Development of Multi-scale/Multi-objective Spatial Optimization Model Based on Genetic Algorithms

윤은주 서울대학교 대학원 2019 국내박사

The meeting of heterogeneous goals while staying within the constraints of spatial planning is a nonlinear problem that cannot be solved by linear methodologies. Instead, this problem can be solved using multi-objective optimization algorithms such as genetic algorithms (GA), simulated annealing (SA), ant colony optimization (ACO), etc., and research related to this field has been increasing rapidly. GA, in particular, are the most frequently applied spatial optimization algorithms and are known to search for a good solution within a reasonable time period by maintaining a balance between exploration and exploitation. However, despite its good performance and applicability, it has not adequately addressed recent urgent issues such as climate change adaptation, disaster management, and green infrastructure planning. It is criticized for concentrating on only the allocation of specific land use such as urban and protected areas, or on the site selection of a specific facility. Therefore, in this study, a series of spatial optimizations are proposed to address recent urgent issues such as climate change, disaster management, and urban greening by supplementing quantitative assessment methodologies to the spatial planning process based on GA and Non-dominated Sorting Genetic Algorithm II (NSGA II). This optimization model needs to be understood as a tool for providing a draft plan that quantitatively meets the essential requirements so that the stakeholders can collaborate smoothly in the planning process. Three types of spatial planning optimization models are classified according to urgent issues. Spatial resolution, planning objectives, and constraints were also configured differently according to relevant issues. Each spatial planning optimization model was arranged in the order of increasing spatial resolution. In the first chapter, the optimization model was proposed to simulate land use scenarios to adapt to climate change on a provincial scale. As climate change is an ongoing phenomenon, many recent studies have focused on adaptation to climate change from a spatial perspective. However, little is known about how changing the spatial composition of land use could improve resilience to climate change. Consideration of climate change impacts when spatially allocating land use could be a useful and fundamental long-term adaptation strategy, particularly for regional planning. Here climate adaptation scenarios were identified on the basis of existing extents of three land use classes using Multi-objective Genetic Algorithms (MOGA) for a 9,982 km2 region with 3.5 million inhabitants in South Korea. Five objectives were selected for adaptation based on predicted climate change impacts and regional economic conditions: minimization of disaster damage; and existing land use conversion; maximization of rice yield; protection of high-species-richness areas; and economic value. The 17 Pareto land use scenarios were generated by six weighted combinations of the adaptation objectives. Most scenarios, although varying in magnitude, showed better performance than the current spatial land use composition for all adaptation objectives, suggesting that some alteration of current land use patterns could increase overall climate resilience. Given the flexible structure of the optimization model, it is expected that regional stakeholders would efficiently generate other scenarios by adjusting the model parameters (weighting combinations) or replacing the input data (impact maps) and selecting a scenario depending on their preference or a number of problem-related factors. In the second chapter, the optimization model was proposed to simulate land use scenarios for managing disaster damage due to climate change on local scale. Extreme landslides triggered by rainfall in hilly regions frequently lead to serious damage, including casualties and property loss. The frequency of landslides may increase under climate change, because of the increased variability of precipitation. Developing urban areas outside landslide risk zones is the most effective method of reducing or preventing damage; planning in real life is, however, a complex and nonlinear problem. For such multi-objective problems, GA may be the most appropriate optimization tool. Therefore, comprehensive land use allocation plans were suggested using the NSGA II to overcome multi-objective problems, including the minimization of landslide risk, minimization of change, and maximization of compactness. The study area is Pyeongchang-gun, the host city of the 2018 Winter Olympics in Korea, where high development pressure has resulted in an urban sprawl into the hazard zone that experienced a large-scale landslide in 2006. We obtained 100 Pareto plans that are better than the actual land use data for at least one objective, with five plans