Skip to main content

Advertisement

Log in

Characterizing river discharge along River Niger using complexity–entropy causality plane

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

Water resources planning and management is critical for socio-economic, conflict resolution, and agricultural purposes within the Niger Basin. Understanding the river system requires techniques which will capture the dynamical phases and regimes of river discharge. In this study, the characteristics of River Niger were investigated using the complexity–entropy plane at three stations along the river course. This method allows for the dynamical characterization of a time series as either periodic, stochastic, or chaotic. The permutation entropy and statistical complexity values of the original river discharge data were found in the range of 0.44 − 0.63 and 0.30 − 0.34 respectively. Detrending of river discharge time series was found to increase the permutation entropy. Detrended river discharge at Niamey was reported to follow a fractional Brownian motion with Hurst exponent of 0.45. Using a 3-year shifting window, the complexity–entropy plane was found to identify different characteristics of river discharge driven by drought and dam construction. Results obtained can be used by relevant agencies for planning and monitoring of water resources across different rivers in West Africa.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability

Data used in this work is publicly available at the Global Runoff Data Centre (GRDC) database (GRDC 2020).

References

  • Allen GH, Pavelsky TM (2018) Global extent of rivers and streams. Science 361(6402):585–588

    Article  Google Scholar 

  • Araújo F et al (2023) Characterization of human mobility based on information theory quantifiers. Physica A: Stat Mech Appl 609:128344

    Article  Google Scholar 

  • Bandt C, Pompe B (2002) Permutation entropy: a natural complexity measure for time series. Phys Rev Lett 88(17):174102

    Article  Google Scholar 

  • Bonakdari H, Binns AD, Gharabaghi B (2020) A comparative study of linear stochastic with nonlinear daily river discharge forecast models. Water Resour Manage 34(11):3689–3708

    Article  Google Scholar 

  • Bordalo A, Nilsumranchit W, Chalermwat K (2001) Water quality and uses of the Bangpakong River (eastern thailand). Water Res 35(15):3635–3642

    Article  Google Scholar 

  • Braga A et al (2016) Characterization of river flow fluctuations via horizontal visibility graphs. Physica A 444:1003–1011

    Article  Google Scholar 

  • Bravard J-P, Landon N, P’eiry J-L, Piegay H (1999) Principles of engineering geomorphology for managing channel erosion and bedload transport, examples from French rivers. Geomorphology 31(1–4):291–311

    Article  Google Scholar 

  • Davies RB, Harte D (1987) Tests for hurst effect. Biometrika 74(1):95–101

    Article  Google Scholar 

  • de Araujo FHA & Fernandes LH (2022) Lighting the populational impact of covid-19 vaccines in Brazil. Available at SSRN 4171331

  • de CarvalhoBarreto ID et al (2023) Hydrological changes caused by the construction of dams and reservoirs: The cecp analysis. Chaos: An Interdisciplinary Journal of Nonlinear Science 33(2):023115

    Article  Google Scholar 

  • Fashae OA, Olusola AO, Ndubuisi I, Udomboso CG (2019) Comparing Ann and Arima model in predicting the discharge of River Opeki from 2010 to 2020. River Res Appl 35(2):169–177

    Article  Google Scholar 

  • Frausto-Solis J, Pita E & Lagunas J (2008) Short-term streamflow forecasting: Arima vs neural networks, 402–407

  • Fuwape IA, Ogunjo ST, Oluyamo S, Rabiu A (2017) Spatial variation of deterministic chaos in mean daily temperature and rainfall over Nigeria. Theoret Appl Climatol 130(1):119–132

    Article  Google Scholar 

  • Fuwape I, Oluyamo S, Rabiu B, Ogunjo S (2020) Chaotic signature of climate extremes. Theoret Appl Climatol 139(1):565–576

    Article  Google Scholar 

  • GRDC (2020) Major river basins of the world

  • Huotari J, Haapanala S, Pumpanen J, Vesala T, Ojala A (2013) Efficient gas exchange between a boreal river and the atmosphere. Geophys Res Lett 40(21):5683–5686

    Article  Google Scholar 

  • Hurst HE (1951) Long-term storage capacity of reservoirs. Trans Am Soc Civ Eng 116(1):770–799

