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Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9753742/ https://www.ncbi.nlm.nih.gov/pubmed/36530408 http://dx.doi.org/10.7717/peerj.14561 |
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author | Omotere, Olumide Pan, Feifei Wang, Lei |
author_facet | Omotere, Olumide Pan, Feifei Wang, Lei |
author_sort | Omotere, Olumide |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9753742 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97537422022-12-16 Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture Omotere, Olumide Pan, Feifei Wang, Lei PeerJ Soil Science 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. PeerJ Inc. 2022-12-12 /pmc/articles/PMC9753742/ /pubmed/36530408 http://dx.doi.org/10.7717/peerj.14561 Text en © 2022 Omotere et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Soil Science Omotere, Olumide Pan, Feifei Wang, Lei Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture |
title | Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture |
title_full | Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture |
title_fullStr | Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture |
title_full_unstemmed | Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture |
title_short | Using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture |
title_sort | using solar radiation data in soil moisture diagnostic equation for estimating root-zone soil moisture |
topic | Soil Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9753742/ https://www.ncbi.nlm.nih.gov/pubmed/36530408 http://dx.doi.org/10.7717/peerj.14561 |
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