituting these operators are based on process understanding or empirical evidence. Results obtained for 34 basins located in Germany indicated that this regionalization technique contributed not only to reduce significatively the number of free parameters but also to ensure their transferability to ungauged basins. The Nash-Sutcliffe Efficiency (NSE) of mHM was on average 6% greater than that obtained with the standard HBV model but required 85% less effective parameters to calibrate. The HBV model was regionalized with the standard homogeneous response unit (HRU) concept. Moreover, uncertainty and leave-on-out crossvalidation tests showed that this technique produced acceptable streamflow predictions in target basins which were assumed ungauged during crossvalidation. The NSE in the calibration and crossvalidation phases ranged between 0.70 to 0.85 and between 0.55 to 0.75 respectively. Additionally, soil moisture patterns compared well against proxies derived from daily MODIS images (NASA).

Samaniego, L.; Kumar, R.; Attinger, S.

2008-12-01

29

The Central Valley Hydrologic Model  

NASA Astrophysics Data System (ADS)

Historically, California’s Central Valley has been one of the most productive agricultural regions in the world. The Central Valley also is rapidly becoming an important area for California’s expanding urban population. In response to this competition for water, a number of water-related issues have gained prominence: conjunctive use, artificial recharge, hydrologic implications of land-use change, subsidence, and effects of climate variability. To provide information to stakeholders addressing these issues, the USGS made a detailed assessment of the Central Valley aquifer system that includes the present status of water resources and how these resources have changed over time. The principal product of this assessment is a tool, referred to as the Central Valley Hydrologic Model (CVHM), that simulates surface-water flows, groundwater flows, and land subsidence in response to stresses from human uses and from climate variability throughout the entire Central Valley. The CVHM utilizes MODFLOW combined with a new tool called “Farm Process” to simulate groundwater and surface-water flow, irrigated agriculture, land subsidence, and other key processes in the Central Valley on a monthly basis. This model was discretized horizontally into 20,000 1-mi2 cells and vertically into 10 layers ranging in thickness from 50 feet at the land surface to 750 feet at depth. A texture model constructed by using data from more than 8,500 drillers’ logs was used to estimate hydraulic properties. Unmetered pumpage and surface-water deliveries for 21 water-balance regions were simulated with the Farm Process. Model results indicate that human activities, predominately surface-water deliveries and groundwater pumping for irrigated agriculture, have dramatically influenced the hydrology of the Central Valley. These human activities have increased flow though the aquifer system by about a factor of six compared to pre-development conditions. The simulated hydrology reflects spatial and temporal variability in climate, land-use changes, and available surface-water deliveries. For example, the droughts of 1976-77 and 1987-92 led to reduced streamflow and surface-water deliveries and increased evapotranspiration and groundwater pumpage throughout most of the valley, resulting in a decrease in groundwater storage. Since the mid-1990s, annual surface-water deliveries generally have exceeded groundwater pumpage, resulting in an increase or no change in groundwater storage throughout most of the valley. However, groundwater is still being removed from storage during most years in the southern part of the Central Valley. The CVHM is designed to be coupled with Global Climate Models to forecast the potential supply of surface-water deliveries, demand for groundwater pumpage, potential subsidence, and changes in groundwater storage in response to different climate-change scenarios. The detailed database on texture properties coupled with CVHM's ability to simulate the combined effects of recharge and discharge make CVHM particularly useful for assessing water-management plans, such as conjunctive water use, conservation of agriculture land, and land-use change. In the future, the CVHM could be used in conjunction with optimization models to help evaluate water-management alternatives to effectively utilize the available water resources.

Faunt, C.; Belitz, K.; Hanson, R. T.

2009-12-01

30

Regionalization of a Macroscale Hydrological Model.  

National Technical Information Service (NTIS)

A methodology is presented for regionalization of the parameters of a macroscale land surface hydrologic model (the two-layer variable infiltration capacity model, VIC-2L) for the Arkansas-Red River basin using station hydrological and meteorologic data a...

F. Abdulla

1995-01-01

31

Hydrologic Modeling of Boreal Forest Ecosystems  

NASA Technical Reports Server (NTRS)

This study focused on the hydrologic response, including vegetation water use, of two test regions within the Boreal-Ecosystem-Atmosphere Study (BOREAS) region in the Canadian boreal forest, one north of Prince Albert, Saskatchewan, and the other near Thompson, Manitoba. Fluxes of moisture and heat were studied using a spatially distributed hydrology soil-vegetation-model (DHSVM).

Haddeland, I.; Lettenmaier, D. P.

1995-01-01

32

Hydrological model selection: A Bayesian alternative  

NASA Astrophysics Data System (ADS)

The evaluation and comparison of hydrological models has long been a challenge to the practicing hydrological community. No single model can be identified as ideal over the range of possible hydrological situations. With the variety of models available, hydrologic modelers are faced with the problem of determining which model is best applied to a catchment for a particular modeling exercise. The model selection problem is well documented in hydrologic studies, but a broadly applicable as well as theoretically and practically sound method for comparing model performance does not exist in the literature. Bayesian statistical inference, with computations carried out via Markov chain Monte Carlo (MCMC) methods, offers an attractive alternative to conventional model selection methods allowing for the combination of any preexisting knowledge about individual models and their respective parameters with the available catchment data to assess both parameter and model uncertainty. The aim of this study is to present a method by which hydrological models may be compared in a Bayesian framework. The study builds on previous work (Marshall et al., 2004) in which a Bayesian approach implemented using MCMC algorithms was presented as a simple and efficient basis for assessing parameter uncertainty in hydrological models. In this study, a model selection framework is developed in which an adaptive Metropolis algorithm is used to calculate the model's posterior odds. The model used to illustrate our approach is a version of the Australian Water Balance Model (Boughton, 1993) reformulated such that it can have a flexible number of soil moisture storages. To assess the model selection method in a controlled setting, artificial runoff data were created corresponding to a known model configuration. These data were used to evaluate the accuracy of the model selection method and its sensitivity to the size of the sample being used. An application of the Bayesian model identification methodology to 11 years of daily streamflow data from the Murrumbidgee River at Mittagang Crossing in southeastern Australia concludes our study.

Marshall, Lucy; Nott, David; Sharma, Ashish

2005-10-01

33

Snow hydrology in a general circulation model  

NASA Technical Reports Server (NTRS)

A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

Marshall, Susan; Roads, John O.; Glatzmaier, Gary

1994-01-01

34

Impacts of Operator Order in Hydrological Models  

NASA Astrophysics Data System (ADS)

Operator-Splitting errors are inherent in many hydrological models and can lead to computational inefficiencies, parameter estimation issues and inaccurate model results. A detailed study of the operator splitting errors produced by standard implementations of VIC and TOPMODEL has been performed both to assess their significance and to evaluate methods to correct them. Both VIC and TOPMODEL have been incorporated into RAVEN, an object-oriented hydrological model developed at the University of Waterloo. RAVEN has been developed to model hydrological processes using flexible numerical algorithms. RAVEN's structure is specifically designed to separate the numerical methods from the conceptual design to provide flexibility and to allow a separation of the numerics from the physical representations. The advantages of this numerical and conceptual separation has led to a better understanding of the impacts that operator splitting has on existing hydrological models and has allowed for improvements within models that increase accuracy and minimize errors.

Snowdon, A. P.; Craig, J. R.

2009-05-01

35

Covariance Models for Hydrological Applications  

NASA Astrophysics Data System (ADS)

This methodological contribution aims to present some new covariance models with applications in the stochastic analysis of hydrological processes. More specifically, we present explicit expressions for radially symmetric, non-differentiable, Spartan covariance functions in one, two, and three dimensions. The Spartan covariance parameters include a characteristic length, an amplitude coefficient, and a rigidity coefficient which determines the shape of the covariance function. Different expressions are obtained depending on the value of the rigidity coefficient and the dimensionality. If the value of the rigidity coefficient is much larger than one, the Spartan covariance function exhibits multiscaling. Spartan covariance models are more flexible than the classical geostatatistical models (e.g., spherical, exponential). Their non-differentiability makes them suitable for modelling the properties of geological media. We also present a family of radially symmetric, infinitely differentiable Bessel-Lommel covariance functions which are valid in any dimension. These models involve combinations of Bessel and Lommel functions. They provide a generalization of the J-Bessel covariance function, and they can be used to model smooth processes with an oscillatory decay of correlations. We discuss the dependence of the integral range of the Spartan and Bessel-Lommel covariance functions on the parameters. We point out that the dependence is not uniquely specified by the characteristic length, unlike the classical geostatistical models. Finally, we define and discuss the use of the generalized spectrum for characterizing different correlation length scales; the spectrum is defined in terms of an exponent ?. We show that the spectrum values obtained for exponent values less than one can be used to discriminate between mean-square continuous but non-differentiable random fields. References [1] D. T. Hristopulos and S. Elogne, 2007. Analytic properties and covariance functions of a new class of generalized Gibbs random fields, IEEE Transactions on Information Theory, 53(12), 4667 - 4679. [2] D. T. Hristopulos and M. Zukovic, 2011. Relationships between correlation lengths and integral scales for covariance models with more than two parameters, Stochastic Environmental Research and Risk Assessment, 25(1), 11-19. [3] D. T. Hristopulos, 2014. Radial Covariance Functions Motivated by Spatial Random Field Models with Local Interactions, arXiv:1401.2823 [math.ST] .

Hristopulos, Dionissios

2014-05-01

36

The skill of seasonal ensemble low flow forecasts for four different hydrological models  

NASA Astrophysics Data System (ADS)

This paper investigates the skill of 90 day low flow forecasts using two conceptual hydrological models and two data-driven models based on Artificial Neural Networks (ANNs) for the Moselle River. One data-driven model, ANN-Indicator (ANN-I), requires historical inputs on precipitation (P), potential evapotranspiration (PET), groundwater (G) and observed discharge (Q), whereas the other data-driven model, ANN-Ensemble (ANN-E), and the two conceptual models, HBV and GR4J, use forecasted meteorological inputs (P and PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low flow forecasts without any meteorological forecasts as input (ANN-I) and five different cases of seasonal meteorological forcing: (1) ensemble P and PET forecasts; (2) ensemble P forecasts and observed climate mean PET; (3) observed climate mean P and ensemble PET forecasts; (4) observed climate mean P and PET and (5) zero P and ensemble PET forecasts as input for the other three models (GR4J, HBV and ANN-E). The ensemble P and PET forecasts, each consisting of 40 members, reveal the forecast ranges due to the model inputs. The five cases are compared for a lead time of 90 days based on model output ranges, whereas the four models are compared based on their skill of low flow forecasts for varying lead times up to 90 days. Before forecasting, the hydrological models are calibrated and validated for a period of 30 and 20 years respectively. The smallest difference between calibration and validation performance is found for HBV, whereas the largest difference is found for ANN-E. From the results, it appears that all models are prone to over-predict low flows using ensemble seasonal meteorological forcing. The largest range for 90 day low flow forecasts is found for the GR4J model when using ensemble seasonal meteorological forecasts as input. GR4J, HBV and ANN-E under-predicted 90 day ahead low flows in the very dry year 2003 without precipitation data, whereas ANN-I predicted the magnitude of the low flows better than the other three models. The results of the comparison of forecast skills with varying lead times show that GR4J is less skilful than ANN-E and HBV. Furthermore, the hit rate of ANN-E is higher than the two conceptual models for most lead times. However, ANN-I is not successful in distinguishing between low flow events and non-low flow events. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.

Demirel, M. C.; Booij, M. J.; Hoekstra, A. Y.

2014-05-01

37

A national hydrological model for New Zealand  

NASA Astrophysics Data System (ADS)

New Zealand is a fascinating laboratory for hydrological research. The land area of New Zealand is relatively small (269,000 km2), but within this area there are large differences in precipitation (300 to 12,000 mm/year), vegetation (rainforest, grassland, and desert), and geology (sandstone, pumice, and limestone). Snow can be an important component of the hydrological budget in the Southern Alps, and streamflow in many parts of New Zealand is affected by natural and managed lakes. River forms vary from steep mountain torrents to wide, braided, gravel beds. There are increasing demands for the available water resources and increasing vulnerability to floods, and a national hydrological model is needed for both water resource assessments and flood forecasting. This presentation discusses the use of research conducted as part of the Problem of Ungauged Basins (PUB) initiative to build a national hydrological model for New Zealand. The research has two main steps: (1) evaluate model simulations in experimental watersheds and use internal catchment observations of soil moisture, groundwater levels, and streamflow to identify appropriate model structure(s) and model parameters; and (2) evaluate the spatial patterns of nationwide model simulations and use hydrological classification systems to understand spatial differences in model performance. Nationwide hydrological datasets and modeling systems are already developed in New Zealand, and we invite the community to use this "virtual laboratory" for their own research.

Clark, M. P.; Martinez, G.; McMillan, H.; Jackson, B.; Gupta, H. V.; Goodrich, D.; Srinivasan, M.; Schmidt, J.; Woods, R.

2008-12-01

38

Landsat imagery for hydrologic modeling  

NASA Technical Reports Server (NTRS)

The cost and effectiveness of developing land cover information derived from Landsat imagery for hydrologic studies are compared with the cost and effectiveness of conventional sources. The analysis shows that the conventional and Landsat methods are nearly equally effective in providing adequate land cover data for hydrologic studies. The total cost effectiveness analysis demonstrates that the conventional method is cost effective for a study area of less than 26 sq km and that the Landsat method is to be preferred for areas of more than 26 sq km.

Taylor, R. S.; Shubinski, R. P.; George, T. S.

1980-01-01

39

Disentangling uncertainties in distributed hydrological modeling  

NASA Astrophysics Data System (ADS)

The quantification of uncertainty in hydrologic modeling is a difficult task, as it arises from a combination of physical measurement errors, errors due to different temporal and spatial scales, and errors in the mathematical description of hydrologic processes. In this work we present an efficient tool to explicitly quantify, by means of sequentially assimilating data, the principal sources of uncertainty in hydrologic models, namely parameter, precipitation, potential evapotranspiration, and structural model uncertainty. Sequential data assimilation is performed using a particle filter that combines stochastic universal resampling and kernel smoothing with local shrinkage to improve its performance in comparison to traditional basic importance sampling filters. Precipitation, potential evapotranspiration, and structural model uncertainty are introduced into the assimilation process using multiplicative error models. To illustrate the approach the particle filter is applied to a large-scale distributed hydrological model of the Rhine river. Posterior diagnostic of the model performance and the underlying statistical assumptions of residual errors demonstrate that the posterior distributions can be considered as reliable. Posterior distributions of the precipitation, potential evapotranspiration, and structural model multipliers are used to identify whether a systematic bias for the two input variables as well as for structural model error exists. Furthermore, the distributions illustrate that uncertainty from those sources can be reduced significantly in comparison to the prior assumptions and that they can potentially provide hints about the principal deficiencies of the hydrologic model. An evaluation of the predictive capabilities of the hydrologic model illustrates that considering parameter, precipitation, potential evapotranspiration, and structural model uncertainty appears to be sufficient to characterize the principal sources of error and that the herein presented approach provides a valuable tool to characterize uncertainties in hydrologic models.

Salamon, Peter; Feyen, Luc

2010-05-01

40

ARMA Model identification of hydrologic time series  

Microsoft Academic Search

In recent years, ARMA models have become popular for modeling geophysical time series in general and hydrologic time series in particular. The identification of the appropriate order of the model is an important stage in ARMA modeling. Such model identification is generally based on the autocorrelation and partial autocorrelation functions, although recently improvements have been obtained using the inverse autocorrelation

J. D. Salas; J. T. B. Obeysekera

1982-01-01

41

Hydrologic Models for Inverse Climate Change Impact Modeling  

Microsoft Academic Search

It is expected that the global climate change will have significant impacts on the regime of hydrologic extremes. As a consequence, the design and management of water resource systems will have to adapt to the changing hydrologic extremes. An inverse approach to the modeling of hydrologic risk and vulnerability to changing climatic conditions was developed in this project to improve

Juraj M. Cunderlik; Slobodan P. Simonovic

42

Atmospheric model data for macroscale hydrology  

Microsoft Academic Search

Conventional climate observation networks are often deficient in both quantity and quality of data for macroscale hydrological modelling. In this sense we regard a basin as macroscale if it exceeds 10?000km2. Atmospheric models such as general circulation models (GCM) and numerical weather prediction models (NWP) provide alternative sources of data in such cases. While there are many questions concerning the

G. W Kite; U Haberlandt

1999-01-01

43

Quantile hydrologic model selection and uncertainty assessment  

NASA Astrophysics Data System (ADS)

Inapplicability of state of the art hydrological models due to scarce data motivates the need for a modeling approach that can be well constrained to available data and still model dominant processes. Such an approach requires embedded model relationships to be simple and parsimonious in parameters for robust model selection. Simplicity in functional relationship is also important from water management point of view if these models are to be coupled with economic system models for meaningful policy assessment. We propose a semi-distributed approach wherein we model already known dominant processes in dryland areas of Western India (evaporation, Hortonian overland flows, transmission loses and subsurface flows) in a simple but constrained manner through mathematical programming of relevant equations and constraints. Diverse data sources such as GRACE, MERRA reanalysis data, FAO soil texture map and even Indian Agricultural Census data are used. Such a modeling approach allows uncertainty quantification through quantile parameter estimation, which we present in this talk. Quantile estimation transfers uncertainty due to hydrologic model misspecification or data uncertainty, based on quantiles of residuals, onto parameters of the hydrologic model with a fixed structure. An adaptation of quantile regression to parsimonious hydrologic model estimation, this frequentist approach seeks to complement existing Bayesian approaches to model parameter and prediction uncertainty.

Pande, S.; Keyzer, M. A.; Savenije, H.; Gosain, A. K.

2010-12-01

44

HYDROLOGIC MODELING OF THE RIO GRANDE BASIN  

Microsoft Academic Search

In this study we investigate the use of the NOAH model along with NLDAS2 forcing in building a hydrological model of the Rio Grande basin to study the effect of climate variability and change on water availability in the basin. The model was run retrospectively for the period 2002 to June 2009. This paper describes the steps taken in building

C. PRAKASH KHEDUN

45

On the Use of Models in Hydrology.  

ERIC Educational Resources Information Center

This discussion article addresses the nature of models used in hydrology. It proposes a minimalist classification of models into two categories: models built on data from observations of the processes involved, and those for which there are no observation data on any of these processes, at the scale of interest. (LZ)

de Marsily, G.

1994-01-01

46

Hydrologic design of a wetland: advantages of continuous modeling  

Microsoft Academic Search

A continuous hydrologic model for constructed or depressional wetlands, intended as a design tool to supplement event-based hydrologic methods, uses reservoir routing methods and is driven by daily rainfall and watershed inflows. Simulated daily hydrology provides annual and monthly water balances, hydroperiod distributions, flood frequency distributions, soil exceedance values for hydrologic plant suitability and retention time distributions. The model was

Kenneth D. Konyha; Douglas T. Shaw; Kurt W. Weiler

1995-01-01

47

Balancing model complexity and measurements in hydrology  

NASA Astrophysics Data System (ADS)

The Data Processing Inequality implies that hydrological modeling can only reduce, and never increase, the amount of information available in the original data used to formulate and calibrate hydrological models: I(X;Z(Y)) ? I(X;Y). Still, hydrologists around the world seem quite content building models for "their" watersheds to move our discipline forward. Hydrological models tend to have a hybrid character with respect to underlying physics. Most models make use of some well established physical principles, such as mass and energy balances. One could argue that such principles are based on many observations, and therefore add data. These physical principles, however, are applied to hydrological models that often contain concepts that have no direct counterpart in the observable physical universe, such as "buckets" or "reservoirs" that fill up and empty out over time. These not-so-physical concepts are more like the Artificial Neural Networks and Support Vector Machines of the Artificial Intelligence (AI) community. Within AI, one quickly came to the realization that by increasing model complexity, one could basically fit any dataset but that complexity should be controlled in order to be able to predict unseen events. The more data are available to train or calibrate the model, the more complex it can be. Many complexity control approaches exist in AI, with Solomonoff inductive inference being one of the first formal approaches, the Akaike Information Criterion the most popular, and Statistical Learning Theory arguably being the most comprehensive practical approach. In hydrology, complexity control has hardly been used so far. There are a number of reasons for that lack of interest, the more valid ones of which will be presented during the presentation. For starters, there are no readily available complexity measures for our models. Second, some unrealistic simplifications of the underlying complex physics tend to have a smoothing effect on possible model outcomes, thereby preventing the most obvious results of over-fitting. Thirdly, dependence within and between time series poses an additional analytical problem. Finally, there are arguments to be made that the often discussed "equifinality" in hydrological models is simply a different manifestation of the lack of complexity control. In turn, this points toward a general idea, which is actually quite popular in sciences other than hydrology, that additional data gathering is a good way to increase the information content of our descriptions of hydrological reality.

Van De Giesen, N.; Schoups, G.; Weijs, S. V.

2012-12-01

48

Multi-criteria evaluation of hydrological models  

NASA Astrophysics Data System (ADS)

Over the last years, there is a tendency in the hydrological community to move from the simple conceptual models towards more complex, physically/process-based hydrological models. This is because conceptual models often fail to simulate the dynamics of the observations. However, there is little agreement on how much complexity needs to be considered within the complex process-based models. One way to proceed to is to improve understanding of what is important and unimportant in the models considered. The aim of this ongoing study is to evaluate structural model adequacy using alternative conceptual and process-based models of hydrological systems, with an emphasis on understanding how model complexity relates to observed hydrological processes. Some of the models require considerable execution time and the computationally frugal sensitivity analysis, model calibration and uncertainty quantification methods are well-suited to providing important insights for models with lengthy execution times. The current experiment evaluates two version of the Framework for Understanding Structural Errors (FUSE), which both enable running model inter-comparison experiments. One supports computationally efficient conceptual models, and the second supports more-process-based models that tend to have longer execution times. The conceptual FUSE combines components of 4 existing conceptual hydrological models. The process-based framework consists of different forms of Richard's equations, numerical solutions, groundwater parameterizations and hydraulic conductivity distribution. The hydrological analysis of the model processes has evolved from focusing only on simulated runoff (final model output), to also including other criteria such as soil moisture and groundwater levels. Parameter importance and associated structural importance are evaluated using different types of sensitivity analyses techniques, making use of both robust global methods (e.g. Sobol') as well as several alternative local sensitivity analysis methods. The latter methods can yield similar results, however they are much more computationally frugal than the global methods and often are better suited to analysis of complex models. Simple models are used to compare the global and local methods, and insights used to interpret results for complex model for which the local methods are much more convenient. The analyses are carried out for a medium-sized catchment (200 km2) in the Belgian Ardennes, for which meteorological, fluxnet data, in situ soil moisture and groundwater time series are available.

Rakovec, Oldrich; Clark, Martyn; Weerts, Albrecht; Hill, Mary; Teuling, Ryan; Uijlenhoet, Remko

2013-04-01

49

Approaches to modelling hydrology and ecosystem interactions  

NASA Astrophysics Data System (ADS)

As the pressures of industry, agriculture and mining on groundwater resources increase there is a burgeoning un-met need to be able to capture these multiple, direct and indirect stresses in a formal framework that will enable better assessment of impact scenarios. While there are many catchment hydrological models and there are some models that represent ecological states and change (e.g. FLAMES, Liedloff and Cook, 2007), these have not been linked in any deterministic or substantive way. Without such coupled eco-hydrological models quantitative assessments of impacts from water use intensification on water dependent ecosystems under changing climate are difficult, if not impossible. The concept would include facility for direct and indirect water related stresses that may develop around mining and well operations, climate stresses, such as rainfall and temperature, biological stresses, such as diseases and invasive species, and competition such as encroachment from other competing land uses. Indirect water impacts could be, for example, a change in groundwater conditions has an impact on stream flow regime, and hence aquatic ecosystems. This paper reviews previous work examining models combining ecology and hydrology with a view to developing a conceptual framework linking a biophysically defensable model that combines ecosystem function with hydrology. The objective is to develop a model capable of representing the cumulative impact of multiple stresses on water resources and associated ecosystem function.

Silberstein, Richard P.

2014-05-01

50

ARMA Model Identification of Hydrologic Time Series  

NASA Astrophysics Data System (ADS)

In recent years, ARMA models have become popular for modeling geophysical time series in general and hydrologic time series in particular. The identification of the appropriate order of the model is an important stage in ARMA modeling. Such model identification is generally based on the autocorrelation and partial autocorrelation functions, although recently improvements have been obtained using the inverse autocorrelation and the inverse partial autocorrelation functions. This paper demonstrates the use of the generalized partial autocorrelation function (GPAF) and the R and S functions of Gray et al. (1978) for ARMA model identification of hydrologic time series. These functions are defined, and some recursive relations are given for ease of computation. All three functions, when presented in tabular form, have certain characteristic patterns that are useful in ARMA model identification. Several examples are included to demonstrate the usefulness of the proposed identification technique. Actual applications are made using the Saint Lawrence River and Nile River annual streamflow series.

Salas, J. D.; Obeysekera, J. T. B.

1982-08-01

51

Remote sensing applications in hydrological modelling  

Microsoft Academic Search

Previous studies have suggested that remotely sensed data should provide major benefits to hydrology and water resources and yet there are few case studies that show practical benefits. One of the reasons for this is the lack of tools to convert remotely sensed data to the type of information useful to water resource systems operators. Hydro- logical models can play

G. W. KITE; A. PIETRONIRO

1997-01-01

52

Perspectives in Modelling Climate-Hydrology Interactions  

NASA Astrophysics Data System (ADS)

Various land-atmosphere coupling mechanisms exist that may lead to large-scale impacts on climate and hydrology. Some of them are still less understood and not adequately represented in state-of-the-art climate modelling. But, as the current generation of climate models enables consideration and implementation of important coupling processes, the present study provides perspectives for the modelling of relevant climate-hydrology interactions. On a more short-term perspective, these comprise anthropogenic land use and especially irrigation, which has been shown that it may even affect remote regions. On a long-term perspective, the coupling of hydrology to carbon cycle and vegetation becomes important, specifically the dynamics of permafrost and wetlands. Here, we present a review of current knowledge combined with some exemplary studies from a large-scale point of view. Therefore, we focus on climate-hydrology interactions that are relevant on scales utilized in the current or forthcoming global and regional climate modelling exercises.

Hagemann, Stefan; Blome, Tanja; Saeed, Fahad; Stacke, Tobias

2014-05-01

53

Catchment classification by means of hydrological models  

NASA Astrophysics Data System (ADS)

An important hydrological objective is catchment classification that will serve as a basis for the regionalisation of discharge parameters or model parameters. The main task of this study is the development and assessment of two classification approaches with respect to their efficiency in catchment classification. The study area in western Germany comprises about 80 catchments that range in size from 8 km2 up to 1500 km2, covering a wide range of geological substrata, soils, landscapes and mean annual precipitation. In a first approach Self Organising Maps (SOMs) use discharge characteristics or catchment characteristics to classify the catchments of the study area. Next, a reference hydrological model calibrates the catchments of the study area and tests the possibilities of parameter transfer. Compared to the transfer of parameters outside a class, for most catchments the model performance improves when parameters within a class are transferred. Thus, it should be possible to distinguish catchment classes by means of a hydrological model. The classification results of the SOM are compared to the classification results of the reference hydrological model in order to determine the latter validity. The second approach builds on the first approach in such a way that it uses the Superflex Modelling Framework instead of only one reference model. Within this framework multiple conceptual model structures can be calibrated and adapted. Input data for each calibration of a catchment are hourly time series of runoff, precipitation and evaporation for at least eight years. The calibration of multiple models for each catchment and their comparison allows for the assessment of the influence of different model structures on model performance. Learning loops analyse model performance and adapt model structures accordingly with a view to performance improvement. The result of the modelling exercise is a best performing model structure for each catchment that serves as a basis for catchment description and clustering. Hence, the classes do not only represent a distinctive hydrological regime, but also provide information on specific quantitative aspects that are directly linked to a certain model structure. The clustering that is based on model structures or model parameters are validated by the classifications based on SOM and are thus related to physiographic and climatic catchment properties and runoff behaviour, which provides insight into catchment functioning. Clustering based on model structures can be a fast and simple way of catchment classification. A database consistently relates input data and output data; model structures and model performance and allows formulating distinctive processes that are attached to a class. Thus, the final result of the study is a powerful classification tool that helps to formulate generalizations based on observations and testable hypotheses (i.e. model structures).

Hellebrand, Hugo; Ley, Rita; Casper, Markus

2013-04-01

54

Optimum Grid Size for Hydrological Modeling  

NASA Astrophysics Data System (ADS)

Grids are used to account for the spatial variability and heterogeneity in a physical watershed and are established through appropriate spatial scales to characterize conditions such as topography, landuse and soil properties for hydrological modeling. The current approach for determining grid sizes are often difficult to quantify and encourages the use of equal grid size throughout the watershed regardless of the varying landscape. Studies have shown that as catchment heterogeneity and spatial variability become more complex, the hydrological processes become highly variable with varying topography. This result in a catchment within a watershed showing strong localized hydrological characteristics. In this study we introduce a novel approach to determine grid size based on landscape topography for hydrological modeling. A 30m resolution elevation and watershed boundary data obtained from USGS was used in the Patuxent Watershed. The optimum grid resolution (UCellres) was found to be a function of the catchment area (Sarea) and elevation range (ElevRange) and is expressed as: UCellres = 43.339 + 0.00000002Sarea - 0.0807ElevRange. The GLM model showed a non-linear inverse, relationship between the optimum grid and elevation range indicating decreasing elevation range with increasing grid sizes. A statistical analysis of the model gave an RMSE of 0.9, a coefficient of variation of 0.07 and a relative error of 0.02. The GLM was applied to a neighboring watershed and results showed that each catchment can have unique grid sizes relative to its topography within the watershed. This finding indicate that in topography dominated watershed, individual catchments can be reasonably analyzed at different grid sizes on a localize scale to effectively model the hydrology of a watershed.

Damalie, R.; Yoon, J.

2012-12-01

55

TUWmodel: an educational hydrologic model in R  

NASA Astrophysics Data System (ADS)

In order to show the advantages of using hydrologic models in R environment, particularly for educational purposes, we have implemented a conceptual rainfall-runoff model, originally written in Fortran language into R. This hydrologic model is used in many scientific studies and operational engineering applications in Austria. The model consisting of a snow, a soil moisture and a flow routing routine and run on a daily time step in a lumped or a semi-lumped way. The R environment allows to compile and use this model on different platforms and operating system, taking advantage of many additional routines already available in R (i.e. visualisation or optimisation tools). In this poster we present a set of examples that are used in a graduate level course on engineering hydrology at the Vienna University of Technology, which include: - Multi-objective calibration of the model; - Manual vs. automatic calibration; - Visualisation of model outputs and efficiencies; - Model application in ungauged catchments; - Operational runoff forecast. The flexibility of R is ideal for education, since students can easily play with the extensive list of existing functionalities and define new functions and extensions.

Parajka, J.; Rogger, M.; Kobler, U.; Salinas, J.; Nester, T.; Bloeschl, G.

2013-12-01

56

High Performance Computing for Hydrological Modelling  

NASA Astrophysics Data System (ADS)

A hydrological model represents a simplification of a variety of complex mechanisms occurring in nature at different scales. Some physical phenomena at certain scales are not considered in the set of parameters either because they are deemed unimportant or because they cannot be measured. Hidden variables can be represented by applying stochastic modeling which relates parameters to probability distributions. By this approach, methods of improving parameter sets have been developed. So, a possible way of determining the optimal combination of parameters is to simulate an important set of possible parameters. This requires a considerable number of simulations that exceeds the capabilities of traditional computation. For example, the systematic exploration of the objective function structure of the four-parameter model MEDOR( a daily Rainfall-Runoff Model), specific to the Mediterranean climate, requires 1,476,800 simulations which needs 29.9 hours using a single processor where as this computation only requires 58 minutes when 40 processors are used. The importance of modeling in hydrology is to develop aspects of hydrological models using High Performance Computing (HPC), to utilize the most efficient algorithms on the parallel target architecture in order to combine the algorithmic and the hardware speedup in the optimal way. High Performance Computing, called the "Grand Challenges", requires interdisciplinarity. The combination of Multi-Processor Vector Machines, Massively Parallel Processors, and Parallelism can be exploited by using networks of workstations creating an opportunity to couple single-media models and explore data assimilation issues at the same time. The question is how existing methods and models, specifically hydrological spatial simulations, could be adapted or modified to work in such an environment. A theoretical design is proposed to integrate simulation modules and existing visualisation tools in a heterogeneous parallel computing network to create a dynamic interactive system where users can display and manipulate remote data in a transparent fashion.

Timus, E.

2004-05-01

57

Towards Better Coupling of Hydrological Simulation Models  

NASA Astrophysics Data System (ADS)

Standards for model interoperability and scientific workflow software provide techniques and tools for coupling hydrological simulation models. However, model builders are yet to realize the benefits of these and continue to write ad hoc implementations and scripts. Three case studies demonstrate different approaches to coupling models, the first using tight interfaces (OpenMI), the second using a scientific workflow system (Trident) and the third using a tailored execution engine (Delft Flood Early Warning System - Delft-FEWS). No approach was objectively better than any other approach. The foremost standard for coupling hydrological models is the Open Modeling Interface (OpenMI), which defines interfaces for models to interact. An implementation of the OpenMI standard involves defining interchange terms and writing a .NET/Java wrapper around the model. An execution wrapper such as OatC.GUI or Pipistrelle executes the models. The team built two OpenMI implementations for eWater Source river system models. Once built, it was easy to swap river system models. The team encountered technical challenges with versions of the .Net framework (3.5 calling 4.0) and with the performance of the execution wrappers when running daily simulations. By design, the OpenMI interfaces are general, leaving significant decisions around the semantics of the interfaces to the implementer. Increasingly, scientific workflow tools such as Kepler, Taverna and Trident are able to replace custom scripts. These tools aim to improve the provenance and reproducibility of processing tasks. In particular, Taverna and the myExperiment website have had success making many bioinformatics workflows reusable and sharable. The team constructed Trident activities for hydrological software including IQQM, REALM and eWater Source. They built an activity generator for model builders to build activities for particular river systems. The models were linked at a simulation level, without any daily time-step feedbacks. There was no obvious way to add daily time-step feedbacks without incurring a considerable performance penalty. The Delft-FEWS system connects hydrological models for flood warnings and forecasts in a workflow system. It provides a range of custom facilities for connecting real-time data services. A Delft-FEWS system was constructed to connect a series of eWater Source hydrological models using the batch forecast mode to orchestrate a time-stepping system. The system coupled a series of river models running daily through a service interface. The implementation did not easily support interoperability with other models; however, using command line calls and the file-system did allow a level of language independence. The case-studies covered the coupling of hydrological models through tight interfaces (OpenMI), broad scientific workflow software (Trident) and a tailored execution engine (Delft-FEWS). We found that no approach was objectively better than any other approach. OpenMI had the most flexible interfaces, Trident the best handling of provenance and Delft-FEWS provided a significant set of tools for ingesting and transforming data. The case studies revealed a need for stable execution wrappers, patterns for efficient cross-language interoperability, targeted semantics for hydrological simulation and better handling of daily simulation.

Penton, D.; Stenson, M.; Leighton, B.; Bridgart, R.

2012-12-01

58

Grid based calibration of SWAT hydrological models  

NASA Astrophysics Data System (ADS)

The calibration and execution of large hydrological models, such as SWAT (soil and water assessment tool), developed for large areas, high resolution, and huge input data, need not only quite a long execution time but also high computation resources. SWAT hydrological model supports studies and predictions of the impact of land management practices on water, sediment, and agricultural chemical yields in complex watersheds. The paper presents the gSWAT application as a web practical solution for environmental specialists to calibrate extensive hydrological models and to run scenarios, by hiding the complex control of processes and heterogeneous resources across the grid based high computation infrastructure. The paper highlights the basic functionalities of the gSWAT platform, and the features of the graphical user interface. The presentation is concerned with the development of working sessions, interactive control of calibration, direct and basic editing of parameters, process monitoring, and graphical and interactive visualization of the results. The experiments performed on different SWAT models and the obtained results argue the benefits brought by the grid parallel and distributed environment as a solution for the processing platform. All the instances of SWAT models used in the reported experiments have been developed through the enviroGRIDS project, targeting the Black Sea catchment area.

Gorgan, D.; Bacu, V.; Mihon, D.; Rodila, D.; Abbaspour, K.; Rouholahnejad, E.

2012-07-01

59

A physically-based Distributed Hydrologic Model for Tropical Catchments  

Microsoft Academic Search

Hydrological models are mathematical formulations intended to represent observed hydrological processes in a watershed. Simulated watersheds in turn vary in their nature based on their geographic location, altitude, climatic variables and geology and soil formation. Due to these variations, available hydrologic models vary in process formulation, spatial and temporal resolution and data demand. Many tropical watersheds are characterized by extensive

N. A. Abebe; F. L. Ogden

2010-01-01

60

Spatial resolution considerations for urban hydrological modelling  

NASA Astrophysics Data System (ADS)

Hydrological model simulations can be applied to evaluate the performance of low impact development (LID) tools in urban areas. However, the assessment for large-scale urban areas remains a challenge due to the required high spatial resolution and limited availability of field measurements for model calibration. This study proposes a methodology to parameterize a hydrological model (SWMM) with sufficiently high spatial resolution and direct accessibility of model parameters for LID performance simulation applicable to a large-scale ungauged urban area. Based on calibrated high-resolution models for three small-scale study catchments (6-12 ha), we evaluated how constraints implied by large-scale urban modelling, such as data limitations, affect the model results. The high-resolution surface representation, resulting in subcatchments of uniform surface types, reduced the number of calibration parameters. Calibration conducted independently for all catchments yielded similar parameter values for same surface types in each study catchment. These results suggest the applicability of the parameter values calibrated for high resolution models to be regionalized to larger, ungauged urban areas. The accessibility of surface specific model parameters for LID simulation is then also retained. Conducted perturbations in spatial resolution through sewer network truncation showed that while the runoff volume was mostly unaffected by resolution perturbations, lower resolutions resulted in over-simulation of peak flows due to excessively rapid catchment response to storm events. Our results suggest that a hydrological model where parameter values are adopted from high-resolution models and that is developed based on a minimum conduit diameter of 300 mm provides good simulation performance and is applicable to large-scale urban areas with reasonable effort.

Krebs, G.; Kokkonen, T.; Valtanen, M.; Setälä, H.; Koivusalo, H.

2014-05-01

61

Hydrological Modelling in Ungauged Watersheds.  

National Technical Information Service (NTIS)

A version of MILHY in which the Curve Number procedure for runoff generation is replaced by a finite difference infiltration scheme is presented. The revised model (MILHY2) is applied in an ungauged context to five catchments in the United States. It is s...

M. G. Anderson S. Howes

1986-01-01

62

Hydrology  

ERIC Educational Resources Information Center

The past year saw a re-emphasis on the practical aspects of hydrology due to regional drought patterns, urban flooding, and agricultural and energy demands on water resources. Highlights of hydrologic symposia, publications, and events are included. (MA)

Sharp, John M., Jr.

1978-01-01

63

Modelling hydrological consequences of climate change—Progress and challenges  

NASA Astrophysics Data System (ADS)

The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps: (1) use of general circulation models (GCMs) to provide future global climate scenarios under the effect of increasing greenhouse gases, (2) use of downscaling techniques (both nested regional climate models, RCMs, and statistical methods) for “downscaling” the GCM output to the scales compatible with hydrological models, and (3) use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.

Xu, Chong-Yu; Widén, Elin; Halldin, Sven

2005-11-01

64

Modeling of aggregated hydrologic time series  

NASA Astrophysics Data System (ADS)

The concept of aggregation of the most commonly used models of seasonal hydrologic time series is the main subject discussed herein. The PAR(1) and PARMA(1, 1) models are assumed for representing the seasonal series and their equivalent stationarity and invertibility conditions are given. Likewise explicit expressions are given for determining the periodic covariance structure of such models and the concept of aggregation is illustrated by deriving the model of the corresponding annual series. Since the models of the seasonal series dictate the type of model of the annual series, then a unique structural linkage in the usual linear disaggregation model may be obtained in closed form. Seasonal and annual flows of the Niger River are used to illustrate some of the estimation procedures based on the foregoing aggregation approach.

Obeysekera, J. T. B.; Salas, J. D.

1986-10-01

65

Evaluating spatial patterns in hydrological modeling  

NASA Astrophysics Data System (ADS)

Recent advances in hydrological modeling towards fully distributed grid based model codes, increased availability of spatially distributed data (remote sensing and intensive field studies) and more computational power allow a shift towards a spatial model evaluation away from the traditional aggregated evaluation. The consideration of spatially aggregated observations, in form of river discharge, in the evaluation process does not ensure a correct simulation of catchment-inherent distributed variables. The integration of spatial data and hydrological models is limited due to a lack of suitable metrics to evaluate similarity of spatial patterns. This study is engaged with the development of a novel set of performance metrics that capture spatial patterns and go beyond global statistics. The metrics are required to be easy, flexible and especially targeted to compare observed and simulated spatial patterns of hydrological variables. Four quantitative methodologies for comparing spatial patterns are brought forward: (1) A fuzzy set approach that incorporates both fuzziness of location and fuzziness of category. (2) Kappa statistic that expresses the similarity between two maps based on a contingency table (error matrix). (3) An extended version of (2) by considering both fuzziness in location and fuzziness in category. (4) Increasing the information content of a single cell by aggregating neighborhood cells at different window sizes; then computing mean and standard deviation. The identified metrics are tested on observed and simulated land surface temperature maps in a groundwater dominated catchment in western Denmark. The observed data originates from the MODIS satellite and MIKE SHE, a coupled and fully distributed hydrological model, serves as the modelling tool. Synthetic land surface temperature maps are generated to further address strengths and weaknesses of the metrics. The metrics are tested in different parameter optimizing frameworks, where they are defined as objective functions individually and collectively. Additionally discharge data, representing a different observational dataset, is included in the optimization process which enables a multi constrained evaluation of the model. This allows testing different optimization frameworks under consideration of observable spatial patterns and discharge data which represents a spatially aggregated catchment observation.

Koch, Julian; Stisen, Simon; Høgh Jensen, Karsten

2014-05-01

66

Attributing spatial patterns of hydrological model performance  

NASA Astrophysics Data System (ADS)

Global hydrological models and land surface models are used to understand and simulate the global terrestrial water cycle. They are, in particular, applied to assess the current state of global water resources, to identify anthropogenic pressures on the global water system, and to assess impacts of global and climate change on water resources. Especially in data-scarce regions, the growing availability of remote sensing products, e.g. GRACE estimates of changes in terrestrial water storage, evaporation or soil moisture estimates, has added valuable information to force and constrain these models as they facilitate the calibration and validation of simulated states and fluxes other than stream flow at large spatial scales. Nevertheless, observed discharge records provide important evidence to evaluate the quality of water availability estimates and to quantify the uncertainty associated with these estimates. Most large scale modelling approaches are constrained by simplified physical process representations and they implicitly rely on the assumption that the same model structure is valid and can be applied globally. It is therefore important to understand why large scale hydrological models perform good or poor in reproducing observed runoff and discharge fields in certain regions, and to explore and explain spatial patterns of model performance. We present an extensive evaluation of the global water model WaterGAP (Water - Global Assessment and Prognosis) to simulate 20th century discharges. The WaterGAP modeling framework comprises a hydrology model and several water use models and operates in its current version, WaterGAP3, on a 5 arc minute global grid and . Runoff generated on the individual grid cells is routed along a global drainage direction map taking into account retention in natural surface water bodies, i.e. lakes and wetlands, as well as anthropogenic impacts, i.e. flow regulation and water abstraction for agriculture, industry and domestic purposes as calculated by the water use models. Simulated discharges for the period 1958-2001 are evaluated against more than 1500 observed discharge records provided by the Global Runoff Data Centre (GRDC). Globally, the selected gauging stations differ substantially in terms of upstream area (3000 -- 3.6 mill sqkm) and their available time series (between 5 and > 100 yrs). We assess the model performance by applying complementary metrics such as Nash-Sutcliffe-Efficiency or water balance related coefficients. Moreover, based on these metrics, we investigate if and how physiographic catchment characteristics and climate conditions impact model efficiency and identify possible underlying determinants of spatial patterns of model performance.

Eisner, S.; Malsy, M.; Flörke, M.

2013-12-01

67

A novel TK-NOG based humanized mouse model for the study of HBV and HCV infections.  

PubMed

The immunodeficient mice transplanted with human hepatocytes are available for the study of the human hepatitis viruses. Recently, human hepatocytes were also successfully transplanted in herpes simplex virus type-1 thymidine kinase (TK)-NOG mice. In this study, we attempted to infect hepatitis virus in humanized TK-NOG mice and urokinase-type plasminogen activator-severe combined immunodeficiency (uPA-SCID) mice. TK-NOG mice were injected intraperitoneally with 6 mg/kg of ganciclovir (GCV), and transplanted with human hepatocytes. Humanized TK-NOG mice and uPA/SCID mice were injected with hepatitis B virus (HBV)- or hepatitis C virus (HCV)-positive human serum samples. Human hepatocyte repopulation index (RI) estimated from human serum albumin levels in TK-NOG mice correlated well with pre-transplantation serum ALT levels induced by ganciclovir treatment. All humanized TK-NOG and uPA-SCID mice injected with HBV infected serum developed viremia irrespective of lower replacement index. In contrast, establishment of HCV viremia was significantly more frequent in TK-NOG mice with low human hepatocyte RI (<70%) than uPA-SCID mice with similar RI. Frequency of mice spontaneously in early stage of viral infection experiment (8weeks after injection) was similar in both TK-NOG mice and uPA-SCID mice. Effects of drug treatment with entecavir or interferon were similar in both mouse models. TK-NOG mice thus useful for study of hepatitis virus virology and evaluation of anti-viral drugs. PMID:24140055

Kosaka, Keiichi; Hiraga, Nobuhiko; Imamura, Michio; Yoshimi, Satoshi; Murakami, Eisuke; Nakahara, Takashi; Honda, Yoji; Ono, Atsushi; Kawaoka, Tomokazu; Tsuge, Masataka; Abe, Hiromi; Hayes, C Nelson; Miki, Daiki; Aikata, Hiroshi; Ochi, Hidenori; Ishida, Yuji; Tateno, Chise; Yoshizato, Katsutoshi; Sasaki, Tamito; Chayama, Kazuaki

2013-11-01

68

A novel approach to parameter uncertainty analysis of hydrological models using neural networks  

NASA Astrophysics Data System (ADS)

In this study, a methodology has been developed to emulate a time consuming Monte Carlo (MC) simulation by using an Artificial Neural Network (ANN) for the assessment of model parametric uncertainty. First, MC simulation of a given process model is run. Then an ANN is trained to approximate the functional relationships between the input variables of the process model and the synthetic uncertainty descriptors estimated from the MC realizations. The trained ANN model encapsulates the underlying characteristics of the parameter uncertainty and can be used to predict uncertainty descriptors for the new data vectors. This approach was validated by comparing the uncertainty descriptors in the verification data set with those obtained by the MC simulation. The method is applied to estimate the parameter uncertainty of a lumped conceptual hydrological model, HBV, for the Brue catchment in the United Kingdom. The results are quite promising as the prediction intervals estimated by the ANN are reasonably accurate. The proposed techniques could be useful in real time applications when it is not practicable to run a large number of simulations for complex hydrological models and when the forecast lead time is very short.

