Search Results (116)

Forest drought monitoring tools are crucial for managing tree water stress and enhancing ecosystem resilience. The Forest Drought Response Index (ForDRI) was developed to monitor drought conditions in forested areas across the contiguous United States (CONUS), integrating vegetation health, climate data, groundwater, and soil moisture content. This study evaluated ForDRI using Pearson correlations with the Bowen Ratio (BR) at 24 AmeriFlux sites and Spearman correlations with the Tree-Ring Growth Index (TRSGI) at 135 sites, along with feedback from 58 stakeholders. CONUS was divided into four forest subgroups: (1) the West/Pacific Northwest, (2) Rocky Mountains/Southwest, (3) East/Northeast, and (4) South/Central/Southeast Forest regions. Strong positive ForDRI-TRSGI correlations (ρ > 0.7, p < 0.05) were observed in the western regions, where drought significantly impacts growth, while moderate alignment with BR (R = 0.35–0.65, p < 0.05) was noted. In contrast, correlations in Eastern and Southern forests were weak to moderate (ρ = 0.4–0.6 for TRSGI and R = 0.1–0.3 for BR). Stakeholders’ feedback indicated that ForDRI realistically maps historical drought years and recent trends, though suggestions for improvements, including trend maps and enhanced visualizations, were made. ForDRI is a valuable complementary tool for monitoring forest droughts and informing management decisions. Full article

The Yellow River Basin (YRB) is a critical ecological zone in China now confronting growing tensions between land conservation and development. This study combines land use, climate, and socio-economic data with spatial–statistical models (GeoDetector [GD]–Patch-generating Land Use Simulation [PLUS]–Integrated Valuation of Ecosystem Services and Trade-Offs [InVEST]) to analyze land use changes (2000–2020), evaluate habitat quality, and simulate scenarios to 2040. Key results include the following: (1) Farmland was decreased by the conversion to forests (+3475 km²) and grasslands (+4522 km²), while construction land expanded rapidly (+11,166 km²); (2) the population and Gross Domestic Product (GDP) pressures drove the farmland loss (q = 0.148 for population, q = 0.129 for GDP), while synergies between evapotranspiration (ET) and the Normalized Difference Vegetation Index (NDVI) promoted forest/grassland recovery (q = 0.155); and (3) ecological protection scenarios increased the grassland area by 12.94% but restricted the construction land growth (−13.84%), with persistent unused land (>3.61% in Inner Mongolia) indicating arid-zone risks. The Habitat Quality-Autocorrelated Coupling Index (HQACI) declined from 0.373 (2020) to 0.345–0.349 (2040), which was linked to drought, groundwater loss, and urban expansion. Proposed strategies including riparian corridor protection, adaptive urban zoning, and gradient-based restoration aim to balance ecological and developmental needs, supporting spatial planning and enhancing the basin-wide habitat quality. Full article

Drought, a natural phenomenon intricately intertwined with the broader canvas of climate change, exacts a heavy toll by ushering in acute terrestrial water scarcity. Its ramifications reverberate most acutely within the agricultural heartlands, particularly those nestled in arid regions. To address this pressing issue, this study harnesses the temperature vegetation dryness index (TVDI) as a robust drought indicator, enabling a granular estimation of land water content trends. This endeavor unfolds through the sophisticated integration of geographic information systems (GISs) and remote sensing technologies (RSTs). The methodology bedrock lies in the judicious utilization of 72 high-resolution satellite images captured by the Landsat 7 and 8 platforms. These images serve as the foundational building blocks for computing TVDI values, a key metric that encapsulates the dynamic interplay between the normalized difference vegetation index (NDVI) and the land surface temperature (LST). The findings resonate with significance, unveiling a conspicuous and statistically significant uptick in the TVDI time series. This shift, observed at a confidence level of 0.05 (Z_S = 1.648), raises a crucial alarm. Remarkably, this notable surge in the TVDI exists in tandem with relatively insignificant upticks in short-term precipitation rates and LST, at statistically comparable significance levels. The implications are both pivotal and starkly clear: this profound upswing in the TVDI within agricultural domains harbors tangible environmental threats, particularly to groundwater resources, which form the lifeblood of these regions. The call to action resounds strongly, imploring judicious water management practices and a conscientious reduction in water withdrawal from reservoirs. These measures, embraced in unison, represent the imperative steps needed to defuse the looming crisis. Full article

