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Semi Distributed Conceptual Hydrological Model of Savinja Catchment ( Review of the Hydrological Modeling, HBV-light and Results) Modelling flood events.

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Presentation on theme: "Semi Distributed Conceptual Hydrological Model of Savinja Catchment ( Review of the Hydrological Modeling, HBV-light and Results) Modelling flood events."— Presentation transcript:

1 Semi Distributed Conceptual Hydrological Model of Savinja Catchment ( Review of the Hydrological Modeling, HBV-light and Results) Modelling flood events – application of adequate models and methods for determination of flood risk and flood hazard March 16th, 2016 mag. Andrej Vidmar, UL FGG Email: andrej.vidmar@fgg.uni-lj.si 1

2 Review of some Topics - Contents 1.Hydrological system! What hydrological model? 2.HBV-light & PEST 3.What variables do we consider? 4.The equations for modeling P-R 5.Methods of calibration 6.Computation time –beoPEST parallel processing 7.HIGRIS - Hydrological Graphical Information System (CAD & GIS,DB...) 8.Conceptual settings, distribution of model 9.Analysis of different scenarios 10.Model simulations – varying MAXBAS parameter 2

3 The drainage basin hydrological cycle Source: http://www.alevelgeography.com/drainage-basin-hydrological-system The drainage basin hydrological system 3

4 Drainage Basin Flow Chart Source: http://www.alevelgeography.com Lakes/ Reservoars 4

5 Terms Drainage Basin: area of land drained by a river and its tributaries Watershed: boundary between two river systems on high relief land Precipitation: deposition of moisture from the atmosphere to the surface. Can be: snow, rain, sleet, snow, hail, frost, fog... Evapo-transpiration: release of water vapour from the earths surface in the form of evaporation and transpiration. Interception: retaining of water by plant leaves, stems and branches. Water is stopped from reaching the soil directly. Stem-flow/leaf drip: water that travels through the stem of a plant. Surface run-off/overland flow: the flow of water over the surface of the ground. Infiltration: water that soaks down into the soil. Soil moisture storage: moisture held stationary in the soil. Through-flow: the movement diagonally downward of water through the soil. Percolation: the filtering of water donwards vertically through the joints and pores of permeable rock. Through-fall: droplets of rain dripping straight off leaves and onto the ground. Groundwater flow: water that flows horizontally underground through rock. Soil saturation: when the soil contains a lot of water. Field capacity: the volume of water which is the maximum the soil can hold. Infiltration rate: the rate at which water infiltrates into the soil. Water-table: the level below which the ground is saturated. 5

6 The water balance Precipitation = Runoff + Evapotranspiration +/- change in Storage Dynamic Equilibrium: refers to balanced state of a system when opposing forces are equal. If one element in the system changes then the system changes to reach equilibrium again. 6

7 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 7

8 HBVHBV - 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 LZ = lower groundwater zone lakes = lake volume 8

9 HBV-96 In different model versions HBV has been applied in more than 40 countries all over the world. It has been applied to countries with such different climatic conditions as for example Sweden, Zimbabwe, India and Colombia. The model has been applied for scales ranging from lysimeter plots (Lindström and Rodhe, 1992) to the entire Baltic Sea drainage basin (Bergström and Carlson, 1994; Graham, 1999). HBV can be used as a semi-distributed model by dividing the catchment into subbasins. Each subbasin is then divided into zones according to altitude, lake area and vegetation. The model is normally run on daily values of rainfall and air temperature, and daily or monthly estimates of potential evaporation. The model is used for flood forecasting in the Nordic countries, and many other purposes, such as spillway design floods simulation (Bergström et al., 1992), water resources evaluation (for example Jutman, 1992, Brandt et al., 1994), nutrient load estimates (Arheimer, 1998). 9

10 IHMS [Integrated Hydrological Model System] 10

11 HBV Light Model HBV Light corresponds in principle to the version described by Bergström (1992 and 1995) with only slight changes. The newest version of HBV light was reprogrammed in collaboration with M. Vis (2010) to migrate the software from the programming language VB6 to VB.NET (Seibert und Vis, 2012). The new HBV Light version includes the following innovations: Possibility to run the model for a catchment consisting of several subcatchments Improved user interface (GUI, CLI) Introduction to hydrological modelling and the HBV model ( Jan Seibert) 11

