Drought is a complex phenomenon that has harmed more people than any other natural disaster in the last century (Below, 2007). Drought assessment tools include measurements of lack of rainfall, reduced streamflow and water storage, and Drought Indices. Drought indices are widely used around the world to evaluate drought conditions and estimate drought severity (Keyantash and Dracup, 2002; Salehnia et al., 2017). Drought features such as severity, length, and frequency must be investigated in order to plan and manage water resources in a river basin (Dodangeh, 2017). Meteorological drought indices helps us to track meteological drought.
Drought monitoring has advanced significantly in the recent decade, with monitoring and early warning systems being built in a number of countries and regions. Different drought indices have their own set of benefits and drawbacks, and each index may not accurately reflect drought conditions in every location (Vicente-Serrano, 2008). To offer a measure of the moisture conditions at a location, a drought indicator is calculated using data such as precipitation or soil moisture. Drought indicators are calculated using normal moisture conditions as a reference.
There is no one-size-fits-all technique for describing drought conditions, however there are a number of drought indices that can be used to track meteorological drought (Quiring 2009). The Effective Drought Index (EDI) is a combination of the Standardized Precipitation Index (SPI) and the Standardized Precipitation and Evapo-transpiration Index (SPEI).
Further indices in the meteorological drought category, in addition to precipitation, require other meteorology, climatology, or other inputs, as follows:
PALMER DROUGHT SEVERITY INDEX (PDSI)
The Palmer Drought Severity Index (PDSI) estimates relative dryness using easily available temperature and precipitation data. It’s a standardized scale that ranges from -10 (dry) to +10 (wet) (wet). The range of operating agencies’ maps, like as NOAA’s, is normally -4 to +4, however more extreme readings are possible. Long-term drought has been pretty well quantified using the PDSI. It can capture the basic effect of global warming on drought through changes in potential evapo-transpiration since it employs temperature data and a physical water balance model. Droughts on time scales less than around 12 months are not captured by monthly PDSI values; other pros and downsides are covered in the Expert Guidance.
What are some strengths of this index?
Effective at predicting long-term drought, particularly at low and middle latitudes.
The PDSI accounts for the basic effect of global warming through potential evapo-transpiration by utilizing surface air temperature and a physical water balance model.
Takes into account previous month’s conditions
What are some weakness of this index?
*The Standardized Precipitation Index (SPI) is more comparable across regions, but this can be mitigated by utilizing the self-calibrating PDSI.
*Because it lacks the multi-timescale properties of indices like the SPI, it’s impossible to link it to specific water resources like runoff, snowpack, reservoir storage, and so on.
*Does not take into consideration snow or ice (delayed runoff); assuming precipitation is available right away.
Palmer Hydrological Drought Index (PHDI)
Based on the original PDSI and updated to account for longer-term dryness, which will have an impact on water storage, stream flow, and groundwater. PHDI can predict when a drought will end based on the amount of precipitation required by calculating the ratio of moisture received to moisture required to end the drought.
There are four types of droughts: near normal, which occurs around 28%–50% of the time; mild to moderate, which occurs approximately 11%–27% of the time; severe, which occurs approximately 5%–10% of the time; and extreme, which occurs approximately 4% of the time.
Its water balance technique takes into account the entire water system.
Extreme drought may not be a rare occurrence during some months of the year, but it will vary by place and time of year. Human factors such as management decisions and irrigation are not taken into account in the computations.