Thomas J. Trout

Satellite Irrigation Management Support With the Terrestrial Observation and Prediction System: A Framework for Integration of Satellite and Surface Observations to Support Improvements in Agricultural Water Resource Management

In California and other regions vulnerable to water shortages, satellite-derived estimates of key hydrologic fluxes can support agricultural producers and water managers in maximizing the benefits of available water supplies. The Satellite Irrigation Management Support (SIMS) project combines NASAs Terrestrial Observation and Prediction System (TOPS), Landsat and MODIS satellite imagery, and surface sensor networks to map indicators of crop irrigation demand and develop information products to support irrigation management and other water use decisions. TOPS-SIMS provides the computing and data processing systems required to support automated, near real-time integration of observations from satellite and surface sensor networks, and generates data and information in formats that are convenient for agricultural producers, water managers, and other end users. Using the TOPS modeling framework to integrate data from multiple sensor networks in near real-time, SIMS currently maps crop fractional cover, basal crop coefficients, and basal crop evapotranspiration. Map products are generated at 30 m resolution on a daily basis over approximately 4 million ha of California farmland. TOPS-SIMS is a fully operational prototype, and a publicly available beta-version of the web interface is being pilot tested by farmers, irrigation consultants, and water managers in California. Data products are distributed via dynamic web services, which support both visual mapping and time-series queries, to allow users to obtain information on spatial and temporal patterns in crop canopy development and water requirements. TOPS-SIMS is an application framework that demonstrates the value of integrating multi-disciplinary Earth observation systems to provide benefits for water resource management.

Furrow Inflow and Infiltration Variability

ABSTRACT THE furrow-to-furrow variability of irrigation water inflows is about twice as great with gated pipe and feed ditches as with siphon tubes. The average furrow infiltration coefficient of variation measured on 25 fields in southern Idaho was 25%. As a result of both variabilities, irrigation times and application rates must be increased to insure adequate water application to a desired portion of the field.

WATER PRODUCTION FUNCTIONS FOR CENTRAL PLAINS CROPS

Sustaining irrigated agriculture with limited water supplies requires maximizing productivity per unit of water. Relationships between crop production and water consumed are basic information required to maximize productivity. This information can be used to determine if deficit irrigation is economically desirable and how to best manage limited water supplies. Field trials of corn, sunflower, dry bean, and wheat production with six levels of water application were used to develop water production functions based on consumptive use and to better understand water timing effects and crop responses to stress. Initial results indicate linear relationships between yield and crop ET and transpiration. The field data are being used to improve and validate crop models so they can be used to generalize the field results for other climate and soil characteristics.

Use of Crop Canopy Size to Estimate Crop Coefficient for Vegetable Crops

Planting time, plant density, variety, and cultural practices vary widely for horticultural crops. It is difficult to estimate a basal crop coefficient that can incorporate these variations. Canopy cover, as an indicator of intercepted sunlight, is related to crop water use. We used a weighing lysimeter to measure daily crop water use and a multi-spectral camera to measure canopy cover for two vegetable crops – head lettuce and bell pepper, and related canopy cover to basal crop coefficient. The ratio of crop coefficient to canopy cover declined from about 4 with small canopy cover (0.1) to about 1.3 for a mature crop with canopy cover of 0.9. The relationship was similar for these two crops. Because light interception other than at mid-day will depend on the canopy structure, adjustment may be needed for canopy structure. A generalized canopy cover:basal crop coefficient relationship would allow weatherbased irrigation scheduling for a wide range of horticultural crops based on canopy measurements, and possibly based on remotely-sensed vegetation indices.

Estimation of Furrow Irrigation Sediment Loss Using an Artificial Neural Network

AbstractThe area irrigated by furrow irrigation in the United States has been steadily decreasing but still represents about 20% of the total irrigated area in the United States. Furrow irrigation sediment loss is a major water quality issue, and a method for estimating sediment loss is needed to quantify the environmental effects and estimate effectiveness and economic value of conservation practices. Artificial neural network (NN) modeling was applied to furrow irrigation to predict sediment loss as a function of hydraulic and soil conditions. A data set consisting of 1,926 furrow evaluations, spanning three continents and a wide range of hydraulic and soil conditions, was used to train and test a multilayer perceptron feed forward NN model. The final NN model consisted of 16 inputs, 19 hidden nodes in a single hidden layer, and 1 output node. Model efficiency (ME) of the NN model was ME=0.66 for the training data set and ME=0.80 for the test data set. The prediction performance for the complete data se...