Regional Climate Change Research Articles

Spatial Mapping of Soil CO2 Flux in the Yellow River Delta Farmland of China Using Multi-Source OpticalRemote Sensing Data

The spatial prediction of soil CO2 flux is of great significance for assessing regional climate change and high-quality agricultural development. Using a single satellite to predict soil CO2 flux is limited by climatic conditions and land cover, resulting in low prediction accuracy. To this end, this study proposed a strategy of multi-source spectral satellite coordination and selected seven optical satellite remote sensing data sources (i.e., GF1-WFV, GF6-WFV, GF4-PMI, CB04-MUX, HJ2A-CCD, Sentinel 2-L2A, and Landsat 8-OLI) to extract auxiliary variables (i.e., vegetation indices and soil texture features). We developed a tree-structured Parzen estimator (TPE)-optimized extreme gradient boosting (XGBoost) model for the prediction and spatial mapping of soil CO2 flux. SHapley additive explanation (SHAP) was used to analyze the driving effects of auxiliary variables on soil CO2 flux. A scatter matrix correlation analysis showed that the distributions of auxiliary variables and soil CO2 flux were skewed, and the linear correlations between them (r < 0.2) were generally weak. Compared with single-satellite variables, the TPE-XGBoost model based on multiple-satellite variables significantly improved the prediction accuracy (RMSE = 3.23 kg C ha−1 d−1, R2 = 0.73), showing a stronger fitting ability for the spatial variability of soil CO2 flux. The spatial mapping results of soil CO2 flux based on the TPE-XGBoost model revealed that the high-flux areas were mainly concentrated in eastern and northern farmlands. The SHAP analysis revealed that PC2 and the TCARI of Sentinel 2-L2A and the TVI of HJ2A-CCD had significant positive driving effects on the prediction accuracy of soil CO2 flux. The above results indicate that the integration of multiple-satellite data can enhance the reliability and accuracy of spatial predictions of soil CO2 flux, thereby supporting regional agricultural sustainable development and climate change response strategies.

Surface carbonate dynamics in a temperate coastal system in the Northern Yellow Sea, China

The carbon sink/source in estuaries and coastal seas may have significant implications for regional climate change. This study investigated seawater carbon dioxide partial pressure (pCO2), aragonite saturation state (Ωarag), and related carbonate parameters in the Yalu River estuary and the adjacent Northern Yellow Sea, China, in September 2023. The results indicate that seawater pCO2 ranged from 261 to 1121 μatm, while Ωarag ranged from 0.49 to 3.34 in the study area. High pCO2 were observed in the estuarine and northwestern areas, whereas low pCO2 were found in the southern offshore area. In the estuarine area, high pCO2 levels were attributed to the input of diluted water from the Yalu River. In the southern areas, low pCO2 were a result of primary production, while community respiration played an important role in increasing seawater pCO2 in the northwestern area. On the other hand, seawater Ωarag was extremely low in the estuarine area, and greater than 1.5 in the southern offshore area. Ωarag in the study area was mainly controlled by water mixing and temperature. The study area acted as a source of atmospheric CO2 with an average air-sea CO2 flux of 6.2 mmol m−2d−1 in autumn, which was relatively high compared with other marginal seas. The high pCO2 and low Ωarag associated with diluted water inputs and community respiration could weaken the ability of coastal oceans to uptake CO2. Therefore, it is crucial to explore ways to reduce CO2 levels in riverine and adjacent coastal seas.

Climatic Predictors of Long‐Distance Migratory Birds Breeding Productivity Across Europe

ABSTRACTAimOngoing climate changes represent a major determinant of demographic processes in many organisms worldwide. Birds, and especially long‐distance migrants, are particularly sensitive to such changes. To better understand these impacts on long‐distance migrants' breeding productivity, we tested three hypotheses focused on (i) the shape of the relationships with different climate variables, including previously rarely tested quadratic responses, and on regional differences in these relationships predicted by (ii) mean climatic conditions and (iii) by the rate of climate change in respective regions ranging from Spain to Finland.LocationEurope.Time Period2004–2021.Major Taxa StudiedLong‐distance migratory passerine birds.MethodsWe calculated breeding productivity from constant effort ringing sites from 11 European countries covering 34° of latitude, and extracted temperature‐ and precipitation‐related climate variables from E‐OBS and NASA MODIS datasets. To test our hypotheses, we fitted GLMM and Bayesian meta‐analytic models.ResultsWe revealed hump‐shaped responses of productivity to temperature, growing degree‐days, green‐up onset date, and precipitation anomaly, and negative responses to intense and prolonged rains across the regions. The effects of March temperature and April growing degree‐days were more negative in cold than in warm regions, except for the region with the highest accumulated heat, whereas increasing June precipitation anomalies were associated with higher productivity in both dry and wet regions. Productivity responses to climate were unrelated to the rate of climate warming.Main ConclusionsThe influence of climate on bird productivity proved to be frequently nonlinear, as expected by ecological theory. The rate of climate change is less important than regional interannual variability in climate (which is predicted to increase), but this may change with the progression of climate change in the future. Productivity declines in long‐distance migratory songbirds are particularly expected if out‐of‐norm water excess increases in frequency or strength.

