Climatic Variations Research Articles

Depositing skeletal remains in Czech and Moravian ossuaries and associated climatic variations

AbstractSamples of the bones of 47 individuals from 46 Czech and Moravian ossuaries were dated by the 14C method and analyzed for the collagen isotopic composition of carbon (δ13C) and nitrogen (δ15N). Most of the data for the ages of the remains corresponded to the cooler and damper periods described over the past 1000 years. Of the studied samples, the greatest number of remains corresponded to the Spörer (1400–1570), Dalton (1790–1830) and Wolf minima (1280–1350). One sample studied falls within the Maunder minimum (1645–1715). It can be assumed that these minima are connected with a reduced production of food and fodder, that may have initiated famines, epidemics and armed conflicts. Individual climatic minima showed positive correlations between δ13C and δ15N values, indicating that the individuals studied consumed complementary plant or animal diets to different degrees. The elevated δ15N values in our studied samples compared to the skeletal compositions of the population of the La Tène period (380 – 150 BC) and Germanic inhabitants in the territory of Bohemia (5th–6th centuries AD) and Great Moravia (9th–early 10th centuries AD) might reflect the effect of greater consumption of animal proteins or the proteins of omnivorous animals and fish, which compensated for the lack of plant foodstuffs during the colder periods.The isotopic composition of carbon and nitrogen of the bone collagen for the Spörer and Dalton minima differs from the Wolf minimum. The younger minima show higher δ15N values for a given δ13C value.

Regional Fluctuations in the Eastern Tropical North Pacific Oxygen Minimum Zone during the Late Holocene

This study presents a high-resolution record of δ15Nsed, which serves as a proxy for water column denitrification and oxygen minimum zone (OMZ) intensity, from the Soledad Basin in the Eastern Tropical North Pacific OMZ. The Soledad Basin δ15Nsed record is compared to the Pescadero Slope and Santa Barbara Basin (SBB) δ15Nsed records to gain insight into regional variations in the ETNP OMZ. During the Medieval Climate Anomaly (MCA; 950–1250 CE), Soledad Basin, Pescadero Slope, and SBB records exhibit coherent trends suggesting that there was general water column oxygenation stability. During the Little Ice Age (LIA; 1350–1850 CE), Soledad Basin and SBB showed a similar decreasing trend in δ15Nsed values while the Pescadero Slope δ15Nsed exhibited an increasing trend until values abruptly declined between 1740 and 1840 CE. We suggest that increased δ15Nsed variability and the different trends at the Pescadero Slope during the LIA are due to the influence of the North American monsoon (NAM), which can suppress upwelling when enhanced and result in OMZ contraction. The decoupling between the Soledad Basin, SBB, and the Pescadero Slope could also be due to the increased influence of enriched 15NO3− subarctic waters in the California Current System. Since each site is influenced by local productivity, basin morphology, and regional atmospheric and ocean circulation patterns, we suggest that assessing OMZ fluctuations from multiple sites provides a more comprehensive view of regional OMZ dynamics in response to climate variations.

The impact of climate and potassium nutrition on crop yields: Insights from a 30-year Swiss long-term fertilization experiment

Climate change will strongly influence agricultural practices in the future. In order to promote resource-efficient agriculture, it is important to analyse the impact of climate variation on crop yields. In this study, we report yields of spring wheat, winter barley, maize, potato and sugar beet from the long-term crop rotation and fertilization experiment Demo in Switzerland and analyze their response to different climate variables (e.g., annual and seasonal temperature, precipitation, evapotranspiration, number of heat days and days of heavy rainfall). In addition, we investigate the impact of readily plant-available soil potassium (K) on the relationship of crop yields and precipitation. Annual and summer temperatures increased by 1 °C and 1.5 °C, respectively, over the observation period, and both the number of heat days and days of heavy rainfall increased in summer. Rising summer temperatures have a negative impact on all crop yields, which was most prominent for spring wheat, potato and maize. Annual, spring and summer precipitation show varying effects on different crops. For maize, soil K has a mediating effect on yield reductions under low spring precipitation. Yields are significantly reduced by 1 t ha−1 per 100 mm reduction of precipitation below a soil K threshold of 7 mg K kg−1 soil. Based on these results and the future climate scenarios for Switzerland, crop rotations with less heat-sensitive species and early-maturing varieties should be considered. In order to keep future irrigation demands and costs as low as possible, the soil K fertility classes in the Swiss K fertilization guidelines might need to be revisited. Our study is one of a few long-term observations that show the impact of climate variation on crop yields and highlights the potential of K management as a climate change adaptation measure.

