Search Results (1,756)

Climate change alters not only the availability of solar radiation, but also the thermal, humidity, and cloudiness conditions under which solar energy systems operate. However, limited attention has been paid to the simultaneous comparison of photovoltaic and solar thermal responses using a common hourly climate-based framework under Central European conditions. This study evaluates long-term climate-driven changes in the operating conditions of photovoltaic (PV) panels and solar thermal collectors across five Slovak locations representing contrasting local climatic and topographic settings. Hourly ERA5-Land data for 1985–2024 were used to derive climatic indicators, photovoltaic operating indicators, and solar thermal performance indicators. The analysis combined long-term Mann–Kendall and Sen’s slope trend assessment with a comparison between the reference period 1985–1994 and the recent period 2015–2024. The results show that mean air temperature increased by 1.50–1.69 °C, global horizontal irradiance by 3.24–5.66%, and high-irradiance hours increased substantially across all sites. Photovoltaic yield increased by 2.21–4.52%, but this improvement was accompanied by higher PV cell temperature, more hot operating hours, and increased temperature losses. Solar thermal collectors showed a stronger relative response, with useful thermal gains increasing by 7.27–12.33% at 35 °C and by 9.00–15.73% at 50 °C. The Relative Solar Thermal Gain Advantage was positive at all locations, indicating that recent climatic conditions favored solar thermal gain more strongly than PV yield under the applied assumptions. The findings demonstrate that recent climatic data should be used in solar-system design and that photovoltaic and solar thermal technologies require separate interpretation because they respond differently to warming and changing radiation conditions. Full article

The upper Sebou River occupies a strategic territory draining varied mountain reaches in northern Morocco. As such, it is rich in surface water resources and karst springs with important downstream uses. However, the variability of rainfall threatens its water potential, making it highly vulnerable and at risk of desiccation. This study explores rainfall trends and their effects on streamflow and water resource availability. Data from three stations representing the upstream section of the watershed, along with two streamflow series—one for the upper Sebou River (Pont Medz) and the other for the Aïn Timdrine karst spring—cover the period from 1956 to 2018. The methodology employs Mann–Kendall trend tests, Sen’s Slope test, and the Standardized Precipitation Index (SPI) for rainfall series, as well as the Streamflow Drought Index (SDI) for hydrological series. The results demonstrate a decline in rainfall since 1979, significant at the 5% threshold. This trend has an immediate impact on the flow rates of the area’s rivers and karst springs, which have also tended to decline, with a succession of dry years and seasons since 1980. This observation highlights the depletion of water resources of the fragile upper Sebou region in the face of decreasing rainfall and snowfall, compounded by the rampant and unsustainable exploitation of groundwater resources linked to the development of irrigated cash crops in the Middle Atlas Mountains. Full article

Urbanisation and impervious-cover expansion are reshaping riparian landscapes, particularly in mountain cities where steep terrain concentrates development along valley floors. This study examined spatiotemporal land-cover change within the regulated riparian corridors of Thimphu City, Bhutan, over a 25-year period from 1997 to 2022 using Landsat imagery, Random Forest classification and Google Earth Engine. Results show substantial transformation of riparian land cover, with impervious cover increasing from 26.14% to 32.63%, equivalent to an overall increase of 24.83%, while agriculture/barren/low-vegetation declined from 30.59% to 26.01%, equivalent to an overall decrease of 14.98%. A modest increase in detectable vegetation cover was also observed, although this should be interpreted cautiously because the study measured land-cover extent rather than vegetation condition, floristic composition or ecological quality. Classification performance was robust, with overall accuracies ranging from 89.9% to 94.5%, exceeding the commonly accepted 85% benchmark, although uncertainty remains in narrow riparian corridors due to Landsat’s 30 m spatial resolution. Mann–Kendall analysis provided supplementary evidence of monotonic land-cover trends, but the limited number of temporal observations means these results should be interpreted as indicative, rather than definitive. Spatial analysis revealed uneven transformation, with the southern valley recording the greatest increase in impervious cover. These findings demonstrate sustained development pressure within legally regulated riparian buffers and highlight the need for routine spatial monitoring, place-specific buffer management and stronger integration of riparian protection into urban planning. The study provides a quantitative baseline for assessing future riparian land-cover change and supporting more resilient land governance in rapidly urbanising Himalayan mountain cities. Full article

