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Sample records for hydrological model hbv

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  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)

    Cannon, A. J.

    2006-12-01

    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.

  3. A mouse model for HBV immunotolerance and immunotherapy.

    PubMed

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

    2014-01-01

    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. PMID:24076617

  4. The HBV spatially distributed flash flood forecasting model - The Slovenia case study

    NASA Astrophysics Data System (ADS)

    Tsanis, I. K.; Grillakis, M. G.; Blöschl, G.; Pogačnik, N.

    2009-04-01

    The HBV distributed flash flood forecasting model which is in operational use in northern Austria is applied to a watershed in northwest Slovenia, a case study for the FP6 project HYDRATE. The selected watershed consists of 6 sub-basins with a total area of 646 Km2. Model setup and calibration was performed in this watershed and three long duration rainfall - runoff periods were simulated in order to examine the efficiency of the model. The selected periods included rainfall events that produced high outflows on the exit of the watershed, such as the September 2007 event that caused a flash flooding and severe damages to the towns of Zali Log and Zelezniki. The model uses 1km grid rainfall and temperature data of fifteen minute time intervals in order to simulate the rainfall - runoff process. Inverse distance weighting interpolation is used in order to generate the spatially distributed rainfall and temperature while the hydrological parameters are defined for each 1km grid cell that correspond to one hydrological response units (HRU - areas with analogous hydrogeological characteristics). The basic calibration of the HBV model is based on hydrological parameters of each HRU, parameters that control the rainfall - runoff process within the basin and non HRU parameters that control the river routing between the basins. The model performance is based on seven efficiency criteria that were selected as appropriate for long simulation periods, e.g. coefficient of determination R2 and Nash Sutcliffe efficiency E. The HBV model produced satisfactory results for the three rainfall periods and could be used as an operational model in Slovenia as well.

  5. A Novel Hydrodynamic Injection Mouse Model of HBV Genotype C for the Study of HBV Biology and the Anti-Viral Activity of Lamivudine

    PubMed Central

    Li, Xiumei; Liu, Guangze; Chen, Meijuan; Yang, Yang; Xie, Yong; Kong, Xiangping

    2016-01-01

    Background: Absence of an immunocompetent mouse model of persistent hepatitis B virus (HBV) infection has hindered the research of HBV infection and the development of antiviral medications. Objectives: In the present study, we aimed to develop a novel HBV genotype C mouse model by hydrodynamic injection (HI) and then used it to evaluate the antiviral activity of lamivudine. Materials and Methods: A quantity of 15 μg of HBV plasmid [pcDNA3.1 (+)-HBV1.3C], adeno-associated virus-HBV1.3C (pAAV-HBV1.3C) or pAAV-HBV1.2A) were injected into male C57BL/6 mice, by HI, accounting for a total of 13 mice per group. Then, lamivudine was administered to mice with sustained HBV viremia, for 4 weeks. Real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry methods were used to detect HBsAg, HBeAg, HBsAb, HBcAg and HBV DNA, in serum or liver of the mice, at indicated time points. Results: In 60% of the mice injected with pcDNA3.1 (+)-HBV1.3C, HBsAg, HBeAg, HBcAg and HBV DNA persisted for > 20 weeks in liver, post-injection, with no HBsAb appearance. Meanwhile, no significant inflammation was observed in these mice. Compared with pAAV-HBV1.2A and pAAV-HBV1.3C, pcDNA3.1 (+)-HBV1.3C administration led to higher and longer HBV viremia. Furthermore, serum HBV DNA was significantly reduced by lamivudine, after 4 weeks administration, and returned to the original level, after ceasing administration for 1 week, in the mice. Conclusions: In conclusion, our observations indicated that pcDNA3.1 (+)-HBV1.3C was superior to AAV/HBV plasmid for establishment of persistent HBV infection by HI, in vivo, and this mouse model could be useful for studies of hepatitis virology and for the development of innovatory treatments for HBV infections. PMID:27195013

  6. [Establishment of hepatitis B virus (HBV) chronic infection mouse model by in vivo transduction with a recombinant adeno-associated virus 8 carrying 1. 3 copies of HBV genome (rAAN8-1. 3HBV)].

    PubMed

    Dong, Xiao-Yan; Yu, Chi-Jie; Wang, Gang; Tian, Wen-Hong; Lu, Yue; Zhang, Feng-Wei; Wang, Wen; Wang, Yue; Tan, Wen-Jie; Wu, Xiao-Bing

    2010-11-01

    In this report, we developed a HBV infection model in C57BL/6 mouse line by in vivo injection of a recombinant adeno-associated virus 8 vector carrying 1. 3 copies of HBV genome (ayw subtype) (rAAV8-1. 3HBV). We firstly prepared and purified the rAAV8-1. 3HBV and then injected it into three C57BL/6 mice with the dose of 2 x 10e11vg, respectively. HBsAg and HBeAg were assayed in sera collected at different time points post injection. Ten weeks post injection, the three mice were sacrificed and blood and liver tissue were taken for assay. Copies of HBV DNA were detected by real time PCR and the way of HBV DNA replication was identified by PCR. Subsequently, detection of HBV antigen by immunohistochemistry and pathology analysis of liver tissue of mice were performed. The results suggested that expression of HBsAg and HBeAg lasted for at least 10 weeks in mice sera. Among mice injected with rAAV8-1. 3HBV, HBsAg levels were showed an 'increasing-decreasing-increasing' pattern (the lowest level at the 4th week post injection), while HBeAg levels were kept high and relatively stable. HBV DNA copies were 4.2 x 10(3), 3.6 x 10(3), 2.5 x 10(3) copies/mL in sera and 8.0 x 10(6), 5.7 x 10(6), 2.6 x 10(6) copies/g in hepatic tissues of three mice, respectively. We found that the linear 1. 3HBV DNA in the rAAV8-1. 3HBV could self form into circular HBV genome and replicate in livers of HBV transfected mice. HBsAg and HBcAg were both positive in liver tissue of mice injected with rAAV8-1. 3HBV and no obvious pathological characters were found in liver of mice injected with rAAV8-1. 3HBV. In conclusion, we successfully developed a HBV chronic infection model in C57BL/6 mouse line by in vivo transduction with the recombinant virus rAAV8-1. 3HBV, in which HBV genes could be continuously expressed and replicated over 10 weeks, and paved a way for further characterization of the human chronic hepatitis B virus infection and evaluation of vaccine and anti-HBV agents. PMID:21344744

  7. Watershed Modeling of Nutrient Transport Covering the Country of Sweden - Scale Transfer in HBV-NP

    NASA Astrophysics Data System (ADS)

    Arheimer, B.; Andersson, L.

    2002-12-01

    Eutrophication of the Baltic Sea and its coastal zone is considered a serious environmental problem. The problems are mainly caused by excessive load of nitrogen (N) and phosphorus (P). To improve the situation new policies including watershed-based water management are implemented. However, this also demands watershed-based knowledge of nutrient transport proc-esses and appropriate tools for landscape planning. A watershed model (HBV-NP) that can be applied both on the local and the national scale has thus been developed to be used both for international reporting and scenario estimates for more efficient nutrient control strategies. The P part is presently developed within the Swedish Water Management Research Program (VASTRA), in which HBV-NP will be used for evaluation of best management practices, and for communication with local stake-holders. The model has recently been applied at the national scale for calculations of flow-normalized annual average of gross load, N retention and net transport, and source apportionment of the N load reaching the sea. In this application (called TRK) several submodels with different levels of process descriptions were linked together. Dynamic and detailed models were included for arable leaching (SOIL-N model), rainfall interpolation, atmospheric deposition (MATCH model), water balance (HBV), and nutrient transformation in groundwater, rivers and lakes (HBV-N). Based on landscape information in GIS, different leaching rates and emissions were assigned to the water discharge from similar landscape elements in 1000 subbasins covering Sweden. Scale transfer was mainly achieved through up-scaling procedures and by using the conceptual model approach for watershed hydrology, including variability parameters that are calibrated for regions. The modeled river flow and N concentrations were validated against time-series from several independent-monitoring stations. A similar national system is now under development for P, including

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

    NASA Astrophysics Data System (ADS)

    Ding, Jie; Haberlandt, Uwe

    2014-05-01

    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.

  9. Calibration and Uncertainty in Scenario Simulations with the HBV-N Nitrogen Model

    NASA Astrophysics Data System (ADS)

    Lindstrom, G.; Arheimer, B.

    2002-12-01

    The HBV model, a Swedish precipitation-runoff model has been used extensively in basins all over Sweden for 30 years. Recently, it has been complemented with routines for nitrogen transformation in groundwater, rivers and lakes. The aim is to develop a decision support tool for evaluation of nitrogen load on recipients due to different management practices and policies. The hydrological submodel has a large number of parameters, which are established by calibration, supported by experience from earlier model applications. The root zone leakage of nitrogen, used as input to the HBV model, is simulated by the SOIL-N model, a model for turnover of water, heat and nitrogen in the unsaturated zone. The nitrogen subroutines introduce additional parameters. It is clear that no unique optimum parameter set can be obtained from a single-site model calibation to runoff and nitrogen measurements. This equifinality results in a wide range of uncertainty in the scenario simulations, when studied by ordinary Monte Carlo simulation and acceptance of all parameter sets that produce a fitness criterion above a chosen limit. This is illustrated in a case study for the R”nne † basin in the agricultural region of southern Sweden. The objective of the uncertainty analysis is to explore the uncertainty in the scenario simulations, and to provide support for decision-makers to choose between measures according to expected results and the reliability of these results. However, an ordinary Monte Carlo simulation in which all parameters are simulated and combined randomly does not take advantage of the experience from earlier applications. Therefore, a method is proposed, in which parameter sets are judged not only according to the fitness to observations but also according to their agreement with earlier model applications and hydrological experience, by use of subjective likelihood weights. The range in the scenario simulations obtained from the combined approach is finally compared

  10. An Educational Model for Hands-On Hydrology Education

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox 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 more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been 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 hydrology.

  11. Dynamics of an HBV Model with Drug Resistance Under Intermittent Antiviral Therapy

    NASA Astrophysics Data System (ADS)

    Zhang, Ben-Gong; Tanaka, Gouhei; Aihara, Kazuyuki; Honda, Masao; Kaneko, Shuichi; Chen, Luonan

    2015-06-01

    This paper studies the dynamics of the hepatitis B virus (HBV) model and the therapy regimens of HBV disease. First, we propose a new mathematical model of HBV with drug resistance, and then analyze its qualitative and dynamical properties. Combining the clinical data and theoretical analysis, we demonstrate that our model is biologically plausible and also computationally viable. Second, we demonstrate that the intermittent antiviral therapy regimen is one of the possible strategies to treat this kind of complex disease. There are two main advantages of this regimen, i.e. it not only may delay the development of drug resistance, but also may reduce the duration of on-treatment time compared with the long-term continuous medication. Moreover, such an intermittent antiviral therapy can reduce the adverse side effects. Our theoretical model and computational results provide qualitative insight into the progression of HBV, and also a possible new therapy for HBV disease.

  12. Uncertainty of the hydrological response to climate change conditions; 605 basins, 3 hydrological models, 5 climate models, 5 hydrological variables

    NASA Astrophysics Data System (ADS)

    Melsen, Lieke; Mizukami, Naoki; Newman, Andrew; Clark, Martyn; Teuling, Adriaan

    2016-04-01

    Many studies investigated the effect of a changing climate on the hydrological response of a catchment and uncertainty of the effect coming from hydrologic modelling (e.g., forcing, hydrologic model structures, and parameters). However, most past studies used only a single or a small number of catchments. To go beyond the case-study, and to assess the uncertainty involved in modelling the hydrological impact of climate change more comprehensively, we studied 605 basins over a wide range of climate regimes throughout the contiguous USA. We used three different widely-used hydrological models (VIC, HBV, SAC), which we forced with five distinct climate model outputs. The hydrological models have been run for a base period (1986-2008) for which observations were available, and for a future period (2070-2099). Instead of calibrating each hydrological model for each basin, the model has been run with a parameter sample (varying from 1600 to 1900 samples dependent on the number of free parameters in the model). Five hydrological states and fluxes were stored; discharge, evapotranspiration, soil moisture, SWE and snow melt, and 15 different metrics and signatures have been obtained for each model run. With the results, we conduct a sensitivity analysis over the change in signatures from the future period compared to the base period. In this way, we can identify the parameters that are responsible for certain projected changes, and identify the processes responsible for this change. By using three different models, in which VIC is most distinctive in including explicit vegetation parameters, we can compare different process representations and the effect on the projected hydrological change.

  13. Calibration of hydrological model with programme PEST

    NASA Astrophysics Data System (ADS)

    Brilly, Mitja; Vidmar, Andrej; Kryžanowski, Andrej; Bezak, Nejc; Šraj, Mojca

    2016-04-01

    PEST is tool based on minimization of an objective function related to the root mean square error between the model output and the measurement. We use "singular value decomposition", section of the PEST control file, and Tikhonov regularization method for successfully estimation of model parameters. The PEST sometimes failed if inverse problems were ill-posed, but (SVD) ensures that PEST maintains numerical stability. The choice of the initial guess for the initial parameter values is an important issue in the PEST and need expert knowledge. The flexible nature of the PEST software and its ability to be applied to whole catchments at once give results of calibration performed extremely well across high number of sub catchments. Use of parallel computing version of PEST called BeoPEST was successfully useful to speed up calibration process. BeoPEST employs smart slaves and point-to-point communications to transfer data between the master and slaves computers. The HBV-light model is a simple multi-tank-type model for simulating precipitation-runoff. It is conceptual balance model of catchment hydrology which simulates discharge using rainfall, temperature and estimates of potential evaporation. Version of HBV-light-CLI allows the user to run HBV-light from the command line. Input and results files are in XML form. This allows to easily connecting it with other applications such as pre and post-processing utilities and PEST itself. The procedure was applied on hydrological model of Savinja catchment (1852 km2) and consists of twenty one sub-catchments. Data are temporary processed on hourly basis.

  14. RHydro - Hydrological models and tools to represent and analyze hydrological data in R

    NASA Astrophysics Data System (ADS)

    Reusser, D. E.; Buytaert, W.; Vitolo, C.

    2012-04-01

    In hydrology, basic equations and procedures keep being implemented from scratch by scientist, with the potential for errors and inefficiency. The use of libraries can overcome these problems. As an example, hydrological libraries could contain: 1. Major representations of hydrological processes such as infiltration, sub-surface runoff and routing algorithms. 2. Scaling functions, for instance to combine remote sensing precipitation fields with rain gauge data 3. Data consistency checks 4. Performance measures. Here we present a beginning for such a library implemented in the high level data programming language R. Currently, Top-model, the abc-Model, HBV, a multi-model ensamble called FUSE, data import routines for WaSiM-ETH as well basic visualization and evaluation tools are implemented. Care is taken to make functions and models compatible with other existing frameworks in hydrology, such as for example Hydromad.

  15. Chronic hepatitis B infection and HBV DNA-containing capsids: Modeling and analysis

    NASA Astrophysics Data System (ADS)

    Manna, Kalyan; Chakrabarty, Siddhartha P.

    2015-05-01

    We analyze the dynamics of chronic HBV infection taking into account both uninfected and infected hepatocytes along with the intracellular HBV DNA-containing capsids and the virions. While previous HBV models have included either the uninfected hepatocytes or the intracellular HBV DNA-containing capsids, our model accounts for both these two populations. We prove the conditions for local and global stability of both the uninfected and infected steady states in terms of the basic reproduction number. Further, we incorporate a time lag in the model to encompass the intracellular delay in the production of the infected hepatocytes and find that this delay does not affect the overall dynamics of the system. The results for the model and the delay model are finally numerically illustrated.

  16. Establishment of drug-resistant HBV small-animal models by hydrodynamic injection

    PubMed Central

    Cheng, Junjun; Han, Yanxing; Jiang, Jian-Dong

    2014-01-01

    In antiviral therapy of hepatitis B virus (HBV) infection, drug resistance remains a huge obstacle to the long-term effectiveness of nucleoside/tide analogs (NAs). Primary resistance mutation (rtM204V) contributes to lamivudine (LAM)-resistance, and compensatory mutations (rtL180M and rtV173L) restore viral fitness and increase replication efficiency. The evaluation of new anti-viral agents against drug-resistant HBV is limited by the lack of available small-animal models. We established LAM-resistance HBV replication mice models based on clinical LAM-resistant HBV mutants. Double (rtM204V+rtL180M) or triple (rtM204V+rtL180M+rtV173L) lamivudine-resistant mutations were introduced into HBV expression vector, followed by hydrodynamic injection into tail vein of NOD/SCID mice. Viremia was detected on days 5, 9, 13 and 17 and liver HBV DNA was detected on day 17 after injection. The serum and liver HBV DNA levels in LAM-resistant model carrying triple mutations are the highest among the models. Two NAs, LAM and entecavir (ETV), were used to test the availability of the models. LAM and ETV inhibited viral replication on wild-type model. LAM was no longer effective on LAM-resistant models, but ETV retains a strong activity. Therefore, these models can be used to evaluate anti-viral agents against lamivudine-resistance, affording new opportunities to establish other drug-resistant HBV small-animal models. PMID:26579395

  17. Estimation of instantaneous peak flow from daily data using the HBV model

    NASA Astrophysics Data System (ADS)

    Ding, Jie; Haberlandt, Uwe

    2015-04-01

    The length of the observed instantaneous peak flow (IPF) period has a great influence on the flood design whereas these high resolution flow data are not always available. Our previous research has shown that IPFs can be derived from the easier available observed long time series of mean daily flows (MDFs) using a multiple regression model. The primary aim here is to explore the possibility of deriving frequency distributions of IPFs using hydrological modelling with daily and hourly time steps in comparison. In the post-correction approach the rainfall-runoff model is operated on daily time steps , a flood frequency distribution is fitted to the simulated annual MDFs and the resulting daily quantiles are transferred into IPF quantiles using the multiple regression model. In the pre-processing approach, hourly rainfall is produced by disaggregation of daily data. Then the rainfall-runoff model is operated on hourly time steps resulting in a frequency distribution of IPFs. In addition, two calibrations strategies for the hydrological model using the hydrograph and using flow statistics, respectively, are applied for both approaches. Finally, the performances of estimating the IPFs from daily data using these two approaches are compared considering also the two different calibration strategies. The hydrological simulations are carried out with the HBV-IWW model and the case study is carried out for 18 catchments of the Aller-Leine-River basin in northern Germany. The results show that: (1) the multiple regression model is capable to predict IPFs with the simulated MDFs as well; (2) the estimation of extreme flow quantiles in summer is not as good as in winter; (3) both of the two approaches enable a reasonable estimation of IPFs; (4) if on hand the hydrological model is calibrated on the hydrograph the post-correction approach with daily simulations is superior and if on the other hand the model is calibrated on flow statistics the pre-processing with hourly

  18. Hydrological models are mediating models

    NASA Astrophysics Data System (ADS)

    Babel, L. V.; Karssenberg, D.

    2013-08-01

    Despite the increasing role of models in hydrological research and decision-making processes, only few accounts of the nature and function of models exist in hydrology. Earlier considerations have traditionally been conducted while making a clear distinction between physically-based and conceptual models. A new philosophical account, primarily based on the fields of physics and economics, transcends classes of models and scientific disciplines by considering models as "mediators" between theory and observations. The core of this approach lies in identifying models as (1) being only partially dependent on theory and observations, (2) integrating non-deductive elements in their construction, and (3) carrying the role of instruments of scientific enquiry about both theory and the world. The applicability of this approach to hydrology is evaluated in the present article. Three widely used hydrological models, each showing a different degree of apparent physicality, are confronted to the main characteristics of the "mediating models" concept. We argue that irrespective of their kind, hydrological models depend on both theory and observations, rather than merely on one of these two domains. Their construction is additionally involving a large number of miscellaneous, external ingredients, such as past experiences, model objectives, knowledge and preferences of the modeller, as well as hardware and software resources. We show that hydrological models convey the role of instruments in scientific practice by mediating between theory and the world. It results from these considerations that the traditional distinction between physically-based and conceptual models is necessarily too simplistic and refers at best to the stage at which theory and observations are steering model construction. The large variety of ingredients involved in model construction would deserve closer attention, for being rarely explicitly presented in peer-reviewed literature. We believe that devoting

  19. Humanized Murine Model for HBV and HCV Using Human Induced Pluripotent Stem Cells

    PubMed Central

    Zhou, Xiao-Ling; Sullivan, Gareth J.; Sun, Pingnan; Park, In-Hyun

    2013-01-01

    Infection of hepatitis B virus (HBV) and hepatitis C virus (HCV) results in heterogeneous outcomes from acute asymptomatic infection to chronic infection leading to cirrhosis and hepatocellular carcinoma (HCC). In vitro models using animal hepatocytes, human HCC cell lines, or in vivo transgenic mouse models have contributed invaluably to understanding the pathogenesis of HBV and HCV. A humanized mouse model made by reconstitution of human primary hepatocytes in the liver of the immunodeficient mouse provides a novel experimental opportunity which mimics the in vivo growth of the human hepatocytes. The limited access to primary human hepatocytes necessitated the search for other cellular sources, such as pluripotent stem cells. Human embryonic stem cells (hESCs) have the features of self-renewal and pluripotency and differentiate into cells of all three germ layers, including hepatocytes. Humaninduced pluripotent stem cells (iPSCs) derived from the patient’s or individual’s own cells provide a novel opportunity to generate hepatocyte-like cells with the defined genetic composition. Here, we will review the current perspective of the models used for HBV and HCV study, and introduce the personalized mouse model using human iPSCs. This novel mouse model will facilitate the direct investigation of HBV and HCV in human hepatocytes as well as probing the genetic influence on the susceptibility of hepatocytes to HBV and HCV. PMID:22370780

  20. PATHS groundwater hydrologic model

    SciTech Connect

    Nelson, R.W.; Schur, J.A.

    1980-04-01

    A preliminary evaluation capability for two-dimensional groundwater pollution problems was developed as part of the Transport Modeling Task for the Waste Isolation Safety Assessment Program (WISAP). Our approach was to use the data limitations as a guide in setting the level of modeling detail. PATHS Groundwater Hydrologic Model is the first level (simplest) idealized hybrid analytical/numerical model for two-dimensional, saturated groundwater flow and single component transport; homogeneous geology. This document consists of the description of the PATHS groundwater hydrologic model. The preliminary evaluation capability prepared for WISAP, including the enhancements that were made because of the authors' experience using the earlier capability is described. Appendixes A through D supplement the report as follows: complete derivations of the background equations are provided in Appendix A. Appendix B is a comprehensive set of instructions for users of PATHS. It is written for users who have little or no experience with computers. Appendix C is for the programmer. It contains information on how input parameters are passed between programs in the system. It also contains program listings and test case listing. Appendix D is a definition of terms.

  1. Play with hydrologic models in R

    NASA Astrophysics Data System (ADS)

    Viglione, A.; Parajka, J.; Nester, T.; Blöschl, G.

    2012-04-01

    The aim of this poster is to show the advantages of building hydrologic models using the R environment for educational purposes. As an example we consider a conceptual rainfall-runoff model (HBV type) that was originally written in the fortran language and is used in many scientific studies and practical engineering applications in Austria. A simplified version of the model was built into a R package and compiled for different platforms and operating systems. The model runs on a daily time step and consists of a snow routine, a soil moisture routine and a flow routing routine. In this poster we present a set of examples that have been used in a graduate level course on engineering hydrology at the Vienna University of Technology. These include: - Multi-objective calibration of the model; - Manual vs. automatic calibration; - Visualisation of model outputs and efficiency; - Model application in ungauged catchments; - Operational 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.

  2. Optimal combinations of specialized conceptual hydrological models

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

    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

  3. Modeling and Analyzing the Transmission Dynamics of HBV Epidemic in Xinjiang, China

    PubMed Central

    Zhang, Tailei; Wang, Kai; Zhang, Xueliang

    2015-01-01

    Hepatitis B is an infectious disease caused by the hepatitis B virus (HBV) which affects livers. In this paper, we formulate a hepatitis B model to study the transmission dynamics of hepatitis B in Xinjiang, China. The epidemic model involves an exponential birth rate and vertical transmission. For a better understanding of HBV transmission dynamics, we analyze the dynamic behavior of the model. The modified reproductive number σ is obtained. When σ < 1, the disease-free equilibrium is locally asymptotically stable, when σ > 1, the disease-free equilibrium is unstable and the disease is uniformly persistent. In the simulation, parameters are chosen to fit public data in Xinjiang. The simulation indicates that the cumulated HBV infection number in Xinjiang will attain about 600,000 cases unless there are stronger or more effective control measures by the end of 2017. Sensitive analysis results show that enhancing the vaccination rate for newborns in Xinjiang is very effective to stop the transmission of HBV. Hence, we recommend that all infants in Xinjiang receive the hepatitis B vaccine as soon as possible after birth. PMID:26422614

  4. Sensitivity Analysis of a Conceptual HBV Raınfall-Runoff MODEL Using Eumetsat Snow Covered Area Product

    NASA Astrophysics Data System (ADS)

    Akyurek, Z.; Surer, S.; Parajka, J.

    2014-12-01

    HBV is a conceptual hydrological model extensively used in operational hydrological forecasting and water balance studies. In this study, we apply the HBV model on the upper Euphrates basin in Turkey, which has 10 624 km2 area. The Euphrates basin is largely fed from snow precipitation whereby nearly two-thirds occur in winter and may remain in the form of snow for half of the year. We analyze individual sensitivity of the parameters by calibrating the model using the Multi-Objective Shuffled Complex Evolution (MOSCEM) algorithm. The calibration is performed against snow cover area (SCA) in addition to runoff data for the water years 2009, 2010, 2011, 2012 and 2013. The SCA product has been developed in the framework of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) Project. The product is generated by using data from Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument making observations from a geostationary satellite Meteosat Second Generation (MSG). In the previous study evaluation of the model was done with commonly used statistical performance metrics (Nash-Sutcliffe) for high and low flows, volume error and root mean square error (RMSE). In this study signature metrics, which are based on the flow duration curve (FDC) are used to see the performance of the model for low flows. In order to consider a fairly balanced evaluation between high and low flow phases we divided the flow duration curve into segments of high, medium and low flow phases, and additionally into very high and very low phases. Root mean square error (RMSE) is used to evaluate the performance in these segments. The sensitivity analysis of the parameters around the calibrated optimum points showed that parameters of the soil moisture and evapotranspiration (FC, beta and LPrat) have a strong effect in the total volume error of the model. The

  5. HBV culture and infectious systems.

    PubMed

    Hayes, C Nelson; Chayama, Kazuaki

    2016-07-01

    While an effective vaccine against hepatitis B virus (HBV) has long been available, chronic HBV infection remains a severe global public health concern. Current treatment options have limited effectiveness, and long-term therapy is required to suppress HBV replication; however, complete elimination of the virus is rare. The lack of suitable animal models and infection systems has hindered efforts to unravel the HBV life cycle, particularly the early events in HBV entry, which appear to be highly species- and tissue-specific. Human primary hepatocytes remain the gold standard for HBV replication studies but are limited by availability and variability. While the HepaRG cell line is permissive for HBV replication, other hepatoma cell lines such as HepG2 do not support HBV replication. The recent discovery of sodium taurocholate transporting peptide (NTCP) as a primary receptor for HBV binding has led to the development of replication-competent cell lines such as HepG2-NTCP. Human hepatocytes grown in chimeric mice have provided another approach that allows primary human hepatocytes to be used while overcoming many of their limitations. Although the difficulty in developing HBV infection systems has hindered development of effective treatments, the variability and limited replication efficiency among cell lines point to additional liver-specific factors involved in HBV infection. It is hoped that HBV infection studies will lead to novel drug targets and therapeutic options for the treatment of chronic HBV infection. PMID:26935052

  6. Does model performance improve with complexity? A case study with three hydrological models

    NASA Astrophysics Data System (ADS)

    Orth, Rene; Staudinger, Maria; Seneviratne, Sonia I.; Seibert, Jan; Zappa, Massimiliano

    2015-04-01

    In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisti- cated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for predic- tion of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better perfor- mance in lower altitudes as opposed to (pre-)alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs

  7. Does model performance improve with complexity? A case study with three hydrological models

    NASA Astrophysics Data System (ADS)

    Orth, Rene; Staudinger, Maria; Seneviratne, Sonia I.; Seibert, Jan; Zappa, Massimiliano

    2015-04-01

    In recent decades considerable progress has been made in climate model development. Following the massive increase in computational power, models became more sophisticated. At the same time also simple conceptual models have advanced. In this study we validate and compare three hydrological models of different complexity to investigate whether their performance varies accordingly. For this purpose we use runoff and also soil moisture measurements, which allow a truly independent validation, from several sites across Switzerland. The models are calibrated in similar ways with the same runoff data. Our results show that the more complex models HBV and PREVAH outperform the simple water balance model (SWBM) in case of runoff but not for soil moisture. Furthermore the most sophisticated PREVAH model shows an added value compared to the HBV model only in case of soil moisture. Focusing on extreme events we find generally improved performance of the SWBM during drought conditions and degraded agreement with observations during wet extremes. For the more complex models we find the opposite behavior, probably because they were primarily developed for prediction of runoff extremes. As expected given their complexity, HBV and PREVAH have more problems with over-fitting. All models show a tendency towards better performance in lower altitudes as opposed to (pre-) alpine sites. The results vary considerably across the investigated sites. In contrast, the different metrics we consider to estimate the agreement between models and observations lead to similar conclusions, indicating that the performance of the considered models is similar at different time scales as well as for anomalies and long-term means. We conclude that added complexity does not necessarily lead to improved performance of hydrological models, and that performance can vary greatly depending on the considered hydrological variable (e.g. runoff vs. soil moisture) or hydrological conditions (floods vs. droughts).

  8. Snow hydrology of a headwater Arctic basin. 2. Conceptual analysis and computer modeling

    SciTech Connect

    Hinzman, L.D.; Kane, D.L. )

    1991-06-01

    Lack of hydrologic data in the Arctic, particularly during snowmelt, severely limits modeling strategy. Spring snowmelt in Imnavait watershed is a very brief event, usually lasting about 10 days. Peak flow normally occurs within the top 10 cm of the highly organic soil mat or on the surface. Snow damming of snowmelt runoff is an important mechanism which must be considered in the modeling process of small watersheds. These unique characteristics of Arctic hydrology will affect the methodology and performance of a hydrologic model. The HBV model was used in an investigation of the hydrologic regime of an Arctic watershed during the spring snowmelt period. From the analysis of five spring melt events the authors found that HBV can adequately predict soil moisture, evaporation, snow ablation and accumulation, and runoff. It models the volumes of snowmelt runoff well, but more data are needed to improve the determination of snowmelt initiation. Use of HBV as a predictive tool is dependent upon the quality of the meteorologic forecast data.

  9. The influence of HBV model calibration on flood predictions for future climate

    NASA Astrophysics Data System (ADS)

    Osuch, Marzena; Romanowicz, Renata

    2014-05-01

    The temporal variability of HBV rainfall-runoff model parameters was tested to address the influence of climate characteristics on the values of model optimal parameters. HBV is a conceptual model with a physically-based structure that takes into account soil moisture, snow-melt and dynamic runoff components. The model parameters were optimized by the DEGL method (Differential Evolution with Global and Local neighbours) for a set of catchments located in Poland. The methodology consisted of the calibration and cross-validation of the HBV models on a series of five-year periods within a moving window. The optimal parameter values show large temporal variability and dependence on climatic conditions described by the mean and standard deviation of precipitation, air temperature and PET. Derived regressions models between parameters and climatic indices were statistically significant at the 0.05 level. The set of model optimal values was applied to simulate future flows in a changed climate. We used the precipitation and temperature series from 6 RCM/GCM models for 2071-2100 following the A1B climate change scenario. The climatic variables were obtained from the KLIMADA project. The resulting flow series for the future climate scenario were used to derive flow indices, including the flood quantiles. Results indicate a large influence of climatic variability on flow indices. This work was partly supported by the project "Stochastic flood forecasting system (The River Vistula reach from Zawichost to Warsaw)" carried out by the Institute of Geophysics, Polish Academy of Sciences by order of the National Science Centre (contract No. 2011/01/B/ST10/06866). The rainfall and flow data were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

  10. Importance of temporal and spatial resolution on modelling hydrological extremes in a small catchment

    NASA Astrophysics Data System (ADS)

    Strouhal, L.; Seibert, J.; David, V.

    2012-04-01

    Under the conditions of changing climate the more frequent extremes in hydrological regime are expected. For the small watershed management it is therefore of big interest what the possible range of these changes could be, since it is essential for design of appropriate mitigation measures. An exemplary case study of possible impacts of the climate change was carried out. The conceptual model HBV was applied in a small hilly pre-alpine Rietholzbach catchment with the aim to assess the frequency and magnitude of hydrological extremes under different climatic conditions. The effect of the time and spatial distribution on the model output characteristics was also investigated. For impact evaluation a conceptual lumped model HBV was chosen because of its robustness, easy applicability for long-term simulations and perceptually straight-forward parameters. Two different modelling approaches were used, in the first one the catchment of interest was treated as a lumped system and in the other where it was divided into several subcatchments. As a first step HBV was applied to the historical data set to evaluate his performance and suitability for hydrological predictions. One half of the data time-series was used for HBV parameter calibration, the other one for model validation, wherefore several objective functions were used for goodness of fit evaluation. In order to obtain the range of changes in hydrological characteristics which can be expected due to the changing climate, two extreme scenarios were then applied to the catchment model. A standard daily step was used to obtain data for water balance and long-term droughts analysis and a study of applicability of the model with the hourly computational step was performed, so that occurrance of maximum discharges could be evaluated. The poster presents the model outcomes with focus on flood and long-drought characteristics. The uncertainty of the impacts is illustrated by the range of characteristics obtained from

  11. Model Calibration in Watershed Hydrology

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

    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.

  12. A physical interpretation of hydrologic model complexity

    NASA Astrophysics Data System (ADS)

    Moayeri, MohamadMehdi; Pande, Saket

    2015-04-01

    It is intuitive that instability of hydrological system representation, in the sense of how perturbations in input forcings translate into perturbation in a hydrologic response, may depend on its hydrological characteristics. Responses of unstable systems are thus complex to model. We interpret complexity in this context and define complexity as a measure of instability in hydrological system representation. We provide algorithms to quantify model complexity in this context. We use Sacramento soil moisture accounting model (SAC-SMA) parameterized for MOPEX basins and quantify complexities of corresponding models. Relationships between hydrologic characteristics of MOPEX basins such as location, precipitation seasonality index, slope, hydrologic ratios, saturated hydraulic conductivity and NDVI and respective model complexities are then investigated. We hypothesize that complexities of basin specific SAC-SMA models correspond to aforementioned hydrologic characteristics, thereby suggesting that model complexity, in the context presented here, may have a physical interpretation.

  13. Attribution of hydrologic trends using integrated hydrologic and economic models

    NASA Astrophysics Data System (ADS)

    Maneta, M. P.; Brugger, D. R.; Silverman, N. L.

    2014-12-01

    Hydrologic change has been detected in many regions of the world in the form of trends in annual streamflows, varying depths to the regional water table, or other alterations of the hydrologic balance. Most models used to investigate these changes implement sophisticated descriptions of the physical system but use simplified descriptions of the socioeconomic system. These simplifications come in the form of prescribed water diversions and land use change scenarios, which provide little insight into coupled natural-human systems and have limited predictive capabilities. We present an integrated model that adds realism to the description of the hydrologic system in agricultural regions by incorporating a component that updates the allocation of land and water to crops in response to hydroclimatic (water available) and economic conditions (prices of commodities and agricultural inputs). This component assumes that farmers allocate resources to maximize their net revenues, thus justifying the use of optimality conditions to constrain the parameters of an empirical production function that captures the economic behavior of farmers. Because the model internalizes the feedback between climate, agricultural markets, and farming activity into the hydrologic system, it can be used to understand to what extent human economic activity can exacerbate or buffer the regional hydrologic impacts of climate change in agricultural regions. It can also help in the attribution of causes of hydrologic change. These are important issues because local policy and management cannot solve climate change, but they can address land use and agricultural water use. We demonstrate the model in a case study.

  14. Committee of machine learning predictors of hydrological models uncertainty

    NASA Astrophysics Data System (ADS)

    Kayastha, Nagendra; Solomatine, Dimitri

    2014-05-01

    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

  15. A new multiparameter integrated MELD model for prognosis of HBV-related acute-on-chronic liver failure.

    PubMed

    Luo, Yue; Xu, Yun; Li, Mingming; Xie, Ya; Gong, Guozhong

    2016-08-01

    Hepatitis B virus related acute-on-chronic liver failure (HBV-ACLF) is one of the most deadly diseases. Many models have been proposed to evaluate the prognosis of it. However, these models are still controversial. In this study, we aimed to incorporate some characters into model for end-stage liver disease (MELD) to establish a new reliable and feasible model for the prognosis of HBV-ACLF.A total of 530 HBV-ACLF patients who had received antiviral therapy were enrolled into a retrospective study and divided into the training cohort (300) and validation cohort (230). Logistic regression analysis was used to establish a model to predict the 3-month mortality from the patients in the training cohort, and then, the new model was evaluated in the validation cohort.Except for MELD score, 4 other independent factors, namely degree of hepatic encephalopathy (HE), alpha-fetoprotein (AFP), white blood cell (WBC) count, and age, were important for the new model called HBV-ACLF MELD (HAM) model: R = 0.174 × MELD + 1.106 × HE - (0.003 × AFP) + (0.237 × WBC) + (0.103 × Age) - 11.388. The areas under receiver-operating characteristic curve of HAM in the training and validation cohort were 0.894 and 0.868, respectively, which were significantly higher than those of other 7 models. With the best cut-off value of -1.191, HAM achieved higher sensitivity and negative predictive value.We developed a new model that has a great prognostic value of the 3-month mortality of patients with HBV-ACLF. PMID:27559979

  16. Cost-Effectiveness of HBV and HCV Screening Strategies – A Systematic Review of Existing Modelling Techniques

    PubMed Central

    Geue, Claudia; Wu, Olivia; Xin, Yiqiao; Heggie, Robert; Hutchinson, Sharon; Martin, Natasha K.; Fenwick, Elisabeth; Goldberg, David

    2015-01-01

    Introduction Studies evaluating the cost-effectiveness of screening for Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) are generally heterogeneous in terms of risk groups, settings, screening intervention, outcomes and the economic modelling framework. It is therefore difficult to compare cost-effectiveness results between studies. This systematic review aims to summarise and critically assess existing economic models for HBV and HCV in order to identify the main methodological differences in modelling approaches. Methods A structured search strategy was developed and a systematic review carried out. A critical assessment of the decision-analytic models was carried out according to the guidelines and framework developed for assessment of decision-analytic models in Health Technology Assessment of health care interventions. Results The overall approach to analysing the cost-effectiveness of screening strategies was found to be broadly consistent for HBV and HCV. However, modelling parameters and related structure differed between models, producing different results. More recent publications performed better against a performance matrix, evaluating model components and methodology. Conclusion When assessing screening strategies for HBV and HCV infection, the focus should be on more recent studies, which applied the latest treatment regimes, test methods and had better and more complete data on which to base their models. In addition to parameter selection and associated assumptions, careful consideration of dynamic versus static modelling is recommended. Future research may want to focus on these methodological issues. In addition, the ability to evaluate screening strategies for multiple infectious diseases, (HCV and HIV at the same time) might prove important for decision makers. PMID:26689908

  17. HBV cure: why, how, when?

    PubMed

    Levrero, Massimo; Testoni, Barbara; Zoulim, Fabien

    2016-06-01

    Current HBV treatments control replication and liver disease progression in the vast majority of treated patients. However, HBV patients often require lifelong therapies due to the persistence of transcriptionally active viral cccDNA mini-chromosome in the nucleus, which is not directly targeted by current antiviral therapies. A true complete cure of HBV would require clearance of intranuclear cccDNA from all infected hepatocytes. An intermediate but still relevant step forward that would allow treatment cessation would be reaching a functional cure, equivalent to resolved acute infection, with a durable HBsAg loss±anti-HBs seroconversion, undetectable serum DNA and persistence of cccDNA in a transcriptionally inactive status. Recent advances in technologies and pharmaceutical sciences, including the cloning of the mayor HBV receptor (i.e. the NTCP transporter) and the development in vitro HBV infection models, have heralded a new horizon of innovative antiviral and immune-therapeutic approaches. PMID:27447092

  18. Remote sensing applications to hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

    1977-01-01

    An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

  19. Simulated discharge trends indicate robustness of hydrological models in a changing climate

    NASA Astrophysics Data System (ADS)

    Addor, Nans; Nikolova, Silviya; Seibert, Jan

    2016-04-01

    Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant

  20. Application of hydrologic forecast model.

    PubMed

    Hua, Xu; Hengxin, Xue; Zhiguo, Chen

    2012-01-01

    In order to overcome the shortcoming of the solution may be trapped into the local minimization in the traditional TSK (Takagi-Sugeno-Kang) fuzzy inference training, this paper attempts to consider the TSK fuzzy system modeling approach based on the visual system principle and the Weber law. This approach not only utilizes the strong capability of identifying objects of human eyes, but also considers the distribution structure of the training data set in parameter regulation. In order to overcome the shortcoming of it adopting the gradient learning algorithm with slow convergence rate, a novel visual TSK fuzzy system model based on evolutional learning is proposed by introducing the particle swarm optimization algorithm. The main advantage of this method lies in its very good optimization, very strong noise immunity and very good interpretability. The new method is applied to long-term hydrological forecasting examples. The simulation results show that the method is feasible and effective, the new method not only inherits the advantages of traditional visual TSK fuzzy models but also has the better global convergence and accuracy than the traditional model. PMID:22699326

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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

  2. Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty

    NASA Astrophysics Data System (ADS)

    Moges, Edom; Demissie, Yonas; Li, Hong-Yi

    2016-04-01

    In most water resources applications, any particular model structure might be inadequate to capture the dynamic multiscale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses were used to identify the presence of multiple dominant processes, and the adequacy of a single model, as well as to develop the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

  3. Hydrological modeling as an evaluation tool of EURO-CORDEX RCMs and bias correction methods

    NASA Astrophysics Data System (ADS)

    Hakala, Kirsti; Seibert, Jan; Addor, Nans

    2016-04-01

    This research explores the impacts of climate change on catchment discharge and addresses the challenge of characterizing and communicating their uncertainties. It particularly focuses on the integrated evaluation of EURO-CORDEX regional climate model simulations, using hydrological modeling at the catchment scale. For the evaluation of the various RCMs combined with different bias correction operations there are two main approaches: 1) Separate evaluation of the statistical properties of each climate variable in terms of its statistical properties such as annual mean, seasonal variation, frequency of extreme events. This first approach is the standard way to evaluate RCM runs and bias correction methods. It also prevails by far in the literature. Here we introduce an alternative evaluation approach, which relies on hydrological modeling, 2) Combined evaluation of the different variables at the catchment scale; that is the evaluation is based on hydrological simulation results, which integrate the different variables (mainly temperature, precipitation and evaporation). Although more time demanding, this second approach has a critical advantage in that it allows a focus on the statistical properties of the climate variables which are most important for catchment-scale runoff. We rely on the semi-distributed hydrological model HBV and apply it to Swiss catchments representative of different hydrological regimes and expected responses to climate change. This research investigates both approaches, however the second approach will be discussed in greater depth as an elegant way to consider the multitude of factors relevant for hydrological modeling all at once.

  4. Comparison of global optimization approaches for robust calibration of hydrologic model parameters

    NASA Astrophysics Data System (ADS)

    Jung, I. W.

    2015-12-01

    Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

  5. Hydrologic Modeling of Boreal Forest Ecosystems

    NASA Technical Reports Server (NTRS)

    Haddeland, I.; Lettenmaier, D. P.

    1995-01-01

    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).

  6. Snow Hydrology in a General Circulation Model.

    NASA Astrophysics Data System (ADS)

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

    1994-08-01

    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 snow pack. 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.

  7. Snow hydrology in a general circulation model

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

    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.

  8. Hierarchical Mixture of Experts and Diagnostic Modeling Approach to Reduce Hydrologic Model Structural Uncertainty

    NASA Astrophysics Data System (ADS)

    Moges, E. M.; Demissie, Y.; Li, H. Y.

    2014-12-01

    The choice of hydrologic model structures is one of the sources of uncertainty in representing hydrological process. In most applications, a single comprehensive hydrologic model structure might not be able to capture the entire complex and multi-scale interactions among the different components of the hydrologic process adequately. Calibrating such model can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased parameter values. An alternative to a single model structure is to develop local expert structures that are well suited in representing specific components of the hydrologic system and adaptively integrate them based on an indicator state variable. In this study, the Hierarchical Mixture of Experts (HME) architecture with a modified gating network function is applied to integrate two runoff module structures of the HBV model. The runoff module structures (i.e., buckets number and orientation) are proposed based on their expertise in representing recession flow and flow duration curve. This process based diagnostic framework of local experts provides a skilled platform for HME to effectively capture each distinct characteristic of the hydrograph and stochastically adapt to catchment response through soil moisture as an indicator variable. The approach is tested using two previously studied catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX). The results show that the HME approach has a better performance over a single model for both catchments in terms of the Nash Sutcliffe and correlation coefficient. Furthermore, we have developed and applied a comprehensive performance assessment matrix based on information theory to evaluate the differences between model and observation in terms of different characteristics of the hydrograph.

  9. Effect of different uncertainty sources on the skill of 10 day ensemble low flow forecasts for two hydrological models

    NASA Astrophysics Data System (ADS)

    Demirel, Mehmet C.; Booij, Martijn J.; Hoekstra, Arjen Y.

    2013-07-01

    This paper aims to investigate the effect of uncertainty originating from model inputs, parameters and initial conditions on 10 day ensemble low flow forecasts. Two hydrological models, GR4J and HBV, are applied to the Moselle River and performance in the calibration, validation and forecast periods, and the effect of different uncertainty sources on the quality of low flow forecasts are compared. The forecasts are generated by using meteorological ensemble forecasts as input to GR4J and HBV. The ensembles provided the uncertainty range for the model inputs. The Generalized Likelihood Uncertainty Estimation (GLUE) approach is used to estimate parameter uncertainty. The quality of the probabilistic low flow forecasts has been assessed by the relative confidence interval, reliability and hit/false alarm rates. The daily observed low flows are mostly captured by the 90% confidence interval for both models. However, GR4J usually overestimates low flows whereas HBV is prone to underestimate them, particularly when the parameter uncertainty is included in the forecasts. The total uncertainty in GR4J outputs is higher than in HBV. The forecasts issued by HBV incorporating input uncertainty resulted in the most reliable forecast distribution. The parameter uncertainty was the main reason reducing the number of hits. The number of false alarms in GR4J is twice the number of false alarms in HBV when considering all uncertainty sources. The results of this study showed that the parameter uncertainty has the largest effect whereas the input uncertainty had the smallest effect on the medium range low flow forecasts.

  10. Inter-comparison of subglacial hydrological models

    NASA Astrophysics Data System (ADS)

    de Fleurian, Basile; Werder, Mauro

    2016-04-01

    The recent emergence of a number of subglacial hydrological models allows us to obtain theoretical insights on basal processes; for instance on the coupling between water pressure and the sliding of glaciers. In ice-flow models, it is relatively clear what the simulated physics ought to be. Conversely, the physical processes incorporated into subglacial hydrology models are diverse as it is yet unclear which ones are of relevance for a particular setting. An inter-comparison of hydrology models will therefore need a somewhat different approach to the one used in the many ice-flow model inter-comparisons (EISMINT, ISMIP, etc.). Here, we present a set of experiments that will allow the comparison of the behavior of different hydrology models. The design of the benchmark aims at allowing the participation of a wide range of models based on different physical approaches. We aim at evaluating the models with a focus on the effective pressure which has the most impact on the dynamics of glaciers. The aim of this inter-comparison is to provide modellers with the necessary data to make an informed decision on which subglacial hydrology model to use for a particular study.

