D. Scott Mackay

Effects of spatial detail of soil information on watershed modeling

The impacts of detailed and spatially continuous soil information on hydro-ecological modeling over watersheds of mesoscale size are investigated. The impacts were assessed by comparing the simulated hydro-ecological responses based on the detailed soil spatial information derived from a fuzzy logic-based inference approach with those based on the soil information derived from a conventional soil map. This study reveals that the detailed soil spatial information has impacts on the simulated hydro-ecological responses under a lumped parameter approach. Peak runoff was reduced, yielding more realistic hydrographs for forested watersheds in the area. The detailed soil spatial information strongly impacted the simulation of net photosynthesis over the period when there is a moisture stress, but negligible impacts when there is sufficient water recharge to soil profiles. Simulation of hydro-ecological responses using a distributed parameter approach is less impacted by the detailed soil spatial information. The difference in simulated net photosynthesis under the distributed approach is smaller and also only occurred during the period of moisture stress. The impacts on spatial distribution of simulated transpiration occurred mainly over south facing slopes during the period of moisture stress.

Forest ecosystem processes at the watershed scale: dynamic coupling of distributed hydrology and canopy growth

The hydrological recovery of watersheds from disturbances such as fire and harvest can change the magnitude and distribution of flow paths as the canopy regenerates. The spatial distribution of net water input to the soil‐topography system is mediated by vegetation patterns through the processes of interception, evapotranspiration and snowmelt. We have previously described RHESSys, a distributed model of water and carbon flux with a prescribed canopy cover. Although the canopy structure varied spatially it did not change through time. We present an expanded model in which carbon and nitrogen are dynamically coupled with distributed hydrology. The model fixes and allocates canopy carbon annually to reflect changes in climate forcing. We test the interactions of the forest ecosystem to distributed hydrology through controlled experiments. In the first experiment, we prescribe canopy cover and examine the sensitivity of the hydrological outputs to the distribution of vegetation. The canopy distribution is found to have significant eAects on simulated hydrological outputs where evaporative demand exceeds available water. In a second experiment we simulate the canopy leaf area index (LAI) across the topography and through time. The model is executed over 100 years using repeated 10-year meteorological records to investigate spatial and temporal patterns of LAI. Annual precipitation and temperature diAerences result in temporally fluctuating LAI about a reasonably stable long-term mean. The topographical position has a strong eAect on local forest canopy characteristics. As expected, simulated ecosystem processes are found to be sensitive to rooting depth in more water limited environments. #1997 by John Wiley & Sons, Ltd.

EXTRACTION AND REPRESENTATION OF NESTED CATCHMENT AREAS FROM DIGITAL ELEVATION MODELS IN LAKE-DOMINATED TOPOGRAPHY

This paper presents a new method for extracting flow directions, contributing (upslope) areas, and nested catchments from digital elevation models in lake-dominated areas. Existing tools for acquiring descriptive variables of the topography, such as surface flow directions and contributing areas, were developed for moderate to steep topography. These tools are typically difficult to apply in gentle topography owing to limitations in explicitly handling lakes and other flat areas. This paper addresses the problem of accurately representing general topographic features by first identifying distinguishing features, such as lakes, in gentle topography areas and then using these features to guide the search for topographic flow directions and catchment marking. Lakes are explicitly represented in the topology of a watershed for use in water routing. Nonlake flat features help guide the search for topographic flow directions in areas of low signal to noise. This combined feature-based and grid-based search for topographic features yields improved contributing areas and watershed boundaries where there are lakes and other flat areas. Lakes are easily classified from remotely sensed imagery, which makes automated representation of lakes as subsystems within a watershed system tractable with widely available data sets.

A general model of watershed extraction and representation using globally optimal flow paths and up-slope contributing areas

Many modern hydrological models require data inputs provided by automated digital terrain analysis functions incorporated into GIS. These inputs include fields representing surface flow directions, up-slope contributing areas, and sub-catchment partitions. Existing raster-based terrain analysis tools, including both those in off-the-shelf GIS packages and those in the recent literature, were designed to work with digital elevation data in mountainous topography. For highly variable topography, which may include large flood plains, lakes, wetlands, and other relatively flat areas, existing tools cannot accommodate the variable signal-to-noise in the source elevation data without significant human intervention to handle special cases. A general model for calculating flow directions, up-slope contributing areas, and sub-catchment partitions that automatically adapts to the variable information content of grid-based elevation data sets is presented here. The model uses a combination of breadth-first search and global optimization to extract the maximum amount of signal from any location within the data. The model is demonstrated to work well in handling topography dominated by large flood plains, lakes and other flat areas without the need for a large number of empirical rules. An important contribution of the approach is the handling of explicit hydrologic features, which makes the spatial representation closely related to hydrological processes. The results have important implications for developing hydrological models that are tractable in large, heterogeneous watersheds using moderate resolution data.

