Analyzing adaptation strategies to climate change followed by the farming community of the Indian Sunderbans using Analytical Hierarchy Process

Abstract Background The urban water system is the worst hit in global climate change. Water resilience is the system’s ability to retaliate and recover from various water-related disruptions. The present study aims to delineate the water resilience zones in Chennai city, Tamil Nadu, India, by effectively integrating the geographic information system, remote sensing, and analytical hierarchy process (AHP). Methods The methodology incorporated 15 vital factors. A multi-criteria decision analysis technique was adopted to assign a weight to each parameter using the AHP. A pairwise decision matrix was constructed, parameter’s relative importance and the consistency ratio were established. Integration of all maps by weighted overlay analysis technique depicted water resilience intensities of five different classes. Results Very low, low and moderate water resilience areas accounted for more than three-fourth of the study area. Area Under Curve score (80.12%) depicted the accuracy of the developed model. Sensitivity analysis determined the significance of the parameters in the delineation. The logical structural approach can be employed in other parts of India or elsewhere with modifications. Conclusion This study is novel in its approach by holistically analyzing water resilience by integrating disruptions related to flood, drought and the city's water infrastructure system's adequacy and efficiency. Researchers and planners can effectively use the study results to ensure resilience as a new perspective on effective water resource management and climate change mitigation. It becomes a decision aid mechanism identifying where the system is vulnerable to potential water-related risks for employing resilience measures.

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Vulnerability of Watersheds to Climate Change Assessed by Neural Network and Analytical Hierarchy Process

10.1007/978-981-287-344-6 ◽

2016 ◽

Cited By ~ 2

Author(s):

Uttam Roy ◽

Mrinmoy Majumder

Keyword(s):

Neural Network ◽

Climate Change ◽

Analytical Hierarchy Process ◽

Hierarchy Process

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Climate Change and Rural Female Farmers in Ghana: A Study of the Wenchi Municipality

10.20944/preprints202106.0088.v1 ◽

2021 ◽

Author(s):

Lily Yarney ◽

Emmanuel Kojo Sakyi ◽

Jonathan Chuks Mba ◽

Peter K. Achamwie

Keyword(s):

Climate Change ◽

Crop Production ◽

Adaptation Strategies ◽

Crop Failure ◽

Middle Income ◽

Middle Income Countries ◽

Farming Community ◽

Female Farmers ◽

Basic Infrastructure

Climate change poses a major threat to development in most low and middle-income countries, especially the sub – Saharan Africa. Wurompo is a small farming community in the Wenchi Municipality of the Brong-Ahafo region of Ghana that depends on rain-fed agriculture activities for livelihood. In recent years, droughts, unpredictable rainfall pattern and crop failure have become common in the area. The study assessed knowledge and awareness, effects of climate change on female farmers, and their adaptation strategies. A case study in design, qualitative methods were used to collect data from 50 purposefully selected participants. Data were analyzed using themes and sub-themes generated from the research questions. Findings showed lack of adequate information and knowledge on climate change and its effects. Climate change has impacted negatively on these farmers stemming from decline in crop production and unavailability of adequate water supply in due season. Challenges to climate change adaptation are poverty, poor basic infrastructure, and modern farming practices. Farmers must be educated on climate change and its effects, with training on the necessary adaptation strategies to build their resilience. Policies that target rural farmers to adapt to climate change, and device modern agricultural techniques and practices are also necessary.

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Applying Analytic Hierarchy Process to Adaptation to Saltwater Intrusion in Vietnam

Sustainability ◽

10.3390/su13042311 ◽

2021 ◽

Vol 13 (4) ◽

pp. 2311

Author(s):

Thi Dieu Linh Nguyen ◽

Brent Bleys

Keyword(s):

Climate Change ◽

Focus Group ◽

Analytical Hierarchy Process ◽

Saltwater Intrusion ◽

Coastal Region ◽

Pairwise Comparison ◽

Focus Group Discussions ◽

Group Discussions ◽

Hierarchy Process ◽

Adaptation Options

Given the multidimensional nature of climate change issues, decision-making in climate change adaptation is a complex process, and suitable decision support methods are needed. The aim of this paper was to rank saltwater intrusion adaptation options for farmers in two provinces in the central coastal region of Vietnam using the analytical hierarchy process method. Data for the analysis were obtained through a literature review, field observations, and face-to-face interviews and focus group discussions with key informants. We combined two ways of weighting to arrive at final scores for each of the identified adaptation options: prioritizing criteria and subcriteria by pairwise comparison and rating the different alternatives with respect to the lowest level subcriteria. In doing so, we also investigated differences in the priority sets and final rankings of the analytical hierarchy process applications in both provinces. In our study, we worked with group consensus scores on both the criteria weights and the ratings for the different adaptation options for each of the criteria. Our results revealed that “sustainability and equity” was the most important criteria, while coherence ranked lowest. The final ranking of adaptation options differed between both provinces due to differences in the geographical and socioeconomic characteristics of the study areas. The consistency ratios for all pairwise matrices were less than 0.1, indicating that judgments from the focus group discussions with respect to the different criteria were highly consistent. A sensitivity analysis of our results confirmed the robustness of the rankings in our research.

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