From site-focused intervention towards landscape-scale surface water management using Synthetic Stream Networks and Rapid Scenario Screening release_lmacisqybbbjbpy7gtda3qp6vu

Abstract

<jats:title>Abstract</jats:title> This research addresses the need to transform success in technical understanding and practical implementation of surface water management (SWM) interventions at a site-scale towards integrated landscape-scale management. We achieve this through targeting the informative preliminary stages of strategic design, where broad, early and effective exploration of opportunities can enhance and direct a regional SWM perspective. We present a new method, 'Synthetic Stream Networks' (SSN), capable of meeting these requirements by taking advantage of easily accessible data, likely to be available during regional screening. We find that results from the SSN are validated by existing, 'downstream' focused data (90% of the river network is within 30 m of an associated SSN flow path), with the added advantage of extending understanding of surface water exceedance flow paths and watersheds into the upper catchment, thus establishing a foundational and physically based sub-catchment management unit exploring surface water connectivity at a catchment and landscape scale. We also demonstrate collaborative advantages of twinning the new SSN method with 'Rapid Scenario Screening' (RSS) to develop a novel approach for identifying, exploring and evaluating SWM interventions. Overall, we find that this approach addresses challenges of integrating understanding from sub-catchment, catchment and landscape perspectives within surface water management.
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