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PRELIMINARY DRAFT VISION PAPER

Bridging River Basin Scales and Processes to

Assess Human and Climatic Impacts on Water, Energy, and Biogeochemical Balances

by

Patrick Reed (preed@engr.psu.edu), Robert Brooks, Kenneth Davis, David DeWalle, Christopher Duffy, Hangsheng Lin, Douglas Miller,

Raymond Najjar, Karen Salvage, Brenton Yarnal

for the Consortium of Universities for the Advancement of Hydrologic Sciences

(CUAHSI)

September 10, 2004 Draft # 1

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1.0 INTRODUCTION Human development in the northeastern United States affects the quantity, quality, and regimen of water resources occurring in the atmosphere, streams, lakes, and aquifers. Truly sustainable development must occur in ways that will not threaten the long-term health of the ecologic and human systems that are dependent upon these water resources. Environmental problems in the region today––such as

● excessive flooding, ● dry stream beds, ● excessive sedimentation of reservoirs and streams, ● accelerated loss of top soil, ● fish kills, ● increased occurrence of water-borne diseases, ● declines in drinking water quality, ● acid rain, ● sudden forest decline, ● fish consumption advisories, ● unseasonable declines in water table elevations, ● prolonged droughts, ● acid mine drainage in streams, ● excessive algal blooms in streams and lakes ● loss of aquatic habitat--

are largely the result of human impacts and are symptomatic of unsustainable development. Human development of the Northeast has increased atmospheric emissions of greenhouse gases that may potentially contribute to changes in the region’s climate and the energy balance at the earth’s surface. Impacts of stormwater from urban/suburban development on water quantity and quality have been a long-standing problem for surface and groundwater resources. Although society has made significant progress towards minimizing the impacts of development on water, assessing the large-scale, collective impacts of human activity on water is difficult to accomplish without integrated assessments at the river basin scale. Science needs to address how human development is affecting water resources—specifically, water availability and water use—of large basins (National Research Council 2004). Science also needs to develop indicators of the impacts of human development on water resources to monitor and assess our progress towards achieving sustainability.

Hydrologic observatories (HOs) on large river basins offer the opportunity for

scientists to assess climate and terrestrial feedbacks across multiple scales and physiographic conditions to better define the roles that terrain, ecology, and geology play in partitioning water, energy, and nutrients across the complex environmental systems that make up river basins. We, as hydrologic scientists, will need to reexamine our scientific hypotheses regarding the importance of phenomena and process across multiple scales if we are to improve our ability to understand, forecast and mediate the impacts of climate and anthropogenic change on local water resources. Studying the river-basin as a

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holistic system will serve to enhance collaborations between hydrologic researchers as well as promote improved strategies for communicating with federal, state, and local water managers to enhance land-use planning decisions and develop of hydrologic indicators of sustainable growth, particularly in rapidly urbanizing environments. The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) has recommended that HOs address the following science topics:

● linking hydrologic and biogeochemical cycles ● sustainability of water resources ● hydrologic and ecosystem interactions ● hydrologic extremes ● fate and transport of chemical and biological contaminants.

Proper understanding of the inter-relationships among and within these topics also requires that three cross-cutting themes be included in the design of HOs: (1) forcing, feedbacks and coupling, (2) scaling, and (3) prediction and limits to predictability. A river-basin scale research strategy will require assessment of climate and terrestrial feedbacks in space and time (including landuse change), improving local, regional, and global hydroclimatic predictions, and evaluating how long term system changes impact stakeholders within a basin’s local watersheds. To accomplish this task the scientific hypotheses and directed research infrastructure must capture anthropogenic feedbacks, dominant climatological conditions, and characteristic physiographic landforms impacting the human and ecological sustainability of a river basin.

In this paper, Section 2.0 provides an illustrative discussion of how anthropogenic

and climate changes are impacting the Northeast with recommendations on how HO’s could help scientists better understand these problems. In Section 3.0, we propose that characterizing large river basins in the Northeast will require a holistic regionalization of the systems into “similar” zones based on hydrologic, ecologic, and land use conditions. Section 4.0 proposes new instrumentation platforms for the plot-, reach-, and hillslope-scales, which could provide integrated observations of all the states and fluxes within their footprints (e.g., evaporation, transpiration, recharge, baseflow, and water quality indicators). Section 5.0 discusses outstanding issues that will need to be addressed for CUAHSI to provide cross-disciplinary observation systems that support research at the level of the individual researcher and scale to the level of community-wide initiatives. 2.0 HUMAN AND CLIMATE IMPACTS ON THE NORTHEAST 2.1 Urbanization One of the major challenges that large-scale hydrologic observatories can address is the influence of evolving policies related to urban stormwater management. Initial concerns associated with the impacts of urban development were primarily focused on flooding due to increases in impervious surfaces caused by streets, parking lots, and roof tops. Flow duration curves of streamflow provide one of many ways to assess changes in watershed hydrology resulting from urbanization. For example, in Figure 1 the upper

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two curves represent urbanizing and industrialized sub-basins, Thompson Run and Logan Branch, which show higher flow rates per unit land area due to development. Effects of groundwater withdrawals for public water supply are evident in the lower curve for Slab Cabin Run sub-basin. The middle curves, representing Cedar Run and Buffalo Run, are primarily influenced by agricultural and forest land uses and represent a more natural flow regime. In response, stormwater detention ponds were installed below incremental urban developments to control peak flow rates on a site-by-site basis. Although this practice controlled peak flows from a given development, experience showed that flooding persisted when increased volumes of stormwater from several different developments merged downstream. In addition, although the dry basin approach provided some “point recharge” of groundwater and trapping of sediment, no major attempts were made to keep stormwater on site or to control water quality. Thus, the initial concern with flooding alone and the detention basin approach did not prevent downstream flooding and did not resolve issues related to groundwater recharge and the quality of urban stormwater.

