Annual Precipitation Research Articles

Shifting cold regions streamflow regimes in North America affect flood frequency analysis

ABSTRACT Over threshold flood events in seventy years of data from 202 reference hydrometric stations in Canada and the United States were separated into nival, mixed, and pluvial flood types. While Mann-Kendall trend tests showed few significant trends in flood magnitude, significant changes in flood type fraction were found over time, with annual mean temperature, and with annual precipitation. Nival events decreased in frequency over the seventy-year period in 16% of sites, while mixed and pluvial events increased (5%, 12%). These changes indicate a shift from nival events towards more pluvial dominated systems. Fewer significant changes in flood type fraction were found with analysis against four climate indices. Flood frequency analysis using a combined distribution approach with the three flood types resulted in larger magnitude design flow estimates (median increase of 20 – 30 %) in comparison with the results from considering the data to be a single population.

Water Quality Changes in the Xingkai (Khanka) Lake, Northeast China, Driven by Climate Change and Human Activities: Insights from Published Data (1990–2020)

Water quality degradation and eutrophication of lakes are global ecological and environmental concerns, especially shallow lakes. This study collected hydrochemical data from 2935 samples of the Chinese part of Xingkai (Khanka) Lake, based on 40 published papers spanning the period from 2001 to 2023. Using the water quality index (WQI), improved geo-accumulation index (Igeo), and redundancy analysis (RDA), we analyzed the overall contamination characteristics of the water environment in Xingkai Lake. Additionally, we explored the impact of climate change and human activities on the lake’s water quality. The results showed that the annual WQI for Xingkai Lake ranged from 47.3 to 72, with a general downward trend, indicating improving water quality. Notably, the average WQI in May and total nitrogen (TN) content decreased significantly, signaling further improvement in water quality. The average concentration of TN in sediments was 1401.3 mg/kg, reflecting mild contamination. The Igeo values for the heavy metals Hg and Cr were greater than 1, indicating moderate contamination, while the Igeo values for Cd and Pb were between 0 and 1, which is in the range of uncontaminated to moderately contaminated. Land use and climate change (average annual temperature and annual precipitation) were key factors influencing water quality, with cumulative explanatory ratios of 67.3% and 50.1%. This study utilized land-use change as a metric for human activities, highlighting the potential impacts of climate change and human activities on the water quality of Xingkai Lake. It offers vital insights for the sustainable management of Xingkai Lake and provides valuable references into the management of similar transboundary lakes.

Macro- and micro-geographic genetic variation in early fitness traits in populations of maritime pine (Pinus pinaster Ait.).

Assessing adaptive genetic variation and its spatial distribution is crucial to conserve forest genetic resources and manage species' adaptive potential. Macro-environmental gradients commonly exert divergent selective pressures that enhance adaptive genetic divergence among populations. Steep micro-environmental variation might also result in adaptive divergence at finer spatial scales, even under high gene flow, but it is unclear how often this is the case. Here, we assess genetic variation in early fitness traits among distant and nearby maritime pine (Pinus pinaster Ait.) populations, to investigate climatic factors associated with trait divergence, and to examine trait integration during seedling establishment. Open pollinated seeds were collected from seven population pairs across the European species distribution, with paired populations spatially close (between <1 km up to 21 km) but environmentally divergent. Seeds were sown in semi-natural conditions at three environmentally contrasting sites, where we monitored seedling emergence, growth and survival. At large spatial scales, we found significant genetic divergence among populations in all studied traits, with certain traits exhibiting association with temperature and precipitation gradients. Significant trait divergence was also detected between pairs of nearby populations. Besides, we found consistent trait correlations across experimental sites, notably heavier seeds and earlier seedling emergence were both associated with higher seedling survival and fitness over two years in all experimental conditions. We identified mean annual temperature and precipitation seasonality as potential drivers of P. pinaster population divergence in the studied early-life traits. Populations genetically diverge also at local spatial scales, potentially suggesting that divergent natural selection can override gene flow along local-scale ecological gradients. These results suggest the species exhibits substantial adaptive potential that has allowed it to survive and evolve under contrasting environmental conditions.