This study evaluated the surface area and volume dynamics of the largest and most important natural lakes in the Republic of Moldova: Manta and Beleu. Lakes and surrounding areas represent the main natural ecosystem of the country, are a shelter to thousands of animals and plant species, and are included in the protected areas network. The lakes are situated in the Lower Prut floodplain, with the main water sources being the Prut River through channels, as well as groundwater, surface runoff and precipitation. Regulations of the Prut River flow, climate change, and the increasing frequency of droughts and floods have a certain impact on lake extension and volume dynamics. The main methods used to evaluate surface area variation are the analysis of satellite images (Landsats, from 1975 to 2024) and the application of the NDWI index. As a result, it was identified that the extent of Beleu Lake varied from 0 to 19 km², and that of Manta Lake from 5 to 27 km². The actual average surface area is 7–11 km² for Beleu and 15–19 km² for Manta. The last catastrophic drought in 2022 decreased the surface area of Beleu by up to 3.7 km² and that of Manta by up to 5 km², while the most recent floods in 2020 extended the area of Beleu by up to 12 km² and that of Manta by up to 27.3 km². The volumes of Beleu vary from 0 to 40 mil.m³, with an average of 6.5–9 mil.m³, and of Manta from 4.5 mil.m³ to 55 mil.m³, with an average of 15–22 mil.m³. The shoreline lengths corresponding to the average water surface areas are 14–20 km for Beleu and 35–40 km for Manta. Full article

There are serious ecological and environmental risks associated with groundwater level decline, particularly in areas with little in situ monitoring. In order to monitor and assess the resilience and dependability of groundwater storage, this paper proposes a solid methodology that combines data from land surface models and satellite gravimetry. In particular, the GRACE Groundwater Drought Index (GGDI) is used to analyze the estimated groundwater storage anomalies (GWSA) from the Gravity Recovery and Climate Experiment (GRACE) and the Global Land Data Assimilation System (GLDAS). Aquifer resilience, or the likelihood of recovery after stress, and aquifer reliability, or the long-term probability of remaining in a satisfactory state, are calculated using the core method. The two main components of the methodology are (a) calculating GWSA by subtracting the surface and soil moisture components from GLDAS, total water storage from GRACE, and comparing the results to in situ groundwater level data; and (b) standardizing GWSA time series to calculate GGDI and then estimating aquifer resilience and reliability based on predetermined threshold criteria. Using this framework, we validate GRACE-derived GWSA with in situ observations in eight sub-basins of the Chao Phraya River (CPR) basin, obtaining Pearson correlation coefficients greater than 0.82. With all sub-basins displaying values below 35%, the results raise significant questions about resilience and dependability. This method offers a framework that can be applied to assessments of groundwater sustainability worldwide. Full article

Frequent droughts significantly threaten economic development, necessitating effective long-term drought monitoring. The Gravity Recovery and Climate Experiment (GRACE) satellite and its follow-on mission along with Global Navigation Satellite System (GNSS) inversion technologies provide long-term terrestrial water storage signals. However, their limitations in temporal resolution and spatial continuity are inadequate for current requirements. To solve this problem, this study combines a daily terrestrial water storage anomaly (TWSA) reconstruction method with the GNSS inversion technique to explore daily, spatially continuous TWSA in China’s Yellow River Basin (YRB). Furthermore, the Daily Drought Severity Index (DDSI) is employed to analyze drought dynamics in the YRB. Finally, by reconstructing the climate-driven water storage anomalies model, this study explores the influence of climate and human factors on drought. The results indicate the following: (1) The reconstructed daily TWSA product demonstrates superior quality compared to other available products and exhibits a discernible correlation with GNSS-derived daily TWSA data, while REC_TWSA is closer to the GRACE-based TWSA dataset. (2) The DDSI demonstrates superior drought monitoring capabilities compared to conventional drought indices. During the observation period from 2004 to 2021, the DDSI detected the most severe drought event occurring between 30 October 2010 and 10 September 2011. (3) Human activities become the primary driver of drought in the YRB. The high correlation of 0.81 between human-driven water storage anomalies and groundwater storage anomalies suggests that the depletion of TWSA is due to excessive groundwater extraction by humans. This study aims to provide novel evidence and methodologies for understanding drought dynamics and quantifying human factors in the YRB. Full article

