عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Shallow water table is an important problem in arid and semi-arid regions. Since it causes reduction of agricultural yield; therefore, water table fluctuation is necessary to be monitored in irrigation and drainage fields. These conditions are intensified for arid and semi-arid countries, such as Iran, which saline groundwater are main water resources. These problems increased in sugarcane industrial farm that covered large area in Khuzistan province, Iran. Therefor, it is necessary to determine water table in sugarcane field during growing season. Regarding the purpose, it is important to evaluate water table fluctuations in each farm continuously. There are some problems to achieve this purpose like spending time and financial supports. So, computer models are developed to solve the problems. Water table can be simulated in different farm conditions, even before designing an agricultural unit, using the models. This research was conducted to evaluate two models: DRAINMOD and SWAP in order to estimate water table levels in Amirkabir Agro-industry farms located at latitude between ??? ??’ to ??? ??’ and longitude between ??? ??’ to ??? ??’, Khuzistan. Regarding the aim, water table data were collected from a ?? ha-farm. In order to evaluate the results, four statistics criteria root mean square error (RMSE), modeling efficiency (EF), coefficient of residual mass (CRM) and coefficient of determination (R?) were used.
The calibration results of soil physics parameters for SWAP and DRAINMOD revealed that in both models, the parameters n and Alpha had the most variations compared to other parameters. In calibration stage, the amount of R? for DRAINMOD model was ??. This result showed that there was a good correlation between field and simulated data. The result of R? for SWAP and ENDRAIN models were ?? and ??, respectively. RMSE values for DRAINMOD, SWAP and ENDRAIN were ??.??, ??.?? and ??.?? cm, respectively. So, in calibration stage, SWAP had more accuracy compared to other models to determine water table. The CRM values were obtained as -?.???, -?.??? and -?.??? cm for DRAIMOD, SWAP and ENDRAIN, respectively. Then, all three models lead to overestimate of water table. The results of EF were ?.??, ?.?? and ?.?? for mentioned models, respectively. Validation results of DRAINMOD model revealed that RMSE, CRM and R? were ??.?? (cm), -?.??? and ?.??, respectively. These statistical criteria were found to be ??.?? (cm), ?.??? and ?.?? for SWAP. These parameters were obtained as ??.?? (cm), ?.??? and ?.?? for ENDRAIN model. The results of EF were ?.??, ?.?? and -?.?? for DRAINMOD, SWAP and ENDRAIN models, respectively. These results showed that ENDRAIN had no efficiency to determine water table. SWAP and DRAINMOD had good efficiency to simulate water table.
Thus, DRAINMOD had overestimate error and SWAP and ENDRAIN had underestimate error. DRAINMOD is recommended as a better model according to higher coefficient of determination and lower error value.