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Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Yellow River is the property of Editorial Board of Yellow River and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rainfall and runoff events are two important parameters in the natural hydrological cycle. The rainfall also dominates the formation of runoff in many influence factors. In recent years, various human activities, such as the construction of projects for water conservancy, as well as conservation projects for soil sources, have posed a great impact on the soil infiltration and topography of basin, which further affected the evolution of surface runoff. Heavy rain and runoff can cause a series of natural disasters, such as water erosion and flood damage. Sediment loss from construction sites and soil erosion has become a serious source of water pollution in the loess hilly and gully area. The rapid situation can deeply deteriorate the water and soil resources, further to threaten the safety of flood control. Fortunately, Soil Conservation Service (SCS) model can be used to evaluate the impact of rainfall on runoff yield. The improved model was established to consider the impact of other rainfall characteristics in the supposed conditions and internal structure with the parameter calibration. However, the accuracy of runoff simulation depends mainly on the selection of model parameters, particularly on the regional characteristics of parameters. In this study, a dynamic parameter SCS-Random Forest (RF) model was constructed, according to the dataset from 307 times rainfall runoff in Wangjiagou basin and its sub basins in flood season. The rainfall characteristics were taken as splitting attributes of a decision tree, while the RF was used to determine the Curve Number (CN) and initial abstraction ratio in the model parameters. Various parameters were be calibrated, according to the rainfall characteristics of a same rainfall, and then compared with the SCS model without parameter improvement. The results showed that the Root Mean Square Error (RMSE) of SCS-RF model and SCS model were 1.06 and 6.64, while the Nash-Sutcliffe Efficiency (NSE) were 0.84 and −8.65, respectively. Moreover, the SCS-RF model achieved an excellent performance in each basin, where the simulation effect of SCS-RF model was better than that of SCS model. The SCS-RF model also considered the influence of rainfall characteristics on runoff yield. The process of parameter calibration was simplified, thereby to enhance the universality of the model. The different treatment in the basin made the distribution of parameters significantly different from others. There was small fluctuation for the CN in Yangdaogou basin, and the initial abstraction ratio in the Chacaizhugou basin. The initial abstraction ratios were less than the standard value of 0.2, after the control of soil erosion. The distributions of CN were approximate, comparing with the two basins that were comprehensively treated but with different areas. Specifically, there was a large area fluctuation for the CN and initial abstraction ratio in the Wangjiagou basin, where the CN in Wangjiagou basin was larger than that of Chacaizhugou basin. The compared area was similar, where the Yangdaogou basin did not be treated, while the Chacaizhugou basin was treated. The initial abstraction ratio was small in the basin of Chacaizhugou, but fluctuated greatly in Yangdaogou basin, whereas, the CN fluctuation was small in Yangdaogou basin. It infers that the distribution of initial abstraction ratio was similar. There was a negative correlation between CN and rainfall P in each basin. The data distribution of parameters and rainfall characteristics (P, rainfall intensity in 30 min I30) had a relatively obvious concentration area. The rainfall-runoff simulation can provide a theoretical basis for the conservation planning of soil and water, as well as the management of water resources. [ABSTRACT FROM AUTHOR]

In order to reduce nonlinear and randomness of runoff series influence to the runoff forecasting and improve the prediction accuracy, based on the monthly runoff sequence of Shangjingyou Station, Fenhe Reservoir Station, Zhaishang Station and Lancun Station on the upper Fenhe River from 1958 to 2000, this paper put into the complete ensemble empirical mode decomposition and BP neural network, established the CEEMD-BP model for forecasting monthly runoff in the upper Fenhe River and compared the prediction results of single BP model and EMD-BP model. The results show that the mean absolute error and mean square root error of CEEMD-BP model at four hydrological stations are reduced by 53%-62% and 48%-65% respectively compared with the single BP model and reduced by 34%-46% and 30%-43% respectively compared with the EMD-BP model. The deterministic coefficient of CEEMD-BP model is greater than 0.9 and the prediction precision is Grade A. CEEMD-BP model is feasible and effective for prediction of runoff time series with nonlinear and non-stationary properties. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Yellow River is the property of Editorial Board of Yellow River and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To accurately evaluate the hydrologic drought, it is necessary to objectively construct the drought index. In this study, the data collected from two hydrologic stations in the upper reaches of Fenhe River basin were used as case studies. Firstly, the ability of the logistic, normal, two-parameter log-normal, and Weibull probability distributions was examined to choose the most suitable distribution function for establishing the standardized streamflow drought index (SSDI). Secondly, the hydrologic drought magnitudes were divided based on the characteristics of standard normal curve. Finally, the SSDI was compared with the Z index and departure index of streamflow. The typical records of drought and flood events in the Fenhe River basin were taken as evaluation standard, which was used to evaluate the applicability and rationality of the SSDI and drought magnitudes. The results showed that, the two-parameter log-normal distribution was selected as the best fitting function for monthly streamflow in the study area. The SSDI and the magnitudes were both coincident for the actual drought-flood severity. In addition, the occurrence of various hydrologic drought magnitudes was stable at various time scales. The conclusion could provide scientific basis of drought defense, disaster mitigation, and water supply planning measures for the upper reaches of Fenhe River basin. [ABSTRACT FROM AUTHOR]