Advanced Land use Classification Considering Intra-annual Cropping patterns and Urbanization processes as a Contribution to Improve Knowledge base for Water Management.

Abstract:

Land use and its spatial pattern and dynamics strongly influence water resources and water demand. Therefore, integrated water resources management coordinating water supply and demand is using modeling tools in order to assess the impact of land use changes on the water balance and to conceive infrastructural and operational measures to cope with these impacts. As a consequence, the appropriateness of water management measures depends on the reliability of the output gained by the modeling tools which in turn is highly determined by the capability of the models and the quality of model inputs.

This research combines the Soil and Water Assessment Tool (SWAT) and an advanced procedure for spatio-temporal detection of land use dynamics and irrigation in the Upper Kharun basin in the Chhattisgarh State in India. An on-screen visual digitization technique using the Landsat satellite images and their derivatives (NDVI and tasseled cap indices) were employed for land use classification. The land use maps prepared at different time steps within a year can be combined to produce a single multi-temporal land use classification. This approach captures and integrates all the major variations within a year in a single map and hence better represents an area with multiple crop rotations and different levels of urbanization.

Urbanization and intensification of irrigation by increasing use of groundwater are major land use processes at the global scale as well as in the study region. The study reveals that an increasing pumping rate of groundwater for irrigation is the main reason for decreasing the groundwater contribution to streamflow and subsequently a lowering in discharge and water yield. On the other hand, annual surface runoff is increased significantly by an expansion in built up areas over the decades in the study area.

This information (i) enhances the understanding of land use changes and their relevant drivers, and (ii) facilitates the introduction of best water and land use management practices.