Study on calibration model of soil water content based on actively heated fiber-optic FBG method in the in-situ test

Monitoring volumetric soil water content (θv) is the key for assessing water availability and nutrient fluxes. This study evaluated the empirical accuracy of θv measurements using standard and in situ calibrated frequency domain reflectometers (FDR) with gravimetric water content and bulk density measurements of 1512 samples gathered from 15 profiles across 5 ICP Forests level II intensive monitoring plots. The predicted θv, calibrated with standard functions, predominantly underestimated the real water content. The measurement error exceeded the threshold of 0.03 m3 m−3 in 93% of all soil layers. Layer specific calibration removed bias and reduced the overall prediction error with a factor up to 2.8. A simple linear regression often provided the best calibration model; temperature correction was helpful in specific cases. To adequately remove bias in our study plots, a calibration dataset of up to 24 monthly observations was required for topsoils (whereas 12 observations sufficed for subsoils). Based on estimated precision errors, 3 sensors per soil layer proved to be sufficient, while up to 16 sensors are needed to meet the required accuracy in organic topsoils. Validating FDR sensor outputs using in situ gravimetric measurements is essential for quality control and assurance of long term θv monitoring and for improving site specific instrumentalization.

Download Full-text

Measuring Soil Water Content in Situ using Time-domain Reflectometry Techniques

10.4095/102748 ◽

1977 ◽

Author(s):

A P Annan ◽

J L Davis ◽

G C Topp

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Time Domain ◽

Time Domain Reflectometry

Download Full-text

Mapping variability of soil water content and flux across 1-1000 m scales using the Actively Heated Fiber Optic method

Water Resources Research ◽

10.1002/2013wr014983 ◽

2014 ◽

Vol 50 (9) ◽

pp. 7302-7317 ◽

Cited By ~ 30

Author(s):

Chadi Sayde ◽

Javier Benitez Buelga ◽

Leonor Rodriguez-Sinobas ◽

Laureine El Khoury ◽

Marshall English ◽

...

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Fiber Optic

Download Full-text

An in situ probe-spacing-correction thermo-TDR sensor to measure soil water content accurately

European Journal of Soil Science ◽

10.1111/ejss.12718 ◽

2018 ◽

Vol 69 (6) ◽

pp. 1030-1034 ◽

Cited By ~ 4

Author(s):

M. M. Wen ◽

G. Liu ◽

R. Horton ◽

K. Noborio

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Probe Spacing

Download Full-text

Development and Validation of a New Calibration Model for Diviner 2000® Probe Based on Soil Physical Attributes

Water ◽

10.3390/w12123414 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3414

Author(s):

Giuseppe Provenzano ◽

Giovanni Rallo ◽

Ceres Duarte Guedes Cabral de Almeida ◽

Brivaldo Gomes de Almeida

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Efficiency Index ◽

Calibration Model ◽

Volumetric Soil Water Content ◽

Physical Attributes ◽

Water Volumes ◽

Development And Validation ◽

Mean Square Errors

This study aimed to develop a new model, valid for soil with and without expandable characters, to estimate volumetric soil water content (θ) from readings of scaled frequency (SF) acquired with the Diviner 2000® sensor. The analysis was carried out on six soils collected in western Sicily, sieved at 5 mm, and repacked to obtain the maximum and minimum bulk density (ρb). During an air-drying process SF values, the corresponding gravimetric soil water content (U) and ρb were monitored. In shrinking/swelling clay soils, due to the contraction process, the variation of dielectric permittivity was affected by the combination of the mutual proportions between the water volumes and the air present in the soil. Thus, to account for the changes of ρb with U, the proposed model assumed θ as the dependent variable being SF and ρb the independent variables; then the model’s parameters were estimated based on the sand and clay fractions. The model validation was finally carried out based on data acquired in undisturbed monoliths sampled in the same areas. The estimated θ, θestim, was generally close to the corresponding measured, θmeas, with Root Mean Square Errors (RMSE) generally lower than 0.049 cm3 cm−3, quite low Mean Bias Errors (MBE), ranging between −0.028 and 0.045 cm3 cm−3, and always positive Nash-Sutcliffe Efficiency index (NSE), confirming the good performance of the model.

