Search Results (98)

In arid and semi-arid climates, where water scarcity is a persistent challenge, accurately estimating reference evapotranspiration (ET) becomes essential for sustainable water management and agricultural planning. The objectives of this study are to compare hourly ET among P–M ASCE, P–M FAO, and P–M KSA mathematical models. In addition to the accuracy assessment of daily ET derived from hourly timestep calculations for the P–M ASCE, P–M FAO, and P–M KSA. To achieve these goals, a total of 525,600-min data points from the Riyadh region, KSA, were used to compute the reference ET at multiple temporal resolutions: hourly, daily, hourly averaged over 24 h, and daily as the sum of 24 h values, across all selected Penman–Monteith (P–M) models. For hourly investigation, the comparison between reference ET computed as average hourly values and as daily/24 h values revealed statistically and practically significant differences. The Wilcoxon test confirmed a statistically significant difference (p < 0.0001) with R² of 94.75% for ASCE, 94.87% for KSA at h_plt = 50 cm, 92.41% for FAO, and 92.44% for KSA at h_plt = 12 cm. For daily investigation, comparing the sum of 24 h ET computations to daily ET measurements revealed an underestimation of daily ET values. The Wilcoxon test confirmed a statistically significant difference (p < 0.0001), with R² exceeding 90% for all studied reference ET models. This comprehensive approach enabled a rigorous evaluation of reference ET dynamics under hyper-arid climatic conditions, which are characteristic of central Saudi Arabia. The findings contribute to the growing body of literature emphasizing the importance of high-frequency meteorological data for improving ET estimation accuracy in arid and semi-arid regions. Full article

Leaf phenology is key to ecosystem functioning by regulating carbon, water, and energy fluxes and influencing vegetation productivity. Yet, detecting land surface phenology (LSP) in drylands using remote sensing remains particularly challenging due to sparse and heterogeneous vegetation cover, high spatiotemporal variability, and complex spectral signals. Unlike the Northern Hemisphere, these challenges are further compounded in the Southern Hemisphere (SH), where several regions experience year-round moderate temperatures. When combined with irregular rainfall, this leads to highly variable vegetation activity throughout the year. However, LSP dynamics in the SH remain poorly understood. This study presents a review of remote sensing-based phenology research in drylands, integrating (i) a synthesis of global methodological advances and (ii) a systematic analysis of peer-reviewed studies published from 2015 through April 2025 focused on SH drylands. This review reveals a research landscape still dominated by conventional vegetation indices (e.g., NDVI) and moderate-spatial-resolution sensors (e.g., MODIS), though a gradual shift toward higher-resolution sensors such as PlanetScope and Sentinel-2 has emerged since 2020. Despite the widespread use of start- and end-of-season metrics, their accuracy varies greatly, especially in heterogeneous landscapes. Yet, advanced products such as solar-induced chlorophyll fluorescence or the fraction of absorbed photosynthetically active radiation were rarely employed. Gaps remain in the representation of hyperarid zones, grass- and shrub-dominated landscapes, and large regions of Africa and South America. Our findings highlight the need for multi-sensor approaches and expanded field validation to improve phenological assessments in dryland environments. The accurate differentiation of vegetation responses in LSP is essential not only for refining phenological metrics but also for enabling more realistic assessments of ecosystem functioning in the context of climate change and its impact on vegetation dynamics. Full article

Improving photovoltaic (PV) panel performance under extreme climatic conditions is critical for advancing sustainable energy systems. In hyper-arid regions, elevated operating temperatures significantly reduce panel efficiency. This study investigates and compares three cooling techniques—air cooling, water cooling, and porous media cooling—using thermal and electrical modeling based on CFD simulations in ANSYS. The numerical model replicates a PV system operating under peak solar irradiance (900 W/m²) and realistic ambient conditions in Adrar, Algeria. Simulation results show that air cooling leads to a modest temperature reduction of 6 °C and a marginal efficiency gain of 0.25%. Water cooling, employing a top-down laminar flow, reduces cell temperature by over 35 °C and improves net electrical output by 30.9%, despite pump energy consumption. Porous media cooling, leveraging passive evaporation through gravel, decreases panel temperature by around 30 °C and achieves a net output gain of 26.3%. Mesh sensitivity and validation against experimental data support the accuracy of the model. These findings highlight the significant potential of water and porous material cooling strategies to enhance PV performance in hyper-arid environments. The study also demonstrates that porous media can deliver high thermal effectiveness with minimal energy input, making it a suitable low-cost option for off-grid applications. Future work will integrate long-term climate data, real diffuser geometries, and experimental validation to further refine these models. Full article

