Search Results (374)

In the seasonally frozen area, slopes are exposed to freeze–thaw cycles; thus, water and heat are moved, and the foundation for the transportation infrastructure in cold regions may be weakened. Based on the relatively strong water-recharge effect and considerable fluctuations in shallow soil moisture during the spring thaw along the Naba section of the G218 Highway in Xinjiang, China, a coupled hydro-thermal model for frozen soil that considers snowmelt infiltration and rainfall recharge was developed, and it was numerically implemented in COMSOL. A one-dimensional unidirectional freezing test of a soil column was used to validate the model, and the relative errors of the simulated temperature and moisture fields were 3.8% and 4.3%, respectively; both are within the accuracy requirements for engineering-scale analysis. Then, a model was used to determine how the temperature, volumetric ice content and volumetric water content of a representative slope in the Naba section changed during a freeze–thaw cycle. Based on the above results, the annual temperature range at the surface of the topsoil on the slope is 37.61 °C, and this thermal effect extends to a depth of 0–3 m. In the spring thaw, the volumetric water content of the surface layer increased from 8.45% in February to 19.34% in May, and further to 20.65% in July; therefore, it can be inferred that the shallow soil is still being replenished by snowmelt and rain. Freezing-thaw phase change, freezing-front migration and external water infiltration work together to control hydro-thermal transport in the slope; thus, a redistribution and local accumulation of liquid water occur below the residual frozen layer and under the shallow surface. The above results can serve as a reference for drainage design and as a means to prevent or control freeze–thaw damage to the slope of a highway in Xinjiang’s seasonally frozen area during the spring thaw. Full article

Flood hazards are intensifying across Africa due to rapid urban expansion and hydro-climatic variability. This study develops a multi-metric geospatial framework combining extreme value analysis, hydrograph-based metrics, and dependence modelling to quantify flood magnitude, frequency, timing, and joint risk dynamics. Daily precipitation and streamflow reanalysis data (1985–2025) were analyzed for two contrasting Tanzanian catchments: the large Rufiji basin (RU) and the smaller Mirongo catchment (MW). Annual maxima were modelled using the Generalized Extreme Value (GEV) distribution, complemented by flow duration curves, peak-over-threshold detection, and regression-copula dependence analysis. Results reveal strong hydrological contrasts. RU exhibits amplified rare-event growth (design floods from ~2850 to 11,770 m³/s), extended recession persistence (>100 days), low flashiness, and long rainfall-runoff lags (~15 days), indicating storage-dominated behavior. MW shows smaller design floods (~80 to 370 m³/s), higher flashiness, and short lags (~4 days), reflecting rapid, rainfall-driven response. Gaussian copula parameters indicate moderate dependence in both basins (0.32 and 0.34), suggesting that joint dependence alone does not distinguish flood mechanisms without complementary metrics. The proposed framework improves basin-specific flood risk profiling and supports geospatial early-warning system design in data-scarce Sub-Saharan environments. Full article

Climate models suggest that longer dry periods and heavier rainfall events may occur in arid and semiarid regions, which may greatly affect plant growth and propagation in these regions. Numerous studies have documented the relationship between grassland productivity and precipitation. However, the interactive effects of rainfall amount and rainfall frequency on the growth of perennial grasses with rhizomatous propagation, especially on clonal growth, have not yet been studied. In this study, the effects of three rainfall amounts and two rainfall frequencies on the vegetative traits and clonal growth traits of Leymus chinensis, a perennial rhizomatous species, were examined. Rainfall amount and rainfall frequency exhibited a significant interaction only for the root biomass ratio between the 0–20 cm and 20–40 cm soil layers. All traits (including height, aboveground biomass, root biomass, rhizome number, rhizome length, bud bank size, and daughter shoot number) increased markedly with increasing rainfall amount but showed little response to rainfall frequency. Only the root biomass in the 20–40 cm soil layer increased with an extended dry period between two rainfall events, resulting in a lower root biomass ratio between the 0–20 cm and 20–40 cm soil layers under the medium and high rainfall amount treatments. The size of the belowground bud bank was positively correlated with the daughter shoot number as well as the aboveground biomass, and the positive relationship between the bud bank size and daughter shoot number was strengthened with increasing rainfall amount, but was not sensitive to rainfall frequency. However, lower rainfall frequency significantly decreased the rhizome number per plant. These results highlight that summer rainfall amount is more important than rainfall frequency for the population growth of L. chinensis at medium and high rainfall amounts, and that lower rainfall frequency may reduce the long-term clonal growth ability of L. chinensis in the future. Our findings reveal the response mechanisms of L. chinensis productivity to climate change from the novel perspective of bud banks, which provides practical management insights for artificially established L. chinensis grasslands. This study also offers important implications for elucidating the contributions of belowground biomass production to soil carbon sequestration in grassland ecosystems. Full article

