Monthly hydropower prediction at plant scale in data-scarce regions

Hydropower is currently the largest renewable energy generation method worldwide, being the third overall after coal and natural gas, and providing 15% of global electricity. However, generation data regarding hydropower is scarce. If available, it mostly exists at national and annual level. Only limited generation data is available at plant...

A satellite-image-based method to overcome data scarcity for river morphodynamic modelling

Daily flow simulation in Thailand Part I: Testing a distributed hydrological model with seamless parameter maps based on global data

Study region Upper region of the Greater Chao Phraya River (GCPR) basin in Thailand. Study focus This study presents a (∼1 km resolution) distributed hydrological model, wflow_sbm, with global spatial data and parameterization for estimating daily streamflow in the upper GCPR basin, with the aim to overcome in situ data scarcity often occurring...

Bed composition generation for morphodynamic modeling: Case study of San Pablo Bay in California, USA

Applications of process-based morphodynamic models are often constrained by limited availability of data on bed composition, which may have a considerable impact on the modeled morphodynamic development. One may even distinguish a period of “morphodynamic spin-up” in which the model generates the bed level according to some ill-defined initial...