Temporal and spatial variability in the Guadalquivir estuary: a challenge for real-time telemetry

Meteorological, hydrological, and hydrodynamic data for 3 years (2008–2010) have been used to document and explain the temporal and spatial variability of the physical–biogeochemical interactions in the Guadalquivir River Estuary. A real-time, remote monitoring network has been deployed along the course of the river between its mouth and Seville to study a broad range of temporal scales (semidiurnal, diurnal, fortnightly, and seasonal). This network consists of eight hydrological monitoring stations capable of measuring temperature, conductivity, dissolved oxygen, turbidity, and chlorophyll fluorescence at four depths. In addition, six stations have been deployed to study hydrodynamics, obtaining 20-cell water column current profiles, and there is a meteorological station at the river mouth providing data for understanding atmospheric interactions. Completing this data-gathering network, there are several moorings (tide gauges, current/wave sensors, and a thermistor chain) deployed in the estuary and river mouth. Various sources of physical forcing, such as wind, tide-associated currents, and river discharge, are responsible for the particular temporal and spatial patterns of turbidity and salinity found in the estuary. These variables force the distribution of biogeochemical variables, such as dissolved oxygen and chlorophyll fluorescence. In particular, episodes of elevated turbidity (when suspended particle matter concentration >3,000 mg/l) have been detected by the network, together with episodes of declining values of salinity and dissolved oxygen. All these patterns are related to river discharge and tidal dynamics (spring/neap and high/low tide).     

Interactions and connectivity between runoff generation processes of different spatial scales

Monitoring runoff generation processes in the field is a prerequisite for developing conceptual hydrological models and theories. At the same time, our perception of hydrological processes strongly depends on the spatial and temporal scale of observation. Therefore, the aim of this study is to investigate interactions between runoff generation processes of different spatial scales (plot scale, hillslope scale, and headwater scale). Different runoff generation processes of three hillslopes with similar topography, geology and soil properties, but differences in vegetation cover (grassland, coniferous forest, and mixed forest) within a small v‐shaped headwater were measured: water table dynamics in wells with high spatial and temporal resolution, subsurface flow (SSF) of three 10 m wide trenches at the bottom of the hillslopes subdivided into two trench sections each, overland flow at the plot scale, and catchment runoff. Bachmair et al. ( 2012 ) found a high spatial variability of water table dynamics at the plot scale. In this study, we investigate the representativity of SSF observations at the plot scale versus the hillslope scale and vice versa, and the linkage between hillslope dynamics (SSF and overland flow) and streamflow. Distinct differences in total SSF within each 10 m wide trench confirm the high spatial variability of the water table dynamics. The representativity of plot scale observations for hillslope scale SSF strongly depends on whether or not wells capture spatially variable flowpaths. At the grassland hillslope, subsurface flowpaths are not captured by our relatively densely spaced wells (3 m), despite a similar trench flow response to the coniferous forest hillslope. Regarding the linkage between hillslope dynamics and catchment runoff, we found an intermediate to high correlation between streamflow and hillslope hydrological dynamics (trench flow and overland flow), which highlights the importance of hillslope processes in this small watershed. Although the total contribution of SSF to total event catchment runoff is rather small, the contribution during peak flow is moderate to substantial. Additionally, there is process synchronicity between spatially discontiguous measurement points across scales, potentially indicating subsurface flowpath connectivity. Our findings stress the need for (i) a combination of observations at different spatial scales, and (ii) a consideration of the high spatial variability of SSF at the plot and hillslope scale when designing monitoring networks and assessing hydrological connectivity. Copyright © 2013 John Wiley & Sons, Ltd.     

Multi-scale observation and cross-scale mechanistic modeling on terrestrial ecosystem carbon cycle

