Water Content Reflectometer Research Articles

Applicability of Variable-Rate Nitrogen Top Dressing Based on Measurement of the Within-Field Variability of Soil Nutrients for Cabbage Production

To improve the efficiency of nitrogen (N) fertilization, it is necessary to perform rapid direct measurements in the field rather than time-consuming laboratory-based chemical analysis. Herein, crop and soil data from the early stages of cabbage growth were acquired through two fall cultivations. Chlorophyll meter value, height, and projected leaf area were evaluated as crop indicators. A positive correlation was observed between the projected leaf area or its rate of increase 2–3 weeks after transplantation and head fresh weight (FW). After comparing two water-content reflectometers (WCR) and a nitrate sensor, we selected a WCR with a 12 cm-long rod as the soil indicator. The diagnostic method was verified using varying amounts of N basal fertilizer during spring cultivation. The variable rate of N top dressing (25, 50, and 75% total N) based on the electrical conductivity (EC) 14 days after transplantation reduced the subsequent EC variability. No differences in head FW were observed between the treatments. A 25% reduction in N fertilizer was considered possible for half of the plots. The quantity of inorganic N extracted by potassium chloride from the crop soil after cultivation was unaffected by the amount of N fertilizer. Therefore, the diagnostic method proposed herein is suitable for soil N management.

Importance of Fog and Cloud Water Contributions to Soil Moisture in the Andean Páramo

Páramos are particular ecosystems of the Tropical Andes, where fog and low-intensity rainfall such as drizzle are commonly frequent—but the contribution of these water sources to soil water replenishment and discharge is not yet clear, mainly because the development of techniques for separating fog from drizzle and wind-driven rainfall has been challenging. Fog was measured with a cylindrical Juvik gauge and types of precipitation other than fog with a high-resolution disdrometer. Soil moisture was measured at 100 mm depth by means of Water Content Reflectometers, then Effective precipitation (EP) was calculated. We categorized events as two types: fog only (FO) and cloud water (CW). We found that in the case of FO events, only small amounts reached the soil (EP ranged between 0.1 and 0.2 mm); in contrast, greater amounts of EP originated from CW events (maximum value of 4.3 mm). Although we found that FO events are negligible for stream water contribution; they are ecologically important for maintaining high relative humidity, low net radiation, and consequently low evapotranspiration rates. Our research provides new insights into the hydrological role of fog, enabling us to better understand to what extent its input influences the water resources of the Andean páramo.

Field Proximal Soil Sensor Fusion for Improving High-Resolution Soil Property Maps

Mapping soil properties, using geostatistical methods in support of precision agriculture and related activities, requires a large number of samples. To reduce soil sampling and measurement time and cost, a combination of field proximal soil sensors was used to predict and map laboratory-measured soil properties in a 3.4-ha pasture field in southeastern Brazil. Sensor soil properties were measured in situ on a 10 × 10-m dense grid (377 samples) using apparent electrical conductivity meters, apparent magnetic susceptibility meter, gamma-ray spectrometer, water content reflectometer, cone penetrometer, and portable X-ray fluorescence spectrometer (pXRF). Soil samples were collected on a 20 × 20-m thin grid (105 samples) and analyzed in the laboratory for organic C, sum of bases, cation exchange capacity, clay content, soil volumetric moisture, and bulk density. Another 25 samples collected throughout the area were also analyzed for the same soil properties and used for independent validation of models and maps. To test whether the combination of sensors enhances soil property predictions, stepwise multiple linear regression (MLR) models of the laboratory soil properties were derived using individual sensor covariate data versus combined sensor data—except for the pXRF data, which were evaluated separately. Then, to test whether a denser grid sample boosted by sensor-based soil property predictions enhances soil property maps, ordinary kriging of the laboratory-measured soil properties from the thin grid was compared to ordinary kriging of the sensor-based predictions from the dense grid, and ordinary cokriging of the laboratory properties aided by sensor covariate data. The combination of multiple soil sensors improved the MLR predictions for all soil properties relative to single sensors. The pXRF data produced the best MLR predictions for organic C content, clay content, and bulk density, standing out as the best single sensor for soil property prediction, whereas the other sensors combined outperformed the pXRF sensor for the sum of bases, cation exchange capacity, and soil volumetric moisture, based on independent validation. Ordinary kriging of sensor-based predictions outperformed the other interpolation approaches for all soil properties, except organic C content, based on validation results. Thus, combining soil sensors, and using sensor-based soil property predictions to increase the sample size and spatial coverage, leads to more detailed and accurate soil property maps.

