Journal articles on the topic 'Hydrologic modelling'
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Guilpart, Etienne, Vahid Espanmanesh, Amaury Tilmant, and François Anctil. "Combining split-sample testing and hidden Markov modelling to assess the robustness of hydrological models." Hydrology and Earth System Sciences 25, no. 8 (August 30, 2021): 4611–29. http://dx.doi.org/10.5194/hess-25-4611-2021.
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Abstract. The impacts of climate and land-use changes make the stationary assumption in hydrology obsolete. Moreover, there is still considerable uncertainty regarding the future evolution of the Earth’s climate and the extent of the alteration of flow regimes. Climate change impact assessment in the water sector typically involves a modelling chain in which a hydrological model is needed to generate hydrologic projections from climate forcings. Considering the inherent uncertainty of the future climate, it is crucial to assess the performance of the hydrologic model over a wide range of climates and their corresponding hydrologic conditions. In this paper, numerous, contrasted, climate sequences identified by a hidden Markov model (HMM) are used in a differential split-sample testing framework to assess the robustness of a hydrologic model. The differential split-sample test based on a HMM classification is implemented on the time series of monthly river discharges in the upper Senegal River basin in West Africa, a region characterized by the presence of low-frequency climate signals. A comparison with the results obtained using classical rupture tests shows that the diversity of hydrologic sequences identified using the HMM can help with assessing the robustness of the hydrologic model.
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Cisty, Milan, and Lubomir Celar. "Using R in Water Resources Education." International Journal for Innovation Education and Research 3, no. 10 (October 31, 2015): 97–116. http://dx.doi.org/10.31686/ijier.vol3.iss10.451.
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This review paper will deal with the possibilities of applying the R programming language in water resources and hydrologic applications in education and research. The objective of this paper is to present some features and packages that make R a powerful environment for analysing data from the hydrology and water resources management fields, hydrological modelling, the post processing of the results of such modelling, and other task. R is maintained by statistical programmers with the support of an increasing community of users from many different backgrounds, including hydrologists, which allows access to both well established and experimental techniques in various areas.
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Stella, Juan M., and Glenn S. Warner. "Modelling a hydrologic Black-Box." Tecnología y ciencias del agua 09, no. 1 (2018): 101–12. http://dx.doi.org/10.24850/j-tyca-2018-01-07.
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Tiwari, K. N., P. Kumar, M. Sebastian, and D. K. Pal. "Hydrologic modelling for runoff determination." International Journal of Water Resources Development 7, no. 3 (September 1991): 178–84. http://dx.doi.org/10.1080/07900629108722510.
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Noor, Hamzeh, Mahdi Vafakhah, Masoud Taheriyoun, and Mahnoosh Moghadasi. "Hydrology modelling in Taleghan mountainous watershed using SWAT." Journal of Water and Land Development 20, no. 1 (March 1, 2014): 11–18. http://dx.doi.org/10.2478/jwld-2014-0003.
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Abstract Mountainous regions in Iran are important sources of surface water supply and groundwater recharge. Therefore, accurate simulation of hydrologic processes in mountains at large scales is important for water resource management and for watershed management planning. Snow hydrology is the more important hydrologic process in mountainous watersheds. Therefore, streamflow simulation in mountainous watersheds is often challenging because of irregular topography and complex hydrological processes. In this study, the Soil and Water Assessment Tool (SWAT) was used to model daily runoff in the Taleghan mountainous watershed (800.5 km2) in west of Tehran, Iran. Most of the precipitation in the study area takes place as snow, therefore, modeling daily streamflow in this river is very complex and with large uncertainty. Model calibration was performed with Particle Swarm Optimization. The main input data for simulation of SWAT including Digital Elevation Model (DEM), land use, soil type and soil properties, and hydro-climatological data, were appropriately collected. Model performance was evaluated both visually and statistically where a good relation between observed and simulated discharge was found. The results showed that the coefficient of determination R2 and the Nash- Sutcliffe coefficient NS values were 0.80 and 0.78, respectively. The calibrated model was most sensitive to snowmelt parameters and CN2 (Curve Number). Results indicated that SWAT can provide reasonable predictions daily streamflow from Taleghan watersheds.
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Cranmer, A. J., N. Kouwen, and S. F. Mousavi. "Proving WATFLOOD: modelling the nonlinearities of hydrologic response to storm intensities." Canadian Journal of Civil Engineering 28, no. 5 (October 1, 2001): 837–55. http://dx.doi.org/10.1139/l01-049.
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This paper examines the effects of modelling the nonlinearities of hydrologic response to various storm intensities. Radar rainfall data, remotely sensed land use and land cover data, measured streamflows, and meteorological data were incorporated into the distributed flood forecasting model WATFLOOD to synthesize runoff hydrographs for three significant warm weather rainfall events occurring in 1995. The watershed selected for study was the 288 km2 Duffins Creek drainage basin in southern Ontario. The effects of scaling radar rainfall amounts to match regional storm intensities on the synthesized streamflow hydrographs were examined. Computations and analysis were performed in agreement with widely accepted hydrologic principles and assumptions. The observed and synthesized hydrographs were compared using the unit hydrograph method. The observed and composite unit hydrographs matched extremely well in terms of shape, timing, and peak flow magnitude. These results indicated that WATFLOOD is capable of accurately modelling the nonlinear rainfallrunoff processes for increasing rainfall intensities with respect to peak flow, basin lag, and time to peak flow. However, the arbitrariness of assessing the effective rainfall and base-flow separation for the unit hydrograph method can lead to uncertainties in computing peak flow magnitudes. The grid element size and number and the drainage areas above streamflow gauges are of critical importance to the accuracy of the model.Key words: hydrology, watershed model, flood forecasting, hydrological modelling, model validation, unit hydrograph, nonlinear response.
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Haberlandt, U. "From hydrological modelling to decision support." Advances in Geosciences 27 (August 23, 2010): 11–19. http://dx.doi.org/10.5194/adgeo-27-11-2010.
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Abstract. Decision support for planning and management of water resources needs to consider many target criteria simultaneously like water availability, water quality, flood protection, agriculture, ecology, etc. Hydrologic models provide information about the water balance components and are fundamental for the simulation of ecological processes. Objective of this contribution is to discuss the suitability of classical hydrologic models on one hand and of complex eco-hydrologic models on the other hand to be used as part of decision support systems. The discussion is based on results from two model comparison studies. It becomes clear that none of the hydrologic models tested fulfils all requirements in an optimal sense. Regarding the simulation of water quality parameters like nitrogen leaching a high uncertainty needs to be considered. Recommended for decision support is a hybrid metamodel approach, which comprises a hydrologic model, empirical relationships for the less dynamic processes and makes use of simulation results from complex eco-hydrologic models through second-order modelling at a generalized level.
