Hydrological Simulation Program-Fortran Research Articles

Comprehensive Performance Evaluation for Hydrological and Nutrients Simulation Using the Hydrological Simulation Program-Fortran in a Mesoscale Monsoon Watershed, China.

The Hydrological Simulation Program–Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient (R2) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R2 was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses.

Spatiotemporal patterns and source attribution of nitrogen pollution in a typical headwater agricultural watershed in Southeastern China

Excessive nitrogen (N) discharge from agriculture causes widespread problems in aquatic ecosystems. Knowledge of spatiotemporal patterns and source attribution of N pollution is critical for nutrient management programs but is poorly studied in headwaters with various small water bodies and mini-point pollution sources. Taking a typical small watershed in the low mountains of Southeastern China as an example, N pollution and source attribution were studied for a multipond system around a village using the Hydrological Simulation Program-Fortran (HSPF) model. The results exhibited distinctive spatio-seasonal variations with an overall seriousness rank for the three indicators: total nitrogen (TN) > nitrate/nitrite nitrogen (NOx--N) > ammonia nitrogen (NH3-N), according to the Chinese Surface Water Quality Standard. TN pollution was severe for the entire watershed, while NOx--N pollution was significant for ponds and ditches far from the village, and the NH3-N concentrations were acceptable except for the ponds near the village in summer. Although food and cash crop production accounted for the largest source of N loads, we discovered that mini-point pollution sources, including animal feeding operations, rural residential sewage, and waste, together contributed as high as 47% of the TN and NH3-N loads in ponds and ditches. So, apart from eco-fertilizer programs and concentrated animal feeding operations, the importance of environmental awareness building for resource management is highlighted for small farmers in headwater agricultural watersheds. As a first attempt to incorporate multipond systems into the process-based modeling of nonpoint source (NPS) pollution, this work can inform other hydro-environmental studies on scattered and small water bodies. The results are also useful to water quality improvement for entire river basins.

Two Model Performance Comparisons with Multisite Observations Based on Uncertainty Methods for Modeling Hydrologic Dynamics

AbstractThe HSPF [Hydrologic Simulation Program—FORTRAN (Computer software). EPA National Exposure Research Laboratory, Athens, Georgia] and SWAT [Soil and Water Assessment Tool (Computer software)...

Integrating water quality responses to best management practices in Portugal.

Nutrient nonpoint pollution has a significant impact on water resources worldwide. The main challenge of this work was to assess the application of best management practices in agricultural land to comply with water quality legislation for surface waters. The Hydrological Simulation Program-FORTRAN was used to evaluate water quality of Ave River in Portugal. Best management practices (infiltration basin) (BMP) were applied to agricultural land (for 3, 6, 9, 12, and 15% area) with removal efficiencies of 50% for fecal coliforms and 30% for nitrogen, phosphorus, and biochemical oxygen demand. The inflow of water quality constituents was reduced for all scenarios, with fecal coliforms achieving the highest reduction between 5.8 and 28.9% and nutrients and biochemical oxygen demand between 2 and 13%. Biochemical oxygen demand and orthophosphates concentrations achieved a good water quality status according to the European Legislation for scenarios of BMP applied to 3 and 12% agricultural area, respectively. Fecal coliform levels in Ave River basin require further treatment to fall below the established value in the abovementioned legislation. This study shows that agricultural watersheds such as Ave basins demand special attention in regard to nonpoint pollution sources effects on water quality and nutrient loads.

A Multialgorithm Approach to Land Surface Modeling of Suspended Sediment in the Colorado Front Range.

A new paradigm of simulating suspended sediment load (SSL) with a Land Surface Model (LSM) is presented here. Five erosion and SSL algorithms were applied within a common LSM framework to quantify uncertainties and evaluate predictability in two steep, forested catchments (>1,000 km2). The algorithms were chosen from among widely used sediment models, including empirically based: monovariate rating curve (MRC) and the Modified Universal Soil Loss Equation (MUSLE); stochastically based: the Load Estimator (LOADEST); conceptually based: the Hydrologic Simulation Program—Fortran (HSPF); and physically based: the Distributed Hydrology Soil Vegetation Model (DHSVM). The algorithms were driven by the hydrologic fluxes and meteorological inputs generated from the Variable Infiltration Capacity (VIC) LSM. A multiobjective calibration was applied to each algorithm and optimized parameter sets were validated over an excluded period, as well as in a transfer experiment to a nearby catchment to explore parameter robustness. Algorithm performance showed consistent decreases when parameter sets were applied to periods with greatly differing SSL variability relative to the calibration period. Of interest was a joint calibration of all sediment algorithm and streamflow parameters simultaneously, from which trade‐offs between streamflow performance and partitioning of runoff and base flow to optimize SSL timing were noted, decreasing the flexibility and robustness of the streamflow to adapt to different time periods. Parameter transferability to another catchment was most successful in more process‐oriented algorithms, the HSPF and the DHSVM. This first‐of‐its‐kind multialgorithm sediment scheme offers a unique capability to portray acute episodic loading while quantifying trade‐offs and uncertainties across a range of algorithm structures.