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Figure 1: Flow-duration curves for sub-drainages within the urbanizing Spring Creek basin in central Pennsylvania for 1999-2002 illustrate the impacts of development on stream flow rates. (Data from ClearWater Conservancy, State College, PA.)

Urbanization, as does most other human development in a basin, causes shifts in the water-delivery flow pathways from subsurface sources to surface sources. Stormwater management seeks to reverse that trend and promotes greater infiltration and groundwater recharge. It is well known that urbanization changes flow timing and increases peak flows (see Figure 2). However, the shifts in flow duration for lower frequency flows are less certain, but are of equal importance to sustainable development and ecosystem maintenance.

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DRAFT Figure 2: Stormflow response on Spring Creek tributaries for event of June 27-29, 2002 showing timing of peak flows on urbanized Upper and Lower Slab Cabin and Lower Thompson Runs as compared to flows in the main stream at Houserville, Axemann and Milesburg that integrates inputs from urban areas with delayed flows from agricultural and forest land (Spring Creek Watershed Community 2003). PLACEHOLDER FIGURE Without stormwater management, urbanization may cause increases in low flows as well as high flows due to many factors, such as downstream return flows from sewage treatment plants, from industry, from leaking pipes, and from small impoundments. Shifts in flow paths within watersheds may be monitored using stable isotopes of hydrogen and oxygen in water as tracers to track fractions of precipitation water appearing in stormflow. Understanding the differences in flow regimes across large, diverse basins with a variety of land uses, including shifts in such curves over time and within sub-basins, can be an effective tool in assessing urbanization and stormwater management impacts.

Trends in water quality related to urbanization include the effects of point source and non-point source pollutants and of atmospheric deposition. Point source pollution control has been largely addressed through the National Pollutant Discharge Elimination System (NPDES). The impacts of non-point source pollution control are now being seen, especially the impacts resulting from the adoption of stormwater management. Effects of stormwater treatment and recharge must be viewed at a larger scale than the individual development, especially given the shifting patterns of urbanization and other land uses. Total Maximum Daily Loads (TMDLs) are currently being used to help control point and non-point source pollution on watersheds. TMDLs are set as the maximum amount of various pollutants that a water body can assimilate without violating water quality standards. BMPs for stormwater and other non-point sources and NPDES permits for point sources are being proposed to achieve TMDLs in the context of watershed management plans involving public input to control pollution. With a mix of land uses, identifying the sources of nitrogen and phosphorous pollution in water bodies is often very challenging. Identifying the sources of nutrients and pollutants is important for

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assessing the effectiveness of urban stormwater management independent of other land-use activities. HOs should provide regular sampling of key indicator nutrients, pollutants and related parameters throughout large basins to provide a framework for assessing such change.

HO’s should synergistically support assessments of the impacts of both atmospheric and urban stormwater pollution. Over the past few decades, reductions in emissions of sulfur dioxide and nitrous oxide promulgated by the Clean Air Act (http://www.epa.gov/air, http://www.nadp.sws.uiuc.edu) have steadily decreased acid deposition in rain and snow in the Northeast. Future efforts to control emissions of heavy metals, mercury, and nitrogen compounds into the atmosphere should produce further reductions of atmospheric deposition of pollutants. Stormwater management largely seeks to reduce the volumes of overland flow that reach water bodies, so future atmospheric emissions reductions would also control the contamination of water bodies by wet deposition of pollutants and by washoff of dry atmospheric pollution. A note of caution is in order, however: if atmospheric deposition is not controlled in the future, the emphasis on recharge of urban stormwater could lead to accumulation of atmospheric contaminants on urban lands. Hydrologic observatories offer a unique opportunity to assess the large-scale and long-term impacts of urbanization and the effectiveness of the national stormwater management program. Monitoring the quantity and quality of atmospheric, surface, and subsurface waters over large, urbanizing, mixed land-use watersheds would permit experts to assess the cumulative impacts of all point source and non-point source controls on water related to the Clean Water Act Amendments. In addition, the large-scale hydrologic impacts of urbanization and stormwater management occur concomitantly with other land-use changes and environmental trends. The accurate assessment of trends in water quality and quantity can only result by developing an integrated network of monitoring sites over a wide range of land uses. Thus, the major long-term impacts of urbanization and stormwater management programs that should be addressed within the hydrologic observatory concept are changes in:

● Surface-water flow regimen ● Subsurface water recharge ● Evapotranspiration rates and the water balance ● Water quality of subsurface and surface water resources ● Institutional, policy, and socioeconomic factors that affect

urbanization and the development and adoption of stormwater management.

