Search Results (13,016)

Mountain apricot (Prunus sibirica) is an important fruit tree variety, and has a wide range of planting and application value in China and even the world. However, the current research on the suitable distribution area of P. sibirica is still inconclusive. In this study, we retrieved distribution data for P. sibirica in China from the Global Biodiversity Information Facility (GBIF), and identified six key environmental factors influencing its distribution through cluster analysis. Using these six selected climate factors and P. sibirica distribution points in China, we applied the maximum entropy model (MaxEnt) to evaluate 1160 candidate models for parameter optimization. The final results predict the potential distribution of P. sibirica under the current climate as well as two future climate scenarios (SSPs126 and SSPs585). This study shows that the model optimized with six key climate factors (AUC = 0.897, TSS = 0.658) outperforms the full model using nineteen climate factors (AUC = 0.894, TSS = 0.592). Under the high-emission scenario (SSPs585), the highly suitable habitat for P. sibirica is expected to gradually shrink towards the southeast and northwest, while expanding in the northeast and southwest. After the 2050s, highly suitable habitats are projected to completely disappear in Shandong, while new suitable areas may emerge in Tibet. Additionally, the total area of suitable habitat is projected to increase in the future, with a more significant expansion under the high-emission scenario (SSPs585) compared to the low-emission scenario (SSPs126) (7.33% vs. 0.16%). Seasonal changes in precipitation are identified as the most influential factor in driving the distribution of P. sibirica. Full article

Amid global climate change, recurrent drought events pose significant challenges to regional water resource management and the sustainability of socio-economic growth. Thus, understanding drought characteristics and regional development patterns is essential for effective drought monitoring, prediction, and the creation of robust adaptation strategies. Most prior research has analyzed drought events independently in spatial and temporal dimensions, often overlooking their dynamic nature. In this study, we employ a three-dimensional methodology that accounts for spatiotemporal continuity to identify and extract meteorological drought events based on a 3-month standardized precipitation evapotranspiration index (SPEI3). Measured by the SPEI3 index, the incidence of drought increased in the middle part of the basin, especially in some parts of Sichuan and Yunnan province, and the frequency of drought events decreased in the upper reaches. We evaluate drought events within the Yangtze River basin from 1980 to 2016 by examining five variables: chronology, extent, severity, duration, and epicenter locations. The results show that a total of 97 persisting drought events lasting at least 3 months have been identified in Yangtze River basin. Most events have a duration between 4 and 7 months. The findings indicate that while the number of drought events in the Yangtze River basin has remained unchanged, the intensity, duration, and severity of these events have shown a slight increase from 1980 to 2016. The drought events gradually moved from the western and southeastern parts of the basin to the central region. The most severe drought event occurred between January 2011 and October 2011, with a duration of 10 months and an affected area of 0.94 million km², impacting over fifty percent of the basin. Changes in wetness and dryness in the Yangtze River basin are closely related to El Niño/Southern Oscillation (ENSO) events, with a positive correlation between the intensity of cold events and the probability of extreme drought. This study enhances our understanding of the dynamics and evolution of drought events in the Yangtze River basin, providing crucial insights for better managing water resources and developing effective adaptation strategies. Full article

