Truth in the Soil: Using SMAP to Monitor Drought in Southeast US

Category: Monitoring Drought
Project Team: Southeast United States Agriculture
Team Location: Wise County Clerk of Court’s Office – Wise, Virginia

Standardized Soil Moisture Index layers of three-day data. The Standardized Soil Moisture Index is a Z-score of SMAP data compared to NLDAS historic statistics. Image Credit: Southeast Agriculture Team

Standardized Soil Moisture Index layers of three-day data. The Standardized Soil Moisture Index is a Z-score of SMAP data compared to NLDAS historic statistics. Image Credit: Southeast Agriculture Team

Authors:
Yaping Xu
Yousra Benchekroun
Kimberly Berry
Grant Bloomer

Mentors/Advisors:
Dr. Kenton Ross (NASA Langley Research Center)
Dr. DeWayne Cecil (Global Science & Technology)
Bob VanGundy (The University of Virginia’s College at Wise)
Michael Bender (Wise County, Virginia)

Past/Other Contributors:
Michael Brooke (Center Lead)

Abstract:

Regional climate variability in the southeastern United States is a concern for agricultural and forestry management. Droughts are an important consequence of this variability, affecting the agricultural and forestry sectors’ ability to manage water resources. The U.S. Department of Agriculture (USDA) Southeast Regional Climate Hub (SERCH) has developed a tool called Lately Identified Geospecific Heightened Threat System (LIGHTS) to provide information for its users that would increase water management efficiency. It identifies and alerts users to changes in drought, temperature, and precipitation patterns. However, LIGHTS lacks soil moisture information, which also affects drought patterns. This project aims to update the current drought monitoring system by incorporating Soil Moisture Active Passive (SMAP) level 3 data as a support layer, by retrieving Standardized Soil Moisture Index (SSI) as a measure and by using Python as the programming language. Ground truth soil moisture data from Soil Climate Analysis Network (SCAN) were collected for validation. As a result, this integration of SMAP data into SERCH LIGHTS will increase the end-user’s water management capabilities in response to drought conditions.

Previous story | Main Page | Next story

6 Comments

Darius Hixon (MCHD) 18-08-2016, 20:35

Absolutely great job on the project. Groundbreaking research and I can’t wait to read the tech paper!

Reply
Kimberly Berry 19-08-2016, 19:37

Thank you! We can send it to you later if you would like.

Reply
Daryl Ann Winstead (Mekong River Basin Agriculture) 18-08-2016, 16:48

Great work! Will there be a continuation of the project? Thank you in advance for your response!

Reply
Kimberly Berry 19-08-2016, 19:35

At this time there is no continuation planned but we are eager to work with our partners to intergrate it into their system.

Reply
Georgina 18-08-2016, 14:45

Interesting project and video! What is the data latency from when the SMAP satellite takes the measurements till the data may be included into the tool? Are there plans to automate this process?

Reply
Kimberly Berry 19-08-2016, 19:40

Thank you! We used Level 3 SMAP data so the data latency is less than 72 hours. Our partners are going to automate the soil moisture alerts but the data processing will be manual.

Reply

Leave a Reply