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Water SA

versión On-line ISSN 1816-7950
versión impresa ISSN 0378-4738

Water SA vol.36 no.1 Pretoria ene. 2010

 

Measurement of grassland evaporation using a surface-layer scintillometer

 

 

MJ SavageI,*; GO OdhiamboI; MG MengistuI; CS EversonII; C JarmainIII

ISoil-Plant-Atmosphere Continuum Research Unit, School of Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa
IICSIR Natural Resources and the Environment, c/o Soil-Plant-Atmosphere Continuum Research Unit, School of Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa
IIICSIR Natural Resources and the Environment, Stellenbosch, South Africa

 

 


ABSTRACT

A dual-beam surface-layer scintillometer (SLS) was used to estimate sensible heat flux (H) every 2 min for a path length of either 50 or 101 m, for more than 30 months in a mesic grassland in eastern South Africa. The SLS method relies on Monin-Obukhov similarity theory, the correlation between the laser beam signal amplitude variances and the covariance of the logarithm of the beam signal amplitude measured using 2 laser detectors. Procedures for checking SLS data integrity in real-time are highlighted as are the post-data collection rejection procedures. From the H estimates, using SLS and measurements of soil heat flux and net irradiance, evaporation rates were calculated as a residual of the shortened energy balance equation and compared with grass reference evaporation rates (ETo). Inconsistent hourly ETo values occur in the late afternoon due to the incorrect assumption that the soil heat flux is 10% of net irradiance. The SLS estimates of H and the estimates of evaporation rate as a residual compared favourably with those obtained using the Bowen ratio and eddy covariance methods for cloudless days, cloudy days and days with variable cloud. There was no evidence for the eddy covariance measurements of H being underestimated in comparison to the Bowen ratio and SLS measurements. On many days, the diurnal variation in SLS H was asymmetrical, peaking before noon.

Keywords: energy balance, Bowen ratio, eddy covariance, grass reference evaporation, rejection criteria.


 

 

Introduction

The possible prescription by government of methods for making a volumetric determination of water, for purposes of water allocation and setting charges in the case of activities resulting in stream flow reduction, is stated in the 1998 Republic of South Africa National Water Act. It is therefore important to consider how evaporation, and evaporation rate, can be measured or estimated routinely, with reliable accuracy and precision (Savage et al., 2004; Savage, 2009), for a range of land surface types. Determination of reliable and representative evaporation data using land-based instrumentation is an important issue in atmospheric research with respect to applications in agriculture, applied environmental sciences, hydrology and micrometeorology, and has particular value in validating remotely-sensed evaporation estimates. Long-term measurements of evaporation at different time scales and from different climate regions are not yet readily available (Jarmain et al., 2009).

Point (single-level), profile and path-weighted atmospheric measurements have been used to estimate sensible heat flux H. Profile measurements consist of measurements at 2 vertical positions above the surface in question and are used in the Bowen ratio (BR) method. Sensible heat flux is driven by vertical temperature differences between the canopy or soil surface and overlying air. By contrast, latent energy flux LE – from which evaporation rate may be calculated – is driven by vertical water vapour pressure differences between that which is measured just above the canopy or soil surface and that of overlying air. Point measurements of H = HEC and LE = LEEC are obtained by eddy covariance (EC), and path-weighted measurements of H = HSLS by scintillometry. All of these flux measurements have footprint representation. The flux footprint refers to the relative contribution of upwind surface sources to H, or LE, measured at a height above the canopy surface. Sensible heat flux H and latent energy flux LE are important components of the shortened energy balance. For a flat extensive surface, the shortened energy balance which neglects some terms – advection and canopy-stored heat fluxes for example – is expressed as:

where:

Rnet is the net irradiance
L is approximately 2.43 MJ·kg-1, the specific latent energy of vaporisation
E the evaporation (mass) flux (kg·s-1·m-2, equivalent to mm·s-1)
S the soil heat flux

Hence LE may be estimated as a residual using measurements of the terms on the right hand side of:

There have been reports in the literature of a lack of energy balance closure when using EC to measure both HEC and LEEC directly (Twine et al., 2000; Wilson et al., 2002). Lack of closure usually results in |HEC + LEEC| < Rnet + S. Since a comparison between 2 methods such as BR and EC does not identify the correct method for measurement of H and/or LE, there is a need for a 3rd method, such as the surface-layer scintillometry (SLS), especially in view of the alleged lack of closure using EC flux measurements.

