Development and Assessment of a New Framework for Agricultural Nonpoint Source Pollution Control

The transport of agricultural nonpoint source (NPS) pollutants in water pathways is affected by various factors such as precipitation, terrain, soil erosion, surface and subsurface flows, soil texture, land management, and vegetation coverage. In this study, based on the transmission mechanism of NPS pollutants, we constructed a five-factor model for predicting the path-through rate of NPS pollutants. The five indices of the hydrological processes, namely the precipitation index (α), terrain index (β), runoff index (TI), subsurface runoff index (LI), and buffer strip retention index (RI), are integrated with the pollution source data, including the rural living, livestock and farmland data, obtained from the national pollution source census. The proposed model was applied to the headwater of the Miyun Reservoir watershed for identifying the areas with high path-through rates of agricultural NPS pollutants. The results demonstrated the following. (1) The simulation accuracy of the model is acceptable in mesoscale watersheds. The total nitrogen (TN) and total phosphorus (TP) agriculture loads were determined as 705.11 t and 3.16 t in 2014, with the relative errors of the simulations being 19.62% and 24.45%, respectively. (2) From the spatial distribution of the agricultural NPS, the TN and TP resource loads were mainly distributed among the upstream of Dage and downstream of Taishitun, as well as the towns of Bakshiying and Gaoling. The major source of TN was found to be farmland, accounting for 47.6%, followed by livestock, accounting for 37.4%. However, the path-through rates of TP were different from those of TN; rural living was the main TP source (65%). (3) The path-through rates of agricultural NPS were the highest for the towns of Wudaoying, Dage, Tuchengzi, Anchungoumen, and Huodoushan, where the path-through rate of TN ranged from 0.17 to 0.26. As for TP, it was highest in Wudaoying, Kulongshan, Dage, and Tuchengzi, with values ranging from 0.012 to 0.019. (4) A comprehensive analysis of the distribution of the NPS pollution load and the path-through rate revealed the towns of Dage, Wudaoying, and Tuchengzi as the critical source areas of agricultural NPS pollutants. Therefore, these towns should be seriously considered for effective watershed management. In addition, compared with field monitoring, the export coefficient model, and the physical-based model, the proposed five-factor model, which is based on the path-through rate and the mechanism of agricultural NPS pollutant transfer, cannot only obtain the spatial distribution characteristics of the path-through rate on a field scale but also be applicable to large-scale watersheds for estimating the path-through rates of NPS pollutants.

Statistical Analysis and Review of Event Mean Concentrations in Stormwater Runoff from Agricultural Nonpoint Source Pollution among Different Land Use Types

Objectives : In this study, the characteristics of stormwater runoff from agricultural nonpoint pollution sources investigated under various experimental conditions were evaluated among different land use types (e.g., paddy, field, field (alpine), and vinyl house), and event mean concentrations (EMCs) for each water quality parameter were statistically analyzed. These results can be used in calculating the contribution of stormwater runoff to water quality of receiving water body by performing quantitative and qualitative analysis. The unit loads calculated were compared with Ministry of Environment TMDL (2019) to secure the reliability of the calculated unit loads.Methods : EMCs and unit loads investigated in various studies were classified in terms of paddy, field, field (alpine), and vinyl house. Among various land use types, EMCs and unit loads were statistically analyzed quantitatively and qualitatively. For EMCs, a null hypothesis is that ‘EMCs of water quality parameters among different land use types are not different at a statistically significant level (α=0.05)’. Based on the results of statistical analysis, heteroscedasticity (p<0.05) and Welch-test method were consequently applied, and post hoc test was performed using the Games-Howell method. Finally, unit loads was compared and reviewed against the TMDL (2019) unit loads of the Ministry of Environment.Results and Discussion : Various EMCs in all water quality parameters were found among different land use types (i.e., paddy, field, field (alpine) and vinyl house). For most water quality parameters, EMCs tended to decrease in the order of field (alpine) > field > vinyl house > paddy. The coefficient of variance (CV) values of all water q uality parameters were 0.5 or greater. Based on these results, EMCs in agricultural nonpoint source pollution are very diverse and deviated due to the combination of natural and artificial factors. Post hoc test results indicated different statistical significance among all water quality parameters. In addition to the land use types, both natural factors (i.e., season, rainfall, antecedent rainfall day, and, rainfall runoff rate) and artificial factors (i.e., cultivator manipulation, emission route, type of crop, and amount of compost) affect the characteristics of stormwater runoff. In particular, in the case of field (alpine) with prominent topographical feature of slope, and EMCs were statistically greater than those from other land use types in all water quality categories (p<0.05).Conclusions : Countermeasures for field (alpine)with greater EMCs than paddy, field and vinyl house, should be performed priority. EMCs were affected by a complex interaction between natural factors (i.e., season, rainfall, antecedent rainfall day, and, rainfall runoff rate) and artificial factors (i.e., cultivator manipulation, emission route, type of crop, and amount of compost), and additional data and research are required for further study to elucidate these complex interactions.

