An Agenda for Land Surface
Hydrology Research and a Callfor the Second International
Hydrological Decade
Dara Entekhabi,* Ghassem R. Asrar,+ Alan K. Betts,# Keith J. Beven,&
Rafael L. Bras,* Christopher J. Duffy,@ Thomas Dunne,** Randal D. Koster,++
Dennis P. Lettenmaier,## Dennis B. McLaughlin,* William J. Shuttleworth,&&Martinus T. van Genuchten,@@ Ming-Ying Wei,+ and Eric F. Wood***

ABSTRACT
Hydrologic research at the interface between the atmosphere and land surface is undergoing a dramatic change infocus, driven by new societal priorities, emerging technologies, and better understanding of the earth system. In thispaper an agenda for land surface hydrology research is proposed in order to open the debate for more comprehensive
prioritization of science and application activities in the hydrologic sciences. Sets of priority science questions are posed
and research strategies for achieving progress are identified. The proposed research agenda is also coupled with ongoing international data collection programs. The driving science questions and related research agenda lead to a call forthe second International Hydrologic Decade. This activity will help to ensure that hydrology starts the new millennium
as a coherent and vital discipline.

1. BackgroundHydrologists are facing important, even fundamental, changes in the direction of their science. New tools,
nontraditional datasets, and a better understanding of the*Massachusetts Institute of Technology, Cambridge, Massachusetts.
+
National Aeronautics and Space Administration Headquarters,
Washington, D.C.
#
Atmospheric Research, Pittsford, Vermont.
&
University of Lancaster, Lancaster, United Kingdom.
@
The Pennsylvania State University, University Park, Pennsylvania.
**University of California, Santa Barbara, Santa Barbara, California.
++
National Aeronautics and Space Administration/Goddard Space
Flight Center, Greenbelt, Maryland.
##
University of Washington, Seattle, Washington.
&&
The University of Arizona, Tucson, Arizona.
@@
U.S. Salinity Laboratory, U.S. Department of Agriculture, Riverside, California.
***Princeton University, Princeton, New Jersey.
Corresponding author address: Dara Entekhabi, 48-331 MIT,
Cambridge, MA 02139.
E-mail: darae@MIT.edu
In final form 26 March 1999.
©1999 American Meteorological Society

Bulletin of the American Meteorological Society

connection between hydrology and the rest of the climate
system are being developed just as society’s needs for
improved water management and hazards prediction
are becoming critical. The application of new ideas andtechniques to the difficult hydrologic problems of the
future will require a carefully formulated plan of attack.
Water at the land surface is a vital resource, bothfor human needs and for natural ecosystems. Society’s
growing water resource needs include hazard mitigation (floods, droughts, and landslides), agriculture andfood production, human health, municipal and industrial supply, environmental quality, and sustainable development in a changing global environment.
Desertification and drought are problems of global dimension that affect more than 900 million people in
100 countries. Irrigation already accounts for morethan 70% of freshwater withdrawn from lakes, rivers,
and groundwater aquifers, and perhaps 80% of theadditional food supplies required to feed the world’s
population in the next 30 years will depend on irrigation (UN-SWI 1997). Today, about one-third ofworld’s population live in countries that are experiencing moderate to high water stress, that is, renewablefreshwater availability is below 1700 cubic meters per2043

person. By 2005, projections suggest that one-fifth of
the global population will not have access to safe
drinking water, and more than one-half will lack adequate sanitation (UN-SWI 1997).
Despite the emergence of advanced technology
both developed and developing countries will probably feel the effects of limited freshwater resources in
the near future. Economic growth and social welfare
in major urban centers of the semiarid United Statesand other megacities in the industrialized and industrializing worlds will be affected by hydrometeorological hazards as well as by limited water availability. In
fact, floods and droughts are considered by some tobe the leading natural threats to society in many countries (NRC 1996). Global environmental changes
brought about by land-use modifications, desertification, and anthropogenic greenhouse trace gas emissions are intimately connected with water at the land
surface. The ultimate impact of such changes is highly
uncertain and difficult to predict.
The new hydrological tools available to address
water resource problems are largely a reflection oftechnological advances in environmental monitoring
and computation. Satellite remote sensing provides,
for the first time, the potential for global coverage ofcritical hydrological data (e.g., precipitation, soil moisture, and snow water content). Such global data are logistically and economically impossible to obtain throughtraditional in situ measurement. However, remote sensing datasets are in forms unfamiliar to many hydrologists,largely because the measured quantities are radiancesthat are only indirectly related to the hydrologic variables of most interest. Computational advances havemade it possible to develop new data processing andassimilation techniques that are able to extract useful
information from these indirect measurements.
In addition to new types of data, hydrologists areencountering a new intellectual paradigm that emphasizes connections between land surface hydrology andother components of the earth system (NRC 1991).
This coupling is now widely considered to be essential. It has already led to significant changes in the research and training foci for the discipline.
The continuing shifts in hydrology, driven by new
tools and intellectual paradigms, should not take placeblindly. The hydrological community must take stock of
the current state of knowledge, prioritize the emerging
science questions for the coming decade, set objectives, and identify data needs and standards. This paper, which proposes an agenda for land surfacehydrology research at the beginning of the new mil2044

lennium, is a response to the challenge facing the hydrologic community. The authors collaborated voluntarily, and no institution or agency supported orcommissioned the work. Our purpose is not to claim theagenda but to open the debate. Although our scientificpriorities are focused on the land surface–atmosphere
continuum, the authors hope that this initiative may
serve as an example for other areas of hydrology. The
land surface hydrology agenda we propose originates inthe science questions posed in section 2. These questions
reflect ideas and experiences communicated throughthe existing hydrologic literature. For the sake of clarity,and in order to reduce the need for expanded discussions, the science questions are raised and discussed
without specific references. These questions imply awhole set of data and modeling needs that will requirecommitment of both economic and human resources.
In section 3 we explore these needs and identify important priorities for hydrologic research and development.
In section 4, we propose a concerted effort to answer the science questions and to achieve the research
objectives we have identified. We call this effort theSecond International Hydrological Decade (2d IHD).
The 2d IHD is intended to engage the research community in its efforts to develop effective tools for translating of data into useful information. Key objectivesof the proposed 2d IHD are 1) to develop feedback
between the research community and agencies responsible for water-related research and 2) to provide an
intellectual framework that can be used to guide management decisions, including decisions related to theallocation of research funds.
Land surface hydrology is a discipline throughwhich many of the emerging advances in monitoring,
computation, and telecommunications may be brought
to bear on food supply, health, security, and development issues facing Earth’s growing population. This
promise may only be realized if hydrologic data collection and modeling activities are based on soundscientific principles. This is the overall objective of thescientific agenda we propose.
2. Priority science questions
a. What are the mechanisms and pathways bywhich the coupling between surface hydrologic
systems and the overlying atmospheric modulate
weather and climate variability?
The exchanges of moisture and energy between
soil, vegetation, and snowpack and the overlying atVol. 80, No. 10, October 1999