To predict global climate change and to implement the Kyoto Protocol for stabilizing atmospheric greenhouse gases concentrations require quantifying spatio-temporal variations in the terrestrial carbon sink accurately. During the past decade multi-scale ecological experiment and observation networks have been established using various new technologies (e.g. controlled environmental facilities, eddy covariance techniques and quantitative remote sensing), and have obtained a large amount of data about terrestrial ecosystem carbon cycle. However, uncertainties in the magnitude and spatio-temporal variations of the terrestrial carbon sink and in understanding the underlying mechanisms have not been reduced significantly. One of the major reasons is that the observations and experiments were conducted at individual scales independently, but it is the interactions of factors and processes at different scales that determine the dynamics of the terrestrial carbon sink. Since experiments and observations are always conducted at specific scales, to understand cross-scale interactions requires mechanistic analysis that is best to be achieved by mechanistic modeling. However, mechanistic ecosystem models are mainly based on data from single-scale experiments and observations and hence have no capacity to simulate mechanistic cross-scale interconnection and interactions of ecosystem processes. New-generation mechanistic ecosystem models based on new ecological theoretical framework are needed to quantify the mechanisms from micro-level fast eco-physiological responses to macro-level slow acclimation in the pattern and structure in disturbed ecosystems. Multi-scale data-model fusion is a recently emerging approach to assimilate multi-scale observational data into mechanistic, dynamic modeling, in which the structure and parameters of mechanistic models for simulating cross-scale interactions are optimized using multi-scale observational data. The models are validated and evaluated at different spatial and temporal scales and real-time observational data are assimilated continuously into dynamic modeling for predicting and forecasting ecosystem changes realistically. in summary, a breakthrough in terrestrial carbon sink research requires using approaches of multi-scale observations and cross-scale modeling to understand and quantify interconnections and interactions among ecosystem processes at different scales and their controls over ecosystem carbon cycle.     

Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment

Testing hydrological models over different spatio‐temporal scales is important for both evaluating diagnostics and aiding process understanding. High‐frequency (6‐hr) stable isotope sampling of rainfall and runoff was undertaken during 3‐week periods in summer and winter within 12 months of daily sampling in a 3.2‐km² catchment in the Scottish Highlands. This was used to calibrate and test a tracer‐aided model to assess the (a) information content of high‐resolution data, (b) effect of different calibration strategies on simulations and inferred processes, and (c) model transferability to <1‐km² subcatchment. The 6‐hourly data were successfully incorporated without loss of model performance, improving the temporal resolution of the modelling, and making it more relevant to the time dynamics of the isotope and hydrometric response. However, this added little new information due to old‐water dominance and riparian mixing in this peatland catchment. Time variant results, from differential split sample testing, highlighted the importance of calibrating to a wide range of hydrological conditions. This also provided insights into the nonstationarity of catchment mixing processes, in relation to storage and water ages, which varied markedly depending on the calibration period. Application to the nested subcatchment produced equivalent parameterization and performance, highlighting similarity in dominant processes. The study highlighted the utility of high‐resolution data in combination with tracer‐aided models, applied at multiple spatial scales, as learning tools to enhance process understanding and evaluation of model behaviour across nonstationary conditions. This helps reveal more fully the catchment response in terms of the different mechanistic controls on both wave celerites and particle velocities.     

High‐frequency logging technologies reveal state‐dependent hyporheic process dynamics: implications for hydroecological studies

This paper presents a novel method for assessing hyporheic water quality dynamics using advances in sensor technology. High‐resolution (15 min) dissolved oxygen (DO) and hydraulic head data were combined to assess groundwater–surface water (GW–SW) interactions in the hyporheic zone. DO concentrations varied at fine temporal and spatial scales, depending on the relative contributions of GW and SW. The effect of sample frequency on observed patterns of variability was assessed with reference to studies of the ecology of salmon spawning habitat. Conventional approaches fail to capture the full range of temporal variability in hyporheic water quality and demonstrate the need to reassess the interpretations of previous studies of the hyporheic zone. © Crown Copyright 2006. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd.     

A patch hierarchy approach to modeling surface and subsurface hydrology in complex flood‐plain environments

Geomorphology interacts with surface‐ and ground‐water hydrology across multiple spatial scales. Nonetheless, hydrologic and hydrogeologic models are most commonly implemented at a single spatial scale. Using an existing hydrogeologic computer model, we implemented a simple hierarchical approach to modeling surface‐ and ground‐water hydrology in a complex geomorphic setting. We parameterized the model to simulate ground‐ and surface‐water ?ow patterns through a hierarchical, three‐dimensional, quantitative representation of an anabranched montane alluvial ?ood plain (the Nyack Flood Plain, Middle Fork Flathead River, Montana, USA). Comparison of model results to ?eld data showed that the model provided reasonable representations of spatial patterns of aquifer recharge and discharge, temporal patterns of ?ood‐water storage on the ?ood plain, and rates of ground‐water movement from the main river channel into a large lateral spring channel on the ?ood plain, and water table elevation in the alluvial aquifer. These results suggest that a hierarchical approach to modeling ground‐ and surface‐water hydrology can reproduce realistic patterns of surface‐ and ground‐water ?ux on alluvial ?ood plains, and therefore should provide an excellent ‘quantitative laboratory’ for studying complex interactions between geomorphology and hydrology at and across multiple spatial scales. Copyright © 2004 John Wiley & Sons, Ltd.     

