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Satellite-based observations indicate that seasonal patterns in canopy greenness and productivity in the Amazon are negatively correlated with precipitation, with increased greenness occurring during the dry months. Flux tower measurements indicate that the canopy greening that occurs during the dry season is associated with increases in net ecosystem productivity (NEP) and evapotranspiration (ET). Land surface and terrestrial biosphere model simulations for the region have predicted the opposite of these observed patterns, with significant declines in greenness, NEP, and ET during the dry season. In this study, we address this issue mainly by developing an empirically constrained, light-controlled phenology submodel within the Ecosystem Demography model version 2 (ED2). The constrained ED2 model with a suite of field observations shows markedly improved predictions of seasonal ecosystem dynamics, more accurately capturing the observed patterns of seasonality in water, carbon, and litter fluxes seen at the Tapajos National Forest, Brazil (2.86°S, 54.96°W). Long-term simulations indicate that this light-controlled phenology increases the resilience of Amazon forest NEP to interannual variability in climate forcing.

Summary A major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.

Net radiation, at the Earth's surface, is a key variable of interest in fields such as hydrology, climate research, and agriculture. Retrieval algorithms for estimation of the surface radiation budget (SRB) from remote sensing data generally suffer from two major shortcomings: difficulty in dealing with cloudy-sky conditions and reliance on study-site specific ancillary ground data. In this paper, we use the methodology of Bisht and Bras (BB10) to estimate SRB and its components, using only remote sensing data under all sky conditions. The BB10 framework is applied over seven sites of the Surface Radiation Budget network in the CONtinental United States (CONUS), along with 21 sites of the Atmospheric Radiation Measurement program in the Southern Great Plains. The data from both the Aqua and Terra satellites are used for entire 2006. The study examines instantaneous upwelling and downwelling shortwave, longwave, net shortwave, and net radiations, as well as daily average net shortwave and net radiations. The root-mean-square errors of estimated daily average net radiation and daily average net shortwave radiation when compared to ground observations are 52.42 and 52.21 W · m-2, respectively. An example of the retrieved instantaneous and daily average net radiation is also presented, which highlights the limitation of using only polar-orbiting satellite data in estimating the diurnal cycle of net radiation. Two adaptations to the algorithm are presented that make the production of SRB estimates over the CONUS feasible. Finally, the methodology is applied to produce daily SRB maps for the CONUS, and monthly SRB maps are presented.

Prior research has shown that deforestation in the southwestern Amazon enhances the formation of nonprecipitating shallow cumulus clouds, while deep cumulus convection was favored over forested land. The research presented here further investigates the trends of hydrometeors in the area by examining how precipitation frequency changes as a function of distance to the forest’s edge. Measurements are made from the precipitation radar on the Tropical Rainfall Measuring Mission (TRMM; TRMM 2A25) satellite, and continuous forest coverage is retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS; MODIS MCD12Q1). The event-based areal fractions of precipitation coverage (precipitation fraction) are calculated; referenced to forested, nonforested, and forest-edge land cover; and compared. As results are generally consistent with previous findings, the novel conclusions here extend that precipitation frequency in the southwestern Amazon (i) decreases over regions of nonforests far removed (10-plus km) from forest borders but (ii) increases within several kilometers of the forest edges, particularly over the nonforest side of the transition.

Landslides are a major geologic hazard with estimated tens of deaths and $1–2 billion in economic losses per year in the US alone. The island of Puerto Rico experiences one or two large events per year, often triggered in steeply sloped areas by prolonged and heavy rainfall. Identifying areas susceptible to landslides thus has great potential value for Puerto Rico and would allow better management of its territory. Landslide susceptibility zonation (LSZ) procedures identify areas prone to failure based on the characteristics of past events. LSZs are here developed based on two widely applied methodologies: bivariate frequency ratio (FR method) and logistic regression (LR method). With these methodologies, the correlations among eight possible landslide-inducing factors over the island have been investigated in detail. Both methodologies indicate aspect, slope, elevation, geological discontinuities, and geology as highly significant landslide-inducing factors, together with land-cover for the FR method and distance from road for the LR method. The LR method is grounded in rigorous statistical testing and model building but did not improve results over the simpler FR method. Accordingly, the FR method has been selected to generate a landslide susceptibility map for Puerto Rico. The landslide susceptibility predictions were tested against previous landslide analyses and other landslide inventories. This independent evaluation demonstrated that the two methods are consistent with landslide susceptibility zonation from those earlier studies and showed this analysis to have resulted in a robust and verifiable landslide susceptibility zonation map for the whole island of Puerto Rico.

Net radiation is a key component in the surface radiation budget. Numerous studies have developed frameworks to estimate net radiation or its components (upwelling or downwelling longwave and/or shortwave radiation) from remote sensing data for clear sky conditions. Application of existing methodologies to estimate net radiation for cloudy sky conditions from remote sensing sensors remains a significant challenge. In this paper, we present a framework to estimate instantaneous and daily average net radiation under all sky conditions from using the data from the MODerate Resolution Imaging Spectroradiometer (MODIS), onboard from the Terra satellites. Bisht et al. (2005) methodology is used for the clear sky portion of the MODIS overpass; while for cloudy portion of the MODIS overpass an extension of Bisht et al. (2005) methodology is applied. The extension of Bisht et al. (2005) methodology utilizes the MODIS cloud data product (MOD06_L2) for cloud top temperature, cloud fraction, cloud emissivity, cloud optical thickness and land surface temperature for cloudy days. The methodology is applied over the Southern Great Plains (SGP) for a time period covering all seasons of 2006. During the MODIS-Terra overpasses in 2006 over the SGP, only 24% of day-overpasses and 9% of night-overpasses had 75% or more of the study region as cloud free. Thus, this proposed study is applicable to a large portion of the MODIS-Terra overpasses. The root mean square errors (RMSE) of instantaneous and daily average net radiation estimated under cloudy conditions using the MOD06_L2 product, comparing to ground-based measurements are 37 W m − 2 and 38 W m − 2 , respectively. The strength of the proposed methodology is that it can rely exclusively on remote sensing data in the absence of ancillary ground observations, thus it has a potential to estimate surface energy budget globally.