Interconnectivity can be as important as habitat type in explaining carbon stocks in the coastal lagoons of arid regions

Coastal blue carbon ecosystems, typically comprising interconnected habitat mosaics, are globally important pathways of carbon sequestration and play a significant role in climate change regulation and mitigation. Current coastal management strategies often rely on simplified regional carbon stock estimates, that overlook the geographical variability and intricate ecological dynamics within these ecosystems. This study adopts a seascape ecology approach to evaluate the role of multiple seascape characteristics on carbon storage in two arid region coastal lagoons. We show that seascape location is the most influential driver of carbon stocks. Additionally, carbon isotopic variability, a proxy for connectivity, can be as influential as habitat type, particularly in the UAQ lagoon. This challenges the conventional reliance on data from individual habitat types (e.g., seagrass, mangrove, or tidal marsh) and highlights the context-dependency of carbon stocks. Moreover, the specific characteristics driving carbon stocks vary between seascapes: in Khor Faridah, connectivity to seagrass and mangrove habitats is crucial, while in the UAQ lagoon, sheltered and elevated areas are more influential. Our findings suggest that the interconnectivity between different habitat types, such as mangroves and saltmarshes, significantly enhances carbon storage. This is especially pronounced in large, sheltered mangrove habitat types within upper intertidal zones. Notably, small patches of mangroves, up to 10 ha, are associated with an approximate 10 % increase in carbon stocks. These results underscore the need for a more holistic, context-specific approach to designing nature-based solutions for coastal management and ecosystem restoration. By considering the specific characteristics and connectivity of seascape mosaics, we can more effectively enhance carbon stock potential in coastal ecosystems. This study contributes to a deeper spatially explicit understanding of the complex factors influencing carbon stocks in blue carbon ecosystems, highlighting the importance of tailored management strategies that reflect the unique ecological patterns of each seascape.

Temporal accumulation and lag effects of precipitation on carbon fluxes in terrestrial ecosystems across semi-arid regions in China

Precipitation (PRE) plays a vital role in hydrological processes, ecological vegetation, and land-atmosphere interactions in semi-arid regions. Previous research has mainly focused on the impact of PRE on large-scale regional climate change and ecological evolution. However, there have been few studies on the long-term effects of PRE on carbon fluxes in these regions, especially the time-accumulation and -lag effects. Here, we employed observational data from the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) and integrated multiple data sources, including remote sensing and carbon flux simulation data, to quantitatively assess the lagged response of carbon fluxes to PRE and elucidate the underlying mechanisms from multiple perspectives. Characterization of PRE, soil water content (SWC) and carbon fluxes at SACOL qualitatively reveals the existence of a time-delayed response of carbon fluxes to PRE, both on monthly and finer daily temporal scales. The average lagged response of net ecosystem exchange (NEE) and gross primary productivity (GPP) to accumulated PRE (APRE) is approximately 42 days. When considering time-accumulation and -lag effects, the combined direct and indirect effects of APRE on NEE and GPP increase by 0.37 and 0.58, respectively. Notably, preceding APRE primarily exerts a direct effect on current carbon fluxes, whereas the impact of SWC at a depth of 0.1 m is primarily mediated through the memory effect of preceding APRE, resulting in an indirect effect on carbon fluxes. These findings emphasize the importance of preceding APRE. Significantly, our subsequent study indicates that the delay in NEE and GPP responses to APRE also extends to approximately 40 to 50 days at the regional scale. Our findings emphasize the significant time effects of APRE on carbon fluxes, and considering these effects will contribute to a better understanding of the interplay between PRE and vegetation over semi-arid regions in China.

