Comparing Master Recession Curves using Seven Baseflow Recession Models

https://doi.org/10.22146/ijg.89691

Bokiraiya Latuamury(1*)

(1) Department of Forestry, Pattimura University, Ambon-Maluku, Indonesia
(*) Corresponding Author

Abstract


Baseflow recession analysis is an effective method for understanding catchment area releasing flow during dry season (without rainfall), thereby facilitating the management of water resources. Despite the availability of several theories on recession curves, there are limited studies on the comparison of different approaches. To overcome the limitation, several studies have reported the ability of master recession curves (MRC) modeling to combine automated methods for analyzing recession periods and curves shapes based on river flow data. Therefore, this study aimed to compare seven baseflow recession models for MRC characterization in small island watersheds. The Turkey test results showed that MRC visualization varied, particularly in terms of slope parameters and shapes. The seven recession models were grouped into two subsets based on their similarity. The first subsets consisted of Turbulent, Dupuit-Boussinesq aquifer storage, Depression-detention storage, Horton double exponential, Linear reservoir, and Exponential reservoir. Meanwhile, the second subset comprised Hyperbolic reservoir, Turbulent, Dupuit-Boussinesq aquifer storage, Depression-detention storage, Horton double exponential, and Linear reservoir. The findings also showed that the variability of MRC behavior depended on groundwater recharge, storage channel conditions, aquifer characteristics, and climate in the study area. These findings were also relevant to the development of MRC in other regions, such as hydrorecession tools, MRCPtool applications, sensitivity analysis-based Automatic parameter calibration of the VIC model for streamflow simulation over China, and spatial and temporal patterns in baseflow recession in the continental United States.

Keywords


baseflow; master recession curve; recession model; small watershed

Full Text:

PDF


References

Aksoy, H., & Wittenberg, H. (2011). Nonlinear baseflow recession analysis in watersheds with intermittent streamflow. Hydrological Sciences Journal. https://doi.org/10.1080/02626667.2011.553614

Arciniega-Esparza, S., Breña-Naranjo, J. A., Pedrozo-Acuña, A., & Appendini, C. M. (2017). Hydrorecession: A Matlab toolbox for streamflow recession analysis. Computers and Geosciences. https://doi.org/10.1016/j.cageo.2016.10.005

Basha, H. A. (2020). Flow Recession Equations for Karst Systems. Water Resources Research, 56(7), 1–21. https://doi.org/10.1029/2020WR027384

Biswal, B., & Marani, M. (2010). Geomorphological origin of recession curves. Geophysical Research Letters, 37(24), 1–5. https://doi.org/10.1029/2010GL045415

Biswal, B., & Marani, M. (2014). “Universal” recession curves and their geomorphological interpretation. Advances in Water Resources, 65, 34–42.

Boussinesq, J. (1877). boussinesq1877essai : Essai sur la theorie des eaux courantes. Impr. nationale.

Brutsaert, W., & Nieber, J. (1977). Regionalized drought flow hydrographs from a mature glaciated plateau. Water Resources Research, 13(3), 637–643.

Carlotto, T., & Chaffe, P. L. B. (2019). Computers and Geosciences Master Recession Curve Parameterization Tool ( MRCPtool ): Different approaches to recession curve analysis. Computers and Geosciences, 132(February), 1–8. https://doi.org/10.1016/j.cageo.2019.06.016

Chapmann, T. (1999). A comparison of algorithms for stream flow recession and baseflow separation. Hydrological Processes, 13(5), 701–714. https://doi.org/https://doi.org/10.1002/(SICI)1099-1085(19990415)13:5<701::AID-HYP774>3.0.CO;2-2

Fatchurohman, H., Adji, T. N., Haryono, E., & Wijayanti, P. (2018). Baseflow index assessment and master recession curve analysis for karst water management in Kakap Spring, Gunung Sewu. IOP Conference Series: Earth and Environmental Science, 148(1). https://doi.org/10.1088/1755-1315/148/1/012029

Gou, J., Miao, C., Duan, Q., Tang, Q., Di, Z., Liao, W., Wu, J., & Zhou, R. (2020). Sensitivity Analysis-Based Automatic Parameter Calibration of the VIC Model for Streamflow Simulations Over China. Water Resources Research, 56(1), 1–19. https://doi.org/10.1029/2019WR025968

Gregor, M. & Malík, P. (2012). User manual for Recession Curve 4.0. Version 2, 1–8.

