Christopher J. Duffy - US grants

Present-day environmental fluid flow problems are routinely concerned with making predictions over large space and time scales in systems with sparse field data. The classical approach identifies characteristic length and time scales as a means of resolving the basic forces or fluxes driving fluid circulation. In a study of the hydrology of closed basins, Duffy and Al-Hassan (1988) applied the concept of scale invariant topography to construct an empirical topographic distribution for the range bordering the Pilot Valley Playa in western Utah. Regional correlation of mean precipitation with altitude was used to construct scaled inputs for modeling mountain-front recharge. At the playa or ephemeral lake, high evaporation rates were observed to produce concentrated brines in the shallow groundwater, resulting in unstable stratification and the potential for free convection. These observations guided numerical experiments conducted over a range of closed -basin geometries, and led to the development of a force or flux balance for subsurface circulation driven by mountain precipitation and playa-lake evaporation. The results suggest that the playa margin becomes a critical hyhdrologic zone where upwelling groundwaters from mountain-front recharge (forced convection) and brine recirculation from the central playa (free convection) converge, producing fresh and/or brackish springs. The premise of this work is that the position of the freshwater-saltwater interface represents a balance of hydro-climatic forces in the basin. Using characteristic lengths and velocities of the closed basin, the Rayleigh number for salinity was shown to be linearly related to a dimensionless group representing the steady-state position of the interface. The proposed research will attempt to extend previous numerical experiments to include complexities of space and time variability, namely: (1) the dynamic response of subsurface convection resulting from transient fluctuations in mountain recharge and playa evaporation; (2) the implications of deterministic and stochastic heterogeneity to the estimation of effective basin parameters; (3) regional flow from multiple- cascading basins of varying base level; (4) the role of surficial hydrologic processes (runoff); and (5) the significance of unsaturated flow and the atmosphere-land surface boundary condition.

9418674 Duffy This research will test the hypothesis that the rainfall-runoff process can be represented as a low-dimensional dynamical system, forced by topographic, soil, geologic and climatic variability. By "low-dimensional " we mean the minimum number of state variables required to approximate the processes as a system of nonlinear ordinary differential equations. We examine the case where rainfall-runoff is controlled by porous soils and shallow groundwater circulation, and where the ability of the catchment to store water and yield runoff depends on the nature of the storage-flux relationships of the system. The role of evapotranspiration as a parametic function of soil-moisture storage will also be examined. The "low-dimensional" model will serve as a physically-based alternative to the nonlinear partial differential equations (Richard's equation) representing the local processes. In constructing the dynamical model, the essential problem is to separate or distinguish among spatial and temporal components of watershed dynamics, such that the important mechanics of the processes involved are elucidated, without loss of critical nonlinear structure. The research has the following elements: (1) Comprehensive numerical experiments based on finite element solutions to the partial differential equations for saturated-unsaturated flow will be performed To establish terrain-integrated constitutive relations (e.g. storage-flux relations). the proposed research will build on a series of steady-state numerical experiments (Lee, 1993; Duffy, 1994) for two dimensional hillslope geometry with uniform soil properties. This previous work found that recharge to the water table and subsurface flow to the stream were nonlinear functions of at least two state variables: the integrated soil moisture and integrated saturated storage. The present objective is to extend these experiments to the case of fully three dimensional and time varying flow, and test the role of soil stratification and variability on nonlinear storage-flux relations and runoff response. (2) Develop and test procedures for scaling and spatial integration of the state variables and fluxes for the Shale Hills watershed, 8 hectare, forested, catchment in central PA (J. Lynch et al, 1976). Shale Hills was the site of a unique experiment in the 1970's to evaluate the effects of antecedent soil moisture on stormflow volume and timing. Rainfall was artificially applied for 8 events with initial moisture ranging from dry to very wet. a comprehensive accounting of soil moisture and saturated storage at multiple depths was made over the entire watershed. Although if may seem to be a straight forward problem, spatial integration of scattered field observations requires an appropriate weighting function. Duffy (1994) has proposed weighting function derived from the hypsometric distribution, and a local rescaling of hillslope trajectories for each hillslope or zero-order basin. This scaling and averaging method will be carried out for the Shale Hills data base. Field-estimated storage-flux relations will be compared with the numerical experiments in (1). (3) An independent method known as proper orthogonal decomposition (POD), allows the essential spatial structure of the dynamics to be reconstructed directly from random field data or from the governing pde's. The method is widely applied to detecting coherent structures in hydrodynamics turbulence (Lumley, 1967), the evolution of climatic fields (North et al, 1982), and nonlinear vibration (Cusumano, and Bai, 1993, Cusumano et al, 1993, Lin and Cusumano, 1993, Cusumano et al, 1994). The POD method will be applied to the field data of the Shale Hills experiment and the Richard's equation to provide a measure of the dimensionality, or number of state variables required to model the system.

