Retrospective Comparison of Watershed Analysis Risk Management Framework and Hydrologic Simulation Program Fortran Applications to Mica Creek Watershed

As part of an ongoing watershed model comparison program for forested watersheds, Watershed Analysis Risk Management Framework (WARMF V5.18) and Hydrologic Simulation Program Fortran (HSPF V10) were independently applied to the Mica Creek Watershed in Idaho. A comprehensive model comparison was made in terms of watershed delineation, hydrologic formulations, model parameterization, meteorological data, hydrologic calibration, and hydrologic verification. Comparison was not made for water quality, which was not simulated in the HSPF application. It was concluded that WARMF is a mechanistic model structured to simulate the hydrologic processes, whereas HSPF is an empirical water budget model. The WARMF is suitable for application to forested watersheds. It successfully predicted stream flows comparable to measured values. The HSPF results were also good, if one ignores an unrealistic amount of water loss to inactive groundwater and an empirical treatment of rain-on-snow events.     

Hydrologic and Water Quality Integration Tool: HydroWAMIT

A spatially distributed and continuous hydrologic model focusing on total maximum daily load (TMDL) projects was developed. Hydrologic models frequently used for TMDLs such as the hydrologic simulation program—FORTRAN (HSPF), soil and water assessment tool (SWAT), and generalized watershed loading function (GWLF) differ considerably in terms of spatial resolution, simulated processes, and linkage flexibility to external water quality models. The requirement of using an external water quality model for simulating specific processes is not uncommon. In addition, the scale of the watershed and water quality modeling, and the need for a robust and cost-effective modeling framework justify the development of alternative watershed modeling tools for TMDLs. The hydrologic and water quality integration tool (HydroWAMIT) is a spatially distributed and continuous time model that incorporates some of the features of GWLF and HSPF to provide a robust modeling structure for TMDL projects. HydroWAMIT operates within the WAMIT structure, developed by Omni Environmental LLC for the Passaic River TMDL in N. J. HydroWAMIT is divided into some basic components: the hydrologic component, responsible for the simulation of surface flow and baseflow from subwatersheds; the nonpoint-source (NPS) component, responsible for the calculation of the subwatershed NPS loads; and the linkage component, responsible for linking the flows and loads from HydroWAMIT to the water quality analysis simulation program (WASP). HydroWAMIT operates with the diffusion analogy flow model for flow routing. HydroWAMIT provides surface runoff, baseflow and associated loads as outputs for a daily timestep, and is relatively easy to calibrate compared to hydrologic models like HSPF. HydroWAMIT assumes that the soil profile is divided into saturated and unsaturated layers. The water available in the unsaturated layer directly affects the surface runoff from pervious areas. Surface runoff from impervious areas is calculated separately according to precipitation and the impervious fractions of the watershed. Baseflow is given by a linear function of the available water in the saturated zone. The utility of HydroWAMIT is illustrated for the North Branch and South Branch Raritan River Watershed (NSBRW) in New Jersey. The model was calibrated, validated, and linked to the WASP. The NPS component was tested for total dissolved solids. Available weather data and point-source discharges were used to prepare the meteorological and flow inputs for the model. Digital land use, soil type datasets, and digital elevation models were used for determining input data parameters and model segmentation. HydroWAMIT was successfully calibrated and validated for monthly and daily flows for the NSBRW outlet. The model statistics obtained using HydroWAMIT are comparable with statistics of HSPF and SWAT applications for medium and large drainage areas. The results show that HydroWAMIT is a feasible alternative to HSPF and SWAT, especially for large-scale TMDLs that require particular processes for water quality simulation and minor hydrologic model calibration effort.     

Modeling Nonpoint Source Pollutant Losses from a Small Watershed Using HSPF Model

