Summary of Advances in Heat-Pulse Methods: Measuring Near-Surface Soil Water Content

Surface layer soil water content is important for evaporation, surface energy balance, seed germination, residue decomposition, microbial activity, and many other biological, chemical, and physical processes. The standard method (i.e., the gravimetric method) for measuring soil water content requires destructive sampling and is unsuitable for continuous measurement. Techniques such as neutron thermalization and time domain reflectometry suffer relatively large errors in measuring soil water content near the surface. In a recent Methods of Soil Analysis article, the authors present the principles and procedures for using a heat-pulse sensor to determine near-surface soil water content

Investigating Time-Scale Effects on Reference Evapotranspiration from Epan Data in North China

Reference evapotranspiration (ETo) and pan evaporation (Epan) are key parameters in hydrological and meteorological studies. The authors’ objectives were to evaluate the ratio of ETo to Epan (kp) at daily and monthly scales and to predict average ETo in the following years using calibrated kp and observed Epan at the two time scales. Using 50 yr of data obtained at six typical sites in north China, daily and monthly ETo were calculated using the Food and Agriculture Organization estimation method (FAO-56) Penman–Monteith equation, and kp values were determined at the two time scales. Values of kp varied from 0.457 to 0.589 daily and from 0.392 to 0.528 monthly for the six sites. Both daily and monthly kpcould be fitted as multilinear functions of longitude, latitude, elevation, and relative humidity. Relatively accurate predictions of daily mean ETo for the subsequent years following the calibration years at all six sites were obtained when the year number L used for calibrating daily mean kp was sufficient (\u3e38). In cases when large deviations occurred between average kp for the L calibration years and the actual kp of the following (L + 1)th year, relatively large prediction errors resulted. For the monthly scale, soil heat flux G fluctuated periodically. When variations of G were included, the calculated monthly ETo values were smaller than the monthly ETo cumulated from daily ETo. Thus, monthly kp values were smaller than daily kp values. Predictions of monthly ETo in 2001 for the six sites were relatively accurate with relative errors ranging from −11.9% to 12.1%. In conclusion, this method is simple and accurate with a small demand for weather data

Approaches for estimating unsaturated soil hydraulic conductivities at various bulk densities with the extended Mualem-van Genuchten model

The Mualem-van Genuchten model has been widely used for estimating unsaturated soil hydraulic conductivity (Ku) from measured saturated hydraulic conductivity (Ks) and fitted water retention curve (WRC) parameters. Soil bulk density (ρb) variations affect the accuracy of Ku estimates. In this study, we extend the Mualem-van Genuchten model to account for the ρb effect with ρb-related WRC and Ks models. We apply two functions (A and B) that relate the van Genuchten WRC model to ρb and two models (1 and 2) that estimate Ks with various ρb. By combining the ρb-related WRC functions and Ks models, we develop four integrated approaches (i.e., A1, A2, B1, and B2) for estimating Ku at various ρb. Kumeasurements made on five soils with various textures and ρb are used to evaluate the accuracy of the four approaches. The results show that all approaches produce reasonable Ku estimates, with average root mean square errors (RMSEs) less than 0.35 (expressed in dimensionless unit because logarithmic Ku values are used). Approach A2, with an average RMSE of 0.25, agrees better with Ku measurements than does Approach A1 that has an average RMSE of 0.28. This is because Model 2 accounts for the WRC shape effect near saturation. Approaches A1 and A2 give more accurate Ku estimates than do Approaches B1 and B2 which both have average RMSEs of 0.35, because Function A performs better in estimating WRCs than does Function B. The proposed approaches could be incorporated into simulation models for improved prediction of water, solute, and gas transport in soils

An Improved Thermo-TDR Technique for Monitoring Soil Thermal Properties, Water Content, Bulk Density, and Porosity

