Spatial and Temporal Variations in Reference Crop Evapotranspiration in a Mountainous Island, Jeju, in South Korea

Um, Myoung-Jin; Kim, Yeonjoo; Park, Daeryong

doi:10.3390/w9040261

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…Crop evapotranspiration refers to the process of leaf water transpiration and soil water evaporation during the whole growth period of crops from sowing to maturity [1]. Reference crop evapotranspiration (ET 0 ), as an important index to characterize potential evapotranspiration and to evaluate the degree of drought, water consumption by vegetation, production potential, and water supply and demand balance [2,3], plays an important role in the water and energy cycles during crop growth [4]. ET 0 is an important element to understand global climate change and improve the utilization of agricultural water resources [5].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Distribution Characteristics of Reference Evapotranspiration in Shandong Province from 1980 to 2019

Zhang

Liu

Zhangzhong

et al. 2020

Water

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Reference evapotranspiration (ET0) is an important part of the water cycle and energy cycle during crop growth. Understanding the influencing factors and spatiotemporal variations of ET0 can guide regional water-saving irrigation and regulate agricultural production. Data for daily meteorological observations of temperature, relative humidity, wind speed, and sunshine hours from 38 surface meteorological stations were used to analyze the spatiotemporal variations and trends in Shandong Province from 1980 to 2019. (1) The ET0 from 1980 to 2019 was 1070.5 mm, and there was a significant downward trend in the climate tendency rate of −7.92/10 a. The climate of Shandong Province became warmer and drier. The average annual temperature showed a significant upward trend, while the average annual relative humidity and average annual sunshine hours showed significant downward trends. (2) The annual ET0 ratio in spring, summer, autumn, and winter was 29%, 40%, 21%, and 10%, respectively. (3) A change in Shandong Province’s interannual ET0 occurred in 2002, with a decrease of 130.74 mm since then. (4) The ET0 was positively correlated with temperature, wind speed, and sunshine hours and negatively correlated with relative humidity. This study provides a scientific basis for the regulation and control of agricultural production in Shandong Province.

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Section: Introductionmentioning

confidence: 99%

Spatiotemporal Distribution Characteristics of Reference Evapotranspiration in Shandong Province from 1980 to 2019

Zhang

Liu

Zhangzhong

et al. 2020

Water

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“…Birhanu et al [75], when constructing hydrological models, investigated the effect of model complexity and ET calculation methods on model performance based on the in-situ measurement. Um et al [76] estimated the spatial distribution of ET based on in-situ measurements using the hybrid Kriging method and revealed various ET characteristics depending on the distance from the coast and elevation level above the ground surface. Jung et al [77] developed the physiological modules to simulate the canopy photosynthesis and ET process and established the relationship of photosynthesis and ET with crop production based on satellite data and in-situ measurements.…”

Section: Previous Studies On the Korean Peninsulamentioning

confidence: 99%

Estimation of Daily Potential Evapotranspiration in Real-Time from GK2A/AMI Data Using Artificial Neural Network for the Korean Peninsula

et al. 2021

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Evapotranspiration (ET) is a fundamental factor in energy and hydrologic cycles. Although highly precise in-situ ET monitoring is possible, such data are not always available due to the high spatiotemporal variability in ET. This study estimates daily potential ET (PET) in real-time for the Korean Peninsula, via an artificial neural network (ANN), using data from the GEO-KOMPSAT 2A satellite, which is equipped with an Advanced Meteorological Imager (GK2A/AMI). We also used passive microwave data, numerical weather prediction (NWP) model data, and static data. The ANN-based PET model was trained using data for the period 25 July 2019 to 24 July 2020, and was tested by comparing with in-situ PET for the period 25 July 2020 to 31 July 2021. In terms of accuracy, the PET model performed well, with root-mean-square error (RMSE), bias, and Pearson’s correlation coefficient (R) of 0.649 mm day−1, −0.134 mm day−1, and 0.954, respectively. To examine the efficiency of the GK2A/AMI-derived PET data, we compared it with in-situ ET measured at flux towers and with MODIS PET data. The accuracy of the GK2A/AMI-derived PET, in comparison with the flux tower-measured ET, showed RMSE, bias, and Pearson’s R of 1.730 mm day−1, 1.212 mm day−1, and 0.809, respectively. In comparison with the in-situ PET, the ANN model produced more accurate estimates than the MODIS data, indicating that it is more locally optimized for the Korean Peninsula than MODIS. This study advances the field by applying an ANN approach using GK2A/AMI data and could play an important role in examining hydrologic energy for air-land interactions.

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Effects of climatic conditions and vegetation changes on actual evapotranspiration in Mu Us sandy land

Yang¹,

Shi²,

Li³

et al. 2023

Water Science &Amp; Technology

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Based on the MOD16A3GF data, spatial regression analysis was conducted to explore the annual trends of actual evapotranspiration (AET) and characteristics of its spatial distribution in Mu Us sandy land between 2000 and 2020, and combined meteorological data and MOD13 NDVI data to analyze its effects on AET by trend analysis and correlation coefficient. The results showed that (1) The AET exhibited significant regional differences; (2) The AET showed a rapid upward trend from 2001 to 2020, with an average rate of change of 5.68 mm a−1. The increase in AET rate increased from fast to slow in the order of Shaanxi > Ningxia > Inner Mongolia; (3) The correlation coefficient between AET and precipitation was 0.74, and there was no obvious correlation with temperature. The decreasing trend of water ET did not coincide with the AET trends; (4) AET was consistent with the NDVI spatial distribution and interannual variation curves. Under the influence of precipitation and NDVI, AET increased significantly from 2001 to 2020. Precipitation was the main factor affecting climatic conditions of AET, and NDVI was the dominant factor affecting AET in the same period. This provides a theoretical and scientific basis for the conservation and protection of Mu Us sandy land.

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Spatial and Temporal Variations in Reference Crop Evapotranspiration in a Mountainous Island, Jeju, in South Korea

Cited by 3 publications

References 23 publications

Spatiotemporal Distribution Characteristics of Reference Evapotranspiration in Shandong Province from 1980 to 2019

Spatiotemporal Distribution Characteristics of Reference Evapotranspiration in Shandong Province from 1980 to 2019

Estimation of Daily Potential Evapotranspiration in Real-Time from GK2A/AMI Data Using Artificial Neural Network for the Korean Peninsula

Effects of climatic conditions and vegetation changes on actual evapotranspiration in Mu Us sandy land

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