Reconciling Drought Vulnerability Assessment Using a Convergent Approach: Application to Water Security in the Elqui River Basin, North-Central Chile

Abstract

Drought has been, is and most likely will remain one of the most significant socio-natural disasters affecting society and the environment worldwide. One priority objective in the adoption of national drought policies is to promote standardized approaches to vulnerability assessment. To reach this objective, however, there is a need to address the noticeable lack of reconciliation between the two major epistemic frameworks that have been used to determine who is vulnerable and why: the so-called outcome and contextual frameworks. This study presents a novel procedure called the convergent approach to assess drought vulnerability under an integral framework. The procedure has been applied to the study of the vulnerability of water security to drought in water-use sectors in a basin located in north-central Chile. The study is justified by the role that drought plays as the major threat to water security in a context of global water crisis. The results show that the convergent approach outperforms traditional procedures such as those based on composite indicators, showing sound robustness and reaching sufficient levels of reliability and validity. The potential expansion of this approach to other applications, such as those related to global estimations of vulnerability to drought, is also discussed.

Drought Vulnerability Indices in Mexico

“…However, no method to do this is unanimously accepted, which opens the door for scientists to select and propose the most appropriate method in each case according to the specific study. For instance, in recent years many studies on vulnerability have been carried out in several countries of the world, all of which use different methods and concepts (e.g., [25][26][27][28][29][30][31][32][33][34][35][36][37]). Likewise, in Mexico different studies on vulnerability to drought have been conducted in some states and regions of the country (e.g., [38][39][40][41]), but none of them have used the same procedures or methods.…”

Explainable Artificial Intelligence in Hydrology: Interpreting Black-Box Snowmelt-Driven Streamflow Predictions in an Arid Andean Basin of North-Central Chile

“…In the same model, the SOI for the month of May is less important, which could be explained by the fact that El Niño conditions have lost precipitation prediction ability in central and north-central Chile. Indeed, El Niño has presented less predictive ability in the last decade due to the influence of other ocean climate factors, with the 500 hPa geopotential height in the Amundsen-Bellingshausen sector standing out [42,67].…”

“…Because the study area has experienced megadrought conditions in the last decade, associated with various factors [42,66,67], it is important to analyze how the selected attributes explain the lower streamflow recorded in the available database. To this end, the September (December) 2020 streamflow was selected as the event to forecast, and the results were interpreted in terms of the Shapley value (SHAPv) and LIME, two of the most-used local techniques for hydrological applications in the XAI/iML context [56,63,64].…”