Comparing Three Methods of Sampling Throughfall in a Declining Coniferous Forest at a low Rainfall Site
The Mayson Lake Hydrological Processes Study area is located in the southern interior of British Columbia ∼ 60 km NNW of the City of Kamloops on the Thompson - Bonaparte Plateau (51.2° N, 120.4° W; 1260 m a.m.s.l.). During the summer of 2008 throughfall was measured in a mature declining mixed lodgepole pine (Pinus contorta var. latifolia Dougl.) - hybrid spruce (Picea glauca (Moench) Voss. x engelmanni Perry x Engelm.) - subalpine fir (Abies lasiocarpa (Hook.) Nutt.) stand, where pines were at the grey - attack stage of a mountain pine beetle (Dendroctonus ponderosae Scolytidae) infestation. Throughfall was estimated on a rainfall event basis using three sampling strategies: 32 stationary wedge gauges, 32 roving wedge gauges that were moved periodically during the study period, and 16 stationary trough gauges. The wedge gauges had a catch area of 36 cm2 each, while the trough gauges had a catch area of 2900 cm2 each, ∼ 80 times larger than the wedge gauges. Throughfall depth (mm) for all three sampling methods followed a power relationship with rainfall depth (mm). No significant difference in the slopes or intercepts of the three power relationships were found (α = 0.05). Thus the throughfall data were pooled to give the following equation relating throughfall depth (mm) to event rainfall depth (mm): TF = 0.348Pg1.33, r2 = 0.93, n = 14. An efficiency ratio was derived for this study to compare the sampling accuracy among the three sampling methods used. The efficiency ratio ER between two sampling methods was calculated as n1 / n2, where n1 and n2 are the number of samples required to meet a statistical objective using the method that produces the lowest and highest coefficient of variation (CV) values, respectively. The number of required samples (gauges) for a given method, ni, is found using: t2 x CV2 / CI2, where t is the student t value and CI is the desired confidence interval around the mean expressed as a percentage. Assuming t = 2 and keeping CI constant at 10 %, ni may be equated with 0.04 CV2. At the rainfall event scale trough gauges were more efficient at sampling throughfall than wedge gauges with ER values ranging from 1.4 to 3.3. However, at the season-long time scale wedge gauges that were periodically relocated (gauges were moved after approximately 15 mm of rain fell) provided the most accurate throughfall estimates. The ER values derived for season-long throughfall were 1.5 and 1.8 when roving wedge gauges were compared to stationary troughs and stationary wedge gauges, respectively.The results of this study suggest that using a roving wedge gauge method, and thus being able to sum the errors of individual event estimates quadratically, provides a more accurate estimate of season-long throughfall than stationary trough gauges - even with catch areas ∼ 80 times greater than wedge gauges. A total of 32 roving wedge gauges were found to provide an estimate of the mean season-long throughfall depth to within 10 % at the 95 % confidence level, while 49 and 58 stationary trough and stationary wedge gauges would have had to been used to provide the same degree of accuracy, respectively.
Spatio-temporal Variability of Stemflow Volume in a Beech-Yellow Poplar Forest in Relation to Tree Species and Size
Stemflow is a localized point input at the base of trees that can account for more than 10% of the incident gross precipitation in deciduous forests. Despite the fact that stemflow has been documented to be of hydropedological importance, affecting soil moisture patterns, soil erosion, soil chemistry, and the distribution of understory vegetation, our current understanding of the temporal variability of stemflow yield is poor. The aim of the present study, conducted in a beech-yellow poplar forest in northeastern Maryland (39°42'N, 75°50'W), was to better understand the temporal and variability of stemflow production from Fagus grandifolia Ehrh. (American beech) and Liriodendron tulipifera L. (yellow poplar) in relation to meteorological conditions and season in order to better assess its importance to canopy-soil interactions. The experimental plot had a stand density of 225 trees/ha, a stand basal area of 36.8 sq. m/ha, a mean dbh of 40.8 cm, and a mean tree height of 27.8 m. The stand leaf area index (LAI) is 5.3. Yellow poplar and beech constitute three- quarters of the stand basal area. Using a high resolution (5 min) sequential stemflow sampling network, consisting of tipping-bucket gauges interfaced with a Campbell CR1000 datalogger, the temporal variability of stemflow yield was examined. Beech produced significantly larger stemflow amounts than yellow poplar. The amount of stemflow produced by individual beech trees in 5 minute intervals reached three liters. Stemflow yield and funneling ratios decreased with increasing rain intensity. Temporal variability of stemflow inputs were affected by the nature of incident gross rainfall, season, tree species, tree size, and bark water storage capacity. Stemflow was greater during the leafless period than full leaf period. Stemflow yield was greater for larger beech trees and smaller yellow poplar trees, owing to differences in bark water storage capacity. The findings of this study indicate that stemflow has a detectable affect on soil moisture patterning and the hydraulic conductivity of forest soils.
