Water Chemistry, Fish Indicators, and Ecological Health Dynamics in the Korean Lentic/Lotic Waterbodies and the Identification of Key Factors Regulating the Variations of the Ecosystems

국문 초록 (Abstract)

환경 평가와 생태계 보전을 위해서는 수질, 어류 군집 구조 및 생태적온전성에 미치는 주요 결정요인과 영향을 파악하는 것이 필수적이다. 따라서, 본 논문의 주목적은 우리나라 담수 수생태계의 생태학적 구조와 기능을 주도하는 중요한 물리적, 화학적, 생물학적 요인을 규명하는 것이다. 이 목표를 달성하기 위해 우리는 토지 이용 토지 피복(LULC), 인간 교란, 수질, 어류 구성, 생태건강성, 여름 몬순 체제, 고도, 외래종 및 인공구장벽(보) 사이의 일반적인 관계를 조사하였다. 2장에서는 연구 지역의 영양염류, 유기물, 영양 상태 및 화학적 건전성을 결정하는 LULC와 인간의 교란 요인을 분석하였다. 우리는 토지이용 유형과 인간의 교란이 담수 수생태계의 수질에 영향을 미친다는 가설을 세웠다. 다음 장에서는 인공 장벽, 하수 처리장, 환경 요인 및 수질 역학에 따른 종적 구배의 영향을 조사했다. 수질 변화의 크기는 보와 오염원(하수처리장, STP)과 관련이 있었다. 4장에서는 계절에 따른 영양염류 농도와 조류 바이오매스의 사이의 연관성을 명확히 하고, 여름철 장마기간이 유수생태계의 영양염류, 유기물, 부유물질, 조류 엽록소 및 이온 농도에 미치는 영향을 설명하였다. 5장에서는 호소의 영양 상태 파라미터, 수온, 부유물질, 유기물, 이동 등이 고도에 따라 어떻게 변하는지 설명하였다. 저수지의 수질은 인간의 용도에 따라 다양했다. 6장에서 호소의 영양상태는 용도와 관련이 있을것으로 예상되었다. 수질 데이터는 일반적으로 다면적이므로 통계적으로 예방 또는 관리 목적으로 데이터에 접근하고 해석하는 새로운 방법을 개발하는 것이 가장 중요하다. 7장에서는 다변량 통계 기법(MST)을 사용하여 복잡한 데이터를 연구하였다. 조류 엽록소는 식수 수질이 급격히 악화되어 특별한 주의가 요구된다. 8장에서는 Landsat 5 TM 데이터가 저수지에서 조류 엽록소를 감지하는 방법에 대해 고려하였다. 또한 주요 모델 매개변수를 최적화하여 기계 학습 접근법을 사용하여 조류 엽록소를 예측하였다. 토지 이용 유형과 보는 유수 시스템에서 어류 군집 구조에 영향을 미치는 것으로 가정하였다(9장). 외래종 및 정수종의 상대풍부도는 수역에서 크게 증가하였다. 10장에서는 멀티 메트릭 수질 오염 지수 (WPI)와 생태건강성 지수(IBI) 모델을 사용하여 강과 하천의 생태학적 건강성을 진단하였다. 이 장에서는 어류의 내성 및 섭식 길드와 이화학적 수질 간의 상호 작용을 평가하였다. 본 논문의 결과는 우리나라 담수 수생태계를 관리하고 보전하기 위한 기초자료로 유용하게 활용될 것으로 기대된다.

다국어 초록 (Multilingual Abstract)

Identifying the key determinants and their impacts on water quality, fish community structure, and ecological integrity is imperative to environmental assessment and ecosystem conservation. Therefore, the main objective of this dissertation is to determine critical physical, chemical, and biological factors driving ecological structure and function in the Korean freshwater systems. To achieve this objective, we investigated the prevailing relationship between land use land cover (LULC), human disturbance, water quality, fish composition, ecological health, summer monsoon regime, elevation, exotic species, and artificial barriers (weirs). Chapter 2 analyzed LULC and human disturbance factors determining our study area's nutrients, organic matter, trophic state, and chemical integrity. We hypothesized that land use type and human disturbance influence water quality in freshwater systems. The subsequent chapter examined the impact of artificial barriers, sewage treatment plants, environmental factors, and longitudinal gradients on water quality dynamics. The magnitude of water quality variation was related to weirs and point sources of pollution (sewage treatment plants; STPs). In chapter 4, we clarified links between nutrient concentrations and algal biomass based on season and elucidated the influence of summer monsoon on nutrients, organic matters, suspended solids, algal chlorophyll, and ionic concentration in a lotic ecosystem. Chapter 5 described how trophic state parameters, water temperature, suspended solids, organic matter, and ions of reservoirs vary with altitude. The water quality of the reservoirs varied based on human usage. It is expected that the trophic state of the reservoirs is related to their uses in chapter 6. Water quality datasets are typically multifaceted, so it is of the utmost importance to develop a new way to approach and interpret data with preventive or managing purposes statistically. Chapter 7 studied such complex datasets using multivariate statistical techniques (MSTs). Special attention is given to algal chlorophyll due to the rapid deterioration of drinking water quality. Chapter 8 considered how Landsat 5 TM data detect algal chlorophyll in reservoirs. It also predicts the algal chlorophyll using machine learning approaches by optimizing key model parameters. Land use type and weirs are posited to influence fish community structure in lotic systems (chapter 9). The relative abundance of exotic and stagnant fish species increased significantly in the water bodies. In chapter 10, we diagnosed the ecological health of rivers and streams using the multi-metric water pollution index (WPI) and index of biotic integrity (IBI) model. This chapter also evaluated the interactions of fish trophic and tolerance guilds with water chemistry. The outcomes of this dissertation are expected to be beneficial and used as the baseline information for managing and preserving the Korean freshwater systems.

목차 (Table of Contents)

