In this research,a modeling approach of rainfall generator coupled with high resolution rainfall products were proposed to generate designed rainfall events under multiple spatial and temporal distributions,which was ...In this research,a modeling approach of rainfall generator coupled with high resolution rainfall products were proposed to generate designed rainfall events under multiple spatial and temporal distributions,which was then employed to analyze the impacts of spatial and temporal rainfall heterogeneities on peak runoff for watersheds.Three scenarios were developed under multiple degrees of impermeable underlying surface areas within an urban watershed in south China.Detailed runoff processes were analyzed through the adoption of a distributed hydrological model(GSSHA).A covariance analysis method combined with rainfall spatio-temporal heterogeneity characteristic were used to quantify heterogeneity effects on peak runoff.Results indicated that coupling short period(2008–2016)remotely rainfall data and RainyDay results could successfully reproduce designed rainfall events,spatio-temporal heterogeneity of rainfall contributed significantly to the peak runoff,which was greater than those by rainfall duration and capacity,and the increase in impermeable underlying surface enhanced the complexities of the effects.Over each rainfall duration with increasing rainfall return period,the indicator of rainfall peak coefficient(RWD)would decrease and then increase.Regarding the total rainfall center(tg),25 mm/h threshold rainfall spatial coverage(A25)decreased with increasing imperviousness,1-h maximum rainfall(Rmax)surged with increasing imperviousness at rainfall duration of 2 and 24 h.Innovations of this research lied in:combination of a rainfall generator model based on a stochastic storm transposition technique and remote-sensing rainfall data to generate designed rainfall events,a rainfall spatial and temporal heterogeneities index system was developed to reveal how the changing characteristics of rainfall distribution and the impacts on peak runoff,and in-depth analysis of the impacts on runoff peak under multiple urban development scenarios for increasing capability in flood control/prevention.展开更多
In this study, an integrated approach for runoff estimation using the storm water management model (SWMM) was applied to undertake a stormwater and sewerage modelling in urban setting. The main objectives of the resea...In this study, an integrated approach for runoff estimation using the storm water management model (SWMM) was applied to undertake a stormwater and sewerage modelling in urban setting. The main objectives of the research and this manuscript include overload detection of sewer systems during extreme rainfall events with SWMM and to model and predict the relationship between precipitation parameters and overflooding of sewer collection system that includes emergency ponds to relieve flow from pump stations. The study takes into account monitored concurrent extreme rainfall event data and peak wet weather flows observed at outfall of collection system entering a wastewater treatment plant draining the urban centre. In the study SWMM was modified and adapted for the Tati and Ntshe confluence rivers draining the urban centre of Francistown in Northern Botswana. Landuse, soil, geological, drainage and sewerage network and imperviousness data sets were acquired and developed in GIS database. The runoff coefficient is found to range between 0.12 and 0.24 in the studied catchments. The calibrated model was able to predict the observed outputs with reasonable accuracy for calibration datasets of two peak flood events of 2016-Jan 12 and 2017-Feb 16 and verification flood events of 2016-Feb 05 and 2017-Feb 26. For six watersheds that drain the study area considered with a seventh entire collection system catchment area, we have evaluated the model performance using different criteria. We have found that correlation coefficients range from 0.539 to 0.813 and NSE ranges from 40.9% to 89.0%, and RSR ranges from 0.330 to 0.812 for the calibration datasets. Whereas, for the verification dataset, the correlation coefficients range from 0.539 to 0.813 and NSE values range from 40.9% to 89.0%, and RSR values range from 0.330 to 0.812. Using the criteria adopted, the SWMM-simulated runoff values are in acceptable agreement with the observed hydrographs.展开更多
