Search Results (190)

Accelerating climate change poses significant risks to water security and ecological stability in arid regions due to the increasing frequency and intensity of extreme precipitation events. As a climate-sensitive area, the inland river basin (IRB) of Northwest China—a critical water source for local ecosystems and socioeconomic activities—remains insufficiently studied in terms of future extreme precipitation dynamics. This study evaluated the spatiotemporal evolution of extreme precipitation in the IRB under a new low radiative forcing scenario (SSP1-1.9) by employing four global climate models (GCMs: GFDL-ESM4, MRI-ESM2, MIROC6, and IPSL-CM6A-LR). Eight core extreme precipitation indices were analyzed to quantify changes during the near future (NF: 2021–2050) and far future (FF: 2071–2100) periods. Our research demonstrated that all four models were capable of capturing seasonal patterns and exhibited inherent uncertainty. The annual total precipitation (PRCPTOT) in mountainous regions showed minimal variation, while desert areas were projected to experience a 2-6-fold increase in precipitation in the NF and FF. The Precipitation Intensity Index (SDII) weakened by approximately −10% in mountainous areas but strengthened by around +10% in desert regions. Most mountainous areas showed an increase in the maximum consecutive dry days (CDD), whereas desert regions exhibited extended maximum consecutive wet days (CWD). Moderate rainfall (P1025) variations primarily ranged between −5% and +20%, with greater fluctuations in desert areas. Heavy rainfall (PG25) fluctuated between −40% and +40%, reflecting stark contrasts in extreme precipitation between arid basins and mountainous zones. The maximum 1-day precipitation (Rx1day) and maximum 5-day precipitation (Rx5day) both showed significant increases, which indicated heightened risks from extreme rainfall events in the future. Moreover, the IRB region experienced increased total precipitation, enhanced rainfall intensity, more frequent alternations between drought and precipitation, more frequent moderate-to-heavy rainfall days, and higher daily precipitation extremes in both the NF and FF periods. These findings provide critical data for regional development planning and emergency response strategy formulation. Full article

Drought significantly reduces global agricultural productivity and destabilizes ecosystems. As the primary grain-producing region and a key ecological buffer zone in China, Northeast China is experiencing intensifying drought stress. However, the regional-scale characteristics of refined drought and the impact mechanisms on different types of vegetation in the Northeast are rarely investigated. In this study, we analyzed the spatial and temporal characteristics of drought over 30-, 60-, 90-, 180-, 270-, and 360-day time scales in Northeast China using the Standardized Precipitation Index (SPI) based on high-precision daily precipitation data simulated by CLM3.5 from 2008 to 2023. Additionally, we used the MODIS Normalized Difference Vegetation Index (NDVI) to elucidate the response of vegetation to drought across different land use types. The results showed that SPI-30 was the most sensitive for drought detection, and there was a clear trend of drought aggravation in the northern part of the Northeast region. The strongest correlation between vegetation and drought was found in September. A significant lag in the response of vegetation to drought was observed in May, June, July, and August, with the best correlation observed at a one-month lag. In addition, the degree of response to drought varies among different types of vegetation. Grasslands are the most sensitive to drought, while woodlands and wetlands have a weaker response. This study provides a reference for assessing the dynamics of refined climates at different spatial and temporal scales and offers actionable insights for ecosystem management in climate-sensitive agricultural regions. Full article

