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Visser-Quinn, Annie, Lindsay Beevers, and Sandhya Patidar. "Replication of ecologically relevant hydrological indicators following a modified covariance approach to hydrological model parameterization." Hydrology and Earth System Sciences 23, no. 8 (August 9, 2019): 3279–303. http://dx.doi.org/10.5194/hess-23-3279-2019.
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Abstract. Hydrological models can be used to assess the impact of hydrologic alteration on the river ecosystem. However, there are considerable limitations and uncertainties associated with the replication of ecologically relevant hydrological indicators. Vogel and Sankarasubramanian's 2003 (Water Resources Research) covariance approach to model evaluation and parameterization represents a shift away from algorithmic model calibration with traditional performance measures (objective functions). Using the covariance structures of the observed input and simulated output time series, it is possible to assess whether the selected hydrological model is able to capture the relevant underlying processes. From this plausible parameter space, the region of parameter space which best captures (replicates) the characteristics of a hydrological indicator may be identified. In this study, a modified covariance approach is applied to five hydrologically diverse case study catchments with a view to replicating a suite of ecologically relevant hydrological indicators identified through catchment-specific hydroecological models. The identification of the plausible parameter space (here n≈20) is based on the statistical importance of these indicators. Evaluation is with respect to performance and consistency across each catchment, parameter set, and the 40 ecologically relevant hydrological indicators considered. Timing and rate of change indicators are the best and worst replicated respectively. Relative to previous studies, an overall improvement in consistency is observed. This study represents an important advancement towards the robust application of hydrological models for ecological flow studies.
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Liu, Yue, Jian-yun Zhang, Amgad Elmahdi, Qin-li Yang, Xiao-xiang Guan, Cui-shan Liu, Rui-min He, and Guo-qing Wang. "Transferability of a lumped hydrologic model, the Xin'anjiang model based on similarity in climate and geography." Water Supply 21, no. 5 (February 25, 2021): 2191–201. http://dx.doi.org/10.2166/ws.2021.055.
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Abstract Hydrological experiments are essential to understanding the hydrological cycles and promoting the development of hydrologic models. Model parameter transfers provide a new way of doing hydrological forecasts and simulations in ungauged catchments. To study the transferability of model parameters for hydrological modelling and the influence of parameter transfers on hydrological simulations, the Xin'anjiang model (XAJ model), which is a lumped hydrologic model based on a saturation excess mechanism that has been widely applied in different climate regions of the world, was applied to a low hilly catchment in eastern China, the Chengxi experimental watershed (CXEW). The suitability of the XAJ model was tested in the eastern branch catchment of CXEW and the calibrated model parameters of the eastern branch catchment were then transferred to the western branch catchment and the entire watershed of the CXEW. The results show that the XAJ model performs well for the calibrated eastern branch catchment at both daily and monthly scales on hydrological modelling with the NSEs over 0.6 and the REs less than 2.0%. Besides, the uncalibrated catchments of the western branch catchment and the entire watershed of the CSEW share similarities in climate (the precipitation) and geography (the soil texture and vegetation cover) with the calibrated catchment, the XAJ model and the transferred model parameters can capture the main features of the hydrological processes in both uncalibrated catchments (western catchments and the entire watershed). This transferability of the model is useful for a scarce data region to simulate the hydrological process and its forecasting.
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Chadalawada, Jayashree, and Vladan Babovic. "Review and comparison of performance indices for automatic model induction." Journal of Hydroinformatics 21, no. 1 (December 6, 2017): 13–31. http://dx.doi.org/10.2166/hydro.2017.078.
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Abstract One of the more perplexing challenges for the hydrologic research community is the need for development of coupled systems involving integration of hydrologic, atmospheric and socio-economic relationships. Given the demand for integrated modelling and availability of enormous data with varying degrees of (un)certainty, there exists growing popularity of data-driven, unified theory catchment scale hydrological modelling frameworks. Recent research focuses on representation of distinct hydrological processes using mathematical model components that vary in a controlled manner, thereby deriving relationships between alternative conceptual model constructs and catchments’ behaviour. With increasing computational power, an evolutionary approach to auto-configuration of conceptual hydrological models is gaining importance. Its successful implementation depends on the choice of evolutionary algorithm, inventory of model components, numerical implementation, rules of operation and fitness functions. In this study, genetic programming is used as an example of evolutionary algorithm that employs modelling decisions inspired by the Superflex framework to automatically induce optimal model configurations for the given catchment dataset. The main objective of this paper is to identify the effects of entropy, hydrological and statistical measures as optimization objectives on the performance of the proposed approach based on two synthetic case studies of varying complexity.
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Zheng, Zhen, Jing Zhang, Hui Li Gong, and J. W. Huang. "Application of MIKESHE Model in Water Environmental Management for Guishui River Basin." Applied Mechanics and Materials 580-583 (July 2014): 1823–27. http://dx.doi.org/10.4028/www.scientific.net/amm.580-583.1823.
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In order to comprehensively analyse hydrological environment system of watershed, it is particularly important to couple the surface water and groundwater for better underding the entire hydrologic cycle. Guishui river basin, located in Beijing, was selected as the research area to build a MIKE SHE hydrological integrated model to simulate the surface runoff. The hydrologic response in the Guishui river basin was explored. This study will enrich the experience of the domestic application about MIKESHE model and provided scientific basis for regional water resources planning and management. In the paper, the development process and present research situation of integrated hydrological models were overviewed, concluding the principle of model structure. Considering the water environment issues in the study area (such as water pollution, water resource utilization, watershed underlying surface, climate change, etc.), the integrated hydrological model was setup based on MIKESHE for the simulation year of 2005 to 2010. The preliminary results showed that it is feasibile to apply the MIKESHE model in the study area for water environmental management. Furthermore, some valued suggestions and perspectives about the water environmental problems in the study for the future were provided.
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Nordin, N. A. S., Z. Hassan, N. M. Noor, A. N. Kamarudzaman, and A. S. A. Ahmadni. "Assessing Hydrological Response in the Timah-Tasoh Reservoir Sub-Catchments: Calibration and Validation using the HEC-HMS Model." IOP Conference Series: Earth and Environmental Science 1303, no. 1 (February 1, 2024): 012029. http://dx.doi.org/10.1088/1755-1315/1303/1/012029.
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Abstract Hydrological modelling is a tool that is frequently used for assessing the hydrological response of a basin as a result of precipitation. It is also a vital component as water resources and environmental planning management. The study deals with calibrating and validating the hydrological response in the sub-catchments of the Timah-Tasoh reservoir using the hydrological model named Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS). This study uses the SCS Curve Number, the SCS Unit Hydrograph, the constant monthly baseflow, and lag routing for the model development. The model was simulated for ten (10) years for calibration and nine (9) years for validation. The model calibration and validation efficiency were assessed using the coefficient of correlation (R). The findings show that the HEC-HMS model performs satisfactorily in simulating the observed daily inflow series, with the R-value of 0.4902-0.5139 during calibration and 0.5047-0.5559 during validation process. Thus, the result obtained from this study can be used as a preliminary development of hydrological modelling of the catchment of the Timah-Tasoh reservoir and can be used for extend application such as water inflow forecasting, impact of land use to the reservoir and others.
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Toum, Ezequiel, Mariano,H Masiokas, Ricardo Villalba, Pierre Pitte, and Lucas Ruiz. "The HBV.IANIGLA Hydrological Model." R Journal 13, no. 1 (2021): 378. http://dx.doi.org/10.32614/rj-2021-059.
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Assaf, Hamed, and Michael C. Quick. "Updating hydrological model forecasts." Canadian Journal of Civil Engineering 18, no. 4 (August 1, 1991): 663–74. http://dx.doi.org/10.1139/l91-081.
