Adaptive Water Resource Planning in the South Saskatchewan River Basin: Use of Scenarios of Hydroclimatic Variability and Extremes

The South Saskatchewan River Basin is one of Canada's most threatened watersheds, with water supplies in most subbasins over‐allocated. In 2013, stakeholders representing irrigation districts, the environment, and municipalities collaborated with researchers and consultants to explore opportunities to improve the resiliency of the management of the Oldman and South Saskatchewan River subbasins. Streamflow scenarios for 2025‐2054 were constructed by the novel approach of regressing historical river flows against indices of large‐scale ocean‐atmosphere climate oscillations to derive statistical streamflow models, which were then run using projected climate indices from global climate models. The impacts of some of the most extreme scenarios were simulated using the hydrologic mass‐balance model Operational Analysis and Simulation of Integrated Systems (OASIS). Based on stakeholder observations, the project participants proposed and evaluated potential risk management and adaption strategies, e.g., modifying existing infrastructure, building new infrastructure, changing operations to supplement environmental flows, reducing demand, and sharing supply. The OASIS model was applied interactively at live modeling sessions with stakeholders to explore practical adaptation strategies. Our results, which serve as recommendations for policy makers, showed that forecast‐based rationing together with new expanded storage could dramatically reduce water shortages.     

Prioritizing Stream Barrier Removal to Maximize Connected Aquatic Habitat and Minimize Water Scarcity

Instream barriers, such as dams, culverts, and diversions, alter hydrologic processes and aquatic habitat. Removing uneconomical and aging instream barriers is increasingly used for river restoration. Historically, selection of barrier removal projects used score‐and‐rank techniques, ignoring cumulative change and the spatial structure of stream networks. Likewise, most water supply models prioritize either human water uses or aquatic habitat, failing to incorporate both human and environmental water use benefits. Here, a dual‐objective optimization model identifies barriers to remove that maximize connected aquatic habitat and minimize water scarcity. Aquatic habitat is measured using monthly average streamflow, temperature, channel gradient, and geomorphic condition as indicators of aquatic habitat suitability. Water scarcity costs are minimized using economic penalty functions while a budget constraint specifies the money available to remove barriers. We demonstrate the approach using a case study in Utah's Weber Basin to prioritize removal of instream barriers for Bonneville cutthroat trout, while maintaining human water uses. Removing 54 instream barriers reconnects about 160 km of quality‐weighted habitat and costs approximately US$10 M. After this point, the cost‐effectiveness of removing barriers to connect river habitat decreases. The modeling approach expands barrier removal optimization methods by explicitly including both economic and environmental water uses.     

EPA'S BASINS MODEL: GOOD SCIENCE OR SERENDIPITOUS MODELING?1

ABSTRACT: Better Assessment Science Integrating Point and Non‐point Sources (BASINS) is a geographic‐based watershed assessment tool developed by EPA's Office of Water to help states more efficiently target and evaluate water‐bodies that are not meeting water quality standards. BASINS (EPA, 1996a, 1998) brings together data on water quality and quantity, land uses, point source loadings, and other related spatial data with supporting nonpoint and water quality models at a quicker and more effective pace. EPA developed BASINS, to better integrate point and nonpoint source water quality assessments for the Nation's 2100+ watersheds. In its zeal to achieve this endpoint, EPA has initiated a simplistic approach that was expected to grow through scientific enhancements as TMDL developers become more familiar with modeling requirements. BASINS builds upon federal databases of water quality conditions and point source loadings for numerous parameters where quality assurance is suspect in some cases. Its design allows comprehensive assessments and modeling in typical Total Maximum Daily Load (TMDL) computations. While the TMDL utility is the primary reason BASINS was developed, other longer‐range water quality assessments will become possible as the Agency expands the suite of assessment models and databases in future releases. The simplistic approach to modeling and user‐friendly tools gives rise, however, to technical and philosophical concerns related to default data usage. Seamless generation of model input files and the failure of some utilities to work properly suggest to NCASI that serious problems may still exist and prompts the need for a more rigorous peer‐review. Furthermore, sustainable training becomes paramount, as some older modelers will be unfamiliar with Geographic Information System (GIS) technology and associated computer skills. Overall, however, BASINS was judged to be an excellent beginning tool to meet the complex environmental modeling needs in the 21st Century.     

