Performance Evaluation of Climate Products with Validation Using Bootstrapping and Climate Extremes in the Hadejia-Jama’are River Basin, Nigeria - Idris M. WADA; Abba IBRAHIM; Genesis ISHAYA (FUDMA Journal of Engineering and Technology, 2025)
The increasing availability of satellite, reanalysis, and gauge-based Climate Products (CPs) has significantly advanced hydroclimatic research, particularly in data-scarce regions. Despite their usefulness, these CPs often carry substantial uncertainties, necessitating thorough evaluation before use in regional or basin-level studies. This study assesses the performance of nine precipitation and four temperature gridded datasets over the Hadejia-Jama’are River Basin (HJRB), Nigeria, using observational data from Kano, Jigawa, and Bauchi for the period 1990–2015. Daily and monthly precipitation (Pr), maximum temperature (Tmax), and minimum temperature (Tmin) temperature records were evaluated using Kling-Gupta Efficiency (KGE), Normalized Root Mean Square Error (NRMSE), Pearson correlation (r), Percentage Bias (PBIAS), and Mean Difference (MD). The fifth generation of the European Centre for Medium-Range Weather Forecasts (ERA5) dataset demonstrated superior performance in mean annual assessment for both Tmin and Tmax with minor underestimation. Tmax biases ranged from 2.2% to 3.5% and Tmin from 0.3% to 2.1%. Climate Forecast System Reanalysis (CFSR) had the weakest performance among the temperature products. The Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) outperformed other precipitation products, with modest underestimations of 3.5% (Kano), 9% (Bauchi), and 12% (Jigawa), while Climate Prediction Center (CPC) showed the poorest alignment with observed data. Monthly statistical evaluations yielded stronger statistical performance than daily analyses, especially for temperature datasets. For precipitation, correlation coefficients exceeded 0.5 across all models at daily resolution, with CHIRPS showing the highest values. Overall model ranking using Compromise Programming Index (CPI) and Multi-Criteria Group Decision-Making Method (MCGDM) confirmed ERA5 (for Tmax and Tmin) and CHIRPS (for precipitation) as the most reliable products. Further validation using climate extremes and bootstrapped uncertainty analysis showed that the ratio of modeled to observed extremes consistently exceeded 0.5, indicating suitability for hydrological applications. The bootstrapped 95% uncertainty bands were narrow, reflecting low uncertainty in the selected CPs. ERA5 and CHIRPS emerged as the most robust datasets for hydroclimatic studies in the Hadejia-Jama’are River Basin.
Keywords: Climate Products, Compromise Programming, Multi-Criteria Group Decision Making, Hadejia-Jama’are River basin, Statistical evaluation, Climate extremes.