Satellite data maps Gujarat’s changing water body trends
Sentinel-2 & Normalised Difference Water Index used to measure shifts
Kachchh shows gains; Saurashtra sees water loss
Study aids climate adaptation and resource planning efforts
A recent study published in the Journal of Geography, Environment and Earth Science International highlighted the use of the Normalised Difference Water Index (NDWI) with Sentinel-2 satellite data to monitor changes in surface water across Gujarat between 2020 and 2024.
NDWI is a widely used remote sensing tool that identifies surface water bodies by comparing green and near-infrared light in satellite images, effectively highlighting water-covered areas. Sentinel-2, a high-resolution satellite operated by the European Space Agency, provides the spatial and temporal accuracy required for detailed water body monitoring over time.
The study, led by Nirav K Pampaniya and Duda B Balas, research associates in forest resource management at the College of Forestry, Navsari Agricultural University, analysed high-resolution satellite imagery to detect and measure changes in lakes, ponds, rivers and wetlands across various regions of Gujarat.
To assess these changes, the authors used Sentinel-2A and 2B satellite images from May 2020 and May 2024, obtained via the Copernicus Data Space. The data was processed and analysed using Google Earth Engine and ArcMap 10.8.2.
The NDWI was calculated using the green band (Band 3, 560 nanometers wavelength) and the near-infrared band (Band 8, 842 nanometers wavelength) to enhance the detection of open water features.
NDWI exploits the contrast between the high reflectance of water in the green band and its low reflectance in the near-infrared band. A threshold value was applied to classify pixels as water or non-water. Sentinel-2’s five-day revisit time and multi-spectral capabilities enabled reliable, high-resolution monitoring of surface water dynamics.
Sentinel-2 imagery, featuring 10-meter spatial resolution and 13 spectral bands, is highly effective for mapping various land cover types, including vegetation, water bodies, urban areas and soil.
The red and near-infrared bands facilitate vegetation monitoring, while the shortwave infrared bands enable detection of water bodies, wetlands and soil moisture.
Sentinel-2 data accurately identifies surface features such as reservoirs, rivers and ponds, aligning well with ground observations. Its comprehensive spectral and spatial capabilities make Sentinel-2 a valuable tool for natural resource management, particularly in monitoring and mapping water bodies using NDWI.
After applying their analysis, the authors found significant regional differences in water spread changes across Gujarat. In Middle Gujarat, Anand district showed notable progress with a 52.17 square kilometres increase in water area, driven by pond desilting, construction of check dams and improved monsoon water management. Satellite images confirmed this positive trend.
Meanwhile, the nearby Panchmahal district experienced a 7.6 sq km decline as many small tanks dried up and groundwater recharge efforts lagged, illustrating how effective planning leads to better water outcomes.
In North Gujarat, Banaskantha gained 21.35 sq km of water spread, while Aravalli lost 21.58 sq km, where mining and deforestation disrupted natural water flow and dried borewells, highlighting the importance of land use alongside rainfall.
Saurashtra showed mixed results. In the Bhavnagar district, the water spread increased by 32.39 sq km, likely due to enhanced water harvesting and reservoir maintenance, whereas Rajkot lost 30.67 sq km because of urban expansion and shrinking catchments. In Saurashtra, all districts except Bhavnagar, Surendranagar and Botad exhibited a decrease in the area of water bodies.
Coastal districts like Jamnagar and Morbi also saw water area losses, potentially threatening agriculture and local ecosystems. In South Gujarat, Bharuch recorded the highest gain of 66.08 sq km, benefiting from riverfront development and smart irrigation, but Tapi district lost 44.54 sq km despite good rainfall, underscoring that rainfall alone cannot ensure water availability.
Kachchh, a desert region, was the biggest surprise with a 746.87 sq km increase in water spread, mainly due to improved satellite detection of seasonal wetlands and special efforts in local water conservation practices such as bunds and harvesting. The outcome for the Kachchh area might require validation against real-world data due to the presence of ocean water and marshy land.
According to Duda B Balas, researcher at Navsari Agriculture University, also author of the study, the methodology used to assess water bodies in Gujarat (excluding the Kachchh region) can be replicated in other Indian states, provided that cloud-free satellite imagery is available and the water bodies are clearly visible. Ground-truthing through field visits or using platforms like Google Earth Pro is essential to ensure data accuracy. The study utilised freely available satellite data, with a spatial resolution of 10 metres; however, higher-resolution imagery is recommended for more precise analysis.
The findings, which cover the period from 2020 to 2024, are valuable for water resource planning at both district and village levels and can support national initiatives on water conservation and recharge.
Sandeep Pandey, associate professor at the Gujarat Institute of Disaster Management (GIDM), endorsed the methodology, highlighting the effectiveness of satellite-based tools such as NDWI. He emphasised the importance of integrating remote sensing with field validation and local knowledge to enhance the accuracy and reliability of assessments.
The observed changes — water gains in Kachchh and declines in Saurashtra — demonstrate the impact of land use, climate variability and water management practices, offering key insights for effective planning and climate adaptation.
In the context of climate change, Gujarat’s diverse geography calls for tailored water management strategies rather than a one-size-fits-all approach. Decision-makers should combine local knowledge with scientific evidence and advanced geospatial technologies, such as satellite remote sensing and GIS, to accurately monitor water bodies, track land use changes and assess ecosystem health.
Geospatial tools help identify water scarcity hotspots, predict flood risks, and evaluate conservation efforts. By providing real-time data and spatial analysis, these technologies enable precise, adaptive planning. Integrating geospatial insights with community expertise supports sustainable water use and strengthens resilience against climate variability and extreme weather events.