CONTRIBUTION OF EMPIRICAL METHODS AND SATELLITE DATA USE FOR ESTIMATING DAILY REFERENCE EVAPOTRANSPIRATION

Στην παρούσα εργασία χρησιμοποιούνται επίγεια και δορυφορικά μετεωρολογικά δεδομένα του έτους 2014 από την περιοχή της Βοιωτίας. Τα επίγεια δεδομένα προέρχονται από τον αυτόματο αγρομετεωρολογικό σταθμό (ΑΑΣ) μέτρησης της εξατμισοδιαπνοής αναφοράς (ΕΤο) του Γεωπονικού Πανεπιστημίου Αθηνών (ΓΠΑ). Τα μετεωρολογικά δορυφορικά δεδομένα (SAT) αντιστοιχούν σε πολύγωνο 0.25οΧ0.25ο εντός του οποίου λειτουργεί και ο ΑΑΣ. Χρησιμοποιώντας τα επίγεια αλλά και τα δορυφορικά δεδομένα, υπολογίσθηκε η ΕΤο με τη μέθοδο FAO-56 PM, αλλά και με τρεις εμπειρικές μεθόδους (Copais, Valiantzas και Hargreaves-Samani) και πραγματοποιήθηκαν συγκρίσεις με σκοπό να αξιολογηθεί η αξιοπιστία των μοντέλων. Ως βάση των συγκρίσεων υιοθετήθηκε η μέθοδος FAO-56 PM με χρήση επίγειων δεδομένων. Από την εργασία προκύπτει ότι τόσο για τα επίγεια όσο και για τα δορυφορικά δεδομένα η μέθοδος Copais δίνει τις καλύτερες εκτιμήσεις ακολουθούμενη από την μέθοδο Valiantzas και με σοβαρή υπερεκτίμηση η Hargreaves-Samani. In the present study we used ground and satellite meteorological data of the year 2014 from the region of Viotia-Greece. The ground data were obtained from the automatic grass reference evapotranspiration station (AAS) of the Agricultural University of Athens. The satellite data (SAT) cover an area of 0,25ο x 0,25ο that includes the AAS. By using the ground and the satellite data we calculated the reference evapotranspiration, ΕΤο, with the method FAO-56 PM and with three empirical methods (Copais, Valiantzas and Hargreaves-Samani). The FAO-56 PM was used as a benchmark method to compare and validate the performances of the others methods. The results show that for both the ground and the satellite data, Copais method is the most accurate followed by Valiantzas and Hargreaves-Samani, indicated by serious overestimation

Unveiling soil degradation and desertification risk in the Mediterranean basin: a data mining analysis of the relationships between biophysical and socioeconomic factors in agro-forest landscapes

Soil degradation and desertification processes in the Mediterranean basin reflect the interplay between environmental and socioeconomic drivers. An approach to evaluate comparatively the multiple relationships between biophysical variables and socioeconomic factors is illustrated in the present study using the data collected from 586 field sites located in five Mediterranean areas (Spain, Greece, Turkey, Tunisia and Morocco). A total of 47 variables were chosen to illustrate land-use, farm characteristics, population pressure, tourism development, rainfall regime, water availability, soil properties and vegetation cover, among others. A data mining approach incorporating non-parametric inference, principal component analysis and hierarchical clustering was developed to identify candidate syndromes of soil degradation and desertification risk. While field sites in the same study area showed a substantial similarity, the multivariate relationship among variables diverged among study areas. Data mining techniques proved to be a practical tool to identify spatial determinants of soil degradation and desertification risk. Our findings identify the contrasting spatial patterns for biophysical and socioeconomic variables, in turn associated with different responses to land degradation

A desertification risk assessment decision support tool (DRAST)

Desertification constantly and diachronically manifested itself as one of the most critical environmental issues to be confronted and mitigated by society. This work presents the development of a land desertification risk Expert System (ES) for assessing the application of different land management practices by utilizing indicators through a desertification risk index (DRI). The DRI was developed by a desertification risk assessment framework generated in seventeen study sites worldwide. This assessment was performed through a methodological process incorporating indicators suited to a plethora of physical, social and economic characteristics. Then, the Desertification Risk Assessment Support Tool (DRAST) was created using the indicators’ methodology in an effort to efficiently handle complexity and variability in soil and water resources management. To demonstrate DRAST’s applicability, an independent data base of indicators was used, and the tool was employed in all the seventeen study sites. Five indicative sites, experiencing different desertification processes, are selected as key representatives of the methodological process implementation. Overall, the assessment depicted that DRAST performs appropriately in demarcating existing desertification risk as well as in portraying how the desertification risk changes after the application of pertinent mitigation actions. Thus, the current approach may lead towards a standardized procedure, which is using the advantages of information technology to assess the effectiveness of various land management practices and facilitate stakeholders and decision-makers to produce and implement timely and appropriate responses to combat desertification

