APPLICATION OF INTELLIGENT AUTOCORRELATED MODELS FOR RUNOFF SIMULATION A CASE STUDY OF THE IRANIAN SAMIYAN AND DOOSTBIGHLOU RIVERS

A. MOLAVI

Abstract


Auto-correlated simulation is one of the effective methods for predicting river flows in basins that do not have information and statistics on various climatic factors. In this study, the flow of Doostbighlou and Samiyan Rivers located in Ardabil province, Iran, was predicted with intelligent meta-exploration models of artificial neural networks, support vector machines, and their combination with wavelet transform, considering acceptable runoff delay times. The evaluation results showed that considering the wavelet transform in the individual methods of artificial neural networks and support vector machines can be an effective help in improving the performance of the above models. The t-test analysis indicated that at a 5% significance level, the null hypothesis (H0: µ1 = µ2) was accepted only for the hybrid Wavelet-ANN and Wavelet-SVM models, while the alternative hypothesis (H1: µ1 ≠ µ2) was accepted for the standalone ANN and SVM models. Thus, at Samiyan station, hybridizing the individual artificial neural network model with the wavelet model has increased and decreased the R and RMSE parameters from 0.48 and 1.96 m3s-1 to 0.82 and 1.02 m3s-1, respectively. Also, at Doostbighlou station, integrating artificial neural network and support vector machine models with wavelet transform analysis significantly improved their correlation coefficients, increasing them from 0.39 and 0.45 to 0.77 and 0.72, respectively.


Keywords


Hybrid wavelet, Hydrological variables, Time-delayed, Stream flow.

Full Text:

PDF

References


ADAMOWSKI J. (2013). Using support vector regression to predict direct runoff, base flow and total flow in a mountainous watershed with limited data in Uttaranchal, India, Versita, Vol. 45, Issue 5, pp. 71-83.

ANDALIB G., NOURANI V., MONIRIFAR H., SHARGHI E. (2020). Development of hybrid wavelet-artificial neural network and support vector machine approach for multi-station rainfall-runoff modeling using clustering and mutual information tools, New approaches in civil engineering, Vol. 3, Issue 2, pp. 49-62.

ARGAZ A. (2018). 1D model application for integrated water resources planning and evaluation: case study of Souss river basin, Morocco, Larhyss Journal, No 36, pp. 217-229.

ASSEMIAN A.E., DJE BI DOUTIN S., SAMAKÉ Y. (2021). Consequences of the effects of climate change on water resources in a humic tropical zone of central eastern Côte d’Ivoire, Larhyss Journal, No 45, pp. 95-105.

ATALLAH M., DJELLOULI F., HAZZEB A. (2024). Rainfall-runoff modeling using the HEC-HMS model for the Mekerra wadi watershed (N-W Algeria), Larhyss Journal, No 57, pp. 187-208.

BAUDHANWALA D., KANTHARIA V., PATEL D., MEHTA D., WAIKHOM S. (2023). Applicability of SWMM for urban flood forecasting a case study of the western zone of Surat city, Larhyss Journal, No 54, pp. 71-83.

BEN SAID M., HAFNAOUI M.A., HACHEMI A., MADI M., BENMALEK A. (2024). Evaluating the effectiveness of the existing flood risk protection measures along wadi Deffa in El-Bayadh city, Algeria, Larhyss Journal, No 59, pp. 7-28.

BENSLIMANE M., BERREKSI A., BENMAMAR S., BOUACH A. (2020). Flood risk numerical simulation of Bejaia city urban zone (Algeria), Larhyss Journal, No 42, pp. 167-178.

CANNAS B., FANNI A., SEE L., SIAS G. (2006). Data preprocessing for river flow forecasting using neural network: wavelet transforms and data partitioning, Physics and Chemistry of the Earth, Vol. 31, Issue 18, pp. 1164-1171.

CHABOKPOUR J., AZAMATHULLA H.M.D. (2025). Multi-scale CFD analysis of erosion dynamics in heterogeneous rockfill structures implications for sustainable hydraulic engineering design, Larhyss Journal, No 61, pp. 217-239.

CHADEE A., NARRA M., MEHTA D., ANDREW J., AZAMATHULLA H. (2023). Impact of climate change on water resource engineering in Trinidad and Tobago, Larhyss Journal, No 55, pp. 215-229.