Shrestha, D. L.; Kayastha, N.; Solomatine, D. P.

2009-07-01

69

A novel approach to parameter uncertainty analysis of hydrological models using neural networks  

NASA Astrophysics Data System (ADS)

In this study, a methodology has been developed to replicate time consuming Monte Carlo (MC) simulation by using an Artificial Neural Network (ANN) for assessment of model parametric uncertainty. First, MC simulation of a given process model is run. Then an ANN is trained to approximate the functional relationships between the input variables of the process model and the synthetic uncertainty descriptors estimated from the realizations. The trained ANN model encapsulates the underlying characteristics of the parameter uncertainty and can be used to predict uncertainty descriptors for the new data vectors. This approach was validated by comparing the uncertainty descriptors in the verification data set with those obtained by MC simulation. The method is applied to estimate parameter uncertainty of a lumped conceptual hydrological model, HBV, for the Brue catchment in UK. The results are quite promising as the prediction intervals estimated by ANN are reasonably accurate. The proposed techniques could be useful in real time applications when it is not practicable to run a large number of simulations for complex hydrological models and when the forecast lead time is very short.

Shrestha, D. L.; Kayastha, N.; Solomatine, D. P.

2009-03-01

70

Validation of uncertainty estimates in hydrologic modelling  

NASA Astrophysics Data System (ADS)

Meaningful characterization of uncertainties affecting conceptual rainfall-runoff (CRR) models remains a challenging research area in the hydrological community. Numerous methods aimed at quantifying the uncertainty in hydrologic predictions have been proposed over the last decades. In most cases, the outcome of such methods takes the form of a predictive interval, computed from a predictive distribution. Regardless of the method used to derive it, it is important to notice that the predictive distribution results from the assumptions made during the inference. Consequently, unsupported assumptions may lead to inadequate predictive distributions, i.e. under- or over-estimated uncertainties. It follows that the estimated predictive distribution must be thoroughly scrutinized ("validated"); as discussed by Hall et al. [2007] "Without validation, calibration is worthless, and so is uncertainty estimation". The aim of this communication is to study diagnostic tools aimed at assessing the reliability of uncertainty estimates. From a methodological point of view, this requires diagnostic approaches that compare a time-varying distribution (the predictive distribution at all times t) to a time series of observations. This is a much more stringent test than validation methods currently used in hydrology, which simply compare two time series (observations and "optimal" simulations). Indeed, standard goodness-of-fit assessments (e.g. using the Nash-Sutcliff statistic) can not check if the predictive distribution is consistent with the observed data. The usefulness of the proposed diagnostic tools will be illustrated with a case study comparing the performance of several uncertainty quantification frameworks. In particular, it will be shown that standard validation approaches (e.g. based on the Nash-Sutcliff statistic or verifying that about p% of the observations lie within the p% predictive interval) are not able to discriminate competing frameworks whose performance (in terms of uncertainty quantification) is evidently different.

Thyer, M.; Engeland, K.; Renard, B.; Kuczera, G.; Franks, S.

2009-04-01

71

A novel approach to parameter uncertainty analysis of hydrological models: Application of machine learning techniques  

NASA Astrophysics Data System (ADS)

Monte Carlo (MC) simulation-based techniques are widely used for analyzing parameter uncertainty in hydrological models. Although MC simulations are flexible and robust, and capable of solving a great variety of problems, they are not always practicable for computationally intensive models. This study presents a novel approach for assessment of parameter uncertainty in hydrological models using machine learning techniques. The presented approach replicates MC simulation by using various machine learning techniques, which is subsequently used for assessment of model parametric uncertainty. It is assumed a hydrological model M(p) is given and the propagation of the uncertainty in parameters p to the output is to be investigated. MC simulation of model M(p) is run and the stored realizations are used to form the dataset for training machine learning models. One of the issues was selection of the input variables for the machine learning models; it was done by searching for the variables (or their transformed variants) with the highest relatedness (average mutual information) to the sought distribution of the model M output. Machine learning models are trained to approximate the functional relationships between the variables characterizing the process modelled by M(p) and the uncertainty descriptors of its output. The trained machine learning models encapsulate the underlying characteristics of the parameter uncertainty and can be used to predict uncertainty descriptors for the new data. In this study three machine learning models - artificial neural networks, model trees and locally weighted regressions are used. The approach was demonstrated by estimating parameter uncertainty of a lumped conceptual hydrological model, HBV with application to a case study of meso scale mountainous catchment of Nepal. Uncertainty measures such as prediction intervals estimated by three machine learning methods are compared to those obtained by MC simulation in verification period. The results are promising as the uncertainty measures estimated by machine learning models are reasonably accurate. The proposed technique could be useful in real time applications for computationally intensive models (e.g. physically based hydrological models) which require run times that make traditional MC analysis impractical and when the forecast lead time is very short.

Shrestha, D. L.; Kayastha, N.; Solomatine, D. P.

2009-04-01

72

Plant adaptive behaviour in hydrological models (Invited)  

NASA Astrophysics Data System (ADS)

Models that will be able to cope with future precipitation and evaporation regimes need a solid base that describes the essence of the processes involved [1]. Micro-behaviour in the soil-vegetation-atmosphere system may have a large impact on patterns emerging at larger scales. A complicating factor in the micro-behaviour is the constant interaction between vegetation and geology in which water plays a key role. The resilience of the coupled vegetation-soil system critically depends on its sensitivity to environmental changes. As a result of environmental changes vegetation may wither and die, but such environmental changes may also trigger gene adaptation. Constant exposure to environmental stresses, biotic or abiotic, influences plant physiology, gene adaptations, and flexibility in gene adaptation [2-6]. Gene expression as a result of different environmental conditions may profoundly impact drought responses across the same plant species. Differences in response to an environmental stress, has consequences for the way species are currently being treated in models (single plant to global scale). In particular, model parameters that control root water uptake and plant transpiration are generally assumed to be a property of the plant functional type. Assigning plant functional types does not allow for local plant adaptation to be reflected in the model parameters, nor does it allow for correlations that might exist between root parameters and soil type. Models potentially provide a means to link root water uptake and transport to large scale processes (e.g. Rosnay and Polcher 1998, Feddes et al. 2001, Jung 2010), especially when powered with an integrated hydrological, ecological and physiological base. We explore the experimental evidence from natural vegetation to formulate possible alternative modeling concepts. [1] Seibert, J. 2000. Multi-criteria calibration of a conceptual runoff model using a genetic algorithm. Hydrology and Earth System Sciences 4(2): 215-224. [2] McClintock B. The significance of responses of the genome to challenge. Science 1984; 226: 792-801 [3] Ries G, Heller W, Puchta H, Sandermann H, Seldlitz HK, Hohn B. Elevated UV-B radiation reduces genome stability in plants. Nature 2000; 406: 98-101 [4] Lucht JM, Mauch-Mani B, Steiner H-Y, Metraux J-P, Ryals, J, Hohn B. Pathogen stress increases somatic recombination frequency in Arabidopsis. Nature Genet. 2002; 30: 311-314 [5] Kovalchuk I, Kovalchuk O, Kalck V., Boyko V, Filkowski J, Heinlein M, Hohn B. Pathogen-induced systemic plant signal triggers DNA rearrangements. Nature 2003; 423: 760-762 [6] Cullis C A. Mechanisms and control of rapid genomic changes in flax. Ann. Bot. (Lond.) 2005; 95: 201-206 [7] de Rosnay, P. and J. Polcher. 1998. Modelling root water uptake in a complex land surface scheme coupled to a GCM. Hydrology and Earth System Sciences 2: 239-255. [8] Feddes, R.A., H. Hoff, M. Bruen, T. Dawson, P. de Rosnay, P. Dirmeyer, R.B. Jackson, P. Kabat, A. Kleidon, A. Lilly, and A.J. Pitman. 2001. Modeling root water uptake in hydrological and climate models. Bulletin of the American Meteorological Society 82: 2797-2809. [9] Jung, M., M. Reichstein, P. Ciais, S.I. Seneviratne, J. Sheffield et al. 2010. Recent decline in the global land evaporation trend due to limited moisture supply. Nature 476: 951-954, doi:10.1038/nature09396.

van der Ploeg, M. J.; Teuling, R.

2013-12-01

73

Modeling hydrologic processes at the residential scale  

NASA Astrophysics Data System (ADS)

In California, urbanization has led to polluted runoff, flooding during winter, and water shortages during summer. There is growing interest in application of microscale hydrologic solutions that eliminate storm runoff and conserve water at the source. In this study, a physically-based numerical model was developed to better understand hydrologic processes at the residential scale and the interaction of these processes among different Best Management Practices (BMPs). This model calculates all in-flow and out-flow using an hourly interval over a full year or for specific storm events. Water enters the system via precipitation and irrigation and leaves the system via evapotranspiration, surface and subsurface runoff, and from percolation to groundwater. The model was applied to two single-family residential parcels in Los Angeles. Two years of data collected from the control and treatment sites were used to calibrate and validate the model. More than 97% of storm runoff to the street was eliminated with installation of low-cost BMPs (i.e., rain gutters that direct roof runoff to a lawn retention basin and a driveway interceptor that directs runoff to a drywell in the lawn retention basin). Evaluated individually, the driveway interceptor was the most effective BMP for storm runoff reduction (65%), followed by the rain gutter installation (28%), and lawn converted to retention basin (12%). Installation of an 11 m3 cistern did not substantially reduce runoff, but did provide storage for 9% of annual irrigation demand. Simulated landscape irrigation demand was reduced 53% by increasing efficiency through use of a drip irrigation system for shrubs, and adjusting monthly application rates based on evapotranspirational water demand. The model showed that infiltration and surface runoff processes were particularly sensitive to the soil's physical properties and its effective depth. If the existing loam soil were replaced by clay soil annual runoff discharge to the street would be increased by 63% when climate and landscape features remained unchanged.

Xiao, Q.; McPherson, G.; Simpson, J.; Ustin, S.

2003-12-01

74

A spatial and temporal continuous surface-subsurface hydrologic model  

Microsoft Academic Search

A hydrologic model integrating surface-subsurface processes was developed based on spatial and temporal continuity theory. The raster-based mass balance hydrologic model consists of several submodels which determine spatial and temporal patterns in precipitation, surface flow, infiltration, subsurface flow, and the linkages between these submodels. Model parameters and variables are derived directly or indirectly from satellite remote sensing data, topographic maps,

Qing-Fu Xiao; Susan L. Ustin; Wesley W. Wallender

1996-01-01

75

Integration of the variable infiltration capacity model soil hydrology scheme into the community land model  

Microsoft Academic Search

Enhancements to the soil hydrology scheme in the NCAR Community Land Model version 3 (CLM3) are described, which are intended to improve the ability of CLM to represent land surface hydrologic processes. Specifically, the CLM3 soil hydrology scheme has been replaced with the scheme used in the Variable Infiltration Capacity model (VIC). While the modified model incorporates VIC soil hydrology,

Aihui Wang; Kaiyuan Y. Li; Dennis P. Lettenmaier

2008-01-01

76

Hydrology  

ERIC Educational Resources Information Center

Lists many recent research projects in hydrology, including flow in fractured media, improvements in remote-sensing techniques, effects of urbanization on water resources, and developments in drainage basins. (MLH)

Sharp, John M.

1977-01-01

77

Comparing the performance of different model structures with respect to different hydrological signatures  

NASA Astrophysics Data System (ADS)

Correctly representing the dominant flow generation processes in conceptual rainfall-runoff models is crucial for ensuring adequate predictive power of the models. Recent work showed that on the small scale uniqueness of place requires different model structures for different catchments and that different calibration strategies frequently result in a wide range of model parameter sets. In this study we investigate the following research questions: (1) What is the effect of different calibration objective functions on the model performance? (2) Can the difference in performance of specific objective functions be related to hydrological signatures and physical catchment characteristics. Data from four experimental (approx. 1000 km2) sub-catchments (Alzette, Kyll, Orne and Seille) of the Moselle were used in this study. Eleven conceptual model structures (HBV, GR4J and 9 SUPERFLEX (flexible) model structures) of varying level of complexity are applied on each of the four study catchments. Besides classical objective functions (eg. Nash-Sutcliffe efficiency), additional objective functions are defined based on several hydrological signatures, such as the flow duration curve, rising limb density and auto-correlation. A multi-objective optimization is performed on all the objective functions for each catchment and each model structure considered. The results of the multi-objective optimization are then compared using Principle Component Analysis in order to identify the causes for differences in performance in the objective functions and relate these to physical catchment characteristics such as elevation, shape of the catchment and the height distribution above the nearest drain within a catchment. If such relationships are found then they can help to a priori identify suitable model structures and hydrological signatures in a catchment, given its spatial scale and physical characteristics.

Euser, T.; Winsemius, H. C.; Hrachowitz, M.; Fenicia, F.; Savenije, H. H. G.

2012-04-01

78

Constraining hydrologic models using thermal analysis  

SciTech Connect

Starting with regional geographic, geologic, hydrologic, geophysical, and meteorological data for the Tono area in Gifu, Japan, we develop a numerical model to simulate subsurface flow and transport in a 4 km by 6 km by 3 km thick fractured granite rock mass overlain by sedimentary layers. Individual fractures are not modeled explicitly. Rather, continuum permeability and porosity distributions are assigned stochastically, based on well-test data and fracture density measurements. The primary goal of the study is to simulate steady-state groundwater flow through the site, then calculate travel times to the model boundaries from specified monitoring points. The lateral boundaries of the model follow topographic features such as ridgelines and rivers. Assigning lateral boundary conditions is a major point of uncertainty in model construction. We evaluate two models with opposing boundary conditions: mostly closed and mostly open boundaries. The two models show vastly different spatial distributions of groundwater flow, so we would like to find a means of choosing the more realistic model. Surface recharge is much larger for the closed model, but field recharge data are of too limited spatial extent to provide a definitive model constraint. Temperature profiles in 16 boreholes show consistent trends with conduction-dominated (linear) temperature profiles below depths of about 300 m. The open and closed models predict strongly different temperature versus depth profiles; with the closed model showing a strong convective signature produced by widespread surface recharge effects to the depth. The open model shows more linear temperature profiles, better agreeing with measurements from the field. Based on this data we can eliminate from consideration the closed model, at least in its present form in which surface recharge penetrates deep into the model.

Doughty, Christine; Karasaki, Kenzi

2002-12-12

79

A RETROSPECTIVE ANALYSIS OF MODEL UNCERTAINTY FOR FORECASTING HYDROLOGIC CHANGE  

EPA Science Inventory

GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...

80

Hydrological Modelling of Small Catchments Using Swat  

NASA Astrophysics Data System (ADS)

The data from a 142ha catchment in Eastern England(Colworth, Bedfordshire)are be- ing used to investigate the performance of the USDA SWAT software for modelling hydrology of small catchments. Stream flow at the catchment outlet has been mon- itored since October 1999. About 50% of the total catchment is directly controlled within one farm and a rotation of wheat, oil seed rape, grass, linseed, beans and peas is grown. Three years of stream flow and climate data are available. Calibration and validation of stream flow was carried out with both runoff modelling options in the SWAT model (USDA curve number method and the Green and Ampt method). The Nash and Sutcliffe efficiencies for the calibration period were 66% and 63% respec- tively. The performance of SWAT was better in the validation period as a whole, with regard to timing of peaks, baseflow values and Nash and Sutcliffe efficiency. An ef- ficiency of 70% was obtained using the curve number method, which is comparable with the efficiencies obtainable with more complex models. Despite this performance, SWAT is under predicting stream flow peaks. A detailed investigation of important model components, has allowed us to identify some of the reasons for under predic- tion of stream flow peaks.

Kannan, N.; White, S. M.; Worrall, F.; Groves, S.

81

Hydrology  

NASA Astrophysics Data System (ADS)

Water in its different forms has always been a source of wonder, curiosity and practical concern for humans everywhere. Hydrology - An Introduction presents a coherent introduction to the fundamental principles of hydrology, based on the course that Wilfried Brutsaert has taught at Cornell University for the last thirty years. Hydrologic phenomena are dealt with at spatial and temporal scales at which they occur in nature. The physics and mathematics necessary to describe these phenomena are introduced and developed, and readers will require a working knowledge of calculus and basic fluid mechanics. The book will be invaluable as a textbook for entry-level courses in hydrology directed at advanced seniors and graduate students in physical science and engineering. In addition, the book will be more broadly of interest to professional scientists and engineers in hydrology, environmental science, meteorology, agronomy, geology, climatology, oceanology, glaciology and other earth sciences. Emphasis on fundamentals Clarification of the underlying physical processes Applications of fluid mechanics in the natural environment

Brutsaert, Wilfried

2005-08-01

82

Studying Hydrological Response of the Churchill River to Climate Change Using Distributed Hydrological Models  

NASA Astrophysics Data System (ADS)

The global climate has shown drastic changes in recent decades. It is of critical importance to investigate how global climate changes affect the different aspects of the hydrological cycle and the availability of freshwater resources in particular. In this study, the impact of climate change on the regional water and energy cycles in the Churchill River basin was assessed using distributed hydrological models. The applicability of the North American Regional Reanalysis (NARR) data for hydrological assessment in this remote region was also investigated. First monthly averaged precipitation and air temperature from NARR data were compared with a historical dataset interpolated using the ANUSPLIN method provided by the Canadian Forest service. The NARR data are available from 1979 to present at a 32-km resolution, while the interpolated dataset are available from 1950-2005 at a 5-km resolution. The NARR data was re-gridded to 5-km for comparison. The two datasets showed similar spatial distributions in multi-year precipitation and air temperature averaged from 1979 to 2005. A significant increase in the air temperature was also found in both datasets, especially in the winter. However, the air temperature in the NARR data was slightly higher, while the precipitation was slightly lower than the historical dataset. The WATFLOOD and Variable Infiltration Capacity (VIC) model were used to model the changes in the regional hydrological cycles in Churchill River during the past 30 years. The NARR data provided necessary inputs to the hydrological model, and the hydrological predictions including evapotranspiration, runoff, soil moisture and also snow water equivalent (SWE) from the NARR dataset were also examined through comparing with the outputs of the two models. The downscaling results from the Canadian regional climate (CRCM) model provided climate scenarios for the models to study the hydrological response to future climate change.

Yi, Y.; Rasmussen, P. F.

2009-05-01

83

Hydrology  

USGS Publications Warehouse

Hydrologic process are the main determinants of the type of wetland located on a site. Precipitation, groundwater, or flooding interact with soil properties and geomorphic setting to yield a complex matrix of conditions that control groundwater flux, water storage and discharge, water chemistry, biotic productivity, biodiversity, and biogeochemical cycling. Hydroperiod affects many abiotic factors that in turn determine plant and animal species composition, biodiversity, primary and secondary productivity, accumulation, of organic matter, and nutrient cycling. Because the hydrologic regime has a major influence on wetland functioning, understanding how hydrologic changes influence ecosystem processes is essential, especially in light of the pressures placed on remaining wetlands by society's demands for water resources and by potential global changes in climate.

Eisenbies, Mark H.; Hughes, W. Brian

2000-01-01

84

Global scale hydrology - Advances in land surface modeling  

SciTech Connect

Research into global scale hydrology is an expanding area that includes researchers from the meteorology, climatology, ecology and hydrology communities. This paper reviews research in this area carried out in the United States during the last IUGG quadrennial period of 1987-1990. The review covers the representation of land-surface hydrologic processes for general circulation models (GCMs), sensitivity analysis of these representations on global hydrologic fields like precipitation, regional studies of climate that have global hydrologic implications, recent field studies and experiments whose aims are the improved understanding of land surface-atmospheric interactions, and the use of remotely sensed data for the further understanding of the spatial variability of surface hydrologic processes that are important at regional and global climate scales. 76 refs.

Wood, E.F. (USAF, Geophysics Laboratory, Hanscom AFB, MA (United States))

1991-01-01

85

Operational use of distributed hydrological models. Experiences and challenges at a Norwegian hydropower company (Agder Energi).  

NASA Astrophysics Data System (ADS)

The Scandinavian hydropower industry has traditionally adopted the lumped conceptual hydrological model - HBV, as the tool for producing forecasts of inflows and mountain snow packs. Such forecasting systems - based on lumped conceptual models - have several drawbacks. Firstly, a lumped model does not produce spatial data, and comparisons with remote sensed snow cover data (which are now available) are complicated. Secondly, several climate parameters such as wind speed are now becoming more available and can potentially improve forecasts due to improved estimates of precipitation gauge efficiency, and more physically correct calculation of turbulent heat fluxes. At last, when the number of catchments increases, it is cumbersome and slow to run multiple hydrology models compared to running one model for all catchments. With the drawbacks of the lumped hydrology models in mind, and with inspiration from other forecasting systems using distributed models, Agder Energy decided to develop a forecasting system applying a physically based distributed model. In this paper we describe an operational inflow and snowpack forecast system developed for the Scandinavian mountain range. The system applies a modern macroscale land surface hydrology model (VIC) which in combination with historical climate data and weather predictions can be used to produce both short-term, and seasonal forecasts of inflow and mountain snowpack. Experiences with the forecast system are illustrated using results from individual subcatchments as well as aggregated regional forecasts of inflow and snowpack. Conversion of water volumes into effective energy inflow are also presented and compared to data from the Nordic hydropower system. Further on, we document several important "lessons-learned" that may be of interest to the hydrological research community. Specifically a semi-automatic data cleansing system combining spatial and temporal visualization techniques with statistical procedures are combined into a robust and fast data cleansing and interpolation system. One experience from this work is that advanced interpolation techniques (kriging), do not outperform calibrated inverse distance methods when also computational speed is used as a criteria for model selection. The paper also discusses several challenges related to uncertainty in simulated snow reservoir, regionalization of parameters, choice of spatial resolution, techniques for reducing computational needs without compromising information needs, amongst others.

Viggo Matheussen, Bernt; Andresen, Arne; Weisser, Claudia

2014-05-01

86

A novel approach to Monte Carlo-based uncertainty analysis of hydrological models using artificial neural networks  

NASA Astrophysics Data System (ADS)

The presented approach replicates Monte Carlo (MC) simulation by using an Artificial Neural Network (ANN), which is subsequently used for assessment of model parametric uncertainty. It is assumed a hydrological model M(p) is given and the propagation of the uncertainty in parameters p to the output is to be investigated. MC simulation of model M(p) is run and the stored realizations are used to form the dataset for training an ANN. One of the issues was selection of the input variables for the ANN model; it was done by searching for the variables (or their transformed variants) with the highest relatedness (average mutual information) to the sought distribution of the model M output. ANN is trained to approximate the functional relationships between the variables characterizing the process modelled by M(p) and the uncertainty descriptors of its output. The trained ANN model encapsulates the underlying characteristics of the parameter uncertainty and can be used to predict uncertainty descriptors for the new data. The approach was validated by comparing the uncertainty descriptors in the verification data set with those obtained by MC simulation. The method is applied to estimate parameter uncertainty of a lumped conceptual hydrological model, HBV. The results are promising as the prediction intervals estimated by ANN are reasonably accurate. The proposed techniques could be useful in real time applications when it is not possible to run a large number of simulations for complex hydrological models and when the forecast lead time is very short.

Shrestha, D. L.; Kayastha, N.; Solomatine, D.

2009-04-01

87

Distributed Hydrologic Models for Flow Forecasts - Part 2  

NSDL National Science Digital Library

Distributed Hydrologic Models for Flow Forecasts Part 2 is the second release in a two-part series focused on the science of distributed models and their applicability to different flow forecasting situations. Presented by Dr. Dennis Johnson, the module provides a more detailed look at the processes and mechanisms involved in distributed hydrologic models. It examines the rainfall/runoff component, snowmelt, overland flow routing, and channel response in a basin as represented in a distributed model. Calibration issues and situations in which distributed hydrologic models might be most appropriate are also addressed.

2011-01-01

88

Development of a Macro-Scale Land-Surface Hydrologic Model for General Circulation Models.  

National Technical Information Service (NTIS)

The development and evaluation of a macroscale land surface hydrology model, appropriate for inclusion into atmospheric general circulation models (AGCMs) is presented. The model includes hydrologically important processes such as base flow, infiltration ...

E. F. Wood

1992-01-01

89

Data Mining of Hydrological Model Performances  

NASA Astrophysics Data System (ADS)

Multi-objective criteria have long been used to infer hydrological simulations and fit the natural world. On the other hand, modelling frameworks are also becoming more and more popular as identification of the processes occurring in a catchment is still a very uncertain matter. In theory, multi-objective criteria and multi-model frameworks should be used in combination so that the 'representation' of the catchment is fitted to the observations, not only the simulated results. In practise those approaches are highly computationally demanding. The modeller is often obliged to find a compromise reducing either the number of objective functions or model structures taken into consideration. This compromise is becoming obsolete using parallel computing. In the present study we investigate the extend to which model selection algorithms and regionalisation techniques can be improved by such facilities and highlight the challenges that still need to be addressed. The model simulations are obtained using an ensemble of conceptual lumped models (FUSE by Clark et al. 2008), but techniques and suggestions are of general use and applicable to any modelling frameworks. In particular we developed a novel model selection algorithm tuned to drastically reduce the subjectivity in the analysis. The procedure was automated and coupled with redundancy reduction techniques such as PCA and Cluster Analysis. Results show that the actual model 'representation' has the shape of a set of complementing model structures. It is also possible to capture intra-annum dynamics of the response as the algorithm recognises subtle variations in the selected model structures in different seasons. Similar variations can be found analysing different catchments. This suggests the same methodology would be suitable for analysing spatial patterns in the distribution of suitable model structures and maybe long term dynamics in relation with expedited climate modifications. Although the mentioned methodology has proven to be successful with regards to the case study, some limitations are worth noting. If this is going to be applied to the more general case of 'models of everywhere', for instance, there could be dominant processes not described in the FUSE framework. Further studies could therefore extend the current framework to include routines able to simulate missing processes.

Vitolo, Claudia; Buytaert, Wouter

2013-04-01

90

Climate Change Impacts to Watershed Hydrology using an Integrated Hydrologic Model (Invited)  

Microsoft Academic Search

Many climatologists project that increased green house gases (GHGs) will cause long term changes to the earth's climate superimposed onto historical variability of climate. As a result, climate change poses a difficult problem for water resource managers making longterm forcasts. Modeling hydrologic change associated with climate variability has historically been performed with compartmental models, where surface and groundwater interactions are

J. L. Huntington; R. G. Niswonger

2010-01-01

91

Incorporating landscape classifications in hydrological conceptual models A case study for a central European meso-scale catchment  

NASA Astrophysics Data System (ADS)

Landscape classification into meaningful hydrological units has important implications for hydrological modeling. Conceptual hydrological models, such as HBV- type models, are most commonly designed to represent catchments in a lumped or semi-distributed way at best, i.e. treating them as single entities or sometimes accounting for topographical and land cover variability by introducing some level of stratification. These oversimplifications can frequently lead to substantial misrepresentations of flow generating processes in the catchments in question, as feedback processes between topography, land cover and hydrology in different landscape units can arguably lead to distinct hydrological patterns. By making use of readily available topographical information, hydrological units can be identified based on the concept of "Height above Nearest Drainage" (HAND; Rennó et al., 2008; Nobre et al., 2011). These hydrological units are characterized by different distinct hydrological behavior and can thus be assigned different model structures (Savenije, 2010). In this study we classified the Wark Catchment in Grand Duchy of Luxembourg which exhibits three distinct landscape units: plateau, wetland and hillslope using a 5-5 m2 DEM. A revised and extended version of HAND gave preliminary estimates of uncertainty in the landscape unit identification as they were implemented in a stochastic framework. As the transition thresholds between the landscape units are a priori unknown, they were calibrated against landscape units observed in the field using a single probability based objective function. As a result, each grid cell of the DEM was characterized by a certain probability of being a certain landscape unit, producing maps of dominant landscape and therefore hydrological units. The maps of the landscape classification using HAND and slope in a probabilistic framework were then used to determine the proportions of the three individual hydrological response units in the catchment. The classified landscapes were used to assign different model structures to the individual hydrological response units. As an example deep percolation was defined as dominant process for plateaus, rapid subsurface flow as dominant process for hillslopes and saturation overland flow as dominant process for wetlands. The modeled runoffs from each hydrological unit were combined in a parallel set-up to proportionally contribute to the total catchment runoff. The hydrological units are, in addition, linked by a common groundwater reservoir. The parallel hydrological units, although increasing the number of parameters, have the benefit of comparative calibration. As an example, one may consider the lag time of wetland to be shorter than the lag time of water traveling to the outlet from a plateau. Moreover, due to the dominance of forest on hillslopes in this catchment, hillslope interception should be higher than interception on plateaus which are mainly used for agriculture in the Wark catchment. Furthermore fluxes and processes can be compared. For example, actual evaporation from wetland can potentially be higher than other entities within a catchment as wetland is water logged and evaporation thus less supply limited than on plateaus. To include all the comparisons and criteria in calibration, an evolutionary algorithm was used. The algorithm was adapted and applied in a way that in subsequent steps more and more comparative criteria are forced to be satisfied. At the end of the calibration it is expected that all the criteria should be satisfied. Including landscape classification into hydrological models seems to be a powerful tool which not only allows to consider and to make use of crucial feedback processes controlling the evolution of the hydrological system together with the eco-system but may also lead to more detailed information on how a catchment may work than a simple lumped model.

Gharari, S.; Hrachowitz, M.; Fenicia, F.; Savenije, H. H. G.

2012-04-01

92

Assessing hydrological model behaviors by intercomparison of the simulated stream flow compositions: case study in a steep forest watershed in Taiwan  

NASA Astrophysics Data System (ADS)

The accurate stream flow composition simulated by different models is rarely discussed, and few studies addressed the model behaviors affected by the model structures. This study compared the simulated stream flow composition derived from two models, namely HBV and TOPMODEL. A total of 23 storms with a wide rainfall spectrum were utilized and independent geochemical data (to derive the stream composition using end-member mixing analysis, EMMA) were introduced. Results showed that both hydrological models generally perform stream discharge satisfactory in terms of the Nash efficiency coefficient, correlation coefficient, and discharge volume. However, the three simulated flows (surface flow, interflow, and base flow) derived from the two models were different with the change of storm intensity and duration. Both simulated surface flows showed the same patterns. The HBV simulated base flow dramatically increased with the increase of storm duration. However, the TOP-derived base flow remained stable. Meanwhile, the two models showed contrasting behaviors in the interflow. HBV prefers to generate less interflow but percolates more to the base flow to match the stream flow, which implies that this model might be suited for thin soil layer. The use of the models should consider more environmental background data into account. Compared with the EMMA-derived flows, both models showed a significant 2 to 4 h time lag, indicating that the base-flow responses were faster than the models represented. Our study suggested that model intercomparison under a wide spectrum of rainstorms and with independent validation data (geochemical data) is a good means of studying the model behaviors. Rethinking the characterization of the model structure and the watershed characteristics is necessary in selecting the more appropriate hydrological model.

Huang, J.-C.; Lee, T.-Y.; Lee, J.-Y.; Hsu, S.-C.; Kao, S.-J.; Chang, F.-J.

2013-01-01

93

Hydrological Modeling of the Jiaoyi Watershed (China) Using HSPF Model  

PubMed Central

A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001–2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R2), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin.

Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie

2014-01-01

94

ENHANCING HYDROLOGICAL SIMULATION PROGRAM - FORTRAN MODEL CHANNEL HYDRAULIC REPRESENTATION  

EPA Science Inventory

The Hydrological Simulation Program? FORTRAN (HSPF) is a comprehensive watershed model that employs depth-area - volume - flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross-sections and reservoirs. ...

95

An open-source distributed mesoscale hydrologic model (mHM)  

NASA Astrophysics Data System (ADS)

The mesoscale hydrological model (mHM) is based on numerical approximations of dominant hydrological processes that have been tested in various hydrological models such as: HBV and VIC. In general, mHM simulates the following processes: canopy interception, snow accumulation and melting, soil moisture dynamics (n-horizons), infiltration and surface runoff, evapotranspiration, subsurface storage and discharge generation, deep percolation and baseflow, and discharge attenuation and flood routing. The main characteristic of mHM is the treatment of the sub-grid variability of input variables and model parameters which clearly distinguishes this model from existing precipitation-runoff models or land surface models. It uses a Multiscale Parameter Regionalization (MPR) to account for the sub-grid variability and to avoid continuous re-calibration. Effective model parameters are location and time dependent (e.g., soil porosity). They are estimated through upscaling operators that link sub-grid morphologic information (e.g., soil texture) with global transfer-function parameters, which, in turn, are found through multi-basin optimization. Global parameters estimated with the MPR technique are quasi-scale invariant and guarantee flux-matching across scales. mHM is an open source code, written in Fortran 2003 (standard), fully modular, with high computational efficiency, and parallelized. It is portable to multiple platforms (Linux, OS X, Windows) and includes a number of algorithms for sensitivity analysis, analysis of parameter uncertainty (MCMC), and optimization (DDS, SA, SCE). All simulated state variables and outputs can be stored as netCDF files for further analysis and visualization. mHM has been evaluated in all major river basins in Germany and over 80 US and 250 European river basins. The model efficiency (NSE) during validation at proxy locations is on average greater than 0.6. During last years, mHM had been used for number of hydrologic applications such as, for example, a) to investigate the influence of the antecedent soil moisture on extreme floods in Germany (2002 and 2013), b) for establishing benchmark agricultural drought events for Germany since 1950. A 60-year reconstruction of the daily mHM soil moisture fields over Germany at high resolution 4 × 4 km2 was used for this purpose, and c) to investigate the potential benefits of a high resolution modeling approach for the drought monitoring and forecasting system over Pan-EU. We invite the community to take advantage of this open-source code which is freely available (after nominal registration) at: http://www.ufz.de/index.php?en=31389.

Samaniego, Luis; Kumar, Rohini; Zink, Matthias; Thober, Stephan; Mai, Juliane; Cuntz, Matthias; Schäfer, David; Schrön, Martin; Musuuza, Jude; Prykhodko, Vladyslav; Dalmasso, Giovanni; Attinger, Sabine; Spieler, Diana; Rakovec, Oldrich; Craven, John; Langenberg, Ben

2014-05-01

96

Indirect hyperbilirubinemia in HBV carriers  

Microsoft Academic Search

Summary  Indirect hyperbilirubinemia without any other abnormalities of liver function tests was seen in 14.3% inHBV carriers and 1.2% in controls in the previous study. In order to clarify the mechanism of hyperbili-rubinemia inHBV carriers, 33HBV carriers with normal liver functions regardless of hyperbilirubinemia and with no past history of acute hepatitis were investigated\\u000a clinically. Most ofHBV carriers with indirect hyperbilirubinemia

Kensuke Miura; Shiro Suzuki; Satoshi Tanaka; Ryota Kinoshita; Haruto Uchino; Shinichi Hirose; Tadayuki Nakagawa; Yukio Imai

1980-01-01

97

The transferability of hydrological models under nonstationary climatic conditions  

NASA Astrophysics Data System (ADS)

This paper investigates issues involved in calibrating hydrological models against observed data when the aim of the modelling is to predict future runoff under different climatic conditions. To achieve this objective, we tested two hydrological models, DWBM and SIMHYD, using data from 30 unimpaired catchments in Australia which had at least 60 yr of daily precipitation, potential evapotranspiration (PET), and streamflow data. Nash-Sutcliffe efficiency (NSE), modified index of agreement (d1) and water balance error (WBE) were used as performance criteria. We used a differential split-sample test to split up the data into 120 sub-periods and 4 different climatic sub-periods in order to assess how well the calibrated model could be transferred different periods. For each catchment, the models were calibrated for one sub-period and validated on the other three. Monte Carlo simulation was used to explore parameter stability compared to historic climatic variability. The chi-square test was used to measure the relationship between the distribution of the parameters and hydroclimatic variability. The results showed that the performance of the two hydrological models differed and depended on the model calibration. We found that if a hydrological model is set up to simulate runoff for a wet climate scenario then it should be calibrated on a wet segment of the historic record, and similarly a dry segment should be used for a dry climate scenario. The Monte Carlo simulation provides an effective and pragmatic approach to explore uncertainty and equifinality in hydrological model parameters. Some parameters of the hydrological models are shown to be significantly more sensitive to the choice of calibration periods. Our findings support the idea that when using conceptual hydrological models to assess future climate change impacts, a differential split-sample test and Monte Carlo simulation should be used to quantify uncertainties due to parameter instability and non-uniqueness.

Li, C. Z.; Zhang, L.; Wang, H.; Zhang, Y. Q.; Yu, F. L.; Yan, D. H.

2012-04-01

98

Assessing hydrologic response to climate change of a stream watershed using SLURP hydrological model  

Microsoft Academic Search

The impact on streamflow and groundwater recharge considering future potential climate and land use changes was assessed using\\u000a Semi-distributed Land-Use Runoff Process (SLURP) continuous hydrologic model. The model was calibrated and verified using\\u000a 4 years (1999–2002) daily observed streamflow data for a 260.4 km2 watershed which has been continuously urbanized during the past couple of decades. The model was calibrated

So Ra Ahn; Geun Ae Park; In Kyun Jung; Kyoung Jae Lim; Seong Joon Kim

2011-01-01

99

Hydrologic Predictions in the Anthropocene: Exploration with Co-evolutionary Socio-hydrologic Models  

NASA Astrophysics Data System (ADS)

Socio-hydrology studies the co-evolution and self-organization of humans in the hydrologic landscape, which requires a thorough understanding of the complex interactions between humans and water. On the one hand, the nature of water availability greatly impacts the development of society. On the other hand, humans can significantly alter the spatio-temporal distribution of water and in this way provide feedback to the society itself. The human-water system functions underlying such complex human-water interactions are not well understood. Exploratory models with the appropriate level of simplification in any given area can be valuable to understand these functions and the self-organization associated with socio-hydrology. In this study, a simple coupled modeling framework for socio-hydrology co-evolution is developed, and is used to illustrate the explanatory power of such models. In the Tarim River, humans depend heavily on agricultural production (other industries can be ignored for a start), and the social processes can be described principally by two variables, i.e., irrigated-area and human population. The eco-hydrological processes are expressed in terms of area under natural vegetation and stream discharge. The study area is the middle and the lower reaches of the Tarim River, which is divided into two modeling units, i.e. middle reach and lower reach. In each modeling unit, four ordinary differential equations are used to simulate the dynamics of the hydrological system represented by stream discharge, ecological system represented by area under natural vegetation, the economic system represented by irrigated area under agriculture and social system represented by human population. The four dominant variables are coupled together by several internal variables. For example, the stream discharge is coupled to irrigated area by the colonization rate and mortality rate of the irrigated area in the middle reach and the irrigated area is coupled to stream discharge by water used for irrigation. In a similar way, the stream discharge and natural vegetation are coupled together. The irrigated area is coupled to population by the colonization rate and mortality rate of the population. The discharge of the lower reach is determined by the discharge from the middle reach. The natural vegetation area in the lower reach is coupled to the discharge in the middle reach by water resources management policy. The co-evolution of the Tarim socio-hydrological system is then analyzed within this modeling framework to gain insights into the overall system dynamics and sensitivity to the external drivers and internal system variables.

Sivapalan, Murugesu; Tian, Fuqiang; Liu, Dengfeng

2013-04-01

100

Application of a Distributed Hydrological Model to Detect Hydrological Effect on Gravity  

NASA Astrophysics Data System (ADS)

A major problem in many hydrological studies is that almost all of the stocks and fluxes in the hydrologic cycle are difficult to measure, and if measured or estimated, the accuracy often is questionable. A new generation of in-situ gravimeters and NASA's Gravity Recovery and Climate Experiment promise the possibility of tracking the movement of the water on and beneath the earth surface. A research programme was started to investigate the possibility of detecting the variations in river basin water storage from measurements of the time dependent gravity field, and to assess the accuracy of these estimations using models. In this paper we study the hydrological effect on in-situ gravity measurements by means of water balance modeling. The relatively simple GIS-based Soil Moisture Routing (SMR) model is used to compute time varying storage change of spatially distributed pixels within the observation domain of a superconducting gravity observation station near Moxa (Germany). The so-derived mass changes in the vicinity of the gravimeter are then converted into a time varying gravity signal and is compared to the observed gravity residual. It is anticipated that this approach will yield valuable insights into the interaction of hydrologically driven mass changes and the in-situ gravity measurements, allowing for a more accurate correction and/or interpretation of the data.

Hasan, S.; Boll, J.; Troch, P. A.

2003-12-01

101

New insights for the hydrology of the Rhine based on the new generation climate models  

NASA Astrophysics Data System (ADS)

Decision makers base their choices of adaptation strategies on climate change projections and their associated hydrological consequences. New insights of climate change gained under the new generation of climate models belonging to the IPCC 5th assessment report may influence (the planning of) adaption measures and/or future expectations. In this study, hydrological impacts of climate change as projected under the new generation of climate models for the Rhine were assessed. Hereto we downscaled 31 General Circulation Models (GCMs), which were developed as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5), using an advanced Delta Change Method for the Rhine basin. Changes in mean monthly, maximum and minimum flows at Lobith were derived with the semi-distributed hydrological model HBV of the Rhine. The projected changes were compared to changes that were previously obtained in the trans-boundary project Rheinblick using eight CMIP3 GCMs and Regional Climate Models (RCMs) for emission scenario A1B. All eight selected CMIP3 models (scenario A1B) predicted for 2071-2100 a decrease in mean monthly flows between June and October. Similar decreases were found for some of the 31 CMIP5 models for Representative Concentration Pathways (RCPs) 4.5, 6.0 and 8.5. However, under each RCP, there were also models that projected an increase in mean flows between June and October and on average the decrease was smaller than for the eight CMIP3 models. For 2071-2100, also the mean annual minimum 7-days discharge decreased less in the CMIP5 model simulations than was projected in CMIP3. When assessing the response of mean monthly flows of the CMIP5 simulation with the CSIRO-Mk3-6-0 and HadGEM2-ES models with respect to initial conditions and RCPs, it was found that natural variability plays a dominant role in the near future (2021-2050), while changes in mean monthly flows are dominated by the radiative forcing in the far future (2071-2100). According to RCP 8.5 model simulations, the change in mean monthly flow from May to November may be half the change in mean monthly flow projected by RCP 4.5. From January to March, RCP 8.5 simulations projected higher changes in mean monthly flows than RCP 4.5 simulations. These new insights based on the CMIP5 simulations imply that for the Rhine, the mean and low flow extremes might not decrease as much in summer as was expected under CMIP3. Stresses on water availability during summer are therefore also less than expected from CMIP3.

Bouaziz, Laurène; Sperna Weiland, Frederiek; Beersma, Jules; Buiteveld, Hendrik

2014-05-01

102

Risks in hydrological modelling due to uncertainties in discharge determination  

Microsoft Academic Search

Uncertainties in discharge determination may have serious consequences for hydrological\\u000amodelling and resulting discharge predictions affecting flood and drought risk assessment and decision\\u000amaking. The aim of this study is to quantify the effect of discharge errors on parameters and performance of\\u000aa conceptual hydrological model for discharge prediction applied to two catchments. Four error sources in\\u000adischarge determination are

Martijn J. Booij; Tillaart van den Sander P. M; Maarten S. Krol; Gunther Bloschl; Kuni Takeuchi; Sharad Jain; Andreas Farnleitner; Andreas Schumann

2011-01-01

103

Spatial interpolation schemes of daily precipitation for hydrologic modeling  

Microsoft Academic Search

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational\\u000a points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the\\u000a spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based\\u000a estimation schemes fail to describe the realistic spatial variability of daily precipitation field.

Yeonsang Hwang; Martyn Clark; Balaji Rajagopalan; George Leavesley

104

Modeling hydrology and sediment transport in vegetative filter strips  

Microsoft Academic Search

The performance of vegetative filter strips is governed by complex mechanisms. Models can help simulate the field conditions and predict the buffer effectiveness. A single event model for simulating the hydrology and sediment filtration in buffer strips is developed and field tested. Input parameters, sensitivity analysis, calibration and field testing of the model are presented. The model was developed by

Rafael Muñoz-Carpena; John E. Parsons; J. Wendell Gilliam

1999-01-01

105

Parsimonious hydrological modeling of urban sewer and river catchments  

NASA Astrophysics Data System (ADS)

A parsimonious hydrological model is developed for urban watershed flow modeling. Complexity of the drainage network is ignored by considering it as a linear storage. A single representative CSO represents all others. A WWTP drainage basin and an urban river catchment provide model validation. Model and validation consider two overlapping watersheds.

Coutu, Sylvain; Del Giudice, Dario; Rossi, Luca; Barry, D. A.