Combining WetSpass and MODFLOW to assess the groundwater recharge in the agricultural highlands of Ethiopia

Estimating the temporal and spatial patterns of recharge is crucial in Jedeb Watershed, which has shallow aquifers, a proliferation of wells, and limited observations. This paper uses the WetSpass-MODFLOW coupling to evaluate the groundwater recharge in the Jedeb watershed. The ArcGIS tool is used to build grid maps that contain the input data for the WetSpass-M model. These findings are then used to simulate the hydraulic head distribution in the groundwater flow simulation program MODFLOW. WetSpass-M calculated that long-term spatial and temporal average annual precipitation of 1394 mm is distributed as 99 mm (7.1%) groundwater recharge and 722 mm (51.79%) surface runoff, while 574 mm (41.11%) is lost through evapotranspiration. In such seasonal variations, the groundwater level due to the annual stress period varied from 2164.2 to 2213.1 m. The findings contribution could serve as a benchmark for future research by researchers, policymakers, and specialists in regional water resources.

Detection of changes in local-scale statistical distribution of daily temperature and precipitation in dryland region: a case study of Ningxia, China

Identifying alterations in the local-scale statistical distributions of daily temperature indices and precipitation is crucial for adapting to climate change and combating desertification in arid regions. This study focuses on Ningxia, a representative dryland area in China, where we investigated changes in the statistical distributions of daily temperature and precipitation across ten weather stations over two 30-year periods: 1991–2020 compared to 1961–1990. From 1961 to 2020, annual air temperature indices (mean, maximum, and minimum) exhibited a significant upward trend at all ten weather stations (P < 0.05). Specifically, when comparing the decades of 1961–1970 with those of 2001–2020, annual air temperature indices increased by 1.2–2.2 °C for annual air temperatures, by 0.91–1.97 °C for maximum air temperature, and by 1.26–3.28 °C for minimum air temperature; these corresponded to rates of increase ranging from 0.20–0.40 °C per decade for mean air temperatures, from 0.15–0.33 °C per decade for maximum air temperatures, and from 0.21–0.55 °C per decade for minimum air temperatures, respectively during this period. The observed differences in the statistical distributions of daily temperature indices between the two periods were statistically significant (P < 0.05), indicating an increase rate of approximately 1 °C during the period from 1991 to 2020 relative to that from 1961 to 1990 across various weather stations. In contrast, there were no significant increasing or decreasing trends in annual precipitation (P > 0.05). Similarly, the changes in statistical distributions of daily precipitation also did not reach a significance level (P > 0.05) when comparing data from both periods within these stations. Furthermore, the correlation coefficients between daily temperature indices and daily precipitation have decreased across these stations during the later period compared to earlier years. These findings suggest that while there has been a notable shift toward higher values in the statistical distribution of daily temperature indices—indicating rising temperatures—the corresponding distribution patterns for daily precipitation have remained relatively stable between these time frames. Consequently, this research confirmed an escalation in localized drought conditions within certain dryland areas despite broader regional trends toward humidification observed over recent decades; thus implying an increased risk of desertification as aridity intensifies.

MaxEnt modeling of Klebsiella pneumoniae: predicting future distribution and evaluating the risk for public health

Klebsiella pneumoniae is a Gram-negative bacterium known for causing infections such as pneumonia, urinary tract infections, and bloodstream infections in humans. Its increasing drug resistance poses a significant threat. Understanding the effects of climate change on this bacterium is crucial to managing its impacts effectively. In this study, we employed MaxEnt modeling to explore the current and future distribution of K. pneumoniae under different climate change scenarios for 2050 and 2070. Our models utilized 280 valid occurrence points and 19 bioclimatic variables, with Mean Annual Temperature and Mean Annual Precipitation being the most influential variables. The models demonstrated high accuracy, with an AUC of 0.889. Our findings revealed that K. pneumoniae has a cosmopolitan distribution, with the highest suitability observed in Southeastern Asia, Central Africa, and Southern Europe. Future predictions indicated an apparent expansion of its range across almost all continents, particularly in the RCP 8.5 2070 scenario. Results have crucial implications for epidemiology, as they enable the identification of current and potential future disease hotspots and geographical patterns. This knowledge can inform the development of effective infection control strategies. Furthermore, it provides valuable insights for decision-makers and policymakers in allocating resources efficiently for medical control and prevention strategies.