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Banda, Vincent Dzulani, Rimuka Bloodless Dzwairo, Sudhir Kumar Singh, and Thokozani Kanyerere. "Hydrological Modelling and Climate Adaptation under Changing Climate: A Review with a Focus in Sub-Saharan Africa." Water 14, no. 24 (December 10, 2022): 4031. http://dx.doi.org/10.3390/w14244031.
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Empirical evidence continues to show that climate change remains a threat to the stability of the hydrologic system. As the climate system interacts with the hydrologic cycle, one significant repercussion of global warming includes changes in water availability at both regional and local scales. Climate change adaptation is intrinsically difficult to attain due to the dynamic earth system and lack of a comprehensive understanding of future climate and its associated uncertainties. Mostly in developing countries, climate adaptation is hampered by scarcity of good quality and adequate hydro-meteorological data. This article provides a synopsis of the modelling chain applied to investigate the response of the hydrologic system under changing climate, which includes choosing the appropriate global climate models, downscaling techniques, emission scenarios, and the approach to be used in hydrologic modelling. The conventional criteria for choosing a suitable hydrological model are discussed. The advancement of emission scenarios including the latest Shared Socioeconomic Pathways and their role in climate modelling, impact assessment, and adaptation, are also highlighted. This paper also discusses the uncertainties associated with modelling the hydrological impacts of climate change and the plausible approaches for reducing such uncertainties. Among the outcomes of this review include highlights of studies on the commonly used hydrological models for assessing the impact of climate change particularly in the sub-Saharan Africa region and some specific reviews in southern Africa. Further, the reviews show that as human systems keep on dominating within the earth system in several ways, effective modelling should involve coupling earth and human systems models as these may truly represent the bidirectional feedback experienced in the modern world. The paper concludes that adequate hydro-meteorological data is key to having a robust model and effective climate adaptation measures, hence in poorly gauged basins use of artificial neural networks and satellite datasets have shown to be successful tools, including for model calibration and validation.
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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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Cecílio, Roberto Avelino, Wesley Augusto Campanharo, Sidney Sara Zanetti, Amanda Tan Lehr, and Alessandra Cunha Lopes. "Hydrological modelling of tropical watersheds under low data availability." Research, Society and Development 9, no. 5 (March 30, 2020): e100953262. http://dx.doi.org/10.33448/rsd-v9i5.3262.
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Hydrologic simulation is an important tool for the planning and management of water resources. However, the lack of input data, particularly soil and climate data, frequently complicates the application of hydrological models in Brazilian Atlantic Rainforest basins. The purpose of this study was to analyse the application of the VIC model, under the condition of low data availability, to predict the daily streamflow of two basins (Jucu and Santa Maria da Vitória). The results showed satisfactory statistical indexes only for the Santa Maria da Vitória basin. Due to data limitations and the simplified forms used to estimate these missing data, the model proved promising for understanding the hydrologic regime of these basins.
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Javadinejad, Safieh. "A review on homogeneity across hydrological regions." Resources Environment and Information Engineering 3, no. 1 (2021): 124–37. http://dx.doi.org/10.25082/reie.2021.01.004.
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Hydrologic classification is the method of scientifically arranging streams, rivers or catchments into groups with the most similarity of flow regime features and use it to recognize hydrologically homogenous areas. Previous homogeneous attempts were depended on overabundance of hydrologic metrics that considers features of variability of flows that are supposed to be meaningful in modelling physical progressions in the basins. This research explains the techniques of hydrological homogeneity through comparing past and existing methods; in addition it provides a practical framework for hydrological homogeneity that illustrates serious elements of the classification process.
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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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Krause, P., D. P. Boyle, and F. Bäse. "Comparison of different efficiency criteria for hydrological model assessment." Advances in Geosciences 5 (December 16, 2005): 89–97. http://dx.doi.org/10.5194/adgeo-5-89-2005.
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Abstract. The evaluation of hydrologic model behaviour and performance is commonly made and reported through comparisons of simulated and observed variables. Frequently, comparisons are made between simulated and measured streamflow at the catchment outlet. In distributed hydrological modelling approaches, additional comparisons of simulated and observed measurements for multi-response validation may be integrated into the evaluation procedure to assess overall modelling performance. In both approaches, single and multi-response, efficiency criteria are commonly used by hydrologists to provide an objective assessment of the "closeness" of the simulated behaviour to the observed measurements. While there are a few efficiency criteria such as the Nash-Sutcliffe efficiency, coefficient of determination, and index of agreement that are frequently used in hydrologic modeling studies and reported in the literature, there are a large number of other efficiency criteria to choose from. The selection and use of specific efficiency criteria and the interpretation of the results can be a challenge for even the most experienced hydrologist since each criterion may place different emphasis on different types of simulated and observed behaviours. In this paper, the utility of several efficiency criteria is investigated in three examples using a simple observed streamflow hydrograph.
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Pietroniro, A., V. Fortin, N. Kouwen, C. Neal, R. Turcotte, B. Davison, D. Verseghy, et al. "Using the MESH modelling system for hydrological ensemble forecasting of the Laurentian Great Lakes at the regional scale." Hydrology and Earth System Sciences Discussions 3, no. 4 (August 29, 2006): 2473–521. http://dx.doi.org/10.5194/hessd-3-2473-2006.
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Abstract. Environment Canada has been developing a community environmental modelling system (Modélisation Environmentale Communautaire – MEC), which is designed to facilitate coupling between models focusing on different components of the earth system. The ultimate objective of MEC is to use the coupled models to produce operational forecasts. MESH (MEC – Surface and Hydrology), a configuration of MEC currently under development, is specialized for coupled land-surface and hydrological models. To determine the specific requirements for MESH, its different components were implemented on the Laurentian Great Lakes watershed, situated on the Canada–U.S. border. This experiment showed that MESH can help us better understand the behaviour of different land-surface models, test different schemes for producing ensemble streamflow forecasts, and provide a means of sharing the data, the models and the results with collaborators and end-users. This modelling framework is at the heart of a testbed proposal for the Hydrologic Ensemble Prediction Experiment (HEPEX) which should allow us to make use of the North American Ensemble Forecasting System (NAEFS) to improve streamflow forecasts of the Great Lakes tributaries, and demonstrate how MESH can contribute to a Community Hydrologic Prediction System (CHPS).