An extremum hypothesis of turbulent transport in the atmospheric surface layer is postulated. The hypothesis has led to a unique solution of Monin–Obukhov similarity equations in terms of simple expressions linking shear stress (momentum flux) and heat flux to mean wind shear and temperature gradient. The extremum solution is consistent with the well-known asymptotic properties of the surface layer. Validation of the extremum solution has been made by comparison to field measurements of momentum and heat fluxes. Furthermore, a modeling test of predicting surface heat fluxes using the results of this work is presented. A critical reexamination of the interpretation of the Obukhov length is given.

Microwave radiometry will emerge as an important tool for global remote sensing of near-surface soil moisture in the coming decade. In this modeling study, we find that hillslope-scale topography (tens of meters) influences microwave brightness temperatures in a way that produces bias at coarser scales (kilometers). The physics underlying soil moisture remote sensing suggests that the effects of topography on brightness temperature observations are twofold: 1) the spatial distribution of vegetation, moisture, and surface and canopy temperature depends on topography and 2) topography determines the incidence angle and polarization rotation that the observing sensor makes with the local land surface. Here, we incorporate the important correlations between factors that affect emission (e.g., moisture, temperature, and vegetation) and topographic slope and aspect. Inputs to the radiative transfer model are obtained at hillslope scales from a mass-, energy-, and carbon-balance-resolving ecohydrology model. Local incidence and polarization rotation angles are explicitly computed, with knowledge of the local terrain slope and aspect as well as the sky position of the sensor. We investigate both the spatial organization of hillslope-scale brightness temperatures and the sensitivity of spatially aggregated brightness temperatures to satellite sky position. For one computational domain considered, hillslope-scale brightness temperatures vary from approximately 121 to 317 K in the horizontal polarization and from approximately 117 to 320 K in the vertical polarization. Including hillslope-scale heterogeneity in factors effecting emission can change watershed-aggregated brightness temperature by more than 2 K, depending on topographic ruggedness. These findings have implications for soil moisture data assimilation and disaggregation of brightness temperature observations to hillslope scales.

Terrascope is a freshman learning community at the Massachusetts Institute of Technology (MIT) in which teams of students work to find solutions to large ‘unsolvable’ problems and to communicate about those problems with a wide variety of audiences in multiple formats. The program strongly promotes students’ autonomy in focusing and structuring their work, and student projects culminate in public presentations, both to general audiences and to panels of technical specialists. Students who have completed the program tend to show strong engagement with environmental and sustainability issues, as well as the skills and experience to work intensively on such issues within multidisciplinary teams. Here, we present the program as a case study, with some discussion of the factors that are key to its operation.

Shallow clouds are prone to appear over deforested surfaces whereas deep clouds, much less frequent than shallow clouds, favor forested surfaces. Simultaneous atmospheric soundings at forest and pasture sites during the Rondonian Boundary Layer Experiment (RBLE-3) elucidate the physical mechanisms responsible for the observed correlation between clouds and land cover. We demonstrate that the atmospheric boundary layer over the forested areas is more unstable and characterized by larger values of the convective available potential energy (CAPE) due to greater humidity than that which is found over the deforested area. The shallow convection over the deforested areas is relatively more active than the deep convection over the forested areas. This greater activity results from a stronger lifting mechanism caused by mesoscale circulations driven by deforestation-induced heterogeneities in land cover.

Reanalysis data are an important source of information for hydrometeorology applications, which use data assimilation to combine an imperfect atmospheric model with uncertain observations. However, uncertainty estimates are not normally provided with reanalyses. The model “first guess” (6-h forecast) is sometimes saved along with reanalysis estimates, which allows the calculation of the analysis increment (AI), defined as the analysis minus the model first guess. Analysis increment statistics could provide a quantitative index for comparing models in regions with sufficient observations. Monthly analysis increment statistics for the NCEP–NCAR Global Reanalysis 1 (NCEP-R1) and the NCEP/Department of Energy Global Reanalysis 2 (NCEP-R2) are computed for a North American and South American location for zonal and meridional wind and specific humidity at three atmospheric levels for 1998–2001. NCEP-R2 specific humidity was found to have a smaller mean monthly standard deviation of the analysis increment than NCEP-R1 at the North American location at the 300-mb level. The NCEP-R2 specific humidity monthly standard deviation at the South American location is much larger than NCEP-R1 for September–November 1998, which may be related to the transition to La Niña. For both zonal and meridional wind, the monthly AI standard deviations are similar for NCEP-R1 and NCEP-R2 at all atmospheric levels for the North American location. The South American location exhibits similar behavior for the wind AI statistics as for specific humidity: NCEP-R2 has a much larger monthly standard deviation of the AI for September–November 1998. The analysis increment statistics could be one method for quantitatively comparing reanalyses. First guess information should be available to the user in reanalysis archives.

