Impact of Watershed Subdivision and Soil Data Resolution on SWAT Model Calibration and Parameter Uncertainty1

Abstract: Impact of watershed subdivision and soil data resolution on Soil Water Assessment Tool (SWAT) model calibration and parameter uncertainty is investigated by creating 24 different watershed model configurations for two study areas in northern Indiana. SWAT autocalibration tool is used to calibrate 14 parameters for simulating seven years of daily streamflow records. Calibrated parameter sets are found to be different for all 24 watershed configurations, however in terms of calibrated model output, their effect is minimal. In some cases, autocalibration is followed by manual calibration to correct for low flows, which were underestimated during autocalibration. In addition to normal validation using four years of streamflow data for each calibrated parameter set, cross‐validation (using a calibrated parameter set from one model configuration to validate observations using another configuration) is performed to investigate the effect of different model configurations on streamflow prediction. Results show that streamflow output during cross‐validation is not affected, thus highlighting the non‐unique nature of calibrated parameters in hydrologic modeling. Finally, parameter uncertainty is investigated by extracting good parameter sets during the autocalibration process. Parameter uncertainty analysis suggests that significant parameters show very narrow range of uncertainty across different watershed configurations compared with nonsignificant parameters. Results from recalibration of some configurations using only six significant parameters were comparable to that from calibration using 14 parameters, suggesting that including fewer significant parameters could reduce the uncertainty arising from model parameters, and also expedite the calibration process.     

Parameter Uncertainty Reduction for SWAT Using Grace,Streamflow, and Groundwater Table Data for Lower Missouri River Basin1

Abstract: This study incorporates the newly available Gravity Recovery and Climate Experiment (GRACE) water storage data and water table data from well logs to reduce parameter uncertainty in Soil and Water Assessment Tool (SWAT) calibration using a SUFI2 (sequential uncertainty fitting) framework for the Lower Missouri River Basin. Model evaluations are performed in multiple stages using a multiobjective function consisting of multisite streamflow and GRACE water storage data as well as a groundwater component. Results show that (1) a model calibrated with both streamflow and GRACE data simultaneously can maintain the water balance for the whole basin, but may improperly partition surface flow and base flow. Additional inclusion of the groundwater constraint can significantly improve the model performance in groundwater hydrological processes. In our case, the estimation of specific yield of shallow aquifers has been increased to 10^?2 from previous much underestimated level (<10^?3). (2) The daily streamflow data are needed to confine the parameters related to water flow in channels such as the Manning’s coefficient, which are less sensitive to the monthly simulations. (3) Parameters are nonuniformly sensitive for different goal variables, and thus, proper specification of a prior distribution of parameters may be the key factor for global optimization algorithms to obtain stable and realistic model performance.     

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.     

HYDROLOGIC EFFECTS OF TWO METHODS OF HARVESTING MATURE SOUTHERN PINE1

ABSTRACT: Hydrologic responses to logging with skidders and responses to logging with a cable yarder are compared. After a 23-year calibration with an undisturbed control catchment, mixed stands of shortleaf pine (Pinus echinata Mill.) and hardwoods were clearfelled on two small catchments in the hilly Coastal Plain of north Mississippi and observed for five years. Runoff increased 370 mm (skidded) and 116 mm (yarded) during the first year with 1876 mm of rainfall, and 234 mm (skidded) and 228 mm (yarded) during the second year when 1388 mm of precipitation equaled the calibration mean. Sediment concentrations for the yarded catchment during the first two years averaged 641 and 1,629 mg L^?1, respectively, and yields were 6,502 and 12,086 kg ha^?1. Compared to calibration means of 74 mg L^?1 and 142 kg ha^?1, these extreme values can be attributed largely to transport of sediment stored in the channel and to erosion of subsurface flow paths, which was exacerbated by high flow volumes. During the first year, the concentration (231 mg L^?1) and yield (2,827 kg ha^?1) for the control catchment also exceeded the calibration means. However, concentrations (134 mg L^?1) and yields (1,806 kg ha^?1) for the skidded catchment were about 40 percent lower than for the control catchment during the first year, and were higher than those for the control only during the second year. Because deep percolation was limited and because rainfall was unusually high, increases in flows and sediment concentrations and yields probably approximate maximum responses to clearcut harvesting in the uplands of the southern Coastal Plain.     

