Assessment of Flood-Emanated Impediments to Kaziranga National Park Grassland Ecosystem—A Binocular Vision with Remote Sensing and Geographic Information System
276Kaziranga National Park (KNP), a UNESCO World Heritage Site, harbors one of the last unmodified natural grasslands of Northeast India. The park has proudly been the humble abode of two remarkable megaherbivores, the great Indian rhino and the elephant, and also provides a prime habitat for the Royal Bengal Tiger. It is a haven to various economically important graminoids. Each year, KNP’s grassland ecosystem encounters a battle with flood affecting its plant and animal components. Remote sensing and geographic information systems can offer a binocular viewpoint for regular assessment of the park’s flood-prone areas, which will contribute to long-term conservation practices and better natural resource management of its grassland ecosystem.
Natural disasters are the leading causes of natural and private property damage. They also lead to long-term adverse effects on biodiversity of the damaged area. Water-related hazards are responsible for about 90% of all natural hazards. Flood is a frequent event in the lower catchment of the Brahmaputra where KNP is situated. The park’s land cover has ~74% of grasslands (excluding river and other water bodies), making it a unique habitat for great Indian one-horned rhino. Flood has adversely affected the park’s alluvial grassland, which emerged as one of the leading causes of the inundation of the vast grasslands causing habitat degradation and fragmentation. Habitat loss is one of the significant threats to the biodiversity. As flood always disrupts the natural habitat, it unfailingly impacts the rhino feeding habitat, which consequently takes a considerable time for recovering its preflood biodiversity status. According to the red list category of the International Union for Conservation of Nature and Natural Resources, the rhino comes under the vulnerable B1ab (iii) category and, hence, the annual impact of the flood on its prime feeding habitat (grasslands) is a matter of grave concern.
In the research reported in this chapter, different remotely sensed data sets such as SARAL/AltiKa, Landsat 8, and Sentinel 1A were used to assess the flood situation of the park during August 2017. SARAL/AltiKa was used to obtain the water level of that Brahmaputra River, Landsat 8 OLI data were used for making the park’s land use and land cover (LULC), and Sentinel 1A was employed to detect the study area’s flood situation. The advantages of integrating real-time assessment data for better management of the park’s grassland ecosystem are thoroughly discussed.