Mapping
the run-off related to the land use in Little Bear Watershed-Logan Utah
1 Introduction
It is
well know that land cover changes influence watershed hydrology. For example, deforestation to create cropland
or urban areas causes an increase in runoff and earlier peak flows. It also
leads to environment problems, such as the decay of groundwater table (less
recharge come into the subsurface); flood (large ground run-off occurred).
While, the magnitude of the effect of land cover changes on runoff depends on
the size, average slope, and land cover characteristics of the watershed. The object of this project is to find out the
runoff related to the land use in 1992 in the Little Bear-Logan UT for a
100-year storm.
2 Site descriptions
The
Cache County is a broad arid agricultural valley in northern Utah and southern
Idaho in the US. It extends approximately 80km from Avon, UT to north of
Preston, Idaho along the west side of the Bear River Mountains, the north most
extension of the Wasatch Range, and along the east side of the Wellsville
Mountains and the Bannock Range. It is largely drained and irrigated by the
Bear River and its tributaries into the watershed of the Great Salt Lake. The
cultural and economic hub of the region is Logan, Utah, and home to Utah State
University. In this project, the HUC8 is16010203 was chose from the Cache HUC12
Watershed Boundary Dataset, which Logan is located at.
3 Methodologies
3.1
Building up the Catchment with HydroID
The
first step in doing this project was obtaining necessary data to set up a base
map of research area------Little Bear-Logan. Cache HUC8 Watershed Boundary
Dataset and HUC12 Watershed Boundary Dataset (1:24000) [1] were
downloaded from the Geospatial Data Gateway.
And the Catchment Flow-line data [2] was downloaded from the
NHDPlus.
Those
data were then loaded into a geodatabase and added to Arcmap. The USA
Contiguous Albert Equal Area Projected Coordinates System was used in this
project. The base map comprises watershed boundaries and streams. The Utah
State is located at Water resources Region 16, which is Great Basin with 71
HUC8 sub basin. The Figure 1 showed the location of the research area in Region
16 and Utah State, and the Figure 2 showed the outline of research area.
Fig 1 the layout of research area
in Region 16 and Utah State
Fig. 2 the outline of research
area
The
second step was to create a map that contained elevation. The DEM was
downloaded from the NHDPlus webpage and imported into the existing map. Project
the DEM and the cell size is 60´60m. Extract the DEM by mask of research areas. The
DEM recondition was done by setting “smooth drop in Z units” 10. Then, by the terrain preprocessing of Fill Sinks, Flow Direction, Flow
Accumulation, Stream Definition, Stream Segmentation, Catchment Grid
Delineation, and Catchment Polygon Processing to delineation the research area.
The Terrain Processing Workflow was showed in Fig3, and 1500 was used to define
the stream.
Fig 3 The
Terrain Processing Workflow
Fig 4 the layout of DEM Fig 5 the flow
direction
Fig 6 the flow accumulation Fig 7 the Cat raster
Fig 8 the layout of catchment polygon
There are 269-polygon catchments in Little Bear- Logan Utah, and Arc Hydro tools populated HydroID automatically for each catchment. The fig 8 showed the catchments labeled with HydroIDs.
3.2 Land
Cover Analysis
The land
cover change (1992/2001) data [3] was got from the U.S. Geological
Survey (USGS). They mainly used the modified
Anderson Level 1 class code and land cover change code to classify the land
type and land change (see table 1 for more detail).
Table 1 Land cover types and the runoff coefficients
|
Class No. |
LUT |
Description |
C [4] |
|
1 |
Open water |
Generally with less
than25% vegetation or soil cover |
0 |
|
2 |
Urban |
Includes developed,
low, medium and high intensity with a mixture of constructed materials and
vegetation |
0.7 |
|
3 |
Barren |
Barren areas of
bedrock, desert pavement, scarps, talus, slides and other earthen material,
vegetation accounts for less than 15% of total cover |
0.8 |
|
4 |
Forest |
Areas dominated by
trees generally greater than 5m tall, and greater than 20% of total
vegetation cover. Deciduous forest, Evergreen forest and Mixed forest was
included |
0.15 |
|
5 |
Grassland/Shrub |
Areas dominated by
shrubs or herbaceous vegetation less than 5m, and greater than20% of total
cover |
0.25 |
|
6 |
Agricultural Land |
Includes cultivated
crops and pasture/hay |
0.4 |
|
7 |
Wetland |
Includes woody wetland
and herbaceous wetlands |
0.05 |
Note: LUT refers to USGS Land Use Type; C refers
to Runoff Coefficient.
