Assessing and Optimizing Ecological Flow Rates for the Habitat of Zacco platypus in the Tan River

Abstract

As rivers face growing environmental challenges due to climate change and the construction of artificial structures, it is essential that we improve river ecosystems to maintain their ecological functions and preserve the health of aquatic habitats. The aim of this study was to assess the aquatic ecosystem health of the lower reaches of the Tan River. We employed the Physical Habitat Simulation System and Hydrologic Engineering Center’s River Analysis System to calculate the ecological flow rate based on the weighted usable area (WUA) of Zacco platypus, which is a representative fish species in the Tan River, and the flow rate relationship curves. By analyzing the flow rates in the Tan River across different seasons from 2012 to 2021, we determined that the seasonal optimal ecological flow rate was 10.21–10.27 m³/s. Meanwhile, the WUAs for spring, summer, and autumn and winter were 90–100%, 95–100%, and 75–100%, respectively. Despite meeting the ecological flow criteria for summer, fall, and winter over 50% of the time, spring fell short at 41%; hence, the Tan River flow rates should be secured particularly in spring. This study highlights the urgency of addressing seasonal variations to ensure the overall health of the Tan River ecosystem.

1. Introduction

Humans use water for domestic, industrial, agricultural, and developmental purposes; rivers play an essential role in making water resources readily accessible for their easier utilization. Owing to rapid urbanization and industrialization, numerous dams, weirs, and reservoirs have been constructed along the rivers in Korea for drainage and flood control. Although these artificial structures have increased the usability of the rivers, these have also altered the water quality and geomorphology of the rivers. Consequently, erosion and changes in hydraulic phenomena and sedimentation patterns have affected the physical characteristics (e.g., flow velocity, bed structure, water depth, and discharge) and surrounding vegetation of the rivers [1]. The threats posed by man-made structures to the water quality and flow in rivers have raised social concerns regarding river environments.

At present, rivers are primarily managed for dimensions and discharge to ensure an adequate water supply for agricultural, industrial, and domestic purposes. However, there has been a growing interest in the ecological functions of rivers aside from their economic value. The ecological functions of rivers play a crucial role in maintaining environmental health by preserving the habitat conditions for the organisms inhabiting them. The vegetation in rivers not only provides food for lower-trophic consumers but also contributes to river purification as primary producers in the food chain; meanwhile, higher-trophic consumers such as fish are economically important food resources for rural communities [2]. Eco-friendly river projects and management have significantly been strengthened in Korea since the revision of the River Act in 2007; currently, most river-related initiatives require the incorporation of eco-friendly elements. Vegetation on riverbanks and floodplains serves as an eco-friendly factor that contributes to optimizing river utilization, improving river landscapes, enhancing water quality, and preserving the habitats of aquatic organisms.

Since the 1970s, river restoration efforts have been initiated globally to improve river environments. In Korea, the concept of “instream flow” was first introduced in the 1960s; in the mid-1990s, the guidelines for calculating the instream flow were established, leading to the introduction of “environmental flow” in the River Act [3]. River environmental flow refers to the minimum amount of water necessary to maintain the normal functions and conditions of a river, considering its domestic, industrial, agricultural, environmental, economic, and navigational uses [4]. The concept of “ecological flow”, which goes beyond securing water for human use and landscape purposes but also considers the ecological health of river ecosystems as well as the needs of river-inhabiting organisms, was officially introduced in the revised “Act on the Conservation of Water Quality and Aquatic Ecosystems” in 2017.

The organisms belonging to river ecosystems serve as indicators of river changes caused by physical and chemical environmental factors, such as water flow and quality [5,6,7,8]. Compared with other organisms, fish species are commonly used as indicators of river ecosystem conservation because they are relatively accessible to humans [1], are mobile, have long lifespans, and can inhabit various habitats. Furthermore, apex predators in aquatic ecosystems comprehensively reflect changes in lower ecosystems and their environmental impacts. Unlike other wildlife species, fish have a limited habitat range; thus, changes in water flow, which alters the area of their habitats, directly impact their survival. Therefore, the physical characteristics of rivers, such as water velocity, depth, and substrate material, significantly influence fish populations and habitats—both directly and indirectly [9].

