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The impacts of different meteorology data sets on nitrogen fate and transport in the SWAT
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watershed model
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Supporting Information Section
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Authors: Mark Gabriel1*, Christopher Knightes1, Ellen Cooter2, Robin Dennis2
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(1) USEPA/Office of Research and Development(ORD)/National Exposure Research Laboratory
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(NERL)/Ecosystem Research Division (ERD), 960 College Station Rd., Athens, GA, 30605,
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USA
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(2) USEPA/ORD/NERL/Atmospheric Modeling and Analysis Division (AMAD), 109 T W
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Alexander Drive, Research Triangle Park, NC, 27711, USA
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*Corresponding Author- email: gabriel.mark@epa.gov, phone: 706-355-8349, fax: 706-355-
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8326
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1.0
SWAT Nitrogen Cycle Simulation
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SWAT simulates nitrogen cycles in the soil profile and groundwater [1]. Within both
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media, nitrogen is highly reactive and exists in many forms. Nitrogen may be added to soil
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through fertilizer and manure application, atmospheric deposition (dry and wet) and biological
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fixation [2]. Nitrogen may be removed from soil through plant uptake, soil erosion, leaching,
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volatilization, denitrification and through runoff [2]. In SWAT, there are five different pools of
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nitrogen in the soil: two pools are inorganic forms (ammonium [NH4+] and nitrate [NO-3]), while
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the other three are organic (fresh, active, and stable). Fresh organic nitrogen is associated with
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crop residue and microbial biomass, and the active and stable organic nitrogen pools are
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associated with the soil humus. The fresh component is much more bioavailable than humus.
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Organic nitrogen associated with humus is partitioned into two pools (active, stable) to account
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for variations in availability of humic substances to mineralization. Humus is a complex mixture
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of organic substances that have been significantly modified from their original form over time,
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and contains other substances that have been synthesized by soil organisms [2]. Typically,
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humus represents the majority of total soil organic matter and plays a major role in the ability of
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a soil to retain nutrients and water. Inorganic nitrogen may be transported with runoff, lateral
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flow or soil percolation. Inorganic nitrogen entering shallow groundwater in recharge from soil
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percolation may remain in groundwater, move into the main channel, or move into the soil zone
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in response to water deficiencies [2]. Inorganic nitrogen may also move from the shallow soils to
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deep groundwater. For low-lying areas, groundwater flow is the primary transport pathway and
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plays an important role in the delivery of inorganic nitrogen to the main channel or to the soil
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zone.
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2.0
SWAT Model Input Data
2.1
Data Input and Processing
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The Soil Survey Geographic Database (SSURGO) (National Resources Conservation
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Service [NRCS]; http://soils.usda.gov/survey/geography/ssurgo/) was the source of soil input for
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the studied watersheds. SSURGO soil data was available for all necessary counties (Wayne,
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Johnson, Greene, Durham, Orange, and Person) within and surrounding both watersheds. These
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data represent surveys and compilations between 1990 and 2009. A digital elevation model
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(DEM) (http://www.mapmart.com/Products/DigitalElevationModel/USGSNED.aspx) at 30 m
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resolution was used to represent surface elevation within each watershed. For the Nahunta
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watershed, the 2009 Crop Data Layer (CDL: http://datagateway.nrcs.usda.gov) and 2001
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National Land Cover Data Layer (NLCD: http://www.epa.gov/mrlc/nlcd-2001.html) were used
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for land cover characterizations. For the Little River watershed, the 2009 CDL and 2006 NLCD
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(http://www.mrlc.gov/nlcd06_data.php) were used. The 2006 NLCD was used because we
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suspect the Little River watershed experienced clear-cutting for an area approximately 0.6 km2
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near the watershed outlet that was not captured in the 2001 NLCD. Using the EPA’s landscape
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characterization program (http://www.maps6.epa.gov) the phenological record shows a sharp
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drop in normalized difference vegetation index (NDVI) after 2006 near the watershed outlet and
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a gradual increase in NDVI which likely indicates clear cutting (R. Lunetta pers. comm.).
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Therefore, to help account for this disturbance the 2006 NLCD was used instead of the 2001.
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The hydrologic response units (HRU) in each watershed were defined on the basis of soil, land
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use, and topographic characteristics. The following HRU threshold limit delineation scheme was
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applied: 5% land use, 10% soil, 5% slope. Under this scheme, HRUs were not developed from
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land uses, soil types or surface slopes that were less than these percentages compared to the total
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areas of each. This scheme was developed to negate the consideration of numerous small HRUs
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that, if considered, would have negligible impacts on flow and nitrogen transport.
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2.2
Observed Flow and Nitrate Data
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Stream flow (m3 s-1) and nitrate (NO-3-N, mg/L) data were retrieved for both watersheds
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from 1990 to 2009.