Interdependence of chronic hydraulic dysfunction and canopy processes can improve integrated models of tree response to drought

Hydraulic systems of plants have evolved in the context of carbon allocation and fitness trade-offs of maximizing carbon gain and water transport in the face of short and long-term fluctuations in environmental conditions. The resulting diversity of traits include a continuum of isohydry-anisohydry or high to low relative stomatal closure during drought, shedding of canopy foliage or disconnecting roots from soil to survive drought, and adjusting root areas to efficiently manage canopy water costs associated with photosynthesis. These traits are examined within TREES, an integrated model that explicitly couples photosynthesis and carbon allocation to soil-plant hydraulics and canopy processes. Key advances of the model are its ability to account for differences in soil and xylem cavitation, transience of hydraulic impairment associated with delayed or no refilling of xylem, and carbon allocation to plant structures based on photosynthetic uptake of carbon and hydraulic limitations to water transport. The model was used to examine hydraulic traits of cooccurring isohydric (pinon pine) and anisohydric (one-seed juniper) trees from a field-based experimental drought. Model predictions of both transpiration and leaf water potential were improved when there was no refilling of xylem over simulations where xylem was able refill in response to soil water recharge. Model experiments with alternative root-to-leaf area ratios (RR/L) showed the RR/L that supports maximum cumulative water use is not beneficial for supporting maximum carbon gain during extended drought, illustrating how a process model reveals trade-offs in plant traits.

A multiple criteria decision support system for testing integrated environmental models

Abstract Spatial models of ecological and hydrological processes are widely used tools for studying natural systems over large areas. However, these models lack specific mechanisms for reporting output uncertainty contributed by model structure, and so testing their suitability for studying a large range of problems is difficult. This paper describes a method of evaluating the uncertainty contributed by underlying assumptions used in constructing integrated environmental models from two or more sub-models that were developed for different purposes. Integrated environmental models are typically constructed from many individual process-based models. Conflicting assumptions between these sub-models, e.g., spatial scale differences, are easily overlooked during model development and application. This “semantic error” cannot be predicted prior to simulation, as it may only emerge through the interaction of sub-models applied to a particular set of data used to drive a simulation. Model agreement is proposed and demonstrated as a way to detect problems of model integration at the state variable level within an integrated ecosystem model. This model agreement is then propagated to model response variables using multiple criteria to examine their sensitivity, predictability, and synchronicity to the measured uncertainty in state variables. These three properties are combined under fuzzy logic in order to provide decision support on where, for a given time during simulation the sub-models agree on a particular response variable. This paper describes the details of the approach and its application using an existing integrated environmental model. The results show that, for a given set of model inputs and application, integrated environmental models may have spatially variable levels of agreement at the sub-model level. The results using RHESSysD, a spatially integrated ecosystem hydrology model, indicate that semantic error in estimates of plant available soil moisture are consistent with observations of the need for resetting events, such as flooding, to initialize the model to a point where further simulation results can be trusted. These results suggest that a dynamic selection of sub-models may be warranted given a reasonable method of determining sub-model disagreement during simulation. Fuzzy set theory may be a useful tool in arriving at such a model selection process as it allows for a relatively straightforward synthesis of numerous model evaluation criteria with a large quantity of output from the model.

Multi-objective parameter estimation for simulating canopy transpiration in forested watersheds

A Jarvis based [Philos. Trans. R. Soc. London, Ser. B 273 (1976) 593] model of canopy stomatal conductance was evaluated in context of its application to simulating transpiration in a conifer forest covered watershed in the Central Sierra Nevada of California, USA. Parameters influencing stomatal conductance were assigned values using Monte Carlo sampling. Model calibration was conducted by evaluating predicted latent heat fluxes against thermal remote sensing estimates of surface temperature. A fuzzy logic approach was used to select or reject simulations and form a restricted set of ensemble parameter solutions. Parameter estimates derived from the ensembles were evaluated using theory on how stomatal conductance regulates leaf water potential to prevent runaway cavitation. Canopy level parameters were found to be sufficient for predicting hydraulically consistent transpiration when soils were well watered. A rooting length parameter controlling the amount of plant available water was a sufficient addition to the parameter set to predict hydraulically consistent transpiration when soil moisture stress was occurring. Variations in maximum stomatal conductance among different hillslopes within the watershed were explained by a light threshold parameter. The results demonstrate that the Jarvis model can be reliably parameterized using thermal remote sensing data for estimating transpiration in meso-scale watersheds. q 2003 Elsevier Science B.V. All rights reserved.

