Towards validation of the Canadian precipitation analysis (CaPA) for hydrologic modeling applications in the Canadian Prairies

被引:24
作者
Boluwade, Alaba [1 ]
Zhao, K. -Y. [2 ]
Stadnyk, T. A. [1 ]
Rasmussen, P. [1 ]
机构
[1] Univ Manitoba, Dept Civil Engn, 15 Gillson St, Winnipeg, MB R3T 5V6, Canada
[2] Manitoba Infrastruct & Transportat, Winnipeg, MB, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Precipitation forcing; Precipitation data quality; Hydrologic modeling; Canadian precipitation analysis; Bayesian change point analysis; Spatial autocorrelation; Interpolation; CHANGE-POINT ANALYSIS; BAYESIAN-ANALYSIS; TIME-SERIES; GEM MODEL; INTERPOLATION; RAINFALL; PACKAGE; SCALE;
D O I
10.1016/j.jhydrol.2017.05.059
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study presents a three-step validation technique to compare the performance of the Canadian Precipitation Analysis (CaPA) product relative to actual observation as a hydrologic forcing in regional watershed simulation. CaPA is an interpolated (6 h or 24 h accumulation) reanalysis precipitation product in near real time covering all of North America. The analysis procedure involves point-to-point (P2P) and map-to-map (M2M) comparisons, followed by proxy validation using an operational version of the WATFLOOD (TM) hydrologic model from 2002 to 2005 in the Lake Winnipeg Basin (LWB), Canada. The P2P technique using a Bayesian change point analysis shows that CaPA corresponds with actual observations (Canadian daily climate data, CDCD), on both an annual and seasonal basis. CaPA has the same spatial pattern, dependency and autocorrelation properties as CDCD pixel by pixel (M2M). When used as hydrologic forcing in WATFLOOD (TM), results indicate that CaPA is a reliable product for water resource modeling and predictions, but that the quality of CaPA data varies annually and seasonally, as does the quality of observations. CaPA proved most beneficial as a hydrologic forcing during winter seasons where observation quality is the lowest. Reanalysis products, such as CaPA, can be a reliable option in sparse network areas, and is beneficial for regional governments when the cost of new weather stations is prohibitive. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:1244 / 1255
页数:12
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