Model‐Based Nitrogen and Phosphorus (Nutrient) Criteria for Large Temperate Rivers: 2. Criteria Derivation

Nitrogen and phosphorus criteria were developed for 233 km of the Yellowstone River, one of the first cases where a mechanistic model has been used to derive large river numeric nutrient criteria. A water quality model and a companion model which simulates lateral algal biomass across transects were used to simulate effects of increasing nutrients on five variables (dissolved oxygen, total organic carbon, total dissolved gas, pH, and benthic algal biomass in depths ≤1 m). Incremental increases in nutrients were evaluated relative to their impact on predefined thresholds for each variable; the first variable to exceed a threshold set the nutrient criteria. Simulations were made at a low flow, the 14Q5 (lowest average 14 consecutive day flow, July‐September, recurring one in five years), which was derived using benthic algae growth curves and EPA guidance on excursion frequency. An extant climate dataset with an annual recurrence was used, and tributary water quality and flows were coincident with the river's 10 lowest flow years. The river had different sensitivities to nutrients longitudinally, pH being the most sensitive variable in the upstream reach and algal biomass in the lower. Model‐based criteria for the Yellowstone River are as follows: between the Bighorn and Powder river confluences, 55 μg TP/l and 655 μg TN/l; from the Powder River confluence to Montana state line, 95 μg TP/l and 815 μg TN/l. Pros and cons of using steady‐state models to derive river nutrient criteria are discussed.     

Regional Scale Stressor‐Response Models in Aquatic Ecosystems1

Abstract: A systematic method for identification and estimation of regional scale stressor‐response models in aquatic ecosystems will be useful in monitoring and assessment of aquatic resources, determination of regional nutrient criteria and for increased understanding of the differences between regions. The model response variable is chlorophyll a, a measure of algal density, while the stressors include nutrient concentrations from the USEPA Nutrient Criteria Database (NCD) for lakes/ponds and reservoirs of the continental United States. The NCD has observations for both stressors and biological responses determined using methods that are not consistently available at the continental scale. To link multiple environmental stressors to biological responses and quantify uncertainty in model predictions, we take a multilevel modeling approach to the estimation of a linear model for prediction of log Chlorophyll a using predictors log TP and log TN. The multilevel modeling approach allows us to adjust the impact of covariates at all levels (observation, higher level groups) for the simultaneous operation of contextual and individual variability in the outcome. Here, we wish to allow separate regression coefficients for inference regarding similarities and differences between each of 14 ecoregions, and between the two water‐body types, lakes/ponds and reservoirs. We are also interested in the nuisance effects of the categorical variables indicating the type of nitrogen measurements (three levels) and the type of chlorophyll a measurements (four levels) used. Model‐based determination of nutrient criteria points to an apparent incompatibility of criteria developed for nutrient stressors and eutrophication responses using current Environmental Protection Agency’s guidance.     

Linear Superposition in Total Maximum Daily Loads Applications: The Steady‐State Response Matrix Revisited1

Abstract: The steady‐state response matrix has historically proved a valuable tool in computing the water quality response to loadings and in providing insight into the relative impact of individual loading sources. The insight obtained may be is particularly useful in modern applications of increasingly complex water quality models to problems involving multiple point and nonpoint sources, such as in the assessment of total maximum daily loads (TMDLs). Where appropriate and the underlying equations linear, the steady‐state response matrix can be used to synthesize the results of more complicated models and present them in a way easily understood by policy makers. A straightforward method is presented for generating the response matrix using complex models, and example applications discussed. Example applications include a simple demonstration; incorporation of the method into the Mississippi Department of Environmental Quality’s STREAM model used in TMDL development; a TMDL modeling study of the Grand Calumet River and Indiana Harbor Canal, Indiana, using CE‐QUAL‐ICM; and a TMDL modeling study of the Big Sunflower River, Mississippi, using the Water Analysis Simulation Program model.     