Microwave-based remote sensing possesses the capability to penetrate through atmospheric obstructions such as cloud layers and fog, making it extensively utilized for estimating parameters including soil water content, atmospheric moisture levels, and terrestrial surface temperatures. Extended temporal datasets serve as fundamental requirements for climatological investigations; however, individual satellite operational lifespans remain constrained and prove inadequate for establishing multi-decade temporal sequences. Consequently, conducting comparative analyses and implementing cross-calibration procedures across measurements obtained from distinct sensors exhibiting comparable operational features becomes imperative. The FengYun (FY)-3G spacecraft, deployed into orbit during April 2023, hosts China’s most recent orbiting microwave radiometric instrument, designated as the Microwave Radiation Imager–Rainfall Mission (MWRI-RM). The FY-3G satellite’s unique drifting equator crossing time orbit plays a critical role in the calibration behavior of the MWRI-RM instrument, representing a key novelty of this study. The reliability of its brightness temperature (TB) observations has attracted considerable attention. Within this investigation, we conduct comparative assessments of orbital TB observations acquired from FY-3G/MWRI-RM against corresponding measurements obtained from the Advanced Microwave Scanning Radiometer 2 (AMSR2) installed on the Global Change Observation Mission–Water 1 (GCOM-W1) platform, and establish a straightforward linear inter-calibration methodology. Both sensing systems show strong consistency, with correlation coefficients exceeding 0.9 for all corresponding channels and systematic biases ranging from −1.40 K to −0.14 K. FY-3G/MWRI-RM generally reports lower TB values than GCOM-W1/AMSR2. The inter-sensor differences vary with frequency, land cover type, and TB range. Larger negative biases are mainly observed at 23.8 GHz and over water bodies, whereas the biases at 89 GHz are generally close to zero for most surface types. Latitude-dependent TB biases are most evident at 10.65 and 18.7 GHz, especially for vertical polarization at high latitudes, while orbit-dependent differences are more pronounced for vertically polarized low- and mid-frequency channels. After applying an inter-calibration procedure using AMSR2 as the reference, the agreement between FY-3G/MWRI-RM and GCOM-W1/AMSR2 is improved substantially, with mean biases below 0.25 K and RMSE values below 2 K for all channels. Validation using independent datasets further supports the stability of the calibration. The calibrated FY-3G/MWRI-RM TB data provide a basis for constructing long-term passive microwave brightness temperature records and for retrieving land and atmospheric parameters. Full article

The Global Navigation Satellite System Reflectometry (GNSS-R) technique provides global ocean surface wind observations unaffected by rainfall with high spatiotemporal resolution. The Fengyun-3E (FY-3E) mission, as the first operational GNSS-R satellite in China, offers low-latency data suitable for numerical weather prediction (NWP). However, the dense along-track sampling of GNSS-R winds poses challenges for observation error specification in data assimilation. In this study, FY-3E GNSS-R winds are assimilated into the Weather Research and Forecasting (WRF) model to investigate the impacts of different observation error configurations. Both static and dynamic error specifications, with and without data thinning, are evaluated through a sensitivity experiment and subsequent Observing System Experiments (OSEs). The results indicate that using a static observation error of 6 m/s without data thinning achieves the best performance. Under this configuration, GNSS-R winds influence atmospheric analyses from the surface up to approximately 700 hPa in a single assimilation case, while cycling experiments further extend the impact vertically and spatially. These findings highlight the importance of appropriate observation error specification for dense GNSS-R data and provide a practical reference for their assimilation in WRF, with potential applicability to other NWP systems. Full article

