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Mendez, M., and L. Calvo-Valverde. "Development of the HBV-TEC Hydrological Model." Procedia Engineering 154 (2016): 1116–23. http://dx.doi.org/10.1016/j.proeng.2016.07.521.
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Akhtar, M., N. Ahmad, and M. J. Booij. "Use of regional climate model simulations as input for hydrological models for the Hindukush-Karakorum-Himalaya region." Hydrology and Earth System Sciences 13, no. 7 (July 9, 2009): 1075–89. http://dx.doi.org/10.5194/hess-13-1075-2009.
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Abstract. The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and results of the PRECIS (Providing REgional Climate for Impact Studies) RCM driven by the outputs of reanalysis ERA 40 data and HadAM3P general circulation model (GCM) results are used as input in the hydrological model. The objective is to investigate the effect of precipitation and temperature simulated with the PRECIS RCM nested in these two data sets on discharge simulated with the HBV model for three river basins in the Hindukush-Karakorum-Himalaya (HKH) region. Six HBV model experiments are designed: HBV-Met, HBV-ERA and HBV-Had, HBV-MetCRU-corrected, HBV-ERABenchmark and HBV-HadBenchmark where HBV is driven by meteorological stations data, data from PRECIS nested in ERA-40 and HadAM3P, meteorological stations CRU corrected data, ERA-40 reanalysis and HadAM3P GCM data, respectively. Present day PRECIS simulations possess strong capacity to simulate spatial patterns of present day climate characteristics. However, also some quantitative biases exist in the HKH region, where PRECIS RCM simulations underestimate temperature and overestimate precipitation with respect to CRU observations. The calibration and validation results of the HBV model experiments show that the performance of HBV-Met is better than the HBV models driven by other data sources. However, using input data series from sources different from the data used in the model calibration shows that HBV-Had is more efficient than other models and HBV-Met has the least absolute relative error with respect to all other models. The uncertainties are higher in least efficient models (i.e. HBV-MetCRU-corrected and HBV-ERABenchmark) where the model parameters are also unrealistic. In terms of both robustness and uncertainty ranges the HBV models calibrated with PRECIS output performed better than other calibrated models except for HBV-Met which has shown a higher robustness. This suggests that in data sparse regions such as the HKH region data from regional climate models may be used as input in hydrological models for climate scenarios studies.
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AghaKouchak, A., N. Nakhjiri, and E. Habib. "An educational model for ensemble streamflow simulation and uncertainty analysis." Hydrology and Earth System Sciences 17, no. 2 (February 1, 2013): 445–52. http://dx.doi.org/10.5194/hess-17-445-2013.
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Abstract. 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.
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AghaKouchak, A., N. Nakhjiri, and E. Habib. "An educational model for ensemble streamflow simulation and uncertainty analysis." Hydrology and Earth System Sciences Discussions 9, no. 6 (June 8, 2012): 7297–315. http://dx.doi.org/10.5194/hessd-9-7297-2012.
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Abstract. This paper presents a hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this model, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The model includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for not only hydrological processes, but also for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity.
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Zelelew, M. B., and K. Alfredsen. "Sensitivity-guided evaluation of the HBV hydrological model parameterization." Journal of Hydroinformatics 15, no. 3 (December 4, 2012): 967–90. http://dx.doi.org/10.2166/hydro.2012.011.
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Applying hydrological models for river basin management depends on the availability of the relevant data information to constrain the model residuals. The estimation of reliable parameter values for parameterized models is not guaranteed. Identification of influential model parameters controlling the model response variations either by main or interaction effects is therefore critical for minimizing model parametric dimensions and limiting prediction uncertainty. In this study, the Sobol variance-based sensitivity analysis method was applied to quantify the importance of the HBV conceptual hydrological model parameterization. The analysis was also supplemented by the generalized sensitivity analysis method to assess relative model parameter sensitivities in cases of negative Sobol sensitivity index computations. The study was applied to simulate runoff responses at twelve catchments varying in size. The result showed that varying up to a minimum of four to six influential model parameters for high flow conditions, and up to a minimum of six influential model parameters for low flow conditions can sufficiently capture the catchments' responses characteristics. To the contrary, varying more than nine out of 15 model parameters will not make substantial model performance changes on any of the case studies.
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Akhtar, M., N. Ahmad, and M. J. Booij. "Use of regional climate model simulations as input for hydrological models for the Hindukush–Karakorum–Himalaya region." Hydrology and Earth System Sciences Discussions 5, no. 2 (March 26, 2008): 865–902. http://dx.doi.org/10.5194/hessd-5-865-2008.
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Abstract. The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and results of the PRECIS (Providing REgional Climate for Impact Studies) RCM driven by the outputs of reanalysis ERA-40 data and HadAM3P general circulation model (GCM) results are used as input in the hydrological model. The objective is to investigate the effect of precipitation and temperature simulated with the PRECIS RCM nested in these two data sets on discharge simulated with the HBV model for three river basins in the Hindukush-Karakorum-Himalaya (HKH) region. Three HBV model experiments are designed: HBV-Met, HBV-ERA and HBV-Had where HBV is driven by meteorological station data and by the outputs from PRECIS nested with ERA-40 and HadAM3P data, respectively. Present day PRECIS simulations possess strong capacity to simulate spatial patterns of present day climate characteristics. However, there also exist some quantitative biases in the HKH region, where PRECIS RCM simulations underestimate temperature and overestimate precipitation with respect to CRU observations. The calibration and validation results of the HBV model experiments show that the performance of HBV-Met is better than the HBV models driven by the PRECIS outputs. However, using input data series from sources different from the data used in the model calibration shows that HBV models driven by the PRECIS outputs are more robust compared to HBV-Met. The Gilgit and Astore river basin, which discharges are depending on the preceding winter precipitation, have higher uncertainties compared to the Hunza river basin which discharge is driven by the energy inputs. The smaller uncertainties in the Hunza river basin may be because of the stable behavior of the input temperature series compared to the precipitation series. The resulting robustness and uncertainty ranges of the HBV models suggest that in data sparse regions such as the HKH region data from regional climate models may be used as input in hydrological models for climate scenarios studies.
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Lestari, Isnayulia, and Bambang Dwi Dasanto. "Determination of Extreme Hydrological Index using HBV Model Simulation Results (Case Study : Upper Ciliwung Watershed)." Agromet 33, no. 1 (June 11, 2019): 20–29. http://dx.doi.org/10.29244/j.agromet.33.1.20-29.
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The study of climate change on hydrological response is a crucial as climate change impact will drive the change in hydrological regimes of river. Upper Ciliwung watershed is one of the critical rivers in Java Island, which has been affected by climate change. This study aims to: (i) simulate the discharge flow using the Hydrologiska Byrans Vattenbalansavdelning (HBV) model; (ii) simulate future flow using three general circulation models (GCM) namely Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mk.3.6.0, Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Geophysical Fluid Dynamics Laboratory-Coupled Model generation 3 (GFDL-CM3); (iii) determine the changes of extreme hydrological index during historical period (2001-2015) and projected period (2031-2045). The historical year simulation and projections are used to determine eight hydrologic extreme indices for high flow and low flow. We calibrated the HBV model for two years (2001-2002) and validated it for two years (2003-2004). Our model performed well in discharge simulation as shown by the NSE values (0.66 for calibration and validation). Then we calculated the indices for each period used (historical and projected). To show the changes in hydrological regimes, we compare the indices between two periods. Changes in the index of the two periods tend to decrease in value on the index parameters that characterize the minimum extreme events. Hence, that it is possible in the projected period there will be extreme hydrological events in the form of drought.
