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

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

GIS‐Based Predictive Models of Hillslope Runoff Generation Processes1

Abstract: Successful nonpoint source pollution control using best management practice placement is a complex process that requires in‐depth knowledge of the locations of runoff source areas in a watershed. Currently, very few simulation tools are capable of identifying critical runoff source areas on hillslopes and those available are not directly applicable under all runoff conditions. In this paper, a comparison of two geographic information system (GIS)‐based approaches: a topographic index model and a likelihood indicator model is presented, in predicting likely locations of saturation excess and infiltration excess runoff source areas in a hillslope of the Savoy Experimental Watershed located in northwest Arkansas. Based on intensive data collected from a two‐year field study, the spatial distributions of hydrologic variables were processed using GIS software to develop the models. The likelihood indicator model was used to produce probability surfaces that indicated the likelihood of location of both saturation and infiltration excess runoff mechanisms on the hillslope. Overall accuracies of the likelihood indicator model predictions varied between 81 and 87% for the infiltration excess and saturation excess runoff locations respectively. On the basis of accuracy of prediction, the likelihood indicator models were found to be superior (accuracy 81‐87%) to the predications made by the topographic index model (accuracy 69.5%). By combining statistics with GIS, runoff source areas on a hillslope can be identified by incorporating easily determined hydrologic measurements (such as bulk density, porosity, slope, depth to bed rock, depth to water table) and could serve as a watershed management tool for identifying critical runoff source areas in locations where the topographic index or other similar methods do not provide reliable results.     

EFFECTS OF INITIAL ABSTRACTION AND URBANIZATION ON ESTIMATED RUNOFF USING CN TECHNOLOGY1

ABSTRACT: Few studies have been conducted to explore the effects of initial abstraction on estimated direct runoff despite the widespread use of the curve number (CN) method in many hydrologic models to estimate direct runoff. In this study, use of a 5 percent ratio of initial abstraction (I_a) to storage (S) to estimate daily direct runoff with modified CN values for a 5 percent I_a/S value was investigated using the Long‐Term Hydrologic Impact Assessment (L‐THIA) geographic information system (GIS). In addition, the effects on estimated runoff of altering the hydrologic soil group due to urbanization were investigated. The L‐THIA model was applied to the Indiana Little Eagle Creek watershed with 5 percent and 20 percent I_a/S values, considering hydrologic soil group alteration due to urbanization. The results indicate that uses of a 5 percent l_a/S and modified CN values and Hydrologic Soil Group D for urbanized areas in model runs can improve long term direct runoff prediction.     

A Multilevel Model of the Impact of Farm‐Level Best Management Practices on Phosphorus Runoff1

Abstract: Multilevel or hierarchical models have been applied for a number of years in the social sciences but only relatively recently in the environmental sciences. These models can be developed in either a frequentist or Bayesian context and have similarities to other methods such as empirical Bayes analysis and random coefficients regression. In essence, multilevel models take advantage of the hierarchical structure that exists in many multivariate datasets; for example, water quality measurements may be taken from individual lakes, lakes are located in various climatic zones, lakes may be natural or man‐made, and so on. The groups, or levels, may effectively yield different responses or behaviors (e.g., nutrient load response in lakes) that often make retaining group membership more effective when developing a predictive model than when working with either all of the data together or working separately with the individuals. Here, we develop a multilevel model of the impact of farm level best management practices (BMPs) on phosphorus runoff. The result of this research is a model with parameters which vary with key practice categories and thus may be used to evaluate the effectiveness of these practices on phosphorus runoff. For example, it was found that the effect of fertilizer application rate on farm‐scale phosphorus loss is a function of the application method, the hydrologic soil group, and the land use (crop type). Further, results indicate that the most effective method for controlling fertilizer loss is through soil injection. In summary, the resultant multilevel model can be used to estimate phosphorus loss from farms and hence serve as a useful tool for BMP selection.     