Dielectric permittivity-water content relationships in woodchips: Particle size and temperature effects

Information on the amount of water held by woodchips in the field is needed to assess environmental risks when they are kept in stockpiles or for inferring their efficiency as denitrifying bioreactors. Reflectometry is a widely used method for estimating volumetric water content (θ) in permeable media, but material-specific calibration functions should be developed. This study aimed at developing relationships between the bulk dielectric permittivity (εb) and θ in woodchips considering their particle size distribution (PSD), temperature (T) and the dielectric permittivity of the dry material plus air (εsa). The εb of fine, medium and coarse PSDs were measured with CS616-L water content reflectometers up to θ of 0.83 cm3/cm3 and at T (°C) of 10°, 24°, 37°, 55° and 70°. Calibration equations were developed using a multivariate power law function fitted to the data with a hierarchical Bayesian inference procedure. The best fit (R2 = 0.96; RMSE=0.04 cm3/cm3) was obtained for the fine PSD (εsa ∼ 1.09); while medium (εsa ∼ 1.09) and coarse (εsa ∼ 1.03) PSDs were more influenced by T and the presence of large air voids (R2 ∼ 0.92; RMSE∼0.06 cm3/cm3). A modified calibration equation independent of PSD (εsa = 1) reduced only slightly the goodness-of-fit (R2 = 0.90; RMSE=0.07 cm3/cm3). The equations developed in this study are well suited for field applications as they cover a wider range of θ than previously published functions and they are applicable within the range of T found in field applications.

Performance evaluation of a recently developed soil water content, dielectric permittivity, and bulk electrical conductivity electromagnetic sensor

CS655 Water Content Reflectometer (WCR) (Campbell Scientific, Inc., Logan, UT, USA) is a recently developed multiparameter electromagnetic sensor measuring volumetric soil water content (θ), bulk soil electrical conductivity (σb), and temperature. In this study, CS655 sensor’s performance was investigated through laboratory experiments using a set of liquids with known dielectric and salinity properties and soils featuring a wide range of conditions (including physico-chemical properties, water regimes and salinity of the water solution). The sensor’s performance was analyzed in comparison with WET and ML2 theta probe (Delta-T Device Ltd, Cambridge, UK) dielectric sensors. It was found that CS655 apparent dielectric permittivity (εa) readings were higher than that of Topp’s permittivity-water content relationship, especially at higher soil water content values, as much as 12 dimensionless permittivity units. The results suggested that the relationship between experimentally measured soil water content (θm) and εa was strongly linear (0.911<R2<0.997). The most accurate results were provided by the multi-point calibration method. Moreover, for the case of non-conductive soils, Kelleners’s method provides similar εa values with CS655 sensor readings for a maximum σb value of about 0.8 dS m−1. Concerning the use of empirical calibration equations, which include the effect of bulk electrical conductivity in εa, the obtained results suggest that the equation θ=aεa+b+cσb has a strong physical basis and adequate performance (RMSE<0.03 m3 m-3). Finally, the investigation of the εa-σb relationship revealed that it is strongly linear and that slope mainly depends on the pore water electrical conductivity (σp), which is closely related to the soil solution salinity in contact with plant roots that influences plants growth. The Malliki-Walzcak model provide more reliable σp predictions as compared to the Hilhorst model.