An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation

Water quality modeling has been shown to be a useful tool in strategic water quality management. The present study combines the Qual2K model with the HEC-RAS model to assess the water quality of a tidal river in northern Taiwan. The contaminant loadings of biochemical oxygen demand (BOD), ammonia nitrogen (NH₃-N), total phosphorus (TP), and sediment oxygen demand (SOD) are utilized in the Qual2K simulation. The HEC-RAS model is used to: (i) estimate the hydraulic constants for atmospheric re-aeration constant calculation; and (ii) calculate the water level profile variation to account for concentration changes as a result of tidal effect. The results show that HEC-RAS-assisted Qual2K simulations taking tidal effect into consideration produce water quality indices that, in general, agree with the monitoring data of the river. Comparisons of simulations with different combinations of contaminant loadings demonstrate that BOD is the most import contaminant. Streeter-Phelps simulation (in combination with HEC-RAS) is also performed for comparison, and the results show excellent agreement with the observed data. This paper is the first report of the innovative use of a combination of the HEC-RAS model and the Qual2K model (or Streeter-Phelps equation) to simulate water quality in a tidal river. The combination is shown to provide an alternative for water quality simulation of a tidal river when available dynamic-monitoring data are insufficient to assess the tidal effect of the river.     

Continental‐Scale River Flow Modeling of the Mississippi River Basin Using High‐Resolution NHDPlus Dataset

As a key component of the National Flood Interoperability Experiment (NFIE), this article presents the continental scale river flow modeling of the Mississippi River Basin (MRB), using high‐resolution river data from NHDPlus. The Routing Application for Parallel computatIon of Discharge (RAPID) was applied to the MRB with more than 1.2 million river reaches for a 10‐year study (2005‐2014). Runoff data from the Variable Infiltration Capacity (VIC) model was used as input to RAPID. This article investigates the effect of topography on RAPID performance, the differences between the VIC‐RAPID streamflow simulations in the HUC‐2 regions of the MRB, and the impact of major dams on the streamflow simulations. The model performance improved when initial parameter values, especially the Muskingum K parameter, were estimated by taking topography into account. The statistical summary indicates the RAPID model performs better in the Ohio and Tennessee Regions and the Upper and Lower Mississippi River Regions in comparison to the western part of the MRB, due to the better performance of the VIC model. The model accuracy also increases when lakes and reservoirs are considered in the modeling framework. In general, results show the VIC‐RAPID streamflow simulation is satisfactory at the continental scale of the MRB.     

NUTRIENT CONCENTRATION CRITERIA AND CHARACTERIZATION OF PATTERNS IN TROPHIC STATE FOR RIVERS IN HETEROGENEOUS LANDSCAPES1

ABSTRACT: A method is demonstrated for the development of nutrient concentration criteria and large scale assessment of trophic state in environmentally heterogeneous landscapes. The method uses the River Environment Classification (REC) as a spatial framework to partition rivers according to differences in processes that control the accrual and loss of algae biomass. The method is then applied to gravel bed rivers with natural flow regimes that drain hilly watersheds in New Zealand's South Island. An existing model is used to characterize trophic state (in terms of chlorophyll a as a measure of maximum biomass) using nutrient concentration, which controls the rate of biomass accrual, and flood frequency, which controls biomass loss. Variation in flood frequency was partitioned into three classes, and flow data measured at 68 sites was used to show that the classes differ with respect to flood frequency. Variation in nutrient concentration was partitioned at smaller spatial scales by subdivision of higher level classes into seven classes. The median of flood frequency in each of the three higher level classes was used as a control variable in the model to provide spatially explicit nutrient concentration criteria by setting maximum chlorophyll a to reflect a desired trophic state. The median of mean monthly soluble reactive phosphorus and soluble inorganic nitrogen measured at 68 water quality monitoring sites were then used to characterize the trophic state of each of the seven lower level classes. The method models biomass and therefore allows variation in this response variable to provide options for trophic state and the associated nutrient concentrations to achieve these. Thus it is less deterministic than using reference site water quality. The choice from among these options is a sociopolitical decision, which reflects the management objectives rather than purely technical considerations.     

