Hydrological Simulation Program-Fortran Research Articles

Effect of Flow Depth and Velocity on Nitrate Loss Rates in Natural Channels1

Carleton, James N. and Yusuf M. Mohamoud, 2012. Effect of Flow Depth and Velocity on Nitrate Loss Rates in Natural Channels. Journal of the American Water Resources Association (JAWRA) 1‐12. DOI: 10.1111/jawr.12007Abstract: Loss rates of nitrate from streams and rivers are governed by movement of the ion from water column to anoxic bed sediments. Quantitative representations of nitrate in streams and rivers have often treated such losses as governed by first‐order mechanisms that are invariant with respect to potential modulating factors other than temperature. Results of studies in recent years, however, suggest that rates of water column‐sediment mass transfer are influenced by stream geometry and associated hydraulics. We develop expressions for the instream nitrate loss rate coefficient, k, as a function of water velocity and depth, using hydraulic geometry to empirically relate velocity to depth for two cases: (1) variability in mean conditions among reaches; and (2) temporal variability in conditions at a single reach, under changing flow. The result is expressions for k as functions of water column depth. Measured stream k values reported in the literature are shown to be well represented by expressions developed for the first case, and the potential for application to probabilistic analysis is briefly examined. We explore the latter case using the Hydrologic Simulation Program – FORTRAN (HSPF) model, modified to incorporate the dependence of k on instantaneous stream depth. In example simulations of two nitrate‐exporting watersheds, the incorporation of depth‐dependence of k produces improvement in the model’s ability to match observed stream nitrate concentrations.

Modeling the sediment yield from landslides in the Shihmen Reservoir watershed, Taiwan

ABSTRACTLandslides generate enormous volumes of sediment in mountainous watersheds; however, quantifying the downstream transport of landslide‐derived sediment remains a challenge. Landslide erosion and sediment delivery to the Shihmen Reservoir watershed in Taiwan was estimated using empirical landslide frequency–area and volume–area relationships, empirical landslide runout models, and the Hydrological Simulation Program‐ FORTRAN (HSPF). Landslide erosion rates ranged from 0.4 mm yr‐1 to 2.2 mm yr‐1 during the period 1986–2003, but increased to 7.9 mm yr‐1 following Typhoon Aere in 2004. The percentage of landslide sediment delivered to streams decreased from 78% during the period 1986–1997 to 55% in 2004. Although the delivery ratio was lower, the volume of landslide sediment delivered to streams was 2.81 × 106 Mg yr‐1 in 1986–1997 and 8.60 × 106 Mg yr‐1 in 2004. Model simulations indicate that only a small proportion of the landslide material was delivered downstream. An average of 13% of the landslide material delivered to rivers was moved downstream during the period 1986–1997. In 2004, the period including Typhoon Aere, the annual fluvial sediment yield accounted for approximately 23% of the landslide material delivered to streams. In general, the transfer of sediment in the fluvial system in the Shihmen Reservoir watershed is dominantly transport limited. The imbalance between sediment supply and transport capacity has resulted in a considerable quantity of landslide material remaining in the upper‐stream regions of the watershed. Copyright © 2012 John Wiley & Sons, Ltd.

Assessing fecal coliform fate and transport in a coastal watershed using HSPF

There is increasing concern regarding spread and proliferation of pathogenic microorganisms in watersheds and their impacts on water quality. In agricultural and rural watersheds fecal coliform occurrence, an indicator of pathogenic contamination, is often thought to be a result of land applications of animal waste. This study used the Hydrologic Simulation Program Fortran (HSPF) along with the Bacterial Indicator Tool to model fecal coliform transport in a coastal watershed with a view to identifying contaminant sources and key contributing areas. Results indicated that the highest levels of fecal coliform contamination (often exceeding the 400 counts/100 ml standard for the area) emanated from areas with and without livestock operations, and from largely forested areas, indicating that livestock operations were not the determining source of fecal coliform as suggested in previous studies. This study found HSPF to be an effective tool for identifying key coliform contributing areas in coastal watersheds.