Hacking a soil water content reflectometer to measure liquid level

A method for converting a soil water reflectometer to a water level sensor is presented. The sensor essentially records the time of travel of an electromagnetic pulse along two parallel rods, which is then used to infer the relative permittivity (dielectric constant) of the medium around these two rods. While the sensor is designed to capture the relative permittivity variation of soil with its moisture content, the immersion depth of the rods in water (or potentially other dielectric liquids) also influences the average dielectric constant of the air-water medium between the rods (consequently affecting its permittivity). Here we show how this change in permittivity can be calibrated to measure small liquid depths. An empirical calibration equation is developed; it accounts for the impact of water salinity, whereas the temperature effect on the measurements is shown to be negligible.

Multi-source data assimilation for physically based hydrological modeling of an experimental hillslope

Abstract. Data assimilation has recently been the focus of much attention for integrated surface–subsurface hydrological models, whereby joint assimilation of water table, soil moisture, and river discharge measurements with the ensemble Kalman filter (EnKF) has been extensively applied. Although the EnKF has been specifically developed to deal with nonlinear models, integrated hydrological models based on the Richards equation still represent a challenge, due to strong nonlinearities that may significantly affect the filter performance. Thus, more studies are needed to investigate the capabilities of the EnKF to correct the system state and identify parameters in cases where the unsaturated zone dynamics are dominant, as well as to quantify possible tradeoffs associated with assimilation of multi-source data. Here, the CATHY (CATchment HYdrology) model is applied to reproduce the hydrological dynamics observed in an experimental two-layered hillslope, equipped with tensiometers, water content reflectometer probes, and tipping bucket flow gages to monitor the hillslope response to a series of artificial rainfall events. Pressure head, soil moisture, and subsurface outflow are assimilated with the EnKF in a number of scenarios and the challenges and issues arising from the assimilation of multi-source data in this real-world test case are discussed. Our results demonstrate that the EnKF is able to effectively correct states and parameters even in a real application characterized by strong nonlinearities. However, multi-source data assimilation may lead to significant tradeoffs: the assimilation of additional variables can lead to degradation of model predictions for other variables that are otherwise well reproduced. Furthermore, we show that integrated observations such as outflow discharge cannot compensate for the lack of well-distributed data in heterogeneous hillslopes.

Laboratory temperature-compensating calibration procedure for soil water content determination by reflectometry

The water content reflectometer allows a temporal and spatial assessment in soil water dynamic. This work aimed to study the behavior of the sensor (CS616) for the period measurement in function to the temperature and soil water content. The tests were conducted at State University of Mato Grosso, Tangara da Serra municipality. We used PVC (polymerizing vinyl chloride) pipe to make six recipients (0.1 m diameter and 0.4 m height) and filled them with soil. For each one of them a sensor CS616 and temperature sensor (K type) were allocate in a central position. The soil water content for each recipient were fitted to 0.00; 0.06; 0.11; 0.16; 0.22; 0.27 m 3 m -3 , and the samples were submitted to temperature gradient from 1.0 up to 40.0 °C. Data of temperature, and period response were recorded in a data logger. Notice that the temperature provides changes for period response val­ues (μs), and as greater the soil water content, as greater the temperature influence. From collected data, two models were fitted (linear and quadratic), and compared with manufacturer standard equations. For conditions in that study, the fitted quadratic model provide the best approach for the water soil content prediction.

Investigation clogging dynamic of permeable pavement systems using embedded sensors