  11. Accelerating advances in continental domain hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Archfield, Stacey A.; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew; Wagener, Thorsten; Farmer, William H.; Andréassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas

    2015-12-01

    In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

  12. Streamflow data assimilation for the mesoscale hydrologic model (mHM) using particle filtering

    NASA Astrophysics Data System (ADS)

    Noh, Seong Jin; Rakovec, Oldrich; Kumar, Rohini; Samaniego, Luis; Choi, Shin-woo

    2015-04-01

    Data assimilation has been becoming popular to increase the certainty of the hydrologic prediction considering various sources of uncertainty through the hydrologic modeling chain. In this study, we develop a data assimilation framework for the mesoscale hydrologic model (mHM 5.2, http://www.ufz.de/mhm) using particle filtering, which is a sequential DA method for non-linear and non-Gaussian models. The mHM is a grid based distributed model that is based on numerical approximations of dominant hydrologic processes having similarity with the HBV and VIC models. The developed DA framework for the mHM represents simulation uncertainty by model ensembles and updates spatial distributions of model state variables when new observations are available in each updating time interval. The evaluation of the proposed method is carried out within several large European basins via assimilating multiple streamflow measurements in a daily interval. Dimensional limitations of particle filtering is resolved by effective noise specification methods, which uses spatial and temporal correlation of weather forcing data to represent model structural uncertainty. The presentation will be focused on gains and limitations of streamflow data assimilation in several hindcasting experiments. In addition, impacts of non-Gaussian distributions of state variables on model performance will be discussed.

  13. On the Use of Models in Hydrology.

    ERIC Educational Resources Information Center

    de Marsily, G.

    1994-01-01

    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)

  14. Dynamic Multicriteria Evaluation of Conceptual Hydrological Models

    NASA Astrophysics Data System (ADS)

    de Vos, N. J.; Rientjes, T. H.; Fenicia, F.; Gupta, H. V.

    2007-12-01

    Accurate and precise forecasts of river streamflows are crucial for successful management of water resources and under the threat of hydrological extremes such as floods and droughts. Conceptual rainfall-runoff models are the most popular approach in flood forecasting. However, the calibration and evaluation of such models is often oversimplified by the use of performance statistics that largely ignore the dynamic character of a watershed system. This research aims to find novel ways of model evaluation by identifying periods of hydrologic similarity and customizing evaluation within each period using multiple criteria. A dynamic approach to hydrologic model identification, calibration and testing can be realized by applying clustering algorithms (e.g., Self-Organizing Map, Fuzzy C-means algorithm) to hydrological data. These algorithms are able to identify clusters in the data that represent periods of hydrological similarity. In this way, dynamic catchment system behavior can be simplified within the clusters that are identified. Although clustering requires a number of subjective choices, new insights into the hydrological functioning of a catchment can be obtained. Finally, separate model multi-criteria calibration and evaluation is performed for each of the clusters. Such a model evaluation procedure shows to be reliable and gives much-needed feedback on exactly where certain model structures fail. Several clustering algorithms were tested on two data sets of meso-scale and large-scale catchments. The results show that the clustering algorithms define categories that reflect hydrological process understanding: dry/wet seasons, rising/falling hydrograph limbs, precipitation-driven/ non-driven periods, etc. The results of various clustering algorithms are compared and validated using expert knowledge. Calibration results on a conceptual hydrological model show that the common practice of single-criteria calibration over the complete time series fails to perform

  15. Balancing model complexity and measurements in hydrology

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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

  16. Improving hydrology models for a changing climate

    NASA Astrophysics Data System (ADS)

    Palus, Shannon

    2014-12-01

    Changes over time in the relationship between rainfall and catchment runoff pose a significant challenge for hydrological models, which are often calibrated under the assumption that the future relationship will be consistent with that of the past. In a recent paper, Westra et al. outlined a method for diagnosing, interpreting, and improving the capacity of models to develop predictions under such conditions.

  17. Treatments of Precipitation Inputs to Hydrologic Models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrological models are used to assess many water resources problems from agricultural use and water quality to engineering issues. The success of these models are dependent on correct parameterization; the most sensitive being the rainfall input time series. These records can come from land-based ...

  18. Hydrological Modeling and Repeatability with Brokering

    NASA Astrophysics Data System (ADS)

    Easton, Z. M.; Collick, A.; Srinivasan, R.; Braeckel, A.; Nativi, S.; McAlister, C.; Wright, D. J.; Khalsa, S. J. S.; Fuka, D.

    2014-12-01

    Data brokering aims to provide those in the hydrological sciences with access to relevant data to represent physical, biological, and chemical characteristics researchers need to accelerate discovery in their domain. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these models requires many different data sources from different disciplines (e.g., atmospheric, geoscience, ecology). In hydrological modeling, the traditional procedure for model initialization starts with obtaining elevation models, land-use characterizations, soils maps, and weather data. It is often the researcher's past experience with these datasets that determines which datasets will be used in a study, and often newer, more suitable data products exist. An added complexity is that various science communities have differing data formats, storage protocols and manipulation methods, which makes use by a non domain scientist difficult and time consuming. We propose data brokering as a means to address several of these challenges. We present two test case scenarios in which researchers attempt to reproduce hydrological model results using 1) general internet based data gathering techniques, and 2) a scientific data brokering interface. We show that data brokering increases the efficiency with which data are collected, models are initialized, and results are analyzed. As an added benefit, it appears brokering significantly increases the repeatability of a study.

  19. Multi-criteria evaluation of hydrological models

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    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

  20. Approaches to modelling hydrology and ecosystem interactions

    NASA Astrophysics Data System (ADS)

    Silberstein, Richard P.

    2014-05-01

    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.

  1. Comparison of complex and parsimonious model structures by means of a modular hydrological model concept

    NASA Astrophysics Data System (ADS)

    Holzmann, Hubert; Massmann, Carolina

    2015-04-01

    A plenty of hydrological model types have been developed during the past decades. Most of them used a fixed design to describe the variable hydrological processes assuming to be representative for the whole range of spatial and temporal scales. This assumption is questionable as it is evident, that the runoff formation process is driven by dominant processes which can vary among different basins. Furthermore the model application and the interpretation of results is limited by data availability to identify the particular sub-processes, since most models were calibrated and validated only with discharge data. Therefore it can be hypothesized, that simpler model designs, focusing only on the dominant processes, can achieve comparable results with the benefit of less parameters. In the current contribution a modular model concept will be introduced, which allows the integration and neglection of hydrological sub-processes depending on the catchment characteristics and data availability. Key elements of the process modules refer to (1) storage effects (interception, soil), (2) transfer processes (routing), (3) threshold processes (percolation, saturation overland flow) and (4) split processes (rainfall excess). Based on hydro-meteorological observations in an experimental catchment in the Slovak region of the Carpathian mountains a comparison of several model realizations with different degrees of complexity will be discussed. A special focus is given on model parameter sensitivity estimated by Markov Chain Monte Carlo approach. Furthermore the identification of dominant processes by means of Sobol's method is introduced. It could be shown that a flexible model design - and even the simple concept - can reach comparable and equivalent performance than the standard model type (HBV-type). The main benefit of the modular concept is the individual adaptation of the model structure with respect to data and process availability and the option for parsimonious model design.

  2. Detecting hydrological changes through conceptual model

    NASA Astrophysics Data System (ADS)

    Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

    2015-04-01

    Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General

  3. Inverse distributed hydrological modelling of Alpine catchments

    NASA Astrophysics Data System (ADS)

    Kunstmann, H.; Krause, J.; Mayr, S.

    2006-06-01

    Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2 in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. Application of a 2-dimensional numerical

  4. Catchment classification by means of hydrological models

    NASA Astrophysics Data System (ADS)

    Hellebrand, Hugo; Ley, Rita; Casper, Markus

    2013-04-01

    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

  5. Inverse distributed hydrological modelling of alpine catchments

    NASA Astrophysics Data System (ADS)

    Kunstmann, H.; Krause, J.; Mayr, S.

    2005-12-01

    Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2) in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. A detailed covariance analysis was performed

  6. TUWmodel: an educational hydrologic model in R

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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.

  7. Application of SMOS and ASCAT soil moisture estimations to hydrological modelling in Serbia

    NASA Astrophysics Data System (ADS)

    Zlatanovic, Nikola; Ivkovic, Marija; Drobnjak, Aleksandar

    2016-04-01

    This study explores the performance of satellite-based soil moisture products from satellites SMOS (Soil Moisture and Ocean Salinity, measuring brightness temperatures in the L-Band at 1.4 GHz) and ASCAT (Advanced SCATterometer, measuring surface backscattering coefficients in the C-band at 5.255 GHz) for hydrological application. Firstly, SMOS and ASCAT Level 2 soil moisture data were compared to in situ data over Serbia at available sites. All available in situ ground-based point measurements of soil moisture, from the Republic Hydrometeorological Service of Serbia and other independent stations, were collected for the overlapping period with satellite observations and compared against remotely sensed satellite-based soil moisture products. Two approaches are presented in this study to evaluate the applicability of satellite-based SMOS and ASCAT soil moisture products to basin-scale hydrological modelling in a case study catchment in Serbia. The first approach was based on a continuous conceptual forecast-based rainfall-runoff model (using distributed HBV model), where satellite-based soil moisture data helped perform corrections to calculated model soil moisture. The second approach analysed individual event-based rainfall-runoff modelling (using HEC-HMS), where initial (pre-event) model parameters were estimated using satellite-based soil moisture data. Both approaches involved calibration of the hydrological models with and without satellite-based soil moisture data on a case study in Serbia.

  8. Assimilating GRACE terrestrial water storage data into a conceptual hydrology model for the River Rhine

    NASA Astrophysics Data System (ADS)

    Widiastuti, E.; Steele-Dunne, S. C.; Gunter, B.; Weerts, A.; van de Giesen, N.

    2009-12-01

    Terrestrial water storage (TWS) is a key component of the terrestrial and global hydrological cycles, and plays a major role in the Earth’s climate. The Gravity Recovery and Climate Experiment (GRACE) twin satellite mission provided the first space-based dataset of TWS variations, albeit with coarse resolution and limited accuracy. Here, we examine the value of assimilating GRACE observations into a well-calibrated conceptual hydrology model of the Rhine river basin. In this study, the ensemble Kalman filter (EnKF) and smoother (EnKS) were applied to assimilate the GRACE TWS variation data into the HBV-96 rainfall run-off model, from February 2003 to December 2006. Two GRACE datasets were used, the DMT-1 models produced at TU Delft, and the CSR-RL04 models produced by UT-Austin . Each center uses its own data processing and filtering methods, yielding two different estimates of TWS variations and therefore two sets of assimilated TWS estimates. To validate the results, the model estimated discharge after the data assimilation was compared with measured discharge at several stations. As expected, the updated TWS was generally somewhere between the modeled and observed TWS in both experiments and the variance was also lower than both the prior error covariance and the assumed GRACE observation error. However, the impact on the discharge was found to depend heavily on the assimilation strategy used, in particular on how the TWS increments were applied to the individual storage terms of the hydrology model.

  9. Global-scale regionalization of hydrological model parameters using streamflow data from many small catchments

    NASA Astrophysics Data System (ADS)

    Beck, Hylke; de Roo, Ad; van Dijk, Albert; McVicar, Tim; Miralles, Diego; Schellekens, Jaap; Bruijnzeel, Sampurno; de Jeu, Richard

    2015-04-01

    Motivated by the lack of large-scale model parameter regionalization studies, a large set of 3328 small catchments (< 10000 km2) around the globe was used to set up and evaluate five model parameterization schemes at global scale. The HBV-light model was chosen because of its parsimony and flexibility to test the schemes. The catchments were calibrated against observed streamflow (Q) using an objective function incorporating both behavioral and goodness-of-fit measures, after which the catchment set was split into subsets of 1215 donor and 2113 evaluation catchments based on the calibration performance. The donor catchments were subsequently used to derive parameter sets that were transferred to similar grid cells based on a similarity measure incorporating climatic and physiographic characteristics, thereby producing parameter maps with global coverage. Overall, there was a lack of suitable donor catchments for mountainous and tropical environments. The schemes with spatially-uniform parameter sets (EXP2 and EXP3) achieved the worst Q estimation performance in the evaluation catchments, emphasizing the importance of parameter regionalization. The direct transfer of calibrated parameter sets from donor catchments to similar grid cells (scheme EXP1) performed best, although there was still a large performance gap between EXP1 and HBV-light calibrated against observed Q. The schemes with parameter sets obtained by simultaneously calibrating clusters of similar donor catchments (NC10 and NC58) performed worse than EXP1. The relatively poor Q estimation performance achieved by two (uncalibrated) macro-scale hydrological models suggests there is considerable merit in regionalizing the parameters of such models. The global HBV-light parameter maps and ancillary data are freely available via http://water.jrc.ec.europa.eu.

  10. Optimizing hydrological consistency by incorporating hydrological signatures into model calibration objectives

    NASA Astrophysics Data System (ADS)

    Shafii, Mahyar; Tolson, Bryan A.

    2015-05-01

    The simulated outcome of a calibrated hydrologic model should be hydrologically consistent with the measured response data. Hydrologic modelers typically calibrate models to optimize residual-based goodness-of-fit measures, e.g., the Nash-Sutcliffe efficiency measure, and then evaluate the obtained results with respect to hydrological signatures, e.g., the flow duration curve indices. The literature indicates that the consideration of a large number of hydrologic signatures has not been addressed in a full multiobjective optimization context. This research develops a model calibration methodology to achieve hydrological consistency using goodness-of-fit measures, many hydrological signatures, as well as a level of acceptability for each signature. The proposed framework relies on a scoring method that transforms any hydrological signature to a calibration objective. These scores are used to develop the hydrological consistency metric, which is maximized to obtain hydrologically consistent parameter sets during calibration. This consistency metric is implemented in different signature-based calibration formulations that adapt the sampling according to hydrologic signature values. These formulations are compared with the traditional formulations found in the literature for seven case studies. The results reveal that Pareto dominance-based multiobjective optimization yields the highest level of consistency among all formulations. Furthermore, it is found that the choice of optimization algorithms does not affect the findings of this research.

  11. Improving subsurface hydrology in Earth System Models

    NASA Astrophysics Data System (ADS)

    Volk, J. M.; Clark, M. P.; Swenson, S. C.; Lawrence, D. M.; Tyler, S. W.

    2015-12-01

    Hydrologic processes that govern storage and transport of soil water and groundwater can have strong dynamic relationships with biogeochemical and atmospheric processes. This understanding has lead to a push to improve subsurface hydrologic parametrization in Earth System Models. Here we present results related to improving the implementation of soil moisture distribution, groundwater recharge/discharge, and subsurface drainage in the Community Land Model (CLM) which is the land surface model in the Community Earth System Model. First we identified geo-climatically different locations around the world to develop test cases. For each case we compare the vertical soil moisture distribution from the different implementations of 1D Richards equation, considering the boundary conditions, the treatment of the groundwater sink term, the vertical discretization, and the time stepping schemes. Generally, large errors in the hydrologic mass balance within the soil column occur when there is a large vertical gradient in soil moisture or when there is a shallow water table within a soil column. We then test the sensitivity of the algorithmic parameters that control temporal discretization and error tolerance of the adaptive time-stepping scheme to help optimize its computational efficiency. In addition, we vary the spatial discretization of soil layers (i.e. quantity of layers and their thicknesses) to better understand the sensitivity of vertical discretization of soil columns on soil moisture variability in ESMs. We present multivariate and multi-scale evaluation for the different model options and suggest ways to move forward with future model improvements.

  12. Towards Better Coupling of Hydrological Simulation Models

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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

  13. The value of multiple data set calibration versus model complexity for improving the performance of hydrological models in mountain catchments

    NASA Astrophysics Data System (ADS)

    Finger, David; Vis, Marc; Huss, Matthias; Seibert, Jan

    2015-04-01

    The assessment of snow, glacier, and rainfall runoff contribution to discharge in mountain streams is of major importance for an adequate water resource management. Such contributions can be estimated via hydrological models, provided that the modeling adequately accounts for snow and glacier melt, as well as rainfall runoff. We present a multiple data set calibration approach to estimate runoff composition using hydrological models with three levels of complexity. For this purpose, the code of the conceptual runoff model HBV-light was enhanced to allow calibration and validation of simulations against glacier mass balances, satellite-derived snow cover area and measured discharge. Three levels of complexity of the model were applied to glacierized catchments in Switzerland, ranging from 39 to 103 km2. The results indicate that all three observational data sets are reproduced adequately by the model, allowing an accurate estimation of the runoff composition in the three mountain streams. However, calibration against only runoff leads to unrealistic snow and glacier melt rates. Based on these results, we recommend using all three observational data sets in order to constrain model parameters and compute snow, glacier, and rain contributions. Finally, based on the comparison of model performance of different complexities, we postulate that the availability and use of different data sets to calibrate hydrological models might be more important than model complexity to achieve realistic estimations of runoff composition.

  14. Enhancements for Hydrological Modeling in ESMF

    NASA Astrophysics Data System (ADS)

    Deluca, C.; Oehmke, R.; Neckels, D.; Theurich, G.; O'Kuinghttons, R.; de Fainchtein, R.; Murphy, S.; Dunlap, R.

    2008-12-01

    Hydrological systems connect Earth's global physical phenomena with the local environmental impacts that affect our food, health, finances, and homes. The scales and processes that hydrological modelers must span are reflected in the challenges of developing infrastructure for this community. The basic requirements - the need to assemble and couple model components, the need for efficient I/O, the need for integrated visualization, analysis, and data services - are shared with other domains, such as climate and space weather. Where hydrology goes beyond other domains is in its terrific heterogeneity. The diversity of models, data structures, grids, computing platforms, computing languages, and specialized sub-domains involved is daunting. It's not surprising that the hydrological community has spawned a variety of different integrative efforts and frameworks, with distinctly different approaches. This talk will outline how the Earth System Modeling Framework (ESMF), which began in realm of high performance computing for the climate and weather domain, has begun to address the needs of hydrological modelers. We will describe ESMF's new mesh and observational data stream data structures, which join its structured grids and lower-level, index-space constructs as options for data representation, and the flexible, parallel regridding services that can interpolate data between them. The ESMF team is exploring a service oriented architecture approach to computing language and platform diversity, and to interfacing with other standard frameworks. We have also implemented C interfaces for optimized coupling between C and Fortran codes on traditional high performance computing platforms. To address the variety of components available, distributed communities, and integration with data and other services, ESMF has been exhancing its ability to store and write standard component and field metadata, and to link that metadata with full-service science portals. This enables

  15. Global-scale regionalization of hydrologic model parameters

    NASA Astrophysics Data System (ADS)

    Beck, Hylke; van Dijk, Albert; de Roo, Ad; Miralles, Diego; Schellekens, Jaap; McVicar, Tim; Bruijnzeel, Sampurno

    2016-04-01

    Current state-of-the-art models typically applied at continental to global scales (hereafter called macro-scale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments (10--10 000~km^2) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5° grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the ten most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially-uniform (i.e., averaged calibrated) parameters for 79~% of the evaluation catchments. Substantial improvements were evident for all major Köppen-Geiger climate types and even for evaluation catchments >5000~km distance from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV using regionalized parameters outperformed nine state-of-the-art macro-scale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via http://water.jrc.ec.europa.eu/HBV/.

  16. Grid-Xinanjiang Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Li, Z.; Yao, C.; Yu, Z.

    2009-12-01

    The grid-based distributed Xinanjiang (Grid-Xinanjiang) model by combining the well-tested conceptual rainfall-runoff model and the physically based flow routing model has been developed for hydrologic processes simulation and flood forecasting. The DEM is utilized to derive the flow direction, routing sequencing, hillslope and channel slopes. The developed model includes canopy interception, direct channel precipitation, evapotranspiration, as well as runoff generation via saturation excess mechanism. The diffusion wave considering the influent of upstream inflow, direct channel precipitation and flow partition to the channels is developed to route the hillslope and channel flow on a cell basis. The Grid-Xinanjiang model is applied at a 1-km grid scale in a nested basin located in Huaihe basin, China. The basin with the drainage area of 2692.7 km2, contains five internal points where observed streamflow data are available, and is used to evaluate the developed model for its’ ability on the simulation of hydrologic processes within the basin. Calibration and verification of the Grid-Xinanjiang model are carried out at both daily and hourly time steps. The model is assessed by comparing streamflow and water stage simulation to observations at the basin outlet and gauging stations within the basin and also compared with these simulated with the original Xinanjiang model. The results indicate that the parameter estimation approach is efficient and the developed model can forecast the streamflow and stage hydrograph well.

  17. Operational hydrological ensemble forecasts in France, taking into account rainfall and hydrological model uncertainties.

    NASA Astrophysics Data System (ADS)

    Mathevet, T.; Garavaglia, F.; Gailhard, J.; Garçon, R.; Dubus, L.

    2009-09-01

    In operational conditions, the actual quality of meteorological and hydrological forecasts do not allow decision-making in a certain future. In this context, meteorological and hydrological ensemble forecasts allow a better representation of forecasts uncertainties. Compared to classical deterministic forecasts, ensemble forecasts improve the human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. In this paper, we present a hydrological ensemble forecasting system under development at EDF (French Hydropower Company). Our results were updated, taking into account a longer rainfall forecasts archive. Our forecasting system both takes into account rainfall forecasts uncertainties and hydrological model forecasts uncertainties. Hydrological forecasts were generated using the MORDOR model (Andreassian et al., 2006), developed at EDF and used on a daily basis in operational conditions on a hundred of watersheds. Two sources of rainfall forecasts were used : one is based on ECMWF forecasts, another is based on an analogues approach (Obled et al., 2002). Two methods of hydrological model forecasts uncertainty estimation were used : one is based on the use of equifinal parameter sets (Beven & Binley, 1992), the other is based on the statistical modelisation of the hydrological forecast empirical uncertainty (Montanari et al., 2004 ; Schaefli et al., 2007). Daily operational hydrological 7-day ensemble forecasts during 4 years (from 2005 to 2008) in few alpine watersheds were evaluated. Finally, we present a way to combine rainfall and hydrological model forecast uncertainties to achieve a good probabilistic calibration. Our results show that the combination of ECMWF and analogues-based rainfall forecasts allow a good probabilistic calibration of rainfall forecasts. They show also that the statistical modeling of the hydrological forecast empirical

  18. Proving the ecosystem value through hydrological modelling

    NASA Astrophysics Data System (ADS)

    Dorner, W.; Spachinger, K.; Porter, M.; Metzka, R.

    2008-11-01

    Ecosystems provide valuable functions. Also natural floodplains and river structures offer different types of ecosystem functions such as habitat function, recreational area and natural detention. From an economic stand point the loss (or rehabilitation) of these natural systems and their provided natural services can be valued as a damage (or benefit). Consequently these natural goods and services must be economically valued in project assessments e.g. cost-benefit-analysis or cost comparison. Especially in smaller catchments and river systems exists significant evidence that natural flood detention reduces flood risk and contributes to flood protection. Several research projects evaluated the mitigating effect of land use, river training and the loss of natural flood plains on development, peak and volume of floods. The presented project analysis the hypothesis that ignoring natural detention and hydrological ecosystem services could result in economically inefficient solutions for flood protection and mitigation. In test areas, subcatchments of the Danube in Germany, a combination of hydrological and hydrodynamic models with economic evaluation techniques was applied. Different forms of land use, river structure and flood protection measures were assed and compared from a hydrological and economic point of view. A hydrodynamic model was used to simulate flows to assess the extent of flood affected areas and damages to buildings and infrastructure as well as to investigate the impacts of levees and river structure on a local scale. These model results provided the basis for an economic assessment. Different economic valuation techniques, such as flood damage functions, cost comparison method and substation-approach were used to compare the outcomes of different hydrological scenarios from an economic point of view and value the ecosystem service. The results give significant evidence that natural detention must be evaluated as part of flood mitigation projects

  19. Hepatitis B (HBV)

    MedlinePlus

    ... How Can I Help a Friend Who Cuts? Hepatitis B (HBV) KidsHealth > For Teens > Hepatitis B (HBV) Print A A A Text Size ... Prevented? How Is It Treated? What Is It? Hepatitis (pronounced: hep-uh-TIE-tiss) is a disease ...

  20. Multivariate Probabilistic Analysis of an Hydrological Model

    NASA Astrophysics Data System (ADS)

    Franceschini, Samuela; Marani, Marco

    2010-05-01

    Model predictions derived based on rainfall measurements and hydrological model results are often limited by the systematic error of measuring instruments, by the intrinsic variability of the natural processes and by the uncertainty of the mathematical representation. We propose a means to identify such sources of uncertainty and to quantify their effects based on point-estimate approaches, as a valid alternative to cumbersome Montecarlo methods. We present uncertainty analyses on the hydrologic response to selected meteorological events, in the mountain streamflow-generating portion of the Brenta basin at Bassano del Grappa, Italy. The Brenta river catchment has a relatively uniform morphology and quite a heterogeneous rainfall-pattern. In the present work, we evaluate two sources of uncertainty: data uncertainty (the uncertainty due to data handling and analysis) and model uncertainty (the uncertainty related to the formulation of the model). We thus evaluate the effects of the measurement error of tipping-bucket rain gauges, the uncertainty in estimating spatially-distributed rainfall through block kriging, and the uncertainty associated with estimated model parameters. To this end, we coupled a deterministic model based on the geomorphological theory of the hydrologic response to probabilistic methods. In particular we compare the results of Monte Carlo Simulations (MCS) to the results obtained, in the same conditions, using Li's Point Estimate Method (LiM). The LiM is a probabilistic technique that approximates the continuous probability distribution function of the considered stochastic variables by means of discrete points and associated weights. This allows to satisfactorily reproduce results with only few evaluations of the model function. The comparison between the LiM and MCS results highlights the pros and cons of using an approximating method. LiM is less computationally demanding than MCS, but has limited applicability especially when the model

  1. Modeling residual hydrologic errors with Bayesian inference

    NASA Astrophysics Data System (ADS)

    Smith, Tyler; Marshall, Lucy; Sharma, Ashish

    2015-09-01

    Hydrologic modelers are confronted with the challenge of producing estimates of the uncertainty associated with model predictions across an array of catchments and hydrologic flow regimes. Formal Bayesian approaches are commonly employed for parameter calibration and uncertainty analysis, but are often criticized for making strong assumptions about the nature of model residuals via the likelihood function that may not be well satisfied (or even checked). This technical note outlines a residual error model (likelihood function) specification framework that aims to provide guidance for the application of more appropriate residual error models through a nested approach that is both flexible and extendible. The framework synthesizes many previously employed residual error models and has been applied to four synthetic datasets (of differing error structure) and a real dataset from the Black River catchment in Queensland, Australia. Each residual error model was investigated and assessed under a top-down approach focused on its ability to properly characterize the errors. The results of these test applications indicate that a multifaceted assessment strategy is necessary to determine the adequacy of an individual likelihood function.

  2. An operational GLS model for hydrologic regression

    USGS Publications Warehouse

    Tasker, Gary D.; Stedinger, J.R.

    1989-01-01

    Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities. ?? 1989.

  3. Physical models for classroom teaching in hydrology

    NASA Astrophysics Data System (ADS)

    Rodhe, A.

    2012-09-01

    Hydrology teaching benefits from the fact that many important processes can be illustrated and explained with simple physical models. A set of mobile physical models has been developed and used during many years of lecturing at basic university level teaching in hydrology. One model, with which many phenomena can be demonstrated, consists of a 1.0-m-long plexiglass container containing an about 0.25-m-deep open sand aquifer through which water is circulated. The model can be used for showing the groundwater table and its influence on the water content in the unsaturated zone and for quantitative determination of hydraulic properties such as the storage coefficient and the saturated hydraulic conductivity. It is also well suited for discussions on the runoff process and the significance of recharge and discharge areas for groundwater. The flow paths of water and contaminant dispersion can be illustrated in tracer experiments using fluorescent or colour dye. This and a few other physical models, with suggested demonstrations and experiments, are described in this article. The finding from using models in classroom teaching is that it creates curiosity among the students, promotes discussions and most likely deepens the understanding of the basic processes.

  4. Modeling of surface microtopography and its impacts on hydrologic processes

    NASA Astrophysics Data System (ADS)

    Habtezion, Noah Lebassi

    Understanding the impacts of surface microtopography on hydrologic processes is critical. The objectives of this thesis research are: (1) to evaluate the effects of DEM resolution on microtopographic characteristics, hydrologic connectivity, and modeling of hydrologic processes; and (2) to assess the influences of multiple rainfall events on surface and subsurface hydrologic processes with the use of a puddle-to-puddle (P2P) modeling system. The change in DEM resolution has a significant effect on how surface microtopography is depicted, which in turn alters the hydrologic response of a topographic surface. The smoothing of reduced DEM resolution tends to enhance hydrologic connectivity, reduce the depression storage and infiltration, and increase surface runoff. Temporal rainfall distribution results in spatio-temporal variations in soil water dynamics, depression storage, infiltration, hydrologic connectivity, and surface runoff. The reduction in ponding time and infiltration, and the enhancement of hydrologic connectivity further caused earlier and greater surface runoff generation.

  5. A Smallholder Socio-hydrological Modelling Framework

    NASA Astrophysics Data System (ADS)

    Pande, S.; Savenije, H.; Rathore, P.

    2014-12-01

    Small holders are farmers who own less than 2 ha of farmland. They often have low productivity and thus remain at subsistence level. A fact that nearly 80% of Indian farmers are smallholders, who merely own a third of total farmlands and belong to the poorest quartile, but produce nearly 40% of countries foodgrains underlines the importance of understanding the socio-hydrology of a small holder. We present a framework to understand the socio-hydrological system dynamics of a small holder. It couples the dynamics of 6 main variables that are most relevant at the scale of a small holder: local storage (soil moisture and other water storage), capital, knowledge, livestock production, soil fertility and grass biomass production. The model incorporates rule-based adaptation mechanisms (for example: adjusting expenditures on food and fertilizers, selling livestocks etc.) of small holders when they face adverse socio-hydrological conditions, such as low annual rainfall, higher intra-annual variability in rainfall or variability in agricultural prices. It allows us to study sustainability of small holder farming systems under various settings. We apply the framework to understand the socio-hydrology of small holders in Aurangabad, Maharashtra, India. This district has witnessed suicides of many sugarcane farmers who could not extricate themselves out of the debt trap. These farmers lack irrigation and are susceptible to fluctuating sugar prices and intra-annual hydroclimatic variability. This presentation discusses two aspects in particular: whether government interventions to absolve the debt of farmers is enough and what is the value of investing in local storages that can buffer intra-annual variability in rainfall and strengthening the safety-nets either by creating opportunities for alternative sources of income or by crop diversification.

  6. Hybrid Modelling Approach to Prairie hydrology: Fusing Data-driven and Process-based Hydrological Models

    NASA Astrophysics Data System (ADS)

    Mekonnen, B.; Nazemi, A.; Elshorbagy, A.; Mazurek, K.; Putz, G.

    2012-04-01

    Modeling the hydrological response in prairie regions, characterized by flat and undulating terrain, and thus, large non-contributing areas, is a known challenge. The hydrological response (runoff) is the combination of the traditional runoff from the hydrologically contributing area and the occasional overflow from the non-contributing area. This study provides a unique opportunity to analyze the issue of fusing the Soil and Water Assessment Tool (SWAT) and Artificial Neural Networks (ANNs) in a hybrid structure to model the hydrological response in prairie regions. A hybrid SWAT-ANN model is proposed, where the SWAT component and the ANN module deal with the effective (contributing) area and the non-contributing area, respectively. The hybrid model is applied to the case study of Moose Jaw watershed, located in southern Saskatchewan, Canada. As an initial exploration, a comparison between ANN and SWAT models is established based on addressing the daily runoff (streamflow) prediction accuracy using multiple error measures. This is done to identify the merits and drawbacks of each modeling approach. It has been found out that the SWAT model has better performance during the low flow periods but with degraded efficiency during periods of high flows. The case is different for the ANN model as ANNs exhibit improved simulation during high flow periods but with biased estimates during low flow periods. The modelling results show that the new hybrid SWAT-ANN model is capable of exploiting the strengths of both SWAT and ANN models in an integrated framrwork. The new hybrid SWAT-ANN model simulates daily runoff quite satisfactorily with NSE measures of 0.80 and 0.83 during calibration and validation periods, respectively. Furthermore, an experimental assessment was performed to identify the effects of the ANN training method on the performance of the hybrid model as well as the parametric identifiability. Overall, the results obtained in this study suggest that the fusion

  7. Modeling hydrologic and ecologic responses using a new eco-hydrological model for identification of droughts

    NASA Astrophysics Data System (ADS)

    Sawada, Yohei; Koike, Toshio; Jaranilla-Sanchez, Patricia Ann

    2014-07-01

    Drought severely damages water and agricultural resources, and both hydrological and ecological responses are important for its understanding. First, precipitation deficit induces soil moisture deficiency and high plant water stress causing agricultural droughts. Second, hydrological drought characterized by deficit of river discharge and groundwater follows agricultural drought. However, contributions of vegetation dynamics to these processes at basin scale have not been quantified. To address this issue, we develop an eco-hydrological model that can calculate river discharge, groundwater, energy flux, and vegetation dynamics as diagnostic variables at basin scale within a distributed hydrological modeling framework. The model is applied to drought analysis in the Medjerda River basin. From model inputs and outputs, we calculate drought indices for different drought types. The model shows reliable accuracy in reproducing observed river discharge in long-term (19 year) simulation. Moreover, the drought index calculated from the model-estimated annual peak of leaf area index correlates well (correlation coefficient r = 0.89) with the drought index from nationwide annual crop production, which demonstrates that the modeled leaf area index is capable of representing agricultural droughts related to historical food shortages. We show that vegetation dynamics have a more rapid response to meteorological droughts than river discharge and groundwater dynamics in the Medjerda basin because vegetation dynamics are sensitive to soil moisture in surface layers, whereas soil moisture in deeper layers strongly contributes to streamflow and groundwater level. Our modeling framework can contribute to analyze drought progress, although analyses for other climate conditions are needed.

  8. Evaluating spatial patterns in hydrological modeling

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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

  9. A multicomponent coupled model of glacier hydrology

    NASA Astrophysics Data System (ADS)

    Flowers, Gwenn Elizabeth

    Multiple lines of evidence suggest a causal link between subglacial hydrology and phenomena such as fast-flowing ice. This evidence includes a measured correlation between water under alpine glaciers and their motion, the presence of saturated sediment beneath Antaxctic ice streams, and geologic signatures of enhanced paleo-ice flow over deformable substrates. The complexity of the glacier bed as a three-component mixture presents an obstacle to unraveling these conundra. Inadequate representations of hydrology, in part, prevent us from closing the gap between empirical descriptions and a comprehensive consistent framework for understanding the dynamics of glacierized systems. I have developed a distributed numerical model that solves equations governing glacier surface runoff, englacial water transport, subglacial drainage, and subsurface groundwater flow. Ablation and precipitation drive the surface model through a temperature-index parameterization. Water is permitted to flow over and off the glacier, or to the bed through a system of crevasses, pipes, and fractures. A macroporous sediment horizon transports subglacial water to the ice margin or to an underlying aquifer. Governing equations are derived from the law of mass conservation and are expressed as a balance between the internal redistribution of water and external sources. Each of the four model components is represented as a two-dimensional, vertically-integrated layer that communicates with its neighbors through water exchange. Stacked together, these layers approximate a three-dimensional system. I tailor the model to Trapridge Glacier, where digital maps of the surface and bed have been derived from ice-penetrating radar data. Observations of subglacial water pressure provide additional constraints on model parameters and a basis for comparison of simulations with real data. Three classical idealizations of glacier geometry are used for simple model experiments. Equilibrium tests emphasize geometric

  10. Use of different sampling schemes in machine learning-based prediction of hydrological models' uncertainty

    NASA Astrophysics Data System (ADS)

    Kayastha, Nagendra; Solomatine, Dimitri; Lal Shrestha, Durga; van Griensven, Ann

    2013-04-01

    In recent years, a lot of attention in the hydrologic literature is given to model parameter uncertainty analysis. The robustness estimation of uncertainty depends on the efficiency of sampling method used to generate the best fit responses (outputs) and on ease of use. This paper aims to investigate: (1) how sampling strategies effect the uncertainty estimations of hydrological models, (2) how to use this information in machine learning predictors of models uncertainty. Sampling of parameters may employ various algorithms. We compared seven different algorithms namely, Monte Carlo (MC) simulation, generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), partical swarm optimization (PSO) and adaptive cluster covering (ACCO) [1]. These methods were applied to estimate uncertainty of streamflow simulation using conceptual model HBV and Semi-distributed hydrological model SWAT. Nzoia catchment in West Kenya is considered as the case study. The results are compared and analysed based on the shape of the posterior distribution of parameters, uncertainty results on model outputs. The MLUE method [2] uses results of Monte Carlo sampling (or any other sampling shceme) to build a machine learning (regression) model U able to predict uncertainty (quantiles of pdf) of a hydrological model H outputs. Inputs to these models are 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. The problem here is that different sampling algorithms result in different data sets used to train such a model U, which leads to several models (and 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 U and

  11. Attributing spatial patterns of hydrological model performance

    NASA Astrophysics Data System (ADS)

    Eisner, S.; Malsy, M.; Flörke, M.

    2013-12-01

    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

  12. Hydrology

    ERIC Educational Resources Information Center

    Sharp, John M., Jr.

    1978-01-01

    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)

  13. Improving Hydrology in Land Ice Models

    NASA Astrophysics Data System (ADS)

    Price, Stephen; Flowers, Gwenn; Schoof, Christian

    2011-05-01

    Community Earth System Model Land Ice Working Group Meeting; Boulder, Colorado, 13 January 2011 ; Recent observations indicate that mass loss from glaciers and ice sheets (“land ice”) is increasing. The drivers of these changes are not well understood, and modeling the land ice response to them remains challenging. As a result, the Intergovernmental Panel on Climate Change explicitly avoided speculating on 21st-century sea level rise from ice dynamical processes in its fourth assessment report. The mismatch between observations of land ice change and model skill at mimicking those changes is behind recent efforts to develop next-generation land ice models. Necessary improvements to existing models include improved dynamics, coupling to climate models, and better representations of important boundary conditions and physical processes. Basal sliding, the primary control on the rate of land ice delivery to the oceans, is one such boundary condition that is largely controlled by land ice hydrology.

  14. Improving the representation of hydrologic processes in Earth System Models

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Fan, Ying; Lawrence, David M.; Adam, Jennifer C.; Bolster, Diogo; Gochis, David J.; Hooper, Richard P.; Kumar, Mukesh; Leung, L. Ruby; Mackay, D. Scott; Maxwell, Reed M.; Shen, Chaopeng; Swenson, Sean C.; Zeng, Xubin

    2015-08-01

    Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.

  15. Coupled land surface/hydrologic/atmospheric models

    NASA Technical Reports Server (NTRS)

    Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers

    1993-01-01

    The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.

  16. The Diagnostic Accuracy and Clinical Utility of Three Noninvasive Models for Predicting Liver Fibrosis in Patients with HBV Infection

    PubMed Central

    Zhang, Zhiqiao; Wang, Gongsui; Kang, Kaifu; Wu, Guobiao; Wang, Peng

    2016-01-01

    Aim To evaluate the diagnostic accuracy and clinical utility of the fibrosis index based on the four factors (FIB-4), aspartate aminotransferase -to-platelet ratio index (APRI), and aspartate aminotransferase–alanine aminotransferase ratio index (AAR) for predicting liver fibrosis in patients with HBV infection. Methods From January 2006 to December 2010,a total of 1543 consecutive chronic hepatitis B(CHB) patients who underwent liver biopsies were enrolled. FIB-4,APRI, and AAR were calculated.The areas under the receiver-operating characteristic curves (AUROCs) were calculated to assess the diagnostic accuracy of these models.The AUROCs of these models were compared by DeLong’s test.For further comparisons in different studies,the AUROCs were adjusted to conduct Adjusted AUROCs(ADjAUROCs) according to the prevalence of fibrosis stages using the difference between advanced and nonadvanced fibrosis (DANA). Results For prediction of significant fibrosis,severe fibrosis,and cirrhosis,the AUROCs of FIB-4 were 0.646(ADjAUROC 0.717),0.670(ADjAUROC 0.741), and 0.715(ADjAUROC 0.786) respectively;whereas it were 0.656(ADjAUROC 0.727),0.653(ADjAUROC 0.724) and 0.639(ADjAUROC 0.710) for APRI, 0.498(ADjAUROC 0.569),0.548(ADjAUROC 0.619) and 0.573(ADjAUROC 0.644) for AAR. The further comparisons demonstrated that there were no significant differences of AUROCs between FIB-4 and APRI in predicting significant and severe fibrosis(P > 0.05),while FIB-4 was superior to APRI in predicting cirrhosis(P < 0.001). Further subgroup analysis demonstrated that the diagnostic accuracy of FIB-4 and APRI in patients with normal alanine aminotransferase(ALT) were higher than that in patients with elevated ALT. Conclusions The results demonstrated that FIB-4 and APRI are useful for diagnosis of fibrosis. FIB-4 and APRI have similar diagnostic accuracy in predicting significant and severe fibrosis,while FIB-4 is superior to APRI in predicting cirrhosis. The clinical utility of FIB-4 and APRI

  17. Global-scale regionalization of hydrologic model parameters

    NASA Astrophysics Data System (ADS)

    Beck, Hylke E.; van Dijk, Albert I. J. M.; de Roo, Ad; Miralles, Diego G.; McVicar, Tim R.; Schellekens, Jaap; Bruijnzeel, L. Adrian

    2016-05-01

    Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments (10-10,000 km2) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5° grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Köppen-Geiger climate types and even for evaluation catchments > 5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via www.gloh2o.org.

  18. Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

    NASA Astrophysics Data System (ADS)

    Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

    2015-04-01

    The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.

  19. The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

    This paper investigates the skill of 90-day low-flow forecasts using two conceptual hydrological models and one data-driven model based on Artificial Neural Networks (ANNs) for the Moselle River. The three models, i.e. HBV, GR4J and ANN-Ensemble (ANN-E), all use forecasted meteorological inputs (precipitation P and potential evapotranspiration PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low-flow forecasts for 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 models. 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 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 runoff during low-flow periods 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. The results of the comparison of forecast skills with varying lead times show that GR4J is less skilful than ANN-E and HBV. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low-flow forecasts than the uncertainty from ensemble PET

  20. Plant adaptive behaviour in hydrological models (Invited)

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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

  1. Hydrological modelling in sandstone rocks watershed

    NASA Astrophysics Data System (ADS)

    Ponížilová, Iva; Unucka, Jan

    2015-04-01

    The contribution is focused on the modelling of surface and subsurface runoff in the Ploučnice basin. The used rainfall-runoff model is HEC-HMS comprising of the method of SCS CN curves and a recession method. The geological subsurface consisting of sandstone is characterised by reduced surface runoff and, on the contrary, it contributes to subsurface runoff. The aim of this paper is comparison of the rate of influence of sandstone on reducing surface runoff. The recession method for subsurface runoff was used to determine the subsurface runoff. The HEC-HMS model allows semi- and fully distributed approaches to schematisation of the watershed and rainfall situations. To determine the volume of runoff the method of SCS CN curves is used, which results depend on hydrological conditions of the soils. The rainfall-runoff model assuming selection of so-called methods of event of the SCS-CN type is used to determine the hydrograph and peak flow rate based on simulation of surface runoff in precipitation exceeding the infiltration capacity of the soil. The recession method is used to solve the baseflow (subsurface) runoff. The method is based on the separation of hydrograph to direct runoff and subsurface or baseflow runoff. The study area for the simulation of runoff using the method of SCS CN curves to determine the hydrological transformation is the Ploučnice basin. The Ploučnice is a hydrologically significant river in the northern part of the Czech Republic, it is a right tributary of the Elbe river with a total basin area of 1.194 km2. The average value of CN curves for the Ploučnice basin is 72. The geological structure of the Ploučnice basin is predominantly formed by Mesozoic sandstone. Despite significant initial loss of rainfall the basin response to the causal rainfall was demonstrated by a rapid rise of the surface runoff from the watershed and reached culmination flow. Basically, only surface runoff occures in the catchment during the initial phase of

  2. Hydrological model uncertainty assessment in southern Africa

    NASA Astrophysics Data System (ADS)

    Hughes, D. A.; Kapangaziwiri, E.; Sawunyama, T.

    2010-06-01

    The importance of hydrological uncertainty analysis has been emphasized in recent years and there is an urgent need to incorporate uncertainty estimation into water resources assessment procedures used in the southern Africa region. The region is characterized by a paucity of accurate data and limited human resources, but the need for informed development decisions is critical to social and economic development. One of the main sources of uncertainty is related to the estimation of the parameters of hydrological models. This paper proposes a framework for establishing parameter values, exploring parameter inter-dependencies and setting parameter uncertainty bounds for a monthly time-step rainfall-runoff model (Pitman model) that is widely used in the region. The method is based on well-documented principles of sensitivity and uncertainty analysis, but recognizes the limitations that exist within the region (data scarcity and accuracy, model user attitudes, etc.). Four example applications taken from different climate and physiographic regions of South Africa illustrate that the methods are appropriate for generating behavioural stream flow simulations which include parameter uncertainty. The parameters that dominate the model response and their degree of uncertainty vary between regions. Some of the results suggest that the uncertainty bounds will be too wide for effective water resources decision making. Further work is required to reduce some of the subjectivity in the methods and to investigate other approaches for constraining the uncertainty. The paper recognizes that probability estimates of uncertainty and methods to include input climate data uncertainties need to be incorporated into the framework in the future.

  3. Modeling hydrologic processes at the residential scale

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

    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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    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.

  5. Uncertainty Analysis of the Ensemble Hydrological Forecasts in the Coupled Meteorological-Hydrological Modelling Environment

    NASA Astrophysics Data System (ADS)

    Xuan, Y.; Cluckie, I. D.

    2006-12-01

    The advances in meso-scale numerical weather predication render hydrologists the capability to incorporate high-resolution NWP directly into flood forecasting systems in order to obtain an extended lead time. However, such a direct application of rainfall outputs from the NWP model can contribute considerable uncertainties to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be highlighted by the scaling process. In this research, the ensemble hydrological forecasts driven by the ensemble weather prediction are investigated in an effort trying to understand both the potential and the implication of the ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. A data-rich catchment facilitated with dense rainguage network as well as high resolution weather radar was chosen to run the ensemble hydrological simulations of a distributed hydrological model driven by the high resolution NWP predictions. The uncertainties of the amount and the location/timing of the rainfall prediction are discussed whith the results showing that: (1) the hydrological model driven by the short-range NWP can produce forecasts comparable with those from a raingauge-driven one; (2) the ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematical biases sometimes are significantly large and, as such, extra efforts need to be made to improve the quality of such a system.

  6. Constraining hydrologic models using thermal analysis

    SciTech Connect

    Doughty, Christine; Karasaki, Kenzi

    2002-12-12

    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.

  7. Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change

    NASA Astrophysics Data System (ADS)

    Karlsson, Ida B.; Sonnenborg, Torben O.; Refsgaard, Jens Christian; Trolle, Dennis; Børgesen, Christen Duus; Olesen, Jørgen E.; Jeppesen, Erik; Jensen, Karsten H.

    2016-04-01

    Impact studies of the hydrological response of future climate change are important for the water authorities when risk assessment, management and adaptation to a changing climate are carried out. The objective of this study was to model the combined effect of land use and climate changes on hydrology for a 486 km2 catchment in Denmark and to evaluate the sensitivity of the results to the choice of hydrological model. Three hydrological models, NAM, SWAT and MIKE SHE, were constructed and calibrated using similar methods. Each model was forced with results from four climate models and four land use scenarios. The results revealed that even though the hydrological models all showed similar performance during calibration, the mean discharge response to climate change varied up to 30%, and the variations were even higher for extreme events (1th and 99th percentile). Land use changes appeared to cause little change in mean hydrological responses and little variation between hydrological models. Differences in hydrological model responses to land use were, however, significant for extremes due to dissimilarities in hydrological model structure and process equations. The climate model choice remained the dominant factor for mean discharge, low and high flows as well as hydraulic head at the end of the century.