On the representativeness of plot size and location for scaling transpiration from trees to a stand

[1] Scaling transpiration from trees to larger areas is a fundamental problem in ecohydrology. For scaling stand transpiration from sap flux sensors we asked if plot representativeness depended on plot size and location, the magnitude of environmental drivers, parameter needs for ecosystem models, and whether the goal was to estimate transpiration per unit ground area (E C ), per unit leaf area (E L ), or canopy stomatal conductance (G S ). Sap flux data were collected in 108 trees with heat dissipation probes, and biometric properties were measured for 752 trees within a 1.44 ha Populus tremuloides stand along an upland-to-wetland gradient. E C was estimated for the stand using eight different plot sizes spanning a radius of 2.0-12.0 m. Each estimate of E C was derived from 200 plots placed randomly throughout the stand. We also derived leaf area index (L), canopy closure (P CC ), and the canopy average reference stomatal conductance (G Sref ), which are key parameters used in modeling transpiration and evapotranspiration. With increasing plot size, E C declined monotonically but E L and G Sref were largely invariant. Interplot variance of E C also declined with increasing plot size, at a rate that was independent of vapor pressure deficit. Plot representativeness was dependent on location within the stand. Scaling to the stand required three plots spanning the upland to wetland, with one to at most 10 trees instrumented for sap flux. Plots that were chosen to accurately reflect the spatial covariation of L, P CC , and G Sref were most representative of the stand.

Evaluation of hydrologic equilibrium in a mountainous watershed: incorporating forest canopy spatial adjustment to soil biogeochemical processes

Abstract Hydrologic equilibrium theory has been used to describe both short-term regulation of gas exchange and long-term adjustment of forest canopy density. However, by focusing on water and atmospheric conditions alone a hydrologic equilibrium may impose an oversimplification of the growth of forests adjusted to hydrology. In this study nitrogen is incorporated as a third regulation of catchment level forest dynamics and gas exchange. This was examined with an integrated distributed hydrology and forest growth model in a central Sierra Nevada watershed covered primarily by old-growth coniferous forest. Water and atmospheric conditions reasonably reproduced daily latent heat flux, and predicted the expected catenary trend of leaf area index (LAI). However, it was not until the model was provided a spatially detailed description of initial soil carbon and nitrogen pools that spatial patterns of LAI were generated. This latter problem was attributed to a lack of soil history or memory in the initialization of the simulations. Finally, by reducing stomatal sensitivity to vapor pressure deficit (VPD) the canopy density increased when water and nitrogen limitations were not present. The results support a three-control hydrologic equilibrium in the Sierra Nevada watershed. This has implications for modeling catchment level soil–vegetation–atmospheric interactions over interannual, decade, and century time-scales.

Predicting stomatal responses to the environment from the optimization of photosynthetic gain and hydraulic cost.

Stomatal regulation presumably evolved to optimize CO2 for H2 O exchange in response to changing conditions. If the optimization criterion can be readily measured or calculated, then stomatal responses can be efficiently modelled without recourse to empirical models or underlying mechanism. Previous efforts have been challenged by the lack of a transparent index for the cost of losing water. Yet it is accepted that stomata control water loss to avoid excessive loss of hydraulic conductance from cavitation and soil drying. Proximity to hydraulic failure and desiccation can represent the cost of water loss. If at any given instant, the stomatal aperture adjusts to maximize the instantaneous difference between photosynthetic gain and hydraulic cost, then a model can predict the trajectory of stomatal responses to changes in environment across time. Results of this optimization model are consistent with the widely used Ball-Berry-Leuning empirical model (r2  > 0.99) across a wide range of vapour pressure deficits and ambient CO2 concentrations for wet soil. The advantage of the optimization approach is the absence of empirical coefficients, applicability to dry as well as wet soil and prediction of plant hydraulic status along with gas exchange.