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|???metadata.dc.title???: ||Hydrological assessment and modelling of the River Fani Catchment, Albania|
|???metadata.dc.contributor.*???: ||Nicandrou, Aphrodite|
|???metadata.dc.subject???: ||River engineering|
|???metadata.dc.identifier.citation???: ||Nicandrou, A. (2010) Hydrological assessment and modelling of the River Fani Catchment, Albania. Unpublished Ph D thesis. University of Glamorgan.|
|???metadata.dc.description.abstract???: ||Aid In Action Porthcawl (a registered South Wales Charity Organisation) has been carrying out charity work in the town of Rubik in the Mirdita Region of North Albania for many years. Rubik lies within the Catchment of the River Fani which is remote, ungauged and characterised by frequent flooding, erosion and deforestation. Over the years these processes have had a huge environmental and socioeconomic impact on the residents of Rubik. Aid In Action was concerned about this situation and wished to provide a sustainable solution. Following discussions with staff at the University of Glamorgan, it was agreed that a sustainable solution was the development of an integrated hydrological decision support system for the whole River Fani Catchment.
Hydrological models can be a valuable tool, providing a common platform for experts, decision-makers and stakeholders for the sustainable management of catchments, especially when used within the framework of a Geographic Information System (GIS). Such models and systems require quantitative data of good quality over appropriate spatial and temporal scales. For remote mountainous ungauged river catchments in developing countries the development of a catchment model and management system is often complicated due to limited availability of such data. Very often, any available data are difficult to obtain; they could, for example, be scattered among local authorities and are generally in the national language of the country concerned, thus adding the challenge of having records translated into the study language.
Over the last few decades, advances in hydrological data capture (e.g. using remote sensing) and data management systems (e.g. GIS) have provided opportunities for overcoming some of the challenges of modelling ungauged catchments. However, the data captured is often from different sensors and sources and at different scales. This research project sought out to creatively use multi-source and multi-scale data to develop a GIS based hydrological model of the River Fani Catchment in the North of Albania to provide, a long term solution for the sustainable management of the Fani Catchment, thus improving the quality of life for the residents of Rubik and the rest of the Catchment. Data from various remote sensing sensors (e.g. Landsat, MODIS, ASTER) and other sources such as published maps, limited gauged flow and rainfall records, local library archives, digital datasets (e.g. CORINE and radar rainfall) and interviews with residents were used to develop the integrated GIS-based hydrological (using WMS hydrological modelling environment) and hydraulic (HEC-RAS) model of the Fani Catchment. The model was then used to not only map significant environmental change in the Catchment (e.g. deforestation using various vegetation indices), but also to assess flooding impact and to analyse various “What-if” scenarios of conservation strategies (e.g. deforestation, afforestation and provision of runoff attenuation systems).
The results suggest that the changes in vegetation cover (apart from farming practices) are not considerably extensive in the Catchment between 1984 and 2000. It was observed that afforestation as a flooding mitigation measure did not play a decisive role in runoff reduction compared with attenuation measures. This study has demonstrated the effectiveness of remote sensing and GIS in generating quantitative information on land classification, change detection, soil erosion and general catchment management for remote and ungauged catchments in developing countries. This has been particularly so, owing to recent developments in sensor technologies and increasing available datasets from data providers and the global scientific community at little or no cost.|