  8. Improvements of Physically-Based Hydrological Modelling using the ACRU Agro-Hydrological Modelling System

    NASA Astrophysics Data System (ADS)

    Bonifacio, C. M. T.; Kienzle, S. W.; Xu, W.; Zhang, J.

    2014-12-01

    The uncertainty of future water availability due to climate change in the Upper Oldman River Basin in Alberta, Canada, and downstream users is considered in this study. A changing climate can significantly perturb hydrological response within a region, thereby affecting the available water resources within southern Alberta. The ACRU agro-hydrological modelling system is applied to simulate historical (1950-2010) and future (2041-2070) streamflows and volumes of a major irrigation reservoir. Like many highly complex, process-based distributed models, major limitations include the data availability and data quality at finer spatial resolutions. With the use of a scripting language, certain limitations can be greatly reduced. Three phases of the project will be emphasized. First, the assimilation of solar radiation, relative humidity, sunshine hours and wind speed daily data into the Canadian 10KM daily climate data that contains daily precipitation, maximum and minimum temperature data for the period 1950-2010, so as to enable potential evapotranspiration calculations using the Penman-Monteith equation. Second, the downscaling of five regional climate model (RCM) data to match the 10KM spatial resolution was undertaken. Third, a total of 1722 hydrological response units (HRUs) were delineated within the 4403 km2 large upper Oldman River Basin. In all phases of model input data parameterization and calibration, the automation of known external procedures greatly decreased erroneous model inputs and increased the efficiency of validating the quality of input data to be used within the ACRU model.

  9. Ensemble evaluation of hydrological model hypotheses

    NASA Astrophysics Data System (ADS)

    Krueger, Tobias; Freer, Jim; Quinton, John N.; MacLeod, Christopher J. A.; Bilotta, Gary S.; Brazier, Richard E.; Butler, Patricia; Haygarth, Philip M.

    2010-07-01

    It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a "leaking" of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error.

  10. Monthly Hydrological Model Evaluation through Mapping the Hydrological Pattern to Information Space

    NASA Astrophysics Data System (ADS)

    Pan, B.; Cong, Z.

    2014-12-01

    Conceptual and stochastic monthly hydrological models have been widely used for climatic change impact exploration and long-range stream flow forecast. With disparate philosophies and different but insufficient inputs, most of the existing models are capable of generating satisfying outputs, which reveals a relatively robust idiosyncrasy of hydrological pattern over monthly time scale. This research uses the epistemic-aleatory uncertainties evaluation framework to examine the information source sink terms and flows of 6 conceptual monthly water balance models and a seasonal autoregressive stochastic hydrologic model over 19 basins in Jiangxi Province, China and the experiment basins of MOPEX project. By using the stream technique of Lisp, we constructed two programming paradigms into which the hydrological models mentioned above could be fitted. We focus on detecting and explaining the best achievable predictive performances and data-revealed insufficient of the models in each paradigm, especially the hydrological meaning of the iteration variables in these models. Finally, we make an attempt to compare and connect these two paradigms against the backdrop of algorithmic information theory to help us form a better understanding of monthly hydrological pattern.

  11. A hydrological model of New Zealand

    NASA Astrophysics Data System (ADS)

    Woods, R. A.; Tarboton, D. G.; Ibbitt, R. P.; Wild, M.; Henderson, R. D.; Turner, R.

    2003-04-01

    We present initial results from a hydrological model of New Zealand, using Topnet, a variant of TOPMODEL, linked to a kinematic wave channel network routing algorithm. This model run uses daily timesteps for the period 1985-2001, and subdivides the country into approximately 35,000 sub-catchments of 7-10 sq km each. The sub-catchments are linked by 55,000 river reaches, which route sub-catchment runoff. The model subcatchments and reaches are defined automatically by DEM analyses, and initial estimates of model parameters are defined by GIS overlay, coupled with purpose-built model assembly code, and lookup tables for model parameters. A daily simulation for 1 year over New Zealand takes two hours on a standard desktop computer. The model is forced by gridded daily rainfall and temperature data, and it calculates daily water balance for each of the sub-catchments (rain, evaporation, throughfall, infiltration, soil drainage, surface runoff, subsurface runoff, and changes in storage in the canopy, root zone, and saturated storage), as well as daily flows in each river reach. The model as currently implemented does not include snow, glaciers, or deep groundwater flow (i.e. across sub-catchment boundaries). The first applications of the model are for developing an annual water balance of New Zealand for the period 1994-2001, at the regional scale, and for driving a high-spatial resolution, daily time-stepping national erosion model. We are moving to further applications for water resource modeling (e.g. impact of abstraction and/or storage), and for flood forecasting, using hourly rainfall from a mesoscale atmospheric model.

  12. Modeling the Interactions between Hydrological Extremes, Water Management and Society.

    NASA Astrophysics Data System (ADS)

    Martinez, Fabian; Di Baldassarre, Giuliano; Kalantari, Zahra

    2016-04-01

    Over the past years, several studies have focused on exploring human impacts on the hydrological regime. Even though the dominant hydrological processes are mostly well understood, there are still several challenges related to modeling the coevolution of human impacts on (and responses to) hydrological extremes, such as floods and droughts. Some initial modeling attempts have proved to capture the essential dynamics emerging from two-way feedbacks between hydrological and social processes. However, they have predominantly focused on flooding. This research aims to develop a new conceptual model unraveling the interplay between hydrological extremes (floods and droughts) and human societies in a changing climate. In particular, this socio-hydrological model aims at understanding, and predicting the dynamics of coupled human-water systems to explain and capture how the occurrence of hydrological extremes changes water management approach, and how such a change (in turn) mitigates the impacts of hydrological extremes. The conceptual model is then applied to a case study to test its ability in simulating the dynamics emerging from the interplay between hydrological and social processes.

  13. Hydrological Modelling of Ganga River basin.

    NASA Astrophysics Data System (ADS)

    Anand, J.; Gosain, A. K.; Khosa, R.

    2015-12-01

    Application of a hydrological model, Soil and Water Assessment Tool (SWAT) to the Ganga basin having a total drainage area of around 1.08 M sq. km extending over Tibet, Nepal, India and Bangladesh has been made. The model is calibrated to determine the spatial deviations in runoff at sub-basin level, and to capture the water balance of the river basin. Manual calibration approach was used for calibrating the SWAT model by following multi-step procedure to get to the realistic present situation as close as possible. Simulations were then further made with and without proposed future projects to obtain various scenarios. The various statistical parameters used for the evaluation of the monthly runoff simulation showed that SWAT performed well in mimicking the monthly stream flow for Ganga River basin. The model under predicted the flows in the non-perennial region during non-monsoon season, due to low rainfall and regulated flows and seepage taking place from the reservoirs. The impacts of the interventions, both existing as well as proposed, on the water balance of the basin were evaluated and quantified. The derived results suggest that there is a substantial reduction in overall water resources availability in the study basin on account of the current level of development and further, future developments, as are being proposed, may require a careful study of their potential impact on currently sanctioned water use. The present study showcases that efficacy of the model for simulating the stream flow is admirable.

  14. An integrated hydrologic modeling framework for coupling SWAT with MODFLOW

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil and Water Assessment Tool (SWAT), MODFLOW, and Energy Balance based Evapotranspiration (EB_ET) models are extensively used to estimate different components of the hydrological cycle. Surface and subsurface hydrological processes are modeled in SWAT but limited to the extent of shallow aquif...

  15. 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...

  16. Multi-Objective Calibrationo of Hydrologic Model Using Satellite Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrologic modeling often involves a large number of parameters, some of which cannot be measured directly and may vary with land cover, soil or even seasons. Therefore parameter estimation is a critical step in applying a hydrologic model to any study area. Parameter estimation is typically done by...

  17. Modelling the hydrological cycle in assessments of climate change

    NASA Technical Reports Server (NTRS)

    Rind, D.; Rosenzweig, C.; Goldberg, R.

    1992-01-01

    The predictions of climate change studies depend crucially on the hydrological cycles embedded in the different models used. It is shown here that uncertainties in hydrological processes and inconsistencies in both climate and impact models limit confidence in current assessments of climate change. A future course of action to remedy this problem is suggested.

  18. A question driven socio-hydrological modeling process

    NASA Astrophysics Data System (ADS)

    Garcia, M.; Portney, K.; Islam, S.

    2015-08-01

    Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human induced changes may propagate through this coupled system. Modeling of coupled human and hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding the choice of modeling structure, scope, and detail. A shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope, and detail to remain contingent and adaptive to the question context. We demonstrate its utility by exploring a question: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result per capita demand decreases during periods of water stress are more frequent but less drastic and the additive effect of small adjustments decreases the tendency of the system to overshoot available

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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

  20. Hydrology

    ERIC Educational Resources Information Center

    Sharp, John M.

    1977-01-01

    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)

  1. Hydrological system dynamics of glaciated Karnali River Basin Nepal Himalaya using J2000 Hydrological model

    NASA Astrophysics Data System (ADS)

    Khatiwada, K. R.; Nepal, S.; Panthi, J., Sr.; Shrestha, M.

    2015-12-01

    Hydrological modelling plays an important role in understanding hydrological processes of a catchment. In the context of climate change, the understanding of hydrological characteristic of the catchment is very vital to understand how the climate change will affect the hydrological regime. This research facilitates in better understanding of the hydrological system dynamics of a himalayan mountainous catchment in western Nepal. The Karnali River, longest river flowing inside Nepal, is one of the three major basins of Nepal, having the area of 45269 sq. km. is unique. The basin has steep topography and high mountains to the northern side. The 40% of the basin is dominated by forest land while other land cover are: grass land, bare rocky land etc. About 2% of the areas in basin is covered by permanent glacier apart from that about 12% of basin has the snow and ice cover. There are 34 meteorological stations distributed across the basin. A process oriented distributed J2000 hydrologial model has been applied to understand the hydrological system dynamics. The model application provides distributed output of various hydrological components. The J2000 model applies Hydrological Response Unit (HRU) as a modelling entity. With 6861 HRU and 1010 reaches, the model was calibrated (1981-1999) and validated (2000-2004) at a daily scale using split-sample test. The model is able to capture the overall hydrological dynamics well. The rising limbs and recession limbs are simulated equally and with satisfactory ground water conditions. Based on the graphical and statistical evaluation of the model performance the model is able to simulate hydrological processes fairly well. Calibration shows that Nash Sutcliffe efficiency is 0.91, coefficient of determination is 0.92 Initial observation shows that during the pre-monsoon season(March to May) the glacial runoff is 25% of the total discharge while in the monsoon(June to September) season it is only 13%. The surface runoff

  2. Comparing TRMM 3B42, CFSR and ground-based rainfall estimates as input for hydrological models, in data scarce regions: the Upper Blue Nile Basin, Ethiopia

    NASA Astrophysics Data System (ADS)

    Worqlul, A. W.; Collick, A. S.; Tilahun, S. A.; Langan, S.; Rientjes, T. H. M.; Steenhuis, T. S.

    2015-02-01

    Accurate prediction of hydrological models requires accurate spatial and temporal distribution of rainfall observation network. In developing countries rainfall observation station network are sparse and unevenly distributed. Satellite-based products have the potential to overcome these shortcomings. The objective of this study is to compare the advantages and the limitation of commonly used high-resolution satellite rainfall products as input to hydrological models as compared to sparsely populated network of rain gauges. For this comparison we use two semi-distributed hydrological models Hydrologiska Byråns Vattenbalansavdelning (HBV) and Parameter Efficient Distributed (PED) that performed well in Ethiopian highlands in two watersheds: the Gilgel Abay with relatively dense network and Main Beles with relatively scarce rain gauge stations. Both are located in the Upper Blue Nile Basin. The two models are calibrated with the observed discharge from 1994 to 2003 and validated from 2004 to 2006. Satellite rainfall estimates used includes Climate Forecast System Reanalysis (CFSR), Tropical Rainfall Measuring Mission (TRMM) 3B42 version 7 and ground rainfall measurements. The results indicated that both the gauged and the CFSR precipitation estimates were able to reproduce the stream flow well for both models and both watershed. TRMM 3B42 performed poorly with Nash Sutcliffe values less than 0.1. As expected the HBV model performed slightly better than the PED model, because HBV divides the watershed into sub-basins resulting in a greater number of calibration parameters. The simulated discharge for the Gilgel Abay was better than for the less well endowed (rain gauge wise) Main Beles. Finally surprisingly, the ground based gauge performed better for both watersheds (with the exception of extreme events) than TRMM and CFSR satellite rainfall estimates. Undoubtedly in the future, when improved satellite products will become available, this will change.

  3. Data Mining of Hydrological Model Performances

    NASA Astrophysics Data System (ADS)

    Vitolo, Claudia; Buytaert, Wouter

    2013-04-01

    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

  4. Improvement of Continuous Hydrologic Models and HMS SMA Parameters Reduction

    NASA Astrophysics Data System (ADS)

    Rezaeian Zadeh, Mehdi; Zia Hosseinipour, E.; Abghari, Hirad; Nikian, Ashkan; Shaeri Karimi, Sara; Moradzadeh Azar, Foad

    2010-05-01

    Hydrological models can help us to predict stream flows and associated runoff volumes of rainfall events within a watershed. There are many different reasons why we need to model the rainfall-runoff processes of for a watershed. However, the main reason is the limitation of hydrological measurement techniques and the costs of data collection at a fine scale. Generally, we are not able to measure all that we would like to know about a given hydrological systems. This is very particularly the case for ungauged catchments. Since the ultimate aim of prediction using models is to improve decision-making about a hydrological problem, therefore, having a robust and efficient modeling tool becomes an important factor. Among several hydrologic modeling approaches, continuous simulation has the best predictions because it can model dry and wet conditions during a long-term period. Continuous hydrologic models, unlike event based models, account for a watershed's soil moisture balance over a long-term period and are suitable for simulating daily, monthly, and seasonal streamflows. In this paper, we describe a soil moisture accounting (SMA) algorithm added to the hydrologic modeling system (HEC-HMS) computer program. As is well known in the hydrologic modeling community one of the ways for improving a model utility is the reduction of input parameters. The enhanced model developed in this study is applied to Khosrow Shirin Watershed, located in the north-west part of Fars Province in Iran, a data limited watershed. The HMS SMA algorithm divides the potential path of rainfall onto a watershed into five zones. The results showed that the output of HMS SMA is insensitive with the variation of many parameters such as soil storage and soil percolation rate. The study's objective is to remove insensitive parameters from the model input using Multi-objective sensitivity analysis. Keywords: Continuous Hydrologic Modeling, HMS SMA, Multi-objective sensitivity analysis, SMA Parameters

  5. Global scale hydrology - Advances in land surface modeling

    SciTech Connect

    Wood, E.F. )

    1991-01-01

    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.

  6. Complexity of groundwater models in catchment hydrological models

    NASA Astrophysics Data System (ADS)

    Attinger, Sabine; Herold, Christian; Kumar, Rohini; Mai, Juliane; Ross, Katharina; Samaniego, Luis; Zink, Matthias

    2015-04-01

    In catchment hydrological models, groundwater is usually modeled very simple: it is conceptualized as a linear reservoir that gets the water from the upper unsaturated zone reservoir and releases water to the river system as baseflow. The baseflow is only a minor component of the total river flow and groundwater reservoir parameters are therefore difficult to be inversely estimated by means of river flow data only. In addition, the modelled values of the absolute height of the water filling the groundwater reservoir - in other words the groundwater levels - are of limited meaning due to coarse or no spatial resolution of groundwater and due to the fact that only river flow data are used for the calibration. The talk focuses on the question: Which complexity in terms of model complexity and model resolution is necessary to characterize groundwater processes and groundwater responses adequately in distributed catchment hydrological models? Starting from a spatially distributed catchment hydrological model with a groundwater compartment that is conceptualized as a linear reservoir we stepwise increase the groundwater model complexity and its spatial resolution to investigate which resolution, which complexity and which data are needed to reproduce baseflow and groundwater level data adequately.

  7. 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)

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

    2013-01-01

    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.

  8. Experiments with clustering of catchments in PCA-reduced space and regionalization of a hydrological model (Central Alborz region, Iran)

    NASA Astrophysics Data System (ADS)

    Khosravi, Mohammad; Solomatine, Dimitri; Salajegheh, Ali; Mohseni Saravi, Mohsen; Malekian, Arash; Corzo, Gerald

    2015-04-01

    This study tested the possibility of simulating time series of daily streamflows in ungauged catchments based on climatic and physiographic similarity. The study area is located in central Alborz region in Iran. Fourteen (14) proper catchments, with the area ranged between 16 to 827Km2, in this region selected for testing. After applying Principal Component Analysis for selecting the most important parameters among the different climatic and physiographic parameters, five components which could explain more than 90% of variances of the data were selected and according to the values of the coefficients in selected PCA components, five parameters including: Area, Annual Rainfall, Annual temperature, gravelius compactness coefficient and mean elevation, were selected as the measures for clustering. Then mentioned parameters entered in K-means clustering analysis method to classify the catchments. Finally the catchments divided in three different clusters. Using the well known HBV model, we built a model for the closest catchment to the center of each cluster. Then, the thirteen (13) HBV model parameters were calibrated using Genetic Algorithm. We assumed that the remained catchments in each cluster are ungauged, and using the calibrated model, the daily time series of streamflows simulated in the remained catchments in the considered cluster (as the receiver catchments). Nash Sutcliffe and RMSE indices used to comparing the simulated and recorded data. The experiments with the considered case study confirmed that the model regionalization based on the physiographic and climatic characteristics could be a useful instrument in hydrological studies. Key words: Regionalization, HBV, PCA, Cluster, Catchment, central Alborz region

  9. From local hydrological process analysis to regional hydrological model application in Benin: Concept, results and perspectives

    NASA Astrophysics Data System (ADS)

    Bormann, H.; Faß, T.; Giertz, S.; Junge, B.; Diekkrüger, B.; Reichert, B.; Skowronek, A.

    This paper presents the concept, first results and perspectives of the hydrological sub-project of the IMPETUS-Benin project which is part of the GLOWA program funded by the German ministry of education and research. In addition to the research concept, first results on field hydrology, pedology, hydrogeology and hydrological modelling are presented, focusing on the understanding of the actual hydrological processes. For analysing the processes a 30 km 2 catchment acting as a super test site was chosen which is assumed to be representative for the entire catchment of about 15,000 km 2. First results of the field investigations show that infiltration, runoff generation and soil erosion strongly depend on land cover and land use which again influence the soil properties significantly. A conceptual hydrogeological model has been developed summarising the process knowledge on runoff generation and subsurface hydrological processes. This concept model shows a dominance of fast runoff components (surface runoff and interflow), a groundwater recharge along preferential flow paths, temporary interaction between surface and groundwater and separate groundwater systems on different scales (shallow, temporary groundwater on local scale and permanent, deep groundwater on regional scale). The findings of intensive measurement campaigns on soil hydrology, groundwater dynamics and soil erosion have been integrated into different, scale-dependent hydrological modelling concepts applied at different scales in the target region (upper Ouémé catchment in Benin, about 15,000 km 2). The models have been applied and successfully validated. They will be used for integrated scenario analyses in the forthcoming project phase to assess the impacts of global change on the regional water cycle and on typical problem complexes such as food security in West African countries.

  10. Hydrology

    NASA Astrophysics Data System (ADS)

    Brutsaert, Wilfried

    2005-08-01

    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

  11. Uncertainties of the extreme high flows under climate change impact due to emission scenarios, hydrological models and parameters

    NASA Astrophysics Data System (ADS)

    Tian, Ye; Booij, Martijn; Zhu, Qian; Pan, Suli; Xu, Yue-Ping

    2013-04-01

    Climate change has exerted a significant impact on the hydrological cycle which is closely related to human's daily life. Due to the fact that the extreme precipitation is happening with increasing frequency and intensity, the study of extreme high flows has been an issue of great importance in recent years. Normally the future discharges are simulated by hydrological models with outputs from the RCMs. However the uncertainties are involved in every step of the processes, including GCMs, emission scenarios, downscaling methods, hydrological models and etc. In this study, the uncertainties in extreme high flows originating from greenhouse gas emission scenarios, hydrological model structures and their parameters were evaluated for the Jinhua River basin, East China. The baseline (1961-1990) climate and future (2011-2040) climate for scenario A1B, A2 and B2 were downscaled by the PRECIS Regional Climate Model with a spatial resolution of 50km×50km from the General Circulation Model (GCM). The outputs of the PRECIS (daily temperature and daily precipitation) were bias corrected by a distribution based method and a linear correction method. Three hydrological models (GR4J, HBV and Xinanjiang) were applied to simulate the daily discharge. The parameter uncertainty in hydrological models were taken into account and quantified by means of the Generalized Likelihood Uncertainty Estimation (GLUE) method. The GLUE was applied for each hydrological model in three emission scenarios. In total 30000 parameter sets were randomly generated within the parameter ranges, in which about 10% parameter sets were above the pre-assigned threshold and represented as the parameter uncertainty. The annual maximum discharge was used for the extreme high flow analysis. There was an overestimation for the monthly precipitation in July, August and September and an overestimation of 6.3-7.8 oC for monthly temperature all year round in the PRECIS output. The biases were reduced after bias

  12. Comparing Sediment Yield Predictions from Different Hydrologic Modeling Schemes

    NASA Astrophysics Data System (ADS)

    Dahl, T. A.; Kendall, A. D.; Hyndman, D. W.

    2015-12-01

    Sediment yield, or the delivery of sediment from the landscape to a river, is a difficult process to accurately model. It is primarily a function of hydrology and climate, but influenced by landcover and the underlying soils. These additional factors make it much more difficult to accurately model than water flow alone. It is not intuitive what impact different hydrologic modeling schemes may have on the prediction of sediment yield. Here, two implementations of the Modified Universal Soil Loss Equation (MUSLE) are compared to examine the effects of hydrologic model choice. Both the Soil and Water Assessment Tool (SWAT) and the Landscape Hydrology Model (LHM) utilize the MUSLE for calculating sediment yield. SWAT is a lumped parameter hydrologic model developed by the USDA, which is commonly used for predicting sediment yield. LHM is a fully distributed hydrologic model developed primarily for integrated surface and groundwater studies at the watershed to regional scale. SWAT and LHM models were developed and tested for two large, adjacent watersheds in the Great Lakes region; the Maumee River and the St. Joseph River. The models were run using a variety of single model and ensemble downscaled climate change scenarios from the Coupled Model Intercomparison Project 5 (CMIP5). The initial results of this comparison are discussed here.

  13. Comparing complementary NWP model performance for hydrologic forecasting for the river Rhine in an operational setting

    NASA Astrophysics Data System (ADS)

    Davids, Femke; den Toom, Matthijs

    2016-04-01

    This paper investigates the performance of complementary NWP models for hydrologic forecasting for the river Rhine, a large river catchment in Central Europe. An operational forecasting system, RWsOS-Rivieren, produces daily forecasts of discharges and water levels at the Water Management Centre Netherlands. A combination of HBV (rainfall-runoff) and SOBEK (hydrodynamic routing) models is used to produce simulations and forecasts for the catchment. Data assimilation is applied both to the model state of SOBEK and to model outputs. The primary function of the operational forecasting system is to provide reliable and accurate forecasts during periods of high water. The secondary main function is producing daily predictions for water management and water transport in The Netherlands. In addition, predicting water levels during drought periods is becoming increasingly important as well. At this moment several complementary deterministic and ensemble NWP models are used to provide the forecasters with predictions with varied initial conditions, such as ICON, ICON-EU Nest, ECMWF-DET, ECMWF-EPS, HiRLAM, COSMO-LEPS and GLAMEPS. ICON and ICON-EU have recently replaced DWD-GME and DWD COSMO-EU. These models provide weather forecasts with different lengths of lead times and also different periods of operational usage. A direct and quantitative comparison is therefore challenging. Nevertheless, it is important to investigate the suitability of the different NWP models for certain lead times and certain weather situations to help support the hydrological forecasters make an informed forecast during an operational crisis. A hindcast study will investigate the performance of these models in the operational system for different lead times and focusing on periods of both high and low water for Lobith, the location of entry of the river Rhine into The Netherlands.

  14. Hydrological modeling of the Jiaoyi watershed (China) using HSPF model.

    PubMed

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

    2014-01-01

    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 (R (2)), 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. PMID:25013863

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

    PubMed Central

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

    2014-01-01

    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. PMID:25013863

  16. Revisiting an interdisciplinary hydrological modelling project. A socio-hydrology (?) example from the early 2000s

    NASA Astrophysics Data System (ADS)

    Seidl, Roman; Barthel, Roland

    2016-04-01

    Interdisciplinary scientific and societal knowledge plays an increasingly important role in global change research. Also, in the field of water resources interdisciplinarity as well as cooperation with stakeholders from outside academia have been recognized as important. In this contribution, we revisit an integrated regional modelling system (DANUBIA), which was developed by an interdisciplinary team of researchers and relied on stakeholder participation in the framework of the GLOWA-Danube project from 2001 to 2011 (Mauser and Prasch 2016). As the model was developed before the current increase in literature on participatory modelling and interdisciplinarity, we ask how a socio-hydrology approach would have helped and in what way it would have made the work different. The present contribution firstly presents the interdisciplinary concept of DANUBIA, mainly with focus on the integration of human behaviour in a spatially explicit, process-based numerical modelling system (Roland Barthel, Janisch, Schwarz, Trifkovic, Nickel, Schulz, and Mauser 2008; R. Barthel, Nickel, Meleg, Trifkovic, and Braun 2005). Secondly, we compare the approaches to interdisciplinarity in GLOWA-Danube with concepts and ideas presented by socio-hydrology. Thirdly, we frame DANUBIA and a review of key literature on socio-hydrology in the context of a survey among hydrologists (N = 184). This discussion is used to highlight gaps and opportunities of the socio-hydrology approach. We show that the interdisciplinary aspect of the project and the participatory process of stakeholder integration in DANUBIA were not entirely successful. However, important insights were gained and important lessons were learnt. Against the background of these experiences we feel that in its current state, socio-hydrology is still lacking a plan for knowledge integration. Moreover, we consider necessary that socio-hydrology takes into account the lessons learnt from these earlier examples of knowledge integration

  17. Uses and limitations of the soil survey in hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Brooks, E.; Boll, J.

    2009-12-01

    One of the greatest challenges in hydrologic modeling is characterizing the effects of soil structure of hydrologic flow paths in complex watersheds. The Predictions in Ungauged Basins (PUB) initiative is pushing scientists to come up with innovative ways to reduce model calibration and predictive uncertainty and improve process understanding. Some of these innovative approaches have included incorporating ‘soft data’ as information for developing conceptual watershed frameworks and guiding calibration. In this study we examine the uses and limitations of the soil survey in hydrologic modeling. County soil surveys were initiated in 1899 and now digital maps are available throughout most of the US. Although these surveys were initially meant to guide selection and development of land, these surveys now include a great wealth of information from specific physical properties to indicators of saturation and development of perched water tables. To what degree does the information in the soil survey improve understanding of dominant hydrologic processes in a watershed? At what point must a hydrologist exercise discretion in using this information? We will discuss the extent to which the soil survey can be used to 1.) conceptualize the basic hydrology of a watershed, 2.) provide input data to a process-based hydrologic model, and 3.) validate spatial predictions of runoff and erosion from distributed hydrologic models. We will demonstrate each of these uses through case studies from multiple ecological regions across the country.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    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

  19. An open-source distributed mesoscale hydrologic model (mHM)

    NASA Astrophysics Data System (ADS)

    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

    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

  20. Climate model uncertainty versus conceptual geological uncertainty in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Sonnenborg, T. O.; Seifert, D.; Refsgaard, J. C.

    2015-09-01

    Projections of climate change impact are associated with a cascade of uncertainties including in CO2 emission scenarios, climate models, downscaling and impact models. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project) forced by the same CO2 scenario (A1B). The changes from the reference period (1991-2010) to the future period (2081-2100) in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context-dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty due to the climate models is more important for groundwater hydraulic heads and stream flow.

  1. Climate model uncertainty vs. conceptual geological uncertainty in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Sonnenborg, T. O.; Seifert, D.; Refsgaard, J. C.

    2015-04-01

    Projections of climate change impact are associated with a cascade of uncertainties including CO2 emission scenario, climate model, downscaling and impact model. The relative importance of the individual uncertainty sources is expected to depend on several factors including the quantity that is projected. In the present study the impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Each projection of future climate is a result of a GCM-RCM model combination (from the ENSEMBLES project) forced by the same CO2 scenario (A1B). The changes from the reference period (1991-2010) to the future period (2081-2100) in projected hydrological variables are evaluated and the effects of geological model and climate model uncertainties are quantified. The results show that uncertainty propagation is context dependent. While the geological conceptualization is the dominating uncertainty source for projection of travel time and capture zones, the uncertainty on the climate models is more important for groundwater hydraulic heads and stream flow.

  2. Capabilities and limitations of detailed hillslope hydrological modelling

    NASA Astrophysics Data System (ADS)

    Bronstert, Axel

    1999-01-01

    Hillslope hydrological modelling is considered to be of great importance for the understanding and quantification of hydrological processes in hilly or mountainous landscapes. In recent years a few comprehensive hydrological models have been developed at the hillslope scale which have resulted in an advanced representation of hillslope hydrological processes (including their interactions), and in some operational applications, such as in runoff and erosion studies at the field scale or lateral flow simulation in environmental and geotechnical engineering. An overview of the objectives of hillslope hydrological modelling is given, followed by a brief introduction of an exemplary comprehensive hillslope model, which stimulates a series of hydrological processes such as interception, evapotranspiration, infiltration into the soil matrix and into macropores, lateral and vertical subsurface soil water flow both in the matrix and preferential flow paths, surface runoff and channel discharge. Several examples of this model are presented and discussed in order to determine the model's capabilities and limitations. Finally, conclusions about the limitations of detailed hillslope modelling are drawn and an outlook on the future prospects of hydrological models on the hillslope scale is given.The model presented performed reasonable calculations of Hortonian surface runoff and subsequent erosion processes, given detailed information of initial soil water content and soil hydraulic conditions. The vertical and lateral soil moisture dynamics were also represented quite well. However, the given examples of model applications show that quite detailed climatic and soil data are required to obtain satisfactory results. The limitations of detailed hillslope hydrological modelling arise from different points: difficulties in the representations of certain processes (e.g. surface crusting, unsaturated-saturated soil moisture flow, macropore flow), problems of small-scale variability

  3. Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation

    NASA Astrophysics Data System (ADS)

    Vrugt, Jasper A.; Ter Braak, Cajo J. F.; Clark, Martyn P.; Hyman, James M.; Robinson, Bruce A.

    2008-12-01

    There is increasing consensus in the hydrologic literature that an appropriate framework for streamflow forecasting and simulation should include explicit recognition of forcing and parameter and model structural error. This paper presents a novel Markov chain Monte Carlo (MCMC) sampler, entitled differential evolution adaptive Metropolis (DREAM), that is especially designed to efficiently estimate the posterior probability density function of hydrologic model parameters in complex, high-dimensional sampling problems. This MCMC scheme adaptively updates the scale and orientation of the proposal distribution during sampling and maintains detailed balance and ergodicity. It is then demonstrated how DREAM can be used to analyze forcing data error during watershed model calibration using a five-parameter rainfall-runoff model with streamflow data from two different catchments. Explicit treatment of precipitation error during hydrologic model calibration not only results in prediction uncertainty bounds that are more appropriate but also significantly alters the posterior distribution of the watershed model parameters. This has significant implications for regionalization studies. The approach also provides important new ways to estimate areal average watershed precipitation, information that is of utmost importance for testing hydrologic theory, diagnosing structural errors in models, and appropriately benchmarking rainfall measurement devices.

  4. Hydrological modelling of urbanized catchments: A review and future directions

    NASA Astrophysics Data System (ADS)

    Salvadore, Elga; Bronders, Jan; Batelaan, Okke

    2015-10-01

    In recent years, the conceptual detail of hydrological models has dramatically increased as a result of improved computational techniques and the availability of spatially-distributed digital data. Nevertheless modelling spatially-distributed hydrological processes can be challenging, particularly in strongly heterogeneous urbanized areas. Multiple interactions occur between urban structures and the water system at various temporal and spatial scales. So far, no universal methodology exists for simulating the urban water system at catchment scale. This paper reviews the state of the art on the scientific knowledge and practice of modelling the urban hydrological system at the catchment scale, with the purpose of identifying current limitations and defining a blueprint for future modelling advances. We compare conceptual descriptions of urban physical hydrological processes on basis of a selection of 43 modelling approaches. The complexity of the urban water system at the catchment scale results in an incomplete understanding of the interaction between urban and natural hydrological systems, and in a high degree of uncertainty. Data availability is still a strong limitation since current modelling practice recognizes the need for high spatial and temporal resolution. Spatio-temporal gaps exist between the physical scales of hydrological processes and the resolution of applied models. Therefore urban hydrology is often simplified either as a study of surface runoff over impervious surfaces or hydraulics of piped systems. Many approaches target very specific objectives and the level of detail in representing physical processes is not consistent. Based on our analysis, we propose a blueprint for a highly complex integrated urban hydrological model. We regard flexibility, in terms of model structure and data assimilation, as the key characteristic for overcoming these limitations. We advocate the use of modular, process-based approaches, which are flexible and adaptable

  5. Improving the representation of hydrologic processes in Earth System Models

    SciTech Connect

    Clark, Martyn P.; Fan, Ying; Lawrence, David M.; Adam, Jennifer C.; Bolster, Diogo; Gochis, David J.; Hooper, Richard P.; Kumar, Mukesh; Leung, L. Ruby; Mackay, D. Scott; Maxwell, Reed M.; Shen, Chaopeng; Swenson, Sean C.; Zeng, Xubin

    2015-08-21

    Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale models, such as the land components of Earth System Models (ESMs), do not yet represent the terrestrial water cycle in a fully integrated manner or resolve the finer-scale processes that can dominate large-scale water budgets. This paper reviews the current representation of hydrologic processes in ESMs and identifies the key opportunities for improvement. This review suggests that (1) the development of ESMs has not kept pace with modeling advances in hydrology, both through neglecting key processes (e.g., groundwater) and neglecting key aspects of spatial variability and hydrologic connectivity; and (2) many modeling advances in hydrology can readily be incorporated into ESMs and substantially improve predictions of the water cycle. Accelerating modeling advances in ESMs requires comprehensive hydrologic benchmarking activities, in order to systematically evaluate competing modeling alternatives, understand model weaknesses, and prioritize model development needs. This demands stronger collaboration, both through greater engagement of hydrologists in ESM development and through more detailed evaluation of ESM processes in research watersheds. Advances in the representation of hydrologic process in ESMs can substantially improve energy, carbon and nutrient cycle prediction capabilities through the fundamental role the water cycle plays in regulating these cycles.

  6. Modeling the hydrological patterns on Pantanal wetlands, Brazil

    NASA Astrophysics Data System (ADS)

    Castro, A. A.; Cuartas, A.; Coe, M. T.; Koumrouyan, A.; Panday, P. K.; Lefebvre, P.; Padovani, C.; Costa, M. H.; de Oliveira, G. S.

    2014-12-01

    The Pantanal of Brazil is one of the world's largest wetland regions. It is located within the 370,000 km2 Alto Paraguai Basin (BAP). In wet years almost 15% of the total area of the basin can be flooded (approximately 53,000 km2). The hydrological cycle is particularly important in the Pantanal in the transport of materials, and the transfer of energy between atmospheric, aquatic, and terrestrial systems. The INLAND (Integrated Land Surface Model) terrestrial ecosystem model is coupled with the THMB hydrological model to examine the hydrological balance and water dynamics for this region. The INLAND model is based on the IBIS dynamic vegetation model, while THMB represents the river, wetland and lake dynamics of the land surface. The modeled hydrological components are validated with surface and satellite-based estimates of precipitation (gridded observations from CRU v. 3.21, reanalysis data from ERA-interim, and TRMM estimates), evapotranspiration (MODIS and Land Flux-Eval dataset), total runoff (discharge data from ANA-Agência Nacional das Águas - Brazil), and terrestrial water storage (GRACE). Results show that the coupled hydrological model adequately represents the water cycle components, the river discharge and flooded areas. Model simulations are further used to study the influences of climatic variations on the hydrological components, river network, and the inundated areas in the Pantanal.

  7. RHydro - Hydrological models and tools to represent and analyze hydrological data in R

    NASA Astrophysics Data System (ADS)

    Reusser, Dominik; Buytaert, Wouter

    2010-05-01

    In hydrology, basic equations and procedures keep being implemented from scratch by scientist, with the potential for errors and inefficiency. The use of libraries can overcome these problems. Other scientific disciplines such as mathematics and physics have benefited significantly from such an approach with freely available implementations for many routines. As an example, hydrological libraries could contain: Major representations of hydrological processes such as infiltration, sub-surface runoff and routing algorithms. Scaling functions, for instance to combine remote sensing precipitation fields with rain gauge data Data consistency checks Performance measures. Here we present a beginning for such a library implemented in the high level data programming language R. Currently, Top-model, data import routines for WaSiM-ETH as well basic visualization and evaluation tools are implemented. The design is such, that a definition of import scripts for additional models is sufficient to have access to the full set of evaluation and visualization tools.

  8. Hydrological responses to dynamically and statistically downscaled climate model output

    USGS Publications Warehouse

    Wilby, R.L.; Hay, L.E.; Gutowski, W.J., Jr.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.

    2000-01-01

    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 stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.

  9. 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. ...

  10. Future hydrological extremes: the uncertainty from multiple global climate and global hydrological models

    NASA Astrophysics Data System (ADS)

    Giuntoli, I.; Vidal, J.-P.; Prudhomme, C.; Hannah, D. M.

    2015-05-01

    Projections of changes in the hydrological cycle from global hydrological models (GHMs) driven by global climate models (GCMs) are critical for understanding future occurrence of hydrological extremes. However, uncertainties remain large and need to be better assessed. In particular, recent studies have pointed to a considerable contribution of GHMs that can equal or outweigh the contribution of GCMs to uncertainty in hydrological projections. Using six GHMs and five GCMs from the ISI-MIP multi-model ensemble, this study aims: (i) to assess future changes in the frequency of both high and low flows at the global scale using control and future (RCP8.5) simulations by the 2080s, and (ii) to quantify, for both ends of the runoff spectrum, GCMs and GHMs contributions to uncertainty using a two-way ANOVA. Increases are found in high flows for northern latitudes and in low flows for several hotspots. Globally, the largest source of uncertainty is associated with GCMs, but GHMs are the greatest source in snow-dominated regions. More specifically, results vary depending on the runoff metric, the temporal (annual and seasonal) and regional scale of analysis. For instance, uncertainty contribution from GHMs is higher for low flows than it is for high flows, partly owing to the different processes driving the onset of the two phenomena (e.g. the more direct effect of the GCMs' precipitation variability on high flows). This study provides a comprehensive synthesis of where future hydrological extremes are projected to increase and where the ensemble spread is owed to either GCMs or GHMs. Finally, our results underline the need for improvements in modelling snowmelt and runoff processes to project future hydrological extremes and the importance of using multiple GCMs and GHMs to encompass the uncertainty range provided by these two sources.

  11. Modelling hydrological management for the restoration of acidified floating fens

    NASA Astrophysics Data System (ADS)

    Dekker, Stefan C.; Barendregt, Aat; Bootsma, Margien C.; Schot, Paul P.

    2005-12-01

    Wetlands show a large decline in biodiversity. To protect and restore this biodiversity, many restoration projects are carried out. Hydrology in wetlands controls the chemical and biological processes and may be the most important factor regulating wetland function and development. Hydrological models may be used to simulate these processes and to evaluate management scenarios for restoration. HYDRUS2D, a combined saturated-unsaturated groundwater flow and transport model, is presented. This simulates near-surface hydrological processes in an acidified floating fen, with the aim to evaluate the effect of hydrological restoration in terms of conditions for biodiversity. In the acidified floating fen in the nature reserve Ilperveld (The Netherlands), a trench system was dug for the purpose of creating a runoff channel for acid rainwater in wet periods and to enable circum-neutral surface water to enter the fen in dry periods. The model is calibrated against measured conductivity values for a 5 year period. From the model simulations, it was found that lateral flow in the floating raft is limited. Furthermore, the model shows that the best management option is a combination of trenches and inundation, which gave the best soil water quality in the root zone. It is concluded that hydrological models can be used for the calculation of management scenarios in restoration projects. The combined saturated-unsaturated model concept used in this paper is able to incorporate the governing hydrological processes in the wetland root zones. Copyright

  12. Progress and Prospects of Anti-HBV Gene Therapy Development

    PubMed Central

    Maepa, Mohube B.; Roelofse, Ilke; Ely, Abdullah; Arbuthnot, Patrick

    2015-01-01

    Despite the availability of an effective vaccine against hepatitis B virus (HBV), chronic infection with the virus remains a major global health concern. Current drugs against HBV infection are limited by emergence of resistance and rarely achieve complete viral clearance. This has prompted vigorous research on developing better drugs against chronic HBV infection. Advances in understanding the life cycle of HBV and improvements in gene-disabling technologies have been impressive. This has led to development of better HBV infection models and discovery of new drug candidates. Ideally, a regimen against chronic HBV infection should completely eliminate all viral replicative intermediates, especially covalently closed circular DNA (cccDNA). For the past few decades, nucleic acid-based therapy has emerged as an attractive alternative that may result in complete clearance of HBV in infected patients. Several genetic anti-HBV strategies have been developed. The most studied approaches include the use of antisense oligonucleotides, ribozymes, RNA interference effectors and gene editing tools. This review will summarize recent developments and progress made in the use of gene therapy against HBV. PMID:26263978

  13. Genomic Methylation Inhibits Expression of Hepatitis B Virus Envelope Protein in Transgenic Mice: A Non-Infectious Mouse Model to Study Silencing of HBV Surface Antigen Genes

    PubMed Central

    Graumann, Franziska; Churin, Yuri; Tschuschner, Annette; Reifenberg, Kurt; Glebe, Dieter; Roderfeld, Martin; Roeb, Elke

    2015-01-01

    Objective The Hepatitis B virus genome persists in the nucleus of virus infected hepatocytes where it serves as template for viral mRNA synthesis. Epigenetic modifications, including methylation of the CpG islands contribute to the regulation of viral gene expression. The present study investigates the effects of spontaneous age dependent loss of hepatitis B surface protein- (HBs) expression due to HBV-genome specific methylation as well as its proximate positive effects in HBs transgenic mice. Methods Liver and serum of HBs transgenic mice aged 5–33 weeks were analyzed by Western blot, immunohistochemistry, serum analysis, PCR, and qRT-PCR. Results From the third month of age hepatic loss of HBs was observed in 20% of transgenic mice. The size of HBs-free area and the relative number of animals with these effects increased with age and struck about 55% of animals aged 33 weeks. Loss of HBs-expression was strongly correlated with amelioration of serum parameters ALT and AST. In addition lower HBs-expression went on with decreased ER-stress. The loss of surface protein expression started on transcriptional level and appeared to be regulated epigenetically by DNA methylation. The amount of the HBs-expression correlated negatively with methylation of HBV DNA in the mouse genome. Conclusions Our data suggest that methylation of specific CpG sites controls gene expression even in HBs-transgenic mice with truncated HBV genome. More important, the loss of HBs expression and intracellular aggregation ameliorated cell stress and liver integrity. Thus, targeted modulation of HBs expression may offer new therapeutic approaches. Furthermore, HBs-transgenic mice depict a non-infectious mouse model to study one possible mechanism of HBs gene silencing by hypermethylation. PMID:26717563

  14. Using climate model ensemble forecasts for seasonal hydrologic prediction

    NASA Astrophysics Data System (ADS)

    Wood, Andrew Whitaker

    Seasonal hydrologic forecasting has long played an invaluable role in the development and use of water resources. Despite notable advances in the science and practice of climate prediction, current approaches of hydrologists and water managers largely fail to incorporate seasonal climate forecast information that has become operationally available during the last decade. This study is motivated by the view that a combination of hydrologic and climate prediction methods affords a new opportunity to improve hydrologic forecast skill. A relatively direct statistical approach for achieving this combination (i.e., downscaling) was formulated that used ensemble climate model forecasts with a six month lead time produced by the NCEP/CPC Global Spectral Model (GSM) as input to the macroscale Variable Infiltration Capacity hydrologic model to produce ensemble runoff and streamflow forecasts. The approach involved the bias correction of climate model precipitation and temperature fields, and spatial and temporal disaggregation from monthly climate model scale (about 2 degrees latitude by longitude) fields to daily hydrology model scale (1/8 degrees) inputs. A qualitative evaluation of the approach in the eastern U.S. suggested that it was successful in translating climate forecast signals to local hydrologic variables and streamflow, but that the dominant influence on forecast results tended to be persistence in initial hydrologic conditions. The suitability of the statistical downscaling approach for supporting hydrologic simulation was then assessed (using a continuous retrospective 20-year climate simulation from the DOE Parallel Climate Model) relative to dynamical downscaling via a regional, meso-scale climate model. The statistical approach generally outperformed the dynamical approach, in that the dynamical approach alone required additional bias-correction to reproduce the retrospective hydrology as well as the statistical approach. Finally, using 21 years of

  15. A question driven socio-hydrological modeling process

    NASA Astrophysics Data System (ADS)

    Garcia, M.; Portney, K.; Islam, S.

    2016-01-01

    Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human-induced changes may propagate through this coupled system. Modeling of coupled human-hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding model conceptualization. There are no universally accepted laws of human behavior as there are for the physical systems; furthermore, a shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope and detail to remain contingent on and adaptive to the question context. We demonstrate the utility of this process by revisiting a classic question in water resources engineering on reservoir operation rules: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result, per capita demand decreases during

  16. A multiphase model of the dynamics of HBV infection in HBeAg-negative patients during pegylated interferon-alpha2a, lamivudine and combination therapy.

    PubMed

    Colombatto, Piero; Civitano, Luigi; Bizzarri, Ranieri; Oliveri, Filippo; Choudhury, Somesh; Gieschke, Ronald; Bonino, Ferruccio; Brunetto, Maurizia R

    2006-01-01

    Using a multiphase bio-mathematical model, we studied the dynamics of hepatitis B virus (HBV) infection in 72 HBeAg-negative patients who received 48 weeks of either lamivudine (3TC; 25 patients); pegylated interferon-alpha2a (peg-IFN-alpha2a) 180 mg weekly plus 3TC (23 patients), or peg-IFN-alpha2a 180 mg weekly plus placebo (24 patients). During the first month of therapy most of the 3TC -/+ peg-IFN-alpha2a treated patients showed a multiphase decay of viral load: during the first two phases, where we hypothesized a direct inhibition of virus production, the mean viral production per infected cell was reduced by 2.22 log10 and 2.36 log10, respectively. At variance, peg-IFN-alpha2a treated patients had a biphasic profile: the first phase HBV DNA decline was slower than that observed in 3TC patients (mean HBV DNA t(1/2) = 1.6 +/- 1.1 days and 9.5 +/- 3.0 h, respectively) and the direct antiviral effect reduced virus production by 1.14 log10. From day 14 onwards (third or second phase according to multi- or biphasic patterns), HBV DNA declined mainly because of the infected hepatocyte clearance that slowed down in approximately 50% of the patients from day 35, possibly because of a negative feedback on the immune system activity. Computing the number of infected cells at the end of therapy we found that peg-IFN-alpha2a and 3TC monotherapy determined a similar reduction of infected hepatocytes (mean: -3.3 log10), whereas there was a greater reduction in combination therapy patients (-5.0 versus -3.3 log10, P = 0.039). In conclusion, peg-IFN-alpha2a, in spite of having direct antiviral activity lower than that of 3TC, achieved a comparable reduction of infected hepatocytes, possibly because of a higher infected cell clearance rate. PMID:16640101

  17. Doing hydrology forwards: Using field experimental data to inform a conceptual model of landscape driven hydrologic connectivity

    NASA Astrophysics Data System (ADS)

    Marshall, L. A.; Smith, T. J.; McGlynn, B. L.; Jencso, K. G.

