1. Introduction
In recent decades the effective pollution abatement measures to the
water quality are sizeable (Hering et al., 2010; Barton et al., 2005;
Hettige et al., 1996) But, in developing countries like India, the water
quality pollution levels are so high, creating existential threats to
biodiversity, as well as threatening economic progress and
sustainability of human lives (World Economic Forum, 2019). India is one
of the foremost agriculture-based economies in the world, with high
fertilizer applications and the excessive nutrients from agricultural
lands, leading to prominent diffuse pollution to the surface water
quality (Central Pollution Control Board, 2016; Bassi et al., 2014). The
high alarming rate of increasing pollutant load of surface water from
industrial accompanies is known from the concentration based discharge
control of point sources, which is already an important task to control
and to achieve water quality targets (Wang et al., 2004). Additionally,
the reduction of diffuse pollution sources is required.
Although urbanization and demographic changes are substantial influences
within the lake’s catchment, land-use changes cause extreme disturbances
of the catchment’s ecosystems and the lake itself. Most studies
demonstrate that land-use changes (Tu 2009; Zampella et al., 2007) as a
driving factor for the environmental, including the physical and
chemical characteristics of surface water bodies and their internal
structure. Improper management of natural resources, coupled with an
ever-increasing population, is responsible for introducing many
impairments of water quality threats. Most of the freshwater resources
are under stress caused by urbanization, and large-scale
industrialization processes are a worldwide concern (Fang et al., 2019;
Holopainen et al., 2016; Liao et al., 2012).
The complexity of several ecosystem functions in the surface water
bodies adversely affected foremost water quality in freshwater lakes
which, in turn, and among others, influence ponds, rivers, streams and
slowly enter into the groundwater (Gilboa et al., 2014; Thevenon et al.,
2011; Banadda et al., 2010). Diffuse pollution caused by agricultural
activities can be carried into adjacent water bodies by surface runoff
and erosion (Taylor et al., 2016; Guo et al., 2010). Such excess of
nutrients accelerates eutrophication and algae blooming in freshwater
ecosystems. Besides, point sources are another significant reason for
the deteriorating water quality in surface water bodies. However, the
spatial and temporal distribution of diffuse pollutants is a challenge.
It is important to monitor these distributions even for a large
catchment area, due to changing climate, land-use, and strong relations
to anthropogenic activities (Shen et al., 2013; Randhir and Tsvetkova
2011). Therefore, it is essential to identify the critical pollution
sources of a catchment and to apply the best management practices (BMPs)
to protect lake water quality.
The Kolleru Lake catchment in India has been taken as a case study for
understanding and modeling of the Spatio-temporal variability in the
pollutant loads, which will be a prerequisite for better management of
agricultural, industrial, and water resources.
In recent decades, the Soil and Water Assessment Tool (SWAT) (Arnold et
al., 1998) has become widely used to model the management of
agricultural catchments for identifying polluted areas. SWAT is a useful
tool for the estimation of both nitrogen and phosphorus (N & P)
emissions and the degree of eutrophication. Both information a necessary
prerequisite for the selection of BMPs from small scale areas (Coffey et
al., 2013; Shang et al., 2012; Kang et al., 2006) to large scale
catchments (Abbaspour et al., 2015; Yalew et al., 2013). The U.S.
Environmental Protection Agency (EPA) recognized the SWAT model and
incorporated it into the EPA’s BASINS (Better Assessment Science
Integrating Point and Non-point Sources) (Abbaspour et al., 2015). Apart
from that, several studies were extended into the SWAT-based
optimization tool for obtaining cost-effective strategies for
sustainable management (Liu et al., 2019; Wallace et al., 2017).
However, due to continuous simulations and operations on a daily time
step, it is a useful tool for the identification of pollutant sources.
The main objective of this study serves a better understanding of
diffuse pollution sources in the Kolleru Lake catchment, a typical flood
balancing catchment between the Krishna and the Godavari basins. Here
the first study is conducted to estimate diffuse pollution in Kolleru
Lake for the catchment level. Further, the study assimilated the
critical sub-basin measures on the Hydrological Response Unit (HRU)
level priority areas, to conclude the planning of BMPs. Furthermore,
suggestions are provided for the implementation of better lake
management practices in the catchment.