Increased precipitation has not enhanced the carbon sequestration of afforestation in Northwest China

Concerns have been raised about the sustainability of large-scale afforestation in semi-arid regions due to potential water constraints. This study investigated whether increased humidity in the semi-arid regions of northwest China could sustain the continued expansion of afforestation efforts. Using multi-source remote sensing data, we found that between 2012 to 2020, annual cumulative precipitation increased by 2.5 millimeters per year, while annual average carbon sequestration in afforested areas declined by 0.002 kilograms of carbon per square meter per year, indicating asynchronous trends. This disparity was primarily attributed to the trade-off between vegetation photosynthesis and transpiration in response to external water conditions, which led to a decline in the water use efficiency of afforested vegetation. The effect of water use efficiency on carbon sequestration was driven by gross primary productivity, rather than evapotranspiration. These findings underscore the importance of targeted afforestation in semi-arid regions, considering local water resource sustainability.

Aerosol size distribution properties associated with cold-air outbreaks in the Norwegian Arctic

Abstract. The aerosol particles serving as cloud condensation and ice nuclei contribute to key cloud processes associated with cold-air outbreak (CAO) events but are poorly constrained in climate models due to sparse observations. Here we retrieve aerosol number size distribution modes from measurements at Andenes, Norway, during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) and at Zeppelin Observatory, approximately 1000 km upwind from Andenes at Svalbard. During CAO events at Andenes, the sea-spray-mode number concentration is correlated with strong over-ocean winds with a mean of 8±4 cm−3 that is 71 % higher than during non-CAO conditions. Additionally, during CAO events at Andenes, the mean Hoppel minimum diameter is 6 nm smaller than during non-CAO conditions, though the estimated supersaturation is lower, and the mean number concentration of particles that likely activated in-cloud is 109±61 cm−3 with no statistically significant difference from the non-CAO mean of 99±66 cm−3. For CAO trajectories between Zeppelin Observatory and Andenes, the upwind-to-downwind change in number concentration is the largest for the accumulation mode with a mean decrease of 93±95 cm−3, likely attributable primarily to precipitation scavenging. These characteristic properties of aerosol number size distributions during CAO events provide guidance for evaluating CAO aerosol–cloud interaction processes in models.

Revealing the optimal strategy for tree plantations on controlling soil erosion in China: A meta-analysis

Tree plantation has increased globally, driven by a desire to supply multiple ecosystem services including soil erosion control. However, how to plant trees can more effectively mitigate soil erosion still lacks systematic investigation. Therefore, we conducted a meta-analysis consisting of 412 paired observations from 80 studies to rigorously compare the effects of tree plantations on soil erosion control across different plantation approaches in China. The results showed that plantation age and ground cover type were the primary factors influencing the efficiency of tree plantations on runoff and sediment reduction. Mature plantations (>20 years) showed more efficiency in runoff (80.9 %) and sediment (97.2 %) reduction than young plantations (<10 years). The benefit of tree plantations with grass cover on runoff reduction was 70 %, while the capacity of plantations without ground cover was not significant. In addition, tree plantations in areas with steep slope, low mean annual precipitation, high soil sand content, and low soil organic carbon had better benefits on soil erosion control. Loess Plateau and Karst areas suffer the most severe water erosion in China, with distinct environmental conditions. This paper further revealed the targeted plantation strategy for these two regions: tree plantations in Karst areas should focus on the lithophyticity and drought tolerance of tree species, in the Loess Plateau should consider the trade-off between water consumption and soil erosion control.

Hydraulic traits exert greater limitations on tree-level maximum sap flux density than photosynthetic ability: Global evidence

Transpiration is a key process that couples the land-atmosphere exchange of water and carbon, and its maximum water transport ability affects plant productivity. Functional traits significantly influence the maximum transpiration rate; however, which factor plays the dominant role remains unknown. SAPFLUXNET dataset, which includes sap flux density of diverse species worldwide, provides fundamental data to test the importance of photosynthetic and hydraulic traits on maximum tree-level sap flux density (Js_max). Here, we investigated variations in Js_max of 2194 trees across 129 species using data from the SAPFLUXNET dataset, and analysed the relationship of Js_max with photosynthetic and hydraulic traits. Our results indicated that Js_max was positively correlated with photosynthetic traits at both leaf and tree level. Regarding hydraulic traits, Js_max was positively related to xylem hydraulic conductivity (Ks), leaf-specific hydraulic conductivity (Kl), xylem pressure inducing 50 % loss of hydraulic conductivity (P50), xylem vessel diameter (Vdia), and leaf-to-sapwood area ratio (AlAs). Random forest model showed that 87 % of the variability in Js_max can be explained by functional traits, and hydraulic traits (e.g., P50 and sapwood area, As) exerted larger effects on Js_max than photosynthetic traits. Moreover, trees with a lower sapwood area or depth could increase their sap flux density to compensate for the reduced whole-tree transpiration. Js_max of the angiosperms was significantly higher than that of the gymnosperms. Mean annual total precipitation (MAP) were positively related to Js_max with a weak correlation coefficient. Furthermore, Js_max showed a significant phylogenetic signal with Blomberg's K below 0.2. Overall, tree species with acquisitive resource economics or more efficient hydraulic systems show higher water transport capacity, and the efficiency of xylem hydraulic system rather than the demand for carbon uptake predominantly determines water transport capacity.