mospheric boundary layer have impacts on near-surface about by the introduction of improved land surface
atmospheric moisture and temperature. These in turn characterization and initialization in an operationallargely define regional climate. For example, when soil numerical weather prediction model. At longer leadmoisture or plant stomatal closure limit latent heat times, deeper soil storage and plant root distribution
flux, the near-surface atmospheric humidity deficit and may affect prediction skill. Studies of surface and subtemperature are increased. This leads, in turn, to el- surface water budgets are needed to better describe theevated growth of the boundary layer and enhanced surface water–groundwater interactions that operate
entrainment of relatively warm and dry air. The over- over these longer timescales.
all process constitutes a positive feedback mechanism
It should be recognized that hydrologic states suchfor continued surface drying.
as soil moisture and snow cover influence the surface
The behavior introduced by such multivariate cou- flux of moisture and energy only under a limited set
pling and feedback may lead to excursions, oscilla- of conditions that depend on surface properties and attions, and persistence of hydroclimatological mospheric forcing (see Fig. 3). There are timescales
anomalies (e.g., extreme precipitation, droughts, etc.; (i.e., storm, interstorm, and seasonal) and geographic
see Fig. 1). These phenomena cannot be accounted for regions in which fluxes of moisture and energy are
in analyses or models that force the various compo- essentially independent of land surface moisture.
nents of the land–air system inisolation. The contributions ofland–atmosphere coupling toregional anomalies such as continental droughts (e.g., 1970s
Sahel or 1988 U.S. Midwest)
and large-scale flooding precipitation events (e.g., 1993 U.S.
upper Midwest) need to be established and quantified. Bothobservations and models canhelp in this endeavor. The timescales associated with the surface and subsurface storage ofmoisture depend in complex
ways on both climate and geology. These connections need to
be clarified if we are to develop
a better understanding of connections between the landscape,hydrologic response, and thepersistence of climate anomalies.
Hydrologic states that have
FIG. 1. Relative influences of sea surface temperature (SST) on boreal summer precipilong memory or serve to integrate past atmospheric forcing tation. (a) Observed precipitation over the continental United States for summers containmay be used to enhance predic- ing the extreme 1988 drought and 1993 flood events are presented as a difference field. (b),(c), (d) General circulation model results for the same differences between rainfall during
tion skill for regional climates. the 1993 flood and 1988 drought events are shown. (b) Both SSTs and soil moisture fields
For example, the short-term are either observed or estimated for the specific period of simulation. (c) Estimates of soil
evolution of weather events is moisture for the particular time period are used in conjunction with SST climatology. (d)affected by fluxes (e.g., summer- Observed SSTs are used as boundary condition for the simulation in conjunction with estitime precipitating convection) mated soil moisture climatology. This figure demonstrates both the impact of soil moisturethat depend on surface states on the numerical forecasting of the extreme events and the notion that surface soil moistureis equivalent in importance to SST as boundary conditions for the climatic system. It is evisuch as soil moisture and tem- dent that precipitation extremes over the United States are more strongly affected by soil
perature. Figure 2 shows the moisture fields than SSTs, which are currently the principal fields used to extend forecast
gains in forecast skill brought lead times (M. Suarez, S. Schubert, and A. Chang 1999, personal communication).
Bulletin of the American Meteorological Society

2045

FIG. 2. Threat scores (a measure of forecast skill) for 36-h forecasts of 24-h accumulated precipitation as a function of precipitation threshold. The bottom curve shows the relationship obtained
when the prediction system uses a standard bucket model initialized with climatological soil moisture values. The upper curveshows the relationship obtained when the bucket model is replaced
by a more sophisticated land surface scheme and the soil moisture is more realistically initialized from reanalysis data. The combination of improved model physics and improved initialconditions for soil moisture has led to significantly improved
weather prediction. The improvement seen here is of the sameorder as that obtained from doubling the resolution of the atmospheric model (K. Mitchell 1999, personal communication).

There is a need to identify and investigate climatic
regimes that prevent surface conditions from influencing fluxes into the lower boundary of the atmosphere.
The seasonal cycle and interannual variability of eachof these regimes need to be understood as a prerequisite for predicting variability in regional climates.
A critical problem in coupled land–atmosphereprocess studies is the need to define appropriate system boundaries (see the heat and moisture budget
example in Fig. 4). Air entrainment associated withthe large diurnal variations of the atmospheric boundary layer is a significant factor in surface energy andmass balance. These processes need to be better understood if we are to substantially improve our ability to predict either atmospheric or land surfacehydrologic processes.
Over larger scales and over longer periods, theconvergence of moisture and static energy across the2046

FIG. 3. Evaporation following rainstorms and soil wetting proceed through several stages. In the first stage, although soil moisture is steadily depleted by evaporation (equal to the so-called
potential evaporation, ep), the rate of evaporation is limited only
by available energy to vaporize liquid soil water and it is essentially independent of soil moisture content. During the early period of the day or across high-latitude regions where available
energy may be the limiting factor, this first phase may extend up
to the next wetting event. Similarly, in climates with frequent wetting events, the first stage may dominate much of the time. During
the second stage of evaporation, lower levels of soil moisture limit
the movement of water in the soil to supply evaporation at thesurface. The transition from the first to the second stage occurs at
the time to drying (td), which depends on soil texture and climate.
The figure shows field experiment observations by R. D. Jackson
and the applicability of a model of the process by Salvucci (1997).
The soil drying effect and the time to drying are evident in thealbedo observations (lower plot). During this phase of evaporation soil moisture exerts strong influence on latent heat flux, surface energy balance, ground temperature, and the near-surface
atmosphere states. In a third stage (not evident in this experiment),
the evaporation rate is dominated by vapor flow driven by thermal gradients within the soil column. The influence of soil texture, vegetation, and atmospheric forcing on the timing of thetransitions between evaporation regimes, and the effects of spatial and temporal aggregation on modeling the phenomena are not
yet well established.

depth of the troposphere are strong constraints on regional hydroclimatology and on the atmospheric convergence of moisture and energy. Aspects of this effectmay be monitored remotely (e.g., top-of-atmosphereradiation may be measured easily and accurately with
Vol. 80, No. 10, October 1999

satellite sensors). Constraints on atmospheric convergence need to be better
understood and, if possible, used to provide better estimates of fluxes in the atmospheric branch of the hydrologic
cycle.
b. What are the mechanisms and thetimescales of interactions between
the formation of terrain, soils,
vegetation ecotones, and hydrologic
response?
The terrain, soil, and vegetation of
the land surface all have important anddirect effects on hydrologic response.
Conversely, surficial hydrologic processes influence the development ofthese landscape characteristics. Thesemutual interactions between landscape,soil, and vegetation, on the one hand, andhydrologic processes on the other, occur
over a wide range of timescales. In somecases the hydraulic properties of soils,
including soil seals and macropores, maychange over seasonal or annual scales in
response to human activity. But soil conditions in environments not disturbed byhumans seem to be controlled by longerterm processes that are driven by ecosys-

