Subsoil Moisture: A Forgotten Drought Indicator

Drought monitoring and prediction are critical for agricultural planning, water resource management, and environmental protection. While numerous drought indicators exist, subsoil moisture - the water content in deeper soil layers - represents a valuable but often overlooked indicator with unique properties and advantages. Research demonstrates that subsoil moisture provides crucial information during extended drought periods, offers early warning capabilities, and exhibits strong correlation with agricultural productivity. Despite these benefits, technical challenges in measurement and interpretation have limited its widespread adoption. This comprehensive report examines subsoil moisture's role as a drought indicator, why it's often forgotten, and its future potential in integrated drought monitoring systems.

Understanding Subsoil Moisture

Definition and Importance

Subsoil moisture refers to the water content in soil layers below the topsoil, typically from six inches to 3-4 feet below the surface. While topsoil (the upper six inches) responds quickly to precipitation and evaporative demand, subsoil moisture changes more gradually and provides a longer-term indicator of water availability3. This distinction is crucial for understanding drought dynamics, as different soil depths respond to water deficits at different rates.

Soil moisture in general is essential to plants for four primary reasons: it constitutes 80–95% of the plant's protoplasm, it is essential for photosynthesis, it serves as the solvent in which nutrients are carried throughout the plant, and it provides the turgidity necessary for plants to maintain proper position1. The deeper subsoil moisture specifically becomes critical during periods of limited precipitation when plants must access water stored below the surface.

The moisture content of soil depends on numerous factors including texture, structure, organic matter content, density, temperature, salinity, and depth2. These factors influence how water moves through the soil profile and becomes available to plants, making subsoil moisture behavior complex but informative for drought monitoring.

Measurement Methods

Several methods exist for measuring subsoil moisture:

Direct (Gravimetric) Methods: Taking physical soil samples and measuring water content by weight2. This provides accurate point measurements but is labor-intensive and destructive.
Neutron Probes: One of the more accurate devices for measuring soil moisture. The probe contains a source of fast neutrons and is lowered into the soil down an access tube where neutrons interact with soil water. The density of the neutron flux depends on the amount of water in the surrounding soil5.
Time Domain Reflectometry (TDR): Measures the velocity of electromagnetic waves in the soil, which are slowed by soil moisture. These measurements are very accurate and come factory-calibrated6.
Frequency Domain Reflectometry (FDR): Similar to TDR but uses frequency changes to determine soil moisture content6.
Capacitance Probes: Multi-depth sensors can measure at various depths (10-90cm) simultaneously, providing detailed soil moisture profiles46.
Dielectric Sensors: Measure soil's dielectric properties, which change with water content.
Remote Sensing: Satellite-based measurements like NASA's SMAP (Soil Moisture Active Passive) mission provide soil moisture data across large areas15.
Electrical Resistance Blocks: Measure resistance changes associated with soil moisture. These are generally reliable, easy to use, and suitable for most soil types except clays, gravel, very coarse sand, or peat6.

Most accurate measurements of subsoil moisture require in-situ sensors placed at appropriate depths, though these can be costly and impractical for large-scale monitoring.

Subsoil Moisture as a Drought Indicator

Relationship to Drought Assessment

Research shows that subsoil moisture serves as a critical drought indicator with distinct advantages:

Deep soil moisture (90-100cm) correlates strongly with longer-term drought conditions8
Provides crucial information during extended drought periods
Can offer early warning of drought onset in many contexts
Shows high correlation with agricultural productivity
Has a "memory effect" that persists longer than surface indicators

The correlation between soil moisture and drought indices varies by depth. Studies have found that the majority of stations show an optimum time scale of 1–3 months for correlations with shallow soil moisture (0–5 cm), while deeper soil moisture (90–100cm) correlates best with longer timescales of 9–12 months8. This suggests that subsoil moisture is particularly valuable for monitoring long-term drought conditions.

Research also indicates that soil moisture observations were drier than usual prior to U.S. Drought Monitor onset for nearly 80% of events and worsening drought weeks9. This demonstrates subsoil moisture's potential as an early warning indicator, particularly during the initial and final stages of drought events.

