Remote Sensing and GIS Applications for Hilly Watersheds SUBASHISA DUTTA DEPARTMENT OF CIVIL ENGINEERING IIT GUWAHATI
Deciding Alternative Land Use Options in a Watershed Using GIS Source: Anita Prakash et al, 2007 2
High Resolution of IRS-P6 Imagery VIENNA Source: NRSC website 3
High Resolution of CARTOSAT-2 Imagery Part of Varanasi, Uttar Pradesh, India Source: NRSC website 4
Topics to be covered Hydrological response of a hillslope under extreme rainfall events GIS as a tool for watershed management Analysis of digital elevation model ( terrain data) Case studies and discussion 5
The Hydrologic Cycle at hillslope Physical Processes Involved in Runoff Generation 6
Hillslope Hydrology Critical Hydrologic Processes Infiltration Overland Flow Subsurface Stormflow Soil Macropores and Water Flow Consequences : Flash Flooding Slope Failures and Slides Soil Erosion Debris Flow Groundwater Pollution 7
Hillslope Experimental Plot Geographic Location - 26 12 N latitude and 91 42 E longitude Topography Average slope 20%, COV 10.49% Microtopographic variation not significant 8
Hillslope Experimental Setup Upper Channel VENTURIMETER UPSTREAM CHANNEL PROFILE PROBE LOCATION SIDE PLATES Side Plate VALVE OVERLAND FLOW 18 m Piezometer PUMP DOWNSTREAM CHANNEL PUMP POND OUTLE T MEASURING TANK Lower Channel 6 m Extreme Storm Intensity about 50-400 mm/hr Storm Durations 15-120 minutes 9
10
Overland Flow - Results Time of Conce entration, t c (min) 6 5 4 3 2 1 Sparse Moderate Dense Infiltration n Rate, f b (mm/hr) Fig. 7 Fig. 5 Outflow hydrograph 300 Sparse 250 Moderate Dense 200 150 100 50 0 0 100 200 300 400 500 Equivalent Rainfall Intensity, i (mm/hr) Relationship between f b and i 0 Fig. 6 0 100 200 300 400 500 Equivalent Rainfall Intensity, i (mm/hr) Relationship between t c and i Similar response in sparse and moderrate vegetation Similar macropore network Distinct changes in behavior in dense vegetation Significant change in macropore connectivity and network 11
Temporal dynamics of subsurface storm flow Initial state At t=18min. At t=22min At t=29 min. At t=42 rainfall ceased At t=51min. 12
Temporal dynamics of subsurface storm flow ( Continued) At t=66min. At t=85 min. At t=99 min. Cii Critical lobservations : 1. Fast subsurface stormflow ( within 1-2 hours of the storm event) 2. Initiation of subsurface storm flow occurs for even a storm event of 50 mm/hr 3. Temporally perched water-table t formation on the bed-rock 13
Saturation in zones of convergent topography p
Hydrological effect of land use/land cover change Change in top soil macroporosity, more likely to have overland flow generation Blocking of subsurface stormflow path, more concentrated flow generation, leading high sheet erosion Being a thresholdh flow mechanism, it is controlled by rainfall intensity, it vegetation condition, soil layers Wetness index, based on DEM, predicts the subsurface storm flow paths Identification of Hotspots in a hilly watershed, related to flash 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 17
18
Why GIS? Can handle geographically referenced data or spatial data as well as non-spatial data Can handle relational numerical expressions between these data sets Ideal for natural resource management 19
Basic Functions of fgis Capturing data Storing data Manipulating data Retrieving and Querying data Analyzing data Displaying i data 20
Data Types Spatial Data Non-spatial Data Topography Land Use Land Cover Soil Water bodies State, District, Blocks Villages Forests Geology Road Network Descriptive Attributes Soil Type Land Use Type Village Name Street Name 21
Representation of Spatial Data 22
23
Spatial Data Models Vector Data Model Raster Data Model Based on geometry of Point Line Pl Polygon Digital Representation as GidCll Grid Cells Satellite Images Aerial Photographs Digital Elevation Models (DEM) 24
Vector and Raster Data Model 25
Vector Data Model Arc-Node data structure Basic graphical features Point Line Polygon 26
Arc-Node Data Structure Nodes & Vertices Arc-node structure Polygon structure Arc Number Start node Vertices End node Polygon Arc List 1 20 d,c,b.a 10 2 10 e 20 3 10 f,g,h,i,j 20 A 1,2 B 23 2,3 27
Topology : Defining Spatial Relationships Three major topological concepts: Connectivity: Arcs connect to each other at nodes. Area definition: Arcs that connect to surround an area define a polygon Contiguity: Arcs have direction and left and right sides 28
