Stylized sociohydrological models have mainly used social memory aspects such as community awareness or sensitivity to connect hydrologic change and social response. However, social memory alone does not satisfactorily capture the details of how human behavior is translated into collective action for water resources governance. Nor is it the only social mechanism by which the two‐way feedbacks of sociohydrology can be operationalized. This study contributes toward bridging of this gap by developing a sociohydrological model of a flood resilience that includes two additional components: (1) institutions for collective action, and (2) connections to an external economic system. Motivated by the case of community‐managed flood protection systems (polders) in coastal Bangladesh, we use the model to understand critical general features that affect long‐term resilience of human‐flood systems. Our findings suggest that occasional adversity can enhance long‐term resilience. Allowing some hydrological variability to enter into the polder can increase its adaptive capacity for resilience through the preservation of social norm for collective action. Further, there are potential trade‐offs associated with optimization of flood resistance through structural measures. By reducing sensitivity to floods, the system may become more fragile under the double impact of floods and economic change.

The Korean Social Life, Health, and Aging Project (KSHAP) is a population-based longitudinal study of health determinants among elderly Koreans. The target population of the KSHAP are people aged 60 years or older and their spouses living in a rural community of Korea. A complete enumeration survey was conducted in the first wave of the KSHAP on 94.7% (814 of 860) of the target population between December 2011 and July 2012. The KSHAP-Health Examination (KSHAP-HE) cohort consists of 698 people who completed additional health examinations at a public health center (n=533) or at their home (n=165). Face-to-face questionnaires were used to interview participants on their demographics, social network characteristics, medical history, health behaviors, cognitive function, and depression symptoms. Health center examinations included anthropometric measures, body impedance analysis, resting blood pressure measurement, radial artery tonometry, bone densitometry, the timed up-and-go test, and fasting blood analysis. However, only anthropometric measures, blood pressure measurement, and non-fasting blood analysis were available for home health examinations. Collaboration is encouraged and access to the KSHAP baseline data will be available via the website of the Korean Social Science Data Archive (http://www.kossda.or.kr).

A community capacity to cope with flood hazards, or community flood resilience, emerges from the interplay of hydrological and social processes. This interplay can be significantly influenced by the flood control strategy adopted by a society, i.e., how a society sets its desired flood protection level and strives to achieve this goal. And this interplay can be further complicated by rising land‐sea level differences, seasonal water level fluctuations, and economic change. But not much research has been done on how various forms of flood control strategies affect human‐flood interactions under these disturbances and therefore flood resilience in the long run. The current study is an effort to address these issues by developing a conceptual model of human‐flood interaction mediated by flood control strategies. Our model extends the existing model of Yu et al. (2017), who investigated the flood resilience of a community‐based flood protection system in coastal Bangladesh. The major extensions made in this study are inclusions of various forms of flood control strategies (both adaptive and nonadaptive ones), the challenge of rising land‐sea level differences, and various high tide level scenarios generated from modifying the statistical variances and averages. Our results show that adaptive forms of flood control strategies tend to outperform nonadaptive ones for maintaining the model community's flood protection system. Adaptive strategies that dynamically adjust target flood protection levels through close monitoring of flood damages and social memories of flood risk can help the model community deal with various disturbances.

Background: Since the mid-20th century, the ways in which social networks and older adults' health are related have been widely studied. However, few studies investigate the relationship between self-rated health and position in a complete social network of one entire Korean rural village. This study highlights use of a complete network in health studies. Methods: Using the Korean Social Life and Health Project, the population-based data of adults aged 60 or older and their spouses in one myeon in Ganghwa island (Ganghwa-gun, Incheon, Korea), Incheon, Korea (with a 95% response rate), this study built a 1,012×1,012 complete social network matrix of the village. The data were collected from 2011 to 2012, and 731 older adults were analyzed. The ordered logistic models to predict self-rated health allowed us to examine social factors from socio-demographic to individual community activities, ego-centered network characteristics, and positions in a complete network. Results: From the network data, 5 network components were identified. Even after controlling for all other factors, if a respondent belonged to a segregated component, the probability that he or she reported good health dropped substantially. Additionally, high in-degree centrality was connected to greater self-rated health. Conclusion: This finding highlights the importance of social position not only from the respondents' point of view but also from the entire village's perspective. Even if a respondent maintained a large social network, when all of those social ties belonged to a segregated group in the village, the respondent's health suffered from this segregation.

Abstract. There are indications that the reference climatology underlying meteorological drought has shown non-stationarity at seasonal, decadal, and centennial time scales, impacting the interpretation of normalized drought indices and potentially producing serious ecological, economic, and social consequences. Analyzing these trends in the meteorological drought climatology beyond the 100-year observation period contributes to a better understanding of the non-stationary changes, ultimately determining whether they are within the range of natural variability or outside this range. To accomplish this, our study introduces a novel approach to incorporate unevenly scaled tree-ring proxy data (NASPA) with instrumental precipitation datasets by first temporal downscaling the proxy data to produce a regular time series, and then modeling climate non-stationarity while simultaneously correcting model induced bias. This new modeling approach was applied to 14 sites across the continental United States using the 3-month Standardized Precipitation Index (SPI) as a basis. Findings showed locations which have experienced recent rapid shifts towards drier or wetter conditions during the instrumental period compared to the past 1000 years, with drying trends generally in the west and wetting trends in the east. This study also found that seasonal shifts have occurred in some regions recently, with seasonality changes most notable for southern gauges. We expect that our new approach provides a foundation for incorporating various datasets to examine non-stationary variability in long-term precipitation climatology and to confirm the spatial patterns noted here in greater detail.