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Pietroniro, A., V. Fortin, N. Kouwen, C. Neal, R. Turcotte, B. Davison, D. Verseghy, et al. "Development of the MESH modelling system for hydrological ensemble forecasting of the Laurentian Great Lakes at the regional scale." Hydrology and Earth System Sciences 11, no. 4 (May 3, 2007): 1279–94. http://dx.doi.org/10.5194/hess-11-1279-2007.
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Abstract. Environment Canada has been developing a community environmental modelling system (Modélisation Environmentale Communautaire – MEC), which is designed to facilitate coupling between models focusing on different components of the earth system. The ultimate objective of MEC is to use the coupled models to produce operational forecasts. MESH (MEC – Surface and Hydrology), a configuration of MEC currently under development, is specialized for coupled land-surface and hydrological models. To determine the specific requirements for MESH, its different components were implemented on the Laurentian Great Lakes watershed, situated on the Canada-US border. This experiment showed that MESH can help us better understand the behaviour of different land-surface models, test different schemes for producing ensemble streamflow forecasts, and provide a means of sharing the data, the models and the results with collaborators and end-users. This modelling framework is at the heart of a testbed proposal for the Hydrologic Ensemble Prediction Experiment (HEPEX) which should allow us to make use of the North American Ensemble Forecasting System (NAEFS) to improve streamflow forecasts of the Great Lakes tributaries, and demonstrate how MESH can contribute to a Community Hydrologic Prediction System (CHPS).
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Prepas, Ellie E., Gordon Putz, Daniel W. Smith, Janice M. Burke, and J. Douglas MacDonald. "The FORWARD Project: Objectives, framework and initial integration into a Detailed Forest Management Plan in Alberta." Forestry Chronicle 84, no. 3 (June 1, 2008): 330–37. http://dx.doi.org/10.5558/tfc84330-3.
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The Forest Watershed and Riparian Disturbance (FORWARD) project input into the Millar Western Forest Products Ltd. Detailed Forest Management Plan consists of three main components: 1) watershed and stream layer maps and associated datasets; 2) soil and wetland layer maps and associated datasets; and 3) a lookup table that permits planners to determine runoff coefficients (the variable selected for hydrological modelling) for functional first order watersheds, based upon various site factors and time since disturbance. The watershed and stream layer component includes a hydrological network, a Digital Elevation Model, and Strahler classified streams and watersheds for functional first and third order watersheds in the entire Millar Western Forest Management Agreement area. Relatively coarse mineral soils (which drain quickly) and wetlands (which retain water) were the key features that needed to be identified for the FORWARD modelling effort; therefore, the soil and wetland layers represent a combined soil texture and wetland coverage. The runoff coefficient lookup table integrates predictions of hydrologic impacts of harvest into planning. Key words: forest management, watershed, hydrology, stream, soils, wetlands, modelling
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Høybye, Jan A. "Uncertainty Analysis in Water Quality Modelling." Hydrology Research 27, no. 3 (June 1, 1996): 203–14. http://dx.doi.org/10.2166/nh.1996.0005.
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An important part of regional planning of water resources and quality is efficient design of monitoring systems and proper use of hydrologic models (Beven 1993). In the design of monitoring systems as well as validation of numerical models, based on, for example, the equation of continuity such as hydrologic routing models and mass balance nutrient models, it is essential to estimate the uncertainties of the model-predictions. This paper presents an implementation of a first-order analysis for estimating the error-propagation when introducing mass balance models as to predict nutrient-concentrations. The uncertainty assessment, developed from a first order theory, is implemented in the analysis and modelling of Hjarbaek fjord in Denmark. The project includes hydrological modelling of input of water and nutrients to the fjord from tributaries, and a hydrodynamic estimation of water levels and velocities in the fjord. A two-system water quality box-model is used for estimation of concentrations in water and sediment phases. The system uncertainties are analysed, starting with input data uncertainties and the error propagation to the final concentration estimates, in order to optimise the future monitoring programme, and to control the model results.
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Chang, Fi-John, and Shenglian Guo. "Advances in Hydrologic Forecasts and Water Resources Management." Water 12, no. 6 (June 24, 2020): 1819. http://dx.doi.org/10.3390/w12061819.
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The impacts of climate change on water resources management as well as the increasing severe natural disasters over the last decades have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resources management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modelling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has the great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modelling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; and (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue can not only advance water sciences but can also support policy makers toward more sustainable and effective water resources management.
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Domingo, N. D. Sto, A. Refsgaard, O. Mark, and B. Paludan. "Flood analysis in mixed-urban areas reflecting interactions with the complete water cycle through coupled hydrologic-hydraulic modelling." Water Science and Technology 62, no. 6 (September 1, 2010): 1386–92. http://dx.doi.org/10.2166/wst.2010.365.
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The potential devastating effects of urban flooding have given high importance to thorough understanding and management of water movement within catchments, and computer modelling tools have found widespread use for this purpose. The state-of-the-art in urban flood modelling is the use of a coupled 1D pipe and 2D overland flow model to simultaneously represent pipe and surface flows. This method has been found to be accurate for highly paved areas, but inappropriate when land hydrology is important. The objectives of this study are to introduce a new urban flood modelling procedure that is able to reflect system interactions with hydrology, verify that the new procedure operates well, and underline the importance of considering the complete water cycle in urban flood analysis. A physically-based and distributed hydrological model was linked to a drainage network model for urban flood analysis, and the essential components and concepts used were described in this study. The procedure was then applied to a catchment previously modelled with the traditional 1D-2D procedure to determine if the new method performs similarly well. Then, results from applying the new method in a mixed-urban area were analyzed to determine how important hydrologic contributions are to flooding in the area.
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Kunstmann, H., J. Krause, and S. Mayr. "Inverse distributed hydrological modelling of alpine catchments." Hydrology and Earth System Sciences Discussions 2, no. 6 (December 1, 2005): 2581–623. http://dx.doi.org/10.5194/hessd-2-2581-2005.
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Abstract. Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2) in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. A detailed covariance analysis was performed allowing to derive confidence bounds for all estimated parameters. The correlation between the estimated parameters was in most cases negligible, showing that parameters were estimated independently from each other.
