Search Results (214)

Climate change may alter both basin-outlet water availability and runoff responses within large semi-arid tributaries. We evaluated climate-driven runoff changes at four gauged catchments in the Jinghe River Basin using a 16-gauge, multi-gauge EA-LSTM. Thirty-one NEX-GDDP-CMIP6 model–grid configurations were evaluated against 1960–2014 observations from 66 stations, and four models with strong historical statistical agreement and complete scenario records formed the screened ensemble. Native NEX-GDDP-CMIP6 forcing was used directly. At the Zhangjiashan outlet, test-period NSE and KGE were 0.823 and 0.615, respectively, while PBIAS was −31.6%. Under late-century SSP585, annual runoff decreased at Jingheyuan and Zhanghe but increased at Jingcun and Zhangjiashan, ranging from −16.7% at Zhanghe to +16.8% at Jingcun; flood-season responses showed a similar upstream–downstream contrast. At Zhangjiashan, screened-ensemble means were 0.2–11.5 percentage points lower than the corresponding expanded-ensemble means across the scenario–period combinations. Within the present input set and learned relation, precipitation and runoff changes were associated (Pearson r = 0.918), although this does not establish physical attribution. Full article

This study evaluates the unique ecological and floristic identity of the coastal dune vegetation in the Enez delta and adjacent dune coast of Saros Bay (southern Thrace) by comparing it with diverse dune systems across the Anatolian peninsula. A comprehensive data matrix of 97 phytosociological relevés across nine representative coastal dunes spanning the East Mediterranean, Aegean, Marmara, and Black Sea coasts was analyzed. Methodologically, univariate non-parametric approaches (Friedman variance analysis and Durbin–Conover tests) were integrated with multivariate techniques, including Hierarchical Cluster Analysis and Principal Coordinates Analysis (PCoA) based on a Bray–Curtis dissimilarity matrix. Ephedra distachya ssp. monostachya was found to be the most characteristic and differentiating taxa from the clustering. Friedman test results demonstrated highly heterogeneous species abundance across localities (χ² = 27.2, p < 0.001). The multivariate synthesis revealed a profound ecological decoupling for Saros Bay dunes: while macroclimatic filtering forces a powerful functional convergence with arid Mediterranean models dominated by therophyte, strict composition-based metrics isolate Saros Bay coastal dunes into an entirely independent taxonomic clade. PCoA ordination confirmed this distinctiveness (p < 0.05 against six of the eight national localities), with the first two axes explaining 33.58% of the total variation (Axis 1: 19.66%, Axis 2: 13.92%). This isolation is driven by a high density of Irano-Turanian elements and specialized local lineages like Silene kotschyi. Conversely, a sharp latitudinal bio-climatic macro-gradient was mapped, showing a transition toward humid Black Sea systems strictly dictated by macroclimatic filtering rather than biotic competition (p > 0.05). To preserve these specialized niches, designating coastal dunes of Saros Bay as a Priority Conservation Unit and establishing international, transboundary catchment to coast monitoring frameworks are essential. Full article