Commonly, evaporation rate is estimated from grass reference evaporation rate, ETo, at an automatic weather station (AWS) using the Penman-Monteith approach (Allen et al., 1998; 2006), based on daily or hourly point atmospheric measurements at a single level of solar irradiance, air temperature, water vapour pressure and wind speed. In addition, a crop factor is used as a multiplying factor for ETo to obtain the actual evaporation rate. The crop factor effectively distinguishes the vegetation under consideration from a grass reference crop. The dual crop factor approach uses 1 crop factor for the soil surface and another for vegetation.

A scintillometer is used to measure path-weighted H. The instrument measures the intensity fluctuations of visible or infrared radiation after propagation above the plant canopy of interest. It optically measures a parameter associated with refractive index fluctuations of air, Cn2 , caused by air temperature fluctuations that represent the atmospheric turbulence structure. The sensible heat flux, H, may be estimated using the empirically-based Monin-Obukhov similarity theory (MOST). SLS instruments operate over horizontal distances between 50 and 350 m. Large aperture scintillometers (LAS) operate over typical distances between 250 m and up to 3 km. Typically, for areas of between about 0.25 and 5 ha, the SLS would be appropriate, whereas the LAS is suitable for areas larger than about 6 ha.

The objective of this work is to contrast various methods used for estimating evaporation rate as a residual of the shortened energy balance. Practical aspects of the use of the SLS method for the estimation of evaporation rate for a natural grassland are presented. Grass reference evaporation rate (ETo) measurements are also presented for comparison. Comparisons are made between H obtained using the various methods, to investigate whether H estimates using the EC method are underestimated, as is implied by the lack of closure when using EC measurements. The methodology for the measurement of H = HSLS and subsequent estimation of LE = LESLS is presented. A comparison is made between BR, EC and SLS methods of estimating H and LE. Also, procedures and definitions used for rejection of out-of-range and bad or 'doubtful' SLS data are presented.

 

Energy balance aspects, evaporation methods, energy balance closure and measurement footprint

There are many methods used for estimating evaporation rate. As mentioned by Drexler et al. (2004) in their review, very few evaporation estimation methods work well for an hourly time-step, and in some cases do not even work well for a daily time-step. Virtually all of the methods, except for EC, from which direct measurements of HEC and LEEC at a point are obtained, rely on a theoretical framework and certain assumptions or approximations for arriving at an expression for LE, in terms of other measurable quantities. Many methods invoke the use of a shortened surface energy balance (Eq. (1)) that allows LE to be estimated indirectly.

Weighing lysimeters are large containers, filled with soil, water, other chemicals and entire plant(s). The weighing lysimeter method allows for a direct measurement of the rate of total water loss from a vegetated surface (soil evaporation plus transpiration plus wet-canopy evaporation), and is often regarded as the standard method for measuring LE (Aboukhaled et al., 1982). Weight measurements are made at regular time intervals. The weight difference per unit time difference divided by the density of water and divided by the cross-sectional area of the lysimeter yields the evaporation rate in mm·h-1 or mm·d-1. Lysimeters allow the water loss rate from such containers to be measured for very short time intervals and longer time intervals, from hours to days or longer. The disadvantages of the lysimetric method include: cost, destructive nature of the measurements – in the sense that a relatively large volume of disturbed or sometimes undisturbed soil is placed in a container usually of metal construction, which isolates the lysimeter soil from neighbouring soil, and the non-portable nature of the measurement method. Also, the representation, or the so-called footprint, of the evaporation rate measurement is localised to the cross-sectional area of the lysimeter, although evaporation rate is also influenced by atmospheric events not confined to this area. Much less expensive is the microlysimetric method, but the surface area is an order of magnitude less than a large weighing lysimeter and it is still a destructive method, still isolated from neighbouring soil, and often not able to contain whole plants and therefore only used for measuring soil evaporation rate over short periods.

