Evaluation of AquaCrop and SWAP models in simulating the growth and biomass of different maize cultivars under the conditions of using saline water with drip irrigation system

Document Type : Research Paper

Authors

Department of Irrigation and Reclamation Engineering, Faculty of Agriculture, University of Tehran, Karaj, Iran.

Abstract

Using simulation models is a key strategy in agricultural water management and an effective way to predict the impact of irrigation management and water quality on crop yield. This study aimed to evaluate the performance of the SWAP and AquaCrop models in simulating the growth and biomass production of three maize varieties under the conditions of using saline water for irrigation with a drip irrigation system at the research farm of Tehran University of Agriculture and Natural Resources Campus. In order to calibrate and validate the models, field data obtained from a factorial experiment with two factors of maize variety (SC704, 400, and 260) and irrigation water salinity (0.7, 3, and 5 dS/m) were used. In the validation stage of the AquaCrop model, the R2, RMSE, and NRMSE statistics for the canopy cover (CC) showed a high level of agreement between the measured and simulated data, with values of 0.953, 5.69, and 8% respectively. For the SWAP model, the calculated statistics for the leaf area index (LAI) were 0.477, 1.610, and 54.2%, respectively. Despite the poor performance of the SWAP model in estimating LAI, both the SWAP and AquaCrop models effectively simulated the biomass of maize cultivars under different treatments. In the calibration and validation stage, RMSE and NRMSE of both models were less than 0.5 ton/ha, with 3% (calibration) and 1 ton/ha, 7% (validation), respectively. In general, both models can be used in various studies for different maize cultivars under irrigation water and soil salinity conditions.

Keywords

Main Subjects

Evaluation of AquaCrop and SWAP models in simulating the growth and biomass of different maize cultivars under the conditions of using saline water with drip irrigation system

EXTENDED ABSTRACT

Introduction

Water management is one of the most significant challenges of this century. The world is experiencing a decrease in fresh water due to population growth. Furthermore, the widespread use of saline water for irrigation has become prevalent due to water scarcity in many regions of the country. In areas where plants are under irrigation, it is necessary to have proper management and planning for the optimal use of water. It is possible to enhance irrigation management and precise planning for optimal water use in arid and semi-arid areas through the use of mathematical models. The use of simulation models is a strategy for managing agricultural water consumption and an effective method for predicting the impact of irrigation management and water quality on crop yield, provided that the models are proven to be accurate. Therefore, it is important to assess the accuracy of product simulation models in simulating product performance under these conditions.

Objective

The aim of this study is to assess the performance of two SWAP and AquaCrop models in simulating the growth of different maize cultivars under conditions involving the use of saline water for irrigation with a drip irrigation system.

 Materials and method

This research was conducted using a factorial experiment and a randomized complete block design with two factors and three blocks (repetitions), resulting in a total of 9 treatments and 27 experimental plots in 2016 at the research farm of the Department of Irrigation and Development Engineering, University of Tehran, situated in Karaj. The area of each plot is approximately 12 m2 (3 × 4), which includes four rows of maize plants spaced 75 cm apart and extending four meters in length. The experimental factors included three maize varieties: SC 704, 400, and 260 (V1, V2 and V3), and three levels of irrigation water salinity: 0.7, 3 and 5 dS m-1 (S1, S2 and S3) to apply salinity stress. The data measured in the field, including leaf area index, canopy cover, and biomass, were used to calibrate and verify two AquaCrop and SWAP models.

Results and discussion

In the calibration stage of the AquaCrop model, the R2, RMSE, NRMSE, and CRM statistics between the measured and simulated data of crop canopy cover (CC) are 0.953, 6.107%, 8.4%, and -0.059, respectively. For the SWAP model, the corresponding statistics for leaf area index (LAI) were calculated as 0.763, 0.986 (m2 m-2), 33.2%, and 0.010. In the validation stage of the AquaCrop model, the R2, RMSE, and NRMSE statistics for the comparison between the measured and simulated data of CC are 0.953, 5.69, and 8%, respectively. For the SWAP model, the corresponding statistics for LAI are 0.477, 1.610 (m2 m-2), and 54.2%. Considering that LAI was measured in the laboratory for a single plant, and the SWAP model estimates LAI using specific leaf area (SLA) without considering crop density as an input parameter, it appears that one of the reasons for the low accuracy of this model in estimating this index is the omission of crop density as a factor. The low simulation accuracy can also be attributed to errors in selecting the plant for LAI measurement. Contrary to the poor results of the SWAP model in LAI estimation, both the SWAP and AquaCrop models effectively simulated the biomass of corn cultivars in different treatments. In the calibration and validation phase, RMSE and NRMSE of both models were less than 0.5 ton/ha and 3% (validation), and 1 ton/ha and 7% (validation), respectively.

Conclusion

According to the simulation results and the assessment of model efficiency using statistical indicators, both the AquaCrop and SWAP models demonstrate acceptable accuracy in simulating the growth and yield of corn when irrigated with saline water. These models can be utilized under various scenarios. In general, the SWAP and AquaCrop models can be utilized in various studies involving different maize cultivars under varying irrigation water and soil salinity conditions. Finally, the results of this study can assist farmers and researchers in making informed decisions about irrigation management strategies and crop selection. Furthermore, the outcomes of these evaluations can contribute to enhancing the models, making them more precise and dependable for simulating the growth and performance of various maize cultivars under saltwater irrigation.

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Iranian Journal of Soil and Water Research
Volume 55, Issue 4
July 2024
Pages 615-636

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