Rossano Ciampalini

Forests support a broad range of ecosystem services. These services cannot simply be traced back to the individual biotic and abiotic components of the forest ecosystems. Rather, they stem from complex interactions between these components. CON.ECO.FOR, the Italian branch of the ICP-Forests (International Co-operative Program on Assessment and Monitoring of Air Pollution Effects on Forests) network, established in 1994, has shown to be a unique data source for understanding forest interactions and processes. This contribution aims to draw a comprehensive picture of the Italian forest soil conditions by reviewing the main issues that have arisen and the results obtained over the last 30 years of forest soil monitoring. Forest health is often controlled by soil-mediated processes. Thus, we have evidenced how including soil parameters in environmental studies has proven to be of high value for a better understanding of forest ecosystem conditions and trends. Here, we are reviewing all of the results obtained concerning soils from the analyses of the impacts of atmospheric deposition on forest soils to the study of the relationships between organism diversity and the soil.

Water management in agricultural systems is essential for optimal crop yields without incurring excessive water costs and wastage. The choice of irrigation method is crucial for better water management and distribution. The drip system appears to be among the best methods in the field of precision agriculture. In addition to the irrigation system, mulching with ridge plastic film to drain excess water is widely used to increase crop yields in terms of plant water availability.In this study, the time-lapse Electrical Resistivity Tomography (ERT), a not-invasive geophysical technique, is proposed as a simple and reliable method to evaluate the effectiveness of the irrigation systems and to monitor the changes in water content over time and over a volume of soil. ERTs data were compared to moisture one retrieved from sensors that record continuously over time, but punctually. The ERT investigations were conducted in melon-growing lands in southern Tuscany (Italy).The aim of the work was to evaluate, by means of volumetric measures of the soil conductivity, the effectiveness of three different drip systems and of the mulch ridge: a two-wings drip system and a three-wings drip line with the same flow rate and a three-wings drip lines with a higher flow, in two different seasonal periods (spring and summer). In both the monitored fields the ridge was created in a half portion of the field itself, while in the other part the land was left plat.The data collected showed that the 2-wing system was particularly ineffective, and that the distribution of irrigation water favoured some areas more than others. While they led to satisfactory results for the 3-wing system and same water flow than two wings and the 3-wing system and highest water flow. The first system has shown that the same quantity of water as the classic irrigations system (two wings) distributed over three wings instead of two leads to a greater concentration of water in the root zone over time, slowly draining downwards. On the contrary, the second system distributes the water uniformly like the first system, but the quantity introduced was excessive, leading the soil to always be positioned above the field capacity and draining a lot of water downwards. The excessive accumulation of water below the root zone represents a waste of water, as this cannot be used by the root system. The tests, in addition to considering which system was optimal, also evaluated the effectiveness of the mulch ridge, leading to the deduction that during the spring season a ridge of height equal to or greater than 20 cm is to be considered better than a ridge of less than 20 cm or absent, as it allows excess water, represented by rainfall, to be drained. However, during the summer period, when rainfall is less if not absent, the presence of a much lower ridge (around 10 cm in height) is much more effective as it allows the irrigation water to be retained at the root system avoiding excessive drainage.

Water erosion is one of the most widespread forms of soil degradation and it is expected to increase as an effect of global change, especially due to the amplified frequency of extreme and localised rainfall events. Focusing on the Mediterranean region, where these phenomena persist producing the most catastrophic erosion, this research aims to model soil erosion focusing on patterns and spatial distribution using rainfall data as detected by weather ground-radar upon an analysis of rainfall-cell patterns at regional scale (Tuscany, Italy).Precipitations were elaborated by adopting a kriging method processing CAPPI (Constant Altitude Plan Position Indicator) reflectivity and rain gauges rainfall with an External Drift Kriging (KED) over a 30' time-step frames. Soil erosion was modelled using the platform based on the soil erosion/landscape evolution model LandSoil under Python coding simulating runoff combining a cinematic wave using St.Venant equations on a simplified “bucket” conceptual model for soil infiltration, and a two-level sediment redistribution process for rill and inter-rill erosion.Soil erosion was simulated over a selection of rainfall events over the last ten years and results illustrated through a combined representation of factors that considers: 1. The sediment yield produced over the erosive event, 2. The land surface affected by the storm (i.e., rainfall-cell patterns of the event and subjected to runoff), 3. The involved rainfall energy and erosion rate of the processes. Such approach, applied to seasonal analysis, opens-up to a methodology better analysing spatial extent and effects on the ground. Drifts in erosion could be also detected by the use of long-terms rainfall series and return-time of the erosive events, useful to inspect evolution of the processes due to climate change.

