Assessment of Climate Change Impacts on the Hydroclimatic Response in Burundi Based on CMIP6 ESMs

Abstract

Burundi is susceptible to future water-related disasters, but examining the influence of climate change on regional hydroclimatic features is challenging due to a lack of local data and adaptation planning. This study investigated the influence of climate change on hydroclimate-focused changes in the climatology of heavy precipitation (and streamflow) means and extremes based on the multi-model ensemble mean of earth system models in the sixth phase of the Coupled Model Intercomparison Project (CMIP). For runoff analysis, hydrologic responses to future climate conditions were simulated using the Soil and Water Assessment Tool (SWAT) model over the Ruvubu River basin, Burundi. Temperature increases by 5.6 °C, with strong robustness, under future climate conditions. The mean annual precipitation (and runoff) undergoes large seasonal variations, with weak robustness. Precipitation (and streamflow) changes between the wet and dry seasons differ in signal and magnitude. However, alterations in both the amount and frequency of precipitation reveal the intensification of the water cycle due to anthropogenic climate change. Thus, the highest variability in the maximum daily streamflow is shown in months of long wet seasons, especially in the far future (2085). Without considering the regional climate characteristics and shared socioeconomic pathway (SSP) scenarios, this behavior is expected to be enhanced in 2085 (compared with 2045) and increase the severity of extreme precipitation and flood risk. Climate change will cause alterations in the magnitude and seasonal distributions of extreme precipitation (and streamflow). These findings could be important for flood planning and mitigation measures to cope with climate change in Burundi.

Potential hydro-meteorological impacts over Burundi from climate change

“…We found a general increase in the average river discharge in North Burundi and a general decrease in South Burundi that agree with the anomalies found for precipitation in this study as well as by Kim et al (2021). The later concludes about the rise of seasonal mean and extreme runoff in the Ruvubu River Basin (station kag_290 in this study) as an effect of the intensification of the hydrological cycle, based on the projections from two earth system models in the sixth phase of the Coupled Model Intercomparison Project (CMIP6).…”

“…Such studies relate mainly to the change in precipitation over the lake (Thiery et al, 2015(Thiery et al, , 2016, its water level (Tungaraza et al, 2012), or the stratification (Tierney et al, 2010). Yet, information about the responses in upstream basins, as represented by Burundi's network, is scarce (Kim et al, 2021;Ogiramoi Nyeko, 2011). One reason could be the difficulty to model this area due to the multiple swamps and high evaporation (Di Baldassarre et al, 2011).…”

“…One reason could be the difficulty to model this area due to the multiple swamps and high evaporation (Di Baldassarre et al, 2011). Moreover, the lack of investment in Burundi due to the violence and conflict in the country since its independence in 1962 (Kamungi et al, 2005), has probably contributed to the research gap in this region Information about climate projections in Burundi can be only found in few publications (Baramburiye et al, 2013;Kim et al, 2021) or extracted from regional maps that illustrate such in Central/East Africa (Endris et al, 2013(Endris et al, , 2019Nikulin et al, 2012); hence lacking accuracy. Despite the existence of a few national plans for adaptation to climate change (NAPA, 2007), the information about climate change impacts is not very detailed.…”

Assessing the Implication of Climate Change to Forecast Future Flood Using CMIP6 Climate Projections and HEC-RAS Modeling

“…Additionally, the increase in monthly peak for some months and change in the month in which the peak occurs agrees with the results of Xiang et al [45], who found a change in peak month from the month of August to July. In most past research studies, the largest change in flow values has been due to the higher emission scenario, but this study had a different outcome, which suggested higher values for the lower emission scenario [62]. This means that the likelihood of higher flooding is due to the SSP-126 emission scenario as opposed to the SSP-585 emission scenario.…”

Determining Hydrological Variability Using a Multi-Catchment Model Approach for the Western Cape, South Africa

“…Distributed rainfall-runoff models have been used in numerous studies as predictive tools to assess the impact of different climate change projections on future water resource availability around the world [87][88][89]. In South Africa, the most comprehensive assessment includes the analysis of three different global circulation models (GCMs) (CNRM-CM3, ECHAM5/MPI-OM, IPSL-CM4), which, in combination with the A2 emission scenario, projected severe hydrological droughts for much of the Western Cape when comparing present and future conditions (1971-1990 and 2081-2100) [90].…”