Implementing the Surface Water Quality Framework for the Lower Athabasca River

Kim Westcott & Hannah McKenzie

Water Tech April 11, 2013

Presentation Outline

– Provincial Context

– Overview of the Surface Water Quality Framework

– Approach to Annual Surface Water Quality Assessment • Water quality triggers & limits • Evaluating exceedances

– Ongoing Surface Water Quality Framework Development

• Approach to Assessing Trends • Future work

Provincial Context

In 2008, Alberta released its Land-use Framework, which sets out a new approach for managing the province’s land and natural resources. The Land-use Framework establishes seven new land-use regions and calls for the development of a regional plan for each.

Provincial Context

The Lower Athabasca Regional Plan (LARP) is the first regional plan to be implemented under the Land-use Framework. It identifies strategic directions for the region over a ten year timeframe (2012-2022). LARP came into effect on September 1, 2012.

• LARP identifies seven regional outcomes that describe what we want to achieve at a regional level.

• Environmental management frameworks were developed in support of Outcome 4:

“Air and water are managed to support human and ecosystem needs.”

• These management frameworks (air quality, surface water quality, groundwater) build on existing policies, legislation, regulations and management tools.

Lower Athabasca Regional Plan

Surface Water Quality Framework

– Provides a framework in which to monitor and manage long-term cumulative changes in water quality within the lower Athabasca River. – The Framework is a policy document that is given legal authority as specified in the LARP. – Applies to the lower Athabasca River downstream of the Grand Rapids to the Athabasca River Delta.

Map of the Athabasca River basin and the boundary of the Lower Athabasca Region.

Surface Water Quality Framework Overview

The Framework establishes a regional objective for surface water quality.

Regional objective

"Water quality in the lower Athabasca River is managed so current and future water uses are protected."

Water uses include: protection of aquatic life, drinking water, recreation and aesthetics, agricultural and industrial purposes.

To evaluate whether the regional objective is being met, a suite of water quality indicators were selected.

Water Quality Indicators

Water Quality Indicators Thirty eight indicators were selected:

• 11 General Indicators: calcium, chloride, magnesium, potassium, sodium, sulphate, total dissolved phosphorus, total phosphorus, nitrate, total ammonia, total nitrogen.

• 27 Metal Indicators: (total and dissolved except where noted) aluminum, antimony, arsenic, barium, beryllium (total only), bismuth (total only), boron, cadmium, chromium, cobalt, copper, iron, lead, lithium, manganese, mercury (total only), molybdenum, nickel, selenium, silver (total only), strontium, thallium, thorium, titanium, uranium, vanadium and zinc.

Historical record varies for each water quality indicator (length of the record and frequency of sampling).

Surface water quality triggers & limits apply at the Athabasca River

at Old Fort monitoring

station.

Annual Assessment

• The Framework commits to annual evaluation and reporting.

• Ambient monitoring data from the Old Fort station will be evaluated annually relative to surface water quality triggers & limits.

• For each indicator, one of three ambient surface water quality levels is assigned. There are corresponding management intentions for each of the three ambient water quality levels.

• The first annual surface water quality assessment report will be for 2012 data.

Ambient Surface Water Quality Levels

Level Description Management Intent

3 Exceedance of water quality limits.

Improve ambient water quality to below limits.

Limit

2 Exceedance of water quality triggers.

Proactively maintain water quality below limits.

Improve knowledge and understanding of trends.

Trigger

1 Mean and peak water quality conditions at or better than historical water quality conditions.

Apply standard regulatory and non-regulatory approaches to manage water quality.

Approach to Annual Assessment

The annual water quality assessment reports will describe the results of the first 2 steps in the management response - verification & preliminary assessment.

Management Response

Annual Assessment – Mean Triggers

Calculate annual mean for

all indicators.

Determine if the annual mean is significantly higher than mean trigger using Welch’s two-sample t-test and

the Wilcoxin rank sum test.

If the annual mean is > mean trigger (historical mean)

• We will use the results of both tests to inform our conclusions.