Peak discharge plays an important role in triggering channelized debris flows.The rainfall regimes and rainfall characteristics have been demonstrated to have important influences on peak discharge.In order to explore...Peak discharge plays an important role in triggering channelized debris flows.The rainfall regimes and rainfall characteristics have been demonstrated to have important influences on peak discharge.In order to explore the relationship between rainfall regimes and peak discharge,a measuring system was placed at the outlet of a small,debris flow-prone catchment.The facility consisted of an approximately rectangular stilling basin,ending with a sharp-crested weir.Six runoff events were recorded which provided a unique opportunity for characterizing the hydrological response of the debris flow-prone catchment.Then,a rainfall–runoff model was tested against the flow discharge measurements to have a deep understanding of hydrological response.Based on the calibrated rainfall-runoff model,twelve different artificially set rainfall patterns were regarded as the input parameters to investigate the effect of rainfall regimes on peak discharge.The results show that the rainfall patterns have a significant effect on peak discharge.The rainfall regimes which have higher peak rainfall intensity and peak rainfall point occur at the later part of rainfall process are easy to generate larger peak discharge in the condition of the same cumulative rainfall and duration.Then,in order to explore the relationship between rainfall characteristics and peak discharge under different cumulative precipitation and different duration,167 measured rainfall events were also collected.On the basis of rainfall depth,rainfall duration,and maximum hourly intensity,all the rainfall events were classified into four categories by using K-mean clustering.Rainfall regime 1 was composed of rainfall events with a moderate mean P(precipitation),a moderate D(duration),and a moderate I60(maximum hourly intensity).Rainfall regime 2 was the group of rainfall events with a high mean P,long D.Rainfall regime 3,however,had a low P and a long D.The characteristic of Rainfall regime 4 was high I60 and short duration with large P.The results show that the rainfall regime 2 and 4 are easier to generate peak discharge as the rainfall intensity plays an important role in generating peak discharge.The results in this study have implications for improving peak discharge prediction accuracy in debris flow gully.展开更多
Peak discharge of flood in small mountainous watershed is usually calculated using the "Rainstorm–runoff calculation method in small watersheds in Sichuan Province"(RRM). This study evaluated the RRM calcul...Peak discharge of flood in small mountainous watershed is usually calculated using the "Rainstorm–runoff calculation method in small watersheds in Sichuan Province"(RRM). This study evaluated the RRM calculation using real-time monitored rainfall and hydrologic data from a small watershed in the Wenchuan Earthquake area of Sichuan Province, China. The results indicated that the discharge values given by the RRM are commonly overestimating the measured discharge. The overestimation rate was discussed and empirical equations were proposed for improving RRM estimations, based on the relationship between calculated and measured discharge values at different watershed scales(2, 30, and 40 km2), under different rainfall probabilities(0.97–0.5, 0.5–0.2, and 0.2–0.002), and for different rainfall durations(0–6, 6–24, and >24 h). The results of this study help contribute to the understanding of water floods formation and help provide more accurate estimations of peak flow discharge in small watersheds in the Wenchuan Earthquake area.展开更多
A number of physically-based and distributed watershed models have been developed to model the hydrology of the watershed. For a specific watershed, selecting the most suitable hydrological model is necessary to obtai...A number of physically-based and distributed watershed models have been developed to model the hydrology of the watershed. For a specific watershed, selecting the most suitable hydrological model is necessary to obtain good simulated results. In this study, two hydrologic models, Soil and Water Assessment Tool (SWAT) and Hydrological Engineering Centre<span style="font-family:;" "=""><span style="font-family:Verdana;">-The Hydrologic Modeling System (HEC-HMS), were applied to predict streamflow in Katar River basin, Ethiopia. The performances of these two models were compared in order to select the right model for the study basin. Both models were calibrated and validated with stream flow data of 11 years (1990-2000) and 7 years (2001-2007) respectively. Nash-Sutcliffe Error (NSE) and Coefficient of Determination (R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;">) were used to evaluate efficiency of the models. The results of calibration and validation indicated that, for river basin Katar, both models could simulate fairly well the streamflow. SWAT gave the model performance with the R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> > 0.78 and NSE > 0.67;and the HEC-HMS model provided the model performance with the R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> > 0.87 and NSE > 0.73. Hence, the simulated streamflow given by the HEC-HMS model is more satisfactory than that provided by the SWAT model.</span></span>展开更多
