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为科学合理选择适宜的水土保持措施,利用特尔斐(Delphi)法和模糊数学原理,对紫色土丘陵区典型水土保持措施进行区域适宜性评价。以问卷调查为基础进行评价指标的筛选,从“求-供”和“产-望”2个角度建立2套评价指标体系。根据评价指标与水土保持措施适宜性之间的关系选择单项指标评价模型,采用特尔斐法确定各评价指标的权重,最后结合加权求和与几何平均方法对水土保持措施适宜性进行综合评价,并以四川省遂宁市群力村为例进行实证研究。结果表明:研究专家注重措施的水土保持效益和自然环境效益,当地农民则看重措施实施后的社会经济效益;在群力村较为普遍的4种水土保持措施中,退耕还草最为适宜,其次为退耕还林,等高耕作和梯田的适宜性相对较小,与实际推广情况一致;梯田和等高耕作的适宜性较低主要受到农村劳动力数量、农民投资能力和措施社会经济效益的限制。
In order to select proper soil and water conservation measures scientifically and reasonably, Delphi method and fuzzy mathematics are used to evaluate the regional suitability of typical soil and water conservation measures in the hilly area of purple soil. Based on the questionnaire survey, the evaluation indexes are screened, and two sets of evaluation index system are established from the perspective of “begging for ” and “producing hope ”. According to the relationship between evaluation index and suitability of soil and water conservation measures, the single index evaluation model is selected, and the weight of each evaluation index is determined by using Delphi method. Finally, the suitability of soil and water conservation measures is evaluated comprehensively by means of weighted summation and geometric mean. Taking Qunli Village of Suining City in Sichuan Province as an example, an empirical study was conducted. The results show that: the research experts pay attention to the soil and water conservation benefits and the natural environment benefits of the measures, while the local farmers value the social and economic benefits after the measures are implemented. Among the four kinds of soil and water conservation measures that are more common in Qunli Village, returning farmland to grassland is the most appropriate The suitability of the conversion of cropland to forest and contouring and terrace is relatively small, which is consistent with the actual promotion. The low suitability of terraced fields and contour tillage is mainly limited by the number of rural labor force, peasants’ investment ability and the social and economic benefits of the measures.