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首页> 外文会议>Sinkholes and the engineering and environmental impacts of karst >Water Level Variation and Prediction of the Pingshan Sinkhole in Guizhou, Southwestern China
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Water Level Variation and Prediction of the Pingshan Sinkhole in Guizhou, Southwestern China

机译：黔西南州坪山污水池水位变化及预报

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摘要

The study area is located in the Houzhai Basin, Guizhou Province, in southwest China. The aquifer is a highly heterogeneous triple porosity karst aquifer with diverse hydraulic properties. The Pingshan Sinkhole serves as a perfectly placed well whose water level records the water level in the aquifer. The rainfall and water level time series from 1990 to 1995 have been analyzed and the results indicate that the observed water level variation can be divided into three stages, i.e. low water level stages, water level decreasing-rising stages and high water level stages.rnA Pingshan Sinkhole water level prediction model has been developed using partial least squares (PLS) regressions and artificial neural network (ANN) methods. The rainfall in the previous 12 hours and the antecedent water level are the main factors influencing the sinkhole water level in the rainy season. The predicted results obtained by the ANN or PLS regression combined with the ANN method are better than the results of PLS regression method alone. The study of the variation and prediction of water level in the Pingshan Sinkhole could benefit the understanding of the hydrological cycle and the hydrogeological conditions in this highly heterogeneous triple porosity karst aquifer.
机译：研究区域位于中国西南部的贵州省后寨盆地。含水层是具有多种水力特性的高度非均质三孔岩溶岩溶含水层。坪山污水池是一个位置理想的井，其水位记录了含水层中的水位。对1990-1995年的降水和水位时间序列进行了分析，结果表明，观测到的水位变化可以分为低水位，高水位下降，高水位三个阶段。利用偏最小二乘（PLS）回归和人工神经网络（ANN）方法开发了坪山污水池水位预测模型。前12小时的降雨和前期水位是影响雨季下沉水位的主要因素。通过ANN或PLS回归结合ANN方法获得的预测结果要比单独使用PLS回归方法获得的结果更好。对平山污水池的水位变化和预测进行研究有助于了解这一高度非均质的三孔岩溶含水层的水文循环和水文地质条件。

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  • 来源
  • 会议地点 Tallahassee FL(US)
  • 作者

    Longcang Shu; Guiming Dong; Lihong Liu; Yufei Tao; Maomei Wang;

  • 作者单位

    State Key Laboratory of Hydrology-Water Resource and Hydraulic Engineering, No.1 Xikang Road Nanjing , 210098, China 210098;

    State Key Laboratory of Hydrology-Water Resource and Hydraulic Engineering, No.1 Xikang Road Nanjing , 210098, China 210098;

    State Key Laboratory of Hydrology-Water Resource and Hydraulic Engineering, No.1 Xikang Road Nanjing , 210098, China 210098;

    State Key Laboratory of Hydrology-Water Resource and Hydraulic Engineering, No.1 Xikang Road Nanjing , 210098, China 210098;

    State Key Laboratory of Hydrology-Water Resource and Hydraulic Engineering, No.1 Xikang Road Nanjing , 210098, China 210098;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 岩溶（喀斯特）地貌学;
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