Hydrologic models play an important role in the assessment of nonpoint source (NPS) pollution, which is essential for the environmental management of water resources. The present study has been undertaken to evaluate the applicability of a physically based continuous time scale, hydrological, and water quality computer model—Hydrologic Simulation Program-Fortran (HSPF)—in simulating runoff and sediment associated NPS pollutant losses from a small mixed type (land under agriculture, shrubs and forest, rocks, grasses) watershed of the Damodar Valley Corporation, Hazaribagh, India. Water soluble NO3–N, NH4–N, and P were considered as pollutants and their concentrations in the runoff were measured at the outlet of the watershed, randomly for 15 dates during the monsoon season (June–October) of 2000 and 2001. The model calibration and validation results reveal that the seasonal trend of HSPF simulated runoff, sediment yield, and NPS pollutants compared reasonably with their measured counterparts. Although the concentrations of pollutants were generally overpredicted for NO3–N and underpredicted for NH4–N and water-soluble P in the month of June when fertilizers releasing NH4–N and P are applied in rice fields, the differences in the mean concentration were not significantly different at a 95% level of confidence. Variation in the simulated losses of water soluble N and P species between the years occurred largely due to differences in the amount and distribution of rainfall. These results indicate that the HSPF model can be used as a tool for simulating runoff and sediment associated NPS pollution losses from the study area.     

Event and Continuous Hydrologic Modeling with HEC-HMS

Event hydrologic modeling reveals how a basin responds to an individual rainfall event (e.g., quantity of surface runoff, peak, timing of the peak, detention). In contrast, continuous hydrologic modeling synthesizes hydrologic processes and phenomena (i.e., synthetic responses of the basin to a number of rain events and their cumulative effects) over a longer time period that includes both wet and dry conditions. Thus, fine-scale event hydrologic modeling is particularly useful for understanding detailed hydrologic processes and identifying the relevant parameters that can be further used for coarse-scale continuous modeling, especially when long-term intensive monitoring data are not available or the data are incomplete. Joint event and continuous hydrologic modeling with the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) is discussed in this technical note and an application to the Mona Lake watershed in west Michigan is presented. Specifically, four rainfall events were selected for calibrating/verifying the event model and identifying model parameters. The calibrated parameters were then used in the continuous hydrologic model. The Soil Conservation Service curve number and soil moisture accounting methods in HEC-HMS were used for simulating surface runoff in the event and continuous models, respectively, and the relationship between the two rainfall-runoff models was analyzed. The simulations provided hydrologic details about quantity, variability, and sources of runoff in the watershed. The model output suggests that the fine-scale (5?min time step) event hydrologic modeling, supported by intensive field data, is useful for improving the coarse-scale (hourly time step) continuous modeling by providing more accurate and well-calibrated parameters.     

Modeling Evapotranspiration of Two Land Covers Using Integrated Hydrologic Model

Modeling evapotranspiration (ET) distribution in shallow water table environments is of great importance for understanding and reproducing other hydrologic fluxes such as runoff and recharge. Unfortunately, ET distribution can be the most difficult hydrologic process to analyze. The partitioning of ET into upper zone ET, lower zone ET, and groundwater ET is complex because it depends on land cover and subsurface characteristics. One comprehensive distributed parameter model, integrated hydrologic model (IHM), builds on an improved understanding and characterization of ET partitioning between surface storages, vadose zone storage, and saturated groundwater storage. It provides a smooth transition to satisfy ET demand between the vadose zone and the deeper saturated groundwater. In this paper, the IHM was used to analyze ET contribution from different regions of the vadose zone and saturated zone. Rigorous testing was done on two distinct land covers, grass land and forest land, at a study site in West-Central Florida. Sensitivity analysis on the key parameters was investigated and influence of parameters on ET behavior was also discussed. Statistics with the root mean square error and mean bias error for forest total ET were about 1.46 and 0.04 mm/day, respectively, and 1.61 and 1.07 mm/day for grass total ET. Modeling results further proved that ET distributions from the upper and lower soil and water table, while incorporating field-scale variability of soil and land cover properties, can be predicted reasonably well using IHM model.     

Case Study: Model to Simulate Regional Flow in South Florida

South Florida has a complex regional hydrologic system that consists of thousands of miles of networked canals, sloughs, highly pervious aquifers, open areas subjected to overland flow and sheet flow, agricultural areas and rapidly growing urban areas. This region faces equally complex problems related to water supply, flood control, and water quality management. Advanced computational methods and super fast computers alone have limited success in solving modern day problems such as these because the challenge is to model the complexity of the hydrologic system, while maintaining computational efficiency and acceptable levels of numerical errors. A new, physically based hydrologic model for South Florida called the regional simulation model (RSM) is presented here. The RSM is based on object oriented design methods, advanced computational techniques, extensible markup language, and geographic information system. The RSM uses a finite volume method to simulate two-dimensional (2D) surface and groundwater flow. It is capable of working with unstructured triangular and rectangular mesh discretizations. The discretized control volumes for 2D flow, canal flow and lake flow are treated as abstract “water bodies” that are connected by abstract “water movers.” The numerical procedure is designed to work with these and many other abstractions. An object oriented code design is used to provide robust and highly extensible software architecture. A weighted implicit numerical method is used to keep the model fully integrated and stable. A limited error analysis was carried out and the results were compared with analytical error estimates. The paper describes an application of the model to the L-8 basin in South Florida and the strength of this approach in developing models over complex areas.     

