Modeling Parent and Metabolite Fate and Transport in Subsurface Drained Fields With Directly Connected Macropores1

Abstract: Few studies exist that evaluate or apply pesticide transport models based on measured parent and metabolite concentrations in fields with subsurface drainage. Furthermore, recent research suggests pesticide transport through exceedingly efficient direct connections, which occur when macropores are hydrologically connected to subsurface drains, but this connectivity has been simulated at only one field site in Allen County, Indiana. This research evaluates the Root Zone Water Quality Model (RZWQM) in simulating the transport of a parent compound and its metabolite at two subsurface drained field sites. Previous research used one of the field sites to test the original modification of the RZWQM to simulate directly connected macropores for bromide and the parent compound, but not for the metabolite. This research will evaluate RZWQM for parent/metabolite transformation and transport at this first field site, along with evaluating the model at an additional field site to evaluate whether the parameters for direct connectivity are transferable and whether model performance is consistent for the two field sites with unique soil, hydrologic, and environmental conditions. Isoxaflutole, the active ingredient in BALANCE^® herbicide, was applied to both fields. Isoxaflutole rapidly degrades into a metabolite (RPA 202248). This research used calibrated RZWQM models for each field based on observed subsurface drain flow and/or edge of field conservative tracer concentrations in subsurface flow. The calibrated models for both field sites required a portion (approximately 2% but this fraction may require calibration) of the available water and chemical in macropore flow to be routed directly into the subsurface drains to simulate peak concentrations in edge of field subsurface drain flow shortly after chemical applications. Confirming the results from the first field site, the existing modification for directly connected macropores continually failed to predict pesticide concentrations on the recession limbs of drainage hydrographs, suggesting that the current strategy only partially accounts for direct connectivity. Thirty‐year distributions of annual mass (drainage) loss of parent and metabolite in terms of percent of isoxaflutole applied suggested annual simulated percent losses of parent and metabolite (3.04 and 1.31%) no greater in drainage than losses in runoff on nondrained fields as reported in the literature.     

REVIEW AND ANALYSIS OF METHODS FOR QUANTIFYING INSTREAM FLOW REQUIREMENTS1

ABSTRACT: Present guidelines for selecting a method to determine instream flow requirements and evaluating the validity of the results from a particular method are insufficient. This paper contributes to the efforts of researchers to develop a guide and critique for instream flow methods. A review of instreani flow methods and recommendations for their application is supplemented by a summary of a comparison of four independent analyses. The four analyses: the Physical Habitat Simulation System approach of the Instream Flow Incremental Methodology by the U.S. Fish and Wildlife Service, the Montana Method by Tennant, and two methods by Orsborn (Maximum Spawning Area Flow and Maximum Spawning Area) represent resource intensive and simplistic data collection and analysis methods. Each analysis was used to independently determine flows to support spawning by chinook salmon (Oncorhynchus tshawytscha) in Willow Creek, Alaska. Results of these analyses indicate that each method can be used independently or collectively to generate instream flow recommendations, if calibrated to the site or area studied. Once adjusted to the species and basin of interest, methods similar to the Montana and two Orsborn methods should be used to determine flow recommendations for areas where competition for water is minimal. The Instream Flow Incremental Methodology or similar methods should be applied when competition for water is keen or when detailed evaluations of the responses of species/life phases to flow variations are required.     

Examining Modeling Approaches for the Rainfall‐Runoff Process in Wildfire‐Affected Watersheds: Using San Dimas Experimental Forest

Wildfire can significantly change watershed hydrological processes resulting in increased risks for flooding, erosion, and debris flow. The goal of this study was to evaluate the predictive capability of hydrological models in estimating post‐fire runoff using data from the San Dimas Experimental Forest (SDEF), San Dimas, California. Four methods were chosen representing different types of post‐fire runoff prediction methods, including a Rule of Thumb, Modified Rational Method (MODRAT), HEC‐HMS Curve Number, and KINematic Runoff and EROSion Model 2 (KINEROS2). Results showed that simple, empirical peak flow models performed acceptably if calibrated correctly. However, these models do not reflect hydrological mechanisms and may not be applicable for predictions outside the area where they were calibrated. For pre‐fire conditions, the Curve Number approach implemented in HEC‐HMS provided more accurate results than KINEROS2, whereas for post‐fire conditions, the opposite was observed. Such a trend may imply fundamental changes from pre‐ to post‐fire hydrology. Analysis suggests that the runoff generation mechanism in the watershed may have temporarily changed due to fire effects from saturation‐excess runoff or subsurface storm dominated complex mechanisms to an infiltration‐excess dominated mechanism. Infiltration modeling using the Hydrus‐1D model supports this inference. Results of this study indicate that physically‐based approaches may better reflect this trend and have the potential to provide consistent and satisfactory prediction.     

