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Sample records for hydrological model hbv

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  2. HBV light - A user-friendly catchment-runoff-model software

    NASA Astrophysics Data System (ADS)

    Seibert, J.; Vis, M.; Käser, D.

    2012-04-01

    Conceptual models are frequently used for catchment hydrology studies. Here we present a new version of the HBV model, which has been programmed in Visual Basic .NET. This software provides a user-friendly version which is especially useful for education. Different functionalities like an automatic calibration and the possibility to perform Monte Carlo runs make the software also interesting for research projects. Furthermore, a command line version is suitable for automating modeling procedures and for coupling with software such as PEST.

  3. Adaptation of the HBV model for the study of drought propagation in European catchments

    NASA Astrophysics Data System (ADS)

    van Loon, A. F.; van Lanen, H. A. J.; Seibert, J.; Torfs, P. J. J. F.

    2009-04-01

    Drought propagation is the conversion of a meteorological drought signal into a hydrological drought (e.g. groundwater and streamflow) as it moves through the subsurface part of the hydrological cycle. The lag, attenuation and possibly pooling of parts of the signal are dependent on climate and catchment characteristics. The understanding of processes underlying drought propagation is still very limited. Our aim is to study these processes in small catchments across Europe with different climate conditions and physical structures (e.g. hard rock, porous rock, flat areas, steep slopes, snow, lakes). As measurements of soil moisture and groundwater storage are normally scarce, simulation of these variables using a lumped hydrological model is needed. However, although a simple model is preferable, many conceptual rainfall-runoff models are not suitable for this purpose because of their focus on fast reactions and therefore unrealistic black box approach of the soil moisture and groundwater system. We studied the applicability of the well-known semi-distributed rainfall-runoff model HBV for drought propagation research. The results show that HBV reproduces observed discharges fairly well. However, in simulating groundwater storage in dry periods, HBV has some conceptual weaknesses: 1) surface runoff is approximated by a quick flow component through the upper groundwater box; 2) the storage in the upper groundwater box has no upper limit; 3) lakes are simulated as part of the lower groundwater box; 4) the percolation from the upper to the lower groundwater box is not continuous, but either zero or constant. So, adaptation of the HBV model structure was needed to be able to simulate realistic groundwater storage in dry periods. The HBV Light model (Seibert et al., 2000) was used as basis for this work. As the snow and soil routines of this model have proven their value in previous (drought) studies, these routines are left unchanged. The lower part of HBV Light, the "response function" that transforms groundwater recharge into discharge, is replaced by a for this study adapted conceptual research model programmed in R. The structure of this conceptual research model is based on a number of coupled reservoirs representing storage in shallow and deep groundwater, and lakes. The recession characteristics of the catchment determine the model elements: i.e. number of reservoirs, linear vs. non-linear reservoirs, in series vs. parallel connections. We used data from Narsjø (Norway), Metuje and Sázava (Czech Republic) to select the proper configuration for the conceptual research model and to test the combined HBV Light-conceptual research model approach. The influence of different model configurations on drought characteristics is presented. Subsequently, the new approach was applied to 4-5 other European catchments with contrasting climate conditions and physical structures (including Nedožery (Slovakia), and Upper-Guadiana (Spain)). Our adapted model approach finally gives a better representation of groundwater storage during drought periods than the original HBV model, which makes it a useful tool for the study of processes underlying drought propagation. Simulated drought characteristics are shown to illustrate drought propagation for the different catchment conditions. Seibert, J., Unlenbrook, S., Leibundgut, C. and Halldin, S., 2000. Multiscale calibration and validation of a conceptual rainfall-runoff model. Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, 25(1): 59-64.

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

    PubMed

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

    2000-09-01

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

  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. 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 the ICECREAM model for arable leaching, routines for erosion and algae growth. Several applications with scenario evaluation for N have shown that the HBV-NP model is a very useful tool that facilitates discussions among local actors, acceptance of management plans and implementation of measures for nutrient reduction in watersheds.

  7. Multi-purpose calibration of HBV models for the Rhine with OpenDA

    NASA Astrophysics Data System (ADS)

    van Verseveld, W. J.; Sperna-Weiland, F.; Meissner, D.; Winsemius, H. C.; Weerts, A. H.; Hummel, S.; Sumihar, J. H.; Hegnauer, M.

    2012-04-01

    Calibration strategies for hydrological models nearly always depend on user interests. These interests are strongly determined by the eventual practical application of the model: what information should the model primarily provide, e.g. low flows, high flows, or accumulated inflows; what spatial and temporal information density is available in terms of data, and what information needed in terms of practical use; should parameter uncertainty estimation of the hydrological model be included? The Open-source Data Assimilation toolbox (OpenDA) is an open software framework for calibration and data-assimilation of hydrological models. In this contribution, we show that OpenDA can be used to rapidly calibrate a hydrological model, which is to be used for different purposes or under different circumstances such as mentioned above. To this end, OpenDA includes a number of calibration algorithms, can communicate with a multitude of hydrological and hydraulic models, and can handle multiple calibration signals in one calibration experiment. It can therefore be employed in complex calibration experiments. New algorithms and models can be included efficiently in the software. Our case study focuses on an HBV model structure for the international Rhine basin (area ~ 185.000 km2), consisting of 134 sub-catchment units containing many different gauging stations. This model is embedded in Delft-FEWS, an operational forecasting system which can also be used for offline data management and model integration. We performed a recalibration focussing on two applications: FEWS-Rivers / FEWS-BfG (operational forecasting): Simulations of snow pack and melt within HBV performed poorly in this application. The model was optimized on hourly time scale. Parameters, related to snow processes were identified and optimized on a large number of available gauge data sets, using the Shuffled Complex Evolution algorithm. FEWS-GRADE (extreme discharges for dike design): In this application, very long synthetic discharge series are simulated on a daily basis. Because of the high return periods of interest (1/1250 years), uncertainty of these estimates should be taken into account. Therefore, calibration has been performed using the GLUE algorithm. GLUE is used to select an ensemble of parameter sets, rather than one single set. Parameter performance was tested with specific criteria for extreme high discharges.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  10. 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.

  11. 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.

  12. 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.

  13. 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 simulations is better; (5) the overall best performance is obtained by hourly simulations with pre-processing of rainfall data.

  14. netherland hydrological modeling instrument

    NASA Astrophysics Data System (ADS)

    Hoogewoud, J. C.; de Lange, W. J.; Veldhuizen, A.; Prinsen, G.

    2012-04-01

    Netherlands Hydrological Modeling Instrument A decision support system for water basin management. J.C. Hoogewoud , W.J. de Lange ,A. Veldhuizen , G. Prinsen , The Netherlands Hydrological modeling Instrument (NHI) is the center point of a framework of models, to coherently model the hydrological system and the multitude of functions it supports. Dutch hydrological institutes Deltares, Alterra, Netherlands Environmental Assessment Agency, RWS Waterdienst, STOWA and Vewin are cooperating in enhancing the NHI for adequate decision support. The instrument is used by three different ministries involved in national water policy matters, for instance the WFD, drought management, manure policy and climate change issues. The basis of the modeling instrument is a state-of-the-art on-line coupling of the groundwater system (MODFLOW), the unsaturated zone (metaSWAP) and the surface water system (MOZART-DM). It brings together hydro(geo)logical processes from the column to the basin scale, ranging from 250x250m plots to the river Rhine and includes salt water flow. The NHI is validated with an eight year run (1998-2006) with dry and wet periods. For this run different parts of the hydrology have been compared with measurements. For instance, water demands in dry periods (e.g. for irrigation), discharges at outlets, groundwater levels and evaporation. A validation alone is not enough to get support from stakeholders. Involvement from stakeholders in the modeling process is needed. There fore to gain sufficient support and trust in the instrument on different (policy) levels a couple of actions have been taken: 1. a transparent evaluation of modeling-results has been set up 2. an extensive program is running to cooperate with regional waterboards and suppliers of drinking water in improving the NHI 3. sharing (hydrological) data via newly setup Modeling Database for local and national models 4. Enhancing the NHI with "local" information. The NHI is and has been used for many decision supports and evaluations. The main focus of the instrument is operational drought management and evaluating adaptive measures for different climate scenario's. It has also been used though as a basis to evaluate water quality of WFD-water bodies and measures, nutrient-leaching and describing WFD groundwater bodies. There is a toolkit to translate the hydrological NHI results to values for different water users. For instance with the NHI results agricultural yields can be calculated, effects on ground water dependant ecosystems, subsidence, shipping, drinking water supply. This makes NHI a valuable decision support system in Dutch water management.

  15. 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 more importance to identifying and communicating on the many factors involved in model development might increase transparency of model building.

  16. Thermal-hydrological models

    SciTech Connect

    Buscheck, T., LLNL

    1998-04-29

    This chapter describes the physical processes and natural and engineered system conditions that affect thermal-hydrological (T-H) behavior in the unsaturated zone (UZ) at Yucca Mountain and how these effects are represented in mathematical and numerical models that are used to predict T-H conditions in the near field, altered zone, and engineered barrier system (EBS), and on waste package (WP) surfaces.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    PubMed

    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

  19. 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

  20. 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 parameters from the response and transformation routines (LSUZ, K1, K0 and bmax) have a significant influence on the peak flows. It is observed that the parameters of snow routine (Tmelt, CSF and DDF) have strong effect in high flows and total volume. The parameters FC, K0, K1 And K2 are found to have effect on low flows from the signature metrics.

  1. a statistical model based on serological parameters for predicting occult HBV infection: implications for organ/ blood donations.

    PubMed

    Coen, Sabrina; Angeletti, Claudio; Piselli, Pierluca; Tronchin, Michele; Vincenti, Donatella; Capobianchi, Maria Rosaria; Galli, Claudio; Menzo, Stefano

    2015-01-01

    The transmission of hepatitis B virus by donors with occult HBV infection (OBI) is a threat for blood transfusion and organ/tissue transplantation. The risk of carrying HBV DNA is currently not predictable by simple serologic markers, while HBV DNA testing is not universally deployed. This study evaluated an integrated serologic approach for assessing this risk. Anti-HBc positive subjects (461 HIV-negative, 262 HIV-positive) were selected for the study. Serology was analyzed by a commercial CMIA technique. HBV DNA was analyzed by both commercial and home-brew real-time amplification assays. A penalized maximum likelihood logistic approach was used to analyze the data. In HBsAg-negative subjects (HIV-negative), anti-HBc signal/cut off values, the presence of anti-HBc IgM, the absence of anti-HBsAg, and the absence of anti-HCV were correlated to the probability of finding circulating HBV DNA. A model for predicting HBV DNA presence by 4 serological parameters is therefore proposed. The predictive value of the logistic model based on simple serologic markers may represent a reasonable tool for the assessment of HBV transmission risk by transfusion or organ/tissue donation in the context of limited resources and where nucleic acid testing is not performed. In addition, it may be helpful for assessing the risk of reactivation in immunosuppressed OBI patients. PMID:25742146

  2. Teaching hydrological modeling with a user-friendly catchment-runoff-model software package

    NASA Astrophysics Data System (ADS)

    Seibert, J.; Vis, M. J. P.

    2012-05-01

    Computer models, and especially conceptual models, are frequently used for catchment hydrology studies. Teaching hydrological modeling, however, is challenging as students, when learning to apply computer models, have both to understand general model concepts and to be able to use particular computer programs. Here we present a new version of the HBV model. This software provides a user-friendly version which is especially useful for education. Different functionalities like an automatic calibration using a genetic algorithm or a Monte Carlo approach as well as the possibility to perform batch runs with predefined model parameters make the software also interesting for teaching in more advanced classes and research projects. Different teaching goals related to hydrological modeling are discussed and a series of exercises is suggested to reach these goals.

  3. Teaching hydrological modeling with a user-friendly catchment-runoff-model software package

    NASA Astrophysics Data System (ADS)

    Seibert, J.; Vis, M. J. P.

    2012-09-01

    Computer models, especially conceptual models, are frequently used for catchment hydrology studies. Teaching hydrological modeling, however, is challenging, since students have to both understand general model concepts and be able to use particular computer programs when learning to apply computer models. Here we present a new version of the HBV (Hydrologiska Byråns Vattenavdelning) model. This software provides a user-friendly version that is especially useful for education. Different functionalities, such as an automatic calibration using a genetic algorithm or a Monte Carlo approach, as well as the possibility to perform batch runs with predefined model parameters make the software interesting especially for teaching in more advanced classes and research projects. Different teaching goals related to hydrological modeling are discussed and a series of exercises is suggested to reach these goals.

  4. 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.

  5. Virtual hydrology observatory: an immersive visualization of hydrology modeling

    NASA Astrophysics Data System (ADS)

    Su, Simon; Cruz-Neira, Carolina; Habib, Emad; Gerndt, Andreas

    2009-02-01

    The Virtual Hydrology Observatory will provide students with the ability to observe the integrated hydrology simulation with an instructional interface by using a desktop based or immersive virtual reality setup. It is the goal of the virtual hydrology observatory application to facilitate the introduction of field experience and observational skills into hydrology courses through innovative virtual techniques that mimic activities during actual field visits. The simulation part of the application is developed from the integrated atmospheric forecast model: Weather Research and Forecasting (WRF), and the hydrology model: Gridded Surface/Subsurface Hydrologic Analysis (GSSHA). Both the output from WRF and GSSHA models are then used to generate the final visualization components of the Virtual Hydrology Observatory. The various visualization data processing techniques provided by VTK are 2D Delaunay triangulation and data optimization. Once all the visualization components are generated, they are integrated into the simulation data using VRFlowVis and VR Juggler software toolkit. VR Juggler is used primarily to provide the Virtual Hydrology Observatory application with fully immersive and real time 3D interaction experience; while VRFlowVis provides the integration framework for the hydrologic simulation data, graphical objects and user interaction. A six-sided CAVETM like system is used to run the Virtual Hydrology Observatory to provide the students with a fully immersive experience.

  6. 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.

  7. Many-Criterion Calibration of Hydrologic Models Using Hydrological Signatures

    NASA Astrophysics Data System (ADS)

    Shafii, M.; Tolson, B.

    2014-12-01

    Experts have used a variety of techniques for calibration of hydrologic models including optimization-based and Bayesian methods. The simulated outcome of calibrated hydrologic models should be consistent with both the measured response data and the catchment's hydrological behaviour. The literature indicates that, due to the computational issues associated with many-criterion optimization-based calibration, calibration experiments start by the optimization against performance metrics, e.g., the Nash-Sutcliffe Efficiency measure, and are followed by the evaluation of the results with respect to hydrological signatures, e.g., the flow duration curve indices, to verify the hydrological consistency of the obtained parameter sets. The proposed research develops a full multi-criterion calibration framework that is capable of utilizing many goodness-of-fit and hydrological signature-based measures to locate the hydrologically consistent parameter sets. This calibration approach applies optimization concepts to facilitate the parameters search, and moreover, implements experts' priorities in terms of the level of acceptability for each calibration measure. The preliminary results demonstrate that the proposed many-criterion calibration approach yields a higher proportion of hydrologically consistent parameter sets in comparison to the traditional approaches in the literature. The proposed approach can be extended to other calibration studies where the modeller has specific targets for individual calibration criteria.

  8. Rangeland Hydrology and Erosion Model

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Wi, S.; Brown, C. M.

    2013-12-01

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

  10. 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.

  11. 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, 2013. [3] N., Kayastha, J. Ye, F. Fenicia, V. Kuzmin, and D. P. Solomatine. Fuzzy committees of specialized rainfall-runoff models: further enhancements and tests. Hydrol. Earth Syst. Sci., 17, 4441-4451, 2013

  12. 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

  13. The Central Valley Hydrologic Model

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  14. 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

  15. 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).

  16. General and Abdominal Adiposity and Risk of Death in HBV Versus Non-HBV Carriers

    PubMed Central

    Lin, Wen-Yuan; Peng, Cheng-Yuan; Lin, Cheng-Chieh; Davidson, Lance E.; Pi-Sunyer, F. Xavier; Sung, Pei-Kun; Huang, Kuo-Chin

    2016-01-01

    Abstract Both obesity and hepatitis B virus (HBV) infection increase the risk of death. We investigate the association between general and central obesity and all-cause mortality among adult Taiwanese HBV versus non-HBV carriers. A total of 19,850 HBV carriers and non-hepatitis C virus (HCV) carriers, aged 20 years and older at enrollment in 1998 to 1999 in Taiwan, were matched to 79,400 non-HBV and non-HCV carriers (1:4). Cox proportional-hazards models were used to estimate the relative risks for all-cause mortality during a maximum follow-up period of 10 years. Four obesity-related anthropometric indices—body mass index (BMI), waist circumference, waist-to-hip ratio, and waist-to-height ratio—were the main variables of interest. During the follow-up period, 628 and 2366 participants died among HBV and non-HBV carriers, respectively. Both underweight and general obesity were associated with an increased risk of death. The highest risk of all-cause death in relation to BMI was found in the HBV carriers with underweight (BMI <18.5 kg/m2) and non-HBV carriers with obesity (BMI ≥30 kg/m2). The lowest risks of all-cause death in relation to abdominal adiposity were found at the third quartiles of waist circumference, waist-to-hip ratio, and waist-to-height ratio among HBV carriers, but in the second quartiles among non-HBV carriers. For those with pre-existing liver disease among HBV carriers, patients with underweight have higher risk of death than those with obesity. Hepatitis B virus carriers with underweight have higher risk of death than non-HBV carriers. HBV carriers with mild abdominal obesity have the lowest risk of death, but not in the non-HBV carriers. PMID:26765398

  17. Snow hydrology in a general circulation model

    SciTech Connect

    Marshall, S. ); Roads, J.O. ); Glatzmaier, G. )

    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. A 3-year GCM simulation with this 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. 52 refs., 13 figs., 5 tabs.

  18. 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.

  19. 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.

  20. Multivariable, Multiprocess Validation of Hydrological Models

    NASA Astrophysics Data System (ADS)

    Lakshmi, V.

    2001-12-01

    Hydrological models use a variety of parameters, inputs and variables of which some variables are model computed outputs. In the case of hydrological models that have water balance modules only, we can compare the computed streamflow to the observed discharges at stream gauge locations and the computed soil moisture to observed soil moisture (if available). If the hydrological model has energy balance modules, the output surface temperatures can be compared with (satellite) observed quantities. In this paper, we examine (using several examples), the validation of hydrological processes using a combination of in-situ, and satellite data. In addition, we use the simple principles of mass and energy balance to undertake hydrological data assimilation so as to better predict mass and energy fluxes. A fully integrated hydrological modeling framework is envisaged to be consist of (a) simple water and energy budgets along with process parameterization (b) remote sensing data for a distributed approach as well as for validation (c) simple assimilation for adjustment of output variables to reflect inaccuracies in modeling

  1. 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.

  2. 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.

  3. Do we need a Community Hydrological Model?

    NASA Astrophysics Data System (ADS)

    Weiler, Markus; Beven, Keith

    2015-09-01

    We believe that there are too many models in hydrology and we should ask ourselves the question, if we are currently wasting time and effort in developing another model again instead of focusing on the development of a Community Hydrological Model. In other fields, this kind of models has been quite successful, but due to several reasons, no single community model has been developed in the field of hydrology yet. The concept, strength, and weakness of a community model were discussed at the Chapman Conference on Catchment Spatial Behaviour and Complex Organisation held in Luxembourg in September 2014. This discussion as well as our own opinions about the potential of a community models or at least the necessary discussion to establish one are debated in this commentary.

  4. 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)

  5. HBV-DNA levels predict overall mortality in HIV/HBV coinfected individuals.

    PubMed

    Nikolopoulos, Georgios K; Paraskevis, Dimitrios; Psichogiou, Mina; Hatzakis, Angelos

    2016-03-01

    The coinfection of Hepatitis B virus (HBV) and human immunodeficiency virus (HIV) has been associated with increased death rates. However, the relevant research has mostly relied on serologic HBV testing [HBV surface antigen (HBsAg)]. The aim of this work was to explore the relationship of HBV viraemia with overall mortality among HIV/HBV coinfected individuals. The analysis included 1,609 HIV seropositives of a previously described cohort (1984-2003) with limited exposure to tenofovir (12%) and a median follow-up of approximately 5 years. Those with persistent expression of HBsAg were further tested for HBV-DNA. The data were analyzed using Poisson regression models. Totally, 101 participants were chronic carriers of HBsAg (6.28%). Of these, 81 were tested for HBV-DNA. The median HBV-DNA levels were 3.81 log (base-10) International Units (IU)/ml. A third (31%) of those tested for HBV-DNA had received tenofovir. Before developing acquired immune deficiency syndrome (AIDS), the adjusted incidence rate ratio (IRR) for all-cause mortality of coinfected patients with HBV viraemia above the median value versus the HIV monoinfected group was 3.44 [95% confidence interval (CI): 1.05-11.27]. Multivariable regressions in the coinfected group only (n?=?81) showed that one log-10 increase in HBV-DNA levels was associated with an elevated risk for death (IRR: 1.24, 95%CI: 1.03-1.49). HBV-DNA levels predict overall mortality in the setting of HIV/HBV coinfection, especially during the period before developing AIDS, and could thus help prioritize needs and determine the frequency of medical monitoring. J. Med. Virol. 88:466-473, 2016. 2015 Wiley Periodicals, Inc. PMID:26288334

  6. Teaching hydrological modelling as a subsidiary subject

    NASA Astrophysics Data System (ADS)

    Hörmann, G.; Schmalz, B.; Fohrer, N.

    2009-04-01

    The department of hydrology and water resources management is part of the Ecology Center of Kiel University, an interdisciplinary research organization. We teach hydrology for geographers, biologists, agricultural engineers and ecologists. Hydrological modeling is part of the curriculum since 1988. It has moved from the subject for specialists to a basic component of all hydrological courses. During the first year, we focussed on in-depth teaching of theory and practice of one big model, but the students found it hard to follow and beyond practical problems. During the last years we switched to a broader, but more shallow policy. Modeling is now part of nearly all courses, but remains limited to mostly 2-4 days of teaching. We now present only very basic theory and leave it to the students to discover the details during the practical work with pre-installed data sets. The poster shows how the models SWAT, Hydrus, Coupmodel, SIMPEL and PC-Raster are embedded in the hydrological curriculum and what kind of problems we experienced in teaching.

  7. 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 adequately in all periods or on all criteria. Subsequently, improved model structures are constructed and the evaluation repeated. We conclude that a dynamic, multi-criteria approach to model identifying and testing is effective in constructing models that are more accurate and precise in forecasting streamflow.

  8. 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.

  9. Parameterization guidelines and considerations for hydrologic models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Imparting knowledge of the physical processes of a system to a model and determining a set of parameter values for a hydrologic or water quality model application (i.e., parameterization) is an important and difficult task. An exponential increase in literature has been devoted to the use and develo...

  10. 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 ...

  11. 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.

  12. 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 alternative local sensitivity analysis methods. The latter methods can yield similar results, however they are much more computationally frugal than the global methods and often are better suited to analysis of complex models. Simple models are used to compare the global and local methods, and insights used to interpret results for complex model for which the local methods are much more convenient. The analyses are carried out for a medium-sized catchment (200 km2) in the Belgian Ardennes, for which meteorological, fluxnet data, in situ soil moisture and groundwater time series are available.

  13. 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.

  14. 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 ...

  15. 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 Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened.

  16. Revising Hydrology of a Land Surface Model

    NASA Astrophysics Data System (ADS)

    Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher

    2015-04-01

    Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.

  17. 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.

  18. 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 for catchment description and clustering. Hence, the classes do not only represent a distinctive hydrological regime, but also provide information on specific quantitative aspects that are directly linked to a certain model structure. The clustering that is based on model structures or model parameters are validated by the classifications based on SOM and are thus related to physiographic and climatic catchment properties and runoff behaviour, which provides insight into catchment functioning. Clustering based on model structures can be a fast and simple way of catchment classification. A database consistently relates input data and output data; model structures and model performance and allows formulating distinctive processes that are attached to a class. Thus, the final result of the study is a powerful classification tool that helps to formulate generalizations based on observations and testable hypotheses (i.e. model structures).

  19. 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.

  20. 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.

