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of Savinja catchment Ljubljana, 01.12.2016 Email: - - PowerPoint PPT Presentation

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Precipitation & Runoff modeling of Savinja catchment Ljubljana, 01.12.2016 Email: andrej.vidmar@fgg.uni-lj.si 1 The drainage basin hydrological cycle The drainage basin hydrological system Source:

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Precipitation & Runoff modeling

  • f Savinja catchment

Ljubljana, 01.12.2016 Email: andrej.vidmar@fgg.uni-lj.si

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The drainage basin hydrological cycle

Source: http://www.alevelgeography.com/drainage-basin-hydrological-system

The drainage basin hydrological system

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Drainage Basin Flow Chart

Source: http://www.alevelgeography.com

Lakes/ Reservoars

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The basic principle

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Which hydrological model?

  • various ongoing researches are there on topics like which model will give

more compatible results compared to P-R relations

  • HSPF, TOPMODEL, HBV, MIKE-SHE, SWAT,…

HBV-light & PEST

HBV-light: http://www.geo.uzh.ch/en/units/h2k/services/hbv-model/ PEST: http://www.pesthomepage.org/

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HBV - Hydrologiska Byråns Vattenbalansavdelning (Hydrological Agency Water Balance Department)

  • The HBV model (Bergström, 1976, 1992) is a rainfall-runoff model, which includes conceptual

numerical descriptions of hydrological processes at the catchment scale. The general water balance can be described as Where P = precipitation E = evapotranspiration Q = runoff SP = snow pack SM = soil moisture TZ = storage in soil top zone (introduced in HBV-light) UZ = upper groundwater zone storage LZ = lower groundwater zone storage lakes = lake volume

 

lakes LZ UZ TZ SM SP dt d

Q E P

     

 

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Source: http://www.smhi.se/forskning/forskningsomraden/hydrologi/hbv-1.1566

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Semi-distribution

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Subdivides a large problem into smaller, simpler parts with unique characteristic

  • Elevation zones
  • Vegetation zones
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HBV overview

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  • The HBV model is a

simple multi-tank- type model for simulating runoff.

  • Rainfall and air temperature

data as well as estimated potential evaporation data based on the American Society of Civil Engineers Penman–Monteith method are inputs to the model, which consists of four commonly used routines: snow; soil moisture; response; and routing. Picture: Help HBV-light – An Overview of the HBV Model

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Model of Computed Runoff

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Source: Help HBV-light – Three GW Box (Distributed STZ and SUZ) Model

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Equations Overview

Source: Help HBV-light – An Overview of the HBV Model

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Catchment Parameters

Three GW Box (Distributed STZ and SUZ) Model

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Vegetation Zone Parameters

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Source: Help HBV-light – Parameter Overview

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Effect of TT

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Picture: Help HBV-light

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Savinja Catchment

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  • Enclosed Area of 1852.3 sq km
  • min_Elev_m=190.1 m
  • max_Elev_m=2429.0 m
  • avg_Elev_m=604.5 m
  • avg_Aspect=SE (127°)
  • Older_Celje_elev=~238.0 m
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Flood 1954 Savinja-Celje

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Jo Josephinische Landesaufnahme (1 (1763-1787)

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Flood 1990 Savinja-Laško

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Relational Hydro and Meteo Data

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Data source: MOP -ARSO, 2015

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HIGRIS –Hydrologic Graphical IS

  • basically designed with Global Mapper and has more than 130 layers and

a lot of external links

  • GIS (Global Mapper [LiDAR], Map Window, SAGA, ILWIS, Google Earth Pro)
  • CAD (AutoCAD MAP 3D, QuickSurf, Surfer)
  • Graphic design (PhotoLine, PaintShop)
  • DB (ASCII, MS Access, PostGIS)
  • Statistic (MS Excell, Origin, Scilab)
  • Programming (SQL, PowerBasic, Python with NumPy)
  • P-R model (HBV-light_CLI, HBV-light-GUI)
  • Calibration Tools (PEST, GAP and Monte Carlo are included in HBV-light)
  • File navigation and data preview (Total Commander, IrfanView, Acrobat)

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Savinja 21 sub-catchments; I. model

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Savinja 77 sub-catchments; II. model

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Geology [Alluvi-Karst]

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Vegetation zones

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  • 3 vegetation zones
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Elevation zones

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  • 16 elevation zones
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Precipitation RRhour

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  • 33 precipitation stations
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What is PEST?

