CornSoyWater: New Web and Mobile App to Aid Irrigation Management

CornSoyWater: New Web and Mobile App to Aid Irrigation Management

July 17, 2015

The UNL crop modeling team is pleased to announce the release of A web and mobile app, CornSoyWater helps irrigators determine in real-time the available soil water in a particular field and when to irrigate. The program currently covers Nebraska and its surrounding states and will be expanded to other states later. CornSoyWater combines CornWater and SoyWater, two separate irrigation decision support tools developed by UNL researchers.

CornSoyWater Sample Screen
Figure 1. Graphic display of the amount of soil available water (yellow line), threshold for triggering irrigation (red dashed line), crop water stress (red solid line), and crop stage (on X-axis). The graph title is your irrigation recommendation message.
CornSoyWater Sample ScreenFigure 2. Up-to-date crop water related summary that displays below the graph in Figure 1.
CornSoyWater Sample ScreenFigure 3. User-specified information for a field

Using real-time weather data and field specific crop information provided by the user, CornSoyWater uses simulation to track, from planting to now, crop water use, water inputs from rainfall and past irrigation, soil available water to the maximum rooting depth, and possible crop water stress. Irrigation is recommended for a field if crop water stress is indicated currently or within the next three days if no significant rainfall is expected.

In the background, CornSoyWater uses the Hybrid-Maize model and SoySim model to accomplish the following tasks for a specific field using real-time weather data for that area:

  • Simulate the up-to-date crop growth and development.
  • Track crop water use and water inputs from rainfall and past irrigations. Estimate the amount of soil available water to the maximum rooting depth.
  • Assess possible crop water stress based on soil water depletion and crop water uptake. Irrigation is recommended if crop water stress is likely occurring or will occur in the next three days.

CornSoyWater charts the amount of soil available water, available water threshold for triggering irrigation, crop water stress assessment, and the current crop stage (Figure 1).

Other features of the CornSoyWater program include:

  • Direct field identification using the Google map,
  • Automatic determination of average soil texture of the root zone for a field,
  • Showing all of a user's fields in one map in either red indicating need for irrigation or green indicating no need for irrigation, and
  • A summary table showing up-to-date critical information related to water status (Figure 2).

Besides the web application, CornSoyWater also has a smart phone app for iPhones and Androids. Users can download the app from Apple Store or Google Play. A water stress notification message will be sent to users every morning.

As with any simulation-based technology, the CornSoyWater program may produce results with significant errors, especially under unusual conditions. As a result, irrigators should exercise caution when using the program and should combine information from CornSoyWater with their current irrigation guidelines.

To use the CornSoyWater app, register (for free) for an account at To add a field to an account, provide required crop information, including planting date, maturity, plant population, and basic soil properties. Note that the average soil texture for the root zone of a field is, by default, auto-determined by the program using the online USDA-SSURGO database; however, when desired, the user can set it manually.

CornSoyWater Developers

The UNL core team developing CornSoyWater is led by Haishun Yang, crop simulation modeler in the Department of Agronomy and Horticulture, and includes James Han, PhD student, Department of Agronomy and Horticulture; William Sorensen, senior programmer analyst, School of Natural Resources; Stonie Cooper, Climate Center systems manager, SNR; and Dharmic Payyala, graduate assistant, Department of Computer Science and Engineering. The project team also includes UNL faculty and extension educators: Jenny Rees, Greg Kruger, Martha Shulski, Ken Hubbard, Derek Heeren, Suat Irmak, Gary Zoubek, Patricio Grassini, Ken Cassman, and Jim Specht.

The project is supported by funding from the Nebraska Corn Board, Nebraska Soybean Board, and the Nebraska Center for Energy Sciences Research under the program of Water, Energy and Agriculture Initiative (WEAI) – Phase 2.

James Han, PhD student, UNL Department of Agronomy and Horticulture
Haishun Yang, Crop Simulation Modeler, UNL Department of Agronomy and Horticulture

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