The use of service (cover) crops is widely practiced in soil agriculture due to their many benefits, including enhanced nutrient supply and improved soil health. Bacteria, as major decomposers of plant residues in the soil, play essential roles in nutrient cycling. This study examined the impact of various almond orchard management practices on the soil microbial community composition in a hyper-arid ecosystem. High-throughput sequencing was used to compare the microbial communities in two adjacent almond orchards managed with either organic (ORG) or regenerative agriculture (RA) practices, alongside an uncultivated (UC) site. Notably, little is known about the responses of soil bacterial communities in hyper-arid regions to intercrop mulch from service crops. This study may offer insights into the ecological limits of the benefits of service crops in promoting soil health under extreme conditions. Our findings demonstrate that RA management can alter soil organic carbon levels and reshape microbial communities by increasing overall bacterial abundance and enriching specific keystone taxa. These changes may have significant implications for nutrient cycling processes in hyper-arid agroecosystems. Full article

“Production–Living–Ecological” spatial conflicts (PLECs) are critical issues arising from regional land development, affecting economic, social, and ecological security. Identifying and analyzing these conflicts’ spatiotemporal characteristics is essential for sustainable development. This study focuses on the Tuha region, which experiences an extremely arid climate, classifying the region’s “Production–Living–Ecological” (PLE) spaces into four types: living–production, ecological–production, production–ecological, and ecological spaces. A spatial conflict measurement model based on landscape patterns was developed to analyze the evolution of PLECs from 2000 to 2020. Additionally, the PLUS model was used to simulate PLEC patterns in 2030 under different development scenarios. The results indicate that between 2000 and 2020, the area proportions in the Tuha region ranked from largest to smallest as follows: ecological space, ecological–production space, production–ecological space, and living–production space. The area of living–production space increased, while production–ecological space first increased and then stabilized, and the areas of ecological and ecological–production spaces decreased. From 2000 to 2020, spatial conflicts in the region were predominantly characterized by mild weak conflicts. High–high PLEC clusters were concentrated in urban and surrounding areas of Gaochang District, Toksun County, Shanshan County, and Yizhou District, while low–low clusters were found in the Eastern Tianshan Mountains and northern Barkol Kazakh Autonomous County. NDVI, GDP, population, and proximity to roads positively influenced PLECs, while elevation, slope, aspect, and precipitation had inhibitory effects. Under different development scenarios, the natural development scenario leads to the most severe spatial conflicts, while the cropland protection scenario reduces PLECs and enhances regional welfare, making it the optimal pathway for future development. Full article

The interplay between terrestrial water storage and vegetation dynamics in arid regions is critical for understanding ecohydrological responses to climate change and human activities. This study examines the coupling between total water storage anomaly (TWSA) and vegetation greenness changes in the Hexi Corridor, an arid region in northwestern China consisting of three inland river basins—Shule, Heihe, and Shiyang—from 2002 to 2022. Utilizing TWSA data from GRACE/GRACE-FO satellites and MODIS Enhanced Vegetation Index (EVI) data, we applied a trend analysis and partial correlation statistical techniques to assess spatiotemporal patterns and their drivers across varying aridity gradients and land cover types. The results reveal a significant decline in TWSA across the Hexi Corridor (−0.10 cm/year, p < 0.01), despite a modest increase in precipitation (1.69 mm/year, p = 0.114). The spatial analysis shows that TWSA deficits are most pronounced in the northern Shiyang Basin (−600 to −300 cm cumulative TWSA), while the southern Qilian Mountain regions exhibit accumulation (0 to 800 cm). Vegetation greening is strongest in irrigated croplands, particularly in arid and hyper-arid regions of the study area. The partial correlation analysis highlights distinct drivers: in the wetter semi-humid and semi-arid regions, precipitation plays a dominant role in driving TWSA trends. Such a rainfall dominance gives way to temperature- and human-dominated vegetation greening in the arid and hyper-arid regions. The decoupling of TWSA and precipitation highlights the importance of human irrigation activities and the warming-induced atmospheric water demand in co-driving the TWSA dynamics in arid regions. These findings suggest that while irrigation expansion cause satellite-observed greening, it exacerbates water stress through increased evapotranspiration and groundwater depletion, particularly in most water-limited arid zones. This study reveals the complex ecohydrological dynamics in drylands, emphasizing the need for a holistic view of dryland greening in the context of global warming, the escalating human demand of freshwater resources, and the efforts in achieving sustainable development. Full article

