Irrigation Decision Support Systems (IDSS) for California’s Water–Nutrient–Energy Nexus

Abstract

California has unsustainable use of agricultural water and energy, as well as problems of severe drought, nitrate pollution and groundwater salinity. As the leading producer and exporter of agricultural produce in the United States, 5.6 percent of California’s energy is currently used for pumping groundwater. These problems and new regulatory policies (e.g., Sustainable Groundwater Management Act, Irrigated Lands Regulatory Program) pressure growers to schedule, account and maintain records of water, energy and nutrients needed for crop and soil management. Growers require varying levels of decision support to integrate different irrigation strategies into farm operations. Decision support can come from the public or private sector, where there are many tradeoffs between cost, underlying science, user friendliness and overall challenges in farm integration. Thus, effective irrigation management requires clear definitions, decision support and guidelines for how to incorporate and evaluate the water–nutrient–energy nexus benefits of different practices and combinations of practices under shifting water governance. The California Energy Commission-sponsored Energy Product Evaluation Hub (Cal-EPE Hub) project has a mission of providing science-based evaluation of energy-saving technologies as a direct result of improved water management for irrigation in agriculture, including current and future irrigation decision support systems in California. This project incorporates end-user perceptions into evaluations of existing decision support tools in partnership with government, agricultural and private stakeholders. In this article, we review the policy context and science underlying the available irrigation decision support systems (IDSS), discuss the benefits/tradeoffs and report on their efficacy and ease of use for the most prevalent cropping systems in California. Finally, we identify research and knowledge-to-action gaps for incorporating irrigation decision support systems into new incentives and requirements for reporting water and energy consumption as well as salinity and nitrogen management in the state of California.

Crop water stress monitoring through precision technologies: A review

“…The combination of several sensor arrays with a web-based decision support tool measures realtime soil moisture data and direct transmission to a server allows farmers to monitor their fields in real time. Sensors put in the field collect data on crop features, soil type, irrigation network hydraulic properties, climate (historical and forecasted data) and information on water availability and crop production in order to produce an ideal weekly irrigation schedule [9] . Furthermore, DSS detects the amount of water used by crops in real time during the growing season to acquire an exact and employs many irrigation management indicators to assess irrigation water efficiency.…”

“…Furthermore, the web-based decision support tool's smart programming enables the entire system to make quick irrigation recommendation calculations. [9] Conclusions and Future Scopes Implementing an appropriate irrigation scheduling approach is essential in order to meet the demand for increased global food production while dealing with limited water resources. Thus, technical advancement in the irrigation sector through remote sensing, machine learning, deep learning, wireless sensor network for assessing crop water stress undoubtedly increase water use efficiency.…”

Relationships between Soil Moisture and Visible–NIR Soil Reflectance: A Review Presenting New Analyses and Data to Fill the Gaps

“…As moisture is a critical component of productive soils, it is important to be able to monitor soil MC across a landscape. In agricultural settings, the monitoring of soil MC allows the efficient allocation of resources (e.g., irrigation water), synchronisation of planting and harvest activities with climatic conditions, the prevention of salinisation and the maintenance of soil moisture levels for optimal crop growth, disease management and many other purposes [1][2][3][4][5]. In engineering scenarios, soil moisture is relevant to the behaviour and structural integrity of soils [6][7][8].…”

Detection of Water Leakage in Drip Irrigation Systems Using Infrared Technique in Smart Agricultural Robots

“…Apart from this, it is also important which crop to choose, as well as where to plant it. In this way, we have the chance to make decisions about irrigation techniques [37,38]. It is not desirable to have an excessive or inadequate amount of water in the field than expected.…”