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Abstract
Communicating the threat of severe winter weather is not simply a matter of the number of inches of snow or degrees of cold; it also considers the potential impacts of the storm. The winter storm severity index (WSSI) is a graphical product from the National Weather Service that presents anticipated impacts from forecast winter weather for a range of winter conditions. To assess the utility of the WSSI and how an impact-based winter weather forecast product is interpreted and used to inform decision-making, a mixed-methods social science study was conducted by the Nurture Nature Center in coordination with the Weather Prediction Center. Through focus groups and surveys, testing in the Hydrometeorological Testbed, and iterations on design and category descriptions, several themes emerged about how professional stakeholders understand, interpret, and use this product for communicating about impending winter weather. There is perceived utility in the WSSI for situational awareness and as part of a package of other information to inform decision-making. However, there is variability in interpretations of impacts, resulting from differences in geography, community readiness, and experience, among other factors, which creates complications in communicating the forecast. Furthermore, many users seek quantities related to winter weather, suggesting that education about what impact-based products include and what data are shown is necessary. Understanding the factors that influence perspectives on impact levels and the variable needs for winter weather information across regions improves forecasters’ abilities to effectively communicate and provide critical information that helps end users prepare for severe winter weather.
Significance Statement
Effectively communicating severe winter weather is critical to supporting communities in being prepared for and mitigating weather-related losses and damages. The winter storm severity index focuses on impacts to provide awareness of impending winter weather, information that is useful but not always interpreted consistently, requiring an understanding of factors influencing perspectives on impact levels and user education.
Abstract
Communicating the threat of severe winter weather is not simply a matter of the number of inches of snow or degrees of cold; it also considers the potential impacts of the storm. The winter storm severity index (WSSI) is a graphical product from the National Weather Service that presents anticipated impacts from forecast winter weather for a range of winter conditions. To assess the utility of the WSSI and how an impact-based winter weather forecast product is interpreted and used to inform decision-making, a mixed-methods social science study was conducted by the Nurture Nature Center in coordination with the Weather Prediction Center. Through focus groups and surveys, testing in the Hydrometeorological Testbed, and iterations on design and category descriptions, several themes emerged about how professional stakeholders understand, interpret, and use this product for communicating about impending winter weather. There is perceived utility in the WSSI for situational awareness and as part of a package of other information to inform decision-making. However, there is variability in interpretations of impacts, resulting from differences in geography, community readiness, and experience, among other factors, which creates complications in communicating the forecast. Furthermore, many users seek quantities related to winter weather, suggesting that education about what impact-based products include and what data are shown is necessary. Understanding the factors that influence perspectives on impact levels and the variable needs for winter weather information across regions improves forecasters’ abilities to effectively communicate and provide critical information that helps end users prepare for severe winter weather.
Significance Statement
Effectively communicating severe winter weather is critical to supporting communities in being prepared for and mitigating weather-related losses and damages. The winter storm severity index focuses on impacts to provide awareness of impending winter weather, information that is useful but not always interpreted consistently, requiring an understanding of factors influencing perspectives on impact levels and user education.
Abstract
Social science studies of weather and natural hazards have examined in depth the sources of information individuals use in response to a disaster. This research has primarily focused on information sources in isolation and as they relate to severe weather. Thus, less research has examined how individuals use information acquisition strategies during routine times. This paper addresses this limitation by examining patterns of routine weather information source usage. Using three unique survey datasets and latent class analysis, we find that weather information source usage can be summarized by a limited number of coherent classes. Importantly, our results suggest that weather information types, or classes, are generally consistent across datasets and samples. We also find demographic determinants, particularly age, help to explain class membership; older respondents were more likely to belong to classes that are less reliant on technology-based information sources. Income and education also were related to more complex or comprehensive information use strategies. Results suggest that the prevalent view of single-source information usage in previous research may not be adequate for understanding how individuals access information, in both routine and extreme contexts.
