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Spatial variability of soil properties and soil erodibility in the Alqueva reservoir watershed

Publication . Ferreira, V.; Panagopoulos, Thomas; Andrade, R.; Guerrero, Carlos; Loures, L.

The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area. To this end, three areas representative of different land uses (agroforestry grassland, lucerne crop and olive orchard) were studied within a 900 ha farm. The interrelationships between variables were analyzed by multivariate techniques and extrapolated using geostatistics. The results confirmed differences between land uses for all properties analyzed, which was explained mainly by the existence of diverse management practices (tillage, fertilization and irrigation), vegetation cover and local soil characteristics. Soil organic matter, clay and nitrogen content decreased significantly, while the K factor increased with intensive cultivation. The HJ-Biplot methodology was used to represent the variation of soil erodibility properties grouped in land uses. Native grassland was the least correlated with the other land uses. The K factor demonstrated high correlation mainly with very fine sand and silt. The maps produced with geostatistics were crucial to understand the current spatial variability in the Alqueva region. Facing the intensification of land-use conversion, a sustainable management is needed to introduce protective measures to control soil erosion.

2015Journal article

Open Access

Assessing soil erosion due to land use change at the Alqueva reservoir surrounding area

Publication . Ferreira, Vera Lúcia Matias; Panagopoulos, Thomas

Soil erosion is one of the most dynamic environmental and economic threats in Mediterranean regions. As a consequence of water availability in the surrounding area of the Alqueva reservoir, new challenges were created. The conversion from native Montado grassland to intensive and irrigated agriculture, the development of golf resorts and the ongoing climate change were insufficiently considered for the erosion problem during the environmental impact study of the Alqueva project, and consequently there is an urgent need to delineate a sustainable land management for the region. The main objective of this investigation was to assess current and future soil erosions in the surrounding area of the Alqueva reservoir using the Revised Universal Soil Loss Equation (RUSLE) in combination with Geographic Information Systems (GIS). Different soil erosion factors, the main causes and consequences, and also spatial variability and seasonality were investigated, and a simulation model was developed to support decision based on the acquired scientific knowledge. On the first part of the study, the RUSLE equation was applied at field scale, and different land uses were selected for erosion assessment (Montado grassland, lucerne cultivation, olive orchard and vineyard). The spatial variability analysis (with geostatistics and HJ-Biplot) indicates that the intensification of land use, with tillage practices and vegetation removal, is likely to increase the susceptibility to soil erosion (soil erodibility). The effect of seasonality on soil erosion was confirmed, with the autumn season contributing the most to annual soil erosion (around 65%). Future soil erosion scenarios were investigated for the entire study area, according to the expected land use changes (which affect vegetation cover) and climate changes (which affect rainfall-runoff erosivity). The forecasting scenarios of land use changes indicated that the intensive agriculture area is likely to increase, as well as sparse and xerophytic vegetation and rainfall-runoff erosivity. As a consequence, soil erosion in the study area is forecasted to increase from 1.78 t/ha to 3.65 t/ha by 2100. A backcasting scenario was investigated by considering the application of soil conservation practices, that will decrease soil erosion considerably to an average of 2.27 t/ha. For each scenario studied, the sediment delivery was assessed, and for the worst case scenario in 2100, an annual sedimentation value of 182 000 tonnes is predicted for the study area. Finally it was developed a dynamic simulation model for soil erosion performed on Stella, and a graphic user interface as a decision support tool allowing the user (e.g. decision maker) to create, modify, save, and select site specific data. The system simulates the risk for soil erosion for particular local characteristics and land use, and then suggesting soil conservation practices to decrease susceptibility to erosion. In conclusion, due to its characteristics, the study area is very vulnerable to land degradation processes, which is expected to worsen in the future. The distribution maps provide for a better understand of soil erosion and its processes under local conditions, and for the identification of critical periods, high-risk areas, and their respective causes. This information is crucial to delineate local strategies for sustainable land management, and future scenarios reveal the importance of considering the effects of land use and climate change. The decision support system is a useful tool for the exchange of scientific knowledge; however, close collaboration between scientists and local stakeholders is essential to preserve the natural resources and avoid unnecessary costs. In future research, collaboration with international projects will be important to exchange information and knowledge as a key element in the global effort to fight land degradation and to promote sustainable land management.

2015-11-20Doctoral thesis

Open Access

Soil erosion vulnerability under scenarios of climate land-use changes after the development of a large reservoir in a semi-arid area

Publication . Ferreira, Vera; Samora-Arvela, André; Panagopoulos, Thomas

Climate and land-use/cover changes (LUCC) influence soil erosion vulnerability in the semi-arid region of Alqueva, threatening the reservoir storage capacity and sustainability of the landscape. Considering the effect of these changes in the future, the purpose of this study was to investigate soil erosion scenarios using the Revised Universal Soil Loss Equation (RUSLE) model. A multi-agent system combining Markov cellular automata with multi-criteria evaluation was used to investigate LUCC scenarios according to delineated regional strategies. Forecasting scenarios indicated that the intensive agricultural area as well as the sparse and xerophytic vegetation and rainfall-runoff erosivity would increase, consequently causing the soil erosion to rise from 1.78 Mg ha(-1) to 3.65 Mg ha(-1) by 2100. A backcasting scenario was investigated by considering the application of soil conservation practices that would decrease the soil erosion considerably to an average of 2.27 Mg ha(-1). A decision support system can assist stakeholders in defining restrictive practices and developing conservation plans, contributing to control the reservoir's siltation.

2016Journal article

Open Access