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Shrestha, Subarna, and Knut Alfredsen. "Application of HBV Model in Hydrological Studies of Nepali River Basins: A Case Study." Hydro Nepal: Journal of Water, Energy and Environment 8 (October 12, 2012): 38–43. http://dx.doi.org/10.3126/hn.v8i0.4910.
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Ungauged basins are challenges for hydrological study, the key discipline to analyse for planning and the operation of water resources projects. Several river basins have no hydrologic measurements where there is feasibility of promising water resources schemes. This study deals with use of the Hydrologiska Byråns avdeling for Vattenbalans (HBV) hydrological model to generate stream flow time series and other hydrological variables. The model was calibrated successfully in the Sanghutar catchment of the Likhu River of Nepal, and then used to simulate runoff series at the proposed intake site of Likhu HEP, where the gauging station has not been installed. The model can be used to generate runoff of other ungauged catchments which have similar catchment characteristics.DOI: http://dx.doi.org/10.3126/hn.v8i0.4910 Hydro Nepal: Journal of Water, Energy and Environment Issue No. 8, 2011 JanuaryPage: 38-43Uploaded date: 17 June, 2011
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Medina, Yelena, and Enrique Muñoz. "Analysis of the Relative Importance of Model Parameters in Watersheds with Different Hydrological Regimes." Water 12, no. 9 (August 25, 2020): 2376. http://dx.doi.org/10.3390/w12092376.
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Depending on the purpose of the study, aggregated hydrological models are preferred over distributed models because they provide acceptable results in terms of precision and are easy to run, especially in data scarcity scenarios. To obtain acceptable results in terms of hydrological process representativeness, it is necessary to understand and assess the models. In this study, the relative importance of the parameters of the Hydrologiska Byråns Vattenbalansavdelning (HBV) model is analyzed using sensitivity analysis to detect if the simulated processes represent the predominant hydrological processes at watershed scale. As a case study, four watersheds with different hydrological regimes (glacial and pluvial) and therefore different dominant processes are analyzed. The results show that in the case of the rivers with a glacial regime, the model performance depends highly on the snow module parameters, while in the case of the rivers with a pluvial regime, the model is sensitive to the soil and evapotranspiration modules. The results are directly related to the hydrological regime, which indicates that the HBV model, complemented by sensitivity analysis, is capable of both detecting and representing hydrological processes at watershed scale.
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Machlica, Andrej, Oliver Horvát, Stanislav Horáček, Jacob Oosterwijk, Anne F. Van Loon, Miriam Fendeková, and Henny A. J. Van Lanen. "Influence of model structure on base flow estimation using Bilan, frier and HBV-light models / Vplyv štruktúry modelu na stanovenie veľkosti podzemného odtoku využitím modelov bilan, frier a hbv-light. j. hydrol. hydromech., 60, 2012, 4; 29 lit., 7 obr., 1 tab." Journal of Hydrology and Hydromechanics 60, no. 4 (December 1, 2012): 242–51. http://dx.doi.org/10.2478/v10098-012-0021-4.
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Hydrological models are widely used tools to solve a broad range of hydrological issues. Each model has its own structure defining inter-relationships of hydrological balance components, and comparative differences in the models’ inner structure must be taken into account when discrepancies result from the same data. Results of base flow simulation by three different models BILAN, FRIER and HBV-light were compared based on knowledge of the models’ internal structure. It was proven that the courses of modelled parameters are quite similar, but that the respective values differ. The highest base flow values were simulated by the BILAN model, due to the threshold value of the soil moisture storage incorporated within this model’s structure. The lowest values were obtained by HBV-light model. Simulated base flow values were compared with groundwater heads and minimum monthly discharges. This comparison showed that the base flow values in the Nitra catchment at Nedožery profile simulated by BILAN and FRIER models are closer to the reality than those, simulated by HBV-light model.
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Bui, Minh Tuan, Jinmei Lu, and Linmei Nie. "A Review of Hydrological Models Applied in the Permafrost-Dominated Arctic Region." Geosciences 10, no. 10 (October 6, 2020): 401. http://dx.doi.org/10.3390/geosciences10100401.
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The Arctic region is the most sensitive region to climate change. Hydrological models are fundamental tools for climate change impact assessment. However, due to the extreme weather conditions, specific hydrological process, and data acquisition challenges in the Arctic, it is crucial to select suitable hydrological model(s) for this region. In this paper, a comprehensive review and comparison of different models is conducted based on recently available studies. The functionality, limitations, and suitability of the potential hydrological models for the Arctic hydrological process are analyzed, including: (1) The surface hydrological models Topoflow, DMHS (deterministic modeling hydrological system), HBV (Hydrologiska Byråns Vattenbalansavdelning), SWAT (soil and water assessment tool), WaSiM (water balance simulation model), ECOMAG (ecological model for applied geophysics), and CRHM (cold regions hydrological model); and (2) the cryo-hydrogeological models ATS (arctic terrestrial simulator), CryoGrid 3, GEOtop, SUTRA-ICE (ice variant of the existing saturated/unsaturated transport model), and PFLOTRAN-ICE (ice variant of the existing massively parallel subsurface flow and reactive transport model). The review finds that Topoflow, HBV, SWAT, ECOMAG, and CRHM are suitable for studying surface hydrology rather than other processes in permafrost environments, whereas DMHS, WaSiM, and the cryo-hydrogeological models have higher capacities for subsurface hydrology, since they take into account the three phase changes of water in the near-surface soil. Of the cryo-hydrogeological models reviewed here, GEOtop, SUTRA-ICE, and PFLOTRAN-ICE are found to be suitable for small-scale catchments, whereas ATS and CryoGrid 3 are potentially suitable for large-scale catchments. Especially, ATS and GEOtop are the first tools that couple surface/subsurface permafrost thermal hydrology. If the accuracy of simulating the active layer dynamics is targeted, DMHS, ATS, GEOtop, and PFLOTRAN-ICE are potential tools compared to the other models. Further, data acquisition is a challenging task for cryo-hydrogeological models due to the complex boundary conditions when compared to the surface hydrological models HBV, SWAT, and CRHM, and the cryo-hydrogeological models are more difficult for non-expert users and more expensive to run compared to other models.
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Sarchani, Sofia, Frezer Seid Awol, and Ioannis Tsanis. "Hydrological Analysis of Extreme Rain Events in a Medium-Sized Basin." Applied Sciences 11, no. 11 (May 26, 2021): 4901. http://dx.doi.org/10.3390/app11114901.
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The hydrological response of a medium-sized watershed with both rural and urban characteristics was investigated through event-based modeling. Different meteorological event conditions were examined, such as events of high precipitation intensity, double hydrological peak, and mainly normal to wet antecedent moisture conditions. Analysis of the hydrometric features of the precipitation events was conducted by comparing the different rainfall time intervals, the total volume of water, and the precedent soil moisture. Parameter model calibration and validation were performed for rainfall events under similar conditions, examined in pairs, in order to verify two hydrological models, the lumped HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modeling System model) and the semi-distributed HBV-light (a recent version of Hydrologiska Byråns Vattenbalansavdelning model), at the exit of six individual gauged sub-basins. Model verification was achieved by using the Nash–Sutcliffe efficiency and volume error index. Different time of concentration (Tc) formulas are better applied to the sub-watersheds with respect to the dominant land uses, classifying the Tc among the most sensitive parameters that influence the time of appearance and the magnitude of the peak modeled flow through the HEC-HMS model. The maximum water content of the soil box (FC) affects most the peak flow via the HBV-light model, whereas the MAXBAS parameter has the greatest effect on the displayed time of peak discharge. The modeling results show that the HBV-light performed better in the events that had less precipitation volume compared to their pairs. The event with the higher total precipitated water produced better results with the HEC-HMS model, whereas the rest of the two high precipitation events performed satisfactorily with both models. April to July is a flood hazard period that will be worsened with the effect of climate change. The suggested calibrated parameters for severe precipitation events can be used for the prediction of future events with similar features. The above results can be used in the water resources management of the basin.
