Role of Sar Data in Water Body Mapping and Reservoir Sedimentation Assessment

Abstract

<p><strong>Abstract.</strong> Reservoir sedimentation is the major problem, due to it every year the reservoir capacity is lost to considerable amount. Surveying for assessment of the reservoir by conventional approach is time and money consuming. Geospatial technology provides ample opportunity in this field through the availability of high resolution satellite data from sensors such as Sentinel, Indian Remote Sensing Satellite, Landsat, and SPOT have been used to calculate the water spread area of the reservoir. However, due to presence of cloud in most of the optical data during onset of monsoon, the water spread at the lowest reservoir level could not be mapped. In turn the revised capacity or sedimentation is generally assessed between either below full reservoir level (FRL) or above maximum draw down level (MDDL). Nowadays, the microwave synthetic aperture radar (SAR) data at reasonable spatial resolution is available freely in public domain. Moreover, microwave data has capability to penetrate cloud and the information below cloud can easily be retrieved. To overcome the issues related to optical data, in the present study, the reservoir sedimentation for Ghataprabha reservoir was estimated using SAR data. Sentinel-1A data was used to delineate the water spread area for the water year of 2016–17. The original live storage capacity (1974) was estimated to be 1434.14<span class="thinspace"></span>Mm<sup>3</sup> at FRL 662.940<span class="thinspace"></span>m by the authorities using the hydrographic survey during the commissioning of the reservoir in the year 1974. The live storage capacity was found out to be 1366.14<span class="thinspace"></span>Mm<sup>3</sup> at FRL, however, as per original elevation-area-capacity curve the live capacity is around 1262.404<span class="thinspace"></span>Mm<sup>3</sup> at 660.50<span class="thinspace"></span>m. Estimated live storage capacity from Remote sensing approach (2016–17) was assesses as 1182.5<span class="thinspace"></span>Mm<sup>3</sup> at 660.51<span class="thinspace"></span>m. The storage capacity has reduced from 1262.40<span class="thinspace"></span>Mm<sup>3</sup> (1974) to 1182.51<span class="thinspace"></span>Mm<sup>3</sup> i.e. around 171.732<span class="thinspace"></span>Mm<sup>3</sup>. As per present analysis the rate of sedimentation is around 4<span class="thinspace"></span>Mm<sup>3</sup>/yr. It was realized that using the SAR microwave data, the revised capacity of the reservoir from its near MDDL to FRL could be assessed through remote sensing approach.</p>

Sedimentation mapping in shallow shoreline of arid environments using active remote sensing data

“…5) and the overlaid sedimented pixels conducted from the crisis image in Fig. 6 (Billa and Pradhan 2011;Prasad et al 2018). The total sedimented area in the archive image was counted to be 1706 km 2 , while in the crisis image, the sedimentation of the sea was calculated to cover an area of 4630 km 2 .…”

Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications

“…As an example, Reference [208] reported that many reservoirs in the Yatenga region in Burkina Faso lost more than 50% of their original capacity in a time frame of 25 years. Reference [225] exploited Sentinel-1 SAR images and elevation data to study the Ghataprabha reservoir (India) and estimated a sedimentation rate of about 4 Mm 3 /year since its construction made in 1974. The continuous monitoring of this phenomenon is therefore essential for an effective management of water resources, especially in areas characterized by chronical water scarcity.…”

Training, Education, Research and Capacity Building Needs and Future Requirements in Applications of Geospatial Technology for Water Resources Management

“…In the last 50 years, ever since the launch of Landsat in 1970s, and IRS in 1990s, the efforts are made to include/integrate GST with traditional methods of WRM by, using RS based Land Use Land Cover (LULC) map, generation of soil map and Digital Elevation Model (DEM) for estimating runoff potential and soil erosion of an area (Garg et al, 2012), ground water potential mapping, soil erosion, sediment yield and reservoir sedimentation assessment (Lilhare et al, 2014, Rawat et al, 2017, Foteh et al, 2018Prasad et al, 2018), watershed delineation using DEM, economic and hydrologic evaluation of watershed management plans (Rao et al, 1994;Sharma and Thakur, 2007), flood and drought mapping, monitoring and damage assessment (Thakur and Sumangala, 2006; Corresponding author 2014, 2017), snow cover and glacier mapping and monitoring (Joughin et al, 2010;Kulkarni et al 2010;Bhambari and Bolch, 2011;Kumar et al, 2011;Thakur et al, 2012;Aggarwal et al, 2014;Nikam et al, 2017;Thakur et al, 2017a,b), irrigated area and irrigation infrastructure mapping and monitoring (Roy et al, 2010;Nikam and Aggarwal, 2012;NRSC, 2018), irrigation water and supply requirement (Durga Rao et al, 2001), assessment of land use land cover & climate change impact on water availability (Aggarwal et al, 2012;Aggarwal et al, 2016;Garg et al, 2017;Nikam et al, 2018). Most of these applications are driven by optical RS till mid-1990s, and addition of active Microwave (MW) remote sensing after mid-1990's and early 2000, with launch of ERS-1, 2 and Radarsat series of satellites (Britannica-2018, www.britannica.com/topic/list-of-satellites-2024625).…”