微型土压力传感器标定方法研究

离心模型试验常用微型土压力传感器测量地基或土与结构接触边界上的土压力。传感器使用之前应进行标定。传统的液标或气标方法不能准确反映传感器埋置过程对土体的扰动或传感器周围人为土拱边界条件形成,导致测试结果不甚理想。故针对试验条件,设计制作一套标定微型土压力传感器的方法和装置,以水、粉质黏土和福建标准砂为标定介质,考虑有无刚性靠背两种工作状态对多个传感器进行室内标定,得到标定系数。结果表明:水标未出现卸载滞后,砂标和土标均出现卸载滞后,且表现为非线性;引入滞后比R评价微型土压力传感器的滞后性,认为标定介质和传感器类型是影响滞后比的两个主要因素;传感器自身材料特性和几何特性、地基土的制备和传感器放置、加载预压和加卸载循环等对土体密实度、土体强度等的改变、工作介质和状态等对标定结果有影响。建议尽量模拟试验工作介质和工作状态,逐个标定传感器,以得到更准确的土压力测量值。     

Water Level Monitoring Pressure Transducers—A Need for Industry‐Wide Standards

There are currently no industry‐wide standards for the calibration and specification of water‐level monitoring pressure transducers. Consequently, specifications from different manufacturers are currently not directly comparable, and different branded sensors may not perform similarly under the same environmental conditions. This has been highlighted by the varied performance of 14 leading brands of pressure transducers under test conditions. In laboratory tests, transducers generally met product accuracy specifications, although temperature compensation was substandard in five absolute sensors. In a 99‐day field test, accuracy was typically within around ±10 mm for lower range pressure sensors, which exceeded some product specifications. Furthermore, there was evidence for linear and curved forms of instrument drift. As a result of the diverse performance of the transducers, it is recommended that an industry‐wide standard for calibration and specification is introduced. This would eliminate any uncertainty surrounding the current procedures and lead to more informed procurement by the user who would have a greater understanding of comparative instrument performance. Any new standard should also address sensor drift which is currently rarely cited in product specifications.     

Preferential percolation quantified by large water content sensors with artifactual macroporous envelopes

For many scientific and practical tasks, it is important to estimate the soil–water percolation fluxes. This paper builds on measurements with large horizontal time‐domain reflectometry water content sensors in a loamy Mollisol. The sensors were installed into pre‐drilled holes and the gaps between them, and the soil was filled with a slurry of local soil with water. This gave rise to envelopes around them that contained artificial macropores. The sensors reacted to intensive rains by a rapid increase of their readings, often above the native soil's porosity, followed by an almost equally rapid decrease. The paper explores the feasibility of quantifying the rapid percolation, based on these anomalous water content peaks, and demonstrates that this is possible in principle, if the processes are simulated by a suitable model. A two‐dimensional dual porosity non‐equilibrium (mobile‐immobile) model was tried. The envelope around the sensor was modelled as an annulus with higher porosity and hydraulic conductivity, which attracts preferential flow and amplifies the percolation signal. With the model at hand, the flux hydrographs can be derived from model simulations and measured precipitation. For contrast, the Durner equilibrium dual porosity model was tried but was found little suitable. However, even the mobile‐immobile model did not perform perfectly. Simulated water contents were similar to the measured ones at some depths but not in the others, and the percolation fluxes were overestimated, compared to cumulative soil–water balance. Efforts to improve model performance were not successful. Hence, the model structure needs to be improved. Copyright © 2015 John Wiley & Sons, Ltd.     

