Preprints
https://doi.org/10.5194/egusphere-2022-246
https://doi.org/10.5194/egusphere-2022-246
 
19 May 2022
19 May 2022

Accuracy of regional-to-global soil maps for on-farm decision making: Are soil maps “good enough”?

Jonathan J. Maynard1, Edward Yeboah2, Stephen Owusu2, Michaela Buenemann3, Jason C. Neff1, and Jeffrey E. Herrick4 Jonathan J. Maynard et al.
  • 1Sustainability Innovation Lab, University of Colorado, Boulder, Colorado, United States of America
  • 2CSIR-Soil Research Institute, Kwadaso, Kumasi, Ghana
  • 3Department of Geography, New Mexico State University, Las Cruces, New Mexico, United States of America
  • 4Jornada Experimental Range, Agricultural Research Service, United States Department of Agriculture, Las Cruces, New Mexico, United States of America

Abstract. A major obstacle to selecting the most appropriate crops and closing the yield gap in many areas of the world is a lack of site-specific soil information. Accurate information on soil properties is critical for identifying soil limitations and the management practices needed to improve crop yields. However, acquiring accurate soil information is often difficult due to the high spatial and temporal variability of soil properties at fine scales and the cost and inaccessibility of laboratory-based soil analyses. With recent advancements in predictive soil mapping, there is a growing expectation that soil map predictions can provide much of the information needed to inform soil management. Yet, it is unclear how accurate current soil map predictions are at scales relevant to management. The main objective of this study was to address this issue by evaluating the site-specific accuracy of regional-to-global soil maps, using Ghana as a test case. Four web-based soil maps of Ghana were evaluated using a dataset of 6,514 soil profile descriptions collected on smallholder farms using the LandPKS mobile application. Results from this study revealed that publicly available soil maps in Ghana lack the needed accuracy (i.e., correct identification of soil limitations) to reliably inform soil management decisions at the 1–2 ha scale common to smallholders. Standard measures of map accuracy for soil texture class and rock fragment class showed that all soil maps had similar performance in estimating the correct property class, with overall accuracies ranging from 8–39 % for soil texture classes and 26–33 % for soil rock fragment classes. Furthermore, there were substantial differences in soil property predictions among the four maps, highlighting that soil map errors are not uniform between maps despite their similar overall accuracies. To better understand the functional implications of these soil property differences, we used a modified version of the FAO Global Agro-Ecological Zone (GAEZ) soil suitability modelling framework to derive soil suitability ratings for each soil data source. Using a low-input, rain-fed, maize production scenario, we evaluated the functional accuracy of map-based soil property estimates. This analysis showed that soil map data significantly overestimated crop suitability for over 65 % of study sites, potentially leading to ineffective agronomic investments by farmers, including cash-constrained smallholders.

Jonathan J. Maynard et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-246', Colby Brungard, 22 Jun 2022
    • AC1: 'Reply on RC1', Jonathan Maynard, 28 Sep 2022
  • RC2: 'Comment on egusphere-2022-246', Anonymous Referee #2, 04 Aug 2022
    • AC2: 'Reply on RC2', Jonathan Maynard, 28 Sep 2022

Jonathan J. Maynard et al.

Jonathan J. Maynard et al.

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Short summary
Accurate information on soil properties is critical for identifying soil limitations and the management practices needed to improve crop yields on smallholder farms. This study evaluated the accuracy of soil map information for agronomic decision making. Based on four publicly available soil maps in Ghana, we found that soil map data significantly overestimated crop suitability, potentially leading to ineffective agronomic investments by smallholder farmers.