The USWB Class A Evaporation Pan. Section 13.2 A-PAN EQUIVALENT REFERENCE POTENTIAL EVAPORATION R.E. Schulze and M. Maharaj

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1 Section 13.2 A-PAN EQUIVALENT REFERENCE POTENTIAL EVAPORATION R.E. Schulze and M. Maharaj Background to Mapping A-Pan Equivalent Reference Potential Evaporation Over South Africa For the two to three decades up to the turn of the present century the A- pan was the de facto accepted reference for potential evaporation, E r, in South Africa, having replaced as the reference the British Symon s-tank as the reference from the 1970s onwards. The maps and statistics presented in this Atlas are unchanged from those of the 1997 Atlas (Schulze, 1997), in which A-pan equivalent E r was derived from a regression equation based on monthly means of daily temperatures (as a surrogate for net radiation), modulated by a monthly rainfall factor (to account for cloudiness) and altitude (influencing the vaporisation process). The 1997 Atlas results have served their purpose well and no new daily temperature driven equations for A-pan equivalent E r were researched, as the move in recent years has been internationally towards using the Penman-Monteith approach as a reference for crop potential evaporation. The USWB Class A Evaporation Pan Evaporation has historically been measured at over 750 stations in South Africa using the standard USWB Class A evaporation pan. This pan is supported on a low wooden frame, has a diameter of 1.2 m, a depth of 254 mm and is filled with water to 203 mm. Daily evaporation is obtained by recording the change in water level from the previous day after allowance has been made for precipitation. The A-pan may be screened by a wire mesh (cf. photo below) to prevent birds and animals from drinking out of the pan Figure The USWB Class A evaporation pan Reasons for Having Selected the A-Pan as a Reference for Potential Evaporation Reasons for having selected the Class A evaporation pan (Figure ) as a reference for potential evaporation are as follows: The US Weather Bureau Class A evaporimeter (Photo 1) is, universally, the most common evaporation pan in usage, having been adopted as the standard evaporation pan since the International Geophysical Year 1957/8. When operated properly it is accepted as a reasonably reliable, simple and inexpensive local integrator of atmospheric evaporative demand, particularly for time periods longer than one day. It has been used widely in South Africa as a reference for potential evaporation (e.g. Photo 1 Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 1

