The study assesses the effect of climate and land use change on water resources and soil ero-sion in the Dano catchment, Burkina Faso. Field measurements and derived process under-standing are complemented by a physically based modeling approach that is also used to simu-late the impact of land use and climate change. Extensive hydro-meteorological (e. g. precipitation, discharge), pedological (e. g. texture, bulk density) and soil erosion measurements (e. g. suspended sediment load) are investigated to gain knowledge on governing hydrological and soil erosion processes. Data from erosion plot measurements suggest statistically significant differences of runoff and soil erosion between differently used plots. The data and the retrieved understanding are used to setup and drive the physically based spa-tially distributed hydrological and soil erosion model SHETRAN. Statistical performance measures (R², NSE, KGE) range between 0.66 and 0.8 for the calibration and validation of dis-charge. Achieved quality measures of suspended sediment load are lower than for hydrology but comparable to other SHETRAN studies. The impact of land use and land cover (LULC) change on water resources and soil erosion is studied by applying observed and modeled land use maps to the period 1990 – 2030. The past LULC change is studied using land use maps of the years 1990, 2000, 2007 and 2013. Based on these maps future LULC scenarios were developed for the years 2019, 2025 and 2030. Ob-served and modeled climate data cover the period 1990 – 2030. The observed past and modeled future LULC maps are used to feed SHETRAN. The isolated and combined influence of LULC and climate change is investigated. The land use investigation from 1990 to 2013 suggests a decrease of savanna at annual rates of 1.15% while cropland and settlement areas have increased. The simulations that assumed a constant climate and a changing LULC show in-creasing water yield (3.9% – 77.5%) and mainly increasing specific sediment yield (-1.4% – 115.78%). The simulations that assume constant LULC and climate as changing factor indicate increases in water yield of 24.5% to 46.7% and in sediment yield of 31.1% to 54.7%. The com-bined application of LULC and climate change signals a clear increase in water yield (20.3% – 73.4%) and specific sediment yield (24.7% to 90.1%). Actual evapotranspiration is estimated to change across all simulations by -6.8% to 3.35%. The predicted climate change signal is investigated in detail by comparing the future period 2021 – 2050 with the historical period 1971 – 2000. Representative concentration pathways (RCP) 4.5 and 8.5 of six datasets of the CORDEX framework were used to study the future change in tem-perature and precipitation. Most of the used climate models predict an increase of temperature between 0.9°C and 2.0°C. Large uncertainties among the climate models exist regarding the climate change signal of future precipitation. Some climate models predict an increase (5.9% – 36.5%) others a decreased (6.4% – 10.9%) or a mixed signal. The application of the historical and future climate data to SHETRAN shows that future changes in discharge and specific sedi-ment yield follow the predicted precipitation signal. Simulated future discharge change ranges from -43% to +207%. The future change in sediment yield is in the same order.

This map shows the spatial soil erosion and deposition pattern as simulated by the hydrological and soil erosion model SHETRAN. A general discussion on the creation of this map and the uncertainty is given under: http://www.mdpi.com/2073-4441/9/2/101

This study presents the calibration and validation of the physically based spatially distributed hydrological and soil erosion model SHETRAN for the Dano catchment, Burkina Faso. A sensitivity analysis of six model parameters was performed to assess the model response and to reduce the number of parameters for calibration. The hydrological component was calibrated and validated using observed discharge data of two years. Statistical quality measures (R2, NSE, KGE) ranged from 0.79 to 0.66 during calibration and validation. The calibrated hydrological component was used to feed the erosion modeling. The simulated suspended sediment load (SSL) was compared with turbidity‐based measurements of SSL of two years. Achieved quality measures are comparable to other SHETRAN studies. Uncertainties of measured discharge and suspended sediment concentration were determined to assess the propagated uncertainty of SSL. The comparison of measurement uncertainties of discharge and SSL with parameter uncertainty of the corresponding model output showed that simulated discharge and SSL were frequently outside the large measured uncertainty bands. A modified NSE was used to incorporate measurement and parameter uncertainty into the efficiency evaluation of the model. The analyses of simulated erosion sources and spatial patterns showed the importance of river erosion contributing more than 60% to the total simulated sediment loss.

