Document Type : Research/Original/Regular Article
Authors
1
Associate Professor, Agricultural Research, Education and Extension, Organization, Agricultural Engineering Research Institute, Karaj, Alborz, Iran
2
Ph.D. in Hydraulic Structures, Department of Water Engineering, University of Tabriz, Tabriz, Iran
3
MSc. of Irrigation and Drainage, Department of Water Engineering, Urmia University, Urmia, Iran
4
Professor, Department of Water Engineering, Urmia University, Urmia, Iran
5
Assistant Professor, Technical and Engineering Research, Agricultural and Natural Resources Research Center, West Azerbaijan, Agricultural Research, Education and Extension Organization, Urmia, Iran
6
Ph.D. Department of Engineering and Water Management, Tarbiat Modares University, Tehran, Iran
7
Ph.D. Candidate, Department of Engineering and Water Management, Tarbiat Modares University, Tehran, Iran
8
Associate Professor/ Agricultural Research, Education and Extension Organization, Agricultural Engineering Research Institute, Karaj, Alborz, Iran
Abstract
Abstract
Introduction
Irrigation decision support systems (IDSS) are among the approaches that have been considered a tool in complex decision-making for water resource managers due to the enormous development of computer systems. Modernizing and using intelligent solutions at different levels of water consumption can significantly increase the water productivity indicators. Performing these conditions requires technological changes. The primary pillar of any IDSS system is its ability to adapt to environmental changes. Adaptability is the most influential component of any intelligent system, which provides the system with the ability to change to adapt to changing conditions. This process allows the prediction model to compare predicted values with actual results and automatically adjust itself. IDSS systems for designing cropping patterns and optimal irrigation programs have the critical capabilities to control and manage optimal irrigation on large levels and water rights. These systems suggest the optimal cultivation pattern and dynamically provide the water consumption optimization schedule. According to previous studies, the most critical challenge of irrigation management is the limitation in the amount of available water, which leads to the complexity of the optimal use of agricultural water in real conditions. One of the most important strategies to save Lake Urmia is to take necessary measures to reduce water consumption in the agricultural sector. One of the primary solutions to reduce water consumption in the agriculture sector is to decrease the loss of valuable and non-useful uses of agricultural water through the improvement of irrigation management. For this purpose, in the present study, the details of the adaptability of a developed IDSS system to improve irrigation management with the conditions of irrigation and drainage network, water and soil resources, climate, and vegetation in Mahabad Plain have been discussed.
Materials and Methods
To evaluate the IDSS the downstream farms of the Mahabad irrigation and drainage network located southeast of Lake Urmia were selected. The Mahabad irrigation and drainage network consists of a diversion dam, two main canals, 11 2nd-grade canals, 69 main drains, and 10 water pumping stations. Four sites from the Mahabad irrigation and drainage network were chosen as selected sites. In each site, 20 farms were considered for monitoring the IDSS. The rest of the fields were under the control of the farmer, and only optimal irrigation programs were provided to the farmer by the IDSS. The general framework of the IDSS has been developed to achieve the goal of optimal management of water consumption in agriculture, taking into account the time and amount of water availability using international methods. The IDSS provides the optimal irrigation schedule for the cropping pattern in the field by using online information on agricultural meteorology, water access conditions of the farm, soil, and plant characteristics, and the type of irrigation system used in the farm. The IDSS can suggest the optimal cropping pattern for field conditions. During the plant growth period, it is possible that the farmer can introduce the events in the field as feedback to the system. In this situation, the IDSS simulates new scenarios according to the current situation on the farm and presents the new optimal irrigation program again for the next few days.
Results and Discussion
To adapt the IDSS for irrigation planning the physicochemical characteristics of soil and water, water right, soil texture, etc. were considered. It is possible to update soil and water resource details during the growing season in the system. The information on irrigation systems can be loaded separately in the IDSS. According to the uploaded details, the optimal irrigation schedule was designed. IDSS takes advantage of seven-day agricultural meteorological forecasts, which leads to the maximum use of rainfall in the region and a proper matching between the provided irrigation schedule and the forecast of meteorological information in the coming days. To adapt the IDSS for irrigation planning the physicochemical characteristics of soil and water, water right, soil texture, etc. were considered. The virtual agricultural meteorological station launched by IDSS estimated the minimum temperature, maximum temperature, and sunshine hours with a good degree and relative humidity with a very good degree compared to the regional synoptic station data. Based on statistical indicators, the performance of IDSS for simulating volumetric soil moisture is evaluated as good to very good. Also, IDSS is adapted to the social conditions, the agricultural structure of the study area, and the knowledge level of farmers. The use of irrigation planning provided by IDSS has been able to reduce water consumption by 41% and 14% and increase the crop yield by 10.3% and 8.6% respectively in farms under drip and sprinkler irrigation systems. In farms that are under the basin irrigation system, the use of irrigation planning provided by IDSS has resulted in an average increase of 13.5% in water consumption and 8.6% in crop yield. The reason for the increase in water consumption in the basin irrigation systems is the high advance time in the farms under monitoring, and to meet the water requirments at the end of the irrigation farms, IDSS has inevitably increased the water consumption.
Conclusion
IDSS has up-to-date simulations and is suitable for providing an optimal irrigation schedule within the study area. Determining the effectiveness of IDSS in water consumption showed that the irrigation schedule provided by IDSS reduced the water consumption in the area. Therefore, the potential application of IDSS as an irrigation consultation and the degree that this system has in improving the irrigation management of agricultural farms can be used in most areas of the Lake Urmia basin. Next, it is suggested that IDSS be evaluated for other areas and crop yields, emphasizing the application of IDSS in humid and semi-humid climates.
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