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Harlin, Joakim. "Modelling the Hydrological Response of Extreme Floods in Sweden." Hydrology Research 23, no. 4 (August 1, 1992): 227–44. http://dx.doi.org/10.2166/nh.1992.0016.
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Hydrological models are today used for simulating extreme floods with the purpose of designing dams and spillways. In doing so, an extrapolation beyond the floods of the calibration period is made. This paper addresses this problem in connection to the HBV hydrological model. The model component describing flood dynamics, the runoff-response function, is studied. The methodology has been to calibrate different runoff-response functions over small to moderately large floods and to verify the performance over independent periods containing large experienced floods. Furthermore, the different model versions were run with extreme rainfall in order to generate design floods. It was found that the five-parameter response function of the original HBV model could be replaced by nonlinear functions including fewer parameters. However, it was difficult to select any response function formulation as significantly better than the others when extreme floods larger than those of the calibration period were simulated.
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Lindström, Göran, Barbro Johansson, Magnus Persson, Marie Gardelin, and Sten Bergström. "Development and test of the distributed HBV-96 hydrological model." Journal of Hydrology 201, no. 1-4 (December 1997): 272–88. http://dx.doi.org/10.1016/s0022-1694(97)00041-3.
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Tian, Ye, Yue-Ping Xu, Martijn J. Booij, and Guoqing Wang. "Uncertainty in Future High Flows in Qiantang River Basin, China." Journal of Hydrometeorology 16, no. 1 (February 1, 2015): 363–80. http://dx.doi.org/10.1175/jhm-d-13-0136.1.
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Abstract Uncertainties in high flows originating from greenhouse gas emissions scenarios, hydrological model structures, and their parameters for the Jinhua River basin, China, were assessed. The baseline (1961–90) and future (2011–40) climates for A1B, A2, and B2 scenarios were downscaled from the general circulation model (GCM) using the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model with a spatial resolution of 50 km × 50 km. Bias-correction methods were applied to the PRECIS-derived temperature and precipitation. The bias-corrected precipitation and temperature were used as inputs for three hydrological models [modèle du Génie Rural à 4 paramètres Journalier (GR4J), Hydrologiska Byråns Vattenbalansavdelning (HBV), and Xinanjiang] to simulate high flows. The parameter uncertainty was considered and quantified in the hydrological model calibration by means of the generalized likelihood uncertainty estimation (GLUE) method for each hydrological model for the three emissions scenarios. It was found that, compared with the high flows in the baseline period, the high flows in the future tended to decrease under scenarios A1B, A2, and B2. The largest uncertainty was observed in HBV, and GR4J had the smallest uncertainty. It was found that the major source of uncertainty in this study was from parameters, followed by the uncertainties from the hydrological model structure, and the emissions scenarios have the smallest uncertainty contribution to high flows in this study.
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Demirel, M. C., M. J. Booij, and A. Y. Hoekstra. "The skill of seasonal ensemble low flow forecasts for four different hydrological models." Hydrology and Earth System Sciences Discussions 11, no. 5 (May 23, 2014): 5377–420. http://dx.doi.org/10.5194/hessd-11-5377-2014.
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Abstract. This paper investigates the skill of 90 day low flow forecasts using two conceptual hydrological models and two data-driven models based on Artificial Neural Networks (ANNs) for the Moselle River. One data-driven model, ANN-Indicator (ANN-I), requires historical inputs on precipitation (P), potential evapotranspiration (PET), groundwater (G) and observed discharge (Q), whereas the other data-driven model, ANN-Ensemble (ANN-E), and the two conceptual models, HBV and GR4J, use forecasted meteorological inputs (P and PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low flow forecasts without any meteorological forecasts as input (ANN-I) and five different cases of seasonal meteorological forcing: (1) ensemble P and PET forecasts; (2) ensemble P forecasts and observed climate mean PET; (3) observed climate mean P and ensemble PET forecasts; (4) observed climate mean P and PET and (5) zero P and ensemble PET forecasts as input for the other three models (GR4J, HBV and ANN-E). The ensemble P and PET forecasts, each consisting of 40 members, reveal the forecast ranges due to the model inputs. The five cases are compared for a lead time of 90 days based on model output ranges, whereas the four models are compared based on their skill of low flow forecasts for varying lead times up to 90 days. Before forecasting, the hydrological models are calibrated and validated for a period of 30 and 20 years respectively. The smallest difference between calibration and validation performance is found for HBV, whereas the largest difference is found for ANN-E. From the results, it appears that all models are prone to over-predict low flows using ensemble seasonal meteorological forcing. The largest range for 90 day low flow forecasts is found for the GR4J model when using ensemble seasonal meteorological forecasts as input. GR4J, HBV and ANN-E under-predicted 90 day ahead low flows in the very dry year 2003 without precipitation data, whereas ANN-I predicted the magnitude of the low flows better than the other three models. The results of the comparison of forecast skills with varying lead times show that GR4J is less skilful than ANN-E and HBV. Furthermore, the hit rate of ANN-E is higher than the two conceptual models for most lead times. However, ANN-I is not successful in distinguishing between low flow events and non-low flow events. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.
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Zhang, Xingnan, and Göran Lindström. "Development of an automatic calibration scheme for the HBV hydrological model." Hydrological Processes 11, no. 12 (October 15, 1997): 1671–82. http://dx.doi.org/10.1002/(sici)1099-1085(19971015)11:12<1671::aid-hyp497>3.0.co;2-g.
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Griessinger, Nena, Jan Seibert, Jan Magnusson, and Tobias Jonas. "Assessing the benefit of snow data assimilation for runoff modeling in Alpine catchments." Hydrology and Earth System Sciences 20, no. 9 (September 22, 2016): 3895–905. http://dx.doi.org/10.5194/hess-20-3895-2016.
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Abstract. In Alpine catchments, snowmelt is often a major contribution to runoff. Therefore, modeling snow processes is important when concerned with flood or drought forecasting, reservoir operation and inland waterway management. In this study, we address the question of how sensitive hydrological models are to the representation of snow cover dynamics and whether the performance of a hydrological model can be enhanced by integrating data from a dedicated external snow monitoring system. As a framework for our tests we have used the hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) in the version HBV-light, which has been applied in many hydrological studies and is also in use for operational purposes. While HBV originally follows a temperature-index approach with time-invariant calibrated degree-day factors to represent snowmelt, in this study the HBV model was modified to use snowmelt time series from an external and spatially distributed snow model as model input. The external snow model integrates three-dimensional sequential assimilation of snow monitoring data with a snowmelt model, which is also based on the temperature-index approach but uses a time-variant degree-day factor. The following three variations of this external snow model were applied: (a) the full model with assimilation of observational snow data from a dense monitoring network, (b) the same snow model but with data assimilation switched off and (c) a downgraded version of the same snow model representing snowmelt with a time-invariant degree-day factor. Model runs were conducted for 20 catchments at different elevations within Switzerland for 15 years. Our results show that at low and mid-elevations the performance of the runoff simulations did not vary considerably with the snow model version chosen. At higher elevations, however, best performance in terms of simulated runoff was obtained when using the snowmelt time series from the snow model, which utilized data assimilation. This was especially true for snow-rich years. These findings suggest that with increasing elevation and the correspondingly increased contribution of snowmelt to runoff, the accurate estimation of snow water equivalent (SWE) and snowmelt rates has gained importance.
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Gregorić, Enika, Gordana Matović, and Vesna Počuča. "Application of GIS tools for preparation of input data for HBV-light hydrological model." Poljoprivredna tehnika 45, no. 2 (2020): 56–66. http://dx.doi.org/10.5937/poljteh2002056g.