Soil water content in southern England derived from a cosmic‐ray soil moisture observing system – COSMOS‐UK

Cosmic‐ray soil moisture sensors have the advantage of a large measurement footprint (approximately 700 m in diameter) and are able to operate continuously to provide area‐averaged near‐surface (top 10–20 cm) volumetric soil moisture content at the field scale. This paper presents the application of this technique at four sites in southern England over almost 3 years. Results show the soil moisture response to contrasting climatic conditions during 2011–2014 and are the first such field‐scale measurements made in the UK. These four sites are prototype stations for a UK COsmic‐ray Soil Moisture Observing System, and particular consideration is given to sensor operating conditions in the UK. Comparison of these soil water content observations with the Joint UK Land Environment Simulator 10‐cm soil moisture layer shows that these data can be used to test and diagnose model performance and indicate the potential for assimilation of these data into hydro‐meteorological models. The application of these large‐area soil water content measurements to evaluate remotely sensed soil moisture products is also demonstrated. Numerous applications and the future development of a national COsmic‐ray Soil Moisture Observing System network are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

Improved spatial delineation of streambed properties and water fluxes using distributed temperature sensing

A new method was developed for analysing and delineating streambed water fluxes, flow conditions and hydraulic properties using coiled fibre‐optic distributed temperature sensing or closely spaced discrete temperature sensors. This method allows for a thorough treatment of the spatial information embedded in temperature data by creating a matrix visualization of all possible sensor pairs. Application of the method to a 5‐day field dataset reveals the complexity of shallow streambed thermal regimes. To understand how velocity estimates are affected by violations of assumptions of one‐dimensional, saturated, homogeneous flow and to aid in the interpretation of field observations, the method was also applied to temperature data generated by numerical models of common field conditions: horizontal layering, presence of lateral flow and variable streambed saturation. The results show that each condition creates a distinct signature visible in the triangular matrices. The matrices are used to perform a comparison of the behaviour of one‐dimensional analytical heat‐tracing models. The results show that the amplitude ratio‐based method of velocity calculation leads to the most reliable estimates. The minimum sensor spacing required to obtain reliable velocity estimates with discrete sensors is also investigated using field data. The developed method will aid future heat‐tracing studies by providing a technique for visualizing and comparing results from fibre‐optic distributed temperature sensing installations and testing the robustness of analytical heat‐tracing models. Copyright © 2016 John Wiley & Sons, Ltd.     

Continuous field estimation of dissolved organic carbon concentration and biochemical oxygen demand using dual‐wavelength fluorescence,turbidity and temperature

Dissolved organic matter (DOM) quality and quantity is not measured routinely in‐situ limiting our ability to quantify DOM process dynamics. This is problematic given legislative obligations to determine event based variability; however, recent advances in field deployable optical sensing technology provide the opportunity to address this problem. In this paper, we outline a new approach for in‐situ quantification of DOM quantity (Dissolved Organic Carbon: DOC) and a component of quality (Biochemical Oxygen Demand: BOD) using a multi‐wavelength, through‐flow fluorescence sensor. The sensor measured tryptophan‐like (Peak T) and humic‐like (Peak C) fluorescence, alongside water temperature and turbidity. Laboratory derived coefficients were developed to compensate for thermal quenching and turbidity interference (i.e., light attenuation and scattering). Field tests were undertaken on an urban river with ageing wastewater and stormwater infrastructure (Bourn Brook; Birmingham, UK). Sensor output was validated against laboratory determinations of DOC and BOD collected by discrete grab sampling during baseflow and stormflow conditions. Data driven regression models were then compared to laboratory correction methods. A combination of temperature and turbidity compensated Peak T and Peak C was found to be a good predictor of DOC concentration (R² = 0.92). Conversely, using temperature and turbidity correction coefficients provided low predictive power for BOD (R² = 0.46 and R² = 0.51, for Peak C and T, respectively). For this study system, turbidity appeared to be a reasonable proxy for BOD, R² = 0.86. However, a linear mixed effect model with temperature compensated Peak T and turbidity provided a robust BOD prediction (R² = 0.95). These findings indicate that with careful initial calibration, multi‐wavelength fluorescence, coupled with turbidity, and temperature provides a feasible proxy for continuous, in‐situ measurement of DOC concentration and BOD. This approach represents a cost effective monitoring solution, particularly when compared to UV – absorbance sensors and DOC analysers, and could be readily adopted for research and industrial applications.     

