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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. 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.

  13. 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)

  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. 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.

  17. 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.

  18. 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

  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. 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.

  19. 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.

  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. 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 ...

  6. 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...

  7. 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...

  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. 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.

  10. 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

  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 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...

  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. 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...

  11. 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...

  12. 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...

  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. 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.

  17. 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.

  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. 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.

  14. 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.

  15. 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...

  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. 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.

  19. 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.

  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. 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.

  3. 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

  4. 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...

  5. 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...

  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