9805035
Duffy

This research proposes to investigate historical river discharge and dissolved solids records from the unique landform of the Colorado River Basin (CRB). The purpose of study is to develop a detection and modeling strategy for large-scale basin response from low-frequency climate forcing (interannual and decadal time scales) and secular trends from natural and anthropogenic origin. The characteristic terrain of the CRB, represented by the Colorado plateau in the upper basin and the Basin and Range physiography in the lower basin, serves to define the natural space and time scales of fluid and solute storage across the region; while landuse practices of irrigation and reservoir operation modify the natural and hydrochemical "signal). An important question to be addressed is "what is the minimum state-space dimension of dissolved solids-discharge as a function of landuse, landform and hydrogeologic conditions, and how do they relate to long term climate forcing. The data base is: 40-60 years of monthly average streamflow and stream chemistry for 20 stations distributed from the upper Green and Colorado rivers to the Gulf of California; monthly precipitation-temperature records across the basin and adjacent plateaus and ranges; groundwater levels in irrigated and nonirrigated regions as well as digital terrain and landuse data.
Two methods for extracting space-time signal from noisy hydrochemical data will be used: principal component analysis for spatial modal analysis and, singular spectrum analysis for detection of temporal oscillations. Our recent research published in Water Resources Research (Duffy, 1996; Duffy and Cusumano, 1998; Shun and Duffy, 1998) has involved formulation of dynamical models from terrain averaging of hydrochemcial variables and underlying partial differential equations. The study will form the basis for testing a practical, low-dimensional modeling strategy for the CRB which attempts to balance the degree of model complexity with a definable level of modeling skill, and to evaluate the effect of interannual and decadal climate oscillations on the water resources of the CRB.

0310122
Duffy
Although the river basin is the organizing principal of the terrestrial water cycle research, until recently, models which couple the complexity of climate, terrain, ecology, and geology at this scale to the particular needs of a water resource forecast, have not been considered practical. The present research proposes to investigate the multi-scale dynamics of precipitation-recharge-runoff, and the partitioning of water and energy budgets over complex terrain and hydrogeological conditions. The approach maintains the natural coupling between surface and subsurface processes at each scale of interest but recognizes that surface water basins and groundwater basins may have distinct delineations. The modeling approach is based on a finite volume representation, where conservation and constitutive equations are averaged over a specified support scale. The model is multi-scale in the sense that climatic, vegetative, topographic and hydrogeologic elements of the landscape are resolved in such a way as to preserve the necessary space-time scales for a particular water resource forecast (flood dynamics, stream-aquifer response to drought, etc.). The research addresses the tradeoff between the scale of computing and the need to include fine-scale material properties in water resource predictions.

Long-term flow forecasts for the SRB must account for the competing time scales of the surface and subsurface processes governing the basin's response to climatologic or landuse forcing. Our strategy is to condition forecasts on both rapid surface responses as well as slower subsurface responses using multiobjective evolutionary algorithms. This multiobjective framework will adapt model parameters and resolution to account for the disparate time-scales and physical complexities of surface and subsurface flow regimes.
This research will initially focus on developing regional conceptual surface-groundwater models for component watersheds within the SRB. The next phase of the research will develop a strategy for synthesis of the regional conceptual models with geospatial data as input to a large-scale model for the surface-groundwater dynamics of the entire SRB. The final phase of the research will develop a decision-support system that will assimilate new climatologic data into long-range runoff predictions. These long-range predictions will support the development of improved water management policies for the entire SRB.

The research addresses four fundamental questions: 1) What role does hydrogeology play in long-term and short-term runoff and what is the relation to climate and landuse dynamics? 2) When does small-scale soil and subsurface variability control runoff and how can models "adapt" to changing external (climate) and internal conditions (landuse)? 3) What are the space-time scales at which tributaries of the river basin are dynamically coupled? 4) How can evolutionary computing strategies and "qualitative" conceptual models be incorporated to better resolve model dimensionality, parameterization, and prediction at the river basin scale?

