Abstract

Conventional agricultural practices often lead to increased soil compaction, a decline in soil organic matter (SOM) and an associated decrease in structural porosity, compromising the water holding capacity and resilience of agricultural soils to hydrological extremes. Regenerative agriculture practices, with their focus on building healthy soil ecosystems, hold promises for enhancing agricultural resilience to extreme weather events like floods and droughts. These practices, such as reduced tillage, reduced trafficking and stocking density, cover cropping, and afforestation, can improve soil organic matter content, reduce compaction, enhance soil structure, and promote microbial activity, leading to increased soil porosity, water infiltration, and retention. However, due to the slow response of soils to changes in agricultural management, a critical research gap exists in the timely quantification of the potential effectiveness of these practices in mitigating flood and drought risks. Although undoubtedly robust and informative, long-term monitoring of soil properties before and after a management intervention may take decadal timescales to reveal any significant impacts.We have therefore adopted an exploratory approach to investigate the merits of back-analysing existing long-term soil moisture datasets to reveal any changes in inferred soil porosity due to changes in land use and/or management. The following UKCEH long-term datasets, which include soil moisture information, have been considered: Neutron Probe Soil Moisture Database (~50 years range), UK Greenhouse Gases Flux Network (last 15+ years), and COSMOS-UK TDT probe data (last 10 years). In addition, we have land cover information from UKCEH Land Cover Maps from 1990 onwards. For UK conditions, it is anticipated that an annual maximum soil moisture content, representing saturated conditions, is likely to be attained during most winter seasons (excluding any ‘dry’ winters, excluded based on rainfall data). It is then possible to estimate soil porosity in any particular year by equating it to the maximum soil moisture content, in effect using this as a proxy measurement with due regard for potential air entrapment effects. Any identified long-term changes in soil porosity obtained through trend, wavelet, and before-after-control-impact analysis might then be linked to changes in land use and/or management. Land cover changes may be identified using Land Cover Map data and local site knowledge, the latter of which will also provide insights into changes in land management. COSMOS-UK TDT data is particularly interesting in terms of land management impacts as, when installed, the instrumentation at each site was enclosed by a newly erected fence. The resultant compound therefore excluded stock and vehicle trafficking and initiated a change in land use from generally arable or improved grassland to rough grassland. It will therefore be valuable to understand if the proposed exploratory analysis approach can reveal any significant changes in soil porosity over time due to this intervention. Likely challenges to be discussed include disentangling any long-term changes in maximum soil moisture due to changes in soil porosity from background changes in climate. We will also share lessons learned and provide recommendations for future work on the back-analysis of long-term soil moisture datasets.    

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