FIG. 4. Surface water and energy budgets are strongly coupled to the mixed
atmospheric layer above the surface. In some applications it may be important toinclude the mixed layer water and energy budgets together with that of the surface. This is effectively redefining the control volume or the system boundaries
for budget calculations. In the top panels the profiles of specific humidity (q) andpotential temperature (θ ) are shown conceptually for two time periods during the
growth phase of the mixed layer. In plot (a) the results of surface input into themixed layer are considered in isolation. Evaporation (E) and sensible heat flux(H) contribute to increase the q and θ of the mixed layer with height (h). If the h isfixed, the profiles of the variables at the new time follow the dashed lines. However, the h grows during the time period in response to thermals originating fromnear the surface. When the mixed layer grows to the new height (h + dh), dry andwarm air is entrained into the mixed layer as depicted in plot (b). This growth in hcontributes dry air to the mixed layer partially counteracting the moistening effect of surface evaporation. In contrast, the entrainment of air with higher θ fromaloft, similar to surface sensible heat flux, contributes to increase the mixed layer
θ. As a result, often times the diurnal range of q in the mixed layer is small andthe diurnal range of θ is large. This is evident in the lower panel where averagesof diurnal coevolution of the two variables are plotted for a set of days with different mean soil moisture (SM) but similar net radiation conditions across the FirstInternational Satellite Land Surface Climatology Project (ISLSCP) Field Experiment site in Kansas (from Betts and Ball 1995). The diurnal range of q is small
and the curvature is reminiscent of the early-day evaporation input into a shallow

Bulletin of the American Meteorological Society

mixed layer, and decrease during the latter part ofthe day when there is more rapid growth of themixed layer into drier portions of the atmosphere.
The potential temperature, θ, has a larger diurnal
amplitude. The amplitude of the diurnal cycle inθ is larger for days with drier land surface conditions when the surface sensible heat flux andgrowth of the mixed layer due to thermals originating from the near surface are dominant factors.
Since the surface turbulent fluxes (E and H) are
driven by the gradient between the surface moisture and temperature states and those in the nearsurface atmosphere, the coupled evolution ofthese states at the land surface and within themixed layer may contain important feedback
phenomena.

2047

tem change. The development of distinct soil horizons
with different topographic contexts is a process thatspans centuries.
Vegetation and hydrologic processes are linked
over an even wider range of time- and space scales.
A substantial fraction of the hydrologic exchange between the soil and the atmosphere is mediated by vegetation. Conversely, moisture availability is a key
factor in the development and distribution of ecotones.
The representation of vegetation in hydrologic
models and the consideration of its influence on thehydrologic cycle remain at rudimentary levels. Somepossible areas of improvement include better representation of the limitations imposed by nutrient deficits.
This will require incorporation of nutrient cycles, especially the nitrogen cycle, in models that account for coupling between hydrologic and ecological processes.
The commonly used resistance-network representation of plant control on moisture flux should be replaced with coupled physical and chemical models ofwater uptake by roots, moisture transport within xylem, and reaction processes within leaves. The physical characteristics and structure of vegetation stands
need to be explicitly represented in ways that make itpossible to directly observe model parameters withremote sensing instruments (e.g., lidar and radar).
Furthermore, radiance measurements in regions of thespectrum where photosynthesis captures solar radiation should be used to provide strong constraints onland data assimilation algorithms in regions with vegetation cover.
In addition to studies of how plant physiology andtranspiration respond on short-term timescales, investigations into the longer-term coevolution of ecotones
and hydroclimate are needed. The amplitude of thecomponents of surface water and energy balance depend on vegetation function. Furthermore, some interannual variability of hydrologic processes and, on
paleotimescales, shifts in climate are associated withecotone successions and variations. The nature of theseassociations needs to be understood, and their geologic
and geochemical fingerprints need to be uncovered.
The coevolution of the hydroclimatic and biosphericsystems hints at the possibility (requires further study)
that coupled ecological–climate models may in fact beaffected by ecotone initialization, that is, different initial specification of vegetation types leads different
equilibrium climate–vegetation regimes (Pielke 1998).
We need to better understand the extent that different
initial specifications of soils and vegetation can leadto distinct climatic regimes. This can be done with the2048

help of long-term coupled models of climate, hydrology, and ecology.
Field experiments need to be conducted to clarify
the many complex interactions among soil, vegetation,and hydroclimate. Coupled models need to be developed to reveal the effects of feedbacks, nonlinearities,
and multiple timescales. Field and modeling studies
should be directed toward a more integrated understanding of the genesis and joint evolution of topography, soils, vegetation, and hydroclimate.
c. Are there critical scales at which spatial
variations in surface properties should be
explicitly represented in models of land–
atmosphere exchange? Can macroscaleequations be formulated by upscaling processdescriptions at the microscale and under what
conditions can effective parameters be used torepresent upscaled hydrologic processes?
Some hydrologic processes such as runoff are significant only because there is heterogeneity in the natural system. Most homogeneous soil textural classes
have sorption rates that exceed generally observed rain
intensities. They also have sufficient storage to contain an entire rainstorm. Nonetheless, flood runoff
occurs due to the intermittent nature of rainstorms andthe occurrence of low-permeability soil patches, rockoutcrops, low transmissivity profiles, and high topographic convergence zones.
Temporal, as well as spatial, heterogeneity can beimportant in many hydrologic applications. In somecases, simple aggregation of temporal fluctuations canmisrepresent important physical processes. For example, multistage evaporation and transitions fromflux to ponding surface infiltration boundary conditions are processes that cannot be aggregated in time
without introducing errors (see Fig. 3).
In all hydrologic investigations, it should be natural to first identify the critical time- and space scales
at which heterogeneity should be explicitly represented. Such scales typically vary for each hydrologic
process and for each application (see Fig. 5). There isa critical need to develop a systematic framework forthe identification of critical hydrologic scales and thedependence of these scales on mean conditions. In
many cases, including the runoff generation example
given above, the relevant scales of natural heterogeneity span a wide range of time- and space scales. It is
often not feasible to characterize variability over suchwide ranges with available in situ or even remote sensing instrumentation. In such cases, models designed
Vol. 80, No. 10, October 1999

to predict macroscopic variables such as watershed
runoff (e.g., hydrograph) need to account indirectly forthe effects of unresolved heterogeneities. This process
is frequently referred to as “parameterization” or“upscaling.”
Successful field-scale parameterizations need to be
based on a good understanding of microscale (often
pore scale) physics as well as realistic characterizations of heterogeneity. They also should account for
nonlinearities and scale interactions. A number ofmathematical upscaling procedures have been appliedin various branches of hydrology. In some cases, theseprocedures yield macroscale equations that have thesame structure as microscale equations but with modified parameters. These “effective parameters” typically depend on the statistical properties of theunresolved heterogeneities as well as other sitespecific variables.
For example, pedotransfer functions have been
proposed as a means for assigning effective hydraulicproperties to soils based on taxonomic units that are
differentiated by parent geology, minerology, texture,bulk density, and organic matter content. These functions may be viewed as a first step in a sequential process of upscaling hydrologic processes from porescales to hillslope scale. Nonetheless, important issues
need to be resolved with respect to the design and application of pedotransfer functions. The effects ofstructured soils, soil chemistry, vegetation, climate,
and topography all need further study. Also, attention
should be devoted to methods for combining multitemporal and multispectral remote sensing with traditional sources of soil taxonomic data.
A number of theoretical and field studies have suggested that there may be hydrologic processes thatelude upscaling with an effective parameter approach.
Alternative procedures for upscaling microscale equations for such processes need to be established moreformally than is done at present. The resulting fieldscale models need to be tested with carefully designed
experiments.
Although upscaling is required in many hydrologic
applications, it should be noted that natural heterogeneity is often evident at scales that are close to the scaleat which it is feasible to explicitly represent them innumerical models. Hydrologic processes that vary on
scales that may be feasible to model explicitly include
variations of snowpack with topographic aspect, variations of evapotranspiration with topographic gradients,
variations in vegetation, boundary layer mixing andland-breeze circulations with surface cover changes,
Bulletin of the American Meteorological Society