• CONTENTS
• ABSTRACT……………………………………………………………………….I CONTENTS……………………………………………………………………...V
• LIST OF TABLES……………………………………………………………XIII
• LIST OF FIGURES…………………………………………………………...XVI
• Chapter 1: General Introduction……………………………………………...1
• Chapter 2: Land Use Patterns and Human Disturbance Impact on Water Chemistry and Trophic State Dynamics………………………….13
• 2.1 Introduction…………………………………………………………….14
• 2.2 Materials and Methods……………………………………………….17
• 2.2.1 Study area…………………………………………………………17
• 2.2.2 Analysis of water quality parameters, land use cover, trophic state, and water pollution model……………………..18
• 2.2.3 Human disturbance data………………………………………...19
• 2.2.4 Statistical analysis……………………………………………….19
• 2.3 Results…………………………………………………………………..22
• 2.3.1 Water chemistry dynamics and relations with land use patterns……………………………………………………………22
• 2.3.2 Variation of human disturbance value and linked with trophic state index and chemical integrity………………….24
• 2.4 Discussion………………………………………………………………27
• 2.4.1 Impact of land use patterns on water quality……………….27
• 2.4.2 Human disturbance impact on trophic state and chemical
• Integrity................................................................................29
• 2.5 Conclusions……………………………………………………………..30
• 2.6 Summary………………………………………………………………..31
• Chapter 3: Deciphering Major Effects of Artificial Barriers, Sewage Treatment Plants, Environmental Factors and Longitudinal Gradient on Water Quality Dynamics………………………………………………….32
• 3.1 Introduction…………………………………………………………….33
• 3.2 Materials and Methods……………………………………………….36
• 3.2.1 Target watershed………………………………………………..36
• 3.2.2 Measurement of physicochemical, fish, and environmental variables…………………………………………………………...37
• 3.2.3 Statistical analysis……………………………………………….40
• 3.3 Results…………………………………………………………………..41
• 3.3.1 Spatial and temporal variations in water quality: a case study for Geum River watershed……………………………41
• 3.3.2 Spatial and temporal differences in water quality: a case study for Yeongsan River Basin……………………………..46
• 3.3.3 Effects of the weir on the Geum River water quality……..51
• 3.3.4 Impacts of weirs on the Yeongsan water quality dynamics…………………………………………………………53
• 3.3.5 Relationships between environmental factors and water quality variables………………………………………………..55
• 3.4 Discussion………………………………………………………………57
• 3.4.1 Longitudinal and sewage treatment plants impact on water quality……………………………………………………………...57
• 3.4.2 Effect of environmental factors on water quality…………..58
• 3.4.3 Artificial barrier impacts on water quality…………………..58
• 3.5 Conclusions……………………………………………………………..62
• 3.6 Summary………………………………………………………………..63
• Chapter 4: Understanding the Influence of Summer Monsoon on Nutrients, Organic Matter, and Algal Chlorophyll Dynamics in a Lotic System…………………………………………………………………………...64
• 4.1 Introduction…………………………………………………………….65
• 4.2 Materials and Methods……………………………………………….68
• 4.2.1 Sampling sites…………………………………………………….68
• 4.2.2 Water quality parameters………………………………………68
• 4.2.3 Biodegradability index and trophic state classification…..70
• 4.2.4 Calculation of water quality index in Geum River…………70
• 4.2.5 Statistical analysis ………………………………………………72
• 4.3 Results…………………………………………………………………..73
• 4.3.1 Water quality variables dynamics and seasonal variations……………………………………………………….73
• 4.3.2 Biodegradability index and trophic state classification…...75
• 4.3.3 Suspended solids, nutrients, and algal chlorophyll dynamics………………………………………………………..78
• 4.3.4 Water quality index………………………………………………80
• 4.4 Discussion………………………………………………………………82
• 4.4.1 Monsoon effects on water quality…………………………….82
• 4.4.2 Solids, nutrients, and chlorophyll-a dynamics…………….83
• 4.4.3 Water quality index……………………………………………...85
• 4.5 Conclusions……………………………………………………………..86
• 4.6 Summary………………………………………………………………..87
• Chapter 5: Functional Responses of Elevation to Nutrients-Chlorophyll Empirical Models, Water Clarity, and Trophic Conditions in Reservoirs……………………………………………………………………88
• 5.1 Introduction…………………………………………………………….89
• 5.2 Materials and Methods……………………………………………….93
• 5.2.1 Study region………………………………………………………93
• 5.2.2 Data source and analysis of water quality…………………..94
• 5.2.3 Trophic status index deviation………………………………..95
• 5.2.4 Non-algal turbidity……………………………………………...96
• 5.2.5 Statistical analysis……………………………………………….97
• 5.3 Results………………………………………………………………......98
• 5.3.1 Physicochemical characteristics of Korean reservoirs.....98
• 5.3.2 Assessment of nutrients, non-algal turbidity, and algal CHL-a……………………………………………………………100
• 5.3.3 Water clarity, non-algal turbidity, and other variables…103
• 5.3.4 Trophic status index and its deviation……………………...105
• 5.4 Discussion……………………………………………………………..109
• 5.4.1 Reservoirs physicochemical water quality attributes…..109
• 5.4.2 Limiting factors for algal growth…………………………….111
• 5.4.3 Water clarity and non-algal turbidity………………………112
• 5.4.4 Trophic status and its deviation……………………………..114
• 5.5 Conclusions……………………………………………………………119
• 5.6 Summary………………………………………………………………120
• Chapter 6: Elucidating Variations of Nutrients-Chlorophyll Dynamics, TN:TP Ratios and Trophic State in Natural Lakes and Agricultural, Multipurpose, Power Generation, and Estuarine Reservoirs……….122
• 6.1 Introduction…………………………………………………………...123
• 6.2 Materials and Methods……………………………………………...127
• 6.2.1 Description of study area and reservoirs………………….127
• 6.2.2 Analysis of water quality parameters and Trophic state index……………………………………………………………...131
• 6.2.3 Statistical analysis……………………………………………...132
• 6.3 Results…………………………………………………………………133
• 6.3.1 Physicochemical properties of Korean reservoirs………133
• 6.3.2 Variations in the CHL-a:TP and TN:TP ratios…………135
• 6.3.3 Relationship between chlorophyll-a and nutrient dynamics………………………………………………………139
• 6.3.4 Relationships of water transparency and non-algal light attenuation with water quality parameters…………….141
• 6.3.5 Trophic state index and its deviation……………………….144
• 6.4 Discussion……………………………………………………………..148
• 6.4.1 Reservoirs conditions…………………………………………148
• 6.4.2 Variations in algal chlorophyll and nutrients ratios……...149
• 6.4.3 Empirical models……………………………………………….150
• 6.4.4 Evaluations of trophic state index and its deviation…….152
• 6.5 Conclusions……………………………………………………………155
• 6.6 Summary………………………………………………………………156
• Chapter 7: Application of Multivariate Statistical Techniques for the Assessment of Water Quality and Apportionment of Pollution Sources in the Lentic and Lotic Waterbodies……………………………………...157
• 7.1 Introduction…………………………………………………………...158
• 7.2 Materials and Methods……………………………………………...161
• 7.2.1 Study area and water quality data…………………………..161
• 7.2.2 Co-occurrence network analysis…………………………..163
• 7.2.3 Cluster analysis (CA)…………………………………………163
• 7.2.4 Discriminant analysis (DA)…………………………………..164
• 7.2.5 Principal component analysis and factor analysis (PCA/FA)………………………………………………………165
• 7.2.6 Positive matrix factorization (PMF) model……………….166
• 7.3 Results…………………………………………………………………168
• 7.3.1 A case study for the Yeongsan Watershed………………..168
• 7.3.2 A case study for the Paldang Reservoir…………………...186
• 7.4 Discussion…………………………………………………………….195
• 7.4.1 Spatial and temporal variations of Yeongsan River……..195
• 7.4.2 Identification of potential pollution sources in Yeongsan River………………………………………………………………196
• 7.4.3 Source apportionment using the PMF model……………..198
• 7.4.4 Water quality variations of Paldang Reservoir…………...199
• 7.4.5 Spatial-temporal variations and Pollution sources of Paldang Reservoir…………………………………………….200
• 7.5 Conclusions……………………………………………………………203
• 7.6 Summary………………………………………………………………204
• Chapter 8: Prediction of Algal Chlorophyll using Landsat-5 TM Data and Machine Learning Approaches……………………………………….206
• 8.1 Introduction…………………………………………………………...207
• 8.2 Materials and Methods……………………………………………...213
• 8.2.1 Study area……………………………………………………….213
• 8.2.2 Methodological approach for Paldang Reservoir………...215
• 8.2.3 Methodological approach for Imha Reservoir…………….220
• 8.3 Results…………………………………………………………………223
• 8.3.1 Relations of band compositions with CHL-a……………..223
• 8.3.2 Empirical model development of CHL-a from Landsat 5 TM data…………………………………………………………..225
• 8.3.3 Spatial and temporal patterns of water quality parameters……………………………………………………227
• 8.3.4 Chlorophyll-a prediction, cross-validation and trophic state in different zones………………………………………228
• 8.4 Discussion……………………………………………………………..233
• 8.5 Conclusions……………………………………………………………235
• 8.6 Summary………………………………………………………………236
• Chapter 9: Disentangling the Effects of Land Use and Weirs on Fish Trophic and Tolerance Guilds……………………………………………..238
• 9.1 Introduction…………………………………………………………...239
• 9.2 Materials and Methods……………………………………………...241
• 9.2.1 Study area……………………………………………………….241
• 9.2.2 Fish sampling, land use data and statistical analysis……243
• 9.3 Results…………………………………………………………………244
• 9.3.1 Relationships between land cover with trophic and tolerance guilds……………………………………………….244
• 9.3.2 Weirs impact on fish community……………………………..245
• 9.4 Discussion……………………………………………………………..247
• 9.4.1 Land cover impacts on fish guilds…………………………..247
• 9.4.2 Artificial barriers impact on fish community……………..248
• 9.5 Conclusions……………………………………………………………250
• 9.6 Summary………………………………………………………………251
• Chapter 10: Ecosystem Health Assessment Based on Chemical and Biological Multi-Metric Models and Their Relationships with Water Chemistry and Fish Guilds………………………………………………….252
• 10.1 Introduction………………………………………………………….253
• 10.2 Materials and Methods………………………………………….…258
• 10.2.1 Study area……………………………………………………...258
• 10.2.2 Water quality parameters…………………………………..261
• 10.2.3 Fish sampling………………………………………………….261
• 10.2.4 Multi-metric water pollution index (WPI) model……..261
• 10.2.5 Multi-metric index of biotic integrity (IBI) model…….262
• 10.2.6 Statistical analyses…………………………………………..263
• 10.3 Results………………………………………………………………..264
• 10.3.1 A case study for the Geum River watershed……………264
• 10.3.2 A case study for the Yeongsan River watershed………273
• 10.3.3 A case study for the Nakdong River watershed………279
• 10.3.4 A case study for the Nonsan Stream……………………..290
• 10.4 Discussion…………………………………………………………...301
• 10.5 Conclusions………………………………………………………….305
• 10.6 Summary……………………………………………………………..307
• References…………………………………………………………………….308
• Chapter 11: Overall Conclusions………………………………………….339
• Korean Abstract……………………………………………………………...346
• List of Publications…………………………………………………………..349
• List of International/National Academic Conferences………………..353
• List of Awards………………………………………………………………..355