2012-09-01

106

Hydrological Modeling Uncertainty Analysis with the Bayesian Model Averaging method  

NASA Astrophysics Data System (ADS)

Bayesian Model Averaging (BMA) method is a tool to infer the statistical distribution of a quantity to be predicted as the mixture of a set of individual prediction distributions, with each individual prediction distribution constructed on the basis of the performance of each different model. In the BMA, there should be a number of models used to construct the model ensemble, and the mixture coefficient, or the weight of each individual model, is traditionally determined by the Expectation-Maximization (EM) algorithm. Since the BMA is a method that can combine the forecasts of different models together to generate a new forecast expected to be better than any individual model's forecast, it has been widely used in hydrology for ensemble hydrologic prediction. Previous studies of the BMA mostly focused on the comparison of the expected BMA prediction with the prediction of each individual model. As the BMA has the ability to provide a statistical distribution of the quantity to be forecasted, the research focus in this study is shifted onto the comparison of the prediction interval generated by the BMA with that of each individual model, in order to see if the BMA can improve the prediction reliability. Three hydrological models are employed in the investigation of two BMA schemes. The first BMA scheme is to calibrate each of the three models under the same Nash-Sutcliffe efficiency objective function, thus providing three different forecasts for the BMA combination. In the second BMA scheme, three different objective functions other than Nash-Sutcliffe efficiency are adopted, each of which is targeted for simulating different parts of flows, i.e. low flow, medium flow, and high flow. All three models are respectively calibrated for each of three objective functions to obtain the optimized parameter sets. As the same model with the different optimized parameter sets will give rise to different forecasts, thus in the second BMA scheme, there are nine different forecasts used for the BMA combination. For each of individual member model as well as both BMA combination schemes, the Monte Carlo method is used to infer the probability distribution of the quantity to be forecasted and determine prediction intervals. Then, the model efficiency and uncertainty of each member model and two BMA combination schemes are assessed and compared.

Dong, Leihua; Xiong, Lihua

2010-05-01

107

Modeling conditional covariance between meteorological and hydrological drought  

NASA Astrophysics Data System (ADS)

This study introduces a bivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) approach to model the time varying second order moment or conditional variance-covariance link of hydrologic and meteorological drought. The standardized streamflow and rainfall time series are selected as drought indices and the bivariate diagonal BEKK model is applied to estimate the conditional variance-covariance structure between hydrologic and meteorological drought. Results of diagonal BEKK(1,1) model indicated that the conditional variance of meteorological drought is weak and much smaller than that for hydrological drought which shows a strong volatility effect. However both drought indices show a weak memory in the conditional variance. It is also observed that the conditional covariance between two drought indices is also weak and only shows a slight short run volatility effect. This may suggest the effect of basin features such as groundwater storage and physical characteristics which attenuate and modify the effect of meteorological drought on hydrologic drought in the basin scale. conditional correlation time series between meteorological and hydrologic drought at two selected stations monthly variation of conditional correlation between meteorological and hydrologic drought at two selected stations

Modarres, R.

2012-12-01

108

A sensitivity analysis of regional and small watershed hydrologic models  

NASA Technical Reports Server (NTRS)

Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.

Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.

1975-01-01

109

Strategies for using remotely sensed data in hydrologic models  

NASA Technical Reports Server (NTRS)

Present and planned remote sensing capabilities were evaluated. The usefulness of six remote sensing capabilities (soil moisture, land cover, impervious area, areal extent of snow cover, areal extent of frozen ground, and water equivalent of the snow cover) with seven hydrologic models (API, CREAMS, NWSRFS, STORM, STANFORD, SSARR, and NWSRFS Snowmelt) were reviewed. The results indicate remote sensing information has only limited value for use with the hydrologic models in their present form. With minor modifications to the models the usefulness would be enhanced. Specific recommendations are made for incorporating snow covered area measurements in the NWSRFS Snowmelt model. Recommendations are also made for incorporating soil moisture measurements in NWSRFS. Suggestions are made for incorporating snow covered area, soil moisture, and others in STORM and SSARR. General characteristics of a hydrologic model needed to make maximum use of remotely sensed data are discussed. Suggested goals for improvements in remote sensing for use in models are also established.

Peck, E. L.; Keefer, T. N.; Johnson, E. R. (principal investigators)

1981-01-01

110

Eco-hydrological modeling to integrate ecological processes and hydrological processes in a small forested catchment  

NASA Astrophysics Data System (ADS)

Ecological processes and hydrological processes are very tightly connected with each other. Especially, to estimate the amount of water outflow and water retention in forest, it is needed to quantify the role of vegetation in the forest. For this reason, Eco-hydrological modeling provides an useful tool to understand the forest ecosystem processes and services. But because the numerous processes is entangled each other, the model usually has a number of parameters but our ability to measure all necessary data at field condition is highly limited, which makes model calibration difficult. Therefore, we took a basic aim to estimate a water balance of forest ecosystem and studied an efficient methods to establish the relationship of ecological process and hydrological process and to find a significant parameters in the study site. A procedure of model calibration was separated by 5-steps according to time sequence of processes. (1) Initialize the Carbon, Nitrogen states based on the measured data. (2) Calibrate the maximum LAI and compute a rain interception parameter using the measured rain interception data. (3) Compute the long-term ET from the long-term streamflow and rainfall data and determine a canopy conductance parameter of ET algorithm. (4) Determine the soil parameter to separate a surface runoff and baseflow and (5) to estimate the pattern of outflow. By using the structured calibration process, we could independently assess the each hydrological and/or ecological process and provide analytical explanations of simulated results. Our improved modeling indicates that annual precipitation (1,329 mm) is partitioned to evapotranspiration, 486 mm (37 percent), and stream outflow, 843 mm (63 percent), respectively. The calibrated model was further applied to investigate spatial pattern of soil water content and evapotranspiration to support validation of satellite-driven estimations. - Keyword : Eco-hydrological model, calibration, parameterization, ecological process, hydrological process - Acknowledgements : This work was supported by the Sustainable Water Resources Research Center of the 21st Century Frontier Program (Project No. 1-8-2, Hydrokorea), Ministry of Environment (Carbokorea), Korea Forest Research Institute and Korean National Arboretum

Kim, E.; Kang, S.; Lee, A.; Kim, S.; Kim, K.; Kim, J.; Lee, D.

2006-12-01

111

Models of atmosphere-ecosystem-hydrology interactions: Approaches and testing  

NASA Technical Reports Server (NTRS)

Interactions among the atmosphere, terrestrial ecosystems, and the hydrological cycle have been the subject of investigation for many years, although most of the research has had a regional focus. The topic is broad, including the effects of climate and hydrology on vegetation, the effects of vegetation on hydrology, the effects of the hydrological cycle on the atmosphere, and interactions of the cycles via material flux such as solutes and trace gases. The intent of this paper is to identify areas of critical uncertainty, discuss modeling approaches to resolving those problems, and then propose techniques for testing. I consider several interactions specifically to illustrate the range of problems. These areas are as follows: (1) cloud parameterizations and the land surface, (2) soil moisture, and (3) the terrestrial carbon cycle.

Schimel, David S.

1992-01-01

112

Radar data bias correction implementing quantile mapping and investigation of its influence in a hydrological model  

NASA Astrophysics Data System (ADS)

Weather radar is an important source of data for estimating rainfall rate with relatively high temporal and spatial resolution covering large areas. Although weather radar provides fine temporal and spatial resolution data, it is subject to different sources of error. Beside casual problems associated with radar, e.g. clutter and attenuation, weather radar either underestimates or overestimates the rainfall amount. Additionally, time steps with strangely high values result in destroying the structure of time series derived from radar data. In order to estimate areal precipitation for hydrological analyses, radar data could be merged with rain gauge network data. The merging product quality is strongly dependent on radar data quality. The main purpose of this study is to illustrate a method for improving radar data quality and to investigate the influence of radar data quality on merging products by means of cross validation. Quantile mapping on the two sources of data, the radar and rain gauge network, is implemented in this study to improve the radar data quality. After correcting the radar data, considering rain gauge data as the truth, the data is implemented into a hydrological model, HBV-IWW, to investigate the influence of the different input sources regarding model performance. It has been observed that implementing quantile mapping improves radar data quality significantly. On the other hand, using radar data after correction not only improves interpolation performances but also reveals other possible applications like disaggregation of daily rainfall data into finer temporal resolutions. Beside radar data quality, there are other factors influencing the model performance like network density and the applied interpolation technique. The study area is a mesoscale catchment located in Lower Saxony, northern Germany.

Rabiei, Ehsan; Wallner, Markus; Haberlandt, Uwe

2014-05-01

113

Hydrologic Modeling in a Service-Oriented Architecture  

Microsoft Academic Search

Service Oriented Architectures (SOA) offer an approach for creating hydrologic models whereby a model is decomposed into independent computational services that are geographically distributed yet accessible through the Internet. The advantage of this modeling approach is that diverse groups can contribute computational routines that are usable by a wide community, and these routines can be used across operating systems and

J. L. Goodall

2008-01-01

114

An equivalent cross-sectional basis for semidistributed hydrological modeling  

NASA Astrophysics Data System (ADS)

computational effort associated with physically based distributed hydrological models is one of their major limitations that restrict their application in soil moisture and land surface flux simulation problems for large catchments. In this work, a new approach for reducing the computational effort associated with such models is investigated. This approach involves the formation of equivalent cross sections, designed in a manner that ensures comparable accuracy in simulating the hydrological fluxes as a fully distributed simulation. Single or multiple equivalent cross sections are formulated in each Strahler's first-order subbasin on the basis of topographic and physiographic variables representing the entire or part of the subbasin. An unsaturated soil moisture movement model based on a two-dimensional solution of the Richards' equation is used for simulating the soil moisture and hydrologic fluxes. The equivalent cross-section approach and the model are validated against observed soil moisture data in a semiarid catchment and found consistent. The results indicate that the equivalent cross-section approach is an efficient alternative for reducing the computational time of distributed hydrological modeling while maintaining reasonable accuracy in simulating hydrologic fluxes, in particular dominant fluxes such as transpiration and soil evaporation in semiarid catchments.

Khan, Urooj; Tuteja, Narendra Kumar; Ajami, Hoori; Sharma, Ashish

2014-05-01

115

Comparison of hydrological impacts of climate change simulated by six hydrological models in the Dongjiang Basin, South China  

Microsoft Academic Search

Large differences in future climatic scenarios found when different global circulation models (GCMs) are employed have been extensively discussed in the scientific literature. However, differences in hydrological responses to the climatic scenarios resulting from the use of different hydrological models have received much less attention. Therefore, comparing and quantifying such differences are of particular importance for the water resources management

Tao Jiang; Yongqin David Chen; Chong-Yu Xu; Xiaohong Chen; Xi Chen; Vijay P. Singh

2007-01-01

116

Scaling of input data for macroscale hydrologic modeling  

SciTech Connect

Hydrologic models provide the land-phase link between atmospheric models and oceanographic models within the global water cycle. They provide independent validation of the outputs from atmospheric models and may also provide a mechanism to examine the implications of climatic change on water resources. To form a component of a global model, hydrologic models must be applicable at macroscale and continental scale. The sources and scales of input data are critical to the development of such models. Results from the application of a distributed hydrologic model to Canadian watersheds from 500 km{sup 2} to 1.6 million km{sup 2} in area are used to compare errors found using input data at different scales. Data considered include land cover, vegetation index, and snow water equivalent from satellite sensors and distributed climate data from a general circulation model and from numerical weather prediction models. Analysis of the results allows a consideration of appropriate data scaling in the development of macroscale hydrologic models. 35 refs., 7 figs., 5 tabs.

Kite, G.W. [National Hydrology Research Inst., Saskatoon, Saskatchewan (Canada)] [National Hydrology Research Inst., Saskatoon, Saskatchewan (Canada)

1995-11-01

117

Innate immune responses in hepatitis B virus (HBV) infection  

PubMed Central

Hepatitis B virus (HBV) infection has a low rate of chronicity compared to HCV infection, but chronic liver inflammation can evolve to life threatening complications. Experimental data from HBV infected chimpanzees and HBV transgenic mice have indicated that cytotoxic T cells are the main cell type responsible for inhibition of viral replication, but also for hepatocyte lysis during chronic HBV infection. Their lower activation and impaired function in later stages of infection was suggested as a possible mechanism that allowed for low levels of viral replication. The lack of an interferon response in these models also indicated the importance of adaptive immunity in clearing the infection. Increased knowledge of the signalling pathways and pathogen associated molecular patterns that govern activation of innate immunity in the early stages of viral infections in general has led to a re-evaluation of the innate immune system in HBV infection. Numerous studies have shown that HBV employs active strategies to evade innate immune responses and induce immunosuppression. Some of the immune components targeted by HBV include dendritic cells, natural killer cells, T regulatory cells and signalling pathways of the interferon response. This review will present the current understanding of innate immunity in HBV infection and of the challenges associated with clearing of the HBV infection.

2014-01-01

118

Satellite-derived potential evapotranspiration for distributed hydrologic runoff modeling  

NASA Astrophysics Data System (ADS)

Distributed models have the ability of incorporating spatially variable data, especially high resolution forcing inputs such as precipitation, temperature and evapotranspiration in hydrologic modeling. Use of distributed hydrologic models for operational streamflow prediction has been partially hindered by a lack of readily available, spatially explicit input observations. Potential evapotranspiration (PET), for example, is currently accounted for through PET input grids that are based on monthly climatological values. The goal of this study is to assess the use of satellite-based PET estimates that represent the temporal and spatial variability, as input to the National Weather Service (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). Daily PET grids are generated for six watersheds in the upper Mississippi River basin using a method that applies only MODIS satellite-based observations and the Priestly Taylor formula (MODIS-PET). The use of MODIS-PET grids will be tested against the use of the current climatological PET grids for simulating basin discharge. Gridded surface temperature forcing data are derived by applying the inverse distance weighting spatial prediction method to point-based station observations from the Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS). Precipitation data are obtained from the Climate Prediction Center's (CPC) Climatology-Calibrated Precipitation Analysis (CCPA). A-priori gridded parameters for the Sacramento Soil Moisture Accounting Model (SAC-SMA), Snow-17 model, and routing model are initially obtained from the Office of Hydrologic Development and further calibrated using an automated approach. The potential of the MODIS-PET to be used in an operational distributed modeling system will be assessed with the long-term goal of promoting research to operations transfers and advancing the science of hydrologic forecasting.

Spies, R. R.; Franz, K. J.; Bowman, A.; Hogue, T. S.; Kim, J.

2012-12-01

119

Understanding uncertainty in process-based hydrological models  

NASA Astrophysics Data System (ADS)

Building an environmental model requires making a series of decisions regarding the appropriate representation of natural processes. While some of these decisions can already be based on well-established physical understanding, gaps in our current understanding of environmental dynamics, combined with incomplete knowledge of properties and boundary conditions of most environmental systems, make many important modeling decisions far more ambiguous. There is consequently little agreement regarding what a 'correct' model structure is, especially at relatively larger spatial scales such as catchments and beyond. In current practice, faced with such a range of decisions, different modelers will generally make different modeling decisions, often on an ad hoc basis, based on their balancing of process understanding, the data available to evaluate the model, the purpose of the modeling exercise, and their familiarity with or investment in an existing model infrastructure. This presentation describes development and application of multiple-hypothesis models to evaluate process-based hydrologic models. Our numerical model uses robust solutions of the hydrology and thermodynamic governing equations as the structural core, and incorporates multiple options to represent the impact of different modeling decisions, including multiple options for model parameterizations (e.g., below-canopy wind speed, thermal conductivity, storage and transmission of liquid water through soil, etc.), as well as multiple options for model architecture, that is, the coupling and organization of different model components (e.g., representations of sub-grid variability and hydrologic connectivity, coupling with groundwater, etc.). Application of this modeling framework across a collection of different research basins demonstrates that differences among model parameterizations are often overwhelmed by differences among equally-plausible model parameter sets, while differences in model architecture lead to pronounced differences in model simulations at larger spatial scales. Work is ongoing to use this modeling framework to understand differences among existing models, especially, to understand why different hydrologic models have a very different portrayal of the impacts of climate change on water resources.

Clark, M. P.; Kavetski, D.; Slater, A. G.; Newman, A. J.; Marks, D. G.; Landry, C.; Lundquist, J. D.; Rupp, D. E.; Nijssen, B.

2013-12-01

120

Application of environmental models to different hydrological systems  

Microsoft Academic Search

In recent years global problems such as climatic change, acid rain, and water pollution in surface and subsurface environments dominate discussions of world environmental problems. In this paper, the roles of hydrologic processes and hydrogeochemical processes are investigated through development, modification, and application of mathematical models for addressing point and non-point source water quality modelling of receiving waters: surface water,

A. Ghosh Bobba; Vijay P. Singh; Lars Bengtsson

2000-01-01

121

Multiscale Parameter Regionalization of a Grid-based Hydrologic Model  

Microsoft Academic Search

Integrated water resources planning and management at the mesoscale requires, among other things of a parsimonious and distributed hydrologic model able to reproduce not only the discharge hydrograph at any gauged or ungauged location but also the spatio-temporal distribution of state variables such as soil moisture. Furthermore, this model should be able to take into account changes in land cover

L. Samaniego; R. Kumar; S. Attinger

2008-01-01

122

The Use of Simulation Models in Teaching Geomorphology and Hydrology.  

ERIC Educational Resources Information Center

Learning about the physical environment from computer simulation models is discussed in terms of three stages: exploration, experimentation, and calibration. Discusses the effective use of models and presents two computer simulations written in BBC BASIC, STORFLO (for catchment hydrology) and SLOPEK (for hillslope evolution). (Author/GEA)

Kirkby, Mike; Naden, Pam

1988-01-01

123

Modelling the hydrological behaviour of a mountain catchment using TOPMODEL  

Microsoft Academic Search

The mathematical catchment model TOPMODEL was used to simulate the hydrological behaviour of a mountain catchment at Jalovecky Creek, Western Tatras, Slovakia. The model provided adequate results in simulation of daily runoff from the catchment for the period 1 August 1987–31 October 1993. Air temperature inversions, typical of certain periods in mountain catchments, caused overestimation of simulated runoff because of

L. Holko; A Lepistö

1997-01-01

124

A conceptual glacio-hydrological model for high mountainous catchments  

Microsoft Academic Search

In high mountainous catchments, the spatial precipitation and therefore the overall water balance is generally difficult to estimate. The present paper describes the structure and calibration of a semi-lumped conceptual glacio-hydrological model for the joint simulation of daily discharge and annual glacier mass balance that represents a better integrator of the water balance. The model has been developed for climate

B. Schaefli; B. Hingray; M. Niggli; A. Musy

2005-01-01

125

A sequential Bayesian approach for hydrologic model selection and prediction  

NASA Astrophysics Data System (ADS)

When a single model is used for hydrologic prediction, it must be capable of estimating system behavior accurately at all times. Multiple-model approaches integrate several model behaviors and, when effective, they can provide better estimates than that of any single model alone. This paper discusses a sequential model fusion strategy that uses the Bayes rule. This approach calculates each model's transient posterior distribution at each time when a new observation is available and merges all model estimates on the basis of each model's posterior probability. This paper demonstrates the feasibility of this approach through case studies that fuse three hydrologic models, auto regressive with exogenous inputs, Sacramento soil moisture accounting, and artificial neural network models, to predict daily watershed streamflow.

Hsu, Kuo-Lin; Moradkhani, Hamid; Sorooshian, Soroosh

2009-12-01

126

Hydrologic Data Assimilation: State Estimation and Model Calibration  

NASA Astrophysics Data System (ADS)

This thesis is a combination of two separate studies which examine hydrologic data assimilation techniques: (1) to determine the applicability of assimilation of remotely sensed data in operational models and (2) to compare the effectiveness of assimilation and other calibration techniques. The first study examines the ability of Data Assimilation of remotely sensed microwave radiance data to improve snow water equivalent prediction, and ultimately operational streamflow forecasts. Operational streamflow forecasts in the National Weather Service River Forecast Center are produced with a coupled SNOW17 (snow model) and SACramento Soil Moisture Accounting (SAC-SMA) model. A comparison of two assimilation techniques, the Ensemble Kalman Filter (EnKF) and the Particle Filter (PF), is made using a coupled SNOW17 and the Microwave Emission Model for Layered Snowpack model to assimilate microwave radiance data. Microwave radiance data, in the form of brightness temperature (TB), is gathered from the Advanced Microwave Scanning Radiometer-Earth Observing System at the 36.5GHz channel. SWE prediction is validated in a synthetic experiment. The distribution of snowmelt from an experiment with real data is then used to run the SAC-SMA model. Several scenarios on state or joint state-parameter updating with TB data assimilation to SNOW-17 and SACSMA models were analyzed, and the results show potential benefit for operational streamflow forecasting. The second study compares the effectiveness of different calibration techniques in hydrologic modeling. Currently, the most commonly used methods for hydrologic model calibration are global optimization techniques. While these techniques have become very efficient and effective in optimizing the complicated parameter space of hydrologic models, the uncertainty with respect to parameters is ignored. This has led to recent research looking into Bayesian Inference through Monte Carlo methods to analyze the ability to calibrate models and represent the uncertainty in relation to the parameters. Research has recently been performed in filtering and Markov Chain Monte Carlo (MCMC) techniques for optimization of hydrologic models. At this point, a comparison of the effectiveness of global optimization, filtering and MCMC techniques has yet to be reported in the hydrologic modeling community. This study compares global optimization, MCMC, the PF, the Particle Smoother, the EnKF and the Ensemble Kalman Smoother for the purpose of parameter estimation in both the HyMod and SAC-SMA hydrologic models.

Dechant, Caleb Matthew

127

Hydrologic Modeling in a Service-Oriented Architecture  

NASA Astrophysics Data System (ADS)

Service Oriented Architectures (SOA) offer an approach for creating hydrologic models whereby a model is decomposed into independent computational services that are geographically distributed yet accessible through the Internet. The advantage of this modeling approach is that diverse groups can contribute computational routines that are usable by a wide community, and these routines can be used across operating systems and languages with minimal requirements on the client computer. While the approach has clear benefits in building next generation hydrologic models, a number of challenges must be addressed in order for the approach to reach its full potential. One such challenge in achieving service-oriented hydrologic modeling is establishing standards for web service interfaces and for service-to-service data exchanges. This study presents a prototype service-oriented modeling system that leverages existing protocols and standards (OpenMI, WaterML, GML, etc.) to perform service-oriented hydrologic modeling. The goal of the research is to access the completeness of these existing protocols and standards in achieving the goal, and to highlight shortcomings that should be addressed through future research and development efforts.

Goodall, J. L.

2008-12-01

128

Use of hydrologic and hydrodynamic modeling for ecosystem restoration  

USGS Publications Warehouse

Planning and implementation of unprecedented projects for restoring the greater Everglades ecosystem are underway and the hydrologic and hydrodynamic modeling of restoration alternatives has become essential for success of restoration efforts. In view of the complex nature of the South Florida water resources system, regional-scale (system-wide) hydrologic models have been developed and used extensively for the development of the Comprehensive Everglades Restoration Plan. In addition, numerous subregional-scale hydrologic and hydrodynamic models have been developed and are being used for evaluating project-scale water management plans associated with urban, agricultural, and inland costal ecosystems. The authors provide a comprehensive summary of models of all scales, as well as the next generation models under development to meet the future needs of ecosystem restoration efforts in South Florida. The multiagency efforts to develop and apply models have allowed the agencies to understand the complex hydrologic interactions, quantify appropriate performance measures, and use new technologies in simulation algorithms, software development, and GIS/database techniques to meet the future modeling needs of the ecosystem restoration programs. Copyright ?? 2011 Taylor & Francis Group, LLC.

Obeysekera, J.; Kuebler, L.; Ahmed, S.; Chang, M. -L.; Engel, V.; Langevin, C.; Swain, E.; Wan, Y.

2011-01-01

129

Neural Networks for Hydrological Modeling Tool for Operational Purposes  

NASA Astrophysics Data System (ADS)

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. Runoff is generally computed using rainfall-runoff models. Computer based hydrologic models have become popular for obtaining hydrological forecasts and for managing water systems. Rainfall-runoff library (RRL) is computer software developed by Cooperative Research Centre for Catchment Hydrology (CRCCH), Australia consisting of five different conceptual rainfall-runoff models, and has been in operation in many water resources applications in Australia. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conceptual models actually in use in real catchments. In this paper, the results from an investigation on the use of RRL and ANNs are presented. Out of the five conceptual models in the RRL toolkit, SimHyd model has been used. Genetic Algorithm has been used as an optimizer in the RRL to calibrate the SimHyd model. Trial and error procedures were employed to arrive at the best values of various parameters involved in the GA optimizer to develop the SimHyd model. The results obtained from the best configuration of the SimHyd model are presented here. Feed-forward neural network model structure trained by back-propagation training algorithm has been adopted here to develop the ANN models. The daily rainfall and runoff data derived from Bird Creek Basin, Oklahoma, USA have been employed to develop all the models included here. A wide range of error statistics have been used to evaluate the performance of all the models developed in this study. The ANN models developed consistently outperformed the conceptual model developed in this study. The results obtained in this study indicate that the ANNs can be extremely useful tools for modeling the complex rainfall-runoff process in real catchments. The ANNs should be adopted in real catchments for hydrological modeling and forecasting. It is hoped that more research will be carried out to compare the performance of ANN model with the conceptual models actually in use at catchment scales. It is hoped that such efforts may go a long way in making the ANNs more acceptable by the policy makers, water resources decision makers, and traditional hydrologists.

Bhatt, Divya; Jain, Ashu

2010-05-01

130

Integrating Geophysics, Geology, and Hydrology for Enhanced Hydrogeological Modeling  

NASA Astrophysics Data System (ADS)

Geophysical measurements are important for providing information on the geological structure to hydrological models. Regional scale surveys, where several watersheds are mapped at the same time using helicopter borne transient electromagnetic, results in a geophysical model with a very high lateral and vertical resolution of the geological layers. However, there is a bottleneck when it comes to integrating the information from the geophysical models into the hydrological model. This transformation is difficult, because there is not a simple relationship between the hydraulic conductivity needed for the hydrological model and the electrical conductivity measured by the geophysics. In 2012 the Danish Council for Strategic Research has funded a large research project focusing on the problem of integrating geophysical models into hydrological models. The project involves a number of Danish research institutions, consulting companies, a water supply company, as well as foreign partners, USGS (USA), TNO (Holland) and CSIRO (Australia). In the project we will: 1. Use statistical methods to describe the spatial correlation between the geophysical and the lithological/hydrological data; 2. Develop semi-automatic or automatic methods for transforming spatially sampled geophysical data into geological- and/or groundwater-model parameter fields; 3. Develop an inversion method for large-scale geophysical surveys in which the model space is concordant with the hydrological model space 4. Demonstrate the benefits of spatially distributed geophysical data for informing and updating groundwater models and increasing the predictive power of management scenarios. 5. Develop a new receiver system for Magnetic Resonance Sounding data and further enhance the resolution capability of data from the SkyTEM system. 6. In test areas in Denmark, Holland, USA and Australia we will use data from existing airborne geophysical data, hydrological and geological data and also collect new airborne data, MRS surface and downhole data, and pump test data. The project is still in a startup phase but we already have results from two existing algorithms. The first one is an algorithm making a full joint inversion of Magnetic Resonance Sounding (MRS) data, Transient Electromagnetic Data (TEM) and pump test data. The second one is an algorithm using geostatistic and linear inverse theory to link boreholes categorized into clay and sand sequences together with electrical resistivities measured in spatially distributed soundings resulting in 3D models of clay and sand. We will present the HyGEM project and show results from the first two algorithms developed in the project.

Auken, E.

2012-12-01

131

Hydrological Modelling of a Canadian Prairie Wetland Basin  

NASA Astrophysics Data System (ADS)

The eastern Canadian Prairies are a region of cropland, pasture, woodland and wetlands. The region is characterized with many poor and internal drainage systems and large surface water storage terms, so watersheds here have proven challenging to hydrological models that assume good drainage to a stream. The cold climate means that snow redistribution, snowmelt and infiltration to frozen soils are important in regulating runoff generation. The Cold Regions Hydrological Modelling platform (CRHM) is an assembly system to create physically based, flexible, object oriented models. It was used to develop a prairie hydrological model to simulate the hydrological cycling in prairie watersheds and eventually the impact of land use and wetland change on hydrology. Smith Creek Basin (˜445 km2) was divided into five sub- basins, and a modelling feature - 'Groups' or representative basins was applied to model these sub-basins. Within each sub-basin, seven hydrological response units (HRUs): fallow, stubble, grassland, river channel, open water, woodland, and wetland were derived from supervised classification of SPOT 5 imagery. Physically based modules were sequentially assembled in CRHM and applied to all HRUs to simulate hydrological processes, including redistribution of snow by wind, snowmelt, infiltration, evaporation, soil moisture balance, wetland storage and runoff routing. Almost all parameters were set from values determined by remote sensing or field observations; however calibration was used to determine upland depressional storage capacity which could not be measured. Model performance in simulating snow accumulation during the winter of 2007-08 and the subsequent spring freshet was evaluated. Results show the model had generally good performance in estimating snow accumulation, with Root Mean Square Difference (RMSD) ranging from 1.8 mm to 7.9 mm for fallow, stubble, open water and woodland HRUs. Grassland, river channel and wetland HRUs had moderately large values of RMSD, ranging from 6.4 mm to 18.1 mm. The model estimated springtime basin streamflow fairly well; RMSD and Model Bias (MB) were 0.16 m3/s and -0.22, respectively. The model was also tested on an extremely wet year, 1995, and a drought year 2002. In the wet year, wetland storage was nearly full at the time of snowmelt; in the drought year wetland storage was severely depleted. The model showed satisfactory performance in both years though parameter uncertainty was affected by the lack of intense field observations.

Fang, X.; Pomeroy, J.; Brown, T.; Guo, X.; Westbrook, C.

2009-05-01

132

Bayesian parameter uncertainty modeling in a macroscale hydrologic model and its impact on Indian river basin hydrology under climate change  

NASA Astrophysics Data System (ADS)

Macroscale hydrologic models (MHMs) were developed to study changes in land surface hydrology due to changing climate over large domains, such as continents or large river basins. However, there are many sources of uncertainty introduced in MHM hydrological simulation, such as model structure error, ineffective model parameters, and low-accuracy model input or validation data. It is hence important to model the uncertainty arising in projection results from an MHM. The objective of this study is to present a Bayesian statistical inference framework for parameter uncertainty modeling of a macroscale hydrologic model. The Bayesian approach implemented using Markov Chain Monte Carlo (MCMC) methods is used in this study to model uncertainty arising from calibration parameters of the Variable Infiltration Capacity (VIC) MHM. The study examines large-scale hydrologic impacts for Indian river basins and changes in discharges for three major river basins with distinct climatic and geographic characteristics, under climate change. Observed/reanalysis meteorological variables such as precipitation, temperature and wind speed are used to drive the VIC macroscale hydrologic model. An objective function describing the fit between observed and simulated discharges at four stations is used to compute the likelihood of the parameters. An MCMC approach using the Metropolis-Hastings algorithm is used to update probability distributions of the parameters. For future hydrologic simulations, bias-corrected GCM projections of climatic variables are used. The posterior distributions of VIC parameters are used for projection of 5th and 95th percentile discharge statistics at four stations, namely, Farakka, Jamtara, Garudeshwar, and Vijayawada for an ensemble of three GCMs and three scenarios, for two time slices. Spatial differences in uncertainty projections of runoff and evapotranspiration for years 2056-2065 for the a1b scenario at the 5th and 95th percentile levels are also projected. Results from the study show increased mean monthly discharges for Farakka and Vijayawada stations, and increased low, mid and high duration flows at Farakka, Jamtara and Vijayawada for the future. However, it is seen that uncertainty introduced due to choice of GCM, is larger than that due to parameter uncertainty for the VIC MHM. The largest effects of runoff predictive uncertainty due to uncertainty in VIC parameters are seen in the Himalayan foothills belt, and the high-precipitation Northeast region of the country. It is demonstrated through the study that it is relevant and feasible to provide Bayesian uncertainty estimates for macroscale models in projection of large-scale and regional hydrologic impacts.

Raje, D.; Krishnan, R.

2012-08-01

133

Bayesian Selection of Hydrological Models Using Sequential Monte Carlo Sampling  

NASA Astrophysics Data System (ADS)

An important challenge with using computer models to represent hydrological systems is the decision of how much detail to include in the model. A model that simplifies the real system too much obviously may not be reliable. However, a model can also be too complex, for example in case there is not enough data available to reliably specify all necessary input for the model. Bayesian statistics provides a general framework for deciding between a set of competing models of varying complexity; the approach involves computing the posterior probability of each model, as the product of the prior model probability and the model (marginal) likelihood. The latter involves integrating or averaging the likelihood function over the entire parameter space, which can be quite challenging for models with many parameters. Several easy-to-compute approximations are available (e.g. Bayes Information Criterion or BIC), however these may not always be valid for highly nonlinear hydrological models. Alternatively, we present and apply a Monte Carlo algorithm that results in accurate estimates of posterior model probabilities without the need for simplifying assumptions about the model structure. The algorithm relies on a combination of path sampling, Markov Chain Monte Carlo, and resampling. We present a hydrological application that illustrates these features.

Schoups, G.; Vrugt, J. A.

2011-12-01

134

Physical Modeling of Hydrologic Processes in South Central Texas  

NASA Astrophysics Data System (ADS)

Flood magnitude and recurrence modeling and analysis play an important role in water resources planning, management, and permitting. In both urban and rural situations, flood analysis is important to flood plain mapping and the development of best management practices for both environmental and engineering concerns. The majority of annual precipitation in South Texas results from extreme, large storm events, which produce flash floods (the number one cause of weather-related deaths in Texas). Surface geology such as such as Edward out crop faulting zone at Balcones escarpment has different properties than the classified soil; affect the soil parameters such as infiltration or hydraulic conductivity. This result in a very high infiltration and channel loss as a recharge component to the Edward aquifer from the surface runoff and rivers that are crossing the recharge zone, such as Nueces, San Antonio, Guadalupe and Colorado Rivers. Water quality is another issue in hydrological modeling, specifically in south central Texas. Water quality assessment is another issue on hydrological modeling in south central Texas. SWAT Soil and water assessment tool model is used for water quality assessment in San Antonio River basin since the rainfall runoff simulation is a necessity to derive the surface water quality process especially in the streams. With the advances in the Geographical information system (GIS) and instant precipitation products such as next generation radar (NEXRAD) and data acquisition for these products, the accuracy of the hydrological models has improved. Different hydrological models were used to evaluate the surface water and other hydrological cycle components in different watersheds in south central Texas through different events and their different causes and effects in these watersheds. Some of them are semi distributed and lumped models such as Soil and Water Assessment Tool (SWAT), Hydrologic Modeling System (HEC-HMS) and physically based distributed model Girded Surface Subsurface Hydrologic Assessment GSSHA taking the advances of GIS, NEXRAD product, remote sensing and other product such as gridded land use and soil map to achieve the highest accuracy of these models.

El Hassan, A.; Sharif, H.; Xie, H.; Terrance, J.; Mcclelland, J.

2012-04-01

135

Integration of GRACE mass variations into a global hydrological model  

NASA Astrophysics Data System (ADS)

Time-variable gravity data of the GRACE (Gravity Recovery And Climate Experiment) satellite mission provide global information on temporal variations of continental water storage. In this study, we incorporate GRACE data for the first time directly into the tuning process of a global hydrological model to improve simulations of the continental water cycle. For the WaterGAP Global Hydrology Model (WGHM), we adopt a multi-objective calibration framework to constrain model predictions by both measured river discharge and water storage variations from GRACE and illustrate it on the example of three large river basins: Amazon, Mississippi and Congo. The approach leads to improved simulation results with regard to both objectives. In case of monthly total water storage variations we obtained a RMSE reduction of about 25 mm for the Amazon, 6 mm for the Mississippi and 1 mm for the Congo river basin. The results highlight the valuable nature of GRACE data when merged into large-scale hydrological modeling. Furthermore, they reveal the utility of the multi-objective calibration framework for the integration of remote sensing data into hydrological models.

Werth, S.; Güntner, A.; Petrovic, S.; Schmidt, R.

2009-01-01

136

Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation  

NASA Astrophysics Data System (ADS)

A universal problem of the calibration of hydrological models is the equifinality of different parameter sets derived from the calibration of models against total runoff values. This is an intrinsic problem stemming from the quality of the calibration data and the simplified process representation by the model. However, discharge data contains additional information which can be extracted by signal processing methods. An analysis specifically developed for the disaggregation of runoff time series into flow components is the Functional Streamflow Disaggregation (FSD; Carl & Behrendt, 2008). This method is used in the calibration of an implementation of the hydrological model SWIM in a medium sized watershed in Thailand. FSD is applied to disaggregate the discharge time series into three flow components which are interpreted as base flow, inter-flow and surface runoff. In addition to total runoff, the model is calibrated against these three components in a modified GLUE analysis, with the aim to identify structural model deficiencies, assess the internal process representation and to tackle equifinality. We developed a model dependent (MDA) approach calibrating the model runoff components against the FSD components, and a model independent (MIA) approach comparing the FSD of the model results and the FSD of calibration data. The results indicate, that the decomposition provides valuable information for the calibration. Particularly MDA highlights and discards a number of standard GLUE behavioural models underestimating the contribution of soil water to river discharge. Both, MDA and MIA yield to a reduction of the parameter ranges by a factor up to 3 in comparison to standard GLUE. Based on these results, we conclude that the developed calibration approach is able to reduce the equifinality of hydrological model parameterizations. The effect on the uncertainty of the model predictions is strongest by applying MDA and shows only minor reductions for MIA. Besides further validation of FSD, the next steps include an extension of the study to different catchments and other hydrological models with a similar structure.

Lüdtke, Stefan; Apel, Heiko; Nied, Manuela; Carl, Peter; Merz, Bruno

2014-05-01

137

Do land parameters matter in large-scale hydrological modelling?  

NASA Astrophysics Data System (ADS)

Many of the most pending issues in large-scale hydrology are concerned with predicting hydrological variability at ungauged locations. However, current-generation hydrological and land surface models that are used for their estimation suffer from large uncertainties. These models rely on mathematical approximations of the physical system as well as on mapped values of land parameters (e.g. topography, soil types, land cover) to predict hydrological variables (e.g. evapotranspiration, soil moisture, stream flow) as a function of atmospheric forcing (e.g. precipitation, temperature, humidity). Despite considerable progress in recent years, it remains unclear whether better estimates of land parameters can improve predictions - or - if a refinement of model physics is necessary. To approach this question we suggest scrutinizing our perception of hydrological systems by confronting it with the radical assumption that hydrological variability at any location in space depends on past and present atmospheric forcing only, and not on location-specific land parameters. This so called "Constant Land Parameter Hypothesis (CLPH)" assumes that variables like runoff can be predicted without taking location specific factors such as topography or soil types into account. We demonstrate, using a modern statistical tool, that monthly runoff in Europe can be skilfully estimated using atmospheric forcing alone, without accounting for locally varying land parameters. The resulting runoff estimates are used to benchmark state-of-the-art process models. These are found to have inferior performance, despite their explicit process representation, which accounts for locally varying land parameters. This suggests that progress in the theory of hydrological systems is likely to yield larger improvements in model performance than more precise land parameter estimates. The results also question the current modelling paradigm that is dominated by the attempt to account for locally varying land parameters in ever greater detail. While improved physically-based models are under development, the proposed statistical model can be used to produce full space-time estimates of monthly runoff in Europe, contributing to practical aspects of the discipline including water resources monitoring and seasonal forecasting.

Gudmundsson, Lukas; Seneviratne, Sonia I.

2013-04-01

138

Hydrological Distributed Modelling on Non Conventional Basin Partitioning  

Microsoft Academic Search

Mathematical modeling of environmental processes often requires strongly non linear and highly spatially and temporally variable phenomena to be described. Particularly, as far as hydrology is concerned, a detailed description of catchment topography is fundamental in order to correctly describe viz. runoff generation, debris flow mechanics and shallow landslide processes triggered by heavy rainfall. The topographic analysis is basic both

M. Rulli; G. Menduni; R. Rosso

2002-01-01

139

Hydrological Modelling of a Canadian Prairie Wetland Basin  

Microsoft Academic Search

The eastern Canadian Prairies are a region of cropland, pasture, woodland and wetlands. The region is characterized with many poor and internal drainage systems and large surface water storage terms, so watersheds here have proven challenging to hydrological models that assume good drainage to a stream. The cold climate means that snow redistribution, snowmelt and infiltration to frozen soils are

X. Fang; J. Pomeroy; T. Brown; X. Guo; C. Westbrook

2009-01-01

140

A two-layer model of soil hydrology  

Microsoft Academic Search

A two-layer model of soil hydrology is developed for applications where only limited computer time and complexity are allowed. Volumetric soil water is computed in a thin upper layer for use in calculation of surface evaporation. Storage of water is computed for an underlying deeper layer.

L. Mahrt; H. Pan

1984-01-01

141

Hidden Markov model segmentation of hydrological and enviromental time series  

Microsoft Academic Search

Motivated by Hubert's segmentation procedure (16, 17), we discuss the application of hidden Markov models (HMM) to the segmentation of hydrological and enviromental time series. We use a HMM algorithm which segments time series of several hundred terms in a few seconds and is compu- tationally feasible for even longer time series. The segmentation algorithm computes the Maximum Likelihood segmentation

Athanasios Kehagias

2002-01-01

142

Hydrological responses to dynamically and statistically downscaled climate model output  

Microsoft Academic Search

Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction\\/ National Center for Atmospheric Research (NCEP\\/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic simulations of basin scale

Robert L. Wilby; Lauren E. Hay; William J. Gutowski Jr.; Raymond W. Arritt; Eugene S. Takle; Zaitao Pan; George H. Leavesley; Martyn P. Clark

2000-01-01

143

Application of regional climate data as input for hydrological modelling  

NASA Astrophysics Data System (ADS)

The goal of this study was to check the suitability of application of regional climate model (RCM) forcing data for hydrological modelling. The spatially distributed finite volume based hydrological model was set-up for the pilot basin in central Latvia (river Aiviekste, catchment area 9300 sq.km). The primary forcing input for the model consists of the time-series of temperature and precipitation. We considered set of 21 RCM model output data from the PRUDENCE project. They were statisically tested against temperature and precipitation observations for the reference period (1961-1990). The best performing RCM was selected according to penalty function constructed based on monthly average temperature, precipitation and montly standard deviation of temperature and precipitation. The calibrated hydrological model was employed for the run-off calculations of climatic reference period (1961-1990). The first step of the study was to statistically compare (1) observed discharge, (2) modelled discharge using observed temperature and precipitation as the forcing, (3) modelled discharge using the temperature and precipitation time series from the best RCM as the forcing. The monthly average observed discharge agrees well with the modelled discharge in case of usage of the observed forcing. The agreement of observed discharge with modelled discharge using RCM data is rather disappointing, especially during winter and spring snow melt flood periods. Usage of the meteorological forcing from the RCM's reference period overestimates yearly average discharge by approximately 70%. The second step of our study was to modify and use the modified RCM data as an input for hydrological modelling. The modification method relies on equalizing of temperature and precipitation histograms between observed and RCM data for each day of the year and each observation location. We show that monthly average discharges agree quite well with observed in the case of use of modified RCM data as a forcing. In the third step we applied RCM modification method to the climatic scenarious A2 and B2 modeled by selected regional climate model and calculated corresponding hydrological scenarious. The main features of the expected future hydrological regime for our region were revealed, namely, (1) yearly average run-off slightly decreases, (2) winter run-off significant increases, (3) value of the peak discharge during spring snow-melt is significantly smaller, (4) spring peak shifts towards winter.

Sennikovs, J.; Timuhins, A.

2009-04-01

144

Hydrological modelling in a "big data" era: a proof of concept of hydrological models as web services  

NASA Astrophysics Data System (ADS)

Dealing with the massive increase in global data availability of all sorts is increasingly being known as "big data" science. Indeed, largely leveraged by the internet, a new resource of data sets emerges that are so large and heterogeneous that they become awkward to work with. New algorithms, methods and models are needed to filter such data to find trends, test hypotheses, make predictions and quantify uncertainties. As a considerable share of the data relate to environmental processes (e.g., satellite images, distributed sensor networks), this evolution provides exciting challenges for environmental sciences, and hydrology in particular. Web-enabled models are a promising approach to process large and distributed data sets, and to provide tailored products for a variety of end-users. It will also allow hydrological models to be used as building blocks in larger earth system simulation systems. However, in order to do so we need to reconsider the ways that hydrological models are built, results are made available, and uncertainties are quantified. We present the results of an experimental proof of concept of a hydrological modelling web-service to process heterogeneous hydrological data sets. The hydrological model itself consists of a set of conceptual model routines implemented with on a common platform. This framework is linked to global and local data sets through web standards provided by the Open Geospatial Consortium, as well as to a web interface that enables an end-user to request stream flow simulations from a self-defined location. In essence, the proof-of-concept can be seen as an implementation of the "Models of Everywhere" concept introduced by Beven in 2007. Although the setup is operational and effectively simulates stream flow, we identify several bottlenecks for optimal hydrological simulation in a web-context. The major challenges we identify are related to (1) model selection; (2) uncertainty quantification, and (3) user interaction and scenario analysis. Model selection is inherent to hydrological modelling, because of the large spatial and temporal variability of processes, which inhibits the use of one optimal model structure. However, in a web context it becomes paramount that such selection is automatic, yet objective and transparent. Similarly, uncertainty quantification is a mainstream practice in hydrological modelling, but in a web-context uncertainty analysis face unprecedented challenges in terms of tracking uncertainties throughout a possibly geographically distributed workflow, as well as dealing with an extreme heterogeneity of data availability. Lastly, the ability of end-users to interact directly with hydrological models poses specific challenges in terms of mapping user scenarios (e.g., a scenario of land-use change) into the model parameter space for prediction and uncertainty quantification. The setup has been used in several scientific experiments, including the large-scale UK consortium project on an Environmental Virtual Observatory pilot.

