New Flood Risk Management Data Have Been Reported by Investigators at Chang’an University (Estimation of Extreme Rainfall Quantiles At Ungauged Sites In the Loess Plateau, China By Regional Frequency Analysis): Risk Management – Flood Risk Management

2022 OCT 12 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Current study results on Risk Management - Flood Risk Management have been published. According to news originating from Xi’an, People’s Republic of China, by NewsRx correspondents, research stated, “An increase in the frequency of extreme rainfall events has caused more severe floods than before under the influence of climate change, and is receiving a lot of attention in data-scarce areas like the Loess Plateau, especially in some small basins without hydrometeorological data, and to avert the risk of disaster needs the estimation of extreme rainfall quantiles. In this study, generalized additive models (GAM) are combined with a nonlinear canonical correlation analysis (NLCCA) procedure to estimate extreme rainfall quantiles at ungauged sites in the Wei River basin on the Loess Plateau.”

Financial supporters for this research include National Natural Science Foundation of China (NSFC), Natural Science Basic Research Program of Shaanxi.

Our news journalists obtained a quote from the research from Chang’an University, “Also, the single inverse distance weighting (IDW) interpolation, NLCCA-backpropagation (BP), and NLCCA-radial basis function (RBF) models were used as comparative methods for testing the efficiency of the NLCCA-GAM model. Because meteorological data are generally lacking in rainfall-ungauged basins, data at ungauged sites was interpolated by IDW interpolation when NLCCA delineated homogeneous regions. Results of validation indicated that maximum daily rainfall quantiles in the Loess Plateau were well estimated by NLCCA-GAM-based regional frequency analysis, implying the NLCCA-GAM is a useful tool for estimating design extreme rainfall in ungauged basins. Results of comparison demonstrated that NLCCA-GAM was more robust and better reflected the nonlinear relationship between explanatory and response variables in the region than did comparative approaches.”

According to the news editors, the research concluded: “In addition, it was found that the NLCCA-GAM approach made full use of the data from sites in homogeneous regions to mine the valuable nonlinear correlation between ungauged and gauged sites and estimate extreme rainfall quantiles at ungauged sites.”

For more information on this research see: Estimation of Extreme Rainfall Quantiles At Ungauged Sites In the Loess Plateau, China By Regional Frequency Analysis. Journal of Flood Risk Management, 2022. Journal of Flood Risk Management can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - http://www.wiley.com/; Journal of Flood Risk Management - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1753-318X)

The news correspondents report that additional information may be obtained from Hongbo Zhang, Chang’an University, Sch Water & Environm, Xian 710064, People’s Republic of China. Additional authors for this research include Jingru Zhang, Shuting Shao, Hao Ding, Yanrui Wu and Vijay P. Singh.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/jfr3.12853. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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