- 1. HawaiiNational Hydrogrpahy DatasetStewardship Partnership
Malie Beach-Smith Principal Steward
2. Overview of theNational Hydrography DatasetWhat it looks
like?How it work? 3. NHDNational Hydrography Dataset 4. collection
of points, lines, and polygons in a digital vector
database.HanapepeBayKauai 5. Oceans, lakes, ponds, reservoirs,
rivers,wider streams, swamps and marshes are represented by
POLYGONS. lake/pondriverreservoirsea/ocean 6. Coastlines, streams,
irrigation ditches, pipelines and artificial paths arerepresented
by LINES. artificial pathpipeline stream canal/ditchcoastline 7.
Dams, gaging stations, wells, and springs are represented by
POINTS.gagingstationsdams springs 8. Note: There are many more
feature types represented in the NHD.Those were just a few of the
more prominent ones. 9. seamless dataset covering:contiguous United
States, Alaska, Hawaii, the Virgin Islands, Puerto Rico, American
Samoa, and Guam Includes: bordering watersheds in Canada and Mexico
10. Data Organized into Hydrologic UnitsHYDROLOGIC UNITSDefined
byheadwaters,bordered by a ridge system,converging to a pour point
or belt flow Subregions 11. Hydrologic Units Subregions of the
Contiguous United States22,056 Subregions in the countiguous U.S.
12. Region 20NiihauKauai2008 2007 Oahu2006Molokai 2005 Maui
20042002 Lanai2003KahoolaweHawaii20018 subregions in Hawaii.Hawaiis
SUBREGIONS are defined by ISLAND.Each ISLAND subregion is further
divided into drainage units by the WBD. 13. Hydrologic Units
Watershed Boundary DatasetSix level hierarchy ofnested watersheds
Hydrologic Unit Code (HUC)Each level is referred to by the
Hydrologic Unit Code or HUC 14. Hydrologic Units Watershed Boundary
DatasetHawaii(subregion 2001)HUC_8This is the HUC 8 for the island
of Hawaii (subregion 2001) 15. Hydrologic Units Watershed Boundary
Dataset HUC_10These are the HUC 10s 16. Hydrologic Units Watershed
Boundary Dataset HUC_12These are the HUC 12s 17. Hydrologic Units
Watershed Boundary Dataset HUC_12And these are the HUC 12s uniquely
color coded 18. Watershed Boundary Datasetand the National
Hydrography Dataset Streams (hydrography dataset) Sub-watersheds
(WBD)HUC_12This slide shows the integration of the WBD with the
hydrography feature class. 19. Streams - the fundamental core of
the NHD HalawaBayMolokaiNHD carries a lot of information about
streams. Stream classification is one piece ofinformation within
the data structure. Here, the perennial streams are displayed as
dark blueand the intermittent streams as light blue. 20. Streams -
the fundamental core of the NHD HalawaBay MolokaiFlowlines also
carry names. These names are collected directly from the Geographic
NamesInformation System, where all names have been approved by the
Board of Geographic Names. 21. Flow Direction giving intelligence
to the dataFlow direction: Flowlines in the NHD contain information
about where the water is flowing. With directional information we
can navigate upstream and downstream. This allows us to ask
questions, and get answers, such as 22. Navigation Creating
fundamental knowledgeKaiaka BayOahu What is upstream of a given
point? 23. Navigation Creating fundamental knowledgeKaiaka BayOahu
Because we know which way the water flows, we can navigate upstream
24. Navigation Creating fundamental knowledgeand capture all the
flowlines in the network upstream of a given point. 25. Navigation
Creating fundamental knowledgeOr you may sayshow me everything
downstream of a given point 26. Navigation Creating fundamental
knowledge and the database can navigated downstream through the
network.This ability to navigate upstream or downstream through the
network is useful for a variety ofmodeling and analysis exercises.