2 Green, 1985) and A-pan relationships with maximum evaporation from crops and to natural water body evaporation have been well documented (e.g. Doorenbos and Pruitt, 1977) in many countries. In South Africa, crop coefficients, which relate the consumptive water use of the plant/soil continuum under different growth stages to a reference evaporation, have been tried and tested widely against the A-pan (e.g. Green, 1985). In many comparisons the A-pan has been shown to be very highly correlated with lysimeter evaporation under potential conditions, often with a correlation coefficient higher than that by the Penman equation and invariably higher than correlations against simpler empirical methods (Chang, 1968). For three days and longer good correlations exist with the Penman method in Australia (Chiew and McMahon, 1992), which climatically is similar to southern Africa. Furthermore, in the presence of advected energy, pans inside an irrigated field have been found to give more representative evaporation values than the Penman equation, particularly under arid and semi-arid conditions (Chang, 1968). Compared with a reference crop evaporation, the A-pan presents no problem with what, in a reference crop, constitutes "active growth" or a period of senescence or uniform crop height or complete shading of the ground (which may occur for only a few weeks of a crop's growing season). Mathematically elegant physically based methods of estimating E r, such as the universally accepted Penman based methods already referred to (e.g. Penman, 1948), make high demands on input data, including net radiation, wind and vapour pressure deficits. These data were, until recently, not yet directly available for any considerable length of record from many stations in South Africa, particularly not in high lying and in developing areas where agrohydrological decisions need to be taken frequently. Physically based methods such as the Penman-Monteith equation could, until 2007, only be used with confidence where relevant data were available. A first attempt at mapping Penman-Monteith equivalent reference crop evaporation from basic principles has been made and is presented in this Atlas. At locations where stations up to the recent past did not measure the variables required for Penman-based equations, there has often been at least a rudimentary, if physiographically biased, network of A-pans. In South Africa, for example, a network of over 750 A-pans exists and at over 570 stations A-pan data were in the early 1990s already concurrent for at least a number of years with rainfall and temperature data (Schulze and Maharaj, 1991). The A-pan network in South Africa was also considerably denser and altitudinally more representative than that of any other type of evaporimeter, e.g. the Symon's tank. Problems Associated with the A-Pan as a Reference for Potential Evaporation Use of the A-pan is not without its problems, however, and much contemporary literature is critical of the pan as a reference for potential evaporation. Points include the following: The spatial distribution of A-pans in South Africa, for example, is such that they are found generally near dams, existing irrigation projects or in areas of low relative relief where commercial agriculture is practised. These sites are not always representative of higher altitudes where water is generated or of rural areas where agricultural development is required. According to Smith (1975) the extrapolation of evaporation pan data from its measurement at a site to other locations is a "very hazardous procedure". Green (1985) also discusses errors which could be incurred when extrapolating A-pan data in South Africa and local climate can yield inexplicably variable results. Research by Bosman (1990) highlighted the necessity for proper pan installation and consideration of micro site conditions, both of which could cause readings from adjacent A-pans to vary significantly by over 20% in the long term. A-pans may or may not be screened with a wire mesh (to prevent, for example, animals drinking from the pans). Screening suppresses evaporation losses from the pan by 5-15%, depending on the mesh size of the screen (Bosman, 1990). Public records of pan evaporation seldom indicate whether or not the pan is screened. Other errors may be due to accumulation of dirt/algae in the pans, or to interference by animals. Evaporation pan data since the 1970s were usually assumed to be those from a Class A-pan, they may have been derived from other evaporation tanks with different physical properties (e.g. the Symon's tank), thus requiring a regionally and seasonally dependent Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 2

3 conversion to A-pan equivalents. The A-pan's small physical dimensions and exposure to the atmosphere often render its readings to be unrepresentative of atmospheric evaporative demand, because of rapid heat storage and heat loss in the water contained in the pan. Advective processes can exaggerate pan evaporative losses by the so-called oasis effect. This is caused by the pan s relatively small evaporating surface, with the saturated air over the pan being often replaced by relatively drier air from the surrounding area. Advection is particularly important in arid/semiarid areas, especially in winter months when the location is in a summer rainfall area, or in summer months when the location is in a winter rainfall region. Maps of A-pan equivalent E r would thus tend to give values which were on the high side. With regard particularly to the A-pan as a reference for crop evaporation, the Penman-Monteith equation (Penman, 1948; Monteith, 1981) has become the de facto accepted standard for E r. Furthermore, crop water use is often related more closely to solar radiation than to A-pan evaporation (Turner and Wiersma, 1964) and the A-pan has been shown to overestimate crop reference evaporation by up to 30% (Van Zyl et al., 1989). The relative importance of factors influencing A-pan evaporation (e.g. net radiation, vapour pressure deficit, wind) may vary from region to region within South Africa, depending on climatic, physiographic and seasonal factors. It becomes evident from the above discussion on problems associated with the A-pan that not all data obtained through existing networks are necessarily accurate for the pan to be used as the reference for potential evaporation. Great care should therefore be taken in checking the A-pan data for reliability, and if need be, many pans' data may have to be rejected when mapping E p (Clemence, 1986). For the reasons listed above, it therefore became necessary to consider surrogates of A-pan evaporation which, when calibrated against pan data of acceptable quality, would yield equivalent evaporation information which may then be extrapolated with greater confidence to locations where no pan evaporation measurements are available. The Use of Temperature Based Information for Estimating A-Pan Equivalent Reference Potential Evaporation A number of reasons may be advanced for using temperature information as a surrogate for estimating daily A-pan equivalent evaporation: Temperature, while closely associated with the solar energy forcing function in the evaporation process, is less susceptible than pans to measurement errors or effects of local anomalies in micro-climate. There are, in South Africa, approximately twice as many stations with good temperature than with good evaporation records (cf. Section 2.1). The distribution of temperature stations is, furthermore, more even spatially and the network covers a wider range of altitudes and physiographic zones than that of A-pans (Schulze, 1985). Temperature information may be interpolated to unmeasured locations more readily than evaporation pan information by use of multivariate techniques, including, for example, trend surface analysis (Schulze, 1982; Schulze 1997) and may also be extrapolated to altitudes beyond the range of observations by application of regional lapse rate based equations (e.g. Schulze and Schäfer, 1989; Schulze, 1997), because of the close association of temperature with altitude and other physiographic factors. A problem which then has to be solved is the selection of existing, or development of new, temperature based equations appropriate to a given agrohydrological problem, or specific for a given time of the year and location, to be applied should A-pan data not be available at the location or be deemed unreliable there. Simple Climatic and Physiographic Variables Used to Develop A-Pan Equivalent Reference Potential Evaporation Equations for South Africa If the variables which affect A-pan equivalent evaporation are considered, then those climatic and physiographic variables which are readily available for South Africa may be simplified and reduced to: maximum daily temperature, which like evaporation is predominantly a daytime phenomenon and may be used as a surrogate for net Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 3