Watershed monitoring usually invokes images of sensor arrays measuring various biophysical components of the hydrologic system, but the human imprint on today’s hydrology is so great that it is necessary to think of watersheds as coupled human-environment systems. Changes in water availability and water quality over time and space are the result of complex interactions of varying physical and socioeconomic processes. Consequently, understanding coupled human-watershed dynamics requires

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not only biophysical monitoring, but also socioeconomic monitoring. Hydrologic observatories offer an opportunity to identify and monitor the legal, institutional, and other human factors that control land uses, industrial processes, and governmental policies and that are crucial to understanding watershed dynamics.

For example, patterns of urban development and of adoption and implementation of stormwater management are major controls on water resources impacts. In any one place, as population, land use, technology, and regulation change over time, water availability and water quality also change. In states with strong central governments and restricted local determination, it is likely stormwater management impacts will be more limited over space than in states with greater local autonomy. Thus, biophysical measurements are insufficient for understanding how urbanization and stormwater management interact to produce the unique hydrology of a watershed; simultaneous monitoring of human processes is also necessary to gain such knowledge. 2.2 Climate Change Uncertainty in future hydrologic projection stems from uncertainty in climate projection and errors in hydrologic models. Errors in climate projection arise from uncertain anthropogenic forcing (greenhouse gas levels, land use change, etc.) and errors in the climate models themselves. Both kinds of errors are difficult to quantify because, unlike weather forecasting, where errors can be rigorously evaluated based on a nearly exhaustive prior experience, humanity is entering societal and climatic states not previously encountered. Nevertheless, confidence in future climate projection is bolstered by the ability of climate models to “provide credible simulations of the climate, at least down to sub-continental scales and over temporal scales from seasonal to decadal” (McAvaney et al. 2001). Furthermore, different models are consistent in their projections on continental scales (Cubasch et al. 2001; Giorigi et al. 2001): the troposphere warms, with greater warming at high latitudes, over land and during the winter; Northern Hemisphere snowcover decreases; evaporation increases; precipitation increases in the tropics and high latitudes and decreases in the subtropics; mid-continental soil moisture decreases in the summer; interannual variability in Northern Hemisphere summer monsoon precipitation increases; and intensity of rainfall events increases. Many of these changes have already started to occur, which gives increased confidence in future projections.

Hydrologic models have been successful for several decades at simulating

observed streamflow given accurate atmospheric conditions, particularly when properly calibrated (e.g., Jones 1984; Mather 1981; Nijssen et al. 2001; Wolock et al. 1993; Wood et al. 1997). Improvements in recent years have focused on improving the physical realism of the processes as opposed to reproducing the streamflow record. This focus has generally resulted in more complex models with a greater number of free parameters, which has spawned the problem of “equifinality” in which different models, or even the same model with different parameter sets, produce results of similar skill (Beven 1993). The essential problem is a lack of observations of what happens to water after it falls as precipitation and before it ends up as streamflow. It is therefore difficult to say how

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hydrologic functions will respond to climate change, even if that climate change were perfectly known. Observations mainly show how streamflow responds to precipitation, and hydrologic models can be calibrated with these observations to produce the correct runoff efficiency. In a synthesis of many such studies of streamflow trends, Arnell et al. (2001) note that streamflow has changed in a manner that is largely consistent with precipitation. Globally, precipitation over land has increased by 2% over the past 100 years, with much greater increases in middle and high latitudes of the Northern Hemisphere and decreases in the tropics and subtropics of both hemispheres. Fractional changes in streamflow are often significantly greater than those changes in precipitation (Groisman et al. 2001). Like precipitation, much of this increase in streamflow has been in the extreme high category. Another trend has been a shift in flow from spring to winter in many watersheds in middle and high latitudes, which is largely consistent with increasing temperature, decreasing length of winter, and decreasing snowpack (Cayan et al. 2001; Westmacott and Burn 1997).

Given this past record of streamflow and precipitation, it is possible to say with

some confidence how streamflow will respond to future climate change. The projected warming and decreases in snow will make it likely that streamflow will shift from spring to winter in high latitudes. Total streamflow changes at high latitudes are less predictable because of the competing effects of increased precipitation and temperature. Total streamflow in subtropical regions is likely to increase due increased temperatures and decreased rainfall. Variability of flow is likely to increase due to increased variability in precipitation. Many of these changes have already occurred, as noted above. There is much greater uncertainty in predictions of how water reservoirs and water fluxes other than streamflow will respond to climate change because scientists lack the observations with which to calibrate their hydrologic models. Hydrologists need to go beyond modeling the streamflow response to precipitation changes and consider how other water fluxes and reservoirs respond to climate change. What is needed, at least, is an observational network of soil moisture, evapotranspiration, groundwater, and horizontal water fluxes (surface and subsurface) that is on par with the network of precipitation and stream gages. Even if an extensive hydrologic network is built, however, hydrologists are faced with the problem of forecasting hydrologic regimes and shifts that have not been previously observed. Projections of mean temperature for the end of the 21st Century exceed the range of current interannual variability in many regions. For example, in the Susquehanna River Basin, projected temperature increases for 2100 are from 2 to 4 deg ºC whereas past interannual variability is less than 0.5 ºC (Najjar 1999). Thus, hydrologists do not have the instrumental data record for evaluating how hydrological systems respond to temperature changes of this magnitude. The case is similar for the direct response of vegetation to CO2. In both cases, scientists mainly have measurements from laboratory studies and a few whole-ecosystem studies, such as the Free Air Carbon Enrichment (FACE) experiment. Even these data have their weaknesses because they simulate responses of ecosystems to instantaneous changes in temperature and CO2, whereas the actual perturbation will occur over many decades.

Three approaches to monitoring by today’s hydrologists will enable future

hydrologists to quantify the response of water fluxes and reservoirs to climate change.

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Foremost among these approaches is observation. Because vegetation influences many water fluxes, it is imperative that these observations will allow scientists to quantify ecosystem responses to climate change. For example, ecologists need to know the direct response of forest ecosystems to increases in temperature and CO2. Because the expected decadal and centennial time scale of the anthropogenic climate change is similar to that of forest turnover, it is essential to capture transient responses of ecosystems. Thus, hydrological monitoring should include indicators of ecosystem function, such as primary production, respiration, speciation, and age distribution. These needs are similar to programs that are currently monitoring the terrestrial carbon cycle (e.g., Billesbach et al. 2004; Birdsey and Heath 2001). For instance, Ameriflux is a network of towers that measures fluxes of carbon dioxide, water vapor, and sensible heat between terrestrial systems and the atmosphere. Hydrologists should build on existing capabilities to extract the maximum information about hydrologic processes at minimum cost.

Paleohydrologic reconstruction is the second approach to monitoring needed to

project future hydrologic responses to climate change. This field is still in its infancy, but furnishes a window into hydroclimatic regimes not observed during the period of observation, but which may occur in the future. Cronin et al. (2000), for example, developed proxies of salinity from Chesapeake Bay sediment cores to show that “megadroughts” have occurred during the past 1000 years in the Northeast. Tree rings and lacustrine sediment cores have produced similar findings. Again, efforts to expand current hydrologic reconstruction efforts can provide a large payoff for minimal cost.

The third approach to projecting future hydrologic states is numerical model

development. Improved modeling will result from the expanded monitoring network and paleodata base because modelers will need to contend with the increasing constraints placed on models by the new observations. Therefore, the problem of equifinality will be significantly diminished and confidence in future projections will be greatly increased. 3.0 BUILDING A HOLISTIC BASIN-SCALE CONCEPTUAL MODEL 3.1 Hydrologic Similarity Regions Climatic and human impacts on the landscape are large-scale phenomena. Large river basins, however, can span regions having different hydrology and ecology and thus require different land management strategies. “Hydrologic Similarity Regions (HSRs)” are large land areas defined by commonality in soils, topography, geology, climate, and vegetation. HSRs can span multiple watersheds and other traditionally defined natural regions. Large river basins in the Northeast, like the Susquehanna River Basin, are composed of multiple hydrologic similarity regions. Assessment of changing socioeconomic or climatic conditions on the hydrology of a large river basin requires an understanding of its impact within different hydrologic regions within the basin. Observations must be conducted across different HSRs and at multiple scales within HSRs to better define the roles that soils, vegetation, terrain, climate, and geology play in partitioning water, energy, and nutrients across the complex environmental systems that make up the river basin (Strayer et al. 2003).

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UPLAND

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groundwater

surface water

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flow direction

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Figure 3: The Fundamental Hydrologic Landscape Unit (adapted from Winter, 2001). Key challenges to understanding large river basin hydrology lie in the predicting the responses of ungauged portions of a basin and in scaling up from small watershed studies to descriptions of regional hydrology. One approach that will assist investigators within any basin, is to use classification systems to effectively compartmentalize both individual units and sub-basins that share common characteristics. Classification systems for streams (Hughes et al. 1986; Rosgen 1996), wetlands (Brinson 1993; Cole et al. 1997), and hydric soils (citation), for instance, can be used effectively to distinguish hydrologic differences among types and group like types into clusters that can be modeled uniformly. Dimensionless “similarity parameters” have been developed and tested for catchment hydrology (Burn and Boorman 1992; Castellarin et al. 2001; Woods 2003), groundwater hydrology (Petheram et al. 2003), and seasonality of climate (Castellarin et al. 2001; Woods 2003). The definition of “similarity”, however, can vary with individual disciplinary perspectives within hydrology: similarity with respect to geology (limestone aquifer, glacial outwash, fractured crystalline rock, etc.); to physiographic elements (mountainous valley, coastal plain, playa, etc.); or to climate (Mediterranean, humid, arid, etc.) depending on whether approached from a groundwater or surface water perspective (Winter 2001). A holistic approach is needed.

While the watershed provides well-defined boundaries for characterization and

study, groundwater and surface water basin boundaries may not necessarily coincide. Winter (2001) proposes the concept of the “Fundamental Hydrologic Landscape Unit (FHLU)” as a means to break any landscape down into its most basic form: upland and lowland separated by a steeper slope (Figure 3). Each FHLU’s specific characteristics, its land surface form, geologic framework, and climatic setting, control its hydrology (Figure 4). The land slope and soil permeability control surface water runoff and infiltration; permeability of the underlying geologic formations control its ground water flow; climate controls the availability and exchange of atmospheric moisture with the land surface. Watersheds can contain multiple FHLUs adjacent to or superimposed upon each other (Winter 2001). Figure 5 illustrates this concept for the Susquehanna River Basin. We must be able to pose and test scientific hypotheses regarding the importance of phenomena and process across multiple scales if we are to improve our ability to

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understand, forecast and mitigate the impacts of climate and anthropogenic change on local and regional water resources. Using the FHLU concept, it is then possible to pose and test hypotheses across FHLUs having similar or differing geology, physiography, or climate features that control water flow. Developing an understanding of hydrologic behavior at the FHLU scale will aid in developing understanding at the similarity region and large river basin scales. Although the FHLU concept provides a conceptual framework for comparing, contrasting, and synthesizing our understanding of hydrological systems, we must be careful to consider water quality, ecology, and land-use in when decomposing river basins into similarity regions.