that explain the trade-offs between meeting the first and the second objectives mentioned above. The results can be used by decision makers for better urban planning and for climate change-related spatial adaptation. In the third chapter, the optimization model was proposed to simulate urban greening plans on a neighborhood scale. Green space is fundamental to the good quality of life of residents, and therefore urban planning or improvement projects often include strategies directly or indirectly related to greening. Although green spaces generate positive effects such as cooling and reduction of rainwater runoff, and are an ecological corridor, few studies have examined the comprehensive multiple effects of greening in the urban planning context. To fill this gap in this field’s literature, this study seeks to identify a planning model that determines the location and type of green cover based on its multiple effects (e.g., cooling and enhancement of ecological connectivity) and the implementation cost using NSGA II. The 30 Pareto-optimal plans were obtained by applying our model to a hypothetical landscape on a neighborhood scale. The results showed a synergistic relationship between cooling and enhancement of connectivity, as well as a trade-off relationship between greenery effects and implementation cost. It also defined critical lots for urban greening that are commonly selected in various plans. This model is expected to contribute to the improvement of existing planning processes by repeating the positive feedback loop: from plan modification to quantitative evaluation and selection of better plans. These optimal plans can also be considered as options for “co-design” by related stakeholders. 공간계획 과정에서 다양한 이해관계자와 결부된 목표와 제약 요건을 만족시키는 것은 복잡한 비선형적 문제로서 해결하기 어려운 것으로 알려져 왔다. 그러나 최근 이러한 문제에 유전 알고리즘 (genetic algorithms), 담금질 기법 (simulated annealing), 개미 군집 최적화 (ant colony optimization) 등의 다목적 최적화 알고리즘이 응용되고 있으며, 관련 연구 역시 급증하고 있다. 이 중 유전 알고리즘은 공간 최적화 부문에 가장 빈도 높게 적용된 최적화 알고리즘으로 “exploration”과 “exploitation”의 균형으로 합리적인 시간 내에 충분히 좋은 계획안을 제시할 수 있다. 그러나 공간 최적화 연구가 보여준 좋은 성과에도 불구하고 대부분의 연구가 특정 용도 혹은 시설의 배치에 집중되어 있으며, 기후변화 적응, 재해 관리, 그린인프라 계획과 같은 최근의 환경 이슈를 다룬 사례는 매우 미흡하다. 따라서 본 연구에서는 유전 알고리즘과 비지배 정렬 유전 알고리즘 (non-dominated sorting genetic algorithm II)에 기초하여 기후변화 적응, 재해 관리, 도시의 녹지 계획 등과 같은 환경 이슈를 공간계획에 반영할 수 있는 일련의 공간 최적화 모델을 제시하였다. 개별 환경 이슈에 따라 공간 해상도, 목적, 제약요건이 다르게 구성하였으며, 공간적 범위가 좁아지고 공간해상도는 높아지는 순서대로 나열하였다. 논문의 첫번째 장에서는 행정구역 도 규모 (province scale, 해상도 1㎢)에서 미래의 기후변화에 적응하기 위한 토지이용 시나리오를 모의할 수 있는 공간 최적화 모델을 제안하였다. 기후변화가 먼 미래가 아닌, 현재 이미 진행되고 있으며 관련한 다수의 피해가 관찰되고 있기 때문에 공간적 관점에서 기후변화에 대한 적응의 필요성이 지적되어 왔다. 그러나 구체적으로 기후에 대한 회복 탄력성을 향상시키기 위하여 토지이용의 공간적 구성을 어떻게 변화시켜야 할지에 대한 방법론 제시는 미흡하다. 지역계획에서 기후변화 영향을 고려한 토지이용 배분은 매우 유용한, 기본적인 중장기 적응 전략에 해당한다. 본 연구에서는 다목적 유전 알고리즘 (MOGA, multi-objective genetic algorithm)에 기초하여 9,982㎢에 350만의 인구가 거주하는 한국의 충청남도 및 대전광역시 일대를 대상으로 기후변화 적응을 위한 토지이용 시나리오를 제시하였다. 지역적인 기후변화 영향과 경제적 여건을 고려하여 재해 피해 및 전환량의 최소화, 벼 생산량, 종 풍부도 보전, 경제적 가치의 최대화 등 다섯 가지의 목적을 선택하였다. 각 목적 별 가중치를 변화시키며 여섯 가지 가중치 조합에 대한 17개의 파레토 최적 토지이용 시나리오를 생성하였다. 대부분의 시나리오는 정도의 차이는 있으나 현재의 토지이용에 비해 기후변화 적응 부분에서 더 좋은 퍼포먼스를 보였으므로, 기후변화에 대한 회복탄력성이 개선할 수 있을 것으로 판단하였다. 또한 공간 최적화 모델의 유연한 구조를 고려하였을 때, 지역의 실무자 역시 가중치와 같은 모델의 파라미터, 기후변화 영향 평가와 같은 입력자료를 변경함으로써 효율적으로 새로운 시나리오를 생성 및 선택하는 것이 가능할 것으로 예상하였다. 논문의 두 번째 장에서는 행정구역 군 규모 (local scale, 해상도 100m)에서 기후변화에 따른 재해 피해를 관리하기 위한 토지이용 시나리오를 모의할 수 있는 공간 최적화 모델을 제안하였다. 산악지형에서 폭우로 인한 산사태는 인명과 재산에 심각한 피해를 초래할 수 있는 것으로 알려져 있다. 더욱이 기후변화에 따른 강우의 변동성 증가로 이러한 산사태 빈도 및 강도 역시 증대될 것으로 예상된다. 일반적으로 산사태 리스크가 높은 지역을 피해 개발지역을 배치하는 것이 피해를 저감 혹은 회피할 수 있는 가장 효과적인 전략으로 알려져 있으나, 실제공간에서의 계획은 매우 복잡한 비선형의 문제로서 이것을 실현하는 데 어려움이 있다. 따라서 본 연구에서는 비지배 정렬 유전 알고리즘 II에 기초하여 산사태 리스크 및 전환량, 파편화의 최소화 등의 다양한 목적을 만족시키는 종합적인 토지이용 배분 계획을 제안하였다. 대상지는 2018년 동계올림픽 개최지인 한국의 평창군으로서 2006년에 산사태로 인한 대규모의 피해를 경험하였으나, 올림픽 특수 등의 개발압력으로 인한 난개발이 우려되는 지역이다. 최종적으로 한번의 모의를 통해 현재의 토지이용 보다 적어도 한가지 이상의 목적에서 좋은 퍼포먼스를 보이는 100개의 파레토 최적 계획안을 생성하였다. 또한 5개의 대표적인 계획안을 선정하여 산사태리스크 최소화와 전환량 최소화 간에 발생하는 상쇄 효과를 설명하였다. 본 연구결과는 기후변화와 관련된 공간 적응 전략의 수립, 보다 향상된 개발계획을 위한 의사결정을 효과적으로 지원할 수 있을 것으로 예상하였다. 논문의 세 번째 장에서는 블록 규모(neighborhood scale, 2m)에서 도시 내 녹지계획안을 모의할 수 있는 공간 최적화 모델을 제안하였다. 녹지 공간은 도시민의 삶의 질에 결정적인 영향을 미치기 때문에 다양한 도시 재생 및 개발계획에는 녹지와 직 간접적으로 관련된 전략이 포함된다. 녹지 공간은 도시지역 내에서 열섬 현상 완화, 유출량 저감, 생태 네트워크 증진 등 다양한 긍정적 효과가 있음이 알려져 있으나, 공간 계획의 관점에서 이러한 다양한 효과를 종합적, 정량적으로 고려된 사례는 매우 미흡하다. 따라서 본 연구에서는 비지배 정렬 유전 알고리즘 II에 기초하여 녹지의 생태적 연결성 증진, 열섬 효과 완화와 같은 다양한 효과와 설치에 따르는 비용을 종합적으로 고려하여 적절한 녹지의 유형과 위치를 결정한 녹지계획안을 제시하였다. 블록 규모의 가상의 대상지에 본 최적화 모델을 적용함으로써 30개의 파레토 최적 녹지계획안을 생성하였으며, 각 목적 간 퍼포먼스를 비교하여 녹지의 열섬 완화 효과와 생태적 연결성 증진 효과 간의 상승 관계 (synergistic relationship), 이러한 긍정적 효과와 비용 절감 간의 상쇄 효과 (trade-off relationship)를 분석하였다. 또한 다양한 계획안 중 대표적인 특성을 지니는 계획안, 다수의 계획안에서 공통적으로 녹지 설치를 위해 선택된 주요 후보지역 역시 규명하였다. 본 연구에서 제시된 모델은 계획안의 수정에서부터 정량적 평가, 계획안 선택에 이르는 일련의 긍정적인 피드백 과정을 수없이 반복함으로써 기존의 녹지계획 과정을 개선하는 데 기여할 수 있을 뿐만 아니라 모델의 결과 역시 다자간 협력적 디자인 (co-design)을 위한 초안으로서 활용될 수 있을 것으로 예상하였다.

