Hydrological Classification Research Articles

Hydrological classification and performance of Himalayan springs in climate change scenario – a case study

AbstractThe present study was conducted to evaluate 33 springs' hydrology (discharge and yield estimation) of Chandrabhaga and Danda watersheds of Uttarakhand, India. The springs were classified using Meinzer method and evaluated the relative performance for rejuvenation strategy. It was found that most of springs fall in sixth and seventh class order with flow rate 6.5 to 65.5 and 0.8 to 6.5 m3·day−1, respectively. The relative performance of springs were analyzed based on four methods: (i) spring flow variability, (ii) normalized spring flow (short and long duration), (iii) rainfall spring flow lag and (iv) spring flow gradient. The relative results of springs were analyzed on a scale of 0–5. The Chandrabhaga springs 01, 03, 4B, 05, 06 and 13 were found to be relatively good on a scale value of 4 out of 5 as compared to springs 4A, 07, and 10A with a scale value of 1. For the Danda watershed, the relative performance of springs 4A and 28 found on scale value of 5 and springs 4B, 11 and 20 with a scale value of 4 are relatively good compared to springs 02, 06, 07, 15 and 17. The cumulative flow of spring showed a linear response with cumulative rainfall for the period of June to September (monsoon period). The spring-shed was delineated and evaluated for optimization for the maximum efficiency, spring flow, ratio of area and relief versus maximum spring flow yield. The results revealed that the quantification of water fluxes for water balances, storage of groundwater and development of mathematical models can be used for sustainable water resources development and to revive the mountain springs which helped the adverse impacts of climate change.

Mid and long-term hydrological classification forecasting model based on KDE-BDA and its application research

In view of the uncertainties in the current mid and long-term hydrological forecast results, a mid and long-term hydrological classification forecasting model based on KDE-BDA is built and its application research is performed. The kernel density estimation method (KDE) is used to improve the distribution density function estimation method in the conventional Bayesian discriminant method (BDA). Based on this, a mid and long-term hydrological classification prediction model based on KDE-BDA was built. An example of its application is demonstrated in the runoff forecast of the Danjiangkou Reservoir in the autumn of September. The results show that different forecasting factors have different forecasting ability for runoff classification (flood, normal, dry). Among them, the 500hPa height field factor has higher forecasting ability for the Danjiangkou runoff category (flood, normal, dry), and the 100hPa height field factor, SST and circulation characteristics have a good indication of the runoff’s flood state. The results of Half-Brier score show that the combined forecasting model combines the forecasting advantages of each factor, so the forecasting effect is the best. The pass rate in the simulation period was 89.8%, and the pass rate in the inspection period was 87.5%. The simulation and forecast results were relatively stable.

Catchment classification in a transboundary river using runoff and sub-basin characteristics

ABSTRACTTransboundary rivers that run through separate water management jurisdictions with distinct hydrological characteristics sometimes experience competitive water usage. A system of classification of catchments along such river basins could help ease hydrological modelling on subbasin scales and hopefully refine the spatial and temporal resolution of information about adjacent catchments especially under changing natural and anthropogenic influences. However, there exists no universally accepted basis for hydrological classification of catchments. Some studies have applied hydrological models to catchment classification based upon criteria like streamflow regimes, hydrologic similarity, and hydroclimatic factors. But some constraints have included geographic or situational limitations of models, and large numbers of model parameters and data involved. The latter is counterproductive because the main purpose of catchment classification is to decrease the complexity of water systems by grouping them into several like categories. This study performed catchment classification in four different ways (quasi-runoff coefficients, empirical runoff equations, Muskingum-Cunge routing, and exceedance probabilities) in a major transboundary river whose basins sometimes experience water security issues. Using predefined catchment classification criteria and thirteen initial hydrological zones, the results across all four methods revealed five distinct catchment areas and suggest that a combination of different methodology may be needed for reliably classifying catchments. The methodology and information gathered could be used by stakeholders for applications in irrigation planning, river discharge modelling, navigation, flood risk management, improving dam storage and release policies, and optimizing food-water-energy nexus in the region.

