The goal of the Development of a Multi-Scale Remote-Sensing Based Framework for Mapping Drought over North America project is to develop a drought monitoring tool for North America based on remotely sensed estimates of evapotranspiration (ESI; Evaporative Stress Index). The ESI represents anomalies in the ratio of actual-to-potential ET generated with the thermal remote sensing based Atmosphere-Land Exchange Inverse (ALEXI) surface energy balance model. The LST inputs to ESI have been shown to provide early warning information about the development of vegetation stress with stress-elevated canopy temperatures observed well before a decrease in greenness is detected in remotely sensed vegetation indices. Whereas many drought indicators based on precipitation or atmospheric conditions capture meteorological drought, the ESI is one of few indicators of agricultural drought that reveals actual vegetation stress conditions realized on the ground. As a diagnostic indicator of actual ET, the ESI requires no information regarding antecedent precipitation or soil moisture storage capacity - the current available moisture to vegetation is deduced directly from the remotely sensed LST signal. This signal also inherently accounts for both precipitation and non-precipitation related inputs/sinks to the plant-available soil moisture pool (e.g., irrigation, tile drainage) which can modify crop response to rainfall anomalies. Independence from precipitation data is a benefit for global agricultural monitoring applications due to sparseness in existing ground-based precipitation networks, and time delays in public reporting. Even as satellite precipitation monitoring has closed some of the observational gaps, these data are usually provided at coarse resolution with accuracy dependent on extensive calibration with ground-based precipitation estimates.
ESI will be used by collaborators at the National Drought Mitigation Center (supporting the US Drought Monitor and the North American Drought Monitor) and collaborators at the USDA National Agricultural Statistics Service to establish utility of ESI in monitoring crop condition. The proposed framework has led to the development of the GOES Evapotranspiration and Drought Product (GET-D) system at NOAA. GET-D has been developed over the project life cycle and has been approved for operational transition at the NOAA Office of Satellite Products and Operations (OSPO). GET-D has been operational at NOAA OSPO since June 2016 and serves operational ESI products to our group of project stakeholders and others in the drought monitoring community.
Websites:
GET-D website
Evaporative Stress website
Drought monitor website
Drought website
Ag Data Map Tools website
Operational FTP:
FTP website
Geographic Focus
North America for GET-D (NOAA Operational); Prototype Global GET-D (UMD Research)
Application Readiness Level
ARL- 9 (Sustained Use)
The GOES Evapotranspiration and Drought Product (GET-D) system has been approved and operationally deployed at NOAA. Operational ESI products are provided by NOAA to our project stakeholders and others in the drought monitoring community for use in decision making.
Principal Investigator
Christopher Hain, University of Maryland, Earth System Science Interdisciplinary Center, NOAA
Project Team
Martha Anderson and Feng Gao, USDA-ARS
Xiwu Zhan, NOAA-NESDIS
Li Fang, Zhengpeng Li, Jifu Yin, ESSIC/UMD, NOAA
Mark Svoboda and Brian Wardlow, NDMC/University of Nebraska
Collaborators & Stakeholders
University of Maryland, USDA-ARS, NOAA-NESDIS, NDMC/University of Nebraska, USDA-NASS, University of Alabama in Huntsville, National Drought Mitigation Center, NOAA NCEP Environmental Modeling Center, NOAA NCEP Climate Prediction Center, USDA Foreign Agricultural Service, Texas Water Development Board, NOAA National Centers for Environmental Information, G20 GeoGLAM Crop Monitor Initiative for the Agricultural Market Information System, Regional Drought Management System for the Middle East and North Africa, NIDIS Global Drought Information System
Technical Overview
The Evaporative Stress Index (ESI) describes temporal anomalies in evapotranspiration (ET), highlighting areas with anomalously high or low rates of water use across the land surface. Here, ET is retrieved via energy balance using remotely sensed land-surface temperature (LST) time-change signals. LST is a fast- response variable, providing proxy information regarding rapidly evolving surface soil moisture and crop stress conditions at relatively high spatial resolution. The ESI also demonstrates capability for capturing early signals of “flash drought”, brought on by extended periods of hot, dry and windy conditions leading to rapid soil moisture depletion. The LST inputs to ESI have been shown to provide early warning information about the development of stress, with stress-elevated canopy temperatures observed well before a decrease in “greenness” is detected in remotely sensed vegetation indices. Whereas many drought indicators based on precipitation or atmospheric conditions capture meteorological drought, the ESI is one of few indicators of agricultural drought that reveals actual vegetation stress conditions realized on the ground. This distinction is particularly important for the agricultural sector where human activity can alter how the drought is actually affecting crop health (e.g., through irrigation, use of drought-resistant crop varietals, etc.). Not all meteorological droughts develop into an agricultural drought, and having indicators specifically related to crop vegetation stress is imperative for improved decision-making by agricultural stakeholders.
As a diagnostic indicator of actual ET, the ESI requires no information regarding antecedent precipitation or soil moisture storage capacity - the current available moisture to vegetation is deduced directly from the remotely sensed LST signal. This signal also inherently accounts for both precipitation and non-precipitation related inputs/sinks to the plant-available soil moisture pool (e.g., irrigation, tile drainage; Hain et al. 2015), which can modify crop response to rainfall anomalies. Independence from precipitation data is a benefit for global agricultural monitoring applications due to sparseness in existing ground-based precipitation networks, and time delays in public reporting. Even as satellite precipitation monitoring has closed some of the observational gaps, these data are usually provided at coarse resolution with accuracy dependent extensive calibration with ground-based precipitation estimates. Additionally, the ESI also provides an important distinction from drought indicators that focus on atmospheric demand (e.g., the Evaporative Demand Drought Index; EDDI) which signal the potential for stress but provide no direct link to the onset of actual vegetation stress. In each of these respects, the ESI and ESI-derived Rapid Change Indices will give stakeholders a unique perspective for assessing impacts of agricultural drought on crop and rangeland productivity at the global scale.
ESI values quantify standardized anomalies (σ values) in the ratio of clear-sky actual-to-potential ET (fPET), derived using thermal infrared (TIR) satellite imagery from geostationary platforms. To capture a range in timescales, fPET composites are developed for 1, 2 and 3 month moving windows, advancing at 7-day intervals. Standardized anomalies are then computed with respect to normal conditions (mean and standard deviation) for each compositing interval assessed over a period of record from 2000-2015.
Additional Information
2016 Press Releases:
ESI featured as NASA’s Earth Observatory Image of the Day:
Earth Observatory NASA website
NOAA Climate Program Office, “New NOAA product improves early warning of drought”:
U. of Maryland, “UMD Scientists Help Develop New Drought Early Warning Tool”:
Related Research Areas