Given the limitations of the lysimetric method, the search for an alternative standard for evaporation rate estimation has been the focus of many studies for several decades. Methods such as EC involve measurement, typically at a frequency of 10 Hz, of 2 atmospheric variables, vertical wind speed and water vapour pressure, from which LEEC is calculated directly by eddy covariance following many corrections. Similarly, using eddy covariance, HEC is calculated from the covariance of vertical wind speed and air temperature measurements over a specified time interval – usually hourly or sub-hourly. The BR method involves up to 8 measurements, usually at a frequency of 1 Hz, of atmospheric and energy balance components, and a theoretical framework and assumptions to estimate HBR and LEBR (Savage et al., 2004). Empirical methods, or the Penman-Monteith approach, are used to estimate grass reference evaporation rate, ETo, which uses the crop factor approach to calculate evaporation rate. The more portable and much less invasive BR and EC methods, compared to the use of a lysimeter, are more popular research methods for the estimation of evaporation rate and can be used to collect unattended measurements for extended periods of time. These methods were the focus of previous research reports (Savage et al., 1997; 2004; Jarmain et al., 2009). The EC and BR methods essentially yield point estimates of H and LE although these flux estimates are influenced by events upwind of the point of measurement. The extent of the footprint area of influence on the flux measurement, using both BR and EC methods, has received attention. For example, Stannard (1997) investigated the footprint of BR flux measurements and Savage et al. (1995; 1996) investigated the footprint of EC flux measurements. Agreement between BR, EC, and SLS flux measurements of H, for example, may be dependent on the footprint of H, which in turn depends on sensor height and atmospheric stability condition.

Some literature reports on the inadequacy of the EC method for the direct estimation of LE (Wilson et al., 2002; Ham and Heilman, 2003) resulting in |HEC + LEEC| < Rnet + S (Twine et al., 2000). An alternative approach to using a full EC system for measuring HEC and LEEC is to measure HEC only, and to estimate LE as a residual of the shortened energy balance from simultaneous measurements of Rnet, S and H = HEC using Eq. (2).

The frequency of SLS measurements is typically 1 kHz, or 125 Hz for boundary-layer scintillometer measurements for which the path length is up to 10 km, compared to 1 Hz for BR measurements and 10 Hz for EC measurements. Because of the high frequency of the SLS measurements, the averaging period for HSLS can be as short as 1 or 2 min compared to the commonly-used 20 min for BR and 30 min for EC averaging periods (Savage, 2009).

The SLS method appears to be a useful, robust and accurate method for obtaining a path-weighted estimate for H = HSLS. However, many of the studies employing the SLS method have been very short in duration – in some cases just for a few days as mentioned by Odhiambo and Savage (2009b) and in other cases for a couple of months – and have not in detail compared the SLS method with BR and EC measurement methods.

