International Journal of Environment and Climate Change

Urban Green Infrastructure and Community Forestry: A Comparative Analysis of Approaches in the United Kingdom and India

Brijesh Pal Yadav, Ram Ajeet Chaudhary — Sat, 04 Jul 2026 00:00:00 +0000

Urban green infrastructure (UGI) and community forestry represent complementary yet contextually distinct responses to the ecological and social challenges of rapid urbanisation. As cities expand globally, the provision and governance of urban tree cover, green corridors, and participatory forest management have attracted growing scholarly and policy attention. This article presents a critical comparative review of UGI development and community forestry practice in two contrasting national contexts: the United Kingdom (UK) and India. The UK has developed mature statutory frameworks for green infrastructure (GI) planning, embedded within spatial planning legislation and reinforced by National Forest programmes, urban tree strategies, and biodiversity obligations. India, by contrast, relies on a mosaic of decentralised governance arrangements—including Joint Forest Management (JFM) and the Van Panchayat (VP) system—that have shaped the interface between community institutions, municipal authorities, and forest resources over a century. Drawing on peer-reviewed literature published primarily between January 2000 and March 2026, this review examines the ecosystem services delivered by urban forests and GI in each country, the governance architectures underpinning their management, community participation models, equity dimensions, and the transferability of lessons across divergent contexts. The analysis reveals that the UK's planning-led approach achieves structural coherence but struggles with social inclusion and biodiversity mainstreaming, whilst India's decentralised models generate community ownership but remain fragmented and under-resourced in urban settings. Critical research gaps persist in monitoring, standardised ecosystem service valuation, and intercountry policy learning. Future frameworks should integrate adaptive governance with robust spatial data systems and deliberate equity targeting.

Artificial Intelligence and Machine Learning in Precision Agriculture: Applications, Challenges, and Future Directions

Sat, 04 Jul 2026 00:00:00 +0000

Precision agriculture has shifted from a sensor-driven discipline into a data-driven one, with artificial intelligence and machine learning now embedded in crop monitoring, disease and weed management, irrigation scheduling, soil assessment, robotics, and farm decision support. This review synthesises the state of artificial intelligence and machine learning applications across the precision agriculture value chain, drawing on peer-reviewed literature published between January 2018 to March 2026, supplemented by a small number of earlier foundational studies. The review traces the evolution from conventional algorithms such as random forests and support vector machines toward deep convolutional and recurrent architectures, and more recently toward transformer-based models, vision-language systems, and large language models adapted for agronomic reasoning. Five themes receive particular attention: crop monitoring and yield forecasting; detection and management of diseases, pests, and weeds; soil, water, and nutrient management; remote sensing and robotic field operations; and the data infrastructure, including the Internet of Things, big data analytics, and federated learning, that underpins these applications. The review also examines the economic and socio-political dimensions of adoption, particularly the disparities between well-resourced and smallholder farming systems, alongside the ethical and governance questions raised by farm data ownership and algorithmic transparency. The discussion closes with an assessment of emerging directions, including explainable artificial intelligence, privacy-preserving learning, and generative model integration, and concludes by identifying methodological gaps that constrain translation of laboratory performance into field-scale reliability. The review is intended for agricultural scientists, data scientists, and policymakers seeking a structured, critically evaluated synthesis of where artificial intelligence currently stands in precision agriculture and where it is heading.

Physiological and Yield Performance of Some Upland Rice Cultivars of Assam under Aerobic and Normal Moisture Regimes

Sat, 20 Jun 2026 00:00:00 +0000

Upland rice (broadcast summer rice) is a major component of rice production in Assam, particularly during flood and post-flood periods. The present study evaluated selected upland rice cultivars under normal irrigated and aerobic moisture regimes to identify physiological, biochemical and yield-related responses associated with moisture-stress tolerance. The experiment was conducted during the Rabi season at the Department of Crop Physiology, Assam Agricultural University, Jorhat. Five upland rice genotypes (Banglami, Inglongkiri, Boga ahu, Ronga ahu and Bengungutia ahu), selected after preliminary screening from 169 genotypes, were compared with the national check variety CR Dhan in a fractional randomised block design with three replications. Normal plots were maintained at 17-19% soil moisture, whereas aerobic plots were maintained at 7-8% soil moisture through life-saving irrigation. Aerobic conditions reduced mean flag leaf area by 29.94%, photosynthetic rate by 32.10%, internal CO2 concentration by 15.12%, transpiration rate by 12.73%, total leaf chlorophyll content by 22.95%, nitrate reductase activity by 29.78%, panicle number per hill by 29.56%, grain yield by 20.84% and harvest index by 30.26%. In contrast, mean leaf proline content increased by 43.98% under aerobic conditions. Among the genotypes, Inglongkiri recorded the highest grain yield under aerobic conditions (489.89 g m-2), closely followed by Banglami (488.21 g m-2) and Ronga ahu (468.23 g m-2). These genotypes also maintained relatively favourable physiological and biochemical traits under aerobic conditions. The findings indicate that Inglongkiri, Banglami and Ronga ahu may be more suitable for cultivation under aerobic moisture regimes, whereas Boga ahu and Bengungutia ahu showed relatively greater susceptibility to moisture stress in the present study.