Based on the long-term daily historical rainfall data, this study analyzes the seasonal differences in extreme rainfall in the monsoon region with frequent extreme rainfall in China over the past 40 years. From the detailed analysis of extreme rainfall indicators, the spatial and temporal variation in extreme rainfall indicators in the monsoon region of China from 1980 to 2020 is explored. Through Mann–Kendall test and multi-index spatial and temporal analysis, the spatial and temporal evolution law and seasonal differentiation characteristics of extreme precipitation events are revealed. The results show the following: (1) The precipitation change presents a dipole pattern of southeast–northeast enhancement, northwest–central attenuation. (2) The precipitation intensity showed the spatial heterogeneity of latitude differentiation of “strong in summer and weak in winter, strong in south and weak in north”, and generally attenuated in winter after reaching the peak in summer. (3) There were significant dry and wet differences between continuous drought days (CDDs) and wet days (CWDs), reflecting the characteristics of “dry in winter and wet in summer”, and the seasonal differentiation of cumulative precipitation (PRCPTOT) was significant. (4) The extreme precipitation threshold is strengthened in winter, and the frequency shows the characteristics of “high in winter and spring, low in summer and autumn”. Studies have shown that extreme precipitation in the monsoon region of China has seasonal redistribution characteristics, which may aggravate the challenge of water resources management. It is necessary to further analyze its driving factors in combination with a dynamic climate mechanism. Full article

Land Surface Temperature (LST), as a core variable in the coupling of land–atmosphere energy transfers and ecological responses, relies heavily on the global coverage capacity of thermal infrared remote sensing (TIR-LST) for dynamic monitoring. Currently, the time reconstruction method of the TIR-LST products from China’s Fengyun polar-orbiting satellite under dynamic cloud interference remains under exploration. This study focuses on the Heihe River Basin in western China, and addresses the issue of cloud coverage in relation to the Fengyun-3C (FY-3C) satellite TIR-LST. An innovative spatiotemporal reconstruction framework based on multi-source data collaboration was developed. Using a hybrid ensemble learning framework of random forest and ridge regression, environmental parameters such as vegetation index (NDVI), land cover type (LC), digital elevation model (DEM), and terrain slope were integrated. A downscaling and multi-factor collaborative representation model for land surface temperature was constructed, thereby integrating the passive microwave LST and thermal infrared VIRR-LST from the FY-3C satellite. This produced a seamless LST dataset with 1 km resolution for the period of 2017–2019, with temporal continuity across space. The validation results show that the reconstructed data significantly improves accuracy compared to the original VIRR-LST and demonstrates notable spatiotemporal consistency with MODIS LST at the daily scale (annual R² ≥ 0.88, RMSE < 2.3 K). This method successfully reconstructed the FY-3C satellite’s 1 km level all-weather LST time series, providing reliable technical support for the use of domestic satellite data in remote sensing applications such as ecological drought monitoring and urban heat island tracking. Full article

The Atlantic Forest has undergone deforestation and prolonged droughts, affecting ecosystem services. This study assesses the water balance using hydrological observations from representative tree species within a Montane Semideciduous Seasonal Forest (MF) remnant. Gross precipitation (GP), canopy interception (CI), and effective precipitation (EP = Throughfall + Stemflow) were recorded daily, and soil moisture was measured down to 1.80 m every two days during the dry period of the 2023/2024 hydrological year. Additionally, aboveground biomass (AGB), fresh root biomass (BR), and soil hydrological properties in the soil profile were obtained to support the water balance results. The highest EP values were recorded in Miconia willdenowii, while the lowest were in Xylopia brasiliensis. Root zone water storage exhibited a declining trend, with the highest values in Miconia willdenowii. ET remained low, mainly in April, July, and September, with Miconia willdenowii and Copaifera langsdorffii showing the highest values, and AGB correlated with CI and ET. The dynamic of this ecosystem is apparent in the temporal variations (CVt) of soil moisture, influenced by EP and ET. The greatest variability was recorded in the surface layer (0–20 cm), stabilizing with depth, especially below 120 cm. The Temporal Stability Index (TSI) of soil water storage indicated greater stability in Blepharocalyx salicifolius. This study highlights the significance of soil water storage and ET in a tropical forest ecosystem, particularly under drought conditions, suggesting potential species that may be more effective in recovering degraded areas. Full article