HYDROLOGIC IMPACTS OF ALTERNATIVE APPROACHES TO STORM WATER MANAGEMENT AND LAND DEVELOPMENT1

Low impact development (LID) and other land development methods have been presented as alternatives to conventional storm water management and site design. Low impact development encourages land preservation and use of distributed, infiltration‐based storm water management systems to minimize impacts on hydrology. Such systems can include shallow retention areas, akin to natural depression storage. Other approaches to land development may emphasize land preservation only. Herein, an analysis of four development alternatives is presented. The first was Traditional development with conventional pipe/pond storm water management and half‐acre lots. The second alternative was Cluster development, in which implementation of the local cluster development ordnance was assumed, resulting in quarter‐acre lots with a pipe/pond storm water management system and open space preservation. The “Partial” LID option used the same lot layout as the Traditional option, with a storm water management system emphasizing shallow depression storage. The “Full” LID used the Cluster site plan and the depression storage‐based storm water management system. The alternatives were compared to the hydrologic response of existing site conditions. The analysis used two design storms and a continuous rainfall record. The combination of land preservation and infiltration‐based storm water management yielded the hydrologic response closest to existing conditions, although ponds were required to control peak flows for the design storms.     

THE FLEXIBLE TOLERANCE METHOD FOR ESTIMATING HYDROLOGIC PARAMETERS IN THE ROOT ZONE1

In this study, a constrained minimization method, the flexible tolerance method, was used to solve the optimization problems for determining hydrologic parameters in the root zone: water uptake rate, spatial root distribution, infiltration rate, and evaporation. Synthetic soil moisture data were first generated using the Richards' equation and its associated initial and boundary conditions, and these data were then used for the inverse analyses. The results of inverse simulation indicate the following. If the soil moisture data contain no noise, the rate of estimated water uptake and spatial root distribution parameters are equal to the true values without using constraints. If there is noise in the observed data, constraints must be used to improve the quality of the estimate results. In the estimation of rainfall infiltration and surface evaporation, interpolation methods should be used to reduce the number of unknowns. A fewer number of variables can improve the quality of inversely estimated parameters. Simultaneous estimation of spatial root distribution and water uptake rate or estimation of evaporation and water uptake rate is possible. The method was used to estimate the water uptake rate, spatial root distribution, infiltration rate, and evaporation using long‐term soil moisture data collected from Nebraska's Sand Hills.     

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.     

Filyos River Streamflow Reconstruction from Tree‐Ring Chronologies with Nonparametric Approaches

The article presents nonparametric methods based on K nearest neighbors (KNNs), modified KNNs, and local polynomial techniques to reconstruct streamflow ensembles from tree‐ring data in Filyos River region (Turkey). Three methods were tested using cross‐validation for the overlap period, 1963‐1997 for which the tree‐ring and streamflow data are available. It was found that for the study where the length of the overlap period was limited, a nonparametric method based on a local polynomial technique provides simulations that have a slightly better solution than the other methods. After verification using standard statistical techniques, these methods were utilized to develop streamflow reconstructions from tree‐ring data for the paleo‐hydrologic period (1657‐1963). These reconstructions of seasonal low and high flows were discussed with the obtained flood duration curve. They were also compared with the historical archives and other tree‐ring reconstructions data available in the same river. Overall, the utility and limitations of these methods and the resulting streamflow simulations were discussed to assess the long‐term discharge behavior of Filyos River and to evaluate water supply reliability.     

Modeling Postfire Response and Recovery using the Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS)1