Error Assessment for Height Above the Nearest Drainage Inundation Mapping

Real‐time flood inundation mapping is vital for emergency response to help protect life and property. Inundation mapping transforms rainfall forecasts into meaningful spatial information that can be utilized before, during, and after disasters. While inundation mapping has traditionally been conducted on a local scale, automated algorithms using topography data can be utilized to efficiently produce flood maps across the continental scale. The Height Above the Nearest Drainage method can be used in conjunction with synthetic rating curves (SRCs) to produce inundation maps, but the performance of these inundation maps needs to be assessed. Here we assess the accuracy of the SRCs and calculate statistics for comparing the SRCs to rating curves obtained from hydrodynamic models calibrated against observed stage heights. We find SRCs are accurate enough for large‐scale approximate inundation mapping while not as accurate when assessing individual reaches or cross sections. We investigate the effect of terrain and channel characteristics and observe reach length and slope predict divergence between the two types of rating curves, and SRCs perform poorly for short reaches with extreme slope values. We propose an approach to recalculate the slope in Manning’s equation as the weighted average over a minimum distance and assess accuracy for a range of moving window lengths.     

A PARAMETRIC MODEL CALIBRATED WITH A PHYSICALLY BASED MODEL FOR RUNOFF PREDICTION FROM UNGAGED STREAMS1

ABSTRACT: Recent developments in the numerical solution of the governing partial differential equations for overland and channel flow should make possible physically based models which predict runoff from ungaged streams. However, these models, which represent the watershed by sets of intersecting planes, are complex and require much computer time. Parametric models exist that have the advantage of being relatively simple, and once calibrated are inexpensive to use and require limited data input. In this study, a procedure was developed for calibrating a parametric model against a physically based model, utilizing base areas of one acre and one square mile, with the expectation that base areas can be combined to model real watersheds. Simulation experiments with the physically based model showed that, for the one-acre base area, the dominant parameter (cell storage ratio, K) related to the slope and friction of the planes, whereas for one square-mile areas, the dominant parameters (K plus a lag factor, L) relate to channel properties. These parameters decreased exponentially as rainfall intensity increased.     

MODEL DEVELOPMENT FOR CONJUNCTIVE USE STUDY OF THE SAN JACINTO BASIN,CALIFORNIA1

ABSTRACT: A two-layered confined-unconfined numerical model for flow and mass transport is developed for the San Jacinto Basin. The model structure is determined by the geological structure of the Basin and model parameters are calibrated using 20 years of historical records. The total number of historical head observations used for the flow model calibration is 1,117 and the total number of the estimated parameters is 91. The two-layered transport model is also calibrated using historical water quality records. Sensitivity analysis of the flow model shows that only 68 parameters (out of a total of 91) are relatively sensitive and reliable. However, the unreliable parameters (23 of them) are found to be insensitive and thus not significant to the prediction and management of conjunctive use of surface water and ground water. The developed flow model has been used to study the two proposed artificial recharge scenarios for the San Jacinto Basin. We have found that during a relatively dry condition, an artificial recharge rate of 80 acre-ft/day can be achieved during the recharge period October through January. However, for a relatively wet condition, only 80 percent of the proposed rate can be effectively stored in the Basin during these months.     