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Yusop, Z., C. H. Chan, and A. Katimon. "Runoff characteristics and application of HEC-HMS for modelling stormflow hydrograph in an oil palm catchment." Water Science and Technology 56, no. 8 (October 1, 2007): 41–48. http://dx.doi.org/10.2166/wst.2007.690.
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Rainfall-runoff processes in a small oil palm catchment (8.2 ha) in Johor, Malaysia were examined. Storm hydrographs show rapid responses to rainfall with a short time to peak. The estimated initial hydrologic loss for the oil palm catchment is 5 mm. Despite the low initial loss, the catchment exhibits a high proportion of baseflow, approximately 54% of the total runoff. On an event basis, the stormflow response factor and runoff coefficient ranges from 0.003 to 0.21, and 0.02 to 0.44, respectively. Peakflow and stormflow volume were moderately correlated with rainfall. The hydrographs were satisfactorily modelled using the Hydrologic Engineering Centre–Hydrologic Modelling System (HEC-HMS). The efficiency indexes of the calibration and validation exercises are 0.81 and 0.82, respectively. Based on these preliminary findings, it could be suggested that an oil palm plantation would be able to serve reasonably well in regulating basic hydrological functions.
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Höge, Marvin, Andreas Scheidegger, Marco Baity-Jesi, Carlo Albert, and Fabrizio Fenicia. "Improving hydrologic models for predictions and process understanding using neural ODEs." Hydrology and Earth System Sciences 26, no. 19 (October 11, 2022): 5085–102. http://dx.doi.org/10.5194/hess-26-5085-2022.
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Abstract. Deep learning methods have frequently outperformed conceptual hydrologic models in rainfall-runoff modelling. Attempts of investigating such deep learning models internally are being made, but the traceability of model states and processes and their interrelations to model input and output is not yet fully understood. Direct interpretability of mechanistic processes has always been considered an asset of conceptual models that helps to gain system understanding aside of predictability. We introduce hydrologic neural ordinary differential equation (ODE) models that perform as well as state-of-the-art deep learning methods in stream flow prediction while maintaining the ease of interpretability of conceptual hydrologic models. In neural ODEs, internal processes that are represented in differential equations, are substituted by neural networks. Therefore, neural ODE models enable the fusion of deep learning with mechanistic modelling. We demonstrate the basin-specific predictive performance for 569 catchments of the continental United States. For exemplary basins, we analyse the dynamics of states and processes learned by the model-internal neural networks. Finally, we discuss the potential of neural ODE models in hydrology.
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Chiew, F. H. S., H. Zheng, and J. Vaze. "Implication of calibration period on modelling climate change impact on future runoff." Proceedings of the International Association of Hydrological Sciences 371 (June 12, 2015): 3–6. http://dx.doi.org/10.5194/piahs-371-3-2015.
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Abstract. This paper explores the consideration and implication of calibration period on the modelled climate change impact on future runoff. The results show that modelled runoff and hydrologic responses can be influenced by the choice of historical data period used to calibrate and develop the hydrological model. Modelling approaches that do not take this into account may therefore underestimate the range and uncertainty in future runoff projections. Nevertheless, the uncertainty associated with the choice of hydrological models and consideration of calibration dataset for modelling climate change impact on runoff is likely to be small compared to the uncertainty in the future rainfall projections.
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St-Hilaire, André. "Floods in a changing climate: hydrologic modelling." Canadian Water Resources Journal / Revue canadienne des ressources hydriques 39, no. 3 (July 3, 2014): 372–73. http://dx.doi.org/10.1080/07011784.2014.942108.
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Newham, LachlanT H., and David A. Post. "Preface to: The modelling of hydrologic systems." Environmental Modelling & Software 18, no. 8-9 (October 2003): 681. http://dx.doi.org/10.1016/s1364-8152(03)00069-0.
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Lin, Gwo-Fong, and Fong-Chung Lee. "Assessment of aggregated hydrologic time series modelling." Journal of Hydrology 156, no. 1-4 (April 1994): 447–58. http://dx.doi.org/10.1016/0022-1694(94)90089-2.
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Mendes, Juliana, and Rodrigo Maia. "Hydrologic Modelling Calibration for Operational Flood Forecasting." Water Resources Management 30, no. 15 (September 28, 2016): 5671–85. http://dx.doi.org/10.1007/s11269-016-1509-1.
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Kunstmann, H., J. Krause, and S. Mayr. "Inverse distributed hydrological modelling of Alpine catchments." Hydrology and Earth System Sciences 10, no. 3 (June 7, 2006): 395–412. http://dx.doi.org/10.5194/hess-10-395-2006.
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Abstract. Even in physically based distributed hydrological models, various remaining parameters must be estimated for each sub-catchment. This can involve tremendous effort, especially when the number of sub-catchments is large and the applied hydrological model is computationally expensive. Automatic parameter estimation tools can significantly facilitate the calibration process. Hence, we combined the nonlinear parameter estimation tool PEST with the distributed hydrological model WaSiM. PEST is based on the Gauss-Marquardt-Levenberg method, a gradient-based nonlinear parameter estimation algorithm. WaSiM is a fully distributed hydrological model using physically based algorithms for most of the process descriptions. WaSiM was applied to the alpine/prealpine Ammer River catchment (southern Germany, 710 km2 in a 100×100 m2 horizontal resolution. The catchment is heterogeneous in terms of geology, pedology and land use and shows a complex orography (the difference of elevation is around 1600 m). Using the developed PEST-WaSiM interface, the hydrological model was calibrated by comparing simulated and observed runoff at eight gauges for the hydrologic year 1997 and validated for the hydrologic year 1993. For each sub-catchment four parameters had to be calibrated: the recession constants of direct runoff and interflow, the drainage density, and the hydraulic conductivity of the uppermost aquifer. Additionally, five snowmelt specific parameters were adjusted for the entire catchment. Altogether, 37 parameters had to be calibrated. Additional a priori information (e.g. from flood hydrograph analysis) narrowed the parameter space of the solutions and improved the non-uniqueness of the fitted values. A reasonable quality of fit was achieved. Discrepancies between modelled and observed runoff were also due to the small number of meteorological stations and corresponding interpolation artefacts in the orographically complex terrain. Application of a 2-dimensional numerical groundwater model partly yielded a slight decrease of overall model performance when compared to a simple conceptual groundwater approach. Increased model complexity therefore did not yield in general increased model performance. A detailed covariance analysis was performed allowing to derive confidence bounds for all estimated parameters. The correlation between the estimated parameters was in most cases negligible, showing that parameters were estimated independently from each other.
