<em>In Situ</em> Soil Moisture Sensors in Undisturbed Soils

Soil moisture directly affects operational hydrology, food security, ecosystem services, and the climate system. However, the adoption of soil moisture ...

U.S. Department of Agriculture

An Egyptian national program targets annual reuse of 2.4 billion m3 of treated wastewater (TWW) to irrigate 84,000 ha of manmade forests in areas close to treatment plants and in the desert. To evaluate the feasibility of such afforestation efforts, we describe information about TWW irrigation strategies based on (1) water use of different tree species, (2) weather conditions in different climate zones of Egypt, (3) soil types and available irrigation systems, and (4) the requirement to avoid deep percolation losses that could lead to groundwater contamination. We conclude that drip irrigation systems are preferred, that they should in most cases use multiple emitters per tree in order to increase wetted area and decrease depth of water penetration, that deep rooting should be encouraged, and that in most situations irrigation system automation is desirable to achieve several small irrigations per day in order to avoid deep percolation losses. We describe directed research necessary to fill knowledge gaps about depth of rooting of different species in sandy Egyptian soils and environments, tree crop coefficients needed for rational irrigation scheduling, and depth of water penetration under different irrigation system designs. A companion paper addresses recommendations for afforestation strategies (see Zalesny et al. 2011, this issue).

Opportunities for woody crop production using treated wastewater in Egypt. II. Irrigation strategies.

Knowledge of crop abiotic and biotic stress is important for optimal irrigation management. While spectral reflectance and infrared thermometry provide a means to quantify crop stress remotely, these measurements can be cumbersome. Computer vision offers an inexpensive way to remotely detect crop stress independent of vegetation cover. This paper presents a technique using computer vision to detect disease stress in wheat. Digital images of differentially stressed wheat were segmented into soil and vegetation pixels using expectation maximization (EM). In the first season, the algorithm to segment vegetation from soil and distinguish between healthy and stressed wheat was developed and tested using digital images taken in the field and later processed on a desktop computer. In the second season, a wireless camera with near real-time computer vision capabilities was tested in conjunction with the conventional camera and desktop computer. For wheat irrigated at different levels and inoculated with wheat streak mosaic virus (WSMV), vegetation hue determined by the EM algorithm showed significant effects from irrigation level and infection. Unstressed wheat had a higher hue (118.32) than stressed wheat (111.34). In the second season, the hue and cover measured by the wireless computer vision sensor showed significant effects from infection (p = 0.0014), as did the conventional camera (p < 0.0001). Vegetation hue obtained through a wireless computer vision system in this study is a viable option for determining biotic crop stress in irrigation scheduling. Such a low-cost system could be suitable for use in the ﬁeld in automated irrigation scheduling applications. 

Development of a wireless computer vision instrument to detect biotic stress in wheat.

Accurate estimates of actual crop evapotranspiration (ET) are important for optimal irrigation water management, especially in arid and semi-arid regions. Common ET sensing methods include Bowen Ratio, Eddy Covariance (EC), and scintillometers. Large weighing lysimeters are considered the ultimate standard for measurement of ET, however, they are expensive to install and maintain. Although EC and scintillometers are less costly and relatively portable, EC has known energy balance closure discrepancies. Previous scintillometer studies used EC for ground-truthing, but no studies considered weighing lysimeters. In this study, a Surface Layer Scintillometer (SLS) was evaluated for accuracy in determining ET as well as sensible and latent heat fluxes, as compared to a large weighing lysimeter in Bushland, TX. The SLS was installed over irrigated grain sorghum ( (L.) Moench) for the period 29 July-17 August 2015 and over grain corn ( L.) for the period 23 June-2 October 2016. Results showed poor correlation for sensible heat flux, but much better correlation with ET, with r² values of 0.83 and 0.87 for hourly and daily ET, respectively. The accuracy of the SLS was comparable to other ET sensing instruments with an RMSE of 0.13 mm·h (31%) for hourly ET; however, summing hourly values to a daily time step reduced the ET error to 14% (0.75 mm·d). This level of accuracy indicates that potential exists for the SLS to be used in some water management applications. As few studies have been conducted to evaluate the SLS for ET estimation, or in combination with lysimetric data, further evaluations would be beneficial to investigate the applicability of the SLS in water resources management.

Steven R. Evett

Agricultural Research Service,
Conservation and Production Research Lab.,
Agricultural Research Service, Conservation and Production Research Lab.

U.S. Department of Agriculture

In Situ Soil Moisture Sensors in Undisturbed Soils

Steven R. Evett

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Agricultural Research Service,Conservation and Production Research Lab.,Agricultural Research Service, Conservation and Production Research Lab.

U.S. Department of Agriculture

In Situ Soil Moisture Sensors in Undisturbed Soils

Agricultural Research Service,
Conservation and Production Research Lab.,
Agricultural Research Service, Conservation and Production Research Lab.