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

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

Pairing Modern and Paleolimnological Approaches to Evaluate the Nutrient Status of Lakes in Upper Midwest National Parks

Understanding what constitutes a reference (background) nutrient condition for lakes is important for National Park Service managers responsible for preserving and protecting aquatic resources. For this study we characterize water quality conditions in 29 lakes across four national parks, and compare their nutrient status to U.S. Environmental Protection Agency (USEPA) nutrient reference criteria and alternative criteria recently proposed by others. Where appropriate we also compare the nutrient status of these 29 lakes to state or tribal nutrient reference criteria or standards. For lakes that exceed reference criteria we investigate physical and chemical patterns, and for a subset of lakes compare modern nutrient conditions to paleolimnological (i.e., diatom‐inferred [DI]) nutrient reconstructions. Many lakes exceeded USEPA nutrient reference criteria, but met alternative less restrictive criteria. Modern nutrient conditions were also largely consistent with DI historic (pre‐1900) nutrient conditions. Lakes exceeding alternative nutrient criteria and with elevated nutrient levels relative to DI historic conditions were mostly small, shallow, and dystrophic; continued attention to their nutrient dynamics and biological response is warranted. Coupling modern and paleolimnological data offer an innovative and scientifically defensible approach to understand long‐term nutrient trends and provide greater context for comparison with reference conditions.     

Investigating the Fate and Transport of Escherichia coli in the Charles River,Boston, Using High‐Resolution Observation and Modeling1

Abstract: The processes affecting the fate and transport of Escherichia coli in surface waters were investigated using high‐resolution observation and modeling. The concentration patterns in Boston’s Charles River were observed during four sampling events with a total of 757 samples, including two spatial surveys with two along‐river (1,500 m length) and three across‐river (600 m length) transects at approximately 25‐m intervals, and two temporal surveys at a fixed location (Community Boating) over seven days at hourly intervals. The data reveal significant spatial and temporal structure at scales not resolved by typical monitoring programs. A mechanistic, time‐variable, three‐dimensional coupled hydrodynamic and water quality model was developed using the ECOMSED and RCA modeling frameworks. The computational grid consists of 3,066 grid cells with average length dimension of 25 m. Forcing functions include upstream and downstream boundary conditions, Stony Brook, and Muddy River (major tributaries) combined sewer overflow (CSO) and non‐CSO discharge and wind. The model generally reproduces the observed spatial and temporal patterns. This includes the presence and absence of a plume in the study area under similar loading, but different hydrodynamic conditions caused by operation of the New Charles River Dam (downstream) and wind. The model also correctly predicts an episode of high concentrations at the time‐series station following seven days of no rainfall. The model has an overall root mean square error (RMSE) of 250 CFU/100 ml and an error rate (above or below the USEPA‐recommended single sample criteria value of 235 CFU/100 ml) of 9.4%. At the time series station, the model has an RMSE of 370 CFU/100 ml and an error rate of 15%.     

Water Quality and Land Use Changes in the Alafia and Hillsborough River Watersheds,Florida, USA1

Abstract: Spatial distribution of land use can have a substantial effect on surface and groundwater quality. Our objective was to test for trends in flow components and water quality related to changes in land use in the Alafia and Hillsborough River watersheds in Florida, USA, over the period 1974‐2007. In addition, water quality statistics were evaluated in the perspective of numeric water quality criteria and proposed reclassification of segments of the Alafia River. Trends in 10 water quality parameters and three discharge variables were evaluated using a nonparametric trend detection test. Results of land use analysis indicated substantial urbanization and loss of agricultural land in the study area. Discharge variables did not exhibit significant trends, whereas trends in the majority of water quality concentrations were negative or nonsignificant with total nitrogen and total Kjeldahl nitrogen as exceptions showing positive trends. Changes in nutrient pathways could not be clearly identified. Considering recently promulgated numeric nutrient criteria and standards for dissolved fluoride, much of the Alafia River was found to be out of compliance. While there were land use changes and changes in water quality over the study period, it was difficult to identify a direct cause‐effect relationship. Responses to regulatory efforts, such as the Clean Water Act and improvements in phosphate mining practices, may have had greater impacts on water quality than changes in land use.     