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BeoPEST is an tool for model calibration

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Model Calibration

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Source: Help HBV-light – Model Calibration

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[PTQ screen]

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Flood Wave Celje 18.-20.09.1007

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Goodnes of f Fit for calibration period - year 2007

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Average model efficiency of Savinja River to Gračnica inflow for whole calibration period 2007 0.952 Average model efficiency for flood wave 18.-22.09.2007 0.988

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Savinja - vp Nazarje

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0.00 100.00 200.00 300.00 400.00 500.00 600.00 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

3+4i vp Savinja - Nazarje

Series1 Series2

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Savinja - vp Letuš 1

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100 200 300 400 500 600 700 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

5 vp Savinja -Letuš I

Series1 Series2

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Savinja – vp Medlog

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100 200 300 400 500 600 700 800 900 1000 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

11 vp Savinja - Medlog

Series1 Series2

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Savinja – vp Celje II _ brv

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200 400 600 800 1000 1200 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

13 vp Savinja - Celje II - brv

Series1 Series2

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Savinja – vp Laško

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200 400 600 800 1000 1200 1400 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

19 vp Savinja - Laško

Series1 Series2

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Dreta – vp Kraše

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0.00 50.00 100.00 150.00 200.00 250.00 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

4 vp Dreta - Kraše

Series1 Series2

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Bolska – vp Dolenja vas

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20 40 60 80 100 120 140 160 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

10 vp Bolska - Dolenja vas

Series1 Series2

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Ložnica – vp Levec I

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20 40 60 80 100 120 140 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

12 vp Ložnica - Levec I

Series1 Series2

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Gračnica – vp Vodiško I

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2 4 6 8 10 12 14 17.09.2007 12:00 18.09.2007 00:00 18.09.2007 12:00 19.09.2007 00:00 19.09.2007 12:00 20.09.2007 00:00 20.09.2007 12:00

20 vp Gračnica - Vodiško I

Series1 Series2

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Goodnes of f Fit for validation period - year 1990

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WS2 WS2_Name NS (1.10-14.11.1990) 1 Savinja do VP Solčava I 0.85 8 Dreta do VP Kraše 0.90 38 Ložnica do VP Levec I 0.94 45 Savinja do VP Celje II - brv 0.97 53 Hudinja do VP Škofja Vas 0.8 62 Voglajna do VP Celje II 0.8 67 Savinja do VP Laško 0.97 76 Savinja do VP Veliko Širje I 0.84

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Flood Wave vp Laško 26.10.-05.11.1990

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Savinja – vp Celje II _ brv

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200 400 600 800 1000 1200 1400 26.10.1990 00:00:00 28.10.1990 00:00:00 30.10.1990 00:00:00 01.11.1990 00:00:00 03.11.1990 00:00:00 05.11.1990 00:00:00 07.11.1990 00:00:00 09.11.1990 00:00:00 11.11.1990 00:00:00

Savinja-Celje II - brv

Series2 Series3

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Savinja – vp Laško

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200 400 600 800 1000 1200 1400 1600 26.10.1990 00:00:00 28.10.1990 00:00:00 30.10.1990 00:00:00 01.11.1990 00:00:00 03.11.1990 00:00:00 05.11.1990 00:00:00 07.11.1990 00:00:00 09.11.1990 00:00:00 11.11.1990 00:00:00

Savinja-Laško I

Series1 Series2

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Ložnica – vp Levec I

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10 20 30 40 50 60 70 80 90 26.10.1990 00:00 28.10.1990 00:00 30.10.1990 00:00 1.11.1990 00:00 3.11.1990 00:00 5.11.1990 00:00 7.11.1990 00:00 9.11.1990 00:00 11.11.1990 00:00

Ložnica-Levec I

Series1 Series2

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Dreta – vp Kraše

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50 100 150 200 250 300 26.10.1990 00:00:00 28.10.1990 00:00:00 30.10.1990 00:00:00 01.11.1990 00:00:00 03.11.1990 00:00:00 05.11.1990 00:00:00 07.11.1990 00:00:00 09.11.1990 00:00:00 11.11.1990 00:00:00

Dreta-Kraše

Series1 Series2

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Voglajna – vp Celje II

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10 20 30 40 50 60 70 26.10.1990 00:00 28.10.1990 00:00 30.10.1990 00:00 1.11.1990 00:00 3.11.1990 00:00 5.11.1990 00:00 7.11.1990 00:00 9.11.1990 00:00 11.11.1990 00:00

Voglajna-Celje II

Series1 Series2

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  • 1. Why use a P-R modeling?
  • for education
  • for decision support
  • for data quality control
  • for water balance studies
  • for drought runoff forecasting (irrigation)
  • for fire risk warning
  • for runoff forecasting/prediction (flood warning and reservoir
  • peration)
  • for what happens if’ questions

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  • 2. Why use a P-R modeling?
  • to compute design floods for flood risk detection
  • to extend runoff data series (or filling gaps)
  • to compute design floods for dam safety
  • to compute energy production
  • to investigate the effects of land-use changes within the catchment
  • to simulate discharge from ungauged catchments
  • to simulate climate change effects

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Designed Flood Predictions

  • based on flood event 2007 (50 year return period)

24 hour Precipitation Event for Q10, Q20, Q50, Q100, Q200 and Q500

  • based on flood event 1990 and 1998 (100 year return period)

48 hour Precipitation Event for Q10, Q20, Q50, Q100, Q200 and Q500

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