Effect of Environmental Measurement Uncertainty on Prediction of Evapotranspiration

被引:14
作者
Chen, Ling-Hsi [1 ]
Chen, Jiunyuan [2 ]
Chen, Chiachung [2 ]
机构
[1] Taichung Dist Agr Res & Extens Stn, Taichung 51544, Taiwan
[2] Natl Chung Hsing Univ, Dept Bioind Mechatron Engn, Taichung 40227, Taiwan
来源
ATMOSPHERE | 2018年 / 9卷 / 10期
关键词
evapotranspiration model; sensors; uncertainty analysis; LEAF-AREA INDEX; MEDITERRANEAN CLIMATE; CROP TRANSPIRATION; SIMPLIFIED VERSION; SALINE WATER; MODEL; SENSITIVITY; CALIBRATION; ACCURACY; EQUATION;
D O I
10.3390/atmos9100400
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Evapotranspiration (ET) is a typical biological environmental process to influence leaf temperature, crop water requirement, and greenhouse microclimate. Affecting factors of ET include air temperature, air relative humidity, wind speed, solar radiation, longwave radiation, soil moisture, CO2 concentration, and crop state. In this study, two ET models of indoor cultivation commonly adopted in literature were selected to evaluate the effect of the performance of sensors on the model uncertainty. The method of the International Organization for Standardization, Guides to the expression of Uncertainty in Measurement (ISO GUM) was adopted. The result indicated that the performance of leaf area index (LAI) and solar radiation (Is) sensors were primary sources of uncertainty. The uncertainty of ET models due to sensor performance needs to be considered. To ensure the predictive ability for applying the ET model for crops irrigation management and greenhouse environmental control, the improvements in the measurement of environmental variables for calculating ET would be of particular importance. The method of this study can be used for evaluating the uncertainty of ET models that calculate ET based on environmental variables measured by meteorological sensors or the remote sensing technique.
引用
收藏
页数:13
相关论文
共 50 条
  • [11] Quantifying uncertainty in groundwater recharge due to spatiotemporal rainfall and temporal evapotranspiration variability
    Wiebe, Andrew J.
    Rudolph, David L.
    Craig, James R.
    JOURNAL OF HYDROLOGY, 2025, 657
  • [12] Influence of buffer quality on pH measurement uncertainty: prediction and experimental evaluation
    Irina Ekeltchik
    Elena Kardash-Strochkova
    Orna Dreazen
    I. Kuselman
    Accreditation and Quality Assurance, 2002, 7 : 412 - 416
  • [13] Influence of buffer quality on pH measurement uncertainty: prediction and experimental evaluation
    Ekeltchik, I
    Kardash-Strochkova, E
    Dreazen, O
    Kuselman, I
    ACCREDITATION AND QUALITY ASSURANCE, 2002, 7 (10) : 412 - 416
  • [14] Comparing the ability of different remotely sensed evapotranspiration products in enhancing hydrological model performance and reducing prediction uncertainty
    Taia, Soufiane
    Scozzari, Andrea
    Erraioui, Lamia
    Kili, Malika
    Mridekh, Abdelaziz
    Haida, Souad
    Chao, Jamal
    El Mansouri, Bouabid
    ECOLOGICAL INFORMATICS, 2023, 78
  • [15] Improving Streamflow Prediction Using Uncertainty Analysis and Bayesian Model Averaging
    Meira Neto, Antonio A.
    Oliveira, Paulo Tarso S.
    Rodrigues, Dulce B. B.
    Wendland, Edson
    JOURNAL OF HYDROLOGIC ENGINEERING, 2018, 23 (05)
  • [16] The effect of parameter uncertainty on a model with adjusted parameters
    Wallach, D
    Goffinet, B
    Bergez, JE
    Debaeke, P
    Leenhardt, D
    Aubertot, JN
    AGRONOMIE, 2002, 22 (02): : 159 - 170
  • [17] Environmental and canopy conditions regulate the forest floor evapotranspiration of larch plantations
    Liu, Zebin
    Wang, Yanhui
    Yu, Pengtao
    Xu, Lihong
    Yu, Songping
    FOREST ECOSYSTEMS, 2022, 9
  • [18] Uncertainty in the estimation of potential evapotranspiration under climate change
    Kingston, Daniel G.
    Todd, Martin C.
    Taylor, Richard G.
    Thompson, Julian R.
    Arnell, Nigel W.
    GEOPHYSICAL RESEARCH LETTERS, 2009, 36
  • [19] Separating Measurement Error and Signal in Environmental Data: Use of Replicates to Address Uncertainty
    Furman, Marschall
    Thomas, Kent W.
    George, Barbara Jane
    ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2023, 57 (41) : 15356 - 15365
  • [20] Sensitivity and uncertainty quantification for the ECOSTRESS evapotranspiration algorithm - DisALEXI
    Cawse-Nicholson, Kerry
    Braverman, Amy
    Kang, Emily L.
    Li, Miaoqi
    Johnson, Margaret
    Halverson, Gregory
    Anderson, Martha
    Hain, Christopher
    Gunson, Michael
    Hook, Simon
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2020, 89