This series of datasets has been created by AAFC’s National Agroclimate Information Service (NAIS) of the Agro-Climate, Geomatics and Earth Observations (ACGEO) Division of the Science and Technology Branch. The Canadian Drought Monitor (CDM) is a composite product developed from a wide assortment of information such as the Normalized Difference Vegetation Index (NDVI), streamflow values, Palmer Drought Index, and drought indicators used by the agriculture, forest and water management sectors. Drought prone regions are analyzed based on precipitation, temperature, drought model index maps, and climate data and are interpreted by federal, provincial and academic scientists. Once a consensus is reached, a monthly map showing drought designations for Canada is digitized. AAFC’s National Agroclimate Information Service (NAIS) updates this dataset on a monthly basis, usually by the 10th of every month to correspond to the end of the previous month, and subsequent Canadian input into the larger North American Drought Monitor (NA-DM).The drought areas are classified as follows: D0 (Abnormally Dry) – represents an event that occurs once every 3-5 years;D1 (Moderate Drought) – represents an event that occurs every 5-10 years;D2 (Severe Drought) – represents an event that occurs every 10-20 years;D3 (Extreme Drought) – represents an event that occurs every 20-25 years; andD4 (Exceptional Drought) – represents an event that occurs every 50 years. Impact lines highlight areas that have been physically impacted by drought. Impact labels specify the longitude and magnitude of impacts.The impact labels are classified as follows:S – Short-Term, typically less than 6 months (e.g. agriculture, grasslands).L – Long-Term, typically more than 6 months (e.g. hydrology, ecology).

The term "Palmer Drought Index" has been used collectively to represent multiple indices. This index is simply a water balance model which analyzes precipitation and temperature, and used as a tool to measure meteorological and hydrological drought across space and time. All versions of the index uses the Versatile Soil Moisture Budget to model the movement of water within the system, and a daily Priestly-Taylor model to estimate evapotranspiration. The Palmer Drought Index (PDI) uses monthly temperature and precipitation data to calculate a simple soil water balance. The index is a relative measure that typically ranges from -4 (extremely dry) to +4 (extremely wet) and represents how soil moisture availability differs from that expected for a given place and time of year. The PDI includes a "memory" component that considers past conditions and persistence of soil moisture surplus or deficit.The Palmer Hydrological Drought Index (PHDI) is a specific version of the PDI that accounts for longer-term drought that reduces surface and groundwater supply.

This data represents the dryness of the land surface based on vegetation conditions. The data is created weekly and uses weekly information on precipitation anomalies (namely the Standardized Precipitation Index or SPI) and satellite vegetation condition derived from Normalized Difference Vegetation Index (NDVI) from the MODIS Satellite. These dynamic data sets along with static data sets on land cover, soil water holding capacity, irrigation, ecozones and land surface elevation are used to model the drought severity, based on the Palmer Drought Severity Index (PDSI). The mapcubist model was trained on historical data and applied in real time to the dynamic inputs to produce drought severity ratings. The model is run at a 1km resolution and was developed by the AAFC, the United States Geological Survey and the United States Drought Monitor at the University of Nebraska Lincoln.

The term "Palmer Drought Index" has been used collectively to represent multiple indices. This index is simply a water balance model which analyzes precipitation and temperature, and used as a tool to measure meteorological and hydrological drought across space and time. All versions of the index uses the Versatile Soil Moisture Budget to model the movement of water within the system, and a daily Priestly-Taylor model to estimate evapotranspiration.The Palmer Drought Index (PDI) uses monthly temperature and precipitation data to calculate a simple soil water balance. The index is a relative measure that typically ranges from -4 (extremely dry) to +4 (extremely wet) and represents how soil moisture availability differs from that expected for a given place and time of year. The PDI includes a "memory" component that considers past conditions and persistence of soil moisture surplus or deficit. The Modified Palmer Drought Index (PMDI) is obtained from the sum of the wet and dry terms weighted by probability values. The PMDI has the same value as the PDI during established dry or wet spells but can be different during transition periods.

The Drought Impact Lines dataset highlights areas that have been physically impacted by drought. All drought impact lines have a drought impact label inside of them to express the longevity of the impact.The impact lines are classified using impact labels as follows:S – Short-Term, typically less than 6 months.L – Long-Term, typically more than 6 months.SL – A combination of Short and Long-Term impacts.