27. Navigation Creating fundamental knowledgeTransport downstream
Toxic spillSewage spillFor example, you may want to model the
downstream transport of a toxic spill. Or, you maywant to know what
waters will be affected by a sewage spill. 28. Navigation Creating
fundamental knowledge You may want to model fish migration
upstream. 29. Navigation Creating fundamental knowledge trace
upstream with barriers Northern East Maui CoastAnd here, you may
want to model possible barriers to fish migration upstream. In
thisexample, the irrigation ditch layer was used as a barrier to
fish migration. 30. Linear Referencing Stream ReachesAnother very
important part of the NHD is its ability to address information to
the dataset. 31. Linear Referencing Stream Reaches referencing
systemLinking information to the dataset gives the data its
intelligenceThe flowlines are more than just blue lines on a map,
they are also a referencing system for 32. Linear Referencing
Stream Reaches 20060000001050ReachMalie StreetStreet NHD Road MapIn
the NHD, the linear referencing system can be analogous to street
addresses on a road map. The NHD uses reaches the way road maps use
street names. 33. Linear Referencing Stream Reaches Each reach has
aSimilar to the way20060000001050 unique 14 digit reachcodea zip
code describesMalie Streetthat holds information the region of a
country, about the subregion,county,and the hydrologic unitor
townthat flowlines reside in Reach Street 34. Linear Referencing
Stream Reaches Each reach uniquely color coded unique numerical
codeEach reach in this slide is uniquely color coded, and each
reach has a unique numerical code. 35. Linear Referencing Stream
Reaches regionThe first two digits, 2, 0, tell us what region we
are in. 20 indicates Hawaii. 36. Linear Referencing Stream
ReachessubregionThe next two digits, 0,6 identify the subregion .
2006 is the island of Oahu. 37. Linear Referencing Stream
Reachessub-watershedThe next six digits describe finer divisions of
watersheds and sub-watersheds. 38. Linear Referencing Stream
Reaches unique reach (basis for the address referencing system)The
last 4 digits describe a unique reach that is the basis for the
address referencing system. This is reach number 2164 of subregion
2006 (Oahu). 39. Linear Referencing Measures80.00543 2468
20060000001050ReachStreetMalie StreetLike a house number on a
street. A point on a reach has a measure. 40. Linear Referencing
Stream Addresses Reachcode20060000000848 100 75 0 2550A reach is
divided into address ranges called measures. A measure works like
this 41. Linear Referencing Stream Addresses
Reachcode20060000000848 1000The downstream end of a reach is
designated as 0, and the upstream end is designated 100. 42. Linear
Referencing Stream AddressesReachcode 2006000000084810075 0 25
50Every location along the reach has a measure (like a percentage
of the total length). It doesntmatter how long, or sinuous a reach
is, a particular address is anywhere between 0 and 100. 43. Linear
Referencing Data Events Reachcode20060000000848 data point =
eventSo having an address referencing system, allows us to attach
information to the dataset.Data related to the NHD is referred to
as events. 44. Linear Referencing Data EventsReachcode
20060000000848 Water quality sampling site Biological survey
siteStream gageetc.An event may be a water quality sampling site, a
biological survey site, or a stream gage ordam. 45. Linear
Referencing Data EventsReachcode 20060000000848 37.52676
(measure)Eventshave an address within the network using a reachcode
and measure. This site is at measure 37.52676 on reach 848 in
subregion 2006 (Oahu) 46. Linear Referencing Data Events
Reachcode20060000000848 data segment = eventEvents can also
describe stretches or segments of a flowline. 47. Linear
Referencing Data Events Reachcode20060000000848Biological survey
segmentSegment of impaired waterWaters with special usesA line
event may be a biological survey segment, a segment of impaired
water, or waterswith special uses. 48. Linear Referencing Data
Events Reachcode2006000000084882.37655 T0_measure31.49238
FROM_measureLine events are addressed using a from measure and a to
measure. 49. Linear Referencing Data EventsHanalei Bay USGS stream
gage ID: 16103000Events can be layers within the NHD that contain
additional information or links toadditional data. This is a USGS
gage on the Hanalei River. It is gage number 1610300. 50. Linear
Referencing Data Events HanaleiBayUSGS stream gageID:
16103000Latitude 221046.5Longitude 1592759.0"We know the stream
gages position in space.We know its X Y position in latitude and
longitude 51. Linear Referencing Data EventsHanalei BayUSGS stream
gageID: 16103000Latitude 221046.5Reachcode: 20070000001000
Longitude 1592759.0"Measure: 98.66498 but even more importantly, as
an event in the NHD, we know where this stream gage iswithin the
network. We know its address. .. 52. Linear Referencing Data
EventsHanalei Bay USGS stream gage ID: 16103000Latitude
221046.5Reachcode: 20070000001000Longitude 1592759.0"Measure:
98.66498And having an address on the network allows use to analyze
relationships between features. 53. Events Intelligence about the
dataThrough the Events table, we have a link from this particular
stream gage record to theNational Water Information System.
