Implementation and Validation of an Electricity-Driven Water Conservation Method for Plain-Region Irrigation: A Control Method Based on Power-Consumption Feedback
Abstract
:1. Introduction
- (1)
- The “electricity-driven water conservation” control method proves to be both economically viable and operationally reliable in plain regions. The measurement model developed in this system utilizes pre-calibrated pump station water-electricity conversion coefficients to calculate irrigation water usage in real time. This innovative approach eliminates the need for installing additional metering devices or specialized irrigation equipment, thereby relieving farmers of any extra financial burdens.
- (2)
- The system demonstrates particular applicability in multi-user centralized irrigation districts, featuring user-friendly operation. Equipped with automated functions including data acquisition, real-time analysis, and remote control capabilities, the system enables farmers to monitor real-time water consumption and receive pricing notifications. Through mobile terminals, users can conveniently operate irrigation equipment remotely. Compared with existing automated irrigation management systems, this solution exhibits superior learnability, facilitating efficient and simplified farm management for end users.
- (3)
- The proposed system employs water pricing adjustment strategies to incentivize rational water usage among farmers, thereby enhancing water conservation effectiveness. In contrast to conventional systems that primarily focus on automated control equipment or optimization of specific irrigation techniques, our approach utilizes scientifically designed water pricing incentives to guide farmers in the judicious utilization of irrigation water resources.
2. Materials and Methods
2.1. Theoretical Basis of “Electricity-Driven Water Conservation” in the Agricultural Irrigation Coordination Management System
2.2. Technical Basis of the Agricultural Irrigation Coordination Management System
2.2.1. Basic Development Architecture of the Management System
2.2.2. Data Transmission and Real-Time Collection Technology Basis of the Management System
2.2.3. Pre-Input Basic Data Information of the Management System
- (1)
- Core data: The primary monitoring equipment can accurately record the electricity consumption of each irrigation device and upload the data to the system for calculating irrigation water usage. This enables water conservation through economic measures of water and electricity pricing control, with the entire process requiring no manual intervention. This approach fundamentally ensures the reliability of core data.
- (2)
- Auxiliary data: The spatial information of irrigation stations and canal systems is primarily used for visualization in management. The system provides satellite imagery basemaps to assist managers in area demarcation, with relatively lenient accuracy requirements. These data serve as references for decision making and do not affect the core water usage calculations.
2.2.4. Overview of the Management System’s Overall Framework
2.3. Implementation Process Framework of the “Electricity-Driven Water Conservation” Control Method Based on the Irrigation Coordination Management System
3. Results
3.1. Specific Operational Instructions for the “Electricity-Driven Water Conservation” Control Method Based on the Irrigation Coordination Management System
3.1.1. Remote Water Gate Operation
3.1.2. Intelligent Data Input
3.2. Functions Achievable by the Control Method Based on the Irrigation Coordination Management System
3.3. Water-Saving Effectiveness of the Electricity-Driven Water Conservation Management Method
4. Discussion
4.1. Advantages of the Electricity-Driven Water Conservation Management Method
- (1)
- The “electricity-driven water conservation” control method based on the agricultural irrigation coordination management system has low learning and labor costs. For grassroots management personnel, it effectively reduces the workload of recording water usage information for pump station managers with lower educational levels and insufficient professional competence. On this basis, it ensures the accuracy of data collection, the real-time nature of the transmission process, the reliability of the storage process, and the convenience of the retrieval process. Technical personnel from water stations or county-level management departments can directly log into the system to remotely obtain electricity and water consumption information and pre-input various preset parameter information in the system.
- (2)
- The “electricity-driven water conservation” control method based on the agricultural irrigation coordination management system is convenient and timely in measurement, with transparent and open data. The “electricity-driven water conservation” control method uses informatized statistics, with the system transmitting the electricity consumption information of each pump station to the system in real time. Combined with the preset water-electricity conversion coefficient, the system performs water-electricity conversion calculations, publicly displaying the calculated actual water consumption, planned water quota, and other water-saving indicators in the system. When excessive water usage behavior is predicted or detected, the system promptly issues warning or alarm information and calculates the corresponding water usage fees for each pump station in real time, allowing grassroots management personnel to query relevant data.
