DOI: 10.1002/2017MS000986
Scopus记录号: 2-s2.0-85042145185
论文题名: A Hybrid of Optical Remote Sensing and Hydrological Modeling Improves Water Balance Estimation
作者: Gleason C ; J ; , Wada Y ; , Wang J
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2018
卷: 10, 期: 1 起始页码: 2
结束页码: 17
语种: 英语
英文关键词: Gages
; Hydrology
; Water resources
; AMHG
; Hydrological modeling
; Nile
; Optical remote sensing
; PCR-GLOBWB
; Ungauged basins
; Water balance estimation
; Water balance models
; Remote sensing
; baseflow
; flow measurement
; flow modeling
; gauge
; hydrograph
; hydrological modeling
; Landsat
; remote sensing
; river discharge
; river flow
; river management
; water budget
; Nile Basin
英文摘要: Declining gauging infrastructure and fractious water politics have decreased available information about river flows globally. Remote sensing and water balance modeling are frequently cited as potential solutions, but these techniques largely rely on these same in-decline gauge data to make accurate discharge estimates. A different approach is therefore needed, and we here combine remotely sensed discharge estimates made via at-many-stations hydraulic geometry (AMHG) and the PCR-GLOBWB hydrological model to estimate discharge over the Lower Nile. Specifically, we first estimate initial discharges from 87 Landsat images and AMHG (1984–2015), and then use these flow estimates to tune the model, all without using gauge data. The resulting tuned modeled hydrograph shows a large improvement in flow magnitude: validation of the tuned monthly hydrograph against a historical gauge (1978–1984) yields an RMSE of 439 m3/s (40.8%). By contrast, the original simulation had an order-of-magnitude flow error. This improvement is substantial but not perfect: tuned flows have a 1–2 month wet season lag and a negative base flow bias. Accounting for this 2 month lag yields a hydrograph RMSE of 270 m3/s (25.7%). Thus, our results coupling physical models and remote sensing is a promising first step and proof of concept toward future modeling of ungauged flows, especially as developments in cloud computing for remote sensing make our method easily applicable to any basin. Finally, we purposefully do not offer prescriptive solutions for Nile management, and rather hope that the methods demonstrated herein can prove useful to river stakeholders in managing their own water. © 2017. The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75676
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
There are no files associated with this item.
作者单位: Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, MA, United States; International Institute for Applied Systems Analysis, Laxenburg, Austria; Faculty of Geosciences, Department of Physical Geography, Utrecht University, Utrecht, Netherlands; Department of Geography, Kansas State University, Manhattan, KS, United States
Recommended Citation:
Gleason C,J,, Wada Y,et al. A Hybrid of Optical Remote Sensing and Hydrological Modeling Improves Water Balance Estimation[J]. Journal of Advances in Modeling Earth Systems,2018-01-01,10(1)