Abstract
Social science studies of weather and natural hazards have examined in depth the sources of information individuals use in response to a disaster. This research has primarily focused on information sources in isolation and as they relate to severe weather. Thus, less research has examined how individuals use information acquisition strategies during routine times. This paper addresses this limitation by examining patterns of routine weather information source usage. Using three unique survey datasets and latent class analysis, we find that weather information source usage can be summarized by a limited number of coherent classes. Importantly, our results suggest that weather information types, or classes, are generally consistent across datasets and samples. We also find demographic determinants, particularly age, help to explain class membership; older respondents were more likely to belong to classes that are less reliant on technology-based information sources. Income and education also were related to more complex or comprehensive information use strategies. Results suggest that the prevalent view of single-source information usage in previous research may not be adequate for understanding how individuals access information, in both routine and extreme contexts.
Abstract
When forecasts for a major weather event begin days in advance, updates may be more accurate but inconsistent with the original forecast. Evidence suggests that resulting inconsistency may reduce user trust. However, adding an uncertainty estimate to the forecast may attenuate any loss of trust due to forecast inconsistency, as has been shown with forecast inaccuracy. To evaluate this hypothesis, this experiment tested the impact on trust of adding probabilistic snow-accumulation forecasts to single-value forecasts in a series of original and revised forecast pairs (based on historical records) that varied in both consistency and accuracy. Participants rated their trust in the forecasts and used them to make school-closure decisions. One-half of the participants received single-value forecasts, and one-half also received the probability of 6 in. or more (decision threshold in the assigned task). As with previous research, forecast inaccuracy was detrimental to trust, although probabilistic forecasts attenuated the effect. Moreover, the inclusion of probabilistic forecasts allowed participants to make economically better decisions. Surprisingly, in this study inconsistency increased rather than decreased trust, perhaps because it alerted participants to uncertainty and led them to make more cautious decisions. Furthermore, the positive effect of inconsistency on trust was enhanced by the inclusion of probabilistic forecast. This work has important implications for practical settings, suggesting that both probabilistic forecasts and forecast inconsistency provide useful information to decision-makers. Therefore, members of the public may benefit from well-calibrated uncertainty estimates and newer, more reliable information.
Significance Statement
The purpose of this study was to clarify how explicit uncertainty information and forecast inconsistency impact trust and decision-making in the context of sequential forecasts from the same source. This is important because trust is critical for effective risk communication. In the absence of trust, people may not use available information and subsequently may put themselves and others at greater-than necessary risk. Our results suggest that updating forecasts when newer, more reliable information is available and providing reliable uncertainty estimates can support user trust and decision-making.
Abstract
When forecasts for a major weather event begin days in advance, updates may be more accurate but inconsistent with the original forecast. Evidence suggests that resulting inconsistency may reduce user trust. However, adding an uncertainty estimate to the forecast may attenuate any loss of trust due to forecast inconsistency, as has been shown with forecast inaccuracy. To evaluate this hypothesis, this experiment tested the impact on trust of adding probabilistic snow-accumulation forecasts to single-value forecasts in a series of original and revised forecast pairs (based on historical records) that varied in both consistency and accuracy. Participants rated their trust in the forecasts and used them to make school-closure decisions. One-half of the participants received single-value forecasts, and one-half also received the probability of 6 in. or more (decision threshold in the assigned task). As with previous research, forecast inaccuracy was detrimental to trust, although probabilistic forecasts attenuated the effect. Moreover, the inclusion of probabilistic forecasts allowed participants to make economically better decisions. Surprisingly, in this study inconsistency increased rather than decreased trust, perhaps because it alerted participants to uncertainty and led them to make more cautious decisions. Furthermore, the positive effect of inconsistency on trust was enhanced by the inclusion of probabilistic forecast. This work has important implications for practical settings, suggesting that both probabilistic forecasts and forecast inconsistency provide useful information to decision-makers. Therefore, members of the public may benefit from well-calibrated uncertainty estimates and newer, more reliable information.
