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Academic Journal of Environmental Biology, 2022, 3(4); doi: 10.38007/AJEB.2022.030405.

Water Resources Ecological Footprint Based on ARIMA Model

Author(s)

Ankite Singh

Corresponding Author:
Ankite Singh
Affiliation(s)

LBEF Campus, Nepal

Abstract

Water resources are an important part of maintaining the normal operation of ecosystems and the normal development of human society. With the continuous development of social economy, water shortage and water pollution have increasingly attracted the attention of the international community. The purpose of this work is to study the prediction of the ecological footprint of water resources based on the ARIMA model. Based on the ecological footprint theory, a water resources ecological footprint prediction model is established to provide specific reference for the planning goals of sustainable water resource utilization in the future. By studying the time series analysis method, that is, using the eviews software to establish a time series analysis model ARIMA (p, d, q) model, a short-term forecast of M province from 2018 to 2021 is made. According to the time series analysis The prediction results of the model ARIMA (4, 1, 2) show that: from 2018 to 2021, the ecological footprint in M province is on the rise, and the water crisis situation will become increasingly severe. The ARIMA model has a good prediction effect.

Keywords

ARIMA Model, Ecological Footprint, Water Resource Analysis, Predictive Analysis

Cite This Paper

Ankite Singh. Water Resources Ecological Footprint Based on ARIMA Model. Academic Journal of Environmental Biology (2022), Vol. 3, Issue 4: 37-44. https://doi.org/10.38007/AJEB.2022.030405.

References

[1] Hadjira A, Salhi H, Hafa F E. A Comparative Study between ARIMA Model, Holt-Winters – No Seasonal and Fuzzy Time Series for New Cases of COVID-19 in Algeria. American Journal of Public Health Research, 2021, 9(6):248-256. https://doi.org/10.12691/ajphr-9-6-4

[2] Satrio C, Darmawan W, Nadia B U, et al. Time series analysis and forecasting of coronavirus disease in Indonesia using ARIMA model and PROPHET. Procedia Computer Science, 2021, 179(12):524-532. https://doi.org/10.1016/j.procs.2021.01.036

[3] Patowary A N, Barman M P, Dutta B. Application Of Arima Model For Forecasting Road Accident Deaths In India. International Journal of Agricultural and Statistics Sciences, 2021, 16(2):607-615.

[4] Sam S O, Pokhariyal G P, Ndhine E O. Otoi-NARIMA Model for forecasting seasonality of COVID-19 waves: Case of Kenya. International Journal of Applied Mathematics and Statistics, 2021, Vol6(Issue 2, Part a):48-58.

[5] Kedar S V. Stock Market Increase and Decrease using Twitter Sentiment Analysis and ARIMA Model. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021, 12(1S):146-161.

[6] Abolmaali S, Shirzaei S. A comparative study of SIR Model, Linear Regression, Logistic Function and ARIMA Model for forecasting COVID-19 cases. AIMS Public Health, 2021, 8(4):598-613. https://doi.org/10.3934/publichealth.2021048

[7] Meher B K, Hawaldar I T, Cristi S, et al. Forecasting stock market prices using mixed ARIMA model: A case study of Indian pharmaceutical companies. Investment Management and Financial Innovations, 2021, 18(1):42-54. https://doi.org/10.21511/imfi.18(1).2021.04

[8] Sharma S, Karol S. Modeling And Forecasting Of India's Defense Expenditures Using Box-Jenkins Arima Model. International Journal of Research - GRANTHAALAYAH, 2021, 9(2):334-344.

[9] Etner E M. Trkye'de Ar-Ge Harcamalari Ve Ekonomk Byme Arasindak Lknn Arima Model Le Analz: 1990-2019. Social Sciences Studies Journal, 2020, 6(72):4823-4833. https://doi.org/10.26449/sssj.2744

[10] Das U D, Singh B P, Roy T D. Temporal Variation of Temperature in Guwahati, Assam: An Application of Seasonal ARIMA Model. Journal of Statistics Applications & Probability, 2020, 9(1):169-180. https://doi.org/10.18576/jsap/090115

[11] Nwuju K, Better L, Etuk E. Modelling And Forecasting Daily Mortality Rate Of Covid-19 In Ecowas: Evidence From Arima Model. International Journal of Advanced Research, 2020, 6(12):67-89.

[12] Mathew S, Ram K S. Study of Sales Forecasting Accuracy using ARIMA Model. International Journal Of Management, 2020, 08(2):40-46. https://doi.org/10.35620/IJM.2020.8201

[13] Babu M, Sugirtha R, Jayapal D G, et al. Price Movement of Gold Commodity: An Application of ARIMA Model. Solid State Technology, 2020, 63(2s):1455-1462.

[14] Emmanuel B O, Enegesele D, Arimie C O. Additive Decomposition with Arima Model Forecasts When the Trend Component Is Quadratic. Open Access Library Journal, 2020, 07(7):1-20. https://doi.org/10.4236/oalib.1106435

[15] Tarasenko V S, Volkova N E, Ivanyutin N M. Integrated Water Resources Management – the Way to Improve the Water Situation in the Republic of Crimea. Ecology and Industry of Russia, 2020, 24(9):64-71.

[16] Tume S. Standardised Precipitation Valuation of Water Resources Vulnerability to Climate Variability on the Bui Plateau, Northwest Cameroon. Environment and Ecology Research, 2019, 7(2):83-92. https://doi.org/10.13189/eer.2019.070202

[17] Rybkina I D, Sivokhip Z T. Water Resources Of The Russian㎏Azakhstan Transboundary Region And Their Use. South of Russia ecology development, 2019, 14(2):70-86.

[18] Troni N, Hoti R, Omanovic D, et al. Quality estimation and chemical characterisation of water resources of Lepenci River by DPASV. Journal of environmental protection and ecology, 2018, 19(2):490-498.