Estimation of evapotranspiration and its components from an apple orchard in northwest China using sap flow and water balance methods

Field experiments were conducted to investigate the effects of leaf area index and soil moisture content on evapotranspiration and its components within an apple orchard in northwest China for 2 years. Evapotranspiration in the non‐rainfall period was estimated using two approaches: the soil water balance method based on tube‐type time‐domain reflection measurements, and sap flow plus micro‐lysimeter methods. The two methods were in good agreement, with differences usually less than 10%. The components of evapotranspiration varied with canopy development. During spring and autumn, soil evaporation was dominating as result of low leaf area index. In summer, plant transpiration became significant, with an average transpiration to evapotranspiration ratio of 0·87. The crop coefficient K_c showed a strong linear dependence on leaf area index. The water stress coefficient K_s was around 1·0 when soil moisture was above 23% and started to decrease linearly after that. This study demonstrates that prediction of evapotranspiration in apple orchards can be made using the Food and Agriculture Organization's crop coefficient method from commonly available meteorological data in the area. Copyright © 2006 John Wiley & Sons, Ltd.     

Differences in soil moisture in two Middle Eastern oak forests: Comparing the effects of trees and soil composition

The incidence of large rain events in Mediterranean ecosystems vary among years. Summer aridity is interpreted as a resetting event, eliminating previous soil‐moisture dynamics. The dynamics of soil moisture and retention are critical to tree survival, particularly in dry regions. This study examines the long‐term soil water content (θ_V) dynamics in two distinct locations within the forest, under the canopy and forest clearing, within two diverse oak forests: subhumid mixed oak forests (MG) and semiarid monospecific oak woodlands (YE). Plots were established at small‐scale catchments and soil water contents were measured during 2010–2013, at three depths in the two different locations. Cumulative rainfall was used as an independent proxy for θ_V analysis. A novel bell‐bilogistic mathematical model of wetting, saturation, and drying arms was developed. We aimed to study the θ_V distribution differences between soil profiles giving the large climatic gradient between the two forested sub basins, the differences in vegetation traits along with soil attributes. We further aimed at determining the role of an individual tree in regulating soil‐moisture dynamics. We hypothesized the occurrence of distinct responses between sites in all soil‐moisture indices with higher θ_V at the wetter site. We tested the hypothesis that seasonal cumulative rainfall dictates the variations in soil‐moisture regimes throughout contiguous years. Annual rainfall was higher than long‐term average throughout the study. Soil profiles under the canopies at both sites were consistently wetter. Infiltration and depletion constants were higher at MG whereas maximum soil moisture was higher at YE. Homogenous recharge patterns were seen at MG although YE evinced more variation. Oaks had no effect on recharge at MG compared with the forest clearing. Soil properties primarily affected the wetting arm whereas vegetation composition regulated the drying arm. Mixed‐stands characterized by ever‐green and deciduous species may maintain favourable soil‐moisture conditions, in comparison with other mixed stand morphologies. The increasing role of slacking forces in infiltration process may alter the interaction between trees and herbaceous vegetation.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective,laboratory and in situ estimates

Simulation of soil moisture content requires effective soil hydraulic parameters that are valid at the modelling scale. This study investigates how these parameters can be estimated by inverse modelling using soil moisture measurements at 25 locations at three different depths (at the surface, at 30 and 60 cm depth) on an 80 by 20 m hillslope. The study presents two global sensitivity analyses to investigate the sensitivity in simulated soil moisture content of the different hydraulic parameters used in a one‐dimensional unsaturated zone model based on Richards' equation. For estimation of the effective parameters the shuffled complex evolution algorithm is applied. These estimated parameters are compared to their measured laboratory and in situ equivalents. Soil hydraulic functions were estimated in the laboratory on 100 cm³ undisturbed soil cores collected at 115 locations situated in two horizons in three profile pits along the hillslope. Furthermore, in situ field saturated hydraulic conductivity was estimated at 120 locations using single‐ring pressure infiltrometer measurements. The sensitivity analysis of 13 soil physical parameters (saturated hydraulic conductivity (K_s), saturated moisture content (θ_s), residual moisture content (θ_r), inverse of the air‐entry value (α), van Genuchten shape parameter (n), Averjanov shape parameter (N) for both horizons, and depth (d) from surface to B horizon) in a two‐layer single column model showed that the parameter N is the least sensitive parameter. K_s of both horizons, θ_s of the A horizon and d were found to be the most sensitive parameters. Distributions over all locations of the effective parameters and the distributions of the estimated soil physical parameters from the undisturbed soil samples and the single‐ring pressure infiltrometer estimates were found significantly different at a 5% level for all parameters except for α of the A horizon and K_s and θ_s of the B horizon. Different reasons are discussed to explain these large differences. Copyright © 2004 John Wiley & Sons, Ltd.     

