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Rainfall induced landslides and soil erosion are part of a complex system ofmultiple interacting processes, and both are capable of significantly affectingsediment budgets. These sediment mass movements also have the potential tosignificantly impact on a broad network of ecosystems health, functionality andthe services they provide. To support the integrated assessment of theseprocesses it is necessary to develop reliable modelling architectures. Thispaper proposes a semi-quantitative integrated methodology for a robustassessment of soil erosion rates in data poor regions affected by landslideactivity. It combines heuristic, empirical and probabilistic approaches. Thisproposed methodology is based on the geospatial semantic array programmingparadigm and has been implemented on a catchment scale methodology usingGeographic Information Systems (GIS) spatial analysis tools and GNU Octave. Theintegrated data-transformation model relies on a modular architecture, wherethe information flow among modules is constrained by semantic checks. In orderto improve computational reproducibility, the geospatial data transformationsimplemented in ESRI ArcGis are made available in the free software GRASS GIS.The proposed modelling architecture is flexible enough for futuretransdisciplinary scenario analysis to be more easily designed. In particular,the architecture might contribute as a novel component to simplify futureintegrated analyses of the potential impact of wildfires or vegetation typesand distributions, on sediment transport from water induced landslides anderosion.

Estimating the effects of water-induced shallow landslides on soil erosion