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Search Results (1,145)

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19 pages, 2239 KB  
Article
Assessment of Satellite Precipitation Products in an Andean Catchment: Ambato River Basin, Ecuador
by Pablo Arechúa-Mazón, César Cisneros-Vaca, Julia Calahorrano-González and Mery Manzano-Cepeda
Hydrology 2025, 12(9), 225; https://doi.org/10.3390/hydrology12090225 - 28 Aug 2025
Viewed by 172
Abstract
Accurate precipitation data are essential for hydrological planning in mountainous regions with sparse opportunities for observation, such as the Ambato River basin in Ecuador. In this study, CHIRPS and IMERG satellite precipitation products were compared against six automatic rain gauges from 2014 to [...] Read more.
Accurate precipitation data are essential for hydrological planning in mountainous regions with sparse opportunities for observation, such as the Ambato River basin in Ecuador. In this study, CHIRPS and IMERG satellite precipitation products were compared against six automatic rain gauges from 2014 to 2023, using both categorical metrics (to assess daily rainfall detection skill) and continuous validation (to evaluate rainfall amount), complemented by bias decomposition and spatiotemporal analysis. Our results show that IMERG demonstrated higher skill in detecting daily rainfall, while CHIRPS delivered a more stable performance during dry conditions, with fewer false alarms. Both products capture the main seasonal precipitation patterns but differ in bias behavior: CHIRPS tends to under-estimate daily rainfall less, whereas IMERG provides more reliable volumetric estimates overall. These findings suggest that IMERG may be best suited for flood risk and hydrological modelling, while CHIRPS could be preferred for drought monitoring and climatological studies in Andean catchments. Full article
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25 pages, 15090 KB  
Article
Climate Change Effects on Precipitation and Streamflow in the Mediterranean Region
by Abdulkadir Baycan, Osman Sonmez and Gamze Tuncer Evcil
Water 2025, 17(17), 2556; https://doi.org/10.3390/w17172556 - 28 Aug 2025
Viewed by 256
Abstract
This study investigates the impact of climate change on the Mudurnu Stream Basin in northwest Türkiye by analyzing climate parameters in the Mediterranean region. Historical data from EC-Earth2, HadGEM2-ES, and MPI-ESM-MR GCMs from the CMIP5 Euro-CORDEX archive were assessed, and future precipitation and [...] Read more.
This study investigates the impact of climate change on the Mudurnu Stream Basin in northwest Türkiye by analyzing climate parameters in the Mediterranean region. Historical data from EC-Earth2, HadGEM2-ES, and MPI-ESM-MR GCMs from the CMIP5 Euro-CORDEX archive were assessed, and future precipitation and temperature data were derived using five statistical bias correction methods for the selected EC-Earth2 model under RCP4.5 and RCP8.5 scenarios. The SWAT model was employed to simulate future runoff amounts for the Mudurnu Stream Basin. The findings reveal notable changes in precipitation and temperature. The annual and seasonal variations of total precipitation and average, maximum, and minimum temperatures for the RCP4.5 and RCP8.5 scenarios in the Sakarya and Mudurnu regions were analyzed and determined. The projections for future river flow indicate a significant increase in precipitation during the rainy seasons. The Mudurnu Stream mainstem will experience an increase in flow of between 70 and 140% under RCP4.5 and between 80 and 160% under RCP8.5. In the Dinsiz Stream tributary, a 32–55% increase is observed for the spring and summer months. In this context, the rainfall and runoff projections required for the estimation of potential drought and flood risks in the near and distant future were calculated. Full article
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21 pages, 4720 KB  
Article
Infestation and Larval Habitat Ecology of Aedes aegypti and Aedes albopictus in an Urban Gradient in Vassouras, Rio de Janeiro, Brazil
by Gilliarde de Carvalho Caetano, Samanta Cristina das Chagas Xavier and Mariana Rocha David
Insects 2025, 16(8), 869; https://doi.org/10.3390/insects16080869 - 21 Aug 2025
Viewed by 501
Abstract
Since there are no available vaccines against some arboviruses, vector control is the most effective way to reduce their incidence. In this context, mechanical control is one of the most cost-effective ways to suppress Aedes populations, but it requires knowledge about vector breeding [...] Read more.
