The era of "big data'' promises to provide new hydrologic insights, and open web-based platforms are being developed and adopted by the hydrologic science community to harness these datasets and data services. This shift accompanies advances in hydrology education and the growth of web-based hydrology learning modules, but their capacity to utilize emerging open platforms and data services to enhance student learning through data-driven activities remains largely untapped. Given that generic equations may not easily translate into local or regional solutions, teaching students to explore how well models or equations work in particular settings or to answer specific problems using real data is essential. This paper introduces an open web-based learning module developed to advance data-driven hydrologic process learning, targeting upper level undergraduate and early graduate students in hydrology and engineering. The module was developed and deployed on the HydroLearn open educational platform, which provides a formal pedagogical structure for developing effective problem-based learning activities. We found that data-driven learning activities utilizing collaborative open web platforms like HydroShare and CUAHSI JupyterHub computational notebooks allowed students to access and work with datasets for systems of personal interest and promoted critical evaluation of results and assumptions. Initial student feedback was generally positive, but also highlights challenges including trouble-shooting and future-proofing difficulties and some resistance to open-source software and programming. Opportunities to further enhance hydrology learning include better articulating the myriad benefits of open web platforms upfront, incorporating additional user-support tools, and focusing methods and questions on implementing and adapting notebooks to explore fundamental processes rather than tools and syntax. The profound shift in the field of hydrology toward big data, open data services and reproducible research practices requires hydrology instructors to rethink traditional content delivery and focus instruction on harnessing these datasets and practices in the preparation of future hydrologists and engineers.
When formulating a hydrologic model, scientists rely on parameterizations of multiple processes based on field data, but literature review suggests that more frequently people select parameterizations that were included in pre-existing models rather than re-evaluating the underlying field experiments. Problems arise when limited field data exist, when “trusted” approaches do not get reevaluated, and when processes fundamentally change in different environments. The physics and dynamics of snow interception by conifers, including both loading and unloading of snow, is just such a case. The most commonly used interception parameterization is based on data from four trees from one site, but field study results are not directly transferable between environments. The process varies dramatically between locations with relatively warmer versus colder winters. Here, we combine a comprehensive literature review with a model to demonstrate essential improvements to model representations of snow interception. We recommend that, as a first and essential step, all models include increased loading due to increased adhesion and cohesion when temperatures rise from -3 and 0°C. The commonly used parameters of a fixed maximum value for loading and an e-folding time for unloading are not supported by observations or physical understanding and are not necessary to reproduce observations. In addition to unloading based on physical processes, such as wind or canopy warming, all models must represent melting of in-canopy snow so that it can be unloaded in liquid form. As a second step, we propose field experiments across climates and forest types to investigate: a) a representation of the force balance between adhesion and cohesion versus gravity for both interception efficiency and rates of unloading, b) wind effects during and between storms, and c) lubrication when snow melts. For greatest impact, this framework requires dedicated field measurements. These processes are essential for models to accurately represent the impacts of dynamically changing forest cover and snow cover on both global albedo and water supplies.
While 1992 marked the first major dam – Manwan – on the main stem of the Mekong River, the post-2010 era has seen the construction and operationalisation of mega dams such as Xiaowan (started operations in 2010) and Nuozhadu (started operations in 2014) that were much larger than any dams built before. The scale of these projects implies that their operations will likely have significant ecological and hydrological impacts from the Upper Mekong Basin to the Vietnamese Delta and beyond. Historical water level and water discharge data from 1960 to 2020 were analysed to examine the changes to streamflow conditions across three time periods: 1960-1991 (pre-dam), 1992-2009 (growth) and 2010-2020 (mega-dam). At Chiang Saen, the nearest station to the China border, monthly water discharge in the mega-dam period has increased by up to 98% during the dry season and decreased up as much as -35% during the wet season when compared to pre-dam records. Similarly, monthly water levels also rose by up to +1.16m during the dry season and dropped by up to -1.55m during the wet season. This pattern of hydrological alterations is observed further downstream to at least Stung Treng (Cambodia) in our study, showing that Mekong streamflow characteristics have shifted substantially in the post-2010 era. In light of such changes, the 2019-2020 drought – the most severe one in the recent history in the Lower Mekong Basin – was a consequent of constructed dams reducing the amount of water during the wet season. This reduction of water was exacerbated by the decreased monsoon precipitation in 2019. Concurrently, the untimely operationalisation of the newly opened Xayaburi dam in Laos coincided with the peak of the 2019-2020 drought and could have aggravated the dry conditions downstream. Thus, the mega-dam era (post-2010) may signal the start of a new normal of wet-season droughts.
