Journal articles on the topic 'Hydrological simulation model'
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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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Li, Zhanjie, Jingshan Yu, Xinyi Xu, Wenchao Sun, Bo Pang, and Jiajia Yue. "Multi-model ensemble hydrological simulation using a BP Neural Network for the upper Yalongjiang River Basin, China." Proceedings of the International Association of Hydrological Sciences 379 (June 5, 2018): 335–41. http://dx.doi.org/10.5194/piahs-379-335-2018.
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Abstract. Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.
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Đukić, Vesna, and Ranka Erić. "SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)." Water 13, no. 6 (March 23, 2021): 872. http://dx.doi.org/10.3390/w13060872.
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Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.
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van Kempen, Gijs, Karin van der Wiel, and Lieke Anna Melsen. "The impact of hydrological model structure on the simulation of extreme runoff events." Natural Hazards and Earth System Sciences 21, no. 3 (March 12, 2021): 961–76. http://dx.doi.org/10.5194/nhess-21-961-2021.
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Abstract. Hydrological extremes affect societies and ecosystems around the world in many ways, stressing the need to make reliable predictions using hydrological models. However, several different hydrological models can be selected to simulate extreme events. A difference in hydrological model structure results in a spread in the simulation of extreme runoff events. We investigated the impact of different model structures on the magnitude and timing of simulated extreme high- and low-flow events by combining two state-of-the-art approaches: a modular modelling framework (FUSE) and large ensemble meteorological simulations. This combination of methods created the opportunity to isolate the impact of specific hydrological process formulations at long return periods without relying on statistical models. We showed that the impact of hydrological model structure was larger for the simulation of low-flow compared to high-flow events and varied between the four evaluated climate zones. In cold and temperate climate zones, the magnitude and timing of extreme runoff events were significantly affected by different parameter sets and hydrological process formulations, such as evaporation. In the arid and tropical climate zones, the impact of hydrological model structures on extreme runoff events was smaller. This novel combination of approaches provided insights into the importance of specific hydrological process formulations in different climate zones, which can support adequate model selection for the simulation of extreme runoff events.
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Galleguillos, G., G. Méndez, and A. Lucchini. "MOSAH, An Agro-hydrological Simulation Model." IFAC Proceedings Volumes 18, no. 14 (October 1985): 21–26. http://dx.doi.org/10.1016/s1474-6670(17)60028-4.
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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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Jiang, Lulu, Huan Wu, Jing Tao, John S. Kimball, Lorenzo Alfieri, and Xiuwan Chen. "Satellite-Based Evapotranspiration in Hydrological Model Calibration." Remote Sensing 12, no. 3 (January 29, 2020): 428. http://dx.doi.org/10.3390/rs12030428.
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Hydrological models are usually calibrated against observed streamflow (Qobs), which is not applicable for ungauged river basins. A few studies have exploited remotely sensed evapotranspiration (ETRS) for model calibration but their effectiveness on streamflow simulation remains uncertain. This paper investigates the use of ETRS in the hydrological calibration of a widely used land surface model coupled with a source–sink routing scheme and global optimization algorithm for 28 natural river basins. A baseline simulation is a setup based on the latest model developments and inputs. Sensitive parameters are determined for Qobs and ETRS-based model calibrations, respectively, through comprehensive sensitivity tests. The ETRS-based model calibration results in a mean Kling–Gupta Efficiency (KGE) value of 0.54 for streamflow simulation; 61% of the river basins have KGE > 0.5 in the validation period, which is consistent with the calibration period and provides a significant improvement over the baseline. Compared to Qobs, the ETRS calibration produces better or similar streamflow simulations in 29% of the basins, while further significant improvements are achieved when either better ET or precipitation observations are used. Furthermore, the model results show better or similar performance in 68% of the basins and outperform the baseline simulations in 90% of the river basins using model parameters from the best ETRS calibration runs. This study confirms that with reasonable precipitation input, the ETRS-based spatially distributed calibration can efficiently tune parameters for better ET and streamflow simulations. The application of ETRS for global scale hydrological model calibration promises even better streamflow accuracy as the satellite-based ETRS observations continue to improve.
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Maheu, Audrey, Islem Hajji, François Anctil, Daniel F. Nadeau, and René Therrien. "Using the maximum entropy production approach to integrate energy budget modelling in a hydrological model." Hydrology and Earth System Sciences 23, no. 9 (September 20, 2019): 3843–63. http://dx.doi.org/10.5194/hess-23-3843-2019.
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Abstract. Total terrestrial evaporation, also referred to as evapotranspiration, is a key process for understanding the hydrological impacts of climate change given that warmer surface temperatures translate into an increase in the atmospheric evaporative demand. To simulate this flux, many hydrological models rely on the concept of potential evaporation (PET), although large differences have been observed in the response of PET models to climate change. The maximum entropy production (MEP) model of land surface fluxes offers an alternative approach for simulating terrestrial evaporation in a simple way while fulfilling the physical constraint of energy budget closure and providing a distinct estimation of evaporation and transpiration. The objective of this work is to use the MEP model to integrate energy budget modelling within a hydrological model. We coupled the MEP model with HydroGeoSphere (HGS), an integrated surface and subsurface hydrologic model. As a proof of concept, we performed one-dimensional soil column simulations at three sites of the AmeriFlux network. The coupled model (HGS-MEP) produced realistic simulations of soil water content (root-mean-square error – RMSE – between 0.03 and 0.05 m3 m−3; NSE – Nash–Sutcliffe efficiency – between 0.30 and 0.92) and terrestrial evaporation (RMSE between 0.31 and 0.71 mm d−1; NSE between 0.65 and 0.88) under semi-arid, Mediterranean and temperate climates. At the daily timescale, HGS-MEP outperformed the stand-alone HGS model where total terrestrial evaporation is derived from potential evaporation, which we computed using the Penman–Monteith equation, although both models had comparable performance at the half-hourly timescale. This research demonstrated the potential of the MEP model to improve the simulation of total terrestrial evaporation in hydrological models, including for hydrological projections under climate change.
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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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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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Kim, Seokhyeon, Hoori Ajami, and Ashish Sharma. "Using Remotely Sensed Information to Improve Vegetation Parameterization in a Semi-Distributed Hydrological Model (SMART) for Upland Catchments in Australia." Remote Sensing 12, no. 18 (September 18, 2020): 3051. http://dx.doi.org/10.3390/rs12183051.