This research focuses on the complex dynamics governing the sensitivity of streamflow to variations in rainfall and potential evapotranspiration (PET) within the Nile basin. By employing a hydrological model, our study examines the interrelationships between meteorological variables and hydrological responses across six catchments (Blue Nile, El Diem, Kabalega, Malaba, Mpanga, and Ribb) and explores the intricate balance between rainfall, PET, and streamflow. Nash Sutcliffe Efficiency (NSE) for calibration of the hydrological model ranged from 0.636 (Ribb) to 0.831 (El Diem). For validation, NSE ranged from 0.608 (Ribb) to 0.811 (Blue Nile). With rainfall kept constant while PET was increased by 5%, the streamflows of the Blue Nile, El Diem, Kabalega, Malaba, Mpanga, and Ribb decreased by 7.00, 5.08, 2.49, 4.10, 1.84, and 7.67%, respectively. With the original PET data unchanged, increasing rainfall of the Blue Nile, El Diem, Kabalega, Malaba, Mpanga, and Ribb by 5% led to an increase in streamflow by 9.02, 9.87, 5.38, 4.34, 6.58, and 8.32%, respectively. The research reveals that the rate at which a catchment losing water to the atmosphere (determined by PET) substantially influences its drying rate. Utilizing linear models, we demonstrate that the surplus rainfall available for increasing streamflow (represented by model intercepts) amplifies with higher rainfall intensities. This highlights the pivotal role of rainfall in shaping catchment water balance dynamics. Moreover, our study stresses the varied sensitivities of catchments within the basin to changes in PET and rainfall. Catchments with lower PET exhibit heightened responsiveness to increasing rainfall, accentuating the influence of evaporative demand on streamflow patterns. Conversely, regions with higher PET rates necessitate refined management strategies due to their increased sensitivity to changes in evaporative demand. Understanding the intricate interplay between rainfall, PET, and streamflow is paramount for developing adaptive strategies amidst climate variability. By examining these relationships, our research contributes essential knowledge for sustainable water resource management practices at both the catchment and regional scales, especially in regions susceptible to varying sensitivities of catchments to climatic conditions. Full article

Highland ecologies are the most susceptible to climate change, often experiencing intensified impacts. Due to climate change and human activities, there were dramatic changes in the alpine domain of the China–Pakistan Economic Corridor (CPEC), which is a vital project of the Belt and Road Initiative (BRI). The CPEC is subjected to rapid infrastructure expansion, which may lead to potential land surface susceptibility. Hence, focusing on sustainable development goals, mainly SDG 9 (industry, innovation, and infrastructure) and SDG 13 (climate action), to evaluate the conservation and management practices for the sustainable and regenerative development of the mountainous region, this study aims to assess change detection and find climatic conditions using multispectral indices along the mountainous area of Gilgit and Hunza-Nagar, Pakistan. It has yielded practical and highly relevant implications. For sustainable and regenerative ecologies, this study utilized 30 × 30 m Landsat 5 (TM), Landsat 7 (ETM+), and Landsat-8/9 (OLI and TIRS), and meteorological data were employed to calculate the aridity index (AI). The results of the AI showed a non-significant decreasing trend (−0.0021/year, p > 0.05) in Gilgit and a significant decreasing trend (−0.0262/year, p < 0.05) in Hunza-Nagar. NDVI distribution shows a decreasing trend (−0.00469/year, p > 0.05), while NDWI has depicted a dynamic trend in water bodies. Similarly, NDBI demonstrated an increasing trend, with rates of 79.89%, 87.69%, and 83.85% from 2008 to 2023. The decreasing values of AI mean a drying trend and increasing drought risk, as the study area already has an arid and semi-arid climate. The combination of multispectral indices and the AI provides a comprehensive insight into how various factors affect the mountainous landscape and climatic conditions in the study area. This study has practical and highly relevant implications for policymakers and researchers interested in research related to land use and land cover change, environmental and infrastructure development in alpine regions. Full article