Permeable pavement is a stormwater control measure commonly selected in both new and retrofit applications. However, there is limited information about the clogging mechanism of these systems that effects the infiltration. A permeable pavement site located at the Seitz Elementary School, on Fort Riley, Kansas was selected for this study. An 80-space parking lot was built behind the school as part of an EPA collaboration with the U.S. Army. The parking lot design includes a permeable interlocking concrete pavement section along the downgradient edge. This study monitored the clogging progress of the pavement section using twelve water content reflectometers and three buried tipping bucket rain gauges. This clogging dynamic investigation was divided into three stages namely pre-clogged, transitional, and clogged. Recorded initial relative water content of all three stages were significantly and negatively correlated to antecedent dry weather periods with stronger correlations during clogged conditions. The peak relative water content correlation with peak rainfall 10-min intensity was significant for the water content reflectometers located on the western edge away from the eastern edge; this correlation was strongest during transition stage. Once clogged, rainfall measurements no longer correlated with the buried tipping bucket rain gauges. Both water content reflectometers and buried tipping bucket rain gauges showed the progress of surface clogging. For every 6 mm of rain, clogging advanced 1 mm across the surface. The results generally support the hypothesis that the clogging progresses from the upgradient to the downgradient edge. The magnitude of the contributing drainage area and rainfall characteristics are effective factors on rate and progression of clogging.

Field and Laboratory Evaluation of the CS655 Soil Water Content Sensor

Core Ideas The CS655 measures two‐way travel time and attenuation of a low‐frequency EM pulse to derive Ka, EC, and SWC. Laboratory and field evaluations for five central Texas soils found the sensor robust but RMSE could be reduced by a soil‐ or site‐specific function. The factory calibration has a cross‐over point at Ka ∼15, with low bias below and high bias above. The TxSON network mean was unaffected by calibration but the variance was significantly reduced. Soil moisture sensors infer volumetric soil water content (SWC) from other properties of the bulk porous media. The CS655 water content reflectometer is a relatively new, low‐frequency electromagnetic sensor that determines relative permittivity (Ka) using the two‐way travel period and voltage attenuation of the applied signal along two 12‐cm rods. This measured attenuation is quadratically related to bulk electrical conductivity (EC). Along with an onboard thermistor, the CS655 allows a more robust correction of propagation time and Ka, which its predecessors, the CS615 and CS616, lacked. However, with new sensors it is necessary to quantify their practical accuracy in the field. Here, we present an overview of the CS655 sensor and an evaluation under both laboratory and field conditions, using five surface soils (0–10‐cm depth) in the laboratory and gravimetric samples collected in the field. Overall, a site‐specific calibration using a two‐term linearization of the SWC–Ka function reduced the root mean square error (RMSE) of the factory‐derived SWC of 0.073 and 0.043 m3 m−3 during batch and infiltration experiments, respectively, to 0.025 and 0.028 m3 m−3. Results further indicate that a soil‐specific calibration additionally reduced the RMSE to &lt;0.02 m3 m−3. Field evaluation across the Texas Soil Observation Network found that calibration reduced the variance across the network but did not affect the arithmetic mean or the RMSE against gravimetric sampling, which remained ∼0.05 m3 m−3 regardless of the SWC–Ka–EC function applied. At the regional scale, a global calibration is sufficient.

Soil Water Dynamics and Nitrate Leaching Under Corn–Soybean Rotation, Continuous Corn, and Kura Clover

Core Ideas Corn–soybean and continuous corn had similar soil water dynamics and N leaching. Urea and anhydrous ammonia resulted in similar leachate nitrate concentrations. The kura clover cropping system reduced drainage, N leaching, and fall soil N. Improving water quantity and quality impacts of corn (Zea mays L.)‐ and soybean [Glycine max (L.) Merr.]‐based cropping systems is a key challenge for agriculture in the US Midwest. Long‐term field experiments are important for documenting those effects and exploring possible solutions. This study examines differences in soil water dynamics and nitrate‐nitrogen (N) leaching among cropping systems and N fertilizer sources in a long‐term experiment in southeastern Minnesota. Drainage and leachate concentrations were measured for 4 yr using automated equilibrium tension lysimeters installed below the root zone in replicated, large plots on a well‐drained silt loam soil. Soil water storage was monitored using water content reflectometers. Corn–soybean and continuous corn cropping systems exhibited similar soil water dynamics, drainage rates (145–202 mm yr−1), leachate nitrate N concentrations (21.3–25.6 mg L−1), and nitrate N leaching loads (30–75 kg ha−1 yr−1). Nitrate‐N concentrations in the leachate were similar whether N was added as urea (21.2 mg L−1) or anhydrous ammonia (25.7 mg L−1). A perennial kura clover (Trifolium ambiguum M. Bieb)‐based cropping system with no N fertilizer significantly altered soil water dynamics and resulted in lower (p &lt; 0.10) drainage rates (53 mm yr−1), nitrate N concentrations (7.1 mg L−1), and nitrate N leaching loads (2–5 kg ha−1 yr−1) compared with corn–soybean or continuous corn, but also reduced corn grain yields. These impacts are generally consistent with a growing body of literature showing substantial environmental benefits of a kura clover living mulch system for corn production, but the economic viability of such a system is not yet proven.