Buytaert, Wouter; Vitolo, Claudia

2013-04-01

145

Identification of possible structural error in hydrological models  

NASA Astrophysics Data System (ADS)

Hydrological Models are simplifications and theoretical approximations of complex natural phenomena. Hence, they cannot predict perfectly what happen in natural systems. There are several reasons; some of the main reasons are error in the input data, imperfect model structure, insufficient information for parameter identification etc. The identification of structural error in a complex model is very difficult task. This is especially difficult as the final differences between observation and model results are a combined consequence of the above reasons. In this study we aimed to develop a tool to identify possible model structural error in hydrological model by using the concept of the data depth function. The model was calibrated using the ROPE (Bárdossy and Singh 2008) algorithm and the optimal parameter space was obtained. From N optimal parameter sets N discharge series were obtained and boundary of the convex hull from d-dimensional dataset corresponding N discharge series (DB) is taken for further analysis. A d-dimensional dataset corresponding to the observed discharge (DX) is taken and depth of the each elements of observed discharge is calculated with respect to the boundary of the convex hull from N model discharge series. If there are elements in DX whose depths are zero with respect to the convex hull (DB), then those corresponding to d-days trajectories of the observation for which there is no similarity in any of the model parameterization. These elements can give possible indication for model structure errors. The methodology was demonstrated on two models HYMOD and TopNet in Pelorous catchment of New Zealand. Bárdossy, A. and S. K. Singh (2008). "Robust estimation of hydrological model parameters." Hydrology and Earth System Sciences 12: 1273-1283.

Singh, S. K.; Bárdossy, A.; McMillan, H.

2012-04-01

146

Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River basin  

NASA Astrophysics Data System (ADS)

Terrestrial water storage (TWS) can be defined as an integrated measure of surface water, soil moisture, snow water, and groundwater. TWS data is valuable for water resources management and hydrology. The ability to simulate realistic TWS is essential for understanding past hydrological events and predicting future changes of the hydrological cycle. Inadequacies in physics, deficiencies in land characteristics and uncertainties in meteorological data commonly limit the performance of hydrological models in estimating TWS. In this study, we investigated the benefits of assimilating TWS derived from the Gravity Recovery And Climate Experiment (GRACE) into the Wflow HBV-96 model using the Ensemble Kalman Filter (EnKF). Since hydrological model parameters are often uncertain over a large part of the Earth, we investigated the impact of GRACE assimilation in different model scenarios representing different degrees of data availability. Four case studies were considered comparing calibrated and non-calibrated model parameters and local and global forcing data. The chosen study area is the Rhine River basin. Our results were validated using in-situ stream gauge data. In all scenarios, the temporal signatures of the averaged TWS are similar after assimilating GRACE while the spatial distribution is heavily influenced by the model parameters and input data as well as their uncertainties. Assimilation using the EnKF reduced the standard deviation at every updating stage, resulting in lower standard deviations than the model or the observations alone. Discrepancies between the local and global precipitation products had a significant impact on discharge estimates. For instance, when the global forcing data were used, discharge was drastically overestimated when spurious heavy rainfall occurred during the winter. Based on the correlation coefficient, Nash-Sutcliffe coefficient (NS), and root-mean-square error (RMSE) computed between the estimated and measured discharges at 13 gauge stations, we concluded that GRACE assimilation slightly improves the model performance when the model is well calibrated (calibrated parameters with local forcing data). More importantly, the improvement observed for the non-calibrated model (non-calibrated parameters with global forcing data), suggests that the impact of GRACE assimilation may be more significant in data-sparse regions.

Tangdamrongsub, Natthachet; Steele-Dunne, Susan; Gunter, Brian C.; Widiastuti, Endang; Weerts, Albrecht; Ditmar, Pavel; Tsompanopoulos, Efstratios

2014-05-01

147

Characterization of Near-Surface Moisture Dynamics Using Hydrologic Model-Based Interpretation of GPR Data.  

National Technical Information Service (NTIS)

The objective of this project was to test whether transient GPR data provide useful information for constraining hydrologic processes in the vadose zone and evaluate alternative methods for hydrologic model calibration using this data. Modeling studies co...

S. Moysey

2009-01-01

148

Assessment of Digital Elevation Model (DEM) aggregation methods for hydrological modeling: Lake Chad basin, Africa  

Microsoft Academic Search

Digital Elevation Models (DEMs) are used to compute the hydro-geomorphological variables required by distributed hydrological models. However, the resolution of the most precise DEMs is too fine to run these models over regional watersheds. DEMs therefore need to be aggregated to coarser resolutions, affecting both the representation of the land surface and the hydrological simulations. In the present paper, six

Mathieu Le Coz; François Delclaux; Pierre Genthon; Guillaume Favreau

2009-01-01

149

Modeling Soil Depth Based Upon Topographic and Land Cover Attributes to Improve Models of Hydrological Response  

Microsoft Academic Search

Soil depth is an important input parameter in hydrological modeling. Presently, the soil depth data available in national soil databases (STATSGO, SSURGO) is provided as averages within generalized map units. Spatial uncertainty within these units limits their applicability for distributed hydrological modeling in complex terrain. Statistical models were developed for prediction of soil depth in a semiarid mountainous watershed based

T. K. Tesfa; D. G. Tarboton; D. G. Chandler; J. P. McNamara

2008-01-01

150

Improving the transferability of hydrological model parameters under changing conditions  

NASA Astrophysics Data System (ADS)

Hydrological models are widely utilized to describe catchment behaviors with observed hydro-meteorological data. Hydrological process may be considered as non-stationary under the changing climate and land use conditions. An applicable hydrological model should be able to capture the essential features of the target catchment and therefore be transferable to different conditions. At present, many model applications based on the stationary assumptions are not sufficient for predicting further changes or time variability. The aim of this study is to explore new model calibration methods in order to improve the transferability of model parameters. To cope with the instability of model parameters calibrated on catchments in non-stationary conditions, we investigate the idea of simultaneously calibration on streamflow records for the period with dissimilar climate characteristics. In additional, a weather based weighting function is implemented to adjust the calibration period to future trends. For regions with limited data and ungauged basins, the common calibration was applied by using information from similar catchments. Result shows the model performance and transfer quantity could be well improved via common calibration. This model calibration approach will be used to enhance regional water management and flood forecasting capabilities.

Huang, Yingchun; Bárdossy, András

2014-05-01

151

Modelling of hydrologic processes in a small natural hillslope basin, based on the synthesis of partial hydrological relationships  

NASA Astrophysics Data System (ADS)

The authors have equipped a natural small experimental basin, with a catchment area of 4.4 ha, in the Tama Hills in the western suburbs of Tokyo, Japan. It has not only precipitation and streamflow gauging but also soil moisture measuring instruments and groundwater observation wells. At first, based upon the observed data, the partial hydrologic processes such as direct runoff, rainfall-loss, groundwater runoff, groundwater recharge, and evapotranspiration are analyzed. Then a daily hydrological model and an hourly hydrological model are constructed by synthesizing the results of the above analysis, and their applicability is examined.

Ando, Yosihisa; Musiake, Katumi; Takahasi, Yutaka

1983-07-01

152

Vegetation Dynamics And Soil Moisture: Consequences For Hydrologic Modeling  

NASA Astrophysics Data System (ADS)

Current global population growth and economical development accelerates land cover conversion in many parts of the world. Introducing non-native species and woody species encroachment, with different water demands, can affect the partitioning of hydrological fluxes. The impacts on the hydrologic cycle at local to regional scales are poorly understood. The present study investigates the hydrologic implications of land use conversion from native vegetation to rubber. We first compare the vegetation dynamics of rubber (Hevea brasiliensis), a non- native specie in Southeast Asia, to the other main vegetation types in the study area. The experimental catchment, Nam Ken (69km 2), is located in the Xishuangbanna Prefecture (21 °N, 100 °E), in the south of Yunnan province in South China. From 2005 to 2006, we collected continuous records of 2 m deep soil moisture profiles in four different land covers (tea, secondary forest, grassland and rubber), and measured surface radiation in tea and rubber canopies. Our observations show that root water uptake by rubber during the dry season is controlled by the change of day-length, whereas water demand of the native vegetation starts with the arrival of the first monsoon rainfall. The different root water uptake dynamics of rubber result in distinct depletion of deeper layer soil moisture. Traditional evapotranspiration and soil moisture models are unable to simulate this specific behavior, thus a different conceptual model is needed to predict hydrologic changes due to land use conversion in the area.

Guardiola-Claramonte, M.; Troch, P. A.

2007-12-01

153

A flexible open data assimilation framework for hydrological modelling  

NASA Astrophysics Data System (ADS)

Traditionally, data assimilation algorithms are implemented in model specific form. This requires in-depth knowledge of the numerical core and additional programming to perform data assimilation experiments. We present a more flexible approach to setup a hydrological forecasting system using a generic coupling between the Open Model Interface (OpenMI) and the model interface of OpenDA. OpenMI is used for all interactions between the model and the data assimilation algorithms avoiding the need to alter the computational core of the hydrological model. OpenDA is an open source data assimilation toolbox that contains a number of state-of-the-art data assimilation algorithms to easily set up a forecasting system with data assimilation capabilities. The developed coupling allows users to run any OpenMI compliant model seamlessly in OpenDA. A number of assimilation experiments with the MIKE SHE distributed and integrated hydrological modeling system is performed to demonstrate the capabilities of the coupled OpenMI - OpenDA approach. Various ensemble based data assimilation algorithms are used to improve the forecasted groundwater levels and river discharges. Biases in the measurements are detected and corrected by the generic bias correction module of OpenDA.

van Velzen, Nils; Ridler, Marc; Altaf, Umer; Madsen, Henrik; Heemink, Arnold

2014-05-01

154

Effect of Parametrization in a Grid based mesoscale Hydrologic model on the Streamflow Prediction  

Microsoft Academic Search

Distributed hydrologic models have the potential to simulate the spatial distribution of hydrological processes and provide the estimate on streamflow at all points along the river network within the catchment. While such models can explain the variability of spatially distributed hydrological process, they have often complex structure and contains significant number of unknown model parameters that need to be defined

R. Kumar; L. Samaniego; S. Attinger

2009-01-01

155

The application of remote sensing to the development and formulation of hydrologic planning models  

NASA Technical Reports Server (NTRS)

The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.

Fowler, T. R.; Castruccio, P. A.; Loats, H. L., Jr.

1977-01-01

156

Mathematical Model for the Watershed Hydrologic System.  

National Technical Information Service (NTIS)

A physically based mathematical model has been developed to simulate the four most important parts of the watershed continuum that are controlled by the properties of soils and plants and by meteorological factors. The model couples three-dimensional tran...

R. W. Al-Soufi

1989-01-01

157

Large Scale Hydrological Modeling of Upper Mississippi River Basin  

Microsoft Academic Search

The work involves simulation of river discharge\\/stream-flow for Upper Mississippi River Basin using Variable Infiltration Capacity - Three-Layer (VIC-3L) Macro-scale Hydrologic Model using hydro-meteorological forcings - precipitation, maximum and temperatures and wind data for the years 1950-1999. The model simulated streamflow results under water balance mode at daily time-step were comparable (regression coefficients of around 0.90) with measured USGS stream-gage

R. Srinivasan; V. Lakshmi

2001-01-01

158

The coupled routing and excess storage (CREST) distributed hydrological model  

Microsoft Academic Search

The Coupled Routing and Excess STorage model (CREST, jointly developed by the University of Oklahoma and NASA SERVIR) is a distributed hydrological model developed to simulate the spatial and temporal variation of land surface, and subsurface water fluxes and storages by cell-to-cell simulation. CREST's distinguishing characteristics include: (1) distributed rainfall–runoff generation and cell-to-cell routing; (2) coupled runoff generation and routing

Jiahu Wang; Yang Hong; Li Li; Jonathan J. Gourley; Sadiq I. Khan; Koray K. Yilmaz; Robert F. Adler; Frederick S. Policelli; Shahid Habib; Daniel Irwn; Ashutosh S. Limaye; Tesfaye Korme; Lawrence Okello

2011-01-01

159

A distributed hydrology-vegetation model for complex terrain  

Microsoft Academic Search

A distributed hydrology-vegetation model is described that includes canopy interception, evaporation, transpiration, and snow accumulation and melt, as well as runoff generation via the saturation excess mechanisms. Digital elevation data are used to model topographic controls on incoming solar radiation, air temperature, precipitation, and downslope water movement. Canopy evapotranspiration is represented via a two-layer Penman-Monteith formulation that incorporates local net

Mark S. Wigmosta; D. P. Lettenmaier; L. W. Vail

1994-01-01

160

Pursuing the method of multiple working hypotheses for hydrological modeling  

NASA Astrophysics Data System (ADS)

Ambiguities in the representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. The current overabundance of models is symptomatic of an insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in measuring and representing the heterogeneity encountered in natural systems. This presentation advocates using the method of multiple working hypotheses for systematic and stringent testing of model alternatives in hydrology. We discuss how the multiple hypothesis approach provides the flexibility to formulate alternative representations (hypotheses) describing both individual processes and the overall system. When combined with incisive diagnostics to scrutinize multiple model representations against observed data, this provides hydrologists with a powerful and systematic approach for model development and improvement. Multiple hypothesis frameworks also support a broader coverage of the model hypothesis space and hence improve the quantification of predictive uncertainty arising from system and component non-identifiabilities. As part of discussing the advantages and limitations of multiple hypothesis frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting different types of data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from major uncertainties in environmental data, quantifying regional differences in dominant hydrological processes, and the grander challenge of understanding the self-organization and optimality principles that may functionally explain and describe the heterogeneities evident in most environmental systems. We assess recent progress in these research directions, and how new advances are possible using multiple hypothesis methodologies.

Clark, M. P.; Kavetski, D.; Fenicia, F.

2012-12-01

161

Hydrological Modelling and Parameter Identification for Green Roof  

NASA Astrophysics Data System (ADS)

Green roofs, a multilayered system covered by plants, can be used to replace traditional concrete roofs as one of various measures to mitigate the increasing stormwater runoff in the urban environment. Moreover, facing the high uncertainty of the climate change, the present engineering method as adaptation may be regarded as improper measurements; reversely, green roofs are unregretful and flexible, and thus are rather important and suitable. The related technology has been developed for several years and the researches evaluating the stormwater reduction performance of green roofs are ongoing prosperously. Many European counties, cities in the U.S., and other local governments incorporate green roof into the stormwater control policy. Therefore, in terms of stormwater management, it is necessary to develop a robust hydrologic model to quantify the efficacy of green roofs over different types of designs and environmental conditions. In this research, a physical based hydrologic model is proposed to simulate water flowing process in the green roof system. In particular, the model adopts the concept of water balance, bringing a relatively simple and intuitive idea. Also, the research compares the two methods in the surface water balance calculation. One is based on Green-Ampt equation, and the other is under the SCS curve number calculation. A green roof experiment is designed to collect weather data and water discharge. Then, the proposed model is verified with these observed data; furthermore, the parameters using in the model are calibrated to find appropriate values in the green roof hydrologic simulation. This research proposes a simple physical based hydrologic model and the measures to determine parameters for the model.

Lo, W.; Tung, C.

2012-12-01

162

Distributed hydrological modelling of a Mediterranean mountainous catchment – Model construction and multi-site validation  

Microsoft Academic Search

A multi-site validation approach is necessary to further constrain distributed hydrological models. Such an approach has been tested on the Gardon catchment located in the mountainous Mediterranean zone of southern France using data gathered over a 10 year period on nine internal subcatchments. A spatially distributed hydrological model linked to a Geographical Information System, was developed on the basis of

Roger Moussa; Nanée Chahinian; Claude Bocquillon

2007-01-01

163

An educational model for ensemble streamflow simulation and uncertainty analysis  

NASA Astrophysics Data System (ADS)

This paper presents the hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity. HBV-Ensemble was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.

AghaKouchak, A.; Nakhjiri, N.; Habib, E.

2013-02-01

164

An improved ARIMA model for hydrological simulations  

NASA Astrophysics Data System (ADS)

Auto Regressive Integrated Moving Average (ARIMA) model is often used to calculate time series data formed by inter-annual variations of monthly data. However, the influence brought about by inter-monthly variations within each year is ignored. Based on the monthly data classified by clustering analysis, the characteristics of time series data are extracted. An improved ARIMA model is developed accounting for both the inter-annual and inter-monthly variation. The correlation between characteristic quantity and monthly data within each year is constructed by regression analysis first. The model can be used for predicting characteristic quantity followed by the stationary treatment for characteristic quantity time series by difference. A case study is conducted to predict the precipitation in Lanzhou precipitation station, China, using the model, and the results show that the accuracy of the improved model is significantly higher than the seasonal model, with the mean residual achieving 9.41 mm and the forecast accuracy increasing by 21%.

Wang, H. R.; Wang, C.; Lin, X.; Kang, J.

2014-04-01

165

Research on Acquisition Methods of High-Precision DEM for Distributed Hydrological Model  

Microsoft Academic Search

\\u000a Compared with the traditional lumped hydrological models, distributed hydrological model, considering the effects of the uneven\\u000a spatial distribution of watershed land surface on the hydrological cycle, has the characteristic of physical mechanism. Seeing\\u000a from overall structure, there are two types of distributed hydrological model, which are runoff and convergence. The establishment\\u000a of convergence network is on the basis of calculating

Li Deng; Yong Liang; Chengming Zhang

2010-01-01

166

Selection of Hydrological Model for Waterborne Release  

SciTech Connect

This evaluation will aid in determining the potential impacts of liquid releases to downstream populations on the Savannah River. The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the Design Basis and Beyond Design Basis accidents to be used in the future study.

Blanchard, A.

1999-04-21

167

Selection of Hydrological Model for Waterborne Release  

SciTech Connect

The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the DB and BDB accidents to be used in the future study.

Blanchard, A.

1999-02-03

168

RECURSIVE PARAMETER ESTIMATION OF HYDROLOGIC MODELS  

EPA Science Inventory

Proposed is a nonlinear filtering approach to recursive parameter estimation of conceptual watershed response models in state-space form. he conceptual model state is augmented by the vector of free parameters which are to be estimated from input-output data, and the extended Kal...

169

Modeling hydrology and sediment transport in vegetative filter strips  

SciTech Connect

Sediment and sediment bounded pollutants carried by runoff from non-point sources is a major pollutant of water bodies. Vegetative filter strips (VFS) are bands of planted or indigenous vegetation used to control runoff and sediment outflow from disturbed areas. This work presents and validates a research model to study the hydrology and sediment movement in VFS. This was accomplished in four steps. The numerical solution of the overland flow kinematic wave equations is subject to numerical problems when a rapid change in parameters is encountered (kinematic shock). An improved finite element method, i.e. a Petrov-Galerkin (PG) formulation, is presented. The formulation depends on four parameters. The PG method decreased the mean sum of square error by about 65%. The finite element overland flow solution is modified and linked to the Green-Ampt infiltration equation to form a VFS-specific hydrology model. An analysis of the effect of different filter properties (soil type, slope, surface roughness, buffer length) on the major hydrological out-puts (runoff volume, velocity and peak flow rate) is made. Optimal filter performance (i.e. reduction in runoff volume, velocity and peak flow rate) is found for soils with high infiltration capacity, dense grass cover and small slopes. A sediment transport/filtration submodel (based on the University of Kentucky model) is added to the hydrology submodel. The interaction between submodels and a natural event application case to illustrate the capability of the model and its various outputs is presented in detail. An analysis of sensitivity and a field validation are performed. The most sensitive parameters are soil initial water content, vertical saturated hydraulic conductivity, particle class and grass spacing. The model predictions were compared with a set of natural events from an experimental site in the North Carolina Piedmont. In general the model performs well.

Munoz-Carpena, R.

1993-12-31

170

Hydrological Modelling of The Guadiana Basin  

NASA Astrophysics Data System (ADS)

Increased anthropogenic activities such as agriculture, irrigation, industry, mining, ur- ban water supply and sewage treatment, have created significant environmental prob- lems. To ensure sustainable development of water resources, water managers need new strategies and suitable tools. In particular it is often compulsory that surface wa- ter and groundwater be managed simultaneously both in terms of quantity and quality at catchment scales. To this purpose, a model coupling SWAT (Soil and Water As- sessment Tool) and MODFLOW (Modular 3-D Flow model) was developed. SWAT is a quasi-distributed watershed model with a GIS interface that outlines the sub-basins and stream networks from a Digital Elevation Model (DEM) and calculates daily wa- ter balances from meteorological data, soil and land-use characteristics. The particular advantage of this model, compared to other fully distributed physically based mod- els, is that it requires a small amount of readily available input data. MODFLOW is a fully distributed model that calculates groundwater flow from aquifer characteris- tics. We have adapted this new coupled model SWAT-MODFLOW to a Mediterranean catchment, the Guadiana basin, and present the first results of this work. Only wa- ter quantity results are available at this stage. The validation consisted in comparing measured and predicted daily flow at the catchment and sub-catchment outlets for the period 1970-1995. The model accurately reproduced the decrease of the piezometric level, due to increased water abstraction, and the exchanges between surface water and ground-water. The sensitivity of the model to irrigation practices was evaluated. The usefulness of this model as a management tool has been illustrated through the analysis of alternative scenarios of agricultural practices and climate change.

Conan, C.; Bouraoui, F.; de Marsily, G.; Bidoglio, G.

171

eWaterCycle: A high resolution global hydrological model  

NASA Astrophysics Data System (ADS)

In 2013, the eWaterCycle project was started, which has the ambitious goal to run a high resolution global hydrological model. Starting point was the PCR-GLOBWB built by Utrecht University. The software behind this model will partially be re-engineered in order to enable to run it in a High Performance Computing (HPC) environment. The aim is to have a spatial resolution of 1km x 1km. The idea is also to run the model in real-time and forecasting mode, using data assimilation. An on-demand hydraulic model will be available for detailed flow and flood forecasting in support of navigation and disaster management. The project faces a set of scientific challenges. First, to enable the model to run in a HPC environment, model runs were analyzed to examine on which parts of the program most CPU time was spent. These parts were re-coded in Open MPI to allow for parallel processing. Different parallelization strategies are thinkable. In our case, it was decided to use watershed logic as a first step to distribute the analysis. There is rather limited recent experience with HPC in hydrology and there is much to be learned and adjusted, both on the hydrological modeling side and the computer science side. For example, an interesting early observation was that hydrological models are, due to their localized parameterization, much more memory intensive than models of sister-disciplines such as meteorology and oceanography. Because it would be deadly to have to swap information between CPU and hard drive, memory management becomes crucial. A standard Ensemble Kalman Filter (enKF) would, for example, have excessive memory demands. To circumvent these problems, an alternative to the enKF was developed that produces equivalent results. This presentation shows the most recent results from the model, including a 5km x 5km simulation and a proof of concept for the new data assimilation approach. Finally, some early ideas about financial sustainability of an operational global hydrological model are presented.

van de Giesen, Nick; Bierkens, Marc; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

2014-05-01

172

Drought Analysis for River Basins, Using the Hydrological Model SIMGRO  

NASA Astrophysics Data System (ADS)

Drought is a recurring and worldwide phenomenon, with spatial and temporal characteristics that vary significantly from one region to another. Drought has major impacts on society and affects among others the environment and the economy. Impacts are likely to increase with time as societies demands higher services for water and the environment. This will even be more pronounced in the coming decades with the projected climate change, i.e. droughts are becoming more severe in large parts of the world. The prediction of droughts is an essential part of impact assessment for current and future conditions, as part of integrated land and water management. An important question is how changes in meteorological drought will propagate into hydrological droughts in terms of changes in the groundwater system or in the river flow. The objective of our study is to develop and test tools that quantify the space-time development of droughts in a river basin. The spatial aspect of a hydrological drought (spatially-distributed recharge and groundwater heads), in a river basin brings different challenges with respect to describing the characteristics of a drought, such as: onset, duration, severity and extend. We used the regional hydrological model SIMGRO as a basis to generate the necessary data for the drought analysis. SIMGRO is a distributed physically-based model that simulates regional transient saturated groundwater flow, unsaturated flow, actual evapotranspiration, sprinkler irrigation, stream flow, groundwater and surface water levels as a response to rainfall, reference evapotranspiration, and groundwater abstraction. The model is used within the GIS environment Arc-View, which enables the use of digital data, such as soil map, land use, watercourses, as input data for the model. It is also a tool for analysis, because interactively data and results can be presented, as will be shown. Droughts in different hydrological variables (recharge, groundwater heads, river flow) are identified by applying the fixed threshold concept to spatially-distributed simulated time series. The method captures the development of both the duration and the severity for the area in a drought. For the analysis we applied the model to the Taquari river basin (about 106.000 km2), which is situated in the Pantanal region, the upper part of the Paraguay River Basin, Brazil. The question we will address is: how does a hydrological drought develop and what are the spatial characteristics and what are the underlying mechanisms. Examples of the analysis will be shown that aim at a better understanding of the process involved which are essential; to assess the vulnerability of river basins for hydrological droughts.

Querner, E.; van Lanen, H.; Rhebergen, W.

2009-05-01

173

Eco-hydrological Modeling in the Framework of Climate Change  

NASA Astrophysics Data System (ADS)

A blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the plot and small catchment scale is presented. Input hydro-meteorological variables for hydrological and eco-hydrological models for present and future climates are reproduced using a stochastic downscaling technique and a weather generator, "AWE-GEN". The generated time series of meteorological variables for the present climate and an ensemble of possible future climates serve as input to a newly developed physically-based eco-hydrological model "Tethys-Chloris". An application of the proposed methodology is realized reproducing the current (1961-2000) and multiple future (2081-2100) climates for the location of Tucson (Arizona). A general reduction of precipitation and a significant increase of air temperature are inferred. The eco-hydrological model is successively applied to detect changes in water recharge and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of south Arizona. Results for the future climate account for uncertainties in the downscaling and are produced in terms of probability density functions. A comparison of control and future scenarios is discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is offset by a positive effect of carbon dioxide augment. This implies a positive shift in plant capabilities to exploit water. Consequently, the plant water use efficiency and rain use efficiency are expected to increase. Interesting differences in the long-term vegetation productivity are also observed for the ensemble of future climates. The reduction of precipitation and the substantial maintenance of vegetation cover ultimately leads to the depletion of soil moisture and recharge to deeper layers. Such an outcome can affect the long-tem water availability in semi-arid systems and expose plants to more severe and frequent periods of stress.

Fatichi, Simone; Ivanov, Valeriy Y.; Caporali, Enrica

2010-05-01

174

A NEW APPROACH TO HYDROLOGIC MODELING: DERIVED DISTRIBUTIONS REVISITED. (R824780)  

EPA Science Inventory

A fractal geometric procedure to model hydrologic (geophysical) phenomena is introduced. The method consists of using derived distributions, obtained by transforming arbitrary multinomial multifractal measures via fractal interpolating functions, to represent observed hydrologic ...

175

How to Reduce Computational Time in Distributed Hydrological Modeling?  

NASA Astrophysics Data System (ADS)

One of the key limitations of distributed hydrologic modeling for large scale simulations of soil moisture and land surface fluxes is the computational time spent in simulating hydrological processes. It is for this reason that applications involving assessment of model uncertainty, or simulating multiple input realizations as often needed to assess climate change impacts on a catchment, are not attempted, and models applied to understand hydrological processes in small sized, experimental catchments. The questions asked in this presentation are (a) whether one can simulate the catchment hydrology by simulating across multiple cross sections in a hillslope ; and (b) can one improve these simulations further by simulating on a single (or selected few) "Equivalent" cross-sections in the catchment. This new concept of an Equivalent Cross-section informed by the catchment landform is developed for upland catchments, to reduce computational time while maintaining the same order of accuracy in simulating hydrologic fluxes. The Unsaturated Soil Moisture Movement model (U3M-2d), based on a 2-dimensional solution of the Richards' equation, is used to simulate hydrologic fluxes. In this method, simulations with U3M-2d are first done for a number of uniformly spaced cross-sections in each Strahler's first order sub-basin and the total fluxes are estimated (reference case). Single or multiple Equivalent Cross-sections are then derived for each Strahler's first order sub-basin and results are compared against the reference case. To formulate the Equivalent Cross-section, the catchment is divided into four major landforms using the methodology developed by Khan et al. [2009] and then a range of weighting schemes for topographic variables and soil types are investigated. The Equivalent Cross-section approach is investigated for seven first order sub-basins of McLaughlin catchment of Snowy River and Wagga Wagga experimental catchment of NSW, Australia. Simulated fluxes by the Equivalent Cross-sections approach are close to the reference fluxes while the computational time is reduced significantly of the order of ~7 to ~10 times. The U3M-2d model evaluation is performed by comparing the simulated soil moisture of hillslope cross-sections with the observed soil moisture at several locations in the Wagga Wagga experimental catchment. Results illustrates that the model has capability to produce consistent results and capture daily soil moisture dynamics. Results from this study indicate that an Equivalent Cross-section based distributed hydrological modeling approach has the potential to reduce the computational time significantly while retaining the same order of accuracy. References Khan, U., A. Sharma, and N. K. Tuteja (2009), A new approach for delineation of hydrologic response units in large catchments, in 18th IMACS World Congress MODSIM 2009, International Conference, Modelling and Simulation Society of Australia and New Zealand, edited by R. S. Anderssen, R.D. Braddock and L.T.H. Newham, pp. 3521-3527, Cairns, Australia.

Khan, U.; Tuteja, N. K.; Ajami, H.; Sharma, A.

2012-12-01

176

Selection of Hydrological Model for Waterborne Release  

SciTech Connect

Following a request from the States of South Carolina and Georgia, downstream radiological consequences from postulated accidental aqueous releases at the three Savannah River Site nonreactor nuclear facilities will be examined. This evaluation will aid in determining the potential impacts of liquid releases to downstream populations on the Savannah River. The purpose of this report is to evaluate the two available models and determine the appropriate model for use in following waterborne release analyses. Additionally, this report will document the accidents to be used in the future study.

Blanchard, A.

1999-04-21

177

Development of a "Hydrologic Equivalent Wetland" Concept for Modeling Cumulative Effects of Wetlands on Watershed Hydrology  

NASA Astrophysics Data System (ADS)

Wetlands are one of the most important watershed microtopographic features that affect, in combination rather than individually, hydrologic processes (e.g., routing) and the fate and transport of constituents (e.g., sediment and nutrients). Efforts to conserve existing wetlands and/or to restore lost wetlands require that watershed-level effects of wetlands on water quantity and water quality be quantified. Because monitoring approaches are usually cost or logistics prohibitive at watershed scale, distributed watershed models, such as the Soil and Water Assessment Tool (SWAT), can be a best resort if wetlands can be appropriately represented in the models. However, the exact method that should be used to incorporate wetlands into hydrologic models is the subject of much disagreement in the literature. In addition, there is a serious lack of information about how to model wetland conservation-restoration effects using such kind of integrated modeling approach. The objectives of this study were to: 1) develop a "hydrologic equivalent wetland" (HEW) concept; and 2) demonstrate how to use the HEW concept in SWAT to assess effects of wetland restoration within the Broughton's Creek watershed located in southwestern Manitoba of Canada, and of wetland conservation within the upper portion of the Otter Tail River watershed located in northwestern Minnesota of the United States. The HEWs were defined in terms of six calibrated parameters: the fraction of the subbasin area that drains into wetlands (WET_FR), the volume of water stored in the wetlands when filled to their normal water level (WET_NVOL), the volume of water stored in the wetlands when filled to their maximum water level (WET_MXVOL), the longest tributary channel length in the subbasin (CH_L1), Manning's n value for the tributary channels (CH_N1), and Manning's n value for the main channel (CH_N2). The results indicated that the HEW concept allows the nonlinear functional relations between watershed processes and wetland characteristics (e.g., size and morphology) to be accurately represented in the models. The loss of the first 10 to 20% of the wetlands in the Minnesota study area would drastically increase the peak discharge and loadings of sediment, total phosphorus (TP), and total nitrogen (TN). On the other hand, the justifiable reductions of the peak discharge and loadings of sediment, TP, and TN in the Manitoba study area may require that 50 to 80% of the lost wetlands be restored. Further, the comparison between the predicted restoration and conservation effects revealed that wetland conservation seems to deserve a higher priority while both wetland conservation and restoration may be equally important. Moreover, although SWAT was used in this study, the HEW concept is generic and can also be applied with any other hydrologic models.

Wang, X.; Liu, T.; Li, R.; Yang, X.; Duan, L.; Luo, Y.

2012-12-01

178

Defining prior probabilities for hydrologic model structures in UK catchments  

NASA Astrophysics Data System (ADS)

The selection of a model structure is an essential part of the hydrological modelling process. Recently flexible modeling frameworks have been proposed where hybrid model structures can be obtained by mixing together components from a suite of existing hydrological models. When sufficient and reliable data are available, this framework can be successfully utilised to identify the most appropriate structure, and associated optimal parameters, for a given catchment by maximizing the different models ability to reproduce the desired range of flow behaviour. In this study, we use a flexible modelling framework to address a rather different question: can the most appropriate model structure be inferred a priori (i.e without using flow observations) from catchment characteristics like topography, geology, land use, and climate? Furthermore and more generally, can we define priori probabilities of different model structures as a function of catchment characteristics? To address these questions we propose a two-step methodology and demonstrate it by application to a national database of meteo-hydrological data and catchment characteristics for 89 catchments across the UK. In the first step, each catchment is associated with its most appropriate model structure. We consider six possible structures obtained by combining two soil moisture accounting components widely used in the UK (Penman and PDM) and three different flow routing modules (linear, parallel, leaky). We measure the suitability of a model structure by the probability of finding behavioural parameterizations for that model structure when applied to the catchment under study. In the second step, we use regression analysis to establish a relation between selected model structures and the catchment characteristics. Specifically, we apply Classification And Regression Trees (CART) and show that three catchment characteristics, the Base Flow Index, the Runoff Coefficient and the mean Drainage Path Slope, can be used to predict which model structure is more appropriate. The study constitutes a first step to enhance the choice of model structures in hydrological modeling across regions, with potentially interesting applications for predictions in ungauged basins, that was made possible by the analyses of large datasets.

Clements, Michiel; Pianosi, Francesca; Wagener, Thorsten; Coxon, Gemma; Freer, Jim; Booij, Martijn

2014-05-01

179

Physically Based Mountain Hydrological Modelling using Reanalysis Data in Patagonia  

NASA Astrophysics Data System (ADS)

Remote regions in South America are often characterized by insufficient observations of meteorology for robust hydrological model operation. Yet water resources must be quantified, understood and predicted in order to develop effective water management policies. Here, we developed a physically based hydrological model for a major river in Patagonia using the modular Cold Regions Hydrological Modelling Platform (CRHM) in order to better understand hydrological processes leading to streamflow generation in this remote region. The Baker River -with the largest mean annual streamflow in Chile-, drains snowy mountains, glaciers, wet forests, peat and semi-arid pampas into a large lake. Meteorology over the basin is poorly monitored in that there are no high elevation weather stations and stations at low elevations are sparsely distributed, only measure temperature and rainfall and are poorly maintained. Streamflow in the basin is gauged at several points where there are high quality hydrometric stations. In order to quantify the impact of meteorological data scarcity on prediction, two additional data sources were used: the ERA-Interim (ECMWF Re-analyses) and CFSR (Climate Forecast System Reanalysis) atmospheric reanalyses. Precipitation temporal distribution and magnitude from the models and observations were compared and the reanalysis data was found to have about three times the number of days with precipitation than the observations did. Better synchronization between measured peak streamflows and modeled precipitation was found compared to observed precipitation. These differences are attributed to: (i) lack of any snowfall observations (so precipitation records does not consider snowfall events) and (ii) available rainfall observations are all located at low altitude (<500 m a.s.l), and miss the occurrence of high altitude precipitation events. CRHM parameterization was undertaken by using local physiographic and vegetation characteristics where available and transferring locally unknown hydrological process parameters from cold regions mountain environments in Canada. Some soil moisture parameters were calibrated from streamflow observations. Model performance was estimated through comparison with observed streamflow records. Simulations using observed precipitation had negligible representativeness of streamflow (Nash-Sutcliffe coefficient, NS ? 0.2), while those using any of the two reanalyses as forcing data had reasonable model performance (NS ? 0.7). In spite of the better spatial resolution of the CFSR, the ability to simulate streamflow were not significantly different using either CFSR or ERA-Interim. The modeled water balance shows that snowfall is about 30% of the total precipitation input, but snowmelt superficial runoff comprises about 10% of total runoff. About 75% of all precipitation is infiltrated, and approximately 15% of the losses are attributed to evapotranspiration from soil and lake evaporation.

Krogh, S.; Pomeroy, J. W.; McPhee, J. P.

2013-05-01

180

A Coupled Surface/Subsurface Model for Hydrological Drought Investigations  

NASA Astrophysics Data System (ADS)

Hydrological droughts occur when storage in the ground and surface-water bodies falls below statistical average. Due to the inclusion of regional groundwater, hydrological droughts evolve relatively slowly. The atmospheric and surface components of the hydrological cycle have been widely studied, are well understood, and their prognoses are fairly accurate. In large-scale land surface models on the other hand, subsurface (groundwater) flow processes are usually assumed unidirectional and limited to the vertically-downward percolation and the horizontal runoffs. The vertical feedback from groundwater to the unsaturated zone as well as the groundwater recharge from surface waters are usually misrepresented, resulting in poor model performance during low-flow periods. The feedback is important during meteorological droughts because it replenishes soil moisture from ground- and surface water, thereby delaying the onset of agricultural droughts. If sustained for long periods however, the depletion can significantly reduce surface and subsurface storage and lead to severe hydrological droughts. We hypothesise that an explicit incorporation of the groundwater component into an existing land surface model would lead to better representation of low flows, which is critical for drought analyses. It would also improve the model performance during low-flow periods. For this purpose, we coupled the process-based mHM surface model (Samaniego et al. 2010) with MODFLOW (Harbaugh 2005) to analyse droughts in the Unstrut catchment, one of the tributaries of the Elbe. The catchment is located in one of the most drought-prone areas of Germany. We present results for stand-alone and coupled mHM simulations for the period 1970-2000. References Arlen W. Harbaugh. MODFLOW-2005, The U.S. Geological Survey Modular Ground-water Model-the Ground-water Flow Process, chapter Modelling techniques, sec. A. Ground water, pages 1:1-9:62. USGS, 2005. Luis Samaniego, Rohini Kumar, and Sabine Attinger. Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res., 46(W05523), 2010. doi: 10.1029/2008WR007327.

Musuuza, J. L.; Kumar, R.; Samaniego, L. E.; Fischer, T.; Kolditz, O.; Attinger, S.

2013-12-01

181

Modeling Soil Moisture Fields Using the Distributed Hydrologic Model MOBIDIC  

NASA Astrophysics Data System (ADS)

The Modello Bilancio Idrologico DIstributo e Continuo (MOBIDIC) is a fully-distributed physically-based basin hydrologic model [Castelli et al., 2009]. MOBIDIC represents watersheds using a system or reservoirs that interact through both mass and energy fluxes. The model uses a single-layered soil on a grid. For each grid element, soil moisture is conceptually partitioned into gravitational (free) and capillary-bound water. For computational parsimony, linear parameterization is used for infiltration rather than solving it using the nonlinear Richard's Equation. Previous applications of MOBIDIC assessed model performance based on streamflow which is a flux. In this study, the MOBIDIC simulated soil moisture, a state variable, is compared against observed values as well as values simulated by the legacy Simultaneous Heat and Water (SHAW) model [Flerchinger, 2000] which was chosen as the benchmark. Results of initial simulations with the original version of MOBIDIC prompted several model modifications such as changing the parameterization of evapotranspiration and adding capillary rise to make the model more robust in simulating the dynamics of soil moisture. In order to test the performance of the modified MOBIDIC, both short-term (a few weeks) and extended (multi-year) simulations were performed for 3 well-studied sites in the US: two sites are mountainous with deep groundwater table and semiarid climate, while the third site is fluvial with shallow groundwater table and temperate climate. For the multi-year simulations, both MOBIDIC and SHAW performed well in modeling the daily observed soil moisture. The simulations also illustrated the benefits of adding the capillary rise module and the other modifications introduced. Moreover, it was successfully demonstrated that MOBIDIC, with some conceptual approaches and some simplified parameterizations, can perform as good, if not better, than the more sophisticated SHAW model. References Castelli, F., G. Menduni, and B. Mazzanti (2009), A distributed package for sustainable water management: a case study in the Arno basin, IAHS Publ. 327 Flerchinger, G. N. (2000), The Simultaneous Heat and Water (SHAW) Model: Technical Documentation, Technical Report NWRC 2000-09, USDA Agricultural Research Service, Boise, Idaho

Castillo, A. E.; Entekhabi, D.; Castelli, F.

2011-12-01

182

Digital elevation model grid size, landscape representation, and hydrologic simulations  

Microsoft Academic Search

High-resolution digital elevation data from two small catchments in the western United States are used to examine the effect of digital elevation model (DEM) grid size on the portrayed of the land surface and hydrologic simulations. Elevation data were gridded at 2-, 4-, 10-, 30-, and 90-m scales to generate a series of simulated landscapes. Frequency distributions of slope (tanB),

Weihua Zhang; David R. Montgomery

1994-01-01

183

Understanding changes in the hydrological cycle with imperfect models  

Microsoft Academic Search

Our ability to detect, attribute and predict externally driven changes in the hydrological cycle is generally considered to be much lower than our ability to predict temperature changes. Part of the reason for this is that model-simulated rainfall changes disagree with both each other and with observations, measured in terms of root-mean-square error or pattern correlation, much more than temperature

Myles Allen; Mark Jenkinson; Hugo Lambert; Chris Huntingford; William Ingram; Peter Stott

2010-01-01

184

NRCS GeoHydro—A GIS interface for hydrologic modeling  

Microsoft Academic Search

The US Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) has developed NRCS GeoHydro 9x, a new ArcGIS application, to complement the WinTR–20 application and assist USDA field staff, and other government, private, and foreign organizations. WinTR–20 is a storm event hydrologic model used to evaluate impacts of structural and land treatment measures. NRCS GeoHydro 9x, using geographic information

William H. Merkel; Ravichandran M. Kaushika; Eddy Gorman

2008-01-01

185

Integrating snowfall limit forecasts to improve hydrological modeling  

NASA Astrophysics Data System (ADS)

Flood forecasting in mountainous areas requires accurate partitioning between rain and snowfall; an incorrect snow/rainfall limit (on daily or sub-daily timescales) typically implies a significant over- (or under-)estimation of the source catchment areas contributing to runoff and infiltration. This study details the development of a snow/rainfall partitioning method which incorporates snowfall limit information from Limited Area Models (LAMs) to improve catchment-scale hydrological modeling. LAMs consider the vertical, humid, atmospheric structure including wet bulb temperature in their snowfall limit calculations. Such an approach is more physically-based than inferring snowfall limit estimates based on dry, ground temperature measurements, which is the standard procedure in most hydrological models. A case study involving complex topography in the Swiss Alps demonstrates the potential of the developed method with the integration of COSMO forecast re-analysis snowfall limit information. Such data and the new method are proven here to significantly improve runoff simulation, particularly in the spring when a large part of the catchment is close to saturation. Integrating LAM snowfall limits thereby provides good estimates of runoff contributing areas, with practical implications for operational hydrology in Alpine regions.

Tobin, C.; Rinaldo, A.; Schaefli, B.

2012-04-01

186

Distributed Hydrologic Modeling of LID in The Woodlands, Texas  

NASA Astrophysics Data System (ADS)

As early as the 1960s, the Woodlands, TX employed stormwater management similar to modern Low Impact Development (LID) design. Innovative for its time, the master drainage plan attempted to minimize adverse impact to the 100-year floodplain and reduce the impact of development on the natural environment. Today, it is Texas's most celebrated master-planned community. This paper employs the use of NEXRAD radar rainfall in the distributed hydrologic model, VfloTM, to evaluate the effectiveness of The Woodlands master drainage design as a stormwater management technique. Three models were created in order to analyze the rainfall-runoff response of The Woodlands watershed under different development conditions: two calibrated, fully distributed hydrologic models to represent the (A) undeveloped and (B) 2006-development conditions and (C) a hypothetical, highly urbanized model, representing Houston-style development. Parameters, such as imperviousness and land cover, were varied in order to represent the different developed conditions. The A and B models were calibrated using NEXRAD radar rainfall for two recent storm events in 2008 and 2009. All three models were used to compare peak flows, discharge volumes and time to peak of hydrographs for the recent radar rainfall events and a historical gaged rainfall event that occurred in 1974. Results show that compared to pre-developed conditions, the construction of The Woodlands resulted in an average increase in peak flows of only 15% during small storms and 27% during a major event. Furthermore, when compared to the highly urbanized model, peak flows are often two to three times smaller for the 2006-model. In the 2006-model, the peak flow of the 100 year event was successfully attenuated, suggesting that the design of The Woodlands effectively protects the development from the 1% occurrence storm event using LID practices and reservoirs. This study uses a calibrated hydrologic distributed-model supported by NEXRAD radar rainfall to show that innovative LID strategies have been an effective stormwater management technique in The Woodlands, TX.

Bedient, P.; Doubleday, G.; Sebastian, A.; Fang, N.

2012-12-01

187

Understanding hydrologic partitioning: Combining mechanistic modelling with signature analysis to understand controls on hydrologic behaviour in headwater catchments  

NASA Astrophysics Data System (ADS)

Headwater streams are the most abundant portion of the river network but the least monitored. As such, we have a limited understanding of headwater stream behaviors and how they are influenced by watershed properties such as topography, geology, and vegetation. Given the lack of runoff monitoring within headwater streams, improving an understanding of how catchment properties influence hydrologic behavior is necessary for transferring information from instrumented areas to ungauged sites. We utilize this concept to understand physical controls on similarities and differences in hydrologic behavior for five adjacent sub-catchments located in the Tenderfoot Creek Experimental Forest in central Montana with variable topographies and vegetative cover. We use an uncalibrated, distributed, physically-based watershed model, the Distributed Hydrology-Soil-Vegetation Model (DHSVM) combined with global, variance-based sensitivity analysis to investigate physical controls on a range of model-predicted hydrologic behavior (i.e. states) across multiple time scales. We implement comparative hydrology to improve our understanding of headwater watershed runoff behavior within this framework by directly relating physical properties of a given catchment to process-based predictions of hydrologic behavior, i.e. signatures. We find that across different hydrologic fluxes, including streamflow, evapotranspiration, and snow water equivalent change, only a few vegetation and soil parameters control the variability in hydrologic behavior for all sub-catchments. These controls are similar at the annual and weekly scale, though parameter influence varies seasonally from wet to dry periods. Three of the five watersheds exhibited different controls on hydrologic behavior, likely resulting from past vegetation treatments and differing surficial geology within these sub-watersheds. This framework has strong potential to inform how similarities and differences in headwater watershed characteristics can influence the variability in spatially and temporally varying hydrologic signatures. We ultimately demonstrate that the influences of soil and vegetation across headwater watersheds vary, using a modeling framework to understand physical controls on hydrologic signatures at a high resolution. We suggest that this approach can especially enhance estimation of controls on headwater watershed behavior at unmonitored sites.