Evapotranspiration is a crucial component of the water cycle and is significantly influenced by climate change and human activities. Agricultural expansion, as a major aspect of human activity, together with climate change, profoundly affects regional ET variations. This study proposes a quantification framework to assess the impacts of climate change (ET_m) and agricultural development (ET_h) on regional ET variations based on the Random Forest algorithm. The framework was applied in a large-scale agricultural expansion area in China, specifically, the Songhua River Basin. Meteorological, topographic, and ET remote sensing data for the years of 1980 and 2015 were selected. The Random Forest model effectively simulates ET in the natural areas (i.e., forest, grassland, marshland, and saline-alkali land) in the Songhua River Basin, with R² values of around 0.99. The quantification results showed that climate change has altered ET by −8.9 to 24.9 mm and −3.4 to 29.7 mm, respectively, in the natural areas converted to irrigated and rainfed agricultural areas. Deducting the impact of climate change on the ET variation, the development of irrigated and rainfed agriculture resulted in increases of 2.9 mm to 55.9 mm and 0.9 mm to 53.4 mm in ET, respectively, compared to natural vegetation types. Finally, the Self-Organizing Map method was employed to explore the spatial heterogeneity of ET_h and ET_m. In the natural–agriculture areas, ET_m is primarily influenced by moisture conditions. When moisture levels are adequate, energy conditions become the predominant factor. ET_h is intricately linked not only to meteorological conditions but also to the types of original vegetation. This study provides theoretical support for quantifying the effects of climate change and farmland development on ET, and the findings have important implications for water resource management, productivity enhancement, and environmental protection as climate change and agricultural expansion persist. Full article

In response to the intensification of global warming, extreme weather events, such as tropical cyclones (TCs) and cold waves (CWs) have become increasingly frequent near the eastern Guangdong coast, significantly affecting the structure and material transport of coastal waters. Based on nearshore-measured and remote sensing reanalysis data in the winter of 2011 and summer of 2012 on the eastern Guangdong coast, this study analyzed the nearshore hydrodynamic evolution process, influencing mechanism, and marine environmental effects under the influence of TCs and CWs, and further compared the similarities and differences between the two events. The results revealed significant seasonal variations in the hydrological and meteorological elements of the coastal waters, which were disrupted by the passage of TCs and CWs. The primary influencing factors were TC track and CW intensity. The current structure changed significantly during the TCs and CWs, with the TC destroying the original upwelling current and the CW affecting the prevailing northeastward current. Wind is one of the major forces driving nearshore hydrodynamic processes. According to the synchronous analysis of research data, the TC-induced water level rise is primarily attributed to the combined effects of wind stress curl and the Ekman effect, whereas the water level rise associated with CW is primarily linked to the Ekman effect. The water transport patterns during the TC and CW differed, with transport concentrated on the right side of the TC track and within the coastal strong-wind zones, respectively. Additionally, the temporal frequency domain of wavelet analysis highlighted the distinct nature of TC and CW signals, with 1–3 d and 4–8 d, respectively, and with TC signals being short-lived and rapid compared to the more sustained CW signals. This study enhances our understanding of the response of coastal hydrodynamics to extreme weather events on the eastern Guangdong coast, and the results can provide references for disaster management and protection of nearshore ocean engineering under extreme events. Full article

Accurate assessment of net primary production (NPP) can truly reflect the carbon budget balance of the forest ecosystem. In this study, the boreal ecosystem productivity simulation (BEPS) model was used to simulate the NPP of Saihanba mechanized forest farm in 2020, and the influencing factors of NPP were analyzed. The meteorological, forest cover, leaf area index (LAI) and other data required for the model, as well as the data for verifying, were from field surveys or downloaded from different sources. The results showed that: (1) Within the scale of the flux tower, the diurnal variation of NPP reached a maximum in June. The monthly average peak value of latent heat flux was in June, and the sensible heat flux was in March. The temperature of the understory canopy was mostly higher than that of the overstory canopy and air temperature. (2) At the regional scale, the total NPP in the study area in 2020 was 4.25 × 10¹¹ g C a⁻¹, with an average of 564.71 g C m⁻² a⁻¹. The annual average NPP of silver birch (Betula platyphylla) was the largest, and the total NPP of northern Chinese larch (Larix principis-ruprechtii) was the largest. (3) NPP was highly sensitive to LAI. Topographic factors had effects on NPP. The average value of NPP was relatively high in the shady slope and the gentle slope. Full article

