Hydrological Simulation Program-Fortran Model Research Articles

Evaluation of Non-Point Source Pollution Load Characteristics and Identifying Management Sub-Basin Area and Best Management Practices Using HSPF Model in Yongdam Dam Watershed

Objectives : To identify and estimate the non-point source (NPS) pollution loads in the Yongdam watershed, and to take an appropriate NPS management plan suitable for the environmental conditions of the sub-basin of Yongdam watershed.Methods : The NPS pollutant loads of the Yongdam watershed was investigated to establish the hydrological simulation program-fortran (HSPF) model for the study area so that the characteristics of non-point runoff were simulated. Furthermore, the detailed catchment area subject to non-point pollution management was selected and the effect of reducing non-point pollution was examined based on the various simulation results.Results and Discussion : The three sub-basins, including specific component of catchments, of Yongdam watershed was selected according to the load intensity and distribution of NPS pollution. The result of analyzing the load flowing into the downstream by rainfall intensity revealed that the pollutant load accounted for 11.8~19.9% in the dry season, and for Jinan-cheon sub-basin the load was high in the range of 10~30 mm while Janggye-cheon sub-basin and downstream of Janggye-cheon junction sub-basin showed a high load in the range 30~60 mm. In addition, the load duration curve (LDC) showed the excess frequency of BOD load was high when the flow rate increased at the end of stream for each sub-basin, whereas the load excess frequency was high in T-P in the entire flow range. LDC analysis led to us that the water quality of stream was affected by point and non-point pollutants in a complex way. When the ground cover in a farm were installed by selecting 10 detailed catchments with high need for NPS pollution management, the reduction of T-P load was estimated to be reduced by 325.256~995.912 g/d in Jinan-cheon sub-basin, 1279.813~3327.513 g/d in Janggye-cheon sub-basin, and 1316.831~3555.443 g/d in downstream of Janggye-cheon junction sub-basin.Conclusion : Through various simulation experiments using the HSPF model, it was feasible to select an catchment subject to NPS pollution control in detail and evaluate the effect of reducing NPS pollution.

Analysis of the effects of low impact development practices on hydrological components using HSPF

The purposes of this study are to propose the new approach for modeling the effectiveness of low impact development (LID) practices using Hydrological Simulation Program-Fortran (HSPF)'s Surface-FTABLE (function table) and to evaluate the impacts of LID application on hydrological components and water balance. LID was simulated using Surface-FTABLE, and changes in hydrological components and water balance were analyzed. These results were compared with results simulating LID using the HSPF LID Controls Tool built in the HSPF model. Embedded within the HSPF model, the HSPF LID Controls Tool is used to design and simulate infiltration-based best management practices. Surface runoff decreased similarly for both methods using Surface-FTABLE and LID Controls Tool. For Surface-FTABLE, the infiltration in the facility was reflected in the model, so interflow, outflow and baseflow outflow increased. As a result of the water balance analysis, the results of Surface-FTABLE showed a similar bias to those of the model without LID. In contrast, the results of the LID Controls Tool showed a large bias due to uninvolved infiltration. This study showed that HSPF Surface-FTABLE is applicable to LID simulation and that it is possible to simulate the change of each element of hydrologic components reasonably.

Adaptation measures under the impacts of climate and land-use/land-cover changes using HSPF model simulation: Application to Gongola river basin, Nigeria

