Farmers’ Willingness as Well as Its Compensation Strategy to Prevent and Control Agricultural Non-Point Source Pollution in Water Source Areas-Based on a Comparative Analysis of Pesticide and Fertilizer Inputs

Abstract

This paper took the voluntary pesticide and fertilizer reduction ratios of the farmers as the substitute variables for farmers' willingness to prevent and control the agricultural non-point source pollution. Then, the paper adopted an improved double-bounded dichotomous choice (DBDC) to obtain farmers’ voluntary pesticide and fertilizer reduction ratios and the corresponding compensation attitudes of the farmers. The research found that, in contrast to fertilizers, pesticides are a stronger output-related factor for farmers, and any reduction in pesticides would cause great output fluctuations. After the influencing factors of the farmers’ compensation attitude towards pesticide and fertilizer reduction were subject to ordinal regression analysis, the main influencing factors of farmers’ compensation attitude towards fertilizer and pesticide reduction were obtained respectively, which had further proved that for farmers, compared with pesticides, the risk of fertilizer reduction is lower, and their attitudes are quite different, but as long as the compensation is sufficient, they are willing to take more stringent measures.

Incentive Measures for Agricultural Nonpoint Source Pollution Control of Farmers Based on Choice Modelling: A Case Study on the Water Source Region of Xin’an River Reservoir

“…Meanwhile, the existing literature has realized that fertilizers and pesticides are core input elements of modern agricultural production, which overlap and lead to most agricultural nonpoint source pollution [30,31]. Nevertheless, the vast majority of studies on the governance of the ecological environment, such as the study of Zheng et al [32], still choose to separate fertilizers from pesticides and study them as two independent decision-making projects.…”

Application of Data Visualization and Big Data Analysis in Intelligent Agriculture

“…As a large agricultural country, China far exceeds the other countries in the total population involved in agricultural production and the coverage of agricultural production equipment. However, the country faces obvious defects in productivity, crop yield, and quality of agricultural products [1][2][3][4].…”

Multi Node Based Smart Monitoring System with Motor Dry Run Avoidance for Sustainable Agriculture

“…Hence there is a need to schedule or control the usage of energy resources in agriculture [2]. Climatic changes, plantation density, soil pollution due to pesticides [3,4], air pollution due to road transport vehicles are also impacting the yield in the agriculture. The crops which are closer to roads have greater impact when compared to the faraway fields [5].…”