Wagener, Thorsten; Kelleher, Christa; Pianosi, Francesca; McGlynn, Brian

2014-05-01

188

DEVELOPING A TEXTURE-BASED SOIL HYDROLOGIC CHARACTERISTICS MODEL AND EXTENDING THIS MODEL TO PREDICT SOIL STRENGTH CHARACTERISTICS  

Microsoft Academic Search

Hydrologic models are used to describe water flow patterns in the soil, but there are not many models to describe the influence of soil water on soil mechanical properties. The purpose of this study was to adapt a hydrologic model to predict soil strength. In order to accomplish this goal, a new soil hydrologic characteristics model was developed using new

R. Pulley; M. Min; J. Chaplin

189

Coupled geophysical-hydrological modeling of controlled NAPL spill  

NASA Astrophysics Data System (ADS)

Past studies have shown reasonable sensitivity of geophysical data for detecting or monitoring the movement of non-aqueous phase liquids (NAPLs) in the subsurface. However, heterogeneity in subsurface properties and in NAPL distribution commonly results in non-unique data interpretation. Combining multiple geophysical data types and incorporating constraints from hydrological models will potentially decrease the non-uniqueness in data interpretation and aid in site characterization. Large-scale laboratory experiments have been conducted over several years to evaluate the use of various geophysical methods, including ground-penetrating radar (GPR), seismic, and electrical methods, for monitoring controlled spills of tetrachloroethylene (PCE), a hazardous industrial solvent that is pervasive in the subsurface. In the current study, we consider an experiment in which PCE was introduced into a large tank containing a heterogeneous distribution of sand and clay mixtures, and allowed to migrate while time-lapse geophysical data were collected. We consider two approaches for interpreting the surface GPR and crosswell seismic data. The first approach involves (a) waveform inversion of the surface GPR data using a non-gradient based optimization algorithm to estimate the dielectric constant distributions and (b) conversion of crosswell seismic travel times to acoustic velocity distributions; the dielectric constant and acoustic velocity distributions are then related to NAPL saturation using appropriate petrophysical models. The second approach takes advantage of a recently developed framework for coupled hydrological-geophysical modeling, providing a hydrological constraint on interpretation of the geophysical data and additionally resulting in quantitative estimates of the most relevant hydrological parameters that determine NAPL behavior in the system. Specifically, we simulate NAPL migration using the multiphase multicomponent flow simulator TOUGH2 with a 2-D radial model that takes advantage of radial symmetry in the experimental setup. The flow model is coupled to forward models for simulating the GPR and seismic measurements, and joint inversion of the multiple data types results in images of time-varying NAPL saturation distributions. Comparison of the two approaches with results of the post-experiment excavation indicate that combining geophysical data types and incorporating hydrological constraints improves estimates of NAPL saturation relative to the conventional interpretation of the geophysical data sets. Notice: Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect the official Agency policy. Mention of trade names or commercial products does not constitute endorsement or recommendation by EPA for use. This work was supported, in part, by the U.S. Dept. of Energy under Contract No. DE-AC02- 05CH11231.

Kowalsky, M. B.; Majer, E.; Peterson, J. E.; Finsterle, S.; Mazzella, A.

2006-12-01

190

Assessing climate change impact by integrated hydrological modelling  

NASA Astrophysics Data System (ADS)

Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations showed some unexpected results, where climate models predicting the largest increase in net precipitation did not result in the largest increase in groundwater heads. This was found to be the result of different initial conditions (1990 - 2010) for the various climate models. In some areas a combination of a high initial groundwater head and an increase in precipitation towards 2021 - 2050 resulted in a groundwater head raise that reached the drainage or the surface water system. This will increase the exchange from the groundwater to the surface water system, but reduce the raise in groundwater heads. An alternative climate model, with a lower initial head can thus predict a higher increase in the groundwater head, although the increase in precipitation is lower. This illustrates an extra dimension in the uncertainty assessment, namely the climate models capability of simulating the current climatic conditions in a way that can reproduce the observed hydrological response. Højberg, AL, Troldborg, L, Stisen, S, et al. (2012) Stakeholder driven update and improvement of a national water resources model - http://www.sciencedirect.com/science/article/pii/S1364815212002423 Seaby, LP, Refsgaard, JC, Sonnenborg, TO, et al. (2012) Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections (submitted) Journal of Hydrology Stisen, S, Højberg, AL, Troldborg, L et al., (2012): On the importance of appropriate rain-gauge catch correction for hydrological modelling at mid to high latitudes - http://www.hydrol-earth-syst-sci.net/16/4157/2012/

Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

2013-04-01

191

Challenges in Urban Hydrologic Modeling: A Baltimore Case Study  

NASA Astrophysics Data System (ADS)

To effectively and sustainably manage water resources in urban areas we need to better understand the effects of urbanization on the hydrologic cycle and conversely, the ways that surface and groundwater quality and quantity can affect humans. We present work on coupled modeling groundwater and surface water in Dead Run, a small urban watershed in Baltimore, Maryland. We use ParFlow, which models three dimensional, variably saturated subsurface - surface flow. This poster reviews some of the challenges that have been encountered in modeling elevations and slopes for overland flow in the Dead Run case. Elevations from a Digital Elevation Model (DEM) in an urban landscape may not be able to adequately define surface flow paths as streams may have been moved, channelized, piped underground, or otherwise modified. Knowledge of the locations of streams may not be adequate, as the surface stream expressions may be disconnected due to piping in between. Here we present the beginnings of ways to deal with the challenges of modeling urban as well as future plans to incorporate urbanization within existing models. This work will be expanded to a regional hydrologic model, which will be coupled with an urban growth model of the Baltimore region to explore the predictions and feedbacks between the two models.

Bhaskar, A.; Welty, C.; Maxwell, R. M.

2009-05-01

192

Hierarchical Modeling of Fen Hydrology across Multiple Scales  

NASA Astrophysics Data System (ADS)

Significantly increased groundwater withdrawals, intensive agriculture, and urbanization have caused a loss of biodiversity in wetland habitats; especially evident in groundwater dependent wetlands. An example of this phenomenon is Michigan’s prairie fens - habitats to some of the rarest and globally unique species, including the federally listed endangered species. Efforts to conserve and restore these groundwater dependent ecosystems are, however, hampered by lack of understanding of complex fen hydrology. In this paper, we investigate 10 carefully selected fen sites, with a goal to systematically improve our understanding of the underlying fen flow regimes, landscape connections, and how local and regional groundwater flow systems interact to control fen ecology. We achieve this by applying the Michigan “hierarchical” groundwater modeling system live-linked a GIS-based, statewide hydrological and ecological database.

Li, S.; Abbas, H.; Liao, H.

2010-12-01

193

Parallelization of a hydrological model using the message passing interface  

USGS Publications Warehouse

With the increasing knowledge about the natural processes, hydrological models such as the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with increasing computation time. Additionally, other procedures such as model calibration, which may require thousands of model iterations, can increase running time and thus further reduce rapid modeling and analysis. Using the widely-applied SWAT as an example, this study demonstrates how to parallelize a serial hydrological model in a Windows® environment using a parallel programing technology—Message Passing Interface (MPI). With a case study, we derived the optimal values for the two parameters (the number of processes and the corresponding percentage of work to be distributed to the master process) of the parallel SWAT (P-SWAT) on an ordinary personal computer and a work station. Our study indicates that model execution time can be reduced by 42%–70% (or a speedup of 1.74–3.36) using multiple processes (two to five) with a proper task-distribution scheme (between the master and slave processes). Although the computation time cost becomes lower with an increasing number of processes (from two to five), this enhancement becomes less due to the accompanied increase in demand for message passing procedures between the master and all slave processes. Our case study demonstrates that the P-SWAT with a five-process run may reach the maximum speedup, and the performance can be quite stable (fairly independent of a project size). Overall, the P-SWAT can help reduce the computation time substantially for an individual model run, manual and automatic calibration procedures, and optimization of best management practices. In particular, the parallelization method we used and the scheme for deriving the optimal parameters in this study can be valuable and easily applied to other hydrological or environmental models.

Wu, Yiping; Li, Tiejian; Sun, Liqun; Chen, Ji

2013-01-01

194

NRCS GeoHydro—A GIS interface for hydrologic modeling  

NASA Astrophysics Data System (ADS)

The US Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) has developed NRCS GeoHydro 9x, a new ArcGIS application, to complement the WinTR-20 application and assist USDA field staff, and other government, private, and foreign organizations. WinTR-20 is a storm event hydrologic model used to evaluate impacts of structural and land treatment measures. NRCS GeoHydro 9x, using geographic information systems (GIS) tools and techniques, performs hydrologic modeling on a drainage area to compute its catchments, drainage points, drainage lines, slope, runoff curve number, longest flow path, time of concentration ( T c), and cross-section details. The application acts as a GIS interface to WinTR-20 by exporting the results of GIS analyses of the drainage area in the input format of WinTR-20. NRCS GeoHydro 9x reinforces the idea that GIS tools and techniques enhance productivity by doing preliminary hydrologic analysis of the drainage area in an objective and accurate manner in a relatively short duration.

Merkel, William H.; Kaushika, Ravichandran M.; Gorman, Eddy

2008-08-01

195

An analogue model for subglacial hydrology (Invited)  

NASA Astrophysics Data System (ADS)

Analogue models have been used extensively in the Earth sciences to improve understanding of natural processes. Here we apply these techniques to simulate water flow under ice sheets and glaciers. Ice deformation is represented with polydimethyl-siloxane (PDMS) - a liquid polymer used extensively in the tectonics-related deformation experiments. PDMS is a transparent, non-toxic material with a specific weight similar to that of ice and a strain-rate dependent viscosity making it well-suited to ice flow studies. The polymer is loaded into a 4’x 6’ plastic box coated with a water-based lubricant across 80% of the box width to reduce friction at the interface between the polymer and the base of the box. Water is injected at this interface via a set of tubes that distribute the incoming water supply across the upstream end at a constant discharge. We measure horizontal surface displacement by tracking several bright stickers placed on the surface of the polymer through a sequence of images that make up each experimental run. Coincident water discharge and channel pattern measurements are made to correlate changes in discharge to changes in channel geometry and surface motion. Of particular interest is the response of the channel system to discharge pulses. To observe this we change discharge into the flume from ~70 cm3/s to 550 cm3/s which reflects an ~8-fold increase in discharge and represents a typical diurnal discharge fluctuation observed on alpine glaciers.

Catania, G. A.; Buttles, J. L.; Mohrig, D. C.

2009-12-01

196

A macro-scale natural hydrologic cycle water availability model  

Microsoft Academic Search

Long-term water usage can be no more than that which is naturally available through the hydrologic cycle. To help in the determination of the hydrologically desirable water usage from surface and groundwater sources, a simple, idealized long-term analysis of water availability based solely on the natural hydrologic cycle is suggested. The concept of a hydrologic replacement time is introduced to

Adam H. Slutsky; Ben C. Yen

1997-01-01

197

Self-Organizing Basal Hydrology for Ice Sheet Flowline Models  

NASA Astrophysics Data System (ADS)

Subglacial water pressure is a fundamental control on basal drag and glacier sliding rates. However, it has seldom been included as a variable in glacier flow models, mainly due to the great difficulty in calculating water pressure in a realistic yet tractable way. Here we present preliminary results of a simple basal hydrological model designed for coupling to ice sheet flow models. A key feature of the model is that hydraulic conductivity k evolves in response to water discharge Q (which melts ice and increases the capacity of the system) and effective pressure pi - pw (reducing system capacity through ice creep). The timescales of these processes relative to temporal variations in surface water inputs produces contrasting pressure-discharge relationships as an emergent property of the model. Specifically, pw varies directly with Q over diurnal timescales, whereas pw is inversely proportional to Q on seasonal timescales. In combination with suitable friction laws, the hydrology model provides an adaptive basal boundary condition for flowline models. Despite its simplicity, the model allows a rich variety of behaviour to be simulated, including spring 'speed-up' events and summer 'slowdowns'.

Rutt, I. C.; Benn, D.; Cook, S.; Hulton, N. R.

2013-12-01

198

Geomorphological Approach to Glacial and Snow Modeling applied to Hydrology  

NASA Astrophysics Data System (ADS)

Hydrological modeling of mountainous watershed has specific problems due to the effect of ice and snow cover in a certain range of altitude. The representation of the snow and ice storage dyanmics is a main issue for the understanding of mountainous hydrosystems mechanisms for future and past climate. That's also an operational concern for watersheds equipped with hydroelectric dams, whose dimensioning and electric capacity evaluation rely on a good understanding of ice-snow dynamics, in particular for a lapse of several years. The objective of the study is to get ahead, at a theoretical view, in a way in between classical representation used in hydrological models (infinity of ice stock) and 3D ice tongues modeling describing explicitly viscous glacier evolution at a river basin scale. Geomorphology will be used in this approach. Noticing that glaciers, at a catchment scale, take the drainage system as a geometrical framework, an axe of our study lies on the coupling of the probabilistic description of the river network with determinist glacier models using concepts that already have been used in hydrology modeling like Geomorphological Instantaneous Unitary Hydrogram. By analogy, a simplified glacier model (Shallow Ice Approximation or Minimal Glacier Models) will be put together as a transfer function to simulate large scale ablation and ice front dynamics. In our study, we analyze the distribution of upstream area for a dataset of 78 river basins in the Southern Rocky Mountains. In a certain range of scale and under a few assumptions, we use a statistic model for river networks description that we adapt by considering relief by linking hypsometry and morphology. The model developed P(A>a,z) allow us to identify any site of the river network from a DEM analysis via elevation z and upstream area a fields with the help of 2 parameters. The 3D consideration may be relevant for hydrologic implications as production function usually increases with relief. This model has been tested and applied at a mountain range scale in order to analyze the regional coherence in river networks structure.

Gsell, P.; Le Moine, N.; Ribstein, P.

2012-12-01

199

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

NASA Astrophysics Data System (ADS)

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.

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

2011-10-01

200

The value of regionalised information for hydrological modelling  

NASA Astrophysics Data System (ADS)

A recurrent problem in hydrology is the absence of runoff data to calibrate conceptual models. This has implications for the reliable application of such models for prediction of streamflow and water resource management. Whilst a large and increasing number of regions are insufficiently gauged, there are also many highly monitored catchments. Transferring the knowledge gained in data-rich areas to ungauged catchments offers possibilities to overcome the absence of runoff observations in data-scarce regions. Here, we transfer knowledge in the form of response signatures, which reflect the hydrological response characteristics of a particular catchment (e.g. runoff ratio and base flow index). A large data set from the Model Parameter Estimation Experiment (MOPEX) is used to regionalise five different response signatures. Observed response signatures are regressed against physical and climatic characteristics of the catchments. Signatures (with uncertainty) for an ungauged location with known physical and climatic characteristics are then estimated utilising the derived relationships. A Bayesian procedure is subsequently used to condition a hydrological model for the target ungauged catchment on the estimated response signatures with formal uncertainty estimation. Particular challenges related to the Bayesian approach include the specification of the prior distribution and the likelihood functions. In this research we introduce and test a method that considers all five regionalised response signatures, where sources of information are not necessarily independent. By explicitly taking account of the inter-signature error covariance structure, regional information is neither neglected nor double-counted. To avoid masking effects of the model structural error, the value of quantity and quality of regionalised information is assessed employing a ';perfect model' approach. Bayes factor is used to evaluate hydrological predictions, as the commonly used performance measures, such as QQ plots or Nash-Sutcliffe, are shown to be unsuitable. Our results demonstrate that the explicit representation of the uncertainty introduced by the regionalisation procedure (including the inter-dependencies between the regionalised signatures) contributes to an improved specification of the optimal model parameter set. Further, it is shown that higher quality (more precise) information leads to a stronger parameter identification. Lastly, the choice of signature is shown to have a strong impact on the estimation of model parameters. Where resources are finite we therefore suggest that modelling should focus initially on those signatures that give the greatest marginal gains for streamflow estimation.

Almeida, S.; Bulygina, N.; McIntyre, N.; Wagener, T.; Buytaert, W.

2013-12-01

201

A GIS-based variable source area hydrology model  

NASA Astrophysics Data System (ADS)

Effective control of nonpoint source pollution from contaminants transported by runoff requires information about the source areas of surface runoff. Variable source hydrology is widely recognized by hydrologists, yet few methods exist for identifying the saturated areas that generate most runoff in humid regions. The Soil Moisture Routing model is a daily water balance model that simulates the hydrology for watersheds with shallow sloping soils. The model combines elevation, soil, and land use data within the geographic information system GRASS, and predicts the spatial distribution of soil moisture, evapotranspiration, saturation-excess overland flow (i.e., surface runoff), and interflow throughout a watershed. The model was applied to a 170 hectare watershed in the Catskills region of New York State and observed stream flow hydrographs and soil moisture measurements were compared to model predictions. Stream flow prediction during non-winter periods generally agreed with measured flow resulting in an average r2 of 0·73, a standard error of 0·01 m3/s, and an average Nash-Sutcliffe efficiency R2 of 0·62. Soil moisture predictions showed trends similar to observations with errors on the order of the standard error of measurements. The model results were most accurate for non-winter conditions. The model is currently used for making management decisions for reducing non-point source pollution from manure spread fields in the Catskill watersheds which supply New York City's drinking water.

Frankenberger, Jane R.; Brooks, Erin S.; Walter, M. Todd; Walter, Michael F.; Steenhuis, Tammo S.

1999-04-01

202

High pretransplant HBV level predicts HBV reactivation after kidney transplantation in HBV infected recipients  

PubMed Central

Purpose HBsAg-positive kidney recipients are at increased risk for mortality and graft failure. The aims of this study were to identify the outcomes of HBsAg-positive recipients who received preemptive antiviral agents after successful kidney transplantation and to analyze risk factors for HBV reactivation. Methods We retrospectively reviewed the medical records of 944 patients performed kidney transplantation between 1999 and 2010. Results HBsAg-negative recipients were 902 patients and HBsAg-positive recipients, 42. Among HBsAg-positive recipients, HBV reactivation was detected in 7 patients and well controlled by switch or combination therapy. Graft failure developed in only one patient due to chronic rejection regardless of HBV reactivation but no deaths occurred. All patients were alive at the end of follow-up and none developed end-stage liver disease or hepatocellular carcinoma. There was statistically significant difference in graft survival between HBsAg-positive recipients and HBsAg-negative. Multivariate analysis identified increased HBV DNA levels (>5 × 104 IU/mL) in the HBsAg-positive kidney transplant recipients as a risk factor for HBV reactivation (P = 0.007). Conclusion Effective viral suppression with antiviral agents in HBsAg-positive renal transplant recipients improves patient outcome and allograft survival. Antiviral therapy may be especially beneficial in patients with high HBV DNA levels prior to transplantation.

Kim, Jong Man; Park, Hyojun; Jang, Hye Ryoun; Park, Jae Berm; Kwon, Choon Hyuck David; Huh, Wooseong; Lee, Joon Hyeok; Joh, Jae-Won

2014-01-01

203

Parameter Sensitivity analysis for hydrological model improvement in diverse catchments  

NASA Astrophysics Data System (ADS)

We investigate the sensitivity of the semi-distributed TopNet hydrological model, in order to understand the important hydrologic processes and influential model parameters to be accurately calibrated. Using different objective functions to evaluate the model performance, sensitivity analysis was done for TopNet applications in seven catchments located in South and North Island of New Zealand, with diverse watershed characteristics (i.e., topographic properties, response behaviours and geological features). The sensitivity approach combining the global sensitivity analysis methodology, Morris method and State Dependent Parameter (SDP) method was used in this study. Generally, the most sensitive parameters are precipitation multiplier( to correct water balance), TOPMODEL f parameter and soil water capacity which contributes to over 50% model uncertainty, while other parameters (e.g., snowmelt and routing parameters) are watershed and objective function dependent. It has being found that shape of the catchments and objective function have a strong influence on the sensitivity of the parameters. A relationship between the catchment feature and the sensitivity of the parameters was established. This will help in selection of sensitive parameters for catchments of interest. Which will help in proper calibration of the model parameters. That in turn will help in improving the model structure and reducing the uncertainty in the prediction due to parameterisation.

Singh, Shailesh Kumar; Yang, Jing; McMillan, Hilary

2014-05-01

204

Spatial organisation in hydrological model structure for New Zealand catchments  

NASA Astrophysics Data System (ADS)

Hydrologists increasingly agree that a single hydrological model structure is unlikely to be suitable for all catchments: instead, models should be selected according to characteristics of the catchment. Our challenge is to determine how to select the most appropriate model structure. This complex question requires that we use observed data to infer dominant runoff generation processes, and translate this process knowledge into model structure choices. We can then ask questions such as: over what scales do recommended model structures change? How much data is needed to select model structure? How can we generalise model structure choices to catchments where data is scarce? In this presentation we address these questions, using the New Zealand landscape as our 'virtual laboratory'. New Zealand is an excellent location to test hypotheses relating to model structure, due to its rich diversity of hydrological landscapes. Landscape types range from temperate rainforest with steep, bedrock gorges, through rolling pasture, to alluvial plains with braided rivers. Our method is to apply diagnostic signatures, which use a range of hydrological data types, to target specific aspects of model structure choice. We bring together results from national hydrometric networks, and in-depth studies in experimental catchments, to explore organisation, similarity and diversity in recommended model structures across the New Zealand landscape. To identify model structures which are consistent with measured data, we use a range of diagnostic signatures tailored to the data types available. At the national scale, networks of rain and flow gauges are used to investigate runoff ratio, recession characteristics and threshold responses to precipitation and soil moisture. At the experimental Mahurangi catchments, dense networks of 13 rain, 27 flow and 36 soil moisture gauges within a 50 km2 area enable us to evaluate small-scale patterns and diversities of model structure. In contrast, the experimental Waipara catchment in the Eastern foothills of the NZ alps provides networks of 20 soil moisture sensors and 10 shallow groundwater wells within a 1 km2 catchment, as well as deep groundwater wells and 5 nested flow gauges. This data enables us to test for additional aspects of model design related to groundwater response. We relate the local responses and diagnostic signatures to the wider, national-scale patterns. We consider whether local and national model recommendations are compatible, and how model structure patterns and diversity change with scale. Finally, we consider how uncertainty in measured data sources in NZ has the potential to affect diagnostics and hypothesis testing for model structure.

McMillan, Hilary; Woods, Ross; Clark, Martyn

2013-04-01

205

Input Variable Selection for Hydrologic Modeling Using Anns  

NASA Astrophysics Data System (ADS)

The use of artificial neural network (ANN) models in water resources applications has grown considerably over the last couple of decades. In learning problems, where a connectionist network is trained with a finite sized training set, better generalization performance is often obtained when unneeded weights in the network are eliminated. One source of unneeded weights comes from the inclusion of input variables that provide little information about the output variables. Hence, in the ANN modeling methodology, one of the approaches that has received little attention, is the selection of appropriate model inputs. In the past, different methods have been used for identifying and eliminating these input variables. Normally, linear methods of Auto Correlation Function (ACF) and Partial Auto Correlation Function (PACF) have been adopted. For nonlinear physical systems e.g. hydrological systems, model inputs selected based on the linear correlation analysis among input and output variables cannot assure to capture the non-linearity in the system. In the present study, two of the non-linear methods have been explored for the Input Variable Selection (IVS). The linear method employing ACF and PACF is also used for comparison purposes. The first non-linear method utilizes a measure of the Mutual Information Criterion (MIC) to characterize the dependence between a potential model input and the output, which is a step wise input selection procedure. The second non-linear method is improvement over the first method which eliminates redundant inputs based on a partial measure of mutual information criterion (PMIC), which is also a step wise procedure. Further, the number of input variables to be considered for the development of ANN model was determined using the Principal Component Analysis (PCA), which previously used to be done by trial and error approach. The daily river flow data derived from Godavari River Basin @ Polavaram, Andhra Pradesh, India, and the daily average rainfall data of three rain gauge stations spatially distributed in Godavari River Basin have been employed to evaluate all the IVS methods for ANN hydrologic model development. Single hidden layer architecture trained using Levenberg-Marquardt algorithm (LMA) has been employed. A wide range of error statistics was used to evaluate the performance of all the models developed with different input selection methods in this study. It has been found that PCA helps to fix the number of input variables to be considered for the model development. The results obtained show that the ANN hydrologic model developed using the inputs based on the first non-linear method performed better than the model developed using the inputs based on the linear method. Further, the ANN hydrologic model developed using the inputs based on the second non-linear method performed the best among all the models developed on various IVS methods investigated in this study. It is recommended that PCA should first be used to determine the number of inputs to be selected and then the second non-linear method should be used to select the specific inputs for the development of ANN hydrologic model.

Ganti, R.; Jain, A.

2011-12-01

206

Genetic Algorithm Optimization of Artificial Neural Networks for Hydrological Modelling  

NASA Astrophysics Data System (ADS)

This paper will consider the case for genetic algorithm optimization in the development of an artificial neural network model. It will provide a methodological evaluation of reported investigations with respect to hydrological forecasting and prediction. The intention in such operations is to develop a superior modelling solution that will be: \\begin{itemize} more accurate in terms of output precision and model estimation skill; more tractable in terms of personal requirements and end-user control; and/or more robust in terms of conceptual and mechanical power with respect to adverse conditions. The genetic algorithm optimization toolbox could be used to perform a number of specific roles or purposes and it is the harmonious and supportive relationship between neural networks and genetic algorithms that will be highlighted and assessed. There are several neural network mechanisms and procedures that could be enhanced and potential benefits are possible at different stages in the design and construction of an operational hydrological model e.g. division of inputs; identification of structure; initialization of connection weights; calibration of connection weights; breeding operations between successful models; and output fusion associated with the development of ensemble solutions. Each set of opportunities will be discussed and evaluated. Two strategic questions will also be considered: [i] should optimization be conducted as a set of small individual procedures or as one large holistic operation; [ii] what specific function or set of weighted vectors should be optimized in a complex software product e.g. timings, volumes, or quintessential hydrological attributes related to the 'problem situation' - that might require the development flood forecasting, drought estimation, or record infilling applications. The paper will conclude with a consideration of hydrological forecasting solutions developed on the combined methodologies of co-operative co-evolution and operational specialization. The standard approach to neural-evolution is at the network level such that a population of working solutions is manipulated until the fittest member is found. SANE [Symbiotic Adaptive Neuro-Evolution]1 source code offers an alternative method based on co-operative co-evolution in which a population of hidden neurons is evolved. The task of each hidden neuron is to establish appropriate connections that will provide: [i] a functional solution and [ii] performance improvements. Each member of the population attempts to optimize one particular aspect of the overall modelling process and evolution can lead to several different forms of specialization. This method of adaptive evolution also facilitates the creation of symbiotic relationships in which individual members must co-operate with others - who must be present - to permit survival. 1http://www.cs.utexas.edu/users/nn/pages/software/abstracts.html#sane-c

Abrahart, R. J.

2004-05-01

207

Multi-objective global optimization for hydrologic models  

NASA Astrophysics Data System (ADS)

The development of automated (computer-based) calibration methods has focused mainly on the selection of a single-objective measure of the distance between the model-simulated output and the data and the selection of an automatic optimization algorithm to search for the parameter values which minimize that distance. However, practical experience with model calibration suggests that no single-objective function is adequate to measure the ways in which the model fails to match the important characteristics of the observed data. Given that some of the latest hydrologic models simulate several of the watershed output fluxes (e.g. water, energy, chemical constituents, etc.), there is a need for effective and efficient multi-objective calibration procedures capable of exploiting all of the useful information about the physical system contained in the measurement data time series. The MOCOM-UA algorithm, an effective and efficient methodology for solving the multiple-objective global optimization problem, is presented in this paper. The method is an extension of the successful SCE-UA single-objective global optimization algorithm. The features and capabilities of MOCOM-UA are illustrated by means of a simple hydrologic model calibration study.

Yapo, Patrice Ogou; Gupta, Hoshin Vijai; Sorooshian, Soroosh

1998-01-01

208

Climate change impact on available water resources obtained using multiple global climate and hydrology models  

NASA Astrophysics Data System (ADS)

Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. This multi-model ensemble allows us to investigate how the hydrology models contribute to the uncertainty in projected hydrological changes compared to the climate models. Due to their systematic biases, GCM outputs cannot be used directly in hydrological impact studies, so a statistical bias correction has been applied. The results show a large spread in projected changes in water resources within the climate-hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change, and that the spread resulting from the choice of the hydrology model is larger than the spread originating from the climate models over many areas. But there are also areas showing a robust change signal, such as at high latitudes and in some midlatitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence in this ensemble mean signal. In many catchments an increase of available water resources is expected but there are some severe decreases in Central and Southern Europe, the Middle East, the Mississippi River basin, southern Africa, southern China and south-eastern Australia.

Hagemann, S.; Chen, C.; Clark, D. B.; Folwell, S.; Gosling, S. N.; Haddeland, I.; Hanasaki, N.; Heinke, J.; Ludwig, F.; Voss, F.; Wiltshire, A. J.

2013-05-01

209

Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models  

NASA Technical Reports Server (NTRS)

A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

Miller, L. D.; Tom, C.; Nualchawee, K.

1977-01-01

210

Assessing spatial patterns to characterize performance in hydrological modeling  

NASA Astrophysics Data System (ADS)

In Hydrology, spatially distributed models are traditionally evaluated against a single spatially aggregated catchment scale observation in form of river discharge with the conviction that it features the correct simulation of catchment-inherent distributed variables. Recent advances in fully distributed grid based model codes, the availability of spatially distributed data (remote sensing and intensive field studies) and computational power allow a shift towards a spatial model evaluation away from the traditional aggregated evaluation. The need of this paradigm shift is demanded in literature; however no single spatial performance metric was identified yet that proofed suitable for comparing observed and simulated spatial patterns. The goal of this study is to develop and test simple and flexible metrics for assessing spatial patterns of distributed hydrological variables that go beyond global statistics. These metrics, individually or collectively can later be used as performance criteria in the calibration process of hydrological models. Observed and simulated land surface temperature, by the MODIS satellite and by MIKE SHE, a coupled and fully distributed hydrological model, respectively are used as a benchmark to test promising spatial metrics. Additionally a synthetic dataset which contains systematic temperature perturbations, e.g. a general bias or a shift/displacement of data, is generated to test strengths and weaknesses of the spatial metrics. Four quantitative methodologies for comparing spatial patterns are brought forward in this study: (1) A fuzzy set approach that incorporates both fuzziness of location and fuzziness of category. (2) Kappa statistic that expresses the similarity between two maps based on a contingency table (error matrix). (3) An extended version of (2) by considering both fuzziness in location and fuzziness in category. (4) Increasing the information content of a single cell by aggregating neighborhood cells at different window sizes; then computing mean and standard deviation. All algorithms except (2) require subjective judgment: E.g. a distance decay function is utilized to compute the similarity values of neighborhood cells for the fuzziness of location. Therefore a web-based survey is set up where participants are asked to grade similarity of maps in the synthetic dataset. These results are used to calibrate the subjective parameters in the algorithms accordingly and to generally test how well the four algorithms can perform relative to the visual comparison.

Koch, Julian; Stisen, Simon; Høgh Jensen, Karsten

2014-05-01

211

Analysis of runoff for the Baltic basin with an integrated Atmospheric-Ocean-Hydrology Model  

Microsoft Academic Search

A fully integrated Atmospheric-Ocean-Hydrology Model (BALTIMOS = Baltic Integrated Model System) has been developed using existing model components. Experiment and model design has been adapted to the Baltic basin with a catchment area of approximately 1 750 000 km2. A comprehensive model validation has been completed using large meteorological and hydrological measurement database. Comparing the calculated runoff from the integrated

K.-G. Richter; M. Ebel

2006-01-01

212

Evaluating Hydrological Model Outputs with Satellite derived Land Surface Temperature  

NASA Astrophysics Data System (ADS)

A combined investigation of the water and energy balance in hydrologic models is needed for a better understanding of exchange, transport, and feedback processes in the soil-vegetation-atmosphere system. These models, however, are often only evaluated at gauging stations. While this evaluation does not provide any information about the spatial distribution of hydrological variables, such as evapotranspiration and soil moisture, additional methods have to be found. The objective of this study is to indirectly evaluate such variables using satellite derived Land Surface Temperature (LST) fields. Therefore, we calculate the Land Surface Temperature with the hydrological model mHM from the sensible heat formulation. The sensible heat is determined as residual of the energy balance, assuming that the soil heat flux and the storage term is negligible at the daily time scale. Additionally, the evapotranspiration is determined due to solving the water balance with mHM. Furthermore, the remaining term of the energy balance, the net radiation, is obtained by solving the radiation budget using long and shortwave incoming radiation, albedo and emissivity data from the Land Surface Analysis - Satellite Application Facility (LSA-SAF, landsaf.meteo.pt). Finally, to determine the LST, the aerodynamic resistance is parameterized to solve the sensible heat formulation. The calculated fields of land surface temperature are evaluated against those provided by LSA-SAF for a period from 2005-2010. The study is carried out in Germany, whereas sets of good performing global transfer parameters are estimated in seven German river basins: Danube, Ems, Main, Mulde, Neckar, Saale and Weser. The average Nash Sutcliffe Efficiencies exceeds 0.7 in the validation period from 2005 to 2010. Preliminary results indicate that the estimated mHM LST agrees quite well with the satellite observations. This result indirectly indicates that the simulated evapotranspiration and corresponding soil moisture fields are reasonable estimates. This assertion will be corroborated by comparison with hourly evapotranspiration fluxes obtained at nine eddy covariance measurement stations (www.fluxdata.org).

Zink, M.; Samaniego, L.; Cuntz, M.; Kumar, R.

2012-04-01

213

Assessing model state and forecasts variation in hydrologic data assimilation  

NASA Astrophysics Data System (ADS)

Data assimilation (DA) has been widely used in hydrological models to improve model state and subsequent streamflow estimates. However, for poor or non-existent state observations, the state estimation in hydrological DA can be problematic, leading to inaccurate streamflow updates. This study evaluates the soil moisture and flow variations and forecasts by assimilating streamflow and soil moisture. Three approaches of Ensemble Kalman Filter (EnKF) with dual state-parameter estimation are applied: (1) streamflow assimilation, (2) soil moistue assimilation, and (3) combined assimilation of soil moisture and streamflow. The assimilation approaches are evaluated using the Sacramento Soil Moisture Accounting (SAC-SMA) model in the Spencer Creek catchment in southern Ontario, Canada. The results show that there are significant differences in soil moisture variations and streamflow estimates when the three assimilation approaches were applied. In the streamflow assimilation, soil moisture states were markedly distorted, particularly soil moisture of lower soil layer; whereas, in the soil moisture assimilation, streamflow estimates are inaccurate. The combined assimilation of streamflow and soil moisture provides more accurate forecasts of both soil moisture and streamflow, particularly for shorter lead times. The combined approach has the flexibility to account for model adjustment through the time variation of parameters together with state variables when soil moisture and streamflow observations are integrated into the assimilation procedure. This evaluation is important for the application of DA methods to simultaneously estimate soil moisture states and watershed response and forecasts.

Samuel, Jos; Coulibaly, Paulin; Dumedah, Gift; Moradkhani, Hamid

2014-05-01

214

Adaptable Web Modules to Stimulate Active Learning in Engineering Hydrology using Data and Model Simulations of Three Regional Hydrologic Systems  

NASA Astrophysics Data System (ADS)

The hydrologic community has long recognized the need for broad reform in hydrologic education. A paradigm shift is critically sought in undergraduate hydrology and water resource education by adopting context-rich, student-centered, and active learning strategies. Hydrologists currently deal with intricate issues rooted in complex natural ecosystems containing a multitude of interconnected processes. Advances in the multi-disciplinary field include observational settings such as Critical Zone and Water, Sustainability and Climate Observatories, Hydrologic Information Systems, instrumentation and modeling methods. These research advances theory and practices call for similar efforts and improvements in hydrologic education. The typical, text-book based approach in hydrologic education has focused on specific applications and/or unit processes associated with the hydrologic cycle with idealizations, rather than the contextual relations in the physical processes and the spatial and temporal dynamics connecting climate and ecosystems. An appreciation of the natural variability of these processes will lead to graduates with the ability to develop independent learning skills and understanding. This appreciation cannot be gained in curricula where field components such as observational and experimental data are deficient. These types of data are also critical when using simulation models to create environments that support this type of learning. Additional sources of observations in conjunction with models and field data are key to students understanding of the challenges associated with using models to represent such complex systems. Recent advances in scientific visualization and web-based technologies provide new opportunities for the development of active learning techniques utilizing ongoing research. The overall goal of the current study is to develop visual, case-based, data and simulation driven learning experiences to instructors and students through a web server-based system. Open source web technologies and community-based tools are used to facilitate wide dissemination and adaptation by diverse, independent institutions. The new hydrologic learning modules are based on recent developments in hydrologic modeling, data, and resources. The modules are embedded in three regional-scale ecosystems, Coastal Louisiana, Florida Everglades, and Utah Great Salt Lake Basin. These sites provide a wealth of hydrologic concepts and scenarios that can be used in most water resource and hydrology curricula. The study develops several learning modules based on the three hydro-systems covering subjects such as: water-budget analysis, effects of human and natural changes, climate-hydrology teleconnections, and water-resource management scenarios. The new developments include an instructional interface to give critical guidance and support to the learner and an instructor's guide containing adaptation and implementation procedures to assist instructors in adopting and integrating the material into courses and provide a consistent experience. The design of the new hydrologic education developments will be transferable to independent institutions and adaptable both instructionally and technically through a server system capable of supporting additional developments by the educational community.

Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.

2013-12-01

215

Hydrological Ensemble Simulation in Huaihe Catchment Based on VIC Model  

NASA Astrophysics Data System (ADS)

Huaihe catchment plays a very important role in the political, economic, and cultural development in China. However, hydrological disasters frequently occur in Huaihe catchment, and thus hydrological simulation in this area has very important significance. The Variable Infiltration Capacity(VIC)model, a macroscale distributed hydrological model is applied to the upper Huaihe Catchment, to simulate the discharge of the basin outlet Bengbu station from 1970 to 1999. The uncertainty in the calibration of VIC model parameters has been analyzed, and the best set of parameters in the training period of 1970~1993 is achieved using the Generalized Likelihood Uncertainty Estimation (GLUE) method. The study also addresses the influence of different likelihood functions for the parameter sensitivity as well as the uncertainty of discharge simulation. Results show that among the six chosen parameters, the soil thickness of the second layer (d2) is the most sensitive one, followed by the saturation capacity curve shape parameter (B). Moreover, the parameter selection is sensitive to different likelihood functions. For example, the soil thickness of the third layer (d3) is sensitive when using Nash coefficient as the likelihood function, while d3 is not sensitive when using relative error as the likelihood function. With the 95% confidence interval, the coverage rate of the simulated discharge versus the observed discharge is small (around 0.4), indicating that the uncertainty in the model is large. The coverage rate of selecting relative error as the likelihood function is bigger than that of selecting Nash coefficient. Based on the calibration and sensitivity studies, hydrological ensemble forecasts have been established using multiple parameter sets. The ensemble mean forecasts show better simulations than the control forecast (i.e. the simulation using the best set of parameters) for the long-term trend of discharge, while the control forecast is better in the simulation of peak value. Probabilistic streamflow forecasts are also evaluated in the simulation of extreme peak flow. In addition, the influence of different training periods for the parameter sensitivity is discussed. Parameter scatter diagrams Discharge of Bengbu station

Sun, R.; Yuan, H.

2013-12-01

216

Quantile hydrologic model selection and model structure deficiency assessment: 1. Theory  

NASA Astrophysics Data System (ADS)

A theory for quantile based hydrologic model selection and model structure deficiency assessment is presented. The paper demonstrates that the degree to which a model selection problem is constrained by the model structure (measured by the Lagrange multipliers of the constraints) quantifies structural deficiency. This leads to a formal definition of model structure deficiency (or rigidity). Model structure deficiency introduces a bias in the prediction of an observed quantile, which is often not equal across quantiles. Structure deficiency is therefore diagnosed when any two quantile predictions for a given model structure cross since unequal bias across quantiles result in quantile predictions crossing. The analysis further suggests that the optimal value of quantile specific loss functions order different model structures by its structure deficiencies over a range of quantiles. In addition to such novelties, quantile hydrologic model selection is a frequentist approach that seeks to complement existing Bayesian approaches to hydrological model uncertainty.

Pande, Saket

2013-09-01

217

Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution  

NASA Astrophysics Data System (ADS)

Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive conceptualizations of hydrology in modeling landscape evolution.

Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

218

Particle filtering and ensemble Kalman filtering for state updating with hydrological conceptual rainfall-runoff models  

Microsoft Academic Search

Sequential importance resampling (SIR) filter, residual resampling filter (RR), and an ensemble Kalman (EnKF) filter that can handle dynamic nonlinear\\/non-Gaussian models are compared to correct erroneous model inputs and to obtain a rainfall-runoff update with a conceptual rainfall-runoff model HBV-96 for flood forecasting purposes. EnKF performs best with a low number of ensemble members. The RR filter performs best at

Albrecht H. Weerts; Ghada Y. H. El Serafy

2006-01-01

219

Hydrological modeling of the Mun River basin in Thailand  

NASA Astrophysics Data System (ADS)

SummarySources of pollution in river basins are increasing due to rapid changes in land uses and excessive nutrient application to crops which lead to degraded instream water quality. In this connection, the Mun River basin, one of the important and largest river basins in Thailand, has been studied. Comparative figures of nutrients in the Mun's water over a decade showed an increased total nitrogen (TN) and phosphorus (TP) ratio in the Lower Mun region (TN:TP > 14). Laboratory analysis of weekly water samples showed a realistic nutrient response when daily rainfall was compared to the seasonal water quality data collected by the Pollution Control Department (PCD). The Hydrologic Simulation Program - FORTRAN (HSPF) was calibrated and used to assess the effects of different land uses on river water quality. Model parameters related to hydrology and sediment were calibrated and validated using relevant measurements by the Royal Irrigation Department (RID). With a reasonable and acceptable model performance (r2 = 0.62), the highest simulated runoff was observed in urban areas. The trend of agricultural land (as a percentage of total area) - total nitrogen showed a linear relationship of a good correlation (i.e. r2 = 0.85). Based on the findings, it can be concluded that this model is expected to provide vital information for developing suitable land management policies and strategies to improve river water quality.

Akter, Aysha; Babel, Mukand S.

2012-07-01

220

Multivariate Extreme Value models in hydrology: a copula approach  

NASA Astrophysics Data System (ADS)

Multivariate Extreme Value models are a fundamental tool in hydrology in order to assess potentially dangerous events. For instance, the analysis of the 2003 severe drought event, or of the 1994 catastrophic food event, occurred over the Po river basin (Northern Italy) cannot be addressed completely by considering only the data collected at a single river section, e.g. at Pontelagoscuro gauge station close to the outlet. As frequently stressed in hydrologic literature, the statistical analysis of multivariate extremes is difficult, essentially due to (1) the complexity of the phenomena, (2) the reduced sample size of the actual multivariate datasets, and (3) the availability of suitable multivariate probability distributions. The target of this work is twofold. On the one hand we outline how, exploiting recent theoretical developments in the theory of Copulas, new models can be easily constructed: in particular, we show how a suitable number of parameters, having a physical meaning, can be introduced, a feature not shared by traditional Extreme Value models. On the other hand, we suggest several strategies in order to estimate the parameters of interest according to different criteria: these may use either a nearest neighbour or a nearest cluster approach, or exploit the pair-wise relationships between the available gauge stations. An application to food data is also illustrated and discussed.

de Michele, Carlo; Salvadori, Gianfausto

2010-05-01

221

Integrating water resources management in eco-hydrological modelling.  

PubMed

In this paper the integration of water resources management with regard to reservoir management in an eco-hydrological model is described. The model was designed to simulate different reservoir management options, such as optimized hydropower production, irrigation intake from the reservoir or optimized provisioning downstream. The integrated model can be used to investigate the impacts of climate variability/change on discharge or to study possible adaptation strategies in terms of reservoir management. The study area, the Upper Niger Basin located in the West African Sahel, is characterized by a monsoon-type climate. Rainfall and discharge regime are subject to strong seasonality. Measured data from a reservoir are used to show that the reservoir model and the integrated management options can be used to simulate the regulation of this reservoir. The inflow into the reservoir and the discharge downstream of the reservoir are quite distinctive, which points out the importance of the inclusion of water resources management. PMID:23552241

Koch, H; Liersch, S; Hattermann, F F

2013-01-01

222

The Coupling and Modeling of Eco-hydrological Processes in the Upper Reaches of Heihe River  

NASA Astrophysics Data System (ADS)

Developing new watershed models to couple the ecological, hydrological and social-economical processes for improving the understanding and regulation ability of the processes involved in water resources generation and transformation in the inland watersheds, is one important general scientific target of the NSFC Major Plan of "Integrated Research on the Eco-Hydrological Processes of Heihe Basin". With aims at this scientific target, the proposed research project will carry out a multi-scales and multi-processes study on eco-hydrology in the upper reaches of the Heihe River, identify the key eco-hydrological processes in the study region, develop a distributed eco-hydrological model for this region, and build a data assimilation and uncertainty analysis system for the developed model. Then this model will be used to assess the impacts of climate change and human activity on the runoff in the upper reaches of Heihe River. This study will improve the ability in simulating and predicting the runoff responses to environment changes in this basin, and also to promote the realization of the target of the NSFC Major Plan. This project will focus on the following three major researches: 1) the identification of key eco-hydrological processes and the overall structure designing of eco-hydrological model; 2) the development of distributed eco-hydrological watershed model; 3) the simulation and prediction of the eco-hydrological changes in the upper reaches of Heihe River. Through this study, it is expected to establish a benchmark eco-hydrological model for the mountainous watersheds with arid-cold climate and high elevation, where there are the most complex landscape, closely coupled ecological and hydrological system, and the most comprehensive hydrological processes. Also a breakthrough in the simulation of coupled eco-hydrological processes is expected.