Physiological meaning of bimodal tree growth-climate response patterns.

Correlation coefficients are widely used to identify and quantify climate signals in proxy archives. Significant relationships between tree-ring chronologies and meteorological measurements are typically applied by dendroclimatologists to distinguish between more or less relevant climate variation for ring formation. While insignificant growth-climate correlations are usually found with cold season months, we argue that weak relationships with high summer temperatures not necessarily disprove their importance for xylogenesis. Here, we use maximum latewood density records from ten treeline sites between northern Scandinavia and southern Spain to demonstrate how monthly growth-climate correlations change from narrow unimodal to wide bimodal seasons when vegetation periods become longer and warmer. Statistically meaningful relationships occur when minimum temperatures exceed 'biological zero' at around 5° C. We conclude that the absence of evidence for statistical significance between tree growth and the warmest summer temperatures at Mediterranean sites is no evidence of absence for the physiological importance of high summer temperatures for ring formation. Since correlation should never be confused with causation, statistical values require mechanistic understanding, and different interpretations are needed for insignificant correlations within and outside the growing season.

A data‐driven topsoil classification framework to support soil health assessment in Minnesota

AbstractSoil health assessments aim to quantify soil health status using indicators linked to ecosystem services such as yield, nutrient cycling, water cycling, or carbon storage. Many indicators are related to soil biological processes, which can be challenging to interpret because they are sensitive not only to management, but also to nonmanagement variables such as soil inherent properties, topography, and climate. Existing studies address this challenge by grouping similar soils by taxonomy, geography, or a combination of these and other variables for soil health assessment. We investigated whether grouping soils based on multiple quantitative topsoil properties could be an alternative to taxonomic or geographic groups. We used an unsupervised classification algorithm, k‐means, to cluster publicly available soil and climate data for Minnesota. Clustering into eight conceptual groups (“clusters”) based on 10 topsoil properties was determined to be the optimal algorithm output. We evaluated the ability of our soil clusters and other grouping methods to explain variance in eight soil health indicators. We found the combination of Major Land Resource Area (MLRA) and soil cluster performed best, explaining as much or more variance than other groupings for five of the eight indicators. The clusters distinguish zones of topsoil variation at the field scale, and MLRAs account for broader scale variation in climate and other landscape factors. The approach we describe is flexible and could be applied at different locations and scales to produce conceptual soil groups and associated maps to support soil health test sampling and interpretation at the field scale.

Legacies of millennial-scale climate oscillations in contemporary biodiversity in eastern North America.

The Atlantic meridional overturning circulation (AMOC) has caused significant climate changes over the past 90 000 years. Prior work has hypothesized that these millennial-scale climate variations effected past and contemporary biodiversity, but the effects are understudied. Moreover, few biogeographic models have accounted for uncertainties in palaeoclimatic simulations of millennial-scale variability. We examine whether refuges from millennial-scale climate oscillations have left detectable legacies in the patterns of contemporary species richness in eastern North America. We analyse 13 palaeoclimate estimates from climate simulations and proxy-based reconstructions as predictors for the contemporary richness of amphibians, passerine birds, mammals, reptiles and trees. Results suggest that past climate changes owing to AMOC variations have left weak but detectable imprints on the contemporary richness of mammals and trees. High temperature stability, precipitation increase, and an apparent climate fulcrum in the southeastern United States across millennial-scale climate oscillations aligns with high biodiversity in the region. These findings support the hypothesis that the southeastern United States may have acted as a biodiversity refuge. However, for some taxa, the strength and direction of palaeoclimate-richness relationships varies among different palaeoclimate estimates, pointing to the importance of palaeoclimatic ensembles and the need for caution when basing biogeographic interpretations on individual palaeoclimate simulations. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Spring Meteorological Drought over East Asia and Its Associations with Large-Scale Climate Variations