Estimates of the net convergence of atmospheric moisture flux over the Amazon Basin, [C], derived using data products from three global reanalyses, the NCEP–NCAR reanalysis (NCEP-1), the NCEP/Department of Energy reanalysis (NCEP-2), and the 40-yr ECMWF Re-Analysis (ERA-40), are compared. Two types of uncertainty in these [C] estimates are distinguished and quantified: “model-associated uncertainty,” which necessarily arises from imperfections in the numerical weather models or data assimilation algorithms, and “postprocessing uncertainty” introduced by operations performed on the original reanalysis data products to compute [C], particularly the finite-difference approximation of divergence. Model-associated uncertainty is found to overwhelm the postprocessing error. A closer look at the time series of this field extending over the period 1980–2001, and their comparison to basin-averaged precipitation and runoff data, reveals the signatures of two potential sources of model-associated errors. 1) ERA-40 estimates of [C] exhibit an artificial shift in 1987, possibly produced by the start of assimilation of Special Sensor Microwave Imager (SSM/I) data. The estimates preceding 1988 are negatively biased relative to the remaining time series, and hence subsequent analysis is limited to the 14-yr period 1988–2001. 2) NCEP-1 and NCEP-2 estimates of [C] show a negative bias over the period 1992–98, which likely originates in biased Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) data assimilated by these reanalyses. A measure of the random error in the [C] time series produced by each reanalysis, computed using river discharge data as reference, indicates that ERA-40 gives the most accurate estimates of net atmospheric moisture flux convergence for the aforementioned 14-yr period.

Spatially averaged evapotranspiration [ET] over the Amazon Basin is computed as the residual of the basin’s atmospheric water balance equation, at the monthly time scale and for the period 1988–2001. Basin-averaged rainfall [P] is obtained from the Global Precipitation Climatology Project (GPCP) dataset, and alternative estimates of the net convergence of atmospheric water vapor flux over the basin [C] are derived from three global reanalyses: the NCEP–NCAR and NCEP–Department of Energy (DOE) reanalyses and the 40-yr ECMWF Re-Analysis (ERA-40). Additionally, a best estimate of [C] is obtained by taking a weighted average of data from these three sources, in which the weight factors are based on the random error attributed to each reanalysis’ [C] estimates by comparison to river discharge data. The resulting time series is dominated by ERA-40’s contribution, which was found to be the most accurate over the study period. Data products from the three reanalyses are also employed to compute the monthly tendencies of total precipitable water over the basin. While the seasonal signature of this “accumulation term” provides important insight into the Amazon Basin’s hydrological cycle, its magnitude is found to be negligible relative to the other components of the water budget. The value of mean annual [ET] presented in this work is significantly lower than other published estimates that are based on simulations by various land surface models. Furthermore, when the best estimate of [C] is used, the resulting [ET] time series exhibits a seasonal cycle that is in phase with that of basin-averaged surface net radiation, suggesting that Amazonian evapotranspiration is prevalently limited by energy availability. In contrast, most land surface models, including that of the NCEP–NCAR reanalysis, simulate water-limited evapotranspiration in the Amazon Basin. The analysis presented here supports the hypothesis that most Amazonian trees sustain elevated evapotranspiration rates during the dry season through deep roots, which tap into large reservoirs of soil water that are replenished during the following wet season.

This study investigates the use of a previously published algorithm for estimating ground heat flux (GHF) at the global scale. The method is based on an analytical solution of the diffusion equation for heat transfer in a soil layer and has been shown to be effective at the point scale. The algorithm has several advantageous properties: 1) it only needs a single-level input of surface (skin) temperature, 2) the time-mean GHF can be derived directly from time-mean skin temperature, 3) it has reduced sensitivity to the variability in soil thermal properties and moisture, 4) it does not requires snow depth, and 5) it is computationally effective. A global map of the necessary thermal inertia parameter is derived using reanalysis data as a function of soil type. These parameter estimates are comparable to values obtained from in situ observations. The new global GHF estimates are generally consistent with the reanalysis GHF output simulated using two-layer soil hydrology models. The authors argue that the new algorithm is more robust and trustworthy in regions where they differ. The proposed algorithm offers potential benefits for direct assimilation of observations of surface temperature as well as GHF into the reanalysis models at various time scales.

Summary Knowledge of initial conditions is very important to correctly model the basin response at the storm event scale. Of particular interest is the influence of topography and soil type on the principal hydrologic variables and runoff generation mechanisms as a function of antecedent wetness conditions. This study addresses the influence of initial states on the short-term hydrologic response and characterizes the effects of topography and soils on the dissipation of the influence of the initialization conditions. Two case studies are considered: a synthetic two-dimensional planar hillslope with various assumed slope magnitudes and soil types; and a real basin (∼800 km2) with actual land-surface characteristics. These case studies have been chosen in order to investigate the hydrological behavior at two different scales. Various precipitation rates and durations are used to force both domains, each initialized assuming different positions of spatially variable water table. The results illustrate the existence of complex mechanisms that modulate the watershed response depending on the catchment initial state and rainfall forcing. Factors contributing to the unsaturated zone soil moisture movement are discussed in relation to different soils and topographic properties. The role of rainfall intensity in determining the degree of control exerted by initial conditions on the total runoff as well as its partition into various mechanisms is examined for both case studies. Differences in the sensitivity of certain terrain locations to the initialization and the rainfall rates are revealed. In particular, the real case study points out that the effects of initial conditions strongly depend on rainfall intensity and that the spatial hydrologic variations is influenced by the initial groundwater position.

The dynamics of soil organic carbon (SOC) in tropical forests play an important role in the global carbon (C) cycle. Past attempts to quantify the net C exchange with the atmosphere in regional and global budgets do not systematically account for dynamic feedbacks among linked hydrological, geomorphological, and biogeochemical processes, which control the fate of SOC. Here we quantify effects of geomorphic perturbations on SOC oxidation and accumulation in two adjacent wet tropical forest watersheds underlain by contrasting lithology (volcaniclastic rock and quartz diorite) in the Luquillo Critical Zone Observatory. This study uses the spatially-explicit and physically-based model of SOC dynamics tRIBS-ECO (Triangulated Irregular Network-based Real-time Integrated Basin Simulator-Erosion and Carbon Oxidation) and measurements of SOC profiles and oxidation rates. Our results suggest that hillslope erosion at the two watersheds may drive C sequestration or CO2 release to the atmosphere, depending on the forest type and land use. The net erosion-induced C exchange with the atmosphere was controlled by the spatial distribution of forest types. The two watersheds were characterized by significant erosion and dynamic replacement of upland SOC stocks. Results suggest that the landscape underlain by volcaniclastic rock has reached a state close to geomorphic equilibrium, and the landscape underlain by quartz diorite is characterized by greater rates of denudation. These findings highlight the importance of the spatially-explicit and physical representation of C erosion driven by local variation in lithological and geomorphological characteristics and in forest cover. This article is protected by copyright. All rights reserved.

