LI Ruzhong. Estimation of Non-point Source Pollution Loads Under Uncertain Information[J]. Chinese Geographical Science, 2008, 18(4): 348-355. doi: 10.1007/s11769-008-0348-2
Citation: LI Ruzhong. Estimation of Non-point Source Pollution Loads Under Uncertain Information[J]. Chinese Geographical Science, 2008, 18(4): 348-355. doi: 10.1007/s11769-008-0348-2

Estimation of Non-point Source Pollution Loads Under Uncertain Information

doi: 10.1007/s11769-008-0348-2
  • Received Date: 2008-05-02
  • Rev Recd Date: 2008-09-12
  • Publish Date: 2008-12-20
  • Many kinds of uncertainties are involved, such as random, fuzzy, grey, unascertained property and so on, in soil erosion process. To exactly predict the non-point source pollution loads, some uncertainties should be taken into consideration. Aiming at the deficiency of present blind number theory being helpless for fuzziness, a novel blind number, i.e. extended-blind number, was introduced by substituting a set of triangular fuzzy numbers (TFNs), expressed as α-cuts, for interval values in present blind number, and the expected value of extended-blind number was also brought forward by referring to the current blind number theory. On the basis of denoting the parameters of Universal Soil Loss Equation (USLE) as extended-blind parameters, a novel USLE model was established for quantitatively evaluating soil erosion loss and non-point source pollution loads. As a case, the uncertain USLE was employed for predicting the soil erosion loss and non-point source pollution loads of absorbed nitrogen and phosphorus in a district in the Hangbu-Fengle River basin, in the upstream of Chaohu Lake watershed. The results show that it is feasible in theory to extend blind number into fuzzy environment and reliable on conclusion to apply extended-blind number theory for predicting non-point source pollution loads.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Estimation of Non-point Source Pollution Loads Under Uncertain Information

doi: 10.1007/s11769-008-0348-2

Abstract: Many kinds of uncertainties are involved, such as random, fuzzy, grey, unascertained property and so on, in soil erosion process. To exactly predict the non-point source pollution loads, some uncertainties should be taken into consideration. Aiming at the deficiency of present blind number theory being helpless for fuzziness, a novel blind number, i.e. extended-blind number, was introduced by substituting a set of triangular fuzzy numbers (TFNs), expressed as α-cuts, for interval values in present blind number, and the expected value of extended-blind number was also brought forward by referring to the current blind number theory. On the basis of denoting the parameters of Universal Soil Loss Equation (USLE) as extended-blind parameters, a novel USLE model was established for quantitatively evaluating soil erosion loss and non-point source pollution loads. As a case, the uncertain USLE was employed for predicting the soil erosion loss and non-point source pollution loads of absorbed nitrogen and phosphorus in a district in the Hangbu-Fengle River basin, in the upstream of Chaohu Lake watershed. The results show that it is feasible in theory to extend blind number into fuzzy environment and reliable on conclusion to apply extended-blind number theory for predicting non-point source pollution loads.

LI Ruzhong. Estimation of Non-point Source Pollution Loads Under Uncertain Information[J]. Chinese Geographical Science, 2008, 18(4): 348-355. doi: 10.1007/s11769-008-0348-2
Citation: LI Ruzhong. Estimation of Non-point Source Pollution Loads Under Uncertain Information[J]. Chinese Geographical Science, 2008, 18(4): 348-355. doi: 10.1007/s11769-008-0348-2

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