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Appropriate representation of the vegetation dynamics is crucial in hydrological modelling. To improve an existing limited vegetation parameterization in a semi-distributed hydrologic model, called the Soil Moisture and Runoff simulation Toolkit (SMART), this study proposed a simple method to incorporate daily leaf area index (LAI) dynamics into the model using mean monthly LAI climatology and mean rainfall. The LAI-rainfall sensitivity is governed by a parameter that is optimized by maximizing the Pearson correlation coefficient (R) between the estimated and satellite-derived LAI time series. As a result, the LAI-rainfall sensitivity is smallest for forest, shrub, and woodland regions across Australia, and increases for grasslands and croplands. The impact of the proposed method on catchment-scale simulations of soil moisture (SM), evapotranspiration (ET) and discharge (Q) in SMART was examined across six eco-hydrologically contrasted upland catchments in Australia. Results showed that the proposed method produces almost identical results compared to simulations by the satellite-derived LAI time series. In addition, the simulation results were considerably improved in nutrient/light limited catchments compared to the cases with the default vegetation parameterization. The results showed promise, with possibilities of extension to other hydrologic models that need similar specifications for inbuilt vegetation dynamics.
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Refsgaard, Jens Christian. "Validation and Intercomparison of Different Updating Procedures for Real-Time Forecasting." Hydrology Research 28, no. 2 (April 1, 1997): 65–84. http://dx.doi.org/10.2166/nh.1997.0005.
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The paper presents a classification and a review of the updating procedures currently used in real-time flood forecasting modelling. On the basis of results from the WMO project ‘Simulated Real-Time Intercomparion of Hydrological Models’, comprising more than 10 commonly used hydrological models and a variety of different updating procedures, an analysis of the relative importance of updating procedures and hydrological simulation models is provided. In particular, an intercomparison is made beteween two models (NAMS11/MIKE11 and NAMKAL) consisting of the same hydrological model (NAM conceptual rainfall-runoff) but containing different routing modules (linear reservoirs versus hydraulic routing) and different updating procedures (error prediction versus state variable updating based on an extended Kalman filter). A main conclusion is that updating procedures significantly improve the performances of hydrological models for short-range forecasting. Furthermore, there are no clear conclusions regarding which type of updating procedure performs the better. However. intercomparison of the NAMS11 and NAMKAL models indicates that the extended Kalman filter is marginally better than an error prediction model in cases where the basic hydrological model simulation is good. Finally, it is concluded that the basic simulation is very essential for accurate forecasts, and that the better the basic simulations are the better the updating routines in general function. This puts emphasis on the importance of thoroughly calibrating and validating the hydrological simulation models before applying them together with updating routines in operational real-time forecasting.
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Wang, Jie, Jianyun Zhang, Guoqing Wang, Xiaomeng Song, Xiaoying Yang, and Yueyang Wang. "Ensemble flood simulation for the typical catchment in humid climatic zone by using multiple hydrological models." Proceedings of the International Association of Hydrological Sciences 383 (September 16, 2020): 213–22. http://dx.doi.org/10.5194/piahs-383-213-2020.
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Abstract. A good performance of hydrological model for flood simulation is of critical importance for flood forecasting. Taking Yandu River catchment, as the study area, three hydrological models (i.e. Xin'anjiang model, TOPMODEL, artificial neural network model) and a multi-model ensemble simulation method (i.e. entropy-based method) were applied to simulate the hydrological processes of 30 flood events occurring in 1981–1987. The performance of the ensemble members and multi-model ensemble simulation method was evaluated by comparing indicators of Nash-Efficiency coefficient, errors in root mean square, peak occurrence time, and relative errors of flood peak discharge, event runoff depth. Results show that the three hydrological models perform well for hydrological simulation of all 30 storm floods with Nash and Sutcliffe Efficiency coefficient of above 0.75 and relative error of less than 10 %. However, different model exhibits a difference in simulation errors of peak discharge and peak occurrence time. For example, BP model has the smallest error of 3.78 % for peak discharge simulation while that of Xin'anjiang model and TOPMODEL are 20.9 % and 24.7 % respectively. The entropy-based ensemble simulation method improved flood simulation accuracy to some extent for all evaluation criteria comparing to the three hydrological models. It is feasible to apply entropy-based ensemble approach for improving accuracy of flood forecasting in humid regions of China.
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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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Meng, Xian Meng, Bang Yang, and Xian Wu Xue. "Advancement in Research of Hydrological Processes Simulation for Karst Region and Future Challenges." Advanced Materials Research 518-523 (May 2012): 4104–10. http://dx.doi.org/10.4028/www.scientific.net/amr.518-523.4104.
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Hydrological processes simulation is an effective way for water resources evaluation and can provide scientific basis for sustainable utilization of water resources and ecological environment restoration. Compared with traditional watershed hydrological processes, hydrological processes in karst region have their unique in runoff generation and concentration stage because of the complexity and multiplicity of karst aquifer system. This paper reviews the two stages of hydrological processes simulation method in karst region: 1. systematic simulation model stage; 2. process based mechanism model stage. By analyzing the characteristics and limitation of two kinds of models, the tendency of future karst hydrological processes simulation method in two aspects are discussed: 1. quasi physically based model balancing physical senses and data richness; 2. scale adaptable model based on macro-scale applicable equations.
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Qi, W., C. Zhang, G. T. Fu, C. Sweetapple, and H. C. Zhou. "Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations." Hydrology and Earth System Sciences Discussions 12, no. 9 (September 10, 2015): 9337–91. http://dx.doi.org/10.5194/hessd-12-9337-2015.
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Abstract. The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products using different precipitation computation recipes, is comprehensively evaluated using statistical and hydrological methods in a usually-neglected area (northeastern China), and a framework quantifying uncertainty contributions of precipitation products, hydrological models and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products include TRMM3B42, TRMM3B42RT, GLDAS/Noah, APHRODITE, PERSIANN and GSMAP-MVK+. Two hydrological models of different complexities, i.e., a water and energy budget-based distributed hydrological model and a physically-based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and the cloud motion vectors used by GSMAP-MVK+ show huge advantage. These findings could be very useful for validation, refinement and future development of satellite-based products (e.g., NASA Global Precipitation Measurement). Although significant uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models contribute significantly to uncertainty in discharge simulations and a better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based product, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.
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Chen, Jiongfeng, and Wan-chang Zhang. "A new numerical model for simulating top surface soil moisture and runoff." Engineering Computations 35, no. 3 (May 8, 2018): 1344–63. http://dx.doi.org/10.1108/ec-01-2017-0031.
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PurposeThis paper aims to construct a simplified distributed hydrological model based on the surveyed watershed soil properties database.Design/methodology/approachThe new established model requires fewer parameters to be adjusted than needed by former hydrological models. However, the achieved stream-flow simulation results are similar and comparable to the classic hydrological models, such as the Xinanjiang model and the TOPMODEL.FindingsGood results show that the discharge and the top surface soil moisture can be simultaneously simulated, and that is the exclusive character of this new model. The stream-flow simulation results from two moderate hydrological watershed models show that the daily stream-flow simulation achieved the classic hydrological results shown in the TOPMODEL and Xinanjiang model. The soil moisture validation results show that the modeled watershed scale surface soil moisture has general agreement with the obtained measurements, with a root-mean-square error (RMSE) value of 0.04 (m3/m3) for one of the one-measurement sites and an averaged RMSE of 0.08 (m3/m3) over all measurements.Originality/valueIn this paper, a new simplified distributed hydrological model was constructed.
