Ranking of Empirical Evapotranspiration Models in Different Climate Zones of Pakistan

Abstract

Accurate estimation of evapotranspiration (ET) is vital for water resource development, planning and management, particularly in the present global warming context. A large number of empirical ET models have been developed for estimating ET. The main limitations of this method are that it requires several meteorological variables and an extensive data span to comprehend the ET pattern accurately, which is not available in most developing countries. The efficiency of 30 empirical ET models has been evaluated in this study to rank them for Pakistan to facilitate the selection of suitable models according to data availability. Princeton Global Meteorological Forcing daily climate data with a 0.25° × 0.25° resolution for 1948–2016 were utilized. The ET estimated using Penman–Monteith (PM) was considered as the reference. Multi-criteria group decision making (MCGDM) was used to rank the models for Pakistan. The results showed the temperature-based Hamon as the best model for most of Pakistan, followed by Hargreaves–Samani and Penman models. Hamon also showed the best performance in terms of different statistical metrics used in the study with a mean bias (PBias) of −50.2%, mean error (ME) of −1.62 mm and correlation coefficient (R2) of 0.65. Ivan showed the best performance among the humidity-based models, Irmak-RS and Ritch among the radiation-based models and Penman among the mass transfer-based models. Northern Pakistan was the most heterogeneous region in the relative performance of different ET models.

Comparative Assessment of Eight Empirical and Four Hybrid Machine Learning Models for Estimating Daily Reference Evapotranspiration in Sub-Humid and Semi-Arid Climates

“…The statistical results of the eight empirical models (Dal1802, Trab1896, Harg1975, Irs2003, HargS1985, BC1986, VAL2013a and VAL2013b) for estimating daily RET at the five meteorological stations within the Gharb and Loukkos perimeters are presented in Tables 8 and 9 outperform radiation-based models like Harg1975 and Irs2003, as well as mass transfer models like Dal1802 and Trab1896. This finding is in line with the conclusions drawn by several other researchers [11]. Conversely, it is important to note that some researchers [14,55,57] have suggested that radiationbased models may perform better than temperature-based models.…”

“…𝑥 𝑛𝑜𝑟𝑚 = 𝑥 0 − 𝑥 𝑚𝑖𝑛 𝑥 𝑚𝑎𝑥 − 𝑥 𝑚𝑖𝑛 (11) Where, xnorm represents the normalised value, x0 is the real value, and xmin and xmax are the minimum and maximum values respectively.…”

“…Numerous researches have been conducted to investigate the effectiveness of different RET methods across different regions and climatic conditions. These studies compare empirical models with PM-FAO56 using different approaches [10][11][12][13], including (a) temperature-based methods, (b) radiationbased methods, (c) mass transfer based methods, (d) methods combining radiation and temperature, and (e) methods integrating radiation, temperature, mass transfer, and other variables. For example, Almorox et al [12] assessed eleven temperature-based potential evapotranspiration (PET) estimation methods and determined that the Hargreaves and Samani model exhibited the most accurate performance on a global scale across diverse climatic regions.…”

A novel approach for evaluation of CMIP6 GCMs in simulating temperature and precipitation extremes of Pakistan

“…Over the last century, Pakistan's average temperature has risen by over 0.6°C, with more significant increases observed in the northern, high‐elevated areas. Moreover, the increase was more pronounced in the second half (1951–2000) than in the first half (1901–1949) (Ali et al, 2019; Hamed et al, 2022a). These variations in temperature and precipitation variables are worth studying for the water resource management of the region.…”