Accurate forest cover maps are essential for forest conservation and sustainable development. Numerous global forest cover products have emerged in recent years; however, most tend to neglect sparsely forested arid and semi-arid areas, such as the Three-North Shelter Forest (TNSF) Program Region in China. Despite their sparse distribution, forests in these areas play a vital role in maintaining global ecological balance and biodiversity. Therefore, a comprehensive evaluation of these products is necessary. In this study, the performance of nine global forest cover products was systematically investigated at a 10–30 m resolution (GlobeLand30, GLC_FCS30D, FROM-GLC30, FROM-GLC10, ESA World Cover, ESRI Land Cover, GFC30, GFC 2020, and GFC) in the TNSF region around 2020. Specifically, a novel and comprehensive validation dataset was first generated by integrating all available open-access validation datasets in the TNSF region after visual interpretation. Second, the consistency and accuracy of nine forest cover products were evaluated, and their discrepancies with government statistical data were analyzed. The results indicate that GFC2020 provides the highest overall accuracy (OA) of 90.49%, followed by ESA World Cover, while GlobeLand30 had the lowest accuracy of 84.78%. Meanwhile, compared with statistical data, all nine products underestimated forest areas, especially in these hyper-arid zones (aridity index < 0.03). Notably, 31.04% of the area is identified as forest by only one product, attributable to differences in forest definitions and remote sensing data among the products. Therefore, this study provides a detailed assessment and analysis of nine global forest cover products from multiple perspectives, offering valuable insights for users in selecting appropriate forest cover products and supporting forest management. Full article

Groundwater plays a vital role in sustaining dryland ecosystems, yet our understanding of the spatiotemporal dynamics of groundwater–vegetation interactions in endorheic river basins remains limited. In this study, the covariation between the normalized difference vegetation index (NDVI) and water table depth (WTD) in the Heihe River Basin (HRB), a representative endorheic system, is investigated via multisource data and generalized additive models (GAMs). The results indicate that the NDVI peaks in summer (July), with a corresponding decline in the WTD, indicating a basin-wide negative correlation. Spatial analysis reveals distinct upstream–downstream gradients: upstream regions exhibit strong seasonal synchronization, whereas midstream and downstream areas show weaker correlations because of mixed surface and groundwater influences. Landcover and climate significantly affect these interactions, with arid zones showing the strongest negative correlations (ρ = −0.38), particularly in wetlands, whereas humid regions show nonsignificant relationships. Geomorphological analysis highlights stronger correlations in mountainous areas than in low-relief plains. Positive correlations are the most prevalent in arid regions (54.5%), followed by hyper-arid regions (28.9%), while negative correlations also dominate arid regions (54.6%), followed by semiarid regions (27.6%). Cross-correlation analysis reveals synchronous NDVI–WTD changes at 95% of the grid points, with 5% exhibiting time lags (1–3 months), indicating localized hydrogeological feedback. Notably, 32% of the zones with negative correlations overlap with groundwater-dependent ecosystems (GDEs). GAM analysis reveals that 87.9% of the spatial variability in the NDVI–WTD correlations is attributed to environmental factors, with climate (26.6%) and hydrogeology (19.5%) as the dominant contributors. These findings provide critical insights into groundwater–vegetation interactions in arid ecosystems and offer valuable implications for sustainable water resource management. Full article

Drought is a major meteorological disaster that affects the growth of spring maize in Inner Mongolia. Understanding the spatiotemporal characteristics of drought is crucial for maintaining crop production. This study categorized Inner Mongolia into five climatic regions based on geography and climate characteristics: hyper-arid, arid, semi-arid, dry and semi-humid, and moist and semi-humid, reflecting Regions I to V, respectively. Based on data collected from 107 meteorological stations, the standardized precipitation evapotranspiration index (SPEI) was used to assess the characteristics of drought occurrence in different climatic regions during the spring maize growing season over the past 60 years, as well as the impact of drought on yield. SPEI decreased across all regions during growth periods, with mid-growth stages showing the smallest decline and a slight slowdown in drought severity. Spatially, 15 stations showed reduced drought during the early growth stage, which increased to 20 stations during the mid-growth stage. The overall drought trend of intensification was obtained across various climate regions, with Region I showing the most severe drought. The drought frequency during the growth period of spring maize ranged from 20% to 42%, and the drought frequency decreased from light drought, moderate drought, and severe drought to extreme drought. The drought range in each growth stage increased, with localized and regional drought dominating the region. The drought intensity also increased. Precipitation is the main factor affecting spring maize yield, and water replenishment during the early and middle stages of growth is crucial. These findings provide a basis for efficient water resource management in the region. Full article

