Enhancing data fusion, parallelisation for hydrological modelling and estimating sensitivity to spatial parameterization of SWAT to model nitrogen and phosphorus runoff at local and global scale
The widely used Soil and Water Assessment Tool (SWAT) is a spatially distributed model that can be used to estimate flow and nutrient transport at a variety of scales. The proposed project aims to investigate how spatial resolution of core input datasets of all types (precipitation, DEM, land use and soil) impacts SWAT modelling results and estimate the nutrient runoff on a local and global scale.
Sensitivity analysis to all of precipitation, DEM, land use and soil will therefore be tested. However, due to higher resolution or global scale data the computational effort becomes too large for automated calibration. In order to surpass these limitations, we test novel ways of data management and model data partitioning and apply the MapReduce framework as a method for parallelization.
H2020 Marie Sklodowska Curie Individual Fellowship, PI Alexander Kmoch 1.09.2019−31.08.2021