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Figure 4: The FHLU in different geologic frameworks (a) fractured igneous and metamorphic rock; (b) limestone; (c) unconsolidated sediments (adapted from Winter 2001).

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DRAFT Figure 5: The Susquehanna River Basin spans multiple hydrological similarity regions (HSRs). The watersheds within each HSR contain multiple Fundamental Hydrologic Landscape Units (SRBHOS Partners 2004). PLACEHOLDER FIGURE 3.2 Links between Ecologic and Hydrologic Similarity Regions Hydrology has a central role in determining the ecology of a region. The same features that control hydrology - land surface features and form (soils, vegetation, relief), geologic framework, and climatic setting – cause regions of ecologic similarity to develop. Ecologic “Similarity Regions” are large areas that contain distinct assemblages of natural communities that have common species, dynamics, and environmental conditions. This concept of the ecoregion provides a biologically meaningful, geographically based framework for land management and conservation (Ricketts et al. 1999). Terrestrial ecoregions are based upon land surface form, climate, vegetation, soils, and fauna (Bailey 1978; Ricketts et al. 1999), and can span multiple river drainage basins. The Susquehanna River Basin, for example, is composed of a wide range of unique physiographic and ecologic terrains, including forested Appalachian headwaters, mixed forest-agricultural-urban land uses and karst terrain in the Ridge and Valley Province, and rapidly urbanizing lowlands in the upper Chesapeake Bay Piedmont and Coastal Plain regions. Figure 6 clearly illustrates the relationship between ecoregions and physiographic provinces in the Susquehanna River Basin is clear. The boundaries of freshwater ecoregions, by contrast, are closely related to large drainage basins, as freshwater species distribution tends to coincide with these basins (Abell et al. 2000).

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Figure 6: The Susquehanna River Basin’s (a) ecoregions and (b) physiographic provinces (from www.SRBC.net). PLACEHOLDER FIGURE

When taking a river basin approach, it is essential and efficient to have

information about all hydrologic elements of aquatic ecosystems; rivers, streams, floodplains, wetlands, lakes, and near-surface waters. Such a pre-condition poses challenges to those seeking to quantify water, energy, and solute budgets, requiring the integration of a variety of measurements derived from a range of methods and devices. For example, near-surface measurements used to characterize the hydroperiods of hydrogeomorphically diverse wetlands, which themselves are often a blend of surface runoff and groundwater discharges, must be linked to precipitation patterns and existing soil conditions in the contributing watershed. On-going research at Penn State and other institutions has identified several ways to capture the similarities among watersheds. Some techniques examine only physical properties (e.g., topography, precipitation, discharge, etc.) to create similarity clusters, whereas others add components of land use and vegetative cover to further refine the hydrologic responses in various classes. Concurrently, we have found that properly classified aquatic habitats, function similarly with regard to their hydrology and other ecological factors. The hydrogeomorphic (HGM) classification approach (Brinson 1993; Cole et al. 1997) is especially useful for placing wetlands in hydrologically comparable classes. Thus, having a few instrumented test beds for each major wetland class (e.g., headwater riverine, depression, fringing) allows one to extrapolate to similar units throughout the basin. The HGM approach has been applied across the physiographic regions of the U.S., and is applicable to wetland ecosystems anywhere in the world.

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Although hydrology may help drive the ecology, there is of course a feedback of the ecosystem on the hydrology. Evapotranspiration is a major process impacting the water balance and temporal variability of hydrologic systems. Interception of rainfall by vegetative canopy, creation of macro pores within the soil, and soil moisture dynamics all are dependent upon the nature of the flora in the ecoregion. The role of riparian vegetation structure and pattern on the hydrology and geochemistry of water within and exported from watersheds is reasonably well known (e.g., Baker et al. 2001; Gold et al. 2001; Weller et al. 1998). 3.3 Links between Land-Use Classes and Hydrologic Similarity Regions Development is related to the availability of adequate fresh water supply, whether through ample rainfall, large surface water bodies, or productive aquifers. Development has historically occurred along river and stream corridors. For example, the major population centers within the Susquehanna River Basin are located along the main channels (Figure 7). Large rivers may also be of key importance in electric power generation to support development, whether flowing in steep terrain to allow for hydropower generation or as a supply of cooling water for other power plant types. Two nuclear power plants are located along the main stem of the Susquehanna River: Three Mile Island in Harrisburg and Peach Bottom in Southern Pennsylvania.

