Using meteorological data to forecast seasonal runoff on the River Jhelum, Pakistan

被引:102
作者
Archer, D. R. [1 ]
Fowler, H. J. [2 ]
机构
[1] JBA Consulting, Skipton BD23 3AE, N Yorks, England
[2] Newcastle Univ, Sch Civil Engn & Geosci, Water Resource Syst Res Lab, Newcastle Upon Tyne, Tyne & Wear, England
基金
英国自然环境研究理事会;
关键词
River Jhelum; Seasonal flow forecasting; Summer runoff; Multiple linear regression; Water management;
D O I
10.1016/j.jhydrol.2008.07.017
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The upper River Jhelum, which drains the southern slopes of the Himalaya and Pir Panjal, provides water for power and irrigated agriculture, the mainstay of the national economy of Pakistan. Seasonal forecasts of spring and summer flow provide the opportunity for planning and would confer significant national benefits. In this mountainous region, runoff from snowmelt and glacier-melt provides the dominant contribution to river flows during the spring and summer seasons although monsoon rainfall may also influence peak flows. Estimates of runoff in the Jhelum and its main tributaries can be made using precipitation measurements from valley stations; producing correlation coefficients of >0.7 between winter precipitation and spring and summer runoff. This study investigates the links between climate and runoff for eight gauging stations in the Jhelum catchment but then concentrates on seasonal forecasting of spring and summer inflows to Mangla Dam which is a major controlling structure contributing to the Indus Basin Irrigation System. Observed climatic variabtes, precipitation and temperature, from valley stations are used to forecast summer season flows at stations upstream from the reservoir with a lead time of up to three months based on multiple linear regression models built using data from 1965 to 1979. The analysis demonstrates that good forecasts within 15% of observed flows for 92% of years (ROC score = 0.77) can be achieved for summer season flows from April to September over the 1980-1991 validation period. For spring flows from April to June, excellent forecasts can be provided within 15% of observed flows for 83% of years, with a ROC score of 0.93. These provide a useful basis for practical. water management. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:10 / 23
页数:14
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