This paper intends to assess the potential impacts of the future SLR on the operability of berthing structures and to estimate in monetary terms the adaptation costs to it. To do this, three ...scenarios of SLR are considered, two corresponding to the last assessment report of IPCC (RCP4.5 and RCP8.5) and the other being a high-end scenario (HES), with a low probability of occurrence but physically possible. The research is focused on the case study of Tangier-Med port, which is considered as an economic magnet for the northern region of Morocco and the centerpiece of the government strategy for port development. The results show that the operability of the port will be affected only under the HES and from 2090 onwards. However, by 2100, in this scenario all the docks would be affected, especially the service terminal and those dedicated to containers, hydrocarbons, vehicles and general cargo, in which the percentage of inoperability could exceed 30% of the time. This would lead to traffic losses of 1.9 million TEUS and more than 22 million tons of cargo by 2100 while the adaptation costs would exceed 40 million euros (in present monetary units).
•A methodology to assess the inoperability of port terminals due to SLR is presented.•The analysis is carried out for three sea level rise scenarios and applied to Tangier-Med.•Results show no impact for IPCC scenarios during the full 21st century.•In the worst case scenario, port operability would be significantly reduced by 2190.•Adaptation measures to overcome inoperability are proposed and their costs are assessed.
This paper explores the empirical assessment of social vulnerability in the
Algerian context using the Social Vulnerability Index (SoVI). The SoVI is
applied at the municipal level in the province of ...Chlef. The assessment aims
to map the geographical variability of social vulnerability for the 35
municipalities of the study area. While following the original SoVI
methodology, some adjustments were made to the variables to adapt them to
the context. Principal Component Analysis (PCA) was performed on a set of
40 selected variables resulting in six vulnerability factors. After
as-signing a sign (negative, positive, or absolute) to each factor, they
were summed to calculate the overall SoVI score. The resulting maps
highlight the most vulnerable municipalities in the province, and their
interpretation was aided by geographical maps depicting the natural and
human characteristics of the territory.
Riparian erosion is one of the major causes of sediment and contaminant load to streams, degradation of riparian wildlife habitats, and land loss hazards. Land and soil management practices are ...implemented as conservation and restoration measures to mitigate the environmental problems brought about by riparian erosion. This, however, requires the identification of vulnerable areas to soil erosion. Because of the complex interactions between the different mechanisms that govern soil erosion and the inherent uncertainties involved in quantifying these processes, assessing erosion vulnerability at the watershed scale is challenging. The main objective of this study was to develop a methodology to identify areas along the riparian zone that are susceptible to erosion. The methodology was developed by integrating the physically-based watershed model MIKE-SHE, to simulate water movement, and a habitat suitability model, MaxEnt, to quantify the probability of presences of elevation changes (i.e., erosion) across the watershed. The presences of elevation changes were estimated based on two LiDAR-based elevation datasets taken in 2009 and 2012. The changes in elevation were grouped into four categories: low (0.5 - 0.7 m), medium (0.7 – 1.0 m), high (1.0 - 1.7 m) and very high (1.7 – 5.9 m), considering each category as a studied “species”. The categories’ locations were then used as “species location” map in MaxEnt. The environmental features used as constraints to the presence of erosion were land cover, soil, stream power index, overland flow, lateral inflow, and discharge. The modeling framework was evaluated in the Fort Cobb Reservoir Experimental watershed in southcentral Oklahoma. Results showed that the most vulnerable areas for erosion were located at the upper riparian zones of the Cobb and Lake sub-watersheds. The main waterways of these sub-watersheds were also found to be prone to streambank erosion. Approximatively 80% of the riparian zone (streambank included) has up to 30% probability to experience erosion greater than 1.0 m. By being able to identify the most vulnerable areas for stream and riparian sediment mobilization, conservation and management practices can be focused on areas needing the most attention and resources.
•Integration of hydrologic and habitat suitability models.•Identification of areas prone to riparian erosion at watershed scale.•Evaluation of erosion vulnerability using probabilistic approach.•Use of principle of maximum entropy for erosion assessment.•Physically-based hydrologic model representation of water movement.
