Academia.eduAcademia.edu

Figure 4 – uploaded by Ken Fritz

See full PDFdownloadDownload figure
Fic. 4. Stream networks in a small (1.9 km?) catchment in Hamilton County, Ohio, modeled in ArcHydro® with flow accumulation coefficients (FAC) corresponding to the mean catchment area for forested (FAC = 62, n = 22) (A) and urban (FAC = 613, n = 26) (B) catchments. The forested map portrays ephemeral, intermittent, and perennial stream channels with minimal human influence.

Figure 4 Fic. 4. Stream networks in a small (1.9 km?) catchment in Hamilton County, Ohio, modeled in ArcHydro® with flow accumulation coefficients (FAC) corresponding to the mean catchment area for forested (FAC = 62, n = 22) (A) and urban (FAC = 613, n = 26) (B) catchments. The forested map portrays ephemeral, intermittent, and perennial stream channels with minimal human influence.

Related Figures (12)

Fic. 1. Map of surveyed channel origins and origins of intermittent and perennial flow within Hamilton County, Ohio (US) Ephemeral stream origins occur where channel origins do not overlap with intermittent and perennial flow origins. Multipl adjacent X’s indicate >1 ephemeral flow origin.
Fic. 1. Map of surveyed channel origins and origins of intermittent and perennial flow within Hamilton County, Ohio (US) Ephemeral stream origins occur where channel origins do not overlap with intermittent and perennial flow origins. Multipl adjacent X’s indicate >1 ephemeral flow origin.
* log(x)-transformed for analysis ® arcsine(\[x])-transformed for analysis TABLE 1. Summary statistics for ephemeral, intermittent, and perennial flow origins and comparison between Eastern Corn Belt Plains and Interior Plateau ecoregions (2-tailed t-test, assuming unequal variances).
* log(x)-transformed for analysis ® arcsine(\[x])-transformed for analysis TABLE 1. Summary statistics for ephemeral, intermittent, and perennial flow origins and comparison between Eastern Corn Belt Plains and Interior Plateau ecoregions (2-tailed t-test, assuming unequal variances).
Fic. 2. Stream networks in a representative section of Hamilton County, Ohio, based on the US Geological Survey National Hydrography Dataset (NHD, 1:100,000 scale) and extended networks created in ArcHydro® using flow accumulation coefficients (FAC) corresponding to the median catchment area (ha) of ephemeral, intermittent, and perennial flow origins based on field surveys. Commonly used stream maps greatly underesti- mate actual stream length (Mueller 1979, Meyer and Wallace 2001). Inaccuracies are biased toward under- representation of the smallest, intermittently flowing headwater streams. In our study (in the eastern US), 1:100,000-scale maps identified only % of perennial channel length, and ~1/7" of the total channel length, whereas 1:24,000-scale maps identified 22% of the total channel length. These underestimations are comparable to those reported for a field assess-
Fic. 2. Stream networks in a representative section of Hamilton County, Ohio, based on the US Geological Survey National Hydrography Dataset (NHD, 1:100,000 scale) and extended networks created in ArcHydro® using flow accumulation coefficients (FAC) corresponding to the median catchment area (ha) of ephemeral, intermittent, and perennial flow origins based on field surveys. Commonly used stream maps greatly underesti- mate actual stream length (Mueller 1979, Meyer and Wallace 2001). Inaccuracies are biased toward under- representation of the smallest, intermittently flowing headwater streams. In our study (in the eastern US), 1:100,000-scale maps identified only % of perennial channel length, and ~1/7" of the total channel length, whereas 1:24,000-scale maps identified 22% of the total channel length. These underestimations are comparable to those reported for a field assess-
TABLE 2. Stream network lengths for Hamilton County, Ohio, based on publically available Geographical Information Syste (GIS) data sources and median catchment area for ephemeral, intermittent, and perennial flow origins from field data collected ir our study. USGS = US Geological Survey, NHD = National Hydrography Dataset, DEM = digital elevation model, FAC = flow accumulation coefficient, ArcHydro® = tools in ArcGIS software. Discussion
TABLE 2. Stream network lengths for Hamilton County, Ohio, based on publically available Geographical Information Syste (GIS) data sources and median catchment area for ephemeral, intermittent, and perennial flow origins from field data collected ir our study. USGS = US Geological Survey, NHD = National Hydrography Dataset, DEM = digital elevation model, FAC = flow accumulation coefficient, ArcHydro® = tools in ArcGIS software. Discussion