Hydrodynamic Modeling Approaches for Agricultural Storm Water Impoundments

Hydrologic modeling of storm water impoundments is an effective tool in evaluating different water management options for addressing regional water issues in Florida. However, modeling impoundment water dynamics could be challenging because of the difference in scale between canals and the entire impoundment. Water pumped into the impoundments is first discharged into canals inside the impoundments, which distributes the water. The canal eventually overflows and water floods all the impoundment. Two modeling approaches to simulate this process were tested on two impoundments using the integrated MIKE-SHE and MIKE 11 model. The first approach simulates the one-dimensional flow in the canal in a link-node model; and once water floods, it is modeled as two-dimensional flow. The second approach simulates the entire impoundment as a canal. In both impoundments, Modeling Approach 1 resulted in overestimation of peaks and poor results. Modeling Approach 2 showed considerable improvements in the results and a satisfactory match between observed and simulated water levels. The difference is attributed to the difficulty in representing the canal flooding process in hydrodynamic models.     

Watershed-Scale Impacts of Nitrogen from On-Site Wastewater Systems: Parameter Sensitivity and Model Calibration

A numerical watershed model was used to evaluate the potential influence of various point and nonpoint sources including on-site wastewater systems (OWS) on stream nitrate concentration in Turkey Creek Watershed, Colorado. A watershed analysis risk management framework model was used for this study, and was calibrated to observed stream nitrate concentrations using an automatic calibration tool. Parameter sensitivity analysis was done to select critical parameters for calibration and to reduce uncertainty in the simulated results. Sensitivity analysis of nitrate transport and transformation parameters showed that stream nitrate concentration is highly sensitive to cation exchange capacity, nitrification rate, base saturation of ammonium, initial concentration of ammonium in the soil, and some of the crop growth related parameters. The calibrated model was used to evaluate scenarios related to OWS including the impacts of population growth and new development and impacts of conversion of OWS to conventional sewers. The results showed that there would be a significant increase in stream nitrate concentration with increasing population. Conversion of OWS to sewers increased stream nitrate concentration but decreased nitrate concentration in the bottom soil layer indicating that OWS are beneficial with respect to stream nitrate concentration but may increase nitrate concentrations in groundwater.     

Case Study: Application of the HEC-6 Model for the Main Stem of the Kankakee River in Illinois

This case study paper presents results on the application of the HEC-6 model to the main stem of the Kankakee River in Illinois, a distance of about 39.3?km. Modeling was performed to develop comprehensive plans for enhancing the aquatic habitats and also to forecast future sedimentation problems if specific management practices are implemented. The paper concentrates on the modeling aspects of this research. The extent of the model was from the Stateline Bridge to Kankakee Dam in Kankakee. The HEC-6 model, originally developed by the Hydrologic Engineering Center (HEC) of the U.S. Army Corps of Engineers, was adapted for this application. The model was run, calibrated, and verified for both the hydraulic and sediment components. The hydraulic component was calibrated through comparison of measured yearly hydrographs with computed values for three gauging stations on the river. The hydrologic component was verified for the same three gauging stations for two yearly hydrographs for 2 additional water years. The sediment component was calibrated with river cross-sectional data collected by the Illinois State Water Survey in 1980 and 1999. The calibrated and verified hydraulic and calibrated sediment components then were used to predict future changes in water surface elevations and thalweg elevations for a 20-year period beginning in 1999, the last date for which river cross-sectional data are available.     