East Asia is a region that is highly vulnerable to drought disasters during the spring season, as this period is critical for planting, germinating, and growing staple crops such as wheat, maize, and rice. The climate in East Asia is significantly influenced by three large-scale climate variations: the Pacific Decadal Oscillation (PDO), the El Niño–Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD) in the Pacific and Indian Oceans. In this study, the spring meteorological drought was quantified using the standardized precipitation evapotranspiration index (SPEI) for March, April, and May. Initially, coupled climate networks were established for two climate variables: sea surface temperature (SST) and SPEI. The directed links from SST to SPEI were determined based on the Granger causality test. These coupled climate networks revealed the associations between climate variations and meteorological droughts, indicating that semi-arid areas are more sensitive to these climate variations. In the spring, PDO and ENSO do not cause extreme wetness or dryness in East Asia, whereas IOD does. The remote impacts of these climate variations on SPEI can be partially explained by atmospheric circulations, where the combined effects of air temperatures, winds, and air pressure fields determine the wet/dry conditions in East Asia.

Elevation and local climate variation control changes in Aleppo pine growth responses to hydroclimate and drought in semi-arid Spain

Elevation and local climate variation control changes in Aleppo pine growth responses to hydroclimate and drought in semi-arid Spain

Predicting the potential distribution of Dendrolimus punctatus and its host Pinus massoniana in China under climate change conditions

IntroductionDendrolimus punctatus, a major pest endemic to the native Pinus massoniana forests in China, displays major outbreak characteristics and causes severe destructiveness. In the context of global climate change, this study aims to investigate the effects of climatic variations on the distribution of D. punctatus and its host, P. massoniana. MethodsWe predict their potential suitable distribution areas in the future, thereby offering a theoretical basis for monitoring and controlling D. punctatus, as well as conserving P. massoniana forest resources. By utilizing existing distribution data on D. punctatus and P. massoniana, coupled with relevant climatic variables, this study employs an optimized maximum entropy (MaxEnt) model for predictions. With feature combinations set as linear and product (LP) and the regularization multiplier at 0.1, the model strikes an optimal balance between complexity and accuracy.ResultsThe results indicate that the primary climatic factors influencing the distribution of D. punctatus and P. massoniana include the minimum temperature of the coldest month, annual temperature range, and annual precipitation. Under the influence of climate change, the distribution areas of P. massoniana and its pests exhibit a high degree of similarity, primarily concentrated in the region south of the Qinling−Huaihe line in China. In various climate scenarios, the suitable habitat areas for these two species may expand to varying degrees, exhibiting a tendency to shift toward higher latitude regions. Particularly under the high emission scenario (SSP5-8.5), D. punctatus is projected to expand northwards at the fastest rate. DiscussionBy 2050, its migration direction is expected to closely align with that of P. massoniana, indicating that the pine forests will continue to be affected by the pest. These findings provide crucial empirical references for region-specific prevention of D. punctatus infestations and for the rational utilization and management of P. massoniana resources.

Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables

This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann–Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses. The findings highlight significant spatial and temporal variations in NDVI, with an annual increase averaging 0.00197 per year (p < 0.0001). This positive trend is coupled with an increase in precipitation by 0.4801 mm/year (p = 0.0016). In contrast, our analysis recorded a slight decrease in temperature (− 0.01011 °C/year, p < 0.05) and a reduction in solar radiation (− 0.27526 W/m2/year, p < 0.05). Notably, cross-wavelet transform analysis underscored significant coherence between NDVI and climatic factors, revealing periods of synchronized fluctuations and distinct lagged relationships. This analysis particularly highlighted precipitation as a primary driver of vegetation growth, illustrating its crucial impact across various Pakistani regions. Moreover, the analysis revealed distinct seasonal patterns, indicating that vegetation health is most responsive during the monsoon season, correlating strongly with peaks in seasonal precipitation. Our investigation has revealed Pakistan's complex association between vegetation health and climatic factors, which varies across different regions. Through cross-wavelet analysis, we have identified distinct coherence and phase relationships that highlight the critical influence of climatic drivers on vegetation patterns. These insights are crucial for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in the face of ongoing climatic changes.

