Satellite monitoring of yield responses to irrigation practices across thousands of fields

Geographic information systems (GIS) present new opportunities for empirical agronomic research that can complement experimental and modeling approaches. In this study, GIS databases of irrigation practices for more than 4000 fields were compared with wheat yields derived from remote sensing for five growing seasons in the Yaqui Valley of Northwest Mexico. Significant yield effects were observed for both number and timing of irrigations, but not for reported water volumes, suggesting that proper timing is more important to yields than total water amounts. In most years, yield losses were observed when the second irrigation occurred more than 60 d after preplant irrigation, with an average loss of 11 kg ha -1 for each day above this value. Overall, we estimate that optimal timing and number of irrigations for all fields in Yaqui Valley could increase average yields by roughly 5%. Results varied by year, in part because of variability in growing season rainfall and in part because of variations in water allocations. Interactions with soil types were also evident, with greater yield variability attributed to irrigation on soils with higher clay contents. The results of this study provide new insight into specific causes of yield losses in farmers' fields, which can inform future field experiments, management, and water policy in this region. In general, empirical studies of large GIS databases can help to improve crop management, and meet the dual needs of higher yields and improved water use efficiency.

[1]  R. A. Fischer,et al.  Number of kernels in wheat crops and the influence of solar radiation and temperature , 1985, The Journal of Agricultural Science.

[2]  James W. Jones,et al.  Wading through a swamp of complete confusion: how to choose a method for estimating soil water retention parameters for crop models , 2002 .

[3]  David B. Lobell,et al.  Evaluating strategies for improved water use in spring wheat with CERES , 2006 .

[4]  David B. Lobell,et al.  Remote sensing of regional crop production in the Yaqui Valley, Mexico: estimates and uncertainties , 2003 .

[5]  Frédéric Baret,et al.  Spectral estimates of the absorbed photosynthetically active radiation and light-use efficiency of a winter wheat crop subjected to nitrogen and water deficiencies† , 1990 .

[6]  David B. Lobell,et al.  Remote sensing assessment of regional yield losses due to sub-optimal planting dates and fallow period weed management , 2007 .

[7]  Jeffrey W. White,et al.  Insufficient geographic characterization and analysis in the planning, execution and dissemination of agronomic research? , 2002 .

[8]  James W. Jones,et al.  The DSSAT cropping system model , 2003 .

[9]  David B. Lobell,et al.  Analysis of wheat yield and climatic trends in Mexico , 2005 .

[10]  J. I. Ortiz-Monasterio,et al.  Combining Field Surveys, Remote Sensing, and Regression Trees to Understand Yield Variations in an Irrigated Wheat Landscape , 2005, Agronomy Journal.

[11]  Gen-xuan Wang,et al.  Effect of water deficits on within-plot variability in growth and grain yield of spring wheat in northwest China , 2003 .

[12]  Kenneth G. Cassman,et al.  Meeting Cereal Demand While Protecting Natural Resources and Improving Environmental Quality , 2003 .

[13]  J. Wallace Increasing agricultural water use efficiency to meet future food production , 2000 .

[14]  J. Monteith Climate and the efficiency of crop production in Britain , 1977 .

[15]  David B. Lobell,et al.  Regional importance of crop yield constraints: Linking simulation models and geostatistics to interpret spatial patterns , 2006 .