Ammonia Toxicity Model AMMTOX Training Session Held 5 Dec 2005 Hosted by EPA Region VIII Presented by Jim Saunders, Colorado WQCD.

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Ammonia Toxicity Model AMMTOX Training Session Held 5 Dec 2005 Hosted by EPA Region VIII Presented by Jim Saunders, Colorado WQCD

Purpose of Training Session Explain rationale for model Identify data needs and sources, including options for use of site-specific data Demonstrate operation of model Work with test data sets

Assumptions and Disclaimers Familiarity with Excel is assumed VB programming is NOT covered Future tech support is not my job Merits of National Criteria are not open for discussion Ideas and suggestions presented in this session may not conform to policies of state or federal permitting agencies

Section 1: Concepts and Construction Central Question: Where is there greatest risk of exceeding stream standard? Depends on pollutant behavior and control of toxicity

Location of Controlling Conditions Control of Toxicity Control of Concentration Concentration+ pH & Temp ConservativeOutfallDownstream, simple Non-conservativeOutfallDownstream, complex

How do you handle a problem like Ammonia? Calculating permit limits becomes difficult when controlling conditions are displaced downstream Good news: solution likely to benefit discharger

Pattern of Toxicity, Simple Scenario Initial –pH: 6.6 –Temp: 16.3 Final –pH: 8.0 –Temp: 10 Rebound –pH: 0.2/mi –Temp: 0.7/mi

Pattern of Toxicity, Complex Scenario Simple Scenario pH, temperature Initial ammonia = 5.5 Loss = 3/d V= 2 fps

Required Tasks Define d/s trajectory of stream standard Define d/s trajectory of ammonia concentration Determine maximum effluent concentration such that instream ammonia will not exceed standard at any point downstream

Trajectory of Standard Effect of effluent on stream chemistry generally elevates standard Effect is transitory Initial value of standard declines downstream because underlying controls (pH and temperature) trend separately toward “equilibrium” values Greatest risk of exceedance may occur anywhere between outfall and equilibrium conditions

What is equilibrium? Stable pH and temperature characteristic of this mixture of effluent and stream water May differ from upstream conditions, especially if effluent flow is large Equilibrium is dynamic with substantial diel and seasonal variation in pH and temperature This variability must be captured in standard

Trajectories for pH and Temperature Initial mixed conditions defined from flow- weighted mean pH and temperature Effect of effluent on stream pH and temperature is transitory Initial mixed pH and temperature trend separately toward “equilibrium” values If the equilibrium value and the rate of change are known, pH or temperature can be predicted at any point downstream of the outfall

Setpoint: Equilibrium with Regulatory Twist pH and temperature associated with greatest risk of exceeding ammonia standard for equilibrium conditions Worst case in each month, subject to once-in-three-year exceedance Terminus for pH and temperature trajectories, not a fixed location

Why Obtaining Setpoint is Difficult Sole task of Recur model Field grab samples form framework Apply characteristics of temporal variation to construct set of hourly values spanning entire period of record Calculate standards hourly and determine acute (1-h) and chronic (30-d) values consistent with once-in-three-year exceedance threshold Find associated pH (acute and chronic) and temperature (chronic)

Application for Setpoint Hidden hand – guides pH and temperature toward target with regulatory meaning Essential for producing d/s trajectory of ammonia standard, separately for acute and chronic

Back up a step.... Incorporation of temporal variation pH and temperature in stream exhibit temporal variation of diel and seasonal scales...thus applies to standard, too Predictable diel pattern –Based on sine curve –Given amplitude and time of max, one grab value can define complete 24-h pattern –Model contains defaults, or user can supply

Diel Patterns of Variation Pattern of each is predictable (sine curve) Asynchronous pH and temperature patterns

Adjusting Grab Sample Data Translate grab sample to daily average or maximum using amplitude and time of maximum

Implications for Toxicity Time of day matters Not a sine function Average toxicity is not same as toxicity based on average pH and temperature

Empirical Seasonal Pattern Driven by pattern observed in recent historical record Temperature shows strong seasonal variation in mean; tracking air temperature pH shows strong seasonal variation in amplitude; result of biological activity

Seasonal Variation: Temperature Strong pattern Monthly time step Importance of physical processes

Seasonal Variation: pH Seasonal change in maxima, but not in minima Amplitude varies across sites in same region Importance of biological processes

Next Task: Ammonia Trajectory Initial concentration determined by mass balance calculations Change in concentration d/s affected strongly by biological processes (i.e., non- conservative behavior) Dominant process: nitrification Others: uptake (-), ammonification (+) Model represents a net loss rate