    2011-12-01

    Given the known tradeoffs between hydrologic model complexity, efficiency, and predictive uncertainty there is an increasing desire to identify conceptual catchment models that accurately reflect catchment processes whilst preserving model identifiability. These models should specify the relationship between catchment form (including landscape topography, vegetation patterns, and stream networks) and hydrologic functioning (including streamflow patterns). We present a new hydrologic modeling approach that uses the distribution of landscape elements along the stream network as a template by which landscape-scale hydrologic connectivity and catchment runoff can be simulated. Here, we define hydrologic connectivity as the transient hydrological linkages between landscape elements and the stream. Our conceptualization emphasizes the importance of hydrologic connections between hillslope-riparian-stream (HRS) zones. Observations indicate that it is the frequency of these HRS hydrologic connections that drive aggregate catchment runoff response, rather than the magnitude of flux at any one connection. We applied the model to the Stringer Creek watershed of the Tenderfoot Creek Experimental Forest (TCEF), located in central Montana, USA. Detailed field observations were used to inform the underpinnings of the model and to corroborate internal consistency of the model's simulations. The ability of the model to simulate internal dynamics without conditioning the parameters on these data indicate the potential of this model to be more convincingly extrapolated to other hydrologic conditions and tested at catchments of varying topographic structure. Current and future work is aimed at further developing the modeling approach and testing the limits of its applicability across space and time.

  18. Effects of uncertainties in hydrological modelling. A case study of a mountainous catchment in Southern Norway

    NASA Astrophysics Data System (ADS)

    Engeland, Kolbjørn; Steinsland, Ingelin; Johansen, Stian Solvang; Petersen-Øverleir, Asgeir; Kolberg, Sjur

    2016-05-01

    In this study, we explore the effect of uncertainty and poor observation quality on hydrological model calibration and predictions. The Osali catchment in Western Norway was selected as case study and an elevation distributed HBV-model was used. We systematically evaluated the effect of accounting for uncertainty in parameters, precipitation input, temperature input and streamflow observations. For precipitation and temperature we accounted for the interpolation uncertainty, and for streamflow we accounted for rating curve uncertainty. Further, the effects of poorer quality of precipitation input and streamflow observations were explored. Less information about precipitation was obtained by excluding the nearest precipitation station from the analysis, while reduced information about the streamflow was obtained by omitting the highest and lowest streamflow observations when estimating the rating curve. The results showed that including uncertainty in the precipitation and temperature inputs has a negligible effect on the posterior distribution of parameters and for the Nash-Sutcliffe (NS) efficiency for the predicted flows, while the reliability and the continuous rank probability score (CRPS) improves. Less information in precipitation input resulted in a shift in the water balance parameter Pcorr, a model producing smoother streamflow predictions, giving poorer NS and CRPS, but higher reliability. The effect of calibrating the hydrological model using streamflow observations based on different rating curves is mainly seen as variability in the water balance parameter Pcorr. When evaluating predictions, the best evaluation scores were not achieved for the rating curve used for calibration, but for rating curves giving smoother streamflow observations. Less information in streamflow influenced the water balance parameter Pcorr, and increased the spread in evaluation scores by giving both better and worse scores.

  19. Evaluation of regional-scale hydrological models using multiple criteria for 12 large river basins on all continents

    NASA Astrophysics Data System (ADS)

    Huang, Shaochun; Krysanova, Valentina; Hattermann, Fred; Vetter, Tobias; Flörke, Martina; Samaniego, Luis; Arheimer, Berit; Yang, Tao; van Griensven, Ann; Su, Buda; Gelfan, Alexander; Breuer, Lutz; Haberlandt, Uwe

    2016-04-01

    A good performance of hydrological impact models under historical climate and land use conditions is a prerequisite for reliable projections under climate change. The evaluation of nine regional-scale hydrological models considering monthly river discharge, long-term average seasonal dynamics and extremes was performed in the framework of the ISI-MIP project for 12 large river basins on all continents. The modelling tools include: ECOMAG, HBV, HYMOD, HYPE, mHM, SWAT, SWIM, VIC and WaterGAP3. These models were evaluated for the following basins: the Rhine and Tagus in Europe, the Niger and Blue Nile in Africa, the Ganges, Lena, Upper Yellow and Upper Yangtze in Asia, the Upper Mississippi, MacKenzie and Upper Amazon in America, and Darling in Australia. The model calibration and validation was done using WATCH climate data for all cases. The model outputs were evaluated using twelve statistical criteria to assess the fidelity of model simulations for monthly discharge, seasonal dynamics, flow duration curves, extreme floods and low flow. The reproduction of monthly discharge and seasonal dynamics was successful in all basins except the Darling, and the high flows and flood characteristics were also captured satisfactory in most cases. However, the criteria for low flow were below the thresholds in many cases. An overview of this collaborative experiment and main results on model evaluation will be presented.

  20. Using satellite precipitation data for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Commandeur, Tom

    2013-04-01

    strategies for the MPE data. Since the MPE data is an estimate rather than a measurement, the data presents the need for validation. Comparison of the MPE data with ground radar and ground measurements will show the usability for hydrological modeling according to realistic scenarios. The end purpose is improving precipitation estimates by calibration, using ground radar and ground measurements where available. This study also researches their relations and combination approach.

  1. Validation of the hydrological cycle of ECMWF and NCEP reanalyses using the MPI hydrological discharge model

    NASA Astrophysics Data System (ADS)

    Hagemann, Stefan; Gates, Lydia Dümenil

    2001-01-01

    To validate the hydrological cycle of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) reanalyses in comparison with observed river discharge, a hydrological discharge model is used to compute the corresponding river discharge. The HD model requires daily time series of surface runoff and drainage from the soil as input fields. As it turned out that a direct application to the reanalyses was not possible, a simplified land surface scheme was developed to compute runoff and drainage fields from daily reanalysis values of total precipitation and 2 m temperature. These fields were then used as input to the global simulation of river discharge with the discharge model. Results show several shortcomings of the two reanalyses in representing the hydrological cycle at the land surface. The water balance is not closed, and the snowmelt is not incorporated in the runoff and drainage fields of either of the two reanalyses. In addition, the NCEP reanalysis overestimates summer precipitation and evapotranspiration for most parts of the Northern Hemisphere, while the ECMWF reanalysis underestimates 2 m temperatures in high latitudes during the winter and spring. In the monsoon region the hydrological cycle is well represented by both reanalyses, especially over India.

  2. Neural network modelling of non-linear hydrological relationships

    NASA Astrophysics Data System (ADS)

    Abrahart, R. J.; See, L. M.

    2007-09-01

    Two recent studies have suggested that neural network modelling offers no worthwhile improvements in comparison to the application of weighted linear transfer functions for capturing the non-linear nature of hydrological relationships. The potential of an artificial neural network to perform simple non-linear hydrological transformations under controlled conditions is examined in this paper. Eight neural network models were developed: four full or partial emulations of a recognised non-linear hydrological rainfall-runoff model; four solutions developed on an identical set of inputs and a calculated runoff coefficient output. The use of different input combinations enabled the competencies of solutions developed on a reduced number of parameters to be assessed. The selected hydrological model had a limited number of inputs and contained no temporal component. The modelling process was based on a set of random inputs that had a uniform distribution and spanned a modest range of possibilities. The initial cloning operations permitted a direct comparison to be performed with the equation-based relationship. It also provided more general information about the power of a neural network to replicate mathematical equations and model modest non-linear relationships. The second group of experiments explored a different relationship that is of hydrological interest; the target surface contained a stronger set of non-linear properties and was more challenging. Linear modelling comparisons were performed against traditional least squares multiple linear regression solutions developed on identical datasets. The reported results demonstrate that neural networks are capable of modelling non-linear hydrological processes and are therefore appropriate tools for hydrological modelling.

  3. Robert Horton and the Application of Distributed Hydrological Models

    NASA Astrophysics Data System (ADS)

    Beven, K. J.

    2004-12-01

    The name of Walter Langbein provides a link with the hydrology of Robert Horton. Langbein both worked with Horton and was the very first recipient of the AGU Horton Medal in 1976. In his response to the award, Langbein paid tribute to Horton's wide ranging interests as evidenced in the "several dozen research files in the National Archive". A recent search of some of these files has revealed some very interesting insights into Horton's hydrological concepts and, in particular, his appreciation of the difficulties involved in hydrological analysis and distributed prediction. Despite modern computer technology and the availability of geographical information systems, these insights are still relevant and important today and should be the basis for an approach to hydrological prediction that recognises the limitations of applying general, but incomplete, theory to specific places. An analysis of the sources of uncertainty in the modelling process leads to some suggestions about how we should proceed in the application of models in the future.

  4. Coupled Hydrological and Hydraulic Modeling for Flood Mapping

    NASA Astrophysics Data System (ADS)

    Drobot, Radu; Draghia, Aurelian

    2014-05-01

    The delineation of the flooded areas involves both hydrological and hydraulic modeling. Usually, the hydrological and hydraulic processes are separately treated. In the proposed methodology, the coupled modeling of the hydrological and hydraulic processes is used. The calibration and validation of the hydrological parameters is undertaken based on historical floods using the corresponding precipitations for the same period. The calibration process was more complicated in the presence of reservoirs, when not only the discharges downstream but also the water level in the reservoirs had to be accurately reproduced. The time step for precipitation is 1 hour, corresponding to the concentration time of the smallest catchments. The maximum annual precipitation for different time steps (1; 3; 6; 24 hours) were statistically processed and based on these results the cumulative rainfall curves and the synthetic hyetographs were derived. The rainfall duration is depending on the concentration time. Mike 11 with UHM module based on SCS model was used for coupled hydrological and hydraulic modeling. The coupled hydrological and hydraulic simulation for the scaled precipitation leads both at the computation of the components which contribute to the generation of the P% flood at the Hydrometric stations as well as to the determination of the discharge hydrograph along the main river. Based on these results the flood hazard maps were obtained using a DTM based on Lidar data. The methodology was applied for a river basin in Romania of 12500 km2.

  5. Hydrologic Modeling Strategy for the Islamic Republic of Mauritania, Africa

    USGS Publications Warehouse

    Friedel, Michael J.

    2008-01-01

    The government of Mauritania is interested in how to maintain hydrologic balance to ensure a long-term stable water supply for minerals-related, domestic, and other purposes. Because of the many complicating and competing natural and anthropogenic factors, hydrologists will perform quantitative analysis with specific objectives and relevant computer models in mind. Whereas various computer models are available for studying water-resource priorities, the success of these models to provide reliable predictions largely depends on adequacy of the model-calibration process. Predictive analysis helps us evaluate the accuracy and uncertainty associated with simulated dependent variables of our calibrated model. In this report, the hydrologic modeling process is reviewed and a strategy summarized for future Mauritanian hydrologic modeling studies.

  6. Coupling Hydrologic and Hydrodynamic Models to Estimate PMF

    NASA Astrophysics Data System (ADS)

    Felder, G.; Weingartner, R.

    2015-12-01

    Most sophisticated probable maximum flood (PMF) estimations derive the PMF from the probable maximum precipitation (PMP) by applying deterministic hydrologic models calibrated with observed data. This method is based on the assumption that the hydrological system is stationary, meaning that the system behaviour during the calibration period or the calibration event is presumed to be the same as it is during the PMF. However, as soon as a catchment-specific threshold is reached, the system is no longer stationary. At or beyond this threshold, retention areas, new flow paths, and changing runoff processes can strongly affect downstream peak discharge. These effects can be accounted for by coupling hydrologic and hydrodynamic models, a technique that is particularly promising when the expected peak discharge may considerably exceed the observed maximum discharge. In such cases, the coupling of hydrologic and hydraulic models has the potential to significantly increase the physical plausibility of PMF estimations. This procedure ensures both that the estimated extreme peak discharge does not exceed the physical limit based on riverbed capacity and that the dampening effect of inundation processes on peak discharge is considered. Our study discusses the prospect of considering retention effects on PMF estimations by coupling hydrologic and hydrodynamic models. This method is tested by forcing PREVAH, a semi-distributed deterministic hydrological model, with randomly generated, physically plausible extreme precipitation patterns. The resulting hydrographs are then used to externally force the hydraulic model BASEMENT-ETH (riverbed in 1D, potential inundation areas in 2D). Finally, the PMF estimation results obtained using the coupled modelling approach are compared to the results obtained using ordinary hydrologic modelling.

  7. Open source data assimilation framework for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

    2013-04-01

    An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent

  8. Sensitivity of climate model to hydrology

    NASA Astrophysics Data System (ADS)

    Ye, Duzheng

    The importance of land—surface processes in affecting climate change has been analyzed and discussed by Namias [1962,1963]. The physics of the land-surface processes affect the climate because the ground hydrology, together with the vegetation and soil, determine the surface moisture availability which, in turn, controls the partition between the sensible and latent heat fluxes [Rowntree, 1984] and also the transfer of momentum. Further the vegetation cover and the soil moisture content can determine the ground surface albedo in snowless conditions. Therefore the heat balance and water balance in the planetary boundary layer are highly influenced by the hydrological processes. Through the planetary boundary layer, the influence of the ground hydrological processes can be felt through the whole troposphere [Yeh, et al., 1984; Rowntree and Bolton, 1983]. Here a crucial factor is the soil moisture content. In the region of dry anomalies, the following sequence of events tends to occur: a decrease of evaporation, a ground surface warming with an increase of sensible heat flux, a wanning of lower layers of the atmosphere with a decrease of relative humidity (due to decrease of evaporation and warming of lower atmophere), a decrease of precipitation with a cooling of the atmosphere higher up (due to decrease of latent heat), and then a change of upper air circulation [Rowntree and Bolton, 1983]. It is the decrease of precipitation which will cause the initial dry anomaly to persist. In the region of moist anomalies, the opposite sequence of events tends to occur.

  9. Strategies for using remotely sensed data in hydrologic models

    NASA Technical Reports Server (NTRS)

    Peck, E. L.; Keefer, T. N.; Johnson, E. R. (Principal Investigator)

    1981-01-01

    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.

  10. Impact of the use of two different hydrological models on scores of hydrological ensemble forecasts

    NASA Astrophysics Data System (ADS)

    Ramos, M. H.; Thirel, G.; Andréassian, V.; Martin, E.

    2009-04-01

    The aim of this study is two-fold. Firstly, a comparative analysis is conducted to assess the quality of streamflow forecasts issued by two different modelling conceptualizations of catchment response, both driven by the same weather ensemble prediction system. Secondly, the results are jointly investigated with a view to providing guidance on the operational use of ensemble forecast products for flood warning at national hydrologic forecasting services. The study is based on weather forecasts from the ensemble prediction system PEARP of Météo-France, which was originally developed to better predict high impact storms in France. PEARP forecasts are based on the global spectral ARPEGE model zoomed over France. Initial perturbations are generated by the singular vector technique. The model runs 11 perturbed members for a forecast range of 60 hours. In this study, the two hydrological modelling approaches used are: 1) the coupled physically-based hydro-meteorological model SAFRAN-ISBA-MODCOU developed at Météo-France and based on a fully distributed catchment model, and 2) the GRPE forecasting system developed at Cemagref and based on a lumped soil-moisture-accounting type rainfall-runoff model. Both models were set up and tested on about 1000 catchments in France. For this study, a common subset of about 250 gauging stations representative of a wide range of upstream areas and hydro-meteorological conditions was selected. The discharges simulated by both systems are compared over an 18-month period (March 2005-September 2006). Skill scores are then computed for the first two days of forecast range and the performance of both hydrologic ensemble forecasting systems is assessed. The results of this experiment are examined with a focus on the setting up of a fully operational product in real-time hydrological forecasting. The combined use of forecasts issued by different systems is a demand of French operational forecasting service to better guide flood warning

  11. Spatial Resolution and Catchment Size Interaction of Soil Hydrological Properties for Hydrological Modeling

    NASA Astrophysics Data System (ADS)

    Libohova, Zamir; Bowling, Laura C.; Owens, Phillip R.; Schoeneberger, Philip; Wysocki, Douglas; Wills, Skye; Lindbo, David

    2016-04-01

    Spatial resolution of soil hydrologic properties is critical for distributed hydrological model streamflow simulations. Soils from US Soil Survey Geographic (SSURGO) Database are mapped at scales varying from 1:12,000 to 65,000. Related to these scales are also soil hydrological properties, which could vary spatially outside of the common SSURGO scale range. The objective of this research was to assess the role of the spatial resolution of soil depth on simulated hydrological response for various watershed sizes using the Distributed Hydrology Soil Vegetation Model (DHSVM). The study site was Hall Creek watershed a 56 km2 in size located in Dubois County in southern Indiana, USA. The watershed size was divided in 55 sub-watersheds varying in size from less than 5 km2 to 56 km2. The grid size spatial resolution of soil hydrological properties varied from 10x10, 30x30 and 90x90m. The simulated streamflow metrics were annual mean, minimum and maximum streamflow, and R-B Flashiness, which measures the variability in streamflow between successive days highlighting the fluctuation of discharge relative to total discharge. The slopes of the regression of simulated stream discharge parameters versus watershed size were used to assess the presence of interaction. In addition, the coefficient of variation was used to assess the variability for the R-B index, annual mean, annual minimum and maximum stream discharge across different model resolutions within each watershed category. The slope for 10x10 and 30x30m spatial resolution for annual mean, and minimum streamflow were not significantly different from zero across all watershed sizes indicating lack of interaction. However, slope for the R-B flashiness was significantly different from zero for the 90x90 m grid size indicating that watershed size change is sensitive at this spatial resolution. The variability of R-B index, annual mean and annual minimum hydrologic metrics decreased with increasing watershed size but

  12. Impact of improved snowmelt modelling in a monthly hydrological model.

    NASA Astrophysics Data System (ADS)

    Folton, Nathalie; Garcia, Florine

    2016-04-01

    The quantification and the management of water resources at the regional scale require hydrological models that are both easy to implement and efficient. To be reliable and robust, these models must be calibrated and validated on a large number of catchments that are representative of various hydro-meteorological conditions, physiographic contexts, and specific hydrological behavior (e.g. mountainous catchments). The GRLoiEau monthly model, with its simple structure and its two free parameters, answer our need of such a simple model. It required the development of a snow routine to model catchments with temporarily snow-covered areas. The snow routine developed here does not claim to represent physical snowmelt processes but rather to simulate them globally on the catchment. The snowmelt equation is based on the degree-day method which is widely used by the hydrological community, in particular in engineering studies (Etchevers 2000). A potential snowmelt (Schaefli et al. 2005) was computed, and the parameters of the snow routine were regionalized for each mountain area. The GRLoiEau parsimonious structure requires meteorological data. They come from the distributed mesoscale atmospheric analysis system SAFRAN, which provides estimations of daily solid and liquid precipitations and temperatures on a regular square grid at the spatial resolution of 8*8 km², throughout France. Potential evapotranspiration was estimated using the formula by Oudin et al. (2005). The aim of this study is to improve the quality of monthly simulations for ungauged basins, in particular for all types of mountain catchments, without increasing the number of free parameters of the model. By using daily SAFRAN data, the production store and snowmelt can be run at a daily time scale. The question then arises whether simulating the monthly flows using a production function at a finer time step would improve the results. And by using the SAFRAN distributed climate series, a distributed approach

  13. A strategy for diagnosing and interpreting hydrological model nonstationarity

    NASA Astrophysics Data System (ADS)

    Westra, Seth; Thyer, Mark; Leonard, Michael; Kavetski, Dmitri; Lambert, Martin

    2014-06-01

    This paper presents a strategy for diagnosing and interpreting hydrological nonstationarity, aiming to improve hydrological models and their predictive ability under changing hydroclimatic conditions. The strategy consists of four elements: (i) detecting potential systematic errors in the calibration data; (ii) hypothesizing a set of "nonstationary" parameterizations of existing hydrological model structures, where one or more parameters vary in time as functions of selected covariates; (iii) trialing alternative stationary model structures to assess whether parameter nonstationarity can be reduced by modifying the model structure; and (iv) selecting one or more models for prediction. The Scott Creek catchment in South Australia and the lumped hydrological model GR4J are used to illustrate the strategy. Streamflow predictions improve significantly when the GR4J parameter describing the maximum capacity of the production store is allowed to vary in time as a combined function of: (i) an annual sinusoid; (ii) the previous 365 day rainfall and potential evapotranspiration; and (iii) a linear trend. This improvement provides strong evidence of model nonstationarity. Based on a range of hydrologically oriented diagnostics such as flow-duration curves, the GR4J model structure was modified by introducing an additional calibration parameter that controls recession behavior and by making actual evapotranspiration dependent only on catchment storage. Model comparison using an information-theoretic measure (the Akaike Information Criterion) and several hydrologically oriented diagnostics shows that the GR4J modifications clearly improve predictive performance in Scott Creek catchment. Based on a comparison of 22 versions of GR4J with different representations of nonstationarity and other modifications, the model selection approach applied in the exploratory period (used for parameter estimation) correctly identifies models that perform well in a much drier independent

  14. Advancing Collaboration through Hydrologic Data and Model Sharing

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.

    2015-12-01

    HydroShare is an online, collaborative system for open sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined primarily by standardized metadata, content data models for each resource type, and an overarching resource data model based on the Open Archives Initiative's Object Reuse and Exchange (OAI-ORE) standard and a hierarchical file packaging system called "BagIt". HydroShare expands the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated to include geospatial and multidimensional space-time datasets commonly used in hydrology. HydroShare also includes new capability for sharing models, model components, and analytical tools and will take advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. It also supports web services and server/cloud based computation operating on resources for the execution of hydrologic models and analysis and visualization of hydrologic data. HydroShare uses iRODS as a network file system for underlying storage of datasets and models. Collaboration is enabled by casting datasets and models as "social objects". Social functions include both private and public sharing, formation of collaborative groups of users, and value-added annotation of shared datasets and models. The HydroShare web interface and social media functions were developed using the Django web application framework coupled to iRODS. Data visualization and analysis is supported through the Tethys Platform web GIS software stack. Links to external systems are supported by RESTful web service interfaces to HydroShare's content. This presentation will introduce the HydroShare functionality developed to date and describe ongoing development of functionality to support collaboration and integration of data and models.

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

    NASA Technical Reports Server (NTRS)

    Schimel, David S.

    1992-01-01

    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.

  16. Models for hydrologic design of evapotranspiration landfill covers.

    PubMed

    Hauser, Victor L; Gimon, Dianna M; Bonta, James V; Howell, Terry A; Malone, Robert W; Williams, Jimmy R

    2005-09-15

    The technology used in landfill covers is changing, and an alternative cover called the evapotranspiration (ET) landfill cover is coming into use. Important design requirements are prescribed by Federal rules and regulations for conventional landfill covers but not for ET landfill covers. There is no accepted hydrologic model for ET landfill cover design. This paper describes ET cover requirements and design issues, and assesses the accuracy of the EPIC and HELP hydrologic models when used for hydrologic design of ET covers. We tested the models against high-quality field measurements available from lysimeters maintained by the Agricultural Research Service of the U.S. Department of Agriculture at Coshocton, Ohio, and Bushland, Texas. The HELP model produced substantial errors in estimating hydrologic variables. The EPIC model estimated ET and deep percolation with errors less than 7% and 5%, respectively, and accurately matched extreme events with an error of less than 2% of precipitation. The EPIC model is suitable for use in hydrologic design of ET landfill covers. PMID:16201652

  17. Geographically isolated wetlands and watershed hydrology: A modified model analysis

    NASA Astrophysics Data System (ADS)

    Evenson, Grey R.; Golden, Heather E.; Lane, Charles R.; D'Amico, Ellen

    2015-10-01

    Geographically isolated wetlands (GIWs) are defined as wetlands that are completely surrounded by uplands. While GIWs are therefore spatially isolated, field-based studies have observed a continuum of hydrologic connections between these systems and other surface waters. Yet few studies have quantified the watershed-scale aggregate effects of GIWs on downstream hydrology. Further, existing modeling approaches to evaluate GIW effects at a watershed scale have utilized conceptual or spatially disaggregated wetland representations. Working towards wetland model representations that use spatially explicit approaches may improve current scientific understanding concerning GIW effects on the downstream hydrograph. The objective of this study was to quantify the watershed-scale aggregate effects of GIWs on downstream hydrology while emphasizing a spatially explicit representation of GIWs and GIW connectivity relationships. We constructed a hydrologic model for a ∼202 km2 watershed in the Coastal Plain of North Carolina, USA, a watershed with a substantial population of GIWs, using the Soil and Water Assessment Tool (SWAT). We applied a novel representation of GIWs within the model, facilitated by an alternative hydrologic response unit (HRU) definition and modifications to the SWAT source code that extended the model's "pothole" representation. We then executed a series of scenarios to assess the downstream hydrologic effect of various distributions of GIWs within the watershed. Results suggest that: (1) GIWs have seasonally dependent effects on baseflow; (2) GIWs mitigate peak flows; and (3) The presence of GIWs on the landscape impacts the watershed water balance. This work demonstrates a means of GIW simulation with improved spatial detail while showing that GIWs, in-aggregate, have a substantial effect on downstream hydrology in the studied watershed.

  18. Hydrological model uncertainty due to spatial evapotranspiration estimation methods

    NASA Astrophysics Data System (ADS)

    Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

    2016-05-01

    Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

  19. Linking Hydrology and Atmospheric Sciences in Continental Water Dynamics Modeling

    NASA Astrophysics Data System (ADS)

    David, C. H.; Gochis, D. J.; Maidment, D. R.; Wilhelmi, O.

    2006-12-01

    Atmospheric observation and model output datasets as well as hydrologic datasets are increasingly becoming available on a continental scale. Although the availability of these datasets could allow large-scale water dynamics modeling, the different objects and semantics used in atmospheric science and hydrology set barriers to their interoperability. Recent work has demonstrated the feasibility for modeling terrestrial water dynamics for the continental United States of America. Continental water dynamics defines the interaction of the hydrosphere, the land surface and subsurface at spatial scales ranging from point to continent. The improved version of the National Hydrographic Dataset (NHDPlus, an integrated suite of geospatial datasets stored in a vector and raster GIS format) was used as hydrologic and elevation data input to the Noah community Land Surface Model, developed at NCAR. Noah was successfully run on a watershed in the Ohio River Basin with NHDPlus inputs. The use of NHDPlus as input data for Noah is a crucial improvement for community modeling efforts allowing users to by-pass much of the time consumed in Digital Elevation Model and hydrological network processing. Furthermore, the community Noah land surface model, in its hydrologically-enhanced configuration, is capable of providing flow inputs for a river dynamics model. Continued enhancement of Noah will, as a consequence, be beneficial to the atmospheric science community as well as to the hydrologic community. Ongoing research foci include using a diversity of weather drivers as an input to Noah, and investigation of how to use land surface model outputs for river forecasting, using both the ArcHydro and OpenMI frameworks.

  20. Modelling hydrological effects of wetland restoration: a differentiated view.

    PubMed

    Staes, J; Rubarenzya, M H; Meire, P; Willems, P

    2009-01-01

    The paper presents findings of a conjunctive hydrological and ecological study into habitat restoration and catchment hydrology. Physically-based, fully distributed hydrological modelling was coupled with spatial analysis and wetland scenario generation techniques to simulate potential effects of restoring lower, middle, and upper catchment wetlands. In the past, anthropogenic interference of this catchments' landscape for agriculture and settlement has left most wetland areas drained, and brought the natural functioning of the ecosystem into conflict with human needs. Many eco-hydrology studies conclude that such disturbances result in a more extreme hydrological regime. The study objectives were to develop and study innovative methods for habitat restoration, and understand the potential hydrological impacts of each approach. The study aims to analyze the scenarios and whether the hydrological response is influenced by the topological placement of the restoration sites. Land-use change scenarios are developed on the basis of physical characteristics and consider the credibility of transitions from current land-use. This study focused on the position of the wetlands in the catchment and hydrological typology. Wetland restoration scenarios are created for different geographical settings within the catchment. A distinction is made between groundwater dependent wetlands and wetlands that are influenced by in-stream water tables or surface water inundations. Results show that there is little effect on the total annual water budget. The results point to river valley rewetting as having the effect of decreasing the paved overland component of stream flow, and increasing the saturated zone flow component. It promoted groundwater recharge. There was no increase of peak flows due to headwater wetlands, contrary to some sources (Bullock & Acreman 2003). The catchments' actual evapotranspiration and root zone water responses were found to be varied over the analysis points

  1. Modeling of reservoir operation in UNH global hydrological model

    NASA Astrophysics Data System (ADS)

    Shiklomanov, Alexander; Prusevich, Alexander; Frolking, Steve; Glidden, Stanley; Lammers, Richard; Wisser, Dominik

    2015-04-01

    Climate is changing and river flow is an integrated characteristic reflecting numerous environmental processes and their changes aggregated over large areas. Anthropogenic impacts on the river flow, however, can significantly exceed the changes associated with climate variability. Besides of irrigation, reservoirs and dams are one of major anthropogenic factor affecting streamflow. They distort hydrological regime of many rivers by trapping of freshwater runoff, modifying timing of river discharge and increasing the evaporation rate. Thus, reservoirs is an integral part of the global hydrological system and their impacts on rivers have to be taken into account for better quantification and understanding of hydrological changes. We developed a new technique, which was incorporated into WBM-TrANS model (Water Balance Model-Transport from Anthropogenic and Natural Systems) to simulate river routing through large reservoirs and natural lakes based on information available from freely accessible databases such as GRanD (the Global Reservoir and Dam database) or NID (National Inventory of Dams for US). Different formulations were applied for unregulated spillway dams and lakes, and for 4 types of regulated reservoirs, which were subdivided based on main purpose including generic (multipurpose), hydropower generation, irrigation and water supply, and flood control. We also incorporated rules for reservoir fill up and draining at the times of construction and decommission based on available data. The model were tested for many reservoirs of different size and types located in various climatic conditions using several gridded meteorological data sets as model input and observed daily and monthly discharge data from GRDC (Global Runoff Data Center), USGS Water Data (US Geological Survey), and UNH archives. The best results with Nash-Sutcliffe model efficiency coefficient in the range of 0.5-0.9 were obtained for temperate zone of Northern Hemisphere where most of large

  2. Satellite-derived potential evapotranspiration for distributed hydrologic runoff modeling

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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.

  3. Understanding uncertainty in process-based hydrological models

    NASA Astrophysics Data System (ADS)

    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

    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

  4. WEB-DHM: A distributed biosphere hydrological model developed by coupling a simple biosphere scheme with a hillslope hydrological model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...

  5. Performance measures and criteria for hydrologic and water quality models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Performance measures and criteria are essential for model calibration and validation. This presentation will include a summary of one of the papers that will be included in the 2014 Hydrologic and Water Quality Model Calibration & Validation Guidelines Special Collection of the ASABE Transactions. T...

  6. Hydrologic and water quality teminology as applied to modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A survey of literature and examination in particular of terminology use in a previous special collection of modeling calibration and validation papers has been conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and val...

  7. A fully integrated SWAT-MODFLOW hydrologic model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Soil and Water Assessment Tool (SWAT) and MODFLOW models are being used worldwide for managing surface and groundwater water resources. The SWAT models hydrological processes occurring at the surface including shallow aquifers, while MODFLOW simulate groundwater processes. However, neither SWAT ...

  8. The Use of Simulation Models in Teaching Geomorphology and Hydrology.

    ERIC Educational Resources Information Center

    Kirkby, Mike; Naden, Pam

    1988-01-01

    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)

  9. Ensemble stream flow predictions, a way towards better hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Edlund, C.

    2009-04-01

    The hydrological forecasting division at SMHI has been using hydrological EPS and hydrological probabilities forecasts operationally since some years ago. The inputs to the hydrological model HBV are the EPS forecasts from ECMWF. From the ensemble, non-exceedance probabilities are estimated and final correction of the ensemble spread, based on evaluation is done. Ensemble stream flow predictions are done for about 80 indicator basins in Sweden, where there is a real-time discharge gauge. The EPS runs are updated daily against the latest observed discharge. Flood probability maps for exceeding a certain threshold, i.e. a certain warning level, are produced automatically once a day. The flood probabilistic forecasts are based on a HBV- model application, (called HBV-Sv, HBV Sweden) that covers the whole country and consist of 1001 subbasins with an average size between 200 and 700 km2. Probabilities computations for exceeding a certain warning level are made for each one of these 1001 subbasins. Statistical flood levels have been calculated for each river sub-basin. Hydrological probability forecasts should be seen as an early warning product that can give better support in decision making to end-users communities, for instance Civil Protections Offices and County Administrative Boards, within flood risk management. The main limitations with probability forecasts are: on one hand, difficulties to catch small-scale rain (mainly due to resolution of meteorological models); on the other hand, the hydrological model can't be updated against observations in all subbasins. The benefits of working with probabilities consist, first of all, of a new approach when working with flood risk management and scenarios. A probability forecast can give an early indication for Civil Protection that "something is going to happen" and to gain time in preparing aid operations. The ensemble stream flow prediction at SMHI is integrated with the national forecasting system and the products

  10. A physically-based Distributed Hydrologic Model for Tropical Catchments

    NASA Astrophysics Data System (ADS)

    Abebe, N. A.; Ogden, F. L.

    2010-12-01

    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 and persistent biological activity and a large amount of rain. The Agua Salud catchments located within the Panama Canal Watershed, Panama, are such catchments identified by steep rolling topography, deep soils derived from weathered bedrock, and limited exposed bedrock. Tropical soils are highly affected by soil cracks, decayed tree roots and earthworm burrows forming a network of preferential flow paths that drain to a perched water table, which forms at a depth where the vertical hydraulic conductivity is significantly reduced near the bottom of the bioturbation layer. We have developed a physics-based, spatially distributed, multi-layered hydrologic model to simulate the dominant processes in these tropical watersheds. The model incorporates the major flow processes including overland flow, channel flow, matrix and non-Richards film flow infiltration, lateral downslope saturated matrix and non-Darcian pipe flow in the bioturbation layer, and deep saturated groundwater flow. Emphasis is given to the modeling of subsurface unsaturated zone soil moisture dynamics and the saturated preferential lateral flow from the network of macrospores. Preliminary results indicate that the model has the capability to simulate the complex hydrological processes in the catchment and will be a useful tool in the ongoing comprehensive ecohydrological studies in tropical catchments, and help improve our understanding of the hydrological effects of deforestation and aforestation.

  11. Analysis of Streamflow Predictive Uncertainty using Multiple Hydrologic Models in Climate Change Impact Study

    NASA Astrophysics Data System (ADS)

    Yang, P.; Najafi, M.; Moradkhani, H.

    2010-12-01

    Based on the statistically downscaled outputs from 8 global climate model projections and 2 emission scenarios we assess the uncertainties associated with GCMs and hydrologic models by means of multi-modeling. As there is no conceivable reason that any hydrologic model is performing better under all circumstances, four hydrologic models are selected for the hydrologic impact study: the Sacramento Soil Moisture Accounting (SAC-SMA) model, Conceptual HYdrologic MODel (HYMOD), Thornthwaite-Mather model (TM) and the Precipitation Runoff Modeling System (PRMS). Three objective functions are adopted to calibrate each model. The hydrologic model simulations are combined using the Bayesian Model Averaging (BMA) method. This study shows that the application of the BMA in analyzing the models ensemble is useful in minimizing the uncertainty in selecting the hydrologic model selection. It is also concluded that the hydrologic model uncertainty is considerably smaller than GCM uncertainty, except during the dry season.

  12. Neural Networks for Hydrological Modeling Tool for Operational Purposes

    NASA Astrophysics Data System (ADS)

    Bhatt, Divya; Jain, Ashu

    2010-05-01

    Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. 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

  13. Use of hydrologic and hydrodynamic modeling for ecosystem restoration

    USGS Publications Warehouse

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

    2011-01-01

    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.

  14. Brokering as a framework for hydrological model repeatability

    NASA Astrophysics Data System (ADS)

    Fuka, Daniel; Collick, Amy; MacAlister, Charlotte; Braeckel, Aaron; Wright, Dawn; Jodha Khalsa, Siri; Boldrini, Enrico; Easton, Zachary

    2015-04-01

    Data brokering aims to provide those in the the sciences with quick and repeatable access to data that represents physical, biological, and chemical characteristics; specifically to accelerate scientific discovery. Environmental models are useful tools to understand the behavior of hydrological systems. Unfortunately, parameterization of these hydrological models requires many different data, from different sources, and from different disciplines (e.g., atmospheric, geoscience, ecology). In basin scale hydrological modeling, the traditional procedure for model initialization starts with obtaining elevation models, land-use characterizations, soils maps, and weather data. It is often the researcher's past experience with these datasets that determines which datasets will be used in a study, and often newer, or more suitable data products will exist. An added complexity is that various science communities have differing data formats, storage protocols, and manipulation methods, which makes use by a non native user exceedingly difficult and time consuming. We demonstrate data brokering as a means to address several of these challenges. We present two test case scenarios in which researchers attempt to reproduce hydrological model results using 1) general internet based data gathering techniques, and 2) a scientific data brokering interface. We show that data brokering can increase the efficiency with which data are obtained, models are initialized, and results are analyzed. As an added benefit, it appears brokering can significantly increase the repeatability of a given study.

  15. Modeller subjectivity and calibration impacts on hydrological model applications: an event-based comparison for a road-adjacent catchment in south-east Norway.

    PubMed

    Kalantari, Zahra; Lyon, Steve W; Jansson, Per-Erik; Stolte, Jannes; French, Helen K; Folkeson, Lennart; Sassner, Mona

    2015-01-01

    Identifying a 'best' performing hydrologic model in a practical sense is difficult due to the potential influences of modeller subjectivity on, for example, calibration procedure and parameter selection. This is especially true for model applications at the event scale where the prevailing catchment conditions can have a strong impact on apparent model performance and suitability. In this study, two lumped models (CoupModel and HBV) and two physically-based distributed models (LISEM and MIKE SHE) were applied to a small catchment upstream of a road in south-eastern Norway. All models were calibrated to a single event representing typical winter conditions in the region and then applied to various other winter events to investigate the potential impact of calibration period and methodology on model performance. Peak flow and event-based hydrographs were simulated differently by all models leading to differences in apparent model performance under this application. In this case-study, the lumped models appeared to be better suited for hydrological events that differed from the calibration event (i.e., events when runoff was generated from rain on non-frozen soils rather than from rain and snowmelt on frozen soil) while the more physical-based approaches appeared better suited during snowmelt and frozen soil conditions more consistent with the event-specific calibration. This was due to the combination of variations in subsurface conditions over the eight events considered, the subsequent ability of the models to represent the impact of the conditions (particularly when subsurface conditions varied greatly from the calibration event), and the different approaches adopted to calibrate the models. These results indicate that hydrologic models may not only need to be selected on a case-by-case basis but also have their performance evaluated on an application-by-application basis since how a model is applied can be equally important as inherent model structure. PMID

  16. Assessing the hydrologic restoration of an urbanized area via integrated distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Trinh, D. H.; Chui, T. F. M.

    2013-04-01

    Green structures (e.g. green roof and bio-retention systems) are adopted to mitigate the hydrological impacts of urbanization. However, our current understanding of the urbanization impacts are often process-specific (e.g. peak flow or storm recession), and our characterizations of green structures are often on a local scale. This study uses an integrated distributed hydrological model, Mike SHE, to evaluate the urbanization impacts on both overall water balance and water regime, and also the effectiveness of green structures at a catchment level. Three simulations are carried out for a highly urbanized catchment in the tropics, representing pre-urbanized, urbanized and restored conditions. Urbanization transforms vegetated areas into impervious surfaces, resulting in 20 and 66% reductions in infiltration and base flow respectively, and 60 to 100% increase in peak outlet discharge. Green roofs delay the peak outlet discharge by 2 h and reduce the magnitude by 50%. Bio-retention systems mitigate the peak discharge by 50% and also enhance infiltration by 30%. The combination of green roofs and bio-retention systems even reduces the peak discharge to the pre-urbanized level. The simulation results obtained are independent of field data, enabling a generic model for understanding hydrological changes during the different phases of urbanization. This will benefit catchment level planning of green structures in other urban areas.

  17. Assessing the hydrologic restoration of an urbanized area via an integrated distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Trinh, D. H.; Chui, T. F. M.

    2013-12-01

    Green structures (e.g. green roof and bio-retention systems) are adopted to mitigate the hydrological impacts of urbanization. However, our current understanding of urbanization impacts are often process-specific (e.g. peak flow or storm recession), and our characterizations of green structures are often on a local scale. This study uses an integrated distributed hydrological model, Mike SHE, to evaluate the urbanization impacts on both overall water balance and water regime, and also the effectiveness of green structures at a catchment level. Three simulations are carried out for a highly urbanized catchment in the tropics, representing pre-urbanized, urbanized and restored conditions. Urbanization transforms vegetated areas into impervious surfaces, resulting in 20 and 66% reductions in infiltration and base flow respectively, and 60 to 100% increase in peak outlet discharge. Green roofs delay the peak outlet discharge by 2 h and reduce the magnitude by 50%. Bio-retention systems mitigate the peak discharge by 50% and also enhance infiltration by 30%. The combination of green roofs and bio-retention systems even reduces the peak discharge to the pre-urbanized level. The simulation results obtained are independent of field data, enabling a generic model for understanding hydrological changes during the different phases of urbanization. This will benefit catchment-level planning of green structures in other urban areas.

  18. The reduction of hydrological models for less tedious practical applications

    NASA Astrophysics Data System (ADS)

    Delay, Frederick; Ackerer, Philippe

    2016-02-01

    This work evidences that inconsistencies may persist between the complexity of hydrological models and available data for model documentation and application. For example, the integrated hydrological models handle the whole water dynamics over a watershed, but are only conditioned on data that incompletely record the dimensions of the flow. It is suggested to reduce this type of model by aggregating the physical background to diminish its Euclidean dimension. Paradoxically, the complexity in the physics of a model may also result in some reduction. For example, handling a flow by relying upon a dual continuum approach conceals the structural heterogeneity of the reservoir in the model equations. The parameterization at the scale of the aquifer becomes much simpler and the model reduction is here associated with diminishing the effort to condition the model onto data.

  19. Development of human impact modeling in global hydrology

    NASA Astrophysics Data System (ADS)

    Bierkens, M. F.; Wada, Y.

    2015-12-01

    During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments comparing water availability with water use. These first efforts mostly relied on statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by proxy by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand. In this talk we review the evolution of human impact modelling in global hydrology, e.g.: confronting yearly water demand with water availability using a water scarcity index; calculating a water scarcity index at monthly time scale; adding groundwater depletion; adding dams and reservoirs; fully integrating water use (abstraction, application, consumption, return flow) in the hydrology; simulating the effects of land use change. A number of challenges are identified that hamper the further development of current water use modelling as well as prohibit realistic modelling of future water use. We also speculate on pathways to overcome these challenges.

  20. High resolution distributed hydrological modeling for river flood forecasting

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2014-12-01

    High resolution distributed hydrological model can finely describe the river basin hydrological processes, thus having the potential to improve the flood forecasting capabilities, and is regarded as the next generation flood forecast model. But there are great challenges in deploying it in real-time river flood forecasting, such as the awesome computation resources requirement, parameter determination, high resolution precipitation assimilation and uncertainty controls. Liuxihe Model is a physically-based distributed hydrological model proposed mainly for catchment flood forecasting, which is a process-based hydrological model. In this study, based on Liuxihe Model, a parallel computation algorithm for Liuxihe model flood forecasting is proposed, and a cloudy computation system is developed on a high performance computer, this largely improves the applicability of Liuxihe Model in large river. Without the parallel computation, the Liuxihe Model is computationally incapable in application to rivers with drainage area bigger than 10,000km2 at the grid size of 100m. With the parallel computation, the Liuxihe Model is used in a river with a drainage area of 60,000km2, and could be expended indefinitely. Based on this achievement, a model parameter calibration method by using Particle Swale Optimization is proposed and tested in several rivers in southern China with drainage areas ranging from several hundreds to tens thousands km2, and with the model parameter optimization, the model performance has been approved largely. The modeling approach is also tested for coupling radar-based precipitation estimation/prediction for small catchment flash forecasting and for coupling quantitative precipitation estimation/prediction from meteorological model for large river flood forecasting.

  1. A surface hydrology model for regional vector borne disease models

    NASA Astrophysics Data System (ADS)

    Tompkins, Adrian; Asare, Ernest; Bomblies, Arne; Amekudzi, Leonard

    2016-04-01

    Small, sun-lit temporary pools that form during the rainy season are important breeding sites for many key mosquito vectors responsible for the transmission of malaria and other diseases. The representation of this surface hydrology in mathematical disease models is challenging, due to their small-scale, dependence on the terrain and the difficulty of setting soil parameters. Here we introduce a model that represents the temporal evolution of the aggregate statistics of breeding sites in a single pond fractional coverage parameter. The model is based on a simple, geometrical assumption concerning the terrain, and accounts for the processes of surface runoff, pond overflow, infiltration and evaporation. Soil moisture, soil properties and large-scale terrain slope are accounted for using a calibration parameter that sets the equivalent catchment fraction. The model is calibrated and then evaluated using in situ pond measurements in Ghana and ultra-high (10m) resolution explicit simulations for a village in Niger. Despite the model's simplicity, it is shown to reproduce the variability and mean of the pond aggregate water coverage well for both locations and validation techniques. Example malaria simulations for Uganda will be shown using this new scheme with a generic calibration setting, evaluated using district malaria case data. Possible methods for implementing regional calibration will be briefly discussed.

  2. Legacy model integration for enhancing hydrologic interdisciplinary research

    NASA Astrophysics Data System (ADS)

    Dozier, A.; Arabi, M.; David, O.

    2013-12-01

    Many challenges are introduced to interdisciplinary research in and around the hydrologic science community due to advances in computing technology and modeling capabilities in different programming languages, across different platforms and frameworks by researchers in a variety of fields with a variety of experience in computer programming. Many new hydrologic models as well as optimization, parameter estimation, and uncertainty characterization techniques are developed in scripting languages such as Matlab, R, Python, or in newer languages such as Java and the .Net languages, whereas many legacy models have been written in FORTRAN and C, which complicates inter-model communication for two-way feedbacks. However, most hydrologic researchers and industry personnel have little knowledge of the computing technologies that are available to address the model integration process. Therefore, the goal of this study is to address these new challenges by utilizing a novel approach based on a publish-subscribe-type system to enhance modeling capabilities of legacy socio-economic, hydrologic, and ecologic software. Enhancements include massive parallelization of executions and access to legacy model variables at any point during the simulation process by another program without having to compile all the models together into an inseparable 'super-model'. Thus, this study provides two-way feedback mechanisms between multiple different process models that can be written in various programming languages and can run on different machines and operating systems. Additionally, a level of abstraction is given to the model integration process that allows researchers and other technical personnel to perform more detailed and interactive modeling, visualization, optimization, calibration, and uncertainty analysis without requiring deep understanding of inter-process communication. To be compatible, a program must be written in a programming language with bindings to a common

  3. Reducing equifinality of hydrological models by integrating Functional Streamflow Disaggregation

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  4. Impact of multicollinearity on small sample hydrologic regression models

    NASA Astrophysics Data System (ADS)

    Kroll, Charles N.; Song, Peter

    2013-06-01

    Often hydrologic regression models are developed with ordinary least squares (OLS) procedures. The use of OLS with highly correlated explanatory variables produces multicollinearity, which creates highly sensitive parameter estimators with inflated variances and improper model selection. It is not clear how to best address multicollinearity in hydrologic regression models. Here a Monte Carlo simulation is developed to compare four techniques to address multicollinearity: OLS, OLS with variance inflation factor screening (VIF), principal component regression (PCR), and partial least squares regression (PLS). The performance of these four techniques was observed for varying sample sizes, correlation coefficients between the explanatory variables, and model error variances consistent with hydrologic regional regression models. The negative effects of multicollinearity are magnified at smaller sample sizes, higher correlations between the variables, and larger model error variances (smaller R2). The Monte Carlo simulation indicates that if the true model is known, multicollinearity is present, and the estimation and statistical testing of regression parameters are of interest, then PCR or PLS should be employed. If the model is unknown, or if the interest is solely on model predictions, is it recommended that OLS be employed since using more complicated techniques did not produce any improvement in model performance. A leave-one-out cross-validation case study was also performed using low-streamflow data sets from the eastern United States. Results indicate that OLS with stepwise selection generally produces models across study regions with varying levels of multicollinearity that are as good as biased regression techniques such as PCR and PLS.

