Information content of snow hydrological signatures based on streamflow,precipitation and air temperature

Hydrological signatures that represent snow processes are valuable to gain insights into snow accumulation and snow melt dynamics. We investigated five snow signatures. Considering inter-annual average of each calendar day, two slopes derived from the relation between streamflow and air temperature for different periods and streamflow peak maxima are used as signatures. In addition, two different approaches are used to compute inter-annual average and yearly snow storage estimates. We evaluated the ability of these signatures to characterize average (a) snow melt dynamics and (b) snow storage. They were applied in 10 Critical Zone Observatory catchments of the Southern Sierra mountains (USA) characterized by a Mediterranean climate. The relevance and information content of the signatures are evaluated using snow depth and snow water equivalent measurements as well as inter-catchment differences in elevation. The slopes quantifying the relations between streamflow and air temperature and the date of streamflow peak were found to characterize snow melt dynamics in terms of snow melt rates and snow melt affected areas. Streamflow peak dates were linked to the period of highest snow melt rates. Snow storage could be estimated both on average, considering all years, and for each year. Snow accumulation dynamics could not be characterized due to the lack of streamflow response during the snow accumulation period. The signatures were found potentially valuable to gain insights into catchment scale snow processes. In particular, when comparing catchments or observed and simulated data, they could provide insights into differences in terms of (a) snow melt rate and/or snow melt affected area over the snow melt season and (b) average or yearly snow storage. Requiring only widely available data, these hydrological signatures can be valuable for snow processes characterization, catchment comparison/classification or model development, calibration or evaluation.     

Global sensitivity analysis of hydrologic processes in major snow‐dominated mountainous river basins in Colorado

The performance of watershed models in simulating stream discharge depends on the adequate representation of important watershed processes. In snow‐dominated systems, snow, surface and subsurface hydrologic processes comprise a complex network of nonlinear interactions that influence the magnitude and timing of discharge. This study aims to identify critical processes and interactions that control discharge hydrographs in five major mountainous snow‐dominated river basins in Colorado, USA. A comprehensive watershed model (Soil and Water Assessment Tool) and a variance‐based global sensitivity analysis technique (Fourier Amplitude Sensitivity Test) were used in conjunction to identify critical models parameters and processes that they represent. Average monthly streamflow and streamflow root mean square error over a period of 20 years were used as two separate objective functions in this analysis. Examination of the sensitivity of monthly streamflow revealed the influence of parameters on flow volume, whereas the sensitivity of streamflow root mean square error also exposed the influence of parameters on the timing of the hydrographs. A stability analysis was performed to investigate the computational requirements for a robust sensitivity analysis. Results show that streamflow volume is mostly influenced by shallow subsurface processes, whereas interactions between groundwater and snow processes were the key in the timing of streamflows. A large majority of important parameters were common among all study watersheds, which underlies the prospect for regionalization of process‐based hydrologic modelling in headwater river basins in Colorado. Copyright © 2013 John Wiley & Sons, Ltd.     

Watersheds dynamics following wildfires: Nonlinear feedbacks and implications on hydrologic responses

In recent years, wildfires in the western United States have occurred with increasing frequency and scale. Climate change scenarios in California predict prolonged periods of droughts with even greater potential for conditions amenable to wildfires. The Sierra Nevada Mountains provide 70% of water resources in California, yet how wildfires will impact watershed-scale hydrology is highly uncertain. In this work, we assess the impacts of wildfires perturbations on watershed hydrodynamics using a physically based integrated hydrologic model in a high-performance-computing framework. A representative Californian watershed, the Cosumnes River, is used to demonstrate how postwildfire conditions impact the water and energy balance. Results from the high-resolution model show counterintuitive feedbacks that occur following a wildfire and allow us to identify the regions most sensitive to wildfires conditions, as well as the hydrologic processes that are most affected. For example, whereas evapotranspiration generally decreases in the postfire simulations, some regions experience an increase due to changes in surface water run-off patterns in and near burn scars. Postfire conditions also yield greater winter snowpack and subsequently greater summer run-off as well as groundwater storage in the postfire simulations. Comparisons between dry and wet water years show that climate is the main factor controlling the timing at which some hydrologic processes occur (such as snow accumulation) whereas postwildfire changes to other metrics (such as streamflow) show seasonally dependent impacts primarily due to the timing of snowmelt, illustrative of the integrative nature of hydrologic processes across the Sierra Nevada-Central Valley interface.     

