[1] It is necessary to improve our understanding of the exchange of dissolved constituents between surface and subsurface waters in river systems in order to better evaluate the fate of water-borne contaminants and nutrients and their effects on water quality and aquatic ecosystems. Here we present a model that can predict hyporheic exchange at the bed-form-to-reach scale using readily measurable system characteristics. The objective of this effort was to compare subsurface flow induced at scales ranging from very small scale bed forms up to much larger planform geomorphic features such as meanders. In order to compare exchange consistently over this range of scales, we employed a spectral scaling approach as the basis for a generalized analysis of topography-induced stream-subsurface exchange. The spectral model involves a first-order approximation for local flow-boundary interactions but is fully three-dimensional and includes the lateral hyporheic zone in addition to the flow directly beneath the streambed. The primary model input parameters are stream velocity and slope, sediment permeability and porosity, and detailed measurements of the stream channel topography. The primary outputs are the distribution of water flux across the stream channel boundary, the resulting pore water flow paths, and the subsurface residence time distribution. We tested the bed-formexchange component of the model using a highly detailed two-dimensional data set for exchange with ripples and dunes and then applied the model to a three-dimensional meandering stream in a laboratory flume. Having spatially explicit information allowed us to evaluate the contributions of both gravitational and current-driven hyporheic flow through various classes of stream channel features including ripples, dunes, bars, and meanders. The model simulations indicate that all scales of topography between ripples and meanders have a significant effect on pore water flow fields and residence time distributions. Furthermore, complex interactions across the spectrum of topographic features play an important role in controlling the net interfacial flux and spatial distribution of hyporheic exchange. For example, shallow exchange induced by current-driven interactions with small bed forms dominates the interfacial flux, but local pore water flows are modified significantly by larger-scale surface-groundwater interactions. As a result, simplified representations of the stream topography do not adequately characterize patterns and rates of hyporheic exchange.

[1] Hyporheic flow in streams has typically been studied separately from geomorphic processes. We investigated interactions between bed mobility and dynamic hyporheic storage of solutes and fine particles in a sand-bed stream before, during, and after a flood. A conservatively transported solute tracer (bromide) and a fine particles tracer (5 mm latex particles), a surrogate for fine particulate organic matter, were co-injected during base flow. The tracers were differentially stored, with fine particles penetrating more shallowly in hyporheic flow and retained more efficiently due to the high rate of particle filtration in bed sediment compared to solute. Tracer injections lasted 3.5 h after which we released a small flood from an upstream dam one hour later. Due to shallower storage in the bed, fine particles were rapidly entrained during the rising limb of the flood hydrograph. Rather than being flushed by the flood, we observed that solutes were stored longer due to expansion of hyporheic flow paths beneath the temporarily enlarged bedforms. Three important timescales determined the fate of solutes and fine particles: (1) flood duration, (2) relaxation time of flood-enlarged bedforms back to base flow dimensions, and (3) resulting adjustments and lag times of hyporheic flow. Recurrent transitions between these timescales explain why we observed a peak accumulation of natural particulate organic matter between 2 and 4 cm deep in the bed, i.e., below the scour layer of mobile bedforms but above the maximum depth of particle filtration in hyporheic flow paths. Thus, physical interactions between bed mobility and hyporheic transport influence how organic matter is stored in the bed and how long it is retained, which affects decomposition rate and metabolism of this southeastern Coastal Plain stream. In summary we found that dynamic interactions between hyporheic flow, bed mobility, and flow variation had strong but differential influences on base flow retention and flood mobilization of solutes and fine particulates. These hydrogeomorphic relationships have implications for microbial respiration of organic matter, carbon and nutrient cycling, and fate of contaminants in streams.Citation: Harvey, J. W., et al. (2012), Hydrogeomorphology of the hyporheic zone: Stream solute and fine particle interactions with a dynamic streambed,