Assessment of Land Use and Land Cover Change Dynamics Using Google Earth Engine

Shashi Bhushan Kumar, Krishna Mondal, Ashok Mishra, Suyog Babasaheb Khose — Sat, 20 Jun 2026 00:00:00 +0000

This study assessed land use and land cover (LULC) dynamics in the Subarnarekha River Basin, eastern India, using multi-temporal satellite datasets and cloud-based geospatial analysis. The study aimed to map LULC changes during 2019–2021, evaluate their spatial and temporal variability, and compare the performance of Random Forest and Support Vector Machine classifiers within Google Earth Engine. Sentinel-2 multispectral imagery and Sentinel-1 synthetic-aperture radar data were integrated to reduce limitations associated with cloud cover and spectral ambiguity. Seasonal, annual and combined LULC maps were generated for seven classes: trees, shrubland, grassland, cropland, built-up areas, bare/sparse vegetation and permanent water bodies. The overall classification accuracy ranged from 65.16% to 73.87%, while the kappa coefficient ranged from 0.61 to 0.69. Combined multi-temporal datasets produced higher classification accuracy than single-season datasets, indicating the value of temporal integration for reducing classification uncertainty. The results showed a gradual decline in forest cover, accompanied by increases in cropland and built-up areas. Grassland and bare/sparse vegetation showed moderate variability, whereas permanent water bodies remained comparatively stable with seasonal fluctuations. These changes indicate increasing anthropogenic pressure associated with agricultural expansion and urban development. The findings provide baseline spatial information for understanding land-transformation processes and supporting sustainable land and water resource management in the Subarnarekha River Basin.

Influence of Meteorological Variables on the Population Dynamics of Insect Pests of Pea in North-Western India

Jasmine Jasmine, Kavita Bajaj, Jenia Thakur — Mon, 22 Jun 2026 00:00:00 +0000

Pea (Pisum sativum L.) is a short-duration legume crop valued for its protein-rich seeds, fodder use and contribution to soil fertility through nitrogen fixation. The present study examined the population dynamics of major insect pests of pea and their association with selected meteorological variables during the rabi season of 2024–25 at Khalsa College, Amritsar, Punjab, India. The experiment was laid out in a randomised block design with thirteen treatments and three replications. Weekly observations were recorded from the first appearance of pests until harvest on five randomly selected plants from each plot. Aphids were assessed on a 10 cm apical twig per plant, leaf miner and thrips populations were recorded from three canopy leaves per plant, and pod borer incidence was determined by counting larvae per plant. The major insect pests observed were aphid, leaf miner, thrips and pod borer. Aphid infestation began during the 49th Standard Meteorological Week (SMW) and peaked during the 4th SMW with 35.00 aphids per 10 cm apical twig. Leaf miner first appeared during the 48th SMW and reached 17.23 larvae per plant during the 4th SMW. Thrips incidence started during the 48th SMW and peaked at 6.85 thrips per plant during the 7th SMW, whereas pod borer infestation began during the 4th SMW and reached 1.90 larvae per plant during the 7th SMW. Aphid, leaf miner and thrips populations showed significant negative associations with maximum temperature, minimum temperature and relative humidity. Pod borer showed non-significant negative associations with these variables, and rainfall had a non-significant effect on all pests. Multiple regression analysis showed that weather parameters explained 66.5%, 59.6%, 61.2% and 46.2% of variation in aphid, leaf miner, thrips and pod borer populations, respectively.

Ichthyofaunal Diversity and Physicochemical Water Quality of Dahod Reservoir, Raisen, Madhya Pradesh, India

Elias Constance Wahlang, Mahendra Kumar Yadav, Shriparna Saxena — Mon, 22 Jun 2026 00:00:00 +0000

This study assessed ichthyofaunal diversity and selected physicochemical water quality parameters of Dahod Reservoir in Raisen district, Madhya Pradesh, India. The reservoir, constructed in 1958, is used for irrigation and water supply and also supports aquatic biodiversity. Monthly sampling was conducted from December 2025 to April 2026 at four selected sites, namely Bithori, Dahod, Landing Centre and Imaliya Gondi, with the assistance of local fishermen. Fish specimens were collected using gill nets, cast nets and drag nets of different mesh sizes, and species were identified using standard taxonomic keys. Water quality was evaluated through measurements of air temperature, water temperature, transparency, pH, free carbon dioxide, dissolved oxygen, total hardness and total alkalinity. The study recorded 18 aquatic taxa distributed across 7 orders and 10 families. Cypriniformes was the dominant order, contributing 47% of the total recorded fauna, followed by Siluriformes (24%), Perciformes (8%), Cichliformes (6%), Beloniformes (5%), Osteoglossiformes (6%) and Decapoda (5%). The family Cyprinidae was represented by eight species and was the most abundant family. Shannon diversity values ranged from 1.519 to 1.890, while Shannon equitability ranged from 0.547 to 0.667, indicating moderate diversity with uneven species distribution. Physicochemical parameters remained within ranges generally favourable for freshwater fish survival, with pH from 6.9 to 8.5, dissolved oxygen from 6.0 to 9.8 mg/L, total hardness from 110 to 136 mg/L and total alkalinity from 136 to 190 mg/L. Overall, the findings indicate that Dahod Reservoir supports moderate aquatic diversity and maintains water quality conditions suitable for fish productivity, while continued monitoring is needed to address increasing anthropogenic pressures and the presence of exotic species.