Climate change can lead to significant environmental and societal impacts; for example, through increases in the amount and intensity of rainfall with the associated possibility of flooding. Twenty-first-century climate change simulations for Great Britain reveal an increase in heavy precipitation that may lead to widespread soil loss by rising the likelihood of surface runoff. Here, hourly high-resolution rainfall projections from a 1.5 km (‘convection-permitting’) regional climate model are used to simulate the soil erosion response for two periods of the century (1996–2009 and a 13-year future period at ~2100) in the “Rother” catchment, West Sussex, England. Modeling soil erosion with EROSION 3D, we found a general increase in sediment production (off-site erosion) for the end of the century of about 43.2%, with a catchment-average increase from 0.176 to 0.252 t ha⁻¹ y⁻¹ and large differences between areas with diverse land use. These results highlight the effectiveness of using high-resolution rainfall projections to better account for spatial variability in the assessment of long-term soil erosion than other current methods.

Radar-based rainfall estimation represents an effective tool for hydrological modelling. Nevertheless, this data type is subject to systemic and natural perturbations that need to be considered before to use it. Because of that and to improve data quality, corrections based on raingauge observations are frequently adopted. Here, we compared the efficacy of different radar-raingauge merging procedures over a regional raingauge-radar network focusing on a selected number of rainfalls events.We adopted the methods: 1) Kriging with External Drift (KED) interpolation (Wackernagel 1998), 2) Probability-Matching-Method (PMM, Rosenfeld et al., 1994), and 3) a kriging mixed method exploiting the Conditional Merging (CM) process (Sinclair-Pegram, 2005) based on elaborations available at DPCN (Italian National Civil Protection Department). These methods have been applied on the Tuscany Regional Territory using raingauge recorded rainfalls at 15’ time-step and CAPPI (Constant altitude plan position indicator) reflectivity data at 2000/3000/5000 m at 5’ and 10’.Relationships describing precipitation VS radar reflectivity were integrated and elaborated as part of the development of the merging procedures, while the comparison involved the analysis of variance and diversity coefficients. Kriging-based elaborations showed different spatial patterns depending on the applied procedure, with patterns closer to radar variability when using DPCN, and more reflecting the gauge data structure when adopting KED. The probabilistic method (PMM), instead, had the advantage of integrating the gauge data while preserving the spatial radar patterns, confirming interesting perspectives.

Soil erosion is a balance between forces acting to detach and transport sediment and those resisting, such as soil cohesion or protection of vegetation cover. The amount of eroded particles is proportional to the acting forces, but the feedback, as is widely acknowledged, has a non-linear behaviour. Moreover, most of the erosion is concentrated in the strongest events, as evidenced by many authors.Here, in a long-term simulation, we investigate the occurrence of the size of the erosion events in a vineyard catchment area. We analysed around 700 rainfall events over 20 years from two climate series (historical 1985-2005, and and future 2040-2060), and four contrasted land use and management scenarios.The results confirmed that the erosion is driven by a limited number of strong events with an increment in future series due to an increase in frequency of the more severe rainfall events. We observed that: 1) Size of erosion events VS return time exhibit different logarithmic trends in each LU scenario; 2) Long-term erosion series show that the few major erosion phases are due to a limited number of events, the most severe; 3) The concentration of erosion events towards the highest values is more pronounced in intensified landscape indicating more reactive erosion than in protected landscapes.This suggests that controlling the state of intensification of a landscape (i.e. intensified or preserved) can mitigate soil erosion even if climate change tends to increase erosion rates.

