COMPILATION, QUALITY CONTROL, AND SATELLITE-BASED AUGMENTATION OF HYDROMETEOROLOGICAL DATASETS FOR ABIA STATE, NIGERIA

Abstract

Reliable hydrometeorological data are a prerequisite for hydrological modelling and flood risk assessment, yet gauge networks in southeastern Nigeria remain sparse and discontinuous. This study compiled, quality-controlled and augmented a 35-year (1988–2022) daily hydrometeorological dataset — rainfall, maximum and minimum temperature, relative humidity, solar radiation and wind speed — for six flood-prone small watersheds in Abia State, integrating Nigerian Meteorological Agency (NiMet) records at Aba and Umuahia with CHIRPS, IMERG and ERA5 products. Quality control comprised threshold, internal- and temporal-consistency checks, double-mass homogeneity screening and inverse-distance-weighted gap-filling. Satellite rainfall was bias-corrected against gauge observations by monthly linear scaling; bootstrap confidence intervals and leave-one-gauge-out cross-validation were used to quantify uncertainty and the spatial transferability of the correction factors. Correction improved CHIRPS daily correlation from 0.58 to 0.72 and reduced percent bias from +12.4% to +1.8% at Aba, with comparable gains at Umuahia; IMERG better resolved daily extremes. The augmented series showed mean annual rainfall of 1,842–2,487 mm and statistically significant increasing trends in annual rainfall (pre-whitened Mann-Kendall, p < 0.05; Sen’s slope 11–18 mm/year), with 90th-percentile daily rainfall rising by 2.1–3.4 mm/decade. The dataset provides a defensible, uncertainty-documented climate forcing basis for SWAT-based flood modelling in data-scarce catchments.