(Clicking on this point will take us there.) 54. Events
Intelligence about the dataThis is the record of that Hanalei
stream gage from March 4th. You can see that the waterflowing
though that stream was well above the median daily statistic. 55.
Events Intelligence about the dataBy linking an event to the
dataset, (in this case we linked a stream gage to a river), we add
toour knowledge about that dataset. We went from knowing we had a
riverto knowing something about that river. 56. Events Intelligence
about the databiological communitiesfish habitat water qualityfish
migration barriersetc.Events can be added to provide information
about all kinds of things. You can add eventsabout biological
communities, fish habitat, water quality, stream flow, and fish
barriers, forexample. 57. Events More than just dots on a mapData
that is truly integrated The building blocks for knowledge
Diversions in the headwaters of the Colorado River (12,500
diversions in this particular dataset)So events are more than just
dots on a map. Events are data that is truly integrated into
theJeff Simley, USGSframework of the dataset. 58. Events More than
just dots on a mapData that is truly integrated The building blocks
for knowledge Diversions in the headwaters of the Colorado River
(12,500 diversions in this particular dataset)The black dots in
this slide are diversions in the headwaters of the Colorado
Simley,There areJeff River. USGS over 12,500 diversions in this
particular dataset. 59. Events More than just dots on a map Data
that is truly integratedThe building blocks for knowledgeThere is
so much data, here, it can be a bit overwhelming. But by indexing
these diversions to Jeff Simley, USGS the dataset, we can use the
power of the computer to sort all this information out. 60.
Analyzing Information to create knowledge Jeff Simley, USGSWe can
sort out which diversions affect the flow of water through a
particular stream gage.Taking advantage of the upstream -
downstream directionality of the dataset we can do thesekinds of
calculations. 61. National Water Information System Linear
EventsThe NHD integratesinformation frommany resources. In DFIRM
Floodplainsthe future, the USGSplans to include National
WetlandsDFIRM floodplain Inventorydata, the
NationalWatershedWetlands Inventory, BoundaryDatasetand the
NationalElevation
Dataset.NationalHydrographyDatasetNationalElevationDataset 62.
Traditional GISNational Water Information System NHDoverlays themes
of Data is linkedinformation, one onLinear Events together within
thetop of other data structure.Relationships betweenfeatures are
DFIRM Floodplains Analysis is muchdetermined by theirmore powerful.
Nationalspatial proximity. Wetlands InventoryWorks well for some
Watershedanalysis. Boundary A highly effectiveDataset solution
toWorks for makingNational geospatial analysis.maps.
HydrographyDatasetThe power of the GISto sort this
informationNationalElevationand understand theDatasetrelationships
becomesWell integrated datastrained when youmakes this
possible.have a lot of data toanalyze. 63. So, how do we make all
this happen? There are a lot of things we need to do to keep the
NHDcurrent: add data to it, add intelligence to it, add new
features, new content, things like that.Jeff SimleyThe capabilities
of the USGS are rather limited. So what the USGS has done is to
leveragethose capabilities with a partnership of people. 64. In
building the NHD for the country, the USGS partnered with a lot of
different people, States,and other Federal AgenciesA huge
partnership made all this possible. And the USGS needsto continue
these partnerships to help maintain and improve this data. To do
this, The USGSestablished the Stewardship capability. The partners
of the Stewardship join in to helpmaintain and improve the National
Dataset. 65. Building the National Hydrography DatasetThe National
Hydrography Dataset was designed and substantially built by three
FederalpartnersThe USGS remains the lead agency for: maintaining
the NHD framework;developing NHD software; quality-control of
edits; and housing and disseminating the data. 66. Maintaining the
National Hydrography Dataset Hawaii NHD Stewardship Partnership
State Stewardship programs (like Hawaiis Partnership) take the lead
in UPDATING andMAINTAIING the datasets. Hawaiis NHD Stewardship
Program began in August 2009 as apartnership between the USGS and
three primary State agencies These state agencies tookthe lead to
establish the Stewardship Program and provide direction and
oversight of changesto the NHD. Since its formation, over 10,000
edits have been made to Hawaiis datasets. 67. GOALProvide the State
and the Nation with themost up-to-date and reliablesurface water
dataset 68. NHDs is notable for these Achievements: 69. NHDs is
notable for these Achievements:1. Developing a standardized data
model almost everyone can agree to. 70. NHDs is notable for these
Achievements:1. Developing a standardized data model almost
everyone can agree to.2. Creating a fundamental framework to serve
as an application foundation. 71. NHDs is notable for these
Achievements:1. Developing a standardized data model almost
everyone can agree to.2. Creating a fundamental framework to serve
as an application foundation.3. Developing a robust solution that
will advance the science. 72. NHDs is notable for these
Achievements:1. Developing a standardized data model almost
everyone can agree to.2. Creating a fundamental framework to serve
as an application foundation.3. Developing a robust solution that
will advance the science.4. Making the solution simple enough to be
implementable. 73. NHDs is notable for these Achievements:1.