This forum is dedicated to the life and career of Donald R. F. Harleman, an eminent engineer and scholar, a celebrated friend, and a trusted mentor to many. Donald R. F. Harleman, Ford Professor Emeritus of the Massachusetts Institute of Technology MIT died of cancer on September 28, 2005 in Nantucket, Massachusetts. Don was 82 years old. Born on December 5, 1922, in Palmerton, Pennsylvania, Don received a bachelor’s degree in civil engineering from Pennsylvania State University in 1943. He then worked as a design engineer for the Curtis-Wright Corporation in Ohio during the last years of World War II. In October 1945, he arrived at MIT, a 22-year-old

Spurious pits in digital elevation models (DEMs) are traditionally removed by filling depressions, often creating flat regions that lead to inaccurate estimation of landscape flow directions. In this study, a physical approach based on a simple landscape evolution model is proposed for DEM pit removal. This method, an alternative to traditional geometrical procedures, enforces more realistic slopes and flow directions on topography. The procedure is compared with the method most commonly used in the literature and distributed with commercial GIS software where, generally, elevations of a depression are increased up to the lowest value among neighbouring cells. Several tests are performed and parameters sensitivity is carried out in order to demonstrate the performance of the proposed model as compared to traditional methods.

During the period of 01 August 2014 to 31 May 2015 the maximum entropy production (MEP) model, now formulated for all land-cover types including bare soil, canopy, water, snow and ice, was expanded to modeling global surface energy budget, fluxes and greenhouse gases(e.g. carbon dioxide and methane) fluxes, ocean freshwater fluxes, regional crop yield among others. An on-going study suggests that the global annual evapotranspiration (ET) over oceans may be significantly lower than previously thought. The MEP model parameterized turbulent transfer coefficients result in good estimates of surface fluxes of greenhouse gases, a finding pointing to a new method of modeling the global carbon budget using remotely sensed data. A new model of ocean freshwater fluxes derived from sea surface salinity provides independent estimates of ocean ET for cross-validation of the MEP modeled ET.

The predictability of hydrometeorological flood events is investigated through the combined use of radar nowcasting and distributed hydrologic modeling. Nowcasting of radar-derived rainfall fields can extend the lead time for issuing flood and flash flood forecasts based on a physically based hydrologic model that explicitly accounts for spatial variations in topography, surface characteristics, and meteorological forcing. Through comparisons to discharge observations at multiple gauges (at the basin outlet and interior points), flood predictability is assessed as a function of forecast lead time, catchment scale, and rainfall spatial variability in a simulated real-time operation. The forecast experiments are carried out at temporal and spatial scales relevant for operational hydrologic forecasting. Two modes for temporal coupling of the radar nowcasting and distributed hydrologic models (interpolation and extended-lead forecasting) are proposed and evaluated for flood events within a set of nested basins in Oklahoma. Comparisons of the radar-based forecasts to persistence show the advantages of utilizing radar nowcasting for predicting near-future rainfall during flood event evolution.

Incised ephemeral channels provide a window into the fluvial processes that help sculpt rangeland landscapes. This paper presents observations of ephemeral channels and valley networks in the high plains of Colorado, USA, with an eye toward painting a picture of the ingredients that must be included in mathematical models of landscape evolution in such environments. Channel incision in the study area is driven by summer thunderstorms, which can with reasonable frequency (3–5 yr) generate boundary shear stresses high enough to penetrate the highly resistant vegetation armor, but only within erosional hot spots where hydraulic forces are amplified by channel constriction and locally steep gradients. Focusing of erosion at these hot spots (which correspond to knickpoints and channel heads) is amplified by the small areal footprint and short “erosional reach” of most convective storms. Upstream migration of knickpoints creates a pattern of short, active channel reaches separated by unchanneled or weakly channeled, fully vegetated stable reaches. Based on our observations, we interpret the necessary and sufficient conditions leading to the observed channel forms and dynamics as: (1) a resistant vegetation layer overlying an erodible substrate, which sets up a conditional instability through which erosional perturbations can grow by positive feedback; (2) high flow variability; (3) moderate to high substrate cohesion; and (4) a high volume fraction of fine-grained erodible material. Concave-upward valley long profiles are interpreted as a trade-off between downstream-increasing flood frequency and downstream-decreasing flood effectiveness. The observed process dynamics imply that long-term rates of valley incision should be especially sensitive to climatic oscillations between episodes of drought and warm-season convective rainfall.

Fluvial processes have the potential to obscure, expose, or even destroy portions of the archaeological record. Floodplain aggradation can bury and hide archaeological features, whereas actively migrating channels can erode them. The archaeological record preserved in the subsurface of a fluvial system is potentially fragmented and is three-dimensionally complex, especially when the system has been subjected to successive phases of alluviation and entrenchment. A simulation model is presented to gain insight into the threedimensional subsurface distribution, visibility, and preservation potential of the archaeological record in a meander-floodplain system as a function of geomorphic history. Simulation results indicate that fluvial cut-fill cycles can strongly influence the density of archaeological material in the subsurface. Thus, interpretation of floodplain habitation based solely upon features visible in the shallow subsurface (through traditional techniques such as aerial photography and geophysical prospection) can be misleading. In the examples, the loss of archaeological record by channel migration ranges between 45% and 90% over 12,000 years for channel belt-dominated systems, decreasing to 10 to 30% for rivers where the floodplain width is a multiple of channel belt width. The modeling presented can be used to test excavation strategies in relation to hypothesized scenarios of stratigraphic evolution for archaeological sites. © 2006 Wiley Periodicals, Inc.