Comparison with Other Drought Indicators

Common drought indicators include:

Standardized Precipitation Index (SPI): Based solely on precipitation10
Palmer Drought Severity Index (PDSI): Combines precipitation, temperature, and soil moisture10
Vegetation Indices (NDVI): Based on satellite measurements of vegetation health
Surface Soil Moisture: Measures only the top layer of soil

Subsoil moisture stands out because:

It's rated very effective across all climate zones
Provides a more stable signal than surface soil moisture
Correlates well with actual plant water availability
Responds to cumulative water deficits over longer periods
Less influenced by short-term weather fluctuations

Comparative analysis shows that drought indices from a two-layer bucket model (like the PDSI) have a higher correlation with soil moisture within 30–100cm depth than with the surface layer8. This underscores the value of subsoil information in drought assessment, particularly for sustained drought conditions.

Why It's Often Forgotten

Despite its value, subsoil moisture is often overlooked as a drought indicator due to:

Measurement Challenges: Difficulty in measuring at deeper soil layers
Temporal Lag: Slower response compared to surface indicators9
Technical Difficulties: Challenges in data acquisition and interpretation
Spatial Inconsistency: Variations in readings across different soil types and regions
Limited Historical Data: Less historical data compared to precipitation records
Cost and Resources: Higher cost of installation and maintenance of deep soil sensors

The utility of deeper soil depths for drought monitoring is hampered by this temporal lag, which can cause soil moisture conditions at those depths to misalign with current drought conditions9. This is particularly evident during rapidly evolving drought situations, where more responsive surface indicators might be preferred.

Current Technologies and Applications

Modern Monitoring Technologies

Current technologies for subsoil moisture monitoring include:

Advanced Sensor Networks: Modern wireless sensor networks with multiple depth capabilities. The Sensoterra Multi Depth sensor, for example, measures soil moisture at six different depths (10, 20, 30, 45, 60, and 90 cm) with hourly measurements and 6-8 years of battery life4.
Satellite Remote Sensing: NASA's SMAP (Soil Moisture Active Passive) satellite provides soil moisture data across large areas. SMAP data products include surface (5 cm) and root zone (1 m) soil moisture measurements15.
Integrated Monitoring Systems: Systems that combine in-situ measurements with modeling, such as the Integrated Drought Monitoring and Prediction System, which incorporates soil moisture as a key component20.
Zero-calibration Sensors: Newer sensors that provide accurate readings immediately upon installation, minimizing calibration requirements418.
Wireless Mesh Networks: Ensure dependable communication from remote sensors, making data collection more reliable even in challenging environments418.

Case Studies

Several notable applications demonstrate the value of subsoil moisture monitoring:

Colorado River Headwaters Networks: The iRON and YBASIN networks provide data for water resource management in the headwaters region of the Colorado River. These networks collect recurrent data on soil moisture at multiple depths across mountain watersheds14.
NASA's SMAP Applications: Research showing correlations between soil moisture changes and drought intensity. The change in soil moisture over a four-week interval correlates well with one-month SPI values, suggesting that short-term negative soil moisture change may indicate a lack of precipitation, while persistent long-term change indicates severe drought conditions15.
Central Mediterranean Research: Demonstrated that seasonal forecasts can detect wet and dry events in deep soil layers with 6-month lead times. The study successfully predicted the 2012 drought in Italy with a 6-month lead time16.
U.S. Department of Agriculture: Uses soil moisture to improve crop yield forecasts, particularly in areas lacking good precipitation data. SMAP soil moisture enhances the USDA FAS's ability to predict the availability of root-zone soil water for plant growth and development15.

Practical Applications and Limitations

Benefits of Monitoring Subsoil Moisture

Key advantages include:

Early Drought Detection: Identifies developing drought before visible plant symptoms appear
Precision Irrigation Management: Enables more efficient water use by providing accurate information about water availability in the root zone. This is particularly valuable as water resources become more constrained.
Improved Forecast Accuracy: Provides lead times of up to 6 months for drought predictions16. The Central Mediterranean study demonstrated the capacity of seasonal forecasting models to predict drought events with significant lead time when incorporating subsoil moisture data.
Enhanced Drought Risk Protection: Better information for agricultural planning and risk management. Understanding subsoil moisture conditions helps farmers make more informed decisions about planting, fertilization, and irrigation schedules.
Stable Indicators: The "memory effect" of subsoil moisture contributes significantly (91±3%) to sub-seasonal forecast skill. This stability makes it particularly valuable for medium-term planning.
Improved Water Management: Facilitates better allocation of water resources by providing a more complete picture of water availability throughout the soil profile.

