CALIBRATING AND VERIFYING THE SSARR MODEL -MISSOURI RIVER WATERSHEDS STUDY1

The Streamflow Synthesis and Reservoir Regulation (SSARR) model was calibrated and verified on the Madison and Gallatin watersheds in the upper Missouri River drainage. The study was performed to determine if the SSARR model could simulate snowmelt-runoff volumes to effect better operation of six multipurpose reservoirs on the Missouri River. Physical watershed characteristics and parameter sensitivity are incorporated into a procedure which expedites model calibration. Criteria are established to facilitate parameter development and to objectively evaluate calibration and verification results. A ratio of simulated to observed snowmelt-runoff volumes of the Madison River averaged 1.00 and 1.02 for calibration (N = 8 years) and verification (N = 6 years) with corresponding standard deviations of 0.08 and 0.13. Gallatin volume ratios averaged 0.99 and 0.95 for calibration (N = 7 years) and verification (N = 5 years) with respective standard deviations of 0.08 and 0.28.     

HYDROLOGICAL MODELING OF THE IROQUOIS RIVER WATERSHED USING HSPF AND SWAT1

ABSTRACT: The performance of two popular watershed scale simulation models — HSPF and SWAT — were evaluated for simulating the hydrology of the 5,568 km² Iroquois River watershed in Illinois and Indiana. This large, tile drained agricultural watershed provides distinctly different conditions for model comparison in contrast to previous studies. Both models were calibrated for a nine‐year period (1987 through 1995) and verified using an independent 15‐year period (1972 through 1986) by comparing simulated and observed daily, monthly, and annual streamflow. The characteristics of simulated flows from both models are mostly similar to each other and to observed flows, particularly for the calibration results. SWAT predicts flows slightly better than HSPF for the verification period, with the primary advantage being better simulation of low flows. A noticeable difference in the models' hydrologic simulation relates to the estimation of potential evapotranspiration (PET). Comparatively low PET values provided as input to HSPF from the BASINS 3.0 database may be a factor in HSPF's overestimation of low flows. Another factor affecting baseflow simulation is the presence of tile drains in the watershed. HSPF parameters can be adjusted to indirectly account for the faster subsurface flow associated with tile drains, but there is no specific tile drainage component in HSPF as there is in SWAT. Continued comparative studies such as this, under a variety of hydrologic conditions and watershed scales, provide needed guidance to potential users in model selection and application.     

HYDROLOGICAL APPLICATIONS OF LANDSAT IMAGERY USED IN THE STUDY OF THE 1973 INDUS RIVER FLOOD,PAKISTAN1

ABSTRACT: During August and September 1973, the Indus River Valley of Pakistan experienced one of the largest floods on record, resulting in damages to homes, businesses, public works, and crops amounting to millions of rupees. Tremendous areas of lowlands were inundated along the Indus River and major tributaries. Landsat data made it possible to easily measure the extent of flooding, totaling about 20,000 km² within an area of about 400,000 km² south from the Punjab to the Arabian Sea. The Indus River data were used to continue experimentation in the development of rapid, accurate, and inexpensive optical techniques of flood mapping by satellite begun in 1973 for the Mississipi River floods. The research work on the Indus River not resulted in the development of more effective procedures for optical processing of flood data and synoptically depicting flooding, but also provided potentially valuable ancillary information concerning the hydrology of much of the Indus River Basin.     

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.     