참고문헌 (Reference)

1. Support-vector networks, Cortes, C., Vapnik, V., 20, 273–297. https://doi. org/10.1088/1742- 6596/628/1/012073, , 1995

2. Environmental indicators, Lopez-Lopez, E., Sedeno-Dıaz, J. E., 1–19. https://doi. org/10.1007/978-94-017- 9499-2, , 2015

3. Fundamentals of hydrology ed, Davie, T., Third Edit, , 2019

4. A trophic state index for lakes, Carlson, R. E., 22, 361–369. https://doi. org/10.4319/lo.1977.22.2.0361, , 1977

5. Limnology Lake and River Ecosystem, Wetzel, R. G., https://doi. org/10.1063/1.3224729, , 2001

6. Limnology—Inland water ecosystems, Smith, R., 21, 346–347. https://doi. org/10.2307/1468422, , 2002

7. Algal blooms hit South Korean rivers, Park, S. Bin, https://doi. org/10.1038/nature.2012.11221, , 2012

8. Phosphorus movement in the landscape, Sharpley, A., Daniel, T., Edwards, D., 6, 492–500, , 1993

9. Ecology of soil erosion in ecosystems, Pimentel, D., Kounang, N., 1, 416–426. https://doi. org/10.1007/s100219900035, , 1998

10. Recent developments in receptor modeling, Hopke, P. K., 17, 255–265. https://doi. org/10.1002/cem.796, , 2003

11. Eutrophication of reservoirs in South Korea, Jun, M. S., Hwang, G., Park, J. H., Choi, K., Kim, B., 2, 223– 229. https://doi. org/10.1007/s10201-001-8040-6, , 2001

12. Evolution of phosphorus limitation in lakes, Schindler, D. W., 80. 195, 260–262. https://doi. org/10.1126/science.195.4275.260, , 1977

13. Agroforestry, environment and sustainability, Young, A., 19, 155–160, , 1990

14. Mountain Rivers. water resources monograph 14, Wohl, E., https://doi. org/10.1029/WM014, , 2000

15. Ecological integrity is both real and valuable, Karr, J. R., Chu, E. W., Larson, E. R., 4, 1–10. https://doi. org/10.1111/csp2.583, , 2022

16. Water quality and limnology of Korean reservoirs, Kwun, S.-K., Hwang, S.-J., Yoon, C.-G., 1, 43–52. https://doi. org/10.1007/s10333-003-0010-7, , 2003

17. Microbiological water quality of the Nišava River, Marković, N. V., Čučak, D. I., Radnović, D. V., 1668–1673. https://doi. org/10.2166/ws.2016.089, , 2016

18. Local determinants influencing stream water quality, Bhat, S. U., Jehangir, A., Hamid, A., 10, 1–16. https://doi. org/10.1007/s13201-019-1043-4, , 2020

19. Nitrogen, phosphorus, and eutrophication in streams, Dodds, W. K., Smith, V. H., 155–164. https://doi. org/10.5268/IW-6.2.909, , 2016

20. Biological criteria for the protection of aquatic life, Ohio, E., Vol. III, , 1989

21. Chemical index for surveillance of river water quality, Bach, E.., 24, 102–106, , 1980

22. comparative limnology of some lakes in interior alaska, Laperriere, J. D., Simpson, T. D., Jones, J. R., 19, 122–132, , 2003

23. Determination of optimal SVM parameters by using GA/PSO, Ren, Y., Bai, G., 5, 1160–1168. https://doi. org/10.4304/jcp.5.8.1160-1168, , 2010

24. A Treatise on Limnology. Geography, physics and chemistry, Hutchinson, G. E., Volume 1, , 1957

25. Global patterns of current and future road infrastructure, Huijbregts, M. A. J., Schipper, A. M., Meijer, J. R., Schotten, K. C. G. J., 13. https://doi. org/10.1088/1748- 9326/aabd42, , 2018

26. Lake ecoregions and nutrient criteria development in China, Deng, X., He, Z., Su, J., Huo, S., Gao, R., Xi, B., Liu, H., Wu, F., Ma, C., Jiang, T., 46, 1–10. https://doi. org/10.1016/j. ecolind.2014.06.014, , 2014

27. Reservoir trophic state evaluation using Landsat TM images, Cheng, K. S., Lei, T. C., 37, 1321–1334. https://doi. org/10.1111/j.1752-1688.2001. tb03642. x, , 2001

28. Trophic state assessment of Bhindawas Lake, Haryana, India, Saluja, R., Garg, J. K., 189. https://doi. org/10.1007/s10661-016-5735-z, , 2017

29. Human impact on current environmental state in Chinese lakes, Jeppessen, E., Wang, Q., Chen, F., Liu, L., Cui, S., Liu, X., Li, Y., 1–13. https://doi. org/10.1016/j. jes.2022.05.031, , 2022

30. Global perturbation of organic carbon cycling by river damming, Maavara, T., Van Cappellen, P., Lauerwald, R., Regnier, P., 8, 1–10. https://doi. org/10.1038/ncomms15347, , 2017

31. Hyperparameter selection in kernel principal component analysis, Fukumizu, K., Alam, M. A., 10, 1139–1150. https://doi. org/10.3844/jcssp.2014.1139.1150, , 2014

32. The biological control of chemical factors in the envi- ronment, Redfield, A. C., 46, 205–212, , 1958

33. The clean water rule: Defining the scope of the clean water act, Hawkins, C. P., 34, 1584–1587. https://doi. org/10.1086/684005, , 2015

34. Least squares formulation of robust non-negative factor analysis, Paatero, P., 37, 23–35. https://doi. org/10.1016/S0169-7439(96)00044-5, , 1997

35. Defining and assessing ecological integrity: Beyond water quality, Karr, J. R., 12, 1521–1531. https://doi. org/10.1002/etc.5620120902, , 1993

36. Major ion chemistry of the Ganga-Brahmaputra river systems, India, Sarin, M. M., Krishnaswami, S., 312, 538–541. https://doi. org/10.1038/312538a0, , 1984

37. A Carlson‐Type Trophic State Index for Nitrogen in Florida Lakes, Brezonik, P. L., Kratzer, C. R., 18, 543–544. https://doi. org/10.1111/j.1752- 1688.1982. tb00027. x, , 1982

38. A trophic state index for tropical/subtropical reservoirs (TSItsr), Lamparelli, M. C., Cunha, D. G. F., Calijuri, M. do C., 60, 126–134. https://doi. org/10.1016/j. ecoleng.2013.07.058, , 2013

39. EPA Positive M atrix Factorization ( PM F ) 5 . 0 Fundamentals and., USEPA, 20460 136, , 2014

40. Human impact on freshwater ecosystem services: A global perspective, Perkin, J. S., Dodds, W. K., Gerken, J. E., 47, 9061–9068. https://doi. org/10.1021/es4021052, , 2013

41. Standard methods for the examination of water quality contamination, MOE, seventh ed. Gwacheon p. 435in Korean, , 2000

42. Atmospheric aerosol over Alaska 2. Elemental composition and sources, Paatero, P., Sisler, J. F., Malm, W. C., Hopke, P. K., Polissar, A. V., 103, 19045–19057. https://doi. org/10.1029/98JD01212, , 1998

43. Assessment of surface water quality of the Ceyhan River basin, Turkey, Alp, A., Tanriverdi, Ç ., Demirkiran, A. R., Ü çkardeş, F., 167, 175–184. https://doi. org/10.1007/s10661-009-1040-4, , 2010

44. Evaluation of water quality index for River Sabarmati, Gujarat, India, Joshi, G. S., Shah, K. A., 7, 1349–1358. https://doi. org/10.1007/s13201-015-0318-7, , 2017

45. Remote sensing estimation of water clarity for various lakes in China, Zhou, Y., Zhang, Zhang, Yibo, Yunlin, Shi, K., Li, N., 192. https://doi. org/10.1016/j. watres.2021.116844, , 2021

46. Impacts of urban land cover on trout streams in Wisconsin and Minnesota, Kanehl, P., Wang, L., Lyons, J., 132, 825–839. https://doi. org/10.1577/t02-099, , 2003