Recently, there is an upsurge in flood emergencies in Nigeria, in which their frequencies and impacts are expected to exacerbate in the future due to land-use/land cover (LULC) and climate change stressors. The separate and combined forces of these stressors on the Gongola river basin is feebly understood and the probable future impacts are not clear. Accordingly, this study uses a process-based watershed modelling approach – the Hydrological Simulation Program FORTRAN (HSPF) (i) to understand the basin's current and future hydrological fluxes and (ii) to quantify the effectiveness of five management options as adaptation measures for the impacts of the stressors. The ensemble means of the three models derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are employed for generating future climate scenarios, considering three distinct radiative forcing peculiar to the study area. Also, the historical and future LULC (developed from the hybrid of Cellular Automata and Markov Chain model) are used to produce the LULC scenarios for the basin. The effective calibration, uncertainty and sensitivity analyses are used for optimising the parameters of the model and the validated result implies a plausible model with efficiency of up to 75 %. Consequently, the results of individual impacts of the stressors yield amplification of the peak flows, with more profound impacts from climate stressor than the LULC. Therefore, the climate impact may trigger a marked peak discharge that is 48 % higher as compared to the historical peak flows which are equivalent to 10,000-year flood event. Whilst the combine impacts may further amplify this value by 27 % depending on the scenario. The proposed management interventions such as planned reforestation and reservoir at Dindima should attenuate the disastrous peak discharges by almost 36 %. Furthermore, the land management option should promote the carbon-sequestering project of the Paris agreement ratified by Nigeria. While the reservoir would serve secondary functions of energy production; employment opportunities, aside other social aspects. These measures are therefore expected to mitigate feasibly the negative impacts anticipated from the stressors and the approach can be employed in other river basins in Africa confronted with similar challenges.

Analysis of Water Balance Changes and Parameterization Reflecting Soil Characteristics in a Hydrological Simulation Program—FORTRAN Model

Efficient water resource management requires accurate analyses of hydrological components and water balance. The Hydrological Simulation Program—FORTRAN (HSPF) model serves this purpose at the watershed scale. It has limited accuracy in calculating runoff and infiltration because the model simulates hydrological processes using one representative parameter for each land use in the watershed. Accuracy requires field-scale analysis of hydrological components. We calculated the lower zone storage nominal parameter, which markedly affects runoff in HSPF, from effective moisture content and depth of each soil layer. Analysis of hydrological components suggested re-calculating the parameters reflecting soil characteristics. We investigated two scenarios through simulations: Scenario 1 used the existing method. Scenario 2 used parameters that reflected soil properties. Total flows for each sub-catchment were identical, but proportions of direct and intermediate runoff were larger in Scenario 1. Ratios of baseflow, evapotranspiration, and infiltration were larger in Scenario 2, reflecting soil characteristics. Comparing the baseflow ratio to total flow, Scenario 2 values were similar to observed values. Comparisons of R2 and Nash–Sutcliffe Efficiency (NSE) at the end of the watershed were well matched (R2 and NSE are higher than 0.9) in both scenarios, but proportions of each hydrological component differed. It is important to consider soil characteristics when applying water quantity and quality analyses in an HSPF simulation.

Comparative Water Environment Simulation Study of Two Typical Models with BMPs in a Karst Basin

Carbonate rocks are widely distributed in southwest China, forming a unique karst landscape. The Lijiang River Basin provides a typical example of an area with concentrated karst. Research on the laws of hydrology and water quality migration in the Lijiang River Basin is important for the management of the water resources of Guilin City and similar areas. In this study, we combined three meteorological data with the soil and water assessment tool (SWAT) model and the hydrological simulation program-Fortran (HSPF) model to simulate the hydrological and water quality processes in the Lijiang River Basin separately. We chose the Nash–Sutcliffe efficiency (NSE) coefficient, coefficient of determination (R2), root mean square error-observations standard deviation ratio (RSR), and mean absolute error (MAE) as the metrics used to evaluate the models. The results, combined with the time-series process lines, indicated that the SWAT model provides a more accurate performance than the HSPF model in streamflow, ammonia nitrogen (NH3-N), and dissolved oxygen (DO) simulations. In addition, we divided the karst and non-karst areas, and we analyzed the differences between them in water balance, sediment transport, and pollution load. We further identified the key source areas of pollution load in the Lijiang River Basin, evaluated the pollution reduction effect of best management practices (BMPs) on surface source pollution, and proposed some pollution control countermeasures. Each scenario, especially returning farmland to forest and creating vegetation buffer zones, reduces the NH3-N and DO pollution load.