Our understanding of water and salt changes in the context of declining groundwater levels in the Tarim Basin remains limited, largely due to the scarcity of hydrological monitoring stations and field observation data. This study utilizes water and salt monitoring data from 474 apparent electromagnetic induction (ECa, measured by EM38-MK2 device) sites across seven oases, combined with groundwater level observation data from representative areas, to analyze the spatiotemporal changes in ECa within the oases of the Tarim Basin from 2000 to 2022. Specific results are shown below: Numerous algorithmic predictions show the ensemble learning algorithm with the smallest error explained 71% of the ECa spatial variability. The ECa was particularly effective at identifying areas where groundwater extends beyond a depth of 5 m, demonstrating increased efficacy when ECa readings exceed the threshold of 1100 mS/m. Our spatiotemporal analysis spanning the years 2000 to 2022 has revealed a significant decline in ECa values within the artificially irrigated zones of the oasis clusters. In contrast, the transitional ecotone between the desert and the oases in Atux, Aksu, Kuqa, and Luntai have experienced a significant increase in ECa value. The variations observed within the defined Zone B, where ECa values ranged from 800 mS/m to 1100 mS/m, and Zone A, characterized by ECa values exceeding 1100 mS/m, aligned with the periodic fluctuations in the groundwater drought index (GDI), indicating a clear pattern of correlation. This study demonstrated that ECa can serve as a valuable tool for revealing the spatial and temporal variations of water resources in arid zones. The results obtained through this approach provided essential references for the local scientific management of soil and water resources. Full article

Groundwater drought, a significant natural disaster in arid and semi-arid regions, contributes to numerous consecutive issues. Due to the inherent complexity of groundwater flow systems, accurately quantifying and describing this phenomenon remains a challenging task. As a result of excessive agricultural development, the Marand Plain in northwestern Iran is experiencing both groundwater drought and land subsidence. The present study provides the first in-depth investigation into the intricate link between groundwater drought and subsidence. For this purpose, the open-source package LiCSBAS, integrated with the automated Sentinel-1 InSAR processor (COMET-LiCSAR), was utilized to assess land subsidence. The Standard Groundwater Index (SGI) was computed to quantify groundwater drought, aquifer characteristics, and human-induced disturbances in the hydrological system, using data collected from piezometric wells in a confined aquifer. The results revealed a negative deformation of 65 cm over a 75-month period, affecting an area of 57,412 hectares within the study area. The analysis showed that drought duration and severity significantly influence land subsidence, with longer and more severe droughts leading to greater subsidence, while more frequent drought periods are primarily associated with subsidence magnitude. Multi-resolution Wavelet Transform Coherence (WTC) analysis revealed significant correlations between groundwater drought and InSAR-derived land deformation in the 8–16-month period. Full article

Oases are part of the natural wealth and heritage of Morocco and contribute to the social, economic, and touristic environment. Morocco has lost more than 2/3 of its oases during the past century due to water scarcity, succession of drought periods, climate change and over-exploitation of groundwater resources. Palm trees are strongly dependent on irrigation and availability of surface water as soon as the water table depth falls below the root zone of 9 m. Improving management and monitoring of oasis ecosystems is strongly encouraged by UNESCO Biosphere Reserve and RAMSAR guidelines. The Boudenib and Tafilalet oases are among the biggest palm groves located in the south-eastern part of Morocco. These oases belong to catchments of the rivers Guir and Ziz, respectively. This paper uses remotely sensed data from PROBA-V for monitoring vegetation in oases, and linking vegetation characteristics to water availability, water management and quality and quantity of date crops. The Normalized Differential Vegetation Index (NDVI) derived from optical images provides a good estimation of changes in vegetation cover over time. Images of various spatial resolutions (100 m, 300 m and 1 km) obtained with the frequently revisiting Belgian satellite PROBA-V and available since 2014, can be successfully used for deriving time series of vegetation dynamics. TREX—Tool for Raster data Exploration—is a Python-GDAL processing tool of PROBA-V NDVI images for analyzing vegetation dynamics, developed at the Vrije Universiteit Brussel and available online. TREX has various applications, but the main functionality is to provide an automatic processing of PROBA-V satellite images into time series of NDVI and LAI, used in vegetation monitoring of user-defined points of interest. This study presents the results of application of TREX in the arid ecosystems of the Boudenib oasis for the period 2014–2018. The resulting NDVI and LAI time series are also compared to time series of groundwater depth and date crops quantity and quality. Low LAI is observed when water depth is low, and the palm trees lose their greenery. Low LAI is also correlated to low quantity and quality of dates in October 2015 and October 2017. PROBA-V images can therefore be used for monitoring the health of palm trees in oasis environments. However, considering the fact that the PROBA-V satellite mission has ended, this approach could instead be applied to Sentinel-3 data using the same analysis. These results have important implications for water management in the area and can help decision-makers to make better decisions about prevention of water scarcity in the region. Full article