  1. 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 for fibrosis need further external validation in a large population before it was used for prediction of fibrosis in patients with HBV infection. PMID:27050531

  2. 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-step feedbacks. There was no obvious way to add daily time-step feedbacks without incurring a considerable performance penalty. The Delft-FEWS system connects hydrological models for flood warnings and forecasts in a workflow system. It provides a range of custom facilities for connecting real-time data services. A Delft-FEWS system was constructed to connect a series of eWater Source hydrological models using the batch forecast mode to orchestrate a time-stepping system. The system coupled a series of river models running daily through a service interface. The implementation did not easily support interoperability with other models; however, using command line calls and the file-system did allow a level of language independence. The case-studies covered the coupling of hydrological models through tight interfaces (OpenMI), broad scientific workflow software (Trident) and a tailored execution engine (Delft-FEWS). We found that no approach was objectively better than any other approach. OpenMI had the most flexible interfaces, Trident the best handling of provenance and Delft-FEWS provided a significant set of tools for ingesting and transforming data. The case studies revealed a need for stable execution wrappers, patterns for efficient cross-language interoperability, targeted semantics for hydrological simulation and better handling of daily simulation.

  3. Inactivated ORF virus shows antifibrotic activity and inhibits human hepatitis B virus (HBV) and hepatitis C virus (HCV) replication in preclinical models.

    PubMed

    Paulsen, Daniela; Urban, Andreas; Knorr, Andreas; Hirth-Dietrich, Claudia; Siegling, Angela; Volk, Hans-Dieter; Mercer, Andrew A; Limmer, Andreas; Schumak, Beatrix; Knolle, Percy; Ruebsamen-Schaeff, Helga; Weber, Olaf

    2013-01-01

    Inactivated orf virus (iORFV), strain D1701, is a potent immune modulator in various animal species. We recently demonstrated that iORFV induces strong antiviral activity in animal models of acute and chronic viral infections. In addition, we found D1701-mediated antifibrotic effects in different rat models of liver fibrosis. In the present study, we compare iORFV derived from two different strains of ORFV, D1701 and NZ2, respectively, with respect to their antifibrotic potential as well as their potential to induce an antiviral response controlling infections with the hepatotropic pathogens hepatitis C virus (HCV) and hepatitis B virus (HBV). Both strains of ORFV showed anti-viral activity against HCV in vitro and against HBV in a transgenic mouse model without signs of necro-inflammation in vivo. Our experiments suggest that the absence of liver damage is potentially mediated by iORFV-induced downregulation of antigen cross-presentation in liver sinus endothelial cells. Furthermore, both strains showed significant anti-fibrotic activity in rat models of liver fibrosis. iORFV strain NZ2 appeared more potent compared to strain D1701 with respect to both its antiviral and antifibrotic activity on the basis of dosages estimated by titration of active virus. These results show a potential therapeutic approach against two important human liver pathogens HBV and HCV that independently addresses concomitant liver fibrosis. Further studies are required to characterize the details of the mechanisms involved in this novel therapeutic principle. PMID:24066148

  4. 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. In addition can be stated that the loss of detention due to land use and dikes can be called an externality and results in economic inefficiencies.

  5. 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 to sue a dynamic averaging scheme to generate the final output. [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. A novel approach to parameter uncertainty analysis of hydrological models using neural networks. Hydrol. Earth Syst. Sci., 13, 1235-1248, 2009.

  6. Debates—Perspectives on socio-hydrology: Socio-hydrologic modeling: Tradeoffs, hypothesis testing, and validation

    NASA Astrophysics Data System (ADS)

    Troy, Tara J.; Pavao-Zuckerman, Mitchell; Evans, Tom P.

    2015-06-01

    Socio-hydrology focuses on studying the dynamics and co-evolution of coupled human and water systems. Recently, several new socio-hydrologic models have been published that explore these dynamics, and these models offer unique opportunities to better understand these coupled systems and to understand how water problems evolve similarly in different regions. These models also offer challenges, as decisions need to be made by the modeler on trade-offs between generality, precision, and realism. In addition, traditional hydrologic model validation techniques, such as evaluating simulated streamflow, are insufficient, and new techniques must be developed. As socio-hydrology progresses, these models offer a robust, invaluable tool to test hypotheses about the relationships between aspects of coupled human-water systems. They will allow us to explore multiple working hypotheses to greatly expand insights and understanding of coupled socio-hydrologic systems.

  7. 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 response is highly nonlinear. Higher-order approximations can provide more accurate estimations, but reduce the numerical advantage of the LiM. The results of the uncertainty analysis identify the main sources of uncertainty in the computation of river discharge. In this particular case the spatial variability of rainfall and the model parameters uncertainty are shown to have the greatest impact on discharge evaluation. This, in turn, highlights the need to support any estimated hydrological response with probability information and risk analysis results in order to provide a robust, systematic framework for decision making.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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)

  15. 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 defined as objective functions individually and collectively. Additionally discharge data, representing a different observational dataset, is included in the optimization process which enables a multi constrained evaluation of the model. This allows testing different optimization frameworks under consideration of observable spatial patterns and discharge data which represents a spatially aggregated catchment observation.

  16. 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 calculated by the water use models. Simulated discharges for the period 1958-2001 are evaluated against more than 1500 observed discharge records provided by the Global Runoff Data Centre (GRDC). Globally, the selected gauging stations differ substantially in terms of upstream area (3000 -- 3.6 mill sqkm) and their available time series (between 5 and > 100 yrs). We assess the model performance by applying complementary metrics such as Nash-Sutcliffe-Efficiency or water balance related coefficients. Moreover, based on these metrics, we investigate if and how physiographic catchment characteristics and climate conditions impact model efficiency and identify possible underlying determinants of spatial patterns of model performance.

  17. 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.

  18. 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 forecasts and initial model conditions.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  1. A Novel Approach to Parameter Identification for Distributed Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Gupta, H.; Durcik, M.; Wagener, T.

    2007-12-01

    The demands on, and interest in, distributed hydrologic models have increased considerably in recent years. However, most parameters used in hydrologic models (especially those of the "conceptual" type) do not correlate strongly with measurable physical quantities and therefore cannot be directly derived from field observations. Since applying a model in a distributed fashion significantly increases the number of model parameters, the development and implementation of parameter identification strategies represent a real challenge for distributed hydrologic modeling. In this presentation, we discuss a novel methodology for distributed hydrologic parameter identification based on the classification of hydrologic landscapes (HL), which reflect the dominant controls on the fundamental hydrologic processes and therefore arguably the major system parameters. The HL-based approach proposed here is computationally inexpensive and holds promise for making improved predictions in ungaged basins. Applications of this new approach to distributed modeling in river basins in the US Southwest will be presented and discussed.

  2. 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.

  3. Plant growth simulation for landscape scale hydrologic modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Landscape scale hydrologic models can be improved by incorporating realistic, process-oriented plant models for simulating crops, grasses, and woody species. The objective of this project was to present some approaches for plant modeling applicable to hydrologic models like SWAT that can affect the...

  4. 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.

  5. 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): 215-224. [2] McClintock B. The significance of responses of the genome to challenge. Science 1984; 226: 792-801 [3] Ries G, Heller W, Puchta H, Sandermann H, Seldlitz HK, Hohn B. Elevated UV-B radiation reduces genome stability in plants. Nature 2000; 406: 98-101 [4] Lucht JM, Mauch-Mani B, Steiner H-Y, Metraux J-P, Ryals, J, Hohn B. Pathogen stress increases somatic recombination frequency in Arabidopsis. Nature Genet. 2002; 30: 311-314 [5] Kovalchuk I, Kovalchuk O, Kalck V., Boyko V, Filkowski J, Heinlein M, Hohn B. Pathogen-induced systemic plant signal triggers DNA rearrangements. Nature 2003; 423: 760-762 [6] Cullis C A. Mechanisms and control of rapid genomic changes in flax. Ann. Bot. (Lond.) 2005; 95: 201-206 [7] de Rosnay, P. and J. Polcher. 1998. Modelling root water uptake in a complex land surface scheme coupled to a GCM. Hydrology and Earth System Sciences 2: 239-255. [8] Feddes, R.A., H. Hoff, M. Bruen, T. Dawson, P. de Rosnay, P. Dirmeyer, R.B. Jackson, P. Kabat, A. Kleidon, A. Lilly, and A.J. Pitman. 2001. Modeling root water uptake in hydrological and climate models. Bulletin of the American Meteorological Society 82: 2797-2809. [9] Jung, M., M. Reichstein, P. Ciais, S.I. Seneviratne, J. Sheffield et al. 2010. Recent decline in the global land evaporation trend due to limited moisture supply. Nature 476: 951-954, doi:10.1038/nature09396.

  6. Hydrological modelling in sandstone rocks watershed

    NASA Astrophysics Data System (ADS)

    Ponilov, Iva; Unucka, Jan

    2015-04-01

    The contribution is focused on the modelling of surface and subsurface runoff in the Plou?nice 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 Plou?nice basin. The Plou?nice 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 Plou?nice basin is 72. The geological structure of the Plou?nice 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 this extreme event. The increase of the baseflow runoff is slower and remains constant after reaching a certain level. The rise of the baseflow runoff is showed in a descending part of the hydrograph. The recession method in this case shows almost 20 hours delay. Results from the HEC-HMS prove availability of both methods for the runoff modeling in this type of catchment. When simulating extreme short-term rainfall-runoff episodes, the influence of geological subsurface is not significant, but it is manifested. Using more relevant rainfall events would bring more satisfactory results.

  7. Evaluating snow models for hydrological applications

    NASA Astrophysics Data System (ADS)

    Jonas, T.; Magnusson, J.; Wever, N.; Essery, R.; Helbig, N.

    2014-12-01

    Much effort has been invested in developing snow models over several decades, resulting in a wide variety of empirical and physically-based snow models. Within the two categories, models are built on the same principles but mainly differ in choices of model simplifications and parameterizations describing individual processes. In this study, we demonstrate an informative method for evaluating a large range of snow model structures for hydrological applications using an existing multi-model energy-balance framework and data from two well-instrumented sites with a seasonal snow cover. We also include two temperature-index snow models and one physically-based multi-layer snow model in our analyses. Our results show that the ability of models to predict snowpack runoff is strongly related to the agreement of observed and modelled snow water equivalent whereas such relationship is not present for snow depth or snow surface temperature measurements. For snow water equivalent and runoff, the models seem transferable between our two study sites, a behaviour which is not observed for snow surface temperature predictions due to site-specificity of turbulent heat transfer formulations. Uncertainties in the input and validation data, rather than model formulation, appear to contribute most to low model performances in some winters. More importantly, we find that model complexity is not a determinant for predicting daily snow water equivalent and runoff reliably, but choosing an appropriate model structure is. Our study shows the usefulness of the multi-model framework for identifying appropriate models under given constraints such as data availability, properties of interest and computational cost.

  8. 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.

  9. 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.

  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. 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.

  12. 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 combined into a robust and fast data cleansing and interpolation system. One experience from this work is that advanced interpolation techniques (kriging), do not outperform calibrated inverse distance methods when also computational speed is used as a criteria for model selection. The paper also discusses several challenges related to uncertainty in simulated snow reservoir, regionalization of parameters, choice of spatial resolution, techniques for reducing computational needs without compromising information needs, amongst others.

  13. 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

  14. 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...

  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. 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...

  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 supplies. This distinction between the two policies was not apparent using a traditional non-coupled model.

  19. 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

  20. Hydrologic modeling across climates, and space scales

    NASA Astrophysics Data System (ADS)

    Vinogradov, Y. B.; Semenova, O. M.; Restrepo, P. J.

    2009-12-01

    This presentation will address several specific and general scientific hydrology questions such as the problem of heterogeneity of landscapes and its representation in the models. The essential fundamentals of physics suggest that the process of runoff formation must be the same in any point of space, implying the possibility to simulate them in any watershed within the framework of a universal methodological approach, its mathematical realization and unified informational support. The presentation will explain the basic concepts behind the Hydrograph model, a distributed model with physically based parameters, which is being developed based on the principle of universality. The model’s universality can be measured only by its performance over basins of any type, regardless of their scale and landscape/climate characteristics. This presentation reports the model performance for watersheds ranging from small, experimental watersheds to large river basins with areas in excess of 2 M km2, and from climates ranging from the snow-dominated plains and mountainous basins of Russia and the US, to the tropical lowland climate of Angola and the high-precipitation, high-mountains of Central and South America.

  1. 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

  2. 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)

  3. 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.

  4. Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1997-01-01

    Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

  5. 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

  6. 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 has proven to be successful with regards to the case study, some limitations are worth noting. If this is going to be applied to the more general case of 'models of everywhere', for instance, there could be dominant processes not described in the FUSE framework. Further studies could therefore extend the current framework to include routines able to simulate missing processes.

  7. FIELD AND POND HYDROLOGIC ANALYSES WITH THE SPAW MODEL

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The SPAW (Soil-Plant-Air-Water) computer model simulates the daily hydrology of agricultural fields and ponds including wetlands, lagoons and reservoirs. Field hydrology is represented by daily climatic descriptions of rainfall, temperature and evaporation; a layered soil profile with automated wat...

  8. 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

  9. Hydrology

    USGS Publications Warehouse

    Eisenbies, Mark H.; Hughes, W. Brian

    2000-01-01

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

  10. 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, for example, a) to investigate the influence of the antecedent soil moisture on extreme floods in Germany (2002 and 2013), b) for establishing benchmark agricultural drought events for Germany since 1950. A 60-year reconstruction of the daily mHM soil moisture fields over Germany at high resolution 4 × 4 km2 was used for this purpose, and c) to investigate the potential benefits of a high resolution modeling approach for the drought monitoring and forecasting system over Pan-EU. We invite the community to take advantage of this open-source code which is freely available (after nominal registration) at: http://www.ufz.de/index.php?en=31389.

  11. 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 catchment. The classified landscapes were used to assign different model structures to the individual hydrological response units. As an example deep percolation was defined as dominant process for plateaus, rapid subsurface flow as dominant process for hillslopes and saturation overland flow as dominant process for wetlands. The modeled runoffs from each hydrological unit were combined in a parallel set-up to proportionally contribute to the total catchment runoff. The hydrological units are, in addition, linked by a common groundwater reservoir. The parallel hydrological units, although increasing the number of parameters, have the benefit of comparative calibration. As an example, one may consider the lag time of wetland to be shorter than the lag time of water traveling to the outlet from a plateau. Moreover, due to the dominance of forest on hillslopes in this catchment, hillslope interception should be higher than interception on plateaus which are mainly used for agriculture in the Wark catchment. Furthermore fluxes and processes can be compared. For example, actual evaporation from wetland can potentially be higher than other entities within a catchment as wetland is water logged and evaporation thus less supply limited than on plateaus. To include all the comparisons and criteria in calibration, an evolutionary algorithm was used. The algorithm was adapted and applied in a way that in subsequent steps more and more comparative criteria are forced to be satisfied. At the end of the calibration it is expected that all the criteria should be satisfied. Including landscape classification into hydrological models seems to be a powerful tool which not only allows to consider and to make use of crucial feedback processes controlling the evolution of the hydrological system together with the eco-system but may also lead to more detailed information on how a catchment may work than a simple lumped model.

  12. Discharge simulations performed with a hydrological model using bias corrected regional climate model input

    NASA Astrophysics Data System (ADS)

    van Pelt, S. C.; Kabat, P.; Ter Maat, H. W.; van den Hurk, B. J. J. M.; Weerts, A. H.

    2009-06-01

    Studies have demonstrated that precipitation on Northern Hemisphere mid-latitudes has increased in the last decades and that it is likely that this trend will continue. This will have an influence on discharge of the river Meuse. The use of bias correction methods is important when the effect of precipitation change on river discharge is studied. The objective of this paper is to investigate the effect of using two different bias correction methods on output from a Regional Climate Model (RCM) simulation. In this study a Regional Atmospheric Climate Model (RACMO2) run is used, forced by ECHAM-5 under the condition of the SRES-A1B emission scenario, with a 25 km horizontal resolution. The RACMO2 runs contain a systematic precipitation bias on which two bias correction methods are applied. The first method corrects for the wet day fraction and wet day average (WD bias correction) and the second method corrects for the mean and coefficient of variance (MV bias correction). The WD bias correction initially corrects well for the average, but it appears that too many successive precipitation days were removed with this correction. The second method performed less well on average bias correction, but the temporal precipitation pattern was better. Subsequently, the discharge was calculated by using RACMO2 output as forcing to the HBV-96 hydrological model. A large difference was found between the simulated discharge of the uncorrected RACMO2 run, the WD bias corrected run and the MV bias corrected run. These results show the importance of an appropriate bias correction.

  13. Discharge simulations performed with a hydrological model using bias corrected regional climate model input

    NASA Astrophysics Data System (ADS)

    van Pelt, S. C.; Kabat, P.; Ter Maat, H. W.; van den Hurk, B. J. J. M.; Weerts, A. H.

    2009-12-01

    Studies have demonstrated that precipitation on Northern Hemisphere mid-latitudes has increased in the last decades and that it is likely that this trend will continue. This will have an influence on discharge of the river Meuse. The use of bias correction methods is important when the effect of precipitation change on river discharge is studied. The objective of this paper is to investigate the effect of using two different bias correction methods on output from a Regional Climate Model (RCM) simulation. In this study a Regional Atmospheric Climate Model (RACMO2) run is used, forced by ECHAM5/MPIOM under the condition of the SRES-A1B emission scenario, with a 25 km horizontal resolution. The RACMO2 runs contain a systematic precipitation bias on which two bias correction methods are applied. The first method corrects for the wet day fraction and wet day average (WD bias correction) and the second method corrects for the mean and coefficient of variance (MV bias correction). The WD bias correction initially corrects well for the average, but it appears that too many successive precipitation days were removed with this correction. The second method performed less well on average bias correction, but the temporal precipitation pattern was better. Subsequently, the discharge was calculated by using RACMO2 output as forcing to the HBV-96 hydrological model. A large difference was found between the simulated discharge of the uncorrected RACMO2 run, the WD bias corrected run and the MV bias corrected run. These results show the importance of an appropriate bias correction.

  14. 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

  15. 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

  16. 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.

  17. Evaluating the performance in the Swedish operational hydrological forecasting systems

    NASA Astrophysics Data System (ADS)

    Pechlivanidis, Ilias; Bosshard, Thomas; Spångmyr, Henrik; Lindström, Göran; Olsson, Jonas; Arheimer, Berit

    2014-05-01

    The production of hydrological forecasts generally involves the selection of model(s) and setup, calibration and initialization, verification and updating, generation and evaluation of forecasts. Although, field data are commonly used to calibrate and initiate hydrological models, technological advancements have allowed the use of additional information, i.e. remote sensing data and meteorological ensemble forecasts, to improve hydrological forecasts. However, the precision of hydrological forecasts is often subject to uncertainty related to various components of the production chain and data used. The Swedish Meteorological and Hydrological Institute (SMHI) operationally produces hydrological medium-range forecasts in Sweden using two modeling systems based on the HBV and S-HYPE hydrological models. The hydrological forecasts use both deterministic and ensemble (in total 51 ensemble members which are further reduced to 5 statistical members; 2, 25, 50, 75, 98% percentiles) meteorological forecasts from ECMWF to add information on the uncertainty of the predicted values. In this study, we evaluate the performance of the two operational hydrological forecasting systems and identify typical uncertainties in the forecasting production chain and ways to reduce them. In particular, we investigate the effect of autoregressive updating of the forecasted discharge, and of using the median of the ensemble instead of deterministic forecasts. Medium-range (10 days) hydrological forecasts across 71 selected indicator stations are used. The Kling-Gupta Efficiency and its decomposed terms are used to analyse the performance in different characteristics of the flow signal. Results show that the HBV and S-HYPE models with AR updating are both capable of producing adequate forecasts for a short lead time (1 to 2 days), and the performance steadily decreases in lead time. The autoregressive updating method can improve the performance of the two systems by 30 to 40% in terms of the KGE. This is mainly because the method has a significant impact on the improvement of discharge volume. S-HYPE seems to perform slightly better than HBV in the longer lead time, probably because the S-HYPE system is capable of updating the lake water level, which has an impact on the longer lead times. Moreover, the deterministic and ensemble HBV systems with AR updating perform fairly similar for all lead times. Keywords: Hydrological forecasting, S-HYPE, HBV, Operational production, Kling-Gupta Efficiency, Uncertainty.

  18. General and Abdominal Adiposity and Risk of Death in HBV Versus Non-HBV Carriers: A 10-Year Population-based Cohort Study.

    PubMed

    Lin, Wen-Yuan; Peng, Cheng-Yuan; Lin, Cheng-Chieh; Davidson, Lance E; Pi-Sunyer, F Xavier; Sung, Pei-Kun; Huang, Kuo-Chin

    2016-01-01

    Both obesity and hepatitis B virus (HBV) infection increase the risk of death. We investigate the association between general and central obesity and all-cause mortality among adult Taiwanese HBV versus non-HBV carriers.A total of 19,850 HBV carriers and non-hepatitis C virus (HCV) carriers, aged 20 years and older at enrollment in 1998 to 1999 in Taiwan, were matched to 79,400 non-HBV and non-HCV carriers (1:4). Cox proportional-hazards models were used to estimate the relative risks for all-cause mortality during a maximum follow-up period of 10 years. Four obesity-related anthropometric indices-body mass index (BMI), waist circumference, waist-to-hip ratio, and waist-to-height ratio-were the main variables of interest.During the follow-up period, 628 and 2366 participants died among HBV and non-HBV carriers, respectively. Both underweight and general obesity were associated with an increased risk of death. The highest risk of all-cause death in relation to BMI was found in the HBV carriers with underweight (BMI <18.5 kg/m2) and non-HBV carriers with obesity (BMI ≥30 kg/m2). The lowest risks of all-cause death in relation to abdominal adiposity were found at the third quartiles of waist circumference, waist-to-hip ratio, and waist-to-height ratio among HBV carriers, but in the second quartiles among non-HBV carriers. For those with pre-existing liver disease among HBV carriers, patients with underweight have higher risk of death than those with obesity.Hepatitis B virus carriers with underweight have higher risk of death than non-HBV carriers. HBV carriers with mild abdominal obesity have the lowest risk of death, but not in the non-HBV carriers. PMID:26765398

  19. Common Research Framework for Global Hydrology Utilizing Various Datasets and Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Kim, H.; Oki, T.; Kanae, S.; Seto, S.

    2008-12-01

    A flexible research framework is developed for common needs in global hydrological research. This framework consists of five components including input/output (I/O) interfaces, models, analyzers, and publishers. Backbone chassis of this framework is developed using the Python, because it provides functionalities to wrap and integrate other languages. Global hydrologic simulation needs various dataset such as model forcing data, parameter sets, and validation data, and all of them are distributed in different formats. Therefore, I/O interfaces are implemented to handle different dataset uniformly. They does not only support various data format including text, binary, network common data form (netCDF), gridded binary (GRIB), and GTool, but also provide presets for many field/satellite observational datasets. Model part provides modulized models and interface generators for external numerical models. Noah land surface model and Total Runoff Integrated Pathway (TRIP) are modulized, and helper interfaces to manage an environment of numerical simulation projects including atmospheric and hydrologic models. The analyzer part and publisher consists of many small snippets and utilities to manipulate data with graphical user interface and to publish data on web or so. For computational efficiency, most of base components are written in native compiler languages such as Fortran and C with a wrapping tool F2py, and the Python array calculation module Numpy and plotting module matplotlib are heavily used. This framework solves many difficulties dramatically reducing required time and effort to prepare simulation and process result in the research of global hydrology.

  20. 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.

  1. 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.

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

    SciTech Connect

    Clark, Martyn P.; Fan, Ying; Lawrence, David M.; Adam, J. C.; Bolster, Diogo; Gochis, David; Hooper, Richard P.; Kumar, Mukesh; Leung, Lai-Yung R.; 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.

  3. 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.

  4. 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. ...

