Extreme Hydro-Climate Events: Past, Present, and Future

In recent years, extreme hydro-climate events (such as floods and droughts) have occurred more frequently, leading to significant threats to lives and damage of property [1,2,3,4,5,6]. For example, the Food and Agriculture Organization (FAO) of the United Nations (UN) reported that the annual loss caused by drought was between 250 and 300 billion USD [7]. It is, therefore, important and necessary (1) to better understand their mechanisms of occurrence and evolution, (2) to propose more effective methods for early warning, and (3) to develop novel techniques for risk analysis and vulnerability analysis. For instance, it is vital to study extreme hydro-climate events at different spatial–temporal scales for a better understanding of their occurrence and propagation [8,9]; to utilize multisource data (e.g., ground data and remote sensing data) for more accurate and reliable prediction [10]; and to develop accurate disaster control methods (e.g., soil moisture prediction, rainfall data crowdsourcing, and streamflow forecasting) for better planning and management [11]. Advances in these fields can be helpful for coping with extreme hydro-climate events.

This Special Issue (SI) was proposed with the aim to collect the latest methodological developments and applications in studying both historic and future extreme hydro-climate events. Potential topics included but were not limited to the following: dynamics, mechanisms, and evolutions of extreme hydro-climate events; development of methods for the identification and early warning of extreme hydro-climate events, especially in ungauged basins; improvements to information integration using multisource data; new techniques for risk analysis and vulnerability analysis of extreme hydro-climate events; mitigation practices for real-world extreme hydro-climate events; etc. The collection of papers covers several of these aspects, and the contributions of each specific paper are summarized in the following.

The first paper was written by Yin et al. [12], who explored the spatiotemporal patterns of meteorological drought changes and the mechanisms of meteorological drought occurrence in Yulin City of northern Shaanxi from 1961 to 2015. The authors used the Standardized Precipitation Index (SPI), the Empirical Orthogonal Function (EOF) analysis, and a composite analysis for their analyses, and the findings obtained could provide a reference for the early warning and prediction of regional meteorological drought.

The second paper was written by Luhaim et al. [13], who used two indices (i.e., SPI and the Standardized Streamflow Index (SSI)) to analyze the spatiotemporal changes in historical droughts, taking the Muda River basin in Malaysia as the study area. The authors not only evaluated the trends and magnitude changes in the droughts but also explored the relationships among the droughts with large-scale atmospheric circulations. They reported that the El Niño Southern Oscillation (ENSO) could have the largest impact on the drought formations over the study area, especially during the dry period. They also pointed out the potential directions for future studies, for example, including other parameters (e.g., temperature and relative humidity) to investigate the atmospheric circulation impact on regional drought.

The third paper was written by Vega-Durán et al. [14], who evaluated the areal monthly average precipitation estimates in the Sinu River basin, Colombia, based on two reanalysis datasets (i.e., MERRA2 and ERA5). The authors found that both datasets would overestimate the monthly average precipitation in the study area, and ERA5 generally outperformed MERRA2. It is suggested that other techniques (e.g., bias correction techniques, additional mathematical and statistical techniques, etc.) should be included in future studies to improve the performance of these reanalysis datasets.

In conclusion, the present SI provides new avenues for recognizing past, present, and future extreme hydro-climate events. The findings reported are helpful for understanding the evolution of extreme hydro-climate events, especially in the context of climate change.