1. IntroductionTropical mountainous ecosystems are recognized as providers of valuable ecological and hydrological services (Viviroli et al, 2007). In Central America, the Páramo, a high‐elevation tropical grassland ecosystem, extends over ~ 200 km2 in Costa Rica and Panama, with ~50% of this area located within the Chirripó National Park between 3,100 and 3,820 m asl (-83.49°, 9.46°). Vegetation mostly consists of 0.5 to 2.5 m tall bamboo dominated (Chusquea subtessellata ) grasslands, covering up to 60% of the total Páramo area in Costa Rica (Fig.1a). The climate is controlled by the northeast trade winds, the latitudinal migration of the Intertropical Convergence Zone (ITCZ), cold continental outbreaks (i.e., northerly winds), and the seasonal influence of Caribbean cyclones. These circulation patterns produce two rainfall maxima on the Pacific slope, one in June and one in September, which are interrupted by a relative minimum between July-August, known as the Mid-Summer Drought, due to intensification of trade winds over the Caribbean Sea (Magaña et al., 1999; Waylen, 1996). The wettest season extends from May to November (contributing up to 89% of the annual precipitation), whereas the driest season is from December to April (Fig. 2a; Esquivel-Hernández et al., 2018). The surface water system of Chirripó is characterized by a lake district which comprises approximately 30 lakes of glacial origin and streams flowing down the Caribbean and Pacific slopes (Fig 1b). Lake catchments are characterized by steep slopes that promote rapid hydrological responses such as fast water‐level changes. Input of water to these glacial lakes is mostly controlled by the seasonal inputs of rainfall, which mix up with stream and subsurface waters. In April 2015, the Chirripó Hydrological Research Site (CHRS) was installed with the goal of advancing the understanding of the hydrological functioning in the Central American Páramo using environmental tracers (i.e., water stable isotopes) in combination with hydrometric data. A detailed map of CHRS is available in Esquivel-Hernández et al. (2019).
The active rock glacier “Innere Ölgrube”, and its catchment area (Ötztal Alps, Austria) are assessed using various hydro(geo)logical tools to provide a thorough catchment characterization and to quantify temporal variations in recharge and discharge components. During the period from June 2014 to July 2018, an average contribution derived from snowmelt, ice melt and rainfall of 35,8 %, 27,6 % and 36,6 %, respectively, is modelled for the catchment using a rainfall-runoff model. Discharge components of the rock glacier springs are distinguished using isotopic data as well as other natural and artificial tracer data, when considering the potential sources rainfall, snowmelt, ice melt and groundwater. Seasonal as well as diurnal variations in runoff are quantified and the importance of shallow groundwater within this rock glacier-influenced catchment is emphasized. Water derived from ice melt is suggested to be provided mainly by melting of two small cirque glaciers within the catchment and subordinately by melting of permafrost ice of the rock glacier. The active rock glacier is characterized by a layered internal structure with an unfrozen base layer responsible for groundwater storage and retarded runoff, a main permafrost body contributing little to the discharge (at the moment) by permafrost thaw and an active layer responsible for fast lateral flow on top of the permafrost body. Snowmelt contributes at least 1/3rd of the annual recharge. During droughts, meltwater derived from two cirque glaciers provides runoff with diurnal runoff variations; however, this discharge pattern will change as these cirque glaciers will ultimately disappear in the future. The storage-discharge characteristics of the investigated active rock glacier catchment are an example of a shallow groundwater aquifer in alpine catchments that ought to be considered when analysing (future) river runoff characteristics in alpine catchments as these provide retarded runoff during periods with little or no recharge.