流域水文模型在面源污染模拟与管控中的应用研究进展

PDF HTML阅读 XML下载 导出引用 引用提醒 流域水文模型在面源污染模拟与管控中的应用研究进展 DOI: 10.5846/stxb202109062508 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划(2021YFD1700600)；国家自然科学基金项目(42007362，51809177) Research of the HSPF model on nonpoint source pollution modeling and management：progresses and perspectives Author: Affiliation: Fund Project: National Key R&D Program of China；National Natural Science Foundation of China 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:面源污染是影响流域水环境和水安全的重要污染来源,对其进行有效防控需要对其负荷以及防控措施效果进行科学高效精准的预测。流域水文模型(Hydrological Simulation Program-FORTRAN,HSPF)具有突出的综合性和灵活性,是面源污染模型的典范。近年来,HSPF模型应用于我国流域面源污染相关的研究和实践有了飞速发展,但同样也面临着模型机理和参数本地化、模型构建精细化、模型结构不确定性较大等方面的挑战。围绕该模型在面源污染模拟与管控中的研究进展,对其在变化环境下的模拟方法和成果,以及应对参数识别、不确定性分析、措施效果评估和总量控制的思路和方法等方面进行了总结,并分析了现代化环境模拟形势下HSPF模型的延伸发展。结合模型相关研究的总结,强调了面向我国流域特色的本地化模型改进、服务河长制精细监管的大尺度精细化模拟、以及模型与大数据统计及人工智能耦合的互馈集合模拟等后续研究是需要重点关注的发展动向。 Abstract:Non-point source (NPS) pollution has become a major threat to watershed environment and security in recent decades. The occurrence and transport of NPS pollution include several dynamic processes which are characterized by randomness, complexity, uncertainty, etc. Existing monitoring network is not sufficient to accurately evaluate the contribution of NPS pollution and understand the underlying mechanisms. Efficient and sound assessment tools are needed to facilitate preventing and controlling NPS pollution. Nowadays many watershed models become increasingly popular to simulate, predict, and analyze NPS pollution processes and assist in decision makings for integrated watershed management. HSPF (Hydrological Simulation Program-FORTRAN) is one of the most comprehensive and flexible NPS models around the world. It has been developed and maintained mainly by the U.S. Environment Protection Agency and is highly recommended in flood-control planning and operations, water quality planning and management, conservation practices evaluation, etc. The HSPF model conceptualizes a watershed system into surface, soil, and stream segments to simulate the continuous, storm event, or steady-state behavior of both hydrologic and water quality processes in natural or manmade water systems. The model has proven its ability to be used with reasonable accuracy in diverse hydrologic regimes, which leads to its broad application worldwide. The research and practice of the HSPF model applied to watersheds in China have expanded rapidly in recent years, but the model is also facing challenges in terms of localization for model theory and parameters, refinement during the model setup process, and uncertainty embedded in the simulated results. Therefore, this paper focused on the research progress of the HSPF model in NPS pollution modeling and control by reviewing existing relative papers. The conceptualization principles of the HSPF model to simulate NPS pollution was first described. This was followed by extensive reviews of the modeling methods and application in changing environment, as well as the ideas and methods for parameter identification, uncertainty analysis, control measures evaluation and total emission control. The extended development of HSPF model under the modern environmental modeling situation was also summarized. PyHSPF and HSP2 as two representatives were specifically discussed in their improvement in compiling environment, data management, dynamic representation of watershed properties, parallel computing, and Application Program Interface. The suggested developments in future studies include: localization model improvement for China's watershed characteristics, large-scale refinement modeling to cope with the fine regulatory services of the river chief system, coupling with big data statistics and artificial intelligence for crossfeed ensemble modeling. 参考文献 相似文献 引证文献

In-stream <i>Escherichia coli</i> modeling using high-temporal-resolution data with deep learning and process-based models

Abstract. Contamination of surface waters with microbiological pollutants is a major concern to public health. Although long-term and high-frequency Escherichia coli (E. coli) monitoring can help prevent diseases from fecal pathogenic microorganisms, such monitoring is time-consuming and expensive. Process-driven models are an alternative means for estimating concentrations of fecal pathogens. However, process-based modeling still has limitations in improving the model accuracy because of the complexity of relationships among hydrological and environmental variables. With the rise of data availability and computation power, the use of data-driven models is increasing. In this study, we simulated fate and transport of E. coli in a 0.6 km2 tropical headwater catchment located in the Lao People's Democratic Republic (Lao PDR) using a deep-learning model and a process-based model. The deep learning model was built using the long short-term memory (LSTM) methodology, whereas the process-based model was constructed using the Hydrological Simulation Program–FORTRAN (HSPF). First, we calibrated both models for surface as well as for subsurface flow. Then, we simulated the E. coli transport with 6 min time steps with both the HSPF and LSTM models. The LSTM provided accurate results for surface and subsurface flow with 0.51 and 0.64 of the Nash–Sutcliffe efficiency (NSE) values, respectively. In contrast, the NSE values yielded by the HSPF were −0.7 and 0.59 for surface and subsurface flow. The simulated E. coli concentrations from LSTM provided the NSE of 0.35, whereas the HSPF gave an unacceptable performance with an NSE value of −3.01 due to the limitations of HSPF in capturing the dynamics of E. coli with land-use change. The simulated E. coli concentration showed the rise and drop patterns corresponding to annual changes in land use. This study showcases the application of deep-learning-based models as an efficient alternative to process-based models for E. coli fate and transport simulation at the catchment scale.

Assessing runoff and pollutant loading upstream of the Miyun Reservoir for sustainable water resources management

AbstractSediment deposition and intensified eutrophication of the Miyun Reservoir are directly affecting the water quality in Beijing, China, owing to water pollution issues in the Chaohe River Basin, which contains the main inflow river of the reservoir. This study analysed the runoff, sediment, total nitrogen and total phosphorus load simulation results from three observation stations using the Hydrological Simulation Program–FORTRAN model (Nash efficiency coefficient [NSE] = 0.65–0.8, R2 = 0.62–0.92) and a statistical regression model (R2 = 0.55–0.79). Results indicate that applying these models in combination to basins from which pollution source data are difficult to obtain can fully utilize the advantages of both models. The parameter uncertainty analysis of the model's runoff and pollution‐related parameters is discussed from the basis of the generalized likelihood uncertainty estimation analysis method. Further, using the Mann–Kendall test and the double cumulative curve method, an attribute analysis of climate change and human activities in the basin was carried out. Results show that in the context of global climate change, fundamental ways to achieve the goal of adaptive catchment management include adjusting the land use structure, optimizing the land use mode and carrying out comprehensive management of soil and water loss with vegetation restoration as the main body.

Comparative Study of Different Types of Hydrological Models Applied to Hydrological Simulation

AbstractThe hydrological model is one of the key methods in hydrological research and management, which can be divided into physical model and mathematical model. In order to explore the applicability of different models in hydrological simulation, the physical model Hydrologic Simulation Program‐FORTRAN (HSPF), the mathematical models Autoregressive Integrated Moving Average (ARIMA) and Back Propagation Neural Network (BPNN) are built to simulate the hydrological process of Sanya River, China. First, the result shows that all three models have good performance, but the HSPF model has the best performance followed by the ARIMA and the BPNN model with the lowest performance. Next, the effect of time step on the performance of the BPNN and ARIMA models is obviously greater than for the HSPF model. Finally, the applicability of various models is discussed by combining the modeling process and data requirements of the model, and the applicability of the mathematical model in the hydrological simulation of watersheds with insufficient data is confirmed.

Impact of BMPs on water quality: a case study in Big Sunflower River watershed, Mississippi

ABSTRACT Impact of Best Management Practices (BMPs) can be evaluated using hydrologic and water quality models. Although numerous models with diverse function, capability and degree of complexity are available, suitable model for each watershed should be determined. The Soil and Water Assessment Tool (SWAT) and Hydrologic Simulation Program-Fortran (HSPF) models were applied to the Big Sunflower River Watershed (BSRW) and their performances in simulating hydrology and water quality were evaluated. Both the models simulated streamflow, sediment, and nutrient concentrations with model efficiency greater than 50%. The SWAT model simulated streamflow and sediment concentration more accurately than HSPF whereas, for total nitrogen (TN) and total phosphorous (TP) concentrations, the HSPF model simulated equally good as SWAT. Models evaluated effect of two BMPs: vegetative filter strip (VFS) and tailwater recovery pond (TRP) in reduction of streamflow, sediment, TN, and TP concentrations. Average reduction of streamflow due to the implementation of both BMPs in SWAT and HSPF were less than 1% but average reduction of sediment concentration by VFS in SWAT was 26% and in HSPF was 38%. Average reduction of sediment concentration by TRP in SWAT and HSPF were 21% and 30% respectively. VFS reduced TN concentration by 51% in SWAT and by 25% in HSPF, while average reduction of TN concentration by TRP in SWAT and HSPF were 7% and 2% respectively. Similarly, average reduction of TP concentration by VFS in SWAT and HSPF were 56% and 31% respectively and that by TRP in SWAT and HSPF were 2% and 1% respectively. Differences in simulation results based on application of two models were mainly attributed by the modelling mechanism and equations used. The results from this study will provide a broader idea to other modellers and end-users in selecting appropriate model according to their need and type of watershed.

