Mahdian, M., Khorsandi, N., Nikkami, D., Pazira, E., Sarreshtedari, A. (2013). Application of Fuzzy Logic to Some Imprecise Data of Rainfall Erosivity and Its Spatial Variability in Caspian Sea Watershed. , 27(3), 397-404. doi: 10.22092/ijsr.2013.126273
Mohammad Hossein Mahdian; N. Khorsandi; D. Nikkami; Ebrahim Pazira; A. Sarreshtedari. "Application of Fuzzy Logic to Some Imprecise Data of Rainfall Erosivity and Its Spatial Variability in Caspian Sea Watershed". , 27, 3, 2013, 397-404. doi: 10.22092/ijsr.2013.126273
Mahdian, M., Khorsandi, N., Nikkami, D., Pazira, E., Sarreshtedari, A. (2013). 'Application of Fuzzy Logic to Some Imprecise Data of Rainfall Erosivity and Its Spatial Variability in Caspian Sea Watershed', , 27(3), pp. 397-404. doi: 10.22092/ijsr.2013.126273
Mahdian, M., Khorsandi, N., Nikkami, D., Pazira, E., Sarreshtedari, A. Application of Fuzzy Logic to Some Imprecise Data of Rainfall Erosivity and Its Spatial Variability in Caspian Sea Watershed. , 2013; 27(3): 397-404. doi: 10.22092/ijsr.2013.126273

Application of Fuzzy Logic to Some Imprecise Data of Rainfall Erosivity and Its Spatial Variability in Caspian Sea Watershed

پژوهش های خاک
Volume 27, Issue 3, November 2013, Pages 397-404    PDF (401.27 K)
Document Type: Research Paper
DOI: 10.22092/ijsr.2013.126273
Authors
Mohammad Hossein Mahdian* 1; N. Khorsandi2; D. Nikkami3; Ebrahim Pazira4; A. Sarreshtedari5
1Professor, Agricultural Research, Education and Extension Organization
2Assistant professor, Islamic Azad University, Takestan branch
3Professor, Soil Conservation and Watershed Management Institute
4Professor, Islamic Azad University, Science and Research Unit, Tehran branch
5Scientific board, Soil Conservation and Watershed Management Institute
Abstract
Rainfall erosivity (EI30) of the Universal Soil Loss Equation is one of the major factors in soil erosion and sediment yield models. Measurement of this factor is costly and time consuming. Therefore, empirical relationships based on rainfall intensity are used. In many places, however, access to rainfall intensity is limited and rainfall erosivity is estimated by rainfall amount, causing uncertainty in the results. In this research, fuzzy logic was applied to some imprecise data of rainfall erosivity and its spatial variability was evaluated by ordinary kriging, cokriging, spline, local polynomial, global polynomial and inverse distance weighting methods. Among the available parameters or indices of 11 synoptic stations, only Modified Fournier index () showed a significant correlation with EI30 (r2=0.762, P<0.001). Therefore, a regression model was developed for estimating EI30 from FImod in 66 rain gauge stations. Also, the Mamdani inference system and five Gaussian membership functions, were used to investigate the fuzzy interpolation method for elevation as the input and rainfall erosivity as the output variables. The fuzzified sets were transformed to certain data. The nugget to sill ratio (0.23) showed strong spatial correlation in a distant of 630 km of EI30. The negative values of the mean bias error in the fuzzy kriging and fuzzy cokriging methods indicated an underestimation of EI30 values, while its positive values in the other methods demonstrated an overestimation of EI30. The Mean Absolute Error (MAE) of the Fuzzy Cokriging method declined by 28%, 21%, 19%, 22%, 15%, and 11 percent, when compared to that of, respectively, the IDW, kriging, cokriging, spline and fuzzy IDW, fuzzy kriging, and fuzzy spline methods in the study area. The output maps for all of the interpolation methods followed similar decreasing trends in west to east direction of the watershed. The highest value of rainfall erosivity index (1450 MJ mm ha-1 h-1 y-1) was found in the west of the study area. This pattern is similar to the pattern of climatic change from humid to semiarid.  
Keywords
Fuzzy cokriging; Interpolation; Modified Fournier Index
References
  1. خرسندی، ن. 1389. بررسی تغییرات مکانی شاخص فرسایندگی باران در حوزه آبخیز دریای خزر. پایان‌نامه دکتری، دانشکده کشاورزی، دانشگاه آزاد، واحد علوم و تحقیقات.
  2. رحیمی‌بندرآبادی، س. و ب. ثقفیان. 1386. برآورد توزیع مکانی بارندگی با کمک تئوری مجموعه‌های فازی، تحقیقات منابع آب ایران، سال سوم، جلد 2، صفحه 26 الی 38.
  3. رفاهی، ح. ق. 1379. فرسایش آبی و کنترل آن، انتشارات دانشگاه تهران، 672 صفحه.
  4. علی‌پور، ز. ت. 1384، کاربرد فازی کریجینگ برای تهیه نقشه فرسایندگی باران در حوزه دریاچه نمک. پایان‌نامه دکتری، دانشکده کشاورزی، دانشگاه آزاد، واحد علوم و تحقیقات.
  5. Arnoldus, H.M.J. 1980. An approximation to the rainfall factor in the universal soil loss equation. In: Assessment of Erosion (Eds. De Boodt M. and M. Gabriels, Wiley, New York, pp. 127-132.
  6. Brown, L.C. and G.R. Foster. 1987. Storm erosivity using idealized intensity distributions. T. Am. Soc. Agri. Eng., 30:379-386.
  7. Hoyos, N., P.R. Waylen and A. Jaramillo. Seasonal and spatial patterns of erosivity in a tropical watershed of the Colombian Andes. J. Hydrol., 314:177-191.
  8. Kavian, A., Y. Fathollah Nejad, M. Habibnejad and K. 2011. Modeling seasonal rainfall erosivity on a regional scale: A case study from northeastern Iran. Int. J. Environ. Res., 5(4): 939-950.
  9. Mamdani, E.H. and Assilian. 1999. An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Hum-Comput. Stud., 51(2):135-147.
  10. Men, M., Z. Yu and H. 2008. Study on the spatial pattern of rainfall erosivity based on geostatistics in Hebei province, China. Front. Agric. China, 2(3): 281-289.
  11. Piotrowski, J.A., F. Bartels, A. Salski and G. Schmidt. Geostatistical regionalization of glacial aquitard thickness in northwestern Germany based on fuzzy kriging. Math. Geol., 28: 437-452.
  12. Theodossiou, N. and P. Latinopoulos. Evaluation and optimization of groundwater observation networks using the kriging methodology. Environ. Model Softw., 21:991-1000.
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