We proposed unit flood discharge model that defined as the discharge into end-order (smallest) drainage canals. The discharge acts an important role for estimating regional flooding by big rainfall events which leadin...We proposed unit flood discharge model that defined as the discharge into end-order (smallest) drainage canals. The discharge acts an important role for estimating regional flooding by big rainfall events which leading roughly estimation of flood discharge associated with land use changes as urbanization. In some areas of Japan, increased urbanization with insufficient drainage canal capacity has led to increasingly frequent flooding and flood damage. The aim of this study was to investigate the effect of urbanization on unit flood discharge using a runoff model for the Tedori River alluvial fan area, Japan. The discharge was studied as collecting runoff from paddy fields, upland crop fields, and residential lots. A runoff model for various land use types in the study area was developed using actual and physical properties of the runoff sites, and parameters for paddy fields. The model was tested using 54 big events and inputted those. The maximum total runoff ratio among different land use types was observed for residential lots, and the ratio remained relatively constant across different flood events. The minimum total runoff ratio was observed for irrigated paddy fields. There was a positive relationship between the total runoff ratio and total precipitation for all land use types. Whereas, the relationship between the peak runoff ratio and peak precipitation was variable. The runoff analysis was carried out using 60-min and 10-min precipitation data. For agricultural land, data for both intervals produced similar results.展开更多
Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive mode...Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days （ADD）, have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency＇s Storm Water Management Model （SWMM）. The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid （TSS） discharge loads and event mean concentrations （EMC） were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.展开更多
文摘We proposed unit flood discharge model that defined as the discharge into end-order (smallest) drainage canals. The discharge acts an important role for estimating regional flooding by big rainfall events which leading roughly estimation of flood discharge associated with land use changes as urbanization. In some areas of Japan, increased urbanization with insufficient drainage canal capacity has led to increasingly frequent flooding and flood damage. The aim of this study was to investigate the effect of urbanization on unit flood discharge using a runoff model for the Tedori River alluvial fan area, Japan. The discharge was studied as collecting runoff from paddy fields, upland crop fields, and residential lots. A runoff model for various land use types in the study area was developed using actual and physical properties of the runoff sites, and parameters for paddy fields. The model was tested using 54 big events and inputted those. The maximum total runoff ratio among different land use types was observed for residential lots, and the ratio remained relatively constant across different flood events. The minimum total runoff ratio was observed for irrigated paddy fields. There was a positive relationship between the total runoff ratio and total precipitation for all land use types. Whereas, the relationship between the peak runoff ratio and peak precipitation was variable. The runoff analysis was carried out using 60-min and 10-min precipitation data. For agricultural land, data for both intervals produced similar results.
基金supported by the Korea Ministry of Environment, as "The Eco-innovation Project" (No. 413111-003)
文摘Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days （ADD）, have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency＇s Storm Water Management Model （SWMM）. The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid （TSS） discharge loads and event mean concentrations （EMC） were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.