0418798
Reed

Support form this award will establish a new Information Systems Technician position in support of the Penn State Institutes of the Environment's (PSIE) Real-Time Hydrologic Monitoring Network (RTH_Net). RTH_Net is a field facility within the university's experimental forest supporting research and education focusing on the interaction among atmospheric, terrestrial, and hydrologic processes. RTH_Net will support these efforts through the long-term deployment and maintenance of a real-time network of integrated sensor systems designed to augment the existing experimental infrastructure within the Penn State Experimental Forest. RTH_Net will integrate the existing but disparate observing systems within the Penn State Forest such that surface, groundwater and atmospheric data streams are coherent and in real time. Deployment and integration of traditional weather station technology with soil moisture/pressure arrays, groundwater level and stream stage sensors will allow a more coherent approach to the estimation of critical fluxes and feedbacks at the hillslope, watershed, and river basin scales. The network will play a fundamental role in improving forecast models of extreme events (flood, drought) as well as seasonal and interannual water resource dynamics. The facility will modernize and expand the current research infrastructure within the Penn State Experimental Forest. The Information Systems Technician will deploy physical sensor systems, maintain internet accessibility (i.e., IP connectivity) for the sensor data, and manage wireless or landline communication networks. The technician position will help ensure reliable data access and storage for RTH_Net through the management of combined onsite and offsite archives. The technician will manage internet-based publication using specialized software that will enable RTH_Net's datasets to be easily queried, analyzed, and visualized by researchers and students. These systems will be made accessible to the more than 30 faculty members within PSIE that have research interests in water resources. RTH_Net will support a long-term university-level effort to develop tools for a more holistic approach to real-time monitoring of water resources.
***

0609791
Duffy
Hydrologic Observatory: The Susquehanna River Basin (SRB) is the largest tributary
to the Chesapeake Bay. Without this flow the estuary could not sustain its extraordinary
diversity and productivity of aquatic life. The dilemma of our water-resource legacy is to balance
the competing societal and environmental needs placed on the Susquehanna's freshwater
resources. In 2002, Penn State took the leadership role in forming a consortium of scientists,
policy makers, and stakeholders drawn from 30 universities as well as from federal and state
agencies to design and implement the Susquehanna River Basin Hydrologic Observing System
(SRBHOS) (www.srbhos.psu.edu). SRBHOS has been initiated to address "How do humans
and climate impact the sustainability of the water resources within large river basins? What role
do large rivers play in the global climate system?".
Overview of Research: This proposed research plan will advance the SRBHOS
science agenda by investigating the three research themes: (1) Assessment of the significance
of the regional water table, its role as a lower boundary condition to soil moisture, and the
impact of water table status on hydrologic extremes (floods, droughts). We propose to develop
the concept of a subsurface boundary layer (SBL), which we define as the depth beneath the
land surface for which the local atmosphere and land-surface processes will affect the local flow
of groundwater to streams. An algorithm will be developed to map the SBL using the SRBHOS
digital data. (2) Integrated models that include vegetation water and energy dynamics will
improve hydrologic forecasts at the basin-scale and are critical to resolving the relative
importance of recharge to the shallow groundwater table and transpiration of soil moisture (3)
Macropores have a significant affect on the hydroclimatic performance of watersheds during
wet and dry cycles. We intend to develop new parameterization strategies to correct the
regional soils database for macropore flow based on the Shale Hills testbed. Currently soil
classification only considers "matrix" properties (conductivity and water holding capacity).
Finally, this research will attempt to demonstrate how a unification of modeling, existing digital
data, and new data collection strategies will advance our understanding of river basin water
resources and support the design of hydrologic observatories.
Intellectual Merit: The present proposal will unify early SRBHOS science efforts and
address how a physical model and a-priori data can be used to promote scientific collaborations
that: (1) will aid the SRBHOS community in formulating hypotheses and potential scenarios for
hydrologic change within the basin; (2) will promote the development of new data-driven
algorithms that enhance our ability to represent and predict water cycle dynamics; and (3) that
will support a scientifically-based design for the future observatory's sensor network. Addressing
these issues will aid SRBHOS scientists in assessing climate and human feedbacks across
multiple scales as well as physiographical and ecological conditions. The tools developed in
this research will contribute to improving our understanding of the roles of terrain, ecology, and
geology in partitioning water and energy across the complex environmental systems that make
up the SRB.
Broader Impacts: This proposed research will be disseminated broadly to the
academic, state, and federal SRBHOS partners through a Susquehanna Data and Modeling
Symposium, which will be organized by the PIs in conjunction with the Chesapeake Research
Consortium. Funds requested in this proposal for the symposium will be leveraged with others
sources of funding to maximize our ability to invite national leaders in river basin modeling and
data systems to review the proposed tools developed in this research as well as contribute their
own expertise and tools to the SRBHOS community modeling effort. All software and data
resources developed in this project are dedicated to the "open source" framework and shared
through the Chesapeake Community Modeling Program. Additionally, this research effort will
exploit basin-wide collaborations such as the currently pending Susquehanna REU to promote
undergraduate education and to recruit demographically and geographically diverse students
currently underrepresented in hydrologic science.