Using the HSPF and SWMM Models in a High Pervious Watershed and Estimating Their Parameter Sensitivity

Models are necessary tools for watershed management. However, applying watershed models is time consuming and requires technical knowledge, including model selection and validation. The objective of this study is to assess two commonly used watershed models and their parameter sensitivity to reduce model loadings and to gain a better understanding of the model performances. The Hydrological Simulation Program-Fortran (HSPF) model and Storm Water Management Model (SWMM) were applied to a mostly forested Taiwanese reservoir watershed with pollution from tea plantations. Statistical analysis showed that both models are suitable for the studied watershed, but the performances of the flow and water quality simulations are different. The mean flow simulated by SWMM was lower than the experimental observations. The HSPF model performed better, possibly because the soil in the study area is highly permeable and the HSPF model has more precise soil layer calculations. SWMM may underestimate the total phosphorous (TP) and suspended solid (SS) loads following small storm events in highly permeable watersheds. The Latin Hypercube-One factor At a Time (LH-OAT) method was used to determine the parameter sensitivity of the HSPF model and SWMM. In both of the models, the parameters related to infiltration and soil characteristics strongly affected the flow simulation, except when using the Horton infiltration method in the SWMM. Manning’s roughness coefficient for pervious areas was more sensitive in SWMM than in the HSPF model because SWMM has fewer parameters.

Implications of potential evapotranspiration methods for streamflow estimations under changing climatic conditions

ABSTRACTSeveral potential evapotranspiration (PET) estimation methods are commonly used to quantify water and energy budgets. As each PET method can differ, their effects on projected streamflows under changing climatic conditions are critical to quantify the sensitivities of these methods. We used the Coupled Model Intercomparison Project (CMIP5) climate dataset and Hydrological Simulation Program – FORTRAN (HSPF) model to compare the following five PET methods [Hargreaves (HG), Hamon (HM), Thornthwaite (TW), Priestley–Taylor (PT) and Penman–Monteith (PM)] for the Susquehanna River Basin in the northeastern United States. As PET is used as an input, various configurations of HSPF driven by these five PET estimates were used to calibrate HSPF with observed streamflow data from 41 gaging stations. We also used nine global climate model inputs to derive five PET estimates, which were subsequently used as inputs to compute streamflow projections for 2020–2099. An increase in precipitation from 6.2 to 7.2% and an increase in temperature from 1.8 to 2.7 °C were projected, while changes in PET and actual evapotranspiration (AET) were found to substantially differ among the PET methods. The HM method shows an increase in AET of between 14 and 24%, while the other methods show an increase of between 7 and 12%. It is concluded that streamflow projections are sensitive to the selection of the PET methods in the HSPF model; a decrease of up to 5.5% and increase of up to 3.6% are projected for PET levels estimated by using the HM and HG methods, respectively; and both HM and TW are found to be suitable for simple seasonal water balance analyses conducted at regional scales.

Predictions of Diffuse Pollution by the HSPF Model and the Back-Propagation Neural Network Model.

Watershed models are important tools for predicting the possible change of watershed responses. Environmental models comprise the deterministic model and the probabilistic model. This study discusses the Hydrological Simulation Program Fortran (HSPF) and the Back-Propagation Neural Network (BPNN); these two models represent the deterministic model and the probabilistic model, respectively. As the properties of the two models are distinct, they have differing abilities to predict surface-runoff pollution. For the two models, the runoff simulation results are satisfactory. However, due to the limitation of the water quality monitoring records, pollution simulation is more difficult than runoff simulation. The results indicate that the prediction accuracy in the pollution simulation can be improved by adjusting the BPNN neurons. On the contrary, improving the prediction accuracy is limited by HSPF. Although the flexibility of BPNN is higher than HSPF, sufficient historical monitoring records are important for both of these models.

