Abstract:

Debris flow, as a common geological disaster, has a complex formation mechanism with numerous influencing factors and multiple uncertainties. To comprehensively consider the synergistic effects of various influencing factors, based on information fusion and uncertainty analysis theory, this paper proposed a debris flow susceptibility evaluation method based on evidence theory and cloud model. Firstly, the BPA function of key evaluation indicators for debris flow susceptibility was calculated using a connection cloud model. Subsequently, the reliability and uncertainty of the indicators' BPA were modified using Lance distance and DENG entropy, respectively, resulting in a corrected BPA. Finally, evidence fusion was performed on the corrected BPA based on Dempster-Shafer (D-S) evidence theory to achieve debris flow susceptibility assessment, followed by a case validation. The results show that the connection cloud model used in this paper overcomes the limitation that the normal cloud model requires indicators to follow the normal distribution when calculating BPA, and it considers the randomness and uncertainty of indicator distribution. The proposed method's evaluation results are generally consistent with those of four other commonly used evidence fusion methods, proving it to be effective and feasible for debris flow susceptibility evaluation. The conflict evidence fusion method improved based on Lance distance and DENG entropy can enhance the convergence speed and precision of evidence fusion, making the results more accurate and reliable.

Key words: connection cloud model(CCM), debris flow, susceptibility evaluation, basic probability assignment (BPA), conflict evidence fusion, Lance distance, DENG entropy, evidence fusion