Land use is, to some degree, dictated by the hydrologic setting of the land:

including land surface features and form, geologic framework, and climate. Suitability of land for agricultural use depends on flatness of slopes and soil—texture, structure, and infiltration capacity- while climate will influence which crops are feasible for cultivation in that location. Steep slopes, unsuitable for farming, will likely remain forested. Coal or other mining of the land is only possible where the geology framework supports it. Land use in the Susquehanna Basin shows dependence upon topography and soils (Figure 7) and physiographic province (Figure 6). With development comes changing land use, and a resulting feedback on the local and regional hydrologic cycle. Forest clearing for agricultural use, implementation of different farm management practices, or the reversion of agricultural land to forest all impact the surface and subsurface water flow pathways. Replacing permeable land with impervious pavement prevents infiltration and groundwater recharge and creates flashier surface stream response to storms. Zoning and land management choices, for exampling requiring detention basins for the control of storm flow, also alter the resulting hydrology. These activities, when imposed on a set of physical watershed characteristics, create stressors that impact aquatic biota and human health (Brooks et al. 1998; Bryce et al. 1999) and should be considered when developing similarity-based conceptual models for river basins.

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Figure 7: The Susquehanna River Basin’s (a) topography, (b) average annual precipitation, (c) soils, and (d) land cover. (from www.SRBC.net). PLACEHOLDER FIGURE

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3.4 Links between Soil and Hydrologic Similarity Regions Storages, pathways, and residence times of water fluxes in the soil zone exhibit identifiable spatial distributions and temporal stability, possibly with interacting spatial and temporal dimensions. This spatio-temporal persistence of water fluxes can be used to subdivide landscapes into similarly-functioning soil hydrologic units. The functional unit concept based on functional characterization of 4-D (3-D + time) soil units within fields allows reliable quantification of fluxes within those fields. Hydrologically similar soil-landscape units exist within watersheds and these can be identified using traditional and new techniques and data sources. Soil-landscape relationships and soil hydrologic characteristics can be used to expand Winter’s (2001) concept of “fundamental hydrologic landscape unit.” A holistic conceptual framework calls for defining quantitative relationships between soil structure and hydrologic functions at various scales and the incorporation of such relationships into robust models for prediction. Figure 8 illustrates four intertwined components identified for this framework: (1) Structure determines physics (processes/functions), (2) Physics (processes/functions) determines an appropriate notion of scale (physical scale), (3) Scale determines variability and pattern, and (4) Variability or pattern determines suitability of model formulations and predictions.

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Figure 8: A multiscale framework for soil and hydrologic systems: At each scale illustrated, structure reflects states or properties (much like roads); function indicates fluxes or processes (much like traffic). The two-way connection between the two is dictated by scale, which also determines the variability or pattern of the system. The model at each level integrates all. The challenge is to build the bridge connecting different scales.

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Translating information about soil and hydrologic processes and properties across scales has emerged as a major theme in contemporary soil science and hydrology. Scale transfer remains at the heart of many hydrologic and pedologic studies. As remote sensing techniques for estimating large-area soil and hydrologic properties and in situ measurement for point-scale information continue to be developed, bridging multiple scales becomes even more prominent. At present, no single theory emerges that is ideal for spatial aggregation (or upscaling) and disaggreagation (or downscaling) of soils and hydrologic information. The major contenders seem to be either scaling via a naturally-defined or human-defined hierarchy or through potential continuous hierarchies as suggested by fractal theory (e.g., Cushman 1990; Lin 2003; Lin and Rathbun 2003; Sposito 1998; Vogel and Roth 2003; Wagenet 1998).

Hierarchical frameworks have been conceptualized by soil scientists as a means

for organizing multiple spatial and temporal scales from the soil pore to the pedosphere (Figure 9a) (Hoosbeek and Bryant 1992; Wilding 2000). Hierarchical complexity has been studied in pedology, which has long recognized self-organized complexity in the processes of soil formation, with taxonomic frameworks constructed to summarize that ordering (Buol et al. 2001). However, quantitative hierarchy of soil systems (e.g., soil-landscape structures) that could be coupled into models of flow, scaling, and rate processes is still lacking. If properly constructed, a hierarchy of soil systems should reflect logical links and quantitative relationships among scales. It can be argued, however, that the soil scientists’ hierarchy of scales is more an operational or observational device, based on the ability or feasibility to measure, rather than fundamental differences in basic processes (Wagenet 1998). As suggested by Wagenet, an examination of ecological hierarchy theory (Haigh 1987; O'Neill et al. 1986; O'Neill et al. 1989) should present some valuable philosophical and practical concepts pertaining to the translation of information across scales in soil systems. Hierarchy theory in ecology defines “holons,” which are nested spatial units characterized by integrated biological, physical, and chemical processes (Haigh 1987). In comparison, soil science uses entities that are less well defined and procedures that are less integrated. Lin and Rathbun (2003) discussed two hierarchical frameworks for bridging multiscales in hydropedology through either data-driven or process-based approaches (Figure. 9). In the first, the soil mapping hierarchy depicts soil spatial distribution over landscapes of varying sizes, considering five orders of soil surveys, spatial aggregations of soil map units, and various applications of geostatistics. The merger of geostatistics with traditional soil mapping has led to encouraging new developments of environmental correlation modeling and landscape-guided soil mapping. In the second, the soil modeling hierarchy deals with soil process models at different scales. While the current generation of surface and subsurface process models is strongly scale-dependent because of process representations, parameter requirements, and changes of support in model variables, several approaches are available for scale bridging, including upscaling, downscaling, upscaling with downscaling embedded, strategic cyclical scaling, and strategic spatial scaling (Lin and Rathbun 2003; Mulla and Addiscott 1999; Root and Scheider 1995).

