TECIIMQUES FOR DETECTING HYDROLOGIC CHANGE IN HIGH RESOURCE STREAMS1

ABSTRACT: A “synthetic paired basin” technique that combines hydrologic monitoring and watershed modeling proves to be a useful tool in detecting hydrologic change in creeks draining basins undergoing urbanization. In this approach, measured stream flow following subbasin treatment (a period of urbanization) is compared with flow from a control subbasin over the same time period. The control subbasin is the pretreatment subbasin itself as represented by a well‐calibrated hydrologic model that is input with post‐treatment meteorological data. The technique is illustrated for stream monitoring sites at the outlets of two high‐resource sub‐basins in the Bear Creek basin of King County, Washington. Application of this technique holds promise to provide earlier warning of cumulative, human impacts on aquatic resources and to better inform adaptive watershed management for resource protection.     

A STRIP MODEL APPROACH TO PARAMETERIZE A COUPLED GREEN‐AMPT KINEMATIC WAVE MODEL1

ABSTRACT: Infiltration processes at the plot scale are often described and modeled using a single effective hydraulic conductivity (Kg) value. This can lead to errors in runoff and erosion prediction. An integrated field measurement and modeling study was conducted to evaluate: (1) the relationship among rainfall intensity, spatially variable soil and vegetation characteristics, and infiltration processes; and (2) how this relationship could be modeled using Green and Ampt and a spatially distributed hydrologic model. Experiments were conducted using a newly developed variable intensity rainfall simulator on 2 m by 6 m plots in a rangeland watershed in southeastern Arizona. Rainfall application rates varied between 50 and 200 mm/hr. Results of the rainfall simulator experiments showed that the observed hydrologic response changed with changes in rainfall intensity and that the response varied with antecedent moisture condition. A distributed process based hydrologic simulation model was used to model the plots at different levels of hydrologic complexity. The measurement and simulation model results show that the rainfall runoff relationship cannot be accurately described or modeled using a single Kg value at the plot scale. Multi‐plane model configurations with infiltration parameters based on soil and plot characteristics resulted in a significant improvement over single‐plane configurations.     

Evaluation of the MIKE SHE Model for Application in the Loess Plateau,China1

Abstract: Quantifying the hydrologic responses to land use/land cover change and climate variability is essential for integrated sustainable watershed management in water limited regions such as the Loess Plateau in Northwestern China where an adaptive watershed management approach is being implemented. Traditional empirical modeling approach to quantifying the accumulated hydrologic effects of watershed management is limited due to its complex nature of soil and water conservation practices (e.g., biological, structural, and agricultural measures) in the region. Therefore, the objective of this study was to evaluate the ability of the distributed hydrologic model, MIKE SHE to simulate basin runoff. Streamflow data measured from an overland flow‐dominant watershed (12 km²) in northwestern China were used for model evaluation. Model calibration and validation suggested that the model could capture the dominant runoff process of the small watershed. We found that the physically based model required calibration at appropriate scales and estimated model parameters were influenced by both temporal and spatial scales of input data. We concluded that the model was useful for understanding the rainfall‐runoff mechanisms. However, more measured data with higher temporal resolution are needed to further test the model for regional applications.     

CLIMATE CHANGE AND WATERSHED PLANNING IN WASHINGTON STATE1

ABSTRACT: This paper draws on interviews with Washington State Watershed Planning Leads (Planning Leads) and interactions with local watershed planning units to identify factors that may influence the inclusion of climate change in watershed planning efforts in Washington State. These factors include the interest of individual planning unit members in climate change; Planning Lead familiarity with climate impacts; the influence of trust, leadership, and “genetic knowledge” on planning units; and perceptions of strategic gain. The research also identifies aspects of the planning process that may create opportunities for addressing climate impacts in future planning. These aspects include continuation of watershed planning units after plans are developed; commitment to updating watershed plans; recognition of climate impacts in planning documentation; dedicated incentive funding; and the availability of hydrologic modeling tools for assessing hydrologic impacts. Additional types of technical assistance that could support integration of climate impacts are also identified. It is hoped that the insight provided by this analysis will help individuals involved in stakeholder‐based watershed planning recognize the various dynamics potentially affecting the inclusion of climate change in watershed planning and in doing so, contribute to the development of planning approaches and tools that will support local efforts to adapt to climate impacts.     