This study analyzed precipitation and air temperature in the Zhambyl, Almaty, Zhetysu, Abay, and East Kazakhstan regions of Kazakhstan using data from the national meteorological network of the RSE Kazhydromet. The purpose of the study was to reveal the climatic changes and their spatial distribution throughout the study area. A modified Mann–Kendall test and Sen’s Slope estimator were applied to analyze aridity conditions in combination with the drought indices SPEI and Selyaninov hydrothermal coefficient, enabling analysis of the magnitude and statistical significance of trend changes from April to September for the period 1981 to 2023. The magnitude of the observed trends of the mean growing-season temperature increased by 0.211 °C decade⁻¹, while precipitation declined by 2.074 mm decade⁻¹, which indicates a decrease in moisture availability for crops in the southeast and east of Kazakhstan. The results of this study may be of interest to agricultural specialists, ecologists, the Ministry of Emergency Situations, and hydrologists to develop activities aimed at preventing threats and mitigating the effects of climate change in Kazakhstan. The use of the above statistical methods in combination with drought indices is relevant in the context of climate change and worsening food security and can serve as a good indicator for determining when significant changes in climatic parameters occurred, which will be valuable information for making management decisions. Full article

This study assessed the spatiotemporal dynamics of eco-environmental quality (EEQ) in Sonid Left Banner from 2000 to 2025, using Landsat imagery and the remote sensing ecological index (RSEI) via Google Earth Engine. Theil–Sen slope, Mann–Kendall test, Hurst exponent, and Pearson correlation analysis were used to analyze trends and their associations with climatic and anthropogenic factors. Results showed that EEQ exhibited an overall improving trend, with a mean RSEI of 0.270 and an annual increase of 0.0022 a⁻¹, though it remained at a fair grade with a spatial pattern of “regionally poor but locally improved.” Hurst exponent analysis has indicated that 75.35% of the study area will sustain improvement, while 17.03% faces continuous degradation risk. Climatic factors showed the strongest associations with RSEI: precipitation (r = 0.329) and humidity (r = 0.313) showed the strongest positive correlations, with a distinct north–south spatial gradient in their association patterns; temperature (r = 0.272) showed bidirectional correlation patterns; and wind speed (r = −0.197) was the primary negative correlated factor. Human activity intensity (HAI) was negatively correlated with RSEI (r = −0.128), with 7.8% of high-intensity development areas showing significant degradation. These findings reveal that moisture availability establishes the ecological baseline in semi-arid grasslands, while human activities modulate ecosystem change, informing targeted ecological restoration. Full article

This study examines long-term mangrove vegetation dynamics in the Cananéia–Iguape Coastal System (CICS), southeastern Brazil, with emphasis on their relevance for coastal ecosystem monitoring and sustainability. Land-use and land-cover (LULC) data from MapBiomas were combined with MODIS-derived vegetation indices, namely the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), and Fractional Vegetation Cover (FVC) to assess spatial variability and temporal trends from 2003 to 2024. Spatial anomalies were calculated as deviations from long-term mean conditions, whereas temporal trajectories were evaluated using the non-parametric Mann–Kendall test and Sen’s slope estimator. The results indicate limited spatial variability, with 98.35% of the study area for the NDVI and 99.51% for the EVI showing no detectable deviations from long-term averages. Within mangrove areas, however, statistically significant positive trends were identified for the NDVI (Z_MK = 2.43; p = 0.02), EVI (Z_MK = 2.03; p = 0.04), and FVC (Z_MK = 2.43; p = 0.02), suggesting a gradual increase in spectral greenness and FVC-derived vegetation density. The moderate correlation between mangrove extent and the NDVI (r = 0.61; p < 0.05) indicates that the mapped mangrove area is partially associated with variations in spectral greenness, although this relationship should not be interpreted as direct evidence of ecological recovery or improved ecosystem conditions. Overall, the findings point to low-magnitude but consistent vegetation index changes in a predominantly stable mangrove system. The integration of LULC information, spectral indices, and FVC provides a consistent regional-scale basis for interpreting mangrove dynamics in heterogeneous coastal environments and for guiding long-term monitoring efforts. Full article