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Geological Survey (USGS) gauging station 208521324: Little River at SR1461 near Orange
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Factory, NC. Flow for the Nahunta watershed was retrieved at the USGS gauging station
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2091000: Nahunta Swamp near Shine, NC. The USGS, National Weather Information Service
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(NWIS) (http://waterdata.usgs.gov/nwis) was the source of all surface flow data. Observed flow
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data was calculated on an average monthly basis from daily data. Observed nitrate data was
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retrieved from USEPA STORET (Storage and Retrieval) (http://www.epa.gov/STORET/). The
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frequency of collection for the nitrate concentrations was approximately monthly to bimonthly.
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Missing values for nitrate concentration data were determined using the USGS Estimator
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protocol [3]. For information on field data retrieval and analytical quality assurance/control
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(QAQC) measures for the NWIS flow and USEPA STORET data, refer to the respective web
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links.
Watershed flow for the Little River watershed was retrieved at US
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2.3
Atmospheric Deposition of Nitrogen for Calibration
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Observed dry (kg/ha-yr) and wet (mg/L) atmospheric deposition data (ammonium [NH4+]
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and nitrate [NO3-]) were obtained from the USEPA Clean Air Status and Trends Network
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(CASTNET; http://java.epa.gov/castnet/) and the National Atmospheric Deposition Program
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(NADP; http://nadp.sws.uiuc.edu/). Yearly dry deposition data was obtained from CASTNET
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and weekly wet deposition data from NADP. The stations used were: NC41, NC03 (NADP) and
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CDN125 (CASTNET). SWAT only allows one constant value for dry and wet deposition;
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therefore, average values were used for the nine year period. CASTNET dry deposition does not
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include NH3 (ammonia), PAN (peroxyacetyl nitrate), NO2 (nitrogen dioxide) and NO (nitrogen
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monoxide).
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2.4
Agricultural Land Practice and Soil Geochemical Information
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Several sources of information were used to represent actual agricultural practices and
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soil nitrogen levels for the studied watersheds (see Table S1). For agriculture, the modifications
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involved crop rotations and nitrogen applications; in both watersheds, corn-soybean rotations
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were applied for both corn and soybean crop layers. Both watersheds contained varying numbers
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of concentrated feeding operations (CAFOs), poultry and swine operations which were
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represented through published values for fertilizer and manure applications on crop land [4].
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Specifically, two different fertilizer/manure application schemes were applied -- one for urban
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land uses and one for cropland/agricultural lands. Fertilizer and manure application rates varied
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per year for each watershed. Fertilizer application for urban land uses was evenly delivered as
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urea (CO (NH2)2), and ranged from 0.07 to 1.37 kg/ha-yr. Agricultural land received nitrogen
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application through fresh swine manure application and ranged from 8.2 to 8.93 kg/ha-yr.
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Fertilizer application to agricultural land uses was as elemental nitrogen, ranging form 5.50 to
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38.0 kg/ha-yr. Overall, more nitrogen was applied to the Nahunta agricultural land uses. In all
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cases, fertilizer application decreased from the first year (1998) to the last year (2009) as
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estimated from [4]. Crop turn-over for all agricultural layers was managed through heat units.
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Soil geochemistry data was obtained from published values for organic and inorganic nitrogen
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concentrations for the top three soil layers (Table S1).
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3.0
Parameter Sensitivity Analysis
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Following data collection and SWAT initialization, we performed parameter sensitivity
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analysis. The most sensitive model input parameters for flow and nutrient loading were identified
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with an automated sensitivity analysis procedure in SWAT. This sensitivity analysis was
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performed for flow and nutrient loading for the sub-watersheds that contained the outlet for the
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entire watershed. Latin Hypercube (LH) sampling and the one-factor-at-a-time (OAT) method
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was applied [5] to determine parameter sensitivity for flow and nutrient loading. Ten LH
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intervals and an OAT parameter change value of 0.05 were applied. Under LH, samples were
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chosen across the full range of values (SWAT default) for each parameter assuming a uniform
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distribution. Following simulation, the overall effect of each parameter is ranked highest to
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lowest. The top 10th percentile of all parameters for each category (flow, nutrients) was used for
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the next step, calibration and validation.
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Table S2 shows calibrated parameter values for both watersheds. The top 10th percentile
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of the most sensitive input parameters (identified in the parameter sensitivity analysis) was used
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for calibration. In all, the input parameters found to be most sensitive, as indicated by those with
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p<0.001 in Table S2, closely agrees with past studies, in particular, Rouhani et al. [6], Sexton et
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al. [7], Lam et al. [8],Wang et al. [9] Masih et al. [10]. Several other input parameters were used
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to fine tune the calibration: Gw_Delay.gw, Gw_Revap.gw, Surlag.bsn, AI1.wwq, Sol_No3.chm,
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Sol_Orgn.chm, Shallst_N.gw, Biomix.mgt, Sdnco.bsn, Cdn.bsn and Rsdco.bsn (see Table S2 for
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a description of each parameter).
