Abstract
Regime-based approach recently becomes an important strategy while considering aquatic ecosystems in environmental flow management. The key element for supporting this strategy is long streamflow data which is usually not available for determining natural flow regimes. This study uses a back-propagation network to estimate ungauged natural flow regimes. A set of the upper reaches of Taiwan’s 42 flow stations with non-human control streamflow and at least 20 years daily flow data is used to quantify the natural flow regimes using 31 Indicators of Hydrologic Alteration (IHA). Watershed geomorphologic characteristic factors and rainfall parameters are used to classify homogeneous flow regime areas. The results show that there are three types of flow regimes from the flow stations, and each group of indicators in the IHA has different correlations with different geomorphologic characteristic factors and rainfall parameters. The results of using an artificial neural network model to estimate IHA show that the group average percent error fell from 21 % to 8 % and the average correlation coefficient was over 0.7, indicating that the model presented in this study is able to accurately estimate the natural flow regime in ungauged stations. Instead of predicting daily streamflow, this study estimates indicator values for ease of ecological water resources management.
Similar content being viewed by others
References
Alcázar J, Palau A, García CV (2008) A neural net model for environmental flow estimation at the Ebro River Basin, Spain. J Hydrol 349:44–55
Arthington AH (1994) A holistic approach to water allocation to maintain the environment values of Australian streams and rivers: a case history. Mitteilung International Vereinigung Limnologie 24:165–177
Ban X, Du Y, Liu HZ, Ling F (2011) ) Applying instream flow incremental method for the spawning habitat protection of Chinese sturgeon (Acipenser sinensis). River Res Appl 27(1):87–98
Bernardo JM, Alves MH (1999) New perspectives for ecological flow determination in semi-arid regions: a preliminary approach. Regul Rivers: Res Manage 15(1–3): 221–229.
Bovee, KD (1982) A guide to stream habitat analysis using instream flow incremental methodology, Instream flow information paper no. 12. U. S. fish and wildlife service, Fort Collins, CO
Bunn SE, Arthington AH (2002) Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ Manag 30(4):492–507
Chang FJ, Yang HC, JY L, Hong JH (2008) Neural network modelling for mean velocity and turbulence intensities of steep channel flows. Hydrol Process 22(2):265–274
Chen CF, Lai MC, Yeh CC (2012) Forecasting tourism demand based on empirical mode decomposition and neural network. Knowl-Based Syst 26:281–287
Chen D, Li R, Chen Q, Cai D (2015) Deriving optimal daily reservoir operation scheme with consideration of downstream ecological hydrograph through a time-nested approach. Water Resour Manag 29(9):3371–3386
Cohen Liechti T, Matos JP, Boillat JL, Schleiss AJ (2015) Influence of hydropower development on flow regime in the Zambezi River basin for different scenarios of environmental flows. Water Resour Manag 29(3):731–747
Crone TM (2005) An alternative definition of economic regions in the United States based on similarities in state business cycles. Rev Econ Stat 87(4):617–626
de Oliveira RP, Matos JS, Monteiro AJ (2015) Managing the urban water cycle in a changing environment. Water Util J 9:3–12
Godinho F, Costa S, Pinheiro P, Reis F, Pinheiro A (2014) Integrated procedure for environmental flow assessment in rivers. Environ Processes 1(2):137–147
Gul A (2015) Comparing past and present hydrologic aspects of a mediterranean wetland from a sustainable management perspective. Water Resour Manag 29(8):2771–2787
Haines AT, Finlayson BL, McMahon TA (1988) A global classification of river regimes. Appl Geogr 8:255–272
Jain SK (2012) Assessment of environmental flow requirements. Hydrol Process 26(22):3472–3476
Kisi O (2011) Modeling reference evapotranspiration using evolutionary neural networks. J Irrig Drain Eng 137(10):636–643
Longobardi A, Villani P (2015) Statistical methods to quantify environmental flow and its variability in a Mediterranean environment. Eur Water 49: 33–41.
Mittal N, Bhave AG, Mishra A, Singh R (2016) Impact of human intervention and climate change on natural flow regime. Water Resour Manag 30(2):685–699
Moran-Tejeda E, Lorenzo-Lacruz J, Lopez-Moreno JI, Ceballos-Barbancho A, Zabalza J, Vicente-Serrano SM (2012) Reservoir management in the Duero Basin (Spain): impact on river regimes and the response to environmental change. Water Resour Manag 26(8):2125–2146
Pahl-Wostl C, Arthington AH, Bogardi J, Bunn SE, Hoff H, Lebel L, Nikitina E, Palmer MA, Poff NL, Richards K, Schlüter M, Schulze R, St-Hilaire A, Tharme R, Tockner K, Tsegai D (2013) Environmental flows and water governance: managing sustainable water uses. Curr Opin Environ Sustain 5(3–4):341–351
Pasha MFK, Yeasmin D, Rentch JW (2015) Dam-lake operation to optimize fish habitat. Environ Processes 2(4):631–645
Perdisci R, Lee W, Feamster N (2010) Behavioral clustering of HTTP-based malware and signature generation using malicious network traces. In NSDI, pp. 391–404.