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Abbaris, A., H. Dakhlaoui, S. Thiria, and Z. Bargaoui. "Variational data assimilation with the YAO platform for hydrological forecasting." Proceedings of the International Association of Hydrological Sciences 364 (September 16, 2014): 3–8. http://dx.doi.org/10.5194/piahs-364-3-2014.
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Abstract. 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.
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te Linde, A. H., J. C. J. H. Aerts, R. T. W. L. Hurkmans, and M. Eberle. "Comparing model performance of two rainfall-runoff models in the Rhine basin using different atmospheric forcing data sets." Hydrology and Earth System Sciences 12, no. 3 (June 25, 2008): 943–57. http://dx.doi.org/10.5194/hess-12-943-2008.
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Abstract. Due to the growing wish and necessity to simulate the possible effects of climate change on the discharge regime on large rivers such as the Rhine in Europe, there is a need for well performing hydrological models that can be applied in climate change scenario studies. There exists large variety in available models and there is an ongoing debate in research on rainfall-runoff modelling on whether or not physically based distributed models better represent observed discharges than conceptual lumped model approaches do. In addition, it is argued that Land Surface Models (LSMs) carry the potential to accurately estimate hydrological partitioning, because they solve the coupled water and energy balance. In this paper, the hydrological models HBV and VIC were compared for the Rhine basin by testing their performance in simulating discharge. Overall, the semi-distributed conceptual HBV model performed much better than the distributed land surface model VIC (E=0.62, r2=0.65 vs. E=0.31, r2=0.54 at Lobith). It is argued here that even for a well-documented river basin such as the Rhine, more complex modelling does not automatically lead to better results. Moreover, it is concluded that meteorological forcing data has a considerable influence on model performance, irrespectively to the type of model structure and the need for ground-based meteorological measurements is emphasized.
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Alhamda, Muhamad Zulvi, Entin Hidayah, and Wiwik Yunarni. "Perbadingan Estimasi Curah Hujan MRR dan TRMM 3B42 Sebagai Input Model Hidrologi HBV Studi Kasus DAS Bedadung." Rekayasa Sipil 14, no. 2 (June 25, 2020): 112–19. http://dx.doi.org/10.21776/ub.rekayasasipil.2020.014.02.5.
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The limitations of spatial and temporal distribution of rain gauge networks causes inaccuracies in prediction of hydrological modeling. The availability of satellite rain data products is a potential to overcome this limitation. This studies objective is to compare the quality of rain data from the recording of the Manual Rainfall Recorder (MRR) with satellite data TRMM B342 which is entered in the HBV hydrological modeling. Calibration results shows that HBV modeling performance with MRR rain data input is better than TRMM. R2 and NSE values from MRR rain data input were 0.7153 and 0.7133 respectively with a mean error of 89 (mm / year). While the R2 and NSE values of the TRMM B342 satellite rain data input were 0.57 and 0.55 with a mean error of 305 (mm / year), respectively.
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Jehn, Florian U., Lutz Breuer, Tobias Houska, Konrad Bestian, and Philipp Kraft. "Incremental model breakdown to assess the multi-hypotheses problem." Hydrology and Earth System Sciences 22, no. 8 (August 29, 2018): 4565–81. http://dx.doi.org/10.5194/hess-22-4565-2018.
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Abstract. The ambiguous representation of hydrological processes has led to the formulation of the multiple hypotheses approach in hydrological modeling, which requires new ways of model construction. However, most recent studies focus only on the comparison of predefined model structures or building a model step by step. This study tackles the problem the other way around: we start with one complex model structure, which includes all processes deemed to be important for the catchment. Next, we create 13 additional simplified models, where some of the processes from the starting structure are disabled. The performance of those models is evaluated using three objective functions (logarithmic Nash–Sutcliffe; percentage bias, PBIAS; and the ratio between the root mean square error and the standard deviation of the measured data). Through this incremental breakdown, we identify the most important processes and detect the restraining ones. This procedure allows constructing a more streamlined, subsequent 15th model with improved model performance, less uncertainty and higher model efficiency. We benchmark the original Model 1 and the final Model 15 with HBV Light. The final model is not able to outperform HBV Light, but we find that the incremental model breakdown leads to a structure with good model performance, fewer but more relevant processes and fewer model parameters.
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Seibert, Jan, Marc J. P. Vis, Irene Kohn, Markus Weiler, and Kerstin Stahl. "Technical note: Representing glacier geometry changes in a semi-distributed hydrological model." Hydrology and Earth System Sciences 22, no. 4 (April 9, 2018): 2211–24. http://dx.doi.org/10.5194/hess-22-2211-2018.
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Abstract. Glaciers play an important role in high-mountain hydrology. While changing glacier areas are considered of highest importance for the understanding of future changes in runoff, glaciers are often only poorly represented in hydrological models. Most importantly, the direct coupling between the simulated glacier mass balances and changing glacier areas needs feasible solutions. The use of a complex glacier model is often not possible due to data and computational limitations. The Δh parameterization is a simple approach to consider the spatial variation of glacier thickness and area changes. Here, we describe a conceptual implementation of the Δh parameterization in the semi-distributed hydrological model HBV-light, which also allows for the representation of glacier advance phases and for comparison between the different versions of the implementation. The coupled glacio-hydrological simulation approach, which could also be implemented in many other semi-distributed hydrological models, is illustrated based on an example application.
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Melsen, Lieke Anna, and Björn Guse. "Climate change impacts model parameter sensitivity – implications for calibration strategy and model diagnostic evaluation." Hydrology and Earth System Sciences 25, no. 3 (March 18, 2021): 1307–32. http://dx.doi.org/10.5194/hess-25-1307-2021.
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Abstract. Hydrological models are useful tools for exploring the impact of climate change. To prioritize parameters for calibration and to evaluate hydrological model functioning, sensitivity analysis can be conducted. Parameter sensitivity, however, varies over climate, and therefore climate change could influence parameter sensitivity. In this study we explore the change in parameter sensitivity for the mean discharge and the timing of the discharge, within a plausible climate change rate. We investigate whether changes in sensitivity propagate into the calibration strategy and diagnostically compare three hydrological models based on the sensitivity results. We employed three frequently used hydrological models (SAC, VIC, and HBV) and explored parameter sensitivity changes across 605 catchments in the United States by comparing GCM(RCP8.5)-forced historical and future periods. Consistent among all hydrological models and both for the mean discharge and the timing of the discharge is that the sensitivity of snow parameters decreases in the future. Which other parameters increase in sensitivity is less consistent among the hydrological models. In 45 % to 55 % of the catchments, dependent on the hydrological model, at least one parameter changes in the future in the top-5 most sensitive parameters for mean discharge. For the timing, this varies between 40 % and 88 %. This requires an adapted calibration strategy for long-term projections, for which we provide several suggestions. The disagreement among the models on the processes that become more relevant in future projections also calls for a strict evaluation of the adequacy of the model structure for long-term simulations.
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Pettersson, Anna, Berit Arheimer, and Barbro Johansson. "Nitrogen Concentrations Simulated with HBV-N: New Response Function and Calibration Strategy." Hydrology Research 32, no. 3 (June 1, 2001): 227–48. http://dx.doi.org/10.2166/nh.2001.0014.