Model‐Based Nitrogen and Phosphorus (Nutrient) Criteria for Large Temperate Rivers: 1. Model Development and Application

An initial inquiry into model‐based numeric nitrogen and phosphorus (nutrient) criteria for large rivers is presented. Field data collection and associated modeling were conducted on a segment of the lower Yellowstone River in the northwestern United States to assess the feasibility of deriving numeric nutrient criteria using mechanistic water‐quality models. The steady‐state one‐dimensional model QUAL2K and a transect‐based companion model AT2K were calibrated and confirmed against low‐flow conditions at a time when river loadings, water column chemistry, and diurnal indicators were approximately steady state. Predictive simulation was then implemented via nutrient perturbation to evaluate the steady‐state and diurnal response of the river to incremental nutrient additions. In this first part of a two‐part series, we detail our modeling approach, model selection, calibration and confirmation, sensitivity analysis, model outcomes, and associated uncertainty. In the second part (Suplee et al., 2015) we describe the criteria development process using the tools described herein. Both articles provide a fundamental understanding of the process required to develop site‐specific numeric nutrient criteria using models in applied regulatory settings.     

Rehabilitation and Flood Management Planning in a Steep,Boulder-Bedded Stream

This study demonstrates the integration of rehabilitation and flood management planning in a steep, boulder-bedded stream in a coastal urban catchment on the South Island of New Zealand. The Water of Leith, the primary stream flowing through the city of Dunedin, is used as a case study. The catchment is steep, with a short time of concentration and rapid hydrologic response, and the lower stream reaches are highly channelized with floodplain encroachment, a high potential for debris flows, significant flood risks, and severely degraded aquatic habitat. Because the objectives for rehabilitation and flood management in urban catchments are often conflicting, a number of types of analyses at both the catchment and the reach scales and careful planning with stakeholder consultation were needed for successful rehabilitation efforts. This included modeling and analysis of catchment hydrology, fluvial geomorphologic assessment, analysis of water quality and aquatic ecology, hydraulic modeling and flood risk evaluation, detailed feasibility studies, and preliminary design to optimize multiple rehabilitation and flood management objectives. The study showed that all of these analyses were needed for integrated rehabilitation and flood management and that some incremental improvements in stream ecological health, aesthetics, and public recreational opportunities could be achieved in this challenging environment. These methods should be considered in a range of types of stream rehabilitation projects.     

Water Resources Modeling of the Ganges‐Brahmaputra‐Meghna River Basins Using Satellite Remote Sensing Data1

Nishat, Bushra and S.M. Mahbubur Rahman, 2009. Water Resources Modeling of the Ganges‐Brahmaputra‐Meghna River Basins Using Satellite Remote Sensing Data. Journal of the American Water Resources Association (JAWRA) 45(6):1313‐1327. Abstract: Large‐scale water resources modeling can provide useful insights on future water availability scenarios for downstream nations in anticipation of proposed upstream water resources projects in large international river basins (IRBs). However, model set up can be challenging due to the large amounts of data requirement on both static states (soils, vegetation, topography, drainage network, etc.) and dynamic variables (rainfall, streamflow, soil moisture, evapotranspiration, etc.) over the basin from multiple nations and data collection agencies. Under such circumstances, satellite remote sensing provides a more pragmatic and convenient alternative because of the vantage of space and easy availability from a single data platform. In this paper, we demonstrate a modeling effort to set up a water resources management model, MIKE BASIN, over the Ganges, Brahmaputra, and Meghna (GBM) river basins. The model is set up with the objective of providing Bangladesh, the lowermost riparian nation in the GBM basins, a framework for assessing proposed water diversion scenarios in the upstream transboundary regions of India and deriving quantitative impacts on water availability. Using an array of satellite remote sensing data on topography, vegetation, and rainfall from the transboundary regions, we demonstrate that it is possible to calibrate MIKE BASIN to a satisfactory level and predict streamflow in the Ganges and Brahmaputra rivers at the entry points of Bangladesh at relevant scales of water resources management. Simulated runoff for the Ganges and Brahmaputra rivers follow the trends in the rated discharge for the calibration period. However, monthly flow volume differs from the actual rated flow by (?) 8% to (+) 20% in the Ganges basin, by (?) 15 to (+) 12% in the Brahmaputra basin, and by (?) 15 to (+) 19% in the Meghna basin. Our large‐scale modeling initiative is generic enough for other downstream nations in IRBs to adopt for their own modeling needs.     