Abstract: This paper investigates application of the Army Corps of Engineers’ Hydrologic Engineering Center Hydrologic Modeling System (HEC‐HMS) to a burned watershed in San Bernardino County, California. We evaluate the HEC‐HMS’ ability to simulate discharge in prefire and postfire conditions in a semi arid watershed and the necessary parameterizations for modeling hydrologic response during the immediate, and subsequent recovery, period after a wildfire. The model is applied to City Creek watershed, which was 90% burned during the Old Fire of October 2003. An optimal spatial resolution for the HEC‐HMS model was chosen based on an initial sensitivity analysis of subbasin configurations and related model performance. Five prefire storms were calibrated for the selected model resolution, defining a set of parameters that reasonably simulate prefire conditions. Six postfire storms, two from each of the following rainy (winter) seasons were then selected to simulate postfire response and evaluate relative changes in parameter values and model behavior. There were clear trends in the postfire parameters [initial abstractions (I_a), curve number (CN), and lag time] that reveal significant (and expected) changes in watershed behavior. CN returns to prefire (baseline) values by the end of Year 2, while I_a approaches baseline by the end of the third rainy season. However, lag time remains significantly lower than prefire values throughout the three‐year study period. Our results indicate that recovery of soil conditions and related runoff response is not entirely evidenced by the end of the study period (three rainy seasons postfire). Understanding the evolution of the land surface and related hydrologic properties during the highly dynamic postfire period, and accounting for these changes in model parameterizations, will allow for more accurate and reliable discharge simulations in both the immediate, and subsequent, rainy seasons following fire.     

An Open Source GIS‐Based Decision Support System for Watershed Evaluation of Best Management Practices

Economic costs, water quantity/quality benefits, and cost effectiveness of agricultural best management practices (BMPs) at a watershed scale are increasingly examined using integrated economic‐hydrologic models. However, these models are typically complex and not user‐friendly for examining the effects of various BMP scenarios. In this study, an open source geographic information system (GIS)‐based decision support system (DSS), named the watershed evaluation of BMPs (WEBs), was developed for creating BMP scenarios and simulating economic costs and water quantity/quality benefits at farm field, subbasin, and watershed scales. This DSS or WEBs interface integrated a farm economic model, the Soil and Water Assessment Tool (SWAT), and an optimization model within Whitebox Geospatial Analysis Tools (GAT), an open source GIS software. The DSS was applied to the 14.3‐km² Gully Creek watershed, a coastal watershed in southern Ontario, Canada that drains directly into Lake Huron. BMPs that were evaluated included conservation tillage, nutrient management, cover crop, and water and sediment control basins. In addition to assessing economic costs, water quantity/quality benefits, and cost effectiveness of BMPs, the DSS can be also used to examine prioritized BMP types/locations and corresponding economic and water quantity/quality tradeoffs in the study watershed based on environmental targets or budget constraints. Further developments of the DSS including interface transfer to other watersheds are also discussed. 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.     

Optimizing Agricultural Best Management Practices in a Lake Erie Watershed

Implementing agricultural best management practices (BMPs) is influenced by a balance of desired environmental outcomes, economic feasibility, and stakeholder familiarity, the latter taken to be related to BMP acceptability. To explore this balance, we developed a multi‐objective decision support system for allocating BMP type and placement by coupling the Soil and Water Assessment Tool with a nondominated sorted genetic algorithm that minimizes total phosphorus (TP) yields from agricultural hydrologic response units (HRUs) and costs, while using stakeholder BMP familiarity as a constraint; conventional tillage, no tillage, nutrient management, riparian buffers, and contour cropping were explored. Using constraints representing current conditions, the optimization resulted in 59.6 to 81.0% reduction in agricultural TP yield from HRUs at costs ranging between US $0.8 and US $5.3 million. The constrained optimization tended to select mostly single BMPs or at most two BMPs for a given HRU due to these BMPs having higher acceptability to stakeholders. In contrast, the unconstrained case, representing full familiarity, selected 2‐ and 3‐BMP applications. There was little difference in costs between the constrained and unconstrained cases below an 80% TP yield reduction; however, significant differences were found at larger reductions, supporting the value of stakeholder education and extension efforts. 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.     

A Hydrologic Drying Bias in Water‐Resource Impact Analyses of Anthropogenic Climate Change

For water‐resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (E_p) as inputs. Because E_p is not a climate‐model output, an intermediary model of E_p must be introduced to connect the climate model to the hydrologic model. Several E_p methods are used. The suitability of each can be assessed by noting a credible E_p method for offline analyses should be able to reproduce climate models’ ACC‐driven changes in actual evapotranspiration in regions and seasons of negligible water stress (E_w). We quantified this ability for seven commonly used E_p methods and for a simple proportionality with available energy (“energy‐only” method). With the exception of the energy‐only method, all methods tend to overestimate substantially the increase in E_p associated with ACC. In an offline hydrologic model, the E_p‐change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC‐induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water‐resource impact analyses.     