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HBV-N is a conceptual process-based model for simulation of transformation and transport of nitrogen on the catchment scale. This paper presents further development with focus on the response function and calibration procedures. Evaluation of the model routines was made in 12 test basins in southern Sweden (without or with only few lakes). Previous versions of HBV-N included a HBV version with a single reservoir in the response function. The presented results show that both nitrogen concentrations and water discharge simulations improved when a second reservoir was introduced. The two-reservoir model was found to be more well-posed for description of residence-times and flow paths. On average, this resulted in an increase in explained variance (R2) for nitrogen concentrations by 0.3. Multiple-responee split-sample calibration was found to further improve the model performance and reliability. In previous applications HBV-N has been applied by using single-response calibration. However, simultaneous calibration of water discharge and nitrogen improved the R2 for nitrogen concentrations by about 0.1 (range 0.02-0.25), but did not affect the simulation of water discharge. This new calibration strategy forces the hydrological parameters to a new optimum, and reduces the level of uncertainty for both hydrochemical and hydrological modelling.
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te Linde, A. H., J. C. J. H. Aerts, R. T. W. L. Hurkmans, and M. Eberle. "Comparing model performance of two rainfall-runoff models in the Rhine basin using different atmospheric forcing data sets." Hydrology and Earth System Sciences Discussions 4, no. 6 (December 4, 2007): 4325–60. http://dx.doi.org/10.5194/hessd-4-4325-2007.
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Abstract. Due to the growing wish and necessity to simulate the possible effects of climate change on the discharge regime on large rivers such as the Rhine in Europe, there is a need for well performing hydrological models that can be applied in climate change scenario studies. There exists large variety in available models and there is an ongoing debate in research on rainfall-runoff modelling on whether or not physically based distributed models better represent observed discharges than conceptual lumped model approaches do. In this paper, the hydrological models HBV and VIC were compared for the Rhine basin by testing their performance in simulating discharge. Overall, the semi-distributed conceptual HBV model performed much better than the distributed physically based VIC model (E=0.62, r2=0.65 vs. E=0.31, r2=0.54 at Lobith). It is argued here that even for a well-documented river basin such as the Rhine, more complex modelling does not automatically lead to better results. Moreover, it is concluded that meteorological forcing data has a considerable influence on model performance, irrespectively to the type of model structure and the need for ground-based meteorological measurements is emphasized.
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Huang, Yingchun, András Bárdossy, and Ke Zhang. "Sensitivity of hydrological models to temporal and spatial resolutions of rainfall data." Hydrology and Earth System Sciences 23, no. 6 (June 19, 2019): 2647–63. http://dx.doi.org/10.5194/hess-23-2647-2019.
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Abstract. Rainfall is the most important input for rainfall–runoff models. It is usually measured at specific sites on a daily or sub-daily timescale and requires interpolation for further application. This study aims to evaluate whether a higher temporal and spatial resolution of rainfall can lead to improved model performance. Four different gridded hourly and daily rainfall datasets with a spatial resolution of 1 km × 1 km for the state of Baden-Württemberg in Germany were constructed using a combination of data from a dense network of daily rainfall stations and a less dense network of sub-daily stations. Lumped and spatially distributed HBV models were used to investigate the sensitivity of model performance to the spatial resolution of rainfall. The four different rainfall datasets were used to drive both lumped and distributed HBV models to simulate daily discharges in four catchments. The main findings include that (1) a higher temporal resolution of rainfall improves the model performance if the station density is high; (2) a combination of observed high temporal resolution observations with disaggregated daily rainfall leads to further improvement in the tested models; and (3) for the present research, the increase in spatial resolution improves the performance of the model insubstantially or only marginally in most of the study catchments.
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ЛУПАКОВ, С. Ю., Т. С. ГУБАРЕВА, В. В. ШАМОВ, А. В. РУБЦОВ, Б. И. ГАРЦМАН, А. Н. БУГАЕЦ, and А. М. ОМЕЛЬКО. "Aplicability of sap flow data in hydrological modeling." Tihookeanskaia geografiia, no. 2(6) (June 21, 2021): 54–65. http://dx.doi.org/10.35735/tig.2021.6.2.005.
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Статья содержит результаты моделирования стока малого речного бассейна в верховьях р. Уссури с использованием оригинальных данных о стволовом сокодвижении, пересчитанных в объем воды, транспирируемый древостоем. В теплый период 2019 г. на территории Верхнеуссурийского стационара ФНЦ биоразнообразия наземной биоты Восточной Азии ДВО РАН проведен комплекс наблюдений за компонентами влагооборота, позволивший накопить необходимый массив данных для гидрологического моделирования. В дополнение к традиционным водно-балансовым измерениям проводился мониторинг транспирации на основе системы датчиков регистрации водотока в стволах деревьев. Полученные данные точечных наблюдений распространены на масштаб водосбора (площадь около 3.1 км2). Показано, что в теплых и сухих условиях объем суточного суммарного испарения с малого речного бассейна может достигать 8.5 тыс. м3, что больше объема речного стока за тот же период в 5–6 раз, а во время выпадения дождей транспирация деревьев уменьшается практически до нуля. Для расчета водного баланса изучаемого объекта использована гидрологическая модель HBV (Hydrologiska Byråns Vattenbalansavdelning). Ряды суточной потенциальной эвапотранспирации, рассчитанные на основе широко используемых методов Пенмана-Монтейса и Одина, применены в HBV как входные данные. Расчетные суточные значения испарения, по сравнению с полученными на основе данных стволового сокодвижения, оказались выше в 1.5–2 раза, разница сумм испарения за весь теплый период года достигает слоя 100 мм и более. При этом надежной связи между расчетными значениями суточного испарения и измерениями не было обнаружено. Сделан вывод, что использование приборных данных о стволовом сокодвижении в составе входных переменных в гидрологическую модель повышает качество расчетов стока. The article deals with the experience of applying an alternative method for quantifying evapotranspiration volume as input to the hydrological model to simulate runoff of a small catchment located in the upper reaches of the Ussuri River. In the warm period of 2019 at the territory of the Verkhneussuriyskiy station of the Federal Scientific Center of the East Asia Terrestrial Biodiversity (FEB RAS), a set of field measurements was carried out. The measured data were used to calibrate the HBV hydrological model (Hydrologiska Byråns Vattenbalansavdelning). In addition to traditional water-balance measurements, there was assessed the evapotranspiration rate based on sap flow measurements eliminating other parts of water losses. The Tissue Heat Balance technique was applied to measure a sap flow in some individual trees. After that, the obtained data were scaled up to the catchment area (3.1 km2). It is shown that in warm and dry weather conditions, the volume of daily total evaporation from a small catchment can reach 8.5 ths.m3 that is 5-6 times more than the river runoff volume over the same period. During the rainfall events, the transpiration rate in trees decreases to almost zero. To compare the obtained results with the modelled ones, the potential evapotranspiration was also calculated based on well-known Penman-Monteith’s and L. Oudin’s methods that forced HBV model as input. Based on hydrological simulations, these methods overestimated the actual daily evaporation volume up to 2 times in comparison with the sap flow data, and the difference for the warm season reaches 100 mm and more. No reliable relationship was found between the calculated values of daily evaporation rate and the conventionally “measured” ones. Basically, runoff simulations quality was improved while using evapotranspiration volume assessed with the sap flow data. We conclude that water balance via HBV simulations is quite different depending on applied evapotranspiration method. In this case, overestimated volume of evapotranspiration by Penman-Monteith and L. Oudin methods leads to excessive water extraction from the HBV soil moisture storage. If it’s actually not correct, long-term runoff simulations would result in wrong water balance and error accumulation.
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Fenicia, F., D. P. Solomatine, H. H. G. Savenije, and P. Matgen. "Soft combination of local models in a multi-objective framework." Hydrology and Earth System Sciences Discussions 4, no. 1 (January 19, 2007): 91–123. http://dx.doi.org/10.5194/hessd-4-91-2007.
