Environmental Flows Assessment in Nepal: The Case of Kaligandaki River
Abstract
:1. Introduction
1.1. Overview of E-Flow Concept
1.2. Environmental Flows Practices in Nepal
2. Materials and Method
2.1. Study Area
2.2. Methodology
2.2.1. Annual Distribution Method
2.2.2. Global Environmental Flow Calculator
2.2.3. Flow Duration Curve Analysis
2.2.4. Tennant Method
2.2.5. Dynamic Methods
2.2.6. Mean Annual Flow
2.2.7. Indicators of Hydrological Alteration (IHA) and Global Indexes
2.2.8. Environmental Flow Components
2.2.9. Limitations of the Methodology
3. Results
3.1. E-Fows Allocation
3.2. Interannual and Seasonal E-Flows Characterization
3.3. Flow Regime Alteration
3.3.1. IHA Alteration
3.3.2. E-flows Components (EFC)
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
IHA Parameters | Mean | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
30% Q-D | 10% MAF | Q80% | Q85% | Q90% | ADM | Class B | Class C | Class D | Class E | Class F | Tennant | |
Group #1 | ||||||||||||
July | 0.70 | 0.96 | 0.96 | 0.96 | 0.96 | 0.46 | 0.82 | 0.87 | 0.91 | 0.93 | 0.94 | 0.89 |
August | 0.70 | 0.97 | 0.97 | 0.97 | 0.97 | 0.46 | 0.85 | 0.90 | 0.92 | 0.94 | 0.95 | 0.91 |
September | 0.70 | 0.95 | 0.95 | 0.95 | 0.96 | 0.54 | 0.79 | 0.85 | 0.89 | 0.92 | 0.93 | 0.87 |
October | 0.70 | 0.90 | 0.89 | 0.90 | 0.91 | 0.50 | 0.54 | 0.68 | 0.77 | 0.82 | 0.85 | 0.79 |
November | 0.70 | 0.80 | 0.78 | 0.80 | 0.81 | 0.50 | 0.12 | 0.35 | 0.53 | 0.63 | 0.69 | 0.79 |
December | 0.70 | 0.70 | 0.68 | 0.70 | 0.72 | 0.50 | 0.03 | 0.10 | 0.30 | 0.45 | 0.54 | 0.70 |
January | 0.70 | 0.62 | 0.58 | 0.61 | 0.63 | 0.50 | 0.05 | 0.06 | 0.14 | 0.29 | 0.40 | 0.62 |
February | 0.70 | 0.55 | 0.51 | 0.54 | 0.57 | 0.52 | 0.05 | 0.06 | 0.08 | 0.18 | 0.29 | 0.55 |
March | 0.70 | 0.50 | 0.45 | 0.49 | 0.52 | 0.49 | 0.04 | 0.05 | 0.06 | 0.14 | 0.23 | 0.50 |
April | 0.70 | 0.54 | 0.50 | 0.54 | 0.56 | 0.46 | 0.04 | 0.06 | 0.10 | 0.20 | 0.30 | 0.35 |
May | 0.70 | 0.69 | 0.66 | 0.68 | 0.70 | 0.34 | 0.05 | 0.14 | 0.29 | 0.42 | 0.51 | 0.19 |
June | 0.70 | 0.89 | 0.88 | 0.88 | 0.89 | 0.43 | 0.51 | 0.64 | 0.73 | 0.79 | 0.82 | 0.67 |
Group #2 | ||||||||||||
1-day minimum | 0.70 | 1.10 | 0.09 | 0.07 | 0.06 | 0.02 | 0.69 | 0.00 | 0.00 | 0.02 | 0.06 | 0.32 |
3-day minimum | 0.70 | 0.39 | 0.34 | 0.38 | 0.42 | 0.42 | 1.00 | 1.00 | 0.00 | 0.03 | 0.10 | 0.39 |
7-day minimum | 0.70 | 0.41 | 0.35 | 0.40 | 0.43 | 0.42 | 1.00 | 0.00 | 0.00 | 0.04 | 0.11 | 0.41 |
30-day minimum | 0.70 | 0.46 | 0.41 | 0.45 | 0.48 | 0.46 | 1.00 | 0.02 | 0.03 | 0.09 | 0.18 | 0.46 |
90-day minimum | 0.70 | 0.51 | 0.47 | 0.50 | 0.53 | 0.47 | 1.00 | 0.03 | 0.05 | 0.14 | 0.24 | 0.51 |
1-day maximum | 0.70 | 0.99 | 0.99 | 0.99 | 0.99 | 0.64 | 1.00 | 0.96 | 0.97 | 0.98 | 0.98 | 0.97 |
3-day maximum | 0.70 | 0.99 | 0.98 | 0.98 | 0.99 | 0.59 | 0.93 | 0.95 | 0.96 | 0.97 | 0.98 | 0.96 |
7-day maximum | 0.70 | 0.98 | 0.98 | 0.98 | 0.98 | 0.53 | 0.91 | 0.94 | 0.95 | 0.96 | 0.97 | 0.94 |
30-day maximum | 0.70 | 0.97 | 0.97 | 0.97 | 0.97 | 0.51 | 0.87 | 0.91 | 0.94 | 0.95 | 0.96 | 0.92 |
90-day maximum | 0.70 | 0.96 | 0.96 | 0.96 | 0.96 | 0.49 | 0.83 | 0.88 | 0.91 | 0.93 | 0.94 | 0.89 |
Number of zero days | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
Base flow index | 0 | 4.580357 | 0.0008 | 0.000801 | 0 | 0.8071 | 1.455677 | 0.255647 | 0.253194 | 0.184867 | 0.080163 | 0.452621 |
Group #3 | ||||||||||||
Date of minimum | 0.000 | 0.94 | 0.90 | 0.94 | 0.94 | 0.05 | 0.00 | 0.000 | 0.000 | 0.148 | 0.475 | 1.000 |
Date of maximum | 0.00 | 0.18 | 0.18 | 0.18 | 0.18 | 0.03 | 0.18 | 0.18 | 0.185 | 0.178 | 0.178 | 0.183 |
Group #4 | ||||||||||||
