Search Results (100)

Rivers play a crucial role in the hydrological cycle and serve as essential freshwater resources for both human populations and ecosystems. Climate change significantly alters precipitation patterns and river discharge variability. However, the impact of precipitation patterns (rainfall and snowfall) and air temperature on river discharge in coastal zones remains inadequately understood. This study focused on Toyama Prefecture, located along the Sea of Japan, as a representative coastal area. We analyzed over 30 years of datasets, including air temperature, precipitation, snowfall, and river discharge, to assess the effects of climate change on river discharge. Trends in hydroclimatic datasets were assessed using the rescaled adjusted partial sums (RAPS) method and the Mann–Kendall (MK) non-parametric test. Furthermore, a correlation analysis and the Structural Equation Model (SEM) were applied to construct a relationship between precipitation, temperature, and river discharge. Our findings indicated a significant increase in air temperature at a rate of 0.2 °C per decade, with notable warming observed in late winter (January and February) and early spring (March). The average river fluxes for the Jinzu, Oyabe, Kurobe, Shou, and Joganji rivers were 182.52 m³/s, 60.37 m³/s, 41.40 m³/s, 38.33 m³/s, and 18.72 m³/s, respectively. The tipping point for snowfall decline occurred in 1992, marked by an obvious decrease in snowfall depth. The SEM showed that, although rainfall dominated the changes in river discharge (loading = 0.94), the transition from solid (snow) to liquid (rain) precipitation may alter the river discharge regime. The percentage of flood occurrence increased from 19% (1940–1992) to 41% (1993–2020). These changes highlight the urgent need to raise awareness about the impacts of climate change on river floods and freshwater resources in global coastal regions. Full article

Detection and analysis of hydroclimatic trends are crucial for quantifying climate change, global warming, and their potential impacts. This study investigates hydroclimatic trends over the South African Sugar Belt (SASB) under a changing climate using nonparametric and innovative trend detection techniques for the periods 1980–2022, 2025–2050, and 2050–2080. Statistical tests, including the original and modified Mann–Kendall test, sequential Mann–Kendall test, and Innovative Trend Analysis were performed to detect trends and changes in hydroclimatic variables over the SASB’s dryland and irrigated regions. An 18-month low-pass filter was applied to 19 GCMs of the CMIP6, which were downscaled to a local setting. The results indicate contrasting rainfall trends: a positive trend in the dryland region and a negative trend in the irrigated region from 1980 to 2022. Under low- (SSP2–4.5) and high-emission (SSP5–8.5) scenarios, both regions exhibited a significant drying trend from 1980 to 2080, with the irrigated region drying and warming faster than the dryland region. Mann–Kendall tests and Innovative Trend Analysis revealed robust positive trends in surface air temperatures across the SASB, with even stronger trends projected for the future, potentially promoting water loss in the area. Compound dry–hot events were also projected to cause significant socioeconomic impacts in the near and distant future. Future studies can explore nonparametric and monotonic trend detection and analysis for water quality parameters in the SASB under a changing climate. Full article

The objective of this study was to analyse the influence of two large-scale climate indices on precipitation in the Danube basin, both separately and in combination. The evolution of the hydroclimatic regime in this area is of particular importance but has received limited attention. One of the indices for these data is the well-known the North Atlantic Oscillation (NAOI) climate index, which has been used in numerous investigations; the aim of using this index is to determine its influence on various hydroclimatic variables in many regions of the globe. The other index, the Greenland–Balkan Oscillation index (GBOI), has been demonstrated to have a greater influence on various hydroclimatic variables in Southeastern Europe compared to the NAOI. First, through different bivariate methods, such as estimating wavelet total coherence (WTC) in the time–frequency domain and applying partial wavelet coherence (PWC), the performance of the GBOI contributing to precipitation in the Danube basin was compared with that of the NAOI in the winter season. Then, by using relatively simple multivariate methods such as multiple linear regression (MLR) and a variant thereof called ridge regression (RR), notable results were obtained regarding the prediction of overall precipitation in the Danube basin in the winter season. The training period was 90 years (1901–1990), and the testing period was 30 years (1991–2020). The used Nash–Sutcliffe (NS) performance criterion varied between 0.65 and 0.94, depending on the preprocessing approach applied for the input data, proving that statistical modelling for the winter season is both simple and powerful compared to modern deep learning methods. Full article

