A Search for Understanding Potential Evapotranspiration

Mather, John R.; Ambroziak, Russell A.

doi:10.2307/214911

Cited by 17 publications

(7 citation statements)

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“…The annual amount of precipitation ( P ) can be relatively easily measured in rain gauges. However, the PET requires physical–mathematical calculation (Mather and Ambroziak, ). Although the Penman method (Penman ) is considered more accurate to calculate PET , as used in the UNESCO () map, very few meteorological stations collect all the required physical and meteorological parameters needed for its calculation.…”

Section: Methodsmentioning

confidence: 99%

Degradation of Springs in the Arava Valley: Anthropogenic and Climatic Factors

et al. 2012

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Groundwater pumping in the hyper-arid Arava Valley began in 1936 for industrial use, south of the Dead Sea, and since 1949 for domestic and agricultural use with the establishment of Eilat. Pumping gradually increased with the founding of 19 rural villages throughout the Arava Valley. Groundwater levels dropped as a result, and springs in the Arava Valley began to deteriorate. Their status had not been studied for decades, and we conducted comprehensive fieldwork of virtually all the known springs on the Israeli side of the Arava Valley, 31 springs, within the period 2008-2010. Our objectives were (i) to determine the current condition of each spring, (ii) to study spring deterioration through time in relation to historical data and (iii) to evaluate anthropogenic and climatic factors through time. Our results reveal that only 13 springs discharged water on the landscape surface and 18 springs were found dry. Detailed evaluations and time-series analyses are presented for the springs: 'Ein Tamar, 'Ein Mashak, 'Ein Evrona and 'Ein Netafim, selected on the basis of geodiversity. Climatic trends in the region were studied using the novel P/PET aridity index (P = annual precipitation, PET = annual potential evapotranspiration). We calculated yearly P/PET values since 1970 for five meteorological stations in Israel and six stations in Jordan. All stations, without exception, show a negative downward trend toward increasing aridity, often with significant p values (below 0Á10). The change to a drier climate in the region should be considered as an important factor regarding sustainable groundwater management in the Arava Valley.Note: Largely based on Amiran et al. (1995: 336). A moshav and a kibbutz are communal villages. The former has private property, whereas in a kibbutz, property is usually shared. 368 H. J. BRUINS ET AL.Note: The humid zone is also shown but without differentiation, except for the sub-humid zone, bordering the drylands. P = annual precipitation; PET = annual potential evapotranspiration.

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Section: Methodsmentioning

confidence: 99%

Degradation of Springs in the Arava Valley: Anthropogenic and Climatic Factors

et al. 2012

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“…Although temperature-based models may have practical value, they have limitations that have been addressed in detail elsewhere [21,25,57]; thus we restrict focus on methods of estimation that explicitly consider a radiative component. Penman's model [27] combines radiative and aerodynamic drivers of evaporation:…”

Section: Models Of Potential Evaporationmentioning

confidence: 99%

“…It is, therefore, determined by the energy available to change the phase of water from liquid to gas [17][18][19][20]. Although PE has a conceptual definition, it is not easy to measure directly above land surfaces [21]. Inferences can be made from measurements of evaporation from lakes, lysimeters, evaporation pans, or models.…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variability of Potential Evaporation across North American Forests

2017

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Given the widespread ecological implications that would accompany any significant change in evaporative demand of the atmosphere, this study investigated spatial and temporal variation in several accepted expressions of potential evaporation (PE). The study focussed on forest regions of North America, with 1 km-resolution spatial coverage and a monthly time step, from 1951-2014. We considered Penman's model (E Pen ), the Priestley-Taylor model (E PT ), 'reference' rates based on the Penman-Monteith model for grasslands (E RG ), and reference rates for forests that are moderately coupled (E RFu ) and well coupled (E RFc ) to the atmosphere. To give context to the models, we also considered a statistical fit (E PanFit ) to measurements of pan evaporation (E Pan ). We documented how each model compared with E Pan , differences in attribution of variance in PE to specific driving factors, mean spatial patterns, and time trends from 1951-2014. The models did not agree strongly on the sensitivity to underlying drivers, zonal variation of PE, or on the magnitude of trends from 1951-2014. Sensitivity to vapour pressure deficit (D a ) differed among models, being absent from E PT and strongest in E RFc . Time trends in reference rates derived from the Penman-Monteith equation were highly sensitive to how aerodynamic conductance was set. To the extent that E PanFit accurately reflects the sensitivity of PE to D a over land surfaces, future trends in PE based on the Priestley-Taylor model may underestimate increasing evaporative demand, while reference rates for forests, that assume strong canopy-atmosphere coupling in the Penman-Monteith model, may overestimate increasing evaporative demand. The resulting historical database, covering the spectrum of different models of PE applied in modern studies, can serve to further investigate biosphere-hydroclimate relationships across North America.

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“…The atmospheric moisture demand, potential evapotranspiration PET in mm, is estimated in DryMOD for months from January to December over each study region using mean monthly air temperature data from the WorldClim temperature climatology and the Thornthwaite model [29][30][31][32] including an adjustment for day length and solar angle [33] and heat index calculation (see Section 3, Supplementary Material). The WorldClim dataset provides a monthly air temperature climatology at approximately 1-km spatial resolution (30-arc seconds horizontal grid spacing) and covers the 1950-2000 time period [34].…”

Section: Potential Evapotranspirationmentioning

confidence: 99%

Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall

et al. 2013

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This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting OPEN ACCESSRemote Sens. 2013, 5 6692 according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

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A Search for Understanding Potential Evapotranspiration

Cited by 17 publications

References 0 publications

Degradation of Springs in the Arava Valley: Anthropogenic and Climatic Factors

Degradation of Springs in the Arava Valley: Anthropogenic and Climatic Factors

Spatial and Temporal Variability of Potential Evaporation across North American Forests

Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall

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