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A flow updating model is presented in which the flow is estimated using outputs from a physically based watershed model (UBC watershed model) and a feedback of the most recent flow measurement. These outputs (the flow components) are modified by certain parameters that are updated whenever a flow measurement is available. The updating process is based on a state-space model where Kalman filter technique is used to update the parameters from their past values and the most recent flow measurement. The extent of updating is controlled by the relative uncertainties in the flow measurements and the parameters. The updating model has been applied on the Illecilewaet basin and the flow forecasts have shown great improvement over the ones obtained by using the UBC watershed model only. The flow updating model is formulated based on an assumption that the errors in the watershed model output are of a certain linear structure. The validity of such assumption could be tested by comparing some statistical measures of performance. Key words: real-time, flow forecasting, updating, Kalman filter, state-space, linear errors.
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Di Salvo, Cristina. "Groundwater Hydrological Model Simulation." Water 15, no. 4 (February 20, 2023): 822. http://dx.doi.org/10.3390/w15040822.
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Xiao, Qintai, Li Zhou, Xin Xiang, Lingxue Liu, Xing Liu, Xiaodong Li, and Tianqi Ao. "Integration of Hydrological Model and Time Series Model for Improving the Runoff Simulation: A Case Study on BTOP Model in Zhou River Basin, China." Applied Sciences 12, no. 14 (July 7, 2022): 6883. http://dx.doi.org/10.3390/app12146883.
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Improving the accuracy of runoff simulations is a significant focus of hydrological science for multiple purposes such as water resources management, flood and drought prediction, and water environment protection. However, the simulated runoff has limitations that cannot be eliminated. This paper proposes a method that integrates the hydrological and time series models to improve the reliability and accuracy of simulated runoffs. Specifically, the block-wise use of TOPMODEL (BTOP) is integrated with three time series models to improve the simulated runoff from a hydrological model of the Zhou River Basin, China. Unlike most previous research that has not addressed the influence of runoff patterns while correcting the runoff, this study manually adds the hydrologic cycle to the machine learning-based time series model. This also incorporates scenario-specific knowledge from the researcher’s area of expertise into the prediction model. The results show that the improved Prophet model proposed in this study, that is, by adjusting its holiday function to a flow function, significantly improved the Nash–Sutcliffe efficiency (NSE) of the simulated runoff by 53.47% (highest) and 23.93% (average). The autoregressive integrated moving average (ARIMA) model and long short-term memory (LSTM) improved the runoff but performed less well than the improved Prophet model. This paper presents an effective method to improve the runoff simulation by integrating the hydrological and time series models.
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Krzeminska, D. M., T. A. Bogaard, J. P. Malet, and L. P. H. van Beek. "A model of hydrological and mechanical feedbacks of preferential fissure flow in a slow-moving landslide." Hydrology and Earth System Sciences 17, no. 3 (March 5, 2013): 947–59. http://dx.doi.org/10.5194/hess-17-947-2013.
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Abstract. The importance of hydrological processes for landslide activity is generally accepted. However, the relationship between precipitation, hydrological responses and movement is not straightforward. Groundwater recharge is mostly controlled by the hydrological material properties and the structure (e.g., layering, preferential flow paths such as fissures) of the unsaturated zone. In slow-moving landslides, differential displacements caused by the bedrock structure complicate the hydrological regime due to continuous opening and closing of the fissures, creating temporary preferential flow paths systems for infiltration and groundwater drainage. The consecutive opening and closing of fissure aperture control the formation of a critical pore water pressure by creating dynamic preferential flow paths for infiltration and groundwater drainage. This interaction may explain the seasonal nature of the slow-moving landslide activity, including the often observed shifts and delays in hydrological responses when compared to timing, intensity and duration of precipitation. The main objective of this study is to model the influence of fissures on the hydrological dynamics of slow-moving landslide and the dynamic feedbacks between fissures, hydrology and slope stability. For this we adapt the spatially distributed hydrological and slope stability model (STARWARS) to account for geotechnical and hydrological feedbacks, linking between hydrological response of the landside and the dynamics of the fissure network and applied the model to the hydrologically controlled Super-Sauze landslide (South French Alps).
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Krzeminska, D. M., T. A. Bogaard, J. P. Malet, and L. P. H van Beek. "A model of hydrological and mechanical feedbacks of preferential fissure flow in a slow-moving landslide." Hydrology and Earth System Sciences Discussions 9, no. 10 (October 1, 2012): 11161–97. http://dx.doi.org/10.5194/hessd-9-11161-2012.
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Abstract. The importance of hydrological processes for landslide activity is generally accepted. However, the relationship between precipitation, hydrological responses and movement is not straightforward. Groundwater recharge is mostly controlled by the hydrological material properties and the structure (e.g. layering, preferential flow paths such as fissures) of the unsaturated zone. In slow-moving landslides, differential displacements caused by the bedrock structure complicate the hydrological regime due to continuous opening and closing of the fissures, creating temporary preferential flow paths systems for infiltration and groundwater drainage. The consecutive opening and closing of fissure aperture control the formation of a critical pore water pressure by creating dynamic preferential flow paths for infiltration and groundwater drainage. This interaction may explain the seasonal nature of the slow-moving landslide activity, including the often observed shifts and delays in hydrological responses when compared to timing, intensity and duration of precipitation. The main objective of this study is to model the influence of fissures on the hydrological dynamics of slow-moving landslide and the dynamic feedbacks between fissures, hydrology and slope stability. For this we adapt the spatially distributed hydrological and slope stability model (STARWARS) to account for geotechnical and hydrological feedbacks, linking between hydrological response of the landside and the dynamics of the fissure network and applied the model to the hydrologically controlled Super-Sauze landslide (South French Alps).
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Lee, Hanyong, Min Suh Chae, Jong-Yoon Park, Kyoung Jae Lim, and Youn Shik Park. "Development and Application of a QGIS-Based Model to Estimate Monthly Streamflow." ISPRS International Journal of Geo-Information 11, no. 1 (January 8, 2022): 40. http://dx.doi.org/10.3390/ijgi11010040.
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Changes in rainfall pattern and land use have caused considerable impacts on the hydrological behavior of watersheds; a Long-Term Hydrologic Impact Analysis (L-THIA) model has been used to simulate such variations. The L-THIA model defines curve number according to the land use and hydrological soil group before calculating the direct runoff based on the amount of rainfall, making it a convenient method of analysis. Recently, a method was proposed to estimate baseflow using this model, which may be used to estimate the overall streamflow. Given that this model considers the spatial distribution of land use and hydrological soil groups and must use rainfall data at multiple positions, it requires the usage of a geographical information system (GIS). Therefore, a model that estimates streamflow using land use maps, hydrologic soil group maps, and rain gauge station maps in QGIS, a popular GIS software, was developed. This model was tested in 15 watersheds.
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He, Shaokun, Shenglian Guo, Zhangjun Liu, Jiabo Yin, Kebing Chen, and Xushu Wu. "Uncertainty analysis of hydrological multi-model ensembles based on CBP-BMA method." Hydrology Research 49, no. 5 (March 1, 2018): 1636–51. http://dx.doi.org/10.2166/nh.2018.160.
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Abstract Quantification of the inherent uncertainty in hydrologic forecasting is essential for flood control and water resources management. The existing approaches, such as Bayesian model averaging (BMA), hydrologic uncertainty processor (HUP), copula-BMA (CBMA), aim at developing reliable probabilistic forecasts to characterize the uncertainty induced by model structures. In the probability forecast framework, these approaches either assume the probability density function (PDF) to follow a certain distribution, or are unable to reduce bias effectively for complex hydrological forecasts. To overcome these limitations, a copula Bayesian processor associated with BMA (CBP-BMA) method is proposed with ensemble lumped hydrological models. Comparing with the BMA and CBMA methods, the CBP-BMA method relaxes any assumption on the distribution of conditional PDFs. Several evaluation criteria, such as containing ratio, average bandwidth and average deviation amplitude of probabilistic application, are utilized to evaluate the model performance. The case study results demonstrate that the CBP-BMA method can improve hydrological forecasting precision with higher cover ratios more than 90%, which are increased by 4.4% and 3.2%, 2.2% and 1.7% over those of BMA and CBMA during the calibration and validation periods, respectively. The proposed CBP-BMA method provides an alternative approach for uncertainty estimation of hydrological multi-model forecasts.