Yang, Dawen; Cong, Zhentao; Yang, Hanbo

2013-04-01

223

A high-resolution European dataset for hydrologic modeling  

NASA Astrophysics Data System (ADS)

There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as inputs to the hydrological calibration and validation of EFAS as well as for establishing long-term discharge "proxy" climatologies which can then in turn be used for statistical analysis to derive return periods or other time series derivatives. In addition, this dataset will be used to assess climatological trends in Europe. Unfortunately, to date no baseline dataset at the European scale exists to test the quality of the herein presented data. Hence, a comparison against other existing datasets can therefore only be an indication of data quality. Due to availability, a comparison was made for precipitation and temperature only, arguably the most important meteorological drivers for hydrologic models. A variety of analyses was undertaken at country scale against data reported to EUROSTAT and E-OBS datasets. The comparison revealed that while the datasets showed overall similar temporal and spatial patterns, there were some differences in magnitudes especially for precipitation. It is not straightforward to define the specific cause for these differences. However, in most cases the comparatively low observation station density appears to be the principal reason for the differences in magnitude.

Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

2013-04-01

224

Hydrologic and geochemical modeling of a karstic Mediterranean watershed  

NASA Astrophysics Data System (ADS)

The SWAT model was modified to simulate the hydrologic and chemical response of karstic systems and assess the impacts of land use management and climate change of an intensively managed Mediterranean watershed in Crete, Greece. A methodology was developed for the determination of the extended karst area contributing to the spring flow as well as the degree of dilution of nitrates due to permanent karst water volume. The modified SWAT model has been able to capture the temporal variability of both karst flow and surface runoff using high frequency monitoring data collected since 2004 in addition to long term flow time series collected since 1973. The overall hydrologic budget of the karst was estimated and its evaporative losses were calculated to be 28% suggesting a very high rate of karst infiltration. Nitrate chemistry of the karst was simulated by calibrating a dilution factor allowing for the estimation of the total karstic groundwater volume to approximately 500 million m3 of reserve water. The nitrate simulation results suggested a significant impact of livestock grazing on the karstic groundwater and on surface water quality. Finally, simulation results for a set of climate change scenarios suggested a 17% decrease in precipitation, 8% decrease in ET and 22% decrease in flow in 2030-2050 compared to 2010-2020. A validated tool for integrated water management of karst areas has been developed, providing policy makers an instrument for water management that could tackle the increasing water scarcity in the island.

Nikolaidis, N. P.; Bouraoui, F.; Bidoglio, G.

2012-01-01

225

ANNIE - INTERACTIVE PROCESSING OF DATA BASES FOR HYDROLOGIC MODELS.  

USGS Publications Warehouse

ANNIE is a data storage and retrieval system that was developed to reduce the time and effort required to calibrate, verify, and apply watershed models that continuously simulate water quantity and quality. Watershed models have three categories of input: parameters to describe segments of a drainage area, linkage of the segments, and time-series data. Additional goals for ANNIE include the development of software that is easily implemented on minicomputers and some microcomputers and software that has no special requirements for interactive display terminals. Another goal is for the user interaction to be based on the experience of the user so that ANNIE is helpful to the inexperienced user and yet efficient and brief for the experienced user. Finally, the code should be designed so that additional hydrologic models can easily be added to ANNIE.

Lumb, Alan, M.; Kittle, John, L.

1985-01-01

226

Recent advances in modeling the coupled hydrologic cycle: Connecting atmospheric processes, land energy fluxes and hydrology (Invited)  

NASA Astrophysics Data System (ADS)

Complete models of the hydrologic cycle have gained recent attention as research has shown interdependence between the coupled land and energy balance of the subsurface, land surface and lower-atmosphere. Here the coupling strategy behind “groundwater to atmospheric models” is discussed and two models are presented, PF.WRF and PF.ARPS. These models are combinations of the of the Weather Research and Forecasting (WRF) and Advanced Regional Prediction System (ARPS) atmospheric models and ParFlow (PF) a parallel hydrology model that fully integrates three-dimensional, variably-saturated subsurface flow with overland flow. These models are coupled in an explicit, operator-splitting manner via the land surface model (LSM). The coupled model formulations will be presented and a very accurate balance of water between the subsurface, land surface and atmosphere is verified. A number of examples are then used to demonstrate the improvement in important physical processes afforded by the coupled models. As energy fluxes are an important component of land-atmosphere interactions, different formulations for water stress on transpiration will also be presented. These formulations provide differing degrees of interaction between deep roots and the free water table in addition to different mechanisms to moderate transpiration based on water limitations. Finally, thoughts on the path forward for modeling the hydrologic cycle will be presented.

Maxwell, R. M.; Ferguson, I. M.; Lundquist, J. K.; Chow, F. K.; Kollet, S. J.

2010-12-01

227

A hydrologic and geomorphic model of estuary breaching and closure  

NASA Astrophysics Data System (ADS)

To better understand how the hydrology of bar-built estuaries affects breaching and closing patterns, a model is developed that incorporates an estuary hydrologic budget with a geomorphic model of the inlet system. Erosion of the inlet is caused by inlet flow, whereas the only morphologic effect of waves is the deposition of sand into the inlet. When calibrated, the model is able to reproduce the initial seasonal breaching, seasonal closure, intermittent closures and breaches, and the low-streamflow (closed state) estuary hydrology of the Carmel Lagoon, located in Central California. Model performance was tested against three separate years of water-level observations. When open during these years, the inlet was visually observed to drain directly across the beach berm, in accordance with model assumptions. The calibrated model predicts the observed 48-h estuary stage amplitude with root mean square errors of 0.45 m, 0.39 m and 0.42 m for the three separate years. For the calibrated model, the probability that the estuary inlet is closed decreases exponentially with increasing inflow (streamflow plus wave overtopping), decreasing 10-fold in probability as mean daily inflow increases from 0.2 to 1.0 m3/s. Seasonal patterns of inlet state reflect the seasonal pattern of streamflow, though wave overtopping may become the main hydrologic flux during low streamflow conditions, infrequently causing short-lived breaches. In a series of sensitivity analyses it is seen that the status of the inlet and storage of water are sensitive to factors that control the storage, transmission, and inflow of water. By varying individual components of the berm system and estuary storage, the amount of the time the estuary is open may increase by 57%, or decrease by 44%, compared to the amount of time the estuary is open during calibrated model conditions for the 18.2-year model period. The individual components tested are: berm height, width, length, and hydraulic conductivity; estuary hypsometry (storage to stage relationship); two factors that control wave-swash sedimentation of the inlet; and sea level rise. The elevation of the berm determines the volume of water that must enter the estuary in order to breach, and it modulates the wave-overtopping flux and frequency. By increasing estuary storage capacity, the estuary will breach less frequently (- 27% change in time open for modeled excavation scenario) and store water up to 3 months later into the summer. Altering beach aquifer hydraulic conductivity affects inlet state, and patterns of breaching and water storage. As a result of sea-level rise of 1.67 m by 2100, and a beach berm that remains in its current location and accretes vertically, the amount of time the estuary remains open may decrease by 44%. Such a change is an end-member of likely scenarios given that the berm will translate landwards. Model results indicate that the amount of time the estuary is open is more sensitive to changes in wave run-up than the amount of sand deposited in the inlet per each overtopping wave.

Rich, Andrew; Keller, Edward A.

2013-06-01

228

Neural Network Hydrological Modelling: Linear Output Activation Functions?  

NASA Astrophysics Data System (ADS)

The power to represent non-linear hydrological processes is of paramount importance in neural network hydrological modelling operations. The accepted wisdom requires non-polynomial activation functions to be incorporated in the hidden units such that a single tier of hidden units can thereafter be used to provide a 'universal approximation' to whatever particular hydrological mechanism or function is of interest to the modeller. The user can select from a set of default activation functions, or in certain software packages, is able to define their own function - the most popular options being logistic, sigmoid and hyperbolic tangent. If a unit does not transform its inputs it is said to possess a 'linear activation function' and a combination of linear activation functions will produce a linear solution; whereas the use of non-linear activation functions will produce non-linear solutions in which the principle of superposition does not hold. For hidden units, speed of learning and network complexities are important issues. For the output units, it is desirable to select an activation function that is suited to the distribution of the target values: e.g. binary targets (logistic); categorical targets (softmax); continuous-valued targets with a bounded range (logistic / tanh); positive target values with no known upper bound (exponential; but beware of overflow); continuous-valued targets with no known bounds (linear). It is also standard practice in most hydrological applications to use the default software settings and to insert a set of identical non-linear activation functions in the hidden layer and output layer processing units. Mixed combinations have nevertheless been reported in several hydrological modelling papers and the full ramifications of such activities requires further investigation and assessment i.e. non-linear activation functions in the hidden units connected to linear or clipped-linear activation functions in the output unit. There are two obvious advantages related to the use of a linear activation function in the output unit: (i) to restrict potential impacts and distortions associated with upper limit and lower limit saturation effects; and (ii) to address potential deficiencies and ceilings associated with undershoots or requirements to extrapolate beyond the range of the training dataset. The harmful side effects of using linear as opposed to non-linear activation functions in the output unit will be reported in this paper based on an investigation of six-hour timestep operational river level forecasting for the Skelton Gauging Station [Station No: 027009; Grid Ref: SE 568 554] on the River Ouse in England. The power to develop simple near-linear one-step-ahead forecasts remained more or less unchanged; whereas the challenge to develop more demanding non-linear four-step-ahead forecasts revealed major shortcomings related to the implementation of a linear activation function in the output unit of a parsimonious neural network model.

Abrahart, R. J.; Dawson, C. W.

2005-12-01

229

Hydrological Modelling in the Lake Tana Basin, Ethiopia Using SWAT Model  

Microsoft Academic Search

The SWAT2005 model was applied to the Lake Tana Basin for modeling of the hydrological water balance. The main objective of this study was to test the performance and feasibility of the SWAT model for prediction of stream- flow in the Lake Tana Basin. The model was calibrated and validated on four tributaries of Lake Tana; Gumera, GilgelA- bay, Megech

Shimelis G. Setegn; Ragahavan Srinivasan; Bijan Dargahi

2008-01-01

230

Development and application of a spatially-distributed Arctic hydrological and thermal process model (ARHYTHM)  

Microsoft Academic Search

A process-based, spatially distributed hydrological model was developed to quantitatively simulate the energy and mass transfer processes and their interactions within arctic regions (arctic hydrological and thermal model, ARHYTHM). The model first determines the flow direction in each element, the channel drainage network and the drainage area based upon the digital elevation data. Then it simulates various physical processes: including

Ziya Zhang; Douglas L. Kane; Larry D. Hinzman

2000-01-01

231

Assessment of Digital Land Cover Maps for Hydrological Modeling in the Yampa River Basin, Colorado, USA  

Microsoft Academic Search

Land cover data are required to parameterize watersheds for hydrological modeling. There is a multitude of different land cover maps, and determining which input data map for the model can be unclear. The goal of this study is to quantify the differences between various publically available land cover maps to determine their relative suitability for hydrological modeling of the Yampa

J. M. Repass; S. Fassnacht; R. Reich

2004-01-01

232

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs  

Microsoft Academic Search

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the

Andrew W. Wood; Lai R. Leung; V. Sridhar; D. P. Lettenmaier

2004-01-01

233

Building Community Around Hydrologic Data Models Within CUAHSI  

NASA Astrophysics Data System (ADS)

The Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI) has a Hydrologic Information Systems project which aims to provide better data access and capacity for data synthesis for the nation's water information, both that collected by academic investigators and that collected by water agencies. These data include observations of streamflow, water quality, groundwater levels, weather and climate and aquatic biology. Each water agency or research investigator has a unique method of formatting their data (syntactic heterogeneity) and describing their variables (semantic heterogeneity). The result is a large agglomeration of data in many formats and descriptions whose full content is hard to interpret and analyze. CUAHSI is helping to resolve syntactic heterogeneity through the development of WaterML, a standard XML markup language for communicating water observations data through web services, and a standard relational database structure for archiving data called the Observations Data Model. Variables in these data archiving and communicating systems are indexed against a controlled vocabulary of descriptive terms to provide the capacity to synthesize common data types from disparate data sources.

Maidment, D.

2007-12-01

234

EVALUATION OF SATELLITE IMAGES OF SNOW COVER AREAS FOR IMPROVING SPRING FLOOD IN THE HBV-MODEL  

Microsoft Academic Search

For the hydro power companies it is of major importance to know the magnitude of the spring flood. Hence, the amount of snow is crucial for forecast modelling. In mountainous areas with plenty of snow, the meteorological network is often sparse, and they lack direct observations of the snow pack. Therefore, if it is possible to combine satellite snow cover

Karen Lundholm; Barbro Johansson; Eirik Malnes; Rune Solberg

235

Coupling Sediment Transport with the Integrated Hydrologic Model (PIHM)  

NASA Astrophysics Data System (ADS)

Penn State Integrated Hydrologic Model (PIHM) was developed by Qu and Duffy (2004) for multi-process simulation. As a further work, a physically-based non-equilibrium non-uniform sediment transport modeling component is developed and coupled with PIHM. It combines the hillslope and channel processes, and accounts for sediment yield as well as morphological evolution. For hillslope, the rain splash erosion, hydraulic erosion, and sediment transport by overland flow are simulated; for channel, it takes into account the hydraulic detachment and sediment transport by channel flow. An algorithm for bed armoring is proposed and incorporated in the component. And it also includes a river bank erosion submodel which is modified from Darby et al. (2002). The coupling system is solved using a semi-discrete finite volume approach. It is being tested based on three types of flow routing schemes: dynamic wave, diffusion wave and kinematic wave using different scales of watershed data.

Li, S.; Duffy, C. J.; Qu, Y.

2006-12-01

236

Assessing Hydrologic Impacts of Land Configuration Changes Using an Integrated Hydrologic Model at the Rocky Flats Environmental Technology Site, Colorado  

NASA Astrophysics Data System (ADS)

The Rocky Flats Environmental Technology Site (RFETS) in Golden, Colorado, a former Department of Energy nuclear weapons manufacturing facility, is currently undergoing closure. The natural semi-arid interaction between surface and subsurface flow at RFETS is complex and complicated by the industrial modifications to the flow system. Using a substantial site data set, a distributed parameter, fully-integrated hydrologic model was developed to assess the hydrologic impact of different hypothetical site closure configurations on the current flow system and to better understand the integrated hydrologic behavior of the system. An integrated model with this level of detail has not been previously developed in a semi-arid area, and a unique, but comprehensive, approach was required to calibrate and validate the model. Several hypothetical scenarios were developed to simulate hydrologic effects of modifying different aspects of the site. For example, some of the simulated modifications included regrading the current land surface, changing the existing surface channel network, removing subsurface trenches and gravity drain flow systems, installing a slurry wall and geotechnical cover, changing the current vegetative cover, and converting existing buildings and pavement to permeable soil areas. The integrated flow model was developed using a rigorous physically-based code so that realistic design parameters can simulate these changes. This code also permitted evaluation of changes to complex integrated hydrologic system responses that included channelized and overland flow, pond levels, unsaturated zone storage, groundwater heads and flow directions, and integrated water balances for key areas. Results generally show that channel flow offsite decreases substantially for different scenarios, while groundwater heads generally increase within the reconfigured industrial area most of which is then discharged as evapotranspiration. These changes have significant implications to site closure and operation.

Prucha, R. H.; Dayton, C. S.; Hawley, C. M.

2002-12-01

237

GIS embedded hydrological modeling: the SID&GRID project  

NASA Astrophysics Data System (ADS)

The SID&GRID research project, started April 2010 and funded by Regione Toscana (Italy) under the POR FSE 2007-2013, aims to develop a Decision Support System (DSS) for water resource management and planning based on open source and public domain solutions. In order to quantitatively assess water availability in space and time and to support the planning decision processes, the SID&GRID solution consists of hydrological models (coupling 3D existing and newly developed surface- and ground-water and unsaturated zone modeling codes) embedded in a GIS interface, applications and library, where all the input and output data are managed by means of DataBase Management System (DBMS). A graphical user interface (GUI) to manage, analyze and run the SID&GRID hydrological models based on open source gvSIG GIS framework (Asociación gvSIG, 2011) and a Spatial Data Infrastructure to share and interoperate with distributed geographical data is being developed. Such a GUI is thought as a "master control panel" able to guide the user from pre-processing spatial and temporal data, running the hydrological models, and analyzing the outputs. To achieve the above-mentioned goals, the following codes have been selected and are being integrated: 1. Postgresql/PostGIS (PostGIS, 2011) for the Geo Data base Management System; 2. gvSIG with Sextante (Olaya, 2011) geo-algorithm library capabilities and Grass tools (GRASS Development Team, 2011) for the desktop GIS; 3. Geoserver and Geonetwork to share and discover spatial data on the web according to Open Geospatial Consortium; 4. new tools based on the Sextante GeoAlgorithm framework; 5. MODFLOW-2005 (Harbaugh, 2005) groundwater modeling code; 6. MODFLOW-LGR (Mehl and Hill 2005) for local grid refinement; 7. VSF (Thoms et al., 2006) for the variable saturated flow component; 8. new developed routines for overland flow; 9. new algorithms in Jython integrated in gvSIG to compute the net rainfall rate reaching the soil surface, as input for the unsaturated/saturated flow model. At this stage of the research (which will end April 2013), two primary components of the master control panel are being developed: i. a SID&GRID toolbar integrated into gvSIG map context; ii. a new Sextante set of geo-algorithm to pre- and post-process the spatial data to run the hydrological models. The groundwater part of the code has been fully integrated and tested and 3D visualization tools are being developed. The LGR capability has been extended to the 3D solution of the Richards' equation in order to solve in detail the unsaturated zone where required. To be updated about the project, please follow us at the website: http://ut11.isti.cnr.it/SIDGRID/

Borsi, I.; Rossetto, R.; Schifani, C.

2012-04-01

238

Improved cavity detection from coupled seismic and hydrologic models  

NASA Astrophysics Data System (ADS)

Seismic methods hold much promise for cavity detection, but the results from field measurements have been frustratingly inconsistent between field sites. The reasons for the inconsistencies are not fully understood, though water saturation in the near-surface may be responsible to some extent. The conventional approach has been to focus on reflections and refractions generated from the impedance contrast of the cavity wall itself, where the dimensions and geometry of the cavity should play key roles. Here, we instead focus on the influence of impedance contrasts that are generated by hydrologic processes in the adjacent porous medium. These contrasts can potentially increase or decrease the reflection/refraction footprint of the cavity itself. Detectable hydrologic anomalies can be created by the simple drainage of groundwater into the cavity (initially saturated conditions) or by the creation of a capillary barrier around the cavity (initially unsaturated conditions). Because both processes ultimately involve unsaturated conditions we use HYDRUS 2D to numerically solve the Richard's equation and simulate flow through the vadose zone. Using the generated soil moisture information and Brutsaert's (1964) saturation-velocity relation, we constructed velocity models. Our simulations suggest several scenarios where changes in saturation due to the cavity may be utilized to enhance cavity detection with seismic waves. One simulation is for unsaturated conditions in the top 10 meters of soil, where capillary forces exert a major influence on velocity. In this case, the impedance contrast is greatest for near-saturated soils. Deeper cavities (100s of meters) in permeable saturated materials are also favorable due to the sharp impedance contrast between saturated and unsaturated material. Our hydrology-determined velocity models are then used in finite-difference wave propagation simulations to determine the effects on seismic waves at various depths and saturations. Saturation features in the seismic data can then be utilized to detect cavities rather than relying on traditional yet inconsistent reflection/refraction approach. In ongoing work, we will ground-truth these models with both laboratory and experimental results. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Desilets, S.; Bonal, N. D.; Desilets, D.

2012-12-01

239

Parameterization of potential evapotranspiration approaches for distributed hydrologic modeling  

NASA Astrophysics Data System (ADS)

Reliable soil moisture products are needed for the estimation of plant available water or agricultural droughts. For the simulation of hydrological states, e.g. soil moisture, the estimation of evapotranspiration is crucial since it has the largest contribution to the water balance besides precipitation. In hydrological modeling the evapotranspiration is usually estimated based on potential evapotranspiration (PET). The common approaches for PET estimation and their parameterization are sufficient at the point or field scale for which they have been developed. But for spatially distributed estimations on the mesoscale, e.g. 4 km, their robust parameterization is still a challenge in current research. The aim of this study is to find scale and location independent parameters for three different potential evapotranspiration formulations, which are applied in the mesoscale Hydrologic Model (mHM). PET is estimated using the 1) Hargreaves-Samani, 2) Priestley-Taylor, and 3) Penman-Monteith equations. The Hargreaves-Samani method is a temperature driven approach, whereas the other two methods are based on radiation. For estimating the parameters of the above mentioned PET formulations, the Multiscale Parameter Regionalization technique is used. This technique accounts for subgrid variabilities by connecting morphological terrain properties, which are available in a higher resolution than the model resolution, with the parameters for the particular PET approach. The parameters, which needed to be estimated, are the coefficient of the Hargreaves-Samani equation, the Priestley-Taylor coefficient, and the aerodynamic and bulk surface resistance for the Penman-Monteith equation. The Hargreaves-Samani coefficient is regionalized based on the aspect of the terrain. The Priestley-Taylor coefficient as well as the aerodynamic and bulk surface resistance have been estimated using static land cover information combined with leaf area index (LAI) development curves and thus an approximation for vegetation information. This new parameterized PET approaches are evaluated in six different German river basins ranging from 6,000 km2 to 38,000 km2 including a spatial variety from catchments in the northern German lowlands to alpine catchments in the south. The comparison of the results is focusing on evapotranspiration, soil moisture and discharge. Whereas only slight changes in the discharge hydrograph have been observed in the comparison of the three PET equations, the impact on soil moisture is significant. Especially during the summer period the soil moisture is lower for the Priestley-Taylor and Penman-Monteith formulation compared to the Hargreaves-Samani equation. This effect is due to higher estimates in PET for those two methods. Furthermore a validation against eddy covariance measurements showed that the dynamics of evapotranspiration is captured well by the three methods.

Zink, Matthias; Mai, Juliane; Cuntz, Matthias; Samaniego, Luis

2014-05-01

240

Forensic isotope analysis to refine a hydrologic conceptual model.  

PubMed

Water resources in the arid southwestern United States are frequently the subject of conflict from competing private and public interests. Legal remedies may remove impasses, but the technical analysis of the problem often determines the future success of legal solutions. In Owens Valley, California, the source of water for the Los Angeles Aqueduct (LAA) is flow diverted from the Owens River and its tributaries and ground water from valley aquifers. Future management of ground water delivered to the LAA needs technical support regarding quantity available, interconnection of shallow and confined aquifers, impact on local springs, and rate of recharge. Ground water flow models and ground water composition are tools already in use, but these have large uncertainty for local interpretations. This study conducted targeted sampling of springs and wells to evaluate the hydrologic system to corroborate conceptual and numerical models. The effort included measurement of intrinsic isotopic composition at key locations in the aquifers. The stable isotopic data of boron (delta(11)B), sulfur (delta(34)S), oxygen (delta(18)O), hydrogen (delta D), and tritium ((3)H) supported by basic chemical data provided rules for characterizing the upper and the lower aquifer system, confirmed the interpretation of ground water flow near faults and flow barriers, and detected hydraulic connections between the LAA and the perennial springs at key locations along the unlined reach of the LAA. This study exemplifies the use of forensic isotopic approaches as independent checks on the consistency of interpretations of conceptual models of a ground water system and the numerical hydrologic simulations. PMID:18266731

Bassett, R L; Steinwand, Aaron; Jorat, Saeed; Petersen, Christian; Jackson, Randy

2008-01-01

241

A distributed hydrology-vegetation model for complex terrain  

NASA Astrophysics Data System (ADS)

A distributed hydrology-vegetation model is described that includes canopy interception, evaporation, transpiration, and snow accumulation and melt, as well as runoff generation via the saturation excess mechanisms. Digital elevation data are used to model topographic controls on incoming solar radiation, air temperature, precipitation, and downslope water movement. Canopy evapotranspiration is represented via a two-layer Penman-Monteith formulation that incorporates local net solar radiation, surface meteorology, soil characteristics and moisture status, and species-dependent leaf area index and stomatal resistance. Snow accumulation and ablation are modeled using an energy balance approach that includes the effects of local topography and vegetation cover. Saturated subsurface flow is modeled using a quasi three-dimensional routing scheme. The model was applied at a 180-m scale to the Middle Fork Flathead River basin in northwestern Montana. This 2900-km2, snowmelt-dominated watershed ranges in elevation from 900 to over 3000 m. The model was calibrated using 2 years of recorded precipitation and streamflow. The model was verified against 2 additional years of runoff and against advanced very high resolution radiometer based spatial snow cover data at the 1-km2 scale. Simulated discharge showed acceptable agreement with observations. The simulated areal patterns of snow cover were in general agreement with the remote sensing observations, but were lagged slightly in time.

Wigmosta, Mark S.; Vail, Lance W.; Lettenmaier, Dennis P.

1994-06-01

242

Developing a Framework for Testing Distributed Hydrologic Models at the Hillslope Scale  

NASA Astrophysics Data System (ADS)

Numerous hydrologic models solve Richards equation for the variably saturated subsurface domain. However, the scarcity of measured hydrologic states and variables and the scale discrepancies between observations and simulations pose a challenge in testing and evaluating such models. We develop a flexible framework for testing distributed hydrologic models at the hillslope scale. The proposed method consists of three major steps. First we generate "hypothetical realities" representing the hydrologic response of a synthetic watershed modeled after the 10.5 ha Tarrawarra catchment in Australia. The catchment was extensively monitored and has a relatively simple geometry with 0.5-1.5m deep soils overlaying bedrock and a fairly uniform grass cover. Eleven years of half-hourly time increment hydrological states and fluxes generically termed "hypothetical realities" have been generated using the complex Integrated Hydrology Model (InHM) representing fully coupled 3D variably saturated subsurface and 2D surface flow with high resolution. In the second step, simpler distributed hydrologic models can be evaluated against the hypothetical realities, which represent an error-free data set of hydrologic variables. The simpler distributed models are run first without calibration and then with calibration against different combinations of the observed data from the hypothetical realities. In the third step, further tests of distributed models incorporate event based and continuous simulations, variable spatial and temporal scales and increasing amounts and types of model input data and observed data.

Cristea, N. C.; Kampf, S. K.; Mirus, B. B.; Loague, K.; Burges, S. J.

2007-12-01

243

Development and comparison of Bayesian modularization method in uncertainty assessment of hydrological models  

NASA Astrophysics Data System (ADS)

With respect to model calibration, parameter estimation and analysis of uncertainty sources, different approaches have been used in hydrological models. Bayesian method is one of the most widely used methods for uncertainty assessment of hydrological models, which incorporates different sources of information into a single analysis through Bayesian theorem. However, none of these applications can well treat the uncertainty in extreme flows of hydrological models' simulations. This study proposes a Bayesian modularization method approach in uncertainty assessment of conceptual hydrological models by considering the extreme flows. It includes a comprehensive comparison and evaluation of uncertainty assessments by a new Bayesian modularization method approach and traditional Bayesian models using the Metropolis Hasting (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions are used in combination with traditional Bayesian: the AR (1) plus Normal and time period independent model (Model 1), the AR (1) plus Normal and time period dependent model (Model 2) and the AR (1) plus multi-normal model (Model 3). The results reveal that (1) the simulations derived from Bayesian modularization method are more accurate with the highest Nash-Sutcliffe efficiency value, and (2) the Bayesian modularization method performs best in uncertainty estimates of entire flows and in terms of the application and computational efficiency. The study thus introduces a new approach for reducing the extreme flow's effect on the discharge uncertainty assessment of hydrological models via Bayesian. Keywords: extreme flow, uncertainty assessment, Bayesian modularization, hydrological model, WASMOD

Li, L.; Xu, C.-Y.; Engeland, K.

2012-04-01

244

An attempt of ensemble modelling of future hydrological regime for selected river basin.  

NASA Astrophysics Data System (ADS)

Ensemble modelling of hydrological regime may refer to usage of different Regional Climate Models (RCMs) coupled with one hydrological model, or usage of one RCM coupled with multiple hydrological models. Our goal was to examine future flow regimes based on different hydrological models. We conducted a river basin study based on one particular subbasin (Berze) of the river Lielupe basin. Lielupe is a lowland river with basin area of 17000 sq.km, situated in Latvia and Lithuania. Area of chosen subbasin is approximately 1000 sq.km. Ensemble of hydrological models consisted of MIKE SHE, and MIKE BASIN by DHI, the runoff model embedded in RCM, and in-house FiBasin model. MIKE SHE is grid based distributed hydrological model coupled with MIKE 11 flow routing model. MIKE Basin has embedded, conceptual catchment based NAM model. FiBasin is spatially distributed, finite volume based hydrological model with hydraulic routing network. The RCM and climate change scenarios are provided by Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) project. Time period for climate change scenarios is 2071-2100. The different responses from climate change, using different calibration sets where evaluated. The uncertainty related to choice of hydrological models is evaluated. It is found that the choice of hydrological model can lead to uncertainty witch is comparable with the even to difference between the climate scenarios, or the climate change itself. This conclusion is valid for the area of study in which the expected change of the hydrological regime is rather small.

Valainis, A.; Timuhin, A.; Bethers, U.

2009-04-01

245

Studying Hydrological Response of the Churchill River to Climate Change Using Distributed Hydrological Models  

Microsoft Academic Search

The global climate has shown drastic changes in recent decades. It is of critical importance to investigate how global climate changes affect the different aspects of the hydrological cycle and the availability of freshwater resources in particular. In this study, the impact of climate change on the regional water and energy cycles in the Churchill River basin was assessed using

Y. Yi; P. F. Rasmussen

2009-01-01

246

A simple hydrologically based model of land surface water and energy fluxes for general circulation models  

Microsoft Academic Search

A generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model (GCM) is described. The new model is comprised of a two-layer characterization of the soil column, and uses an aerodynamic representation of the latent and sensible heat fluxes at the land surface. The

Xu Liang; Dennis P. Lettenmaier; S. J. Burges

1994-01-01

247

Calibration of hydrological models using flow-duration curves  

NASA Astrophysics Data System (ADS)

The degree of belief we have in predictions from hydrologic models depends on how well they can reproduce observations. Calibrations with traditional performance measures such as the Nash-Sutcliffe model efficiency are challenged by problems including: (1) uncertain discharge data, (2) variable importance of the performance with flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. A new calibration method using flow-duration curves (FDCs) was developed which addresses these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) of the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested - based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments without resulting in overpredicted simulated uncertainty. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application e.g. using more/less EPs at high/low flows. While the new method is less sensitive to epistemic input/output errors than the normal use of limits of acceptability applied directly to the time series of discharge, it still requires a reasonable representation of the distribution of inputs. Additional constraints might therefore be required in catchments subject to snow. The results suggest that the new calibration method can be useful when observation time periods for discharge and model input data do not overlap. The new method could also be suitable for calibration to regional FDCs while taking uncertainties in the hydrological model and data into account.

Westerberg, I. K.; Guerrero, J.-L.; Younger, P. M.; Beven, K. J.; Seibert, J.; Halldin, S.; Freer, J. E.; Xu, C.-Y.

2010-12-01

248

Calibration of hydrological models using flow-duration curves  

NASA Astrophysics Data System (ADS)

The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1) uncertain discharge data, (2) variable sensitivity of different performance measures to different flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs) to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested - based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WASMOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e.g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of acceptability applied directly to the time series of discharge, it still requires a reasonable representation of the distribution of inputs. Additional constraints might therefore be required in catchments subject to snow and where peak-flow timing at sub-daily time scales is of high importance. The results suggest that the calibration method can be useful when observation time periods for discharge and model input data do not overlap. The method could also be suitable for calibration to regional FDCs while taking uncertainties in the hydrological model and data into account.

Westerberg, I. K.; Guerrero, J.-L.; Younger, P. M.; Beven, K. J.; Seibert, J.; Halldin, S.; Freer, J. E.; Xu, C.-Y.

2011-07-01

249

Dynamic Neural Networks for Nonstationary Hydrological Time Series Modeling  

Microsoft Academic Search

Evidence of nonstationary trends in hydrological time series, which result from natural and\\/or anthropogenic climatic variability\\u000a and change, has raised a number of questions as to the adequacy of conventional statistical methods for long-term (seasonal\\u000a to annual) hydrologic time series forecasting. Most conventional statistical methods that are used in hydrology will suffer\\u000a from severe limitations as they assume a stationary

P. Coulibaly; C. K. Baldwin

250

Hydrological Land Classification Based on Landscape Units  

NASA Astrophysics Data System (ADS)

Landscape classification in meaningful hydrological units has important implications for hydrological modeling. Conceptual hydrological models, such as HBV- type models, are most commonly designed to represent catchments in a lumped or semi-distributed way at best, i.e. treating them as single entities or sometimes accounting for topographical and land cover variability by introducing some level of stratification. These oversimplifications can frequently lead to substantial misrepresentations of flow generating processes in the catchments in question, as feedback processes between topography, land cover and hydrology in different landscape units are poorly represented. By making use of readily available topographical information, hydrological units can be identified based on the concept of ''Height above Nearest Drainage'' (HAND; Rennó et al., 2008). These units are characterized by distinct hydrological behavior, and they can be represented using different model structures (Savenije, 2010). We selected the Wark Catchment in Grand Duchy of Luxembourg and identified three landscape units: plateau, wetland and hillslope. The original HAND was compared to other, similar models for landscape classification, which make use of other topographical indicators. The models were applied to a 5±5 m2 DEM, and were tested using data collected in the field. The comparison between the models showed that HAND is a more appropriate hydrological descriptor than other models. The map of the classified landscape was set in a probabilistic framework and was then used to determine the proportion of the individual units in the catchment. Different model structures were then assigned to the individual units and were used to model total runoff.

Gharari, S.; hrachowitz, M.; Fenicia, F.; Savenije, H.

2011-12-01

251

Feedback Loop of Data Infilling Using Model Result of Actual Evapotranspiration from Satellites and Hydrological Model  

NASA Astrophysics Data System (ADS)

Using satellite data in a hydrological model has long been occurring in modelling of hydrological processes, as a source of low cost regular data. The methods range from using satellite products as direct input, model validation, and data assimilation. However, the satellite data frequently face the missing value problem, whether due to the cloud cover or the limited temporal coverage. The problem could seriously affect its usefulness in hydrological model, especially if the model uses it as direct input, so data infilling becomes one of the important parts in the whole modelling exercise. In this research, actual evapotranspiration product from satellite is directly used as input into a spatially distributed hydrological model, and validated by comparing the catchment's end discharge with measured data. The instantaneous actual evapotranspiration is estimated from MODIS satellite images using a variation of the energy balance model for land (SEBAL). The eight-day cumulative actual evapotranspiration is then obtained by a temporal integration that uses the reference evapotranspiration calculated from meteorological data [1]. However, the above method cannot fill in a cell if the cell is constantly having no-data value during the eight-day periods. The hydrological model requires full set of data without no-data cells, hence, the no-data cells in the satellite's evapotranspiration map need to be filled in. In order to fills the no-data cells, an output of hydrological model is used. The hydrological model is firstly run with reference evapotranspiration as input to calculate discharge and actual evapotranspiration. The no-data cells in the eight-day cumulative map from the satellite are then filled in with the output of the first run of hydrological model. The final data is then used as input in a hydrological model to calculate discharge, thus creating a loop. The method is applied in the case study of Rijnland, the Netherlands where in the winter, cloud cover is persistent and leads to many no-data cells in the satellite products. The Rijnland area is a low-lying area with tight water system control. The satellite data is used as input in a SIMGRO model, a spatially distributed hydrological model that is able to handle the controlled water system and that is suitable for the low-lying areas in the Netherlands. The application in the Rijnland area gives overall a good result of total discharge. By using the method, the hydrological model is improved in term of spatial hydrological state, where the original model is only calibrated to discharge in one location. [1] Alexandridis, T.K., Cherif, I., Chemin, Y., Silleos, G.N., Stavrinos, E. & Zalidis, G.C. (2009). Integrated Methodology for Estimating Water Use in Mediterranean Agricultural Areas. Remote Sensing. 1

Murdi Hartanto, Isnaeni; Alexandridis, Thomas K.; van Andel, Schalk Jan; Solomatine, Dimitri

2014-05-01

252

Simulated Climatology of a General Circulation Model with a Hydrologic CYCLE1  

Microsoft Academic Search

A numerical experiment with a general circulation model with a simple hydrologic cycle is performed. The basic framework of this model is identical with that adopted for the previous study (35) except for the incorporation of a simplified hydrologic cycle which consists of the advection of water vapor by large-scale motion, evaporation from t.he surface, precipitation, and an artificial adjustment

Syukuro Manabe; Joseph Smagorinsky; Robert F. Strickler

1965-01-01

253

Investigation of Hydrological Variability in West Africa Using Land Surface Models  

Microsoft Academic Search

The availability of freshwater is a particularly important issue in Africa where large portions of the continent are arid or semiarid and climate is highly variable. Sustainable water resource management requires the assessment of hydrological variability in response to nature climate fluctuation. In this study, a land surface model, the Integrated Biosphere Simulator (IBIS), and a hydrological routing model, the

K. Y. Li; M. T. Coe; N. Ramankutty

2005-01-01

254

Stimulation from Simulation? A Teaching Model of Hillslope Hydrology for Use on Microcomputers.  

ERIC Educational Resources Information Center

The design and use of a simple computer model which simulates a hillslope hydrology is described in a teaching context. The model shows a relatively complex environmental system can be constructed on the basis of a simple but realistic theory, thus allowing students to simulate the hydrological response of real hillslopes. (Author/TRS)

Burt, Tim; Butcher, Dave

1986-01-01

255

Adaptive neural-based fuzzy inference system (ANFIS) approach for modelling hydrological time series  

Microsoft Academic Search

The main aim of this study is to develop a flow prediction method, based on the adaptive neural-based fuzzy inference system (ANFIS) coupled with stochastic hydrological models. An ANFIS methodology is applied to river flow prediction in Dim Stream in the southern part of Turkey. Application is given for hydrological time series modelling. Synthetic series, generated through autoregressinve moving-average (ARMA)

M. EROL KESKIN; DILEK TAYLAN; ÖZLEM TERZI

2006-01-01

256

Hydrologic Setting and Conceptual Hydrologic Model of the Walker River Basin, West-Central Nevada  

USGS Publications Warehouse

The Walker River is the main source of inflow to Walker Lake, a closed-basin lake in west-central Nevada. Between 1882 and 2008, agricultural diversions resulted in a lake-level decline of more than 150 feet and storage loss of 7,400,000 acre-ft. Evaporative concentration increased dissolved solids from 2,500 to 17,000 milligrams per liter. The increase in salinity threatens the survival of the Lahontan cutthroat trout, a native species listed as threatened under the Endangered Species Act. This report describes the hydrologic setting of the Walker River basin and a conceptual hydrologic model of the relations among streams, groundwater, and Walker Lake with emphasis on the lower Walker River basin from Wabuska to Hawthorne, Nevada. The Walker River basin is about 3,950 square miles and straddles the California-Nevada border. Most streamflow originates as snowmelt in the Sierra Nevada. Spring runoff from the Sierra Nevada typically reaches its peak during late May to early June with as much as 2,800 cubic feet per second in the Walker River near Wabuska. Typically, 3 to 4 consecutive years of below average streamflow are followed by 1 or 2 years of average or above average streamflow. Mountain ranges are comprised of consolidated rocks with low hydraulic conductivities, but consolidated rocks transmit water where fractured. Unconsolidated sediments include fluvial deposits along the active channel of the Walker River, valley floors, alluvial slopes, and a playa. Sand and gravel deposited by the Walker River likely are discontinuous strata throughout the valley floor. Thick clay strata likely were deposited in Pleistocene Lake Lahontan and are horizontally continuous, except where strata have been eroded by the Walker River. At Walker Lake, sediments mostly are clay interbedded with alluvial slope, fluvial, and deltaic deposits along the lake margins. Coarse sediments form a multilayered, confined-aquifer system that could extend several miles from the shoreline. Depth to bedrock in the lower Walker River basin ranges from about 900 to 2,000 feet. The average hydraulic conductivity of the alluvial aquifer in the lower Walker River basin is 10-30 feet per day, except where comprised of fluvial sediments. Fluvial sediments along the Walker River have an average hydraulic conductivity of 70 feet per day. Subsurface flow was estimated to be 2,700 acre-feet per year through Double Spring. Subsurface discharge to Walker Lake was estimated to be 4,400 acre-feet per year from the south and 10,400 acre-feet per year from the north. Groundwater levels and groundwater storage have declined steadily in most of Smith and Mason Valleys since 1960. Groundwater levels around Schurz, Nevada, have changed little during the past 50 years. In the Whisky Flat area south of Hawthorne, Nevada, agricultural and municipal pumpage has lowered groundwater levels since 1956. The water-level decline in Walker Lake since 1882 has caused the surrounding alluvial aquifer to drain and groundwater levels to decline. The Wabuska streamflow-gaging station in northern Mason Valley demarcates the upper and lower Walker River basin. The hydrology of the lower Walker River basin is considerably different than the upper basin. The upper basin consists of valleys separated by consolidated-rock mountains. The alluvial aquifer in each valley thins or pinches out at the downstream end, forcing most groundwater to discharge along the river near where the river is gaged. The lower Walker River basin is one surface-water/groundwater system of losing and gaining reaches from Wabuska to Walker Lake, which makes determining stream losses and the direction and amount of subsurface flow difficult. Isotopic data indicate surface water and groundwater in the lower Walker River basin are from two sources of precipitation that have evaporated. The Walker River, groundwater along the Wassuk Range, and Walker Lake plot along one evaporation line. Groundwater along th

Lopes, Thomas J.; Allander, Kip K.

2009-01-01

257

Plug-and-Play Hydrologic Modeling: Is That Really Possible?  

NASA Astrophysics Data System (ADS)

The vision of a community of modelers that shares reusable and well-tested process components that can easily be linked together to create new models is very appealing. In this vision, trying a new method for modeling a physical process, comparing two methods from different groups or coupling two models together to do something new is painless and straightforward. Scientists get to spend more time on understanding the natural world, making predictions and analyzing model results. Students quickly learn how different approaches differ and how sensitive models are to various input parameters. They begin to understand how the whole system works instead of just one part of it. Believe it or not, this vision is on the verge of becoming a reality but we aren't quite there yet. In order for the hydrologic modeling community to achieve this vision and work together in this way it isn't necessary for us to drastically change the way we do things. However, we do need to agree on some minimum set of standards and these have mostly to do with providing standardized metadata decriptions of our models and our data sets. We already have great software tools for accommodating differences between models that allow them to be coupled and work together. These include tools for spatial regridding, time interpolation, unit conversion, format conversion and even computer language interoperability. But in order to write software that automatically invokes these tools when needed, we need standardized machine and human-readable metadata descriptions of our models and data sets. The purpose of this talk is to review some of the technical problems that have already been solved, including the tools mentioned above, and then explain why we need standardized metadata in order to achieve the vision of seamless model integration. A new standard called the CSDMS Standard Names that is being developed for the Community Surface Dynamics Modeling System (CSDMS) project to address this problem will also be introduced.

Peckham, S. D.

2012-12-01

258

Simulations of a hydrological model as coupled to a regional climate model  

NASA Astrophysics Data System (ADS)

Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltration, is constructed and incorporated into the land surface scheme BATS. Via the coupled-model (i.e., a regional climate model) simulations, the following major conclusions are obtained: the simulation of surface hydrology is sensitive to the inclusion of heterogeneities in precipitation and infiltration; the runoff ratio is increased after considering the infiltration heterogeneity, a result which is more consistent with the observations of surface moisture balance over humid areas; the introduction of the parameterization of infiltration heterogeneity can have a greater influence on the regional hydro-climatology than the precipitation heterogeneity; and the consideration of the impermeable fraction for the region reveals some features that are closer to the trend of aridification over northern China.

Xinmin, Zeng; Ming, Zhao; Bingkai, Su; Jianping, Tang; Yiqun, Zheng; Qijun, Gui; Zugang, Zhou

2003-06-01

259

Simulations of a hydrological model as coupled to a regional climate model  

NASA Astrophysics Data System (ADS)

Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltration, is constructed and incorporated into the land surface scheme BATS. Via the coupled-model (i.e., a regional climate model) simulations, the following major conclusions are obtained: the simulation of surface hydrology is sensitive to the inclusion of heterogeneities in precipitation and infiltration; the runoff ratio is increased after considering the infiltration heterogeneity, a result which is more consistent with the observations of surface moisture balance over humid areas; the introduction of the parameterization of infiltration heterogeneity can have a greater influence on the regional hydro-climatology than the precipitation heterogeneity; and the consideration of the impermeable fraction for the region reveals some features that are closer to the trend of aridification over northern China.

Zeng, X. M.; Zhao, M.; Su, B. K.; Tang, J. P.; Zheng, Y. Q.; Gui, Q. J.; Zhou, Z. G.

2003-03-01

260

A METHODOLOGY FOR ESTIMATING UNCERTAINTY OF A DISTRIBUTED HYDROLOGIC MODEL: APPLICATION TO POCONO CREEK WATERSHED  

EPA Science Inventory

Utility of distributed hydrologic and water quality models for watershed management and sustainability studies should be accompanied by rigorous model uncertainty analysis. However, the use of complex watershed models primarily follows the traditional {calibrate/validate/predict}...

