The decline in groundwater storage (GWS) poses a critical threat to water security in semi-arid regions where increasing agricultural water demand and climate variability are increasing pressure on aquifers. This study presents a novel hybrid modeling framework integrating multi-source satellite and climate data (GRACE, GLDAS, TerraClimate, and MODIS) with machine learning and explanatory artificial intelligence techniques for the long-term assessment and interpretation of GWS anomalies in the data-poor Iğdır Basin. Three different modeling approaches were developed: XGBoost, Long Short-Term Memory (LSTM) networks, and their combined model, and interpreted using the Shapley Additive Explanations (SHAP) method. The results showed a significant long-term decreasing trend in groundwater storage anomalies at a rate of −0.87 mm per month during the 2002–2016 period, indicating continuous depletion. The LSTM model demonstrated the best performance with R2 of 0.59, RMSE of 19.5 mm, and MAE of 15.1 mm, revealing the dominant role of temporal dependencies in groundwater systems. SHAP analysis identified lagged groundwater anomalies (especially GWS_lag3) as the most effective predictors; this may reflect the memory effect and lagged response specific to semi-arid aquifer systems, but this interpretation needs to be validated in different study areas. Snow water equivalent and total water storage anomalies also emerged as significant determinants, while the direct effect of instantaneous precipitation was found to be limited. This study addresses significant gaps in the literature by combining sequence-based modeling with model interpretability in a semi-arid closed basin. The findings highlight the necessity of using system memory and explainable artificial intelligence together for reliable groundwater prediction. While the proposed hybrid approach has the potential for application in other semi-arid regions, its broader usability needs to be supported by independent validation studies under different hydrogeological and climatic conditions.
Mehmet Ali Çelik, Adile Bilik, Yasin Paşa· Hydrology· 0 citations
Understanding the climatic heterogeneity of Nigeria is essential for evaluating ecosystem vulnerability, climate‑risk exposure, and hydrological stability. However, existing classifications remain limited by sparse meteorological observations and predominantly single‑variable approaches. This study aims to provide a comprehensive, data‑driven eco‑climatic regionalisation of Nigeria, explicitly addressing the lack of multivariate and validated climatic frameworks that capture compound hydro‑ecological interactions. The strong north–south hydrothermal gradients of Nigeria, together with increasing climate variability, make it a critical location for developing a refined climatic zoning framework. Conventional classifications, including threshold‑based systems, often mask intra‑regional variability and fail to resolve ecological stress patterns. This study integrates four decades (1981–2024) of MODIS vegetation stress indicators, including Moisture Stress Index (MSI), Temperature Condition Index (TCI), and Vegetation Health Index (VHI), with ERA5‑Land precipitation, temperature, soil moisture, solar radiation, and runoff datasets. Principal Component Analysis (PCA) was applied to extract dominant climatic–ecological gradients, followed by K‑means clustering to delineate homogeneous eco‑climatic regions, while quantitative validation against the Köppen–Geiger classification (Cohen’s Kappa and Adjusted Rand Index) was performed to assess robustness and added value. Five coherent climatic regimes emerged along a distinct north–south gradient. Moisture availability was identified as the primary driver of climatic differentiation, with the semi‑arid northern zones exhibiting the highest moisture stress (MSI = 0.96) and the lowest vegetation health (VHI = 39.5). Humid southern regions displayed the lowest stress levels (MSI = 0.40–0.53) and higher VHI (> 53), while the Middle Belt formed a transitional ecotone with balanced hydro‑thermal conditions. Statistical validation (ANOVA,
p
< 0.001) and clustering diagnostics confirm that these regions are both distinct and internally consistent, while approximately 68% spatial agreement with Köppen–Geiger indicates systematic refinement rather than redundancy. The results provide a refined spatial differentiation and ecologically relevant climatic classification of Nigeria to date. By integrating vegetation response with atmospheric and hydrological variables, this study advances climatic regionalisation beyond conventional approaches and establishes a validated, high-resolution framework. The findings support drought-resilient agriculture in the north, flood- and water-resource management in the south, and improved climate-risk assessment across transitional zones.
Graphical Abstract
Based on the graphical abstract, this study presents an integrated multivariate framework for delineating ecological zones across Nigeria using four (4) decades (1981–2024) of MODIS and ERA5-Land datasets. It begins with a map of the study area, highlighting the pronounced latitudinal hydroclimatic gradients that structure the environmental conditions in Nigeria. The workflow then introduces the two major input datasets: MODIS land surface products and ERA5 Land reanalysis variables, which were systematically harmonised by spatial resampling onto a common 0.1° grid to ensure analytical comparability. Environmental stress indices derived from MODIS (Moisture Stress Index, Temperature Condition Index, and Vegetation Health Index), together with multivariate hydroclimatic variables from ERA5-Land (precipitation, temperature, soil moisture, solar radiation, and runoff), were processed to characterise long-term climatic and eco-physiological dynamics. Principal Component Analysis (PCA) was employed to extract dominant climatic–ecological gradients, enabling substantial dimensionality reduction and revealing strong moisture-driven north–south contrasts. Subsequently, hierarchical and K-means clustering algorithms were applied to partition Nigeria into five internally coherent eco-climatic zones, ranging from arid and semi-arid domains in the north to humid tropical systems in the south, with the Middle Belt forming a distinct transitional ecotone. In general, the study presents a robust, data-driven ecological classification framework that integrates compound vegetation–temperature–moisture interactions and provides a scientific foundation for climate-risk assessment, sustainable agricultural planning, biodiversity monitoring, and environmental management across Nigeria.
