Combining Evapotranspiration and Soil Apparent Electrical Conductivity Mapping to Identify Potential Precision Irrigation Benefits
by
Mallika A. Nocco 1,6,*
, Samuel C. Zipper 2, Eric G. Booth 3,4, Cadan R. Cummings 5, Steven P. Loheide II 4 and Christopher J. Kucharik 1,3
Mallika A. Nocco 1,6,*, Samuel C. Zipper 2, Eric G. Booth 3,4, Cadan R. Cummings 5, Steven P. Loheide II 4 and Christopher J. Kucharik 1,3
1
Nelson Institute Center for Sustainability and the Global Environment, University of Wisconsin-Madison, 1710 University Ave., Madison, WI 53726, USA
2
Kansas Geological Survey, University of Kansas, 1930 Constant Ave, Lawrence, KS 66047, USA
3
Department of Agronomy, University of Wisconsin-Madison, 1575 Linden Dr., Madison, WI 53706, USA
4
Department of Civil and Environmental Engineering, University of Wisconsin-Madison, 1415 Engineering Dr., Madison, WI 53706, USA
5
Department of Soil, Water, and Climate, University of Minnesota-Twin Cities, 1991 Upper Buford Circle, St. Paul, MN 55108, USA
6
Department of Land, Air, and Water Resources, University of California, Davis; One Shields Avenue, Davis, CA 95616, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(21), 2460; https://doi.org/10.3390/rs11212460
Received: 6 September 2019 / Revised: 16 October 2019 / Accepted: 16 October 2019 / Published: 23 October 2019
(This article belongs to the Special Issue Advances of Multi-Temporal Remote Sensing in Vegetation and Agriculture Research)
Precision irrigation optimizes the spatiotemporal application of water using evapotranspiration (ET) maps to assess water stress or soil apparent electrical conductivity (ECa) maps as a proxy for plant available water content. However, ET and ECa maps are rarely used together. We developed high-resolution ET and ECa maps for six irrigated fields in the Midwest United States between 2014–2016. Our research goals were to (1) validate ET maps developed using the High-Resolution Mapping of EvapoTranspiration (HRMET) model and aerial imagery via comparison with ground observations in potato, sweet corn, and pea agroecosystems; (2) characterize relationships between ET and ECa; and (3) identify potential precision irrigation benefits across rotations. We demonstrated the synergy of combined ET and ECa mapping for evaluating whether intrafield differences in ECa correspond to actual water use for different crop rotations. We found that ET and ECa have stronger relationships in sweet corn and potato rotations than field corn. Thus, sweet corn and potato crops may benefit more from precision irrigation than field corn, even when grown rotationally on the same field. We recommend that future research consider crop rotation, intrafield soil variability, and existing irrigation practices together when determining potential water use, savings, and yield gains from precision irrigation.
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Keywords:
precision agriculture; precision irrigation; evapotranspiration; apparent electrical conductivity; proximal sensing; soil water content; crop rotations; coarse-textured soils; aerial remote sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Nocco, M.A.; Zipper, S.C.; Booth, E.G.; Cummings, C.R.; Loheide, S.P., II; Kucharik, C.J. Combining Evapotranspiration and Soil Apparent Electrical Conductivity Mapping to Identify Potential Precision Irrigation Benefits. Remote Sens. 2019, 11, 2460.
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