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Harsoyo, Budi. "REVIEW MODELING HIDROLOGI DAS DI INDONESIA." Jurnal Sains & Teknologi Modifikasi Cuaca 11, no. 1 (June 16, 2010): 41. http://dx.doi.org/10.29122/jstmc.v11i1.2179.
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Berbagai model simulasi hidrologi telah dikembangkan untuk menjelaskan prosesmengubah input (dalam bentuk hujan) menjadi output (dalam bentuk aliran sungai) dengan mempertimbangkan karakteristik fisik DAS. Model simulasi hidrologi pada dasarnya dirancang untuk menyederhanakan sistem hidrologi, sehingga perilaku dari beberapa komponen dalam sistem dapat diketahui. Makalah ini membahas pemodelan hidrologi banyak diterapkan di Indonesia, dimulai dengan peninjauan definisi dan klasifikasi model hidrologi, dan lanjutkan dengan ulasan beberapa model hidrologi DAS untuk skala bersama dengan beberapa contoh aplikasi yang telah dilakukan dalam penelitian di Indonesia.Various hydrological simulation model has been developed to explain the process of changing inputs (in the form of rain) into outputs (in the form of the river flow) by considering the physical characteristics of the watershed. Hydrologic simulation model is basically designed to simplify the hydrological system, so the behavior of some components in the system can be known. This paper discusses the many hydrologic modeling applied in Indonesia, starting with a review of the definition and classification of hydrological model, and proceed with a review of several watershed hydrological model to scale along with some examples of applications that have been done in research in Indonesia.
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Janicka, Ewelina, Jolanta Kanclerz, Tropikë Agaj, and Katarzyna Gizińska. "Comparison of Two Hydrological Models, the HEC-HMS and Nash Models, for Runoff Estimation in Michałówka River." Sustainability 15, no. 10 (May 12, 2023): 7959. http://dx.doi.org/10.3390/su15107959.
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Floods are among the most devastating natural disasters in small suburban catchments. These phenomena, causing loss of life and massive property damage, pose a serious threat to the economy. Hydrological modeling is extremely important in terms of climate change, and the use of appropriate modeling can be a useful tool for flood risk prevention and mitigation. Rainfall–runoff modeling requires the selection of an appropriate hydrological model in order to obtain satisfactory results. Hydrological models are used in water resource planning and management to estimate catchment runoff. Small uncontrolled catchments play a particularly important role in hydrological phenomena, since changes in them affect flows in the recipient. Hydrologists are particularly interested in developing hydrological models that can be made with a minimum of data and parameters. Nash models and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) are examples of simple and most practical hydrologic models. These models were used in this paper to study geographic and qualitative changes in precipitation runoff due to land cover changes. The modeling was carried out for two spatial aspects relating to the years 1940 and 2018. The model allowed for the simulation of the river flow that can occur under different rainfall probabilities. The analysis of the results was used to evaluate the hydrological models used. The hundred-year flow modeled with the Nash model for 1940 was 13.4 m3∙s−1, whereas the second model gave slightly lower flow values. In addition, modeling the flow for 2018 (after changing the land cover) highlighted the increase in the flow value for both models, where again the flow volume was slightly higher for the Nash model and amounted to about 19 m3∙s−1. The flow differences for individual models were not too large. This made it possible to conclude that the simulated outflow hydrographs are in good agreement, and this means that the models accurately reproduce the flow of the Michałówka River. The study showed that rapid urbanization adversely affects hydrological processes. In addition, the study showed that a well-distributed model can outperform a global flood forecasting model, especially in terms of magnitude, as in the current study example.
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Bingeman, A. K., N. Kouwen, and E. D. Soulis. "Validation of the Hydrological Processes in a Hydrological Model." Journal of Hydrologic Engineering 11, no. 5 (September 2006): 451–63. http://dx.doi.org/10.1061/(asce)1084-0699(2006)11:5(451).
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Tegelhoffová, M. "Analysis of the development of a hydrological balance for future decades in the Senianska depression in the Eastern Slovak lowland." Slovak Journal of Civil Engineering 18, no. 4 (December 1, 2010): 30–40. http://dx.doi.org/10.2478/v10189-010-0020-6.
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Analysis of the development of a hydrological balance for future decades in the Senianska depression in the Eastern Slovak lowlandThe goal of the article was to analyze the hydrological balance for future decades in a pilot area in the Eastern Slovak lowland. The aim was to set up the physically-based Mike SHE hydrological model for the modeling hydrological balance in the selected wetland ecosystem in the Eastern Slovak Lowland. The pilot area - the Senianska depression is located near the village of Senne, between the Laborec and Uh Rivers. Specifically, it is a traditional landscape of meadows, marshes, cultivated soil, small water control structures and forests. To get a complete model set up for simulating elements of the hydrologic balance in the pilot area, it was necessary to devise a model for a larger area, which includes the pilot area - the Senianska depression. Therefore, both the Mike SHE model was set up for the Laborec River basin (a model domain of 500 × 500 m) and the Čierna voda River basin (a model domain of 100 × 100 m), for the simulation period of 1981-2007, is order to get the boundary conditions (overland flow depth, water levels, discharges and groundwater table) for the model of the pilot area. The Mike SHE model constructed for the pilot area - the Senianska depression (a model domain of 1 × 1 m) -was used to simulate the elements of the hydrological balance for the existing conditions during the simulation period of 1983-2007 and for climate scenarios for the simulation period of 1983-2100. The results of the simulated elements of the hydrological balance for the existing conditions were used for a comparison of the evolution of the hydrologic conditions in the past, for identifying wet and flooded areas and for identifying the spatial distribution of the actual evapotranspiration in the pilot area. The built-up model with setting values was used for modeling the hydrological balance in changed conditions - climate change.
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Abbas, Ather, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, and Kyung Hwa Cho. "AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods." Geoscientific Model Development 15, no. 7 (April 8, 2022): 3021–39. http://dx.doi.org/10.5194/gmd-15-3021-2022.
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Abstract. Machine learning has shown great promise for simulating hydrological phenomena. However, the development of machine-learning-based hydrological models requires advanced skills from diverse fields, such as programming and hydrological modeling. Additionally, data pre-processing and post-processing when training and testing machine learning models are a time-intensive process. In this study, we developed a python-based framework that simplifies the process of building and training machine-learning-based hydrological models and automates the process of pre-processing hydrological data and post-processing model results. Pre-processing utilities assist in incorporating domain knowledge of hydrology in the machine learning model, such as the distribution of weather data into hydrologic response units (HRUs) based on different HRU discretization definitions. The post-processing utilities help in interpreting the model's results from a hydrological point of view. This framework will help increase the application of machine-learning-based modeling approaches in hydrological sciences.
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Mai, Juliane, James R. Craig, and Bryan A. Tolson. "Simultaneously determining global sensitivities of model parameters and model structure." Hydrology and Earth System Sciences 24, no. 12 (December 8, 2020): 5835–58. http://dx.doi.org/10.5194/hess-24-5835-2020.