Soil erosion is recognized as one main reason for soil degradation in West Africa. However, predictions on the impact of climate change on soil erosion are rare for most West African countries including Burkina Faso. This study assesses the impact of climate change on water resources and soil erosion in a small catchment (126 km2) in southwestern Burkina Faso. Climate data from an ensemble of six regional (RCM) and global (GCM) climate models were used to run the physically based spatially distributed hydrological and soil erosion model SHETRAN. The Representative Concentration Pathways (RCPs) 4.5 and 8.5 were selected as future climate scenarios. Bias corrected precipitation and temperature required for the calculation of potential evapotranspiration were used as input for the SHETRAN model to simulate total discharge and specific suspended sediment yield (SSY). Discharge and SSY from simulations run with climate data were able to reproduce discharge and SSY from a simulation that used observed precipitation and temperature from the historical period (1971–2000). The impact of climate change on hydrology and soil erosion was assessed by comparing the historical period with the future climate scenarios (2021–2050). Most of the used climate models predict an increase of temperature between 0.9 °C and 2.0 °C. The bias correction did not alter the climate change signal of temperature. Large uncertainties among the RCMs-GCMs exist regarding the climate change signal of future precipitation. Some climate models predict an increased (5.9%–36.5%) others a decreased (6.4%–10.9%) or mixed signal. The applied bias correction did not reverse the climate change signal in most cases but it influenced magnitude and timing of precipitation. The ensemble mean suggests an increased discharge between 19.5% (RCP 8.5) and 36.5% (RCP4.5) and an increased SSY of the same order. In general, the climate change signal and the corresponding discharge and SSY predictions are afflicted with large uncertainties. These uncertainties impede direct conclusions regarding future development of discharge and erosion. As a consequence of the mixed signals, potential increase and decrease of future discharge and soil erosion have to be incorporated in climate change adaption strategies.

These models enable the user to estimate forage quantity (green biomass, gBM) and forage quality (metabolisable energy, ME) from hyperspectral reflectance data of vegetation canopies measured using an ASD FieldSpec 3 (or higher) Hi-Res Portable Spectroradiometer. The models were calibrated in R statistical software and were provided as RData-Files. The models were calibrated using spectral reflectance as well as forage provision data from several sites within the study area, comprising a steep south-north gradient of climatic aridity reaching from northern Ghana to central Burkina Faso between 9.0°N and 13.5°N latitude and 0.1°W and 2.0°W longitude. It is located in the southern and northern Sudanian zone of West Africa’s savanna belt, capturing a precipitation range of 600 mm to 1200 mm corresponding to UNEP aridity indices of 0.31 (semi-arid) to 0.69 (humid). Data collection took place at 21 sites during the rainy season 2012 (June-September). Our sampling design intended to cover diverse vegetation types and a wide range of land-use intensities (including protected and degraded areas). We stratified sampling at sites by topographic position (upslope, footslope and lowland). Vegetation samples were oven-dried (60°C, > 48 h) to obtain gBM. Dried samples were ground for analysis of in vitro gas production (GP) using the Hohenheim gas test (HGT). Crude protein (CP) content was determined by LUFA NRW using Kjeldahl´s method (method 4.1.1). The ME was calculated using the following equation: ME (MJ kg-1 dry matter, DM) = 2.20 + 0.1357 GP + 0.0057 CP + 0.0002859 CP², where GP is expressed as ml 200 mg-1 DM and CP is expressed as g kg-1 DM. A partial least-squares regression was used to model the relations between spectral data and target variables (ME and gBM). We used the PLSR implementation in the R package 'autopls'. During PLSR, we also performed multiplicative scatter correction and brightness normalization of reflectance spectra. Before the models can be applied, spectra have to be smoothed using Savitzky-Golay smoothing filter and noisy regions (bands 940:1170, 1350:1700, 2001:5000) have to be excluded from model application. Further information: Ferner, J., Linstädter, A., Südekum, K. H., & Schmidtlein, S. (2015). Spectral indicators of forage quality in West Africa’s tropical savannas. International Journal of Applied Earth Observation and Geoinformation, 41, 99-106.