Precipitation events have been occurring more frequently in the hyper-arid region of the Taklamakan Desert (TD) under recent climate change. However, in this water-limited environment, the microphysical characteristics of precipitation, as well as their link to rainfall intensity, remain unclear. To address this, this study utilizes dual-frequency precipitation radar (DPR) data of the Global Precipitation Measurement (GPM) satellite from 2014 to 2023 to analyze the microphysical characteristics of different precipitation types (stratiform and convective) in the TD during the summer. The results show that liquid water path (LWP) is a key factor influencing precipitation type: when LWP is insufficient, stratiform precipitation is more likely to occur (84.1%), while convective precipitation is difficult to occur (15.9%). Microphysical process analysis indicates that in convective precipitation, abundant low-level moisture leads to the growth of liquid particles primarily through the collision–coalescence process (59.7%), resulting in larger raindrop diameters (1.7 mm) and lower concentrations (31.9 mm⁻¹ m⁻³). In contrast, stratiform precipitation, with limited LWP, primarily involves the melting and breaking-up of high-level ice-phase particles, leading to smaller raindrop diameters (1.2 mm) and higher concentrations (34.3 mm⁻¹ m⁻³). The warm rain process plays a significant role in raindrop formation in both types of precipitation. The greater (lesser) the amount of LWP, the larger (smaller) the contribution of collision–coalescence (break-up) processes, and the larger (smaller) the raindrop diameter and precipitation intensity. Full article

Glacial retreat is a major global challenge, particularly in arid and semi-arid regions where glaciers serve as critical water sources. This research focuses on glacial retreat and its impact on land cover and land use changes (LULC) in the Barroso Mountain range, Tacna, Peru, which is a critical area for water resources in the hyperarid Atacama Desert. Employing advanced remote sensing techniques through the Google Earth Engine (GEE) cloud computing platform, we analyzed historical trends (1985–2022) using Landsat satellite imagery. A normalized index classification was carried out to generate LULC maps for the years 1986, 2001, 2012, and 2022. Future projections until 2042 were developed using Cellular Automata–Markov (CA–Markov) modeling in QGIS, incorporating six predictive environmental variables. The resulting maps presented an overall accuracy (OA) greater than 83%. Historical analysis revealed a dramatic glacier reduction from 44.7 km² in 1986 to 7.4 km² in 2022. In contrast, wetlands expanded substantially from 5.70 km² to 12.14 km², indicating ecosystem shifts potentially driven by glacier meltwater availability. CA–Markov chain modeling projected further glacier loss to 3.07 km² by 2042, while wetlands are expected to expand to 18.8 km² and bodies of water will reach 4.63 km². These future projections (with accuracies above 84%) underline urgent implications for water management, environmental sustainability, and climate adaptation strategies, particularly with regard to downstream hydrological risks and ecosystem resilience. Full article

This study integrates morphometric analysis, remote sensing, and GIS with the analytical hierarchical process (AHP) to identify high potential groundwater recharge areas in Wadi Abadi, Egyptian Eastern Desert, supporting sustainable water resource management. Groundwater recharge primarily comes from rainfall and Nile River water, particularly for Quaternary aquifers. The analysis focused on the Quaternary and Nubian Sandstone aquifers, evaluating 16 influencing parameters, including elevation, slope, rainfall, lithology, soil type, and land use/land cover (LULC). The drainage network was derived from a 30 m-resolution Digital Elevation Model (DEM). ArcGIS 10.8 was used to classify the basin into 13 sub-basins, with layers reclassified and weighted using a raster calculator. The groundwater potential map revealed that 24.95% and 29.87% of the area fall into very low and moderate potential categories, respectively, while low, high, and very high potential zones account for 18.62%, 17.65%, and 8.91%. Data from 41 observation wells were used to verify the potential groundwater resources. In this study, the ROC curve was applied to assess the accuracy of the GWPZ models generated through different methods. The validation results indicated that approximately 87% of the wells corresponded accurately with the designated zones on the GWPZ map, confirming its reliability. Over-pumping in the southwest has significantly lowered water levels in the Quaternary aquifer. This study provides a systematic approach for identifying groundwater recharge zones, offering insights that can support resource allocation, well placement, and aquifer sustainability in arid regions. This study also underscores the importance of recharge assessment for shallow aquifers, even in hyper-arid environments. Full article