  5. Strategies to eliminate HBV infection

    PubMed Central

    Kapoor, Rama; Kottilil, Shyam

    2014-01-01

    Chronic HBV infection is a major public health concern affecting over 240 million people worldwide. Although suppression of HBV replication is achieved in the majority of patients with currently available newer antivirals, discontinuation of therapy prior to hepatitis B surface antigen loss or seroconversion is associated with relapse of HBV in the majority of cases. Thus, new therapeutic modalities are needed to achieve eradication of the virus from chronically infected patients in the absence of therapy. The basis of HBV persistence includes viral and host factors. Here, we review novel strategies to achieve sustained cure or elimination of HBV. The novel approaches include targeting the viral and or host factors required for viral persistence, and novel immune-based therapies, including therapeutic vaccines. PMID:25309617

  6. 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.

  7. Representing Watersheds with Physics Based Distributed Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Downer, C. W.; Ogden, F. L.

    2011-12-01

    Hydrologic models are useful tools for representing watershed response, helping to understand the dominant hydrologic processes in the watershed, and for estimating system response under different forcing, climatic, or physical conditions in the watershed. Model skill in predicting system response is most often demonstrated by history matching. Useful models for predicting system response under varying conditions must include the dominant processes controlling the system response. While many types of hydrologic models are capable of simulating watershed response, physics- based models are capable of simulating the actual physical conditions and responses within the watershed. There are a variety of physics-based hydrologic models available to the practicing community. Like simpler models, these models vary in formulation and complexity. Many of these models, such as the US Army of Corps of Engineers Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model, allow flexibility in terms of both processes simulated and the formulation used to approximate the process. This flexibility allows the user to build the model according to his or her understanding or conceptualization, of the system, including processes that are thought to be important to system response. This also allows the user to use more rigorous methods of simulating critical processes and less rigorous methods of simulating non-critical processes or when data limitations preclude the use of more rigorous methods. In this presentation we will discuss how physics based models can, and have, been used to describe various hydrologic systems to both represent the physical processes in the system and the system response. Using examples from a variety of applications we will demonstrate and discuss the utility of utilizing a flexible physics-based model design for realizing watershed conceptualizations for hydrologic analysis.

  8. Adaptive Parameter Optimization of a Grid-based Conceptual Hydrological Model

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

    Any spatially explicit hydrological model at the mesoscale is a conceptual approximation of the hydrological cycle and its dominant process occurring at this scale. Manual-expert calibration of this type of models may become quite tedious---if not impossible---taking into account the enormous amount of data required by these kind of models and the intrinsic uncertainty of both the data (input-output) and the model structure. Additionally, the model should be able to reproduce well several process which are accounted by a number of predefined objectives. As a consequence, some degree of automatic calibration would be required to find "good" solutions, each one constituting a trade-off among all calibration criteria. In other words, it is very likely that a number of parameter sets fulfil the optimization criteria and thus can be considered a model solution. In this study, we dealt with two research questions: 1) How to assess the adequate level of model complexity so that model overparameterization is avoided? And, 2) How to find a good solution with a relatively low computational burden? In the present study, a grid-based conceptual hydrological model denoted as HBV-UFZ based on some of the original HBV concepts was employed. This model was driven by 12~h precipitation, temperature, and PET grids which are acquired either from satellite products or from data of meteorological stations. In the latter case, the data was interpolated with external drift Kriging. The first research question was addressed in this study with the implementation of nonlinear transfer functions that regionalize most model parameters as a function of other spatially distributed observables such as land cover (time dependent) and other time independent basin characteristics such as soil type, slope, aspect, geological formations among others. The second question was addressed with an adaptive constrained optimization algorithm based on a parallel implementation of simulated annealing (SA). The main difference with the standard SA is the parameter search routine which uses adaptive heuristic rules to improve its efficiency. These rules are based on the relative behavior of the efficiency criteria. The efficiency of the model is evaluated with the Nash-Sutcliffe efficiency coefficient (NS) and the RMSE obtained for various short and long term runoff characteristics such as daily flows; semiannual high and low flow characteristics such as total drought duration frequency of high flows; and annual specific discharge at various gauging stations. Additionally, the parameter search was constrained with the 95% confidence bands of the runoff characteristics mentioned above. The proposed method was calibrated in the Upper Neckar River basin covering an area of approximately 4000~km2 during the period from 1961 to 1993. The spatial and temporal resolutions used were a grid size of (1000 × 1000)~m and 12~h intervals respectively. The results of the study indicate significant improvement in model performance (e.g. Nash-Sutcliffe of various runoff characteristics ~ 0.8) and a significant reduction in computational burden of at least 25%.

  9. 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 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 supplies. This distinction between the two policies was not apparent using a traditional noncoupled model.

  10. Multilayer Control Hierarchy in an Integrated Hydrological Model

    NASA Astrophysics Data System (ADS)

    Park, J.; Obeysekera, J.; Vanzee, R.

    2005-05-01

    Considerable progress has been made in the functionality of integrated hydrological models which can provide evaluation of anthropogenic control and management policies of water resources. Nonetheless, there is still room for improvement in the coupling and expression of water control policies into hydrological models [1]. The Management Simulation Engine (MSE) component of the Regional Simulation Model (RSM) incorporates a multi-level hierarchical control architecture which emphasizes the decoupling of hydrological state information from the management information processing applied to the states. The MSE is intended to allow a flexible, extensible expression of a wide variety anthropogenic water resource control schemes integrated with the hydrological state evaluations of the RSM. Synergy between the multilayer control hierarchy and decoupled hydrologic state and management information facilitates a water resource management feature set not typical of integrated hydrological models. Some of these features include: interoperation and compatibility of diverse management algorithms such as PID, Fuzzy control, LP; and dynamic switching of control processors. This paper describes the MSE control hierarchy with a focus on the aforementioned features and their implementation. [1] Belaineh, G., Peralta, R. C., Hughes, T. C., Simulation/ Optimization Modeling for Water Resources Management, ASCE Journal Water Resources Planning Management, 125(3), p 154-61, 1999

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    Sivapalan, Murugesu; Tian, Fuqiang; Liu, Dengfeng

    2013-04-01

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

  13. Climate noise effect on uncertainty of hydrological extremes: numerical experiments with hydrological and climate models

    NASA Astrophysics Data System (ADS)

    Gelfan, A. N.; Semenov, V. A.; Motovilov, Yu. G.

    2015-06-01

    An approach has been proposed to analyze the simulated hydrological extreme uncertainty related to the internal variability of the atmosphere ("climate noise"), which is inherent to the climate system and considered as the lowest level of uncertainty achievable in climate impact studies. To assess the climate noise effect, numerical experiments were made with climate model ECHAM5 and hydrological model ECOMAG. The case study was carried out to Northern Dvina River basin (catchment area is 360 000 km2), whose hydrological regime is characterised by extreme freshets during spring-summer snowmelt period. The climate noise was represented by ensemble ECHAM5 simulations (45 ensemble members) with identical historical boundary forcing and varying initial conditions. An ensemble of the ECHAM5-outputs for the period of 1979-2012 was used (after bias correction post-processing) as the hydrological model inputs, and the corresponding ensemble of 45 multi-year hydrographs was simulated. From this ensemble, we derived flood statistic uncertainty caused by the internal variability of the atmosphere.

  14. 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.

  15. Using satellite precipitation data for hydrological modeling

    NASA Astrophysics Data System (ADS)

    Commandeur, Tom

    2013-04-01

    The growing demand for precipitation data covering larger areas of the globe as lead to the need of innovative approaches to the operationalization of data streams. One possible classical solution is combining and calibrating various ground radar stations, however the availability and cost of these data streams work against its use for global coverage . The alternative is to use Earth Observation data from satellites. There is a wide range of weather data available from polar orbital satellites with sensors for measurements. The biggest advantage is that the spatial coverage is wide, however the temporal resolution for the covered area is more limited. To take advantage of the better of two worlds, geostationary satellites can be used to give the temporal resolution for the same covered area at a regular interval. EUMETSAT's Multi-Sensor Precipitation Estimate (MPE) is based on a classical blending algorithm. This algorithm combines SSM/I instruments on DMSP satellites with the 10.8 micron IR window channel on Meteosat satellites. The result is precipitation estimates with a spatial coverage on most of Europe and Africa and a temporal resolution of 15 minutes. To be able to receive the latest MPE data from EUMETSAT in near real-time a reception station for EUMETCast needs to be set up. With this reception station all data received from Meteosat satellites can be acquired as well as third-party products. The data is post-processed by Meteorological Products Extraction Facility of EUMETSAT, mostly for correction of image distortion and quality assurance. Due to this the data is received with a delay of about 15 minutes. MPE data is stored, by default, in Geostationary Satellite View projection and needs to be transformed into a usable projection system. Projections are translated into WGS84 after which they can be interpolated onto a regular spaced latitude/longitude grid. This paper handles the description of the process of transformation and interpolation 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.

  16. 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.

  17. 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 processes from a different domain or have different spatial and temporal resolutions. An open source framework that bridges OpenMI and OpenDA is presented. The framework provides a generic and easy means for any OpenMI compliant model to assimilate observation measurements. An example test case will be presented using MikeSHE, and OpenMI compliant fully coupled integrated hydrological model that can accurately simulate the feedback dynamics of overland flow, unsaturated zone and saturated zone.

  18. 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.

  19. A sensitivity analysis of regional and small watershed hydrologic models

    NASA Technical Reports Server (NTRS)

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

    1975-01-01

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

  20. Groundwater level simulations using a mesoscale hydrological model SWIM

    NASA Astrophysics Data System (ADS)

    Sipek, Vaclav

    2013-04-01

    Integrated water resources management based on the profound understanding of the hydrological cycle may be a suitable tool for alleviating the upcoming water resource crisis. The application of the physically based distributed hydrological models is a significant tool for studies of hydrological behavior of river basins under the change of natural condition and. The SWIM (Soil and Water Integrated Model) is physically based hydrological models that could be used for impact studies. It is a continuous-time model which works on a daily step and integrates hydrology, vegetation, erosion and nutrients (N-nitrogen and P-phosphorus) at the river basin scale. Its hydrological module is based on the water balance equation, taking into account precipitation, evapotranspiration, percolation, surface runoff and subsurface runoff for the soil column subdivided into several layers. The catchment is spatially subdivided into hydrotops (or hydrologically similar response units) by GIS. The aim of this study was to examine the ability of this type of the model to simulate the course of the groundwater level in the mesoscale catchment in the Czech Republic. The weekly values of the groundwater table height were compared to the simulated ones at several uniformly distributed locations. In one particular site, the results were also discussed in the context of the soil moisture content. It was found that in the warm period of the year the model is able to simulate satisfactorily both the course of groundwater and soil moisture. Nevertheless, in the winter season the rate of percolation is probably underestimated as the simulated groundwater height is lower than observed and at the same time the soil moisture content is overestimated. Acknowledgement: The study was supported by the research grant GA AS CR IAA 300600901

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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 reservoirs designed for hydropower generation, water supply and flood control. Less reliable results were observed for Africa and dry areas of Asia and America. There are several possible causes of large uncertainties in discharge simulations for these areas including: accuracy of observational data, model underestimation of extensive water use and greater uncertainties of used climatic data in these regions due to sparser observational network. In general the applied approach for streamflow routing through reservoirs and large natural lakes has significantly improved simulated discharge estimates.

  6. 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.

  7. 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 to pronounced differences in model simulations at larger spatial scales. Work is ongoing to use this modeling framework to understand differences among existing models, especially, to understand why different hydrologic models have a very different portrayal of the impacts of climate change on water resources.

  8. 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...

  9. 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:25262294

  10. The CRISPR/Cas9 System Facilitates Clearance of the Intrahepatic HBV Templates In Vivo

    PubMed Central

    Lin, Su-Ru; Yang, Hung-Chih; Kuo, Yi-Ting; Liu, Chun-Jen; Yang, Ta-Yu; Sung, Ku-Chun; Lin, You-Yu; Wang, Hurng-Yi; Wang, Chih-Chiang; Shen, Yueh-Chi; Wu, Fang-Yi; Kao, Jia-Horng; Chen, Ding-Shinn; Chen, Pei-Jer

    2014-01-01

    Persistence of hepatitis B virus (HBV) covalently closed circular DNA (cccDNA) under current antiviral therapy is a major barrier to eradication of chronic hepatitis B (CHB). Curing CHB will require novel strategies for specific disruption of cccDNA. The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system is a newly developed tool for site-specific cleavage of DNA targets directed by a synthetic guide RNA (gRNA) base-paired to the target DNA sequence. To examine whether this system can cleave HBV genomes, we designed eight gRNAs against HBV of genotype A. With the HBV-specific gRNAs, the CRISPR/Cas9 system significantly reduced the production of HBV core and surface proteins in Huh-7 cells transfected with an HBV-expression vector. Among eight screened gRNAs, two effective ones were identified. Interestingly, one gRNA targeting the conserved HBV sequence acted against different genotypes. Using a hydrodynamics-HBV persistence mouse model, we further demonstrated that this system could cleave the intrahepatic HBV genome-containing plasmid and facilitate its clearance in vivo, resulting in reduction of serum surface antigen levels. These data suggest that the CRISPR/Cas9 system could disrupt the HBV-expressing templates both in vitro and in vivo, indicating its potential in eradicating persistent HBV infection. PMID:25137139

  11. Comparing spatial and temporal transferability of hydrological model parameters

    NASA Astrophysics Data System (ADS)

    Patil, Sopan D.; Stieglitz, Marc

    2015-06-01

    Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal aspects of catchment hydrological variability.

  12. 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.

  13. 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)

  14. 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...

  15. 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 ...

  16. 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...

  17. Assessing the Uncertainty in Downscaling Approaches using Hydrological Model

    NASA Astrophysics Data System (ADS)

    Sharma, Tarul; Chhabra, Surbhi; Karmakar, Subhankar; Ghosh, Subimal; Salvi, Kaustubh

    2015-04-01

    General Circulation Models (GCMs) play an important role in defining the climate change impacts at a global scale, but its coarser resolution limits its direct application at regional scale. To understand the meteorological variability at regional scale, regional climate models have been developed which use the GCM outputs as boundary condition to downscale them at finer scale. Two broad classes of downscaling are dynamical, which involve developing physics based regional model and statistical, which involves establishing statistical relationship between coarse scale climate variables and fine resolution variable of interest. The two approaches perform well in their own domain, however, comparing the results, obtained using two approaches with different basis leads to a source of uncertainty, associated with the approach. Here, we quantify the uncertainty associated with approach in terms of hydrologic variables that are simulated separately using dynamically and statistically downscaled climate forcings. GCM model named EC-Earth has been statistically downscaled (SD) using multi-site kernel regression method and it has been compared with dynamically downscaled CORDEX outputs of the same GCM. For this, period from 1981 to 2005 has been considered as baseline period and period from 2016 to 2040 has been considered as future period. Since, these meteorological outputs affect the regional hydrological components such as runoff, Evapo-Transpiration (ET), soil moisture, and baseflow; simulated outputs from a meso-scale hydrological model named Variable Infiltration Capacity (VIC) model has been used to compare these downscaled variables. Advantage of this model is that it considers the effect of Land Use/Land Cover (LULC), vegetative properties, and soil properties at sub-grid level; which plays an important role in the hydrology of a region. Comparatively more future increase in all the hydrological variables over major part of India was simulated using SD outputs, then CORDEX outputs. Also, downscaling uncertainty showed decrease in minimum and maximum temperature derived from SD model as compared to CORDEX data. Partial correlation of each hydrological variable with meteorological data showed future change in precipitation and maximum temperature as the most affecting variables which will influence the change in hydrological parameters as compared to wind and minimum temperature. However, CORDEX results showed change in precipitation and maximum temperature as the major parameters that will affect ET, runoff and soil moisture; whereas statistically downscaled results showed only change in precipitation as the most influential variable. Keywords: Dynamical and Statistical Downscaling, Hydrological model, Uncertainty analysis

  18. 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.

  19. Hydrologic Data Assimilation: State Estimation and Model Calibration

    NASA Astrophysics Data System (ADS)

    Dechant, Caleb Matthew

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

  20. The value of stream level observations to constrain low-parameter hydrologic models

    NASA Astrophysics Data System (ADS)

    Seibert, J.; Vis, M.; Pool, S.

    2014-12-01

    While conceptual runoff models with a low number of model parameters are useful tools to capture the hydrological catchment functioning, these models usually rely on model calibration, which makes their use in ungauged basins challenging. One approach might be to take at least a few measurements. Recent studies demonstrated that few streamflow measurements, representing data that could be measured with limited efforts in an ungauged basin, might be helpful to constrain runoff models for simulations in ungauged basins. While in these previous studies we assumed that few streamflow measurements were taken, obviously it would also be reasonable to measure stream levels. Several approaches could be used in practice for such stream level observations: water level loggers have become less expensive and easier to install; stream levels will in the near future be increasingly available from satellite remote sensing resulting in evenly space time series; community-based approaches (e.g., crowdhydrology.org), finally, can offer level observations at irregular time intervals. Here we present a study where a runoff model (the HBV model) was calibrated for 600+ gauged basins in the US assuming that only a subset of the data was available. We pretended that only stream level observations at different time intervals, representing the temporal resolution of the different observation approaches mentioned before, were available. The model, which was calibrated based on these data subsets, was then evaluated on the full observed streamflow record. Our results indicate that streamlevel data alone already can provide surprisingly good model simulation results in humid catchments, whereas in arid catchments some form of quantitative information (streamflow observation or regional average value) is needed to obtain good results. These results are encouraging for hydrological observations in data scarce regions as level observations are much easier to obtain than streamflow observations. Based on runoff modeling it might be possible to derive streamflow series from level observations using loggers, satellites or community-based approaches. The approach presented here also allows comparing the value of different types of observations and, thus, to guide the monitoring of (previously) ungauged basins.

  1. 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 developed in this study. The ANN models developed consistently outperformed the conceptual model developed in this study. The results obtained in this study indicate that the ANNs can be extremely useful tools for modeling the complex rainfall-runoff process in real catchments. The ANNs should be adopted in real catchments for hydrological modeling and forecasting. It is hoped that more research will be carried out to compare the performance of ANN model with the conceptual models actually in use at catchment scales. It is hoped that such efforts may go a long way in making the ANNs more acceptable by the policy makers, water resources decision makers, and traditional hydrologists.

  2. 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.

  3. 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.

  4. Anti-HBV effect of TAT- HBV targeted ribonuclease

    PubMed Central

    Ding, Jin; Liu, Jun; Xue, Cai-Fang; Gong, Wei-Dong; Li, Ying-Hui; Zhao, Ya

    2003-01-01

    AIM: To prepare and purify TAT-HBV targeted ribonuclease fusion protein, evaluate its transduction activity and investigate its effect on HBV replication in 2.2.15 cells. METHODS: The prokaryotic expression vector pTAT containing TR gene was used in transforming E.coli BL21 (DE3) LysS and TR was expressed with the induction of IPTG. The TAT-TR fusion protein was purified using Ni-NTA-agrose and PD-10 desalting columns, and analyzed by SDS-PAGE. Transduction efficiency of TAT-TR was detected with immunofluorescence assay and the concentration of HBeAg in the supernatant of the 2.2.15 cells was determined via solid-phase radioimmunoassay (spRIA). MTT assay was used to detect the cytotoxicity of TAT-TR. RESULTS: The SDS-PAGE showed that the TAT-TR fusion protein was purified successfully, and the purity of TAT-TR was 90%. The visualization of TAT-TR by immunofluorescence assay indicated its high efficiency in transducing 2.2.15 cells. RIA result suggests that TAT-TR could inhibit the replication of HBV effectively, it didn’t affect cell growth and had no cytotoxicity. CONCLUSION: TAT-TR possesses a significant anti-HBV activity and the preparation of TAT-TR fusion protein has laid the foundation for the use of TR in the therapeutic trial of HBV infection. PMID:12854156

  5. 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.

  6. 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.

  7. Integrating Geophysics, Geology, and Hydrology for Enhanced Hydrogeological Modeling

    NASA Astrophysics Data System (ADS)

    Auken, E.

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Raje, D.; Krishnan, R.

    2012-08-01

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

  9. 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.

  10. Identification of the HYPE hydrological model over the Indian subcontinent

    NASA Astrophysics Data System (ADS)

    Pechlivanidis, Ilias; Gustafsson, David; Arheimer, Berit

    2014-05-01

    Large-scale hydrological modelling has the potential to encompass many river basins, cross regional and international boundaries and represent a number of different geophysical and climatic zones. However the performance of this type of model is subject to several sources of uncertainty/error which may be caused by, among others, the imperfectness of driving inputs, i.e. regional and global databases. This uncertainty further leads to wrong model parameterisation and incomplete process understanding. Data assimilation aims to utilize both hydrological process knowledge (as embodied in a hydrologic model) and information that can be gained from observations; hence information from model predictions and observations is synergistically used to improve performance. This study presents a methodology, drawn on experience from modelling with the HYPE model in the Indian subcontinent (covering a modelled area of 4.9 million km2), to enhance identification of highly parameterised large-scale hydrological models. The model was set up using available large-scale datasets on topography, land use, soil, precipitation, temperature, lakes, reservoirs, crop types, irrigation, evaporation, snow and discharge. A stepwise automatic calibration is carried out to avoid, to a certain extent, errors incurring in some model processes and being compensated by introducing errors in other parts of the model. In addition, information from remote sensing data is assimilated in the model to drive identification of parameters that control the spatial distribution of potential evapotranspiration. Results show that despite the strong hydro-climatic gradient over the domain, the model can adequately describe the hydrological process in the Indian subcontinent. Overall, the median Kling-Gupta Efficiency (KGE) increased from 0.08 to 0.64 during the calibration process using 43 stations of monthly discharge series over the period 1971 to 1979. Finally, decomposition of the KGE (i.e. into terms describing agreement in correlation, bias and variability between observed and modelled streamflow series) allowed a thorough understanding of model inadequacies. Keywords Large-scale hydrological modelling, HYPE, model identification, Kling-Gupta Efficiency, remote sensing, India

  11. 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.

  12. Physical Modeling of Hydrologic Processes in South Central Texas

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  13. Integrating earth observation data into hydrological modeling and water management

    NASA Astrophysics Data System (ADS)

    Hartanto, I. M.; van Andel, S. J.; Lobbrecht, A. H.; van Griensven, A.; Solomatine, D. P.

    2012-04-01

    One of the most important aspects of hydrological modeling in water management is uncertainties. It covers input, model structure, parameters and state variables. Therefore, it is very important to reduce uncertainty in model development, hence the decision makers have higher confidence in taking their decision. The use of Earth Observation (EO) data is increasing significantly during these years. These were driven by many advantages, such as: it covers almost all space, in specific time-steps, and cost effective. Also the amount and reliability of earth observation data has reached a high degree. The EU FP7 project MyWater (www.mywater-fp7.eu, coordinated by GMV) aims to utilize and evaluate the value of EO data in water management by analyzing EO data such as Land use changes, Eta, LAI and Soil moisture. The project aims at developing a water management system that integrates EO data, meteorological data, catchment models and ground based data to improve the forecasting capabilities. An innovative hydrological modelling approache is needed to utilize the increasing amount of EO data and reliability. Especially if the approach is able to reduce uncertainties of the data itself as well as the model output. The approach must be able to integrate EO data into recent hydrological modelling advances, and improve result and/or modelling development. Although the EO data availability and reliability has reached quite a high level, the value of using these data in a hydrological model needs to be evaluated. More data and a wider coverage does not necessarily mean it will give a better result, and different model structures react in different ways. A spatially distributed model is possibly the most benefiting from EO data, however, a lumped model could also benefit greatly. The value can be gained through calibration, validation, data assimilation and feedback loops throughout the modeling process. The approach is tested and compared in wider usage of hydrological modeling, such as different model structure from lumped to spatially distributed, well gauged catchment to un-gauged one and various catchment characteristics. With this approach it is expected to have an understanding how to maximize the utilization of EO data in hydrological modeling and water management.

  14. 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.