Importance of Spatial Resolution in Global Groundwater Modeling

Global-scale gradient-based groundwater models are a new endeavor for hydrologists who wish to improve global hydrological models (GHMs). In particular, the integration of such groundwater models into GHMs improves the simulation of water flows between surface water and groundwater and of capillary rise and thus evapotranspiration. Currently, these models are not able to simulate water table depth adequately over the entire globe. Unsatisfactory model performance compared to well observations suggests that a higher spatial resolution is required to better represent the high spatial variability of land surface and groundwater elevations. In this study, we use New Zealand as a testbed and analyze the impacts of spatial resolution on the results of global groundwater models. Steady-state hydraulic heads simulated by two versions of the global groundwater model G³M, at spatial resolutions of 5 arc-minutes (9 km) and 30 arc-seconds (900 m), are compared with observations from the Canterbury region. The output of three other groundwater models with different spatial resolutions is analyzed as well. Considering the spatial distribution of residuals, general patterns of unsatisfactory model performance remain at the higher resolutions, suggesting that an increase in model resolution alone does not fix problems such as the systematic overestimation of hydraulic head. We conclude that (1) a new understanding of how low-resolution global groundwater models can be evaluated is required, and (2) merely increasing the spatial resolution of global-scale groundwater models will not improve the simulation of the global freshwater system.     

Effect of streamflow stochasticity on bedform-driven hyporheic exchange

The interactions between the stream and the geomorphologic units that compose the stream channel result in an exchange of water, heat, and chemicals that is an important component of the flows of energy and nutrients in the river ecosystem. This exchange is characterized by complex spatial and temporal dynamics that depend on the characteristics of the stream flow and morphology. At present, many studies have addressed the development of spatial patterns of hyporheic exchange that are induced by many geomorphological factors at different scales. However, much less is known about the temporal evolution of the surface–subsurface exchange in response to the dynamics of the stream discharge. In order to investigate this problem, the present work analyzes the influence of streamflow variability on the hyporheic exchange induced by fluvial bedforms. A stochastic approach is employed to generate streamflow series whose statistical properties are representative of streams with different hydrological regimes. The resulting exchange fluxes and travel times are then computed, and the relationships between the streamflow regime and the dynamics of the exchange flux and travel times are investigated. The results show that the mean stream discharge can be used to estimate the average features of the temporal dynamics of hyporheic exchange. Moreover, exchange fluxes and residence times distributions exhibit significant fluctuations, which are tightly related to the coefficient of variation of the streamflow hydrograph.     

A review of continental scale hydrological models and their suitability for drought forecasting in (sub-Saharan) Africa

The aim of this review is to provide a basis for selecting a suitable hydrological model, or combination of models, for hydrological drought forecasting in Africa at different temporal and spatial scales; for example short and medium range (1–10 days or monthly) forecasts at medium to large river basin scales or seasonal forecasts at the Pan-African scale. Several global hydrological models are currently available with different levels of complexity and data requirements. However, most of these models are likely to fail to properly represent the water balance components that are particularly relevant in arid and semi-arid basins in sub-Saharan Africa. This review critically looks at weaknesses and strengths in the representation of different hydrological processes and fluxes of each model. The major criteria used for assessing the suitability of the models are (1) the representation of the processes that are most relevant for simulating drought conditions, such as interception, evaporation, surface water-groundwater interactions in wetland areas and flood plains and soil moisture dynamics; (2) the capability of the model to be downscaled from a continental scale to a large river basin scale model; and (3) the applicability of the model to be used operationally for drought early warning, given the data availability of the region. This review provides a framework for selecting models for hydrological drought forecasting, conditional on spatial scale, data availability and end-user forecast requirements. Among 16 well known hydrological and land surface models selected for this review, PCR-GLOBWB, GWAVA, HTESSEL, LISFLOOD and SWAT show higher potential and suitability for hydrological drought forecasting in Africa based on the criteria used in this evaluation.     