261

HBV mutations in untreated HIV-HBV co-infection using genomic length sequencing  

PubMed Central

HIV infection has a significant impact on the natural progression of hepatitis B virus (HBV) related liver disease. In HIV-HBV co-infected patients, little is known about mutations in the HBV genome, which can influence severity of liver disease. The aim of this study was to characterize and to determine the frequency of known clinically-significant mutations in the HBV genomes from HIV-HBV co-infected patients and from HBV mono-infected patients. To accomplish this, genomic length HBV sequencing was performed in highly-active anti-retroviral therapy (HAART) –naïve HIV-HBV co-infected patients (n= 74) and in anti-HBV therapy-naïve HBV mono-infected patients (n=55). The frequency of HBV mutations differed between the co-infected and mono-infected patients when comparing patients with the same genotype. BCP mutations A1762T and G1764A were significantly more frequent in HBV genotype C mono-infection and the ?1G frameshift was significantly more frequent in co- infection and was only observed in HBV genotype A co-infection. PreS2 deletions were observed more frequently in the setting of co-infection. Further work is needed to determine if these mutational patterns influence the differences in liver disease progression in HIV-HBV co-infected and HBV mono-infected patients.

Audsley, Jennifer; Littlejohn, Margaret; Yuen, Lilly; Sasadeusz, Joe; Ayres, Anna; Desmond, Christopher; Spelman, Tim; Lau, George; Matthews, Gail V.; Avihingsanon, Anchalee; Seaberg, Eric; Philp, Frances; Saulynas, Melissa; Ruxrungtham, Kiat; Dore, Gregory J.; Locarnini, Stephen A.; Thio, Chloe L.; Lewin, Sharon R.; Revill, Peter A.

2010-01-01

262

Integrating an open source dynamic river model in hydrology modeling frameworks  

NASA Astrophysics Data System (ADS)

A challenge for hydrology modeling is linking landscape runoff models with river network models. Although some hydrological models directly implement a river routing scheme within their code, such a monolithic approach is too rigid because it does not allow the latest river routing advances to be used. Unlike the 2D interface between atmospheric and landscape models, the interface between landscape runoff models and river network models is more difficult to define. In this PICO presentation, we address problems with model interfaces, which are related to issues such as time and space-scale differences between the models. We also provide an overview of SPRINT, an open source river network model, which has adapted the model interface architecture and numerical methods widely used in semiconductor microchip design. Finally, we propose two model integration mechanisms: the file-based "net-list" and the API (application programming interface) approach.

Liu, Frank; Hodges, Ben

2014-05-01

263

Multi-period calibration of a semi-distributed hydrological model based on hydroclimatic clustering  

NASA Astrophysics Data System (ADS)

Changing climatic conditions contribute to a time varying nature of hydrological responses over different temporal scales. The temporal dynamics of hydrological systems bring uncertainties into hydrological simulation which are different to uncertainties from spatial heterogeneity of soil and land use. This study develops a new approach to improve the calibration of hydrological based on hydroclimatic similarities. Six climatic indexes are integrated using Principal Component Analysis and Fuzzy C-mean Clustering methods to transform hydrological years into hydroclimatic periods. Parameter sets of SWAT model are calibrated independently for each period and used together to generate continuous simulation for a prairie watershed in southern Canada. Results indicate that the multi-period model exhibits comprehensive advantages over the traditional single-period model under various flow conditions. The simulation ability of the model is improved through using period-specific parameter sets in fitting the observations to compensate for deficiencies in the model structure or input data.

Zhang, Hua; Huang, Guo H.; Wang, Dunling; Zhang, Xiaodong

2011-10-01

264

Effects of soil parameterization on distributed hydrologic response: Testing a distributed hydrologic model using a hypothetical reality dataset  

NASA Astrophysics Data System (ADS)

Hydrologic data scarcity and discrepancies between model scale and point measurements are often identified as the most important limitations in evaluating distributed hydrologic models. To overcome data limitation issues, we present a framework for testing and evaluating distributed hydrologic models at the catchment scale using a hypothetical reality (HR) dataset. The HR is a synthetically generated dataset using the finite element 3D fully coupled surface-subsurface Integrated Hydrology Model (VanderKwaak, 1999) that emulates the hydrologic behavior of the real Tarrawarra catchment located in southeastern Australia. The long term HR dataset is composed of continuous outflow hydrograph and internal states at 55 observation nodes for an 11-year period as well as daily snapshots of the internal states at all nodes during the six months wet period of each year. A test model, MODHMS (HydroGeoLogic, Inc, 2000, Panday and Huyakorn, 2004), is used against the HR to illustrate the framework flexibility and functionality. We use examples from the long-term simulations to show the effects of the shape of the soil moisture retention curve and saturated hydraulic conductivity Ksat on both the integrated and distributed MODHMS hydrologic responses. We consider three base cases where we use class average van Genuchten parameters from the ROSETTA database (Schaap et al., 2001) for three soil types: clay loam, loamy sand and silty clay and one common Ksat value that is within one standard deviation interval of all three classes. For each of the three base cases we then vary Ksat sequentially to the one standard deviation interval limits for each class, according to ROSETTA, to illustrate the effects of Ksat variability for the same soil water retention curve. We examine a wet period and a dry period and discuss the range of simulated hydrographs and soil moisture states that result from different MODHMS soil parameterizations, as compared with the HR. We show soil moisture patterns in the top 2cm of soil during the wet and dry periods and illustrate the variability of surface runoff production in MODHMS for the range of parameters used.

Cristea, N. C.; Kampf, S. K.; Mirus, B. B.; Loague, K.; Burges, S. J.

2010-12-01

265

Bayesian analysis of data and model error in rainfall-runoff hydrological models  

NASA Astrophysics Data System (ADS)

A major unresolved issue in the identification and use of conceptual hydrologic models is realistic description of uncertainty in the data and model structure. In particular, hydrologic parameters often cannot be measured directly and must be inferred (calibrated) from observed forcing/response data (typically, rainfall and runoff). However, rainfall varies significantly in space and time, yet is often estimated from sparse gauge networks. Recent work showed that current calibration methods (e.g., standard least squares, multi-objective calibration, generalized likelihood uncertainty estimation) ignore forcing uncertainty and assume that the rainfall is known exactly. Consequently, they can yield strongly biased and misleading parameter estimates. This deficiency confounds attempts to reliably test model hypotheses, to generalize results across catchments (the regionalization problem) and to quantify predictive uncertainty when the hydrologic model is extrapolated. This paper continues the development of a Bayesian total error analysis (BATEA) methodology for the calibration and identification of hydrologic models, which explicitly incorporates the uncertainty in both the forcing and response data, and allows systematic model comparison based on residual model errors and formal Bayesian hypothesis testing (e.g., using Bayes factors). BATEA is based on explicit stochastic models for both forcing and response uncertainty, whereas current techniques focus solely on response errors. Hence, unlike existing methods, the BATEA parameter equations directly reflect the modeler's confidence in all the data. We compare several approaches to approximating the parameter distributions: a) full Markov Chain Monte Carlo methods and b) simplified approaches based on linear approximations. Studies using synthetic and real data from the US and Australia show that BATEA systematically reduces the parameter bias, leads to more meaningful model fits and allows model comparison taking into account forcing uncertainty. The full MCMC approach also yields estimates of the true forcing (conditioned on the model assumptions), which can be used to improve data collection. We expect the ability to meaningfully disaggregate sources of uncertainty to be of significant benefit in hydrology and environmental modeling in general.

Kavetski, D.; Franks, S. W.; Kuczera, G.

2004-12-01

266

Soil hydrologic characterization for modeling large scale soil remediation protocols  

NASA Astrophysics Data System (ADS)

In Campania Region (Italy), the Ministry of Environment identified a National Interest Priority Sites (NIPS) with a surface of about 200,000 ha, characterized by different levels and sources of pollution. This area, called Litorale Domitio-Agro Aversano includes some polluted agricultural land, belonging to more than 61 municipalities in the Naples and Caserta provinces. In this area, a high level spotted soil contamination is moreover due to the legal and outlaw industrial and municipal wastes dumping, with hazardous consequences also on the quality of the water table. The EU-Life+ project ECOREMED (Implementation of eco-compatible protocols for agricultural soil remediation in Litorale Domizio-Agro Aversano NIPS) has the major aim of defining an operating protocol for agriculture-based bioremediation of contaminated agricultural soils, also including the use of crops extracting pollutants to be used as biomasses for renewable energy production. In the framework of this project, soil hydrologic characterization plays a key role and modeling water flow and solute transport has two main challenging points on which we focus on. A first question is related to the fate of contaminants infiltrated from stormwater runoff and the potential for groundwater contamination. Another question is the quantification of fluxes and spatial extent of root water uptake by the plant species employed to extract pollutants in the uppermost soil horizons. Given the high variability of spatial distribution of pollutants, we use soil characterization at different scales, from field scale when facing root water uptake process, to regional scale when simulating interaction between soil hydrology and groundwater fluxes.

Romano, Nunzio; Palladino, Mario; Di Fiore, Paola; Sica, Benedetto; Speranza, Giuseppe

2014-05-01

267

Building Community Around Hydrologic Data Models Within CUAHSI  

Microsoft Academic Search

The Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI) has a Hydrologic Information Systems project which aims to provide better data access and capacity for data synthesis for the nation's water information, both that collected by academic investigators and that collected by water agencies. These data include observations of streamflow, water quality, groundwater levels, weather and climate

D. Maidment

2007-01-01

268

Disinformative data in large-scale hydrological modelling  

NASA Astrophysics Data System (ADS)

Large-scale hydrological modelling has become an important tool for the study of global and regional water resources, climate impacts, and water-resources management. However, modelling efforts over large spatial domains are fraught with problems of data scarcity, uncertainties and inconsistencies between model forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aimed at identifying data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. The consistency between (i) basin areas for different hydrographic datasets, and (ii) between climate data (precipitation and potential evaporation) and discharge data, was examined in terms of how well basin areas were represented in the flow networks and the possibility of water-balance closure. It was found that (i) most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between flow-network datasets and archived basin areas, (ii) basins exhibiting too-high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and (iii) the occurrence of basins exhibiting losses exceeding the potential-evaporation limit was strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. Some inconsistencies may be resolved by considering sub-grid variability in climate data, surface-dependent potential-evaporation estimates, etc., but further studies are needed to determine the reasons for the inconsistencies found. Our results emphasise the need for pre-modelling data analysis to identify dataset inconsistencies as an important first step in any large-scale study. Applying data-screening methods before modelling should also increase our chances to draw robust conclusions from subsequent model simulations.

Kauffeldt, A.; Halldin, S.; Rodhe, A.; Xu, C.-Y.; Westerberg, I. K.

2013-07-01

269

Stable Isotope Tracers in Large Scale Hydrological Models  

NASA Astrophysics Data System (ADS)

Stable isotopes of oxygen and hydrogen (deuterium and oxygen-18) have been shown to be effective tracers for characterizing hydrological processes in small river basins. Their application in large river basins has lagged behind due to the lack of sufficient isotope data. Recent availability of isotope data from most US rivers and subsequent efforts by the International Atomic Energy Agency (IAEA) to collect comprehensive global information on isotope compositions of river runoff is changing this situation. These data sets offer new opportunities to utilize stable isotopes in studies of large river basins. Recent work carried out jointly by the Water Systems Analysis Group of the University of New Hampshire and the Isotope Hydrology Section of the IAEA applied isotope-enabled global water balance and transport models to assess the feasibility of using isotope data for improving water balance estimations at large scales. The model implemented simple mixing in the various storage pools (e.g. snow pack, soil moisture, groundwater, and river channel) and fractionation during evapotranspiration. Sensitivity tests show that spatial and temporal distributions of isotopes in precipitation and their mixing in the various storage pools are the most important factors affecting the isotopic composition of river discharge. The groundwater storage pool plays a key role in the seasonal dynamics of stable isotope composition of river discharge. Fractionation during phase changes appears to have a less pronounced impact. These findings are consistent with those in small scale catchments where ``old water'' and ``new water'' (i.e. pre-event water and storm runoff) can be easily separated by using isotopes. Model validation using available data from the US rivers showed remarkable performance considering the inconsistencies in the temporal sampling of precipitation and runoff isotope composition records. The good model performance suggests that seasonal variations of the isotopic composition of the precipitation and as a consequence the runoff follow a regular pattern that is less affected by inter-annual variations. The presentation will discuss the design and implementation of the isotope enabled water balance/transport model, its application and the potential of using global isotope information as (``soft'') calibration/validation data. Because of the sensitivity of runoff isotopic composition to groundwater storage pools, isotope data may offer new opportunities to assess the volumes of these storage terms and to evaluate their sustainability for human use.

Fekete, B. M.; Aggarwal, P.

2004-05-01

270

Distributed hydrological modelling in California semi-arid shrublands: MIKE SHE model calibration and uncertainty estimation  

Microsoft Academic Search

The Generalized Likelihood Uncertainty Estimation (GLUE) methodology is used for model calibration, testing and predictive uncertainty estimation in the application of the MIKE SHE hydrologic model for estimating monthly streamflow in a semi-arid shrubland (chaparral) catchment in central California. Monte Carlo simulation is used to randomly generate one thousand parameter sets for a 20-year calibration period encompassing variable climatic and

Christine E. McMichael; Allen S. Hope; Hugo A. Loaiciga

2006-01-01

271

HYDROLOGY AND SEDIMENT MODELING USING THE BASINS NON-POINT SOURCE MODEL  

EPA Science Inventory

The Non-Point Source Model (Hydrologic Simulation Program-Fortran, or HSPF) within the EPA Office of Water's BASINS watershed modeling system was used to simulate streamflow and total suspended solids within Contentnea Creek, North Carolina, which is a tributary of the Neuse Rive...

272

A global hydrological model for deriving water availability indicators: model tuning and validation  

Microsoft Academic Search

Freshwater availability has been recognized as a global issue, and its consistent quantification not only in individual river basins but also at the global scale is required to support the sustainable use of water. The WaterGAP Global Hydrology Model WGHM, which is a submodel of the global water use and availability model WaterGAP 2, computes surface runoff, groundwater recharge and

Petra Döll; Frank Kaspar; Bernhard Lehner

2003-01-01

273

Satellite Remote Sensing and Hydrological Modeling for Flood Inundation Mapping in Lake Victoria Basin: Implications for Hydrologic Prediction in Ungauged Basins  

NASA Astrophysics Data System (ADS)

Floods are among the most catastrophic natural disasters around the globe impacting human lives and infrastructure. Implementation of a flood prediction system can potentially reduce these losses. Typically, the set up and calibration of a hydrologic model requires in situ observations (e.g. rain gauges and stream gauges). Satellite remote sensing data have emerged as viable alternatives or supplements to in situ observations due to their coverage over ungauged regions. The focus of this study is to utilize the best available satellite products and integrate them in a state-of-the-art hydrologic model to characterize the spatial extent of flooding and associated hazards over sparsely-gauged or ungauged basins. This study presents a methodology based entirely on satellite remote sensing data to calibrate a hydrologic model, simulate the spatial extent of flooding, and evaluate the probability of detecting inundated areas. A raster-based distributed hydrologic model, CREST, was implemented for the Nzoia basin, a sub-basin of Lake Victoria (Africa). MODIS- and ASTER-based flood inundation maps were retrieved over the region and used to benchmark the distributed hydrologic model simulations of streamflow and inundation areas. The analysis showed the applicability of integrating satellite data products as input for a distributed hydrological model as well as direct estimation of flood extent maps. The quantification of flooding spatial extent through orbital sensors can help to evaluate hydrologic models and hence potentially improve hydrologic prediction and flood management strategies in ungauged catchments.

Khan, S. I.; Hong, Y.; Wang, J.; Yilmaz, K. K.; Gourley, J. J.; Adler, R. F.; Brakenridge, G. R.; Policelli, F.; Habib, S.; Irwin, D.

2009-12-01

274

Significance of hydrological model choice and land use changes when doing climate change impact assessment  

NASA Astrophysics Data System (ADS)

Uncertainty in impact studies arises both from Global Climate Models (GCM), emission projections, statistical downscaling, Regional Climate Models (RCM), hydrological models and calibration techniques (Refsgaard et al. 2013). Some of these uncertainties have been evaluated several times in the literature; however few studies have investigated the effect of hydrological model choice on the assessment results (Boorman & Sefton 1997; Jiang et al. 2007; Bastola et al. 2011). These studies have found that model choice results in large differences, up to 70%, in the predicted discharge changes depending on the climate input. The objective of the study is to investigate the impact of climate change on hydrology of the Odense catchment, Denmark both in response to (a) different climate projections (GCM-RCM combinations); (b) different hydrological models and (c) different land use scenarios. This includes: 1. Separation of the climate model signal; the hydrological model signal and the land use signal 2. How do the different hydrological components react under different climate and land use conditions for the different models 3. What land use scenario seems to provide the best adaptation for the challenges of the different future climate change scenarios from a hydrological perspective? Four climate models from the ENSEMBLES project (Hewitt & Griggs 2004): ECHAM5 - HIRHAM5, ECHAM5 - RCA3, ARPEGE - RM5.1 and HadCM3 - HadRM3 are used, assessing the climate change impact in three periods: 1991-2010 (present), 2041-2060 (near future) and 2081-2100 (far future). The four climate models are used in combination with three hydrological models with different conceptual layout: NAM, SWAT and MIKE SHE. Bastola, S., C. Murphy and J. Sweeney (2011). "The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments." Advances in Water Resources 34: 562-576. Boorman, D. B. and C. E. M. Sefton (1997). "Recognising the uncertainty in the quantification of the effects of climate change on hydrological response." Climate Change 35: 415-434. Hewitt, C. D. and D. J. Griggs (2004). "Ensembles-based predictions of climate changes and their impacts." Eos, Transactions American Geophysical Union 85: 1-566. Jiang, T., Y. D. Chen, C. Xu, X. Chen, X. Chen and V. P. Singh (2007). "Comparison of hydrological impacts of climate change simulated by six hydrological models in the Dongjiang Basin, South China." Journal of hydrology 336: 316-333. Refsgaard, J. C., K. Arnbjerg-Nielsen, M. Drews, K. Halsnæs, E. Jeppesen, H. Madsen, A. Markandya, J. E. Olesen, J. R. Porter and J. H. Christensen (2013). "The role of uncertainty in climate change adaptation strategies - A Danish water management example." Mitigation and Adaptation Strategies for Global Change 18: 337-359.

Bjørnholt Karlsson, Ida; Obel Sonnenborg, Torben; Refsgaard, Jens Christian; Høgh Jensen, Karsten

2014-05-01

275

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs  

SciTech Connect

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregation (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the ?-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.

Wood, Andrew W.; Leung, Lai R.; Sridhar, V.; Lettenmaier, D. P.

2004-01-01

276

Niger River Basin - Hydrological Modeling: Inter-changeability of parameters between models versions  

NASA Astrophysics Data System (ADS)

An enhanced hydrological framework from the existing conceptual model GR2M leads to significant results in inter-changing the models parameters, using the parameters obtained during the calibration process of a first model version in the validation process of a second model version. A two parameters and three input variables' conceptual framework called SimulHyd is used to simulate the runoff of sixteen watersheds on the Niger River and its tributaries, over eighteen years to forty six years. The first parameter controls the three model input variables and the second controls its output runoff information. Between either a lumped version and a semi-distributed version or the GR2M model and SimulHyd model, a set of three significant models parameters inter-changeability are detected: SimulHyd is better in validation process after 1970 using the calibrated parameters from GR2M before 1970, in forward modeling; GR2M is better in validation process before 1970 using the calibrated parameters from SimulHyd after 1970; and in some cases the models are more efficient in validation than in calibration. The combination both of two hydrological models drifting one of the other and of two concepts of modeling are used to demonstrate a success in the synergy of four models versions to simulate more accurately the behaviors of hydrological systems. This particularity (of these models version), responding positively in models parameters importing and exporting between different models versions, can be explored in the context of the assessment of climate change impact on water resources.INTER-CHANGED PARAMETERS NON-DISTRIBUTED MODELING VS SEMI-DISTRIBUTED MODELING SimulHyd (Simulation of hydrological Systems)N-D : Non-Distributed modelingS-D : Semi-Distributed modeling

KONE, S.

2013-12-01

277

Application of Multi-Model Superensemble technique to flood forecasting through distributed hydrologic models  

NASA Astrophysics Data System (ADS)

Streamflow forecasts are generally produced through the use of a single hydrologic model. In spite of the existence of a wide range of hydrologic models, it is hard to claim that any single model among them performs better than the rest, for all type of watersheds under all conditions. This is because hydrologic models, lumped or distributed, introduce many assumptions and simplifications in their structure. Since various model structures capture different aspects of the watershed processes, one way of exploiting the strength of different models and compensating for their weaknesses is to obtain consensus predictions by combining their results using model combination techniques such as Multi Model SuperEnsmble (MMSE). MMSE is a special case of ensemble techniques, which consider the model outputs as ensemble members. This study surveys the performance of MMSE for flood forecasting by using the simulation results from various distributed models participated in the Distributed Model Intercomparison Project (DMIP), an international project sponsored by National Weather Service. The key questions addressed in this study are: (1) What is the skill level of the consensus forecast compared to those of individual forecasts? (2) How many models do we need to produce accurate consensus forecasts? (3) Can model combination techniques compensate for the inadequacy of model calibration? Simulations for the Illinois River Basin at Watts from 7 uncalibrated DMIP models are combined and the results are compared to the calibrated model results.

Ajami, N. K.; Duan, Q.; Gao, X.; Sorooshian, S.

2004-12-01

278

Flexible automated parameterization of hydrologic models using fuzzy logic  

NASA Astrophysics Data System (ADS)

Recent developments in model calibration suggest that information obtained from calibration is inherently uncertain in nature. Therefore identification of optimum parameter values is often highly nonspecific. A calibration framework using fuzzy logic is presented to deal with such uncertain information. An application of this technique to calibrate the streamflow of a hydrologic submodel embedded within an ecosystem simulation model demonstrates that objective estimates of parameter values and the range of model output associated with a failure to identify a unique solution can be obtained with suitable choices of objective functions. An iterative refinement in parameter estimates through a process of elimination was possible by incorporating multiple objective functions in calibration, thereby reducing the range of parameter values that capture the streamflow response. It is shown that objective function tradeoffs can lead to suboptimal solutions using the process of elimination without an automated procedure for reevaluation. Owing to its computational simplicity and flexibility this framework could be extended into a nonmonotonic system for automated parameter estimation.

Samanta, Sudeep; Mackay, D. Scott

2003-01-01

279

Regional scale hydrology with a new land surface processes model  

NASA Technical Reports Server (NTRS)

Through the CaPE Hydrometeorology Project, we have developed an understanding of some of the unique data quality issues involved in assimilating data of disparate types for regional-scale hydrologic modeling within a GIS framework. Among others, the issues addressed here include the development of adequate validation of the surface water budget, implementation of the STATSGO soil data set, and implementation of a remote sensing-derived landcover data set to account for surface heterogeneity. A model of land surface processes has been developed and used in studies of the sensitivity of surface fluxes and runoff to soil and landcover characterization. Results of these experiments have raised many questions about how to treat the scale-dependence of land surface-atmosphere interactions on spatial and temporal variability. In light of these questions, additional modifications are being considered for the Marshall Land Surface Processes Model. It is anticipated that these techniques can be tested and applied in conjunction with GCIP activities over regional scales.

Laymon, Charles; Crosson, William

1995-01-01

280

Modeling low impact development potential with hydrological response units.  

PubMed

Evaluations of benefits of implementing low impact development (LID) stormwater management techniques can extend up to a watershed scale. This presents a challenge for representing them in watershed models, since they are typically orders of magnitude smaller in size. This paper presents an approach that is focused on trying to evaluate the benefits of implementing LIDs on a lot level. The methodology uses the concept of urban hydrological response Unit and results in developing and applying performance curves that are a function of lot properties to estimate the potential benefit of large-scale LID implementation. Lot properties are determined using a municipal geographic information system database and processed to determine groups of lots with similar properties. A representative lot from each group is modeled over a typical rainfall year using USEPA Stormwater Management Model to develop performance functions that relate the lot properties and the change in annual runoff volume and corresponding phosphorus loading with different LIDs implemented. The results of applying performance functions on all urban areas provide the potential locations, benefit and cost of implementation of all LID techniques, guiding future decisions for LID implementation by watershed area municipalities. PMID:24334886

Eric, Marija; Fan, Celia; Joksimovic, Darko; Li, James Y

2013-01-01

281

Quantile hydrologic model selection and model structure deficiency assessment: 2. Applications  

NASA Astrophysics Data System (ADS)

Quantile hydrologic model selection and structure deficiency assessment is applied in three case studies. The performance of quantile model selection problem is rigorously evaluated using a model structure on the French Broad river basin data set. The case study shows that quantile model selection encompasses model selection strategies based on summary statistics and that it is equivalent to maximum likelihood estimation under certain likelihood functions. It also shows that quantile model predictions are fairly robust. The second case study is of a parsimonious hydrological model for dry land areas in Western India. The case study shows that an intuitive improvement in the model structure leads to reductions in asymmetric loss function values for all considered quantiles. The asymmetric loss function is a quantile specific metric that is minimized to obtain a quantile specific prediction model. The case study provides evidence that a quantile-wise reduction in the asymmetric loss function is a robust indicator of model structure improvement. Finally a case study of modeling daily streamflow for the Guadalupe River basin is presented. A model structure that is least deficient for the study area is identified from nine different model structures based on quantile structural deficiency assessment. The nine model structures differ in interception, routing, overland flow and base flow conceptualizations. The three case studies suggest that quantile model selection and deficiency assessment provides a robust mechanism to compare deficiencies of different model structures and helps to identify better model structures. In addition to its novelty, quantile hydrologic model selection is a frequentist approach that seeks to complement existing Bayesian approaches to hydrological model uncertainty.

Pande, Saket

2013-09-01

282

Definition of Hydrologic Response Units in Depression Plagued Digital Elevation Models  

Microsoft Academic Search

Definition of hydrologic response units using digital elevation models (DEMs) is sensitive to the occurrence of topographic depressions. Real depressions can be important to the hydrology and biogeochemistry a catchment, often coinciding with areas of surface saturation. Artifact depressions, in contrast, result in digital \\

J. B. Lindsay; I. F. Creed

2002-01-01

283

Is the groundwater reservoir linear? Learning from data in hydrological modelling  

Microsoft Academic Search

Although catchment behaviour during recession periods appears to be better identifiable than in other periods, the representation of hydrograph recession is often weak in hydrological simulations. Reason lies in the various sources of uncertainty that affect hydrological simulations, and in particular in the inherent uncertainty concerning model conceptualizations, when they are based on an a-priori representation of the natural system.

F. Fenicia; H. H. G. Savenije; P. Matgen; L. Pfister

2005-01-01

284

Operational Hydrologic Simulation Modeling at the Natural Resources Conservation Service's National Water and Climate Center  

Microsoft Academic Search

This paper describes the current status and anticipated near-term future directions of the U.S. Department of Agriculture's Natural Resources Conservation Service's (NRCS) National Water and Climate Center with respect to the use of hydrologic simulation models. It begins with a description of the water supply forecasting operations, and continues with a review of past attempts to adopt operational hydrologic simulation

Thomas Pagano; Tom Perkins; Jennifer Erxleben

285

New Mexico Climate and Hydrology: is the Historic Record Valid for Predictive Modeling?  

Microsoft Academic Search

In using measured stream-flow to assess water supply or to drive hydrologic models, hydrologists assume that the stream-flow record used is representative of present and future hydrologic conditions. However, in regions like the arid southwest where stream flow is highly variable from year to year and strongly affected by climate forcing like El Nino, assuming the record is representative without

Karen Lewis; Deborah Hathaway; S. S. Papadopulos

286

Land Surface Hydrology Parameterization for Atmospheric General Circulation models Including Subgrid Scale Spatial Variability  

Microsoft Academic Search

Parameterizations are developed for the representation of subgrid hydrologic processes in atmospheric general circulation models. Reasonable a priori probability density functions of the spatial variability of soil moisture and of precipitation are introduced. These are used in conjunction with the deterministic equations describing basic soil moisture physics to derive expressions for the hydrologic processes that include subgrid scale variation in

D. Entekhabi; P. S. Eagleson

1989-01-01

287

Hydrologic modeling to screen potential environmental management methods for malaria vector control in Niger  

Microsoft Academic Search

This paper describes the first use of Hydrology-Entomology and Malaria Transmission Simulator (HYDREMATS), a physically based distributed hydrology model, to investigate environmental management methods for malaria vector control in the Sahelian village of Banizoumbou, Niger. The investigation showed that leveling of topographic depressions where temporary breeding habitats form during the rainy season, by altering pool basin microtopography, could reduce the

Rebecca L. Gianotti; Arne Bomblies; Elfatih A. B. Eltahir

2009-01-01

288

Hydrologic Response of a Wetland to Changing Moisture Conditions: Modeling Effects of Soil Heterogeneity  

Microsoft Academic Search

Prediction of the effects of external influences such as climate change on wetland systems requires the prediction of hydrologic effects. Because wetland soils are typically heterogeneous, it is particularly important to understand the extent and connectedness of hydraulically conductive soil units, since water flow may be concentrated in such units while bypassing others of lower conductivity. However, subsurface hydrologic models

Peter J. Zeeb; Harold F. Hemond

1998-01-01

289

Land surface modelling in hydrology and meteorology - lessons learned from the Baltic Basin  

NASA Astrophysics Data System (ADS)

By both tradition and purpose, the land parameterization schemes of hydrological and meteorological models differ greatly. Meteorologists are concerned primarily with solving the energy balance, whereas hydrologists are most interested in the water balance. Meteorological climate models typically have multi-layered soil parameterisation that solves temperature fluxes numerically with diffusive equations. The same approach is carried over to a similar treatment of water transport. Hydrological models are not usually so interested in soil temperatures, but must provide a reasonable representation of soil moisture to get runoff right. To treat the heterogeneity of the soil, many hydrological models use only one layer with a statistical representation of soil variability. Such a hydrological model can be used on large scales while taking subgrid variability into account. Hydrological models also include lateral transport of water - an imperative if' river discharge is to be estimated. The concept of a complexity chain for coupled modelling systems is introduced, together with considerations for mixing model components. Under BALTEX (Baltic Sea Experiment) and SWECLIM (Swedish Regional Climate Modelling Programme), a large-scale hydrological model of runoff in the Baltic Basin is used to review atmospheric climate model simulations. This incorporates both the runoff record and hydrological modelling experience into atmospheric model development. Results from two models are shown. A conclusion is that the key to improved models may be less complexity. Perhaps the meteorological models should keep their multi-layered approach for modelling soil temperature, but add a simpler, yet physically consistent, hydrological approach for modelling snow processes and water transport in the soil.

Graham, L. P.; Bergström, S.

290

Impact of modellers' decisions on hydrological a priori predictions  

NASA Astrophysics Data System (ADS)

In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of added information. In this qualitative analysis of a statistically small number of predictions we learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements.

Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

2014-06-01

291

Integrating fire with hydrological projections: model evaluation to identify uncertainties and tradeoffs in model complexity  

NASA Astrophysics Data System (ADS)

It is imperative for resource managers to understand how a changing climate might modify future watershed and hydrological processes, and such an understanding is incomplete if disturbances such as fire are not integrated with hydrological projections. Can a robust fire spread model be developed that approximates patterns of fire spread in response to varying topography wind patterns, and fuel loads and moistures, without requiring intensive calibration to each new study area or time frame? We assessed the performance of a stochastic model of fire spread (WMFire), integrated with the Regional Hydro-Ecological Simulation System (RHESSys), for projecting the effects of climatic change on mountain watersheds. We first use Monte Carlo inference to determine that the fire spread model is able to replicate the spatial pattern of fire spread for a contemporary wildfire in Washington State (the Tripod fire), measured by the lacunarity and fractal dimension of the fire. We then integrate a version of WMFire able to replicate the contemporary wildfire with RHESSys and simulate a New Mexico watershed over the calibration period of RHESSys (1941-1997). In comparing the fire spread model to a single contemporary wildfire we found issues in parameter identifiability for several of the nine parameters, due to model input uncertainty and insensitivity of the mathematical function to certain ranges of the parameter values. Model input uncertainty is caused by the inherent difficulty in reconstructing fuel loads and fuel moistures for a fire event after the fire has occurred, as well as by issues in translating variables relevant to hydrological processes produced by the hydrological model to those known to affect fire spread and fire severity. The first stage in the model evaluation aided the improvement of the model in both of these regards. In transporting the model to a new landscape in order to evaluate fire regimes in addition to patterns of fire spread, we find reasonable outcomes with respect to both. This two-stage model evaluation against multiple criteria and for more than one landscape demonstrates that a relatively simple model of fire spread can be sufficiently robust to simulate fire regimes for varying ecosystems and time periods. A careful model evaluation allows for identification of model uncertainties, which are then reduced by improvements to model structure. When integrating a fire spread model with a hydrological model for watershed projections it is insufficient to determine the adequacy of the fire spread module independently of the hydrological model. The integration of the two models should be assessed as vigorously as the individual modules.

Kennedy, M.; McKenzie, D.

2013-12-01

292

PREDICTIVE UNCERTAINTY IN HYDROLOGIC AND WATER QUALITY MODELING: APPROACHES, APPLICATION TO ENVIRONMENTAL MANAGEMENT, AND FUTURE CHALLENGES  

EPA Science Inventory

Extant process-based hydrologic and water quality models are indispensable to water resources planning and environmental management. However, models are only approximations of real systems and often calibrated with incomplete and uncertain data. Reliable estimates, or perhaps f...

293

Coupling Hydrological Processes with the TRIPLEX Modeling System. Part I: Model Implementation and Sensitivity Analysis  

NASA Astrophysics Data System (ADS)

Understanding the carbon dynamics of the boreal forests often relies on the understanding the hydrological processes. The TRIPLEX Model incorporates several fundamental submodels that describe the water, nutrients and plant biomass relationships in forest ecosystems. To simulate hydrological processes, water balance and their interactions with carbon dynamics is a desirable step in designing projects in or near forested wetlands by using the TRIPLEX model. The purpose of this research was to develop a submodel for the TRIPLEX1.0 model system to simulate hydrological processes, hydroperiods and wetland interactions with aquifers. This submodel is capable of simulating flow routing, export and import of water, and evapotranspiration from forested wetlands for different hydroperiods. The model calculates a water balance based on precipitation, snowmelt, evaporation and transpiration from the forest canopy, evaporation from the understory and soil, surface runoff, water infiltration, diffusion, bypass flow, drainage and subsurface flow on a daily time-step. The ground water flow model was used to reproduce the surface water flow process through wetlands, and then to estimate new flow rates and values. The results are used to explore the interaction between water table positions, vertical soil moisture fluxes using by TRIPLEX to simulate carbon dynamics. The response and sensitivity of hydrology and soil carbon predictions to changes in model inputs, using both univariate and simultaneous changes in multivariable were examined in this study.

Cui, J.; Peng, C.; Zhou, X.; Hua, D.; Dang, Q.

2004-05-01

294

Statistical procedures for evaluating daily and monthly hydrologic model predictions  

USGS Publications Warehouse

The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

Coffey, M. E.; Workman, S. R.; Taraba, J. L.; Fogle, A. W.

2004-01-01

295

Clinical impact of occult HBV infections.  

PubMed

HBV infection in the absence of HBsAg has been a matter of debate for years, but its existence and clinical relevance are now supported by many publications, editorials and reviews. HBV DNA without HBs antigenemia was detected in the following clinical situations: (1) Chronic, presumably viral, hepatitis unrelated to HCV, atypical alcoholic hepatitis and hepatocellular carcinoma (HCC); (2) viral reactivation following immunosuppression; (3) Transmission through transplantation, transfusion or experimental transmission to chimpanzees. Occult HBV infections are not restricted to areas of high HBV endemicity. Indeed, such cases have been described in Western countries including France. It is now established that occult HBV infection among non-HCV patients suffering from chronic hepatitis varies from 20% to 30% in Europe, and in the context of HCV infection it varies from 20% in France up to 80% in Japan. The percentage of occult HBV infections among non A-E cases depends on several parameters: (1) The method of detection, including PCR primer selection; (2) patient recruitment; (3) patients from countries highly endemic for HBV are more likely to develop occult HBV infections; (4) prevalence may also vary depending on the nature of biological material tested, with a higher proportion for liver compared to serum specimen. The mechanisms leading to HCC in occult HBV infection seem similar to those overt cases, patients with low-grade but diagnosable HBV replication that retains its pro-oncogenic properties. During the course of HCV infection, occult HBV infection may worsen liver damage induced by HCV and reduce the response to HCV antiviral treatment. Occult HBV infection is a frequent phenomenon and HBV DNA testing with highly sensitive PCR in the clinical setting is therefore becoming of paramount importance. PMID:16461218

Chemin, I; Trépo, C

2005-12-01

296

Impact of modellers' decisions on hydrological a priori predictions  

NASA Astrophysics Data System (ADS)

The purpose of this paper is to stimulate a re-thinking of how we, the catchment hydrologists, could become reliable forecasters. A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek) without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1) for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments). They did not obtain time series of stream flow, soil moisture or groundwater response. (2) Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3) For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step 1. Here, we detail the modeller's decisions in accounting for the various processes based on what they learned during the field visit (step 2) and add the final outcome of step 3 when the modellers made use of additional data. We document the prediction progress as well as the learning process resulting from the availability of added information. For the 2nd and 3rd step, the progress in prediction quality could be evaluated in relation to individual modelling experience and costs of added information. We learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing), and (iii) that added process understanding can be as efficient as adding data for improving parameters needed to satisfy model requirements.

Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

2013-07-01

297

Accesible hydrological monitoring for better decision making and modelling: a regional initiative in the Andes  

NASA Astrophysics Data System (ADS)

The goal of the Hydrological Monitoring of Andean Ecosystems Initiative is to improve the conservation and management of High-Andean ecosystems by providing information on the hydrological response of these ecosystems and how different land-uses affect their water yield and regulation capacity. The initiative fills a gap left by widespread hydrological modeling exercises that suffer from lack of data, and by glacier monitoring under climate change. The initiative proposes a hydrological monitoring system involving precipitation, discharge and land cover monitoring in paired catchments. The methodology is accessible for non-specialist organizations, and allows for generation of evidence of land use impact on hydrology on the short term (i.e. a few years). Nevertheless, long term monitoring is pursued with the aim of identifying trends in hydrological response (as opposed to trends in climate) under global change. In this way it supports decision making on the preservation of the hydrological services of the catchment. The initiative aims at a high number of paired catchment sites along the Andes, in order to draw regional conclusions and capture variability, and is connected to more detailed hydrological research sites of several Andean universities. We present preliminary results of a dozen of sites from Venezuela to Bolivia, summarized in hydrological performance indicators that were agreed upon among hydrologists, local stakeholders, and water authorities. The success factors, as well as limitations, of the network are discussed.

De Bievre, B.; Célleri, R.; Crespo, P.; Ochoa, B.; Buytaert, W.; Tobón, C.; Villacís, M.; Villazon, M. F.; Llerena, C.; Rodriguez, M.; Viñas, P.

2013-05-01

298

New hydrologic model of fluid migration in deep porous media  

NASA Astrophysics Data System (ADS)

The authors present a new hydrological model of mantle processes that effect on formation of oil-and-gas bearing basins, fault tectonics and thermal convection. Any fluid migration is initially induced by lateral stresses in the crust and lithosphere which result from global geodynamic processes related to the mantle convection. The global processes are further transformed into regional movements in weakness zones. Model of porous media in deep fractured zones and idea of self-oscillation processes in mantle layers and fractured zones of the crust at different depths was used as the basis for developed concept. The content of these notions resides in the fact that there are conditions of dynamic balance in mantle layers originating as a result of combination and alternate actions of compaction and dilatance mechanisms. These mechanisms can be manifested in different combinations and under different conditions as well as can be complemented by other processes influencing on regime of fluid migration. They can act under condition of passive margin, ocean rift and ocean subduction zones as well as in consolidated platform and sheet. Self-oscillation regime, sub vertical direction of fluid flows, anomalously high layer pressure, and high level of anomalies of various geophysical fields are common for them. A certain class of fluid dynamic models describing consolidation of sedimentary basins, free oscillation processes slow and quick (at the final stage) fluid dynamic processes of the evolution of a sedimentary basin in subduction zones is considered for the first time. The last model of quick fluid dynamic processes reflects the process of formation of hydrocarbon deposits in the zones of collision of lithosphere plates. The results of numerical simulation and diagrams reflecting consecutive stages of the gas-fluid dynamic front propagation are assessed of the Pri-Caspian depression as the example. Calculations with this model will simultaneously be carried out for the sedimentary basins of Timan-Pechora region, Barents Sea, Volga-Ural area, etc. Hydrologic model of deep porous media and the idea of self-oscillation processes in fractured layers of the crust at different depths were used as the basis for developed concept. The content of these notions resides in the fact that there are conditions of dynamic balance in fractured layers originating as a result of combination and alternate actions of compaction and dilatance mechanisms. These mechanisms can be manifested in different combinations and under different conditions as well as can be complemented by other processes influencing on regime of fluid migration. They can act under condition of passive margin, rift and subduction zones as well as in consolidated platform and sheet. Self-oscillation regime, sub vertical direction of fluid flows, anomalously high layer pressure, and high level of anomalies of various geophysical fields are common for them. Specific manifestations of these mechanisms can vary in dependence on geological settings and geodynamic situations. In particular, periods of self-oscillations and depths of fractured layers can be various. Orientation of layers can be not only horizontal, but vertical as well, that is, self-oscillations can occur not only in deep porous media, but in faults and impaired fractured zones as well. Predominating vertical fluid migration can be accompanied by horizontal migration along crust waveguide. A set of fluid dynamic models is considered. Mathematical modeling of geodynamic and fluid dynamic processes in these zones seems very promising. Combined consideration of geodynamic and fluid dynamic aspects in a model of lithosphere plates collision enables to understand the influence of P-T conditions and shear deformations on the mechanism of hydrocarbon generation and to look after their migration and to explain these processes, but also to predict some features essential for the search and exploration of hydrocarbon fields in these regions and their classification. In terms of compaction models, multiphase filtration in a

Dmitrievsky, A.; Balanyuk, I.

2009-04-01

299

Test and Sensitivity Analysis of Hydrological Modeling in the Coupled WRF-Urban Modeling System  

NASA Astrophysics Data System (ADS)

Rapid urbanization has emerged as the source of many adverse effects that challenge the environmental sustainability of cities under changing climatic patterns. One essential key to address these challenges is to physically resolve the dynamics of urban-land-atmospheric interactions. To investigate the impact of urbanization on regional climate, physically-based single layer urban canopy model (SLUCM) has been developed and implemented into the Weather Research and Forecasting (WRF) platform. However, due to the lack of realistic representation of urban hydrological processes, simulation of urban climatology by current coupled WRF-SLUCM is inevitably inadequate. Aiming at improving the accuracy of simulations, recently we implemented urban hydrological processes into the model, including (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation over impervious surface, and (4) urban oasis effect. In addition, we couple the green roof system into the model to verify its capacity in alleviating urban heat island effect at regional scale. Driven by different meteorological forcings, offline tests show that the enhanced model is more accurate in predicting turbulent fluxes arising from built terrains. Though the coupled WRF-SLUCM has been extensively tested against various field measurement datasets, accurate input parameter space needs to be specified for good model performance. As realistic measurements of all input parameters to the modeling framework are rarely possible, understanding the model sensitivity to individual parameters is essential to determine the relative importance of parameter uncertainty to model performance. Thus we further use an advanced Monte Carlo approach to quantify relative sensitivity of input parameters of the hydrological model. In particular, performance of two widely used soil hydraulic models, namely the van Genuchten model (based on generic soil physics) and an empirical model (viz. the CHC model currently adopted in WRF-SLUCM) is investigated. Results show that the CHC model requires a much finer time step for numerical stability in hydrological modeling and thus is more computationally expensive in the coupled WRF-SLUCM modeling environment.

Wang, Z.; yang, J.

2013-12-01

300

Modeling Jupiter's atmospheric dynamics with an active hydrological cycle  

NASA Astrophysics Data System (ADS)

An active hydrological cycle has been added to the EPIC general circulation model (GCM) for planetary applications, with a special emphasis on Jupiter. Scientists have suspected for decades that clouds, and in particular latent heating, strongly influence Jupiter's atmospheric dynamics and this research provides a tool to investigate this phenomenon. Components of the model have been adapted for the planetary setting from recently published Earth microphysics schemes. The behavior of the cloud model is investigated in two steps. First, we explore in detail the runtime properties of a nominal model; and second, through sensitivity tests we determine how the full microphysics and selected components of the scheme affect the formation and evolution of clouds and precipitation. Results from our one-dimensional (vertical) simulations match expectations based on thermochemical models about the vertical positioning of ammonia and water clouds, and the nature of precipitation. Using meridional- plane (two-dimensional) simulations, we investigate the latitudinal variation of clouds. We conclude that the zonal-wind structure under the visible cloud deck strongly affects the position of the cloud bases. We describe in detail an equatorial storm system observed in our 2D simulations. We also show that simplification of our microphysics scheme would improperly simulate large scale weather phenomena on Jupiter. We support future laboratory tests and in-situ measurements that would improve the cloud parameterization scheme and would also add more constraints on the global distribution of condensibles and on the zonal wind-structure. The complete computer program resulting from this research can be downloaded as open-source software from NASA's Planetary Data System (PDS) Atmospheres node.

Palotai, Csaba

301

Modeling of Thermal-Hydrological-Chemical Laboratory Experiments  

SciTech Connect

The emplacement of heat-generating nuclear waste in the potential geologic repository at Yucca Mountain, Nevada, will result in enhanced water-rock interaction around the emplacement drifts. Water present in the matrix and fractures of the rock around the drift may vaporize and migrate via fractures to cooler regions where condensation would occur. The condensate would react with the surrounding rock, resulting in mineral dissolution. Mineralized water flowing under gravity back towards the heat zone would boil, depositing the dissolved minerals. Such mineral deposition would reduce porosity and permeability above the repository, thus altering the flow paths of percolating water. The objective of this research is to use coupled thermal-hydrological-chemical (THC) models to simulate previously conducted laboratory experiments involving tuff dissolution and mineral precipitation in a boiling, unsaturated fracture. Numerical simulations of tuff dissolution and fracture plugging were performed using a modified version of the TOUGHREACT code developed at LBNL by T. Xu and K. Pruess. The models consider the transport of heat, water, gas and dissolved constituents, reactions between gas, mineral and aqueous phases, and the coupling of porosity and permeability to mineral dissolution and precipitation. The model dimensions and initial fluid chemistry, rock mineralogy, permeability, and porosity were defined using the experimental conditions. A 1-D plug-flow model was used to simulate dissolution resulting from reaction between deionized water and crushed ash flow tuff. A 2-D model was developed to simulate the flow of mineralized water through a planar fracture within a block of ash flow tuff where boiling conditions led to mineral precipitation. Matrix blocks were assigned zero permeability to confine fluid flow to the fracture, and permeability changes in the fracture were specified using the porosity cubic law relationship.