A Tree-based Approach for Modelling Interception Loss From Evergreen Oak Mediterranean Savannas
In sparse forests, trees occur as widely spaced individuals rather than as a continuous forest canopy. Therefore, interception loss for this vegetation type can be more adequately modelled if the overall forest evaporation is derived by scaling up the evaporation from individual trees. Evaporation rate for a single tree can be estimated using a simple Dalton-type diffusion equation for water vapour as long as its surface temperature is known. From theory, this temperature is shown to be dependent upon the available energy and windspeed. However, surface temperature of a fully saturated tree crown, under rainy conditions, will approach the wet bulb temperature as the energy input to the tree reduces to zero. This was experimentally confirmed from measurements of the radiation balance and surface temperature of an isolated tree crown. Thus, evaporation of intercepted rainfall can be estimated using an equation which only requires knowledge of the air dry and wet bulb temperatures and of the bulk tree crown aerodynamic conductance. This was taken as the basis of a new approach for modelling interception loss from savanna-type woodland: first, the aforementioned equation was combined with the Gash's analytical model to estimate interception loss from isolated trees; second, interception loss was scaled up to the entire forest accounting for the canopy cover fraction. This modelling approach was tested using data from two Mediterranean savanna-type oak woodlands in southern Portugal. For both sites, simulated interception loss agreed well with the observations indicating the adequacy of this new methodology for modelling interception loss by isolated trees in savanna-type ecosystems. Furthermore, the proposed approach is physically based and only requires a limited amount of data.
Application of Wireless Sensor Networks for Environmental Monitoring
The application of wireless sensor networks (WSNs) for environmental monitoring enhances measurements over multiple locations and reduces the manpower for data collection. This study examines the applicability of WSNs for sap flow monitoring, which can benefit land-surface modeling with a better understanding and representation of plant water use phenomena. Two sap flow sensor designs are presented and their performance is tested against their expensive commercial sensor counterparts. These sensors are then integrated into a WSN. The data quality of the sap flow measurements is dependent upon the data sampling frequency. When sap flow monitoring is integrated into a WSN, a tradeoff is created between the measured data quality and the battery life of the wireless network. This study examines the tradeoff to determine an optimal sampling frequency for wireless sap flow monitoring.
An Automated Instrument for the Measurement of Bark Microrelief
Bark microrelief is of importance to the physiological ecology of forested ecosystems because it has been documented to influence the distribution of corticolous lichens, stemflow generation, and forest biogeochemical cycles. Hitherto no instrument existed to characterize the inherent variability of bark microrelief with high spatial resolution. Our newly-designed bark microrelief instrument, the LaserBarkTM, consists of a hinged ring, laser rangefinder, and motor linked to a standard laptop. The LaserBarkTM produces trunk cross- sections at a 0.33 degree horizontal resolution and detects bark ridge-to furrow heights at < 1 mm resolution. The LaserBarkTM was validated by comparing measurements of bark microrelief between the instrument and digital calipers. The mean absolute error of the instrument was 0.83 mm. Our bark microrelief instrument can supply critical requisite information of bark microstructure that be used by researchers to interpret the distribution of lichens and bryophytes on tree surfaces, relate stemflow yield and chemistry to bark microrelief, and provide detailed measurements of the changes of bark microrelief with stem dehydration. In short, the LaserBarkTM can be used to gain a more holistic understanding of the functional ecology of forest ecosystems.
Model Simulation of Urban Evapotranspiration Rates Given Spatial Changes in Land Cover and Elevation
Urban heat islands (UHI) emerge due to changes in albedo and imperviousness as compared with surrounding countryside, and UHI mitigation plans have focused on increasing urban tree cover. Trees can cool urban areas by direct shading and indirect evapotranspiration. Our goal is to create spatially distributed estimates of tree evapotranspiration during the growing season, to use in human thermal comfort models and other UHI simulations. We are modifying tree anatomy and growth functions in the USDA Forest Service Urban Forest Effects (UFORE) model. Modification represents the spatial variation of soil moisture and canopy radiation, which regulate evapotranspiration. Surface elevation derived topographic indices and land cover maps, including NLCD and aerial photographs, are used to adjust weather station estimates of radiation and soil moisture. Tree species and initial anatomy were selected from data gathered by the USDA Forest Service from plots in Syracuse, New York. Model estimates of evapotranspiration were generated for 30m by 30m pixels, and represented soil water and radiation constraints by modifying parameters in the Penman Monteith equations. Future work involves incorporating land cover and topographic data uncertainty into soil moisture and radiation constraints, which would be represented through Monte Carlo simulations. Applications of this research will be considered for the UFORE model in managing urban forest tree plantings to mitigate UHI impacts.