The use of agent based modelling techniques in hydrology: determining the spatial and temporal origin of channel flow in semi‐arid catchments

Information on the spatial and temporal origin of runoff entering the channel during a storm event would be valuable in understanding the physical dynamics of catchment hydrology; this knowledge could be used to help design flood defences and diffuse pollution mitigation strategies. The majority of distributed hydrological models give information on the amount of flow leaving a catchment and the pattern of fluxes within the catchment. However, these models do not give any precise information on the origin of runoff within the catchment. The spatial and temporal distribution of runoff sources is particularly intricate in semi‐arid catchments, where there are complex interactions between runoff generation, transmission and re‐infiltration over short temporal scales. Agents are software components that are capable of moving through and responding to their local environment. In this application, the agents trace the path taken by water through the catchment. They have information on their local environment and on the basis of this information make decisions on where to move. Within a given model iteration, the agents are able to stay in the current cell, infiltrate into the soil or flow into a neighbouring cell. The information on the current state of the hydrological environment is provided by the environment generator. In this application, the Connectivity of Runoff Model (CRUM) has been used to generate the environment. CRUM is a physically based, distributed, dynamic hydrology model, which considers the hydrological processes relevant for a semi‐arid environment at the temporal scale of a single storm event. During the storm event, agents are introduced into the model across the catchment; they trace the flows of water and store information on the flow pathways. Therefore, this modelling approach is capable of giving a novel picture of the temporal and spatial dynamics of flow generation and transmission during a storm event. This is possible by extracting the pathways taken by the agents at different time slices during the storm. The agent based modelling approach has been applied to two small catchments in South East Spain. The modelling approach showed that the two catchments responded differently to the same rainfall event due to the differences in the runoff generation and overland flow connectivity between the two catchments. The model also showed that the time of travel to the nearest flow concentration is extremely important for determining the connectivity of a point in the landscape with the catchment outflow. Copyright © 2007 John Wiley & Sons, Ltd.     

黄河流域多时空尺度土地利用与水质的关系

为探究不同时空尺度土地利用与水质的相互关系,以黄河流域为研究对象,基于2018年河流水质与土地利用数据,提取3种空间尺度(1000 m河段缓冲区、500 m河岸带缓冲区、子流域)的景观格局指数,结合4个季节河流水质指标,采用冗余分析方法定量探讨土地利用对河流水质的多时空尺度影响,获得水质资源管理最有效的时空尺度.结果表明:(1)在3种空间尺度下,耕地和草地占比最大.斑块密度(PD)在1000 m河段缓冲区尺度下更大,香农多样性指数(SHDI)在3种空间尺度下变化不大;(2)水质指标季节性和空间性存在显著差异,夏季水质优于冬季;(3)土地利用在夏季和1000 m河段缓冲区尺度下对水质影响最显著;(4)不同景观格局指数对河流水质产生的影响不同,耕地面积占比和林地面积占比、未利用地面积占比和SHDI对水质影响最为显著,除了耕地面积占比和PD值的增加会导致水质下降外,其余土地利用指数在大多数时空尺度下均可改善水质.该研究基于不同的时空尺度对土地利用与水质的关系进行定量研究,为合理规划土地资源提供参考,从而保护流域水质安全.     

Challenges in Studying and Modeling Heat and Moisture Exchange in Soil–Vegetation/Snow Cover–Surface Air Layer Systems

The current state of the art in the investigation and modeling of soil–vegetation/snow cover–surface air layer system (SVAS) is briefly reviewed. This system plays a decisive role in the formation of heat and moisture exchange between the land surface and atmosphere. The SWAP model, developed by the authors of this paper, is used to illustrate the potentialities of SVAS models in reproducing the dynamics of components of water and heat balances of the land surface under different natural conditions and at different spatial and temporal scales. The challenges and perspectives of further development of SVAS models are analyzed.     