  15. Comparing spatial and temporal transferability of hydrological model parameters

    NASA Astrophysics Data System (ADS)

    Patil, Sopan; Stieglitz, Marc

    2015-04-01

    Operational use of hydrological models requires the transfer of calibrated parameters either in time (for streamflow forecasting) or space (for prediction at ungauged catchments) or both. Although the effects of spatial and temporal parameter transfer on catchment streamflow predictions have been well studied individually, a direct comparison of these approaches is much less documented. In our view, such comparison is especially pertinent in the context of increasing appeal and popularity of the "trading space for time" approaches that are proposed for assessing the hydrological implications of anthropogenic climate change. Here, we compare three different schemes of parameter transfer, viz., temporal, spatial, and spatiotemporal, using a spatially lumped hydrological model called EXP-HYDRO at 294 catchments across the continental United States. Results show that the temporal parameter transfer scheme performs best, with lowest decline in prediction performance (median decline of 4.2%) as measured using the Kling-Gupta efficiency metric. More interestingly, negligible difference in prediction performance is observed between the spatial and spatiotemporal parameter transfer schemes (median decline of 12.4% and 13.9% respectively). We further demonstrate that the superiority of temporal parameter transfer scheme is preserved even when: (1) spatial distance between donor and receiver catchments is reduced, or (2) temporal lag between calibration and validation periods is increased. Nonetheless, increase in the temporal lag between calibration and validation periods reduces the overall performance gap between the three parameter transfer schemes. Results suggest that spatiotemporal transfer of hydrological model parameters has the potential to be a viable option for climate change related hydrological studies, as envisioned in the "trading space for time" framework. However, further research is still needed to explore the relationship between spatial and temporal aspects of catchment hydrological variability.

  16. HBV Genotypic Variability in Cuba

    PubMed Central

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

    2015-01-01

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

  17. 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 implementation of the message passing interface (MPI), which includes FORTRAN, C, Java, the .NET languages, Python, R, Matlab, and many others. The system is tested on a longstanding legacy hydrologic model, the Soil and Water Assessment Tool (SWAT), to observe and enhance speed-up capabilities for various optimization, parameter estimation, and model uncertainty characterization techniques, which is particularly important for computationally intensive hydrologic simulations. Initial results indicate that the legacy extension system significantly decreases developer time, computation time, and the cost of purchasing commercial parallel processing licenses, while enhancing interdisciplinary research by providing detailed two-way feedback mechanisms between various process models with minimal changes to legacy code.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  19. 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.

  20. Do land parameters matter in large-scale hydrological modelling?

    NASA Astrophysics Data System (ADS)

    Gudmundsson, Lukas; Seneviratne, Sonia I.

    2013-04-01

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

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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

  8. 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...

  9. 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 represent the catchment's hydrological behavior. Further steps in the collaboration may include (1) repeating the experiment for other sub-catchments of the Meuse River Basin where different hydrological processes may be relevant and where other models may perform better; and (2) the comparison of hydrological model results obtained by forcing the model with daily local measured precipitation and lower resolution gridded precipitation from the E-OBS (Haylock et at., 2008) dataset to estimate the value of high-resolution data versus lower resolution gridded products. 1 Service Publique de Wallonie, Direction générale opérationnelle de la Mobilité et des Voies hydrauliques, Département des Etudes et de l'Appui à la Gestion, Direction de la Gestion hydrologique intégrée, Boulevard du Nord 8 - 5000 Namur "Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201"

  10. 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.

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

    PubMed

    Nakabayashi, Jun

    2016-05-01

    Hepatitis B virus (HBV) is a causative agent of hepatitis. Clinical outcome of hepatitis type B depends on the viral titer observed in the peripheral blood of the patient. In the chronic hepatitis patient, production of HBV virion remains low level. On the other hand, the viral load prominently increases in fulminant hepatitis patient as compared with that in the chronic hepatitis patient. We previously proposed a mathematical model describing the intracellular dynamics of HBV replication. Our model clarified that there are two distinguishable replication patterns of HBV named "arrested" and "explosive" replication. In the arrested replication, the amount of virion newly reproduced from an infected cell remains low level, while the amount of virion extremely increases in the explosive replication. Viral load is drastically changed by slight alteration of expression ratio of 3.5kb RNA to 2.4kb mRNA of HBV. Though our model provided the switching mechanism determining the replication pattern of HBV, HBV dynamics is determined by not only the expression pattern of viral genes. In this study, "recycling" of HBV virion in the replication cycle is investigated as a new factor affecting the intracellular dynamics of HBV replication. A part of newly produced virion of HBV is reused as a core particle that is a resource of HBV replication. This recycling of HBV virion lowers the threshold for the explosive replication when waiting time for the next cycle of the replication is large. It is seemingly contradicting that prominent production of HBV is caused by large recycling rate and small release rate of HBV virion from infected cell to extracellular space. But the recycling of HBV virion can contribute to the positive feedback cycle of HBV replication for the explosive replication to accumulate the core particle as a resource of HBV replication in an infected cell. Accumulation of core particle in the infected cell can be risk factor for the exacerbation of hepatitis rather than rapid release of HBV virion from the infected cell. PMID:26924390

  12. 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.

  13. 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.

  14. 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.

  15. 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 components, interception and transpiration from different landscapes, fit well with our existing knowledge obtained from experimental hydrologists.

  16. 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 scenario analysis. Model selection is inherent to hydrological modelling, because of the large spatial and temporal variability of processes, which inhibits the use of one optimal model structure. However, in a web context it becomes paramount that such selection is automatic, yet objective and transparent. Similarly, uncertainty quantification is a mainstream practice in hydrological modelling, but in a web-context uncertainty analysis face unprecedented challenges in terms of tracking uncertainties throughout a possibly geographically distributed workflow, as well as dealing with an extreme heterogeneity of data availability. Lastly, the ability of end-users to interact directly with hydrological models poses specific challenges in terms of mapping user scenarios (e.g., a scenario of land-use change) into the model parameter space for prediction and uncertainty quantification. The setup has been used in several scientific experiments, including the large-scale UK consortium project on an Environmental Virtual Observatory pilot.

  17. 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 hydrodynamic models. The hydrological model will run operationally for the whole globe. Once special situations are predicted, such as floods, navigation hindrances, or water shortages, a detailed local hydraulic model will start to predict the exact local consequences. In Vienna, we will show for the first time the operational global eWaterCycle model, including high resolution forecasts, our new data assimilation technique, and coupled hydrological/hydraulic models.

  18. 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

    Based on an international literature review on model structures of existing rainfall-runoff and hydrological models, a generalized model structure is proposed. It consists of different types of meteorological components, storage components, splitting components and routing components. They can be spatially organized in a lumped way, or on a grid, spatially interlinked by source-to-sink or grid-to-grid (cell-to-cell) routing. The grid size of the model can be chosen depending on the application. The user can select/change the spatial resolution depending on the needs and/or the evaluation of the accuracy of the model results, or use different spatial resolutions in parallel for different applications. Major research questions addressed during the study are: How can we assure consistent results of the model at any spatial detail? How can we avoid strong or sudden changes in model parameters and corresponding simulation results, when one moves from one level of spatial detail to another? How can we limit the problem of overparameterization/equifinality when we move from the lumped model to the spatially distributed model? The proposed approach is a step-wise one, where first the lumped conceptual model is calibrated using a systematic, data-based approach, followed by a disaggregation step where the lumped parameters are disaggregated based on spatial catchment characteristics (topography, land use, soil characteristics). In this way, disaggregation can be done down to any spatial scale, and consistently among scales. Only few additional calibration parameters are introduced to scale the absolute spatial differences in model parameters, but keeping the relative differences as obtained from the spatial catchment characteristics. After calibration of the spatial model, the accuracies of the lumped and spatial models were compared for peak, low and cumulative runoff total and sub-flows (at downstream and internal gauging stations). For the distributed models, additional 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".

  19. 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 season due to shorter snowcover persistence and less precipitation and an increase in runoff in the low flow season due to higher temperatures and more precipitation. The runoff originating from snow melt is projected to decrease by 22% and 30%, respectively. The projected runoff from glaciers will diminish by 85% in the mid-term and disappear completely in the long-term. The results from discharge emerging from snow- and glacier melt are significant. The main cause for the spread in the results was found in the large differences between the climate scenarios. These results are in line with findings of a similar study about the Mattmark reservoir in the Vispa valley.

  20. 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.

  1. Hyper-resolution hydrological modeling of polygonal ground

    NASA Astrophysics Data System (ADS)

    Liljedahl, A. K.; Hinzman, L. D.; Schulla, J.; Tweedie, C.

    2010-12-01

    While evapotranspiration is the major pathway of water loss from the Arctic Coastal Plain, Northern Alaska, the water balance of the tundra wetlands is highly dependent upon small scale topographical features (<1 m). Unique to arctic terrestrial ecosystems are patterned ground due to the formation or degradation of massive ground ice. These closed, multi-sided ground features, with high or low centers, complicate hydrological modeling efforts. Low centered polygons favor ponding and therefore reduced runoff, while high centered polygons result in large geographical contrasts of near-surface soil moisture. Therefore, hydrological model simulations in spatial resolutions larger than these ground features may result in a significant amount of uncertainty. Constraining this uncertainty is critical in order to refine our understanding of the future abiotic and biotic state of Arctic wetlands as well as the strength of positive feedbacks to the Earth system. We applied the Water Balance Simulation Model ETH (WaSiM-ETH), a physically-based hydrological model, to this intensively studied watershed, which is represented by a vegetated (moss and sedge) drained thaw lake basin. Important processes represented in WaSiM-ETH include a) simple empirical formula representing the seasonal freezing and thawing above the permafrost, b) a dynamic linkage between soil moisture and evapotranspiration and, c) surface routing module allowing dynamic generation of ponds. We validated WaSiM-ETH on runoff, evapotranspiration, and water table observations. We show that WaSiM-ETH generates a realistic water balance and is a powerful tool to project hydrological fluxes and stores. Runoff and soil moisture are controlled by the polygon rims as is the simulated evapotranspiration rates. This study demonstrates that it is crucial to resolve the micro-topographical gradients found in a low-gradient tundra landscape due to its unique polygonal ground, in order successfully represent the larger-scale hydrological fluxes and stores.

  2. 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...

  3. The Integrated Landscape Hydrology Model (ILHM), a Fully-Distributed Approach to Simulate Regional Watershed Hydrologic Processes

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

    Modeling fine-scale regional landscape and subsurface hydrology with fully-distributed process models requires data and computational resources that have only recently become available. For this reason most hydrologic models either do not represent crucial hydrologic processes or are not practical for regional-scale simulations. To overcome these limitations we linked a set of existing codes with novel approaches in the new Integrated Landscape Hydrology Model (ILHM), designed to integrate widely-available GIS and remotely- sensed data using a simple parameterization The ILHM is a loosely-coupled suite of codes that allows fine-scale numerical modeling for some processes while integrating simpler water-balance models at disparate temporal and spatial scales. This approach enables individual process models to be swapped with different modules or with measured data. Currently, the ILHM includes codes that simulate canopy and soil processes, snowpack accumulation and melt, surface ponding and runoff, shallow sub-surface flow, and both unsaturated and saturated groundwater flow. The ILHM also has potential as a tool to simulate fluxes through large ungaged basins and evaluate historical and future hydrologic scenarios. We present an application of the ILHM to a 137 square kilometer catchment within the larger Muskegon River Watershed in northern-lower Michigan. A comparison of model outputs to measured and gaged stream discharges demonstrates that the ILHM is capable of predicting hydrologic fluxes with reasonable accuracy without significant parameter calibration. In addition, the model results suggest interesting and important linkages between land use and groundwater recharge.

  4. Hydrological modelling under non-stationarity - climate change and floods

    NASA Astrophysics Data System (ADS)

    Bloeschl, G.; Salinas, J.; Viglione, A.; Merz, R.

    2012-12-01

    Understanding and modelling climate effects on floods, often, are essential parts of developing climate adaptation strategies. The traditional scenario method of climate impact studies is problematic due to the large uncertainties which are difficult to estimate. Moreover, it is rarely clear how the uncertainties in the assumptions propagate to the results. The focus of this work is on the mechanisms to allow a more transparent assessment of cause-effect than is possible by scenarios alone. This allows us to separate changes that are likely to occur (hard facts) from changes that are possible but not supported by data evidence (soft facts). For instance, we found that some mechanisms allow us to suggest likely changes of floods with some confidence, e.g. the increase of winter floods due to higher temperatures (rising snow fall line) and the decreasing summer floods due to earlier snowmelt. We will contrast this assessment with our views on the current state of change prediction and outline the opportunities in this area of hydrologic research. Improving the understanding of hydrological processes under the current climate, focusing on why impact studies predict changes rather than on the magnitudes of the change, improving hydrologically-driven uncertainty methods, being more transparent about what we can and cannot predict and being realistic about the role of adaptation measures in the context of water management, we believe, are the cornerstones of modelling hydrological processes in a transient climate.

  5. Hydrologic Modeling for Flood Control Detention Basin Design and Operation.

    NASA Astrophysics Data System (ADS)

    Smiley, Mark Andrew

    This dissertation presents a methodology for hydrologic modeling related to the design and operation of flood control detention basins. Prior to this document, a comprehensive, tractable methodology for detention basin hydrologic modeling did not exist. Furthermore, techniques used in the past have not always taken advantage of computer technology or recent advances in the field of hydrology. New and original methods are presented and are developed from personal experience, recent literature, and relevant courses at The University of Arizona. Chapters in this document include precipitation data analysis, detention basin stormwater inflow, detention basin sediment inflow, stored water losses through evaporation and infiltration, design issues, and operation under competing water use objectives. Engineering constraints and data availability are explicitly addressed throughout the methodology. The goal is to determine hydrologic variables for detention basin design such as active storage volume, spillway capacity, drain outlet capacity, and, additionally for some systems, the bypass channel capacity and side-weir threshold spill flow rate. In addition to providing an increased level of protection from flood damage, detention basins may also accommodate land use and water conservation objectives of urban society.

  6. 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.

  7. Gravitational and capillary soil moisture dynamics for distributed hydrologic models

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Distributed and continuous catchment models are used to simulate water and energy balance and fluxes across varied topography and landscape. The landscape is discretized into computational plan elements at resolutions of 101-103 m, and soil moisture is the hydrologic state variable. At the local scale, the vertical soil moisture dynamics link hydrologic fluxes and provide continuity in time. In catchment models these local-scale processes are modeled using 1-D soil columns that are discretized into layers that are usually 10-3-10-1 m in thickness. This creates a mismatch between the horizontal and vertical scales. For applications across large domains and in ensemble mode, this treatment can be a limiting factor due to its high computational demand. This study compares continuous multi-year simulations of soil moisture at the local scale using (i) a 1-pixel version of a distributed catchment hydrologic model and (ii) a benchmark detailed soil water physics solver. The distributed model uses a single soil layer with a novel dual-pore structure and employs linear parameterization of infiltration and some other fluxes. The detailed solver uses multiple soil layers and employs nonlinear soil physics relations to model flow in unsaturated soils. Using two sites with different climates (semiarid and sub-humid), it is shown that the efficient parameterization in the distributed model captures the essential dynamics of the detailed solver.

  8. 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...

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. An event-based hydrologic simulation model for bioretention systems.

    PubMed

    Roy-Poirier, A; Filion, Y; Champagne, P

    2015-01-01

    Bioretention systems are designed to treat stormwater and provide attenuated drainage between storms. Bioretention has shown great potential at reducing the volume and improving the quality of stormwater. This study introduces the bioretention hydrologic model (BHM), a one-dimensional model that simulates the hydrologic response of a bioretention system over the duration of a storm event. BHM is based on the RECARGA model, but has been adapted for improved accuracy and integration of pollutant transport models. BHM contains four completely-mixed layers and accounts for evapotranspiration, overflow, exfiltration to native soils and underdrain discharge. Model results were evaluated against field data collected over 10 storm events. Simulated flows were particularly sensitive to antecedent water content and drainage parameters of bioretention soils, which were calibrated through an optimisation algorithm. Temporal disparity was observed between simulated and measured flows, which was attributed to preferential flow paths formed within the soil matrix of the field system. Modelling results suggest that soil water storage is the most important short-term hydrologic process in bioretention, with exfiltration having the potential to be significant in native soils with sufficient permeability. PMID:26524443

  14. 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.

  15. Developing a hydrological model in the absence of field data

    NASA Astrophysics Data System (ADS)

    Sproles, E. A.; Orrego Nelson, C.; Kerr, T.; Lopez Aspe, D.

    2014-12-01

    We present two runoff models that use remotely-sensed snow cover products from the Moderate Resolution Imaging Spectrometer (MODIS) as the first order hydrologic input. These simplistic models are the first step in developing an operational model for the Elqui River watershed located in northern Central Chile (30°S). In this semi-arid region, snow and glacier melt are the dominant hydrologic inputs where annual precipitation is limited to three or four winter events. Unfortunately winter access to the Andean Cordillera where snow accumulates is limited. While a monitoring network to measure snow where it accumulates in the upper elevations is under development, management decisions regarding water resources cannot wait. The two models we present differ in structure. The first applies a Monte Carlo approach to determine relationships between lagged changes in monthly snow cover frequency and monthly discharge. The second is a modified degree-day melt model, utilizing the MODIS snow cover product to determine where and when snow melt occurs. These models are not watershed specific and are applicable in other regions where snow dominates hydrologic inputs, but measurements are minimal.

  16. Complexity of a flexible topography driven conceptual hydrological model

    NASA Astrophysics Data System (ADS)

    Moayeri, MohamadMehdi; Gharari, Shervan; Pande, Saket

    2015-04-01

    Defining a measure of complexity for a hydrological model is required for selection of a model structure among the structures an expert designs. Flex-Topo conceptual modelling approach enables us to design different model structures. We define complexity of a model as a measure in the model output space which can be used for selecting optimal model by minimizing empirical risk of models indicating lowest complex model. We applied this approach on different model structures which we designed a Flex-Topo model for a catchment in Iran. These model structures are based on landscape units including plateau, hillslope and wetland with separate conceptualisation of water balance and also constitutive equations. The complexity based model selection provides us a model structure which is more robust in prediction of future data in comparison to the other structures.

  17. 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 methodologies.

  18. 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-hypothesis methodologies.

  19. 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...

  20. 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.

  1. 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 scaled GCM projections of daily temperature and precipitation from 2010 to 2100 using six GCMs and 2 greenhouse gas emissions scenarios of A2 and B1. To illustrate clear cause and effect, several hydrologic processes are presented together where ensemble means of selected results for each GHG scenario and watershed are grouped to show mean monthly hydrologic change throughout the early, mid, and late 21st century. Model results indicate that significant changes in mountain hydrology of the Sierra Nevada are likely to occur due to projected climate change, including shifts in the timing and magnitude of groundwater recharge and discharge. For example, multiple processes work together to provide springflow and streamflow during driest part of the season. Warming due to climate change reduces the snow pack during the spring snowmelt period and shifts the timing of the peak of groundwater discharge to springs and streams earlier in the season. Consequently, the aridity of these basins will increase during the warmest parts of the year. These results highlight the extreme interdependencies in the predicted changes of streamflow, evapotranspiration, groundwater recharge, and groundwater discharge.

  2. Postexposure Prophylactic Effect of Hepatitis B Virus (HBV)-Active Antiretroviral Therapy against HBV Infection

    PubMed Central

    Watanabe, Tsunamasa; Hamada-Tsutsumi, Susumu; Yokomaku, Yoshiyuki; Imamura, Junji; Sugiura, Wataru

    2014-01-01

    Retrospective study indicates that hepatitis B virus (HBV)-active nucleoside (nucleotide) analogues (NAs) used for antiretroviral therapy reduce the incidence of acute HBV infections in human immunodeficiency virus (HIV)-infected patients. Learning from HIV postexposure prophylaxis (PEP), we explored the possibility of using NAs in PEP following HBV exposure, if preexposure prophylaxis is feasible clinically. Using freshly isolated primary human hepatocytes cultured in vitro, we analyzed the effect of HBV-active tenofovir and lamivudine in primary HBV infection and also the effect of treatment with these NAs after HBV infection. HBV-active NAs applied from 24 h before inoculation could not prevent the secretion of hepatitis B surface antigen into the culture medium, and cessation of the NAs after inoculation allowed the cells to establish an apparent HBV infection. In contrast, hepatitis B immune globulin was able to prevent HBV infection completely. NA treatment before infection, however, can control the spread of HBV infection, as detected by immunohistochemistry. Practically, starting NA treatment within 2 days of primary HBV infection inhibited viral spread effectively, as well as preexposure treatment. We demonstrated that preexposure NA treatment was not able to prevent the acquisition of HBV infection but prevented viral spread by suppressing the production of mature progeny HBV virions. The effect of postexposure treatment within 2 days was similar to the effect of preexposure treatment, suggesting the possibility of HBV PEP using HBV-active NAs in HIV- and HBV-susceptible high-risk groups. PMID:25512419

  3. Postexposure prophylactic effect of hepatitis B virus (HBV)-active antiretroviral therapy against HBV infection.

    PubMed

    Watanabe, Tsunamasa; Hamada-Tsutsumi, Susumu; Yokomaku, Yoshiyuki; Imamura, Junji; Sugiura, Wataru; Tanaka, Yasuhito

    2015-02-01

    Retrospective study indicates that hepatitis B virus (HBV)-active nucleoside (nucleotide) analogues (NAs) used for antiretroviral therapy reduce the incidence of acute HBV infections in human immunodeficiency virus (HIV)-infected patients. Learning from HIV postexposure prophylaxis (PEP), we explored the possibility of using NAs in PEP following HBV exposure, if preexposure prophylaxis is feasible clinically. Using freshly isolated primary human hepatocytes cultured in vitro, we analyzed the effect of HBV-active tenofovir and lamivudine in primary HBV infection and also the effect of treatment with these NAs after HBV infection. HBV-active NAs applied from 24 h before inoculation could not prevent the secretion of hepatitis B surface antigen into the culture medium, and cessation of the NAs after inoculation allowed the cells to establish an apparent HBV infection. In contrast, hepatitis B immune globulin was able to prevent HBV infection completely. NA treatment before infection, however, can control the spread of HBV infection, as detected by immunohistochemistry. Practically, starting NA treatment within 2 days of primary HBV infection inhibited viral spread effectively, as well as preexposure treatment. We demonstrated that preexposure NA treatment was not able to prevent the acquisition of HBV infection but prevented viral spread by suppressing the production of mature progeny HBV virions. The effect of postexposure treatment within 2 days was similar to the effect of preexposure treatment, suggesting the possibility of HBV PEP using HBV-active NAs in HIV- and HBV-susceptible high-risk groups. PMID:25512419

  4. 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 basin (Basque Country, North of Spain). So that adaptation strategies can be defined. In order to fulfil this objective four subobjectives are defined: (1)selection of the future climate projections for the case study area from a wide spectrum of possibilities; (2) model the hydrological processes of the basin with a physically distributed complex hydrological model; (3) validation of the hydrological model with observation data; and (4) runoff simulation introducing regional climate model data selected. The analysis of climate models suggests that extreme precipitation in the Basque Country increased by about 10% during the twenty-first century. This increase of extreme precipitations raised discharge and water level in Nerbioi river basin. That is why in the 21st century it is expected that the flood-prone area will expand for precipitation with a return period of 50 years. In this context, it is necessary to define and evaluate different adaptation options which are already in practice or conceivable according to the current scientific knowledge. As well as evaluate the adaptation measures in terms of their ability to lower the vulnerability of water resources to climate change. For example, land use change could be a useful tool to adapt our basin systems. The land use plays an important role on the water balance of a river by varying the proportion of precipitation that runs off and the fraction that is lost by evapotranspiration. Therefore, both climate change and adaptation strategies will have an impact on the hydrodynamic conditions of rivers; particularly the changes in flow conditions will have a severe ecological, economical and social impact. As future work, adaptation measures will introduce in the future runoff simulation in order to evaluate the effectiveness and as a decision-making tool to operational organisations.

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

    PubMed Central

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

    2015-01-01

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

  6. Chapman Conference on Spatial Variability in Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

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

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

  7. eWaterCycle: A high resolution global hydrological model

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  8. 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. Mazzanti (2009), A distributed package for sustainable water management: a case study in the Arno basin, IAHS Publ. 327 Flerchinger, G. N. (2000), The Simultaneous Heat and Water (SHAW) Model: Technical Documentation, Technical Report NWRC 2000-09, USDA Agricultural Research Service, Boise, Idaho

  9. Drought Analysis for River Basins, Using the Hydrological Model SIMGRO

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  10. Selection of Hydrological Model for Waterborne Release

    SciTech Connect

    Blanchard, A.