Pronounced spatio-temporal variability of rainfall in semi-arid basins remains a central challenge for rainfall–infiltration–runoff modeling, particularly in ungauged or newly instrumented catchments where continuous soil-moisture data are unavailable. This study evaluates the comparative predictive performance of the SCS-CN and Green-Ampt (GA) infiltration methods, implemented within HEC-HMS at the sub-basin scale, using eight rainfall–runoff analysis time windows recorded during the 2020–2025 rainy seasons within a monitoring network operational since October 2019 in an instrumented semi-arid basin in Mexico. A blind-validation framework was adopted: parameters for both methods were derived a priori from tabulated sources indexed by land use, hydrologic soil group, soil textural class, and locally supported by textural analysis at three depths per sub-basin, in situ testing of saturated hydraulic conductivity, and gravimetric determination of field capacity; the initial moisture content required by GA was set equal to the measured field capacity (θ_i = θ_fc) to equate initial conditions between the two methods. Spatially distributed rainfall was captured by four monitoring stations under a one-to-one gauge–sub-basin assignment scheme, with monthly rainfall depth varying from 22.8 to 204.9 mm across the four sub-basins. Both methods reproduced observed discharge with varying levels of agreement: SCS-CN yielded very good performance (Pearson R = 0.95; Nash–Sutcliffe efficiency NSE = 0.76), whereas Green-Ampt yielded moderate correlation but unsatisfactory NSE (R = 0.70; NSE = 0.45) against the Levelogger records. Contrary to the initial expectation that the physically based GA would outperform SCS-CN, SCS-CN yielded substantially higher performance across windows, with the two simulated discharge series differing by a mean absolute deviation of 36.9 m³/s. A systematic sensitivity analysis (±6%, ±10%, ±20% perturbations) revealed an asymmetric response: SCS-CN was highly sensitive to Curve Number perturbations (mean-deviation amplitude 65.9 m³/s), whereas Green-Ampt was nearly insensitive to its compound soil-hydraulic parameterization (amplitude 3.2 m³/s), indicating a structural limitation of the physically based method under blind validation. Full article

Water scarcity strongly constrains the revegetation of disturbed mine substrates in cold-arid regions. This study compared soil-moisture dynamics between a microtopographic reclamation area and an adjacent flat reclamation area in an abandoned stone quarry within the Kalamaili Ungulate Nature Reserve, northwestern China. The integrated restoration treatment, established in 2018, combined linear trenches 30–40 cm deep and spaced 60 cm apart, native seed sowing, transferred seed-bank topsoil, and water-retaining material. From January to December 2024, sensor-derived apparent volumetric water content was monitored at five depths—0–10, 10–20, 20–30, 30–40, and 40–50 cm—at 10 min intervals using sensors operated with the manufacturer’s standard calibration. Following quality control and temporal synchronization, 41,475 valid timestamps were retained for each monitored profile. The study provides a continuous full-year, multi-depth record from an unirrigated, cold-arid reconstructed quarry substrate, a setting that remains underrepresented in previous micro-catchment and dryland-restoration research. However, this study is based on a single hydrological year and does not directly measure plant physiological responses or long-term restoration outcomes. Therefore, elevated soil moisture should be interpreted as a preliminary indicator of restoration potential rather than a definitive measure of ecological recovery success. The monitored microtopographic profile maintained higher mean apparent water content than the flat profile during most of the year. The largest annual relative profile difference occurred at 10–20 cm depth, reaching 18.0%, followed by 11.7% at 0–10 cm, whereas differences decreased below 20 cm and reached 1.9% at 40–50 cm. During selected rainfall and probable snowmelt periods, the microtopographic profile exhibited larger wetting responses and slower post-event recession. These patterns indicate contrasting upper-profile wetting and drying dynamics between the two monitored reclamation configurations. However, runoff, infiltration, evaporation, snow accumulation, soil-water potential, and vegetation responses were not measured directly. Moreover, monitoring began several years after vegetation establishment, and trenching, seed addition, seed-bank transfer, and water-retaining material were not evaluated independently. The findings should therefore be interpreted as a site-specific post-establishment comparison rather than evidence of the isolated effect of microtopography. Replicated, multi-year studies are required to determine the mechanisms, effectiveness, and broader transferability of this integrated reclamation configuration. Full article

This study investigates flood behavior in the Wadi Ibrahim watershed by evaluating the sensitivity of flood estimates to different Peak Rate Factor (PRF) values, with a focus on their influence on peak discharge (Q_p), time to peak (t_p), volume (V) and inundation depth. Flood simulations were conducted using the Ari-Zo model, an empirical rainfall–runoff approach designed for arid regions, combined with unit hydrograph derivation across multiple PRF scenarios (Low, Medium, High, and NRCS) for 50-, 100-, and 200-year return periods. Envelope curves were constructed as validation to characterize the range of potential flooding. Comparative analysis indicates that the widely used NRCS model, including in Saudi Arabia, consistently underestimates Q_p and overestimates t_p relative to the Ari-Zo model. The Ari-Zo model produces sharper, faster-rising hydrographs with shorter durations, reflecting the rapid flash flood response characteristics of arid catchments. The Q_p in the High scenario is up to 71% higher than in the NRCS scenario. Hydraulic modeling shows that the different water depths of the Ari-Zo model relative to the NRCS scenario are 0.8 m (Low-NRCS), 1.8 m (Medium-NRCS), and 3.3 m (High-NRCS) for the 50-year return period, with the High scenario inundating nearly the entire valley bottom. The study highlights that PRF selection and model choice significantly influence flood predictions, emphasizing the importance of using arid-zone-adapted models to ensure reliable flood risk assessment and resilient infrastructure planning. Full article