Climatic Variations and Challenges to Socio-economic Development amongst Mbororo Communities in Mbum Plateau, North West Region of Cameroon

This study sets out to investigate the challenges hindering Mbororo sources of livelihood in Mbum Plateau, North West Region of Cameroon. Explanatory research was used where it specify the nature and direction of the relationships between the studied variables. The study used mixed methods of qualitative and quantitative approaches. The study employed the primary and secondary data sources to bring out realistic results. Rainfall Seasonality Index (SI) and Standardized Precipitation Index (SPI) were employed to assess the vulnerability of the agro-hydrological system to climate variation. The major primary data sources used were field survey, interviews and questionnaires. A total of 200 questionnaires were distributed using stratified random and snow ball sampling techniques. The data obtained was complemented by secondary sources from published and unpublished materials. Data collected during the field survey were analyzed through two statistical techniques. The qualitative data obtained was analyzed through the content analysis whereas themes and codes were given to the different opinions and perceptions of the informants and their frequencies and percentages were being determined from there. Data were presented in tables, charts, maps, and graphs with some attempted interpretations. Data were analyzed using the chi-square and multiple regression models. The findings revealed that climate variability, dwindling pasture and low streams discharge are having negative effects on Mbororo communities. It was observed from satellite images that, land use over the years has been changing with reducing aerial extent and quality of pasture, reducing water points in Mbum Plateau. In order to adapt the decreasing cattle numbers on the side of the Mborroro, they have taken farming, diving, hawking arm rubbery, and schooling as new livelihoods sustenance. The study recommends a sustainable pastoral activity by encouraging the introduction of drought resistant cattle species, Bracharia and Guatemala grass to supplement the natural pasture. MINEPAI should regularly control herd size so as to ensure ecosystem balance and avoid overgrazing. Transhumance tracts and areas should be well demarcated to avoid frequent farmer-grazers’ conflicts and frequent cattle theft observed in the region.

Hydrological response of Andean catchments to recent glacier mass loss

Abstract. The impacts of the accelerated glacier retreat in recent decades on glacier runoff changes are still unknown in most Andean catchments, increasing uncertainties in estimating water availability. This particularly affects the outer tropics and Dry Andes, heavily impacted by prolonged droughts. Current global estimates overlook climatic and morphometric disparities, which significantly influence model parameters, among Andean glaciers. Meanwhile, local studies have used different approaches to estimate glacier runoff in a few catchments. Improving 21st-century glacier runoff projections relies on calibrating and validating models using corrected historical climate inputs and calibrated parameters across diverse glaciological zones. Here, we simulate glacier evolution and related runoff changes between the periods 2000–2009 and 2010–2019 across 786 Andean catchments (11 282 km2 of glacierized area, 11° N to 55° S) using the Open Global Glacier Model (OGGM). TerraClimate atmospheric variables were corrected using in situ data, getting a mean temperature bias by up to 2.1 °C and enhanced monthly precipitation. Glacier mass balance and volume were calibrated, where melt factor and the Glen A parameter exhibited significant alignment with varying environmental conditions. Simulation outcomes were validated against in situ data in three documented catchments (with a glacierized area &gt; 8 %) and monitored glaciers. Our results at the Andes scale reveal an average reduction of 8.3 % in glacier volume and a decrease of 2.2 % in surface area between the periods 2000–2009 and 2010–2019. Comparing these two periods, glacier and climate variations have led to a 12 % increase in mean annual glacier melt (86.5 m3 s−1) and a decrease in rainfall on glaciers of −2 % (−7.6 m3 s−1) across the Andes, with both variables comprising the glacier runoff. We confirmed the utility of our corrected regional simulations of glacier runoff contribution at the catchment scale, where our estimations align with previous studies (e.g., Maipo 34° S, Chile) as well as provide new insights on the seasonal glaciers' largest contribution (e.g., La Paz 16° S, Bolivia) and new estimates of glacier runoff contribution (e.g., Baker 47° S, Chile).