Rock glaciers are increasingly influencing the hydrology and water chemistry of Alpine catchments, with important implications for drinking water quality and ecosystem health under a changing climate. During summers of 2017 - 2019, we monitored the physical and chemical conditions of springs emerging from two active rock glaciers (ZRG and SRG) with distinct geomorphological settings in the Eastern Italian Alps (Solda/Sulden catchment). Both springs had constantly cold waters (1.4 ± 0.1 °C), and their ionic composition was dominated by SO42-, HCO3-, Ca2+ and Mg2+. Concentrations of major ions and trace elements, and values of water isotopes (δ18O, δ2H), increased towards autumn with an asymptotic trend at SRG, and a positive unimodal pattern at ZRG, where concentrations peaked 60 - 80 days after the end of the snowmelt. Wavelet analysis on electrical conductivity (EC) and water temperature records revealed daily cycles only at SRG, and significant weekly/biweekly fluctuations at both springs attributable to oscillations of meteorological conditions. Several rainfall events triggered a transient (0.5 - 2 hrs) EC drop and water temperature rise (dilution and warming) at SRG, whereas only intense rainfall events occasionally increased EC at ZRG (solute enrichment and thermal buffering), with a long-lasting effect (6 - 48 hrs). Our results, supported by a limited but emerging literature, suggest that: i) the distinctive composition of the bedrock drives different concentrations of major ions and trace elements in rock glacier springs; ii) pond-like and stream-like springs have distinct fluctuations of water parameters at different timescales; iii) peaks of EC/solute concentrations indicate a seasonal window of major permafrost thaw for rock glaciers feeding pond-like springs. These results provide a first quantitative description of the hydrological seasonality in rock glacier outflows, and their hydrochemical response to precipitation events, bringing relevant information for water management in the European Alps under climate change.
Aquatic vegetation, hydraulics and sediment transport have complex interactions that are not yet well understood. These interactions are important for sediment conveyance, sediment sequestration, phasing of sediment delivery from runoff events, and management of ecosystem health in lowland streams. To address this knowledge gap detailed field measurements of sediment transport through natural flexible aquatic vegetation are required to supplement and validate laboratory results. This paper contributes a field study of suspended sediment transport through aquatic vegetation and includes mechanical removal of aquatic vegetation with a weed cutting boat. It also provides methods to quantify vegetation cover through remote sensing with Unmanned Aerial Vehicles (UAVs) and estimate biomass from ground truth sampling. Suspended sediment concentrations were highly dependent on aquatic vegetation abundance, and the distance upstream that had been cleared of aquatic vegetation. When the study reach was fully vegetated (i.e. cover >80%), the maximum recorded SSC was 14.6 g/m3 (during a fresh with discharge of 2.47 m3/s), during weed cutting operations SSC was 76.8 g/m3 at 0.84 m3/s (weedcutting boat 0.5-1 km upstream from study reach), however following weed cutting operations (4.6 km cleared upstream), SSC was 139.0 g/m3 at a discharge of 1.52 m3/s. The data indicates that fine sediment was being sequestered by aquatic vegetation and likely remobilised after vegetation removal. Investigation of suspended sediment spatial dynamics illustrated changes in particle size distribution due to preferential settling of coarse particles within aquatic vegetation. Hydraulic resistance in the study reach (parameterized by Manning’s n) dropped by over 70% following vegetation cutting. Prior to cutting hydraulic resistance was discharge dependent, while post cutting hydraulic resistance was approximately invariant of discharge. Aerial surveying captured interesting changes in aquatic vegetation cover, where some very dense regions of aquatic vegetation were naturally removed leaving behind unvegetated riverbed and fine sediment.
Peatlands are globally important long-term sinks of carbon, however there is concern that enhanced moss moisture stress due to climate change mediated drought will reduce moss productivity making these ecosystems vulnerable to carbon loss and associated long-term degradation. Peatlands are resilient to summer drought moss stress because of negative ecohydrological feedbacks that generally maintain a wet peat surface, but where feedbacks may be contingent on peat depth. We tested this ‘survival of the deepest’ hypothesis by examining water table position, near-surface moisture content, and soil water tension in peatlands that differ in size, peat depth, and catchment area during a summer drought. All shallow sites lost their WT (i.e. the groundwater well was dry) for considerable time during the drought period. Near-surface soil water tension increased dramatically at shallow sites following water table loss, increasing ~5–7.5× greater at shallow sites compared to deep sites. During a mid-summer drought intensive field survey we found that 60%–67% of plots at shallow sites exceeded a 100 mb tension threshold used to infer moss water stress. Unlike the shallow sites, tension typically did not exceed this 100 mb threshold at the deep sites. Using species dependent water content - chlorophyll fluorescence thresholds and relations between volumetric water content and water table depth, Monte Carlo simulations suggest that moss had nearly twice the likelihood of being stressed at shallow sites (0.38 ± 0.24) compared to deep sites (0.22 ± 0.18). This study provides evidence that mosses in shallow peatland may be particularly vulnerable to warmer and drier climates in the future, but where species composition may play an important role. We argue that a critical ‘threshold’ peat depth specific for different hydrogeological and hydroclimatic regions can be used to assess what peatlands are especially vulnerable to climate change mediated drought.
