6559800 Spatial Hydrology

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SPATIAL HYDROLOGY

Bahram Saghafian

Presented at:

Civil Engineering Department

Sharif Technical University

Jan. 2002


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What is Spatial Hydrology?

Study of the motion of the earths

waters (and the transport of their

constituents) with the explicitreference to the spatial dimension and

using the data structure and functions

of geographic information systems


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Major Developments

Increasing availability of spatial hydrologic data(DEM, Images, etc.)

Inclination towards the use of spatial data bases

and GIS functions in hydrology Need to study detailed spatial distribution of

hydrologic processes and their effects

Development of distributed hydrologic models

Need to disaggregate synthesized hydrologicresponses (flood hydrograph, sediment load, etc.)

Progress in high-powered computing equipments


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Active Areas in SpatialSurface Hydrology

Effect of land use changes Floodplain mapping and hazard

Flood potential and risk mapping within watersheds

Spatial optimization of flood control countermeasures

Site selection for hydro-climatological stations Distributed watershed erosion mapping

Pollutant affected areas

Distributed runoff/snowmelt/sediment modeling

Spatial correlation of climatological factors with geo-environmental characteristics

Distributed modeling of hydro-climatologic and geo-morphologic characteristics


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Geographic Information System

Software tool for storing, managing,manipulating spatial (geographic) data

Has four components: data entry, datamanagement, manipulation and analysis,and data output

Models geographic features using points,

lines, and cells in either vector or cellulardata models


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GIS Relation to SpatialHydrology

Spatial hydrology deals with spatially

distributed processes and features

GIS can handle spatial (geographic) data Conjunctive use of GIS and hydrology is

natural and unavoidable


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Distributed Rainfall-RunoffModeling of Golabdareh

Catchment


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Distinctive Algorithms and Tools

Upgrade time-area rainfall-runoff

transformation into a distributed technique

Determine travel time based on kinematicwave theory

Introduce, for the first time, temporally-

variable isochrone hydrograph estimationmethod


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Digitally extracted drainage network


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50-yr Flood Hydrograph

50-Year Hydrograph Convolution

0

4

8

12

16

20

24

28

32

36

40

1 4 710

13

16

19

22

25

28

31

34

37

40

43

46

49

52

55

58

61

64

67

70

73

76

Time-(min)

Discharge-(m^3/s)

Q1 (m3/s)

Q2(m3/s)

Q3 (m3/s)

Q4 (m3/s)

Q5(m3/s)

Q6(m3/s)

QTotal(m3/s)


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Effect of Land Use Changes inNekarood River Basin

Land use change detection using remotely-sensed data

Hydrologic simulation of floods

Prediction of future effects based of landuse change scenarios

Further application: How to manage

spatially the timber harvesting and otherland activities


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View of Nekarood River Basin


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View of Nekarood River Basin


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Digital Elevation Model (DEM)


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Land Use Map, Year 1346


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Land Use map, Year 1372


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Land Use Map, Year 1379


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Land Use Change Over Years

FOREST(POOR) :F(P) FOREST(MEDUM) :F(M)

FOREST(DENSE) :F(D) AGRICULTURE :A

RANGE LAND(POOR) :R(P) RANGE LAND(NORMAL) :R(N)

RESIDENTAL :RES.

0

100

200

300

400500

600

700

800

900

F(P) F(M) F(D) A R(P) R(N) RES.

Land Use

Area

1346 1372 1379

FOREST(POOR) :F(P) FOREST(MEDUM) :F(M)

FOREST(DENSE) :F(D) AGRICULTURE :A

RANGE LAND(POOR) :R(P) RANGE LAND(NORMAL) :R(N)

RESIDENTAL :RES.

0

100

200

300

400500

600

700

800

900

F(P) F(M) F(D) A R(P) R(N) RES.

Land Use

Area

1346 1372 1379


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Change in peak floods

100

105

110

115

120

125

20 50 100 500 1000

RETURN PERIOD (Yr)

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Q/Qbase

100

105

110

115

120

125

20 50 100 500 1000

RETURN PERIOD (Yr)

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Q/Qbase


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Sediment Deposition SpatialPattern

Minab Dam

0 4 0 00

100


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Spatial correlation betweenrainfall and vegetation

Daily rainfall maps using geostatistical tools

Terrain mapping units defined

NOAA satellite images processed for NDVI

vegetation index

Spatial correlation of rainfall and NDVI studied

on 10-day and monthly basis with different lagtimes


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Terrain mapping Units


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Sample daily rainfall map


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Results

Monthly NDVI vegetation index followmonthly rainfall data with a lag of one totwo months and are best correlated with

the bimonthly antecedent rainfall. The multiple regression method is best

suited compared with others methods.

Results may be used for rainfall spatialvariation and drought mapping.


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Drought SDF Mapping

Drought Severity-Duration-Frequency

analysis using run theory

Spatial extent of drought severity

l d i l i i i i


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Flood Potential Prioritization

and Spatial Mapping Set up a selected semi-distributed hydrologicmodel for the watershed

Identify and rank the areas (sub-watersheds)

based on their quantitative contribution indischarge characteristics at the outlet

Determine the impact of sub-watershed factorson the outlet flood peak

Propose priority flood control measures Ongoing: conduct research on observed

discharge data and/or use a fully distributedmodel


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Snow Mapping & Snowmelt

Runoff Simulation

Use satellite images for continuous mapping

Propose an algorithm for snow/cloud/grounddelineation

Simulate snowmelt and rainfall runoff using

SRM model and processed images


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6559800 Spatial Hydrology