Assessment of micro‐aggregation using laser diffractometry

In order to evaluate the influence of the measuring technique on the determination of (micro‐)aggregation in soil and sediment samples, results of grain size distributions of undispersed silty soil samples obtained by the sieve‐pipette method are compared with those obtained using a laser diffraction grain size analyser, the Coulter LS‐100. Reduced major axis relationships are calculated which may be used to convert Coulter LS‐100 results to those obtained by the sieve‐pipette method. The relationships obtained are very similar to the reduced major axis relationships established for dispersed silty soil samples. The results also show that the Coulter LS measurements have a systematic bias compared to the sieve‐pipette data. This implies that, if the percentage of (micro‐)aggregation is determined, the (interpretation of the) results will be strongly dependent on the measurement technique used. Using the calibration relationships that were established, nomographs can be developed to predict the level of sieve‐pipette (micro‐) aggregation from Coulter LS‐100 data. Copyright © 1999 John Wiley & Sons, Ltd.     

Multi‐variable and multi‐site calibration and validation of SWAT in a large mountainous catchment with high spatial variability

Many methods developed for calibration and validation of physically based distributed hydrological models are time consuming and computationally intensive. Only a small set of input parameters can be optimized, and the optimization often results in unrealistic values. In this study we adopted a multi‐variable and multi‐site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Motueka catchment, making use of extensive field measurements. Not only were a number of hydrological processes (model components) in a catchment evaluated, but also a number of subcatchments were used in the calibration. The internal variables used were PET, annual water yield, daily streamflow, baseflow, and soil moisture. The study was conducted using an 11‐year historical flow record (1990–2000); 1990–94 was used for calibration and 1995–2000 for validation. SWAT generally predicted well the PET, water yield and daily streamflow. The predicted daily streamflow matched the observed values, with a Nash–Sutcliffe coefficient of 0·78 during calibration and 0·72 during validation. However, values for subcatchments ranged from 0·31 to 0·67 during calibration, and 0·36 to 0·52 during validation. The predicted soil moisture remained wet compared with the measurement. About 50% of the extra soil water storage predicted by the model can be ascribed to overprediction of precipitation; the remaining 50% discrepancy was likely to be a result of poor representation of soil properties. Hydrological compensations in the modelling results are derived from water balances in the various pathways and storage (evaporation, streamflow, surface runoff, soil moisture and groundwater) and the contributions to streamflow from different geographic areas (hill slopes, variable source areas, sub‐basins, and subcatchments). The use of an integrated multi‐variable and multi‐site method improved the model calibration and validation and highlighted the areas and hydrological processes requiring greater calibration effort. Copyright © 2005 John Wiley & Sons, Ltd.     

A theory of pressure sensor performance in snow

A theory of pressure sensor response in snow is derived and used to examine the sources of measurement errors in snow water equivalent (SWE) pressure sensors. Measurement errors in SWE are caused by differences in the compressibility of the pressure sensor and the adjacent snow layer, which produces a shear stress along the perimeter of the sensor. When the temperature at the base of the snow cover equals 0 °C, differences in the snowmelt rate between the snow–SWE sensor interface and the adjacent snow–soil interface may also produce a shear stress along the sensor's perimeter. This shear stress perturbs the pressure field over the sensor, producing SWE measurement errors. Snow creep acts to reduce shear stresses along the SWE sensor's perimeter at a rate that is inversely proportional to the snow viscosity. For sustained periods of differential snowmelt, a difference in the mass of snow over the sensor compared with the surrounding soil will develop, producing additional permanent errors in SWE measurements. The theory indicates that SWE pressure sensor performance can be improved by designing a sensor with a high Young's modulus (low compressibility), low aspect ratio, large diameter and thermal properties that match those of the surrounding soil. Simulations of SWE pressure sensor errors using the theory are in close agreement with observed errors and may provide a means to correct historical SWE measurements for use in hydrological hindcast or climate studies. Published in 2003 by John Wiley & Sons, Ltd.     