Extreme precipitation can have profound consequences for communities, resulting in natural hazards such as rainfall-triggered landslides that cause casualties and extensive property damage. A key challenge to understanding and predicting rainfall-triggered landslides comes from observational uncertainties in the depth and intensity of precipitation preceding the event. Practitioners and researchers must select among a wide range of precipitation products, often with little guidance. Here we evaluate the degree of precipitation uncertainty across multiple precipitation products for a large set of landslide-triggering storm events and investigate the impact of these uncertainties on predicted landslide probability using published intensity-duration thresholds. The average intensity, peak intensity, duration, and NOAA-Atlas return periods are compared ahead of 228 reported landslides across the continental US and Canada. Precipitation data are taken from four products that cover disparate measurement methods: near real-time and post-processed satellite (IMERG), radar (MRMS), and gauge-based (NLDAS-2). Landslide-triggering precipitation was found to vary widely across precipitation products with the depth of individual storm events diverging by as much as 296 mm with an average range of 51 mm. Peak intensity measurements, which are typically influential in triggering landslides, were also highly variable with an average range of 7.8 mm/hr and as much as 57 mm/hr. The two products more reliant upon ground-based observations (MRMS and NLDAS-2) performed better at identifying landslides according to published intensity-duration storm thresholds, but all products exhibited hit-ratios of greater than 0.56. A greater proportion of landslides were predicted when including only manually-verified landslide locations. We recommend practitioners consider low-latency products like MRMS for investigating landslides, given their near-real time data availability and good performance in detecting landslides. Practitioners would be well-served considering more than one product as a way to confirm intense storm signals and minimize the influence of noise and false alarms.
Groundwater age is often used to estimate groundwater recharge through a simplified analytical approach. This estimated recharge is thought to be representative of the mean recharge between the point of entry and the sampling point. However, given the complexity in actual recharge, whether the mean recharge is reasonable is still unclear. This study examined the validity of the method to estimate long-term average groundwater recharge and the possibility of obtaining reasonable spatial recharge pattern. We first validated our model in producing reasonable age distributions using a constant flux boundary condition. We then generated different flow fields and age patterns by using various spatially-varying flux boundary conditions with different magnitudes and wavelengths. Groundwater recharge was estimated and analyzed afterwards using the method at the spatial scale. We illustrated the main findings with a field example in the end. Our results suggest that we can estimate long-term average groundwater recharge with 10% error in many parts of an aquifer. The size of these areas decreases with the increase in both the amplitude and the wavelength. The chance of obtaining a reasonable groundwater recharge is higher if an age sample is collected from the middle of an aquifer and at downstream areas. Our study also indicates that the method can also be used to estimate local groundwater recharge if age samples are collected close to the water table. However, care must be taken to determine groundwater age regardless of conditions.
Clay aquitards are semipermeable membranes that allow groundwater flow while retarding solute migration have been researched extensively but also subjected to much debate. In this study, we collected clay samples from drilling cores (30–90m) in the Hengshui area located in the Hebei Plain, then extracted pore water using a high-pressure squeezing device. Vertical hydrochemical and isotopic profile variation trends for the pore water were revealed using hydrochemical (Cl－, Na+, Ca2+, K+, Mg2+, and SO42-) and stable isotopic measurements of H, O, and Cl. The results showed that the hydrochemical clay interlayer pore water of the saline aquifer is Cl•SO4-Na•Mg type and the average total dissolved solids（TDS）is 10.17g/L. The hydrochemical clay aquitard pore water is of the Cl•SO4-Na•Ca type with an average TDS of 1.9g/L. The hydrochemical clay interlayer pore water of aquifer II is of Cl-Na•Ca type with an average TDS of 1.1g/L. Our results showed that the water quality of the aquifer II is not affected by the upper part of saline aquifer, thus the clay aquitard acts as a significant barrier to salt movement. A polarization layer concentrated in ions was formed between the upper part of saline aquifer and the clay aquitard. The concentration polarization layer increases the salt-inhibition effect. Isotpic H, O, and Cl results showed significant fractionation. The pore water of aquifer II lacked heavy isotopes(D、18O、37Cl), but had significant heavy isotope enrichment in the concentrated polarized layer (the δD value was -76‰, the δ18O value was -8.4‰, and the δ37Cl value was 1.59‰). Hyperfiltration thus played a significant role in isotope fractionation.
