Prediction and monitoring of LULC shift using cellular automata-artificial neural network in Jumar watershed of Ranchi District, Jharkhand

Jumar watershed of Ranchi district is agrarian in nature. The unplanned and exponentially growing urban sprawl has become one of the probable threats in achieving sustainable development goals (SDG-15). The purpose of this research study is to monitor the urban sprawl in Jumar watershed within three decades i.e. from the year 1990 to 2021. Land use land cover (LULC) change has been monitored using satellite data from LANDSAT (4, 5 and 8). Various indices are calculated like normalised difference vegetation index (NDVI), normalised difference built-up index (NDBI), normalised difference water index (NDWI) and built-up index (BUI) to monitor LULC change in the area. For prediction of urban sprawl, cellular automata and artificial neural network (CA-ANN) with GIS application technique is used. The model is validated by using Kappa coefficient. The prediction results showed increase in built-up area by 8.23 sq. km in the next decade. The built-up and barren land together increase up to 42.85 sq. km by 2030 and 34.61 sq. km in 2021. The NDVI for 3-decade period showed significant decrease in the healthy vegetation and increase in sparse vegetation. The NDBI showed a slight increase in urban area but massive increase in uncultivated and barren land. NDWI showed a decrease in area of the surface water. The LULC studies showed a major shift from healthy vegetation to agriculture and then to barren land. To assess the impact of urbanisation on water quality, water samples are taken seasonally from J1to J11 sampling locations and are analysed as per APHA procedure. The sites are classified as urban, semi urban and rural area as per their location. The water quality index (WQI) varied between 42.14 to 61.42 during pre-monsoon, 62.20 to 68.7995 during monsoon and 43.48 to 60.12 during post-monsoon. The quality of water is found poor in all seasons at all sampling sites. The water is found highly turbid and alkaline throughout the year. Overall, it can be concluded that the water needs to be pre-treated for drinking purposes throughout the year. Graphical abstract