The thermo-time domain reflectometry (thermo-TDR) technique is valuable for monitoring in situ soil water content (θ), thermal properties, bulk density (ρb), porosity (n), and air-filled porosity (na) in the vadose zone. However, the previous thermo-TDR sensor has several weaknesses, including limited precision of TDR waveforms due to the short probe length, small measurement volume, and thermal property estimation errors resulting from finite probe properties not accounted for by the heat pulse method. We have developed a new thermo-TDR sensor design for monitoring θ, thermal properties, ρb, n, and na. The new sensor has a robust heater probe (outer diameter of 2.38 mm and length of 70 mm) and a 10-mm spacing between the heater and sensing probes, which provides a sensing volume three times larger than that of the previous sensor. The identical cylindrical perfect conductors and the tangent line–second-order bounded mean oscillation theories were applied to analyze the raw data. Laboratory tests showed that θ values determined with the new sensor had a RMSE of 0.014 m3 m−3 compared with 0.016 to 0.026 m3 m−3 with the previous sensor. Soil thermal property estimates with the new sensor agreed well with modeled values. Soil ρb, n, and na derived from θ and thermal properties were consistent with those derived from gravimetric measurements. Thus, the new thermo-TDR sensor provides more accurate θ, thermal properties, ρb, n, and na values than the previous sensor

Determining In-situ Unsaturated Soil Hydraulic Conductivity at a Fine Depth Scale with Heat Pulse and Water Potential Sensors

Unsaturated hydraulic conductivity (K) of surface soil changes substantially with space and time, and it is of great importance for many ecological, agricultural, and hydrological applications. In general, K is measured in the laboratory, or more commonly, predicted using soil water retention curve and saturated hydraulic conductivity. In the field, K can be determined through infiltration experiments. However, none of these approaches are capable of continuously monitoring K insitu at fine depth scales. In this study, we propose and investigate an approach to continuously estimate fine depth-scale K dynamics under field conditions. Evaporation rate and change in water storage in a near-surface soil layer are measured with the heat pulse method. Then, water flux density at the lower boundary of the soil layer is estimated from evaporation rate, change in water storage, and rainfall or irrigation rate using a simple water balance approach. Finally, K values at different soil depths are derived using the Buckingham-Darcy equation from water flux densities and measured water potential gradients. A field experiment is performed to evaluate the performance of the proposed approach. K values at 2-, 4-, 7.5-, and 12.5-cm depths are estimated with the new approach. The results show that in-situ K estimates vary with time following changes in soil water content, and the K-water content relationship changes with depth due to the difference in bulk density. In-situ estimated K-matric potential curves agree well with those measured in the laboratory. In-situ K estimates also show good agreement with the Mualem-van Genuchten model predictions, with an average root mean square error in log10 (K, mm h-1) of 0.54 and an average bias of 0.17. The new approach provides reasonable in-situ K estimates and has potential to reveal the influences of natural soil conditions on hydraulic properties as they change with depth and time

Summary of Advances in the Heat-Pulse Technique: Improvements in Measuring Soil Thermal Properties

This essay provides a summary of “Advances in the Heat-Pulse Technique: Improvements in Measuring Soil Thermal Properties” recently appearing in Methods of Soil Analysis. Series

Design of a multi-channel high precision wearable temperature collection system based on negative temperature coefficient thermistor

Body temperature is often used to screen infectious diseases and monitor treatment. Through the method of measuring the resistance of constant voltage temperature measuring circuit, a wearable multi-point body temperature monitoring system is researched and designed to determine skin surface temperature. The STM32F103C8T6 chip is used as the core processor, and the negative temperature coefficient thermistor (NTC) as the temperature sensing component. ADS1256 chip is a temperature signal conditioner, Bluetooth module is a wireless transmission unit, and LABVIEW is used to design the host computer interface. The constant voltage bridge circuit composed of thermistor and resistor voltage divider to carry out the acquisition of 8 channels of temperature data, and the 24bits ultra-high-precision analog-to-digital conversion module is configured with differential inputs to amplify, filter and convert analog signals; the converted data is processed and calculated in the single-chip microcomputer; finally, the data is transmitted to the host computer via Bluetooth. The thermistor is linearly compensated using the fourth-order formulation of the Stein-hart formula. Reduce the impact of environmental interference and uneven body temperature distribution from software and hardware. The error during the temperature measurement of temperature sensor is analyzed. The experimental results showed that the resolution of measurement system reached 0. 01 , and the temperature measurement accuracy was up to ± 0. 02 . This design scheme has high stability and accuracy; and the circuit is simple in structure, small in size, and low power consumption which can be used in occasions requiring precise body temperature measurement