Fic. 3. Mean (+1 SE) % urban, forest, and agriculture land cover in a 100-m buffer around randomly selected channel origins within Hamilton County based on the Cincinnati Area Geographic Information System (CAGIS) Cd — map. = p < 0.001 (2-tailed t-test, assuming unequal variances). ment in the Chattooga River watershed in the Blue Ridge Mountains of Georgia, South Carolina, and North Carolina (Hansen 2001). However, Colson et al. (2008) found that accuracy of maps can vary by ecoregion. USGS 1:24,000-scale maps underestimated stream length in the Southwestern Mountain eco region of North Carolina by 54% and overestimated stream length in the Coastal Plain ecoregion by 31% (Colson et al. 2008). This difference could be caused by higher drainage densities in mountains than in ower elevations, or cartographic guidelines tha require minimum lengths and distances from ridges before identifying streams (Drummond 1974, Colson et al. 2008). The substantial underestimation of streams based on nationally available maps can lead o inaccurate scientific understanding of ecosystem processes. For example, riparian buffers calculated
Fic. 3. Mean (+1 SE) % urban, forest, and agriculture land cover in a 100-m buffer around randomly selected channel origins within Hamilton County based on the Cincinnati Area Geographic Information System (CAGIS) Cd — map. = p < 0.001 (2-tailed t-test, assuming unequal variances). ment in the Chattooga River watershed in the Blue Ridge Mountains of Georgia, South Carolina, and North Carolina (Hansen 2001). However, Colson et al. (2008) found that accuracy of maps can vary by ecoregion. USGS 1:24,000-scale maps underestimated stream length in the Southwestern Mountain eco region of North Carolina by 54% and overestimated stream length in the Coastal Plain ecoregion by 31% (Colson et al. 2008). This difference could be caused by higher drainage densities in mountains than in ower elevations, or cartographic guidelines tha require minimum lengths and distances from ridges before identifying streams (Drummond 1974, Colson et al. 2008). The substantial underestimation of streams based on nationally available maps can lead o inaccurate scientific understanding of ecosystem processes. For example, riparian buffers calculated
TABLE 3. Comparison of mean catchment areas draining to ephemeral, intermittent, and perennial flow origins between forested and urban catchments (2-tailed t-test assuming unequal variances). Flow accumulation coefficients (FAC) were calculated from catchment areas based on a formula (see text) and were used to generate county-level stream networks using ArcHydro® tools in ArcGIS. Stream network length includes the entire network below flow origins; i.e., the length indicated under ephemeral includes ephemeral, intermittent, and perennial streams, and the length under intermittent includes intermittent and perennial streams. Drainage density (Dd) was calculated based on stream lengths and total area for Hamilton County, Ohio. natural settings) because locations of origins are related to local headcuts, bedrock, springs, and other site-specific variables (Adams and Spotila 2005). Thus, precise locations of origins are not likely to be mapped accurately and consistently from regional landscape variables. However, locations of origins might be easily and more accurately predicted in some regions, such as areas strongly influenced by groundwater. from coarse-scale maps overestimated buffer preva- lence and led to artificially high estimates of water- shed-scale nutrient retention potential (Baker et al. 2007). In regions where headwater streams have retained their forested buffers, coarse-scale maps could underestimate riparian buffers. Accurate delin- eation of stream networks also is a critical first step for identifying anthropogenic impacts within catchments and developing watershed management plans that protect headwater streams and, thus, downstream ecosystems.
TABLE 3. Comparison of mean catchment areas draining to ephemeral, intermittent, and perennial flow origins between forested and urban catchments (2-tailed t-test assuming unequal variances). Flow accumulation coefficients (FAC) were calculated from catchment areas based on a formula (see text) and were used to generate county-level stream networks using ArcHydro® tools in ArcGIS. Stream network length includes the entire network below flow origins; i.e., the length indicated under ephemeral includes ephemeral, intermittent, and perennial streams, and the length under intermittent includes intermittent and perennial streams. Drainage density (Dd) was calculated based on stream lengths and total area for Hamilton County, Ohio. natural settings) because locations of origins are related to local headcuts, bedrock, springs, and other site-specific variables (Adams and Spotila 2005). Thus, precise locations of origins are not likely to be mapped accurately and consistently from regional landscape variables. However, locations of origins might be easily and more accurately predicted in some regions, such as areas strongly influenced by groundwater. from coarse-scale maps overestimated buffer preva- lence and led to artificially high estimates of water- shed-scale nutrient retention potential (Baker et al. 2007). In regions where headwater streams have retained their forested buffers, coarse-scale maps could underestimate riparian buffers. Accurate delin- eation of stream networks also is a critical first step for identifying anthropogenic impacts within catchments and developing watershed management plans that protect headwater streams and, thus, downstream ecosystems.
