A semi-empirical Boltzmann model is proposed to describe the relationship between the rate of temperature increase and soil moisture content, which can replace the existing complicated numerical iterative algorithm. The proposed method greatly simplifies the calculation process and improves the applicability of the passive distributed temperature sensing (PDTS) technology. A field test was performed in the Loess Plateau of China to validate the capability of this method. The field site has four typical land cover conditions: bare soil (G1), plastic mulch (G2), plastic mulch cover with potatoes (G3), and plastic much cover with maize (G4). The monitoring results indicate that for G1 and G2, the relationship between soil moisture content and the rate of temperature increase can be quantitatively described by the Boltzmann model with a root-mean-square error of 0.024 m3/m3. For G3, a linear relationship is found. In contrast, the PDTS technology is not applicable for G4 because a constant ground surface heat power from solar radiation and small air temperature fluctuations are preconditions of PDTS. If the coefficient of determination (R2) for fitting rate of temperature increase is larger than 0.9, the ground surface heat power by solar radiation can be considered as a constant.
This is a preview of subscription content, access via your institution.
We’re sorry, something doesn't seem to be working properly.
Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.
Benítez-Buelga J, Sayde C, Rodríguez-Sinobas L, Selker JS (2014) Heated fiber optic distributed temperature sensing: a dual-probe heat-pulse approach. Vadose Zone J 13:1–12. https://doi.org/10.2136/vzj2014.02.0014
Benítez-Buelga J, Rodríguez-Sinobas L, Sánchez Calvo R, Gil-Rodríguez M, Sayde C, Selker JS (2016) Calibration of soil moisture sensing with subsurface heated fiber optics using numerical simulation. Water Resour Res 52:2985–2995. https://doi.org/10.1002/2015WR017897
Bi Y, Qiu L, Zhakypbek Y, Jiang B, Cai Y, Sun H (2018) Combination of plastic film mulching and AMF inoculation promotes maize growth, yield and water use efficiency in the semiarid region of Northwest China. Agric Water Manag 201:278–286. https://doi.org/10.1016/j.agwat.2017.12.008
Cao DF, Shi B, Wei GQ, Chen SE, Zhu HH (2018a) An improved distributed sensing method for monitoring soil moisture profile using heated carbon fibers. Measurement 123:175–184. https://doi.org/10.1016/j.measurement.2018.03.052
Cao DF, Shi B, Loheide SP, Gong X, Zhu HH, Wei G, Yang L (2018b) Investigation of the influence of soil moisture on thermal response tests using active distributed temperature sensing (A-DTS) technology. Energy Build 173:239–251. https://doi.org/10.1016/j.enbuild.2018.01.022
Cao DF, Shi B, Zhu HH, Inyang H, Wei GQ, Zhang Y, Tang CS (2019) Feasibility investigation of improving the modified Green–Ampt model for treatment of horizontal infiltration in soil. Water 11(4):645. https://doi.org/10.3390/w11040645
Ciocca F, Lunati I, Van de Giesen N, Parlange MB (2012) Heated optical fiber for distributed soil-moisture measurements: a lysimeter experiment. Vadose Zone J 11(4):1–10. https://doi.org/10.2136/vzj2011.0199
Dobriyal P, Qureshi A, Badola R, Hussain SA (2012) A review of the methods available for estimating soil moisture and its implications for water resource management. J Hydrol 458–459:110–117. https://doi.org/10.1016/j.jhydrol.2012.06.021
Dong J, Steele-Dunne SC, Judge J, van de Giesen N (2015) A particle batch smoother for soil moisture estimation using soil temperature observations. Adv Water Resour 83:111–122. https://doi.org/10.1016/j.advwatres.2015.05.017
Dong J, Steele-Dunne SC, Ochsner TE, van de Giesen N (2016a) Determining soil moisture and soil properties in vegetated areas by assimilating soil temperatures. Water Resour Res 52:4280–4300. https://doi.org/10.1002/2015WR018425
Dong J, Steele-Dunne SC, Ochsner TE, van de Giesen N (2016b) Estimating soil moisture and soil thermal and hydraulic properties by assimilating soil temperature using a particle batch smoother. Adv Water Resour 91:104–116. https://doi.org/10.1016/j.advwatres.2016.03.008
Gadi VK, Garg A, Manogaran IP, Sekharan S, Zhu HH (2020) Understanding soil surface water content using light reflection theory: a novel color analysis technique considering variability in light intensity. J Test Eval 48(5):4053–4066. https://doi.org/10.1520/JTE20180320
