By switching to dark mode you can reduce the energy consumption of our digital service.

Methodology of Colombia NCAP Project

This article describes the methodological framework used in the Colombia NCAP project.


The methodological framework used in the project (see Figure 1) combines the adaptation framework proposed by Klein and Nicholls (1999), the UNDP-GEF Adaptation Policy Framework (2003), the DINAS-COAST project methodology, and the Framework for Planning and Decision-making Process proposed by Sharifi et al. (2004). The framework recognizes that local-scale strategies should be consistent with and inform national-scale policies. The framework also assumes that systems change over time, and that vulnerability and adaptation capacity to current experiences will not necessarily be the same in the future.

Figure 1. Methodology framework used in the project

Under this framework, an initial review and description of the system is first conducted. Then a vulnerability assessment is developed to analyze potential impacts upon the system. A scenario development process is also included in this stage. An adaptation decision matrix (IPCC, 2001) is then applied to identify and assess alternative policy options that respond to different adaptation measures to SLR. Finally, a policy exercise approach is conducted to downscale national policy options that reduce climate risks at the local level. Finally, the identified adaptation strategies are analyzed and the most suitable ones are selected.

System description: The first stage of the methodology examines the biophysical and socio-economic systems of the study areas to identify current problems and opportunities. Descriptions of current economic activities, especially those activities that increase vulnerability to climate risks are also included. In general, the system description is based on existing assessments and published and available studies, expert judgment and stakeholders’ feedback. Efforts were made to use the most recent and updated information sources.

For the biophysical component of this stage, the main sources of information are previous studies carried out in the study areas. These provided sufficient information to gain a general idea of the current state of the natural systems. Stakeholders also provided feedback on this information and assisted in identifying current pressures on the natural system. These pressures were identified with the stakeholders through a problem analysis carried out for each area based on the Driving Force, Pressure, State and Impact – DPSIR methodology. As a result of this analysis, the stakeholders recognized the need to reduce the study area for Cartagena. It appeared that the administrative limits were considered to be too complicated to manage because of the large differences and variety of issues and pressures threatening the area. The study area was therefore limited to the portion of territory between La Boquilla (the northern limit of the Carnaga de la Virgen) and the urban area of Cartagena, including the Cartagena Bay system.

The description of the socio-economic system of Cartagena is based on secondary information available on-line, as well as on statistical and analytical documents. Unfortunately, studies that analyze the current socio-economic situation of Tumaco were not found . The first stage of the methodology contributed towards the development of a current scenario for each study area that led directly into the vulnerability assessment.

<em>Vulnerability assessment scheme</em>

Vulnerability Assessment: The second stage of the methodology focuses on the vulnerability assessment of the natural and socio-economic systems of each area. For the natural systems, the term susceptibility was preferred as it refers to the degree to which a system is open, liable, or sensitive to climate change effects. This approach considers the system’s natural resilience and resistance to damage, the risk of hazards and the acquired resilience. The environmental susceptibility index model assumes that resilience is greater for a system that is less damaged. The susceptibility depends not only on the systems’ characteristics, but on other pressures imposed upon the system as well. Box 1 explains the vulnerability and resilience of a natural system within the SLR context. The socio-economic vulnerability, on the other hand, refers to the society’s economic, institutional, technical and cultural ability to prevent or face changes in the socio-economic system.

Box 1: Vulnerability and resilience

Within the SLR context, vulnerability of the natural system can be referred to as the effects of an event on a given ecosystem and the capacity of this ecosystem to survive over time. This survival capacity depends upon the ecosystem’s ability to recover quickly from shock, injury or depression (resilience). It is important to note that resilience can either be natural (intrinsic to a given system) or acquired (if it is gained from previous damage). Therefore a natural system’s vulnerability is decreased as its resilience increases.

The vulnerability and susceptibility of the coastal areas of Cartagena and Tumaco are assessed from two different approaches: 1) considering current circumstances without taking into account the possible effects of SLR; and 2), considering different scenarios that include socio-economic changes and different levels of SLR.

Firstly, the natural system’s susceptibility was calculated using the information obtained from the previous stage, as well as expert knowledge and local stakeholders’ perceptions. The overall susceptibility index is composed of six indicators used by the Colombian Environmental Information System (SIAC in Spanish) (IDEAM et al., 2002). To calculate the overall natural susceptibility index (BSI) for each area, the results of each independent indicator were computed, resulting in a general numerical value for each case. Each indicator is weighted in accordance with the perceived importance allocated to each one of them.

