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Determining the Optimal Irrigation Pattern in Agricultural Areas Using a Combination of Remote Sensing Data and the Development of a Lump Soil Moisture Model

Noori, Amir Hossein | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55471 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Danesh-Yazdi, Mohammad
  7. Abstract:
  8. The purpose of this study is to introduce a new indicator to estimate the amount of irrigation water in excess of the need and also to determine the optimal irrigation pattern to reduce water loss in agriculture. According to the Food and Agriculture Organization of the United Nations, the major loss of fresh water takes place in agriculture, and the reduction of water resources is more significant in developing countries that do not have advanced agricultural equipment. One of the challenges in the studies related to reducing the amount of water used in agriculture is a lack of knowledge on the spatial distribution and temporal changes in water loss in a region. Although estimation of actual evapotranspiration rate with remote sensing has been an important step in estimating the amount of water loss in an area, the limitation of these methods in terms of disrespectin antecnedent soil moisture condition has caused errors in estimating the amount of excess irrigation. In this study, a new indicator has been introduced to estimate the amount of excess irrigation water, which has been directly quantified using information related to porosity, plant wilting point, pre-irrigation moisture and post-irrigation moisture. Soil moisture content before and after irrigation has been determined by developing an integrated soil moisture model. In the next step, with the aid of the developed model and the use of meteorological data, the net plant water requirement was estimated, and the optimal irrigation model in an agricultural area was also presented. The most important output of the analysis was to identify areas prone to damage due to insufficient irrigation and also to identify periods of no need for irrigation. In order to explain the efficiency of this method, the Miandoab study area, which is one of the most important agricultural areas of this basin, has been selected as the case study. This research was investigated in two SMAP sensor pixels with different conditions. The results show that the availability of water sources has a great effect on the amount of irrigation. In the first pixel, due to the presence of the river and the availability of water, the average irrigation was 1131 mm, and in the second pixel, where water resources are limited, the amount of irrigation reached 1036 mm in the sugar beet fields. In the first pixel, 217 mm and in the second pixel, 258 mm, the excess of irrigation has been calculated
  9. Keywords:
  10. Irrigation ; Remote Sensing ; Soil Moisture ; Water Resources Management ; Sustainable Development ; Integrated Model ; Water Conservation

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