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SAV Nutrient Cycling – Nicole Cai, VIMS

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Impacts of Submerged Aquatic Vegetation on Water Quality In Cache Slough Complex, Sacramento-San Joaquin Delta: A Numerical Study Nicole Cai, Joseph Zhang, Jian Shen Jun 07, 2021 1 A story of a fish Egeria densa (invasive) ➢ Displaced most of the native SAV species within Delta ➢ Form canopies in slow-flowing or still water ➢ Stems can grow from 1.8 m to 3 m, or even to the water surface ➢ Delta Smelt Resiliency Strategy calls for enhanced control and study of the effects of removal by herbicide. Delta Smelt (endangered) ➢ Endemic and indicator species for the health of the Delta ecosystem ➢ It is functionally extinct in the wild, which coincides with substantial changes in Delta ecosystem 2 Impacts of SAV 3) 1) Impact through Direct Impact Feedback Effects on 2) Hydrodynamics Impact through • Nutrient uptake/release Interactions with • Oxygen production/consumption Phytoplankton • Decreased local velocity • Prolonged residence time • Altered material transport • Nutrient competition • Light shading 3 SCHISM-ICM-SAV SAV Model (Biomass dynamics) SCHISM ICM Hydrodynamics Model Water Quality Model (Tide, Temperature, Salinity, Wind) (Algae, C, N, P, DO) Sediment Flux Model (Diagenesis of POM, recycling of nutrients) 4 Background Model developments Model implementations Results Discussions Summary Vegetation impacts on hydrodynamics in SCHISM 휕푤 Continuity equation: 훻 ∙ 퐮 + = 0 휕푧 where 퐟 is forcing terms in momentum treated explicitly in 휕퐶 휕 휕퐶 the numerical formulation – Coriolis force, baroclinic Transport equation: + 훻 ∙ 퐮퐶 = 휅 + 퐹ℎ 휕푡 휕푧 휕푡 gradient, atmospheric pressure, earth tidal potential, 퐷퐮 휕 휕퐮 Momentum equation: = 휈 − 푔 ∙ 훻휂 푥, 푦, 푡 + 퐟 + 퐅 horizontal viscosity and other forces. 퐷푡 휕푧 휕푧 퐯퐞퐠 퐅퐯퐞퐠 = 0.5 ∙ 퐷푣 ∙ 푁푣 ∙ 퐶퐷푣 ∙ 퐮 퐮 ∙ 퐿(푥, 푦, 푧) SAV-induced drag force Turbulence closure equations: SAV-induced additional source term 퐷퐾 휕 휕퐾 turbulent kinetic energy 퐾: = 휈휓 + 휈푀2 + 휇푁2 − 휀 + 푐 ∙ 0.5 ∙ 퐷 ∙ 푁 ∙ 퐶 ∙ 퐮 3ℋ 푧 − 푧 퐷푡 휕푧 푘 휕푧 푓푘 푣 푣 퐷푣 푣 퐷휓 휕 휕휓 휓 휓 generic length-scale variable 휓: = 휈 + (푐 휈푀2 + 푐 휇푁2 − 푐 퐹 휀) + (푐 ∙ 0.5 ∙ 퐷 ∙ 푁 ∙ 퐶 ∙ 퐮 3ℋ 푧 − 푧 ) 퐷푡 휕푧 휓 휕푧 퐾 휓1 휓2 휓3 푤 퐾 푓휓 푣 푣 퐷푣 푣 2 where Dv is the stem diameter (m), Nv is vegetation density (number of stems per m ), CDv is a bulk drag coefficient with a typical value of 1.13 (Garcia et al. 2004; Nepf and Vivoni, 2000) and 퐿 is a step function. SAV impact on hydrodynamic is incorporated implicitly into the SCHISM hydrodynamics part by Zhang et al. (2019), in order to avoid the stringent stability constraints associated with this term. 5 Background Model developments Model implementations Results Discussions Summary Fully-coupled ICM-VEG model 6 Background Model developments Model implementations Results Discussions Summary SAV component • Three components of SAV biomass: leaf, stem and root. • Leaf is the photosynthetic portion of the above-ground plant biomass. o Growth of leaf is a function of temperature, light and nutrient limitation. • Stem is the structural, non- photosynthetic portions of the above-ground plant biomass. • Root is the below-ground portions of the plant biomass associated with