Performance evaluation of Auto-Regressive Integrated Moving Average models for forecasting saltwater intrusion into Mekong river estuaries of Vietnam

Authors

  • Tran Thanh Thai Institute of Tropical Biology, VAST, Ho Chi Minh City, Vietnam
  • Nguyen Duy Liem Nong Lam University, Ho Chi Minh City, Vietnam
  • Pham Thanh Luu 1-Institute of Tropical Biology, VAST, Ho Chi Minh City, Vietnam; 2-Graduate University of Science and Technology, VAST, Hanoi, Vietnam
  • Nguyen Thi My Yen Institute of Tropical Biology, VAST, Ho Chi Minh City, Vietnam
  • Tran Thi Hoang Yen Institute of Tropical Biology, VAST, Ho Chi Minh City, Vietnam
  • Ngo Xuan Quang 1-Institute of Tropical Biology, VAST, Ho Chi Minh City, Vietnam; 2-Graduate University of Science and Technology, VAST, Hanoi, Vietnam
  • Lam Van Tan Department of Science and Technology of Ben Tre Province, Ben Tre Province, Vietnam
  • Pham Ngoc Hoai Institute of Applied Technology, Thu Dau Mot University, Binh Duong Province, Vietnam

DOI:

https://doi.org/10.15625/2615-9783/16440

Keywords:

Climate change, Empirical Bayesian Kriging, water salinity forecast, saltwater intrusion, time series analysis

Abstract

The Mekong Delta is the most severely affected area by saltwater intrusion in Vietnam. Recent studies have focused on predicting this disaster with weekly and decade lead times without many seasonal forecasts, which is important for planning crop selection, crop structure, and sowing time. This study aims to forecast the spatial distribution of saltwater intrusion into the Mekong river estuaries of Vietnam during the dry season of 2021 by integrating Auto-Regressive Integrated Moving Average with Geographic Information System. ARIMA models were trained with a single input of water salinity measurements from 2012 to 2020. Compared to the weekly salinity observations in 2021, these models predicted very well in the My Tho and Ham Luong rivers but unsatisfactory performance in the Co Chien river. The deepest saltwater intrusion will occur between March 19th and April 16th of 2021, when the 4‰ saline front will move the farthest distance of 41,41 and 44 kilometers inland from the sea through My Tho, Ham Luong Co Chien rivers, respectively. The entire river system will be exposed to moderate risk of saltwater intrusion. Freshwater zones decreased significantly to 0.73% of the whole area of Ben Tre province. These findings could provide a valuable scientific foundation for the appropriate management of coastal aquifers to control or reduce saltwater intrusion.

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References

Abdullah A.D., Gisen J.I.A., Van Der Zaag P., Savenije H.H.G., Karim U.F.A., Masih, I., Popescu I., 2016. Predicting the salt water intrusion in the Shatt al-Arab estuary using an analytical approach. Hydrol. Earth Syst. Sci., 20(10), 4031-4042.

Abuamra I.A., Maghari A.Y.A., Abushawish H.F., 2021. Medium-term forecasts for salinity rates and groundwater levels. Model Earth Syst. Environ., 7(1), 485-494.

Ahmadianfar I., Jamei M., Chu X., 2020. A novel Hybrid Wavelet-Locally Weighted Linear Regression (W-LWLR) Model for Electrical Conductivity (EC) Prediction in Surface Water. J. Contam. Hydrol., 232, 1-17.

An Q., Zhao M., 2017. Time Series Analysis in the Prediction of Water Quality. In 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017), Atlantis Press, 51-54.

Apel H., Khiem M., Hong Quan N., Quang Toan T., 2020. Brief communication: Seasonal prediction of salinity intrusion in the Mekong Delta. Nat. Hazards Earth Syst. Sci., 20(6), 1609-1616.

Baena-Ruiz L., Pulido-Velazquez D., Collados-Lara A.J., Renau-Pruñonosa A., Morell I., 2018. Global Assessment of Seawater Intrusion Problems (Status and Vulnerability). Water Resour. Manag, 32(8), 2681-2700.

Ben Tre Statistical Office, 2020. Statistical Yearbook of Ben Tre 2019. Ho Chi Minh City General Publishing House.

Bouteraa O., Mebarki A., Bouaicha F., Nouaceur Z., Laignel, B., 2019. Groundwater quality assessment using multivariate analysis, geostatistical modeling, and water quality index (WQI): a case of study in the Boumerzoug-El Khroub valley of Northeast Algeria. Acta Geochim., 38(6), 796-814.

Box G.E.P., Jenkins G.M., Reinsel G.C., 2008. Time Series Analysis. Wiley Series in Probability and Statistics, Wiley.

