农户对节水型农业种植结构调整意愿的量化分析-- 以黑河干流中游为例

Quantitative analysis of farmer attitude towards water-saving plantingstructure adjustment: A case study of Heihe River middle reaches

  • 摘要: 通过探究农户对节水型农业种植结构调整的接受意愿, 提出合理性对策以确保其顺利实施, 从而提高作物群体用水效率, 保障未来干旱缺水地区的粮食安全和农业发展。基于黑河流域中游3个灌区200位农户的调查问卷及入户访谈所取得的具体调查资料, 分别运用Logistic回归中的Enter法和Backward conditional法分析农户对节水型种植结构调整的意愿及其关键影响因素。结果表明, 节水型种植结构调整接受率与农户文化程度、劳动力人口数、耕地面积、兼业程度、政府是否参与、农户节水意识等因素呈显著正相关, 与农户年龄、上一季种植作物种类数、商业化程度、农户风险意识等其他因素呈负相关。在此基础上, 对影响节水型种植结构调整接受率的关键因素按重要性进行排序为: 年龄>政府是否参与>农户节水意识>兼业程度>农户文化程度>耕地面积, 其中年龄和政府是否参与2个变量的显著水平分别达到0.002和0.044。此外还构建了关键因素与种植业结构调整接受率的概率关系式。从拟合效果来看, 模型拟合值与观测值的吻合度高达78%, 说明模型拟合结果较好。基于实证结果, 提出依靠示范户带动整体、加强宣传培训及科技投入力度、强化惠农经济补偿、重视政府导向地位等措施, 可保证节水型农业种植结构调整的顺利实施。

     

    Abstract: To ensure smooth implementation of water-saving planting structure adjustment, countermeasures were proposed by analyzing farmer attitude toward it. It was important for increasing crop water use efficiency, ensuring food security and agricultural development in water deficient districts. Based on survey data (by questionnaire and household interviews) of 200 farmers in 3 irri-gation districts in the middle reaches of Heihe River Basin, the Enter and Backward conditional methods of Logistic Regression were used to analyze the factors affecting farmer attitude towards crop planning structure adjustment. The results indicated that education, ratio of labor force, arable land area, commercialization degree, government participation and water-saving consciousness were posi-tively related with planting structure adjustment adoption. Also farmer age, previous season crop number, commercialization degree and risk consciousness were negatively related with planting structure adjustment adoption. Based on above analysis, key factors of supportive ratios of planting structure adjustment were sequenced in order of importance as: age > government participation > wa-ter-saving consciousness > commercialization degree > education > arable land area. Among these factors, age and government partici-pation were most critical, with significant levels of 0.002 and 0.044, respectively. Also a probability equation between five key factors and supportive ratios was developed. The regression results showed that the goodness of fit between model and observed values was 78%, suggesting a good regression relation. Finally, several countermeasures were put forward to boost implementation of wa-ter-saving planting structure adjustment with model-simulated ones. They were reinforced propaganda trainings and investments in sci-ence and technology, strengthening economic compensations and farmer benefits, and emphasizing government guidance.

     

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