Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt

Vremec, Matevž; Collenteur, Raoul; Birk, Steffen

doi:10.5194/hess-2022-417

Cited by 3 publications

(2 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If EZ > 5, EZ was set to 5 to be consistent with the spatial resolution of the different atmospheric forcings (≥0.05°) in mountainous areas. Based on the maximum and minimum daily temperature of each dataset, Ep was calculated using the Hargreaves equation and the PyEt package 109 . To maximise the KGE between observed and simulated streamflow, the automatic calibration was performed for each combination of atmospheric forcing (n = 6) and each independent catchment using the hydroPSO R package v0.5 74,110 .…”

Section: Data Recordsmentioning

confidence: 99%

PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia

Aguayo,

León-Muñoz,

Aguayo

et al. 2024

Sci Data

View full text Add to dashboard Cite

Western Patagonia (40–56°S) is a clear example of how the systematic lack of publicly available data and poor quality control protocols have hindered further hydrometeorological studies. To address these limitations, we present PatagoniaMet (PMET), a compilation of ground-based hydrometeorological data (PMET-obs; 1950–2020), and a daily gridded product of precipitation and temperature (PMET-sim; 1980–2020). PMET-obs was developed considering a 4-step quality control process applied to 523 hydrometeorological time series obtained from eight institutions in Chile and Argentina. Following current guidelines for hydrological datasets, several climatic and geographic attributes were derived for each catchment. PMET-sim was developed using statistical bias correction procedures, spatial regression models and hydrological methods, and was compared against other bias-corrected alternatives using hydrological modelling. PMET-sim was able to achieve Kling-Gupta efficiencies greater than 0.7 in 72% of the catchments, while other alternatives exceeded this threshold in only 50% of the catchments. PatagoniaMet represents an important milestone in the availability of hydro-meteorological data that will facilitate new studies in one of the largest freshwater ecosystems in the world.

show abstract

Section: Data Recordsmentioning

confidence: 99%

PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia

Aguayo,

León-Muñoz,

Aguayo

et al. 2024

Sci Data

View full text Add to dashboard Cite

show abstract

“…Evapotranspiration (ET) is a complex process that proves challenging to measure directly (Jensen and Allen, 2016;Vremec et al, 2023a;Vremec et al, 2023b;Wang and Dickinson, 2012). Consequently, it is commonly estimated by (semi-)empirical formulas based on more readily available meteorological observations, including air temperature and humidity, wind speed, and radiation (global radiation or net radiation).…”

Section: Introductionmentioning

confidence: 99%

On the Estimation of Global Plant Water Requirement

Wang,

Zeng,

Song

et al. 2024

Preprint

View full text Add to dashboard Cite

Abstract. Water supply is the most critical constraint for vegetation growth and food security. The amount of water demand by plant growth is usually estimated by plant water requirement which unfortunately cannot be directly measured at any large scale in field conditions. Different estimation methods have been proposed in the past seven decades for estimating plant water requirements using the concept of reference evapotranspiration (ET0) methods or potential evapotranspiration (PET) methods. In addition, using PET or ET0 to estimate actual evapotranspiration (ETa) is a critical approach in hydrological and climate models. However, different PET or ET0 models provide diverse results for irrigation water requirement (IWR) that in turn may result in a huge waste of irrigation water. Here, we assess the suitability of six common methods for estimating PET at 170 eddy covariance flux sites and propose a practical approach for estimating the IWR using a physically consistent model STEMMUS-SCOPE. Notably, the Priestley-Taylor and LSA_SAF method excels in providing reasonable approximations of daily PET. Consequently, in scenarios where net radiation data and ground heat flux are accessible, the Priestley-Taypor method emerges as the recommended choice. The LSA_SAF method is the better one when only net radiation data is available. Alternatively, in cases where only global radiation data is available, the Makkink and Hargreaves methods serve as viable substitutes. Although the FAO56 Penman-Monteith method is much better than the original Penman-Monteith method when wind speed and air humidity data are at hand, its suitability falls short of the preferred status. This study contributes to understanding and quantifying the applicability of different methods in estimating PET and IWR, based on input data availability and physical considerations.

show abstract