Development of Student-centered Modules to Support Active Learning in Hydrology

Transcription

1 Paper ID #17397 Development of Student-centered Modules to Support Active Learning in Hydrology Dr. Emad Habib, University of Louisiana, Lafayette Dr. Emad Habib is a Professor of Civil Engineering at the University of Louisiana at Lafayette. His research interests are in Hydrology, Water Resources, Rainfall Remote Sensing, Water Management, Coastal Hydrology, and Advances in Hydrology Education Research Prof. David G Tarboton, Utah State University David Tarboton is a professor of Civil and Environmental Engineering, Utah Water Research Laboratory, Utah State University. He received his Sc.D. and M.S. in Civil Engineering (Water Resources and Hydrology) from the Massachusetts Institute of Technology and his B.Sc Eng in Civil Engineering from the University of Natal in South Africa. His research and teaching are in the area of surface water hydrology. His research focuses on advancing the capability for hydrologic prediction by developing models that take advantage of new information and process understanding enabled by new technology. He has developed a number of models and software packages including the TauDEM hydrologic terrain analysis and channel network extraction package that has been implemented in parallel, and a snowmelt model. He is lead on the National Science Foundation HydroShare project to expand the data sharing capability of Hydrologic Information Systems to additional data types and models and to include social interaction and collaboration functionality. He teaches Hydrology and Geographic Information Systems in Water Resources. Mr. Matthew Wayne Deshotel, University of Louisiana at Lafayette Mr. David J Farnham, Columbia University c American Society for Engineering Education, 2016

2 Introduction Development of Student-Centered Modules to Support Active Learning in Hydrology Traditional approaches to undergraduate hydrology and water resource education are textbook based, adopt unit processes and rely on idealized examples of specific applications, rather than examining the contextual relations in the processes and the dynamics connecting climate and ecosystems. The overarching goal of this study is to address the needed paradigm shift in undergraduate education of engineering hydrology and water resources to reflect parallel advances in hydrologic research and technology, mainly in the areas of new observational settings, 1,2 data and modeling resources, 3,4,5 professional practice, and web-based technologies 6,7. This paper presents efforts to develop a set of learning modules that are case-based, data and simulation driven, and delivered via a web user interface. The modules are based on real-world case studies from three regional hydrologic ecosystems: Coastal Louisiana, Florida Everglades, and Utah Rocky Mountains. Each ecosystem provides unique, yet transferrable hydrologic concepts, problems and scenarios that can be used in many water resource and hydrology curricula. Examples of such learning opportunities that are transferrable to other settings include: regional-scale budget analysis, hydrologic effects of human and natural changes, flashflood protection, climate-hydrology tele-connections, and water resource management scenarios. The technical design and contents of the modules aim to support students ability for transforming their learning outcomes and skills to hydrologic systems other than those used by the specific activity. Learning Module: Climate Teleconnections The goal of this learning module is to equip students with a basic understanding of climate teleconnections 6 and the implications for enhancing the skills of precipitation forecasting and thus informing water resources engineering design and analysis. The module focuses on climate variability and the influence of remote oceanic and atmospheric conditions on regional precipitation and temperature. The module promotes students understanding of how local water balance and extreme hydrologic events may result from global-scale climate patterns. The module is arranged in three main sections: (1) Climate variability and teleconnections; (2) Climate Modeling and Forecasting; and (3) Statistical Tools for Precipitation Predictive Models. Students are first introduced to the four main oscillations (the El-Niño Southern Oscillation, ENSO; the Pacific Decadal Oscillation, PDO; the Atlantic Multidecadal Oscillation, AMO; and the Madden-Julian Oscillation, MJO) that influence climate in various locations and operate on various time-scales. Some atmospheric science concepts are introduced while discussing the dynamics of the El-Niño Southern Oscillation. The second section covers the types of models that are used to characterize the relationship between ocean and atmosphere conditions and circulations, and regional precipitation conditions. The basics of both dynamical and statistical climate modeling techniques are introduced. The third section in the module provides students to the process of building their own statistical model for the prediction of regional or local precipitation by leveraging the teleconnection relationships presented earlier in the module.

3 Winter Figure 1: Seasonal correlation maps of precipitation and NINO3.4 index for the US produced by students based on data from the KNMI Summer climate explorer ( The module includes a set of quantitative learning activities ranging from data analysis, model assessment and comparison, statistical tests, and developing linear regression models. For example, to predict local precipitation students are guided through a process of identifying candidate predictors, selecting the best subset of predictors, and fitting a linear regression model by least squares. In another exercise, students perform an exploratory analysis of sea surface temperature (SST) and precipitation anomaly records in a region of their selection and use lagged correlations to establish relationships between prior month s SST record with the current month s precipitation record. Figure 2: Example of precipitation analysis performed by the students as part of the climate teleconnections module. Data are based on actual precipitation records in Sacramento, CA, from 1850 to 1996, overlaid with 1-year, 5-year, and 30-year moving averages.