47. Landscape influences on water chemistry in Midwestern stream ecosystems, Host, G. E., Johnson, L. B., Richards, C., Arthur, J. W., 37, 193–208. https://doi. org/10.1046/j.1365- 2427.1997. d01-539. x, , 1997

48. Stream ecology: Structure and function of running waters Second edition, Allan, J. D., Castillo, M. M., https://doi. org/10.1007-978-1- 4020-5583-6, , 2007

49. Fuzzy modelling of chlorophyll production in a Brazilian upwelling system, Pereira, G. C., Evsukoff, A., Ebecken, N. F. F., 220, 1506–1512. https://doi. org/10.1016/j. ecolmodel.2009.03.025, , 2009

50. Non-algal seston, light, nutrients and chlorophyll in missouri reservoirs, Jones, J. R., Knowlton, M. F., 16, 322–332. https://doi. org/10.1080/07438140009354239, , 2000

51. Understanding the role of land use in urban stormwater quality management, Goonetilleke, A., Gilbert, D., Ginn, S., Thomas, E., 74, 31–42. https://doi. org/10.1016/j. jenvman.2004.08.006, , 2005

52. A multi-model approach to evaluating target phosphorus loads for Lake Erie, DePinto, J. V., Scavia, D., Bertani, I., 42, 1139–1150. https://doi. org/10.1016/j. jglr.2016.09.007, , 2016

53. Landscapes and riverscapes: The influence of land use on stream ecosystems, Allan, J. David, 35, 257–284, , 2004

54. Nutrient limitation of phytoplankton and periphyton growth in upland lakes, King, L., Dent, M. M., Jones, R. I., Maberly, S. C., Gibson, C. E., 47, 2136–2152. https://doi. org/10.1046/j.1365-2427.2002.00962. x, , 2002

55. Correction to: Extracting Shoreline from Satellite Imagery for GIS Analysis, Ghorai, D., Mahapatra, M., 3, 23–23. https://doi. org/10.1007/s41976-020-00031-0, , 2020

56. Limnology of lakes in gates of the arctic national park and preserve, Alaska, Swanson, D. K., Jones, J. R., Laperriere, J. D., 19, 108–121, , 2003

57. Relationship of chlorophyll to phosphorus and nitrogen in nutrient-rich lakes, Filstrup, C. T., Downing, J. A., 7, 385–400. https://doi. org/10.1080/20442041.2017.1375176, , 2017

58. Anthropogenic climate change has altered primary productivity in Lake Superior, Werne, J. P., O’Beirne, M. D., Johnson, T. C., Reavie, E. D., Katsev, S., Hecky, R. E., 8, 15713. https://doi. org/10.1038/ncomms15713, , 2017

59. Influence function and robust variant of kernel canonical correlation analysis, Alam, M. A., Wang, Y. P., Fukumizu, K., https://doi. org/10.1016/j. neucom.2018.04.008, , 2018

60. Fish community responses to multiple municipal wastewater inputs in a watershed, Servos, M. R., Tetreault, G. R., Brown, C. J. M., Oakes, K. D., McMaster, M. E., Bennett, C. J., 9, 456–468. https://doi. org/10.1002/ieam.1364, , 2013

61. Lindemans trophic- dynamic aspect of ecology: will you still need me when im 64?, Sobczak, W. V, 14, 53–57, , 2005

62. Trophic state, seasonal patterns and empirical models in South Korean Reservoirs, Jones, J. R., Knowlton, M. F., An, K. G., 19, 64–78. https://doi. org/10.1080/07438140309353991, , 2003

63. Impacts of urbanization on stream habitat and fish across multiple spatial scales, Lyons, J., Bannerman, R., Kanehl, P., Wang, L., 28, 255–266. https://doi. org/10.1007/s0026702409, , 2001

64. Integrating water-quality management and land-use planning in a watershed context, Wang, X., https://doi. org/10.1006/jema.2000.0395, , 2001

65. PAST: Paleontological statistics software package for education and data analysis, Hammer, Ø ., Harper, D., Ryan, P., 4, 9, , 2001

66. The influence of dam construction on water quality in the lower Geum River, Korea, Yoon, Y. Y., Shim, M. J., Yoon, S. C., 28, 113–121. https://doi. org/10.1002/tqem.21591, , 2018

67. Chlorophyll maxima and chlorophyll: Total phosphorus ratios in Missouri reservoirs, Jones, J. R., Obrecht, D. V., Thorpe, A. P., 27, 321–328. https://doi. org/10.1080/07438141.2011.627625, , 2011

68. Nitrogen and phosphorus relationships to benthic algal biomass in temperate streams, Dodds, W. K., Smith, V. H., Lohman, K., 59, 865–874. https://doi. org/10.1139/f02- 063, , 2002

69. Phytoplankton nutrient deficiencies vary with season in sub-tropical lakes of Nepal, Gurung, T. B., Obrecht, D. V., North, R. L., Jones, J. R., Rowland, F. E., McEachern, P., Jones, S. B., 833, 157–172. https://doi. org/10.1007/s10750- 019-3897-8, , 2019

70. Cyanobacterial occurrence and geosmin dynamics in Paldang Lake watershed, South Korea, Byeon, M. S., Yu, S. J., Youn, S. J., Kim, H. N., 1–10. https://doi. org/10.1111/wej.12547, , 2020

71. Land use impacts on river health of Uma Oya, Sri Lanka: implications of spatial scales, Gunawardana, W. D. T. M., Udayakumara, E. P. N., Westbrooke, M., Jayawardana, J. M. C. K., 189. https://doi. org/10.1007/s10661-017- 5863-0, , 2017

72. The influence of catchment land use on stream integrity across multiple spatial scales, Fay, J., Allan, J. D., Erickson, D. L., 37, 149–161. https://doi. org/10.1046/j.1365- 2427.1997. d01-546. x, , 1997

73. Factors regulating phytoplankton production and standing crop in the worlds freshwaters, Schindler, D. W., 23, 478–486. https://doi. org/10.4319/lo.1978.23.3.0478, , 1978

74. Freshwater algal bloom prediction by support vector machine in Macau storage reservoirs, Xie, Z., Lou, I., Ung, W. K., Mok, K. M., https://doi. org/10.1155/2012/397473, , 2012

75. Catchment-wide impacts on water quality: The use of snapshot sampling during stable flow, Finlayson, B. L., Grayson, R. B., Gippel, C. J., Hart, B. T., 199, 121– 134. https://doi. org/10.1016/S0022-1694(96)03275-1, , 1997

76. Characterizing the river water quality in China: Recent progress and on-going challenges, Huang, J., Bing, H., Arhonditsis, G. B., Zhang, Y., Gao, J., Dong, F., Peng, J., 201, 117309. https://doi. org/10.1016/j. watres.2021.117309, , 2021

77. Ecosystem responses to climate change in a large on-river reservoir, Lake Paldang, Korea, Park, H. K., Cho, K. H., Kong, D. S., Jung, D. Il, Won, D. H., Lee, J., 120, 477–489. https://doi. org/10.1007/s10584-013-0801-9, , 2013

78. Watershed urbanization and changes in fish communities in southeastern Wisconsin streams, Lyons, J., Emmons, E., Bannerman, R., Wang, L., Kanehi, P., 36, 1173–1189. https://doi. org/10.1111/j.1752- 1688.2000. tb05719. x, , 2000

79. Effects of non-algal turbidity on cyanobacterial biomass in seven turbid Kansas reservoirs, Wang, S. H., Smith, V. H., Dzialowski, A. R., Martin, M. C., DeNoyelles, F., 27, 6–14. https://doi. org/10.1080/07438141.2011.551027, , 2011

80. Chemical weathering of silicate rocks as a function of elevation in the southern Swiss Alps, Zobrist, J., Drever, J. I., 56, 3209–3216. https://doi. org/10.1016/0016- 7037(92)90298-W, , 1992

81. Nutrients, eutrophication and harmful algal blooms along the freshwater to marine continuum, Paerl, H. W., Dodds, W. K., Wurtsbaugh, W. A., 6, 1–27. https://doi. org/10.1002/wat2.1373, , 2019

82. Feedbacks between nutrient enrichment and geomorphology alter bottom-up control on food webs, Deegan, L. A., Sommer, N. R., Nelson, J. A., Johnson, D. S., Spivak, A. C., 22, 229–242. https://doi. org/10.1007/s10021- 018-0265-x, , 2019

83. A comprehensive review on water quality parameters estimation using remote sensing techniques, Reddi, L., Gholizadeh, M. H., Melesse, A. M., 16. https://doi. org/10.3390/s16081298, , 2016

84. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity, Arthington, A. H., Bunn, S. E., 30, 492–507. https://doi. org/10.1007/s00267- 002-2737-0, , 2002

85. Detection of organic pollution of streams in southern Sweden using benthic macroinvertebrates, Dahl, J., Johnson, R. K., Sandin, L., . https://doi. org/10.1023/B:HYDR.0000025264.35531. cb, , 2004

86. Geomorphology and hydrochemistry of 12 Alpine lakes in the Gran Paradiso National Park, Italy, Tiberti, R., Tartari, G. A., Marchetto, A., 69, 242–256. https://doi. org/10.3274/JL10-69-2-07, , 2010

87. Influences of watershed land use on habitat quality and biotic integrity in Wisconsin Streams, Gatti, R., Kanehl, P., Wang, L., Lyons, J., 22, 6–12. https://doi. org/10.1577/1548- 8446(1997)022<0006:iowluo>2.0. co;2, , 1997

88. Long-term Trend Analysis of Chlorophyll a and Water Quality in the Yeongsan River (In Korean), Shin, Y., Song, E., Park, D., Jeon, S., Lee, E., 45, 302–313, , 2012

89. Relationships between water quality parameters in rivers and lakes: BOD5, COD, NBOPs, and TOC, Yu, S., Lee, J., Rhew, D., Lee, S., 188, 1–8. https://doi. org/10.1007/s10661-016-5251-1, , 2016

90. Roles of nutrient regime and N:P ratios on algal growth in 182 Korean agricultural reservoirs, An, K. G., Mamun, M., Lee, S. J., 27, 1175–1185. https://doi. org/10.15244/pjoes/76676, , 2018

91. Factors regulating bluegreen dominance in a reservoir directly influenced by the asian monsoon, An, K. G., Jones, J. R., https://doi. org/10.1023/A:1004077220519, , 2000

92. Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution, Linke, S., Lehner, B., Ouellet Dallaire, C., Ariwi, J., Grill, G., Anand, M., Beames, P., Burchard-Levine, V., Maxwell, S., Moidu, H., Tan, F., Thieme, M., 6, 1–15. https://doi. org/10.1038/s41597-019-0300-6, , 2019

93. Influence of hydrology on water quality and trophic state of irrigation reservoirs in Sri Lanka, Amarasinghe, U. S., Wijenayake, W. M. H. K., Nadarajah, S., 24, 287–298. https://doi. org/10.1111/lre.12283, , 2019

94. Relationships between chlorophyll, salinity, phosphorus, and nitrogen in lakes and marine areas, Håkanson, L., Eklund, J. M., 263, 412–423. https://doi. org/10.2112/08-1121.1, , 2010

95. Water quality assessment of river Beas, India, using multivariate and remote sensing techniques, Bhardwaj, R., Sharma, A., Thukral, A. K., Kumar, V., Chawla, A., 188, 1– 10. https://doi. org/10.1007/s10661-016-5141-6, , 2016

96. Estimating the biodegradability of treated sewage samples using synchronous fluorescence spectra, Hur, J., Lai, T. M., Shin, J. K., 11, 7382–7394. https://doi. org/10.3390/s110807382, , 2011

97. Response of reservoir water quality to nutrient inputs from streams and in-lake fishfarms. Water, An, K. G., Kim, D. S., https://doi. org/10.1023/A:1025602213674, , 2003

98. Simple graphical methods for the interpretation of relationships between trophic state variables, Havens, K. E., Carlson, R. E., 21, 107–118. https://doi. org/10.1080/07438140509354418, , 2005

99. A large-scale assessment of lakes reveals a pervasive signal of land use on bacterial communities, Shapiro, B. J., Walsh, D. A., Kraemer, S. A., Fradette, M., Huot, Y., Barbosa da Costa, N., 14, 3011–3023. https://doi. org/10.1038/s41396-020-0733-0, , 2020

100. An empirical model for predicting microhabitat of 0+ juvenile fishes in a lowland river catchment, Copp, G. H., 91, 338–345. https://doi. org/10.1007/BF00317621, , 1992

101. Effect of land use on the seasonal variation of streamwater quality in the Wei River basin, China, Zuo, D., Yu, S., Xu, Z., Wu, W., 368, 454–459. https://doi. org/10.5194/piahs-368-454-2015, , 2015

102. Mapping inland lake water quality across the Lower Peninsula of Michigan using Landsat TM imagery, Becker, B., Torbick, N., Wiangwang, N., Hagen, S., Qi, J., Hession, S., 34, 7607–7624. https://doi. org/10.1080/01431161.2013.822602, , 2013

103. Mapping the concentrations of total suspended matter in Lake Taihu, China, using Landsat-5 TM data, Wang, S., Zhou, W., Troy, A., Zhou, Y., 27, 1177–1191. https://doi. org/10.1080/01431160500353825, , 2006

104. A hydrodynamic modeling study to determine the optimum water intake location in Lake Paldang, Korea, Eun, H. N., Seok, S. P., 41, 1315–1332. https://doi. org/10.1111/j.1752-1688.2005. tb03802. x, , 2005

105. Effects of weir construction on phytoplankton assemblages and water quality in a large river system, Cheon, S. U., Lee, H. J., Park, H. K., https://doi. org/10.3390/ijerph15112348, , 2018

106. The influence of nutrients and physical habitat in regulating algal biomass in agricultural streams, Tesoriero, A., Frey, J., Munn, M., 45, 603–615. https://doi. org/10.1007/s00267-010-9435-0, , 2010

107. Eutrophication development and its key regulating factors in a water-supply reservoir in North China, Liu, L., Zheng, B., Wang, L., 25, 962–970. https://doi. org/10.1016/S1001-0742(12)60120-X, , 2013

108. Spatio-temporal Variation Analysis of Physico-chemical Water Quality in the Yeongsan-River Watershed, Kang, S.-A., An, K., 39, 73–84, , 2006

109. Temporal and spatial variation of nutrients, suspended solids, and chlorophyll in Yeongsan watershed, Mamun, M., Lee, S. J., An, K. G., 11, 206–216. https://doi. org/10.1016/j. japb.2018.02.006, , 2018

110. Effects of water and substratum nutrient supplies on lotic periphyton growth—An integrated bioassay, Pringle, C.., 44, 619–629, , 1987

111. Primary production by phytoplankton community in some Japanese lakes and its dependence on lake depth, Sakamoto, M., 62, 1–28, , 1966

112. Investigating industrial effluent impact on municipal wastewater treatment plant in vaal, South Africa, Iloms, E., Selvarajan, R., Ololade, O. O., Ogola, H. J. O., 17, 1–18. https://doi. org/10.3390/ijerph17031096, , 2020

113. Urbanization, sedimentation, and the homogenization of fish assemblages in the Etowah River Basin, USA, Bearden, A. B., Leigh, D. S., Walters, D. M., 494, 5–10. https://doi. org/10.1023/A:1025412804074, , 2003

114. Managing the middle: A shift in conservation priorities based on the global human modification gradient, Baruch-Mordo, S., Kiesecker, J., Oakleaf, J. R., Kennedy, C. M., Theobald, D. M., 25, 811–826. https://doi. org/10.1111/gcb.14549, , 2019

115. The phosphorus-chlorophyll in lakes 19 767–773 Eutrophication and trophic state in rivers and streams, Dodds, W. K., Dillon, P. J., 51, 671–680. https://doi. org/10.4319/lo.2006.51.1_part_2.0671, , 1974

116. Phosphorus accumulates faster than nitrogen globally in freshwater ecosystems under anthropogenic impacts, Sardans, J., Peñuelas, J., Han, W., Elser, J. J., Du, E., Fang, J., Yan, Z., Reich, P. B., 19, 1237–1246. https://doi. org/10.1111/ele.12658, , 2016

117. Developing an empirical model from Landsat data series for monitoring water salinity in coastal Bangladesh, Ferdous, J., Rahman, M. T. U., 255, 109861. https://doi. org/10.1016/j. jenvman.2019.109861, , 2020

118. causes, assessment, and treatment of nutrient (n and p) pollution in rivers, estuaries, and coastal waters, Feng, H., Nie, J., Alebus, M., Mahajan, M. D., Zhang, W., Witherell, B. B., Yu, L., 4, 154–161. https://doi. org/10.1007/s40726- 018-0083-y, , 2018

119. Indirect influence of the summer monsoon on chlorophyll-total phosphorus models in reservoirs: A case study, An, K. G., Park, S. S., 152, 191–203. https://doi. org/10.1016/S0304-3800(02)00020-0, , 2002