Assessment of spatial variation of cesium-137 in small catchments

Surface contamination by bomb-derived and Chernobyl-derived 137Cs has been subject to changes due to physical decay and lateral transport of contaminated soil particles, which have resulted in an on-going transfer of radionuclides from terrestrial ecosystems to surface water, river bed sediments, and flood plains. Knowledge of the different sources of spatial variation of 137Cs is particularly essential for estimating 137Cs transfer to fluvial systems and for successfully applying 137Cs as an environmental tracer in soil erosion studies. This study combined a straightforward sediment redistribution model and geostatistical interpolation of point samples of 137Cs activities in soil to distinguish the effects of sediment erosion and deposition from other sources of variation in 137Cs in the small Mochovce catchment in Slovakia. These other sources of variation could then be interpreted. Besides erosion and deposition processes, the initial pattern of 137Cs deposition, floodplain sedimentation, and short-range spatial variation were identified as the major sources of spatial variation of the 137Cs inventory.     

SENSITIVITY ANALYSIS,CALIBRATION, AND VALIDATIONS FOR A MULTISITE AND MULTIVARIABLE SWAT MODEL1

The ability of a watershed model to mimic specified watershed processes is assessed through the calibration and validation process. The Soil and Water Assessment Tool (SWAT) watershed model was implemented in the Beaver Reservoir Watershed of Northwest Arkansas. The objectives were to: (1) provide detailed information on calibrating and applying a multisite and multivariable SWAT model; (2) conduct sensitivity analysis; and (3) perform calibration and validation at three different sites for flow, sediment, total phosphorus (TP), and nitrate‐nitrogen (NO₃‐N) plus nitrite‐nitrogen (NO₂‐N). Relative sensitivity analysis was conducted to identify parameters that most influenced predicted flow, sediment, and nutrient model outputs. A multi objective function was defined that consisted of optimizing three statistics: percent relative error (RE), Nash‐Sutcliffe Coefficient (R_NS²), and coefficient of determination (R²). This function was used to successfully calibrate and validate a SWAT model of Beaver Reservoir Watershed at multi‐sites while considering multivariables. Calibration and validation of the model is a key factor in reducing uncertainty and increasing user confidence in its predictive abilities, which makes the application of the model effective. Information on calibration and validation of multisite, multivariable SWAT models has been provided to assist watershed modelers in developing their models to achieve watershed management goals.     

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.     

FORESTS AND OTHER FACTORS ASSOCIATED WITH STREAMFLOWS IN EAST TEXAS1

Effects of proportion of watersheds in forest and watershed physiographic factors on mean annual streamflow (1965-76), median flow, and 12 flood flow characteristics were regionally analyzed for 19 unregulated streams in East Texas. Annual streamflow increased with decreasing proportion of forest area. Differences in annual streamflow between full forest cover and bare watersheds could be as much as 200 mm. Other things being equal, the minimum watershed area required to generate 0.142 cm (5 cfs), a criterion used by the U.S. Corps of Engineering in regulating dredge and fill activity for water pollution abatement in East Texas streams, is 70 km² (27 mi²). Of the 31 physio-climatic parameters analyzed, watershed area, percent forest area, shape index, spring precipitation, and annual temperature were the most significant in affecting streamflow characteristics in East Texas. Using 2-3 of these five variables, all of the 14 streamflow characteristics can be estimated with accuracy ranging from acceptable to excellent levels.     

On the Role of Spatial,Temporal, and Climatic Forces on Stream Sediment Loading from Rural and Urban Ecosystems

In this study, we characterize the greatest sediment loading events by their sediment delivery behavior; dominant climate, watershed, and antecedent conditions; and their seasonal distribution for rural and urban land uses. The study area is Paradise Creek Watershed, a mixed land use watershed in northern Idaho dominated by saturation excess processes in the upstream rural area and infiltration excess in the downstream urban area. We analyzed 12 years of continuous streamflow, precipitation, and watershed data at two monitoring stations. We identified 137 sediment loading events in the upstream rural section of the watershed and 191 events in the downstream urban section. During the majority of these events conditions were transport limited and the sediment flush occurred early in the event, generally in the first 20% of elapsed event time. Statistical analysis including two dozen explanatory variables showed peak discharge, event duration, and antecedent baseflow explained most of the variation in event sediment load at both stations and for the watershed as a whole (R² = 0.73‐0.78). In the rural area, saturated soils combined with spring snowmelt in March led to the greatest loading events. The urban area load contribution peaked in January, which could be a re‐suspension of streambed sediments from the previous water year. Throughout the study period, one event contributed, on average, 33% of the annual sediment load but only accounted for 2% of the time in a year.     

