INTRODUCTION
Soil erosion (SE) is one of the major environmental issues in arid and
semi-arid regions, especially in agricultural lands, identified as the
areas with the highest average rate of soil losses around the world
(Panagos et al., 2015a). SE represents the main cause of land
degradation and desertification, with consequent loss of ecosystems
services (Adhikari and Hartemink, 2016; Grilli et al., 2021; Zhao et
al., 2013). The rate of SE is generally controlled by numerous factors
and processes like wind, water inputs and balance, plant cover,
geomorphology, soil type and anthropogenic activities (Arabameri et al.,
2018; Bhattacharya et al., 2020). On a global scale, rainfall frequency
and duration are the most important drivers of the observed and modeled
SE rates (Borrelli et al., 2020; Burt et al., 2016). Especially in the
last century, SE rates have strongly increased, leading to a world
average soil loss rate of about 10.2 t/ha/year, which is expected to
increase of 14% by the end of the twenty-first century (Yang et al.,
2003), with climate change (CC) having a significant role in determining
the severity of SE increase (IPCC, 2014). The Mediterranean region has
been identified as one of the most vulnerable zones for SE, representing
a CC ‘hot-spot’, due to the magnitude of the expected increase in
temperature and anomalies in rainfall patterns (Giorgi, 2006; Giorgi and
Lioniello, 2008; Zittis et al., 2019), such as higher frequency of
extreme events, increased intensity of storms, extended drought periods,
and higher risk of fire events (Moriondo et al., 2006; Busico et al.,
2019). Additionally, the Mediterranean region is also characterized by
centuries of anthropic disturbance, mainly related to agricultural and
silvopastoral activities which might contribute to a substantial
increase of SE rates (Raclot et al., 2016).
A robust quantitative SE assessment is a fundamental requirement for
land management planning and policies aimed at stopping and reversing
land degradation. Among the available tools, the empirical Universal
Soil Loss Equation (USLE) (Wischmeier and Smith, 1978) and its revised
version (RUSLE) (Renard et al., 1997) have been widely applied to
determine the mean annual SE rates at regional and local scales (Mancino
et al., 2016; Benavidez et al., 2018; Maltsev and Yermolaev, 2020).
Panagos et al. (2015b) estimated the whole set of USLE parameters for
Europe, significantly improving the potential applicability of this
model. Despite their wide applicability, both methodologies still limit
our ability to simulate soil deposition and to determine the location of
sediment sources (Alewell et al., 2019). To overcome these drawbacks, a
variety of river basin scale models were developed to simulate SE
mechanisms and dynamics, such as the Water Erosion Prediction Model
(WEPP) (Laflen et al., 1997), the Limburg Soil Erosion Model (LISEM) (De
Roo et al., 1996), the European Soil Erosion Model (EUROSEM) (Morgan et
al., 1998), and the Soil and Water Assessment Tool (SWAT) (Arnold et
al., 1998; 2012) proposed by the United States Department of Agriculture
(USDA). Among these, SWAT is one of the most appropriate models for
assessing hydrological responses (water, sediment, and nutrient loss) to
land use and CC in watersheds with different land covers, soil types,
and management conditions (Bhatta et al., 2019; Busico et al., 2021,
2020; Golmohammadi et al., 2017; Tasdighi et al., 2018). In the last
years, SWAT applicability was greatly increased thanks to the
possibility of using a growing number of available global and regional
datasets, making SWAT utilization much easier than before (Abbaspour et
al., 2019). The proposed study is part of the European LIFE project
“Desert-Adapt”
(http://www.desert-adapt.it/index.php/it/)
aimed at identifying appropriate land management strategies to reduced
land degradation and desertification risk in semi-arid Mediterranean
regions of Portugal, Spain, and Italy.
The goal of the present study is to evaluate if and how CC will affect
SE rate within the Guadiana sub-basin, an arid area of Portugal
(Alentejo) where four sites of the LIFE project are located (Fig. 1),
assuming no change in land use (business as usual scenario, BAU) and
considering two CC projection scenarios corresponding to different
greenhouse gasses (GHGs) Representative Concentration Pathways (RCP 4.5
and RCP 8.5; IPCC, 2014). To meet this goal the operative steps of the
study were: i) to create maps of SE susceptibility of the whole basin,
ii) to assess its evolution over time (1980-2000, 2020-2040), and iii)
to identify the areas more at risk and their current land uses to
support adequate land management planning. Understanding the impact that
CC will have on SE rates in the study area, and the identification of
the most critical combinations of land management and environmental
conditions which require special attention by farmers, is of paramount
importance to define the most appropriate land management strategies to
reduce current SE rates.