Stream Classification System Research Articles

Assessment of physical condition and anthropogenic disturbance of streams of the northcentral United States

The recent introduction of large geospatial databases and virtual measurement devices for streams of the United States have the potential to greatly improve stream classification systems as well as answer fundamental questions about river morphology. The physical condition of over 800 streams of the adjoining Upper Midwest and Temperate Plains ecoregions of the northcentral US were analyzed using principle components analysis of 10 selected site variables. Delineation was along three axes, with the first axis corresponding to differences in base flow, temperature, and soil permeability; the second corresponding to stream gradient, depth to bedrock and water table, and composite topographic index; and the third corresponding to stream sinuosity. Separation of streams into the two ecoregions was distinct, and primarily along axis 1. Adding a secondary matrix of 10 anthropogenic and geographic predictor variables produced a similar ecoregional separation, with latitude, percent of non-native plants, and overall intact habitat corresponding with axis 1. Natural and anthropogenic differences in streams of these two ecoregions appear inexorably linked, a situation probably common throughout the developed world.

Using the Rosgen Stream Classification System to Aid in Riparian Complex Ecological Site Descriptions Development

Land managers need consistent terminology and classification frameworks to discuss the ecological status of the land. A common framework used in upland terrestrial systems is an ecological site description (ESD), in which systems are categorized by soils, vegetation, and topography. Creating ESDs in riparian areas must follow a different framework than upland systems because function of riparian systems is driven by hydrology. This study categorized riparian areas by hydrology using stream geomorphology and the Rosgen Stream Classification System. Stream cross sectional and longitudinal profile data were collected from 75 reaches from 19 streams in North Dakota from 2012 to 2018. Each reach (i.e., one full meander) was classified by channel type (E, C, B, F, and G), and stability class (stable and unstable). A stream parameter matrix was constructed using entrenchment ratio, width-to-depth ratio, sinuosity, slope, channel bed material, bank height ratio, and meander width ratio. A multiple response permutation procedure showed that the parameters differed on the basis of both channel type and stability class. An indicator analysis showed that entrenchment ratio, bank height ratio, and meander width ratio were the parameters most influential in separating the reaches by stability class. The strongest indicator stable reach was entrenchment ratio, but meander width ratio and bank height ratio were also significant indicators of stable and unstable reaches, respectively. The parameters used in this study to delineate channel type can be used to consistently discriminate between stable and unstable channels. This information may be a useful tool in describing the states and transitions of prairie stream development in riparian complex ESDs, validating the continued use of Rosgen Stream Classification System in ESD development.

The stream evolution triangle: Integrating geology, hydrology, and biology

AbstractThe foundations of river restoration science rest comfortably in the fields of geology, hydrology, and engineering, and yet, the impetus for many, if not most, stream restoration projects is biological recovery. Although Lane's stream balance equation from the mid‐1950s captured the dynamic equilibrium between the amount of stream flow, the slope of the channel, and the amount and calibre of sediment, it completely ignored biology. Similarly, most of the stream classification systems used in river restoration design today do not explicitly include biology as a primary driver of stream form and process. To address this omission, we cast biology as an equal partner with geology and hydrology, forming a triumvirate that governs stream morphology and evolution. To represent this, we have created the stream evolution triangle, a conceptual model that explicitly accounts for the influences of geology, hydrology, and biology. Recognition of biology as a driver leads to improved understanding of reach‐scale morphology and the dynamic response mechanisms responsible for stream evolution and adjustment following natural or anthropogenic disturbance, including stream restoration. Our aim in creating the stream evolution triangle is not to exclude or supersede existing stream classifications and evolutionary models but to provide a broader “thinking space” within which they can be framed and reconsidered, thus facilitating thought outside of the alluvial box.

A stream classification system for the conterminous United States

Stream classifications are important for understanding stream ecosystem diversity while also serving as tools for aquatic conservation and management. With current rates of land and riverscape modification within the United States (US), a comprehensive inventory and evaluation of naturally occurring stream habitats is needed, as this provides a physical template upon which stream biodiversity is organized and maintained. To adequately represent the heterogeneity of stream ecosystems, such a classification needs to be spatially extensive where multiple stream habitat components are represented at the highest resolution possible. Herein, we present a multi-layered empirically-driven stream classification system for the conterminous US, constructed from over 2.6 million stream reaches within the NHDPlus V2 stream network. The classification is based on emergent natural variation in six habitat layers meaningful at the stream-reach resolution: size, gradient, hydrology, temperature, network bifurcation, and valley confinement. To support flexibility of use, we provide multiple alternative approaches to developing classes and report uncertainty in classes assigned to stream reaches. The stream classification and underlying data provide valuable resources for stream conservation and research.