EFFECTS OF SCALE ON LAND USE AND WATER QUALITY RELATIONSHIPS: A LONGITUDINAL BASIN‐WIDE PERSPECTIVE1

ABSTRACT: Human land use is a major source of change in catchments in developing areas. To better anticipate the long‐term effects of growth, land use planning requires estimates of how changes in land use will affect ecosystem processes and patterns across multiple scales of space and time. The complexity of biogeochemical and hydrologic interactions within a basin makes it difficult to scale up from process‐based studies of individual reaches to watershed scales over multiple decades. Empirical models relating land use/land cover (LULC) to water quality can be useful in long‐term planning, but require an understanding of the effects of scale on apparent land use‐water quality relationships. We empirically determined how apparent relationships between water quality and LULC data change at different scales, using LIJLC data from the Willapa Bay watershed (Washington) and water quality data collected along the Willapa and North Rivers. Spatial scales examined ranged from the local riparian scale to total upstream catchment. The strength of the correlations between LTJLC data and longitudinal water quality trends varied with scale. Different water quality parameters also varied in their response to changes in scale. Intermediate scales of land use data generally were better predictors than local riparian or total catchment scales. Additional data from the stream network did not increase the strength of relationships significantly. Because of the likelihood of scale‐induced artifacts, studies quantifying land use‐water quality relationships performed at single scales should be viewed with great caution.     

Assessing Watershed-Scale, Long-Term Hydrologic Impacts of Land-Use Change Using a GIS-NPS Model

Land-use change, dominated by an increase in urban/impervious areas, has a significant impact on water resources. This includes impacts on nonpoint source (NPS) pollution, which is the leading cause of degraded water quality in the United States. Traditional hydrologic models focus on estimating peak discharges and NPS pollution from high-magnitude, episodic storms and successfully address short-term, local-scale surface water management issues. However, runoff from small, low-frequency storms dominates long-term hydrologic impacts, and existing hydrologic models are usually of limited use in assessing the long-term impacts of land-use change. A long-term hydrologic impact assessment (L-THIA) model has been developed using the curve number (CN) method. Long-term climatic records are used in combination with soils and land-use information to calculate average annual runoff and NPS pollution at a watershed scale. The model is linked to a geographic information system (GIS) for convenient generation and management of model input and output data, and advanced visualization of model results. The L-THIA/NPS GIS model was applied to the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana, USA. Historical land-use scenarios for 1973, 1984, and 1991 were analyzed to track land-use change in the watershed and to assess impacts on annual average runoff and NPS pollution from the watershed and its five subbasins. For the entire watershed between 1973 and 1991, an 18% increase in urban or impervious areas resulted in an estimated 80% increase in annual average runoff volume and estimated increases of more than 50% in annual average loads for lead, copper, and zinc. Estimated nutrient (nitrogen and phosphorus) loads decreased by 15% mainly because of loss of agricultural areas. The L-THIA/NPS GIS model is a powerful tool for identifying environmentally sensitive areas in terms of NPS pollution potential and for evaluating alternative land use scenarios for NPS pollution management.     

The Watershed Flow and Allocation Model: An NHDPlus‐Based Watershed Modeling Approach for Multiple Scales and Conditions

The Watershed Flow and Allocation model (WaterFALL^®) provides segment‐specific, daily streamflow at both gaged and ungaged locations to generate the hydrologic foundation for a variety of water resources management applications. The model is designed to apply across the spatially explicit and enhanced National Hydrography Dataset (NHDPlus) stream and catchment network. To facilitate modeling at the NHDPlus catchment scale, we use an intermediate‐level rainfall‐runoff model rather than a complex process‐based model. The hydrologic model within WaterFALL simulates rainfall‐runoff processes for each catchment within a watershed and routes streamflow between catchments, while accounting for withdrawals, discharges, and onstream reservoirs within the network. The model is therefore distributed among each NHDPlus catchment within the larger selected watershed. Input parameters including climate, land use, soils, and water withdrawals and discharges are georeferenced to each catchment. The WaterFALL system includes a centralized database and server‐based environment for storing all model code, input parameters, and results in a single instance for all simulations allowing for rapid comparison between multiple scenarios. We demonstrate and validate WaterFALL within North Carolina at a variety of scales using observed streamflows to inform quantitative and qualitative measures, including hydrologic flow metrics relevant to the study of ecological flow management decisions.     

Spatiotemporal Variability of Snow Depletion Curves Derived from SNODAS for the Conterminous United States, 2004‐2013

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental‐scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental‐extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1‐km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed‐scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed‐scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national‐scale categorization of snowmelt processes.     