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Schröder, B. "Pattern, process, and function in landscape ecology and catchment hydrology – how can quantitative landscape ecology support predictions in ungauged basins (PUB)?" Hydrology and Earth System Sciences Discussions 3, no. 3 (June 29, 2006): 1185–214. http://dx.doi.org/10.5194/hessd-3-1185-2006.
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Abstract. The understanding of landscape controls on the natural variability of hydrologic processes is an important research question of the PUB (Predictions in Ungauged Basins) initiative. Quantitative landscape ecology, which aims at understanding the relationships of patterns and processes in dynamic heterogeneous landscapes, may greatly contribute to this research effort by assisting the coupling of ecological and hydrological models. The present paper reviews the currently emerging rapprochement between ecological and hydrological research. It points out some common concepts and future research needs in both areas in terms of pattern, process and function analysis and modelling. Focusing on riverine landscapes, the interrelation between ecological and hydrological processes are illustrated. Two further complementary examples show how both disciplines can provide valuable information for each other. I close with some visions about promising (landscape) ecological concepts that may help advancing one of the most challenging tasks in catchment hydrology: Predictions in ungauged basins.
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Bhattacharya, Biswa, Maurizio Mazzoleni, and Reyne Ugay. "Flood Inundation Mapping of the Sparsely Gauged Large-Scale Brahmaputra Basin Using Remote Sensing Products." Remote Sensing 11, no. 5 (March 1, 2019): 501. http://dx.doi.org/10.3390/rs11050501.
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Sustainable water management is one of the important priorities set out in the Sustainable Development Goals (SDGs) of the United Nations, which calls for efficient use of natural resources. Efficient water management nowadays depends a lot upon simulation models. However, the availability of limited hydro-meteorological data together with limited data sharing practices prohibits simulation modelling and consequently efficient flood risk management of sparsely gauged basins. Advances in remote sensing has significantly contributed to carrying out hydrological studies in ungauged or sparsely gauged basins. In particular, the global datasets of remote sensing observations (e.g., rainfall, evaporation, temperature, land use, terrain, etc.) allow to develop hydrological and hydraulic models of sparsely gauged catchments. In this research, we have considered large scale hydrological and hydraulic modelling, using freely available global datasets, of the sparsely gauged trans-boundary Brahmaputra basin, which has an enormous potential in terms of agriculture, hydropower, water supplies and other utilities. A semi-distributed conceptual hydrological model was developed using HEC-HMS (Hydrologic Modelling System from Hydrologic Engineering Centre). Rainfall estimates from Tropical Rainfall Measuring Mission (TRMM) was compared with limited gauge data and used in the simulation. The Nash Sutcliffe coefficient of the model with the uncorrected rainfall data in calibration and validation were 0.75 and 0.61 respectively whereas the similar values with the corrected rainfall data were 0.81 and 0.74. The output of the hydrological model was used as a boundary condition and lateral inflow to the hydraulic model. Modelling results obtained using uncorrected and corrected remotely sensed products of rainfall were compared with the discharge values at the basin outlet (Bahadurabad) and with altimetry data from Jason-2 satellite. The simulated flood inundation maps of the lower part of the Brahmaputra basin showed reasonably good match in terms of the probability of detection, success ratio and critical success index. Overall, this study demonstrated that reliable and robust results can be obtained in both hydrological and hydraulic modelling using remote sensing data as the only input to large scale and sparsely gauged basins.
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Laganier, O., P. A. Ayral, D. Salze, and S. Sauvagnargues. "A coupling of hydrologic and hydraulic models appropriate for the fast floods of the Gardon River basin (France)." Natural Hazards and Earth System Sciences 14, no. 11 (November 5, 2014): 2899–920. http://dx.doi.org/10.5194/nhess-14-2899-2014.
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Abstract. Mediterranean catchments are regularly affected by fast and flash floods. Numerous hydrologic models have been developed, and allow modelling of these floods. However, these approaches often concern average-size basins of a few hundred km2. At larger scales (>1000 km2), coupling of hydrologic and hydraulic models appears to be an adapted solution. This study has as its first objective the evaluation of the performances of a coupling of models for flood hydrograph modelling. Secondly, the coupling results are compared with those of other modelling options. The aim of these comparisons is to clear up the following points. (1) Is a simplified routing model (lag and route) as efficient as a full hydraulic model for the modelling of hydrographs, in the intermediary downstream part of the stream? (2) Is adding lateral inflows necessary for all studied events? (3) What is the impact of the qualities of upstream hydrologic modelling feeding the coupling? The coupling combines the SCS–LR (Soil Conservation Service–lag-and-route) hydrologic model of the ATHYS platform and the MASCARET 1-D hydraulic model based on full Saint-Venant equations. It is applied to the Gardon River basin (2040 km2) in the south of France. For the seven studied events, the results of the coupling are satisfactory, the calculated Nash indexes varying between 0.61 and 0.97. The comparisons with the other modelling options show the important role of the spatial distribution of rains during events: when rains are centered on the intermediary downstream part of the catchment, adding lateral inflows is necessary; when rains are more important in the upstream part, the quality of the hydrologic modelling upstream of the coupling has a strong impact. Furthermore, the used coupling of models seems well adapted for water rising and flooded area forecasting. The future developments of the tool will concentrate on this point.
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Silvestro, F., S. Gabellani, F. Delogu, R. Rudari, and G. Boni. "Exploiting remote sensing land surface temperature in distributed hydrological modelling: the example of the Continuum model." Hydrology and Earth System Sciences 17, no. 1 (January 11, 2013): 39–62. http://dx.doi.org/10.5194/hess-17-39-2013.
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Abstract. Full process description and distributed hydrological models are very useful tools in hydrology as they can be applied in different contexts and for a wide range of aims such as flood and drought forecasting, water management, and prediction of impact on the hydrologic cycle due to natural and human-induced changes. Since they must mimic a variety of physical processes, they can be very complex and with a high degree of parameterization. This complexity can be increased by necessity of augmenting the number of observable state variables in order to improve model validation or to allow data assimilation. In this work a model, aiming at balancing the need to reproduce the physical processes with the practical goal of avoiding over-parameterization, is presented. The model is designed to be implemented in different contexts with a special focus on data-scarce environments, e.g. with no streamflow data. All the main hydrological phenomena are modelled in a distributed way. Mass and energy balance are solved explicitly. Land surface temperature (LST), which is particularly suited to being extensively observed and assimilated, is an explicit state variable. A performance evaluation, based on both traditional and satellite derived data, is presented with a specific reference to the application in an Italian catchment. The model has been firstly calibrated and validated following a standard approach based on streamflow data. The capability of the model in reproducing both the streamflow measurements and the land surface temperature from satellites has been investigated. The model has been then calibrated using satellite data and geomorphologic characteristics of the basin in order to test its application on a basin where standard hydrologic observations (e.g. streamflow data) are not available. The results have been compared with those obtained by the standard calibration strategy based on streamflow data.