Development and application of the soil moisture routing (SMR) model to identify subfield-scale hydrologic classes in dryland cropping systems using the Budyko framework

Crop yield patterns at the field level in dryland agricultural systems often trace back to the spatial structure of water storage and subsurface flow paths. These lateral flow paths create zones of saturation that promote nutrient loss from runoff and leaching beneath the root zone. Despite its clear importance, a spatially explicit representation of landscape hydrology is frequently missing from site-specific crop and fertilizer management plans. This work uses the grid-based water balance model, SMR (soil moisture routing), to adapt an established method of hydrologic classification, the Budyko framework, for small agricultural watersheds. The model was evaluated with spatially distributed soil moisture data and surface runoff measurements in four annually cropped fields located across the eastern Palouse region of the inland Pacific Northwest. The Budyko framework, modified to include change in root zone water storage and lateral flow, was combined with a separate indicator of yield potential to form a dual-threshold classification scheme for variable-rate fertilizer management that balances agronomic benefit with environmental impact. Each field was divided into zones based on crop yield and nitrogen loss potentials, which link to the hydrologic functioning of the landscape through soil water storage and subsurface redistribution, respectively. Results showed large variability in the annual water balance assessed within individual fields and between fields. The greatest variability was observed in the two eastern-most fields where the wettest zone of each had water supply 172% and 137% that of the dry zone. Depth to a hydraulic restrictive layer and topography were identified as primary landscape controls on the water supply (precipitation plus net lateral flow minus change in water storage) in these fields. Moreover, the steep climate gradient in the region created field-to-field variability in water balance with the ratio of evapotranspiration to precipitation ranging from 91% in the western-most field to approximately 70% in each of the fields to the east. The clearest choice is for growers to apply more fertilizer in areas with high water storage capacity and high crop yield and where fertilizer loss through leaching and runoff is minimal. Less fertilizer should be applied in areas with low water storage capacity that frequently saturate. Areas with high storage capacity and frequent saturation involve a tradeoff between yields and minimizing fertilizer loss that may be best served by splitting fertilizer application to avoid excessive over-winter leaching losses. Even though remote sensing and variable-rate applicators are at the frontiers of precision agriculture, landscape hydrology underlies all dryland crop production and should accordingly be looked to for inspiration in the design of cropping systems.

Unsupervised hydrologic classification of rivers: Watershed controls on natural and anthropogenic flow regimes, Alabama, USA

AbstractWatershed hydrology has often focused on modelling studies of individual watersheds, which consider each river system as unique. Classification is an alternative approach that instead focuses on the similarities among different watersheds. Although both supervised and unsupervised hydrologic classifications have been developed, few previous studies have used classification to assess the degree of anthropogenic modification of hydrologic regime. Here, we conducted an unsupervised hydrologic classification of 189 U.S. Geological Survey gages, including 41 minimally impacted gages from the Hydro‐Climatic Data Network (HCDN), in the five major interstate river basins in the U.S. state of Alabama. For the natural classification, the most significant predictor variables for cluster membership were related to compressive strength of bedrock, bedrock depth, hydraulic conductivity, elevation, temperature, and soil texture, and several land‐cover variables were also significant in the anthropogenic classification. We then developed two random‐forest models: one based on all 189 gages using both natural and anthropogenic variables from the Stream‐Catchment (StreamCat) dataset and one based on the 41 HCDN gages using natural StreamCat variables only. We used the random‐forest models to predict natural and anthropogenic normative hydrologic class for over 158,000 National Hydrography Dataset Plus catchments in the study area. Catchments that changed their class between the natural and anthropogenic classifications can be identified as those that have a large amount of anthropogenic influences on their hydrologic regime, including many catchments on the coast, in the north‐western Coastal Plain, in the Interior Low Plateaus, and in the Piedmont. Using unsupervised hydrologic classifications is a promising approach for uncovering the physical processes that affect hydrologic regime. There are also potential applications in river management, including predicting the hydrologic behaviour of ungaged watersheds, identifying relatively unimpaired rivers to serve as conservation and restoration targets, and regionalization of environmental instream flow standards and climate‐change impacts.

