Search Results (12,221)

Drought is a widespread natural hazard resulting from an extended period of reduced rainfall, with significant socioeconomic and ecological consequences. Drought severity can impact food security globally due to its high spatial and temporal coverage. The primary objective of this paper consists of a comparative spatiotemporal analysis of environmental extremes (drought/wetness) through the estimation of a twelve-month Standardized Precipitation Index (SPI₁₂) between three distinct vulnerable agricultural regions in the Mediterranean basin (i.e., Spain, Lebanon and Tunisia), under a climate change environment in the last 38 years (1982–2020). The added value of this paper lies in the simultaneous estimation of temporal and spatial variability of drought and wetness periodic events, paying special attention to the geographical patterns of these extremes both in annual and interannual (seasonal) time scales. The results indicated that Spain and Tunisia (western Mediterranean) exhibit similar patterns over the studied period, while Lebanon demonstrates contrasting trends. Comparing the two extreme dry hydrological years, the Spanish study area faced the highest drought intensity, areal extent and duration (SPI₁₂ = −1.18; −1.84; 28–78%; 9–12 months), followed by the Lebanese (SPI₁₂ = −1.28; −1.39; 37–50%; 7–12 months) and the Tunisian ones (SPI₁₂ = −1.05; −1.08; 10–34%; 8 months). Concerning the wettest hydrological years, the Lebanese study domain has recorded the highest SPI₁₂ values, areal extent and duration (SPI₁₂ = 1.58; 2.28; 66–83%; 8–11 months), followed by the Tunisian (SPI₁₂ = 1.55; 1.79; 49–73%; 7–10 months) and Spanish one (SPI₁₂ = 1.07; 1.99; 21–73%; 4–11 months). The periodicity of drought/wetness episodes is about 20 years in Spanish area and 10 years in the Lebanese area (for drought events), whereas there seems no periodicity in the Tunisian one. Understanding the spatial distribution of drought is crucial for targeted mitigation strategies in high-risk areas, potentially avoiding broad, resource-intensive measures across entire regions. Full article

The extensive implementation of the ‘Grain for Green’ project over the Loess Plateau has improved environmental quality. However, it has resulted in a greater consumption of soil water, and its overall hydrological effects remain highly controversial. Our study utilized a coupled land-atmosphere model to evaluate the effects of vegetation changes resulting from revegetation or reclamation on the hydrology of the Loess Plateau. Revegetation was found to stimulate an increase in precipitation, evapotranspiration, and atmospheric water content. However, the increase in precipitation was insufficient to compensate for soil water loss driven by intensified evapotranspiration, resulting in a decrease in both runoff and soil water content. In contrast to revegetation, reclamation would reduce precipitation, although the reduction was less than the decrease in evapotranspiration. This could lead to an increase in both runoff and soil water content. The results provide an important scientific basis for the hydrological effects of vegetation changes on the Loess Plateau, which is particularly important for guiding current and future revegetation activities toward sustainable ecosystem development and water resources management. Full article

Identifying surface sites with significant astrobiological potential on Mars requires a comprehensive understanding of past geological processes and conditions there, including the shallow subsurface region. Numerical modelling could distinguish between regions dominated by erosion and those characterized by sediment accumulation in ancient wet environments. The target area of Jezero Crater is relatively well explored and thus is an ideal site to evaluate model calculations; however, important works are still missing on expectations related to its shallow subsurface . In this work, the best available approaches were followed, and only surface morphology was considered (supposedly formed by the last fluvial episode). The shallow subsurface became an important target recently, and this model could provide new inputs in this area. Erosion–accumulation models are suitable for terrestrial surface features, but few have been applied to Mars. This work addresses this challenge using the SIMWE (SIMulated Water Erosion) model on the Jezero Crater delta, the landing site of the Perseverance rover. For calculations, the average grain size according to the THEMIS TI data was applied to the target area. The flow depth varied between 1.89 and 34.74 m (average of 12.66 m). The water-filled channel width ranged from 35.3 to 341.42 m. A flow velocity of 0.008–11.6 m/s, a maximum erosion rate of 5.98 g/m²/h, and a deposition 4.07 g/m²/h were estimated. These calculated values are close to the range of estimations from other authors assuming precipitation of 1–20 mm/h and discharges of 60–400 m³/s. The model was able to distinguish between erosion- and accumulation-dominated areas about 1 m above Jezero Crater’s delta that are not visible from above. This model helps to identify the accumulation-dominated areas with the finest grain size with good preservation capability for the shallow but invisible subsurface. Full article

