Evaluation of the performance of SWAP model updated with satellite data in estimating of rice evapotranspiration and its crop coefficients

Document Type : Research Paper

Authors

1 Graduate M.Sc., Department of Soil Science, Faculty of Agricultural Sciences, University Of Guilan, Rasht, Iran.

2 Assistant Professor, Department of Soil Science, Faculty of Agricultural Sciences, University Of Guilan, Rasht, Iran

3 Associate Professor, Department of Water Engineering, Faculty of Agricultural Sciences, University Of Guilan, Rasht, Iran

4 Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization (AREEO), Rasht, Iran.

Abstract

Due to the upcoming climate threats, challenge of water shortage and its impact on the food security of the growing population in Iran, the optimal use of soil and water resources is very important. With the development of remote sensing technologies, free access to a variety of field data has become widely available, which can be used to reduce the uncertainty of simulation models. The aim of this study was to simulate actual evapotranspiration (ETa) and rice crop coefficients (Kc) during its growth stages using the SWAP model updated with satellite data and evaluate the accuracy of the results with/without updating. This research was conducted at the National Rice Research Institute of Iran in Rasht in the year of 2017. Based on the obtained results, total ETa measured by lysimeter and simulated by SWAP model with and without updating were 395.4, 373.2 and 363.6 mm, respectively. The average crop coefficients during the growth stages of vegetative, reproductive and ripening were estimated as 1.13, 1.49, 1.21, respectively. The crop coefficients for the proposed stages estimated by SWAP model without using satellite data were 1.02, 1.39, 1.04, respectively. After updating with satellite data, the crop coefficients were modified as 1.05, 1.43 and 1.07, respectively. Finally, the statistical analysis indicated that the SWAP model has a reasonable performance in estimation of ETa (RMSE=0.89; EF=0.98; R2=0.74) and rice crop coefficients (RMSE=0.53; EF=0.96; R2=0.63). The results indicate that the SWAP model combined with satellite data improved the accuracy of ETa estimation (RMSE=0.75; EF=0.99; R2=0.86) and rice crop coefficient (RMSE=0.40; EF=0.99; R2=0.74) at field scale.

Keywords


Evaluation of the performance of SWAP model updated with satellite data in estimating rice evapotranspiration and its crop coefficients

 

EXTENDED ABSTRACT

 

Introduction

Determining evapotranspiration during the growing season is very important for estimating water consumption and crop production. Both the remote sensing and crop growth simulation models provide a variety of field data including actual evapotranspiration (ETa) and crop biomass production. The water requirement of rice has direct relationship with the quantity of ETa which is depends on the weather conditions, soil texture, crop growth period and farm management. Considering the variability of rice evapotranspiration in different climatic conditions and the importance of rice cultivation in Guilan province, this study was conducted to determine the crop coefficient of rice (modified Hashemi variety) during the different growth stages, to measure ETa by direct method (lysimeter), to simulate ETa with and without updating the SWAP model with satellite data, and to analyze the accuracy of outcomes.

Material and Methods

This research was conducted in a paddy field located at the Rice Research Institute of Iran in Rasht in 2017. The field is located at 37°12 N, 49°38 E, with an altitude of 24 m below the sea level. The rice variety used in this study was the modified Hashemi with growth period of 83 days. In order to directly determine the rice evapotranspiration, mini lysimeters with 75 cm diameter and 40 cm height were used. The experimental lysimeters were installed in the center of the farms with 20 m distance from each other and then filled with paddy soil. A number of 7 groups of rice seedlings were planted in each lysimeter based on the dimensions and spacing of the seedlings in the field. The required input data for SWAP model including soil data, irrigation, plant parameters and meteorological data was set from related sources. In the next step, Sentinel2 satellite images with a time step of 5 days and Landsat 7 and 8 were used to calculate the Normalized Difference Vegetation Index (NDVI) during the rice growth period. Then, the crop coefficients were derived using the calibrated NDVI-based equations recommended for rice crop coefficients in the similar climate. In order to evaluate the accuracy and efficiency of the results with and without updating, statistical indices including coefficient of determination (R2), root mean square error (RMSE), normalized root mean square error (nRMSE), model efficiency (EF) and residual mass coefficient (CRM) were used.

Results and Discussion

Based on the obtained results, total ETa measured by the lysimeter and simulated by SWAP model with and without updating were 395.4, 373.2 and 363.6 mm, respectively. The average crop coefficients during the growth stages of vegetative, reproductive and ripening were estimated as 1.13, 1.49, 1.21, respectively. The crop coefficients for the proposed stages estimated by SWAP model without using satellite data were 1.02, 1.39, 1.04, respectively. After updating with satellite data, the crop coefficients were modified as 1.05, 1.43 and 1.07, respectively. Finally, the statistical analysis indicated that the SWAP model has a reasonable performance in estimation of ETa (RMSE=0.89; EF=0.98; R2=0.74) and rice crop coefficients (RMSE=0.53; EF=0.96; R2=0.63). The results indicate that the SWAP model combined with satellite data improved the accuracy of ETa estimation (RMSE=0.75; EF=0.99; R2=0.86) and rice crop coefficient (RMSE=0.40; EF=0.99; R2=0.74) at field scale.

Conclusion

The integration of remote sensing with SWAP model has improved the accuracy of simulation. In the current situation with upcoming water crisis, it is necessary to improve the water efficiency in consumption of limited water resources. Since the rainfall in the rice growing season is not sufficient to meet the rice water requirements, the irrigation authorities can use the results of this research to calculate the irrigation water requirements with higher accuracy and allocate the limited water resources with more efficiently.

 

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