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JDR Vol.12 No.4 pp. 793-805
doi: 10.20965/jdr.2017.p0793
(2017)

Paper:

A Study on Flood Forecasting in the Upper Indus Basin Considering Snow and Glacier Meltwater

Tong Liu*,†, Morimasa Tsuda*, and Yoichi Iwami**

*International Centre for Water Hazard and Risk Management (ICHARM) under the auspices of UNESCO, Public Works Research Institute
1-6 Minamihara, Tsukuba, Ibaraki 305-8516, Japan

Corresponding author

**Public Works Department, Nagasaki Prefectural Government, Nakagaki, Japan

Received:
June 10, 2016
Accepted:
May 11, 2017
Online released:
July 28, 2017
Published:
August 1, 2017
Keywords:
flood, hydrological modeling, glaciermelt, snowmelt, Indus River
Abstract

This study considered glacier and snow meltwater by using the degree–day method with ground-based air temperature and fractional glacier/snow cover to simulate discharge at Skardu, Partab Bridge (P. Bridge), and Tarbela Dam in the Upper Indus Basin during the monsoon season, from the middle of June to the end of September. The optimum parameter set was determined and validated in 2010 and 2012. The simulated discharge with glaciermelt and snowmelt could capture the variations of the observed discharge in terms of peak volume and timing, particularly in the early monsoon season. The Moderate Resolution Imaging Spectroradiometer (MODIS) daily and eight-day snow cover products were applied and recommended with proper settings for application. This study also investigated the simulations with snow packs instead of daily snow cover, which was found to approach the maximum magnitude of observed discharge even from the uppermost station, Skardu.

This study estimated the glacier and snow meltwater contribution at Skardu, Partab Bridge, and Tarbela as 43.2–65.2%, 22.0–29.3%, and 6.3–19.9% of average daily discharge during the monsoon season, respectively. In addition, this study evaluated the main source of simulation discrepancies and concluded that the methodology proposed in the study worked well with proper precipitation.

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Last updated on Oct. 20, 2017