Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/2015WR017738 |
Comparison of soil wetness from multiple models over Australia with observations | |
Vinodkumar1,2; Dharssi, I.1; Bally, J.3; Steinle, P.1; McJannet, D.4; Walker, J.5 | |
2017 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2017 |
卷号 | 53期号:1 |
文章类型 | Article |
语种 | 英语 |
国家 | Australia |
英文摘要 | The McArthur Forest Fire Danger Index used in Australia for operational fire warnings has a component representing fuel availability called the Drought Factor (DF). The DF is partly based on soil moisture deficit, calculated as either the Keetch-Byram Drought Index (KBDI) or Mount's Soil Dryness Index (MSDI). The KBDI and MSDI are simplified water balance models driven by observation based daily rainfall and temperature. In this work, gridded KBDI and MSDI analyses are computed at a horizontal resolution of 5 km and are verified against in-situ soil moisture observations. Also verified is another simple model called the Antecedent Precipitation Index (API). Soil moisture analyses from the Australian Community Climate and Earth System Simulator (ACCESS) global Numerical Weather Prediction (NWP) system as well as remotely sensed soil wetness retrievals from the Advanced Scatterometer (ASCAT) are also verified. The verification shows that the NWP soil wetness analyses have greater skill and smaller biases than the KBDI, MSDI and API analyses. This is despite the NWP system having a coarse horizontal resolution and not using observed precipitation. The average temporal correlations (root mean square difference) between cosmic ray soil moisture monitoring facility observations and modeled or remotely sensed soil wetness are 0.82 (0.15 0.02), 0.66 (0.33 0.07), 0.77 (0.20 0.03), 0.74 (0.22 0.03) and 0.83 (0.18 +/- 0.04) for NWP, KBDI, MSDI, API and ASCAT. The results from this study suggests that analyses of soil moisture can be greatly improved by using physically based land surface models, remote sensing measurements and data assimilation. |
英文关键词 | soil moisture verification remote sensing wildfire ASCAT drought index |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000394911200038 |
WOS关键词 | TRIPLE COLLOCATION ANALYSIS ; IN-SITU OBSERVATIONS ; ERROR CHARACTERIZATION ; HYDRAULIC-PROPERTIES ; MOISTURE PRODUCTS ; DROUGHT INDEX ; ASCAT ; CLIMATE ; VARIABILITY ; EQUATIONS |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
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/21026 |
专题 | 资源环境科学 |
作者单位 | 1.Bur Meteorol, Melbourne, Vic, Australia; 2.Bushfire & Nat Hazards Cooperat Res Ctr, Melbourne, Vic, Australia; 3.Bur Meteorol, Hobart, Tas, Australia; 4.CSIRO Land & Water, Ecosci Precinct, Dutton Pk, Qld, Australia; 5.Monash Univ, Dept Civil Engn, Clayton, Vic, Australia |
推荐引用方式 GB/T 7714 | Vinodkumar,Dharssi, I.,Bally, J.,et al. Comparison of soil wetness from multiple models over Australia with observations[J]. WATER RESOURCES RESEARCH,2017,53(1). |
APA | Vinodkumar,Dharssi, I.,Bally, J.,Steinle, P.,McJannet, D.,&Walker, J..(2017).Comparison of soil wetness from multiple models over Australia with observations.WATER RESOURCES RESEARCH,53(1). |
MLA | Vinodkumar,et al."Comparison of soil wetness from multiple models over Australia with observations".WATER RESOURCES RESEARCH 53.1(2017). |
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