L. Douglas James

                                                                                                            January 10, 2005




            Over the past several years, the academic community pursuing research and education in hydrology and related sciences has organized CUAHSI and gained NSF support for the concept of establishing a national network of Hydrologic Observatories to assemble coordinated, commensurate data to support science for addressing critical resource issues at the watershed scale.  Simultaneously, the environmental engineering community has been organizing CLEANER and forming an observatory program at this larger scale to support the stronger science base needed to protect the environment from contamination; and the ecological community has established NEON to expand an observational base from the small areas covered by the long-successful LTER program to support research at a larger scale in environmental biology.  Soil scientists are working toward an observation program to support research into the weathering of geologic materials, the carbon community is expanding the observation base used to gain a working understanding of the global carbon cycle and achieving a mass balance in estimated quantities, and geomorphologists are assembling data to support establishment of a Community Sediment Model. The Ocean Sciences are also developing observatory programs to address their needs.  The Atmospheric Sciences long ago formed UniData to facilitate access to information on weather and climate. 


These initiatives by research communities are augmenting long-established efforts by management agencies for measuring river flows and quality, groundwater levels, soils, geology, topography, land cover, land use, and many other characteristics of the continually changing Earth’s surface.  In addition, the need for field data to support research to expedite management was recognized more than 60 years ago when large numbers of experimental watersheds were established.  However, these lack needed geographical size and diversity, interdisciplinary connections, and combination of natural and built environments.


            The emerging efforts by the research communities and the agency experiences with data gathering and experimental watersheds pose an opportunity for raising environmental science to a higher level.  The criteria to use in responding are best drawn from 1)the value to science that can be added by joining observatories to support interdisciplinary work and 2)the potential for reducing the costs of the individual Observatory programs by providing easy access to a common database.  That task requires a broad vision of the science ahead.



            The surface of the Earth is exposed to diverse forces (but largely originating in solar radiation or gravity) operating at different scales that drive physical and chemical change.  Water is a key agent.  Fresh water is a resource that continually moves among many storages throughout the entire Earth surface environment.  Amounts and residence times vary greatly among these storages.  Residence times vary from fractional seconds to centuries and longer.  The water fluxes among storages move and interact in highly irregular patterns and carry sediments and chemicals.  These properties at a given time define the environment for chemical reactions, microbial activity, food chains, ecological evolution, and human land and water choices.  Over time, the resulting change dynamics modify distributions of the physical and chemical properties of the surface of the solid Earth. Over geologic time, the process sequences and distributions have given the Earth a highly heterogeneous surface.  


It is within this setting that water continually travels physical pathways through the atmosphere, over land surfaces, within soils and rocks, down streams and rivers, and across coastlines to the open sea.  We can track these pathways, define conditions along the routes and the evolving characteristics of both the water and the surrounding media and use the results to code models for hydrologic simulation.   Since alternate pathways through a given medium aggregate at different scales, a major science challenge arises in quantifying the fluxes across connections between media; however, recent advances in instrumentation now enable us to observe the velocity distributions needed to begin to understand the processes and quantify the fluxes as water moves from one medium to another.  Such research shows that chemical reactions alter the media, change the fluxes, modify the pathways, and add a new dimension to assess, a new dimension that requires that the pathways be tracked in much more detail.


That dimension is chemical cycling.  Nitrogen, carbon, metals (where iron and manganese are primary actors), and organic substances take on different forms (e.g., N2, NH4, NO2, NO3) in progressions dependent on pH, oxidation state, temperature, etc. and these properties themselves depend on relationships with water.  Here, it becomes critical to track a chemical and not just a locational state.  Elements cycle among relatively few chemical forms, and the cycling processes are often reversible.  In the highly heterogeneous settings found in Earth surface materials, cycling processes vary in time and space (where definition of the determining setting introduces additional scaling issues).  Different movements within a cycle take place at different rates.  Chemicals of a given form are held in storage at various locations and are later exposed to conditions that lead to their release.  The chemical substances have their own cycles, and these are interdependent.  Hence, many properties must be observed at many locations to gain understanding of the complex, dynamic geochemical system.


This dynamic physical-chemical context at surface Earth provides the habitat for microbes that interact within populations and among species and collectively become important agents in chemical and physical change.  The dynamic habitat with its continually perturbs the microbiological system that supports life sequences in which local environments attract microbes, stimulate growth, or inflict harm.  Life sequence processes are fundamentally different than chemical cycling processes in that they are irreversible.  Also, observations at still different scales must be used to define how species in complex natural settings interact, evolve, and change the media that support them.   Different cultures function in different sequences with varied interdependencies.  Terrestrial and aquatic flora and fauna introduce multiple additional life forms, interdependencies, and changes to track.


