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Forecasting reservoir inflows using remotely sensed precipitation estimates: a pilot study for the River Naryn, Kyrgyzstan

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journal contribution
posted on 2016-01-25, 10:46 authored by Samuel G. Dixon, Robert WilbyRobert Wilby
This study explores the feasibility of applying remotely sensed precipitation estimates (in this case from the Tropical Rainfall Measuring Mission [TRMM]) for forecasting inflows to the strategically important Toktogul reservoir in the Naryn basin, Kyrgyzstan. Correlations between observed precipitation at Naryn and 0.5° TRMM totals is weaker for daily (r = 0.25) than monthly (r = 0.93) totals, but the Naryn gauge is representative of monthly TRMM precipitation estimates across ~60% of the basin. We evaluate predictability of monthly inflows given TRMM estimates, air temperature and antecedent flows. Regression model skill was superior to the zero order forecast (mean flow) for lead-times up to three months, and had lower errors in estimated peaks. Over 80% of the variance in monthly inflows is explained with three-month lead, and up to 65% for summer half-year average. The analysis also reveals zones that are delivering highest predictability and hence candidate areas for surface network expansion.

History

School

  • Social Sciences

Department

  • Geography and Environment

Published in

Hydrological Sciences Journal

Citation

DIXON, S.G. and WILBY, R.L., 2015. Forecasting reservoir inflows using remotely sensed precipitation estimates: a pilot study for the River Naryn, Kyrgyzstan. Hydrological Sciences Journal, 61(1), pp. 107-122.

Publisher

© IAHS. Published by Taylor & Francis

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

This is an Accepted Manuscript of an article published by Taylor & Francis in Hydrological Sciences Journal on 11/11/2015, available online: http://wwww.tandfonline.com/10.1080/02626667.2015.1006227.

ISSN

0262-6667

eISSN

2150-3435

Language

  • en

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