Shift from legacy to emerging per- and polyfluoroalkyl substances for watershed management along the coast of China

Per- and polyfluoroalkyl substances and their short-chain alternatives have attracted world-wide attention due to their widespread presence and persistence in the environment. However, the sources, environmental fate, and driving forces of PFAS in coastal ecosystems remain poorly understood. In this study, the spatial distribution, source apportionment, and driving mechanisms of PFAS were investigated through a comprehensive analysis of water samples collected along the China's coastline. The concentrations of Σ25PFAS in water samples followed a general pattern, with higher levels observed in northern coastal zones of China than the south, ranging from 0.72 to 1872.21 ng L−1. PFOA and PFBA were dominant. Emerging short-chain PFAS, such as PFBS, PFBA, F-53B and GenX, were frequently detected, with detection rates of 97%, 99%, 95% and 77%, respectively. This indicated a shift in coastal PFAS contamination from legacy compounds to emerging short-chain alternatives. Source apportionment using the Positive Matrix Factorization model identified key contributors to PFAS pollution, including textile production, volatile precursors, precious metal industries, aqueous film-forming foam, metal-plating, electrochemical fluorination, and fluoropolymer manufacturing. Additionally, PFAS concentrations were significantly positively correlated with cultivated land, urban area, and wastewater discharge, while negatively correlated with annual precipitation and woodland coverage (p < 0.05). Socio-economic development was identified as a major driver of PFAS emissions, while the hydrological factors and vegetation coverage can significantly enhance watershed resilience against PFAS pollution.

Precipitation, solar radiation, and their interaction modify leaf hydraulic efficiency-safety trade-off across angiosperms at the global scale.

In theory, there is a trade-off between hydraulic efficiency and safety. However, the strength and direction of this trade-off at the leaf level are not consistent across studies, and habitat climate may impact this trade-off. We compiled a leaf hydraulic efficiency and safety dataset for 362 species from 81 sites world-wide, with 280 paired observations of both traits, and tested whether climate was associated with departure from the proposed trade-off. The leaf hydraulic efficiency-safety trade-off was weak (R2 = 0.144) at the global scale. Mean annual precipitation and solar radiation (SR) modified the trade-off. Species from dry and high SR habitats (e.g. desert and tropical savanna) were generally located above the trade-off line, indicating that these species tended to have higher leaf hydraulic safety and efficiency than species from wet habitats with low SR (e.g. subtropical monsoon forest and montane rainforest), which were located below the trade-off line. Leaves with high vein density, dry leaf mass per area, and osmotic regulation enhanced safety without compromising hydraulic efficiency. Variation in the hydraulic efficiency-safety trade-off at the leaf level likely facilitates plant survival in specific habitats and allows for a more nuanced view of leaf hydraulic adaption strategies at the global scale.

The temporal distribution of endophytic and exophytic insect guilds responds to host plant phenology in the Brazilian Savannah