anchoring the plant and with nutrient uptake 7 Background Model developments Model implementations Results Discussions Summary Formulations of the SAV biomass 푑퐿퐹 = 푃푙푓 ∙ 1 − 퐹푎푚 ∙ 퐹푃푙푓 ∙ 퐿퐹 − 퐵푀푙푓 ∙ 퐿퐹 푑푡 푑 푆푇 = 푃푙푓 ∙ 1 − 퐹푎푚 ∙ 퐹푃푠푡 ∙ 퐿퐹 − 퐵푀푠푡 ∙ 푆푇 State variables: 푑푡 푳푭, 푺푻, 푹푻 are biomasses of leaves, stems, 푑 푅푇 −3 = 푃푙푓 ∙ 1 − 퐹푎푚 ∙ 퐹푃푟푡 ∙ 퐿퐹 − 퐵푀푟푡 ∙ 푅푇 and roots (g C m ); 푑푡 퐻푐푎푛 = min(푤푑푒푝, 푟푙푓 ∙ 퐿퐹 + 푟푠푡 ∙ 푆푇 + 푟푟푡 ∙ 푅푇 + ℎ푐푎푛푠푎푣0) Parameters: • 푃푙푓 푎푛푑 푃푒푝 are leaf production rate (d−1). • 퐹푎푚, 퐹푃푙푓, 퐹푃푠푡, 퐹푃푟푡 are fractions of production devoted to active metabolism, routed to leaf, stem, and root biomass. • 퐵푀푙푓, 퐵푀푠푡, 퐵푀푟푡 are basal metabolism (d−1). • 푟푙푓, 푟푠푡, 푟푟푡, ℎ푐푎푛푠푎푣0 are coefficients to transfer SAV biomass to canopy height. 푤푑푒푝 is water depth. 8 Background Model developments Model implementations Results Discussions Summary Interactions of SAV and light −2 −1 • 퐼푤푐 is the irradiance at certain layer (E m d ); 퐼0 is surface irradiance; 퐼푛 is irradiance at the bottom of vertical layer n. • 퐾푒 is total diffuse light attenuation (m−1); 퐾푤 is diffuse light attenuation in layers without SAV (m−1); 퐾푠ℎ is light attenuation by SAV absorption (m2 g−1 C). 퐼0 퐾푒 = 퐾푤 = 퐾푏 + 퐾푇푆푆 ∙ 푇푆푆 + 푲푪풉풍 ∙ 푪풉풍 퐼푛−1 −퐾푒∙푑푒푝푛 퐼푤푐 = 퐼푛−1 ∙ 푒 2푑푒푝푛 퐾푒 = 퐾푤 + 푲풔풉 ∙ (푳푭 + 푺푻) 퐼푛 퐼푛푣 9 Study area Bathymetry (m) Cache Slough Complex • Cut out from the Bay-Delta grid. • Complex geometry with large shallow habitat and deep channels • Influence by both tide and flow discharges 10 Background Model developments Model implementations Results Discussions Summary Study area • Little Hastings Tract and French Island, two of the selected locations for this study, are hydrologically connected to Liberty Island and have been consistently infested with SAV in recent years (Shruti Khanna, CDFW). • For model initiation and validation, we mostly use the observed SAV distributions. • French Island (no herbicide treatment) and Little Hastings Tract (treated) are chosen for comparison. But French Island is not included in the current model domain. DWR report, 2017 11 Background Model developments Model implementations Results Discussions Summary Model experiments Impacts of SAV on hydrodynamics and SAV removal water quality Local biological impacts of SAV With SAV but no impacts on hydrodynamics Significance of feedback effects of SAV to hydrodynamics. Base Case: Dynamic feedback 12 Background Model developments Model implementations Results Discussions Summary Model calibrations • The elevation is mainly controlled by the boundary condition and fits the observation in Cache Slough. • Salinity is low in this area and the model simulation matches the observed temporal variations. The modelled temperature agrees with the observations. • Overall, the model catches the magnitude of the chlorophyll-a concentration. • It matches both the pattern and magnitude of the dissolved oxygen. • The nutrient concentrations agree well with the observations well in terms of temporal variations and values. 