Publications

Flood Risk in India’s Arid Ramsar Wetlands: Integrating Extreme Rainfall, Fuzzy Risk Assessment, and CMIP6 Projections

A Socio-Technical Framework for Assessing Flash Drought Risks to Key Biodiversity Areas: A Scientists' Warning

Flash droughts, characterized by their rapid onset and intensification, pose significant risks to biodiversity and local populations, with extensive impacts on ecosystems and agriculture. This study presents a comprehensive framework to quantify flash drought risk across Key Biodiversity Areas (KBAs) in India from 1979 − 2021. By combining hazard, vulnerability, and exposure components, we found that 45.8 % of KBAs fall within the high-risk category, with inland forest areas and national parks showing higher vulnerability than coastal regions. Analysis of 42 freshwater KBAs revealed that 73.8 % face moderate to high risk from flash droughts, while significant correlations were observed between risk index and trends in tree cover loss and wildfire events. The average flash drought duration across KBAs was 34 days, with October being the most frequent onset month (18 %). Our findings indicate that high-risk areas with extensive cropland, such as the Jawaharlal Nehru Bustard Sanctuary (8316 km2), face substantial agricultural vulnerability where flash droughts could lead to rapid crop failure, affecting food security and local livelihoods. The study also revealed that proximity to large water bodies provides some protection against flash droughts, as coastal and marine protected areas mostly showed lower risk levels. These results emphasize the urgent need for targeted conservation strategies and policy reforms to address the challenges posed by flash droughts. Our framework provides a valuable tool for prioritizing conservation efforts and developing resilient ecosystem management plans in the face of increasing climate-related challenges.

Policy Recommendations and Future Directions

No abstract is provided for this article.

Review of: "Spatio-Temporal Analysis of Precipitation Patterns in Xinjiang Using TRMM Data and Spatial Interpolation Methods: A Comparative Study"

Potential competing interests: No potential competing interests to

Technology–Policy Interface for Combating Forest Loss and Fires

No abstract is provided for this article.

Key Biodiversity Areas (KBAs)

No abstract is provided for this article.

Application of Water Accounting Plus Framework for the Assessment of the Water Consumption Pattern and Food Security

No abstract is provided for this article.

Heatwave magnitude impact over Indian cities: CMIP 6 projections

No abstract is provided for this article.

Protecting wetlands for future generations: A comprehensive approach to the water-climate-society nexus in South Asia

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine

Wetlands are one of the most critical components of an ecosystem, supporting many ecological niches and a rich diversity of flora and fauna. The ecological significance of these sites makes it imperative to study the changes in their inundation extent and propose necessary measures for their conservation. This study analyzes all 64 Ramsar sites in China based on their inundation patterns using Landsat imagery from 1991 to 2020. Annual composites were generated using the short-wave infrared thresholding technique from June to September to create inundation maps. The analysis was carried out on each Ramsar site individually to account for its typical behavior due to regional geographical and climatic conditions. The results of the inundation analysis for each site were subjected to the Mann-Kendall test to determine their trends. The analysis showed that 8 sites exhibited a significantly decreasing trend, while 14 sites displayed a significantly increasing trend. The accuracy of the analysis ranged from a minimum of 72.0% for Hubei Wang Lake to a maximum of 98.0% for Zhangye Heihe Wetland National Nature Reserve. The average overall accuracy of the sites was found to be 90.0%. The findings emphasize the necessity for conservation strategies and policies for Ramsar sites.

Water Resource Management Studies at Micro Level Using Geospatial Technologies

A Techno‐Societal Framework for Quantifying the Risk of Heavy Rainfall Events Over Ramsar Wetlands

Abstract Wetlands are often found in depressions or around rivers, lakes, and coastal seas, where they periodically flood. Hence, this study presents a new techno‐societal framework for quantifying the risk of heavy rainfall events (HREs) on wetland ecosystems and surrounding communities in India. By integrating advanced technological approaches such as Bayesian analysis, fuzzy logic, and remote sensing with societal considerations, we provide a comprehensive assessment of wetland vulnerability to climate change impacts. An effort has been made to understand the non‐stationarity of HREs, inundation patterns of wetlands, impact evaluation, and future precipitation trends (CMIP6). The overall assessment of the extreme precipitation indices indicated that return periods were highest for Thane Creek, followed by Bhoj Wetland. We also assessed the risk index based on the parameters of hazard, vulnerability, and exposure for all wetlands using the fuzzy logic approach. The overall risk index evaluation indicated that Bhoj Wetland, Thane Creek, Point Calimere, Deepor Beel, Sasthamkotta Lake, and Vembannur Wetland are at “very high” risk. The study also investigated inundation patterns of critical “very high” risk wetlands and conducted an impact evaluation for the Bhoj Wetland, highlighting the influence of HREs on infrastructures, human settlements, and ecosystems. Wetlands such as Point Calimere, Vembannur Wetland, Karikili Bird Sanctuary, Vendanthangal, and Vaduvur Bird Sanctuary showed a significantly increasing trend in precipitation for both historical and future SSP2‐4.5 scenario. These findings are useful in decision‐making for policymakers to adopt the best practices to manage the local wetlands wisely.

Key Biodiversity Areas and Forest Cover Loss

No abstract is provided for this article.

Key Biodiversity Areas and Stable Night Lights

No abstract is provided for this article.