Mediterranean coastal groundwater-dependent ecosystems are among the most vulnerable environments to the combined effects of climate change and local anthropogenic pressures, yet long-term quantitative assessments disentangling these drivers remain limited. The 41-year hydro-ecological dynamics (1984–2025) of “Le Soglitelle”, a transitional man-made coastal GDE located in the Campania Plain (southern Italy), were reconstructed across three management regimes: illegal hunting via electric pumps augmentation of flooded areas (1984–2004), post-seizure transition (2005–2015), and fenced natural reserve sustained by artesian wells flow (2016–2025). A monthly multi-sensor time series of seven spectral indices was derived from cross-calibrated Landsat program Surface Reflectance products via Google Earth Engine. Spectral indices were then combined with climatic variables (precipitation, reference evapotranspiration, air temperature) and then integrated in a statistical framework including Mann–Kendall test, Pettitt test, and Principal Component Analysis. Significant breakpoints were identified for the water fraction (2007; mean decrease from 0.18 to 0.09) and the Normalized Difference Vegetation Index (2009; mean increase from 0.30 to 0.42), consistent with a hydrological regime shift following the interruption of anthropogenic pressures. The relationship between the water fraction and the Vegetation Soil Salinity Index was 2.7 times steeper in the last period than the first one, indicating that, for an equivalent flooded extent, osmotic stress on vegetation is substantially higher under the artesian flow alone, likely due to reduced dilution of saline inputs combined with the effect of ongoing climate change. PCA showed that PC1 reflected the transition from anthropogenic to more natural system conditions, whereas PC2 was associated with increasing ET₀, became more prominent during the last period of management, suggesting a shift toward stronger climate-driven control. Long-term satellite monitoring provides a quantitative baseline for designing targeted management interventions aimed at sustaining ecosystem functioning under ongoing Mediterranean warming. Full article

The accurate prediction of Arctic sea ice concentration is essential for polar ecological protection and shipping safety. However, existing prediction methods suffer from insufficient feature representation, which limits their ability to capture the complex spatiotemporal distribution of sea ice. Furthermore, they cannot effectively integrate multi-source, heterogeneous sea ice-related data, resulting in limited prediction accuracy. To address these issues, this paper proposes a Multimodal Feature and Trend analysis (MFT) method for sea ice concentration prediction. In the feature extraction stage, MFT combines a Convolutional Neural Network with a Convolutional Block Attention Module to deeply extract global deep semantic features while also employing the Scale-Invariant Feature Transform algorithm to accurately capture local stable features. To improve processing efficiency for high-dimensional remote sensing data, a coarse-resolution dimensionality reduction strategy is developed to select core spatial features, thereby preserving key spatial distribution information while optimizing computational efficiency. For temporal analysis, the Mann–Kendall (MK) non-parametric test and Sen’s slope method are integrated to quantitatively analyze long-term evolution trends in Arctic sea ice concentration. Experimental results show that the proposed MFT model outperforms random forest (RF), LSTM, and traditional MK methods in both prediction accuracy and computational efficiency. Full article

The Aconcagua River Basin is one of the most important basins in Chile, supporting a large percentage of economic activities such as intensive agriculture, mining, agroindustry, manufacturing, and hydropower generation. This basin is highly sensitive to climate change because it relies primarily on snowmelt and glacier contributions for water availability. In recent decades, a water deficit has been reported affecting water supply for the entire basin. This study focuses on changes in snow cover in the headwater catchment of the Aconcagua Basin and their relationship with meteorological conditions. The databases rely on satellite remote sensing and climate reanalysis data, using Landsat and MODIS collections for Snow Cover Area (SCA) data and ERA5 reanalysis for meteorological data, respectively. SCA, albedo, air temperature and relative humidity, in addition to snowfall, were assessed using Sen’s slope and Mann–Kendall non-parametric test to estimate trends and their significance. The results showed a decrease in SCA of about 99.1 and 138.2 km² per decade for MODIS and Landsat, respectively. Reanalysis datasets are related to the increase in warming trends, which accelerate the snow melting process and reduce water availability for the summer season. Hence, these results suggest the need to increase the ground-based snow monitoring stations to validate satellite data. Finally, the results can be used for new insights into water management at the basin scale in order to promote water use efficiency. Full article