Flow directions of stream-groundwater exchange in a headwater catchment during the hydrologic year

Understanding near-stream groundwater dynamics and flow directions is important for predicting hillslope-stream connectivity, streamflow generation, and hydrologic controls of streamwater quality. To determine the drivers of groundwater flow in the stream corridor (i.e., the stream channel and the adjacent groundwater in footslopes and riparian areas), we observed the water levels of 36 wells and 7 piezometers along a headwater stream section over a period of 18 months. Groundwater dynamics during events were controlled by the initial position of the groundwater table relative to the subsurface structure. The near-stream groundwater table displayed a fast and pronounced response to precipitation events when lying in fractured bedrock with low storage capacity, and responded less frequently and in a less pronounced way when lying in upper layers with high storage capacity. Precipitation depth, intensity, regolith thickness above the fractured bedrock, and proximity to and elevation above the stream channel also had an effect on the groundwater dynamics, which varied with hydrologic conditions. Our high-frequency and spatially dense measurements highlight the competing influence of groundwater inflow from upslope locations, streamwater level and bedrock properties on the spatiotemporal dynamics of flowpaths in the stream corridor. Near-stream groundwater pointed uniformly towards the stream channel when the stream corridor was hydrologically connected to upslope groundwater. However, local interruptions of the water inflow from upslope locations caused flow reversals towards the footslopes. The direction of near-stream groundwater followed the local fractured bedrock topography during dry hydrologic conditions on a few occasions after events. The outcomes of this research contribute to a better understanding of the drivers controlling spatiotemporal changes in near-stream groundwater dynamics and flow directions in multiple wetness states of the stream corridor.     

Complexity as a streamflow metric of hydrologic alteration

We explore the potential of using a complexity measure from statistical physics as a streamflow metric of basin-scale hydrologic alteration. The complexity measure that we employ is a non-trivial function of entropy. To determine entropy, we use the so-called permutation entropy (PE) approach. The PE approach is desirable in this case since it accounts for temporal streamflow information and it only requires a weak form of stationarity to be satisfied. To compute the complexity measure and assess hydrologic alteration, we employ daily streamflow records from 22 urban basins, located in the metropolitan areas of the cities of Baltimore, Philadelphia, and Washington DC, in the United States. We use urbanization to represent hydrologic alteration since urban basins are characterized by varied and often pronounced human impacts. Based on our application of the complexity measure to urban basins, we find that complexity tends to decline with increasing hydrologic alteration while entropy rises. According to this evidence, heavily urbanized basins tend to be temporally less complex (less ordered or structured) and more random than basins with low urbanization. This complexity loss may have important implications for stream ecosystems whose ability to provide ecosystem services depend on the flow regime. We also find that the complexity measure performs better in detecting alteration to the streamflow than more conventional metrics (e.g., variance and median of streamflow). We conclude that complexity is a useful streamflow metric for assessing basin-scale hydrologic alteration.     

Hydrologic connectivity at the hillslope scale through intra-snowpack flow paths during snowmelt