SNOW WETNESS ESTIMATES OF VEGETATED TERRAIN FROM SATELLITE PASSIVE MICROWAVE DATA

The Special Sensor Microwave/Imager (SSM/I) radiometer is a useful tool for monitoring snow wetness on a large scale because water content has a significant effect on the microwave emissions at the snowpack surface. To date, SSM/I snow wetness algorithms, based on statistical regression analysis, have been developed only for specific regions. Inadequate ground-based snow wetness measurements and the non-linearity between SSM/I brightness temperatures (T_Bs) and snow wetness over varied vegetation covered terrain has impeded the development of a general model. In this study, we used a previously developed linear relationship between snowpack surface wetness (% by volume) and concurrent air temperature (°C) to estimate the snow wetness at ground weather stations. The snow condition (snow free, dry, wet or refrozen snow) of each SSM/I pixel (a 37 × 29 km area at 37.0 GHz) was determined from ground-measured weather data and the T_B signature. SSM/I T_Bs of wet snow were then linked with the snow wetness estimates as an input/output relationship. A single-hidden-layer back-propagation (backprop) artificial neural network (ANN) was designed to learn the relationships. After training, the snow wetness values estimated by the ANN were compared with those derived by regression models. Results show that the ANN performed better than the existing regression models in estimating snow wetness from SSM/I data over terrain with different amounts of vegetation cover.     

Spatio‐temporal distribution of near‐surface and root zone soil moisture at the catchment scale

Soil moisture is highly variable both spatially and temporally. It is widely recognized that improving the knowledge and understanding of soil moisture and the processes underpinning its spatial and temporal distribution is critical. This paper addresses the relationship between near‐surface and root zone soil moisture, the way in which they vary spatially and temporally, and the effect of sampling design for determining catchment scale soil moisture dynamics. In this study, catchment scale near‐surface (0–50 mm) and root zone (0–300 mm) soil moisture were monitored over a four‐week period. Measurements of near‐surface soil moisture were recorded at various resolutions, and near‐surface and root zone soil moisture data were also monitored continuously within a network of recording sensors. Catchment average near‐surface soil moisture derived from detailed spatial measurements and continuous observations at fixed points were found to be significantly correlated (r² = 0·96; P = 0·0063; n = 4). Root zone soil moisture was also found to be highly correlated with catchment average near‐surface, continuously monitored (r² = 0·81; P < 0·0001; n = 26) and with detailed spatial measurements of near‐surface soil moisture (r² = 0·84). The weaker relationship observed between near‐surface and root zone soil moisture is considered to be caused by the different responses to rainfall and the different factors controlling soil moisture for the soil depths of 0–50 mm and 0–300 mm. Aspect is considered to be the main factor influencing the spatial and temporal distribution of near‐surface soil moisture, while topography and soil type are considered important for root zone soil moisture. The ability of a limited number of monitoring stations to provide accurate estimates of catchment scale average soil moisture for both near‐surface and root zone is thus demonstrated, as opposed to high resolution spatial measurements. Similarly, the use of near‐surface soil moisture measurements to obtain a reliable estimate of deeper soil moisture levels at the small catchment scale was demonstrated. Copyright © 2007 John Wiley & Sons, Ltd.     

Developing an empirical model of canopy water flux describing the common response of transpiration to solar radiation and VPD across five contrasting woodlands and forests