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Abstract. Conceptual hydrologic models are useful tools as they provide an interpretable representation of the hydrologic behaviour of a catchment. Their representation of catchment's hydrological processes and physical characteristics, however, implies simplification of the complexity and heterogeneity of reality. As a result, those models often show a lack of flexibility in reproducing the vast spectrum of catchment responses. Hence, the accuracy in reproducing certain aspects of the system behaviour is often paid in terms of a lack of accuracy in the representation of other aspects. By acknowledging the structural limitations of those models, a modular approach to hydrological simulation is proposed. Instead of using a single model to reproduce the full range of catchment responses, multiple models are used, each of them assigned to a specific task. The approach is here demonstrated in the case where the different models are associated with different parameter realizations within a fixed model structure. We show that using a composite "global" model, obtained by a combination of individual "local" models, the accuracy of the simulation is improved. We argue that this approach can be useful because it partially overcomes the structural limitations that a conceptual model might exhibit. The approach is shown in application to the discharge simulation of the experimental Alzette River basin in Luxembourg, with a conceptual model that follows the structure of the HBV model.
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Harlin, Joakim. "Development of a Process Oriented Calibration Scheme for the HBV Hydrological Model." Hydrology Research 22, no. 1 (February 1, 1991): 15–36. http://dx.doi.org/10.2166/nh.1991.0002.
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A process oriented calibration scheme (POC), developed for the HBV hydrological model is presented. Twelve parameters were calibrated in two steps. Firstly, initial parameter estimates were made from recession analysis of observed runoff. Secondly, the parameters were calibrated individually in an iteration loop starting with the snow routine, over the soil routine and finally the runoff-response function. This was done by minimizing different objective functions for different parameters and only over subperiods where the parameters were active. Approximately three hundred and fifty objective function evaluations were needed to find the optimal parameter set, which resulted in a computer time of about 17 hours on a 386 processor PC for a ten-year calibration period. Experiments were also performed with fine tuning as well as direct search of the response surface, where the parameters were allowed to change simultaneously. A calibration period length of between two and six years was found sufficient to find optimal parameters in the test basins. The POC scheme yielded as good model performance as after a manual calibration.
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Bárdossy, A., and S. K. Singh. "Robust estimation of hydrological model parameters." Hydrology and Earth System Sciences 12, no. 6 (November 28, 2008): 1273–83. http://dx.doi.org/10.5194/hess-12-1273-2008.
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Abstract. The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study) for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
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Bárdossy, A., and S. K. Singh. "Robust estimation of hydrological model parameters." Hydrology and Earth System Sciences Discussions 5, no. 3 (June 25, 2008): 1641–75. http://dx.doi.org/10.5194/hessd-5-1641-2008.
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Abstract. The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives an unique and very best parameter vector. The parameters of hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on the half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study) for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
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Mohammed, Safa A., Dimitri P. Solomatine, Markus Hrachowitz, and Mohamed A. Hamouda. "Impact of Dataset Size on the Signature-Based Calibration of a Hydrological Model." Water 13, no. 7 (March 31, 2021): 970. http://dx.doi.org/10.3390/w13070970.
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Many calibrated hydrological models are inconsistent with the behavioral functions of catchments and do not fully represent the catchments’ underlying processes despite their seemingly adequate performance, if measured by traditional statistical error metrics. Using such metrics for calibration is hindered if only short-term data are available. This study investigated the influence of varying lengths of streamflow observation records on model calibration and evaluated the usefulness of a signature-based calibration approach in conceptual rainfall-runoff model calibration. Scenarios of continuous short-period observations were used to emulate poorly gauged catchments. Two approaches were employed to calibrate the HBV model for the Brue catchment in the UK. The first approach used single-objective optimization to maximize Nash–Sutcliffe efficiency (NSE) as a goodness-of-fit measure. The second approach involved multiobjective optimization based on maximizing the scores of 11 signature indices, as well as maximizing NSE. In addition, a diagnostic model evaluation approach was used to evaluate both model performance and behavioral consistency. The results showed that the HBV model was successfully calibrated using short-term datasets with a lower limit of approximately four months of data (10% FRD model). One formulation of the multiobjective signature-based optimization approach yielded the highest performance and hydrological consistency among all parameterization algorithms. The diagnostic model evaluation enabled the selection of consistent models reflecting catchment behavior and allowed an accurate detection of deficiencies in other models. It can be argued that signature-based calibration can be employed for building adequate models even in data-poor situations.
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Demirel, M. C., M. J. Booij, and A. Y. Hoekstra. "The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models." Hydrology and Earth System Sciences 19, no. 1 (January 16, 2015): 275–91. http://dx.doi.org/10.5194/hess-19-275-2015.
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Abstract. 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.
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Huang, J. C., T. Y. Lee, J. Y. Lee, S. C. Hsu, S. J. Kao, and F. J. Chang. "Assessing hydrological model behaviors by intercomparison of the simulated stream flow compositions: case study in a steep forest watershed in Taiwan." Hydrology and Earth System Sciences Discussions 10, no. 1 (January 18, 2013): 855–93. http://dx.doi.org/10.5194/hessd-10-855-2013.
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Abstract. The accurate stream flow composition simulated by different models is rarely discussed, and few studies addressed the model behaviors affected by the model structures. This study compared the simulated stream flow composition derived from two models, namely HBV and TOPMODEL. A total of 23 storms with a wide rainfall spectrum were utilized and independent geochemical data (to derive the stream composition using end-member mixing analysis, EMMA) were introduced. Results showed that both hydrological models generally perform stream discharge satisfactory in terms of the Nash efficiency coefficient, correlation coefficient, and discharge volume. However, the three simulated flows (surface flow, interflow, and base flow) derived from the two models were different with the change of storm intensity and duration. Both simulated surface flows showed the same patterns. The HBV simulated base flow dramatically increased with the increase of storm duration. However, the TOP-derived base flow remained stable. Meanwhile, the two models showed contrasting behaviors in the interflow. HBV prefers to generate less interflow but percolates more to the base flow to match the stream flow, which implies that this model might be suited for thin soil layer. The use of the models should consider more environmental background data into account. Compared with the EMMA-derived flows, both models showed a significant 2 to 4 h time lag, indicating that the base-flow responses were faster than the models represented. Our study suggested that model intercomparison under a wide spectrum of rainstorms and with independent validation data (geochemical data) is a good means of studying the model behaviors. Rethinking the characterization of the model structure and the watershed characteristics is necessary in selecting the more appropriate hydrological model.
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Seibert, J., and M. J. P. Vis. "Teaching hydrological modeling with a user-friendly catchment-runoff-model software package." Hydrology and Earth System Sciences 16, no. 9 (September 17, 2012): 3315–25. http://dx.doi.org/10.5194/hess-16-3315-2012.
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Abstract. 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.
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Seibert, J., and M. J. P. Vis. "Teaching hydrological modeling with a user-friendly catchment-runoff-model software package." Hydrology and Earth System Sciences Discussions 9, no. 5 (May 9, 2012): 5905–30. http://dx.doi.org/10.5194/hessd-9-5905-2012.
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Abstract. 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.
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Grillakis, M. G., I. K. Tsanis, and A. G. Koutroulis. "Application of the HBV hydrological model in a flash flood case in Slovenia." Natural Hazards and Earth System Sciences 10, no. 12 (December 22, 2010): 2713–25. http://dx.doi.org/10.5194/nhess-10-2713-2010.
