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Application of developed Grid-GA distributed hydrologic model in semi-humid and semi-arid basin

Transactions of Tianjin University 2025年第3期16卷 209-215页

作者： Lili Wang Zhijia Li Hongjun Bao College of Hydrology and Water Resources Hohai University Nanjing China National Meteorological Center China Meteorological Administration Beijing China

A grid and Green-Ampt based(Grid-GA)distributed hydrologic physical model was developed for flood simulation and forecasting in semi-humid and semi-arid basin. Based on topographical information of each grid cell extracted from the digital elevation model (DEM) and Green-Ampt infiltration method, the Grid-GA model takes into consideration the redistribution of water content, and consists of vegetation and root interception, evapotranspiration, runoff generation via the excess infiltration mechanism, runoff concentration, and flow routing. The downslope redistribution of soil moisture is explicitly calculated on a grid basis, and water exchange among grids within runoff routing along the river drainage networks is taken into consideration. The proposed model and Xin’anjiang model were applied to the upper Lushi basin in the Luohe River, a tributary of the Yellow River, with an area of 4 716 km² for flood simulation. Results show that both models perform well in flood simulation and can be used for flood forecasting in semi-humid and semi-arid region.

关键词： distributed hydrologic model digital elevation model (DEM) Green-Ampt redistribution excess infiltration mechanism semi-humid and semi-arid basin

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Simulating the spatio-temporal dynamics of soil erosion, deposition, and yield using a coupled sediment dynamics and 3D distributed hydrologic model

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ENVIRONMENTAL modelLING & SOFTWARE 2016年第0期83卷 310-325页

作者： Zi, Tan Kumar, Mukesh Kiely, Gerard Lewis, Ciaran Albertson, John Duke Univ Dept Civil & Environm Engn Durham NC 27706 USA Duke Univ Nicholas Sch Environm Durham NC 27706 USA Univ Coll Cork Ctr Hydrol Micrometeorol & Climate Change Dept Civil & Environm Engn Cork Ireland Cornell Univ Sch Civil & Environm Engn Ithaca NY 14853 USA

Since soil erosion is driven by overland flow, it is fair to expect heterogeneity in erosion and deposition in both space and time. In this study, we develop and evaluate an open-source, spatially-explicit, sediment erosion, deposition and transport module for the distributed hydrological model, GEOtop. The model was applied in Dripsey catchment in Ireland, where it captured the total discharge volume and suspended sediment yield (SSY) with a relative bias of -1.2% and -22.4%, respectively. Simulation results suggest that daily SSY per unit rainfall amount was larger when the top soil was near saturation. Simulated erosion and deposition areas, which varied markedly between events, were also found to be directly influenced by spatial patterns of soil saturation. The distinct influence of soil saturation on erosion, deposition and SSY underscores the role of coupled surface-subsurface hydrologic interactions and a need to represent them in models for capturing fine resolution sediment dynamics. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： distributed hydrologic model Soil erosion Sediment spatio-temporal dynamics Coupled modeling Sediment transport model GEOtop model

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Predicting Flood Severity for New England Basins with a Semi-distributed hydrologic model

Predicting Flood Severity for New England Basins with a Semi...

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作者： Buckley, Eric William University of Connecticut

学位级别：M.S., Master of Science

In an effort to modernize the state of practice of flash flood forecasting, recent research has shown promise in utilizing regionalized, continuous, distributed hydrologic models. Additional avenues of refining the forecasting methods have included attempting to forecast event frequencies in lieu of relying on flood magnitudes generated by the models. It is anticipated that this additional post processing of the distributed modeling results can alleviate some modeling errors inherent with trying to represent any natural process. This study examines the application of a regional distributed hydrologic model of lower New England, specifically the results calculated at internal sub-basins by comparing those results to historical gauged data. Then, through frequency transform methods, the forecasting potential is reassessed to determine if frequency predictions can increase confidence in predicting a flash flood. This study further addresses the sensitivity of the spatial scale of the subject catchments as well as the temporal scale in determining the effectiveness of both the distributed model and the frequency prediction. It was found that by post processing the predicted data, the bias in the forecasted events was greatly reduced as compared to the raw output from the modeling. This bias was also sensitive to the resolution of the time step, with the error directly related to that resolution. On the spatial scale, it was shown that the variation in the catchment size did not have a significant impact on the results. Overall, it is shown that there is value to post processing hydrologic modeling results from a continuous, distributed model in order to predict a probability of exceedance as opposed to basing flood warnings on raw flow magnitude calculations.