IDENTIFICATION OF CHANGES IN STREAMFLOW CHARACTERISTICS1

ABSTRACT: A set of procedures for identifying changes in selected streamflow characteristics at sites having long‐term continuous streamflow records is illustrated by using streamflow data from the Waccamaw River at Freeland, North Carolina for the 55‐year period of 1940–1994. Data were evaluated and compared to streamflow in the adjacent Lumber River Basin to determine if changes in streamflow characteristics in the Waccamaw River were localized and possibly the result of some human activity, or consistent with regional variations. Following 1963, droughts in the Waccamaw Basin seem to have been less severe than in the Lumber Basin, and the annual one‐, seven‐, and 30‐day low flows exhibited a slightly increasing trend in the Waccamaw River. Mean daily flows in the Waccamaw River at the 90 percent exceedance level (low flows) during 1985–194, a relatively dry period, were very nearly equal to flows at the same exceedance level for 1970–1979, which represents the 10‐year period between 1940 and 1994 with the highest flows. Prior to the 1980s, flows per unit drainage area in the Waccamaw Basin were generally less than those in the Lumber Basin, but after 1980, the opposite was true. The ratio of base flow to runoff in the Waccamaw River may have changed relative to that in the Lumber River in the late 1970s. There was greater variability in Waccamaw River streamflow than in Lumber River flow, and flow variability in the Waccamaw River may have increased slightly during 1985–1994.     

Reduced Soil Macropores and Forest Cover Reduce Warm‐Season Baseflow below Ecological Thresholds in the Upper Delaware River Basin

We examined the impacts of changes in land cover and soil conditions on the flow regime of the upper Delaware River Basin using the Water Availability Tool for Environmental Resources. We simulated flows for two periods, c. 1600 and 1940, at three sites using the same temperature and precipitation conditions: the East Branch, West Branch, and mainstem Delaware River at Callicoon, New York. The 1600 period represented pristine forest and soils. The 1940 period included reduced forest cover, increased agriculture, and degraded soils with reduced soil macropore fractions. A model‐sensitivity test examined the impact of soil macropore and land cover change separately. We assessed changes in flow regimes between the 1600 and 1940 periods using a variety of flow statistics, including established ecological limits of hydrologic alteration (ELOHA) thresholds. Reduced forest soil macropore fraction significantly reduced summer and fall baseflows. The 1940 period had significantly lower Q50 flows (50% exceedance) than the 1600 period, as well as summer and fall Q90 and Q75–Q90 flows below the ELOHA thresholds. The one‐ to seven‐day minimum flows were also lower for the 1940 period, by 17% on the mainstem. 1940 flows were 6% more likely than the 1600 period to fall below the low‐flow threshold for federally endangered dwarf wedgemussel (Alasmidonta heterodon) habitat. In contrast, the 1940 period had higher flows than the 1600 period from late fall to early winter.     

Adaptation of Climate Model Projections of Streamflow to Account for Upstream Anthropogenic Impairments

A statistical procedure is developed to adjust natural streamflows simulated by dynamical models in downstream reaches, to account for anthropogenic impairments to flow that are not considered in the model. The resulting normalized downstream flows are appropriate for use in assessments of future anthropogenically impaired flows in downstream reaches. The normalization is applied to assess the potential effects of climate change on future water availability on the Rio Grande at a gage just above the major storage reservoir on the river. Model‐simulated streamflow values were normalized using a statistical parameterization based on two constants that relate observed and simulated flows over a 50‐year historical baseline period (1964–2013). The first normalization constant is a ratio of the means, and the second constant is the ratio of interannual standard deviations between annual gaged and simulated flows. This procedure forces the gaged and simulated flows to have the same mean and variance over the baseline period. The normalization constants can be kept fixed for future flows, which effectively assumes that upstream water management does not change in the future, or projected management changes can be parameterized by adjusting the constants. At the gage considered in this study, the effect of the normalization is to reduce simulated historical flow values by an average of 72% over an ensemble of simulations, indicative of the large fraction of natural flow diverted from the river upstream from the gage. A weak tendency for declining flow emerges upon averaging over a large ensemble, with tremendous variability among the simulations. By the end of the 21st Century the higher‐emission scenarios show more pronounced declines in streamflow.     