 

Materials and methods

Site details

Field EC and SLS measurements were conducted during the period January 2003 to June 2005 in the Hay Paddock area, neighbouring Ashburton and close to Pietermaritzburg, South Africa (29º38' S, 30º26' E) with an altitude of 671.3 m. This is a natural grassland site dominated by Diheteropogon amplectens, Themeda triandra, Tristachya leucothrix and Cymbopogon excavatus. The soils are derived from Dwyka Tillite with a typical soil profile consisting of a loam A horizon (0 - 0.3 m) overlying clay B1 and B2 horizons extending to 1 m. The site experiences summer rainfall and has an average slope of 1º15' to the SE and a minimum fetch distance in the prevailing S-E wind direction of 135 m for the EC system (Fig. 1). The SLS system, consisting of a transmitter and a receiver, had respective fetch distances of 90 and 138 m for the 101 m path length. The minimum fetch for the next-most dominant winds from the N-W is 117 m for the EC system and 146 and 114 m for the SLS transmitter and SLS receiver respectively. Fetch distances from the middle position of the beam were 118 m for S-E winds and 130 m for N-W winds; vegetation height at this position has the greatest influence on the calculated beam-weighted vegetation height used in the SLS computations. Beyond these distances and to the south, the site is exposed and the slope increases. Adjacent to the site was natural grassland and occasional trees, with the exception of the north-west side of the study area which is residential with some trees. The grass growth is seasonal and this seasonality affects the partitioning of –Rnet – S into H and LE. There were occasional power problems and interruptions due to an accidental fire in August 2004 and accidental cutting of cables. The BR measurements commenced in December 2003.

 

 

Grass reference evaporation estimation

The procedures for estimating sub-daily grass reference evaporation rate, ETo, are described by Allen et al. (2006). The calculations were performed in a spreadsheet with ETo estimated every 2 min using these procedures, from AWS measurements of solar irradiance, air temperature, water vapour pressure and wind speed. While the AWS system was available at the site, ETo estimates were based on the AWS data. After the AWS system was removed, measurements from the same model of sensors were used to calculate ETo, except that for solar irradiance a Kipp and Zonen (Delft, The Netherlands) CM3 thermopile sensor was used. For some of the time, horizontal wind speed from the 3-D sonic anemometer was used. Water vapour pressure was measured using a Vaisala CS500 (Helsinki, Finland) air temperature and relative humidity sensor from the AWS system, or one of the following humidity sensors: another CS500, a Vaisala HMP35C or HMP45C air temperature and relative humidity sensor or a cooled dew point hygrometer (model Dew-10, General Eastern Corp., Watertown, Massachusetts, USA).

Surface-layer scintillometer measurements

A dual-beam surface-layer scintillometer (model SLS40-A, Scintec Atmospärenmessetechnik, Tübingen, Germany) (Thiermann, 1992; Thiermann and Grassl, 1992), was used to estimate H = HSLS. The beam distance of the SLS was 50 m for the initial experiments and later changed to 101 m. The beam heights were 1 and 1.6 m above the soil surface. Different path lengths would need to be used for different experimental areas. The objective for the use of the 2 path lengths was to test the reliability of the SLS method for the shortest possible and an average path length. The SLS40-A receiver has 4 detectors, with 2 of the detectors used for automatic identification of, and correction for, transmitter vibration by the software used for analysis. In other words, the SLS40-A dual-beam system and its 4 detectors enable the separation of, and correction for, the intensity fluctuations caused by beam movement. There are 2 detectors per beam. The SLS employs a diode laser source with an output wavelength of 670 nm and 1-mW mean output power (2-mW peak). The beam displacement and detector separation distances are 2.5 mm each, with a detector diameter of 2.7 mm. The correlation between the transmitted laser beam signal variances and the covariance of the logarithm of the beam signal amplitude is measured using the 2 detectors. Software, together with the instrument, allows on-line measurements at a frequency of 1 kHz and subsequent calculation every 1 or 2 min (Thiermann and Grassl, 1992) of the structure parameter for refractive index fluctuations , m-2/3), structure parameter for temperature ( K2 m-2/3), the inner scale of turbulence lo (mm), turbulent kinetic energy dissipation rate (ε, m2 s-3), sensible heat flux (H, W m-2), momentum flux (τ, Pa) and the Obukhov length (L, m). Monin-Obukhov similarity theory (MOST) is assumed. The methodology for calculating the 2-, 20- or 30-min HSLS, using MOST, is described b