关键词： Flash Flood distributed hydrologic model forecasting flood frequency

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pytRIBS: An open, modular, and reproducible python-based framework for distributed hydrologic modeling

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ENVIRONMENTAL modelLING & SOFTWARE 2025年 188卷

作者： Raming, L. Wren Vivoni, Enrique R. Cederstrom, C. Josh Hossain, M. Akram Becerra, Jose A. Arizona State Univ Sch Sustainable Engn & Built Environm Tempe AZ 85287 USA Arizona State Univ Ctr Hydrol Innovat Tempe AZ 85287 USA

distributed hydrologic models (DHM) are essential tools for understanding how and where water moves through a landscape. However, DHMs can be time-consuming and challenging to setup, limiting their application. Here, we present pytRIBS, a tool that addresses these challenges for the TIN-based Real-time Integrated Basin Simulator (tRIBS). pytRIBS is an open-source Python package with an object-oriented design intended to initialize, execute, and analyze tRIBS simulations. This package mirrors a tRIBS workflow with five preprocessing classes (Project, Mesh, Soil, Land, and Met) that can be used together or separately to obtain and convert data into a tRIBS format. Finally, the Results class manages outputs, provides analytical tools, and visualizes results. We illustrate these capabilities with an example case study of the Newman Canyon watershed, AZ, USA.

关键词： distributed hydrologic model Hydrology Python Integrated modeling systems Open-source

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Ensemble Kalman Filtering and Particle Filtering in a Lag-Time Window for Short-Term Streamflow Forecasting with a distributed hydrologic model

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JOURNAL OF hydrologic ENGINEERING 2013年第12期18卷 1684-1696页

作者： Noh, Seong Jin Tachikawa, Yasuto Shiiba, Michiharu Kim, Sunmin Korea Inst Construct Technol Water Resources & Environm Res Dept Water Resources Res Div Goyang Si 411712 Gyeonggi Do South Korea Kyoto Univ Dept Civil & Earth Resources Engn Kyoto 6158540 Japan

The performance of the ensemble Kalman filter (EnKF) and the particle filter (PF) is assessed for short-term streamflow forecasting with a distributed hydrologic model, namely, the water and energy transfer processes (WEP) model. To mitigate the drawbacks of conventional filters, the ensemble square root filter (EnSRF) and the regularized particle filter (RPF) are implemented. For both the EnSRF and the RPF, sequential data assimilation is performed within a lag-time window to consider the response times of internal hydrologic processes. The proposed methods are applied to two catchments in Japan and Korea to assess their performance. The model ensembles are perturbed by the noise of the soil moisture content and are assimilated with streamflow observations. The forecasting accuracy of both the EnSRF and the RPF is improved when sufficient lag-time windows are provided. The EnSRF is sensitive to the length of the lag-time window and has a limited ability to forecast within short lead times, whereas the RPF has a more stable forecasting capability for the entire range of lead times. Filtering with a limited number of ensembles also yields improved performance using a lag-time window.

关键词： Kalman filters Streamflow Forecasting hydrologic models Ensemble Kalman filter Particle filter Streamflow forecasting distributed hydrologic model Lag-time window

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Research and application of the parallel computing method for the grid-based Xin'anjiang model

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HYDROLOGY RESEARCH 2023年第4期54卷 591-605页

作者： Liu, Qian Wan, Dingsheng Yu, Yufeng Zhang, Yangming Hohai Univ Coll Comp & Informat Nanjing 211100 Jiangsu Peoples R China Bank Nanjing Nanjing 211100 Jiangsu Peoples R China

The grid-based Xin'anjiang model (GXM) has been widely applied to flood forecasting. However, when the model warm-up period is long and the amount of input data is large, the computational efficiency of the GXM is obviously low. Therefore, a GXM parallel algorithm based on grid flow direction division is proposed from the perspective of spatial parallelism, which realizes the parallel computing of the GXM by extracting the parallel routing sequence of the watershed grids. To solve data skew, a DAG scheduling algorithm based on dynamic priority is proposed for task scheduling. The proposed GXM parallel algorithm is verified in the Qianhe River watershed of Shaanxi Province and the Tunxi watershed of Anhui Province. The results show that the GXM parallel algorithm based on grid flow direction division has good flood forecasting accuracy and higher computational efficiency than the traditional serial computing method. In addition, the DAG scheduling algorithm can effectively improve the parallel efficiency of the GXM.

