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
  • [1] Spatial-Temporal Interpolation of Reference Evapotranspiration for Pakistan
    Saeed Shah, Syed Muhammad
    El-Morshedy, M.
    Mansoor, Wahidullah
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [2] Signal processing methods in analysing of spatial-temporal climate data
    Reljin, B
    Reljin, I
    Jovanovic, G
    SCS 2003: INTERNATIONAL SYMPOSIUM ON SIGNALS, CIRCUITS AND SYSTEMS, VOLS 1 AND 2, PROCEEDINGS, 2003, : 49 - 52
  • [3] A power load forecast approach based on spatial-temporal clustering of load data
    Zhang, Wei
    Mu, Gang
    Yan, Gangui
    An, Jun
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2018, 30 (23):
  • [4] Seasonal Prediction of Regional Reference Evapotranspiration Based on Climate Forecast System Version 2
    Tian, Di
    Martinez, Christopher J.
    Graham, Wendy D.
    JOURNAL OF HYDROMETEOROLOGY, 2014, 15 (03) : 1166 - 1188
  • [5] Spatial-temporal wave height forecast using deep learning and public reanalysis dataset
    Ti, Zilong
    Song, Yubing
    Deng, Xiaowei
    APPLIED ENERGY, 2022, 326
  • [6] Spatial-temporal Distribution Characteristics of Snow Depth in Mongolian Plateau Based on Reanalysis Data
    Quan, Lai
    Bao, Yulong
    Bao, Yongbin
    Sa Chula
    Bao, Yuhai
    PROCEEDINGS OF THE 8TH ANNUAL MEETING OF RISK ANALYSIS COUNCIL OF CHINA ASSOCIATION FOR DISASTER PREVENTION (RAC 2018), 2018, 66 : 258 - 264
  • [7] Spatial-temporal Data Interpolation Based on Spatial-temporal Kriging Method
    Xu M.-L.
    Xing T.
    Han M.
    Zidonghua Xuebao/Acta Automatica Sinica, 2020, 46 (08): : 1681 - 1688
  • [8] Temporal and Spatial Variability of Wind Resources in the United States as Derived from the Climate Forecast System Reanalysis
    Yu, Lejiang
    Zhong, Shiyuan
    Bian, Xindi
    Heilman, Warren E.
    JOURNAL OF CLIMATE, 2015, 28 (03) : 1166 - 1183
  • [9] Spatial-Temporal Analysis of Field Evapotranspiration Based on Complementary Relationship Model and IKONOS Data
    Yang Guijun
    Zhao Chunjiang
    Xu Qingyun
    2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 2836 - 2839
  • [10] Intercomparison of the different fusion methods for generating high spatial-temporal resolution data
    Shi Yue-Chan
    Yang Gui-Jun
    Li Xin-Chuan
    Song Jian
    Wang Ji-Hua
    Wang Jin-Di
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 2015, 34 (01) : 92 - 99