Gregor, M., & Malík, P. (2012). Construction of master recession curve using genetic algorithms. Journal of Hydrology and Hydromechanics. https://doi.org/10.2478/v10098-012-0001-8

Gregor, M., & Malík, P. (2014). Using Hybrid Genetic Algorithms in Assembling Master Recession Curves of Karst Springs. In H2Karst Research in Limestone Hydrogeology. https://doi.org/10.1007/978-3-319-06139-9_6

Hammond, M., & Han, D. (2006). Recession curve estimation for storm event separations. Journal of Hydrology, 330(3–4), 573–585. https://doi.org/10.1016/j.jhydrol.2006.04.027

Hannah, D. M., & Gurnell, A. M. (2001). A conceptual, linear reservoir runoff model to investigate melt season changes in cirque glacier hydrology. Journal of Hydrology, 246(1–4), 123–141. https://doi.org/10.1016/S0022-1694(01)00364-X

Harman, C. J., Sivapalan, M., & Kumar, P. (2009). Power law catchment-scale recessions arising from heterogeneous linear small-scale dynamics. Water Resources Research, 45(9), 1–13. https://doi.org/10.1029/2008WR007392

Heppner, C. S., & Nimmo, J. R. (2005). A Computer Program for Predicting Recharge with a Master Recession Curve. 8.

Latuamury, B., Marasabessy, H., Talaohu, M., & Imlabla, W. (2021). Small island watershed morphometric and hydrological characteristics in Ambon Region, Maluku Province. IOP Conference Series: Earth and Environmental Science, 800(1), 0–15. https://doi.org/10.1088/1755-1315/800/1/012047

Latuamury, B., Parera, L. R., & Marasabessy, H. (2020). Characterizing river baseflow recession using linear reservoir model in Alang Watershed, Central Java, Indonesia. Indonesian Journal of Geography, 52(1). https://doi.org/10.22146/ijg.43565

Latuamury, B., Imlabla, W. N., Sahusilawane, J. F., & Marasabessy, H. (2023). One-Way ANOVA Test of Five Digital Filter Recursive Graphic Methods in Baseflow Separation on Wae Tomu Watershed Ambon City. AIP Conference Proceedings, 2588. https://doi.org/10.1063/5.0111720

Latuamury, B., Imlabla, W., Sahusilawane, J., & Marasabessy, H. (2022). Comparing Master Recession Curve Shapes Between Linear and Exponential Reservoir Models. Journal of Geographical Studies, 6(2), 68–72. https://doi.org/10.21523/gcj5.22060202

Lázaro, J. M., Ángel, J., Navarro, S., Gil, A. G., & Romero, V. E. (2015). A new adaptation of linear reservoir models in parallel sets to assess actual hydrological events. Journal of Hydrology, 524, 507–521. https://doi.org/https://doi.org/10.1016/j.jhydrol.2015.03.009

Lee, G., Shin, Y., & Jung, Y. (2014). Development of web-based RECESS model for estimating baseflow using SWAT. Sustainability (Switzerland), 6(4), 2357–2378. https://doi.org/10.3390/su6042357

Maillet, E. (1905). Essais d’Hydraulique Souterraine et Fluviale. In Hermann Paris (p. 218).

Nurkholis, A., Adji, T. N., Haryono, E., Cahyadi, A., Waskito, W. A., Fathoni, H., Kurniawan, I. A., & Agniy, R. F. (2019). Analysis of Master Recession Curve (MRC) and flood hydrograph components for karstification degree estimation in Kiskendo Cave, Jonggrangan Karst System, Indonesia. IOP Conference Series: Earth and Environmental Science, 256(1). https://doi.org/10.1088/1755-1315/256/1/012011

Posavec, K., Bačani, A., & Nakić, Z. (2006). A visual basic spreadsheet macro for recession curve analysis. Ground Water, 44(5), 764–767. https://doi.org/10.1111/j.1745-6584.2006.00226.x

Posavec, K., Parlov, J., & Nakić, Z. (2010). Fully automated objective-based method for master recession curve separation. Ground Water, 48(4), 598–603. https://doi.org/10.1111/j.1745-6584.2009.00669.x

