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The risks to human populations in coastal areas are changing due to climate and socio-economic changes, and these trends are predicted to accelerate during the 21 st Century. To understand these changing risks, and the resulting choices and pathways to successful management and adaptation, broad-scale integrated assessment is essential. Due to their complexity these two risks are usually managed independently, yet frequently they are interconnected by longshore exchange of sediments and the resulting broad scale morphological system behaviour. Simply put, if beach levels rise or fall, flood risk in adjacent low-lying coastal areas decreases or increases respectively. In order to generate new insights into the effects of climate change and coastal management practises on coastal erosion and flood risk, we present an integrated assessment of 72 km of shoreline over the 21 st Century on the East Anglian Coast of England. A coupled system of hydrodynamic, morphological, reliability and socio-economic models has been developed for the analysis, which has been implemented under scenarios of climate and socio-economic change. The study is unique in coastal management terms because of the large spatial scale and extended temporal scales over which the analysis is quantified, but is also a site of significant controversy about how to manage coastal flood and erosion risks over the 21 st Century. This study for the first time quantifies what has for some years been argued qualitatively: the role of sediments released from cliff erosion in protecting neighbouring low-lying land from flooding. The losses and benefits are expressed using the common currency of economic risk. The analysis demonstrates that over the 21 st Century, flood risk in the study area is expected to be an order of magnitude greater than erosion risk. Both climate and socio-economic change can have a significant influence on flood risk. This study demonstrates that the choices concerning coastal management are profound, and there are clear tradeoffs between erosion and flood impacts.

In Europe, the most susceptible areas to land degradation and desertification (LDD) are found in the Mediterranean region. The present study focuses on the island of Lesvos (Greece) and maps the environmental sensitivity of the island to LDD between the years 1990 and 2000. Sensitivity is estimated with a modification of the MEDALUS Environmentally Sensitive Area Index (ESAI) approach, employing 21 quantitative parameters divided in five main quality indices: climate, vegetation, soils, groundwater and socio-economic quality. Parameterisation of these indices is achieved via remote sensing and ancillary data in a Geographical Information System (GIS). Results show that~85% of the island is fragile or critically sensitive in both epochs. Fragile areas are on the increase, covering an estimated 72% of the island in 1990 and 77% in 2000, whereas critically sensitive areas decrease from 214 to 113 km 2 . By modifying the ESAI to include 10 additional parameters related to soil erosion, groundwater quality, demographic and grazing pressure, and by applying the modified ESAI in two-rather than one-periods, this study was able to identify that, contrary to previous belief, critically sensitive areas are also found in the eastern side of the island mainly due to human-related factors. It is concluded that the proposed methodology is a useful tool for regional scale trend analyses of environmental sensitivity and the identification of LDD hot spots in Mediterranean environments.

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This paper explores potential future land use/cover (LUC) dynamics in the Attica region, Greece, under three distinct economic performance scenarios. During the last decades, Attica underwent a significant and predominantly unregulated process of urban growth, due to a substantial increase in housing demand coupled with limited land use planning controls. However, the recent financial crisis affected urban growth trends considerably. This paper uses the observed LUC trends between 1991 and 2016 to sketch three divergent future scenarios of economic development. The observed LUC trends are then analysed using 27 dynamic, biophysical, socio-economic, terrain and proximity-based factors, to generate transition potential maps, implementing a Random Forests (RF) regression modelling approach. Scenarios are projected to 2040 by implementing a spatially explicit Cellular Automata (CA) model. The resulting maps are subjected to a multiple resolution sensitivity analysis to assess the effect of spatial resolution of the input data to the model outputs. Findings show that, under the current setting of an underdeveloped land use planning apparatus, a long-term scenario of high economic growth will increase built-up surfaces in the region by almost 24%, accompanied by a notable decrease in natural areas and cropland. Interestingly, in the case that the currently negative economic growth rates persist, artificial surfaces in the region are still expected to increase by approximately 7.5% by 2040.

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