A big-data spatial,temporal and network analysis of bovine tuberculosis between wildlife (badgers) and cattle

Bovine tuberculosis (TB) poses a serious threat for agricultural industry in several countries, it involves potential interactions between wildlife and cattle and creates societal problems in terms of human-wildlife conflict. This study addresses connectedness network analysis, the spatial, and temporal dynamics of TB between cattle in farms and the European badger (Meles meles) using a large dataset generated by a calibrated agent based model. Results showed that infected network connectedness was lower in badgers than in cattle. The contribution of an infected individual to the mean distance of disease spread over time was considerably lower for badger than cattle; badgers mainly spread the disease locally while cattle infected both locally and across longer distances. The majority of badger-induced infections occurred when individual badgers leave their home sett, and this was positively correlated with badger population growth rates. Point pattern analysis indicated aggregation in the spatial pattern of TB prevalence in badger setts across all scales. The spatial distribution of farms that were not TB free was aggregated at different scales than the spatial distribution of infected badgers and became random at larger scales. The spatial cross correlation between infected badger setts and infected farms revealed that generally infected setts and farms do not coexist except at few scales. Temporal autocorrelation detected a two year infection cycle for badgers, while there was both within the year and longer cycles for infected cattle. Temporal cross correlation indicated that infection cycles in badgers and cattle are negatively correlated. The implications of these results for understanding the dynamics of the disease are discussed.     

Modelling the interaction of climate,forest ecosystem,and hydrology to estimate catchment dissolved organic carbon export

The potential for increased loads of dissolved organic carbon (DOC) in streams and rivers is a concern for regulating the water quality in water supply watersheds. With increasing hydroclimatic variability related to global warming and shifts in forest ecosystem community and structure, understanding and predicting the magnitude and variability of watershed supply and transport of DOC over multiple time scales have become important research and management goals. In this study, we use a distributed process‐based ecohydrological model (Regional Hydro‐Ecological Simulation System [RHESSys]) to explore controls and predict streamflow DOC loads in Biscuit Brook. Biscuit Brook is a forested headwater catchment of the Neversink Reservoir, part of the New York City water supply system in the Catskill Mountains. Three different model structures of RHESSys were proposed to explore and evaluate hypotheses addressing how vegetation phenology and hydrologic connectivity between deep groundwater and riparian zones influence streamflow and DOC loads. Model results showed that incorporating dynamic phenology improved model agreement with measured streamflow in spring, summer, and fall and fall DOC concentration, compared with a static phenology. Additionally, the connectivity of deep groundwater flux through riparian zones with dynamic phenology improved streamflow and DOC flux in low flow conditions. Therefore, this study suggests the importance of inter‐annual vegetation phenology and the connectivity of deep groundwater drainage through riparian zones in the hydrology and stream DOC loading in this forested watershed and the ability of process‐based ecohydrological models to simulate these dynamics. The advantage of a process‐based modelling approach is specifically seen in the sensitivity to forest ecosystem dynamics and the interactions of hydroclimate variability with ecosystem processes controlling the supply and distribution of DOC. These models will be useful to evaluate different forest management approaches toward mitigating water quality concerns.     

Effect of temporal resolution of water level and temperature inputs on numerical simulation of groundwater–surface water flux exchange in a heavily modified urban river

Groundwater interacts with surface water features nearly in all types of landscapes. Understanding these interactions has practical consequences on the quantity and quality of water in either system, because the depletion or contamination of one of the systems will eventually affect the other one. Many studies have shown that the use of heat as natural tracer in conjunction with water level measurements is an effective method for estimating water flow (fluxes) between groundwater and surface water. A number of studies have explored the effects of spatial and temporal variability of groundwater–surface water flux exchanges using temperature and water level measurements; however, the effect of temporal resolution of water level and temperature data on estimating flux remains unexplored. Therefore, this study investigated the effect of temporal resolution of input data on temporal variation of groundwater–surface water flux exchanges. To this end, we calibrated a variably saturated two‐dimensional groundwater flow and heat transport model (VS2DH) at hourly and daily time scales using temperatures measured at multiple depths below the riverbed of the Zenne River, located at a well‐known Belgian brownfield site. Results of the study showed that the computed water flux through the streambed ranged between ?32 mm/day and +25 mm/day using the hourly model and from ?10 mm/day to ?37 mm/day using the daily model. The hourly model resulted in detecting reversal of flow direction inducing short‐term surface water flow into the streambed. However, such events were not captured if daily temperature and water level measurements were used as input. These findings have important implications for understanding contaminant mass flux and their attenuation in the mixing zone of groundwater and surface water. Copyright © 2012 John Wiley & Sons, Ltd.     