FORECASTING FUTURE LAND USE FOR WATERSHED ASSESSMENT1

ABSTRACT: Protecting surface water quality in watersheds undergoing demographic change requires both the management of existing threats and planning to address potential future stresses arising from changing land use. Many reservoirs and threatened waterbodies are located in areas undergoing rapid population growth, and increases in density of residential and commercial land use, accompanied by increased amount of impervious surface area, can result in increased pollutant loading and degradation of water quality. Effective planning to address potential threats, including zoning and growth management, requires analytical tools to predict and compare the impacts of different management options. The focus of this paper is not on developing demographic projections, but rather the translation of such projections into changes in land use which form the basis for assessment of future watershed loads. Land use change can be forecast at a variety of spatial and temporal scales. A semi-lumped, GIS-based, transition matrix approach is recommended as consistent with the level of complexity achievable in most watershed models. Practical aspects of forecasting future land use for watershed assessment are discussed. Several recent reservoir water supply projection studies are used to demonstrate a general framework for simulating changes in land use and resulting impacts on water quality. In addition to providing a technical basis for selecting optimal management alternatives, such a tool is invaluable for demonstrating to different stakeholder groups the trade-offs among management alternatives, both in terms of water quality and future land use patterns within the watershed.     

Agro-Ecological Analysis for the EU Water Framework Directive: An Applied Case Study for the River Contract of the Seveso Basin (Italy)

The innovative approach to the protection and management of water resources at the basin scale introduced by the European Union water framework directive (WFD) requires new scientific tools. WFD implementation also requires the participation of many stakeholders (administrators, farmers and citizens) with the aim of improving the quality of river waters and basin ecosystems through cooperative planning. This approach encompasses different issues, such as agro-ecology, land use planning and water management. This paper presents the results of a methodology suggested for implementing the WFD in the case of the Seveso river contract in Italy, one of the recent WFD applications. The Seveso basin in the Lombardy region has been one of the most rapidly urbanizing areas in Italy over the last 50?years. First, land use changes in the last 50?years are assessed with the use of historical aerial photos. Then, elements of an ecological network along the river corridor are outlined, and different scenarios for enhancing existing ecological connections are assessed using indicators from graph theory. These scenarios were discussed in technical workshops with involved stakeholders of the river contract. The results show a damaged rural landscape, where urbanization processes have decimated the system of linear green features (hedges/rows). Progressive reconnections of some of the identified network nodes may significantly increase the connectivity and circuitry of the study area.     

Review of Urban Stormwater Quality Models: Deterministic,Stochastic, and Hybrid Approaches1

Abstract: The growing impact of urban stormwater on surface‐water quality has illuminated the need for more accurate modeling of stormwater pollution. Water quality based regulation and the movement towards integrated urban water management place a similar demand for improved stormwater quality model predictions. The physical, chemical, and biological processes that affect stormwater quality need to be better understood and simulated, while acknowledging the costs and benefits that such complex modeling entails. This paper reviews three approaches to stormwater quality modeling: deterministic, stochastic, and hybrid. Six deterministic, three stochastic, and three hybrid models are reviewed in detail. Hybrid approaches show strong potential for reducing stormwater quality model prediction error and uncertainty. Improved stormwater quality models will have wide ranging benefits for combined sewer overflow management, total maximum daily load development, best management practice design, land use change impact assessment, water quality trading, and integrated modeling.     

