Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

Regional-Scale Assessment and Simulation of Land Salinization Using Cellular Automata-Markov Model

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  RRV12110,  ASABE/CSBE North Central Intersectional Meeting. (doi: 10.13031/2013.41320) @2012
Authors:   Zhulu Lin, De Zhou, Liming Liu
Keywords:   Cellular automata model, Salinity assessment, Salinization and desalinization, Spatial pattern analysis, Yinchuan Plain

Land salinization or its reversion, desalinization, is a complex process affected by both biophysical and human-induced driving factors. Conventional approaches to land salinization assessment and simulation are either too time consuming or focused only on biophysical factors. The cellular automata (CA)-Markov model is well suited for regional-scale assessment and simulation since both biophysical and socioeconomic data can be efficiently incorporated into a GIS framework. Through a case study of Yinchuan Plain in northwest China we demonstrated that the CA-Markov model can be effectively used to model the spatial and temporal dynamics of the salt- affected landscape changes caused by the underlying salinization/desalinization process. Our research showed that Yinchuan Plain had been in the process of desalinization in the past ten years when the salt-affected lands decreased about 11%, mainly due to the construction and improvement of irrigation and drainage channel networks. CA-Markov model performed better in simulating salt-affected landscape changes when accounting for both biophysical and human-induced driving factors that affected the land salinization/desalinization processes in Yinchuan Plain. The CA-Markov model simulation results showed that the desalinization trend in Yinchuan Plain would continue into the future. By 2015, the total salt-affected lands would be further reduced to about 26.7 %. Our findings not only shed light on the causes behind the salt-affected landscape changes in Yinchuan Plain in the past decade, but also established the CA-Markov model as a promising tool for land salinization assessment and simulation at a regional scale.

(Download PDF)    (Export to EndNotes)