Evaluation of SWAT Impoundment Modeling Methods in Water and Sediment Simulations

Worldwide studies show 80%–90% of all sediments eroded from watersheds is trapped within river networks such as reservoirs, ponds, and wetlands. To represent the impact of impoundments on sediment routing in watershed modeling, Soil and Water Assessment Tool (SWAT) developers recommend to model reservoirs, ponds, and wetlands using impoundment tools (ITs). This study evaluates performance of SWAT ITs in the modeling of a small, agricultural watershed dominated by lakes and wetlands. The study demonstrates how to incorporate impoundments into the SWAT model, and discusses and evaluates involved parameters. The study then recommends an appropriate calibration sequence, i.e., landscape parameters calibration, followed by pond/wetlands calibration, then channel parameter calibrations, and lastly, reservoir parameter calibration. Results of this study demonstrate not following SWAT recommendation regarding modeling water land use as an impoundment depreciates SWAT performance, and may lead to misplaced calibration efforts and model over‐calibration. Further, the chosen method to model impoundments’ outflow significantly impacts sediment loads in the watershed, while streamflow simulation is not very sensitive. This study also allowed calculation of mass accumulation rates in modeled impoundments where the annual mass accumulation rate in wetlands (2.3 T/ha/yr) was 39% higher than mass accumulation rate in reservoirs (1.4 T/ha/yr).     

AN OBJECTWE TEST FOR HYDROLOGIC SCALE1

ABSTRACT: Improving the reliability of parametric hydrologic models (sometimes called cenceptual rainfall-runoff models) in the continuous simulation of runoff from ungaged catchments has been frustrated by difficulties in estimating model parameters from catchment characteristics. An underlying problem is that these models use parameters to represent catchments as a whole, whereas data on catchment characteristics are collected at multiple field locations and are difficult to transform into one measure of collective impact. Subdividing the catchment and calibrating a stochastic parametric model to estimate distributions for the parameters that covered the range of observed streamflow values was found to improve the simulations. This paper presents an optimization of the amount of subdivision to use in simulation with a version of the Stanford Watershed Model using available climatological data. The calibration process assumes that catchment heterogeneity introduces errors that can be reduced by calibrating parameters as spatial distributions rather than single values. Calibrations for three diverse small gaged catchments located in California and in Virginia found the optimal number of subdivisions to range from 4 to 25 and the optimal scale to range from 0.3 to 2.1 mi².     

MODELING THE HYDROCHEMISTRY OF THE CANNONSVILLE WATERSHED WITH GENERALIZED WATERSHED LOADING FUNCTIONS (GWLF)1

ABSTRACT: A previous modeling study used the Generalized Watershed Loading Functions (GWLF) model to simulate stream‐flow, and nutrient and sediment loads to Cannonsville Reservoir from the West Branch Delaware River (WBDR). We made several model revisions, calibrated key parameters, and tested the original GWLF model and a revised GWLF model using more recent data. Model revisions included: addition of unsaturated leakage between unsaturated and saturated subsurface reservoirs; revised timing of sediment export; inclusion of urban sediments and dissolved nutrients; tracking of particulate nutrients from point sources; and revised timing of septic system loads. The revision of sediment yield timing resulted in significant improvements in monthly sediment and particulate phosphorus predictions as compared to the original model. Addition of unsaturated leakage improved hydrologic predictions during low flow months. The other model changes improve realism without adding significant model complexity or data requirements. Goodness of fit of revised model predictions versus stream measurements, as measured by the Nash‐Sutcliff coefficient of model efficiency, exceeded 0.8 for streamflow‐0.7 for sediment yield and dissolved nitrogen (N) and 0.6 for particulate and dissolved phosphorus (P). The revised GWLF model, with limited calibration, provides reasonable estimates of monthly streamflow, and nutrient and sediment loads in the Cannonsville watershed.     