    1999-04-21

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

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

    NASA Astrophysics Data System (ADS)

    Viger, R.; Bock, A.

    2014-12-01

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

  12. Inverting MODIS Snow Covered Area in a Hydrology Model

    NASA Astrophysics Data System (ADS)

    Slater, A. G.; Clark, M. P.

    2009-12-01

    Direct application of remote sensing products into hydrologic models has been an ongoing challenge for the past 30 years. Microwave signals which have the potential to inform about snow mass, are at low spatial resolution and easily confused by many mixed signals. Snow covered area is much more readily available at the scales relevant to hydrologic models than other snow products derived from remote sensing. The MODIS MOD10A1/MYDA1 products give snow cover as a binary value (present or not) over an area or approximately 500m resolution. This data will contain some error due to the assumption that any pixel with less than 50% snow cover is flagged as bare. In this work we look at snow regimes within a hydrologic model that can reproduce the proportional area of snow cover over a given basin. The model we use is TopNet which includes a scale invariant fractional snow cover parameterization. This parameterization accounts for the hysteresis associated with snow covered area during accumulation and ablation processes. We use two basins (and their subsequent sub-basins) in the Sierra Nevada Mountains of California and Nevada; namely the North Fork of the American River and the East Fork of the Carson. The scale dependence of the ability to reproduce snow fractional cover will be assessed from first order through to fifth order basins and we seek to determine at what scale and under what snow regime can meaningful information be garnered about snow mass.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it requires the use of additional software. In particular, there are at least three elements that are needed: a geospatially enabled database, a map server, and geoprocessing toolbox. We recommend a software stack for geospatial web application development comprising: MapServer, PostGIS, and 52 North with Python as the scripting language to tie them together. Another hurdle that must be cleared is managing the cloud-computing load. We are using HTCondor as a solution to this end. Finally, we are creating a scripting environment wherein developers will be able to create apps that use existing hydrologic models in our system with minimal effort. This capability will be accomplished by creating a plugin for a Python content management system called CKAN. We are currently developing cyberinfrastructure that utilizes this stack and greatly lowers the investment required to deploy cloud-based modeling apps. This material is based upon work supported by the National Science Foundation under Grant No. 1135482

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  18. Hydrologic modeling of reclaimed strip mine spoil

    SciTech Connect

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

    1998-12-31

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  20. What is the minimal geomorphology based hydrological model?

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  2. Distributed Hydrologic Modeling of LID in The Woodlands, Texas

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    EPA Science Inventory

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. USING DIGITAL TERRAIN ANALYSIS MODELING TECHNIQUES FOR THE PARAMETERIZATION OF A HYDROLOGIC MODEL.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper discusses the application of digital terrain analysis modeling techniques to the parameterization of a semi-distributed hydrologic model. Most current techniques for deriving physiographic parameters in watershed analyses, including those using commercial geographic information systems (...

  6. Coupled geophysical-hydrological modeling of controlled NAPL spill

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Process-based conceptual rainfall-runoff models are useful to understand runoff generation at different time and spatial resolutions. Contrary to physically-based models, they do not rely much on field observations (e.g. soil physical properties) which may not be available everywhere. Instead, these mathematical tools close the water balance and predict runoff as a function of some empirical parameters. Since corresponding values are hardly measurable, modellers usually proceed to a calibration against available observations to obtain an acceptable match between observations and predictions. However, in the case of poorly monitored areas such as elevated catchments in the Andean Cordillera, good high frequency calibration data available over a long time span are scarce. Therefore, in spite of the development of multiple effective automatized calibration techniques in recent years, results remain uncertain because of the non-uniqueness of optimal parameter sets. A state-of-the-art option to cope with this predictive uncertainty is to consider ensembles of predictions rather than single ones. Furthermore, by gathering more independent parameterisations of the same processes, multi-model approaches allow a better representation of the uncertainty than multiple realisations of the same, eventually biased, model structure subjectively chosen by the modeller based on previous experience or project requirements. As a demonstration of the usefulness of this approach in scarcely-monitored areas, we present here results of an ensemble of heterogeneous rainfall-runoff models applied to the remote San Francisco (75 km2) tropical montane forest catchment, located in the southern part of Ecuador. Each of the 7 models (CHIMP, HBV-D, HBV-light, HMS, LASCAM, NAM, SWAT) is applied to simulate runoff whilst being forced by 6 increasingly uncertain meteorological data: on-site precipitation gauges record (also used for calibration), bias-corrected downscaled re-analysis (SDSM) output of the CCSM Regional Climate Model (RCM) over the first decade of the 21st century, and output of the same RCM forced by two different IPCC emission scenarios (A1B, B1) for two decades of the middle (2050-2059) and the end of the current century (2090-2099). Results show that the annual cumulative runoff and maximum flows should increase in this area during the 21st century. Furthermore, in spite of a good agreement in the timing of seasonal runoff patterns between rainfall-runoff models forced by the same input data, there is a great variability in the magnitude of predicted extreme values. The uncertainty in the RCM emission scenarios is not greater than the uncertainty between hydrological model predictions but the ensemble still allows targeting the most probable future.

  8. Assessing climate change impact by integrated hydrological modelling

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  9. A one-parameter Budyko model for water balance captures emergent behavior in darwinian hydrologic models

    NASA Astrophysics Data System (ADS)

    Wang, Dingbao; Tang, Yin

    2014-07-01

    Hydrologic models can be categorized as being either Newtonian or Darwinian in nature. The Newtonian approach requires a thorough understanding of the individual physical processes acting in a watershed in order to build a detailed hydrologic model based on the conservation equations. The Darwinian approach seeks to explain the behavior of a hydrologic system as a whole by identifying simple and robust temporal or spatial patterns that capture the relevant processes. Darwinian-based hydrologic models include the Soil Conservation Service (SCS) curve number model, the "abcd" model, and the Budyko-type models. However, these models were developed based on widely differing principles and assumptions and applied to distinct time scales. Here, we derive a one-parameter Budyko-type model for mean annual water balance which is based on a generalization of the proportionality hypothesis of the SCS model and therefore is independent of temporal scale. Furthermore, we show that the new model is equivalent to the key equation of the "abcd" model. Theoretical lower and upper bounds of the new model are identified and validated based on previous observations. Thus, we illustrate a temporal pattern of water balance amongst Darwinian hydrologic models, which allows for synthesis with the Newtonian approach and offers opportunities for progress in hydrologic modeling.

  10. Challenges in Urban Hydrologic Modeling: A Baltimore Case Study

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

  11. Intercomparison of hydrologic processes in global climate models

    NASA Technical Reports Server (NTRS)

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

    1995-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    In a major Danish funded research project (www.hyacints.dk) a coupling is being established between the HIRHAM regional climate model code from Danish Meteorological Institute and the MIKE SHE distributed hydrological model code from DHI. The linkage between those two codes is a soil vegetation atmosphere transfer scheme, which is a module of MIKE SHE. The coupled model will be established for the entire country of Denmark (43,000 km2 land area) where a MIKE SHE based hydrological model already exists (Henriksen et al., 2003, 2008). The present paper presents the MIKE SHE SVAT module and the methodology used for parameterising and calibrating the MIKE SHE SVAT module for use throughout the country. As SVAT models previously typically have been tested for research field sites with comprehensive data on energy fluxes, soil and vegetation data, the major challenge lies in parameterisation of the model when only ordinary data exist. For this purpose annual variations of vegetation characteristics (Leaf Area Index (LAI), Crop height, Root depth and the surface albedo) for different combinations of soil profiles and vegetation types have been simulated by use of the soil plant atmosphere model Daisy (Hansen et al., 1990; Abrahamsen and Hansen, 2000) has been applied. The MIKE SHE SVAT using Daisy generated surface/soil properties model has been calibrated against existing data on groundwater heads and river discharges. Simulation results in form of evapotranspiration and percolation are compared to the existing MIKE SHE model and to observations. To analyse the use of the SVAT model in climate change impact assessments data from the ENSEMBLES project (http://ensembles-eu.metoffice.com/) have been analysed to assess the impacts on reference evapotranspiration (calculated by the Makkink and the Penmann-Monteith equations) as well as on the individual elements in the Penmann-Monteith equation (radiation, wind speed, humidity and temperature). The differences on the hydrological impacts of characterising climate change in terms of changes in the reference evapotranspiration or in the individual climate variables have been analysed. References Abrahamsen, P., and Hansen, S. (2000) Daisy: An Open Soil-Crop-Atmosphere System Model. Environ. Model. Software 15, 313-330. Hansen, S., Jensen, H. E., Nielsen, N. E., and Svendsen, H. (1990). Daisy - soil plant atmostphere system model. Technical Report A10, Miljostyrelsen. Henriksen, H. J., Troldborg, L., Nyegaard, P., Sonnenborg, T. O., Refsgaard, J. C. and Madsen, B. (2003) Methodology for construction, calibration and validation of a national hydrological model for Denmark. Journal of Hydrology 280(1-4), 52-71. Henriksen, H. J., Troldborg, L., Hojberg, A. L. and Refsgaard, J. C. (2008) Assessment of exploitable groundwater resources of Denmark by use of ensemble resource indicators and a numerical groundwater-surface water model. Journal of Hydrology 348(1-2), 224-240.

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

    USGS Publications Warehouse

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

    2013-01-01

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

  14. Hydrological modeling of an ungauged watershed in Southern Andes

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  15. Hierarchical Modeling of Fen Hydrology across Multiple Scales

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  16. Hydrologic effects of evapotranspiration representation in a Richards equation based distributed hydrologic model at the catchment scale

    NASA Astrophysics Data System (ADS)

    Cristea, N. C.; Burges, S. J.

    2013-12-01

    Evapotranspiration (ET) is a key water budget term that is rarely evaluated in hydrologic modeling due to the scarcity of observed actual ET fluxes. However, the ET process representation within a hydrologic model is important as it affects the simulated hydrologic response. Here we illustrate how different ET representations affect both the hydrograph and the soil moisture states within MODHMS, a Richards' equation based distributed hydrologic model at the catchment scale. MODHMS, a MODFLOW based model, has a flexible modular structure that allowed testing of 4 different base case ET scenarios: two MODFLOW ET representations (linear and piece-wise linear) and one physically based ET model in two configurations. These 4 ET sub-models were applied sequentially for the case of the well-studied 10.5 ha - Tarrawarra catchment in Australia keeping the soil parameterization constant. The hydrologic response sensitivity to each of the ET sub-models parameterization was evaluated. The ET process representation chosen for use in MODHMS is important for adequately representing soil saturation areas, lateral flow and drying of the upslope areas of the catchment as well as the outflow hydrograph.

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

    NASA Astrophysics Data System (ADS)

    Zhuo, Lu; Han, Dawei

    2016-04-01

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

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

    SciTech Connect

    McManamay, Ryan A

    2014-01-01

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

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

    PubMed

    Beaumont, Elodie; Roingeard, Philippe

    2015-02-18

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

  20. Modeling Hydrologic and Vegetation Responses in Freshwater Wetlands

    NASA Astrophysics Data System (ADS)

    Chui, Ting Fong May; Low, Swee Yang; Liong, Shie-Yui

    2010-05-01

    Wetlands constitute 6 - 7 % of the Earth's land surface and provide various critical ecosystem services such as purifying the air and water, mitigating floods and droughts, and supporting wildlife habitats. Despite the importance of wetlands, they are under threat of degradation by human-induced land use changes and climate change. Even if the value of wetlands is recognized, they are often not managed properly or restored successfully due to an inadequate understanding of the ecosystems and their responses to management scenarios. A better understanding of the main components of wetlands, namely the interdependent hydrologic and vegetation systems, and the sensitivity of their responses to engineering works and climate change, is crucial for the preservation of wetlands. To assess these potential impacts, a model is developed in this study for characterizing the coupled dynamics between soil moisture and plant biomass in wetland habitats. The hydrology component of the model is based on the Richards' equation and simulates spatially-varying groundwater movement and provides information on soil moisture at different depths. The plant growth component of the model is described through an equation of the Lotka-Volterra type modified for plant growth dynamics and is adapted from published literature. The two components are coupled via transpiration and ecosystem carrying capacity for plants. Transpiration is modeled for both unsaturated and saturated zones, while the carrying capacity describes limiting oxygen and subsequent nutrient availability in the soil column as a function of water table depth. Vegetation is represented by two species characteristic of mudflat herbaceous plants ranging from facultative wetland to upland plants. The model is first evaluated using a simplified domain and the hydrological information available in the RG2 site of the Everglades wetlands region. The modeled water table fluctuations in general are comparable to field data collected on-site, indicating the potential of the model in capturing soil moisture dynamics. Further application of the model for impact assessments demonstrates that drainage of wetlands resulting in groundwater drawdown is expected to produce appreciable effects on vegetation biomass response. The model developed in this study simulates the coupled and spatially-varying groundwater movement and plant growth dynamics, which allows researchers to better understand and protect the integrated hydrologic and vegetation systems of wetlands worldwide.

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

    NASA Astrophysics Data System (ADS)

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

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

  2. Sensitivity testing of a coupled Escherichia coli - Hydrologic catchment model

    NASA Astrophysics Data System (ADS)

    Haydon, S.; Deletic, A.

    2007-05-01

    SummaryA conceptual model of microbial behaviour in catchments coupled with a standard hydrological model, known as the EG model, has been previously developed and tested for Escherichia coli. Due to the unavailability of pathogen data, E. coli has been used as a pathogen indicator. However, the model uses a broad conceptual approach and therefore should be tested for other microbes in future. This paper presents work done on sensitivity of the EG model, as well as its further refinement. Sensitivity of the model results to all E. coli calibration parameters was carried out. The EG model was then tested for its sensitivity to the number of events used to calibrate the model. The data collected at three different Australian drinking water catchments were used. Of the four parameters in the E. coli component of the EG model, two proved to be insensitive while the other two proved to be important. The sensitive parameters were the coefficients associated with the 'wash-off' functions in the model, while the two insensitive coefficients were associated with the E. coli decay functions in the model. However, the model became more sensitive towards the decay parameters in cleaner catchments. This indicates that the hydrologic aspects of the E. coli transport processes dominate rather than the E. coli decay functions. Apart from one catchment (that was partly urbanised and much smaller than the other two), the model was successfully calibrated using a small number of monitored events. It was concluded that the EG model could be simplified further by not modelling the decay of the pathogen indicator, E. coli.

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

    NASA Astrophysics Data System (ADS)

    Ficchi, Andrea; Perrin, Charles; Andréassian, Vazken

    2015-04-01

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

  4. S gene mutations of HBV in children with HBV-associated glomerulonephritis

    PubMed Central

    2012-01-01

    Background Hepatitis B virus-associated glomerulonephritis (HBV-GN) is a kind of immune complex-induced glomerulonephritis. The present study was designed to determine whether mutation of Hepatitis B virus (HBV) S gene is associated with glomerulonephritis in Chinese children. Methods Total 53 subjects, including 30 HBV-GN, 5 nephrosis with HBV carriers (control group 1), and 18 HBV carriers (control group 2) were included in this study. Polymerase chain reaction (PCR) was used to detect the HBV-GN S gene mutation. Results (1) The serotype of HBV was adw in the majority (52/53) of subjects, and was adr in only 1 subject in the control group 2; (2) the genotype of HBV was the type B in 51 subjects, the type E in 1 HBV-GN child, and the type C in 1 HBV carrier; (3) Seventeen point mutations in the S gene of HBV were identified in 21 of 30 (70%) HBV-GN patients. Among them, 16 of 21 (76.2%) mutations may cause amino acid substitutions of the HBV proteins, which occur predominantly (11/16 mutations) at threonine, serine or tyrosine phosphorylation sites of mitogen-activated protein kinase (MAPK) or protein tyrosine kinase (PTK). (4) In addition, single nucleotide mutations without amino acid substitutions (same sense mutation) were found in 2 subjects in each control group and 5 subjects in HBV-GN group. Conclusions HBV S gene mutations and the subsequent amino acid substitutions in HBV proteins were found in most children with HBV-GN, suggesting that these mutations may play an important role in the pathogenesis of HBV-GN. PMID:22390814

  5. Exploring Information Theory for improving Hydrologic Model Performance

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Cantone, Joshua; Schmidt, Arthur

    2011-08-01

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

  7. Semidistributed hydrologic modeling using remotely sensed data and GIS

    NASA Astrophysics Data System (ADS)

    Biftu, Getu Fana

    1998-12-01

    A semi-distributed, physically based hydrologic model (called DPHM-RS) is designed to take advantage of distributed hydrologic information retrieved from various space platform and topographic information processed from Digital Terrain Elevation Data (DTED). DPHM-RS was applied to the Paddle River Basin of central Alberta which was characterized by 5 sub-basins with each sub-basin having its own land cover types and terrain features. Input data to the model included meteorological data collected from 2 meteorological towers set up at the study site, field soil moisture data, topographic information derived from DTED, and distributed hydrologic information retrieved from NOAA-AVHRR, Landsat-TM, and Radarsat SAR data. DPHM-RS was calibrated with the data of summer, 1996 and validated with data of summer, 1997 and 1998. Excellent agreements between simulated and observed runoff at the basin outlet, energy fluxes and surface temperature demonstrated that DPHM-RS is capable of modeling basin-scale hydrologic processes. This is further confirmed by logical differences in the actual evapotranspiration (ET) simulated for different land covers and by sensible temporal variations of soil moisture simulated for each sub-basin. Given that in many aspects the performance of DPHM-RS is creditable, the ET component is used, the two-source model, to assess two popular ET models, the Penman-Menteith equation and the modified Penman equation of Granger and Gray (1989) for non-saturated surface. Based on the ET simulated for several land use classes, it seems that the closed canopy assumption of Penman-Menteith is applicable to coniferous forest and agricultural lands but not to mixed forest and pasturelands of the Canadian Prairies. The modified Penman model is generally applicable under dry environment but could estimate ET that is biased under cloudy, rainy days and wet environment. From 6 scenes of Radarsat SAR images acquired for the Paddle River Basin, and 1350 soil moisture samples collected in the same days from 9 selected sites of the Basin, we demonstrated the feasibility of retrieving near-surface soil moisture from Radarsat SAR images using a linear regression and the theoretical integration equation model (IEM) of Fung et al. (1992). From these data, we also found that for a single land use, the relationship between the cross-correlation of soil moisture and inter-site distance breaks down at a distance of about 250 m.

  8. Estimating Runoff From Roadcuts With a Distributed Hydrologic Model

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. How simple can a distributed hydrological model be?

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  11. Genetic Algorithm Optimization of Artificial Neural Networks for Hydrological Modelling

    NASA Astrophysics Data System (ADS)

    Abrahart, R. J.

    2004-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  13. Mid-Holocene hydrologic model of the Shingobee watershed, Minnesota

    USGS Publications Warehouse

    Filby, S.K.; Locke, Sharon M.; Person, M.A.; Winter, T.C.; Rosenberry, D.O.; Nieber, J.L.; Gutowski, W.J.; Ito, E.

    2002-01-01

    A hydrologifc model of the Shingobee Watershed in north-central Minnesota was developed to reconstruct mid-Holocene paleo-lake levels for Williams Lake, a surface-water body located in the southern portion of the watershed. Hydrologic parameters for the model were first estimated in a calibration exercise using a 9-yr historical record (1990-1998) of climatic and hydrologic stresses. The model reproduced observed temporal and spatial trends in surface/groundwater levels across the watershed. Mid-Holocene aquifer and lake levels were then reconstructed using two paleoclimatic data sets: CCM1 atmospheric general circulation model output and pollen-transfer functions using sediment core data from Williams Lake. Calculated paleo-lake levels based on pollen-derived paleoclimatic reconstructions indicated a 3.5-m drop in simulated lake levels and were in good agreement with the position of mid-Holocene beach sands observed in a Williams Lake sediment core transect. However, calculated paleolake levels based on CCM1 climate forcing produced only a 0.05-m drop in lake levels. We found that decreases in winter precipitation rather than temperature increases had the largest effect on simulated mid-Holocene lake levels. The study illustrates how watershed models can be used to critically evaluate paleoclimatic reconstructions by integrating geologic, climatic, limnologic, and hydrogeologic data sets. ?? 2002 University of Washington.

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

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

    SciTech Connect

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

    2006-05-05

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

  16. Assessing spatial patterns to characterize performance in hydrological modeling

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Herma, Felix; Bárdossy, András; Hörning, Sebastian

    2015-04-01

    Hydrological modelling is an important tool for many applications in water resources engineering. It is widely used for designing storage reservoirs, flood protection measures or for prediction purposes. Therefore the quality of the required input data and the used hydrological model have a significant influence on the quality of the results and, consequently, on the reliability for the mentioned objectives above. Many factors affect the usefulness of data and models. In the first place, the number and spatial distribution of observation points build the base for all subsequent processes. Secondly, the quality of the input data, e.g. discharge, precipitation, has to be checked. It is known that rain gauge measurements underlie a high uncertainty, especially during periods with high rain intensities or snowfall. Last, the choice of the model according to the objective of its usage is the determining factor. Under such conditions a reliable assessment of the uncertainty is required. This contribution will focus on the described items and try to provide approaches on how to handle the presented problems. A hydrological model usually needs areal information of specific input data. The density and distribution of gauging stations lead to uncertainty if a spatial interpolation of the measures is applied. In the case of a high topographic variability within a catchment, uncertainties through the underestimation of rainfall amounts at exposed stations can occur. Drifts of rain or snow by wind are a central issue at this point. Common interpolation methods of precipitation are different forms of kriging which provide only the best estimate at the ungauged locations. However, these methods cannot correctly quantify the associated uncertainty of the estimation. Thus, this contribution applies a new method of random mixing of spatial random fields with the ability to incorporate equality and inequality constraints. Such conditions are applied to exposed gauging stations on different elevation levels. Instead of an interpolated kriging field, a number of simulated realizations of precipitation are passed to a hydrological model. This approach allows a better assessment of the uncertainty induced by the lack of spatial information at ungauged locations as well as the measurement inaccuracy under certain meteorological conditions at certain conditional points. The applied hydrological model has a lumped configuration and requires as input data just discharge, precipitation, temperature and evapotranspiration. Based on the comparatively simple model set-up it is checked if a distributed external pre-processing of the input data on a high spatial resolution yields a gain of information and an improved model performance. This is shown by using the example of temporal and spatial snow distributions. Hereby it is investigated if a simple model approach combined with an elaborated pre-processing is sufficient or even improving, for instance, the prediction of snowmelt caused flood events. The results are presented on the basis of a catchment in south-eastern Bavaria, Germany. The catchment is characterized by its high topographic variability. In addition, the measuring network is very unbalanced within the catchment and contains regions with very rare coverage of gauging stations. There, measured data of low quality can have an essential impact on spatial interpolations, model results and, finally, on the predictions.

  20. Spatial interpolation schemes of daily precipitation for hydrologic modeling

    USGS Publications Warehouse

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

    2012-01-01

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

  1. Modelling exploration of non-stationary hydrological system

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Sun, R.; Yuan, H.

    2013-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1983-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Liu, Yuanming; Zhang, Wanchang; Zhang, Zhijie

    2015-11-01

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

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

    PubMed

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

    2013-01-01

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

  6. Bayesian inverse modeling at the hydrological surface-subsurface interface

    NASA Astrophysics Data System (ADS)

    Cucchi, K.; Rubin, Y.

    2014-12-01

    In systems where surface and subsurface hydrological domains are highly connected, modeling surface and subsurface flow jointly is essential to accurately represent the physical processes and come up with reliable predictions of flows in river systems or stream-aquifer exchange. The flow quantification at the interface merging the two hydrosystem components is a function of both surface and subsurface spatially distributed parameters. In the present study, we apply inverse modeling techniques to a synthetic catchment with connected surface and subsurface hydrosystems. The model is physically-based and implemented with the Gridded Surface Subsurface Hydrologic Analysis software. On the basis of hydrograph measurement at the catchment outlet, we estimate parameters such as saturated hydraulic conductivity, overland and channel roughness coefficients. We compare maximum likelihood estimates (ML) with the parameter distributions obtained using the Bayesian statistical framework for spatially random fields provided by the Method of Anchored Distributions (MAD). While ML estimates maximize the probability of observing the data and capture the global trend of the target variables, MAD focuses on obtaining a probability distribution for the random unknown parameters and the anchors are designed to capture local features. We check the consistency between the two approaches and evaluate the additional information provided by MAD on parameter distributions. We also assess the contribution of adding new types of measurements such as water table depth or soil conductivity to the reduction of parameter uncertainty.

