A Markovian and cellular automata land-use change predictive model of the Usangu Catchment

Usangu Catchment, in Tanzania, is vital for its rice production in which more than 30% of Tanzanian rice is grown. The catchment is a part of the Southern Agricultural Corridor of Tanzania where major agricultural intensification is expected to take place. Given the role of this catchment, it is important to investigate the effect of agricultural intensification, land-use/land-cover (LULC) change and climate variability on water balance in the catchment. Thus, the objective of the study was to simulate Usangu Catchment’s LULC of 2020 based on LULC of 2000, 2006 and 2013 using Markov Chain and Cellular Automata Analysis.Social, edaphic, climatic and landscape geomorphology factors governing the LULC change and distribution were used to prepare LULC suitability maps in geographical information system.The relative importance of LULC change factors was determined using the analytic hierarchy process and aggregated using weighted linear combination under multi-criteria evaluation approach. The model was validated using simulated and observed LULC 2013. The standard kappa coefficient (κ-standard) and overall agreements of the model were 0.6776 and 0.9125, respectively. The error due to quantity is 0.0243 while error due to allocation is 0.0667. The simulated LULC 2020 scenario shows the increase in urban area by 8.2% and a major decrease in forestland and shrubs by 20.6% and 6.9%, respectively. About 19.6% grassland and 8.5% of agricultural land in 2013 will be converted to urban land by 2020. On the other hand, about 372.0 km2 (10.4%) of wetlands and 368.2 km2 (10.3%) of woodlands will be converted to agricultural land. The 2020 LULC simulation model of Usangu developed in this study provide some useful information for future LULC scenarios and data for water balance models and preparation of future ecological conservation plans.