Developing a standardized data model almost everyone can agree
to.2. Creating a fundamental framework to serve as an application
foundation.3. Developing a robust solution that will advance the
science.4. Making the solution simple enough to be implementable.5.
Creating a national partnership to pool resources. 74. NHDs is
notable for these Achievements:1. Developing a standardized data
model almost everyone can agree to.2. Creating a fundamental
framework to serve as an application foundation.3. Developing a
robust solution that will advance the science.4. Making the
solution simple enough to be implementable.5. Creating a national
partnership to pool resources.6. Actually building the national
dataset. 75. NHDs is notable for these Achievements:1. Developing a
standardized data model almost everyone can agree to.2. Creating a
fundamental framework to serve as an application foundation.3.
Developing a robust solution that will advance the science.4.
Making the solution simple enough to be implementable.5. Creating a
national partnership to pool resources.6. Actually building the
national dataset.7. Creating a stewardship community and process to
enhance and maintain the data. 76. How to get it. Where to learn
more. Who to call to contribute. 77. END 78. The NHD is a
collection of points, lines, and polygons in a vector
dataset.Polygons represent lakes, ponds, reservoirs, and
oceans,MakaoKahai Point, KauaiWorldview2 imagery 79.
polygonsLake/pondNomilo Fishpond reservoirSea/OceanMakaoKahai
Point, Kauai 80. as well as rivers, wider streams, swamps and
marshes.Anahulu River, Oahu Worldview 2 imagery 81. polygons
swamp/marshswamp/ marshswamp/ marsh 82. canals and ditchesKohala
DitchHawaii 83. Kohala Ditch, HawaiiKohala Ditch, Hawaii DOQQ
natural color imageryDOQQ Natural Color imagery 84. Kohala Ditch,
Hawaii 85. Kohala DitchHawaii 86. springs Honolulunui BayHanaw
SpringsPali SpringBig Spring Hawaii Island Worldview 2 imagery 87.
Honolulunui BayHanaw SpringsPali SpringBig SpringHawaii Island 88.
wells 89. Lanai Lanai 90. gaging stationsOlowalu stream gage Maui
91. gaging stationsMaui Gaging station 92. waterfallsKahiwa Falls,
Molokai 93. waterfalls Kahiwa FallsEast Molokai 94. damsWahiawa Dam
95. dam Wahiaw ReservoirOahu 96. coastlinesWorld Imagery Service
97. Albers_Equal Area_Conic 98. including larger offshore
isletsFord IslandSand IslandOahu 99. Lehua StateSeabird
Sanctuaryand smaller offshore isletsNiihau 100. Watershed Boundary
Datasetintegrated into the NHDHUC_8 Hawaii Island 101. HUC_10
Hawaii Island 102. HUC_12 Hawaii Island 103. Put it all together
104. coastline,Hanapepe Bay Kauai 105. watershed
boundaries,Hanapepe BayKauai 106. rivers,Hanapepe Bay Kauai 107.
streams,Hanapepe BayKauai 108. irrigation ditches,Hanapepe Bay
Kauai 109. lakes, ponds, and reservoirs,Hanapepe BayKauai 110.
gaging stations,Hanapepe Bay Kauai 111. dams,Hanapepe BayKauai 112.
and wells.Hanapepe BayKauai 113. More than just a collection of
shapefilesMore than just a collection of shapefiles Hanalei Bay
TOPOLOGY Kauai TOPOLOGY 114. With topology, the flowlines carry
information about the relationship between the . Hanalei Bay