Predicting Impact of Climate Change on Water Temperature and Dissolved Oxygen in Tropical Rivers

Predicting the impact of climate change and human activities on river systems is imperative for effective management of aquatic ecosystems. Unique information can be derived that is critical to the survival of aquatic species under dynamic environmental conditions. Therefore, the response of a tropical river system under climate and land-use changes from the aspects of water temperature and dissolved oxygen concentration were evaluated. Nine designed projected climate change scenarios and three future land-use scenarios were integrated into the Hydrological Simulation Program FORTRAN (HSPF) model to determine the impact of climate change and land-use on water temperature and dissolved oxygen (DO) concentration using basin-wide simulation of river system in Malaysia. The model performance coefficients showed a good correlation between simulated and observed streamflow, water temperature, and DO concentration in a monthly time step simulation. The Nash–Sutcliffe Efficiency for streamflow was 0.88 for the calibration period and 0.82 for validation period. For water temperature and DO concentration, data from three stations were calibrated and the Nash–Sutcliffe Efficiency for both water temperature and DO ranged from 0.53 to 0.70. The output of the calibrated model under climate change scenarios show that increased rainfall and air temperature do not affects DO concentration and water temperature as much as the condition of a decrease in rainfall and increase in air temperature. The regression model on changes in streamflow, DO concentration, and water temperature under the climate change scenarios illustrates that scenarios that produce high to moderate streamflow, produce small predicted change in water temperatures and DO concentrations compared with the scenarios that produced a low streamflow. It was observed that climate change slightly affects the relationship between water temperatures and DO concentrations in the tropical rivers that we include in this study. This study demonstrates the potential impact of climate and future land-use changes on tropical rivers and how they might affect the future ecological systems. Most rivers in suburban areas will be ecologically unsuitable to some aquatic species. In comparison, rivers surrounded by agricultural and forestlands are less affected by the projected climate and land-uses changes. The results from this study provide a basis in which resource management and mitigation actions can be developed.

Comprehensive study on parameter sensitivity for flow and nutrient modeling in the Hydrological Simulation Program Fortran model

Numerous parameters are used to construct the HSPF (Hydrological Simulation Program Fortran) model, which results in significant difficulty in calibrating the model. Parameter sensitivity analysis is an efficient method to identify important model parameters. Through this method, a model's calibration process can be simplified on the basis of understanding the model's structure. This study investigated the sensitivity of the flow and nutrient parameters of HSPF using the DSA (differential sensitivity analysis) method in the Xitiaoxi watershed, China. The results showed that flow was mostly affected by parameters related to groundwater and evapotranspiration, including DEEPFR (fraction of groundwater inflow to deep recharge), LZETP (lower-zone evapotranspiration parameter), and AGWRC (base groundwater recession), and most of the sensitive parameters had negative and nonlinear effects on flow. Additionally, nutrient components were commonly affected by parameters from land processes, including MON-SQOLIM (monthly values limiting storage of water quality in overland flow), MON-ACCUM (monthly values of accumulation), MON-IFLW-CONC (monthly concentration of water quality in interflow), and MON-GRND-CONC (monthly concentration of water quality in active groundwater). Besides, parameters from river systems, KATM20 (unit oxidation rate of total ammonia at 20°C) had a negative and almost linear effect on ammonia concentration and MALGR (maximal unit algal growth rate for phytoplankton) had a negative and nonlinear effect on ammonia and orthophosphate concentrations. After calibrating these sensitive parameters, our model performed well for simulating flow and nutrient outputs, with R 2 and ENS (Nash-Sutcliffe efficiency) both greater than 0.75 for flow and greater than 0.5 for nutrient components. This study is expected to serve as a valuable complement to the documentation of the HSPF model to help users identify key parameters and provide a reference for performing sensitivity analyses on other models.