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Figure 9: Two hierarchical frameworks for bridging multiscale: Hierarchies of (A) soil mapping (for soil distributions) and (B) soil modeling (for soil processes). SSURGO, STATSGO, and NATSGO are county-, state-, and national-level soil maps, respectively.

In moving beyond the notion of “trying to model everything,” we should be developing methods to identify dominant processes that control pedologic and hydrologic responses in various environments at different scales, and then develop models to focus on these dominant processes (a notion called the “Dominant Processes Concept”) (Grayson and Blöschl 2000). The grand challenge of river-basin science is then to design observing systems where the all of the dominant or critical fluxes and states can be observed coherently and at the appropriate scale. This will require a synthesis of observing system and multi-scale science to develop a multi-scale, multi-process observation network of watershed scale experimental sites chosen from existing and new locations, such that the similarity regions of river basins are represented (i.e., regions with “similar” physiographic, ecologic, geologic, and anthropogenic characteristics). A community wide effort within the hydrologic sciences to holistically characterize the similarity regions of major river basins within the United States will provide coherent, long-term data sets that can help resolve human and climatic impacts on water resources systems and improve federal, state, and local water management decisions. 4.0 MULTI-SCALE, MULTI-PROCESS OBSERVATION PLATFORMS [Chris Duffy text]

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5.0 OUTSTANDING NEEDS A paradigmatic shift within the hydrologic sciences which embraces cross-disciplinary basin-scale problems will dramatically improve water management practices through the holistic assessment of the atmospheric, land surface, and subsurface processes that characterize a basin from headwaters to estuary. In order to advance a comprehensive approach to river-basin science that integrates atmospheric, land surface and subsurface processes, and their control of river-basin responses to human and climatic forcings, will require a substantial investment in shared research infrastructure, a comprehensive scientific agenda, and a new generation of information and data publication strategies. A coherent framework is needed to promote cross-disciplinary collaboration from the level of the individual researchers up to the scale of community-wide initiatives for the hydrologic sciences. 5.1 Building a Hydrologic Data Grid Cross-disciplinary, community-wide collaboration can be achieved by explicitly designing the CUAHSI HO network using the data grid framework (National Science Foundation Blue Ribbon Advisory Panel on Cyberinfrastructure 2003) The term data grid refers to “…building infrastructure to enhance our capacity to monitor and respond to changes in our environment by developing both the [sensor] networks and the integrated, seamless, and transparent information management system that will collect and stream data… to a variety of end users in real-time”(Braun et al. 2002). A national data grid for the hydrologic sciences can be established by developing federated networks of real-time sensors and data repositories as illustrated in Figure 10. A federated sensor and information management architecture will allow researchers to define site specific sensor configurations and data management strategies best suited to local infrastructural constraints and the scale of scientific processes as long the systems satisfy software and communication protocols defined by the broader hydrologic community. The protocols will promote multi-scale, multi-process observatories in the sense that climatic, vegetative, topographic, and hydrogeologic elements of characteristic landscapes within river basins can be resolved at the appropriate space-time scales necessary to support specific scientific goals. Federation of sensor communication and software protocols will allow network design teams to collect a core of integrated weather, soil, groundwater, and surface water data in manner best suited to existing scientific infrastructure within observed watersheds.

The CUAHSI initiative must provide the empirical investigations to define sensor

communication protocols and train scientists to utilize state-of-the-art real-time systems to initiate long-term historical data records for basin-scale processes. When establishing global network design protocols, CUAHSI needs to better incorporate the network design experiences of existing large scale environmental monitoring initiatives. For example, the federated architecture illustrated in Figure 10 is currently being employed within the NSF-supported Real-time Observatories, Applications, and Data Management Network (ROADNet) project for integrated monitoring of weather, soil properties, water quantity and quality. ROADNet’s real-time data grid protocols (Braun et al. 2002; ROADNET

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2002) for autonomous field sensor networks are a generalization of the approaches first successfully employed by the seismic community for building a national network of real-time event detection observatories (A-Amri and Al-Amri 2000; Braun et al. 2002; Harvey et al. 1998).

Onsite

Figure 10: Illustration of federated architecture for nested basin observation (adapted from ROADNet http://roadnet.ucsd.edu/). 5.2 Embracing New Technology The tremendous variability of the scales and processes impacted by human and climatic changes within river basins make it vital for CUAHSI to facilitate the development a new class of hydrologic observation infrastructure that incorporates recent developments in the areas of Networked Infomechanical Systems (NIMS) and embedded computing (Kaiser et al. 2004). The focus of this research is to create scalable, energy aware networks of multi-hop, wireless sensors and micro-field computers. The term multi-hop refers to the use of sensor nodes connected to microprocessors with onboard low-frequency radios for data storage, transmission, and reception. NIMS-based multi-hop, wireless sensing technologies will likely evolve to be the dominant mode of in-situ, real-time sensing. In broad terms, these technologies will promote the transformation of our national cyberinfrastructure towards Tera-scale ubiquitous computing and data grid applications. The National Science Foundation’s Blue Ribbon Panel on Cyberinfrastructure has recommended a $1-billion investment in the next decade to

Site specific sensor configuration

Site specific sensor configuration

Site specific sensor configuration

Watershed 1

Buffer

IP Converter

Watershed 2

IP Converter

Watershed 3

IP Converter

Internet-based Data Synthesis, Transmission, &

Archiving

Onsite Buffer

Real-time clientsOnsite Buffer

Offsite Archival Buffer

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facilitate this transformation (National Science Foundation Blue Ribbon Advisory Panel on Cyberinfrastructure 2003).