In the context of global climate warming, compound drought and heatwave events (CDHEs) have exhibited a pronounced escalation in frequency since the Second Industrial Revolution, incurring substantial socioeconomic losses. This study investigates the spatiotemporal variations of CDHEs in semi-arid and semi-humid regions of northern China based on daily Standardized Precipitation Index (SPI) and maximum temperature (Tmax) datasets. The results show that compared to the 1980s, the occurrence frequency of CDHEs during the 2010s exhibited an increasing trend increase by 20–50 times in the southern region and 10–30 times in the northern region, while some watersheds in the central part of the study area show a decreasing trend. From the 1980s to the 2010s, the percentage of area affected by CDHE with a duration exceeding 11 days/year has risen from 28.3% to 56.7%, reflecting a pronounced upward trend in CDHE duration. Spatiotemporal patterns revealed significant interdecadal disparities in both the frequency and duration of CDHEs, which are primarily determined by heatwave events pattern and the synchronicity of heatwave and drought events. However, drought intensity exhibits comparatively weaker influence. Due to the decrease in the proportion of short–duration heatwaves, the short–duration CDHEs (1–2 days) in all levels exhibited a declining trend in their proportions. Furthermore, the delayed occurrence of drought events resulted in the peak occurrence of CDHEs has gradually shifted June to July–August. Full article

The aim of this study was to examine variations in the hydrological regime of the Krapina River from 1964 to 2023. The river basin spans 1263 km² and is characterized by a temperate, humid continental climate with warm summers. Hydrological data from the Kupljenovo gauging station, which monitors 91.1% of the basin (1150 km²), indicate an average annual discharge of 11.2 m³/s, ranging from 3.25 m³/s to 18.3 m³/s. Over the 60-year study period, the minimum mean daily discharges show a statistically insignificant increasing trend, while the mean annual and maximum annual mean daily discharges exhibit statistically insignificant declines. Annual precipitation averages 1037 mm, varying between 606 mm and 1459 mm, with a non-significant decreasing trend. In contrast, the mean annual air temperatures demonstrate a statistically significant increasing trend, with a pronounced intensification beginning in 1986. The annual runoff coefficients series exhibits a statistically insignificant downward trend, with an average value of 0.293 (range: 0.145–0.399). Application of the New Drought Index (NDI) revealed a marked increase in the frequency of strong and extreme droughts since 2000. Full article

This study presents a comprehensive analysis of hydrological alterations and environmental flow components in the Beht River basin in northwest Morocco, using a coupled approach involving the Soil and Water Assessment Tool (SWAT) for hydrological modeling, the Indicators of Hydrologic Alteration (IHA) for flow regime assessment, and the Standardized Precipitation Index (SPI) for drought characterization. The SWAT model, run on a daily time step, showed satisfactory performance in terms of statistical criteria for both calibration and validation periods, despite encountering limitations, and proved its ability to simulate and reproduce the hydrological behavior of the basin. Using the IHA, we investigated changes in the hydrological regime over two distinct periods, revealing significant hydrological alteration. The SPI analysis supported these findings by highlighting the variable impacts of dry and wet periods on the hydrological regime, thus validating the observed changes in river flow indicators. As a preliminary step toward establishing environmental flows in the Beht River, this study provides foundational insights into the temporal evolution of its hydrology. These findings offer a valuable basis for better water resource management and conservation in the region. Full article

Drought poses a severe threat to crop health and food security, particularly in arid regions like the Shiyang River Basin (SRB), highlighting the need for timely monitoring to support sustainable agriculture. The normalized difference vegetation index (NDVI) is a critical tool for evaluating crop conditions. However, existing NDVI datasets often lack the spatial-temporal resolution required for effective crop monitoring. This study introduces an NDVI reconstruction method combining Savitzky–Golay filtering with the variation-based spatiotemporal data fusion model to produce a high-resolution daily NDVI dataset for SRB cropland in 2022, with a 30 m spatial resolution. The dataset achieves a cropland integrity rate of 98.50%, a 42.35% improvement over the initial MOD09GA NDVI. It also demonstrates high accuracy, with an average r-mean of 0.7511—49.88% higher than MOD09GA NDVI. Validation metrics, including abs-AD (0.0064), RMSE (0.0466), abs-EDGE (0.0373), and abs-LBP (0.0317), fall within acceptable ranges. This enhanced NDVI dataset facilitates detailed monitoring of crop conditions across diverse growth stages and planting structures, offering valuable insights for precision agriculture in the region. 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