Assessing the optimal or minimum flow required to preserve ecosystem functions is typically performed using habitat-based models that define the relationship between river flows and the availability of fish habitats; the Physical Habitat Simulation System (PHABSIM) is the most commonly used habitat-based model for assessing the optimal ecological flow. Such an approach established a connection between flow regimes and fish habitats, aiding in the conservation of ecological functions. Environmental flow assessments using PHABSIM have been conducted in South Korea since the 1990s; in 1995, K-Water was the first organization to introduce the concept of river ecosystems to instream flow calculations. It determines the flow required to provide and sustain habitats for freshwater fish species and to facilitate their movement [10]. In addition, a flow increment methodology was employed using a physical habitat modeling system that considered the limitations of riffle sections in evaluating fish habitat conditions [11]. In ref. [11], a process for determining optimal flows based on habitat requirements specific to different life stages of fish was established. Subsequently, refs. [12] and [13] established the criteria for habitat suitability for Zacco platypus, a representative fish species in the Nakdong River basin and the Han River watershed; they calculated flow rates suitable for fish habitats and applied the Instream Flow Incremental Methodology (IFIM), one of the fish habitat environmental assessment methods. Ref. [14] used the PHABSIM to determine the Habitat Suitability Index (HSI) for fish habitats in the Geum River basin, whereas ref. [15] calculated the ecological flow for Z. platypus using probability density functions.

Since the 1970s, research on ecological habitat interpretation and environmental flow estimation for river habitat conservation has been conducted internationally. Currently, the PHABSIM, which is a one-dimensional model developed by the United States Geological Survey, and River2D, which is a two-dimensional model developed by the University of Alberta in Canada, are the most prominent among the commonly used physical habitat models worldwide [16,17,18,19,20]. Using the PHABSIM, ref. [21] confirmed that the release of water from an upstream dam significantly shortens the favorable periods for fish habitat suitability. Additionally, ref. [22] conducted a study using the PHABSIM to examine changes in the habitat of Oncorhynchus masou under hydropower release conditions, affirming that flow fluctuations caused by hydropower releases adversely affect the physical habitats of fish. Ref. [23] analyzed the physical habitat of Cyprinus carpio in the Yangtze River using a one-dimensional unsteady flow model and HSI; meanwhile, ref. [24] proposed a minimum instream flow to minimize its impact on fish habitats. Although ecological flow analyses based on the physical habitats of fish, including domestic rivers, have been conducted worldwide, research on the influence of seasonal variation in river discharge is scarce.

Hence, the aim of this study was to determine the seasonal ecological flow ranges for the Tan River, which is a vulnerable point for aquatic ecosystem health, by calculating the weighted usable area of a representative fish species downstream of the Tan River based on seasonal discharge variation. The findings of this study provide guidelines for river restoration or ecological flow maintenance to support the aquatic ecosystem health in the Tan River region.

2. Materials and Methods

2.1. Study Area

This study was conducted in the Tan River, a first-order tributary of the Han River in South Korea (Figure 1); it is a national river classified as a local Class 2 river. It has a length of 35.4 km and exhibits a rectangular shape, extending predominantly in a north–south direction. Its watershed area is 302.4 km², and the average width of the watershed is approximately 10 km from east to west and 15–17 km from north to south. The upstream region of the Tan River is characterized mostly by arable land (47%), whereas the downstream areas are predominantly developed for residential and commercial establishments ref. [25]. The annual average precipitation in the Tan River watershed from 2012 to 2021 was 1184 mm, which was lower than the nationwide average of 1306.3 mm. Sedimentary components in the riverbed such as silt were almost absent, and the prevalence of gravel and neutral sand was high.