Fic. 5. Total ephemeral, intermittent, and perennial channel length within Hamilton County, Ohio, based on modeled stream networks corresponding to mean flow accumulation coefficients (FAC) for forested vs urban catchments. Numbers above bars indicate the absolute and % difference in channel length in forested and urban catchments.
Fic. 5. Total ephemeral, intermittent, and perennial channel length within Hamilton County, Ohio, based on modeled stream networks corresponding to mean flow accumulation coefficients (FAC) for forested vs urban catchments. Numbers above bars indicate the absolute and % difference in channel length in forested and urban catchments.
TABLE 4. Comparison of catchment area and channel cross-sectional area at channel and ephemeral, intermittent, and perennial flow origins with and without pipes (2-tailed t-test assuming unequal variances). Entrenchment ratio is flood-prone width (width at 2X bankfull height) divided by bankfull width. Entrenchment ratios were limited to <2.2. na = not applicable. stream drainage density, connectivity, and flow. For particularly large catchments, researchers could con- sider mapping streams initially based on empirical formulas (e.g., from our study for eastern US streams) and conducting field surveys to adjust actual loca- tions. data). An alternative to point surveys is long-term, continuous monitoring of the presence and duration of flow (as done by Svec et al. 2005), which should accurately determine hydrologic permanence of headwater streams and eliminate some of the prob lems of intra- and interannual variability. However gauges placed at single points in a catchment cannot capture longitudinal differences in permanence with in stream networks. Geomorphic and _biologica indicators also could be used as surrogate measures of hydrologic permanence. For example, the North Carolina Division of Water Quality assigns point values to geomorphic, hydrologic, and biologic characteristics of the stream reach to classify streams as intermittent and perennial (NCDWQ 2005). How- ever, these alternatives are more time-consuming and expensive than the approach we used, and these problems minimize their usefulness for large geo- graphic areas. Last, our methods did not account for situations in which long sections of channel down- stream of flowing reaches are dry (i.e., discontinuous or interrupted surface flow). In a temporal assessment of flow in headwater streams, Hunter et al. (2005) found no predictable pattern of longitudinal drying along a stream reach. Instead, dry-season recession typically was characterized by a transition from long segments of surface flow to short segments of dry a
TABLE 4. Comparison of catchment area and channel cross-sectional area at channel and ephemeral, intermittent, and perennial flow origins with and without pipes (2-tailed t-test assuming unequal variances). Entrenchment ratio is flood-prone width (width at 2X bankfull height) divided by bankfull width. Entrenchment ratios were limited to <2.2. na = not applicable. stream drainage density, connectivity, and flow. For particularly large catchments, researchers could con- sider mapping streams initially based on empirical formulas (e.g., from our study for eastern US streams) and conducting field surveys to adjust actual loca- tions. data). An alternative to point surveys is long-term, continuous monitoring of the presence and duration of flow (as done by Svec et al. 2005), which should accurately determine hydrologic permanence of headwater streams and eliminate some of the prob lems of intra- and interannual variability. However gauges placed at single points in a catchment cannot capture longitudinal differences in permanence with in stream networks. Geomorphic and _biologica indicators also could be used as surrogate measures of hydrologic permanence. For example, the North Carolina Division of Water Quality assigns point values to geomorphic, hydrologic, and biologic characteristics of the stream reach to classify streams as intermittent and perennial (NCDWQ 2005). How- ever, these alternatives are more time-consuming and expensive than the approach we used, and these problems minimize their usefulness for large geo- graphic areas. Last, our methods did not account for situations in which long sections of channel down- stream of flowing reaches are dry (i.e., discontinuous or interrupted surface flow). In a temporal assessment of flow in headwater streams, Hunter et al. (2005) found no predictable pattern of longitudinal drying along a stream reach. Instead, dry-season recession typically was characterized by a transition from long segments of surface flow to short segments of dry a
TABLE 5. Best-supported linear regression models predicting log(x)-transformed catchment area for channel origins, and ephemeral, intermittent, and perennial flow origins after model comparisons with Akaike’s Information Criterion. Adjusted r values (bold) are reported for whole models. Relief ratio and road density were log(x)-transformed; % forest land cover (% forest) was arcsine(,[x])-transformed. areas with scattered pools. Despite these caveats, the random sampling and methods of on-the-ground observation used in our study were cost-effective, enabled us to gather data efficiently over a wide area, and allowed us to estimate the locations of ephemeral, intermittent, and perennial streams. However, the methods should be tested elsewhere to determine their appropriateness and to test the generality of the predictive models in other regions of the world. have arisen because developments typically occur on flatter landscapes, which have naturally larger catch- ments. However, the correlation between relief ratio and urban land cover was weak (r = —0.33, n = 240). The loss of ephemeral and intermittent stream length also might be a consequence of increased flow in urban areas. For example, naturally ephemeral or intermittent streams could become perennial if flow increased. However, our study was not designed to distinguish among the causes of reductions of channel length, and hydrologic monitoring would be neces- sary to understand changes in baseflow hydrology with urbanization.