Effect of Heat Stress Mitigators on Growth Performance of Wheat (Triticum aestivum L.) under Varying Sowing Windows

Pragati Kumari, Suborna Roy Choudhury, Seema, Anupam Das — Mon, 22 Jun 2026 00:00:00 +0000

Rising temperature adversely affects cereal production and threatens global food security. Wheat is highly vulnerable to heat stress, which reduces its growth, development and productivity. A field experiment was conducted during the rabi seasons of 2024–25 and 2025–26 at Bihar Agricultural University, Sabour, to evaluate the effect of heat stress mitigators on wheat growth under different sowing windows. The experiment was laid out in a split-plot design with three replications. Three sowing windows, namely timely sown, late sown and very late sown, were assigned to the main plots, while five foliar treatments, namely water spray, 2% potassium nitrate, melatonin at 100 µM, sodium nitroprusside at 100 µM and progesterone at 1 µM, were assigned to the subplots. Growth parameters were recorded at 30, 60 and 90 days after sowing and at harvest. Timely sowing produced the highest plant height, leaf area index and number of tillers m⁻², whereas very late sowing recorded the lowest values. Among the foliar treatments, 2% potassium nitrate produced the highest growth values and remained statistically comparable with sodium nitroprusside for most observations. At harvest, 2% potassium nitrate recorded a plant height of 98.80 cm, a leaf area index of 3.44 and 292.02 tillers m⁻². The corresponding values under water spray were 88.77 cm, 2.98 and 270.17 tillers m⁻². The interaction between sowing windows and heat stress mitigators was non-significant. The findings indicate that delayed sowing reduced wheat growth, while foliar application of potassium nitrate and sodium nitroprusside improved growth performance under the tested conditions.

Study on Fish Biodiversity of Upper Lake, Bhopal, M.P, India

Soumyadeep Panda, Shriparna Saxsena, Mahendra Kumar Yadav — Tue, 23 Jun 2026 00:00:00 +0000

Understanding the ecological importance of fish is fundamental, particularly because of their role in sustaining healthy aquatic ecosystems. Fish communities, including habitat-associated species, are directly influenced by local habitat features and function as important components of aquatic food webs. They contribute to nutrient cycling, prey-predator dynamics and ecosystem stability. The present study investigates the fish biodiversity and water-quality parameters of Upper Lake (Bhoj Wetland), Bhopal, Madhya Pradesh, India. The wetland showed moderate water-quality conditions in relation to anthropogenic activities, including the inflow of domestic sewage, urbanisation and encroachment in the catchment area. The study focused on three sampling sites, namely S1, Van Vihar Site (Shymala Hills); S2, Manav Sangrahalaya; and S3, VIP Apartment Housing Society, Khanugaon. The results indicated a total of 28 fish species belonging to 10 orders and 13 families. Species diversity was assessed using diversity indices that captured both species richness and evenness. Evenness describes variation in the relative abundance of species within a community. Statistical analyses were performed using Microsoft Excel and Species Diversity and Richness (SDR). The ichthyofaunal diversity of Upper Lake comprised ten orders, with dominance of Cypriniformes, represented by five families and 15 species, followed by Siluriformes, represented by three families and eight species. Cypriniformes (45%) was the dominant order, and the family Cyprinidae showed the highest diversity and abundance, including major carps and barbs. Biodiversity indices varied among the three study sites during the winter season. Site S2 exhibited the highest overall species diversity, with a Shannon-Wiener index (H’) of 2.45 and a Simpson’s index of diversity (1-D) of 0.85. Conversely, Site S1 yielded the lowest diversity indices (H’ = 2.095; 1-D = 0.80), despite showing the highest standardised species richness value (0.75) among the sampled locations. Future studies should use advanced ecological modelling to analyse shifting community dynamics at the sampling sites.

Evaluation of the Physico-chemical and Bacteriological Quality of Well Water along the Tilé River in N’Zérékoré, Guinea

Tue, 23 Jun 2026 00:00:00 +0000

Water resources used for domestic purposes require continuous quality assessment, particularly in urban areas where surface water and shallow groundwater are exposed to domestic effluents, solid waste and runoff. This study evaluated the physico-chemical and bacteriological quality of well water along the Tilé River in the urban commune of N’Zérékoré, Guinea. The investigation was based on direct site observation and laboratory analyses of water samples collected from riverside wells and the Tilé River across nine districts. A total of 180 samples were analysed, comprising 10 well-water samples and 10 river-water samples per district. The measured parameters included temperature, pH, dissolved oxygen, colour, total dissolved solids, electrical conductivity, turbidity, total coliforms and faecal coliforms. The results were compared with World Health Organization guideline values for drinking water. Well-water temperatures ranged from 25.7°C to 26.1°C, whereas river-water temperatures ranged from 27.2°C to 27.7°C. The pH showed marked spatial variation, with acidic conditions recorded in Bellevue (3.52) and a higher value in Kwitiapoulou (7.79). Conductivity and total dissolved solids were generally higher in wells than in the river, indicating stronger groundwater mineralisation. In contrast, turbidity and colour were more pronounced in the Tilé River, with particularly high values in some districts. Bacteriological results indicated contamination by total and faecal coliforms, with concentrations ranging from 4 to 2,200 CFU/100 mL in the reported samples. These findings indicate that the Tilé River and adjacent wells are vulnerable to physico-chemical variation and faecal contamination. The water should not be consumed without appropriate treatment, and regular monitoring is required to support safer local water use.

Evolving Research Dynamics at the Climate–Migration Nexus: A Global Bibliometric Analysis (1995–2024)

Mriganka Barman, Chandan Hazarika — Tue, 23 Jun 2026 00:00:00 +0000

Climate change is increasingly recognized as a critical driver of human mobility, with environmental stressors such as droughts, flooding and sea-level rise shaping migration patterns globally. Despite substantial scholarly attention, research on climate-induced migration remains fragmented across disciplines and geographies. This study provides a comprehensive bibliometric analysis of global literature on climate-induced migration from 1995 to 2024, employing 1,980 publications retrieved from the Dimensions database. Analytical methods included performance analysis, co-authorship network mapping, source citation analysis, institutional collaboration profiling, and keyword co-occurrence mapping, implemented via Biblioshiny and VOSviewer. Results reveal a marked surge in research output post-2019, with the United States, United Kingdom, and Germany dominating publication volume and citation impact. India ranks fourth in output but exhibits limited international collaboration. Key intellectual clusters are identified around prominent scholars such as Clark Gray, Robert McLeman, and Caroline Zickgraf. Keyword analysis highlights central themes including “displacement,” “drought,” and “livelihood,” reflecting the field’s focus on rural vulnerability and adaptive capacity. Thematic evolution indicates a shift from deterministic “environmental refugee” narratives toward household-centered adaptation frameworks and climate justice paradigms. The study underscores structural disparities between empirical foci in the Global South and intellectual authority in the Global North, proposing pathways to foster South-South collaborations and integrate mobility research into climate adaptation policies. Findings provide a systematic taxonomy of climate-migration scholarship, supporting evidence-based policy-making and guiding future interdisciplinary research.

Dynamics of Biological Resource Use and Conservation Challenges within the Yaka Community of Kasongo-Lunda, Kwango Province, DRC

Thu, 25 Jun 2026 00:00:00 +0000

Biodiversity management in the Democratic Republic of Congo is situated at the intersection of Indigenous knowledge, livelihood needs and conservation requirements. In Kingulu, Kwango Province, the conservation practices and uses of biological resources within the Yaka community remain insufficiently documented. This study aimed to identify the biological resources used locally, describe their food, medicinal and socio-cultural uses, analyse the contribution of traditional knowledge to sustainable management, evaluate land-cover dynamics and propose conservation strategies adapted to the local context. The study combined direct and participatory observation, household surveys, interviews with key informants, biological inventories and remote-sensing analysis of land-use change from 2001 to 2025. Data were collected from 217 households and 100 key informants in selected villages located near forest, savannah and collection areas. The findings show that biological resources support food, health, cultural practices, household income and local environmental governance. Remote-sensing analysis indicates a decline in forest cover from 30.33% in 2001 to 26.94% in 2025, despite a temporary increase to 31.17% in 2013. Local observations also indicate increasing scarcity, and in some cases local disappearance, of species reported by respondents, including Encephalartos laurentianus, Loxodonta cyclotis and Pan troglodytes. The main pressures identified include extensive agriculture, hunting, deforestation, overfishing, felling of host trees and unsustainable harvesting practices. Although Yaka traditional knowledge supports staggered harvesting, domestication, livestock keeping, aquaculture, protection of sacred forests and respect for designated collection sites, these practices remain challenged by poverty, weak management mechanisms and changing environmental conditions. The study highlights the need for integrated conservation approaches that combine community knowledge, ecological monitoring and locally appropriate governance.

Evaluation of Water Pollution Index using Physicochemical Characteristics in Coastal Water of Sutrapada, Gujarat, India

Thu, 25 Jun 2026 00:00:00 +0000

Water quality in coastal environments is influenced by natural processes and human activities, and regular assessment is needed to support sustainable management. This study evaluated the water quality status of the Sutrapada coastal waters, Gujarat, India, using physicochemical characteristics and the Water Pollution Index (WPI). Surface water samples were collected monthly from five sampling stations from June 2025 to January 2026. Fourteen physicochemical characteristics, namely temperature, pH, salinity, dissolved oxygen, biochemical oxygen demand, turbidity, electrical conductivity, total hardness, total dissolved solids, total suspended solids, total solids, ammonia, phosphate and nitrate, were analysed using standard methods and compared with seawater quality standards.

The results showed seasonal variation associated with climatic conditions, freshwater inflow, tidal fluctuations and anthropogenic activities. The pollution index values were below unity for most characteristics, including temperature (0.9996), pH (0.9888), salinity (0.9765), dissolved oxygen (0.9996), biochemical oxygen demand (0.8692), turbidity (0.9595), electrical conductivity (0.9860), total hardness (0.6340), total dissolved solids (0.9720), total suspended solids (0.9333), total solids (0.9809) and ammonia (0.7778). However, phosphate (1.0513) and nitrate (1.0551) exceeded unity, indicating nutrient enrichment.

The overall WPI value of 0.9356 classified the Sutrapada coastal waters as moderately polluted. The findings provide baseline information for continued water quality monitoring and sustainable coastal management.