Low pulse count | 0 | 1 | 0.988495 | 1 | 1 | 0.709692 | 0 | 0.067454 | 0.272659 | 0.580616 | 0.736016 | 1 |
Low pulse duration | 0.00 | 1.00 | 0.91 | 1.00 | 1.00 | 0.41 | 0.00 | 0.09 | 0.56 | 0.61 | 0.75 | 1.00 |
High pulse count | 0.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.29 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.44 |
High pulse duration | 0.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.46 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 4.56 |
Low Pulse Threshold | 0.70 | 0.57 | 0.53 | 0.56 | 0.59 | 0.45 | 0.01 | 0.05 | 0.14 | 0.25 | 0.34 | 1.00 |
High Pulse Threshold | 0.70 | 0.96 | 0.95 | 0.96 | 0.96 | 0.52 | 0.79 | 0.85 | 0.89 | 0.92 | 0.93 | 0.88 |
Group #5 | ||||||||||||
Rise rate | 0.70 | 1.00 | 0.99 | 1.00 | 1.00 | 0.67 | 0.91 | 0.93 | 0.96 | 0.97 | 0.98 | 0.86 |
Fall rate | 0.70 | 1.00 | 0.99 | 1.00 | 1.00 | 0.63 | 0.90 | 0.92 | 0.94 | 0.95 | 0.97 | 0.68 |
Number of reversals | 0.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.08 | 0.44 | 0.53 | 0.69 | 0.86 | 0.94 | 0.87 |
References
- Couto, T.B.; Olden, J.D. Global Proliferation of Small Hydropower Plants—Science and Policy. Front. Ecol. Environ. 2018, 16, 91–100. [Google Scholar] [CrossRef]
- Karimi, S.S.; Yasi, M.; Eslamian, S. Use of Hydrological Methods for Assessment of Environmental Flow in a River Reach. Int. J. Environ. Sci. Technol. 2012, 9, 549–558. [Google Scholar] [CrossRef] [Green Version]
- Kuriqi, A.; Ali, R.; Pham, Q.B.; Gambini, J.M.; Gupta, V.; Malik, A.; Linh, N.T.T.; Joshi, Y.; Anh, D.T.; Nam, V.T.; et al. Seasonality Shift and Streamflow Flow Variability Trends in Central India. Acta Geophys. 2020, 68, 1461–1475. [Google Scholar] [CrossRef]
- Ali, R.; Kuriqi, A.; Abubaker, S.; Kisi, O. Long-Term Trends and Seasonality Detection of the Observed Flow in Yangtze River Using Mann-Kendall and Sen’s Innovative Trend Method. Water 2019, 11, 1855. [Google Scholar] [CrossRef] [Green Version]
- Huang, X.; Suwal, N.; Fan, J.; Pandey, K.P.; Jia, Y. Hydrological Alteration Assessment by Histogram Comparison Approach: A Case Study of Erdu River Basin, China. J. Coast. Res. 2019, 93, 139–145. [Google Scholar] [CrossRef]
- Gao, Y.; Pandey, K.P.; Huang, X.; Suwal, N.; Bhattarai, K.P. Estimation of Hydrologic Alteration in Kaligandaki River Using Representative Hydrologic Indices. Water 2019, 11, 688. [Google Scholar]
- Suwal, N.; Huang, X.; Pandey, K.P.; Bhattarai, K.P. Assessment of Hydrological Alteration and Selection of Representative Hydrological Indicators in Erdu River. In Proceedings of the ICWRER 2019, Nanjing, China, 14–18 June 2019. [Google Scholar]
- Tharme, R.E. A Global Perspective on Environmental Flow Assessment: Emerging Trends in the Development and Application of Environmental Flow Methodologies for Rivers. River Res. Appl. 2003, 19, 397–441. [Google Scholar] [CrossRef]
- Kuriqi, A.; Pinheiro, A.N.; Sordo-Ward, A.; Garrote, L. Water-Energy-Ecosystem Nexus: Balancing Competing Interests at a Run-of-River Hydropower Plant Coupling a hydrologic–ecohydraulic Approach. Energy Convers. Manag. 2020, 223, 113267. [Google Scholar] [CrossRef]
- Ali, R.; Kuriqi, A.; Abubaker, S.; Kisi, O. Hydrologic Alteration at the Upper and Middle Part of the Yangtze River, China: Towards Sustainable Water Resource Management Under Increasing Water Exploitation. Sustainability 2019, 11, 5176. [Google Scholar] [CrossRef] [Green Version]
- Li, Q.; Gleeson, T.; Zipper, S.C.; Kerr, B. Too Many Streams and Not Enough Time or Money? New Analytical Depletion Functions for Rapid and Accurate Streamflow Depletion Estimates. OSF Preprints 2020. Available online: https://osf.io/gfhym (accessed on 21 October 2020).
