Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture

Area of Science:

• Environmental Science
• Hydrology
• Agricultural Science

Background:

• The soil moisture daily diagnostic equation (SMDE) traditionally uses day of the year (DOY) to estimate seasonal soil moisture loss.
• DOY has been a proxy for environmental factors like temperature, wind speed, and solar radiation.
• Accurate soil moisture estimation is vital for understanding earth-atmospheric processes and biogeochemical cycles.

Purpose of the Study:

• To enhance the accuracy of the soil moisture daily diagnostic equation (SMDE).
• To investigate the impact of incorporating actual and clear sky solar radiation into the SMDE's loss function coefficient.
• To improve the estimation of soil moisture loss by accounting for more precise environmental drivers.

Main Methods:

• Introduced actual solar radiation and clear sky solar radiation parameters into the SMDE loss function coefficient.
• Applied the enhanced SMDE to analyze 2 years of rainfall and soil moisture data from four USDA SCAN sites.
• Evaluated the changes in correlation coefficient and root mean square errors (RMSEs) for volumetric soil moisture estimations.

Main Results:

• The correlation coefficient between observed soil moisture and B values increased by an average of 2.3%.
• Root mean square errors (RMSEs) for volumetric soil moisture estimation across various depths (0-100 cm) decreased by an average of 8.6%.
• The inclusion of solar radiation data demonstrated a significant improvement in SMDE accuracy.

Conclusions:

• Incorporating actual solar radiation data into the soil moisture daily diagnostic equation (SMDE) demonstrably improves its accuracy.
• The enhanced SMDE provides more reliable soil moisture loss estimations compared to methods relying solely on DOY.
• This advancement offers better insights into hydrological processes and agricultural water management.