Given the complex spatiotemporal variability of aerosols, high-frequency satellite observations are essential for accurately mapping their distribution. However, optical remote sensing encounters difficulties in detecting Aerosol Optical Depth (AOD) over cloud-covered regions, creating data gaps that limit comprehensive environmental analysis. This study introduces a spatial gap-filling method for Himawari-8/Advanced Himawari Imager (AHI) hourly AOD data, using a Random Forest (RF) model that integrates meteorological variables and model-based AOD data. Developed and validated over South Korea from 1 January to 31 December 2019, the model effectively improved data coverage from 6% to 100%. The approach demonstrated high performance in blind tests, achieving a root mean square error (RMSE) of 0.064 and a correlation coefficient (CC) of 0.966. Meteorological analysis indicated optimal model performance under cold, dry conditions (RMSE: 0.047, CC: 0.956), compared to humid conditions (RMSE: 0.105, CC: 0.921). Validation against Aerosol Robotic Network (AERONET) ground observations showed that, while the original Himawari-8 data exhibited higher accuracy (RMSE: 0.189, CC: 0.815, n = 346), the gap-filled dataset maintained reasonable precision (RMSE: 0.208, CC: 0.711) and significantly increased the number of valid data points (n = 4149). Furthermore, the gap-filled dataset successfully captured seasonal AOD patterns, with values ranging from 0.245–0.300 in winter to 0.381–0.391 in summer, providing a comprehensive view of aerosol dynamics across South Korea. Full article

This national-scale assessment explores the anticipated impact of climate change on stream temperature in Poland. Utilizing an ensemble of six EURO-CORDEX projections (2006 to 2100) under Representative Concentration Pathways (RCPs) 4.5 and 8.5, the study employs the Soil and Water Assessment Tool (SWAT) to simulate stream temperature regimes. Validation against observed stream temperatures at 369 monitoring points demonstrates the reliability and accuracy of the SWAT model performance. Projected changes in air temperature reveal distinct seasonal variations and emission scenario dependencies. The validated stream temperature model indicates a uniform warming tendency across Poland, emphasizing the widespread nature of climate change impacts on aquatic ecosystems. Results show an increase in country-averaged stream temperature from the baseline (16.1 °C), with a rise of 0.5 °C in the near future (NF) and a further increase by 1 °C in the far future (FF) under RCP4.5. Under RCP8.5, the increase is more pronounced, reaching 1 °C in the NF and a substantial 2.6 °C in the FF. These findings offer essential insights for environmental management, emphasizing the need for adaptive strategies to mitigate adverse effects on freshwater ecosystems. However, as a preliminary study, this work uses a simplified temperature model that does not account for detailed hydrological processes and spatial variability, making it a good starting point for more detailed future research. Full article

Small- and medium-sized reservoirs significantly alter natural flood processes, making it essential to understand their impact on runoff for effective water resource management. However, the lack of measured data for most small reservoirs poses challenges for accurately simulating their behavior. This study proposes a novel method that utilizes readily available satellite observation data, integrating hydraulic, hydrological, and mathematical formulas to derive outflow coefficients. Based on the Grid-XinAnJiang (GXAJ) model, the enhanced GXAJ-R model accounts for the storage and release effects of ungauged reservoirs and is applied to the Tunxi watershed. Results show that the original GXAJ model achieved a stable performance with an average NSE of 0.88 during calibration, while the NSE values of the GXAJ and GXAJ-R models during validation ranged from 0.78 to 0.97 and 0.85 to 0.99, respectively, with an average improvement of 0.03 in the GXAJ-R model. This enhanced model significantly improves peak flow simulation accuracy, reduces relative flood peak error by approximately 10%, and replicates the flood flow process with higher fidelity. Additionally, the area–volume model derived from classified small-scale data demonstrates high accuracy and reliability, with correlation coefficients above 0.8, making it applicable to other ungauged reservoirs. The OTSU-NDWI method, which improves the NDWI, effectively enhances the accuracy of water body extraction from remote sensing, achieving overall accuracy and kappa coefficient values exceeding 0.8 and 0.6, respectively. This study highlights the potential of integrating satellite data with hydrological models to enhance the understanding of reservoir behavior in data-scarce regions. It also suggests the possibility of broader applications in similarly ungauged basins, providing valuable tools for flood management and risk assessment. Full article