Although South Korea has been assessing aquatic ecosystem health since 2008, it has only begun using a biological monitoring network since 2016. As mandated by Article 9-3 of the Water Environment Conservation Act (Survey and Health Assessment of Aquatic Ecosystem Status), aquatic ecosystem health is evaluated by conducting one to two surveys annually, following the Biomonitoring Survey and Assessment Manual (Science Notice No. 2017-439) guidelines. Health assessment involves the examination and evaluation of five aspects: the Fish Assessment Index (FAI), Trophic Diatom Index (TDI), and Benthic Macroinvertebrate Index (BMI) as biological indicators; and the Habitat and Riparian Index (HRI) and Riparian Vegetation Index (RVI) as indices of river environments. Each assessment category involves the derivation of a health index through the analysis of indicators such as species abundance, individual density, and pollution sensitivity. Subsequently, these indices were categorized into five grades: A (very good), B (good), C (fair), D (poor), and E (very poor). For fish health assessment, scores were assigned based on eight criteria that reflect the characteristics of the species in relation to the environment, including the number of species, population density, and sensitive and resistant species. According to the aquatic ecosystem health map constructed from 2016 to 2018, the Tan River exhibited an FAI grade of D at all survey points; hence, it was classified as a river with poor fish health in the Han River basin. Additionally, over 80% of the survey points on the Tan River had HRI scores of D or lower, indicating unfavorable conditions for habitat and riparian environmental health. The results of the 10-year (2012–2021) evaluation of the Daewang Bridge point, which is located downstream of the Tan River, revealed that its TDI, BMI, FAI, and RVI scores ranged from D to E. Notably, the Daewang Bridge point was vulnerable to long-term aquatic ecosystem health issues because more than 50% of its survey points had a grade of E across the following criteria: TDI, BMI, and FAI (

Table 1. Aquatic ecological index evaluation result (2012–2021) for the Daewang Bridge.

Index	Number of Measurements	Rating
		A	B	C	D	E
Trophic Diatom Index (TDI)	20	0	1	3	5	11 (55%)
Benthic Macroinvertebrate Index (BMI)	20	0	0	2	5	13 (65%)
Fish Assessment Index (FAI)	20	0	0	2	6	12 (60%)
Habitat and Riparin Index (HRI)	11	0	0	2	8 (73%)	1
Riparian Vegetation Index (RVI)	7	0	0	4 (57%)	3	0

).

2.2. The Concept of the PHABSIM Model

In this study, the ecological flow was estimated using the PHABSIM model. The PHABSIM is a one-dimensional physical habitat model based on the IFIM [26], which was established by the US Fish and Wildlife Service to conserve aquatic organisms in rivers. As flow gradually increases, the PHABSIM models the corresponding fluctuations in water level and velocity through hydraulic modeling. Subsequently, these dynamics are combined with habitat suitability curves to derive the weighted usable area (WUA)–flow relationship curve. This simulation system was developed by incrementally increasing the flow and modeling the resulting variations in water level and velocity, adhering to the principles outlined in the IFIM [27] (Figure 2). The WUA refers to the available habitat area for the target fish species in a river. Because WUA values allow the observation of changes in the available habitat area for a species in response to variations in flow, the maximum value of WUA, which represents habitat quality and quantity, can be identified as the optimal environmental flow. In the PHABSIM, the WUA for fish is calculated as the product of water occupancy area (A), which is computed through hydraulic modeling, expressed in Equation (1):

$$WUA=\sum _i^n{A}_i\times C_i$$

(1)

where WUA refers to the weighted usable area (m²/1000 m) of a fish species, $A_i$ represents the water area occupied (m²) at the ith cross-section within the river channel, and $C_i$ is the composite component factor for the ith cross-section. The HSI for fish species was utilized to calculate the WUA based on the water depth, flow velocity, and substrate material at each cross-section of the river channel.

2.3. Constructing the PHABSIM Input Data

Operating the PHABSIM model requires the hydraulic and ecological data of the simulated reach, including channel geometry, water level, flow velocity, and fish habitat information. In this study, the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) was established for the Tan River using the data from the Tan River Basic Plan Reports in 2015 for 10 rivers, including the shape information for each cross-section obtained from computer-aided design (CAD) data. The HEC-RAS was employed to model hydraulic and hydrological data, such as water level and flow velocity, for various discharge scenarios. Additionally, the observed data from the Tan River Basic Plan Reports in 2015 and the HSI for fish, which was calculated through field measurements, were used as input data for the PHABSIM. Furthermore, actual measurements from the Daejeon Bridge, which is located near the Daewang Bridge and a vulnerable point for implementing the PHABSIM flow boundary conditions, were used.