A modified Jarvis–Stewart model of canopy transpiration (E_c) was tested over five ecosystems differing in climate, soil type and species composition. The aims of this study were to investigate the model's applicability over multiple ecosystems; to determine whether the number of model parameters could be reduced by assuming that site‐specific responses of E_c to solar radiation, vapour pressure deficit and soil moisture content vary little between sites; and to examine convergence of behaviour of canopy water‐use across multiple sites. This was accomplished by the following: (i) calibrating the model for each site to determine a set of site‐specific (SS) parameters, and (ii) calibrating the model for all sites simultaneously to determine a set of combined sites (CS) parameters. The performance of both models was compared with measured E_c data and a statistical benchmark using an artificial neural network (ANN). Both the CS and SS models performed well, explaining hourly and daily variation in E_c. The SS model produced slightly better model statistics [R² = 0.75–0.91; model efficiency (ME) = 0.53–0.81; root mean square error (RMSE) = 0.0015–0.0280 mm h^‐1] than the CS model (R² = 0.68–0.87; ME = 0.45–0.72; RMSE = 0.0023–0.0164 mm h^‐1). Both were highly comparable with the ANN (R² = 0.77–0.90; ME = 0.58–0.80; RMSE = 0.0007–0.0122 mm h^‐1). These results indicate that the response of canopy water‐use to abiotic drivers displayed significant convergence across sites, but the absolute magnitude of E_c was site specific. Period totals estimated with the modified Jarvis–Stewart model provided close approximations of observed totals, demonstrating the effectiveness of this model as a tool aiding water resource management. Analysis of the measured diel patterns of water use revealed significant nocturnal transpiration (9–18% of total water use by the canopy), but no Jarvis–Stewart formulations are able to capture this because of the dependence of water‐use on solar radiation, which is zero at night. Copyright © 2012 John Wiley & Sons, Ltd.     

Towards quantifying the negative feedback regulation of peatland evaporation to drought

The frequency and intensity of drought is projected to increase within the boreal region under future climatic conditions. Peatlands are widely considered to regulate water loss under drought conditions, increasing surface resistance (r_s) and reducing evaporative losses. This maintains peat moisture content, increasing the resilience of these globally important carbon stores. However, the magnitude and form of this important negative feedback response remains uncertain. To address this, we monitored the response of r_s to drought within four peat cores under controlled meteorological conditions. When the water‐table was dropped to a depth of 0.30 m and the humidity reduced to ≤40%, a step shift in r_s from ~50 s m^‐1 up to 1000 s m^‐1 was observed within burned and unburned peat, which virtually shuts down evaporation, limiting water loss. We show that measured near‐surface tension cannot be used to directly calculate this transition in peat surface resistance. However, empirical relationships that account for strong vertical variations in tension through the near‐surface and/or disequilibrium between pore air and near‐surface pore water pressure provide the potential to incorporate this negative feedback response into peatland ecohydrological models. Further observations are necessary to examine this response under dynamic atmospheric conditions. We suggest that the link between surface temperature and evaporation provides potential to further examine this feedback in either burned peatlands or peatlands with a low vascular vegetation cover. Copyright © 2013 John Wiley & Sons, Ltd.     

AMSR‐E algorithm for snowmelt onset detection in sub‐arctic heterogeneous terrain

The onset of snowmelt in the upper Yukon River basin, Canada, can be derived from brightness temperatures (T_b) obtained by the Advanced Microwave Scanning Radiometer for EOS (AMSR‐E) on NASA's Aqua satellite. This sensor, with a resolution of 14 × 8 km² for the 36·5 GHz frequency, and two to four observations per day, improves upon the twice‐daily coverage and 37 × 28 km² spatial resolution of the Special Sensor Microwave Imager (SSM/I). The onset of melt within a snowpack causes an increase in the average daily 36·5 GHz vertically polarized T_b as well as a shift to high diurnal amplitude variations (DAV) as the snow melts during the day and re‐freezes at night. The higher temporal and spatial resolution makes AMSR‐E more sensitive to sub‐daily T_b oscillations, resulting in DAV that often show a greater daily range compared to SSM/I. Therefore, thresholds of T_b > 246 K and DAV > ± 10 K developed for use with SSM/I have been adjusted for detecting the onset of snowmelt with AMSR‐E using ground‐based surface temperature and snowpack wetness relationships. Using newly developed thresholds of T_b > 252 K and DAV > ± 18 K, AMSR‐E derived snowmelt onset correlates well with SSM/I observations in the small subarctic Wheaton River basin through the 2004 and 2005 winter/spring transition. In addition, the onset of snowmelt derived from AMSR‐E data gridded at a higher resolution than the SSM/I data indicates that finer‐scale differences in elevation and land cover affect the onset of snowmelt and are detectable with the AMSR‐E sensor. On the basis of these observations, the enhanced resolution of AMSR‐E is more effective than SSM/I at delineating spatial and temporal snowmelt dynamics in the heterogeneous terrain of the upper Yukon River basin. Copyright © 2007 John Wiley & Sons, Ltd.     