Annual Assessment – Peak Triggers

• With 12 samples during the year the peak trigger will:

– Not be exceeded if there are 2 observation > peak trigger (95th percentile of the historical data), p-value = 0.12

– Be exceeded if there are 3 observation > peak trigger, p-value =0.02

Count the number of observations that are greater

than the peak trigger.

Use the Binomial test to determine if the proportion of exceedances is significantly

higher than expected by chance, given the assumption that the annual data have the

same 95th percentile as the historical data.

At least one observation > peak trigger (historical 95th percentile)

Annual Assessment – Limits

• A limit is deemed to have been exceeded if the annual mean (i.e., average conditions) for a given surface water quality indicator exceeds the limit established in the Framework for that indicator. • Not all indicators have limits as appropriate guidelines do not exist for all indicators. • Work to develop appropriate limits for surface water quality indicators is ongoing.

Evaluating Exceedances

Part of the preliminary assessment step in the management response involves ensuring that the effects of natural factors on water quality exceedances are understood.

– Hydrological conditions – was it a particularly dry or wet year? Is the indicator sensitive to changes in flow?

– Is a trend developing? Is it in a direction of concern?

– Are changes evident upstream? In tributaries? Other river systems?

Hydrological Conditions

0 100 200 300

01

00

02

00

03

00

04

00

0

Day of the Year

Flo

w (

cms)

max75th percentilemedian199925th percentilemin

Need to check annual flow patterns against historical flows. Also need to examine the observations that drove the exceedance for correspondence with flow events.

. Data from the Athabasca River upstream of Fort McMurray 1988-2009

Relating Flow & Water Quality • To explore the relationship between flow and water

quality for each of the water quality indicators we use Kendall’s tau-b.

• Kendall’s tau-b is a rank correlation coefficient that provides a measure of the association between two variables, i.e., measures the similarities in ordering of the two variables.

• tau-b = 1, rankings are identical = -1, rankings are reverse of each other = 0, discharge and water quality are independent

• Different interpretation than Pearson’s correlation coefficient.

Results of Kendall’s tau for all water

quality indicators

Relating Flow & Water Quality

Total Aluminum tau = 0.71, p<0.001

Dissolved Antimony tau = 0.11, p=0.38

Sodium tau = -0.81, p<0.001

Some examples of the types of relationships we found:

Approach to Assessing Trends • Need to choose a trend assessment method appropriate to the

characteristics of the data:

Data characteristics – Non-normal distributions – Non-detects, multiple detection limits – Outliers – Varying measurement frequency – Seasonality – Covariates (discharge)

• We chose to use Partial Seasonal Kendall or partial Hirsch-Slack

(PHS) tests (Libiseller and Grimvall 2002), depending on the presence of temporal autocorrelation in the water quality indicator.

Trend Assessment Example - Sodium • Monthly,1988 –

2009

• Non-normal (Shapiro-Wilk, p<0.001)

• Significant seasonality (Kruskal-Wallis, p<0.001)

Trend Assessment Example - Sodium

• No significant trends detected in sodium (1988-2009)

No. observations

Response variable

Covariate

Trend test

Test statistic

p-value (2-sided)

SK Slope

235

Sodium - HS 58 0.75 0.024

Sodium Flow

Flow -

PHS HS

-46 -158

0.80 0.40

0.024 -1.45

• Temporal autocorrelation (Durbin-Watson, p<0.001)

• Strong log-linear relationship with discharge (tau=-0.81, p<0.001)

Assessing Trends

– Presently evaluating how best to incorporate trend assessment in the management response.

– Current thinking is to run a trend assessment for indicators when an exceedance happens (to put it in context), and for all indicators at least every 5 years.

– Would like to estimate our power to detect trends to inform a recommended frequency, however, this would require a simulation approach that is complex and computationally intense.

Future work

• Plans to look at how to incorporate other stations in a trend assessment for a more complete analysis.

• Need to determine when we have enough data to incorporate additional stations in the Framework.