Evaluation Of Satellite Rainfall Products for Water-Related Studies Across Borno State, Nigeria

Abstract

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DOI:

https://doi.org/10.4314/5vca9522

Abstract

Understanding rainfall variability is essential for sustainable rain-fed agriculture, optimised water resources management, and improved drought early warning systems in semi-arid regions such as Borno State, Nigeria. However, the scarcity of rain gauge networks limits accurate rainfall monitoring and drought assessment. With comprehensive spatial and temporal coverage, satellite rainfall products (SRPs) offer a viable alternative, but their accuracy requires local validation. The study evaluates the performance of the three SRPs, Precipitation from Remotely Sensed Information Using Artificial Neural Networks- Climate Data Record (PERSIANN-CDR), Climate Hazard Group InfraRed Precipitation with Station Data (CHIRPS), and Climate Research Unit Time Series (CRU TS), against rainfall data from the Nigeria Meteorological Agency (NiMet) from 1993 to 2021. Statistical techniques, including the correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), and Bland-Altman analysis, were used for validation. Among the evaluated SRPs, PERSIANN-CDR exhibited the strongest agreement with the NiMet rainfall dataset (r = 0.85), and the lowest error metrics (MAE = 29.7 mm; RMSE = 50.2 mm). CHIRPS and CRU TS showed moderate correlation (r = 0.81 0.82), and slightly higher error metrics (MAE = 29.5 - 33.3 mm, RMSE = 55.7 - 55.9 mm). Bias analysis revealed slight underestimation by PERSIANN-CDR (-5.1 mm) and CHIRPS (-5.5 mm), while showing slight overestimation by CRU TS (+6.5 mm). The results suggest that optimal planting periods should align with the onset of rainfall in late April to early May to maximise crop yield. These findings demonstrate that PERSIANN-CDR enhances localised drought monitoring, supports improved planting schedules, and strengthens agricultural planning and water management decision-making across Borno State, thereby contributing to food security, sustainable water use, and climate resilience in line with (SDG 2, 6, and 13).

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Author Biographies

  • Ashe Abubakar Wulet, KNUST

    Hydrogeologist at National Water Resources Institute (NWRI), Kaduna, Nigeria. Currently pursuing a PhD in Water Resources and Engineering Management at Kwam Nkruma University of Science and Technology. Holds Masters Degree in Geographic Information System (GIS) from Kaduna State University and Bachelor’s Degree in Geology from University of Maiduguri, Professional Member of the Nigerian Mining and Geosciences Society and the National Association of Hydrogeologists. Engaged in Hydrological investigations, groundwater exploration, borehole drilling supervision and sustainable water resources management. Research interests include climate variability, drought assessment, geospatial analysis, groundwater systems, application of GIS and remote sensing in water resources management.

  • Jonathan Arthur Quaye-Ballard, Kwame Nkrumah University of Science and Technology

    Professor at the Department of Geomatic Engineering, KNUST, Kumasi, Ghana. Holds BSc. Geodetic Engineering from KNUST, Kumasi, Ghana, MSc. Geo-Information Science and Earth Observation from ITC, Enschede, Netherlands, and PhD in Geodesy and Surveying Engineering from Hohai University, Nanjing, China. Professional Member of the Ghana Institution of Surveyors (GhIS), Fellow of Ghana Institution of Engineering (GhIE) and License Surveyors of Ghana (LiSAG). Teaches Geographic Information Systems (GIS), Principles of Land Surveying, Cartographic Visualisation, Remote Sensing (RS), Research Methods and System Analysis. Research interests include Usability Testing, Computer Supported Collaborative Learning (CSCL) and the application of Geo-Information, surveying and mapping in managing spatial information, solving complex global problems and environmental monitoring.

  •  Samuel Ato Andam-Akorful, Kwame Nkrumah University of Science and Technology

    Samuel Ato Andam-Akorful is an associate professor of Geospatial Science at the Department of Geomatic Engineering at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana. He holds a PhD in Geodesy and Survey Engineering from Hohai University, China, an MSc in Navigation Technology from the University of Nottingham, United Kingdom, and a BSc in Geomatic Engineering from KNUST. His research interests include GIS and remote sensing applications, geospatial data analytics, environmental monitoring, spatial modelling, navigation technologies, and geospatial solutions for sustainable development. He has extensive experience in geospatial research, capacity building, and interdisciplinary collaborations in Africa.

  • Charles Gyamfi, Kwame Nkrumah University of Science and Technology

    Dr. Charles Gyamfi is a Senior Lecturer in the Department of Civil Engineering at the Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. His expertise is in hydrology and water resources engineering. He is an active scholar in the fields of hydrological modelling, climate–water interactions, groundwater systems, and integrated water resources management with most of his works published in high impact journals. He has guided and mentored over 40 postgraduate students through the provision of research grants, student supervision and enabling environment for effective research undertaken.

    On the international front, Dr. Gyamfi serves as a reviewer to international journals, serves as external examiner and assessor for Universities in Ghana and across the West African Sub-region. He is a visiting scholar to the International Institute of Water and Environmental Engineering (2iE), Burkina Faso and the Swiss Federal Institute of Technology Zurich (ETH), Switzerland where he shares his expertise in hydrology and water resources. 

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Published

2026-08-15

Issue

Vol. 44 No. 3 (2026)

Section

Articles

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How to Cite

Evaluation Of Satellite Rainfall Products for Water-Related Studies Across Borno State, Nigeria: Abstract. (2026). Journal of Science and Technology, 44(3). https://doi.org/10.4314/5vca9522