Significance Statement
The purpose of this study was to clarify how explicit uncertainty information and forecast inconsistency impact trust and decision-making in the context of sequential forecasts from the same source. This is important because trust is critical for effective risk communication. In the absence of trust, people may not use available information and subsequently may put themselves and others at greater-than necessary risk. Our results suggest that updating forecasts when newer, more reliable information is available and providing reliable uncertainty estimates can support user trust and decision-making.
Abstract
South Florida experiences some of the highest coastal hurricane vulnerability in the United States. Mobile home communities in south Florida are particularly vulnerable to hurricanes due to the weaker structural integrity of the home or land and a mix of structural and sociodemographic factors. A mixed-methods study was conducted to assess hurricane risk perceptions, experiences, and decision-making among permanent mobile home park (MHP) residents in Broward and Miami-Dade Counties. Return-by-mail surveys were distributed in July 2016 after several years of nominal hurricane activity in south Florida (and before Hurricane Matthew’s formation in September 2016), and focus groups were conducted at MHPs in May 2018, eight months after Hurricane Irma’s September 2017 landfall. Quantitative analysis of 44 in-person and 57 return-by-mail survey responses revealed that respondents tended to be older, retired, or unemployed and had modest levels of education, with many expressing forms of social- and structural-level hurricane risk before Hurricane Matthew. Qualitative analysis of six focus group discussions conducted after Hurricane Irma revealed that the constraints and vulnerabilities experienced by residents coalesced into several primary themes related to preparation, evacuation, assistance, stress and anxiety, tree concerns, and recovery. Participants specifically highlighted their concerns about tree hazards, damages, and maintenance issues arising before, during, and after hurricanes in MHPs. These results build on the scholarship on hurricane risk by underscoring the structural and social vulnerability of residents living in MHPs that constrain building resilience, adaptive capacity, community restoration efforts, and advocating for policy changes.
Significance Statement
This study aims to understand local hurricane risk perceptions, experiences, and vulnerabilities among residents of mobile home parks after a decade-long hurricane drought in south Florida and also to understand the barriers residents faced after a major hurricane. A hurricane drought is critical to study because it can erode individual and community-level preparedness. Residents of mobile home parks may experience more flooding, higher winds, tornadoes, and other dangers during hurricanes. Residents also face county-, neighborhood-, and household-level structural vulnerabilities that restrict their options related to hurricane preparedness, safety during a storm, and resilience in its aftermath. Our study uses various forms of data collection to obtain insights from permanent residents of mobile home parks in south Florida. In addition, it discusses the social and economic disadvantages and opportunities that policy makers can address in climate change risk management.
Abstract
South Florida experiences some of the highest coastal hurricane vulnerability in the United States. Mobile home communities in south Florida are particularly vulnerable to hurricanes due to the weaker structural integrity of the home or land and a mix of structural and sociodemographic factors. A mixed-methods study was conducted to assess hurricane risk perceptions, experiences, and decision-making among permanent mobile home park (MHP) residents in Broward and Miami-Dade Counties. Return-by-mail surveys were distributed in July 2016 after several years of nominal hurricane activity in south Florida (and before Hurricane Matthew’s formation in September 2016), and focus groups were conducted at MHPs in May 2018, eight months after Hurricane Irma’s September 2017 landfall. Quantitative analysis of 44 in-person and 57 return-by-mail survey responses revealed that respondents tended to be older, retired, or unemployed and had modest levels of education, with many expressing forms of social- and structural-level hurricane risk before Hurricane Matthew. Qualitative analysis of six focus group discussions conducted after Hurricane Irma revealed that the constraints and vulnerabilities experienced by residents coalesced into several primary themes related to preparation, evacuation, assistance, stress and anxiety, tree concerns, and recovery. Participants specifically highlighted their concerns about tree hazards, damages, and maintenance issues arising before, during, and after hurricanes in MHPs. These results build on the scholarship on hurricane risk by underscoring the structural and social vulnerability of residents living in MHPs that constrain building resilience, adaptive capacity, community restoration efforts, and advocating for policy changes.