Comparison of Unsteady and Quasi‐Unsteady Flow Models in Simulating Sediment Transport in an Ephemeral Arizona Stream1

Hummel, Ryan, Jennifer G. Duan, and Shiyan Zhang, 2012. Comparison of Unsteady and Quasi‐Unsteady Flow Models in Simulating Sediment Transport in an Ephemeral Arizona Stream. Journal of the American Water Resources Association (JAWRA) 48(5): 987‐998. DOI: 10.1111/j.1752‐1688.2012.00663.x Abstract: Hydrodynamic and sediment transport models are useful engineering tools for predicting unsteady flood flow and sediment transport. Many models such as HEC‐RAS, HEC‐6, and IALLUVIAL apply quasi‐unsteady flow model, whereas others apply the unsteady flow model. It remains unknown if a quasi‐unsteady flow model is sufficiently accurate for simulating sediment transport in rapidly varied unsteady flood events, especially in ephemeral rivers in arid and semiarid regions. This study compared the quasi‐unsteady HEC‐RAS 4.1 model with one‐dimensional (1D) Finite Volume Method (FVM) based model in simulating flood flow and sediment transport in the Pantano Wash, a dryland river in the state of Arizona. The objective is to determine which sediment transport method is appropriate in predicting bed elevation changes in an ephemeral stream, Pantano Wash, and if an unsteady model is more accurate than a quasi‐unsteady flow model in predicting sediment transport. Results showed that the quasi‐unsteady HEC‐RAS model and the 1D FVM yielded similar results of bed degradation and aggradation for this dryland stream, although the FVM model predicted better flood hydrographs. Among the seven sediment transport formulas embedded in HEC‐RAS, Yang’s and Engelund‐Hansen’s equations gave the best matches with the field measurements for this particular case study.     

Impact of Climate and Land Use Change on Streamflow and Sediment Yield in a Snow‐Dominated Semiarid Mountainous Watershed

This study investigates the impact of climate and land use change on the magnitude and timing of streamflow and sediment yield in a snow‐dominated mountainous watershed in Salt Lake County, Utah using a scenario approach and the Hydrological Simulation Program — FORTRAN model for the 2040s (year 2035–2044) and 2090s (year 2085–2094). The climate scenarios were statistically and dynamically downscaled from global climate models. Land use and land cover (LULC) changes were estimated in two ways — from a regional planning scenario and from a deterministic model. Results indicate the mean daily streamflow in the Jordan River watershed will increase by an amount ranging from 11.2% to 14.5% in the 2040s and from 6.8% to 15.3% in the 2090s. The respective increases in sediment load in the 2040s and 2090s is projected to be 6.7% and 39.7% in the canyons and about 7.4% to 14.2% in the Jordan valley. The historical 50th percentile timing of streamflow and sediment load is projected to be shifted earlier by three to four weeks by mid‐century and four to eight weeks by late‐century. The projected streamflow and sediment load results establish a nonlinear relationship with each other and are highly sensitive to projected climate change. The predicted changes in streamflow and sediment yield will have implications for water supply, flood control and stormwater management.     

MODELING METALS TRANSPORT AND SEDIMENT/WATER INTERACTIONS IN A MINING IMPACTED MOUNTAIN STREAM1

ABSTRACT: The U.S. Environmental Protection Agency (USEPA) Water Quality Analysis Simulation Program (WASP5) was used to model the transport and sediment/water interactions of metals under low flow, steady state conditions in Tenmile Creek, a mountain stream supplying drinking water to the City of Helena, Montana, impacted by numerous abandoned hard rock mines. The model was calibrated for base flow using data collected by USEPA and validated using data from the U.S. Geological Survey (USGS) for higher flows. It was used to assess metals loadings and losses, exceedances of Montana State water quality standards, metals interactions in stream water and bed sediment, uncertainty in fate and transport processes and model parameters, and effectiveness of remedial alternatives that include leaving contaminated sediment in the stream. Results indicated that during base flow, adits and point sources contribute significant metals loadings to the stream, but that shallow ground water and bed sediment also contribute metals in some key locations. Losses from the water column occur in some areas, primarily due to adsorption and precipitation onto bed sediments. Some uncertainty exists in the metal partition coefficients associated with sediment, significance of precipitation reactions, and in the specific locations of unidentified sources and losses of metals. Standards exceedances are widespread throughout the stream, but the model showed that remediation of point sources and mine waste near water courses can help improve water quality. Model results also indicate, however, that alteration of the water supply scheme and increasing base flow will probably be required to meet all water quality standards.     

