118
Tecnología y Ciencias del Agua
, vol. VIII, núm. 2, marzo-abril de 2017, pp. 117-126
Wang
et al
.,
Simulation for non-point source pollution based on QUAL2E in the Jinghe River, Shaanxi Province, China
•
ISSN 2007-2422
Introduction
The extensive expansion of agriculture, rapid
urbanization, and large-scale industrialization
in China over the past three decades were
accompanied with inevitable side effects, in-
cluding water pollution, which is getting more
severe each year. Moreover, anthropogenic
activities associated with the revival and deve-
lopment of the Silk Road can further aggravate
the water pollution crisis (Li, Qian, & Wu, 2014;
Li, Qian, Howard, & Wu, 2015). Noteworthy
is that surface water pollution has two main
sources: (a) point source pollutants, such as
industrial wastes and domestic sewage, and (b)
non-point source pollutants, such as pesticides,
herbicides, and fertilizers from agricultural
activities. In addition, pollutants may originate
from recharge of poor-quality groundwater
and deposition of atmospheric pollutants. Once
entering the aquatic environment, these pollu-
tants may alter the composition and functions
of ecosystems, thereby leading to a series of ir-
reversible ecological changes (Huo
et al
., 2014).
While the point source pollution can be moni-
tored by routine procedures and techniques,
the non-point source one is difficult to control
because it comes from the everyday activities
of many different people, such as fertilizing a
lawn, using a pesticide, or constructing a road
or building. The fact that non-point source pol-
lution is dynamic and complex process, which
usually covers extensive areas, makes it quite
problematic to provide an accurate quantifica-
tion of its spatial location, extent, and discharge
volume (Chowdary, Rao, & Sarma, 2005).
In order to face this challenge, numerous
researchers developed various models of the
agricultural non-point source pollution, most
of which are based on different land use pat-
terns (Whitehead, Johnes, & Butterfield, 2002;
Polyakov, Fares, Kubo, Jacobi, & Smith, 2007;
Munafo, Cecchi, Baiocco, & Mancini, 2005).
Although these models are clearly mechanistic,
they require a large number of input data, and
it is difficult to directly monitor some of the
processes for which data are required. Pollutant
mobilization processes and transport to the river
network vary by region and river; studies that
report model simulations at a range of spatial
and temporal scales are also very scarce, so
wide-spread application is constrained by
both the variability in the landscape and lack
of experience (Azzellino, Salvetti, Vismara,
& Bonomo, 2006). We have made progress in
non-point source pollution research in China by
using software combined with remote sensing
(RS) and Geographical Information Systems
(GIS) (Feier, Huanchun, Yingxu, & Dong, 2003;
Guihong & Jiangyong, 2007; Gao, Zhu, Zhou,
Zhi, & Tang, 2008). However, these above
methods are prone to large discrepancies when
there are unique geographical features, complex
landscape types, and diverse land use patterns
in loess regions, which may, to a certain degree,
bias the large-scale simulation results.
In this study, we used the River and Stream
Water Quality Model (QUAL2E) developed by
the United States Environmental Protection
Agency (USEPA, 1992). We also used multi-
variate statistics principal component analysis
(PCA) and factor analysis (FA) (Melching &
Yoon, 1996; Wu, Li, Qian, Duan, & Zhang, 2014)
to examine the sources of non-point pollution
and to highlight the impacts of point and non-
point source pollution on river water quality.
The object of this study was the Shaanxi Reach
of the Jinghe River in Shaanxi province of
China. To provide a robust scientific basis for
reducing water pollution in this area, the point
source and non-point source loads of ammonia
nitrogen and nitrate nitrogen between Jingcun
and Zhangjiashan in dry and wet seasons are
assessed.
Materials and methods
Study area
The Jinghe River originates in the eastern foot-
hills of the Liupan Mountain, Jingyuan County,
Ningxia Hui Autonomous Region. It enters