EAR-0725019
Duffy
THE SUSQUEHANNA/SHALE HILLS CRITICAL ZONE OBSERVATORY
Intellectual Merit: The surface of the earth comprises a weathering engine or mill that solubilizes and disaggregates rock to form regolith. Over the long term, the rates of weathering and erosion combine to control the evolution of landscapes and help to define the access, rates of motion, and time scales of water and energy within the Critical Zone (CZ). Despite the importance of these processes, we are generally unable to quantitatively predict the rates or mechanisms by which regolith forms or how it controls water flow. Understanding these rates is of particular importance due to the rapid rates of change of the CZ in response to anthropogenic and climate perturbation. Here we propose a Critical Zone Observatory dedicated to developing this understanding for one of the most common lithologies on earth.
Our Critical Zone Observatory site, the focus of National Science Foundation-supported research since the 1970s, provides long term datasets for hydrological response that will be augmented here by new geochemical, geomorphological, ecological, and soils datasets. The observatory is a small catchment in central Pennsylvania (hereafter termed the Susquehanna/Shale Hills Observatory or SSHO) on Rose Hill Shale. As a tectonically quiescent and relatively pristine watershed, Shale Hills presents the opportunity to investigate the rates and mechanisms of regolith formation on a simple but ubiquitous bedrock lithology. The regolith at the SSHO has experienced at least two potentially significant perturbations in the geologically recent past: a climatic perturbation from peri-glacial to modern conditions and a biologic perturbation from anthropogenic clearing of forests during colonial occupation. The magnitude of these perturbations and their influence on regolith generation afford an opportunity to assess the time scales of response of soil production to both long-term climate change and human activity.
Broader Impacts: To predict the creation, evolution, and structure of regolith as a function of the geochemical, hydrologic, biologic, and geomorphologic processes in our forested landscape, we have created an interdisciplinary team of 14 scientists from 8 universities, 1 federal agency, and 2 national laboratories. This team will coordinate not only the SSHO but also six satellite sites where we will initiate similar but less extensive investigations to explore the effect of climate and composition on shale weathering. Among these, Alabama A&M and University of Puerto Rico are minority-serving institutions that will facilitate the involvement of under-represented groups in Critical Zone science. Scientists and REU students from each satellite site (eighteen students over three years) will work closely with members of the Penn State team on a variety of activities ranging from geochemical analyses of soil and bedrock samples to measurement of soil moisture with onsite detectors. The observational data and model capabilities developed in the proposed effort will be made available through web-services for both time series data and geospatial data through the CZEN cyberinfrastructure initiative. Development of the SSHO on-line information system will be supported by ongoing NSF observatory and cyberinfrastructure grants. It is our vision that the SSHO will become an exemplar for Critical Zone observational and modeling science that will attract many additional investigators from the broader community to test ideas, techniques, and predictions.

Acquiring airborne LiDAR (Light Detection and Ranging) data for the Critical Zone Observatories (CZOs) will significantly advance research, both within and across the CZOs. Uniformly acquired and processed LiDAR data would stimulate cross‐CZO activities and synthesis surrounding the terrain and canopy information obtained. As a cross-site activity for the National CZO program a LiDAR supplement from the UC Merced CZO has been requested. At the Annual National CZO Meeting, it was made clear that standardized data and ground truth protocols would need to accompany the supplement to ensure that the LiDAR data receive sufficient support to galvanize the research that will use the LiDAR products. It was determined that each local CZO team will do the vegetation ground truth for their site, following protocols developed. Each CZO, then, takes the needed field measurements and provides the data to the PI at UC Merced. The need for a RAPID proposal is that the vegetation ground truth has to be completed before the LIDAR survey in summer 2010.