Climate Perception of Farmers and Their Livelihood Resilience to Climate Change in Inner Mongolia, China

한지영 서울대학교 대학원 2024 국내박사

기후 변화는 농업이 주된 생계수단인 개발도상국에 중대한 도전을 가져왔다. 농민들은 기후 변화를 직접 인식하며 영향을 받는 주체로, 정확한 기후 변화 인식은 효과적인 적응 전략 선택에 중요하다. 뿐만 아니라, 그들의 생계 회복력은 기후 변화의 중단에 직면할 때 그들이 생계를 회복하고 개선하는 데 도움이 된다. 본 연구의 두 가지 목표는 1) 농민들의 기후 변화에 대한 인식을 조사하고 이 인식의 정확도에 영향을 미치는 요인을 분석하는 것이며, 2) 농민들의 생계가 기후 변화에 얼마나 강건한지 및 이 회복력에 영향을 미치는 요인을 평가하는 것이다. Aohan Banner를 연구 지역으로 삼아 2021년에 농민 630명과 전문가 77명 (인식에 대한 42명, 생계 회복력에 대한 35명)을 대상으로 설문조사를 실시했다. 목표 1에 대한 답으로, 농민들의 기후 변화 인식의 정확도는 기상 데이터와 비교하여 측정되었다. 그런 다음 농민과 전문가는 12가지 기상 재해의 영향을 순위로 매겼다. 마지막으로, 농민들의 기후 변화에 대한 정확한 인식에 영향을 미치는 요인은 순서형 로지스틱 회귀를 통해 분석되었다. 발견된 결과는 다음과 같다: 1) 대부분의 농민은 기온이 상승하고 강수량이 감소하는 것으로 인식하고 있으며, 이는 기상 데이터 및 대부분의 전문가 의견과 일치한다. 2) 대부분의 농민은 풍속이 증가했다고 인식하고 있으나, 이는 기상 데이터 및 대부분의 전문가 의견과 반대이다. 3) 농민들의 기상 재해 영향 정도에 대한 인식은 연속적으로 가뭄, 서리 및 폭우이다. 영향 정도는 전문가 의견과 다르지만 가뭄에 대한 인식은 같다. 가뭄은 농민에게 가장 심각한 기상 재해로 여겨진다. 4) 경작 연수, 농업 수입, 인터넷과 텔레비전을 통한 정보 접근 및 기후 변화에 대한 관심은 농민들의 기후 변화 정확한 인식과 양의 상관 관계가 있다. 목표 2에 대한 답으로, 내는 강건성 이론을 기반으로 지표 체계를 구축하여 회복력을 측정하였고 종합 지수 방법을 사용하여 전문가와 농민 조사 데이터를 분석했다. 동시에 다중 선형 회귀 모델을 사용하여 서로 다른 생계 유형 및 도시 간에 농민의 생계 회복력에 영향을 미치는 주요 요인을 분석했다. 발견된 결과는 농업이 주된 직업인 농민들이 가장 높은 회복력 점수를 가지고 있으며, 생계 회복력은 지리적 위치에 따라 다르다는 것이다. 구체적으로, 생계 회복력은 남부에서 북부로, 그리고 산림 및 산림 초지에서 초원으로 점차 감소한다. 결과는 또한 교육 수준, 농업 기술 교육, 교통 인프라, 정보 접근성, 기후 변화에 대한 인식, 기후 변화 인식, 생계 전략 변화, 가족 규모 및 경작 지역 보유 크기가 농민 생계 회복력과 양의 상관 관계가 있음을 보여준다. 반면에 가구주 나이는 회복력과 음의 상관 관계가 있다. 따라서 정책 결정자는 1) 가뭄 재해를 효과적으로 대응하기 위한 전략을 시행하고, 2) 농민들을 위한 학습 활동과 농업 기술 교육을 확대하며, 3) 기후 변화 지식을 홍보하고, 4) 농업 생계 다양화, 5) 경작 지역 주변의 산림화, 6) 농촌 교통 환경 개선을 권고한다. Climate change brings significant challenges to developing countries whose primary livelihood is agriculture. Farmers are the ones directly perceiving and being affected by climate change, and their correct perception of climate change is critical for choosing effective adaptation strategies. In addition, their livelihood resilience can help them recover and improve their livelihoods in the face of climate change disruptions. This study has two objectives: 1) to examine farmers’ perception of climate change and analyze the factors that affect the accuracy of their perception; 2) to evaluate how resilient farmers’ livelihoods are to climate change and what factors influence this resilience. Taking Aohan Banner as a study area, I surveyed 630 farmers and 77 experts (42 for perception, 35 for livelihood resilience) in 2021. To answer objective 1, the accuracy of farmers’ perception of climate change was measured by comparing it with meteorological data. Farmers and experts then ranked the impact of 12 meteorological disasters. Finally, the factors affecting farmers’ correct perception of climate change were analyzed by ordinal logistic regression. I found that: 1) Most farmers’ perception of temperature is rising, while their perception of precipitation is falling, consistent with meteorological data and most expert views. 2) Most farmers’ perception of wind speed has increased, which is contrary to meteorological data and most expert views. 3) Farmers’ perception of the impact degree of meteorological disasters, whose impact degree is successively drought, frost, and rainstorms. The impact degree is different from experts’ opinion, but the perception of drought is the same that drought is considered to be the most severe meteorological disaster affecting farmers. 4) The years of farming, agricultural income, access to information via the Internet and television, and concern about climate change are positively correlated with farmers’ correct perception of climate change. To answer objective 2, I constructed an indicator system based on resilience theory to measure resilience and analyzed expert and farmer survey data using the comprehensive index method. Meanwhile, I used a multiple linear regression model to analyze the key factors affecting farmer livelihood resilience across different livelihood types and towns. I found that farmers who primarily worked in agriculture had the highest resilience scores and that livelihood resilience differed by geographical location; specifically, livelihood resilience gradually declines from southern to northern and from forest and forest-grassland to grassland locations. The results also showed that education level, agricultural technology training, transportation infrastructure, accessibility of information, awareness of climate change, climate change perception, change of livelihood strategies, family size, and the holding size of the arable area are positively associated with farmer livelihood resilience, while household head age is negatively associated with resilience. I, therefore, advise that policymakers should 1) implement strategies to effectively address drought disasters, 2) increase learning activities and agricultural skill training for farmers, 3) publicize climate change knowledge, 4) diversify agricultural livelihoods, 5) afforest surrounding arable areas, 6) improve rural transportation conditions.

(The) role of social marketing in meeting the challenges of climate change : lessons from New Zealand for Nigerian rural farmers

Afolabi Aanuoluwapo Okiki Graduate School of International Studies, Korea Un 2018 국내석사

For several years now, the need to combat and mitigate climate change has dominated international development agenda. This is primarily because the fight for a cleaner and sustainable environment affects every country. However, the beginning of collectively winning this journey is that citizens must be well aware of the reality of climate change—the nexus between human activities and the changes in climate. While the majority of citizens in the advanced nations seem to be aware of this relationship, many of the citizens in the developing world are otherwise. This paper focuses on Nigeria. Much more, it focuses on the rural farmers who produce food which serves as the basket of the nation. Through a survey of literature, it is found that the Nigerian rural farmers can be classified into two groups. The first group are those that are unaware of this nexus. They rather relate climate change to anger from God or simply natural disasters. This paper does not argue to discard their understanding of climate change. The second group are those who are aware of the nexus but are not responding mostly because of lack of mitigating information and tools. To this end, the paper argues for the use of social marketing to reach these groups. To justify this possibility, the successful case study of Check, Clean and Dry Campaign in New Zealand is examined. It is found that the use of community-based social marketing approach and public- private partnership helped achieve this success. This is applicable in Nigeria too because the society is communal and the government is experienced with using public private partnership to fund infrastructural projects. Thus, overall, this thesis argues that social marketing can become an effective tool to reach the rural farmers in Nigeria. At the core, the knowledge of the nexus of human activity and climate change phenomenon, and having the right information can help them design the most appropriate local mitigation and combating mechanism.