AutoRAPID: A Model for Prompt Streamflow Estimation and Flood Inundation Mapping over Regional to Continental Extents

This article couples two existing models to quickly generate flow and flood‐inundation estimates at high resolutions over large spatial extents for use in emergency response situations. Input data are gridded runoff values from a climate model, which are used by the Routing Application for Parallel computatIon of Discharge (RAPID) model to simulate flow rates within a vector river network. Peak flows in each river reach are then supplied to the AutoRoute model, which produces raster flood inundation maps. The coupled tool (AutoRAPID) is tested for the June 2008 floods in the Midwest and the April‐June 2011 floods in the Mississippi Delta. RAPID was implemented from 2005 to 2014 for the entire Mississippi River Basin (1.2 million river reaches) in approximately 45 min. Discretizing a 230,000‐km² area in the Midwest and a 109,500‐km² area in the Mississippi Delta into thirty‐nine 1° by 1° tiles, AutoRoute simulated a high‐resolution (~10 m) flood inundation map in 20 min for each tile. The hydrographs simulated by RAPID are found to perform better in reaches without influences from unrepresented dams and without backwater effects. Flood inundation maps using the RAPID peak flows vary in accuracy with F‐statistic values between 38.1 and 90.9%. Better performance is observed in regions with more accurate peak flows from RAPID and moderate to high topographic relief.     

Improving watershed decisions using run-off and yield models at different simulation scales

Water managers face the daunting task of balancing limited water resources with over-subscribed water users among competing demands. They face the additional challenge of taking water planning decisions in an uncertain environment with limited and sometimes inaccurate observed and simulated hydrological data. Within South African watersheds, spatial parameterization data for hydrological models are now available at two different basin management resolutions (termed quaternary and quinary). Currently, water management decisions in the Crocodile River watershed are often made at a more coarse resolution, which may exclude crucial insights into the data. This research has the following aims (1) to explore whether model performance is improved by parameterization using a more detailed quinary-scale watershed data and (2) to explore whether quinary-scale models reduce uncertainty in allocation or restriction decisions to provide better informed water resources management and decision outcomes. This study used the Agricultural Catchments Research Unit (ACRU) agro-hydrological watershed model, to evaluate the effects of spatial discretization at the quaternary and quinary scales on watershed hydrological response and runoff within the Crocodile River basin. Model performance was evaluated using statistical comparisons of results using traditional goodness-of-fit measures such as the coefficient of efficiency (C _eff), root mean square of the error and the coefficient of determination (R ²) to compare simulated monthly flows and observed flows in six subcatchments. Traditional interpretation of these goodness-of-fit measures may be inadequate as they can be subjectively interpreted and easily influenced by the number of data points, outliers and model bias. This research utilizes a recently released model evaluation program (FITEVAL) which presents probability distributions of R ²and C _eff derived by bootstrapping, graphical representation of observed and simulated stream flows, incorporates statistical significance to detect the sufficiency of the R ²and C _eff and determines the presence of outliers and bias. While analyses indicate that the ACRU model performs marginally better when parameterized and calibrated at the quinary scale, the measurements at both scales show significant variability in predictions for both high and low flows that are endemic to southern African hydrology. The improved evaluation methods also allow for the analysis of data collection errors at monitoring sites and help determine the effect of data quality on adaptive water planning management decisions. Given that many water resource challenges are complex adaptive systems, these expanded performance analysis tools help provide deeper insights into matching watershed decision metrics and model-derived predictions.     

Statistically Integrated Flow and Flood Modelling Compared to Hydrologically Integrated Quantity and Quality Model for Annual Flows in the Regulated Macquarie River in Arid Australia

Water resource management traditionally depends on use of highly complex hydrological models designed originally to manage water for abstraction but increasingly relied on to determine ecological impacts and test ecological rehabilitation opportunities. These models are rarely independently tested. We compared a relatively simple statistical model, integrated flow and flood modelling (IFFM), with a complex hydrological model, the integrated quality and quantity model (IQQM), on the highly regulated Macquarie River of the Murray-Darling Basin, southeastern Australia. We compared annual flows (1891–2007) at three gauges to actual data and modelled output: before dams and diversions (unregulated) and after river regulation (regulated), using the goodness of fit (Nash-Sutcliffe coefficient of efficiency) and nonparametric tests. IQQM underestimated impacts of river regulation respectively on median and average flows at the Macquarie Marshes (Oxley gauge) by about 10% and 16%, compared to IFFM. IFFM model output more closely matched actual unregulated and regulated flows than IQQM which tended to underestimate unregulated flows and overestimate regulated flows at the Ramsar-listed wetland. Output was reasonably similar for the two models at the other two flow gauges. Relatively simple statistical models could more reliably estimate ecological impact at floodplains of large river systems, as well as an independent assessment tool compared to complex hydrological models. Finally, such statistical models may be valuable for predicting ecological responses to environmental flows, given their simplicity and relative ease to run.     

