TY - JOUR
T1 - Propagation of soil moisture sensing uncertainty into estimation of total soil water, evapotranspiration and irrigation decision-making
AU - Sharma, Kiran
AU - Irmak, Suat
AU - Kukal, Meetpal S.
N1 - Funding Information:
This manuscript is a part of a long-term research that continues to investigate the fundamentals, performance and feasibility of different soil moisture and other soil properties measurement technologies in different soil types with various cropping systems in the Irmak Research Laboratory. The work presented in this paper was included as part of the first author's MS study while she was a graduate student in the Irmak Research Laboratory at the University of Nebraska-Lincoln under the supervision of Professor Suat Irmak. Meetpal S. Kukal was an MS and Ph.D. student under Professor Irmak's supervision and is currently a post-doctoral research associate with Professor Irmak. This project was partially supported by a grant obtained from the National Science Foundation (NSF) under the project number CNS-1619285. Professor Suat Irmak acknowledges NSF and Irmak Research Laboratory members who assisted in this project. This research is partially based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Professor Irmak's Hatch Project, under the Project Number NEB-21-155. The trade names or commercial products are provided solely for the information of the reader and do not constitute a recommendation for use by the authors or their institutions.
Funding Information:
This manuscript is a part of a long-term research that continues to investigate the fundamentals, performance and feasibility of different soil moisture and other soil properties measurement technologies in different soil types with various cropping systems in the Irmak Research Laboratory. The work presented in this paper was included as part of the first author’s MS study while she was a graduate student in the Irmak Research Laboratory at the University of Nebraska-Lincoln under the supervision of Professor Suat Irmak. Meetpal S. Kukal was an MS and Ph.D. student under Professor Irmak’s supervision and is currently a post-doctoral research associate with Professor Irmak. This project was partially supported by a grant obtained from the National Science Foundation (NSF) under the project number CNS-1619285. Professor Suat Irmak acknowledges NSF and Irmak Research Laboratory members who assisted in this project. This research is partially based upon work that is supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Professor Irmak’s Hatch Project, under the Project Number NEB-21-155. The trade names or commercial products are provided solely for the information of the reader and do not constitute a recommendation for use by the authors or their institutions.
Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - Soil moisture sensors are subject to uncertainty (inaccuracy) in measuring soil water status, that hinders various applications. User groups (researchers and growers/advisers) rely on these sensors for estimating critical agricultural water management decisions and information such as total soil water in the crop root zone (TSW), crop evapotranspiration (ETc) and predicting irrigation triggers (IT), i.e., when TSW is equal to or lower than readily available water. There is a lack of translation of errors in sensor-reported soil moisture (θv) into TSW, ETc, and IT, which is critical to farm-level decision-making as well as research assessments. Nine soil moisture sensors (based on principles of time-domain reflectometry, capacitance and electrical resistance) were investigated in field conditions for silt loam and loamy sand soils under two installation orientations (vertical and horizontal) during two growing seasons (2017 and 2018). Accurate representation of TSW, ETc, and IT was found to be a function of sensor-type, soil-type as well as calibration-type [factory calibration (F.C.) vs. site-specific calibration (S.S.C.)]. Sensor installation orientation did not affect sensor accuracy. Uncertainties in estimation of TSW, ETc and IT were quantified under each condition of use, and sensors were comparatively ranked for effective selection. It was found that all sensors underestimated ETc in silt loam soil. The deviation of sensor-measured ETc from true ETc ranged from −14 to −31 %, which implies that the choice of sensor under a given soil type impacts the quantification of consumptive use of the soil-vegetation system being monitored. Sensors showed both overstimation and underestimation of ETc in loamy sand soil with deviations of sensor-estimated ETc from true ETc ranging from 14 to −61 %. The S.S.C. resulted in 45 and 17 % improvement in TSW and ETc in silt loam soil, respectively, and 42, 80 and 86 % improvement observed in TSW, IT and ETc in loamy sand soil, respectively. The research findings showed that suitability of soil moisture sensors can differ when different target metrics are used as criteria. These findings emphasize the need for evaluating soil moisture sensors based on practical and application-oriented criteria, in addition to reliance on θv accuracy. To the best of authors’ knowledge, this research is the first to translate traditional θv accuracy assessments into practical and application-oriented criteria and use them to evaluate sensors for these specific applications. Sensor rankings and uncertainty associated with their use presented here will allow diverse users to effectively identify sensors for targeted applications in water management decision-making and research.
AB - Soil moisture sensors are subject to uncertainty (inaccuracy) in measuring soil water status, that hinders various applications. User groups (researchers and growers/advisers) rely on these sensors for estimating critical agricultural water management decisions and information such as total soil water in the crop root zone (TSW), crop evapotranspiration (ETc) and predicting irrigation triggers (IT), i.e., when TSW is equal to or lower than readily available water. There is a lack of translation of errors in sensor-reported soil moisture (θv) into TSW, ETc, and IT, which is critical to farm-level decision-making as well as research assessments. Nine soil moisture sensors (based on principles of time-domain reflectometry, capacitance and electrical resistance) were investigated in field conditions for silt loam and loamy sand soils under two installation orientations (vertical and horizontal) during two growing seasons (2017 and 2018). Accurate representation of TSW, ETc, and IT was found to be a function of sensor-type, soil-type as well as calibration-type [factory calibration (F.C.) vs. site-specific calibration (S.S.C.)]. Sensor installation orientation did not affect sensor accuracy. Uncertainties in estimation of TSW, ETc and IT were quantified under each condition of use, and sensors were comparatively ranked for effective selection. It was found that all sensors underestimated ETc in silt loam soil. The deviation of sensor-measured ETc from true ETc ranged from −14 to −31 %, which implies that the choice of sensor under a given soil type impacts the quantification of consumptive use of the soil-vegetation system being monitored. Sensors showed both overstimation and underestimation of ETc in loamy sand soil with deviations of sensor-estimated ETc from true ETc ranging from 14 to −61 %. The S.S.C. resulted in 45 and 17 % improvement in TSW and ETc in silt loam soil, respectively, and 42, 80 and 86 % improvement observed in TSW, IT and ETc in loamy sand soil, respectively. The research findings showed that suitability of soil moisture sensors can differ when different target metrics are used as criteria. These findings emphasize the need for evaluating soil moisture sensors based on practical and application-oriented criteria, in addition to reliance on θv accuracy. To the best of authors’ knowledge, this research is the first to translate traditional θv accuracy assessments into practical and application-oriented criteria and use them to evaluate sensors for these specific applications. Sensor rankings and uncertainty associated with their use presented here will allow diverse users to effectively identify sensors for targeted applications in water management decision-making and research.
UR - http://www.scopus.com/inward/record.url?scp=85089947365&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85089947365&partnerID=8YFLogxK
U2 - 10.1016/j.agwat.2020.106454
DO - 10.1016/j.agwat.2020.106454
M3 - Article
AN - SCOPUS:85089947365
SN - 0378-3774
VL - 243
JO - Agricultural Water Management
JF - Agricultural Water Management
M1 - 106454
ER -