Integration of Tidal Prism Model and HSPF for simulating indicator bacteria in coastal watersheds

Coastal water quality is strongly influenced by tidal fluctuations and water chemistry. There is a need for rigorous models that are not computationally or economically prohibitive, but still allow simulation of the hydrodynamics and bacteria sources for coastal, tidally influenced streams and bayous. This paper presents a modeling approach that links a Tidal Prism Model (TPM) implemented in an Excel-based modeling environment with a watershed runoff model (Hydrologic Simulation Program FORTRAN, HSPF) for such watersheds. The TPM is a one-dimensional mass balance approach that accounts for loading from tidal exchange, runoff, point sources and bacteria die-off at an hourly time step resolution. The novel use of equal high-resolution time steps in this study allowed seamless integration of the TPM and HSPF. The linked model was calibrated to flow and E. Coli data (for HSPF), and salinity and enterococci data (for the TPM) for a coastal stream in Texas. Sensitivity analyses showed the TPM to be most influenced by changes in net decay rates followed by tidal and runoff loads, respectively. Management scenarios were evaluated with the developed linked models to assess the impact of runoff load reductions and improved wastewater treatment plant quality and to determine the areas of critical need for such reductions. Achieving water quality standards for bacteria required load reductions that ranged from zero to 90% for the modeled coastal stream.

Potential impact of climate change on streamflow of major Ethiopian rivers

In this study, HSPF (Hydrologic Simulation Program-FORTRAN) was used to analyze the potential impact of climate change on the streamflow of four major river basins in Ethiopia: Awash, Baro, Genale, and Tekeze. The calibrated and validated HSPF model was forced with daily climate data of 10 CMIP5 (Coupled Model Intercomparison Project phase 5) Global Climate Models (GCMs) for the 1971–2000 control period and the RCP4.5 and RCP8.5 climate projections of 2041–2070 (2050s) and 2071–2100 (2080s). The ensemble median of these 10 GCMs projects the temperature in the four study areas to increase by about 2.3 °C (3.3 °C) in 2050s (2080s), whereas the mean annual precipitation is projected to increase by about 6% (9%) in 2050s (2080s). This results in about 3% (6%) increase in the projected annual streamflow in Awash, Baro, and Tekeze rivers whereas the annual streamflow of Genale river is projected to increase by about 18% (33%) in the 2050s (2080s). However, such projected increase in the mean annual streamflow due to increasing precipitation over Ethiopia contradicts the decreasing trends in mean annual precipitation observed in recent decades. Regional climate models of high resolutions could provide more realistic climate projections for Ethiopia’s complex topography, thus reducing the uncertainties in future streamflow projections.

Usability of the BLRP model for hydrological applications in arid and semi-arid regions with limited precipitation data

In this study, Hydrological Simulation Program-FORTRAN (HSPF) is used to investigate rainfall-runoff process in Taleghan watershed, northern Iran. Despite the high accuracy of the model, the lack of rainfall data at short time scales (hour and less than hour) restricted implementation of the model especially for long time simulations. Some studies use simple division for daily rainfall disaggregation into the hourly values to provide data requirements of HSPF model. In simple division, each rainfall event is divided into 24 pulse stochastically and the peak flows may not properly being simulated due to the lower rainfall intensities. In this study, random parameter Bartlett–Lewis rectangular pulse (BLRP) model was implemented to disaggregate daily rainfall time series into the hourly values and the results compared with that of simple division. In BLRP model, parameters of the model calibrated against the 1, 24 and 48 h mean, variance, lag1 auto covariance and proportion dry of observed rainfall. The calibrated model was then implemented to disaggregate daily rainfall data into the hourly values. To compare two disaggregation approaches, daily stream flow simulation by HSPF model is initialized in 2 scenarios by applying the hourly rainfall data resulted from two disaggregation methods. The results indicated that while using the simple division method leads to the underestimation of peak flows, using the BLRP model improved peak flow simulations. This study indicated usability of the BLRP model for rainfall disaggregation in arid and semi-arid regions with limited fine scale precipitation data availability.

Estimating impact of rainfall change on hydrological processes in Jianfengling rainforest watershed, China using BASINS-HSPF-CAT modeling system

