Abstract Drought hazards have complex climatic and spatio-temporal features. Therefore, its accurate monitoring is a challenging task in hydrological research. In recent, the use of standardized drought indices for drought monitoring is common in practice. However, the existence of several drought indices creates chaotic problems in data mining and decision making. This article presents a new weighting scheme for combining multiple drought indices. We propagated steady-state probabilities of Markov chain as weights in the Probabilistic Weighted Joint Aggregative Index (PWJADI) criterion. Hence, to aggregate drought characterization two or more indices, averaged long term behavior of drought classification states observed in the individual drought index is considered as a weighting characteristic. The proposed algorithm is rather general and can be used for any standardized type of drought indices. The new procedure is named as Long Averaged Weighted Joint Aggregative Criterion (LAWJAC). In this research, we focused on the three multi-scalar drought indices namely, Standardized Precipitation Index (SPI), Standardized Precipitation Evaporation Index (SPEI), Standardized Precipitation Temperature Index (SPTI). The selection of these indices is due to their similar computational procedures. In the evolution of LAWJAC, three meteorological stations of the Northern Area of Pakistan are considered. A comparison of LAWJAC is made with PWJADI. Results show significant deviations between existing and proposed methods. By the rationale of the proposed algorithm, these deviations strongly advocate the use of LAWJAC for more accuracy in drought characterization.

中文翻译：

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一种新的多标量标准化干旱指数的广义组合程序-长平均加权联合聚合准则

摘要 干旱灾害具有复杂的气候和时空特征。因此，对其进行准确监测是水文研究中的一项具有挑战性的任务。最近，在实践中普遍使用标准化干旱指数进行干旱监测。然而，多个干旱指数的存在给数据挖掘和决策带来了混乱的问题。本文提出了一种用于组合多个干旱指数的新加权方案。我们将马尔可夫链的稳态概率作为概率加权联合聚合指数 (PWJADI) 标准中的权重进行传播。因此，为了汇总两个或多个指数的干旱特征，在单个干旱指数中观察到的干旱分类状态的平均长期行为被视为加权特征。所提出的算法相当通用，可用于任何标准化类型的干旱指数。新程序被命名为长平均加权联合聚合准则 (LAWJAC)。在本研究中，我们重点研究了三个多标量干旱指数，即标准化降水指数（SPI）、标准化降水蒸发指数（SPEI）、标准化降水温度指数（SPTI）。选择这些指数是因为它们的计算程序相似。在 LAWJAC 的演变过程中，考虑了巴基斯坦北部地区的三个气象站。LAWJAC 与 PWJADI 进行了比较。结果显示现有方法和提议方法之间存在显着差异。根据所提出算法的基本原理，