Key Points
Climate change causes shifts in flow regime
The shifts can be reconstructed
Canadian prairies is vulnerable to the regime shifts
Assessments of potential impacts of climate change on water ...resources systems are generally based on the use of downscaled climate scenarios to force hydrological and water resource systems models and hence quantify potential changes in system response. This approach, however, has several limitations. The uncertainties in current climate and hydrological models can be large, such analyses are rapidly outdated as new scenarios become available, and limited insight into system response is obtained. Here, we propose an alternative methodology in which system vulnerability is analyzed directly as a function of the potential variations in flow characteristics. We develop a stochastic reconstruction framework that generates a large ensemble of perturbed flow series at the local scale to represent a range of potential flow responses to climate change. From a theoretical perspective, the proposed reconstruction scheme can be considered as an extension of both the conventional resampling and the simple delta‐methods. By the use of a two‐parameter representation of regime change (i.e., the shift in the timing of the annual peak and the shift in the annual flow volume), system vulnerability can be visualized in a two‐dimensional map. The methodology is applied to the current water resource system in southern Alberta, Canada, to explore the system's vulnerability to potential changes in the streamflow regime. Our study shows that the system is vulnerable to the expected decrease in annual flow volume, particularly when it is combined with an earlier annual peak. Under such conditions, adaptation will be required to return the system to the feasible operational mode.
Groundwater over-exploitation is related to various environmental, economic, and social aspects, which should be addressed comprehensively to support a sustainable water supply globally. This is the ...first study to delineate the sustainable development goals (SDGs) associated with groundwater management practices to minimize over-exploitation episodes. Ten thematic maps of hydrologic, geologic, and topographic layers for the Wadi El-Natrun basin, Egypt, were investigated using geographic information system-based multi-criteria decision analysis. The layers were integrated to obtain an overall vulnerability map, which showed that ~ 45%, ~ 35%, ~ 15%, and ~ 5% of the total basin area have ‘high’, ‘medium’, ‘very high’, and ‘low’ vulnerability index (VI) values, respectively. Field measurements of piezometric water levels fit well to the estimated VI values, depicting high validation accuracy (
R
2
= 0.87). Based on sensitivity analysis, the vulnerability to groundwater over-exploitation was influenced highly by distance from feeding fault (DFF), followed by the aquifer’s hydraulic conductivity (HC) and land surface elevation. The western and southern zones of the basin were highly vulnerable to groundwater over-exploitation because of long DFF, low HC, and dominance of upland plains, steep slopes, and elevated surface with increased groundwater depth. The interactions among all thematic criteria and vulnerability indices showed strong correlations with SDGs and associated targets regarding ending poverty and hunger, providing safe and affordable water utilization, supporting economic growth, and protecting land and water ecosystems. Defining SDG linkages would assist in sustainable water resource utilization, planning, and management worldwide, particularly in water-stressed areas.
Graphic Abstract
Assessment of coastal vulnerability has achieved a recent pace due to the increasing frequency and intensity of tropical cyclones and anticipated sea-level rise. The coastal vulnerability is often ...assessed along the shoreline and it fails to capture the inland physical variabilities. During storm surge, rivers and creeks act as carriers that induce inundation to the low-lying inland areas causing damage to the invaluable coastal livelihood. The study addresses this gap by developing an approach to assess the vulnerability of a coastal inland as two-dimensional vulnerability maps that captures the physical and demographic variabilities of the inland region. We have estimated the coastal vulnerability for Jagatsinghpur District, Odisha, along the eastern Indian coast using coastal landforms, elevation, creek order, proximity to the creek, proximity to the open coast as the physical variables. The analysis resulted in the classification of 31 villages as highly vulnerable that are mostly located over swales and low-lying areas adjacent to creeks. More than half of the villages are located away from the shoreline, which are not considered in the conventional method of vulnerability assessment. Further, we assessed the social vulnerability of the 31 vulnerable villages and the composite map identified 18 villages as highly vulnerable, out of which 9 villages are located away from the shoreline. As the drainage network carry the surge water landwards, the vulnerability estimation have to consider the physical and social characteristics of the coastal inland region. The study finds its applicability in identifying the vulnerable areas along the coast for disaster reduction under a climate change scenario.