Load the
land use change image into Arcmap, and extracted the elements so that it could
match the outline of research area and project the land use raster file with
the cell size by 60´60m.
Fig 9 the Land use in research
area
The
total area in research area was about 2286.8 km2, and land cover
change during 1992 to 2001 showed in table 2.
There were almost no changes during this 10yr. Compared to the others,
the Agriculture land changed most, and decreased by 1.975km2, which
was 0.09% less than the one in 1992. The Urban area increased by about 1.048km2,
which was 0.05% more compared to the one in 1992. In this project, choose the
land use condition in 1992 as the research target (see table 2).
Table 2 the land use of research
area in 1992 and 2001
|
LUT |
1992 |
2001 |
Different |
|||
|
Area (km2) |
Percentage (%) |
Area (km2) |
Percentage (%) |
Area (km2) |
Percentage (%) |
|
|
Open water |
9.1625 |
0.40 |
9.325 |
0.41 |
0.1625 |
0.01 |
|
Urban |
85.21 |
3.72 |
86.2575 |
3.77 |
1.0475 |
0.05 |
|
Barren |
3.5725 |
0.16 |
3.58 |
0.16 |
0.0075 |
0.00 |
|
Forest |
1238.8025 |
54.10 |
1236.3425 |
53.99 |
-2.46 |
-0.11 |
|
Grassland/Shrub |
657.0925 |
28.70 |
658.6425 |
28.76 |
1.55 |
0.07 |
|
Agriculture Land |
269.2475 |
11.76 |
267.2725 |
11.67 |
-1.975 |
-0.09 |
|
Wetland |
26.6825 |
1.17 |
28.35 |
1.24 |
1.6675 |
0.07 |
|
Total |
2289.77 |
100 |
2289.77 |
100 |
0 |
0.00 |
By
hierarchical cluster analysis in SPSS, the catchments were divided into 7
types: Open Water, Wetland, Urban, Agriculture land, Urban+Agriculture land,
and Forest domain catchments. And the results were showed in table 3.
Table 3 the Hierarchical cluster
analysis of land use by catchments
|
Type |
Description |
HydroID |
|
Open Water |
The area of open water>75% |
58, 59, 63 |
|
Wetland |
The area of wetland>75% |
73, 74, 77 |
|
Urban |
The area of urban>90% |
147 |
|
Agriculture land |
The area of agriculture>75% |
48-49, 54-56, 60-61, 64, 71, 76, 79-80, 91,
101-102, 104, 107-108, 112-115, 117, 120-121, 129, 136, 142, 148, 153, 155,
158, 165, 173, 183-184, 188, 197, 218 |
|
Urban+Agriculture land |
The area of urban and agriculture>75%, they
are almost the same areas |
97, 109, 111, 116, 143, 152 |
|
Forest+Grass+Agrculure land |
The area of forest, grass and
agriculture>75%, they are almost the same areas |
47, 62, 72, 82, 93, 98, 103, 106, 110, 122,
123, 128, 141, 163, 164, 166, 172, 189, 196, 213, 217, 220 |
|
Forest |
The area of forest>75% |
others |
3.3
Run-off Analysis
Use the
“Tabulate Area” function to statistic the land type in each catchment. Add
field in the catchment feature class, join and related (by HydroID) with the
statistic table got from the Tabulate Area function, and by field calculation,
the land areas for land types for each catchment. Generate an EXCEL of runoff
coefficient and precipitation, join relationship (by HydroID) with catchment,
and by field calculation, the runoff coefficient for each land type was
assigned.
Fig 10 the tabulate area function
Fig 11 the layout of attribute table of catchment
Note: value* was passed down by land use
raster file.
Assuming the precipitation intensity is constant, and the following precipitation runoff model will perform the runoff analysis:
¾(1)
------Refers to
the runoff of catchment, mm;
------Refers to
the runoff coefficient of different land use types;
------Refers to the precipitation intensity, m/h, and
it is constant here;
------Refers to the continuous time of rainfall, h;
-----Refers to the area of land use in a catchment, m2;
-----Refers to the land use types.