Environmental Aspects and Impacts of Porto Seco: the Case of the Largest Dry Port in Latin America, Located in Foz do Iguaçu (Brazil)

Objective: This work aims to present and describe the process of identifying and classifying environmental aspects in a Brazilian dry port. Theoretical Framework: The Climate Change Adaptation Strategies aim to reduce greenhouse gas (GHG) emissions, increase the share of renewable energy in total energy production and increase the energy efficiency. Unfortunately, road-based dry ports increase heavy truck congestion, energy consumption and, inherently, GHG emissions. Method: The general approach includes a literature review on the importance of managing environmental aspects and impacts in dry ports, followed by the description of the holistic procedure that involves the inventory of port activities linked to environmental aspects, the Leopold matrix and specialized knowledge about the local context (e.g., compliance with law, regional climate change adaptation strategy, stakeholder concerns) to perform the classification. Results and Discussion: The results showed that atmospheric emissions, noise and resource consumption are among the most significant environmental aspects of dry port. The absence of a railway that enables a multimodal transport system and the fact that the port is located in the city center constitute a disadvantage that worsens road congestion and air emissions, since the train would reduce GHG emissions. Research Implications: The work contributes to the planning and management of the activities of Foz do Iguaçu Dry Port considering environmental aspects and impacts, direct and indirect, from a holistic perspective. Originality/Value: The work presents a ranking of the environmental aspects and impacts of dry port to help defining priority actions in light of climate change strategies.

Running to warmer-drier springs in the Greater Mekong Subregion as climate warms

Using the multivariate EOF analysis performed on the observation datasets, this study reveals that the Greater Mekong Subregion (GMS) has been toward warm-dry springs over most regions especially after the 2000s, accompanied by increased surface temperature and decreased precipitation anomalies. Such climate condition provides favourable environment for compound heat and drought events, raising questions about how the spring climate in GMS will change as climate warms. Based on a multi-model weighting scheme among CMIP6 models, we project the regional climate changes in GMS in a warmer world under the SSP5–8.5 scenario. Results show that the southern GMS including Vietnam, Laos, Thailand, and Cambodia will become warmer-drier throughout the 21st century in response to global warming. In contrast, the climate condition over the northern GMS including Myanmar and Yunnan province of Southwest China is expected to experience a transition from dry to wet springs in a warmer world, resulting in a tendency toward the warm-wet springs particularly in the long-term future. This knowledge indicates the spatial non-uniformity of regional climate under global warming and will aid in advance to plan for water management and agricultural adaptation.

Case Study on Obstacles and Implementation Paths of Shandong Energy's Green and Low-carbon Transformation

In the context of global climate change and environmental regulations, it is worth exploring in theory and practice how coal enterprises can achieve green and low-carbon transformation and maintain sustainable development. This article takes Shandong Energy in China as an example, analyzes the obstacles faced by Shandong Energy's green and low-carbon transformation, such as resource distribution, talent structure, industrial structure, and supporting policies. From the perspectives of mergers and acquisitions, industrial structure, resource reserves, intelligent mines, technological innovation, integration of industry and finance, and resource integration, it deeply analyzes and summarizes Shandong Energy's practical paths and beneficial experiences in green and low-carbon transformation and achieving sustainable development. The research results have been found that mergers and acquisitions, as well as resource integration, have broadened the temporal and spatial boundaries and opportunity set for the green and low-carbon transformation of coal enterprises; Technological innovation is the intrinsic driving force for the green and low-carbon transformation of coal enterprises, providing technical support for their sustainable development; Financial innovation provides fund support for the green and low-carbon transformation and sustainable development of coal enterprises. The research conclusions have important practical significance and theoretical marginal contributions, provides experience reference and theoretical guidance for the green and low-carbon transformation of the other coal industry enterprises.

Reconstructing 10-km-resolution direct normal irradiance dataset through a hybrid algorithm