  5. An educational model for ensemble streamflow simulation and uncertainty analysis

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

    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.

  6. Hydrologic and water quality models: Performance measures and evaluation criteria

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Performance measures and corresponding criteria constitute an important aspect of calibration and validation of any hydrological and water quality (H/WQ) model. As new and improved methods and information are developed, it is essential that performance measures and criteria be updated. Therefore, th...

  7. Information and complexity measures for hydrologic model evaluation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrological models are commonly evaluated through the residual-based performance measures such as the root-mean square error or efficiency criteria. Such measures, however, do not evaluate the degree of similarity of patterns in simulated and measured time series. The objective of this study was to...

  8. Hydrologic and water quality models: Use, calibration, and validation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper introduces a special collection of 22 research articles that present and discuss calibration and validation concepts in detail for hydrologic and water quality models by their developers and presents a broad framework for developing the American Society of Agricultural and Biological Engi...

  9. Green roof hydrologic performance and modeling: a review.

    PubMed

    Li, Yanling; Babcock, Roger W

    2014-01-01

    Green roofs reduce runoff from impervious surfaces in urban development. This paper reviews the technical literature on green roof hydrology. Laboratory experiments and field measurements have shown that green roofs can reduce stormwater runoff volume by 30 to 86%, reduce peak flow rate by 22 to 93% and delay the peak flow by 0 to 30 min and thereby decrease pollution, flooding and erosion during precipitation events. However, the effectiveness can vary substantially due to design characteristics making performance predictions difficult. Evaluation of the most recently published study findings indicates that the major factors affecting green roof hydrology are precipitation volume, precipitation dynamics, antecedent conditions, growth medium, plant species, and roof slope. This paper also evaluates the computer models commonly used to simulate hydrologic processes for green roofs, including stormwater management model, soil water atmosphere and plant, SWMS-2D, HYDRUS, and other models that are shown to be effective for predicting precipitation response and economic benefits. The review findings indicate that green roofs are effective for reduction of runoff volume and peak flow, and delay of peak flow, however, no tool or model is available to predict expected performance for any given anticipated system based on design parameters that directly affect green roof hydrology. PMID:24569270

  10. Hydrologic and water quality modeling: spatial and temporal considerations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrologic and water quality models are used to help manage water resources by investigating the effects of climate, land use, land management, and water management on water resources. Each water-related issue is better investigated at a specific scale, which can vary spatially from point to watersh...

  11. Hydrological modeling using a multi-site stochastic weather generator

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Weather data is usually required at several locations over a large watershed, especially when using distributed models for hydrological simulations. In many applications, spatially correlated weather data can be provided by a multi-site stochastic weather generator which considers the spatial correl...

  12. Generating distributed forcing fields for spatial hydrologic modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial hydrologic modeling requires the development of distributed forcing fields of weather and precipitation. This is particularly difficult in mountainous regions of the western US, where measurement sites are limited and the landscape is dominated by complex terrain and variations in vegetatio...

  13. Modeling the Hydrologic Processes of a Permeable Pavement System

    EPA Science Inventory

    A permeable pavement system can capture stormwater to reduce runoff volume and flow rate, improve onsite groundwater recharge, and enhance pollutant controls within the site. A new unit process model for evaluating the hydrologic performance of a permeable pavement system has be...

  14. Sharing hydrological knowledge: an international comparison of hydrological models in the Meuse River Basin

    NASA Astrophysics Data System (ADS)

    Bouaziz, Laurène; Sperna Weiland, Frederiek; Drogue, Gilles; Brauer, Claudia; Weerts, Albrecht

    2015-04-01

    International collaboration between institutes and universities working and studying the same transboundary basin is needed for consensus building around possible effects of climate change and climate adaptation measures. Education, experience and expert knowledge of the hydrological community have resulted in the development of a great variety of model concepts, calibration and analysis techniques. Intercomparison could be a first step into consensus modeling or an ensemble based modeling strategy. Besides these practical objectives, such an intercomparison offers the opportunity to explore different ranges of models and learn from each other, hopefully increasing the insight into the hydrological processes that play a role in the transboundary basin. In this experiment, different international research groups applied their rainfall-runoff model in the Ourthe, a Belgium sub-catchment of the Meuse. Data preparation involved the interpolation of hourly precipitation station data collected and owned by the Service Public de Wallonie1 and the freely available E-OBS dataset for daily temperature (Haylock et al., 2008). Daily temperature was disaggregated to hourly values and potential evaporation was derived with the Hargreaves formula. The data was made available to the researchers through an FTP server. The protocol for the modeling involved a split-sample calibration and validation for pre-defined periods. Objective functions for calibration were fixed but the calibration algorithm was a free choice of the research groups. The selection of calibration algorithm was considered model dependent because lumped as well as computationally less efficient distributed models were used. For each model, an ensemble of best performing parameter sets was selected and several performance metrics enabled to assess the models' abilities to simulate discharge. The aim of this experiment is to identify those model components and structures that increase model performance and may best

  15. Test plan for hydrologic modeling of protective barriers

    SciTech Connect

    Fayer, M.J.

    1990-03-01

    Pacific Northwest Laboratory prepared this test plan for the Model Applications and Validation Task of the Hanford Protective Barriers Program, which is managed by Westinghouse Hanford Company. The objectives of this plan are to outline the conceptual hydrologic model of protective barriers, discuss the available computer codes, describe the interrelationships between the modeling task and the other tasks of the Protective Barriers Program, present the barrier modeling tests, and estimate the schedule and costs of the hydrologic modeling task for planning purposes by the Protective Barriers Program. The purpose of the tests is to validate models that will be used to confirm the long-term performance of the barrier in minimizing drainage. A second purpose of the tests is to provide information to other parts of the Protective Barriers Program that require such information. 26 refs., 2 figs., 3 tabs.

  16. A visual interface for the SUPERFLEX hydrological modelling framework

    NASA Astrophysics Data System (ADS)

    Gao, H.; Fenicia, F.; Kavetski, D.; Savenije, H. H. G.

    2012-04-01

    The SUPERFLEX framework is a modular modelling system for conceptual hydrological modelling at the catchment scale. This work reports the development of a visual interface for the SUPERFLEX model. This aims to enhance the communication between the hydrologic experimentalists and modelers, in particular further bridging the gap between the field soft data and the modeler's knowledge. In collaboration with field experimentalists, modelers can visually and intuitively hypothesize different model architectures and combinations of reservoirs, select from a library of constructive functions to describe the relationship between reservoirs' storage and discharge, specify the shape of lag functions and, finally, set parameter values. The software helps hydrologists take advantage of any existing insights into the study site, translate it into a conceptual hydrological model and implement it within a computationally robust algorithm. This tool also helps challenge and contrast competing paradigms such as the "uniqueness of place" vs "one model fits all". Using this interface, hydrologists can test different hypotheses and model representations, and stepwise build deeper understanding of the watershed of interest.

  17. JAMS - a software platform for modular hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kralisch, Sven; Fischer, Christian

    2015-04-01

    Current challenges of understanding and assessing the impacts of climate and land use changes on environmental systems demand for an ever-increasing integration of data and process knowledge in corresponding simulation models. Software frameworks that allow for a seamless creation of integrated models based on less complex components (domain models, process simulation routines) have therefore gained increasing attention during the last decade. JAMS is an Open-Source software framework that has been especially designed to cope with the challenges of eco-hydrological modelling. This is reflected by (i) its flexible approach for representing time and space, (ii) a strong separation of process simulation components from the declarative description of more complex models using domain specific XML, (iii) powerful analysis and visualization functions for spatial and temporal input and output data, and (iv) parameter optimization and uncertainty analysis functions commonly used in environmental modelling. Based on JAMS, different hydrological and nutrient-transport simulation models were implemented and successfully applied during the last years. We will present the JAMS core concepts and give an overview of models, simulation components and support tools available for that framework. Sample applications will be used to underline the advantages of component-based model designs and to show how JAMS can be used to address the challenges of integrated hydrological modelling.

  18. Geographically Isolated Wetlands and Catchment Hydrology: A Modified Model Analyses

    NASA Astrophysics Data System (ADS)

    Evenson, G.; Golden, H. E.; Lane, C.; D'Amico, E.

    2014-12-01

    Geographically isolated wetlands (GIWs), typically defined as depressional wetlands surrounded by uplands, support an array of hydrological and ecological processes. However, key research questions concerning the hydrological connectivity of GIWs and their impacts on downgradient surface waters remain unanswered. This is particularly important for regulation and management of these systems. For example, in the past decade United States Supreme Court decisions suggest that GIWs can be afforded protection if significant connectivity exists between these waters and traditional navigable waters. Here we developed a simulation procedure to quantify the effects of various spatial distributions of GIWs across the landscape on the downgradient hydrograph using a refined version of the Soil and Water Assessment Tool (SWAT), a catchment-scale hydrological simulation model. We modified the SWAT FORTRAN source code and employed an alternative hydrologic response unit (HRU) definition to facilitate an improved representation of GIW hydrologic processes and connectivity relationships to other surface waters, and to quantify their downgradient hydrological effects. We applied the modified SWAT model to an ~ 202 km2 catchment in the Coastal Plain of North Carolina, USA, exhibiting a substantial population of mapped GIWs. Results from our series of GIW distribution scenarios suggest that: (1) Our representation of GIWs within SWAT conforms to field-based characterizations of regional GIWs in most respects; (2) GIWs exhibit substantial seasonally-dependent effects upon downgradient base flow; (3) GIWs mitigate peak flows, particularly following high rainfall events; and (4) The presence of GIWs on the landscape impacts the catchment water balance (e.g., by increasing groundwater outflows). Our outcomes support the hypothesis that GIWs have an important catchment-scale effect on downgradient streamflow.

  19. Spatial transferability of landscape-based hydrological models

    NASA Astrophysics Data System (ADS)

    Gao, Hongkai; Hrachowitz, Markus; Fenicia, Fabrizio; Gharari, Shervan; Sriwongsitanon, Nutchanart; Savenije, Hubert

    2015-04-01

    Landscapes, mainly distinguished by land surface topography and vegetation cover, are crucial in defining runoff generation mechanisms, interception capacity and transpiration processes. Landscapes information provides modelers with a way to take into account catchment heterogeneity, while simultaneously keeping model complexity low. A landscape-based hydrological modelling framework (FLEX-Topo), with parallel model structures, was developed and tested in various catchments with diverse climate, topography and land cover conditions. Landscape classification is the basic and most crucial procedure to create a tailor-made model for a certain catchment, as it explicitly relates hydrologic similarity to landscape similarity, which is the base of this type of models. Therefore, the study catchment is classified into different landscapes units that fulfil similar hydrological function, based on classification criteria such as the height above the nearest drainage, slope, aspect and land cover. At present, to suggested model includes four distinguishable landscapes: hillslopes, terraces/plateaus, riparian areas, and glacierized areas. Different parallel model structures are then associated with the different landscape units to describe their different dominant runoff generation mechanisms. These hydrological units are parallel and only connected by groundwater reservoir. The transferability of this landscape-based model can then be compared with the transferability of a lumped model. In this study, FLEX-Topo was developed and tested in three study sites: two cold-arid catchments in China (the upper Heihe River and the Urumqi Glacier No1 catchment), and one tropical catchment in Thailand (the upper Ping River). Stringent model tests indicate that FLEX-Topo, allowing for more process heterogeneity than lumped model formulations, exhibits higher capabilities to be spatially transferred. Furthermore, the simulated water balances, including internal fluxes, hydrograph

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

    NASA Astrophysics Data System (ADS)

    Buytaert, Wouter; Vitolo, Claudia

    2013-04-01

    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

  1. eWaterCycle: A global operational hydrological forecasting model

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Development of an operational hyper-resolution hydrological global model is a central goal of the eWaterCycle project (www.ewatercycle.org). This operational model includes ensemble forecasts (14 days) to predict water related stress around the globe. Assimilation of near-real time satellite data is part of the intended product that will be launched at EGU 2015. The challenges come from several directions. First, there are challenges that are mainly computer science oriented but have direct practical hydrological implications. For example, we aim to make use as much as possible of existing standards and open-source software. For example, different parts of our system are coupled through the Basic Model Interface (BMI) developed in the framework of the Community Surface Dynamics Modeling System (CSDMS). The PCR-GLOBWB model, built by Utrecht University, is the basic hydrological model that is the engine of the eWaterCycle project. Re-engineering of parts of the software was needed for it to run efficiently in a High Performance Computing (HPC) environment, and to be able to interface using BMI, and run on multiple compute nodes in parallel. The final aim is to have a spatial resolution of 1km x 1km, which is currently 10 x 10km. This high resolution is computationally not too demanding but very memory intensive. The memory bottleneck becomes especially apparent for data assimilation, for which we use OpenDA. OpenDa allows for different data assimilation techniques without the need to build these from scratch. We have developed a BMI adaptor for OpenDA, allowing OpenDA to use any BMI compatible model. To circumvent memory shortages which would result from standard applications of the Ensemble Kalman Filter, we have developed a variant that does not need to keep all ensemble members in working memory. At EGU, we will present this variant and how it fits well in HPC environments. An important step in the eWaterCycle project was the coupling between the hydrological and

  2. The One-Water Hydrologic Flow Model - The next generation in fully integrated hydrologic simulation software

    NASA Astrophysics Data System (ADS)

    Boyce, S. E.; Hanson, R. T.

    2015-12-01

    The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. MF-OWHM fully links the movement and use of groundwater, surface water, and imported water for consumption by agriculture and natural vegetation on the landscape, and for potable and other uses within a supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 combined with Local Grid Refinement, Streamflow Routing, Surface-water Routing Process, Seawater Intrusion, Riparian Evapotranspiration, and the Newton-Raphson solver. MF-OWHM also includes linkages for deformation-, flow-, and head-dependent flows; additional observation and parameter options for higher-order calibrations; and redesigned code for facilitation of self-updating models and faster simulation run times. The next version of MF-OWHM, currently under development, will include a new surface-water operations module that simulates dynamic reservoir operations, the conduit flow process for karst aquifers and leaky pipe networks, a new subsidence and aquifer compaction package, and additional features and enhancements to enable more integration and cross communication between traditional MODFLOW packages. By retaining and tracking the water within the hydrosphere, MF-OWHM accounts for "all of the water everywhere and all of the time." This philosophy provides more confidence in the water accounting by the scientific community and provides the public a foundation needed to address wider classes of problems such as evaluation of conjunctive-use alternatives and sustainability analysis, including potential adaptation and mitigation strategies, and best management practices. By Scott E. Boyce and Randall T. Hanson

  3. A New Wavelet Based Approach to Assess Hydrological Models

    NASA Astrophysics Data System (ADS)

    Adamowski, J. F.; Rathinasamy, M.; Khosa, R.; Nalley, D.

    2014-12-01

    In this study, a new wavelet based multi-scale performance measure (Multiscale Nash Sutcliffe Criteria, and Multiscale Normalized Root Mean Square Error) for hydrological model comparison was developed and tested. The new measure provides a quantitative measure of model performance across different timescales. Model and observed time series are decomposed using the a trous wavelet transform, and performance measures of the model are obtained at each time scale. The usefulness of the new measure was tested using real as well as synthetic case studies. The real case studies included simulation results from the Soil Water Assessment Tool (SWAT), as well as statistical models (the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods). Data from India and Canada were used. The synthetic case studies included different kinds of errors (e.g., timing error, as well as under and over prediction of high and low flows) in outputs from a hydrologic model. It was found that the proposed wavelet based performance measures (i.e., MNSC and MNRMSE) are a more reliable measure than traditional performance measures such as the Nash Sutcliffe Criteria, Root Mean Square Error, and Normalized Root Mean Square Error. It was shown that the new measure can be used to compare different hydrological models, as well as help in model calibration.

  4. Improving the transferability of hydrological model parameters under changing conditions

    NASA Astrophysics Data System (ADS)

    Huang, Yingchun; Bárdossy, András

    2014-05-01

    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.

  5. Flash flood modeling with the MARINE hydrological distributed model

    NASA Astrophysics Data System (ADS)

    Estupina-Borrell, V.; Dartus, D.; Ababou, R.

    2006-11-01

    Flash floods are characterized by their violence and the rapidity of their occurrence. Because these events are rare and unpredictable, but also fast and intense, their anticipation with sufficient lead time for warning and broadcasting is a primary subject of research. Because of the heterogeneities of the rain and of the behavior of the surface, spatially distributed hydrological models can lead to a better understanding of the processes and so on they can contribute to a better forecasting of flash flood. Our main goal here is to develop an operational and robust methodology for flash flood forecasting. This methodology should provide relevant data (information) about flood evolution on short time scales, and should be applicable even in locations where direct observations are sparse (e.g. absence of historical and modern rainfalls and streamflows in small mountainous watersheds). The flash flood forecast is obtained by the physically based, space-time distributed hydrological model "MARINE'' (Model of Anticipation of Runoff and INondations for Extreme events). This model is presented and tested in this paper for a real flash flood event. The model consists in two steps, or two components: the first component is a "basin'' flood module which generates flood runoff in the upstream part of the watershed, and the second component is the "stream network'' module, which propagates the flood in the main river and its subsidiaries. The basin flash flood generation model is a rainfall-runoff model that can integrate remotely sensed data. Surface hydraulics equations are solved with enough simplifying hypotheses to allow real time exploitation. The minimum data required by the model are: (i) the Digital Elevation Model, used to calculate slopes that generate runoff, it can be issued from satellite imagery (SPOT) or from French Geographical Institute (IGN); (ii) the rainfall data from meteorological radar, observed or anticipated by the French Meteorological Service (M

  6. Variational data assimilation with the YAO platform for hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Abbaris, A.; Dakhlaoui, H.; Thiria, S.; Bargaoui, Z.

    2014-09-01

    In this study data assimilation based on variational assimilation was implemented with the HBV hydrological model using the YAO platform of University Pierre and Marie Curie (France). The principle of the variational assimilation is to consider the model state variables as control variables and optimise them by minimizing a cost function measuring the disagreement between observations and model simulations. The variational assimilation is used for the hydrological forecasting. In this case four state variables of the rainfall-runoff model HBV (those related to soil water content in the water balance tank and to water contents in rooting tanks) are considered as control variables. They were updated through the 4D-VAR procedure using daily discharge incoming information. The Serein basin in France was studied and a high level of forecasting accuracy was obtained with variational assimilation allowing flood anticipation.

  7. EVALUATION OF HYDROLOGIC MODELS IN THE DESIGN OF STABLE LANDFILL COVERS

    EPA Science Inventory

    The study evaluates the utility of two hydrologic models in designing stable landfill cover systems. The models evaluated were HELP (Hydrologic Evaluation of Landfill Performance) and CREAMS (Chemicals, Runoff, and Erosion from Agricultural Management Systems). Studies of paramet...

  8. An improved ARIMA model for hydrological simulations

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

    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%.

  9. Vegetation Dynamics And Soil Moisture: Consequences For Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

    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.

  10. Hydrologic modeling in dynamic catchments: A data assimilation approach

    NASA Astrophysics Data System (ADS)

    Pathiraja, S.; Marshall, L.; Sharma, A.; Moradkhani, H.

    2016-05-01

    The transferability of conceptual hydrologic models in time is often limited by both their structural deficiencies and adopted parameterizations. Adopting a stationary set of model parameters ignores biases introduced by the data used to derive them, as well as any future changes to catchment conditions. Although time invariance of model parameters is one of the hallmarks of a high quality hydrologic model, very few (if any) models can achieve this due to their inherent limitations. It is therefore proposed to consider parameters as potentially time varying quantities, which can evolve according to signals in hydrologic observations. In this paper, we investigate the potential for Data Assimilation (DA) to detect known temporal patterns in model parameters from streamflow observations. It is shown that the success of the DA algorithm is strongly dependent on the method used to generate background (or prior) parameter ensembles (also referred to as the parameter evolution model). A range of traditional parameter evolution techniques are considered and found to be problematic when multiple parameters with complex time variations are estimated simultaneously. Two alternative methods are proposed, the first is a Multilayer approach that uses the EnKF to estimate hyperparameters of the temporal structure, based on apriori knowledge of the form of nonstationarity. The second is a Locally Linear approach that uses local linear estimation and requires no assumptions of the form of parameter nonstationarity. Both are shown to provide superior results in a range of synthetic case studies, when compared to traditional parameter evolution techniques.

  11. Flexible hydrological modeling - Disaggregation from lumped catchment scale to higher spatial resolutions

    NASA Astrophysics Data System (ADS)

    Tran, Quoc Quan; Willems, Patrick; Pannemans, Bart; Blanckaert, Joris; Pereira, Fernando; Nossent, Jiri; Cauwenberghs, Kris; Vansteenkiste, Thomas

    2015-04-01

    validation on spatial results was done for the groundwater head values at observation wells. To ensure that the lumped model can produce results as accurate as the spatially distributed models or close regardless to the number of parameters and implemented physical processes, it was checked whether the structure of the lumped models had to be adjusted. The concept has been implemented in a PCRaster - Python platform and tested for two Belgian case studies (catchments of the rivers Dijle and Grote Nete). So far, use is made of existing model structures (NAM, PDM, VHM and HBV). Acknowledgement: These results were obtained within the scope of research activities for the Flemish Environment Agency (VMM) - division Operational Water Management on "Next Generation hydrological modeling", in cooperation with IMDC consultants, and for Flanders Hydraulics Research (Waterbouwkundig Laboratorium) on "Effect of climate change on the hydrological regime of navigable watercourses in Belgium".

  12. A rangeland hydrology and erosion model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 is needed because existing erosion models were developed from cropland...

  13. 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...

  14. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-02-03

    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.

  15. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

    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.

  16. Impacts of Climate change on the watershed of the hydropower reservoir Gigerwaldsee using hydrological modeling

    NASA Astrophysics Data System (ADS)

    Etter, Simon; Seibert, Jan; Vis, Marc; Addor, Nans; Huss, Matthias; Finger, David

    2015-04-01

    Increasing temperatures and changing precipitation patterns will diminish snow cover and force glaciers to shrink in mountain environments. The runoff in Alpine catchments such as the watershed of the Gigerwaldsee, providing water resources for hydro power production in the Swiss Alps, will be affected by those changes. Using an updated version of the conceptual hydrological model HBV-light future hydro-climatic changes in the catchment where simulated. The hydrological model was driven by seven GCM-RCM combinations from the ENSEMBLES project under the emission scenario A1B. The climate projections were bias-corrected using quantile mapping. Besides a baseline scenario (1992-2021), a mid-term future scenario (2036-2065) and a long term scenario (2069-2098) were calculated. For calibration, the model was driven with a gridded dataset from MeteoSwiss and glacier extents from 1990. The calibration was performed using three datasets: i) discharge data, derived from a volume-lake level relationship of the Gigerwaldsee, ii) the fraction of the snow covered area in the catchment, retrieved from MODIS snowcover images and iii) extrapolated glacier mass balances. The parameters were determined using Pareto selection from 10'000 Monte Carlo simulation runs according to their performance over five objective functions. Two objective functions were used to evaluate the discharge simulation and two for snow cover, whereof one rated the simulation over the whole year and one only during summer. A fifth objective function was used for glacier mass balance simulations. An evaluation of different selections of parameter sets showed that relying on discharge, snowcover and glacier mass balance data led to a higher model consistency. The contribution of the climate scenarios, model parameters and glacier scenarios to the total uncertainty of the simulated future discharge was assessed using analysis of variance (ANOVA). The results indicate a decrease in runoff during the high flow

  17. Hydrological Modelling of The Guadiana Basin

    NASA Astrophysics Data System (ADS)

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

    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.

  18. Utilization of remote sensing observations in hydrologic models

    NASA Technical Reports Server (NTRS)

    Ragan, R. M.

    1977-01-01

    Most of the remote sensing related work in hydrologic modeling has centered on modifying existing models to take advantage of the capabilities of new sensor techniques. There has been enough success with this approach to insure that remote sensing is a powerful tool in modeling the watershed processes. Unfortunately, many of the models in use were designed without recognizing the growth of remote sensing technology. Thus, their parameters were selected to be map or field crew definable. It is believed that the real benefits will come through the evolution of new models having new parameters that are developed specifically to take advantage of our capabilities in remote sensing. The ability to define hydrologically active areas could have a significant impact. The ability to define soil moisture and the evolution of new techniques to estimate evoportransportation could significantly modify our approach to hydrologic modeling. Still, without a major educational effort to develop an understanding of the techniques used to extract parameter estimates from remote sensing data, the potential offered by this new technology will not be achieved.

  19. Anticipating the Role of SWOT in Hydrologic and Hydrodynamic Modeling

    NASA Astrophysics Data System (ADS)

    Pavelsky, T.; Biancamaria, S.; Andreadis, K.; Durand, M. T.; Schumann, G.

    2015-12-01

    The Surface Water and Ocean Topography (SWOT) satellite mission is a joint project of NASA and CNES, the French space agency. It aims to provide the first simultaneous, space-based measurements of inundation extent and water surface elevation in rivers, lakes, and wetlands around the world. Although the orbit repeat time is approximately 21 days, many areas of the earth will be viewed multiple times during this window. SWOT will observe rivers as narrow as 50-100 m and lakes as small as 0.01-0.06 km2, with height accuracies of ~10 cm for water bodies 1 km2 in area. Because SWOT will measure temporal variations in the height, width, and slope of rivers, several algorithms have been developed to estimate river discharge solely from SWOT measurements. Additionally, measurements of lake height and area will allow estimation of variability in lake water storage. These new hydrologic measurements will provide important sources of information both hydrologic and hydrodynamic models at regional to global scales. SWOT-derived estimates of water storage change and discharge will help to constrain simulation of the water budget in hydrologic models. Measurements of water surface elevation will provide similar constraints on hydrodynamic models of river flow. SWOT data will be useful for model calibration and validation, but perhaps the most exciting applications involve assimilation of SWOT data into models to enhance model robustness and provide denser temporal sampling than available from SWOT observations alone.

  20. Pursuing the method of multiple working hypotheses for hydrological modeling

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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

  1. Pursuing the method of multiple working hypotheses for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Kavetski, Dmitri; Fenicia, Fabrizio

    2011-09-01

    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 commentary 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 nonidentifiabilities. 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

  2. Flash flood warning based on fully dynamic hydrology modelling

    NASA Astrophysics Data System (ADS)

    Pejanovic, Goran; Petkovic, Slavko; Cvetkovic, Bojan; Nickovic, Slobodan

    2016-04-01

    Numerical hydrologic modeling has achieved limited success in the past due to, inter alia, lack of adequate input data. Over the last decade, data availability has improved substantially. For modelling purposes, high-resolution data on topography, river routing, and land cover and soil features have meanwhile become available, as well as the observations such as radar precipitation information. In our study, we have implemented the HYPROM model (Hydrology Prognostic Model) to predict a flash flood event at a smaller-scale basin in Southern Serbia. HYPROM is based on the full set of governing equations for surface hydrological dynamics, in which momentum components, along with the equation of mass continuity, are used as full prognostic equations. HYPROM also includes a river routing module serving as a collector for the extra surface water. Such approach permits appropriate representation of different hydrology scales ranging from flash floods to flows of large and slow river basins. The use of full governing equations, if not appropriately parameterized, may lead to numerical instability systems when the surface water in a model is vanishing. To resolve these modelling problems, an unconditionally stable numerical scheme and a method for height redistribution avoiding shortwave height noise have been developed in HYPROM, which achieve numerical convergence of u, v and h when surface water disappears. We have applied HYPROM, driven by radar-estimated precipitation, to predict flash flooding occurred over smaller and medium-size river basins. Two torrential rainfall cases have been simulated to check the accuracy of the model: the exceptional flooding of May 2014 in Western Serbia, and the convective flash flood of January 2015 in Southern Serbia. The second episode has been successfully predicted by HYPROM in terms of timing and intensity six hours before the event occurred. Such flash flood warning system is in preparation to be operationally implemented in the

  3. Hydrological Modelling and Parameter Identification for Green Roof

    NASA Astrophysics Data System (ADS)

    Lo, W.; Tung, C.

    2012-12-01

    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.

  4. On the Usefulness of Hydrologic Landscapes for Hydrologic Modeling and Water Management

    EPA Science Inventory

    Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

  5. On the Usefulness of Hydrologic Landscapes on Hydrologic Model calibration and Selection

    EPA Science Inventory

    Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

  6. Hydrological trend analysis in the Yellow River basin using a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Cong, Zhentao; Yang, Dawen; Gao, Bing; Yang, Hanbo; Hu, Heping

    2009-07-01

    The hydrological cycle has been highly influenced by climate change and human activities, and it is significant for analyzing the hydrological trends that occurred in past decades in order to understand past changes and to predict future trends. The water crisis of the Yellow River basin has drawn much attention from around the world, especially the drying up of the main river along the lower reaches during the 1990s. By incorporating historical meteorological data and available geographic information related to the conditions of the landscape, a distributed hydrological model has been employed to simulate the natural runoff without consideration of artificial water intake. On the basis of the data observed and the results simulated by the model, the hydrological trends have been analyzed quantitatively for evaluating the impact from climate change and human activity. It is found that the simulated natural runoff follows a similar trend as the precipitation in the entire area being studied during the last half century, and this implies that changes in the natural runoff are mainly controlled by the climate change rather than land use change. Changes in actual evapotranspiration upstream of the Lanzhou gauge are controlled by changes in both precipitation and potential evaporation, while changes of actual evapotranspiration downstream of the Lanzhou gauge are controlled mainly by the changes in precipitation. The difference between the annual observed runoff and the simulated runoff indicates that there is little artificial water consumption upstream of the Lanzhou gauge, but the artificial water consumption becomes larger downstream of the Lanzhou gauge. The artificial water consumption shows a significant increasing trend during the past 50 years and is the main cause of the drying up of the Yellow River. However, in contrast to the common perception that the serious drying up downstream of the Yellow River during the 1990s is caused by the rapid increase of

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

    NASA Astrophysics Data System (ADS)

    Huntington, J. L.; Niswonger, R. G.

    2010-12-01

    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 decoupled. For example, in the few studies that explicitly consider the effects of the unsaturated zone on recharge, the unsaturated zone is represented as a stagnant column of soil through which water flows independently of the underlying water table. Furthermore, previous studies have not considered the coupled interactions of the streamflow components, including snowmelt, runoff, subsurfrace stormflow, and groundwater flow. The interaction of these dynamic coupled processes need to be simulated so they can change with the climate, rather than assuming stagnant conditions based on the present climate. Consequently, to fully assess how climate change might affect water resources, integrated models are likely the best tools. Snow dominated watersheds of the Sierra Nevada are of great importance to water supplies in the western U.S. To analyze how climate change might affect these watersheds, we rely on a integrated surface and groundwater model for three snow dominated watersheds of the eastern Sierra Nevada that are tributary to Lake Tahoe and Truckee Meadows hydrographic areas of California and Nevada. Streamflow was simulated over a 20 year period, and results indicate that 4 month, 6 month, 2 year, and 11 year observed perodicities are well simulated. Model predicted 11 year periodicities are the result of simulating spatial and temporal variations in groundwater recharge, groundwater storage, and groundwater discharge to streams. To assess hydrologic change, we use as direct input, bias corrected and statistically down

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

    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.

  9. Modelling hydrological responses of Nerbioi River Basin to Climate Change

    NASA Astrophysics Data System (ADS)

    Mendizabal, Maddalen; Moncho, Roberto; Chust, Guillem; Torp, Peter

    2010-05-01

    Future climate change will affect aquatic systems on various pathways. Regarding the hydrological cycle, which is a very important pathway, changes in hydrometeorological variables (air temperature, precipitation, evapotranspiration) in first order impact discharges. The fourth report assessment of the Intergovernmental Panel for Climate Change indicates there is evidence that the recent warming of the climate system would result in more frequent extreme precipitation events, increased winter flood likelihoods, increased and widespread melting of snow and ice, longer and more widespread droughts, and rising sea level. Available research and climate model outputs indicate a range of hydrological impacts with likely to very likely probabilities (67 to 99%). For example, it is likely that up to 20% of the world population will live in areas where river flood potential could increase by the 2080s. In Spain, within the Atlantic basin, the hydrological variability will increase in the future due to the intensification of the positive phase of the North Atlantic Oscillation (NAO) index. This might cause flood frequency decreases, but its magnitude does not decrease. The generation of flood, its duration and magnitude are closely linked to changes in winter precipitation. The climatic conditions and relief of the Iberian Peninsula favour the generation of floods. In Spain, floods had historically strong socio-economic impacts, with more than 1525 victims in the past five decades. This upward trend of hydrological variability is expected to remain in the coming decades (medium uncertainty) when the intensification of the positive phase of the NAO index (MMA, 2006) is considered. In order to adapt or minimize climate change impacts in water resources, it is necessary to use climate projections as well as hydrological modelling tools. The main objective of this paper is to evaluate and assess the hydrological response to climate changes in flow conditions in Nerbioi river

  10. Modeling Soil Moisture Fields Using the Distributed Hydrologic Model MOBIDIC

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    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

  11. Chapman Conference on Spatial Variability in Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Woolhiser, D. A.; Morel-Seytoux, H. J.

    The AGU Chapman Conference on Spatial Variability in Hydrologic Modeling was held July 21-23, 1981, at the Colorado State University Pingree Park Campus, located in the mountains some 88.5 km (55 miles) west of Fort Collins, Colorado. The conference was attended by experimentalists and theoreticians from a wide range of disciplines, including geology, hydrology, civil engineering, watershed science, chemical engineering, geography, statistics, mathematics, meteorology, and soil science. The attendees included researchers at various levels of research experience, including a large contingent of graduate students and many senior scientists.The conference goal was to review progress and discuss research approaches to the spatial variability of catchment surface and subsurface properties in a distributed modeling context. Mathematical models of water movement dynamics within a catchment consist of linked partial differential equations that describe free surface flow and unsaturated and saturated flow in porous media. Such models are utilized extensively in attempts to understand and predict the environmental consequences of human activities such as agricultural land management, waste disposal, urbanization, etc. We are concerned with the spatial structure of the parameters in such models, the precipitation input, and the geometric complexity of the system boundaries. The emphasis of this conference was on surface and subsurface hydrological process and their interactions.

  12. Modeling of subglacial hydrological development following rapid supraglacial lake drainage

    PubMed Central

    Dow, C F; Kulessa, B; Rutt, I C; Tsai, V C; Pimentel, S; Doyle, S H; van As, D; Lindbäck, K; Pettersson, R; Jones, G A; Hubbard, A

    2015-01-01

    The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections. Key Points Model for subglacial hydrological analysis of rapid lake drainage events Limited subglacial channel growth during and following rapid lake drainage Persistence of distributed drainage in inland areas where channel growth is limited PMID:26640746

  13. eWaterCycle: A high resolution global hydrological model

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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

  14. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

    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.

  15. A Geospatial Fabric (GF) for National Hydrological Modeling

    NASA Astrophysics Data System (ADS)

    Viger, R.; Bock, A.

    2014-12-01

    The US Geological Survey (USGS) Geospatial Fabric (GF) supports the USGS National Hydrologic Model (NHM) by defining a minimally sufficient, nationally consistent set of geographic information needed to simulate streamflow at almost 60,000 points of interest (POIs). POIs primarily are defined based on: (a) a high quality set of USGS stream gages (Gages-II), (b) National Weather Service forecast nodes, (c) the USGS National Water Quality Assessment's modeling network, (d) at inlets and outlets of selected water bodies, and (e) at confluences. Each POI is associated with a stream segment which typically has two adjacent land surface areas, referred to as hydrologic response units (HRUs). Parameter tables, largely based on the National Land Cover Databases, the Soil Survey Geographic Database (SSURGO), and the geometry of the spatial data, have been derived for these features. Configurations of GF features and attribute tables are defined and made available through the USGS ScienceBase (https://www.sciencebase.gov/catalog/item/537b7327e4b0929ba496f66f). Data are organized into 20 ESRI file geodatabases, each covering a different region of the United States (https://www.sciencebase.gov/catalog/item/535edb4ae4b08e65d60fc837). Future releases will include additional realizations of NHM parameter tables. These will serve to assess the impact of alternate data sources and processing methodologies on simulated streamflows. Tools for dynamically subsetting geodatabases and model inputs based on custom watersheds are currently being prototyped. The GF is a versatile framework for data integration because it maintains feature-level indexing back to NHDPlus and the National Hydrography Dataset, which is used in many water resource studies. In addition, the GF will help to ensure a minimum initial quality of parameter information, reduce the time of developing hydrological modeling applications in the United States, and generally improve the accuracy and scientific impact of

  16. Subgrid spatial variability of soil hydraulic functions for hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kreye, Phillip; Meon, Günter

    2016-07-01

    State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.

  17. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    NASA Astrophysics Data System (ADS)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  18. Computationally efficient calibration of WATCLASS Hydrologic models using surrogate optimization

    NASA Astrophysics Data System (ADS)

    Kamali, M.; Ponnambalam, K.; Soulis, E. D.

    2007-07-01

    In this approach, exploration of the cost function space was performed with an inexpensive surrogate function, not the expensive original function. The Design and Analysis of Computer Experiments(DACE) surrogate function, which is one type of approximate models, which takes correlation function for error was employed. The results for Monte Carlo Sampling, Latin Hypercube Sampling and Design and Analysis of Computer Experiments(DACE) approximate model have been compared. The results show that DACE model has a good potential for predicting the trend of simulation results. The case study of this document was WATCLASS hydrologic model calibration on Smokey-River watershed.

  19. Hydrologic modeling of soil water storage in landfill cover systems

    SciTech Connect

    Barnes, F.J.; Rodgers, J.C.

    1987-01-01

    The accuracy of modeling soil water storage by two hydrologic models, CREAMS and HELP, was tested by comparing simulation results with field measurements of soil moisture in eight experimental landfill cover systems having a range of well-defined soil profiles and vegetative covers. Regression analysis showed that CREAMS generally represented soil moisture more accurately than HELP simulations. Soil profiles that more closely resembled natural agricultural soils were more accurately modeled than highly artificial layered soil profiles. Precautions for determining parameter values for model input and for interpreting simulation results are discussed.

  20. Defining prior probabilities for hydrologic model structures in UK catchments

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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

  1. Coupled Dynamic Modeling to Assess Human Impact on Watershed Hydrology

    NASA Astrophysics Data System (ADS)

    Mohammed, I. N.; Tsai, Y.; Turnbull, S.; Bomblies, A.; Zia, A.

    2014-12-01

    Humans are intrinsic to the hydrologic system, both as agents of change and as beneficiaries of ecosystem services. This connection has been underappreciated in hydrology. We present a modeling linkage framework of an agent-based land use change model with a physical-based watershed model. The coupled model framework presented constitutes part of an integrated assessment model that is being developed to study human-ecosystem interaction in Missisquoi Bay, spanning Vermont and Québec, which is experiencing high concentrations of nutrients from the Missisquoi River watershed. The integrated assessment approach proposed is comprised of linking two simulation models: the Interactive Land-Use Transition Agent-Based Model (ILUTABM) and a physically based process model, the Regional Hydro-Ecological Simulation System (RHESSys). The ILUTABM treats both landscape and landowners as agents and simulates annual land-use patterns resulting from landowners annual land-use decisions and Best Management Practices (BMPs) adaptations to landowners utilities, land productivity and perceived impacts of floods. The Missisquoi River at Swanton watershed RHESSys model (drainage area of 2,200 km2) driven by climate data was first calibrated to daily streamflows and water quality sensor data at the watershed outlet. Simulated land-use patterns were then processed to drive the calibrated RHESSys model to obtain streamflow nutrient loading realizations. Nutrients loading realizations are then examined and routed back to the ILUTAB model to obtain public polices needed to manage the Missisquoi watershed as well as the Lake Champlain in general. We infer that the applicability of this approach can be generalized to other similar watersheds. Index Terms: 0402: Agricultural systems; 1800: Hydrology; 1803: Anthropogenic effects; 1834 Human impacts; 6344: System operation and management; 6334: Regional Planning

  2. Hydrologic modeling of reclaimed strip mine spoil

    SciTech Connect

    Edwards, K.B.; Stoertz, M.W.; Turney, D.C.

    1998-12-31

    A numerical groundwater flow model (MODFLOW) of a surface coal mine in southeast Ohio was calibrated under steady state conditions to match measured heads by varying hydraulic conductivity (K) and recharge (R). Sensitivity studies indicated that K was not largely dependent on the poorly quantified underclay elevation or on the lake boundary condition. The baseflow recharge was determined to be between 8 and 60 mm/yr (1 to 6% of annual rainfall) and K between 0.004 and 0.01 cm/s for the spoil aquifer.

  3. A Coupled Surface/Subsurface Model for Hydrological Drought Investigations

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    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

  4. Physically Based Mountain Hydrological Modelling using Reanalysis Data in Patagonia

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

    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

  5. Precipitation forecasts and their uncertainty as input into hydrological models

    NASA Astrophysics Data System (ADS)

    Kobold, M.; Sušelj, K.

    2005-10-01

    Torrential streams and fast runoff are characteristic of most Slovenian rivers and extensive damage is caused almost every year by rainstorms affecting different regions of Slovenia. Rainfall-runoff models which are tools for runoff calculation can be used for flood forecasting. In Slovenia, the lag time between rainfall and runoff is only a few hours and on-line data are used only for now-casting. Predicted precipitation is necessary in flood forecasting some days ahead. The ECMWF (European Centre for Medium-Range Weather Forecasts) model gives general forecasts several days ahead while more detailed precipitation data with the ALADIN/SI model are available for two days ahead. Combining the weather forecasts with the information on catchment conditions and a hydrological forecasting model can give advance warning of potential flooding notwithstanding a certain degree of uncertainty in using precipitation forecasts based on meteorological models. Analysis of the sensitivity of the hydrological model to the rainfall error has shown that the deviation in runoff is much larger than the rainfall deviation. Therefore, verification of predicted precipitation for large precipitation events was performed with the ECMWF model. Measured precipitation data were interpolated on a regular grid and compared with the results from the ECMWF model. The deviation in predicted precipitation from interpolated measurements is shown with the model bias resulting from the inability of the model to predict the precipitation correctly and a bias for horizontal resolution of the model and natural variability of precipitation.

  6. What is the minimal geomorphology based hydrological model?

    NASA Astrophysics Data System (ADS)

    de Lavenne, Alban; Rigon, Riccardo; Formetta, Giuseppe; Cudennec, Christophe

    2013-04-01

    Hydrological modelling is a usefull tool to understand hydrological process. With knowledge increasing, models often become more complex. Drived by each researchers hypothesis, new components are added years after years. However, in many cases, the need of this complexity appears to be unnecessary or, in a context of lack of data, even unsuitable. We propose a modelling framework improvement of geomorphology-based models. By updating step by step models' structure and by checking separatly hypotheses for improving model performance, we aim to improve our understanding of catchment behaviour. We apply this framework on six catchments in Brittany, France. With catchment's area varying from 5km² to 316km², we explore heterogeneous situations to enrich the discussion about model's efficiency, robustness and facility of implementation. Simulations are performed from monthly time scale to annual time scale using 5 years of rainfall-runoff data. We compare the improvement bring by changing progressively model's structure. This is done by splitting catchment dynamics through the play of several flow velocities inside one or several width functions. We test separatly different hypothesis of model improvement, like accounting of velocity and rainfall spatio-temporal variability, as well as considering hydrodynamic dispersion. Models are parametrized using a particle swarm optimisation algorithm. With a minimum complexity level, this framework enable to choose wich model suits the objectives and how to take advantage of the available data.

  7. Advancing reservoir operation description in physically based hydrological models

    NASA Astrophysics Data System (ADS)

    Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

    2016-04-01

    Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir

  8. A priori discretization quality metrics for distributed hydrologic modeling applications

    NASA Astrophysics Data System (ADS)

    Liu, Hongli; Tolson, Bryan; Craig, James; Shafii, Mahyar; Basu, Nandita

    2016-04-01

    In distributed hydrologic modelling, a watershed is treated as a set of small homogeneous units that address the spatial heterogeneity of the watershed being simulated. The ability of models to reproduce observed spatial patterns firstly depends on the spatial discretization, which is the process of defining homogeneous units in the form of grid cells, subwatersheds, or hydrologic response units etc. It is common for hydrologic modelling studies to simply adopt a nominal or default discretization strategy without formally assessing alternative discretization levels. This approach lacks formal justifications and is thus problematic. More formalized discretization strategies are either a priori or a posteriori with respect to building and running a hydrologic simulation model. A posteriori approaches tend to be ad-hoc and compare model calibration and/or validation performance under various watershed discretizations. The construction and calibration of multiple versions of a distributed model can become a seriously limiting computational burden. Current a priori approaches are more formalized and compare overall heterogeneity statistics of dominant variables between candidate discretization schemes and input data or reference zones. While a priori approaches are efficient and do not require running a hydrologic model, they do not fully investigate the internal spatial pattern changes of variables of interest. Furthermore, the existing a priori approaches focus on landscape and soil data and do not assess impacts of discretization on stream channel definition even though its significance has been noted by numerous studies. The primary goals of this study are to (1) introduce new a priori discretization quality metrics considering the spatial pattern changes of model input data; (2) introduce a two-step discretization decision-making approach to compress extreme errors and meet user-specified discretization expectations through non-uniform discretization threshold

  9. Development of a landscape unit delineation framework for ecoy-hydrologic models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A spatially distributed representation of basin hydrology and transport processes in eco-hydrological models facilitates the identification of critical source areas and the placement of management and conservation measures. Especially floodplains are critical landscape features that differ from nei...

  10. 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 ...

  11. A strategy for using climate data for hydrological modelling

    NASA Astrophysics Data System (ADS)

    Rust, Henning W.; Ulbrich, Uwe; Vagenas, Christos; Meredith, Edmund; Agbeko Kpogo-Nuwoklo, Komlan

    2016-04-01

    Hydrological modeling is the basis for water related impact assessment and the development of management strategies. These models are driven with meteorological data such as precipitation, temperature, wind and humidity. Depending on the nature of the problem, hydrological modelers require meteorological data with a very high spatial and temporal resolution, e.g. to a few kilometers and hours. As dynamical downscaling to such a high resolution is computationally very costly, a continuous downscaling of global climate projections is not feasible for a longer time period. For BINGO, a double-tracked strategy will be implemented to cope with this problem: 1) high resolution dynamical downscaling is limited to episodes favoring hydrological extremes and 2) conditional weather generators are used to simulated large ensembles of spatio-temporal driving fields consistent with the current or projected climate. The first track requires identification of the relevant episodes from global simulations. This is realized by clustering atmospheric variables to obtain a set of circulation patterns. Episodes containing sequences of circulation patterns associated with hydrological extremes are then further downscaled and bias corrected. The second track relies on setting up a weather generator allowing to simulate all relevant variables consistent with the recent climate. We seek to establish a link between this generator and large scale atmospheric drivers to allow simulations consistent with climate projections. While dynamical downscaling is strong in simulating meteorological driving data associated with particular events, conditional weather generators simulate a broader range of events consistent with the large scale situation. The two tracks thus complement each other.

  12. Coupled geophysical-hydrological modeling of controlled NAPL spill

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

    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

  13. Assessing climate change impact by integrated hydrological modelling

    NASA Astrophysics Data System (ADS)

    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

    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

  14. Distributed hydrological models: comparison between TOPKAPI, a physically based model and TETIS, a conceptually based model

    NASA Astrophysics Data System (ADS)

    Ortiz, E.; Guna, V.