[1] Stream channel morphology from grain-scale roughness to large meanders drives hyporheic exchange flow. In practice, it is difficult to model hyporheic flow over the wide spectrum of topographic features typically found in rivers. As a result, many studies only characterize isolated exchange processes at a single spatial scale. In this work, we simulated hyporheic flows induced by a range of geomorphic features including meanders, bars and dunes in sand bed streams. Twenty cases were examined with 5 degrees of river meandering. Each meandering river model was run initially without any small topographic features. Models were run again after superimposing only bars and then only dunes, and then run a final time after including all scales of topographic features. This allowed us to investigate the relative importance and interactions between flows induced by different scales of topography. We found that dunes typically contributed more to hyporheic exchange than bars and meanders. Furthermore, our simulations show that the volume of water exchanged and the distributions of hyporheic residence times resulting from various scales of topographic features are close to, but not linearly additive. These findings can potentially be used to develop scaling laws for hyporheic flow that can be widely applied in streams and rivers.

[1] Improved predictions of hyporheic exchange based on easily measured physical variables are needed to improve assessment of solute transport and reaction processes in watersheds. Here we compare physically based model predictions for an Indiana stream with stream tracer results interpreted using the Transient Storage Model (TSM). We parameterized the physically based, Multiscale Model (MSM) of stream-groundwater interactions with measured stream planform and discharge, stream velocity, streambed hydraulic conductivity and porosity, and topography of the streambed at distinct spatial scales (i.e., ripple, bar, and reach scales). We predicted hyporheic exchange fluxes and hyporheic residence times using the MSM. A Continuous Time Random Walk (CTRW) model was used to convert the MSM output into predictions of in stream solute transport, which we compared with field observations and TSM parameters obtained by fitting solute transport data. MSM simulations indicated that surface-subsurface exchange through smaller topographic features such as ripples was much faster than exchange through larger topographic features such as bars. However, hyporheic exchange varies nonlinearly with groundwater discharge owing to interactions between flows induced at different topographic scales. MSM simulations showed that groundwater discharge significantly decreased both the volume of water entering the subsurface and the time it spent in the subsurface. The MSM also characterized longer timescales of exchange than were observed by the tracerinjection approach. The tracer data, and corresponding TSM fits, were limited by tracer measurement sensitivity and uncertainty in estimates of background tracer concentrations. Our results indicate that rates and patterns of hyporheic exchange are strongly influenced by a continuum of surface-subsurface hydrologic interactions over a wide range of spatial and temporal scales rather than discrete processes.

Heterogeneity in hydraulic conductivity (K) and channel morphology both control surface water‐groundwater exchange (hyporheic exchange), which influences stream ecosystem processes and biogeochemical cycles. Here we show that heterogeneity in K is the dominant control on exchange rates, residence times, and patterns in hyporheic zones with abrupt lithologic contrasts. We simulated hyporheic exchange in a representative low‐gradient stream with 300 different bimodal K fields composed of sand and silt. Simulations span five sets of sand‐silt ratios and two sets of low and high K contrasts (1 and 3 orders of magnitude). Heterogeneity can increase interfacial flux by an order of magnitude relative to homogeneous cases, drastically changes the shape of residence time distributions, and tends to decrease median residence times. The positioning of highly permeable sand bodies controls patterns of interfacial flux and flow paths. These results are remarkably different from previous studies of smooth, continuous K fields that indicate only moderate effects on hyporheic exchange. Our results also show that hyporheic residence times are least predictable when sand body connectivity is low. As sand body connectivity increases, the expected residence time distribution (ensemble average for a given sand‐silt ratio) remains approximately constant, but the uncertainty around the expectation decreases. Including strong heterogeneity in hyporheic models is imperative for understanding hyporheic fluxes and solute transport. In streams with strongly heterogeneous sediments, characterizing lithologic structure is more critical for predicting hyporheic exchange metrics than characterizing channel morphology.