2.3.1. Construction of Hydraulic and Hydrological Data Using the HEC-RAS

The ecological flow estimation method using the PHABSIM model requires hydraulic and hydrological data, such as water level and flow velocity, for each river cross-section. Because the PHABSIM model does not exhibit a self-correction feature for the hydraulic analysis module, it relies on externally validated stage-discharge relationships as input data [28]. Therefore, we constructed the input data in this study using the HEC-RAS, a one-dimensional flow analysis program that employs the same hydraulic analysis module as the PHABSIM. Flow velocity and water level data were obtained and calibrated using the actual discharge measurements at the Daejeon Bridge, which was a flow observation point in the HEC-RAS, and then utilized as input data for the PHABSIM.

To simulate river morphology using the HEC-RAS, we initially extracted cross-sectional coordinates (m) and ground elevation (m) data from the Tan River Basic Plan cross-sectional data in CAD format. Subsequently, the extracted data were adjusted to align with the measured elevation values by correcting the cross-sectional coordinates and ground elevations to match the observed altitude values. Using this information, we inputted geometric data for each river cross-section. Additionally, we incorporated terrain data, such as the distances between each section and roughness coefficients, based on the observed values from the Tan River Basic Plan Reports in 2015 for the 10 rivers.

In this study, the observed discharge data at the downstream point 180 m (Daegok Bridge) from Daewang Bridge were utilized for water level and flow velocity simulations using the HEC-RAS. The discharge values were obtained from the daily flow information in the hydrological survey records, and a flow–duration curve for the last 10 years (2012–2020) was plotted to analyze the annual and seasonal flow characteristics. Generally, river flows are defined by various flow magnitudes with corresponding durations based on the number of days in a year; the base flow (Q355) represents the flow that does not fall below the specified value for 355 out of 365 days, whereas the low (Q275), mean (Q185), and high (Q95) flows are defined for 275, 185, and 95 days, respectively.

In this study, flow–duration curve analysis was performed to determine the ecological flow values for each year, specifically Q355, Q275, Q185, and Q95. Of these, Q355, Q275, and Q185 were used as input data for HEC-RAS modeling; Q95 was excluded from the model input data because it reflects the rainfall concentration during specific periods in summer, which was deemed inappropriate for inclusion in the regular ecological flow estimation process. The discharge data used for seasonal ecological flow analysis were calculated using the same flow–duration curve analysis method employed for annual flow analysis by proportionally adjusting the criteria for Q355, Q275, Q185, and Q95 based on the seasonal duration for seasonal flow analysis.

The simulation section for the PHABSIM was selected for the target areas where the riverbed did not change significantly and were minimally affected by artificial structures such as underwater weirs. This section included the locations where assessments of aquatic ecosystem health were conducted. The simulation covered a straight river section that is 445.5 m long; it is approximately 250 m downstream of the Daewang Bridge and approximately 70 m downstream of the Daegok Bridge—a flow measurement point. The data from five river cross-sections at intervals approximately 100–150 m within the simulation section were inputted in the PHABSIM to determine the ecological flow.

2.3.2. Fish HSI

HSI is necessary input data for determining ecological flow because it numerically represents the suitability of the physical habitat for various organisms living in aquatic ecosystems [28]. Therefore, the HSI for a fish species indicates its ability to survive in its habitat. In physical habitat simulation programs, such as the PHABSIM, factors such as flow velocity, water depth, and channel index are reflected in the HSI [29]. Generally, there are three main methods for developing an HSI: expert judgment, field survey analysis, and a method that eliminates convenience by considering the utilization of the habitat environment [15]. As fish of the same species may have different HSIs depending on the water system or river [20], it is desirable to use the HSI data collected from the river being surveyed. Therefore, the HSI values determined through field surveys conducted in 2022 by the Biological Monitoring Center at a vulnerable site near the Daewang Bridge on the Tan River were used in this study.

As most freshwater fishes in Korea can survive at both high and low temperatures, the fish species in most rivers in Korea undergo a wintering period in spring (March–May) before entering the spawning season; fish activity increases in summer (June–August) as water temperature increases. Taking this into account, field surveys were conducted four times between March and June. According to a previous study [30], Z. platypus had the highest relative abundance among the fish species inhabiting the downstream region of the Tan River, which also included Carassius carassius and Rhinogobius brunneus. A field survey was conducted in 2022. Based on its relative abundance, Z. platypus was also identified as a dominant species in the Tan River.

