Integrated Approaches in Hydrological Process Studies I
Presiding: K McGuire, Georgia Institute of Technology; M Weiler, University of British Columbia
H13D-01 INVITED 13:30h
Integrated process studies and dynamical upscaling from the observation scale to the catchment scale
A cardinal problem in hydrology is what we call the "scale gap" in understanding. We urgently need representative data on dynamics of surface and subsurface state variables at the catchment scale, for e.g., as additional performance measures for validating meso-scale models. However, due to the known shortcomings of geophysical measurement techniques such as time domain reflectometry (TDR), ground penetrating radar (GPR) or geo electrics, our observations, and therefore also our process understanding, are restricted to the point or small field scale. Common ways to assess e.g. information on the space-time pattern of soil moisture at larger scales is to perform a distributed set of point observations either using mobile sensors, such as the "green machine", or a fixed set of TDR stations distributed in a catchment. The first approach is restricted to field campaigns and does not yield continuous information in time. The latter suffers from the fact that the correlation structure of soil moisture depends on the saturation state of the catchment. Hence, especially in dry states the network might be too coarse for explaining spatial variability of soil moisture in a geo-statistical sense. Whatever measurement approach is employed, there is no easy way to scale the information from the distributed set of small scale observations to the catchment scale because of non-linear process dynamics and strong sub-catchment heterogeneity of soils and vegetation. Geostatistical interpolation including updating approaches suffer from the fact that they either assume stationary relations between drift parameters and soil moisture or the sampling is not sufficient to obtain useful posterior probability distributions of soil moisture within different classes of available soft information. In this study we present an approach for integrated process studies in catchments by comparing principles from landscape ecology such as the pattern process paradigm with physical reasoning/modelling. The first is used to optimise a distributed network small scale hydrological observation network e.g. for soil moisture based on the dominating patterns of soils, topography and plant communities. The process model is used for something we call "dynamic" upscaling of local observations to the catchment scale. The proposed concept of integrated process studies and dynamical upscaling is discussed for a catchment in the Austrian alps and a catchment in South West of Germany.
H13D-02 13:45h
Equivalence of Hydraulic Functions and Its Implication on Upscaling for Steady State Flux and Surface Soil Moisture in Heterogeneous Soils
Soil hydraulic properties at large scales (e.g., remote sensing footprints) are important for land-atmosphere interaction and general circulation models or other applications. This study investigates two major issues involving soil hydraulic properties: (1) hydraulic parameter equivalence among some of the more commonly used soil hydraulic conductivity functions, and (2) its implication in upscaling of hydraulic properties to large scales for steady-state flow in heterogeneous soils. We first establish parameter equivalence among the conductivity functions based on hydrologic process equivalence. We propose two important equivalence criteria based on hydraulic behavior equivalence. Our approach forces both the predicted flux across the soil surface and the surface soil moisture content to be the same for the different hydraulic property functions. We selected these two hydrologic quantities for the equivalence purpose since they are important state variables in upscaling of hydrologic processes from local scale to footprint scale. Next we investigate the significance of parameter equivalence on upscaling schemes for the hydraulic parameters to allow predictions of the ensemble characteristics for steady-state flow at large scales.
H13D-03 14:00h
Inverting Electromagnetic Data to Identify Soil Hydraulic Properties in Northern New South Wales, Australia
Pressure on water resources in Northern New South Wales, Australia has increased interest in water use efficiency, with variations in soil hydraulic properties being the main focus for management. Recent studies have shown that the clay-dominated alluvial plains commonly contain buried streams (often referred to as "palaeochannels" or "relict streams") which appear to have dramatic effects on subsurface water movement. Groundwater simulations are required for evaluating management options on potential sites; however their use is limited by a sparse 3-dimensional data set in Australia. Electromagnetic induction methods (EM) are a useful way to augment soil survey information, but they are traditionally limited to mapping lateral variations due to the nature of the equipment. In this research we use a combination of EM instruments at different frequencies and heights above the surface to delineate field-scale vadose zone heterogeneities which are likely to affect water movement. This paper compares various techniques for inverting the electromagnetic data including multiple linear regression, Tikhonov regularization, and 1-D inversion with lateral constraints. We will subsequently show how the different inversion techniques affect the behavior of a 2-D groundwater model based on 11 transects located within two differing management schemes. The results will help to explain effective sampling and measurement schemes for hydrological investigations in highly conductive areas with contrasting soil textures.
