ASSESSMENT OF A NON-PARAMETRIC METHOD FOR HYDROLOGIC DATA DISAGGREGATION IN SPACE-TIME BASED ON K-NEAREST NEIGHBORS (CASE STUDY: THREE SUB-BASINS IN WEST OF URMIA LAKE) (TECHNICAL NOTE)

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BATENI M.M.; MONTASERI M.

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Journal: IRAN-WATER RESOURCES RESEARCH Year:2018 | Volume:14 | Issue:1 Page(s): 268-277

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Title

ASSESSMENT OF A NON-PARAMETRIC METHOD FOR HYDROLOGIC DATA DISAGGREGATION IN SPACE-TIME BASED ON K-NEAREST NEIGHBORS (CASE STUDY: THREE SUB-BASINS IN WEST OF URMIA LAKE) (TECHNICAL NOTE)

Author(s)

BATENI M.M. | MONTASERI M. | Issue Writer Certificate

Keywords

NON-PARAMETRIC MODELSQ1

K-NEAREST NEIGHBORQ1

DISAGGREGATION MODELSQ1

HYDROLOGICAL SYSTEMQ1

SYNTHETIC TIME SERIESQ2

Abstract

Stochastic parametric DISAGGREGATION MODELS that maintain spatial and temporal correlation are widely used in hydrology. To avoid high complexity and large number of parameters, which imposes a significant amount of uncertainty to the results, the use of non-parametric disaggregation methods has been widely suggested by researchers as an alternative. Among the non-parametric modeling methods, the K-NEAREST NEIGHBORs method proposed by Prairie et al. gains strong mathematical basis and inherent simplicity. In our work, the modified disaggregation approach of the K-NEAREST NEIGHBORs method is used for temporal and spatial disaggregation of rainfall and river flow values and the method performance is evaluated. The exploited flow and rainfall data corresponded to three stations in three sub-basins located at west of Lake Urmia. The total amount of annual rainfall and flow of the three stations were generated using stochastic lag -1 autoregressive model (AR (1)). Using the non-parametric disaggregation model, the generated annual values were disaggregated into three sub-basins. The annual values for each sub-basin were then disaggregated into different months. Comparing statistics of disaggregated data with those of historical data, showed the good performance of the proposed disagreation model and its ability to disaggregate streamflow and rainfall data.

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APA: Copy

BATENI, M.M., & MONTASERI, M.. (2018). ASSESSMENT OF A NON-PARAMETRIC METHOD FOR HYDROLOGIC DATA DISAGGREGATION IN SPACE-TIME BASED ON K-NEAREST NEIGHBORS (CASE STUDY: THREE SUB-BASINS IN WEST OF URMIA LAKE) (TECHNICAL NOTE). IRAN-WATER RESOURCES RESEARCH, 14(1 ), 268-277. SID. https://sid.ir/paper/100303/en

Vancouver: Copy

BATENI M.M., MONTASERI M.. ASSESSMENT OF A NON-PARAMETRIC METHOD FOR HYDROLOGIC DATA DISAGGREGATION IN SPACE-TIME BASED ON K-NEAREST NEIGHBORS (CASE STUDY: THREE SUB-BASINS IN WEST OF URMIA LAKE) (TECHNICAL NOTE). IRAN-WATER RESOURCES RESEARCH[Internet]. 2018;14(1 ):268-277. Available from: https://sid.ir/paper/100303/en

IEEE: Copy

M.M. BATENI, and M. MONTASERI, “ASSESSMENT OF A NON-PARAMETRIC METHOD FOR HYDROLOGIC DATA DISAGGREGATION IN SPACE-TIME BASED ON K-NEAREST NEIGHBORS (CASE STUDY: THREE SUB-BASINS IN WEST OF URMIA LAKE) (TECHNICAL NOTE),” IRAN-WATER RESOURCES RESEARCH, vol. 14, no. 1 , pp. 268–277, 2018, [Online]. Available: https://sid.ir/paper/100303/en

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