Z. platypus is a fish species belonging to the Cyprinidae family and is commonly found in rivers and reservoirs flowing into the West Sea or South Sea in Korea. It mainly inhabits fast-flowing riffles in the middle and lower reaches of rivers and is classified as a tolerant species because it does not react to water pollution or changes in its environment. According to fish tolerance levels, fish species are classified as tolerant, intermediate, and sensitive [31,32]. Sensitive species are highly responsive to qualitative changes in their habitats and have a broader range of tolerance to environmental stress. Consequently, sensitive species tend to increase in number and distribution in polluted waters [33]. Zacco platypus is characterized by a long (12–17 cm) and flat body, a large head, and a pointed snout. At the Daewang Bridge, the physical habitat conditions for Z. platypus were measured at flow rates and depths of 0.2–0.4 m³/s and 0.3–0.5 m, respectively. The channel index was calculated based on the bed material at the site, which ranged from fine to coarse gravel: silt (<0.062 mm) rated as 1, sand (0.062–2.0 mm) as 2, fine gravel (2.0–16.0 mm) as 3, coarse gravel (16.0–64.0 mm) as 4, and cobble (64.0–256.0 mm) and boulder (>256.0 mm) falling within the 2–3 range on the HSI graph (

Table 2. Characteristics of Zacco platypus and the Habitat Suitability Index (HSI).

Target Fishes	Zacco platypus
Appearance
HSI

).

3. Results and Discussion

3.1. Results of the Tan River Flow Analysis

In this study, flow analysis was conducted using the measured flow values at the flow measurement points to apply the flow boundary conditions in PHABSIM and generate input data for HEC-RAS. Flow analyses were performed annually from 2012 to 2021 and seasonally in spring (March–May), summer (June–August), autumn (September–November), and winter (December–February) (Figure 3).

When comparing the annual values of Q355, Q275, Q185, and Q95 with their respective 10-year average values, Q355, Q275, and Q185 generally showed differences within ±0.5, while Q95 showed a difference within ±1.0. However, the Q185 (9.41 m³/s) and Q95 (12.75 m³/s) in 2012 were higher than those in other years, showing a difference approximately twice as high as the deviations observed from the 10-year average flow values. Particularly, the Q355 (6.321 m³/s), Q275 (7.21 m³/s), Q185 (8.321 m³/s), and Q95 (11.271 m³/s) in 2013 were all higher than their respective 10-year averages, with differences approximately twice higher than those in other years. Therefore, the flow values for the Tan River in 2012 and 2013 were relatively higher than those in other years.

According to the seasonal flow analysis results, the 10-year average seasonal flow values exhibited a small deviation of 0.46 in Q355, indicating minimal seasonal variation. From Q275 onwards, a seasonal difference was observed; there were relatively lower flows in spring and winter and higher flows in summer and autumn. For Q275, Q185, and Q95, the deviations were 0.53, 3.04, and 12.1, respectively.

3.2. Determination of Optimal Ecological Flow

3.2.1. Results of the Ecological Flow Determination for the Last 10 Years

The annual WUA–flow relationship curves determined from the PHABSIM simulations at the Daewang Bridge on the Tan River from 2012 to 2021 are illustrated along with the 10-year average flow analysis results. The optimal ecological flow values for Z. platypus over the last 10 years ranged from 10.1 to 10.5 m³/s; such values are approximately twice as high as the river maintenance flow rate of 5.06 m³/s, according to the Korea Han River Flood Control Office.

The comparison of the optimal ecological flow each year with the annual flow analysis results revealed that the optimal ecological flow for the years with relatively higher flows (2012 and 2013) was between Q185 and Q95. For 2014 until 2021, the optimal ecological flow was approximately 1.94–2.93 m³/s higher than Q95.

3.2.2. Seasonal Ecological Flow Calculation Results

Figure 4 shows the estimated usable area and seasonal ecological flow of Z. platypus. The average optimal ecological flow values for each season were as follows: 10.21 m³/s in spring, 10.27 m³/s in summer, 10.27 m³/s in autumn, and 10.24 m³/s in winter. The average optimal ecological flow values for summer and autumn were the same (10.27 m³/s) and the largest among all seasons. Meanwhile, the average optimal ecological flow values for winter and spring differed.

