Evaluation of the Relationship between Rainfed Fig Orchards Yield and Effective Precipitation using Remote Sensing Datasets

Document Type : Research Paper

Authors

1 M.Sc. Student, Department of Water Engineering, Faculty of Agricultural Technology, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran

2 Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Iran

3 Soil and Water Research Institute, Agricultural Research, Education and Extension Organization., Karaj, Iran

4 Department of Water Engineering, Faculty of Agricultural Technology, College of Agriculture and Natural Resources, University of Tehran, Tehran, Iran

10.22059/jwim.2024.372488.1146

Abstract

Appropriate precipitation can play a crucial role in providing soil water content in rainfed fig orchards. Meanwhile, one of the main problems in most rainfed agriculture areas is the unavailability of rainfall data, which satellite rainfall datasets can help to solve this problem. The area investigated in this research is rainfed fig orchards of Estahban and the rainfall data of the meteorological station located in the area was applied for different periods of time. In this research, first, the relationship between yield and distribution of precipitation values in different time scales (monthly, seasonal and annual) was determined. Then the amount of satellite-derived rainfall was found using the rainfall datasets (i.e. CHIRPS, ERA5, ERA5-Land, GPM, PERSIANN and GSMaP) and based on these values, the amount of effective rainfall was calculated using different methods including USDA, ET-Rainfall, and Dependable Rain for the time period range between 2005 and 2021. Results showed, the rainfall in the months of April and then in May and November has had the greatest effect on improving the yield of the crop. Additionally, it is recommended supplemental irrigation events at the beginning of spring to provide higher soil water content for fig orchards in drought conditions. Based on the analyzed statistical criteria, it can be said that GPM was the most suitable dataset and USDA was the best effective rainfall method among the investigated methods in the area.

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