Understanding ecological resilience (ER) across urban–rural gradients is important for differentiated management in arid metropolitan areas. Using 2 km grid data for 2013, 2018, and 2023, this study delineated travel-time-based urban–rural catchments in the Urumqi Metropolitan Area. The optimal-parameter Geodetector and multiscale geographically weighted regression were used to examine global explanatory patterns and local ER–factor associations, while spatially constrained clustering identified management types. The results showed that (1) mean ER values were 0.49, 0.50, and 0.48, respectively. ER was lower in urban centers and higher in rural areas and hinterlands. Compared with 2013, ER in 2023 was higher in urban centers and peri-urban regions but lower in rural areas and hinterlands. (2) Socioeconomic factors were more prominent in urban centers and peri-urban regions, whereas rural areas exhibited temporally variable natural and socioeconomic patterns. Elevation and soil organic matter were more prominent in hinterlands, and factor interactions were predominantly characterized by bi-factor or nonlinear enhancement. (3) Local ER–factor associations varied in direction, magnitude, and spatial scale. Negative associations with nighttime light intensity, road density, and built-up land proportion were concentrated in more urbanized areas. (4) Overlaying four spatial clusters with four catchment categories produced 16 integrated management types. These units provide a spatial basis for differentiated ecological management and regional planning in the Urumqi Metropolitan Area. Full article

Reliable climate data are essential for hydroclimatic assessment and water-resources management in data-scarce regions. This study evaluated the performance of the WorldClim 2.1 historical weather dataset (WC2.1– CRU-TS v4.09), downscaled and bias-corrected from CRU-TS v4.0 using WorldClim 2.1 climatology, against observed meteorological records within the semi-arid C5 Secondary Drainage Region (C5 SDR; comprising the Riet and Modder River catchments) in central South Africa for the period 1950–2023. Precipitation, maximum temperature (TMAX), and minimum temperature (TMIN) were assessed using statistical performance evaluation metrics, scatter and residual analyses, Innovative Trend Analysis (ITA), Rescaled Adjusted Partial Sums (RAPS), and extreme-event evaluation based on the 95th-percentile threshold. The results showed strong agreement between observed and gridded precipitation records, with correlation coefficients ranging (R) from 0.78 to 0.90 and Nash–Sutcliffe Efficiency (NSE) values between 0.61 and 0.90. Temperature datasets exhibited similarly good performance, with TMAX showing stronger agreement than TMIN. ITA and RAPS analyses demonstrated that the dataset successfully reproduced long-term climatic trends, hydroclimatic regime shifts, and interannual variability observed in station records. Performance varied spatially, with the strongest agreement occurring at lower-elevation stations and comparatively lower performance at stations influenced by localized convective rainfall and topographic variability. Extreme-event analysis revealed that although the dataset effectively reproduced the timing and occurrence of high-rainfall years (R² = 0.974–0.997), it systematically underestimated the magnitude of extreme precipitation events, with percent bias values ranging from −5.5% to −21.0%. In contrast, extreme temperature events were reproduced with very high accuracy and minimal bias. Overall, the WC2.1– CRU-TS v4.09 dataset provides a reliable climatic baseline for hydroclimatic assessments in the C5 SDR. However, caution is required when applying the dataset to analyses sensitive to localized precipitation extremes. The results provide confidence in the use of this dataset for climate characterization, drought assessment, hydrological modeling, ecosystem service evaluation, and future climate-change impact investigations in data-scarce semi-arid environments. Full article

