In a new paper I co-authored with Dr. Jonghun Kam and his Ph.D student Soon-Yoon Kim at the Department of Civil and Environmental Engineering, we used Google Trends to reveal the spatiotemporal patterns of US drought awareness. This paper has been published in Palgrave Communications (a Nature journal). Here is more information about this paper:
Article Title: Spatiotemporal Patterns of US Drought Awareness
Summary:
Drought is a creeping climatological phenomenon with persistent precipitation deficits. The intangible and gradual characteristics of drought cause a lack of social response during the onset. The level of awareness of a local drought increases rapidly through mass media reports and online information searching activities when the drought reaches its peak severity. This high level of local drought awareness drives concerns for water shortage and support for water policy. However, spatiotemporal patterns of national-scale drought awareness have never been studied due to constraints imposed by time-consuming and costly survey data collection and surveys' limited sample sizes.
Here, we present the national-scale study to reveal the spatiotemporal patterns of drought awareness over the contiguous United States (CONUS) using Google Trends data and an advanced statistical technique, Principal Component Analysis (PCA). Results show that the first two PC modes can explain 48% (38% for PC1 and 10% for PC2; see Figures below) of the total variance of state-level drought awareness. We find that the PC1 mode relates to a national pattern of drought awareness across the CONUS. The spatiotemporal patterns further imply that residents in the Northeastern US region are the most aware of the emergence of drought, regardless of the geographic location of the occurrence. The results illustrate how search engine queries and social media data can help develop an effective and efficient plan for drought mitigation in the future.
The following Figure comes from Kim et al. (forthcoming):
Article Title: Spatiotemporal Patterns of US Drought Awareness
Summary:
Drought is a creeping climatological phenomenon with persistent precipitation deficits. The intangible and gradual characteristics of drought cause a lack of social response during the onset. The level of awareness of a local drought increases rapidly through mass media reports and online information searching activities when the drought reaches its peak severity. This high level of local drought awareness drives concerns for water shortage and support for water policy. However, spatiotemporal patterns of national-scale drought awareness have never been studied due to constraints imposed by time-consuming and costly survey data collection and surveys' limited sample sizes.
Here, we present the national-scale study to reveal the spatiotemporal patterns of drought awareness over the contiguous United States (CONUS) using Google Trends data and an advanced statistical technique, Principal Component Analysis (PCA). Results show that the first two PC modes can explain 48% (38% for PC1 and 10% for PC2; see Figures below) of the total variance of state-level drought awareness. We find that the PC1 mode relates to a national pattern of drought awareness across the CONUS. The spatiotemporal patterns further imply that residents in the Northeastern US region are the most aware of the emergence of drought, regardless of the geographic location of the occurrence. The results illustrate how search engine queries and social media data can help develop an effective and efficient plan for drought mitigation in the future.
The following Figure comes from Kim et al. (forthcoming):
Figure 1: Major principle components of state-level drought awareness and state-level drought risk over the contiguous United States. Temporal correlations of Drought Awareness from the first two major modes with individual state-level drought awareness ((c) and (d), respectively) and individual state-level drought risk ((e) and (f), respectively). White colored states depict the states with insignificant temporal correlation at the 99% confident level.
Figure 2: State-level correlation analysis of drought awareness and drought risk. Colors in the grid cells depict temporal correlation coefficients of state-level drought awareness (left triangle) and state-level drought risk (right triangle) of one state with those of the rest 48 states. To assist interpretation, areas that depict interstate relationships within the region (green colored boundaries) and across regions (blue colored boundaries) are shown in the legend box at upper-left corner.
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