Modeling the Impacts of Climate Change on Hydrology and Agricultural Pollutant Runoff in California's Central Valley

Ficklin, Darren L University of California, Davis 2010 해외박사(DDOD)

Quantifying the hydrologic and agricultural pollutant runoff response to an increased atmospheric CO2 concentration and climate change is critical for proper management of water resources within agricultural systems. This research takes this challenge by simulating the effects of climate change on the hydrologic cycle and agricultural pollutant transport in the Central Valley of California using the Soil and Water Assessment Tool (SWAT) water quality model and the HYDRUS soil water transport model. Specifically, changes in hydrology (streamflow, surface runoff, groundwater recharge, evapotranspiration, and irrigation water use) and agricultural pollutant runoff (sediment, nitrate, phosphorus, chlorpyrifos, and diazinon) were assessed. For the first three studies, hydrological responses were modeled in the San Joaquin River watershed using variations of atmospheric CO2 (550 and 970 ppm), temperature (+1.1 and +6.4°C), and precipitation (0%, +/-10%, and +/-20%) based on Intergovernmental Panel on Climate Change projections. The fourth study used a calibration and an uncertainty analysis technique for the calibration of the Sacramento River watershed. This study confirmed that SWAT was able to capture the large amount of uncertainty within the Sacramento River watershed and successfully simulate streamflow, sediment, nitrate, chlorpyrifos and diazinon loads. The final study uses a novel stochastic climate change analysis technique to bracket the 95% confidence interval of potential climate changes. For all studies, increases in precipitation generally changed the hydrological cycle and agricultural runoff proportionally, where increases in precipitation resulted in increases in surface runoff and thus agricultural runoff and vice-versa. Also, for all studies, increasing temperature caused a temporal shift in plant growth patterns and redistributed evapotranspiration and irrigation water demand earlier in the year. This lead to an increase in streamflow during the summer months compared to the present-day climate due to decreased irrigation demand. Increasing CO2 concentration to 970 ppm and temperature by 6.4°C in the San Joaquin River watershed caused watershed-wide average evapotranspiration, averaged over 50 simulated years, to decrease by 37.5%, resulting in increases of water yield by 36.5% and stream flow by 23.5% compared to the present-day climate. Solely increasing CO2 concentration in the San Joaquin River watershed resulted in an increase in nitrate, phosphorus, and chlorpyrifos yield by 4.2, 7.8, and 6.4%, respectively, and a decrease in sediment and diazinon yield by 6.3 and 5.3%, respectively, in comparison to the presentday reference scenario. Only increasing temperature reduced yields of all agricultural runoff components. Elevating atmospheric CO 2 concentrations generally decreased groundwater recharge under almonds, alfalfa, and tomatoes in the San Joaquin Valley due to decreased evapotranspiration resulting in decreased irrigation water use. Increasing average daily temperature by 1.1 and 6.4°C and atmospheric CO2 concentration to 550 and 970 ppm led to a decrease in cumulative groundwater recharge for most scenarios. For the final study, 95% confidence interval (CI) results from stochastic climate change simulations indicate that streamflow (3% for the upper CI limit, 9.5% for the lower CI limit) and sediment runoff (20% for the upper CI limit, 26% for the lower CI limit) in the Sacramento River watershed is more likely to decrease under climate changes compared to present-day, while the increase and decrease for nitrate runoff was found to be equal (13% for the upper CI limit, 13% for the lower CI limit). For the San Joaquin River watershed, streamflow slightly decreased under climate change (27% for the upper CI limit, 28% for the lower CI limit), while sediment (73% for the upper CI limit, 49% for the lower CI limit) and nitrate (28% for the upper CI limit, 26% for the lower CI limit) increased compared to present-day climate. Comparisons of watershed sensitivities indicate that San Joaquin River watershed is more sensitive to climate changes than the Sacramento River watershed largely due to differences in land use and soil properties. This research improves the understanding between climate change and hydrology and agricultural pollutant runoff within the Central Valley of California. Theses climate change analyses may be used by water resource managers to evaluate the potential effects of climate change.

The effects of climate change and socioeconomic deprivation on mortality in Korea

최민서 강원대학교 대학원 2024 국내박사

Objective: This dissertation examines the impacts of climate change and socioeconomic deprivation on mortality rates in Korea from 2010 to 2019, with a specific focus on understanding the association of health inequalities. Methods: The study investigates all-cause deaths reported in Korea during the specified period, utilizing data from the Microdata Integrated Service (MDIS) for mortality and socioeconomic information from the Korean Statistical Information Service (KOSIS). Meteorological and air pollution data are sourced from the Weather Data Open Portal provided by the Korea Meteorological Administration. Statistical analyses, employing SAS 9.4 and R 4.3.2, encompass various methodologies such as mean calculation, percentage determination, independent t-test, correlation analysis, principal component analysis, and multilevel analysis. Multilevel analysis is conducted through four models to explore the impact of diverse environmental factors. This includes 14 climate variables and 5 air pollution variables. Additionally, a socioeconomic factor is derived from an initial set of 14 socioeconomic variables after principal component analysis. The study investigates the combined effect of these factors concerning their influence on all-cause mortality. The null model is implemented as a random effect. In Model 1, five individual variables are considered, while Model 2 incorporates area-level variables, consisting of 14 meteorological variables, 5 air pollution variables, and 1 socioeconomic factor. Notably, Model 3 includes all variables and reveals a significant effect on mortality in Korea. Results: In the multilevel analysis of all-cause mortality at Time 1, Model 3 revealed that the relative risk (RR) for average temperature was 0.83 (95% CI: 0.63, 1.08), and average precipitation had an RR of 1.11 (95% CI: 0.90, 1.37). Notably, individual, and socioeconomic factors exhibited significant associations with mortality across all models at both Time 1 and Time 2. Specifically, during Time 1 in Model 3, the risks associated with socioeconomic factors (SEFs) were as follows: SEF3 with RR 1.40 (95% CI: 1.19, 1.65), SEF4 with RR 3.11 (95% CI: 2.64, 3.68), and SEF5 with RR 2.66 (95% CI: 0.53, 13.3). In Time 2, Model 3 indicated the following SEF risks: SEF2 with an RR of 1.22 (0.87, 1.71), SEF3 with RR 1.19 (0.96, 1.49), SEF4 with RR 1.71 (1.36, 2.14), and SEF5 with RR 4.95 (95% CI: 3.95, 6.19). Additionally, the multilevel analysis of cancer mortality at Time 1 revealed relative risks associated with cloud cover (MCL) and total sunshine hours (TSH), even though the results were not statistically significant. Specifically, the risks were as follows: MCL with RR 1.90 (95% CI: 0.85, 4.25), TSH2 with RR 1.14 (95% CI: 0.92, 1.41), TSH3 with RR 0.99 (95% CI: 0.72, 1.35), and TSH4 with RR 1.22 (95% CI: 0.87, 1.71). Conclusion: While the impact of climate change on mortality was not found to surpass that of individual and socio-economic factors, our study did affirm that changes in cloud cover and total hours of sunlight, attributed to climate change, indeed influenced mortality rates. This underscores the importance of ongoing research to delve deeper into these environmental variables and develop models that can accurately identify their effects. Furthermore, our findings highlight an exacerbation of health inequality in the context of cancer, driven by socioeconomic and personal factors. Addressing this issue requires a proactive approach through policy interventions to establish health equity. Continued efforts in this direction are crucial to mitigate the impact of these factors and ensure a more equitable distribution of health outcomes. □ keywords Climate change, Mortality, Socioeconomic factor, Deprivation, Multilevel analysis