The seasonal snowmelt period is a critical component of the hydrologic cycle for many mountainous areas. Changes in the timing and rate of snowmelt as a result of physical hydrologic flow paths, such as longitudinal intra-snowpack flow paths, can have strong implications on the partitioning of meltwater amongst streamflow, groundwater recharge, and soil moisture storage. However, intra-snowpack flow paths are highly spatially and temporally variable and thus difficult to observe. This study utilizes new methods to non-destructively observe spatio-temporal changes in the liquid water content of snow in combination with plot experiments to address the research question: What is the scale of influence that intra-snowpack flow paths have on the downslope movement of liquid water during snowmelt across an elevational gradient? This research took place in northern Colorado with study plots spanning from the rain-snow transition zone up to the high alpine. Results indicate an increasing scale of influence from intra-snowpack flow paths with elevation, showing higher hillslope connectivity producing larger intra-snowpack contributing areas for meltwater accumulation, quantified as the upslope contributing area required to produce observed changes in liquid water content from melt rate estimates. The total effective intra-snowpack contributing area of accumulating liquid water was found to be 17, 6, and 0 m² for the above tree line, near tree line, and below tree line plots, respectively. Dye tracer experiments show capillary and permeability barriers result in increased number and thickness of intra-snowpack flow paths at higher elevations. We additionally utilized aerial photogrammetry in combination with ground penetrating radar surveys to investigate the role of this hydrologic process at the small watershed scale. Results here indicate that intra-snowpack flow paths have influence beyond the plot scale, impacting the storage and transmission of liquid water within the snowpack at the small watershed scale.     

Patterns of hydrologic connectivity in the McMurdo Dry Valleys,Antarctica: a synthesis of 20 years of hydrologic data

Streams in the McMurdo Dry Valleys (MDVs) of Antarctica moderate an important hydrologic and biogeochemical connection between upland alpine glaciers, valley‐bottom soils, and lowland closed‐basin lakes. Moreover, MDV streams are simple but dynamic systems ideal for studying interacting hydrologic and ecological dynamics. This work synthesizes 20 years of hydrologic data, collected as part of the MDVs Long‐Term Ecological Research project, to assess spatial and temporal dynamics of hydrologic connectivity between glaciers, streams, and lakes. Long‐term records of stream discharge (Q), specific electrical conductance (EC), and water temperature (T) from 18 streams were analysed in order to quantify the magnitude, duration, and frequency of hydrologic connections over daily, annual, and inter‐annual timescales. At a daily timescale, we observe predictable diurnal variations in Q, EC, and T. At an annual timescale, we observe longer streams to be more intermittent, warmer, and have higher median EC values, compared to shorter streams. Longer streams also behave chemostatically with respect to EC, whereas shorter streams are more strongly characterized by dilution. Inter‐annually, we observe significant variability in annual runoff volumes, likely because of climatic variability over the 20 record years considered. Hydrologic connections at all timescales are vital to stream ecosystem structure and function. This synthesis of hydrologic connectivity in the MDVs provides a useful end‐member template for assessing hydrologic connectivity in more structurally complex temperate watersheds. Copyright © 2016 John Wiley & Sons, Ltd.     

Evaluation of distributed hydrologic impacts of temperature-index and energy-based snow models

Two commonly used strategies in modeling snowmelt are the energy balance and temperature-index methods. Here we evaluate the distributed hydrologic impacts of these two different snowmelt modeling strategies, each in conjunction with a physics-based hydrologic model (PIHM). Results illustrate that both the Isnobal energy-balance and calibrated temperature-index methods adequately reproduce snow depletion at the observation site. However, the models exhibit marked differences in the distribution of snowmelt. When combined with PIHM, both models capture streamflow reasonably during calibration year (WY06), but Isnobal model gives better streamflow results in the validation year (WY07). The uncalibrated temperature-index model predicts streamflow poorly in both years. Differences between distributed snowmelt, as predicted by Isnobal and calibrated temperature-index method, and its consequent effect on predicted hydrologic states suggest the need to carefully calibrate temperature-index models in both time and space. Combined physics-based snow and hydrologic models provide the best accuracy, while a temperature-index model using coefficients from the literature the poorest.     

