Surface Water Derivation with WaMaPro to support hydrological applications

Kurzfassung

The extent of water surfaces and their inherent temporal dynamics are key parameters governing the hydrological cycle. Information on water surfaces such as delineation of water extent, permanent water bodies, partially and temporarily inundated regions, and flooded areas, as well as on specific surface water dynamics is considered beneficial for hydrological modelling purposes. Numerous research groups active in hydrological modelling have included surface water datasets derived on the basis of satellite remote sensing in their models for calibration and validation purposes. This presentation gives an overview of WaMaPro – that stands for WaterMaskProcessor – a watermask generation approach for earth observation-based surface water detection from radar remote sensing data developed at DLR-DFD. Furthermore, the integration of watermask information products in hydrological modelling approaches is presented. Examples from joint research application projects are given for the Mekong Delta in Vietnam and the Yellow River Delta in China, where surface water information generated with WaMaPro has been already used for the calibration of regional hydrological models, as well as for setting boundary conditions of hydrodynamical models. The methodological background of WaMaPro will be briefly outlined and advantages of using active satellite remote sensing data – such as Sentinel-1, TerraSAR-X, and Envisat-ASAR – will be presented especially for regions on Earth were the generation of time series of high temporal resolution, that is necessary for hydrological applications, is nearly impossible to be acquired from optical data related to persistent cloud cover. The implementation of WaMaPro is based on Python language as a plug-in for the well-known open source GIS software Quantum GIS. Therefore, this software can be shared with interested potential users of a large community without inflicting any license fees. The tool has been designed for the usage by scientists and aims to support even non-experts and remote sensing beginners to easily and effective derive water surface information.