This study develops and applies an adapted New Urbanism–Transit-Oriented Development (NU–TOD) framework to evaluate spatial, functional, and climatic performance in Al Malqa District, Riyadh. Integrating NU–TOD principles with hot-arid microclimate research, Saudi sociocultural norms, and Vision 2030 governance, the study employs a convergent mixed-methods design that combines Geographic Information Systems (GIS)-based land-use and network analyses, shading and microclimate indicators, and policy review. Results show that Al Malqa benefits from strong civic anchors and proximity to a Line 1 metro station but exhibits limited walkability, low station-area densities, constrained mixed-use intensity, and insufficient shading, which together reduce effective walking catchments and transit viability. A phased intervention strategy is proposed: short-term shading and feeder-mobility improvements; medium-term TOD zoning, parking reform, and public-realm upgrades; and long-term mixed-use redevelopment and district-scale green infrastructure. A reproducible Multi-criteria Decision Analysis (MCDA) feasibility assessment (impact, regulatory ease, cost, timeline) prioritises shaded pedestrian corridors and feeder mobility as the most implementable early actions. The study contributes a replicable evaluation model for hot-arid cities and offers actionable guidance for Vision 2030, aligned with suburban intensification in Riyadh. Full article

Developing effective adaptation and mitigation strategies depends on climate predictions capable of representing future conditions across multiple temporal scales. Decadal climate predictions bridge seasonal forecasting and long-term climate projections, providing near-term climate information for decision-making and adaptation planning at multi-year timescales. This study assesses the predictive skill of CMIP6 decadal precipitation forecasts from the Decadal Climate Prediction Project for three strategic catchments in state of Ceará, in the Brazilian semi-arid region. Forecast skill was assessed using deterministic and probabilistic metrics for three averaging horizons corresponding to years 1, 1–5, and 1–10 after initialization. Systematic biases were assessed and corrected. The results indicate that predictive skill varies across forecast systems, averaging horizons, and catchments. While skill was generally lower for the 1–5-year averaging horizon, several forecast systems showed positive skill relative to climatology for the 1-year and the 1–10-year averaging horizons, especially for below-normal and above-normal precipitation categories. Although bias correction reduced effectively systematic errors, it did not consistently improve forecast skill. These findings suggest potentially useful predictive skill at decadal timescales and highlight the potential of decadal climate information to provide complementary information for near-term water resources planning and drought preparedness in the Brazilian semi-arid region. Full article

Flash flood events are among the most critical hydrological hazards in arid and semi-arid regions, posing extreme threats to critical infrastructure, human safety, and sustainable development plans. This paper evaluates the flash flood susceptibility of the Al’Ataya catchment, a key watershed on the southern Red Sea coast, using an integrated geospatial analysis approach. To assess and quantify the flood hazard, we investigated 15 morphometric parameters for 24 particular sub-catchments within a sixth-order drainage system. Two complementary methods, the Morphometric Ranking Method and El-Shamy’s approach, were utilized to classify the catchment into different flood susceptibility levels. Results from the Ranking Method identified seven sub-catchments (SC-2, SC-3, SC-6, SC-7, SC-8, SC-9, and SC-19) as having high flood hazard levels, mainly driven by large watershed areas, steep slopes, and high relief ratios. In contrast, El-Shamy’s approach resulted in a different evaluation, identifying sub-catchments in Zone B (SC-23, SC-16, SC-17, SC-15, SC-6, SC-20) as high hazard sub-catchments due to the particular relationship between the bifurcation ratio parameter and the drainage density and stream frequency parameters. The integration of the two methods suggests that the susceptibility factor is controlled by the combined influence of a low drainage density and steep mountainous terrain draining toward the coastal zone. These results provide a spatial model for flood mitigation and early warning systems, supporting Saudi Vision 2030 through improvement to the development of southern urban centers such as Al’Ataya and Sabya. Full article