Abstract Niche theory predicts high specialisation in species‐rich environments such as neotropics, where plant‐herbivore interactions are ubiquitous in all terrestrial systems. However, there is much to be explored on how different insect guilds respond to plant phenology in these specialised environments. Using a Fabaceae‐herbivore community as an ecological model, we evaluated how plant phenology affects the abundance and shapes the temporal distribution of exophytic (folivore chewers) and endophytic (seed chewers) insects. We tested the specialisation hypothesis, predicting insect species on only one or a few host plants, with a seasonal pattern of occurrence, many rare and few abundant species. Additionally, we analysed the relationship between plant phenology and environmental factors (temperature and precipitation). We conducted fieldwork with five species and 97 individuals of Fabaceae in Brazilian Savannah and performed an insect‐rearing study in the laboratory. We found an immediately synchronised relationship between endophytic insects and plant phenology in the dry season, whereas exophytic were throughout the year. Only six species from the exophytic guild, out of a total of 87 species for both guilds, fed on more than one host plant, showing a specialised network. Endophytic herbivores are more abundant, ephemeral and predictable than exophytic ones. We also found a negative relationship between fruiting and precipitation and a positive relationship between new leaves and temperature and precipitation. Our study shows that the temporal distribution of insect‐herbivore guilds responds to plant phenology. In a scenario of global warming with effects on the annual precipitation, endophytic insects are most vulnerable to local extinction due to temporal changes in plant phenology than the exophytic ones.

A decade of rain exclusion in a Mediterranean forest reveals trade-offs of leaf chemical defenses and drought legacy effects

Increasing aridity in the Mediterranean region will result in longer and recurrent drought. These changes could strongly modify plant defenses, endangering tree survival. We investigate the response of chemical defenses from central and specialized metabolism in Quercus pubescens Willd. to future Mediterranean drought using a long-term drought experiment in natura where trees have been submitted to amplified drought (~ –30% annual precipitation) since April 2012. We focused on leaf metabolites including chlorophylls and carotenoids (central metabolism) and flavonols (specialized metabolism). Measurements were performed in summer from 2016 to 2022. Amplified drought led to higher concentrations of total photosynthetic pigments over the 2016–2022 period. However, it also led to lower AZ/VAZ and flavonol concentrations. Additionally, chemical defenses of Q. pubescens responded to previous precipitation where low precipitation 1 year and/or 2 years preceding sampling was associated to low concentrations of VAZ, flavonol and high neoxanthin concentrations. Our study indicates that the decline of flavonol concentration under long-term drought is counterbalanced by a higher production of several central metabolites. Such results are potentially due to an adjustment in tree metabolism, highlighting the importance of performing long-term experimental studies in natura for assessing drought legacy effects and thus forest adaptation to climate change.

Assessment of the long-term hydrological performance of a green roof system in stormwater control

Green roof systems (GRs) are effective tools for urban stormwater management. However, there is limited documentation of the long-term hydrological performance of GRs to support decision-making. This study evaluated long-term field monitoring records (7 years) from a 12-year-old GR, situated in a Moist Subtropical Mid-Latitude Climate, to analyze seasonality in and evolution of hydrological performance. The monitoring system was built within a pan lysimeter buried under substrate layers matching the surrounding GR. The monitoring results highlight the efficacy of this GR in long-term stormwater runoff control. The GR can retain 87% of the annual precipitation and return 54% of the precipitation to the atmosphere through evapotranspiration (ET) and sustain long-term event-based mean runoff volume reductions, peak flow reductions, and flow delays of 82%, 93%, and 4.3 h, respectively. The initial moisture content prior to events was highly correlated with hydrological performance, with a seasonal mean Spearman correlation coefficient of 0.47, suggesting the potential of enhancing ET from the GR to improve performance. Substrate water holding capacity increased over time, but no obvious changes in water retention performance were observed. These monitoring results from the aging GR demonstrate the effectiveness of GR systems for long-term stormwater management.

Climate Change Effects on Spatiotemporal Distribution of Precipitation over West Central India: A Statistical Downscaling Approach

The long-term shifts in temperatures and weather patterns are referred to as climate change. Climate change not only leads to long-term shifts in average temperatures but also changes in the spatial and temporal distribution of rainfall over continents. This study aims to predict likely changes in the rainfall pattern induced by climate change over the West Central (WC) region of India. The approach uses a statistical downscaling technique that converts coarse-scale outputs of the global climate model (GCM) to high-resolution future precipitation projections giving refined distribution. The decision support tool that uses a robust statistical downscaling technique viz. statistical downscaling model (SDSM) is used for assessing local climate change impacts. The research includes the study of likely regional climate variability, by integrating historical observational data and empirical relationships between large-scale climate variables and local weather patterns. Historical data and the SDSM, version 4.2, are employed to forecast future rainfall trends. Rainfall data from the India Meteorological Department and the National Centre for Environmental Prediction (NCEP) from 1961 to 2001 are used along with outputs from general circulation models (GCMs), viz. Hadley Centre coupled model, version 3 (HadCM3), and coupled global climate model, version 3 (CGCM3), for the period 1961–2099. Rainfall scenarios are presented for three future time periods (2011–2040, 2041–2070, and 2071–2099). The study indicates a significant increase in the mean annual precipitation across the West Central India region, particularly in the 2050s and 2080s. Mean annual rainfall is projected to rise by 10–19.4% under HadCM3 A2 and B2 scenarios. The HadCM3 indicates the month of September as the month of the highest precipitation in later time periods, whereas it is the month of August, according to CGCM3 simulations. When comparing the results of the two models, HadCM3 gives better results, as indicated by better R2 value in validation. Thus, the analysis gives climate change-induced likely changes in the spatiotemporal distribution of precipitation over the West Central India region. The insight given by the work will be useful for decision making in many sectors like agriculture, water management, disaster risk reduction, and infrastructure planning.

