DOI: 10.1016/j.gloplacha.2016.10.018
论文题名: Seasonal predictions of precipitation in the Aksu-Tarim River basin for improved water resources management
作者: Hartmann H. ; Snow J.A. ; Su B. ; Jiang T.
刊名: Global and Planetary Change
ISSN: 0921-8181
出版年: 2016
卷: 147 起始页码: 86
结束页码: 96
语种: 英语
英文关键词: Artificial neural networks
; Precipitation
; Seasonal predictions
; Tarim River basin
; Water resources
Scopus关键词: Atmospheric temperature
; Climatology
; Forecasting
; Linear regression
; Neural networks
; Oceanography
; Precipitation (chemical)
; Precipitation (meteorology)
; Rain
; Rivers
; Surface waters
; Water management
; Watersheds
; Artificial neural network modeling
; Multi layer perceptron
; Multiple linear regressions
; Sea surface temperature (SST)
; Seasonal prediction
; Spearman rank correlation
; Tarim River basin
; Water resources management
; Water resources
英文摘要: Since the 1950s, the population in the arid to hyperarid Tarim River basin has grown rapidly concurrent with an expansion of irrigated agriculture. This threatens the Tarim River basin's natural ecosystems and causes water shortages, even though increased discharges in the headwaters have been observed more recently. These increases have mainly been attributed to receding glaciers and are projected to cease when the glaciers are unable to provide sufficient amounts of meltwater. Under these circumstances water management will face a serious challenge in adapting its strategies to changes in river discharge, which to a greater extent will depend on changes in precipitation. In this paper, we aim to develop accurate seasonal predictions of precipitation to improve water resources management. Possible predictors of precipitation for the Tarim River basin were either downloaded directly or calculated using NCEP/NCAR Reanalysis 1 and NOAA Extended Reconstructed Sea Surface Temperature (SST) V3b data in monthly resolution. To evaluate the significance of the predictors, they were then correlated with the monthly precipitation dataset GPCCv6 extracted for the Tarim River basin for the period 1961 to 2010. Prior to the Spearman rank correlation analyses, the precipitation data were averaged over the subbasins of the Tarim River. The strongest correlations were mainly detected with lead times of four and five months. Finally, an artificial neural network model, namely a multilayer perceptron (MLP), and a multiple linear regression (LR) model were developed each in two different configurations for the Aksu River subbasin, predicting precipitation five months in advance. Overall, the MLP using all predictors shows the best performance. The performance of both models drops only slightly when restricting the model input to the SST of the Black Sea and the Siberian High Intensity (SHI) pointing towards their importance as predictors. © 2016 Elsevier B.V. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994803138&doi=10.1016%2fj.gloplacha.2016.10.018&partnerID=40&md5=961a540aec4d1b5cebe32d8dfae5ab20
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/11594
Appears in Collections: 全球变化的国际研究计划 气候变化与战略
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作者单位: Department of Geography, Geology and the Environment, Slippery Rock University, Slippery Rock, PA, United States
Recommended Citation:
Hartmann H.,Snow J.A.,Su B.,et al. Seasonal predictions of precipitation in the Aksu-Tarim River basin for improved water resources management[J]. Global and Planetary Change,2016-01-01,147.