Background: Chironomidae occupy a pivotal position within global aquatic ecosystems. The unique structural attributes of the mitochondrial genome provide profound insights and compelling evidence, underpinning the morphological classification of organisms and substantially advancing our understanding of the phylogenetic relationships within Chironomidae. Results: We have meticulously sequenced, assembled, and annotated the mitogenomes of Tanypus chinensis (Wang, 1994) and Tanypus kraatzi (Kieffer, 1912), incorporating an additional 25 previously published mitogenomes into our comprehensive analysis. This extensive dataset enables us to delve deeper into the intricate characteristics and nuances of these mitogenomes, facilitating a more nuanced understanding of their genetic makeup. Conclusions: The genomic nucleotide composition of T. kraatzi was 39.10% A, 36.51% T, 14.33% C, and 10.06% G, with a total length of 1508 bp. The genomic nucleotide composition of T. chinensis was 39.61% A, 36.27% T, 14.55% C, and 9.57% G, with a total length of 1503 bp. This significant enrichment of the chironomid mitogenome library establishes a novel foundation for further exploration in the realm of phylogenetics. Full article

Soil dielectric sensors have been widely used to obtain real-time soil moisture data, which are important for water resource management. However, soluble salts in the soil significantly affect the accuracy of these sensor measurements. Therefore, it is crucial to select suitable soil dielectric sensors for soil moisture measurements at different salinity levels. Eight mainstream sensors (EC-5, 5TE, Teros12, Hydra-probe II, TDR315L, TDR315H, TDR305H, and CS655) were selected and tested at four different soil salinity levels (EC_1:5 = 3.0, 1.5, 1.0, and 0.75 dS·m⁻¹). The measured values using the factory calibration formulas were compared at six soil moisture levels. The results showed that the measured soil moisture values from various sensors exhibited varying degrees of overestimation, which increased with increasing salinity. Only EC-5 did not exhibit distortion at high-salinity levels, with the measured values showing a good linear trend compared to the standard values. Mutational distortion of the measured apparent dielectric permittivity occurred in TDR315L, TDR315H, Hydra-probe II, and 5TE at EC_1:5 = 3.0 dS·m⁻¹. Insensitive distortion of the measured apparent dielectric permittivity occurred in Teros12 and TDR305H at EC_1:5 = 3.0 dS·m⁻¹ as well as in Teros12, TDR305H, 5TE and Hydra-probe II at EC_1:5 = 1.5 dS·m⁻¹. All tested sensors performed reasonably well at EC_1:5 ≤ 1.0 dS·m⁻¹. Seven sensors (excluding CS655) were calibrated within the distortion threshold. The soil moisture accuracy using the calibrated formulas could reach ±0.02 cm³·cm⁻³. At EC_1:5 ≤ 1.0 dS·m⁻¹, most sensors in this study could be applied with the factory calibration formulas. TDR series, EC-5, 5TE and Teros12 were recommended after calibration for EC_1:5 > 1.0 dS·m⁻¹. For extremely high soil salinity levels, the TDR series and EC-5 may be the best choices. Full article

