Performance Evaluation of Climate Products with Validation Using Bootstrapping and Climate Extremes in the Hadejia-Jama’are River Basin, Nigeria
- Authors
-
-
Idris M. WADA
Department of Agricultural Engineering, Faculty of Engineering, Federal University, Wukari, Nigeria
Author
-
Abba IBRAHIM
Department of Agricultural and Environmental Engineering, Faculty of Engineering, Bayero University, Kano, Nigeria
Author
-
Genesis ISHAYA
Department of Agricultural Engineering, Faculty of Engineering, Federal University, Wukari, Nigeria
Author
-
- Keywords:
- Climate Products, Compromise Programming, Multi-Criteria Group Decision Making, Hadejia-Jama’are River basin, Statistical evaluation, Climate extremes.
- Abstract
-
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.
- References
- Downloads
- Published
- 08-08-2025
- Section
- Articles
- License
-
Copyright (c) 2025 FUDMA Journal of Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
Similar Articles
- Sirajo ALHASSAN, Abdullahi A. ADAMU, Mohammed T. JIMOH, Multi-Criteria Decision Analysis and Optimization Approaches in Sustainable Waste-to-Energy Planning: A Systematic Review , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Samuel E. CHUKWU, Martins Y. OTACHE, Precious O. ATEMOAGBO, Emmanuel O. AGBESE, Copula-Based Modelling of Drought Severity-Duration-Frequency Relationship of Sokoto-Rima-River Basin, Nigeria , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Yusuf L. SHUAIB-BABATA, Kabiru S. AJAO, Yusuf O. BUSARI, Ibrahim O. AMBALI, Kehinde O. ARUNA, Henrietta O. COKER, Toheeb A. NURUDEEN, Evaluation of UNILORIN Dam Moulding Sand Properties for Foundry Applications , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Joseph A. OJENIYI, Zainab L. BELLO, Ismail IDRIS, Noel M. DOGONYARO, Suleiman AHMAD, Sikiru O. SUBAIRU, Entropy-Based Deep Learning Framework for Classifying Ransomware Families in Windows Environment , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Oluwayinka. G. AKINWAMIDE, Olugbenga O. AMU, Christopher FAPOHUNDA, Prediction of International Roughness Index of Flexible Pavement Using Machine Learning-Based Predictive Framework in Ekiti State , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Isaac O. OLAOYE, Design Modification and Performance Evaluation of an Existing Cashew Nut Shell Liquid (CNSL) Extraction Machine , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Tina I. FRANCIS-AKILAKI, Raymond A. EKEMUBE, Design, Construction, and Performance Evaluation of an Efficient Ethanol Stove for Domestic Cooking Application , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
- Muazu D. ZAKARI, Md R. KAMAL, Wada I. MUHAMMAD, Nuraddeen M. NASIDI, Dahiru MOHAMMED, Agro-Hydrological Modelling Systems in Peninsula Malaysia: A Comprehensive Review and a Guide towards Model Development , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Zainab B. LAPAI, Joseph A. OJENIYI, Ismail IDRIS, Abdulkadir O. ABDULBAKI, Jennifer BALA, Entropy-Guided Neural Architecture for Family-Level Classification of Windows Ransomware , FUDMA Journal of Engineering and Technology: Vol. 1 No. 2 (2025): December 2025
- Isiaq O. ALABI, Hassan T. ABDULAZEEZ, Sulaiman AHMAD, Yahaya M. SANI, Scalability Versus Accuracy Trade-offs in Distributed Big Data Processing Frameworks: A Comparative Evaluation of Apache Spark, Flink, and Dask Using Benchmark Datasets , FUDMA Journal of Engineering and Technology: Vol. 2 No. 1 (2026): June 2026
You may also start an advanced similarity search for this article.