Investigating the geomorphic characteristics of an Amazonian headwater stream draining a páramo ecosystem

ABSTRACTPáramos are neotropical alpine grasslands located in the northern Andes of South America. Although they cover important headwater regions, little is known about the hydro-geomorphic characteristics of páramo river systems, which are increasingly being impacted by human use and climate change. The objective of this research is to characterize the geomorphology of the Ningar River, Ecuador, an Amazonian headwater river that drains a 22.7 km2 páramo sub-basin, by (1) classifying the geomorphology based on common geomorphic classifications, (2) deriving downstream hydraulic geometry relationships, and (3) performing a global comparison with mountain river systems. Common geomorphic field surveying techniques were used to acquire the necessary data. Results suggest that the Ningar River has similar form-function characteristics as other known mountain headwater streams and corresponds to commonly known stream classification systems, but displays more of an alluvial character than might be expected for montane headwater streams as a result of a convexity in the stream’s longitudinal profile. Additionally, preliminary analyses suggest that other páramo headwater streams may exhibit similar characteristics; thus, the findings of this research are important for future management and protection of these valuable headwater ecosystems.

A stream classification system to explore the physical habitat diversity and anthropogenic impacts in riverscapes of the eastern United States.

Describing the physical habitat diversity of stream types is important for understanding stream ecosystem complexity, but also prioritizing management of stream ecosystems, especially those that are rare. We developed a stream classification system of six physical habitat layers (size, gradient, hydrology, temperature, valley confinement, and substrate) for approximately 1 million stream reaches within the Eastern United States in order to conduct an inventory of different types of streams and examine stream diversity. Additionally, we compare stream diversity to patterns of anthropogenic disturbances to evaluate associations between stream types and human disturbances, but also to prioritize rare stream types that may lack natural representation in the landscape. Based on combinations of different layers, we estimate there are anywhere from 1,521 to 5,577 different physical types of stream reaches within the Eastern US. By accounting for uncertainty in class membership, these estimates could range from 1,434 to 6,856 stream types. However, 95% of total stream distance is represented by only 30% of the total stream habitat types, which suggests that most stream types are rare. Unfortunately, as much as one third of stream physical diversity within the region has been compromised by anthropogenic disturbances. To provide an example of the stream classification’s utility in management of these ecosystems, we isolated 5% of stream length in the entire region that represented 87% of the total physical diversity of streams to prioritize streams for conservation protection, restoration, and biological monitoring. We suggest that our stream classification framework could be important for exploring the diversity of stream ecosystems and is flexible in that it can be combined with other stream classification frameworks developed at higher resolutions (meso- and micro-habitat scales). Additionally, the exploration of physical diversity helps to estimate the rarity and patchiness of riverscapes over large region and assist in conservation and management.

Featured Collection Introduction: North Carolina Ecological Flows

Featured Collection Introduction: North Carolina Ecological Flows

Evaluating Flow Metric-Based Stream Classification Systems to Support the Determination of Ecological Flows in North Carolina

Hydroecological classification systems are typically based on an assemblage of streamflow metrics and seek to divide streams into ecologically relevant classes. Assignment of streams to classes is suggested as an initial step in the process of establishing ecological flow standards. We used two distinct hydroecological river classification systems available within North Carolina to evaluate the ability of a hydrologic model to assign the same classes as those determined by observed streamflows and to assess the transferability of such systems to ungaged streams. Class assignments were examined by rate of overall matches, rate of class matches, spatial variability in matches, and time period used in class assignment. The findings of this study indicate assignments of stream class: (1) are inconsistent among different classification systems; (2) differ between observed and modeled data; and (3) are sensitive to the period of record within observed data. One clear source of inconsistency/sensitivity in class assignments lies with the use of threshold values for metrics that distinguish stream classes, such that even small changes in metric values can result in different class assignments. Because these two hydroecological classification systems are representative of other classification systems that rely on quantitative decision thresholds, it can be surmised that the use of such systems based on stream flow metrics is not a reliable approach for guiding ecological flow determinations.