关键词： distributed hydrologic model flood forecasting grid-based Xin'anjiang model parallel computing

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A comprehensive evaluation of calibration strategies for flood prediction in a large catchment using HEC-HMS

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modelING EARTH SYSTEMS AND ENVIRONMENT 2025年第1期11卷 1-21页

作者： Kalakuntla, Nikhil Teja Umamahesh, N. V. Natl Inst Technol Warangal Warangal India

Effective calibration is essential for the performance of hydrological models, particularly in flood forecasting. This study aims to explore various calibration strategies for improving the accuracy of an event based hydrological model. The proposed strategies are optimized at the flood forecasting station located at Bamni (Balharsha) in Wardha subbasin of Godavari River Basin, India. The effect of spatial variability of hydro-meteorological processes and catchment characteristics on streamflow for such a large catchment is modelled by employing a distributed hydrologic model (HEC-HMS). Different characteristics of a flood hydrograph for calibration are addressed using single- and multi-objective optimization algorithms. Four calibration strategies are formulated based on single- and multi-site calibration approaches, combined with single- and multi-objective optimization algorithms. These strategies are compared against the default calibration technique used in HEC-HMS, serving as the benchmark. In this event based study, six flood events are chosen for calibration and six for validation. The results of the study seek to identify the optimal calibration strategy for accurate prediction of floods during flood forecasting. While single-site calibration strategies yield similar results, the incorporation of interior streamgage data substantially enhances model performance by improving the hydrological simulations at the outlet. The benchmark calibration strategy outperforms single-site calibration strategies;with the multi-site multi-objective combination demonstrating the best results, albeit slightly better than the benchmark strategy. Additionally, the external automation of HEC-HMS model facilitates the implementation of joint-event calibration and application of global search algorithms, making the optimization process more straightforward and efficient.

关键词： HEC-HMS distributed hydrologic model Single-objective optimization Multi-objective optimization Single-site calibration Multi-site calibration

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Simulation and Prediction of Soil Erosion in Typical Karst Rocky Desertification Area Based on SWAT model 14th

Simulation and Prediction of Soil Erosion in Typical Karst R...

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14th Congress of the International-Association-for-Engineering-Geology-and-the-Environment (IAEG)

作者： Liu, Qi Deng, Dapeng Yao, Bangjie Lu, Kewen Tongji Univ Coll Civil Engn Dept Geotech Engn Shanghai 200092 Peoples R China Tongji Univ Key Lab Geotech & Underground Engn Minist Educ Shanghai 200092 Peoples R China Shanghai Cehui Informat Technol Co Ltd Shanghai 200433 Peoples R China

ISBN: (纸本)9789819990672;9789819990658;9789819990641

The karst rocky desertification caused due to soil erosion had seriously hindered the production and economic development in some karst regions of China. In order to comprehensively explore the law of soil erosion based on basin scale in karst rocky desertification areas, the moderate-intensity karst rocky desertification area of Beipanjiang River's Guanling partial basin in Guizhou Province, was taken as the study area. The basin area 4510.41 km(2) of study area was divided into 33 sub basins, and the construction of distributed hydrologic spatial database and attribute database was completed. Taking the hydrological station data in the study area as the correction and verification, the distributed hydrologic model (SWAT model) of the study area was obtained. The simulation analysis showed that the soil erosion in the study area was serious, which had 5 grades from mild erosion to extreme intensity erosion, and the proportion of soil erosion intensity area was: mild > severe > moderate > slight > intense. Using the weather generator to get meteorological data for the next 36 years from 2022 to 2057, calculate runoff and sediment yield under the condition of returning farmland to forest in the study area. The results show that the average sediment yield from 2054 to 2057 will be 76% lower than that from 2022 to 2025, so returning farmland to forest has a significant inhibitory effect on sediment yield, and puts forward suggestions for the prevention and control of soil erosion.

关键词： Karst rocky desertification distributed hydrologic model Soil erosion Land-use type Prediction

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Sequential data assimilation for streamflow forecasting using a distributed hydrologic model: particle filtering and ensemble Kalman filtering

Sequential data assimilation for streamflow forecasting usin...