TABLE 5. Best-supported linear regression models predicting log(x)-transformed catchment area for channel origins, and ephemeral, intermittent, and perennial flow origins after model comparisons with Akaike’s Information Criterion. Adjusted r values (bold) are reported for whole models. Relief ratio and road density were log(x)-transformed; % forest land cover (% forest) was arcsine(,[x])-transformed. areas with scattered pools. Despite these caveats, the random sampling and methods of on-the-ground observation used in our study were cost-effective, enabled us to gather data efficiently over a wide area, and allowed us to estimate the locations of ephemeral, intermittent, and perennial streams. However, the methods should be tested elsewhere to determine their appropriateness and to test the generality of the predictive models in other regions of the world. have arisen because developments typically occur on flatter landscapes, which have naturally larger catch- ments. However, the correlation between relief ratio and urban land cover was weak (r = —0.33, n = 240). The loss of ephemeral and intermittent stream length also might be a consequence of increased flow in urban areas. For example, naturally ephemeral or intermittent streams could become perennial if flow increased. However, our study was not designed to distinguish among the causes of reductions of channel length, and hydrologic monitoring would be neces- sary to understand changes in baseflow hydrology with urbanization.
TABLE 6. Linear regression models predicting catchment area for channel and ephemeral, intermittent, and perennial flow origins. Models were compared usi Akaike’s Information Criterion for small sample size (AIC,). Akaike weights (7w;) indicate the relative support for each model type. Asterisks indicate the best mo: for each stream type (AAIC. = 0), and bold indicates equally plausible models (AAIC, < 2). k is the number of parameters, including the intercept and resid variance. Relief = relief ratio, soil = soil depth, road = road density, sewer = sewer density, septic = septic density, urban = % urban land cover, agriculture = agricultural land cover, forest = % forest land cover.
TABLE 6. Linear regression models predicting catchment area for channel and ephemeral, intermittent, and perennial flow origins. Models were compared usi Akaike’s Information Criterion for small sample size (AIC,). Akaike weights (7w;) indicate the relative support for each model type. Asterisks indicate the best mo: for each stream type (AAIC. = 0), and bold indicates equally plausible models (AAIC, < 2). k is the number of parameters, including the intercept and resid variance. Relief = relief ratio, soil = soil depth, road = road density, sewer = sewer density, septic = septic density, urban = % urban land cover, agriculture = agricultural land cover, forest = % forest land cover.
Fic. 6. Scatter plots between catchment area and relief ratio for channel (A), and ephemeral (B), intermittent (C), and perennial D) flow origins in Eastern Corn Belt Plains and Interior Plateau Omernik Type III ecoregions.
Fic. 6. Scatter plots between catchment area and relief ratio for channel (A), and ephemeral (B), intermittent (C), and perennial D) flow origins in Eastern Corn Belt Plains and Interior Plateau Omernik Type III ecoregions.
Fic. 7. Conceptual representation of study results. Urbanization results in a loss of ephemeral (dotted lines) and intermitten‘ (dashed lines) stream length through channel burial/piping, as indicated by larger drainage areas. Perennial catchments are smaller in nonforested areas, associated with an increase in channel length (solid lines) resulting from reduced evapotranspiration
Fic. 7. Conceptual representation of study results. Urbanization results in a loss of ephemeral (dotted lines) and intermitten‘ (dashed lines) stream length through channel burial/piping, as indicated by larger drainage areas. Perennial catchments are smaller in nonforested areas, associated with an increase in channel length (solid lines) resulting from reduced evapotranspiration
Related topics:
HydrologyEcology
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved