scholarly journals Determinants of Climate Change Risk Management Strategies Among the Aquaculture Fish Farmers in Nigeria Using Multinomial Logit Model

2021 ◽  
Author(s):  
Brenden Jongman ◽  
Hessel C. Winsemius ◽  
Stuart A. Fraser ◽  
Sanne Muis ◽  
Philip J. Ward

The flooding of rivers and coastlines is the most frequent and damaging of all natural hazards. Between 1980 and 2016, total direct damages exceeded $1.6 trillion, and at least 225,000 people lost their lives. Recent events causing major economic losses include the 2011 river flooding in Thailand ($40 billion) and the 2013 coastal floods in the United States caused by Hurricane Sandy (over $50 billion). Flooding also triggers great humanitarian challenges. The 2015 Malawi floods were the worst in the country’s history and were followed by food shortage across large parts of the country. Flood losses are increasing rapidly in some world regions, driven by economic development in floodplains and increases in the frequency of extreme precipitation events and global sea level due to climate change. The largest increase in flood losses is seen in low-income countries, where population growth is rapid and many cities are expanding quickly. At the same time, evidence shows that adaptation to flood risk is already happening, and a large proportion of losses can be contained successfully by effective risk management strategies. Such risk management strategies may include floodplain zoning, construction and maintenance of flood defenses, reforestation of land draining into rivers, and use of early warning systems. To reduce risk effectively, it is important to know the location and impact of potential floods under current and future social and environmental conditions. In a risk assessment, models can be used to map the flow of water over land after an intense rainfall event or storm surge (the hazard). Modeled for many different potential events, this provides estimates of potential inundation depth in flood-prone areas. Such maps can be constructed for various scenarios of climate change based on specific changes in rainfall, temperature, and sea level. To assess the impact of the modeled hazard (e.g., cost of damage or lives lost), the potential exposure (including buildings, population, and infrastructure) must be mapped using land-use and population density data and construction information. Population growth and urban expansion can be simulated by increasing the density or extent of the urban area in the model. The effects of floods on people and different types of buildings and infrastructure are determined using a vulnerability function. This indicates the damage expected to occur to a structure or group of people as a function of flood intensity (e.g., inundation depth and flow velocity). Potential adaptation measures such as land-use change or new flood defenses can be included in the model in order to understand how effective they may be in reducing flood risk. This way, risk assessments can demonstrate the possible approaches available to policymakers to build a less risky future.


Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2643
Author(s):  
Flavia Simona Cosoveanu ◽  
Jean-Marie Buijs ◽  
Marloes Bakker ◽  
Teun Terpstra

Diversification of flood risk management strategies (FRMS) in response to climate change relies on the adaptive capacities of institutions. Although adaptive capacities enable flexibility and adjustment, more empirical research is needed to better grasp the role of adaptive capacities to accommodate expected climate change effects. This paper presents an analytical framework based on the Adaptive Capacity Wheel (ACW) and Triple-loop Learning. The framework is applied to evaluate the adaptive capacities that were missing, employed, and developed throughout the ‘Alblasserwaard-Vijfheerenlanden’ (The Netherlands) and the ‘Wesermarsch’ (Germany) pilot projects. Evaluations were performed using questionnaires, interviews, and focus groups. From the 22 capacities of ACW, three capacities were identified important for diversifying the current FRMS; the capacity to develop a greater variety of solutions, continuous access to information about diversified FRMS, and collaborative leadership. Hardly any capacities related to ‘learning’ and ‘governance’ were mentioned by the stakeholders. From a further reflection on the data, we inferred that the pilot projects performed single-loop learning (incremental learning: ‘are we doing what we do right?’), rather than double-loop learning (reframing: ‘are we doing the right things?’). As the development of the framework is part of ongoing research, some directions for improvement are highlighted.


Author(s):  
Happy M. Tirivangasi

Natural disasters and food insecurity are directly interconnected. Climate change related hazards such as floods, hurricanes, tsunamis, droughts and other risks can weaken food security and severely impact agricultural activities. Consequently, this has an impact on market access, trade, food supply, reduced income, increased food prices, decreased farm income and employment. Natural disasters create poverty, which in turn increases the prevalence of food insecurity and malnutrition. It is clear that disasters put food security at risk. The poorest people in the community are affected by food insecurity and disasters; hence, there is a need to be prepared as well as be in a position to manage disasters. Without serious efforts to address them, the risks of disasters will become an increasingly serious obstacle to sustainable development and the achievement of sustainable development goals, particularly goal number 2 ‘end hunger, achieve food security and improved nutrition and promote sustainable agriculture’. In recent years, countries in southern Africa have experienced an increase in the frequency, magnitude and impact of climate change–related hazards such as droughts, veld fire, depleting water resources and flood events. This research aims to reveal Southern African Development Community disaster risk management strategies for food security to see how they an influence and shape policy at the national level in southern Africa. Sustainable Livelihood approach was adopted as the main theoretical framework for the study. The qualitative Analysis is based largely on data from databases such as national reports, regional reports and empirical findings on the disaster management–sustainable development nexus.


2010 ◽  
Vol 01 (03) ◽  
pp. 167-185 ◽  
Author(s):  
JINXIA WANG ◽  
ROBERT MENDELSOHN ◽  
ARIEL DINAR ◽  
JIKUN HUANG

A multinomial logit model is estimated across the crop choices of a sample of thousands of Chinese farmers. As temperatures warm, farmers are more likely to choose cotton and maize, but less likely to choose soybeans, and vegetables. As precipitation increases, farmers are more likely to choose wheat and less likely to choose vegetables and potatoes. We simulate how crop choice outcomes might change using the empirical results and a set of climate change predictions for 2100. The magnitude of the change is sensitive to the climate scenario and to the seasonal and regional variation of climate change predictions within China.


Author(s):  
Sanjib Sharma ◽  
Michael Gomez ◽  
Klaus Keller ◽  
Robert Nicholas ◽  
Alfonso Mejia

AbstractFlood-related risks to people and property are expected to increase in the future due to environmental and demographic changes. It is important to quantify and effectively communicate flood hazards and exposure to inform the design and implementation of flood risk management strategies. Here we develop an integrated modeling framework to assess projected changes in regional riverine flood inundation risks. The framework samples climate model outputs to force a hydrologic model and generate streamflow projections. Together with a statistical and hydraulic model, we use the projected streamflow to map the uncertainty of flood inundation projections for extreme flood events. We implement the framework for rivers across the state of Pennsylvania, United States. Our projections suggest that flood hazards and exposure across Pennsylvania are overall increasing with future climate change. Specific regions, including the main stem Susquehanna River, lower portion of the Allegheny basin and central portion of Delaware River basin, demonstrate higher flood inundation risks. In our analysis, the climate uncertainty dominates the overall uncertainty surrounding the flood inundation projection chain. The combined hydrologic and hydraulic uncertainties can account for as much as 37% of the total uncertainty. We discuss how this framework can provide regional and dynamic flood-risk assessments and help to inform the design of risk-management strategies.


2017 ◽  
Vol 08 (03) ◽  
pp. 1740001 ◽  
Author(s):  
LUN OU ◽  
ROBERT MENDELSOHN

This paper explores how southeast Asia farmers adapt to climate change. We develop three models: a logit model of livestock choice, an OLS model of total livestock value, and a multinomial logit model of species choice. The data were collected from five countries in Southeast Asia. We find that climate has a significant impact on farmers’ livestock choice. We use three climate projections to predict future impacts. Climate change would increase the probability of raising livestock. However, the total value of livestock owned per livestock farm will shrink 9%–10%. Climate change will cause farmers to choose smaller animals such as ducks, goats, and chicken rather than larger animals.


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