Jongho Kim

TL;DR: The use of process-based hydrological models has a long history dating back to the 1960s as mentioned in this paper, and a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrologogical model.

TL;DR: An intercomparison study of seven coupled surface-subsurface models based on a series of benchmark problems shows good agreement for the simpler test cases, while the more complicated test cases bring out some of the differences in physical process representations and numerical solution approaches between the models.

TL;DR: In this article, a coupling framework between a hydrologic model and a hydrodynamic model has been developed, which considers spatially-distributed, physically-based hydrology processes over the land-surface and subsurface by using the TIN (Triangulated Irregular Network)-based Real Time Integrated Basin Simulator (tRIBS).

TL;DR: In this paper, the authors apply a comprehensive stochastic downscaling technique to climate model outputs for three exemplary locations and show that the evidence of the predominant role of internal climate variability leaves little room for uncertainty reduction in precipitation projections; however, the inference is not necessarily negative, since the uncertainty of historic observations is almost as large as that for future projections with direct implications for climate change adaptation measures.

TL;DR: In this article, a two-dimensional, physically based model of soil erosion and sediment transport coupled to models of hydrological and overland flow processes has been developed, which is integrated within the framework of the hydrologic and hydrodynamic model tRIBS-OFM, Triangulated irregular network-based, Real-time Integrated Basin Simulator-Overland Flow Model.