Distributed modelling of future changes in hydrological processes of Spencer Creek watershed

The hydrologic impact of climate change has been largely assessed using mostly conceptual hydrologic models. This study investigates the use of distributed hydrologic model for the assessment of the climate change impact for the Spencer Creek watershed in Southern Ontario (Canada). A coupled MIKE SHE/MIKE 11 hydrologic model is developed to represent the complex hydrologic conditions in the Spencer Creek watershed, and later to simulate climate change impact using Canadian global climate model (CGCM 3·1) simulations. Owing to the coarse resolution of GCM data (daily GCM outputs), statistical downscaling techniques are used to generate higher resolution data (daily precipitation and temperature series). The modelling results show that the coupled model captured the snow storage well and also provided good simulation of evapotranspiration (ET) and groundwater recharge. The simulated streamflows are consistent with the observed flows at different sites within the catchment. Using a conservative climate change scenario, the downscaled GCM scenarios predicted an approximately 14–17% increase in the annual mean precipitation and 2–3 °C increase in annual mean maximum and minimum temperatures for the 2050s (i.e., 2046–2065). When the downscaled GCM scenarios were used in the coupled model, the model predicted a 1–5% annual decrease in snow storage for 2050s, approximately 1–10% increase in annual ET, and a 0·5–6% decrease in the annual groundwater recharge. These results are consistent with the downscaled temperature results. For future streamflows, the coupled model indicated an approximately 10–25% increase in annual streamflows for all sites, which is consistent with the predicted changes in precipitation. Overall, it is shown that distributed hydrologic modelling can provide useful information not only about future changes in streamflow but also changes in other key hydrologic processes such as snow storage, ET, and groundwater recharge, which can be particularly important depending on the climatic region of concern. The study results indicate that the coupled MIKE SHE/MIKE 11 hydrologic model could be a particularly useful tool for understanding the integrated effect of climate change in complex catchment scale hydrology. Copyright © 2010 John Wiley & Sons, Ltd.     

Multivariate analysis as a tool to infer hydrologic response types and controlling variables in a humid temperate catchment

We assess the ability of multivariate statistical analyses applied to event hydrographs parameters, to characterize a catchment hydrological behaviour. Motivation for such an approach lies in the fact that streamflow records have yet to be exploited to their full potential towards hydrological interpretation and can be used to infer a catchment state of connectivity from a qualitative standpoint. We have therefore processed 96 event hydrographs from a small headwater temperate humid forested catchment using principal component analysis, variation partitioning and classification tree analysis. These techniques prove to be promising in discriminating contrasted types of hydrologic responses (e.g. low‐ vs high‐magnitude events, slow vs quick timing events), identifying the main hydro‐meteorological variables that control these responses and determining thresholds values of the hydro‐meteorological variables leading to a switch between catchment response types. Copyright © 2010 John Wiley & Sons, Ltd.     

Influence of climate on alpine stream chemistry and water sources

The resilience of alpine/subalpine watersheds may be viewed as the resistance of streamflow or stream chemistry to change under varying climatic conditions, which is governed by the relative size (volume) and transit time of surface and subsurface water sources. Here, we use end‐member mixing analysis in Andrews Creek, an alpine stream in Rocky Mountain National Park, Colorado, from water year 1994 to 2015, to explore how the partitioning of water sources and associated hydrologic resilience change in response to climate. Our results indicate that four water sources are significant contributors to Andrews Creek, including snow, rain, soil water, and talus groundwater. Seasonal patterns in source‐water contributions reflected the seasonal hydrologic cycle, which is driven by the accumulation and melting of seasonal snowpack. Flushing of soil water had a large effect on stream chemistry during spring snowmelt, despite making only a small contribution to streamflow volume. Snow had a large influence on stream chemistry as well, contributing large amounts of water with low concentrations of weathering products. Interannual patterns in end‐member contributions reflected responses to drought and wet periods. Moderate and significant correlations exist between annual end‐member contributions and regional‐scale climate indices (the Palmer Drought Severity Index, the Palmer Hydrologic Drought Index, and the Modified Palmer Drought Severity Index). From water year 1994 to 2015, the percent contribution from the talus‐groundwater end member to Andrews Creek increased an average of 0.5% per year (p < 0.0001), whereas the percent contributions from snow plus rain decreased by a similar amount (p = 0.001). Our results show how water and solute sources in alpine environments shift in response to climate variability and highlight the role of talus groundwater and soil water in providing hydrologic resilience to the system.     

