Hamed Nozari; Azin Poursadri; Saeed Azadi; abdolmajid liaghat
Abstract
After installing subsurface drainage system, quality of drainage water in saline lands continuously changes, starting from the beginning of irrigation and drainage network operation, until reaching a more or less equilibrium state. Reaching a state of equilibrium in areas with saline groundwater may ...
Read More
After installing subsurface drainage system, quality of drainage water in saline lands continuously changes, starting from the beginning of irrigation and drainage network operation, until reaching a more or less equilibrium state. Reaching a state of equilibrium in areas with saline groundwater may take several years. In this regard, field experiments are useful but they also have significant limitations. As an alternative, simulation models are among the methods that greatly eliminate these limitations. Therefore, in this research, the performance of DRAINMOD-S model was evaluated in simulation of drainage volume, drainage water salinity, and water table fluctuations. To validate the results of the model, data collected in the 2007-2008 cropping year from ARC18-18 farm was used in the research site of Sugarcane Research Center (Amir Kabir Agro Industrial Development Unit of Sugarcane Development Company, Khuzestan Province). This information included meteorological and soil data, drainage outflow, irrigation water salinity, water salinity within piezometers, and drainage water salinity. After statistical analysis and calculating the root mean square error (RMSE) and standard error (SE), the fits between the measured and simulated values of drainage water salinity, groundwater salinity, water table fluctuations and drainage discharge were investigated. The RMSE statistical index was 4.76 dS /m for drainage water salinity, 0.82 dS/m for groundwater salinity, 21.2 cm for groundwater surface and 2.1 L/s for the drain discharge, which indicated a fairly good accuracy compared with actual conditions. The results showed that the model was capable of simulating the water level fluctuations, drainage outflow and its salinity in Khuzestan region with saline and shallow groundwater table.
Hamed Nozari; Majid Heydari; Saeed Azadi
Abstract
One of the agricultural development strategies is to establish irrigation and drainage networks that will lead to higher productivity and greater economic benefits. In the present study, by using system dynamics approach, a computer model was developed that can estimate the crop yield of an irrigation ...
Read More
One of the agricultural development strategies is to establish irrigation and drainage networks that will lead to higher productivity and greater economic benefits. In the present study, by using system dynamics approach, a computer model was developed that can estimate the crop yield of an irrigation network according to the quantity and quality of simulated irrigation water and to estimate the net profit of the products. In order to calibrate and validate the model results, the data collected from the research lands of the right side of Abshar Irrigation Network were used. After statistical analysis and calculation of RMSE, relative error, the standard error, and correlation coefficient, adjustment between the measured and simulated network products performance was calculated. The value of these product indexes according to the conditions of the network was estimated as 209.98 kg/ha, 1.36 percent, 0.007, and 0.99, respectively. The results showed that the model had reasonable accuracy in simulation of the irrigation network, its cropping pattern, and definition of other scenarios. Also, an initial check showed that groundwater exploitation in the mentioned area was more than the permitted limit. Considering the importance of water resources, two scenarios were defined i.e. irrigation according to water requirement of crops and irrigation based on limitation of exploiting groundwater resources. Analysis of the results showed that the average of the products income to cost ratio for irrigation of the network in 2006-2007, the first scenario, and the second scenario was, respectively, 2.58, 2.88, and 2.75.