Integrating Modeling and Field Experiments to Evaluate Impacts of Vegetative Practices on Ponderosa Pine Watersheds1

Abstract: Determining watershed response to vegetation treatment has been the subject of numerous hydrologic studies over the years. However, generalizing the information obtained from traditional paired‐watershed studies to other watersheds in a region is problematic because of the empirical nature of such studies and the context dependence of hydrologic responses. This paper addresses the issue of generalizing hydrologic information through integration of process‐based modeling and field observations from small‐scale watershed experiments. To this end, the results from application of a process‐based model were compared with the results from small‐scale watershed experiments in ponderosa pine forests of Arizona. The model simulated treatment impacts reasonably well when compared to the traditional paired‐watershed approach. However, the model tended to overestimate water yields during periods of low flow, and there was a significant difference between the two approaches in the estimation of treatment impacts during the first four years following treatment. The results indicate that the lumped‐parameter modeling approach used here may be limited in its ability to detect small changes, and tends to overestimate changes that occur immediately following treatment. It is concluded that watershed experiments can be highly informative due to their direct examination of cause‐effect relationships, while process‐based models are useful for their processing power and focus on functional relationships. The integrated use of both watershed experiments and process‐based models provides a way to generalize hydrologic information, illuminate the processes behind landscape treatment effects, and to generate and test hypotheses.     

Modeling Megacity Drinking Water Security under a DSS Framework in a Tidal River at the North Pearl River Delta,China

A modeling study was undertaken under a decision support system (DSS) for drinking water security in the Foshan section of the Beijiang River, a typical tidal river in the North Pearl River Delta. The DSS included a database layer, application support layer, and an application layer. As an integral part of the DSS application support layer, an integrated modeling system was developed to simulate hydrodynamics. The balance of dissolved oxygen and toxicants was based on an environmental fluid dynamics code and a water quality analysis simulation program (WASP) modeling framework. Model calibration and validation was undertaken using monitoring data in normal hydrological conditions. Four scenarios for the environmental management of water, including current water temp‐spatial feature analysis, control of pollution sources, and emergency response, were designed and analyzed in the DSS. The results indicated that the tide downstream has a distinct influence on hydrodynamics and pollutant diffusion, and the DSS could be used to design effective schemes to reduce pollutant discharges and provide emergency responses for ensuring drinking water security.     

Oregon Hydrologic Landscapes: A Classification Framework1

Wigington, Parker J., Jr., Scott G. Leibowitz, Randy L. Comeleo, and Joseph L. Ebersole, 2012. Oregon Hydrologic Landscapes: A Classification Framework. Journal of the American Water Resources Association (JAWRA) 1‐20. DOI: 10.1111/jawr.12009 Abstract: There is a growing need for hydrologic classification systems that can provide a basis for broad‐scale assessments of the hydrologic functions of landscapes and watersheds and their responses to stressors such as climate change. We developed a hydrologic landscape (HL) classification approach that describes factors of climate‐watershed systems that control the hydrologic characteristics of watersheds. Our assessment units are incremental watersheds (i.e., headwater watersheds or areas draining directly into stream reaches). Major components of the classification include indices of annual climate, climate seasonality, aquifer permeability, terrain, and soil permeability. To evaluate the usefulness of our approach, we identified 30 rivers with long‐term streamflow‐gauging records and without major diversions and impoundments. We used statistical clustering to group the streams based on the shapes of their annual hydrographs. Comparison of the streamflow clusters and HL distributions within river basin clusters shows that the Oregon HL approach has the ability to provide insights about the expected hydrologic behavior of HLs and larger river basins. The Oregon HL approach has potential to be a useful framework for comparing hydrologic attributes of streams and rivers in the Pacific Northwest.     