Accurate representation of terrain with appropriate reproduction of topographic characteristics is important for increasingly sophisticated physically-based models of natural processes. Recently investigators have successfully enforced slope area relationships to interpolate more realistic topographies from the sparse data. The limitation of those procedures is that, for the most part, they preserve only the first moment (the mean), when scaling slope with contributing area. Here we present a simple approach to also enforce the second moment, the variance, during landscape evolution simulations or physically-based spatial interpolations.

Distributed hydrologic models based on triangulated irregular networks (TIN) provide a means for computational efficiency in small to large-scale watershed modelling through an adaptive, multiple resolution representation of complex basin topography. Despite previous research with TIN-based hydrology models, the effect of triangulated terrain resolution on basin hydrologic response has received surprisingly little attention. Evaluating the impact of adaptive gridding on hydrologic response is important for determining the level of detail required in a terrain model. In this study, we address the spatial sensitivity of the TIN-based Real-time Integrated Basin Simulator (tRIBS) in order to assess the variability in the basin-averaged and distributed hydrologic response (water balance, runoff mechanisms, surface saturation, groundwater dynamics) with respect to changes in topographic resolution. Prior to hydrologic simulations, we describe the generation of TIN models that effectively capture topographic and hydrographic variability from grid digital elevation models. In addition, we discuss the sampling methods and performance metrics utilized in the spatial aggregation of triangulated terrain models. For a 64 km2 catchment in northeastern Oklahoma, we conduct a multiple resolution validation experiment by utilizing the tRIBS model over a wide range of spatial aggregation levels. Hydrologic performance is assessed as a function of the terrain resolution, with the variability in basin response attributed to variations in the coupled surface–subsurface dynamics. In particular, resolving the near-stream, variable source area is found to be a key determinant of model behaviour as it controls the dynamic saturation pattern and its effect on rainfall partitioning. A relationship between the hydrologic sensitivity to resolution and the spatial aggregation of terrain attributes is presented as an effective means for selecting the model resolution. Finally, the study highlights the important effects of terrain resolution on distributed hydrologic model response and provides insight into the multiple resolution calibration and validation of TIN-based hydrology models. Copyright © 2005 John Wiley & Sons, Ltd.

This study presents various aspects of the continuous simulation capabilities of a fully-distributed, triangulated irregular network (TIN) hydrologic model. The TIN-based Real-time Integrated Basin Simulator (tRIBS) is calibrated and verified for the Baron Fork at Eldon, Illinois River at Watts, and Blue River at Blue over the period 1993–2000. Computational effort is significantly reduced by simulating complex watersheds using a multiple resolution mesh to represent terrain. Model performance is assessed by comparing streamflow predictions to observations at the basin outlet and interior gauging stations. In addition, simulation results describing the distributed basin response to atmospheric forcing are discussed, including the spatial and temporal variability of runoff, surface soil moisture, evaporative flux, and groundwater table position. By modeling the land-surface water and energy states and fluxes over the computational domain in an efficient manner, the potential for utilizing fully-distributed models at the scales of operational hydrologic forecasting is realized. Through the spatially-explicit approach, high-resolution remote sensing data describing surface properties, topography, rainfall, and soil moisture can be integrated directly into a predictive hydrologic model. A greater degree of physical interpretation of hydrological estimation can thus be added to existing methods of operational forecasting.

Distributed hydrologic models typically incorporate topographic data through the use of raster-based digital elevation models. The resampling of high-resolution grid data required to effectively use distributed models, however, can result in the distortion of terrain and hydrographic properties. In this study, we present a geographic information system approach for deriving multiple resolution meshes that conserve physiographic features while significantly reducing the number of computational nodes in a distributed hydrologic model. We utilize triangulated irregular networks ~TINs! which serve to integrate information on the surface topography, hydrographic features and land surface characteristics into an adaptive representation of a basin. We discuss three approaches for constructing TIN models for hydrologic applications: ~1! Traditional, ~2! hydrographic and ~3! hydrological similarityTINs. We focus on the generation of triangulated terrain models using the concept of hydrological similarity provided through a topographic or wetness index. This new method embeds an estimate of the steady-state hydrologic response directly into the basin terrain model. Through a series of case studies, we demonstrate the advantages of the multiple resolution approaches over a range of terrain characteristics, basin scales and elevation data products. Finally, we discuss the implications of TIN terrain representation for watershed simulation with the TIN-based Real-Time Integrated Basin Simulator model.

Production of digital elevation maps often requires interpolation of observations at particular locations. For hydrologicapplications the resulting surface should have well defined drainage directions, should reproduce the roughness of naturalterrain and should ideally preserve distributions of elevations, slopes and curvatures. The work of J. Niemann et al. (WaterResources Research, 2003, vol. 39, pp. 1017–1032) proposes a physically based interpolation method that is an improvementover commonly used linear or fractal interpolators. The methodology does have difficulty dealing with very sparse initialelevation and boundary flux information. This work suggests that using the commonly available horizontal location of mainchannels (‘blue lines’) improves the physical interpolation significantly. The results are illustrated on two river basins.Copyright © 2004 John Wiley & Sons, Ltd. KEY WORDS: digital elevation models; interpolation methods; erosion models; terrain analysis INTRODUCTIONThe first step in distributed hydrologic modelling is to build the computational framework using a digitalrepresentation of the topography. Digital elevation models (DEMs) are the most common digital representation.Since their introduction (Miller and Laflamme, 1958), models used for terrain representation have changed(Hutchinson and Gallant, 2000). Currently, DEMs are grids with regularly spaced elevation points. These gridsare generally constructed by linear interpolation between ground observation points. Hydrologists and geomorpho-logists commonly use publicly available DEMs built by national institutions such as USGS in the USA andIGM in Italy. Recently, investigators (Walker and Willgoose, 1999; Wise, 2000; Holmes