Since there are no available vaccines against some arboviruses, vector control is the most effective way to reduce their incidence. In this context, mechanical control is one of the most cost-effective ways to suppress Aedes populations, but it requires knowledge about vector breeding ecology in varied landscapes and climates. Here we investigated the infestation levels and container types used as larval habitats by Aedes aegypti and Aedes albopictus in an urban gradient of Vassouras, a countryside city in Rio de Janeiro. Larval surveys were conducted bimonthly from January 2017 to December 2018. Infestation was measured through the House (HI) and Breteau indexes (BI). Container types found with Aedes spp. immatures were correlated with temperature and rainfall and were compared between urbanization zones. The distribution of positive containers was mapped. The HI for Ae. aegypti increased during rainy seasons, but the HI and BI were always <1% for both mosquito vectors. More reservoirs were found harboring Ae. albopictus than Ae. aegypti, but in general their relative distribution into types was similar between species. On the other hand, the amount and distribution of containers into types varied across urbanization zones. Finally, the spatial distribution of larval habitats was similar between species, as well as often constant between seasons and study years. Full article
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18 pages, 4034 KB  
Article
Effects of Irrigation Practices on Potato Yield and Water Productivity: A Global Meta-Analysis
by Yining Niu, Linlin Wang, Zhuzhu Luo, Setor Kwami Fudjoe, Jairo A. Palta, Lingling Li and Shiqing Li
Agronomy 2025, 15(8), 1942; https://doi.org/10.3390/agronomy15081942 - 12 Aug 2025
Viewed by 617
Abstract
The efficiency of water use in irrigated agriculture is a global priority to address water scarcity. A comprehensive meta-analysis was conducted to evaluate the effects of irrigation practices on potato yield, crop evapotranspiration (ETc), water productivity (WP), and irrigation water productivity (IWP) across [...] Read more.
The efficiency of water use in irrigated agriculture is a global priority to address water scarcity. A comprehensive meta-analysis was conducted to evaluate the effects of irrigation practices on potato yield, crop evapotranspiration (ETc), water productivity (WP), and irrigation water productivity (IWP) across diverse growing conditions, including soil texture, fertilizer application rates, annual precipitation, and soil organic carbon (SOC). The results revealed that supplementary irrigation increased potato yield by 55% and ETc by 39% while maintaining WP comparable to non-irrigated conditions. The greatest yield and WP improvements from supplementary irrigation occurred under drip irrigation with moderate N, P, and K application rates (150–250 kg ha−1) and irrigation amounts below 150 mm. This practice was particularly effective in sandy soils with 1.5–2.0% SOC and annual rainfall of 200–400 mm. Conversely, deficit irrigation reduced potato yield and ETc by 25% and 24%, respectively, but significantly enhanced WP and IWP by 9% and 28% compared to full irrigation. When a water-saving ratio of 10–20% was implemented under drip irrigation with optimal fertilizer rates (240–360 kg N ha−1, >104 kg P2O5 ha−1, 150–200 kg K2O ha−1), deficit irrigation improved WP without yield loss in sandy soils with annual rainfall of 600–800 mm when compared to full irrigation. The IWP increased with rising SOC levels, indicating that SOC improvement in low-carbon soils enhances water productivity in irrigated potato systems. These findings demonstrate that tailored irrigation strategies can simultaneously reduce water inputs and achieve higher yield and WP in potato production systems. Full article
(This article belongs to the Section Water Use and Irrigation)
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18 pages, 1861 KB  
Article
Clay Nanomaterials Sorbents for Cleaner Water: A Sustainable Application for the Mining Industry
by María Molina-Fernández, Albert Santos Silva, Rodrigo Prado Feitosa, Edson C. Silva-Filho, Josy A. Osajima, Santiago Medina-Carrasco and María del Mar Orta Cuevas
Nanomaterials 2025, 15(15), 1211; https://doi.org/10.3390/nano15151211 - 7 Aug 2025
Viewed by 546
Abstract
The increasing shortage of drinking water, driven by reduced rainfall and the intensification of industrial and agricultural activities, has raised justified concerns about the quantity and quality of available water resources. These sectors not only demand high water consumption but also discharge large [...] Read more.