Evaluating, mapping, and monitoring high-quality Direct Normal Irradiance (DNI) is crucial for the design, financing, and operation of solar power plants, especially those utilizing concentrating technologies. In China, limited number of first-class meteorological stations provide DNI observations. To bridge this gap, this study has reconstructed a comprehensive 41-year (1982–2022) daily DNI dataset for China (CHDNI). This dataset integrated CMA ground-based observations with ERA5 and MERRA-2 reanalysis data, employing a spatial resolution of 10 km. The data was processed using the REST2 radiation transfer model combined with Stacking ensemble machine learning. Validation with ground-based measurements indicated that the Stacking model exhibited high and consistent performance. This was evidenced by its sample-based cross-validation results, showing a correlation coefficient (R) of 0.92, a root-mean-square error (RMSE) of 32.04 W/m2, a mean absolute error (MAE) of 23.68 W/m2, and a global performance indicator of 3.86. Among the four analyzed DNI products (CERES, ERA5, SWGDN, and CHDNI), CHDNI demonstrated the closet alignment with ground observations, evidenced by the least deviation (MAE = 21.67 W/m2 and RMSE = 31.00 W/m2) and the highest R value (0.92). Aerosol optical depth and cloud cover emerged as the primary factors influencing the quality and accuracy of DNI products under clear-sky and total-sky conditions. The spatial distribution of DNI across China is complex, showcasing DNI values ranging from 25.82 W/m2 to 194.22 W/m2, with an average value of 98.08 W/m2 over 41-year. This dataset is a valuable resource for analyzing regional climate change, photovoltaic applications, and solar energy resources assessment.

Assessing methane emissions and soil carbon stocks in the Camargue coastal wetlands: Management implications for climate change regulation

Coastal wetlands are crucial in climate change regulation due to their capacity to act as either sinks or sources of carbon, resulting from the balance between greenhouse gas (GHG) emissions, mainly methane (CH4), and soil carbon sequestration. Despite the paramount role of wetlands in climate regulation few studies investigate both aspects. The Camargue is one of the largest wetlands in Europe, yet the ways in which environmental and anthropic factors drive carbon dynamics remain poorly studied. We examined GHG emissions and soil organic carbon (SOC) stocks and accumulation rates in twelve representative wetlands, including two rice fields, to gain insights into the carbon dynamics and how it is influenced by hydrology and salinity. Mean CH4 rates ranged between – 87.0 and 131.0 mg m−2 h−1and the main drivers were water conductivity and redox, water table depth and soil temperature. High emission rates were restricted to freshwater conditions during summer flooding periods whereas they were low in wetlands subjected to summer drought and water conductivity higher than 10 mS cm−1. Nitrous oxide emissions were low, ranging from – 0.5 to 0.9 mg N2O m−2 h−1. The SOC stocks in the upper meter ranged from 17 to 90 Mg OC ha−1. Our research highlights the critical role of low-saline wetlands in carbon budgeting which potentially are large sources of CH4 but also contain the largest SOC stocks in the Camargue. Natural hydroperiods, involving summer drought, can maintain them as carbon sinks, but altered hydrology can transform them into sources. Artificial freshwater supply during summer leads to substantial CH4 emissions, offsetting their SOC accumulation rates. In conclusion, we advocate for readjusting the altered hydrology in marshes and for the search of management compromises to ensure the compatibility of economic and leisure activities with the preservation of the inherent climate-regulating capacity of coastal wetlands.

Spatiotemporal and weather effects on the reproductive success of piping plovers on Prince Edward Island, Canada.

Piping plovers (Charadrius melodus sp.) rank among North America's most endangered shorebird species, facing compounding environmental challenges that reduce habitat availability and suppress recruitment and survival rates. Despite these challenges, research on the direct effects of climate variability and extremes on their breeding ecology remains limited. Here, we employ a spatiotemporal modelling approach to investigate how location, nest timing and weather conditions influence reproductive success rates in a small breeding population of C. m. melodus in Prince Edward Island (PEI), Canada from 2011 to 2023. Analysis of 40 years of monitoring records from a subset of nesting sites revealed that flooding and predation have been persistent sources of reproductive failures in this population, with unexplained losses increasing in recent years. Contrary to our hypotheses, our modelled results did not support a negative impact of extreme high temperatures and strong precipitation events on reproductive outcomes. Instead, we identified a positive effect of T MAX and no effect of strong precipitation, perhaps due to limited exposure to extreme high temperatures (>32°C) and context-specific risks associated with precipitation-induced flooding. However, trends in regional climate change are likely to increase exposure to-and the influence of-such factors in the near future. Our models also identified spatiotemporal variability in apparent hatch success over the study period, as well as worse hatch outcomes across popular beachgoing regions and for delayed nesting attempts. While our results offer preliminary insights into factors affecting breeding success in this population, further research will be imperative to enhance understanding of constraints on recruitment. To this end, we encourage the collection and analysis of additional time-series data of prey populations, human activities, fine-scale weather data and predator/flood risks associated with each nest on PEI.

