• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.2
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• pp.1-11
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• 2017

The analysis of baseflow contribution is very significant in Korea because most rivers have high variability of streamflow due to the monsoon climate. Recently, the importance of such analysis is being more evident especially in terms of river management because of the changing pattern of rainfall and runoff resulted from climate change. Various baseflow separation methods have been developed to separate baseflow from streamflow. However, it is very difficult to identify which method is the most accurate way due to the lack of measured baseflow data. Moreover, it is inappropriate to analyze the annual baseflow contribution for Korean rivers because rainfall patterns varies significantly with the seasons. Thus, this study compared the baseflow contributions at various time-scales (annual, seasonal and monthly) for the 4 major river basins through BFI (baseflow index) and suggested baseflow contribution of each basin by the BFI ranges searched from different baseflow separation methods (e.g., BFLOW, HYSEP, PART, WHAT). Based on the comparison of baseflow contributions at the three time scales, this study showed that the baseflow contributions from the monthly and seasonal analysis are more reasonable than that from the annual analysis. Furthermore, this study proposes that defining BFI with its range is more proper than a specific value for a watershed, considering the difference of BFIs between various baseflow separation methods.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.75-83
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• 2016

Streamflow is composed of baseflow and direct runoff. However, most of streamflow during dry seasons depends on baseflow. Thus, baseflow analysis is very important to simulate streamflow of dry seasons. Generally, baseflow analysis is conducted using watershed-scale runoff models due to diffilculty of measuring baseflow. However, it is needed to understand and review how the model simulates baseflow because each model uses inherent baseflow analysis techniques. In this study, SWAT, HSPF, PRMS-IV were reviewed focusing on baseflow and soil water. HSPF and PRMS-IV calculate baseflow using the variables which depends on user, so the baseflow analysis results of HSPF and PRMS-IV are not consistent. Moreover, soil structures which were assumed from HSPF and PRMS-IV, since these two models assume soil structure as two soil zones and three conceptual reservoirs, were not enough to describe real soil structure. On the other hand, baseflow in SWAT is calculated using baseflow recession constant which can consider the characteristics of aquifer and also, soil structure in SWAT is similar to real soil structures. Thus, baseflow analysis result from SWAT was concluded as the most suitable and reliable model because SWAT can reflect the characteristics and soil structure which is close to reality.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.101-108
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• 2017

This study attempted to improve the accuracy of streamflow and baseflow prediction of Soil and Water Assessment Tool (SWAT) by applying baselfow recession constants for each sub-watershed. This study set two different scenarios (S1 and S2) to evaluate the impact of application of baseflow recession constants for each sub-watershed on streamflow prediction. In S1, Only the baseflow recession constant obtained from the streamflow station located in the final outlet of study area was applied for whole sub-watersheds. In S2, baseflow recession constants obtained from six different streamflow stations were applied for each sub-watershed. Then, baseflow was separated form the measured streamflow data and the predicted streamflow of S1 and S2 using Web-based Hydrograph Analysis Tool (WHAT). The results showed Nash-Sutcliff efficiency (NSE) and $R^2$ of S2 were a little higher than these of S1 in both streamflow and baseflow prediction results. However, it is important that S2 reflected physical meaning of baseflow recess. Also, recession part of hydrograph in S2 was calibrated better than that of S1 compared to the measured hydrograph.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.373-373
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• 2011

