hydrologic measurement

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Hydrologic Measurement. Precipitation Evaporation Streamflow Channel Properties Topography GIS datasets. Reading: Applied Hydrology Chapter 6. Hydrologic Measurement. Water Quality Sampling. Precipitation, Climate, Stream Gaging. Precipitation Station. Tipping Bucket Raingage - PowerPoint PPT Presentation

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Hydrologic Measurement

• Precipitation• Evaporation• Streamflow• Channel Properties• Topography• GIS datasets

Reading: Applied Hydrology Chapter 6

Hydrologic Measurement

Precipitation, Climate, Stream Gaging Water Quality Sampling

Precipitation Station• Tipping Bucket Raingage

– The gauge registers precipitation (rainfall) by counting small increments of rain collected.

– When rain falls into the funnel it runs into a container divided into two equal compartments by a partition

– When a specified amount of rain has drained from the funnel the bucket tilts the opposite way.

– The number and rate of bucket movements are counted and logged electronically.

Tipping bucket rain gage

Weather/climate station

• Following variables are recorded– Wind

velocity/direction– Rainfall– Relative humidity and

temperature– Radiation

Components of a weather station

Anemometer

Radiometer

Tipping bucket raingage

Relative humidity and temperature

Precipitation (continued)

• Snow Pillows

http://wsoweb.ladwp.com/Aqueduct/snow/pillow.htm

8

Snow Pillows

Evaporation pan

Measuring streamflow

Streamflow using a boat

Tag line

Measurement at high flows

Using stream gaging cable car

From bridge

13

Acoustic Doppler Current Profiler

Schematic of a stilling well gaging station

Pressure transducer gaging station

Stream Flow Rate

A

Q AdV

Discharge at a cross-section

Water Surface

Depth Averaged Velocity

Height above bed

%60

%40

Velocity

n

iiii wdVQ

1**

iw

id

1i ni

Velocity profile in stream

Example

distance depth velocity(ft) (ft) (ft/s)

i d V1 0 0 02 12 3.1 0.43 32 4.4 0.94 52 4.6 1.15 72 5.7 1.36 92 4.5 0.77 112 4.4 0.98 132 5.4 1.49 152 6.1 2.010 167 5.8 2.211 182 5.7 2.512 197 5.1 3.113 212 6.0 3.114 227 6.5 3.015 242 7.2 2.616 257 7.2 2.017 272 8.2 1.618 287 5.5 2.019 302 3.6 1.620 317 3.2 1.221 325 0.0 0.0

0

1

2

3

4

5

6

7

8

9

0 25 50 75 100 125 150 175 200 225 250 275 300 325

Distance

Dep

th

Colorado River at Austin

Example (Cont.)Distance Depth Velocity Width Area Discharge

(ft) (ft) (ft/s) (ft) (ft2) (ft3/s)i d V w A Q

1 0 0 0 6 4.7 0.02 12 3.1 0.4 16.0 49.6 18.43 32 4.4 0.9 20.0 88.0 76.64 52 4.6 1.1 20.0 92.0 100.35 72 5.7 1.3 20.0 114.0 152.86 92 4.5 0.7 20.0 90.0 63.97 112 4.4 0.9 20.0 88.0 76.68 132 5.4 1.4 20.0 108.0 153.49 152 6.1 2.0 17.5 106.8 216.710 167 5.8 2.2 15.0 87.0 193.111 182 5.7 2.5 15.0 85.5 214.612 197 5.1 3.1 15.0 76.5 234.113 212 6.0 3.1 15.0 90.0 280.814 227 6.5 3.0 15.0 97.5 288.615 242 7.2 2.6 15.0 108.0 283.016 257 7.2 2.0 15.0 108.0 220.317 272 8.2 1.6 15.0 123.0 191.918 287 5.5 2.0 15.0 82.5 168.319 302 3.6 1.6 15.0 54.0 84.820 317 3.2 1.2 11.5 36.8 43.421 325 0.0 0.0 4.0 3.2 0.0

325 1693.0 3061.4

0

1

2

3

4

5

6

7

8

9

0 25 50 75 100 125 150 175 200 225 250 275 300 325

Distance

Dep

th

Q = 3061 ft3/s

V = Q/A = 1.81 ft/s

19

Rating Curve• It is not feasible to measure flow daily.• Rating curves are used to estimate flow from stage

data• Rating curve defines stage/streamflow relationship

0

2

4

6

8

10

12

14

16

18

20

0 5000 10000 15000 20000 25000 30000Discharge (cfs)

Stag

e (ft

)

