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Potential evapotranspiration is expressed in terms of a depth of water or soil moisture percentage. If the actual evapotranspiration is considered the net result of atmospheric demand for moisture from a surface and the ability of the surface to supply moisture, then PET is a measure of the demand side (also called evaporative demand).
Crop coefficients are properties of plants used in predicting evapotranspiration (ET). The most basic crop coefficient, K c, is simply the ratio of ET observed for the crop studied over that observed for the well calibrated reference crop under the same conditions.
The Standardized Precipitation Evapotranspiration Index (SPEI) is a multiscalar drought index based on climatic data. It was developed by Vicente-Serrano et al. (2010) at the Institute Pirenaico de Ecologia in Zaragoza, Spain . [ 1 ]
The Penman-Monteith equation approximates net evapotranspiration (ET) from meteorological data as a replacement for direct measurement of evapotranspiration. The equation is widely used, and was derived by the United Nations Food and Agriculture Organization for modeling reference evapotranspiration ET 0 .
It uses meteorological data from the moment of the recording of the satellite data to solve the 'instantaneous' energy balance, and uses extrapolation to calculate daily evapotranspiration. Using a time series of satellite and meteorological data, periodic cumulative (e.g. weekly, monthly, yearly) evapotranspiration data can be calculated.
Monthly estimated potential evapotranspiration and measured pan evaporation for two locations in Hawaii, Hilo and Pahala. Potential evapotranspiration is usually measured indirectly, from other climatic factors, but also depends on the surface type, such as free water (for lakes and oceans), the soil type for bare soil, and also the density and diversity of vegetation.
Given the limited data input to the equation, the calculated evapotranspiration should be regarded as only broadly accurate. Rather than a precise measure of evapotranspiration, the output of the equation is better thought of as providing an order of magnitude. [2] The inaccuracy of the equation is exacerbated by extreme variants of weather.
This leads to false measurements and must be compensated for in the data analysis. Models accounting for additional local terrain moisture match global estimates. [ 18 ] In a different view, an analysis of pan trends in records from 154 instruments shows no coherency and pattern of statistically significant trends, with 38% decreasing, 42% no ...