Superimposed on this complexity in nature, people change their uses of land, construct projects that alter water flows, generate and discharge chemicals at different places in different time patterns, and manufacture new chemicals that eventually reach natural systems where they are dissipated at varying rates.  Human development (both building and operating) alters natural pathways, cycling, and life sequences; physically, chemically, and biologically.  It exposes natural systems to nutrients that stimulate and to poisons that destroy life.  The fundamental distinction of human-managed processes is that they result from conscious decision making among alternatives.   People are motivated by economic and social drivers, and these vary with culture.  Hence, Observatories must also track drivers that generally operate at larger spatial scales and changes to the built environment and human practices in operating facilities, using land and water, and discharging wastes.


We have long recognized this great complexity in the Earth surface system.  Scattered studies have defined hydrologic pathways, chemical cycling, life sequences, and human development and identified interactions among them.  However, it is only recently that rapidly advancing sensing and information technology have provided the means to characterize and quantify all of these in the detail needed to study the total system.  We have much to learn about monitoring attributes, changes and ties among them so that we can deduce processes in the highly complex natural environment at larger scales.  We are still in the formative stages of learning how to go about compiling the data needed to address interactions among their vastly different scales of operation.   The formation of effective Observatories is a learning process.



The goal of an integrated Observatory is to support systematic collection and recording of data on the characteristics of the total system with its many interactive physical pathways, chemical cycles, biological sequences, and decision trees.    Such an approach would add to environmental science the much-needed dimension of moving out of the laboratory and small field plots to watershed and larger scales.  The tracking would document fluxes with widely varying travel rates, storages with widely varying residence times, and drivers operating in different patterns and at different scales.  


However, we cannot enter all aspects of this vast domain at once.  Order may be given to the growth process by using hypothesis testing.  Diverse hypotheses on how this complex system functions can be used to build a common framework that scientists in all relevant specialties can use to define the pathways, cycling, sequences, and decision trees related to fluxes of water, sediment, nutrients, toxic materials, etc. at the fine spatial and temporal scales necessary to enhance understanding and predictability.


The organizing concept would be to start Observatory design with a hypothesis in watershed science that cannot be resolved by laboratory and field experiments nor by presently available data on watershed processes.   Specifically, the hypothesis should cross the dimensional boundaries described above on an issue that cannot be addressed without an Observatory.


That hypothesis should then be used to identify a set of needed sensor types and a network for sensor deployment.  Initial testing at the watershed scale should begin with pilot studies to ascertain feasibility before going to expensive large scale monitoring.   Some hypotheses can doubtlessly be resolved by judicious deployment of existing sensor technology.  Others will require “new” sensors.  Some needs can be satisfied by a sensor that provides direct measurement of a desired property; others will have to be calculated by developing algorithms for estimating the desired properties indirectly from secondary data.


Observatory design needs several hypotheses.  The additional hypotheses will suggest other sensor types and deployment networks.   Data common to hypotheses on two or more issues would then provide “core data” for collection by the Observatory.  Additional sensors that complement the network to support the testing of hypotheses on individual issues would then be used in that testing, form a basis for publication, and then be added to the core data for other to use soon afterwards.  Observatory management will need to decide which measurements to continue after primary studies end.



Observatory data are to be assembled under the banner of a “Digital Watershed.”  The needed Digital Watershed system would be designed by following guidance provided by research in cyberinfrastructure.  A Digital Watershed would logically start by organizing data already being collected (or having been collected in the past) by agencies, companies, etc. and germane to the hypotheses selected to guide Observatory development.   The vision should be to work toward a coverage (a framework that can be readily expanded to accommodate) that encompasses the range of physical pathways, chemical cycles, life sequences, and human decision trees germane to watershed science.


Many major challenges must be overcome to bring watershed data from many sources into a common framework in space and time.  Some of the most difficult challenges will be in developing a common protocol for presenting meta data.  Diverse scientists will have to have a common framework for effective communication among a wide variety of sciences.  The initial major challenge in Digital Watershed development would be to find an effective and efficient way to bring this together in a system where all relevant disciplines would have easy access to understandable information in a convenient form.