Assessing the water productivity using remote sensing data and WATPRO model, Case study of wheat lands of the Jiroft plain

In recent years, climate change and rising global water demand as a result of population growth has caused water scarcity. In this regard, calculation of agricultural water productivity in order to optimize the management of water resources and reduce the water consumption is essential. One of the promising methods for this purpose is remote sensing. In this research, a functional and fully satellite-based model that called WATPRO was used for direct calculation of agricultural water productivity and its evaluation in the Jiroft plain located in Kerman province. For this aim, Landsat8 satellite imagery were acquired during the growing season of wheat on 2016-2017 years and after necessary image preprocessing, the WATPRO model was implemented. The deployment peak, cultivation and harvesting time for six divided field were determined by using the time series of Normalized Deference Vegetation Index (NDVI) extracted from satellite imagery, then wheat water productivity was calculated and the results were evaluated with ground control points. The results shows that the highest and lowest water productivity for wheat in this area is 0.4 and 0.8 kg m-3, respectively and the average of water productivity in the study area was estimated around 0.5 kg m-3. Also the correlation coefficient of 76.5% was found between average NDVI and water productivity in this area. Assessing the accuracy of the WATPRO model with the measured water productivity at field show that this model perform well for estimation and mapping water productivity with an RMSE and correlation coefficient of 0.16 kgm-3 and 85% respectively.