Simulation effects of clean water corridor technology on the control of non-point source pollution in the Paihe River basin, Chaohu lake.

At present, water pollution is still a serious problem in some parts of China. Clean water corridor technology (which provides water quality assurance and pollution load reduction from the Major Science and Technology Program for Water Pollution Control and Treatment) is a river pollution control and treatment measure. However, due to the differences of specific river conditions, it is not initially clear which technology can be used to obtain the best effect. Numerical simulation can address this issue. The results can be used as the basis for selecting clean water corridor technology. Combined with remote sensing (RS) and geographic information system (GIS) technology, the relationship between land use and non-point source pollution load was analyzed by using the HSPF (Hydrological Simulation Program-Fortran) model. According to the distribution of pollution load, the effect of the clear water corridor technology and its combination scenario on the reduction of non-point source pollution in the basin was simulated, and the best clear water corridor technology scheme for the control of non-point source pollution was identified. Research results show that from 2015 to 2018, the non-point source pollution load of total nitrogen in the Paihe River basin showed an overall increasing trend, while the total phosphorus showed a slightly increasing trend. Agricultural land and construction land accounted for 70% and 20%, respectively, of the non-point source pollution load, and the change in land use played an important role in the load of non-point source pollution. In terms of spatial distribution, the non-point source pollution of total nitrogen and total phosphorus was mainly concentrated in the downstream region and the central region. The non-point source pollution load reduction rates of total nitrogen and total phosphorus by the three types of clean water corridor technologies of vegetation buffer zones, permeable sidewalks and constructed wetlands, and their combinations were 15.29% and 15.03%, 11.93% and 11.48%, 8.96% and 8.67%, and 24.12% and 23.20%, respectively. It is necessary to comprehensively adopt clean water corridor technology for an optimal allocation and reasonable layout and to increase the pollution load reduction rate to further achieve ecological environment restoration goals.

Investigating the Error Propagation from Satellite-Based Input Precipitation to Output Water Quality Indicators Simulated by a Hydrologic Model

This study investigated the propagation of errors in input satellite-based precipitation products (SPPs) on streamflow and water quality indicators simulated by a hydrological model in the Occoquan Watershed, located in the suburban Washington, D.C. area. A dense rain gauge network was used as reference to evaluate three SPPs which are based on different retrieval algorithms. A Hydrologic Simulation Program-FORTRAN (HSPF) hydrology and water quality model was forced with the three SPPs to simulate output of streamflow (Q), total suspended solids (TSS), stream temperature (TW), and dissolved oxygen (DO). Results indicate that the HSPF model may have a dampening effect on the precipitation-to-streamflow error. The bias error propagation of all three SPPs showed a positive dependency on basin scale for streamflow and TSS, but not for TW and DO. On a seasonal basis, bias error propagation varied by product, with larger values generally found in fall and winter. This study demonstrated that the spatiotemporal variability of SPPs, along with their algorithms to estimate precipitation, have an influence on water quality simulations in a hydrologic model.