On the potential of MetOp ASCAT‐derived soil wetness indices as a new aperture for hydrological monitoring and prediction: a field evaluation over Luxembourg

In situ soil moisture data from the Bibeschbach experimental catchment in Luxembourg are used to evaluate relative surface soil moisture observed with the MetOp‐A Advanced Scatterometer (ASCAT). Filtered and bias‐corrected surface soil wetness indices (SWIs) derived from coarse‐resolution (25 km) C‐band scatterometer observations are shown to be highly correlated (r = 0.86) with catchment‐averaged soil moisture measured in the field. The combination of ASCAT and ENVISAT Advanced Synthetic Aperture Radar (ASAR) data sets yields high‐resolution (1 km) relative surface soil moisture that is equally well correlated with in situ measurements. It is concluded that for soil moisture monitoring applications at a catchment scale, the two soil moisture products are equivalent. The best correlation between the SWI derived from ASCAT and ASCAT‐ASAR with in situ soil moisture observations at ca. 5 cm depth is obtained with a characteristic time length parameter T equal to 288 h. These results suggest that satellite‐derived surface soil wetness may serve as proxy for soil storage that enables the monitoring of abrupt switches in river system dynamics to appear when an effective field capacity is exceeded and rapid subsurface stormflow is initiated. In catchments where soil moisture is the main controlling factor of rapid subsurface flow, MetOp ASCAT–derived SWI has the potential to monitor how a river system approaches a critical threshold. Copyright © 2011 John Wiley & Sons, Ltd.     

Atmospheric and soil moisture controls on evapotranspiration from above and within a Western Boreal Plain aspen forest

The Western Boreal Plain of North Central Alberta comprises a mosaic of wetlands and aspen (Populus tremuloides) dominated uplands where precipitation (P) is normally exceeded by evapotranspiration (ET). As such these systems are highly susceptible to the climatic variability that may upset the balance between P and ET. Above canopy evapotranspiration (ET_C) and understory evapotranspiration (ET_B) were examined using the eddy covariance technique situated at 25.5 m (7.5 m above tree crown) and 4.0 m above the ground surface, respectively. During the peak period of the growing seasons (green periods), ET_C averaged 3.08 mm d^?1 and 3.45 mm d^?1 in 2005 and 2006, respectively, while ET_B averaged 1.56 mm d^?1 and 1.95 mm d^?1. Early in the growing season, ET_B was equal to or greater than ET_C once understory development had occurred. However, upon tree crown growth, ET_B was lessened due to a reduction in available energy. ET_B ranged from 42 to 56% of ET_C over the remainder of the snow‐free seasons. Vapour pressure deficit (VPD) and soil moisture (θ) displayed strong controls on both ET_C and ET_B. ET_C responded to precipitation events as the developed tree crown intercepted and held available water which contributed to peak ET_C following precipitation events >10 mm. While both ET_C and ET_B were shown to respond to VPD, soil moisture in the rooting zone is shown to be the strongest control regardless of atmospheric demand. Further, soil moisture and tension data suggest that rooting zone soil moisture is controlled by the redistribution of soil water by the aspen root system. Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluation of multiple surface soil moisture for Korean regional flux monitoring network sites: Advanced Microwave Scanning Radiometer E,land surface model,and ground measurements

In the past few decades, there have been great developments in remotely sensed soil moisture, with validation efforts using land surface models (LSMs) and ground‐based measurements, because soil moisture information is essential to understanding complex land surface–atmosphere interactions. However, the validation of remotely sensed soil moisture has been very limited because of the scarcity of the ground measurements in Korea. This study validated Advanced Microwave Scanning Radiometer E (AMSR‐E) soil moisture data with the Common Land Model (CLM), one of the most widely used LSMs, and ground‐based measurements at two Korean regional flux monitoring network sites. There was reasonable agreement regarding the different soil moisture products for monitoring temporal trends except National Snow and Ice Data Centre (NSIDC) AMSR‐E soil moisture, albeit there were essential comparison limitations by different spatial scales and soil depths. The AMSR‐E soil moisture data published by the National Aeronautics and Space Administration and Vrije Universiteit Amsterdam (VUA) showed potential to replicate temporal variability patterns (root‐mean‐square errors = 0·10–0·14 m³ m^?3 and wet BIAS = 0·09 ? 0·04 m³ m^?3) with the CLM and ground‐based measurements. However, the NSIDC AMSR‐E soil moisture was problematic because of the extremely low temporal variability and the VUA AMSR‐E soil moisture was relatively inaccurate in Gwangneung site characterized by complex geophysical conditions. Additional evaluations should be required to facilitate the use of recent and forthcoming remotely sensed soil moisture data from Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive missions at representative future validation sites. Copyright © 2011 John Wiley & Sons, Ltd.     