CALIBRATION OF A WATER-BALANCE MODEL FOR SMALL WATERSHEDS IN EASTERN OREGON1

ABSTRACT: The BURP water-balance model was calibrated for 13 small (0.46 to 7.00 mi²), forested watersheds in the Blue Mountains of eastern Oregon where snowmelt is the dominant source of runoff. BURP is the model name and is not an acronym. Six of the 16 parameters in BURP were calibrated. The subsurface recession coefficient and three subsurface water-storage parameters were most sensitive for simulating monthly flow. Calibrated subsurface recession coefficients ranged from 0.988 to 0.998. The subsurface-water storage parameters were calibrated at between 20 to 120 percent of their initial values obtained from a category III soil survey. That reconnaissance-level survey was apparently too broad to accurately reflect subsurface-water storage in small watersheds. Tests of model performance showed BURP is capable of producing accurate simulations of monthly flow for mountainous, snow-dominated watersheds with shallow (< 4 ft) soils when calibrated with 2 to 4 years of streamflow data. A regression of observed versus simulated monthly flows with data from all watersheds combined showed that BURP accounted for 85 percent of the variability in observed flows, which ranged from 0.01 to 20.8 inches, but underpredicted high flow months, with a slope of 1.15 that is significantly different from 1.0 (p = 0.05). Without prior calibration, subsurface-water storage parameters appeared to be the greatest source of potential error.     

IMPROVEMENT OF LEACHATE PREDICTION THROUGH MUNICIPAL SOLID WASTE LAYERS1

ABSTRACT: Existing leachate prediction models over- or underestimate leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distributions. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the one-domain water balance model HELP, and two-domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the HELP model yields reasonable predictions of cumulative leachate flow and PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to 0.2 and 2.2 cm/s respectively. In the long term, a new modeling approach must be developed to adequately describe the moisture movement mechanisms.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

VELOCITY EQUATION FOR WATER QUALITY MODELING IN GEORGIA1

ABSTRACT: Tabletop water quality modeling still plays an important role in the water pollution control activities of the Georgia Environmental Protection Division. Tabletop models are those developed with out the aid of extensive field data. One important component of GEORGIA DOSAG, our basic water quality model, is the equation used to predict flow through velocity. However, Georgia is characterized by wide physiographic diversity which reduces the effectiveness of uncalibrated velocity equations. Using 15 years of accumulated time-of-travel studies, a series of empirical velocity equations were developed and calibrated to various physiographic conditions in Georgia. Equations are available for each major soil province and for three stream flow ranges within each province - Q<100 cfs, 100<Q<1000 cfs, and Q>1000 cfs. Now, in the absence of extensive field data, we have data based velocity equations which can be tailored to each site under study.     

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

Water quality modeling of fertilizer management impacts on nitrate losses in tile drains at the field scale

Nitrate losses from subsurface tile drained row cropland in the Upper Midwest U.S. contribute to hypoxia in the Gulf of Mexico. Strategies are needed to reduce nitrate losses to the Mississippi River. This paper evaluates the effect of fertilizer rate and timing on nitrate losses in two (East and West) commercial row crop fields located in south-central Minnesota. The Agricultural Drainage and Pesticide Transport (ADAPT) model was calibrated and validated for monthly subsurface tile drain flow and nitrate losses for a period of 1999-2003. Good agreement was found between observed and predicted tile drain flow and nitrate losses during the calibration period, with Nash-Sutcliffe modeling efficiencies of 0.75 and 0.56, respectively. Better agreements were observed for the validation period. The calibrated model was then used to evaluate the effects of rate and timing of fertilizer application on nitrate losses with a 50-yr climatic record (1954-2003). Significant reductions in nitrate losses were predicted by reducing fertilizer application rates and changing timing. A 13% reduction in nitrate losses was predicted when fall fertilizer application rate was reduced from 180 to 123 kg/ha. A further 9% reduction in nitrate losses can be achieved when switching from fall to spring application. Larger reductions in nitrate losses would require changes in fertilizer rate and timing, as well as other practices such as changing tile drain spacings and/or depths, fall cover cropping, or conversion of crop land to pasture.     

Industrial metabolism of PVC in China: A dynamic material flow analysis

In China, the rapid development of the polyvinylchloride (PVC) industry will inevitably lead to various environmental problems. This paper studies the PVC metabolism further by (1) constructing dynamic models based on material flow analysis (MFA), (2) introducing calculation on detailed lifetime distribution of different types of products and recycling, and (3) obtaining the performances of waste emissions and accumulation as a function of raw material input and time. Based on system evolution theory and population development models, the developing trend of the PVC industry is studied, and annual consumptions in future years are predicted. The annual emission and accumulation after metabolism can be calculated by tracking the amount of raw material input, existing form and process flow for a single year (2003), as well as over a longer period (from 1958 to 2048) in China. Analysis indicates that over 0.6 billion tons of PVC waste will have accumulated in the environment by the end of 2050. In this scenario analysis, the effects of product structure, lifetime distribution, mechanical recycling, chemical recycling and incineration on waste output are all taken into consideration. The product metabolism process can be decelerated by changing these factors appropriately. However, mechanical recycling and chemical recycling are the most effective solutions.     