Scenarios serve science by testing the sensitivity of a system and/or society to adapt to the future. In this study, we present a new land use scenario methodology called ScenaLand. This methodology aims to develop plausible and contrasting land use and management (LUM) scenarios, useful to explore how LUM (e.g. soil and water conservation techniques) may affect ecosystem services under global change in a wide range of environments. ScenaLand is a method for constructing narrative and spatially explicit land use scenarios that are useful for end-users and impact modellers. This method is innovative because it merges literature and expert knowledge, and its low data requirement makes it easy to be implemented in the context of inter-site comparison, including global change projections. ScenaLand was developed and tested on six different Mediterranean agroecological and socioeconomic contexts during the MASCC research project (Mediterranean agricultural soil conservation under global change). The method first highlights the socioeconomic trends of each study site including emerging trends such as new government laws, LUM techniques through a qualitative survey addressed to local experts. Then, the method includes a ranking of driving factors, a matrix about land use evolution, and soil and water conservation techniques. ScenaLand also includes a framework to develop narratives along with two priority axes (contextualized to environmental protection vs. land productivity in this study). In the context of this research project, four contrasting scenarios are proposed: S1 (business-as-usual), S2 (market-oriented), S3 (environmental protection), and S4 (sustainable). Land use maps are then built with the creation of LUM allocation rules based on agroecological zoning. ScenaLand resulted in a robust and easy method to apply with the creation of 24 contrasted scenarios. These scenarios come not only with narratives but also with spatially explicit maps that are potentially used by impact modellers and other end-users. The last part of our study discusses the way the method can be implemented including a comparison between sites and the possibilities to implement ScenaLand in other contexts.

Soil erosion by water is one of the most widespread forms of soil degradation responsible for relevant agricultural productivity losses. Under climate change, soil erosion is expected to increase mostly for a rising of the frequency of extreme and localised events. In intense hydrological phenomena such as flooding, and soil erosion, the spatiotemporal extent significantly impacts these phenomena, especially in extreme events. Therefore, an approach directed to better refine to understand such dynamics is recommended.Here, we present the MSCA – SED RUNS project, focusing on the extreme rainfall effects on soil erosion using ground-weather-radar observations and hydrological modelling at regional scale (namely in Tuscany, central Italy).The approach, based on statistical analysis and modelling methods, aims to: 1) Quantifying, over the last decade, the spatiotemporal distribution of extreme rainfalls / runoff and soil erosion, 2) Building a platform to model runoff and soil erosion for extreme events, 3) Simulating in real-time runoff and soil erosion as a precursor of for a regional-warning-system for extreme weather events.Rainfall data will be provided by the national and regional institutions such as LaMMA Consortium (Tuscany Meteorological Agency) and the “Italian Civil Protection”, whose radar dataset of the national network (DPCN) covers the 2010–2020 period, with a spatial resolution of 1 km in a 10-mins time-step.The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie, Grant Agreement n. 101033236.

Wildfire is known to create the pre-conditions leading to accelerated soil erosion. Unfortunately, its occurrence is expected to increase with climate change. The objective of this study was to assess the impacts of fire on runoff and soil erosion in a context of global change, and to evaluate the effectiveness of mulching as a post-fire erosion mitigation measure. For this, the long-term soil erosion model LandSoil was calibrated for a Mediterranean catchment in north-central Portugal that burnt in 2011. LandSoil was then applied for a 20-year period to quantify the separate and combined hydrological and erosion impacts of fire frequency and of post-fire mulching using four plausible site-specific land use and management scenarios (S1. business-as-usual, S2. market-oriented, S3. environmental protection and S4. sustainable trade-off) and an intermediate climate change scenario Representative Concentration Pathway (RCP) 4.5 by 2050. The obtained results showed that: (i) fire had a reduced impact on runoff generation in the studied catchment (SY) by about 30%; (ii) eucalypt intensification combined with climate change and fires can increase SY by threefold and (iii) post-fire mulching, combined with riparian vegetation maintenance/restoration and reduced tillage at the landscape level, was highly effective to mitigate soil erosion under global change and associated, increased fire frequency (up to 50% reduction). This study shows how field monitoring data can be combined with numerical erosion modeling to segregate the prominent processes occurring in post forest fire conditions and find the best management pathways to meet international goals on achieving land degradation neutrality (LDN).