FIG. 5. High-resolution in situ observations of the soil moisture field in the small (0.1 km2) Tarrawarra experimental catchment, southeastern Australia, demonstrates the role of competinghydrologic processes in defining spatial structures in the soil
moisture field (Western and Grayson 1998). (top) The volumetric moisture content within the top 30 cm of soil during a typical
wet season day (27 Sept 1995). In this case soil moisture patternis organized by terrain elevation. The wetter zones follow elevation contours and drainage depressions. High hydraulic conductivity of moist soils allows significant redistribution along a
topographic gradient. During a typical day in the dry season (22Feb 1996 conditions shown in the bottom panel), there is no discerned correspondence between topography and soil moisture.
Dry soil moisture has lower hydraulic conductivity and lateral redistribution is less dominant as a factor in organizing soil moisture patterns. The random spatial variability of soil texture may
be a more critical factor in explaining any spatial variability in thesoil moisture field. Lateral redistribution in the saturated and unsaturated zones, ground and surface water interaction, evapotranspiration, macropore flow, and soil texture heterogeneity are among
the competing factors that influence the spatial organization of
surface soil moisture fields. Detailed understanding of these processes and the development of parsimonious characterizations ofthem for inclusion in coarse-resolution models remain important
challenges in land surface hydrology.

and variations of runoff with surface cover and topographic gradients.
The identification of critical scales and related
upscaling issues are problems that are directly relevant
not only to the design of models but also to the design ofin situ and remote observing systems, which may provide information at scales different than needed for modeling or other applications. These topics are also related
to the question of how data should be interpreted, extended, aggregated, or disaggregated for various pur2049

poses. For these reasons, it is crucial that we develop
a systematic framework for describing and detailingwith the scale dependence of hydrologic phenomena.
d. Does lateral soil water redistribution
significantly affect large-scale soil–vegetation–
atmosphere exchange processes?
The partitioning of incident precipitation into runoff is dependent on near-surface processes that are significantly influenced by spatial interactions and lateralredistribution of moisture over complex terrain.
Runoff-producing zones are limited to areas of low soil
permeability, low gradient, and high moisture content.
The latter source areas are primarily concentrated
around the drainage network, either in convergent topographic regions that receive the gradient-driven lateral water movement in soils, or where the depressionof the topographic surface decreases the storage capacity of the soil above the water table (see Fig. 5).
The representation of land surface hydrologic processes in spatially lumped (e.g., conceptual models
used in operational hydrology and flood forecasting)or one-dimensional soil hydrology models (e.g., soil–
vegetation–atmosphere transfer schemes used in numerical climate and weather forecast models) cannot,
by construct, capture these important lateral redistribution processes. Instead, these models rely on cali-

bration (or adjustment) of empirical parameters to reproduce observations of hydrologic processes over complex
terrain. Without lateral redistribution through the regional groundwater system, flood runoff from large
areas cannot be represented in a realistic manner by suchmodels. The representation of lateral redistribution
processes, groundwater, and surface water interactions
should consider the time- and space scales of naturalvariations in topography, soils, vegetation, and climate.
Geochemical tracers are effective and sometimes
underutilized tools for mapping lateral moisture
movement in the subsurface. Identification of regional
groundwater recharge and discharge zones, flow pathway studies, and hydrograph separation techniques
benefit from simultaneous hydrologic and geochemical observations. Such observational capabilities, together with advances in computational capabilities,
may be used to construct distributed hydrologic models that properly account for lateral flow. Such models can be used to assess the importance of lateral soil
moisture redistribution and to clarify its role in runoff generation and the distribution of vegetation.
e. How can the effects of human activity on thelandscape, its ecology, and hydrology be
distinguished from natural climate variability?
Human modifications of the environment, includ-

FIG. 6. Human land use practices can lead to significant changes in large-scale hydrological fluxes. The figure on the left shows
mosaicked Landsat images of the Imperial Valley, on the border between California and Mexico (courtesy of U.S. Geological Survey
Eros Data Center, Landsat images). Red indicates the presence of vegetation. The sharp southern edge of the red region corresponds
to the California–Mexico border and thus reflects different land use practices in the two countries. Evaporation must be significantly
higher north of the border. The figure on the right shows the extent of irrigation in the United States (Bajwa et al. 1992). The patterns
suggest a large-scale human-induced increase in evaporation from the land surface, particularly in the arid West. The effects of thisincrease on large-scale weather patterns are unknown.
2050

Vol. 80, No. 10, October 1999

ing land cover change, irrigation, and flow regulation,
now occur on scales that significantly affect seasonaland interannual hydrologic variations (see Fig. 6).
However, long-term climate fluctuations and climatechange are also major contributing factors to hydrologic variability. The partial (individual) contributionsof human activity and climate variability need to be
separated in the analyses of floods, drought, and otherhydrologic phenomena. This raises methodologicalissues for both hydrologic data collection and modeling.
In the forthcoming decade, global change and its
consequences will probably remain the major largescale environmental issue. The hazards associatedwith global change are mostly realized through effects
on the hydrological cycle and water availability.
However, hydrologists have not yet developed thetools necessary to assess the possible impacts of climate change with enough certainty to enable managers and policy makers to benefit from current scientificand technical programs. Moreover, the lessons of pastlarge-scale shifts in global and regional climates (e.g.,
paleoclimate variability and contemporary soil loss
and desertification) and the role of hydrology in theseanalogs of global change have not been fully exploited. Finally, the feedback role played by the hydrological cycle in a changing climate has not been
widely considered by the hydrologic science community (Chahine 1997). These three shortcomings indealing with the global change problem need to be
faced directly.
In the short term there is a need for robust statistical tests that can quantitatively identify the effects ofhuman intervention from inherently noisy hydrologic
data with multiple scales of variation (e.g., interannualand decadal). Care should be exercised in using hydrologic models to predict the human impacts on regional hydrologic processes. In particular, thesemodels should be shown to be applicable to the regions
where environmental conditions have changed. Also,
investigators need to assess sources of prediction uncertainty and the relevance of current effective parameters for impact studies of changing environments.
In the longer term, climate models and models forregional hydrologic change need to converge and, inparticular, account for the feedbacks and interactions
that couple land surface, atmospheric, and oceanic
processes. Both the developers and users of thesemodels will need to exploit all available paleoclimaticand remote sensing data in order to clarify the respective roles of human activities and long-term naturalfluctuations.
Bulletin of the American Meteorological Society