Korean Government has been promoting Four River Restoration Project (i.e., Han, Geum, Nakdong, and Yeongsan rivers) since the second half of 2008. This project is expected to protect against floods and droughts by water resources management. Many researchers have study water resources management, but most studies were focused on direct runoff. However, in order to efficiently protect against floods and droughts, baseflow should be studied as well as direct runoff. Because baseflow has a great effect on streamflow, it needs to be correctly analyzed. For more accurate analysis of baseflow, direct runoff and baseflow from streamflow should be separated first. In this study, 12 flow gauging stations of four major rivers were selected, and flow data from them were obtained (2004-2010) through WAMIS and Web-based SWAT Bflow system (http://www.envsys.co.kr/~swatbflow) which was used to separate direct runoff and baseflow. Baseflow values of Pass 2 in SWAT Bflow system were used. As a result of this study, baseflow contribution was ranged from 23.4% to 68.6% and accounted for about 50% of streamflow. Through this study, it shows that in the case of the flow fluctuation, baseflow is more affected than direct runoff by changes in streamflow in a flood or dry season. Thus, baseflow estimation should not be overlooked for efficient water resources management. However, it has a limitation in this study that because this study used to select randomly 12 flow gauging stations, it did not show a common tendency on each watershed. It is important that flow gauging stations reflected on topographic characteristics of each watershed should be selected in a rigorous manner for further reliable and accurate baseflow estimation on four major rivers.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.149-149
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• 2022

Accurate quantitative evaluation of baseflow contribution to streamflow is imperative to address seasonal drought vulnerability, flood occurrence and groundwater management concerns for efficient and sustainable water resources management in watersheds. Several baseflow separation algorithms using recursive filters, graphical method and tracer or chemical balance have been developed but resulting baseflow outputs always show wide variations, thereby making it hard to determine best separation technique. Therefore, the current global shift towards implementation of artificial intelligence (AI) in water resources is employed to compare the performance of deep learning models with conventional hydrograph separation techniques to quantify baseflow contribution to streamflow of Piney River watershed, Tennessee from 2001-2021. Streamflow values are obtained from the USGS station 03602500 and modeled to generate values of Baseflow Index (BI) using Web-based Hydrograph Analysis (WHAT) model. Annual and seasonal baseflow outputs from the traditional separation techniques are compared with results of Long Short Term Memory (LSTM) and simple Gated Recurrent Unit (GRU) models. The GRU model gave optimal BFI values during the four seasons with average NSE = 0.98, KGE = 0.97, r = 0.89 and future baseflow volumes are predicted. AI offers easier and more accurate approach to groundwater management and surface runoff modeling to create effective water policy frameworks for disaster management.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.580-585
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• 2005

Natural environment of Weolgok-ri watershed has been well preserved as a traditional agricultural watershed. A year record of streamflow, $NO_3-N$, T-N and T-P concentrations data(Apr, 2004-Mar. 2005) was examined to estimate annual and seasonal patterns of pollutnat loads in streamflow and baseflow from the agriculture watershed. To estimate pollutant loads from baseflow, baseflow component from total stream flow was seperated using digital filter method in the Web-based Hydrograph Analysis Tool system. Loads of $NO_3-N$, T-N and T-P from streamflow and baseflow were evaluated to investigate pollutant loads contribution by baseflow. The $NO_3-N$, T-N, and T-P loads from streamflow were 13.85 kg/ha, 45.92 kg/ha and 1.887 kg/ha, respectively. $NO_3-N$, T-N and T-P loads from baseflow were 7.43 kg/ha, 24.70 kg/ha, 0.582 kg/ha, respectively. It was found that $NO_3-N$ and T-N loads were contributed by the baseflow(53% and 53% of Total-loads) than the direct runoff(47% and 47% of Total loads). However, only 30% of total T-P was contributed by the baseflow. It is recommended that one needs to assess pollutant load contribution by the baseflow to identify appropriate control strategies for effective watershed management.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.4
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• pp.235-246
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• 2021

This study investigated the impact of baseflow on fish community in the Ungcheon stream (16.5 km long) located downstream of the Boryeong Dam, Korea. Based on field monitoring, there were five dominant fish species in the Ungcheon Stream accounting for 75% of the total fish community: Zacco platypus, Zacco koreanus, Tridentiger brevispinis, Rhinogobius brunneus, and Pungtungia herzi. These five fish species were selected as target species. HydroGeoSphere (HGS) and River2D models were used for hydrologic and hydraulic simulations, respectively. A habitat suitability index model was used to simulate fish habitat. To assess the impact of baseflow, each representative discharge was examined with or without baseflow. The HGS model was used to calculate baseflow within the study reach. This baseflow was observed to increase gradually with longitudinal distance. Validation of the hydraulic model dem onstrated that computed water surface elevated when baseflow was included, which was in good agreement with measured data, as opposed to the result when baseflow was excluded. Composite suitability index distributions and weighted usable area in the study reach were presented for target species. Simulations indicated that the baseflow significantly increased habitat suitability for the entire fish community. These results demonstrate that there should be a substantial focus on the baseflow for physical habitat simulation.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.1
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• pp.27-38
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• 2016