Spatial Trend and Geostatistical Prediction of Water Quality Index in the Pra River Basin of Ghana

Frank B. K. Twenefour, Henry Otoo, Eric Neebo Wiah, Emmanuel Ayitey — Fri, 26 Jun 2026 00:00:00 +0000

Reliable spatial prediction of river water quality is essential in mining-affected river basins where pollution varies across space. This article examined the spatial behaviour of the Water Quality Index (WQI) in the Pra River Basin system of Ghana and compared the performance of inverse distance weighting (IDW), ordinary kriging (OK), and co-kriging (CK) for WQI interpolation. The study used 150 sampling points distributed across the Birim, Offin, and Pra basins, and WQI was derived from pH, total suspended solids (TSS), total dissolved solids (TDS), and electrical conductivity (EC). Spatial trend was assessed using Kendall’s tau, distributional skewness was reduced using the Yeo-Johnson transformation, and interpolation performance was evaluated using cross-validation metrics including RMSE, MAE, and R². Results showed a statistically significant positive spatial trend in WQI (Kendall’s τ = 0.2612, p < 0.001), confirming non-stationarity. The Yeo-Johnson transformation substantially reduced skewness from 0.4797 to 0.0276 at λ = -0.3611. Among the interpolation methods, ordinary kriging produced the best predictive performance (RMSE = 0.6782, MAE = 0.5103, R² = 0.5370), outperforming both the best IDW configuration and co-kriging. The findings show that spatially structured WQI data in the Pra Basin are better modelled with variogram-based geostatistical methods than with deterministic interpolation alone. Ordinary kriging therefore produced the best relative performance among the interpolation methods tested and is suitable for basin-scale WQI mapping in the study area, although further improvement may be achieved by incorporating additional spatial covariates and trend-explicit models.

Drivers of Urban PM₂.₅ Pollution in Ouagadougou, Burkina Faso: Evidence from STIRPAT, ARDL, LMDI and Tapio Analysis

Mon, 29 Jun 2026 00:00:00 +0000

This study investigates the socioeconomic drivers of urban fine particulate matter (PM₂.₅) in Ouagadougou, Burkina Faso, over the period 2000–2024 using an integrated analytical framework that combines STIRPAT modelling, ARDL cointegration analysis, Environmental Kuznets Curve (EKC) testing, logarithmic mean Divisia index (LMDI) decomposition and Tapio decoupling analysis. The objective is to identify the relative contributions of population dynamics, urbanisation, motorisation, biomass energy use, income growth and total energy consumption to long-term changes in air pollution exposure. Annual PM₂.₅ concentrations were derived from satellite-based estimates calibrated against regional retrievals, while socioeconomic variables were compiled from national statistical and international databases.

The results indicate that annual mean PM₂.₅ increased from 41.7 to 56.5 µg m⁻³ during the study period, remaining substantially above WHO guideline values. Econometric analysis reveals severe multicollinearity in the full STIRPAT specification; therefore, a parsimonious model is required. In this model, motorisation is the most robust and statistically significant driver of pollution. ARDL bounds testing supports a stable long-run relationship between PM₂.₅, motorisation and biomass energy use, with motorisation showing a long-run elasticity of approximately 0.20. EKC analysis indicates a U-shaped relationship, with the turning point lying outside the observed income range, suggesting no evidence of income-driven environmental improvement within the sample period. LMDI decomposition identifies population growth and urban expansion as the dominant contributors, partially offset by declining per-capita biomass intensity. Tapio decoupling analysis shows weak decoupling between income and emissions throughout the study period.

Overall, the findings suggest that transport-sector growth, particularly motorisation, was the most robust long-term correlate of PM₂.₅ exposure within the available dataset, with implications for targeted urban air quality management policies.

Assessment of Rainfall Variability, Meteorological Drought Characteristics and Agricultural Implications Using SPI, Rainy Days and Trend Analysis in Hyderabad, India

K. Nagaraju, Deepak Rati, R. P. Ahirwar, Rita Kapil Narvariya, Umesh Singh — Mon, 29 Jun 2026 00:00:00 +0000

Background: Rainfall variability and meteorological drought are major concerns in semi-arid regions such as Hyderabad, where agricultural planning and water-resource management depend strongly on the amount and distribution of monsoon rainfall.

Aims: This study assessed rainfall variability, meteorological drought characteristics and agricultural implications in Hyderabad, India, using the Standardized Precipitation Index (SPI), rainy-day analysis, the Mann–Kendall trend test and Sen’s slope estimator.

Study Design: A quantitative climatic data analysis was conducted using historical rainfall records.

Place and Duration of Study: Hyderabad, Telangana, India, using daily rainfall data for the period 2003–2024.

Methodology: Daily rainfall observations obtained from the India Meteorological Department were aggregated to monthly and annual scales. SPI values were computed to identify wet and dry conditions and to classify drought severity. Annual rainy days, defined as days with measurable rainfall of at least 2.5 mm, were used to examine rainfall distribution. The Mann–Kendall test and Sen’s slope estimator were applied to assess the direction, significance and magnitude of rainfall-related trends.

Results: Rainfall conditions showed marked inter-annual variability during 2003–2024. Of the 22 years analysed, 12 years (54.55%) had dry conditions (SPI < 0), while 10 years (45.45%) had wet conditions (SPI > 0). Moderate drought occurred in 2 years (9.09%), and no severe drought events were identified. The Mann–Kendall analysis indicated a positive but statistically non-significant SPI trend (p > 0.05), while Sen’s slope showed a marginal increase of about +0.01 SPI units per year. Annual rainy days varied from 47 to 102 days, indicating considerable variability in rainfall frequency and distribution.