We explore the link between channel-bed texture and river basin concavity in equilibrium catchments using a numerical landscape evolution model. Theory from homogeneous sediment transport predicts that river basin concavity directly increases with bed sediment size. If the effective grain size on a river bed governs its concavity, then natural phenomena such as grain-size sorting and channel armouring should be linked to concavity. We examine this hypothesis by allowing the bed sediment texture to evolve in a transport-limited regime using a two grain-size mixture of sand and gravel. Downstream fining through selective particle erosion is produced in equilibrium. As the channel-bed texture adjusts downstream so does the local slope. Our model predicts that it is not the texture of the original sediment mixture that governs basin concavity. Rather, concavity is linked to the texture of the sorted surface layer. Two different textural regimes are produced in the experiments: a transitional regime where the mobility of sand and gravel changes with channel-bed texture, and a sanddominated region where the mobility of sand and gravel is constant. The concavity of these regions varies depending on the median gravel- or sand-grain size, erosion rate, and precipitation rate. The results highlight the importance of adjustments in both surface texture and slope in natural rivers in response to changes in fluvial and sediment inputs throughout a drainage network. This adjustment can only be captured numerically using multiple grain sizes or empirical downstream fining rules. Copyright © 2004 John Wiley & Sons, Ltd.

The benefits of short-term (1–6 h), distributed quantitative precipitation forecasts (DQPFs) are well known. However, this area is acknowledged to be one of the most challenging in hydrometeorology. Previous studies suggest that the “state of the art” methods can be enhanced by exploiting relevant information from radar and numerical weather prediction (NWP) models, using process physics and data-dictated tools where each fits best. Tests indicate that improved results are obtained by decomposing the overall problem into component processes, and that each process may require alternative tools ranging from simple interpolation to statistical time series models and artificial neural networks (ANNs). A new hybrid modeling strategy is proposed for DQPF that utilizes measurements from radar [Weather Surveillance Radar-1998 Doppler (WSR-88D) network: 4 km, 1 h] and outputs from NWP models (48-km Eta Model: 48 km, 6 h). The proposed strategy improves distributed QPF over existing methods like radar extr...

We develop a new method for analysis of meandering channels based on planform sinuosity. This analysis objectively identifies three channel-reach lengths based on sinuosity measured at those lengths: the length of typical, simple bends; the length of long, often compound bends; and the length of several bends in sequence that often evolve from compound bends to form multibend loops. These lengths, when normalized by channel width, tend to fall into distinct and clustered ranges for different natural channels. Mean sinuosity at these lengths also falls into distinct ranges. That range is largest for the third and greatest length, indicating that, for some streams, multibend loops are important for planform sinuosity, whereas for other streams, multibend loops are less important. The role of multibend loops is seldom addressed in the literature, and they are not well predicted by previous modelling efforts. Also neglected by previous modelling efforts is bank–flow interaction and its role in meander evolution. We introduce a simple river meandering model based on topographic steering that has more in common with cellular approaches to channel braiding and landscape evolution modelling than to rigorous, physics-based analyses of river meandering. The model is sufficient to produce reasonable meandering channel evolution and predicts compound bend and multibend loop formation similar to that observed in nature, in both mechanism and importance for planform sinuosity. In the model, the tendency to form compound bends is sensitive to the relative magnitudes of two lengths governing meander evolution: (i) the distance between the bend cross-over and the zone of maximum bank shear stress, and (ii) the bank shear stress dissipation length related to bank roughness. In our simple model, the two lengths are independent. This sensitivity implies that the tendency for natural channels to form compound bends may be greater when the banks are smoother. Copyright © 2002 John Wiley & Sons, Ltd.

We demonstrate that the global fields of temperature, humidity and geopotential heights admit a nearly sparse representation in the wavelet domain, offering a viable path forward to explore new paradigms of sparsity-promoting data assimilation and compressive recovery of land surface-atmospheric states from space. We illustrate this idea using retrieval products of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) on board the Aqua satellite. The results reveal that the sparsity of the fields of temperature is relatively pressure-independent while atmospheric humidity and geopotential heights are typically sparser at lower and higher pressure levels, respectively. We provide evidence that these land-atmospheric states can be accurately estimated using a small set of measurements by taking advantage of their sparsity prior., 12 pages, 8 figures, 1 table

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO

The conventional energy balance equation at land surface representing the repartition of net radiation into latent, sensible, and ground heat fluxes was revised to acknowledge the fact that sensible heat flux is always measured at a certain height level within the atmosphere even though the other components are well defined at the surface. A correction factor defined as the ratio of surface (skin) temperature to air temperature associated with the measured sensible heat flux term should be included in the energy balance equation. A preliminary test using independent measurements of radiation and heat fluxes shows that the revision improves the energy balance at the surface.

We describe a newset of data structures and algorithms for dynamic terrain modeling using a triangulated irregular network (TINs). The framework provides an efficient method for storing, accessing, and updating a Delaunay triangulation and its associated Voronoi diagram. The basic data structure consists of three interconnected data objects: triangles, nodes, and directed edges. Encapsulating each of these geometric elements within a data object makes it possible to essentially decouple the TIN representation from the modeling applications that make use of it. Both the triangulation and its corresponding Voronoi diagram can be rapidly retrieved or updated, making these methods well suited to adaptive remeshing schemes. We develop a set of algorithms for defining drainage networks and identifying closed depressions (e.g., lakes) for hydrologic and geomorphic modeling applications. We also outline simple numerical algorithms for solving network routing and 2D transport equations within the TIN framework. The methods are illustrated with two example applications, a landscape evolution model and a distributed rainfall-runoff model. # 2001 Elsevier Science Ltd. All rights reserved.