3. Implications for research anddevelopment in observing andmodeling
a. In situ observations
There are numerous sources of in situ data that
could help to address the science questions posed in
section 2 of this paper. These include data rescue andrecovery operations, augmentation of existing observing networks, and development of new networks, often in conjunction with focused field experiments.
Each of these options is discussed in the following
paragraphs.
Long-term monitoring and experimental hydrologic data are archived in a variety of forms and at diverse locations. There is a wealth of data on water andsoils but fragmentation across agencies and archives
has resulted in the underutilization of this information.
In some cases, recovery of measurements made overlong periods is a cost-effective form of investment thata government or institution could make for long-term
environmental monitoring and change detection.
The decay of monitoring networks over the last 30
years due to political and fiscal instabilities has been
substantial. For some hydrologic and climate variables
less is known today than a few decades ago in termsof measurements. National and international agencies
must take effective measures to reverse the trend inmonitoring network losses.
There is a need for a series of workshops that could
focus on strategies for carrying out particular data rescue operations. Participants should include digitalarchive specialists, institutional representatives, andend users. Funding and mission agencies need to provide incentives for individuals or groups to engage incost-saving data recovery activities that will benefit thelarger hydrologic community. A distributed information network could serve as the dissemination medium
for the recovered data.
For a relatively low cost, existing observing networks could be augmented to provide valuable newin situ measurements. Technological advances in instrumentation allow the addition of new variables tothe suite of standard measurements available at existing monitoring stations. Examples include addition ofsoil thermistors to measure soil temperature, devices
to estimate soil water content, instruments to sense
snow properties, and robust devices to measure surface moisture and energy fluxes. In many cases, realtime telemetry of both standard and new types ofmeasurements may be technologically feasible and2051

cost effective. Stream gauging can certainly be mademore efficient and cheaper through telemetry. Water
surface elevations and gradients can be monitored ata greater number of points along channels and withinfloodplains. This could greatly facilitate the measurement of floodwaves and improve our understandingof floods. Sediment and solute sampling can also be
automated well beyond current levels.
Data users and providers need to work together incost–benefit analysis of new and augmented observing systems (e.g., Showstack 1998). This is anotherinstance where focused workshops with broad participation could be very helpful. The impact of expanded
and extended measuring stations within each networkneeds to be assessed in terms of both scientific impact
and operational benefit. Scientific impact can be measured relative to a set of critical science questions suchas those posed in this paper. Operational benefit canbe related to the disaster costs avoided through improved predictions and more advanced warning capabilities. Documentation of the economic, policy, andscientific value of open-release policies of organizations may motivate other national and international
agencies to take similar steps. Finally, protocols andregulations for effective user access to data archives
need to be established in clear terms.
It is often advantageous to simultaneously monitor several processes that are coupled to hydrologic
systems. For example, data on diurnal variations in thetemperature and humidity profiles of the atmosphericboundary layer and observations of conditions in the
troposphere can provide important information forsurface water and energy balance studies (seeFig. 4). Subsurface flow pathways can be better characterized if traditional hydrologic measurements aresupplemented with observations of natural chemical
tracers. Tracers can also be used to improve estimatesof long-term sediment loading and to quantify sediment fluxes between floodplains and rivers. In allthese examples, and in other similar cases, augmentation of traditional sampling programs can be a highly
cost-effective way to obtain the data needed to address
key science questions.
A final priority for in situ data collection is thedevelopment of focused validation datasets that can beused to evaluate new hydrologic theories, models, andremote sensing techniques. These datasets should beobtained from a variety of basins and regions characterized by different topography, climate, vegetation,and snow conditions (see Fig. 7). They should also be
closely coordinated with related remote sensing ex2052

periments and ground truth studies, preferably under
the auspices of international agencies and hydrologic
initiatives (see discussion in the remote sensing section that follows). Validation datasets could fit within
the continental-scale basin experiments of the Global
Energy and Water Cycle Experiment (GEWEX). But
they should also include smaller areas that can bemonitored more intensively (WCRP 1997; NRC 1998).
Data provided by data recovery activities, existingand expanded observing networks, and other sources
need to be properly archived, well organized, andreadily available if they are to be of value to the user
community. These objectives could greatly benefit
from standardization. There is a pressing need for
protocols and standards for systematically linking various hydrologic data archives. These should be devel-

FIG. 7. The importance of high quality in situ data to hydrological modeling is indicated. Each of a number of different river
basins is represented in the plot by two points: a circle for 1987
data, and a triangle for 1988 data. The abscissa represents “model
error;” i.e., it represents the average runoff generated for the basin by nine land surface parameterizations (LSPs) minus the observed runoff there. The LSPs were forced with observed
precipitation, radiation, and other atmospheric variables for 1987–
88 as part of the Global Soil Wetness Project. The ordinate shows
the density of rain gauges within the basin, a measure of the accuracy of the precipitation forcing used by the LSPs. The salientfeature of the plot is the significant reduction in model error as
the density of rain gauges increases. This suggests that much of
the overall error in model runoff predictions may not be related
to flaws in the model parameterizations but to an inadequate coverage of rain gauges (courtesy of T. Oki and cited in Dirmeyer1997).

Vol. 80, No. 10, October 1999

oped with broad participation by the hydrologic community, in cooperation with related communities in theearth and atmospheric sciences.
b. Remote sensing
Remotely sensed observations of land surface conditions from satellites and suborbital platforms (e.g.,
aircraft and balloons) provide synoptic high-resolution coverage that is unprecedented in the hydrologic
sciences. The new information available from remotesensing technology may initiate important shifts in theconceptual basis for hydrology. Analogous shifts havealready occurred in the atmospheric and oceanic sciences, where space-based observations have led to
the reformulation of many fundamental disciplinary
ideas. Hydrologists should be ready to embrace thisspecial opportunity to rethink prevailing theories andapproaches. The benefits for their discipline may beconsiderable.
For land surface hydrologic applications, the existing large amounts of multiangle visible and thermal
spectral measurements have proven very valuable forhydrologic applications. These measurements havebeen used to estimate surface incident radiation, surface temperature, spectral albedo, land cover type,canopy structure features, and a number of other variables relevant to the derivation of energy and moisture fluxes at the land surface. Unfortunately, theatmosphere is a strong absorber and reflector of radiation in these frequency ranges, especially under cloud
conditions. The error associated with atmospheric corrections under cloudy conditions precludes the use ofvisible and thermal spectral observations to retrieve
surface fields that have relatively small and subtle
impacts on the signal.
Fortunately, the atmosphere is relatively more transparent to surface emissions in the lower-frequency(longer wavelength) microwave region. This makes it
more feasible to directly observe land surface variablesof hydrologic interest. Polarized microwave emissivity is sensitive to near-surface soil moisture. An optimum soil moisture remote sensing system would be
able to measure microwave radio brightness in spectral bands that are sensitive to soil moisture farther
below the surface. The system would also provide
measurements in spectral bands that are least affectedby the atmosphere and moderate vegetation cover.
This is possible with low-frequency microwave
radiation that is also used for telecommunications.
Fortunately a few spectral bands are protected for radioastronomy. The band centered on 21-cm waveBulletin of the American Meteorological Society