A desertification risk assessment decision support tool (DRAST)

Desertification constantly and diachronically manifested itself as one of the most critical environmental issues to be confronted and mitigated by society. This work presents the development of a land desertification risk Expert System (ES) for assessing the application of different land management practices by utilizing indicators through a desertification risk index (DRI). The DRI was developed by a desertification risk assessment framework generated in seventeen study sites worldwide. This assessment was performed through a methodological process incorporating indicators suited to a plethora of physical, social and economic characteristics. Then, the Desertification Risk Assessment Support Tool (DRAST) was created using the indicators’ methodology in an effort to efficiently handle complexity and variability in soil and water resources management. To demonstrate DRAST's applicability, an independent data base of indicators was used, and the tool was employed in all the seventeen study sites. Five indicative sites, experiencing different desertification processes, are selected as key representatives of the methodological process implementation. Overall, the assessment depicted that DRAST performs appropriately in demarcating existing desertification risk as well as in portraying how the desertification risk changes after the application of pertinent mitigation actions. Thus, the current approach may lead towards a standardized procedure, which is using the advantages of information technology to assess the effectiveness of various land management practices and facilitate stakeholders and decision-makers to produce and implement timely and appropriate responses to combat desertification.</p

Assessing the effectiveness of sustainable land management policies for combating desertification: A data mining approach.

This study investigates the relationship between fine resolution, local-scale biophysical and socioeconomic contexts within which land degradation occurs, and the human responses to it. The research draws on experimental data collected under different territorial and socioeconomic conditions at 586 field sites in five Mediterranean countries (Spain, Greece, Turkey, Tunisia and Morocco). We assess the level of desertification risk under various land management practices (terracing, grazing control, prevention of wildland fires, soil erosion control measures, soil water conservation measures, sustainable farming practices, land protection measures and financial subsidies) taken as possible responses to land degradation. A data mining approach, incorporating principal component analysis, non-parametric correlations, multiple regression and canonical analysis, was developed to identify the spatial relationship between land management conditions, the socioeconomic and environmental context (described using 40 biophysical and socioeconomic indicators) and desertification risk. Our analysis identified a number of distinct relationships between the level of desertification experienced and the underlying socioeconomic context, suggesting that the effectiveness of responses to land degradation is strictly dependent on the local biophysical and socioeconomic context. Assessing the latent relationship between land management practices and the biophysical/socioeconomic attributes characterizing areas exposed to different levels of desertification risk proved to be an indirect measure of the effectiveness of field actions contrasting land degradation

An exploratory analysis of land abandonment drivers in areas prone to desertification

The abandonment of land is a global problem with environmental and socioeconomic implications. An approach to assess the relationship between land abandonment and a large set of indicators was illustrated in the present study by using data collected in the framework of the European Union DESIRE research project from 808 field sites located in 10 study sites in the Mediterranean region, Eastern Europe, Latin America, Africa and Asia. A total of 48 indicators provided information for biophysical conditions and socioeconomic characteristics measured at the plot level. The selected indicators refer to farm characteristics (family status, land tenure, present and previous types of land-use, soil depth, slope gradient, tillage operations) and to site-specific characteristics including annual rainfall, rainfall seasonality and water availability. Classes were designated for each indicator and a sensitivity score was assigned to each class based on existing research or empirically assessing the importance of each indicator to the land abandonment issue. Questionnaires for each process of land degradation were prepared and data were collected at field site level in collaboration with land users. Based on correlation statistics and multivariate analyses more than ten indicators out of 48 resulted as significant in affecting land abandonment in the studied field sites. Among them, the most important were rainfall seasonality, elderly index, land fragmentation, farm size, selected soil properties, and the level of policy implementation. Results contribute to the development of appropriate tools for assessing the effectiveness of land management practices for contrasting land abandonment