Studies on Heavy Precipitation in Portugal: A Systematic Review

This systematic review, based on an adaptation of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement from 2020, focuses on studies of the atmospheric mechanisms underlying extreme precipitation events in mainland Portugal, as well as observed trends and projections. The 54 selected articles cover the period from 2000 to 2024, in which the most used keywords are “portugal” and “extreme precipitation”. Of the 54, 23 analyse trends and climate projections of precipitation events, confirming a decrease in total annual precipitation, especially in autumn and spring, accompanied by an increase in the frequency and intensity of extreme precipitation events in autumn, spring and winter. Several articles (twelve) analyse the relationship between synoptic-scale circulation and heavy precipitation, using an atmospheric circulation types approach. Others (two) establish the link with teleconnection patterns, namely the North Atlantic Oscillation (NAO), and still others (three) explore the role of atmospheric rivers. Additionally, five articles focus on evaluating databases and Numerical Weather Prediction (NWP) models, and nine articles focus on precipitation-related extreme weather events, such as tornadoes, hail and lightning activity. Despite significant advances in the study of extreme precipitation events in Portugal, there is still a lack of studies on hourly or sub-hourly scales, which is critical to understanding mesoscale, short-lived events. Several studies show NWP models still have limitations in simulating extreme precipitation events, especially in complex orography areas. Therefore, a better understanding of such events is fundamental to promoting continuous improvements in operational weather forecasting and contributing to more reliable forecasts of such events in the future.

Sewage sludge as soil amendment in arid soils - A trace metal, nutrient and trace organics perspective

Sewage sludge management has emerged as a critical environmental challenge due to the large volumes generated globally. Valorization techniques, including energy production and agricultural applications, offer sustainable solutions, particularly in regions with low soil fertility. The sewage sludge utilization in the Middle East region is low. This paper presents a pragmatic risk-based assessment using the risk-based corrective action approach to evaluate sludge application in desert soils. This methodology focuses on the source-pathway-receptor interaction and assesses the likelihood of contaminants posing a real threat. In arid desert regions like Kuwait, where soil organic content and moisture are extremely low, the application of sewage sludge presents a feasible option to enhance soil quality and valorize unutilized sludge dumps which pose significant environmental concerns but are left to desiccate in the absence of any environmental regulation towards its utilization and due to religious apprehensions. Since the sludge characterization is not well detailed a brief review of the available data was included to establish the bounds of various organic, metal and nutrients that were used for generating the model. This study examines the changes in the physico-chemical properties of desert soils following sludge application, focusing on the likely fate of trace metals and organic contaminants. The alkaline desert soils of Kuwait, with a pH range of 7.7–8.9, are particularly suitable for sludge application due to the low mobility of metals in alkaline conditions. Additionally, sludge application lowers soil pH, improving conditions for plant growth. The region's deeper water table and scant annual precipitation (<0.15 m) further reduce the risk of groundwater contamination and deeper soil profile contamination. The presence of organic content, nitrates, Zn, and Cu in sludge can promote native vegetation growth. However, trace organic contaminants, including PAHs, PCBs, and pharmaceuticals, pose a potential risk to soil contamination, but since the geological section shows intervening impervious layers the contamination is going to be localized, even if there is sufficient leachable fraction. Given the minimal risk of contamination under the unique conditions of arid regions, this approach highlights the potential for eco-friendly sludge valorization, that will improve vegetation cover and arrest the suspended particulate suspension. However, before the large-scale implementation of this modelled concept, a detailed experimental study on the pilot scale or lysimeters is recommended to assess the long-term impacts of sludge application and to obtain data that can inform policy guidelines for sustainable sludge management in desert environments.