A Comparison of Statistical Approaches for Predicting Stream Temperatures Across Heterogeneous Landscapes1

Abstract: Estimating stream temperatures across broad spatial extents is important for regional conservation of running waters. Although statistical models can be useful in this endeavor, little information exists to aid in the selection of a particular statistical approach. Our objective was to compare the accuracy of ordinary least‐squares multiple linear regression, generalized additive modeling, ordinary kriging, and linear mixed modeling (LMM) using July mean stream temperatures in Michigan and Wisconsin. Although LMM using low‐rank thin‐plate smoothing splines to measure the spatial autocorrelation in stream temperatures was the most accurate modeling approach; overall, there were only slight differences in prediction accuracy among the evaluated approaches. This suggests that managers and researchers can select a stream temperature modeling approach that meets their level of expertise without sacrificing substantial amounts of prediction accuracy. The most accurate models for Michigan and Wisconsin had root mean square errors of 2.0‐2.3°C, suggesting that only relatively coarse predictions can be produced from landscape‐based statistical models at regional scales. Explaining substantially more variability in stream temperatures likely will require the collection of finer‐scale hydrologic and physiographic data, which may be cost prohibitive for monitoring and assessing stream temperatures at regional scales.     

Application of best subset method for river water quality modeling: A study on Godavari River,India

The utilization of water quality analysis to inform optimal decision-making is imperative to achieve sustainable management of river water quality. A multitude of research works in the past has focused on river water quality modeling. Despite being a precise statistical regression technique that allows for fitting separate models for all potential combinations of predictors and selecting the optimal subset model, the application of best subset method in river water quality modeling is not widely adopted. The current research aims to validate the use of best subset method in evaluating the water quality parameters of the Godavari River, one of the largest rivers in India, by developing regression equations for different combinations of its physicochemical parameters. The study involves in formulating best subset regression equations to estimate the concentrations of river water quality parameters while also identifying and quantifying their variations. A total of 17 water quality parameters are analyzed at 13 monitoring sites using 13 years (1993–2005) of observed data for the monsoon (June–October) period and post-monsoon (November–February) period. The final subset model is selected among model combinations that are developed for each year's dataset through widely used statistical criteria such as R², F value, adjusted R²_a, AIC_c, and RSS. The final best subset model across all parameters exhibits R² values surpassing 0.8, indicating that the models possess the ability to account for over 80% of the variations in the concentrations of dependent parameters. Therefore, the findings demonstrated the appropriateness of this method in evaluating the water quality parameters in extensive rivers. This work is very useful for decision-making and in the management of river water quality for its sustainable use in the study area.     

Human Impacts to River Temperature and Their Effects on Biological Processes: A Quantitative Synthesis1

Hester, Erich T. and Martin W. Doyle, 2011. Human Impacts to River Temperature and Their Effects on Biological Processes: A Quantitative Synthesis. Journal of the American Water Resources Association (JAWRA) 47(3):571‐587. DOI: 10.1111/j.1752‐1688.2011.00525.x Abstract: Land‐use change and water resources management increasingly impact stream and river temperatures and therefore aquatic organisms. Efforts at thermal mitigation are expected to grow in future decades. Yet the biological consequences of both human thermal impacts and proposed mitigation options are poorly quantified. This study provides such context for river thermal management in two ways. First, we summarize the full spectrum of human thermal impacts to help thermal managers consider the relative magnitudes of all impacts and mitigation options. Second, we synthesize biological sensitivity to river temperature shifts using thermal performance curves, which relate organism‐level biological processes to temperature. This approach supplements the popular use of thermal thresholds by directly estimating the impact of temperature shifts on the rates of key biological processes (e.g., growth). Our results quantify a diverse array of human thermal impacts, revealing that human actions tend to increase more than decrease river temperatures. Our results also provide a practical framework in which to quantify the sensitivity of river organisms to such impacts and related mitigation options. Finally, among the data and studies we synthesized, river organisms appear to be more sensitive to temperature above than below their thermal maxima, and fish are more sensitive to temperature change than invertebrates.     

