Modeling the Amount of Water in Soil using Satellite Image Information and Infiltration Flux to Estimate Precipitation and Irrigation Water Data
Precipitation is one of the essential parameters of the water cycle, the estimation of which is effective in water and soil resources management. In this study, the SM2RAIN-NWF algorithm was used to estimate irrigation water consumption at the field scale based on satellite soil moisture data. Satel...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | fas |
| Published: |
Iranian Rainwater Catchment Systems Association
2024-09-01
|
| Series: | محیط زیست و مهندسی آب |
| Subjects: | |
| Online Access: | http://www.jewe.ir/article_187755_92a76b30b9d589f17f370de966a29663.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846169712691511296 |
|---|---|
| author | Mohammad Zarei Bahram Malek Mohammadi |
| author_facet | Mohammad Zarei Bahram Malek Mohammadi |
| author_sort | Mohammad Zarei |
| collection | DOAJ |
| description | Precipitation is one of the essential parameters of the water cycle, the estimation of which is effective in water and soil resources management. In this study, the SM2RAIN-NWF algorithm was used to estimate irrigation water consumption at the field scale based on satellite soil moisture data. Satellite soil moisture observations obtained from Advanced Microwave Scanning Radiometer (AMSR2) along with GLEAM products and rainfall were used for the period of 2012-2020 as model inputs. Precipitation estimation was performed for three different sites including an agricultural land in Miandoab, a vegetated surface in Malekan, and a barren land in Bonab. Using this model, the coefficient of determination (R2) of precipitation estimation was between 0.53 and 0.70. A comparison of the results revealed that the model exerted much better results in regions with no vegetation. The results of irrigation estimation in Miandoab plain showed that although the model systematically over/under-estimated irrigation data in some seasons compared to the in-situ data, the average performance of the model in irrigated regions (NS = 0.55, R2 = 0.63, and PRMSE = 2.48%) proved that the proposed approach can provide a suitable prediction of irrigation pattern. |
| format | Article |
| id | doaj-art-b971697d33214755b9a90e90a9a2ad3c |
| institution | Kabale University |
| issn | 2476-3683 |
| language | fas |
| publishDate | 2024-09-01 |
| publisher | Iranian Rainwater Catchment Systems Association |
| record_format | Article |
| series | محیط زیست و مهندسی آب |
| spelling | doaj-art-b971697d33214755b9a90e90a9a2ad3c2024-11-12T11:01:37ZfasIranian Rainwater Catchment Systems Associationمحیط زیست و مهندسی آب2476-36832024-09-0110337939110.22034/ewe.2024.413340.1887187755Modeling the Amount of Water in Soil using Satellite Image Information and Infiltration Flux to Estimate Precipitation and Irrigation Water DataMohammad Zarei0Bahram Malek Mohammadi1PhD Scholar, Department of Environmental Engineering and Water Resources, Faculty of Environmental Engineering, Kish International Campus, University of Tehran, Tehran, IranAssoc. Professor, Department of Environmental Planning and Management, Faculty of Environment, University of Tehran, Tehran, IranPrecipitation is one of the essential parameters of the water cycle, the estimation of which is effective in water and soil resources management. In this study, the SM2RAIN-NWF algorithm was used to estimate irrigation water consumption at the field scale based on satellite soil moisture data. Satellite soil moisture observations obtained from Advanced Microwave Scanning Radiometer (AMSR2) along with GLEAM products and rainfall were used for the period of 2012-2020 as model inputs. Precipitation estimation was performed for three different sites including an agricultural land in Miandoab, a vegetated surface in Malekan, and a barren land in Bonab. Using this model, the coefficient of determination (R2) of precipitation estimation was between 0.53 and 0.70. A comparison of the results revealed that the model exerted much better results in regions with no vegetation. The results of irrigation estimation in Miandoab plain showed that although the model systematically over/under-estimated irrigation data in some seasons compared to the in-situ data, the average performance of the model in irrigated regions (NS = 0.55, R2 = 0.63, and PRMSE = 2.48%) proved that the proposed approach can provide a suitable prediction of irrigation pattern.http://www.jewe.ir/article_187755_92a76b30b9d589f17f370de966a29663.pdfamsr2 satellitegleam productsirrigationprecipitation estimationsm2rain-nwfwater |
| spellingShingle | Mohammad Zarei Bahram Malek Mohammadi Modeling the Amount of Water in Soil using Satellite Image Information and Infiltration Flux to Estimate Precipitation and Irrigation Water Data محیط زیست و مهندسی آب amsr2 satellite gleam products irrigation precipitation estimation sm2rain-nwf water |
| title | Modeling the Amount of Water in Soil using Satellite Image Information and Infiltration Flux to Estimate Precipitation and Irrigation Water Data |
| title_full | Modeling the Amount of Water in Soil using Satellite Image Information and Infiltration Flux to Estimate Precipitation and Irrigation Water Data |
| title_fullStr | Modeling the Amount of Water in Soil using Satellite Image Information and Infiltration Flux to Estimate Precipitation and Irrigation Water Data |
| title_full_unstemmed | Modeling the Amount of Water in Soil using Satellite Image Information and Infiltration Flux to Estimate Precipitation and Irrigation Water Data |
| title_short | Modeling the Amount of Water in Soil using Satellite Image Information and Infiltration Flux to Estimate Precipitation and Irrigation Water Data |
| title_sort | modeling the amount of water in soil using satellite image information and infiltration flux to estimate precipitation and irrigation water data |
| topic | amsr2 satellite gleam products irrigation precipitation estimation sm2rain-nwf water |
| url | http://www.jewe.ir/article_187755_92a76b30b9d589f17f370de966a29663.pdf |
| work_keys_str_mv | AT mohammadzarei modelingtheamountofwaterinsoilusingsatelliteimageinformationandinfiltrationfluxtoestimateprecipitationandirrigationwaterdata AT bahrammalekmohammadi modelingtheamountofwaterinsoilusingsatelliteimageinformationandinfiltrationfluxtoestimateprecipitationandirrigationwaterdata |