120. Relationships between water quality, habitat quality, and macroinvertebrate assemblages in Illinois Streams, Heatherly, T., Royer, T. V., Whiles, M. R., David, M. B., 36, 1653–1660. https://doi. org/10.2134/jeq2006.0521, , 2007

121. Water quality assessment in terms of water quality index (WQI): case study of the Kolong River, Assam, India, Goswami, D. C., Bora, M., 7, 3125–3135. https://doi. org/10.1007/s13201-016-0451-y, , 2017

122. Application of landsat 5 and landsat 7 images data for water quality mapping in Mosul Dam Lake, Northern Iraq, Merkel, B. J., Khattab, M. F. O., 7, 3557–3573. https://doi. org/10.1007/s12517-013-1026-y, , 2014

123. Impact of the river nutrient load variability on the North Aegean ecosystem functioning over the last decades, Triantafyllou, G., Kourafalou, V. H., Petihakis, G., Tsiaras, K. P., 86, 97– 109. https://doi. org/10.1016/j. seares.2013.11.007, , 2014

124. Nutrients, seston, and transparency of missouri reservoirs and oxbow lakes: An analysis of regional limnology, Knowlton, M. F., Obrecht, D. V., Watanabe, S., Thorpe, A. P., Bacon, R. R., Perkins, B. D., Jones, J. R., 24, 155–180. https://doi. org/10.1080/07438140809354058, , 2008

125. Forest cover correlates with good biological water quality. Insights from a regional study (Wallonia, Belgium), Jacobs, S., Dufrêne, M., Latli, A., Michez, A., Dendoncker, N., Brogna, D., Vincke, C., 211, 9–21. https://doi. org/10.1016/j. jenvman.2018.01.017, , 2018

126. Spatiotemporal analysis of water quality parameters in machángara river with nonuniform interpolation methods, Sanromán-Junquera, M., Vizcaino, I. P., Cumbal, L. H., Carrera, E. V., Muñoz- Romero, S., Rojo-Á lvarez, J. L., 8, 1–17. https://doi. org/10.3390/w8110507, , 2016

127. Comparison of mainstem spawning habitats for two populations of fall Chinook salmon in the Columbia River Basin, Dauble, D., Geist, D., 16, 345–361, , 2000

128. Major ion chemistry of the Ganga-Brahmaputra river system: Weathering processes and fluxes to the Bay of Bengal, Dilli, K., Moore, W. S., Somayajulu, B. L. K., Krishnaswami, S., Sarin, M. M., 53, 997–1009. https://doi. org/10.1016/0016-7037(89)90205-6, , 1989

129. Source apportionment of polycyclic aromatic hydrocarbons in the urban atmosphere: A comparison of three methods, Larsen, R. K., Baker, J. E., 37, 1873–1881. https://doi. org/10.1021/es0206184, , 2003

130. Spatio-temporal changes in surface water quality and sediment phosphorus content of a large reservoir in Turkey, Varol, M., 259, 113860. https://doi. org/10.1016/j. envpol.2019.113860, , 2020

131. Assessment of water quality based on Landsat 8 operational land imager associated with human activities in Korea, Choi, M., Lim, J., 187, 1–17. https://doi. org/10.1007/s10661-015-4616-1, , 2015

132. Characterizing trophic state in tropical/subtropical reservoirs: deviations among indexes in the lower latitudes, Cunha, D. G. F., Dodds, W. K., Lamparelli, M. C., Carlson, R. E., Finkler, N. R., Calijuri, M. do C., https://doi. org/10.1007/s00267-021-01521-7, , 2021

133. Physical and chemical limnology of 34 lentic waterbodies along a tropical-to-alpine altitudinal gradient in Nepal, Lacoul, P., Freedman, B., 90, 254–276. https://doi. org/10.1002/iroh.200410766, , 2005

134. Variation in chlorophyll a to total phosphorus ratio across 94 UK and Irish lakes: Implications for lake management, Carvalho, L., Spears, B. M., Dudley, B., May, L., 115, 287–294. https://doi. org/10.1016/j. jenvman.2012.10.011, , 2013

135. River health assessment using macroinvertebrates and water quality parameters: A case of the Orange River in Namibia, Kongo, V., Munyika, S., Kimwaga, R., 76–78, 140– 148. https://doi. org/10.1016/j. pce.2015.01.001, , 2014

136. Spatio-temporal variations and source apportionment of water pollution in Danjiangkou Reservoir Basin, Central China, Chen, P., Zhang, H., Li, L., 7, 2591–2611. https://doi. org/10.3390/w7062591, , 2015

137. Rapid bioassessment protocols for use in streams and wadeable rivers: periphyton, benthic macroinvertebrates and fish, Barbour, M.., Gerritsen, J., Snyder, B. D., Stribling, J. B., Second Edition, , 1991

138. Assessing the causal relationships of ecological integrity a re‐evaluation of Karrs Iconic Index of Biotic Integrity, Rooney, N., Capmourteres, V., Anand, M., https://doi. org/e02168. 10.1002/ecs2.2168, , 2018

139. Rapid bioassessment protocols for use in streams and wadeable rivers: periphyton, benthic macriinvertebrates, and fish, Barbour, M. T., Faulkner, C., Gerritsen, J., Second Edition, EPA 841- B-99-002 337, , 1999

140. Water quality assessment and source identification of the Shuangji River (China) using multivariate statistical methods, Liu, R., Liu, J., Huang, S., Zhang, D., Xu, H., Shang, D., Tang, Q., 16, 1–19. https://doi. org/10.1371/journal. pone.0245525, , 2021

141. The application of chemical and biological multi-metric models to a small urban stream for ecological health assessments, Mamun, M., An, K. G., 50, 1–12. https://doi. org/10.1016/j. ecoinf.2018.12.004, , 2019

142. The four major rivers restoration project of South Korea: An assessment of its process, program, and political dimensions, Park, Y., Cho, Y. J., Lah, T. J., 24, 375–394. https://doi. org/10.1177/1070496515598611, , 2015

143. Assessing river biotic condition at a continental scale: A European approach using functional metrics and fish assemblages, Roset, N., Melcher, A., Hugueny, B., Pont, D., Beier, U., Rogers, C., Goffaux, D., Schmutz, S., Noble, R., 43, 70–80. https://doi. org/10.1111/j.1365-2664.2005.01126. x, , 2006

144. Ecological health assessments of 72 streams and rivers in relation to water chemistry and land-use patterns in South Korea, An, K.-G., Mamun, M., 18, 871–880. https://doi. org/10.4194/1303-2712-v18, , 2018

145. Effect of water quality variation on fish assemblages in an anthropogenically impacted tropical estuary, Colombian Pacific, Cogua, P., Gamboa-García, D. E., Duque, G., Molina, A., 27, 25740–25753. https://doi. org/10.1007/s11356-020-08971-2, , 2020

146. Identification of long-term trends and seasonality in high-frequency water quality data from the Yangtze River basin, China, Chen, W., Nover, D., Yang, G., Wang, Y., He, B., Zou, S., Chen, Y., Duan, W., 13, 1–18. https://doi. org/10.1371/journal. pone.0188889, , 2018

147. Integrated ecological river health assessments, based on water chemistry, physical habitat quality and biological integrity, An, K. G., Kim, J. Y., Switzerland) 7, 6378–6403. https://doi. org/10.3390/w7116378, , 2015

148. Long-term effects of hydrometeorological and water quality conditions on algal dynamics in the Paldang dam watershed, Korea, Kim, K., Min, J. H., Kim, D. W., Kang, M., Yoo, M., 14, 601–608. https://doi. org/10.2166/ws.2014.014, , 2014

149. Reservoir water quality assessment based on chemical parameters and the chlorophyll dynamics in relation to nutrient regime, Atique, U., An, K. G., 28, 1043–1061. https://doi. org/10.15244/pjoes/85675, , 2019

150. Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network, Cho, K. H., Pachepsky, Y. A., Sthiannopkao, S., Kim, K. W., Kim, J. H., 45, 5535–5544. https://doi. org/10.1016/j. watres.2011.08.010, , 2011

151. Empirical estimation of total phosphorus concentration in the mainstream of the Qiantang River in China using Landsat TM data, Qi, J., Zhang, L., Wu, C., Lou, L., Wu, J., Chen, Y., Huang, H., 31, 2309–2324. https://doi. org/10.1080/01431160902973873, , 2010

