In the spring of 2017, almost no one in Montana saw the drought coming. Not when winter snowpack and early rains soaked the landscapes with adequate moisture. Not when springtime green-up seemed to hold such promise.
But the days grew warm, the precipitation shut down, and a driving wind raking eastern Montana would not stop. With the drying power of the atmosphere drastically increasing, “it dried out any moisture that was in the soil very rapidly,” Montana’s State Climatologist Kelsey Jencso recalls.
And so it began.
The drought of 2017 took hold in the state’s northeast corner and progressed westward along the Montana Hi-Line. As it did, Jencso and others on a monitoring subgroup of the Governor’s Drought and Water Supply Committee in Montana turned to a variety of drought indices to help them track the evolving conditions. Two important products—the Vegetation Drought Response Index (VegDRI) and Quick Drought Response Index (QuickDRI)—were developed in part at the U.S. Geological Survey’s (USGS) Earth Resources Observation and Science (EROS) Center near Sioux Falls, SD.
What climatologists like Jencso know is that drought often manifests itself in different forms at different time scales. It occurs at a meteorological level with a lack of weather-related moisture. There is agricultural drought as soil moisture diminishes, hydrological drought with the drying up of surface and ground water, even ecological drought.
VegDRI, QuickDRI are 'very unique tools'
From an agricultural standpoint, the value of VegDRI and QuickDRI to the subcommittee turned out to be significant, Jencso said. The two indices integrate remotely sensed time series observations of vegetation with climate, land cover-land use types, the ecological setting, and soil characteristics to show drought’s effect at 1-kilometer resolution. The massive remote sensing archives at USGS EROS that supply historical satellite data from the last several decades are vital to both indices in establishing a sound comparison with normal conditions over a longer historical period.
“Something like VegDRI and QuickDRI are very unique tools, especially for these rapid onset droughts,” Jencso said. “The vegetation state and its greenness are representative of the soil water limit, as well as the kind of atmospheric conditions that lead to declines in soil moisture. It’s ultimately showing that key impact, which is the vegetation water stress."
VegDRI is more of a seasonal drought indicator that uses moving inputs that still can change weekly, said Jess Brown, a research geographer at EROS who is the lead on VegDRI and QuickDRI. VegDRI uses two MODIS-based inputs—Percent of Average Seasonal Greenness, which indicates how vegetation greenness over a season differs from the historical average, and the Start of Season Anomaly. VegDRI also incorporates the Standardized Precipitation Index (SPI), a drought indicator based only on precipitation.
QuickDRI was released as an early warning system in 2017 and answered a need to detect even faster-emerging and changing drought conditions. To do that, QuickDRI relies on a variety of moving weekly inputs as well, including SPI and:
- Soil Moisture Anomaly, a NASA product that models root-zone soil moisture;
- Evaporative Stress Index, produced by the U.S. Department of Agriculture and showing evaporative moisture loss from plants;
- Standardized Vegetation Index, based on the MODIS Normalized Differentiated Vegetation Index (NDVI), to gauge plant vigor compared to historical norms;
- Landscape characteristics, such as soil texture, land cover, and elevation.
“Vegetation is always going to move a little slower, change a little slower, than everything else during a drought,” Brown said. “You can have long- and short-term droughts, but with QuickDRI, because it has this soil moisture component and the Evaporative Stress Index, it really makes it much more sensitive. People use the terminology that QuickDRI is like a drought alarm. It’s really an alarm for changing conditions.”
While QuickDRI certainly was beneficial to his committee in identifying rapid onset, Jencso said VegDRI‘s 1-kilometer resolution and metrics were equally important for helping to assess how the drought was evolving across the state’s different counties.
“We used (VegDRI) as an input to say, ‘This county is in a drought category of this magnitude, but the adjacent county, maybe it’s a little bit behind. Maybe it has a reduced drought magnitude,” he said. “So, we used (VegDRI) as one of the key indicators to designate drought class and category for Montana’s counties, and that became very important for emergency declarations and drought aid.”
Data offered detail, guidance during drought emergency
In 2017, Jencso said the governor of Montana declared upward of 12 emergency designations as the drought progressed. Counties had to have a drought emergency designation to receive insurance aid from the Federal government, but also to be eligible for services related to mitigating drought, he said. For example, emergency designations would allow truckers to extend the time they could be on the roads hauling hay, water, and feed across county borders and across the state.
“Having that emergency classification becomes very important for the allocation of aid, too, and for just responding to drought conditions,” Jencso said.
QuickDRI and VegDRI provide what he characterizes as “fine-grained information” that would be useful as well to range managers watching conditions evolve across landscapes they are responsible for overseeing, Jencso said. It may be valuable information that leads to moving cattle from one allotment to the next, for example. Or it may be useful in deciding how long to let those cattle graze on a given allotment.
“To me, those fine-grained assessments are very important for management decisions on the ground,” Jencso said.
While emphasizing that there are many good drought indicators available, Jencso said his subcommittee’s work would be much more difficult without VegDRI or QuickDRI. That’s because they not only incorporate the kinds of responses vegetation have to limits in moisture, but they reflect land use characteristics as well, and use gridded meteorological datasets that capture rainfall, temperature, and evapotranspiration rates occurring within localized settings.
“I think the uniqueness of especially VegDRI is that it incorporates those gridded meteorological datasets at a relatively high resolution, and a temporal resolution, with these satellite-based measures of vegetation greenness,” Jencso said. ‘It accounts for differences in land use. And I think it’s a great framework for assessing these conditions over time.”
It certainly was useful in Montana in 2017, he said. And continues to be so today.
“I really believe that it will only improve over time, too,” Jencso said. “As our ability to measure things from space or via our atmospheric datasets becomes even more improved, those indices will only become better.”
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