Development of stream classification system on tropical areas with statistical approval in Pahang River basin, Malaysia

Development of stream classification system on tropical areas with statistical approval in Pahang River basin, Malaysia

Reservoir Sedimentation and Upstream Sediment Sources: Perspectives and Future Research Needs on Streambank and Gully Erosion.

The future reliance on water supply and flood control reservoirs across the globe will continue to expand, especially under a variable climate. As the inventory of new potential dam sites is shrinking, construction of additional reservoirs is less likely compared to simultaneous flow and sediment management in existing reservoirs. One aspect of this sediment management is related to the control of upstream sediment sources. However, key research questions remain regarding upstream sediment loading rates. Highlighted in this article are research needs relative to measuring and predicting sediment transport rates and loading due to streambank and gully erosion within a watershed. For example, additional instream sediment transport and reservoir sedimentation rate measurements are needed across a range of watershed conditions, reservoir sizes, and geographical locations. More research is needed to understand the intricate linkage between upland practices and instream response. A need still exists to clarify the benefit of restoration or stabilization of a small reach within a channel system or maturing gully on total watershed sediment load. We need to better understand the intricate interactions between hydrological and erosion processes to improve prediction, location, and timing of streambank erosion and failure and gully formation. Also, improved process-based measurement and prediction techniques are needed that balance data requirements regarding cohesive soil erodibility and stability as compared to simpler topographic indices for gullies or stream classification systems. Such techniques will allow the research community to address the benefit of various conservation and/or stabilization practices at targeted locations within watersheds.

남강에 대한 하천분류체계의 적용 연구

하천은 구간에 따라 하도의 지형학적인 특성이 다양하기 때문에 수리 및 하도 특성 평가를 위해서는 하천의 유형을 분류할 필요가 있다. 또한 하도 특성에 대한 정량적 평가체계는 하천 유형의 특성이 반영되어야 한다. 따라서, 본 연구에서는 하천분류체계의 한국 하천에 대한 적용성을 검토하기 위하여 Rosgen의 하천분류체계와 Yamamoto의 하천분류체계를 비교, 분석하였고, 남강을 사례로 그 적용성을 검토하였다. 하천 지형학적인 측면에서 우리나라의 지방 및 국가하천의 평균하상경사와 종적 연속성을 고려하기 위해서는 하천 지형학적인 측면에서 Yamamoto의 하천분류체계가 적용성이 높은 것으로 판단된다. 또한, 하상재료의 측면에서 Rosgen 분류체계가 Yamamoto의 분류체계보다는 하상경사와의 상관성이 낮게 나타났다. 반면에 Yamamoto의 분류체계는 하상경사에 따른 토사분급 (수리분급)을 반영할 수 있는 것으로 확인되었다. 남강에 대하여 얻어진 결과에 의하면, Rosgen의 분류체계로서는 하상경사와 하상재료의 관계로서 하천유형을 분류할 수 없으나, Yamamoto 분류체계는 그 상관성을 입증할 수 있었다. 다만, 자연하천에 대하여 추가적인 적용성 검토가 필요하다. 하도 특성 평가체계에 적용할 수 있는 3개의 하천유형을 결정하여 제시하였다. Because streams have a great diversity of morphological features according to their reaches, it is necessary to classify the types of streams in order to assess their characteristics of channel. In addition, a quantitative assessment system for channel characteristics should be reflected in the stream type properties. Therefore, this study compares two stream classification system (Rosgen's and Yamamoto's) to review their applicability on Korean streams, and the two classification systems were applied on the Nam River. In order for the mean bed slope and the longitudinal connectivity of the provincial and national streams to be reflected in the assessment system of channel characteristics, the Yamamoto system is considered highly adaptable in the stream geomorphology side. In addition, it has been found the Rosgen system has a low correlation of bed slope compared to the Yamamoto system in the view of bed materials. On the other hand, the Yamamoto system was found to be capable of reflecting sediment sorting (hydraulic sorting) of the bed slope. According to the results obtained at the Nam River, the Rosgen system could not classify a type of stream by relationship between bed material and bed slope, but the Yamamoto system can verify the correlation of stream type. However, further review is needed with respect to the applicability of natural rivers. Three types of stream that can be applied to the assessment system of channel characteristics were proposed.