    Article  Google Scholar 

  • Jara J, Morales-Rojas C, Fernández-Muñoz J, Haunton VJ, Chacón M (2021) Using complexity–entropy planes to detect parkinson’s disease from short segments of haemodynamic signals. Physiol Measur 42(8):084002

    Article  Google Scholar 

  • Javadinejad S, Eslamian S, Ostad-Ali-Askari K (2019) Investigation of monthly and seasonal changes of methane gas with respect to climate change using satellite data. Appl Water Sci 9(8):180

    Article  Google Scholar 

  • Joss J & Resele G (1987) In Mathematical modelling of the heat exchange between a river and the atmosphere 27–40 Springer

  • Kantelhardt JW et al. (2006) Long-term persistence and multifractality of precipitation and river runoff records. J Geophys Res: Atmospheres 111 (D1):

  • Lamberti PW, Martin M, Plastino A, Rosso O (2004) Intensive entropic non-triviality measure. Physica A 334(1–2):119–131

    Article  Google Scholar 

  • Lange H, Rosso OA, Hauhs M (2013) Ordinal pattern and statistical complexity analysis of daily stream flow time series. Eur Physical J Special Topics 222(2):535–552

    Article  Google Scholar 

  • Lehner B et al (2011) High-resolution mapping of the world’s reservoirs and dams for sustainable river-flow management. Front Ecol Environ 9(9):494–502

    Article  Google Scholar 

  • Li X, Gao G, Hu T, Ma H, Li T (2014) Multiple time scales analysis of runoff series based on the chaos theory. Desalin Water Treat 52(13–15):2741–2749

    Article  Google Scholar 

  • Livina V et al (2003) A stochastic model of river discharge fluctuations. Physica A 330(1–2):283–290

    Article  Google Scholar 

  • Ma F, Fan Q, Ling G (2022) Complexity-entropy causality plane analysis of air pollution series. Fluctuation Noise Lett 21(02):2250011

    Article  Google Scholar 

  • Maftei C, Barbulescu A, Carsteanu AA (2016) Long-range dependence in the time series of Tai¸ta river discharges. Hydrol Sci J 61(9):1740–1747

    Article  Google Scholar 

  • Masih I, Maskey S, Mussá F, Trambauer PA (2014) review of droughts on the African continent: a geospatial and long-term perspective. Hydrol Earth Syst Sci 18(9):3635–3649

    Article  Google Scholar 

  • Mateos DM, Zozor S, Olivares F (2020) Contrasting stochasticity with chaos in a permutation Lempel-Ziv complexity—Shannon entropy plane. Physica A 554:124640

    Article  Google Scholar 

  • Mehrdad F, Mehrdad R, Hossein B, Hossein S, Mohammad RE (2012) Comparison of artificial neural networks and stochastic models in river discharge forecasting,(case study: Ghara-aghaj river, fars province, iran). Afr J Agric Res 7(40):5446–5458

    Google Scholar 

  • Milliman JD, Farnsworth K, Jones P, Xu K, Smith L (2008) Climatic and anthropogenic factors affecting river discharge to the global ocean, 1951–2000. Global Planet Change 62(3–4):187–194

    Article  Google Scholar 

  • Ogunjo S (2015) Effect of data transformation on long term memory of chaotic time series. Afr Rev Physics 10:

  • Ogunjo S, Olusola A (2022) Signature of teleconnection patterns in river discharge within the Niger Basin. Meteorol Atmos Phys 134(2):1–15

    Article  Google Scholar 

  • Ogunjo S, Olusola A, Fuwape I, Durowoju O (2022) Temporal variation in deterministic chaos: the influence of kainji dam on downstream stations along lower Niger River. Arab J Geosci 15(3):1–11

    Article  Google Scholar 

  • Ogunjo S, Fuwape I, Oluyamo S & Rabiu B (2019) Spatial dynamical complexity of precipitation and temperature extremes over Africa and South America. Asia-Pacific J Atmos Sci 1–14

  • Okpara JN, Tarhule AA and Perumal M (2013) Study of climate change in Niger River basin, West Africa: Reality not a myth. Climate Change: Realities, Impacts Over Ice Cap, Sea Level and Risks 1