Continuous Multi‐probe Measurements in Fastflowing Waters Using a Hydrographic Slot

Taking continuous spatiotemporal in situ measurements with multi‐probes in fast‐flowing waters/rivers can be problematic because the sensors may be damaged by high shear forces and flotsam. To protect the multi‐probe and to enable easy access for the maintenance and calibration of the sensors, a special multi‐probe holder fixed in a hydrographic slot was developed. The validation of the probe system revealed a “memory effect” at short time scales (< 10 s) within sharp gradients caused by the overflow container of the multi‐probe rack keeping the sensors submerged in the sample water. Continuously recorded data (conductivity, temperature, pH, oxygen concentration and saturation, as well as in vivo fluorescence of chlorophyll‐a) from a research cruise on board the RV ALBIS along the river Elbe (river km 309) and entering the river Saale are presented. This river stretch upstream of the city of Magdeburg to the mouth of the Saale tributary was found to have a complex physicochemical character, which is attributable to the long mixing process of water from the river Saale and the river Elbe.     

Simple Chloride Sensors for Continuous Groundwater Monitoring

The development of chloride sensors which can be used for continuous, on‐line monitoring of groundwater could be very valuable in the management of our coastal water resources. However, sensor stability, drift, and durability all need to be addressed in order for the sensors to be used in continuous application. This study looks at the development of a simple, inexpensive chloride electrode, and evaluates its performance under continuous use, both in the laboratory and in a field test in a monitoring well. The results from the study showed a consistent response to changing chloride concentrations over longer periods. The signal was seen to be stable, with regular drift in both laboratory and field test. In the field application, the sensor signal was corrected for drift, and errors were observed to be under 7% of that of conductivity measurements. The study also found that the chloride sensor remained responsive even at low chloride concentrations, where the conductivity electrode was no longer responding to changing chloride levels. With the results, it is believed that the simple chloride sensor could be used for continuous monitoring of groundwater quality.     

A soil-water flux sensor and its use for field studies of transfer processes in surface soil

A soil-water flux sensor was developed, which determines the flux value from the difference between downstream and upstream temperatures at some distances from an artificial heat source. It can detect flux values ranging from several mm hr.⁻¹ to as small as 0.01 mm hr.⁻¹. Design and calibration of the sensor are described.

The sensor was applied to the field studies of transfer processes in a surface soil, including rainwater infiltration, upward soil-water flow during evapotranspiration, and their effects on the water table level. Cl⁻ accumulation in the surface soil is discussed on the basis of upward water flux and Cl⁻ content observed.     

Evaluation of Subsurface Oxygen Sensors for Remediation Monitoring

Continuous remediation monitoring using sensors is potentially a more effective and inexpensive alternative to current methods of sample collection and analysis. Gaseous components of a system are the most mobile and easiest to monitor. Continuous monitoring of soil gases such as oxygen, carbon dioxide, and contaminant vapors can provide important quantitative information regarding the progress of bioremediation efforts and the area of influence of air sparging or soil venting. Laboratory and field tests of a commercially available oxygen sensor show that the subsurface oxygen sensor provides rapid and accurate data on vapor phase oxygen concentrations. The sensor is well suited for monitoring gas flow and oxygen consumption in the vadose zone during air sparging and bioventing. The sensor performs well in permeable, unsaturated soil environments and recovers completely after being submerged during temporary saturated conditions. Calibrations of the in situ oxygen sensors were found to be stable after one year of continuous subsurface operation. However, application of the sensor in saturated soil conditions is limited. The three major advantages of this sensor for in situ monitoring arc as follows: (1) it allows data acquisition at any specified time interval; (2) it provides potentially more accurate data by minimizing disturbance of subsurface conditions; and (3) it minimizes the cost of field and laboratory procedures involved in sample retrieval and analysis.     

