In Ethiopia, climate change and associated risks are expected to have serious consequences for agriculture and food security. This in turn will seriously impact on the welfare of the people, ...particularly the rural farmers whose main livelihood depends on rain-fed agriculture. The level of impacts will mainly depend on the awareness and the level of adaptation in response to the changing climate. It is thus important to understand the role of the different factors that influence farmers’ adaptation to ensure the development of appropriate policy measures and the design of successful development projects. This study examines farmers’ perception of change in climatic attributes and the factors that influence farmers’ choice of adaptation measures to climate change and variability. The estimated results from the climate change adaptation models indicate that level of education, age and wealth of the head of the household; access to credit and agricultural services; information on climate, and temperature all influence farmers’ choices of adaptation. Moreover, lack of information on adaptation measures and lack of finance are seen as the main factors inhibiting adaptation to climate change. These conclusions were obtained with a Multinomial logit model, employing the results from a survey of 400 smallholder farmers in three districts in Tigray, northern Ethiopian.
Drought‐induced water shortage and salinization are a global threat to agricultural production. With climate change, drought risk is expected to increase as drought events are assumed to occur more ...frequently and to become more severe. The agricultural sector's adaptive capacity largely depends on farmers’ drought risk perceptions. Understanding the formation of farmers’ drought risk perceptions is a prerequisite to designing effective and efficient public drought risk management strategies. Various strands of literature point at different factors shaping individual risk perceptions. Economic theory points at objective risk variables, whereas psychology and sociology identify subjective risk variables. This study investigates and compares the contribution of objective and subjective factors in explaining farmers’ drought risk perception by means of survey data analysis. Data on risk perceptions, farm characteristics, and various other personality traits were collected from farmers located in the southwest Netherlands. From comparing the explanatory power of objective and subjective risk factors in separate models and a full model of risk perception, it can be concluded that farmers’ risk perceptions are shaped by both rational and emotional factors. In a full risk perception model, being located in an area with external water supply, owning fields with salinization issues, cultivating drought‐/salt‐sensitive crops, farm revenue, drought risk experience, and perceived control are significant explanatory variables of farmers’ drought risk perceptions.
The conventional method of risk analysis (with risk as a product of probability and consequences) does not allow for a pluralistic approach that includes the various risk perceptions of stakeholders ...or lay people within a given social system. This article introduces a methodology that combines the virtues of three different methods: the quantifiable conventional approach to risk; the taxonomic analysis of perceived risk; and the analytical framework of a spatial multi-criteria analysis. This combination of methods is applied to the case study ‘Ebro Delta’ in Spain as part of the European sixth framework project ‘Floodsite’. First, a typology for flood hazards is developed based on individual and/or stakeholders’ judgements. Awareness, worry and preparedness are the three characteristics that typify a community to reflect various levels of ignorance, perceived security, perceived control or desired risk reduction. Applying ‘worry’ as the central characteristic, a trade-off is hypothesized between Worry and the benefits groups in society receive from a risky situation. Second, this trade-off is applied in Spatial Multi-Criteria Analysis (SMCA). MCA is the vehicle that often accompanies participatory processes, where governmental bodies have to decide on issues in which local stakeholders have a say. By using risk perception-scores as weights in a standard MCA procedure a new decision framework for risk assessment is developed. Finally, the case of sea-level rise in the Ebro Delta in Spain serves as an illustration of the applied methodology. Risk perception information has been collected with help of an on-site survey. Risk perception enters the multi-criteria analysis as complementary weights for the criteria risk and benefit. The results of the survey are applied to a set of scenarios representing both sea-level rise and land subsidence for a time span of 50 years. Land use alternatives have been presented to stakeholders in order to provide the regional decision maker with societal preferences for handling risk. Even with limited resources a characteristic ‘risk profile’ could be drawn that enables the decision maker to develop a suitable land use policy.
Theoretical and experimental studies from psychological and behavioral sciences show that heuristics and social networks play an important role in decision-making under risk. The goal of this paper ...is to investigate the effects of empirical social networks and different behavioral rules on farmers’ irrigation adoption under drought risk and its impacts on several macroeconomic indicators such as the rate of adaptation, water demand and regional agricultural income. We present an application of a spatial economic ABM which is able to simulate the effect of droughts on crop production, farm income and farm decision-making. The agents’ population is parameterized using survey data, including data on social networks. Four experiments are conducted combining two climate scenarios with two behavioral scenarios (maximizers vs. heuristic-based agents). The results show that the adoption process follows a different path in the scenario with heuristic-based farmers. The adoption of irrigation is slower in the short run due to reliance on information from social networks and farmers’ uncertainty regarding drought events. This results in agricultural income loss and a lower water demand in the short run compared to the scenario with maximizing agents.
