Study of irrigation effect wastewater on soil salinity by using satellite image ( case study : Birjand treatment)
A severe shortage of water resource in south Khorasan province caused, water resource managements use waste water for irrigation agriculture lands. Soil salinity is one of the pervasive phenomena in the word that due to its adverse effects on the growth of plants and the final product has become one of the main challenges in the field of natural resource management. In this study attempted to investigate effects of long-term irrigation with wastewater of Birjand refinery on soil salinity characteristic, taken effective step to inhibit this phenomenon and, more importantly, management and conservation of water resources. Since evaluating effects of irrigation with wastewater on soil salinity requires access to soil salinity information before and after constructing the refinery building, and we have no information about soil salinity in the past, so to finding out soil salinity information in the past year’s, the option of using satellite images was selected. For this purpose, satellite images of the study area were downloaded from USGS site, and using PCI-Geomatica software bands of Landsat satellite merged together to create one image that is prepared for studying. Because satellite image contains raw information and hard to interpretation alone, so using some soil salinity indices is required for reach this goal. With an assessment of correlation between gathered information from different soil salinity indices and actual EC amounts, it was found that SI-1 with root square equal to %84 have the most correlation with actual amounts of EC values. Then with making a meaningful relation between this salinity index and EC can achieve a comprehensive relationship to extract data related to soil salinity obtained from satellite images. Results of this study represented that irrigation with waste water generally have not devastating effects on soil salinity and in most cases caused decreasing about 3% to 5% of soil salinity in sampling points.
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Using Remote Sensing Data and Machine Learning Methods to Estimate Changes in Hyrcanian Forests along the Southern Coasts of the Caspian Sea
Mahdi Afraz, Davoud Omarzadeh, Mobin Eftekhari *, Mostafa Yaghoobzadeh, Ali Haji Elyasi
Journal of Land Management, -
Impact of Vapor Pressure Deficit on Saffron Yield and Its Prediction Using Artificial Intelligence Algorithms
Elham Ghochanian Haghverdi *, Mostafa Yaghoobzadeh, Alireza Moghri Friz, Omid Khorashadizadeh, Hamed Javadi
Journal of Saffron Research,