地理科学进展

地理科学进展 ›› 2012, Vol. 31 ›› Issue (3): 324-329.doi: 10.11820/dlkxjz.2012.03.007

• 生态环境 • 上一篇    下一篇

基于熵权的属性识别模型在海水入侵现状评价中的应用

李淼1,2, 夏军1,3, 李福林4, 孟德娟1,2   

  1. 1. 中国科学院陆地水循环及地表过程重点实验室地理科学与资源研究所，北京 100101;
    2. 中国科学院研究生院，北京 100049;
    3. 武汉大学水资源与水电工程科学国家重点实验室，武汉 430072;
    4. 山东省水利科学研究院，济南 250013
  • 收稿日期:2011-10-01 修回日期:2012-02-01 出版日期:2012-03-25 发布日期:2012-03-25
  • 基金资助:
    中国科学院对外合作重点项目计划项目(GJHZ1016)；国家重点基础研究973项目(2010CB428406)。

The Application of Attribute Recognition Model Based on Coefficient of Entropy to the Assessment of Seawater Intrusion

LI Miao1,2, XIA Jun1,3, LI Fulin4, MENG Dejuan1,2   

  1. 1. Key Laboratory ofWater Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China;
    3. State Key Laboratory ofWater Resources and Hydropower Engineering Sciences, Wuhan University,Wuhan 430072, China;
    4.Water Conservancy Research Institute of Shandong Province, Jinan 250013, China
  • Received:2011-10-01 Revised:2012-02-01 Online:2012-03-25 Published:2012-03-25

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15 | 6

摘要： 针对海水入侵现状评价中单指标(Cl-或矿化度)评价方法的片面性和不确定性等问题，本文将熵值理论和属性识别模型相结合，建立了熵权属性识别模型，并将其应用于滨海地区海水入侵现状评价中。以潍北平原8 个海水入侵实测点为应用实例进行研究。结果表明，潍北平原大部分地区海水入侵属于轻度侵染，水质为微咸水，东部地区(6、8 号点位)在5 月份海水入侵属于较严重侵染，但在11 月份侵染程度减缓，可能的原因是气候因素(降水增加、海平面上升)以及人为因素(地下水抽水量减少)等共同影响的结果。同时，5 月及11 月各个测点海水入侵侵染排序略有差异，但是差异较小。通过实例证明，该方法通俗易懂，计算方法简洁明了，便于掌握和应用，为海水入侵现状评价提供了一种可行有效的方法。

关键词: 海水入侵, 评价, 熵权, 潍北平原, 属性识别模型

Abstract: In this study, to solve the question of the one-sidedness and uncertainties when taking an assessment of seawater intrusion by using a single index (such as Cl- or mineralization), an attribute recognition model based on coefficient of entropy theory was built to take an assessment of seawater intrusion in coastal areas, and take a sample application of eight measured wells for seawater intrusion in plain north of Weifang. It is found that the intrusion was mild in most parts of plain north of Weifang where the water quality is brackish water, and more serious intrusion occurred in May, and changed back to mild intrusion in November in the eastern part of the study area (locations No.6 and No.8). There are two possible reasons responsible for this change. The first one is natural factors which include precipitation increases and sea level falls from May to November. The second reason is human activities mainly due to the reduction of groundwater pumping. Meanwhile, there are small differences in the rank of eight measurement wells for seawater intrusion in May and November. The sample application shows that this model is easy to understand and master, and that it provides a feasible and effective method for the assessment of seawater intrusion.

Key words: assessment, attribute recognition model, plain north ofWeifang City, seawater intrusion, weight coefficient by entropy