Nutrient Concentrations in Coastal Streams, Variation with Land Use in the Carpinteria Valley (Santa Barbara Coastal LTER) Timothy H. Robinson John M.

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Presentation transcript:

Nutrient Concentrations in Coastal Streams, Variation with Land Use in the Carpinteria Valley (Santa Barbara Coastal LTER) Timothy H. Robinson John M. Melack Arturo A. Keller Bren School of Environmental Science and Management University of California Santa Barbara

Outline of the talk Project overview Sampling strategy and location Measuring stream nutrient concentrations and flow Nutrient loading and the development of a flux model Basin outlet mass flux Comparison of nutrient loading by land use type Nutrient export coefficient modeling Integration with an urban growth model

Project Overview

Methodology Identify land use classes and sampling site locations: Chaparral/Forest, Avocado, Greenhouse, Open-Field Nursery, Residential and Commercial Sampling strategies: Subcatchment, point discharge and above-below Sampling methods: Manual sample or ISCO auto-sampler GIS database development Data analysis Nutrient flux calculation (hydrology and stream chemistry) Nutrient export coefficient model development Integration with an urban growth model

Sampling Site Locations

Measuring Nutrient Concentrations Grab samples and ISCO auto- samplers

Analyzing for: Ammonium (NH 4 + ), Nitrate (NO 3 - ), Total Dissolve Nitrogen (TDN), Phosphate (PO 4 3- ), Total Particulate Carbon (TPC), Total Particulate Nitrogen (TPN), Total Particulate Phosphate (TPP), Total Suspended Sediments (TSS) and major ions at selected locations Frequency: Regular sampling: Once a week during the wet season Once every 2 weeks during the dry season Storm sampling: Every hour on the rising limb of the hydrograph Every 2-4 hours on the falling limb of the hydrograph Specifics:

Measuring Stream Flow Staff Gauges and Pressure Transducers Surveying the Cross-Sections Developing Rating Curves

Stream Chemistry and Hydrology Carpinteria Creek (WY-2002)

General Trends in Nutrient Concentrations by Watershed FranklinCarpinteriaSanta Monica nitrate (µM) baseflow stormflow FranklinCarpinteriaSanta Monica phosphate (µM) baseflow stormflow

Nutrient Loading Development of a Nutrient Flux Model Stream Chemistry Observed Stage PT Stage (5-min) Observed Flow PT Flow (5-min) Stream Chemistry Stage-Discharge Relationship (HEC-RAS) Flow (hourly) Flow (hourly) Stream Chemistry (hourly) Identify: Baseflow, Peakflow.. Nut. Conc. Flow (hourly) Stream Chemistry (model/obs) Nut. Flux (conc/flow) Annual Nutrient Loading Observed Flow (hourly) Linear extrapolation

Modeled vs. Observed Residential - CP30

Cumulative Nitrate Export Nursery Site

WY 2001 Basin Nutrient Export Franklin Creek Watershed

WY2001 Basin Outlet Mass Flux WY 2001

Comparison of Flux after Normalizing with Runoff

AGISE IInterviewILiteratureKLiterature  k tD/V LUGIS Abbreviation key: E – Export Coefficient Function B – Watershed Response Variable S – Soils P - Precipitation Nutrient Export Coefficient Model D atm LTER Literature S+P +ASMC ASMC – Antecedent Soil Moisture Content K – Down Stream Distance-Decay Function k +  – Coefficients t – Time D – Distance Traveled Downstream V – Average Velocity Traveled Downstream L

Integration with an Urban Growth Model (SLEUTH) SLEUTH : an urban growth model implemented for the Santa Barbara area that predicts future land use, example 2050 Enables comparison of future loadings to standards being set for stream water quality regulations (TMDLs) Evaluation of proposed BMP mitigations

Conclusions Stream nutrient concentrations only partially tell the story Hydrology is the critical element of any flux calculation, which is necessary to characterize nutrient loading The finer the sampling strategy the better the results, particularly with urban/agriculturally dominated sites Creating a dedicated and enthusiastic group of stream samplers is a crucial component of any project of this nature Nutrient export coefficients for a Mediterranean climate need to accommodate the high inter/intra-year storm variability A minimum of two years of data are needed to statistically validate model results Hope for rain!!

Questions Thank you