Wetlands played an important role in human development and nature nutrient store for rice cultivation. Spatial techniques have gained importance in monitoring wetland changes. The study aimed to assess wetland soils for rice production using spatial techniques. The area was sample using stratified grid sampling. Nutrient availability and rice suitability were assessed in ArcGIS 10.6 environment. The soil was characterized into Eutric fluvaquent (Soil Survey Staff, 2010) and correlated as fluvisols in the World Reference Base system. The results of the land cover changes showed that built-up, waterbody, and farmland have increased by 39, 18, and 29%, respectively, and 13% decrease was observed in vegetation. The study concluded that soils of the studied area varied from marginally (75%), not suitable (20%), and permanently not suitable (5%) for rice production. Therefore, without proper assessment and management of these studied soils, rice production will continue to be futile.

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Landsat satellite imagery plays a crucial role in providing information on land use/cover modifications on local, regional, and global scales, especially where aerial photographs are missing. Monitoring land-use changes from past to present tends to be time-consuming especially when dealing with ground-truth information. Determining the past and current land-use change on Earth's surface using Landsat imagery tends to be effective and efficient when high-resolution imagery is unavailable. This study employed the use of Landsat satellite imagery to assess the past and present land use/cover using supervised classification and Normalized Difference Vegetation Index (NDVI). The result of the supervised classification land use/cover showed that forest cover and woodland undergo rapid loss, while farmland, wetland, built-up, and waterbodies tend to experience gradual loss. The NDVI demonstrated that farmland and forest cover was the most affected land use/cover. Hence, land use/cover of the study area is affected by human activities, such as intensive farming, population size, and deforestation.

Since the 1970s, climate change has led to decreasing water resources in the Sahel. To cope with climate change, reliable modelling of future hydroclimatic evolutions is required. This study uses multiclimate and hydrological modelling approaches to access past and future (1951–2100) hydroclimatic trends on nine headwater catchments of the Niger River Basin. Eight global climate models (GCMs) dynamically downscaled under the CORDEX CMIP5 project were used. The GCM data were bias-corrected with quantile–quantile mapping. Three rainfall–runoff models (IHACRES-CMD, IHACRES-CWI and Sacramento) were calibrated and validated with observed data and used to simulate runoff. The projected future runoff trend from 2061 to2090 was compared across the three hydrological models to assess uncertainties from hydrological models. Results show that the bias correction positively enhanced the quality of eight GCMs across the nine catchments. An average Nash–Sutcliffe Efficiency (NSE) across the nine catchments was improved from 0.53 to 0.68 and the Kling–Gupta Efficiency (KGE) was enhanced from 0.65 to0.83. The three hydrological models were calibrated and validated appropriately on the nine catchments. Despite this, high hydrological modelling uncertainties were witnessed with contrasting projected future runoff patterns by the three models. We recommended the use of ensembles of both climate and hydrological models to provide reliable hydroclimatic modelling.

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