P. F. Dobson; T. J. Kneafsey; E. L. Sonnenthal; Nicolas Spycher

2001-05-31

302

Pitfalls and improvements in the joint inference of heteroscedasticity and autocorrelation in hydrological model calibration  

NASA Astrophysics Data System (ADS)

Residual errors of hydrological models are usually both heteroscedastic and autocorrelated. However, only a few studies have attempted to explicitly include these two statistical properties into the residual error model and jointly infer them with the hydrological model parameters. This technical note shows that applying autoregressive error models to raw heteroscedastic residuals, as done in some recent studies, can lead to unstable error models with poor predictive performance. This instability can be avoided by applying the autoregressive process to standardized residuals. The theoretical analysis is supported by empirical findings in three hydrologically distinct catchments. The case studies also highlight strong interactions between the parameters of autoregressive residual error models and the water balance parameters of the hydrological model.

Evin, Guillaume; Kavetski, Dmitri; Thyer, Mark; Kuczera, George

2013-07-01

303

Elements of a flexible approach for conceptual hydrological modeling: 2. Application and experimental insights  

NASA Astrophysics Data System (ADS)

In this article's companion paper, flexible approaches for conceptual hydrological modeling at the catchment scale were motivated, and the SUPERFLEX framework, based on generic model components, was introduced. In this article, the SUPERFLEX framework and the "fixed structure" GR4H model (an hourly version of the popular GR4J model) are applied to four hydrologically distinct experimental catchments in Europe and New Zealand. The estimated models are scrutinized using several diagnostic measures, ranging from statistical metrics, such as the statistical reliability and precision of the predictive distribution of streamflow, to more process-oriented diagnostics based on flow-duration curves and the correspondence between model states and groundwater piezometers. Model performance was clearly catchment specific, with a single fixed structure unable to accommodate intercatchment differences in hydrological behavior, including seasonality and thresholds. This highlights an important limitation of any "fixed" model structure. In the experimental catchments, the ability of competing model hypotheses to reproduce hydrological signatures of interest could be interpreted on the basis of independent fieldwork insights. The potential of flexible frameworks such as SUPERFLEX is then examined with respect to systematic and stringent hypothesis-testing in hydrological modeling, for characterizing catchment diversity, and, more generally, for aiding progress toward a more unified formulation of hydrological theory at the catchment scale. When interpreted in physical process-oriented terms, the flexible approach can also serve as a language for dialogue between modeler and experimentalist, facilitating the understanding, representation, and interpretation of catchment behavior.

Kavetski, Dmitri; Fenicia, Fabrizio

2011-11-01

304

Modeling and monitoring the hydrological effects of the Sand Engine.  

NASA Astrophysics Data System (ADS)

Since 1887, Dunea Water Company produces high quality drinking water using the dune area at Monster (Province of South Holland, the Netherlands). Annually, 8 billion liters of water is produced here using artificial recharge and recovery with shallow wells and infiltration lakes. The dunes are an important step in producing drinking water serving as an underground buffer, leveling fluctuating in temperature and quality and removing bacteria and viruses from the infiltrated water in a natural way. Since space is limited in the Netherlands, the drinking water production of Dunea is closely matched with surrounding land uses and natural constraints. This prevents groundwater nuisance, upconing and intrusion of salt water and, in this case, movement of a nearby groundwater pollution. This is especially true in the Monster area where the dunes are fairly low and small; the coast is less than 350 meters from the recovery wells. The coast of Monster was identified as a weak link in the coastal defense of The Netherlands. Because of this, two coastal defense projects were carried out between 2009 and 2011. The first project involved creating an extra dune ridge in front of existing dunes which leads to intrusion of a large volume of seawater. Directly after completion, the Sand Engine was constructed. This hook shaped sand peninsula will supply the coast with sand for the coming decades due to erosion and deposition along the coast. These two large coastal defense projects would obviously influence the tightly balanced hydrological system of Monster. Without hydrological intervention, the drinking water production would no longer be sustainable in this area. To study the effects of these projects and to find a solution to combine coastal defense and drinking water supply, field research and effect (geochemical) modeling were used interactively. To prevent negative effects it was decided to construct interception wells on top of the new dune ridge (28 in total). A comprehensive monitoring system was built to keep track of the salt groundwater and the groundwater heads. The zero measurement included groundwater heads, water samples, but also geophysical methods such as SkyTEM and CVES. We will also show the monitoring system we use to keep track of the groundwater heads and salt water intrusion in the future.

Schaars, Frans; Hoogmoed, Merel; van Vliet, Frank; Stuyfzand, Pieter; Groen, Michel; van der Made, Kees-Jan; Caljé, Ruben; Auken, Esben; Bergsted Pedersen, Jesper

2013-04-01

305

A Conceptual Model for Evaluating Hydrologic Connectivity in Geographically Isolated Wetlands (Invited)  

NASA Astrophysics Data System (ADS)

Knowledge about hydrologic connectivity between aquatic resources is critical to understanding and managing watershed hydrology and to the legal status of those resources. In particular, information is needed on the hydrologic connectivity and effects of geographically isolated wetlands (GIWs) on downstream waters. GIWs mostly consist of depressions that typically lack surface water connections to other water bodies. However, GIWs may connect to downstream waters at a range of time scales through either surface water fill and spill events during flooding or through groundwater. Investigations of such connectivity are few, and have been limited to specific regional types of GIWs. An understanding of the general factors that control hydrologic connectivity of GIWs and downstream waters is lacking. Here we present a conceptual model that describes these general factors. By combining elements of the hydrologic budget with site and regional characteristics, we classify GIWs by type and magnitude of potential hydrologic connectivity. Combining this information with hydrologic landscape characteristics that are generally available throughout the US could allow GIW hydrologic connectivity to be evaluated. For example, GIWs that occur in areas that have high rainfall and/or snowmelt relative to basin capacity, that have low soil permeability, and occur on a high slope would have a higher probability of fill and spill connectivity. For these same climatic and basin characteristics, high soil and aquifer permeability would favor groundwater connectivity. We illustrate the conceptual model with several case studies of different GIW types.

Leibowitz, S. G.; Rains, M. C.

2013-12-01

306

Coupled Atmosphere-Biophysics-Hydrology Models for Environmental Modeling  

Microsoft Academic Search

The formulation and implementation of LEAF-2, the Land Ecosystem-Atmosphere Feedback model, which comprises the representation of land-surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision

Robert L. Walko; Larry E. Band; Jill Baron; Timothy G. F. Kittel; Richard Lammers; Tsengdar J. Lee; Dennis Ojima; Roger A. Pielke Sr.; Chris Taylor; Christina Tague; Craig J. Tremback; Pier Luigi Vidale

2000-01-01

307

Virtual Hydrologic Environment (VHE) - Design and implementation of a GIS data model for the integration with hydrologic modeling and its application to Meijiang watershed area in East China  

NASA Astrophysics Data System (ADS)

Virtual Hydrologic Environment (VHE) is an integrated approach where two major data systems are included: integration of different types of GIS and water resources data, integration of data and modeling. The Unified Modeling Language (UML) facilitates the design of GIS based relational database model GeoHydro/DataBase(GH/DB) and is used to create a specialized set of geo- and hydro-objects from both surface and subsurface hydrology in a consistent manner. Feather classes were created to store spatial data, such as sub-catchments and steam network. Tables were created to store time series and other parameters. Relationship classes were developed to link related objects. Furthermore, a graphical user interface is implemented as a link between object- and process-oriented numerical model GeoSys/RockFlow and GH/DB for the pre- and post-processing of model data and parameters. This VHE concept is applied to the Meijiang watershed area which belongs to the Poyang lake basin, the biggest freshwater drainage area in East China. A coupled regional hydrologic soil model is developed for the understanding of surface/subsurface water interaction. The GH/DB has been populated with data from the Meijiang site. The soil compartment is directly coupled to the atmosphere via the land surface and to the aquifers. The high-resolution modeling is achieved by parallel computation techniques. VHE as a bridge between surface and subsurface hydrology can improve our understanding of the hydrologic cycle, the interactions between water, earth, ecosystems and man and its role in the context of climate change. The integration of databases and modeling by the use of methods from scientific computing and information technology leads to a comprehensive and consistent representation of the VHE and thus enhances our understanding about the interactions and coupling processes between the different compartments of the hydrologic system.

Chen, C.; Sun, F.; Lai, G. Y.; Kalbacher, T.; Kolditz, O.

2009-04-01

308

Frozen soil parameterization in a distributed biosphere hydrological model  

NASA Astrophysics Data System (ADS)

In this study, a frozen soil parameterization has been modified and incorporated into a distributed biosphere hydrological model (WEB-DHM). The WEB-DHM with the frozen scheme was then rigorously evaluated in a small cold area, the Binngou watershed, against the in-situ observations from the WATER (Watershed Allied Telemetry Experimental Research). In the summer 2008, land surface parameters were optimized using the observed surface radiation fluxes and the soil temperature profile at the Dadongshu-Yakou (DY) station in July; and then soil hydraulic parameters were obtained by the calibration of the July soil moisture profile at the DY station and by the calibration of the discharges at the basin outlet in July and August that covers the annual largest flood peak of 2008. The calibrated WEB-DHM with the frozen scheme was then used for a yearlong simulation from 21 November 2007 to 20 November 2008, to check its performance in cold seasons. Results showed that the WEB-DHM with the frozen scheme has given much better performance than the WEB-DHM without the frozen scheme, in the simulations of soil moisture profile at the DY station and the discharges at the basin outlet in the yearlong simulation.

Wang, L.; Koike, T.; Yang, K.; Jin, R.; Li, H.

2009-11-01

309

Frozen soil parameterization in a distributed biosphere hydrological model  

NASA Astrophysics Data System (ADS)

In this study, a frozen soil parameterization has been modified and incorporated into a distributed biosphere hydrological model (WEB-DHM). The WEB-DHM with the frozen scheme was then rigorously evaluated in a small cold area, the Binngou watershed, against the in-situ observations from the WATER (Watershed Allied Telemetry Experimental Research). First, by using the original WEB-DHM without the frozen scheme, the land surface parameters and two van Genuchten parameters were optimized using the observed surface radiation fluxes and the soil moistures at upper layers (5, 10 and 20 cm depths) at the DY station in July. Second, by using the WEB-DHM with the frozen scheme, two frozen soil parameters were calibrated using the observed soil temperature at 5 cm depth at the DY station from 21 November 2007 to 20 April 2008; while the other soil hydraulic parameters were optimized by the calibration of the discharges at the basin outlet in July and August that covers the annual largest flood peak in 2008. With these calibrated parameters, the WEB-DHM with the frozen scheme was then used for a yearlong validation from 21 November 2007 to 20 November 2008. Results showed that the WEB-DHM with the frozen scheme has given much better performance than the WEB-DHM without the frozen scheme, in the simulations of soil moisture profile at the cold regions catchment and the discharges at the basin outlet in the yearlong simulation.

Wang, L.; Koike, T.; Yang, K.; Jin, R.; Li, H.

2010-03-01

310

Hydrological regime of the Black Sea waters: numerical modeling  

NASA Astrophysics Data System (ADS)

The aim of the present work was to study the hydrological regime of the Black Sea basing on climatic temperature and salinity data massives and using numerical modeling techniques. The climatic temperature and salinity data massives used in this research are based on measurements performed between 1956 and 1995. Measurements from each month of the year were averaged during this period and the averaged values were interpolated to a grid of 12' x 16' cells. To optimize the calculations monthly data were replaced by three-month running average at depths more than 400 m and by yearly averaged data at depths more than 1000 m. In order to improve the quality of the data a search for water density inversion was performed at every grid node. The model used in this research is a mode split sigma-coordinate numerical ocean model developed at the University of Bergen. It is also known as the Bergen Ocean Model (BOM). Monthly 3-D fields of temperature, salinity and current velocity were received as a result of modeling. In order to visualize this data maps of temperature and salinity distribution at different depths and sections were created. Quite good accordance of modeling results with the present knowledge on the hydrological regime and termohaline structure of the Black Sea was found. The surface temperature values are higher in the southeastern part of the sea in all seasons. It is particulary evident in February, when the waters in the shallow northwestern region become extremely cold - down to 0 °C - due to strong heat exchange with the atmosphere and considerable river discharge. At the same time the surface water close to the Georgian coast is relatively warm, its temperature may rise up to 10 °C. The vertical distribution of water temperature is unique in the Black Sea due to the presence of the well-known cold intermediate layer, which exists from summer to autumn, and a gradual temperature growth from the depth of approximately 200 m and till the bottom. The bottom temperature is nearly the same in all seasons - approximately 9,1 °C. The values of salinity at the sea surface are usually less near the coasts (16 - 17 ‰) than in the central areas of the sea (approximately 18 ‰) due to fresh water discharge and its further transportation by surface currents. A very strong surface salinity gradient is observed in May near the Danube estuary. The salinity values are growing with the depth. They reach their maximal values at the bottom of the sea - approximately 22,3 ‰. The most significant surface currents of the Black Sea are the cyclonic Main Rim Current (MRC) running along the continental slope, several quasi-cyclonic gyres inside the MRC and quasi-static anticyclonical eddies between the MRC and the shore. The MRC is most intense in spring, its velocities may reach 24 cm/s at that time.

Gippius, F. N.; Arkhipkin, V. S.

2012-04-01

311

Application of remote sensing to hydrology. [for the formulation of watershed behavior models  

NASA Technical Reports Server (NTRS)

Streamflow forecasting and hydrologic modelling are considered in a feasibility assessment of using the data produced by remote observation from space and/or aircraft to reduce the time and expense normally involved in achieving the ability to predict the hydrological behavior of an ungaged watershed. Existing watershed models are described, and both stochastic and parametric techniques are discussed towards the selection of a suitable simulation model. Technical progress and applications are reported and recommendations are made for additional research.

Ambaruch, R.; Simmons, J. W.

1973-01-01

312

A framework to assess the realism of model structures using hydrological signatures  

NASA Astrophysics Data System (ADS)

The use of flexible hydrological model structures for hypothesis testing requires an objective and diagnostic method to identify whether a rainfall-runoff model structure is suitable for a certain catchment. To determine if a model structure is realistic, i.e. if it captures the relevant runoff processes, both performance and consistency are important. Performance describes the ability of a model structure to mimic a specific part of the hydrological behaviour in a specific catchment. This can be assessed based on evaluation criteria, such as the goodness of fit of specific hydrological signatures obtained from hydrological data. Consistency describes the ability of a model structure to adequately reproduce several hydrological signatures simultaneously, while using the same set of parameter values. In this paper we describe and demonstrate a new evaluation Framework for Assessing the Realism of Model structures (FARM). The evaluation framework tests for both performance and consistency using a principal component analysis on a range of evaluation criteria, all emphasizing different hydrological behaviour. The utility of this evaluation framework is demonstrated in a case study of two small headwater catchments (Maimai, New Zealand and Wollefsbach, Luxembourg). Eight different hydrological signatures and eleven model structures have been used for this study. The results suggest that some model structures may reveal the same degree of performance for selected evaluation criteria, while showing differences in consistency. The results also show that some model structures have a higher performance and consistency than others. The principal component analysis in combination with several hydrological signatures is shown to be useful to visualize the performance and consistency of a model structure for the study catchments. With this framework performance and consistency can be tested to identify which model structures suit a catchment better than other model structures.

Euser, T.; Winsemius, H. C.; Hrachowitz, M.; Fenicia, F.; Uhlenbrook, S.; Savenije, H. H. G.

2012-11-01

313

A framework to assess the realism of model structures using hydrological signatures  

NASA Astrophysics Data System (ADS)

The use of flexible hydrological model structures for hypothesis testing requires an objective and diagnostic method to identify whether a rainfall-runoff model structure is suitable for a certain catchment. To determine if a model structure is realistic, i.e. if it captures the relevant runoff processes, both performance and consistency are important. We define performance as the ability of a model structure to mimic a specific part of the hydrological behaviour in a specific catchment. This can be assessed based on evaluation criteria, such as the goodness of fit of specific hydrological signatures obtained from hydrological data. Consistency is defined as the ability of a model structure to adequately reproduce several hydrological signatures simultaneously while using the same set of parameter values. In this paper we describe and demonstrate a new evaluation Framework for Assessing the Realism of Model structures (FARM). The evaluation framework tests for both performance and consistency using a principal component analysis on a range of evaluation criteria, all emphasizing different hydrological behaviour. The utility of this evaluation framework is demonstrated in a case study of two small headwater catchments (Maimai, New Zealand, and Wollefsbach, Luxembourg). Eight different hydrological signatures and eleven model structures have been used for this study. The results suggest that some model structures may reveal the same degree of performance for selected evaluation criteria while showing differences in consistency. The results also show that some model structures have a higher performance and consistency than others. The principal component analysis in combination with several hydrological signatures is shown to be useful to visualise the performance and consistency of a model structure for the study catchments. With this framework performance and consistency are evaluated to identify which model structure suits a catchment better compared to other model structures. Until now the framework has only been based on a qualitative analysis and not yet on a quantitative analysis.

Euser, T.; Winsemius, H. C.; Hrachowitz, M.; Fenicia, F.; Uhlenbrook, S.; Savenije, H. H. G.

2013-05-01

314

Remote sensing and hydrological modeling of burn scars  

NASA Astrophysics Data System (ADS)

This study examined the potential usefulness of combining remote sensing data with hydrologic models and mapping tools available from Geographic Information Systems (GIS), to evaluate the effects of wildfire. Four subprojects addressed this issue: (1) validation of burn scar maps derived from the Advanced Very High Resolution Radiometer (AVHRR) with the National Fire Occurrence Database; (2) testing the potential of thermal MODIS (Moderate Resolution Imaging Spectroradiometer) data for near-real time burn scar and fire severity mapping; (3) evaluation of Landsat derived burn severity maps within WEPP through the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP), and (4) predicting potential post-fire erosion for western U.S. forests utilizing existing datasets and models. Wildfire poses incredibly complex management problems in all of its stages. Today's land managers have the option of trying to mitigate the effects of a severe fire before it occurs by fuel management practices. This process is expensive especially considering the uncertainty of when and where the next fire in a given region will occur. When a wildfire does occur, deciding when to let it burn and when to suppress it may lead to controversial decisions. In addition to the threat to life and property from the fire itself, smoke emissions from large fires can cause air quality problems in distant airsheds. Even after the fire is extinguished, erosion and water quality problems may pose difficult management questions. Contributions stemming from these studies include improved burn scar maps for studying historical fire extent and demonstration of the feasibility of using thermal satellite data to predict burn scar extent when clouds and smoke obscure visible bands. The incorporation of Landsat derived burn severity maps was shown to improve post-fire erosion modeling results. Finally the potential post-fire burn severity and erosion risk maps generated for western US forests will be used for planning pre-fire fuel reduction treatments.

Miller, Mary Ellen

315

Modelling hydrology and water quality in a Mediterranean catchment  

NASA Astrophysics Data System (ADS)

In this study the SWAT model has been used in order to analyse and quantify pollution dynamics at basin scale depending on concentrated and diffuse sources. Nowadays, the receiving water bodies quality safeguarding is of growing importance due to the promulgation of recent laws as well as the growing sensitivity regarding the environment issues by the scientific and practitioner committee. Recently the EU 2000/60 (Water Framework Directive) makes the analysis of receiving water bodies even more complex by integrating the pollution in urban areas in a framework of the pollution sources at catchment scale. and making necessary further integration of environmental impacts associated with discharges concentrates civilian and productive with the widespread pollution linked mainly to agriculture and zoo-technical activities. The complexity of natural systems and the large number of polluting sources and variables to be monitored requires the adoption of models able to get a better view of the whole system in a simplified way without neglecting the most important physical phenomena. Particularly, in this study the SWAT model was considered since it is an integrated hydrological model that are, nowadays, needed to support the implementation of integrated water management plans and to comply with the current requirements of the WFD. In addition, the SWAT model is interfaced with the ARC-VIEW software which allows easy pre-and post processing of the spatially distributed input data, driving the rainfall-runoff process. The model has been applied to the experimental Nocella catchment located in Sicily (Italy), with an area of about 50 km2. The river receives wastewater and stormwater from two urban areas drained by combined sewers. The study demonstrates that the analysis of water quality in partially urbanised natural basins is complex depending on variable polluting contributions of the different parts of the system depending on specific polluting compounds. The model was calibrated and then validated, obtaining satisfactory performance. The estimation of loads from diffuse sources was difficult due to limited data availability. Thus, it was only possible to include constant diffuse pollution concentrations at present. In spite of these limitations, the model captured rather well the dynamic of flow generation and was able to predict the range of nutrient concentrations in surface water. The contribution of urban areas to the polluting loads at catchment scale is relevant especially during the dry season.

Candela, Angela; Viviani, Gaspare

2010-05-01

316

An educational model for ensemble streamflow simulation and uncertainty analysis  

NASA Astrophysics Data System (ADS)

This paper presents a hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this model, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The model includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for not only hydrological processes, but also for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity.

AghaKouchak, A.; Nakhjiri, N.; Habib, E.

2012-06-01

317

Establishing an Operation System with Unified Regional Circulation Rainfall Model and Hydrological Watershed Model  

NASA Astrophysics Data System (ADS)

The Taiwan Typhoon and Flood Research Institute (TTFRI) is a newly founded national laboratory in Taiwan. One of the major tasks of TTFRI is to develop locally coupled meteorological rainfall model and hydrological watershed model to abate the lost of people’s lives and properties in an earlier warning system. TTFRI examines flood simulations in our watershed scale modeling activities using precipitation from mesocale numerical weather prediction systems, Weather Research Forecasting (WRF) Model, as input. The hydrology and hydraulic modeling are going to be conducted by WASH123D numerical model. The long-term goal of TTFRI is to deliver fully coupled weather-hydrology interaction models. To date, only off-line simulations are implemented because the development of a fully integrated or coupled rainfall-runoff model is yet to complete. The paper presents an operation system established by TTFRI using WRF to generate precipitation, and the WASH123D numerical model is utilized to determine the flood routing. The operation runs are implemented twice a day (0000 and 1200, GMT) in TTFRI during regular period, and four times a day (0000, 0600 1200 and 1800, GMT) as typhoon invaded.

Liou, J.; Chiang, C.

2009-12-01

318

Hydrological modelling of a small catchment using SWAT-2000 Ensuring correct flow partitioning for contaminant modelling  

NASA Astrophysics Data System (ADS)

SummaryThe performance of the SWAT-2000 model was evaluated using stream flow at the outlet of the 142 ha Colworth catchment (Bedfordshire, UK). This catchment has been monitored since October 1999. The soil type consists of clay loam soil over stony calcareous clay and a rotation of wheat, oil seed rape, grass, beans and peas is grown. Much of the catchment is tile drained. Acceptable performance in hydrological modelling, along with correct simulation of the processes driving the water balance were essential first requirements for predicting contaminant transport. Initial results from SWAT-2000 identified some necessary modifications in the model source code for correct simulation of processes driving water balance. After modification of the code, hydrological simulation, crop growth and evapotranspiration (ET) patterns were realistic when compared with empirical data. Acceptable model performance (based on a number of error measures) was obtained in final model runs, with reasonable runoff partitioning into overland flow, tile drainage and base flow.

Kannan, N.; White, S. M.; Worrall, F.; Whelan, M. J.

2007-02-01

319

Parsimonious Hydrologic and Nitrate Response Models For Silver Springs, Florida  

NASA Astrophysics Data System (ADS)

Silver Springs with an approximate discharge of 25 m3/sec is one of Florida's first magnitude springs and among the largest springs worldwide. Its 2500-km2 springshed overlies the mostly unconfined Upper Floridan Aquifer. The aquifer is approximately 100 m thick and predominantly consists of porous, fractured and cavernous limestone, which leads to excellent surface drainage properties (no major stream network other than Silver Springs run) and complex groundwater flow patterns through both rock matrix and fast conduits. Over the past few decades, discharge from Silver Springs has been observed to slowly but continuously decline, while nitrate concentrations in the spring water have enormously increased from a background level of 0.05 mg/l to over 1 mg/l. In combination with concurrent increases in algae growth and turbidity, for example, and despite an otherwise relatively stable water quality, this has given rise to concerns about the ecological equilibrium in and near the spring run as well as possible impacts on tourism. The purpose of the present work is to elaborate parsimonious lumped parameter models that may be used by resource managers for evaluating the springshed's hydrologic and nitrate transport responses. Instead of attempting to explicitly consider the complex hydrogeologic features of the aquifer in a typically numerical and / or stochastic approach, we use a transfer function approach wherein input signals (i.e., time series of groundwater recharge and nitrate loading) are transformed into output signals (i.e., time series of spring discharge and spring nitrate concentrations) by some linear and time-invariant law. The dynamic response types and parameters are inferred from comparing input and output time series in frequency domain (e.g., after Fourier transformation). Results are converted into impulse (or step) response functions, which describe at what time and to what magnitude a unitary change in input manifests at the output. For the hydrologic response model, frequency spectra of groundwater recharge and spring discharge suggest an exponential response model, which may explain a significant portion of spring discharge variability with only two fitting parameters (mean response time 2.4 years). For the transport model, direct use of nitrate data is confounded by inconsistent data and a strong trend. Instead, chloride concentrations in rainfall and at the spring are investigated as a surrogate candidate. Preliminary results indicate that the transport response function of the springshed as a whole may be of the gamma type, which possesses both a larger initial peak as well as a longer tail than the exponential response function. This is consistent with the large range of travel times to be expected between input directly into fast conduits connected to the spring (e.g., though sinkholes) and input or back-diffusion from the rock matrix. The result implies that reductions in nitrate input, especially at remote and hydraulically not well connected locations, will only manifest in a rather delayed and smoothed out form in concentration observed at the spring.

Klammler, Harald; Yaquian-Luna, Jose Antonio; Jawitz, James W.; Annable, Michael D.; Hatfield, Kirk

2014-05-01

320

Using models for the optimization of hydrologic monitoring  

USGS Publications Warehouse

Hydrologists are often asked what kind of monitoring network can most effectively support science-based water-resources management decisions. Currently (2011), hydrologic monitoring locations often are selected by addressing observation gaps in the existing network or non-science issues such as site access. A model might then be calibrated to available data and applied to a prediction of interest (regardless of how well-suited that model is for the prediction). However, modeling tools are available that can inform which locations and types of data provide the most 'bang for the buck' for a specified prediction. Put another way, the hydrologist can determine which observation data most reduce the model uncertainty around a specified prediction. An advantage of such an approach is the maximization of limited monitoring resources because it focuses on the difference in prediction uncertainty with or without additional collection of field data. Data worth can be calculated either through the addition of new data or subtraction of existing information by reducing monitoring efforts (Beven, 1993). The latter generally is not widely requested as there is explicit recognition that the worth calculated is fundamentally dependent on the prediction specified. If a water manager needs a new prediction, the benefits of reducing the scope of a monitoring effort, based on an old prediction, may be erased by the loss of information important for the new prediction. This fact sheet focuses on the worth or value of new data collection by quantifying the reduction in prediction uncertainty achieved be adding a monitoring observation. This calculation of worth can be performed for multiple potential locations (and types) of observations, which then can be ranked for their effectiveness for reducing uncertainty around the specified prediction. This is implemented using a Bayesian approach with the PREDUNC utility in the parameter estimation software suite PEST (Doherty, 2010). The techniques briefly described earlier are described in detail in a U.S. Geological Survey Scientific Investigations Report available on the Internet (Fienen and others, 2010; http://pubs.usgs.gov/sir/2010/5159/). This fact sheet presents a synopsis of the techniques as applied to a synthetic model based on a model constructed using properties from the Lake Michigan Basin (Hoard, 2010).

Fienen, Michael N.; Hunt, Randall J.; Doherty, John E.; Reeves, Howard W.

2011-01-01

321

Investigations of Sensitivity and Uncertainty in Some Hydrologic Models of Yucca Mountain and Vicinity.  

National Technical Information Service (NTIS)

The uncertainty in travel time for water through unsaturated and saturated zones of Yucca Mountain and vicinity was determined by considering uncertainty associated with input parameters to the hydrologic models of these zones. A first-order analysis was ...

E. A. Jacobson M. D. Freshley F. H. Dove

1985-01-01

322

High Seroprevalence of HBV and HCV Infection in HIV-Infected Adults in Kigali, Rwanda  

PubMed Central

Background Data on prevalence and incidence of hepatitis B virus (HBV) and hepatitis C virus (HCV) infection in Rwanda are scarce. Methods HBV status was assessed at baseline and Month 12, and anti-HCV antibodies at baseline, in a prospective cohort study of HIV-infected patients in Kigali, Rwanda: 104 men and 114 women initiating antiretroviral therapy (ART) at baseline, and 200 women not yet eligible for ART. Results Baseline prevalence of active HBV infection (HBsAg positive), past or occult HBV infection (anti-HBc positive and HBsAg negative) and anti-HCV was 5.2%, 42.9%, and 5.7%, respectively. The active HBV incidence rate was 4.2/1,000 person years (PY). In a multivariable logistic regression model using baseline data, participants with WHO stage 3 or 4 HIV disease were 4.19 times (95% CI 1.21–14.47) more likely to have active HBV infection, and older patients were more likely to have evidence of past exposure to HBV (aRR 1.03 per year; 95%CI 1.01–1.06). Older age was also positively associated with having anti-HCV antibodies (aOR 1.09; 95%CI 1.04–1.14) while having a higher baseline HIV viral load was negatively associated with HCV (aOR 0.60; 95% CI 0.40–0.98). The median CD4 increase during the first 12 months of ART was lower for those with active HBV infection or anti-HCV at baseline. Almost all participants (88%) with active HBV infection who were on ART were receiving lamivudine monotherapy for HBV. Conclusion HBV and HCV are common in HIV-infected patients in Rwanda. Regular HBsAg screening is needed to ensure that HIV-HBV co-infected patients receive an HBV-active ART regimen, and the prevalence of occult HBV infection should be determined. Improved access to HBV vaccination is recommended. Active HCV prevalence and incidence should be investigated further to determine whether HCV RNA PCR testing should be introduced in Rwanda.

Rusine, John; Ondoa, Pascale; Asiimwe-Kateera, Brenda; Boer, Kimberly R.; Uwimana, Jean Marie; Mukabayire, Odette; Zaaijer, Hans; Mugabekazi, Julie; Reiss, Peter; van de Wijgert, Janneke H.

2013-01-01

323

Coupling of a climate model and a hydrological model and implications on land surface fluxes  

NASA Astrophysics Data System (ADS)

In recent years there has been an increasing focus on the need to establish coupled climate-hydrological models to better describe the feedback processes in the energy and water fluxes between the atmosphere and the land surface. Such improved descriptions may be important for two main reasons. First, they may enable developments of improved climate models with more correct land surface feedbacks than the existing simple land surface schemes which have a poor representation of soil moisture and basically neglect the effects of groundwater. Secondly, they may be able to reduce the uncertainty in climate change impact predictions on water resources, which today are performed in an uncoupled two-step process, where output from a climate model is used to force a hydrological model. Within the HYACINTS project (www.hyacints.dk) we have by use of the Open Modelling Interface (OpenMI) standard developed a coupling between two model codes, the regional climate model HIRHAM and the hydrological model MIKE SHE. HIRHAM is a regional climate model (RCM) being used for dynamically downscaling of GCM results to a finer resolution (5-25 km). It is run on a high performance computer at the Danish Meteorological Institute using Linux. MIKE SHE is a distributed model with coupled descriptions of groundwater, unsaturated zone, overland flow, river flow and including a component for simulating energy and water fluxes between the land surface and the atmosphere. MIKE SHE is run on Windows PCs and typically operates on spatial grid scales between 25 m and 1 km depending on the modelling objectives. In contrary to other existing coupling approaches using the same model grid for the same domain in the climate and hydrological models, our coupling uses the large RCM domain with usual resolution and a hydrological model with a much finer resolution for a smaller domain. We show test results from a catchment in the US (225 km2 FIFE area) and a catchment inDenmark (2500 km2 Skjern River catchment) with focus on the effects on simulation of fluxes and the importance of groundwater. Furthermore, we discuss the potentials and limitations of coupled models at these scales.

Refsgaard, J.; Rasmussen, S.; Larsen, M. A.; Drews, M.; Butts, M. B.; Christensen, J. H.; Jensen, K. H.

2012-12-01

324

Numerical prediction of subsidence with coupled geomechanical-hydrological modeling  

SciTech Connect

A coupled finite element geomechanical-hydrology code is currently under development for application to the problem of predicting groundwater disturbances associated with mine subsidence. The structural-fluid coupling is addressed by calculating the subsided mine geometry, with emphasis placed on determining the strata disturbance and locating damaged regions, for input into a hydrology code, which determines localized volume flow rates and aquifer fluctuations. Benefits from coupling will be best realized when field measurements, an additional aspect of the study concurrent with analytical investigations, indicating the relationship between increasing rock strain and increasing permeability are incorporated into hydraulic material descriptions. Hydrologic and structural calculations are presented to demonstrate computational capabilities applicable to mine subsidence.

Girrens, S.P.; Anderson, C.A.; Bennett, J.G.; Kramer, M.

1981-01-01

325

Water balance modelling in the Baltic Sea drainage basin – analysis of meteorological and hydrological approaches  

Microsoft Academic Search

Summary   Efforts to understand and simulate the global climate in numerical models have led to regional studies of the energy and\\u000a water balance. The Baltic Basin provides a continental scale test basin where meteorology, oceanography and hydrology all\\u000a can meet. Using a simple conceptual approach, a large-scale hydrological model of the water balance of the total Baltic Sea\\u000a Drainage Basin

L. P. Graham; S. Bergström

2001-01-01

326

Hydrology of malaria: Model development and application to a Sahelian village  

Microsoft Academic Search

We present a coupled hydrology and entomology model for the mechanistic simulation of local-scale response of malaria transmission to hydrological and climatological determinants in semiarid, desert fringe environments. The model is applied to the Sahel village of Banizoumbou, Niger, to predict interannual variability in malaria vector mosquito populations that lead to variations in malaria transmission. Using a high-resolution, small-scale distributed

Arne Bomblies; Jean-Bernard Duchemin; Elfatih A. B. Eltahir

2008-01-01

327

Adding sediment transport to the integrated hydrology model (InHM): Development and testing  

Microsoft Academic Search

The addition of a sediment transport algorithm to the comprehensive hydrologic-response model known as the Integrated Hydrology Model (InHM) is discussed. The first test of the sediment transport version of InHM is reported, using field data from a series of erosion experiments conducted by Gabet and Dunne [E.J. Gabet, T. Dunne, Sediment detachment by rain power, Water Resour Res 39

Christopher S. Heppner; Qihua Ran; Joel E. VanderKwaak; Keith Loague

2006-01-01

328

Stepwise calibration procedure for regional coupled hydrological-hydrogeological models  

NASA Astrophysics Data System (ADS)

Stream-aquifer interaction is a complex process depending on regional and local processes. Indeed, the groundwater component of hydrosystem and large scale heterogeneities control the regional flows towards the alluvial plains and the rivers. In second instance, the local distribution of the stream bed permeabilities controls the dynamics of stream-aquifer water fluxes within the alluvial plain, and therefore the near-river piezometric head distribution. In order to better understand the water circulation and pollutant transport in watersheds, the integration of these multi-dimensional processes in modelling platform has to be performed. Thus, the nested interfaces concept in continental hydrosystem modelling (where regional fluxes, simulated by large scale models, are imposed at local stream-aquifer interfaces) has been presented in Flipo et al (2014). This concept has been implemented in EauDyssée modelling platform for a large alluvial plain model (900km2) part of a 11000km2 multi-layer aquifer system, located in the Seine basin (France). The hydrosystem modelling platform is composed of four spatially distributed modules (Surface, Sub-surface, River and Groundwater), corresponding to four components of the terrestrial water cycle. Considering the large number of parameters to be inferred simultaneously, the calibration process of coupled models is highly computationally demanding and therefore hardly applicable to a real case study of 10000km2. In order to improve the efficiency of the calibration process, a stepwise calibration procedure is proposed. The stepwise methodology involves determining optimal parameters of all components of the coupled model, to provide a near optimum prior information for the global calibration. It starts with the surface component parameters calibration. The surface parameters are optimised based on the comparison between simulated and observed discharges (or filtered discharges) at various locations. Once the surface parameters have been determined, the groundwater component is calibrated. The calibration procedure is performed under steady state hypothesis (to minimize the procedure time length) using recharge rates given by the surface component calibration and imposed fluxes boundary conditions given by the regional model. The calibration is performed using pilot point where the prior variogram is calculated from observed transmissivities values. This procedure uses PEST (http//:www.pesthomepage.org/Home.php) as the inverse modelling tool and EauDyssée as the direct model. During the stepwise calibration process, each modules, even if they are actually dependant from each other, are run and calibrated independently, therefore contributions between each module have to be determined. For the surface module, groundwater and runoff contributions have been determined by hydrograph separation. Among the automated base-flow separation methods, the one-parameter Chapman filter (Chapman et al 1999) has been chosen. This filter is a decomposition of the actual base-flow between the previous base-flow and the discharge gradient weighted by functions of the recession coefficient. For the groundwater module, the recharge has been determined from surface and sub-surface module. References : Flipo, N., A. Mourhi, B. Labarthe, and S. Biancamaria (2014). Continental hydrosystem modelling : the concept of nested stream-aquifer interfaces. Hydrol. Earth Syst. Sci. Discuss. 11, 451-500. Chapman,TG. (1999). A comparison of algorithms for stream flow recession and base-flow separation. hydrological Processes 13, 701-714.

Labarthe, Baptiste; Abasq, Lena; de Fouquet, Chantal; Flipo, Nicolas

2014-05-01

329

A simple hydrologically based model of land surface water and energy fluxes for general circulation models  

NASA Technical Reports Server (NTRS)

A generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model (GCM) is described. The new model is comprised of a two-layer characterization of the soil column, and uses an aerodynamic representation of the latent and sensible heat fluxes at the land surface. The infiltration algorithm for the upper layer is essentially the same as for the single layer VIC model, while the lower layer drainage formulation is of the form previously implemented in the Max-Planck-Institut GCM. The model partitions the area of interest (e.g., grid cell) into multiple land surface cover types; for each land cover type the fraction of roots in the upper and lower zone is specified. Evapotranspiration consists of three components: canopy evaporation, evaporation from bare soils, and transpiration, which is represented using a canopy and architectural resistance formulation. Once the latent heat flux has been computed, the surface energy balance is iterated to solve for the land surface temperature at each time step. The model was tested using long-term hydrologic and climatological data for Kings Creek, Kansas to estimate and validate the hydrological parameters, and surface flux data from three First International Satellite Land Surface Climatology Project Field Experiment (FIFE) intensive field campaigns in the summer-fall of 1987 to validate the surface energy fluxes.

Liang, XU; Lettenmaier, Dennis P.; Wood, Eric F.; Burges, Stephen J.

1994-01-01

330

Use of the WATFLOOD Distributed Hydrological Model in the Distributed Model Intercomparison Project  

NASA Astrophysics Data System (ADS)

The National Weather Service Hydrology Laboratory has coordinated the Distributed Model Intercomparison Project (DMIP). The purpose of the project is to explore issues related to distributed hydrological modeling. WATFLOOD is a distributed hydrological model developed at the University of Waterloo. WATFLOOD subdivides the watershed into grids, and is therefore ideally suited for use with gridded data sets, such as radar data. WATFLOOD uses the Grouped Response Unit methodology to account for landcover inhomogeneity. All areas of similar landcover within a grid (not necessarily contiguous) form a GRU, and runoff is calculated for each GRU separately. The runoff estimates for each GRU are summed to calculate the grid runoff, which is then routed downstream to the basin outlet. The parameters for WATFLOOD are landcover based, and may be transferred between basins. The model has been used for a variety of basins within Canada, with a single set of (landcover-based) parameters. The WATFLOOD model has been used to develop streamflow estimates on the DMIP test basins. This presentation will describe the model itself, how the DMIP watersheds were setup for WATFLOOD, and the initial and calibrated streamflow estimates.

Bingeman, A.; Kouwen, N.

2002-05-01

331

Sequential assimilation of radar data into a coupled hydrologic-hydraulic model for operational water management  

NASA Astrophysics Data System (ADS)

Nonlinearity and non-Gaussianity of Hydrological and Hydraulic Models is increasingly receiving attention in the scientific community for the development of new state estimation algorithms. Particle Filtering is widely used in different fields such as nonlinear system identification or nonlinear state estimation. Some recent literature on data assimilation in hydrology presents important results in the application of particle filters, as compared to traditional nonlinear filters. The objective of this work is to analyze the results of a coupled hydrologic-hydraulic model, optimized through the assimilation of radar data using the Particle Filter. The data assimilation framework involves the hydrological and the hydraulic assimilation separately. For the hydrologic data assimilation, the Sampling Importance Resampling Particle Filter (SIR) and the Community Land Model (CLM2.0) are used to assimilate soil moisture observations. The discharge generated by the hydrologic model serves as input to the 1-D hydraulic model. For the hydraulic assimilation, the SIR filter and the HEC-RAS model, forced with the discharge generated by CLM2.0, are used to assimilate Synthetic Aperture Radar-derived water stages. Finally, the validity, strengths and weaknesses of the data assimilation methodology are analyzed.

Plaza Guingla, D. A.; de Lannoy, G. J.; Montanari, M.; Matgen, P.; Hoffmann, L.; Pfister, L.; de Keyser, R.; Pauwels, V. R.

2009-12-01

332

Dominant Process Concept, Model Simplification and Classification System in Catchment Hydrology  

NASA Astrophysics Data System (ADS)

Technological and methodological advances have facilitated enormous growth in hydrologic science during the last century. However, there are also serious concerns that these advances indirectly contribute to additional problems in hydrologic research. An insight into hydrologic literature clearly reveals our tendency to develop more complex models than perhaps needed and our increasing emphasis on individual mathematical techniques rather than general hydrologic issues. Some recent studies of diverse forms have suggested that simplification in modeling and development of a common framework may help alleviate these problems. The present study is intended to bring such studies together for a more coherent approach to research in catchment hydrology. This is done by highlighting the need for model simplification and generalization, and also proposing some potential directions to achieve these. Through a discussion of difficulties (technological, economic, political and societal) in data measurements, the need for moving beyond the notion of `modeling everything' to the notion of `capturing the essential features' is explained. The concept of dominant processes in model simplification and the utility of integration of concepts for modeling improvements are explained. Formulation of a catchment classification system is advocated as a possible means for a common framework in hydrology, and the roles of dominant processes and data reconstruction in this formulation are discussed.

Sivakumar, B.

2006-12-01

333

Improved ground hydrology calculations for global climate models (GCMs) - Soil water movement and evapotranspiration  

NASA Technical Reports Server (NTRS)

A physically based ground hydrology model is presented that includes the processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff. Data from the Goddard Institute for Space Studies GCM were used as inputs for off-line tests of the model in four 8 x 10 deg regions, including Brazil, Sahel, Sahara, and India. Soil and vegetation input parameters were caculated as area-weighted means over the 8 x 10 deg gridbox; the resulting hydrological quantities were compared to ground hydrology model calculations performed on the 1 x 1 deg cells which comprise the 8 x 10 deg gridbox. Results show that the compositing procedure worked well except in the Sahel, where low soil water levels and a heterogeneous land surface produce high variability in hydrological quantities; for that region, a resolution better than 8 x 10 deg is needed.

Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

1988-01-01

334

A method for coupling a parameterization of the planetary boundary layer with a hydrologic model  

NASA Technical Reports Server (NTRS)

Deardorff's parameterization of the planetary boundary layer is adapted to drive a hydrologic model. The method converts the atmospheric conditions measured at the anemometer height at one site to the mean values in the planetary boundary layer; it then uses the planetary boundary layer parameterization and the hydrologic variables to calculate the fluxes of momentum, heat and moisture at the atmosphere-land interface for a different site. A simplified hydrologic model is used for a simulation study of soil moisture and ground temperature on three different land surface covers. The results indicate that this method can be used to drive a spatially distributed hydrologic model by using observed data available at a meteorological station located on or nearby the site.

Lin, J. D.; Sun, Shu Fen

1986-01-01

335

A Method for Coupling a Parameterization of the Planetary Boundary Layer with a Hydrologic Model.  

NASA Astrophysics Data System (ADS)

Deardorff's parameterization of the planetary boundary layer is adapted to drive a hydrologic model. The method converts the atmospheric conditions measured at the anemometer height at one site to the mean values in the planetary boundary layer it then uses the planetary boundary layer parameterization and the hydrologic variables to calculate the fluxes of momentum, heat and moisture at the atmosphere-land interface for a different site. A simplified hydrologic model is used for a simulation study of soil moisture and ground temperature on three different land surface covers. The results indicate that this method can be used to drive a spatially distributed hydrologic model by using observed data available at a meteorological station located on or nearby the site.

Lin, J. D.; Sun, Shu Fen

1986-12-01

336

Catchment modeling and model transferability in upper Blue Nile Basin, Lake Tana, Ethiopia  

Microsoft Academic Search

Understanding spatial and temporal distribution of water resources has an important role for water resource management. To understand water balance dynamics and runoff generation mechanisms at the Gilgel Abay catchment (a major tributary into lake Tana, source of Blue Nile, Ethiopia) and to evaluate model transferability, catchment modeling was conducted using the conceptual hydrological model HBV. The catchment of the

A. S. Gragne; S. Uhlenbrook; Y. Mohammed; S. Kebede

2008-01-01