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Abstract. Model structure uncertainty is known to be one of the three main sources of hydrologic model uncertainty along with input and parameter uncertainty. Some recent hydrological modeling frameworks address model structure uncertainty by supporting multiple options for representing hydrological processes. It is, however, still unclear how best to analyze structural sensitivity using these frameworks. In this work, we apply the extended Sobol' sensitivity analysis (xSSA) method that operates on grouped parameters rather than individual parameters. The method can estimate not only traditional model parameter sensitivities but is also able to provide measures of the sensitivities of process options (e.g., linear vs. non-linear storage) and sensitivities of model processes (e.g., infiltration vs. baseflow) with respect to a model output. Key to the xSSA method's applicability to process option and process sensitivity is the novel introduction of process option weights in the Raven hydrological modeling framework. The method is applied to both artificial benchmark models and a watershed model built with the Raven framework. The results show that (1) the xSSA method provides sensitivity estimates consistent with those derived analytically for individual as well as grouped parameters linked to model structure. (2) The xSSA method with process weighting is computationally less expensive than the alternative aggregate sensitivity analysis approach performed for the exhaustive set of structural model configurations, with savings of 81.9 % for the benchmark model and 98.6 % for the watershed case study. (3) The xSSA method applied to the hydrologic case study analyzing simulated streamflow showed that model parameters adjusting forcing functions were responsible for 42.1 % of the overall model variability, while surface processes cause 38.5 % of the overall model variability in a mountainous catchment; such information may readily inform model calibration and uncertainty analysis. (4) The analysis of time-dependent process sensitivities regarding simulated streamflow is a helpful tool for understanding model internal dynamics over the course of the year.
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Arnold, S., S. Attinger, K. Frank, and A. Hildebrandt. "Uncertainty in parameterisation and model structure affect simulation results in coupled ecohydrological models." Hydrology and Earth System Sciences 13, no. 10 (October 6, 2009): 1789–807. http://dx.doi.org/10.5194/hess-13-1789-2009.
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Abstract. In this paper we develop and apply a conceptual ecohydrological model to investigate the effects of model structure and parameter uncertainty on the simulation of vegetation structure and hydrological dynamics. The model is applied for a typical water limited riparian ecosystem along an ephemeral river: the middle section of the Kuiseb River in Namibia. We modelled this system by coupling an ecological model with a conceptual hydrological model. The hydrological model is storage based with stochastical forcing from the flood. The ecosystem is modelled with a population model, and represents three dominating riparian plant populations. In appreciation of uncertainty about population dynamics, we applied three model versions with increasing complexity. Population parameters were found by Latin hypercube sampling of the parameter space and with the constraint that three species should coexist as observed. Two of the three models were able to reproduce the observed coexistence. However, both models relied on different coexistence mechanisms, and reacted differently to change of long term memory in the flood forcing. The coexistence requirement strongly constrained the parameter space for both successful models. Only very few parameter sets (0.5% of 150 000 samples) allowed for coexistence in a representative number of repeated simulations (at least 10 out of 100) and the success of the coexistence mechanism was controlled by the combination of population parameters. The ensemble statistics of average values of hydrologic variables like transpiration and depth to ground water were similar for both models, suggesting that they were mainly controlled by the applied hydrological model. The ensemble statistics of the fluctuations of depth to groundwater and transpiration, however, differed significantly, suggesting that they were controlled by the applied ecological model and coexistence mechanisms. Our study emphasizes that uncertainty about ecosystem structure and intra-specific interactions influence the prediction of the hydrosystem.
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Wang, Shao, Su, Cui, and Zhang. "The Application of Improved SWAT Model to Hydrological Cycle Study in Karst Area of South China." Sustainability 11, no. 18 (September 13, 2019): 5024. http://dx.doi.org/10.3390/su11185024.
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In the karst area of southern China, karst water is important for supporting the sustainable production and home living for the local residents. Consequently, it is of significance to fully understand the water cycle, so as to make full use of water resources. In karst areas, epikarst and conduits are developed, participating in the hydrological cycle actively. For conventional lumped hydrologic models, it is difficult to simulate the hydrological cycle accurately. These models neglect to consider the variation of underlying surface and weather change. Meanwhile, for the original distributed hydrological model, the existence of epikarst and underground conduits as well as inadequate data information also make it difficult to achieve accurate simulation. To this end, the framework combining the advantages of lumped model–reservoir model and distributed hydrologic model–Soil and Water Assessment Tool (SWAT) model is established to simulate the water cycle efficiently in a karst area. Xianghualing karst watershed in southern China was selected as the study area and the improved SWAT model was used to simulate the water cycle. Results show that the indicators of ENS and R2 in the calibration and verification periods are both above 0.8, which is evidently improved in comparison with the original model. The improved SWAT model is verified to have better efficiency in describing the hydrological cycle in a typical karst area.
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Li, Zeli, Kai Gao, Xiaochao Gu, Pengyu Mei, Zhen Zhang, and Yuqiu Wang. "Nitrogen and phosphorus load estimation of inflow rivers to Yuqiao Reservoir based on GWLF model." IOP Conference Series: Earth and Environmental Science 1087, no. 1 (October 1, 2022): 012016. http://dx.doi.org/10.1088/1755-1315/1087/1/012016.
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Abstract Watershed model technology was an important tool for non-point source pollution prevention and control. In order to figure out the total nitrogen (TN) and total phosphorus (TP) load of inflow rivers to Yuqiao Reservoir in 2021, GWLF model was used to simulate the hydrologic process in its sub-basin. Firstly, the hydrological parameters of the model were determined by the measured meteorological and hydrological data. Secondly, the hydrological parameters were extended to the whole basin, and the three main river inflows to Yuqiao Reservoir were simulated in 2021. Lastly, the nutrient loads were estimated by multiplying the simulated inflow as mentioned above by the observed TN and TP concentration data at the same site. The results showed that the TN and TP load of inflow rivers was 7 106.9 t and 80.0 t, respectively, of which the flood period from July to August contributed 55.3% and 69.3%, respectively. GWLF model was effective in simulating hydrological processes in the study area. The Nash efficiency coefficients of the calibration and the validation period were 0.89 and 0.91, respectively. GWLF model was suitable for hydrological simulation and estimation of non-point source pollution load in small and medium-sized basins.
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Voinov, A., R. Costanza, C. Fitz, and T. Maxwell. "Patuxent landscape model: 1. Hydrological model development." Water Resources 34, no. 2 (April 2007): 163–70. http://dx.doi.org/10.1134/s0097807807020066.
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Shu, Lele, Paul Ullrich, Xianhong Meng, Christopher Duffy, Hao Chen, and Zhaoguo Li. "rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment." Geoscientific Model Development 17, no. 2 (January 19, 2024): 497–527. http://dx.doi.org/10.5194/gmd-17-497-2024.
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Abstract. Hydrological modeling is a crucial component in hydrology research, particularly for projecting future scenarios. However, achieving reproducibility and automation in distributed hydrological modeling research for modeling, simulation, and analysis is challenging. This paper introduces rSHUD v2.0, an innovative, open-source toolkit developed in the R environment to enhance the deployment and analysis of the Simulator for Hydrologic Unstructured Domains (SHUD). The SHUD is an integrated surface–subsurface hydrological model that employs a finite-volume method to simulate hydrological processes at various scales. The rSHUD toolkit includes pre- and post-processing tools, facilitating reproducibility and automation in hydrological modeling. The utility of rSHUD is demonstrated through case studies of the Shale Hills Critical Zone Observatory in the USA and the Waerma watershed in China. The rSHUD toolkit's ability to quickly and automatically deploy models while ensuring reproducibility has facilitated the implementation of the Global Hydrological Data Cloud (https://ghdc.ac.cn, last access: 1 September 2023), a platform for automatic data processing and model deployment. This work represents a significant advancement in hydrological modeling, with implications for future scenario projections and spatial analysis.
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Herbst, M., H. V. Gupta, and M. C. Casper. "Mapping model behaviour using Self-Organizing Maps." Hydrology and Earth System Sciences Discussions 5, no. 6 (December 4, 2008): 3517–55. http://dx.doi.org/10.5194/hessd-5-3517-2008.