Conclusion: Hyderabad experienced recurrent dry years and substantial rainfall variability rather than a clear long-term wetting or drying trend. The findings highlight the need for climate-resilient crop planning, efficient water management, drought preparedness and improved use of climate information in rainfed and water-sensitive agricultural systems.

Spatio-temporal Analysis of Land Use and Land Cover Dynamics using Multi-temporal Landsat Imagery in the Dantiwada Watershed, Gujarat, India

Mon, 29 Jun 2026 00:00:00 +0000

Land use and land cover (LULC) change is an important indicator of landscape transformation and provides useful information for watershed planning and natural resource management. This study assessed spatio-temporal changes in LULC in the Dantiwada watershed, Gujarat, India, using multi-temporal Landsat satellite imagery for 2002, 2013, and 2024. Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI datasets were processed and classified using the Iterative Self-Organising Data Analysis Technique (ISODATA), an unsupervised classification approach. Five major LULC classes were identified: waterbody, barren land, built-up area, dense vegetation, and vegetation. Post-classification comparison was used to quantify the area and percentage distribution of each class across the 22-year study period. The results showed a marked reduction in barren land from 73.70% in 2002 to 58.22% in 2013 and 45.76% in 2024. Vegetation increased from 18.50% to 28.65% and 33.13%, while dense vegetation increased from 5.70% to 10.07% and 15.97% during the same period. The combined vegetation and dense vegetation classes increased from 24.20% in 2002 to 49.10% in 2024. Built-up area increased from 1.10% to 3.45%, and waterbody area increased from 1.00% to 1.69%. The findings indicate a substantial shift from barren land towards vegetated land cover within the Dantiwada watershed and provide baseline information for watershed-level land resource planning and long-term monitoring.

Spatiotemporal Variability of Compound Heat Drought Events in Sahel Region

Fredy Edson Mhenzi, Philemon Henry King’uza, Innocent John Junior — Tue, 30 Jun 2026 00:00:00 +0000

Compound heat-drought events (CHDEs) represent an important climate-related hazard in semi-arid regions, where high-temperature extremes and precipitation deficits can occur simultaneously and intensify environmental and socioeconomic stress. This study investigated the spatiotemporal variability of CHDEs across the Sahel during the June-September season for the period 1990-2020. Daily mean air temperature and daily precipitation data from ERA5 reanalysis were used to identify high-temperature extremes (HTEs) and low-precipitation extremes (LPEs) based on percentile thresholds. HTEs were defined using the 90th percentile of daily temperature, whereas LPEs were defined using the 25th percentile of daily precipitation. CHDEs were identified when both extremes occurred concurrently at the same grid cell and time step. Trend magnitudes were estimated using Sen's slope estimator, statistical significance was assessed using the Mann-Kendall test, and dominant modes of variability were examined using empirical orthogonal function analysis. The results showed that HTEs were most frequent over the northern Sahel, while LPEs occurred mainly across the northern and central Sahel. The highest frequencies of CHDEs were found over the southern and central Sahel. HTEs increased across much of the northern and eastern Sahel, whereas LPE trends showed spatial heterogeneity. CHDE trends were spatially mixed, with localised increases in parts of the central and northeastern Sahel. The leading empirical orthogonal function mode explained 33.4% of the total variance and indicated broad regional variability, with a tendency towards increased events in recent years. These findings highlight the importance of monitoring compound climate extremes for climate risk assessment and adaptation planning in the Sahel.

Assessment of Metal Pollution in Water and Sediments in Gold Mining Areas in Mayo, Dalalang, Forage and Vounbiyao in Mayo Kebbi-Ouest, Chad

Thu, 02 Jul 2026 00:00:00 +0000

Artisanal gold mining can affect aquatic and sedimentary environments through the mobilisation and discharge of metallic elements. This study assessed metal pollution in water and sediments from four gold mining sites in Gamboké, Mayo Kebbi-Ouest, Chad, namely Mayo, Dalalang, Forage and Vounbiyao. Wastewater and sediment samples were collected from the study sites and analysed by atomic absorption spectrometry to determine the concentrations of Hg, Cd, Pb, Ni, Co, Zn, Mn and Fe. Mercury was determined using a hydride generator coupled to atomic absorption spectrometry. Sediment quality was evaluated using the geoaccumulation index, enrichment factor, contamination factor, degree of contamination and ecological risk index, while water concentrations were compared with the standards used in the study. The results showed marked metal contamination, particularly by Hg and Cd. In sediments, Hg and Cd had the highest geoaccumulation values, while Pb, Ni, Fe, Zn and Mn generally showed negative Igeo values. The enrichment factor indicated very high enrichment of Hg and Cd, with the highest mercury enrichment at Mayo. The degree of contamination was very high at Mayo and moderate at Vounbiyao, Forage and Dalalang. Water samples contained elevated Hg, Cd, Pb, Ni and Fe concentrations, with mercury exceeding the reference limit at all sites. The findings indicate that artisanal gold mining contributes to metal pollution and requires mitigation measures to reduce environmental and health risks.