Predicting the impact of climate change on crop water footprint using CMIP6 in the Shule River Basin, China

Quantitatively predicting the impacts of climate change on water demands of various crops is essential for developing measures to ensure food security, sustainable agriculture, and water resources management, especially in arid regions. This study explored the water footprints (WFs) of nine major crops in the middle and downstream areas of Shule River Basin, Northwest China, from 1989 to 2020 using the WF theory and CROPWAT model and predicted the future WFs of these crops under four emission and socio-economic pathway (SSPs-RCPs) scenarios, which provides scientific support for actively responding to the negative impacts of climate change in arid regions. Results indicated: (1) an increasing trend of the overall crop WF, with blue WF accounting for 80.31–99.33% of the total WF in the last 30 years. Owing to differences of planting structure, water-conservation technologies, and other factors, the multi-year average WF per unit area of crops was 0.75 × 104 m3 hm−2 in downstream area, which was higher than that in midstream area (0.57 × 104 m3 hm−2) in the last 30 years; therefore agricultural water use efficiency in the downstream area was lower than that in the midstream area, implying that the midstream area has more efficient agricultural water utilization. (2) an initial increase and then decrease of crop WFs in the study area under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios by the end of the century, reaching their peak in 2030s which was higher than that from 1989 to 2020; with the maximum growth rates in the midstream area ranging from −0.85% in SSP5-8.5 to 5.33% in SSP2-4.5 and 29.74% in SSP5-8.5 to 34.71% in SSP2-4.5 in the downstream area. The local agricultural water demand would continue to increase and water scarcity issues would be more severe in the next 10–20 years, affecting downstream areas more. Under the SSP3-7.0 scenario, crop WF values of the midstream and downstream regions will be 2.63 × 108 m3 and 4.22 × 108 m3 in 2030, respectively, which is significantly higher than those of other scenarios and show a long-term growth trend. The growth rate of the midstream and downstream regions will reach 44.71% and 81.12%, respectively, by the end of this century, so the local agricultural water use would be facing more strain if this scenario materializes in the future. Therefore, the Shule River Basin should encourage development of water-saving irrigation technologies, adjust the planting ratio of high water consuming crops, and identify other measures to improve water resource utilization efficiency to cope with future water resource pressures.

Effects of climate change on seed germination may contribute to habitat homogenization in freshwater forested wetlands

Climate changes in temperate regions are expected to result in warmer, shorter winters in temperate latitudes. These changes may have consequences for germination of plant species that require a period of physiological dormancy. The effect of cold duration on seed germination has been investigated in a number of plant taxa, but has not been well studied in wetland and bottomland forest tree species, an ecosystem that is threatened by habitat homogenization. Our work sought to test the role of changing winter temperatures on seed germination in specialist (Nyssa aquatica and Taxodium distichum) and generalist (Acer rubrum and Liquidambar styraciflua) tree species within forested wetlands throughout the eastern U.S. The experiment was conducted in an environmental chamber in Norfolk, VA, USA. Seeds of T. distichum, N. aquatica, A. rubrum, and L. styraciflua were exposed to each of seven pre-germination cold exposure durations (0, 15, 30, 45, 60, 75, and 90 days) and observed for germination for 30 days. Cold stratification duration positively impacted total percent germination in N. aquatica (p < 0.0001) as well as A. rubrum (p = 0.0008) and T. distichum (p = 0.05). Liquidambar styraciflua seeds exhibited more rapid rates of germination with increasing cold exposure duration and greater percent germination compared to the others regardless of cold stratification duration. Our results provide insight into how community dynamics and biodiversity of wetland and bottomland trees may shift with a changing climate. Further, this work emphasizes the importance of understanding the role of plant functional traits in early life stages in community dynamics and has implications for management practices.