Analyzing the Spatiotemporal Changes in Climatic Extremes in Cold and Mountainous Environment: Insights from the Himalayan Mountains of Pakistan

This study assessed the past changes in extreme precipitation and temperature events across the Himalayan Mountains of Pakistan. This cold and mountainous environmental region has witnessed a significant increase in climate-related disasters over the past few decades. Spatiotemporal changes in extreme temperature and precipitation events were analyzed using 24 indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this study, in situ data of 16 national meteorological stations were obtained from the Pakistan Meteorological Department (PMD) for the past three decades (1991–2020). The significance of the trends was assessed using the modified Mann–Kendall (MMK) test, and the Theil–Sen (TS) slope estimator was used to estimate the slope of the trend. The results showed that there has been a consistent decline in the total precipitation amount across the Himalayan Mountains of Pakistan. The trend exhibited a decrease in the annual average precipitation at a rate of −6.56 mm/year. Simultaneously, there was an increasing trend in the annual average minimum and maximum temperatures at rates of 0.02 °C/year and 0.07 °C/year, respectively. The frequencies of consecutive wet days (CWDs) and maximum 5-day precipitation (RX5day) have decreased significantly, with decreasing rates of −0.40 days/year and −1.18 mm/year, respectively. The amount of precipitation during very wet days (R95p) and extremely wet days was decreased by −19.20 and −13.60 mm/decade, respectively. The warm spell duration (WSDI) and the frequency of warm days (TX90p) across the Himalayan Range both increased by 1.5 and 1.4 days/decade. The number of cold days (TX10p) and cold nights (TN10p) decreased by 2.9 and 3.4 days/decade. The average temperature of the hottest nights (TXn) and the diurnal temperature range (DTR) were increased by 0.10 and 0.30 °C/decade. The results indicated an increasing tendency of dry and warm weather in the Himalayan region of Pakistan, which could have adverse consequences for water resources, agriculture, and disaster management in the country. Therefore, it is essential to prioritize the implementation of localized adaptation techniques in order to enhance sustainable climate resilience and effectively address the emerging climate challenges faced by these mountainous regions.

Climate Predicts NDVI Better Than Plant Functional Group Attributes Along a Latitudinal Gradient in Nunavik

ABSTRACTAimThis study aims to describe the latitudinal pattern in plant functional groups' (PFGs') biomass and cover in Nunavik to test whether PFG attributes are better Normalized Difference Vegetation Index (NDVI) predictors than climate.LocationThe study spans a 700‐km latitudinal gradient from the lichen woodland to prostrate shrub tundra vegetation zones across Nunavik, Canada.TaxonOur analysis focuses on the following PFGs: erect and prostrate shrubs, herbaceous plants, bryophytes, and lichens.MethodsBiomass and cover data of the different PFGs were sampled in 40 sites distributed across the latitudinal gradient. NDVI data were obtained through remote sensing, while climatic, permafrost depth, and surficial deposits were derived from various databases. The PFG models were built to explore relationships between average NDVI (2016–2020) at the sampling site and ecological attributes such as PFG biomass or cover but also other variables such as surficial deposits and permafrost depth. A second series of models, the climatic models, were built using only climatic variables such as seasonal temperature and precipitation.ResultsThe most parsimonious PFG model was built with the biomass data of erect shrubs, herbaceous plants, bryophytes, and lichens and included surficial deposits and permafrost depth (R2 = 0.74). This biomass model performed better than the most parsimonious cover model (cover of erect shrubs and herbaceous, surficial deposits, permafrost depth; R2 = 0.63). However, the most parsimonious climatic model (fall temperature, annual, and winter precipitations) exhibited superior predictive power compared to the ecological ones (R2 = 0.87).ConclusionsPFG models built with PFGs aboveground biomass or cover are good predictors of NDVI of the plant formations sampled along the latitudinal gradient in Nunavik. Despite the intrinsic association between NDVI and vegetation attributes, our study emphasizes the importance of the regional climate in the control of primary productivity in Arctic and subarctic ecosystems. This study provides new insights into the interpretation of NDVI data and enhances our understanding of Arctic vegetation responses under rapid climate change. Furthermore, it underscores the balance between climatic drivers and ecological dynamics in shaping fragile Arctic ecosystems.