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5th International Conference on Flood Management (ICFM5)

作者： Noh, Seong Jin Tachikawa, Yasuto Shiiba, Michiharu Kim, Sunmin Kyoto Univ Dept Urban & Env Eng Kyoto 6158540 Japan Korea Inst Construct Technol Water Resources & Environm Res Dept Gyeonggi 411712 South Korea Kyoto Univ Dept Civil & Earth Resources Engn Kyoto 6158540 Japan

ISBN: (纸本)9781907161353

Accurate streamflow predictions are crucial for mitigating flood damage and addressing operational flood scenarios. In recent years, sequential data assimilation methods have drawn attention due to their potential to handle explicitly the various sources of uncertainty in hydrologic models. In this study, we implement two ensemble-based sequential data assimilation methods for streamflow forecasting via the particle filters and the ensemble Kalman filter (EnKF). Among variations of filters, the ensemble square root filter (EnSRF) and the lagged regularized particle filter (LRPF) are implemented for a distributed hydrologic model. Two methods are applied for short-term flood forecasting in a small-sized catchment located in Japan (<1000 km(2)). Soil moisture contents are perturbed by process noises and model ensembles are updated by streamflow observation at the outlet. In the case of the LRPF, state updating is performed through a lag-time window to take into account the different response times of hydrologic processes. For different flood events and various forecast lead times, LRPF forecasts outperform EnSRF forecasts and deterministic cases. The EnSRF shows limited performance in both forecasting accuracy and probabilistic intervals, which require introduction of a lag-time window in the filtering processes.

关键词： sequential data assimilation flood forecasting particle filter ensemble Kalman filter distributed hydrologic model

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hydrological characteristics and changes in the Nu-Salween River basin revealed with model-based reconstructed data

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Journal of Mountain Science 2021年第11期18卷 2982-3002页

作者： YANG Fan LU Hui YANG Kun HUANG Guang-wei LI Yi-shan WANG Wei LU Ping TIAN Fu-qiang HUANG Yu-gang Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Ministry of Education Ecological Field Station for East Asian Migratory Birds Beijing 100084China Center for Excellence in Tibetan Plateau Earth Sciences and National Tibetan Plateau Data Center Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China Graduate School of Global Environmental Studies Sophia UniversityTokyo 102-8554Japan Changjiang Institute of Survey PlanningDesign and ResearchWuhan 430010China Department of Hydraulic Engineering State Key Laboratory of Hydroscience and EngineeringTsinghua UniversityBeijing 100084China The International Economic&Technical Cooperation and Exchange Center Ministry of Water ResourcesBeijing 100053China

The Nu-Salween River(NSR),the longest free-flow river in Southeast Asia,plays an irreplaceable role in social development and ecological *** lower NSR region is particularly valuable as it is inhabited by approximately 6.7 million *** basin has limited hydraulic conservancy infrastructure and insufficient ability to cope with climate change *** the hydrological characteristics and changes in the basin provides the scientific basis for rational protection and development of the ***,owing to the limitation of observation data,previous studies have focused on the local area and neglected the study of the lower reaches,which is not enough to reflect the spatial characteristics of the entire *** this study,the ECMWF 5th generation reanalysis data(ERA5)and Multi-Source Weighted-Ensemble Precipitation(MSWEP)were applied to develop a geomorphology-based hydrological model(GBHM)for reconstructing hydrological datasets(***-ERA5 and GBHM-MSWEP).The reconstructed datasets covering the complete basin were verified against the gauge observation and compared with other commonly used streamflow products,including Global Flood Awareness System v2.1,GloFAS-Reanalysis dataset v3.0,and linear optimal runoff aggregate(LORA).The comparison results revealed that GBHM-ERA5 is significantly better than the other four datasets and provides a good reproduction of the hydrological characteristics and trends of the *** analysis of GBHM-ERA5 revealed that:(1)A multi-year mean surface runoff represented 39%of precipitation over the basin during 1980–2018,which had low surface runoff in the upstream,while areas around the Three Parallel Rivers Area and the estuary had abundant surface runoff.(2)The surface runoff and discharge coefficient of variations in spring were larger than those in other seasons,and the inter-annual variation in the downstream was smaller than that in the upstream and midstream regions.(3)More than 70%of the basin are

关键词： Nu-Salween River distributed hydrologic model ERA5 Surface runoff Discharge Climate Change

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