Validation of simulated surface states against observations over the Southern Great Plains: Implications for accurate modeling of precipitation-soil moisture interactions
Atmospheric precipitation is an important factor in controlling spatial and temporal patterns of the soil moisture, especially in arid and semi-arid regions. Noah and Mosaic LSMs, available within NASA's Land Information System (LIS) framework, were used to simulate surface and subsurface state variables. Both models were configured at 0.1x0.1 latitude-longitude grid over the domain (with 200x80 grid points) covering south-central United States. In order to produce realistic soil moisture fields, both LSMs were integrated for 2.5 year period (from 1 Jan. 2005 to 31 Oct. 2008) using NLDAS forcing fields and starting from a constant 30 % volumetric soil moisture (SM) content. Results of these simulations were validated against in-situ point-scale soil moisture (available at SCAN sites) and surface fluxes (at ARM-CART sites) observations during Mar.-Oct. 2008. Observed and simulated linear trends and typical SM decaying times will be compared. To better understand precipitation (observed ammount and frequency) control on SM, precipitation-SM relationship was examined using a linear systems approach. Implications for potential quality improvement of surface and sub- surface states simulated with LSMs will be formulated.
Towards Improved Drought Understanding: Temporal Persistence of Soil Moisture Fields in Alberta, Canada
The devastating prairie drought, which affected western Canada from 1999-2004, is recognized as the countries most expensive natural disaster. The impacts of this drought have led to the call for increased drought-related research with a particular focus on better understanding the spatial and temporal evolution of soil moisture fields. Soil moisture is a critical hydrologic indicator of drought extent and severity; however, present understanding of soil moisture is impeded by a poor understanding of the evolution of soil moisture fields and a paucity of observations at sufficient spatial and temporal scales. As such, this study focuses on characterizing the temporal persistence of soil moisture fields in an agricultural region of Alberta from 2004- 2008. Specifically, the purpose of this study is to compare the temporal decorrelation of soil moisture anomalies over time, space and depth, and relate these differences to process controls. Using data from the Alberta Agricultural Drought Monitoring Network decorrelation times of soil moisture at depths of 5, 20, 50, and 100 cm are correlated with meso-scale controls on soil moisture (precipitation, evaporation and soil texture) over a 5-year period (2004 to 2008 inclusive). This is done in order to determine the relative influence of each on the temporal persistence of soil moisture fields. This study offers insight into the spatial and temporal stability of soil moisture anomaly fields and controls on their evolution.
Observational Evidence of the Impact of Groundwater Pumping on Streamflow: The High Plains Aquifer, USA.
Groundwater is an essential component of the terrestrial water cycle, a very important but poorly explained
system due to the complex interactions between its components. Although it is quite clear that the hydrological
cycle is being altered by human modifications such as land-use changes, urbanization and groundwater
pumping, our knowledge of the impacts of these modifications on the components of water cycle is very
limited. This study explores the influence of long-term, large-scale irrigational pumping on streamflow in the
High Plains aquifer using observational data to determine the effects of regional-scale human alterations on
the hydrological cycle with a particular attention to surface-subsurface water interactions. Groundwater and
streamflow data spanning the period of intensive irrigational development (1950-2000) in the region were
collected and analyzed to detect long-term, low-season and no-flow trends in streamflow with the help of basic
statistical techniques and the non-parametric Mann-Kendall test. Preliminary results indicate strong
decreasing trends in the long-term surface flow and ongoing research investigates other hydrologic variables
for trend detection in an attempt to establish a linkage between groundwater pumping and the observed trends
Applicability of the Green-Ampt Model Under Non-ideal Conditions
Green and Ampt presented the first physical-based equation for describing the infiltration of water into soil. It is based on the fundamental physics of infiltration and provides results that match well with empirical observations. The Green and Ampt model has been widely used in applied soil physics and hydrology owing to its simplicity, computational expediency, and satisfactory performance for a variety of hydrological applications. The model is used to estimate cumulative infiltration by assuming water flow into a vertical homogeneous soil that is infinite in depth. There is no water table, capillary fringe, or soil heterogeneity considered. In regional scale applications, these idealized conditions will often be violated, and it is presently unclear what implications this has for regional water resource models. This paper investigates under what conditions the Green-Ampt model is appropriate and how individual assumptions affect the applicability of the model. The Green-Ampt model is compared to the numerical solution of Richards' equation under non-ideal conditions. The numerical scheme has been tested with published simulation results and successfully reproduces moisture profiles with boundary conditions of constant pressure head, constant flux, or a dynamic infiltration condition at the top of a soil column. In this study, the infiltration capacity is the main concern. Therefore, the rainfall intensity was chosen to be greater than the saturated conductivity in all tests. Variable initial conditions, including the level of heterogeneity, with or without a water table and impermeable layer (e.g., frost table), and the depth of the soil, were used to test the rationality of the Green-Ampt model. Results demonstrate that even when the assumptions are relaxed, the Green-Ampt model often still provides reasonable results and can be amended to account for a variety of conditions.
