Satellite rainfall for crop growth modelling
This study aims to assess the applicability of satellite rainfall estimates (SRE) in crop growth modelling by means of the Aquacrop model. Any misrepresentation of rainfall data can propagate to affect the outcome and performance of a crop growth model by misrepresenting soil moisture storage in the model, which leads to inaccurate and unreliable biomass estimates. For this study (very) high-quality in-situ rainfall data is available for the period 2012 to 2018. The area of study will be the Lake Victoria basin in Kenya. The topic is directly related to an ongoing Ph.D. study at WRS department.
The study aims to assess crop growth for each crop growth stage by comparing biomass for in-situ rainfall, uncorrected and bias-corrected Spatial Rainfall Estimates (SRE). The study targets three SRE products, and three bias correction methods. The FAO based Aquacrop model is selected for crop growth simulation. As a final output, the study targets the development of an ensemble SRE rainfall product based on the three selected SRE rainfall products.
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