Water (Dec 2023)

Estimation of Pollutant Load in Typical Drainage Ditches of Ningxia Yellow River Diversion Irrigation Area Based on LOADEST Statistical Model

  • Xiuxia Ma,
  • Wenfa Peng,
  • Bingwei Tong,
  • Taiyun Li,
  • Le Wang,
  • Bin Du,
  • Chaochao Li

DOI
https://doi.org/10.3390/w16010120
Journal volume & issue
Vol. 16, no. 1
p. 120

Abstract

Read online

To comprehensively comprehend the spatiotemporal variations in pollution load within the Sixth Drainage Ditch of the Ningxia Yellow River Diversion Irrigation Area, we employed the LOADEST model. We utilized daily flow data and concentrations of ammonia nitrogen (NH3-N), nitrate nitrogen (NO2-N), total nitrogen (TN), and total phosphorus (TP) to construct regression equations for the pollutant load at four distinct monitoring sections of the Sixth Drainage Ditch. The results unveiled an impressive range of correlation coefficients (R2) for the pollution load regression equations at the four monitoring sections, ranging from 72.42% to 94.4%. This indicates a strong fit for the pollution load regression equations, rendering them suitable for estimating the pollution load of the Sixth Drainage Ditch. Furthermore, the changing patterns of various pollutants in the same monitoring section exhibit a remarkable level of consistency. In each case, they initially experience an upward trajectory followed by a subsequent decrease. Notably, the total nitrogen (TN) load in the drainage area exceeds that of the total phosphorus (TP). The spatial distribution patterns of the total nitrogen (TN) and total phosphorus (TP) load within the Sixth Drainage Ditch exhibit a progressive increase from the upstream to downstream areas. Meanwhile, the spatial distribution characteristics of ammonia nitrogen (NH3-N) and nitrate nitrogen (NO2-N) follow a similar pattern of an initial increase followed by a decrease.

Keywords