In general, the most important indicator is considered to be ecosystem quality, followed by ecosystem coverage. The other four indicators (water quality and hydrographic processes integrity, recovery areas, land use and hazards) receive the same weight as they are considered to be equally important in defining the natural systems’ susceptibility in the studied areas. It is very important to understand the entire process given that the general value does not provide as much information as each indicator does by itself. While understanding the entire process is critical in defining the measures to be taken, the susceptibility index shows the extent to which the natural system is prone to damage and degradation. The larger the general value obtained, the more susceptible the areas are from a natural system’s perspective.

Secondly, the causality analysis of the socio-economic and environmental problems in both study areas contributed towards the recognition of relevant variables to evaluate the socio-economic systems’ vulnerability. The indicators for the socio-economic vulnerability index were selected considering the results of the DPSIR analysis conducted in the first regional workshop , as well as available information for each area. The socio-economic vulnerability index (SVI) is composed of 5 categories (see Figure 2) and the following indicators: population indicator; public investment indicator; natural disaster risk indicator; human capital factor; and life quality indicator (includes sewage disposal, water supply, waste recollection, cooking fuel, house wall materials and house floor material). The socio-economic vulnerability index values are allocated in the range 0 to 100, an increase in the value indicates that the vulnerability diminishes.

The first susceptibility and vulnerability assessment only reflects the current state of the natural and socio-economic systems. To evaluate future possible situations, future scenarios are developed considering different changes to socio-economic and environmental characteristics and different levels of SLR. An important input to the scenario development process is the perception of the stakeholders in relation to the areas at risk of flooding due to an SLR. Scenarios extend to the year 2019. To summarize, while topographic characteristics are not modified for the development of scenarios, socio-economic variables and SLR levels are modified to gain a better understanding of the potential impacts of SLR on the selected study areas considering the susceptibility of the natural systems and the socio-economic system’s vulnerability.

Adaptation Decision Matrix: The third stage of the methodology considers the information gained about the system’s behavior in the previous stage and establishes a functional and structural relationship among major elements. The Adaptation Decision Matrix (ADM) is a tool used to relate given local circumstances to adaptation measures that are likely to be implemented in the short term, given the characteristics of the measures, the local needs and the institutional capacity. This process involves expert judgment and analysis carried out by the project team. It is implemented in an interactive manner, maintaining feedback with the stakeholders and following a step-by-step process to estimate the potential impacts for each policy adaptation strategy. The fields used in this matrix were developed based on different sources, but mainly on the Checklist and Database for Evaluating Adaptation Measures and Strategies, developed by the Stockholm Environment Institute (SEI).

<em>Scheme for the policy option analysis</em>

Policy Exercise Approach (Policy Option Analysis): The last stage of the methodology is based on different steps to analyze different adaptation strategies. While the DPSIR identifies root causes of environmental problems that can be directly related to the vulnerability of coastal areas to SLR , the policy options are suggested to address those roots causes. The strategies are grouped according to the subject they cover, for instance, technology, knowledge, economics, governance or demographics, among others. After establishing a clear definition for each group, the policy option analysis is carried out considering the following criteria for each alternative: effectiveness, efficiency, equity, political feasibility and implementation capacity (see Figure). The main strategies are selected by a scoring exercise and analyzed in more detail.

Next. . .

On to: Key findings from Colombia NCAP Project

Lessons learned from Colombia NCAP Project

Source text

This article is taken from the chapter “Building Capacity in Two Vulnerable Areas of the Colombian Coastal Area” in O’Brien, G., Devisscher, T., O’Keefe, P. (Eds.) (2010) The adaptation continuum: groundwork for the future. Netherlands Climate Assistance Programme (pp. 93-134)

Suggested citation:

Vides, M., Sierra, P., Ariasis, F., Devisscher, T. and Downing, T. E. (2010) Building Capacity in Two Vulnerable Areas of the Colombian Coastal Area. In: O’Brien, G., Devisscher, T., O’Keefe, P. (Eds.) The adaptation continuum: groundwork for the future (pp. 93-134). Saarbrücken, Germany: LAP LAMBERT Academic Pub.

On weADAPT, the Collaborative Platform on Climate Adaptation. (Date information retrieved), from Key findings from Colombia NCAP Project, 30th March 2011, from

Related Pages

Colombia NCAP project overview: Building Capacity in two vulnerable areas of the Colombian coastal area

Key findings from Colombia NCAP Project

Lessons learned from Colombia NCAP Project

Netherlands Climate Assistance Programme

Colombia NCP synthesis report

Add your project

Exchange your climate change adaptation projects and lessons learned with the global community.