Diagnostic calibration and cross‐catchment transferability of a simple process‐consistent hydrologic model

The transferability of hydrologic models is of ever increasing importance for making improved hydrologic predictions and testing hypothesized hydrologic drivers. Here, we present an investigation into the variability and transferability of the recently introduced catchment connectivity model (Smith et al., 2013 ). The catchment connectivity model was developed following extensive experimental observations identifying the key drivers of streamflow in the Tenderfoot Creek Experimental Forest (Jencso et al., 2009 ; Jencso et al., 2010 ), with the goal of creating a simple model consistent with internal observations of catchment hydrologic connectivity patterns. The model was applied across seven catchments located within Tenderfoot Creek Experimental Forest to investigate spatial variability and transferability of model performance and parameterization. The results demonstrated that the model resulted in historically good fits (based on previous studies at the sites) to both the hydrograph and internal water table dynamics (corroborated with experimental observations). The impact of a priori parameter limits was also examined. It was observed that enforcing field‐based limits on model parameters resulted in slight reductions to streamflow hydrograph fits, but significant improvements to model process fidelity (as hydrologic connectivity), as well as moderate improvement in the transferability of model parameterizations from one catchment to the next. Copyright © 2016 John Wiley & Sons, Ltd.     

Surface and subsurface water contributions to streamflow from a mesoscale watershed in complex mountain terrain

An understanding of surface and subsurface water contributions to streamflow is essential for accurate predictions of water supply from mountain watersheds that often serve as water towers for downstream communities. As such, this study used the end‐member mixing analysis technique to investigate source water contributions and hydrologic flow paths of the 264 km² Boulder Creek Watershed, which drains the Colorado Front Range, USA. Four conservative hydrochemical tracers were used to describe this watershed as a 3 end‐member system, and tracer concentration reconstruction suggested that the application of end‐member mixing analysis was robust. On average from 2009 to 2011, snowmelt and rainwater from the subalpine zone and groundwater sampled from the upper montane zone contributed 54%, 22%, and 24% of the annual streamflow, respectively. These values demonstrate increased rainwater and decreased snow water contributions to streamflow relative to area‐weighted mean values derived from previous work at the headwater scale. Young water (2.3 ± 0.8 months) fractions of streamflow decreased from 18–22% in the alpine catchment to 8–10% in the lower elevation catchments and the watershed outlet with implications for subsurface storage and hydrological connectivity. These results contribute to a process‐based understanding of the seasonal source water composition of a mesoscale watershed that can be used to extrapolate headwater streamflow generation predictions to larger spatial scales.     

Catchment water storage variation with elevation

One of the most important functions of catchments is the storage of water. Catchment storage buffers meteorological extremes and interannual streamflow variability, controls the partitioning between evaporation and runoff, and influences transit times of water. Hydrogeological data to estimate storage are usually scarce and seldom available for a larger set of catchments. This study focused on storage in prealpine and alpine catchments, using a set of 21 Swiss catchments comprising different elevation ranges. Catchment storage comparisons depend on storage definitions. This study defines different types of storage including definitions of dynamic and mobile catchment storage. We then estimated dynamic storage using four methods, water balance analysis, streamflow recession analysis, calibration of a bucket‐type hydrological model Hydrologiska Byråns Vattenbalansavdelning model (HBV), and calibration of a transfer function hydrograph separation model using stable isotope observations. The HBV model allowed quantifying the contributions of snow, soil and groundwater storages compared to the dynamic catchment storage. With the transfer function hydrograph separation model both dynamic and mobile storage was estimated. Dynamic storage of one catchment estimated by the four methods differed up to one order of magnitude. Nevertheless, the storage estimates ranked similarly among the 21 catchments. The largest dynamic and mobile storage estimates were found in high‐elevation catchments. Besides snow, groundwater contributed considerably to this larger storage. Generally, we found that with increasing elevation the relative contribution to the dynamic catchment storage increased for snow, decreased for soil, but remained similar for groundwater storage.     