4 Learning Module: Flash Flood Protection The intent of this module is to bring together different concepts and techniques typically covered in hydrology courses using a real-world case study with an actual hydrologic problem on flood protection project at the mouth of Dry Canyon located near Logan, Utah. Flash flooding is a hazard in many parts of the world. For example, in the Rocky Mountains in the US, flash flooding is common in mountain canyons, desert washes, and other such topographic areas where runoff from rainfall quickly accumulates in gullies or ravines. A flash flood is a sudden and rapid rise in stream water depth resulting from heavy, localized rainfall. With a growing population, the development of neighborhoods in areas susceptible to flash floods has become more common. Hydrologists are frequently required to design flood protection infrastructure to protect people and property from the impacts of flash flooding. Figure 3. An aerial view of the existing detention basin at the mouth of the Logan Dry Canyon from Google Maps. In this module, students will learn about the topics in hydrology needed to design a detention basin to protect an area of urban development from flooding. The module is organized into four main sections: (1) Watershed Properties; (2) Precipitation and Surface Water Input; (3) Runoff Generation; and (4) Design of a flood protection system. In the first section, students learn the steps needed to determine the physical characteristics of the watershed and delineate the boundaries of the watershed using the USGS StreamStats web tool. In the second section, students learn how precipitation and snowpack are measured, how to estimate area-average precipitation over the watershed, and how to analyze and quantify the variability of precipitation.

5 Figure 4: Topographic map of Dry Canyon showing delineated watershed (blue) and water point trace (red) lines (left); elevation drop of water point trace line of Dry Canyon (right). Figure 5: Depth-Duration-Frequency (DDF) curves calculated using historical data from a rain gage in the Dry Canyon watershed. The module includes several quantitative activities and mini-projects such as: calculation of annual maximums and exceedance probabilities; developing Depth-Duration-Frequency (DDF) curves using historical rain gauge data; and designing an event storm hyetograph using Intensity- Duration-Frequency (IDF)/ Depth-Duration-Frequency (DDF) curves and methods such as the alternating block method. The third section deals with methods for quantifying how much runoff is generated from surface water input comprised of rain or snowmelt. Students are then guided into another activity where they use this information within the Hydrologic Engineering Center s Hydrologic Modeling System (HEC-HMS) to construct a storm hydrograph. The final section of the module covers the design of the detention basin where students use HEC-HMS to determine the required size of the detention basin at Dry Canyon based on various outlet sizes. Learning Modules: Coastal Restoration From an educational perspective, large-scale coastal ecosystems, such as those in south Louisiana, present unprecedented opportunities for enhancing students learning about fundamental hydrological processes and linkage between hydrologic engineering and other scientific disciplines (e.g. geomorphology, ecology, sociology). The Louisiana coastal zone is a unique system as it captures the transition from inland to coastal/wetland hydrology and actively

6 serves several important ecological and economical functions. Being a multi-use ecosystem, the region faces challenges on how to reach a balanced and sustainable strategy among its various often-conflicting functions. The Coastal Louisiana set of learning modules are based on a suite of modeling tools 7,8 that were developed for the purposes of testing and screening hundreds of restoration strategies in the region 9. The modules are based on the overall theme of how and whether engineered restoration measures (e.g. marsh creation, shoreline nourishment, water control structures) can actually help in preserving ecosystems. By examining a coupled naturalhuman ecosystem such as that in south Louisiana, the module exposes students to the unintended consequences of human restoration activities and their negative impacts on the ecosystem (e.g., undesirable flooding of nearby communities, or over-freshening of estuarine systems). Figure 6: Map of Coastal Louisiana showing the domain and boundaries of computational models developed by the investigators. The Coastal Louisiana modules are composed of four main case studies: (1) Water budget analysis for regional-scale coastal ecosystems; (2) Assessment of design alternatives for the Calcasieu Ship Channel salinity control project; (3) Tradeoff analysis in the use of oyster reefs as a restoration strategy in Vermilion Bay; and (4) Impact of hydrologic alterations on coastal vegetation types. In each of these modules, students are presented with the restoration problem at hand, and asked to perform an inquiry-drive analysis to assess the feasibility, potential benefits, and undesirable impacts of a proposed restoration strategy on the ecosystem. Students conduct analyses using observational datasets available from web-based platforms such as the United States Geological Survey, the US Army Corps of Engineers, and the Louisiana Coastwide Reference Monitoring System. Students also use outputs from model simulations to analyze preand post-project hydrologic conditions (e.g., water level and stage) and the impact on the ecosystem services (e.g., habitat suitability indices). The analysis is typically done at daily time step, and cover simulation periods that span 20 years to capture seasonal as well as intra-annual variability.

7 Dredging of materials to form terraces. Terraces protect marshes from wave erosive forces Terraces providing additional areas for vegetation and animal life. Figure 7: Example coastal restoration strategies examined by students as part of the coastal Louisiana modules. Figure 8: Students examine the effect of different project structural alternatives (Alt1, Alt2, Alt3 and Alt4) to reduce salinity levels in the estuarine system of Calcasieu Lake in south Louisiana.