RIVERWARE: A GENERALIZED TOOL FOR COMPLEX RESERVOIR SYSTEM MODELING1

ABSTRACT: Water management agencies seek the next generation of modeling tools for planning and operating river basins. Previous site‐specific models such as U.S. Bureau of Reclamation's (USBR) Colorado River Simulation System and Tennessee Valley Authority's (TVA) Daily Scheduling Model have become obsolete; however, new models are difficult and expensive to develop and maintain. Previous generalized river basin modeling tools are limited in their ability to represent diverse physical system and operating policy details for a wide range of applications. RiverWare(tm), a new generalized river basin modeling tool, provides a construction kit for developing and running detailed, site‐specific models without the need to develop or maintain the supporting software within the water management agency. It includes an extensible library of modeling algorithms, several solvers, and a rich “language” for the expression of operating policy. Its point‐and‐click graphical interface facilitates model construction and execution, and communication of policies, assumptions and results to others. Applications developed and used by the TVA and the USBR demonstrate that a wide range of operational and planning problems on widely varying basins can be solved using this tool.     

Development and Application of the 2010 Chesapeake Bay Watershed Total Maximum Daily Load Model

The Phase 5.3 Watershed Model simulates the Chesapeake watershed land use, river flows, and the associated transport and fate of nutrient and sediment loads to the Chesapeake Bay. The Phase 5.3 Model is the most recent of a series of increasingly refined versions of a model that have been operational for more than two decades. The Phase 5.3 Model, in conjunction with models of the Chesapeake airshed and estuary, provides estimates of management actions needed to protect water quality, achieve Chesapeake water quality standards, and restore living resources. The Phase 5.3 Watershed Model tracks nutrient and sediment load estimates of the entire 166,000 km² watershed, including loads from all six watershed states. The creation of software systems, input datasets, and calibration methods were important aspects of the model development process. A community model approach was taken with model development and application, and the model was developed by a broad coalition of model practitioners including environmental engineers, scientists, and environmental managers. Among the users of the Phase 5.3 Model are the Chesapeake watershed states and local governments, consultants, river basin commissions, and universities. Development and application of the model are described, as well as key scenarios ranging from high nutrient and sediment load conditions if no management actions were taken in the watershed, to low load estimates of an all‐forested condition.     

Evaluating Links Between Forest Harvest and Stream Temperature Threshold Exceedances: The Value of Spatial and Temporal Data

We present the results of a replicated before‐after‐control‐impact study on 33 streams to test the effectiveness of riparian rules for private and State forests at meeting temperature criteria in streams in western Oregon. Many states have established regulatory temperature thresholds, referred to as numeric criteria, to protect cold‐water fishes such as salmon and trout. We examined across‐year and within‐year patterns of exceedance at control and treatment stream temperature probes. Determining whether an exceedance at the downstream end of a harvest was unambiguously related to harvest proved surprisingly difficult. The likelihood of a site exceeding its numeric criterion appeared related, in part, to the site's preharvest temperature range. Four control reaches as well as three preharvest treatment reaches exceeded their numeric criteria, necessitating additional analysis to evaluate timber harvest impacts. Nine percent of sites (3 of 33) both exceeded their numeric criteria and exhibited a potential harvest effect (16.7% of private sites [3 of 18], 0% of State sites [0 of 15]). After harvest, exceedances were typically observed in only the first of the two post‐harvest years. These findings highlight the importance of including temporal and spatial controls in temperature assessments of numeric criteria when the assessment's purpose is to determine whether exceedances are related to human activities.     

