Assessing bias in satellite rainfall products and their impact in water balance closure at the Zambezi headwaters

Transcription

1 Assessing bias in satellite rainfall products and their impact in water balance closure at the Zambezi headwaters Omondi C.K. 1 Rientjes T.H.M. 1, Haile T.A. 2, Gumindoga W. 1,3 (1) Faculty ITC, University of Twente, THE NETHERLANDS (2) International Water management Institute (IWMI), ETHIOPIA (3) Department of Civil Engineering, University of Zimbabwe, ZIMBABWE, c.k.omondi@utwente.nl RCMRD September 2017

2 Outline Introduction Objectives Methodology Results Conclusion

3 Introduction In-situ meteorological data limitations. Satellite rainfall estimates (SREs) prone to error. SREs accuracy is affected by seasonal variations. Use of bias corrected SREs in streamflow simulations at the Zambezi headwaters.

4 Objectives Assess performance of 3 satellite rainfall products for streamflow simulation ( ) Specifically: a) SREs error analysis and comparison (occurrence, depth, error decomposition). b) compare SREs bias correction algorithms for different rain rates and seasons. c) parameterize TOPMODEL RR model using RS data. d) assess water balance closure as affected by use of bias corrected satellite rainfall.

5 Methodology Satellite products Satellite rainfall and evaporation products Ground measurements Ground measurements CMORPH TMPA CHIRPS FEWSNET Gauge Rainfall Discharge PET variables SREs pre-processing Rainfall data quality assessment Rainfall products performance evaluation Bias corrections Modified TopMODEL IDL code TopMODEL application Calibration using gauge & bias corrected SREs Streamflow Sensitivity & simulations statistical error analysis Validation Model parameters Comparison of simulated hydrograph processes Water balance closure analysis

6 a) In-situ & discharge data ( ) Station Coordinates of station Type of meteorological variable from the station ID Name Lat. Lon. Altitude P Tmax Tmin RH WS SS Kabompo x x x x x Kaoma x x x x x Kasempa x x x x Mwinilunga x x x x x x Solwezi x x x x x Zambezi x x x x x x P rainfall, Tmax - daily maximum temperature. Tmin daily minimum temperature, RH relative humidity, WS wind speed and SS sunshine hours

7 b) Satellite rainfall estimates products Rainfall product CMORPH TMPA CHIRPS Provider NOAA-CPC NASA CHG, USGS Spatial coverage 60 N to 60 S, globally 50 N to 50 S, globally 50 N to 50 S, across all longitudes Temporal coverage Since since Since Period tested Original/ used spatial resolution 0.07 / / Original/ used time step ½ h / 24 h 3 h / 24 h 24 h Stream line Contour line c) SRTM 90m digital elevation model d) TOPMODEL

8 Annual rainfall [mm] Elevation [masl] Results Elevation influence on satellite rainfall detections Gauge TMPA Elevation CHIRPS CMORPH Zambezi Kaoma Kasempa Mwinilunga Solwezi 1000 Elevation SREs rainfall measured at the stations. TMPA > Gauge rainfall accumulations unlike CMORPH & CHIRPS. CMORPH underestimates mean annual gauge rainfall.

9 Standard deviation [mm d -1 ] 0.0 Satellite estimates versus gauge rainfall (reference) o SREs underestimated (Max & തP) gauge rainfall depths. o CHIRPS had the largest daily deviation (1.05 mm) from തP. o CMORPH shows highest bias (1.56 mm d -1 ) while TMPA (<0.05 mm d -1 ) T4 Taylor s diagram M2 M4 T3 M3 M1 P3 T2 T5 M5 P4 P2 T1 P5 P1 T-CMORPH P-CHIRPS M-TMPA o Rainy seasons and high rainfall events exhibit higher bias REF 10 Standard deviation [mm d -1 ] 1: Kaoma, 2: Kasempa, 3: Mwinilunga, 4: Solwezi, 5: Zambezi

10 CHIRPS TMPA CMORPH CHIRPS TMPA CMORPH CHIRPS TMPA CMORPH CHIRPS TMPA CMORPH CHIRPS TMPA CMORPH Bias [mm d-1] Sources of SREs errors CHIRPS, TMPA and CMORPH s main error source are miss, false and hit bias, resp. Error sources are season dependent, conforming to Ward et al. (2011). Hit and false bias prevailed for wet and dry periods, resp. 1,50 0,00-1,50 Hit bias Miss bias False bias -3,00 Kaoma Kasempa Mwinilunga Solwezi Zambezi

11 Bias correction algorithms compared 1 st rank 2 nd rank 3 rd rank Evaluation coef./ BC DT TVSV TVSF TFSV TFSF Total P depth Maximum Mean STD Correlation coef. RMSE Error reduction Rain rate patterns Effectiveness vary depending on evaluation indicator. Deterioration on correction (e.g. BF DT: 1.14 vs uncorrected CMORPH: 0.95).

12 TOPMODEL hydrologic evaluation (Gauge) Discharge [m 3 s -1 ] Simulated Observed Calibration (09/ /2012) NS: 0.65 RV E : 10.03% Sep-2009 Mar-2010 Sep-2010 Mar-2011 Sep-2011 Mar-2012 Sep Observed Simulaed Discharge [m 3 s -1 ] Aug-07 Sep-07 Oct-07 Nov-07 Dec-07 Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-08 Sep-08 Oct-08 Nov-08 Validation (09/ /2008) NS: 0.57 RV E : 21.2% Dec-08

13 Gauge observed Uncorrected CHIRPS Corrected CHIRPS Discharge [m 3 s- 1 ] Sep-09 Mar-10 Sep-10 Mar-11 Sep-11 Mar-12 Sep-12 Uncorrected Bias corrected Discharge [m 3 s- 1 ] NS RV E 11.82% 5.81% Gauge observed Corrected TMPA Corrected CHIRPS Corrected CMORPH Sep-09 Mar-10 Sep-10 Mar-11 Sep-11 Mar-12 Sep-12

14 Water balance closure assessment Un-corrected Corrected WB components [mm] In- situ TMPA CHIRPS CMORPH TMPA CHIRPS CMORPH Precipitation Actual ET Simulated Q Root zone storage deficit Catchment Sat. deficit WB Closure Error WB Closure Error, [%] NS [-] RV E [%] o o o SREs over-simulated P, ETa and RZ storage vs in-situ forcing. Bias corrected satellite rainfall result in improved water balance closure. Compared to in-situ, corrected CMORPH resulted in deteriorated WB closure

15 Conclusion and Recommendation Conclusion: o Satellite rainfall detection can be related to seasonal variations in Kabompo. o Bias corrected satellite rainfall resulted in improved water balance closure. o No perfect fit of observed Q could be modelled by respective rainfall forcings. Recommendation: o Incorporate omitted rain gauge stations in CHIRPs blending procedure. o Further investigations a/o validation of rainfall and discharge time series OR increase no. of met. stations in the basin. o Assess how seasonality effects can be incorporated in SREs product s algorithms.

16 References Omondi, C. K. (2017). Assessment of bias corrected satellite rainfall products for streamflow simulation: A TOPMODEL application in the Kabompo River Basin, Zambia. ITC MSc. Thesis. University of Twente Faculty of Geo-Information and Earth Observation (ITC).

17 Thank You Questions?