Modelling spatiotemporal land dynamics for a trans-boundary river basin using integrated Cellular Automata and Markov Chain approach

Nowadays, trans-boundary natural systems are facing land management issues due to conflicts of two territories. Thus, land dynamics information has great importance to understand the consequences of natural resources at spatial and temporal scales. In this study, spatiotemporal LU/LC modelling approach has been emphasized to address land resource problems of a trans-boundary river basin of Central India using satellite imagery data. An integrated Cellular Automata (CA)-Markov Chain (MC) model was employed over the Betwa River basin (BRB), located in Madhya Pradesh and Uttar Pradesh States, facing agriculture and water resource management issues. The spatiotemporal LU/LC pattern during 1972-2013 has been elaborated to focus changes in agriculture and waterbody area. Historical LU/LC analysis shows that 4.16% area under agriculture was accrued due to increased 1.62% waterbody in the BRB. However, after the year 2007 agriculture area is accrued by 1.75% mainly due to irrigation water availability from newly accomplished Rajghat reservoir. Further, the CA-MC model has been firstly validated, and then successfully employed to predict future LU/LC maps for the years 2020, 2040, 2060, 2080 and 2100. Future analysis shows that vegetation pattern may alter in future due to decline in dense forest (1.39%) and agriculture area (6.41%), which cease to increase in degraded forest and barren land by 4% and 4.23%, respectively. The modelling results depicted that 0.71% decrement in waterbody and subsequent decrease in the agriculture area by 6.41% could occur in future. The present study reveals that, changes in future LU/LC may lead to severe reduction in food productivity land of Central India. Therefore, it is evoked that integrated CA-MC modelling approach can interactively predict future LU/LC scenarios by furnishing some solutions to the current land resources problems.