Research on Wetlands

Saline lakes occupy 44% and 23% of the volume and area of all lakes that are tending to suffer from extended dryness, reduced hydro period, or complete desiccation by 2025. The current study is conducted on Sambhar Salt Lake, the largest inland saline Ramsar site of India, contributing to 9.86% of the total salt production. The lake is under threat due to illegal salt pan encroachment, losing brine worth 300 million USD. The objective was to identify the key drivers that affect the lake at a landscape level. Geospatial modelling was conducted for 96 years (1963–2059) at a decadal scale, integrating ground data (birds-soil-water). Land Use Land Cover (LULC) classification was conducted using CORONA aerial imagery of 1963, along with Landsat imageries, using supervised classification for 1972, 1981, 1992, 2009, and 2019, and future prediction for 2029, 2039, 2049, and 2059. Further, images were classified into 8 classes that include the Aravalli hills, barren land, saline soil, salt crust, salt pans, wetland, settlement, and vegetation. Past trends show a reduction of wetland from 30.7 to 3.4% at a constant rate (4.23%) to saline soil, which subsequently seemed to increase by 9.3%, increasing thereby the barren land by 4.2%, salt pans by 6.6%, and settlement by 1.2% till 2019. Future predictions show a loss of 40% wetland and 120% of saline soil and a net increase of 30% for vegetation, 40% for settlement, 10% for salt pan, 5% for barren land, and a net loss of 20%, each by Aravalli Hills and salt crust. Additionally, the ground result shows its alteration and reduction of migratory birds from 3 million to 3000. In light of the UN Decade on Ecosystem Restoration (2021–2030), restoration strategies are suggested; if delayed, more restoration capital may be required than its revenue generation.

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Lakes are sensitive to environmental changes, and lakes globally are increasingly being negatively impacted by algal blooms due to climate change, rapidly increasing populations and unsustainable utilization of water resources. Remote Sensing (RS) techniques present the opportunity to manage and protect water resources. RS applications offer researchers and policymakers the opportunity to carry out synoptic, consistent, repetitive, detailed, and cost-effective assessments of water quality on a spatiotemporal scale compared with point-based in situ measurements. Measurement of Water Quality Parameters (WQPs) with RS satellite sensors can be performed at a great distance, i.e., several hundred to thousands of miles, which helps in the coverage of large areas on the ground and can observe water surfaces repeatedly. 

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The use of satellite images saves users a huge sum of money that would have been spent on field or laboratory work. The use of satellite images and improved statistical and mechanistic modelling of WQPs has been performed at local, watershed, and regional scales with a high degree of accuracy. These models can also effectively enhance the real-time detection of hydrological variability, which is key in providing early warnings and rapid responses to harmful algal bloom events. RS sensors capture spectral signatures of water constituents, which makes them an effective tool for the estimation of different WQPs, including TSS and chlorophyll-a concentration. Several WQPs have been monitored with these techniques. Some of these parameters include TDS or salinity, SS, chlorophyll-a concentration, turbidity, surface water temperature, cations, and anions. Salinity distribution can also be determined by microwave radiometers.

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Several WQPs have been monitored with these techniques. Some of these parameters include TDS or salinity, SS, chlorophyll-a concentration, turbidity, surface water temperature, cations, and anions. Salinity distribution can also be determined by microwave radiometers. Different RS sensors have been reportedly used in the estimation of WQPs, including Landsat 5, 7, and 8 Operational Land Imager (OLI) sensors, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, and Sentinel-2A/B Multispectral Instruments (MSI). These sensors have been used extensively to effectively quantify various parameters, including but not limited to chlorophyll-a concentration, turbidity, TSS and total phosphate.

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