| Title: | Estimating sediment and nutrient delivery ratios in the Big Sunflower Watershed using a multiple linear regression model |
| Authors: | Kannan, N., E. Osei, Y. Cao and A. Saleh |
| Year: | 2017 |
| Journal: | Journal of Soil and Water Conservation |
| Volume (Issue): | 72(5) |
| Pages: | 438-451 |
| Article ID: | |
| DOI: | 10.2489/jswc.72.5.438 |
| URL (non-DOI journals): | |
| Model: | APEX & SWAT |
| Broad Application Category: | hydrologic and pollutant |
| Primary Application Category: | model and/or data interface |
| Secondary Application Category: | hydrologic, pollutant and/or crop indices (or metrics) |
| Watershed Description: | 7,814 km^2 Big Sunflower River, a tributary of the Yazoo River located in northwestern Mississippi, U.S. |
| Calibration Summary: | |
| Validation Summary: | |
| General Comments: | |
| Abstract: | This study is part of an effort to analyze the nutrient load reductions obtained
from current and future best management practices implementations in the Big Sunflower
Watershed to meet the 45% nutrient reduction goal set for the watershed based on the US
Environmental Protection Agency Science Advisory Board’s (USEPA 2007) Gulf of Mexico
hypoxia report. This paper describes the identification of dominant pollutant delivery mechanisms
in the watershed, estimation of instream pollutant delivery ratios (DR) from subbasins
to watershed outlet, and development of a tool to estimate changes in instream pollutant
DR for what-if scenarios. The Big Sunflower Watershed is a 7,800 km2 intensively cultivated
agricultural watershed in the State of Mississippi. The Comprehensive Environmental and
Economic Optimization Tool (CEEOT) modeling system, consisting of the Soil and Water
Assessment Tool (SWAT) and Agricultural Policy and Environmental Extender (APEX) models,
was used to develop a multiple regression equation to estimate the sediment and nutrient
DRs for this watershed. The models used 32 years of weather data from 1981 to 2012. The
explanatory variables considered for the DR are distance to watershed outlet, flow, and pollutant
loads leaving subbasins. They were chosen based on their strength of correlations and
type of relationship with DR. Our results indicate that flow from each subbasin is the dominant
factor affecting DR for this watershed. Together, the explanatory variables considered
under the multiple linear regression framework were able to estimate sediment and nutrient
DRs with satisfactory regression parameters. The R2 values for the regression relationship
between the pollutant DRs and their counterparts estimated with multiple linear regression
method were 0.8 for sediment, 0.96 for total nitrogen (N), and 0.9 for total phosphorus (P).
The corresponding standard errors were 0.01 for sediment, 0.03 for total N, and 0.07 for total
P. The explanatory variables were more strongly correlated to sediment DR than to nutrient
DR. The tool developed to analyze changes in DRs for alternative scenarios appears to be
useful for watershed managers. |
| Language: | English |
| Keywords: | Big Sunflower; Comprehensive Environmental and Economic Optimization Tool (CEEOT); delivery ratio; nitrogen—phosphorus—sediment |