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

Author:

Omotere Olumide1,Pan Feifei2,Wang Lei1ORCID

Affiliation:

1. Geography & Anthropology, Louisiana State University and Agricultural and Mechanical College, Baton Rouge, Louisiana, USA

2. Geography and The Environment, University of North Texas, Denton, Texas, USA

Abstract

The soil moisture daily diagnostic equation (SMDE) evaluates the relationship between the loss function coefficient and the summation of the weighted average of precipitation. The loss function coefficient uses the day of the year (DOY) to approximate the seasonal changes in soil moisture loss for a given location. Solar radiation is the source of the energy that drives the complex and intricates of the earth-atmospheric processes and biogeochemical cycles in the environment. Previous research assumed DOY is the approximation of other environmental factors (e.g., temperature, wind speed, solar radiation). In this article, two solar radiation parameters were introduced,i.e., the actual solar radiation and the clear sky solar radiation and were incorporated into the loss function coefficient to improve its estimation. This was applied to 2 years of continuous rainfall, soil moisture data from USDA soil climate network (SCAN) sites AL2053, GA2027 MS2025, and TN2076. It was observed that the correlation coefficient between the observed soil moisture and B values (which is the cumulated average of rainfall to soil moisture loss) increased on average by 2.3% and the root mean square errors (RMSEs) for estimating volumetric soil moisture at columns 0–5, 0–10, 0–20, 0–50, 0–100 cm reduced on average by 8.6% for all the study sites. The study has confirmed that using actual solar radiation data in the soil moisture daily diagnostic equation can improve its accuracy.

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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