Annex III. Globally mapping river basin vulnerability

data. The pixel changes for each annual data set were then added (gains) or removed (losses) from the 2010 baseline raster mask. In order to produce national statistics for indicator 6.6.1 monitoring, the year 2000 was used as a proxy and based on the 1996 annual data set, to align this baseline with that of the surface water data set.

The percentage change of spatial extent was calculated using the formula:

Percentage change in spatial extent = ((γ-β)/β)×100

Where β is the national spatial extent from the baseline and γ is the national spatial extent for the reporting period. This means that a positive value represents a gain in mangrove extent and a negative value represents a loss in extent.

Method for calculating water quality statistics and classifying “affected” lakes

A baseline reference period has been produced comprising monthly averages for the trophic state and turbidity of lakes from observations made during the five-year 2006–2010 period. A further set of monthly observations made during 2017– 2019 were then used to calculate the change (Δ) against the baseline data using the formula:

Δ = ((γ-β)/β)×100

Where:

β = monthly average for the baseline period (2006–2010)

γ = average for each month in 2017, 2018 and 2019 Zero and below-zero values indicate normal or improved water quality conditions, whereas positive values indicate a water quality deterioration. Water quality parameters are intrinsically dynamic both in space and time, which is why both temporal and spatial criteria are used to classify the ecological state of lakes relative to the baseline. For each pixel, and for each month, monthly deviations were analysed and categorized into one of the following ranges: 0–25 per cent (no to low change); 25–50 per cent (medium change); 50–75 per cent (high change) and 75–100 per cent (extreme change). An annual temporal aggregation was then performed, with the spatial coverage of each lake in the low, medium, high and extreme categories for the years 2017, 2018 and 2010 calculated thereafter. The last step involved isolating lakes with deteriorating conditions using a 50:50 rule, i.e. lakes whose area mostly fell within the high to extreme change categories if any of the three reporting years were classified as deteriorating relative to the baseline. For transboundary lakes, the rule was applied to national shares of the lake, i.e. if a riparian state exceeded the 50:50 rule, the entire lake was classified as high change. Lakes falling within the tundra and boreal forest/taiga biomes (Dinerstein and others, 2017) were excluded due to known issues with the water quality detection method in high latitudes.

Annex III. Globally mapping river basin vulnerability

To accelerate action towards achieving the global target on the protection and restoration of water-related ecosystems, subindicator data must be combined into an aggregate score. However, this is inherently challenging when dealing with dynamic changes to different ecosystem types. A simple aggregation of each subindicator (ecosystem type) into a national