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Lestari, Isnayulia, and Bambang Dwi Dasanto. "Determination of Extreme Hydrological Index using HBV Model Simulation Results (Case Study : Upper Ciliwung Watershed)." Agromet 33, no. 1 (June 11, 2019): 20–29. http://dx.doi.org/10.29244/j.agromet.33.1.20-29.
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The study of climate change on hydrological response is a crucial as climate change impact will drive the change in hydrological regimes of river. Upper Ciliwung watershed is one of the critical rivers in Java Island, which has been affected by climate change. This study aims to: (i) simulate the discharge flow using the Hydrologiska Byrans Vattenbalansavdelning (HBV) model; (ii) simulate future flow using three general circulation models (GCM) namely Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mk.3.6.0, Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Geophysical Fluid Dynamics Laboratory-Coupled Model generation 3 (GFDL-CM3); (iii) determine the changes of extreme hydrological index during historical period (2001-2015) and projected period (2031-2045). The historical year simulation and projections are used to determine eight hydrologic extreme indices for high flow and low flow. We calibrated the HBV model for two years (2001-2002) and validated it for two years (2003-2004). Our model performed well in discharge simulation as shown by the NSE values (0.66 for calibration and validation). Then we calculated the indices for each period used (historical and projected). To show the changes in hydrological regimes, we compare the indices between two periods. Changes in the index of the two periods tend to decrease in value on the index parameters that characterize the minimum extreme events. Hence, that it is possible in the projected period there will be extreme hydrological events in the form of drought.
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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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Liu, Zhanyan, Hongbin Zhang, and Qiuhua Liang. "A coupled hydrological and hydrodynamic model for flood simulation." Hydrology Research 50, no. 2 (December 13, 2018): 589–606. http://dx.doi.org/10.2166/nh.2018.090.
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Abstract This paper presents a new flood modelling tool developed by coupling a full 2D hydrodynamic model with hydrological models. The coupled model overcomes the main limitations of the individual modelling approaches, i.e. high computational costs associated with the hydrodynamic models and less detailed representation of the underlying physical processes related to the hydrological models. When conducting a simulation using the coupled model, the computational domain (e.g. a catchment) is first divided into hydraulic and hydrological zones. In the hydrological zones that have high ground elevations and relatively homogeneous land cover or topographic features, a conceptual lumped model is applied to obtain runoff/net rainfall, which is then routed by a group of pre-acquired ‘unit hydrographs’ to the zone borders. These translated hydrographs will then be used to drive the full 2D hydrodynamic model to predict flood dynamics at high resolution in the hydraulic zones that are featured with complex topographic settings, including roads, buildings, etc. The new coupled flood model is applied to reproduce a major flood event that occurred in Morpeth, northeast England in September 2008. While producing similar results, the new coupled model is shown to be computationally much more efficient than the full hydrodynamic model.
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Ding, Zhenzhou, Haishen Lü, Naveed Ahmed, Yonghua Zhu, Qiqi Gou, Xiaoyi Wang, En Liu, Haiting Xu, Ying Pan, and Mingyue Sun. "Soil Moisture Data Assimilation in MISDc for Improved Hydrological Simulation in Upper Huai River Basin, China." Water 14, no. 21 (October 31, 2022): 3476. http://dx.doi.org/10.3390/w14213476.
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In recent years, flash floods have become increasingly serious. Improving the runoff simulation and forecasting ability of hydrological models is urgent. Therefore, data assimilation (DA) methods have become an important tool. Many studies have shown that the assimilation of remotely sensed soil moisture (SM) data could help improve the simulation and forecasting capability of hydrological models. Still, very few studies have attempted to assimilate SM data from land surface process models into hydrological models to improve model simulation and forecasting accuracy. Therefore, in this study, we used the ensemble Kalman filter (EnKF) to assimilate the China Land Data Assimilation System (CLDAS) SM product into the MISDc model. We also corrected the CLDAS SM and assimilated the corrected SM data into the hydrological model. In addition, the effects of the 5th and 95th percentiles of flow were evaluated to see how SM DA affected low and high flows, respectively. Additionally, we tried to find an appropriate size for the number of ensemble members of the EnKF for this study. The results showed that the EnKF SM DA improved the runoff simulation ability of the hydrological model, especially for the high flows of the model; however, the simulation for the low flows deteriorated. In general, SM DA positively affected the ability of the MISDc model runoff simulation.
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Flores, Neftali, Rolando Rodríguez, Santiago Yépez, Victor Osores, Pedro Rau, Diego Rivera, and Francisco Balocchi. "Comparison of Three Daily Rainfall-Runoff Hydrological Models Using Four Evapotranspiration Models in Four Small Forested Watersheds with Different Land Cover in South-Central Chile." Water 13, no. 22 (November 11, 2021): 3191. http://dx.doi.org/10.3390/w13223191.
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We used the lumped rainfall–runoff hydrologic models Génie Rural à 4, 5, 6 paramètres Journalier (GR4J, GR5J and GR6J) to evaluate the most robust model for simulating discharge on four forested small catchments (<40 ha) in south-central Chile. Different evapotranspiration methods were evaluated: Oudin, Hargreaves–Samani and Priestley–Taylor. Oudin’s model allows the achievement of the highest efficiencies in the flow simulation. The more sensitive parameters for each model were identified through a Generalized Probability Uncertainty Estimation (GLUE) model. Our results demonstrate that the three hydrological models were capable of efficiently simulating flow in the four study catchments. However, the GR6J model obtained the most satisfactory results in terms of simulated to measured streamflow closeness. In general, the three models tended to underestimate peak flow, as well as underestimate and overestimate flow events in most of the in situ observations, according to the probability of non-exceedance. We also evaluated the models’ performance in a simulation of summer discharge due to the importance of downstream water supply in the months of greatest scarcity. Again, we found that GR6J obtained the most efficient simulations.
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Jiang, Dejuan, and Kun Wang. "The Role of Satellite-Based Remote Sensing in Improving Simulated Streamflow: A Review." Water 11, no. 8 (August 4, 2019): 1615. http://dx.doi.org/10.3390/w11081615.