Chung S.Y., Venkatramanan S., Hussam E.E., Selvam S., Prasanna M.V., 2019. Chapter 4 - Supplement of Missing Data in Groundwater-Level Variations of Peak Type Using Geostatistical Methods. In: Venkatramanan S., Prasanna M.V., Chung S.Y. (Eds.). GIS and Geostatistical Techniques for Groundwater Science, Elsevier, 33-41.

De Silva S.S., Phuong N.T., 2011. Striped catfish farming in the Mekong Delta, Vietnam: a tumultuous path to a global success. Rev. Aquac., 3(2), 45-73.

Dung B.Q., Khanh, U.D., 2016. Calculation of Vietnam’s Coastline Length (Mainland) Based on Topographic Map System at Scale 1/50,000. Vietnam Journal of Marine Science and Technology, 16(3), 221-227.

Goh Y.M., Case K., 2016. Advances in Manufacturing Technology XXX. Proceedings of the 14th International Conference on Manufacturing Research, iIncorporating the 31st National Conference on Manufacturing Research, Sep 6-8, Loughborough University, UK.

Hai T.X., Van Nghi V., Hung V.H., Tuan D.N., Lam D.T., Van CT., 2019. Assessing and Forecasting Saline Intrusion in the Vietnamese Mekong Delta Under the Impact of Upstream flow and Sea Level Rise. J. Environ. Sci. Eng. B., 8, 174.

Lam N.T., 2019. Real-time prediction of salinity in the Mekong River Delta. In: Viet N.T., Xiping D., Tung T.T., (Eds). Proceedings of the 10th International Conference on Asian and Pacific Coasts, Hanoi, Springer Nature Singapore, 1461-1468.

Loc H.H., Van Binh D., Park E., Shrestha S., Dung T.D., Son V.H., Truc N.H.T., Mai N.P., Seijger C., 2021. Intensifying saline water intrusion and drought in the Mekong Delta: From physical evidence to policy outlooks. Sci. Total Environ., 757, 143919.

Lola M.S., Zainuddin N.H., Abdullah M.T., Ponniah V., Mohd N.A.R., Zakariya R., Idris M.S., Khalili I., 2018. Improving the Performance of ANN-ARIMA Models for Predicting Water Quality in the Offshore Area of Kuala Terengganu, Terengganu, Malaysia. J. Sustain. Sci. Manag., 13(1), 27-37.

Magesh N.S., Elango L., 2019. Spatio-Temporal Variations of Fluoride in the Groundwater of Dindigul District, Tamil Nadu, India: A Comparative Assessment Using Two Interpolation Techniques. In: Venkatramanan S., Prasanna M.V., Chung S.Y. (Eds.). GIS and Geostatistical Techniques for Groundwater Science, Elsevier, 283-296.

Maliva RG., 2020. Chapter 21 Saline-Water Intrusion Management. In: Maliva R.G., (Eds.). Anthropogenic Aquifer Recharge: WSP Methods in Water Resources Evaluation Series No. 5, Springer Hydrogeology, Springer International Publishing, 683-685.

Mastrocicco M., Busico G., Colombani N., Vigliotti M., Ruberti D., 2019. Modelling actual and future seawater intrusion in the variconi coastal wetland (Italy) due to climate and landscape changes. Water (Switzerland), 11(7).

Melesse A.M., Khosravi K., Tiefenbacher J.P., Heddam S., Kim S., Mosavi A., Pham BT., 2020. River Water Salinity Prediction Using Hybrid Machine Learning Models. Water, 12(10), 2951.

Nash J.E., Sutcliffe J.V., 1970. River flow forecasting through conceptual models part I - A discussion of principles. J. Hydrol., 10(3), 282-290.

National Centre for Hydro-Meteorological Forecasting, 2021. Forecast Newsletter of Saltwater Intrusion in Southern Vietnam. [online] Available at: <https://nchmf.gov.vn/Kttvsite/vi-VN/1/xam-nhap-man-20-18.html> [Accessed 10 Jun. 2021].

Nguyen H.Q., Korbee D., Ho H.L., Weger J., Thi Thanh Hoa P., Thi Thanh Duyen N., Dang Manh Hong Luan P., Luu T.T., Ho Phuong Thao D., Thi Thu Trang N., Hermans L., Evers J., Wyatt A., Chau Nguyen X.Q., Long Phi H., 2019. Farmer adoptability for livelihood transformations in the Mekong Delta: a case in Ben Tre province. J. Environ. Plan. Manag., 62(9), 1603-1618.

Nguyen PTB., Koedsin W., McNeil D., Van TPD., 2018. Remote sensing techniques to predict salinity intrusion: application for a data-poor area of the coastal Mekong Delta, Vietnam. Int. J. Remote Sens., 39(20), 6676-6691.