Regional climate change adaptation plans in Russia: Legal political overview

Regional climate change adaptation plans in Russia: Legal political overview

Promoting Nutritional and Sustainable value of Shree Anna (Millets) in India

"Shree Anna (Millets)" stands out as a viable contender in the search for wholesome and sustainable food solutions because it presents a nuanced strategy for tackling today's global food issues as well as the agrarian and nutritional aspects of millets, highlighting their capacity to change perceptions about food production. When it comes to harsh growing conditions, millets—a "nutri-cereals" crop that is compliant with climate change regulations—perform better than other grains like wheat and rice. These grains are meant to provide enough food that is both sufficient and nutritious, while also maximizing climate resilience, minimizing resource demands, and adapting to a variety of ecological conditions. Millets are renowned for their excellent nutritional value, which includes increased concentrations of calcium, magnesium, potassium, iron, manganese, zinc, and B complex vitamins, as well as balanced amino acids, complex carbs with a low GI, dietary fiber, and high-quality unsaturated fat. Additionally, they have a lot of bioactive phytochemicals. Because of these qualities, millets have become a long-term substitute for sustainable food production methods, protecting farmers' livelihoods and food security. The United Nations General Assembly has proclaimed 2023 as the "International Year of Millets" in an effort to increase awareness of millets as a crop and to highlight the importance of nutrient-rich crops for climate resilient agriculture. According to this study, millet grains provide similar and beneficial levels of different nutrients to primary cereal grains.

Astronomically forcing salinity variations in a marginal-marine environment, Bohai Bay Basin, NE China

Exploring the interdependence between watermass conditions and climate change in marginal marine regions is essential for gaining insights into contemporary environmental challenges arising from global warming. Salinity, a key parameter of watermass conditions in coastal areas, plays a crucial role in influencing nutrient availability, stratification, and the spatial-temporal distribution of redox conditions. Here, we focus on the cyclostratigraphic analysis of gamma-ray (GR) data obtained from Eocene strata in the Luo-69 drillcore from the Bohai Bay Basin (NE China). This analysis establishes a high-resolution astronomical time scale (ATS) for the lower third member of the Shahejie Formation (Es3l), spanning 39.04 Ma to 41.46 million years ago (Ma). Various proxies for watermass conditions, such as salinity, sedimentary structures, mineral content, total organic carbon (TOC), organic carbon isotopes and nitrogen isotopes (δ13Corg and δ15N), exhibit a strong correlation with 405-kyr long orbital eccentricity climate forcing. Notably, spectral analysis of salinity data (represented by the Sr/Ba proxy) reveals a clear astronomical control, with 405-kyr eccentricity cycles that align closely with variations in the GR data. Peaks in paleosalinity, as indicated by Sr/Ba (as well as B/Ga and S/TOC), correspond with maxima in 405-kyr long orbital eccentricity cycles in the GR data. As such, we infer that astronomical forcing regulated long-term changes in watermass conditions, likely through mediation of the East Asia monsoon system. Specifically, during eccentricity maxima, the basin would have experienced a warm and humid climate with pronounced seasonality and a robust summer monsoon. During such periods, increased continental runoff would lead to a rise in lake-levels, facilitating better connections with the ocean, and hence increased salinity. By contrast, during eccentricity minima, cooler and more arid conditions with weaker seasonality would result in lower lake levels which together with a global eustatic lowstand would result in as weakened connection with the open ocean restricting the ingress of seawater into the basin lowering salinity. Our dataset spans the Middle Eocene Climatic Optimum (MECO, ∼40.60–40.10 Ma), identified by elevated GR values and a conspicuous negative excursion in oxygen isotopes. This interval is characterized by a significant decline in salinity, likely attributed to enhanced freshwater runoff driven by an extremely warm and humid climate. The paleosalinity fluctuation recorded by the proxies B/Ga, Sr/Ba, and S/TOC in Bohai Bay Basin demonstrate the sensitivity of marginal-marine environment to subtle changes in climate driven by astronomical forcing. Our results provide new insights into how elemental salinity proxies can be utilized in paleoenvironmental reconstruction studies.

Blue and green water availability under climate change in arid and semi-arid regions

Challenges involving water scarcity have raised concerns about sustainability and human well-being in many regions of Iran. Uncertainty related to the effects of climate change further complicates the use of projections for water resources planning. Hence, investigating the impacts of climate change on water resources is essential for their efficient management. In the present study, water availability was assessed under different climate change projections using eight CMIP6 General Circulation Models (GCMs) to create a multi-model ensemble of well-performing GCMs over the Hamedan-Bahar watershed in western Iran for three futures, near (2026 to 2050), mid (2051 to 2075), and far (2076 to 2100). Impacts of climate change on blue and green water availability was assessed by coupling Soil and Water Assessment Tool (SWAT) with modelled climate change projections and applying distribution mapping bias correction under three Shared Socioeconomic Pathways Scenarios (SSPs). The results showed that three GCMs (MIROC6, CMCC-ESM2, and NorESM2-MM) agreed well with observed climate in the region. The mean annual precipitation was projected to decrease at most by 16.3% under the SSP5–8.5 scenario during mid-future. Maximum and minimum temperatures are expected to increase by 2.3 and 2.4 °C, respectively, under the SSP5–8.5 scenario for the far future. The highest reductions of green and blue water storage and blue water flow were projected at 22%, 28.5% and 35%, respectively, under the SSP5–8.5 scenario during the mid-future. In contrast, green flow was projected to increase by 18% under SSP5–8.5 during the far future. Thus, the water resources of Hamedan-Bahar are sensitive to future climatic changes requiring considerations for adaptation strategies to mitigate water deficits.

