Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR024487 |
Can Improved Flow Partitioning in Hydrologic Models Increase Biogeochemical Predictability? | |
Shafii, Mahyar1,2; Craig, James R.2,3; Macrae, Merrin L.2,4,5; English, Michael C.4; Schiff, Sherry L.1,2; Van Cappellen, Philippe1,2; Basu, Nandita B.1,2,3 | |
2019-04-01 | |
发表期刊 | WATER RESOURCES RESEARCH |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:4页码:2939-2960 |
文章类型 | Article |
语种 | 英语 |
国家 | Canada |
英文摘要 | Hydrologic models partition flows into surface and subsurface pathways, but their calibration is typically conducted only against streamflow. Here we argue that unless model outcomes are constrained using flow pathway data, multiple partitioning schemes can lead to the same streamflow. This point becomes critical for biogeochemical modeling as individual flow paths may yield unique chemical signatures. We show how information on flow pathways can be used to constrain hydrologic flow partitioning and how improved partitioning can lead to better water quality predictions. As a case study, an agricultural basin in Ontario is used to demonstrate that using tile discharge data could increase the performance of both the hydrology and the nitrogen transport models. Watershed-scale tile discharge was estimated based on sparse tile data collected at some tiles using a novel regression-based approach. Through a series of calibration experiments, we show that utilizing tile flow signatures as calibration criteria improves model performance in the prediction of nitrate loads in both the calibration and validation periods. Predictability of nitrate loads is improved even with no tile flow data and by model calibration only against an approximate understanding of annual tile flow percent. However, despite high values of goodness-of-fit metrics in this case, temporal dynamics of predictions are inconsistent with reality. For instance, the model predicts significant tile discharge in summer with no tile flow occurrence in the field. Hence, the proposed tile flow upscaling approach and the partitioning-constrained model calibration are vital steps toward improving the predictability of biogeochemical models in tiled landscapes. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000468597900021 |
WOS关键词 | WATER ASSESSMENT-TOOL ; GULF-OF-MEXICO ; DIAGNOSTIC-APPROACH ; TIME DISTRIBUTIONS ; PHOSPHORUS EXPORT ; NITROGEN-CYCLE ; SOIL-MOISTURE ; TILE DRAINS ; CATCHMENT ; NITRATE |
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/182226 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Waterloo, Dept Earth & Environm Sci, Waterloo, ON, Canada; 2.Univ Waterloo, Water Inst, Waterloo, ON, Canada; 3.Univ Waterloo, Dept Civil & Environm Engn, Waterloo, ON, Canada; 4.Wilfrid Laurier Univ, Dept Geog & Environm Studies, Waterloo, ON, Canada; 5.Univ Waterloo, Dept Geog & Environm Management, Waterloo, ON, Canada |
推荐引用方式 GB/T 7714 | Shafii, Mahyar,Craig, James R.,Macrae, Merrin L.,et al. Can Improved Flow Partitioning in Hydrologic Models Increase Biogeochemical Predictability?[J]. WATER RESOURCES RESEARCH,2019,55(4):2939-2960. |
APA | Shafii, Mahyar.,Craig, James R..,Macrae, Merrin L..,English, Michael C..,Schiff, Sherry L..,...&Basu, Nandita B..(2019).Can Improved Flow Partitioning in Hydrologic Models Increase Biogeochemical Predictability?.WATER RESOURCES RESEARCH,55(4),2939-2960. |
MLA | Shafii, Mahyar,et al."Can Improved Flow Partitioning in Hydrologic Models Increase Biogeochemical Predictability?".WATER RESOURCES RESEARCH 55.4(2019):2939-2960. |
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