Statistical analysis of modified Hargreaves equation for precise estimation of reference evapotranspiration

Habeeb, Rimsha; Zhang, Xiang; Hussain, Ijaz; Hashmi, Muhammad Zaffar; Elashkar, Elsayed Elsherbini; Khader, Jameel Ahmad; Soudagar, Sadaf Shamshoddin; Shoukry, Alaa Mohamd; Ali, Zulfiqar; Al-Deek, Fares Fawzi

doi:10.1080/16000870.2021.1966869

Cited by 9 publications

(5 citation statements)

References 17 publications

(35 reference statements)

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“…The monthly, seasonal, and annual observations found that RF estimated better than other models. The trend of estimated ET 0 by the modi ed Hargreaves-Samani model was similar to the previous study done around the globe (Trajkovic 2007, Habeeb et al, 2021, Gentilucci et al 2021). The growth and yield of the maize and wheat crops were found to be comparable for both treatments.…”

Section: Calibration and Validation Modelssupporting

confidence: 87%

Development of machine learning-based reference evapotranspiration model for the semi-arid region of Punjab, India

Das

Kaur

Raheja

et al. 2022

Preprint

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Evapotranspiration (ET) is a critical element of the hydrological cycle, and its proper assessment is essential for irrigation scheduling, agricultural and hydro-meteorological studies, and water budget estimation. It is computed for most applications as a product of reference crop evapotranspiration (ET0) and crop coefficient, notably using the well-known two-step method. Accurate predictions of reference evapotranspiration (ET0) using limited meteorological inputs are critical in data-constrained circumstances, and the preferred FAO-56 Penman-Monteith (PM) equation cannot be used. To overcome the complexity of calculation, the present study is focused on developing a Random Forest-based ET0 model to estimate the crop ET for the semi-arid region of northwest India. The RF-based model was developed by focusing on the readily available data at the farm level. For comparative study Hargreaves–Samani model was also modified and used to estimate the ET0. Further, ET0 was also estimated using existing models like Hargreaves–Samani model and the Modified Panman model. The models' calibration and validation were done using meteorological data collected from the weather station of Punjab Agricultural University for 21 years (2090 − 2010) and nine years (2011–2019), respectively, and the PM FAO-56 model was taken as a standard model. The developed RF-based model's mean absolute error and root-mean-square deviation were found to be better than the other models, and it was obtained as 0.95 mm/d and 1.32, respectively, with an r2 value of 0.92. The developed RF-based model was used to predict the ET0, and further, predicted ET0 values were used for irrigation scheduling of two growing seasons (2020–2021) of maize and wheat crops. The result of the field experiment also shows that there was no significant yield reduction in the crop. Hence, This developed study model can be used for the irrigation in the semiarid region of the Punjab India as well as other part of world. Also, it can be used as a replacement FAO-56 model.

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Section: Calibration and Validation Modelssupporting

confidence: 87%

Development of machine learning-based reference evapotranspiration model for the semi-arid region of Punjab, India

Das

Kaur

Raheja

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…Some of the input data used for ET estimation were based on assumptions. Moreover, Habeeb et al [47] evaluated the performance of the Hargreaves method and its modified version in estimating ET in Pakistan. They showed the modified Hargreaves method performs better than its original version in estimating ET in Pakistan.…”

Section: Introductionmentioning

confidence: 99%

Ranking of Empirical Evapotranspiration Models in Different Climate Zones of Pakistan

Hamed

Khan

Muhammad

et al. 2022

Land

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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.

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“…A python script was written to serve this purpose. Three methods were covered in the detection, i.e., Pettitt test (Mallakpour & Villarini, 2016), Buishand U test (Habeeb et al, 2021), and Standard Normal Homogeneity test (SNHT) (Pohlert, 2020). These tests were applied in the two time series of HMI values of magazines and newspapers.…”

Section: Change Point Detectionmentioning

confidence: 99%

Have media texts become more humorous?

Zhu,

Deng

2023

EJHR

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As a research topic, humour has drawn much attention from multiple disciplines including linguistics. Based on Engelthaler & Hills’ (2018) humour scale, this study developed a measure named Humour Index (HMI) to quantify the degree of humour of texts. This measure was applied to examine the diachronic changes in the degree of humour of American newspapers and magazines across a time span of 118 years (1900-2017) with the use of texts from Corpus of Historical American English (COHA). Besides, the study also discussed the contributions of different types of words to the degree of humour in the two genres. The results show significant uptrends in the degree of humour of both newspapers and magazines in the examined period. Moreover, derogatory and offensive words are found to be less frequently used than other categories of words in both genres. This study provides both theoretical and methodological implications for humour studies and claims or hypotheses of previous research, such as infotainment and linguistic positivity bias.

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Statistical analysis of modified Hargreaves equation for precise estimation of reference evapotranspiration

Cited by 9 publications

References 17 publications

Development of machine learning-based reference evapotranspiration model for the semi-arid region of Punjab, India

Development of machine learning-based reference evapotranspiration model for the semi-arid region of Punjab, India

Ranking of Empirical Evapotranspiration Models in Different Climate Zones of Pakistan

Have media texts become more humorous?

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