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1. Open storm: a complete framework for sensing and control of urban watersheds

   https://doi.org/10.1039/C7EW00374A  

   Bartos, Matthew; Wong, Brandon; Kerkez, Branko (January 2018, Environmental Science: Water Research & Technology)

   Leveraging recent advances in technologies surrounding the Internet of Things , “smart” water systems are poised to transform water resources management by enabling ubiquitous real-time sensing and control. Recent applications have demonstrated the potential to improve flood forecasting, enhance rainwater harvesting, and prevent combined sewer overflows. However, adoption of smart water systems has been hindered by a limited number of proven case studies, along with a lack of guidance on how smart water systems should be built. To this end, we review existing solutions, and introduce open storm —an open-source, end-to-end platform for real-time monitoring and control of watersheds. Open storm includes (i) a robust hardware stack for distributed sensing and control in harsh environments (ii) a cloud services platform that enables system-level supervision and coordination of water assets, and (iii) a comprehensive, web-based “how-to” guide, available on open-storm.org, that empowers newcomers to develop and deploy their own smart water networks. We illustrate the capabilities of the open storm platform through two ongoing deployments: (i) a high-resolution flash-flood monitoring network that detects and communicates flood hazards at the level of individual roadways and (ii) a real-time stormwater control network that actively modulates discharges from stormwater facilities to improve water quality and reduce stream erosion. Through these case studies, we demonstrate the real-world potential for smart water systems to enable sustainable management of water resources. 

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2. Propagation of future climate conditions into hydrologic response from coastal southern California watersheds

   https://doi.org/10.1007/s10584-019-02371-3  

   Feng, Dongmei; Beighley, Edward; Raoufi, Roozbeh; Melack, John; Zhao, Yuanhao; Iacobellis, Sam; Cayan, Daniel (March 2019, Climatic Change)
3. Comparing catchment hydrologic response to a regional storm using specific conductivity sensors

   https://doi.org/10.1002/hyp.11091  

   Inserillo, E. Ashley; Green, Mark B.; Shanley, James B.; Boyer, Joseph N. (February 2017, Hydrological Processes)
4. Flash Flood–Producing Storm Properties in a Small Urban Watershed

   https://doi.org/10.1175/JHM-D-16-0070.1  

   Smith, Brianne K.; Smith, James; Baeck, Mary Lynn (October 2016, Journal of Hydrometeorology)

   The structure and evolution of flash flood–producing storms over a small urban watershed in the mid-Atlantic United States with a prototypical flash flood response is examined. Lagrangian storm properties are investigated through analyses of the 32 storms that produced the largest peak discharges in Moores Run between January 2000 and May 2014. The Thunderstorm Identification, Tracking, Analysis, and Nowcasting (TITAN) algorithm is used to track storm characteristics over their life cycle with a focus on storm size, movement, intensity, and location. First, the 13 June 2003 and 1 June 2006 storms, which produced the two largest peak discharges for the study period, are analyzed. Heavy rainfall for the 13 June 2003 and 1 June 2006 storms were caused by a collapsing thunderstorm cell and a slow-moving, low-echo centroid storm. Analyses of the 32 storms show that collapsing storm cells play an important role in peak rainfall rate production and flash flooding. Storm motion is predominantly southwest-to-northeast, and approximately half of the storms exhibited some linear organization. Mean storm total rainfall for the 32 storms displayed an asymmetric distribution around Moores Run, with sharply decreasing gradients southwest of the watershed (upwind and into the city) and increased rainfall to the northeast (downwind and away from the city). Results indicate urban modification of rainfall in flash flood–producing storms. There was no evidence that the storms split around Baltimore. Flood-producing rainfall was highly concentrated in time; on average, approximately 21% of the storm total rainfall fell within 15 min. 

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5. Institutional Dynamics Impact the Response of Urban Socio‐Hydrologic Systems to Supply Challenges

   https://doi.org/10.1029/2023WR035565  

   Wiechman, Adam; Alonso_Vicario, Sara; Anderies, John_M; Garcia, Margaret; Azizi, Koorosh; Hornberger, George (February 2024, Water Resources Research)

   Abstract Designing urban water systems to respond to the accelerating and unpredictable changes of the Anthropocene will require changes not only to built infrastructure and operating rules, but also to the governance arrangements responsible for investing in them. Yet, inclusion of thispolitical‐economic feedbackin dynamic models of infrastructure systems and socio‐hydrology has lagged behindoperationalfeedback concerns. We address this gap through a dynamical systems application of the Coupled Infrastructure Systems (CIS) Framework, which provides the conceptual building blocks for analyzing social‐ecological systems through various classes of infrastructure and the flows of material and information among them. In the model, political‐economic feedback involves three decisions—infrastructure investment, rate‐setting, and short‐term demand curtailment—and each decision is constrained by institutional friction, the aggregation of decision and transaction costs associated with taking action. We apply the model to three cities in the Phoenix Metropolitan Area to compare how institutional friction interacts with a city's water resource portfolio and financial position to determine its sensitivity, or the degree to which its performance (e.g., providing sufficient supply to meet demand) changes given reductions in Colorado River water availability. We find that the slowing effect of institutional friction on investment and rate‐setting decisions can increase the sensitivity of a city's supply, but it can also promote objectives that compete with over‐response (e.g., rate burden). The effect is dependent on the initial operating capacity of the CIS and flexibility within the institutions, highlighting the need to consider political‐economic and operational feedback together when evaluating infrastructure systems. 

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