Fire-driven land cover change has generated a paradox: while habitat fragmentation from agriculture, livestock, and urban expansion has reduced natural fire occurrences, human-induced ignitions have increased wildfire frequency and intensity. In northern Colombia’s Magdalena Department, most of the territory faces moderate to high wildfire risk, especially during recurrent dry seasons and periods of below-average precipitation. However, knowledge of wildfire spatiotemporal occurrence and its drivers remains scarce. This work addresses this gap by identifying fire-prone zones and analyzing the influence of climate and vegetation in the Magdalena Department. Fire-prone zones were identified using the Getis–Ord Gi* method over fire density and burned area data from 2001 to 2023; then, they were analyzed with seasonally aggregated hydroclimatic indices via logistic regression to quantify their influence on wildfires. Vegetation susceptibility was assessed using geostatistics, obtaining land cover types most affected by fire and their degree of fragmentation. Fire-prone zones in the Magdalena Department covered ~744.35 km² (3.21%), with a weak but significant (τ = 0.20, p < 0.01) degree of coincidence between classification based on fire density, as pre-fire variable, and burned area, as a post-fire variable. Temporally, fire probability increased during the dry season, driven by short-lagged precursors such as Dry Spell Length and precipitation from the preceding wet season. Fire-prone zones were dominated by pastures (62.39%), grasslands and shrublands (19.61%) and forests (15.74%), and exhibited larger, more complex high-risk patches, despite similar spatial connectedness with non-fire-prone zones. These findings enhance wildfire vulnerability understanding, contributing to risk-based territorial planning. Full article

Background: The Amazon region possesses vast natural and anthropogenic ecosystems within a hydroclimatic environment conducive to the proliferation of arboviruses associated with infectious diseases in the human population, notably dengue fever, which poses a recurrent and significant public health challenge. Objective and Methods: We wished to update the dengue mapping for the state of Pará (eastern Amazon) using municipality-level secondary data between 2010 and 2024, including epidemiological information. Furthermore, the seasonal effects of soil and atmospheric meteorological variables (ERA5 reanalysis) on the annual municipal incidence of dengue were statistically analyzed through correlation and cluster-based regression methods. Results: Dengue mapping identified key areas over the central, southwest, and southeast parts of Pará, with eleven municipalities exhibiting extreme dengue counts exceeding 300 cases per 100,000 inhabitants. The epidemiological profile in these cities with worsening transmission showed a higher incidence in adults aged 20–39 years old (39%) and a predominance among women (54%). The majority of dengue cases occur during the rainy season (January to May), accounting for 69% of annual cases, when the climate conditions maximize vector proliferation. The statistical analyses highlighted the significant and spatially heterogeneous influence of regional climate variables on the dengue transmission cycle. Conclusions: This study advances our understanding of climatic drivers of dengue in the Amazon and provides relevant evidence to support region-specific surveillance and control strategies. Full article

Diffuse agricultural pollution is a leading contributor to surface water degradation, particularly in regions undergoing rapid land use change and agricultural intensification. In many developing countries, conventional assessment approaches fall short of capturing the spatial complexity and cumulative nature of multiple environmental drivers that influence surface water vulnerability. This study addresses this gap by introducing the Integral Index of Vulnerability to Diffuse Contamination (IIVDC), a spatially explicit, multi-criteria framework that combines the Analytical Hierarchy Process (AHP) with Geographic Information Systems (GIS). The IIVDC integrates six key indicators—slope, soil erodibility, land use, runoff potential, hydrological connectivity, and observed water quality—weighted through expert elicitation and mapped at high spatial resolution. The methodology was applied to the Guachal River watershed in Valle del Cauca, Colombia, where agricultural pressures are pronounced. Results indicate that 33.0% of the watershed exhibits high vulnerability and 4.3% very high vulnerability, with critical zones aligned with steep slopes, limited vegetation cover, and strong hydrological connectivity to cultivated areas. By accounting for both biophysical attributes and pollutant transport pathways, the IIVDC offers a replicable tool for prioritizing land management interventions. Beyond its technical application, the IIVDC contributes to sustainability by enabling evidence-based decision-making for water resource protection and land use planning. It supports integrated, spatially targeted actions that can reduce long-term contamination risks, guide sustainable agricultural practices, and improve institutional capacity for watershed governance. The approach is particularly suited for contexts where data are limited but spatial planning is essential. Future refinement should consider dynamic water quality monitoring and validation across contrasting hydro-climatic regions to enhance transferability. Full article

