Comparison of Soil Physical Quality Indicators Using Direct and Indirect Data Inputs Derived from a Combination of In‐Situ and Ex‐Situ Methods. Issue 1 (14th February 2019) - Bacher, M. G.; Schmidt, O.; Bondi, G.; Creamer, R.; Fenton, O.
Abstract : Core Ideas: Soil quality indicators such as S and PAWC are considered as static indicators with low sensitivity. The soil quality indicator AWr is considered a dynamic indicator with high sensitivity. Indirect pedotransfer function based SWRCs are appropriate for static baseline indicators. Soil monitoring programs should use AWr as a sensitive and reliable soil quality indicator. The quality of a soil is its ability to deliver functions providing ecosystem services, human health and well‐being. Soil physical quality (SPQ) values use different parts of the soil water retention curve (SWRC) to calculate SPQ. For example, the plant available water capacity (PAWC) method is the difference in water content between permanent wilting point and field capacity. The S‐index uses the slope of the SWRC at its inflection point and the relative air‐water energy (AWr ) is the integral of "dry" divided by the "wet" area of the SWRC. Increasing demand for soil monitoring policies calls for reliable and sensitive soil quality indicators (SQIs). The objectives of the study were to assess the sensitivity and applicability of SPQ indicators using direct and indirect data inputs. The indirect approach provided sufficient data complexity for the PAWC and S‐index values, but the more complex AWr required the direct approach. PAWC and S‐index values were identified as static SPQ indicators. The values obtained from these approaches should be used to form baseline static datasets and therefore have an indicative role only. The AWr value was identified as a dynamic SPQ indicator and provided required sensitivity to pick up temporal changes in SPQ. This indicator could be used at multiple scales and could even guide grassland management in terms of SPQ. Higher SWRC data resolution will require more complex hydraulic models to fit and will ultimately improve the accuracy of soil hydraulic data and improve the sensitivity of AWr as a SPQ indicator.