Hydrologic Landscape Classification to Estimate Bristol Bay,Alaska Watershed Hydrology

Hydrologic landscapes (HLs) have proven to be a useful tool for broad scale assessment and classification of landscapes across the United States as they help organize larger geographical areas into areas of similar hydrologic characteristics. We developed a HL classification for the Bristol Bay watershed of southwest Alaska that incorporates indices of annual climate and seasonality, terrain, geology, and the influences of large lakes and glaciers. A HL classification is particularly useful in this large watershed because of its hydrologic and landscape variability, important salmon fishery, variety of environmental and potential anthropogenic stressors, and lack of widespread hydrologic data. Following creation of Bristol Bay basin‐wide HL classes, we compared the HL distributions within watersheds grouped by two calculated runoff parameters derived from available long‐term streamflow records and found HL distributions within these groups provided predictive insight on hydrologic behavior. Using these developed runoff groups, we estimated expected hydrologic behavior in watersheds across the larger Bristol Bay watershed that lacked gauged streamflow records. The HL approach provides a scientific basis for estimating the first‐order hydrologic behavior of watersheds and landscapes that lack detailed hydrologic information.     

ESTIMATING ATRAZINE LEACHING IN THE MIDWEST1

Data from seven Management Systems Evaluation Areas (MSEA) were used to test the sensitivity of a leaching model, Pesticide Root Zone Model-2, to a variety of hydrologic settings in the Midwest. Atrazine leaching was simulated because it was prevalent in the MSEA studies and is frequently detected in the region's groundwater. Short-term simulations used site specific soil and chemical parameters. Generalized simulations used data avail. able from regional soil databases and standardized variables. Accurate short-term simulations were precluded by lack of antecedent atrazine concentrations in the soil profile and water, suggesting that simulations using data for less than five years underestimate atrazine leaching. The seven sites were ranked in order of atrazine detection frequency (concentration > 0.2 μg L^-1) in soil water at 2 m depth in simulations. The rank order of the sites based on long-term simulations were similar to the ranks of sites based on atrazine detection frequency from groundwater monitoring. Simulations with Map Unit Use File (MUUF) soils data were more highly correlated with ranks of observed atrazine detection frequencies than were short-term simulations using site-specific soil data. Simulations using the MIJUIF data for soil parameters were sufficiently similarity to observed atrazine detection to allow the credible use of regional soils data for simulating leaching with PRZM-2 in a variety of Midwest soil and hydrologic conditions. This is encouraging for regional modeling efforts because soil parameters are among the most critical for operating PRZM-2 and many other leaching models.     

SPATIALLY EXPLICIT HYDROLOGIC MODELING OF LAND USE CHANGE1

ABSTRACT: Using a Geographic Information System (GIS), a method is presented to develop a spatially explicit time series of land use in an urbanizing watershed. The method is prefaced on the existence of independent observations of land use at different times and data that describes the spatial‐temporal land use transition characteristics of the watershed between these two points in time. A method is then presented to generalize the TR‐55 graphical method, a common lumped hydrologic model for estimating peak discharge, for use in a spatially explicit scheme. This scheme predicts peak discharge throughout a watershed, rather than at a single selected watershed outlet. Coupling these two methods allows the engineer to model both the temporal and spatial evolution of peak discharge for the watershed. An illustrative watershed in a suburban area of Washington, DC is selected to demonstrate the methods. The model results from these analyses are presented graphically to highlight the complex features in peak discharge behavior that exist both spatially, as a function of position within the watershed drainage network, and temporally, as the watershed undergoes urbanization. These features are not commonly noted in most hydrologic analyses but are captured in these analyses because of the high spatial and temporal resolution of the methods presented. The physical implications of the modeled results are discussed in the context of the information content of a stream gauge located at the overall outlet of the illustrative watershed. This work shows that the common practice of transposition of gauge information to locations internal to the watershed would neglect internal variability in peak discharge behavior, and could potentially lead to the determination of inappropriate design discharges.     