Enhancing Hyrdological Simulation Program – FORTRAN Model Channel Hydraulic Representation1

Abstract: The hydrological simulation program – FORTRAN (HSPF) is a comprehensive watershed model that employs depth‐area‐volume‐flow relationships known as the hydraulic function table (FTABLE) to represent the hydraulic characteristics of stream channel cross‐sections and reservoirs. An accurate FTABLE determination for a stream cross‐section site requires an accurate determination of mean flow depth, mean flow width, roughness coefficient, longitudinal bed slope, and length of stream reach. A method that uses regional regression equations to estimate mean flow depth, mean flow width, and roughness coefficient is presented herein. FTABLES generated by the proposed method (Alternative Method) and FTABLES generated by Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) were compared. As a result, the Alternative Method was judged to be an enhancement over the BASINS method. First, the Alternative Method employs a spatially variable roughness coefficient, whereas BASINS employs an arbitrarily selected spatially uniform roughness coefficient. Second, the Alternative Method uses mean flow width and mean flow depth estimated from regional regression equations whereas BASINS uses mean flow width and depth extracted from the National Hydrography Dataset (NHD). Third, the Alternative Method offers an option to use separate roughness coefficients for the in‐channel and floodplain sections of compound channels. Fourth, the Alternative Method has higher resolution in the sense that area, volume, and flow data are calculated at smaller depth intervals than the BASINS method. To test whether the Alternative Method enhances channel hydraulic representation over the BASINS method, comparisons of observed and simulated streamflow, flow velocity, and suspended sediment were made for four test watersheds. These comparisons revealed that the method used to estimate the FTABLE has little influence on hydrologic calibration, but greatly influences hydraulic and suspended sediment calibration. The hydrologic calibration results showed that observed versus simulated daily streamflow comparisons had Nash‐Sutcliffe efficiencies ranging from 0.50 to 0.61 and monthly comparisons had efficiencies ranging from 0.61 to 0.84. Comparisons of observed and simulated suspended sediments concentrations had model efficiencies ranging from 0.48 to 0.56 for the daily, and 0.28 to 0.70 for the monthly comparisons. The overall results of the hydrological, hydraulic, and suspended sediment concentration comparisons show that the Alternative Method yielded a relatively more accurate FTABLE than the BASINS method. This study concludes that hydraulic calibration enhances suspended sediment simulation performance, but even greater improvement in suspended sediment calibration can be achieved when hydrological simulation performance is improved. Any improvements in hydrological simulation performance are subject to improvements in the temporal and spatial representation of the precipitation data.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Distributed Hydrologic Modeling in the Suburban Landscape: Assessing Parameter Transferability from Gauged Reference Catchments1

Mittman, Tamara, Lawrence E. Band, Taehee Hwang, and Monica Lipscomb Smith, 2012. Distributed Hydrologic Modeling in the Suburban Landscape: Assessing Parameter Transferability from Gauged Reference Catchments. Journal of the American Water Resources Association (JAWRA) 48(3): 546-557. DOI: 10.1111/j.1752-1688.2011.00636.x Abstract: Distributed, process-based models of catchment hydrologic response are potentially useful tools for the assessment of Low Impact Development (LID) techniques in urbanized catchments. Their application is often limited, however, by the lack of continuous streamflow records to calibrate poorly constrained parameters. This article examines the transferability of soil and groundwater parameters from a forested reference catchment to a nearby suburban catchment. We use the Regional Hydro-Ecologic Simulation System (RHESSys) to develop hydrologic models of one gauged forested and one ungauged suburban catchment within the Baltimore Ecosystem Study (BES) study area. We use a parameter uncertainty framework to calibrate soil and groundwater parameters for the forested catchment, and discrete measurements of streamflow from the suburban catchment to assess parameter transferability. Results indicate that the transfer of soil and groundwater parameters from forested reference to nearby suburban catchments is viable, with performance measures for the suburban catchment often exceeding those for the forested catchment. We propose that the simplification of hydrologic processes in urbanized catchments may account for the increase in model performance in the suburban catchment.     

REGIONALIZATION AND PREDICTION OF FLOODS IN THE FRASER RIVER CATCHMENT,B.C.1

Probability distributions that model the return periods of flood characteristics derived from partial duration series are proposed and tested in the Fraser River catchment of British Columbia. Theoretical distributions describing the magnitude, duration, frequency and timing of floods are found to provide a goof fit to the observed data. The five estimated parameters summarizing the flood characteristics of each basin are entered into a discriminant analysis procedure to establish flood regions. Three regions were identified, each displaying flood behavior closely related to the physical conditions of the catchment. Within each region, regression equations are obtained between parameter values and basin climatic and physiographic variables. These equations provide a satisfactory prediction of flood parameters and this allows the estimation of a comprehensive set of flood characteristics for areas with sparse hydrologic information.