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Abstract. Hydrological model evaluation and identification essentially depends on the extraction of information from model time series and its processing. However, the type of information extracted by statistical measures has only very limited meaning because it does not relate to the hydrological context of the data. To overcome this inadequacy we exploit the diagnostic evaluation concept of Signature Indices, in which model performance is measured using theoretically relevant characteristics of system behaviour. In our study, a Self-Organizing Map (SOM) is used to process the Signatures extracted from Monte-Carlo simulations generated by a distributed conceptual watershed model. The SOM creates a hydrologically interpretable mapping of overall model behaviour, which immediately reveals deficits and trade-offs in the ability of the model to represent the different functional behaviours of the watershed. Further, it facilitates interpretation of the hydrological functions of the model parameters and provides preliminary information regarding their sensitivities. Most notably, we use this mapping to identify the set of model realizations (among the Monte-Carlo data) that most closely approximate the observed discharge time series in terms of the hydrologically relevant characteristics, and to confine the parameter space accordingly. Our results suggest that Signature Index based SOMs could potentially serve as tools for decision makers inasmuch as model realizations with specific Signature properties can be selected according to the purpose of the model application. Moreover, given that the approach helps to represent and analyze multi-dimensional distributions, it could be used to form the basis of an optimization framework that uses SOMs to characterize the model performance response surface. As such it provides a powerful and useful way to conduct model identification and model uncertainty analyses.
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Herbst, M., H. V. Gupta, and M. C. Casper. "Mapping model behaviour using Self-Organizing Maps." Hydrology and Earth System Sciences 13, no. 3 (March 18, 2009): 395–409. http://dx.doi.org/10.5194/hess-13-395-2009.
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Abstract. Hydrological model evaluation and identification essentially involves extracting and processing information from model time series. However, the type of information extracted by statistical measures has only very limited meaning because it does not relate to the hydrological context of the data. To overcome this inadequacy we exploit the diagnostic evaluation concept of Signature Indices, in which model performance is measured using theoretically relevant characteristics of system behaviour. In our study, a Self-Organizing Map (SOM) is used to process the Signatures extracted from Monte-Carlo simulations generated by the distributed conceptual watershed model NASIM. The SOM creates a hydrologically interpretable mapping of overall model behaviour, which immediately reveals deficits and trade-offs in the ability of the model to represent the different functional behaviours of the watershed. Further, it facilitates interpretation of the hydrological functions of the model parameters and provides preliminary information regarding their sensitivities. Most notably, we use this mapping to identify the set of model realizations (among the Monte-Carlo data) that most closely approximate the observed discharge time series in terms of the hydrologically relevant characteristics, and to confine the parameter space accordingly. Our results suggest that Signature Index based SOMs could potentially serve as tools for decision makers inasmuch as model realizations with specific Signature properties can be selected according to the purpose of the model application. Moreover, given that the approach helps to represent and analyze multi-dimensional distributions, it could be used to form the basis of an optimization framework that uses SOMs to characterize the model performance response surface. As such it provides a powerful and useful way to conduct model identification and model uncertainty analyses.
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Daide, Fatima, Rachida Afgane, Abderrahim Lahrach, Abdel-Ali Chaouni, Mohamed Msaddek, and Ismail Elhasnaoui. "Application of the HEC-HMS hydrological model in the Beht watershed (Morocco)." E3S Web of Conferences 314 (2021): 05003. http://dx.doi.org/10.1051/e3sconf/202131405003.
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This work focused on the collection and preparation of the data required for the hydrological modelling of the Beht catchment area, which covers an area of 4560 km2 with a perimeter of 414 km, by combining the various spatial technologies, in particular geographical information systems (GIS), remote sensing, and digital terrain models (DTM), with hydrological models in order to prepare for spatial hydrological modelling used for flood forecasting. The methodology consists, at first, in the automatic extraction of the sub-basins and the drainage network. Then, edit these data using the HEC-GEO-HMS extension, and the preparation of the land use and land cover data for the elaboration of a Curve Number (CN) map of Beht watershed, then the import of the basin model into the Hydrologic Modeling System (HEC-HMS) to simulate the surface runoff using six extreme daily time series events.
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Kamp, R. G., and H. H. G. Savenije. "Hydrological model coupling with ANNs." Hydrology and Earth System Sciences Discussions 3, no. 6 (December 6, 2006): 3629–53. http://dx.doi.org/10.5194/hessd-3-3629-2006.
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Abstract. Model coupling in general is necessary but complicated. Scientists develop and improve conceptual models to represent physical processes occurring in nature. The next step is to translate these concepts into a mathematical model and finally into a computer model. Problems may appear if the knowledge, encapsulated in a computer model and software program is needed for another purpose. In integrated water management this is often the case when connections between hydrological, hydraulic or ecological models are required. Coupling is difficult for many reasons, related to data formats, compatibility of scales, ability to modify source codes, etc. Hence, there is a need for an efficient and cost effective approach to model-coupling. One solution for model coupling is the use of Artificial Neural Networks (ANNs). The ANN can be used as a fast and effective model simulator which can connect different models. In this paper ANNs are used to couple four different models: a rainfall runoff model, a river channel routing model, an estuarine salt intrusion model, and an ecological model. The coupling as such has proven to be feasible and efficient. However the salt intrusion model appeared difficult to model accurately in an ANN. The ANN has difficulty to represent both short term (tidal) and long term (hydrological) processes.
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Kamp, R. G., and H. H. G. Savenije. "Hydrological model coupling with ANNs." Hydrology and Earth System Sciences 11, no. 6 (December 4, 2007): 1869–81. http://dx.doi.org/10.5194/hess-11-1869-2007.
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Abstract. There is an increasing need for model coupling. However, model coupling is complicated. Scientists develop and improve models to represent physical processes occurring in nature. These models are built in different software programs required to run the model. A software program or application represents part of the system knowledge. This knowledge is however encapsulated in the program and often difficult to access. In integrated water resources management it is often necessary to connect hydrological, hydraulic or ecological models. Model coupling can in practice be difficult for many reasons related to data formats, compatibility of scales, ability to modify source codes, etc. Hence, there is a need for an efficient and cost effective approach to model-coupling. Artificial neural networks (ANNs) can be used as an alternative to replace a model and simulate the model's output and connect it to other models. In this paper, we investigate an alternative to traditional model coupling techniques. ANNs are four different models: a rainfall runoff model, a river channel routing model, an estuarine salt intrusion model, and an ecological model. The output results of each model is simulated by a neural network that is trained on corresponding input and output data sets. The models are connected in cascade and their input and output variables are connected. To test the results of the coupled neural network also a coupled system of four sub-system models has been set-up. These results have been compared to the results of the coupled neural networks. The results show that it is possible to train neural networks and connect these models. The results of the salt intrusion model was however not very accurate. It was difficult for the neural network to represent both short term (tidal) and long term (hydrological) processes.
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ANDO, Yosihisa, and Yosihiko ORISAKA. "Hydrological Model for Mountainous Basin." PROCEEDINGS OF THE JAPANESE CONFERENCE ON HYDRAULICS 33 (1989): 37–42. http://dx.doi.org/10.2208/prohe1975.33.37.
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P. C., Shakti, Tsuyoshi Nakatani, and Ryohei Misumi. "The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan." Water 11, no. 8 (August 16, 2019): 1703. http://dx.doi.org/10.3390/w11081703.