FROM FLOW TO FISH TO DOLLARS: AN INTEGRATED APPROACH TO WATER ALLOCATION1

This paper details a case study of economic and natural system responses to alternative water management policies in the Cache La Poudre River basin, Colorado, 1980–1994. The case study is presented to highlight the value and application of a conceptual integration of economic, salmonid population, physical habitat, and water allocation models. Five alternative regimes, all intended to increase low winter flows, were investigated. Habitat enhancements created by alternative regimes were translated to population responses and economic benefits. Analysis concluded that instream flows cannot compete on the northern Colorado water rental market; cooperative agreements offer an economically feasible way to enhance instream flows; and establishing an instream flow program on the Cache La Poudre River mainstem is a potentially profitable opportunity. The alliance of models is a dynamic multidisciplinary tool for use in professional settings and offers valuable insight for decision-making processes involved in water management.     

Comparison of Morphodynamic Models for the Lower Yellow River1

Xia, Junqiang, Zhengbing Wang, Yanping Wang, and Xin Yu, 2012. Comparison of Morphodynamic Models for the Lower Yellow River. Journal of the American Water Resources Association (JAWRA) 1‐18. DOI: 10.1111/jawr.12002 Abstract: Significant channel adjustments often occur during flood seasons in the Lower Yellow River (LYR), and it is a challenging work to accurately simulate the morphodynamic processes in the LYR using numerical models. A comparison of two morphodynamic models (Delft3D and 2DLLCDM) for the LYR is presented herein to identify critical improvements for these models. The concepts of these models are first compared with each other. The models were then used to simulate the processes of flood routing, sediment transport, and morphological changes occurring in a braided reach of the LYR. The differences were investigated between the simulated results from these models and corresponding field measurements, and the results indicate that: (1) the hydrodynamic processes calculated by both models agree closely with the measurements if an appropriate Manning’s roughness coefficient is used; (2) the concentrations of suspended load at the downstream boundary calculated by the models agree reasonably with the observed data; and (3) the predicted cross‐sectional profiles obtained from these models do not correspond well with the measurements. Based on these findings, the weak aspects of the models are clarified, and three critical improvements are recommended, including: (1) the development of roughness predictor; (2) the refinement of graded sediment transport capacity formulation; and (3) the consideration of bank erosion module. These improvements need to be implemented in the future.     

Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins1

Jin, Xin and Venkataramana Sridhar, 2012. Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins. Journal of the American Water Resources Association (JAWRA) 48(2): 197‐220. DOI: 10.1111/j.1752‐1688.2011.00605.x Abstract: In the Pacific Northwest, warming climate has resulted in a lengthened growing season, declining snowpack, and earlier timing of spring runoff. This study characterizes the impact of climate change in two basins in Idaho, the Spokane River and the Boise River basins. We simulated the basin‐scale hydrology by coupling the downscaled precipitation and temperature outputs from a suite of global climate models and the Soil and Water Assessment Tool (SWAT), between 2010 and 2060 and assess the impacts of climate change on water resources in the region. For the Boise River basin, changes in precipitation ranged from ?3.8 to 36%. Changes in temperature were expected to be between 0.02 and 3.9°C. In the Spokane River region, changes in precipitation were expected to be between ?6.7 and 17.9%. Changes in temperature appeared between 0.1 and 3.5°C over a period of the next five decades between 2010 and 2060. Without bias‐correcting the simulated streamflow, in the Boise River basin, change in peak flows (March through June) was projected to range from ?58 to +106 m³/s and, for the Spokane River basin, the range was expected to be from ?198 to +88 m³/s. Both the basins exhibited substantial variability in precipitation, evapotranspiration, and recharge estimates, and this knowledge of possible hydrologic impacts at the watershed scale can help the stakeholders with possible options in their decision‐making process.     

