gis application for hilly watershed

8/12/2019 GIS Application for Hilly Watershed

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Remote Sensing and GISApplications for Hilly Watersheds

SUB SHIS DUTT

DEP RTMENT OF CIVIL ENGINEERING

IIT GUW H TI


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Deciding Alternative Land Use Options in a Watershed Using GIS

2

Source: Anita Prakash et al, 2007


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High Resolution of IRS-P6 Imagery

VIENN

3Source: NRSC website


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High Resolution of CARTOSAT-2 Imagery

4Part of Varanasi, Uttar Pradesh, India Source: NRSC website


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extreme rainfall events

GIS as a tool for watershed management

Analysis of digital elevation model ( terrain

data

Case studies and discussion

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The Hydrologic Cycle at hillslope

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Physical Processes Involved in Runoff Generation


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Critical Hydrologic Processes

Infiltration

Overland Flow

u sur ace orm ow

Soil Macropores and Water Flow

Consequences :

Flash Floodin

Slope Failures and Slides

Soil Erosion

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Debris Flow

Groundwater Pollution


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Hillslope Experimental Plot

-

longitude

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opograp y Average slope 20%, COV 10.49%Microtopographic variation not significant


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Hillslope Experimental Setup

UPSTREAM CHANNELPROFILE

PROBE

Upper Channel

SIDEPLATES

VENTURIMETER

VALVE 18 m

Side Plate

DOWNSTREAMCHANNEL

FLOW

PUMP

PUMP

PONDMEASURING

TANKOUTLE

T

Lower Channel

6 m

Extreme Storm Intensity about 50 - 400

9Storm Durations 15 -120 minutes


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Overland Flow - Results

6

3

4

5

ntration,tc

(min) Sparse

Moderate

Dense

1

2

Timeof

Conc

Outflow hydrographFig. 5 0 100 200 300 400 500

Equivalent Rainfall Intens ity, i (mm/hr)Fig. 6

Relationship betweentc and i300

Similar response in sparse andmoderrate vegetation

Similar macropore network150

200

250

Rate,fb(

mm/hr)

parse

Moderate

Dense

Distinct changes in behavior indense vegetation

Significant change in macropore0

50

100

Infiltratio

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connectivity and network0 100 200 300 400 500Equivalent Rainfall Intensity, i (mm/hr)Fig. 7

Relationship betweenfb and i


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Temporal dynamics of subsurface storm flow

= m nAt t=18min.

At t=51min.At t=29 min.

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Temporal dynamics of subsurface storm flow ( Continued)

At t=66min. At t=85 min. At t=99 min.

r t ca servat ons :

1. Fast subsurface stormflow ( within 1-2 hours of the storm event)

2. Initiation of subsurface storm flow occurs for even a storm event of50 mm/hr

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. empora y perc e wa er- a e orma on on e e -roc


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Saturation in zones of convergent

to o ra h


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H drolo ical effect of land use/land cover chan e

Change in top soil macroporosity, more likely to have overland flow

generation

Blocking of subsurface stormflow path, more concentrated flowgeneration, leading high sheet erosion

e ng a res o ow mec an sm, s con ro e y ra n a n ens y,

vegetation condition, soil layers

Wetness index, based on DEM, predicts the subsurface storm flow

Identi ficat ion of Hotspots in a hil ly watershed, related to f lash floods

and soil erosion, sediment transport capacity and natural sediment

trapper

Land use/land cover planning to be carried out by integrating hydrological knowledge on geospatial database

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Why GIS?

an an e geograp ca y re erence a a or

spatial data as well as non-spatial data

Can handle relational numerical expressionsbetween these data sets

Ideal for natural resource management

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as c unc ons o

Capturing data

Storing data

Manipulating data

Analyzing data

sp ay ng a a

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Data Types

Spatial Data Non-spatial Data

Topography

Land Use Land Cover

Descriptive Attributes

Soil

Water bodies

Land Use Type

Vil lage Name, ,

Villages

Forests

Street Name

Geology

Road Network

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Representation of Spatial Data

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Spatial Data Models

Vector Data Model Raster Data Model

Based on geometry of Digital Representation

Pointas r e s

Satellite Images Line

Aerial Photographs

o ygon Digital ElevationModels (DEM)

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Vector and Raster Data Model

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Vector Data Model

Arc-Node data structure as c grap ca eaturesPoint

Line

Polygon

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Arc-Node Data Structure

Polygon Arc ListPolygon Arc ListPolygonPolygon Arc ListArc ListA r cN u m b e r

Star t

n o d e

V ertice s E n d

n o d e

A r c

N u m b e r

Star t

n o d e

V ertice s E n d

n o d e

A r c

N u m b e r

A r c

N u m b e r

Star t

n o d e

Star t

n o d e

Ver t ice sV ertice s E n d

n o d e

E n d

n o d e

Nodes & VerticesArc-node structure Polygon structure

A 1,2A 1,2AA 1,21,21 2 0 d ,c ,b .a 10

2 1 0 e 20

1 2 0 d ,c ,b .a 10

2 1 0 e 20

11 2 02 0 d ,c ,b .ad ,c ,b .a 1010

22 1 01 0 ee 2020

27

,,,,

3 1 0 f,g ,h ,i ,j 203 1 0 f,g ,h ,i ,j 2033 1 01 0 f,g ,h ,i ,jf,g ,h ,i ,j 2020


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Topology : Defining Spatial Relationships

Three major topological concepts:

Connectivity:Arcs connect to each other at

nodes.