Natural disaster events caused by extreme precipitation have far-reaching and widespread impacts on society, the economy, and ecosystems. However, understanding the long-term trends of extreme precipitation indices and their spatiotemporal correlations with disaster events remains limited. This is especially true given the diverse factors influencing their relationship in China, which makes their spatial linkage highly complex. This study aims to detect recent spatial trends in extreme precipitation indices in China and link them with related natural disaster events, as well as with the spatial evolution of land use and land cover and Gross Domestic Product (GDP). Daily precipitation data from 1274 rain gauge stations spanning the period from 1961 to 2021 were used to analyze the spatial distribution characteristics of extreme precipitation index climate trends in China. The results revealed a significant increasing trend of the intensity of extreme precipitation in eastern China, but a decreasing trend of amount, frequency, and duration of extreme precipitation in southwest China, accompanied by a significant increase in consecutive dry days. Natural disaster records related to extreme precipitation trends indicated a significant increase at an annual rate of 1.3 times in the frequency of flood, storm, drought, and landslide occurrences nationwide, with substantial regional dependence in disaster types. Furthermore, the spatial evolution of land use and GDP levels showed a close association with the spatial distribution of natural disaster events induced by extreme precipitation. Although the number of deaths caused by extreme precipitation-related disasters in China is decreasing (by 51 people per year), the economic losses are increasing annually at an annual rate of USD 530,991, particularly due to floods and storms. This study holds the potential to inform decision-making processes, facilitate the implementation of mitigation and adaptation measures, and contribute to reducing the impacts of natural disasters across diverse regions worldwide. Full article

Dry weather can severely limit water availability, harming agriculture and natural habitats. Several drought indices assess meteorological conditions relative to historical norms, but absolute indices, expressed in millimeters of water depth, are particularly crucial for agriculture. Every millimeter of water that a crop cannot evaporate results in an almost proportional yield loss. Using daily precipitation, potential evapotranspiration, and temperature data, we calculated five absolute drought indices for a sandy area in the Netherlands. We then validated these indices against the annual registered amount of irrigation water from 2001 to 2021, which served as a proxy for the drought experienced by farmers. The cumulative potential precipitation deficit calculated with (a) a temperature sum-dependent start of the growing season or (b) a start in the wet winter season most closely matched irrigation amounts (R² = 95% and 94%, respectively). The latter index is likely to be applicable in climates where a dry growing season follows a wet season. These indices can be updated daily, providing real-time insight into drought development and can be used in climate projections. To our knowledge, this is the first study to validate meteorological drought indices using irrigation data, which advances the assessment of drought events. Full article

The amplitude and interval of drought events are expected to enhance in upcoming years resulting from global warming and climate alterations. Understanding future drought events’ potential impacts is important for effective regional adaptation and mitigation approaches. The main goal of this research is to study the impacts of climate change on drought in the Büyük Menderes Basin located in the Aegean region of western Türkiye by using the outcomes of three general circulation models (GCMs) from CMIP6 considering two different emission scenarios (SSP2-4.5 and SSP5-8.5). Following a bias correction using a linear scaling method, daily precipitation and temperature projections are used to compute the Standardized Precipitation Evapotranspiration Index (SPEI). The effectiveness of the GCMs in projecting precipitation and temperature is evaluated using observational data from the reference period (1985–2014). Future drought conditions are then assessed based on drought indices for three periods: 2015–2040 (near future), 2041–2070 (mid-term future), and 2071–2100 (late future). Consequently, the number of dry months is projected and expected to elevate, informed by SSP2-4.5 and SSP5-8.5 scenarios, during the late-century timeframe (2071–2100) in comparison to the baseline period (1985–2014). The findings of this study offer an important understanding for crafting adaptation strategies aimed at reducing future drought impacts in the Büyük Menderes Basin in the face of changing climate conditions. Full article