CALCULATION OF NONLINEAR CONFIDENCE AND PREDICTION INTERVALS FOR GROUND-WATER FLOW MODELS1

ABSTRACT: A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. Application of the method to a hypothetical example showed that includsion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals.     

EVAPOTRANSPIRATION AND CANOPY RESISTANCE AT AN UNDEVELOPED PRAIRIE IN A HUMID SUBTROPICAL CLIMATE1

ABSTRACT: Reliable estimates of evapotranspiration from areas of wildland vegetation are needed for many types of water-resource investigations. However, little is known about surface fluxes from many areally important vegetation types, and relatively few comparisons have been made to examine how well evapotranspiration models can predict evapotranspiration for soil-, climate-, or vegetation-types that differ from those under which the models have been calibrated. In this investigation at a prairie site in west-central Florida, latent heat flux (λE) computed from the energy balance and alternatively by eddy covariance during a 15-month period differed by 4 percent and 7 percent on hourly and daily time scales, respectively. Annual evapotranspiration computed from the energy balance and by eddy covariance were 978 and 944 mm, respectively. An hourly Penman-Monteith (PM) evapotranspiration model with stomatal control predicated on water-vapor-pressure deficit at canopy level, incoming solar radiation intensity, and soil water deficit was developed and calibrated using surface fluxes from eddy covariance. Model-predicted λE agreed closely with λE computed from the energy balance except when moisture from dew or precipitation covered vegetation surfaces. Finally, an hourly PM model developed for an Amazonian pasture predicted λE for the Florida prairie with unexpected reliability. Additional comparisons of PM-type models that have been developed for differing types of short vegetation could aid in assessing interchangeability of such models.     

Simple models for phosphorus loss from manure during rainfall

Mechanistic, predictive equations for phosphorus (P) transport in runoff from manure-applied fields constitute a critical knowledge gap for developing nonpoint-source pollution models. We derived two simple equations to describe the P release from animal manure during a rainfall event-one based on first-order P desorption kinetics and one based on second-order kinetics. The manure characteristics needed in the two kinetic equations are the maximum amount of water-extractable phosphorus (WEP) and a characteristic desorption time. Water-extractable P can be measured directly but currently the characteristic time can only be obtained by fitting experimental data. In addition, we evaluated two models usually used to estimate P loss from soil, the Elovitch equation and power function, both of which relate P loss to time. The models were tested against previously published data of P release from different manures under laboratory conditions. All equations fit the data well. Of the two kinetic equations, the second-order model showed better agreement with the data than the first-order model; for example, maximum relative differences between the model results and measured data were 2.6 and 4.7%, respectively. The characteristic times varied between 20 min for dairy manure and almost 100 min for poultry manure. The characteristic time did not appear to change with flow rate but decreased with smaller manure aggregates. The parameters for power-function relationships could not be related to measured manure characteristics. These results provide the first step to process-based approximations for predicting P release from manure with time during rainfall shortly after land application, when P losses are the greatest.     

Sensitivity of Thermal Habitat of a Trout Stream to Potential Climate Change,Wisconsin, United States1

Abstract: Airborne thermal remote sensing from four flights on a single day from a single‐engine airplane was used to collect thermal infrared data of a 10.47‐km reach of the upper East Branch Pecatonica River in southwest Wisconsin. The study uses a one‐dimensional stream temperature model calibrated with the longitudinal profiles of stream temperature created from the four thermal imaging flights and validated with three days of continuous stream temperature data from instream data loggers on the days surrounding the thermal remote‐sensing campaign. Model simulations were used to quantify the sensitivity of stream thermal habitat to increases in air and groundwater temperature and changes in base flow. The simulations indicate that stream temperatures may reach critical maximum thresholds for brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta) mortality, particularly if both air temperature increases and base flow declines. The approach demonstrates that thermal infrared data can greatly assist stream temperature model validation due to its high spatial resolution, and that this spatially continuous stream temperature data can be used to pinpoint spatial heterogeneity in groundwater inflow to streams. With this spatially distributed data on thermal heterogeneity and base‐flow accretion, stream temperature models considering various climate change scenarios are able to identify thermal refugia that will be critical for fisheries management under a changing climate.     

