Surface and subsurface agricultural runoff has
been the main cause of water quality
problems in Lake Decatur, which is the major s
ource of public water supply for the City of
Decatur and the Village of Mt.
Zion, serving a total population of more than 80,000. The lake
has a watershed area of 925 square miles and
was created by building a dam on the Sangamon
River in 1922 with a modification in 1956 to incr
ease its capacity. Extensive siltation is another
critical issue, causing loss of
significant storage volume. Nearly 90 percent of the Lake Decatur
watershed is cropland, of which corn and soyb
ean account for 44 and 39 percent, respectively.
The watershed is extensively tile
-drained to lower the water tabl
e, creating favorable conditions
for agricultural production. Hydr
ologic and water quality monitoring has been conducted from
1993 to 2008 by the Illinois State Wate
r Survey (ISWS) with support fr
om the City of Decatur in
an effort to alleviate the wa
ter quality problem in Lake Decatur through watershed management
alternatives. Additional waters
hed monitoring was carried out from 2005 to 2008 by ISWS for a
United States Environmental Protection Agency
(USEPA) targeted watershed study with the
goal of addressing economic and environmental as
pects of nutrient management in the Upper
Sangamon River watershed.
The Illinois Environmental Protection Agency
(IEPA) added Lake Decatur to the Illinois
2004 Section 303(d) list as impaired for nitr
ogen-nitrate and total phosphorus (IEPA, 2004).
Consequently, a Total Maximum Daily Load (TMDL) assessment was completed for the
Sangamon River/Lake Decatur watershed in 20
07 and was approved by the USEPA. The TMDL
study provided an overview of implementation alte
rnatives that reduce
nitrate and phosphorous
loads, including nutrient manage
ment, conservation tillage, conser
vation buffers, and restriction
of livestock. In addition, practices that limit
losses from private sewage discharges and
sedimentation were also proposed to reduce
phosphorus loading (IEPA, 2007). Most cropland in
the Lake Decatur watershed has been extensively
tile-drained and therefore,
the effectiveness of
surface water-based best management practices
(BMPs) for reducing nitrate may be limited.
Specific placement areas for implementation of thes
e alternatives have not
been identified, which
is the focus of this study.
Two tributary watersheds of Lake Decatur we
re identified for developing alternative
implementation scenarios of selected BMPs
that are designed to reduce nonpoint source
pollutants (NPS) from agricultural sources. The
watersheds are Big/Long
Creek and Big Ditch
watersheds, as illustrated in Figure 1. The
Big/Long Creek watershed is located in the
downstream portion of the Lake Decatur watershed,
draining directly into
the lake. In contrast,
the Big Ditch watershed is located about 50 miles fr
om the lake in the nort
heastern edge of the
Lake Decatur watershed. Both are agricultu
rally dominated watersheds and their areas
considered in this study correspond to the drainage
areas of ISWS monito
ring stations, which are
close to the respective watershed outlets.
The objective of this research was to evaluate
the water quality benefits of selected BMPs
at a watershed scale, generati
ng alternative scenarios for implementation in Big Ditch and
Big/Long Creek watersheds. This was accomp
lished through the development of decision
support models (DSMs) for each watershed. The
DSMs were developed based on an integrated
modeling approach, coupling a watershed si
mulation model known as the Soil and Water
Assessment Tool (SWAT) with an Archived-B
ased Micro-Genetic Algorithm 2 (AMGA2) - a
multi-objective optimization algorithm. Such integrated modeling approach, which involves
interfacing a simulation model with
an optimization algorithm, ha
s been extensively applied to solve complex problems in watershed manageme
nt (Bekele et al., 2013; Bekele et al., 2011),
reservoir operations (Nicklow and Mays,
2000), groundwater monitoring design (Reed and
Minsker, 2004), and others. The DSM was design
ed to generate cost-effective implementation
scenarios of selected conventional and newly em
erging BMPs that include
nutrient management,
cover crops, perennial crops, constructed wetlan
ds, drainage water management, bioreactors,
saturated buffers, and filter strips. It is capable of providing optimal BMP placement scenarios
that result in maximum re
duction of NPS pollutants for
a prescribed level of BMP
implementation. BMP scenarios that strike a ba
lance between NPS reducti
on and total cost of
implementation are identified as best tradeoff so
lutions and are recommended for preparation of
watershed implementation plans.published or submitted for publicationis peer reviewedOpe