12 HBV-light GUI Current version: 4.0.0.10 12

13 HBV-light CLI 13

14 HBV-light [PTQ screen] 14

15 HBV-light [Soil+E+Q screen] 15

16 HBV-light [GW+Q screen] 16

17 Classification of HBV-light model Empirical _ Conceptual _ Physical Linear _ Non-linear Lumped _ Distributed _ Semi-distributed Deterministic _ Stochastic Static _ Dynamic Time-variant _ Time-invariant Event based _ Continuous Complete _ Partial Simple _ Complex General _ Special purpose 17

18 HBV Light Model [semi-distributed] a semi-distributed hydrologic model to simulate catchment runoff 18

19 Modeling Terms Mathematical model - a set of concepts in the form of mathematical equations representing the understanding of natural phenomena. Verification model - study of numerical techniques in computer code to check whether the conceptual model is truly representative and that there are no typical numerical problems obtaining solutions. Calibration model - the test model with a known input and output data, which is used to adjust the parameters for which data is available. Confirmation (Validation) model - independent comparison of model results with the figures derived from experimental or observational environment. 19

20 METHOD OF MODELING Phase 1 - PREPARATION data collecting preparation of input data valuation parameters Phase 2 - TESTING model calibration proof of concepts post-audit Phase 3 - ANALYSIS analysis of alternatives - forecast 20

21 POSTOPEK MODELIRANJA Faza 1 - PRIPRAVA zbiranje podatkov priprava vhodnih podatkov vrednotenje parametrov Faza 2 - TESTIRANJE umerjanje modela potrditev modela post-revizija Faza 3 - ANALIZA analiza alternativ – napovedi 21

22 1. Why use a P-R model like HBV-light ? 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 operation) for what happens if’ questions 22

23 2. Why use a P-R model like HBV-light? to extend runoff data series (or filling gaps) to compute design floods for dam safety to compute energy production to investigate the effects of changes within the catchment to simulate discharge from ungauged catchments to simulate climate change effects 23

24 Osnovno načelo 24

25 Input - Output 25

26 Distribution 26

27 HBV overview 27 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.

28 Input data Areal precipitation Weighted mean Elevation zones (lapse rate ~10% per 100 m) Temperature Weighted mean Elevation zones (lapse rate 0.6 °C per 100 m) Potential evaporation Penman formula or measurements Usually long-term monthly mean values 28

29 Input data (cont.) 29 Correction of long-term potential evaporation

30 Model structure 30

31 Snow routine 31

32 Snow routine (cont.) 32

33 Effect of T T 33

34 Effect of C FMAX 34

35 Soil routine 35

36 Soil routine (cont.) 36

37 Effect of FC 37

38 Effect of ß 38

39 Response function 39 Simulates runoff by summing up three linear outflow equations representing peak, intermediate and base flow.

40 Response function (cont2.) 40

41 Response function (cont3.) 41

42 Response Routine With Delay Model 42

43 Equations Overview 43

44 Effect of K 0 44

45 Effect of U ZL 45

46 Effect of K 1 46

47 Effect of P ERC 47

48 Effect of K 2 48

49 Routing routine 49 The routing routine delivers simulated runoff to the catchment outlet based on a triangular weighting function.

50 Effect of MAXBAS 50

51 Catchment Parameters 51

52 Vegetation Zone Parameters 52

53 Model Calibration 53

54 Goodness of Fit functions 54

55 Goodness of Fit functions (cont.) 55

56 Design flood calculations with HBV model 56

57 PEST 57

58 What is PEST? 58

59 Some PEST specifications (cont.1) 59

60 Some PEST specifications (cont.2) 60

61 Some PEST specifications (cont.3) 61

62 Some PEST specifications (cont.4) 62

63 Some PEST specifications (cont.5) 63

64 PEST – The Book 64

65 PEST control file PSTPST pcf * control data restartestimation 1937441901 11doublepoint100 20-30.30.01100 330.0001 0.1 500.005440.0054 111 * singular value decomposition 1 195E-12 0 … ADDENDUM 65