- Dyson, M.; Bergkamp, G.; Scanlon, J. Flow: The Essentials of Environmental Flows; IUCN: Gland, Switzerland; Cambridge, UK, 2003; pp. 20–87. [Google Scholar]
- Smakhtin, V.; Eriyagama, N. Developing a Software Package for Global Desktop Assessment of Environmental Flows. Environ. Model. Softw. 2008, 23, 1396–1406. [Google Scholar] [CrossRef]
- Arthington, A.H.; Bhaduri, A.; Bunn, S.E.; Jackson, S.E.; Tharme, R.E.; Tickner, D.; Young, B.; Acreman, M.; Baker, N.; Capon, S.; et al. The Brisbane Declaration and Global Action Agenda on Environmental Flows. Front. Environ. Sci. 2018, 6, 6. [Google Scholar] [CrossRef] [Green Version]
- Pittock, J.; Lankford, B.A. Environmental Water Requirements: Demand Management in an Era of Water Scarcity. J. Integr. Environ. Sci. 2010, 7, 75–93. [Google Scholar] [CrossRef]
- Xu, H.; Lee, U.; Coleman, A.M.; Wigmosta, M.S.; Sun, N.; Hawkins, T.R.; Wang, M.Q. Balancing Water Sustainability and Productivity Objectives in Microalgae Cultivation: Siting Open Ponds by Considering Seasonal Water-Stress Impact Using AWARE-US. Environ. Sci. Technol. 2020, 54, 2091–2102. [Google Scholar] [CrossRef] [PubMed]
- De Graaf, I.E.M.; Gleeson, T.; Van Beek, L.P.H.R.; Sutanudjaja, E.H.; Bierkens, M.F.P. Environmental Flow Limits to Global Groundwater Pumping. Nat. Cell Biol. 2019, 574, 90–94. [Google Scholar] [CrossRef]
- Gleeson, T.; Richter, B. How Much Groundwater Can We Pump and Protect Environmental Flows through Time? Presumptive Standards for Conjunctive Management of Aquifers and Rivers. River Res. Appl. 2017, 34, 83–92. [Google Scholar] [CrossRef]
- Jowett, I.G. Instream Flow Methods: A Comparison of Approaches. Regul. Rivers Res. Manag. 1997, 13, 115–127. [Google Scholar] [CrossRef]
- Williams, J.G.; Moyle, P.B.; Webb, J.A.; Kondolf, G.M. Environmental Flow Assessment: Methods and Applications; John Wiley & Sons: Hoboken, NJ, USA, 2019. [Google Scholar]
- Lumbroso, D.M.; Sakamoto, D.; Johnstone, W.M.; Tagg, A.F.; Lence, B.J. Development of a Life Safety Model to Estimate the Risk Posed to People by Dam Failures and Floods. Dams Reserv. 2011, 21, 31–43. [Google Scholar] [CrossRef] [Green Version]
- Acreman, M.C.; Dunbar, M.J. Defining Environmental River Flow Requirements—A Review. Hydrol. Earth Syst. Sci. 2004, 8, 861–876. [Google Scholar] [CrossRef]
- Shokoohi, A.; Hong, Y. Using Hydrologic and Hydraulically Derived Geometric Parameters of Perennial Rivers to Determine Minimum Water Requirements of Ecological Habitats (case Study: Mazandaran Sea Basin-Iran). Hydrol. Process. 2011, 25, 3490–3498. [Google Scholar] [CrossRef]
- Fuladipanah, M.; Jorabloo, M. Hydrological Method to Evaluate Environmental Flow (case Study: Gharasou River, Ardabil). Int. J. Environ. Ecol. Eng. 2015, 9, 62–65. [Google Scholar]
- Dubey, A.; Singh, O.; Shekhar, S.; Pohshna, C. Assessment of Environmental Flow Requirement Using Environmental Management Classes-Flow Duration Curve for Narmada River. Int. J. Curr. Microbiol. Appl. Sci. 2019, 8, 891–897. [Google Scholar] [CrossRef]
- Pandey, K.P. Study on Hydrologic Alteration and Alteration Parameter Reduction Methods. Master’s Dissertation, Hohai University, Nanjing, China, 2019. [Google Scholar]
- Smakhtin, V.U.; Shilpakar, R.L.; Hughes, D.A. Hydrology-Based Assessment of Environmental Flows: An Example from Nepal. Hydrol. Sci. J. 2006, 51, 207–222. [Google Scholar] [CrossRef] [Green Version]
- Suwal, N. Research on Optimal Operation of Cascade Hydropower Stations Considering Ecological Flows. Master’s Dissertation, Hohai University, Nanjing, China, 2019. [Google Scholar]
- Młyński, D.; Operacz, A.; Walega, A. Sensitivity of Methods for Calculating Environmental Flows Based on Hydrological Characteristics of Watercourses Regarding the Hydropower Potential of Rivers. J. Clean. Prod. 2020, 250, 119527. [Google Scholar] [CrossRef]