Why Non-conservative Matters Nitrification reduces ammonia First order kinetics Any loss increases limits

K3 Temperature Dependence Nominal rate applies at 20 o C Ambient rate sensitive to temperature (8%/ o C)

Revisit Scenario with New K3 Interaction of loss rate and d/s trajectory of standard Importance of site-specific data

Next Task: Linking Limits to Standards AMMTOX sets monthly limits by manual iteration (i.e., trial and error) Aiming for maximum effluent concentration such that instream ammonia will not exceed standard at any point downstream

Trial Iteration

Organization of AMMTOX Recurrence model –Defines setpoint conditions, integral to mapping downstream trajectory of toxicity Reach Model –Predicts downstream pattern of stream standard based on expected spatial patterns in pH and temperature –Predicts downstream changes in total ammonia based on first order kinetics –Employs graphical approach for setting permit limits

Section 2: Data Needs and Sources Setpoint Determination –Grab samples from equilibrium stream conditions; 3-5 yrs, weekly-monthly –Diel patterns of variation for pH and temperature (amplitude, time of max) Default (3 levels for pH) User supplied (confirm or replace default) –Ecological Conditions Implied by classification (warm vs. cold) Local knowledge of fish community

Sampling Site Selection Ideal site: far enough downstream for rebound to be complete, yet not influenced by tributaries, etc. Practical site –Upstream OK if too many confounding influences downstream –Small effluent: upstream or 2-4 mi downstream –Large effluent: trajectory based on interim sites

Site-Specific Characterization of Diel Patterns of Variation Summer (July-August best) Low flow Data logger: 15-min intervals; get amplitude and time of max Grab: sunrise for minima, mid- to late afternoon for maxima; get amplitude With either approach, a few sunny days will determine usefulness of defaults

Sunny Days and pH Amplitude

Sampling Time and Default Amplitude

Define Ecological Setting for Reach Model Are salmonids present? –Default assumption might be yes for Cold water classification –Affects pH component (applies to acute and chronic standards) Are Early Life Stages (ELS) present? –Must specify for each month –Applies to all species in fish community –Affects temperature component (does not apply to acute)

Salmonids and Effect of FAV

Acute Values (CMC) 1-h average Nonlinear function of pH Not a function of temperature Linear function of FAV –Salmonids present: 11.23 –Salmonids absent: 16.8

Temperature Dependence and ELS T<7 o C; max effect of ELS 714.5 o C; no effect of ELS

Chronic Values (CCC) 30-d average Nonlinear function of pH Linear function of FAV Nonlinear function at higher temperature –Invertebrate slope: 10 -0.028*(T-25) ; T>7 o C Linear function at lower temperature –ELS absent; invertebrate GMCV (1.45) applies at T<7 –ELS present; fish GMCV (2.85) applies at T<14.5

Reach Model Inputs Flows Water Quality Basis for trajectories –Rebound –Setpoint –K3 –Travel time Characteristics of standards Consistency with Recur Model (not linked)

Hydrologic Conditions Upstream: Regulatory low flow (e.g., DFLOW) Effluent: Design capacity Tributaries and diversions: preserve low flow regime; reconstructions and DFLOW by difference Seepage: Residual between gages; includes alluvial discharge, direct surface runoff and small, ungaged tributaries

Input Water Quality Avoid worst of worst scenarios Upstream: average or median Effluent (pH, temperature): average or median Seepage: average or median Diversions: no direct effect on WQ

Rebound Rates Default rates used in AMMTOX –pH: 0.2 units per mile –Temperature: 0.7 o C per mile Site-specific rates are very rare Produces gradual, linear shift toward setpoint conditions

Spatial Patterns of Variation Addition of effluent changes temperature and depresses pH in stream Shift is transitory, but can be dramatic

Ammonia Loss Rate Measured for many CO streams Wide range of values; generous default Study design considerations –Paired samples d/s of mixing zone –Travel time critical; must be able to see change in concentration –Detection limit and resolving power –Implications for DO modeling –Dilution by seepage vs. biological decay

Velocity Channel Geometry –Default –Site-specific: USGS Surface-water Measurements Manning’s Eqn Fixed Value; enter manually by reach Special Considerations –Acute and chronic can be set separately –Multiple equations or approaches can be used when proper links are established

Time of Travel

Design of Basic Sampling Program What –Stream: pH, temperature, time, ammonia (u/s) –Effluent: pH, temperature When –Stream: biweekly or monthly –Effluent: individual, not DMR summary Where –Upstream –Downstream (equilibrium conditions) Supplemental –Ammonia loss rate –Diel variation in pH and temperature –Seepage –Velocity

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