Category: Climate and Hydrologic Processes

Among the many impacts of the COVID-19, the pandemic has led to improved air quality conditions in the countries under quarantine. Satellite-based maps highlight a remarkable reduction in aerosol and air pollution due to the shutdown of industries and very limited traffic in China and other Asian countries between late January and March 2020. Similarly, many areas across the United States have also experienced a large reduction in air pollution due to the lockdown in response to COVID-19. Meanwhile, large areas of the central United States, particularly within the Missouri River Basin, received less precipitation than normal during February-April 2020. Is it possible that the observed reduction in precipitation was driven by the reduced aerosols due to the coronavirus? If so, how much of these changes can be attributed to the pandemic and what does it mean in terms of discharge?

Our hypothesis is that the local aerosol reduction led to a detectable change in precipitation and discharge across the central United State and Iowa, and that these effects were either magnified or reduced depending on the magnitude of the long-range transport of particles. Therefore, the goal of this proposal is to evaluate how much of an impact this abrupt reduction in local and remote aerosols played during the past winter/spring in terms of precipitation and discharge, and to determine the physical mechanisms at play.

The research methodologies build on analytical tools and data sets with which the research team has extensive experience, and will be developed further to address the role of the reduction in aerosols due to COVID-19 in relation to the reduced precipitation and discharge across the central United States broadly, and Iowa in particular.

We will use the Weather Research and Forecasting (WRF) model coupled with Chemistry version 3.8.1 (WRF-Chem), and force it with the North American Regional Reanalysis (NARR) data and the near real-time Whole Atmosphere Community Climate Model (WACCM) outputs. We propose to design four experiments to isolate the relative contribution of the aerosols: Control (CTRL), Business-as-usual (BAU), NoTrans, and NoLocal experiments. In these runs, the circulation (e.g., zonal and meridional winds, geopotential height) is the same but they have different settings for transported and local aerosols. By comparing the four experiments, we can assess the relative roles of aerosols in forcing the observed changes in precipitation and discharge during February-April 2020. In addition to precipitation and discharge, the proposed experiments will produce outputs (e.g., temperature, humidity, ultraviolet radiation, ozone) which are important to diagnose the environmental conditions for the survival and spread of COVID-19.

The proposed research will enhance our knowledge of the role of local and remote aerosols on precipitation and discharge across the central United States, with a special focus on Iowa. Given the extreme reduction in aerosols due to the pandemic, our findings will have both short- and long-term impacts. In the short term, insights gained from this research can provide information in terms of preparation for the upcoming fall and winter from the perspective of water resources and emergency management. In the long term, our work will provide basic information on the potential impacts of different mitigation efforts aimed at reducing anthropogenic aerosols on precipitation across the central U.S.

The results and data from this project will be made available to federal and state agencies. Moreover, this information will be readily available to local stakeholders and users for their own use. The research team will leverage the tools and expertise provided by the Iowa Flood Center (IFC) to make the results of the proposed work relevant and immediately and directly available to agencies and to the general public. Moreover, the dissemination of the results will be facilitated by means of outreach activities through the IFC and the Iowa Water Center.

Sensor networks, built on the backs of the latest digital communication technologies, are increasingly being deployed in urban sewer networks and at regional scales to monitor flooding and water quality of rivers (Habibi et al. 2017; Mullapudi et al. 2017; Jones et al. 2018; Yildirim and Demir 2019). Concurrently, control technologies are being deployed alongside sensors which allow for water resources operators to actively manipulate these systems in places and in a manner that was previously inconceivable (Kerkez et al. 2016). Together, sensing and control deployments mean massively more complex systems to address persistent water resources challenges such as flooding and water quality. Recent research studies demonstrate the potential for coordinated and increasingly automated management and control approaches to improve performance considering both water quality and quantity objectives (Muschalla et al. 2014; Sadler et al. 2019; Sharior et al. 2019; Mullapudi et al. 2020; Sun et al. 2020; Troutman et al. 2020).

However, decision-making methodology based solely on underlying physical and technical characteristics ignore the social and political structures which overlay and interact with them. Considering these structures as part of a singular, sociotechnical whole exposes normative questions of “right” and “wrong,” or more profound questions of societal ethics and values. Take for example, if some flooding is an inevitable outcome within a catchment with dynamic control capabilities, how ought a controller act to consider the societal implications of such flooding? Or, if a control scheme consistently recommends distributing harm in poor neighborhoods and benefits in richer neighborhoods, ought its directives be followed? To address this gap in knowledge, we previously developed a framework to construct data-driven ethical preference models in relation to water resources issues, such as flooding, using a combination of voting-based practices and machine learning methods (Ewing and Demir, 2020). Ethical preference models captured group “wisdom” and demonstrate that the framework is a candidate for use in decision support toolchains to support water resources decisions.

In this study, we propose to explore a novel methodology to incorporate concepts of ethics and justice into decision support toolchains for water quantity and water quality objectives by building on the preliminary work from our research lab (Ewing and Demir, 2020). To do so we will utilize a modeling framework, the Python programming module pystorms, which allows hydrologic and hydraulic simulation of water conveyance networks with dynamic control of storage assets (Mullapudi and Troutman 2020). Our extension will allow dynamic operation of storage assets while considering social and geographic data – such as census data of social vulnerability, land use type, and landowner type (i.e. public or private) – and voting-based ethical preference models. Through this experimental setup we will investigate how different dynamic control strategies affect the distribution of benefits and harms across communities and landscapes.

The findings from this research will provide greater insight into how to manage our next generation sociotechnical systems such that they preempt injustices, inequities, and inefficiencies. The findings will also inform how novel decision support toolchains for dynamic control may integrate into our water resources management in both catastrophic and quotidian management scenarios.

This project aims to create a web-based serious game geared towards educating K-12 and college students, and public on flood prevention and mitigation strategies, such that they are more informed about the implications of future flooding events. A web-based interactive gaming environment will be designed and implemented that allows players to experiment with different flood mitigation strategies for a real-world location of their choice. As part of the gameplay, the user will be presented with a community under risk of flooding, and various mitigation and preparedness actions. The users will face challenges in decision-making and will evaluate trade-offs in terms of assignment of monetary resources with respect to societal gain. Once decisions are finalized, a realistic flood event will be generated and visualized so that the player can examine impacts on the community. In addition to visual inspection, the proposed game will allow interactive analysis of the economic damage and casualties. This immersive, repeatable, and engaging experience will allow K-12 students and the public to comprehend the consequences of individual measures, build a conceptual understanding of the needs and benefits of mitigation actions, and examine how floods may occur in their communities.