Ecohydrological model parameter selection for stream health evaluation

Variable selection is a critical step in development of empirical stream health prediction models. This study develops a framework for selecting important in-stream variables to predict four measures of biological integrity: total number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa, family index of biotic integrity (FIBI), Hilsenhoff biotic integrity (HBI), and fish index of biotic integrity (IBI). Over 200 flow regime and water quality variables were calculated using the Hydrologic Index Tool (HIT) and Soil and Water Assessment Tool (SWAT). Streams of the River Raisin watershed in Michigan were grouped using the Strahler stream classification system (orders 1–3 and orders 4–6), k-means clustering technique (two clusters: C1 and C2), and all streams (one grouping). For each grouping, variable selection was performed using Bayesian variable selection, principal component analysis, and Spearman's rank correlation. Following selection of best variable sets, models were developed to predict the measures of biological integrity using adaptive-neuro fuzzy inference systems (ANFIS), a technique well-suited to complex, nonlinear ecological problems. Multiple unique variable sets were identified, all which differed by selection method and stream grouping. Final best models were mostly built using the Bayesian variable selection method. The most effective stream grouping method varied by health measure, although k-means clustering and grouping by stream order were always superior to models built without grouping. Commonly selected variables were related to streamflow magnitude, rate of change, and seasonal nitrate concentration. Each best model was effective in simulating stream health observations, with EPT taxa validation R2 ranging from 0.67 to 0.92, FIBI ranging from 0.49 to 0.85, HBI from 0.56 to 0.75, and fish IBI at 0.99 for all best models. The comprehensive variable selection and modeling process proposed here is a robust method that extends our understanding of watershed scale stream health beyond sparse monitoring points.

Mining recurring concepts in a dynamic feature space.

Most data stream classification techniques assume that the underlying feature space is static. However, in real-world applications the set of features and their relevance to the target concept may change over time. In addition, when the underlying concepts reappear, reusing previously learnt models can enhance the learning process in terms of accuracy and processing time at the expense of manageable memory consumption. In this paper, we propose mining recurring concepts in a dynamic feature space (MReC-DFS), a data stream classification system to address the challenges of learning recurring concepts in a dynamic feature space while simultaneously reducing the memory cost associated with storing past models. MReC-DFS is able to detect and adapt to concept changes using the performance of the learning process and contextual information. To handle recurring concepts, stored models are combined in a dynamically weighted ensemble. Incremental feature selection is performed to reduce the combined feature space. This contribution allows MReC-DFS to store only the features most relevant to the learnt concepts, which in turn increases the memory efficiency of the technique. In addition, an incremental feature selection method is proposed that dynamically determines the threshold between relevant and irrelevant features. Experimental results demonstrating the high accuracy of MReC-DFS compared with state-of-the-art techniques on a variety of real datasets are presented. The results also show the superior memory efficiency of MReC-DFS.

Comparing the performance of different stream classification systems using aquatic macroinvertebrates

AIM: We evaluated five stream classification systems observing: 1) differences in richness, abundance and macroinvertebrates communities among stream classes within classification systems; and 2) whether classification systems present better performance using macroinvertebrates. Additionally, we evaluated the effects of taxonomic resolution and data type (abundance and presence) on results. METHODS: Five stream classification systems were used, two based on hydroregions, one based on ecoregions by FEOW, a fourth one based on stream orders and the last one based on clusters of environment variables sampled in 37 streams at Rio Grande do Sul state, Brazil. We used a randomization test to evaluate differences of richness and abundance, a db-MANOVA to evaluate the differences of species assemblages and Classification Strength (CS) to evaluate the classifications performance. RESULTS: There were differences of richness and abundance among stream classes within each stream classification. The same result was found for community data, except for stream order classifications in family level. We observed that stream classes obtained for each stream classification differed in terms of environment variables (db-MANOVA). The classification based on environment variables showed higher CS values than other classification systems. The taxonomic resolution was important to the observed results. Data on genera level presented CS values 12% higher than family level for cluster classification, and the data type was dependent on the classification system and taxonomic resolution employed. CONCLUSION: Our results indicate that classifications based on cluster of environment variables was better than other stream classification systems, and similar results using genera level can be obtained for management programs using family resolution in a geographical context similar to this study.