length or 1.4 GHz (also known as the L band) is thelowest useful microwave frequency that can yield information on soil dielectric constant, which is related
to soil water content (among other factors), down to afew centimeters. Design and deployment of missions
to measure earth emission or reflection of radiation inthis frequency is now among the unique opportunities
for remote sensing in hydrology. There still remainsome major questions that have yet to be adequately
addressed, despite the fact that L-band microwave instruments have been developed and deployed for shortperiods of time on aircraft and spacecraft (see Fig. 8).
There are, however, a number of important technicalissues to be addressed. These include the design ofspace-borne antennae large enough to collect relatively
weak microwave signals with sufficient fidelity, thedesign of retrieval algorithms that are robust under avariety of soil and vegetation conditions, coordination
with spectral measurements at other frequencies, andthe consideration of trade-offs between active radarand passive radiometry instruments.
Other land surface parameters can also be derived
from remote sensing observations. These include topography, vegetation canopy structure, and mappingof inundation through side-looking radar and laser altimetry. Surface sediment concentrations in flowing
water can also be recorded and interpreted to yield vertical concentration profiles or spatial patterns of mixing. Laser and radar altimeters offer the potential formeasuring river stages and assessing floods.
In the current era, a successful remote sensing mission requires an end-to-end system optimization. This
process starts with a clear set of scientific objectives
that could apparently benefit from particular types ofspectral data, as outlined earlier. A convincing casemust be made that such data will, in fact, substantially
improve scientific understanding and/or operational
forecasting abilities. Once this case has been made,attention can turn to mission design. This includes ananalysis of the maximum ground-level spatial resolution, minimum revisit frequency, maximum tolerable
error in radio brightness of reflectivity, maximum offnadir look angle, signal-to-noise ratio, and other characteristics of the mission under consideration.
Trade-offs between passive and active remote sensing
and synergistic use of multispectral (visible, thermal,
and microwave) observations should be considered aspart of this process.
Another important aspect of end-to-end optimization is simulations of space-borne measurements withnumerical models and/or with suborbital prototype
2053

instruments. Important design issues that can be examined in this way include beamfilling, which occurs
when heterogeneous small-scale surface properties
yield a remotely sensed measurement that is not representative of regional conditions. It is advisable, aspart of the design process, to test retrieval algorithms
as well as instruments and mission design. These algorithms should be evaluated over a wide range of topographic, climate, soils, and vegetation conditions,in order to establish their range of applicability.
Moreover, retrieval algorithms need to be integrated
with compatible hydrologic models in order to provide “value added” data products that reveal the full
implications of new remotely sensed observations.

The final stage of end-to-end optimization is theassessment of mission costs and the scientific and societal benefits. Benefits to be considered should include improved forecasting for hazard mitigation, andinformation that can help solve key agricultural, human health, water resources, and industrial policy
problems. It should be apparent from the above discussion that end-to-end optimization requires a closeworking relationship between instrument specialists,
spacecraft engineers, and applications scientists toproperly translate scientific requirements into realistic systems. Such a dialogue should help to streamline the definition, development, and implementation
process, resulting in cost reductions.
It is important to note that endto-end optimization is relevant toanalysis of existing as well as new
remote sensing missions. The sameassessment of multispectral synergy,
retrieval algorithm performance,measurement and retrieval error
budget calculations, value-added
data production, and data quality
control should be carried out withexisting remote sensing measurements. In fact, the same framework
also applies to ground-based technologies such as weather-sensing
radar. In all of these cases, there is aneed for careful evaluation of retrieval algorithms, errors, and potential benefits.
The ready availability of remotesensing information poses a number of specific challenges, both intellectual and organizational, to thehydrologic community, including
the following.

FIG. 8. Remote sensing technology can transcend many of the economical and logistical problems that limit the effectiveness of in situ measurement systems. An exampleof the potential use of remote sensing for hydrological research is shown above. During
the Southern Great Plains 1997 Hydrology Experiment, the L-band Electronically
Scanned Thinned Array Radiometer was deployed on a low-flying aircraft (Jackson et al.
1999). Daily mapping of surface brightness temperature over an area greater than
10 000 km2 and a period on the order of a month was conducted. Sample images fromtwo consecutive days in June show a large drop in brightness temperature at the top of
the mapped region in response to the significant rainfall event that covered the area in
the interim between samplings. Surface soil moisture fields may be inferred from such
remote sensing observations with good accuracy. High costs would prohibit the estimation of spatial fields of soil moisture across large areas using in situ probes.
2054

1) Classic data-poor hydrologic
models designed to function
with (and calibrate with) sparsein situ observations of precipitation, stream discharge, andsurface air micrometeorology
will need to give way to new
distributed hydrologic models
that are forced with remotelysensed observations. More attention will need to be given toformulating models with paVol. 80, No. 10, October 1999

rameters that can be directly measured, rather thancalibrated.
2) Basin-scale and regional validation databases consisting of coordinated in situ and remote sensing
data collection programs will need to be established in order to properly evaluate instruments andretrieval algorithms. Such validation data should
provide the basis for assigning error statistics toremote sensing observations. The validation sites
should be located in regions with different topography, climate, vegetation, and snow conditions.
3) Hydrologists need to evolve from passive recipients of limited remote sensing observations to acting as a unified scientific community that is engaged in supporting the definition, design, andimplementation of suborbital and space-borne missions. The key to fulfilling this challenge is a clear
demonstration of the positive impact of existingand emerging observation streams on the major scientific objectives and questions.
Other challenges will undoubtedly arise as new
data types begin to have impact on hydrologic theory
and practice.
c. Data assimilation
Remote sensing technology provides many typesof spectral data that are related to land surface variables of interest to hyrologists. However, very little ofthis information is available in a form that can be useddirectly for hydrologic purposes. Various types of data
retrieval algorithms are needed to convert spectral data
into variables of hydrologic value. In fact, a similar
situation exists for some types of in situ information,such as data used to infer soil hydraulic properties.
Here again, properties of hydrologic interest must be
inferred from available measurements, with the aid of
retrieval or data processing algorithms.
The simplest data retrieval algorithms are based on
observed correlations between spectral measurements
and hydrologic variables. Such algorithms may not provide data that are compatible with fundamental physical principles such as conservation of mass, momentum,
and energy. Moreover, they may not be able to extend
available measurements over the regions and time
periods of interest in a particular hydrologic application. An important example is the use of soil moistureretrieval algorithms that process passive microwave
radiance measurements. These algorithms provide information on soil moisture only in the top few centimeters of the column. An ideal data processing algorithm
Bulletin of the American Meteorological Society