- Operacz, A.; Wałęga, A.; Cupak, A.; Tomaszewska, B. The Comparison of Environmental Flow Assessment—The Barrier for Investment in Poland or River Protection? J. Clean. Prod. 2018, 193, 575–592. [Google Scholar] [CrossRef]
- Suwal, N.; Huang, X.; Kuriqi, A.; Chen, Y.; Pandey, K.P.; Bhattarai, K.P. Optimisation of Cascade Reservoir Operation Considering Environmental Flows for Different Environmental Management Classes. Renew. Energy 2020, 158, 453–464. [Google Scholar] [CrossRef]
- Pastor, A.V.; Ludwig, F.; Biemans, H.; Hoff, H.; Kabat, P. Accounting for Environmental Flow Requirements in Global Water Assessments. Hydrol. Earth Syst. Sci. 2014, 18, 5041–5059. [Google Scholar] [CrossRef] [Green Version]
- Smakhtin, V.; Anputhas, M. An Assessment of Environmental Flow Requirements of Indian River Basins; IWMI: Colombo, Sri Lanka, 2006; Volume 107. [Google Scholar]
- Poff, N.L.; Tharme, R.E.; Arthington, A.H. Evolution of Environmental Flows Assessment Science, Principles, and Methodologies. In Water for the Environment; Academia Press: Cambridge, MA, USA, 2017; pp. 203–236. [Google Scholar]
- Gaudel, P. Environmental Assessment of Hydropower Development in Nepal: Current Practices and Emerging Challenges. Vidyut. Febraury 2015. Available online: https://www.researchgate.net/publication/316080737_Environmental_Assessment_of_Hydropower_Development_in_Nepal_Current_Practices_and_Emerging_Challenges (accessed on 21 October 2020).
- Doody, T.; Cuddy, S.; Bhatta. Connecting Flow and Ecology in Nepal: Current State of Knowledge for the Koshi Basin; Sustainable Development Investment Portfolio (SDIP) Project; CSIRO: Canberra, Australia, 2016. [Google Scholar]
- Oglethorpe, J.; Regmi, S.; Bartlett, R.; Dongol, B.S.; Wikramanayake, E.; Freeman, S.J.O. The Value of a River Basin Approach in Climate Adaptation. In Proceedings of the International Conference on Climate Change Innovation and Resilience for Sustainable Livelihoods, Kathmandu, Nepal, 12–14 January 2015. [Google Scholar]
- Gubhaju, S.R. Impact of Damming on the Aquatic Fauna in Nepalese Rivers. In Cold Water Fisheries in Thetrans-Himalayan Countries; Petr, T., Swar, S.B., Eds.; Food and Agriculture Organization of the United Nations: Rome, Italy, 2002; pp. 129–145. [Google Scholar]
- Panta, S.K.; Resurrección, B.P. Gender and Caste Relations Amidst a Changing Political Situation in Nepal: Insights from a Farmer-Managed Irrigation System. Gender Technol. Dev. 2014, 18, 219–247. [Google Scholar] [CrossRef]
- International Hydropower, A. Hydropower Status Report: Sector Trends and Insights; IHA: London, UK, 2018. [Google Scholar]
- Jalsrot Vikas Sanstha; GWP Nepal. Assessment of the Environmental Flow in the Gandaki River Basin: A Case of Modi Khola; Jalsrot Vikas Sanstha: Kathmandu, Nepal; GWP Nepal: Hetauda, Nepal, 2016. [Google Scholar]
- Rijal, N.; Shrestha, H.K.; Bruins, B. Environmental Flow Assessment of Hewa Khola A and Lower Hewa Khola Hydropower Projects in Nepal. Hydro Nepal J. Water Energy Environ. 2018, 23, 71–78. [Google Scholar] [CrossRef]
- Zha-Rong, P.A.N.; Xiao-Hong, R.U.A.N.; Jing, X.U. A New Calculation Method of Instream Basic Ecological Water Demand. J. Hydraul. Eng. 2013, 44, 119–126. [Google Scholar]
- Zhang, H.; Chang, J.; Gao, C.; Wu, H.; Wang, Y.; Lei, K.; Long, R.; Zhang, L. Cascade Hydropower Plants Operation Considering Comprehensive Ecological Water Demands. Energy Convers. Manag. 2019, 180, 119–133. [Google Scholar] [CrossRef]
- Tennant, D.L. Instream Flow Regimens for Fish, Wildlife, Recreation and Related Environmental Resources. Fish 1976, 1, 6–10. [Google Scholar] [CrossRef]
