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Residential landscapes are essential to the sustainability of large areas of the United States. However, spatial and temporal variation across multiple domains complicates developing policies to balance these systems’ environmental, economic, and equity dimensions. We conducted multidisciplinary studies in the Baltimore, MD, USA, metropolitan area to identify locations (hotspots) or times (hot moments) with a disproportionate influence on nitrogen export, a widespread environmental concern. Results showed high variation in the inherent vulnerability/sensitivity of individual parcels to cause environmental damage and in the knowledge and practices of individual managers. To the extent that hotspots are the result of management choices by homeowners, there are straightforward approaches to improve outcomes, e.g. fertilizer restrictions and incentives to reduce fertilizer use. If, however, hotspots arise from the configuration and inherent characteristics of parcels and neighborhoods, efforts to improve outcomes may involve more intensive and complex interventions, such as conversion to alternative ecosystem types.

 

In this study, we investigate how seasonal streamflow and soil moisture patterns have responded to variability in vegetation phenology in humid, temperate forested watersheds without significant seasonal snowmelt over the last four decades. We characterize spring streamflow peaks using 50th percentiles of cumulative daily precipitation, streamflow, and soil moisture measurements, and investigate interactions with remotely sensed, greenup anomalies. After removing a dominant precipitation control, 1‐day earlier greenup is usually associated with about 1‐day early spring flow peak at four low‐elevation deciduous catchments using both sequential and multiple linear regressions. This indicates that the strong dependency of seasonal flow regimes on precipitation is mediated by vegetation seasonality, especially by greenup variability. In contrast, we find less significant correlations of the greenup anomalies on flow percentiles from two paired evergreen and two high‐elevation deciduous catchments. At a plot scale, similar correlations were found only at an upslope topographic position, where precipitation also showed tighter coupling with moisture seasonal patterns than downslope. Our study suggests that rainfall‐runoff and rainfall‐soil moisture relations have been closely mediated by vegetation seasonality in deciduous forests, especially by greenup anomalies, but patterned along topoclimate and hillslope gradients. This study emphasizes that it is important to understand phenological responses to ongoing climate change (in both long‐term and interannual variability) for prediction of seasonal flow regimes especially in deciduous forested catchments.

 

Abstract. Spatially distributed hydrological models are commonly employed to optimize the locations of engineering control measures across a watershed. Yet, parameter screening exercises that aim to reduce the dimensionality of the calibration search space are typically completed only for gauged locations, like the watershed outlet, and use screening metrics that are relevant to calibration instead of explicitly describing the engineering decision objectives. Identifying parameters that describe physical processes in ungauged locations that affect decision objectives should lead to a better understanding of control measure effectiveness. This paper provides guidance on evaluating model parameter uncertainty at the spatial scales and flow magnitudes of interest for such decision-making problems. We use global sensitivity analysis to screen parameters for model calibration, and to subsequently evaluate the appropriateness of using multipliers to adjust the values of spatially distributed parameters to further reduce dimensionality. We evaluate six sensitivity metrics, four of which align with decision objectives and two of which consider model residual error that would be considered in spatial optimizations of engineering designs. We compare the resulting parameter selection for the basin outlet and each hillslope. We also compare basin outlet results for four calibration-relevant metrics. These methods were applied to a RHESSys ecohydrological model of an exurban forested watershed near Baltimore, MD, USA. Results show that (1) the set of parameters selected by calibration-relevant metrics does not include parameters that control decision-relevant high and low streamflows, (2) evaluating sensitivity metrics at the basin outlet misses many parameters that control streamflows in hillslopes, and (3) for some multipliers, calibrating all parameters in the set being adjusted may be preferable to using the multiplier if parameter sensitivities are significantly different, while for others, calibrating a subset of the parameters may be preferable if they are not all influential. Thus, we recommend that parameter screening exercises use decision-relevant metrics that are evaluated at the spatial scales appropriate to decision making. While including more parameters in calibration will exacerbate equifinality, the resulting parametric uncertainty should be important to consider in discovering control measures that are robust to it. 

Urban water system managers face a set of interrelated water security challenges as they pursue the goals of sustainable sources of water, mitigating flood hazards, and improving water quality. These challenges are often subject to change (and hence highly uncertain) due to the coupled effects of hydro-climatic variability, socio-economic trends, and regulatory reforms. To meet these intersecting goals, we present a mechanistic framework with illustrative examples that evaluates an urban water system’s resilience under future uncertainty. By employing principles from engineering design, ecosystem science, and social equity studies, our resilient urban water systems (ReUWS) framework explores the potential of effectively combining green and gray infrastructure (GGI) in an urban watershed while prioritizing stakeholder and community engagement throughout the lifecycle of water system projects. A nested set of hydrology, ecosystem, and hydraulic models are developed with data flow among them defining the boundary and initial conditions for each other. An example is shown with the Baltimore water system on an approach to evaluate the effects of GGI hybrids on major water security metrics. The corresponding engineering designs, ecosystem service potentials, and measures of equitable access to services are also analyzed using the framework. The results evaluate performance of the existing systems under future conditions and also compare different GGI-based strategies for improving resilience in urban water systems. The findings of the study help to evaluate the potential for using GGI strategies to cope with changing climate extremes and other environmental factors as well as social change. Trade-offs derived from the case studies also can be used to adjust local/regional policies and regulations.