Natural ecosystems are facing threats from natural and anthropogenic stressors. Wetlands are among the most delicate natural ecosystems and are particularly vulnerable to the impacts of urbanization. One of the intended purposes of the wetlands is to mitigate the impact of urbanization (e.g., stormwater), but we often lack a comprehensive understanding of their capacity in doing so. Determination of water balance is essential in understanding the efficacy of a wetland when it comes to treating excess stormwater. This study therefore considers the Sparrovale Wetland in Victoria, Australia, to assess its performance in mitigating the impacts of urbanization in the surrounding catchment areas. A 1D model (HYDRUS-1D) was previously developed by the authors based on extensive field and laboratory measurements on one side (north) of the wetland. It was crucial to understand the two-dimensional water balance dynamics in the Sparrovale Wetland to utilize its full potential for managing excessive stormwater. This study therefore employed the HYDRUS-2D model (based on HYDRUS-1D) supported by extended, spatially explicit in situ measurements. The model was run (with additional input of inflow added to the rainfall) on the average Van Genuchten parameters obtained from the previously developed HYDRUS-1D model and the extended determination of the parameters. The model performance in simulating measured water content was good for both the south (average RMSE = 0.013 m³/m³) and the north side (average RMSE = 0.028 m³/m³). The model was also used to simulate surface water levels in the wetland and showed a good agreement (RMSE = 0.1 m AHD and R² = 0.72) with in situ surface water level measurements. This developed model was used to determine the water balance dynamics (infiltration, evapotranspiration, soil water storage, surface and bottom boundary flux) in the Sparrovale Wetland. Our results indicate that evapotranspiration is the major factor controlling the water flux losses in the Sparrovale Wetland, while the role of infiltration was minimal, which might be attributed to the dominant soil type (clay) and shallow groundwater levels in the Sparrovale Wetland. Insights provided by this study might be helpful in optimizing the performance of the Sparrovale Wetland in managing the excess stormwater arising from the surrounding catchments. Full article

Under grazing conditions, it is difficult for lactating Yili mares to meet their nutritional requirements and those of their suckling foals solely through the consumption of natural pasture. Furthermore, seasonal variations and rainfall significantly influence the quality and nutrient content of forage, which severely constrains the healthy breeding of Yili horses and the industrial development of mare milk resources. Therefore, this study aimed to investigate the effects of concentrate supplementation on lactation performance and milk concentrations of amino acids, fatty acids, and mineral elements in Yili horses under grazing conditions. Twenty-two healthy Yili mares in early lactation, with similar ages (3–4 years), foaling dates, and body weights (391.5 ± 13.74 kg), were randomly assigned to either a grazing group (G, n = 11) or a grazing + supplementation group (GS, n = 11). Mares in group G grazed naturally on pasture, while those in group GS received 1 kg of concentrate supplement twice daily (totaling 2 kg/day) in addition to grazing. The experimental period lasted for 100 days, including a 10-day adaptation period and a 90-day formal experimental period. The results showed that: (1) In terms of lactation performance, the GS group exhibited highly significant increases in milk yield and lactose yield (p < 0.01), as well as significant increases in milk protein and milk fat yields (p < 0.05), with an extended duration of the peak lactation period. (2) Regarding the amino acid profile, the concentrations of threonine (Thr), serine (Ser), glycine (Gly), and alanine (Ala) in the milk of the GS group were significantly higher than those in the G group (p < 0.05), whereas the proline (Pro) content was significantly lower (p < 0.01); supplementation improved the uptake of certain functional amino acids by the mammary gland. (3) Concerning the fatty acid profile, the concentrations of polyunsaturated fatty acids (PUFA) and alpha-linolenic acid in the milk of the G group were significantly or highly significantly higher than those in the GS group (p < 0.05 or p < 0.01). (4) For mineral elements, concentrate supplementation highly significantly decreased the potassium (K) content and the K/Na ratio in horse milk (p < 0.01), highly significantly increased the levels of iron (Fe) and cobalt (Co) (p < 0.01), and significantly enhanced the chromium (Cr) content (p < 0.05). In conclusion, concentrate supplementation during grazing improved lactation performance in Yili mares, primarily by increasing milk yield and extending the peak lactation period. However, grazing alone was more favorable for maintaining higher PUFA and α-linolenic acid proportions in milk. Therefore, concentrate supplementation should be regarded as a nutritional strategy that increases milk output and modifies amino acid and mineral element composition, but may involve a trade-off with some beneficial fatty acids. Full article

Overhead distribution systems may experience concurrent wind and rainfall loading during typhoon events, but most existing studies still emphasize individual components, single-hazard descriptions, or network-level consequences. To address this gap, this paper develops a probabilistic assessment framework for distribution pole–line segments exposed to compound typhoon wind–rain hazards. A three-dimensional finite-element model of a representative segment with three poles, two spans, and three-phase conductors is constructed, and uncertainties in structural properties and loading-related coefficients are incorporated explicitly. Correlated turbulent wind histories are synthesized using the Davenport spectrum and harmonic superposition method, whereas rainfall actions are represented through an impact-based raindrop spectrum formulation. Nonlinear dynamic analyses are performed for multiple combinations of basic wind speed and rainfall intensity, and the resulting peak conductor tension and pole-base bending moment are used as engineering demand parameters. Logarithmic probabilistic demand models are then fitted to derive failure-probability surfaces for the conductor, the pole, and the pole–line segment. Segment failure is defined through the maximum normalized demand among the central pole and the six connected conductors, thereby extending the assessment from component-level failure to local segment-level risk. The results show that basic wind speed governs the overall evolution of failure probability, whereas rainfall acts as a secondary but non-negligible amplifying factor that shifts the probability transition zone toward lower wind-speed levels. For the adopted configuration, the segment-level failure probability is governed mainly by pole response. Additional model checks and event-based comparisons support the consistency of the proposed segment-level probability formulation. The proposed methodology can support risk screening, warning-threshold setting, and maintenance decision making for overhead distribution systems subjected to compound meteorological hazards. Full article