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A hydrological model is a useful tool to study the effects of human activities and climate change on hydrology. Accordingly, the performance of hydrological modeling is vitally significant for hydrologic predictions. In watersheds with intense human activities, there are difficulties and uncertainties in model calibration and simulation. Alternative approaches, such as machine learning techniques and coupled models, can be used for streamflow predictions. However, these models also suffer from their respective limitations, especially when data are unavailable. Satellite-based remote sensing may provide a valuable contribution for hydrological predictions due to its wide coverage and increasing tempo-spatial resolutions. In this review, we provide an overview of the role of satellite-based remote sensing in streamflow simulation. First, difficulties in hydrological modeling over highly regulated basins are further discussed. Next, the performance of satellite-based remote sensing (e.g., remotely sensed data for precipitation, evapotranspiration, soil moisture, snow properties, terrestrial water storage change, land surface temperature, river width, etc.) in improving simulated streamflow is summarized. Then, the application of data assimilation for merging satellite-based remote sensing with a hydrological model is explored. Finally, a framework, using remotely sensed observations to improve streamflow predictions in highly regulated basins, is proposed for future studies. This review can be helpful to understand the effect of applying satellite-based remote sensing on hydrological modeling.
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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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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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Huo, Jiuyuan, Yaonan Zhang, Lihui Luo, Yinping Long, Zhengfang He, and Li Liu. "Model Parameter Optimization Method Research in Heihe River Open Modeling Environment (HOME)." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 09 (February 16, 2017): 1759017. http://dx.doi.org/10.1142/s0218001417590170.
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How to make the existing models from different disciplines effectively interoperate and integrate is one of the primary challenges for scientists and decision-makers. Heihe river Open Modeling Environment (HOME) provides a convenient model coupling platform that enables researchers concentrate on the theory and applications of ecological and hydrological watershed models. The model parameter optimization is an important component and key step that links models and simulation of watershed. In this paper, through integration modules of existing models, an improved ABC algorithm (ORABC) based on optimization strategy and reservation strategy of the best individuals was introduced into HOME as a hydrological model parameter optimization module, and coupled with the Xinanjiang hydrological model to complete automatically task of model parameter optimization. The runoff simulation experiments in Heihe river watershed were taken to verify the parameter optimization in HOME, and the simulation results testified the efficiency and effectiveness of the method. It can significantly improve simulation accuracy and efficiency of hydrological and ecological models, and promote the scientific researches for watershed issues.
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Paul, Pranesh Kumar, Yongqiang Zhang, Ashok Mishra, Niranjan Panigrahy, and Rajendra Singh. "Comparative Study of Two State-of-the-Art Semi-Distributed Hydrological Models." Water 11, no. 5 (April 26, 2019): 871. http://dx.doi.org/10.3390/w11050871.
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Performance of a newly developed semi-distributed (grid-based) hydrological model (satellite-based hydrological model (SHM)) has been compared with another semi-distributed soil and water assessment tool (SWAT)—a widely used hydrological response unit (HRU)-based hydrological model at a large scale (12,900 km2) river basin for monthly streamflow simulation. The grid-based model has a grid cell size of 25 km2, and the HRU-based model was set with an average HRU area of 25.2 km2 to keep a balance between the discretization of the two models. Both the model setups are calibrated against the observed streamflow over the period 1977 to 1990 (with 1976 as the warm-up period) and validated over the period 1991 to 2004 by comparing simulated and observed hydrographs as well as using coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) as statistical indices. Result of SHM simulation (NSE: 0.92 for calibration period; NSE: 0.92 for validation period) appears to be superior in comparison to SWAT simulation (NSE: 0.72 for calibration period; NSE: 0.50 for validation period) for both calibration and validation periods. The models’ performances are also analyzed for annual peak flow, monthly flow variability, and for different flow percentiles. SHM has performed better in simulating annual peak flows and has reproduced the annual variability of observed streamflow for every month of the year. In addition, SHM estimates normal, moderately high, and high flows better than SWAT. Furthermore, total uncertainties of models’ simulation have been analyzed using quantile regression technique and eventually quantified with scatter plots between P (measured data bracketed by the 95 percent predictive uncertainty (PPU) band) and R (the relative length of the 95PPU band with respect to the model simulated values)-values, for calibration and validation periods, for both the model simulations. The analysis confirms the superiority of SHM over its counterpart. Differences in data interpolation techniques and physical processes of the models are identified as the probable reasons behind the differences among the models’ outputs.
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AghaKouchak, A., N. Nakhjiri, and E. Habib. "An educational model for ensemble streamflow simulation and uncertainty analysis." Hydrology and Earth System Sciences Discussions 9, no. 6 (June 8, 2012): 7297–315. http://dx.doi.org/10.5194/hessd-9-7297-2012.
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Abstract. This paper presents a hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this model, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The model includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for not only hydrological processes, but also for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity.
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Patil, Vaishnavi Kiran, Vidya R. Saraf, Omkesh V. Karad, Swapnil B. Ghodke, Dnyanesvar Gore, and Shweta S. Dhekale. "Simulation of Rainfall Runoff Process Using HEC-HMS Model for Upper Godavari Basin Maharashtra, India." European Journal of Engineering Research and Science 4, no. 4 (April 22, 2019): 102–7. http://dx.doi.org/10.24018/ejers.2019.4.4.927.
Full textAbstract:
The Hydrologic Engineering Centers Hydrologic Modeling System (HEC-HMS) is a popularly used watershed model to simulate rainfall- runoff process. Hydrological modeling is a commonly used tool to estimate the basin’s hydrological response due to precipitation. It allows to predict the hydrologic response to various watershed management practices and to have a better understanding of the impacts of these practices. It is evident from the extensive review of the literature that the studies on comparative assessment of watershed models for hydrologic simulations are very much limited in developing countries including India. In this study, modified SCS Curve Number method is applied to determine loss model as a major component in rainfall-runoff modeling. The study of HEC-HMS model is used to simulate rainfallrunoff process in Nashik region (Upper Godavari basin), Maharashtra. To compute runoff volume, peak runoff rate, and flow routing methods SCS curve number, SCS unit hydrograph, Exponential recession and Muskingum routing methods are chosen, respectively. The results of the present study indicate that HEC-HMS tool applied to watershed proved to be useful in achieving the various objectives. The study confirmed a significant increase in runoff as a result of urbanization. It is a powerful tool for flood forecasting Index
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Patil, Vaishnavi Kiran, Vidya R. Saraf, Omkesh V. Karad, Swapnil B. Ghodke, Dnyanesvar Gore, and Shweta S. Dhekale. "Simulation of Rainfall Runoff Process Using HEC-HMS Model for Upper Godavari Basin Maharashtra, India." European Journal of Engineering and Technology Research 4, no. 4 (April 22, 2019): 102–7. http://dx.doi.org/10.24018/ejeng.2019.4.4.927.