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Recently, the use of gridded rainfall data with high spatial resolutions in hydrological applications has greatly increased. Various types of radar rainfall data with varying spatial resolutions are available in different countries worldwide. As a result of the variety in spatial resolutions of available radar rainfall data, the hydrological community faces the challenge of selecting radar rainfall data with an appropriate spatial resolution for hydrological applications. In this study, we consider the impact of the spatial resolution of radar rainfall on simulated river runoff to better understand the impact of radar resolution on hydrological applications. Very high-resolution polarimetric radar rainfall (XRAIN) data are used as input for the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) to simulate runoff from the Tsurumi River Basin, Japan. A total of 20 independent rainfall events from 2012–2015 were selected and categorized into isolated/convective and widespread/stratiform events based on their distribution patterns. First, the hydrological model was established with basin and model parameters that were optimized for each individual rainfall event; then, the XRAIN data were rescaled at various spatial resolutions to be used as input for the model. Finally, we conducted a statistical analysis of the simulated results to determine the optimum spatial resolution for radar rainfall data used in hydrological modeling. Our results suggest that the hydrological response was more sensitive to isolated or convective rainfall data than it was to widespread rain events, which are best simulated at ≤1 km and ≤5 km, respectively; these results are applicable in all sub-basins of the Tsurumi River Basin, except at the river outlet.
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Zhu, Bowen, Xianhong Xie, Yibing Wang, and Xuehua Zhao. "The Benefits of Continental-Scale High-Resolution Hydrological Modeling in the Detection of Extreme Hydrological Events in China." Remote Sensing 15, no. 9 (May 4, 2023): 2402. http://dx.doi.org/10.3390/rs15092402.
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High-resolution hydrological modeling is crucial for detecting extreme hydrological events and understanding fundamental terrestrial processes. However, spatial resolutions in current hydrological modeling studies have been mostly constrained to relatively coarse resolution (~10–100 km), and they therefore have a difficult time addressing flooding or drought issues with fine resolutions. In this study, a continental-scale high-resolution hydrological modeling framework (0.0625°, ~6 km) driven by remote sensing products was used to detect extreme hydrological event occurrences in China and evaluated based on the Variable Infiltration Capacity (VIC) model. The results showed that the developed model provided more detailed information than the coarser resolution models (a 0.25° and 1°), thereby capturing the timing, duration, and spatial extent of extreme hydrologic events regarding the 2012 Beijing flood and 2009/10 drought in Hai River Basin. Here, the total water storage changes were calculated based on the VIC model (−0.017 mm/year) and Gravity Recovery and Climate Experiment (GRACE) satellite (−0.203 mm/year) to reflect the water availability caused by climate change and anthropogenic factors. This study found that the 0.0625° dataset could capture detailed changes, thereby providing reliable information during occurrences of extreme hydrological events. The high-resolution model integrated with remote sensing products could be used for accurate evaluations of continental-scale extreme hydrological events and can be valuable in understanding its long-term occurrence and water resource security.
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So, Jae-Min, Joo-Heon Lee, and Deg-Hyo Bae. "Development of a Hydrological Drought Forecasting Model Using Weather Forecasting Data from GloSea5." Water 12, no. 10 (October 6, 2020): 2785. http://dx.doi.org/10.3390/w12102785.
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This study developed a hydrological drought forecasting framework linked to the meteorological model and land surface model (LSM) considering hydrologic facilities and evaluated the feasibility of the Modified Surface Water Supply Index (MSWSI) for drought forecasts in South Korea. The Global Seasonal Forecast System version 5 (GloSea5) and variable infiltration capacity (VIC) models were adapted for meteorological and hydrological models for ensemble weather forecasts and corresponding hydrologic river and dam inflow forecasts, respectively. Instead of direct use for weather and runoff forecasts, the anomaly between the ensemble forecast and hindcast data for each month was computed. Then, the monthly forecasted weather and runoff were obtained by adding this anomaly and the statistical nominal values obtained from the average monthly runoff during the last 30 years. For the selection of drought index duration, past historical observation data and drought records were used, and the 3-month period of the MSWSI outperformed any other durations in the study area. In addition, the simulated monthly river and dam inflows agreed well with the observed inflows; therefore, the model-driven runoff data from the VIC model were usable for hydrological drought forecasts. A case study result for the 2015–2016 drought event demonstrated that the hydrological drought forecasting framework suggested in this study is reliable for drought forecasting up to a 2-month forecast lead time. It is therefore concluded that the proposed framework linked with GloSea5, the VIC model and MSWSI(3) provides useful information for supporting decision-making related to water supply and management.
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Haberlandt, U., and I. Radtke. "Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows." Hydrology and Earth System Sciences 18, no. 1 (January 30, 2014): 353–65. http://dx.doi.org/10.5194/hess-18-353-2014.
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Abstract. Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.
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Kaykhosravi, Sarah, Karen Abogadil, Usman T. Khan, and Mojgan A. Jadidi. "The Low-Impact Development Demand Index: A New Approach to Identifying Locations for LID." Water 11, no. 11 (November 8, 2019): 2341. http://dx.doi.org/10.3390/w11112341.
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The primary goal of low impact development (LID) is to capture urban stormwater runoff; however, multiple indirect benefits (environmental and socioeconomic benefits) also exist (e.g., improvements to human health and decreased air pollution). Identifying sites with the highest demand or need for LID ensures the maximization of all benefits. This is a spatial decision-making problem that has not been widely addressed in the literature and was the focus of this research. Previous research has focused on finding feasible sites for installing LID, whilst only considering insufficient criteria which represent the benefits of LID (either neglecting the hydrological and hydraulic benefits or indirect benefits). This research considered the hydrological and hydraulic, environmental, and socioeconomic benefits of LID to identify sites with the highest demand for LID. Specifically, a geospatial framework was proposed that uses publicly available data, hydrological-hydraulic principles, and a simple additive weighting (SAW) method within a hierarchical decision-making model. Three indices were developed to determine the LID demand: (1) hydrological-hydraulic index (HHI), (2) socioeconomic index (SEI), and (3) environmental index (ENI). The HHI was developed based on a heuristic model using hydrological-hydraulic principles and validated against the results of a physical model, the Hydrologic Engineering Center-Hydrologic Modeling System model (HEC-HMS). The other two indices were generated using the SAW hierarchical model and then incorporated into the HHI index to generate the LID demand index (LIDDI). The framework was applied to the City of Toronto, yielding results that are validated against historical flooding records.
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Yu, Cui Song, and Xiao Na Guo. "Hydrological Frequency Calculation Method Study of Urban Rivers Runoff under Changing Environment." Applied Mechanics and Materials 170-173 (May 2012): 2023–26. http://dx.doi.org/10.4028/www.scientific.net/amm.170-173.2023.
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The consistency of hydrological series has been destroyed by the impact of human activities and climate change. Hydrological series is consist of certain component and random element. The random and certain components of hydrological series are identified and separated through statistic analysis. The certain element is determined by using hydrologic model while the consistancy of random element is confirmed directly by hydrological frequency curve. And then add them together. The runoff series of the Huangtai Hydrometric Station in the Xiaoqing River is for example. It proves effective and feasible and the result accord with the reality of the basin.
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Hagemann, Stefan, and Lydia Dümenil. "Application of a Global Discharge Model to Atmospheric Model Simulations in the BALTEX Region." Hydrology Research 30, no. 3 (June 1, 1999): 209–30. http://dx.doi.org/10.2166/nh.1999.0012.
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In this study, a hydrological discharge model is presented which may be applied as a tool to validate the simulation of the hydrologic cycle of atmospheric models that are used in climate change studies. It can also be applied in studies of global climate change to investigate how changes in climate may affect the discharge of large rivers. The model was developed for the application with the climate models used at the Max-Planck-Institute for Meteorology. It describes the translation and retention of the lateral waterflows on the global scale as a function of the spatially distributed land surface characteristics which are globally available. Here, global scale refers to the resolution of 0.5° and lower, corresponding to a typical average gridbox area of about 2,500 km2. The hydrological discharge model separates between the flow processes of overland flow, baseflow and riverflow. The model parameters are mainly functions of the gridbox characteristics of topography and gridbox length. The hydrological discharge model is applied to the BALTEX (Baltic Sea Experiment) region using input from an atmospheric general circulation model (ECHAM4) as well as from a regional climate model (REMO). The simulated inflows into the Baltic Sea and its sub-catchments are compared to observed and naturalized discharges. The results of this comparison are discussed and the simulated values of precipitation, surface air temperature and accumulated snowpack are compared to both observed data and surrogate data.