基金Program for Guangdong Introducing Innovative and Entrepreneurial Teams,Grant/Award Number:2021ZT09Key-Area Research and Development Program of Guangdong Province,Grant/Award Number:2020B1111380003National Natural Science Foundation of China,Grant/Award Number:U20A20117。
文摘In this research,a modeling approach of rainfall generator coupled with high resolution rainfall products were proposed to generate designed rainfall events under multiple spatial and temporal distributions,which was then employed to analyze the impacts of spatial and temporal rainfall heterogeneities on peak runoff for watersheds.Three scenarios were developed under multiple degrees of impermeable underlying surface areas within an urban watershed in south China.Detailed runoff processes were analyzed through the adoption of a distributed hydrological model(GSSHA).A covariance analysis method combined with rainfall spatio-temporal heterogeneity characteristic were used to quantify heterogeneity effects on peak runoff.Results indicated that coupling short period(2008–2016)remotely rainfall data and RainyDay results could successfully reproduce designed rainfall events,spatio-temporal heterogeneity of rainfall contributed significantly to the peak runoff,which was greater than those by rainfall duration and capacity,and the increase in impermeable underlying surface enhanced the complexities of the effects.Over each rainfall duration with increasing rainfall return period,the indicator of rainfall peak coefficient(RWD)would decrease and then increase.Regarding the total rainfall center(tg),25 mm/h threshold rainfall spatial coverage(A25)decreased with increasing imperviousness,1-h maximum rainfall(Rmax)surged with increasing imperviousness at rainfall duration of 2 and 24 h.Innovations of this research lied in:combination of a rainfall generator model based on a stochastic storm transposition technique and remote-sensing rainfall data to generate designed rainfall events,a rainfall spatial and temporal heterogeneities index system was developed to reveal how the changing characteristics of rainfall distribution and the impacts on peak runoff,and in-depth analysis of the impacts on runoff peak under multiple urban development scenarios for increasing capability in flood control/prevention.
文摘In this study, an integrated approach for runoff estimation using the storm water management model (SWMM) was applied to undertake a stormwater and sewerage modelling in urban setting. The main objectives of the research and this manuscript include overload detection of sewer systems during extreme rainfall events with SWMM and to model and predict the relationship between precipitation parameters and overflooding of sewer collection system that includes emergency ponds to relieve flow from pump stations. The study takes into account monitored concurrent extreme rainfall event data and peak wet weather flows observed at outfall of collection system entering a wastewater treatment plant draining the urban centre. In the study SWMM was modified and adapted for the Tati and Ntshe confluence rivers draining the urban centre of Francistown in Northern Botswana. Landuse, soil, geological, drainage and sewerage network and imperviousness data sets were acquired and developed in GIS database. The runoff coefficient is found to range between 0.12 and 0.24 in the studied catchments. The calibrated model was able to predict the observed outputs with reasonable accuracy for calibration datasets of two peak flood events of 2016-Jan 12 and 2017-Feb 16 and verification flood events of 2016-Feb 05 and 2017-Feb 26. For six watersheds that drain the study area considered with a seventh entire collection system catchment area, we have evaluated the model performance using different criteria. We have found that correlation coefficients range from 0.539 to 0.813 and NSE ranges from 40.9% to 89.0%, and RSR ranges from 0.330 to 0.812 for the calibration datasets. Whereas, for the verification dataset, the correlation coefficients range from 0.539 to 0.813 and NSE values range from 40.9% to 89.0%, and RSR values range from 0.330 to 0.812. Using the criteria adopted, the SWMM-simulated runoff values are in acceptable agreement with the observed hydrographs.
