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Paprika’s hydrological stations

Paprika’s hydrological stations. More Paprika’s hydrology. Two small slope basins could be studied in a detailed hydrological field approach. PhD project submitted for funding (feb. 2011) at UM2 CoP. Pangboche 4000-6500m. Kharikola 1600-4000m. Spatialized climate data sets.

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Paprika’s hydrological stations

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  1. Paprika’s hydrological stations

  2. More Paprika’s hydrology

  3. Two smallslope basins could be studied in a detailedhydrologicalfield approach. PhD project submitted for funding (feb. 2011) at UM2 CoP Pangboche4000-6500m Kharikola1600-4000m

  4. Spatialized climate data sets

  5. Available climate datasets précipitation (*) bilinear interpolation

  6. Comparison of seasonal (monthly) precipitation CRU versus Aphrodite on 1952-2006 period over Koshi basin

  7. Spatial comparison of monthly precipitation CRU versus Aphrodite on 1952-2006 period over Koshi basin (resol = 0.25°) monthly bias (CRU-Aphro) monthly correlation between CRU and Aphro (636 values for each cell) Bias: higher CRU values over Tibet plateau (~1000 mm/year) better agreement in the southern basin Correlation: good correlation CRU-Aphrodite on southern part of the basin

  8. Spatial comparison of monthly precipitation TRMM versus Aphrodite on 2000-2007 period over Koshi basin (resol = 0.25°) monthly bias (Aphro-TRMM) monthly correlation between TRMM and Aphro (120 values for each cell) Bias: higher TRMM values over Tibet plateau and in south of Nepal (up to 350 mm/year)  probably reflect a bad aphrodite precipitation interpolation (lack of gages) over Tibet plateau higher Aphrodite values along the montains (up to 1000 mm/year)  TRMM :only rain , Aprhodite : rain+ snow better agreement over a small area in the southern basin Correlation: low correlation TRMM-Aphrodite on north-west part of the basin

  9. DHM’s hydrological balance

  10. Comparison of annual/monthly discharge and precipitation - 5 sub catchments of Koshi river at Chatara (93% of Koshi catchment area at Chatara) - 600.1 : Awa Gaon 29 700 km² 606 : Simle 33 500 km² 690 : Mulghat 5 880 km² 652 : Khurkot 10 200 km² 670 : Rabuwabazar 3 720 km² 695 : Chatara 57 300 km² Awa Gaon Rabuwabazar Khurkot Simle Mulghat Chatara • Aims : • Analysing the reliability of discharge measurements • Basic anlayses of the catchment hydrology • Data : • Discharge : DHM data base • Precipitation : spatial mean precipitation calculated for each catchment with aphrodite data

  11. The main problems : 1. For all the catchment the runoff coefficients C (annual and seasonal time steps) happen to be higher than one All catchments All seasons C >>1 in 2005 Exemple of the Dud Koshi catchment at the annual scale :

  12. 2. This pattern can not be explain by snow or ice melting as it is • observed in all season an mainly in Winter and October-November • it does not exhibit a seasonal cycle Exemple of Dud Koshi winter (=DJF) runoff coefficient • May be it can be explain • by the uncertainty of low flows measurement ? • by the catchment precipitation estimations (Aphrodite)

  13. Inconsistency for Arun river : • Decreasing discharges at Awa Gaon and Simle • No decreasing trend observed for the precipitation Arun – Awa Gaon – 29700 km² Decreasing trend in annual discharge No significant trend for annual precipitation (green curves) Arun – Simle – 33500 km² Break in the annual discharge time serie (near 1996-1997)

  14. 4. Inconsistency in the sub catchments contributions to the total Koshi catchment discharge • We have computed the ratio Qsubcatchment/Qkoshi (annual and seasonal scale) •  The sum of the 5 ratio is greater than one ! Annual contribution of the 5 subcatchments to the Koshi annual discharge (black curve) • This pattern also appears at the seasonal scale • not systematicaly the same year than for annual discharges • the years with runoff coefficient and contribution inconsistencies are not simultaneous !

  15. Comparison of monthly temperature, discharge and precipitation (standardized values)  Show consistent pattern : maximum discharge, temperature and precipitation simultanously happen during summer (Monsoon)

  16. Data bases

  17. HYDRACCESS • DHM hydro & climato • EvK2 climato • Paprika hydro &climato Contact : Pierre Chevallier

  18. Spatial infos • Aphrodite • CRU • TRMM • NCEP • Etc. Contacts: François Delclaux Luc Neppel

  19. ArcGis Projection WGS 84UTM 45N (Nepal) UTM 43N (Pakistan) DEM Snow Cover Hydrology Etc. Contacts: Pierre Chevallier

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