This study evaluates two reanalysis precipitation products (CRA40 and ERA5) over the Ganjiang River Basin with precipitation data from 37 ground rainfall gauges and surface-observed stream flow data from January 1998 to December 2008. Direct comparison with rain gauge observations shows that both CRA40 and ERA5 can capture the spatial and temporal characteristics of precipitation at the basin scale of the Ganjiang River and reflect most of the precipitation events, but there are pronounced differences in the quality of precipitation between them. ERA5 performs better on the daily scale, capturing precipitation changes more accurately over short periods of time, while CRA40 performs better on the monthly scale, providing more stable and long-term precipitation trends. The results of stream flow simulations using two reanalysis precipitation products driving the VIC hydrological model show that (1) CRA40 outperforms ERA5 with a better Nash–Sutcliffe Efficiency (NSE, 0.65 and 0.6) and higher CC (0.96 and 0.91) in daily and monthly scale stream flow simulations, and ERA5 has a good CC (0.86 and 0.93, respectively), but its NSE is poor (0.29 and 0.30, respectively); (2) both CRA40 and ERA5 generally overestimate basin stream flows, especially during the flood season (April–September), with ERA5’s overestimation being more pronounced. This study is expected to provide a basis for the selection of reliable reanalysis products for Ganjiang River Basin precipitation and hydrological simulation. Full article

Given the vulnerability of surface water to the direct impacts of climate change, the accurate prediction of groundwater levels has become increasingly important, particularly for dry regions, offering significant resource management benefits. This study presents the first statewide groundwater level anomaly (GWLA) prediction for Arizona across its two distinct aquifer types—unconsolidated sand and gravel aquifers and rock aquifers. Machine learning (ML) models were combined with empirical Bayesian kriging (EBK) geostatistical interpolation models to predict monthly GWLAs between January 2010 and December 2019. Model evaluations were based on the Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R²) metrics. With average NSE/R² values of 0.62/0.63 and 0.72/0.76 during the validation and test phases, respectively, our multi-model approach demonstrated satisfactory performance, and the predictive accuracy was much higher for the unconsolidated sand and gravel aquifers. By employing a remote sensing-based approach, our proposed model design can be replicated for similar climates globally, and hydrologically data-sparse and remote areas of the world are not left out. Full article

The Sierra Seca aquifer system is located in the northeast (NE) of the province of Granada, in the Prebetic Domain (Betic Cordillera). It is composed of different aquifer units hosted in the Lower Cretaceous and Upper Cretaceous limestones. The two aquifers are separated by a low permeability marl layer, which effectively acts as a barrier between them. To outline the behavior of the hydrogeological system, 407 samples of precipitation and 67 samples of groundwater were obtained from May 2020 to Oct. 2022 and isotopically (${\delta }^{18}O$ and ${\delta }^{2}H$) analyzed. For the estimation of the recharge elevation, a new methodology has been applied to estimate the isotopic content of recharge as a function of precipitation. This allowed the evaluation of the vertical gradient of both precipitation (${\nabla }_Z{\delta }^{18}{O}_P=-2.9‰/\mathrm{k}\mathrm{m}$) and aquifer recharge (${-4.4‰/\mathrm{k}\mathrm{m}\le \nabla }_Z{\delta }^{18}{O}_R\le -2.9‰/\mathrm{k}\mathrm{m}$). Therefore, estimating (1) the recharge zone elevation associated with the aquifer system, which is comprised between 1500 and 1700 m a.s.l., and (2) the transit time of recharge to reach the outflow point of the aquifer system, which varies between 4 and 5 months, is possible. Additionally, three tracer tests were conducted to outline the hydrologic connection between the recharge and discharge zones of the aquifer system. The results show that the Fuente Alta spring drains the limestones of the Lower Cretaceous, while La Natividad spring does the same with the limestones of the Upper Cretaceous. In the case of the Enmedio spring, groundwater discharge is related to infiltration through the streambed of the watercourse fed by the Fuente Alta spring. Full article

Water quality prediction is a fundamental prerequisite for effective water resource management and pollution prevention. Accurate predictions of water quality information can provide essential technical support and strategic planning for the protection of water resources. This study aims to enhance the accuracy of water quality prediction, considering the temporal characteristics, variability, and complex nature of water quality data. We utilized the LTSF-Linear model to predict water quality at the Huangyang Reservoir. Comparative analysis with three other models (ARIMA, LSTM, and Informer) revealed that the Linear model outperforms them, achieving reductions of 8.55% and 10.51% in mean square error (MSE) and mean absolute error (MAE), respectively. This research introduces a novel method and framework for predicting hydrological parameters relevant to water quality in the Huangyang Reservoir. These findings offer a valuable new approach and reference for enhancing the intelligent and sustainable management of the reservoir. Full article