Response of Non-point Source Pollution Loads to Land Use Change under Different Precipitation Scenarios from a Future Perspective

To optimize the management of non-point source (NPS) pollution in a changing environment, the cellular automata (CA) and Hydrological Simulation Program-Fortran (HSPF) models were used to study the response mechanism of NPS pollution loads to land use change and different precipitation scenarios. Taking the Dongjiang River Basin as a case study, the land use situation and its spatial distribution patterns in 2020, 2030 and 2050 were predicted by the logistic regression-based CA model. The trends of the NPS pollution loads under different land use and precipitation scenarios were quantitatively evaluated. The results show that the total accuracy of the land use change simulated by the CA model was 81%. Both the HSPF model and the CA model were highly applicable to this basin. Precipitation is proven to be the main driving force of NPS pollution. From 2020 to 2050, the annual load, average monthly load, maximum and minimum monthly load of the BOD and TP show an upward trend. TN shows a slight downward trend, which is related to the reduction in cultivated land area and the use of nitrogen fertilizer. In view of the future trend of NPS pollution, the basin should continue to control TN pollution and focus on strengthening BOD and TP control to achieve high-quality management of the water environment.

Does Future Climate Bring Greater Streamflow Simulated by the HSPF Model to South Korea?

Evaluating the impact of climate change on water resources is necessary for improving water resource management and adaptation measures at the watershed level. This study evaluates the impact of climate change on streamflow in South Korea using downscaled climate change information based on the global climate model (GCM) and hydrological simulation program–FORTRAN model. Representative concentration pathway (RCP) scenarios 4.5 and 8.5 W/m2 were employed in this study. During the distant future (2071–2099), the flow increased by 15.11% and 24.40% for RCP scenarios 4.5 and 8.5 W/m2, respectively. The flow is highly dependent on precipitation and evapotranspiration. Both precipitation and evapotranspiration increased, but the relative change of precipitation was greater than the relative change of evapotranspiration. For this reason, the flow would show a significant increase. Additionally, for RCP 8.5 W/m2, the variability of the flow according to the GCM also increased because the variability of precipitation increased. Moreover, for RCP 8.5 W/m2, the summer and autumn flow increased significantly, and the winter flow decreased in both scenarios. The variability in autumn and winter was so great that the occurrence of extreme flow could intensify further. These projections indicated the possibility of future flooding and drought in summer and winter. Regionally, the flow was expected to show a significant increase in the southeastern region. The findings presented for South Korea could be used as primary data in establishing national climate change adaptation measures.

Differences in the responses of flow and nutrient load to isolated and coupled future climate and land use changes

Understanding the differences in the responses of river hydrology and water quality to climate and land use changes is particularly crucial for the development and management of water resources in the future. This study was carried out to assess the isolated and coupled effects of future climate change and land use change on the flow and nutrient load of the Xitiaoxi watershed in southeast China by applying the calibrated Hydrological Simulation Program Fortran model. Four representative concentration pathways released by the Intergovernmental Panel on Climate Change and two projected land use change scenarios were used to simulate future conditions. The results indicate that climate change would result in flow increased with an average variation of 25.2% in the future, and the increased flow would be mainly concentrated on the high flow part of the total flow duration curve. Climate change would also induce seasonal shifts to nutrient load. The effects of land use change showed that nutrient load was more sensitive than flow, made Orthophosphate load increase by 2.8%–154.7%, and flow increase by 7.2%–15.1%. The results for coupled climate and land use changes indicate that flow and nutrient load would be more affected by climate change than by land use change. Climate and land use changes may amplify or weaken each other's effects on flow and nutrient load, which suggests that both should be incorporated into hydrologic models when studying the future conditions. The results of this study can help decision-makers guide management practices that aim to minimize flow and nutrient load.

Automatic calibration and improvements on an instream chlorophyll a simulation in the HSPF model

Accurate prediction of chlorophyll a (Chl a) concentration in surface water bodies such as lakes or rivers is crucial for water quality management. This study improved the predictive simulation of instream Chl a with the Hydrological Simulation Program-FORTRAN (HSPF) by adding automatic calibration and modifying the growth-temperature formulation of phytoplankton in the original HSPF model. A total of 62 model parameters, selected from a series of sensitivity analyses, were automatically calibrated in a stepwise manner for different variables in the order of flow, sediment, water temperature, ammonia/nitrate couple, and phosphate/Chl a couple. With finer temporal resolution (5–8 days) data than those of majority of the existing HSPF studies, the automatic calibration procedure provided the model with performance ratings of ‘satisfactory’ or better for all the variables including nutrients and Chl a: The percent bias values ranged from -18% - 54% and -20% – 62% for nutrients and Chl a, respectively. The original linear equation on the growth-temperature relationship of phytoplankton in simulating instream Chl a was modified using a quadratic equation and an exponential equation. The exponential equation outperformed the original linear and quadratic equations, particularly in simulating the excess concentrations of Chl a observed during summer seasons. For the validation data set, the exponential equation predicted 78% of the eutrophic cases while the linear and quadratic equation only predicted 53% and 13% of the eutrophic cases, respectively. The modified HSPF model offers an improved prediction of instream Chl a. This approach will be useful for providing early warning of algal blooms, facilitating the implementation of effective management of stream water quality.