The application of wool as mulch in strawberry cultivation was analysed to find a solution for the rational use of wool from mountain sheep. In the plantation, the experimental plots mulched with wool, straw, and bark were appointed. The plots were monitored during the experiment, while the soil temperature and moisture content were measured. The data collected in two-hour intervals were analysed, taking into account air temperature and falls registered in the local meteorological station. Additionally, the progress of mulch biodegradation was tracked. The changes in the wool morphology that occurred by biodegradation were observed during microscopic examinations using the Scanning Electron Microscope (SEM). It was stated that wool mulch plays an essential role in thermoregulation of the soil surface, prevents the overheating of the soil during the summer heat, and protects soil against excessive cooling during cold nights. The wool mulch minimizes the fluctuations between the soil’s day and night temperature. The fluctuations do not exceed 2–3 degrees on hot summer days, which are five times smaller than for the control plot. The wool retains large amounts of rainwater several times its weight. The water is then slowly released, providing the growing plants with a moist environment during a longer rainless period. Moreover, wool is difficult to biodegrade and maintains its properties for a long time, lasting longer than one vegetation season. Compared to straw and bark, the temperature fluctuations recorded for wool are two times smaller, and its effectiveness in water management is considerably better. The beneficial impact of the wool mulch ensuring favourable conditions for strawberry growth was explained by the specific wool structure and its unique properties. Full article

Joint multivariate distribution and calculation of return period are essential in enhancing drought risk assessment and promoting the sustainable development of water resources. Aiming to address the increasingly serious drought situation in the Yellow River Basin, this study first utilized the Soil and Water Assessment Tool (SWAT) distributed hydrological model combined with the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Soil Moisture Index (SSMI), and the Standard Water Yield Index (SWYI); the duration, peak, and severity of meteorological, agricultural, and hydrological droughts were analyzed. Based on the selected copula function, a three-dimensional joint distribution of drought duration (D), drought severity (S), and maximum severity (M) was constructed. The corresponding copula joint probability was calculated, leading to the three-dimensional joint return period and concurrent return period of meteorological drought, agricultural drought, and hydrological drought. The findings reveal several key trends: (1) Meteorological drought intensifies over time. Although drought areas eased after the 1990s, the overall drought trend continues to rise. Agricultural drought has intensified in arid regions but eased in semi-humid areas after the 2000s. Hydrological drought was severe in the upstream regions during the 1990s but eased in the 2000s, while it was particularly severe in the midstream and downstream regions during the 2000s. (2) Meteorological droughts are more severe in arid and semi-arid temperate regions and milder in semi-humid cold temperate regions. Agricultural droughts are extreme in arid and semi-arid cold temperate regions. Hydrological drought events are fewer but more severe in semi-arid temperate regions and have the lowest probability of occurrence in semi-humid cold temperate regions. (3) The overall probability of the occurrence of meteorological drought is between 55.7% and 69%; that of agricultural drought is between 73.1% and 91.7%, and that of hydrological drought is between 66.9% and 84%. Drought risk assessment provides scientific references for the analysis of the uncertainty of water supply in the basin and the formulation of effective risk management strategies. Full article