  7. Simultaneous calibration of hydrological models in geographical space

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

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

    USGS Publications Warehouse

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

    2014-01-01

    The One-Water Hydrologic Flow Model (MF-OWHM) is a MODFLOW-based integrated hydrologic flow model (IHM) that is the most complete version, to date, of the MODFLOW family of hydrologic simulators needed for the analysis of a broad range of conjunctive-use issues. Conjunctive use is the combined use of groundwater and surface water. MF-OWHM allows the simulation, analysis, and management of nearly all components of human and natural water movement and use in a physically-based supply-and-demand framework. MF-OWHM is based on the Farm Process for MODFLOW-2005 (MF-FMP2) combined with Local Grid Refinement (LGR) for embedded models to allow use of the Farm Process (FMP) and Streamflow Routing (SFR) within embedded grids. MF-OWHM also includes new features such as the Surface-water Routing Process (SWR), Seawater Intrusion (SWI), and Riparian Evapotrasnpiration (RIP-ET), and new solvers such as Newton-Raphson (NWT) and nonlinear preconditioned conjugate gradient (PCGN). This IHM also includes new connectivities to expand the linkages for deformation-, flow-, and head-dependent flows. Deformation-dependent flows are simulated through the optional linkage to simulated land subsidence with a vertically deforming mesh. Flow-dependent flows now include linkages between the new SWR with SFR and FMP, as well as connectivity with embedded models for SFR and FMP through LGR. Head-dependent flows now include a modified Hydrologic Flow Barrier Package (HFB) that allows optional transient HFB capabilities, and the flow between any two layers that are adjacent along a depositional or erosional boundary or displaced along a fault. MF-OWHM represents a complete operational hydrologic model that fully links the movement and use of groundwater, surface water, and imported water for consumption by irrigated agriculture, but also of water used in urban areas and by natural vegetation. Supply and demand components of water use are analyzed under demand-driven and supply-constrained conditions. From large- to small-scale settings, MF-OWHM has the unique set of capabilities to simulate and analyze historical, present, and future conjunctive-use conditions. MF-OWHM is especially useful for the analysis of agricultural water use where few data are available for pumpage, land use, or agricultural information. The features presented in this IHM include additional linkages with SFR, SWR, Drain-Return (DRT), Multi-Node Wells (MNW1 and MNW2), and Unsaturated-Zone Flow (UZF). Thus, MF-OWHM helps to reduce the loss of water during simulation of the hydrosphere and helps to account for “all of the water everywhere and all of the time.” In addition to groundwater, surface-water, and landscape budgets, MF-OWHM provides more options for observations of land subsidence, hydraulic properties, and evapotranspiration (ET) than previous models. Detailed landscape budgets combined with output of estimates of actual evapotranspiration facilitates linkage to remotely sensed observations as input or as additional observations for parameter estimation or water-use analysis. The features of FMP have been extended to allow for temporally variable water-accounting units (farms) that can be linked to land-use models and the specification of both surface-water and groundwater allotments to facilitate sustainability analysis and connectivity to the Groundwater Management Process (GWM). An example model described in this report demonstrates the application of MF-OWHM with the addition of land subsidence and a vertically deforming mesh, delayed recharge through an unsaturated zone, rejected infiltration in a riparian area, changes in demand caused by deficiency in supply, and changes in multi-aquifer pumpage caused by constraints imposed through the Farm Process and the MNW2 Package, and changes in surface water such as runoff, streamflow, and canal flows through SFR and SWR linkages.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    EPA Science Inventory

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

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

    SciTech Connect

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

    2009-06-17

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

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

    NASA Technical Reports Server (NTRS)

    Houser, Paul R.

    1998-01-01

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

  14. A high-resolution European dataset for hydrologic modeling

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  15. A new selection metric for multiobjective hydrologic model calibration

    NASA Astrophysics Data System (ADS)

    Asadzadeh, Masoud; Tolson, Bryan A.; Burn, Donald H.

    2014-09-01

    A novel selection metric called Convex Hull Contribution (CHC) is introduced for solving multiobjective (MO) optimization problems with Pareto fronts that can be accurately approximated by a convex curve. The hydrologic model calibration literature shows that many biobjective calibration problems with a proper setup result in such Pareto fronts. The CHC selection approach identifies a subset of archived nondominated solutions whose map in the objective space forms convex approximation of the Pareto front. The optimization algorithm can sample solely from these solutions to more accurately approximate the convex shape of the Pareto front. It is empirically demonstrated that CHC improves the performance of Pareto Archived Dynamically Dimensioned Search (PA-DDS) when solving MO problems with convex Pareto fronts. This conclusion is based on the results of several benchmark mathematical problems and several hydrologic model calibration problems with two or three objective functions. The impact of CHC on PA-DDS performance is most evident when the computational budget is somewhat limited. It is also demonstrated that 1,000 solution evaluations (limited budget in this study) is sufficient for PA-DDS with CHC-based selection to achieve very high quality calibration results relative to the results achieved after 10,000 solution evaluations.

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

    USGS Publications Warehouse

    Lumb, Alan M.; Kittle, John L.

    1985-01-01

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

  17. Hydrological real-time modeling using remote sensing data

    NASA Astrophysics Data System (ADS)

    Meier, P.; Frömelt, A.; Kinzelbach, W.

    2010-11-01

    Reliable real-time forecasts of the discharge can provide valuable information for the management of a river basin system. Sequential data assimilation using the Ensemble Kalman Filter provides a both efficient and robust tool for a real-time modeling framework. One key parameter in a hydrological system is the soil moisture which recently can be characterized by satellite based measurements. A forecasting framework for the prediction of discharges is developed and applied to three different sub-basins of the Zambezi River Basin. The model is solely based on remote sensing data providing soil moisture and rainfall estimates. The soil moisture product used is based on the back-scattering intensity of a radar signal measured by the radar scatterometer on board the ERS satellite. These soil moisture data correlate well with the measured discharge of the corresponding watershed if the data are shifted by a time lag which is dependent on the size and the dominant runoff process in the catchment. This time lag is the basis for the applicability of the soil moisture data for hydrological forecasts. The conceptual model developed is based on two storage compartments. The processes modeled include evaporation losses, infiltration and percolation. The application of this model in a real-time modeling framework yields good results in watersheds where the soil storage is an important factor. For the largest watershed a forecast over almost six weeks can be provided. However, the quality of the forecast increases significantly with decreasing prediction time. In watersheds with little soil storage and a quick response to rainfall events the performance is relatively poor.

  18. A distributed hydrological model for urbanized areas - Model development and application to case studies

    NASA Astrophysics Data System (ADS)

    Rodriguez, Fabrice; Andrieu, Hervé; Morena, Floriane

    2008-04-01

    SummaryThe circulation of rainwater within urban areas has not yet been described in a detailed manner, as studies on this topic often remain limited to the runoff on impervious surfaces. The need for innovative and sustainable methods of water management has incited increased research efforts on the hydrological processes at work in urban areas. A distributed hydrological model based on information supplied by current urban databanks has been developed in this aim. The components of rainwater flux (i.e. surface runoff, soil runoff, drainage flow via the sewer, and evapotranspiration) as well as information on the hydric state of the urban soil (saturation level, storage capacity) are modeled at the parcel scale, and then coupled with a detailed description of the hydrographic network. This model runs continuously and has been intended to reproduce hydrological variables over very long time series. In order to evaluate this model, it has been applied at two different scales, on two urban catchments of various land use, where hydrological data were available. This evaluation is based on the comparison of observed and simulated flowrates and saturation levels, and details the various compartments (soil, impervious or natural areas) to the outflow. This study shows the importance of water fluxes often neglected in urban hydrology, such as the evapotranspiration or the soil infiltration into sewers. This first evaluation has highlighted the capability of mapping most of the hydrological fluxes on urban catchments, such as the capacity of soil to store water.

  19. Modelling of green roof hydrological performance for urban drainage applications

    NASA Astrophysics Data System (ADS)

    Locatelli, Luca; Mark, Ole; Mikkelsen, Peter Steen; Arnbjerg-Nielsen, Karsten; Bergen Jensen, Marina; Binning, Philip John

    2014-11-01

    Green roofs are being widely implemented for stormwater management and their impact on the urban hydrological cycle can be evaluated by incorporating them into urban drainage models. This paper presents a model of green roof long term and single event hydrological performance. The model includes surface and subsurface storage components representing the overall retention capacity of the green roof which is continuously re-established by evapotranspiration. The runoff from the model is described through a non-linear reservoir approach. The model was calibrated and validated using measurement data from 3 different extensive sedum roofs in Denmark. These data consist of high-resolution measurements of runoff, precipitation and atmospheric variables in the period 2010-2012. The hydrological response of green roofs was quantified based on statistical analysis of the results of a 22-year (1989-2010) continuous simulation with Danish climate data. The results show that during single events, the 10 min runoff intensities were reduced by 10-36% for 5-10 years return period and 40-78% for 0.1-1 year return period; the runoff volumes were reduced by 2-5% for 5-10 years return period and 18-28% for 0.1-1 year return period. Annual runoff volumes were estimated to be 43-68% of the total precipitation. The peak time delay was found to greatly vary from 0 to more than 40 min depending on the type of event, and a general decrease in the time delay was observed for increasing rainfall intensities. Furthermore, the model was used to evaluate the variation of the average annual runoff from green roofs as a function of the total available storage and vegetation type. The results show that even a few millimeters of storage can reduce the mean annual runoff by up to 20% when compared to a traditional roof and that the mean annual runoff is not linearly related to the storage. Green roofs have therefore the potential to be important parts of future urban stormwater management plans.

  20. European Continental Scale Hydrological Model, Limitations and Challenges

    NASA Astrophysics Data System (ADS)

    Rouholahnejad, E.; Abbaspour, K.

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Eisner, Stephanie; Flörke, Martina

    2013-04-01

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

  2. Epidemiology of HBV subgenotypes D.

    PubMed

    Ozaras, Resat; Inanc Balkan, Ilker; Yemisen, Mucahit; Tabak, Fehmi

    2015-02-01

    The natural history of hepatitis B virus infection is not uniform and affected from several factors including, HBV genotype. Genotype D is a widely distributed genotype. Among genotype D, several subgenotypes differentiate epidemiologically and probably clinically. D1 is predominant in Middle East and North Africa, and characterized by early HBeAg seroconversion and low viral load. D2 is seen in Albania, Turkey, Brazil, western India, Lebanon, and Serbia. D3 was reported from Serbia, western India, and Indonesia. It is a predominant subgenotype in injection drug use-related acute HBV infections in Europe and Canada. D4 is relatively rare and reported from Haiti, Russia and Baltic region, Brazil, Kenya, Morocco and Rwanda. Subgenotype D5 seems to be common in Eastern India. D6 has been reported as a rare subgenotype from Indonesia, Kenya, Russia and Baltic region. D7 is the main genotype in Morocco and Tunisia. D8 and D9 are recently described subgenotypes and reported from Niger and India, respectively. Subgenotypes of genotype D may have clinical and/or viral differences. More subgenotype studies are required to conclude on subgenotype and its clinical/viral characteristics. PMID:25037178

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  4. Hydrological modelling of slopes from field monitoring data

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Precipitation is one of the main sources of uncertainty in hydrological modelling, due to its high temporal and spatial variability. A dense network of rain gauge stations or a combination with, e.g., radar data is needed to account for the - in comparison to other climatic elements - pronounced variability. The density of existing station-networks is low in many countries worldwide. Alternative approaches that use additional information should be applied to improve the estimation of areal precipitation. Within the project "International Research Alliance Saxony" (http://www.iwas-sachsen.ufz.de/), one subproject aims at a system analysis of a meso-scale catchment of the Western Bug in Ukraine. Effective and sustainable measures have to be identified to improve the water quality of the Western Bug under the premise of upcoming changes of climate, land use and socio economy. An exact quantification of the water balance is needed as a pre-requisite for a matter balance. This contribution demonstrates possibilities to reduce the uncertainties of water balance modelling of the catchment Kamianka-Buzka/ Western Bug (2560 km2) by applying and combining alternative precipitation inputs. Available precipitation data were undergone an extensive quality check and were bias corrected. The Soil and Water Assessment Tool (SWAT, http://swatmodel.tamu.edu/) was used for water balance modelling. By default, meteorological observations are incorporated into SWAT using the station that is nearest to the centroid of each sub-catchment. Two alternative precipitation inputs were applied: 1) Data of 20 stations were regionalized using kriging methods. 2) The output of the Regional Climate Model CCLM that was set up for the region was used. After a pre-calibration of the model, three models - having different precipitation inputs - were set up and calibrated independently applying the auto-calibration procedure Sequential Uncertainty Fitting (Abbaspour et al. 2004). The performance of the models was evaluated with the Nash-Sutcliff-Efficiency coefficient (NSE) and the R2 between observed and modelled runoff. The model Stations performed better (R2/NSE: 0.66/0.61) than CCLM and Regionalized (0.54/0.54 and 0.57/0.53). Uncertainty of the hydrologic modelling (POC and d-factor) could not be reduced applying the alternative models. A promising method to improve the model performance and reduce the uncertainty is model averaging. Two model averaging methods were tested: arithmetic mean of the ensemble and a weighted mean (depending on NSE). The results show that the model performance could be improved (R2/NSE: 0.67/0.67) and the uncertainty reduced. Differences between the applied model averaging methods were marginal. Although not all observations could be reproduced, neither by the single models nor the ensemble averages, it was illustrated that combining different precipitation inputs improved the hydrologic predictions. Further calibration runs as well as the application of Bayesian Model Averaging are envisaged as next steps. Reference: Abbaspour, K. C., Johnson, C., & van Genuchten, M. T. (2004). Estimating uncertain flow and transport parameters using a sequential uncertainty fitting procedure. Vadose Zone Journal, (3), 1340-1352.

  6. Radar altimetry assimilation in catchment-scale hydrological models

    NASA Astrophysics Data System (ADS)

    Bauer-Gottwein, P.; Michailovsky, C. I. B.

    2012-04-01

    Satellite-borne radar altimeters provide time series of river and lake levels with global coverage and moderate temporal resolution. Current missions can detect rivers down to a minimum width of about 100m, depending on local conditions around the virtual station. Water level time series from space-borne radar altimeters are an important source of information in ungauged or poorly gauged basins. However, many water resources management applications require information on river discharge. Water levels can be converted into river discharge by means of a rating curve, if sufficient and accurate information on channel geometry, slope and roughness is available. Alternatively, altimetric river levels can be assimilated into catchment-scale hydrological models. The updated models can subsequently be used to produce improved discharge estimates. In this study, a Muskingum routing model for a river network is updated using multiple radar altimetry time series. The routing model is forced with runoff produced by lumped-parameter rainfall-runoff models in each subcatchment. Runoff is uncertain because of errors in the precipitation forcing, structural errors in the rainfall-runoff model as well as uncertain rainfall-runoff model parameters. Altimetric measurements are translated into river reach storage based on river geometry. The Muskingum routing model is forced with a runoff ensemble and storages in the river reaches are updated using a Kalman filter approach. The approach is applied to the Zambezi and Brahmaputra river basins. Assimilation of radar altimetry significantly improves the capability of the models to simulate river discharge.

  7. Translating hydrologically-relevant variables from the ice sheet model SICOPOLIS to the Greenland Analog Project hydrologic modeling domain

    NASA Astrophysics Data System (ADS)

    Vallot, Dorothée; Applegate, Patrick; Pettersson, Rickard

    2013-04-01

    Projecting future climate and ice sheet development requires sophisticated models and extensive field observations. Given the present state of our knowledge, it is very difficult to say what will happen with certainty. Despite the ongoing increase in atmospheric greenhouse gas concentrations, the possibility that a new ice sheet might form over Scandinavia in the far distant future cannot be excluded. The growth of a new Scandinavian Ice Sheet would have important consequences for buried nuclear waste repositories. The Greenland Analogue Project, initiated by the Swedish Nuclear Fuel and Waste Management Company (SKB), is working to assess the effects of a possible future ice sheet on groundwater flow by studying a constrained domain in Western Greenland by field measurements (including deep bedrock drilling in front of the ice sheet) combined with numerical modeling. To address the needs of the GAP project, we interpolated results from an ensemble of ice sheet model runs to the smaller and more finely resolved modeling domain used in the GAP project's hydrologic modeling. Three runs have been chosen with three fairly different positive degree-day factors among those that reproduced the modern ice margin at the borehole position. The interpolated results describe changes in hydrologically-relevant variables over two time periods, 115 ka to 80 ka, and 20 ka to 1 ka. In the first of these time periods, the ice margin advances over the model domain; in the second time period, the ice margin retreats over the model domain. The spatially-and temporally dependent variables that we treated include the ice thickness, basal melting rate, surface mass balance, basal temperature, basal thermal regime (frozen or thawed), surface temperature, and basal water pressure. The melt flux is also calculated.

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

    NASA Astrophysics Data System (ADS)

    Pannemans, B.

    2009-04-01

    Traditionally hydrological models are considered as difficult to calibrate: their highly non-linearity results in rugged and rough response surfaces were calibration algorithms easily get stuck in local minima. For the calibration of distributed hydrological models two extra factors play an important role: on the one hand they are often costly on computation, thus restricting the feasible number of model runs; on the other hand their distributed nature smooths the response surface, thus facilitating the search for a global minimum. Lisflood is a distributed hydrological model currently used for the European Flood Alert System - EFAS (Van der Knijff et al, 2008). Its upcoming recalibration over more then 200 catchments, each with an average runtime of 2-3 minutes, proved a perfect occasion to put several existing calibration algorithms to the test. The tested routines are Downhill Simplex (DHS, Nelder and Mead, 1965), SCEUA (Duan et Al. 1993), SCEM (Vrugt et al., 2003) and AMALGAM (Vrugt et al., 2008), and they were evaluated on their capability to efficiently converge onto the global minimum and on the spread in the found solutions in repeated runs. The routines were let loose on a simple hyperbolic function, on a Lisflood catchment using model output as observation, and on two Lisflood catchments using real observations (one on the river Inn in the Alps, the other along the downstream stretch of the Elbe). On the mathematical problem and on the catchment with synthetic observations DHS proved to be the fastest and the most efficient in finding a solution. SCEUA and AMALGAM are a slower, but while SCEUA keeps converging on the exact solution, AMALGAM slows down after about 600 runs. For the Lisflood models with real-time observations AMALGAM (hybrid algorithm that combines several other algorithms, we used CMA, PSO and GA) came as fastest out of the tests, and giving comparable results in consecutive runs. However, some more work is needed to tweak the stopping criteria. SCEUA is a bit slower, but has very transparent stopping rules. Both have closed in on the minima after about 600 runs. DHS equals only SCEUA on convergence speed. The stopping criteria we applied so far are too strict, causing it to stop too early. SCEM converges 5-6 times slower. This is a high price for the parameter uncertainty analysis that is simultaneously done. The ease with which all algorithms find the same optimum suggests that we are dealing with a smooth and relatively simple response surface. This leaves room for other deterministic calibration algorithms being smarter than DHS in sliding downhill. PEST seems promising but sofar we haven't managed to get it running with LISFLOOD. Duan, Q.; Gupta, V. & Sorooshian, S., 1993, Shuffled complex evolution approach for effective and efficient global minimization, J Optim Theory Appl, Kluwer Academic Publishers-Plenum Publishers, 76, 501-521 Nelder, J. & Mead, R., 1965, A simplex method for function minimization, Comput. J., 7, 308-313 Van Der Knijff, J. M.; Younis, J. & De Roo, A. P. J., 2008, LISFLOOD: a GIS-based distributed model for river basin scale water balance and flood simulation, International Journal of Geographical Information Science, Vrugt, J.; Gupta, H.; Bouten, W. & Sorooshian, S., 2003, A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters, Water Resour. Res., 39 Vrugt, J.; Robinson, B. & Hyman, J., 2008, Self-Adaptive Multimethod Search for Global Optimization in Real-Parameter Spaces, IEEE Trans Evol Comput, IEEE,

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  10. Hydrologic Modeling of Conservation Farming Practices on the Palouse

    NASA Astrophysics Data System (ADS)

    van Wie, J.; Adam, J. C.; Ullman, J.

    2009-12-01

    The production of dryland crops such as wheat and barley in a semi-arid region requires a reliable and adequate water supply. This supply of water available for crop use is of heightened importance in areas such as the Palouse region of eastern Washington and northern Idaho where the majority of annual rainfall occurs during the winter months and must be retained in the soil through the dry summer growing season. Farmers can increase conservation of water at the field and watershed scales through the adoption of best management practices that incorporate tillage and crop residue management. This research analyzes conservation farming practices that may be implemented by representing them in a watershed-scale hydrologic model in order to determine whether these practices will effectively save water so that a stable crop yield may be insured. The Distributed Hydrology Soil Vegetation Model (DHSVM) is applied and calibrated to represent the physical changes to infiltration, evaporation, and runoff that result from altered soil and vegetation characteristics brought on by management practices. The model is calibrated with field observations at the basin scale as well as the point scale over individual plots that are under various implementations of conservation management scenarios. Conservation practices are accounted for in DHSVM by adjusting input parameters such as the porosity, roughness, and hydraulic conductivity of the soil to characterize varying levels of tillage. Vegetation parameters such as leaf area index and albedo are altered to represent different amounts of crop residue left on the field through the winter months. After calibration, the model is applied over the entire basin under scenarios representing traditional agricultural methods and a region-wide shift to conservation practices. The resulting water balance suggests that there is a potential to retain water in the seed-zone during the winter months by decreasing evaporation and runoff through the use of conservation in tillage and residue management.

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1976-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  16. Evaluating snow models with varying process representations for hydrological applications

    NASA Astrophysics Data System (ADS)

    Magnusson, Jan; Wever, Nander; Essery, Richard; Helbig, Nora; Winstral, Adam; Jonas, Tobias

    2015-04-01

    Much effort has been invested in developing snow models over several decades, resulting in a wide variety of empirical and physically based snow models. For the most part, these models are built on similar principles. The greatest differences are found in how each model parameterizes individual processes (e.g., surface albedo and snow compaction). Parameterization choices naturally span a wide range of complexities. In this study, we evaluate the performance of different snow model parameterizations for hydrological applications using an existing multimodel energy-balance framework and data from two well-instrumented alpine sites with seasonal snow cover. We also include two temperature-index snow models and an intensive, physically based multilayer snow model in our analyses. Our results show that snow mass observations provide useful information for evaluating the ability of a model to predict snowpack runoff, whereas snow depth data alone are not. For snow mass and runoff, the energy-balance models appear transferable between our two study sites, a behavior which is not observed for snow surface temperature predictions due to site-specificity of turbulent heat transfer formulations. Errors in the input and validation data, rather than model formulation, seem to be the greatest factor affecting model performance. The three model types provide similar ability to reproduce daily observed snowpack runoff when appropriate model structures are chosen. Model complexity was not a determinant for predicting daily snowpack mass and runoff reliably. Our study shows the usefulness of the multimodel framework for identifying appropriate models under given constraints such as data availability, properties of interest and computational cost.

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

    NASA Astrophysics Data System (ADS)

    Wińska, Małgorzata; Nastula, Jolanta

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

  18. Improved cavity detection from coupled seismic and hydrologic models

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  19. Hydrologic Modeling of the White Sands Dune Field, New Mexico

    NASA Astrophysics Data System (ADS)

    Bourret, S. M.; Newton, B. T.; Person, M. A.