볏짚 피복에 의한 밭 비점원오염 저감효과 분석을 위한 HSPF 모델링

This study is to assess the reduction of non-point source pollution loads for rice straw surface covering of upland crop cultivation at a watershed scale. For Byulmi-cheon watershed (<TEX>$1.21km^2$</TEX>) located in the upstream of Gyeongancheon, the HSPF (Hydrological Simulation Program-Fortran), a physically based distributed hydrological model was applied. Before evaluation, the model was calibrated and validated using 9 rainfall events. The Nash-Sutcliffe model efficiency (NSE) for streamflow was 0.62~0.78 and the NSE for water quality (Sediment, T-N, and T-P) were 0.68, 0.60, and 0.58 respectively. From the field experiment of 16 rainfall events, the rice straw covering reduced surface runoff average 10 % compared to normal surface condition. By handling infiltration parameter (INFILT) in the model, the value of 16.0 mm/hr was found to reduce about 10 % reduction of surface runoff. For this condition, the reduction effect of Sediment, T-N, and T-P loads were 87.2, 28.5, and 85.1 % respectively. The rice straw surface covering was effective for removing surface runoff dependent loads such as Sediment and T-P.

Temporal scale effect of loading data on instream nitrate-nitrogen load computation

The temporal scale effect of loading data on nitrate-nitrogen load computation was examined using outputs of watershed modeling tool Hydrologic Simulation Program-FORTRAN (HSPF) for the Amite River in Louisiana, USA. The daily nitrate-nitrogen concentrations simulated using the HSPF were employed first to obtain daily, weekly, bi-weekly, and monthly average data and then to develop load duration curves for the data with four different temporal scales. The duration curves exhibited high variability in the load estimated using daily data as compared with those based on bi-weekly and monthly data. According to daily data, the nitrate-nitrogen load in the winter was found to be 2,780 kg. The nitrate-nitrogen load decreased with increasing temporal (daily, weekly, bi-weekly, and monthly) scale (commonly used in water quality monitoring) of the data. The coefficient of variation, used to quantify the effect of temporal scale on the load, was found to be linearly and inversely correlated with the logarithm of the time scale. Based on the finding, empirical equations were proposed to extrapolate near real-time data for flow and nitrate-nitrogen, greatly simplifying nutrient monitoring and reducing the cost involved in water quality monitoring.

Sensitivity of Simulating Hydrologic Processes to Gauge and Radar Rainfall Data in Subtropical Coastal Catchments

This research evaluated the impact of three rainfall datasets on hydrologic process simulations in two coastal catchments located in Alabama. In this study, rain gauge time series recorded by the U.S. National Oceanic and Atmospheric Administration (NOAA) and Geological Survey (USGS) along with radar precipitation data derived from NOAA National Weather Service (NWS) were input into the Hydrological Simulation Program—FORTRAN (HSPF). Automatic parameter calibration was performed using daily streamflow data recorded at USGS Fish and Magnolia River gauge stations from 07/01/2002 to 12/31/2008. HSPF parameters were optimized using the Model-Independent Parameter Estimation (PEST) program. Model parameter ranges were refined by incorporating physical characteristic of the study areas and after analyzing observed streamflow time series. This approach, in turn, helped PEST optimization tool to find the most physically-related set of parameters that can be transferred to any watershed with similar characteristics and minimum parameter calibration. On average, annual USGS and radar rainfall values were around 480 mm and 250 mm, respectively lower than NOAA precipitation records. Overall, it is found that the NOAA precipitation input data resulted in better daily flow simulations than results from radar and USGS rainfall time series. Streamflows derived from USGS rainfall time series showed the worst model performance at both catchment outlets because of missing data, low amounts, and temporal delay of peaks. This study found that annual actual evapotranspiration values were closed among rainfall time series and varied from 900 to 958 mm. Deep percolation values for Magnolia and Fish River, regardless of rainfall source, ranged from 66 to 192 mm/year. Major discrepancies were found at storm runoff values. Gauge rainfall time series yielded the closest streamflow values compared to observed flow time series at both watershed outlets. Rainfall derived from radar yielded consistent and acceptable runoff results in Fish and Magnolia River models. In both case studies, the high spatial variability of rainfall storm events was not adequately captured by any of the rainfall datasets and yielded high uncertainty in model results.