    2009-04-01

    The present work aims to carry out a comparison between two distributed hydrological models, the TOPKAPI (Ciarapica and Todini, 1998; Todini and Ciarapica, 2001) and TETIS (Vélez, J. J.; Vélez J. I. and Francés, F, 2002) models, obtaining the hydrological solution computed on the basis of the same storm events. The first model is physically based and the second one is conceptually based. The analysis was performed on the 21,4 km2 Goodwin Creek watershed, located in Panola County, Mississippi. This watershed extensively monitored by the Agricultural Research Service (ARS) National Sediment Laboratory (NSL) has been chosen because it offers a complete database compiling precipitation (16 rain gauges), runoff (6 discharge stations) and GIS data. Three storm events were chosen to evaluate the performance of the two models: the first one was chosen to calibrate the models, and the other two to validate them. Both models performed a satisfactory hydrological response both in calibration and validation events. While for the TOPKAPI model it wasn't a real calibration, due to its really good performance with parameters modal values derived of watershed characteristics, for the TETIS model it has been necessary to perform a previous automatic calibration. This calibration was carried out using the data provided by the observed hydrograph, in order to adjust the modeĺs 9 correction factors. Keywords: TETIS, TOPKAPI, distributed models, hydrological response, ungauged basins.

  15. Intercomparison of hydrologic processes in global climate models

    NASA Technical Reports Server (NTRS)

    Lau, W. K.-M.; Sud, Y. C.; Kim, J.-H.

    1995-01-01

    In this report, we address the intercomparison of precipitation (P), evaporation (E), and surface hydrologic forcing (P-E) for 23 Atmospheric Model Intercomparison Project (AMIP) general circulation models (GCM's) including relevant observations, over a variety of spatial and temporal scales. The intercomparison includes global and hemispheric means, latitudinal profiles, selected area means for the tropics and extratropics, ocean and land, respectively. In addition, we have computed anomaly pattern correlations among models and observations for different seasons, harmonic analysis for annual and semiannual cycles, and rain-rate frequency distribution. We also compare the joint influence of temperature and precipitation on local climate using the Koeppen climate classification scheme.

  16. Validating a spatially distributed hydrological model with soil morphology data

    NASA Astrophysics Data System (ADS)

    Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

    2013-10-01

    Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater

  17. Integrated hydrological SVAT model for climate change studies in Denmark

    NASA Astrophysics Data System (ADS)

    Mollerup, M.; Refsgaard, J.; Sonnenborg, T. O.

    2010-12-01

    In a major Danish funded research project (www.hyacints.dk) a coupling is being established between the HIRHAM regional climate model code from Danish Meteorological Institute and the MIKE SHE distributed hydrological model code from DHI. The linkage between those two codes is a soil vegetation atmosphere transfer scheme, which is a module of MIKE SHE. The coupled model will be established for the entire country of Denmark (43,000 km2 land area) where a MIKE SHE based hydrological model already exists (Henriksen et al., 2003, 2008). The present paper presents the MIKE SHE SVAT module and the methodology used for parameterising and calibrating the MIKE SHE SVAT module for use throughout the country. As SVAT models previously typically have been tested for research field sites with comprehensive data on energy fluxes, soil and vegetation data, the major challenge lies in parameterisation of the model when only ordinary data exist. For this purpose annual variations of vegetation characteristics (Leaf Area Index (LAI), Crop height, Root depth and the surface albedo) for different combinations of soil profiles and vegetation types have been simulated by use of the soil plant atmosphere model Daisy (Hansen et al., 1990; Abrahamsen and Hansen, 2000) has been applied. The MIKE SHE SVAT using Daisy generated surface/soil properties model has been calibrated against existing data on groundwater heads and river discharges. Simulation results in form of evapotranspiration and percolation are compared to the existing MIKE SHE model and to observations. To analyse the use of the SVAT model in climate change impact assessments data from the ENSEMBLES project (http://ensembles-eu.metoffice.com/) have been analysed to assess the impacts on reference evapotranspiration (calculated by the Makkink and the Penmann-Monteith equations) as well as on the individual elements in the Penmann-Monteith equation (radiation, wind speed, humidity and temperature). The differences on the

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

    NASA Astrophysics Data System (ADS)

    Tangdamrongsub, N.; Steele-Dunne, S. C.; Gunter, B. C.; Ditmar, P. G.; Weerts, A. H.

    2015-04-01

    The ability to estimate terrestrial water storage (TWS) realistically is essential for understanding past hydrological events and predicting future changes in the hydrological cycle. Inadequacies in model physics, uncertainty in model land parameters, and uncertainties in meteorological data commonly limit the accuracy of hydrological models in simulating TWS. In an effort to improve model performance, this study investigated the benefits of assimilating TWS estimates derived from the Gravity Recovery and Climate Experiment (GRACE) data into the OpenStreams wflow_hbv model using an ensemble Kalman filter (EnKF) approach. The study area chosen was the Rhine River basin, which has both well-calibrated model parameters and high-quality forcing data that were used for experimentation and comparison. Four different case studies were examined which were designed to evaluate different levels of forcing data quality and resolution including those typical of other less well-monitored river basins. The results were validated using in situ groundwater (GW) and stream gauge data. The analysis showed a noticeable improvement in GW estimates when GRACE data were assimilated, with a best-case improvement of correlation coefficient from 0.31 to 0.53 and root mean square error (RMSE) from 8.4 to 5.4 cm compared to the reference (ensemble open-loop) case. For the data-sparse case, the best-case GW estimates increased the correlation coefficient from 0.46 to 0.61 and decreased the RMSE by 35%. For the average improvement of GW estimates (for all four cases), the correlation coefficient increases from 0.6 to 0.7 and the RMSE was reduced by 15%. Only a slight overall improvement was observed in streamflow estimates when GRACE data were assimilated. Further analysis suggested that this is likely due to sporadic short-term, but sizeable, errors in the forcing data and the lack of sufficient constraints on the soil moisture component. Overall, the results highlight the benefit of

  19. Parallelization of a hydrological model using the message passing interface

    USGS Publications Warehouse

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

    2013-01-01

    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.

  20. Hydrological modeling of an ungauged watershed in Southern Andes

    NASA Astrophysics Data System (ADS)

    Alarcon, Vladimir J.; Alcayaga, Hernán; Álvarez, Enrique

    2015-12-01

    In this research, MODIS MCD12Q1 land cover, and SRTM topographical datasets were used for developing hydrological models for two ungauged watersheds: Clarillo river watershed, and Los Almendros watershed. Both watersheds are located in central Chile. Coarse precipitation and stream flow data for Los Almendros catchment were used for calibration of stream flow for Los Almendros River. Acceptable fit (with R2 values ranging within 0.62 to 0.67) was achieved during calibration. The hydrological parameters were then extrapolated for Clarillo river watershed. Simulated annual mean flows for Clarillo River were then compared to annual flows reported in the literature. Simulated mean annual flows were shown to be within the range of historical means with most of the simulated flows falling between the first and third quartile of the measured means.

  1. Hierarchical Modeling of Fen Hydrology across Multiple Scales

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    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.

  2. Misrepresentation and amendment of soil moisture in conceptual hydrological modelling

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

    Although many conceptual models are very effective in simulating river runoff, their soil moisture schemes are generally not realistic in comparison with the reality (i.e., getting the right answers for the wrong reasons). This study reveals two significant misrepresentations in those models through a case study using the Xinanjiang model which is representative of many well-known conceptual hydrological models. The first is the setting of the upper limit of its soil moisture at the field capacity, due to the 'holding excess runoff' concept (i.e., runoff begins on repletion of its storage to the field capacity). The second is neglect of capillary rise of water movement. A new scheme is therefore proposed to overcome those two issues. The amended model is as effective as its original form in flow modelling, but represents more logically realistic soil water processes. The purpose of the study is to enable the hydrological model to get the right answers for the right reasons. Therefore, the new model structure has a better capability in potentially assimilating soil moisture observations to enhance its real-time flood forecasting accuracy. The new scheme is evaluated in the Pontiac catchment of the USA through a comparison with satellite observed soil moisture. The correlation between the XAJ and the observed soil moisture is enhanced significantly from 0.64 to 0.70. In addition, a new soil moisture term called SMDS (Soil Moisture Deficit to Saturation) is proposed to complement the conventional SMD (Soil Moisture Deficit).

  3. Evaluation of a hydrological model based on Bidirectional Reach (BReach)

    NASA Astrophysics Data System (ADS)

    Van Eerdenbrugh, Katrien; Van Hoey, Stijn; Verhoest, Niko E. C.

    2016-04-01

    Evaluation and discrimination of model structures is crucial to ensure an appropriate use of hydrological models. When evaluating model results by aggregating their quality in (a subset of) individual observations, overall results of this analysis sometimes conceal important detailed information about model structural deficiencies. Analyzing model results within their local (time) context can uncover this detailed information. In this research, a methodology called Bidirectional Reach (BReach) is proposed to evaluate and analyze results of a hydrological model by assessing the maximum left and right reach in each observation point that is used for model evaluation. These maximum reaches express the capability of the model to describe a subset of the evaluation data both in the direction of the previous (left) and of the following data (right). This capability is evaluated on two levels. First, on the level of individual observations, the combination of a parameter set and an observation is classified as non-acceptable if the deviation between the accompanying model result and the measurement exceeds observational uncertainty. Second, the behavior in a sequence of observations is evaluated by means of a tolerance degree. This tolerance degree expresses the condition for satisfactory model behavior in a data series and is defined by the percentage of observations within this series that can have non-acceptable model results. Based on both criteria, the maximum left and right reaches of a model in an observation represent the data points in the direction of the previous respectively the following observations beyond which none of the sampled parameter sets both are satisfactory and result in an acceptable deviation. After assessing these reaches for a variety of tolerance degrees, results can be plotted in a combined BReach plot that show temporal changes in the behavior of model results. The methodology is applied on a Probability Distributed Model (PDM) of the river

  4. Simultaneous calibration of hydrological models in geographical space

    NASA Astrophysics Data System (ADS)

    Bárdossy, András; Huang, Yingchun; Wagener, Thorsten

    2016-07-01

    Hydrological models are usually calibrated for selected catchments individually using specific performance criteria. This procedure assumes that the catchments show individual behavior. As a consequence, the transfer of model parameters to other ungauged catchments is problematic. In this paper, the possibility of transferring part of the model parameters was investigated. Three different conceptual hydrological models were considered. The models were restructured by introducing a new parameter η which exclusively controls water balances. This parameter was considered as individual to each catchment. All other parameters, which mainly control the dynamics of the discharge (dynamical parameters), were considered for spatial transfer. Three hydrological models combined with three different performance measures were used in three different numerical experiments to investigate this transferability. The first numerical experiment, involving individual calibration of the models for 15 selected MOPEX catchments, showed that it is difficult to identify which catchments share common dynamical parameters. Parameters of one catchment might be good for another catchment but not the opposite. In the second numerical experiment, a common spatial calibration strategy was used. It was explicitly assumed that the catchments share common dynamical parameters. This strategy leads to parameters which perform well on all catchments. A leave-one-out common calibration showed that in this case a good parameter transfer to ungauged catchments can be achieved. In the third numerical experiment, the common calibration methodology was applied for 96 catchments. Another set of 96 catchments was used to test the transfer of common dynamical parameters. The results show that even a large number of catchments share similar dynamical parameters. The performance is worse than those obtained by individual calibration, but the transfer to ungauged catchments remains possible. The performance of the

  5. HBV Genotypic Variability in Cuba

    PubMed Central

    Loureiro, Carmen L.; Aguilar, Julio C.; Aguiar, Jorge; Muzio, Verena; Pentón, Eduardo; Garcia, Daymir; Guillen, Gerardo; Pujol, Flor H.

    2015-01-01

    The genetic diversity of HBV in human population is often a reflection of its genetic admixture. The aim of this study was to explore the genotypic diversity of HBV in Cuba. The S genomic region of Cuban HBV isolates was sequenced and for selected isolates the complete genome or precore-core sequence was analyzed. The most frequent genotype was A (167/250, 67%), mainly A2 (149, 60%) but also A1 and one A4. A total of 77 isolates were classified as genotype D (31%), with co-circulation of several subgenotypes (56 D4, 2 D1, 5 D2, 7 D3/6 and 7 D7). Three isolates belonged to genotype E, two to H and one to B3. Complete genome sequence analysis of selected isolates confirmed the phylogenetic analysis performed with the S region. Mutations or polymorphisms in precore region were more common among genotype D compared to genotype A isolates. The HBV genotypic distribution in this Caribbean island correlates with the Y lineage genetic background of the population, where a European and African origin prevails. HBV genotypes E, B3 and H isolates might represent more recent introductions. PMID:25742179

  6. Geomorphological Approach to Glacial and Snow Modeling applied to Hydrology

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    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

  7. Quantifying and Generalizing Hydrologic Responses to Dam Regulation using a Statistical Modeling Approach

    SciTech Connect

    McManamay, Ryan A

    2014-01-01

    Despite the ubiquitous existence of dams within riverscapes, much of our knowledge about dams and their environmental effects remains context-specific. Hydrology, more than any other environmental variable, has been studied in great detail with regard to dam regulation. While much progress has been made in generalizing the hydrologic effects of regulation by large dams, many aspects of hydrology show site-specific fidelity to dam operations, small dams (including diversions), and regional hydrologic regimes. A statistical modeling framework is presented to quantify and generalize hydrologic responses to varying degrees of dam regulation. Specifically, the objectives were to 1) compare the effects of local versus cumulative dam regulation, 2) determine the importance of different regional hydrologic regimes in influencing hydrologic responses to dams, and 3) evaluate how different regulation contexts lead to error in predicting hydrologic responses to dams. Overall, model performance was poor in quantifying the magnitude of hydrologic responses, but performance was sufficient in classifying hydrologic responses as negative or positive. Responses of some hydrologic indices to dam regulation were highly dependent upon hydrologic class membership and the purpose of the dam. The opposing coefficients between local and cumulative-dam predictors suggested that hydrologic responses to cumulative dam regulation are complex, and predicting the hydrology downstream of individual dams, as opposed to multiple dams, may be more easy accomplished using statistical approaches. Results also suggested that particular contexts, including multipurpose dams, high cumulative regulation by multiple dams, diversions, close proximity to dams, and certain hydrologic classes are all sources of increased error when predicting hydrologic responses to dams. Statistical models, such as the ones presented herein, show promise in their ability to model the effects of dam regulation effects at

  8. The intracellular dynamics of hepatitis B virus (HBV) replication with reproduced virion "re-cycling".

    PubMed

    Nakabayashi, Jun

    2016-05-01

    Hepatitis B virus (HBV) is a causative agent of hepatitis. Clinical outcome of hepatitis type B depends on the viral titer observed in the peripheral blood of the patient. In the chronic hepatitis patient, production of HBV virion remains low level. On the other hand, the viral load prominently increases in fulminant hepatitis patient as compared with that in the chronic hepatitis patient. We previously proposed a mathematical model describing the intracellular dynamics of HBV replication. Our model clarified that there are two distinguishable replication patterns of HBV named "arrested" and "explosive" replication. In the arrested replication, the amount of virion newly reproduced from an infected cell remains low level, while the amount of virion extremely increases in the explosive replication. Viral load is drastically changed by slight alteration of expression ratio of 3.5kb RNA to 2.4kb mRNA of HBV. Though our model provided the switching mechanism determining the replication pattern of HBV, HBV dynamics is determined by not only the expression pattern of viral genes. In this study, "recycling" of HBV virion in the replication cycle is investigated as a new factor affecting the intracellular dynamics of HBV replication. A part of newly produced virion of HBV is reused as a core particle that is a resource of HBV replication. This recycling of HBV virion lowers the threshold for the explosive replication when waiting time for the next cycle of the replication is large. It is seemingly contradicting that prominent production of HBV is caused by large recycling rate and small release rate of HBV virion from infected cell to extracellular space. But the recycling of HBV virion can contribute to the positive feedback cycle of HBV replication for the explosive replication to accumulate the core particle as a resource of HBV replication in an infected cell. Accumulation of core particle in the infected cell can be risk factor for the exacerbation of hepatitis rather

  9. A Hydrologic and Geomorphic Model of Estuary Breaching and Closure

    NASA Astrophysics Data System (ADS)

    Rich, A.; Keller, E. A.

    2012-12-01

    Many coastal estuaries are separated seasonally from the ocean by a swash-deposited beach berm. The opening of the inlet may occur by fluvial erosion of the beach berm and closure occurs when sand deposition outpaces erosion of the inlet. To better understand how the hydrology of estuaries affects breaching and closing patterns, a model is developed that incorporates an estuary hydrologic budget with a geormorphic model of the inlet system. When calibrated, the model is able to reproduce the initial seasonal breaching, seasonal closure, intermittent closures and breaches, and the low-streamflow estuary hydrology of the Carmel Lagoon, located in Central California. For two years when the estuary inlet drains directly across the beach-berm in accordance with model assumptions, the calibrated model predicts the observed 48-hour estuary stage amplitude with correlation coefficients of 0.77 and 0.65. For the calibrated model, streamflow is the predominant control on whether the estuary inlet is open or closed. In a series of sensitivity analyses, it is seen that the function of bar-built, coastal estuaries are sensitive to morphologic and hydrologic variations of the beach berm, and changes to the estuary storage itself. By varying individual components of the berm-system and estuary storage, the amount of the time the estuary is open changes -43 - 28% for the 18.2 model period. The morphology of the berm affects barrier groundwater flow, inlet hydraulics, and estuary storage. Importantly, 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. A high berm renders streamflow the predominant control on function and decreases the amount of time that the estuary is open by 4%, whereas a lower berm allows wave-overtopping to contribute to function and increases time open by 24%. By excavating an estuary, it will breach less frequently (-32% change in open) and store water up to 3

  10. Parameter estimation of hydrologic models using data assimilation

    NASA Astrophysics Data System (ADS)

    Kaheil, Y. H.

    2005-12-01

    The uncertainties associated with the modeling of hydrologic systems sometimes demand that data should be incorporated in an on-line fashion in order to understand the behavior of the system. This paper represents a Bayesian strategy to estimate parameters for hydrologic models in an iterative mode. The paper presents a modified technique called localized Bayesian recursive estimation (LoBaRE) that efficiently identifies the optimum parameter region, avoiding convergence to a single best parameter set. The LoBaRE methodology is tested for parameter estimation for two different types of models: a support vector machine (SVM) model for predicting soil moisture, and the Sacramento Soil Moisture Accounting (SAC-SMA) model for estimating streamflow. The SAC-SMA model has 13 parameters that must be determined. The SVM model has three parameters. Bayesian inference is used to estimate the best parameter set in an iterative fashion. This is done by narrowing the sampling space by imposing uncertainty bounds on the posterior best parameter set and/or updating the "parent" bounds based on their fitness. The new approach results in fast convergence towards the optimal parameter set using minimum training/calibration data and evaluation of fewer parameter sets. The efficacy of the localized methodology is also compared with the previously used Bayesian recursive estimation (BaRE) algorithm.

  11. Real-data Calibration Experiments On A Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Brath, A.; Montanari, A.; Toth, E.

    The increasing availability of extended information on the study watersheds does not generally overcome the need for the determination through calibration of at least a part of the parameters of distributed hydrologic models. The complexity of such models, making the computations highly intensive, has often prevented an extensive analysis of calibration issues. The purpose of this study is an evaluation of the validation results of a series of automatic calibration experiments (using the shuffled complex evolu- tion method, Duan et al., 1992) performed with a highly conceptualised, continuously simulating, distributed hydrologic model applied on the real data of a mid-sized Ital- ian watershed. Major flood events occurred in the 1990-2000 decade are simulated with the parameters obtained by the calibration of the model against discharge data observed at the closure section of the watershed and the hydrological features (overall agreement, volumes, peaks and times to peak) of the discharges obtained both in the closure and in an interior stream-gauge are analysed for validation purposes. A first set of calibrations investigates the effect of the variability of the calibration periods, using the data from several single flood events and from longer, continuous periods. Another analysis regards the influence of rainfall input and it is carried out varying the size and distribution of the raingauge network, in order to examine the relation between the spatial pattern of observed rainfall and the variability of modelled runoff. Lastly, a comparison of the hydrographs obtained for the flood events with the model parameterisation resulting when modifying the objective function to be minimised in the automatic calibration procedure is presented.

  12. Characterising the hydrological response to climate change of a remote tropical mountainous catchment: a multi-model approach

    NASA Astrophysics Data System (ADS)

    Exbrayat, J.-F.; Timbe, E.; Plesca, I.; Kraft, P.; Windhorst, D.; Trachte, K.; Buytaert, W.; Breuer, L.

    2012-04-01

    Process-based conceptual rainfall-runoff models are useful to understand runoff generation at different time and spatial resolutions. Contrary to physically-based models, they do not rely much on field observations (e.g. soil physical properties) which may not be available everywhere. Instead, these mathematical tools close the water balance and predict runoff as a function of some empirical parameters. Since corresponding values are hardly measurable, modellers usually proceed to a calibration against available observations to obtain an acceptable match between observations and predictions. However, in the case of poorly monitored areas such as elevated catchments in the Andean Cordillera, good high frequency calibration data available over a long time span are scarce. Therefore, in spite of the development of multiple effective automatized calibration techniques in recent years, results remain uncertain because of the non-uniqueness of optimal parameter sets. A state-of-the-art option to cope with this predictive uncertainty is to consider ensembles of predictions rather than single ones. Furthermore, by gathering more independent parameterisations of the same processes, multi-model approaches allow a better representation of the uncertainty than multiple realisations of the same, eventually biased, model structure subjectively chosen by the modeller based on previous experience or project requirements. As a demonstration of the usefulness of this approach in scarcely-monitored areas, we present here results of an ensemble of heterogeneous rainfall-runoff models applied to the remote San Francisco (75 km2) tropical montane forest catchment, located in the southern part of Ecuador. Each of the 7 models (CHIMP, HBV-D, HBV-light, HMS, LASCAM, NAM, SWAT) is applied to simulate runoff whilst being forced by 6 increasingly uncertain meteorological data: on-site precipitation gauges record (also used for calibration), bias-corrected downscaled re-analysis (SDSM) output

  13. Hydrologic consistency analysed through modeling at multiple time steps: does hydrological model performance benefit from finer time step information?

    NASA Astrophysics Data System (ADS)

    Ficchi, Andrea; Perrin, Charles; Andréassian, Vazken

    2015-04-01

    We investigate the operational utility of fine time step hydro-climatic information using a large catchment data set. The originality of this data set lies in the availability of precipitation data from the 6-minute rain gauges of Météo-France, and in the size of the catchment set (217 French catchments in total). The rainfall-runoff model used (GR4) has been adapted to hourly and sub-hourly time steps (up to 6-minute) from the daily time step version (Perrin et al., 2003). The model is applied at different time steps ranging from 6-minute to 1 day (6-, 12-, 30-minute, 1-, 3-, 6-, 12-hour and 1 day) and the evolution of model performance for each catchment is evaluated at the daily time step by aggregation of model outputs. Three classes of behavior are found according to the trend of model performance as the time step becomes finer: (i) catchments presenting an improvement of model performance; (ii) catchments with a model performance insensitive to the time step; (iii) catchments for which the performance even deteriorates as the time step becomes finer. The reasons behind these different trends are investigated from a hydrological point of view, by relating the model sensitivity to data at finer time step to catchment descriptors. References: Perrin, C., C. Michel and V. Andréassian (2003), "Improvement of a parsimonious model for streamflow simulation", Journal of Hydrology, 279(1-4): 275-289.

  14. NIRF, a Novel Ubiquitin Ligase, Inhibits Hepatitis B Virus Replication Through Effect on HBV Core Protein and H3 Histones.

    PubMed

    Qian, Guanhua; Hu, Bin; Zhou, Danlin; Xuan, Yanyan; Bai, Lu; Duan, Changzhu

    2015-05-01

    Np95/ICBP90-like RING finger protein (NIRF), a novel E3 ubiquitin ligase, has been shown to interact with HBc and promote its degradation. This study investigated the effects of NIRF on replication of hepatitis B virus (HBV) and the mechanisms. We have shown that NIRF inhibits replication of HBV DNA and secretion of HBsAg and HBeAg in HepG2 cells transfected with pAAV-HBV1.3. NIRF also inhibits the replication and secretion of HBV in a mouse model that expressed HBV. NIRF reduces acetylation of HBV cccDNA-bound H3 histones. These results showed that NIRF is involved in the HBV replication cycle not only through direct interaction with HBc but also reduces acetylation of HBV cccDNA-bound H3 histones. PMID:25664994

  15. Exploring Information Theory for improving Hydrologic Model Performance

    NASA Astrophysics Data System (ADS)

    Martinez Baquero, G. F.; Gupta, H. V.

    2005-12-01

    For more than 30 years, Information Theory (IT) concepts have appeared in literature and practice of hydrology in several ways. Although these concepts are implicit in many practical applications and ideas, still the language and use are not widespread among the scientific community dedicated to study hydrologic processes. At the same time, new points of view, as the shown in this session, reflect the increasing availability of data and information with finer resolution. Equally, increasing computing capabilities, the development of more complex decision-making systems, and better forecasting tools impose on hydrologists new challenges related to the optimal use of data and the information that can be extracted from it. In our understanding, one of the approaches to address these challenges is to recognize that the notion of information is inherent to the problem of dealing with hydrologic data and the evaluation of its characteristics. The goal of this poster is to evaluate how IT can be used to generate a conceptual framework for assessing the performance of models against real data, and how these assessments can help us to increase our knowledge about the physical mechanisms involved.

  16. Improved understanding and prediction of the hydrologic response of highly urbanized catchments through development of the Illinois Urban Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Cantone, Joshua; Schmidt, Arthur

    2011-08-01

    What happens to the rain in highly urbanized catchments? That is the question that urban hydrologists must ask themselves when trying to integrate the hydrologic and hydraulic processes that affect the hydrologic response of urban catchments. The Illinois Urban Hydrologic Model (IUHM) has been developed to help answer this question and improve understanding and prediction of hydrologic response in highly urbanized catchments. Urban catchments are significantly different than natural watersheds, but there are similarities that allow features of the pioneering geomorphologic instantaneous unit hydrograph concept developed for natural watersheds to be adapted to the urban setting. This probabilistically based approach is a marked departure from the traditional deterministic models used to design and simulate urban sewer systems and does not have the burdensome input data requirements that detailed deterministic models possess. Application of IUHM to the CDS-51 catchment located in the village of Dolton, Illinois, highlights the model's ability to predict the hydrologic response of the catchment as well as the widely accepted SWMM model and is in accordance with observed data recorded by the United States Geological Survey. In addition, the unique structure and organization of urban sewer networks make it possible to characterize a set of ratios for urban catchments that allow IUHM to be applied when detailed input data are not available.

  17. Estimating Runoff From Roadcuts With a Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Cuhaciyan, C.; Luce, C.; Voisin, N.; Lettenmaier, D.; Black, T.

    2008-12-01

    Roads can have a substantial effect on hydrologic patterns of forested watersheds; the most noteworthy being the resurfacing of shallow groundwater at roadcuts. The influence of roads on hydrology has compelled hydrologists to include water routing and storage routines in rainfall-runoff models, such as those in the Distributed Hydrologic Soil Vegetation Model (DHSVM). We tested the ability of DHSVM to match observed runoff in roadcuts of a watershed in the Coast Range of Oregon. Eight roadcuts were instrumented using large tipping bucket gauges designed to capture only the water entering the roadside ditch from an 80-m long roadcut. The roadcuts were categorized by the topography of the upstream hillside as either swale, planar, or ridge. The simulation was run from December 2002 to December 2003 at a relatively fine spatial resolution (10-m). Average observed soil depths are 1.8-m across the watershed, below which there lies deep and highly weathered sandstone. DHSVM was designed for relatively impermeable bedrock and shallow soils; therefore it does not provide a mechanism for deep groundwater movement and storage. In the geologic setting of the study basin, however, water is routed through the sandstone allowing water to pass under roads through the parent material. For this reason a uniformly deep soil of 6.5-m with a decreased decay in conductivity with depth was used in the model to allow water to be routed beneath roadcuts that are up to 5.5-m in height. Up to three, typically shallow, soil layers can be modeled in DHSVM. We used the lowest of the three soil layers to mimic the hydraulically-well-connected sandstone exposed at deeper roadcuts. The model was calibrated against observed discharge at the outlet of the watershed. While model results closely matched the observed hydrograph at the watershed outlet, simulated runoff at an upstream gauge and the roadside ditches were varied and often higher than those observed in the field. The timing of the field

  18. Hydrologic effects of fire in sagebrush plant communities: Implications for rangeland hydrology and erosion modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Millions of dollars are spent annually in the United States mitigating fire effects on rangeland hydrology and erosion. Rangeland managers and scientists need predictive tools to simulate hydrologic processes dictating post-fire responses, assist mitigation and risk assessments, and predict post-fir...

  19. How simple can a distributed hydrological model be?

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    It is well known that lumped conceptual models can often reproduce catchment streamflow response with about a 'handful' of model parameters. But what is the appropriate complexity of a distributed hydrological model, in order to reproduce the distinct streamflow response of heterogeneous internal subcatchments? Is the number of identifiable parameters proportional to the number of stream gauges? Into how many pieces should the catchment be broken-up? And which model structures are best suited to represent the behavior of particular landscape units? We investigated these questions in a case study based on the Attert basin in Luxembourg, where 10 subcatchments with clean and mixed geologies and land use manifested different rainfall-runoff behavior. The hydrological response of individual subcatchments was well represented using a range of lumped models with 4-8 parameters. We then attempted to simulate the 10 streamflow time series simultaneously, using a distributed model. Existing distributed models are often perceived to be over-parameterized. In order to avoid this problem, model development followed an iterative hypothesis-testing process. We developed, calibrated and compared alternative model variants, differing in the landscape classification approach, and in the structure of components intended to represent individual landscape elements. Decisions such as how to break-up the catchment, and which structure to assign to distinct landscape elements were found to significantly influence the model's predictive performance. In the present case, we determined that a geology-based landscape classification provided the best characterization of the observed differences in streamflow responses. In addition, we found that the individual geological units could be represented by remarkably simple model structures. The overall complexity of the distributed model was of about two 'handfuls' (10) of model parameters.

  20. Input Variable Selection for Hydrologic Modeling Using Anns

    NASA Astrophysics Data System (ADS)

    Ganti, R.; Jain, A.

    2011-12-01

    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

  1. Can a multi-model approach improve hydrological ensemble forecasting? A study on 29 French catchments using 16 hydrological model structures

    NASA Astrophysics Data System (ADS)

    Velázquez, J. A.; Anctil, F.; Ramos, M. H.; Perrin, C.

    2011-02-01

    An operational hydrological ensemble forecasting system based on a meteorological ensemble prediction system (M-EPS) coupled with a hydrological model searches to capture the uncertainties associated with the meteorological prediction to better predict river flows. However, the structure of the hydrological model is also an important source of uncertainty that has to be taken into account. This study aims at evaluating and comparing the performance and the reliability of different types of hydrological ensemble prediction systems (H-EPS), when ensemble weather forecasts are combined with a multi-model approach. The study is based on 29 catchments in France and 16 lumped hydrological model structures, driven by the weather forecasts from the European centre for medium-range weather forecasts (ECMWF). Results show that the ensemble predictions produced by a combination of several hydrological model structures and meteorological ensembles have higher skill and reliability than ensemble predictions given either by one single hydrological model fed by weather ensemble predictions or by several hydrological models and a deterministic meteorological forecast.

  2. Assimilating uncertain, dynamic and intermittent streamflow observations in hydrological models

    NASA Astrophysics Data System (ADS)

    Mazzoleni, Maurizio; Alfonso, Leonardo; Chacon-Hurtado, Juan; Solomatine, Dimitri

    2015-09-01

    Catastrophic floods cause significant socio-economical losses. Non-structural measures, such as real-time flood forecasting, can potentially reduce flood risk. To this end, data assimilation methods have been used to improve flood forecasts by integrating static ground observations, and in some cases also remote sensing observations, within water models. Current hydrologic and hydraulic research works consider assimilation of observations coming from traditional, static sensors. At the same time, low-cost, mobile sensors and mobile communication devices are becoming also increasingly available. The main goal and innovation of this study is to demonstrate the usefulness of assimilating uncertain streamflow observations that are dynamic in space and intermittent in time in the context of two different semi-distributed hydrological model structures. The developed method is applied to the Brue basin, where the dynamic observations are imitated by the synthetic observations of discharge. The results of this study show how model structures and sensors locations affect in different ways the assimilation of streamflow observations. In addition, it proves how assimilation of such uncertain observations from dynamic sensors can provide model improvements similar to those of streamflow observations coming from a non-optimal network of static physical sensors. This can be a potential application of recent efforts to build citizen observatories of water, which can make the citizens an active part in information capturing, evaluation and communication, helping simultaneously to improvement of model-based flood forecasting.

  3. Impact of wetlands mapping on parameterization of hydrologic simulation models

    NASA Astrophysics Data System (ADS)

    Viger, R.

    2015-12-01

    Wetlands and other surface depressions can impact hydrologic response within the landscape in a number of ways, such as intercepting runoff and near-surface flows or changing the potential for evaporation and seepage into the soil. The role of these features is increasingly being integrated into hydrological simulation models, such as the USGS Precipitation-Runoff Modeling System (PRMS) and the Soil Water Assessment Tool (SWAT), and applied to landscapes where wetlands are dominating features. Because the extent of these features varies widely through time, many modeling applications rely on delineations of the maximum possible extent to define total capacity of a model's spatial response unit. This poster presents an evaluation of several wetland map delineations for the Pipestem River basin in the North Dakota Prairie-pothole region. The featured data sets include the US Fish and Wildlife Service National Wetlands Inventory (NWI), surface water bodies extracted from the US Geological Survey National Hydrography Dataset (NHD), and elevation depressions extracted from 1 meter LiDAR data for the area. In addition to characterizing differences in the quality of these datasets, the poster will assess the impact of these differences when parameters are derived from them for the spatial response units of the PRMS model.

  4. A flexible modeling package for topographically based watershed hydrology

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Endreny, Theodore A.; Hassett, James M.

    2005-11-01

    An OBJect-oriented TOPographic-based (OBJTOP) hydrological model with a graphical user interface (GUI) was created using object-oriented design (OOD) methods and the objected-oriented programming (OOP) language-C++. OBJTOP presents an array of alternative TOPMODEL hydrological processes of (1) saturation excess or the mixture of infiltration/saturation excess overland flow, (2) exponential or power law decay of hydraulic conductivity with soil depth, (3) topographic index (TI) or soil topographic index (STI) weighting of run-off likelihood, and (4) simulations with or without channel routing, to explain watershed response and increase flexibility and applicability. OBJTOP utilized an object-oriented design (OOD) approach, including the 'inheritance' concept to study individual objects (or processes) at multiple levels, and the 'aggregation' concept to study the interactions of objects (or processes). Further, OOD readily provides for model extension, creating a description of hydrologic processes in a natural, direct, concise, and adaptable manner distinct from procedurally designed and implemented models. The OBJTOP GUI provides an efficient tool for data input, parameter modification, simulation scheme selection and model calibration with three objective functions, including Nash-Sutcliffe. Graphical outputs include time series plots of precipitation depth, partitioned run-off volumes, watertable depth (average or TI/STI based), and map graphics of TI, STI, and depth to watertable. Applications illustrating OBJTOP ability and flexibility include simulation of the TOPMODEL standard Slapton Wood, UK dataset, and simulation of Ward Pound Ridge, NY a small forested catchment with power function decay of hydraulic conductivity and extensive impervious surfaces.

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

    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.

  6. An Integrated Hydrologic Bayesian Multi-Model Combination Framework: Confronting Input, parameter and model structural uncertainty in Hydrologic Prediction

    SciTech Connect

    Ajami, N K; Duan, Q; Sorooshian, S

    2006-05-05

    This paper presents a new technique--Integrated Bayesian Uncertainty Estimator (IBUNE) to account for the major uncertainties of hydrologic rainfall-runoff predictions explicitly. The uncertainties from the input (forcing) data--mainly the precipitation observations and from the model parameters are reduced through a Monte Carlo Markov Chain (MCMC) scheme named Shuffled Complex Evolution Metropolis (SCEM) algorithm which has been extended to include a precipitation error model. Afterwards, the Bayesian Model Averaging (BMA) scheme is employed to further improve the prediction skill and uncertainty estimation using multiple model output. A series of case studies using three rainfall-runoff models to predict the streamflow in the Leaf River basin, Mississippi are used to examine the necessity and usefulness of this technique. The results suggests that ignoring either input forcings error or model structural uncertainty will lead to unrealistic model simulations and their associated uncertainty bounds which does not consistently capture and represent the real-world behavior of the watershed.

  7. Assessing spatial patterns to characterize performance in hydrological modeling

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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

  8. Simultaneous Assimilation of Multiple Data into a Conceptual Rainfall-Runoff Model using Variational Methods for Hydrological Forecasting Applications

    NASA Astrophysics Data System (ADS)

    Schwanenberg, D.; Alvarado Montero, R.; Sensoy Sorman, A.; Krahe, P.

    2015-12-01

    Data assimilation methods applied to hydrological applications have primarily focused on assimilating streamflow and, more recently, soil moisture observations. Few cases actually assimilate both observations, and even fewer incorporate additional observations into the assimilation procedure. This is despite extensive developments in remote sensing information. Most research on data assimilation has focused on the implementation of sequential assimilation using Kalman filters. We present an alternative approach using variational methods based on Moving Horizon Estimation (MHE) to simultaneously assimilate streamflow data and remote sensing information obtained from the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) community, namely snow-covered area, snow water equivalent and soil moisture. This approach enables a highly flexible formulation of distance metrics for the introduction of noise into the model and the agreement between simulated and observed variables. The application of MHE on data assimilation is tested at two data-dense test sites in Germany and one data-sparse environment in Turkey. The assessment of results is based on the lead time performance of state variables of the conceptual rainfall-runoff model, i.e. not limited to the performance of streamflow forecast but also applicable to snow and soil moisture forecast skills. Results show a potential improvement on the performance of the forecasted streamflow when using a perfect time series of state variables generated through the simulation of the conceptual rainfall-runoff model HBV. The assimilation of H-SAF data, in combination with streamflow, reduces the performance of the forecasted streamflow compared to the assimilation using only streamflow data. However, other forecasted quantities such as the snow water equivalent or soil moisture are improved. Recommendations based on the test cases are given following the length of the assimilation

  9. Modelling the Mekong: hydrological simulation for environmental impact studies

    NASA Astrophysics Data System (ADS)

    Kite, Geoff

    2001-11-01

    The Mekong, with a basin area of almost 800,000 km 2 and a length of 4500 km, is one of the most important rivers of the world. The many lakes and wetlands along the river, including Cambodia's Tonle Sap (Grand Lac), are major sources of fish for the riparian peoples and form an important part of the regional economy. This resource may be affected by proposed developments in the basin. Using climatic, topographic and land cover data from the Internet, the semi-distributed land-use runoff process (SLURP) hydrological model was used to simulate the complete hydrological cycle of the Mekong and its tributaries. Information on dam locations and reservoir characteristics were obtained from local sources. The model was verified by comparing simulated flows with recorded daily flows for the Mekong River and by comparing simulated levels of the Tonle Sap lake with recorded daily levels. The daily computed levels of the Tonle Sap lake were then converted into flooded areas for each land cover around the lake which were then used in a fish production model to evaluate the possible impacts of basin development on the fisheries. Model outputs may also be used to investigate issues such as water allocations and the effects of land use change or climate change on water resources and the aquatic and riparian environments.

  10. Modeling Vernal Pool Hydrology and Vegetation in the Sierra Nevadas

    NASA Astrophysics Data System (ADS)

    Montrone, A. K.; Saito, L.; Weisberg, P.; Gosejohan, M.

    2012-12-01

    Vernal pools are geographic depressions with relatively impermeable substrates that are subject to four distinct seasons in mountainous regions: they fill with snow in the winter, melt into inundated pools in the spring, become unsaturated and vegetated by summer, then dry and become fully desiccated by fall. Vernal pools in California are greatly threatened. Over 90% of the pools in California have been destroyed by urbanization and other land use changes and continue to disappear with population growth. Furthermore, these pools face threats posed by climate change due to altered precipitation and temperature regimes. In the context of anthropogenic climate change, we are evaluating the direct and indirect effects of grazing management on ecohydrology and plant community structure in vernal pools Northern Sierra Nevada mountains. Hydrologic models of vernal pool basins, driven by climatic variables, are used to 1) determine if a changing climate will alter the magnitude and spatial distribution of inundation period within the pools; 2) determine how the available habitat for vernal pool vegetation specialists will change with climate change; 3) determine if increased soil compaction due to cattle grazing can help mitigate effects of climate change resulting from changes in hydraulic conductivity; and 4) determine the importance of spatial resolution in constructing the physical representation of the pools within the hydrologic models. Preliminary results from the models including calibration error metrics and hydroperiod impacts of grazing for models with varying spatial complexity will be presented.

  11. Modeling of subglacial hydrological development following rapid supraglacial lake drainage

    NASA Astrophysics Data System (ADS)

    Dow, C. F.; Kulessa, B.; Rutt, I. C.; Tsai, V. C.; Pimentel, S.; Doyle, S. H.; As, D.; Lindbäck, K.; Pettersson, R.; Jones, G. A.; Hubbard, A.

    2015-06-01

    The rapid drainage of supraglacial lakes injects substantial volumes of water to the bed of the Greenland ice sheet over short timescales. The effect of these water pulses on the development of basal hydrological systems is largely unknown. To address this, we develop a lake drainage model incorporating both (1) a subglacial radial flux element driven by elastic hydraulic jacking and (2) downstream drainage through a linked channelized and distributed system. Here we present the model and examine whether substantial, efficient subglacial channels can form during or following lake drainage events and their effect on the water pressure in the surrounding distributed system. We force the model with field data from a lake drainage site, 70 km from the terminus of Russell Glacier in West Greenland. The model outputs suggest that efficient subglacial channels do not readily form in the vicinity of the lake during rapid drainage and instead water is evacuated primarily by a transient turbulent sheet and the distributed system. Following lake drainage, channels grow but are not large enough to reduce the water pressure in the surrounding distributed system, unless preexisting channels are present throughout the domain. Our results have implications for the analysis of subglacial hydrological systems in regions where rapid lake drainage provides the primary mechanism for surface-to-bed connections.

  12. Approaches to handle data of low quality in hydrological modelling

    NASA Astrophysics Data System (ADS)

    Herma, Felix; Bárdossy, András; Hörning, Sebastian

    2015-04-01

    Hydrological modelling is an important tool for many applications in water resources engineering. It is widely used for designing storage reservoirs, flood protection measures or for prediction purposes. Therefore the quality of the required input data and the used hydrological model have a significant influence on the quality of the results and, consequently, on the reliability for the mentioned objectives above. Many factors affect the usefulness of data and models. In the first place, the number and spatial distribution of observation points build the base for all subsequent processes. Secondly, the quality of the input data, e.g. discharge, precipitation, has to be checked. It is known that rain gauge measurements underlie a high uncertainty, especially during periods with high rain intensities or snowfall. Last, the choice of the model according to the objective of its usage is the determining factor. Under such conditions a reliable assessment of the uncertainty is required. This contribution will focus on the described items and try to provide approaches on how to handle the presented problems. A hydrological model usually needs areal information of specific input data. The density and distribution of gauging stations lead to uncertainty if a spatial interpolation of the measures is applied. In the case of a high topographic variability within a catchment, uncertainties through the underestimation of rainfall amounts at exposed stations can occur. Drifts of rain or snow by wind are a central issue at this point. Common interpolation methods of precipitation are different forms of kriging which provide only the best estimate at the ungauged locations. However, these methods cannot correctly quantify the associated uncertainty of the estimation. Thus, this contribution applies a new method of random mixing of spatial random fields with the ability to incorporate equality and inequality constraints. Such conditions are applied to exposed gauging stations on

  13. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    USGS Publications Warehouse

    Hwang, Y.; Clark, M.; Rajagopalan, B.; Leavesley, G.

    2012-01-01

    Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

  14. Considering complementary relationship of evaporation in Budyko's hydrological model

    NASA Astrophysics Data System (ADS)

    Han, Songjun; Shao, Weiwei

    2013-04-01

    In Budyko's hydrological model, actual evaporation was partitioned from precipitation as a function of the relative magnitude of precipitation and potential evaporation. In practice, both Penman equation and Priestley-Taylor equation have been used to estimate the potential evaporation with same Budyko curve, and they are not distinguished under Budyko framework. Nevertheless, according to the complementary relationship of evaporation, the definitions of Penman equation and Priestley-Taylor equation are absolutely different. When water availability is not limited, evaporation occurs at Priestley-Taylor's evaporation (Ew, referred to as wet environment evaporation). As the surface dries without changing the available energy, the actual and Penman's potential evaporation (Epen) rates depart from Ew with opposite changes in fluxes. So the question is: what is the difference of the Budyko's hydrological model with potential evaporation estimated by Penman or Priestley-Taylor equation? How to consider the complementary relationship in Budyko framework? In this study, for both long-term (multiyear) and annual values on water balances in the 29 non-humid catchments in the middle Yellow River Basin of China, the performances of Budyko's hydrological model with potential evaporation estimated by Epen and Ew were distinguished and compared. The catchments with larger value of Ep/Ew (ratio of Penman potential evaporation to Priestley-Taylor evaporation) are characterized with smaller evaporation ratios. The value of Ep/Ew can be served as another variable besides dryness index to partition actual evaporation from precipitation. With Priestley-Taylor equation as energy supply, an empirical formula for the parameter of the Budyko in terms of Ep/Ew and curve is proposed. Therefore, the complementary relationship of evaporation should be considered in the Budyko framework.

  15. Modelling exploration of non-stationary hydrological system

    NASA Astrophysics Data System (ADS)

    Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei

    2015-04-01

    Traditional hydrological modelling assumes that the catchment does not change with time (i.e., stationary conditions) which means the model calibrated for the historical period is valid for the future period. However, in reality, due to change of climate and catchment conditions this stationarity assumption may not be valid in the future. It is a challenge to make the hydrological model adaptive to the future climate and catchment conditions that are not observable at the present time. In this study a lumped conceptual rainfall-runoff model called IHACRES was applied to a catchment in southwest England. Long observation data from 1961 to 2008 were used and seasonal calibration (in this study only summer period is further explored because it is more sensitive to climate and land cover change than the other three seasons) has been done since there are significant seasonal rainfall patterns. We expect that the model performance can be improved by calibrating the model based on individual seasons. The data is split into calibration and validation periods with the intention of using the validation period to represent the future unobserved situations. The success of the non-stationary model will depend not only on good performance during the calibration period but also the validation period. Initially, the calibration is based on changing the model parameters with time. Methodology is proposed to adapt the parameters using the step forward and backward selection schemes. However, in the validation both the forward and backward multiple parameter changing models failed. One problem is that the regression with time is not reliable since the trend may not be in a monotonic linear relationship with time. The second issue is that changing multiple parameters makes the selection process very complex which is time consuming and not effective in the validation period. As a result, two new concepts are explored. First, only one parameter is selected for adjustment while the other

  16. Implications of complete watershed soil moisture measurements to hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Engman, E. T.; Jackson, T. J.; Schmugge, T. J.

    1983-01-01

    A series of six microwave data collection flights for measuring soil moisture were made over a small 7.8 square kilometer watershed in southwestern Minnesota. These flights were made to provide 100 percent coverage of the basin at a 400 m resolution. In addition, three flight lines were flown at preselected areas to provide a sample of data at a higher resolution of 60 m. The low level flights provide considerably more information on soil moisture variability. The results are discussed in terms of reproducibility, spatial variability and temporal variability, and their implications for hydrologic modeling.

  17. Hydrological Ensemble Simulation in Huaihe Catchment Based on VIC Model

    NASA Astrophysics Data System (ADS)

    Sun, R.; Yuan, H.

    2013-12-01

    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

  18. Hydrological Response to Climate Change over the Blue Nile Basin Distributed hydrological modeling based on surrogate climate change scenarios

    NASA Astrophysics Data System (ADS)

    Berhane, F. G.; Anyah, R. O.

