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Hydrology
Special Issues
Advances in Evaporation and Evaporative Demand: Part II
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Advances in Evaporation and Evaporative Demand: Part II

A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Hydrological and Hydrodynamic Processes and Modelling".

Deadline for manuscript submissions: closed (22 May 2024) | Viewed by 10414

Special Issue Editors

Dr. Aristoteles Tegos

E-Mail Website
Guest Editor
Laboratory of Hydrology and Water Resources Development, School of Civil Engineering, National Technical University of Athens, GR-15780 Athens, Greece
Interests: hydrology; environmental; floods; remote sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Nikolaos Malamos

E-Mail Website
Guest Editor
Department of Agriculture, University of Patras, 27200 Amaliada, Greece
Interests: hydrology; hydroinformatics; irrigation; simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are thrilled to introduce our new Special Issue entitled “Advance in Evaporation and Evaporation Demand—Part II” following the great success of Volume 1. The importance of evapotranspiration is well-established in different disciplines, such as hydrology, agronomy, climatology, and other geosciences. Reliable estimates of evapotranspiration are also vital to develop criteria for: in-season irrigation management; water resource allocation; long-term estimates of water supply, demand, and use; design and management of water resources infrastructure; and evaluation of the effect of land use and management changes on the water balance. The objective of this Special Issue is to define and discuss several ET terms, including potential, reference, and actual (crop) ET, and present a wide spectrum of innovative research papers and case studies. We, therefore, encourage researchers and experts to present their innovative contributions in the following areas:

  • New techniques for estimating evapotranspiration and comparative analysis of different evapotranspiration models;
  • New methodologies for estimating evapotranspiration and evaporation in temporal time scales from hourly to monthly;
  • Global and local calibration of parsimonious PET model in data scarce areas using limited climate data;
  • Advanced techniques for quantifying evapotranspiration spatial variability;
  • Calibration of large-scale hydrological model using evapotranspiration spatial products (MODIS, etc.);
  • Micrometeorological evapotranspiration modeling focusing on smart farming;
  • Modeling evapotranspiration for precision irrigation purposes;
  • Weather forecasting model associated with the hydrological modelling and optimal irrigation scheduling;
  • Remote Sensing application for evapotranspiration assessment;
  • Public available hydrological and agronomical software incorporating evapotranspiration modelling;
  • Drought analysis and evapotranspiration modelling in the context of water resources management;
  • Irrigation management and evapotranspiration assessment;
  • Crop coefficients and Eddy measurements;
  • Use of evapotranspiration in climatic studies, long-term climatic trend analysis and stochastic modelling.

Dr. Aristoteles Tegos
Dr. Nikolaos Malamos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Hydrology is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • evapotranspiration
  • hydrology
  • agronomy
  • remote sensing

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Published Papers (3 papers)