[1] High resolution synchrotron-based X-ray computed microtomography (X-CMT) was used to identify the morphology of colloidal deposits formed in porous media. We show that difference microtomography -whereby a tomographic reconstruction is performed across an absorption edge -provides valuable information on the nature and location of the aggregates formed by the deposition of colloidal particles. Column experiments were performed using an idealized porous medium consisting of glass beads through which colloidal ZrO 2 particles were transported. Tomographic reconstructions of the porous medium and of the aggregate structure provide an unique opportunity to observe colloidal particle deposits and of their morphology. These results show that the local pore geometry controls particle deposition and that deposits tend to form in a rather heterogeneous manner in the porous medium.

Variations in permeability have been found to significantly affect the flow of water though hyporheic systems, especially in regions with discontinuous transitions between distinct streambed lithologies. In this study, we probabilistically arranged two sediments (sand and sandy gravel) in a grid framework and imposed a single hyporheic flow cell across the grid to investigate how discontinuous permeability fields influence volumetric flow and residence time distributions. We used both a physical system and computer simulations to model flow through this sediment grid. A solution of blue dye and salt was pumped into the system and used to detect flow. We recorded the dye location using time-lapse photography and measured the electrolytic conductivity levels as the water exited the system as a proxy for salt concentration. We also used a computer simulation to calculate dye-fronts, residence times, and exiting salt concentrations for the modeled system. Comparison between simulations and physical measurements yielded strong agreement. In further simulations with 300 different grids, we found a strong correlation between volumetric flow rate and the placement of high permeability grid cells in regions of high hydraulic head gradients. One implication is that small anomalies in streambed permeability have a disproportionately large influence on hyporheic flows when located near steep head gradients such as steps. We also used moving averages with varying window sizes to investigate the effect of the abruptness of transitions between sediment types. We found that smoother permeability fields increased the volumetric flow rate and decreased the median residence times.

For many large-scale combinatorial search/optimization problems, meta-heuristic algorithms face noisy objective functions, coupled with computationally expensive evaluation times. In this work, we consider the interaction between the technique of "fitness caching" and the straightforward noise reduction approach of "fitness averaging" by repeated sampling. Fitness caching changes how noise affects a fitness landscapes, as noisy values become frozen in the cache. Assuming the use of fitness caching, we seek to develop heuristic methods for predicting the optimal number of sampling replications for fitness averaging. We derive two analytic measures for quantifying the effects of noise on a cached fitness landscape (probabilities of creating "false switches" and "false optima"). We empirically confirm that these measures correlate well with observed probabilities on a set of four well-known test-bed functions (sphere, Rosenbrock, Rastrigin, Schwefel). We also present results from a preliminary experimental study on these landscapes, investigating four possible heuristic approaches for predicting the optimal sampling, using a random-mutation hill-climber with fitness caching.There are a number of problem features that universally pose challenges for all metaheuristic search/optimization processes: predominant among these are noise/uncertainty, and the slowness of fitness evaluation (i.e., the time necessary to evaluate the objective function for any point in the search space). The presence of noise in a fitness function impedes making accurate comparisons between candidate solutions, or knowing how close the search process is to reaching a certain performance objective. In many cases, it is possible to use an average of many independent fitness function evaluations in order to reduce the noise. The length of time required for a single fitness evaluation can be significant, as it expands the length of the search by a direct multiplicative factor, and limits the number of evaluations possible for the search. Sometimes it is possible to use a less accurate surrogate fitness function, which can be evaluated more quickly, but at the cost of additional noise in the fitness estimates (for a survey of fitness approximation, refer to [7]). In general, it is impossible to eliminate both of these problem features, although there are many problems where trade-offs can be made between the two.When fitness evaluation is particularly computationally expensive (e.g., in large complex simulations), it is sometimes attractive to cache fitness values for re-use, to save the cost of re-evaluating them again later. At least in some non-noisy optimization problems, this has been shown to be an effective approach for reducing total computational cost [11,12], and we believe there is potential for applying it to noisy search spaces as well. In this work, we apply a combination of formal and empirical methods to try to investigate the relationship between fitness caching and the noise reduction technique fitness averaging by repeated samplin...