    2013-12-01

    The shallow groundwater flow system of White Sands dune field, located within the Tularosa Basin of Southern New Mexico, likely stabilizes the base of the largest gypsum dunefield in the world. Water table geometry and elevation play a critical role in controlling dune thickness, spatial extent, and migration rates. The White Sands National Monument (WHSA) is concerned that lowering the water table may lead to increased scour and migration of the dune field, which could be unfavorable to the preservation of the flora and fauna that have adapted to survive there. In response to projected increases in groundwater pumping in the regional Tularosa Basin groundwater system, changes in surface water use, and the threat of climate change, the WHSA is interested in understanding how these changes on a regional scale may impact the shallow dune aquifer. We have collected hydrological, geochemical, and geophysical data in order to identify the sources of recharge that contribute to the shallow dune aquifer and to assess interactions between this water table aquifer and the basin-scale, regional system. Vertical head gradients, temperature, and water quality data strongly suggest that local precipitation is the primary source of recharge to the dune aquifer today. This suggests that the modern dune system is relatively isolated from the deeper regional system. However, geochemical and electrical resistivity data indicates that the deeper basin groundwater system does contribute to the shallow system and suggests that hydrologic conditions have changed on geologic time scales. We have constructed a preliminary cross-sectional hydrologic model to attempt to characterize the interaction of the shallow dune aquifer with the deeper basin groundwater. The model cross-section extends about 80 km across the Tularosa Basin in a NW-SE direction parallel to the primary flow path. We represented 6 km of Precambrian crystalline basement, Paleozoic sedimentary rocks as well as Pleistocene and Quaternary units. Preliminary results indicate a component of deep groundwater flows to a depth of 5 km and is discharged near Lake Lucero located west of the WHSA. Computed and observed salinity and groundwater residence times are the primary means of model calibration. The results will allow for an improved understanding of the interaction between the basin- and dune-scale groundwater flow systems.

  20. Parameterization of potential evapotranspiration approaches for distributed hydrologic modeling

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  1. Hydrological Land Classification Based on Landscape Units

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  3. Modelling the hydrology of a catchment using a distributed and a semi-distributed model

    NASA Astrophysics Data System (ADS)

    El-Nasr, Ahmed Abu; Arnold, Jeffrey G.; Feyen, Jan; Berlamont, Jean

    2005-02-01

    Various hydrological models exist that describe the phases in the hydrologic cycle either in an empirical, semi-mechanistic or fully mechanistic way. The way and level of detail for the different processes of the hydrologic cycle that needs to be described depends on the objective, the application and the availability of data. In this study the performance of two different models, the fully distributed MIKE SHE model and the semi-distributed SWAT model, was assessed. The aim of the comparative study was to examine if both models are equally able to describe the different phases in the hydrologic cycle of a catchment, given the availability of hydrologic data in the catchment. For the comparison, historic data of the Jeker river basin, situated in the loamy belt region of Belgium, was used. The size of the catchment is 465 km2. The landscape is rolling, the dominant land use is farmland, and the soils vary from sandy-loam to clay-loam. The daily data of a continuous period of 6 years were used for the calibration and validation of both models. The results were obtained by comparing the performance of the two models using a qualitative (graphical) and quantitative (statistical) assessment, such as graphical representation of the observed and simulated river discharge, performance indices, the hydrograph maxima, the baseflow minima, the total accumulated volumes and the extreme value distribution of river flow data. The analysis revealed that both models are able to simulate the hydrology of the catchment in an acceptable way. The calibration results of the two tested models, although they differ in concept and spatial distribution, are quite similar. However, the MIKE SHE model predicts slightly better the overall variation of the river flow.

  4. Multi-model ensemble hydrologic prediction and uncertainties analysis

    NASA Astrophysics Data System (ADS)

    Jiang, S.; Ren, L.; Yang, X.; Ma, M.; Liu, Y.

    2014-09-01

    Modelling uncertainties (i.e. input errors, parameter uncertainties and model structural errors) inevitably exist in hydrological prediction. A lot of recent attention has focused on these, of which input error modelling, parameter optimization and multi-model ensemble strategies are the three most popular methods to demonstrate the impacts of modelling uncertainties. In this paper the Xinanjiang model, the Hybrid rainfall-runoff model and the HYMOD model were applied to the Mishui Basin, south China, for daily streamflow ensemble simulation and uncertainty analysis. The three models were first calibrated by two parameter optimization algorithms, namely, the Shuffled Complex Evolution method (SCE-UA) and the Shuffled Complex Evolution Metropolis method (SCEM-UA); next, the input uncertainty was accounted for by introducing a normally-distributed error multiplier; then, the simulation sets calculated from the three models were combined by Bayesian model averaging (BMA). The results show that both these parameter optimization algorithms generate good streamflow simulations; specifically the SCEM-UA can imply parameter uncertainty and give the posterior distribution of the parameters. Considering the precipitation input uncertainty, the streamflow simulation precision does not improve very much. While the BMA combination not only improves the streamflow prediction precision, it also gives quantitative uncertainty bounds for the simulation sets. The SCEM-UA calculated prediction interval is better than the SCE-UA calculated one. These results suggest that considering the model parameters' uncertainties and doing multi-model ensemble simulations are very practical for streamflow prediction and flood forecasting, from which more precision prediction and more reliable uncertainty bounds can be generated.

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

    NASA Astrophysics Data System (ADS)

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

    2002-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Tachecí, Pavel; Kimlová, Martina

    2010-05-01

    There is a need for warning system giving prediction of flash-flood risk conditions with sufficient advance even in source areas and in small tributaries catchments. New approach is based on combination of numerical weather prediction (NWP) model, radar or rain gauge data with distributed hydrologic mathematical model of particular area. Set of newly developed tools, customized for particular use in the Czech Hydrometeorological Institute (CHMI) environment enhance import of data and presentation of results. This forecast system focuses on hydrological modelling of running water balance in spatially distributed manner. Its computation is repeated day-to-day. Six models of particular basins (800 - 4000 km2), representing different conditions across the Czech Republic territory were calibrated and validated successfully. The Sázava river basin model (4.000 km2) is used for regular testing operation in CHMI Forecast centre since October 2007. Basic size of grid cells used in models is 300x300 m, basic time step of forecast is 1 day, but can be refined according to the input data. Water balance is computed using simplified 2-layer method for unsaturated zone, 2D approximation of Boussinesq equation for saturated zone, diffusion equation for overland flow and 1D kinematic equation for river flow (MIKE 11 model). The whole process of input data processing, model simulation and result generation may be run automatically or in step-by step mode via simple graphical user interface. Three types of input data are supported: •time series (temperature and precipitation) measured at observation stations and stored in CHMI database •radar data products (precipitation intensity field) •results of ALADIN weather forecast model (temperature and precipitation field). For forecast purposes, reference evapotranspiration is approximated according relationship to air temperature for every computational grid cell. The user may choose area (catchment) to be processed and period of simulation. Back-calculation of initial conditions using regular observation network data is applied to minimize errors of water balance. Scaled values of simulated deficit of water content in unsaturated zone, aggregated over user-defined areas, were chosen as flash-flood danger indicator. User - defined templates for presentation of results are available. The advantage of this approach sustains in a fact, that it uses three different types of input data. Further on, it may give results for user-defined areas, which are not necessarily connected to on-line flow gauging station profiles. This means, that it is capable to give flash-flood danger maps also for upper catchments and small tributaries, which are not included in the network of main warning profiles.

  7. Visualization in hydrological and atmospheric modeling and observation

    NASA Astrophysics Data System (ADS)

    Helbig, C.; Rink, K.; Kolditz, O.

    2013-12-01

    In recent years, visualization of geoscientific and climate data has become increasingly important due to challenges such as climate change, flood prediction or the development of water management schemes for arid and semi-arid regions. Models for simulations based on such data often have a large number of heterogeneous input data sets, ranging from remote sensing data and geometric information (such as GPS data) to sensor data from specific observations sites. Data integration using such information is not straightforward and a large number of potential problems may occur due to artifacts, inconsistencies between data sets or errors based on incorrectly calibrated or stained measurement devices. Algorithms to automatically detect various of such problems are often numerically expensive or difficult to parameterize. In contrast, combined visualization of various data sets is often a surprisingly efficient means for an expert to detect artifacts or inconsistencies as well as to discuss properties of the data. Therefore, the development of general visualization strategies for atmospheric or hydrological data will often support researchers during assessment and preprocessing of the data for model setup. When investigating specific phenomena, visualization is vital for assessing the progress of the ongoing simulation during runtime as well as evaluating the plausibility of the results. We propose a number of such strategies based on established visualization methods that - are applicable to a large range of different types of data sets, - are computationally inexpensive to allow application for time-dependent data - can be easily parameterized based on the specific focus of the research. Examples include the highlighting of certain aspects of complex data sets using, for example, an application-dependent parameterization of glyphs, iso-surfaces or streamlines. In addition, we employ basic rendering techniques allowing affine transformations, changes in opacity as well as variation of transfer functions. We found that similar strategies can be applied for hydrological and atmospheric data such as the use of streamlines for visualization of wind or fluid flow or iso-surfaces as indicators of groundwater recharge levels in the subsurface or levels of humidity in the atmosphere. We applied these strategies for a wide range of hydrological and climate applications such as groundwater flow, distribution of chemicals in water bodies, development of convection cells in the atmosphere or heat flux on the earth's surface. Results have been evaluated in discussions with experts from hydrogeology and meteorology.

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

    NASA Astrophysics Data System (ADS)

    Kim, J.; Hogue, T.

    2005-12-01

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

  9. An eco-hydrologic model of malaria outbreaks

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Peckham, S. D.

    2012-12-01

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

  12. The transcription factor c-JUN/AP-1 promotes HBV-related liver tumorigenesis in mice.

    PubMed

    Trierweiler, C; Hockenjos, B; Zatloukal, K; Thimme, R; Blum, H E; Wagner, E F; Hasselblatt, P

    2016-04-01

    Hepatocellular carcinoma (HCC) develops as a consequence of chronic inflammatory liver diseases such as chronic hepatitis B virus (HBV) infection. The transcription factor c-Jun/activator protein 1 (AP-1) is strongly expressed in response to inflammatory stimuli, promotes hepatocyte survival during acute hepatitis and acts as an oncogene during chemically induced liver carcinogenesis in mice. Here, we therefore aimed to characterize the functions of c-Jun during HBV-related liver tumorigenesis. To this end, transgenic mice expressing all HBV envelope proteins (HBV(+)), an established model of HBV-related HCC, were crossed with knockout mice lacking c-Jun specifically in hepatocytes and tumorigenesis was analyzed. Hepatic expression of c-Jun was strongly induced at several time points during tumorigenesis in HBV(+) mice, whereas expression of other AP-1 components remained unchanged. Importantly, formation of premalignant foci and tumors was strongly reduced in HBV(+) mice lacking c-Jun. This phenotype correlated with impaired hepatocyte proliferation and increased expression of the cell cycle inhibitor p21, whereas hepatocyte survival was not affected. Progression and prognosis of HBV-related HCC correlates with the expression of the cytokine osteopontin (Opn), an established AP-1 target gene. Opn expression was strongly reduced in HBV(+) livers and primary mouse hepatocytes lacking c-Jun, demonstrating that c-Jun regulates hepatic Opn expression in a cell-autonomous manner. These findings indicate that c-Jun has important functions during HBV-associated tumorigenesis by promoting hepatocyte proliferation as well as progression of dysplasia. Therefore, targeting c-Jun may be a useful strategy to prevent hepatitis-associated tumorigenesis. PMID:26470729

  13. Test of Landsat-based urban hydrologic modeling

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  14. Hydrologic modeling of two glaciated watersheds in Northeast Pennsylvania

    USGS Publications Warehouse

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

    1998-01-01

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

  15. Possible origins and evolution of the hepatitis B virus (HBV).

    PubMed

    Locarnini, Stephen; Littlejohn, Margaret; Aziz, Muhammad Nazri; Yuen, Lilly

    2013-12-01

    All members of the family Hepadnaviridae are primarily viruses which contain double-stranded DNA genomes that are replicated via reverse transcription of a pregenomic RNA template. There are two subgroups within this family: mammalian and avian. The avian member's include the duck hepatitis B virus (DHBV), heron hepatitis B virus, Ross goose hepatitis B virus, stork hepatitis B virus and the recently identified parrot hepatitis B virus. More recently, the detection of endogenous avian hepadnavirus DNA integrated into the genomes of zebra finches has revealed a deep evolutionary origin of hepadnaviruses that was not previously recognised, dating back over 40 million years ago. The non-primate mammalian members of the Hepadnaviridae include the woodchuck hepatitis virus (WHV), the ground squirrel hepatitis virus and arctic squirrel virus, as well as the recently described bat hepatitis virus. The identification of hepatitis B virus (HBV) in higher primates such as chimpanzee, gorilla, orangutan, and gibbons that cluster with the human genotypes further implies a more complex origin of this virus. By studying the molecular epidemiology of HBV in indigenous and relict populations in Asia-Pacific we propose a model for the origin and evolution of HBV that involves multiple cross-species transmissions and subsequent recombination events on a background of genotype C HBV infection. PMID:24013024

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

    NASA Astrophysics Data System (ADS)

    Wińska, Małgorzata; Nastula, Jolanta; Salstein, David

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  18. Parameterization of a hydrological model using remote sensing data

    NASA Astrophysics Data System (ADS)

    Oppelt, N.; Rathjens, H.; Müller, T.-L.

    2012-04-01

    The alteration of land cover by humans has multiple consequences on biological systems ranging from local to global scales. The United Nations have rated land use changes as one of the major issues for the coming centuries. In Northern Germany a significant land use change can be observed since 2004, i.e. the amendment of the Renewable Energies Act. Since then, an increasing number of biogas plants have been built resulting in an increased cultivation of so-called energy crops, especially in direct neighbourhood to these plants. Conversion of land is known to alter hydrological processes such as the exchange of energy and water. To investigate the effects of land use change on the water cycle in lowland river catchments in Northern Germany, we used a series of land cover data for the Upper Stoer, a sub-catchment of the river Elbe, as the input for a hydrological model. To derive the land cover data, we applied maximum-likelihood classifications of Landsat TM data for the years 2003 and 2010. The open source model suite SWAT (Soil Water Assessment Tool) was used to model the water cycle. SWAT has proven to be a useful tool for simulating the effect of watershed processes and management practices on water resources. A comparison of the modelled and observed discharge at the outlet of the catchment (gauge Willenscharen) showed good results (Nash Sutcliffe = 0.62). However, the land use change had no measurable effect on the discharge at the outlet due to the masking influence of high groundwater levels in the catchment. Therefore focusing on the discharge at the outlet is not a suitable approach in such cases. To represent the spatial characteristics of a catchment as realistically as possible, the catchment area must be spatially discretized. The configuration used primarily within SWAT is the sub-watershed discretization scheme. This results in a loss of spatial information, which is problematic for our intended applications. Therefore we developed an alternative model interface to manage input and output data based on grid cells. This enabled us to model the changes in evapotranspiration patterns in the catchment with changing land use more realistically and to calculate the water balance for each grid cell without losing its geographic reference. Therefore, the grid cells can interact with each other and exchange matter and energy, which was not possible using the sub-watershed approach. Therefore, the grid-cell interface enables the implementation of remote sensing data to provide a spatially distributed modelling.

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

    USGS Publications Warehouse

    Lopes, Thomas J.; Allander, Kip K.

    2009-01-01

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    ERIC Educational Resources Information Center

    Burt, Tim; Butcher, Dave

    1986-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Finger, David

    2015-04-01

    About 80% of the domestic energy production in Iceland comes from renewable energies. Hydropower accounts for about 20% this production, representing about 75% of the total electricity production in Iceland. In 2008 total electricity production from hydropower was about 12.5 TWh a-1, making Iceland a worldwide leader in hydropower production per capita. Furthermore, the total potential of hydroelectricity in Iceland is estimated to amount up to 220 TWh a-1. In this regard, hydrological modelling is an essential tool to adapt a sustainable management of water resources and estimate the potential of possible new sites for hydropower production. We used the conceptual lumped Hydrologiska Byråns Vattenbalansavdelning model (HBV) to estimate the potential of hydropower production in two remote areas in north-eastern Iceland (Leirdalshraun, a 274 km2 area above 595 m asl and Hafralónsá, a 946 km2 area above 235 m asl). The model parameters were determined by calibrating the model with discharge data from gauged sub catchments. Satellite snow cover images were used to constrain melt parameters of the model and assure adequate modelling of snow melt in the ungauged areas. This was particularly valuable to adequately estimate the contribution of snow melt, rainfall runoff and groundwater intrusion from glaciers outside the topographic boundaries of the selected watersheds. Runoff from the entire area potentially used for hydropower exploitation was estimated using the parameter sets of the gauged sub-catchments. Additionally, snow melt from the ungauged areas was validated with satellite based snow cover images, revealing a robust simulation of snow melt in the entire area. Based on the hydrological modelling the total amount of snow melt and rainfall runoff available in Leirdalshraun and Hafralónsá amounts up to 700 M m3 a-1 and 1000 M m3 a-1, respectively. These results reveal that the total hydropower potential of the two sites amounts up to 1.2 TWh a-1 hydroelectricity, accounting for about 10% of the current production in Iceland. These result are of eminent importance to embed sustainable and resilient based water management in discussions concerning future plans of national energy production.

  4. Optimal application of conceptual rainfall-runoff hydrological models in the Jinshajiang River basin, China

    NASA Astrophysics Data System (ADS)

    Tayyab, M.; Zhou, J.; Zeng, X.; Chen, L.; Ye, L.

    2015-05-01

    For specific research areas different hydrological models have shown different characteristics. By comparing different hydrological models on the same area we should get better and more authentic results. The objective of this research study is to highlight the importance of model selection for specific research areas. For the Jinshajiang River basin, three conceptual hydrological models including the Xin'anjiang model, the Antecedent precipitation index (API) model and the Tank model are applied to select the most suitable model for flood forecasting, based on the hourly rainfall and hourly discharge data. Data were analysed by comparing the simulation outputs of the three models with the Nash-Sutcliffe efficiency and Correlation coefficient index. Results showed that the performance of the three models were not very different. On the basis of data need and the characteristics of the research basin, the Xin'anjiang model was selected as the optimal and practical conceptual hydrological model for the Jinshajiang River basin.

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

    EPA Science Inventory

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

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

  7. Therapeutic vaccines in HBV: lessons from HCV.

    PubMed

    Barnes, Eleanor

    2015-02-01

    Currently, millions of people infected with hepatitis B virus (HBV) are committed to decades of treatment with anti-viral therapy to control viral replication. However, new tools for immunotherapy that include both viral vectors and molecular checkpoint inhibitors are now available. This has led to a resurgence of interest in new strategies to develop immunotherapeutic strategies with the aim of inducing HBeAg seroconversion--an end-point that has been associated with a decrease in the rates of disease progression. Ultimately, a true cure will involve the elimination of covalently closed circular DNA which presents a greater challenge for immunotherapy. In this manuscript, I describe the development of immunotherapeutic strategies for HBV that are approaching or currently in clinical studies, and draw on observations of T cell function in natural infection supported by recent animal studies that may lead to additional rational vaccine strategies using checkpoint inhibitors. I also draw on our recent experience in developing potent vaccines for HCV prophylaxis based on simian adenoviral and MVA vectors used in prime-boost strategies in both healthy volunteers and HCV infected patients. I have shown that the induction of T cell immune responses is markedly attenuated when administered to people with persistent HCV viremia. These studies and recently published animal studies using the woodchuck model suggest that potent vaccines based on DNA or adenoviral vectored vaccination represent a rational way forward. However, combining these with drugs to suppress viral replication, alongside checkpoint inhibitors may be required to induce long-term immune control. PMID:25573348

  8. Automatic input selection for hydrological modelling: a comparative analysis

    NASA Astrophysics Data System (ADS)

    Humphrey, Greer; Galelli, Stefano; Castelletti, Andrea; Maier, Holger; Dandy, Graham; Gibbs, Matthew

    2014-05-01

    Input variable selection is an essential step in the development of statistical models and is particularly relevant in hydrological modelling, where potential model inputs often consist of time lagged values of each different potential input variable. While new methods for identifying important model inputs continue to emerge, each has its own advantages and limitations and no method is best suited to all datasets and purposes. Nevertheless, rigorous evaluation of new and existing input variable selection methods is largely neglected due to the lack of guidelines or precedent to facilitate consistent and standardised assessment. This rigorous evaluation would allow the effectiveness of these algorithms to be properly identified in various circumstances. In this paper, we propose a new framework for the evaluation of input variable selection methods which takes into account a wide range of dataset properties that are relevant to real world data and assessment criteria selected to highlight algorithm suitability in different situations of interest. The framework is supported by a repository of data sets to enable standardised and statistically significant testing. This framework is supposed to help promoting the appropriate application and comparison of input variable selection algorithms and eventually serves to provide guidance as to which algorithm is most suitable in a given situation.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  10. A New Global River Network Database for Macroscale Hydrologic modeling

    SciTech Connect

    Wu, Huan; Kimball, John S.; Li, Hongyi; Huang, Maoyi; Leung, Lai-Yung R.; Adler, Robert F.

    2012-09-28

    Coarse resolution (upscaled) river networks are critical inputs for runoff routing in macroscale hydrologic models. Recently, Wu et al. (2011) developed a hierarchical Dominant River Tracing (DRT) algorithm for automated extraction and spatial upscaling of basin flow directions and river networks using fine-scale hydrography inputs (e.g., flow direction, river networks, and flow accumulation). The DRT was initially applied using HYDRO1K baseline fine-scale hydrography inputs and the resulting upscaled global hydrography maps were produced at several spatial scales, and verified against other available regional and global datasets. New baseline fine-scale hydrography data from HydroSHEDS are now available for many regions and provide superior scale and quality relative to HYDRO1K. However, HydroSHEDS does not cover regions above 60N. In this study, we applied the DRT algorithms using combined HydroSHEDS and HYDRO1K global fine-scale hydrography inputs, and produced a new series of upscaled global river network data at multiple (1/16 to 2) spatial resolutions in a consistent (WGS84) projection. The new upscaled river networks are internally consistent and congruent with the baseline fine-scale inputs. The DRT results preserve baseline fine-scale river networks independent of spatial scales, with consistency in river network, basin shape, basin area, river length, and basin internal drainage structure between upscaled and baseline fine-scale hydrography. These digital data are available online for public access (ftp://ftp.ntsg.umt.edu/pub/data/DRT/) and should facilitate improved regional to global scale hydrological simulations, including runoff routing and river discharge calculations.

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

    EPA Science Inventory

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    Highly instrumented research watersheds provide excellent opportunities for investigating hydrologic processes. A danger, however, is that the processes observed at a particular research watershed are too specific to the watershed and not representative even of the larger scale watershed that contains that particular research watershed. Thus, models developed based on those partial observations may not be suitable for general hydrologic use. Therefore demonstrating the upscaling of hydrologic process from research watersheds to larger watersheds is essential to validate concepts and test model structure. The Hydrograph model has been developed as a general-purpose process-based hydrologic distributed system. In its applications and further development we evaluate the scaling of model concepts and parameters in a wide range of hydrologic landscapes. All models, either lumped or distributed, are based on a discretization concept. It is common practice that watersheds are discretized into so called hydrologic units or hydrologic landscapes possessing assumed homogeneous hydrologic functioning. If a model structure is fixed, the difference in hydrologic functioning (difference in hydrologic landscapes) should be reflected by a specific set of model parameters. Research watersheds provide the possibility for reasonable detailed combining of processes into some typical hydrologic concept such as hydrologic units, hydrologic forms, and runoff formation complexes in the Hydrograph model. And here by upscaling we imply not the upscaling of a single process but upscaling of such unified hydrologic functioning. The simulation of runoff processes for the Dry Creek research watershed, Idaho, USA (27 km2) was undertaken using the Hydrograph model. The information on the watershed was provided by Boise State University and included a GIS database of watershed characteristics and a detailed hydrometeorological observational dataset. The model provided good simulation results in terms of runoff and variable states of soil and snow over a simulation period 2000 - 2009. The parameters of the model were hand-adjusted based on rational sense, observational data and available understanding of underlying processes. For the first run some processes as riparian vegetation impact on runoff and streamflow/groundwater interaction were handled in a conceptual way. It was shown that the use of Hydrograph model which requires modest amount of parameter calibration may serve also as a quality control for observations. Based on the obtained parameters values and process understanding at the research watershed the model was applied to the larger scale watersheds located in similar environment - the Boise River at South Fork (1660 km2) and Twin Springs (2155 km2). The evaluation of the results of such upscaling will be presented.