Soil moisture plays a significant role in land-atmosphere interactions. Changing fractions of latent and sensible heat fluxes caused by soil moisture variations can affect near-surface air temperature, thus influencing the cooling effect of the oasis in arid regions. In this study, the framework for the evaporative fraction (EF) dependence on soil moisture is used to analyze the impacts of soil moisture variation on near-surface air temperature and the oasis effect. The results showed that the contribution rate of soil moisture to EF was significantly higher than that of EF to temperature. Under the interaction of temperature sensitivity to EF and EF to soil moisture, the ∂T/∂ϴ presented a similar tempo-spatial variation with both of the above. It was most significant in oasis areas during summer (−1.676), while it was weaker in plain desert areas during the autumn (−0.071). In the study region, the effect of soil moisture variation on air temperature can reach 0.018–0.242 K for different land-cover types in summer. The maximum variation of soil moisture in summer can alter air temperature by up to 0.386 K. The difference in temperature variability between the oasis and desert areas promoted the formation of the oasis effect. For different oasis, the multi-year average oasis cold effect index (OCI) ranged from −1.36 K to −0.26 K, while average summer OCI ranged from −1.38 K to −0.29 K. The lower bound of the cooling effect of oasis ranged from −4.97 to −1.69 K. The analysis framework and results of this study will provide a new perspective for further research on the evolution process of the oasis effect and water-heat balance in arid areas.
Management of water, regionally, nationally and globally will continue to be a priority and complex undertaking. In riverine systems, biotic components like flora and fauna, play critical roles in filtering water so it is available for human use and consumption. Preservation of ecosystems and associated ecosystem functions is therefore vital. In highly regulated large river basins, natural ecosystems are often supported through provision of environmental flows. Flow delivery, however, should be underpinned by rigorous monitoring to identify and prioritise biotic water requirements. Broadscale monitoring solutions are thus integral and for woody tree vegetation species, this is can be via measurement of field evapotranspiration, regionally scaled using remote sensing. However, as there is generally a mismatch between field data collection area and remote sensing pixel size, new methods are required to proportion tree evapotranspiration based on tree fractional canopy area per pixel. Within, we present a novel method to derive tree fractional canopy cover (FTCC) at 20 m resolution, in semi-arid and arid floodplain areas. The method employs LiDAR as a canopy area field measurement proxy (10 m resolution). Sentinel-1 and Sentinel-2, radar and multispectral imagery, were used in Random forest analysis, undertaken to develop a predictive FTCC model trained using LiDAR for two regions in the Murray-Darling Basin. A predictor model, combing the results of both regions, was able to explain between 85-91% of FTCC variation when compared to LiDAR FTCC, output in 10% increments. Development of this method underpins the advancement of woody vegetation monitoring to inform environmental flow management in the Murray-Darling Basin. The method and fine scale outputs will also be of value to other catchment management concerns such as altered catchment water yields related to bushfires and as such, has application to water management worldwide.
Soil freeze-thaw events have important implications for water resources, flood risk, land productivity, and climate change. A property of these phenomena is the relationship between unfrozen water content and sub-freezing temperature, known as the soil freezing characteristic curve (SFC). It is documented that this relationship exhibits hysteretic behaviour when frozen soil thaws, leading to the definition of the soil thawing characteristic curve (STC). Although explanations have been given for SFC/STC hysteresis, the effect that “scale”—particularly “measurement scale”—may have on these curves has received little attention. The most commonly used measurement scale metric is the “grain” or “support,” which is the spatial (or temporal) unit within which the measured variable is integrated—in this case, the soil volume sampled. We show (1) measurement support can influence the range and shape of the SFC and (2) hysteresis can be, at least partially, attributed to the support and location of the measurements comprising the SFC/STC. We simulated lab measured temperature, volumetric water content (VWC), and permittivity from soil samples undergoing freeze-thaw transitions using Hydrus-1D and a modified Dobson permittivity model. To assess the effect of measurement support and location on SFC/STC, we masked the simulated temperature and VWC/permittivity extent to match the instrument’s grain and location. By creating a detailed simulation of the intra- and inter-grain variability associated with the penetration of a freezing front, we demonstrate how measurement support and location can influence the temperature range over which water freezing events are captured. We show it is possible to simulate hysteresis in homogenous media with purely geometric considerations, suggesting that SFC/STC hysteresis may be more of an apparent phenomenon than mechanistically real. Lastly, we develop an understanding of how the location and support of soil temperature and VWC/permittivity measurements influence the temperature range over which water freezing events are captured.