The Wadi Al-Ahsaba watershed is an arid to semi-arid catchment situated in southwestern Saudi Arabia, characterized by intermittent surface flow, high evaporation and low rainfall, and a dam reservoir built for flood control. The work aims to assess hydrological and anthropogenic controls on surface and groundwater quality, pollution status, and human health risks using an integrated approach of hydrogeochemical analysis, multivariable statistics, and water quality and contamination indices. A total of 21 water samples (15 surface water, 6 groundwater) were analyzed for general chemistry, major ions, and trace elements. Hydrogeochemical analysis and principal component analysis (PCA) were implemented to differentiate the geogenic from anthropogenic control on water quality. The pollution status and associated risk were evaluated using water quality index (WQI), contamination degree (Cd), Hazard Quotient (HQ), and Hazard Index (HI). Results suggest limited surface–groundwater interaction, with surface water dominated by Ca–Mg–HCO₃ facies, indicating recent recharge and limited water–rock interaction, whereas groundwater exhibits mixed Ca–Mg–Cl and Ca–Na–Cl–SO₄ types, revealing longer residence time and water–rock interaction. Nitrate (9.5–109 mg/L) and TDS (522–1003 mg/L) exceeded drinking water standards in 90% and 95% of tested samples, respectively, and WQI ranged from 43 to 134, reflecting excellent to poor water. High non-carcinogenic risk from nitrate was observed, especially for infants. The study concluded that the geogenic processes (water–rock interaction, evaporation, and mineral dissolution) control the general chemistry of tested water, while anthropogenic input from wastewater and agriculture input are likely contributors to nitrate contamination. The study contributes to the understanding of arid wadi-dam systems by revealing how limited recharge, hydrological connectivity, and episodic flow control contaminant transport and persistence, underscoring the critical role of integrated hydrological analysis and land use management in safeguarding freshwater resources in arid environments. Full article

Soil quality assessment, which considers numerous physical, chemical, and biological indicators, has long been a challenge for monitoring soil functions and ensuring sustainable resource use in agriculture. In this study, different indicator selection and weighting methods were compared to derive a reliable Soil Quality Index (SQI) in semi-arid agroecosystems. A total of 117 topsoil samples were taken from the Ap horizon within a 14,200 ha area of the Honam sub-catchment, southwestern Iran. Twenty-one soil indicators were measured and analyzed to assess the overall SQI. Soil indicator selection was performed using Principal Component Analysis (PCA), considering standard and norm value strategies, as well as component rotation. Four weighting approaches, including PCA, Coefficient of Variation (CV), correlation score (r), and Expert Opinion (EO), were applied to the Minimum Dataset (MDS) and Total Dataset (TDS) to compute the Integrated Quality Index (IQI), Nemoro (NQI), simple additive (IQIa), and Fuzzy Fertility Index (FFI). The performance of the SQI models was evaluated using the Sensitivity Index (SI) and their relationships with crop yield. The results showed that the combination of the norm value approach without component rotation was more effective in selecting the influential indicators for SQI determination. The Structural Stability Index (SSI), which integrates soil organic carbon and textural soil properties, was the key indicator with the highest contribution, ranging between 6.3% and 37.5% in most of the models. Among the evaluated approaches, the IQI-CV-MDS showed the highest sensitivity (SI = 6.8) and the strongest correlation (r = 0.53) with rainfed barley yield. The majority of the samples exhibited moderate SQI values, indicating a general risk of soil quality decline in the study area. The findings of this study highlight that appropriate indicator selection and weighting strategies are essential for improving the reliability of SQI assessments in semi-arid environments with diverse mountainous topography. Full article