- (3)
- The “electricity-driven water conservation” control method based on the agricultural irrigation coordination management system is convenient to operate and highly efficient, with stable operation of related equipment and technical support. The “electricity-driven water conservation” control method proposed in this study is primarily implemented through remote control in practice. Grassroots management personnel can log into the system via mobile phones or computers to operate the water gate switches of each pump station and collect data through the system. The system is connected to the monitoring equipment of each pump station, facilitating real-time remote monitoring of the pump station operation status and ensuring normal execution of the scheme.
- (4)
- The “electricity-driven water conservation” control method based on the agricultural irrigation coordination management system has a well-established mechanism and good water-saving economic benefits. The “electricity-driven water conservation” control method proposed in this study links water-saving (or excessive water usage) with water prices through economic means, incentivizing grassroots management personnel and farmers to save water during irrigation and achieving good water-saving results.
- (5)
- The “electricity-driven water conservation” control method based on the agricultural irrigation coordination management system enhances water-saving efficiency without compromising agricultural production or grain yields. Figure 8 illustrates the variation in total grain production in Shuyang County from 2018 to 2023 (data sourced from the Shuyang County People’s Government Statistical Yearbook). As shown in the figure, the total grain yield in the region has fluctuated within a narrow range in recent years, with an overall upward trend, demonstrating that the current water-saving control measures do not adversely affect regional grain production.
4.2. Limitations of the Electricity-Driven Water Conservation Management Method
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Albiac, J.; Calvo, E.; Kahil, T.; Esteban, E. The challenge of irrigation water pricing in the Water Framework Directive. Water Altern. 2020, 13, 674–690. [Google Scholar]
- Santosh, K.S.; Varsha, J.; Supritha, S.; Suganya, R.; Saqquaf, S.S.M.; Nanda, S.S.; Ananthaswamy, R. Sector Based Electronic Polling of Wetting Pattern Data for On-Farm Water Management. In Proceedings of the 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), Bangalore, India, 19–20 May 2017; pp. 1317–1321. [Google Scholar]
- Nagaraj, D.; Proust, E.; Todeschini, A.; Rulli, M.C.; D’Odorico, P. A new dataset of global irrigation areas from 2001 to 2015. Adv. Water Resour. 2021, 152, 103910. [Google Scholar] [CrossRef]
- Hu, Y.; Moiwo, J.P.; Yang, Y.; Han, S.; Yang, Y. Agricultural water-saving and sustainable groundwater management in Shijiazhuang Irrigation District, North China Plain. J. Hydrol. 2010, 393, 219–232. [Google Scholar] [CrossRef]
- Ray, S.; Majumder, S. Water management in agriculture: Innovations for efficient irrigation. In Modern Agronomy; Satish Serial Publishing House: Delhi, India, 2024; pp. 169–185. [Google Scholar]
- Ahmed, Z.; Gui, D.; Murtaza, G.; Yunfei, L.; Ali, S. An overview of smart irrigation management for improving water productivity under climate change in drylands. Agronomy 2023, 13, 2113. [Google Scholar] [CrossRef]
- Abioye, E.A.; Abidin, M.S.Z.; Mahmud, M.S.A.; Buyamin, S.; Ishak, M.H.I.; Abd Rahman, M.K.I.; Otuozec, A.O.; Onotub, P.; Ramli, M.S.A. A review on monitoring and advanced control strategies for precision irrigation. Comput. Electron. Agric. 2020, 173, 105441. [Google Scholar] [CrossRef]
