Hydrological Simulation Program-Fortran Model Research Articles

Comparing Statistical and Semi-Distributed Rainfall–Runoff Models for a Large Subtropical Watershed: A Case Study of Jiulong River Catchment, China

In this contribution, the authors present their preliminary investigations into modeling the rainfall–runoff generation relation in a large subtropical catchment (Jiulong River catchment) on the southeast coast of China. Previous studies have mostly focused on modeling the streamflow and water quality of its small rural subcatchments. However, daily runoff on the scale of the whole catchment has not been modeled before, and hourly runoff data are desirable for some oceanographic applications. Three methods are proposed for modeling streamflow using rainfall outputted by the Weather Research Forecast (WRF) model, calculated potential evaporation (PET), and land cover type: (i) a ridge regression model; (ii) NPRED-KNN: a nonparametric k-nearest neighbor model (KNN) employing a parameter selection method (NPRED) based on partial information coefficient; (iii) the Hydrological Simulation Program-Fortran (HSPF) model with an hourly time step. Results show that the NPRED-KNN approach is the most unsuitable method of those tested. The HSPF model was manually calibrated, and ridge regression performs no worse than HSPF based on daily verification, whilst HSPF can produce realist daily flow time series, of which ridge regression is incapable. The HSPF model seems less prone to systematic underprediction when replicating monthly-annual water balance, and it successfully replicates the baseflow index (the flow intensity) of the Jiulong River catchment system.

Parameter Estimation and Uncertainty Analysis: A Comparison between Continuous and Event-Based Modeling of Streamflow Based on the Hydrological Simulation Program–Fortran (HSPF) Model

Hydrologic modeling is usually applied to two scenarios: continuous and event-based modeling, between which hydrologists often neglect the significant differences in model application. In this study, a comparison-based procedure concerning parameter estimation and uncertainty analysis is presented based on the Hydrological Simulation Program–Fortran (HSPF) model. Calibrated parameters related to base flow and moisture distribution showed marked differences between the continuous and event-based modeling. Results of the regionalized sensitivity analysis identified event-dependent parameters and showed that gravity drainage and storage outflow were the primary runoff generation processes for both scenarios. The overall performance of the event-based simulation was better than that of the daily simulation for streamflow based on the generalized likelihood uncertainty estimation (GLUE). The GLUE analysis also indicated that the performance of the continuous model was limited by several extreme events and low flows. In the event-based scenario, the HSPF model performances decreased as the precipitation became intense in the event-based modeling. The structure error of the HSFP model was recognized at the initial phase of the rainfall-event period. This study presents a valuable opportunity to understand dominant controls in different hydrologic scenario and guide the application of the HSPF model.

Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds

A vast amount of future climate scenario datasets, created by climate models such as general circulation models (GCMs), have been used in conjunction with watershed models to project future climate variability impact on hydrological processes and water quality. However, these low spatial-temporal resolution datasets are often difficult to downscale spatially and disaggregate temporarily, and they may not be accurate for local watersheds (i.e., state level or smaller watersheds). This study applied the US-EPA (Environmental Protection Agency)’s Climate Assessment Tool (CAT) to create future climate variability scenarios based on historical measured data for local watersheds. As a case demonstration, CAT was employed in conjunction with HSPF (Hydrological Simulation Program-FORTRAN) model to assess the impacts of the potential future extreme rainfall events and air temperature increases upon nitrate-nitrogen (NO3-N) and orthophosphate (PO4) loads in the Lower Yazoo River Watershed (LYRW), a local watershed in Mississippi, USA. Results showed that the 10 and 20% increases in rainfall rate, respectively, increased NO3-N load by 9.1 and 18% and PO4 load by 12 and 24% over a 10-year simulation period. In contrast, simultaneous increases in air temperature by 1.0 °C and rainfall rate by 10% as well as air temperature by 2.0 °C and rainfall rate by 20% increased NO3-N load by 12% and 20%, and PO4 load by 14 and 26%, respectively. A summer extreme rainfall scenario was created if a 10% increase in rainfall rate increased the total volume of rainwater for that summer by 10% or more. When this event occurred, it could increase the monthly loads of NO3-N and PO4, by 31 and 41%, respectively, for that summer. Therefore, the extreme rainfall events had tremendous impacts on the NO3-N and PO4 loads. It is apparent that CAT is a flexible and useful tool to modify historical rainfall and air temperature data to predict climate variability impacts on water quality for local watersheds.

A new very high-resolution climatological dataset in Portugal: Application to hydrological modeling in a mountainous watershed

The study of precipitation and temperature variability in Portugal, including their extremes, is often restricted by the lack of high-resolution gridded datasets at daily timescales and available for sufficiently long time periods. They are of quite importance specially when considering hydrology modeling at a local scale. To overcome this limitation, we develop new high-resolution gridded datasets (∼1 km) of daily precipitation (1950–2015) over Portugal. Daily precipitation is downscaled by ordinary kriging from a coarser gridded dataset (∼20 km). Daily temperatures were retrieved from a previous work and extracted for the target watershed in this study, Corgo River (northern Portugal). The aim of the present study was to investigate the potential of the new high-resolution data in improving the performance of a distributed hydrologic model, Hydrological Simulation Program – FORTRAN (HSPF) in simulating flowrates at one target watershed in northern Portugal (Corgo River watershed), thus providing a practical basis for subsequent hydrological analysis. The performances of the HSPF model, driven by either a single weather station or the new gridded datasets are compared. The results clearly hint at an improved model performance when using our dataset (Nash-Sutcliffe coefficient of efficiency at daily timescale: 0.34 for the single-station run and 0.64 for the multi-point run). A good performance was also found in reproducing specific flash flood events. Although the advantage of using these novel climatic datasets for hydrologic modeling in Portugal is demonstrated herein, they can be applied to other areas of research, such as ecology, agriculture and forestry, contributing to more accurate decision support systems to assist decision-makers and stakeholders.

Identification of critical source areas under present and projected land use for effective management of diffuse pollutants in an urbanized watershed

ABSTRACTThe land-use characteristics of a watershed determined the amount of pollution produced in it, which can be curtailed by implementation of best management practices (BMPs) in an identified critical source area (CSA). Present and future land-use scenarios of the watershed were produced, and the hydrological simulation program FORTRAN model was used to model the hydrology and in-stream pollutants’ concentrations. The validated model was utilized to identify the CSA for diffuse total nitrogen, total phosphorus, sediment, and biochemical oxygen demand considering the two land-use scenarios. The results showed that CSA and the water quality index produced by the two land-use scenarios varied in each of the diffuse pollutants considered. It was observed that some portion of the identified CSA remains unchanged despite the changes in the land use and this was attributed to consistent urban development in these areas. The results in this study illustrate that BMPs can be included in the design and planning of future urban expansion based on the identified CSA derived from the expected future land-use changes. As anticipated, this approach will provide resilience on the effects of urbanization on the diffuse pollutants loads in a rapidly urbanized watershed.

Drought and weir construction impact stationarity assumption in watershed water quality modeling in South Korea

Existing watershed water quality models assume that the physio-biochemical processes affecting water quality variables are stationary. Using Hydrologic Simulation Program-Fortran (HSPF) parameterized before drought and weir construction, this study investigates if this assumption is valid in the model used for simulating water quality variables after drought and weir construction. The study area is located in South Korea, where tremendous ecological stress occurred following a drought and the completion of weir construction in 2012. To assess model performance and explore temporal changes in water quality variables, various goodness-of-fit measures and wavelet analyses are used. This study indicates that drought is the dominant stressor on water quality, and the co-occurring impact of weir construction is not discernible. Drought and weir construction cause nonstationary temporal changes in individual water quality variables and in their interrelationships, for example, dependence of dissolved oxygen on water temperature. This study demonstrated that the stationarity assumption implicit in the model parameterized under a non-drought condition is not valid during a drought condition. As a result, the model performance degrades when simulating drought-influenced physio-biochemical processes of water quality variables. The HSPF model lacks functionality for translating temporal changes in water temperature into kinetic parameters that govern biochemical processes of various water quality variables. Wavelet analysis is a good tool for elucidating unique aspects of nonstationary temporal change at various temporal scales, especially for recognizing algal succession pattern changes and identifying nonstationary relationships between any two variables.

Hydrological and flood hazard assessment using a coupled modelling approach for a mountainous catchment in Portugal

Floods may lead to destruction of property, to damage to the environment and ultimately to loss of lives. Although it is not possible to avoid them, they are enhanced by human activities that increase the probability of occurrence of these natural events. Preliminary flood risk assessment and determination of areas of potential significant flood risk is mandatory according to the European Floods Directive (2007). In order to meet the established legislation, a methodology was developed that couples two modelling approaches: the Hydrological Simulation Program—FORTRAN (HSPF) and IBER. A target watershed, with complex orography and known to be vulnerable to flood hazards, is selected: the Vez River (northern Portugal). The performance of the HSPF model, driven by a climate gridded dataset, was assessed, followed by the reconstruction of the flow rate in the catchment for the period from 1950 to 2015. The results hint at an agreement between simulated and observed daily flow rates, with high coefficient of determination value and of the Nash–Sutcliffe coefficient of efficiency (> 0.7 daily timescale). A satisfactory performance was also found in reproducing flood peak events. An average deviation of 10% was found between observed and simulated flood peaks. The output of HSPF was subsequently used to drive IBER, thus determining flood hazard areas for a 10, 50 and 100-year return periods. The methodology presented here provides basic tools for decision-makers to evaluate hydrologic responses to climate data, namely the determination of flood hazard maps, but also risk assessment, water management, environmental protection and sustainability.