(The) Study on the change of perceptions of climate change and extreme weather events : Using topic model

Lee, Kangmyeon Sungkyunkwan University 2024 국내박사

In this research, the author delves into the public's perception of Climate Change, a critical and ongoing threat to human existence. Prior investigations into this subject were constrained by limited survey-based data. To expand this understanding, the study utilized extensive datasets, including 198,717 news articles (sourced from LexisNexis), 61,370 social media posts (from Reddit), and 3,859 academic paper abstracts (acquired from Web of Science) related to Climate Change, spanning from 2018 to 2022. The analysis employed methods such as Dirichlet Multinomial Regression (DMR) for Topic Modeling and Sentiment Analysis to explore the discourse surrounding Climate Change. These methods were chosen for their efficacy in handling large datasets and their ability to provide insights into public discourse. Additionally, the study incorporated objective metrics like coherence scores and perplexity to enhance the reliability of the Topic Modeling process. The findings align with the theoretical frameworks of Conspiracy Theory and the Social Amplification of Risk Framework (SARF), illustrating how Climate Change narratives disseminated through public news media can significantly influence personal feelings of anxiety and fear on social media platforms.

Estimation of NPP change based on Convolutional Neural Network (CNN) classification considering climate and soil factors : in case of Korean peninsula and China from 1979 to 2013

朴東範 Graduate School, Korea University 2019 국내박사

Carbon stocks in terrestrial ecosystems are heavily influenced by climate change. Deforestation and farmland destruction with climate change (droughts, temperature rises) abates terrestrial ecosystem carbon storage and increases global warming. Therefore, in this study, we estimate the NPP of terrestrial ecosystem to understand the effect of meteorological factors on carbon stocks. As a result of using the computer learning model CNN to estimate the NPP of the site (China and the Korean peninsula), the climate-based model is more efficient than the vegetation-based model. The NPP of the Korean Peninsula, which was estimated from 2000 to 2004 by CNN model, showed a similar pattern to the NPP values provided by MODIS, and the estimated NPP from 2006 to 2010 showed a similar pattern to those estimated by VISIT model. For 35 years, average NPP value in China is 380 g · C / m2 / year, North Korea is 340 g · C / m2 / year, and South Korea is 550 g · C / m2 / year. These indicates a slight increase in China and North Korea and clear increasing trend in South Korea. To compare the vegetation NPP due to the impact of climate change, this study adopted 6 climatic zone classification which provided by Chinese Academy of Science (CAS). Three countries had subtropical zone in common among 6 classifications. In this climatic zone, China's vegetation has shown a declining trend in the zone, North Korea has little change, and South Korea is on the rise. However, variation of NPP were huge because NPP were estimated based on climatic data. Therefore, this study adopted moving average method to minimize climatic variation, and the variation from climate change were decreased less than 100 g · C / m2 / year. This results can represent more accurate time-series NPP change, but extreme weather condition or short term impact were neglected. China's average cumulative NPP from 1979 to 2013 is 4.8 Pg · C, and the average cumulative NPP from 1988 to 2013 constructed using the moving average method is 4.0 Pg · C, indicating no significant difference from other process-based models. The results of this study are similar to those of other studies, and it can be confirmed that the CNN model can be used to construct NPP of land ecosystem. 육상생태계의 탄소저장량은 기후변화의 영향을 많이 받고 있다. 기후변화를 (가뭄, 기온 상승) 동반한 산림벌채, 농경지파손 등은 육상생태계의 탄소 저장을 방해하며, 지구온난화를 가중시키고 있다. 따라서, 본 연구에서 육상생태계 NPP를 산정하여 기상인자의 영향이 탄소저장량에 미치는 영향을 파악하고자 하였다. 컴퓨터학습모형 CNN를 이용하여 대상지 (중국과 한반도) NPP를 산정한 결과, 식생인자기반보다 기상인자기반 모델이 효율이 높은 것을 확인할 수 있었다. CNN 모형으로 구축된 한반도의 NPP의 총 양은 2000 - 2004년까지 MODIS에서 구축된 NPP와 유사한 패턴을 가지고, 2006 - 2010년까지는 VISIT모형과 유사한 패턴을 나타내고 있었다. 35년간 중국의 NPP는 평균 380 g · C / m2 / year이고, 북한은 평균 340 g · C / m2 / year, 남한은 평균 550 g · C / m2 / year을 나타내고 있는데, 중국과 북한은 미미하게 증가하는 추세를 보여주고 남한은 선명하게 증가하는 추세를 보여주고 있다. 기후변화의 영향으로 인한 식생의 NPP를 비교하기 위해, 3개국을 중국의 Chinese Academy of Science (CAS) 에서 제공하는 기후대 분류기준에 따라, 6가지 기후대로 분류를 하였더니, 공동으로 식생이 subtropical zone에 분포하고 있고, 중국의 식생은 이 zone에서 NPP가 감소하는 추세를 보여주고, 북한은 거의 변화가 없고, 남한은 증가하는 추세를 보여주고 있었다. 다만, 본 연구는 기후인자를 기반으로 NPP를 구축하였기 때문에, 기후변화로 인한 NPP값의 변동성이 크게 나타나고 있는 것을 확인할 수 있다. 따라서, Moving average 방법을 이용하여, 1988 – 2013 년까지 재분석을 진행해 본 결과 기후변화로 인한 변동성의 차이를 100 g · C / m2 / year이하로 감소되었다. 다만, 이런 결과는 시계열적으로 보다 정확한 식생의 NPP의 변화를 파악할 수 있지만, 단기간의 기후변화로 인해 생긴 식생에 대한 영향을 잘 반영할 수 없었다. 1979 - 2013년간 중국의 평균 누적NPP의 총 양은 4.8 Pg · C이고, Moving average 방법을 사용하여 구축된 1988 - 2013년간 평균 누적NPP의 총 양은 4.0 Pg로 나태내고 있는데, 이는 타 NPP 구축 모형의 결과와 큰 차이가 없는 것으로 나타내고 있었다. 이상의 연구결과는 타 연구에서의 결론과 유사한 결과를 나타내고 있어, 기상인자를 기반으로 한 CNN모형으로 육상생태계의 NPP구축에 이용가능하다는 것을 확인할 수 있음. 陆地生态系统的固碳含量受气候变化的影响很大。例如,基于气候变化(干旱,气温上升)的森林砍伐,农业用地退化等现象直接减少陆地生态系统的固碳量,并且加剧了全球变暖。因此,本研究的目的主要是通过估算陆地生态系统的NPP来了解气候因子对碳储量的影响。 本文通过使用计算机学习模型CNN(卷积神经网络)来估测研究区(中国,韩半岛)的NPP,得到利用气象因子得出的模型更为有效。利用CNN模型估测的韩半岛NPP值在2000 – 2004年为止跟MODIS得出的NPP的时空间趋势相近,2006 – 2010年为止跟VISIT模型得出的结果相近。 近35年间中国的NPP平均值处于380 g · C / m2 / year,北朝鲜的NPP平均值处于340 g · C / m2 / year,南朝鲜则是平均550 g · C / m2 / year。其中,中国和北朝鲜是虽然递增但几乎不变的趋势,而南朝鲜则时明显增加趋势。为了比较因气候变化的影响导致的植被的NPP,利用中科院(Chinese Academy of Science)提供的气候带分类基准,把研究区分类成6个气候带。其中三个国家都共同存在亚热带气候区,中国植被的NPP呈现减少趋势,北朝鲜则几乎没有变化,南朝鲜显现出上升趋势。但是,本文是利用气象因子来估测NPP值,所以所呈现出的NPP值波动性非常大。因此利用Moving average方法,重新估测1988 – 2013年植被的NPP值,结果发现把NPP的波动性减少到100 g · C / m2 / year以内。这种结果虽然能较好的分析时间序列上的植被的NPP变化,但是不能好好反映出当时的气候变化对植被的影响。1979 – 2013年中国植被NPP的年平均累计总量为4.8 Pg · C,而利用Moving average方法得出的1988 – 2013年的结果为4.0 Pg · C,这种结果研究结论更有准确性。 因此,通过本研究得到利用基于气象因子的CNN模型,也可以准确地估测陆地生态系统的NPP值。