The Huaihe River Basin is an important ecological function conservation area in China, and it is also an important production area for national food, energy, minerals, and manufacturing. The groundwater storage and groundwater drought in this region are of great significance for ecological maintenance and water resources management. In this study, based on GRACE data and GLDAS data, a dynamic calculation method for groundwater storage in the Huaihe River Basin was developed, and a groundwater drought index (GRACE-GDI) was derived. By coupling GRACE-GDI with run theory, the quantitative identification of groundwater drought events, as well as their duration, intensity, and other characteristics within the basin, was achieved. The spatiotemporal changes in groundwater storage and groundwater drought in the Huaihe River Basin were analyzed using the developed method. The results showed that GRACE data are highly applicable in the Huaihe River Basin and is capable of capturing the spatiotemporal variations in groundwater storage in this region. Over the study period, mainly affected by rainfall, the terrestrial water storage and surface water storage in the Huaihe River Basin showed a decreasing trend, while groundwater storage showed a slight increasing trend. The duration of groundwater drought events in the basin ranged from 78 to 152 months, with an intensity of 82.77 to 104.4. The duration of drought gradually increased from north to south, while the intensity increased from south to north. Full article

Droughts negatively affect basins by reducing the river streamflow and increasing ion concentrations due to lower dilution. This study examines the impact of droughts in the Colorado River basin in Argentina. For this purpose, data were collected during the period from 2015 to 2021 at eight monitoring stations containing water from the river and drainage canals. The Standardized Precipitation Index (SPI) was used to analyze droughts from 1966 to 2020, and the Mann–Kendall test was used to evaluate the precipitation trends. In addition, water quality indices for human consumption (DWQI) and livestock (LWQI) were calculated by evaluating physicochemical parameters. The results show an intensification of drought since 2007, with an SPI of −1.5 in 2008, which affected the river streamflow regime and reduced the dilution capacity in the Casa de Piedra Dam. This reduction led to the deterioration of the water quality, with DWQI values indicating that 85% of the samples were not suitable for human consumption but were suitable for livestock consumption. In the drainage canals, most of the samples were of low quality for livestock consumption. The physicochemical analyses show that although some parameters (Na⁺, K⁺, CO₃²⁻ + HCO₃⁻, and Cl⁻) were at acceptable levels, others (electrical conductivity, SO₄²⁻, and Ca²⁺) exceeded the WHO’s limits, representing risks to human and livestock health. This study provides insights into how droughts and streamflow regulation affect the water quality in semiarid basins and highlights the broader applicability to other regions that present similar challenges under climate change scenarios. Full article

The study of environmental flow has garnered significant scientific interest due to the considerable degradation caused by human activities on aquatic ecosystem dynamics. Environmental flow is defined as the quantity, timing, and quality of water flow required to sustain freshwater and estuarine ecosystems while meeting human demands. Research in riverine ecosystems can generate the critical scientific knowledge needed to determine an adequate environmental flow that balances the requirements of both aquatic organisms and human populations. This study is part of a series of investigations aimed at field-testing different methodologies to determine appropriate environmental flow levels for rivers with specific characteristics. In particular, we adapted and validated a holistic methodology for calculating the environmental flow regime in the Tempisque River basin in Costa Rica. This research involved analyzing hydrological parameters, hydraulic conditions, the presence of flow bioindicators, and various anthropogenic uses of the river (such as human consumption, productive, recreational, and cultural activities) to estimate environmental flow requirements throughout the year. The findings indicate that the lower and upper limits of the environmental flow for the studied section of the Tempisque River correspond to the monthly excesses of 95.00% and 64.00%, respectively. These results provide a reliable annual flow regime that can inform decision-making by authorities in water resource management, particularly in regions where there is a high demand for water across different human activities. Full article