Can Increasing Scale Efficiency Curb Agricultural Nonpoint Source Pollution?

The Chinese government has made great efforts to improve the scale efficiency of land through various measures during recent years, hoping to realize the coordinated developing goal of promoting agricultural benefits and protecting the environment. Statistics show that China’s land scale efficiency has steadily increased, but agricultural nonpoint source (NPS) pollution has also increased, which seems contrary to the expected outcome. Can increasing scale efficiency really curb agricultural NPS pollution? This study uses provincial-level data from China, together with a panel model and spatial econometric model, to investigate the relationship between scale efficiency and agricultural NPS pollution. It is found that the increase of scale efficiency aggravates the agricultural NPS pollution, and the conclusion still holds after considering spatial effect. The results of spatial analysis shows that the agricultural NPS pollution is spatially dependent. Further decomposition of the spatial effect shows that the scale efficiency not only intensifies the local agricultural NPS pollution, but also has a spillover effect (though not statistically significant) on agricultural NPS pollution in the surrounding areas. It is worth noting that financial policy, raising wage income and upgrading industrial structure can effectively curb agricultural NPS pollution in this region and adjacent areas, which also deserves our attention in the control of agricultural NPS pollution. In addition, it is necessary to make financial and fiscal support policies specifically for the governance of agricultural NPS pollution, adjust the distorted prices of input factors such as chemicals and pesticide, and accelerate the transformation of small-sized farmers to family farms, in order to maximize the inhibitory effect of scale efficiency on relieving agricultural NPS pollution.

‘Get a Fish’ vs. ‘Get a Fishing Skill’: Farmers’ Preferred Compensation Methods to Control Agricultural Nonpoint Source Pollution

Ecological compensation is an important means for controlling agricultural nonpoint source pollution, and compensation methods comprise an essential part of the compensation policy for mitigating this form of pollution. Farmers’ choice of compensation methods affects their response to compensation policies as well as the effects of pollution control and ecological compensation efficiency. This study divides ecological compensation methods into two distinct philosophies—the “get a fish” method (GFM) and “get a fishing skill” method (GFSM)—based on policy objectives, to determine farmers’ choice between the two methods and the factors influencing this choice. Furthermore, by analyzing survey data of 632 farmers in the Ankang and Hanzhong cities in China and using the multivariate probit model, the study determines farmers’ preferred option among four specific compensation modes of GFM and GFSM. The three main results are as follows. (1) The probability of farmers choosing GFM is 82%, while that of choosing GFSM is 51%. Therefore, GFM should receive more attention in compensation policies relating to agricultural nonpoint source pollution control. (2) Of the four compensation modes, the study finds a substitution effect between farmers’ choice of capital and technology compensations, capital and project compensations, material and project compensations, while there is a complementary relationship between the choice of material and technology compensations. Therefore, when constructing the compensation policy basket, attention should be given to achieving an organic combination of different compensation methods. (3) Highly educated, young, and male farmers with lower part-time employment, large cultivated land, and a high level of eco-friendly technology adoption and policy understanding are more likely to choose GFSM. Hence, the government should prioritize promoting GFSM for farmers with these characteristics, thereby creating a demonstration effect to encourage transition from GFM to GFSM.

Regionalization of Agricultural Nonpoint Source Pollution over China with a Combination of Qualitative and Quantitative Method

Agricultural nonpoint source pollution has been a serious problem in China; however, currently a lack of basic data and quantitative analysis hinders control and reduction of agricultural nonpoint source pollution. Therefore, it is necessary to explore a regionalization method in the study of nationwide agricultural nonpoint source pollution over China. This paper proposes a method of combining both quantitative calculation and qualitative analysis. Based on agricultural nonpoint source pollution mechanism, we first proposed the natural environment index, which was calculated from relief degree of land surface, thermal humidity index, water resources quantity and precipitation index, and land cover index. Second, we proposed basic agricultural environment index, which was calculated based on the area of cultivated land use and the quality of integrated soil fertility. Third, we simplified the spatial distribution of natural environment and basic agricultural environment with the method of choropleth map classification, thematic map series, and gravity centers curve. Fourth, we conducted a qualitative analysis for both the natural environment and basic agricultural environment by overlaying the classification and existing regionalization maps to reveal the intra-region homogeneity and inter-region heterogeneity with a high reliability. The regionalization method used in this study resulted in a nationwide regional zoning of agricultural nonpoint source pollution over China, and China can be divided into 10 regions, which can be a trustworthy reference for agricultural nonpoint source pollution study and management.