Comparing fine‐scale structural and hydrologic connectivity within unimproved and improved grassland. Issue 7 (29th July 2021)

• Record Type: Journal Article
• Authors: Ellis, Nicola; Brazier, Richard; Anderson, Karen
• Is Part Of: Ecohydrology. Volume 14:Issue 7(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-07-29
• Subjects: connectivity -- flood management -- grasslands -- microtopography -- UAV -- unimproved grassland; Ecohydrology -- Periodicals; Hydrology -- Periodicals; Water -- Environmental aspects -- Periodicals; 577.6
• DOI: 10.1002/eco.2330
• Languages: English
• ISSNs: 1936-0584

Abstract

Abstract: Grasslands vary with diverse forms and functions ranging from monocultures of perennial rye grass to more biodiverse unimproved grasslands which cover around 5% of Europe. Despite the broad diversity of grassland types, within environmental and flood risk models grasslands are frequently represented by a singular set of hydrological and structural parameters which belies their diversity and complexity. This study aimed to determine empirically the extent to which improved versus unimproved grasslands exhibit different hydrological connectivity. Working in SW England at neighbouring field sites with comparable slopes and rainfall regimes, we used unpiloted aerial vehicles to survey a tussocky Molinia caerulea dominated unimproved grassland field (MCUG) field and a Lolium perenne dominated improved grassland (LPIG) field. Using digital photogrammetry workflows applied to the overlapping aerial images, we produced a digital surface model (DSM) at 0.03‐m resolution from which flow pathways were modelled using GIS and compared with 1‐m LiDAR and DSM produced by a global navigation satellite system (GNSS). MCUG had longer, tortuous pathways through the dense tussock network with a drainage density of 2.54 m m −2 . This was significantly greater than drainage density in the LPIG (1.82 m m −2 ). As a result of this study, we rescaled the Manning's n value for MCUG according to photogrammetrically‐derived roughness values. We suggest it should lie between 0.075 and 0.09. Our data shows that MCUG can play an important role in reducing overland flow impacts when compared to LPIG through lower connectivity which can delay run‐off to rivers.