Lake eutrophication management modeling using dynamic programming

Lake eutrophication problems have received considerable attention in Taiwan, especially because they relate to the quality of drinking water. In this study, steady-state river water quality and lake eutrophication models are solved using dynamic programming algorithms to find the nutrient removal rates for eutrophication control during dry season. The kinetic cycle of chlorophyll-a, phosphorus and nitrogen for a complete-mixed lake is considered in the optimization framework. The Newton-iterative technique is adopted to solve the nonlinear equations for the steady-state lake eutrophication model. The optimization framework is applied to Cheng-Ching Lake in southern Taiwan. Several nutrient loading scenarios for eutrophication control are studied. Optimization results for nutrient removal rates and corresponding wastewater treatment capacities of each reach of the Kao-Ping River define the least cost approach to lake eutrophication control. A natural purification method, structural free water surface wetland, is also suggested to save more investment and improve river water quality at the same time.     

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.     

Landscape connectivity: A conservation application of graph theory

We use focal-species analysis to apply a graph-theoretic approach to landscape connectivity in the Coastal Plain of North Carolina. In doing so we demonstrate the utility of a mathematical graph as an ecological construct with respect to habitat connectivity. Graph theory is a well established mainstay of information technology and is concerned with highly efficient network flow. It employs fast algorithms and compact data structures that are easily adapted to landscape-level focal species analysis. American mink (Mustela vison) and prothonotary warblers (Protonotaria citrea) share the same habitat but have different dispersal capabilities, and therefore provide interesting comparisons on connections in the landscape. We built graphs using GIS coverages to define habitat patches and determined the functional distance between the patches with least-cost path modeling. Using graph operations concerned with edge and node removal we found that the landscape is fundamentally connected for mink and fundamentally unconnected for prothonotary warblers. The advantage of a graph-theoretic approach over other modeling techniques is that it is a heuristic framework which can be applied with very little data and improved from the initial results. We demonstrate the use of graph theory in a metapopulation context, and suggest that graph theory as applied to conservation biology can provide leverage on applications concerned with landscape connectivity.     

Classifying the Health of Connecticut Streams Using Benthic Macroinvertebrates with Implications for Water Management

Bioassessments have formed the foundation of many water quality monitoring programs throughout the United States. Like many state water quality programs, Connecticut has developed a relational database containing information about species richness, species composition, relative abundance, and feeding relationships among macroinvertebrates present in stream and river systems. Geographic Information Systems can provide estimates of landscape condition and watershed characteristics and when combined with measurements of stream biology, provide a useful visual display of information that is useful in a management context. The objective of our study was to estimate the stream health for all wadeable stream kilometers in Connecticut using a combination of macroinvertebrate metrics and landscape variables. We developed and evaluated models using an information theoretic approach to predict stream health as measured by macroinvertebrate multimetric index (MMI) and identified the best fitting model as a three variable model, including percent impervious land cover, a wetlands metric, and catchment slope that best fit the MMI scores (adj-R ² = 0.56, SE = 11.73). We then provide examples of how modeling can augment existing programs to support water management policies under the Federal Clean Water Act such as stream assessments and anti-degradation.     

Computer‐Aided Negotiations of Water Disputes: An Interdisciplinary Role‐Playing Course

This study examines the evolution of a microworld created in a stakeholder process into educational materials used in a classroom setting. Microworlds have been used to stimulate learning through engagement in classroom and professional settings, but to our knowledge this is the first example that demonstrates utilization of the same process in both settings in the field of water resources, involving collaboration between the educational and professional sectors. An interdisciplinary role‐playing course in Computer‐Aided Negotiations (CAN) of water disputes is used as a case study. Upper‐level undergraduate students of varied academic backgrounds interacted in both the CAN process and river basin management model used in the CAN process as microworlds for one semester. We found evidence of meaningful engagement with both the process and model by all students. This finding has implications for engaging stakeholders without technical backgrounds in CAN processes. Students reported learning gains on surveys and pre/posttest scores improved, although only one item showed a statistically significant increase. During and after the teaching of this course, there was feedback of work products from the students to river basin managers. The course also provides the opportunity to learn the art of collaborative modeling through example and practice. Course materials are available at http://www.hydrologics.net/CAN_Course/.