State of the Art of Coupled Thermo–hydro-Mechanical–Chemical Modelling for Frozen Soils

AbstractNumerous studies have investigated the coupled multi-field processes in frozen soils, focusing on the variation in frozen soils and addressing the influences of climate change, hydrological processes, and ecosystems in cold regions. The investigation of coupled multi-physics field processes in frozen soils has emerged as a prominent research area, leading to significant advancements in coupling models and simulation solvers. However, substantial differences remain among various coupled models due to the insufficient observations and in-depth understanding of multi-field coupling processes. Therefore, this study comprehensively reviews the latest research process on multi-field models and numerical simulation methods, including thermo-hydraulic (TH) coupling, thermo-mechanical (TM) coupling, hydro-mechanical (HM) coupling, thermo–hydro-mechanical (THM) coupling, thermo–hydro-chemical (THC) coupling and thermo–hydro-mechanical–chemical (THMC) coupling. Furthermore, the primary simulation methods are summarised, including the continuum mechanics method, discrete or discontinuous mechanics method, and simulators specifically designed for heat and mass transfer modelling. Finally, this study outlines critical findings and proposes future research directions on multi-physical field modelling of frozen soils. This study provides the theoretical basis for in-depth mechanism analyses and practical engineering applications, contributing to the advancement of understanding and management of frozen soils.

Tsallis q-Statistics Fingerprints in Precipitation Data across Sicily.

Precipitation patterns are critical for understanding the hydrological and climatological dynamics of any region. Sicily, the largest island in the Mediterranean sea, with its diverse topography and climatic conditions, serves as an ideal case study for analyzing precipitation data, to gain insights into regional water resources, agricultural productivity, and climate change impacts. This paper employs advanced statistical physics methods, particularly Tsallis q-statistics, to analyze sub-hourly precipitation data from 2002 to 2023, provided by the Sicilian Agrometeorological Informative System (SIAS). We investigate several critical variables related to rainfall events, including duration, depth, maximum record, and inter-event time. The study spans two decades (2002-2012 and 2013-2023), analyzing the distributions of relevant variables. Additionally, we examine the simple returns of these variables to identify significant temporal changes, fitting these returns with q-Gaussian distributions. Our findings reveal the scale-invariant nature of precipitation events, the presence of long-range interactions, and memory effects, characteristic of complex environmental processes.

Regional Climate Change and Drought Dynamics in Tunceli, Turkey: Insights from Drought Indices

Global warming and climate change are causing temperatures to rise, which is having a negative impact on water resources. Climate change is a worldwide problem that affects and will continue to affect the frequency and intensity of natural disasters in many regions of the world. Tunceli region in Turkey, which until 10 years ago was known as an environmentally friendly city with abundant water resources and frequent rainfall, is experiencing a decrease in precipitation during the snowy winter season. This situation has made the investigation of climate change impacts an important issue in the region. Therefore, effective climate change adaptation strategies need to be developed. To determine these strategies, in this study, we assessed long-term drought conditions using multiple drought indices such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Normal Precipitation Index (PNI), and Aridity Index (AI). The SPI and RDI analyses were performed in annual reference periods on a time scale of 3, 6, 9, and 12 months using temperature, precipitation, and evaporation data. Consequently, the SPI and RDI results were compared, and both indices show similar behavior in dry, wet, and normal seasons. Nevertheless, RDI shows less variation between different time scales, which is an advantage over SPI and is probably due to the inclusion of potential evapotranspiration in RDI. The variations in PNI between humid and dry sub-humid categorizations throughout the years, combined with the AI results, indicate that the Tunceli region predominantly experiences a climate ranging from dry sub-humid to semi-arid. This study could help decision-makers take effective measures to become more resilient to climate change in temperate climate regions and take important steps toward sustainable water resources management.