Daily water stress reflects the water stress status of crops on a specific day, which is crucial for studying drought progression and guiding precision irrigation. However, accurately monitoring the daily water stress remains challenging, particularly when eliminating the impact of historical stress and normal growth. Recent studies have demonstrated that the diurnal characteristics of the crop canopy obtained via remote sensing techniques can be used to assess daily water stress levels effectively. Remote sensing observations, such as the solar-induced chlorophyll fluorescence (SIF) and reflectance, offer information on the crop canopy structure, physiology, or their combination. However, the sensitivity of different structural, physiological, or combined remote sensing variables to the daily water stress remains unclear. We investigated this issue via continuous measurements of the active fluorescence, leaf rolling, and canopy spectra of maize under different irrigation conditions. The results indicated that with increasing water stress, vegetation exhibited significant coordinated diurnal variations in both structure and physiology. The influence of water stress was minimal in the morning but peaked at noon. The morning-to-noon ratio (NMR) of the apparent SIF yield (SIFy), in which only the effect of the photosynthetically active radiation (PAR) is eliminated and in which both structural and physiological information is incorporated, exhibited the highest sensitivity to water stress variations. This NMR of the SIFy was followed by the NMR of the normalized difference vegetation index ($\mathrm{N}\mathrm{D}\mathrm{V}\mathrm{I}$) and the NMR of the canopy fluorescence emission efficiency ($\mathsf{\Phi }{\mathrm{F}}_{\mathrm{c}\mathrm{a}\mathrm{n}\mathrm{o}\mathrm{p}\mathrm{y}}$) obtained via the fluorescence correction vegetation index (FCVI) method, which primarily reflect structural and physiological information, respectively. This study highlights the advantages of utilizing diurnal vegetation structural and physiological variations for monitoring daily water stress levels. Full article

In agricultural production, droughts occurring during the crucial growth periods of crops hinder crop development, while the daily-scale standardized precipitation evapotranspiration index (SPEI) can be applied to accurately identify the drought characteristics. In this study, we used the statistical downscaling method to obtain the daily precipitation (P_r), maximum air temperature (T_max) and minimum air temperature (T_min) during the rice growing season in Heilongjiang Province from 2015 to 2100 under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 in CMIP6, to study the spatial and temporal characteristics of drought during the rice growing season in cold region and the effect of climate change on drought characteristics. The potential evapotranspiration (PET₀) was calculated using the regression correction method of the Hargreaves formula recommended by the FAO, and the daily SPEI was calculated to quantitatively identify the drought classification. The Pearson correlation coefficient was used to analyze the correlation between the meteorological factors (P_r, T_max, T_min), PET₀ and SPEI. The results showed that: (1) Under 3 SSP scenarios, P_r showed an increasing trend from the northwest to the southeast, T_max showed an increasing trend from the northeast to the southwest, and higher T_min was mainly distributed in the east and west regions. (2) PET₀ indicated an overall interannual rise in the three future SSP scenarios, with higher values mainly distributed in the central and western regions. The mean daily PET₀ values ranged from 4.8 to 6.0 mm/d. (3) Under SSP1-2.6, rice mainly experienced mild drought and moderate drought (−0.5 ≥ SPEI > −1.5). The predominant drought classifications experienced were mild, moderate, and severe drought under SSP2-4.5 and SSP8.5 (−0.5 ≥ SPEI > −2.0). (4) The tillering stage experienced the highest drought frequency and drought intensity, with the longest drought lasting 24 days. However, the heading flower stage had the lowest drought frequency and drought intensity. The drought barycenter was mainly in Tieli and Suihua. (5) The PET₀ was most affected by the T_max, while the SPEI was most affected by the P_r. This study offers a scientific and rational foundation for understanding the drought sensitivity of rice in Northeast China, as well as a rationale for the optimal scheduling of water resources in agriculture in the future. Full article