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Essenfelder, A. H., and C. Giupponi. "A coupled hydrologic-machine learning modelling framework to support hydrologic modelling in river basins under Interbasin Water Transfer regimes." Environmental Modelling & Software 131 (September 2020): 104779. http://dx.doi.org/10.1016/j.envsoft.2020.104779.
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Schröder, B. "Pattern, process, and function in landscape ecology and catchment hydrology – how can quantitative landscape ecology support predictions in ungauged basins?" Hydrology and Earth System Sciences 10, no. 6 (December 19, 2006): 967–79. http://dx.doi.org/10.5194/hess-10-967-2006.
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Abstract. The understanding of landscape controls on the natural variability of hydrologic processes is an important research question of the PUB (Predictions in Ungauged Basins) initiative. Quantitative landscape ecology, which aims at understanding the relationships of patterns and processes in dynamic heterogeneous landscapes, may greatly contribute to this research effort by assisting the coupling of ecological and hydrological models. The present paper reviews the currently emerging rapprochement between ecological and hydrological research. It points out some common concepts and future research needs in both areas in terms of pattern, process and function analysis and modelling. Focusing on riverine as well as semi-arid landscapes, the interrelations between ecological and hydrological processes are illustrated. Three complementary examples show how both disciplines can provide valuable information for each other. I close with some visions about promising (landscape) ecological concepts that may help advancing one of the most challenging tasks in catchment hydrology: Predictions in ungauged basins.
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Ricard, Simon, Philippe Lucas-Picher, Antoine Thiboult, and François Anctil. "Producing reliable hydrologic scenarios from raw climate model outputs without resorting to meteorological observations." Hydrology and Earth System Sciences 27, no. 12 (June 30, 2023): 2375–95. http://dx.doi.org/10.5194/hess-27-2375-2023.
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Abstract. A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations. This alternative approach is designed by combining asynchronous hydroclimatic modelling and quantile perturbation applied to streamflow observations. Calibration is run by forcing hydrologic models with raw climate model outputs using an objective function that excludes the day-to-day temporal correlation between simulated and observed hydrographs. The resulting hydrologic scenarios provide useful and reliable information considering that they (1) preserve trends and physical consistency between simulated climate variables, (2) are implemented from a modelling cascade despite observation scarcity, and (3) support the participation of end-users in producing and interpreting climate change impacts on water resources. The proposed modelling workflow is implemented over four sub-catchments of the Chaudière River, Canada, using nine North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) simulations and a pool of lumped conceptual hydrologic models. Results confirm that the proposed workflow produces equivalent projections of the seasonal mean flows in comparison to a conventional hydroclimatic modelling approach. They also highlight the sensibility of the proposed workflow to strong biases affecting raw climate model outputs, frequently causing outlying projections of the hydrologic regime. Inappropriate forcing climate simulations were however successfully identified (and excluded) using the performance of the simulated hydrologic response as a ranking criterion. Results finally suggest that further works should be conducted to confirm the reliability of the proposed workflow to assess the impact of climate change on high- and low-flow events.
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Caja, CC, NL Ibunes, JA Paril, AR Reyes, JP Nazareno, CE Monjardin, and FA Uy. "Effects of Land Cover Changes to the Quantity of Water Supply and Hydrologic Cycle using Water Balance Models." MATEC Web of Conferences 150 (2018): 06004. http://dx.doi.org/10.1051/matecconf/201815006004.
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The hydrologic cycle is a recurring consequence of different forms of movement of water and changes of its physical state on a given area of the earth. The land cover of a certain area is a significant factor affecting the watershed hydrology. This also affects the quantity of water supply within the watershed. This study assessed the impacts of the changing land cover of the Ipo watershed, a part of the Angat-Ipo-La Mesa water system which is the main source of Metro Manila’s water supply. The environmental impacts were assessed using the interaction of vegetation cover changes and the output flow rates in Ipo watershed. Using hydrologic modelling system, the hydrological balance using rainfall, vegetation and terrain data of the watershed was simulated. Over the years, there has been a decreasing land cover within the watershed caused mostly by deforestation and other human activities. This significant change in the land cover resulted to extreme increase in water discharge at all streams and rivers in the watershed and the water balance of the area were affected as saturation and shape of the land terrain changes.
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Burlando, Paolo, Francesca Pellicciotti, and Ulrich Strasser. "Modelling Mountainous Water Systems Between Learning and Speculating Looking for Challenges." Hydrology Research 33, no. 1 (February 1, 2002): 47–74. http://dx.doi.org/10.2166/nh.2002.0004.
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For many years considerable efforts have been put into investigating and modelling hydrological processes of mountainous catchments. On the one hand, the complexity and intrinsically high variability of the involved processes as well as insufficient knowledge of the underlying physical mechanisms still induce large uncertainties in understanding observed phenomena and predicting the behaviour of the system. On the other hand, the demand for models that are able to simulate mountainous water resource systems is increasing because of the needs related to both water exploitation and water conservation, which clearly call for an integrated vision and modelling of these systems. Accordingly, this paper moves from a brief survey of the most significant achievements in mountain hydrology to discuss what could be future challenging issues related to the broader spectrum of questions, which hydrologic modelling of mountainous river systems may face in the next decades. Firstly, reference is made to existing methodologies for modelling alpine water systems, focussing on some specific aspects that provide a basis for the discussion of the weaknesses and perspectives of present simulation tools. The future is thus discussed, delineating some of the research challenges that may foster a comprehensive and integrated vision of water related issues in mountainous regions.
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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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Rajmane, Dr Dattatray K., Mr Shubham D. Ghungarde, Mr Satyam B. Daule, Mr Devidas G. Darandale, and Mr Dnyaneshwar D. Kashid. "Simulation of Rainfall Run off Process using HEC-HMS: A Case Study of Upper Godavari Basin (M.S., India)." International Journal for Research in Applied Science and Engineering Technology 11, no. 7 (July 31, 2023): 1437–48. http://dx.doi.org/10.22214/ijraset.2023.54899.