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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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Yao, C., L. Chang, J. Ding, Z. Li, D. An, and Y. Zhang. "Evaluation of the effects of underlying surface change on catchment hydrological response using the HEC-HMS model." Proceedings of the International Association of Hydrological Sciences 364 (September 16, 2014): 145–50. http://dx.doi.org/10.5194/piahs-364-145-2014.
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Abstract. Due to rapid population growth, China, and urbanization, the Dongwan catchment, with a drainage area of 2856 km2 and located in Henan Province, has been subjected to considerable land-use changes since the 1990s. Distributed or semi-distributed models have been widely used in catchment hydrological modeling, along with the rapid development of computer and GIS technologies. The objective of this study is to assess the impact of underlying surface change on catchment hydrological response using the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS), which is a distributed hydrological model. Specifically, 21 flood events were selected for calibrating and validating the model parameters. The satisfactory results show that the HEC-HMS model can be used to simulate the rainfall–runoff response in the Dongwan catchment. In light of the analyses of simulation results, it is shown that the flood peaks and runoff yields after 1990 moderately decrease in comparison with that before 1990 at the same precipitation level. It is also indicated that the underlying surface change leads to the increased flood storage capacity after 1990 in this region.
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Chen, Gang, Wenjuan Hua, Xing Fang, Chuanhai Wang, and Xiaoning Li. "Distributed-Framework Basin Modeling System: II. Hydrologic Modeling System." Water 13, no. 5 (March 9, 2021): 744. http://dx.doi.org/10.3390/w13050744.
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A distributed-framework hydrologic modeling system (DF-HMS) is a primary and significant component of a distributed-framework basin modeling system (DFBMS), which simulates the hydrological processes and responses after rainfall at the basin scale, especially for non-homogenous basins. The DFBMS consists of 11 hydrological feature units (HFUs) involving vertical and horizontal geographic areas in a basin. Appropriate hydrologic or hydraulic methods are adopted for different HFUs to simulate corresponding hydrological processes. The digital basin generation model is first developed to determine the essential information for hydrologic and hydraulic simulation. This paper mainly describes two significant HFUs contained in the DF-HMS for hydrologic modeling: Hilly sub-watershed and plain overland flow HFUs. A typical hilly area application case study in the Three Gorges area is introduced, which demonstrates DF-HMS’s good performance in comparison with the observed streamflow at catchment outlets.
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Zalachori, I., M. H. Ramos, R. Garçon, T. Mathevet, and J. Gailhard. "Statistical processing of forecasts for hydrological ensemble prediction: a comparative study of different bias correction strategies." Advances in Science and Research 8, no. 1 (July 25, 2012): 135–41. http://dx.doi.org/10.5194/asr-8-135-2012.
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Abstract. The aim of this paper is to investigate the use of statistical correction techniques in hydrological ensemble prediction. Ensemble weather forecasts (precipitation and temperature) are used as forcing variables to a hydrologic forecasting model for the production of ensemble streamflow forecasts. The impact of different bias correction strategies on the quality of the forecasts is examined. The performance of the system is evaluated when statistical processing is applied: to precipitation and temperature forecasts only (pre-processing from the hydrological model point of view), to flow forecasts (post-processing) and to both. The pre-processing technique combines precipitation ensemble predictions with an analog forecasting approach, while the post-processing is based on past errors of the hydrological model when simulating streamflows. Forecasts from 11 catchments in France are evaluated. Results illustrate the importance of taking into account hydrological uncertainties to improve the quality of operational streamflow forecasts.
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Zink, Matthias, Rohini Kumar, Matthias Cuntz, and Luis Samaniego. "A high-resolution dataset of water fluxes and states for Germany accounting for parametric uncertainty." Hydrology and Earth System Sciences 21, no. 3 (March 27, 2017): 1769–90. http://dx.doi.org/10.5194/hess-21-1769-2017.
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Abstract. Long-term, high-resolution data about hydrologic fluxes and states are needed for many hydrological applications. Because continuous large-scale observations of such variables are not feasible, hydrologic or land surface models are applied to derive them. This study aims to analyze and provide a consistent high-resolution dataset of land surface variables over Germany, accounting for uncertainties caused by equifinal model parameters. The mesoscale Hydrological Model (mHM) is employed to derive an ensemble (100 members) of evapotranspiration, groundwater recharge, soil moisture, and runoff generated at high spatial and temporal resolutions (4 km and daily, respectively) for the period 1951–2010. The model is cross-evaluated against the observed daily streamflow in 222 basins, which are not used for model calibration. The mean (standard deviation) of the ensemble median Nash–Sutcliffe efficiency estimated for these basins is 0.68 (0.09) for daily streamflow simulations. The modeled evapotranspiration and soil moisture reasonably represent the observations from eddy covariance stations. Our analysis indicates the lowest parametric uncertainty for evapotranspiration, and the largest is observed for groundwater recharge. The uncertainty of the hydrologic variables varies over the course of a year, with the exception of evapotranspiration, which remains almost constant. This study emphasizes the role of accounting for the parametric uncertainty in model-derived hydrological datasets.
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Xin, Zhuohang, Ke Shi, Chenchen Wu, Lu Wang, and Lei Ye. "Applicability of Hydrological Models for Flash Flood Simulation in Small Catchments of Hilly Area in China." Open Geosciences 11, no. 1 (December 31, 2019): 1168–81. http://dx.doi.org/10.1515/geo-2019-0089.
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Abstract Flash flood in small catchments of hilly area is an extremely complicated nonlinear process affected by catchment properties and rainfall spatio-temporal variation characteristics including many physical-geographical factors, and thus accurate simulation of flash flood is very difficult. Given the fact that hundreds of hydrological models are available in the literature, how to choose a suitable hydrological model remains an unsolved task. In this paper, we selected five widely used hydrological models including three lumped hydrologic models, a semi-distributed hydrological model and a distributed hydrological model for flash flood simulation, and studied their applicability in fourteen typical catchments in hilly areas across China. The results show that the HEC-HMS distributed hydrological model outperforms the other models and is suitable to simulate the flash floods caused by highly intense rainfall. The Dahuofang model (lumped) has higher precision in peak runoff time simulation. However, its performance is quite poor on the flood volume simulation in the small catchments characterized by intense vegetation coverage and highly developed stream network. The Antecedent precipitation index and Xinanjiang models (lumped) can obtain good simulation results in small humid catchments as long as long-term historical precipitation and runoff data are provided. The TOPMODEL also shows good performance in small humid catchments, but it is unable to simulate the flash floods characterized by the rapid rise and recession. Our results could be very beneficial in practice, since these provide a solid foundation in the selection of hydrological model for flash flood simulation in small catchments in hilly area.
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Shaikh, Wajid Ali, Syed Feroz Shah, Muhammad Anwar Solangi, and Siraj Muhammed Pandhiani. "Forecasting Analysis of GMDH model with LSSVM and MARS models for Hydrological Datasets (Case study)." Indian Journal of Science and Technology 12, no. 39 (October 20, 2019): 1–6. http://dx.doi.org/10.17485/ijst/2019/v12i39/147941.
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André, Arlon. "Hydrological Modeling of the Cambamba Watershed in Angola Using the HEC-HMS Model." Modern Environmental Science and Engineering 8, no. 9 (September 8, 2022): 459–70. http://dx.doi.org/10.15341/mese(2333-2581)/09.08.2022/002.