Towards a Stream Classification System for the Canadian Prairie Provinces

Temporary streams on the Canadian Prairies have a dry streambed with some regularity. Attributes that capture these zero flows could be used to better compare temporary streams with perennial streams from the same area, and contribute to a broader stream classification. This case study of observed variability in flow rates of prairie streams is a step towards the goal of establishing a stream classification system that would be widely useful for practitioners who need to address prediction in ungauged basins in this region. Such a classification system could support inferences that need to be made for streams that are either not currently gauged or for which the period of record is either too short or too discontinuous to allow an understanding of the potential streamflow responses. An approach to streamflow classification that relies solely on hydrometric record may be of particular value for temporary streams that are common in the southern Canadian Prairie Provinces. Similarity of hydrometric station streamflow response within groups is illustrated using both common techniques such cumulative annual and daily mass curve analysis, and a novel streamflow metric, the ratio of the magnitude of the third quartile monthly flow totals to the maximum of the monthly total flow for the period of record is also examined. The purpose of this case study is to demonstrate that by applying conventional analytical techniques in innovative ways the practicing hydrologist can better infer the behavior of streams in areas that are either ungauged, have been gauged only for a short period of time, or are gauged intermittently. While a complete classification system for these streams would include physical, biological, and chemical properties in addition to those that can be determined from hydrometric records, the grouping of hydrologically similar sites is a first step. Such analysis also provides insight into anticipated stream response that will allow for improving design and operation of hydrometric networks. The analysis presented is restricted to data from the Canadian Reference Hydrologic Basin Network (RHBN).

Effects of Effluents from a Fisheries Research Station on Stream Water Quality

AbstractResearch ponds at the E. W. Shell Fisheries Center usually overflow only following heavy rains in winter and early spring. Water from the ponds continually seeps into the ground (which has a shallow water table), and the ponds are drained annually in the fall for harvest. Drained effluent had the following average composition: pH, 7.18 (range, 6.5–7.7); total nitrogen, 1.21 mg/L (1.05–1.32 mg/L); total phosphorus, 0.64 mg/L (0.52–0.66 mg/L); 5‐d biochemical oxygen demand (BOD5), 7.7 mg/L (2.1–10.3 mg/L); total suspended solids (TSS), 380 mg/L (61–705 mg/L); turbidity, 367 nephelometric turbidity units (NTU; 152–745 NTU). Compared with the sampling station upstream of the research ponds, the downstream sampling station on Lower Station (LS) Creek had higher average pH and concentrations of total alkalinity, chloride, total nitrogen, and BOD5. The downstream sampling station also had higher concentrations of chloride, TSS, total nitrogen, and BOD5 than four reference streams that did not receive aquaculture effluents. Turbidity and TSS concentration were sometimes higher in LS Creek than is allowable under the Alabama stream classification system. Nevertheless, water quality at the downstream sampling station in LS Creek was better than that in Saugahatchee Creek, into which it discharges. A sedimentation basin installed in the lower reach of LS Creek would lessen TSS concentration and turbidity.

안성천 중소하천의 하천분류 및 2차원 수리특성, 하상변동 모의

본 연구에서는 안성천 유역의 중소하천에 Rosgen(1994)의 하천분류체계를 적용하여 하천을 분류하고, 분류된 하천 유형별로 2차원 수리해석 모형을 이용하여 수리특성 및 하상변동을 모의하였다. 하천분류체계를 안성천 유역의 진위천과 오산천에 적용한 결과 크게 C 유형과 E 유형으로 분류되었다. 분류된 유형의 2차원 수리모형 적용에 따른 수리특성 및 하상변동 분석을 위해 C 유형의 구간 중 진위천과 통삼천의 만곡구간, 공세천, E 유형중 수원천을 연구대상지역으로 선정하였다. 하천분류체계에 의해 선정한 연구대상지역에 대하여 CCHE2D 모형을 이용한 빈도별 홍수량에 따른 하상변동 수치모의를 수행하였다. 모형의 경계입력자료는 WMS HEC-1의 유출량 결과 자료를 이용하여 50, 80, 100년 빈도별 홍수량에 대하여 모의하였다. 모의 결과 비교적 하폭/수심비가 큰 C 유형의 경우 하천의 물리적 특성의 변화에 따른 하상변동의 침식 및 퇴적의 경향이 잘 나타난 것으로 분석 되었고, C 유형에 비해 작은 E 유형의 경우 변화에 따른 하상변동의 경향을 파악 할 수 없었다. 본 연구의 결과는 하천의 물리적 변화에 따른 흐름 및 하상변동을 예측하는 방법에 기초자료를 제공할 수 있을 것으로 판단된다. This study tries to find a streambed scouring and sedimentation characteristics through the Rosgen(1994)'s stream classification system while experiencing several flood events. The Jinwee and Osan streams, the tributaries of Anseongcheon were selected. The streams showed type C or type E. By the classification results, two Type C tributaries one Type C stream and one Type E tributary were selected. For the four selected stream reaches, the analysis of streambed change was implemented by using numerical model CCHE2D (Center for Computational Hydroscience and Engineering). To prepare the inlet boundary conditions of each stream, the WMS (Watershed Modeling System) HEC-1 was used and the streamflows of 50, 80, and 100-year return period were generated and the outlet boundary was set to an open boundary condition. The simulation results showed that when the flood pulse periodically the streambed changes also appears regularly. The results can be used to acquire the basic data for stream restoration.

