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DOI | 10.1002/joc.5057 |
Non-stationary modelling framework for rainfall interpolation in complex terrain | |
Kumari, Madhuri1,2; Singh, Chander Kumar1,3; Basistha, Ashoke4; Dorji, Singay5; Tamang, Tayba Buddha5 | |
2017-09-01 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY
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ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2017 |
卷号 | 37期号:11 |
文章类型 | Article |
语种 | 英语 |
国家 | India; Bhutan |
英文摘要 | The knowledge of rainfall-elevation relationship forms an important input for modelling the orographic rainfall in mountainous areas. The conventional regression and geostatistical techniques assume the rainfall and elevation relationship to be constant; however, in complex terrain these exhibit non-stationarity in their relationship. This study proposes a novel spatial rainfall modelling framework, stratified geographically weighted regression-residual kriging (s-GWRK) that integrates the benefit of spatially clustered data as an input, local-scale model and incorporation of spatial correlation structure of residuals. The application of the framework is demonstrated in Indian Himalayas of Uttarakhand region with two spatial clusters of normal annual rainfall data, lowland and upland, based on natural clustering technique. The performance of the proposed model is compared with ordinary co-kriging (OCK), ordinary least square regression (OLS), geographically weighted regression (GWR) and geographically weighted regression kriging (GWRK) that incorporates elevation as predictor variable. Model evaluation shows that s-GWRK performed best with root mean square error (RMSE) of 153.98 and index of agreement (d) of 0.92. OLS performed least with RMSE of 461.2 and d value of 0.32. OCK using elevation as auxiliary variable performed better than OLS with RMSE of 454.7 and d value of 0.53. The predictive capability of s-GWRK was validated using the data collected from rain gauge network in the mountainous terrain of Ashburton in New Zealand and Bhutan. An improvement of 30% and 55% in RMSE was observed compared to OCK for Ashburton and Bhutan respectively. For Uttarakhand, Ashburton and Bhutan, the positive rainfall lapse rate derived from GWR model of rainfall-elevation relation, ranged from 0.01-1.3, 0.2-1.43 and 0.09-0.4mmm(-1). |
英文关键词 | non-stationarity GWR rainfall lapse rate complex terrain residual kriging rainfall interpolation clustering |
领域 | 气候变化 |
收录类别 | SCI-E ; SSCI |
WOS记录号 | WOS:000409036800015 |
WOS关键词 | GEOGRAPHICALLY WEIGHTED REGRESSION ; DAILY PRECIPITATION ; ELEVATION DATA ; SPATIAL INTERPOLATION ; GENERAL FRAMEWORK ; TOPOGRAPHY ; VARIABILITY ; VARIABLES ; REGION ; TEMPERATURE |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/37390 |
专题 | 气候变化 |
作者单位 | 1.TERI Univ, Dept Nat Resources, New Delhi, India; 2.Amity Univ, Amity Sch Engn & Technol, Dept Civil Engn, Noida, Uttar Pradesh, India; 3.TERI Univ, Environm & Energy Dept, Plot 10 Inst Area, New Delhi 110070, India; 4.Egis India Consulting Engineers Pvt Ltd, New Delhi, India; 5.Minist Econ Affairs, Dept Hydro Met Serv, Meteorol Div, Thimphu, Bhutan |
推荐引用方式 GB/T 7714 | Kumari, Madhuri,Singh, Chander Kumar,Basistha, Ashoke,et al. Non-stationary modelling framework for rainfall interpolation in complex terrain[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2017,37(11). |
APA | Kumari, Madhuri,Singh, Chander Kumar,Basistha, Ashoke,Dorji, Singay,&Tamang, Tayba Buddha.(2017).Non-stationary modelling framework for rainfall interpolation in complex terrain.INTERNATIONAL JOURNAL OF CLIMATOLOGY,37(11). |
MLA | Kumari, Madhuri,et al."Non-stationary modelling framework for rainfall interpolation in complex terrain".INTERNATIONAL JOURNAL OF CLIMATOLOGY 37.11(2017). |
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