Addressing potential drought resiliency through high-resolution terrain and depression mapping

Tomasz Oberski, Marek Mróz, Jae Ogilvie, John Paul Arp and Paul A. Arp

Agricultural Water Management, 2021, vol. 254, issue C

Abstract: Increasing occurrences of droughts across Europe and elsewhere require landscape-wide water-retention assessments to evaluate water-supply sustainabilities for local and regional use. This article reports on the results of a study designed to digitally delineate, connect and categorize recurring depression wetness across a rurally cultured morainal landscape, at 1 m resolution. To do this, a digital terrain model (DTM, 1 m resolution) was used to locate and characterize each terrain-detectable depression by type, depth, area, and volume, together with their flow-channel connections and upslope flow-accumulation areas. In addition, historical 2008–2017 Google Earth images and a local daily weather report were used to index and verify weather- and season-induced changes in depression wetness based on ground coloration, vegetation coverage, and image date. Developing and applying these procedures by way of a case study revealed (i) that about 90% of the image-indexed depression wetness variations could mostly be attributed to DTM-determined depression type, area and depth, and (ii) that image-recognized wetness variations were consistent with weather-modelled soil moisture projections. The results so obtained can be used to quantify potential drought resiliency in terms water retention volumes per depression. Since the procedures as described have a broad application potential, they can be used globally for drought resiliency evaluations and agricultural water management.

Keywords: Post-glacial landscape; Digital elevation modelling; Depressions; Recurring wetness; Flow channels; Historical satellite images (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:254:y:2021:i:c:s0378377421002262

DOI: 10.1016/j.agwat.2021.106961

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