CHIBANE B., ALI-RAHMANI S.E. (2015). Hydrological based model to estimate groundwater recharge, real- evapotranspiration and runoff in semi-arid area, Larhyss Journal, No 23, pp. 231-242.

DEHGHANI R., TORABIPOODEH H., YOUNESI H., SHAHINJAD B. (2022). Application of hybrid support vector machine wavelet (WSVM) model in predicting river flow, case study: Dez watershed, Watershed Engineering and Management, Vol. 13, Issue 1, pp. 98-110.

DO T.V.H., PHAM H.G., KIEU Q.L., TRAN T.N.H. (2025). The typical mechanisms and factors leading to flash floods in small watersheds in the mountainous region of Vietnam, a case study in the CHU VA stream watershed, Larhyss Journal, No 61, pp. 141-168.

ERICH C.F., GILMOUR J., MACHIN T., HENDRY L. (2022). Statistics for Research Students, 1st edition, University of Southern Queensland, Toowoomba, 101p.

ESFANDIYARI F., QARACHOORLOO M. (2023). Regional estimation of sediment yield using monthly sediment rating curve in Qarasu watershed, Journal of Applied Research in Geographical Sciences, Vol. 23, Issue 69, pp. 33-52.

ESKANDARI A., NOURI R. (2010). Developing a Proper Model for Online Estimation of the 5-Day Biochemical Oxygen Demand Based on Artificial Neural Network and Support Vector Machine, Ecology, Vol. 38, Issue 61, pp. 76-84.

EZZ H. (2025). Unexpected flooding in Mersa Matruh, Egypt - Investigating causes, hydrological analysis, and flood risk assessment, Larhyss Journal, No 61, pp. 371-399.

FARAJZADEH J., FAKHERI FARD A., LOTFI S. (2014). Modeling of monthly rainfall and runoff of Urmia Lake basin using feed-forward neural network and time series analysis model, Water Resources and Industry, Vol. 7, Issue 8, pp. 38-48.

http://cda.psych.uiuc.edu/matlab_pdf/wavelet_ug.pdf

FAREGH W., BENKHALED A. (2016). GIS based SCS-CN method for estimating runoff in Sigus watershed, Larhyss Journal, No 27, pp. 257-276. (In French)

JELISAVKA B., GORAN R. (2018). Irrigation of agricultural land in Montenegro: overview, Larhyss Journal, No 33, pp. 7-24.

KALTEH A.M. (2013). Monthly River flow forecasting using artificial neural network and support vector regression models coupled with wavelet transform, Computers and Geosciences, Vol. 54, Issue 2, pp. 1-8.

KANTHARIA V., MEHTA D., KUMAR V., SHAIKH M.P., JHA S. (2024). Rainfall–runoff modeling using an Adaptive Neuro-Fuzzy Inference System considering soil moisture for the Damanganga basin, Journal of Water and Climate Change, Vol. 15, Issue 5, pp. 2518-2531.

KANTHARIA V.C., MEHTA D.J. (2024). Integrated rainfall-runoff modelling using fuzzy logic considering soil moisture: case study of Damanganga Basin, International Journal of Hydrology Science and Technology, Vol. 18, Issue 3, pp. 300-318. DOI:10.1504/IJHST.2024.140855

KAVZOGLU T., COLKESEN I. (2009). A kernel functions analysis for support vector machines for land cover classification, International Journal of Applied Earth Observation and Geoinformation, Vol. 11, Issue 5, pp. 352-359.

KIANI ASL M.A., MOTESHAFFEH B., ROSHAAN S.H. (2023). Evaluation of machine earning algorithms (RF and SVM) in producing flood susceptibility mapping Maroon watershed, Iran-Watershed Management Science and Engineering, Vol. 17, Issue 61, pp. 51- 52.

KOUA T., ANOH K., EBLIN S.., KOUASSI K., KOUAME K. (2019). Rainfall and runoff study in climate change context in the buyo lake watershed (southwest Côte d'Ivoire), Larhyss Journal, No 39, pp. 229-258. (In French)

KUMAR V., KEDAM N., SHARMA K.V., MEHTA D., CALOIERO T. (2023). Advanced machine learning techniques to improve hydrological prediction: A comparative analysis of streamflow prediction models, Water, Vol. 15, Issue 14, pp. 1-24.