Understanding and analyzing low river flows are some of key tasks of effective water management, particularly in Chile’s Mediterranean regions, where irregular rainfall distribution leads to drought and water scarcity. This study aims to assess low-flow trends in the four major Chilean river basins (Maipo, Rapel, Maule, and Biobío) by calculating three key hydrological indices: the mean annual minimum and maximum flows (MAM), the base flow index (BFI), and the standardized precipitation index (SPI), using data from 18 hydrometric stations. The indicators of hydrologic alteration (IHA) tool was applied to calculate the MAM and BFI to assess flow variability and groundwater contributions. The SPI was calculated to examine hydrological drought conditions and evaluate how these conditions affect river flow behavior, correlating reduced low river flows with precipitation trends at the beginning of the dry season. Statistical analysis was conducted through the ordinary least squares (OLS) test for normally distributed data, and non-parametric tests, including the Mann–Kendall test, as well as Sen’s slope estimation, for data not meeting normality requirements. The results, presented both analytically and graphically, reveal trends in river flow indices and variations across the river basins, identifying critical areas of reduced flow that may require enhanced water management strategies. Full article

This study introduces the Simple Coincidence Deficit Index (SCDI) and employs Drought Severity Analysis (DSA) to enhance drought detection and assess patterns and persistency across the Mediterranean basin. Utilizing the Global Land Data Assimilation System (GLDAS) based multi-satellite data for precipitation (P) and groundwater storage (GWS), this research applies both SCDI and DSA to visualize and interpret hydrological event time series across the region. The SCDI uniquely combines precipitation and groundwater levels to provide a comprehensive view of drought intensity. DSA tracks the persistence of water deficit and allows straightforward analysis without requiring transformation or normalization, making it easier to use with remote sensing data. The DSA determines the longest drought periods across various time windows, quantifying the number of months a hydrological deficit persists based on groundwater and precipitation data. Findings show that significant deficits are observed in specific months, which become less apparent in shorter time windows ($\Delta$ = 1) due to their rarity. Conversely, in broader time windows ($\Delta$ = 12), the cumulative effects of these deficits significantly impact seasonal and yearly averages, with implications extending from lower to higher latitudes. Additionally, as time windows extend, the variability in SCDI values increases across all regions, rendering long-term drought conditions more visible, particularly in North Africa. These findings form the basis of future studies focusing on understanding of drought phenomena and enhancing drought predictability using remote sensing data. The proposed DSA and SCDI methodologies represent a significant advancement over traditional indices by offering new tools for more effective drought analysis. Full article

Different countries face significant challenges in managing water-related natural hazards, such as floods and shortages, while ensuring adequate water quality and quantity to satisfy human needs and preserve ecosystems. Climate change projections exacerbate this situation by intensifying the hydrological cycle, resulting in substantial changes in precipitation patterns, evapotranspiration, and groundwater storage. This study reviews water security challenges across 43 countries, drawing on 128 articles obtained from databases including EBSCOHOST, Scopus and ResearchGate, as well as specific journals. Key search terms included “water security”, “water security and climate change”, “water scarcity”, “water risk index”, “water balance”, “water assessment”, and “land use and land cover change”. The analysis reveals the main water security issues present in 43 countries (flash floods, drought and water quality), and the response measures identified these challenges to water security. All the countries studied face one or more critical water-related effects. Afghanistan, Bangladesh, India, and Mexico were identified as the most severely affected, dealing with a combination of water scarcity, flooding, and water pollution. The most suggested strategies for improving water security include sustainable urban planning, improving consumption efficiency, strategic land-use planning, applying technologies to predict availability of water resources and planning according to variations in resource availability over time. In addition, other general actions include enhancing water storage infrastructure, improving consumption efficiency and adopting sustainable urban planning. Full article

