Sustaining natural levels of base flow is critical to maintaining ecological function as stream catchments are urbanized. Stream base flow responds variably to urbanization. Base flow or water tables rise in some locations, fall in others, or remain constant. This variable response is the result of the array of natural (e.g., physiographic setting and climate) and anthropogenic (e.g., urban development and infrastructure) factors that influence hydrology. Perhaps because of this complexity, few simple tools exist to assist managers to predict baseflow change in their local urban area. We address this management need by presenting a decision-support tool that can be used to predict the likelihood and direction of baseflow change based on the natural vulnerability of the landscape and aspects of urban development. When the tool indicates a likely increase or decrease, managers can use it for guidance toward strategies that can reduce or increase groundwater recharge, respectively. An equivocal result from application of the tool suggests the need for a detailed water balance. The tool is embedded in an adaptivemanagement framework that encourages managers to define their ecological objectives, assess the vulnerability of their ecological objectives to changes in water-table height, and monitor baseflow responses to urbanization. We tested our framework with 2 different case studies: Perth, Western Australia, Australia and Baltimore, Maryland, USA. Together, these studies show how predevelopment water-table height, climate, and geology together with aspects of urban infrastructure (e.g., stormwater practices, leaky pipes) interacted such that urbanization led to rising (Perth) and falling (Baltimore) base flow. Greater consideration of subsurface components of the water cycle will help to protect and restore the ecology of urban fresh waters.

Summary Environmental flows are a key restoration technique for conserving ecological function in flow‐degraded rivers. Species‐specific, flow–biota relationships are increasingly being used to determine environmental flow needs and manage their use; however, many of these relationships are poorly described. We evaluate relationships between environmental variables and spawning intensity for a fish assemblage from the Murray River, Australia, over a ten‐year period. We developed a hierarchical multispecies model that accounted for incomplete detection to compare spawning outcomes of native and non‐native species using realistic, alternative, water management scenarios. Temperature was an important predictor of spawning intensity for all seven species studied, while both concurrent and antecedent flow conditions were important for many species. Our water management scenario testing accounted for these relationships and indicated that increasing the magnitude of smaller floods following lower antecedent flow conditions, at water temperatures of 18–20°C, achieves the greatest spawning outcome for native fish. Synthesis and applications. Our results indicate that principally temperature, and flow as a secondary variable, influence the timing and strength of fish spawning. The synthesis of these spawning relationships predicts that managers will achieve the greatest spawning return per unit of environmental water when flows are applied on top of an existing flow pulse. This study highlights the importance of considering a range of abiotic factors and the use of modelling scenarios to improve environmental flow outcomes.

SUMMARY1. Relationships between river flow characteristics and fish community/population dynamics (i.e. flow-ecology relationships) underpin methods to determine and monitor environmental water allocations. Quantifying these relationships can be difficult, and consequently, most environmental flow strategies for fish conservation in Australian rivers are based on general flow-ecology relationships as opposed to statistical predictions. 2. Of those studies that have investigated relationships between flow and fish, most have not accounted for incomplete and variable detection of fish by the sampling methods, thus making the implicit assumption that sampling efficiency is invariant. This important assumption is rarely met, leading to inconsistent research findings and spurious results, and a reliance on generic flow-ecology principles for defining flow management strategies. 3. We illustrate how and when detection probability varies when sampling freshwater fish and the consequences to scientific inference about fish-flow relationships. Methods for accounting for imperfect detection of fish are identified and tools to increase the efficiency of experimental designs while reducing sampling cost are discussed. These tools include methods for borrowing information among experimental components and simulation techniques to optimise sampling designs. 4. We argue that, due to the very nature of sampling designs to quantify flow-ecology relationships (e.g. sampling at different flow magnitudes/regimes), the challenge of imperfect detectability is particularly relevant to environmental flow science. We encourage the broader adoption of methods that account for imperfect detection to improve inference about fish-flow relationships and increase the successful application of environmental flows for managing fish communities.