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Urban drainage systems face increased floods and combined sewer overflows due to climate change and population growth. To manage these hazards, cities are seeking stormwater digital twins that integrate sensor data with hydraulic models for real-time response. However, these efforts are complicated by unreliable sensor data, imperfect hydrologic models, and inaccurate rainfall forecasts. To address these issues, we introduce a stormwater digital twin system that uses online data assimilation to estimate stormwater depths and discharges under sensor and model uncertainty. We first derive a novel state estimation scheme based on Extended Kalman Filtering that fuses sensor data into a hydraulic model while simultaneously detecting and removing faulty measurements. The system’s accuracy is evaluated through a long-term deployment in Austin’s flood-prone Waller Creek watershed. The digital twin model demonstrates enhanced accuracy in estimating stormwater depths at ungauged locations and delivers more accurate near-term forecasts. Moreover, it effectively identifies and removes sensor faults from streaming data, achieving a Receiver Operating Characteristic Area Under the Curve (ROC AUC) of over 0.99 and significantly reducing the potential for false flood alarms. This study provides a complete software implementation, offering water managers a reliable framework for real-time monitoring, rapid flood response, predictive maintenance, and active control of sewer systems. 

Companies and their executives are concluding that to accomplish their complex tasks and all-encompassing missions and goals, they must step outside the traditional realms of teamwork and partnership and engage in cross-cultural and multinational alliances. One of the principal areas affecting teamwork today, especially in diverse workplaces, is the variety of cultural value orientations that the members relate to. To better prepare students for joining global enterprises, it is necessary to understand their cultural orientations and how those may influence their teamwork interactions. This study used a mixed methods design to characterize computer and information technology undergraduate students’ cultural orientations and their cultural awareness in the context of teamwork experiences. The data for the study was collected in the form of a reflection assignment that was implemented during the first week of classes as a way to promote students’ cultural awareness and how that may play out in their teamwork interactions. The reflection assignment had two parts: (i) a survey and (ii) reflection questions. The study used descriptive statistics and t-tests to analyze the survey (quantitative data), and thematic analysis was conducted to analyze the reflection questions (qualitative data). Our analysis of the quantitative data revealed that students identified the following core values they are Individualism, Equality, Monochronic, Meritocracy, Informality, Personal Efficacy, and Directness, and these values resonated with most of the students in class. Corresponding qualitative themes that emerged regarding students’ beliefs of how those values may play out in their teamwork experience were (a) Treating everyone equally and understanding others, (b) Increasing temporal Awareness, (c) Enacting effective communication, (d) Monitoring the progress of team members and (e) Establishing rules and boundaries.