Watershed Monitoring Application for Sub-watersheds of Lower Palar River Reach Using Remote Sensing Data and Google Earth Engine Platform

Watershed monitoring is critical for long-term water resource management, drought measures, and flood mitigation planning. Based on satellite data and a cloud-based platform, this study aimed to deploy a web-based application to monitor the sub-watersheds of the lower Palar River reach, which drain part of the Chengalpattu and Kanchipuram districts that are rapidly urbanizing. The geophysical parameters, terrain characteristics, meteorological parameters, and hydrological components of the watersheds were extracted from satellite data in this study. The satellite data was analyzed using the predefined algorithms through the advanced GIS tool Google Earth Engine (GEE). Much research is currently being conducted on revealing surface water potential and fluctuation monitoring using remotely sensed geospatial data and GIS tools. However, the traditional method involves collecting a large number of satellite-sensed images taken from the study area and then processing them in GIS software. The GEE is working on the cloud server, which is dedicated to the processing of satellite image data using machine learning code. GEE does not require image saving or collection, which are simple analyses of satellite data and mapping capabilities. The current study is intended to overcome technical limitations by providing a near real-time, cloud-based, and simple method for mapping hydrological components. Following that, a web-based application was created to provide access to geographical information to the government and other stakeholders. The dynamics of agricultural areas and townships and the state of the stream drainage system were identified without a site inspection. Post-flood information will be monitored, and it should direct the earliest and most beneficial relief operations. By selecting the flood event from the dropdown menu, users can obtain the extent of the flooded area. The web-based watershed monitoring application was deployed successfully.