Wetlandscape hydrologic dynamics driven by shallow groundwater and landscape topography

Wetlands play an important role in watershed eco-hydrology. The occurrence and distribution of wetlands in a landscape are affected by the surface topography and the hydro-climatic conditions. Here, we propose a minimalist probabilistic approach to describe the dynamic behaviour of wetlandscape attributes, including number of inundated wetlands and the statistical properties of wetland stage, surface area, perimeter, and storage volume. The method relies on two major assumptions: (a) wetland bottom hydrologic resistance is negligible; and (b) groundwater level is parallel to the mean terrain elevation. The approach links the number of inundated wetlands (depressions with water) to the distribution of wetland bottoms and divides, and the position of the shallow water table. We compared the wetlandscape attribute dynamics estimated from the probabilistic approach to those determined from a parsimonious hydrologic model for groundwater-dominated wetlands. We test the reliability of the assumptions of both models using data from six cypress dome wetlands in the Green Swamp Wildlife Management Area, Florida. The results of the hydrologic model for groundwater-dominated wetlands showed that the number of inundated wetlands has a unimodal dependence on the groundwater level, as predicted by the probabilistic approach. The proposed models provide a quantitative basis to understand the physical processes that drive the spatiotemporal hydrologic dynamics in wetlandscapes impacted by shallow groundwater fluctuations. Emergent patterns in wetlandscape hydrologic dynamics are of key importance not only for the conservation of water resources, but also for a wide range of eco-hydrological services provided by connectivity between wetlands and their surrounding uplands.     

Unravelling runoff processes in Andean basins in northern Ecuador through hydrological signatures

Streamflow is the runoff response integrated in space and time over a complex system involving climatic and catchment physiographic factors. In the Andes, accelerating runoff process understanding is hampered by the inability to quantify heterogeneity of surface and subsurface catchment properties. Here, we present a statistical approach based on regression models and correlation analysis that links hydrological signatures and catchment properties to unveil processes in a set of volcanic mountain catchments (latitude 0°30'N) in Ecuador. The catchments represent form and function diversity in the same hydrological unit. We found that despite of similar atmospheric-water inputs the water yield in the north-east region is about 5× larger than in the south-west region and their flow regimes are asymmetric. The soil-bedrock interface and lithology exert a first-order control on hydrologic partitioning, and this allowed us to hypothesize two hydrological mechanisms. Firstly, in the north-east region, the perennial streamflow is associated with seasonal rainfall patterns, and subsequent drainage processes taking place at the surface and subsurface level. The amount of streamflow is related to landform characteristics, high canopy density and root development of forest as well as water holding capacity of organic soils. From a mechanistic standpoint, the low concentration time, steep slopes and shallow infiltration limited by high-consolidated deposits of sedimentary and volcanics suggest a lateral movement of the flow. Secondly, in the south-west region the streamflow regime is mostly groundwater-dependent and it becomes seasonally enhanced by rainfall. Larger seasonal variations of precipitation and temperature result into enhanced evapotranspiration in the drier months, limiting shallow soil infiltration. Under the soil layers, highly permeable pyroclastic deposits and andesitic lavas promote deep percolation. The results highlight the degree of dissimilarity of hydrological processes in Andean settings, but unravelling their complexity seems plausible using streamflow signatures and causal explanatory models.     

Addressing snow model uncertainty for hydrologic prediction

Streamflow forecasting methods are moving towards probabilistic approaches that quantify the uncertainty associated with the various sources of error in the forecasting process. Multi-model averaging methods which try to address modeling deficiencies by considering multiple models are gaining much popularity. We have applied the Bayesian Model Averaging method to an ensemble of twelve snow models that vary in their heat and melt algorithms, parameterization, and/or albedo estimation method. Three of the models use the temperature-based heat and melt routines of the SNOW17 snow accumulation and ablation model. Nine models use heat and melt routines that are based on a simplified energy balance approach, and are varied by using three different albedo estimation schemes. Finally, different parameter sets were identified through automatic calibration with three objective functions. All models use the snow accumulation, liquid water transport, and ground surface heat exchange processes of the SNOW17. The resulting twelve snow models were combined using Bayesian Model Averaging (BMA). The individual models, BMA predictive mean, and BMA predictive variance were evaluated for six SNOTEL sites in the western U.S. The models performed best and the BMA variance was lowest at the colder sites with high winter precipitation and little mid-winter melting. An individual snow model would often outperform the BMA predictive mean. However, observed snow water equivalent (SWE) was captured within the 95% confidence intervals of the BMA variance on average 80% of the time at all sites. Results are promising that consideration of multiple snow structures would provide useful uncertainty information for probabilistic hydrologic prediction.     