Climate change over the past several decades has resulted in shifting rainfall pattern and modifying rainfall intensity, which has exacerbated hydrological processes and added the uncertainty and instability to these processes. This study ascertained impacts of potential future rainfall change on hydrological processes at the Jianfengling (JFL) tropical mountain rainforest watershed in Hainan Island, China using the BASINS (Better Assessment Science Integrating Point and Nonpoint Sources)-HSPF (Hydrological Simulation Program-FORTRAN)-CAT (Climate Assessment Tool) modeling system. The HSPF model was calibrated and validated with available measured data prior to its applications. Three simulation scenarios were then performed to gain a better understanding of the impacts of different rainfall rates and storm intensities on stream discharge, surface water runoff from forest land, and water outflow from the JFL watershed outlet. Results showed that a 10% increase in rainfall rate could result in 1.3 times increase in stream discharge, surface runoff, and water outflow. A potential future wet climate could have profound impacts on hydrological processes at the JFL watershed, whereas a potential future dry climate could result less impacts on stream discharge, surface runoff, and water outflow at the same watershed. Our simulation further revealed that climate change driven by extreme rain storms had greater impacts on annual surface runoff than on annual stream discharge. The coupled CAT-HSPF model is a useful tool to modify historical rainfall data for projecting future rainfall variation impacts on forest hydrological processes due to climate change. This approach would be able to extend to other regions around the world.

Time-varying sensitivity analysis of hydrologic and sediment parameters at multiple timescales: Implications for conservation practices

Environmental models can be used to better understand the hydrologic and sediment behavior in a watershed system. However, different processes may dominate at different time periods and timescales, which highly complicate the model interpretation. The related parameter uncertainty may be significant and needs to be addressed to avoid bias in the watershed management. In this study, we used the time-varying and multi-timescale (TVMT) method to characterize the temporal dynamics of parameter sensitivity at different timescales in hydrologic and sediment modeling. As a case study, the first order sensitivity indices were estimated with the Fourier amplitude sensitivity test (FAST) method for the Hydrological Simulation Program - Fortran (HSPF) model in the Zhangjiachong catchment in the Three Gorge Reservoir Region (TGRR) in China. The results were compared to those of the traditional aggregate method to demonstrate the merits of the TVMT method. The time-varying nature of the hydrologic and sediment parameters was revealed and explained mainly by the variation of hydro-climatic conditions. The baseflow recession parameter, evapotranspiration (ET) parameter for the soil storage, and sediment washoff parameter showed high sensitivities almost across the whole period. However, parameters related to canopy interception and channel sediment scour varied notably over time due to changes in the climate forcing. The timescale-dependent characteristics was observed and was most evident for the baseflow recession parameter and ET parameter. At last, the parameters affecting the sediment export and transport were discussed together with the inferred conservation practices. Reasonable controls for sediment must be storm-dependent. Compared to management practices on the land surface, practices affecting channel process would be more effective during storm events. Our results present one of the first investigations for sediment modeling in terms of the importance of parameter sensitivity in both time periods and evaluation timescales for the model calibration, diagnostic evaluation, and prioritizing efforts for conservation practices.

Nitrate, Total Ammonia, and Total Suspended Sediments Modeling for the Mobile River Watershed

This paper presents details of a water quality model of the Mobile River watershed that estimates total suspended sediments at the outlet of the watershed. The model is capable of simulating Nitrate (NO3), Total Ammonia (TAM), and Total Suspended Sediments (TSS) for extended periods of time at a daily temporal resolution (1970-1995). The Hydrological Simulation Program Fortran is used for modeling the hydrological, nitrogenous constituents, and sediment processes. Based on the nutrient simulation and exploration of the effects of two management practices (filter strips and stream bank stabilization and fencing) on nutrient removal, the resulting sediment model is used to implement the most efficient nutrient management practice and explore its effects on TSS concentrations in the Mobile River. Results show that the implementation of the management practice “stream bank stabilization and fencing” to agricultural lands in sub-watersheds that had intense agricultural activities produced the highest reductions of NO3 concentration (up to 14.06%) and TAM concentrations (8.01%). Based on the nutrient simulation and identification of “stream bank stabilization and fencing” as the most efficient BMP for nutrient concentration reduction, the sediment model was used to explore its effects on TSS concentrations in the Mobile River. Implementing “stream bank stabilization and fencing” produced monthly median TSS concentration reductions ranging from 3.6% to 10.6% in the Mobile River.

