An Analysis of Drought Exposure, Impacts, and Adaptation in the South Central U.S.
Nina S Lam (PI – resilience and sustainability), Robert Rohli (Co-PI – climatology), Margaret A Reams (Co-PI – adaptive governance)
Department of Environmental Sciences and Department of Geography & Anthropology at Louisiana State University
This project is funded by the South Central Climate Adaptation Science Center Program with a start date of 08/12/2014 and an end date of 08/11/2016 (two years).
Existing literature has seldom considered the linkages between drought indices for monitoring and the actual damages to crops and properties. In other words, what indices are most effective in representing the occurrence of drought events and their actual damages? Therefore, the project's first objective will be devoted to testing the relationships between a number of indices with the drought damage data (Rohli et al. 2016).
The research will collect and analyze three types of data including:
These three types of data will come in different forms and at different spatial and time scales. Extensive effort will need to be devoted to integrate them into a geographic information system (GIS) for analysis and mapping. First, GIS-based downscaling of indices from the climate divisional to the county scale will be conducted, for the period 1975-2010, when county-scale damage data became available from NOAA. We will examine the existing downscaling methods and test the sensitivity of county-level drought indices estimates. We will then conduct correlation analysis to evaluate whether drought indices are effective in predicting drought damages.
Rohli, R.V., Bushra, N., Lam, N.S.N. et al. (2016) Drought indices as drought predictors in the south-central USA. Nat Hazards 83: 1567.
The research will apply a social-ecological resilience framework to examine the linkages between the exposure of residents and farmers to drought conditions, their vulnerability to that exposure (i.e., crop or property damages), and their ability to adapt, so that damages associated with future droughts can be mitigated.
In an attempt to overcoming some of the measurement issues, we previously developed an approach, called the Resilience Inference Measurement (RIM) model, to quantify community resilience to coastal hazards (Lam et al. 2016). The RIM model is based largely on the IPCC (Intergovernmental Panel on Climate Change) definition of resilience and considers three dimensions and two capacities. The three dimensions are exposure, damage, and recovery, and the two capacities are vulnerability and adaptability. Vulnerability refers to the relationship between exposure and damage, whereas adaptability indicates the relationship between damage and recovery.
Using the RIM framework, we will first group all the counties according to the three dimensions (exposure, damage, and recovery as indicated by population growth rate) into four classes using k-means cluster analysis. Discriminant analysis will be applied to determine which sets of variables are most important in characterizing counties that have high resilience.
Two hypotheses will be tested:
Lam, N. S. N., Reams, M., Li, K., Li, C., & Mata, L. P. (2016). Measuring Community Resilience to Coastal Hazards along the Northern Gulf of Mexico. Natural Hazards Review 17(1), 04015013.
Mihunov V.V., Lam N.S.N., Zou L. et al. (2018) Community Resilience to Drought Hazard in the South-Central United States. Annals of the American Association of Geographers 108:3, 739-755
While a broad-scale assessment of drought resilience across a large geographical space is very useful for comparison and monitoring of progress, a survey of residents is needed to help understand adaptive behavior so that effective management strategies can be made. Specifically, in addressing the question of whether there are differences in the response of communities to the drought events and why, we will examine patterns of adoption of water-conservation and drought-mitigation strategies and behaviors among residents of drought prone urban and rural communities. By understanding how and why the communities differ in their response and adaptive capacity, we can improve the management tools to increase resilience to droughts.
A telephone survey of about 500 residents and 100 farmers will be conducted through collaboration with the LSU Public Policy Research Laboratory. The sample will be selected randomly from the counties with high exposure in Texas. By focusing the survey in one state instead of sampling from different states, we avoid the problem of considering different regulations imposed by different states. We will follow the same survey methodology used in our previous studies and aim to have a brief survey with quantifiable questions to increase participation rate and enable statistical analysis (Lam et al. 2009; Reams et al. 2013). Specifically, the survey will determine whether socioeconomic status and duration of residence in the community affect awareness of and personal experiences with drought. Also, the questions will determine the extent to which respondents have adopted specific water-conservation and drought-mitigation actions.
Reams MA, Lam NSN, Cale TM, Hinton CM (2013) Applying a community resilience framework to examine household emergency planning and exposure-reducing behavior among residents of Louisiana's industrial corridor. Journal of Emergency Management 11(2): 108-120.
Lam NSN, Pace K, Campanella R, LeSage J, Arenas H (2009) Business Return in New Orleans: Decision Making Amid Post-Katrina Uncertainty. PLOS ONE 4(8): e6765.
Rohli, R.V., Bushra, N., Lam, N.S.N. et al. (2016) Drought indices as drought predictors in the south-central USA. Nat Hazards 83: 1567.
Mihunov V.V., Lam N.S.N., Zou L. et al. (2018) Community Resilience to Drought Hazard in the South-Central United States. Annals of the American Association of Geographers 108:3, 739-755
Mihunov V.V., Lam N.S.N., Rohli, R.V., Zou L. et al. (2018) Emerging Disparities in Community Resilience to Drought Hazard in South-Central United States. (under review) See related AGU 2017 Presentation Abstract.
County-level drought indices, 1975-2010
Combined county-level drought incidence, damage, and census data, 1990-2010
Drought adaptation household survey summary