This RAPID request includes the cost of two undergraduate students for three months (full time), necessary field equipment for the vegetation ground truth, and surveyor time for necessary georeference accuracy of vegetation. One graduate student (PhD level) is currently employed and will be provided by the
Susquehanna/Shale Hills CZO at no charge to the request.

EarthCube is focused on community-driven development of an integrated and interoperable knowledge management system for data in the geo- and environmental sciences. By utilizing a cooperative, as opposed to competitive, process like that which created the Internet and Open Source software, EarthCube will attack the recalcitrant and persistent problems that so far have prevented adequate access to and the analysis, visualization, and interoperability of the vast storehouses of disparate geoscience data and data types residing in distributed and diverse data systems. This awards funds a series of broad, inclusive community interactions to gather adequate information and requirements to create a roadmap for a critical capability (workflow) in the development of EarthCube, a major new NSF initiative. Workflow in the context of EarthCube, and cyberinfrastructure in general, encompasses a broad range of topics including distributed execution management, the coupling of multiple models into composite applications, the integration of a wide range of data sources with processing, and the creation of refined data products from raw data. A key benefit of the funded work in terms of evaluating and creating community consensus on the best way forward for this capability (i.e., workflow) is the ability to document the provenance of data used in modeling and reproduce model and data-enabled scientific results. The funded workshop and information collecting activity will be open to all interested parties and is being led by a diverse and expert team of cyberinfrastructure developers, computer scientists, and geoscientists. Broader impacts of the work include converging on approaches, protocols, and standards that may be applicable across the sciences. They also include the fostering of close interaction between communities that do not commonly interact with one another and focusing them on the common goal of creating a new paradigm in data and knowledge management in the geosciences.

This project will focus on the long-term spatial and temporal dynamics of land-use management, agricultural decision making, and patterns of resource availability in the tropical lowlands of Central America. The project will combine diachronic environmental simulation with analysis of historic settlement patterns and environmental surveys to address a series of long-standing questions about the coupled natural and human history in the Central Maya lowlands, with special emphasis given to the UNESCO world heritage site of Tikal in the Maya Biosphere Reserve. The researchers will examine changing patterns of land, water, population, settlement, and political history for a 3,000-year period using climate, soil, and hydrologic modeling and time-series spatial analysis of population and settlement. The critical period of the study, 1000 BC to AD 2000, begins with dispersed settlements accompanied by widespread deforestation and soil erosion. Population size and density grew rapidly for 800 years, while deforestation and erosion rates declined. This period was also characterized by striking evidence of political evolution, including the construction of monumental architecture, hieroglyphic carvings detailing wars and alliances, and the construction of a defensive earthwork feature that signaled political territories, and possibly delineated natural resource boundaries. Population decline and steady reforestation followed until modern migration into the region. Building on previous research by these and other researchers in the region and comparative research completed at Palenque, Mexico, these researchers will model the 3,000-year history of the region, comparing land and water availability to population distributions and examining what is known about political history. The researchers also will analyze the spatial patterns of land and water availability under simulated conditions of drought, thereby addressing modern issues of migration and water availability as they studying the possible impact of climate events on the cultural history of the Ancient Maya.

This project will contribute to understanding long-term environmental change, agrarian decision making, settlement patterns, and critical issues facing smallholder agrarian communities. The project will enhance understanding of one of the most compelling landscape narratives of coupled human and natural history, the rise and fall of the Maya in the lowland tropical forest of Central America. The project will explore a new approach for studying these issues by integrating coupled climate, soil, and hydrologic modeling with traditional anthropological research methods. The project also will provide excellent field and laboratory education and training opportunities for postgraduate, graduate, and undergraduate students from anthropology, engineering, soil science, and landscape architecture. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program.

