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.

This dataset is the sixth of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dassari, Benin. This data was obtained by interviews with smallholder farmers from various communities in the Dassari basin. It provides information on the household level on farming history, fertilizer use, crop rotation practices and the farmers' motivation behind changing their practice. Soil sample data provides information on N,P,K, C content with the intention of evaluating residual effect of fertilizer in soil. Data includes questionaire and results, and soil sample data all corresponding to multi-year study of fields. The coordinates of the soil sample plots can be obtained upon request to the author due to data privacy protection demands.

This survey aims to collect data on farmers in the Niger basin of Benin. The data collected are relative to: (i) demographic information; (ii) crop production; (iii) livestock production; (iv) off-farm activities, and wages; (v) Access to extension, markets, credit, food consumption and social capital; (vi) climate change perception and shocks; (vii) adaptation strategies; (viii) household assets, and basic services. Three-stage sampling was used. First, municipalities were randomly selected within each agro-ecological zone (AEZ) based on their number of agricultural households. Second, villages were randomly selected within selected municipalities. Finally, random farm households were selected within selected villages. Therefore, the municipalities were randomly selected within each AEZ (AEZ I: one municipality, AEZ II: two municipalities, AEZ III: three municipalities, and AEZ IV: one municipality). The choice of the number of municipalities per AEZ is linked to the number of municipalities covered by AEZs I and IV (they covered two municipalities, and it has been decided to select one of the two). The number of municipalities for the AEZs II and III was determined proportionally to their size, referring to the size of AEZ I as a reference. Only four out of the five AEZs covered by the basin are considered, namely AEZ I (totally), AEZ II (totally), AEZ III (partially), and AEZ IV (partially). AEZ V was disregarded because only one of its municipalities is located within the Niger basin and it is a small part of the municipality that is included in the basin. Moreover, Pèrèrè was disregarded, because this municipality is partially covered by the basin (just a small part). Similarly, two municipalities that are partially included in the basin within AEZ III were avoided (Kouandé was maintained because its major part is within the basin). The municipalities were selected within each AEZ by the means of probability-proportional-to-size (PPS). Finally the municipalities that were chosen are: Malanville in AEZ I, Banikoara and Kandi in AEZ II, Bembèrèkè, Kouandé, and Nikki in AEZ III, and Natitingou in AEZ IV. The sample size was 545 agricultural households allocated across selected municipalities by the means of N-proportional allocation . Moreover, some adjustments have been made due to logistical constraints. Based on the allocation of the sample size across municipalities, it has been decided to allocate twenty households per villages, meaning four villages should be surveyed in each municipality, except Natitingou (three villages) and Kandi (due to the fact that one village of Kandi was already randomly selected for the pilot survey). At the end of the process, 28 villages had been surveyed. Due to logistical constraints, twenty agricultural households were not surveyed in every village.

Disasters, particularly recurring small-scale natural disasters of floods and droughts have been affecting West African (WA) communities, impacting particularly weak households. These losses have been significantly high over the last decade due to increasing climate variability and inherently depressed socio-economic systems. However, to date, few studies have attempted to understand the vulnerability profiles in WA to these multiple hazards across several scales. A considerable number of studies predict the impacts of droughts and floods hazards, but many do so at a very coarse scale and without any participatory process, as a result, they are unable to predict localized impacts. Despite many efforts put in vulnerability assessments, there has been limited success in simultaneously traversing scale and hierarchy and the need for upscaling risk indices is important to understand the effects of cross scale interactions. To address these gaps, this thesis (i) explored methods to involve at-risk populations in local communities in a bottom-up participatory process as opposed to the classical top-down, single scale approaches and (ii) assessed the risks from multi-hazard perspectives in a coupled Socio-Ecological System (SES). The thesis also (iii) explored appropriate methodologies that can reflect the spatial variability of flood hazard intensity at community level. Building on these investigations, the thesis finally (iv) introduced a novel risk index upscaling procedure to upscale risk and vulnerability indices across multiple scales. The thesis used several methods ranging from rural participatory methods, statistical, Geographic Information System (GIS), remote sensing and introduced the innovative concept of Community Impact Score (CIS). The results show that more than half of the designated local level indicators and over two thirds of the macro scale indicators are rarely used in present risk assessments in the region. Additionally, although an indicator may be common to three countries, their differential rankings will result in differences in explaining the risks faced by people in different societies. Empirical validation of a flood hazard map using the statistical confusion matrix and the principles of participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. These high mapping accuracies notwithstanding, the flood index categories may change under conditions of very high rainfall intensities beyond the anomalies used to construct the model. To this end, studies that aim at understanding projected flood intensities under varying rainfall conditions beyond the anomalies used in this study are recommended. This is important to determine the trajectory of flood safe havens or hotspots across an entire study area. The study also develops two important indices, The West Sudanian Community Vulnerability Index (WESCVI) and The West Sudanian Community Risk Index (WESCRI). The underlying factors constituting the two indices are the elements of risk and vulnerability profiles of communities in West Africa. The WESCVI and WESCRI should help planners and policy makers to analyse and finally reduce vulnerability and risk. To evaluate the results of the risk indices, this thesis introduces a novel technique to validate the results of complex aggregation methods. Based on up to date knowledge, the CIS concept is the first in the available literature of risk assessment. The thesis also provides a theoretical concept to upscale risk and vulnerability indicators from watershed to higher spatial scales. Further studies are however recommended to apply these theoretical concepts. A conclusion of the thesis is that while it has neither been optimal to completely neglect classical approaches nor to take as an absolute fact opinion from local experts, more emphasis should be paid to the later in risk assessment that is supposed to serve the very people on whose behalf the assessment is done. Attempts should therefore be made in finding mechanisms where the two approaches could interact fruitfully and complement each other.

This dataset is the seventh of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso and Dassari, Benin. This data was obtained by interviews with 118 people from communities in Dano. It provides information on the household level in regard to biophisical and socio-economic data for agroforestry systems.

This dataset is the eighth of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso. Data includes randomly sampled pasture/soil measurments, transcripts of 22 qualitative interviews (anonymized), and a questionnaire with 128 corresponding results focused on livestock systems and climate change adaptation but also with socio-economic information.

This dataset is the seventh of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso and Dassari, Benin. This data was obtained by interviews with 137 people from 17 communities in Dassari. It provides information on the household level in regard to biophysical and socio-economic data for agroforestry systems.

This dataset is the fourth of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso and Dassari, Benin. This Data was obtained by interviews with 137 people from 17 communities,in Dassari. It provides information on the household level in regard to the aspects; challenges and behavioral change.

This dataset is the second of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso and Dassari, Benin. This Data was obtained by interviews with 137 people from 17 communities,in Dassari. It provides information on the household level in regard to the aspects; farming practices, cropping system, productivity, livestock, and consumption.

This dataset is the third of a series of datasets addressing farmers' adaptation to climate change in West-Africa, specifically in Dano, Burkina Faso and Dassari, Benin. This Data was obtained by interviews with 137 people from 17 communities,in Dassari. It provides information on the household level in regard to the aspects; changes in climate, hazards, and drivers of climate change.