The optimal seasonal ecological flow values per year ranged from 9.7 to 10.9 m³/s for all seasons; when compared with the 10-year average flow analysis results, this range of values was above Q95 (8.79 m³/s). The comparison of the 10-year average optimal ecological flow for each season with the 10-year average flow analysis results revealed that the optimal seasonal ecological flow values were Q185–Q95 (6.9–10.55 m³/s) in spring (10.21 m³/s), Q275–Q185 (6.79–14.11 m³/s) in summer (10.27 m³/s), Q185–Q95 (8.21–15.07 m³/s) in autumn (10.27 m³/s), and greater than Q95 (8.19 m³/s) in winter (10.24 m³/s). These results confirm the significant seasonal variations in optimal ecological flows and underscore the importance of seasonal considerations in ecological flow management.

3.3. Range of Ecological Flow

3.3.1. Calculation of Ecological Flow Range for the Last 10 Years

The annual WUA and flow rate relationship curves, as determined through the PHABSIM, reflect various factors, such as river cross-sectional shape, flow rate, and velocity. River flow is subject to variability owing to several factors, including precipitation, water transfer, water intake, and discharge from upstream dams. Therefore, to regulate fish flows in rivers, it is necessary to select not only a specific flow value, such as the optimal ecological flow, but also a practical range of usable flow rates.

Consequently, as the shape of the river cross-section changed, the shape of the WUA–flow rate relationship curve also changed. In this study, to normalize this irregularity and identify the intersections between the annual WUA–flow rate relationship curves, we calculated the values at 95% down to 5% WUA based on the maximum WUA (100% WUA). These values were inputted in the regression formulae shown in

Table 3. Environmental ecological flow rates by WUA% of Zacco platypus (2012–2021).

Unit: m3/s
Year	WUA PERCENT (%)
	100	95	90	85	80	75	70	65	60	55	50	45	40	35	30	25	20	15	10	5
2012	10.4	8.09	7.15	6.58	6.13	5.75	5.40	5.08	4.77	4.48	4.19	3.91	3.62	3.33	3.04	2.73	2.41	2.05	1.64	1.13
2013	10.5	8.34	7.27	6.68	6.22	5.84	5.49	5.17	4.87	4.58	4.29	4.01	3.73	3.45	3.16	2.86	2.53	2.18	1.77	1.26
2014	10.4	8.31	7.36	6.81	6.38	6.01	5.68	5.38	5.09	4.82	4.55	4.28	4.02	3.75	3.48	3.20	2.91	2.59	2.23	1.79
2015	10.4	7.95	7.13	6.63	6.23	5.89	5.58	5.29	5.01	4.74	4.48	4.21	3.94	3.67	3.38	3.08	2.75	2.38	1.94	1.33
2016	10.1	7.91	7.04	6.55	6.17	5.84	5.54	5.26	4.99	4.72	4.46	4.19	3.92	3.63	3.33	2.99	2.61	2.15	1.53	0.73
2017	10.2	7.79	6.95	6.46	6.07	5.73	5.42	5.14	4.86	4.59	4.33	4.06	3.79	3.51	3.22	2.90	2.55	2.15	1.66	0.99
2018	10.1	8.31	7.31	6.79	6.39	6.05	5.74	5.46	5.20	4.94	4.69	4.44	4.19	3.93	3.67	3.39	3.10	2.78	2.40	1.92
2019	10.2	8.09	7.21	6.69	6.27	5.92	5.59	5.30	5.01	4.74	4.47	4.21	3.94	3.67	3.40	3.11	2.80	2.46	2.06	1.56
2020	10.2	8.01	7.12	6.62	6.23	5.90	5.60	5.31	5.04	4.78	4.51	4.25	3.98	3.70	3.41	3.09	2.73	2.32	1.78	0.99
2021	10.3	8.16	7.17	6.64	6.24	5.89	5.57	5.28	4.99	4.72	4.45	4.19	3.92	3.64	3.35	3.04	2.70	2.32	1.85	1.21
Avg.	10.3	8.10	7.17	6.64	6.23	5.88	5.56	5.27	4.98	4.71	4.44	4.17	3.91	3.63	3.34	3.04	2.71	2.34	1.89	1.29
SD	0.13	0.18	0.12	0.10	0.09	0.10	0.10	0.11	0.12	0.12	0.13	0.14	0.15	0.16	0.17	0.18	0.19	0.21	0.26	0.35

