The afforestation actions in China have attracted widely attention in recent years. This paper presents a hydro-ecological modeling approach to assess environmental changes and ecosystem services in the largest inland river basin in China. Our result indicates China's tree-planting in the Tarim River Basin is strictly strained by water stress and 25.9 % of the existing area of natural vegetation will be degraded by 2050. It is a warning for decision-makers and stakeholders.

This study investigates the use of measured water levels to reduce uncertainty bounds of two-dimensional hydrodynamic model output. Uncertainty assessment is generally not reported in practice due to the lack of best practices and too wide uncertainty bounds. Hence, a novel method to reduce the bounds by constraining the model parameter, mainly roughness, is presented. The operational practitioners as well as researchers benefit from the study in the field of flood risk management.

Understanding responses by changes in land use and land cover (LULC) and climate over the past decades on streamflow in the upper Blue Nile River basin is important for water management and water resource planning. Streamflow in the UBNRB has shown an increasing trend over the last 40 years, while rainfall has shown no trend change. LULC change detection findings indicate increases in cultivated land and decreases in forest coverage prior to 1995.

We study flood protection options in a pre-alpine catchment in southern Germany. Protection systems are evaluated probabilistically, taking into account climatic and other uncertainties as well as the possibility of future adjustments. Despite large uncertainty in damage, cost, and climate, we arrive at a rough recommendation. Hence, one can make good decisions under large uncertainty. The results also show it is preferable to plan risk-based rather than protecting from a specific design flood.

In this study we used multimodel GCMs (because of recognized intervariable biases in host GCMs) and two widely used statistical downscaling techniques (LARS-WG and SDSM) to see comparative performances in the Upper Blue Nile River basin, where there is high climate variability. The result from the two downscaling models suggested that both SDSM and LARS-WG approximate the observed climate data reasonably well and project an increasing trend for precipitation and maximum and minimum temperature.

In this research, SWAT was used to model the upper Blue Nile Basin where comparisons between ground and CFSR data were done. Furthermore, this paper introduced the SWAT error index (SEI), an additional tool to measure the level of error of hydrological models. This work proposed an approach or methodology that can effectively be followed to create better and more efficient hydrological models.