How can the shape of biodiversity inform us about cities’ ecoclimatic fitness and guide their development? Can we use species as the harbingers of climatic extremes? Eco-climatically sensitive species carry information about hydroclimatic change in their distribution, fitness, and preferential gradients of habitat suitability. Conversely, environmental features outside of the species’ fitness convey information on potential ecological anomalies in response to extremes to adapt or mitigate, such as through urban parks. Here, to quantify ecosystems’ fitness, we propose a novel computational model to extract multivariate functional ecological networks and their basins, which carry the distributed signature of the compounding hydroclimatic pressures on sentinel species. Specifically, we consider butterflies and their habitat suitability (HS) to infer maximum suitability gradients that are meaningful of potential species networks and flows, with the smallest hydroclimatic resistance across urban landscapes. These flows are compared to the distribution of urban parks to identify parks’ ecological attractiveness, actual and potential connectivity, and park potential to reduce hydroclimatic impacts. The ecosystem fitness index (EFI) is novelly introduced by combining HS and the divergence of the relative species abundance (RSA) from the optimal log-normal Preston plot. In Shenzhen, as a case study, eco-flow networks are found to be spatially very extended, scale-free, and clustering for low HS gradient and EFI areas, where large water bodies act as sources of ecological corridors draining into urban parks. Conversely, parks with higher HS, HS gradients, and EFIs have small-world connectivity non-overlapping with hydrological networks. Diverging patterns of abundance and richness are inferred as increasing and decreasing with HS. HS is largely determined by temperature and precipitation of the coldest quarter and seasonality, which are critical hydrologic variables. Interestingly, a U-shape pattern is found between abundance and diversity, similar to the one in natural ecosystems. Additionally, both abundance and richness are mildly associated with park area according to a power function, unrelated to longitude but linked to the degree of urbanization or park centrality, counterintuitively. The Preston plot’s richness–abundance and abundance-rank patterns were verified to reflect the stationarity or ecological meta-equilibrium with the environment, where both are a reflection of community connectivity. Ecological fitness is grounded on the ecohydrological structure and flows where maximum HS gradients are indicative of the largest eco-changes like climate-driven species flows. These flows, as distributed stress-response functions, inform about the collective eco-fitness of communities, like parks in cities. Flow-based networks can serve as blueprints for designing ecotones that regulate key ecosystem functions, such as temperature and evapotranspiration, while generating cascading ecological benefits across scales. The proposed model, novelly infers HS eco-networks and calculates the EFI, is adaptable to diverse sensitive species and environmental layers, offering a robust tool for precise ecosystem assessment and design. Full article

As global warming continues, extremes in key climate parameters will become more frequent. These extremes are one of the main challenges for the sustainability of cities. The aim of this study is to provide a better understanding of the evolution of extremes in precipitation (pcp) and maximum (Tmax) and minimum (Tmin) temperatures in Grand-Nokoué to improve the resilience of the region. To this end, historical daily precipitation and maximum (Tmax) and minimum (Tmin) temperature data from the Cotonou synoptic station were used from 1991 to 2020. First, the extreme events identified using the 99th percentile threshold were used to analyze their annual and monthly frequency. Secondly, a Generalized Extreme Value (GEV) distribution was fitted to the annual maxima with a 95% confidence interval to determine the magnitude of the specific return periods. The parameters of this distribution were estimated using the method of L moments, considering non-stationarity. The results of the study showed significant upward trends in annual precipitation and minimum temperatures, with p-values of 0.04 and 0.001, respectively. Over the past decade, the number of extreme precipitation and Tmin events has exceeded the expected number. The model provides greater confidence for periods ≤ 50 years. Extreme values of three-day accumulations up to 68.21 mm for pcp, 79.38 °C for Tmin and 97.29 °C for Tmax are expected every two years. The results of this study can be used to monitor hydroclimatic hazards in the region. Full article