The increasing shortage of drinking water, driven by reduced rainfall and the intensification of industrial and agricultural activities, has raised justified concerns about the quantity and quality of available water resources. These sectors not only demand high water consumption but also discharge large amounts of toxic substances such as organic matter, metal ions and inorganic anions, posing risks to both public health and the environment. This study evaluated the effectiveness of clay-based nanomaterials in the treatment of contaminated industrial wastewater from the mining sector. The materials tested included montmorillonite, high-loading expandable synthetic mica, and their organically functionalized forms (MMT, Mica-Na-4, C18-MMT, and C18-Mica-4). The experimental results show that these clays had minimal impact on the pH of the water, while a notable decrease in the chemical oxygen demand (COD) was observed. Ion chromatography indicated an increase in nitrogen and sulfur compounds with higher oxidation states. Inductively coupled plasma analysis revealed a significant reduction in the calcium concentration and an increase in the sodium concentration, likely due to cation exchange mechanisms. However, the removal of copper and iron was ineffective, possibly due to competitive interactions with other cations in the solution. Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) confirmed the structural modifications and interlayer spacing changes in the clay materials upon exposure to contaminated water. These findings demonstrate the potential of clay minerals as effective and low-cost materials for the remediation of industrial wastewater. Full article
(This article belongs to the Special Issue Eco-Friendly Nanomaterials: Innovations in Sustainable Applications)
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23 pages, 28189 KB  
Article
Landslide Susceptibility Prediction Using GIS, Analytical Hierarchy Process, and Artificial Neural Network in North-Western Tunisia
by Manel Mersni, Dhekra Souissi, Adnen Amiri, Abdelaziz Sebei, Mohamed Hédi Inoubli and Hans-Balder Havenith
Geosciences 2025, 15(8), 297; https://doi.org/10.3390/geosciences15080297 - 3 Aug 2025
Viewed by 1261
Abstract
Landslide susceptibility modelling represents an efficient approach to enhance disaster management and mitigation strategies. The focus of this paper lies in the development of a landslide susceptibility evaluation in northwestern Tunisia using the Analytical Hierarchy Process (AHP) and Artificial Neural Network (ANN) approaches. [...] Read more.
Landslide susceptibility modelling represents an efficient approach to enhance disaster management and mitigation strategies. The focus of this paper lies in the development of a landslide susceptibility evaluation in northwestern Tunisia using the Analytical Hierarchy Process (AHP) and Artificial Neural Network (ANN) approaches. The used database covers 286 landslides, including ten landslide factor maps: rainfall, slope, aspect, topographic roughness index, lithology, land use and land cover, distance from streams, drainage density, lineament density, and distance from roads. The AHP and ANN approaches were applied to classify the factors by analyzing the correlation relationship between landslide distribution and the significance of associated factors. The Landslide Susceptibility Index result reveals five susceptible zones organized from very low to very high risk, where the zones with the highest risks are associated with the combination of extreme amounts of rainfall and steep slope. The performance of the models was confirmed utilizing the area under the Relative Operating Characteristic (ROC) curves. The computed ROC curve (AUC) values (0.720 for ANN and 0.651 for AHP) convey the advantage of the ANN method compared to the AHP method. The overlay of the landslide inventory data locations of historical landslides and susceptibility maps shows the concordance of the results, which is in favor of the established model reliability. Full article
(This article belongs to the Section Natural Hazards)
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23 pages, 10868 KB  
Article
Quantitative Analysis and Nonlinear Response of Vegetation Dynamic to Driving Factors in Arid and Semi-Arid Regions of China
by Shihao Liu, Dazhi Yang, Xuyang Zhang and Fangtian Liu
Land 2025, 14(8), 1575; https://doi.org/10.3390/land14081575 - 1 Aug 2025
Viewed by 524
Abstract
Vegetation dynamics are complexly influenced by multiple factors such as climate, human activities, and topography. In recent years, the frequency, intensity, and diversity of human activities have increased, placing substantial pressure on the growth of vegetation. Arid and semi-arid regions are particularly sensitive [...] Read more.