Sensitivity of soil moisture field evolution to rainfall forcing

In this paper the temporal behaviour of soil moisture is modelled and statistically characterized by use of the zero‐dimensional model for soil moisture dynamics and the rectangular pulses Poisson process model for rainfall forcing. The mean, covariance and spectral density function of soil moisture (both instantaneous and locally averaged cases) are analytically derived to evaluate its sensitivity to the model parameters. Finally, the probability density function of soil moisture is derived to evaluate the effect of rainfall forcing. All the model parameters used have been tuned to the Monsoon '90 data. Results can be summarized as follows. (1) Only the soil moisture model parameters (η and nZ_r) are found to affect the autocorrelation function in a distinguishable manner. On the other hand, both the rainfall model parameter (θ) and the effective soil depth (nZ_r) are found to be of impact to the soil moisture spectrum. However, as the smoothing (or damping) effect of soil is so dominant, about ±20% variation of one parameter seems not to affect significantly the second‐order statistics of soil moisture. (2) More difference can be found by applying a longer averaging time, which is found to obviously decrease the variance but increase the correlation even though no overlapping between neighbouring soil moisture data was allowed. (3) Among rainfall model parameters, the arrival rate (λ) was found to be most important for the soil moisture evolution. When increasing the arrival rate of rainfall, the histogram of soil moisture shifts its peak to a certain value as well as becomes more concentrated around the peak. However, by decreasing the arrival rate of rainfall, a much smaller (almost to zero) mean value of soil moisture was estimated, even though the total volume of rainfall remained constant. This indicates that desertification may take place without decreasing the total volume of rainfall. Copyright © 2005 John Wiley & Sons, Ltd.     

Lateral flow thresholds for aspen forested hillslopes on the Western Boreal Plain,Alberta, Canada

To predict the long‐term sustainability of water resources on the Boreal Plain region of northern Alberta, it is critical to understand when hillslopes generate runoff and connect with surface waters. The sub‐humid climate (P ≤ ET) and deep glacial sediments of this region result in large available soil storage capacity relative to moisture surpluses or deficits, leading to threshold‐dependent rainfall‐runoff relationships. Rainfall simulation experiments were conducted using large magnitude and high intensity applications to examine the thresholds in precipitation and soil moisture that are necessary to generate lateral flow from hillslope runoff plots representative of Luvisolic soils and an aspen canopy. Two adjacent plots (areas of 2·95 and 3·4 m²) of contrasting antecedent moisture conditions were examined; one had tree root uptake excluded for two months to increase soil moisture content, while the second plot allowed tree uptake over the growing season resulting in drier soils. Vertical flow as drainage and soil moisture storage dominated the water balances of both plots. Greater lateral flow occurred from the plot with higher antecedent moisture content. Results indicate that a minimum of 15–20 mm of rainfall is required to generate lateral flow, and only after the soils have been wetted to a depth of 0·75 m (C‐horizon). The depth and intensity of rainfall events that generated runoff > 1 mm have return periods of 25 years or greater and, when combined with the need for wet antecendent conditions, indicate that lateral flow generation on these hillslopes will occur infrequently. Copyright © 2008 John Wiley & Sons, Ltd.     

Calibration of an integrated land surface process and radiobrightness (LSP/R) model during summertime

In this study, a soil vegetation and atmosphere transfer (SVAT) model was linked with a microwave emission model to simulate microwave signatures for different terrain during summertime, when the energy and moisture fluxes at the land surface are strong. The integrated model, land surface process/radiobrightness (LSP/R), was forced with weather and initial conditions observed during a field experiment. It simulated the fluxes and brightness temperatures for bare soil and brome grass in the Northern Great Plains. The model estimates of soil temperature and moisture profiles and terrain brightness temperatures were compared with the observed values. Overall, the LSP model provides realistic estimates of soil moisture and temperature profiles to be used with a microwave model. The maximum mean differences and standard deviations between the modeled and the observed temperatures (canopy and soil) were 2.6 K and 6.8 K, respectively; those for the volumetric soil moisture were 0.9% and 1.5%, respectively. Brightness temperatures at 19 GHz matched well with the observations for bare soil, when a rough surface model was incorporated indicating reduced dielectric sensitivity to soil moisture by surface roughness. The brightness temperatures of the brome grass matched well with the observations indicating that a simple emission model was sufficient to simulate accurate brightness temperatures for grass typical of that region and surface roughness was not a significant issue for grass-covered soil at 19 GHz. Such integrated SVAT-microwave models allow for direct assimilation of microwave observations and can also be used to understand sensitivity of microwave signatures to changes in weather forcings and soil conditions for different terrain types.     

