Several studies have been conducted on droughts, precipitation, and temperature, whereas none have addressed the underlying relationship between nonlinear dynamic properties and patterns of two main hydrological parameters, precipitation and temperature, and meteorological and hydrological droughts. Monthly datasets of Midlands in the UK between 1921 and 2019 were collected for analysis. Subsequent to apply a multifractal approach to attain the nonlinear features of the datasets, the relationship between two hydrological parameters and droughts was investigated through the cross-correlation technique. A similar process was performed to analyze the relationship between multifractal strength variations in time series of precipitation and temperature and droughts. The nonlinear dynamic results indicated that droughts (meteorological and hydrological) were substantially affected by precipitation than temperature. In other words, droughts were more sensitive to precipitation fluctuations than temperature fluctuations. Concerning temperature, meteorological, and hydrological droughts were dependent on the minimum and maximum temperatures (\(T_{{{\text{min}}}}\) and \(T_{{{\text{max}}}}\)), respectively. The correlation between precipitation and meteorological drought was more long-range persistence than precipitation and hydrological drought. Besides, the correlation between \(T_{{{\text{max}}}}\) and droughts was more long-range persistence than \(T_{{{\text{min}}}}\) and droughts. Analysis of nonlinear dynamic patterns proved that the multifractal strength of meteorological drought depended on the multifractal strength of precipitation and \(T_{{{\text{max}}}}\), whereas the multifractal strength of hydrological drought depended on the multifractal strength of the \(T_{{{\text{min}}}}\). The correlation between precipitation and drought indices exhibited more multifractal strength than temperature and drought indices. Finally, the pivotal role of maximum temperature on drought events was quite alerting due to global warming intensification.

已经对干旱、降水和温度进行了多项研究，但没有一项研究解决了两个主要水文参数（降水和温度）以及气象和水文干旱的非线性动态特性和模式之间的潜在关系。收集了 1921 年至 2019 年英国中部地区的月度数据集进行分析。在应用多重分形方法获得数据集的非线性特征之后，通过互相关技术研究了两个水文参数与干旱之间的关系。进行了类似的过程来分析降水与温度和干旱时间序列中多重分形强度变化之间的关系。非线性动态结果表明干旱（气象和水文）受降水的影响比受温度的影响更大。换句话说，干旱对降水波动比对温度波动更敏感。关于温度，气象和水文干旱取决于最低和最高温度（\(T_{{{\text{min}}}}\)和\(T_{{{\text{max}}}}\) )，分别。降水与气象干旱的相关性比降水与水文干旱更具长期持续性。此外，\(T_{{{\text{max}}}}\)与干旱的相关性比\(T_{{{\text{min}}}}\)与干旱的相关性更持久。非线性动态模式分析表明，气象干旱的多重分形强度取决于降水的多重分形强度和\(T_{{{\text{max}}}}\)，而水文干旱的多重分形强度取决于多重分形强度的\（T _ {{{\文本{分钟}}}} \）. 降水和干旱指数之间的相关性比温度和干旱指数表现出更强的多重分形强度。最后，由于全球变暖加剧，最高温度对干旱事件的关键作用非常警觉。