- Wałęga, A.; Mlynski, D.; Kokoszka, R.; Miernik, W. Possibilities of Applying Hydrological Methods for Determining Environmental Flows in Select Catchments of the Upper Dunajec Basin. Pol. J. Environ. Stud. 2015, 24, 2663–2676. [Google Scholar] [CrossRef]
- Kuriqi, A.; Pinheiro, A.N.; Sordo-Ward, A.; Garrote, L. Influence of Hydrologically Based Environmental Flow Methods on Flow Alteration and Energy Production in a Run-of-River Hydropower Plant. J. Clean. Prod. 2019, 232, 1028–1042. [Google Scholar] [CrossRef]
- Kuriqi, A.; Pinheiro, A.N.; Sordo-Ward, A.; Garrote, L. Flow Regime Aspects in Determining Environmental Flows and Maximizing Energy Production at Run-of-River Hydropower Plants. Appl. Energy 2019, 256, 113980. [Google Scholar] [CrossRef]
- Bejarano, M.; Sordo-Ward, A.; Gabriel-Martin, I.; Garrote, L. Tradeoff Between Economic and Environmental Costs and Benefits of Hydropower Production at Run-of-River-Diversion Schemes under Different Environmental Flows Scenarios. J. Hydrol. 2019, 572, 790–804. [Google Scholar] [CrossRef]
- Richter, B.D.; Baumgartner, J.V.; Powell, J.; Braun, D.P. A Method for Assessing Hydrologic Alteration Within Ecosystems. Conserv. Biol. 1996, 10, 1163–1174. [Google Scholar] [CrossRef] [Green Version]
- Mathews, R.; Richter, B.D. Application of the Indicators of Hydrologic Alteration Software in Environmental Flow Setting1. JAWRA J. Am. Water Resour. Assoc. 2007, 43, 1400–1413. [Google Scholar] [CrossRef]
- Olden, J.D.; Poff, N.L. Redundancy and the Choice of Hydrologic Indices for Characterizing Streamflow Regimes. River Res. Appl. 2003, 19, 101–121. [Google Scholar] [CrossRef]
- Fausch, K.D.; Bestgen, K.R. Ecology of Fishes Indigenous to the Central and Southwestern Great Plains. In Ecological Studies; Springer: New York, NY, USA, 1997; pp. 131–166. [Google Scholar]
- Rood, S.B.; Mahoney, J.M. River Damming and Riparian Cottonwoods along the Marias River, Montana. Rivers 1995, 5, 195–207. [Google Scholar]
- Richter, B.; Baumgartner, J.; Wigington, R.; Braun, D. How Much Water Does a River Need? Freshw. Biol. 1997, 37, 231–249. [Google Scholar] [CrossRef] [Green Version]
- Richter, B.D.; Baumgartner, J.V.; Braun, D.P.; Powell, J. A Spatial Assessment of Hydrologic Alteration within a River Network. Regul. Rivers Res. Manag. 1998, 14, 329–340. [Google Scholar] [CrossRef]
- Książek, L.; Woś, A.; Florek, J.; Wyrębek, M.; Młyński, D.; Wałęga, A. Combined Use of the Hydraulic and Hydrological Methods to Calculate the Environmental Flow: Wisloka River, Poland: Case Study. Environ. Monit. Assess. 2019, 191, 254. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Młyński, D.; Wałęga, A.; Ozga-Zielinski, B.; Ciupak, M.; Petroselli, A. New Approach for Determining the Quantiles of Maximum Annual Flows in Ungauged Catchments Using the EBA4SUB Model. J. Hydrol. 2020, 589, 125198. [Google Scholar] [CrossRef]
- Cushman, R.M. Review of Ecological Effects of Rapidly Varying Flows Downstream from Hydroelectric Facilities. North Am. J. Fish. Manag. 1985, 5, 330–339. [Google Scholar] [CrossRef]
- Verma, R.K.; Murthy, S.; Verma, S.; Mishra, S.K. Design Flow Duration Curves for Environmental Flows Estimation in Damodar River Basin, India. Appl. Water Sci. 2016, 7, 1283–1293. [Google Scholar] [CrossRef] [Green Version]
- Vogel, R.M.; Fennessey, N.M. Flow-Duration Curves. I: New Interpretation and Confidence Intervals. J. Water Resour. Plan. Manag. 1994, 120, 485–504. [Google Scholar] [CrossRef]
- Searcy, J.K. Flow-Duration Curves; manual of hydrology. Part 2. US Geol. Survey Water Supply Paper 1542-A., Low flow techniques; United States Government Printing Office: Washington, DC, USA, 1959. [Google Scholar]
- Jain, S.K.; Kumar, P. Environmental Flows in India: Towards Sustainable Water Management. Hydrol. Sci. J. 2014, 59, 751–769. [Google Scholar] [CrossRef] [Green Version]