Climate variability impacts on runoff projection in the 21st century based on the applicability assessment of multiple GCMs: A case study of the Lushi Basin, China

In this study, we initiatively employed the improved Secure Hash Algorithm (SHA) to evaluate and compare the competencies of multiple Coupled Model Intercomparison Project Phase Six (CMIP6) General Circulation Models (GCMs). The selected GCM outputs were bias-corrected by the non-parametric quantile mapping (QM) method. The calibrated and validated data were then used to run the XAJ (Xin’anjiang) model to assess long-term climate variation impacts on runoff under four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), where the results were compared with the baseline period (1976–2000). Overall, the CNRM-CM6-1-HR, FIO-ESM-2–0, INM-CM5-0 and NorESM2-MM models reconstructed better spatio-temporal evolutionary trends related to historical precipitation and evaporation, and were applied as selected GCMs for reliable runoff projection applications. The intensification amplitudes of precipitation and evaporation produced by selected GCMs gradually spread from SSP1-2.6 to SSP5-8.5 throughout the 21st century. Compared to the baseline period (257 m3/s), the extreme streamflow during the wet periods is likely to increase for SSP5-8.5 (288 ∼ 298 m3/s), SSP3-7.0 (276 ∼ 294 m3/s), and SSP2-4.5 (222 ∼ 280 m3/s), whereas SSP1-2.6 decreases to varying degrees (178 ∼ 255 m3/s). Meanwhile, during the dry periods, the extreme streamflow is projected to decrease by 28 ∼ 73 m3/s (SSP5-8.5), 32 ∼ 38 m3/s (SSP3-7.0), 8 ∼ 31 m3/s (SSP2-4.5), and 5 ∼ 33 m3/s (SSP1-2.6) from historical levels (62 m3/s). The overwhelming majority of increasing trends in the wet periods and vastly decreasing trends in the dry seasons indicate that the basin will face some floods and water shortage risks in the mid to late 21st century. The findings broaden the efficacious applications of SHA in the performance selection of GCMs and QM method in bias correction. The conclusions provide a reference for flood and drought mitigation planning and water resources policymaking in the Yellow River Basin.

ANALYSE DE L’INFLUENCE DES PARAMETRES METEOROLOGIQUES SUR LA PLUVIOMETRIE A KINSHASA

The understanding of meteorological parameters influencing rainfall is essential to effectively address environmental challenges and anticipate the consequences of extreme weather events. In this study, we analyze meteorological data provided by the Airways Authority of Kinshasa (RVA), covering the period from 1992 to 2019. This in-depth statistical analysis aims to better understand the factors that influence precipitation in the region and to identify relevant climate trends for anticipating future environmental changes. We used logistic regression to assess the impact of various climatic factors such as temperature (daily extremes), relative humidity, and atmospheric pressure on precipitation. The results indicate that minimum temperature, relative humidity, and atmospheric pressure show a strong correlation with rainfall in Kinshasa, highlighting their significant influence on the likelihood of precipitation. In contrast, maximum temperature has a limited impact, making it a less reliable indicator of rainfall in the city. The conclusions of this study provide valuable tools for local authorities in developing effective strategies for managing climate variations and predicting weather phenomena. These insights enable precise modeling of the impacts of meteorological fluctuations on ecosystems and urban infrastructure. Furthermore, the results of this research can guide local farmers in optimizing their agricultural practices by adjusting planting and harvesting schedules based on detailed weather forecasts, thereby minimizing economic losses and enhancing crop resilience to climate variations. Finally, this study provides climatologists with robust data for in-depth analysis of the effects of climate change on meteorological phenomena in Kinshasa. This knowledge is crucial for refining regional climate models and developing specific adaptation strategies for other urban areas in sub-Saharan Africa.

Unveiling UVB resilience in Oryza sativa L.: Integrative analysis of physiological, molecular and microRNA responses

Rice is the staple food for more than half of the global population. It is cultivated in over 100 countries, and is predominant in Asia, which accounts for 90 % of the world's production. As the most crucial food crop globally, rice is sensitive to both UVB radiation and climate variations. UltraViolet-B radiation (UVB) is recognised as adverse factors for photosynthesis and plant growth. The current study investigates the resilience of Oryza sativa L. (IR20) seedlings to UVB irradiation, focusing on parameters such as photosynthetic pigment, total sugar, phenolic, total free amino acids, malondialdehyde content, hydrogen peroxide, and antioxidative enzymes. The mRNA expression levels of genes involved in UVB perception, signalling, and response (UVR8, HY5, RLCK, PHT2, and URP) were studied using quantitative RT-PCR (RT-qPCR). Additionally, a computational approach was employed to identify UVB-responsive microRNAs (miRNAs) and their corresponding target mRNAs; which were subsequently validated using stem-loop RT-qPCR and RT-qPCR, respectively. Surprisingly, it was discovered that the H2O2 content in the IR20 cultivar increased in response to UVB irradiation, despite no significant changes observed in lipid peroxidation, chlorophyll, and phenolic content. Additionally, UVB irradiation increases the total sugar content and decreases the entire free amino acid content, while not affecting total protein. The RT-qPCR analysis of mRNA expression reveals that UVB exposure augment the expression of genes related to UVB signal detection (UVR8), signalling (HY5, RLCK, and WRKY), and response (PHT2, CA, and URP). Our findings also suggest that at the post-transcriptional stage, miRNAs expressed upon UVB irradiation are responsible for the significant tolerance of IR20 seedlings to UVB radiation. Overall, the results reveal that IR20 exhibits promise candidate for the development of rice varieties that are both highly productive and resilient to UVB induced stress.

