Abstract:

Taking the quality evaluation of meteorological support engineering for High−standard farmland (MSEWFF) as the research object, this thesis utilized the Delphi method to identify determinants of project quality. A comprehensive system of evaluation indices for the quality of the MSEWFF was established, and the Analytic hierarchy process was employed to determine the individual indicator weights. Based on the fuzzy comprehensive evaluation method, a quantifiable model for assessing MSEWFF quality was developed, allowing for the assessment of both overall and individual indicators (including grading and scoring) for targeted projects. It identified strengths and deficiencies in construction quality, thereby providing a reference basis for quality evaluation, planning and enhancement of such engineering projects. The results showed that the project quality evaluation system comprised five first−level indicators−observation station network project, forecast & early warning system, information release system, disaster prevention and mitigation project, and benefit assessment of the meteorological support−which were further divided into eight second−level and 25 third−level indicators. The weight ranking of the five first−level indicators, from highest to lowest, was as follows: observation station network (0.261) > forecast and early warning (0.251)>disaster prevention & mitigation (0.228) > information release (0.154)>benefit assessment (0.106). Notably, the top three higher−weighted primary indicators collectively accounted for 74% of the total weight, indicating their critical role in the project quality evaluation. Although the remaining two first−level indicators (information release and benefit assessment) constituted only 26% of the total weight, they served as important connecting links within the agricultural meteorological service chain. Among the second−level indicators, three pairs of indicators under the same first−level category exhibit nearly comparable weights. For the third−level indicators, irrigation and drainage projects, disaster forecast and warning and timeliness of observational data ranked as the top three highest−weighted indicators. The proposed model was applied to evaluate a case project in Dancheng county, Henan province, yielding a comprehensive quality score of 86.3, which corresponds to a Good rating. Additionally, all five first−level indicators achieved Good ratings, though variations existed among the tertiary indicators. The project demonstrated strong performance in areas such as observation station network construction, meteorological information dissemination systems, and infrastructure and capacity building for disaster prevention and mitigation. However, deficiencies were identified in forecast & early warning accuracy and satisfaction with agricultural meteorological services. The case study validates the effectiveness and applicability of the model and provides a scientific basis for quality assessment and management of such projects.

Key words: High?standard farmland, Meteorological support engineering, Fuzzy comprehensive evaluation method, Engineering quality, Evaluation indices