Modelling at the basin scale offers crucial insights for policymakers as they make decisions regarding the optimal utilization of water resources. This study employed the MIKE HYDRO Basin model to analyse water demand and supply dynamics in the Parvati Basin of Rajasthan, India, for the period 2005–2020. The MIKE11 NAM model showcased strong alignment between simulated and observed runoff during both the calibration (NSE = 0.79, PBIAS = −2%, R² = 0.79, RMSE = 4.95, RSR = 0.5, and KGE = 0.84) and validation (NSE = 0.67, PBIAS = −12.4%, R² = 0.68, RMSE = 8.3, RSR = 0.62, and KGE = 0.67) phases. The MIKE HYDRO Basin model also exhibited excellent agreement between observed and simulated reservoir water levels, with R², NSE, RMSE, PBIAS, RSR, and KGE values of 0.86, 0.81, 3.87, −2.30%, 0.43, and 0.88, respectively. The MIKE HYDRO Basin model was employed to create six distinct scenarios, considering conveyance efficiency, irrigation method, and conjunctive water use, to assess irrigation demands and deficits within the basin. In the initial simulation, featuring a conveyance efficiency of 45%, flood irrigation, and no groundwater utilization, the average water demand and deficit throughout the study period were estimated as 43.15 MCM and 3.45 MCM, respectively, resulting in a sustainability index of 0.506. Enhancing conveyance efficiency to 75% under flood irrigation and 5% conjunctive use could elevate the sustainability index to 0.92. Transitioning to sprinkler irrigation and a lift irrigation system could raise the system’s sustainability index to 1. These developed models hold promise for real-time reservoir operation and irrigation planning across diverse climatic conditions and varying cropping patterns. Full article

The Arabian Gulf, a semi-enclosed basin in the Middle East, connects to the Indian Ocean through the Strait of Hormuz and is surrounded by seven arid countries. This study examines the water cycle of the Gulf and its surrounding areas using data from the GRACE and GRACE Follow-On missions, along with ERA5 atmospheric reanalysis data, from 05/2002 to 05/2017 and from 07/2018 to 12/2023. Our findings reveal a persistent water deficit due to high evaporation rates, averaging 370 ± 3 km³/year, greatly surpassing precipitation, which accounts for only 15% of the evaporative loss. Continental runoff provides one-fifth of the needed water, while the remaining deficit, approximately 274 ± 10 km³/year, is balanced by net inflow of saltwater from the Indian Ocean. Seasonal variations show the lowest net inflow of 26 ± 49 km³/year in March and the highest of 586 ± 53 km³/year in November, driven by net evaporation, continental input, and changes in the Gulf’s water budget. This study highlights the complex hydrological dynamics influenced by climate patterns and provides a baseline for future research in the region, which will be needed to quantify the expected changes in the hydrological cycle due to climate change. Full article

The snowmelt process plays a crucial role in hydrological forecasting, climate change, disaster management, and other related fields. Accurate detection of wet snow distribution and its changes is essential for understanding and modeling the snow melting process. To address the limitations of conventional fixed-threshold methods, which suffer from poor adaptability and significant interference from scattering noise, we propose a weakly supervised deep learning change detection algorithm with Sentinel-1 multi-temporal data. This algorithm incorporates the Multi-Region Convolution Module (MRC) to enhance the central region while effectively suppressing edge noise. Furthermore, it integrates the ResNet residual network to capture deeper image features, facilitating wet snow identification through feature fusion. Various combinations of differential images, polarization data, elevation, and slope information during and after snowmelt were input into the model and tested. The results suggest that the combination of differential images, VV polarization data, and slope information has greater advantages in wet snow extraction. Comparisons between our method, the fixed-threshold method, OTSU algorithm, and FCM algorithm against the results of Landsat images indicates that the overall accuracy of our method improves significantly when the proportion of wet snow cover is large, and the average overall accuracy of wet snow extraction is 85.2%. This study provides clues for the accurate identification of wet snow during the mid-snowmelt phase. Full article