152. Chemical water quality and fish component analyses in the periods of before- and after-the weir constructions in Yeongsan River, Kwak, S. Do, An, K. G., Choi, J. W., 39, 99– 110. https://doi. org/10.5141/ecoenv.2016.011, , 2016

153. Assessment of Water Quality Based on Trophic Status and Nutrients-Chlorophyll Empirical Models of Different Elevation Reservoirs, An, K.-G., Atique, U., Mamun, M., 13, 3640. https://doi. org/10.3390/w13243640, , 2021

154. Evaluation of Spatiotemporal Changes in Surface Water Quality and Their Suitability for Designated Uses, Mettur Reservoir, India, Sarkar, U. K., Saha, A., Das, B. K., Mol, S. S., Vijaykumar, M. E., Ramya, V. L., Panikkar, P., Jesna, P. K., https://doi. org/10.1007/s11053-020-09790-5, , 2021

155. Technical Report: The Survey of Pollution Sources of Water for the Agricultural UseIn Korean Defining and measuring river health, KARICO, Karr, J. R., 41, 221–234. https://doi. org/10.1046/j.1365- 2427.1999.00427. x, , 2000

156. Effects of local land-use on riparian vegetation, water quality, and the functional organization of macroinvertebrate assemblages, Fierro, P., Bertrán, C., Tapia, J., Hauenstein, E., Peña-Cortés, F., Vergara, C., Cerna, C., Vargas-Chacoff, L., 609, 724–734, , 2017

157. Physico-chemical and Biological Aspects of Monsoon Waters of AShulia for Economic and Aesthetic Applications: Preliminary Studies, Elahi, S. F., Islam, M. S., Huda, M., Khan, M. A. I., Hossain, A. M., 42, 377–396. https://doi. org/10.3329/bjsir. v42i4.747, , 2007

158. Seasonal changes in cyanobacterial diversity of a temperate freshwater Paldang Reservoir (korea) explored by using pyrosequencing, Boopathi, T., Ki, J.-S., Wang, H., Lee, M.-D., . https://doi. org/10.11626/kjeb.2018.36.3.424, , 2018

159. Geochemical characteristics of water and sediment of the Indus River, Trans-Himalaya, India: Constraints on weathering and erosion, Balakrishnan, S., Ahmad, T., Khanna, P. P., Chakrapani, G. J., 16, 333–346. https://doi. org/10.1016/S0743-9547(98)00016-6, , 1998

160. Major nutrients and chlorophyll dynamics in Korean agricultural reservoirs along with an analysis of trophic state index deviation, Mamun, M., An, K. G., 10, 183–191. https://doi. org/10.1016/j. japb.2017.04.001, , 2017

161. Assessing land-use effects on water quality, in-stream habitat, riparian ecosystems and biodiversity in Patagonian northwest streams, Miserendino, M. L., Brand, C., Di Prinzio, C. Y., Archangelsky, M., Casaux, R., Kutschker, A. M., 409, 612–624. https://doi. org/10.1016/j. scitotenv.2010.10.034, , 2011

162. Landscape heterogeneity impacts water chemistry, nutrient regime, organic matter and chlorophyll dynamics in agricultural reservoirs, Atique, U., An, K. G., 110, 105813. https://doi. org/10.1016/j. ecolind.2019.105813, , 2020

163. Landsat-based remote sensing of lake water quality characteristics, including chlorophyll and colored dissolved organic matter (CDOM), Brezonik, P., Menken, K. D., Bauer, M., 21, 373–382. https://doi. org/10.1080/07438140509354442, , 2005

164. Short-term to seasonal variability in factors driving primary productivity in a shallow estuary: Implications for modeling production, MacIntyre, H. L., Canion, A., Phipps, S., 131, 224–234. https://doi. org/10.1016/j. ecss.2013.07.009, , 2013

165. Trophic state of clear and colored, soft- and hardwater lakes with special consideration of nutrients, anoxia, phytoplankton and fish, Nürnberg, G. K., 12, 432–447. https://doi. org/10.1080/07438149609354283, , 1996

166. Examining the influence of human stressors on benthic algae, macroinvertebrate, and fish assemblages in Mediterranean streams of Chile, Vargas-Chacoff, L., Jara-Flores, A., Valdovinos, C., Habit, E., Arismendi, I., Fierro, P., Díaz, G., 686, 26–37. https://doi. org/10.1016/j. scitotenv.2019.05.277, , 2019

167. Occurrence of cyanobacteria, actinomycetes, and geosmin in drinking water reservoir in Korea: A case study from an algal bloom in 2012, Lee, J. E., Byeon, M., Yu, S. J., Youn, S. J., 20, 1862–1870. https://doi. org/10.2166/ws.2020.102, , 2020

168. Sources and spatial and temporal characteristics of organic carbon in two large reservoirs with contrasting hydrologic characteristics, Jung, D. Il, Park, H. K., Byeon, M. S., Shin, Y. N., 45, 1–12. https://doi. org/10.1029/2009WR008043, , 2009

169. Quantifying the dependence of cyanobacterial growth to nutrient for the eutrophication management of temperatesubtropical shallow lakes, Zou, W., Zhu, G., Cai, Y., Xu, H., Zhu, M., Gong, Z., Zhang, Y., Qin, B., 177,115806. https://doi. org/10.1016/j. watres.2020.115806, , 2020

170. Role of land cover and hydrology in determining nutrients in mid-continent reservoirs: Implications for nutrient criteria and management, Jones, J. R., Knowlton, M. F., Obrecht, D. V., 24, 1–9. https://doi. org/10.1080/07438140809354045, , 2008

171. Spatialtemporal variation and comparative assessment of water qualities of urban river system: A case study of the river Bagmati (Nepal), Kannel, P. R., Lee, S., Kanel, S. R., Khan, S. P., Lee, Y. S., 129, 433–459. https://doi. org/10.1007/s10661-006-9375-6, , 2007

172. Suggested classification of stream trophic state: Distributions of temperate stream types by chlorophyll, total nitrogen, and phosphorus, Dodds, W. K., Jones, J. R., Welch, E. B., 32, 1455–1462. https://doi. org/10.1016/S0043-1354(97)00370-9, , 1998

173. Integrated application of multivariate statistical methods to source apportionment ofwatercourses in the liao river basin, northeast China, Chen, J., Li, F., Fan, Z., Wang, Y., 13. https://doi. org/10.3390/ijerph13101035, , 2016

174. Open-source processing and analysis of aerial imagery acquired with a low-cost Unmanned Aerial System to support invasive plant management, Lehmann, J. R. K., Prinz, T., Ziller, S. R., Thiele, J., Heringer, G., Meira- Neto, J. A. A., Buttschardt, T. K., 5, 1–16. https://doi. org/10.3389/fenvs.2017.00044, , 2017

175. Evaluation of algal chlorophyll and nutrient relations and the N:P ratios along with trophic status and light regime in 60 Korea reservoirs, Kwon, S., An, K. G., Mamun, M., Kim, J. E., 741, 140451. https://doi. org/10.1016/j. scitotenv.2020.140451, , 2020

176. The framework for the assessment of river and wetland health (FARWH) for flowing rivers of south-west Western Australia: method development, Storer, T., White, G., Galvin, L., K, O., van Looij, E., Kitsios, A., Final report Water Science Technical Series, report no. 40, , 2010

177. Assessment of surface water quality using multivariate statistical techniques: case study of the Nampong River and Songkhram River, Thailand, Muangthong, S., Shrestha, S., 187. https://doi. org/10.1007/s10661-015-4774-1, , 2015

178. Application of multivariate statistical techniques in the assessment of water quality in the Southwest New Territories and Kowloon, Hong Kong, Wu, J., Wang, Q., Yu, M., Zhang, X., Liu, Y., 173, 17–27. https://doi. org/10.1007/s10661-010-1366-y, , 2011

179. Applying an artificial neural network (ANN) to assess soil salinity and temperature variability in agricultural areas of a mountain catchment, Ryczek, M., Radecki-Pawlik, A., Kruk, E., Młyński, D., Halecki, W., 26, 2545–2554. https://doi. org/10.15244/pjoes/70925, , 2017

180. Analysis of spatiotemporal variation in river water quality using clustering techniques: a case study in the Yeongsan River, Republic of Korea, Lee, K. H., Ryu, H. S., Kim, K., Hwang, S. H., Kang, T. W., 27, 29327–29340. https://doi. org/10.1007/s11356-020-09276-0, , 2020

