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Frequency estimates of extreme precipitation are revised using a regional L-moments method based on the annual maximum series and Chow’s equation at lower return periods for the Jiangsu area in China. First, the study area is divided into five homogeneous regions, and the optimum distribution for each region is determined by an integrative assessment. Second, underestimation of quantiles and the applicability of Chow’s equation are verified. The results show that quantiles are underestimated based on the annual maximum series, and that Chow’s formula is applicable for the study area. Next, two methods are used to correct the underestimation of frequency estimation. A set of rational and reliable frequency estimations is obtained using the regional L-moments method and the two revised methods, which can indirectly provide a robust basis for flood control and water resource management. This study extends previous works by verifying underestimation of the quantiles and the provision of two improved methods for obtaining reliable quantile estimations of extreme precipitation at lower recurrence intervals, especially in solving reliable estimates for a 1-year return period from the integral lower limit of the frequency distribution.
Yuehong Shao; Jun Zhao; Jinchao Xu; Aolin Fu; Junmei Wu. Revision of Frequency Estimates of Extreme Precipitation Based on the Annual Maximum Series in the Jiangsu Province in China. Water 2021, 13, 1832 .
AMA StyleYuehong Shao, Jun Zhao, Jinchao Xu, Aolin Fu, Junmei Wu. Revision of Frequency Estimates of Extreme Precipitation Based on the Annual Maximum Series in the Jiangsu Province in China. Water. 2021; 13 (13):1832.
Chicago/Turabian StyleYuehong Shao; Jun Zhao; Jinchao Xu; Aolin Fu; Junmei Wu. 2021. "Revision of Frequency Estimates of Extreme Precipitation Based on the Annual Maximum Series in the Jiangsu Province in China." Water 13, no. 13: 1832.
High-precision areal rainfall is crucial for hydrometeorological coupled forecasts. The accuracy of quantitative precipitation estimates (QPE) is improved by merging radar-rain gauge data with an integration approach based on a statistical weight matrix in the Yishu River catchment, China. First, a local Z-R relationship (Z = 85R1.82) is reconstructed using a genetic optimization algorithm to minimize the error from different precipitation patterns and climate zones. Next, based on the local Z-R relationship, six methods of merging radar-rain gauge data are respectively adapted to improve the accuracy of QPE, as follows: mean field bias (MFB), Kalman filter (KLM), optimum interpolation (OPT), variation method (VAR), two-step calibration of KLM and OPT (KOP), and two-step calibration of KLM and VAR (KVR). The results indicate that QPE accuracy is clearly improved, and is in good agreement with rain gauge observations, after the six merging methods are applied. Among these methods, KOP performs the best, reducing the mean relative error from 55.2 to 15.1%. An innovative aspect of this work is the inclusion of an integrated ideology based on a statistical weight matrix, which further improves the accuracy of QPE by incorporating the advantages of each estimation mode. The results further show that the accuracy of QPE derived from the integration approach is higher than that obtained by any individual method; QPE values are similar to those obtained the automatic rain gauge network in both the spatial distribution and location of the intense precipitation centers, and better reflects the precipitation status over the ground surface. This approach could serve as a promising conventional method for QPE in the study region.
Yuehong Shao; Aolin Fu; Jun Zhao; Jinchao Xu; Junmei Wu. Improving quantitative precipitation estimates by radar-rain gauge merging and an integration algorithm in the Yishu River catchment, China. Theoretical and Applied Climatology 2021, 144, 611 -623.
AMA StyleYuehong Shao, Aolin Fu, Jun Zhao, Jinchao Xu, Junmei Wu. Improving quantitative precipitation estimates by radar-rain gauge merging and an integration algorithm in the Yishu River catchment, China. Theoretical and Applied Climatology. 2021; 144 (1-2):611-623.
Chicago/Turabian StyleYuehong Shao; Aolin Fu; Jun Zhao; Jinchao Xu; Junmei Wu. 2021. "Improving quantitative precipitation estimates by radar-rain gauge merging and an integration algorithm in the Yishu River catchment, China." Theoretical and Applied Climatology 144, no. 1-2: 611-623.
Under the background analysis of water issues, water environment random evaluation model based on Bayesian theory is put forward to universally describe and physically analyze the uncertainty information. Guided by the viewpoint of sustainable development, this study applies water conservancy science, intelligence science and information science to discuss about risk indexes from three aspects of water quantity, water quality, and water ecology with the evolution mechanism of water environment. The evaluation index system is selected by qualitative analysis and quantitative calculation, and index weight is determined by the improved TOPSISI method. The Bayesian theory is employed to set up the random evaluation model. The process is to obtain posterior distribution by prior distribution with sample information. Then, the evaluation levels of water environment are given by the principle of probability maximization with advancing the control policy. Taihu Basin, China is taken as an example. It shows that the proposed model is rigorous with theory, flexible with method, and reasonable with results, providing a new way for studying water resources shortage, water pollution prevention, and water ecology protection, which can be widely applied to water environment management.
Jinchao Xu; Yaqian Chen; Jun Zhao; Qingfeng Hang; Xuechun Li. Water Environment Random Evaluation Model based on the improved TOPSIS method and Bayesian Theory and its Application. Water Resources 2019, 46, 344 -352.
AMA StyleJinchao Xu, Yaqian Chen, Jun Zhao, Qingfeng Hang, Xuechun Li. Water Environment Random Evaluation Model based on the improved TOPSIS method and Bayesian Theory and its Application. Water Resources. 2019; 46 (3):344-352.
Chicago/Turabian StyleJinchao Xu; Yaqian Chen; Jun Zhao; Qingfeng Hang; Xuechun Li. 2019. "Water Environment Random Evaluation Model based on the improved TOPSIS method and Bayesian Theory and its Application." Water Resources 46, no. 3: 344-352.
Generally, the operation of the horizontally-framed miter gate in a ship lock should consider the effects of hydrodynamic resistance. If over-filling or over-emptying exists and the miter gate opens with reverse head, the hydrodynamic resistance will increase rapidly, endangering the operation safety of the miter gate. In order to study the operating characteristics of the miter gate, a prototype test is introduced in this paper. Results show that, during the filling or emptying process, when water levels at both sides of the miter gate are equal the first time, opening the gate in a timely manner can obviously avoid the influence of reverse head. Furthermore, a three-dimensional numerical model with a dynamic mesh is established for analyzing the hydrodynamic characteristics in different operating conditions. Results show that the peak value of operating load always occurs at the initial time, and the greater the submerged water depth, the larger the peak value. With the increasing of reverse head, the piston rods sustain a great compression, and the peak value appears at an early stage of gate opening. The results have a reference value for the design of a miter gate in the related engineering projects.
Jinchao Xu; Qiong Chen; Yun Li; Jianxu Zhou; Jianfeng An; Xiujun Yan; Yan Guo. Study on the Hydrodynamic Resistance Moment of Horizontally-Framed Miter Gates. Water 2018, 10, 1345 .
AMA StyleJinchao Xu, Qiong Chen, Yun Li, Jianxu Zhou, Jianfeng An, Xiujun Yan, Yan Guo. Study on the Hydrodynamic Resistance Moment of Horizontally-Framed Miter Gates. Water. 2018; 10 (10):1345.
Chicago/Turabian StyleJinchao Xu; Qiong Chen; Yun Li; Jianxu Zhou; Jianfeng An; Xiujun Yan; Yan Guo. 2018. "Study on the Hydrodynamic Resistance Moment of Horizontally-Framed Miter Gates." Water 10, no. 10: 1345.