Estimation of Mussel Population Response to Hydrologic Alteration in a Southeastern U.S. Stream

The southeastern United States has experienced severe, recurrent drought, rapid human population growth, and increasing agricultural irrigation during recent decades, resulting in greater demand for the water resources. During the same time period, freshwater mussels (Unioniformes) in the region have experienced substantial population declines. Consequently, there is growing interest in determining how mussel population declines are related to activities associated with water resource development. Determining the causes of mussel population declines requires, in part, an understanding of the factors influencing mussel population dynamics. We developed Pradel reverse-time, tag-recapture models to estimate survival, recruitment, and population growth rates for three federally endangered mussel species in the Apalachicola–Chattahoochee–Flint River Basin, Georgia. The models were parameterized using mussel tag-recapture data collected over five consecutive years from Sawhatchee Creek, located in southwestern Georgia. Model estimates indicated that mussel survival was strongly and negatively related to high flows during the summer, whereas recruitment was strongly and positively related to flows during the spring and summer. Using these models, we simulated mussel population dynamics under historic (1940–1969) and current (1980–2008) flow regimes and under increasing levels of water use to evaluate the relative effectiveness of alternative minimum flow regulations. The simulations indicated that the probability of simulated mussel population extinction was at least 8 times greater under current hydrologic regimes. In addition, simulations of mussel extinction under varying levels of water use indicated that the relative risk of extinction increased with increased water use across a range of minimum flow regulations. The simulation results also indicated that our estimates of the effects of water use on mussel extinction were influenced by the assumptions about the dynamics of the system, highlighting the need for further study of mussel population dynamics.     

A SIMULATION OF RIVER-BASIN RESPONSE TO MESOSCALE METEOROLOGICAL FORCING: THE SUSQUEHANNA RIVER BASIN EXPERIMENT (SRBEX)1

ABSTRACT: A mesoscale meteorological model, a surface hydrology model, and a ground-water hydrology model are linked to simulate the hydrographic response of a large river basin to a single storm. Synoptic climatology is employed to choose a representative hydro-climatic event. The mesoscale meteorological model uses three nested domains to simulate relatively high-resolution precipitation over a sub-basin of the Susquehanna River Basin. The hydrology models simulate surface runoff and ground-water baseflow using both analyzed and simulated precipitation. The hydrologic abstractions are handled using both Curve Number and Green-Ampt routines. To support the linkage of the numerical models, special attention is given to data resampling and reprojection. The mesoscale meteorological model simulation captures the spatial and temporal structure of the storm event, while the hydrology models represent the timing of the event well. The Curve Number method generates a realistic hydrograph with both analyzed and simulated precipitation. In contrast, the hydrographic response generated by the Green-Ampt routine is inferior. Several interrelated factors contribute to these results, including: the nature of the precipitation event chosen for the experiment; the tendency of the mesoscale meteorological model to underpredict low intensity, widespread precipitation in this case; and the influence of the surface soil-texture characteristics on infiltration rates.     

Statistical Models to Predict and Assess Spatial and Temporal Low‐Flow Variability in New England Rivers and Streams

In the northern hemisphere, summer low flows are a key attribute defining both quantity and quality of aquatic habitat. I developed one set of models for New England streams/rivers predicting July/August median flows averaged across 1985–2015 as a function of weather, slope, % imperviousness, watershed storage, glacial geology, and soils. These models performed better than most United States Geological Survey models for summer flows developed at a statewide scale. I developed a second set of models predicting interannual differences in summer flows as a function of differences in air temperature, precipitation, the North Atlantic Oscillation (NAO) index, and lagged NAO. Use of difference equations eliminated the need for transformations and accounted for serial autocorrelations at lag 1. The models were used in sequence to estimate time series for monthly low flows and for two derived flow metrics (tenth percentile [Q10] and minimum 3‐in‐5 year average flows). The first metric is commonly used in assessing risk to low‐flow conditions over time, while the second has been correlated with increased probability of localized extinctions for brook trout. The flow metrics showed increasing trends across most of New England for 1985–2015. However, application of summer flow models with average and extreme climate projections to the Taunton River, Massachusetts, a sensitive watershed undergoing rapid development, projected that low‐flow metrics will decrease over the next 50 years.     