Seasonal Dynamics of Water Temperature and Dissolved Oxygen in Wular Lake, Kashmir: Evidence of Weak Dissolved Oxygen–Temperature Relationships in a Himalayan Wetland

Thu, 02 Jul 2026 00:00:00 +0000

Wular Lake is a high-altitude freshwater wetland in the Kashmir Himalaya that experiences strong seasonal variation in physicochemical conditions. This study assessed seasonal changes in water temperature and dissolved oxygen across 20 sampling sites during summer, autumn, winter and spring, yielding 80 observations. Both variables were measured on site at each sampling location. Water temperature was recorded using a mercury-in-glass thermometer, and dissolved oxygen was measured using a portable dissolved oxygen meter. Seasonal differences were evaluated using one-way analysis of variance followed by Tukey post hoc comparisons, while Pearson correlation and simple linear regression were used to examine the relationship between water temperature and dissolved oxygen. Water temperature varied significantly among seasons, with the lowest mean value in winter (4.90 ± 1.62 °C) and the highest in summer (24.01 ± 2.70 °C). Dissolved oxygen also differed significantly among seasons, ranging from 7.31 ± 1.66 mg/L in autumn to 9.82 ± 1.19 mg/L in summer. The pooled temperature-dissolved oxygen relationship was weak and non-significant (r = 0.085, p = 0.452; R² = 0.007), indicating that temperature alone did not explain dissolved oxygen variability across the annual cycle. Seasonal analysis showed a significant negative relationship only in spring 2025 (r = -0.502, p = 0.024), while summer, autumn and winter showed no significant correlations. The relatively high summer dissolved oxygen values despite elevated temperature suggest that site-level oxygen dynamics may be influenced by processes other than solubility alone. One autumn observation of 4.20 mg/L fell below the 5.0 mg/L threshold recommended for sustaining aquatic life (USEPA, 1986), indicating a localised low-oxygen condition requiring attention. These findings demonstrate that the classical temperature-dissolved oxygen solubility relationship was weak in this biologically productive Himalayan wetland and support the need for direct seasonal dissolved oxygen monitoring rather than reliance on temperature as a proxy indicator in Ramsar-designated freshwater ecosystems of the Kashmir Himalaya.

Land Use Dynamics and Ecosystem Services in the Municipality of Dogo, Niger

Thu, 02 Jul 2026 00:00:00 +0000

Wetlands in the Sahel provide important ecosystem services for rural communities, but their functioning is increasingly influenced by land-use change and climate variability. This study assessed land-use dynamics, rainfall patterns, and perceived ecosystem services in the rural municipality of Dogo, Zinder Region, Niger. Socioeconomic information was collected from 93 respondents in four villages along the Korama Valley using a questionnaire on ecosystem services and local environmental change. Land-use changes were analysed using Landsat images from 1986 and 2025, while rainfall and temperature data were used to describe climatic variability and projected relationships with selected ecosystem services. The results show that provisioning services are the most frequently recognised by local populations. Among food-related uses, cereal crops were cited most often, with a citation rate of 75%, followed by fruits, vegetables, and tubers. Land-use analysis indicated an expansion of rain-fed cropland from 31.11% of the municipal area in 1986 to 78.14% in 2025. Wooded steppe declined from 43.57% to 10.79%, and bare land decreased from 23.13% to 2.35%. Settlements increased from 0.25% to 3.40%, while wetlands increased from 1.93% to 5.30%. Annual rainfall ranged from 291.8 mm to 918.2 mm, with an increasing trend after 2013. Regression results suggest that rainfall is associated with changes in wetlands, carbon storage, pollination, and wooded steppe, although the strength of these relationships varies by scenario. The findings indicate that land-use conversion, demographic pressure, and climatic variability jointly influence ecosystem services in Dogo.

Indian Agriculture in Green House Gases Emission and Voluntary Carbon Market-emerging Scenario and Challenges

P. A. Lakshmi Prasanna, B. Sreedevi, Nirmal Karan — Thu, 02 Jul 2026 00:00:00 +0000

Agriculture is an important source of greenhouse gas emissions in India and also offers mitigation opportunities through sustainable land use and carbon market mechanisms. This study examines Indian agriculture’s position in greenhouse gas emissions and the voluntary carbon market using secondary data from national and global databases. It analyses emission trends from 1970 to 2024 and voluntary carbon credit issuance up to 2025, with specific attention to 2009–2024, when agricultural carbon credits from India became available in the voluntary market. The results show that India’s total greenhouse gas emissions increased from 733.24 Mt CO₂e in 1970 to 4371.17 Mt CO₂e in 2024, while agricultural emissions increased from 402.79 Mt CO₂e to 805.43 Mt CO₂e. However, agriculture’s share in India’s total greenhouse gas emissions declined from 54.93% to 18.43%, mainly because emissions from other sectors grew faster. During 2009–2024, agriculture contributed 21.68% of India’s cumulative greenhouse gas emissions but accounted for only 0.20% of carbon credits issued in the voluntary carbon market. This indicates a substantial emission-credit gap. The study identifies carbon credit pricing, demand from compliance and voluntary markets, measurement and verification costs, additionality, farmer participation and institutional design as key factors shaping agricultural carbon markets in India. Policy support, transparent market mechanisms, credible monitoring systems and inclusive farmer-level institutions are required to strengthen the role of agriculture in climate change mitigation and sustainable transition.