This study compares the chemical composition, antioxidant capacity, and antibacterial properties of lavender essential oils extracted using microwave-assisted extraction (MAE) and supercritical CO₂ extraction (SCDE). Gas chromatography–mass spectrometry analysis revealed that the MAE oil contained higher levels of linalyl acetate (36.19%) and linalool (28.29%) compared with the SCDE oil, which had values of 28.72% and 27.48%, respectively. The MAE oil also showed superior antioxidant activity, with DPPH IC₅₀ values of 72.99 mg/mL and FRAP values of 1.31 mM Fe²⁺/g, compared with 80.84 mg/mL and 1.14 mM Fe²⁺/g for the SCDE oil. Antibacterial tests indicated that the MAE oil exhibited lower MIC values, demonstrating twice the antibacterial activity against Bacillus cereus NRRL B3711, Bacillus subtilis PY79, and Enterococcus faecalis ATCC 29212 compared with the SCDE oil. These results highlight the superior bioactivity of MAE-extracted lavender oil, making MAE a preferred method for high-quality oil extraction from drought-affected lavender plants. Full article

Wildfires and drought stressors can significantly limit forest recovery in Mediterranean-type ecosystems. Since 2010, the region of central Chile has experienced a prolonged Mega Drought, which intensified into a Hyper Drought in 2019, characterized by record-low precipitation and high temperatures, further constraining forest recovery. This study evaluates short-term (5-year) post-fire vegetation recovery across drought gradients in two types of evergreen sclerophyllous forests and a thorny forest and shrubland, analyzing Landsat time series (1987–2022) from 42 wildfires. Using the LandTrendr algorithm, we assessed post-fire forest recovery based on NDVI changes between pre-fire values and subsequent years. The results reveal significant differences in recovery across drought gradients during the Hyper Drought period, among the three forest types studied. The xeric forest, dominated by Quillaja saponaria and Lithrea caustica, showed significant interaction effects between levels of drought and fire severity, while the thorny forest and shrubland displayed no significant interaction effects. The mesic forest, dominated by Cryptocarya alba and Peumus boldus, exhibited additional significant differences in recovery between the Hyper Drought and Mega Drought periods, along with significant interaction effects. These findings underscore the critical role of prolonged, severe drought in shaping forest recovery dynamics and highlight the need to understand these patterns to improve future forest resilience under increasingly arid conditions. Full article

The ecosystem’s gross primary productivity (GPP) and greenness, as indicated by the normalized difference vegetation index (NDVI), are both essential ecological indicators used to evaluate how ecosystems responded to climate variability. However, the relationships between NDVI and GPP under the influence of drying and wetting and its characteristics along aridity (AI) gradients were not yet fully understood. In this study, we investigated the relationships of the NDVI-GPP (i.e., the strength of the coupling and the sensitivity, as quantified by the coefficient of determination (R²) and slope of the linear regression, respectively) along the aridity gradients during the growing season from 1982 to 2018 in China. The results show that the coupling between NDVI and GPP was stronger (i.e., high R²) in semi-arid regions (0.24) compared to humid and hyper-humid regions (R² values were 0.11). For different plant functional types (PFTs), decoupling occurred in ENF with a determination coefficient value (R²) of 0.04, whereas GRA shows a higher coupling with an R² of 0.20. The coupling trend experienced a shift in semi-arid regions, characterized by an aridity index (AI) ranging from 0.20 to 0.50. Additionally, the sensitivity of GPP to NDVI also decreased with increasing aridity. The slope values were 0.19, 0.21, 0.24, 0.20, 0.11, and 0.11 in hyper-arid, arid, semi-arid, dry sub-humid, humid, and hyper-humid, respectively. What is more, asynchronous changes in vegetation productivity and greenness can be detected by capturing the inter-annual variability (IAV) of NDVI and GPP. The IAV of GPP steadily decreased with the aridity gradients, while the IAV of NDVI present fluctuated, suggesting that NDVI was more variable than GPP under the influence of drying and wetting conditions. Our study suggests that there may be a stronger trade-off between ecosystem greenness and photosynthesis in more humid areas. Full article