Land-Use and Water Quality Across the Cape Fear River Basin, NC: from 2001 to Jennifer Braswell Alford, PhD

Transcription

1 Land-Use and Water Quality Across the Cape Fear River Basin, NC: Exploring Spatial and Temporal Relationships from 2001 to 2006 Jennifer Braswell Alford, PhD

2 Introduction There are over 3.6 million miles of rivers and streams in the United States each exhibiting unique characteristics that are physically, biologically and chemically influenced by the diverse landscapes they traverse (EPA, 2010). Over the past several decades point source and non point Over the past several decades, point source and non-point source pollution (NPSP) inputs to rivers systems have increasingly impaired surface water quality in local and regional watersheds (Carpenter et al., 1998; Mallin et al., 2009; Brabec, 2009).

3 Study Area The Cape Fear River B i Basin

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5 Methods: Water Quality Analysis The Upper Cape Fear River Basin Assembly Water Quality Monitoring Stations Source: NC DENR Division of Water Quality (2011)

6 Methods: Water Quality Analysis The Middle Cape Fear River Basin Assembly Water Quality Monitoring Stations Source: NC DENR Division of Water Quality (2011)

7 Methods: Water Quality Analysis The Lower Cape Fear River Basin Assembly Water Quality Monitoring Stations Source: NC DENR Division of Water Quality (2011)

8 Methods and Data Sources Dependent Variables Annual Average Dissolved Oxygen Independent Variables Percent Land-Use/Land-Cover Type (km2) Annual Average and Annual Geometric Mean Fecal coliform Number of Permitted Livestock Head by Permit Annual laverage Ammonium Total Precipitation i i Nitrogen (NH3-N) Annual Average Nitrate-Nitrite Nitrite Nitrogen (NO2-NO3) Type of Physiographic Region Annual Average Phosphorus (P)

9 Caveats 30 meter resolution No flow data Imagery dates Nested watersheds Monitoring data

10 Hypotheses Increases in forested land-use types will support better water quality when compared to increases in urban or agricultural land-use types. Water quality will begin to exhibit a noticeable change as Water quality will begin to exhibit a noticeable change as development activities increase across the river basin and at the physiographic region scale.

11 Hypotheses Less-urbanized areas will exhibit poorer water quality when compared to highly urbanized areas. Monitoring stations draining landscape that contain CAFOs will exhibit poorer water quality when compared to those draining traditional agricultural practices.

12 Findings: River Basin Scale Water Quality Parameters Minimum Maximum Mean Standard Deviation Number of Stations with Annual Averages Exceeding State/EPA Standards Water Quality Parameters Minimum Maximum Mean Standard Deviation Number of Stations with Annual Averages Exceeding State/EPA Standards Fecal coliform (col/100ml) DO 18 3, Fecal coliform (col/100ml) DO 24 1, NO2-NO NO2-NO NH3-N P NH3-N P n = 72

13 Findings: Changes in Land-Use-Types 1.50% 1.00% 0.50% 0.00% Agriculture Developed Forested Wetlands CFRB UCFRB MCFRB LCFRB -0.50% -1.00% -1.50%

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16 Findings: Upper CFRB Water Quality Parameters Fecal coliform (col/100ml) Minimum Maximum Mean Standard Deviation Number of Stations with Annual Averages Exceeding State/EPA Standards 85 3, Water Quality Parameters Fecal coliform (col/100ml) Minimum Maximum Mean Standard Deviation Number of Stations with Annual Averages Exceeding State/EPA Standards 42 1, DO NO2-NO DO NO2-NO NH3-N N P NH3-N N P n = 31

17 Findings: UCFRB Water Quality FC_200l col/100ml 1500 FC_2006 col/100ml UCFRB_01 UCFRB_02 UCFRB_03 UCFRB_05 UCFRB_06 UCFRB_07 UCFRB_08 UCFRB_09 UCFRB_11 UCFRB_12 UCFRB_13 UCFRB_14 UCFRB_15 UCFRB_18 UCFRB_19 UCFRB_20 UCFRB_21 UCFRB_22 UCFRB_23 UCFRB_24 UCFRB_25 UCFRB_26 UCFRB_27 UCFRB_29 UCFRB_33 UCFRB_35 UCFRB_37 UCFRB_38 UCFRB_39 UCFRB_42 UCFRB_44 Figure 16. Changes in Fecal coliform from 2001 to 2006 for stations located in the Upper CFRB

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19 UCFRB: Fecal coliform

20 Findings: Middle CFRB Water Quality Parameters Fecal coliform (col/100ml) Minimum Maximum Mean Standard Deviation Number of Stations with Annual Averages Exceeding State/EPA Standards 18 2, Water Quality Parameters Minimum Maximum Mean Standard Deviation Number of Stations with Annual Averages Exceeding State/EPA Standards Fecal coliform (col/100ml) DO DO NO2-NO NO2-NO NH3-N NH3-N P P n = 21