Groundwater in arid and semi-arid regions is increasingly stressed by low rainfall, high evaporation, population growth, agricultural expansion, and climate change. A critical question is whether non-renewable aquifers can sustain rising water demand without irreversible decline. This study addresses that question for the Al Kufrah Basin in southeastern Libya, part of the Nubian Sandstone Aquifer System, the world’s largest fossil aquifer. A three-dimensional groundwater flow model (MODFLOW-2000) was calibrated using data from more than 1000 production wells and 32 piezometers spanning 1968–2022. The model was applied to simulate groundwater behavior under five scenarios extending to 2050, including the planned development of 150 new wells. The results indicate that over 85% of withdrawals are derived from aquifer storage rather than boundary inflows. While regional water levels remain relatively stable over the 25-year horizon, localized drawdowns of up to 11 m are expected near new well fields. These findings highlight short-term resilience but point to long-term vulnerability, as continued reliance on non-renewable reserves without recharge will ultimately lead to depletion. The study underscores the need for adaptive management, climate-resilient water strategies, and regional cooperation to ensure the sustainable use of this transboundary aquifer under increasing environmental and socio-economic pressures. Full article

Environmental and financial datasets often display complex distributional characteristics, including heavy tails, high skewness and the presence of extreme observations. Traditional probability models such as the exponential, gamma or log-normal distributions may not adequately capture these behaviours particularly when modelling extreme events such as rainfall, pollution levels, stock returns or loss severities. By integrating the characteristics of Pareto and exponential distributions into an exponentiated framework that can describe datasets arising from environmental and finance fields, this study presents a novel three-parameter exponentiated Pareto exponential distributions using the exponentiated Pareto family of distributions with classical exponential distribution as the baseline model. This novel model extends the classical exponential distribution with the addition of extra shape parameters which simultaneously regulate the centre and tail behaviours of the new model. The statistical and mathematical characteristics of the proposed distribution are determined and studied. The maximum likelihood estimate approach is used in a conducted simulation exercise, and the estimator’s efficiency is evaluated as seen from the results. The practical applicability of the model is illustrated with four real-life datasets utilising model adequacy and goodness-of-fit measurements such as log–likelihood, Akaike information criteria and Bayesian information criteria. The data reveal that the proposed model gives a better fit than the models chosen as comparators, making the EPE distribution useful and robust in environmental and financial fields of study. Full article

This study examines the effects of climate change on precipitation and drought conditions in Greece, focusing on basin-level hydrological analysis. It builds on existing evidence that the Mediterranean region is highly vulnerable to global warming, experiencing reduced rainfall, extended droughts, and increased hydro-climatic extremes. Using high-resolution down-scaled climate projections under multiple RCP scenarios, the research quantifies precipitation volume within specific hydrological basins, incorporating detailed basin geometries and spatial statistical methods. Alongside precipitation estimates, consecutive dry days and drought frequency, assessed via the Standardised Precipitation Index, offer a multi-indicator view of climate stress. This basin-specific framework connects climate modelling with water resource management, supporting more targeted adaptation strategies. The findings provide new spatial insights into how precipitation redistributes across basins under future climate conditions, with implications for drought-prone regions in Greece. Full article

Ranked 30th globally in dryness, South Africa faces severe challenges in ensuring fodder security, which is worsened by climate change impacts on agriculture. However, there is still limited knowledge about optimising fodder radish cultivation under shifting climatic conditions. This study investigated the effects of planting dates (December to March), cultivars (Nooitgedacht, Line 2 and Endurance) and seasons (2020/21 and 2021/22) on growth, yield, and crude protein (CP) and mineral concentrations under rainfed conditions. Seasonal variation significantly (p < 0.05) influenced emergence, relative growth, and flowering across planting dates. Fresh tuber yield was highest when Nooitgedacht was planted in December (2052 and 2102 kg ha⁻¹). In contrast, January planting enhanced aboveground biomass and crude protein (CP) yield, with Endurance recording the highest biomass (1260 and 1157.95 kg ha⁻¹ DM) and tuber CP yield (19.2 and 18 kg ha⁻¹). December planting favoured tuber production, whereas January planting optimised biomass, CP yield, and persistence. Planting date and cultivar significantly affected leaf and tuber mineral concentrations. December–January plantings generally enhanced leaf P, K, and Zn concentrations. Endurance and Nooitgedacht accumulated higher micronutrients than Line 2, particularly under early planting. The late flowering of Endurance extended the grazing period, aligning with late-winter forage demand under rainfed conditions. Overall, this study offers practical guidance for improving the quantity and quality of fodder radish in diverse agricultural settings. Future work should evaluate these cultivars across more sites to confirm performance stability under variable rainfall patterns. Full article