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Abstract. An atmospheric depression passed over northwest Slovenia on 18 September 2007 producing precipitation that exceeded 300 mm/d and a 100-year return period runoff in Zelezniki tributary. The resultant flash flood in the study area, which consisted of five basins, was simulated with the conceptual distributed hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning). The model was calibrated and validated with past rainfall – runoff events with satisfactory results producing values of Nash – Sutcliffe coefficient between 0.82 and 0.96. The validated model was applied to the flash flood case with stream gauge failure, driven by spatiotemporal precipitation produced by a set of rain gauges and radar data. The model delivered satisfactory results on three out of five basin outlets while the other two had stream gauge failure during the event. The internal basin dynamics of the most affected area in Zelezniki, was successfully tested in eight of its sub-basins by comparing the peak discharges with the ones evaluated by the slope-conveyance method during a detailed intensive post event campaign. The added value of this method is in the reduced uncertainty in peak discharge estimation and event interpretation and in an effective flash flood warning system for the study area when it is combined with radar nowcasts and operational high resolution short range weather forecast models.
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Sivasubramaniam, K., K. Alfredsen, T. Rinde, and B. Sæther. "Can model-based data products replace gauge data as input to the hydrological model?" Hydrology Research 51, no. 2 (January 22, 2020): 188–201. http://dx.doi.org/10.2166/nh.2020.076.
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Abstract Hydrological models require accurate and representative meteorological inputs for better prediction of discharge and hence, the efficient management of water resources. Numerical weather prediction model-based reanalysis data products on the catchment scale are becoming available, and they could be an alternative input data for hydrological models. This study focuses on the applicability of a set of model-based data as input to hydrological models used in inflow predictions for operational hydropower production planning of three hydropower systems in middle Norway. First, the study compared the data products with gauge measurements. Then, Hydrologiska Byråns Vattenbalansavdelning (HBV) models of the three catchments were calibrated with three different meteorological datasets (model-based, gauge and observational gridded) separately using a Monte Carlo approach. It was found that the correlation between the model-based and gauged precipitation was highly variable among stations, and daily values showed a better correlation than hourly. The performance of model-based input data with daily timestep was nearly as good as the gauge or gridded data for the model calibration. Further, the annual simulated flow volume using the model-based data was satisfactory as similar to the gauge or gridded input data, which indicate that model-based data can be a potential data source for long-term operational hydropower production planning.
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Vormoor, Klaus, Maik Heistermann, Axel Bronstert, and Deborah Lawrence. "Hydrological model parameter (in)stability – “crash testing” the HBV model under contrasting flood seasonality conditions." Hydrological Sciences Journal 63, no. 7 (May 17, 2018): 991–1007. http://dx.doi.org/10.1080/02626667.2018.1466056.
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Worqlul, A. W., A. S. Collick, S. A. Tilahun, S. Langan, T. H. M. Rientjes, and T. S. Steenhuis. "Comparing TRMM 3B42, CFSR and ground-based rainfall estimates as input for hydrological models, in data scarce regions: the Upper Blue Nile Basin, Ethiopia." Hydrology and Earth System Sciences Discussions 12, no. 2 (February 18, 2015): 2081–112. http://dx.doi.org/10.5194/hessd-12-2081-2015.
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Abstract. 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.
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Kobold, M., and M. Brilly. "The use of HBV model for flash flood forecasting." Natural Hazards and Earth System Sciences 6, no. 3 (May 24, 2006): 407–17. http://dx.doi.org/10.5194/nhess-6-407-2006.
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Abstract. The standard conceptual HBV model was originally developed with daily data and is normally operated on daily time step. But many floods in Slovenia are usually flash floods as result of intense frontal precipitation combined with orographic enhancement. Peak discharges are maintained only for hours or even minutes. To use the HBV model for flash flood forecasting, the version of HBV-96 has been applied on the catchment with complex topography with the time step of one hour. The recording raingauges giving hourly values of precipitation have been taken in calibration of the model. The uncertainty of simulated runoff is mainly the result of precipitation uncertainty associated with the mean areal precipitation and is higher for mountainous catchments. Therefore the influence of number of raingauges used to derive the areal precipitation by the method of Thiessen polygons was investigated. The quantification of hydrological uncertainty has been performed by analysis of sensitivity of the HBV model to error in precipitation input. The results show that an error of 10% in the amount of precipitation causes an error of 17% in the peak of flood wave. The polynomial equations showing the relationship between the errors in rainfall amounts and peak discharges were derived for two water stations on the Savinja catchment. Simulated discharges of half-yearly runs demonstrate the applicability of the HBV model for flash flood forecasting using the mesoscale meteorological forecasts of ALADIN/SI model as input precipitation data.
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Driessen, T. L. A., R. T. W. L. Hurkmans, W. Terink, P. Hazenberg, P. J. J. F. Torfs, and R. Uijlenhoet. "The hydrological response of the Ourthe catchment to climate change as modelled by the HBV model." Hydrology and Earth System Sciences 14, no. 4 (April 12, 2010): 651–65. http://dx.doi.org/10.5194/hess-14-651-2010.
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Abstract. The Meuse is an important river in Western Europe, which is almost exclusively rain-fed. Projected changes in precipitation characteristics due to climate change, therefore, are expected to have a considerable effect on the hydrological regime of the river Meuse. We focus on an important tributary of the Meuse, the Ourthe, measuring about 1600 km2. The well-known hydrological model HBV is forced with three high-resolution (0.088°) regional climate scenarios, each based on one of three different IPCC CO2 emission scenarios: A1B, A2 and B1. To represent the current climate, a reference model run at the same resolution is used. Prior to running the hydrological model, the biases in the climate model output are investigated and corrected for. Different approaches to correct the distributed climate model output using single-site observations are compared. Correcting the spatially averaged temperature and precipitation is found to give the best results, but still large differences exist between observations and simulations. The bias corrected data are then used to force HBV. Results indicate a small increase in overall discharge, especially for the B1 scenario during the beginning of the 21st century. Towards the end of the century, all scenarios show a decrease in summer discharge, partially because of the diminished buffering effect by the snow pack, and an increased discharge in winter. It should be stressed, however, that we used results from only one GCM (the only one available at such a high resolution). It would be interesting to repeat the analysis with multiple models.
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Driessen, T. L. A., R. T. W. L. Hurkmans, W. Terink, P. Hazenberg, P. J. J. F. Torfs, and R. Uijlenhoet. "The hydrological response of the Ourthe catchment to climate change as modelled by the HBV model." Hydrology and Earth System Sciences Discussions 6, no. 6 (November 19, 2009): 7143–78. http://dx.doi.org/10.5194/hessd-6-7143-2009.
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Abstract. The Meuse is an important river in western Europe, and almost exclusively rain-fed. Projected changes in precipitation characteristics due to climate change, therefore, are expected to have a considerable effect on the hydrological regime of the river Meuse. We focus on an important tributary of the Meuse, the Ourthe, measuring about 1600 km2. The well-known hydrological model HBV is forced with three high-resolution (0.088°) regional climate scenarios, each based on one of three different IPCC CO2 emission scenarios: A1B, A2 and B1. To represent the current climate, a reference model run at the same resolution is used. Prior to running the hydrological model, the biases in the climate model output are investigated and corrected for. Different approaches to correct the distributed climate model output using single-site observations are compared. Correcting the spatially averaged temperature and precipitation is found to give the best results, but still large differences exist between observations and simulations. The bias corrected data are then used to force HBV. Results indicate a small increase in overall discharge for especially the B1 scenario during the beginning of the 21st century. Towards the end of the century, all scenarios show a decrease in summer discharge, partially because of the diminished buffering effect by the snow pack, and an increased discharge in winter. It should be stressed, however, that we used results from only one GCM (the only one available at such a high resolution). It would be interesting to repeat the analysis with multiple models.
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Kalantari, Z., P. E. Jansson, J. Stolte, L. Folkeson, H. K. French, and M. Sassner. "Usefulness of four hydrological models in simulating high-resolution discharge dynamics of a catchment adjacent to a road." Hydrology and Earth System Sciences Discussions 9, no. 4 (April 19, 2012): 5121–65. http://dx.doi.org/10.5194/hessd-9-5121-2012.