Application of Regression Models on Panel Data in the Regional Analysis of Water Consumption

Water is a core component of the nature environment. The problem of good quality water supply to the humans has been aggravating because the available resources of fresh water in some regions of the planet proved to be insufficient for satisfying all the consumer needs. Lack of fresh water has been a structural factor affecting the global economic development, with drinking water acquiring the characteristics of a strategic commodity. These circumstances raise the importance of solutions on saving fresh water resources and ways of their rational use from the local level to the global one.
 The article contains a description of the current situation with water supply and water consumption in Ukraine. As regards water supply, Ukraine, according to the hydrological classification, is undergoing water stress, in parallel with extra water consumption and high water intensity in the domestic production sector.
 The subject of the study is water intensity of the gross domestic product, its main factors and ways of reduction. The object of the study is seven Ukrainian regions across which the river Dnieper flows, and the city of Kyiv. A significant variation of water intensity is observed in administrative and territorial units located in the Dnieper basin, which is caused by the varying industrial capacities, varying systems of technical water supply at industrial enterprises, and varying scopes of fresh water use in water supply for agricultural and utility needs, lack of advanced systems for water supply in some of the regions, which causes large losses of water and high water intensity in some production facilities.
 The impact from the above mentioned factors on the regional water intensity is assessed by the regression model on panel data. The specific conditions of the business operation in some regions of the Dnieper basin are represented in the model by dummy variables. By the model of water intensity of GDP, the largest one is the impact from industrial specialization of a region (especially Dnipropetrovsk, Zaporizhzhia, Kyiv and Kherson regions), the existence of water recycling systems at industrial enterprises, scopes of water drainage and capacities of sewage treatment plants.
 Effective use, rehabilitation and protection of water resources, improvement of water quality, and reduction of water intensity in the production facilities through taking technological and economic measures in water consumption are considered as important factors of the national security.

A Quantitative Hydrological Climate Classification Evaluated With Independent Streamflow Data

AbstractClassification is essential in the study of natural systems, yet hydrology has no formal way to structure the climatic forcing that underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might need. This work presents a hydrologically informed way to quantify global climates, explicitly addressing the shortcomings in earlier climate classifications. In this work, causal factors (climate) and hydrologic response (streamflow) are separated, meaning that our classification scheme is based only on climatic information and can be evaluated with independent streamflow data. Using gridded global climate data, we calculate three dimensionless indices per grid cell, describing annual aridity, aridity seasonality, and precipitation‐as‐snow. We use these indices to create several climate groups and define the membership degree of 1,103 catchments to each of the climate groups, based on each catchment's climate. Streamflow patterns within each group tend to be similar, and tend to be different between groups. Visual comparison of flow regimes and Wilcoxon two‐sample statistical tests on 16 streamflow signatures show that this index‐based approach is more effective than the often‐used Köppen‐Geiger classification for grouping hydrologically similar catchments. Climate forcing exerts a strong control on typical hydrologic response and we show that at the global scale both change gradually in space. We argue that hydrologists should consider the hydroclimate as a continuous spectrum defined by the three climate indices, on which all catchments are positioned and show examples of this in a regionalization context.

A Hydrological Sensor Web Ontology Based on the SSN Ontology: A Case Study for a Flood

Accompanying the continuous development of sensor network technology, sensors worldwide are constantly producing observation data. However, the sensors and their data from different observation platforms are sometimes difficult to use collaboratively in response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains.

The influence of flow permanence and drying pattern on macroinvertebrate biomonitoring tools used in the assessment of riverine ecosystems

Temporary rivers comprise a significant proportion of river networks globally and their prevalence is expected to increase as a result of future climate change and anthropogenic water resource pressures. Despite this, the influence of drying events on freshwater biomonitoring tools within temporary rivers has received limited research attention within temperate environments. This study examines the effects of flow permanence and longitudinal drying patterns on selected biomonitoring indices used within the United Kingdom to assess the ecological status of waterbodies within the context of the Water Framework Directive. These indices are based on faunal tolerances and preferences to nutrient enrichment (BMWP, ASPT and Ntaxa) and flow velocity (Family LIFE). Long-term biomonitoring data from four rivers within southern England were examined, two of which dry longitudinally from the headwaters and two that dry within the mid-reaches. The results demonstrate that all of the biomonitoring indices examined differed significantly between each ‘hydrological class’ (i.e. temporary versus perennial reaches), with those based on absolute scores (BMWP and Ntaxa) displaying greater differences compared to those derived using scores standardized by the number of taxa recorded (ASPT and Family LIFE). The individual influence of drying pattern did not have a significant effect on any biomonitoring index. However, the interaction between the hydrological class and drying pattern significantly influenced all biomonitoring indices, indicating that the effect of flow intermittency on the metrics examined differed between drying patterns. Flow permanence explained a greater amount of statistical variation compared to the hydrological class and highlights the importance of the duration of flowing conditions on biomonitoring indices. The results indicate that flow intermittency has a significant effect on freshwater biomonitoring tools and highlights the need to incorporate this knowledge into existing management and environmental policy frameworks to prevent the misclassification of the ecological status of temporary streams.