to determine the flow rates corresponding to each WUA%. The coefficient of determination (R²) was used to assess the applicability of the regression formula; R² = 1.0 indicated a perfect match between the observed and simulated values. In this study, all the regression formulae for Z. platypus had a coefficient of determination of R² = 0.998 or higher. From the selected flow rates, the flow rate up to 100% WUA was identified as the appropriate ecological flow range for the Z. platypus habitat in the Tan River. The ecological flow range for the Z. platypus habitat in the annual ecological flow curves was approximately 6.23–10.28 m³/s, falling within an average WUA of 80–100%

3.3.2. Seasonal Ecological Flow Range Estimation Results

Similar to the previously calculated 10-year ecological flow ranges, regression analysis was performed to determine seasonal ecological flow ranges and select flow rates corresponding to each WUA%. The range began from the flow rate with the smallest standard deviation to the flow rate at a WUA of 100% in each season (Tables S1–S4). For the past 10 years (2012–2021), the average seasonal ecological flow ranges were estimated as follows: 7.02–10.21 m³/s, corresponding to 90–100% WUA, for spring; 8.07–10.27 m³/s, within 95–100% WUA, for summer; and 5.67–10.2 m³/s and 5.74–10.24 m³/s for autumn and winter, respectively, each corresponding to 75–100% WUA.

Based on the analysis of the seasonal average flow over the past 10 years, calculated using the PHABSIM model as input data, the seasonal ecological flow ranges for Z. platypus were as follows: 7.02–10.21 m³/s in spring, which fell between the 10-year average Q185 (6.9 m³/s) and Q95 (10.55 m³/s) for spring; 8.07–10.27 m³/s in summer, which was between Q275 (6.79 m³/s) and Q185 (14.11 m³/s); 5.67 m³/s, which was smaller than Q355 (6.42 m³/s), up to 10.2 m³/s, which was between Q185 (8.21 m³/s) and Q95 (15.07 m³/s) in autumn; and 5.74–10.24 m³/s in winter, which started from Q185 (5.72 m³/s) and was above Q95 (8.19 m³/s).

Owing to its climatic characteristics, South Korea experiences higher rainfall during summer. Consequently, the seasonal ecological flow ranges calculated in this study predominantly included the Q355–Q185 range, which is naturally easier to maintain because of the high rainfall in summer and the influence of summer rainfall on autumn (September, October, and November). In contrast, the flow range was generally between Q185 and Q95 in seasons with less rainfall, such as spring and winter. Therefore, securing flow within the ecological flow range for Z. platypus may be less stable in spring and winter than in summer and autumn.

3.3.3. Analysis of Days Meeting Ecological Flow Requirements in the Tan River

In this study, we analyzed the number of days in each season that met the ecological flow requirements in the Tan River and compared the calculated ecological flows with the actual measured flow rates. This analysis was based on the daily measured flow rates (m³/s) in the Tan River over the last 10 years (2012–2021), focusing on days when the flow exceeded the calculated seasonal ecological flow ranges. A comparative analysis was conducted to observe the differences in the number of days required to meet the annual and seasonal ecological flow requirements. Of the 3652 days over the last 10 years, 2322 days (64%) met or exceeded the seasonal ecological flow ranges.

The annual analysis revealed that the number of days meeting the ecological flow range was the highest in 2013 (323 days) and 2020 (321 days), both achieving 88% compliance. Except for 2019, which had the lowest compliance (167 days, 46%), more than 50% of the days met the ecological flow range in all other years.

Seasonal analysis revealed that, over the last 10 years, the number of days meeting the seasonal ecological flow range was 376 (41%) in spring, 505 (55%) in summer, 840 (92%) in autumn, and 601 (67%) in winter. Generally, the number of days meeting the ecological flow range was higher in summer and autumn, which correspond to the rainy season. Notably, over 90% of the days in autumn met the ecological flow range for 8 years out of the 10-year period. In winter, which corresponds to the dry season, more than 50% of the days met the annual ecological flow range from 2012 to 2021. However, spring, which is also a dry season, met the ecological flow requirements on less than half of the days over the 10-year period, with only the spring in 2016 exceeding 70% compliance. Compliance was below 20% in 2014, 2015, 2017, and 2019, indicating a significant decrease in days meeting the ecological flow range compared with other seasons. Therefore, it is necessary to maintain and secure flow rates within the seasonal ecological flow range, especially in spring, to ensure the health of the aquatic ecosystems in the lower reaches of the Tan River (

Table 4. Number of days that met the appropriate environmental ecological flow rate range by season (2012–2021).

