Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation

Borona, Pius; Busch, Friedrich; Krueger, Tobias; Rufin, Philippe

doi:10.3390/w13243611

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Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation

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IRI THESys, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany

Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany

Earth and Life Institute, Université Catholique de Louvain, Place Pasteur 3, 1348 Louvain-la-Neuve, Belgium

Author to whom correspondence should be addressed.

Academic Editors: Alban Kuriqi and Luis Garrote

Water 2021, 13(24), 3611; https://doi.org/10.3390/w13243611

Received: 1 November 2021 / Revised: 4 December 2021 / Accepted: 6 December 2021 / Published: 16 December 2021

(This article belongs to the Topic Water Management in the Era of Climatic Change)

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Abstract

Droughts are complex and gradually evolving conditions of extreme water deficits which can compromise livelihoods and ecological integrity, especially in fragile arid and semi-arid regions that depend on rainfed farming, such as Kitui West in south-eastern Kenya. Against the background of low ground-station density, 10 gridded rainfall products and four gridded temperature products were used to generate an ensemble of 40 calculations of the Standardized Precipitation Evapotranspiration Index (SPEI) to assess uncertainties in the onset, duration, and magnitude of past droughts. These uncertainties were driven more by variations between the rainfall products than variations between the temperature products. Remaining ambiguities in drought occurrence could be resolved by complementing the quantitative analysis with ground-based information from key informants engaged in disaster relief, effectively formulating an ensemble approach to SPEI-based drought identification to aid decision making. The reported trend towards drier conditions in Eastern Africa was confirmed for Kitui West by the majority of data products, whereby the rainfall effect on those increasingly dry conditions was subtler than just annual and seasonal declines and greater annual variation of rainfall, which requires further investigation. Nevertheless, the effects of increasing droughts are already felt on the ground and warrant decisive action. View Full-Text

Keywords: droughts; gridded data; SPEI; semi-arid; Eastern Africa

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Doi: 10.20944/preprints202111.0137.v1
Link: https://www.preprints.org/manuscript/202111.0137/v1

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MDPI and ACS Style

Borona, P.; Busch, F.; Krueger, T.; Rufin, P. Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation. Water 2021, 13, 3611. https://doi.org/10.3390/w13243611

AMA Style

Borona P, Busch F, Krueger T, Rufin P. Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation. Water. 2021; 13(24):3611. https://doi.org/10.3390/w13243611

Chicago/Turabian Style

Borona, Pius, Friedrich Busch, Tobias Krueger, and Philippe Rufin. 2021. "Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation" Water 13, no. 24: 3611. https://doi.org/10.3390/w13243611

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Author Biographies

Pius Borona

Pius Borona is a Doctoral Researcher at the Geography Department and IRI THESys of Humboldt-Universität zu Berlin, Germany. He holds a Master of Environmental Science from Kenyatta University, Nairobi, Kenya from 2016. He has six years regional work experience as a researcher, research fellow, and research associate covering roles and areas in East and West Africa. He has involved in regional assessments of climate change and variability adaptation in the context of agricultural ecosystems and food security which are also his doctoral research interests. Additional themes he has worked on include natural resource management and conflict resolution over pastoral Northern Kenya. He is a professional member of the Africa Forest Forum, the Africa Technology and Policy Studies Network, and an associate expert with the Kenya National Environment Management Authority.

Friedrich Busch

Friedrich Busch is currently enrolled in the MSc. Global Change Geography and works as a student assistant at the Geography Department of Humboldt-Universität zu Berlin. He holds a bachelor’s degree in Geoecology from Potsdam University from 2018. His research interests are in statistics, environmental sciences, and expanding the scope of existing procedures to new applications.

Tobias Krueger

Tobias Krueger is a Professor of Hydrology and Society at Humboldt-Universität zu Berlin´s Geography Department and IRI THESys. He studied Geoecology at the Technical University of Braunschweig and obtained his PhD in Environmental Science from Lancaster University in 2009. From 2008 to 2013, he worked as Postdoc at the University of East Anglia. From 2013 to 2020 he was a Junior Professor at Humboldt-Universität zu Berlin. His research is at the intersection of hydrology and critical social science. His hydrological expertise is in modelling, with a focus on the interrelation of land use and management practices with water quality. He cares deeply about data uncertainty and model structural uncertainty, with a methodological focus on developing, applying, and critiquing statistical methods. He is a member of the European Geosciences Union (EGU), the International Association of Hydrological Sciences (IAHS) and the International Environmental Modelling & Software Society (iEMSs), among others.

Philippe Rufin

Philippe Rufin is a postdoctoral researcher at the Université catholique de Louvain, Belgium. He studied Physical Geography of Human-Environment Systems at Humboldt-Universität zu Berlin, where he also obtained a doctoral degree in Geography. His research interests lie in land system science and Earth observation. His previous works involve the development and application of tools and methods for large-area mapping of land use and land use intensity in agricultural landscapes, with a particular focus on processes related to water resources.

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Uncertainty in Drought Identification Due to Data Choices, and the Value of Triangulation

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