Severe hydroclimatic events affect ecosystems and human livelihoods, creating significant challenges for managing water resources. This study analyzed the rainfall and river flow trends in the Bani River Basin (BRB) from 1991 to 2020. Using indices such as the maximum rainfall over a one-day period (RX1DAY), maximum rainfall over a five-day period (RX5DAY), rainfall exceeding the 95th percentile (R95P), simple daily precipitation intensity (SDII), and peak discharge (Qmax), the modified Mann–Kendall test and Pettitt’s test were applied to assess the trends and identify potential breakpoints. The results revealed spatial variability, with southern regions showing reduced rainfall, while northeastern areas exhibit increasing extreme rainfall and river flow. The RX5DAY declined significantly after 2000, reflecting reductions in prolonged rainfall events, followed by the RX1DAY, which declined significantly after 2012, indicating a reduction in short-duration extremes. In contrast, the R99P, SDII, and Qmax exhibited positive trends, indicating intensifying rainfall intensity and extremes in discharge. A notable breakpoint was detected in 1993, marking a transition to increased extreme flows. The highest values of the rainfall indices (R95P, R99P, RX1DAY, RX5DAY, SDII) were concentrated in the southern part of the basin, while the north recorded lower values. These results highlight the basin’s vulnerability to climate variability and provide insights into hydroclimatic changes, serving as a basis for informed decision-making and future research. Full article

Rewetting of drained wetlands is practiced as a method to enhance biodiversity, improve water and nutrient retention, and counteract climate change. While rewetting efforts are most commonly directed toward various types of wetlands, there are relatively few reports on the restoration of lakes drained in the past. The Olsztyn Lake District is a region where extensive, organized drainage works were carried out in the 19th century, leading to the disappearance of numerous lakes. This paper examines the changes that have occurred since the early 19th century in a group of 143 lakes identified as the complete set of fully drained lakes in the region. An analysis of cartographic materials revealed that the total area of these lakes, originally about 3000 hectares, was reduced to nearly zero by the early 20th century. However, a gradual restoration of the former lakes is now being observed, primarily as a result of spontaneous processes but also through planned interventions. The study of water quality and trophic status in 25 fully restored lakes revealed that such water bodies typically exhibit unfavorable conditions, primarily due to excessive phosphorus levels. A similar state was observed in 14 examined wetlands, which were partially rewetted. In the absence of organized restoration programs in the study region, the slow trend of passive rewetting of such water bodies is expected to continue. However, this process may be hindered by adverse hydroclimatic changes associated with ongoing climate warming. Full article

Understanding the historical groundwater recharge process and its influencing factors is crucial for effectively managing regional groundwater resources amidst future climate change. However, the availability of high-resolution hydroclimate archives remains severely limited. In this study, we used a 59 m chloride profile within the unsaturated loess zone to reconstruct the potential groundwater recharge (PGR) records spanning 273 years in a near-humid area on the Loess Plateau. Spectral analysis was employed to identify the principal influencing factors on PGR across various time scales. The reconstructed hydrological records revealed three wet periods and four dry periods from 1745 to 2007 AD, with PGR rates ranging from 66.7 to 222.4 mm yr⁻¹ during wet periods and 20.0 to 66.7 mm yr⁻¹ during dry periods. In addition, spectral analysis indicated multiple cycles, ranging from 2.1 to 50.0 years, within the PGR history. Temperature, precipitation, and sunspot activity emerged as the key factors governing the rate of PGR over the 3-year, 7-year, and 11-year time scales, respectively, highlighting the combined influence of solar activity and climate on the PGR process. These findings enhance our understanding of groundwater recharge and environmental climate dynamics in the near-humid loess unsaturated zone and other regions exhibiting similar hydroclimatic conditions. Full article