Significance Statement
This study aims to understand local hurricane risk perceptions, experiences, and vulnerabilities among residents of mobile home parks after a decade-long hurricane drought in south Florida and also to understand the barriers residents faced after a major hurricane. A hurricane drought is critical to study because it can erode individual and community-level preparedness. Residents of mobile home parks may experience more flooding, higher winds, tornadoes, and other dangers during hurricanes. Residents also face county-, neighborhood-, and household-level structural vulnerabilities that restrict their options related to hurricane preparedness, safety during a storm, and resilience in its aftermath. Our study uses various forms of data collection to obtain insights from permanent residents of mobile home parks in south Florida. In addition, it discusses the social and economic disadvantages and opportunities that policy makers can address in climate change risk management.
Abstract
Management of adverse health-related effects from heat waves requires comprehensive and accessible sources of information. This paper examines the effects of temperature and air pollution on human health and identifies areas with increased occurrence of emergency ambulance dispatches in the city of Würzburg, Bavaria, Germany, and discusses the applicability for health care interventions and urban planning. An overdispersed Poisson generalized additive model was used to examine and predict the association and potential lag of exposure between temperature, air pollution, and three types of emergency ambulance dispatches during the study period from 2011 to 2019. A linear model was used to estimate heat-wave effects. A line density function was used to identify areas with increased occurrence of dispatches. Significant effects of temperature were detected for nontraumatic and cardiovascular diseases after exceeding a threshold temperature. The exposure–response relationships showed an increased relative risk up to two days after exposure for nontraumatic and cardiovascular diseases. Results indicate a significant association between presence of heat waves and cardiovascular diseases with up to 17% (95% confidence interval: 5.9%–30.0%) increased relative risk on a heat-wave day relative to a non-heat-wave day. Dispatches for cardiovascular diseases occur more often in areas with a high population and building density, especially in summer. The analyses identified hotspots of heat-related dispatches in areas with increased population and building density and provides baseline information for interventions in future urban planning and public health care management based on data commonly available even in small cities.
Significance Statement
The purpose of this study is to demonstrate how authorities in even medium- and small-sized cities can assess health impacts of heat stress or air pollution using free accessible emergency ambulance data and software to incorporate the outcomes in their spatial planning or health care management. This is important as ongoing climate change requires all urban communities to adapt and reduce adverse impacts of climate change and air pollution. Our results show that extreme heat leads to increased emergency ambulance dispatches in a medium-sized city in Germany and provide a spatial overview of where health care interventions and urban planning can focus to mitigate adverse effects.
Abstract
Management of adverse health-related effects from heat waves requires comprehensive and accessible sources of information. This paper examines the effects of temperature and air pollution on human health and identifies areas with increased occurrence of emergency ambulance dispatches in the city of Würzburg, Bavaria, Germany, and discusses the applicability for health care interventions and urban planning. An overdispersed Poisson generalized additive model was used to examine and predict the association and potential lag of exposure between temperature, air pollution, and three types of emergency ambulance dispatches during the study period from 2011 to 2019. A linear model was used to estimate heat-wave effects. A line density function was used to identify areas with increased occurrence of dispatches. Significant effects of temperature were detected for nontraumatic and cardiovascular diseases after exceeding a threshold temperature. The exposure–response relationships showed an increased relative risk up to two days after exposure for nontraumatic and cardiovascular diseases. Results indicate a significant association between presence of heat waves and cardiovascular diseases with up to 17% (95% confidence interval: 5.9%–30.0%) increased relative risk on a heat-wave day relative to a non-heat-wave day. Dispatches for cardiovascular diseases occur more often in areas with a high population and building density, especially in summer. The analyses identified hotspots of heat-related dispatches in areas with increased population and building density and provides baseline information for interventions in future urban planning and public health care management based on data commonly available even in small cities.
Significance Statement
The purpose of this study is to demonstrate how authorities in even medium- and small-sized cities can assess health impacts of heat stress or air pollution using free accessible emergency ambulance data and software to incorporate the outcomes in their spatial planning or health care management. This is important as ongoing climate change requires all urban communities to adapt and reduce adverse impacts of climate change and air pollution. Our results show that extreme heat leads to increased emergency ambulance dispatches in a medium-sized city in Germany and provide a spatial overview of where health care interventions and urban planning can focus to mitigate adverse effects.