Area definition:Arcs that connect to surroundan area e ne a po ygon

Contiguity:Arcs have direction and left and

r g s es

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Connectivity

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Area Definition

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Contiguity : Adjacency

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Vector Data Model

Points: represent discrete point features

each point location

has a record in the

table

airports are point features

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eac po n s s ore as a

coordinate pair


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Vector Data Model

Lines: represent linear features

each road segmenthas a record in the

table

33roads are linear features


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Vector Data Model

Polygons: represent bounded areas

each bounded polygonhas a record in the

table

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Multiple Layers of Vector Data

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Data Structures

(map) data structures, but

what of GIS is determined by tabular

relational database data structures

GIS Database= Coordinate data +Attribute Data

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Attribute Data Structures

Attribute data are stored in database tables.

Tables are composed of:

e s

Records

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f


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Use of Tabular Data

Making queries

Displaying selected sets

Modifying selected sets

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M ki Q i


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Making Queries

Selecting records from tables/features

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Di l i S l t d S t


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Displaying Selected Sets

Selecting records from tables also select features

from themes

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A l i T l f GIS


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Analysis Tools of GIS

BUFFER ANALYSIS

OVERLAY ANALYSIS

NETWORK ANALYSIS

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B ff i


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Buffering

Quantifying a spatial entity to influence its neighbours

Spatial entity

Point

Line

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POINT BUFFER

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LINE BUFFER


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LINE BUFFER

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Overlay Analysis


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Overlay Analysis

Point over Polygon

45Line over Polygon

Overlay Operators


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Overlay Operators

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Anal sis of DEM for extraction of Watershed

parameters

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Digital Elevation Models


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Digital Elevation Models

Remotely Sensed Satellite Images

Digital Elevation Models (DEM)

Raster Data

Structure

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DEM Data from Contours


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DEM Data from Contours

720 720

740

720

700

680

49

680700720740

DEM Elevations


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DEM Elevations

Contours

700

680

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A Simple Digital Elevation Model

67 56 49 46 50

cell size

53 44 37 38 48

5058 55 22 31 24

61 47 21 16 19

12 11 123453 cell

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DEM Data Sources


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DEM Data Sources

1 km DEM of the earth (GTOPO)

100 m DEM from 1:250,000 scale maps

30 m DEM from 1:24,000 scale ma

90 m Shuttle Radar To o ra h Mission SRTM

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Eight Direction Pour Point Model

32 64 128

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Flow Direction Grid

2 2 4 4 8

1 2 4 8 4

128 1 2 4 8

2 1 4 4 4

1 2 1611

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30 Meter DEM


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30 Meter DEM

eva ons n me ersftp://ftp.tnris.state.tx.us/tnris/demA.html

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Flow Direction Grid


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32 64 128

16

8 4

1

2

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ow etwor

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Flow Accumulation Grid

0 0 000 0 0 00 0

0

0

03 2 2 0 03 2 2

00

0

0

11 1

115

0 0 01 15

0 2 5 24 1 0 12 245

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ow ccumu at on > e res o

0 0 0 0

ream nes

0 03 2 2

0 0 011 1

0

0

0 01

12

15

245

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ream e wor or ce res oDrainage Area

0 0 000

0 03 2 2

0 0

11

1

0 15

2 5

6124


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Watershed Outlet

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Watershed Draining to the Outlet


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SRTM Data Source Website: http://srtm.csi.cgiar.org/


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SRTM Data Selection Option


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Sample DEM Data


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SRTM Data: 90 m Resolution

Computing Flow Direction


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Flow Direction Map

Flow Accumulation from Raw DEM


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Discontinuous

Flow Lines orLoo s

Sinks

Filling is Required

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Sink Filling


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on nuous ream ne

DEM Data Pre-processing


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Raw DEM Data

Interactive

Sink FillingNO

Continuous

Flow LinesYES

GenerateGenerate

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Stream Linese ec u e a ers e

Boundary

Filled DEM Data


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Stream Network from Filled DEM


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Defining Watershed Boundary


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Watershed Boundary

Outlet

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Case studies : GIS and RS applications

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Case study : Shiwalik hill in Dehradun


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: stereo magery

Wetness index imageLn(As/S) Stream power index (A *S)

Sediment transport index

75Source: suresh kumar et al, 2008, ISRS-36, 159-165

Case study-2: Spatial distribution of annual sediment yield estimation


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Source: Manish and Suresh

76Study area: Jhikhu Khola watershed in NEPAL

Conclusion and Discussions


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Extreme hydrological response of a hillslope :

discussed, their rediction based on wetness index,

their knowledge for land use/land cover planning: n ro uce , s use n wa ers e managemen

Digital elevation model: extraction of watershed

parameters, wetness index, stream power index

Recent case studies usin hi h-resolution DEM and

satellite remote sensing

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h k Yhank You

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gis application for hilly watershed

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