Climate change and land use impacts on hydrologic processes of watershed systems

Land use, land cover and climate change (CC) can significantly influence the hydrologic balance and biogeochemical processes of watershed systems. These changes can alter interception, evapotranspiration (ET), infiltration, soil moisture, water balance, and biogeochemical cycling of carbon, nitrogen, and other elements. The need to evaluate the combined effect of land use change and CC of watershed systems is a focus of this study. We simulated watershed processes in the SuAsCo River watershed in MA, USA, using a calibrated and validated Hydrological Simulation Program Fortran model. Climatic scenarios included downscaled regional projections from Global Climate Model models. The Land Transformation Model was used to project land use. Combined change in land cover and climate reduce ET with loss of vegetation. Changes in climate and land cover increase surface runoff significantly by 2100 as well as stream discharge. Combined change in land cover and climate cause 10% increase in peak volume with 7% increase in precipitation and 75% increase in effective impervious area. Climate and land use changes can intensify the water cycle and introduce seasonal changes in watershed systems. Understanding dynamic changes in watershed systems is critical for mitigation and adaptation options. We propose restoration strategies that can increase the resilience of watershed systems.

HSPEXP+: An Enhanced Expert System for HSPF Model Calibration—A Case Study of the Snake River Watershed in Minnesota

The U.S. Geological Survey developed the Expert System (HSPExp) in 1994 to assist modelers in the calibration of Hydrologic Simulation Program—FORTRAN (H…

Characteristics of Suspended Sediment Loadings under Asian Summer Monsoon Climate Using the Hydrological Simulation Program-FORTRAN

The extreme variation in the amount of annual precipitation and rainfall during single events is typical of the East Asian monsoon climate and may greatly influence the characteristics of the suspended sediment load. The turbidity in Lake Imha which is the eighth largest multipurpose dam in Korea has been the cause of major water quality problems for use as drinking water. The turbidity rose to 882 NTU, and it remained over 30 NTU continuously for 170 days during 2002, as the result of significant amounts of soil erosion from the watershed during the Asian monsoon typhoon. In this study, characteristics of suspended sediment loadings under the Asian summer monsoon climate was investigated by comparing the variation of yearly suspended sediment loads and the ratio of maximum suspended sediment loads in a single event to yearly suspended sediment load from Lake Imha watershed using the Hydrologic Simulation Program-FORTRAN (HSPF). The model calibration is performed according to the 2009–2010 events, and simulation results characterized suspended sediment loadings under the Asian summer monsoon climate for 2001–2010. Water sampling and flow rate measurements were performed every 4–6 h, and calibration was performed using hourly simulated sediment loads. The calibration results demonstrated good agreement with the observed data. The characteristics of suspended sediment loadings under the Asian summer monsoon climate are a high variance of the yearly suspended sediment load and a significant of amount of suspended sediment load during a single event influenced by the typhoon intensity. The maximum yearly suspended sediment load was 10 times higher than the minimum yearly value. About half of the yearly suspended sediment load was loaded with a single event under the Asian summer monsoon climate and the ratio of suspended sediment loads by a single event to total yearly loads ranged from 29% to 90%. Structural best management practices (BMPs) to trap suspended sediment in stormwater such as stormwater ponds or wetlands rely on much more storage volume or area and non-structural BMPs to minimize soil erosion by source control such as mulching or revegetation in disturbed areas, which are important BMPs, especially in the Asian summer monsoon region.

Impacts of climate change and urban growth on the streamflow of the Milwaukee River (Wisconsin, USA)

Hydrological impact studies of climate change increasingly take land use changes into account. However, the Midwestern USA is still understudied in this context. This study investigated the impacts of potential climate change and urban growth on the streamflow characteristics of the Milwaukee River located in southeastern Wisconsin. The Hydrological Simulation Program-Fortran (HSPF) was set up for the catchment and calibrated against observed streamflow data. The calibrated HSPF model was run with a series of climate and urban growth scenarios generated from nine global climate models (GCMs) and a land use simulation model, respectively. The outcomes from the GCMs, statistically downscaled at 10-km grid spacing, generally indicated a warmer and wetter climate by the mid-twenty-first century, and the land use simulation model projected moderate urban growth by the time. Major findings from the study include: (1) land use changes alone resulted in negligible streamflow changes; (2) low flows showed more sensitivity than mean streamflow to climate change; (3) streamflow variability increased with both land use and climate changes, and (4) uncertainty in simulated streamflow among GCMs was larger than uncertainty among the GCM output themselves. The findings suggest that the current pace of urban growth would not pose much threat to the water resources in the area. Considering that low flow indices responded more sensitively than mean streamflow to climate change, measures to improve resilience to drought conditions are recommended. Because land use change impacts were quite small, considering the impact of both climate and land use scenarios did not produce a significantly different result.