MODELING THE FOREST HYDROLOGY OF WETLAND-UPLAND ECOSYSTEMS IN FLORIDA1

ABSTRACT: Few hydrological models are applicable to pine flat-woods which are a mosaic of pine plantations and cypress swamps. Unique features of this system include ephemeral sheet flow, shallow dynamic ground water table, high rainfall and evapotranspiration, and high infiltration rates. A FLATWOODS model has been developed specifically for the cypress wetland-pine upland landscape by integrating a 2-D ground water model, a Variable-Source-Area (VAS)-based surface flow model, an evapotranspiration (ET) model, and an unsaturated water flow model. The FLATWOODS model utilizes a distributed approach by dividing the entire simulation domain into regular cells. It has the capability to continuously simulate the daily values of ground water table depth, ET, and soil moisture content distributions in a watershed. The model has been calibrated and validated with a 15-year runoff and a four-year ground water table data set from two different pine flat woods research watersheds in northern Florida. This model may be used for predicting hydrologic impacts of different forest management practices in the coastal regions.     

Dynamic floodplain vegetation model development for the Kootenai River, USA

The Kootenai River floodplain in Idaho, USA, is nearly disconnected from its main channel due to levee construction and the operation of Libby Dam since 1972. The decreases in flood frequency and magnitude combined with the river modification have changed the physical processes and the dynamics of floodplain vegetation. This research describes the concept, methodologies and simulated results of the rule-based dynamic floodplain vegetation model "CASiMiR-vegetation" that is used to simulate the effect of hydrological alteration on vegetation dynamics. The vegetation dynamics are simulated based on existing theory but adapted to observed field data on the Kootenai River. The model simulates the changing vegetation patterns on an annual basis from an initial condition based on spatially distributed physical parameters such as shear stress, flood duration and height-over-base flow level. The model was calibrated and the robustness of the model was analyzed. The hydrodynamic (HD) models were used to simulate relevant physical processes representing historic, pre-dam, and post-dam conditions from different representative hydrographs. The general concept of the vegetation model is that a vegetation community will be recycled if the magnitude of a relevant physical parameter is greater than the threshold value for specific vegetation; otherwise, succession will take place toward maturation stage. The overall accuracy and agreement Kappa between simulated and field observed maps were low considering individual vegetation types in both calibration and validation areas. Overall accuracy (42% and 58%) and agreement between maps (0.18 and 0.27) increased notably when individual vegetation types were merged into vegetation phases in both calibration and validation areas, respectively. The area balance approach was used to analyze the proportion of area occupied by different vegetation phases in the simulated and observed map. The result showed the impact of the river modification and hydrological alteration on the floodplain vegetation. The spatially distributed vegetation model developed in this study is a step forward in modeling riparian vegetation succession and can be used for operational loss assessment, and river and floodplain restoration projects.     

Does salt marsh fertilization enhance shellfish production? An application of flow analysis

The method of flow analysis, which is similar to economic input-output analysis, is presented as a means of making flow models of ecological systems more useful to environmental managers. This paper considers as an illustration the extent to which nitrogen fertilizer added toSpartina salt marsh sediments can enhance shellfish growth. Nitrogen flow models of both the Barataria Bay salt marsh complex of coastal Louisiana and the Sippewissett Marsh of western Cape Cod are analyzed. The analysis shows the transfer of added nitrogen to shellfish growth viaSpartina growth, decomposition, and detrital feeding to be considerably less efficient than its transfer toSpartina growth itself. These results are similar for both marsh systems, despite their great physical differences and despite the inclusion of considerably more microbial processing of nitrogen in the Barataria Bay model than in the Sippewissett models. The results suggest that the most efficient mechanism by which added nitrogen could enhance shellfish growth in salt marshes may have to bypass the route through theSpartina life cycle.