We investigate the connection between surface elevation and the growth and scaling of river networks. Three planar models (Scheidegger, Eden, and invasion percolation) are first considered. These models develop aggregating networks according to stochastic rules but do not simulate erosion because the network growth is independent of the surface elevation. We show that none of these planar growth models produces scaling results consistent with observations for natural river basins. We then modify the models to include elevation, simulating the effects of fluvial erosion by enforcing the slope-area relationship. The resulting configurations have scaling properties that still depend on the model (Scheidegger, Eden, or invasion percolation) but are closer to natural river networks when compared with those from the planar growth rules. We conclude that inclusion of the vertical dimension in these three models is critical for explaining the formation and regularities of fluvial networks. (C) 2001 Elsevier Science BN. All rights reserved.

Drainage density (D-d), defined as the total length of channels per unit area, is a fundamental property of natural terrain that reflects local climate, relief, geology, and other factors. Accurate measurement of D-d is important for numerous geomorphic and hydrologic applications, yet it is a surprisingly difficult quantity to measure, particularly over large areas. Here, we develop a consistent and efficient method for generating maps of D-d using digital terrain data. The method relies on (i) measuring hillslope flow path distance at every unchanneled site within a basin, and (ii) analyzing this field as a random space function. As a consequence, we measure not only its mean (which is half the inverse of the traditional definition of drainage density) but also its variance, higher moments, and spatial correlation structure. This yields a theoretically sound tool for estimating spatial variability of drainage density. Averaging length-to-channel over an appropriate spatial scale also makes it possible to derive continuous maps of D-d and its spatial variations. We show that the autocorrelation length scale provides a natural and objective choice for spatial averaging. This mapping technique is applied to a region of highly variable D-d in the northern Apennines, Italy. We show that the method is capable of revealing large-scale patterns of variation in D-d that are correlated with lithology and relief. The method provides a new and more general way to quantitatively define and measure D-d to test geomorphic models, and to incorporate D-d variations into regional-scale hydrologic models. (C) 2001 Elsevier Science B.V. All rights reserved.

Playfair's law (J. Playfair, illustrations of the Huttonian Theory of the Earth, 1802) requires any two tributaries in a river network to lower at the same rate near their junction. Although this law holds exactly at the junction, it is unclear how well it holds in the vicinity of the junction. This issue has practical importance because Playfair's law has been used to estimate parameters for detachment-limited models of erosion. If the incision rate of a stream is modelled as βAmSn, where β is an erodibility parameter, A is the area drained by the stream, and S is the local gradient of the channel, then the ratio of the parameters m/n can be estimated from junctions by assuming that Playfair's law holds over the distance used to determine S for each tributary. In this paper, Playfair's law and associated m/n estimates are evaluated for simulated basins with constant and temporally varying uplift rates (or baselevel lowering rates). The results demonstrate that estimates of m/n may be biased for basins with upward-concave stream profiles because the local slope must be approximated with an average upstream slope. In addition, when uplift rate varies temporally, knickpoints are shown to travel through the basins with constant vertical velocity. Because incision rates vary within the basin, Playfair's law only holds exactly at the junctions. These effects are more important when slopes are measured over longer distances. Finally, measurement techniques are presented which address these potential biases. Copyright © 2001 John Wiley & Sons, Ltd.

The heat exchange at the air/ground interface is determined by many complex processes making the energy balance at the earth's surface extremely difficult to quantify and model. A new methodology allows heat flux at the Earth's surface to be estimated using ground surface temperature history reconstructed from geothermal data. We found that over a large region in eastern and central Canada, the average heat flux into the ground during the last 1000 years was on the order of 2.8 mWm−2. Our results suggest that significant change in the ground heat flux occurred in the last two centuries. The 200 years averaged heat flux since 1765 is 17.0 mWm−2, while the average heat flux over the latest 100 years is 74.0 mWm−2. The sensitivity of the subsurface to very small energy imbalances makes these type of data and analysis useful complements to the paleoclimatic record; they also provide constrains for general circulation model land-surface parameterization over a wide range of spatial-temporal scales.

We develop a simple stochastic theory for erosion and sediment transport, based on the Poisson pulse rainfall model, in order to analyze how variability in rainfall and runoff influences drainage basin evolution. Two cases are considered: sediment transport by runoff in rills and channels and particle detachment from bedrock or cohesive soils. Analytical and numerical results show that under some circumstances, rainfall variability can have an impact equal to or greater than that of mean rainfall amount. The predicted sensitivity to rainfall variability is greatest when (1) thresholds for runoff generation and/or particle detachment are significant and/or (2) erosion and transport are strong nonlinear functions of discharge. In general, sediment transport capacity is predicted to increase with increasing rainfall variability. Depending on the degree of nonlinearity, particle detachment capacity may either increase or decrease with increasing rainfall variability. These findings underscore the critical importance of hydrogeomorphic thresholds and other sources of nonlinearity in process dynamics. The morphologic consequences of rainfall variability are illustrated by incorporating the pulse rainfall theory into a landscape simulation model. The simulation results imply that, all else being equal, catchments experiencing a shift toward greater climate variability will tend to have (1) higher erosion rates, (2) higher drainage density (because of increased runoff erosion efficiency), and ultimately (3) reduced relief. The stochastic approach provides a useful method for incorporating physically meaningful climate data within the current generation of landscape evolution models.