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When evaluating the impact of climate change on water resources in river basins it is crucial to accurately estimate the availability of water and such can be attained through hydrological modeling of the basin. The studies of the Hydrological Modeling System (HEC-HMS) for the Cambamba River Basin in Angola has been calibrated and validated for the prediction of its hydrologic response. Due to the complexity of Hydrologic models, a good calibration of the model should be established, therefore, improving its skills and effectiveness. A combination of both the energy budget and a physically-based rainfall-runoff model, which are used for the estimation of lake evaporation, were applied in the lake water balance model. Soil storage, as well as groundwater storage coefficient, are essential parameters for estimating the simulated streamflow. For an adequate performance evaluation of the model which entails the simulation of the streamflow on Cambamba watershed and quantification of water availability, The Nash-Sutcliffe model efficiency criterion; root mean square error; percentage error in volume PEV; and percentage error in peak PEP, were implemented. Model performance is improved by using semiannual parameter sets that consider the change in hydrological conditions, as evaluated in this study. Key words: HEC-HMS, watershed, rainfall-runoff, flood hazards
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Hamdan, Ahmed Naseh Ahmed, Suhad Almuktar, and Miklas Scholz. "Rainfall-Runoff Modeling Using the HEC-HMS Model for the Al-Adhaim River Catchment, Northern Iraq." Hydrology 8, no. 2 (March 26, 2021): 58. http://dx.doi.org/10.3390/hydrology8020058.
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It has become necessary to estimate the quantities of runoff by knowing the amount of rainfall to calculate the required quantities of water storage in reservoirs and to determine the likelihood of flooding. The present study deals with the development of a hydrological model named Hydrologic Engineering Center (HEC-HMS), which uses Digital Elevation Models (DEM). This hydrological model was used by means of the Geospatial Hydrologic Modeling Extension (HEC-GeoHMS) and Geographical Information Systems (GIS) to identify the discharge of the Al-Adhaim River catchment and embankment dam in Iraq by simulated rainfall-runoff processes. The meteorological models were developed within the HEC-HMS from the recorded daily rainfall data for the hydrological years 2015 to 2018. The control specifications were defined for the specified period and one day time step. The Soil Conservation Service-Curve number (SCS-CN), SCS Unit Hydrograph and Muskingum methods were used for loss, transformation and routing calculations, respectively. The model was simulated for two years for calibration and one year for verification of the daily rainfall values. The results showed that both observed and simulated hydrographs were highly correlated. The model’s performance was evaluated by using a coefficient of determination of 90% for calibration and verification. The dam’s discharge for the considered period was successfully simulated but slightly overestimated. The results indicated that the model is suitable for hydrological simulations in the Al-Adhaim river catchment.
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Gunathilake, Miyuru B., Chamaka Karunanayake, Anura S. Gunathilake, Niranga Marasingha, Jayanga T. Samarasinghe, Isuru M. Bandara, and Upaka Rathnayake. "Hydrological Models and Artificial Neural Networks (ANNs) to Simulate Streamflow in a Tropical Catchment of Sri Lanka." Applied Computational Intelligence and Soft Computing 2021 (May 27, 2021): 1–9. http://dx.doi.org/10.1155/2021/6683389.
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Accurate streamflow estimations are essential for planning and decision-making of many development activities related to water resources. Hydrological modelling is a frequently adopted and a matured technique to simulate streamflow compared to the data driven models such as artificial neural networks (ANNs). In addition, usage of ANNs is minimum to simulate streamflow in the context of Sri Lanka. Therefore, this study presents an intercomparison between streamflow estimations from conventional hydrological modelling and ANN analysis for Seethawaka River Basin located in the upstream part of the Kelani River Basin, Sri Lanka. The hydrological model was developed using the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS), while the data-driven ANN model was developed in MATLAB. The rainfall and streamflows’ data for 2003–2010 period have been used. The simulations by HEC-HMS were performed by four types of input rainfall data configurations, including observed rainfall data sets and three satellite-based precipitation products (SbPPs), namely, PERSIANN, PERSIANN-CCS, and PERSIANN-CDR. The ANN model was trained using three well-known training algorithms, namely, Levenberg–Marquadt (LM), Bayesian regularization (BR), and scaled conjugate gradient (SCG). Results revealed that the simulated hydrological model based on observed rainfall outperformed those of based on remotely sensed SbPPs. BR algorithm-based ANN algorithm was found to be superior among the data-driven models in the context of ANN model simulations. However, none of the above developed models were able to capture several peak discharges recorded in the Seethawaka River. The results of this study indicate that ANN models can be used to simulate streamflow to an acceptable level, despite presence of intensive spatial and temporal data sets, which are often required for hydrologic software. Hence, the results of the current study provide valuable feedback for water resources’ planners in the developing region which lack multiple data sets for hydrologic software.
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Wanders, Niko, Stephan Thober, Rohini Kumar, Ming Pan, Justin Sheffield, Luis Samaniego, and Eric F. Wood. "Development and Evaluation of a Pan-European Multimodel Seasonal Hydrological Forecasting System." Journal of Hydrometeorology 20, no. 1 (January 1, 2019): 99–115. http://dx.doi.org/10.1175/jhm-d-18-0040.1.
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Abstract Hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by end users. So far high-resolution multimodel seasonal hydrological forecasts have been unavailable due to 1) lack of availability of high-resolution meteorological seasonal forecasts, requiring temporal and spatial downscaling; 2) a mismatch between the provided seasonal forecast information and the user needs; and 3) lack of consistency between the hydrological model outputs to generate multimodel seasonal hydrological forecasts. As part of the End-to-End Demonstrator for Improved Decision Making in the Water Sector in Europe (EDgE) project commissioned by the Copernicus Climate Change Service (ECMWF), this study provides a unique dataset of seasonal hydrological forecasts derived from four general circulation models [CanCM4, GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 (GFDL-FLOR), ECMWF Season Forecast System 4 (ECMWF-S4), and Météo-France LFPW] in combination with four hydrological models [mesoscale hydrologic model (mHM), Noah-MP, PCRaster Global Water Balance (PCR-GLOBWB), and VIC]. The forecasts are provided at daily resolution, 6-month lead time, and 5-km spatial resolution over the historical period from 1993 to 2012. Consistency in hydrological model parameterization ensures an increased consistency in the hydrological forecasts. Results show that skillful discharge forecasts can be made throughout Europe up to 3 months in advance, with predictability up to 6 months for northern Europe resulting from the improved predictability of the spring snowmelt. The new system provides an unprecedented ensemble of seasonal hydrological forecasts with significant skill over Europe to support water management. This study highlights the potential advantages of multimodel based forecasting system in providing skillful hydrological forecasts.
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Melišová, Eva, Adam Vizina, Linda R. Staponites, and Martin Hanel. "The Role of Hydrological Signatures in Calibration of Conceptual Hydrological Model." Water 12, no. 12 (December 3, 2020): 3401. http://dx.doi.org/10.3390/w12123401.
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Determining an optimal calibration strategy for hydrological models is essential for a robust and accurate water balance assessment, in particular, for catchments with limited observed data. In the present study, the hydrological model Bilan was used to simulate hydrological balance for 20 catchments throughout the Czech Republic during the period 1981–2016. Calibration strategies utilizing observed runoff and estimated soil moisture time series were compared with those using only long-term statistics (signatures) of runoff and soil moisture as well as a combination of signatures and time series. Calibration strategies were evaluated considering the goodness-of-fit, the bias in flow duration curve and runoff signatures and uncertainty of the Bilan model. Results indicate that the expert calibration and calibration with observed runoff time series are, in general, preferred. On the other hand, we show that, in many cases, the extension of the calibration criteria to also include runoff or soil moisture signatures is beneficial, particularly for decreasing the uncertainty in parameters of the hydrological model. Moreover, in many cases, fitting the model with hydrological signatures only provides a comparable fit to that of the calibration strategies employing runoff time series.
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Nagraj, S. Patil, M. Nataraja, and T. Omprakash. "Evaluation of Hydrological Components Using Hydrological Model SWAT for Malaprabha Subbasin." Journal of the Geological Society of India 92, no. 2 (August 2018): 195–200. http://dx.doi.org/10.1007/s12594-018-0981-z.
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