Full textAbstract:
The Hydrologic Engineering Centers Hydrologic Modeling System (HEC-HMS) is a popularly used watershed model to simulate rainfall- runoff process. Hydrological modeling is a commonly used tool to estimate the basin’s hydrological response due to precipitation. It allows to predict the hydrologic response to various watershed management practices and to have a better understanding of the impacts of these practices. It is evident from the extensive review of the literature that the studies on comparative assessment of watershed models for hydrologic simulations are very much limited in developing countries including India. In this study, modified SCS Curve Number method is applied to determine loss model as a major component in rainfall-runoff modeling. The study of HEC-HMS model is used to simulate rainfallrunoff process in Nashik region (Upper Godavari basin), Maharashtra. To compute runoff volume, peak runoff rate, and flow routing methods SCS curve number, SCS unit hydrograph, Exponential recession and Muskingum routing methods are chosen, respectively. The results of the present study indicate that HEC-HMS tool applied to watershed proved to be useful in achieving the various objectives. The study confirmed a significant increase in runoff as a result of urbanization. It is a powerful tool for flood forecasting Index
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Lima Neto, Otacílio Correia, Alfredo Ribeiro Neto, Fellipe Henrique Borba Alves, and José Almir Cirilo. "Sub-daily hydrological-hydrodynamic simulation in flash flood basins: Una river (Pernambuco/Brazil)." Ambiente e Agua - An Interdisciplinary Journal of Applied Science 15, no. 5 (September 3, 2020): 1. http://dx.doi.org/10.4136/ambi-agua.2556.
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Flash floods are observed in the Una River Basin, Pernambuco/Brazil. This particular type of flood is a short-duration hydrological event with occurrence of the peak flow within minutes to few hours after the onset of the rainfall, taking place typically in mountainous regions. The objective of the paper was to assess the sub-daily hydrological and hydrodynamic modeling of flood events in 2011 and 2017. Sub-daily precipitation and streamflow were applied to the models Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) and River Analysis System (HEC-RAS). Model evaluation methods such as Nash-Sutcliffe efficiency (NSE), percent bias, and the ratio of the root mean squared error to the standard deviation of measured data (RSR) were used in the calibration process. The maximum infiltration rate and the Snyder peak coefficient estimation were the most sensitive parameters in the hydrological model. The calibration of the HEC-HMS showed good performances (Catende station NSE=0.78 and RSR=0.46; Palmares station NSE=0.68 and RSR=0.57). During HEC-RAS 1D flow simulations, steep regions in the Una River caused numerical instabilities. The 2D solution was needed to overcome this problem, allowing us to represent the water level in the city of Palmares satisfactorily.
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Guan, Xiaoxiang, Jianyun Zhang, Amgad Elmahdi, Xuemei Li, Jing Liu, Yue Liu, Junliang Jin, et al. "The Capacity of the Hydrological Modeling for Water Resource Assessment under the Changing Environment in Semi-Arid River Basins in China." Water 11, no. 7 (June 27, 2019): 1328. http://dx.doi.org/10.3390/w11071328.
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Conducting water resource assessment and forecasting at a basin scale requires effective and accurate simulation of the hydrological process. However, intensive, complex human activities and environmental changes are constraining and challenging the hydrological modeling development and application by complicating the hydrological cycle within its local contexts. Six sub-catchments of the Yellow River basin, the second-largest river in China, situated in a semi-arid climate zone, have been selected for this study, considering hydrological processes under a natural period (before 1970) and under intensive human disturbance (2000–2013). The study aims to assess the capacity and performance of the hydrological models in simulating the discharge under a changing environment. Four well-documented and applied hydrological models, i.e., the Xin’anjiang (XAJ) model, GR4J model, SIMHYD model, and RCCC-WBM (Water Balance Model developed by Research Center for Climate Change) model, were selected for this assessment. The results show that (1) the annual areal temperature of all sub-catchments presented a significant rising trend, and annual precipitation exhibited insignificant decline trend; (2) as a result of climate change and intensive human activities, the annual runoff series showed a declining trend with abrupt changes mostly occurring in the 1980s with the exception of the Tangnaihai station; (3) the four hydrological models generally performed well for runoff simulation for all sub-catchments under the natural period. In terms of Nash–Sutcliffe efficiency coefficient, the XAJ model worked better in comparison to other hydrological models due to its detailed representations and complicated mechanism in runoff generation and flow-routing scheme; (4) environmental changes have impacted the performance of the four hydrological models under all sub-catchments, in particularly the Pianguan River catchment, which is could be attributed to the various human activities that in turn represent more complexity for the regional hydrological cycle to some extent, and reduce the ability to predict the runoff series; (5) the RCCC-WBM model, well known for its simple structure and principles, is considered to be acceptable for runoff simulation for both natural and human disturbance periods, and is recommended for water resource assessment under changing environments for semi-arid regions.
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Kennedy, Maureen C., Donald McKenzie, Christina Tague, and Aubrey L. Dugger. "Balancing uncertainty and complexity to incorporate fire spread in an eco-hydrological model." International Journal of Wildland Fire 26, no. 8 (2017): 706. http://dx.doi.org/10.1071/wf16169.
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Wildfire affects the ecosystem services of watersheds, and climate change will modify fire regimes and watershed dynamics. In many eco-hydrological simulations, fire is included as an exogenous force. Rarely are the bidirectional feedbacks between watersheds and fire regimes integrated in a simulation system because the eco-hydrological model predicts variables that are incompatible with the requirements of fire models. WMFire is a fire-spread model of intermediate complexity designed to be integrated with the Regional Hydro-ecological Simulation System (RHESSys). Spread in WMFire is based on four variables that (i) represent known influences on fire spread: litter load, relative moisture deficit, wind direction and topographic slope, and (ii) are derived directly from RHESSys outputs. The probability that a fire spreads from pixel to pixel depends on these variables as predicted by RHESSys. We tested a partial integration between WMFire and RHESSys on the Santa Fe (New Mexico) and the HJ Andrews (Oregon State) watersheds. Model assessment showed correspondence between expected spatial patterns of spread and seasonality in both watersheds. These results demonstrate the efficacy of an approach to link eco-hydrologic model outputs with a fire spread model. Future work will develop a fire effects module in RHESSys for a fully coupled, bidirectional model.
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Marke, T., W. Mauser, A. Pfeiffer, G. Zängl, and D. Jacob. "The effect of downscaling on river runoff modeling: a hydrological case study in the Upper Danube Watershed." Hydrology and Earth System Sciences Discussions 8, no. 3 (June 30, 2011): 6331–84. http://dx.doi.org/10.5194/hessd-8-6331-2011.