Obstacles to long‐term soil moisture monitoring with heated distributed temperature sensing

The field deployment of a heated distributed temperature sensor (DTS) for over three years has revealed two obstacles to estimating soil moisture (θ) that may hamper subsurface DTS applications as well as use of other subsurface thermal probes. The first observed obstacle was a hysteretic response of the DTS sensor. The relationship between θ and the temperature response (?T) within the cable was not only dependent on θ of the soil, but also on the previous wetting and drying cycles leading to that state. The second observed obstacle was soil structure healing. Soil structure healing causes the relationship between ?T and θ to evolve through time; this calibration curve becomes flatter, or less sensitive, as the surrounding soil makes better contact with the cable. Effects of the hysteretic response of the instrument and soil structure healing are largely the result of small gaps between the cable and soil. These small gaps can be approximated by a contact resistance between the cable and soil. In this article we characterize the occurrence of hysteretic and soil structure healing effects from field data and parameterize contact resistance by simulating heat transfer using a numerical modelling approach Copyright © 2015 John Wiley & Sons, Ltd.     

Impact of spatial variations of land surface parameters on regional evaporation: a case study with remote sensing data

Most precipitation in watersheds is consumed by evaporation, thus techniques to appraise regional evaporation are important to assess the availability of water resources. Many algorithms to estimate evaporation from remotely sensed spectral data have been developed in the recent past. In addition to differences in the physical parameterization of surface fluxes, these algorithms have different solutions for describing spatial variations of the parameters in the soil–vegetation–atmosphere–transfer (SVAT) continuum. In this study, the necessity to spatially distinguish SVAT parameters for computing surface heat fluxes is analysed for the Naivasha watershed in the Kenyan Rift Valley. Landsat Thematic Mapper (TM) spectral data have been used to first delineate the watershed into 15 hydrological units using surface temperature, normalized difference vegetation index and surface albedo as attributes. Thereafter, semi‐empirical relationships between these TM‐based parameters and other SVAT parameters have been applied to compute the spatial variation of SVAT parameters and the associated evaporation from the different hydrological units. The impact of using watershed‐constant or watershed‐distributed SVAT parameters on the fluxes is analysed. The determination of watershed averaged evaporation with area‐aggregated SVAT parameters is feasible without significant loss of accuracy. Distributed evaporation in heterogeneous watersheds, however, can be investigated only with remote sensing flux algorithms that can account for spatially variable air temperature, surface roughness, surface albedo and the stability correction of the temperature profile due to buoyancy. Erroneous results can be expected if area‐aggregated SVAT parameters are used to calculate local evaporation. As most of the recently developed remote sensing flux algorithms are based on areal constant SVAT parameters, direct applications in watersheds are still limited. Copyright © 2001 John Wiley & Sons, Ltd.     

On-site calibration of air-coil sensor for transient electromagnetic exploration

This paper proposes a time-domain fitting method for on-site calibration of the air-coil sensor. The air-coil sensor has been widely used in transient electromagnetic exploration. Due to limited bandwidth of the coil, the output signal is distorted, causing a phenomenon known as the transition process. To accurately measure the magnetic field from the output signals, the relationship between the coil induced electromotive force and the output voltage must be confirmed by on-site calibration, which requires high calibration accuracy and demands simple operation, portable equipment, and adaptability to the environment. Conventional frequency response methods, however, requires a uniform magnetic field with various frequencies to obtain the frequency response curve of the air-coil sensor. The time to acquire the signal correlates with the number of test frequencies, and the equipment used to generate a uniform magnetic field must be tailored to the shape of the air-coil sensor under test. This paper constructs a relationship between the calibration file and the zero-input response of the air-coil sensor and designs an optimization algorithm to suppress the soil eddy current effect. This on-site calibration method lifts the dependence on the uniform calibration field and reduces significantly the time required for calibration. The calibration source can be generated by cutting off the voltage source in parallel to the calibration coil, which greatly reduces the cost of the signal generator and provides a better solution for realizing the embedded self-test devices. Experimental results show that the proposed method effectively improves the calculation accuracy of the apparent resistivity.     