Abstract
The September 2020 Oregon wildfires were unprecedented in terms of their geographic scope and the number of communities affected by smoke and wildfire. Although it is difficult to directly attribute the event to climate change, scientists have noted the strong connection between warmer and drier conditions in the western United States—conditions that are linked to climate change—and increasing wildfire risk. These wildfires thus had the potential to act as a “focusing event,” potentially strengthening public support for climate change policy. Political ideology is a well-known driver of public support for climate change mitigation policies in the United States, but few studies have examined adaptation policy support. Moreover, other factors shaping postevent support for the two “pillars” of climate change policy—adaptation and mitigation—have rarely been compared. We conducted a survey of Oregonians within 6 months of the 2020 wildfires (n = 1308) to understand postevent support for climate mitigation and adaptation policies. We found that the magnitude of the association between political ideology and policy support was lower for adaptation policies than for mitigation policies, and there was no association with support for forest management changes. In contrast, selected sociodemographic characteristics played a more important role in support for selected adaptation policies than for mitigation policies.
Significance Statement
Increasing wildfire risk in the western United States is connected to warmer and drier conditions, both of which are linked to climate change. Most research on postevent support for climate change policy has focused on climate change mitigation policies. This study examines and compares public support for both mitigation and adaptation policies after the 2020 Oregon wildfires, yielding important information about the factors that shape support for each.
Abstract
The September 2020 Oregon wildfires were unprecedented in terms of their geographic scope and the number of communities affected by smoke and wildfire. Although it is difficult to directly attribute the event to climate change, scientists have noted the strong connection between warmer and drier conditions in the western United States—conditions that are linked to climate change—and increasing wildfire risk. These wildfires thus had the potential to act as a “focusing event,” potentially strengthening public support for climate change policy. Political ideology is a well-known driver of public support for climate change mitigation policies in the United States, but few studies have examined adaptation policy support. Moreover, other factors shaping postevent support for the two “pillars” of climate change policy—adaptation and mitigation—have rarely been compared. We conducted a survey of Oregonians within 6 months of the 2020 wildfires (n = 1308) to understand postevent support for climate mitigation and adaptation policies. We found that the magnitude of the association between political ideology and policy support was lower for adaptation policies than for mitigation policies, and there was no association with support for forest management changes. In contrast, selected sociodemographic characteristics played a more important role in support for selected adaptation policies than for mitigation policies.
Significance Statement
Increasing wildfire risk in the western United States is connected to warmer and drier conditions, both of which are linked to climate change. Most research on postevent support for climate change policy has focused on climate change mitigation policies. This study examines and compares public support for both mitigation and adaptation policies after the 2020 Oregon wildfires, yielding important information about the factors that shape support for each.
Abstract
During the spring of 2019, severe flooding across the U.S. Midwest caused widespread damage to communities in the Missouri and Mississippi River basins. While it is known that flood magnitude and economic damage are often related, little work exists to examine these factors simultaneously. In this study, we analyze both the hydrologic and socioeconomic characteristics of the 2019 Midwest flood to gain a comprehensive understanding of impacts to individuals, households, and communities. We examine flood magnitude, duration, and probability of occurrence in tandem with claim and grant applications from federal disaster recovery programs, such as the National Flood Insurance Program (NFIP) and the Individual and Households Program (IHP). Overall, we find that many areas, particularly in Nebraska and Iowa, experienced moderate or major flooding due to historic discharge magnitudes. In these states, NFIP claims totaled more than $31 million and IHP applications exceeded $42 million in reported damages. In most cases, counties that reported a high density of insurance claims or grant applications overlapped with regions with significant flooding. We also identify the economic advantages to NFIP policyholders for flood recovery in terms of aid eligibility and financial aid amounts.