Impacts of environmental stressors on the water resources of intensively managed hydrologic systems

Watersheds are complex systems due to their surface and subsurface spatially connected water fluxes and biochemical processes that shape Earth's critical zone. In intensively managed landscapes, the implementation of watershed management practices (WMPs) regulate their short‐term responses, whereas climate variability controls the long‐term processes. Understanding their responses to anthropogenic and natural stressors requires a holistic approach that takes into account their multiscale spatio‐temporal linkages. The objective of this study was to simulate the impacts of spatially and temporally varying WMPs and projected climate changes on the surface and groundwater resources in the Upper Sangamon River Basin (USRB), a watershed in central Illinois greatly impacted by agricultural and industrial operations. The physically based hydrologic model MIKE‐SHE was used to simulate the hydrologic responses of the basin to different WMPs and climatic conditions. The simulation of a WMP was varied spatially across the basin to determine the spectrum of responses and critical conditions. In general, the wetlands and forested riparian buffer scenarios were found to cause a reduction in the average streamflow, whereas crop rotation had varied responses depending on the location of implementation and the climate condition assumed. Reductions of up to 30% in the average streamflow were found for the forested riparian buffer under the ESM 2M climate projections, whereas an increase of up to 13% with the crop rotation schemes under CM3 climate was predicted. The model results showed that the installation of tile drains across the USRB increased the water table depth (from ground level) by up to 56%, making crop production possible. Groundwater level in USRB appeared to be more sensitive to future climatic conditions than to WMP implementation. The impacts of WMPs are determined to depend on the climate conditions under which they are applied. Investigating individual and combined stressors' effects over the critical zone at a watershed scale can lead to a more comprehensive analysis of the risk and trade‐offs in every managerial decision that will enable an efficient use of resources.     

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.     

CHOSEN: A synthesis of hydrometeorological data from intensively monitored catchments and comparative analysis of hydrologic extremes

Comparative hydrology has been hampered by limited availability of geographically extensive, intercompatible monitoring data on comprehensive water balance stores and fluxes. These limitations have, for example, restricted comprehensive assessment of multiple dimensions of wetting and drying related to climate change and hampered understanding of why widespread changes in precipitation extremes are uncorrelated with changes in streamflow extremes. Here, we address this knowledge gap and underlying data gap by developing a new data synthesis product and using that product to detect trends in the frequencies and magnitudes of a comprehensive set of hydroclimatic and hydrologic extremes. CHOSEN (Comprehensive Hydrologic Observatory Sensor Network) is a database of streamflow, soil moisture, and other hydroclimatic and hydrologic variables from 30 study areas across the United States. An accompanying data pipeline provides a reproducible, semi-automated approach for assimilating data from multiple sources, performing quality assurance and control, gap-filling and writing to a standard format. Based on the analysis of extreme events in the CHOSEN dataset, we detected hotspots, characterized by unusually large proportions of monitored variables exhibiting trends, in the Pacific Northwest, New England, Florida and Alaska. Extreme streamflow wetting and drying trends exhibited regional coherence. Drying trends in the Pacific Northwest and Southeast were often associated with trends in soil moisture and precipitation (Pacific Northwest) and evapotranspiration-related variables (Southeast). In contrast, wetting trends in the upper Midwest and the Rocky Mountains showed few univariate associations with other hydroclimatic extremes, but their latitudes and elevations suggested the importance of changing snowmelt characteristics. On the whole, observed trends are incompatible with a ‘drying-in-dry, wetting-in-wet’ paradigm for climate-induced hydrologic changes over land. Our analysis underscores the need for more extensive, longer-term observational data for soil moisture, snow and evapotranspiration.