Evaluation of Different Spatial Interpolation Methods for IMERG Precipitation Zoning in Neyshabur Basin

Document Type : Original Article

Authors

1 Ph.D. student of Water Resource Management and Engineering, Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran.

2 Department of Water and Environmental Engineering, Faculty of Civil Engineering, Shahrood University of Technology, Shahrood, Iran.

10.22044/jhwe.2023.13019.1012

Abstract

Direct measurement of continuous spatial data is almost impossible due to the limitations in data collection. To address this issue, many methods have been proposed for data interpolation. Determining the most suitable interpolation method to describe the amount of precipitation at any point on a certain time scale and in a specific region has been the concern of many researchers. In this study, different spatial interpolation methods were evaluated for predicting the rainfall zoning of IMERG satellite products in Iran's Neyshabur basin for a statistical period of 17 years. For this purpose, 11 interpolation methods including Inverse Distance Weighting (IDW), Spline, Ordinary Kriging (OK), and Universal Kriging (UK) with different techniques were used. Regarding the results of statistical indices for the UK method with quadratic drift (with Bias = -2.85, CC = 0.98, KGE = 0.97, and RMSE = 8.1), this method was the best interpolation technique for zoning rainfall in the Neyshabur basin. Finally, the choice of interpolation method depends on the spatial scale, density of stations, and variability of the data.

Keywords


Adhikary, S.K., Muttil, N., and Yilmaz, A.G., 2017. Cokriging for enhanced spatial interpolation of rainfall in two Australian catchments. Hydrological processes, 31(12): 2143-2161.
Amini, M.A., Torkan, G., Eslamian, S., Zareian, M.J., and Adamowski, J.F., 2019. Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales. Acta Geophysica, 67(1): 191-203.
Berger, J.O., De Oliveira, V., and Sansó, B., 2001. Objective Bayesian analysis of spatially correlated data. Journal of the American Statistical Association, 96(456): 1361-1374.
Cao, W., Hu, J., and Yu, X., 2009. A study on temperature interpolation methods based on GIS, 2009 17th International Conference on Geoinformatics. IEEE, pp. 1-5.
Erdogan, S., 2009. A comparision of interpolation methods for producing digital elevation models at the field scale. Earth surface processes and landforms, 34(3): 366-376.
Esmaeili, F. and Vafakhah, M., 2022. A Comparative Performance Evaluation of Interpolation Methods for Estimating Annual and Monthly Rainfall in the Namak Lake Watershed, Iran. Extension and Development of Watershed Management, 10(36): 1-10.
Fadavi, G., 2015. Comparison of different regional estimation methods for daily minimum temperature (A case study of Isfahan province). Journal of Agricultural Meteorology, 3(2): -.
Golian, S., Asadi Oskouei, E., and Lopez-Baeza, E., 2018. Assessment of interpolation methods for annual and seasonal precipitation in Mashhad plain. Nivar, 42(100-101): 11-20.
Goovaerts, P., 2000. Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of hydrology, 228(1-2): 113-129.
Hassim, M. et al., 2020. Comparison of rainfall interpolation methods in Langat River Basin, IOP Conference Series: Earth and Environmental Science. IOP Publishing, pp. 012018.
Karwariya, S., Dey, P., Bhogal, N.S., Kanga, S., and Singh, S.K., 2021. A Comparative Study of Interpolation Methods for Mapping Soil Properties: A Case Study of Eastern Part of Madhya Pradesh, India. Recent Technologies for Disaster Management and Risk Reduction: Sustainable Community Resilience & Responses: 431-449.
Keblouti, M., Ouerdachi, L., and Boutaghane, H., 2012. Spatial interpolation of annual precipitation in Annaba-Algeria-comparison and evaluation of methods. Energy Procedia, 18: 468-475.
Khaddari, A. et al., 2022. Evaluation of Precipitation Spatial Interpolation Techniques using GIS for Better Prevention of Extreme Events: Case of the Assaka Watershed (Southern Morocco).
Mendez, M. and Calvo-Valverde, L., 2016. Assessing the performance of several rainfall interpolation methods as evaluated by a conceptual hydrological model. Procedia Engineering, 154: 1050-1057.
Moradi, H., 2020. Evaluation of Different Interpolation Methods in Climatic Zones of Ilam Province. Geography and Human Relationships, 2(4): 1-15.
Rata, M., Douaoui, A., Larid, M., and Douaik, A., 2020. Comparison of geostatistical interpolation methods to map annual rainfall in the Chéliff watershed, Algeria. Theoretical and Applied Climatology, 141: 1009-1024.
Seyyed Nezhad Golkhatmi, N., Sanaeinejad, H., Ghahraman, B., and Rezaee Pazhand, H., 2013. Daily rainfall interpolation of Mashhad Drainage basin. Journal of Climate Research, 1392(15): 17-30.
Shadeed, S., Jayyousi, A., Khader, A., Chwala, C., and Kunstmann, H., 2022. Comparative analysis of interpolation methods for rainfall mapping in the Faria catchment, Palestine. An-Najah University Journal for Research-A (Natural Sciences), 36(1): 1-20.
Shi, J. et al., 2022. Comparison of the Performance of IMERG Products and Interpolation-Based Precipitation Estimates in the Middle Reaches of Yellow River Basin. Water, 14(9): 1503.
Taher, L.S.B., 2020. Evaluation of Geostatistical Interpolation Methods for Rainfall data Estimation in Libya. Albahit J Appl Sci, 1(1): 54-9.
Vieux, B.E., 2001. Distributed hydrologic modeling using GIS. Springer.
Xiao, Y. et al., 2016. Geostatistical interpolation model selection based on ArcGIS and spatio-temporal variability analysis of groundwater level in piedmont plains, northwest China. SpringerPlus, 5(1): 1-15.
Zandkarimi, A. and Mokhtari, D., 2018. Accuracy of Various Interpolation Methods in Estimating Rainfall Values to Select the Most Optimal Algorithm (Case Study: Kurdistan Province). Physical Geography Research Quarterly, 50(2): 323-338.
Zhang, X., Lu, X., and Wang, X., 2016. Comparison of Spatial Interpolation Methods Based on Rain Gauges for Annual Precipitation on the Tibetan Plateau. Polish journal of environmental studies, 25(3).
Zhao, W. et al., 2022. Comparison and correction of IDW based wind speed interpolation methods in urbanized Shenzhen. Frontiers of Earth Science: 1-11.