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Abstract. In the current study two regional climate models (MM5 and REMO) driven by different global boundary conditions (ERA reanalysis and the ECHAM5 model) are coupled with the uncalibrated hydrological process model PROMET in order to analyze the impact of global boundary conditions, dynamical regionalization and subsequent statistical downscaling (bilinear interpolation, correction of subgrid-scale variability and combined correction of subgrid-scale variability and bias) on river runoff simulation. The results of 12 coupled model runs set up for the catchment of the Upper Danube over the historical period 1971–2000 indicate that the correction of subgrid-scale variability compared to a bilinear interpolation allows for a more accurate simulation of discharge in case of all model configurations and all discharge criteria considered (mean monthly discharge, mean monthly low-flow discharge and mean monthly peak-flow discharge). Further improvements in the hydrological simulations could be achieved by eliminating the biases (in terms of deviations from observed meteorological conditions) inherent in the driving RCM simulations, regardless of the global boundary conditions or RCM applied. Comparing the hydrological results achievable with MM5 and REMO, the application of bias corrected MM5 simulations turned out to allow for a more accurate simulation of discharge volumes while the variance in simulated discharge was often better reflected in case of REMO forcings. The results achieved with different global boundary conditions are characterized by only minor differences. It is, however, noteworthy that all efficiency criteria in case of bias corrected MM5 simulations indicate better performance under ERA40 boundaries, whereas REMO-driven hydrological simulations better correspond to measured discharge under ECHAM5 boundaries. In spite of all downscaling and bias correction efforts described, the RCM-driven hydrological simulations remain less accurate than those achievable with spatially distributed meteorological observations.
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Stanić, Miloš, Andrijana Todorović, Željko Vasilić, and Jasna Plavšić. "Extreme flood reconstruction by using the 3DNet platform for hydrological modelling." Journal of Hydroinformatics 20, no. 4 (December 22, 2017): 766–83. http://dx.doi.org/10.2166/hydro.2017.050.
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Abstract Notwithstanding recent advances in hydrological modelling, flood simulations remain challenging since many processes must be simulated with high computational efficiency. This paper presents a novel geographic information system (GIS)-oriented platform 3DNet and the associated hydrologic model, with focus on the platform and model features that are relevant for flood simulations. The platform enables hydraulic structures to be incorporated in the hydrologic model, as well as water retention. A limiting capacity can be imposed on every river reach enabling estimation of flooding volume. Runoff is simulated within irregularly shaped units that can be aggregated providing spatial flexibility, i.e. model setup can vary from lumped to semi- and fully-distributed. The model contains many parameters with a physical connotation that can be inferred from catchment characteristics, and it enables simulations with minimum data requirements. All algorithms are implemented in C++ warranting fast computations, while the spatial flexibility can provide additional speed-up. The model is used for a reconstruction of a devastating flood in the Kolubara catchment in May 2014. Despite incomplete and uncertain observations, reasonable results across the catchment are obtained with the plausible parameter estimates. The results suggest that enclosure of the presented features in flood simulation tools would improve simulation accuracy and efficiency.
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Khu, S. T., and M. G. F. Werner. "Reduction of Monte-Carlo simulation runs for uncertainty estimation in hydrological modelling." Hydrology and Earth System Sciences 7, no. 5 (October 31, 2003): 680–92. http://dx.doi.org/10.5194/hess-7-680-2003.
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Abstract. Monte-Carlo (MC) simulation based techniques are often applied for the estimation of uncertainties in hydrological models due to uncertain parameters. One such technique is the Generalised Likelihood Uncertainty Estimation technique (GLUE). A major disadvantage of MC is the large number of runs required to establish a reliable estimate of model uncertainties. To reduce the number of runs required, a hybrid genetic algorithm and artificial neural network, known as GAANN, is applied. In this method, GA is used to identify the area of importance and ANN is used to obtain an initial estimate of the model performance by mapping the response surface. Parameter sets which give non-behavioural model runs are discarded before running the hydrological model, effectively reducing the number of actual model runs performed. The proposed method is applied to the case of a simple two-parameter model where the exact parameters are known as well as to a widely used catchment model where the parameters are to be estimated. The results of both applications indicated that the proposed method is more efficient and effective, thereby requiring fewer model simulations than GLUE. The proposed method increased the feasibility of applying uncertainty analysis to computationally intensive simulation models. Keywords: parameters, calibration, GLUE, Monte-Carlo simulation, Genetic Algorithms, Artificial Neural Networks, hydrological modelling, Singapore
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Kim, JungJin, and Jae Ryu. "Quantifying the Performances of the Semi-Distributed Hydrologic Model in Parallel Computing—A Case Study." Water 11, no. 4 (April 19, 2019): 823. http://dx.doi.org/10.3390/w11040823.
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The research features how parallel computing can advance hydrological performances associated with different calibration schemes (SCOs). The result shows that parallel computing can save up to 90% execution time, while achieving 81% simulation improvement. Basic statistics, including (1) index of agreement (D), (2) coefficient of determination (R2), (3) root mean square error (RMSE), and (4) percentage of bias (PBIAS) are used to evaluate simulation performances after model calibration in computer parallelism. Once the best calibration scheme is selected, additional efforts are made to improve model performances at the selected calibration target points, while the Rescaled Adjusted Partial Sums (RAPS) is used to evaluate the trend in annual streamflow. The qualitative result of reducing execution time by 86% on average indicates that parallel computing is another avenue to advance hydrologic simulations in the urban-rural interface, such as the Boise River Watershed, Idaho. Therefore, this research will provide useful insights for hydrologists to design and set up their own hydrological modeling exercises using the cost-effective parallel computing described in this case study.
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Fenicia, F., D. P. Solomatine, H. H. G. Savenije, and P. Matgen. "Soft combination of local models in a multi-objective framework." Hydrology and Earth System Sciences Discussions 4, no. 1 (January 19, 2007): 91–123. http://dx.doi.org/10.5194/hessd-4-91-2007.
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Abstract. Conceptual hydrologic models are useful tools as they provide an interpretable representation of the hydrologic behaviour of a catchment. Their representation of catchment's hydrological processes and physical characteristics, however, implies simplification of the complexity and heterogeneity of reality. As a result, those models often show a lack of flexibility in reproducing the vast spectrum of catchment responses. Hence, the accuracy in reproducing certain aspects of the system behaviour is often paid in terms of a lack of accuracy in the representation of other aspects. By acknowledging the structural limitations of those models, a modular approach to hydrological simulation is proposed. Instead of using a single model to reproduce the full range of catchment responses, multiple models are used, each of them assigned to a specific task. The approach is here demonstrated in the case where the different models are associated with different parameter realizations within a fixed model structure. We show that using a composite "global" model, obtained by a combination of individual "local" models, the accuracy of the simulation is improved. We argue that this approach can be useful because it partially overcomes the structural limitations that a conceptual model might exhibit. The approach is shown in application to the discharge simulation of the experimental Alzette River basin in Luxembourg, with a conceptual model that follows the structure of the HBV model.
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Xu, Q., X. Chen, J. Bi, R. Ouyang, and L. Ren. "Simulating hydrological responses with a physically based model in a mountainous watershed." Proceedings of the International Association of Hydrological Sciences 370 (June 11, 2015): 153–59. http://dx.doi.org/10.5194/piahs-370-153-2015.