4 radiation, and the variation of which also relates to the influence of cloudiness on evaporation rates an adjustment to the influence of maximum temperature on the evaporation process to account for the relative influence of daylength in different seasons, this factor being expressed through the extraterrestrial radiation term for different latitudes and seasons (which may be derived mathematically or simply extracted from published tables) altitude, which accounts for the atmospheric pressure influence on the vaporisation process median monthly rainfall (applied especially in those regions where large spatial variability of monthly rainfall is displayed), which represents a simple determinant of the effects of intra-regional differences of cloudiness and hence also vapour pressure deficits on evaporation, and defined evaporation regions, in which regional wind and vapour pressure deficit characteristics could be assumed to be relatively uniform in their influence on evaporation process. These regions are shown in the next section. For South Africa 12 regions of relatively uniform evaporation response have been identified (Schulze and Maharaj, 1991; Schulze and Maharaj, 2004). These regions are shown in Figure Evaporation Regions for South Africa, Swaziland and Lesotho Figure Evaporation regions for South Africa, Swaziland and Lesotho (Schulze and Maharaj, 1991) Equations for Estimating A-Pan Equivalent E r in South Africa Potential evaporation is a conservative climatic element with relatively small variations from year to year at a given location. Therefore, relatively short records can be used to obtain reasonably accurate estimates of monthly values (Niewolt, 1977). The data from over 570 South African stations at which a minimum of three years' concurrent monthly temperature, rainfall and A-pan evaporation observations are available, were used to develop temperature based equations of A- pan equivalent evaporation for each of the 12 evaporation regions identified in South Africa (cf. Figure ) and for each month, on the premise that the relative importance of the forcing functions of the E r process change with region and season (Schulze and Maharaj, 1991). These equations, for a given region and a specified month, take the general form where E apan (i) = b 0 T max (i)r a (i) + b 1 z - b 2 P md (i) + b 3 E apan = A-pan equivalent reference evaporation estimate (mm.month -1 ) T max = monthly mean of daily maximum air temperatures ( C) R a = mean extra-terrestrial solar radiation for the month z = altitude (m) P md = median monthly precipitation (mm) i = month of the year, and b 0 -b 3 = regression constants. The equations, unique for each month and for each region, were used to develop the 12 rasterised images of mean monthly A-pan equivalent evaporation on a 1' x 1' of a degree latitude/longitude grid. Around the boundaries of two or more evaporation regions averaging and smoothing techniques have been applied (Schulze and Maharaj, 1991). Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 4