Method Category | Resolution Level | Ecosystem | Time | Cost |
---|---|---|---|---|
Hydrologic | Very Low/Low | River | Short | Less |
Hydraulic rating | Low | River | Short/Long | Less/Medium |
Habit simulation | Medium/High | River | Medium/Long | Medium/High |
Holistic | High | Wetland, floodplains, | Long | High |
Name | Details |
---|---|
Elevation | 190 m to 8168 m |
Total catchment area | 11.851 km2 |
Location | 82°52.8′ E to 84°26.3′ E, 27°43.2′ N to 29°19.8′ N |
Mean annual precipitation | 1396 mm |
Flow data Series | 1 January 1964–31 December 2015 |
Min flow (m3/s) | 46 |
Mean flow (m3/s) | 449.7 |
Max flow (m3/s) | 6840 |
Min average monthly flow (m3/s) 10% of min average monthly flow (m3/s) | 90 9 |
EMC | Most likely Ecological Condition | Management Perspective |
---|---|---|
A (Natural) | Same as natural rivers with insignificant modification of instream and riparian habitat | Protected rivers and basins. Reserves and national parks. No new water projects (dams, diversions, etc.) allowed. |
B (Slightly modified) | Largely intact biodiversity and habitats despite anthropogenic activities (dam, diversion, basin modifications) | Water supply schemes or irrigation development present and/or allowed. |
C (Moderately modified) | The biota’s habitats and movement have been impacted, but essential ecosystem functions are still unmodified; some sensitive species are vanished and/or reduced in extent; alien species survived. | Multiple disturbances (for instance, dams, diversions, habitat modification, and reduced water quality) related to the need for socio-economic development |
D (Largely modified) | Substantial changes in natural habitat, biota, and essential ecosystem functions have occurred; a lower than expected species richness; the much-lowered presence of intolerant species; alien species prevail. | Significant and precise visible disturbances (such as dams, diversions, transfers, habitat modification, and water quality degradation) associated with basin and water resources development |
E (Seriously modified) | Habitat diversity and availability have declined; species richness is strikingly lower than expected; only tolerant species remain; indigenous species can no longer breed; alien species have invaded the ecosystem. | High human population density and extensive water resources exploitation. This class is not suitable as a management goal. The management team should move to a higher class to restore the flow pattern of the river. |
F (Critically modified) | Modifications have reached a tipping point; the ecosystem has been completely modified with an almost complete loss of natural habitat and biota; in the worst case, the underlying ecosystem functions have been destroyed, and changes are irreversible. | This status is not acceptable from the management perspective. Management interventions are necessary to restore flow patterns and river habitats (if still possible/feasible) to ‘move’ a river to a higher management category. |
Aquatic-Habitat Condition for Small Stream | Recommended Base Flow (% of MAF) | |
---|---|---|
General Period (October–March) | Fish Spawning Period (April–September) | |
Flushing or maximum | 200% of the average flow | |
Optimum range | 60–100 | 60–100 |
Outstanding | 40 | 60 |
Excellent | 30 | 50 |
Good | 20 | 40 |
Fair or degrading | 10 | 30 |
Poor or minimum | 10 | 10 |
Severe degradation | <10% of average flow to zero flow |
Global Index for Each Group | IHA Parameters | Regime Characteristic (Specific Alteration) | Ecological Significance |
---|---|---|---|