Vegetation dynamics are complexly influenced by multiple factors such as climate, human activities, and topography. In recent years, the frequency, intensity, and diversity of human activities have increased, placing substantial pressure on the growth of vegetation. Arid and semi-arid regions are particularly sensitive to climate change, and climate change and large-scale ecological restoration have led to significant changes in the dynamic of dryland vegetation. However, few studies have explored the nonlinear relationships between these factors and vegetation dynamic. In this study, we integrated trend analysis (using the Mann–Kendall test and Theil–Sen estimation) and machine learning algorithms (XGBoost-SHAP model) based on long time-series remote sensing data from 2001 to 2020 to quantify the nonlinear response patterns and threshold effects of bioclimatic variables, topographic features, soil attributes, and anthropogenic factors on vegetation dynamic. The results revealed the following key findings: (1) The kNDVI in the study area showed an overall significant increasing trend (p < 0.01) during the observation period, of which 26.7% of the area showed a significant increase. (2) The water content index (Bio 23, 19.6%), the change in land use (15.2%), multi-year average precipitation (pre, 15.0%), population density (13.2%), and rainfall seasonality (Bio 15, 10.9%) were the key factors driving the dynamic change of vegetation, with the combined contribution of natural factors amounting to 64.3%. (3) Among the topographic factors, altitude had a more significant effect on vegetation dynamics, with higher altitude regions less likely to experience vegetation greening. Both natural and anthropogenic factors exhibited nonlinear responses and interactive effects, contributing to the observed dynamic trends. This study provides valuable insights into the driving mechanisms behind the condition of vegetation in arid and semi-arid regions of China and, by extension, in other arid regions globally. Full article
(This article belongs to the Section Land Use, Impact Assessment and Sustainability)
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13 pages, 6786 KB  
Article
Hydropower Microgeneration in Detention Basins: A Case Study of Santa Lúcia Basin in Brazil
by Azuri Sofia Gally Koroll, Rodrigo Perdigão Gomes Bezerra, André Ferreira Rodrigues, Bruno Melo Brentan, Joaquín Izquierdo and Gustavo Meirelles
Water 2025, 17(15), 2219; https://doi.org/10.3390/w17152219 - 24 Jul 2025
Viewed by 600
Abstract
Flood control infrastructure is essential for the development of cities and the population’s well-being. The goal is to protect human and economic resources by reducing the inundation area and controlling the flood level and peak discharges. Detention basins can do this by storing [...] Read more.