Global projections of climate change are generally linked to an increase in extreme weather events like extreme precipitation. Thus, improving risk management strategies depends on knowing what the ...most vulnerable to natural disasters areas and populations are. In this study, the Social Vulnerability Index (SoVI), created by Cutter et al. (Soc Sci Q 84(2):242–261,
2003
) is used to identify those areas and populations in the city of Sao Paulo, Brazil. This flood-prone area has high levels of social inequality and has not been evaluated from the perspective of vulnerability to natural disasters, but from the economic one. The study is focused on examining the basin-level social vulnerability in the city of Sao Paulo in the year 2010. Based on the principal component analysis, a SoVI was computed for the city. Results were displayed on maps and then analyzed to monitor trends in spacial distribution. Five main components were found in the analysis: ‘Urbanization level and vulnerable populations’ that explains 21 % of all social vulnerability, ‘Favorable environmental and social conditions’ explaining 18 %, ‘Alternative basic sanitation solutions’ (14 %), ‘Unfavorable social conditions’ (10 %) and ‘Development indicators’ that explain 8 %. Vulnerability increases in the center–periphery direction. Sixty-nine point seven percent of the basins were classified within the medium vulnerability score, 23.2 % within medium–high or medium–low vulnerability and 7 % within very low, low, high or very high vulnerability. These results show that the components contributing to social vulnerability are different for each basin and represent how social fragmentation of the city hinders efforts of risk management strategies.
The use of pesticides and their potentially negative effects on the environment are currently widely debated. However, it is difficult to imagine sufficient food production completely without their ...use; therefore, more attention has to be given to managing their use by considering site-specific spatial environmental data. In this study, the use of the FOOT-CRS (Footprint-Catchment Scale) tool, which was developed in the European project: “Functional tools for pesticide risk assessment and management”, is presented on a model location in the Apače Valley, Slovenia. The results clearly showed that the potential negative impacts of selected pesticides can be foreseen in advance; therefore, the pesticide usage can be adjusted accordingly to environmental and spatial characteristics of a given catchment. Pesticide leaching risk assessment on the catchment scale strongly depends on input spatial data quality. A soil map in the scale of 1:25,000 does not sufficiently cover the variability of soil properties; therefore, pedological data should be supplemented on a larger scale, with the final aim of knowing basic soil properties on the field level.
Urban Heat Island (UHI) is a phenomenon that can cause hotspots in city areas due to dense, impervious infrastructure and minimal vegetation cover. UHI hotspots may become worse in extreme heat ...events that are already affecting many regions across the globe due to increased frequent hot extremes, human-induced warming in cities, and rapidly growing urbanization, as documented by the latest IPCC report 2021. In seeking to support designers, planners, and decision-makers in developing and implementing adaptation strategies and measures to make our cities sustainable and resilient, reliable projections and modelling are required. In this study, we modelled UHI vulnerability using high-resolution spatial data, advanced geospatial tools, and socio-demographic data. This modified vulnerability approach drew upon UHI index maps and 20 select customized indicators of heat exposure, population sensitivity, and mobility/adaptive capacity. The indicators were Delphi evaluated and weighted, and the methodology was applied against the City of Greater Geelong municipality in Australia. The resulting UHI index maps indicated significant hotspots in areas of high building density, commercial/industrial zones, newly constructed sites, and zones with low urban green infrastructure. These UHI maps, in combination with selected indicators, highlighted the areal concentration of heat risk areas and vulnerable locations for the sensitive human population. The highlighted areas were primarily concentrated in high building density and high population density areas, which was seen through correlation curves. However, the building density showed a weak correlation, and population per meshblock indicated a strong correlation with UHI measurements. This study provides a comprehensive analysis of risk mapping and vulnerability assessment using GIS geospatial data for the advancement of a major local government area and concludes that this methodology has replicability incomparable geographical regions.
This article proposes a methodology to accurately monitor seawater intrusion (SWI) using time-varied GALDIT vulnerability maps. The properly produced samples are then used as input–output patterns ...for the approximate SWI simulation. As a novelty, the specific area of high susceptibility to SWI is proposed as the dynamic saltwater wedge position to suitably select the monitoring locations (MLs) from a narrowed area. It is observed that varied initial conditions over time periods have more influence than variable pumping rates on salinity at MLs far from the production wells. Support Vector Regression (SVR), Artificial Neural Network (ANN) and Gaussian Process Regression (GPR) models have been substituted for the numerical model of SWI. Input training patterns of the surrogate models are initial salinity concentrations at selected MLs plus transient pumping values via Latin hypercube sampling. The final salinity at MLs constitutes the output patterns. The paper applies this new methodology to a small study area subject to the SWI problem. The generalization ability of surrogate models for predicting new initial conditions-pumping datasets was evaluated using performance criteria considering the ML locations. All surrogates offered good results for predicting SWI at specified MLs. The SVR model had poor performance compared to ANN and GPR models in MLs near the pumping wells, due to their salinity fluctuations over time.
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