In this study, we utilized ECMWF Reanalysis of the Global Climate at Atmospheric Resolution 5 (ERA5) data, FengYun-4B satellite (FY-4B) data, a Wind3D 6000 Three-Dimensional Scanning Laser Wind Radar, and raindrop spectrum data to analyze the circulation background, convective cloud changes, boundary layer wind field variations, and precipitation drop size spectrum characteristics of a severe convective rainfall process that occurred on 3 April 2024 in the eastern margin of the Tibetan Plateau. The findings indicated the following: (1) The rain belt of this precipitation event showed a southwest–northeast trend. During the vigorous development of convection, the rainfall intensity and total precipitation at the station increased, with a wider raindrop spectrum, and the raindrop spectrum of this precipitation process was unimodal. (2) On 3 April, the interaction between the eastward movement of the plateau trough at 500 hPa and the upper-level jet stream at 200 hPa in the eastern Tibetan Plateau and the Sichuan Basin area, along with the necessary conditions for precipitation, such as energy and moisture, led to severe convective rainfall. (3) This intense convective precipitation process was caused by the vigorous convective clouds that developed in the eastern part of the Tibetan Plateau. As these clouds developed and moved eastward out of the plateau, they precipitated with increased turbulence intensity at the station, leading to the generation of intense convective activities at the site. (4) One hour before the precipitation, there were significant increases in horizontal wind speed, vertical air velocity, and turbulence intensity within the boundary layer, and there were also significant changes in the horizontal wind direction. The results obtained can provide important theoretical references for the prediction of severe convective rainfall and the performance of numerical simulations thereon. Full article

The Magdalena department, influenced by southern trade winds and ocean currents from the Atlantic and Pacific, is a climatically vulnerable region. This study assesses the Magdalena Department’s precipitation trends and stationary patterns by analyzing multi-year monthly records from 55 monitoring stations from 1990 to 2022. To achieve this, the following methods were used: (i) homogeneous regions were established by an unsupervised clustering approach, (ii) temporal trends were quantified using non-parametric tests, (iii) stationarity was identified through Morlet wavelet decomposition, and (iv) Sea Surface Temperature (SST) in four Niño regions was correlated with stationarity cycles. Silhouette’s results yielded five homogeneous regions, consistent with the National Meteorological Institute (IDEAM) proposal. The Department displayed decreasing annual trends (−32–−100 mm/decade) but exhibited increasing monthly trends (>20 mm/decade) during the wettest season. The wavelet decomposition analysis revealed quasi-bimodal stationarity, with significant semiannual cycles (~4.1 to 5.6 months) observed only in the eastern region. Other regions showed mixed behavior: non-stationary in the year’s first half and stationary in the latter half. Correlation analysis showed a significant relationship between SST in the El Niño 3 region (which accounted for 50.5% of the coefficients), indicating that strong phases of El Niño anticipated precipitation responses for up to six months. This confirms distinct rainfall patterns and precipitation trends influenced by the El Niño–Southern Oscillation (ENSO), highlighting the need for further hydrometeorological research in the area. Full article

Sharp-crested weirs are commonly used in hydraulic engineering for flow measurement and control. Despite extensive research on sharp-crested weirs, particularly regarding their discharge coefficients, more information is needed via research on their energy dissipation downstream. This study conducted experimental tests to assess the influence of contraction ratio (b/B) of rectangular sharp-crested weirs (RSCWs) on energy dissipation downstream under free flow conditions. Five RSCWs with different b/B equals 6/24, 7/24, 8/24, 9/24, and 10/24 were used. The results showed a consistent decrease in relative energy dissipation (Δ𝐸_𝑟) with an increase in the head over the weir. Furthermore, as the discharge per unit width (q) increased, the relative energy dissipation (Δ𝐸_𝑟) decreased, indicating more efficient discharge over the weir. A higher b/B further reduces Δ𝐸_𝑟, suggesting that wider weirs are more effective in minimizing energy losses. The maximum relative residual energy (E₁/E₀) and relative energy dissipation (Δ𝐸_𝑟) occurred at b/B = 10/24 and 6/24, with values of 0.825 and 0.613, respectively. Additionally, the maximum discharge coefficient (C_d) of RSCWs is found at b/B = 6/24, with an average value of 0.623. The results support the accuracy of the proposed equation with R² = 0.988, RMSE = 0.0083, and MAPE = 1.43%. Full article