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Table S1: Source information for land cover and soil data input categories
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Category
Fertilizer and manure applications
Soil geochemical properties
Surface and groundwater chemistry
Agricultural management practices (e.g.
soil tillage, contouring, filter strip and tile
drain practices)
Locations and characteristics for confined
feeding operations (CAFOs), swine and
poultry operations
Surface flow and precipitation
Atmospheric nitrogen deposition
Information Source(s)
-NCDAC [11]
-NASS [12]
-NCSU [13]
-Ruddy et al. [4]
-NRCS [14]
-Ibendahl and Fleming [15]
-Chistensen and MacAller [16]
-Roelle and Aneja [17]
-NCDENR [18]
-NCSU [13]
-USGS NWIS [19]
-USEPA STORET [20]
-NC Cooperative Extension [21]
-NC Department of Agriculture [22]
-Folle et al. [23]
-Spruill et al. [24]
-NC One map [25]
-USGS NWIS [19]
-USEPA CASTNET [26]
-NADP [27]
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Table S2: Input parameter values for flow and nitrate loading: Under Parameter Name, italicized input parameters were only used for
nitrate load calibration. Non-italicized input parameters were only used for flow calibration.
Parameter Description
SCS runoff curve number for moisture condition II
Baseflow alpha factor
Manning's “ n” value for main channel
Surface runoff lag coefficient
Soil evaporation compensation factor
Threshold depth of water in the shallow aquifer
required for return flow to occur
Maximum canopy storage
Available water capacity of soil layer
Groundwater “revap” coefficient
Threshold depth of water the shallow aquifer for
“revap” or percolation to the deep aquifer to occur
Groundwater delay time
Deep aquifer percolation fraction
Fraction of algal biomass that is nitrogen
Nitrate percolation coefficient
Phosphorous percolation coefficient
Initial nitrate concentrations in soil layers one, two
an three
Initial organic nitrogen concentrations in soil layer
one, two and three
Nitrate concentration in shallow aquifer
Biological mixing efficiency
Average slope length
Residue decomposition coefficient
Denitrification threshold water content
Denitrification exponential rate coefficient
Phosphorus soil partitioning coefficient
Parameter
Name
CN2.mgt*
ALPHA_BF.gw
CH_N2.rte
SURLAG.bsn
ESCO.hru
GWQMN.gw
CANMX.hru
SOL_AWC1.sol*
GW_REVAP.gw
REVAPMN.gw
GW_DELAY.gw
RCHRG_DP.gw
AI1.wwq
NPERCO.bsn
PPERCO.bsn
SOL_NO3.chm
SOL_ORGN.chm
SHALLST_N.gw
BIOMIX.mgt
SLSUBBSN.hru*
RSDCO.bsn
SDNCO.bsn
CDN.bsn
PHOSKD.bsn
Mode of
Change
During
Calibration#
r
v
v
v
v
v
v
r
v
v
v
v
v
v
v
v
v
v
v
r
v
v
v
v
Little River
Parameter Sensitivity
Indicated by the SUFI-2 pvalue
Nahunta
Uncalibrated
value
55.0-84.0
0.048
0.014
4.0
0.95
Final
calibrated
value
63.8-98.6
0.19
0.19
4.51
0.89
Uncalibrated
value
31-92
0.048
0.014
4.0
0.95
Final
calibrated
value
31.1-92.9
0.95
0.094
8.75
0.96
0
69.1
0
0
0.11-0.2
0.02
92.6
0.134-0.244
0.10
1
31
0.05
0.08
0.2
10
6.25†. 3.0†,
1.5†
25.0†, 12.5†,
6.25†
1.5†
0.20
60.9-121.9
0.05
1
1.4
175
Little River
Nahunta
0.6162
0.9072
0.9486
0.7552
0.0363
<0.0001
0.7378
0.3498
0.8346
<0.0001
254.2
<0.0001
<0.0001
0
0.07-0.7
0.02
45.2
Not changed
Not changed
0.5392
0.1994
0.8954
<0.0001
-
403.3
1
Not changed
0.0011
-
60.7
0.072
0.072
0.50
16.0
31
0.05
0.08
0.2
10
13.46†, 6.73†,
3.3†
50.0†, 25.0†,
12.5†
7.75†
0.20
60.8-121.8
0.05
1
1.4
175
Not changed
0.028
0.087
0.10
13.43
0.264, 6.73,
3.3
19.19, 25.0,
12.5
419.9
0.655
59.7-119.5
Not changed
0.99
0.01
Not changed
<0.0001
<0.0001
0.5749
0.6572
0.0433
<0.0001
0.4346
<0.0001
0.9713
0.3979
0.0003
0.9965
0.0540
0.6735
0.1491
0.7458
No data‡
No data‡
0.9675
0.3652
0.5470
0.4190
No data‡
No data‡
-
0.01, 0.01,0.01
10.43, 12.5,
6.25
178.3
0.03
Not changed
0.03
0.80
0.10
152.1
*varies by watershed/HRU; values shown are the minimum and maximum value
†values determined from literature review
‡ No sensitivity data is available as manual calibration was used, # “r” refers to application by multiplication and “v” refers to application by replacement
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References:
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