A multi‐scenario analysis of climate impacts on plankton and fish stocks in northern seas

AbstractGlobally, impacts of climate change display an increasingly negative development of marine biomass, but there is large regional variability. In this analysis of future climate change on stock productivity proxies for the North Sea, the Norwegian Sea, and the Barents Sea, we have provided calculations of accumulated directional effects as a function of climate exposure and sensitivity attributes. Based on modelled changes in physical and biogeochemical variables from three scenarios and knowledge of 13 different stocks' habitats and response to climate variations, climate exposures have been weighted, and corresponding directions these have on the stocks have been decided. SSP1‐2.6 gives mostly a weak cooling in all regions with almost negligible impacts on all stocks. SSP2‐4.5 and SSP5‐8.5 both provide warmer conditions in the long term but are significantly different in the last 30 years of the century when the SSP5‐8.5 warming is much stronger. The results show that it is the current stocks of cod and Calanus finmarchicusin the North Sea, and polar cod and capelin in the Barents Sea that will be most negatively affected by strong warming. Stocks that can migrate north into the northern seas such as hake in the Norwegian Sea, or stocks that are near the middle of the preferred temperature range such as mackerel and herring in the Norwegian Sea and cod and Calanus finmarchicus in the Barents Sea, are the winners in a warmer climate. The highly different impacts between the three scenarios show that multiple scenario studies of this kind matter.

Climate, wildfire, and volcanic ash drivers of ecosystem change in high mountain forests, British Columbia, Canada

Northwest North America has unique high elevation Picea–Abies forests and parkland classified in British Columbia as the Engelmann Spruce–Subalpine–fir (ESSF) Biogeoclimatic zone. These ecosystems occur on a topographically and climatically complex landscape, juxtaposed with diverse vegetation types including alpine tundra, inland rain forest, dry conifer forest, and grasslands. Spatio-temporal ecosystem disturbance is varied, driven by factors such as climate variation, wildfire, volcanic eruptions, and insect herbivory. A pollen and charcoal record derived from a lake sediment core from the ESSF reveals a unique late-glacial to modern vegetation history progressing from alpine steppe through dry open conifer forest to moist spruce–fir ecosystems, the latter arising only 4600 years ago, late by comparison to other ESSF sites in the region. Repeated disturbance in the mid Holocene by wildfire coupled with volcanic ash deposition and increased climatic variation resulted in recurring Pinus contorta-dominated seral forest stands before cooling and moistening in the late Holocene led to stable Picea–Abies forest. With rapid climate change, changing disturbance regimes, and timber harvest, the management of dry ESSF forests needs to consider that this forest-type could transform into parkland or open seral pine stands, with a high frequency disturbance regime.

Investigation the Level of Groundwater Pollution with Heavy Metals in Mazar-e-Sharif City