66 beoPEST is an ideal tool for model calibration 66

67 PEST Batch RunBatch Run @Echo Off REM By Andy's Soft 2013-2015 for HBV-Light Calibration with BeoPEST REM Set variables used in script SET nproc=7 REM SET host=localhost REM SET host=193.2.92.156 REM SET host=192.168.178.25 REM SET host=141.255.208.24 SET host=ThinkPadT430 SET port=4004 SET pst_file=%1 … 67

68 Uncalibrated Model 68

69 Calibrated Calibrated Model with PEST 69

70 The development of the hydrological model for the Bosna River Razvoj hidrološkega modela porečja reke Bosne za simulacijo poplavnega dogodka maja 2014 v Bosni in Hercegovini The development of the hydrological model for the Bosna River basin to simulate the flood event in May 2014 in Bosnia and Herzegovina Mira Kobold 1,2, Andrej Vidmar 2, Lidija Globevnik 2, Mitja Brilly 2 1 Agencija Republike Slovenije za okolje, Vojkova 1b, 1000 Ljubljana, Slovenija, mira.kobold@gov.si 2 Univerza v Ljubljani, Fakulteta za gradbeništvo in geodezijo, Jamova 2, 1000 Ljubljana, Slovenija 70

71 Bosna River Basin 71

72 Bosna Catchment P-R 72

73 Bosna Elevation zones 73

74 Abstract In mid-May 2014, as a result of high precipitation which is only in three days exceeded the three-month average, part of Bosnia and Herzegovina, Serbia and Croatia captured one of the largest floods along the Sava River and its tributaries. The floods caused loss of human lives and animals, environmental degradation and billions of euros of damage. The flood was estimated as a phenomenon with a hundred, in some places a thousand-year return period. The event caused a major international campaign to help those affected by the floods. Slovenia responded extensively, including the analysis of a flood event of the Bosna river basin. The HBV-light hydrological tool was used for the development of hydrological model for the Bosna river basin. The results of simulation show that the peak discharge of the Bosna River in Maglaj exceeded the return period of 500 years, in other parts even 1000 years. The hydrological model of the Bosna river basin sufficiently and successfully simulates the flood event of May 2014 and provides the basis for further development. The model is already being used for forecasting of flood discharges of the Bosna River in the future. Hydrological model for the Bosna river basin establishes an important transfer of Slovenian knowledge and experience in the field of flood forecasting in BiH. 74

75 Historical Overview of Regulation of Savinja 75

76 Savinja river catchment 76

77 Flood 1954 Savinja-Celje 77

78 2004 Savinja-Celje 78

79 Flood 1990 Savinja-Mozirje (Elkroj) 79

80 Flood 1990 Savinja-Laško 80

81 Hydraulic-hydrological study CELOVITA HIDROLOŠKO HIDRAVLIČNA ŠTUDIJA ZA UTEMELJITEV UKREPOV POPLAVNE VARNOSTI NA POREČJU SAVINJE (Hydraulic hydrological study for argumentation the flood protection measures in the river basin of Savinja) vodilni partner FGG partnerji DHD,Hidrotehnik Naročnik:Ministrstvo za okolje in prostor Dunajska 47 1000 Ljubljana 81

82 Construction of hydrological basics 82

83 Construction of hydrological basics (cont.) 83

84 Objectives and results of studies Cilji celovite hidrološko hidravlične analize in izračunov hidravličnih modelov je preveriti in potrditi: da ima s hidrološko-hidravličnega stališča zadrževanje voda z izvedbo ukrepov poplavne varnosti na pritokih Savinje in Gornji Savinji le lokalni vpliv, da pa je za celovit sistem zagotavljanja poplavne varnosti v porečju Savinje ključna izvedba ukrepov poplavne varnosti na odseku Spodnje Savinjske doline; da bo zagotovljena celovitost reševanja poplavne varnosti v celotnem porečju Savinje, da predvideni ukrepi pri različnih hidroloških stanjih ne povečujejo nevarnosti poplav v dolvodnih profilih Savinje, do vključno profila vtoka v Savo. 84

85 HIGRISHIGRIS –Hydrologic Graphical IS HIGRIS - Hidrološki grafični informacijski sistem 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 included in HBV-light) 85