would be able to extend such measurements farther down
the soil column by accounting for time–space relations
implicit in the vertical movement of soil water.
Meteorology and oceanography have extensively
developed the concept of “adding value” to data, especially remote sensing data, by combining measurements with the predictions of specially selectedmodels. This process, which is commonly known asdata assimilation, is an extension of standard data retrieval techniques. Data assimilation is distinguishedby its reliance on spatially distributed hydrologic
models that incorporate physical principles such as
mass, momentum, and energy conservation. These
principles act as strong constraints on the estimates
produced by the assimilation algorithm.
It is important to note, however, that data assimilation algorithms are data driven rather than model
driven. This means that data assimilation models aredesigned specifically to aid in data processing rather
than model simulation (and calibration). The variables
in a data assimilation model must include the measured spectral data and must be integrated with other
retrieval algorithms required to translate raw signals
into useful hydrologic information. They also must be
computationally efficient, since they are typically integrated into a larger set of processing and retrieval
algorithms (e.g., atmospheric).
One of the primary purposes of data assimilation
is to produce data products that are directly useful forhydrologic analyses. Such products need to be carefully
designed so they meet the needs of potential users.
Issues to be considered include the resolution and spatial configuration of the data product, quantitative measures of data product reliability, quality control issues(e.g., dealing with “outliers”), and sensitivity of thedata product to “hidden” model properties. All of theseissues are important but most have been addressed, atleast to some degree, in similar contexts by oceanographers and meteorologists. The challenge for hydrologists
is to develop data assimilation algorithms that benefit
from previous work in other disciplines while meetingthe special needs of hydrologic science and practice.
Certain aspects of hydrologic processes and data
sources are particularly compatible with the methods
and objectives of data assimilation. First, hydrologic
systems often function over a wide range of timescales.
For example, vegetation canopy structure varies on thescales of seasons, while surface temperature and moisture vary diurnally. Data assimilation algorithms thatneed to simultaneously estimate canopy interference
and surface emission may utilize high-frequency ra2055

diance measurements but keep the canopy parameters
as temporally invariant over weeks or months. The
degrees of freedom needed to carry out the estimation
process are thus reduced significantly.
A second incentive for the use of data assimilationin hydrologic remote sensing applications is that auxiliary data from in situ observations may often provide
important information on factors contributing to theremotely sensed signal. For example, a data assimilation algorithm may be used to merge soil texture measurements, surface micrometeorology, and in situ landuse data with remote sensing measurements.
Finally, the data assimilation framework may be
used to analyze the value of various observing systems
through the so-called data-denial experiments. In theseexperiments the value of a particular data source canbe quantified in terms of the effect it has on estimatesof a particular hydrologic variable.
It is worth noting that the NRC (1998) report on
the GEWEX Continental International Projects recognizes the critical importance of developing and implementing land data assimilation systems. Experienceswith land data assimilation systems have shown that
estimates of land surface states can be quite sensitive
to errors in the estimation of cloud cover and precipitation. In turn, some of the errors in cloud and precipitation amounts in atmospheric data assimilation
systems are due to errors in surface flux estimation.
Thus improvements in coupling of land and atmosphere components of models and the boundary layer
are necessary for the implementation of refined land
and atmosphere data assimilation systems.
A number of important research and operational
issues need to be resolved if data assimilation is toachieve its potential for “adding value” to hydrologic
measurements. Statistical techniques for describing
multiscale spatial heterogeneity need to be incorporated into algorithms that account explicitly for themultiresolution nature of different but complementaryhydrologic measurements (such as rain gauges,
ground-based radar, and satellite radiance measurements of precipitation). Computationally efficientsequential assimilation techniques that are capable ofadequately characterizing multiscale temporal dynamics should also be investigated for applications tohydrologic remote sensing.
Classic hydrologic models that have been optimized for use with sparse in situ observations such as
precipitation accumulation and streamflow are inadequate for extension to work with remote sensing data.
Models and model components for land surface pro2056

cesses need to be developed following criteria for parsimony and observability. Procedures for their rigorous validation need to be defined. It should berecognized that land surface hydrology models for
simulation and for assimilation applications may havesignificantly different requirements/characteristics.
Finally, the importance of modeling studies that do
not employ data assimilation must also be stressed.
Such free-running models (e.g., coupled land–
atmosphere models) have prognostic variables thatvary in response to the modeled physics. This makes
it possible to carry out sensitivity studies that help isolate and characterize physical controls over hydrological variability. Realistic model physics and coupling
behavior is, of course, critical to the credibility of suchsensitivity analyses. Many of the priority science questions outlined in section 2 relate to increasing the realism of hydrological models, whether they are used
for data assimilation, sensitivity analysis, or hydrologic forecasting.
4. Recommendations: A second
international hydrological decade(2d IHD)The authors believe that the discipline of hydrology is intellectually and technologically ready to address the science issues outlined above. In this section,
we propose a scientific initiative—the Second International Hydrological Decade—that would serve toenable and facilitate the needed research.
This infrastructure is best introduced by describing the relevant precursor, the First International Hydrological Decade (1st IHD). During the 1st IHD,
which covered the years 1965–74, a series of international workshops on the current and future problems
in various subdisciplines of hydrology was organized,
and reports of these activities were published by theUnited Nations Educational, Scientific, and Cultural
Organization (UNESCO 1972, 1974a–e). The more
enduring legacy of the 1st IHD is the international datacollection activity that for the first time provided
worldwide sharing of observations. The 1st IHD had
major impacts on the emergence and maturation of thehydrologic sciences.
The atmosphere of change and excitement in hydrology today is reminiscent of the period leading up
to the 1st IHD. However, almost a quarter of a century has passed, with an associated shift in the way thescience is approached. First, hydrologists now widelyVol. 80, No. 10, October 1999

recognize that land surface hydrologic processes areclosely coupled with the subsurface and the overlying
atmosphere. This realization is reflected in the science
questions of section 2, and it has important implications for both modeling and observing strategies, as
discussed in section 3. A second distinguishing feature of modern land surface hydrology is that the global or large-scale approach is often the starting point,
and the challenge is to characterize regional or smallerscale features. The river basin is no longer the exclusive unit of study. A third distinguishing feature is, as
discussed in section 1, the emergence of new technology and substantial amounts of data in nontraditional
forms. Hydrologists must determine how to optimize
their use of these potentially highly valuable data.
The recent changes in approach must be consideredin the context of current critical issues in hydrology.
In a recent address, the World Meteorological Organization (WMO) Secretary-General Dr. G. Obasi
posed two contemporary challenges to the hydrology
and water resources community: 1) reverse declining
trends in the development of hydrologic observing
systems, and 2) reduce prediction and analysis uncertainty so that managers and policy makers can more
effectively use the results of scientific and technicalactivities (Obasi 1999). The first challenge is principally dependent upon international cooperation among
national and regional agencies. Specific issues to address include capacity building, technology transfer,telecommunications and archiving technologies, andprotocols. The second challenge falls on the shouldersof the research community. This community should
develop scientific tools to make effective use of thedata provided by new observing networks and systems. Furthermore, they should strive to reduce uncertainties that limit the usefulness of their products tothe water resources management and policy making
communities.
The core purpose of the 2d IHD is to address thesetwo challenges. We now have the sensing and dataprocessing technologies needed to characterize theglobal distribution and movement of water and energy,
across a wide range of scales. Moreover, these technologies provide information at accuracies and resolutions hitherto unimaginable. The set of new science
questions stimulated by recent technological developments is also global in scope. Answers to these questions lie at the interface of hydrology and climate andhold the promise of great societal benefits. The tools
and science questions are at hand and the 2d IHD is
the medium for realizing their potential.
Bulletin of the American Meteorological Society