HSPF Simulation of Runoff and Sediment Loads in the Upper Changjiang River Basin, China

To evaluate the performance of a computer model simulating runoff and sediment load in the upper region of the Changjiang (Yangtze River) basin over a relatively short time interval, including examining the applicability of the input precipitation data generated from global circulation models and satellite data, we used a spatially distributed model, HSPF with the International Satellite Land Surface Climatology Project (ISLSCP) precipitation data for 1987 and 1988 as input data. The Nash–Sutcliffe coefficient (R2) for 5-day average streamflow was 0.94 in the calibration period and 0.95 in the verification period for the whole upper region. Moreover, the model simulated the 5-day average streamflow well in each main tributary, as shown by R2 values of 0.46–0.96, except that it underestimated the peak flow rates during the flood season over 2 years by up to 71% in Tuojiang and 61% in Jialingjiang. The model simulated the 5-day concentrations of suspended solids (SS) fairly well in the headwaters and upper regions of the Jinshajiang, Yalongjiang, and Minjiang watersheds, as shown by R2 values of 0.31–0.65. In the other regions, however, the model underestimated the SS load by up to 72%, and rarely simulated the fluctuation of SS concentration in each river channel during the flood season. These errors led to the underestimation of sediment runoff volume from the whole upper region during the flood season, as shown by the ratio of the simulated sediment load to the observed data at Yichang: 0.69 in the calibration period and 0.68 in the verification period. The ISLSCP precipitation tended to be more frequent and less intense than the measured precipitation. This was probably the main reason why the HSPF did not perform well in all regions at all times.     

Calibration and Verification of a 2D Hydrodynamic Model for Simulating Flow around Emergent Bendway Weir Structures

The predictive capability of a two-dimensional (2D)-hydrodynamic model, the finite-element surface water modeling system (FESWMS), to describe adequately the flow characteristics around emergent bendway weir structures was evaluated. To examine FESWMS predictive capability, a sensitivity analysis was performed to identify the flow conditions and locations within the modeled reach, where FESWMS inputs for Manning’s n and eddy viscosity must be spatially distributed for to better represent the river bed flow roughness characteristics and regions where the flow is highly turbulent in nature. The sensitivity analysis showed that high flow conditions masked the impact of Manning’s n and eddy viscosity on the model outputs. Therefore, the model was calibrated under low flow conditions when the structures were emergent and had the largest impact on the flow pattern and model inputs. Detailed field measurements were performed under low flow conditions at the Raccoon River, Iowa for model calibration and verification. The model predictions were examined for both spatially averaged and distributed Manning’s n and eddy viscosity model input values within the study reach for an array of emergent structures. Spatially averaged model inputs for Manning’s n and eddy viscosity provided satisfactory flow depth predictions but poor velocity predictions. Estimated errors in the predicted values were less than 10% for flow depth and about 60% for flow velocity. Distributed Manning’s n and eddy viscosity model inputs, on the contrary, provided both satisfactory flow depth and velocity predictions. Further, distributed inputs were able to mimic closely the recirculation flow pattern in the wake region behind the bendway weir structures. Estimated errors in the predicted values were less than 10 and 25% for flow depth and velocity, respectively. Overall, in the case of distributed model inputs, FESWMS provided satisfactory results and allowed a closed depiction of the flow patterns around the emergent bendway weirs. These findings suggest that 2D models with spatially distributed values for Manning’s n and eddy viscosity can adequately replicate the velocity vector field around emergent structures and can be valuable tools to river managers, except in cases when detailed three-dimensional flow patterns are needed. The study was limited to the examined low flow conditions, and more field data, especially under high flow conditions, are necessary to generalize the findings of this study regarding the model prediction capabilities.     

Automatic Calibration of the U.S. EPA SWMM Model for a Large Urban Catchment

The Storm Water Management Model was adapted and calibrated to the Ballona Creek Watershed, a large urban catchment in Southern California. A geographic information system (GIS) was used to process the input data and generate the spatial distribution of precipitation. An optimization procedure using the complex method was incorporated to estimate runoff parameters, and ten storms were used for calibration and validation. The calibrated model predicted the observed outputs with reasonable accuracy. A sensitivity analysis showed the impact of the model parameters, and results were most sensitive to imperviousness and impervious depression storage and least sensitive to Manning roughness for surface flow. Optimized imperviousness was greater than imperviousness predicted from land-use information. The results demonstrate that this methodology of integrating GIS and stormwater model with a constrained optimization technique can be applied to large watersheds.     