Abstract
During the spring of 2019, severe flooding across the U.S. Midwest caused widespread damage to communities in the Missouri and Mississippi River basins. While it is known that flood magnitude and economic damage are often related, little work exists to examine these factors simultaneously. In this study, we analyze both the hydrologic and socioeconomic characteristics of the 2019 Midwest flood to gain a comprehensive understanding of impacts to individuals, households, and communities. We examine flood magnitude, duration, and probability of occurrence in tandem with claim and grant applications from federal disaster recovery programs, such as the National Flood Insurance Program (NFIP) and the Individual and Households Program (IHP). Overall, we find that many areas, particularly in Nebraska and Iowa, experienced moderate or major flooding due to historic discharge magnitudes. In these states, NFIP claims totaled more than $31 million and IHP applications exceeded $42 million in reported damages. In most cases, counties that reported a high density of insurance claims or grant applications overlapped with regions with significant flooding. We also identify the economic advantages to NFIP policyholders for flood recovery in terms of aid eligibility and financial aid amounts.
Abstract
Heat stress from the environment can be detrimental to athletes’ health and performance. No research, however, has explored how elite athletes conceptualize and experience heatwaves and climate change. Utilizing a qualitative approach, this study examined elite athletes’ perceptions, experiences, and responses to extreme heat in relation to climate change and explored the use of their platforms for climate activism. Fourteen elite athletes from the United Kingdom, Australia, the United States, Sweden, and Canada, who represented 10 different sports including race walking, netball, and cricket were recruited using snowball sampling. Data were collected using semistructured interviews. Thematic analysis revealed four broad themes. The first theme reflected uncertainty surrounding the causes of heatwaves and the impact of heat on athlete health and performance. The second theme reflected care and concern for sport and society, including concern for the well-being of athletes and spectators, the impact of heat on facilities and participation at the grassroots level, and how the nature of sport may change in the future. The third theme referred to the implications of heatwave experience on athlete health and performance, and how experience affected individual and organizational preparedness. The fourth theme referred to enablers and barriers to successful climate change communication. This study contributes to the sport ecology literature by introducing the subjective heat experiences of elite athletes. Educating athletes and event organizers about the impacts of heat on sport participation is imperative to increase awareness and, it is hoped, to limit illness for those training and competing.
Abstract
Heat stress from the environment can be detrimental to athletes’ health and performance. No research, however, has explored how elite athletes conceptualize and experience heatwaves and climate change. Utilizing a qualitative approach, this study examined elite athletes’ perceptions, experiences, and responses to extreme heat in relation to climate change and explored the use of their platforms for climate activism. Fourteen elite athletes from the United Kingdom, Australia, the United States, Sweden, and Canada, who represented 10 different sports including race walking, netball, and cricket were recruited using snowball sampling. Data were collected using semistructured interviews. Thematic analysis revealed four broad themes. The first theme reflected uncertainty surrounding the causes of heatwaves and the impact of heat on athlete health and performance. The second theme reflected care and concern for sport and society, including concern for the well-being of athletes and spectators, the impact of heat on facilities and participation at the grassroots level, and how the nature of sport may change in the future. The third theme referred to the implications of heatwave experience on athlete health and performance, and how experience affected individual and organizational preparedness. The fourth theme referred to enablers and barriers to successful climate change communication. This study contributes to the sport ecology literature by introducing the subjective heat experiences of elite athletes. Educating athletes and event organizers about the impacts of heat on sport participation is imperative to increase awareness and, it is hoped, to limit illness for those training and competing.
Abstract
The National Weather Service is planning to implement the system of probabilistic tornado warnings. In this paper, I estimate and compare the full societal costs of tornadoes with existing deterministic and potential probabilistic warnings. These full costs include the value of statistical lives lost as well as the value of the time spent sheltering. I find that probabilistic tornado warnings would decrease total expected fatalities. The improvement in decision-making would also decrease the total opportunity cost of time spent sheltering, even though the total sheltering time is likely to increase. In total, probabilistic warnings should lower the societal costs of tornadoes relative to deterministic warnings by approximately $76–139 million per year, with a large portion of this improvement coming from fewer casualties.
