5. Conclusions
Given the frequent shortage of hydrologic and water quality monitoring data, the distributed models, in some cases cannot be applied to the challenge of diffuse pollution control. Based on the preliminary analysis from this study, the strength of spatial correlation analysis lies in its simplicity and in the fact that it has the advantage of assessing diffuse N loading. Spatial relationships were grouped into sub-basins of rice paddies and uplands, a distinction based on the crops produced. The spatial correlations of eight soil parameters with diffuse N loading at two depths proved that the assumption made Compared to the existing distributed model or field monitoring, these simplified quantitative N loading indicators can assess diffuse N loading effectively without requiring a large amount of monitoring data and can be useful in developing guidelines for basin management. The method presented will be useful in characterizing the influence of soil properties and land use on diffuse N yield, which is more flexible and compatible than the previous application of the SWAT model. The study also differentiated between the effects of agricultural development and practice on soil quality. These indicators could be popular in management of agricultural basin with monitored soil property data. Future research efforts will focus on incorporating historic soil property data into modeling for smaller basins and developing a deeper understanding of the spatial relationship of soil properties and diffuse N loading.
5. Conclusions Given the frequent shortage of hydrologic and water quality monitoring data, the distributed models, in some cases cannot be applied to the challenge of diffuse pollution control. Based on the preliminary analysis from this study, the strength of spatial correlation analysis lies in its simplicity and in the fact that it has the advantage of assessing diffuse N loading. Spatial relationships were grouped into sub-basins of rice paddies and uplands, a distinction based on the crops produced. The spatial correlations of eight soil parameters with diffuse N loading at two depths proved that the assumption made Compared to the existing distributed model or field monitoring, these simplified quantitative N loading indicators can assess diffuse N loading effectively without requiring a large amount of monitoring data and can be useful in developing guidelines for basin management. The method presented will be useful in characterizing the influence of soil properties and land use on diffuse N yield, which is more flexible and compatible than the previous application of the SWAT model. The study also differentiated between the effects of agricultural development and practice on soil quality. These indicators could be popular in management of agricultural basin with monitored soil property data. Future research efforts will focus on incorporating historic soil property data into modeling for smaller basins and developing a deeper understanding of the spatial relationship of soil properties and diffuse N loading.
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