More severe and frequent flood and drought have increased the attentions on the river management. In particular, baseflow is an important element among many streamflow characteristics because streamflow is mainly consisted of direct runoff and baseflow. In this regard, this study attempted to analyze the relationship between streamflow variability and baseflow contributions on Nakdong river basin. For this, two Streamflow Variability Indices (SVI) were used: Coefficient of Variation (CV) and Coefficient of Flow Regime (CFR). Furthermore, baselow separation was individually conducted by three methods (PART, WHAT and BFLOW), and based on this, Baseflow Index (BFI) was calculated. Also, we used the daily streamflow data retrieved from 27 gauge stations in Nakdong river basin for baseflow separation. The results showed that BFI calculated by three models ranges from 0.14 to 0.90 for 27 gauge stations. For SVI, BFI has much higher correlation with CV than with CFR. Also, the inversely proportional relationship between BFI and CV showed that higher baseflow contribution, less streamflow variability.

• Journal of Korean Society on Water Environment
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• v.31 no.1
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• pp.55-66
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• 2015

It has been well known that it is not easy to quantify pollutant loads driven by non-point source pollution due to various factors affecting generation and transport mechanism of it. Especially pollutant loads through baseflow have been investigated by limited number of researchers. Thus in this study, the Web-based WAPLE (WHAT-Pollutant Load Estimation) system was developed and applied at study watersheds to quantify baseflow contribution of pollutant. In YbB watershed, baseflow contribution with WWTP discharge is responsible for 49.5% of total pollutant loads at the watershed. Among these, pollutant loads through baseflow (excluding any WWTP discharge) is responsible for 61.7% of it. In GbA watershed, it was found that 58.4% is contributed by baseflow with WWTP discharge 2.9% and 97.1% is by baseflow. For NbB watershed (without WWTP discharge), 52.3% of pollutant load is transported through baseflow. As shown in this study, it was found that over 50.0% of TN (Total Nitrogen) pollutant loads are contributed by non-direct runoff. Thus pollutant loads contributed by baseflow and WWTP discharge as well as direct runoff contribution should be quantified to develop and implement watershed-specific Best Management Practices during dry period.

• Journal of Korean Society on Water Environment
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• v.22 no.2
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• pp.244-249
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• 2006

Natural environment of Weolgokri watershed has been well preserved as a traditional agricultural watershed. A year record of streamflow, $NO_3-N$, T-N and T-P concentrations data (April 2004 - Mar. 2005) were examined to estimate annual and seasonal patterns of pollutant loads in streamflow and baseflow from the agricultural watershed. To estimate pollutant loads from baseflow, baseflow component was separated from streamflow using the digital filter method in the Web-based Hydrograph Analysis Tool system and loads of $NO_3-N$, T-N and T-P from streamflow and baseflow were evaluated. The $NO_3-N$, T-N, and T-P loads from streamflow were 13.85 kg/ha, 45.92 kg/ha and 1.887 kg/ha, respectively, while corresponding loads from baseflow were 7.43 kg/ha, 24.70 kg/ha, 0.582 kg/ha, respectively. It was found that $NO_3-N$ and T-N loads were contributed slightly more by the baseflow (53% and 53% of Total-loads) than by the direct runoff (47% and 47% of Total loads). However, only 30% of total T-P load was contributed by the baseflow. It is recommended that one needs to assess pollutant load contribution by the baseflow to identify appropriate pollution control strategies for an effective watershed management.