Representation of land-use and hydrologic interactions in respective models has traditionally been problematic. The use of static land-use in most hydrologic models or that of the use of simple hydrologic proxies in land-use change models call for more integrated approaches. The objective of this study is to assess whether dynamic feedback between land-use change and hydrology can (1) improve model performances, and/or (2) produce a more realistic quantification of ecosystem services. To test this, we coupled a land-use change model and a hydrologic mode. First, the land-use change and the hydrologic models were separately developed and calibrated. Then, the two models were dynamically coupled to exchange data at yearly time-steps. The approach is applied to a catchment in South Africa. Performance of coupled models when compared to the uncoupled models were marginal, but the coupled models excelled at the quantification of catchment ecosystem services more robustly.

A web-based framework (AgriSuit) that integrates various global data from different sources for multi-criteria based agricultural land suitability assessment based on the Google Earth Engine (GEE) platform is developed and presented. The platform enables online data gathering, training and classifying of land cover classes based on remote sensing and GIS techniques, as well as computation of suitability of land-use classes for agricultural activities. A demonstration of the framework on the Upper Blue Nile basin in Ethiopia is presented.