Remnant explosive devices are a deadly nuisance to both military personnel and civilians. Traditional mine detection and clearing is dangerous, time-consuming, and expensive. And routine production and testing of explosives can create groundwater contamination issues. Remote detection methods could be rapidly deployed in vegetated areas containing explosives as they are known to cause stress in vegetation that is detectable with hyperspectral sensors. Hyperspectral imagery was employed in a mesocosm study comparing stress from a natural source (drought) to that of plants exposed to two different concentrations of Royal Demolition Explosive (RDX; 250 mg kg⁻¹, 500 mg kg⁻¹). Classification was accomplished with the machine learning algorithms Support Vector Machine (SVM), Random Forest (RF), and Least Discriminant Analysis (LDA). Leaf-level plant data assisted in validating plant stress induced by the presence of explosives and was detectable. Vegetation indices (VIs) have historically been used for dimension reduction due to computational limitations; however, we measured improvements in model precision, recall, and accuracy when using the complete range of available wavelengths. In fact, almost all models applied to spectral data outperformed their index counterparts. While challenges exist in scaling research efforts from the greenhouse to the field (i.e., weather, solar lighting conditions, altitude when imaging from a UAV, runoff containment, etc.), this experiment is promising for subsequent research efforts at greater scale and complexity aimed at detecting emerging contaminants. Full article

Groundwater plays a crucial role in the formation of the Badain Jaran Desert-Sand Dune Lake System, which has been designated a UNESCO World Heritage Site in 2024. However, the region’s wetland ecosystem is significantly impacted by climate change and human activities. This study utilizes GRACE satellite data and in situ observation data to establish a groundwater storage anomaly (GWSA) time series for the Badain Jaran Desert and its surrounding areas (BJDCA) from 2003 to 2022. The analysis reveals the spatiotemporal patterns of groundwater drought and sustainability, as well as the underlying factors affecting regional groundwater sustainability. The results indicate that 99.2% of the study area exhibited a significant decline in GWSA (α ≤ 0.01), with the annual mean GRACE Groundwater Drought Index (GGDI) dropping from 1.44 to −1.54, reflecting a worsening groundwater drought. In 2022, the GGDI in the southeastern part of the BJDCA reached as low as −3.04, highlighting severe groundwater stress. Furthermore, the Sustainability Index (SI) of the study area declined markedly from 1.00 to 0.01, underscoring the critical impact of human activities on groundwater resources in the BJDCA. These findings provide valuable insights for formulating more effective groundwater resource management policies and promoting sustainable development in arid regions. Full article

Analysis of the temporal relationship between meteorological drought and hydrological drought is crucial in monitoring water resource availability. This study examined the linear and lagged relationships of the spread of meteorological drought to hydrological drought and their joint effects on low-flow drought variability in the Oum Er-Rbia (OER) watershed. To this end, random forest (RF) model and statistical methods were used to study the characteristics of the temporal relationships between meteorological and hydrological drought indices at monthly, seasonal, and annual scales. The various analyses revealed that the relationship between hydrological and meteorological drought is mainly a function of the time scale considered, the choice of indices to describe each type of drought and the season considered. The hydrological drought of surface water and snow cover is synchronized with the meteorological drought at the monthly, seasonal, and annual scales. In contrast, the transition from meteorological drought to groundwater drought has a lag time of 1 month and is statistically significant up to t − 5 and t + 5, i.e., 6 months. The linear correlation between the annual rainfall deficit and the monthly groundwater storage index was the lowest (0.15) in December and the highest (0.83) in March. This suggests a seasonal response of groundwater drought to the cumulative effects of precipitation deficits. The RF analysis highlighted the importance of the cumulative characteristics of meteorological drought regarding the severity of low-flow drought. The meteorological drought indices at longer time scales have a greater impact on the severity of low-flow drought, with a contribution of approximately 10% per index. However, the relative contributions of meteorological factors and hydrological indices rarely exceed 5%. Thus, by exploring for the first time the complex interactions among the severity of low-flow regimes, meteorological and hydrological drought indices and meteorological factors, this study provides a new perspective for understanding the characteristics of propagation from meteorological to severe hydrological drought. Full article