13 Background Model developments Model implementations Results Discussions Summary SAV biomass and distributions • Start from uniform biomass 100 g/m2. Channel • Declines by half in 60 days in channels. • Almost completely disappears in 180 days. Shoal • Growth in shallow regions • Clear summer-fall bloom pattern 14 Impacts of SAV on flow fields • Flow is more channelized • Flow velocity is larger in areas without SAV • Flow velocity is largely reduced over SAV beds • The difference of velocity magnitude can be 0.2 m s-1 15 Background Model developments Model implementations Results Discussions Summary Impacts of SAV on water quality • Chl-a increases in local SAV beds while decreases in the rest area • SAV increases DO locally from production of both SAV and increased phytoplankton + • NH4 decreases due to local uptake in the SAV beds, while increases outside the SAV beds 16 Background Model developments Model implementations Results Discussions Summary Phytoplankton Biomass VS. SAV Canopy Height Shoal Area: Shoal Area: • SAV stays emergent. With the presence of SAV, fluctuation of •phytoplanktonShading is significant concentrationto block is greatly reduced. light supply. Median Depth Area: Median Depth Area: • SAV stays submerged with 0.5m In the presence of SAV, the phytoplankton hasin height.double blooms in early spring and late fall, while its concentration• isSAV lowerdoes in notsummer.limit the light supply above the canopy. Deep Channel Area: Deep Channel Area: There is a small decrease in the phytoplankton• No concentrationSAV survived inwithdeepsamechannels. fluctuation. 17 Nutrient Concentration and Bottom Flux Ammonia Concentration Ammonia Bottom Flux Shoal Area: • With SAV nutrient has smaller fluctuations but is not limited for the growth of phytoplankton or SAV. • SAV plays a significant role in decreasing the recycling inorganic nutrients. Median Depth Area: • With SAV the nutrient is lower in winter but still unlimited for the phytoplankton bloom, while in summer, the nutrient is used up. • Nutrient supply limits the growth of both SAV and phytoplankton since late spring to late fall. Deep Channel Area: • There is slight decrease of nutrients. 18 Phytoplankton Local Growth Rates Green Algae Local Growth Rate Shoal Area: • With SAV, local growth rate decreases to almost zero. • Light limitation is the main reason while nutrient is not limited. Median Depth Area: • With SAV, local growth rate is reduced from late spring. • Nutrient limitation is dominant. Deep Channel Area: • Similar local growth rates with or without SAV 19 Horizontal Phytoplankton Transport Horizontal Velocity Magnitude Surface Elevation Shoal and Median Depth Areas: • Horizontal velocity decreases significantly with SAV. • Elevation remains almost unchanged. • Horizontal biomass transport is largely reduced in these areas. Deep Channel Area: • Horizontal velocity increases. • Flushing increases in this areas. 20 Pattern of SAV-phytoplankton interactions Less Flushing 2m • Phytoplankton accumulates with low flushing. 4m • Phytoplankton double blooms in early spring with • Light limits local low flushing and late fall with nutrient available. phytoplankton • SAV blocks bottom nutrient bottom flux, and limits growth. local phytoplankton growth since late spring. Deep Channel Median Depth Area Shoal 21 Local biological impacts of SAV on water quality Phytoplankton: • SAV decrease phytoplankton biomass. • Less than 18.5%
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