Essays on the Economics of Climate Change, Biofuel and Food Prices

Seguin, Charles University of California, Berkeley 2012 해외박사(DDOD)

Climate change is likely to be the most important global pollution problem that humanity has had to face so far. In this dissertation, I tackle issues directly and indirectly related to climate change, bringing my modest contribution to the body of human creativity trying to deal with climate change. First, I look at the impact of non-convex feedbacks on the optimal climate policy. Second, I try to derive the optimal biofuel policy acknowledging the potential negative impacts that biofuel production might have on food supply. Finally, I test empirically for the presence of loss aversion in food purchases, which might play a role in the consumer response to food price changes brought about by biofuel production. Non-convexities in feedback processes are increasingly found to be important in the climate system. To evaluate their impact on the optimal greenhouse gas (GHG) abate- ment policy, I introduce non-convex feedbacks in a stochastic pollution control model. I numerically calibrate the model to represent the mitigation of greenhouse gas (GHG) emissions contributing to global climate change. This approach makes two contributions to the literature. First, it develops a framework to tackle stochastic non-convex pollu- tion management problems. Second, it applies this framework to the problem of climate change. This approach is in contrast to most of the economic literature on climate change that focuses either on linear feedbacks or environmental thresholds. I find that non-convex feedbacks lead to a decision threshold in the optimal mitigation policy, and I characterize how this threshold depends on feedback parameters and stochasticity. There is great hope that biofuel can help reduce greenhouse gas emissions from fossil fuel. However, there are some concerns that biofuel would increase food prices. In an optimal control model, a co-author and I look at the optimal biofuel production when it competes for land with food production. In addition oil is not exhaustible and output is subject to climate change induced damages. We find that the competitive outcome does not necessarily yield an underproduction of biofuels, but when it does, second best policies like subsidies and mandates can improve welfare. In marketing, there has been extensive empirical research to ascertain whether there is evidence of loss aversion as predicted by several reference price preference theories. Most of that literature finds that there is indeed evidence of loss aversion for many different goods. I argue that it is possible that some of that evidence seemingly supporting loss aversion arises because price endogeneity is not properly taken into account. Using scanner data I study four product categories: bread, chicken, corn and tortilla chips, and pasta. Taking prices as exogenous, I find evidence of loss aversion for bread and corn and tortilla chips. However, when instrumenting prices, the "loss aversion evidence" disappears.

Effects of open-field experimental multiple climate change drivers (warming and precipitation manipulation) on soil microbial community, soil extracellular enzyme, and soil respiration