Mean Monthly Flow Alteration Index (Imm) | Group 1: Mean value of each calendar month | Magnitude (increased variation) | Guaranteed favourable habitat conditions and flow regime (quantity, quality, and temperature) for aquatic and terrestrial organisms. Availability of food and cover for fur-bearing mammals. |
Magnitude and Duration of Extreme Flow Alteration Index (IMDE) | Group 2: Annual minima, 1, 3, 7, 30, 90 day means Annual maxima, 1,3,7,30,90 day means Number of zero-flow days Baseflow index: 7 day minimum flow/mean flow for the year | Magnitude and Duration (prolonged low flows; altered inundation duration; prolonged inundation) | Structuring of aquatic ecosystems by abiotic and biotic factors. The shaping of river channel morphology and physical habitat conditions. |
Timing of Extreme Flow Alteration Index (ITE) | Group 3: Julian date of each annual 1 day maximum Julian date of each annual 1 day minimum | Timing (oss of seasonal flow peaks) | Disrupt cues for fish: (spawning, egg hatching, migration) [54]. Evolution of the life history and behaviour mechanism of the aquatic organisms [48]. |
Frequency and Duration Alteration Index (IFD) | Group 4: No. of high pulses each year No. of low pulses each year Mean duration of high pulses within each year (days) Mean duration of low pulses within each year (days) | Frequency and Duration (flow stabilization) | Availability of floodplain habitats for aquatic organisms. Influences bedload transport, channel sediment textures, and duration of substrate disturbance (high pulses). Nutrient and organic matter exchanges between river and floodplain. |
Rate and Frequency Alteration Index (IRF) | Group 5: Means of all positive differences between consecutive daily values Means of all negative differences between consecutive daily values Reversals | Rate of change and Frequency (rapid changes in river stage; accelerated flood recession) | Wash out and stranding of aquatic species [55]. Failure of seedling establishment [56]. |
Range | 0.00–0.25 | 0.25–0.50 | 0.50–0.75 | 0.75–1.00 |
---|---|---|---|---|
Alteration | Low | Mild | Moderate | High |
Method | Classes | (%of MAF) | E-flows (m3/s) | |||||||||
GEFC | Class B | 47.8 | 214.46 | |||||||||
Class C | 32.8 | 147.16 | ||||||||||
Class D | 23.7 | 106.33 | ||||||||||
Class E | 18.6 | 83.45 | ||||||||||
Class F | 15.7 | 70.44 | ||||||||||
Tennant | Oct–Mar | 10 | 44.87 | |||||||||
Apr–Sept | 30 | 134.6 | ||||||||||
FDC | Q80% FDCA, | 49.04 | ||||||||||
Q85% FDCA, | 45.65 | |||||||||||
Q90% FDCA, | 43.05 | |||||||||||
Mean annual flow | 10%MAF | 44.97 | ||||||||||
Dynamic methods | 30%Q-D | 30% of daily flow | ||||||||||
Annual Distribution Method | ||||||||||||
Month | Jan | Feb | March | April | May | June | July | August | Sep | Oct | Nov | Dec |
E-flow (m3/s) | 60.57 | 50.05 | 45.07 | 49.75 | 73.54 | 204.58 | 646.33 | 785.59 | 584.67 | 274.83 | 127.61 | 83.71 |
E-Flows Components (EFC) | Dynamic E-Flows | Minimum Annual | FDC Curve | ADM | Global Environmental Flow Calculator | Tennant | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
EFC Low Flows | 30%Q-D | 10%MAF | Q80% | Q85% | Q90% | Class B | Class C | Class D | Class E | Class F | ||
July—Low Flow | −70 | −100 | −100 | −100 | −100 | −46 | −100 | −100 | −100 | −100 | −100 | −70 |
August—Low Flow | −70 | −100 | −100 | −100 | −100 | −65 | −100 | −100 | −100 | −100 | −100 | −61 |
September—Low Flow | −70 | −100 | −100 | −100 | −100 | −35 | −100 | −100 | −100 | −100 | −100 | −72 |
October—Low Flow | −70 | −100 | −100 | −100 | −100 | −40 | −100 | −100 | −100 | −100 | −100 | −64 |
November—Low Flow | −70 | −100 | −100 | −100 | −100 | −49 | −100 | −100 | −100 | −100 | −100 | −41 |
December—Low Flow | −70 | −100 | −100 | −100 | −100 | −49 | −100 | −100 | −100 | −100 | −100 | −100 |
January—Low Flow | −70 | −100 | −100 | −100 | −100 | −48 | −100 | −100 | −100 | −100 | −100 | −100 |