The majority of drinking and consumable water sources for the residents of Mazar-e-Sharif city are supplied from underground water. Climate variations, depletion of underground water, pollution resulting from human activities, agriculture, industrial processes, and urban development have significantly impacted the quality of underground water in this region. In this research, the quality of groundwater in terms of contamination with heavy metals such as manganese, copper, aluminum, iron, cadmium, mercury, lead, and arsenic was investigated. Twenty-four random well samples were collected based on international sampling standards, and temperature and pH parameters were measured on-site. The concentration of heavy metals was measured using an atomic absorption spectrophotometer. Data analysis was performed using Excel and SPSS software, and GIS software was utilized for mapping the sampled points. Laboratory results indicated that the lead concentration in wells W6, W11, W20, and W22 was 0.014, 0.013, 0.02, and 0.012 milligrams per liter, respectively. The aluminum concentration in wells W5, W16, and W17 was 0.6, 0.5, and 0.4 milligrams per liter, respectively, and the cadmium concentration in well W3 was 0.005 milligrams per liter. The concentrations in these wells exceeded the recommended limits set by the World Health Organization (WHO). In the remaining wells, the concentrations of heavy metals were below the WHO limits. Descriptive statistics results showed that copper had the highest average concentration, and arsenic had the lowest concentration. Since underground water is the sole source of drinking and consumable water for the city's residents, it is recommended to conduct a systematic study of heavy metal concentrations in groundwater sources to reduce the adverse effects of contaminated water in certain wells.

Remote sensing-based seasonal surface urban heat island analysis in the mining and industrial environment.

Cooling spaces have an optimistic influence on surface urban heat islands (SUHI). Blue spaces benefit from balancing thechanging climate and heat variations. Because of the rapid deforestation and SUHI increase, the climate is gradually changing in Paschim Bardhhaman, West Bengal state, India. Paschim Bardhhaman has two sectors: specifically, Durgapur is the main industrial centre and Asansol has coal mines. This investigation aims to categorize spatiotemporal variations and seasonal differences in cooling spaces and their influence on SUHI, land use and land cover (LULC), and thermal differences using Landsat datasets for the years 1992, 2004, 2012, and 2022 in summer and winter. The coal mining and industrial range decreased from 10,391.92 (1992) to 3591.1ha (2022), respectively. Open pit mining distresses fresh water by heavy water uses in ore processing, and mining water was applied to excerpt minerals. Among the two sub-divisions, the blue space amount was higher in Asansol because mining actions were higher in Asansol than in Durgapur. The open vegetation volume has reduced from 46,441.03 (1992) to 25,827.55ha (2022) and dense vegetation has erased from 7368.02 (1992) to 15,608.56ha (2022). Dense vegetation improved because of heavy precipitation in those regions. Mostly, Raghunathpur, Saraswatiganja, Bhagabanpur, Bistupur, Paschim Gangaram, Garkilla Kherobari, and Gourbazar have dense vegetation. The outcomes similarly demonstrate that the total built-up part has increased by 8412.82ha in between 30years. The built-up zone changes near the southeast and western Paschim Bardhhaman district. Those region needs appropriate attention and planning to survive soon.

Strategic Integration of Catchment Level Natural and Structural Methods of Sustainable Flood Management: A Case Study of River Wharfe Catchment Area

Water has a crucial place in the advent of humankind the flourishing of mega population centres, and is an essential source of food, water transportation, and irrigation. The anthropogenic activities in taming the natural water streams to the optimum benefit of human beings disturb natural flood plains, ecology and habitat. The channelisation of streams and hydromodifications in dams, barrages or reservoirs result in climatic variations locally/ regionally and impact transborder stream flow. Researchers have been endeavouring to restore the flood plains to their natural conditions. Still, huge hydromodifications and the development of megacities right in the flood plains or adjacent to the streams have resulted in irreversible disturbances to the natural lay of ground/ landscape. Therefore, to avoid flooding disasters, further structural interventions are undertaken to augment the natural flood prevention methods using advanced materials like cement concrete, steel, and polymers rather than increasing the emissions of greenhouse gases. Considering the strategic necessity of engineering structures as an integrated catchment level solution to augment the natural methods, the researchers/ engineers are now focussing on the use of sustainable, eco-friendly materials and demountable/ hydraulic structures to minimise the carbon footprints of hydromodifications and to decrease the obstruction to the natural flow of streams by using the flood prevention structures/ gates/ walls/ reservoirs only in case of disastrous flooding and otherwise keeping them unemployed during normal stream discharges. This study has been used to review sustainable flood management using natural and structural techniques in the Wharf River catchment in the UK, reviewing the existing research/ flood management schemes giving the pictorial coverage. The study suggests that natural flood management techniques have restricted application parameters and must be augmented by engineering structures to achieve effective flood management against heavy flooding. Low CO2 embodied greener infrastructure structural materials containing supplementary cementitious materials (SCMs) can be a beneficial option for an environmentally friendly flood management strategy.