River Hydrograph Retransmission Functions of Irrigated Valley Surface Water–Groundwater Interactions

Storage and release functions of western U.S. traditional river valley irrigation systems may counteract early and rapid spring river runoff associated with climate variation. Along the Rio Grande in northern New Mexico, we instrumented a 20-km-long irrigated valley to measure water balance components from 2005 to 2007. Hydrologic processes of the system were incorporated into a system dynamics model to test scenarios of changed water use. Of river water diverted into an earthen irrigation canal system, some was consumed by crop evapotranspiration (7.4%), the rest returned to the river as surface return flow (59.3%) and shallow groundwater return flow that originated as seepage from canals (12.1%) and fields (21.2%). The modeled simulations showed that the coupled surface water irrigation system and shallow aquifer act together to store water underground and then release it to the river, effectively retransmitting river flow until later in the year. Water use conversion to nonirrigation purposes and reduced seepage from canals and fields will likely result in higher spring runoff and lower fall and winter river flow.     

Modeling Escherichia Coli and Its Sources in an Urban Bayou with Hydrologic Simulation Program—FORTRAN

Bacterial levels in Buffalo Bayou in Houston commonly exceed contact recreation standards. Potential sources of bacteria include wastewater treatment plants, sanitary sewer overflows, septic systems, wet and dry nonpoint-source discharges via direct runoff and pipes, direct deposition, and sediment. A water-quality model in the Hydrologic Simulation Program—FORTRAN (HSPF) was calibrated and validated for hydrology, sediment, and Escherichia coli and subsequently used to evaluate the impacts of the bacterial sources in the watershed. In addition, simple estimates of bacterial loads were calculated along with source evaluations from load duration curves. Load reductions based upon the simple estimates indicated that water-quality standards were met by reducing dry-weather indicator bacterial loads by 69% and wet-weather loads by 98%. When these load reductions were implemented in the HSPF model, however, standards were not met under dry-weather conditions. Residual nonpoint-source loading was found to cause the discrepancy between simple load estimate calculations and the developed water-quality model. This paper demonstrates that runoff can play a significant role in maintaining high levels of bacteria under all flow conditions and that understanding the temporal variations in bacterial source loading is critical to ensure that load reductions will achieve water-quality standards.     

Integrated Reservoir-Based Canal Irrigation Model. I: Description

The success of irrigation system operation and planning depends on the quantification of supply and demand and equitable distribution of supply to meet the demand if possible, or to minimize the gap between the supply and demand. Most of the irrigation literature mainly focuses on the demand and distribution aspects only. In addition, irrigation projects that receive water from a reservoir can be challenging to manage as annual fluctuations in runoff from the reservoir’s catchment can have considerable impact on the irrigation management strategy. This study focuses on the development of an integrated reservoir-based canal irrigation model (IRCIM) that includes catchment hydrologic modeling, reservoir water balance, command hydrologic modeling, and a rotational canal irrigation management system. The front end of the IRCIM is developed in Visual Basic 6.0, whereas the back-end coding is done in C language. The graphical user interface is the most important feature of the model, as it provides a better interaction between the model and its user. The IRCIM has a modular structure that consists of three modules, viz., catchment module, reservoir module, and crop water demand module. The catchment module predicts daily runoff from the catchment that inflows to the reservoir. Depending on the data availability, this module is provided with the flexibility of choosing between the Soil Conservation Service’s curve number method combined with the Muskingum routing technique, and an artificial neural network technique using the Levenberg–Marquardt algorithm. The reservoir module is based on conservation of mass approach, and results in daily reservoir storage. The crop water demand module is comprised of water-balance models for both paddy and field crops. The irrigation management system serves as the program flow controller for the model and runs the required module when needed. For postseason evaluation of the irrigation system, performance indicators such as adequacy, efficiency, equity, and dependability are used. In a companion paper, the model is applied for Kangsabati Irrigation Project, West Bengal, India.     

Process Modeling of Storm-Water Flow in a Bioretention Cell

A two-dimensional variable saturated flow model was developed to simulate subsurface flow in bioretention facilities employing the Richards’ equation. Variable hydrologic performances of bioretention are evaluated using the underdrain outflow hydrographs, outflow volumes for 10 storms with various duration and depth, and flow duration curves for 25 different storms. The effects of some important design parameters and elements are tested, including media type, surrounding soils, initial water content, ratio of drainage area to bioretention surface area, and ratio of cell length to width. Model results indicate that the outflow volume via underdrain is less than the inflow; the flow peak is significantly reduced and delayed. Underdrain outflow volume from loamy sand media (with larger Ks) is larger than that from sandy clay loam media. The saturated hydraulic conductivity, storage capacity, and exfiltration into surrounding soils contribute to the hydrologic performance of a bioretention cell. Initial media storage capacity is affected by the hydraulic properties of media soils, initial water content, and bioretention surface area. The exfiltration volume is determined by the surrounding soil type and exfiltration area, dominated by flow through the bottom of the media.     