DOI:10.3390/w15142572

MEHTA D., DHABUWALA J., YADAV S.M., KUMAR V., AZAMATHULLA H.M. (2023). Improving flood forecasting in Narmada River basin using hierarchical clustering and hydrological modelling, Results in Engineering, Vol. 20, Issue 13, pp. 1-13.

MEHTA D., HADVANI J., KANTHARIYA D., SONAWALA P. (2023). Effect of land use land cover change on runoff characteristics using curve number: A GIS and remote sensing approach, International Journal of Hydrology Science and Technology, Vol. 16, Issue 1, pp. 1-16.

MEHTA D., YADAV S. (2024). Rainfall runoff modelling using HEC-HMS model: case study of Purna river basin, Larhyss Journal, Vol. 59, No 59, pp. 101-118.

MFOUTOU W., DIABANGOUAYA D.B. (2019). Bank erosion on the Mfilou river on Brazzaville, Larhyss Journal, No 39, pp. 299-311. (In French)

MISITI M., MISITI Y., OPPENHEIM G., POGGI J.M. (1996). Wavelet Toolbox, The MathWorks, Inc., Version 3, pp. 2-36.

MORSLI B., HABI M., BOUCHEKARA B. (2017). Study of marine intrusion in coastal aquifers and its repercussions on the land degradation by the use of a multidisciplinary approach, Larhyss Journal, No 30, pp. 225-237. (In French)

MUSHTAQ H., AKHTAR T., HASHMI M.Z., MASOOD A., SAEED F. (2024). Hydrologic interpretation of machine learning models for 10-daily stream flow simulation in climate sensitive upper Indus catchments, Theoretical and Applied Climatology, Vol. 155, Issue 6, pp. 1-18.

NIANG D., YACOUBA H., DOTO C.V, KARAMBIRI H., LAHMAR R. (2015). Land degradation impact on water transfer of soil-plant-atmosphere continuum in the Burkinabe Sahel, Larhyss Journal, No 24, pp. 109-127.

PANDA C., PANDA K.C., SINGH R.M., SINGH R., SINGH V.P. (2025). A generalized hydrological model for stream flow prediction using wavelet ensembling, Journal of Hydrology, Vol. 655, Issue 2.

PANG J.M., TAN K.W. (2023). Development of regional climate model (RCM) for Cameron highlands based on representative concentration pathways (RCP) 4.5 and 8.5, Larhyss Journal, No 54, pp. 55-70.

RIAHI R., BELAID H., HATIRA A., BACCOUCHE S. (2020). Contribution to the study of runoff and erosion of low slope homogeneous hydrological units of a watershed of the middle valley of Medjerda Tunisia, Larhyss Journal, No 43, pp. 119-137.

ROUISSAT B., SMAIL N. (2022). Contribution of water resource systems analysis for the dynamics of territorial rebalancing, case of Tafna system, Algeria, Larhyss Journal, No 50, pp. 69-94.

SAMANTARAY S., SAWAN S., SAHOO A., SATAPATHY P.S. (2022). Monthly runoff prediction at Baitarani River basin by support vector machine based on Salp swarm algorithm, Ain Shams Engineering Journal, Vol. 13, Issue 5, pp. 1-18.

TAIE SEMIROMI M., KOCH M. (2024). Statistical downscaling of precipitation in northwestern Iran using a hybrid model of discrete wavelet transform, artificial neural networks, and quantile mapping, Theoretical and Applied Climatology, Vol. 155, Issue 7, pp. 6591-6691.

VERMA S., KUMAR K., VERMA M.K., PRASAD A.D., MEHTA D., RATHNAYAKE U. (2023). Comparative analysis of CMIP5 and CMIP6 in conjunction with the hydrological processes of reservoir catchment, Chhattisgarh, India, Journal of Hydrology: Regional Studies, Vol. 50, pp. 1-42.

DOI: 10.1016/j.ejrh.2023.101533

ZARE ABYANEH H., BAYAT VARKSHI M., AKHAVAN S., MOHAMMADI M. (2010). Estimation of nitrate in Hamedan-Bahar plain groundwater using ANN and the effect of data resolution on prediction accuracy, Journal of Environment Studies, Vol. 37, Issue 58, pp. 129-140.

ZERKAOUI L., BENSLIMANE M., HAMIMED A., KHALDI A. (2016). Land development issues and water use conflict in mountain areas, case of the Beni Chougrane mountains (northwestern Algeria), Larhyss Journal, No 26, pp. 209-223. (In French).


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.