李冠霖 Graduate School, Korea University 2017 국내박사

생물지구화학적 물질 순환의 주요 조절 인자인 대기 온도와 강수량은 기후변화에 따라 크게 변화할 것으로 예상된다. 그리고 기후변화에 따른 대기 온도 및 강수량의 변화는 토양 내 양분의 무기화, 손실 및 흡수 과정과 CO2 배출 등에 영향을 미칠 것이다. 그런데 육상 생태계의 구조와 기능은 토양 내 미생물에 의하여 조절되므로, 기후변화에 대한 미생물의 반응과 이에 따른 피드백 작용을 이해하는 것은 매우 중요하다. 그러나 기후변화가 토양 미생물에 미치는 영향은 여전히 불분명한 부분으로 남아 있다. 본 연구의 목적은 기후변화(대기 온도 및 강수량의 변화)가 토양 미생물 군집, 효소 활성도, 토양 호흡에 미치는 영향과, 이러한 미생물 변화가 기후변화에 어떠한 피드백 작용을 할 것인지를 밝히는 것이다. 이를 위하여 2013년 4월, 고려대학교 캠퍼스에 2년생 소나무 묘목을 식재한 실외 실험적 온난화(+3 °C) 및 강수량 조절(-30%, +30%) 실험지를 조성하고 연구를 진행하였다. 첫 번째로 기후변화가 토양 미생물 군집의 구조와 조성에 미치는 영향을 분석하였다. 이를 위하여 2014년 10월부터 2015년 12월까지 2개월 주기로 매월 세 번째 주에 토양(0–15 cm 깊이)을 채취하고, High-throughput analysis와 BIOLOG EcoPlate를 활용하여 토양의 미생물 군집의 구조와 조성을 조사하였다. 조사 결과, 강수량을 변화시키지 않은 조건에서, 온난화 처리는 비온난화 처리에 비하여 미생물 바이오매스 탄소와 질소를 각각 3.7%와 19.9% 증가시켰다. 그러나 강수량을 감소시킨 조건에서는, 온난화에 의한 미생물 바이오매스의 변화는 나타나지 않았다. 한편 온난화 및 강수량 조절을 적용한 처리들은 온난화와 강수량 조절을 모두 적용하지 않은 처리에 비하여 세균과 곰팡이의 군집 풍부도(community richness)를 각각 -14.3%–-2.1%와 -26.0%–17.4%만큼 변화시켰다. 이들 처리는 세균의 군집 다양성(community diversity)을 -3.5%–-0.9%만큼 변화시켰으나, 곰팡이의 군집 다양성을 -52.3%–0.5%만큼 변화시켰다(P < 0.01). 그런데 온난화가 미생물 군집 조성에 미치는 영향은 강수량 조절 처리에 따라, 그리고 세균과 곰팡이 간에 상이하였다. 특히 온난화 및 강수량 조절 처리는 실험지에서 우점하는 세균 그룹인 Proteobacteria의 풍부도(abundance)를 유의하게 변화시켰다(P < 0.05). 이러한 토양 미생물 군집의 변화는 온난화 및 강수량 조절 처리에 따른 토양 조건(토양 온도, 수분, 양분 유효도 등) 변화에 의한 것으로 추정된다. 두 번째로 기후변화가 탄소, 질소 및 인 순환에 관여하는 토양 효소(β-glucosidase, N-acetyl-glucosaminidase, Leucyl aminopeptidase, phosphatase)의 활성도에 미치는 영향을 분석하였다. 이를 위하여 2015년 4월부터 12월까지 2개월 주기로 매월 세 번째 주에 토양(0–15 cm 깊이)을 채취하였다. 측정 결과, 토양 효소의 활성도와 이들 간 비율(ecoenzymatic ratios)은 온난화 및 강수량 조절 처리보다는 월 변이의 영향을 크게 받는 것으로 나타났다. 즉, 정도의 차이는 있으나 모든 토양 효소의 활성도는 12월에 가장 높았다. 한편 온난화 처리는 효소의 활성도를 증가 또는 감소시켰으며, 처리의 영향은 일관되지 않고 조사구별로 상이하였다. 이는 기후변화가 토양 조건과 미생물 군집을 변화시킴으로써 효소의 활성도에 영향을 미치며, 이러한 기후변화의 영향이 토양 수분 등의 조건에 따라 차이를 보일 수 있다는 것을 의미한다. 마지막으로 기후변화가 토양 호흡에 미치는 영향을 분석하였다. 이를 위하여 2015년 6월 19일, 8월 19일, 10월 20일 오전에 비분산형 적외선 CO2 센서와 폴리아크릴 재질 챔버로 토양 호흡을 측정하였다. 강수량을 증가시킨 조건에서, 온난화 처리는 비온난화 처리에 비하여 토양 호흡을 54.6%–59.7%만큼 증가시켰다(P < 0.05). 그러나 이와 대조적으로 강수량을 감소시킨 조건에서, 온난화 처리는 비온난화 처리에 비하여 토양 호흡을 19.4%만큼 감소시켰다. 그리고 온난화에 따른 토양 호흡의 변화는 토양 수분 조건별로 상이하였다. 따라서 온난화는 토양 호흡을 유의하게 증가시키나, 수분이 부족한 조건에서는 온도 증가에 의한 토양 건조 현상이 온난화에 따른 토양 호흡 변화를 제한할 수 있을 것으로 판단된다. 이와 같은 결과들을 종합하면, 대기 온도의 증가와 강수량의 변화는 토양 환경을 변화시킴으로써 토양 미생물 군집, 효소 활성도, 토양 호흡 등에 영향을 미치는 것으로 나타났다. 그런데 이러한 기후변화가 토양 미생물 군집, 효소 활성도, 토양 호흡에 미치는 영향은 일관되지 않고 측정 월 등에 따른 변이를 보였다. 특히 수분이 부족할 경우, 토양 수분 조건이 기후변화에 대한 토양 미생물 군집, 효소 활성도, 토양 호흡의 반응을 제한하였다. 본 연구의 결과는 기후변화가 토양 미생물에 미치는 영향이 주위 환경에 따른 차이(context-dependency)를 보이며, 이를 기후변화에 따른 변화를 모의하는데 고려해야 함을 의미한다. 소나무가 한국의 침엽수림과 혼효림에서 가장 우점하는 수종임을 고려하면, 소나무를 식재한 조건에서 토양 미생물 반응을 모의한 본 연구의 결과는 미래 기후변화 하에서 소나무림의 변화를 예측하는 데에 기여할 수 있을 것으로 기대된다. Atmospheric temperature and natural precipitation regimes are major environmental factors regulating important biogeochemical cycles in terrestrial ecosystems and are expected to be altered by climate change. Therefore, soil nutrient mineralization, transformation, loss, and uptake by plants, as well as gas (e.g., CO2 and N2) efflux from soil are likely to change as well. Despite the likelihood that the terrestrial ecosystem process and functions mediated and catalyzed by soil microbes will react to climate change, their response and feedback has yet to be clearly understood. The present study aims to determine the effects of climate change drivers (i.e., atmospheric warming and precipitation manipulation) and their interaction on soil microbial community, soil extracellular enzyme, and soil respiration (RS), and to understand their feedbacks to this process. This will be accomplished by conducting a multiple climate change drivers experiment involving atmospheric warming by 3 °C and reduced or elevated precipitation manipulations by 30%. The site was established at Korea University in April, 2013 and used to study the effects of open-field experimental atmospheric warming and precipitation manipulation on two-year-old Pinus densiflora seedlings. In the first study, soil microbial community structure and composition were analyzed to investigate how multifactor climate change drivers affected soil microbial communities. Surface soil (0 - 15 cm) was collected during the third week of October and December in 2014, and April, June, August, October, and December in 2015. High-throughput analysis and BIOLOG EcoPlate assays were used to detected the soil microbial community structure and composition. The results showed that warming slightly increased microbial biomass carbon (C) and nitrogen (N) by an average of 3.7% and 19.9%, respectively, in precipitation control plots. However, the enhancement of microbial biomass as a function of warming was not observed in the reduced precipitation plots. Compared with the ambient treatment (unwarmed and precipitation control treatment), all other treatments slightly altered bacterial and fungal community richness, ranging from -14.3% to -2.1% and -26.0% to 17.4%, respectively. However, all other treatments altered bacterial community diversity, ranging from -3.5% to - 0.9%, and significantly altered fungal community diversity ranging from -52.3% to 0.5% (P < 0.01). Warming distinguished bacterial and fungal community composition under different precipitation manipulation plots. In particular, the experimental treatments induced significant differences in Proteobacteria abundance (P < 0.05), which was the dominant group in the bacterial community. The alterations in the soil microbial community may result from a direct and/or indirect treatment effect on soil conditions (e.g., soil temperature, moisture, and quantity and quality of available nutrients). In the second study, four soil potential extracellular enzyme activities which likely impact C, N, and phosphorus (P) dynamics were measured to investigate the effects of climate change drivers and their interaction on soil extracellular enzyme. Surface soil (0 - 15 cm) was collected during the third week of April, June, August, October, and December in 2015. The results showed that four soil potential extracellular enzyme activities and three ecoenzymatic ratios were more affected by the month than by the direct and/or interaction effects of climate change drivers. The highest values of all potential extracellular enzyme activities were observed in December at various levels. Both positive and negative warming effects on soil extracellular enzymes were observed, and the responses of enzymes to treatments were dissimilarity among plots. The results indicated that climate change drivers altered soil potential extracellular enzyme activities through alterations in soil conditions, and soil microbial biomass and community structure. In particular, soil moisture could regulate the responses of soil extracellular enzymes to the climate change effect. In the third study, RS was examined to investigate the effects of climate change drivers and their interaction on the RS of P. densiflora seedlings. RS were measured on the mornings of June 19th, August 19th, and October 20th, 2015 using a portable diffusion-type, non-dispersive infrared (NDIR) CO2 sensor and a polyacrylics chamber. The results showed that warming induced significant changes in RS (P < 0.05), enhancing RS by an average of 54.6% and 59.7% in the control and elevated precipitation plots, respectively; however, warming reduced RS by 19.4% in plots subjected to lower rates of precipitation, indicating a link between warming and moisture. On the basis of these findings, warming is posited to significantly influence RS, but the warming effect on RS may be weakened by warming-induced soil drying in water-limited environments. These results indicate that climate change drivers would alter soil microbial communities, soil extracellular enzymes, and RS directly and indirectly through changes in soil conditions. The responses of soil microbial communities, soil extracellular enzyme activities, and RS to climate change drivers showed strong but dissimilarity monthly variations. In particular, soil moisture regulated the responses of soil microbial communities, soil extracellular enzyme activities, and RS to climate change in water-limited environments. These results indicate that the responses of soil ecosystem to climate change are context-dependent and indicate the importance of taking into account the context-dependency of climate change effects on soil microbial communities and functions. Given that P. densiflora is one of the representative temperate coniferous trees in the naturally occurring coniferous and mixed forests of South Korea, the results of this research are useful for predicting microbial responses in P. densiflora forest ecosystems across South Korea in the face of future climate change.