A Spatiotemporal Analysis on the Correlation of Leaf Chlorophyll With Light-use-efficiencies Across a Heterogeneous Corn Field
Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (Cab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of spatiotemporal Cab estimates for optimizing CO2 fluxes simulated by a coupled water and carbon cycle model that implements an analytical, light-use-efficiency (LUE) based model of canopy resistance within a two-source energy balance scheme. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal value (LUEn) in response to variations in humidity, CO2 concentration, temperature (soil and air), wind speed, and direct beam vs. diffuse light composition. LUEn is typically indexed by vegetation class assuming conservation of LUE for major vegetation types under unstressed environmental conditions. LUEn is highly influential in modifying CO2 assimilation rates and may need further adjustment on a daily timescale to accommodate changes in plant phenology, physiological condition and nutrient status. Day to day variations in LUEn was assessed for a heterogeneous corn crop field in Maryland, U.S.A. through model calibration with eddy covariance CO2 flux tower observations. The optimized daily LUEn values were then compared to estimates of Cab integrated from gridded Cab maps as a weighted sum over the tower flux source area. A continuous spatiotemporal Cab record (spanning the period from 3 weeks after leaf emergence through corn tasseling and silking and a stage of leaf senescence) was generated by fusing extensive in-situ measurements with retrievals generated from 1 m resolution aircraft imagery using an integrated radiative transfer modeling tool (validated to 10% accuracy). Extreme environmental conditions imposed highly variable degrees of plant stress across the field due to spatial variations in soil texture, topography and sub-surface hydrology. The resultant daily changes in Cab within the tower flux source area generally correlated well with corresponding changes in daily calibrated LUEn values indicating utility of Cab for delineating spatiotemporal variations in LUEn. The results open new possibilities for using leaf chlorophyll estimates for optimizing estimates of carbon and water fluxes within a coupled framework.
Foliage Temperature Profile Responses to Stomatal Resistance and Foliage Density Profiles
Remotely sensed land surface temperatures provide valuable information regarding land surface processes such as the surface energy and water balances. However, it is now known that foliage and soil temperatures and even foliage skin temperatures at different levels within the same canopy, can vary by several K. This work was undertaken to improve our understanding of the processes that lead to vertical foliage temperature gradients. A multilayer canopy model was developed using a combination equation for each canopy layer and localized near-field (LNF) turbulent transport. The model was driven by data collected from a micrometeorological station at a dense grassland site in the Southern Great Plains, 1997, field experiment. The model was run with three vertical foliage density profiles and two stomatal resistance profiles for a total of six scenarios. Model results suggest that foliage temperature profiles are strongly affected by the canopy density and stomatal resistance profiles. The density profile determines the layers of canopy that absorb the most radiation for a given solar elevation angle. Dense portions of the canopy that receive a large fraction of net radiation tend to be warm. The enhanced transport efficiency near the canopy top tends to cool the upper layers, but this effect seems to be secondary to the radiation effect, since nearly all runs with uniform canopy density showed peak temperatures at the canopy top. In this study, the magnitude of the foliage temperature changed when the stomatal resistance profile was changed, but the basic shape of the foliage temperature profiles changed little with the stomatal resistance profile. The bulk behavior of the canopy, including production of sensible and latent heat fluxes and radiometric surface temperatures, was moderately affected by the canopy density and stomatal resistance profiles tested.