Journal of Water Resource and Protection, 2014, 6, 961-971 Published Online August 2014 in SciRes. http://www.scirp.org/journal/jwarp http://dx.doi.org/10.4236/jwarp.2014.611091 How to cite this paper: Pan, L., Adamchuk, V.I., Ferguson, R.B., Dutilleul, P.R.L. and Prasher, S.O. (2014) Analysis of Water Stress Prediction Quality as Influenced by the Number and Placement of Temporal Soil-Water Monitoring Sites. Journal of Water Resource and Protection, 6, 961-971. http://dx.doi.org/10.4236/jwarp.2014.611091 Analysis of Water Stress Prediction Quality as Influenced by the Number and Placement of Temporal Soil-Water Monitoring Sites Luan Pan 1 , Viacheslav I. Adamchuk 1* , Richard B. Ferguson 2 , Pierre R. L. Dutilleul 3 , Shiv O. Prasher 1 1 Department of Bioresource Engineering, McGill University, Ste-Anne-de-Bellevue, Canada 2 Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, USA 3 Department of Plant Science, McGill University, Ste-Anne-de-Bellevue, Canada Email: * viacheslav.adamchuk@mcgill.ca Received 20 June 2014; revised 16 July 2014; accepted 2 August 2014 Copyright © 2014 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract In an agricultural field, monitoring the temporal changes in soil conditions can be as important as understanding spatial heterogeneity when it comes to determining the locally-optimized applica- tion rates of key agricultural inputs. For example, the monitoring of soil water content is needed to decide on the amount and timing of irrigation. On-the-go soil sensing technology provides a way to rapidly obtain high-resolution, multiple data layers to reveal soil spatial variability, at a relatively low cost. To take advantage of this information, it is important to define the locations, which represent diversified field conditions, in terms of their potential to store and release soil water. Choosing the proper locations and the number of soil monitoring sites is not straightforward. In this project, sensor-based maps of soil apparent electrical conductivity and field elevation were produced for seven agricultural fields in Nebraska, USA. In one of these fields, an eight-node wire- less sensor network was used to establish real-time relationships between these maps and the Water Stress Potential (WSP) estimated using soil matric potential measurements. The results were used to model hypothetical WSP maps in the remaining fields. Different placement schemes for temporal soil monitoring sites were evaluated in terms of their ability to predict the hypothet- ical WSP maps with a different range and magnitude of spatial variability. When a large number of monitoring sites were used, it was shown that the probability for uncertain model predictions was relatively low regardless of the site selection strategy. However, a small number of monitoring sites may be used to reveal the underlying relationship only if these locations are chosen carefully. * Corresponding author.