Afeez Alabi Salami, M. Togo, Zehra Işık et al.· Earth Systems and Environmen...· 0 citations
Long-term exposure to ambient fine particulate matter (PM2.5) is the leading environmental risk factor for premature mortality worldwide, yet comprehensive province-level evidence quantifying its health burden across Türkiye remains limited. This study investigated the spatial relationship between long-term PM2.5 exposure and all-cause attributable mortality across all 81 Turkish provinces in 2022 using province-level annual mean PM2.5 concentrations and World Health Organisation (WHO) AirQ+ estimates of PM2.5-attributable deaths among adults aged ≥30 years, assuming a counterfactual concentration of 5 µg/m3. The association between PM2.5 exposure and mortality was evaluated using Pearson and Spearman correlation analyses, ordinary least squares (OLS) regression, a log–log elasticity model, and population-weighted regional and exposure-quartile comparisons, while national temporal indicators for 2010–2023 were reported solely as supplementary context for the primary single-year 2022 cross-sectional analysis. The population-weighted annual mean PM2.5 concentration was 27.0 µg/m3, exceeding the WHO Air Quality Guideline by a factor of 5.4, and all 81 provinces exceeded the recommended threshold. The bivariate OLS model accounted for 41% of the between-province variation in attributable mortality rates (OLS slope = 3.23 additional deaths per 100,000 population for each 1 µg/m3 increase in PM2.5; 95% CI: 2.37–4.10; R2 = 0.41; p < 0.001), while the log–log elasticity model indicated that a 1% increase in PM2.5 concentration was associated with a 0.80% increase in the attributable mortality rate (95% CI: 0.65–0.95). The attributable fraction of natural-cause mortality increased progressively from 8.8% in the lowest exposure quartile to 24.6% in the highest. Nationwide, an estimated 68,440 premature deaths, representing 14.2% of all natural-cause deaths among adults aged ≥30 years, were attributable to PM2.5 exposure. These findings quantify a steep, spatially graded PM2.5-attributable mortality burden across Türkiye. As the attributable estimates derive from the WHO AirQ+ concentration–response function, the gradient describes the magnitude and spatial distribution of the modelled burden rather than an independently estimated exposure–response relationship, and on that basis the results support the adoption of WHO-aligned air-quality standards and accelerated decarbonization strategies to reduce the national health burden attributable to ambient air pollution.
Nebile Özmen, V. Duran, Fatma Şencan et al.· Toxics· 0 citations
This study examines the long-term associations between ambient air pollutants and the burden of major respiratory and infectious diseases in this geographically sensitive region. A retrospective analysis was conducted using ICD-10-coded hospital records of patients diagnosed with asthma, chronic obstructive pulmonary disease (COPD), bronchitis, and tuberculosis from January 2020 to June 2026. These data were integrated with in situ air quality measurements, including PM10, PM2.5, and SO2, as well as satellite-derived Aerosol Optical Depth (AOD) from MODIS. Disease incidence was stratified by year, sex, and age groups (0–85+ years) to assess demographic susceptibility patterns. Respiratory diseases constituted a substantial public health burden over the study period. Asthma showed a marked female predominance (≈29,700 females vs. ≈16,000 males) and a bimodal age distribution with peaks in early childhood (0–5 years) and mid-adulthood (35–50 years). COPD was predominantly observed in males (≈8300 males vs. ≈5500 females), with a higher median age range (≈67–70 years). Bronchitis exhibited a similar bimodal pattern, disproportionately affecting both pediatric and elderly populations, while overall case numbers declined over time. Tuberculosis incidence was approximately threefold higher in males than females, with notable age-related divergence, affecting younger females (≈30–32 years) and middle-aged males (≈42–45 years). The findings suggest a spatial–temporal correspondence between elevated pollutant concentrations and respiratory disease prevalence in the Iğdır Basin. The observed sex- and age-specific disparities underscore the potential value of region-specific environmental health strategies, strengthened air quality management, and continuous epidemiological surveillance in enclosed basin environments.
Melahat Batu Ağırkaya, Fatma Şencan, Mehmet Ali Çelik· Pollutants· 0 citations
