Evaluation and selection of indicators for land degradation and desertification monitoring: types of degradation, causes, and implications for management.

Indicator-based approaches are often used to monitor land degradation and desertification from the global to the very local scale. However, there is still little agreement on which indicators may best reflect both status and trends of these phenomena. In this study, various processes of land degradation and desertification have been analyzed in 17 study sites around the world using a wide set of biophysical and socioeconomic indicators. The database described earlier in this issue by Kosmas and others (Environ Manage, 2013) for defining desertification risk was further analyzed to define the most important indicators related to the following degradation processes: water erosion in various land uses, tillage erosion, soil salinization, water stress, forest fires, and overgrazing. A correlation analysis was applied to the selected indicators in order to identify the most important variables contributing to each land degradation process. The analysis indicates that the most important indicators are: (i) rain seasonality affecting water erosion, water stress, and forest fires, (ii) slope gradient affecting water erosion, tillage erosion and water stress, and (iii) water scarcity soil salinization, water stress, and forest fires. Implementation of existing regulations or policies concerned with resources development and environmental sustainability was identified as the most important indicator of land protection.

Evaluation and selection of indicators for land degradation and desertification monitoring: methodological approach.

An approach to derive relationships for defining land degradation and desertification risk and developing appropriate tools for assessing the effectiveness of the various land management practices using indicators is presented in the present paper. In order to investigate which indicators are most effective in assessing the level of desertification risk, a total of 70 candidate indicators was selected providing information for the biophysical environment, socio-economic conditions, and land management characteristics. The indicators were defined in 1,672 field sites located in 17 study areas in the Mediterranean region, Eastern Europe, Latin America, Africa, and Asia. Based on an existing geo-referenced database, classes were designated for each indicator and a sensitivity score to desertification was assigned to each class based on existing research. The obtained data were analyzed for the various processes of land degradation at farm level. The derived methodology was assessed using independent indicators, such as the measured soil erosion rate, and the organic matter content of the soil. Based on regression analyses, the collected indicator set can be reduced to a number of effective indicators ranging from 8 to 17 in the various processes of land degradation. Among the most important indicators identified as affecting land degradation and desertification risk were rain seasonality, slope gradient, plant cover, rate of land abandonment, land-use intensity, and the level of policy implementation.

Multi-criteria Decision Support System (DSS) for optimal locations of Soil Aquifer Treatment (SAT) facilities.

Managed Aquifer Recharge is a wide-spread well-established groundwater engineering method which is largely seen as sound and sustainable solution to water scarcity hydrologically sensitive areas, such as the Circum Mediterranean. The process of site selection for the installation of a MAR facility is of paramount importance for the feasibility and effectiveness of the project itself, especially when the facility will include the use of waters of impaired quality as a recharge source, as in the case of Soil-Aquifer-Treatment systems. The main objective of this study is to present the developed framework of a multi-criteria Decision Support System (DSS) that integrates within a dynamic platform the main groundwater engineering parameters associated with MAR applications together with the general geographical features which determine the effectiveness of such a project. The proposed system will provide an advanced coupled DSS-GIS tool capable of handling local MAR-related issues -such as hydrogeology, topography, soil, climate etc., and spatially distributed variables -such as societal, economic, administrative, legislative etc., with special reference to Soil-Aquifer-Treatment technologies.

Seawater intrusion mapping using electrical resistivity tomography and hydrochemical data. An application in the coastal area of eastern Thermaikos Gulf, Greece.

The aim of this study was to determine the extent and geometrical characteristics of seawater intrusion in the coastal aquifer of the eastern Thermaikos Gulf, Greece. Hydrochemical data and geoelectrical measurements were combined and supplemented to determine the hydrochemical regime of the study site in regard to seawater phenomena. Chemical analysis of groundwater was performed in 126 boreholes and fifteen electrical resistivity tomographies (ERT) were measured, whereas in two sites the ERT measurements were repeated following the wet season. The Cl(-) concentrations recorded reached 2240 mg/L indicating seawater intrusion which was also verified by ionic ratios. The ionic ratios were overlapped and a seawater intrusion map (SWIM) was produced. A significant part of the coastal aquifer (up to 150 km(2)) is influenced by seawater intrusion. The areas with the most intensive salinization are located between Nea Kallikratia-Epanomi and Aggelochori-Peraia. According to the ERTs, in the influenced areas the salinization of the aquifer exceeds 1 km toward the mainland and its depth reaches 200 m. In the area surrounding Thessaloniki airport, the ERTs revealed salinization of the upper aquifer to depths of up to 40 m, whereas the lower aquifer is uninfluenced. This abnormal distribution of seawater intrusion demonstrates the value of geoelectrical methods in the study of seawater intrusion especially in areas with limited available hydrochemical data.