This paper shows, through a numerical example, how to develop portfolios of flood management activities that generate the highest return under an acceptable risk for an area in the central part of ...the Netherlands. The paper shows a method based on Modern Portfolio Theory (MPT) that contributes to developing flood management strategies. MPT aims at finding sets of investments that diversify risks thereby reducing the overall risk of the total portfolio of investments. This paper shows that through systematically combining four different flood protection measures in portfolios containing three or four measures; risk is reduced compared with portfolios that only contain one or two measures. Adding partly uncorrelated measures to the portfolio diversifies risk. We demonstrate how MPT encourages a systematic discussion of the relationship between the return and risk of individual flood mitigation activities and the return and risk of complete portfolios. It is also shown how important it is to understand the correlation of the returns of various flood management activities. The MPT approach, therefore, fits well with the notion of adaptive water management, which perceives the future as inherently uncertain. Through applying MPT on flood protection strategies current vulnerability will be reduced by diversifying risk.
We simulate a large-scale flooding in the province of South-Holland in the economic centre of the Netherlands. In traditional research, damage due to flooding is computed with a unit loss method ...coupling land use information to depth-damage functions. Normally only direct costs are incorporated as an estimate of damage to infrastructure, property and business disruption. We extend this damage concept with the indirect economic effects on the rest of the regional and national economy on basis of a bi-regional input output table.We broaden this damage estimation to the concept of vulnerability. Vulnerability is defined as a function of dependence, redundancy and susceptibility. Susceptibility is the probability and extent of flooding. Dependency is the degree to which an activity relates to other economic activities in the rest of the country. Input-output multipliers form representations of this dependency. Redundancy is the ability of an economic activity to respond to a disaster by deferring, using substitutes or relocating. We measure redundancy as the degree of centrality of an economic activity in a network. The more central an activity is, the less it encounters possibilities to transfer production and the more vulnerable it is for flooding. Vulnerability of economic activities is then visualized in a GIS. Kernel density estimation is applied to generalize point information on inundated firms to sectoral information in space. We apply spatial interpolation techniques for the whole of the province of South-Holland. Combining information of sectoral data on dependency and redundancy, we are able to create maps of economic hotspots. Our simulation of a flood in the centre of Holland reveals the vulnerability of a densely populated delta.
Stakeholder analysis and social network analysis were used to analyze stakeholders' social and structural characteristics based on their interests, influence and interactions in Lake Naivasha basin, ...Kenya. Even though the Kenyan government and its agencies seem to command higher influence and interest in water resource management, the presence of influential and central stakeholders from non-government sectors plays a key role in strengthening partnership in a governance environment with multiple sectors, complex issues and competing interests. Interactions in the basin are guided by stakeholders' interest and sphere of influence, which have both promoted participation in implementing a collaborative water governance framework.
Ecosystem‐based fisheries management (EBFM) is an important complement to existing fisheries management approaches to maintain ecosystem health and function; to translate goals and aspirations for ...sustainability into operational objectives, the preferences of the fishing communities should be considered for successful implementation of EBFM. This study analysed the preferences of the fishing community for alternative EBFM developments for Lake Naivasha, Kenya, and estimated the willingness to pay, using a choice experiment approach. Protection of fish breeding grounds, improving tilapia fish abundance and accessibility of fishing zones were identified as relevant EBFM attributes for the choice experiment. A monetary attribute (payment for fishing permit) was also included. In addition to a conditional logit model, mixed logit models are estimated to account for heterogeneity in preferences. This study results indicated fishing communities are most concerned about tilapia fish abundance and protection of fish breeding grounds. The welfare measures reveal that members of the Lake Naivasha fishing community are willing to pay a considerable sum of money for ecosystem services improvement, relative to their low income derived from fishing. These study findings highlighted that evaluating the preferences of the fishing community and valuing the fishery at an ecosystem level are vital to prioritize and choose between alternative interventions for sound implementation of EBFM.
Climate change and variability severely affect rural livelihoods and agricultural productivity, yet they are causes of stress vulnerable rural households have to cope with. This paper investigated ...farming communities' vulnerability to climate change and climate variability across 34 agricultural-based districts in Tigray, northern Ethiopia. It considered 24 biophysical and socio-economic indicators to reflect the three components of climate change vulnerability: exposure, sensitivity and adaptive capacity. A framework was used that combines exposure and sensitivity to produce potential impact, which was then compared with adaptive capacity in order to yield an overall measure of vulnerability. The classic statistical technique of factor analysis was applied to generate weights for the different indicators and an overall vulnerability index was constructed for the 34 rural districts. The analysis revealed that the districts deemed to be most vulnerable to climate change and variability overlapped with the most vulnerable populations. The most exposed farming communities showed a relatively low capacity for adaptation. The study further showed that vulnerability to climate change and variability is basically linked to social and economic developments.
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