This study focuses on a 10-m2 plot within a granitic hillslope in Cevennes mountainous area in France, in order to study infiltration and subsurface hydrological processes during heavy rainfalls and flash floods. The monitoring device included water content at several depths (0-70cm for the shallow soil water; 0-10m for the deep water) during both intense artificial and natural rainfall events, chemical and physical tracers, time-lapse electrical resistivity tomography. During the most intense events, the infiltrated water was estimated to be some hundreds of millimeters, which largely exceeds the topsoil capacity (≤40 cm deep in most of the cases). The weathered/fractured rock area below the soil clearly has an active role in the water storage and sub-surface flow dynamics. Vertical flow was dominant in the first 0-10m, and lateral flow was effective at 8-10 m depth, at the top of the saturated area. The speed of the vertical flow was estimated between 1 and 10 m/h, whereas it was estimated between 0.1 and 1 m/h for the lateral flow. The interpretation of the experiments led to a local pattern of the 2D-hydrological processes and profile properties. It suggests that fast triggering of floods at the catchment scale cannot be explained by a mass transfer within the hillslope, but should be due to a pressure wave propagation through the bedrock fractures, which allows exfiltration of the water downstream the hillslope.
Snow is Earth’s most climatically sensitive land cover type. Air temperature and moisture availability are first-order controls on snowfall. Maximum snowfall occurs at temperatures very near 0°C, so even a slight increase in temperature will shift a snowy winter to one with midseason rainfall and melt events. Traditional snow metrics are not able to adequately capture the changing nature of snow cover. For example, April 1 snow water equivalent (SWE, the amount of water represented by the snowpack) is used as a streamflow predictor. Still, it cannot express the effects of midwinter melt events, now expected in warming snow climates. The multiple impacts of a changing snowpack require a suite of climate indicators derived from readily measured or modelled data that serve as proxies for relevant snow-related and climate-driven processes. Such indicators need to be simple enough to “tell the story” of snowpack changes over space and time, but not overly simplistic as to be conflated with other variables or, conversely, overly complicated in their interpretation. This paper describes a targeted set of spatially explicit, multi-temporal snow metrics for multiple sectors, stakeholders, and scientists. They include metrics based on satellite data from NASA’s Moderate Resolution Imaging Spectroradiometer, meteorological observations and snow data from ground-based stations, and climate model output. We describe and provide examples for Snow Cover Frequency (SCF), Snow Disappearance Date (SDD), snowstorm temperature (ST), At-Risk Snow (ARS), and Frequency of a Warm Winter (FWW).
Catchment-scale response functions, such as transit time distribution (TTD) and evapotranspiration time distribution (ETTD), are considered fundamental descriptors of a catchment’s hydrologic and ecohydrologic responses to spatially and temporally varying precipitation inputs. Yet, estimating these functions is challenging, especially in headwater catchments where data collection is complicated by rugged terrain, or in semi-arid or sub-humid areas where precipitation is infrequent. Hence, we developed practical approaches for estimating both TTD and ETTD from commonly available tracer flux data in hydrologic inflows and outflows without requiring continuous observations. Using the weighted wavelet spectral analysis method of Kirchner and Neal  for δ18O in precipitation and stream water, we specifically calculated TTDs that contribute to streamflow via spatially and temporally variable flow paths in a sub-humid mountain headwater catchment in Arizona, USA. Our results indicate that composite TTDs most accurately represented this system for periods up to approximately one month and that a Gamma TTD was most appropriate thereafter. The TTD results also suggested that some contribution of subsurface water was beyond the applicable tracer range. For ETTD and using δ18O as a tracer in precipitation and xylem waters, a Gamma ETTD type best matched the observations, and stable water isotopes were capable tracers for the majority of vegetation source waters. This study contributes to a better understanding of a fundamental question in mountain catchment hydrology; namely, how tracer input fluxes are modulated by spatially and temporally varying subsurface flow paths that support evapotranspiration and streamflow at multiple time scales.
Soil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data-sparse region. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically-based, one-dimensional ecohydrologic Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13-year period. Using a Generalized Likelihood Uncertainty Estimation (GLUE) parameterization, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five-year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight-year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures (RMSE) that minimize error in soil moisture simulation, with those that were designed to minimize the dependence of model performance on interannual climate variability. The latter case moderately decreases traditional model performance but is likely more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterization, and (3) a novel objective function for parameter selection to improve applicability in non-stationary climates.