This study intends to contribute to the ongoing discussion on whether land use and land cover changes (LULC) or climate trends have the major influence on the observed increase of flood magnitudes in the Sahel. A simulation-based approach is used for attributing the observed trends to the postulated drivers. For this purpose, the ecohydrological model SWIM (Soil and Water Integrated Model) with a new, dynamic LULC module was set up for the Sahelian part of the Niger River until Niamey, including the main tributaries Sirba and Goroul. The model was driven with observed, reanalyzed climate and LULC data for the years 1950-2009. In order to quantify the shares of influence, one simulation was carried out with constant land cover as of 1950, and one including LULC. As quantitative measure, the gradients of the simulated trends were compared to the observed trend. The modeling studies showed that for the Sirba River only the simulation which included LULC was able to reproduce the observed trend. The simulation without LULC showed a positive trend for flood magnitudes, but underestimated the trend significantly. For the Goroul River and the local flood of the Niger River at Niamey, the simulations were only partly able to reproduce the observed trend. In conclusion, the new LULC module enabled some first quantitative insights into the relative influence of LULC and climatic changes. For the Sirba catchment, the results imply that LULC and climatic changes contribute in roughly equal shares to the observed increase in flooding. For the other parts of the subcatchment, the results are less clear but show, that climatic changes and LULC are drivers for the flood increase; however their shares cannot be quantified. Based on these modeling results, we argue for a two-pillar adaptation strategy to reduce current and future flood risk: Flood mitigation for reducing LULC-induced flood increase, and flood adaptation for a general reduction of flood vulnerability.
Measure plans are currently being developed for the Water Framework Directive (WFD) by European water authorities. In Sweden, such plans include measures for good ecological status in the coastal ecosystem. However, the effect of suggested measures is not yet known. We therefore experimented with different nutrient reduction measures on land and in the sea, using a model system of two coupled dynamic models for a semi-enclosed bay and its catchment. The science question was whether it is worthwhile to implement measures in the local catchment area to reach local environmental goals, or if the status of the Bay is more governed by the water exchange with the Sea. The results indicate that by combining several measures in the catchment, the nutrient load can be reduced by 15%-20%. To reach the same effect on nutrient concentrations in the Bay, the concentrations of the sea must be reduced by 80%. Hence, in this case, local measures have a stronger impact on coastal water quality. The experiment also show that the present targets for good ecological status set up by the Swedish water authorities may be unrealistic for this Bay. Finally, we discuss when and how to use hydro-ecological models for societal needs.
This investigation reports on a new national model to evaluate the effectiveness of catchment sensitive farming in England, and how pollution mitigation measures have improved water quality between 2006 and 2016. An adapted HYPE (HYdrological Predictions for the Environment) model was written to use accurate farm emissions data so that the pathway impact could be accounted for in the land phase of transport. Farm emissions were apportioned into different runoff fractions simulated in surface and soil layers, and travel time and losses were taken into account. These were derived from the regulator's catchment change matrix' and converted to monthly load time series, combined with extensive point source load datasets. Very large flow and water quality monitoring datasets were used to calibrate the model nationally for flow, nitrogen, phosphorus, suspended sediments and faecal indicator organisms. The model was simulated with and without estimated changes to farm emissions resulting from catchment measures, and spatial and temporal changes to water quality concentrations were then assessed.
The impact of climate change on the hydro-climatology of the Indian subcontinent is investigated by comparing statistics of current and projected future fluxes resulting from three RCP scenarios (RCP2.6, RCP4.5, and RCP8.5). Climate projections from the CORDEX-South Asia framework have been bias-corrected using the Distribution-Based Scaling (DBS) method and used to force the HYPE hydrological model to generate projections of evapotranspiration, runoff, soil moisture deficit, snow depth, and applied irrigation water to soil. We also assess the changes in the annual cycles in three major rivers located in different hydro-climatic regions. Results show that conclusions can be influenced by uncertainty in the RCP scenarios. Future scenarios project a gradual increase in temperature (up to 7 degrees C on average), whilst changes (both increase and decrease) in the long-term average precipitation and evapotranspiration are more severe at the end of the century. The potential change (increase and decrease) in runoff could reach 100% depending on the region and time horizon. Analysis of annual cycles for three selected regions showed that changes in discharge and evapotranspiration due to climate change vary between seasons, whereas the magnitude of change is dependent on the region's hydro-climatic gradient. Irrigation needs and the snow depth in the Himalayas are also affected.