Season	Year	Number of Days Satisfied	Total Number of Days
		Appropriate Environmental Ecological Flow Rate Range
Spring	2012	29 (32%)	92
	2013	51 (55%)	92
	2014	14 (15%)	92
	2015	18 (20%)	92
	2016	89 (97%)	92
	2017	8 (9%)	92
	2018	58 (63%)	92
	2019	7 (8%)	92
	2020	52 (57%)	92
	2021	50 (54%)	92
Summer	2012	61 (66%)	92
	2013	91 (99%)	92
	2014	46 (50%)	92
	2015	26 (28%)	92
	2016	34 (37%)	92
	2017	59 (64%)	92
	2018	28 (30%)	92
	2019	29 (32%)	92
	2020	88 (96%)	92
	2021	43 (47%)	92
Fall	2012	91 (100%)	91
	2013	91 (100%)	91
	2014	91 (100%)	91
	2015	90 (99%)	91
	2016	70 (77%)	91
	2017	91 (100%)	91
	2018	89 (98%)	91
	2019	91 (100%)	91
	2020	91 (100%)	91
	2021	45 (49%)	91
Winter	2012	44 (48%)	91
	2013	90 (100%)	90
	2014	44 (49%)	90
	2015	49 (54%)	90
	2016	72 (79%)	91
	2017	36 (40%)	90
	2018	85 (94%)	90
	2019	40 (44%)	90
	2020	90 (100%)	90
	2021	51 (57%)	90
Sum	Spring Sum	376 (41%)	920
	Summer Sum	505 (55%)	920
	Fall Sum	840 (92%)	910
	Winter Sum	601 (67%)	902
	10-Year Total	2322 (64%)	3652

).

4. Conclusions

This study was conducted to assess the health of the aquatic ecosystem at the Daewang Bridge site on the lower reaches of the Tan Stream, which has been identified as a vulnerable point for aquatic ecosystem health. Z. platypus, the dominant fish species in the Tan River, was selected as an indicator of river health. Using the PHABSIM model, we calculated the seasonal ecological flow based on the optimal habitat available to Z. platypus. The intersections between the fish WUA calculated from the last 10 years of flow data and the corresponding yearly and seasonal ecological flow values were identified. The optimal ecological flow rates for the last 10 years (2012–2021) ranged from 10.1 to 10.5 m³/s, with an average seasonal optimal ecological flow of 10.21, 10.27, 10.27, and 10.24 m³/s for spring, summer, autumn, and winter, respectively, indicating that the maximum WUA for Z. platypus did not exhibit significant annual or seasonal variations.

However, the range of seasonal ecological flows calculated using regression formulae from the WUA exhibited seasonal variability: 7.02–10.21 m³/s for spring, 8.07–10.27 m³/s for summer, 5.67–10.2 m³/s for autumn, and 5.74–10.24 m³/s for winter. The lower values within these ranges indicate seasonal fluctuations. The comparison of the measured daily flow rates and seasonal ecological flow ranges over 10 years showed a particular need to maintain the flow within the ecological flow range during spring, the dry season. If the flow could be maintained within the ranges proposed in this study for each season, habitat conditions for the dominant fish species in the Tan River could be improved or preserved.

Although Z. platypus was chosen as a representative species for determining the ecological flow in the Tan River, it has limitations in reflecting the diversity of the fish community because of its tolerance to water pollution and habitat ecosystem changes. Future research should focus on calculating the seasonal ecological flows of other native fish species, especially those sensitive to environmental changes. A more comprehensive approach to ecological flow determination, considering the spawning periods and HSI of various fish species, could aid in the conservation and recovery of fish populations and their diversity in rivers. Nevertheless, the findings of this study provide guidelines for practical seasonal ecological flow ranges, considering the variability in river flow due to factors such as rainfall.