Rivera-Ramírez, H. D., Warner, G. S., & Scatena, F. N. (2002). Prediction of master recession curves and baseflow recessions in the Luquillo mountains of Puerto Rico. Journal of the American Water Resources Association, 38(3), 693–704. https://doi.org/10.1111/j.1752-1688.2002.tb00990.x

Shaw, S. B., McHardy, T. M., & Riha, S. J. (2013). Evaluating the influence of watershed moisture storage on variations in base flow recession rates during prolonged rain-free periods in medium-sized catchments in New York and Illinois, USA. Water Resources Research, 49(9), 6022–6028. https://doi.org/10.1002/wrcr.20507

Shaw, S. B., & Riha, S. J. (2012). Examining individual recession events instead of a data cloud: Using a modified interpretation of dQ/dt-Q streamflow recession in glaciated watersheds to better inform models of low flow. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2012.02.034

Stewart, M. K. (2015). Promising new baseflow separation and recession analysis methods applied to streamflow at Glendhu Catchment, New Zealand. Hydrology and Earth System Sciences, 19(6), 2587–2603. https://doi.org/10.5194/hess-19-2587-2015

Stoelzle, M., Stahl, K., & Weiler, M. (2013). Are streamflow recession characteristics really characteristic? Hydrology and Earth System Sciences. https://doi.org/10.5194/hess-17-817-2013

Sujono, J., Shikasho, S., & Hiramatsu, K. (2004). A comparison of techniques for hydrograph recession analysis. Hydrological Processes, 18(3), 403–413. https://doi.org/10.1002/hyp.1247

Szilagyi, J., Gribovszki, Z., & Kalicz, P. (2007). Estimation of catchment-scale evapotranspiration from baseflow recession data: Numerical model and practical application results. Journal of Hydrology, 336(1–2), 206–217. https://doi.org/10.1016/j.jhydrol.2007.01.004

Szilagyi, J., & Parlange, M. B. (1998). Baseflow separation based on analytical solutions of the Boussinesq equation. Journal of Hydrology, 204(1–4), 251–260. https://doi.org/10.1016/S0022-1694(97)00132-7

Tallaksen, L. (1995). A review of baseflow recession analysis. Journal of Hydrology, 165(1–4), 349–370. https://doi.org/10.1016/0022-1694(95)92779-d

Tashie, A., Pavelsky, T., & Band, L. E. (2020). An Empirical Reevaluation of Streamflow Recession Analysis at the Continental Scale. Water Resources Research, 56(1), 1–18. https://doi.org/10.1029/2019WR025448

Tashie, A., Pavelsky, T., & Emanuel, R. E. (2020). Spatial and Temporal Patterns in Baseflow Recession in the Continental United States. Water Resources Research, 56(3), 1–18. https://doi.org/10.1029/2019WR026425

Thomas, B. F., & Vogel, R. M. (2015). Baseflow Recession Analysis : Testing the Nonlinear Reservoir Hypothesis. Tufts University, January, 2011.

Thomas, B. F., Vogel, R. M., & Famiglietti, J. S. (2015). Objective hydrograph baseflow recession analysis. JOURNAL OF HYDROLOGY, 525, 102–112. https://doi.org/10.1016/j.jhydrol.2015.03.028

Vogel, R.M. & Kroll, C. N. (1996). Estimation of baseflow recession constants. Water Resources Management. https://doi.org/10, pages303–320(1996)

Ward, A. S., Fitzgerald, M., Gooseff, M. N., Voltz, T. J., Binley, A. M., & Singha, K. (2012). Correction to “hydrologic and geomorphic controls on hyporheic exchange during baseflow recession in a headwater mountain stream.” Water Resources Research, 48(8), 12663. https://doi.org/10.1029/2012WR012663

Wittenberg, H., & Sivapalan, M. (1999). Watershed groundwater balance estimation using streamflow recession analysis and baseflow separation. Journal of Hydrology, 219(1–2), 20–33. https://doi.org/10.1016/S0022-1694(99)00040-2



DOI: https://doi.org/10.22146/ijg.89691

Article Metrics

Abstract views : 602 | views : 481

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2024 Bokiraiya Latuamury

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)

ISSN 2354-9114 (online), ISSN 0024-9521 (print)

Web Analytics IJG STATISTIC