Proof of Concept: Development of Snow Liquid Water Content Profiler Using CS650 Reflectometers at Caribou, ME, USA.

The quantity of liquid water in the snowpack defines its wetness. The temporal evolution of snow wetness’s plays a significant role in wet-snow avalanche prediction, meltwater release, and water availability estimations and assessments within a river basin. However, it remains a difficult task and a demanding issue to measure the snowpack’s liquid water content (LWC) and its temporal evolution with conventional in situ techniques. We propose an approach based on the use of time-domain reflectometry (TDR) and CS650 soil water content reflectometers to measure the snowpack’s LWC and temperature profiles. For this purpose, we created an easily-applicable, low-cost, automated, and continuous LWC profiling instrument using reflectometers at the Cooperative Remote Sensing Science and Technology Center-Snow Analysis and Field Experiment (CREST-SAFE) in Caribou, ME, USA, and tested it during the snow melt period (February–April) immediately after installation in 2014. Snow Thermal Model (SNTHERM) LWC simulations forced with CREST-SAFE meteorological data were used to evaluate the accuracy of the instrument. Results showed overall good agreement, but clearly indicated inaccuracy under wet snow conditions. For this reason, we present two (for dry and wet snow) statistical relationships between snow LWC and dielectric permittivity similar to Topp’s equation for the LWC of mineral soils. These equations were validated using CREST-SAFE in situ data from winter 2015. Results displayed high agreement when compared to LWC estimates obtained using empirical formulas developed in previous studies, and minor improvement over wet snow LWC estimates. Additionally, the equations seemed to be able to capture the snowpack state (i.e., onset of melt, medium, and maximum saturation). Lastly, field test results show advantages, such as: automated, continuous measurements, the temperature profiling of the snowpack, and the possible categorization of its state. However, future work should focus on improving the instrument’s capability to measure the snowpack’s LWC profile by properly calibrating it with in situ LWC measurements. Acceptable validation agreement indicates that the developed snow LWC, temperature, and wetness profiler offers a promising new tool for snow hydrology research.

Evaluations of the effects of soil properties and electrical conductivity on the water content reflectometer calibration for landfill cover soils

This study presents soil-moisture calibrations using low-frequency (15–40 MHz) time domain reflectometry (TDR) probe, referred to as water content reflectometer (WCR), for measuring the volumetric water content of landfill cover soils, developing calibrations for 28 different soils, and evaluating how WCR calibrations are affected by soil properties and electrical conductivity. A 150-mm-diameter PVC cell was used for the initial WCR calibration. Linear and polynomial calibrations were developed for each soil. Although the correlation coefficients (R&lt;sup&gt;2&lt;/sup&gt;) for the polynomial calibration are slightly higher, the linear calibrations are accurate and pragmatic to use. The effects of soil electrical conductivity and index properties were investigated using the slopes of linear WCR calibrations. Soils with higher electrical conductivity had lower calibration slopes due to greater attenuation of the signal during transmission in the soil. Soils with higher electrical conductivity tended to have higher clay content, organic matter, liquid limit, and plasticity index. The effects of temperature and dry unit weight on WCR calibrations were assessed in clayey and silty soils. The sensor period was found to increase with the temperature and density increase, with greater sensitivity in fine-textured plastic soils. For typical variations in temperature, errors in volumetric water content on the order of 0.04 can be expected for wet soils and 0.01 for drier soils if temperature corrections are not applied. Errors on the order of 0.03 (clays) and 0.01 (silts) can be expected for typical variations in dry unit weight (± 2 kN/m&lt;sup&gt;3&lt;/sup&gt;).

