Simulation Of Monthly Agricultural Runoff Pollution In East Tiaoxi River Basin

In recent years, people come to realize that non-point source, especially agricultural non-point source, is a particularly important factor affecting the water quality of watershed. Estimate of agricultural non-point source contributing to total water pollution in China range up to81%for nitrogen and to93%for phosphorus. Different from point sources, which are intensively discharged from industry and domestic sewage emission, agricultural non-point source is influenced by various factors, produced with randomness, and originated from the scattered and diverse areas. These characteristics make it harder to research and control the agricultural non-point source. Lots of researchers have made progresses in agricultural runoff pollutants on producing mechanism, influencing factors and pollution hazards. Many scholars propose agricultural non-point source water pollutants estimation models, which correspond to some specific watersheds. Export coefficient model is the most common model, and many scholars improved and developed it in order to make it suitable for their survey regions, which greatly promoted its research and application.Influenced by crop rotation and rainfall fluctuation, the agricultural runoff pollution load estimated by traditional export coefficient model had a low accuracy. Based on export coefficient model improved by previous scholars, this study chose the amount of monthly nitrogen and phosphorus production from different crops and administrative areas as the study objects. Monthly rainfall in administrative regions was extracted by MM5model, and other geographical factors were also considered to correct the export coefficient. Based on different periods of crop rotation in the basin, modified export coefficient model was applied to estimate the amount of monthly nitrogen and phosphorus production. According to the results, the spatial and temporal characteristics were summed up. Correlation between calculation results and actual monitoring concentration values was analyzed by Pearson Correlation Coefficient with SPSS as well. This paper eventually got a comprehensive scientific assessment on agricultural runoff emissions status, thus provided theoretical and practical basis for the non-point source pollution control and new ideas for the latter in-depth studies.In this study, the monthly trend correlation between the simulated values and the actual nonitoring concentration values of TN and TP were analyzed. Take TN for example, Pearson coefficient of TN estimated value and monitoring concentration value was0.796, the sgnificance P was far less than0.05. The result confirmed that they had approximate variation endency. It was shown that the irrigated land emission was170.55t, which had a large contribution to the emissions of TN in July. Total crop TN emission in June was158.11t, in which108.38t was from vegetables and fruits emission. Followed by paddy fields, the TN emission of rice was184.31t in July and168.14t in June; the TN emission of sugar TN was the lowest, its emission was nearly0in November and December. Therefore, effective measures, such as adjusting the proportion of crop land use, must be taken to control pollutant emissions from vegetables, fruits and rice.