Comparing Environmental Flow Implementation Options with Structured Decision Making: Case Study from the Willamette River,Oregon

Many frameworks have been used to identify environmental flows for sustaining river ecosystems or specific taxa in the face of widespread flow alteration. However, these frameworks largely focus on identifying suitable flows and often ignore the important links between management actions, resulting flows, and valued ecosystem or social responses. Structured decision making (SDM) could assist the comparison of environmental flows by providing a mature framework to link management actions to objectives via environmental flow science. We describe SDM and illustrate its application using a case study focused on comparing environmental flow scenarios for the mainstem Willamette River, Oregon. In a short timeframe, SDM was applied to identify objectives, develop empirical and expert opinion‐based models, and compare flow scenarios while accounting for interannual flow variability and partial controllability. No scenario was clearly preferred based on available knowledge, largely because river flows could only be partially controlled through dam operations. Participants agreed that SDM was useful for comparing alternative dam operations, but that refined predictive models and additional objectives were needed to better inform basinwide flow decisions. In our view, SDM can provide more realistic comparisons of environmental flows by accounting for partial controllability and uncertainty, which may result in greater implementation of available flow management actions.     

KALMAN FILTER ESTIMATION AND PREDICTION OF DAILY STREAM FLOWS: I. REVIEW,ALGORITHM, AND SIMULATION EXPERIMENTS1

An important class of models, frequently used in hydrology for the forecasting of hydrologic variables one or more time periods ahead, or for the generation of synthetic data sequences, is the class of autoregressive(AR) models. As the AR models belong to the family of linear stochastic difference equations, they have both a deterministic and a stochastic component. The stochastic component is often assumed to have a Gaussian distribution. It is well known that hydrologic observations (e.g., stream flows) are heavily affected by noise. To account explicitly for the observation noise, the linear stochastic difference equation is expressed in state variable form and an observation model is introduced. The discrete Kalman filter algorithm can then be used to obtain estimates of the state variable vector. Typically, in hydrologic systems, model parameters, system noise statistics and measurement noise statistics are unknown, and have to be estimated. In this study an adaptive algorithm is discussed which estimates these quantities simultaneously with the state variables. The performance of the algorithm is evaluated by using simulated data.     

Climate Change and Floodplain Delineation in Two Southern Quebec River Basins1

Laforce, Serge, Marie‐Claude Simard, Robert Leconte, and François Brissette, 2011. Climate Change and Floodplain Delineation in Two Southern Quebec River Basins. Journal of the American Water Resources Association (JAWRA) 47(4):785‐799. DOI: 10.1111/j.1752‐1688.2011.00560.x Abstract: A methodology is presented for mapping the flooded extent of rivers under projected climate change. The methodology follows a top‐down modeling approach, where future climate projections generated by global climate models (GCMs) are downscaled to the watershed scale and used as input to hydrological and hydrodynamic models for predicting future river flows and associated open water levels. A range of possible future climate responses are taken into account, allowing quantification of flood‐mapping uncertainties resulting from GCM structure and greenhouse gas emission scenarios (GHGES). Probabilistic projections of future flood zones are developed by assuming that all GCMs and GHGES be equally weighted. The proposed methodology was applied to two river basins located in southern Quebec, Canada, for the time horizons 2020 and 2080. Twenty‐ and hundred‐year floods were computed and corresponding flood maps have been produced. Results indicate that there is a general trend toward an increased spring peak discharge for the Châteauguay River Basin and a decrease for the du Nord River Basin at the 2020 horizon. A less obvious trend was observed for the 2080 horizon, some GCM‐GHGES producing an increase in spring peak flows, whereas others would result in a less severe spring flood. These uncertainties in flood flows have cascaded into uncertainties in the corresponding flooded extent and represented as probabilistic flood maps.