Scarcity of rainfall and limited irrigation water resources is the main challenge for agricultural expanding policies and strategies. At the same time, there is a high concern to increase the area of wheat cultivation...Scarcity of rainfall and limited irrigation water resources is the main challenge for agricultural expanding policies and strategies. At the same time, there is a high concern to increase the area of wheat cultivation in order to meet the increasing local consumption. The big challenge is to incerese wheat production using same or less amount of irrigation water. In this trend, the study was carried out to analyze the sensitivity of wheat yield to water deficit using remotely sensed data in El-Salhia agricultural project which located in the eastern part of Nile delta. Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) were extracted from Landsat 7. Water Deficit Index (WDI) used both LST minus air temperature (Tair) and vegetation index to estimate the relative water status. Yield response factor (ky) was derived from relationship between relative yield decrease and relative evapotranspiration deficit. The relative Evapotranspiration deficit was replaced by WDI. Linear regression was found between predicted wheat yield and actual wheat yield with 0.2?6, 0.025, 0.252 and 0.76 as correlation coefficient on 30th of Dec. 2012, 15th of Jan. 2013, 16th of Feb. 2013 and 20th of Mar. 2013 respectively. The main objective of this study is using a combination between FAO 33 paper approach and remote sensing techniques to estimate wheat yield response to water.展开更多
文摘Scarcity of rainfall and limited irrigation water resources is the main challenge for agricultural expanding policies and strategies. At the same time, there is a high concern to increase the area of wheat cultivation in order to meet the increasing local consumption. The big challenge is to incerese wheat production using same or less amount of irrigation water. In this trend, the study was carried out to analyze the sensitivity of wheat yield to water deficit using remotely sensed data in El-Salhia agricultural project which located in the eastern part of Nile delta. Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) were extracted from Landsat 7. Water Deficit Index (WDI) used both LST minus air temperature (Tair) and vegetation index to estimate the relative water status. Yield response factor (ky) was derived from relationship between relative yield decrease and relative evapotranspiration deficit. The relative Evapotranspiration deficit was replaced by WDI. Linear regression was found between predicted wheat yield and actual wheat yield with 0.2?6, 0.025, 0.252 and 0.76 as correlation coefficient on 30th of Dec. 2012, 15th of Jan. 2013, 16th of Feb. 2013 and 20th of Mar. 2013 respectively. The main objective of this study is using a combination between FAO 33 paper approach and remote sensing techniques to estimate wheat yield response to water.
