Ensemble streamflow projections for a small watershed with HSPF model

Albek, Mine; Albek, Erdem; Göncü, Serdar; Uygun, Burcu Şimşek

doi:10.1007/s11356-019-06749-9

Cited by 10 publications

(5 citation statements)

References 34 publications

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“…Tsai et al (2017) also applied the HSPF to the Feitsui Reservoir and obtained satisfactory results. Albek et al (2019) used the HSPF to assess the inflow impacts in the Sarısu catchment under climate change scenarios. The application of the HSPF in China (e.g., Li et al, 2017) and the USA (e.g., Ouyang et al, 2015) has also been reported.…”

Section: Methodsmentioning

confidence: 99%

A combined catchment‐reservoir water quality model to guide catchment management for reservoir water quality control

Chen

Chong

Lin

2021

Water & Environment J

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In this study, the Hydrological Simulation Programme‐FORTRAN (HSPF) and the Water Quality Analysis Simulation Programme (WASP), were adopted as a combined tool. The long Feitsui impounding reservoir located in Taiwan was used as a case study. The combined model helped illustrate the total phosphorus (TP) mass balance. Approximately 51.4% of the TP flowed out from the reservoir, while 16.2% of the TP remained in the waterbody and 32.2% of the TP was deposited. The reservoir was divided into five sections along its length for a quality analysis. The exceedance probability (the probability of exceeding the eutrophic level, i.e., TP = 24 μg/L) was 9.7% in the upstream section. If the TP load increased by 20%, the eutrophication exceedance probability could increase to 25.5%. This study demonstrated the usage of the combined model tool and the exceedance probability method in the data analysis, which could guide effective catchment management and eutrophication risk prevention.

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Section: Methodsmentioning

confidence: 99%

A combined catchment‐reservoir water quality model to guide catchment management for reservoir water quality control

Chen

Chong

Lin

2021

Water & Environment J

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“…The watershed model was HSPF, which was developed by the U.S. Environmental Protection Agency (US EPA) to simulate various complex phenomena associated with water hydraulics and water quality occurring over an extended period of time in a watershed. It consists of the three major application modules to simulate hydrological phenomena and water quality within the pervious layer (PERLND), impervious layer (IMPLND), and river (RCHRES) [23].…”

Section: Model Selectionmentioning

confidence: 99%

Evaluation of Water Circulation by Modeling: An Example of Nonpoint Source Management in the Yeongsan River Watershed

Lee

Park

et al. 2021

Sustainability

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Owing to urbanization, impervious areas within watersheds have continuously increased, distorting healthy water circulation systems by reducing soil infiltration and base flow; moreover, increases in surface runoff deteriorate water quality by increasing the inflow of nonpoint sources. In this study, we constructed a Hydrological Simulation Program—Fortran (HSPF) watershed model that applies the impervious area and can set medium- and long-term water circulation management goals for watershed sub-areas. The model was tested using a case study from the Yeongsan River watershed, Korea. The results show that impervious land-cover accounts for 18.47% of the upstream reach in which Gwangju City is located; approximately twice the average for the whole watershed. Depending on the impervious area reduction scenario, direct runoff and nonpoint source load could be reduced by up to 56% and 35%, respectively; the water circulation rate could be improved by up to 16%. Selecting management goals requires the consideration of both policy objectives and budget. For urban areas with large impervious cover, the designation of nonpoint source management areas is required. For new cities, it is necessary to introduce water circulation systems (e.g., low impact development techniques) to improve rainwater penetration and recharge and activate preemptive water circulation.

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“…Physically-based models simulate the involved hydrological processes and estimate reservoir inflow 6 – 8 . Physically-based models such as the Soil and Water Assessment Tool (SWAT) 9 , the watershed-scale Long-Term Hydrologic Impact Assessment model (watershed-scale L-THIA) 10 and the Hydrological Simulation Program—Fortran (HSPF) 11 are used to simulate water cycle components 12 . Physically-based models can be applied to simulate flood events accounting for the key hydrologic processes involved.…”

Section: Introductionmentioning

confidence: 99%

Machine-learning algorithms for forecast-informed reservoir operation (FIRO) to reduce flood damages

Zarei

Bozorg‐Haddad

Baghban

et al. 2021

Sci Rep

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Water is stored in reservoirs for various purposes, including regular distribution, flood control, hydropower generation, and meeting the environmental demands of downstream habitats and ecosystems. However, these objectives are often in conflict with each other and make the operation of reservoirs a complex task, particularly during flood periods. An accurate forecast of reservoir inflows is required to evaluate water releases from a reservoir seeking to provide safe space for capturing high flows without having to resort to hazardous and damaging releases. This study aims to improve the informed decisions for reservoirs management and water prerelease before a flood occurs by means of a method for forecasting reservoirs inflow. The forecasting method applies 1- and 2-month time-lag patterns with several Machine Learning (ML) algorithms, namely Support Vector Machine (SVM), Artificial Neural Network (ANN), Regression Tree (RT), and Genetic Programming (GP). The proposed method is applied to evaluate the performance of the algorithms in forecasting inflows into the Dez, Karkheh, and Gotvand reservoirs located in Iran during the flood of 2019. Results show that RT, with an average error of 0.43% in forecasting the largest reservoirs inflows in 2019, is superior to the other algorithms, with the Dez and Karkheh reservoir inflows forecasts obtained with the 2-month time-lag pattern, and the Gotvand reservoir inflow forecasts obtained with the 1-month time-lag pattern featuring the best forecasting accuracy. The proposed method exhibits accurate inflow forecasting using SVM and RT. The development of accurate flood-forecasting capability is valuable to reservoir operators and decision-makers who must deal with streamflow forecasts in their quest to reduce flood damages.

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Ensemble streamflow projections for a small watershed with HSPF model

Cited by 10 publications

References 34 publications

A combined catchment‐reservoir water quality model to guide catchment management for reservoir water quality control

A combined catchment‐reservoir water quality model to guide catchment management for reservoir water quality control

Evaluation of Water Circulation by Modeling: An Example of Nonpoint Source Management in the Yeongsan River Watershed

Machine-learning algorithms for forecast-informed reservoir operation (FIRO) to reduce flood damages

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