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Abstract: Runoff plays an important role in the hydrological cycle by returning excess precipitation to the oceans and controlling how much water flows into stream systems. “Modelling runoff can help to understand, control, and monitor the quality and quantity of water resources.” (Jan Sitterson et. al.) Therefore, the present work entitled “Simulation of Rainfall Runoff process using HEC-HMS; A Case study of Upper Godavari Basin (M.S., India)”is undertaken for the present research work. The latest version Q-GIS 3.18 is used for numerous purposes such as Maps preparation, Implementation of Theisen polygon method and Delineation of watershed, sub-watersheds and inclusive streams while HEC-HMS 4.7.1 is used to simulate the complete hydrologic processes of the present dendritic watershed system. Estimation of all input parameters with their appropriate methods are discussed in detail in this study and Runoff is simulated at outlet of each sub-basin. The Model efficiency is assessed with the help of Coefficient of Inter Correlation, it gives values as 0.793 and 0.562 for year 2000 and 2010. It is concluded that the model shows High level of Coefficient of Inter Correlation. On the line of present study, it is concluded that, “The Hydrologic Engineering Centres Hydrologic Modelling System (HEC-HMS) watershed model can be effectively used to simulate Rainfall Runoff process to estimate basin’s hydrological phenomenon caused due to precipitation.” “The increase in Urbanization & change in Landuse pattern in the Upper Godavari basin have definitely increased the peak runoff significantly especially in Kham sub-basin.”
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Liu, Shaofeng, Yaping Shao, Chuanguo Yang, Zhaohui Lin, and Min Li. "Improved regional hydrologic modelling by assimilation of streamflow data into a regional hydrologic model." Environmental Modelling & Software 31 (May 2012): 141–49. http://dx.doi.org/10.1016/j.envsoft.2011.12.005.
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Habtezion, Noah, Mohsen Tahmasebi Nasab, and Xuefeng Chu. "How does DEM resolution affect microtopographic characteristics, hydrologic connectivity, and modelling of hydrologic processes?" Hydrological Processes 30, no. 25 (August 22, 2016): 4870–92. http://dx.doi.org/10.1002/hyp.10967.
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Shu, Yanfeng, Kerry Taylor, Prasantha Hapuarachchi, and Chris Peters. "Modelling provenance in hydrologic science: a case study on streamflow forecasting." Journal of Hydroinformatics 14, no. 4 (June 13, 2012): 944–59. http://dx.doi.org/10.2166/hydro.2012.134.
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The web, and more recently the concept and technology of the Semantic Web, has created a wealth of new ideas and innovative tools for data management, integration and computation in an open framework and at a very large scale. One area of particular interest to the science of hydrology is the capture, representation, inference and presentation of provenance information: information that helps to explain how data were computed and how they should be interpreted. This paper is among the first to bring recent developments in the management of provenance developed for e-science and the Semantic Web to the problems of hydrology. Our main result is a formal ontological model for the representation of provenance information driven by a hydrologic case study. Along the way, we support usability, extensibility and reusability for provenance representation, relying on the concept of modelling both domain-independent and domain-specific aspects of provenance. We evaluate our model with respect to its ability to satisfy identified requirements arising from the case study on streamflow forecasting for the South Esk River catchment in Tasmania, Australia.
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Laganier, O., P. A. Ayral, D. Salze, and S. Sauvagnargues. "A coupling of hydrologic and hydraulic models appropriate for the fast floods of the Gardon river basin (France): results and comparisons with others modelling options." Natural Hazards and Earth System Sciences Discussions 1, no. 5 (September 6, 2013): 4635–80. http://dx.doi.org/10.5194/nhessd-1-4635-2013.
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Abstract. Mediterranean catchments are regularly affected by fast and flash floods. Numerous hydrologic models were developed, and allow to reconstruct these floods. However, these approaches often concern average size basins, of some hundreds km2. At more important scales (>1000 km2), a coupling of hydrologic and hydraulic models appears to be an adapted solution. This study analyses the performances of a coupling of models and compares them with those of others modelling strategies. The distributed SCS-LR hydrologic model implemented in the ATHYS modelling platform ( http://www.athys-soft.org ), and the MASCARET hydraulic modelling code, based on full Saint-Venant equations, are employed. The coupling is applied to the Gardon river basin (2040 km2), in the southeast of France. The results are satisfactory at the downstream stations. Furthermore, the coupling has few parameters, expecting interesting perspectives for flood forecasting.
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Faisal, Islam M., Robert A. Young, and James W. Warner. "Integrated Economic-Hydrologic Modelling for Groundwater Basin Management." International Journal of Water Resources Development 13, no. 1 (March 1997): 21–34. http://dx.doi.org/10.1080/07900629749908.
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Xu, Chong-yu. "From GCMs to river flow: a review of downscaling methods and hydrologic modelling approaches." Progress in Physical Geography: Earth and Environment 23, no. 2 (June 1999): 229–49. http://dx.doi.org/10.1177/030913339902300204.
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The scientific literature of the past decade contains a large number of reports detailing the development of downscaling methods and the use of hydrologic models to assess the potential effects of climate change on a variety of water resource issues. This article reviews the current state of methodologies for simulating hydrological responses to global climate change. Emphasis is given to recent advances in climatic downscaling and the problems related to the practical application of appropriate models in impact studies. Following a discussion of the advantages and deficiencies of the various approaches, challenges for the future study of the hydrological impacts of climate change are identified.
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MacDonald, Ryan J., Sarah Boon, James M. Byrne, Mike D. Robinson, and Joseph B. Rasmussen. "Potential future climate effects on mountain hydrology, stream temperature, and native salmonid life history." Canadian Journal of Fisheries and Aquatic Sciences 71, no. 2 (February 2014): 189–202. http://dx.doi.org/10.1139/cjfas-2013-0221.
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Native salmonids of western North America are subject to many environmental pressures, most notably the effects of introduced species and environmental degradation. To better understand how native salmonids on the eastern slopes of the Canadian Rocky Mountains may respond to future changes in climate, we applied a process-based approach to hydrologic and stream temperature modelling. This study demonstrates that stream thermal regimes in western Alberta, Canada, may only warm during the summer period, while colder thermal regimes during spring, fall, and winter could result from response to earlier onset of spring freshet. Model results of future climate impacts on hydrology and stream temperature are corroborated by an intercatchment comparison of stream temperature, air temperature, and hydrological conditions. Earlier fry emergence as a result of altered hydrological and thermal regimes may favour native westslope cutthroat trout (Oncorhynchus clarkii lewisii) in isolated headwater streams. Colder winter stream temperatures could result in longer incubation periods for native bull trout (Salvelinus confluentus) and limit threatened westslope cutthroat trout habitat.