Effluent volume and pollutant loads at an inland, low-salinity, shrimp farm in Alabama

An inland, low-salinity shrimp farm in Alabama released 50–60% of stored water during harvests in 2008 and 2010. Maximum concentrations of potential pollutants occurred in the final 5% of water discharged from ponds during harvest. Average, weighted concentrations of variables were lower than maximum values, but greater than concentrations in the receiving stream upstream of the farm outfall. Nevertheless, chloride was the only variable for which the concentration found downstream of the farm outfall exceeded the permissible concentration limit of the Alabama stream classification system. Pollutant loads per tonne of shrimp for the 2 years averaged were 444.9kg total suspended solids, 51.3kg 5-day biochemical oxygen demand, 15.2kg total nitrogen, 1.33kg total phosphorus, and 4402kg chloride. Concentrations and loads of most potential pollutants could be lessened by passing farm discharge through a settling basin before final discharge, releasing less water during harvest, and improving the feed conversion ratio.

A River Valley Segment Classification of Michigan Streams Based on Fish and Physical Attributes

AbstractWater resource managers are frequently interested in river and stream classification systems to generalize stream conditions and establish management policies over large spatial scales. We used fish assemblage data from 745 river valley segments to develop a two‐level, river valley segment‐scale classification system of rivers and streams throughout Michigan. Regression tree analyses distinguished 10 segment types based on mean July temperature and network catchment area and 26 segment types when channel gradient was also considered. Nonmetric multidimensional scaling analyses suggested that fish assemblages differed among segment types but were only slightly influenced by channel gradient. Species that were indicative of specific segment types generally had habitat requirements that matched segment attributes. A test of classification strength using fish assemblage data from an additional 77 river valley segments indicated that the classification system performed significantly better than random groupings of river valley segments. Our classification system for river valley segments overcomes several weaknesses of the classifications previously used in Michigan, and our approach may prove beneficial for developing classifications elsewhere.

Linkages among watersheds, stream reaches, and riparian vegetation in dryland ephemeral stream networks

Ephemeral streams are common features of landscapes around the world, and are the predominant fluvial environment in arid zones. Current understanding of dryland riparian ecology is derived primarily from perennial stream environments, and little is known about the factors controlling vegetation along ephemeral streams. This study describes relationships between the physical characteristics of watersheds and stream reaches, and their effects on riparian plant communities, for 14 ephemeral stream reaches in the semi-arid southern Colorado Plateau, USA. Interactions of watershed properties produce gradients of hydro-geomorphic regimes throughout stream networks, which give rise to spatial patterns in the structure and composition of perennial woody plant and grass dominated communities. As watershed and network magnitudes increased, and basin slope decreased, stream reaches exhibited reduced erosive capacities and more attenuated alluvial groundwater variability. Decreased disturbance potential and increased moisture availability in the downstream direction was related to greater abundance of obligate riparian taxa, and increasing structural importance of shrub and tree species. Divisions in watershed and stream reach physical properties corresponded with riparian plant community types, implying that progress in dryland fluvial ecology could be made from research within a watershed or network context. These concepts are integrated to form a stream classification system that describes functional linkages between watersheds, stream reaches, and riparian plant ecology. Type I streams drain watersheds less than 10 km2, exhibit the greatest disturbance potential and most xeric alluvial groundwater regime, and are occupied by upland plant associations. Type II streams have watersheds between 10 and 100 km2, and have more moderate shear stresses and more persistent alluvial groundwater. Plant communities consisting of a mix of upland and riparian species occur in Type II reaches. Type III reaches drain watersheds of more than 100 km2 and hydrologic regimes are controlled mainly by upstream hydro-climatic conditions. These streams have the lowest bankfull shear stresses and perennial water tables that span expansive floodplains. Wetland tree and shrub communities dominate Type III reaches, and upland plants are a minor ecological component.