Data collection efforts would be directed towardmeeting the agenda’s goals. These efforts would build
on ongoing international programs that, similar to the
1st IHD, are directed toward the expansion of observing networks and the international exchange of data.
The World Hydrological Cycle Observing System(WHYCOS) and Global Climate Observing System(GCOS) are well-designed and comprehensive international programs for expanding observing networks,
capacity building, technology transfer, and data exchange (WMO 1995, 1998). The implementation ofthese programs is a challenge for the WMO and it represents substantial international cooperation efforts.
As mentioned earlier, data rescue efforts based on existing but nonarchived measurements are also important sources of information. The World Climate
Research Program (WCRP) reports two examples of
initiatives to recover existing observations. The Data
Rescue program in Africa and North and Central
America, and the Archival Climate History Survey inEurope are designed to rescue and preserve climate
data and their associated metadata (WCRP 1997). The
2d IHD may similarly focus on climate and hydrological data rescue and recovery for hydroclimatology
studies dealing with low-frequency variability or nonstationarity (change). The activity may be expanded
to include valuable experimental basin records, water quality, soil and land use surveys, and data from
special or nonoperational observation missions.
WHYCOS, GCOS, data rescue, and associated programs with regional or specialized emphasis will certainly form the backbone of future advances in
reducing hydrological hazards and increasing freshwater availability for growing populations.
This paper outlines a proposed scientific agenda forthe 2d IHD, an agenda that could drive land surfacehydrology research during the next 10 years. The proposed agenda is open to debate—our intention is to put
our proposals “on the table” and thereby stimulate discussion in the larger community. A final form of thisagenda, modified as necessary to reflect the concernsof the hydrological community at large, must still beestablished. This final agenda would give the 2d IHD
focus and would provide guidance for the allocationof limited research and observing system resources.
The burden of making the agreements and protocols that will launch the 2d IHD falls on national andinternational institutions and agencies that deal with
scientific research and cooperation, water resources,and natural hazards. The agenda for land surface hydrology proposed here demonstrates the readiness of2057

the research community to take the initiative for advancing the discipline. Hydrologists can and shouldtake the lead in developing the scientific knowledge
required to address contemporary global environmental issues such as food security, human health, andeconomic development. A focused research agenda for
a 2d IHD, whatever its final form, should give hydrology the direction it needs to address the critical science and water resource problems of the next century.
This is an opportunity that will provide great benefits,
both for the discipline and for society as a whole.

References
Bajwa, R. S., W. M. Crosswhite, J. A. Hostetler, and O. W. Wright.
1992: Agriculture, irrigation, and water use. USDA Agricultural Information Bulletin, No. 638. [Available from U.S. Department of Agriculture, 14th and Independence Ave. SW,
Washington, DC 20250.]
Betts, A. K., and J. H. Ball, 1995: The FIFE surface diurnal cycle
climate. J. Geophys. Res., 100, 25 679–25 693.
Chahine, M. T., 1997: Accelerating the hydrologic cycle.
GEWEXNews, 7 (2), 2.
Dirmeyer, P. A., 1997: The Global Soil Wetness Project(GSWP)—Initial results. GEWEX News, 7 (2), 3–6.
Jackson, T. J., D. M. Le Vine, A. Y. Hsu, A. Oldak, P. J. Starks,
C. T. Swift, J. Isham, and M. Haken, 1999: Soil moisture mapping at regional scales using microwave radiometry: The
Southern Great Plains Hydrology Experiment. IEEE Trans.
Geosci. Remote Sens., submitted.
NRC, 1991: Opportunities in the Hydrologic Sciences. National
Academy Press, 348 pp.
——, 1996: Assessment of Hydrologic and Hydrometeorological
Operations and Services. National Academy Press, 51 pp.
——, 1998: Global Energy and Water Cycle Experiment(GEWEX) Continental-Scale International Project (GCIP): A
Review of Progress and Opportunities. National Academy
Press, 93 pp.
Obasi, G. O. P., 1999: Hydrology and water resources: A global
challenge for WMO. Preprints, 14th Conf. on Hydrology, Dallas, TX, Amer. Meteor Soc., 330–336.
Pielke, R. A., 1998: Climate prediction as an initial value problem. Bull. Amer. Meteor. Soc., 79, 2743–2746.

2058

Salvucci, G. D., 1997: Soil and moisture independent estimationof stage-two evaporation from potential evaporation and albedo or surface temperature. Water Resour. Res., 33, 111–
122.
Showstack, R., 1998: Real-time monitoring and warning for natural hazards can provide real-time benefits. Eos, Trans. Amer.
Geophys. Union, 79, 329–333.
UNESCO, 1972: Status and Trends of Research in Hydrology: A
Contribution to the International Hydrological Decade.
UNESCO.
——, 1974a: Records of the International Conference on the Results of the International Hydrological Decade and on future
programmes in hydrology: I Final Report. UNESCO, 99 pp.
——, 1974b: Records of the International Conference on the Results of the International Hydrological Decade and on future
programmes in hydrology: II. Reports of international governmental and non-governmental organizations on their contributions to the programme of the decade. UNESCO, 102 pp.
——, 1974c: Records of the International Conference on the Results of the International Hydrological Decade and on future
programmes in hydrology: III. Technical reports of the Working Groups of the Co-ordinating Council of the International
Hydrological Decade. UNESCO.
——, 1974d: Records of the International Conference on the Results of the International Hydrological Decade and on Future
Programmes in Hydrology: IV. Technical reports of the Working Groups of the Co-ordinating Council of the International
Hydrological Decade. UNESCO, 106 pp.
——, 1974e: Records of the International Conference on the Results of the International Hydrological Decade and on Future
Programmes in Hydrology: V. Technical reports on Selected
Scientific Activities Related to the IHD Programme. UNESCO,
74 pp.
UN-SWI, 1997: Comprehensive assessment of the freshwater
resources of the world. United Nations and the Stockholm
Water Institute, World Meteorological Organization, 33 pp.
Western, A. W., and R. B. Grayson, 1998: The Tarrawarra data
set: Soil moisture patterns, soil characteristics, and hydrological flux measurements. Water Resour. Res., 34, 2765–2768.
WCRP, 1997: Seventh Planning Meeting on World Climate
Programme—Water. Final Rep. WCASP-45, WMO/TD-No.
854.
WMO, 1995: World Climate Observing System, Version 1.0.
WMO/TD-No. 681, 8 pp.
——, 1998: World Hydrological Cycle Observing System. WMO/
TD-No. 876, 12 pp.

Vol. 80, No. 10, October 1999