عنوان مقاله [English]
Drought is one of the natural hazards whose consequences and effects on social, economic, water resources and agriculture can be significantly revealed. Although the occurrence of drought is inevitable, it can be planned by anticipating a reduction in its devastating effects on the economy, society and the environment. The purpose of this study was to explain the types of drought indicators and introducing the important and widely used indicators in assessing and quantifying meteorological and hydrological droughts. Meteorological drought is usually defined by the degree of dryness (compared to the normal or average value) and the duration of the dry period. Meteorological drought definitions should be considered separately for each specific region; Because the weather conditions that lead to deficit of rainfall vary from one region to another. Drought, in its meteorological sense, means a decrease in rainfall for a certain period of time on a specific area compared to the long-term average of the same area's rainfall in the same period of time.
While introducing the benefits, limitations and scope of different drought classes, the relationships used by droughts are presented. Standardized precipitation indices (SPI), percentage of normal rainfall index (PNPI), rainfall anomaly index (RAI), Bhalme and Mooly drought index (BMDI), decile index (DI), evapotranspiration deficit index (ETDI), Palmer Drought Severity Index (PDSI), reclamation drought index (RDI) and Soil Moisture Drought Index (SMDI) were introduced in the category of meteorological drought. In the category of hydrological drought, surface water supply indices (SWSI) were also examined.
Result and Discussion
Various drought indicators along with variables, time scales and their concepts are presented in the results section. The results showed that the SPI index has a high comparative advantage for monitoring meteorological drought. Also, RDI index is more sensitive to climatic variables than SPI index and PNPI index is not recommended for drought assessment due to high error. The standard precipitation index (SPI) is known as the most suitable index for drought analysis, especially spatial analysis, due to the simplicity of calculations, the use of available rainfall data, the ability to calculate for any desired time scale, and the very high ability to compare results spatially. Due to its simplicity and practicality, Rainfall Anomaly Index (RAI) has been often used in drought estimation to deal with drought in different stages for different climatic regions. The time scale for calculating this index is monthly and yearly. The calculation method of BMDI drought index is similar to Palmer's drought severity index and the index works recursively; That is, in calculating the drought intensity of a given month, a coefficient of the previous month's drought intensity is also considered. The DI index is defined as a rating of the amount of precipitation in a specific period of time and is presented in order to solve the deficiencies in the percentage of normal method. The Decimal Index provides a statistically accurate measure of precipitation, provided long-term climate data are available. The need for low input variables, including all components of water balance in index calculations, and comparability in different times and places are considered strengths of the PDSI index. This index is able to monitor drought in short-term and long-term periods (one to 48 months). This index is increasing due to the need for low data, high sensitivity and high flexibility of its use; Due to the fact that the RDI index is calculated based on rainfall and potential evaporation and transpiration, it is more sensitive to climate variables and changes than drought indicators that are based only on rainfall (such as the standardized precipitation index). The purpose of the SWSI index is to obtain a standard for determining the amount of water available in mountainous areas and the possibility of comparing different areas with each other. The SWSI index determines the severity of ongoing droughts in the region and the future situation can be predicted with the help of this index. SMDI drought index is an index that is based on the total soil moisture daily for one year and the only climatic factor used in it is soil moisture data.
A major part of Iran is located in dry and semi-arid areas, and the drought phenomenon is an inseparable part and is considered one of the characteristics of dry and semi-arid areas. Based on this, a two- to three-year drought period is experienced in the country almost every five years. These droughts have reduced surface and underground water sources and reduced usable water. The occurrence of drought and its continuation also affects the quantity and quality of ground water resources. The reduction of precipitation, which is one of the most important parameters of feeding the underground water aquifers, can cause the destruction and loss of the ground water aquifers. There are different drought indicators, each of which has advantages and disadvantages. Meanwhile, the Comprehensive Drought Index (RDI) is more sensitive to climate variables and changes compared to the SPI index. In this regard, it can be said that the RDI index is calculated based on rainfall and potential evaporation and transpiration, but the SPI index is only calculated based on rainfall. RAI index has the ability to evaluate drought in short-term and long-term time periods (one to 48 months). Overall, a review of the indicators provided can help determine the appropriate indicator to assess drought. An appropriate indicator to provide information on drought management challenges. In addition, it quantifies the practical aspects of drought, such as the severity, duration, and frequency of drought, along with possible, and statistical characteristics. Among the studied indices, the PNPI index is not recommended for drought evaluation due to its high error; Also, the DI index is not suitable for areas having stations with a short-term data period because it requires long-term data to evaluate drought. The PDSI index is calculated from the data of precipitation, temperature and soil moisture and considers any type of precipitation as precipitation. In PDSI index, the average precipitation is not the same as the median, which is one of the disadvantages of this index.