Connectivity 29
Area Definition 30
Contiguity : Adjacency 31
Vector Data Model Points: represent discrete point features each point location has a record in the table airports are point features each point tis stored as a coordinate pair 32
Vector Data Model Lines: represent linear features each road segment has a record in the table roads are linear features 33
Vector Data Model Polygons: represent bounded areas each bounded polygon has a record in the table polygonal features 34
Multiple Layers of Vector Data 35
Data Structures where of GIS is determined by coordinate (map) data structures, but what of GIS is determined by tabular (relational database) data structures GIS Database = Coordinate data + Attribute Data 36
Attribute Data Structures Attribute data are stored in database tables. Tables are composed of: Fields and Records 37
Use of Tabular Data Making queries Promoting and sorting records Displaying selected sets Modifying selected sets Basic descriptive statistics 38
Making Queries Selecting records from tables/features 39
Displaying Selected Sets Selecting records from tables also select features from themes 40
Analysis Tools of GIS BUFFER ANALYSIS OVERLAY ANALYSIS NETWORK ANALYSIS 41
Buffering Quantifying a spatial entity to influence its neighbours or the neighbours to influence the character of a Spatial entity Point Line Polygon 42
POINT BUFFER 43
LINE BUFFER 44
Overlay Analysis Point over Polygon Line over Polygon 45
Overlay Operators 46
Analysis of DEM for extraction of Watershed parameters 47
Digital Elevation Models Remotely Sensed Satellite Images Digital Elevation Models (DEM) Raster Data Structure 48
DEM Data from Contours 720 720 Contours 740 720 700 680 740 720 700 680 49
DEM Elevations Contours 700 680 50
A Simple Digital Elevation Model 67 56 49 46 50 cell size 53 44 37 38 48 58 55 22 31 24 61 47 21 16 19 53 34 12 11 12 50 (cell value) cell 51
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 map 90 m Shuttle Radar Topography p Mission (SRTM) 52
Using DEM Data Direction of Steepest Descent 1 1 67 56 49 67 56 49 53 44 37 53 44 37 58 55 22 58 55 22 Slope: 67 44 = 16.26 67 2 1 53 = 14 53
Eight Direction Pour Point Model 32 64 128 16 1 8 4 2 54
Flow Direction Grid 2 2 4 4 8 1 2 4 8 4 128 1 2 4 8 2 1 4 4 4 1 1 1 2 16 55
30 Meter DEM Elevations in meters ftp://ftp.tnris.state.tx.us/tnris/dema.html 56
Flow Direction Grid 32 64 128 16 8 4 1 2 57
Flow Network 58
Flow Accumulation Grid 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 2 2 0 0 11 1 1 15 0 0 2 5 24 1 0 0 0 0 3 2 2 0 11 0 1 0 1 15 0 0 2 5 24 1 59
Flow Accumulation > 5 Cell Threshold h Stream Lines 0 0 0 0 0 0 3 2 2 0 0 0 0 11 1 0 0 1 15 0 0 2 5 24 1 60
Stream Network for 5 cell Threshold h Drainage Area 0 0 0 0 0 0 3 2 2 0 0 0 0 1 11 0 0 0 1 15 0 2 5 1 24 61
Watershed Outlet 62
Watershed Draining to the Outlet 63
SRTM Data Source Website: http://srtm.csi.cgiar.org/ 64
SRTM Data Selection Option 65
Sample DEM Data SRTM Data: 90 m Resolution 66
Computing Flow Direction Flow Direction Map 67
Flow Accumulation from Raw DEM Discontinuous Flow Lines or Loops Sinks Filling is Required 68
Sink Filling Continuous Stream Line 69
DEM Data Pre-processing Raw DEM Data Interactive Sink Filling NO YES Continuous Flow Lines Generate Stream Lines Select Outlet Generate Watershed Boundary 70
Filled DEM Data 71
Stream Network from Filled DEM 72
Defining Watershed Boundary Watershed Boundary Outlet 73
Case studies : GIS and RS applications 74
Case study : Shiwalik hill in Dehradun DEM : stereo CARTOSAT imagery Wetness index image Ln(As/S) Stream power index (A *S) Sediment transport index Source: suresh kumar et al, 2008, ISRS-36, 159-165 75
Case study-2: Spatial distribution of annual sediment yield estimation Source: Manish and Suresh Study area: Jhikhu Khola watershed in NEPAL 76
Conclusion and Discussions Extreme hydrological response of a hillslope : discussed, their prediction based on wetness index, their knowledge for land use/land cover planning GIS: introduced, its use in watershed management Digital elevation model: extraction of watershed parameters, wetness index, stream power index Recent case studies using high-resolution DEM and satellite remote sensing 77
Thank You 78