Flood control infrastructure is essential for the development of cities and the population’s well-being. The goal is to protect human and economic resources by reducing the inundation area and controlling the flood level and peak discharges. Detention basins can do this by storing a large volume of water to be released after the peak discharge. By doing this, a large amount of energy is stored, which can be recovered via micro-hydropower. In addition, as the release flow is controlled and almost constant, Pumps as Turbines (PAT) could be a feasible and economic option in these cases. Thus, this study investigates the feasibility of micro-hydropower (MHP) in urban detention basins, using the Santa Lúcia detention basin in Belo Horizonte as a case study. The methodology involved hydrological modeling, hydraulic analysis, and economic and environmental assessment. The results demonstrated that PAT selection has a crucial role in the feasibility of the MHP, and exploiting rainfall with lower intensities but higher frequencies is more attractive. Using multiple PATs with different operating points also showed promising results in improving energy production. In addition to the economic benefits, the MHP in the detention basin produces minimal environmental impact and, as it exploits a wasted energy source, it also reduces the carbon footprint in the urban water cycle. Full article
(This article belongs to the Special Issue Research Status of Operation and Management of Hydropower Station)
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19 pages, 3205 KB  
Article
A Climatology of Errors in HREF MCS Precipitation Objects
by William A. Gallus, Anna Duhachek, Kristie J. Franz and Tyreek Frazier
Water 2025, 17(15), 2168; https://doi.org/10.3390/w17152168 - 22 Jul 2025
Viewed by 330
Abstract
Numerical weather prediction of warm season rainfall remains challenging and skill at achieving this is often much lower than during the cold season. Prior studies have shown that displacement errors play a large role in the poor skill of these forecasts, but less [...] Read more.
Numerical weather prediction of warm season rainfall remains challenging and skill at achieving this is often much lower than during the cold season. Prior studies have shown that displacement errors play a large role in the poor skill of these forecasts, but less is known about how such errors compare to other sources of error, particularly within forecasts from convection-allowing ensembles. The present study uses the Method for Object-based Diagnostic Evaluation to develop a climatology of errors for precipitation objects from High-Resolution Ensemble Forecasting forecasts for mesoscale convective systems during the warm seasons from 2018 to 2023 in the United States. It is found that displacement errors in all ensemble members are generally not systematic, and on average are between 100 and 150 km. Errors are somewhat smaller in September, possibly reflecting increased forcing from synoptic-scale systems. Although most ensemble members have a negative error for the 10th percentile of rainfall intensity, the error becomes positive for heavier amounts. However, the total system rainfall is less than that observed for all members except the 12 UTC NAM. This is likely due to the negative errors for area that are present in all models, except again in the 12 UTC NAM. Full article
(This article belongs to the Special Issue Analysis of Extreme Precipitation Under Climate Change)
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22 pages, 10354 KB  
Article
Leaching Characteristics of Exogenous Cl in Rain-Fed Potato Fields and Residual Estimation Model Validation
by Jiaqi Li, Jingyi Li, Hao Sun, Xin Li, Lei Sun and Wei Li
Plants 2025, 14(14), 2171; https://doi.org/10.3390/plants14142171 - 14 Jul 2025
Viewed by 363
Abstract
Potato (Solanum tuberosum L.) is a chlorine-sensitive crop. When soil Cl concentrations exceed optimal thresholds, the yield and quality of potatoes are limited. Consequently, chloride-containing fertilizers are rarely used in actual agricultural production. Therefore, two years of field experiments under natural [...] Read more.