Assessment of Household Water Supply Security as Climate Change Adaptive Capacity: : a case study of Guimaras Island, Philippines

Fara-On, Neil Paul 한림대학교 글로벌협력대학원 2022 국내석사

The impacts of climate change are primarily manifested through water, brought about by changes in the frequency and intensity of extreme weather events. The Intergovernmental Panel on Climate Change (IPCC) highlighted the adve rse effects of climate change on water security as a result of extreme variations in climate parameters. The Philippines has been experiencing various climate hazards induced by increasing temperatures, rainfall variability, stronger typhoons, and sea leve l rise. Climate change and natural hazards remain challenging in ensuring a safe water supply. Securing the water sector is imperative for any adaptive response to climate change. This study adopted the structure of the water security assessment framework developed by M.S. Babel in 2020. This study focused on household water supply security (HWSS) as the foundation of water security. It is essential to eradicate poverty, which is the fundamental responsibility of a government entity. The researcher selected and categorized indicators and variables based on the normative criteria of the human rights to safe water and the Philippine policies on water supply. The framework was applied to the five municipalities and the island province of Guimaras, Philippines. The study found that out of the 50,906 households, almost all have available when-needed and improved source water supply services. Nearly half have inside their premises water supply services. However, only one-third have free from Escherichia coli water supply services. The DILG-administered water supply projects have supplied safe water to almost half of the households. The island province of Guimaras has a “good” level of Household Water Supply Security. Only the municipality of Buenavista has reached the “very good” level of household water supply security. In contrast, the rest of the municipalities have only a “good” level. The developed framework is based on the United Nations' working definition to enhance the operationalization of household water supply security at the local rural, or provincial level. The approach and findings of the study can effectively monitor the household water security situation and design policy measures accordingly to improve water management in the local government units. 기후 변화의 영향은 주로 극단적인 기후 사건의 빈도와 강도의 변화에 의해 야기되는 물을 통해 나타난다. 기후 변화에 관한 정부간 패널(IPCC)은 기후 변수의 극단적인 변화의 결과로 인한 기후 변화가 물 안보에 미치는 부정적인 영향을 강조했다. 필리핀은 기온 상승, 강우량 변동성, 태풍 강화, 해수면 상승으로 인한 다양한 기후 위험을 경험하고 있다. 기후 변화와 자연 재해는 안전한 물 공급을 보장하는 데 있어 여전히 어려운 과제이다. 물 부문의 확보는 기후 변화에 대한 모든 적응적 대응을 위해 필수적이다. 본 연구는 2020년 M.S. Babel이 개발한 물안보 평가 프레임워크의 구조를 채택하였다. 본 연구는 물안보의 기초로서 가정용 급수 보장(HWSS)에 초점을 맞추었다. 정부 기관의 근본적인 책임인 빈곤을 근절하는 것은 필수적이다. 연구자는 안전한 물에 대한 인권의 규범적 기준과 필리핀의 물 공급 정책에 대한 지표와 변수의 선정과 분류를 하였다. 이 프레임워크는 5개 지방 자치체와 필리핀 기마라스 섬주에 적용되었다. 이 연구는 50,906가구 중 거의 모든 가구가 필요할 때 이용할 수 있고 개선된 수원 급수 서비스를 가지고 있다는 것을 발견했다. 거의 절반이 그들의 구내에 상수도 서비스를 가지고 있다. 그러나 대장균 급수 서비스가 무료인 곳은 3분의 1에 불과하다. DILG가 관리하는 상수도 사업은 거의 절반의 가정에 안전한 물을 공급했다. 기마라스 섬 지역은 "좋은" 수준의 가정용수 공급 보안을 갖추고 있다. 부에나비스타 시만이 가정용수 공급이 "매우 양호한" 수준에 도달했고, 나머지 시는 "좋은" 수준에 불과하다. 개발된 프레임워크는 지역 농촌 수준 또는 지방 규모에서 가정용 급수 보안의 운영화 강화를 촉진하기 위한 유엔의 작업 정의에 기초한다. 본 연구의 접근방법과 결과는 효과적으로 가정의 물안보 상황을 모니터링하고 그에 따른 정책방안을 설계하여 지방자치단체 단위의 물관리를 개선할 수 있다.