5 How Much More Detail do Temperature Derived A-Pan Equivalent Evaporation Maps Provide? The accompanying map of part of the Western Cape illustrates the detail the temperature derived A-pan equivalent maps provide, compared with previously published evaporation maps (the bold 220 mm isoline) which are still used by some practitioners. The implications of accurate estimates of open water evaporation in a water scarce South Africa are immense when one considers that potential evaporation is a vital input into irrigation scheduling and the estimation of evaporative water losses from dams. Example of Mapping Detail: January A-Pan Equivalent How Reliable are the A-Pan Estimates over South Africa? Reliability may be assessed by statistical and graphical methods. Using Region 11, viz. the South West Cape Interior, as an example (its statistics are considered average when compared with those of the other regions), the scatterplots show a good correspondence between simulated and observed A-pan equivalent reference potential evaporation for both annual and January totals (Figure ). Similarly, if one examines the bar graph of percentage residuals between observed and estimated values, it may be deduced that in January 69% of the estimated A-pan values from 52 stations are within ±2% of the observed and 89% within ±4% of the observed values, while in July 63% and 77% of A-pan estimates are within ±2% and ±4% respectively of observed values. Region 6 SW Cape Interior: Annual Region 6 SW Cape Interior: January Simulated (mm) : 1 Simulated (mm) : Observed A-Pan Evaporation (mm) Observed A-Pan Evaporation (mm) Percentage Residuals, Simulated vs. Observed A-Pan Evaporation - Region 6 Western Cape Interior Percent Frequency Figure Example of mapping detail of A-pan equivalent potential evaporation for the month of January from temperature-derived equations (Schulze, 1997) Percent Residual January Figure Verification of temperature based A-pan equivalent potential evaporation estimates (Schulze, 1997) July Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 5

6 How Reliable are the A-Pan Estimates for South Africa? (continued) Other statistics (not shown here) indicate that in general in all regions the simulations tend to overestimate slightly at stations with lowest observed A-pan values and underestimate slightly at stations with highest observed A-pan values. The estimations thus tend to be slightly conservative at the extremes, a fact borne out of the CVs of observations in a given region usually being slightly higher than the CVs of the estimates. Overall the statistics do, however, show that the A-pan estimates may be used with confidence. Deriving Estimates of Monthly A-Pan Equivalent Potential Evaporation for South Africa from Annual Values For each of the 12 evaporation regions of South Africa, each month's E apan has been expressed as a percentage of the annual E apan (Table ). If only mean annual A-pan equivalent potential evaporation is known, then monthly estimates can be made by applying the relevant region's percentages to the annual value. Table Monthly A-pan as a percentage of annual values, per region (Schulze, 1997) Region Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Distribution Patterns over South Africa of Mean Annual and Mean Monthly A-Pan Equivalent Potential Evaporation Mean monthly January to December A-pan equivalent evaporation values were summed at each of the grid points covering South Africa, Lesotho and Swaziland to give a mean annual value. Intra-provincial statistics were then performed on those values. Mean annual A-pan equivalent potential evaporation "lows" are around mm in the Drakensberg and mm along the eastern and southern coastal areas, with a general southeast-northwest increasing trend culminating in highs exceeding mm per annum in the northwest. Mean monthly A-pan equivalent evaporation values for summer months (e.g. December and January) display an east to west trend ranging from < 180 mm to > 340 mm/month. In the transitional months (e.g. April) the evaporation trend shifts to northwest (with ~ 180 mm/month) to southeast (with ~ 110 mm/month). By mid-winter (June to July) the latitudinal influence on A-pan evaporation is very strong, with ~ 120 mm/month evaporating in the north, reducing to < 60 mm/month in the south. A mirror image of these trends occurs between July and December. References (In the sequence in which they appear in this Section, with the full references given in Section 22) 1. Schulze, R.E. (1997) 2. Green, G.C. (1985) 3. Doorenbos, J. and Pruitt, W.O. (1977) 4. Chang, J-H. (1968) 5. Chiew, F.H.S. and McMahon, T.A. (1992) 6. Penman, H.L. (1948) 7. Schulze, R.E. and Maharaj, M. (1991) 8. Smith, L.P. (1975) 9. Bosman, H.H. (1990) 10. Turner, R. and Wiersma, D. (1964) 11. Van Zyl, W.H., de Jager, J.M. and Maree, C.J. (1989) 12. Clemence, B.S.E. (1992) 13. Schulze, R.E. (1985) 14. Schulze, R.E. (1982) 15. Niewolt, S. (1977) Photo 1 - Schulze, R.E. Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 6