Peres DJ, Cancelliere A (2016) Environmental flow assessment based on different metrics of hydrological alteration. Water Resour Manag. doi:10.1007/s11269-016-1394-7
Poff NL, Allan JD, Bain MB, Karr JR, Prestegaard KL, Richter BD, Sparks RE, Stromberg JC (1997) The natural flow regime. Bioscience 47(11):769–784
Poff NL, Richter BD, Arthington AH, Bunn SE, Naiman RJ, Kendy E, Acreman M, Apse C, Bledsoe BP, Freeman MC, Henriksen J, Jacobson RB, Kennen J, Merritt DM, O’Keeffe J, Olden JD, Rogers K, Tharme RE, Warner A (2010) The Ecological Limits of Hydrologic Alteration (ELOHA): a new framework for developing regional environmental flow standards. Freshw Biol 55: 147–170.
Pradhan B, Lee S (2010) Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models. Environ Earth Sci 60:1037–1054
Richter BD, Baumgartner JV, Powell J, Braun DP (1996) A method for assessing hydrologic alteration within ecosystems. Conserv Biol 10(4):1163–1174
Richter BD, Baumgartner JV, Wigington R, Braun DP (1997) How much water does a river need? Freshw Biol 37(1):231–249
Richter BD, Warner AT, Meyer JL, Lutz K (2006) ) A collaborative and adaptive process for developing environmental flow recommendations. River Res Appl 22(2):297–318
Roozbahani R, Schreider S, Abbasi B (2013) Economic sharing of basin water resources between competing stakeholders. Water Resour Manag 27(8):2965–2988
Sanborn SC, Bledsoe BP (2006) Predicting streamflow regime metrics for ungauged streams in Colorado, Washington, and Oregon. J Hydrol 325(1–4):241–261
Suen JP (2011) Determining the ecological flow regime for existing reservoir operation. Water Resour Manag 25(3):817–835
Suen JP, Eheart JW (2006) Reservoir management to balance ecosystem and human needs: incorporating the paradigm of the ecological flow regime. Water Resour Res 42(3):W03417
Suen JP, Lai HN (2013) A salinity projection model for determining impacts of climate change on river ecosystems in Taiwan. J Hydrol 493:124–131
Tennant DL (1976) Instream flow regimens for fish, wildlife, recreation and related environmental resources. Fisheries 1(4):6–10
Tian JH, Yu L, Zheng ZH (2010) A study of ecological water use based on the improved Tennant method. Adv Mater Res 113:1504–1508
Tonkin JD, Jähnig SC, Haase P (2014) The rise of riverine flow-ecology and environmental flow research. Environ Processes 1(3):323–330
Tran LD, Zilberman D, Schilizzi S, Chalak M, Kingwell R (2016) Policy implications of managing reservoir water for multiple uses of irrigation and fisheries in southeast Vietnam. Water Util J 13:69–81
Tsai HC (2009) Hybrid high order neural networks. Appl Soft Comput 9(3):874–881
Wang H, Liu JG (2013) Reservoir operation incorporating hedging rules and operational inflow forecasts. Water Resour Manag 27(5):1427–1438
Yang N, Mei YD, Zhou C (2012) An optimal reservoir operation model based on ecological requirement and its effect on electricity generation. Water Resour Manag 26(14):4019–4028
Yue TX, Liu JY, Jørgensen SE, Ye QH (2003) Landscape change detection of the newly created wetland in Yellow River Delta. Ecol Model 164(1):21–31
Acknowledgments
The authors gratefully acknowledge the support for this research provided in part by the National Science Council, Taiwan, under grant numbers NSC 100-2625-M-366-001-MY3 and NSC 102-2221-E-006-246-MY3, and in part by the Headquarters of University Advancement at the National Cheng Kung University, which is sponsored by the Ministry of Education, Taiwan.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yang, HC., Suen, JP. & Chou, SK. Estimating the Ungauged Natural Flow Regimes for Environmental Flow Management. Water Resour Manage 30, 4571–4584 (2016). https://doi.org/10.1007/s11269-016-1437-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-016-1437-0