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Dan-Jumbo, Nimi G., and Marc Metzger. "Relative Effect of Location Alternatives on Urban Hydrology. The Case of Greater Port-Harcourt Watershed, Niger Delta." Hydrology 6, no. 3 (September 17, 2019): 82. http://dx.doi.org/10.3390/hydrology6030082.
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Globally, cities in developing countries are urbanising at alarming rates, and a major concern to hydrologists and planners are the options that affect the hydrologic functioning of watersheds. Environmental impact assessment (EIA) has been recognised as a key sustainable development tool for mitigating the adverse impacts of planned developments, however, research has shown that planned developments can affect people and the environment significantly due to urban flooding that arises from increased paved surfaces. Flooding is a major sustainable development issue, which often result from increased paved surfaces and decreased interception losses due to urbanisation and deforestation respectively. To date, several environmental assessment studies have advanced the concept of alternatives, yet, only a small number of hydrologic studies have discussed how the location of paved surface could influence catchment runoff. Specifically, research exploring the effects of location alternative in EIAs on urban hydrology is very rare. The Greater Port-Harcourt City (GPH) development established to meet the growth needs in Port-Harcourt city (in the Niger Delta) is a compelling example. The aim of this research is to examine the relative effect of EIA alternatives in three different locations on urban hydrology. The Hydrologic Engineering Centre’s hydrologic modelling system (HEC-HMS) hydrodynamic model was used to generate data for comparing runoff in three different basins. HEC-HMS software combine models that estimate: Loss, transformation, base flow and channel routing. Results reveal that developments with the same spatial extent had different effects on the hydrology of the basins and sub-basins in the area. Findings in this study suggest that basin size rather than location of the paved surface was the main factor influencing the hydrology of the watershed.
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Palla, A., J. J. Sansalone, I. Gnecco, and L. G. Lanza. "Storm water infiltration in a monitored green roof for hydrologic restoration." Water Science and Technology 64, no. 3 (August 1, 2011): 766–73. http://dx.doi.org/10.2166/wst.2011.171.
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The objectives of this study are to provide detailed information about green roof performance in the Mediterranean climate (retained volume, peak flow reduction, runoff delay) and to identify a suitable modelling approach for describing the associated hydrologic response. Data collected during a 13-month monitoring campaign and a seasonal monitoring campaign (September–December 2008) at the green roof experimental site of the University of Genova (Italy) are presented together with results obtained in quantifying the green roof hydrologic performance. In order to examine the green roof hydrologic response, the SWMS_2D model, that solves the Richards' equation for two-dimensional saturated-unsaturated water flow, has been implemented. Modelling results confirm the suitability of the SWMS_2D model to properly describe the hydrologic response of the green roofs. The model adequately reproduces the hydrographs; furthermore, the predicted soil water content profile generally matches the observed values along a vertical profile where measurements are available.
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Olayinka, D. N., and H. E. Irivbogbe. "Estimation of Hydrological Outputs using HEC-HMS and GIS." July 2017 1, no. 2 (July 2017): 390–402. http://dx.doi.org/10.36263/nijest.2017.02.0054.
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Estimating runoff and understanding of the relationship between rainfall and runoff are of great importance in the management of flood. Several computer based hydrological models have been developed and used in simulating runoff in various watersheds in different parts of the world and in water resource studies. This study focuses on the combination of Geographic Information System (GIS) with Hydrologic Engineering Center –Hydrologic Modelling System (HEC-HMS) hydrological model to simulate runoff process of the adjoining areas of the Lagos Island and Eti-Osa Local Government Areas (LGAs). The study makes use of LIDAR Digital Elevation Model (DEM), drainage data and land use map for catchment delineation and hydrological modelling, using HECGeoHMS and ArcGIS 10.2. In HEC-HMS 4.2.1, the delineated catchment with all hydrological parameters and average daily rainfall data, are used to simulate and compute rainfall runoff volume, peak discharges for 10 months (between Jan to October) and a total of three years (2012, 2015 and 2017) were considered. Direct runoff volume and depth estimation for the years under review were determined. Results show that the peak discharge occurred on the 2nd of July 2012 at a rate of 14m3/s with an estimated runoff volume at the basin outlet of 39,669.70 x 103m3 (this date tallies with the severe flood events that occurred in that year). The study shows that estimating hydrological outputs is possible with the use of HEC-HMS and GIS. It recommends the application of such technologies in the prediction and development of basic flood warning systems for the area.
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Montanari, M., R. Hostache, P. Matgen, G. Schumann, L. Pfister, and L. Hoffmann. "Calibration and sequential updating of a coupled hydrologic-hydraulic model using remote sensing-derived water stages." Hydrology and Earth System Sciences Discussions 5, no. 6 (November 19, 2008): 3213–45. http://dx.doi.org/10.5194/hessd-5-3213-2008.
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Abstract. Two of the most relevant components of any flood forecasting system, namely the rainfall-runoff and flood inundation models, increasingly benefit from the availability of spatially distributed Earth Observation data. With the advent of microwave remote sensing instruments and their all weather capabilities, new opportunities have emerged over the past decade for improved hydrologic and hydraulic model calibration and validation. However, the usefulness of remote sensing observations in coupled hydrologic and hydraulic models still requires further investigations. Radar remote sensing observations are readily available to provide information on flood extent. Moreover, the fusion of radar imagery and high precision digital elevation models allows estimating distributed water levels. With a view to further explore the potential offered by SAR images, this paper investigates the usefulness of remote sensing-derived water stages in a modelling sequence where the outputs of hydrologic models (rainfall-runoff models) serve as boundary condition of flood inundation models. The methodology consists in coupling a simplistic 3-parameter conceptual rainfall-runoff model with a 1-D flood inundation model. Remote sensing observations of flooded areas help to identify and subsequently correct apparent volume errors in the modelling chain. The updating of the soil moisture module of the hydrological model is based on the comparison of water levels computed by the coupled hydrologic-hydraulic model with those estimated using remotely sensed flood flood extent. The potential of the proposed methodology is illustrated with data collected during a storm event of the Alzette River (Grand-Duchy of Luxembourg). The study contributes to assessing the value of remote sensing data for evaluating the saturation status of a river basin.