Nhung T.T., Le Vo P., Van Nghi V., Bang H.Q., 2019. Salt intrusion adaptation measures for sustainable agricultural development under climate change effects: A case of Ca Mau Peninsula, Vietnam. Clim. Risk Manag., 23, 88-100.

Phan TTH., Nguyen XH., 2020. Combining statistical machine learning models with ARIMA for water level forecasting: The case of the Red river. Adv. Water Resour., 142, 103656.

Qie J., Yuan J., Wang G., Zhang X., Zhou B., Deng W., 2015. Water Quality Prediction Based on an Improved ARIMA- RBF Model Facilitated by Remote Sensing Applications. In: Ciucci D., Wang G., Mitra S., Wu W.Z (Eds.). Rough Sets and Knowledge Technology 10th International Conference, RSKT 2015, Held as Part of the International Joint Conference on Rough Sets, IJCRS 2015, Tianjin, China, November 20-23, Springer, 470-481.

Ranjbar M., Khaledian M., 2014. Using Arima Time Series Model in Forecasting the Trend of Changes in Qualitative Parameters of Sefidrud River. Int. Res. J. Basic Appl. Sci., 8(3), 346-351.

Renaud F.G., Le T.T.H., Lindener C., Guong V.T., Sebesvari Z., 2015. Resilience and shifts in agro-ecosystems facing increasing sea-level rise and salinity intrusion in Ben Tre Province, Mekong Delta. Clim. Change, 133(1), 69-84.

Socialist Republic of Vietnam, 2004. National Report on Disaster Reduction in Vietnam (For the World Conference on Disaster Reduction, Kobe-Hyogo, Japan, 18-22 January 2005), Hanoi.

Southern Institute of Water Resources Research, 2021. Forecast of salinity in the Mekong Delta. [online] Available at: <http://www.siwrr.org.vn/?mod=list&id=93&cid=906&page=&lang=> [Accessed 10 Jun. 2021].

StatPoint Technologies, 2017. STATGRAPHICS® Centurion 18 User Manual, Statgraphics Technologies, Inc.

Sun, B.H., Koch, M., 2001. Case Study: Analysis and Forecasting of Salinity in Apalachicola Bay, Florida, using Box-Jenkins ARIMA Models. J. Hydraul. Eng., 127(9), 718-727.

The Prime Minister, 2021. Decision no. 18/2021/QD-TTg on natural disaster forecast, warning and information transmission and disaster severity levels.

Tran D.A., Tsujimura M., Ha N.T., Van Binh D., Dang T.D., Doan Q.V., Bui D.T., Trieu N.A., Le V.P., Pham T.B.T., Pham T.D., 2021. Evaluating the predictive power of different machine learning algorithms for groundwater salinity prediction of multi-layer coastal aquifers in the Mekong Delta, Vietnam. Ecol. Indic., 127, 107790.

Tran T.T., Thien L.D., Quang N.X., Lam V.T., 2020. Forecasting of saline intrusion in Ham Luong river, Ben Tre province (Southern Vietnam) using Box-Jenkins ARIMA models. Science and Technology Development Journal, 23(1), 446-453.

Tran T.V., Tran D.X., Myint S.W., Huang C.Y., Pham H.V., Luu T.H., Vo T.M., 2019. Examining spatiotemporal salinity dynamics in the Mekong River Delta using Landsat time series imagery and a spatial regression approach. Sci. Total Environ., 687, 1087-1097.

Vietnamese Disaster Management Authority, 2019. Statistics of damage caused by natural disasters in 2016. [online] Hanoi. Available at: <http://phongchongthientai.mard.gov.vn/Pages/bang-thong-ke-thiet-hai-do-thien-tai-nam-2016.aspx>.

Vietnamese Disaster Management Authority, 2020. Statistics of damage caused by natural disasters in 2020. [online] Hanoi. Available at: <http://phongchongthientai.mard.gov.vn/Pages/bieu-tong-hop-thiet-hai-do-thien-tai-2020-tinh-den-17h-15-11-2020-.aspx>.

Vinh D.H., Dung T.D., Thuc P.T.B., Khoi D.N., Phuong T.H., Ninh N.T., 2019. Exploring freshwater regimes and impact factors in the coastal estuaries of the Vietnamese mekong delta. Water (Switzerland), 11(4), 1-17.

Willmott C.J., Matsuura K., 2005. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim. Res., 30(1), 79-82.

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Published

2021-08-19

How to Cite

Tran Thanh, T., Nguyen Duy, L., Pham Thanh, L., Nguyen Thi My , Y., Tran Thi Hoang, Y., Ngo Xuan, Q., Lam Van, T., & Pham Ngoc, H. (2021). Performance evaluation of Auto-Regressive Integrated Moving Average models for forecasting saltwater intrusion into Mekong river estuaries of Vietnam. Vietnam Journal of Earth Sciences. https://doi.org/10.15625/2615-9783/16440

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