Redetermining the curve number of Korean forest according to hydrologic condition class

The SCS-CN (Soil Conservation Service-Curve Number) method has been practically applied for estimating the effective precipitation. The CN is used to be determined according to the land use condition based on the US standard. However, there are two distinctive differences between U.S. and Korean land use conditions: mountainous (forest) and rice paddy area that cover more than 70% of the Korean territory. The previous work proposed to use 79 for rice paddy area, regardless of the soil type. Because US SCS’s goal was originally to increase crops, the SCS classification standard provides only for woods and there are no criteria to distinguish the wood and forest. To determine the CN for forest, alternatively the U.S. Forest Service criteria have been employed in practice considering hydrologic condition class. In this study, we investigated the change of the forest CN using the observed rainfall - runoff data within the target area. The results indicated that the CN for forest was suitable for HC=1, and the corresponding CNs were redetermined between 54 and 55.

Exploring hydrologically similar catchments in terms of the physical characteristics of upstream regions

Abstract Catchment classification strategies based on easily available physical characteristics are important for extrapolating hydrologic model parameters and improving hydrologic predictions in ungauged catchments. In this study, we conduct an experiment of catchment classification and explore the feasibility of characterizing hydrologically similar catchments using certain physical characteristics in upstream regions of the Huai River Basin. The similarity metrics of hydrologic response factors (high flow, low flow and average annual runoff) and physical factors (topography, shape, soil and vegetation) are fed into the K-means algorithm for catchment classification. All the catchments are classified into two classes regardless of the types of metrics used. By comparing the overlap coefficient (η) and Rand index (RI) between any two classification results, we found that the topography classification displays the highest concordance with the high flow classification (η = 79.2% and RI = 0.66) among all metrics. Including more metrics would not produce consistently better classification results. The optimal combination of metrics, with η = 87.5%, is the high flow metrics (Q10%, SFH and MAX90) with the topography metrics (AS and HI). The results indicate that the physical metrics adopted for hydrologic classification should be determined carefully in terms of specific hydrologic characteristics.

Revealing the Diversity of Natural Hydrologic Regimes in California with Relevance for Environmental Flows Applications

AbstractAlterations to flow regimes for water management objectives have degraded river ecosystems worldwide. These alterations are particularly profound in Mediterranean climate regions such as California with strong climatic variability and riverine species highly adapted to the resulting flooding and drought disturbances. However, defining environmental flow targets for Mediterranean rivers is complicated by extreme hydrologic variability and often intensive water management legacies. Improved understanding of the diversity of natural streamflow patterns and their spatial arrangement across Mediterranean regions is needed to support the future development of effective flow targets at appropriate scales for management applications with minimal resource and data requirements. Our study addresses this need through the development of a spatially explicit reach‐scale hydrologic classification for California. Dominant hydrologic regimes and their physio‐climatic controls are revealed, using available unimpaired and naturalized streamflow time‐series and generally publicly available geospatial datasets. This methodology identifies eight natural flow classes representing distinct flow sources, hydrologic characteristics, and catchment controls over rainfall‐runoff response. The study provides a broad‐scale hydrologic framework upon which flow‐ecology relationships could subsequently be established towards reach‐scale environmental flows applications in a complex, highly altered Mediterranean region.

Identifying Small Depressional Wetlands and Using a Topographic Position Index to Infer Hydroperiod Regimes for Pond-Breeding Amphibians

Small, seasonal pools and temporary ponds (<4.0 ha) are the most numerous and biologically diverse wetlands in many natural landscapes. Thus, accurate determination of their numbers and spatial characteristics is beneficial for conservation and management of biodiversity associated with these freshwater systems. We examined the utility of a topographic position index (TPI) landscape classification to identify and classify depressional wetlands. We also assessed relationships between topographic characteristics and ponded duration of known wetlands to allow hydrological characteristics to be extended to non-monitored locations in similar landscapes. Our results indicate that this approach was successful at identifying wetlands, but did have higher errors of commission (10%) than omission (5%). Additionally, the TPI procedure provided a reasonable means to correlate general ponded duration characteristics (long/short) with wetland topography. Although results varied by hydrologic class, permanent/long ponded duration wetlands were more often classified correctly (80%) than were short ponded duration wetlands (67%). However, classification results were improved to 100 and 75% for permanent/long and short ponded duration wetlands, respectively, by removing wetlands occurring on an abrupt marine terrace that erroneously inflated pond topographic characteristics. Our study presents an approach for evaluating wetland suitability for species or guilds that are associated with key habitat characteristics, such as hydroperiod.

