Spatial-temporal evaluation of different reference evapotranspiration methods based on the climate forecast system reanalysis data

被引:9
|
作者
Woldesenbet, Tekalegn Ayele [1 ]
Elagib, Nadir Ahmed [2 ]
机构
[1] Addis Ababa Univ, Ethiopian Inst Water Resources, POB 150461, Addis Ababa, Ethiopia
[2] Univ Cologne, Inst Geog, Fac Math & Nat Sci, Cologne, Germany
关键词
Ethiopia; FAO Penman-Monteith; NCEP CFSR data; Omo-Gibe river basin; radiation-based evapotranspiration methods; temperature-based evapotranspiration methods; HARGREAVES-SAMANI EQUATION; PENMAN-MONTEITH METHOD; REFERENCE CROP EVAPOTRANSPIRATION; POTENTIAL EVAPOTRANSPIRATION; EVAPORATION TRENDS; PAN EVAPORATION; RIVER-BASIN; CALIBRATION; SENSITIVITY; MODELS;
D O I
10.1002/hyp.14239
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Evapotranspiration is a major component of the interaction between land-surface processes and the atmosphere. Climate Forecast System Reanalysis (CFSR) data offer a promising database for overcoming the limitations in availability and reliability of climatological data and, hence, for understanding the evapotranspiration process. Using these data on grid-by-grid daily, seasonal and yearly scales, the present study attempts to advance the spatio-temporal evaluation of two radiation-based and three temperature-based methods for estimating potential evapotranspiration (PET) against estimates of grass reference evapotranspiration (ETo) by FAO Penman-Monteith method (FAO-PM). The analysis was performed for the period 1979-2013, considering the second largest (79 000 km(2)) river system in Ethiopia, that is, Omo-Gibe basin, which accommodates national parks and vast hydropower, cultivation and afforestation developments and discharges its flow to Lake Turkana in Kenya. Despite the large regional variations in climate and elevation, the results in overall emphasize the outperformance of the simple temperature method, viz. Hargreaves-Samani method, in capturing both the annual and seasonal FAO-PM estimates. Calibration of the Hargreaves-Samani equation is, however, a requisite for spectacular improvement of its performance. Accordingly, new coefficients of the equation are proposed. The annual trends in the basin's ETo increased with rising temperature and decreasing relative humidity, wind speed, and solar radiation, but with decreasing (increasing) rainfall in the upper region (the middle and lower regions). It is deduced that trends in simple methods do not necessarily reflect the true trends in ETo. Annual ETo decreases with increasing elevation and annual rainfall. The present findings are discussed in the context of a worldwide literature, thereby improving the understanding of the best performing PET methods in similar data-scarce national or transboundary rivers basin in Ethiopia, the region or worldwide. The wider implications regarding water loss from reservoirs and the rain-fed food and sugar production in the basin under study are also highlighted.
引用
收藏
页数:20
相关论文
共 50 条
  • [41] Comparison features importance for temporal and spatial-temporal approaches in GRACE and GRACE-FO signal reconstruction based on GLDAS data
    Szabo, Viktor
    INTERNATIONAL JOURNAL OF HYDROLOGY SCIENCE AND TECHNOLOGY, 2023, 16 (04) : 370 - 389
  • [42] Spatial and Temporal Variations of Terrestrial Evapotranspiration in the Upper Taohe River Basin from 2001 to 2018 Based on MOD16 ET Data
    Cheng, Lizhen
    Yang, Meixue
    Wang, Xuejia
    Wan, Guoning
    ADVANCES IN METEOROLOGY, 2020, 2020
  • [43] Deep graph gated recurrent unit network-based spatial-temporal multi-task learning for intelligent information fusion of multiple sites with application in short-term spatial-temporal probabilistic forecast of photovoltaic power
    Bai, Mingliang
    Zhou, Zhihao
    Li, Jingjing
    Chen, Yunxiao
    Liu, Jinfu
    Zhao, Xinyu
    Yu, Daren
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 240
  • [44] Daily reference evapotranspiration prediction based on climatic conditions applying different data mining techniques and empirical equations
    Unes, Fatih
    Kaya, Yunus Ziya
    Mamak, Mustafa
    THEORETICAL AND APPLIED CLIMATOLOGY, 2020, 141 (1-2) : 763 - 773
  • [46] Estimation of daily reference evapotranspiration with limited climatic data using machine learning approaches across different climate zones in New Mexico
    Mokari, Esmaiil
    DuBois, David
    Samani, Zohrab
    Mohebzadeh, Hamid
    Djaman, Koffi
    THEORETICAL AND APPLIED CLIMATOLOGY, 2022, 147 (1-2) : 575 - 587
  • [47] Travel time estimation at intersections based on low-frequency spatial-temporal GPS trajectory big data
    Tang, Luliang
    Kan, Zihan
    Zhang, Xia
    Yang, Xue
    Huang, Fangzhen
    Li, Qingquan
    CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE, 2016, 43 (05) : 417 - 426
  • [48] Evaluation of roadway spatial-temporal travel speed estimation using mapped low-frequency AVL probe data
    Peng, Liqun
    Li, Zhixiong
    Wang, Chenhao
    Sarkodie-Gyan, Thompson
    MEASUREMENT, 2020, 165
  • [49] Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China
    Fan, Junliang
    Yue, Wenjun
    Wu, Lifeng
    Zhang, Fucang
    Cai, Huanjie
    Wang, Xiukang
    Lu, Xianghui
    Xiang, Youzhen
    AGRICULTURAL AND FOREST METEOROLOGY, 2018, 263 : 225 - 241
  • [50] Short-term prediction of reference crop evapotranspiration based on machine learning with different decomposition methods in arid areas of China
    Lu, Yingjie
    Li, Tao
    Hu, Hui
    Zeng, Xuemei
    AGRICULTURAL WATER MANAGEMENT, 2023, 279