Potato (Solanum tuberosum L.) is a chlorine-sensitive crop. When soil Cl concentrations exceed optimal thresholds, the yield and quality of potatoes are limited. Consequently, chloride-containing fertilizers are rarely used in actual agricultural production. Therefore, two years of field experiments under natural rainfall regimes with three chlorine application levels (37.5 kg ha−1/20 mg kg−1, 75 kg ha−1/40 mg kg−1, and 112.5 kg ha−1/60 mg kg−1) were conducted to investigate the leaching characteristics of Cl in field soils with two typical textures for Northeast China (loam and sandy loam soils). In this study, the reliability of Cl residual estimation models across different soil types was evaluated, providing critical references for safe chlorine-containing fertilizer application in rain-fed potato production systems in Northeast China. The results indicated that the leaching efficiency of Cl was significantly positively correlated with both the rainfall amount and the chlorine application rate (p < 0.01). The Cl migration rate in sandy loam soil was significantly greater than that in loam soil. However, the influence of soil texture on the Cl leaching efficiency was only observed at lower rainfall levels. When the rainfall level exceeded 270 mm, the Cl content in all the soil layers became independent of the rainfall amount, soil texture, and chlorine application rate. Under rain-fed conditions, KCl application at 80–250 kg ha−1 did not induce Cl accumulation in the primary potato root zone (15–30 cm), suggesting a low risk of toxicity. In loam soil, the safe application range for KCl was determined to be 115–164 kg ha−1, while in sandy loam soil, the safe KCl application range was 214–237 kg ha−1. Furthermore, a predictive model for estimating Cl residuals in loam and sandy loam soils was validated on the basis of rainfall amount, soil clay content, and chlorine application rate. The model validation results demonstrated an exceptional goodness-of-fit between the predicted and measured values, with R2 > 0.9 and NRMSE < 0.1, providing science-based recommendations for Cl-containing fertilizer application to chlorine-sensitive crops, supporting both agronomic performance and environmental sustainability in rain-fed systems. Full article
(This article belongs to the Special Issue Fertilizer and Abiotic Stress)
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19 pages, 2465 KB  
Article
Long-Term Variations in Extreme Rainfall in Japan for Predicting the Future Trend of Rain Attenuation in Radio Communication Systems
by Yoshio Karasawa
Climate 2025, 13(7), 145; https://doi.org/10.3390/cli13070145 - 9 Jul 2025
Viewed by 1007
Abstract
Rain attenuation of radio waves with frequencies above 10 GHz causes a serious problem in wireless communications. For wireless systems design, highly accurate methods for estimating the magnitude of attenuation have long been studied. ITU-R recommends a calculation method for rain attenuation using [...] Read more.
Rain attenuation of radio waves with frequencies above 10 GHz causes a serious problem in wireless communications. For wireless systems design, highly accurate methods for estimating the magnitude of attenuation have long been studied. ITU-R recommends a calculation method for rain attenuation using R0.01, the 1 min rainfall rate that is exceeded for 0.01% of an average year. Accordingly, an R0.01 database suitable for this calculation has been constructed. In recent years, global warming has emerged as an important climatological issue. If the predicted rise in temperatures associated with global warming induces a significant effect on rainfall characteristics, the existing R0.01 database will need to be revised. However, there is currently no information for quantitatively evaluating the likely long-term change in R0.01. In our previous study, the long-term trend in annual maximum values for 1-day, 1 h, and 10 min rainfall in Japan was estimated from a large amount of meteorological data and a 95% confidence interval approach was used to identify an increasing trend of more than 10% over approximately 100 years. In this paper, we investigate the long-term trend in greater detail using non-linear approximations for three types of rainfall and adopt the Akaike Information Criterion to determine the optimal order of the non-linear approximation. The future trend of R0.01 is then estimated based on the long-term change in annual maximum 1 h rainfall, exploiting the strong correlation between long-term average annual maximum 1 h rainfall and R0.01. Full article
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15 pages, 2700 KB  
Article
Rainfall-Driven Nitrogen Dynamics in Catchment Ponds: Comparing Forest, Paddy Field, and Orchard Systems
by Mengdie Jiang, Yue Luo, Hengbin Xiao, Peng Xu, Ronggui Hu and Ronglin Su
Agriculture 2025, 15(14), 1459; https://doi.org/10.3390/agriculture15141459 - 8 Jul 2025
Viewed by 364
Abstract
The event scale method, employed for assessing changes in nitrogen (N) dynamics pre- and post-rain, provides insights into its transport to surface water systems. However, the relationships between N discharge in catchments dominated by different land uses and water quality remain unclear. This [...] Read more.