    2010-12-01

    The program Soil and Water Assessment Tool (SWAT2009) model has been applied to the Blue Nile Basin to study the hydrological response to surrogate climate changes over the Blue Nile Basin (Ethiopia) by downscaling gridded weather data. The specific objectives of the study include (i) examining the performance of the SWAT model in simulating hydrology-climate interactions and feedbacks within the entire Blue Nile Basin, and (ii) investigating the response of hydrological variables to surrogate climate changes. Monthly weather data from the Climate Research Unit (CRU) are converted to daily values as input into the SWAT using Monthly to Daily Weather Converter (MODAWEC). Using the program SUFI-2 (Sequential Uncertainty Fitting Algorithm), data from 1979 to 1983 are applied for sensitivity analysis and calibration (P-factor = 90%, R-factor =0.7, R2 =0.93 and NS=0.93) and subsequently to validate hindcasts over the period 1984-1989 (R2 =0.92 and NS=0.92). The period from 1960-2000 was used as baseline and has been used to determine the changes and the effect of the surrogate climate changes over the Blue Nile Basin. Overall, our surrogate climate change based simulations indicate the hydrology of the Blue Nile catchment is very sensitive to potential climate change with 100%, 34% and 51% increase to the surface runoff, lateral flow and water yield respectively for the A2 scenario surrogate. Key Words: SWAT, MODAWEC, Blue Nile Basin, SUFI-2, climate change, hydrological modeling, CRU

  19. Disentangling the uncertainty of hydrologic drought characteristics in a multi-model century-long experiment in continental river basins

    NASA Astrophysics Data System (ADS)

    Samaniego, Luis; Kumar, Rohini; Pechlivanidis, Illias; Breuer, Lutz; Wortmann, Michel; Vetter, Tobias; Flörke, Martina; Chamorro, Alejandro; Schäfer, David; Shah, Harsh; Zeng, Xiaofan

    2016-04-01

    The quantification of the predictive uncertainty in hydrologic models and their attribution to its main sources is of particular interest in climate change studies. In recent years, a number of studies have been aimed at assessing the ability of hydrologic models (HMs) to reproduce extreme hydrologic events. Disentangling the overall uncertainty of streamflow -including its derived low-flow characteristics- into individual contributions, stemming from forcings and model structure, has also been studied. Based on recent literature, it can be stated that there is a controversy with respect to which source is the largest (e.g., Teng, et al. 2012, Bosshard et al. 2013, Prudhomme et al. 2014). Very little has also been done to estimate the relative impact of the parametric uncertainty of the HMs with respect to overall uncertainty of low-flow characteristics. The ISI-MIP2 project provides a unique opportunity to understand the propagation of forcing and model structure uncertainties into century-long time series of drought characteristics. This project defines a consistent framework to deal with compatible initial conditions for the HMs and a set of standardized historical and future forcings. Moreover, the ensemble of hydrologic model predictions varies across a broad range of climate scenarios and regions. To achieve this goal, we use six preconditioned hydrologic models (HYPE or HBV, mHM, SWIM, VIC, and WaterGAP3) set up in seven large continental river basins: Amazon, Blue Nile, Ganges, Niger, Mississippi, Rhine, Yellow. These models are forced with bias-corrected outputs of five CMIP5 general circulation models (GCM) under four extreme representative concentration pathway (RCP) scenarios (i.e. 2.6, 4.5, 6.0, and 8.5 Wm‑2) for the period 1971-2099. Simulated streamflow is transformed into a monthly runoff index (RI) to analyze the attribution of the GCM and HM uncertainty into drought magnitude and duration over time. Uncertainty contributions are investigated

  20. A conceptual data model coupling with physically-based distributed hydrological models based on catchment discretization schemas

    NASA Astrophysics Data System (ADS)

    Liu, Yuanming; Zhang, Wanchang; Zhang, Zhijie

    2015-11-01

    In hydrology, the data types, spatio-temporal scales and formats for physically-based distributed hydrological models and the distributed data or parameters may be different before significant data pre-processing or may change during hydrological simulation run time. A data model is devoted to these problems for sophisticated numerical hydrological modeling procedures. In this paper, we propose a conceptual data model to interpret the comprehensive, universal and complex water environmental entities. We also present an innovative integration methodology to couple the data model with physically-based distributed hydrological models (DHMs) based on catchment discretization schemas. The data model provides a reasonable framework for researchers of organizing and pre-processing water environmental spatio-temporal datasets. It also facilitates seamless data flow fluid and dynamic by hydrological response units (HRUs) as the core between the object-oriented databases and physically-based distributed hydrological models.

  1. Integrating water resources management in eco-hydrological modelling.

    PubMed

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

    2013-01-01

    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

  2. Models and data for hydrological analyses - lessons learned from uncertainty

    NASA Astrophysics Data System (ADS)

    Balin, D.; Parent, E.; Goetzinger, J.; Musy, A.; Bardossy, A.; Rode, M.

    2009-04-01

    Modelling has become an unavoidable step in the hydrological analyses. Intensive monitoring of experimental or representative catchments in different environments allowed identifying of dominant processes that further enabled the choice of an appropriate model structure to be used for simulation, forecast or scenario analyses. Progresses have been done in building different modelling structures (conceptual and physically based, lumped and distributed) that are now being extensively used at different scales, with different amounts of input data and together with different calibration procedures. The present study will analyse the role of uncertainty, in a Bayesian context, as a tool to learn how input data (discharge, soil moisture, chemistry, rainfall) could be used to evaluate two semi and fully distributed modelling structures (TOPMODEL and WASIM-ETH) in two different catchments: a small (2km2) one in the Swiss Plateau region (the Haute-Mentue catchment) and a medium (100km2) one in low range mountain in central Germany (Weisse Elster catchment).

  3. Simultaneous calibration of hydrological models in geographical space

    NASA Astrophysics Data System (ADS)

    Bárdossy, A.; Huang, Y.; Wagener, T.

    2015-10-01

    Hydrological models are usually calibrated for selected catchments individually using specific performance criteria. This procedure assumes that the catchments show individual behavior. As a consequence, the transfer of model parameters to other ungauged catchments is problematic. In this paper, the possibility of transferring part of the model parameters was investigated. Three different conceptual hydrological models were considered. The models were restructured by introducing a new parameter η which exclusively controls water balances. This parameter was considered as individual to each catchment. All other parameters, which mainly control the dynamics of the discharge (dynamical parameters), were considered for spatial transfer. Three hydrological models combined with three different performance measures were used in four different numerical experiments to investigate this transferability. The first numerical experiment, individual calibration of the models for 15 selected MOPEX catchments, showed that it is difficult to identify which catchments share common dynamical parameters. Parameters of one catchment might be good for another catchment but not reversed. In the second numerical experiment, a common spatial calibration strategy was used. It was explicitly assumed that the catchments share common dynamical parameters. This strategy leads to parameters which perform well on all catchments. A leave one out common calibration showed that in this case a good parameter transfer to ungauged catchments can be achieved. In the third numerical experiment, the common calibration methodology was applied for 96 catchments. Another set of 96 catchments were used to test the transfer of common dynamical parameters. The results show that even a large number of catchments share similar dynamical parameters. The performance is worse than those obtained by individual calibration, but the transfer to ungauged catchments remains possible. The performance of the common

  4. Hydrologic Analysis for Kankakee River Watershed Streamflow Accounting Model

    NASA Astrophysics Data System (ADS)

    Zhang, Z.; Knapp, H. V.

    2014-12-01

    Streamflow frequency is used for in-stream flow needs evaluation, water supply planning, water quality analysis, and stream classification, among other purposes. The Illinois Streamflow Accounting Model (ILSAM) was developed to predict the streamflow frequency for Illinois streams and has the capacity to explore anthropogenic impacts on streamflow frequency. Over the past two decades, ILSAM has been applied to ten major watersheds in Illinois. This study updates the hydrologic analysis for the Kankakee River watershed. The hydrologic analyses used to develop the model involved evaluating streamflow records from gaging stations and developing regional equations to estimate flows at ungaged sites throughout the watersheds. Impacts to flow quantity from dams, water supplies, and treated wastewater effluents are examined. The baseline flow condition is the flow record at gaged sites which includes historic anthropogenic effects. The unaltered flow condition, influenced primarily by climate, topography, hydrogeology, and land use, is determined by separating the effects of historic human impact. The effects of the various human modifications to flow in the basin have changed substantially over the history of the available streamflow records. The present flow condition is determined by assuming that current human impact extends back throughout the history of available streamflow records, and statistical estimates are computed accordingly. Flow frequency estimates for each gaging record are adjusted to account for differences in the period of record and other factors such as the hydrologic persistence of low flow. For ungaged sites, a regional regression based on unaltered flow conditions is developed to estimate flow frequency, and adjustments are made to account for human impacts to represent the present flow condition for all sites.

  5. One-Water Hydrologic Flow Model (MODFLOW-OWHM)

    USGS Publications Warehouse

    Hanson, Randall T.; Boyce, Scott E.; Schmid, Wolfgang; Hughes, Joseph D.; Mehl, Steffen W.; Leake, Stanley A.; Maddock, Thomas, III; Niswonger, Richard G.

    2014-01-01

    The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply

  6. EFFICIENT HYDROLOGICAL TRACER-TEST DESIGN (EHTD) MODEL

    EPA Science Inventory

    Hydrological tracer testing is the most reliable diagnostic technique available for establishing flow trajectories and hydrologic connections and for determining basic hydraulic and geometric parameters necessary for establishing operative solute-transport processes. Tracer-test...

  7. 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)

    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

    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

  8. Catchment Classification via Hydrologic Modeling: Evaluating the Relative Importance of Model Selection, Parameterization and Classification Techniques

    NASA Astrophysics Data System (ADS)

    Marshall, L. A.; Smith, T. J.; To, L.

    2015-12-01

    Classification has emerged as an important tool for evaluating the runoff generating mechanisms in catchments and for providing a basis on which to group catchments having similar characteristics. These methods are particularly important for transferring models from one catchment to another in the case of data scarce regions or paired catchment studies .In many cases, the goal of catchment classification is to be able to identify models or parameter sets that could be applied to similar catchments for predictive purposes. A potential impediment to this goal is the impact of error in both the classification technique and the hydrologic model. In this study, we examine the relationship between catchment classification, hydrologic models, and model parameterizations for the purpose of transferring models between similar catchments. Building on previous work using a data set of over 100 catchments from south-east Australia, we identify several hydrologic model structures and calibrate each model for each catchment. We use clustering to identify groups of catchments with similar hydrologic response (as characterized through the calibrated model parameters). We examine the dependency of the clustered catchment groups on the pre-selected model, the uncertainty in the calibrated model parameters, and the clustering or classification algorithm. Further, we investigate the relationship between the catchment clusters and certain catchment physical characteristics or signatures, which are more typically used for catchment classification. Overall, our work is aimed at elucidating the potential sources of uncertainty in catchment classification, and the utility of classification for improving hydrologic predictions.

  9. Current Concepts of HBV/HCV Coinfection: Coexistence, but Not Necessarily in Harmony

    PubMed Central

    Jamma, Shailaja; Hussain, Ghazi; Lau, Daryl T.-Y.

    2011-01-01

    Hepatitis B and hepatitis C are important causes of chronic liver disease globally. Although HBV/HCV coinfection is not uncommon, its epidemiology is poorly defined. Numerous studies provided evidence that coinfection accelerates liver disease progression and increases the risk of hepatocellular carcinoma. By applying new cell culture models to examine the interaction of both viruses, investigators concluded that HBV and HCV replicate in the same hepatocyte without interference. The roles of innate and adaptive immunity in determining the viral replication and disease outcomes still need rigorous investigation. To date, no standard-of-care recommendation exists for HBV/HCV coinfection. Pegylated interferon and ribavirin combination therapy demonstrated similar efficacy in suppressing HCV RNA in coinfection and HCV monoinfection. However, HBV reactivation during therapy can be a challenge. Future clinical trials evaluating the addition of a nucleoside/nucleotide analog for selective patients with HBV/HCV coinfection are essential for successful management of HBV/HCV coinfection. PMID:21258658

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

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

    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

  11. Real Time Land-Surface Hydrologic Modeling Over Continental US

    NASA Technical Reports Server (NTRS)

    Houser, Paul R.

    1998-01-01

    The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

  12. Techniques to Access Databases and Integrate Data for Hydrologic Modeling

    SciTech Connect

    Whelan, Gene; Tenney, Nathan D.; Pelton, Mitchell A.; Coleman, Andre M.; Ward, Duane L.; Droppo, James G.; Meyer, Philip D.; Dorow, Kevin E.; Taira, Randal Y.

    2009-06-17

    This document addresses techniques to access and integrate data for defining site-specific conditions and behaviors associated with ground-water and surface-water radionuclide transport applicable to U.S. Nuclear Regulatory Commission reviews. Environmental models typically require input data from multiple internal and external sources that may include, but are not limited to, stream and rainfall gage data, meteorological data, hydrogeological data, habitat data, and biological data. These data may be retrieved from a variety of organizations (e.g., federal, state, and regional) and source types (e.g., HTTP, FTP, and databases). Available data sources relevant to hydrologic analyses for reactor licensing are identified and reviewed. The data sources described can be useful to define model inputs and parameters, including site features (e.g., watershed boundaries, stream locations, reservoirs, site topography), site properties (e.g., surface conditions, subsurface hydraulic properties, water quality), and site boundary conditions, input forcings, and extreme events (e.g., stream discharge, lake levels, precipitation, recharge, flood and drought characteristics). Available software tools for accessing established databases, retrieving the data, and integrating it with models were identified and reviewed. The emphasis in this review was on existing software products with minimal required modifications to enable their use with the FRAMES modeling framework. The ability of four of these tools to access and retrieve the identified data sources was reviewed. These four software tools were the Hydrologic Data Acquisition and Processing System (HDAPS), Integrated Water Resources Modeling System (IWRMS) External Data Harvester, Data for Environmental Modeling Environmental Data Download Tool (D4EM EDDT), and the FRAMES Internet Database Tools. The IWRMS External Data Harvester and the D4EM EDDT were identified as the most promising tools based on their ability to access and

  13. A high-resolution European dataset for hydrologic modeling

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    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

  14. ANNIE - INTERACTIVE PROCESSING OF DATA BASES FOR HYDROLOGIC MODELS.

    USGS Publications Warehouse

    Lumb, Alan M.; Kittle, John L.

    1985-01-01

    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.

  15. Advances in Modeling of Coupled Hydrologic-Socioeconomic Systems

    NASA Astrophysics Data System (ADS)

    Amadio, Mattia; Mysiak, Jaroslav; Pecora, Silvano; Agnetti, Alberto

    2013-04-01

    River flooding is the most common natural disaster in Europe, causing deaths and huge amount of economic losses. Disastrous flood events are often related to extreme meteorological conditions; therefore, climate change is expected to have an important influence over the intensity and frequency of major floods. While approximated large-scale assessments of flood risk scenarios have been carried out, the knowledge of the effects at smaller scales is poor or incomplete, with few localized studies. Also, the methods are still coarse and uneven. The approach of this study starts from the definition of the risk paradigm and the elaboration of local climatic scenarios to track a methodology aimed at elaborating and combining the three elements concurring to the determination of risk: hydrological hazard, value exposure and vulnerability. First, hydrological hazard scenarios are provided by hydrological and hydrodynamic models, used in to a flood forecasting system capable to define "what-if" scenario in a flexible way. These results are then integrated with land-use data (exposure) and depth-damage functions (vulnerability) in a GIS environment, to assess the final risk value (potential flood damage) and visualize it in form of risk maps. In this paper results from a pilot study in the Polesine area are presented, where four simulated levee breach scenarios are compared. The outcomes of the analysis may be instrumental to authorities to increase the knowledge of possible direct losses and guide decision making and planning processes also. As future perspective, the employed methodology can also be extended at the basin scale through integration with the existent flood warning system to gain a real-time estimate of floods direct costs.

  16. A hydrologic and geomorphic model of estuary breaching and closure

    NASA Astrophysics Data System (ADS)

    Rich, Andrew; Keller, Edward A.

    2013-06-01

    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

  17. Can global hydrological models reproduce large scale river flood regimes?

    NASA Astrophysics Data System (ADS)

    Eisner, Stephanie; Flörke, Martina

    2013-04-01

    River flooding remains one of the most severe natural hazards. On the one hand, major flood events pose a serious threat to human well-being, causing deaths and considerable economic damage. On the other hand, the periodic occurrence of flood pulses is crucial to maintain the functioning of riverine floodplains and wetlands, and to preserve the ecosystem services the latter provide. In many regions, river floods reveal a distinct seasonality, i.e. they occur at a particular time during the year. This seasonality is related to regionally dominant flood generating processes which can be expressed in river flood types. While in data-rich regions (esp. Europe and North America) the analysis of flood regimes can be based on observed river discharge time series, this data is sparse or lacking in many other regions of the world. This gap of knowledge can be filled by global modeling approaches. However, to date most global modeling studies have focused on mean annual or monthly water availability and their change over time while simulating discharge extremes, both floods and droughts, still remains a challenge for large scale hydrological models. This study will explore the ability of the global hydrological model WaterGAP3 to simulate the large scale patterns of river flood regimes, represented by seasonal pattern and the dominant flood type. WaterGAP3 simulates the global terrestrial water balance on a 5 arc minute spatial grid (excluding Greenland and Antarctica) at a daily time step. The model accounts for human interference on river flow, i.e. water abstraction for various purposes, e.g. irrigation, and flow regulation by large dams and reservoirs. Our analysis will provide insight in the general ability of global hydrological models to reproduce river flood regimes and thus will promote the creation of a global map of river flood regimes to provide a spatially inclusive and comprehensive picture. Understanding present-day flood regimes can support both flood risk

  18. Inverse hydrological modelling of spatio-temporal rainfall patterns

    NASA Astrophysics Data System (ADS)

    Grundmann, Jens; Hörning, Sebastian; Bárdossy, András

    2016-04-01

    Distributed hydrological models are commonly used for simulating the non-linear response of a watershed to rainfall events for addressing different hydrological properties of the landscape. Such models are driven by spatial rainfall patterns for consecutive time steps, which are normally generated from point measurements using spatial interpolation methods. However, such methods fail in reproducing the true spatio-temporal rainfall patterns especially in data scarce regions with poorly gauged catchments or for highly dynamic, small scaled rainstorms which are not well recorded by existing monitoring networks. Consequently, uncertainties are associated with poorly identified spatio-temporal rainfall distribution in distributed rainfall-runoff-modelling since the amount of rainfall received by a catchment as well as the dynamics of the runoff generation of flood waves are underestimated. For addressing these challenges a novel methodology for inverse hydrological modelling is proposed using a Markov-Chain-Monte-Carlo framework. Thereby, potential candidates of spatio-temporal rainfall patterns are generated and selected according their ability to reproduce the observed surface runoff at the catchment outlet for a given transfer function in a best way. The Methodology combines the concept of random mixing of random spatial fields with a grid-based spatial distributed rainfall runoff model. The conditional target rainfall field is obtained as a linear combination of unconditional spatial random fields. The corresponding weights of the linear combination are selected such that the spatial variability of the rainfall amounts as well as the actual observed rainfall values are reproduced. The functionality of the methodology is demonstrated on a synthetic example. Thereby, the known spatio-temporal distribution of rainfall is reproduced for a given number of point observations of rainfall and the integral catchment response at the catchment outlet for a synthetic catchment

  19. European Continental Scale Hydrological Model, Limitations and Challenges

    NASA Astrophysics Data System (ADS)

    Rouholahnejad, E.; Abbaspour, K.

    2014-12-01

    The pressures on water resources due to increasing levels of societal demand, increasing conflict of interest and uncertainties with regard to freshwater availability create challenges for water managers and policymakers in many parts of Europe. At the same time, climate change adds a new level of pressure and uncertainty with regard to freshwater supplies. On the other hand, the small-scale sectoral structure of water management is now reaching its limits. The integrated management of water in basins requires a new level of consideration where water bodies are to be viewed in the context of the whole river system and managed as a unit within their basins. In this research we present the limitations and challenges of modelling the hydrology of the continent Europe. The challenges include: data availability at continental scale and the use of globally available data, streamgauge data quality and their misleading impacts on model calibration, calibration of large-scale distributed model, uncertainty quantification, and computation time. We describe how to avoid over parameterization in calibration process and introduce a parallel processing scheme to overcome high computation time. We used Soil and Water Assessment Tool (SWAT) program as an integrated hydrology and crop growth simulator to model water resources of the Europe continent. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals for the period of 1970-2006. The use of a large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation and provides the overall picture of water resources temporal and spatial distribution across the continent. The calibrated model and results provide information support to the European Water

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

    NASA Astrophysics Data System (ADS)

    Yang, Dawen; Cong, Zhentao; Yang, Hanbo

    2013-04-01

    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.

  1. Hydrological modelling of slopes from field monitoring data

    NASA Astrophysics Data System (ADS)

    Comegna, Luca; Damiano, Emilia; Greco, Roberto; Guida, Andrea; Olivares, Lucio; Picarelli, Luciano

    2013-04-01

    A simplified hydrological model of a steep slope covered with loose granular pyroclastic deposits is presented. The slope is located in the mountains northern of Naples, and the soil cover, constituted by layers of loose volcanic ashes and pumices with a total thickness of 2.5m, lays upon a fractured limestone bedrock. At the interface between the bedrock and the soil cover, a layer of weathered ashes, with significant clay fraction, is sometimes observed. The slope has a fairly regular inclination of 40°, and is covered by chestnut woods and thick brushwood growing in late spring. The inclination of the slope is comparable with the internal friction angle of the ashes, thus the equilibrium is possible thanks to the contribution offered to the shear strength by the soil suction in unsaturated conditions. Indeed, in December 1999, a landslide was triggered by prolonged and intense precipitations. As it frequently happens with similar pyroclastic covers, the triggered slide exhibited a flow-like behavior, covering 2km in few minutes, heavily hitting the nearby town of Cervinara (AV). Since then, the slope has been constantly monitored, and during the last two years an automated station with seven TDR probes for the measurement of soil water content, eight tensiometers for the measurement of soil suction, and a rain gauge, has been operating. The data, collected every two hours, allowed getting more insight of the hydrological behavior of the slope and building up an effective hydrological model. In the model, the layered soil profile has been replaced with a single homogeneous layer, with water retention curve estimated by coupling the values of water content and suction measured at various depths. A seasonal top boundary condition has been introduced, related to the annual cycle of the vegetation: the observed precipitations quickly caused changes of soil suction at the depth of -50cm during the entire year, with the exception of the period between the end of May

  2. A Hypothesis-based Approach to Hydrological Model Development: The Case for Flexible Model Structures

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    Ambiguities in the appropriate representation of environmental processes have manifested themselves in a plethora of hydrological models, differing in almost every aspect of their conceptualization and implementation. This current overabundance of models is symptomatic of insufficient scientific understanding of environmental dynamics at the catchment scale, which can be attributed to difficulties in quantifying the impact of sub-catchment heterogeneities on the catchment’s hydrological response. In this presentation we advocate the use of flexible modeling frameworks during the development and subsequent refinement of catchment-scale hydrological models. We argue that the ability of flexible modeling frameworks to decompose a model into its constituent hypotheses, necessarily combined with incisive diagnostics to scrutinize these individual hypotheses against observed data, provides hydrologists with a very powerful and systematic approach for improving process representation in models. Flexible models also support a broader coverage of the model hypothesis space and hence facilitate a more comprehensive quantification of the predictive uncertainty associated with system and component non-identifiabilities that plague many model analyses. As part of our discussion of the advantages and limitations of flexible model frameworks, we critically review major contemporary challenges in hydrological hypothesis-testing, including exploiting data to investigate the fidelity of alternative process representations, accounting for model structure ambiguities arising from uncertainty in environmental data, and the challenge of understanding regional differences in dominant hydrological processes. We assess recent progress in these research directions, and how such progress can be exploited within flexible model applications to advance the community’s quest for more scientifically defensible catchment-scale hydrological models.

  3. Modeling Climate Change Impacts on Landscape Evolution, Fire, and Hydrology

    NASA Astrophysics Data System (ADS)

    Sheppard, B. S.; O Connor, C.; Falk, D. A.; Garfin, G. M.

    2015-12-01

    Landscape disturbances such as wildfire interact with climate variability to influence hydrologic regimes. We coupled landscape, fire, and hydrologic models and forced them using projected climate to demonstrate climate change impacts anticipated at Fort Huachuca in southeastern Arizona, USA. The US Department of Defense (DoD) recognizes climate change as a trend that has implications for military installations, national security and global instability. The goal of this DoD Strategic Environmental Research and Development Program (SERDP) project (RC-2232) is to provide decision making tools for military installations in the southwestern US to help them adapt to the operational realities associated with climate change. For this study we coupled the spatially explicit fire and vegetation dynamics model FireBGCv2 with the Automated Geospatial Watershed Assessment tool (AGWA) to evaluate landscape vegetation change, fire disturbance, and surface runoff in response to projected climate forcing. A projected climate stream for the years 2005-2055 was developed from the Multivariate Adaptive Constructed Analogs (MACA) 4 km statistical downscaling of the CanESM2 GCM using Representative Concentration Pathway (RCP) 8.5. AGWA, an ArcGIS add-in tool, was used to automate the parameterization and execution of the Soil Water Assessment Tool (SWAT) and the KINematic runoff and EROSion2 (KINEROS2) models based on GIS layers. Landscape raster data generated by FireBGCv2 project an increase in fire and drought associated tree mortality and a decrease in vegetative basal area over the years of simulation. Preliminary results from SWAT modeling efforts show an increase to surface runoff during years following a fire, and for future winter rainy seasons. Initial results from KINEROS2 model runs show that peak runoff rates are expected to increase 10-100 fold as a result of intense rainfall falling on burned areas.

  4. Reduction of uncertainty of hydrological modelling using different precipitation inputs

    NASA Astrophysics Data System (ADS)

    Pluntke, T.; Pavlik, D.; Bernhofer, C.

    2012-04-01

    Precipitation is one of the main sources of uncertainty in hydrological modelling, due to its high temporal and spatial variability. A dense network of rain gauge stations or a combination with, e.g., radar data is needed to account for the - in comparison to other climatic elements - pronounced variability. The density of existing station-networks is low in many countries worldwide. Alternative approaches that use additional information should be applied to improve the estimation of areal precipitation. Within the project "International Research Alliance Saxony" (http://www.iwas-sachsen.ufz.de/), one subproject aims at a system analysis of a meso-scale catchment of the Western Bug in Ukraine. Effective and sustainable measures have to be identified to improve the water quality of the Western Bug under the premise of upcoming changes of climate, land use and socio economy. An exact quantification of the water balance is needed as a pre-requisite for a matter balance. This contribution demonstrates possibilities to reduce the uncertainties of water balance modelling of the catchment Kamianka-Buzka/ Western Bug (2560 km2) by applying and combining alternative precipitation inputs. Available precipitation data were undergone an extensive quality check and were bias corrected. The Soil and Water Assessment Tool (SWAT, http://swatmodel.tamu.edu/) was used for water balance modelling. By default, meteorological observations are incorporated into SWAT using the station that is nearest to the centroid of each sub-catchment. Two alternative precipitation inputs were applied: 1) Data of 20 stations were regionalized using kriging methods. 2) The output of the Regional Climate Model CCLM that was set up for the region was used. After a pre-calibration of the model, three models - having different precipitation inputs - were set up and calibrated independently applying the auto-calibration procedure Sequential Uncertainty Fitting (Abbaspour et al. 2004). The performance of the

  5. Testing calibration routines for LISFLOOD, a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Pannemans, B.

    2009-04-01

    Traditionally hydrological models are considered as difficult to calibrate: their highly non-linearity results in rugged and rough response surfaces were calibration algorithms easily get stuck in local minima. For the calibration of distributed hydrological models two extra factors play an important role: on the one hand they are often costly on computation, thus restricting the feasible number of model runs; on the other hand their distributed nature smooths the response surface, thus facilitating the search for a global minimum. Lisflood is a distributed hydrological model currently used for the European Flood Alert System - EFAS (Van der Knijff et al, 2008). Its upcoming recalibration over more then 200 catchments, each with an average runtime of 2-3 minutes, proved a perfect occasion to put several existing calibration algorithms to the test. The tested routines are Downhill Simplex (DHS, Nelder and Mead, 1965), SCEUA (Duan et Al. 1993), SCEM (Vrugt et al., 2003) and AMALGAM (Vrugt et al., 2008), and they were evaluated on their capability to efficiently converge onto the global minimum and on the spread in the found solutions in repeated runs. The routines were let loose on a simple hyperbolic function, on a Lisflood catchment using model output as observation, and on two Lisflood catchments using real observations (one on the river Inn in the Alps, the other along the downstream stretch of the Elbe). On the mathematical problem and on the catchment with synthetic observations DHS proved to be the fastest and the most efficient in finding a solution. SCEUA and AMALGAM are a slower, but while SCEUA keeps converging on the exact solution, AMALGAM slows down after about 600 runs. For the Lisflood models with real-time observations AMALGAM (hybrid algorithm that combines several other algorithms, we used CMA, PSO and GA) came as fastest out of the tests, and giving comparable results in consecutive runs. However, some more work is needed to tweak the stopping

  6. Building Community Around Hydrologic Data Models Within CUAHSI

    NASA Astrophysics Data System (ADS)

    Maidment, D.

    2007-12-01

    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.

  7. Ecological Acclimation and Hydrologic Response: Problem Complexity and Modeling Challenges

    NASA Astrophysics Data System (ADS)

    Kumar, P.; Srinivasan, V.; Le, P. V. V.; Drewry, D.

    2012-04-01

    Elevated CO2 in the atmosphere leads to a number of acclimatory responses in different vegetation types. These may be characterized as structural such as vegetation height or foliage density, ecophysiological such as reduction in stomatal conductance, and biochemical such as photosynthetic down-regulation. Furthermore, the allocation of assimilated carbon to different vegetation parts such as leaves, roots, stem and seeds is also altered such that empirical allometric relations are no longer valid. The extent and nature of these acclimatory responses vary between C3 and C4 vegetation and across species. These acclimatory responses have significant impact on hydrologic fluxes both pertaining to water and energy with the possibility of large-scale hydrologic influence. Capturing the pathways of acclimatory response to provide accurate ecohydrologic response predictions requires incorporating subtle relationships that are accentuated under elevated CO2. The talk will discuss the challenges of modeling these as well as applications to soybean, maize and bioenergy crops such as switchgrass and miscanthus.

  8. Calibration by Hydrological Response Unit of a National Hydrologic Model to Improve Spatial Representation and Distribution of Parameters

    NASA Astrophysics Data System (ADS)

    Norton, P. A., II

    2015-12-01

    The U. S. Geological Survey is developing a National Hydrologic Model (NHM) to support consistent hydrologic modeling across the conterminous United States (CONUS). The Precipitation-Runoff Modeling System (PRMS) simulates daily hydrologic and energy processes in watersheds, and is used for the NHM application. For PRMS each watershed is divided into hydrologic response units (HRUs); by default each HRU is assumed to have a uniform hydrologic response. The Geospatial Fabric (GF) is a database containing initial parameter values for input to PRMS and was created for the NHM. The parameter values in the GF were derived from datasets that characterize the physical features of the entire CONUS. The NHM application is composed of more than 100,000 HRUs from the GF. Selected parameter values commonly are adjusted by basin in PRMS using an automated calibration process based on calibration targets, such as streamflow. Providing each HRU with distinct values that captures variability within the CONUS may improve simulation performance of the NHM. During calibration of the NHM by HRU, selected parameter values are adjusted for PRMS based on calibration targets, such as streamflow, snow water equivalent (SWE) and actual evapotranspiration (AET). Simulated SWE, AET, and runoff were compared to value ranges derived from multiple sources (e.g. the Snow Data Assimilation System, the Moderate Resolution Imaging Spectroradiometer (i.e. MODIS) Global Evapotranspiration Project, the Simplified Surface Energy Balance model, and the Monthly Water Balance Model). This provides each HRU with a distinct set of parameter values that captures the variability within the CONUS, leading to improved model performance. We present simulation results from the NHM after preliminary calibration, including the results of basin-level calibration for the NHM using: 1) default initial GF parameter values, and 2) parameter values calibrated by HRU.

  9. Diagnosing non-stationary behaviour in a hydrological model

    NASA Astrophysics Data System (ADS)

    Thyer, Mark; Westra, Seth; Leonard, Michael; Kavetski, Dmitri; Lambert, Martin

    2013-04-01

    The stationarity of hydrological models is increasingly being called into question, due partly to changes in land cover as well as natural and anthropogenic climate change. This issue is manifest in model parameters which change over time, creating challenges in calibration and validation (as the joint distribution of model parameters is conditional to the period used for model calibration), and in prediction when one wishes to investigate runoff properties in the future. This paper describes the incorporation of non-stationary parameters into a well established rainfall-runoff model - GR4J - using a Bayesian framework for calibration and prediction, and the use of an information theoretic approach to evaluate whether the inclusion of non-stationary parameters was justified. A subcatchment of the Onkaparinga river in South Australia was used as a case study, and it was found that GR4J parameter 'x1' varied significantly seasonally and also exhibited a longer-term increasing trend over the calibration period from 1974 to 1999. The inclusion of this non-stationary parameter in the model reduced the over-prediction in the drier validation period from 2000 to 2010 from 25% to 1.5%. Whilst including non-stationarity parameters provided substantial improvements in prediction, it is advocated that this non-stationary parameters be used as a diagnostic tool to identify model deficiencies, rather than for prediction. Techniques to reduce the non-stationarity by enhancing the model structure will to include one or more missing processes will be discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

  11. GIS embedded hydrological modeling: the SID&GRID project

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    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

  12. Spatial calibration and temporal validation of flow for regional scale hydrologic modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validat...

  13. Implications of the choice and configuration of hydrologic models on the portrayal of climate change impact

    NASA Astrophysics Data System (ADS)

    Mendoza, P. A.; Clark, M. P.; Rajagopalan, B.; Mizukami, N.; Gutmann, E. D.

    2013-12-01

    Climate change studies involve several methodological choices that impact the hydrological sensitivities obtained. Among these, hydrologic model structure selection and parameter identification are particularly relevant and usually have a strong subjective component. This subjectivity is not only limited to engineering applications, but also extends to many of our research studies, resulting in problems such as missing processes in our models, inappropriate parameterizations and compensatory effects of model parameters. The goal of this research is to identify the role of model structures and parameter values on the assessment of hydrologic sensitivity to climate change. We conduct our study in three basins located in the Colorado Headwaters Region, using four different hydrologic models (PRMS, VIC, Noah and Noah-MP). We first compare both model performance and climate sensitivities using default parameterizations and parameter values calibrated with the Shuffled Complex Evolution algorithm. Our results demonstrate that calibration doesn't necessarily improve the representation of hydrological processes or decrease inter-model differences in the change of signature measures of hydrologic behavior with respect to a future climate scenario. We found that inter-model differences in hydrologic sensitivities to climate change may be larger than the climate change signal even after models have been calibrated. Results demonstrate that both model choice (after calibration) and parameter selection have important effects in the portrayal of climate change impacts, and work is ongoing to identify more robust modeling strategies that explicitly account for the subjectivity in these choices. Location of the basins of interest Hydrological models used in this study

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

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

    A hydrologic planning model is developed based on remotely sensed inputs. Data from LANDSAT 1 are used to supply the model's quantitative parameters and coefficients. The use of LANDSAT data as information input to all categories of hydrologic models requiring quantitative surface parameters for their effects functioning is also investigated.

  15. Chimeric hepatitis B virus (HBV)/hepatitis C virus (HCV) subviral envelope particles induce efficient anti-HCV antibody production in animals pre-immunized with HBV vaccine.

    PubMed

    Beaumont, Elodie; Roingeard, Philippe

    2015-02-18

    The development of an effective, affordable prophylactic vaccine against hepatitis C virus (HCV) remains a medical priority. The recently described chimeric HBV-HCV subviral envelope particles could potentially be used for this purpose, as they could be produced by industrial procedures adapted from those established for the hepatitis B virus (HBV) vaccine. We show here, in an animal model, that pre-existing immunity acquired through HBV vaccination does not influence the immunogenicity of the HCV E2 protein presented by these chimeric particles. Thus, these chimeric HBV-HCV subviral envelope particles could potentially be used as a booster in individuals previously vaccinated against HBV, to induce protective immunity to HCV. PMID:25596457

  16. Hydrological excitation of polar motion by different variables of the GLDAS models

    NASA Astrophysics Data System (ADS)

    Wińska, Małgorzata; Nastula, Jolanta

    Continental hydrological loading, by land water, snow, and ice, is an element that is strongly needed for a full understanding of the excitation of polar motion. In this study we compute different estimations of hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of land hydrosphere. The main aim of this study is to show the influence of different variables for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in annual and short term scale. In our consideration we employ several realizations of the GLDAS model as: GLDAS Common Land Model (CLM), GLDAS Mosaic Model, GLDAS National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab Model (Noah), GLDAS Variable Infiltration Capacity (VIC) Model. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare a timing, spectra and phase diagrams of different regional and global HAMs with each other. Next, we estimate, the hydrological signal in geodetically observed polar motion excitation by subtracting the atmospheric -- AAM (pressure + wind) and oceanic -- OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal in observed polar motion excitation series. The results help us understand which variables of considered hydrological models are the most important for the polar motion excitation and how well we can close polar motion excitation budget in the seasonal and inter-annual spectral ranges.

  17. Holistic versus monomeric strategies for hydrological modelling of modified hydrosystems

    NASA Astrophysics Data System (ADS)

    Nalbantis, I.; Efstratiadis, A.; Rozos, E.; Kopsiafti, M.; Koutsoyiannis, D.

    2010-10-01

    The modelling of modified basins that are inadequately measured constitutes a challenge for hydrological science. Often, models for such systems are detailed and hydraulics-based for only one part of the system while for other parts oversimplified models or rough assumptions are used. This is typically a bottom-up approach, which seeks to exploit knowledge of hydrological processes at the micro-scale at some components of the system. Also, it is a monomeric approach in two ways: first, essential interactions among system components may be poorly represented or even omitted; second, differences in the level of detail of process representation can lead to uncontrolled errors. Additionally, the calibration procedure merely accounts for the reproduction of the observed responses using typical fitting criteria. The paper aims to raise some critical issues, regarding the entire modelling approach for such hydrosystems. For this, two alternative modelling strategies are examined that reflect two modelling approaches or philosophies: a dominant bottom-up approach, which is also monomeric and very often, based on output information and a top-down and holistic approach based on generalized information. Critical options are examined, which codify the differences between the two strategies: the representation of surface, groundwater and water management processes, the schematization and parameterization concepts and the parameter estimation methodology. The first strategy is based on stand-alone models for surface and groundwater processes and for water management, which are employed sequentially. For each model, a different (detailed or coarse) parameterization is used, which is dictated by the hydrosystem schematization. The second strategy involves model integration for all processes, parsimonious parameterization and hybrid manual-automatic parameter optimization based on multiple objectives. A test case is examined in a hydrosystem in Greece with high complexities, such

  18. Bayesian analysis of input uncertainty in hydrological modeling: 2. Application

    NASA Astrophysics Data System (ADS)

    Kavetski, Dmitri; Kuczera, George; Franks, Stewart W.

    2006-03-01

    The Bayesian total error analysis (BATEA) methodology directly addresses both input and output errors in hydrological modeling, requiring the modeler to make explicit, rather than implicit, assumptions about the likely extent of data uncertainty. This study considers a BATEA assessment of two North American catchments: (1) French Broad River and (2) Potomac basins. It assesses the performance of the conceptual Variable Infiltration Capacity (VIC) model with and without accounting for input (precipitation) uncertainty. The results show the considerable effects of precipitation errors on the predicted hydrographs (especially the prediction limits) and on the calibrated parameters. In addition, the performance of BATEA in the presence of severe model errors is analyzed. While BATEA allows a very direct treatment of input uncertainty and yields some limited insight into model errors, it requires the specification of valid error models, which are currently poorly understood and require further work. Moreover, it leads to computationally challenging highly dimensional problems. For some types of models, including the VIC implemented using robust numerical methods, the computational cost of BATEA can be reduced using Newton-type methods.

  19. Multiobjective sensitivity analysis and optimization of distributed hydrologic model MOBIDIC

    NASA Astrophysics Data System (ADS)

    Yang, J.; Castelli, F.; Chen, Y.

    2014-10-01

    Calibration of distributed hydrologic models usually involves how to deal with the large number of distributed parameters and optimization problems with multiple but often conflicting objectives that arise in a natural fashion. This study presents a multiobjective sensitivity and optimization approach to handle these problems for the MOBIDIC (MOdello di Bilancio Idrologico DIstribuito e Continuo) distributed hydrologic model, which combines two sensitivity analysis techniques (the Morris method and the state-dependent parameter (SDP) method) with multiobjective optimization (MOO) approach ɛ-NSGAII (Non-dominated Sorting Genetic Algorithm-II). This approach was implemented to calibrate MOBIDIC with its application to the Davidson watershed, North Carolina, with three objective functions, i.e., the standardized root mean square error (SRMSE) of logarithmic transformed discharge, the water balance index, and the mean absolute error of the logarithmic transformed flow duration curve, and its results were compared with those of a single objective optimization (SOO) with the traditional Nelder-Mead simplex algorithm used in MOBIDIC by taking the objective function as the Euclidean norm of these three objectives. Results show that (1) the two sensitivity analysis techniques are effective and efficient for determining the sensitive processes and insensitive parameters: surface runoff and evaporation are very sensitive processes to all three objective functions, while groundwater recession and soil hydraulic conductivity are not sensitive and were excluded in the optimization. (2) Both MOO and SOO lead to acceptable simulations; e.g., for MOO, the average Nash-Sutcliffe value is 0.75 in the calibration period and 0.70 in the validation period. (3) Evaporation and surface runoff show similar importance for watershed water balance, while the contribution of baseflow can be ignored. (4) Compared to SOO, which was dependent on the initial starting location, MOO provides more

  20. Limits and failures in hydrology: examples and lessons learned from three decades of process oriented hydrological modelling

    NASA Astrophysics Data System (ADS)

    Bronstert, Axel

    2016-04-01

    In hydrological sciences there have been rather many attempts to develop new mathematical analysis and modelling tools. Some (or even many?) of them failed or were at least only partially successful. Unfortunately, such nun-successful attempts are hardly reported on, because our common academic recognition is based on reports about success only. With all due respect to successful attempts, the scientific community could benefit a lot from reports of unsuccessful attempts or unexpected results. Therefore, in this contribution, the author presents examples of modelling failures from his own experiences during the last three decades. Emphasis is given on results obtained from process-oriented hydrological models, where the "right answer" was obtained "for the wrong reasons". Such example comprise, for instance, modelling infiltration experiments at the plot scale, modelling runoff generation from hillslope scale and in experimental catchments and modelling runoff from glaciated catchments It is explained how the "wrong reasons" could be identified and what was learned from such failures. It is argued that failures, which causes can be identified by the modeller or anybody else, could significantly contribute to a progress in hydrological system understanding or - at least - to the identification of research needs. Identification of causes of failure may even contribute more to scientific progress then brute force modelling of parameter sensitivity and uncertainty.

  1. Hydrologic predictions on ungauged catchments using deterministic distributed modelling system

    NASA Astrophysics Data System (ADS)

    Tachecí, Pavel; Kimlová, Martina

    2010-05-01

    There is a need for warning system giving prediction of flash-flood risk conditions with sufficient advance even in source areas and in small tributaries catchments. New approach is based on combination of numerical weather prediction (NWP) model, radar or rain gauge data with distributed hydrologic mathematical model of particular area. Set of newly developed tools, customized for particular use in the Czech Hydrometeorological Institute (CHMI) environment enhance import of data and presentation of results. This forecast system focuses on hydrological modelling of running water balance in spatially distributed manner. Its computation is repeated day-to-day. Six models of particular basins (800 - 4000 km2), representing different conditions across the Czech Republic territory were calibrated and validated successfully. The Sázava river basin model (4.000 km2) is used for regular testing operation in CHMI Forecast centre since October 2007. Basic size of grid cells used in models is 300x300 m, basic time step of forecast is 1 day, but can be refined according to the input data. Water balance is computed using simplified 2-layer method for unsaturated zone, 2D approximation of Boussinesq equation for saturated zone, diffusion equation for overland flow and 1D kinematic equation for river flow (MIKE 11 model). The whole process of input data processing, model simulation and result generation may be run automatically or in step-by step mode via simple graphical user interface. Three types of input data are supported: •time series (temperature and precipitation) measured at observation stations and stored in CHMI database •radar data products (precipitation intensity field) •results of ALADIN weather forecast model (temperature and precipitation field). For forecast purposes, reference evapotranspiration is approximated according relationship to air temperature for every computational grid cell. The user may choose area (catchment) to be processed and period of

  2. 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)

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

    2002-12-01

    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

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

    NASA Astrophysics Data System (ADS)

    Peckham, S. D.

    2012-12-01

    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

  4. An eco-hydrologic model of malaria outbreaks

    NASA Astrophysics Data System (ADS)

    Montosi, E.; Manzoni, S.; Porporato, A.; Montanari, A.

    2012-03-01

    Malaria is a geographically widespread infectious disease that is well known to be affected by climate variability at both seasonal and interannual timescales. In an effort to identify climatic factors that impact malaria dynamics, there has been considerable research focused on the development of appropriate disease models for malaria transmission and their consideration alongside climatic datasets. These analyses have focused largely on variation in temperature and rainfall as direct climatic drivers of malaria dynamics. Here, we further these efforts by considering additionally the role that soil water content may play in driving malaria incidence. Specifically, we hypothesize that hydro-climatic variability should be an important factor in controlling the availability of mosquito habitats, thereby governing mosquito growth rates. To test this hypothesis, we reduce a nonlinear eco-hydrologic model to a simple linear model through a series of consecutive assumptions and apply this model to malaria incidence data from three South African provinces. Despite the assumptions made in the reduction of the model, we show that soil water content can account for a significant portion of malaria's case variability beyond its seasonal patterns, whereas neither temperature nor rainfall alone can do so. Future work should therefore consider soil water content as a simple and computable variable for incorporation into climate-driven disease models of malaria and other vector-borne infectious diseases.

  5. A coupled energy transport and hydrological model for urban canopies

    NASA Astrophysics Data System (ADS)

    Wang, Z.; Bou-Zeid, E.; Smith, J. A.

    2011-12-01

    Urban land-atmosphere interaction has been attracting more research efforts in order to understand the complex physics of flow and mass and heat transport in urban surfaces and the lower urban atmosphere. In this work, we developed and implemented a new physically-based single-layer urban canopy model, coupling the surface exchange of energy and the subsurface transport of water/soil moisture. The new model incorporates sub-facet heterogeneity for each urban surface (roof, wall or ground). This better simulates the energy transport in urban canopy layers, especially over low-intensity built (suburban type) terrains that include a significant fraction of vegetated surfaces. We implemented detailed urban hydrological models for both natural terrains (bare soil and vegetation) and porous engineered materials with water-holding capacity (concrete, gravel, etc). The skill of the new scheme was tested against experimental data collected through a wireless sensor network deployed over the campus of Princeton University. The model performance was found to be robust and insensitive to changes in weather conditions or seasonal variability. Predictions of the volumetric soil water content were also in good agreement with field measurements, highlighting the model capability of capturing subsurface water transport for urban lawns. The new model was also applied to a case study assessing different strategies, i.e. white versus green roofs, in the mitigation of urban heat island effect.

  6. MODIS-derived Potential Evapotranspiration Estimates for Operational Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Kim, J.; Hogue, T.