The performance of a trial gravel road under accelerated pavement testing

Abstract This study presents the performance of a trial gravel road subjected to HVS (Heavy Vehicle Simulator) trafficking in a compressed time period. The road structure was constructed with 150 mm-thick aggregate base course, and 125 mm-thick sub-base course. The test road responses, such as surface deformation and rutting were recorded using laser profile measurement instrument while the unbound layers’ dynamic deflections and strains data were periodically recorded at different depths during the execution of the test by means of an array of micro strain gauges. The test road was also instrumented with Water Content Reflectometers to record the changes in moisture contents in the road layers caused by the raising of the water table level under HVS trafficking. A total number of 85,000 HVS passes were applied to the trial gravel road structure under near-optimum as well as partially submerged subgrade moisture conditions. The test results emphasize the fact that the partial soaking of the subgrade soil by raising the groundwater table level caused a serious damage to the tested gravel road, as further detailed in this paper.

Lake ice measurements from soil water content reflectometer sensors

AbstractLake ice depth provides important information about local and regional climate change, weather patterns, and recreational safety, as well as impacting in situ ecology and carbon cycling. However, it is challenging to measure ice depth continuously from a remote location, as existing methods are too large, expensive, and/or time‐intensive. Therefore, we present a novel application that resolves size, cost, and automation issues using commercially‐available soil water content reflectometer sensors from multiple manufactures. Analysis of sensors deployed in an environmental chamber using a scale model of a lake demonstrated accurate measure of the change in ice depth over any time period to within 1 cm, through sensor response of liquid‐to‐solid phase change. A robust correlation exists between volumetric water content in time as a function of environmental temperature and ice growth. This relationship allows us to convert volumetric water content into ice depth. An array of these sensors can be used in lake or river settings to create a temporally high‐resolution ice depth record, which fills in a needed gap for ecological or climatological studies as well as increasing public recreational safety.

Calibration of Water Content Reflectometer Sensors with a Large Soil Sample

In situ measurement of soil water content is of fundamental importance in vadose zone processes. While time domain reflectometry (TDR) is a universally accepted technique, having been developed since the 1980s, water content reflectometer (WCR) is still a relatively new technique and does not hold a similar background. The main goal of this study was to establish an accurate calibration curve for WCR sensors to be installed in an artificial hillslope designed to study the triggering of shallow landslides. Therefore, high accuracy calibration at the high end of the water content range and for large soil volumes was necessary. An experimental device was specifically designed to provide a calibration procedure for a soil control volume commensurate with the application scale of the probes in the hillslope. A large box container (60 by 50 by 60 cm) was used, inside which three WCR probes and three tensiometers were arranged. A drip emitter produced assigned flow rates, while a load cell at the base measured the time evolution of the infiltrated water mass. Water content was evaluated at approximately steady-state flow conditions for infiltration and drainage experiments, performed with varying degrees of compaction to detect the effect of the porosity on the calibration curve. The experimental results suggest a calibration relationship linearly depending not only on the WCR output signal but also on the porosity. In addition, the calibration curve provided by the manufacturer significantly underestimates the soil water content, with a range of predicted volumetric water content values between 3 and 35%, compared with actual values varying between 19 and 61%.

