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Copernicus Publications, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, (XLII-3), p. 1461-1465, 2018

DOI: 10.5194/isprs-archives-xlii-3-1461-2018

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Analysis of the Tonle Sap Flood Pulse Based on Remote Sensing: How Much Does Tonle Sap Lake Affect the Mekong River Flood?

Journal article published in 2018 by W. Qu, N. Hu, J. Fu, J. Lu, H. Lu ORCID, T. Lei, Z. Pang, X. Li, L. Li
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Abstract. The economic value of the Tonle Sap Lake Floodplain to Cambodia is among the highest provided to a nation by a single ecosystem around the world. The flow of Mekong River is the primary factor affecting the Tonle Sap Lake Floodplain. The Tonle Sap Lake also plays a very important role in regulating the downstream flood of Mekong River. Hence, it is necessary to understand its temporal changes of lake surface and water storage and to analyse its relation with the flood processes of Mekong River. Monthly lake surface and water storage from July 2013 to May 2014 were first monitored based on remote sensing data. The relationship between water surface and accumulative water storage change was then established. In combination with hydrological modelling results of Mekong River Basin, the relation between the lake’s water storage and the runoff of Mekong River was analysed. It is found that the water storage has a sharp increase from September to December and, after reaching its maximum in December, water storage quickly decreases with a 38.8 billion m3 of drop in only half month time from December to January, while it keeps rather stable at a lower level in other months. There is a two months’ time lag between the maximum lake water storage and the Mekong River peak flood, which shows the lake’s huge flood regulation role to downstream Mekong River. It shows that this remote sensing approach is feasible and reliable in quantitative monitoring of data scarce lakes.