Decision support systems for agriculture 4.0: Survey and challenges

http://hydrologydays.colostate.edu/Abstracts_10/Kinzli_abs.pdf

Using an ADCP to determine canal seepage loss in an irrigation district

Problems, Perspectives and Challenges of Agricultural Water Management

Modelling and multicriteria analysis of water saving scenarios for an irrigation district in the upper Yellow River Basin

C5.0: Advanced Decision Tree (ADT) classification model for agricultural data analysis on cloud

Water is the lifeblood of the American West and the foundation of its economy, but it remains its scarcest resource The explosive population growth in western United States, the emerging additional need for water for environmental uses, and the national importance of the domestic food production are driving major conflicts between these competing water uses The case of the Middle Rio Grande illustrates the problem very well The river is the ecological backbone of the Chihuahuan Desert region in the western United States, and supports its dynamic and diverse ecology, including the fish and wildlife habitat The Rio Grande Silvery Minnow is federally listed as an endangered species, and the irrigated agriculture in the Middle Rio Grande has come under increasing pressure to reduce its water consumption and maintain the desired level of service to its water users This paper will present the writers ongoing research on options to make irrigation system operations more efficient in the Middle Rio Grande Conservancy District (MRGCD) Specifically, it will describe formulation and implementation of a decision support system (DSS) that can assist the MRGCD managers to more efficiently plan and implement their water delivery operations, thereby reducing river diversions The MRGCD DSS uses linear programming to find an optimum water delivery schedule for canal service areas in the MRGCD irrigation system The computer model is presently formulated along with the related data sets for two of the four divisions in the MRGCD For the past 3 years, the model has been validated in the field and the evaluation indicates that the model recommendations are realistic and represent current management practices The future plans are to complete the data files for the irrigation networks in the remaining two divisions and concurrently help the MRGCD implement the DSS to guide water delivery operation

Decision Support Systems for Efficient Irrigation in the Middle Rio Grande Valley

Water is the lifeblood of the American West and the foundation of its economy, but it remains its scarcest resource. The explosive population growth in western urban areas, the emerging need for water for environmental and recreational uses, and the national importance of the domestic food production from western farms are driving major conflicts between these competing water uses (US Department of Interior, 2003). Irrigated agriculture in particular is by far the largest water user – 80% countrywide and 90% in the Western U.S – and since it is perceived to be a comparatively inefficient user, it is frequently asked to decrease its water consumption. Irrigated agriculture in the Middle Rio Grande diverts large quantities of river water, which is believed to leave insufficient water to meet other societal needs such as urban and wildlife requirements. This paper will present our research on options to make irrigation system operations more efficient. Most irrigation systems can meet their users’ needs with decreased river diversions by adopting operational procedures, which are based on real-time knowledge of available water supplies and crop water requirements. The paper will describe our on-going research in the Middle Rio Grande Valley, to develop a Decision-Support System (DSS) that can assist water managers to closely match water deliveries to crop water requirements, thereby reducing river diversions. The DSS uses linear programming logic with an objective function to find an optimum water delivery schedule for the service areas in an irrigation system. Water delivery using the DSS is accomplished using three modules: a water demand module, a supply network module and an irrigation scheduling module. Limited field validation shows that the DSS is indeed able to correctly model the irrigation delivery system, and recommend water delivery schedules that are reasonable. Future plans include more intensive field validation and implementation in the Middle Rio Grande irrigation service area.

/pdf/decision-support-systems-for-efficient-irrigated-agriculture-2db5tkmgor.pdf

Decision support systems for efficient irrigated agriculture

The Colorado State University Irrigation and Drainage model (CSUID) is a decision support system (DSS) that helps design and/or manage irrigation and drainage systems, which maintain crop productivity while controlling drainage return flows. CSUID includes components for irrigation scheduling; root growth calculations; flow and transport in unsaturated and saturated zones; drain discharge; and crop yield estimates. The DSS runs on a PC with Windows 95/NT. Data for the model is currently being collected from four fields in Colorado's Arkansas River Basin.

A decision support system for field drainage management.

South Platte Mapping and Analysis Program (SPMAP) : decision support tools for the lower South Platte

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Dave Patterson

Author Tools

Chat about Author

Papers

Decision Support Systems for Efficient Irrigation in the Middle Rio Grande Valley

Decision support systems for efficient irrigated agriculture

A decision support system for field drainage management.

South Platte Mapping and Analysis Program (SPMAP) : decision support tools for the lower South Platte