February—Low Flow | −70 | −100 | −100 | −100 | −100 | −49 | −100 | −100 | −100 | −100 | −100 | −100 |
March—Low Flow | −70 | −100 | −100 | −100 | −100 | −50 | −100 | −100 | −100 | −100 | −100 | −100 |
April—Low Flow | −70 | −100 | −100 | −100 | −100 | −48 | −100 | −100 | −100 | −100 | −100 | −6 |
May—Low Flow | −70 | −100 | −100 | −100 | −100 | −34 | −100 | −100 | −100 | −100 | −100 | −15 |
June—Low Flow | −70 | −100 | −100 | −100 | −100 | −31 | −100 | −100 | −100 | −100 | −100 | −52 |
EFC Parameters | ||||||||||||
Extreme low peak | −70 | −100 | −100 | −100 | −100 | −41 | −100 | −100 | −100 | −100 | −100 | −39 |
Extreme low duration | 0 | −100 | −100 | −100 | −100 | −55 | −100 | −100 | −100 | −100 | −100 | 1393 |
Extreme low timing | 0 | −100 | −100 | −100 | −100 | −3 | −100 | −100 | −100 | −100 | −100 | 234 |
Extreme low freq. | 0 | −100 | −100 | −100 | −100 | 82% | −100 | −100 | −100 | −100 | −100 | −74 |
High flow peak | −70 | −100 | −100 | −100 | −100 | −62 | −100 | −100 | −100 | −100 | −100 | −100 |
High flow duration | 0 | −100 | −100 | −100 | −100 | −30 | −100 | −100 | −100 | −100 | −100 | −100 |
High flow timing | 0 | −100 | −100 | −100 | −100 | 26 | −100 | −100 | −100 | −100 | −100 | −100 |
High flow frequency | 0 | −100 | −100 | −100 | −100 | −2 | −100 | −100 | −100 | −100 | −100 | −100 |
High flow rise rate | −70 | −100 | −100 | −100 | −100 | −74 | −100 | −100 | −100 | −100 | −100 | −100 |
High flow fall rate | −70 | −100 | −100 | −100 | −100 | −81 | −100 | −100 | −100 | −100 | −100 | −100 |
Small Flood peak | −70 | −100 | −100 | −100 | −100 | −68 | −100 | −100 | −100 | −100 | −100 | −100 |
Small Flood duration | 0 | −100 | −100 | −100 | −100 | 11 | −100 | −100 | −100 | −100 | −100 | −100 |
Small Flood timing | 0 | −100 | −100 | −100 | −100 | 6 | −100 | −100 | −100 | −100 | −100 | −100 |
Small Flood frequency | 0 | −100 | −100 | −100 | −100 | −64 | −100 | −100 | −100 | −100 | −100 | −100 |
Small Flood rise rate | −70 | −100 | −100 | −100 | −100 | −96 | −100 | −100 | −100 | −100 | −100 | −100 |
Small Flood fall rate | −70 | −100 | −100 | −100 | −100 | −85 | −100 | −100 | −100 | −100 | −100 | −100 |
Large flood peak | −70 | −100 | −100 | −100 | −100 | −74 | −100 | −100 | −100 | −100 | −100 | −100 |
Large flood duration | 0 | −100 | −100 | −100 | −100 | −18 | −100 | −100 | −100 | −100 | −100 | −100 |
Large flood timing | 0 | −100 | −100 | −100 | −100 | −2 | −100 | −100 | −100 | −100 | −100 | −100 |
Large flood frequency | 0 | −100 | −100 | −100 | −100 | 260 | −100 | −100 | −100 | −100 | −100 | −100 |
Large flood rise rate | −70 | −100 | −100 | −100 | −100 | −88 | −100 | −100 | −100 | −100 | −100 | −100 |
Large flood fall rate | −70 | −100 | −100 | −100 | −100 | −71 | −100 | −100 | −100 | −100 | −100 | −100 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Suwal, N.; Kuriqi, A.; Huang, X.; Delgado, J.; Młyński, D.; Walega, A. Environmental Flows Assessment in Nepal: The Case of Kaligandaki River. Sustainability 2020, 12, 8766. https://doi.org/10.3390/su12218766
Suwal N, Kuriqi A, Huang X, Delgado J, Młyński D, Walega A. Environmental Flows Assessment in Nepal: The Case of Kaligandaki River. Sustainability. 2020; 12(21):8766. https://doi.org/10.3390/su12218766
Chicago/Turabian StyleSuwal, Naresh, Alban Kuriqi, Xianfeng Huang, João Delgado, Dariusz Młyński, and Andrzej Walega. 2020. "Environmental Flows Assessment in Nepal: The Case of Kaligandaki River" Sustainability 12, no. 21: 8766. https://doi.org/10.3390/su12218766
APA StyleSuwal, N., Kuriqi, A., Huang, X., Delgado, J., Młyński, D., & Walega, A. (2020). Environmental Flows Assessment in Nepal: The Case of Kaligandaki River. Sustainability, 12(21), 8766. https://doi.org/10.3390/su12218766