    2005-12-01

    The current SACramento Soil Moisture Accounting Model (SAC-SMA), used by the National Weather Service, is the primarily model for hydrologic forecasting across the United States. Potential evapotranspiration (PET), one of the required inputs, remains rather simplistic. The model traditionally uses a regional pan evaporation estimate due to the difficulty in acquiring more sophisticated measurements. This study explores an alternative methodology using only remote sensing information to capture the monthly mean distribution of potential evapotranspiration (PET) for the SAC-SMA model. We apply a simple scheme proposed by Jiang and Islam (2005) to estimate the net radiation and estimate PET within the context of the Priestley-Taylor equation using data gathered from the MODIS Terra platform. PET estimates from the MODIS data are compared with those derived from Oklahoma Mesonet ground-based measurements and traditional pan evaporation estimates. Preliminary results will be presented for the Illinois River basin at Watts (OK) identified as part of the National Weather Service's Distributed Modeling Intercomparison Project (DMIP). The resultant streamflow simulations will illustrate the sensitivity of the SAC-SMA model to potential evaporation inputs from different sources and the possibility of the application of a stand-alone PET method for un-gauged basins.

  7. Dissection of trained neural network hydrologic models for knowledge extraction

    NASA Astrophysics Data System (ADS)

    Jain, Ashu; Kumar, Sumant

    2009-07-01

    Artificial neural networks (ANNs) are powerful tools for the modeling and forecasting of complex engineering systems and have been exploited by researchers to solve a variety of problems over the last couple of decades. In spite of their proven ability to provide superior model performance compared to traditional modeling approaches, they have not become popular among decision makers for operational use. It is probably because of their perceived black box nature that does not explain or consider the underlying physical processes involved. This paper presents the results of a study aimed at a systematic dissection of the massively parallel architectures of trained ANN hydrologic models to determine if they learn the underlying physical subprocesses during training. This has been achieved using simple qualitative and quantitative techniques. The data derived from three contrasting catchments at two different time scales were employed to develop ANN models and test the methodologies employed for knowledge extraction. The results obtained in this study indicate that the number of hidden neurons determined during training for a particular data set correspond to certain subprocesses of the overall physical process being modeled. It has been found that the time scale of the data employed has an effect on optimum ANN architecture and knowledge extracted.

  8. Hydrologic modeling of two glaciated watersheds in Northeast Pennsylvania

    USGS Publications Warehouse

    Srinivasan, M.S.; Hamlett, J.M.; Day, R.L.; Sams, J.I.; Petersen, G.W.

    1998-01-01

    A hydrologic modeling study, using the Hydrologic Simulation Program - FORTRAN (HSPF), was conducted in two glaciated watersheds, Purdy Creek and Ariel Creek in northeastern Pennsylvania. Both watersheds have wetlands and poorly drained soils due to low hydraulic conductivity and presence of fragipans. The HSPF model was calibrated in the Purdy Creek watershed and verified in the Ariel Creek watershed for June 1992 to December 1993 period. In Purdy Creek, the total volume of observed streamflow during the entire simulation period was 13.36 x 106 m3 and the simulated streamflow volume was 13.82 x 106 m3 (5 percent difference). For the verification simulation in Ariel Creek, the difference between the total observed and simulated flow volumes was 17 percent. Simulated peak flow discharges were within two hours of the observed for 30 of 46 peak flow events (discharge greater than 0.1 m3/sec) in Purdy Creek and 27 of 53 events in Ariel Creek. For 22 of the 46 events in Purdy Creek and 24 of 53 in Ariel Creek, the differences between the observed and simulated peak discharge rates were less than 30 percent. These 22 events accounted for 63 percent of total volume of streamflow observed during the selected 46 peak flow events in Purdy Creek. In Ariel Creek, these 24 peak flow events accounted for 62 percent of the total flow observed during all peak flow events. Differences in observed and simulated peak flow rates and volumes (on a percent basis) were greater during the snowmelt runoff events and summer periods than for other times.A hydrologic modeling study, using the Hydrologic Simulation Program - FORTRAN (HSPF), was conducted in two glaciated watersheds, Purdy Creek and Ariel Creek in northeastern Pennsylvania. Both watersheds have wetlands and poorly drained soils due to low hydraulic conductivity and presence of fragipans. The HSPF model was calibrated in the Purdy Creek watershed and verified in the Ariel Creek watershed for June 1992 to December 1993 period. In

  9. Test of Landsat-based urban hydrologic modeling

    NASA Technical Reports Server (NTRS)

    Jackson, T. J.; Ragan, R. M.; Fitch, W. N.

    1977-01-01

    A description is presented of the Fourmile Run Study which has been conducted to evaluate Landsat remote sensing as a method of defining input parameters required by urban hydrologic planning models. The evaluation was a part of water resource planning investigations concerning the Fourmile Run Watershed. The investigations involved an examination of the relationship between urban development and flooding for the Fourmile Run Basin. The study indicates that Landsat data provide a suitable source of land cover data for investigations conducted at the planning level. An estimation of the percentage of impervious area on the basis of Landsat data is less expensive than a use of aerial photos in planning studies. Only limited success could be achieved when Landsat data were used for smaller areal units.

  10. Integrating an open source dynamic river model in hydrology modeling frameworks

    NASA Astrophysics Data System (ADS)

    Liu, Frank; Hodges, Ben

    2014-05-01

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

    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.

  12. Hydrological excitation of polar motion by different variables from the GLDAS model

    NASA Astrophysics Data System (ADS)

    Wińska, Małgorzata; Nastula, Jolanta; Salstein, David

    2015-04-01

    Continental hydrological loading, by land water, snow, and ice, is an element that is strongly needed for a full understanding of the excitation of polar motion. In this study we compute different estimations of hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM) using various variables from the Global Land Data Assimilation System (GLDAS) model of the land-based hydrosphere. The main aim of this study is to show the influence of variables from different hydrological processes, including for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in seasonal timescale. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare the timing, spectra and phase diagrams of different regional and global HAMs with each other. Next, we estimate, the hydrological signal in geodetically-observed polar motion excitation as a residual by subtracting the atmospheric - AAM (pressure + wind) and oceanic - OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal from the observed polar motion excitation series residuals. The results help us understand the relative importance for polar motion excitation of the individual variables from different hydrological processes, based on hydrological modeling. This method can allows us to estimate how well the polar motion excitation budget in the seasonal spectral ranges can be closed.

  13. Urban Hydrology and Water Quality Modeling - Resolution Modeling Comparison for Water Quantity and Quality

    NASA Astrophysics Data System (ADS)

    Fry, T. J.; Maxwell, R. M.

    2014-12-01

    Urbanization presents challenging water resource problems for communities worldwide. The hydromodifications associated with urbanization results in increased runoff rates and volumes and increased peak flows. These hydrologic changes can lead to increased erosion and stream destabilization, decreased evapotranspiration, decreased ground water recharge, increases in pollutant loading, and localized anthropogenic climate change or Urban Heat Islands. Stormwater represents a complex and dynamic component of the urban water cycle that requires careful mitigation. With the implementation of Phase II rules under the CWA, stormwater management is shifting from a drainage-efficiency focus to a natural systems focus. The natural system focus, referred to as Low Impact Development (LID), or Green Infrastructure, uses best management practices (BMPs) to reduce the impacts caused by urbanization hydromodification. Large-scale patterns of stormwater runoff from urban environments are complex and it is unclear what the large-scale impacts of green infrastructure are on the water cycle. High resolution physically based hydrologic models can be used to more accurately simulate the urban hydrologic cycle. These types of models tend to be more dynamic and allow for greater flexibility in evaluating and accounting for various hydrologic processes in the urban environment that may be lost with lower resolution conceptual models. We propose to evaluate the effectiveness of high resolution models to accurately represent and determine the urban hydrologic cycle with the overall goal of being able to accurately assess the impacts of LID BMPs in urban environments. We propose to complete a rigorous model intercomparison between ParFlow and FLO-2D. Both of these models can be scaled to higher resolutions, allow for rainfall to be spatially and temporally input, and solve the shallow water equations. Each model is different in the way it accounts for infiltration, initial abstraction losses

  14. Operational hydrological ensemble forecasts in France. Recent development of the French Hydropower Company (EDF), taking into account rainfall and hydrological model uncertainties.

    NASA Astrophysics Data System (ADS)

    Mathevet, T.; Garavaglia, F.; Garçon, R.; Gailhard, J.; Paquet, E.

    2009-04-01

    In operational conditions, the actual quality of meteorological and hydrological forecasts do not allow decision-making in a certain future. In this context, meteorological and hydrological ensemble forecasts allow a better representation of forecasts uncertainties. Compared to classical deterministic forecasts, ensemble forecasts improve the human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. In this paper, we present a hydrological ensemble forecasting system under development at EDF (French Hydropower Company). This forecasting system both takes into account rainfall forecasts uncertainties and hydrological model forecasts uncertainties. Hydrological forecasts were generated using the MORDOR model (Andreassian et al., 2006), developed at EDF and used on a daily basis in operational conditions on a hundred of watersheds. Two sources of rainfall forecasts were used : one is based on ECMWF forecasts, another is based on an analogues approach (Obled et al., 2002). Two methods of hydrological model forecasts uncertainty estimation were used : one is based on the use of equifinal parameter sets (Beven & Binley, 1992), the other is based on the statistical modelisation of the hydrological forecast empirical uncertainty (Montanari et al., 2004 ; Schaefli et al., 2007). Daily operational hydrological 7-day ensemble forecasts during 2 years in 3 alpine watersheds were evaluated. Finally, we present a way to combine rainfall and hydrological model forecast uncertainties to achieve a good probabilistic calibration. Our results show that the combination of ECMWF and analogues-based rainfall forecasts allow a good probabilistic calibration of rainfall forecasts. They show also that the statistical modeling of the hydrological forecast empirical uncertainty has a better probabilistic calibration, than the equifinal parameter set approach

  15. Hydrological Land Classification Based on Landscape Units

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    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.

  16. HYDROLOGIC MODEL UNCERTAINTY ASSOCIATED WITH SIMULATING FUTURE LAND-COVER/USE SCENARIOS: A RETROSPECTIVE ANALYSIS

    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...

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

    ERIC Educational Resources Information Center

    Burt, Tim; Butcher, Dave

    1986-01-01

    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)

  18. HYDROLOGIC EVALUATION OF LANDFILL PERFORMANCE (HELP) MODEL: USER'S GUIDE FOR VERSION 3

    EPA Science Inventory

    The Hydrologic Evaluation of Landfill Performance (HELP) computer program is a quasi-two-dimensional hydrologic model of water movement across, into, through and out of landfills. he model accepts weather, soil and design data. andfill systems including various combinations of ve...

  19. A unified approach for process-based hydrologic modeling: 1. Modeling concept

    NASA Astrophysics Data System (ADS)

    Clark, Martyn P.; Nijssen, Bart; Lundquist, Jessica D.; Kavetski, Dmitri; Rupp, David E.; Woods, Ross A.; Freer, Jim E.; Gutmann, Ethan D.; Wood, Andrew W.; Brekke, Levi D.; Arnold, Jeffrey R.; Gochis, David J.; Rasmussen, Roy M.

    2015-04-01

    This work advances a unified approach to process-based hydrologic modeling to enable controlled and systematic evaluation of multiple model representations (hypotheses) of hydrologic processes and scaling behavior. Our approach, which we term the Structure for Unifying Multiple Modeling Alternatives (SUMMA), formulates a general set of conservation equations, providing the flexibility to experiment with different spatial representations, different flux parameterizations, different model parameter values, and different time stepping schemes. In this paper, we introduce the general approach used in SUMMA, detailing the spatial organization and model simplifications, and how different representations of multiple physical processes can be combined within a single modeling framework. We discuss how SUMMA can be used to systematically pursue the method of multiple working hypotheses in hydrology. In particular, we discuss how SUMMA can help tackle major hydrologic modeling challenges, including defining the appropriate complexity of a model, selecting among competing flux parameterizations, representing spatial variability across a hierarchy of scales, identifying potential improvements in computational efficiency and numerical accuracy as part of the numerical solver, and improving understanding of the various sources of model uncertainty.

  20. An Integrated Model for Channel, Overland and Subsurface Hydrology (IMCOSH)

    NASA Astrophysics Data System (ADS)

    Qu, Y.; Duffy, C. J.

    2004-05-01

    Processes within the terrestrial hydrological cycle operate over a wide range of time scales, with interactions among them ranging from uncoupled to strongly coupled. The multiple scales involved make it necessary to couple processes in an efficient way. Given the fact that governing equations for various processes are usually either partial differential equation (PDE) or ordinary differential equation (ODE), a model strategy based on reduction of PDE's to ODE's, using a semi-discrete finite volume method (SD_FVM) over a triangular irregular network (TIN), is introduced in this paper. In other words, the system of integrated PDE describing some processes is first discretized spatially to form a local system of ODE representing each control volume. By combining with those ODE's describing other processes over the domain, an integrated ODE system is built and can be further solved by ODE solver. In this approach, spatial domain decomposition uses an unstructured grid (triangular irregular network, TIN, at this stage) with constraints, e.g. river network and critical terrain points, delineated from geographic information system (GIS) terrain analysis tools. The paper will also address the issues of multiple temporal and spatial scales of processes in complex hydrologic systems. This model is design to capture "dynamics" within multiple processes of various time scales without losing the big picture. For example, the problem of estimating dynamic recharge to groundwater and runoff in streams, or partitioning of water budgets in the channel, on the surface and within subsurface. By turning on or off particular processes or modifying constitutive relationship inside the kernel, this model can be extend to multiple spatial scales application. Preliminary results show this integrated model can capture the wide range of time scales associated with: 1) land-surface soil moisture and water table coupling, 2) gaining or losing stream channels from or to aquifers, and 3) soil

  1. 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}...

  2. Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall-runoff modelling

    NASA Astrophysics Data System (ADS)

    Zhang, Yongqiang; Vaze, Jai; Chiew, Francis H. S.; Teng, Jin; Li, Ming

    2014-09-01

    Understanding a catchment's behaviours in terms of its underlying hydrological signatures is a fundamental task in surface water hydrology. It can help in water resource management, catchment classification, and prediction of runoff time series. This study investigated three approaches for predicting six hydrological signatures in southeastern Australia. These approaches were (1) spatial interpolation with three weighting schemes, (2) index model that estimates hydrological signatures using catchment characteristics, and (3) classical rainfall-runoff modelling. The six hydrological signatures fell into two categories: (1) long-term aggregated signatures - annual runoff coefficient, mean of log-transformed daily runoff, and zero flow ratio, and (2) signatures obtained from daily flow metrics - concavity index, seasonality ratio of runoff, and standard deviation of log-transformed daily flow. A total of 228 unregulated catchments were selected, with half the catchments randomly selected as gauged (or donors) for model building and the rest considered as ungauged (or receivers) to evaluate performance of the three approaches. The results showed that for two long-term aggregated signatures - the log-transformed daily runoff and runoff coefficient, the index model and rainfall-runoff modelling performed similarly, and were better than the spatial interpolation methods. For the zero flow ratio, the index model was best and the rainfall-runoff modelling performed worst. The other three signatures, derived from daily flow metrics and considered to be salient flow characteristics, were best predicted by the spatial interpolation methods of inverse distance weighting (IDW) and kriging. Comparison of flow duration curves predicted by the three approaches showed that the IDW method was best. The results found here provide guidelines for choosing the most appropriate approach for predicting hydrological behaviours at large scales.

  3. Hydrological model calibration for enhancing global flood forecast skill

    NASA Astrophysics Data System (ADS)

    Hirpa, Feyera A.; Beck, Hylke E.; Salamon, Peter; Thielen-del Pozo, Jutta

    2016-04-01

    Early warning systems play a key role in flood risk reduction, and their effectiveness is directly linked to streamflow forecast skill. The skill of a streamflow forecast is affected by several factors; among them are (i) model errors due to incomplete representation of physical processes and inaccurate parameterization, (ii) uncertainty in the model initial conditions, and (iii) errors in the meteorological forcing. In macro scale (continental or global) modeling, it is a common practice to use a priori parameter estimates over large river basins or wider regions, resulting in suboptimal streamflow estimations. The aim of this work is to improve flood forecast skill of the Global Flood Awareness System (GloFAS; www.globalfloods.eu), a grid-based forecasting system that produces flood forecast unto 30 days lead, through calibration of the distributed hydrological model parameters. We use a combination of in-situ and satellite-based streamflow data for automatic calibration using a multi-objective genetic algorithm. We will present the calibrated global parameter maps and report the forecast skill improvements achieved. Furthermore, we discuss current challenges and future opportunities with regard to global-scale early flood warning systems.

  4. Soil hydrologic characterization for modeling large scale soil remediation protocols

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    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.

  5. 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...

  6. Upscaling from research watersheds: an essential stage of trustworthy general-purpose hydrologic model building

    NASA Astrophysics Data System (ADS)

    McNamara, J. P.; Semenova, O.; Restrepo, P. J.

    2011-12-01

    Highly instrumented research watersheds provide excellent opportunities for investigating hydrologic processes. A danger, however, is that the processes observed at a particular research watershed are too specific to the watershed and not representative even of the larger scale watershed that contains that particular research watershed. Thus, models developed based on those partial observations may not be suitable for general hydrologic use. Therefore demonstrating the upscaling of hydrologic process from research watersheds to larger watersheds is essential to validate concepts and test model structure. The Hydrograph model has been developed as a general-purpose process-based hydrologic distributed system. In its applications and further development we evaluate the scaling of model concepts and parameters in a wide range of hydrologic landscapes. All models, either lumped or distributed, are based on a discretization concept. It is common practice that watersheds are discretized into so called hydrologic units or hydrologic landscapes possessing assumed homogeneous hydrologic functioning. If a model structure is fixed, the difference in hydrologic functioning (difference in hydrologic landscapes) should be reflected by a specific set of model parameters. Research watersheds provide the possibility for reasonable detailed combining of processes into some typical hydrologic concept such as hydrologic units, hydrologic forms, and runoff formation complexes in the Hydrograph model. And here by upscaling we imply not the upscaling of a single process but upscaling of such unified hydrologic functioning. The simulation of runoff processes for the Dry Creek research watershed, Idaho, USA (27 km2) was undertaken using the Hydrograph model. The information on the watershed was provided by Boise State University and included a GIS database of watershed characteristics and a detailed hydrometeorological observational dataset. The model provided good simulation results in

  7. A comparison of alternative multiobjective calibration strategies for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Savenije, Hubert H. G.; Matgen, Patrick; Pfister, Laurent

    2007-03-01

    A conceptual hydrological model structure contains several parameters that have to be estimated through matching observed and modeled watershed behavior in a calibration process. The requirement that a model simulation matches different aspects of system response at the same time has led the calibration problem toward a multiobjective approach. In this work we compare two multiobjective calibration approaches, each of which represents a different calibration philosophy. The first calibration approach is based on the concept of Pareto optimality and consists of calibrating all parameters with respect to a common set of objectives in one calibration stage. This approach results in a set of Pareto-optimal solutions representing the trade-offs between the selected calibration objectives. The second is a stepped calibration approach (SCA), which implies a stepwise calibration of sets of parameters that are associated with specific aspects of the system response. This approach replicates the steps followed by a hydrologist in manual calibration and develops a single solution. The comparison is performed considering the same set of objectives for the two approaches and two model structures of a different level of complexity. The difference in the two approaches, their reciprocal utility, and the practical implications involved in their application are analyzed and discussed using the Hesperange catchment case, an experimental basin in the Alzette River basin in Luxembourg. We show that the two approaches are not necessarily conflicting but can be complementary. The first approach provides useful information about the deficiencies of a model structure and therefore helps the model development, while the second attempts at determining a solution that is consistent with the data available. We also show that with increasing model complexity it becomes possible to reproduce the observations more accurately. As a result, the solutions for the different calibration objectives

  8. Disinformative data in large-scale hydrological modelling

    NASA Astrophysics Data System (ADS)

    Kauffeldt, Anna; Halldin, Sven; Rodhe, Allan; Xu, Chong-Yu; Westerberg, Ida

    2013-04-01

    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 forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aims at identifying two types of data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. Firstly, four hydrographic datasets were examined in terms of how well basin areas were represented in the flow networks. It was found that most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between hydrographic datasets and archived basin areas. Secondly, the consistency between climate data (precipitation and potential evaporation) and discharge data was examined for the possibility of water-balance closure. It was found that basins exhibiting too high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and that the occurrence of basins exhibiting losses exceeding the energy limit were strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. These 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 increases our chances to draw robust conclusions from subsequent model simulations.

  9. Improvement and Comparative Assessment of a New Hydrological Modelling Approach for the Ouémé River Basin (Bénin), West Africa

    NASA Astrophysics Data System (ADS)

    GABA, C. O. U.

    2015-12-01

    Assessing water resources is still an important issue especially in the context of climatic changes. Although numerous hydrological models exist, new approaches are still under investigation. In this context, we propose a new modelling approach based on the Physics Principle of Least Action. A first version of a Least Action based model, in its deterministic version has already given very good results on simulating the Bétérou catchment in the Ouémé basin, Benin. The paper presents new hypotheses to go further in the model development with a view of widening its application. The improved version of the model MODYPMA was applied on 22 subcatchments in Africa, in Bénin, Côte d'Ivoire, Ethiopia; in Europe, and in the USA. Its performance was compared to two well known lumped conceptual models, the GR4J and HBV models. The model could be successfully calibrated and validated; it shows a good performance for a range of scales but a limited applicability to catchments smaller than 500 km2 . The analysis revealed that the three models have similar performance and timing errors. The parameter uncertainty was analysed using the GLUE methodology. It is concluded that model uncertainty is higher during high flows and that uncertainty analysis should include the uncertainty of the discharge data. Finally, some aspects that further research must address are brought out.

  10. Assessing the hydropower potential of ungauged watersheds in Iceland using hydrological modeling and satellite retrieved snow cover images

    NASA Astrophysics Data System (ADS)

    Finger, David

    2015-04-01

    About 80% of the domestic energy production in Iceland comes from renewable energies. Hydropower accounts for about 20% this production, representing about 75% of the total electricity production in Iceland. In 2008 total electricity production from hydropower was about 12.5 TWh a-1, making Iceland a worldwide leader in hydropower production per capita. Furthermore, the total potential of hydroelectricity in Iceland is estimated to amount up to 220 TWh a-1. In this regard, hydrological modelling is an essential tool to adapt a sustainable management of water resources and estimate the potential of possible new sites for hydropower production. We used the conceptual lumped Hydrologiska Byråns Vattenbalansavdelning model (HBV) to estimate the potential of hydropower production in two remote areas in north-eastern Iceland (Leirdalshraun, a 274 km2 area above 595 m asl and Hafralónsá, a 946 km2 area above 235 m asl). The model parameters were determined by calibrating the model with discharge data from gauged sub catchments. Satellite snow cover images were used to constrain melt parameters of the model and assure adequate modelling of snow melt in the ungauged areas. This was particularly valuable to adequately estimate the contribution of snow melt, rainfall runoff and groundwater intrusion from glaciers outside the topographic boundaries of the selected watersheds. Runoff from the entire area potentially used for hydropower exploitation was estimated using the parameter sets of the gauged sub-catchments. Additionally, snow melt from the ungauged areas was validated with satellite based snow cover images, revealing a robust simulation of snow melt in the entire area. Based on the hydrological modelling the total amount of snow melt and rainfall runoff available in Leirdalshraun and Hafralónsá amounts up to 700 M m3 a-1 and 1000 M m3 a-1, respectively. These results reveal that the total hydropower potential of the two sites amounts up to 1.2 TWh a-1

  11. Links between the spatial structure of weather generator and hydrological modeling

    NASA Astrophysics Data System (ADS)

    Li, Zhi; Lü, Zhemin; Li, Jingjing; Shi, Xiaoping

    2015-12-01

    Impacts of the spatial structure of weather generators on hydrological modeling have been largely qualitatively discussed; however, their links have been rarely quantified. The precipitation occurrence and amount were respectively generated with Markov chain and the mixed exponential distribution for single sites, and then the procedures were extended to multi-site simulation according to Wilks (1998). In the multi-site model, precipitation amounts were respectively generated with untapered or tapered mixed exponential scale parameters. The generated precipitation series were used as inputs of Soil and Water Assessment Tool (SWAT) to interpret the links between the spatial structure of weather generators and hydrological modeling. The single-site and multi-site model using untapered scale parameters gave similar averages for monthly and annual streamflow; however, the untapered multi-site model was superior to simulating hydrological variability. The single-site model underestimated the maxima and variances while overestimated the minima of streamflow; therefore, the use of single-site models for hydrological variability simulation should be cautious. The multi-site model using tapered scale parameters greatly overestimated the averages, extremes, and variances of streamflow. The Wilks model for multi-site precipitation simulation using tapered scale parameters is not appropriate for hydrological modeling, and the untapered version is thus recommended. Overall, the spatial structure of weather generators has significant impacts on hydrological modeling, especially for hydrological variability simulation; therefore, the links between them should be paid great attentions.

  12. Hydrologic Characterization for Spring Creek and Hydrologic Budget and Model Scenarios for Sheridan Lake, South Dakota, 1962-2007

    USGS Publications Warehouse

    Driscoll, Daniel G.; Norton, Parker A.

    2009-01-01

    The U.S. Geological Survey cooperated with South Dakota Game, Fish and Parks to characterize hydrologic information relevant to management of water resources associated with Sheridan Lake, which is formed by a dam on Spring Creek. This effort consisted primarily of characterization of hydrologic data for a base period of 1962 through 2006, development of a hydrologic budget for Sheridan Lake for this timeframe, and development of an associated model for simulation of storage deficits and drawdown in Sheridan Lake for hypothetical release scenarios from the lake. Historically, the dam has been operated primarily as a 'pass-through' system, in which unregulated outflows pass over the spillway; however, the dam recently was retrofitted with an improved control valve system that would allow controlled releases of about 7 cubic feet per second (ft3/s) or less from a fixed depth of about 60 feet (ft). Development of a hydrologic budget for Sheridan Lake involved compilation, estimation, and characterization of data sets for streamflow, precipitation, and evaporation. The most critical data need was for extrapolation of available short-term streamflow records for Spring Creek to be used as the long-term inflow to Sheridan Lake. Available short-term records for water years (WY) 1991-2004 for a gaging station upstream from Sheridan Lake were extrapolated to WY 1962-2006 on the basis of correlations with streamflow records for a downstream station and for stations located along two adjacent streams. Comparisons of data for the two streamflow-gaging stations along Spring Creek indicated that tributary inflow is approximately proportional to the intervening drainage area, which was used as a means of estimating tributary inflow for the hydrologic budget. Analysis of evaporation data shows that sustained daily rates may exceed maximum monthly rates by a factor of about two. A long-term (1962-2006) hydrologic budget was developed for computation of reservoir outflow from

  13. visCOS: An R-package to evaluate model performance of hydrological models

    NASA Astrophysics Data System (ADS)

    Klotz, Daniel; Herrnegger, Mathew; Wesemann, Johannes; Schulz, Karsten

    2016-04-01

    The evaluation of model performance is a central part of (hydrological) modelling. Much attention has been given to the development of evaluation criteria and diagnostic frameworks. (Klemeš, 1986; Gupta et al., 2008; among many others). Nevertheless, many applications exist for which objective functions do not yet provide satisfying summaries. Thus, the necessity to visualize results arises in order to explore a wider range of model capacities, be it strengths or deficiencies. Visualizations are usually devised for specific projects and these efforts are often not distributed to a broader community (e.g. via open source software packages). Hence, the opportunity to explicitly discuss a state-of-the-art presentation technique is often missed. We therefore present a comprehensive R-package for evaluating model performance by visualizing and exploring different aspects of hydrological time-series. The presented package comprises a set of useful plots and visualization methods, which complement existing packages, such as hydroGOF (Zambrano-Bigiarini et al., 2012). It is derived from practical applications of the hydrological models COSERO and COSEROreg (Kling et al., 2014). visCOS, providing an interface in R, represents an easy-to-use software package for visualizing and assessing model performance and can be implemented in the process of model calibration or model development. The package provides functions to load hydrological data into R, clean the data, process, visualize, explore and finally save the results in a consistent way. Together with an interactive zoom function of the time series, an online calculation of the objective functions for variable time-windows is included. Common hydrological objective functions, such as the Nash-Sutcliffe Efficiency and the Kling-Gupta Efficiency, can also be evaluated and visualized in different ways for defined sub-periods like hydrological years or seasonal sections. Many hydrologists use long-term water-balances as a

  14. Modeling low impact development potential with hydrological response units.

    PubMed

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

    2013-01-01

    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

  15. Flexible automated parameterization of hydrologic models using fuzzy logic

    NASA Astrophysics Data System (ADS)

    Samanta, Sudeep; Mackay, D. Scott

    2003-01-01

    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.

  16. Regional scale hydrology with a new land surface processes model

    NASA Technical Reports Server (NTRS)

    Laymon, Charles; Crosson, William

    1995-01-01

    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.

  17. Modeling Nitrogen Leaching With A Biogeochemical Model Coupled With Soil Hydrology Model

    NASA Astrophysics Data System (ADS)

    Barman, R.; Yang, X.; Jain, A.; Post, W. M.; Sivapalan, M.

    2008-12-01

    Land use changes for cropland, excessive application of fertilizers in agriculture, and increase in anthropogenic activities such as fossil fuel burning have lead to widespread increases in anthropogenic production of reactive N and NH3 emissions, and N deposition rates. An important consequence of these processes is intensification of soil nutrient leaching activities, leading to serious ground water contamination problems. The current study focuses on the issue of nitrogen (nitrate and ammonium) leaching due to land cover changes for cropland, excess N fertilizer application, and atmospheric nitrogen deposition on nitrogen leaching at a global scale. Simulations of nitrogen leaching require integration of processes involving soil hydrology and biogeochemical cycles. An existing terrestrial coupled carbon-nitrogen cycle model, Integrated Science Assessment Model (ISAM), was used to estimate nitrogen leaching. The N-cycle in ISAM includes the major processes associated with nitrogen (immobilization, mineralization, nitrification, denitrification, leaching, nitrogen fixation, and vegetation nitrogen uptake). ISAM also considers how carbon and nitrogen dynamics are influenced by the effects of human perturbations to the N cycle including atmospheric deposition and fertilizer application, and the fate of N in land use activities, i.e., deforestation and agricultural harvest. In this study, the ISAM soil hydrology was extended and improved with CLM 3.5 hydrology processes and algorithms, which extended the modeling capabilities to consider the prediction of nitrogen leaching. The model performance was evaluated with flow and nutrient data at several locations within the Upper Sangamon River Basin in Illinois, and flow data in contrasting watersheds in Oklahoma. This talk will focus on describing the results of a series of modeling experiments examining the influence of land management changes for cropland and nitrogen deposition on nitrogen leaching at a global scale

  18. Demasking the integrated value of discharge - Advanced sensitivity analysis on the components of hydrological models

    NASA Astrophysics Data System (ADS)

    Guse, Björn; Pfannerstill, Matthias; Gafurov, Abror; Fohrer, Nicola; Gupta, Hoshin

    2016-04-01

    The hydrologic response variable most often used in sensitivity analysis is discharge which provides an integrated value of all catchment processes. The typical sensitivity analysis evaluates how changes in the model parameters affect the model output. However, due to discharge being the aggregated effect of all hydrological processes, the sensitivity signal of a certain model parameter can be strongly masked. A more advanced form of sensitivity analysis would be achieved if we could investigate how the sensitivity of a certain modelled process variable relates to the changes in a parameter. Based on this, the controlling parameters for different hydrological components could be detected. Towards this end, we apply the approach of temporal dynamics of parameter sensitivity (TEDPAS) to calculate the daily sensitivities for different model outputs with the FAST method. The temporal variations in parameter dominance are then analysed for both the modelled hydrological components themselves, and also for the rates of change (derivatives) in the modelled hydrological components. The daily parameter sensitivities are then compared with the modelled hydrological components using regime curves. Application of this approach shows that when the corresponding modelled process is investigated instead of discharge, we obtain both an increased indication of parameter sensitivity, and also a clear pattern showing how the seasonal patterns of parameter dominance change over time for each hydrological process. By relating these results with the model structure, we can see that the sensitivity of model parameters is influenced by the function of the parameter. While capacity parameters show more sensitivity to the modelled hydrological component, flux parameters tend to have a higher sensitivity to rates of change in the modelled hydrological component. By better disentangling the information hidden in the discharge values, we can use sensitivity analyses to obtain a clearer signal

  19. Calibration of a Hydrologic Model Considering Input Uncertainty in Assessing Climate Change Impact on Streamflow

    NASA Astrophysics Data System (ADS)

    Bolisetti, T.; Datta, A. R.; Balachandar, R.

    2009-05-01

    Studies on impact assessment and the corresponding uncertainties in hydrologic regime predictions is of paramount in developing water resources management plans under climate change scenarios,. The variability in hydrologic model parameters is one of the major sources of uncertainties associated with climate change impact on streamflow. Uncertainty in hydrologic model parameters may arise from the choice of model calibration technique, model calibration period, model structure and response variables. The recent studies show that consideration of uncertainties in input variables (precipitation, evapotranspiration etc.) during calibration of a hydrologic model has resulted in decrease in prediction uncertainty. The present study has examined the significance of input uncertainty in hydrologic model calibration for climate change impact studies. A physically distributed hydrologic model, Soil and Water Assessment Tool (SWAT), is calibrated considering uncertainties in (i) model parameters only, and (ii) both model parameters and precipitation input. The Markov chain Monte Carlo algorithm is used to estimate the posterior probability density function of hydrologic model parameters. The observed daily precipitation and streamflow data of the Canard River watershed of Essex region, Ontario, Canada are used as input and output variables, respectively, during calibration. The parameter sets of the 100 most skillful hydrologic model simulations obtained from each calibration technique are used for predicting streamflow by 2070s under climate change conditions. In each run, the climate predictions of the Canadian Regional Climate Model (CRCM) for SRES scenario A2 are used as input to the hydrologic model for streamflow prediction. The paper presents the results of uncertainty in seasonal and annual streamflow prediction. The outcome of the study is expected to contribute to the assessment of uncertainty in climate change impact studies and better management of available

  20. Modular modeling system for building distributed hydrologic models with a user-friendly software package

    NASA Astrophysics Data System (ADS)

    Wi, S.; Ray, P. A.; Brown, C.

    2015-12-01

    A software package developed to facilitate building distributed hydrologic models in a modular modeling system is presented. The software package provides a user-friendly graphical user interface that eases its practical use in water resources-related research and practice. The modular modeling system organizes the options available to users when assembling models according to the stages of hydrological cycle, such as potential evapotranspiration, soil moisture accounting, and snow/glacier melting processes. The software is intended to be a comprehensive tool that simplifies the task of developing, calibrating, validating, and using hydrologic models through the inclusion of intelligent automation to minimize user effort, and reduce opportunities for error. Processes so far automated include the definition of system boundaries (i.e., watershed delineation), climate and geographical input generation, and parameter calibration. Built-in post-processing toolkits greatly improve the functionality of the software as a decision support tool for water resources system management and planning. Example post-processing toolkits enable streamflow simulation at ungauged sites with predefined model parameters, and perform climate change risk assessment by means of the decision scaling approach. The software is validated through application to watersheds representing a variety of hydrologic regimes.

  1. Statistical procedures for evaluating daily and monthly hydrologic model predictions

    USGS Publications Warehouse

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

    2004-01-01

    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.

  2. The HBV Drugs Work: Now What?

    PubMed

    Pruett, Timothy L

    2016-09-01

    Chemotherapeutic agents for Hepatitis B virus (HBV) suppression work, but only when administered to the patient. They do not appear to promote durable, long-term immunological control. After 3 years of effective anti-HBV therapy, a small percentage of patients maintained good control, manifest by controlled serum liver enzymes, low-level HBV-DNA, and controlled HBsAg concentrations. However, this did not occur in the majority of patients. We need a better understanding of the defects in HBV immunity and how to induce effective reconstitution that will maintain viral suppression, albeit either through innate or adaptive immunity. PMID:27580778

  3. An Open Source modular platform for hydrological model implementation

    NASA Astrophysics Data System (ADS)

    Kolberg, Sjur; Bruland, Oddbjørn

    2010-05-01

    An implementation framework for setup and evaluation of spatio-temporal models is developed, forming a highly modularized distributed model system. The ENKI framework allows building space-time models for hydrological or other environmental purposes, from a suite of separately compiled subroutine modules. The approach makes it easy for students, researchers and other model developers to implement, exchange, and test single routines in a fixed framework. The open-source license and modular design of ENKI will also facilitate rapid dissemination of new methods to institutions engaged in operational hydropower forecasting or other water resource management. Written in C++, ENKI uses a plug-in structure to build a complete model from separately compiled subroutine implementations. These modules contain very little code apart from the core process simulation, and are compiled as dynamic-link libraries (dll). A narrow interface allows the main executable to recognise the number and type of the different variables in each routine. The framework then exposes these variables to the user within the proper context, ensuring that time series exist for input variables, initialisation for states, GIS data sets for static map data, manually or automatically calibrated values for parameters etc. ENKI is designed to meet three different levels of involvement in model construction: • Model application: Running and evaluating a given model. Regional calibration against arbitrary data using a rich suite of objective functions, including likelihood and Bayesian estimation. Uncertainty analysis directed towards input or parameter uncertainty. o Need not: Know the model's composition of subroutines, or the internal variables in the model, or the creation of method modules. • Model analysis: Link together different process methods, including parallel setup of alternative methods for solving the same task. Investigate the effect of different spatial discretization schemes. o Need not

  4. France-wide future evolution of discharges for the next decades: a multi-RCP/GCM/hydrological model and calibration exercise

    NASA Astrophysics Data System (ADS)

    Thirel, Guillaume; Nicolas, Madeleine; Beersma, Jules

    2015-04-01

    Due to complex interactions between atmosphere, vegetation, oceans, land and human beings, climate is continually evolving. The last IPCC report highlighted that by the end of the 21st century, dramatic climate modifications may occur: in Europe, the temperature is expected to increase by several degrees, and the evolution of precipitation is more uncertain. These changes will impact the water cycle, and as a consequence river discharges, which can potentially impact economical, industrial and touristic activities as well as the ecosphere. In order to provide new insights for hydrology in France, we propose to assess the impact of climate change on discharge module, high and low flows for over 800 river points in France. For this, the last CMIP5 projections are used for the periods 2021-2050 and 2071-2100. This country-wide evaluation, a compromise between basin-based and continental studies usually performed in literature, is of the utmost importance due to the numerous interconnections of water uses inside France. For this work, the 4 IPCC Representative Concentration Pathways (RCPs) were utilized to drive part or all of 27 Global Circulation Models (GCMs) or versions of GCMs, for which one to ten different runs were available. This represents a total of 183 climatic projections that were then downscaled using the Advanced Delta Change (ADC) method, a statistical method calibrated between a past reference period and the two future periods. In this study, we applied the ADC to an 8x8 km 52-year meteorological reanalysis available over France. Six global conceptual hydrological models (GR4J, GR5J, GR6J, MORD6, TOPMO, HBV0) were used to produce the hydrological projections, allowing the representation of uncertainty in hydrological modelling. Moreover, one of the hydrological models was calibrated with several objective functions and over contrasted climatic periods. By having several methods or models for every step (except regarding the downscaling method), we

  5. New hydrologic model of fluid migration in deep porous media

    NASA Astrophysics Data System (ADS)

    Dmitrievsky, A.; Balanyuk, I.

    2009-04-01

    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

  6. A coupled mechanical/hydrologic model for WIPP shaft seals

    SciTech Connect

    Ehgartner, B.

    1991-06-01

    Effective sealing of the Waste Isolation Pilot Plant (WIPP) shafts will be required to isolate defense-generated transuranic wastes from the accessible environment. Shafts penetrate water-bearing hard rock formations before entering a massive creeping-salt formation (Salado) where the WIPP is located. Short and long-term seals are planned for the shafts. Short-term seals, a composite of concrete and bentonite, will primarily be located in the hard rock formations separating the water-bearing zones from the Salado Formation. These seals will limit water flow to the underlying long-term seals in the Salado. The long-term seals will consist of lengthly segments of initially unsaturated crushed salt. Creep closure of the shaft will consolidate unsaturated crushed salt, thereby reducing its permeability. However, water passing through the upper short-term seals and brine inherent to the salt host rock itself will eventually saturate the crushed salt and consolidation could be inhibited. Before saturating, portions of the crushed salt in the shafts are expected to consolidate to a permeability equivalent to the salt host rock, thereby effectively isolating the waste from the overlying water-bearing formations. A phenomenological model is developed for the coupled mechanical/hydrologic behavior of sealed WIPP shafts. The model couples creep closure of the shaft, crushed salt consolidation, and the associated reduction in permeability with Darcy's law for saturated fluid flow to predict the overall permeability of the shaft seal system with time. 17 refs., 6 figs., 1 tab.

  7. Modelling of green roofs' hydrologic performance using EPA's SWMM.

    PubMed

    Burszta-Adamiak, E; Mrowiec, M

    2013-01-01

    Green roofs significantly affect the increase in water retention and thus the management of rain water in urban areas. In Poland, as in many other European countries, excess rainwater resulting from snowmelt and heavy rainfall contributes to the development of local flooding in urban areas. Opportunities to reduce surface runoff and reduce flood risks are among the reasons why green roofs are more likely to be used also in this country. However, there are relatively few data on their in situ performance. In this study the storm water performance was simulated for the green roofs experimental plots using the Storm Water Management Model (SWMM) with Low Impact Development (LID) Controls module (version 5.0.022). The model consists of many parameters for a particular layer of green roofs but simulation results were unsatisfactory considering the hydrologic response of the green roofs. For the majority of the tested rain events, the Nash coefficient had negative values. It indicates a weak fit between observed and measured flow-rates. Therefore complexity of the LID module does not affect the increase of its accuracy. Further research at a technical scale is needed to determine the role of the green roof slope, vegetation cover and drying process during the inter-event periods. PMID:23823537

  8. Coupling of the simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To represent the effects of frozen soil on hydrology in cold regions, a new physically based distributed hydrological model has been developed by coupling the simultaneous heat and water model (SHAW) with the geomorphology based distributed hydrological model (GBHM), under the framework of the water...

  9. Modeling of Thermal-Hydrological-Chemical Laboratory Experiments

    SciTech Connect

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

    2001-05-31

    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.

  10. 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...

  11. Impact of model development, calibration and validation decisions on hydrological simulations in West Lake Erie Basin

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Watershed simulation models are used extensively to investigate hydrologic processes, landuse and climate change impacts, pollutant load assessments and best management practices (BMPs). Developing, calibrating and validating these models require a number of critical decisions that will influence t...

  12. Evapotranspiration and irrigation algorithms in hydrologic modeling:Present Status and Opportunities

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrologic models are used extensively for predicting water availability and water quality responses to alternative irrigation, tillage, crop, and fertilizer management practices and global climate change. Modeling results have been frequently used by regulatory agencies for developing remedial meas...

  13. Development and application of a simple hydrologic model for water simulation for a Brazilian Headwater Basin

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Physically based hydrologic models for watershed are important tools to support water resources management and predicting hydrologic impacts produced by land-use change. Rio Grande Basin is located in south of Minas Gerais State, and the Rio Grande is the main tributary of basin which has 2080 km2 d...

  14. The Effect of Modeling and Visualization Resources on Student Understanding of Physical Hydrology

    ERIC Educational Resources Information Center

    Marshall, Jilll A.; Castillo, Adam J.; Cardenas, M. Bayani

    2015-01-01

    We investigated the effect of modeling and visualization resources on upper-division, undergraduate and graduate students' performance on an open-ended assessment of their understanding of physical hydrology. The students were enrolled in one of five sections of a physical hydrology course. In two of the sections, students completed homework…

  15. The application of remote sensing to the development and formulation of hydrologic planning models: Executive summary

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

    Methods for the reduction of remotely sensed data and its application in hydrologic land use assessment, surface water inventory, and soil property studies are presented. LANDSAT data is used to provide quantitative parameters and coefficients to construct watershed transfer functions for a hydrologic planning model aimed at estimating peak outflow from rainfall inputs.

  16. Using expert knowledge of the hydrological system to constrain multi-objective calibration of SWAT models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The SWAT model is a helpful tool to predict hydrological processes in a study catchment and their impact on the river discharge at the catchment outlet. For reliable discharge predictions, a precise simulation of hydrological processes is required. Therefore, SWAT has to be calibrated accurately to ...

  17. Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With the availability of advanced hydrologic data in the public domain such as remotely sensed and climate change scenario data, there is a need for a modeling framework that is capable of using these data to simulate and extend hydrologic processes with multidisciplinary approaches for sustainable ...

  18. A model-model and data-model comparison for the early Eocene hydrological cycle

    NASA Astrophysics Data System (ADS)

    Carmichael, Matthew J.; Lunt, Daniel J.; Huber, Matthew; Heinemann, Malte; Kiehl, Jeffrey; LeGrande, Allegra; Loptson, Claire A.; Roberts, Chris D.; Sagoo, Navjit; Shields, Christine; Valdes, Paul J.; Winguth, Arne; Winguth, Cornelia; Pancost, Richard D.

    2016-02-01

    A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP/dT) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a

  19. What have we learned by applying the data driven modelling techniques in the field of hydrological modelling?

    NASA Astrophysics Data System (ADS)

    Stravs, Luka; Brilly, Mitja

    2010-05-01

    Hydrologic data analysis and hydrologic modelling have become major techniques in hydrology and are used for building hydrologic models to generate synthetic hydrologic records, to forecast hydrologic events, to detect trends and shifts in hydrologic records and to fill in missing data and extend the data sets. Well known, praised and widely used are the so-called conceptual models that are based on the prior theoretical knowledge of all the hydrological processes in the form of theoretically developed or empirically derived equations. A modeller needs a lot of detailed data like river network, land cover, soil characteristics and other geographical data or topographical maps to sucessfully calibrate a conceptual model. The availability of all of the aforementioned data can present quite a significant problem in the process of modelling. On the basis of different approaches to the inclusion of geographical, topographical and other data in conceptual models, we distinguish between distributed, semi-distributed and lumped conceptual models. Empirical, mostly black box models simply connecting input and output hydrolgical data have also been widely used in the field of hydrology, especially in the hydrological praxis. Data driven modelling on the other hand is based on the analysis of the data characterising the system being modelled, which in most cases means finding the best type of model or combination of those to connect the input and output data characterising the system being modelled, while the assumptions or learning about the physical bases of the system being modelled are not the top priority. Also, there is still a lot of scepticism among many hydrologists regarding the usage of data driven modelling techniques in hydrology, because the development of the models from the data is usually seen as a computational exercise and is not related to physical principles and mathematical reasoning. This presentation will give a quick overview of more and less

  20. Hydrological Modeling Reproducibility Through Data Management and Adaptors for Model Interoperability

    NASA Astrophysics Data System (ADS)

    Turner, M. A.

    2015-12-01

    Because of a lack of centralized planning and no widely-adopted standards among hydrological modeling research groups, research communities, and the data management teams meant to support research, there is chaos when it comes to data formats, spatio-temporal resolutions, ontologies, and data availability. All this makes true scientific reproducibility and collaborative integrated modeling impossible without some glue to piece it all together. Our Virtual Watershed Integrated Modeling System provides the tools and modeling framework hydrologists need to accelerate and fortify new scientific investigations by tracking provenance and providing adaptors for integrated, collaborative hydrologic modeling and data management. Under global warming trends where water resources are under increasing stress, reproducible hydrological modeling will be increasingly important to improve transparency and understanding of the scientific facts revealed through modeling. The Virtual Watershed Data Engine is capable of ingesting a wide variety of heterogeneous model inputs, outputs, model configurations, and metadata. We will demonstrate one example, starting from real-time raw weather station data packaged with station metadata. Our integrated modeling system will then create gridded input data via geostatistical methods along with error and uncertainty estimates. These gridded data are then used as input to hydrological models, all of which are available as web services wherever feasible. Models may be integrated in a data-centric way where the outputs too are tracked and used as inputs to "downstream" models. This work is part of an ongoing collaborative Tri-state (New Mexico, Nevada, Idaho) NSF EPSCoR Project, WC-WAVE, comprised of researchers from multiple universities in each of the three states. The tools produced and presented here have been developed collaboratively alongside watershed scientists to address specific modeling problems with an eye on the bigger picture of