H13D-04 INVITED 14:15h
Spatial variation of surface hydrological dynamics in semi-arid landscapes
The interactive manner by which abiotic and biotic determinants of resource availability lead to the formation and maintenance of observed ecological patterns is critical to the development of theories regarding the dynamics and diversity of terrestrial ecosystems. Similarly, the challenge of understanding the mechanisms by which the spatial pattern of hydrological fluxes arise within the dynamics of surface hydrological processes is central to the practice of hydrology. In this regard, the space-time distribution of soil moisture provides a crucial link between hydrological and biogeophysical processes through its controlling influence on transpiration, runoff generation, carbon assimilation and nutrient absorption by plants. The emerging science of ecohydrology has provided a framework for the integrated analysis of the coupled ecological-geophysical processes that govern surface water balance in terrestrial landscapes. My talk will focus on the spatial aspects of ecohydrological interactions between plants, soils, and climates in semi-arid landscapes, and will seek to link observed patterns in vegetation organization with the hydrological dynamics operating within landscapes organized around river networks and those that are not.
H13D-05 INVITED 14:30h
Are Big Basins Just the Sum of Small Catchments?
2 Many challenges remain in extending our understanding of how hydrologic processes within small catchments scale to larger river basins. We examine how low-flow runoff varies as a function of basin scale at 11 catchments, many of which are nested, in the 176km2 Neversink River watershed in the Catskill Mountains of New York. Topography, vegetation, soil and bedrock structure are similar across this river basin, and previous research has demonstrated the importance of deep groundwater springs for maintaining low-flow stream discharge at small scales in the basin. Therefore, we hypothesized that deep groundwater would contribute an increasing amount to low-flow discharge as basin scale increased, resulting in increased runoff. Instead, we find that, above a critical basin size of 8 to 21km2, low-flow runoff is similar within the Neversink watershed. These findings are broadly consistent with those of a previous study that examined stream chemistry as a function of basin scale for this watershed. However, we find physical evidence of self-similarity among basins greater than 8km2, whereas the previous study found gradual changes in stream chemistry among basins greater than 3km2. We believe that a better understanding of self-similarity and the subsurface flow processes that affect streamrunoff will be attained through simultaneous consideration of both chemical and physical evidence. We also suggest that similar analyses of stream runoff in other basins that represent a range of spatial scales, geomorphologies and climate conditions will further elucidate the issue of scaling of hydrologic processes.
H13D-06 14:45h
Multilayer Control Hierarchy in an Integrated Hydrological Model
Considerable progress has been made in the functionality of integrated hydrological models which can provide evaluation of anthropogenic control and management policies of water resources. Nonetheless, there is still room for improvement in the coupling and expression of water control policies into hydrological models [1]. The Management Simulation Engine (MSE) component of the Regional Simulation Model (RSM) incorporates a multi-level hierarchical control architecture which emphasizes the decoupling of hydrological state information from the management information processing applied to the states. The MSE is intended to allow a flexible, extensible expression of a wide variety anthropogenic water resource control schemes integrated with the hydrological state evaluations of the RSM. Synergy between the multilayer control hierarchy and decoupled hydrologic state and management information facilitates a water resource management feature set not typical of integrated hydrological models. Some of these features include: interoperation and compatibility of diverse management algorithms such as PID, Fuzzy control, LP; and dynamic switching of control processors. This paper describes the MSE control hierarchy with a focus on the aforementioned features and their implementation. [1] Belaineh, G., Peralta, R. C., Hughes, T. C., Simulation/ Optimization Modeling for Water Resources Management, ASCE Journal Water Resources Planning Management, 125(3), p 154-61, 1999