Remote Sensing to Assess Drought Across Southwestern U.S.A.

Authors: Pratima Khatri-Chhetri, Sean M. Hendryx, Kyle A. Hartfield, Michael A. Crimmins, Willem J.D. van Leeuwen, and Van R. Kane

This study investigates the patterns and relationships between seasonal vegetation productivity, represented by Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Standardized Precipitation Evapotranspiration Index (SPEI) across the Mojave, Sonoran, and Chihuahuan Deserts and the Apache Highlands of the Southwest United States over 16 years from 2000 to 2015.

To examine the spatiotemporal gradient and response of vegetation productivity to dry and wet conditions, we evaluated the linear trend of different SPEI timescales and correlations between NDVI and SPEI.

We analyzed the correlations between NDVI and SPEI across four ecoregions in the Southwest United States to shed new light on the spatiotemporal relationships between vegetation productivity and drought timescales. We analyzed whether general patterns in relationships between vegetation productivity (NDVI) and water availability (SPEI) hold across different desert ecoregions or if the relationships are unique to each. In particular, we examined the impact of different SPEI timescales on NDVI across the Mojave, Sonoran, and Chihuahuan Deserts, and Apache Highlands ecoregions of Southwest United States for 16 years from 2000 to 2015. We also studied the long-term trend and variability of SPEI at different timescales to understand the differences between short- and long-term drought and how this is impacting vegetation productivity. The results of this study are expected to improve our understanding of the spatiotemporal response of vegetation to drought in deserts of the Southwest US and the vulnerability of vegetation to climate change that can be useful in resource management and reducing drought impacts.

We used a linear regression method to analyze the trend and interannual variation of different SPEI timescales for 66 years from 1950 to 2015. To understand the changes in dryness and wetness values for the short-term (1-, 2-, 3-month), medium (6-, 9-month), and long-term (12-month) SPEI, we selected four different monthly SPEI timescales, 1-month, 3-month, 6-month, and 12-month. The ecoregion scale SPEI data from the Global Drought monitor was used to analyze the time series of all four ecoregions. To evaluate if there is a significant difference between the historic (1950–1999) and early 21st century (2000–2015) drought period we also calculated the mean SPEI for both periods using the student t-test. To justify using linear regression on long term SPEI values, we tested for trend-stationarity in selected SPEI timescales by running the augmented Dickey-Fuller Test implemented in the “tseries” package in R.

We used the Pearson Correlation coefficient to study how seasonal vegetation productivity (NDVI) was related to different water stress (SPEI) timescales for each 250 m pixel of NDVI and different SPEI timescales rasters across our study area. For this correlation analysis, we model monthly NDVI as a function of the SPEI value at that month over a precedent timescale (as shown in Equation (2)) where,  timescale  is equal to 1, 3, 6, 9, or 12 months.

We found that all four ecoregions are experiencing more frequent and severe drought conditions in recent years as measured by negative SPEI trends and severe negative SPEI values. We found that changes in NDVI were more strongly correlated with winter rather than summer water availability. Investigating correlations by vegetation type across all four ecoregions, we found that grassland and shrubland productivity were more dependent on summer water availability whereas sparse vegetation and forest productivity were more dependent on winter water availability. Our results can inform resource management and enhance our understanding of vegetation vulnerability to climate change.