Abstract
Understanding the rate and process of land-use/land-cover (LULC) change in a watershed is essential for managing natural resources and achieving sustainable development. Therefore, this study aims to analyze historical LULC change from 1980 to 2010 and project future changes in 2030, 2060, and 2090 in the Guanting Reservoir Basin (GRB), China, a critical water-supplying watershed for China’s capital Beijing, through scenario-based simulations. Two LULC scenarios, ‘business-as-usual’ and ‘governance’ (Gov), were projected using the Cellular Automata-Markov (CA–Markov) model. Historical LULC trend analysis shows that built-up land increased from 2.6% in 1980 to 5.26% in 2010, while cropland, grassland, and water body decreased. LULC conversion analysis indicates that, in general, grassland, cropland, and woodland were converted to built-up area from 1980 to 2010. The BAU scenario projects a dramatic increase in built-up area, rising from 2296.98 km2 (5.26%) in 2010 to 11,757.35 km2 (26.93%) in 2090 at the expense of cropland and grassland areas. Conversely, the Gov scenario predicts an increase in water body, woodland, and grassland, encouraging sustainable development. Overall, these results provide useful inputs to the LULC planners and water resources managers to elaborate on eco-friendly policies and regulations for GRB.
Highlights
Watersheds are dynamic systems by nature; they change constantly [1]
KIA showed a good result for all LULC categories, ranging from 0.60 to 0.92 for the built-up and water body classes, respectively
The results provide clear evidence that cellular automata (CA)–Markov can predict future LULC in Guanting Reservoir Basin (GRB)
Summary
Watersheds are dynamic systems by nature; they change constantly [1]. The simulation and analysis of land-use/land-cover (LULC) change in hydrology are essential, as they help to understand its totality [2]. The above studies provide significant insight into the processes, causes, and consequences of land-use and land-cover change dynamics under socioeconomic development in Northern China. Most of these studies investigated the historical and future land cover changes in the other study areas or used different models [13,15,16,17,18,19]. The CA–Markov model is a hybrid of the CA and Markov models They are suitable for LULC change detection and predictions [23,24] because they take into consideration the spatial and temporal components of land-cover dynamics [25]. It is a robust technique that can simulate complex systems, making it the best fit to project the LULC change in GRB
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