- Zhang, C.Y.; Oki, T. Water pricing reform for sustainable water resources management in China’s agricultural sector. Agric. Water Manag. 2023, 275, 108045. [Google Scholar] [CrossRef]
- Ju, Q.; Du, L.; Liu, C.; Jiang, S. Water resource management for irrigated agriculture in China: Problems and prospects. Irrig. Drain. 2023, 72, 854–863. [Google Scholar] [CrossRef]
- Knox, J.W.; Kay, M.G.; Weatherhead, E.K. Water regulation, crop production, and agricultural water management-Understanding farmer perspectives on irrigation efficiency. Agric. Water Manag. 2012, 108, 3–8. [Google Scholar] [CrossRef]
- Gu, Z.; Qi, Z.; Burghate, R.; Yuan, S.; Jiao, X.; Xu, J. Irrigation scheduling approaches and applications: A review. J. Irrig. Drain. Eng. 2020, 146, 04020007. [Google Scholar] [CrossRef]
- Gebeyhu, B.; Dagalo, S.; Muluneh, M. Soil moisture-based irrigation interval and irrigation performance evaluation: In the case of lower Kulfo catchment, Ethiopia. Heliyon 2024, 10, e36089. [Google Scholar] [CrossRef]
- Rasheed, M.W.; Tang, J.; Sarwar, A.; Shah, S.; Saddique, N.; Khan, M.U.; Khan, M.I.; Nawaz, S.; Shamshiri, R.R.; Aziz, M.; et al. Soil moisture measuring techniques and factors affecting the moisture dynamics: A comprehensive review. Sustainability 2022, 14, 11538. [Google Scholar] [CrossRef]
- Le, C.V.; Jensen, J.R. Individual lift irrigation: A case study in the Cau Son irrigation and drainage area, Red River Basin, Vietnam. Paddy Water Environ. 2014, 12, 223–238. [Google Scholar] [CrossRef]
- Vuolo, F.; D’Urso, G.; de Michele, C.; Bianchi, B.; Cutting, M. Satellite-based irrigation advisory services: A common tool for different experiences from Europe to Australia. Agric. Water Manag. 2015, 147, 82–95. [Google Scholar] [CrossRef]
- Guebs, R.; Mami, S.; Chokmani, K. Drones in precision agriculture: A comprehensive review of applications, technologies, and challenges. Drones 2024, 8, 686. [Google Scholar] [CrossRef]
- Zappa, L.; Dari, J.; Modanesi, S.; Quast, R.; Brocca, L.; De Lannoy, G.; Massari, C.; Quintana-Seguí, P.; Barella-Ortiz, A.; Dorigo, W. Benefits and pitfalls of irrigation timing and water amounts derived from satellite soil moisture. Agric. Water Manag. 2024, 295, 108773. [Google Scholar] [CrossRef]
- Altés, V.; Bellvert, J.; Pascual, M.; Villar, J.M. Understanding Drainage Dynamics and Irrigation Management in a Semi-Arid Mediterranean Basin. Water 2022, 15, 16. [Google Scholar] [CrossRef]
- Tseng, H.T.; Lin, Y.F.; Yu, H.L. Estimating spatiotemporal pumping amounts using multiple signal decomposition methods. J. Hydrol. 2024, 633, 130856. [Google Scholar] [CrossRef]
- Brookfield, A.E.; Zipper, S.; Kendall, A.D.; Ajami, H.; Deines, J.M. Estimating Groundwater Pumping for Irrigation: A Method Comparison. Groundwater 2024, 62, 15–33. [Google Scholar] [CrossRef]
- Zhang, J.; Guan, K.; Zhou, W.; Jiang, C.; Peng, B.; Pan, M.; Grant, R.F.; Franz, T.E.; Suyker, A.; Yang, Y.; et al. Combining Remotely Sensed Evapotranspiration and an Agroecosystem Model to Estimate Center-Pivot Irrigation Water Use at High Spatio-Temporal Resolution. Water Resour. Res. 2023, 59, e2022WR032967. [Google Scholar] [CrossRef]
- Feng, X.; Bi, S.; Li, H.; Qi, Y.; Chen, S.; Shao, L. Soil moisture forecasting for precision irrigation management using real-time electricity consumption records. Agric. Water Manag. 2024, 291, 108656. [Google Scholar] [CrossRef]
- Qin, Y.; Cui, Y. A practical and efficient approach to evaluating the irrigation water supply from electricity consumption: A case study in Siyang County, China. Irrig. Drain. 2025, 74, 362–374. [Google Scholar] [CrossRef]