Discharge GageHeight

(ft3/s) (ft)20 1.5131 2.0307 2.5530 3.0808 3.51130 4.01498 4.51912 5.02856 6.03961 7.05212 8.06561 9.08000 10.09588 11.011300 12.013100 13.015000 14.017010 15.019110 16.021340 17.023920 18.026230 19.028610 20.0

http://nwis.waterdata.usgs.gov/nwis/measurements/?site_no=08158000

National Elevation Dataset• Digital Elevation Model with 1 arc-second

(30m) cells • Seamless in 1° blocks for the United

States• 10 billion data• Derived from USGS 1:24,000 quadrangle

sheets

http://seamless.usgs.gov/Get the data:

http://ned.usgs.gov/

Digital Elevation Model (DEM)Contours

720

700

680

740

680700720740

720 720

Austin West 30 Meter DEM

32

16

8

64

4

128

1

2

Eight Direction Pour Point Model

Water flows in the direction of steepest descent

Flow Direction Grid

32

16

8

64

4

128

1

2

Delineation of Streams and Watersheds on a DEM

Watersheds of the US

2-digit water resource regions 8-digit HUC watersheds

Watershed Hierarchy

8 HUC

4

2

6

NHDPlus

10

12

Available In Progress

Digit #

Watershed of Brushy Creek

HUC12 number

29

LIDAR surveying

LIDAR (Light Detection and Ranging; or Laser Imaging Detection and Ranging) is a technology that determines distance to an object or surface using laser pulses. Like the similar radar technology, which uses radio waves instead of light, the range to an object is determined by measuring the time delay between transmission of a pulse and detection of the reflected signal.

Airborne Lidar

Airborne laser altimetry technology (LiDAR, Light Detection And Ranging) provides high-resolution topographical data, which can significantly contribute to a better representation of land surface. A valuable characteristic of this technology, which marks advantages over the traditional topographic survey techniques, is the capability to derive a high-resolution Digital Terrain Model (DTM) from the last pulse LiDAR data by filtering the vegetation points (Slatton et al., 2007).

Slide courtesy of Dr. Paolo Tarolli, University of Padova, Italy

Slide courtesy of Dr. Paolo Tarolli, University of Padova, Italy

x,y,z

Slide courtesy of Dr. Paolo Tarolli, University of Padova, Italy

3-D detail of the Tongue river at the WY/Mont border from LIDAR.

Roberto GutierrezUniversity of Texas at Austin

Digital elevation data

Grigno basin, ItalyResolution 30 m x 30 mData source: University of Padova

Tanaro basin, ItalyResolution 90 m x 90 mData source: University of Padova

Tirso basin, ItalyResolution 100 m x 100 mData source: University of Padova

Data resolution available until recently 30-100 m.

Rio Cordon basin, Selva di Cadore, Italy

Slide courtesy of Dr. Paolo Tarolli, University of Padova, Italy

The role of data resolution

DTM 10x10 m

Slide courtesy of Dr. Paolo Tarolli, University of Padova, Italy

DTM 1x1 m

Slide courtesy of Dr. Paolo Tarolli, University of Padova, Italy

The role of data resolution

Topographic Lidar

Green LiDARλ = 532 nm + λ =1064 nm

λ = 1064 nm

It is important to remember that the deep water surfaces normally do not reflect the signal: however this is not true in case of presence of floating sediments or when using bathymetric lidar. The bathymetric lidar, that is based on the same principles as topographic lidar, emits laser beams in two wavelengths: an infrared (1064 nm) and a green one (532 nm). The infrared wavelength is reflected on the water surface, while the green one penetrates the water and is reflected by the bottom surface or other objects in the water. Due to this reason the bathymetric lidar is also called green lidar.

Slide courtesy of Dr. Paolo Tarolli, University of Padova, Italy

Fonte: www.optech.ca

During optimal environment condition, when the water is clear, the green lidar survey may reach 50 m water depth with an horizontal accuracy of ±2.5 m, and vertical accuracy of ±0.25 m. This technology is growing fast, and some of the first applications in rivers are coming out (Hilldale and Raff, 2008; McKean et al., 2009).

Slide courtesy of Dr. Paolo Tarolli, University of Padova, Italy

http://srtm.usgs.gov/

HydroSheds derived from SRTM

http://hydrosheds.cr.usgs.gov/

River networksfor 8-digit HUC watersheds

http://nhd.usgs.gov/

Lower West Fork, Trinity River BasinHUC = 12030102

http://www.ncgc.nrcs.usda.gov/products/datasets/statsgo/

1:250,000 Scale Soil Information

Ssurgo for Travis County

103 soil map units described by 7530 polygons of average area 35.37 ha (87 acres)

National Land Cover Dataset

http://seamless.usgs.gov/Get the data:

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