Download Full-text

Definition of soil water content and rainfall thresholds for landslide occurrence

10.5194/egusphere-egu2020-16688 ◽

2020 ◽

Cited By ~ 1

Author(s):

Luca Piciullo ◽

Graham Gilbert

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Climate Adaptation ◽

Early Warning Systems ◽

In Situ Measurements ◽

Physical Parameters ◽

Rainfall Thresholds ◽

Reanalysis Dataset

In the last decades, rainfall thresholds for landslide occurrences were thoroughly investigated, producing several different test cases and relevant technical and scientific advances. However, a recent literature review on rainfall thresholds articles (Segoni et al., 2018), published in journals indexed in SCOPUS or ISI Web of knowledge databases in the period 2008-2016, highlighted significant advances and critical issues about this topic. Only in the 11% of the analysed papers (a total of 115) there were installed instruments for measuring physical parameters other than rainfall. The implication was that, in most cases, the occurrence of landslides was forecasted considering exclusively a rainfall correlation, completely neglecting soil characteristics.A reanalysis dataset (ERA5-Land) providing a consistent view of the evolution of land variables over several decades at an enhanced resolution has been used to evaluate the soil water content. Reanalysis combines numerical model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. A comparison between in situ measurements with the results of the model has been carried out for two sites in Norway (Eidsvoll, Morsa catchmen) with 3 different vegetation types: grass, bush, tree. The results showed a good agreement between the modelled soil water content layer 2 and 3 (respectively representing 2 - 28 cm and 28 -100 cm depths) and, respectively, in-situ measurements at 30 and 50 cm depths.Then, 15 Norwegian basins with moraine and peat covers and, previous landslide occurrences in the period 2009-2018, have been selected for correlations. Combinations of rainfall and soil water contents that triggered and not-triggered landslides have been analysed. Rainfall-soil water content thresholds have been defined for the selected basins highlighting the important role played by soil water content, together with rainfall, in triggering landslides. The use of the soil water content contributed to increase the performance of the thresholds and to reduce the uncertainties of landslide forecast.This paper has been conceived in the context of the project "Klima 2050-Risk reduction through climate adaptation of buildings and infrastructure" http://www.klima2050.no/, and it is included into Work Package 3.3-Early warning systems.&#160;

Download Full-text

Field calibration of ThetaProbe (ML2x) and ECHO probe (EC-20) soil water sensors in a Black Vertosol

Soil Research ◽

10.1071/sr06156 ◽

2007 ◽

Vol 45 (3) ◽

pp. 233 ◽

Cited By ~ 10

Author(s):

J. L. Foley ◽

E. Harris

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Clay Soils ◽

Deep Drainage ◽

Swelling Clay ◽

Field Calibration ◽

Volumetric Measurements

Past studies have shown that soil-specific calibrations are required to attain a higher level of accuracy when measuring soil water content with ThetaProbe and ECHO probe soil water sensors, particularly in swelling clay soils. Both probes were assessed for their capacity to accurately monitor soil water in a deep drainage study on a Black Vertosol. Probes were trialled in situ and calibrated against hand-sampled volumetric measurements. The generic calibrations given by the manufacturers resulted in significant errors in water content estimates for both probes. Using the generic calibration, ECHO probes under-estimated water content by 0.10–0.2 m3/m3, whereas ThetaProbes under-estimated by 0.04 m3/m3 at the wet end and over-estimated by 0.08 m3/m3 at the dry end. The soil-specific calibrations significantly improved the accuracy of both probes. ThetaProbes were chosen for the drainage study. The calibration allowed for accuracy across the full wet–dry range to within 0.001–0.004 m3/m3 of volumetric measurements. ECHO probes were less accurate at the wet end, but still determined soil water content to within 0.02–0.05 m3/m3 of volumetric measurements.

Download Full-text

Evaluating Soil Water Content in a WRF-Noah Downscaling Experiment

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-0239.1 ◽

2013 ◽

Vol 52 (10) ◽

pp. 2312-2327 ◽

Cited By ~ 22

Author(s):

Peter Greve ◽

Kirsten Warrach-Sagi ◽

Volker Wulfmeyer

Keyword(s):

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Land Surface ◽

Root Zone ◽

Regional Scale ◽

Land Surface Model ◽

Surface Model ◽

Flux Partitioning

AbstractSoil water content (SWC) depends on and affects the energy flux partitioning at the land–atmosphere interface. Above all, the latent heat flux is limited by the SWC of the root zone on one hand and radiation on the other. Therefore, SWC is a key variable in the climate system. In this study, the performance of the Weather Research and Forecasting model coupled with the Noah land surface model (WRF-Noah) system in a climate hindcast simulation from 1990 to 2008 is evaluated with respect to SWC versus two reanalysis datasets for Europe during 2007 and 2008 with in situ soil moisture observations from southern France. When compared with the in situ observations, WRF-Noah generally reproduces the SWC annual cycle while the reanalysis SWCs do not. The biases in areal mean WRF-Noah SWCs relate to biases in precipitation and evapotranspiration in a cropland environment. The spatial patterns and temporal variability of the seasonal mean SWCs from the WRF-Noah simulations and from the two reanalyses correspond well, while absolute values differ significantly, especially at the regional scale.

Download Full-text