The event scale method, employed for assessing changes in nitrogen (N) dynamics pre- and post-rain, provides insights into its transport to surface water systems. However, the relationships between N discharge in catchments dominated by different land uses and water quality remain unclear. This study quantified variations in key N components in ponds across forest, paddy field, and orchard catchments before and after six rainfall events. The results showed that nitrate (NO3-N) was the main N component in the ponds. Post-rainfall, N concentrations increased, with ammonium (NH4+-N) and particulate nitrogen (PN) exhibiting significant elevations in agricultural ponds. Orchard catchments contributed the highest N load to the ponds, while forest catchments contributed the lowest. Following a heavy rainstorm event, total nitrogen (TN) loads in the ponds within forest, paddy field, and orchard catchments reached 6.68, 20.93, and 34.62 kg/ha, respectively. These loads were approximately three times higher than those observed after heavy rain events. The partial least squares structural equation model (PLS-SEM) identified that rainfall amount and changes in water volume were the dominant factors influencing N dynamics. Furthermore, the greater slopes of forest and orchard catchments promoted more N loss to the ponds post-rain. In paddy field catchments, larger catchment areas were associated with decreased N flux into the ponds, while larger pond surface areas minimized the variability in N concentration after rainfall events. In orchard catchment ponds, pond area was positively correlated with N concentrations and loads. This study elucidates the effects of rainfall characteristics and catchment heterogeneity on N dynamics in surface waters, offering valuable insights for developing pollution management strategies to mitigate rainfall-induced alterations. Full article
(This article belongs to the Special Issue Soil-Improving Cropping Systems for Sustainable Crop Production)
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16 pages, 5095 KB  
Article
Analyzing the Impact of Climate Change on Compound Flooding Under Interdecadal Variations in Rainfall and Tide
by Jiun-Huei Jang, Tien-Hao Chang, Yen-Mo Wu, Ting-En Liao and Chih-Hung Hsu
Hydrology 2025, 12(7), 182; https://doi.org/10.3390/hydrology12070182 - 6 Jul 2025
Viewed by 794
Abstract
Coastal regions are increasingly threatened by compound flooding due to the increasing intensities of storm surges and rainfall under climate change. However, relevant research has been limited because significant amounts of data, scenarios, and computations are often required to evaluate long-term variations in [...] Read more.
Coastal regions are increasingly threatened by compound flooding due to the increasing intensities of storm surges and rainfall under climate change. However, relevant research has been limited because significant amounts of data, scenarios, and computations are often required to evaluate long-term variations in compound flood risk. In this study, a framework was proposed through efficient hydraulic simulations and a consequence-based statistical method using data projected under different general circulation models (GCMs). The analysis focuses on analyzing the interdecadal trends of compound flood risk for a coastal area in southwestern Taiwan across a baseline period and four future periods in the short-term (2021–2040), mid-term (2041–2060), mid-to-long-term (2061–2080), and long-term (2081–2100). Although discrepancies exist in the short term, the results show that the values of the annual maximum flood area exhibit an increasing pattern in the future for all GCMs by increasing about 27.8% on average at the end of the 21st century. This means that, under the same flood areas given in the baseline period, the return periods will decrease, and flood events will occur more frequently in the future. This framework can be extended to other regions to assess the impacts of compound flooding with different geographical and meteorological conditions. Full article
(This article belongs to the Special Issue Runoff Modelling under Climate Change)
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22 pages, 3424 KB  
Article
Did Environmental and Climatic Factors Influence the Outcome of the COVID-19 Pandemic in the Republic of Serbia?
by Milos Gostimirovic, Ljiljana Gojkovic Bukarica, Jovana Rajkovic, Igor Zivkovic, Ana Bukarica and Dusko Terzic
Healthcare 2025, 13(13), 1589; https://doi.org/10.3390/healthcare13131589 - 2 Jul 2025
Viewed by 629
Abstract
Background: The aim of the study is to determine whether environmental and climatic factors (air quality, precipitation rates, and air temperatures) alongside specific public health measures (social distancing and vaccination) have influenced total number of SARS CoV-2 positive cases (TOTAL CASES) and [...] Read more.