Monitoring ephemeral headwater streams: a paired‐sensor approach

This paper introduces a paired‐sensor approach to monitoring ephemeral streamflow. Part of this approach includes the design of a new flow detection sensor. This flow detection sensor addresses the limitation of previous electronic resistance sensors that use water presence as a proxy for flow for assessing hydrological connectivity, by explicitly measuring flow presence. Using paired electronic resistance and flow detection sensors, this paper evaluates the performance of each sensor individually, and as a pair. Individually, the sensors were tested for the amount of noise they contain and the types of errors they were prone to committing. As a paired set, the sensors were analysed by the percent of time they were in valid states versus invalid states. Valid states included when water was present but flow was absent, when water and flow were both present and when water and flow were both absent during a storm. One invalid case existed, where the sensors recorded flow presence but not water presence. These valid and invalid cases were assessed using data collected from sensor networks established at two study sites in southern Ontario. This analysis was completed for the overall corroboration at each site, for each storm at each site and based on the relative position of the sensors in the channel at each site. The sensors were in valid states 83% and 94% of the time at each respective study site. Differences in local site conditions were found to affect the performance of the sensor network; however, no significant correlation was found between storm characteristics and sensor performance. Particularly, bed roughness was found to be a factor as it restricted the placement of the sensors. Despite this, the paired‐sensor network helps to increase the understanding of the flow dynamics within headwater streams by explicitly separating the two hydrological characteristics. A discussion of the challenges, limitations and opportunities of monitoring ephemeral flow is presented, and insights into how to address those limitations are provided. Copyright © 2015 John Wiley & Sons, Ltd.     

Subgrid variability of snow water equivalent at operational snow stations in the western USA

The spatial distribution of snow water equivalent (SWE) is a key variable in many regional‐scale land surface models. Currently, the assimilation of point‐scale snow sensor data into these models is commonly performed without consideration of the spatial representativeness of the point data with respect to the model grid‐scale SWE. To improve the understanding of the relationship between point‐scale snow measurements and surrounding areas, we characterized the spatial distribution of snow depth and SWE within 1‐, 4‐ and 16‐km² grids surrounding 15 snow stations (snowpack telemetry and California snow sensors) in California, Colorado, Wyoming, Idaho and Oregon during the 2008 and 2009 snow seasons. More than 30 000 field observations of snowpack properties were used with binary regression tree models to relate SWE at the sensor site to the surrounding area SWE to evaluate the sensor representativeness of larger‐scale conditions. Unlike previous research, we did not find consistent high biases in snow sensor depth values as biases over all sites ranged from 74% overestimates to 77% underestimates. Of the 53 assessments, 27 surveys indicated snow station biases of less than 10% of the surrounding mean observed snow depth. Depth biases were largely dictated by the physiographic relationship between the snow sensor locations and the mean characteristics of the surrounding grid, in particular, elevation, solar radiation index and vegetation density. These scaling relationships may improve snow sensor data assimilation; an example application is illustrated for the National Operational Hydrologic Remote Sensing Center National Snow Analysis SWE product. The snow sensor bias information indicated that the assimilation of point data into the National Operational Hydrologic Remote Sensing Center model was often unnecessary and reduced model accuracy. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling the effect of low soil temperatures on transpiration by Scots pine

For ecosystem modelling of the Boreal forest it is important to include processes associated with low soil temperature during spring‐early summer, as these affect the tree water uptake. The COUP model, a physically based SVAT model, was tested with 2 years of soil and snow physical measurements and sap flow measurements in a 70‐year‐old Scots pine stand in the boreal zone of northern Sweden. During the first year the extent and duration of soil frost was manipulated in the field. The model was successful in reproducing the timing of the soil warming after the snowmelt and frost thaw. A delayed soil warming, into the growing season, severely reduced the transpiration. We demonstrated the potential for considerable overestimation of transpiration by the model if the reduction of the trees' capacity to transpire due to low soil temperatures is not taken into account. We also demonstrated that the accumulated effect of aboveground conditions could be included when simulating the relationship between soil temperature and tree water uptake. This improved the estimated transpiration for the control plot and when soil warming was delayed into the growing season. The study illustrates the need of including antecedent conditions on root growth in the model in order to catch these effects on transpiration. The COUP model is a promising tool for predicting transpiration in high‐latitude stands. Copyright © 2006 John Wiley & Sons, Ltd.