SIMGRO, a GIS-Supported Regional Hydrologic Model in Irrigated Areas: Case Study in Mendoza, Argentina

The SIMGRO hydrologic simulation model was extended to include irrigation practice. It could then be used to evaluate the effect of hydrologic changes in an irrigated area in the province of Mendoza, Argentina where, given an average annual rainfall of approximately 200?mm, irrigation is crucial for agriculture. A storage dam was recently constructed in the Mendoza River to control the fluctuating river flow and to guarantee that the demand for water is met throughout the year. The dam will impact on parts of the irrigation system where groundwater levels are already high and salinization occurs. To evaluate these changes and possible mitigation measures, two performance indicators that consider groundwater and surface water were used: Relative evapotranspiration and the depleted fraction. Scenario runs revealed that the irrigation water losses from the canals affect the groundwater levels in the downstream part of the irrigated area; an increase in salinity was also revealed.     

Root Zone Moisture Routing and Water Demand Calculations in the Context of Integrated Hydrology

An important issue that integrated hydrologic models (IHMs) for river basins can address is the management of water resources in heavily inhabited and cultivated basins. To address this issue, these models need to simulate water demands and root zone flows in a basin. Irrigation scheduling models (ISMs) have been widely used by professionals to compute farm level water demands and root zone flows. Available ISMs are neither suitable for use at basin scale nor can they be easily linked to IHMs. This paper describes a new model that utilizes methods used by ISMs to compute root zone flows and water demands in river basins and can be linked to IHMs. The model was applied to a basin in California, and the simulated water demands were compared with data compiled for the basin. The differences in the results were attributed to differences in input potential evapotranspiration rates. The paper demonstrates that simulated water demands for rice are very sensitive to saturated soil hydraulic conductivity, whereas demands for other crops are sensitive to the pore size distribution index.     

Methodology for Estimating Specific Yield in Shallow Water Environment Using Continuous Soil Moisture Data

A methodology for estimating specific yield in shallow water environments using continuous soil moisture data is introduced. An accurate estimate of specific yield is critical for management of water resources affecting well yields, water levels, and rates of water level decline. The study area is located in an intensive small-scale hydrologic monitoring field site in Hillsborough County, Florida. Data from four soil moisture monitoring stations were studied. The objectives of this paper are to describe a methodology to obtain precise estimates of the specific yield that can be obtained by a fitting procedure and to determine functional relationships between measured soil parameters and soil moisture storage variability. Estimated specific yield values varied from zero, when the water table was near land surface, to a maximum that was close to drainable porosity consistent with a humid shallow water environment, where sensitive ecosystems and wetlands are dependent on a seasonal hydroperiod of water table fluctuations. The results will be incorporated into regional integrated surface and ground water models that are being applied successfully in West-Central Florida.     

Multiobjective Water Quality Model Calibration Using a Hybrid Genetic Algorithm and Neural Network–Based Approach

This study aims at coupling a hybrid genetic algorithm (HGA) and a neural network (NN) model for the multiobjective calibration of surface water quality models. The HGA is formed as a robust optimization algorithm through combining a real-coded genetic algorithm with a local search method, i.e., the Nelder-Mead simplex method (NMS). The NN model is developed to approximate the input-output response relationship underlying a numerical water quality model, and is then incorporated into the HGA framework, which results in the HGA-NN approach. This approach has the advantage of evaluating the objective function of the calibration model in a more efficient way. The HGA-NN approach is tested in the calibration of a CE-QUAL-W2 model which is set up to simulate the hydrodynamic process and water quality conditions in Lake Maumelle in central Arkansas. It is found that the HGA-NN approach can improve the computational efficiency. However, it does not guarantee the finding of the parameter values with a low objective function value. An adaptive HGA-NN approach is then proposed to improve its performance. In this adaptive approach, both the water quality model and the NN model are incorporated into the HGA framework. They are executed adaptively to evaluate the objective function. The application results demonstrate that the adaptive approach can be applied to the calibration of water quality models.