Worldwide, flash floods are among the most unpredictable and hazardous hydrological phenomena, particularly in arid and semi-arid regions such as the Kingdom of Saudi Arabia, where sudden heavy rainfall follows prolonged periods of drought. This work presents an effective integrated model for flood hazard evaluation in the Hanefah Catchment, a socioeconomically vital area in the central part of Saudi Arabia that includes the capital city, Riyadh. Using high-resolution ALOS PALSAR 12.5 m Digital Elevation Model spatial data, we extracted and investigated indicative linear, areal, and relief morphometric keys of 64 sub-catchments. This paper employs a dual-method concept that integrates a multi-criteria ranking method and the El-Shamy approach in conjunction with morphotectonic analysis to model flood-susceptibility zones. Furthermore, this paper suggests a comparative assessment of low-cost morphometric models under data-scarce conditions, assessing the multi-criteria ranking method against El-Shamy’s approach, using the topographic position index (TPI) as an internal terrain scale benchmark. The ranking method successfully assigned 85.7% of the historically recorded flood locations to the high-hazard zone that covers ~24.22% of the Hanefah catchment. In contrast, the El-Shamy approach systematically underestimated flood susceptibility because regional tectonic activity increases bifurcation ratios, resulting in just ~42.9% of the historical floods being assigned to the high-hazard zone. The final results highlight the northern and northwestern parts of the catchment as high-hazard zones, characterized by high drainage density and steep relief. This study provides a refined, cost-effective model that aligns with the strategic objectives of Saudi Vision 2030 for sustainable water resources management and significant urban development. Full article

Small hill reservoirs in arid North Africa face accelerating threats from soil erosion and siltation, yet integrated assessments linking erosion dynamics, water quality, and soil fertility remain scarce. This study presents a multi-component geospatial assessment of the 345 km² Es-Sabba watershed in the Saharan Atlas of southwestern Algeria. Soil loss was quantified using the revised universal soil loss equation (RUSLE) integrated with Sentinel-2 imagery, a 30 m digital elevation model (DEM), and GIS analysis for 2016–2025. The mean annual soil loss reached 26.3 t/ha/yr, with 68.4% of the watershed under high-to-severe erosion; topography and vegetation cover were the dominant controls. Estimated sediment delivery to the reservoir is 135,300 t/yr, projecting a functional lifespan of 11–15 years without intervention. Hydrochemical analysis classified reservoir water as alkaline- and sulfate-rich, yet suitable for irrigation with very low sodicity risk (sodium adsorption ratio, SAR = 0.08) and an excellent Irrigation Water Quality Index (IWQI = 91.75). Soils exhibited low-to-moderate fertility (mean soil fertility index, SFI = 0.416), with widespread nitrogen deficiency constraining vegetation-based erosion control. The integrated framework identifies circular-economy opportunities through nutrient-rich sediment reuse and provides actionable guidance for climate-resilient reservoir management in arid catchments. Full article

Sediment accumulation in reservoirs represents a critical challenge for sustainable water resources management in semi-arid regions. In Jordan, accelerated sedimentation threatens the operational capacity of major dams, including the King Talal Dam (KTD), which serves as a key water resource in the Amman–Zarqa Basin (AZB). This study assesses sediment yield and erosion risk at the catchment scale using the Soil and Water Assessment Tool (SWAT) integrated with the Modified Universal Soil Loss Equation (MUSLE). The AZB was subdivided into 31 sub-basins and 586 Hydrological Response Units (HRUs) based on land use, soil characteristics, topography, and slope. The model was calibrated for the period 1993–2002 and validated for 2003–2012 using hydrological and sediment observations from 17 monitoring stations. Long-term simulations covering more than two decades were conducted to quantify spatial and temporal sediment yield patterns across the basin. Results indicate a mean annual sediment yield of 2.79 t ha⁻¹ yr⁻¹, corresponding to approximately 0.59 MCM yr⁻¹ of sediment inflow to the reservoir. These estimates closely agree with bathymetric survey results reported by the Jordan Valley Authority, which indicate sedimentation rates of 2.59 t ha⁻¹ yr⁻¹ (0.55 MCM yr⁻¹). Overall, the model demonstrates strong agreement between observed and simulated sediment loads, confirming its reliability for sediment dynamics assessment. The findings are relevant to Sustainable Development Goals (SDGs) 6 (clean water and sanitation) and 15 (life on land) by informing sustainable watershed and soil erosion management practices. Full article