An Accomplishment-Based Request for Renewal of the Susquehanna - Shale Hills Critical Zone Observatory (SSHO)

With funding from the NSF Critical Zone Observatory (CZO) program, CZO workers led by PI Susan Brantley and coInvestigator Chris Duffy (Pennsylvania State University) will focus on cross-disciplinary synthesis, data sharing, and outreach at the Susquehanna Shale Hills CZO. Established originally in the 1970s as a site to study water flow in forested catchments, the 8-hectare Shale Hills watershed was expanded in 2007 as a CZO to understand broader questions targeting the interplay of water, energy, atmospheric gases, biota, soils, and the land surface. In addition to the small Shale Hills catchment, the CZO includes a suite of satellite sites that overly the same bedrock type (shale) but which are situated in different climate regimes. One additional satellite site is located on organic-rich Marcellus shale. These satellites allow researchers to understand how climate and organic content control water flow and soil formation while working with minority-and undergrad-serving institutions. CZO researchers are investigating i) new methodologies to model the age and chemistry of water as it moves from the atmosphere to groundwater; ii) new techniques to synthesize measurements of soil moisture for incorporation into land-atmosphere models; iii) observations that constrain water, energy, and solute fluxes related to trees; iv) models that quantify how soil grows on shale; v) new uses of isotopes to measure soil formation; and vi) observations concerning how variables describing characteristics at depth such as the fracture distribution in bedrock combine with features at Earth's surface such as the sunniness of hillslopes to control the evolution of soils and hillslopes over time. Datasets of isotopes, chemistry, soil moisture, CO2 and energy flux, LiDAR, sapflux, and other observables collected at high spatial and temporal resolution are published online. Outreach activities include community education about natural gas development on shale and K-12 educational opportunities.

This INSPIRE award is partially funded by the Geobiology & Low Temperature Geochemistry Program in the Division of Earth Sciences in the Directorate for Geoscience; the Human Centered Computing Program in the Division of Information & Intelligent Systems in the Directorate for Computer & Information Science & Engineering; and the Virtual Organizations as Socio-technical Systems Program in the Division of Advanced Cyber-Infrastructure in the Directorate for Computer & Information Science & Engineering.

This project will develop new scientific work practices and cyberinfrastructure tools to advance the fields of hydrology and limnology (lake ecology). The project will develop a socio-technical model of "organic team science" in which scientists are motivated to collaborate across diverse scientific communities and to share and normalize data to solve scientific problems through an open framework. potentially creating new cross-disciplinary collaborations around the modelling problems. The project will advance hydrology by making already-collected geospatial data more usable for analysis and simulations. It will advance limnology by developing an integrated hydrodynamic model of lakes as connected to the broader hydrologic network to quantify water, material, nutrient and energy fluxes, which is potentially transformative for limnology. The project will be carried out with collaborators including the NSF Susquehanna/Shale Hills Critical Zone Observatory and the GLEON projects.

The project will provide benefits by developing cyberinfrastructure to provide access for limnology to climate and geospatial data and models as well as novel practices for supporting organic team science. The later is potentially a significant and transformative contribution to the infrastructure for science. The hydro-dynamic model could be useful for those managing lakes. The proposal includes plans for outreach to the scientific community to share these findings.

This is a request to support the participation of seven US scientists to attend a meeting to be convened and supported by the European Commission, Joint Research Center; Ispra, Italy, in March, 2013. The workshop title is: "SCOPE Rapid Assessment Project on Benefits of Soil Carbon". This workshop will provide an important venue for US scientists studying the Critical Zone to actively engage with the international community in developing science-based solutions to an important issue with global importance. The outcome of the workshop is a monograph of the same title.

The Critical Zone (CZ) is the zone between the upper branches of trees and the depths of groundwater. Humans are changing this zone at geologically unprecedented rates. Maintaining ecosystems will require the ability to project the future of the CZ. Only with concerted efforts to measure and model the landscape will it be possible to make forward projections or "earthcasts" of the CZ.

In the Susquehanna Shale Hills Critical Zone Observatory (CZO), scientists are working to earthcast the CZ by modeling aspects of the atmosphere, land surface, biota, soil, rocks and water. In addition, the models will eventually incorporate impacts of human activity. These models for water, energy, sediment, and solute (WESS) fluxes will be used to project changes spanning from 10^-3 y (water) to 10^6 y (soil). For the sedimentary rocks underlying the CZO, the models will be used to explore how the geological past has impacted today?s land surface, and, in turn, how this structure contributes toward controlling today's water and gas fluxes.