Limitations and Challenges

Primary challenges include:

Measurement Difficulties: Challenging to measure accurately at deeper levels due to access limitations and soil disturbance during sensor installation5.
Data Interpretation Issues: Spatial inconsistency and residual trends in data can make interpretation difficult, particularly when comparing across regions with different soil types.
Soil Property Variations: Different soil types affect moisture behavior, requiring calibration and adjustment of measurements2.
Regional Climate Differences: Varying response patterns in different climate zones must be accounted for when interpreting subsoil moisture data.
Lag Time: Slower response in deep soil compared to surface indicators limits usefulness for detecting rapid-onset drought conditions9.
Non-uniform Water Movement: Water can travel through soil in branching patterns rather than uniformly, making point measurements potentially unrepresentative of larger areas.
Environmental Factors: Freezing, soil type variations, and other factors can affect readings and require careful data quality control7.

Future Directions and Integration

Solutions to Monitoring Challenges

Emerging solutions include:

Advanced Sensor Technologies: TDR, FDR, and capacitance-based sensors with improved accuracy and reliability are becoming more widely available and affordable6.
Satellite Remote Sensing: Enhanced capabilities for large-area monitoring with higher resolution through platforms like SMAP provide increasing coverage of soil moisture conditions15.
Integrated Systems: Combined sensor networks with data platforms for comprehensive monitoring bring together different measurement approaches to overcome individual limitations.
Wireless Networks: More reliable data transmission from remote locations helps ensure continuous monitoring without data gaps4.
Zero-calibration Sensors: Immediate accurate readings without complex calibration requirements reduce the technical expertise needed for deployment4.
Deep Learning Models: LSTM (Long Short-Term Memory) and other AI approaches for improved prediction can help interpret complex soil moisture patterns and their relationship to drought.
Emergent Constraint Techniques: Reducing uncertainty in climate model projections helps improve long-term drought forecasting when incorporating soil moisture data.

Integration with Other Drought Indicators

Several integrated approaches show promise:

Combined Drought Indicator (CDI): Integrates SPI, soil moisture, and vegetation data with three warning levels7 21:
- Watch: When precipitation shortage occurs
- Warning: When precipitation shortage translates to soil moisture shortage
- Alert: When both affect vegetation
Multivariate Standardized Drought Index (MSDI): Uses both precipitation and soil moisture to identify drought episodes that single-parameter indicators might miss22. It's particularly helpful for identifying drought episodes where typical precipitation-based indicators or soil-moisture-based indicators alone may not indicate the presence of drought.
National Coordinated Soil Moisture Monitoring Network (NCSMMN): Aims to integrate diverse data sources into consistent nationwide products19. This initiative integrates soil moisture data from various existing in-situ monitoring networks throughout the United States into a consistent set of data products.
High-resolution Soil Moisture Drought Index (HSMDI): Evaluates meteorological, agricultural, and hydrological droughts using high-resolution soil moisture data.
Integrated Drought Monitoring and Prediction System: Combines streamflow, groundwater, and soil moisture data with seasonal forecasts20. This system links to climate forecasts to assess and download rainfall forecasts, then models streamflow, groundwater, and soil moisture components.

These integrated approaches provide more comprehensive drought assessment than single indicators alone, with subsoil moisture playing a crucial role in improving drought forecasting lead times and accuracy.

Conclusion

Subsoil moisture represents a valuable but often overlooked component of drought monitoring systems. Its ability to reflect longer-term water availability conditions makes it particularly useful for agricultural planning, water resource management, and early drought detection. While challenges in measurement and interpretation have limited its widespread adoption in the past, emerging technologies and integrated monitoring approaches are increasingly incorporating subsoil moisture data.

The future of drought monitoring likely lies in comprehensive systems that integrate multiple indicators, including subsoil moisture, to provide more accurate, timely, and relevant drought information. As climate change increases the frequency and severity of droughts worldwide, the importance of all available drought indicators, especially those with predictive capabilities like subsoil moisture, will only grow. By recognizing the unique value of this "forgotten" indicator, we can develop more robust drought monitoring and early warning systems to mitigate drought impacts.Citations:

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