Hydrological modeling of the Mun River basin in Thailand

► Most of the physicochemical and all of the coliform parameters consisted higher values in wet season. ► Heavy metals moreover appeared at wet season. ► Although the presences of pesticides are very nominal, the higher values were detected at wet season. Sources of pollution in river basins are increasing due to rapid changes in land uses and excessive nutrient application to crops which lead to degraded instream water quality. In this connection, the Mun River basin, one of the important and largest river basins in Thailand, has been studied. Comparative figures of nutrients in the Mun’s water over a decade showed an increased total nitrogen (TN) and phosphorus (TP) ratio in the Lower Mun region (TN:TP > 14). Laboratory analysis of weekly water samples showed a realistic nutrient response when daily rainfall was compared to the seasonal water quality data collected by the Pollution Control Department (PCD). The Hydrologic Simulation Program – FORTRAN (HSPF) was calibrated and used to assess the effects of different land uses on river water quality. Model parameters related to hydrology and sediment were calibrated and validated using relevant measurements by the Royal Irrigation Department (RID). With a reasonable and acceptable model performance ( r 2 = 0.62), the highest simulated runoff was observed in urban areas. The trend of agricultural land (as a percentage of total area) – total nitrogen showed a linear relationship of a good correlation (i.e. r 2 = 0.85). Based on the findings, it can be concluded that this model is expected to provide vital information for developing suitable land management policies and strategies to improve river water quality.

Temporal scale-induced uncertainty in load duration curves for instream-dissolved oxygen

Load duration curves were developed using the Hydrological Simulation Program FORTRAN (HSPF) for dissolved oxygen (DO) for the Amite River in Louisiana, USA. The concept of 'dissolved oxygen reserve', defined as the total quantity of DO, is introduced. The effect of temporal resolution on duration curves of DO reserve was examined using duration curves developed based on daily, weekly, biweekly, and monthly average data. Duration curves for DO exhibited high variability in the load estimated using daily data as compared to those based on biweekly and monthly data. A seasonal analysis revealed the trend in the DO reserve. The daily DO reserve for the Amite River at Port Vincent was 44,049.31 kg when daily summer data were used and 74,255.15 kg for daily annual data. A surplus of 10,691 kg of DO reserve was shown in the monthly data during critical summer months. The coefficient of variation (CV), used to define the temporal scale-induced uncertainty, was found to be linearly and inversely correlated with the logarithm of the time scale. Regression equations were developed to extrapolate near real-time flow and water quality data, greatly simplifying flow and water quality monitoring and reducing the cost involved in flow and water quality monitoring.

A hydro‐economic modelling framework for flood damage estimation and the role of riparian vegetation

AbstractA modelling framework for the quick estimate of flood inundation and the resultant damages is developed in this paper. The model, called the flood economic impact analysis system (FEIAS), can be applied to a river reach of any hydrogeological river basin. For the development of the integrated modelling framework, three models were employed: (1) a modelling scheme based on the Hydrological Simulation Program FORTRAN model that was developed for any geomorphological river basin, (2) a river flow/floodplain model, and (3) a flood loss estimation model. The first sub‐model of the flood economic impact analysis system simulates the hydrological processes for extended periods of time, and its output is used as input to a second component, the river/floodplain model. The hydraulic model MIKE 11 (quasi‐2D) is the river/floodplain model employed in this study. The simulated flood parameters from the hydraulic model MIKE 11 (quasi‐2D) are passed, at the end of each time step, to a third component, the flood loss model for the estimation of flood damage. In the present work, emphasis was given to the seasonal variation of Manning's coefficient (n), which is an important parameter for the determination of the flood inundation in hydraulic modelling. High values of Manning's coefficient for a channel indicate high flow resistance. The riparian vegetation can have a large impact on channel resistance. The modelling framework developed in this paper was used to investigate the role of riparian vegetation in reducing flood damage. Moreover, it was used to investigate the influence of cutting riparian vegetation scenarios on the flow characteristics. The proposed framework was applied to the downstream part of the Koiliaris River basin in Crete, Greece, and was tested and validated with historical data. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Prioritization of water management under climate change and urbanization using multi-criteria decision making methods

Abstract. This paper quantifies the transformed effectiveness of alternatives for watershed management caused by climate change and urbanization and prioritizes five options using multi-criteria decision making techniques. The climate change scenarios (A1B and A2) were obtained by using a statistical downscaling model (SDSM), and the urbanization scenario by surveying the existing urban planning. The flow and biochemical oxygen demand (BOD) concentration duration curves were derived, and the numbers of days required to satisfy the environmental flow requirement and the target BOD concentration were counted using the Hydrological Simulation Program-Fortran (HSPF) model. In addition, five feasible alternatives were prioritized by using multi-criteria decision making techniques, based on the driving force-pressure-state-impact-response (DPSIR) framework and cost component. Finally, a sensitivity analysis approach for MCDM methods was conducted to reduce the uncertainty of weights. The result indicates that the most sensitive decision criterion is cost, followed by criteria response, driving force, impact, state and pressure in that order. As it is certain that the importance of cost component is over 0.127, construction of a small wastewater treatment plant will be the most preferred alternative in this application.