ASSESSING CHANGES IN WATERSHED FLOW REGIMES WITH SPATIALLY EXPLICIT HYDRAULIC MODELS1

ABSTRACT: Urbanization, farming, and other watershed activities can significantly alter storm hydrographs and sediment erosion rates within a watershed. These changes routinely cause severe economic and ecological problems manifested in the form of increased flooding and significant changes in channel morphology. As the activities within a watershed influence the hydrologic, hydraulic, and ecological conditions within a river, interdisciplinary approaches to predict and assess the impacts that different land uses have on streams need to be developed. An important component of this process is ascertaining how hydrologic changes induced by specific watershed activities will affect hydraulic conditions and the accompanying flood levels, sediment transport rates, and habitat conditions within a stream. A conceptual model for using spatially explicit (two‐dimensional) hydraulic models to help evaluate the impacts that changes in flow regime might have on a river is presented. This framework proposes that reproducing and quantifying flow complexity allows one to compare the hydraulic conditions within urban, urbanizing, and non‐urban streams in a more biologically and economically meaningful way. The justification, advantage, and need for such a method is argued through the results of one‐ and two‐dimensional hydraulic model studies. The implementation of this methodology in watershed urbanization studies is described.     

Modeling the relationship between land use and surface water quality

It is widely known that watershed hydrology is dependent on many factors, including land use, climate, and soil conditions. But the relative impacts of different types of land use on the surface water are yet to be ascertained and quantified. This research attempted to use a comprehensive approach to examine the hydrologic effects of land use at both a regional and a local scale. Statistical and spatial analyses were employed to examine the statistical and spatial relationships of land use and the flow and water quality in receiving waters on a regional scale in the State of Ohio. Besides, a widely accepted watershed-based water quality assessment tool, the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS), was adopted to model the plausible effects of land use on water quality in a local watershed in the East Fork Little Miami River Basin. The results from the statistical analyses revealed that there was a significant relationship between land use and in-stream water quality, especially for nitrogen, phosphorus and Fecal coliform. The geographic information systems (GIS) spatial analyses identified the watersheds that have high levels of contaminants and percentages of agricultural and urban lands. Furthermore, the hydrologic and water quality modeling showed that agricultural and impervious urban lands produced a much higher level of nitrogen and phosphorus than other land surfaces. From this research, it seems that the approach adopted in this study is comprehensive, covering both the regional and local scales. It also reveals that BASINS is a very useful and reliable tool, capable of characterizing the flow and water quality conditions for the study area under different watershed scales. With little modification, these models should be able to adapt to other watersheds or to simulate other contaminants. They also can be used to study the plausible impacts of global environmental change. In addition, the information on the hydrologic effects of land use is very useful. It can provide guidelines not only for resource managers in restoring our aquatic ecosystems, but also for local planners in devising viable and ecologically-sound watershed development plans, as well as for policy makers in evaluating alternate land management decisions.     

Efficient Delineation of Nested Depression Hierarchy in Digital Elevation Models for Hydrological Analysis Using Level‐Set Method

In terrain analysis and hydrological modeling, surface depressions (or sinks) in a digital elevation model (DEM) are commonly treated as artifacts and thus filled and removed to create a depressionless DEM. Various algorithms have been developed to identify and fill depressions in DEMs during the past decades. However, few studies have attempted to delineate and quantify the nested hierarchy of actual depressions, which can provide crucial information for characterizing surface hydrologic connectivity and simulating the fill‐merge‐spill hydrological process. In this paper, we present an innovative and efficient algorithm for delineating and quantifying nested depressions in DEMs using the level‐set method based on graph theory. The proposed level‐set method emulates water level decreasing from the spill point along the depression boundary to the lowest point at the bottom of a depression. By tracing the dynamic topological changes (i.e., depression splitting/merging) within a compound depression, the level‐set method can construct topological graphs and derive geometric properties of the nested depressions. The experimental results of two fine‐resolution Light Detection and Ranging‐derived DEMs show that the raster‐based level‐set algorithm is much more efficient (~150 times faster) than the vector‐based contour tree method. The proposed level‐set algorithm has great potential for being applied to large‐scale ecohydrological analysis and watershed modeling.     

Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Modeling Connectivity of Non‐floodplain Wetlands: Insights,Approaches, and Recommendations

Representing hydrologic connectivity of non‐floodplain wetlands (NFWs) to downstream waters in process‐based models is an emerging challenge relevant to many research, regulatory, and management activities. We review four case studies that utilize process‐based models developed to simulate NFW hydrology. Models range from a simple, lumped parameter model to a highly complex, fully distributed model. Across case studies, we highlight appropriate application of each model, emphasizing spatial scale, computational demands, process representation, and model limitations. We end with a synthesis of recommended “best modeling practices” to guide model application. These recommendations include: (1) clearly articulate modeling objectives, and revisit and adjust those objectives regularly; (2) develop a conceptualization of NFW connectivity using qualitative observations, empirical data, and process‐based modeling; (3) select a model to represent NFW connectivity by balancing both modeling objectives and available resources; (4) use innovative techniques and data sources to validate and calibrate NFW connectivity simulations; and (5) clearly articulate the limits of the resulting NFW connectivity representation. Our review and synthesis of these case studies highlights modeling approaches that incorporate NFW connectivity, demonstrates tradeoffs in model selection, and ultimately provides actionable guidance for future model application and development.     

Does Wetland Location Matter When Managing Wetlands for Watershed‐Scale Flood and Drought Resilience?

Wetland protection and restoration strategies that are designed to promote hydrologic resilience do not incorporate the location of wetlands relative to the main stream network. This is primarily attributed to the lack of knowledge on the effects of wetland location on wetland hydrologic function (e.g., flood and drought mitigation). Here, we combined a watershed‐scale, surface–subsurface, fully distributed, physically based hydrologic model with historical, existing, and lost (drained) wetland maps in the Nose Creek watershed in the Prairie Pothole Region of North America to (1) estimate the hydrologic functions of lost wetlands and (2) estimate the hydrologic functions of wetlands located at different distances from the main stream network. Modeling results showed wetland loss altered streamflow, decreasing baseflow and increasing stream peakflow during the period of the precipitation events that led to major flooding in the watershed and downstream cities. In addition, we found that wetlands closer to the main stream network played a disproportionately important role in attenuating peakflow, while wetland location was not important for regulating baseflow. The findings of this study provide information for watershed managers that can help to prioritize wetland restoration efforts for flood or drought risk mitigation.     

Flood Risk Reduction from Agricultural Best Management Practices

Best management practices (BMPs) play an important role in improving impaired water quality from conventional row crop agriculture. In addition to reducing nutrient and sediment loads, BMPs such as fertilizer management, reduced tillage, and cover crops could alter the hydrology of agricultural systems and reduce surface water runoff. While attention is devoted to the water quality benefits of BMPs, the potential co‐benefits of flood loss reduction are often overlooked. This study quantifies the effects of selected commonly applied BMPs on expected flood loss to agricultural and urban areas in four Iowa watersheds. The analysis combines a watershed hydrologic model, hydraulic model outputs, and a loss estimation model to determine relationships between hydrologic changes from BMP implementations and annual economic flood loss. The results indicate a modest reduction in peak discharge and economic loss, although loss reduction is substantial when urban centers or other high‐value assets are located downstream in the watershed. Among the BMPs, wetlands, and cover crops reduce losses the most. The research demonstrates that watershed‐scale implementation of agricultural BMPs could provide benefits of flood loss reduction in addition to water quality improvements.     

SENSITIVITY CONSIDERATIONS WHEN MODELING HYDROLOGIC PROCESSES WITH DIGITAL ELEVATION MODEL1

ABSTRACT: The purpose of this paper is to investigate the sensitivity of a hydrologic models to the type of DEM used. This was done while modeling basin water quality with 1:24,000 and 1:250,000 U.S. Geological Survey DEMs as input to model hydro‐logical processes. The manner in which the model results were sensitive to the choice of raster cell size (scale) is investigated in this study. The Broadhead watershed, located in New Jersey, USA, was chosen as a study area. Curve numbers were estimated by a trial and error to match simulated and observed total discharge. Monthly runoff for the watershed was used in the calibration process. Higher runoff volumes were simulated by the model when the 1:24,000 DEM were used as input data, probably due to the finer resolution which simulated increased average slope and hence higher estimated runoff from the watershed. As the simulated slope of the watershed is flatten with the 1:250,000 DEM, the response of stream flow was delayed and simulated less runoff volume.     