Due to its unique hydrogeological conditions, the Southwest Karst Area (SKA) in China experiences droughts far more frequently than non-karst regions. Exploring the distribution patterns and driving factors of different drought types is crucial for enhancing the region’s disaster prevention and mitigation capabilities and effectively addressing climate change risks. Using meteorological data from 1979 to 2023 in the SKA—including precipitation, temperature, humidity, potential evapotranspiration, and soil moisture—this study employed Copula theory to construct the Standardized Temperature Deficit Index (SDTI), the Standardized Humidity–Temperature Deficit Index (SDHTI), and the Standardized Atmosphere–Soil Index (SASI). Based on these indices and run theory, this study revealed the spatial distribution characteristics of different drought types (general, atmospheric, and composite) in terms of intensity, frequency, severity, and duration. Furthermore, the Mann–Kendall test and random forest analysis were applied to investigate drought trends and primary driving factors. The results indicate that droughts in the SKA exhibit significant regional characteristics and an overall worsening trend. Among them, droughts in karst-developed regions are generally more severe, though their manifestations vary across areas: compound droughts are particularly severe on the western Sichuan Plateau but relatively mild in Guangxi. In contrast, atmospheric droughts are more pronounced in Guangxi. Regarding trends, the rate of drought intensification was relatively moderate in Guangxi and the western Sichuan Plateau but more pronounced in other regions, with the maximum increase reaching 0.59. However, this upward trend is not statistically significant. Additionally, drought in karst areas was characterized by high frequency and intensity but shorter duration and lower severity, whereas the opposite was true in non-karst areas. Random forest analysis revealed that temperature is the primary driver of SDTI (2.60), while relative humidity and temperature have significant impacts on SDHTI (3.21 and 2.42, respectively). Soil moisture and temperature contribute most significantly to SASI (2.08 and 1.48, respectively). These findings provide important insights to guide the rational allocation of regional water resources and optimize agricultural management strategies. Full article

Soil salinization threatens agricultural sustainability in arid zones, yet quantitative attribution of its spatiotemporal dynamics to multi-source drivers remains scarce at regional scales. To address this, we developed an explainable framework merging Sentinel-1/2, ERA5-Land, and topographic-hydrological indices with XGBoost, trained under weak supervision with proxy labels and independently validated using field-measured ECe. A 7-group, 44-feature ensemble with spatial block 5-fold cross-validation ensured robust assessment. SHapley Additive exPlanations (SHAP) quantified driver contributions and enabled a novel dominant driver zoning (DDZ) framework. Monitoring the Hexi Corridor and Tarim Basin (2017–2024) revealed contrasting trajectories: Hexi’s dynamics were primarily climate-driven (Aridity Index), whereas 19.2% of Tarim showed significant salinization along oasis–desert margins co-dominated by elevation, soil indices, and temperature. The model achieved spatial cross-validation R² values around 0.65. DDZ mapping showed climate dominance in 98.2% of Hexi compared to 76.5% in Tarim, where terrain and optical factors were more influential. The weak supervision strategy overcomes scarce in-situ measurements, while the DDZ maps identified that Land-use-dominated zones recorded the highest salinity, offering clear directives for targeted salinity control in arid basins. Full article

To better capture ecological quality under aerosol pollution stress, an AOD-integrated Remote Sensing Ecological Index (ARSEI) was developed for the Shenyang Metropolitan Area (2000–2025). Using Google Earth Engine, multi-source MODIS products were compiled to generate an annual growing-season ARSEI through PCA, combining PC1 and PC2 by variance-weighted contributions. Long-term trends were assessed with Theil–Sen slope estimation and the Mann–Kendall test, future persistence with the Hurst index, and drivers with an optimal parameter geographical detector. ARSEI closely matched conventional RSEI in multi-year pixel means (R² = 0.98, p < 0.001) but identified larger “poor” (+0.4%) and “moderate” (+3.4%) areas from 2000 to 2025, indicating higher sensitivity to pollution-related stress. Ecological quality improved overall, with high grades in eastern mountainous forests and low grades in the central built-up core and surrounding croplands. Improvement was dominant (31.08% significant, 38.27% slight), while degradation was limited (4.27% significant, 13.92% slight) and concentrated in peri-urban expansion belts. Elevation was the strongest natural control, whereas land use and population were the leading socioeconomic drivers with increasing influence over time. Finally, we delineated differentiated management zones based on current status and projected trajectories to support targeted regional governance. Full article