There are seven active climate stations in research area;
the location is just like following:
Table 4 the location of climate
station in Cache
|
Name |
Latitude (º) |
Longitude (º) |
|
LOGAN 5 SW EXP FARM |
41.6661 |
-111.891 |
|
LAKETOWN |
41.825 |
-111.321 |
|
TRENTON |
41.9153 |
-111.913 |
|
RICHMOND |
41.9064 |
-111.81 |
|
LAKETOWN |
41.825 |
-111.321 |
|
LOGAN UTAH ST UNIV |
41.7456 |
-111.803 |
|
LOGAN RADIO KVNU |
41.7353 |
-111.856 |
Then find out the corresponding precipitation in the map of 100-YR 6-HR Precipitation in UT. Here all the precipitations in all the climate station were 23 in tenths of an inch, so, the precipitation intensity should be 0.09737 m/h.
Fig 12 the isopluvials of 100-YR 6-HR precipitation [5]
In the catchment attribute table add fields: R30, R60, R180, and R360, which represented the runoff in 0.5h, 1h, 3h, and 6h, respectively. According to the equation (1), calculate the corresponding runoffs by field calculator, and the result showed below. When rainfall occurred within the first half a hour, the minimum runoff was about 0.34mm, and the maximum reached to about 33.44mm; when the rainfall lasted for 6 hours, the minimum runoff reached to about 4.09mm, and the maximum was about 401.33mm, which occurred in catchment147, and the urban area took more than95%.
Fig 13 the runoff calculation
Fig 14 Runoff within 0.5h Fig 15 Runoff within 1h
Fig 16 Runoff within 3h rainfall Fig 17 Runoff within 6h rainfall
By the hierarchical cluster analysis of runoff in catchments in SPSS, the catchments in Little Bear Logan-UT were divided into 5 levels. The table 5 showed that the runoff generated in each catchment was correlation with the land use features in the catchment. Open water + wetland domain catchment the average runoff was the least, and about 2.05mm, followed by Forest + Grassland, Agriculture land, Urban + Agriculture land and the Urban domain catchments. The Urban domain catchments had the highest runoff, because of its large impermeable surface lead to higher runoff coefficient.
Table 5 Hierarchical Cluster analysis of runoff in 0.5h rainfall in catchments
|
Type |
Description |
HydroID |
|
Open
water+Wetland |
Average runoff
was 2.05mm, and runoff was between 0~4.5mm |
58, 59, 63,
73, 77 |
|
Forest+Grassland |
Average runoff
was 9.8mm, and runoff was between 9~13.5mm |
Others |
|
Agriculture
land |
Average runoff
was 17.93mm, and runoff was between 14~24mm |
48, 54-56, 60,
62, 64, 71-72, 79, 81-82, 91, 93, 98, 101-102, 104, 106-108, 111-115, 117,
120-121, 128-129, 136, 142, 148, 153, 155, 158, 163-165, 173, 183-184,
188-189, 192, 196-197, 203--204, 213, 217, 218, 220 |
|
Urban+Agriculture
land |
Average runoff
was 26.11mm, and runoff was between 25~27mm |
97, 109, 116,
143, 152 |
|
Urban |
Runoff was
33.45mm |
147 |
4 Conclusions and discuss
The GIS-based runoff analysis was used to map the runoff related to the land use in 1992 in Little Bear-Logan UT for a 100yr storm. From the analysis, we could get the following conclusions:
(1) The land covers in the Little Bear Logan-UT, had no significant changes between 1992 and 2001.
(2) The catchments in the Little Bear Logan-UT, could be divided into 7types according to the hierarchical cluster analysis, they were Open Water, Wetland, Urban, Agriculture land, Urban+Agriculture land and Forest domain catchments.
(3) The runoff in the catchments in the Little Bear Logan-UT was divided into 5 levels. The runoff generated in each catchment was correlation with the land use features in the catchment. Open Water domain catchment had the lowest runoff and urban domain catchment had the highest runoff, and followed by Urban+Agriculture land, Agriculture land and Forest+Grassland.
The limitation of this project is that only the static runoff generation was studied and the dynastic flow processing was not considered. To simulate the runoff flow with time, and then use the observed data to assess the result would make this project more completely.
REFERENCE
[1] http://datagateway.nrcs.usda.gov/
[2] http://www.horizon-systems.com/NHDPLUS/HSC-wth16.php
[4] http://igs.indiana.edu/survey/projects/hydrotools/html_files/element2.cfm
[5] http://www.wrcc.dri.edu/pcpnfreq.html