Estimation of Reference Potential Evapotranspiration with Focus on Vegetation Science—the EmPEst Software

Kostinakis, Konstantinos; Xystrakis, Fotios; Θεοδωρόπουλος, Κωνσταντίνος; Stathis, Dimitrios; Eleftheriadou, Eleni; Matzarakis, Andreas

doi:10.1061/(asce)ir.1943-4774.0000335

Cited by 10 publications

(8 citation statements)

References 12 publications

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“…Location of the Sperchios River basin. where Δ is the slope of saturation vapour pressure curve at air temperature T (kPa°C -1 ); R n is the net radiation at the crop surface (MJ m -2 ); G is the soil heat flux density at the crop surface (MJ m -2 ); for daily periods the value is 0); γ is the psychrometric constant (kPa°C -1 ); T mean is the mean air temperature at 1.5-2.5 m height (°C); U 2 is the mean wind speed at 2 m height (m s -1 ); e s is the mean saturation vapour pressure at 1.5-2.5 m height (kPa); e a is the mean actual vapour pressure at 1.5-2.5 m height (kPa); C n is a numerator constant that changes with reference type and takes the value 900 and 1600 K mm s 3 Mg -1 for short and tall crops, respectively; and C d is a denominator constant that changes with reference type and takes the values of 0.34 and 0.38 s m -1 for short and tall crops, respectively (Kostinakis et al 2011). The empirical PET ref equations included in EmPEst cover a wide spectrum of input data requirements.…”

Section: Drought Indexmentioning

confidence: 99%

“…(Xystrakis and Kostinakis 2010, Kostinakis et al 2011, Xystrakis and Matzarakis 2011.2.3.2 EmPEst software for estimation of PETEmPEst (empirical potential evapotranspiration estimation) is a simple program that can estimate daily PET ref by means of 13 different empirical equations. These include the approaches of: Hargreaves(Allen et al 1998, Oudin et al 2005, McGuiness(Oudin et al 2005), Jensen(Jensen and Haise 1963, Rosenberry et al 2004), Hansen(Xu and Singh 2002), Caprio(Caprio 1974), Romanenko(Oudin et al 2005), Turc(Lu et al 2005), Makkink(Rosenberry et al 2004), de Bruin(Rosenberry et al 2004), McCloud(Jacobs and Satti 2001, Irmak et al 2003), and three versions of Hamons approach (Kostinakis et al 2011, Xystrakis and Matzarakis 2011).…”

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confidence: 99%

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Mapping of drought for Sperchios River basin in central Greece

Paparrizos

Maris

Matzarakis

2016

Hydrological Sciences Journal

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The estimation of drought at certain temporal and spatial scales is useful for research on climate change and global warming. Greece is often affected by droughts, which are widespread spatially and temporally due to the complex topography. Within the Greek territory, various complex microclimates are created, linked with the spatial variances in drought phenomena. In this paper an estimation of drought in the Sperchios River basin was conducted using the Aridity Index (AI). Additionally, a seasonal analysis of drought was performed. Meteorological data from the Hellenic National Meteorological Service (HNMS) were used as inputs for the AI equation. Spatial interpolation of AI for the Sperchios River basin was performed using a kriging method by the application of ArcGIS 9.3. In order to produce required input data, several models (EmPEst, RayMan) and techniques (linear regression, interpolation) were combined. Finally, the meteorological data series were randomly separated into two periods and AI was estimated for these sub-periods, in order to test the effectiveness of the drought index used. The results indicate that the conditions prevailing in the area are humid, mostly affected by increased rainfall occurring in the mountainous section of the basin. Broadly, the humid environment in the upstream of Sperchios River prevents drought occurring in the lowlands of Sperchios River valley. Nevertheless, some differentiation appeared during the summer period, to which special attention needs to be given in order to prevent drought conditions.

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Section: Drought Indexmentioning

confidence: 99%

mentioning

confidence: 99%

Mapping of drought for Sperchios River basin in central Greece

Paparrizos

Maris

Matzarakis

2016

Hydrological Sciences Journal

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“…PET was estimated with the use of EmPEst software (Xystrakis and Kostinakis, 2010;Kostinakis et al, 2011). EmPEst (empirical potential evapotranspiration estimation) is a simple software that can estimate daily PET by means of 14 different empirical equations.…”

Section: Empest Software For Pet Estimationmentioning

confidence: 99%

“…EmPEst (empirical potential evapotranspiration estimation) is a simple software that can estimate daily PET by means of 14 different empirical equations. These equations include the PETASCE equation (ASCE Task Committee, 2005), the approaches of Hargreaves (Allen et al, 1998), McGuiness (Oudin et al, 2005), Jensen (Jensen and Haise, 1963), Hansen (Xu and Singh, 2002), Caprio (Caprio, 1974), Romanenko (Oudin et al, 2005), Turc (Lu et al, 2005), Makkink (Rosenberry et al, 2004), de Bruin (Rosenberry et al, 2004), McCloud (Jacobs and Satti, 2001;Irmak et al, 2003) and three versions of Hamons approach (Kostinakis et al, 2011;Xystrakis and Matzarakis, 2011). Table 4 ).…”

Section: Empest Software For Pet Estimationmentioning

confidence: 99%

Integrated analysis and mapping of aridity over Greek areas with different climate conditions

2016

Issue 1

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Assessment of aridity conditions prevailing in a certain area is essential for the research on climate and climate change. Greece is characterized by a variety of climatic conditions such as drought conditions or flooding phenomena. The current study focuses on three selected areas within Greece that present different climatic characteristics due to their location and aims to analyze and compare the aridity conditions prevailing in these areas. Aridity conditions were estimated using the Aridity Index (AI). MannKendall test was applied to investigate possible trends. Spatial distribution of aridity conditions was performed using multi-linear regression techniques and Kriging method within ArcGIS 10.2.1.The results indicated that the study areas face humid conditions, mostly due to the existence of high altitudes. Furthermore, the various climatic conditions are responsible for differentiations in seasonal analysis regarding the aridity conditions. The study areas related to the Mediterranean climate resulted more heterogeneous conditions compared with areas affected by the continental climate. Nevertheless, the created aridity spatial maps of trend analysis presented with differentiations, especially in the mountainous areas were an extreme downward trend is appeared. For the southern investigated area in Crete Island characterized purely by Mediterranean climate, the results were more moderate in terms of aridity conditions.

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“…These variables were additionally used to estimate several other indexes that could potentially describe climatic or weather features combining temperature and precipitation patterns. These indexes included: (i) Giacobbes's indice d'arido-humidité (G); (ii) Emberger's indice pluviothérmique (Tuhkanen 1980); (iii) the area of the Walter & Lieth climatic diagram for the period when precipitation curve undercuts the respective curve of air temperature (arid season -Walter & Lieth 1967); (iv) the annual and fire-season moisture deficit, estimated by applying the monthly soil water balance model as described by Xu (1997), using the most suitable potential evapotranspiration equations for each region as described in Kostinakis et al (2011) and .…”

Section: Weather Datamentioning

confidence: 99%