According to scientists at NASA’s Global Precipitation Measurement (GPM) mission, if you collected all the rain gauges currently in use around the world into one location they would cover an area only about the size of two basketball courts. There simply is no effective way to collect precipitation data at ground level for all points around the globe. This means that assessing water resources globally, especially in remote areas, needs to rely on data collected by Earth observing satellites, such as GPM, launched in 2014; Tropical Rainfall Measuring Mission (TRMM),1997-2015; and Soil Moisture Active Passive (SMAP), launched in 2015.
One remote area in which managing water resources is difficult is the Navajo Nation, which covers more than 70,000 km2 (27,000 square miles) in northern Arizona, southern Utah, and northern New Mexico. The reservation, with a 2010 Census population of 173,667, is dealing with periods of severe drought coupled with a lack of domestic water infrastructure and economic resources. According to the 2010 U.S. Census, at least 70,000 Navajo Nation residents do not have access to potable water in their homes.
Thanks to a recent NASA DEVELOP National Program effort, the Navajo Nation has a new computer application that integrates precipitation data from NASA and other sources to quickly give Navajo Nation managers reservation-wide historic and near real-time data about their water resources. Vickie Ly was part of the NASA DEVELOP team that created the Drought Severity Assessment Tool (DSAT) for the Navajo Nation as part of NASA’s Navajo Nation Climate Project.
Let’s first talk about the Navajo Nation. Tell me about the landscape and the distances involved, and the challenges these present to collecting data.
I think a lot of people don’t realize how large and extensive the Navajo Nation is. It’s about the size of West Virginia. This is one of the reasons why we wanted to create a tool that could address the challenges of covering a large, remote area and allow users, in this case the Navajo Nation Department of Water Resources (NNDWR) to customize what they are looking at in terms of precipitation and how wet or dry a specific area is.
It’s also important to realize that there is a huge heterogeneity in the landscape of the Navajo Nation. There are parts that are 10,000 feet high and receive plenty of precipitation in the form of snow; there are parts that are 6,000 feet and receive a lot less precipitation. There are such differences [in water resources] from one part of the reservation to another that we had to keep in mind the best way to cover this when we were developing DSAT. How can we reflect this in the data we’re using and the tool we’re developing? This was a challenge.
What was the need for developing the Drought Severity Assessment Tool?
One of the many challenges facing the Navajo Nation is how to manage water. They use something called the Standard Precipitation Index (SPI), which is a measure of how wet or dry an area is. It’s a simple calculation of how much the precipitation in an area deviates from normal, which is calculated based on a 30-year average of precipitation. The SPI is needed by reservation water resource managers to report to [Navajo Nation leadership] about which areas in the reservation are experiencing drought and the severity of this drought. These reports determine how [Navajo Nation] financial resources are allocated to mitigate drought.
One problem is that the NNDWR can’t calculate their own SPI due to the lack of data available. The NNDWR collects rain gauge data, but there are only about 88 rain gauges across the entire Navajo Nation. Most of these are clustered along roads and other easily accessible areas and don’t [provide] the spatial resolution to cover the entire reservation. Instead, they use state-based SPI data captured by the Western Regional Climate Center. Since the Navajo Nation covers portions of three states, this cuts the Navajo Nation into three large pieces and uses three SPI values to describe this expansive region. The area has so much heterogeneity that these three SPI numbers don’t adequately reflect what’s going on throughout the [Navajo Nation]. Our approach was to see what data and data products we could use that would have a better spatial and temporal resolution and would lead to more accurate SPI calculations.
What data products did you use to create DSAT?
We’ve created two versions of DSAT at this point. DSAT 1.0 integrates TRMM, GPM, and Parameter elevation Regression on Independent Slopes Model (PRISM) data. With DSAT 2.0, we decided to integrate Climate Hazards group InfraRed Precipitation with Station (CHiRPS) data, which is a 30-plus year quasi-global climate data set with higher resolution data. CHIRPS satellite data come from the University of California-Santa Barbara Climate Hazards Group and affiliated research groups; TRMM data are used to calibrate CHIRPS data, which are further calibrated using precipitation data from ground-based sensors. What is great about CHIRPS data is that they satisfy the SPI requirement of having 30 years of precipitation data. So, it was a perfect fit to use CHIRPS data to calculate the SPI.