Event‐ and Site‐Specific Soil Wetting and Seasonal Change in Amount of Soil Water

Changes in the amount of soil water might not be uniform due to spatially variable soil and landscape factors. The objective of this study was to determine if the changes in the amount of soil water due to rain or during sub‐seasonal times are related to soil or landscape properties within a field. Sub‐seasonal changes in soil water were indicated by neutron probe data and surface soil sampling, and rain‐event‐driven soil water increases were indicated by water content reflectometers (WCRs). Excess rainfall in 2010 resulted in wet soil and surface ponding at some sites. Soil zones satiated with water were apparent from WCR data, especially for concave and depressional sites. The length of time soil remained satiated at the 0.3‐ and 0.6‐m depths was negatively correlated with relative elevation (in relation to the nearest depression edge). Soil water increases for the 0.015‐ to 0.15‐m depth were most often correlated with pre‐rain soil water deficit, especially in the wet year of 2010 (13 of 14 events). Change in the amount of soil water at the deepest depth for the later part of the 2012 season (a drought year) was negatively correlated with profile and plan curvatures and mollic depth and positively correlated with relative elevation and sand fraction, which was the opposite of the expected trend. Two sites with buried sand lenses took the longest time to reach maximum soil water increase, suggesting that further study is needed to describe how buried sand lenses affect wetting in the soil above the sand lens.

Divergent Vegetation Growth Patterns Relative to Bioinfiltration Unit Size and Plant Placement

AbstractIn 2009, the U.S. EPA constructed six experimental bioinfiltration units (BUs) at the Edison Environmental Center in Edison, New Jersey. They were designed as two sets of three BUs with drainage area to surface area ratios of 5.5∶1, 11∶1, and 22∶1. The intent was to determine the effects of area on side-by-side systems that received equivalent inflow. A 0.86-m deep media layer containing 97% sand was installed over 0.10 m of gravel and sandy underlying soils. Water content reflectometers (WCRs) and thermistors were installed 0.38 m into the media and 0.25 m into the underlying in situ soil near the front and rear of each bioinfiltration unit to monitor stormwater infiltrating through the media and into the underlying soil. Infiltration monitored at these sites with the WCRs was not in accordance with the simplified conceptual model of uniform infiltration across the surface; rather, infiltration was concentrated near the inlet. After the third growing season, plant basal area and height were measu...

Moisture content behaviour in extensive green roofs during dry periods: The influence of vegetation and substrate characteristics

Evapotranspiration (ET) is a key parameter that influences the stormwater retention capacity, and thus the hydrological performance, of green roofs. This paper investigates how the moisture content in extensive green roofs varies during dry periods due to evapotranspiration. The study is supported by 29 months continuous field monitoring of the moisture content within four green roof test beds. The beds incorporated three different substrates, with three being vegetated with sedum and one left unvegetated. Water content reflectometers were located at three different soil depths to measure the soil moisture profile and to record temporal changes in moisture content at a five-minute resolution. The moisture content vertical profiles varied consistently, with slightly elevated moisture content levels being recorded at the deepest substrate layer in the vegetated systems. Daily moisture loss rates were influenced by both temperature and moisture content, with reduced moisture loss/evapotranspiration when the soil moisture was restricted. The presence of vegetation resulted in higher daily moisture loss. Finally, it is demonstrated that the observed moisture content data can be accurately simulated using a hydrologic model based on water balance and two conventional Potential ET models (Hargreaves and FAO56 Penman–Monteith) combined with a soil moisture extraction function. Configuration-specific correction factors have been proposed to account for differences between green roof systems and standard reference crops.

Salinity Effects on the Fieldscout TDR 300 Soil Moisture Meter Readings

While studying changes in volumetric water content (VWC) of soilless culture (sand and tuff), the need for a quick and easy-to-operate moisture measurement device with accuracy better than ±0.01 has risen. Before full scale application, we performed some basic tests with the Fieldscout TDR 300 soil moisture meter to evaluate the dependency of the VWC measurements on the salinity of the medium. The TDR300 was used to measure VWC in (i) sand and tuff wetted by deionized water or a 0.02 M NaCl solution to different VWC levels, (ii) sand or tuff wetted by solutions of different salinities to a given VWC level, and (iii) aqueous solutions of different salinities. Medium salinity had a significant effect (up to 60%) on the VWC readings of the TDR 300. Our observations suggest that the technology used by the TDR 300 is similar to that of low frequency water content reflectometers.