Ensemble streamflow projections for a small watershed with HSPF model.

A watershed modeling tool, Hydrological Simulation Program-FORTRAN (HSPF), was utilized to model the hydrological processes in the agricultural Sarısu watershed in western Turkey. The meteorological input data were statistically downscaled time series from General Circulation Model simulations. The input data were constructed as an ensemble of 400 individual time series of temperature, precipitation, dewpoint temperature, solar radiation, potential evapotranspiration, cloudiness, and wind velocity, as required by HSPF. The ensemble was divided into four subsets, each comprising of 100 time series, of different Special Report on Emissions Scenarios. Yearly and monthly total streamflow time series were obtained from the calibrated and validated HSPF model spanning a period of 116 years between the water years of 1984 and 2099. The projections in the watershed showed a median increase of 3 °C in yearly average temperatures between the beginning and end 30-year periods of the 116-year simulation periods based on 400 ensemble members while the corresponding change in total yearly precipitation was - 71 mm. These changes led to a decrease in yearly streamflows by 40% which reflected itself to varying degrees in monthly flows. Correlations were established between the principal drivers of the watershed hydrological cycle, namely temperature and precipitation, and streamflow. The results showed that the changes in the climatic conditions will greatly affect water-related issues in the watershed and emphasize the necessity of preparing carefully to adapt to a warmer and drier climate.

Estimating impact of forest land on groundwater recharge in a humid subtropical watershed of the Lower Mississippi River Alluvial Valley

Study regionLower Mississippi River Alluvial Valley (LMRAV) is located in the humid subtropical region of mid-south USA, and Lower Yazoo River Watershed (LYRW) in Mississippi is within the LMRAV. Study focusGroundwater depletion due to anthropogenic activities is an issue of water resource concern in the LMRAV. Some studies suggested that forest lands reduce water recharge from land surface into aquifers as compared to agricultural lands. However, very few efforts have been devoted to investigating the relationship of water recharge and land use in the LMRAV. This study was designed to meet this need. New hydrological insights for the regionUsing the HSPF (Hydrological Simulation Program-FORTRAN) model along with the LYRW, we found that the annual average water recharge from the land surface into the deep aquifer over the 10-year simulation period for the three land uses was: agriculture < forest < wetland. Only 1.1, 1.2, and 1.4% of the precipitation water from the agriculture, forest, and wetland, respectively, recharged into the deep aquifer in the LYRW. Results demonstrated that forest land slightly increased rather than reduced water recharge from the land surface into the groundwater as compared to that of the agricultural land. These finding could change the traditional scientific view on how forests affect water recharge into groundwater in the humid subtropical region around the world.

Hydrological Simulation of Taizi River Basin with HSPF Model

With the development of economy and the increase of population, water resources are becoming more and more scarce. The total amount of water resources in the Taizi River Basin of Liaoning Province, China is 5.120 billion m3, and the per capita water resources amount is 845 m3. According to the United Nations standards, it is classified as a water shortage area.In order to better manage and protect water resources, this paper uses Hydrological Simulation Program-Fortran (HSPF) model to simulate runoff in the Taizi River Basin. The Parameter Estimation (PEST) procedure was used to calibrate the hydrological parameters. The results showed that the Nash-Sutcliffe efficiency (NSE) of the calibration period (2009-2011) was 0.78, the correlation coefficient (R2) was 0.89; the Nash-Sutcliffe efficiency of the validation period (2012-2013) was 0.68, and the correlation coefficient was 0.85. It indicates that the HSPF hydrological model has good applicability in the Taizi River basin which will provide useful reference for future modeling research.

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.