Significance Statement
I measure societal benefits of probabilistic and deterministic tornado warnings in the United States by evaluating their effects on expected casualties and sheltering costs. I find that probabilistic warnings deliver almost twice as much net societal benefit as deterministic ones. These gains happen as a result of fewer casualties and making protective behavior more responsive to risks and sheltering costs. This paper provides additional evidence of the need to implement probabilistic extreme weather warnings.
Abstract
The National Weather Service is planning to implement the system of probabilistic tornado warnings. In this paper, I estimate and compare the full societal costs of tornadoes with existing deterministic and potential probabilistic warnings. These full costs include the value of statistical lives lost as well as the value of the time spent sheltering. I find that probabilistic tornado warnings would decrease total expected fatalities. The improvement in decision-making would also decrease the total opportunity cost of time spent sheltering, even though the total sheltering time is likely to increase. In total, probabilistic warnings should lower the societal costs of tornadoes relative to deterministic warnings by approximately $76–139 million per year, with a large portion of this improvement coming from fewer casualties.
Significance Statement
I measure societal benefits of probabilistic and deterministic tornado warnings in the United States by evaluating their effects on expected casualties and sheltering costs. I find that probabilistic warnings deliver almost twice as much net societal benefit as deterministic ones. These gains happen as a result of fewer casualties and making protective behavior more responsive to risks and sheltering costs. This paper provides additional evidence of the need to implement probabilistic extreme weather warnings.
Abstract
The impact of climate change on subsistence agriculture is a major concern in the developing world. The vulnerability of the coastal regions to climate change has been highlighted, in particular. The present study assessed the impact of climate change on subsistence rice farming on the eastern Indian coast using an integrated approach of statistical trend analysis by the Mann–Kendall test and Sen’s slope estimation of climate data and remote sensing–based land-cover analyses using the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and land surface temperature (LST) complemented by a questionnaire-based perception survey among the farming community. There has been a noticeable change in both ambient temperature and LST in the region. The delayed arrival of the monsoon critically impacts the cropping calendar. The crop harvest season has shifted farther into a time of the year that is prone to weather extremes. Analyses of NDVI and NDWI also indicate a shift in the cropping calendar. Over the years, there was an increasing degree of negative correlation between LST and NDVI in November, which indicates increasing water stress for crops in that time juncture. This may further cause crop sterility and yield loss. The study also reveals large-scale conversion of paddy-growing agricultural land into prawn aquaculture ponds. Farmers attributed such land-use change to cultivation stress caused by the delayed monsoon and consequent crop loss from weather extremes and changes in crop agronomic conditions. Farmers also report increased pest attacks and attribute that to an increasing temperature regime.
Abstract
The impact of climate change on subsistence agriculture is a major concern in the developing world. The vulnerability of the coastal regions to climate change has been highlighted, in particular. The present study assessed the impact of climate change on subsistence rice farming on the eastern Indian coast using an integrated approach of statistical trend analysis by the Mann–Kendall test and Sen’s slope estimation of climate data and remote sensing–based land-cover analyses using the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and land surface temperature (LST) complemented by a questionnaire-based perception survey among the farming community. There has been a noticeable change in both ambient temperature and LST in the region. The delayed arrival of the monsoon critically impacts the cropping calendar. The crop harvest season has shifted farther into a time of the year that is prone to weather extremes. Analyses of NDVI and NDWI also indicate a shift in the cropping calendar. Over the years, there was an increasing degree of negative correlation between LST and NDVI in November, which indicates increasing water stress for crops in that time juncture. This may further cause crop sterility and yield loss. The study also reveals large-scale conversion of paddy-growing agricultural land into prawn aquaculture ponds. Farmers attributed such land-use change to cultivation stress caused by the delayed monsoon and consequent crop loss from weather extremes and changes in crop agronomic conditions. Farmers also report increased pest attacks and attribute that to an increasing temperature regime.
