Role of Earth Observation (EO) Technologies in Dryland Management towards Adaptation to Climate Change

Abstract

The use of climate information must be applied in developing sustainable practices for dryland management as climatic variation is one of the major factors contributing to or even a trigger to land degradation and diversified farming. Rainfall and temperature are the prime factors in determining the climate and therefore the distribution of vegetation types. There is a strong correlation between rainfall and biomass since water is one of key inputs to photosynthesis. It is essential to understand how climate induces and influences the land management in drylands. Simulation of crop production from dryland regions had several difficulties due to temporal and spatial variability in rainfall, high evapotranspiration rates and heterogeneity in land use. Advances in space-based Earth Observation (EO) technology and its applications have potential for improving the cultivation practices, and thus transforming the quality of human life indirectly. High resolution spatial and temporal satellite data from Indian satellites like RESOURCESAT-1 and CARTOSAT-1 are now available for creating various resource layers on 1:10,000 scale. This scale suffices the requirement of decentralized planning at grass root level. Overlay of cadastral boundaries will help in generating information in greater detail. Any change in land utilization pattern as well as hotspot areas due to climate change impact can be identified and monitored using multi temporal EO data. This paper is based on a technology demonstration for smart rainwater harvesting with the help of EO data. A case study was carried out in a cluster of 50 villages in Jodhpur and Barmer districts of Rajasthan to assess climate change variability and adaptation to it. It also identifies the potential sites for rainwater harvesting and also to assess the volume of harvestable rainwater with the help of remote sensing and GIS techniques. Daily rainfall and temperature data of the study area was analyzed to study their profile and variability. The high resolution satellite data were used to delineate land use/land cover, waste lands, land degradation and surface water bodies, etc. The integration of above thematic layers resulted in identification of potential rainwater harvesting sites at village level and also in calculating the volume of rainwater than can be harvested from a given field. The studies point to the importance of smart infield rainwater harvesting in drylands for food security, safe drinking water, introduction of agrohorticulture, agroforestry practices and high value crops for livelihood generation and achieving long term sustainability of local and regional populations. Key words: Rainwater harvesting sites, digital elevation model, earth observation data and climate change.