Transition Pathways to Sustainable Agricultural Water Management: A Review of Integrated Modeling Approaches

Agricultural water management (AWM) is an interdisciplinary concern, cutting across traditional domains such as agronomy, climatology, geology, economics, and sociology. Each of these disciplines has developed numerous process‐based and empirical models for AWM. However, models that simulate all major hydrologic, water quality, and crop growth processes in agricultural systems are still lacking. As computers become more powerful, more researchers are choosing to integrate existing models to account for these major processes rather than building new cross‐disciplinary models. Model integration carries the hope that, as in a real system, the sum of the model will be greater than the parts. However, models based upon simplified and unrealistic assumptions of physical or empirical processes can generate misleading results which are not useful for informing policy. In this article, we use literature and case studies from the High Plains Aquifer and Southeastern United States regions to elucidate the challenges and opportunities associated with integrated modeling for AWM and recommend conditions in which to use integrated models. Additionally, we examine the potential contributions of integrated modeling to AWM — the actual practice of conserving water while maximizing productivity. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

河流水质模型在双流县流域治理中的应用

研究利用现有的河流水质模型,构建了一个可实时模拟河流水环境质量变化状况的动态模型。模型采用一维稳态单组分水质模型对河流的CODCr、NH3-N的降解进行计算,采用多宾斯-坎普稳态模型对河流的BOD、DO变化情况进行计算。模型引入水文数据、水质监测数据、环境统计数据、社会统计公报数据,以Excel作为数据平台,可以反演出河流不同月份、不同区段的污染物降解系数。研究将该模型应用于双流县的流域治理,以在锦江双流段的应用为例进行了具体说明。根据2008年双流县河流的相关数据,研究使用该模型反演出了锦江双流段的污染物降解系数,并对其反映的流域污染状况进行了分析。随后,研究使用该模型已计算出的岷江中段河流的降解系数,模拟计算了4种情景下锦江双流段出境断面的可能水质变化,以验证拟定的双流县流域治理方案的预期效果。模型具有实用性和进一步扩展的功能。     

Biogeochemical cycling constraints on stream ecosystem recovery

In systems where production is limited by the availability of a nutrient, nutrient input to and recycling within the system is related to the resilience, or speed of recovery, of a system to its steady state following a disturbance. In particular, it is shown that the return timeT _s of the system to steady state, or the inverse of the resilience, is approximately equal to the mean turnover time of the limiting nutrient in the system. From this relationship, it is possible to understand and predict how various properties of food webs and their environments affect resilience. These properties include nutrient input rate, loss rate, size of the detritus compartment, and trophic structure. The effects of these properties on resilience are described by using simple mathematical models. To test model predictions, experimental studies of the response of periphyton-dominated stream ecosystems to disturbance are being conducted on a set of laboratory streams in which nutrient inputs and grazing intensity are regulated at different levels. In streams without snail grazers (low-grazed streams), 90% recirculation of stream water to reduce nutrient inputs resulted in longer turnover times (T _r ) of phosphorus within the stream compared with once-through flow. However, in streams with snail grazers (high-grazed streams), there were no differences in phosphorus turnover time between once-through and partially recirculated treatments. Results on the rate of recovery of periphyton from a flood/scour disturbance to each stream partially support the model prediction of a positive relationship between ecosystem return time (T _s ) and nutrient turnover time (T _r ) within the streams.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: Stream‐loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long‐term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water‐quality model, the flow‐bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water‐quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.     