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Abstract. A physical and distributed approach was proposed by Reggiani et al. (1998) to describe the hydrological responses at the catchment scale. The rigorous balance equations for mass, momentum, energy and entropy are applied on the divided spatial domains which are called Representative Elementary Watershed (REW). Based on the 2nd law of thermodynamics, Reggiani (1999) put forward several constitutive relations of hydrological processes. Associated with the above equations, the framework of a physically based distributed hydrological model was established. The crucial step for successfully applying this approach is to develop physically based closure relations for these terms and simplify the set of equations. The paper showed how a theoretical hydrological model based on the REW method was applied to prosecute the hydrological response simulation for a humid watershed. The established model was used to carry on the long-term (daily runoff forecasting) and short-term (runoff simulation of storm event) hydrological simulation in the studied watershed and the simulated results were analysed. These results and analysis proved that this physically based distributed hydrological model can produce satisfied simulation results and describe the hydrological responses correctly. Finally, several aspects to improve the model demonstrated by the results and analysis were put forward which would be carried out in the future.
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Sikorska-Senoner, Anna E., Bettina Schaefli, and Jan Seibert. "Downsizing parameter ensembles for simulations of rare floods." Natural Hazards and Earth System Sciences 20, no. 12 (December 17, 2020): 3521–49. http://dx.doi.org/10.5194/nhess-20-3521-2020.
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Abstract. For extreme-flood estimation, simulation-based approaches represent an interesting alternative to purely statistical approaches, particularly if hydrograph shapes are required. Such simulation-based methods are adapted within continuous simulation frameworks that rely on statistical analyses of continuous streamflow time series derived from a hydrological model fed with long precipitation time series. These frameworks are, however, affected by high computational demands, particularly if floods with return periods > 1000 years are of interest or if modelling uncertainty due to different sources (meteorological input or hydrological model) is to be quantified. Here, we propose three methods for reducing the computational requirements for the hydrological simulations for extreme-flood estimation so that long streamflow time series can be analysed at a reduced computational cost. These methods rely on simulation of annual maxima and on analysing their simulated range to downsize the hydrological parameter ensemble to a small number suitable for continuous simulation frameworks. The methods are tested in a Swiss catchment with 10 000 years of synthetic streamflow data simulated thanks to a weather generator. Our results demonstrate the reliability of the proposed downsizing methods for robust simulations of rare floods with uncertainty. The methods are readily transferable to other situations where ensemble simulations are needed.
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Scholz, Klaus. "Stochastic simulation of urbanhydrological processes." Water Science and Technology 36, no. 8-9 (October 1, 1997): 25–31. http://dx.doi.org/10.2166/wst.1997.0639.
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Calculations in urban hydrology have almost exclusively been of deterministic character and give therefore unequivocal results. Uncertainties, which are always present, can not been eliminated by more complex models. To take uncertainties into account stochastic algorithms are integrated into hydrological components. A stochastic-hydrological method has developed which can be used to various problems. In contrast to the usual purely deterministic models the model makes it possible to get concrete information of liability of the calibration and prognosis regarding confidence limits The model is applied for the calibration and prognosis of pollutant load hydrographs. The result is, that stochastic and physical based parameters should be taken into account.
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Sun, Guangru, Jie Wen, Jinjin Yang, Siyu Hou, and Weihua Zhang. "Study on hydrological process simulation of lumped hydrological model in Wujiang River Basin." IOP Conference Series: Earth and Environmental Science 826, no. 1 (July 1, 2021): 012028. http://dx.doi.org/10.1088/1755-1315/826/1/012028.
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Gharbia, Salem, Khurram Riaz, Iulia Anton, Gabor Makrai, Laurence Gill, Leo Creedon, Marion McAfee, Paul Johnston, and Francesco Pilla. "Hybrid Data-Driven Models for Hydrological Simulation and Projection on the Catchment Scale." Sustainability 14, no. 7 (March 29, 2022): 4037. http://dx.doi.org/10.3390/su14074037.
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Changes in streamflow within catchments can have a significant impact on agricultural production, as soil moisture loss, as well as frequent drying and wetting, may have an effect on the nutrient availability of many soils. In order to predict future changes and explore the impact of different scenarios, machine learning techniques have been used recently in the hydrological sector for simulation streamflow. This paper compares the use of four different models, namely artificial neural networks (ANNs), support vector machine regression (SVR), wavelet-ANN, and wavelet-SVR as surrogate models for a geophysical hydrological model to simulate the long-term daily water level and water flow in the River Shannon hydrological system in Ireland. The performance of the models has been tested for multi-lag values and for forecasting both short- and long-term time scales. For simulating the water flow of the catchment hydrological system, the SVR-based surrogate model performs best overall. Regarding modeling the water level on the catchment scale, the hybrid model wavelet-ANN performs the best among all the constructed models. It is shown that the data-driven methods are useful for exploring hydrological changes in a large multi-station catchment, with low computational cost.
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Li, Zhi, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong. "CREST-VEC: a framework towards more accurate and realistic flood simulation across scales." Geoscientific Model Development 15, no. 15 (August 8, 2022): 6181–96. http://dx.doi.org/10.5194/gmd-15-6181-2022.
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Abstract. Large-scale (i.e., continental and global) hydrologic simulation is an appealing yet challenging topic for the hydrologic community. First and foremost, model efficiency and scalability (flexibility in resolution and discretization) have to be prioritized. Then, sufficient model accuracy and precision are required to provide useful information for water resource applications. Towards this goal, we craft two objectives for improving US current operational hydrological models: (1) vectorized routing and (2) improved hydrological processes. This study presents a hydrologic modeling framework, CREST-VEC, that combines a gridded water balance model and a newly developed vector-based routing scheme. First, in contrast to a conventional fully gridded model, this framework can significantly reduce the computational cost of river routing by at least 10 times, based on experiments at regional (0.07 vs. 0.002 s per step) and continental scales (0.35 vs. 7.2 s per step). This provides adequate time efficiency for generating operational ensemble streamflow forecasts and even probabilistic estimates across scales. Second, the performance using the new vector-based routing is improved, with the median-aggregated NSE (Nash–Sutcliffe efficiency) score increasing from −0.06 to 0.18 over the CONUS (contiguous US). Third, with the lake module incorporated, the NSE score is further improved by 56.2 % and the systematic bias is reduced by 17 %. Lastly, over 20 % of the false alarms on 2-year floods in the US can be mitigated with the lake module enabled, at the expense of only missing 2.3 % more events. This study demonstrated the advantages of the proposed hydrological modeling framework, which could provide a solid basis for continental- and global-scale water modeling at fine resolution. Furthermore, the use of ensemble forecasts can be incorporated into this framework; and thus, optimized streamflow prediction with quantified uncertainty information can be achieved in an operational fashion for stakeholders and decision-makers.