The prevalence of endoparasites associated with chaetognath abundance in the coastal waters of the Mexican Central Pacific was studied fortnightly from November 2010 to December 2011. A total of 35 (0.21%) out of 16,407 chaetognaths were found to be parasitized. Five out of twelve chaetognath species (Flaccisagitta enflata, F. hexaptera, Parasagitta euneritica, Serratosagitta pacifica, Zonosagitta bedoti) were found to be parasitized by nine endoparasitic taxa: Protists (two morphotypes), digenean metacercariae [Didymozoidae, Hemiuridae, Parahemiurus sp., Lepocreadiidae, Prosorhynchus sp. (Bucephalidae)], and cestodes (metacestodes) [Tetraphyllidea (two morphotypes)]. Parasagitta. euneritica and Z. bedoti were the most abundant chaetognath species, and Protist sp. 2 and Tetraphyllidea sp. 1 were the most abundant parasites. The highest prevalence for most of the endoparasite species occurred in June, and the values varied according to three hydroclimatic periods: stratified (S), semi-mixed (SM), and mixed (M). Eight non-infected chaetognath species, two parasitized chaetognaths (F. enflata and S. pacifica), and two parasites (Protist sp. 1 and Tetraphyllidea sp. 2) were associated with warm temperatures (S and SM periods); in contrast, P. euneritica, Z. bedoti, parasitized F. hexaptera, and the parasite Tetraphyllidea sp. 1 showed a strong local preference for cooler temperatures, high productivity, and high biomass conditions (M periods). We discovered the occurrence of the digenean Prosorhynchus sp. (Bucephalidae) parasitizing the chaetognath P. euneritica, and this is the first report of Prosorhynchus parasitizing chaetognaths worldwide. We also confirmed the presence of Lepocrediidae (metacercariae larval stage) infecting F. hexaptera, a parasite that had only been recorded infecting other chaetognaths of the Atlantic Ocean. The parasite diversity affecting the chaetognath populations of the Central Mexican Pacific coast likely differs between the offshore, outer slope areas, and the surveyed coastal system. Full article

Knowledge regarding the growth of trees is essential to understanding their response to predicted warmer and drier climate scenarios. We used the annual rings of three Mexican pines (Pinus montezumae Lamb., Pinus oocarpa Schiede ex Schltdl., and Pinus monophylla Torr. & Frém) to explore their drought responses. Correlation analyses showed that hydroclimatic factors differentially impact tree species in terms of the intensity and temporality. The negative influence of the maximum temperature and positive effect of the precipitation on the growth indices were notable, with P. montezumae being the most responsive species, followed by P. oocarpa and P. monophylla. The climate–growth relationships were specific and driven by the differential hydrothermal conditions across the study areas. SPEI analyses indicated that P. monophylla is better able to tolerate drought than P. montezumae or P. oocarpa, especially in recent years. The lower resilience of P. montezumae and P. oocarpa could predispose them to a higher mortality risk if warming and drying rates increase. Our findings strengthen the understanding of the responses of tree growth to seasonal drought, which is critical considering the biogeographic shifts that will potentially be experienced by these forests in the future. This knowledge improves the understanding of young Mexican stands and could contribute to the design of management strategies in the face of predicted climatic variations. Full article

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen’s slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson’s correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day⁻¹10a⁻¹. Other climate variables increased at different rates: SM at 0.02 mmday⁻¹10a⁻¹, E at 0.03 mm day⁻¹10a⁻¹, Ep at 0.02 mm day⁻¹ 10a⁻¹, TMIN and TMAX at 0.01 °C day⁻¹10a⁻¹. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions. Full article

The climate in the source region of the Yangtze River, Yellow River, and Mekong River is of great research interest because of its sensitivity to global change and its importance in regulating water resources to densely populated and vast areas downstream. A five-century long record of spring (May–June) for the Palmer Drought Severity Index (PDSI) was reconstructed for this region using tree-ring width chronologies of Qilian juniper (Juniperus przewalskii Kom.) from five high-elevation sites. The reconstruction explained 46% variance in the PDSI during the instrumental period 1955–2005. The reconstructed PDSI showed that the occurrence of dry extremes became frequent during the last century relative to the previous four centuries. The standard deviation of the reconstructed PDSI in the 100-year window showed that the recent century held apparent high values of standard deviation in the long-term context. Sustained droughts occurred in periods 1582–1631, 1737–1757, 1772–1791, 1869–1891, 1916–1939, and 1952–1982, whereas relatively wet intervals were observed in 1505–1527, 1543–1564, 1712–1736, 1792–1816, 1852–1868, 1892–1915, and 1983–2008. Notably, in the context of the past five centuries, the study region showed an increased inter-annual variability in the recent century, suggesting an intensified hydroclimatic activity possibly associated with global warming. Moreover, through diagnostic analysis of atmospheric circulation, we found that the negative phase East Asian–Pacific teleconnection pattern may be likely to trigger drought in the study region. Full article