Hydrologic Connectivity and the Contribution of Stream Headwaters to Ecological Integrity at Regional Scales1

Abstract: Cumulatively, headwater streams contribute to maintaining hydrologic connectivity and ecosystem integrity at regional scales. Hydrologic connectivity is the water‐mediated transport of matter, energy and organisms within or between elements of the hydrologic cycle. Headwater streams compose over two‐thirds of total stream length in a typical river drainage and directly connect the upland and riparian landscape to the rest of the stream ecosystem. Altering headwater streams, e.g., by channelization, diversion through pipes, impoundment and burial, modifies fluxes between uplands and downstream river segments and eliminates distinctive habitats. The large‐scale ecological effects of altering headwaters are amplified by land uses that alter runoff and nutrient loads to streams, and by widespread dam construction on larger rivers (which frequently leaves free‐flowing upstream portions of river systems essential to sustaining aquatic biodiversity). We discuss three examples of large‐scale consequences of cumulative headwater alteration. Downstream eutrophication and coastal hypoxia result, in part, from agricultural practices that alter headwaters and wetlands while increasing nutrient runoff. Extensive headwater alteration is also expected to lower secondary productivity of river systems by reducing stream‐system length and trophic subsidies to downstream river segments, affecting aquatic communities and terrestrial wildlife that utilize aquatic resources. Reduced viability of freshwater biota may occur with cumulative headwater alteration, including for species that occupy a range of stream sizes but for which headwater streams diversify the network of interconnected populations or enhance survival for particular life stages. Developing a more predictive understanding of ecological patterns that may emerge on regional scales as a result of headwater alterations will require studies focused on components and pathways that connect headwaters to river, coastal and terrestrial ecosystems. Linkages between headwaters and downstream ecosystems cannot be discounted when addressing large‐scale issues such as hypoxia in the Gulf of Mexico and global losses of biodiversity.     

Spatial Calibration and Temporal Validation of Flow for Regional Scale Hydrologic Modeling1

Abstract: Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validation is performed at the river basin outlet without accounting for spatial variations in hydrological parameters within the subunits. In this study, we calibrated the model to capture the spatial variations in runoff at subwatershed level to assure local water balance, and validated the streamflow at key gaging stations along the river to assure temporal variability. Ohio and Arkansas‐White‐Red River Basins of the United States were modeled using Soil and Water Assessment Tool (SWAT) for the period from 1961 to 1990. R² values of average annual runoff at subwatersheds were 0.78 and 0.99 for the Ohio and Arkansas Basins. Observed and simulated annual and monthly streamflow from 1961 to 1990 is used for temporal validation at the gages. R² values estimated were greater than 0.6. In summary, spatially distributed calibration at subwatersheds and temporal validation at the stream gages accounted for the spatial and temporal hydrological patterns reasonably well in the two river basins. This study highlights the importance of spatially distributed calibration and validation in large river basins.     

Integrated Modular Modeling of Water and Nutrients From Point and Nonpoint Sources in the Patuxent River Watershed1

Abstract: We present a simple modular landscape simulation model that is based on a watershed modeling framework in which different sets of processes occurring in a watershed can be simulated separately with different models. The model consists of three loosely coupled submodels: a rainfall‐runoff model (TOPMODEL) for runoff generation in a subwatershed, a nutrient model for estimation of nutrients from nonpoint sources in a subwatershed, and a stream network model for integration of point and nonpoint sources in the routing process. The model performance was evaluated using monitoring data in the watershed of the Patuxent River, a tributary to the Chesapeake Bay in Maryland, from July 1997 through August 1999. Despite its simplicity, the landscape model predictions of streamflow, and sediment and nutrient loads were as good as or better than those of the Hydrological Simulation Program‐Fortran model, one of the most widely used comprehensive watershed models. The landscape model was applied to predict discharges of water, sediment, silicate, organic carbon, nitrate, ammonium, organic nitrogen, total nitrogen, organic phosphorus, phosphate, and total phosphorus from the Patuxent watershed to its estuary. The predicted annual water discharge to the estuary was very close to the measured annual total in terms of percent errors for both years of the study period (≤2%). The model predictions for loads of nutrients were also good (20‐30%) or very good (<20%) with exceptions of sediment (40%), phosphate (36%), and organic carbon (53%) for Year 1.