Gil-Rodríguez M, Rodríguez-Sinobas L, Benítez-Buelga J, Sánchez-Calvo R (2013) Application of active heat pulse method with fiber optic temperature sensing for estimation of wetting bulbs and water distribution in drip emitters. Agric Water Manag 120:72–78. https://doi.org/10.1016/j.agwat.2012.10.012
He G, Wang Z, Cao H, Dai J, Li Q, Xue C (2018) Year-round plastic film mulch to increase wheat yield and economic returns while reducing environmental risk in dryland of the Loess Plateau. Field Crop Res 225:1–8. https://doi.org/10.1016/j.fcr.2018.05.019
Jonubi R, Rezaverdinejad V, Salemi H (2018) Enhancing field scale water productivity for several rice cultivars under limited water supply. Paddy Water Environ 16:125–141. https://doi.org/10.1007/s10333-017-0622-y
Mohanty BP, Cosh MH, Lakshmi V, Montzka C (2017) Soil moisture remote sensing: state-of-the-science. Vadose Zone J 16:1–9. https://doi.org/10.2136/vzj2016.10.010
Ramakrishna A, Tam HM, Wani SP, Long TD (2006) Effect of mulch on soil temperature, moisture, weed infestation and yield of groundnut in northern Vietnam. Field Crop Res 95:115–125. https://doi.org/10.1016/j.fcr.2005.01.030
Sayde C, Gregory C, Gil-Rodriguez M, Tufillaro N, Tyler S, van de Giesen N, English M, Cuenca R, Selker JS (2010) Feasibility of soil moisture monitoring with heated fiber optics. Water Resour Res 46:2840–2849. https://doi.org/10.1029/2009WR007846
Sayde C, Buelga JB, Rodriguez-Sinobas L, Khoury L, English M, van de Giesen N, Selker JS (2014) Mapping variability of soil water content and flux across 1–1000 m scales using the actively heated fiber optic method. Water Resour Res 50:7302–7317. https://doi.org/10.1002/2013WR014983
Sourbeer JJ, Loheide SP (2016) Obstacles to long-term soil moisture monitoring with heated distributed temperature sensing. Hydrol Process 30:1017–1035. https://doi.org/10.1002/hyp.10615
Steele-Dunne SC, Rutten MM, Krzeminska DM, Hausner M, Tyler SW, Selker J, Bogaard TA, van de Giesen NC (2010) Feasibility of soil moisture estimation using passive distributed temperature sensing. Water Resour Res 46(W03535):1–12. https://doi.org/10.1029/2009WR008272
Striegl AM, Loheide SP (2012) Heated distributed temperature sensing for field scale soil moisture monitoring. Groundwater 50:340–347. https://doi.org/10.1111/j.1745-6584.2012.00928.x
Susha LSU, Singh DN, Maryam SB (2014) A critical review of soil moisture measurement. Measurement 54:92–105. https://doi.org/10.1016/j.measurement.2014.04.007
Tan X, Shao D, Gu W (2018) Effects of temperature and soil moisture on gross nitrification and denitrification rates of a Chinese lowland paddy field soil. Paddy Water Environ 16:687–698. https://doi.org/10.1007/s10333-018-0660-0
Zhang GS, Hu XB, Zhang XX, Li J (2015) Effects of plastic mulch and crop rotation on soil physical properties in rain-fed vegetable production in the mid-Yunnan plateau, China. Soil Tillage Res 145:111–117. https://doi.org/10.1016/j.still.2014.09.010
Zhang XX, Zhao J, Yang L (2019) Ridge-furrow mulching system regulates diurnal temperature amplitude and wetting-drying alternation behavior in soil to promote maize growth and water use in a semiarid region. Field Crop Res 233:121–130. https://doi.org/10.1016/j.fcr.2019.01.009
Zubelzu S, Rodriguez-Sinobas L, Saa-Requejo A, Benitez J, Tarquis AM (2019) Assessing soil water content variability through active heat distributed fiber optic temperature sensing. Agric Water Manag 212:193–202. https://doi.org/10.1016/j.agwat.2018.08.008
The financial support provided by the National Key Research and Development Programme of China (Grant Nos. 2018YFC1505104, 2018YFC1802303), the National Natural Science Foundation of China (Grant Nos. 41907244 and 41722209), the China Postdoctoral Science Foundation (Grant No. 2019M653180), the Fundamental Research Funds for the Central University (Grant No. 19lgpy254), and the Department of Housing and Urban-Rural Development of Gansu Province (Grant. No. JK2019-05) are gratefully acknowledged.
Conflict of interest
There is no conflict of interest.
About this article
Cite this article
Cao, Df., Zhu, Hh., Guo, C. et al. Passive distributed temperature sensing (PDTS)-based moisture content estimation in agricultural soils under different vegetative canopies. Paddy Water Environ (2021). https://doi.org/10.1007/s10333-021-00839-6
- Soil moisture
- Field soil moisture monitoring
- Loess Plateau
- Optical fibre
- Distributed fibre optic sensing (DFOS)