Lake Vrana on Cres Island (northern Adriatic Sea) is a rare hydrogeological system consisting of a large freshwater body located within a karst cryptodepression with its bottom below sea level and surface above it. This study investigates long-term hydroclimatological changes using daily records of lake water level (1978–2024), water temperature (1979–2024), precipitation, and air temperature (1981–2024). Linear regression, the Mann–Kendall trend test, Sen’s slope estimator, and day-to-day variability metrics were applied to quantify long-term trends and system responses. A multi-index approach was used to enable a robust assessment of drought dynamics in this unique karst system: the Standardized Precipitation Index (SPI), representing meteorological conditions based on precipitation; the Standardized Hydrological Index (SHI), reflecting hydrological response derived from lake levels; and the New Drought Index (NDI), integrating precipitation and temperature to account for evapotranspiration effects. Results indicate a statistically significant decline in lake water levels (−4.5 to −5.2 cm yr⁻¹), while precipitation shows no significant trend. In contrast, both air and water temperatures exhibit a significant increase (~0.5 °C per decade) and are strongly correlated (R² = 0.767). The lake demonstrates pronounced thermal inertia and delayed response to atmospheric forcing. Day-to-day analysis reveals increasing variability in water temperature and decreasing variability in air temperature, suggesting changes in system energy dynamics. Drought indices (SHI and NDI) show significant negative trends, whereas SPI does not, indicating that drought intensification is primarily driven by rising temperatures and enhanced evapotranspiration rather than precipitation deficits. These findings demonstrate that Lake Vrana acts as a sensitive integrator of climatic forcing. Full article

Background/Objectives: The optimal timing of asymptomatic congenital pulmonary airway malformations (CPAM) is controversial. Early resection may reduce inflammation and scarring secondary to respiratory infections, but contemporary practice patterns are unknown. This study assesses trends in operative timing and approach over the past decade. Methods: A retrospective review was performed of 1934 CPAM patients in NSQIP-P undergoing resection (2012–2021). Trends in surgical approach and age at resection were assessed using Mann–Kendall tests. Multivariable logistic and linear regression were used to model the influence of age at operation on operative length, postoperative complications, and postoperative length of stay. Results: Thoracoscopic approach increased from 47.2% in 2012 to 80.8% in 2021 (p < 0.001). Median age at operation was 7.7 months. There was a downtrend in the open approach in patients ≤3 months old (tau = −0.511, p < 0.05) without a corresponding increase in VATS approach (tau = −0.11, p = 0.72). Instead, there was a statistically significant uptrend in all other age cohorts >3 months old in the VATS approach. After adjusting for confounders there was no difference in complication rates between age cohorts. Conclusions: Adoption of thoracoscopic resection for CPAM has substantially increased. Despite the reported benefits of earlier resection, the timing of surgical resection remains variable with most surgeries still occurring after six months of age. Additionally, the decline in open surgeries in patients ≤3 months may reflect a preference towards the VATS approach in a slightly older infant population. Further research is necessary to determine optimal timing for CPAM resection. Full article

This study comprehensively analyzed the compounded effects of climatic factors and non-climatic factors on vegetation dynamics in the northern Shaanxi Loess Plateau region in China. The objective was to provide robust scientific insights and a solid theoretical framework to support the long-term stability and sustainable development of the local ecosystem. The temperature vegetation dryness index was used to improve the water stress factor of the CASA model, so as to estimate the NPP of vegetation on the Loess Plateau of northern Shaanxi from 2000 to 2020. The temporal and spatial change characteristics of vegetation NPP and its relationship with climatic factors were analyzed using the coefficient of variation, the Mann–Kendall test of significance, and second-order partial correlation analysis. The partial derivative residual trend method was used to isolate the specific impacts of climatic factors and non-climatic factors on vegetation NPP. The results indicate the following: (1) The vegetation NPP shows a notable upward trend, with an annual growth rate of 9.4195 gC·m⁻²·a⁻¹ and a long-term average of 269.71 gC·m⁻², with the spatial distribution showing markedly high south, low north, and latitudinal zonation characteristics. (2) Vegetation NPP exhibits positive correlations with temperature, precipitation, and solar radiation. Among these factors, precipitation shows the strongest correlation with variations in vegetation NPP. (3) Non-climatic factors are the main factor affecting vegetation NPP across most parts of the study area, which is greater than the effect of selected climatic factors, and human activities may be the key component within non-climatic factors. Full article