High-resolution landfill characterization using SAR remote sensing and cloud-based processing

Abstract Solid waste management in developing countries such as India faces persistent challenges due to weak monitoring systems and the absence of reliable reporting mechanisms for landfill statistics. To address this gap, this study develops a remote sensing methodology that integrates Python programming with the Sentinel Application Platform (SNAP) to generate Digital Elevation Models (DEMs) from Sentinel-1 synthetic aperture radar (SAR) imagery for quantifying landfill characteristics. Key parameters, including waste height and volumetric estimates, were extracted from satellite observations and processed through Google Earth Engine (GEE), enabling efficient large-scale analysis. A total of 80 landfill sites distributed across India were examined, providing the first nationwide assessment of landfill volume using a uniform and replicable framework. Field validation was conducted at two representative sites, Gondiya Landfill and Ujjain Ring Road Trenching Ground, through drone surveys and Differential Global Positioning System (DGPS) measurements. The evaluation showed deviations of 21.12% and 0.12% in height, 0.7% and 0.65% in area delineation, and 20.21% and 0.8% in volume for Gondiya and Ujjain, respectively, confirming the reliability of the proposed approach. These results demonstrate that SAR-based DEMs offer a cost-effective and scalable solution for systematic, near real-time monitoring of landfills across large regions. The framework not only supports capacity planning, environmental assessments, and policy formulation but also provides a pathway for developing countries to transition toward data-driven waste management strategies in the context of rapid urbanization and increasing waste generation.

Enhancing Sustainable Development through Spatiotemporal Analysis of Ramsar Wetland Sites in South Asia

The ecological significance of wetlands makes it imperative to study changes in their inundation extent and propose necessary conservation measures. Monitoring wetland dynamics and implementing strategies to protect these essential ecosystems is crucial for maintaining the balance of natural systems. This study used pre-processed Landsat imagery (1991–2020) to generate yearly composites and produce inundation maps based on an automated Short-Wave Infrared thresholding technique within the Google Earth Engine platform. The analysis was executed on individual wetlands to describe their typical condition owing to regional climatic and geographical circumstances. The Mann-Kendall test was used to understand the trends in the change of inundation extent. The thresholding method achieved an overall accuracy of 89.0 %, with average dry and wet Producer's accuracies of 90.6 % and 86.6 %, respectively. The accuracy was higher for open water lakes compared to wetlands with complex vegetation dynamics. The trend analysis revealed that 46 sites follow an increasing trend, while the remaining 43 sites were found to be decreasing. Among these 43, 12 sites were found to be significantly decreasing, with the Upper Ganga River showing a maximum decrease of about 59 % in the inundation extent. Factors such as elevation, precipitation, temperature, and climate type were found to influence the trends in wetland inundation. Wetlands at high altitudes (>4000 m) and those receiving less than 500 mm of annual precipitation were more likely to exhibit decreasing trends. Coastal wetlands showed varying trends, with five increasing and three significantly increasing. The findings of this study provide valuable insights into the relationship between sustainable development and wetland conservation, supporting the Ramsar Convention's goals and the UN's Sustainable Development Goals. The individualized analysis of Ramsar sites enables the development of localized management strategies, climate change adaptation, and informed policy-making, ultimately contributing to the sustainable use of these critical ecosystems in South Asia.

Pathways to Build Resilience Toward the Impact of Climate Change on the Indian Sunderban

No abstract is provided for this article.

Are rapid onset drying events escalating forest fires across India’s ecoregions?

Abstract Rapid onset drying events are emerging as a critical driver of ecological vulnerability across India's diverse landscapes. This study investigated the relationship between these accelerated drying phenomena of flash droughts (FDs) and forest fire occurrence across 43 Indian ecoregions from 1979 to 2023, revealing patterns of escalating forest fire risk. We employed a four-criteria methodology based on the Evaporative Stress Ratio (ESR) to identify and characterize FD events. The criteria included temporal duration (minimum 30 days), severity (SESR ≤ 20th percentile), intensification rate (ΔSESR ≤ 40th percentile), and mean intensification (ΔSESRz ≤ 25th percentile). Our analysis uncovered significant regional variations in event frequency, with mountainous regions showing vulnerability - the Karakoram-West Tibetan Plateau alpine steppe experienced 31 rapid drying events, while the Eastern Himalayan broadleaf forests recorded only 10 events. The temporal analysis revealed clear seasonal patterns, with June being the primary onset month in 17.8% of ecoregions, followed by January and October, each dominating 14% of regions. Critically, 79.1% of ecoregions showed increasing forest fire trends from 2001 to 2023, with the Orissa semi-evergreen forests displaying significant vulnerability. High-altitude and semi-arid regions showed statistically significant positive correlations between rapid drying frequency and fire incidents (r = 0.68, p = 0.002 in Karakoram-West Tibetan Plateau alpine steppe; r = 0.59, p = 0.004 in Thar desert), suggesting that accelerated moisture depletion creates conditions conducive to fire outbreaks in these vulnerable ecosystems. Most ecoregions experienced these drying events for 1-2% of the study period, indicating that even brief episodes of rapid desiccation can trigger lasting ecological impacts. These findings highlight the urgent need for integrated drought-fire management strategies that account for the unique challenges posed by rapid onset drying events in different ecological contexts.

Spatiotemporal analysis of Imja Lake to estimate the downstream flood hazard using the SHIVEK approach

Climate change is causing glaciers in the Himalayas to recede and shrink. The changing climate is the primary trigger of the expansion of glacial lakes tha