Improving Curve Number Runoff Estimates Using Dual Hydrologic Soil Classification and Potential Contributing Source Areas Delineation Methods

Runoff models such as the Curve Number (CN) model are dependent upon land use and soil type within the watershed or contributing area. In regions with internal drainage (e.g. wetlands) watershed delineation methods that fill sinks can result in inaccurate contributing areas and estimations of runoff from models such as the CN model. Two methods to account for this inaccuracy have been 1) to adjust the initial abstraction value within the CN model; or 2) to improve the watershed delineation in order to better account for internal drainage. We used a combined approach of examining the watershed delineation, and refining the CN model by the incorporating of dual hydrologic soil classifications. For eighteen watersheds within Wisconsin, we compared the CN model results of three watershed delineation methods to USGS gaged values. We found that for large precipitation events (>100 mm) the CN model estimations are closer to observed values for watershed delineations that identify the directly connected watershed and use the undrained hydrologic soil classification.

Does stream flow structure woody riparian vegetation in subtropical catchments?

The primary objective of this study was to test the relevance of hydrological classification and class differences to the characteristics of woody riparian vegetation in a subtropical landscape in Queensland, Australia. We followed classification procedures of the environmental flow framework ELOHA – Ecological Limits of Hydrologic Alteration. Riparian surveys at 44 sites distributed across five flow classes recorded 191 woody riparian species and 15, 500 individuals. There were differences among flow classes for riparian species richness, total abundance, and abundance of regenerating native trees and shrubs. There were also significant class differences in the occurrence of three common tree species, and 21 indicator species (mostly native taxa) further distinguished the vegetation characteristics of each flow class. We investigated the influence of key drivers of riparian vegetation structure (climate, depth to water table, stream‐specific power, substrate type, degree of hydrologic alteration, and land use) on riparian vegetation. Patterns were explained largely by climate, particularly annual rainfall and temperature. Strong covarying drivers (hydrology and climate) prevented us from isolating the independent influences of these drivers on riparian assemblage structure. The prevalence of species considered typically rheophytic in some flow classes implies a more substantial role for flow in these classes but needs further testing. No relationships were found between land use and riparian vegetation composition and structure. This study demonstrates the relevance of flow classification to the structure of riparian vegetation in a subtropical landscape, and the influence of covarying drivers on riparian patterns. Management of environmental flows to influence riparian vegetation assemblages would likely have most potential in sites dominated by rheophytic species where hydrological influences override other controls. In contrast, where vegetation assemblages are dominated by a diverse array of typical rainforest species, and other factors including broad‐scale climatic gradients and topographic variables have greater influence than hydrology, riparian vegetation is likely to be less responsive to environmental flow management.

Using Nonlinear Dynamic Systems Parameter for Hydrologic Classification of Catchments

Using Nonlinear Dynamic Systems Parameter for Hydrologic Classification of Catchments

Multi-scale Approach to Hydrological Classification Provides Insight to Flow Structure in Altered River System

Rivers are hierarchical systems exhibiting processes and patterns across spatial and temporal scales principally driven by changes in flow. Hydrological indices estimated with mean or median daily flow data (i.e. daily scale) may be insensitive to anthropogenic alteration that imparts sub-daily variation to flow. Therefore, indices developed at multiple temporal resolutions may provide additional insight into the presence of flow patterns masked by traditional techniques. We characterized the flow regime along the longitudinal gradient of the Platte River, a large Great Plains USA river, using hydrological indices derived with mean daily and sub-daily flow data and a combination of multivariate statistical techniques. Three unique flow units were evident using daily scale flow data, whereas six unique flow units were evident at the sub-daily scale. Flow units at both scales were not static, but rather the presence and extent of flow units across the riverscape depended on climate, tributary inflows and human influence. Anthropogenic alteration including hydropeaking was evident at the sub-daily scale but not at the daily scale. The full complement of flow structure within regulated rivers, therefore, may not be captured using mean or median daily discharge values alone. Inductive river classification studies may benefit from assessing hydrological indices at multiple scales, particularly when investigating river systems with anthropogenic modification such as hydropeaking. Copyright © 2016 John Wiley & Sons, Ltd.