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Abstract. Four hydrological models (LISEM, MIKE SHE, CoupModel and HBV) were compared with respect to their capability to predict peak flow in a small catchment upstream of a road in SE Norway on an hourly basis. All four models were calibrated using hourly observed streamflow. Simulated and observed discharge generated during three types of hydrological situations characteristic of winter/spring conditions causing overland flow were considered: snowmelt, partially frozen soil and heavy rain events. Using parameter sets optimised for winter/spring conditions, flows simulated by HBV coupled with CoupModel were comparable to measured discharge from the catchment in corresponding periods. However, this combination was best when all the parameters were calibrated in HBV. For ungauged basins with no real-time monitoring of discharge and when the spatial distribution is important, MIKE SHE may be more suitable than the other models, but the lack of detailed input data and the uncertainty in physical parameters should be considered. LISEM is potentially capable of calculating runoff from small catchments during winter/spring but requires better description of snowmelt, infiltration into frozen layers and tile drainage. From a practical road maintenance perspective, the usefulness and accuracy of a model depends on its ability to represent site-specific processes, data availability and calibration requirements.
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Ciupak, Maurycy, Bogdan Ozga-Zielinski, Jan Adamowski, Ravinesh C. Deo, and Krzysztof Kochanek. "Correcting Satellite Precipitation Data and Assimilating Satellite-Derived Soil Moisture Data to Generate Ensemble Hydrological Forecasts within the HBV Rainfall-Runoff Model." Water 11, no. 10 (October 15, 2019): 2138. http://dx.doi.org/10.3390/w11102138.
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An implementation of bias correction and data assimilation using the ensemble Kalman filter (EnKF) as a procedure, dynamically coupled with the conceptual rainfall-runoff Hydrologiska Byråns Vattenbalansavdelning (HBV) model, was assessed for the hydrological modeling of seasonal hydrographs. The enhanced HBV model generated ensemble hydrographs and an average stream-flow simulation. The proposed approach was developed to examine the possibility of using data (e.g., precipitation and soil moisture) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF), and to explore its usefulness in improving model updating and forecasting. Data from the Sola mountain catchment in southern Poland between 1 January 2008 and 31 July 2014 were used to calibrate the HBV model, while data from 1 August 2014 to 30 April 2015 were used for validation. A bias correction algorithm for a distribution-derived transformation method was developed by exploring generalized exponential (GE) theoretical distributions, along with gamma (GA) and Weibull (WE) distributions for the different data used in this study. When using the ensemble Kalman filter, the stochastically-generated ensemble of the model states generally induced bias in the estimation of non-linear hydrologic processes, thus influencing the accuracy of the Kalman analysis. In order to reduce the bias produced by the assimilation procedure, a post-processing bias correction (BC) procedure was coupled with the ensemble Kalman filter (EnKF), resulting in an ensemble Kalman filter with bias correction (EnKF-BC). The EnKF-BC, dynamically coupled with the HBV model for the assimilation of the satellite soil moisture observations, improved the accuracy of the simulated hydrographs significantly in the summer season, whereas, a positive effect from bias corrected (BC) satellite precipitation, as forcing data, was observed in the winter. Ensemble forecasts generated from the assimilation procedure are shown to be less uncertain. In future studies, the EnKF-BC algorithm proposed in the current study could be applied to a diverse array of practical forecasting problems (e.g., an operational assimilation of snowpack and snow water equivalent in forecasting models).
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Wong, Wai Kwok, Stein Beldring, Torill Engen-Skaugen, Ingjerd Haddeland, and Hege Hisdal. "Climate Change Effects on Spatiotemporal Patterns of Hydroclimatological Summer Droughts in Norway." Journal of Hydrometeorology 12, no. 6 (December 1, 2011): 1205–20. http://dx.doi.org/10.1175/2011jhm1357.1.
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Abstract This study examines the impact of climate change on droughts in Norway. A spatially distributed (1 × 1 km2) version of the Hydrologiska Byråns Vattenbalansavdelning (HBV) precipitation-runoff model was used to provide hydrological data for the analyses. Downscaled daily temperature and precipitation derived from two atmosphere–ocean general circulation models with two future emission scenarios were applied as input to the HBV model. The differences in hydroclimatological drought characteristics in the summer season between the periods 1961–90 and 2071–2100 were studied. The threshold level method was adopted to select drought events for both present and future climates. Changes in both the duration and spatial extent of precipitation, soil moisture, runoff, and groundwater droughts were identified. Despite small changes in future meteorological drought characteristics, substantial increases in hydrological drought duration and drought affected areas are expected, especially in the southern and northernmost parts of the country. Reduced summer precipitation is a major factor that affects changes in drought characteristics in the south while temperature increases play a more dominant role for the rest of the country.
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Al-Safi, Hashim Isam Jameel, and P. Ranjan Sarukkalige. "Evaluation of the impacts of future hydrological changes on the sustainable water resources management of the Richmond River catchment." Journal of Water and Climate Change 9, no. 1 (November 3, 2017): 137–55. http://dx.doi.org/10.2166/wcc.2017.144.
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Abstract The conceptual rainfall–runoff (HBV model) is applied to evaluate impacts of future climate changes on the hydrological system of the Richmond River catchment, Australia. Daily observed rainfall, temperature and discharge and long-term monthly mean potential evapotranspiration from the hydro-meteorological stations within the catchment over the period 1972–2014 were used to run, calibrate and validate the HBV model before the simulation. Future climate signals were extracted from a multi-model ensemble of eight global climate models (GCMs) of the CMIP5 under three scenarios (RCP2.6, RCP4.5 and RCP8.5). The calibrated HBV model was forced with the downscaled rainfall and temperature to simulate future streamflow at catchment outlet for the near-future (2016–2035), mid (2046–2065) and late (2080–2099) 21st century. A baseline run, with baseline climate period 1971–2010, was used to represent current climate status. Almost all GCMs’ scenarios predict slight increase in annual mean rainfall during the beginning of the century and decrease towards the mid and late century. Modelling results also show positive trends in annual mean streamflow during the near-future (13–23%), and negative trends in the mid (2–6%) and late century (6–16%), under all scenarios compared to the baseline-run. Findings could assist in managing future water resources in the catchment.
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Fenicia, F., D. P. Solomatine, H. H. G. Savenije, and P. Matgen. "Soft combination of local models in a multi-objective framework." Hydrology and Earth System Sciences 11, no. 6 (November 22, 2007): 1797–809. http://dx.doi.org/10.5194/hess-11-1797-2007.
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Abstract. Conceptual hydrologic models are useful tools as they provide an interpretable representation of the hydrologic behaviour of a catchment. Their representation of catchment's hydrological processes and physical characteristics, however, implies a simplification of the complexity and heterogeneity of reality. As a result, these models may show a lack of flexibility in reproducing the vast spectrum of catchment responses. Hence, the accuracy in reproducing certain aspects of the system behaviour may be paid in terms of a lack of accuracy in the representation of other aspects. By acknowledging the structural limitations of these models, we propose a modular approach to hydrological simulation. Instead of using a single model to reproduce the full range of catchment responses, multiple models are used, each of them assigned to a specific task. While a modular approach has been previously used in the development of data driven models, in this study we show an application to conceptual models. The approach is here demonstrated in the case where the different models are associated with different parameter realizations within a fixed model structure. We show that using a "composite" model, obtained by a combination of individual "local" models, the accuracy of the simulation is improved. We argue that this approach can be useful because it partially overcomes the structural limitations that a conceptual model may exhibit. The approach is shown in application to the discharge simulation of the experimental Alzette River basin in Luxembourg, with a conceptual model that follows the structure of the HBV model.