EVALUATION OF THE APPLICABILITY OF THE SWAT MODEL FOR COASTAL WATERSHEDS IN SOUTHEASTERN LOUISIANA1

ABSTRACT: The Soil and Water Assessment Tool (SWAT) has been used for hydrologic analyses at various watershed scales. However, little is known about the model's performance in coastal watersheds. In this study SWAT was evaluated for its applicability in three Louisiana coastal watersheds: the Amite, Tickfaw, and Tangipahoa River watersheds. The model was calibrated with daily discharge from 1976 to 1977 and validated from 1979 to 1999 for the Amite and Tangipahoa and with daily discharge from 1979 to 1989 for the Tickfaw. Deviation of mean discharge and the Nash‐Sutcliffe model efficiency were used to evaluate model behavior. The study found that Manning's roughness coefficient for the main channel, SCS curve number, and soil evaporation compensation factor were the most sensitive parameters for these coastal watersheds. The Manning's roughness coefficient showed the greatest effect on the response time of surface runoff, suggesting the critical role of channel routing in hydrologic modeling for lowland watersheds. The SWAT model demonstrated an excellent performance, with Nash‐Sutcliffe efficiencies of 0.935, 0.940, and 0.960 for calibrations of the Amite, Tickfaw, and Tangipahoa watersheds, respectively, and of 0.851, 0.811, and 0.867 for validations. The modeling results demonstrate that SWAT is capable of simulating hydrologic processes for medium scale to large scale coastal lowland watersheds in Louisiana.     

A WATER QUALITY‐BASED APPROACH FOR WATERSHED WIDE BMP STRATEGIES1

ABSTRACT: Watershed management strategies generally involve controlling nonpoint source pollution by implementing various best management practices (BMPs). Currently, stormwater management programs in most states use a performance‐based approach to implement onsite BMPs. This approach fails to link the onsite BMP performance directly to receiving water quality benefits, and it does not take into account the combined treatment effects of all the stormwater management practices within a watershed. To address these issues, this paper proposes a water quality‐based BMP planning approach for effective nonpoint source pollution control at a watershed scale. A coupled modeling system consisting of a watershed model (HSPF) and a receiving water quality model (CE‐QUAL‐W2) was developed to establish the linkage between BMP performance and receiving water quality targets. A Monte Carlo simulation approach was utilized to develop alternative BMP strategies at a watershed level. The developed methodology was applied to the Swift Creek Reservoir watershed in Virginia, and the results show that the proposed approach allows for the development of BMP strategies that lead to full compliance with water quality requirements.     

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

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

ADEQUACY OF SELECTED EVAPOTRANSPIRATION APPROXIMATIONS FOR HYDROLOGIC SIMULATION1

ABSTRACT: Evapotranspiration (ET) approximations, usually based on computed potential ET (PET) and diverse PET‐to‐ET conceptualizations, are routinely used in hydrologic analyses. This study presents an approach to incorporate measured (actual) ET data, increasingly available using micrometeorological methods, to define the adequacy of ET approximations for hydrologic simulation. The approach is demonstrated at a site where eddy correlation‐measured ET values were available. A baseline hydrologic model incorporating measured ET values was used to evaluate the sensitivity of simulated water levels, subsurface recharge, and surface runoff to error in four ET approximations. An annually invariant pattern of mean monthly vegetation coefficients was shown to be most effective, despite the substantial year‐to‐year variation in measured vegetation coefficients. The temporal variability of available water (precipitation minus ET) at the humid, subtropical site was largely controlled by the relatively high temporal variability of precipitation, benefiting the effectiveness of coarse ET approximations, a result that is likely to prevail at other humid sites.