The central focus of the CZO is the forested Shale Hills watershed (~0.1 km2) but investigations will include the multiple-landuse Shavers Creek watershed (165 km2). These nested watersheds will comprise the expanded Susquehanna Shale Hills Observatory (SSHO). This upscaling will force a transition from measuring "everything everywhere" to measuring "only what is needed" in a larger watershed with multiple rock types and land use. The CZO will be used to test the over-arching hypothesis: To project CZ evolution into the future requires knowledge of geological history, observations of CZ processes today, and scenarios of human activities tomorrow.

An important focus of the CZO will be to transfer knowledge to nonCZO scientists and to the public. For example, the CZO will develop hydrological models for two PA watersheds in the region of drilling and hydrofracking for shale gas in western and northern Pennsylvania. The public will also be engaged through a "CZO Four Seasons" music concert, where Penn State musicians will create a music score from many years of watershed data at the CZO.

Geosciences software embodies crucial scientific knowledge, and as such it should be explicitly captured, curated, managed, and disseminated. The goal of this project is to create a system for software stewardship in geosciences that will empower scientists to manage their software as valuable scientific assets. Scientific software stewardship requires a combination of cyberinfrastructure, social infrastructure, and professional development infrastructure. The framework will result in an open transparent and broader access to scientific software to other scientists, software professionals, students, and decision makers. It will significantly improve the adoption of open data and open software initiatives, improve reproducibility, and advance scientific scholarship.

The proposed research will advance knowledge and understanding of scientific software as a valuable community asset that is worth sharing, curating, cataloging, validating, reusing, and maintaining.
1) Facilitating software publication through TurboSoft, a personal assistant (analogous to TurboTax) that guides a user through best practices. Users will choose the degree of investment they are willing to make in componentizing, describing, licensing, and maintaining their software. The system will encourage open source publication, the formation of communities around the software, and set up mechanisms for software citation and credit.
2) Enabling broad software dissemination through GeoSoft, a "software commons" for geosciences that will support software contributions (prepared through TurboSoft or otherwise), software discovery through multi-faceted search, and foster social interactions through dynamic formation of communities of interest. GeoSoft will interoperate with existing software repositories and modeling frameworks in geosciences.
3) Providing just-in-time training materials through GeoCamp, an annotated collection of educational units ranging from basic education to professional training on all aspects of software stewardship. GeoCamp will be seamlessly integrated with TurboSoft and GeoSoft, and present a wide range of options for learning in the context of a user?s context of interaction with the framework or independently.

The success of machine learning (ML) in many applications where large-scale data is available has led to a growing anticipation of similar accomplishments in scientific disciplines. The use of data science is particularly promising in scientific problems involving processes that are not completely understood. However, a purely data-driven approach to modeling a physical process can be problematic. For example, it can create a complex model that is neither generalizable beyond the data on which it was trained nor physically interpretable. This problem becomes worse when there is not enough training data, which is quite common in science and engineering domains. A machine learning model that is grounded by explainable theories stands a better chance at safeguarding against learning spurious patterns from the data that lead to non-generalizable performance. This is especially important when dealing with problems that are critical and associated with high risks (e.g., extreme weather or collapse of an ecosystem). Hence, neither an ML-only nor a scientific knowledge-only approach can be considered sufficient for knowledge discovery in complex scientific and engineering applications. This project is developing novel techniques to explore the continuum between knowledge-based and ML models, where both scientific knowledge and data are integrated synergistically. Such integrated methods have the potential for accelerating discovery in a range of scientific and engineering disciplines. This project will train interdisciplinary scientists who are well versed in such methods and will disseminate results of the project via peer-reviewed publications, open-source software, and a series of workshops to engage the broader scientific community.

This project aims to develop a framework that uses the unique capability of data science models to automatically learn patterns and models from data, without ignoring the treasure of accumulated scientific knowledge. Specifically, the project builds the foundations of knowledge-guided machine learning (KGML) by exploring several ways of bringing scientific knowledge and machine learning models together using pilot applications from four domains: aquatic ecodynamics, climate and weather, hydrology, and translational biology. These pilot applications were selected because they are at tipping points where knowledge-guided machine learning can have a transformative effect. KGML has the potential for providing scientists and engineers with new insights into their domains of interest and will require the development of innovative new machine learning approaches and architectures that can incorporate scientific principles. Scientific knowledge, KGML methods, and software developed in this project could potentially be extended to a wide range of scientific applications where mechanistic (also known as process-based) models are used.

This project is part of the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea activity.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.