Background: The aim of the study is to determine whether environmental and climatic factors (air quality, precipitation rates, and air temperatures) alongside specific public health measures (social distancing and vaccination) have influenced total number of SARS CoV-2 positive cases (TOTAL CASES) and deaths (TOTAL DEATHS) from COVID-19 infection in the Republic of Serbia (RS). Method: An observational, retrospective study was conducted, covering the following three-year period in the RS: I (1 March 2020–1 March 2021); II (1 March 2021–1 March 2022); and III (1 March 2022–1 March 2023). Air quality was expressed as the values of the air quality index (AQI) and the concentrations of particulate matter 2.5 µm (PM2.5). Precipitation rates (PREC) were expressed as the average monthly amount of rainfall (mm), while average air temperatures (AIR TEMP) were expressed in °C. Data were collected from relevant official and publicly available national and international resources. Data regarding the COVID-19 pandemic were collected from the World Health Organization. Results: No differences between the periods were observed for the average values of AIR TEMP (11.2–12.2 °C), PREC (56.1–66.8 mm), and AQI (57.2–58.8), while the average values of PM2.5 significantly decreased in the III period (21.2 compared to 25.2, p = 0.03). Both TOTAL CASES and TOTAL DEATHS from COVID-19 infection showed positive correlation with the AQI and PM2.5 and a negative correlation with the AIR TEMP. The correlation coefficient was strongest between TOTAL DEATHS and the AIR TEMP in the II period (r = −0.7; p = 0.007). The extent of rainfall and vaccination rates did not affect any of the observed variables. No differences in TOTAL CASES and TOTAL DEATHS were observed between the periods of increased social measures and other months, while both statistically significantly increased during the vaccination period compared to months without the vaccination campaign (p < 0.02, for both). Conclusions: Air quality, more precisely AQI and PM2.5 and average air temperatures, but no precipitation rates, influenced the number of TOTAL CASES and TOTAL DEATHS from COVID-19 infection. These were the highest during the vaccination period, but vaccination could be considered as a confounding factor since the intensive vaccination campaign was conducted during the most severe phase of the COVID-19 pandemic. Social distancing measures did not reduce the number of TOTAL CASES or TOTAL DEATHS during the COVID-19 pandemic. Full article
(This article belongs to the Collection COVID-19: Impact on Public Health and Healthcare)
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14 pages, 2196 KB  
Article
Spatial Variability and Time Stability of Throughfall in a Moso Bamboo (Phyllostachys edulis) Forest in Jinyun Mountain, China
by Chunxia Liu, Yunqi Wang, Quanli Zong, Kai Jin, Peng Qin, Xiuzhi Zhu and Yujie Han
Atmosphere 2025, 16(7), 787; https://doi.org/10.3390/atmos16070787 - 27 Jun 2025
Viewed by 254
Abstract
Moso bamboo (Phyllostachys pubescens) is one of the most common species of bamboo in East Asia, and plays a crucial role in regulating hydrological and biogeochemical processes in forest ecosystems. However, throughfall variability and its time stability in Moso bamboo forests [...] Read more.
Moso bamboo (Phyllostachys pubescens) is one of the most common species of bamboo in East Asia, and plays a crucial role in regulating hydrological and biogeochemical processes in forest ecosystems. However, throughfall variability and its time stability in Moso bamboo forests remain unclear. Here, we investigated the spatial variability and temporal stability of throughfall in a Moso bamboo forest in China, and the effects of rainfall characteristics and leaf area index (LAI) on the variability of throughfall, and tree locations on the temporal stability of throughfall were systematically evaluated. The results show that throughfall occupied 74.3% of rainfall in the forest. The coefficient of variation of throughfall (throughfall CV) for rainfall events and throughfall collectors were 18.1% and 19.5%, respectively, and the spatial autocorrelation of the throughfall CV was not significant according to the global Moran’s I. Throughfall CV had a significantly negative correlation with rainfall amount and rainfall intensity, whereas it increased with the increase in LAI. The temporal stability plot indicated that the extreme wet and dry persistence were highly stable. We also found that normalized throughfall increased with the increase in distance from the nearest tree trunk. Our findings are expected to assist in the accurate assessment of throughfall and soil water within bamboo forests. Full article
(This article belongs to the Section Meteorology)
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