Penman–Monteith equation

About: Penman–Monteith equation is a research topic. Over the lifetime, 655 publications have been published within this topic receiving 19862 citations.

Reference Crop Evapotranspiration from Temperature

Abstract: MEASURED lysimeter evapotranspiration of Alta fescue grass (a cool season grass) is taken as an index of reference crop evapotranspiration (ETo). An equation is presented that estimates ETo from measured values of daily or mean values of maximum and minimum temperature. This equation is compared with various other methods for estimating ETo. The equation was developed using eight years of daily lysimeter data from Davis, California and used to estimate values of ETo for other locations. Comparisons with other methods with measured cool season grass evapotranspiration at Aspendale, Australia; Lompoc, California; and Seabrook, New Jersey; with lysimeter data from Damin, Haiti; and with the modified Penman for various locations in Bangladesh indicated that the method usually does not require local calibration and that the estimated values are probably as reliable and useable as those from the other estimating methods used for comparison. Considering the scarcity of complete and reliable climatic data for estimating crop water requirements in developing countries, this proposed method can do much to improve irrigation planning design and scheduling in the developing countries.

Estimating Reference Evapotranspiration Under Inaccurate Data Conditions

Abstract: Reference evapotranspiration (ET0)estimates have been computed on a globalscale using a high-resolution monthlyclimate dataset. Penman-Monteith (PM) andHargreaves (HG) methods have been compared,showing very reasonable agreement betweenthe two methods. Fitting the two parametersof HG using the PM derived ET0 valuesdid not improve estimates by the HG methodsubstantially. Modifying the originalHargreaves method to a Modified-Hargreaves(MH) method by including a rainfall termimproved ET0 estimates significantlyfor arid regions. When a certain level ofinaccuracy in the meteorologicalobservations was assumed, calculatingET0 by PM and MH, given theseinaccuracy in observations, showed that MHperformed better than PM in reproducingoriginal calculations of ET0 ascalculated by PM assuming no data error. Itis concluded that the PM is a recommendedmethodology if accurate weather datacollection can be expected, but otherwiseMH should be considered.

Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis

Abstract: . This guide to estimating daily and monthly actual, potential, reference crop and pan evaporation covers topics that are of interest to researchers, consulting hydrologists and practicing engineers. Topics include estimating actual evaporation from deep lakes and from farm dams and for catchment water balance studies, estimating potential evaporation as input to rainfall-runoff models, and reference crop evapotranspiration for small irrigation areas, and for irrigation within large irrigation districts. Inspiration for this guide arose in response to the authors' experiences in reviewing research papers and consulting reports where estimation of the actual evaporation component in catchment and water balance studies was often inadequately handled. Practical guides using consistent terminology that cover both theory and practice are not readily available. Here we provide such a guide, which is divided into three parts. The first part provides background theory and an outline of the conceptual models of potential evaporation of Penman, Penman–Monteith and Priestley–Taylor, as well as discussions of reference crop evapotranspiration and Class-A pan evaporation. The last two sub-sections in this first part include techniques to estimate actual evaporation from (i) open-surface water and (ii) landscapes and catchments (Morton and the advection-aridity models). The second part addresses topics confronting a practicing hydrologist, e.g. estimating actual evaporation for deep lakes, shallow lakes and farm dams, lakes covered with vegetation, catchments, irrigation areas and bare soil. The third part addresses six related issues: (i) automatic (hard wired) calculation of evaporation estimates in commercial weather stations, (ii) evaporation estimates without wind data, (iii) at-site meteorological data, (iv) dealing with evaporation in a climate change environment, (v) 24 h versus day-light hour estimation of meteorological variables, and (vi) uncertainty in evaporation estimates. This paper is supported by a Supplement that includes 21 sections enhancing the material in the text, worked examples of many procedures discussed in the paper, a program listing (Fortran 90) of Morton's WREVAP evaporation models along with tables of monthly Class-A pan coefficients for 68 locations across Australia and other information.