- Ke, H.; Zhang, F.; Sikai, Y.; Zhe, M.; Bin, X. Using Machine Learning Models to Forecast the Conversion Coefficient between Electricity Consumption and Water Pumped for Irrigation Wells in Baicheng City, China. Water 2024, 16, 523. [Google Scholar] [CrossRef]
- Mitra, A.; Balasubramanya, S.; Brouwer, R. Can cash incentives modify groundwater pumping behaviors? Evidence from an experiment in Punjab. Am. J. Agric. Econ. 2023, 105, 861–887. [Google Scholar] [CrossRef]
- Farrokhi Derakhshandeh, J.; Daghagh Yazd, S.; Attaran, S. Experimental and Practical Study of a Smart Irrigation System Utilizing the Internet of Things. J. Irrig. Drain. Eng. 2024, 150, 04024032. [Google Scholar] [CrossRef]
- Zhao, S.; Chen, J.; Chen, D.; Luo, Z.; Bi, B.; Lin, L.; Du, X.; Liu, Y.; Xia, Q. Optimizing Terminal Water Management in Irrigation District Using Water Balance and Genetic Algorithm. Agronomy 2024, 14, 2987. [Google Scholar] [CrossRef]
- Guo, H.; Li, S. A Review of Drip Irrigation’s Effect on Water, Carbon Fluxes, and Crop Growth in Farmland. Water 2024, 16, 2206. [Google Scholar] [CrossRef]
- Chauhdary, J.N.; Li, H.; Jiang, Y.; Pan, X.; Hussain, Z.; Javaid, M.; Rizwan, M. Advances in Sprinkler Irrigation: A Review in the Context of Precision Irrigation for Crop Production. Agronomy 2023, 14, 47. [Google Scholar] [CrossRef]
- Sahoo, S.R.; Agyeman, B.T.; Debnath, S.; Liu, J. Knowledge-Based Optimal Irrigation Scheduling of Agro-Hydrological Systems. Sustainability 2022, 14, 1304. [Google Scholar] [CrossRef]
- Qasim, S.; Qasim, M.; Hassan, A.; Murtaza, G.; Khan, A.N. A Comparative Analysis of Adopters and Non-adopters of Drip Irrigation under Plastic Tunnels for Cucumber (Cucumis sativus L.) Production in Balochistan, Pakistan. Irrig. Drain. 2022, 71, 635–647. [Google Scholar] [CrossRef]
- Yadav, A.; Sharma, N.; Upreti, H.; Singhal, G.D. Techno-economic analysis of irrigation systems for efficient water use in the backdrop of climate change. Curr. Sci. 2022, 122, 664. [Google Scholar] [CrossRef]
- Alnaim, M.A.; Mohamed, M.S.; Mohammed, M.; Munir, M. Effects of Automated Irrigation Systems and Water Regimes on Soil Properties, Water Productivity, Yield and Fruit Quality of Date Palm. Agriculture 2022, 12, 343. [Google Scholar] [CrossRef]
- Pronti, A.; Auci, S.; Berbel, J. Water conservation and saving technologies for irrigation. A structured literature review of econometric studies on the determinants of adoption. Agric. Water Manag. 2024, 299, 108838. [Google Scholar] [CrossRef]
- Sinha, R.; Borgomeo, E.; Fischer, C.; Hope, R. Do Rehabilitated Canals Influence Irrigation Technology Choices? Evidence From Smallholders in Madhya Pradesh, India. Water Econ. Policy 2021, 07, 2150017. [Google Scholar] [CrossRef]
- Fishman, R.; Giné, X.; Jacoby, H.G. Efficient irrigation and water conservation: Evidence from South India. J. Dev. Econ. 2023, 162, 103051. [Google Scholar] [CrossRef]
- Gil, J.D.; González, R.A.; Sánchez-Molina, J.A.; Berenguel, M.; Rodríguez, F. Reverse osmosis desalination for greenhouse irrigation: Experimental characterization and economic evaluation based on energy hubs. Desalination 2024, 574, 117281. [Google Scholar] [CrossRef]
- Wang, J.; Zhu, Y.; Sun, T.; Huang, J.; Zhang, L.; Guan, B.; Huang, Q. Forty years of irrigation development and reform in China. Aust. J. Agric. Resour. Econ. 2020, 64, 126–149. [Google Scholar] [CrossRef]
- Sinha, R.; Dadson, S.; Hope, R. Does subjective well-being matter when assessing the impacts of irrigation infrastructure? Empirical evidence from Madhya Pradesh, India. Irrig. Drain. 2022, 71, 155–168. [Google Scholar] [CrossRef]