  • Ostad-Ali-Askari K (2022) Developing an optimal design model of furrow irrigation based on the minimum cost and maximum irrigation efficiency. Appl Water Sci 12(7):144

    Article  Google Scholar 

  • Rahimzad M et al (2021) Performance comparison of an lstm-based deep learning model versus conventional machine learning algorithms for streamflow forecasting. Water Resour Manage 35(12):4167–4187

    Article  Google Scholar 

  • Rego C, Frota H, Gusmão M (2013) Multifractality of Brazilian rivers. J Hydrol 495:208–215

    Article  Google Scholar 

  • Ribeiro HV, Zunino L, Mendes RS, Lenzi EK (2012) Complexity– entropy causality plane: a useful approach for distinguishing songs. Physica A 391(7):2421–2428

    Article  Google Scholar 

  • Rosso OA, Larrondo H, Martin MT, Plastino A, Fuentes MA (2007) Distinguishing noise from chaos. Phys Rev Lett 99(15):154102

    Article  Google Scholar 

  • Saurral RI, Barros VR & Lettenmaier DP (2008) Land use impact on the Uruguay River discharge. Geophys Res Lett 35(12)

  • Seabold S & Perktold, J (2010) Statsmodels: econometric and statistical modeling with python. 57, 10–25080, Austin

  • Serinaldi F, Zunino L, Rosso OA (2014) Complexity–entropy analysis of daily stream flow time series in the continental united states. Stoch Env Res Risk Assess 28(7):1685–1708

    Article  Google Scholar 

  • Shayannejad M, Ghobadi M, Ostad-Ali-Askari K (2022) Modeling of surface flow and infiltration during surface irrigation advance based on numerical solution of Saint-Venant equations using Preissmann’s scheme. Pure Appl Geophys 179(3):1103–1113

    Article  Google Scholar 

  • Silva ASA, Menezes RSC, Rosso OA, Stosic B, Stosic T (2021) Complexity entropy-analysis of monthly rainfall time series in Northeastern Brazil. Chaos, Solitons Fractals 143:110623

    Article  Google Scholar 

  • Stosic T, Telesca L, de Souza Ferreira DV, Stosic B (2016) Investigating anthropically induced effects in streamflow dynamics by using permutation entropy and statistical complexity analysis: a case study. J Hydrol 540:1136–1145

    Article  Google Scholar 

  • Stosic D, Stosic D, Ludermir TB, Stosic T (2019) Exploring disorder and complexity in the cryptocurrency space. Physica A 525:548–556

    Article  Google Scholar 

  • Tatli H (2014) Statistical complexity in daily precipitation of ncep/ncar reanalysis over the Mediterranean basin. Int J Climatol 34(1):155–161

    Article  Google Scholar 

  • Tatli H (2015) Detecting persistence of meteorological drought via the hurst exponent. Meteorol Appl 22(4):763–769

    Article  Google Scholar 

  • Tatli H, Dalfes HN (2020) Long-time memory in drought via detrended fluctuation analysis. Water Resour Manage 34(3):1199–1212

    Article  Google Scholar 

  • Thomas KA (2017) The river-border complex: a border-integrated approach to transboundary river governance illustrated by the Ganges River and Indo-Bangladeshi border. Water Int 42(1):34–53

    Article  Google Scholar 

  • Zhang Y, Shang P (2019) The complexity–entropy causality plane based on multivariate multiscale distribution entropy of traffic time series. Nonlinear Dyn 95(1):617–629

    Article  Google Scholar 

  • Zounemat-Kermani M (2016) Investigating chaos and nonlinear forecasting in short term and mid-term river discharge. Water Resour Manage 30(5):1851–1865

    Article  Google Scholar 

  • Zunino L, Zanin M, Tabak BM, Pérez DG, Rosso OA (2010) Complexity-entropy causality plane: a useful approach to quantify the stock market inefficiency. Physica A: Stat Mech Appl 389(9):1891–1901

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Samuel Ogunjo.

Ethics declarations

Conflict of interest

The author declares no conflict of interest.

Additional information

Responsible Editor: Broder J. Merkel

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ogunjo, S. Characterizing river discharge along River Niger using complexity–entropy causality plane. Arab J Geosci 16, 295 (2023). https://doi.org/10.1007/s12517-023-11392-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-023-11392-3

Keywords

Navigation