Linking reported drought impacts with drought indices, water scarcity, and aridity: the case of Kenya

Abstract

Abstract. The relation between drought severity, as expressed through widely used drought indices, and drought impacts is complex. In particular in water-limited regions where water scarcity is prevalent, the attribution of drought impacts is difficult. This study assesses the relation between reported drought impacts, drought indices, water scarcity, and aridity across several counties in Kenya. The monthly bulletins of the National Drought Management Authority in Kenya have been used to gather drought impact data. A Random Forest (RF) model was used to explore which set of drought indices best explains drought impacts on: pasture, livestock deaths, milk production, crop losses, food insecurity, trekking distance for water, and malnutrition. The findings of this study suggest a relation between drought severity and the frequency of drought impacts, whereby the latter also showed a relation with aridity, whilst water scarcity did not. The results of the RF model reveal that drought impacts can be explained by a range of drought indices across regions with different aridity. While the findings strongly depend on the availability of drought impact data and the socio-economic circumstances within a region, this study highlights the potential of linking drought indices with text-based impact reports. In doing so, however, spatial differences in aridity and water scarcity conditions have to be taken into account.

Advances and gaps in the science and practice of impact‐based forecasting of droughts

“…Detected by a range of various drought indices, different drought types can lead to different impacts with various response times across multiple affected sectors (Lam et al, 2022; Wanders et al, 2017). Meteorological drought typically manifests earlier, while agricultural drought requires time to propagate and visibly affect crops or ecosystems (Stagge et al, 2015).…”

“…It is the complex, multifaceted (Van Loon, Stahl, et al, 2016b) and elusive (Kchouk et al, 2021) nature of drought that challenges detecting, quantifying and collecting the information on impacts of droughts. There has been an ongoing debate about the operational needs for drought monitoring (Lam et al, 2022), which constantly results in an urgent call to gather the information of impacts of droughts in a systematic and uniform way. This “missing piece” of information on impacts in drought monitoring affects greatly the capacity to decrease vulnerabilities, anticipate and respond in a timely fashion to droughts and their impacts (Lackstrom & Crimmins, 2013).…”

“…These methods can be applied to diverse sources, including newspaper articles, impact reports and academic texts. Despite the ability to capture the range of drought impacts, textual impact monitoring also presents a number of challenges (Bachmair et al, 2016; Lam et al, 2022; de Brito et al, 2020; Stahl et al, 2016): Media reporting bias on what types of impacts are reported, where they are reported and how regular the reporting is depending on other unrelated local, national, or global events; Human factors affecting perception of impacts over time; Inconsistency in search keywords (except for the automatized detection methods), the selection of relevant texts, and the choice of information channels for retrieving articles (especially for different languages); Difficulty in extracting specific geographical information from textual data that directly links to drought‐related impacts; and Challenging to merge qualitative and quantitative data and/or use as quantitative data only and incorporate into DEWSs; These challenges hinder a systematic monitoring and evaluation of drought impacts and their links to drought indicators. It is especially crucial to be able to create standardized and long‐term impact data records (e.g., US DIR records start in 2005).…”

“…Further research efforts should consider developing an improved impact database in terms of higher spatial and temporal resolution, differentiating between sectors and regions to alleviate reporting bias and enable systematic and standardized collection of quantitative impact information (Kreibich et al, 2020; Lam et al, 2022). One way to achieve this is to employ enhanced data processing tools to collect and merge such quantitative data from validated governmental impact reports in combination with alternatives like insurance data or citizen science that has capacity to be maintained over the long term.…”

Significant relationships between drought indicators and impacts for the 2018–2019 drought in Germany

“…Given these characteristics, drought impacts must be examined comprehensively by geographic region, temporal dimension and affected sector. Consequently, there is a lack of specific impact data solely attributed to droughts, with commonly utilized sources including agricultural statistics, insurance data, impacts bulletins (Lam et al 2022) and media reports (Blauhut et al 2015, Stagge et al 2015, Stahl et al 2016, Sutanto et al 2019, de Brito et al 2020, Torelló-Sentelles and Franzke 2021, O'Connor et al 2022. This research leverages mediabased sources for impact data due to their capacity to encompass a wide range of drought impacts across various sectors and to provide a measure of impact severity without a near-exclusive focus on monetary metrics, as is common in economic or other conventional measures of drought impact.…”