A Probabilistic Weighted Joint Aggregative Drought Index (PWJADI) criterion for drought monitoring systems

Abstract

Drought is a complex natural hazard. Its several adverse impacts are prevailing in almost all climatic zones around the world. In this regards, drought monitoring and forecasting play a vital role in making drought mitigation policies. Therefore, several drought monitoring tools based on probabilistic models had been developed for precise and accurate inferences of drought severity and its effects. However, risk of inaccurate determination of drought classes always exists in probabilistic models. To overcome this issue, we proposed a new system based Probabilistic Weighted Joint Aggregative Drought Index (PWJADI) criterion for three multi-scalar drought indices, namely Standardized Precipitation Index (SPI), Standardized Precipitation Temperature Index (SPTI), and Standardized Precipitation Evapotranspiration Index (SPEI) at one-month time scale. By the basic assumption of the Markov chain, the PWJADI is based on the temporal switched weights that are propagated from the transition probability matrix of each temporal classification of drought index. Application of the proposed method is made for three meteorological stations of Pakistan. We found that our proposed model has ability to restructure the drought classes by capturing and bending the information from the historical behaviour of each drought class. Consequently, to make accurate and precise drought mitigation policies, the proposed method may integrate into effective drought monitoring systems.

A novel generalized combinative procedure for Multi-Scalar standardized drought Indices-The long average weighted joint aggregative criterion

“…Then the transition probability matrix of the process SDIt can be defined as follows: The above (transition probability) matrix, either first order on n th order, gives a probability of moving one drought states to another drought states. In the previous study, Ali et al (2019a) have suggested these probabilities as switching weights. They assumed that the behavior of the process follows first-order Markov chain.…”

“…On the same rationale of PWJADI, in this paper steadystates probability is utilized as a weight. However, the significance of the proposed model over PWJADI (Ali et al, 2019a) is that the proposed model is free from the assumption of 1 st order Markov chain. The next phase describes how these probabilities are configured in the aggregation model.…”

“…Recently, Ali et al (2019a) proposed a new drought aggregation criterion-the Probabilistic Weighted Joint Aggregative Drought Index (PWJADI). In PWJADI, the vectors of three commonly used drought indices namely SPI, SPEI, and SPTI are combined in a systematic way (see equation 17).…”

“…This paper proposes a new criterion to combine temporal classification of drought determined by various standardized tools. The proposed criterion is more likely to PWJADI (Ali et al, 2019a). However, its weighting scheme differs from those which have been used in the PWJADI criterion.…”

“…Accordingly, Luetkemeier et al (2017) have proposed Blended Drought Index (BDI) by integrating SPI, SPEI, and Standardized Soil Moisture Index (SSMI) in copula equation (Hao, and AghaKouchak, 2013). Recently, Ali et al (2019a) have provided a Probabilistic Weighted Joint Aggregative Drought Index (PWJADI) criterion for combining temporal classification of three drought indices namely SPI, SPEI, and SPTI. This paper proposes a new criterion to combine temporal classification of drought determined by various standardized tools.…”