Wednesday, 31 January 2024
Hall E (The Baltimore Convention Center)
Soil moisture, a fundamental component of the terrestrial hydrological cycle, is vital in influencing natural processes and human activities. As a critical parameter in assessing environmental conditions, its significance spans the spectrum of monitoring and mitigating drought – a pressing challenge facing societies worldwide. The Blended Soil Moisture Product in NOAA's Soil Moisture Operational Products System (SMOPS) is generated using soil moisture products from multiple satellite sensors for better spatiotemporal coverage and used in various research topics, including drought monitoring.
This study investigates the application of the Blended Soil Moisture Product from SMOPS to detect and analyze soil moisture anomalies for drought monitoring. Weekly soil moisture climatology and associated standard deviation were generated using SMOPS data from 2014 to 2021, soil moisture anomaly was calculated by the deviation from the historical norm and standard deviation for a target week, and drought levels were determined using the reference drought classification maps from the National Integrated Drought Information System (NIDIS). Global weekly drought level maps are generated using this system for all historical data. Drought level patterns over the CONUS domain are mostly consistent with the patterns observed in the NIDIS’ drought maps, indicating a good potential to use SMOPS blended soil moisture product as a drought monitoring information source. The differences observed in some regions are probably caused by the error in the weekly soil moisture anomaly maps since the blended soil moisture product could be highly affected by one satellite sensor when data from others are unavailable for that region. Another reason for the differences might be that drought levels are based on how far the anomaly is from the climatology's standard deviation, so areas with consistently low soil moisture values might not be classified as drought in some instances. The drought maps can detect some significant global drought events, e.g., the South American drought in 2015 affected by El Niño. A global drought level map can be generated for near real-time monitoring as soon as SMOPS data becomes available for the most recent week. Potential improvements of this study could include setting different drought level thresholds for specific regions with lower average soil moisture levels if they are not classified as drought but a drought is occurring.
Through the integration of multi-year climatology, anomaly assessment, and drought classification, this study introduces a systematic approach using SMOPS blended soil moisture product to drought monitoring on a global scale. The results demonstrate the potential of using satellite soil moisture products as a viable alternative for drought monitoring purposes and also improve our understanding of soil moisture's role in drought dynamics, thereby contributing to improved drought preparedness, response, and mitigation strategies.
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