Scaling characteristics of spatial patterns of soil moisture from distributed modelling

Characterizing the spatial dynamics of soil moisture fields is a key issue in hydrology, offering an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, the statistical structure of soil moisture patterns is examined using modelled soil moisture obtained from the North American Land Data Assimilation System (NLDAS) at 0.125° resolution. The study focuses on the vertically averaged soil moisture in the top 10 cm and 100 cm layers. The two variables display a weak dependence for lower values of surface soil moisture, with the strength of the relationship increasing with the water content of the top layer. In both cases, the variance of the soil moisture follows a power law decay as a function of the averaging area. The superficial layer shows a lower degree of spatial organization and higher temporal variability, which is reflected in rapid changes in time of the slope of the scaling functions of the soil moisture variance. Conversely, the soil moisture in the top 100 cm has lower variability in time and larger spatial correlation. The scaling of these patterns was found to be controlled by the changes in the soil water content. Results have implications for the downscaling of soil moisture to prevent model bias.     

Spatial flow and sedimentation patterns within patches of epibenthic structures: Combining field,flume and modelling experiments

The objectives of the present study were twofold: (1) to identify spatial sedimentation and erosion patterns developing within patches of epibenthic structures (i.e. physical structures that protrude from the sediments, originating either from animals or plants) as a consequence of biophysical interactions; and (2) to assess the relevance of hydrodynamic flume studies for the long-term sediment dynamics in the field. We addressed these objectives by using patches of well-defined artificial structures (bamboo canes) for which we could easily monitor the long-term sediment dynamics in the field, measure the hydrodynamic effects in detail in the flume, and simulate the field and flume set-up with a commercially available hydrodynamic model. Two-year monitoring in the field showed that sedimentation was much larger in the high-density patches than the low-density ones. Within the high-density patches, comparable spatial patterns emerged at different field sites: erosion at the front and the side of the patches, and sedimentation more down-stream within the patches. The low-density patches showed no such patterns, and were generally characterised by some small-scale erosion directly around individual bamboo canes. Sedimentation and erosion in the field was well explained by the patterns in bed shear stress that were derived from our flume measurements. The 3D hydrodynamic modelling facilitated up-scaling of the flume results to the field, but failed to simulate accurately the effects at the leading edge. We conclude that: (A) field observations on sedimentation revealed interesting spatial patterns, but could not elucidate underlying processes; (B) detailed hydrodynamic measurements in a flume can elucidate these underlying processes, provided that appropriate scaling is being used; (C) flume studies are by definition not able to capture all spatial scales that are relevant for estuarine landscape formation and will always cause some flow artefacts; (D) hydrodynamic modelling offers a valuable tool to upscale flume observations, even though present models are not yet capable of fully reproducing all detailed spatial patterns; and (E) spatial heterogeneity is very important when looking at small-scale patches. There is a need for more spatially explicit and scale-dependent knowledge on bio-physical interactions.     

Linking snowmelt‐derived fluxes and groundwater flow in a high elevation meadow system,Sierra Nevada Mountains,California

Quantifying snowmelt‐derived fluxes at the watershed scale within hillslope environments is critical for investigating local meadow scale groundwater dynamics in high elevation riparian ecosystems. In this article, we investigate the impact of snowmelt‐derived groundwater flux from the surrounding hillslopes on water table dynamics in Tuolumne Meadows, which is located in the Sierra Nevada Mountains of California, USA. Results show water levels within the meadow are controlled by a combination of fluxes at the hillslope boundaries, snowmelt within the meadow and changes in the stream stage. Observed water level fluctuations at the boundaries of the meadow show the hydrologic connection and subsequent disconnection between the hillslope and meadow aquifers. Timing of groundwater flux entering the meadow as a result of spring snowmelt can vary over 20 days based on the location, aspect, and local geology of the contributing area within the larger watershed. Identifying this temporal and spatial variability in flux entering the meadow is critical for simulating changes in water levels within the meadow. Model results can vary significantly based on the temporal and spatial scales at which watershed processes are linked to local processes within the meadow causing errors when boundary fluxes are lumped in time or space. Without a clear understanding of the surrounding hillslope hydrology, it is difficult to simulate groundwater dynamics within high elevation riparian ecosystems with the accuracy necessary for understanding ecosystem response. Copyright © 2010 John Wiley & Sons, Ltd.