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shadman veysi; Milad Nouri; Anahita Jabbari
Abstract
To compensate for the lack, or inadequacy, of weather stations data, one of the most reliable ways is to use the remote sensing and re-analysis dataset, which provides a suitable model for such areas. In this study, the performance of two data sources, namely, WaPOR and ERA5, was evaluated in estimating ...
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To compensate for the lack, or inadequacy, of weather stations data, one of the most reliable ways is to use the remote sensing and re-analysis dataset, which provides a suitable model for such areas. In this study, the performance of two data sources, namely, WaPOR and ERA5, was evaluated in estimating reference evapotranspiration at 64 synoptic stations in the Caspian coastal region in Iran, on a daily and monthly basis. To this end, meteorological data of 64 synoptic stations with a 10-year statistical period (2011-2021) was obtained daily from the Iran Meteorological Organization. The field data used included minimum and maximum temperature, relative humidity, wind speed, and solar radiation intensity. Then, evapotranspiration and reference evapotranspiration were calculated using the Penman-Monteith equation and REF-ET software. Finally, the results were compared with the results from the WaPOR and ERA5 data bases. The results showed that, on average, the nRMSE values of the WaPOR and ERA5 datasets compared to the calculated meteorological station data were 29.6% and 29%, respectively, on a daily basis. Also, on a monthly time scale, in more than 85% of the stations, both datasets provided acceptable results. On a monthly scale, the average nRMSE value for both WaPOR and ERA5 sensors in the catchment area was 19%. The rMBE value showed that the ERA5 dataset underestimated the reference evapotranspiration in most of the stations, while the WaPOR dataset overestimated. Given that the error rate of the two sensors is different in over 30 percent of the stations, a suitable estimate of reference evapotranspiration in the Caspian Sea basin area can be obtained by combining the data from these two datasets. The results showed that in the Caspian Sea coastal areas, 34 stations in the WaPOR dataset and 28 stations in the ERA5 dataset showed the minimum error, with two stations showing the same error. Thus, both WaPOR and ERA5 are suitable databases that can be used for hydrological purposes, including estimation of reference evapotranspiration.
7
Ali Morshedi; Hossein Jafari; azhdar Onabi Milani
Abstract
The aim of this study was to estimate the actual evapotranspiration of wheat using Surface Energy Balance Algorithm for Land (SEBAL) and compare with data measured by lysimeters in two study sites in Tabriz and Karaj during three growing seasons (1396-1399). Values of actual evapotranspiration of wheat ...
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The aim of this study was to estimate the actual evapotranspiration of wheat using Surface Energy Balance Algorithm for Land (SEBAL) and compare with data measured by lysimeters in two study sites in Tabriz and Karaj during three growing seasons (1396-1399). Values of actual evapotranspiration of wheat during the growing seasons were calculated by two methods: a) using Landsat 8 satellite data through SEBAL, and b) using drained lysimeter data. Considering that evapotranspiration in SEBAL is in actual conditions and lysimeters provide evapotranspiration in potential conditions (standard situation without any limitation), to reduce errors, remote sensing data were used for pixels that had moisture conditions similar to standard lysimeters conditions. Comparison of actual evapotranspiration obtained from SEBAL and lysimeter in both sites showed relatively good correlation. The coefficients of determination (R2) were 0.73 and 0.65 in, respectively, Karaj and Tabriz sites. In addition, using statistical parameters such as NRMSE, RMSE, MAE, and MBE showed that SEBAL actual evapotranspiration data and lysimeteric data were, relatively, in agreement in the two study sites. However, in most cases, evapotranspiration values by SEBAL were greater than values measured by the lysimeter. In general, considering the advantages of the SEBAL, it is suggested this technology be used to estimate the actual evapotranspiration of wheat in large-scale areas.
m m; h b; f k; n e
Abstract
The agricultural sector is known as the largest consumer of water. Due to limited water resources, water productivity needs to be enhanced in this sector. The concept of water productivity has attracted the attention of policy makers in food and water sector at large scale. Remote sensing is used in ...
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The agricultural sector is known as the largest consumer of water. Due to limited water resources, water productivity needs to be enhanced in this sector. The concept of water productivity has attracted the attention of policy makers in food and water sector at large scale. Remote sensing is used in the assessment and management of soil and water resources in recent decades. In the present research, this method was used to estimate water productivity. Evapotranspiration and actual production levels of dry matter were calculated using SEBAL algorithms and five images from the Landsat 5TM satellite in Qazvin Plain. The results of SEBAL algorithm in five images and lysimeter data were compared and evaluated in the region. The coefficient of determination ( 15R2"> ) and their mean absolute difference were 0.9948 and 0.446 mm/day, respectively, which demonstrated the accuracy of remote sensing methods in estimating agricultural water productivity at the basin level. The results showed that water productivity varied from 0.18 to 1.35 in the field. The wheat water productivity values from Landsat 5TM images and lysimeter data were 0.73 and 0.85 kg/m3, respectively, which are relatively close to each other.