Abstract

Abstract. The conservation of drinking water source reservoirs has a close relationship between regional economic development and people’s livelihood. Research on the non-point pollution characteristics in its watershed is crucial for reservoir security. Tang Pu Reservoir watershed was selected as the study area. The non-point pollution model of Tang Pu Reservoir was established based on the SWAT (Soil and Water Assessment Tool) model. The model was adjusted to analyse the temporal-spatial distribution patterns of total nitrogen (TN) and total phosphorus (TP). The results showed that the loss of TN and TP in the reservoir watershed were related to precipitation in flood season. And the annual changes showed an "M" shape. It was found that the contribution of loss of TN and TP accounted for 84.5% and 85.3% in high flow years, and for 70.3% and 69.7% in low flow years, respectively. The contributions in normal flow years were 62.9% and 63.3%, respectively. The TN and TP mainly arise from Wangtan town, Gulai town, and Wangyuan town, etc. In addition, it was found that the source of TN and TP showed consistency in space.

Highlights

  • Pollution of water can be divided into point source pollution and non-point source pollution (Cao et al, 2003)

  • It suggested that the model was more optimum to simulate the temporal-spatial distribution patterns of non-point pollution

  • The measured result and simulation results of flow/total nitrogen (TN)/total phosphorus (TP) in the calibration period and the validation period are shown as Figs 2−4

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Summary

INTRODUCTION

Pollution of water can be divided into point source pollution and non-point source pollution (Cao et al, 2003). Dissolved solid pollutants from the non-specific locations feed into the receiving waterbody, causing eutrophication or other forms of contamination, through runoff processes by fluviraption of precipitation or snowmelt (Saleh et al 2000). These pollutants were used in agricultural production, and include large amounts of nitrogen, phosphorus, pesticides, heavy metals, and herbicides, etc. Non-point source pollution from fields was the most prominent.

OVERVIEW OF THE STUDY AREA
Spatial data
Division of sub-watershed and HRU
Calibration and verification of parameters
Parameters Results
TEMPORAL DISTRIBUTION OF NON-POINT SOURCE POLLUTION LOAD
SPATIAL DISTRIBUTION OF NON-POINT SOURCE POLLUTION LOAD
CONCLUSION AND SUGGESTIONS

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