8 Web-Based Design In order to enable wide dissemination, the modules were designed and deployed using a webbased interface 10. A client-server architecture is used where geospatial data and educational content are presented to students in a web browser. The design uses open source web-based technologies to enable future development and adaptation. For example, the modules are designed using MySQL, an open source relational database management system that runs as a server, to store and serve hydrological simulations and GIS data in relational database. Each module has a mapping interface designed using OpenLayers to render hydrologic geospatial data on spatial model of the Earth. Hydrologic geospatial data are loaded as KML layers on the background map. Figure 9: Web-based interface for one of the modules showing the table contents on the left with different sections and learning activities, along with a mapping interface where students can navigate the hydrologic basin and extract relevant datasets and model outputs. Conclusions The study presented the development of a set of data and modeling-based modules that support active learning in the field of hydrology and water resources. The modules are based on actual problems and case studies that are situated in different hydrologic settings, ranging from arid environments to humid coastal regions. While the modules are developed for case studies in specific hydrologic sites, the technical content and the problems presented to the students target learning outcomes that are applicable to many other settings (e.g., water budget analysis, flashflood protection, climate-hydrology feedback and analysis of water resource management scenarios). The modules are structured in such a way that students are presented with a specific hydrologic problem (e.g., flood protection, salinity intrusion control) and guided through a set of quantitative, inquiry-based activities using observational datasets and model outputs. In some cases, students develop their own models, statistical and physically-based, to examine the impact

9 of the proposed hydrologic solution. The modules present the case studies within the context of both human needs, as well as natural stresses (e.g., climate variability). The modules are served through the web using a client-server architecture. The design is implemented using open-source technologies and community-based tools to facilitate dissemination and future integration of additional case studies. Ongoing classroom implementation and evaluation resulted in several iterations of design and indicated the importance of building user-support attributes into the modules. Key attributes that were identified and incorporated into the modules include: intermediate feedback to students to facilitate successful progress; use of screencasts to illustrate complex operations; rubrics for students; instructor support in terms of key solutions and supporting material; and templates for data analysis and advances statistical/modeling tasks. Acknowledgment The authors acknowledge the support provided to this study by the National Science Foundation's Transforming Undergraduate Education in Science, Technology, Engineering and Mathematics (TUES) program under Collaborative Award No (Type II). Bibliography 1. Tarboton, D. G., J. S. Horsburgh, D. R. Maidment, T. Whiteaker, I. Zaslavsky, M. Piasecki, J. Goodall, D. Valentine and T. Whitenack, (2009), "Development of a Community Hydrologic Information System," 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation, ed. R. S. Anderssen, R. D. Braddock and L. T. H. Newham, Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, July 2009, p , 2. Tarboton, D. G., D. R. Maidment, I. Zaslavsky,, D. P. Ames, J. Goodall, and J. S. Horsburgh (2010), CUAHSI Hydrologic Information System 2010 Status Report, Consortium of Universities for the Advancement of Hydrologic Science, Inc, 34 p, StatusReport.pdf. [PDF; 1.27MB; 34 pages] 3. Gupta, V. K. (WEB Chair), 2001: Hydrology (summary of the Water, Earth, and Biota initiative as a 2000 highlight for Geosciences), Geotimes, 46(7), Hooper, R., and E. Foufoula-Georgiou (2008), Advancing the Theory and Practice of Hydrologic Science, Eos Trans. AGU, 89(39), doi: /2008eo CUAHSI (2010). Water in a Dynamic Planet: A Five-year Strategic Plan for Water Science ( 6. Shaw, S. B., and M. T. Walter (2012), Using comparative analysis to teach about the nature of nonstationarity in future flood predictions, Hydrol. Earth Syst. Sci., 16(5), , doi: /hess Meselhe, E., McCorquodale, J.A., Shelden, J., Dortch, M., Brown, T.S., Elkan, P., Rodrigue, M.D., Schindler, J.K., and Wang, Z. (2013) "Ecohydrology Component of Louisiana's 2012 Coastal Master Plan: Mass-Balance Compartment Model," Journal of Coastal Research, Special Issue 67, August 2013, Pages Habib, E. and Reed, D. (2013) "Parametric Uncertainty Analysis of Predictive Models in Louisiana's 2012 Coastal Master Plan," Journal of Coastal Research: Special Issue 67, August 2013, Pages Steyer, G.D., Sasser, C.E., Visser, J.M., Swensen, E.M., Nyman, J.A., and Raynie, R.C., 2003, A proposed coast-wide reference monitoring system for evaluating wetland restoration trajectories in Louisiana: Environmental Monitoring and Assessment, v. 81, p Zia, L.L. Web-enabled Learning Environments, Invention and Impact: Building Excellence in Undergraduate Science, Technology, Engineering and Mathematics (STEM) Education, April 2004, Crystal City, Va.,