This study of the Ethiopian Rift Valley meso-climate (5° N–9° N, 37° E–40° E) employed space–time statistical methods over the period 1981–2025. Links between weather conditions at Hawassa (7.1° N, 38.5° E, 1700 m) and the Indian Ocean Dipole (IOD) were uncovered, among 3–4 yr oscillations and a weak upward trend. Seasonal anomalies of local dewpoint temperature (Td) and IOD cross-correlated at R = 0.61 over the four-decade study. Mean annual cycling revealed a narrow range for Td from April to October, in contrast with bi-modal rainfall and asymmetric runoff. Diurnal cycle analysis indicated that evening rainfall was driven by midday heat (0.6 mm/h) and moisture fluxes (0.1 mm/h). A case study revealed how shallow cloud bands extend westward from cool, forested highlands to the warm Rift Valley. Composite differences between warm and cool IOD events exhibited contrasting effects for zonal and meridional airflows, which explains why the equatorial trough and its associated rainfall are confined to the southeastern escarpment of Ethiopia. While earlier studies had anticipated drying trends, wetter conditions during the warm IOD events of 2019 and 2023 resulted in rising lake levels (1.8 m) and crop yields (4 T/ha). These findings enhance our understanding of regional climate dynamics to support adaptive management. Full article

Detection of brown spot needle blight (BSNB) disease caused by the fungal pathogen Lecanosticta acicola (Thum.) Syd. has increased significantly at commercial loblolly pine (Pinus taeda L.) plantations across the southeastern United States in recent years. Historically, it has been a serious problem in longleaf pine (Pinus palustris Mill) during the grass stage of seedlings, when the environment is more conducive to fungal infection. However, since 2016, confirmed cases of the disease on loblolly pines have increased in several states, including AL, AR, FL, GA, LA, MS, SC, TN, and TX. We investigated the distribution pattern of confirmed cases of BSNB on loblolly pine between 2016 and 2023, identified site-specific factors, and evaluated the historical standardized precipitation index (SPI) value record over the past four decades. Our results showed that extended periods of above-normal SPI values are associated with BSNB spatial distribution patterns, particularly where the disease has been widely reported in AL, AR, LA, and MS. We observed significant reduction in tree height and dbh in severely infected versus healthy trees at the six study sites evaluated in 2023. Excessive rainfall and prolonged water saturation associated with historical 5-Year SPI values suggest that vulnerable loblolly pine seedlings (depending on genetic family) are more likely to be predisposed to L. acicola infection due to persistent stress from reduced soil nutrient flux and other physiological processes of the host. Understanding the effect of precipitation patterns on cases of BSNB is an important step toward preventing or minimizing the future impact of the disease on commercial plantations in the Southeast. Full article

Southern India and Sri Lanka (SISL) rainfall during January–April (JFMA) exhibits strong interannual variability and is influenced by the El Niño–Southern Oscillation (ENSO), yet the long-term evolution of this relationship and its physical drivers remain unclear. Based on multiple precipitation datasets and atmospheric reanalysis products for 1950–2024, this study reveals a pronounced strengthening of the negative correlation between JFMA-mean SISL rainfall and the Niño 3.4 index, shifting from a statistically insignificant relationship prior to the late 1970s to a more coherent association after the 1980s. This transition is accompanied by intensified ENSO-related circulation anomalies. The strengthened and westward-extended Northwest Pacific Anticyclone (NWPAC) plays a dominant role, whereas an enhanced cross-equatorial temperature gradient in the Indian Ocean contributes to a lesser extent. Composite analyses further indicate that, on average, Eastern Pacific (EP) ENSO events tend to produce stronger rainfall anomalies over SISL than Central Pacific (CP) events; however, the differences between EP and CP composites are not statistically significant, reflecting pronounced event-to-event variability, especially for CP events. These results highlight the complexity of ENSO–SISL teleconnections and underscore the importance of NWPAC as a key bridge linking Pacific SST variability to regional rainfall responses. Full article