Sources of variation in hydrological classifications: Time scale, flow series origin and classification procedure

Summary Classification of flow regimes in water management and hydroecological research has grown significantly in recent years. However, depending on available data and the procedures applied, there may be several credible classifications for a specific catchment. In this study, three inductive classifications derived from different initial flow data and one expert-driven classification were defined. The hydrological interpretation, statistical performance and spatial correspondence of these classifications were compared. Daily Gauged Classification (DC) was derived from daily flow data while Monthly Gauged Classification (MC) and Monthly Modeled Classification (MMC) were derived from monthly flow series, using gauged and modeled flow data, respectively. Expert-Driven Classification (EDC) was based on a Spanish nationwide hydrological classification, which is being used in the current River Basin Management Plans. The results showed that MC accounted for much of the critical hydrological information variability comprised within the DC. However, it also presented limitations regarding the inability to represent important hydroecological attributes, especially those related to droughts and high flow events. In addition, DC and MC presented an equivalent performance more than 60% of the time and obtained a mean ARI value of 0.4, indicating a similar classification structure. DC and MC outperformed MMC 100% and more than 50% of the times when they were compared by means of the classification strength and ANOVA, respectively. MMC also showed low correspondence with these classifications (ARI = 0.20). Thus, the use of modeled flow series should be limited to poorly gauged areas. Finally, the significantly reduced performance and the uneven distribution of classes found in EDC questions its application for different management objectives. This study shows that the selection of the most suitable approach according to the available data has significant implications for the classification uses. Therefore, caution is recommended, especially if classifications are to be use in a normative manner.

Hydrological Classification, a Practical Tool for Mangrove Restoration.

Mangrove restoration projects, aimed at restoring important values of mangrove forests after degradation, often fail because hydrological conditions are disregarded. We present a simple, but robust methodology to determine hydrological suitability for mangrove species, which can guide restoration practice. In 15 natural and 8 disturbed sites (i.e. disused shrimp ponds) in three case study regions in south-east Asia, water levels were measured and vegetation species composition was determined. Using an existing hydrological classification for mangroves, sites were classified into hydrological classes, based on duration of inundation, and vegetation classes, based on occurrence of mangrove species. For the natural sites hydrological and vegetation classes were similar, showing clear distribution of mangrove species from wet to dry sites. Application of the classification to disturbed sites showed that in some locations hydrological conditions had been restored enough for mangrove vegetation to establish, in some locations hydrological conditions were suitable for various mangrove species but vegetation had not established naturally, and in some locations hydrological conditions were too wet for any mangrove species (natural or planted) to grow. We quantified the effect that removal of obstructions such as dams would have on the hydrology and found that failure of planting at one site could have been prevented. The hydrological classification needs relatively little data, i.e. water levels for a period of only one lunar tidal cycle without additional measurements, and uncertainties in the measurements and analysis are relatively small. For the study locations, the application of the hydrological classification gave important information about how to restore the hydrology to suitable conditions to improve natural regeneration or to plant mangrove species, which could not have been obtained by estimating elevation only. Based on this research a number of recommendations are given to improve the effectiveness of mangrove restoration projects.

Hydrologic Landscape Characterization for the Pacific Northwest, USA

AbstractWe update the Wigington et al. (2013) hydrologic landscape (HL) approach to make it more broadly applicable and apply the revised approach to the Pacific Northwest (PNW; i.e., Oregon, Washington, and Idaho). Specific changes incorporated are the use of assessment units based on National Hydrography Dataset Plus V2 catchments, a modified snowmelt model validated over a broader area, an aquifer permeability index that does not require preexisting aquifer permeability maps, and aquifer and soil permeability classes based on uniform criteria. Comparison of Oregon results for the revised and original approaches found fewer and larger assessment units, loss of summer seasonality, and changes in rankings and proportions of aquifer and soil permeability classes. Differences could be explained by three factors: an increased assessment unit size, a reduced number of permeability classes, and use of smaller cutoff values for the permeability classes. The distributions of the revised HLs in five groups of Oregon rivers were similar to the original HLs but less variable. The improvements reported here should allow the revised HL approach to be applied more often in situations requiring hydrologic classification and allow greater confidence in results. We also apply the map results to the development of hydrologic landscape regions.