Variations in Environmental Parameters inside a Polyhouse during Two Growing Seasons of Hydroponic Basil

Fri, 03 Jul 2026 00:00:00 +0000

Hydroponic cultivation under protected structures requires regular monitoring of internal environmental conditions because crop performance is influenced by seasonal changes in the polyhouse microclimate. The present study evaluated variations in temperature, relative humidity and carbon dioxide (CO₂) concentration inside a naturally ventilated polyhouse during hydroponic basil (Ocimum basilicum L.) cultivation at Dr NTR College of Agricultural Engineering, Bapatla, Andhra Pradesh, India. The crop was grown using the Nutrient Film Technique (NFT), and environmental parameters were recorded with a Rotronic CP11 handheld instrument at 1-hour intervals. Observations were made during Season 3 (October-November) and Season 4 (January-February) to compare the environmental behaviour of the polyhouse across two growing periods. The recorded data showed clear seasonal variation in the internal microclimate. During Season 3, temperature ranged from 25.64°C to 34.04°C, relative humidity ranged from 65.05% to 90.56% and CO₂ concentration ranged from 411.91 to 463.66 ppm. During Season 4, temperature ranged from 24.15°C to 32.05°C, relative humidity ranged from 63.96% to 85.23% and CO₂ concentration ranged from 446.42 to 545.17 ppm. Basil yield was higher in Season 3 (38.9 kg) than in Season 4 (36.2 kg). The comparatively lower yield during Season 4 was associated with lower temperature, reduced light intensity, shorter day length and higher relative humidity during winter, which affected photosynthesis, nutrient uptake and vegetative growth. The findings provide a seasonal basis for interpreting microclimatic variation in the studied hydroponic production system. The study indicates that continuous monitoring and regulation of temperature, relative humidity and CO₂ concentration are important for maintaining a favourable microclimate for hydroponic basil production under polyhouse conditions.

Assessment of Avian Diversity in Miyawaki Micro-Forest Plantations of Yadadri Bhuvanagiri District, Telangana, India

D. Ananda Shiny, Bochu Jeevan, M. Mamatha, K. Kumaraswamy — Sat, 04 Jul 2026 00:00:00 +0000

Aims: To assess bird diversity in the Yadadri Forest Model, Yadadri Bhuvanagiri District, Telangana. Three plantations established in 2018, 2019, and 2022 were evaluated at a spacing of 1 m × 1 m.

Place and Duration of Study: Yadadri Bhuvanagiri District, Telangana, during 2022–2023.

Methodology: During the study period from January 2022 to June 2023, bird visits to the micro-forest plantations established at 1 m × 1 m spacing were documented monthly through visual observations. The resulting data were used to calculate relative abundance, species richness, species diversity, and species evenness.

Results: The relative abundance of the Common crow varied across the three plantations, with 6.86% in Plantation 1, 10.76% in Plantation 2, and 11.70% in Plantation 3. House sparrow had relatively high abundance in Plantations 1 and 2, at 9.42% and 7.89%, respectively. Rufous treepie showed the lowest occurrence across the plantations, with values of 0.00% in Plantations 1 and 2 and 0.45% in Plantation 3. Plantation 2 had the highest species evenness (0.98), whereas Plantation 1 had the highest species diversity (3.06), indicating variation in bird composition and community structure among plantations.

Conclusions: Bird diversity and composition, including habitat, IUCN status, and feeding habits, were recorded at the same micro-forest spacing. The bird community included 10 omnivores, 10 insectivores, 4 granivores, 3 carnivores, 3 frugivores, and 1 herbivore.

Standardization of Fertigation Scheduling of Mango under North Gujarat Conditions

M. V. Patel, C. J. Joshi, Piyush Verma, P. C. Joshi — Sat, 04 Jul 2026 00:00:00 +0000

A field experiment was conducted at the Horticultural Instructional Farm, Sardarkrushinagar Dantiwada Agricultural University, Gujarat, India, during 2020-23 to standardise fertigation scheduling for mango under North Gujarat conditions. The experiment was carried out on cv. Kesar. The experiment included four treatments: T₁, 100% recommended dose of fertiliser through fertigation; T₂, 80% recommended dose of fertiliser through fertigation; T₃, 60% recommended dose of fertiliser through fertigation; and T₄, 100% recommended dose of fertiliser through soil application. The recommended dose was 750:160:750 g N:P:K per plant per year. The treatments were replicated five times, and fertigation was applied in four equal splits during the first week of October, February, March and April. Observations were recorded on fruit physical characteristics, yield and quality parameters. The pooled results showed that application of 100% recommended dose of fertiliser through fertigation produced the highest fruit diameter (6.15 cm), fruit weight (214.49 g), fruit yield (59.88 kg plant⁻¹ and 5988.06 kg ha⁻¹), total soluble solids (19.16 °Brix), reducing sugar (4.25%) and total sugar (13.06%). The 80% recommended dose through fertigation was often statistically comparable with the 100% fertigation treatment for selected fruit and quality traits. The lowest yield was generally recorded with 60% recommended dose through fertigation. The findings indicate that fertigation with the full recommended dose of NPK in four split applications improved mango yield and selected quality attributes under the experimental conditions. This schedule may be considered for mango cultivation under similar North Gujarat conditions, subject to local soil, water and orchard management practices.