3 Materials and
Methods
3.1 SWAT model setup
The SWAT model was developed by the Agriculture Research Service of the
United States Department of Agriculture (Arnold et al., 1998). This
approach was adopted to simulate the diffuse pollution load in the
Kolleru lake catchment. It is a physically-based and semi-distributed
model that operates on a daily step and capable of continuous simulation
over long periods (Gassman et al. 2007). In this study, the SCS (Soil
Conservation Service) (USDA-SCS 1972) curve number was used to calibrate
the surface runoff from daily rainfall data, further potential
evapotranspiration from Penman-Monteith, and sedimentation from the
Modified Universal Soil Loss Equation (MUSLE) (Williams 1976). The model
equations are extensively documented on the official SWAT website
(http://swatmodel.tamu.edu).
The data used in the SWAT model are in two different formats, i.e., from
a spatial and a temporal database. Table 1 outlines the available data
for the SWAT simulation. The spatial data includes the DEM (Digital
Elevation Model) generated using stereo images of ASTER DEM with a
spatial resolution of 30 m. Land-use data were mainly classified into
agricultural land (for paddy cultivation), fishponds, urban, barren land
(unused or uncultivated land), and forest areas (Fig. 2a). The soil
types were categorized into 38 classes (Fig. 2b). The data provide
insights into soil depth, drainage, texture, slope, erosion, salinity,
etc. (Table 2). The temporal data include hydrological parameters, such
as daily precipitation, maximum & minimum temperature, relative
humidity, wind speed, and solar radiation. The mainly used rain gauge
stations were Bhimavaram, Eluru, Gudivada, Nuzvid, and Tadepalligudem.
The catchment weather information used from daily monitoring data for
the period 2008-2014. Information on crop patterns, fertilizer
application, fish farming, social economics, and industrial pollution
was based on previous literature and data collected from local statistic
yearbooks (Azeez et a.. 2011), and on-field investigations as well.
The catchment area is composed of 38 different soil types, dominantly
with clayey texture. According to this data, 46.7 percent of the
catchment is largely extended to the well-drained condition, 19.9
percent is moderately well-drained, while 27.8 percent is composed of
imperfectly drained, and 2.4 percent is excessively drained. Very deep
soils (55 percent) are predominantly identified within the catchment
area, with clay dominance in texture and pore in coarse and medium
pores. Present up-slope in the headwaters are covered by shrub
vegetation and forest areas. The runoff from the upper catchment passes
the agricultural fields of the middle part before entering into the
lake. Agricultural land is the dominant land use cover (68%) of the
catchment, followed by fishponds (16%), mangrove forests on gently
sloped areas (10%), and the urban area does not exceed 3% of the total
area.
Using a digital elevation model (DEM) with 30 m × 30 m resolution, SWAT
delineated the catchment into 20 sub-basins depending on the flow
direction, stream network, and drainage outlets. Slopes were classified
into four gradient categories: <3%, 3-5%, 5-10%, and
>10%. Hydrologic Response Units (HRU) derived from
adjusting thresholds of 12% land-use, 15% soil, and 15% slope. There
are 1,281 feature classes (HRU) that were delineated, while each HRU is
being independent of the SWAT model, with a similar slope, land-use, and
soil characteristics. The model was extensively calibrated against daily
discharge, nitrate pollution (NO3_N), and total
phosphorus (TP) loads in the Kolleru Lake catchment.
3.2 Workflow to Action Plan
After the “Operation Kolleru,” the lake water still received serious
threats by diffuse pollution. Therefore, the state government
authorities approved that the lake was not polluted by the fishponds,
due to agricultural runoff and urban infrastructure. Kolleru Lake
pollution mitigation plans were formulated between 1982 and 2015. The
efforts were taken in 2006 to resolve the pollution by fishponds one
site. Still, the other sources of pollution left for discussion between
researchers, stakeholders, and the state government authorities.
Therefore this paper reports about the identification of priority areas
of diffuse pollution from 2008 to 2014 (after Operation Kolleru), based
on the SWAT model (Fig. 2).
The workflow included four stages: problem definition, preparing a
database and SWAT model execution, identification of priority areas, and
formulation of pollution mitigation measures. The first stage included
the knowledge deficit in this area, discussed with the Kolleru Lake
development programs, especially with the Kolleru Lake Forest Department
(KLFD), Kolleru Lake Development Committee (KLDC), researchers, and
water managers. Researchers and water managers provided the necessary
data for understanding and visualizing the pollution levels in the
catchment. The second stage devoted to the database preparation and
model execution based on the daily time step. The third stage included
the identification of priority areas based on the results obtained from
the SWAT model. Further, the results and necessary actions will be
discussed with the researchers, stakeholders, and state government
authorities. The last stage was the implementation of a measures plan
protecting lake water against pollution.
3.3 BMPs setups and stakeholders
engagements
The first methodological approach has identified the agricultural
management priority areas for applying BMPs to facilitate the relevant
information to the stakeholders. The central and state government
organizations had formulated the Kolleru Lake development programs and
aimed to bring an optimized solution to conserve the lake resources
(Azeez et al., 2011). One such program is the Kolleru Lake Development
Committee (KLDC), which checks the encroachments, regulating or
monitoring the pollution level, and clearing the lake weeds every year.
This study considers the agricultural runoff attributes the first time
for the Kolleru Lake catchment. Thus promotes the awareness of the
decision-makers and stakeholders on values, functions of the stream
network, and variables of the Kolleru Lake catchment.
Furthermore, the potential outcome of the “Operation Kolleru” program
aimed to restore the past glory of the lake. A priority response of an
integrated water management plan (IWMP) on the catchment level became
possible for an optimal set of the lake ecosystem. However, the IWMP
contains an activity to enlighten the stakeholder’s perception towards
lake degradation. Stakeholders will become able to include Kolleru Lake
ecosystem resource users, will be guided about the crucial significance
of the lake functions, values, and resources from which they fulfill
their needs. Moreover, the state government agencies should incorporate
with the stakeholders to adopt sustainable development activities that
would need a priority response.