Submitted as: model description paper 23 Nov 2020

Submitted as: model description paper | 23 Nov 2020

Review status: this preprint was under review for the journal GMD. A revision for further review has not been submitted.

LUCI-EntEx v1.0: A GIS-based algorithm to determine stream entry and exit points at boundaries of any given shape

Bethanna Jackson1, Rubianca Benavidez1, Keith Miller1,a, and Deborah Maxwell1,b Bethanna Jackson et al.
  • 1School of Geography, Environment and Earth Sciences, Victoria University of Wellington, Wellington 6022, New Zealand
  • anow at: Kāpiti Coast District Council, Private Bag 60601, Paraparaumu 5254, New Zealand
  • bnow at: WSP, Majestic Centre, 100 Willis Street, Wellington, New Zealand

Abstract. Increasing attention is turning to moderating the impact of human activity on the environment, both to preserve the intrinsic value of ecosystems and species for their own sake, and to protect the benefits we derive from nature for future generations. Internationally, various regulations and policies are in place or in development to improve our stewardship of the environment and develop more sustainable and resilient management practices. However, policies formulated at national or regional scales are not always suited to enacting targeted and cost-effective approaches at the local scale due to geoclimatic, topographical, or management constraints. The direct monitoring of the local and upstream impacts of every management unit to determine their net impact is a costly practice, thus emphasising the need for modelling approaches to complement limited on-ground measurements. This paper describes and demonstrates tools (LUCI-EntEx v1.0) that automatically identify the fluvial and terrestrial flow of water in and out of a study area, such as a river that enters a farm that is impacted by upstream management, or terrestrial flow coming from neighbouring property. By identifying the stream entry/exit points, the net impact of land management within the study area can be more easily quantified based on the contribution of neighbouring and upstream areas, aiding in the decision-making process. This algorithm also facilitates the identification of inconsistencies in data such as differences between the legal/official catchment boundaries and the hydrological boundaries determined by the representation of terrain and river networks. If such inconsistencies are not resolved, they can cause further error propagation in later stages of the modelling process. Four case studies of New Zealand management units – two at the farm scale and two at the catchment scale – demonstrate the algorithm's utility in determining fluvial and terrestrial entry/exit points and highlighting potential data inconsistencies. The farm case studies also use the Land Utilisation and Capability Indicator (LUCI) framework to demonstrate how this algorithm can be embedded in other models for further value: in this case, we show its potential to improve predictions and enhance management of nutrients and sediment.

Bethanna Jackson et al.

Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Bethanna Jackson et al.

Bethanna Jackson et al.


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Short summary
There is an increasing will to preserve nature for its own sake and to protect its benefits for future generations. Various policies encourage more sustainable land management practices to protect rivers and lakes. Separating out broad scale from local impacts is difficult, but necessary for informed land management outcomes. We present tools automatically identifying flows of water, sediment and chemicals in and out of farms, forestry blocks, etc to enable smarter future management.