This paper presents a novel method that allows the diurnal variation of ground heat flux to be computed from the corresponding time series measurement of surface soil temperature. Soil temperature and soil heat flux over time at one location are uniquely related through a half-order derivative/integral operator when heat transfer in a soil matrix is described by a one-dimensional diffusion equation with a constant diffusivity parameter. Both simulated and observed data have been used to test the method. The case study suggests that the derived relationships between soil heat flux and soil temperature under idealized conditions provide satisfactory approximations for practical purposes. Close agreement of the estimated variables with observations indicates that this proposed method is promising. Its potential applications include the estimation of the regional energy balance at the land surface using remote sensing observations.

Catchment morphology and drainage density are strongly influenced by hillslope processes. The consequences of several different hillslope process laws are explored in a series of experiments with a numerical model of drainage basin evolution. Five different models are considered, including a simple diffusive-advective process transition, a runoff generation threshold, an erosion threshold, and two types of threshold-activated landsliding. These different hillslope processes alter both the visual appearance of the landscape and the predicted relationship between slope and contributing area. On the basis of the different threshold theories, we derive expressions for the relationships between drainage density and environmental factors such as rainfall, relief, and mean erosion rate. These relationships vary depending on the dominant hillslope threshold. In particular, the sign of the predicted relationship between drainage density and relief is positive in semiarid, low-relief landscapes and negative in humid landscapes dominated by a saturation threshold and/or in high-relief landscapes dominated by simple threshold landsliding.

A new method has been proposed for estimating sensible heat flux from single-level measurement of air temperature. When turbulent transfer of heat in the lower atmosphere over a homogeneous surface is modeled by a one-dimensional diffusion equation with a constant diffusivity, heat flux can be expressed as a weighted average (half-order derivative) of the time history of air temperature. This formula provides an approximate solution of the diffusion equation where the (eddy) diffusivity characterizing the turbulent flow is not constant. Eddy diffusivity has been formulated based on Monin-Obukhov similarity theory with Businger-Dyer stability functions or determined by an empirical equation. The knowledge of surface parameters including friction velocity sometimes is needed to apply this method. The method was tested against observations collected during two field experiments, FIFE and ABRACOS. The close agreement between the estimated sensible heat flux and observations suggests that this novel approach is a potentially powerful tool in evaluating the energy balance at the land surface.

This paper describes the first major attempt to compare seven different inverse approaches for identifying aquifer transmissivity. The ultimate objective was to determine which of several geostatistical inverse techniques is better suited for making probabilistic forecasts of the potential transport of solutes in an aquifer where spatial variability and uncertainty in hydrogeologic properties are significant. Seven geostatistical methods (fast Fourier transform (FF), fractal simulation (FS), linearized cokriging (LC), linearized semianalytical )LS), maximum likelihood (ML), pilot point (PP), and sequential self-calibration (SS)) were compared on four synthetic data sets. Each data set had specific features meeting (or not) classical assumptions about stationarity, amenability to a geostatistical description, etc. The comparison of the outcome of the methods is based on the prediction of travel times and travel paths taken by conservative solutes migrating in the aquifer for a distance of 5 km. Four of the methods, LS, ML, PP, and SS, were identified as being approximately equivalent for the specific problems considered. The magnitude of the variance of the transmissivity fields, which went as high as 10 times the generally accepted range for linearized approaches, was not a problem for the linearized methods when applied to stationary fields; that is, their inverse solutions and travel time predictions were as accurate as those of the nonlinear methods. Nonstationarity of the “true” transmissivity field, or the presence of “anomalies” such as high-permeability fracture zones was, however, more of a problem for the linearized methods. The importance of the proper selection of the semivariogram of the log10 (T) field (or the ability of the method to optimize this variogram iteratively) was found to have a significant impact on the accuracy and precision of the travel time predictions. Use of additional transient information from pumping tests did not result in major changes in the outcome. While the methods differ in their underlying theory, and the codes developed to implement the theories were limited to varying degrees, the most important factor for achieving a successful solution was the time and experience devoted by the user of the method.

Drainage density reflects the signature of climate on the topography and dictates the boundary conditions for surface hydrology. Hence defining the relationship between drainage density and climate is important in assessing the sensitivity of water resources and hydrology to climate change. Here we analyze the equilibrium relationship between drainage density and climate and estimate the relative sensitivity of drainage density to climate change. We conclude that the sign of the resulting change in drainage density depends not only on the direction of the change in climate but also on the prevailing climatic regime.

We present the analytical solutions to a hillslope-based formulation of subsurface storm flow and saturation overland flow. Here a hillslope is defined as the area between two streamlines originating from two ends of a channel link or from the channel head and ending at the ridgelines. The three-dimensional soil mantle of a hillslope is reduced to a one-dimensional profile along which the soil moisture and discharge are modeled. Continuity and a kinematic form of Darcy's law lead to quasi-linear wave equations solvable with the method of characteristics. Examples are given to illustrate the ability and limitations of the solutions in capturing the essential runoff behavior of different slope types.

Mesoscale circulations forced by a random distribution of surface sensible heat flux have been investigated using a three-dimensional numerical model. The complex land surface is modeled as a homogeneous random field characterized by a spectral distribution. Standard deviation and length scale of the sensible heat flux at the surface have been identified as the important parameters that describe the thermal variability of land surface. The form of the covariance of the random surface forcing is not critical in driving the mesoscale circulation. The thermally induced mesoscale circulation is significant and extends up to about 5 km when the atmosphere is neutral. It becomes weak and is suppressed when the atmosphere is stable. The mesoscale momentum flux is much stronger than the corresponding turbulent momentum flux in the neutral atmosphere, while the two are comparable in the stable atmosphere. The mesoscale heat flux has a different vertical profile than turbulent heat flux and may provide a major heat transport mechanism beyond the planetary boundary layer. The impact of synoptic wind on the mesoscale circulations is relatively weak. Nonlinear advection terms are responsible for momentum flux in the absence of synoptic wind.