Abstract
Understanding spatial drought characteristics is vital for planning adaptation and mitigation measures in river catchments. In many parts of the world, spatial drought information is not available due to lack of adequate evenly distributed data for spatial drought analyses. This study elucidates a spatial drought analysis in a data-scarce tropical catchment using remote sensing actual evapotranspiration (ET) and potential evapotranspiration (PET) data. Firstly, the time series of 690 images of remotely sensed ET and PET between the years 2000 and 2014 were spatially analyzed using the evapotranspiration deficit index (ETDI) approach to obtain ETDIs in the Kilombero River catchment (Tanzania). Then, spatio-temporal patterns of ETDIs were used to characterize drought frequency, total drought durations, total drought severity, and drought intensity. The frequency, durations, severity, and intensity of drought increased from the year 2000 towards 2014, causing substantial drought changes in the catchment. However, drought intensity revealed that those changes were mainly from no drought and mild drought to moderate drought. Between the years 2000 and 2014, no-drought areas and mild drought areas declined from 10% to 0% and from 42% to 19%, respectively, whereas moderate drought areas increased from 47% to 81% of the catchment size. Those changes of drought conditions were partly attributed to anthropogenic land cover change, especially in the southwest grasslands, and were partly attributed to meteorological factors in other parts of the catchment. This information is crucial for further land cover change and climate change investigations, as well as planning water and land resources in the Kilombero River catchment. Moreover, the study also demonstrates the potential of using publicly available remote sensing ET products and the ETDI approach for spatially characterizing drought in ungauged regions.
Highlights
Drought is an environmental disaster that has harsh and long-lasting impacts on natural and human systems
Due to data scarcity in many large catchments (>40,000 km2 ) such as Kilombero river catchment in Tanzania [20,21] and the need for less data-intensive approaches, this study focused on agricultural drought indices that use a few types of data
The maps of drought frequency (DF) in the Kilombero catchment show that the number of drought events in the
Summary
Drought is an environmental disaster that has harsh and long-lasting impacts on natural and human systems. Drought impacts include humanitarian disasters, economic losses, and stresses on various elements of the environment [1]. Drought is usually characterized using its frequency (how often a drought occurs), duration (the length of a drought), severity (the strength of a drought), and intensity (degree of precipitation shortfall) [2,3]. Information about drought frequency, duration, severity, and intensity is very important in planning adaptation and mitigation measures for reducing drought impacts. In many parts of the world, the coverage of this information is not known or properly documentend because of data scarcity.
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