181. Water quality assessment and apportionment of pollution sources of Gomti river (India) using multivariate statistical techniques - A case study, Sinha, S., Malik, A., Singh, K. P., 538, 355–374. https://doi. org/10.1016/j. aca.2005.02.006, , 2005

182. Aquatic ecosystem health assessment of a typical sub-basin of the Liao River based on entropy weights and a fuzzy comprehensive evaluation method, Li, F., Wang, Y., Chen, J., Liu, Z., 9, 1–13. https://doi. org/10.1038/s41598-019-50499- 0, , 2019

183. Responses of chlorophyll-a, organic matter, and macroinvertebrates to nutrient additions in rivers flowing through agricultural and forested land, Corkum, L.., 136, 391–411, , 1996

184. Water quality assessment and apportionment of pollution sources of Tigris River (Turkey) using multivariate statistical techniques - a case study, Gokot, B., Şen, B., Varol, M, Bekleyen, A., 28, 1428–1438. https://doi. org/10.1002/rra.1533, , 2012

185. Effects of domestic and industrial effluent discharges into the lake and their impact on the drinking water in Pandravedu village, Tamil Nadu, India, Sophia, J. D., Mudgal, B. V., Hemamalini, J., 19, 225–231. https://doi. org/10.30955/gnj.001897, , 2017

186. Assessing positive matrix factorization model fit: A new method to estimate uncertainty and bias in factor contributions at the measurement time scale, Hemann, J. G., Hannigan, M. P., Miller, S. L., Brinkman, G. L., Milford, J. B., Dutton, S. J., 9, 497–513. https://doi. org/10.5194/acp-9-497-2009, , 2009

187. Changes in hydrology, water quality, and algal blooms in a freshwater system impounded with engineered structures in a temperate monsoon river estuary, Lee, H., Sin, Y., 32, 100744. https://doi. org/10.1016/j. ejrh.2020.100744, , 2020

188. Aquatic ecosystem health and trophic status classification of the Bitter Lakes along the main connecting link between the Red Sea and the Mediterranean, Al- Farraj, S. A., El-Serehy, H. A., Irshad, R., Almalki, E. S., Abdallah, H. S., Al-Misned, F. A., 25, 204–212. https://doi. org/10.1016/j. sjbs.2017.12.004, , 2018

189. Water quality assessment and apportionment of pollution sources using APCSMLR and PMF receptor modeling techniques in three major rivers of South Florida, Gholizadeh, M. H., Melesse, A. M., Reddi, L., 566–567, 1552–1567. https://doi. org/10.1016/j. scitotenv.2016.06.046, , 2016

190. Relationships between nutrient, chlorophyll a and Secchi depth in lakes of the Chinese Eastern Plains ecoregion: Implications for eutrophication management, Zou, W., Zhu, G., Cai, Y., Vilmi, A., Xu, H., Zhu, M., Gong, Z., Zhang, Y., Qin, B., 260, , 2020

191. Development of early-warning protocol for predicting chlorophyll-a concentration using machine learning models in freshwater and estuarine reservoirs, Korea, Kim, J. H., Cha, S. M., Park, Y., Park, J., Cho, K. H., 502, 31–41. https://doi. org/10.1016/j. scitotenv.2014.09.005, , 2015

192. Integrative assessments of a temperate stream based on a multimetric determination of biological integrity, physical habitat evaluations, and toxicity tests, Kong, D. S., Kim, D. S., An, K. G., Kim, S. D., 73, 471–478. https://doi. org/10.1007/s00128-004-0453-6, , 2004

193. Use of water quality index and multivariate statistical methods for the evaluation of water quality of a stream affected by multiple stressors: A case study, Varol, M., 266, 115417. https://doi. org/10.1016/j. envpol.2020.115417, , 2020

194. Effects of land use, topography and socioeconomic factors on river water quality in a mountainous watershed with intensive agricultural production in East China, Lu, J., Chen, J., 9, 1–12. https://doi. org/10.1371/journal. pone.0102714, , 2014

195. Assessment of aquatic ecological health based on determination of biological community variability of fish and macroinvertebrates in the Weihe River Basin, China, Mao, R., Song, J., Xia, J., Sun, H., Wu, J., Li, M., Cheng, D., 267, 110651. https://doi. org/10.1016/j. jenvman.2020.110651, , 2020

196. Limnological study on springbloom of a green algae, Eudorina elegans and weirwater pulsed flows in the midstream (Seungchon Weir Pool) of the Yeongsan River, Korea, Shin, J., Kang, B., Hwang, S., 49, 320–333. https://doi. org/https://doi. org/10.11614/KSL.2016.49.4.320, , 2016

197. Empirical estimation of nonchlorophyll light attenuation in Missouri reservoirs using deviation from the maximum observed value in the Secchi- Chlorophyll relationship, Jones, J. R., Hubbart, J. A., 27, 1–5. https://doi. org/10.1080/07438141.2011.554962, , 2011

198. Statistical assessment of water quality parameters for pollution source identification in sukhnag stream: an inflow stream of Lake Wular (Ramsar Site), Kashmir Himalaya, Meraj, G., Yaseen, S., Bhat, S. A., Pandit, A. K., 1–18. https://doi. org/10.1155/2014/898054, , 2014

199. Application of the chemometric approach to evaluate the spatial variation of water chemistry and the identification of the sources of pollution in Langat River, Malaysia, Lim, W. Y., Praveena, S. M., Aris, A. Z., 6, 4891–4901. https://doi. org/10.1007/s12517-012-0756-6, , 2013

200. Development and application of a fish-based Sensitivityweighted Index of Biotic Integrity (SIBI) for use in the assessment of biotic integrity in the Klip River, Gauteng, South Africa, Kotze, P. J., Steyn, G. J., Du Preez, H. H., Kleynhans, C. J., 29 129–143. https://doi. org/10.2989/16085910409503805, , 2004

201. Application of multivariate statistical techniques and water quality index for the assessment of water quality and apportionment of pollution sources in the yeongsan river, south korea, An, K. G., Mamun, M., 18, 1–23. https://doi. org/10.3390/ijerph18168268, , 2021

202. Monitoring spatiotemporal variations in nutrients in a large drinking water reservoir and their relationships with hydrological and meteorological conditions based on Landsat 8 imagery, Zhou, Y., Zhang, Yibo, Zhang, Yunlin, Shi, K., Zhu, G., Li, Y., Guo, Y., 599–600, 1705–1717. https://doi. org/10.1016/j. scitotenv.2017.05.075, , 2017

203. Guidelines of lake management: volume 9 reservoir water quality management Temporal trend and source apportionment of water pollution in different functional zones of Qiantang River, China, Huang, F., Tundisi, G., Li, D., report Vol 9, Zhang, Q., Su, S., Xiao, R., Wu, J., Straskraba, M., 45, 1781– 1795. https://doi. org/10.1016/j. watres.2010.11.030, , 1999

204. Predictive models for the biomass of blue-green algae in lakes times with the poisoning of livestock and domestic animals found in five sources ( Table 1 ): three limnocorrals in the Bay l., Smith, V. H., Smith, L. H., 21, 433– 439, , 1985

205. Soil organic matter and its role in crop production An Evaluation on Health Conditions of Pyong-Chang River using the Index of Biological Integrity (IBI) and Qualitative Habitat Evaluation Index (QHEI), An, K.-G., Jung, S.-H., Choi, S.-S., Allison, F., 34, 153~165, , 1973

206. Long-term interannual and seasonal links between the nutrient regime, sestonic chlorophyll and dominant bluegreen algae under the varying intensity of monsoon precipitation in a drinking water reservoir, Kim, J. Y., An, K. G., Atique, U., Mamun, M., 18, 1–25. https://doi. org/10.3390/ijerph18062871, , 2021

207. Probablistic methods in lake managment. models and software for reservoir eutrophication assessment An empirical analysis of phosphorus, nitrogen, and turbidity effects on reservoir chlorophyll-A levels, Walker, W. W., Walker, W. W., 7, 88–107. https://doi. org/10.4296/cwrj0701088, , 1986

208. Application of water quality index (WQI) as a possible indicator for agriculture purpose and assessing the ability of self purification process by Qalyasan stream in Sulamani City/Iraqi Kurdistan Region (IKR), Ahmed, I., Salih, N., HA, Z., YH., N., 5, 162–173, , 2015

209. Fish and benthic macroinvertebrate assemblages as indicators of stream degradation in urbanizing watersheds, in: simon, t. p. (ed.), biological response signatures: indicator patterns using aquatic communities, Wang, L., Lyons, J., pp. 227–250, , 2003