基金financially supported by the National Natural Science Foundation of China (Grant No. 41772276)Key R&D project of Zhejiang Province (Grant No. 2017C03006)China Postdoctoral Science Foundation (Grant No. 2019M652083)
文摘Peak discharge plays an important role in triggering channelized debris flows.The rainfall regimes and rainfall characteristics have been demonstrated to have important influences on peak discharge.In order to explore the relationship between rainfall regimes and peak discharge,a measuring system was placed at the outlet of a small,debris flow-prone catchment.The facility consisted of an approximately rectangular stilling basin,ending with a sharp-crested weir.Six runoff events were recorded which provided a unique opportunity for characterizing the hydrological response of the debris flow-prone catchment.Then,a rainfall–runoff model was tested against the flow discharge measurements to have a deep understanding of hydrological response.Based on the calibrated rainfall-runoff model,twelve different artificially set rainfall patterns were regarded as the input parameters to investigate the effect of rainfall regimes on peak discharge.The results show that the rainfall patterns have a significant effect on peak discharge.The rainfall regimes which have higher peak rainfall intensity and peak rainfall point occur at the later part of rainfall process are easy to generate larger peak discharge in the condition of the same cumulative rainfall and duration.Then,in order to explore the relationship between rainfall characteristics and peak discharge under different cumulative precipitation and different duration,167 measured rainfall events were also collected.On the basis of rainfall depth,rainfall duration,and maximum hourly intensity,all the rainfall events were classified into four categories by using K-mean clustering.Rainfall regime 1 was composed of rainfall events with a moderate mean P(precipitation),a moderate D(duration),and a moderate I60(maximum hourly intensity).Rainfall regime 2 was the group of rainfall events with a high mean P,long D.Rainfall regime 3,however,had a low P and a long D.The characteristic of Rainfall regime 4 was high I60 and short duration with large P.The results show that the rainfall regime 2 and 4 are easier to generate peak discharge as the rainfall intensity plays an important role in generating peak discharge.The results in this study have implications for improving peak discharge prediction accuracy in debris flow gully.
基金supported by the National Research Project (2017YFC1502504)International S&T Cooperation Project (2016YFE0122400)+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences, Grant No. XDA23*, the Open Fund (SKLGP2017K013)Youth Innovation Promotion Association
文摘Peak discharge of flood in small mountainous watershed is usually calculated using the "Rainstorm–runoff calculation method in small watersheds in Sichuan Province"(RRM). This study evaluated the RRM calculation using real-time monitored rainfall and hydrologic data from a small watershed in the Wenchuan Earthquake area of Sichuan Province, China. The results indicated that the discharge values given by the RRM are commonly overestimating the measured discharge. The overestimation rate was discussed and empirical equations were proposed for improving RRM estimations, based on the relationship between calculated and measured discharge values at different watershed scales(2, 30, and 40 km2), under different rainfall probabilities(0.97–0.5, 0.5–0.2, and 0.2–0.002), and for different rainfall durations(0–6, 6–24, and >24 h). The results of this study help contribute to the understanding of water floods formation and help provide more accurate estimations of peak flow discharge in small watersheds in the Wenchuan Earthquake area.
文摘A number of physically-based and distributed watershed models have been developed to model the hydrology of the watershed. For a specific watershed, selecting the most suitable hydrological model is necessary to obtain good simulated results. In this study, two hydrologic models, Soil and Water Assessment Tool (SWAT) and Hydrological Engineering Centre<span style="font-family:;" "=""><span style="font-family:Verdana;">-The Hydrologic Modeling System (HEC-HMS), were applied to predict streamflow in Katar River basin, Ethiopia. The performances of these two models were compared in order to select the right model for the study basin. Both models were calibrated and validated with stream flow data of 11 years (1990-2000) and 7 years (2001-2007) respectively. Nash-Sutcliffe Error (NSE) and Coefficient of Determination (R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;">) were used to evaluate efficiency of the models. The results of calibration and validation indicated that, for river basin Katar, both models could simulate fairly well the streamflow. SWAT gave the model performance with the R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> > 0.78 and NSE > 0.67;and the HEC-HMS model provided the model performance with the R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> > 0.87 and NSE > 0.73. Hence, the simulated streamflow given by the HEC-HMS model is more satisfactory than that provided by the SWAT model.</span></span>
