Design of an Index System for Deep Groundwater Management Efficiency Evaluation: A Case Study in Tianjin City, China

2016 
An effective evaluation system can provide specific and practical suggestions to the deep groundwater management. But such kind of evaluation system has not been proposed in China. In this study, an evaluation index system is specifically developed to evaluate deep groundwater management efficiency. It is composed of three first-level indicators(law enforcement capability, management ability, and management effectiveness) and eleven second-level indicators. The second-level indicators include seven mandatory indicators and four optional indicators. Piecewise linear function is used to normalize the quantitative indicators, and expert scoring method and questionnaire survey method are used to normalize the qualitative indicators. Then a comprehensive indicator weighting evaluation method is used to evaluate the first-level indicators and the target topic. A case study is carried out to evaluate deep groundwater management efficiency in Tianjin City. According to the evaluation score in each period, the management efficiency of every district in Tianjin City gradually improved. The overall evaluation score in the early deep groundwater extraction period is 0.12. After a series of deep groundwater protection efforts, this score reached to 0.61 in 2007, and met the regulation criteria. The evaluation results also showed that the further groundwater management efforts in Tianjin City should be focused on building a dynamic database to collect comprehensive deep well-log data; and on a reasonable design and distribution of the groundwater monitoring network. It demonstrated that the index system is suitable to locate the deficiencies of current groundwater management systems and to guide further improvements. It can then be used to protect deep groundwater.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    0
    References
    1
    Citations
    NaN
    KQI
    []