1 / 1

Application of satellite nadir altimetry for forecasting river flow in transboundary rivers

. Application of satellite nadir altimetry for forecasting river flow in transboundary rivers S. Biancamaria 1 ( sylvain@hydro.washington.edu ), F. Hossain 2 , D.P. Lettenmaier 1 , E.A. Clark 1 1 Civil and Environmental Engineering, University of Washington, Seattle WA

rainer
Download Presentation

Application of satellite nadir altimetry for forecasting river flow in transboundary rivers

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. . . Application of satellite nadir altimetry for forecasting river flow in transboundary rivers S. Biancamaria1 (sylvain@hydro.washington.edu), F. Hossain2, D.P. Lettenmaier1, E.A. Clark1 1 Civil and Environmental Engineering, University of Washington, Seattle WA 2 Civil and Environmental Engineering, Tennessee Technological University, Cookeville TN H11F-0885 AGU FallMeeting 2010 1. Introduction 2. Purpose of the study and methodology Purpose: Use water level anomalies from Topex/Poseidon (T/P) satellite nadir altimeter (from LEGOS-HYDROWEB, Fig. 1 and Table 1) in India and water level anomalies from two gages in Bangladesh (from BWDB/IWM, Fig. 1) to extend forecast lead time. Methodology: Compute correlation between in-situ and upstream T/P water level anomalies occurring k days earlier (k=time lag). For high correlations, compute in-situ versus time lagged T/P water level anomalies rating curve . Use the rating curve to forecast water level anomalies at the gage location from upstream T/P measurements. Table 1. Topex/Poseidon measurements from HYDROWEB • Ganges and Brahmaputra basins shared between India (upstream) and Bangladesh (downstream). • Issue: no information on rivers’ state shared between the 2 nations. The farthest upstream point of water level measurement for Bangladesh is at the border. • Consequence: Bangladesh can forecast water level only 3 days in advance (inadequate for risk managements). China 116_1 Nepal 116_2 Bhutan 053_1 242_1 166_1 Ganges 079_1 Brahmaputra 155_1 014_1 Bahadurabad (in-situ gage) India Hardinge (in-situ gage) Bangladesh Figure 1. In-situ gages (magenta dots), Topex/Poseidon’s virtual stations (red dots) and ground tracks (red lines) 3. Data used 4. Results • 5-day forecast at Bahadurabad (Brahmaputra) using T/P virtual station 166_1: • Water level in-situ measurements on the Brahmaputra River at Bahadurabad (Fig. 1) are available from January 2000 to September 2005. Measurements on the Ganges River at Hardinge Bridge are available from January 2001 to September 2005. • T/P measurements available from January 1993 to August 2002. T/P repeat period is equal to 10 days, but mean times between 2 obs. in the HYDROWEB time series are higher (Table 1). • Studied time period: Jan. 2000 to Aug. 2002 (Brahmaputra) and Jan. 2001 to Aug. 2002 (Ganges) + focus on monsoon (June to September) and dry season (October to May). • Brahmaputra: year 2000 = high discharge, floods in August; year 2001 = lower discharge, no floods; Ganges: year 2001 = “normal” discharge year, no floods (Fig. 2). 