The hydrologic sciences need to exploit these sensing and data management technologies to overcome the current cost and communication barriers limiting the spatiotemporal resolutions of hydrologic datasets. Initial applications of these wireless systems at hydrologic and ecologic experimental sites have shown that low per node costs and wireless data transmission enable dense distributions of real-time sensors in space capable of unattended monitoring of complex multi-process, multi-scale systems (Batalin et al. 2004; Cerpa and Estrin 2004; Kaiser et al. 2004). CUAHSI needs to explicitly promote wireless in-situ sensing technologies to increase the spatiotemporal monitoring capabilities of the national HO network. Basin-scale observation systems with dense spatial resolution will require autonomous sensing and coherent real-time streaming of diverse data in order maintain feasible system management and maintenance costs for basin-scale observation systems. The national CUAHSI Synthesis, Measurement Technology, and Information Systems teams need develop data grid protocols for basin design teams that will facilitate the long-term evolution of HO infrastructure towards spatially dense real-time sensing. HO’s should serve as test beds for emerging sensing technologies that will reduce the sensor and data management costs while enhancing the long-term reliability of the hydrologic data grid initiated by CUAHSI. The CUAHSI HO network should be designed using an evolving observation network design paradigm, where it is recognized that observation technologies and scientific agendas evolve. The long-term value of the directed research infrastructure within HO’s will depend on their ability to adapt to emerging scientific agendas and innovations in sensing technology. 5.3 Linking Nested Observatories A comprehensive strategy for basin-scale hydrologic system observation requires the augmentation of the nested HO’s with an infrastructure including a network of near-real time environmental observation stations sited at key points throughout the basin as well as a strategy to secure remotely sensed observations at spatial and temporal scales that support the intensive observations made at individual HO’s and with the near-real time network. Near-real time environmental observations are critical to developing a comprehensive understanding of the coupled water and energy budget at the basin scale. Following the pioneering work by the Oklahoma Climate Survey’s Mesonet, the environmental network that we envision as part of the HO is a network, a mesonet, of automated environmental observing stations that collect information on air temperature, relative humidity, wind speed and direction, barometric pressure, rainfall, solar radiation, soil moisture and temperature and air quality Figure 11. These observations would be collected every 5 minutes and then relayed, via advanced wireless communication networks, to a central collection facility in the HOfor data processing, analysis and sharing with users in forms that can be used in a variety of decision making activities.

The locations of individual Mesonet stations would be determined through a detailed analysis of the distribution of combined physiographic factors (soils, vegetation, topography, and climate) within the basin. Some stations within the Mesonet are

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envisioned as “super” sites which will contained an enhanced set of instrumentation for complete measurement of water, energy, and mass fluxes. Each HO testbed would have at least one co-located Mesonet station. Where feasible, Mesonet stations could also be co-located with stream gauging stations on the basin main stem or tributaries.

Figure 11: A typical Mesonet observation station. PLACEHOLDER FIGURE The development of comprehensive water, energy, and mass budgets for the basin will require the timely coordination and acquisition of remotely sensed observations at spatial and temporal scales that provide a bridge between in-situ observations within the basin. Observations from satellite and aircraft provide information on land surface variables related to the terrestrial hydrologic balance including vegetation/land cover status, soil moisture, surface temperature, and precipitation. Remote sensing provides a spatially integrated view of the land surface that bridges the often limited, site-specific observations that can be made at ground observation locations. When validated with in-situ information, remotely-sensed observations can be used to improve our understanding of land surface hydrology processes including measurement of key parameters like soil moisture and precipitation These remote observations provide important insight into land surface hydrologic processes as well as natural and human impacts to land surface cover conditions including modifications due to natural occurrences (plant disease impacts or major vegetation damage from hurricanes or other severe atmospheric events) or human modification (urban development, surface mining, timber harvesting) and to extend our knowledge of land surface hydrology and hydrologic processes to ungauged basins with similar land surface characteristics. The HO will require a well-organized infrastructure for capture, processing, and maintenance of the relevant, complementary remotely sensed observations from the wide range of government and commercial satellite and aircraft platforms that regularly collect

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data over the HO. This infrastructure will be an integral part of the overall information system dedicated to the HO and will leverage heavily from the standard products and resources developed by satellite programs such as NOAA’s current National Environmental Satellite, Data, and Information Service (NESDIS) and their developing NPOESS program, NASA’s Earth Observing System (EOS), and the growing number of commercially available remotely sensed products from the private sector. The in-situ infrastructure will also provide opportunities for the development of focused field campaigns with aircraft and satellite remote sensors. These campaigns provide testing grounds for validating new sensors and sensor combinations with the high quality in-situ observation network.

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