The Drought Impact Label dataset is used on all drought polygons from D1 to D4 to specify the longitude and magnitude of impacts. Impact labels are often used in association with the Drought Impact Line dataset.The impact labels are classified as follows:S – Short-Term, typically less than 6 months.L – Long-Term, typically more than 6 months.SL – A combination of Short and Long-Term impacts.

The Blended Index (BI) is a model which employs multiple potential indicators of drought and excess moisture, such as the Palmer drought index, rolling precipitation amounts and soil moisture, and combines them into a weighted, normalized value between 0 and 100. The inputs and weights used in this model are subject to change periodically as it is optimized to best represent extent, duration and severity of impactful weather conditions. The blended index is deployed as two variations; short term (st) focusing on 1 to 3 months, and long term (lt) focusing on 6 months to 5 years.

The Blended Index (BI) is a model which employs multiple potential indicators of drought and excess moisture, such as the Palmer drought index, rolling precipitation amounts and soil moisture, and combines them into a weighted, normalized value between 0 and 100. The inputs and weights used in this model are subject to change periodically as it is optimized to best represent extent, duration and severity of impactful weather conditions. The blended index is deployed as two variations; short term (st) focusing on 1 to 3 months, and long term (lt) focusing on 6 months to 5 years.

Forest Drought Risk Assessment Tool (ForDRAT) provides estimates of stand-level drought risk for various BC tree species (Interior only at this point). Drought risk estimates are provided across different biogeoclimatic units and relative soil moisture regimes for both current and future climates. The data are currently provided in a spreadsheet, with the following columns: 1. BGC: Biogeoclimatic zone, subzone and variant. 2. Period: Data are provided for three historical periods: (i) 1961-1990 climate normal period; (ii) 1971-2000; and (iii) 1981-2010. Projected drought risk is provided for three future periods: (i) 2020 (2011-2040); (ii) 2050 (2041-2070); and (iii) 2080 (2071-2100). 3. SMR_text: Text description of relative soil moisture regime. 4. SMR: Integer code of relative soil moisture regime. 5. AET_PET: Mean annual ratio of actual to potential evapotranspiration. 6. The remaining columns provide estimated drought risk by species. Species codes are as follows: (i) Pl = lodgepole pine; (ii) Sx = hybrid white spruce; (iii) Fd = Douglas-fir (interior variety); (iv) Bl = subalpine fir; (v) Cw = western redcedar; (vi) Hw = western hemlock; (vii) Lw = western larch; (viii) Py = ponderosa pine; (ix) Ac = black cottonwood; and (x) At = trembling aspen. More species will be added over time. Details on ForDRAT development are provided in the following resources: DeLong et al. 2022: http://library.nrs.gov.bc.ca/digipub/Tr141.pdf DeLong et al. 2019: https://www.for.gov.bc.ca/hfd/pubs/Docs/Tr/TR125.pdf Foord et al. 2017: https://www.for.gov.bc.ca/hfd/pubs/Docs/En/En119.htm Nitschke and Innes. 2008: https://www.sciencedirect.com/science/article/abs/pii/S0304380007004061?via%3Dihub

Drought is a deficiency in precipitation over an extended period, usually a season or more, resulting in a water shortage that has adverse impacts on vegetation, animals and/or people. The Climate Moisture Index (CMI) was calculated as the difference between annual precipitation and potential evapotranspiration (PET) – the potential loss of water vapour from a landscape covered by vegetation. Positive CMI values indicate wet or moist conditions and show that precipitation is sufficient to sustain a closed-canopy forest. Negative CMI values indicate dry conditions that, at best, can support discontinuous parkland-type forests. The CMI is well suited to evaluating moisture conditions in dry regions such as the Prairie Provinces and has been used for other ecological studies.Mean annual potential evapotranspiration (PET) was estimated for 30-year periods using the modified Penman-Monteith formulation of Hogg (1997), based on monthly 10-km gridded temperature data. Data shown on maps are 30-year averages. Historical values of CMI (1981-2010) were created by averaging annual CMI calculated from interpolated monthly temperature and precipitation data produced from climate station records. Future values of CMI were projected from downscaled monthly values of temperature and precipitation simulated using the Canadian Earth System Model version 2 (CanESM2) for multiple RCP radiative forcing scenarios.Provided layer: Climate moisture index (CMI) - Future projections using RCP 8.5 for 2011-2040.Reference: Hogg, E.H. 1997. Temporal scaling of moisture and the forest-grassland boundary in western Canada. Agricultural and Forest Meteorology 84,115–122.