How does DSAT work?
There are four main steps for generating precipitation data:
The first step is that you download the precipitation data and process it within the DSAT tool; these data are CHIRPS data. With the click of a button you can download CHIRPS data and these data will be clipped to a boundary that the user is interested in, like watersheds, ecoregions, or political boundaries in the Navajo Nation.
The second step is calculating the SPI. You can determine the type of SPI you want to look at: 1 month, 6 month, or 12 month. You select a beginning month and year and an ending month and year. Then you click “go.”
In the third step, you get summary statistics. You can take the time range of data you’re looking at and overlay a boundary. Say you want to look at a specific Navajo Nation agency, which is analogous to an individual U.S. state within the Navajo Nation. You can then calculate the SPI for the agency within that boundary. You also can overlay watershed boundaries and calculate the SPI within that watershed. You can then export the data as an Excel file to either work with in the DSAT tool or print it out as an Excel spreadsheet.
The fourth step is the icing on the cake and what we consider the “wow” factor: the visualization. Here the SPI rasters are overlaid onto a web map where you can click through time. Let’s say you set the time from March 2015 to March 2016, you can slide through time and see the changes in SPI values indicated in blue and red, with blue indicating wetter periods and red indicating drier periods within the overlay boundaries you selected.
How is DSAT being used in Navajo Nation?
DSAT is currently being used by the NNDWR for annual reports. The NNDWR compiles annual reports for Navajo Nation leadership, who use these reports to decide how to allocate drought relief dollars. The goal is that with DSAT, providing more spatially and temporally continuous data will provide a better picture of what areas are experiencing more drought and need more financial attention. Carl McClellan, a senior hydrologist with the NNDWR and the main DSAT user, is incorporating visualizations from DSAT to report the state of drought [in the nation] in 2016 and show which geographical areas and towns are experiencing the highest degrees of drought. Since this is the first time DSAT will be used for annual reports, we’re really excited to see it in action.
Along with annual reports, the NNDWR also hopes to use DSAT’s visualizations for presentations and demos with other natural resource agencies and visitors to show changes in drought intensity. The NNDWR is continuing to experiment with the DSAT features and applications.
What is the future of the Navajo Nation Project? What are your next steps?
One thing I’ve learned in this project is that when creating a tool or product, it’s important to think about how the user is actually going to use the product or tool. It’s really spun what collaboration means - working backwards from the application to the methodology. We spent a lot of time with our partners in the Navajo Nation Department of Water Resources developing this tool to incorporate their feedback in each step of our revisions.
I think there are three possible areas where this project can be continued. For one, I think the partnerships we’ve created developing this tool will lead to further collaborations with other projects. Also, there will be follow-up to see how the tool is being used and how it can be improved. Sometimes it’s hard to know this unless you’re checking in regularly. I try to be in frequent contact with the Navajo Nation Department of Water Resources. I hope we’ll be able to see how we can further this relationship and partnership.
The second aspect relates to logistics. This project was part of the NASA DEVELOP Program, and these projects are designed to be intense, short-term sprints. Delivering DSAT was the objective of this project, so it’s no longer part of the DEVELOP Program. This project now has moved to a personal level, with me checking in to see how this project advances.
A third possible continuation of this project could be my work on this as I enter a graduate degree program and make this project and the research questions from it part of my degree work.
What is the impact of this project, and similar projects, for the Navajo Nation and for indigenous peoples?
This project has opened the door to a part of the U.S. that I think is largely underrepresented or unseen. There are a lot of different, interdisciplinary issues that go on in Indian country, and to be able to represent this in the scientific community and raise these issues and give these groups a seat at the table is the next step we can take in thinking about data and applications.
I’m now working with NASA’s Applied Sciences Capacity Building Program on a new initiative focused on providing tools, data, and support to indigenous groups. The initiative is in its infancy, and we’re really excited about its potential. We recently did a remote sensing workshop at a tribal conference in Albuquerque, New Mexico. We had 19 students representing 17 different tribes or tribal groups. It’s amazing since these groups represent a tremendous range of climatic regions and environmental issues across North America. These tribes are dealing with different environmental problems, but, foundationally, they all have similar issues. There is a real opportunity to see how we can use remotely sensed data for natural resource monitoring and assist these groups.