- Zhou, T.; Liu, X.; Jia, S.; Sheng, Y. Exploring the Impact of Irrigation on China’s Crop TFP: Insights From a Structural Break Analysis. Asia Pac. Policy Stud. 2025, 12, e70007. [Google Scholar] [CrossRef]
- Wang, L.; Kinzelbach, W.; Yao, H.; Steiner, J.; Wang, H. How to Meter Agricultural Pumping at Numerous Small-Scale Wells?—An Indirect Monitoring Method Using Electric Energy as Proxy. Water 2020, 12, 2477. [Google Scholar] [CrossRef]
- Liu, X.; Ma, S.; Fang, Y.; Wang, S.; Guo, P. A novel approach to identify crop irrigation priority. Agric. Water Manag. 2023, 275, 108008. [Google Scholar] [CrossRef]
- Mai, Z.J.; He, Y.P.; Feng, C.; Han, C.Y.; Shi, Y.Z.; Qi, W. Multi-objective modeling and optimization of water distribution for canal system considering irrigation coverage in artesian irrigation district. Agric. Water Manag. 2024, 301, 108959. [Google Scholar] [CrossRef]
- Zhu, H.; Zheng, B.; Nie, W.; Fei, L.; Shan, Y.; Li, G.; Liang, F. Optimization of Maize Irrigation Strategy in Xinjiang, China By AquaCrop Based on a Four-year Study. Agric. Water Manag. 2024, 297, 108816. [Google Scholar] [CrossRef]
- Li, M.; Zhou, S.; Shen, S.; Wang, J.; Yang, Y.; Wu, Y.; Chen, F.; Lei, Y. Climate-smart Irrigation Strategy Can Mitigate Agricultural Water Consumption while Ensuring Food Security Under a Changing Climate. Agric. Water Manag. 2024, 292, 108663. [Google Scholar] [CrossRef]
- Chen, Y.; Li, H.; Xu, Y.; Fu, Q.; Wang, Y.; He, B.; Li, M. Sustainable Management in Irrigation Water Distribution System Under Climate Change: Process-driven Optimization Modelling Considering Water-food-energy-environment Synergies. Agric. Water Manag. 2024, 302, 108990. [Google Scholar] [CrossRef]
- Xu, H.; Song, J. Drivers of the Irrigation Water Rebound Effect: A Case Study of Hetao Irrigation District in Yellow River Basin, China. Agric. Water Manag. 2022, 266, 107567. [Google Scholar] [CrossRef]
- Li, X.; Yang, Y.; Zhou, X.; Liu, L.; Yang, Y.; Han, S.; Zhang, Y. Impact of Water Productivity and Irrigated Area Expansion on Irrigation Water Consumption and Food Production in China in Last Four Decades. Agric. Water Manag. 2024, 304, 109100. [Google Scholar] [CrossRef]
Time | 2023 | 2022 | 2021 |
---|---|---|---|
January | 2.74% | 8.59% | 4.39% |
February | 8.52% | 0.69% | 5.26% |
March | 4.58% | 7.20% | 1.14% |
April | 6.13% | 0.40% | 2.65% |
May | 0.75% | −6.22% | −2.89% |
June | 0.11% | 5.50% | 1.40% |
July | −12.75% | −4.94% | −11.16% |
August | −7.31% | −5.40% | −11.59% |
September | 6.81% | −0.13% | −5.82% |
October | 1.03% | 3.23% | 1.33% |
November | 2.34% | 1.77% | 3.09% |
December | 4.57% | −6.36% | 4.60% |
All year | 0.09% | 0.06% | −1.71% |
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Fang, X.; Yang, J. Implementation and Validation of an Electricity-Driven Water Conservation Method for Plain-Region Irrigation: A Control Method Based on Power-Consumption Feedback. Sustainability 2025, 17, 5281. https://doi.org/10.3390/su17125281
Fang X, Yang J. Implementation and Validation of an Electricity-Driven Water Conservation Method for Plain-Region Irrigation: A Control Method Based on Power-Consumption Feedback. Sustainability. 2025; 17(12):5281. https://doi.org/10.3390/su17125281
Chicago/Turabian StyleFang, Xuan, and Jie Yang. 2025. "Implementation and Validation of an Electricity-Driven Water Conservation Method for Plain-Region Irrigation: A Control Method Based on Power-Consumption Feedback" Sustainability 17, no. 12: 5281. https://doi.org/10.3390/su17125281
APA StyleFang, X., & Yang, J. (2025). Implementation and Validation of an Electricity-Driven Water Conservation Method for Plain-Region Irrigation: A Control Method Based on Power-Consumption Feedback. Sustainability, 17(12), 5281. https://doi.org/10.3390/su17125281