Hydrologic Modeling Uncertainty Resulting From Land Cover Misclassification1

Abstract: A stochastic, spatially explicit method for assessing the impact of land cover classification error on distributed hydrologic modeling is presented. One‐hundred land cover realizations were created by systematically altering the North American Landscape Characterization land cover data according to the dataset’s misclassification matrix. The matrix indicates the probability of errors of omission in land cover classes and is used to assess the uncertainty in hydrologic runoff simulation resulting from parameter estimation based on land cover. These land cover realizations were used in the GIS‐based Automated Geospatial Watershed Assessment tool in conjunction with topography and soils data to generate input to the physically‐based Kinematic Runoff and Erosion model. Uncertainties in modeled runoff volumes resulting from these land cover realizations were evaluated in the Upper San Pedro River basin for 40 watersheds ranging in size from 10 to 100 km² under two rainfall events of differing magnitudes and intensities. Simulation results show that model sensitivity to classification error varies directly with respect to watershed scale, inversely to rainfall magnitude and are mitigated or magnified by landscape variability depending on landscape composition.     

APPLICATION OF AN ENVIRONMENTAL AND ECONOMIC MODELING SYSTEM FOR WATERSHED ASSESSMENTS1

ABSTRACT: A National Pilot Project (NPP) on Livestock and the Environment was initiated in 1992 to help provide solutions to environmental problems associated with livestock production. A major development of the NPP was the Comprehensive Economic and Environmental Optimization Tool‐Livestock and Poultry (CEEOT‐LP), an integrated modeling system designed to produce economic and environmental indicators for alternative policy scenarios applied to intensive livestock production watersheds. The system consists of a farm‐level economic model (FEM) and two environmental models: the field‐scale APEX model and the watershed‐level SWAT model. To date, CEEOT‐LP has been applied to two watersheds in Texas and one in Iowa. Predicted reductions in P losses for two P‐based manure application rate scenarios, relative to baseline conditions, ranged from ?4 to ?54 percent across the three watersheds; however, N loss impacts ranged from a decrease of 34 percent to an increase of 79 percent. For five other alternative scenarios that were simulated for only one watershed, N and P loss impacts ranged between a reduction of 78 percent to an increase of 20 percent. Aggregate watershed‐level economic impacts of the seven scenarios spanned a spectrum of a 27 percent decrease to a 25 percent increase in profit, relative to the baseline.     

Modeling Hydrology in a Small Rocky Mountain Watershed Serving Large Urban Populations1

Abstract: This article describes the development of a calibrated hydrologic model for the Blue River watershed (867 km²) in Summit County, Colorado. This watershed provides drinking water to over a third of Colorado’s population. However, more research on model calibration and development for small mountain watersheds is needed. This work required integration of subsurface and surface hydrology using GIS data, and included aspects unique to mountain watersheds such as snow hydrology, high ground‐water gradients, and large differences in climate between the headwaters and outlet. Given the importance of this particular watershed as a major urban drinking‐water source, the rapid development occurring in small mountain watersheds, and the importance of Rocky Mountain water in the arid and semiarid West, it is useful to describe calibrated watershed modeling efforts in this watershed. The model used was Soil and Water Assessment Tool (SWAT). An accurate model of the hydrologic cycle required incorporation of mountain hydrology‐specific processes. Snowmelt and snow formation parameters, as well as several ground‐water parameters, were the most important calibration factors. Comparison of simulated and observed streamflow hydrographs at two U.S. Geological Survey gaging stations resulted in good fits to average monthly values (0.71 Nash‐Sutcliffe coefficient). With this capability, future assessments of point‐source and nonpoint‐source pollutant transport are possible.     

Assessing BMP Effectiveness and Guiding BMP Planning Using Process‐Based Modeling

There is an increasing need for improved process‐based planning tools to assist watershed managers in the selection and placement of effective best management practices (BMPs). In this article, we present an approach, based on the Water Erosion Prediction Project model and a pesticide transport model, to identify dominant hydrologic flow paths and critical source areas for a variety of pollutant types. We use this approach to compare the relative impacts of BMPs on hydrology, erosion, sediment, and pollutant delivery within different landscapes. Specifically, we focus on using this approach to understand what factors promoted and/or hindered BMP effectiveness at three Conservation Effects Assessment Project watersheds: Paradise Creek Watershed in Idaho, Walnut Creek Watershed in Iowa, and Goodwater Creek Experimental Watershed in Missouri. These watersheds were first broken down into unique land types based on soil and topographic characteristics. We used the model to assess BMP effectiveness in each of these land types. This simple process‐based modeling approach provided valuable insights that are not generally available to planners when selecting and locating BMPs and helped explain fundamental reasons why long‐term improvement in water quality of these three watersheds has yet to be completely realized.