6 4 2 0 -2 -4 I. II. III. Forecast RMSE 5 4 3 2 1 0 -1 -2 -3 1.4 1.2 1 0.8 0.6 0.4 0.2 1 0.9 0.8 0.7 0.6 0.5 Monsoon+Dry In-situ Dry Wat. lvl anom. @ gage (m) Correlation in-situ/alti In-situ water lvl anom. (m) RMSE in-situ/alti (m) Monsoon 5-day time lag 5-day time lag 5-day forecast 0 5 10 15 20 0 5 10 15 20 -3 -2 -1 0 1 2 3 4 2000 2000.5 2001 2001.5 2002 0 5 10 15 20 0 5 10 15 20 Time lag (days) 5day lag alti water lvl anom. (m) Time (years) Time lag (days) Water level (m, ref. PWD) Discharge (104 m3.s-1) • 5-day forecast at Bahadurabad (Brahmaputra) using T/P virtual station 242_1: 22 20 18 16 14 12 10 8 6 4 2 0 6 4 2 0 -2 -4 I. II. III. Forecast RMSE 5 4 3 2 1 0 -1 -2 -3 1.4 1.2 1 0.8 0.6 0.4 0.2 1 0.9 0.8 0.7 0.6 0.5 Danger level Monsoon+Dry v v Dry In-situ Brahmaputra at Bahadurabad Flood level Correlation in-situ/alti Wat. lvl anom. @ gage (m) In-situ water lvl anom. (m) RMSE in-situ/alti (m) Monsoon 2000 2001 Lowest year (2002) Highest year (2004) 5-day time lag 5-day time lag 5-day forecast Feb Apr Jun Aug Oct Dec Feb Apr Jun Aug Oct Dec 2000 2000.5 2001 2001.5 2002 0 5 10 15 20 -3 -2 -1 0 1 2 3 4 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 Time lag (days) Time (years) Time lag (days) 5day lag alti water lvl anom. (m) 7 6 5 4 3 2 1 0 16 14 12 10 8 6 4 • 5-day forecast at Hardinge Bridge (Ganges) using T/P virtual station 014_1: Danger level Flood level 6 4 2 0 -2 -4 -6 v I. II. III. Forecast RMSE 1.4 1.2 1 0.8 0.6 0.4 0.2 6 4 2 0 -2 -4 1 0.9 0.8 0.7 0.6 0.5 Ganges at Hardinge Bridge Monsoon+Dry Dry Monsoon Correlation in-situ/alti 2001 Lowest year (2002) Highest year (2003) Wat. lvl anom. @ gage (m) In-situ water lvl anom. (m) RMSE in-situ/alti (m) 5-day forecast 5-day time lag Feb Apr Jun Aug Oct Dec Feb Apr Jun Aug Oct Dec In-situ 5-day time lag Figure 2. Water level and discharge measured at in-situ gage locations (see Fig. 1) 2001 2001.4 2001.8 0 5 10 15 20 -6 -4 -2 0 2 4 6 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 5. Conclusions and perspectives Time lag (days) 5day lag alti water lvl anom. (m) Time (years) Time lag (days) • 10-day forecast at Hardinge Bridge (Ganges) using T/P virtual station 116_2: • Nadir altimetry can forecast water level anomalies on the Brahmaputra and Ganges rivers with RMSE~0.4m for 5-day lead time and with RMSE~0.6-0.8m for 10-day lead time. • Temporal resolution of the forecast could be improved by using data from several nadir altimeters (like ERS-2, GFO, ENVISAT, JASON-2). • Future wide swath altimetry (like SWOT) should improve detection of floods, which might be currently missed when using only 1D measurements from nadir altimeters. • Future work: coupling with hydrodynamic model to forecast water level inside Bangladesh. • Acknowledgements: HYDROWEB (www.legos.obs-mip.fr/en/soa/hydrologie/hydroweb/) for T/P data; BWDB/IWM for in-situ data. 6 4 2 0 -2 -4 I. II. III. Forecast RMSE 1.4 1.2 1 0.8 0.6 0.4 0.2 6 4 2 0 -2 -4 1 0.9 0.8 0.7 0.6 0.5 Monsoon+Dry Monsoon Correlation in-situ/alti Wat. lvl anom. @ gage (m) In-situ water lvl anom. (m) RMSE in-situ/alti (m) 10-day forecast Dry 10-day time lag 10-day time lag In-situ -2 -1 0 1 2 3 2001 2001.4 2001.8 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 Time lag (days) 10day lag alti water lvl anom. (m) Time (years) Time lag (days)

More Related