21 MCFRB: Fecal coliform FC_200l col/100ml FC_2006 col/100ml Figure 24. Changes in Fecal coliform from 2001 to 2006 for stations located in the Middle CFRB

22 Results: MCFRB Fecal coliform

23 Findings: Lower CFRB Wt Water Minimumi Maximum Mean Standard d Number of Wt Water Minimumi Maximum Mean Standard d Number of fstations ti Quality Deviation Quality Deviation Parameters Parameters Fecal coliform (col/100ml) Stations with Annual Averages Exceeding State/EPA Standards Fecal coliform (col/100ml) with Annual Averages Exceeding State/EPA Standards 41 1, DO DO NO2-NO NO2-NO NH3-N NH3-N P P n = 20

24 LCFRB: Fecal coliform FC_200l col/100ml FC_2006 col/100ml Figure 31. Changes Fecal coliform from 2001 to 2006 for stations located in the Lower CFRB

25 LCFRB: Fecal coliform

26 Fecal coliform 2001 Model Independent Model p-value Unstandardized Exponent Percent Variables r 2 b Coefficient Value Change 4 Constant UCFRB Region % % Exurban Development % % Mixed Forest % Total Precipitation % The final regression model for Fecal coliform in 2001 can be formally expressed as follows: Log FC (2001) = UCFRB DOS MF 0.07 PT Where, FC = Fecal coliform col per 100ml UCFRB = Upper Cape Fear River Basin DOS = Percent Exurban Development MF = Percent Mixed Forest PT = Precipitation, Total

27 Fecal coliform 2006 Model Independent Model p-value Unstandardized Exponent Percent Variables r 2 b Coefficient Value Change 6 Constant % Mixed Forest % % Exurban Development % % Scrub/Shrub Land % UCFRB Region % The final regression model for Fecal coliform in 2006 can be formally expressed as follows: Log FC (2006) = MF DOS SS UCFRB Where, FC = Fecal coliform col per 100ml MF = Percent Mixed Forest DOS = Percent Exurban Development SS= Percent Shrub/Scrub Land UCFRB = Upper Cape Fear River Basin Region

28 Dissolved Oxygen 2001 Model Independent Model p-value Unstandardized Exponent Percent Variables r 2 b Coefficient i Vl Value Change 2 Constant MCFRB Region % % Emergent % Herbaceous Wetlands The final regression model for Dissolved Oxygen in 2001 can be formally expressed as follows: Where, Log DO (2001) = MCFRB 0.07 EHW MCFRB = Middle Cape Fear River Basin EHW = Percent Emergent Herbaceous Wetlands

29 Dissolved Oxygen 2006 Model Independent Model p-value Unstandardized b Exponent Percent Variables r 2 Coefficient Value Change 3 Constant LCFRB Region % Number of Permitted Livestock % (Headcount) % Emergent Herbaceous % Wetlands The final regression model for dissolved oxygen in 2006 can be formally expressed as follows: Log DO (2006) = LCFRB 0.12 HC 0.07 EHW Where, LCFRB = Lower Cape Fear River Basin HC = Number of Permitted Livestock (Headcount) EHW = Percent Emergent Herbaceous Wetlands

30 Nutrients The regression models for Nitrate-Nitrite Nitrogen, Ammonium Nitrogen and Phosphorus all generated R-squares less than 17%.

31 Conclusions Although there were only small changes in land-use types from 2001 to 2006, specific land-use types were still statistically linked to water quality impairment at the river basin scale. Stations that exceeded the state standard for fecal in 2001 Stations that exceeded the state standard for fecal in 2001 were largely concentrated in the UCFRB, while in 2006, they were more spatially distributed throughout the river basin.

32 Conclusions Percent mixed forest was the most significant land-use type that was predicted to increase fecal concentrations in both 2001 and Transitional land-use types including exurban development and mixed forest appear to play a critical role in shaping the geography g of water quality across the CFRB.

33 Conclusions Research could be conducted that spatially illustrates how climatic conditions and the proximity of specific land-use types impact water quality as well as the effectiveness of vegetated buffer zones bordering surface water systems. More data is needed to address the extent to which specific activities (e.g. spraying fecal on fields, development, and fertilizer applications) are impacting surface water resources throughout the river basin. Flow data is essential in understanding the extent to which climatic conditions, human activities, and specific land-use types impact water quality throughout h t the basin.

34 Conclusions If decision makers at the local and regional scales are aware of basin wide trends in both land-use changes and water quality, they could then develop more comprehensive policies that benefit the river basin as a whole. Taking into consideration how economic, social, and cultural activities influence water quality will lead to a more well-rounded approach to protecting water resources that can be sustained for future generations to come.

35 Acknowledgements Dr. Keith Debbage Dr, Zhi-Jun Liu Dr. Roy Si Stine Dr. Michael Mallin NC DENR Staff and countless others..thank You!

36 Thank You Jennifer Braswell Alford, PhD