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

    NASA Astrophysics Data System (ADS)

    Thirel, Guillaume; Nicolas, Madeleine; Beersma, Jules

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

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

    NASA Astrophysics Data System (ADS)

    KONE, S.

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Pande, Saket

    2013-09-01

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

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

    NASA Technical Reports Server (NTRS)

    Laymon, Charles; Crosson, William

    1995-01-01

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

  19. Treatment of HBV-related cirrhosis.

    PubMed

    Vallet-Pichard, Anais; Mallet, Vincent; Costentin, Charlotte E; Pol, Stanislas

    2009-06-01

    The goal of antiviral therapy in HBV cirrhotic patients is to prevent progression of the disease to decompensated cirrhosis, end-stage liver disease, hepatocellular carcinoma and death. This goal can be achieved if HBV replication can be suppressed, leading to biochemical remission, histological improvement and prevention of complications. If finite treatment with pegylated interferon is not contraindicated in compensated cirrhosis, long-term treatment with nucleoside/nucleotide analogues is recommended in patients with HBV-related cirrhosis, especially in decompensated cirrhosis. Patients with cirrhosis require careful monitoring to detect resistance and prevent flares, and also to screen for hepatocellular carcinoma, portal hypertension and liver failure. PMID:19485793

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

    NASA Astrophysics Data System (ADS)

    Kennedy, M.; McKenzie, D.

    2013-12-01

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

  1. Impact of modellers' decisions on hydrological a priori predictions

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  2. Simulating hydrological responses with a physically based model in a mountainous watershed

    NASA Astrophysics Data System (ADS)

    Xu, Q.; Chen, X.; Bi, J.; Ouyang, R.; Ren, L.

    2015-06-01

    A physical and distributed approach was proposed by Reggiani et al. (1998) to describe the hydrological responses at the catchment scale. The rigorous balance equations for mass, momentum, energy and entropy are applied on the divided spatial domains which are called Representative Elementary Watershed (REW). Based on the 2nd law of thermodynamics, Reggiani (1999) put forward several constitutive relations of hydrological processes. Associated with the above equations, the framework of a physically based distributed hydrological model was established. The crucial step for successfully applying this approach is to develop physically based closure relations for these terms and simplify the set of equations. The paper showed how a theoretical hydrological model based on the REW method was applied to prosecute the hydrological response simulation for a humid watershed. The established model was used to carry on the long-term (daily runoff forecasting) and short-term (runoff simulation of storm event) hydrological simulation in the studied watershed and the simulated results were analysed. These results and analysis proved that this physically based distributed hydrological model can produce satisfied simulation results and describe the hydrological responses correctly. Finally, several aspects to improve the model demonstrated by the results and analysis were put forward which would be carried out in the future.

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

    USGS Publications Warehouse

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

    2004-01-01

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

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

    SciTech Connect

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

    2004-01-01

    Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregation (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.

  5. An Open Source modular platform for hydrological model implementation

    NASA Astrophysics Data System (ADS)

    Kolberg, Sjur; Bruland, Oddbjørn

    2010-05-01

    An implementation framework for setup and evaluation of spatio-temporal models is developed, forming a highly modularized distributed model system. The ENKI framework allows building space-time models for hydrological or other environmental purposes, from a suite of separately compiled subroutine modules. The approach makes it easy for students, researchers and other model developers to implement, exchange, and test single routines in a fixed framework. The open-source license and modular design of ENKI will also facilitate rapid dissemination of new methods to institutions engaged in operational hydropower forecasting or other water resource management. Written in C++, ENKI uses a plug-in structure to build a complete model from separately compiled subroutine implementations. These modules contain very little code apart from the core process simulation, and are compiled as dynamic-link libraries (dll). A narrow interface allows the main executable to recognise the number and type of the different variables in each routine. The framework then exposes these variables to the user within the proper context, ensuring that time series exist for input variables, initialisation for states, GIS data sets for static map data, manually or automatically calibrated values for parameters etc. ENKI is designed to meet three different levels of involvement in model construction: • Model application: Running and evaluating a given model. Regional calibration against arbitrary data using a rich suite of objective functions, including likelihood and Bayesian estimation. Uncertainty analysis directed towards input or parameter uncertainty. o Need not: Know the model's composition of subroutines, or the internal variables in the model, or the creation of method modules. • Model analysis: Link together different process methods, including parallel setup of alternative methods for solving the same task. Investigate the effect of different spatial discretization schemes. o Need not: Write or compile computer code, handle file IO for each modules, • Routine implementation and testing. Implementation of new process-simulating methods/equations, specialised objective functions or quality control routines, testing of these in an existing framework. o Need not: Implement user or model interface for the new routine, IO handling, administration of model setup and run, calibration and validation routines etc. From being developed for Norway's largest hydropower producer Statkraft, ENKI is now being turned into an Open Source project. At the time of writing, the licence and the project administration is not established. Also, it remains to port the application to other compilers and computer platforms. However, we hope that ENKI will prove useful for both academic and operational users.

  6. Impact of modellers' decisions on hydrological a priori predictions

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Wang, Z.; yang, J.

    2013-12-01

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

  8. Coupling of the simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To represent the effects of frozen soil on hydrology in cold regions, a new physically based distributed hydrological model has been developed by coupling the simultaneous heat and water model (SHAW) with the geomorphology based distributed hydrological model (GBHM), under the framework of the water...

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

    PubMed

    Burszta-Adamiak, E; Mrowiec, M

    2013-01-01

    Green roofs significantly affect the increase in water retention and thus the management of rain water in urban areas. In Poland, as in many other European countries, excess rainwater resulting from snowmelt and heavy rainfall contributes to the development of local flooding in urban areas. Opportunities to reduce surface runoff and reduce flood risks are among the reasons why green roofs are more likely to be used also in this country. However, there are relatively few data on their in situ performance. In this study the storm water performance was simulated for the green roofs experimental plots using the Storm Water Management Model (SWMM) with Low Impact Development (LID) Controls module (version 5.0.022). The model consists of many parameters for a particular layer of green roofs but simulation results were unsatisfactory considering the hydrologic response of the green roofs. For the majority of the tested rain events, the Nash coefficient had negative values. It indicates a weak fit between observed and measured flow-rates. Therefore complexity of the LID module does not affect the increase of its accuracy. Further research at a technical scale is needed to determine the role of the green roof slope, vegetation cover and drying process during the inter-event periods. PMID:23823537

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

    SciTech Connect

    Ehgartner, B.

    1991-06-01

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

  11. Modeling of Thermal-Hydrological-Chemical Laboratory Experiments

    SciTech Connect

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

    2001-05-31

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

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

    EPA Science Inventory

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

  13. Evapotranspiration and irrigation algorithms in hydrologic modeling:Present Status and Opportunities

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrologic models are used extensively for predicting water availability and water quality responses to alternative irrigation, tillage, crop, and fertilizer management practices and global climate change. Modeling results have been frequently used by regulatory agencies for developing remedial meas...

  14. Using expert knowledge of the hydrological system to constrain multi-objective calibration of SWAT models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The SWAT model is a helpful tool to predict hydrological processes in a study catchment and their impact on the river discharge at the catchment outlet. For reliable discharge predictions, a precise simulation of hydrological processes is required. Therefore, SWAT has to be calibrated accurately to ...

  15. Method of constructing distributed hydrological model based on GIS and RS

    NASA Astrophysics Data System (ADS)

    Zhang, Qiuwen; Wang, Cheng; Huang, Pei

    2006-10-01

    Hydrological model is very significant for the runoff simulation and flood prediction. Compared with lump hydrological model, distributed hydrological model has more specific physical mechanisms which consider the spatial non-uniformity of hydrological parameters in the river basin. Because of its complex space-related parameters, DHM is not easy to be constructed in conventional ways. The method and technology to realize DHM in practice have become the major bottleneck that has been restricting DHM construction. This paper proposes a new method for the construction of DHM based on GIS and RS. According to the method, GIS is not only adopted to extract the subcatchment and drainage system in river basin from DEM, but also applied to divide the hydrological subunits and to manage the space-related parameters. Multi-source remotely sensed images are utilized to acquire the parameters of all hydrological subunits distributed in the river basin. Based on the integrated application of GIS and RS, hydrological spatial information grid which serves as the platform of DHM construction is proposed. It is concluded that the integrated application of GIS and RS provides a new modern method for the realization of DHM, and makes it possible to construct a hydrological model in practice with the real meaning of "distributed in the whole scale of river basin".

  16. The Effect of Modeling and Visualization Resources on Student Understanding of Physical Hydrology

    ERIC Educational Resources Information Center

    Marshall, Jilll A.; Castillo, Adam J.; Cardenas, M. Bayani

    2015-01-01

    We investigated the effect of modeling and visualization resources on upper-division, undergraduate and graduate students' performance on an open-ended assessment of their understanding of physical hydrology. The students were enrolled in one of five sections of a physical hydrology course. In two of the sections, students completed homework

  17. The application of remote sensing to the development and formulation of hydrologic planning models: Executive summary

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

    Methods for the reduction of remotely sensed data and its application in hydrologic land use assessment, surface water inventory, and soil property studies are presented. LANDSAT data is used to provide quantitative parameters and coefficients to construct watershed transfer functions for a hydrologic planning model aimed at estimating peak outflow from rainfall inputs.

  18. The Effect of Modeling and Visualization Resources on Student Understanding of Physical Hydrology

    ERIC Educational Resources Information Center

    Marshall, Jilll A.; Castillo, Adam J.; Cardenas, M. Bayani

    2015-01-01

    We investigated the effect of modeling and visualization resources on upper-division, undergraduate and graduate students' performance on an open-ended assessment of their understanding of physical hydrology. The students were enrolled in one of five sections of a physical hydrology course. In two of the sections, students completed homework…

  19. A model-model and data-model comparison for the early Eocene hydrological cycle

    NASA Astrophysics Data System (ADS)

    Carmichael, Matthew J.; Lunt, Daniel J.; Huber, Matthew; Heinemann, Malte; Kiehl, Jeffrey; LeGrande, Allegra; Loptson, Claire A.; Roberts, Chris D.; Sagoo, Navjit; Shields, Christine; Valdes, Paul J.; Winguth, Arne; Winguth, Cornelia; Pancost, Richard D.

    2016-02-01

    A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP/dT) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.

  20. Rapid Prototyping of Hydrologic Model Interfaces with IPython

    NASA Astrophysics Data System (ADS)

    Farthing, M. W.; Winters, K. D.; Ahmadia, A. J.; Hesser, T.; Howington, S. E.; Johnson, B. D.; Tate, J.; Kees, C. E.

    2014-12-01

    A significant gulf still exists between the state of practice and state of the art in hydrologic modeling. Part of this gulf is due to the lack of adequate pre- and post-processing tools for newly developed computational models. The development of user interfaces has traditionally lagged several years behind the development of a particular computational model or suite of models. As a result, models with mature interfaces often lack key advancements in model formulation, solution methods, and/or software design and technology. Part of the problem has been a focus on developing monolithic tools to provide comprehensive interfaces for the entire suite of model capabilities. Such efforts require expertise in software libraries and frameworks for creating user interfaces (e.g., Tcl/Tk, Qt, and MFC). These tools are complex and require significant investment in project resources (time and/or money) to use. Moreover, providing the required features for the entire range of possible applications and analyses creates a cumbersome interface. For a particular site or application, the modeling requirements may be simplified or at least narrowed, which can greatly reduce the number and complexity of options that need to be accessible to the user. However, monolithic tools usually are not adept at dynamically exposing specific workflows. Our approach is to deliver highly tailored interfaces to users. These interfaces may be site and/or process specific. As a result, we end up with many, customized interfaces rather than a single, general-use tool. For this approach to be successful, it must be efficient to create these tailored interfaces. We need technology for creating quality user interfaces that is accessible and has a low barrier for integration into model development efforts. Here, we present efforts to leverage IPython notebooks as tools for rapid prototyping of site and application-specific user interfaces. We provide specific examples from applications in near-shore environments as well as levee analysis. We discuss our design decisions and methodology for developing customized interfaces, strategies for delivery of the interfaces to users in various computing environments, as well as implications for the design/implementation of simulation models.

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  2. On the use of spatially distributed, time-lapse microgravity surveys to inform hydrological modeling

    NASA Astrophysics Data System (ADS)

    Piccolroaz, Sebastiano; Majone, Bruno; Palmieri, Francesco; Cassiani, Giorgio; Bellin, Alberto

    2015-09-01

    In the last decades significant technological advances together with improved modeling capabilities fostered a rapid development of geophysical monitoring techniques in support of hydrological modeling. Geophysical monitoring offers the attractive possibility to acquire spatially distributed information on state variables. These provide complementary information about the functioning of the hydrological system to that provided by standard hydrological measurements, which are either intrinsically local or the result of a complex spatial averaging process. Soil water content is an example of state variable, which is relatively simple to measure pointwise (locally) but with a vanishing constraining effect on catchment-scale modeling, while streamflow data, the typical hydrological measurement, offer limited possibility to disentangle the controlling processes. The objective of this work is to analyze the advantages offered by coupling traditional hydrological data with unconventional geophysical information in inverse modeling of hydrological systems. In particular, we explored how the use of time-lapse, spatially distributed microgravity measurements may improve the conceptual model identification of a topographically complex Alpine catchment (the Vermigliana catchment, South-Eastern Alps, Italy). The inclusion of microgravity data resulted in a better constraint of the inversion procedure and an improved capability to identify limitations of concurring conceptual models to a level that would be impossible relying only on streamflow data. This allowed for a better identification of model parameters and a more reliable description of the controlling hydrological processes, with a significant reduction of uncertainty in water storage dynamics with respect to the case when only streamflow data are used.

  3. Hydrological improvements for nutrient and pollutant emission modeling in large scale catchments

    NASA Astrophysics Data System (ADS)

    Höllering, S.; Ihringer, J.

    2012-04-01

    An estimation of emissions and loads of nutrients and pollutants into European water bodies with as much accuracy as possible depends largely on the knowledge about the spatially and temporally distributed hydrological runoff patterns. An improved hydrological water balance model for the pollutant emission model MoRE (Modeling of Regionalized Emissions) (IWG, 2011) has been introduced, that can form an adequate basis to simulate discharge in a hydrologically differentiated, land-use based way to subsequently provide the required distributed discharge components. First of all the hydrological model had to comply both with requirements of space and time in order to calculate sufficiently precise the water balance on the catchment scale spatially distributed in sub-catchments and with a higher temporal resolution. Aiming to reproduce seasonal dynamics and the characteristic hydrological regimes of river catchments a daily (instead of a yearly) time increment was applied allowing for a more process oriented simulation of discharge dynamics, volume and therefore water balance. The enhancement of the hydrological model became also necessary to potentially account for the hydrological functioning of catchments in regard to scenarios of e.g. a changing climate or alterations of land use. As a deterministic, partly physically based, conceptual hydrological watershed and water balance model the Precipitation Runoff Modeling System (PRMS) (USGS, 2009) was selected to improve the hydrological input for MoRE. In PRMS the spatial discretization is implemented with sub-catchments and so called hydrologic response units (HRUs) which are the hydrotropic, distributed, finite modeling entities each having a homogeneous runoff reaction due to hydro-meteorological events. Spatial structures and heterogeneities in sub-catchments e.g. urbanity, land use and soil types were identified to derive hydrological similarities and classify in different urban and rural HRUs. In this way the hydrological system is simulated spatially differentiated and emissions from urban and rural areas into river courses can be detected separately. In the Ruhr catchment (4.485 km2) as a right tributary of the Rhine located in the lower mountain range of North Rhine-Westphalia in Germany for the validation period 2002-2006 the hydrological model showed first satisfying results. The feasibility study in the Ruhr shows the suitability of the approach and illustrates the potentials for further developments in terms of an implementation throughout the German and contiguous watersheds. IWG, Karlsruhe Institute of Technology (KIT). 2011. http://isww.iwg.kit.edu/MoRE.php. [Online] Institute for Water and River Basin Management, Department of Aquatic Environmental Engineering, October 2011. USGS, U.S. Geological Survey. 2009. PRMS-2009, the Precipitation-Runoff Modeling System. Denver, Colorado : s.n., 2009. Bd. U.S. Geologic Survey Open File Report.

  4. Two-Dimensional Coupled Distributed Hydrologic-Hydraulic Model Simulation on Watershed

    NASA Astrophysics Data System (ADS)

    Cea, Miguel; Rodriguez, Martin

    2016-03-01

    The objective of this work is to develop a coupled distributed model that enables to analyze water movement in watershed as well as analyze the rainfall-runoff. More specifically, it allows to estimate the various hydrologic water cycle variables at each point of the watershed. In this paper, we have carried out a coupled model of a distributed hydrological and two-dimensional hydraulic models. We have incorporated a hydrological rainfall-runoff model calculated by cell based on the Soil Conservation Service (SCS) method to the hydraulic model, leaving it for the hydraulic model (GUAD2D) to conduct the transmission to downstream cells. The goal of the work is demonstrate the improved predictive capability of the coupled Hydrological-Hydraulic models in a watershed.

  5. Two-Dimensional Coupled Distributed Hydrologic-Hydraulic Model Simulation on Watershed

    NASA Astrophysics Data System (ADS)

    Cea, Miguel; Rodriguez, Martin

    2015-10-01

    The objective of this work is to develop a coupled distributed model that enables to analyze water movement in watershed as well as analyze the rainfall-runoff. More specifically, it allows to estimate the various hydrologic water cycle variables at each point of the watershed. In this paper, we have carried out a coupled model of a distributed hydrological and two-dimensional hydraulic models. We have incorporated a hydrological rainfall-runoff model calculated by cell based on the Soil Conservation Service (SCS) method to the hydraulic model, leaving it for the hydraulic model (GUAD2D) to conduct the transmission to downstream cells. The goal of the work is demonstrate the improved predictive capability of the coupled Hydrological-Hydraulic models in a watershed.

  6. Coupling Radar Rainfall to Hydrological Models for Water Abstraction Management

    NASA Astrophysics Data System (ADS)

    Asfaw, Alemayehu; Shucksmith, James; Smith, Andrea; MacDonald, Ken

    2015-04-01

    The impacts of climate change and growing water use are likely to put considerable pressure on water resources and the environment. In the UK, a reform to surface water abstraction policy has recently been proposed which aims to increase the efficiency of using available water resources whilst minimising impacts on the aquatic environment. Key aspects to this reform include the consideration of dynamic rather than static abstraction licensing as well as introducing water trading concepts. Dynamic licensing will permit varying levels of abstraction dependent on environmental conditions (i.e. river flow and quality). The practical implementation of an effective dynamic abstraction strategy requires suitable flow forecasting techniques to inform abstraction asset management. Potentially the predicted availability of water resources within a catchment can be coupled to predicted demand and current storage to inform a cost effective water resource management strategy which minimises environmental impacts. The aim of this work is to use a historical analysis of UK case study catchment to compare potential water resource availability using modelled dynamic abstraction scenario informed by a flow forecasting model, against observed abstraction under a conventional abstraction regime. The work also demonstrates the impacts of modelling uncertainties on the accuracy of predicted water availability over range of forecast lead times. The study utilised a conceptual rainfall-runoff model PDM - Probability-Distributed Model developed by Centre for Ecology & Hydrology - set up in the Dove River catchment (UK) using 1km2 resolution radar rainfall as inputs and 15 min resolution gauged flow data for calibration and validation. Data assimilation procedures are implemented to improve flow predictions using observed flow data. Uncertainties in the radar rainfall data used in the model are quantified using artificial statistical error model described by Gaussian distribution and propagated through the model to assess its influence on the forecasted flow uncertainty. Furthermore, the effects of uncertainties at different forecast lead times on potential abstraction strategies are assessed. The results show that over a 10 year period, an average of approximately 70 ML/d of potential water is missed in the study catchment under a convention abstraction regime. This indicates a considerable potential for the use of flow forecasting models to effectively implement advanced abstraction management and more efficiently utilize available water resources in the study catchment.

  7. Modeling Feedbacks Between Individual Human Decisions and Hydrology Using Interconnected Physical and Social Models

    NASA Astrophysics Data System (ADS)

    Murphy, J.; Lammers, R. B.; Proussevitch, A. A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Alessa, L.; Kliskey, A. D.

    2014-12-01

    The global hydrological cycle intersects with human decision making at multiple scales, from dams and irrigation works to the taps in individuals' homes. Residential water consumers are commonly encouraged to conserve; these messages are heard against a background of individual values and conceptions about water quality, uses, and availability. The degree to which these values impact the larger-hydrological dynamics, the way that changes in those values have impacts on the hydrological cycle through time, and the feedbacks by which water availability and quality in turn shape those values, are not well explored. To investigate this domain we employ a global-scale water balance model (WBM) coupled with a social-science-grounded agent-based model (ABM). The integration of a hydrological model with an agent-based model allows us to explore driving factors in the dynamics in coupled human-natural systems. From the perspective of the physical hydrologist, the ABM offers a richer means of incorporating the human decisions that drive the hydrological system; from the view of the social scientist, a physically-based hydrological model allows the decisions of the agents to play out against constraints faithful to the real world. We apply the interconnected models to a study of Tucson, Arizona, USA, and its role in the larger Colorado River system. Our core concept is Technology-Induced Environmental Distancing (TIED), which posits that layers of technology can insulate consumers from direct knowledge of a resource. In Tucson, multiple infrastructure and institutional layers have arguably increased the conceptual distance between individuals and their water supply, offering a test case of the TIED framework. Our coupled simulation allows us to show how the larger system transforms a resource with high temporal and spatial variability into a consumer constant, and the effects of this transformation on the regional system. We use this to explore how pricing, messaging, and social dynamics impact demand, how changes in demand affect the regional water system, and under what system challenges the values of the individuals are likely to change. This study is a preamble to modeling multiple regionally connected cities and larger systems with impacts on hydrology at the continental and global scales.

  8. Modeling and monitoring the hydrological effects of the Sand Engine.

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  9. Improving statistical forecasts of seasonal streamflows using hydrological model output

    NASA Astrophysics Data System (ADS)

    Robertson, D. E.; Pokhrel, P.; Wang, Q. J.

    2013-02-01

    Statistical methods traditionally applied for seasonal streamflow forecasting use predictors that represent the initial catchment condition and future climate influences on future streamflows. Observations of antecedent streamflows or rainfall commonly used to represent the initial catchment conditions are surrogates for the true source of predictability and can potentially have limitations. This study investigates a hybrid seasonal forecasting system that uses the simulations from a dynamic hydrological model as a predictor to represent the initial catchment condition in a statistical seasonal forecasting method. We compare the skill and reliability of forecasts made using the hybrid forecasting approach to those made using the existing operational practice of the Australian Bureau of Meteorology for 21 catchments in eastern Australia. We investigate the reasons for differences. In general, the hybrid forecasting system produces forecasts that are more skilful than the existing operational practice and as reliable. The greatest increases in forecast skill tend to be (1) when the catchment is wetting up but antecedent streamflows have not responded to antecedent rainfall, (2) when the catchment is drying and the dominant source of antecedent streamflow is in transition between surface runoff and base flow, and (3) when the initial catchment condition is near saturation intermittently throughout the historical record.

  10. Improving statistical forecasts of seasonal streamflows using hydrological model output

    NASA Astrophysics Data System (ADS)

    Robertson, D. E.; Pokhrel, P.; Wang, Q. J.

    2012-07-01

    Statistical methods traditionally applied for seasonal streamflow forecasting use predictors that represent the initial catchment condition and future climate influences on future streamflows. Observations of antecedent streamflows or rainfall commonly used to represent the initial catchment conditions are surrogates for the true source of predictability and can potentially have limitations. This study investigates a hybrid seasonal forecasting system that uses the simulations from a dynamic hydrological model as a predictor to represent the initial catchment condition in a statistical seasonal forecasting method. We compare the skill and reliability of forecasts made using the hybrid forecasting approach to those made using the existing operational practice of the Australian Bureau of Meteorology for 21 catchments in eastern Australia. We investigate the reasons for differences. I