Establishing and evaluating an irrigation decision support system in order to improve irrigation management in pilot farms south of Urmia Lake basin

Document Type : Research Paper

Authors

1 Agricultural Engineering Research Institute, Agricultural Research, Education and Extension Organization, Alborz, Iran

2 Water Management and Engineering Department, Collage of Agriculture, Tarbiat Modares University, Tehran, Iran

3 Department of Water Engineering, Collage of Agriculture, Urmia University, Urmia, Iran.

4 Department of Water Engineering, Collage of Agriculture, Urmia University, Urmia, Iran

5 Technical and Engineering Research, Agricultural and Natural Resources Research Center, West Azerbaijan, Agricultural Research, Education and Extension Organization, Urmia, Iran.

6 Water Engineering Department, Collage of Agriculture, Tabriz University, Tabriz, Iran

7 Department of Engineering and Water Management, Collage of Agriculture,, Tarbiat Modares University, Tehran, Iran

8 Associate Professor, Agricultural Research, Education and Extension‌ Organization, Agricultural Engineering Research Institute, Alborz, Iran

9 Department of Water Engineering, Collage of Agriculture, Bu-Ali sina university, Hamadan, Iran

Abstract

 
Over the years, decision support systems (DSS) have emerged as valuable tools for optimizing irrigation scheduling by integrating various data sources, models, and decision-making algorithms. This research implemented and evaluated an irrigation decision support system (IDSS) that can be easily customized and adapted to different conditions and types of irrigation systems. The IDSS was tested in eight farms and gardens located in the Urmia Lake Basin during 1400-1401. This system provides farmers with the actual irrigation requirements of each crop, based on factors such as soil type, growth stage, climatic conditions, weather forecasts, farm or garden shape, water right, and irrigation system type. With this information, farmers can make informed decisions about irrigation. The investigation of two control (Irrigating by farmers) and treatment sections (Irrigating based on IDSS) revealed that implementing the irrigation scheduling provided by the IDSS in the treatment section increased water productivity by 87.3%, 20.7%, and 1.5% in drip, sprinkler, and basin irrigation systems, respectively. Results showed that using the IDSS system for fields and gardens under basin irrigation can lead to more efficient results, but optimizing the basin irrigation system, such as the length of the irrigation plots, should also be considered. Additionally, the research showed that providing an optimal and accurate irrigation scheduling to meet the crops water requirement is necessary to increase agricultural water productivity that using IDSS can be helpful in this regard.

Keywords

Main Subjects


Establishing and evaluating an irrigation decision support system to improve irrigation management in pilot farms south of Urmia Lake Basin

EXTENDED ABSTRACT

 

Introduction

To help restore Lake Urmia, one solution is to reduce the consumption of its water sources by considering the direct connection of surface and groundwater resources. Implementing irrigation scheduling, which involves irrigating based on the actual crop water requirement at the right time and place, is one of the best management practices to reduce water consumption and improve agricultural water productivity. The main questions that arise in irrigation scheduling are how much to irrigate and when to irrigate. In the present study, an irrigation decision support system was used and evaluated to provide an optimal irrigation schedule for the fields and orchards located in the Mahabad Plain in the Urmia Lake basin during 1400-1401.

Materials and Methods

The developed irrigation decision support system (IDSS) used in this research is designed to achieve the goal of optimal management of water consumption in agriculture, taking into account the time and amount of water availability. In order to update and modify the irrigation schedule due to daily changes in weather conditions, this system automatically uses online weather information. Additionally, the irrigation schedule of each part of the cropping pattern could be modified based on the feedback sent by the farmer during the growing season, and subsequent irrigation schedules were presented based on the updated conditions in the field. For example, if the farmer was unable to irrigate previously or made a change in the irrigation time, by applying feedback in the system and defining revised conditions, the system was able to provide the next irrigation schedule based on the updated conditions. Therefore, the next irrigation schedules were re-optimized and sent to the farmer according to the feedback given by the farmer. The irrigation decision support system utilizes necessary input information, including information related to real-time agricultural meteorological data, the farm's access to water, soil and plant characteristics, the availability of water storage sources, the type of irrigation system, to provide the optimal irrigation scheduling for the cropping pattern on the farm.

Results and Discussion

The results showed that the drip irrigation system had the highest percentage of changes in the irrigation depth, and implementing the irrigation scheduling provided by the IDSS in the treatment section reduced irrigation water depth by about 41%. Therefore, it can be concluded that correct irrigation scheduling is necessary to increase the efficiency of drip irrigation systems. Implementing a pressurized irrigation system without proper irrigation scheduling cannot reduce water consumption or increase water productivity. The results obtained in the basin irrigation system showed that implementing the irrigation scheduling provided by the IDSS in the treatment section increased water consumption compared to the control section. This was due to the long advance time in these gardens and fields, which required an increase in irrigation depth to meet the crops water requirements at the end of the garden or irrigation field.

In sprinkler irrigation systems, implementing the irrigation scheduling provided by the IDSS decreased irrigation water depth. The examination of crop yield in the control section and treatment sections of the monitored gardens and farms indicated an increase in crop yield in the treatment section compared to the control section in all investigated irrigation systems. The highest percentage increase was related to the basin irrigation system, with a 5.14% increase in sugar beet yield. The drip irrigation system had the highest percentage of changes in water productivity, with an increase of 87.3%.

Conclusion

Results showed that using the developed IDSS system in this research for fields and gardens under basin irrigation can lead to more efficient results, but optimizing the basin irrigation system, such as the length of the irrigation plots, should also be considered. Additionally, the research showed that providing an optimal and timely irrigation scheduling to meet the crop's water requirement is necessary to increase agricultural water productivity.

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