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Research

18 pages, 12564 KiB  
Article
Climate Change Projections of Potential Evapotranspiration for the North American Monsoon Region
by Eylon Shamir, Lourdes Mendoza Fierro, Sahar Mohsenzadeh Karimi, Norman Pelak, Emilie Tarouilly, Hsin-I Chang and Christopher L. Castro
Hydrology 2024, 11(6), 83; https://doi.org/10.3390/hydrology11060083 - 14 Jun 2024
Cited by 1 | Viewed by 2348
Abstract
We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed [...] Read more.
We assessed and quantified future projected changes in terrestrial evaporative demand by calculating Potential Evapotranspiration (PET) for the North American Monsoon region in the Southwestern U.S. and Mexico. The PET projections were calculated using the daily Penman–Monteith equation. The terrestrial meteorological variables needed for the equation (i.e., minimum and maximum daily temperature, specific humidity, wind speed, incoming shortwave radiation, and pressure) were obtained from the North American–CORDEX initiative. We used dynamically downscaled projections of three CMIP5 GCMs for RCP8.5 emission scenarios (i.e., HadGEM2-ES, MPI-ESM-LR, and GFDL-ESM2M), and each was dynamically downscaled to ~25 km by two RCMs (i.e., WRF and regCM4). All terrestrial annual PET projections showed a statistically significant increase when comparing the historical period (1986–2005) to future projections (2020–2039 and 2040–2059). The regional spatial average of the six GCM-RCM combinations projected an increase in the annual PET of about +4% and +8% for 2020–2039 and 2040–2059, respectively. The projected average 20-year annual changes over the study area range for the two projection periods were +1.4%–+8.7% and +3%–+14.2%, respectively. The projected annual PET increase trends are consistent across the entire region and for the six GCM-RCM combinations. Higher annual changes are projected in the northeast part of the region, while smaller changes are projected along the pacific coast. The main drivers for the increase are the projected warming and increase in the vapor pressure deficit. The projected changes in PET, which represent the changes in the atmospheric evaporative demand, are substantial and likely to impact vegetation and the hydrometeorological regime in the area. Quantitative assessments of the projected PET changes provided by this study should be considered in upcoming studies to develop resilience plans and adaptation strategies for mitigating the projected future changes. Full article
(This article belongs to the Special Issue Advances in Evaporation and Evaporative Demand: Part II)
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13 pages, 2613 KiB  
Article
On the Sensitivity of Standardized-Precipitation-Evapotranspiration and Aridity Indexes Using Alternative Potential Evapotranspiration Models
by Aristoteles Tegos, Stefanos Stefanidis, John Cody and Demetris Koutsoyiannis
Hydrology 2023, 10(3), 64; https://doi.org/10.3390/hydrology10030064 - 6 Mar 2023
Cited by 18 | Viewed by 3373
Abstract
This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration [...] Read more.
This paper examines the impacts of three different potential evapotranspiration (PET) models on drought severity and frequencies indicated by the standardized precipitation index (SPEI). The standardized precipitation-evapotranspiration index is a recent approach to operational monitoring and analysis of drought severity. The standardized precipitation-evapotranspiration index combines precipitation and temperature data, quantifying the severity of a drought as the difference in a timestep as the difference between precipitation and PET. The standardized precipitation-evapotranspiration index thus represents the hydrological processes that drive drought events more realistically than the standardized precipitation index at the expense of additional computational complexity and increased data demands. The additional computational complexity is principally due to the need to estimate PET within each time step. The standardized precipitation-evapotranspiration index was originally defined using the Thornthwaite PET model. However, numerous researchers have demonstrated the standardized precipitation-evapotranspiration index is sensitive to the PET model adopted. PET models requiring sparse meteorological inputs, such as the Thornthwaite model, have particular utility for drought monitoring in data scarce environments. The aridity index (AI) investigates the spatiotemporal changes in the hydroclimatic system. It is defined as the ratio between potential evapotranspiration and precipitation. It is used to characterize wet (humid) and dry (arid) regions. In this study, a sensitivity analysis for the standardized precipitation-evapotranspiration and aridity indexes was carried out using three different PET models; namely, the Penman–Monteith model, a temperature-based parametric model and the Thornthwaite model. The analysis was undertaken in six gauge stations in California region where long-term drought events have occurred. Having used the Penman–Monteith model as the PET model for estimating the standardized precipitation-evapotranspiration index, our findings highlight the presence of uncertainty in defining the severity of drought, especially for large timescales (12 months to 48 months), and that the PET parametric model is a preferable model to the Thornthwaite model for both the standardized precipitation-evapotranspiration index and the aridity indexes. The latter outcome is worth further consideration for when climatic studies are under development in data scarce areas where full required meteorological variables for Penman–Monteith assessment are not available. Full article
(This article belongs to the Special Issue Advances in Evaporation and Evaporative Demand: Part II)
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26 pages, 2541 KiB  
Article
A Comparative Study of Potential Evapotranspiration Estimation by Three Methods with FAO Penman–Monteith Method across Sri Lanka
by Himasha Dilshani Abeysiriwardana, Nitin Muttil and Upaka Rathnayake
Hydrology 2022, 9(11), 206; https://doi.org/10.3390/hydrology9110206 - 21 Nov 2022
Cited by 11 | Viewed by 3570
Abstract
Among numerous methods that have been developed to estimate potential evapotranspiration (PET), the Food and Agricultural Organization Penman–Monteith model (FAO P–M) is often recognized as a standard method to estimate PET. This study was conducted to evaluate the applicability of three other PET [...] Read more.
Among numerous methods that have been developed to estimate potential evapotranspiration (PET), the Food and Agricultural Organization Penman–Monteith model (FAO P–M) is often recognized as a standard method to estimate PET. This study was conducted to evaluate the applicability of three other PET estimation methods, i.e., Shuttleworth–Wallace (S–W) model, Thornthwaite (TW) and pan methods, to estimate PET across Sri Lanka with respect to the FAO P–M model. The meteorological data, i.e., temperature, relative humidity, wind speed, net solar radiation, and pan evaporation, recorded at 14 meteorologic stations, representing all climate and topographic zones of Sri Lanka, were obtained from 2009 to 2019. The models’ performances were assessed based on three statistical indicators: root mean squared error (RMSE), bias, and Pearson correlation coefficient (R). In comparison with the FAO P–M model estimates, the seasonal and annual estimates of all three models show great differences. The results suggested that pan and S–W methods perform better in the dry zone of the country. Both S–W and pan methods underestimated PET over the entire county in all seasons. TW does not show consistent results over the country, thus being found as the least reliable alternative. Although S–W is highly correlated with the FAO P–M model, the application of the model in a data-scarce region is more constrained, as it requires more parameters than the FAO P–M model. Thus, the study suggests employing alternative methods based on the region of the country instead of one single method across the entire country. Full article
(This article belongs to the Special Issue Advances in Evaporation and Evaporative Demand: Part II)
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