Optimization Model for BMP Placement in a Reservoir Watershed

The purpose of this study was to develop an optimization model for the optimal placement of structural best management practices (BMPs) at the watershed scale for a reservoir. In this research, the authors considered three types of structural BMPs (i.e., a wet detention pond, a grass swale, and an infiltration trench). The complete model consists of three interacting submodels: a watershed water quality simulation model [the Hydrologic Simulation Program-FORTRAN (HSPF) model], a reservoir water quality model (the CE-QUAL-W2 model); and an optimization model that uses a well-developed genetic algorithm (GA) software. This research used the Feitsui Reservoir and its watershed in northern Taiwan as the area of application. For the optimization model, the objective function was to minimize the total annual cost of BMPs, within the constraints of achieving minimum water quality standards for the concentrations of phosphorus, ammonium, nitrate-nitrite and for the total suspended solids in the reservoir. The study first simulated the discharge and pollutant loads for the watershed in 2002–2003 by using HSPF. The reservoir model CE-QUAL-W2 was then used to simulate variations in pollutant concentrations in the reservoir on the basis of the input discharge and pollutant loads from HSPF. The optimization model was finally used to search for the near-optimal selection and placement of BMPs in the watershed. The results obtained from the completed model effectively demonstrate its viability in improving water quality in the reservoir by adopting optimal BMPs placement strategies.

BASINS/HSPF: Model Use, Calibration, and Validation

This article presents recommendations by model developers and the authors about calibration and validation procedures for the Hydrological Simulation Program - Fortran (HSPF) as applied through BASINS. HSPF is a continuous simulation watershed model that simulates nonpoint-source runoff and pollutant loadings for a watershed and performs flow and water quality routing in stream reaches and well-mixed lakes and impoundments. HSPF can be used to estimate nonpoint-source loads from various land uses as well as fate and transport processes in streams and lakes. This article describes the ideal calibration and validation process for the full range of constituents modeled by HSPF, as well as the process for acceptable minimum calibration and validation of this model. The model information and guidance provided in this article may be used to help in determining the scope of the proposed ASABE Standard/Engineering Practice for model calibration and validation. Model calibration and validation are necessary and critical steps in any model application. For HSPF and most other watershed models, calibration is an iterative procedure of parameter evaluation and refinement, as a result of comparing simulated and observed values of interest. Model validation is in reality an extension of the calibration process. Its purpose is to ensure that the calibrated model properly assesses all the variables and conditions that can affect model results, and to demonstrate the ability to predict field observations for periods separate from the calibration effort. For HSPF calibration and validation, a “weight of evidence” approach is most widely used in practice when models are examined and judged for acceptance for assessment and regulatory purposes. This article explores the “weight of evidence” approach and the current practice of watershed model calibration and validation based on more than 30 years of experience with HSPF. Example applications are described and model results are shown to demonstrate the graphical and statistical procedures used to assess model performance. In addition, quantitative criteria for various statistical measures are discussed as a basis for evaluating model results and documenting the model application efforts.

Parameter uncertainty methods in evaluating a lumped hydrological model

Water resources modelers face the challenge of dealing with numerous uncertainties due to the lack of knowledge of the natural systems, numerical approaches used in modeling (equations, parameters, structures, solutions), and field data collected to set up and evaluate models. Propagation of parameter uncertainty into model results is a relevant topic in environmental hydrology. Uncertainty analyses improve assessment of hydrological modeling. There is a need in modern hydrology of developing and testing uncertainty analysis methods that support hydrological model evaluation. In this research the propagation of model parameter uncertainty into streamflow model results is evaluated. The Hydrological Simulation Program – FORTRAN (HSPF) supported by the US Environmental Protection Agency was evaluated using hydroenvironmental data from the Luxapallila Creek watershed located in Mississippi and Alabama, USA. The uncertainty bounds of model outputs were computed using the Monte Carlo simulation and Harr’s point estimation methods. Analysis of parameter uncertainty propagation on streamflow simulations from 12 HSPF parameters was accomplished using 5,000 Monte Carlo random samples and 24 Harr selected points for each selected parameter. The comparison showed that Harr’s method could be an appropriate initial indicator of parameter uncertainty propagation on streamflow simulations, particularly for hydrology models with several parameters.