86 GIS layers More than 100 layers on the topics: 00 DOF\ Orthofoto01 Meje\ Borders 02 Karte\ Maps03 Topografija\ Topography (LiDAR) 04 Hidrografija\ Hydrography05 Meteorologija\ Meteorology 06 Pokrovnost\ Land Cover07 Hidrometrija\ Hydrometry 08 Geologija\ Geology09 Geoanaliza\ Geo-analyses 10 Protipoplavni ukrepi\ Flood Measures11 Hidravlicni modeli\ HydralicMod 12 Hidrotehnicni objekti\ Hydrotechnical13 Hidrogeologija\ Groundwater 86

87 HIGRIS 87

88 GoogleEarthGoogleEarth Visualization 88

89 Relational Hydro and Meteo Data 89 Data source: MOP -ARSO, 2015

90 Geology[Alluvial-Karstic] 90

91 Vegetations zones 91

92 Elevation zones 92

93 Precipitation RR hour 93

94 Goodnes of Fit 94 Savinja P-R Model 1-Savinja1-Luče 2-Lučnica-Luče 3-Savinja2-Nazarje 4-Dreta-Kraše 5-Savinja3-Letuš 6-Paka1-Velenje 7-Velunja-Gaberke 8-Paka2-Šoštanj 9-Paka3-Rečica 10-Bolska-Dolenja_vas 11-Savinja4-Medlog 12-Ložnica-Levec 13-Savinja5-Celje_brv 14-Hudinja1-Polže 15-Hudinja2-Škofja_vas 16-Voglajna1-Črnolica 17-Voglajna2-Celje 18-Hudinja3-Zagrad 19-Savinja6-Laško 20-Gračnica-Vodiško 21-Savinja7-Veliko Širje Eff Water Balance [mm/year]: >9perfect Sum Qsim1894440429134080314424511424218317052661252122702487209220021214893144820994952002 >8.5 Sum Qobs209534922810446031921510155016541704263822802535235415211749819127621286971490 >7.5 Sum Precipitation517355844858567643083616299746043702497343964287349040054233216026633490283920602416 <7.5 Sum AET472641313834399833593064248333233070371234372195301845023605146625011928231624672678 <0.4not good Sum PET820684329464922992879065933284799156932188939140879590759181877588388795908790069062 Contribution of QSTZ0.00 0.010.020.00 0.010.000.010.630.380.00 0.260.050.000.05 Contribution of QSUZ0.320.250.170.330.270.340.190.320.260.480.310.130.290.000.230.300.110.190.270.050.27 Contribution of QSLZ0.680.750.830.660.710.660.810.680.740.520.680.870.700.370.390.700.890.540.670.950.68 Goodness of fit: Coefficient of determination0.800.960.99 0.950.910.800.570.970.990.98 0.920.950.940.950.980.810.93 Model efficiency Nash–Sutcliffe 0.730.930.970.99 0.850.880.770.380.970.990.980.970.400.870.92 0.980.690.75 Efficiency for log(Q)0.880.360.83-0.350.780.160.810.180.530.820.94-23.970.960.56-0.220.690.770.94-1.340.87 Flow weighted efficiency0.680.930.981.00 0.970.930.820.250.981.000.990.980.180.880.930.920.990.650.74 Efficiency for specified season-0.390.530.960.99 0.960.870.71-2.290.960.980.970.96-1.090.840.90 0.990.820.61 Volume Error0.980.910.960.910.990.580.920.681.000.990.890.900.940.780.920.910.970.990.710.86 MARE Measure0.890.530.720.480.69-0.060.64-0.620.260.460.740.240.810.590.43-0.020.670.740.350.68 Lindstrom Measure0.730.920.970.980.990.810.880.730.380.970.980.970.960.380.860.910.920.980.660.73 Spearman Rank0.980.990.980.950.980.920.950.880.790.98 0.850.990.960.930.790.910.980.910.94

95 SubCatchments Q-h 95

96 Flood Predictions based on flood event 2007 (50 year return period) 24 hour 24 hour Precipitation Event for Q10, Q20, Q50, Q100, Q200 and Q500 based on flood event 1998 (100 year return period) 48 hour 48 hour Precipitation Event for Q10, Q20, Q50, Q100, Q200 and Q500 96


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