Improving Hydro-Climatic Projections with Bias-Correction in Sahelian Niger Basin, West Africa

Abstract

Climate simulations in West Africa have been attributed with large uncertainties. Global climate projections are not consistent with changes in observations at the regional or local level of the Niger basin, making management of hydrological projects in the basin uncertain. This study evaluates the potential of using the quantile mapping bias correction to improve the Coupled Model Intercomparison Project (CMIP5) outputs for use in hydrological impact studies. Rainfall and temperature projections from 8 CMIP5 Global Climate Models (GCM) were bias corrected using the quantile mapping approach. Impacts of climate change was evaluated with bias corrected rainfall, temperature and potential evapotranspiration (PET). The IHACRES hydrological model was adapted to the Niger basin and used to simulate impacts of climate change on discharge under present and future conditions. Bias correction with quantile mapping significantly improved the accuracy of rainfall and temperature simulations compared to observations. The mean of six efficiency coefficients used for monthly rainfall comparisons of 8 GCMs to the observed ranged from 0.69 to 0.91 and 0.84 to 0.96 before and after bias correction, respectively. The range of the standard deviations of the efficiency coefficients among the 8 GCMs rainfall data were significantly reduced from 0.05–0.14 (before bias correction) to 0.01–0.03 (after bias correction). Increasing annual rainfall, temperature, PET and river discharge were projected for most of the GCMs used in this study under the RCP4.5 and RCP8.5 scenarios. These results will help improving projections and contribute to the development of sustainable climate change adaptation strategies.

Influence of Parameter Sensitivity and Uncertainty on Projected Runoff in the Upper Niger Basin under a Changing Climate

“…Future PET was computed from the extracted temperature using the Hamon model. In line with previous studies [9,23,45], rainfall and temperature projections were bias corrected with quantile mapping [46] at monthly time steps. Similar to other studies [9,23,47], the future annual runoff was aggregated into two future time periods ("near future" (2010-2035) and "far future" (2036-2099)) and these were compared to the historical period (1951-2005).…”

“…While the IHACRES-CMD model has three soil moisture accounting parameters (Table 1), the GR4J model has four parameters, and the Sacramento model has thirteen parameters ( Table 1). IHACRES-CMD and GR4J were selected due to their wide usage and acceptability in hydrological studies in the Niger basin [9,[22][23][24]. The Sacramento model was added to the two well-known models in the region because of its robust parameterisation.…”

“…GPCP is available from 1997-2016, while MERRA is available from 1979-2010. PET was computed from the MERRA temperature using the Hamon model that was earlier reported to provide acceptable estimations of PET [9,23,37]. The catchment boundary of the Niger basin was obtained from Hydrosheds [38].…”

“…The same scenarios are therefore also the highest priority of the CORDEX simulations [42]. CORDEX data have been evaluated and used for hydrological studies in the region [9,23,43,44]. In this study, basin CORDEX projection data were extracted as described for the observations data.…”

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

“…(6), we show the probability density function where is the gamma function. Approaches to bias adjustment of precipitation have been extensively discussed (see, for example, Piani et al, 2010a, b). Several experiments were made ignor- ing all precipitation values below a fixed low daily precipitation threshold over the whole domain.…”