7 Citing from this Section of the Atlas When making reference to this Section of the Atlas, please cite as follows: Schulze, R.E. and Maharaj, M A-Pan Equivalent Reference Potential Evaporation. In: Schulze, R.E. (Ed) South African Atlas of Climatology and Agrohydrology. Water Research Commission, Pretoria, RSA, WRC Report 1489/1/06, Section Mean Annual A-Pan Equivalent Potential Evaporation (mm) Limpopo Mpumalanga * North West Northern Cape Gauteng Free State * KwaZulu-Natal * Eastern Cape Western Cape * Swaziland Lesotho * * Minimum values considered unreliable because of extrapolation Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 7

8 A-Pan Equivalent Potential Evaporation (mm), January Province / Mean CV Maximum Minimum Exceedance Probability Limpopo Mpumalanga North West Northern Cape Gauteng Free State * KwaZulu-Natal * Eastern Cape Western Cape * Swaziland Lesotho * A-Pan Equivalent Potential Evaporation (mm), April Limpopo Mpumalanga North West Northern Cape Gauteng Free State KwaZulu-Natal * Eastern Cape Western Cape * Swaziland Lesotho * A-Pan Equivalent Potential Evaporation (mm), February Limpopo Mpumalanga * North West Northern Cape Gauteng Free State * KwaZulu-Natal * Eastern Cape Western Cape * Swaziland Lesotho * A-Pan Equivalent Potential Evaporation (mm), May Limpopo Mpumalanga North West Northern Cape Gauteng Free State KwaZulu-Natal Eastern Cape Western Cape * Swaziland Lesotho A-Pan Equivalent Potential Evaporation (mm), March Limpopo Mpumalanga North West Northern Cape Gauteng Free State * KwaZulu-Natal Eastern Cape Western Cape * Swaziland Lesotho A-Pan Equivalent Potential Evaporation (mm), June Limpopo Mpumalanga North West Northern Cape Gauteng Free State KwaZulu-Natal * Eastern Cape Western Cape * Swaziland Lesotho * Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 8

9 A-Pan Equivalent Potential Evaporation (mm), July Limpopo Mpumalanga North West Northern Cape Gauteng Free State KwaZulu-Natal Eastern Cape Western Cape Swaziland Lesotho * A-Pan Equivalent Potential Evaporation (mm), October Limpopo Mpumalanga North West Northern Cape Gauteng Free State * KwaZulu-Natal * Eastern Cape Western Cape * Swaziland Lesotho * A-Pan Equivalent Potential Evaporation (mm), August Limpopo Mpumalanga North West Northern Cape Gauteng Free State * KwaZulu-Natal * Eastern Cape Western Cape Swaziland Lesotho * A-Pan Equivalent Potential Evaporation (mm), November Limpopo Mpumalanga North West Northern Cape Gauteng Free State * KwaZulu-Natal * Eastern Cape Western Cape * Swaziland Lesotho * A-Pan Equivalent Potential Evaporation (mm), September Limpopo Mpumalanga North West Northern Cape Gauteng Free State * KwaZulu-Natal Eastern Cape Western Cape * Swaziland Lesotho * A-Pan Equivalent Potential Evaporation (mm), December Limpopo Mpumalanga North West Northern Cape Gauteng Free State * KwaZulu-Natal * Eastern Cape Western Cape Swaziland Lesotho * Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 9

10 Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 10

11 Section 13.2 Potential Evaporation: A-pan Equivalent Reference Potential Evaporation 11