Impact of tree planting configuration and grazing restriction on canopy interception and soil hydrological properties: implications for flood mitigation in silvopastoral systems

Compaction of upper soil layers by intensive sheep grazing has been connected with increased local flood risk in silvopastoral systems. A 12‐week field study was conducted at the Henfaes Research Station near Bangor, Wales to compare canopy interception, soil water infiltration, and bulk density between a control pasture and two silvopastoral tree planting configurations: trees clumped in fenced‐off ungrazed plots and trees planted evenly and grazed. The study's aim was to characterize the potential of these tree planting configurations to reduce local flood risk. Automated throughfall gauges were installed in each silvopastoral treatment along with a similarly designed control gauge located in the grazed control pasture. Soil water infiltration and bulk density were measured 20 times in a stratified random design for each treatment and control. Results showed that the mean soil infiltration capacity in clumped configuration was 504% greater than the control pasture and 454% greater than the even spaced configuration. Average canopy interception was higher in the clumped configuration (34%) than in the even spaced configuration (28%). Soil bulk density was lower in the clumped configuration (0.87 Mg/m³) than in the control pasture (0.93 Mg/m³) and even spaced configuration (1 Mg/m³). Results suggest that silvopastoral systems are more likely to benefit from clumped and ungrazed tree configurations than from evenly‐spaced and grazed tree configurations because of enhanced infiltration, lower soil compaction, and increased canopy interception. Our findings support the growing evidence base that fenced‐off tree areas in silvopastoral settings can increase infiltration and thus reduce local flood risk. Copyright © 2015 John Wiley & Sons, Ltd.     

Energy budget above a temperate mixed forest in northeastern China

Components of the energy budget were measured continuously above a 300‐year‐old temperate mixed forest at the Changbaishan site, northeastern China, from 1 January to 31 December 2003, as a part of the ChinaFlux programme. The albedo values above the canopy were lower than most temperate forests, and the values for snow‐covered canopy were over 50% higher than for the snow‐free canopy. In winter, net radiation R_n was generally less than 5% of the summer value due to high albedo and low incoming solar radiation. The annual mean latent heat LE was 37·5 W m^?2, accounting for 52% of R_n. The maximum daily evaporation was about 4·6 mm day^?1 in summer. Over the year, the accumulated precipitation was 578 mm; this compares with 493 mm of evapotranspiration, which shows that more than 85% of water was returned to the atmosphere through evapotranspiration. The LE was strongly affected by the transpiration activity and increased quickly as the broadleaved trees began to foliate. The sensible heat H dropped at that time, although R_n increased. Consequently, the seasonal variation in the Bowen ratio β was clearly U‐shaped, and the minimum value (0·1) occurred on a sunny day just after rain, when most of the available energy was used for evapotranspiration. Negative β values occurred occasionally in the non‐growing season as a result of intensive radiative cooling and the presence of water on the surface. The β was very high (up to 13·0) in snow‐covered winter, when evapotranspiration was small due to low surface temperature and available soil water. Vegetation phenology and soil moisture were the key variables controlling the available energy partitioning between H and LE. Energy budget closure averaged better than 86% on a half‐hourly basis, with slightly greater closure on a daily basis. The degree of closure showed a dependence on friction velocity u*. Copyright © 2006 John Wiley & Sons, Ltd.     

First approximations of soil moisture retention curves using the filter‐paper method

Relationships between gravimetric soil moisture content (w) and matric potential (ϕ), and between volumetric soil moisture content (θ_v) and pressure head (h) were approximated for the unsaturated zone on Long Island, New York. Soil samples were collected from two sites using a hand auger. The soil moisture content was determined using the filter‐paper (w_f) and gravimetric (w) methods, respectively. The w_f was then used in an empirical equation to estimate ϕ_m. Each set of ϕ_m and w was combined with a straight‐line empirical model to obtain a w(ϕ_m) relationship. Soil ϕ_m was converted to h, and w to the volumetric moisture content θ_v, in order to produce a θ_v(h) curve. Graphical and statistical comparison showed that the resulting θ_v(h) curves fell within one order of magnitude of similar curves generated by a more sophisticated non‐linear model developed previously. The simplicity and low cost of the filter‐paper approach described in this study recommends it for preliminary studies of hydraulic properties in the unsaturated zone. Copyright © 2000 John Wiley & Sons, Ltd.