Input data measurement-induced uncertainty in watershed modelling

This study presents a new methodology for estimation of input data measurement-induced uncertainty in simulated dissolved oxygen (DO) and nitrate-nitrogen (NO3-N) concentrations using the Hydrological Simulation Program–FORTRAN (HSPF) model and data from the Amite River, USA. Simulation results show that: (1) a multiplying factor of 1.3 can be used to describe the maximum error in temperature measurements; similarly, a multiplying factor of 1.9 was estimated to accommodate the maximum of ±5% error in rainfall measurements; (2) the uncertainty in simulated DO concentration due to positive temperature measurement errors can be described with a normal distribution, N(0.062, 0.567); (3) the uncertainty in simulated NO3-N concentration due to rainfall measurement errors follows a generalized extreme value distribution; and (4) the probability density functions can be utilized to determine the measurement-induced uncertainty in simulated DO and NO3-N concentrations according to the risk level acceptable in water quality management. Editor D. Koutsoyiannis Citation Patil, A. and Deng, Z.-Q., 2012. Input data measurement-induced uncertainty in watershed modelling. Hydrological Sciences Journal, 57 (1), 118–133.

Simulation and Validation of Non-point Source Nitrogen and Phosphorus Loads under Different Land Uses in Sihu Basin, Hubei Province, China

Abstract Many water quality models have been extensively used to evaluate non-point source pollution, such as SWMM (Storm Water Management Model), AnnAGNPS (Annualized Agricultural Non-point Source), HSPF (Hydrological Simulation Program– Fortran), SWAT (Soil and Water Assessment Tool) and so on. However, these models’ construction tended to be complex, only used well in the condition of many parameters and normative data can be obtained. There were much problem to use these models in tidal plain, where topography were flat, stream network were complex and controlled by many water conservancy systems. The L-THIA (Long-Term Hydrologic Impact Assessment) model can be used in the areas with uncompleted data, evaluate the effects of land use on non-point source pollution, because it only needs land use, soil types and some rainfall data. But the output results of L-THIA model are the annual average runoff volume and pollution load, which cannot be obtained easily in in-site observation. In this paper, one of typical tidal plain, Sihu basin in Hubei province of China, was studied. The annual average runoff volume and the non-point source nitrogen and phosphorus load of each grid (16m*16m) and the spatial distribution were estimated by L-THIA model. The average load of non-point source nitrogen and phosphorus at each exit of the units were calculated based on the suppose that the pollution load is inverse to the distance of water flow. Model validation was executed by comparing calculated results and observed water quality data for study area. The results demonstrated that there were highly significant linear correlation between the calculated average load of non-point source nitrogen and phosphorus and the measured concentrations of TP and TN (TN: R=0.828; TP: R=0.957). These suggested that the average load of non-point source nitrogen and phosphorus were reliable to evaluate non-point source pollution. Moreover, the simulation results illustrated that the non-point source nitrogen and phosphorus loads under different land uses were quite different. The impact of dry lands on the non-point source nitrogen and phosphorus was the highest; that of paddy fields and residential areas were secondary; and the impact of woodlands to non-point source nitrogen and phosphorus was the minimum.

Development of spatial water resources vulnerability index considering climate change impacts

This study developed a new framework to quantify spatial vulnerability for sustainable water resources management. Four hydrologic vulnerability indices – potential flood damage (PFDC), potential drought damage (PDDC), potential water quality deterioration (PWQDC), and watershed evaluation index (WEIC) – were modified to quantify flood damage, drought damage, water quality deterioration, and overall watershed risk considering the impact of climate change, respectively. The concept of sustainability in the Driver–Pressure–State–Impact–Response (DPSIR) framework was applied in selecting all appropriate indicators (criteria) of climate change impacts. In the examination of climate change, future meteorological data was obtained using CGCM3 (Canadian Global Coupled Model) and SDSM (Statistical Downscaling Model), and future stream run-off and water quality were simulated using HSPF (Hydrological Simulation Program — Fortran). The four modified indices were then calculated using TOPSIS, a multi-attribute method of decision analysis. As a result, the ranking obtained can be changed in consideration of climate change impacts. This study represents a new attempt to quantify hydrologic vulnerability in a manner that takes into account both climate change impacts and the concept of sustainability.

