|Student:||Harm-Jan Frederik Benninga|
|Timeline:||October 2015 - 4 October 2019|
Many deltas around the world experience increasing pressure on their water systems as a result of changes in supply and demand, caused by socio-economic developments and climate change. The challenge for regional water managers worldwide is to optimize the amount of water available for all functions according to their respective needs by either retaining or draining water. For skilful water management reliable up-to-date information on the current situation and models to evaluate the impact of control measures are indispensable.
Radar backscatter is known to be sensitive to the actual surface soil moisture state. The Sentinel-1 radar satellite programme provides a unique opportunity to monitor the water availability from space at unprecedented spatial and temporal resolutions. The OWAS1S project (Optimizing Water Availability with Sentinel-1 Satellites) stands for integration of the freely available global Sentinel-1 satellite data and local knowledge on soil physical processes, to optimize water management of regional water systems and to develop value-added products for agriculture. The OWAS1S project accommodates three PhD studies focusing on (1) the exploitation of the freely available Sentinel-1 images to retrieve soil moisture states (at UT-ITC), (2) the translation of surface soil moisture data to value-added products (at Wageningen University), and (3) the optimization of operational and strategic water management using spatiotemporal information (at UT-CTW) (see Figure 1).
Figure 1: Schematization of the OWAS1S project
In study (1) it will be investigated how the Sentinel-1 radar backscatter data can be used to retrieve reliable surface soil moisture states over agricultural fields on an operational basis with a method that is applicable to agricultural fields in general (not only applicable to a specific calibration situation). Three soil moisture retrieval methods will be studied, namely a data-driven method, inversion of a radar scattering model and downscaling of coarser resolution products. The retrieved surface soil moisture states will be validated against measurements from three soil moisture monitoring networks in the Netherlands, including the soil moisture monitoring network Twente which consists of 20 measurement locations. The soil moisture measurement stations are located at or near agricultural fields (see for an example Figure 2). Subsequently the surface soil moisture states will be used in a Land Surface Model (e.g. Noah-MP) to improve local-scale water and energy budget simulations and to simulate runoff from a local-scale ‘ungauged’ basin.
Figure 2: An agricultural field near one of the soil moisture
measurement stations in the Twente network