A systematic assessment of watershed-scale nonpoint source pollution during rainfall-runoff events in the Miyun Reservoir watershed.

The assessment of peak flow rate, total runoff volume, and pollutant loads during rainfall process are very important for the watershed management and the ecological restoration of aquatic environment. Real-time measurements of rainfall-runoff and pollutant loads are always the most reliable approach but are difficult to carry out at all desired location in the watersheds considering the large consumption of material and financial resources. An integrated environmental modeling approach for the estimation of flash streamflow that combines the various hydrological and quality processes during rainstorms within the agricultural watersheds is essential to develop targeted management strategies for the endangered drinking water. This study applied the Hydrological Simulation Program-Fortran (HSPF) to simulate the spatial and temporal variation in hydrological processes and pollutant transport processes during rainstorm events in the Miyun Reservoir watershed, a drinking water resource area in Beijing. The model performance indicators ensured the acceptable applicability of the HSPF model to simulate flow and pollutant loads in the studied watershed and to establish a relationship between land use and the parameter values. The proportion of soil and land use was then identified as the influencing factors of the pollution intensities. The results indicated that the flush concentrations were much higher than those observed during normal flow periods and considerably exceeded the limits of Class III Environmental Quality Standards for Surface Water (GB3838-2002) for the secondary protection zones of the drinking water resource in China. Agricultural land and leached cinnamon soils were identified as the key sources of sediment, nutrients, and fecal coliforms. Precipitation volume was identified as a driving factor that determined the amount of runoff and pollutant loads during rainfall processes. These results are useful to improve the streamflow predictions, provide useful information for the identification of highly polluted areas, and aid the development of integrated watershed management system in the drinking water resource area.

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.

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.

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.

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.

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.

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.

실측 하천 단면자료를 이용한 HSPF 유역모델의 수리정확도 개선

The hydrological simulation program FORTRAN (HSPF) is a comprehensive watershed model that employs the hydraulic function table (FTABLE) (depth-area-volume-flow relationship) to represent the geometric and hydraulic properties of water bodies. The hydraulic representation of the HSPF model mainly depends on the accuracy of the FTABLES. These hydraulic representations determine the response time of water quality state variables and also control the scour, deposition, and transport of sediments in the water body. In general, FTABLES are automatically generated based on reach information such as mean depth, mean width, length, and slope along with a set of standard assumptions about the geometry and hydraulics of the channel, so these FTABLES are unable to accurately describe the geometry and hydraulic behavior of rivers and reservoirs. In order to compensate the weakness of HSPF for hydraulic modeling, we generated alternate method to improve the accuracy of FTABLES for rivers, using the surveyed cross sections and rating curves. The alternative method is based on the hydraulics simulated by HEC-RAS using the surveyed cross sections and rating curves, and it could significantly improve the accuracy of FTABLES. Although the alternate FTABLE greatly improved the hydraulic accuracy of the HSPF model, it had little effect on the hydrological simulation.

Hydrologic Evaluation of River Basin Scale Tillage Effects on Non‐Point Source Loads from Upland Crop Areas†

AbstractThis study used the Hydrological Simulation Program—Fortran (HSPF) model to evaluate the river basin scale effects of nonpoint source (NPS) pollution loads caused by tillage and no‐tillage applications to upland crop areas. The study site was the Byulmi‐cheon river basin (1.21 km2) of South Korea. Hourly rainfall, discharge and stream water quality data for 2 years (2012–2013) were collected at the river basin outlet. The HSPF model under tillage conditions was calibrated using 23 rainfall events with an average Nash–Sutcliffe model efficiency value for runoff of 0.61 and determination coefficients for sediment, total nitrogen (T‐N) and total phosphorus (T–P) of 0.58, 0.61 and 0.62 respectively. The field experiment results from the no‐tillage plots with slopes of 3 and 8% under radish and sesame cultivation showed decreases in the runoff ratio, sediment, T‐N and T–P of 10.8, 81.7, 11.9 and 17.1% respectively. The HSPF model parameters soil bulk density (BD) and soil infiltration capacity (INFILT) were controlled for the upland crop areas during the evaluation of the no‐tillage effects. By increasing the parameter values from 1.33 Mg m−3 BD and 4.1 mm h−1 INFILT for the tillage condition to 1.90 Mg m−3 BD and 8.9 mm h−1 INFILT for the no‐tillage condition, the river basin runoff ratio and sediment, T‐N and T–P values were reduced by 10.3, 56.7, 18.3 and 35.9% respectively. Copyright © 2016 John Wiley & Sons, Ltd.