Estimation of dynamic load of mercury in a river with BASINS-HSPF model

Purpose Mercury (Hg) is a naturally occurring element and a pervasive toxic pollutant. This study investigated the dynamic loads of Hg from the Cedar–Ortega Rivers watershed into the Lower St. Johns River (LSJR), Florida, USA, using the better assessment science integrating point and nonpoint sources (BASINS)-hydrologic simulation program—FORTRAN (HSPF) model.

Mass Balance and Water Quality Modeling for Load Allocation of Escherichia coli in an Urban Watershed

A modeling approach based on mass balance coupled with the Hydrologic Simulation Program in FORTRAN (HSPF) is developed in this study to evaluate bacteria reduction strategies and their impact on water quality for an urban watershed in Texas. This approach allowed for spatial and temporal representation of bacteria loading from the adjacent watershed that was balanced with in-stream loading. This decreased the uncertainty in source loading estimates and reduced the number of variables requiring calibration. The resulting model is used to investigate whether reduction goals calculated by using the mass balance data alone would actually achieve water quality standards. Results indicate that 100% elimination of runoff loads would be required to achieve the applicable standards, which is a somewhat unrealistic and costly endeavor. The utility of the developed model is further demonstrated by investigating spatial reduction strategies targeting the various bacteria sources in the watershed. Results indicate th...

Predicting plausible impacts of sets of climate and land use change scenarios on water resources

Our world is changing at an unprecedented rate in terms of climate and land use, but these changes can affect our water resources. Hence, we need a methodology that can predict both their individual and agglomerative ramifications. Using the Little Miami River (LMR) watershed as a case study, this paper describes a spatial analytical approach integrating mathematical modeling and geographical information sciences to quantitatively examine the relative importance of the separate and combined hydrologic and water quality impacts of climate and land use changes. The Hydrologic Simulation Program – Fortran (HSPF) model was chosen in this study to simulate stream flow and nutrient transport process. Five hypothetical climate change scenarios were used to cover the possible ranges of variability in the year 2050. An enhanced population-coupled Markov-Cellular Automata (CA-Markov) land use model was developed to predict the 2050 land use pattern. When these scenarios were incorporated into the HSPF model, the future conditions in the LMR basin were postulated. The findings demonstrated that: 1) the LMR watershed would experience an increase in flow and nutrients under the 2050 land use projection, 2) stream flow and water quality impacts would be amplified when both climate and land use changes were simultaneously considered, 3) land use change (and in the case of the LMR watershed, urbanization) could help to alleviate water shortage during the dry years, 4) total phosphorus and nitrogen would increase under all future climate and land use scenarios; the highest increase was found under the combined wettest and future land use scenarios, and 5) the described approach is effective in simulating the hydrologic and water quality effects of climate and land use changes in a basin scale. These results are relevant to planners; they can be useful in formulating realistic watershed management policies and mitigation measures.

Integrating hydrologic modeling and land use projections for evaluation of hydrologic response and regional water supply impacts in semi-arid environments

Semi-arid environments are generally more sensitive to urbanization than humid regions in terms of both hydrologic modifications and water resources sustainability. The current study integrates hydrologic modeling and land use projections to predict long-term impacts of urbanization on hydrologic behavior and water supply in semi-arid regions. The study focuses on the Upper Santa Clara River basin in northern Los Angeles County, CA, USA, which is undergoing rapid and extensive development. The semi-distributed Hydrologic Simulation Program Fortran (HSPF) model is parameterized with land use, soil, and channel characteristics of the study watershed. Model parameters related to hydrologic processes are calibrated at the daily time step using various spatial configurations of precipitation and parameters. Potential urbanization scenarios are generated on the basis of a regional development plan. The calibrated (and validated) model is run under the proposed development scenarios for a 10 year period. Results reveal that increasing development increases total annual runoff and wet season flows, while decreases are observed in existing baseflow and groundwater recharge during both dry and wet seasons. As development increases, medium-sized storms increase in both peak flow and overall volume, while low and high flow events (extremes) appear less affected. Urbanization is also shown to decrease natural recharge and, when considered at the regional scale, may result in a loss of critical water supply to Southern California. The current study provides a coupled framework for a decision support tool that can guide efforts involved in regional urban development planning and water supply management.