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Wang, Qiang, Jun Xia, Xiang Zhang, Dunxian She, Jie Liu, and Pengjun Li. "Multi-Scenario Integration Comparison of CMADS and TMPA Datasets for Hydro-Climatic Simulation over Ganjiang River Basin, China." Water 12, no. 11 (November 19, 2020): 3243. http://dx.doi.org/10.3390/w12113243.
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The lack of meteorological observation data limits the hydro-climatic analysis and modeling, especially for the ungauged or data-limited regions, while satellite and reanalysis products can provide potential data sources in these regions. In this study, three daily products, including two satellite products (Tropic Rainfall Measuring Mission Multi-Satellite Precipitation Analysis, TMPA 3B42 and 3B42RT) and one reanalysis product (China Meteorological Assimilation Driving Datasets for the SWAT Model, CMADS), were used to assess the capacity of hydro-climatic simulation based on the statistical method and hydrological model in Ganjiang River Basin (GRB), a humid basin of southern China. CAMDS, TMPA 3B42 and 3B42RT precipitation were evaluated against ground-based observation based on multiple statistical metrics at different temporal scales. The similar evaluation was carried out for CMADS temperature. Then, eight scenarios were constructed into calibrating the Soil and Water Assessment Tool (SWAT) model and simulating streamflow, to assess their capacity in hydrological simulation. The results showed that CMADS data performed better in precipitation estimation than TMPA 3B42 and 3B42RT at daily and monthly scales, while worse at the annual scale. In addition, CMADS can capture the spatial distribution of precipitation well. Moreover, the CMADS daily temperature data agreed well with observations at meteorological stations. For hydrological simulations, streamflow simulation results driven by eight input scenarios obtained acceptable performance according to model evaluation criteria. Compared with the simulation results, the models driven by ground-based observation precipitation obtained the most accurate streamflow simulation results, followed by CMADS, TMPA 3B42 and 3B42RT precipitation. Besides, CMADS temperature can capture the spatial distribution characteristics well and improve the streamflow simulations. This study provides valuable insights for hydro-climatic application of satellite and reanalysis meteorological products in the ungauged or data-limited regions.
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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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AghaKouchak, A., N. Nakhjiri, and E. Habib. "An educational model for ensemble streamflow simulation and uncertainty analysis." Hydrology and Earth System Sciences 17, no. 2 (February 1, 2013): 445–52. http://dx.doi.org/10.5194/hess-17-445-2013.
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Abstract. This paper presents the hands-on modeling toolbox, HBV-Ensemble, designed as a complement to theoretical hydrology lectures, to teach hydrological processes and their uncertainties. The HBV-Ensemble can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching uncertainty analysis, parameter estimation, ensemble simulation and model sensitivity. HBV-Ensemble was administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of uncertainty in hydrological modeling.
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Hack, James J., Julie M. Caron, Stephen G. Yeager, Keith W. Oleson, Marika M. Holland, John E. Truesdale, and Philip J. Rasch. "Simulation of the Global Hydrological Cycle in the CCSM Community Atmosphere Model Version 3 (CAM3): Mean Features." Journal of Climate 19, no. 11 (June 1, 2006): 2199–221. http://dx.doi.org/10.1175/jcli3755.1.
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Abstract The seasonal and annual climatological behavior of selected components of the hydrological cycle are presented from coupled and uncoupled configurations of the atmospheric component of the Community Climate System Model (CCSM) Community Atmosphere Model version 3 (CAM3). The formulations of processes that play a role in the hydrological cycle are significantly more complex when compared with earlier versions of the atmospheric model. Major features of the simulated hydrological cycle are compared against available observational data, and the strengths and weaknesses are discussed in the context of specified sea surface temperature and fully coupled model simulations. The magnitude of the CAM3 hydrological cycle is weaker than in earlier versions of the model, and is more consistent with observational estimates. Major features of the exchange of water with the surface, and the vertically integrated storage of water in the atmosphere, are generally well captured on seasonal and longer time scales. The water cycle response to ENSO events is also very realistic. The simulation, however, continues to exhibit a number of long-standing biases, such as a tendency to produce double ITCZ-like structures in the deep Tropics, and to overestimate precipitation rates poleward of the extratropical storm tracks. The lower-tropospheric dry bias, associated with the parameterized treatment of convection, also remains a simulation deficiency. Several of these biases are exacerbated when the atmosphere is coupled to fully interactive surface models, although the larger-scale behavior of the hydrological cycle remains nearly identical to simulations with prescribed distributions of sea surface temperature and sea ice.
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Sang, Guo Qing, Sheng Le Cao, and Ze Biao Wei. "Research and Application of the Combined of SWMM and Tank Model." Applied Mechanics and Materials 166-169 (May 2012): 593–99. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.593.
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Hydrologic Model is the basic tool of simulation of the runoff generation and confluence of the basin. It is widely used in the research of hydrologic process of the drainage basin. In this paper, the characteristics of SWMM Model and Tank Model were introduced. The SWMM-Tank model was established that combined with advantages of the SWMM and Tank model. This model was used in hydrological simulation of the Big Ning river basin. The Surface and Underground runoff was simulated respectively using the SWMM model and Tank model. The simulation results show that the SWMM-Tank model can meet the requirement of accuracy and the combined model is simple. The combined model can be used in hydrologic simulated of the drainage basin that the underground information is lacked.
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Pender, Douglas, Sandhya Patidar, Gareth Pender, and Heather Haynes. "Stochastic simulation of daily streamflow sequences using a hidden Markov model." Hydrology Research 47, no. 1 (May 28, 2015): 75–88. http://dx.doi.org/10.2166/nh.2015.114.
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Estimation of daily streamflow time series is of paramount importance for the design and implementation of river engineering and management projects (e.g., restoration, sediment-transport modelling, hydropower). Traditionally, indirect approaches combining stochastic simulation of rainfall with hydrological rainfall–runoff models are used. However, these are limited by uncertainties in model calibration and computational expense. Thus, this paper demonstrates an alternative, direct approach, for stochastic modelling of daily streamflow data, specifically seeking to address well-known deficiencies in model capability to capture extreme flow events in the simulated time series. Combinations of a hidden Markov model (HMM) with the generalised extreme value (HMM-GEV) and generalised Pareto (HMM-GP) distributions were tested for four hydrologically contrasting catchments in the UK (Rivers Dee, Falloch, Caldew and Lud), with results compared to recorded flow data and estimations obtained from a simpler autoregressive-moving-average (ARMA) model. Results show that the HMM-GP method is superior in performance over alternative approaches (relative mean absolute differences (RMAD) of <2% across all catchments), appropriately captures extreme events and is generically applicable across a range of hydrological regimes. In contrast, the ARMA model was unable to capture the flow regime successfully (average RMAD of 14% across all catchments).