||Headwater streams begin upstream at the channel head and extend downstream to the
confluence of second or third order streams. They may exhibit ephemeral, intermittent,
or perennial flow regimes and often comprise a disproportionate share of the drainage
network. Recent studies estimate that intermittent and ephemeral streams comprise
59% (3,200,000 km) of total stream length in the United States. Dense, dendritic and
fractal networks exponentially expand the extent of stream reaches. These vast networks
are squeezed into the landscape and thus unsurprisingly have a substantial impact
on downstream water quality, biodiversity, water supply, nutrient cycling, and water
treatment costs. However, despite the importance and predominance of headwater streams
in the landscape, their extent remains poorly mapped and understood.
The National Hydrography Dataset (NHD) is the digitized version of USGS 1:24,000 scale
topographic maps, which are typically used to locate streams for a variety of planning
and regulatory purposes. Numerous studies have found the NHD to be inadequate for
determining the extent of stream networks, with underestimations of 56 percent in
North Carolina and up to 300 percent in urban areas reported. Moreover, the Piedmont
eco-region is expected to urbanize by 165 percent over the next 50 years. Since these
small streams thoroughly perfuse the landscape and serve as the most proximate intersection
of the lotic and terrestrial environments, they are especially sensitive to development
pressure. Thus any attempt to protect the integrity of the Piedmont’s environmental
services and water resources will be extraordinarily difficult, and prohibitively
costly, if this urban growth cannot be managed to avoid the maximum amount of harm.
This study presents a reliable method for locating these streams, including intermittent
and ephemeral streams that were recently held to be jurisdictional waters by the EPA.
Fieldwork was undertaken from June to October of 2014 in the Edeburn and Korstian
Divisions of the Duke Forest. Drainage lines were walked from the downstream position
of perennial flow to the upstream channel head position with a high-resolution satellite
Global Positioning System (GPS). Four types of channel segments used to categorize
stream reaches: (1) presence of water, (2) channelized, (3) presence of pools & riffles,
and (4) well-defined concentrated flow. Dietrich and Dunne’s (1993) definition of
the channel head, the upstream limit of concentrated flow, was used to classify the
four simple types of channel heads recorded in this study: (1) headcuts, (2) spring
saps, (3) headwater ponds, & (4) first-order stream heads. Ultimately a total of 117
channel heads and 67 km of streams were mapped in this study. The NHD only displayed
24 km of streams over the same area. This means that the NHD only captured ~35 percent
of the actual stream network, a significant underestimation.
GIS analysis was completed to see if a better estimation of the stream network could
be achieved. Three flow routing algorithms (D8, D∞, MD∞) and grid resolutions (3-meter,
6-meter, 10-meter) were used for sensitivity analysis (9 combinations total) to test
flow accumulation thresholds. Two flow accumulation thresholds were selected: (1)
Upslope-accumulated area (UAA) A= (∑_(i=1)^(# of cells)▒〖cell〗_i ) x (Cell Area),
and (2) Slope-area (AS) AS =A*S^1 where S is local slope (m/m). UAA and AS values
were extracted from mapped channel head locations to compute probability density functions
(PDFs) and cumulative distribution functions (CDFs). Median UAA values were found
to range from 0.075 – 1.122 hectares and median AS values ranged from 43.98 – 1731.39
(where A is in m2).
Grid resolution was found to be the dominant control on flow accumulation threshold
values with the 3-meter and 10-meter DEM providing the smallest values. Flow algorithm
choice only appeared to be pertinent for the coarsest DEM, 10-meter, where the MD∞
algorithm produced half the predicted flow accumulation value of D8. 50th (median)
and 75th quantile CDF channel head values were then used to create stream networks
for the 3-meter DEM with the MD∞ algorithm, which had the smallest flow accumulation
values. These predicted streams were compared to mapped streams and channel heads.
The 75th quantile channel head values provided the best approximation of the stream
network, with minimal overprediction. There was a negligible difference between the
two flow accumulation threshold methods, although AS did tend to outperform UAA using
the 75th quantile channel head values. Median channel head values produced a stream
network with significant overprediction and feathering, particularly for the AS threshold.
A hypsometric curve was also created for the study site, which determined that it
is generally dominated by fluvial erosion, but also influenced diffusive processes.
A scaling relationship between local slope (m/m) and UAA (ha) was then created with
a slope-area curve. The curve gives every grid cell in the DEM (~7 million) a set
of x, y coordinates that can be plotted in two-dimensional coordinate space. The slope
of this curve, or “rollover” point, transitions from dS/dA > 0 at low contributing
areas (positive) to dS/dA < 0 at large contributing areas (negative). This transition
is associated with a change from diffusive, transport-limited hillslopes to fluvial
erosion processes. The curve was fit with a piecewise regression with breakpoints
at the median and 75th quantile channel head values. The transition from positive
to negative slope in the regression occurred at the median channel head value. The
finding that half the channel heads occur before this transition point suggests that
groundwater and subsurface water contributions may be significant, as channel initiation
begins before critical hillslope length is reached.
The 75th quantile channel head CDF value was found to accurately delineate the extent
of the stream network, while minimizing overprediction. This method for stream network
prediction greatly enhances the accuracy hydrography of data when compared to the
NHD, especially for temporary headwater streams. While field mapping channel heads
is time and labor intensive, it can be used to better inform and test predictive methods
that can quickly and more accurately determine the extent of the stream network.