Simulation of water balance and forest treatment effects at the H.J. Andrews Experimental Forest

The distributed hydrology soil–vegetation model (DHSVM) was applied to the small watersheds WS1, 2, 3 in H.J. Andrews Experimental Forest, Oregon, and tested for skill in simulating observed forest treatment effects on streamflow. These watersheds, located in the rain–snow transition zone, underwent road and clearcut treatments during 1959–66 and subsequent natural regeneration. DHSVM was applied with 10 m and 1 h resolution to 1958–98, most of the period of record. Water balance for old‐growth WS2 indicated that evapotranspiration and streamflow were unlikely to be the only loss terms, and groundwater recharge was included to account for about 12% of precipitation; this term was assumed zero in previous studies. Overall efficiency in simulating hourly streamflow exceeded 0·7, and mean annual error was less than 10%. Model skill decreased at the margins, with overprediction of low flows and underprediction of high flows. However, statistical analyses of simulated and observed peakflows yielded similar characterizations of treatment effects. Primary simulation weaknesses were snowpack accumulation, snowmelt under rain‐on‐snow conditions, and production of quickflow. This was the first test of DHSVM against observations of both control and treated watersheds in a classic paired‐basin study involving a long time period of forest regrowth and hydrologic recovery. Copyright © 2005 John Wiley & Sons, Ltd.     

Assessing the impact of distributed snow water equivalent calibration and assimilation of Copernicus snow water equivalent on modelled snow and streamflow performance

Accuracy of the Copernicus snow water equivalent (SWE) product and the impact of SWE calibration and assimilation on modelled SWE and streamflow was evaluated. Daily snowpack measurements were made at 12 locations from 2016 to 2019 across a 4104 km² mixed-forest basin in the Great Lakes region of central Ontario, Canada. Sub-basin daily SWE calculated from these sites, observed discharge, and lake levels were used to calibrate a hydrologic model developed using the Raven modelling framework. Copernicus SWE was bias corrected during the melt period using mean bias subtraction and was compared to daily basin average SWE calculated from the measured data. Bias corrected Copernicus SWE was assimilated into the models using a range of parameters and the parameterizations from the model calibration. The bias corrected Copernicus product agreed well with measured data and provided a good estimate of mean basin SWE demonstrating that the product shows promise for hydrology applications within the study region. Calibration to spatially distributed SWE substantially improved the basin scale SWE estimate while only slightly degrading the flow simulation demonstrating the value of including SWE in a multi-objective calibration formulation. The particle filter experiments yielded the best SWE estimation but moderately degraded the flow simulation. The particle filter experiments constrained by the calibrated snow parameters produced similar results to the experiments using the upper and lower bounds indicating that, in this study, model calibration prior to assimilation was not valuable. The calibrated models exhibited varying levels of skill in estimating SWE but demonstrated similar streamflow performance. This indicates that basin outlet streamflow can be accurately estimated using a model with a poor representation of distributed SWE. This may be sufficient for applications where estimating flow is the primary water management objective. However, in applications where understanding the physical processes of snow accumulation, melt and streamflow generation are important, such as assessing the impact of climate change on water resources, accurate representations of SWE are required and can be improved via multi-objective calibration or data assimilation, as demonstrated in this study.     

Operational snow modeling: Addressing the challenges of an energy balance model for National Weather Service forecasts

Prediction of snowmelt has become a critical issue in much of the western United States given the increasing demand for water supply, changing snow cover patterns, and the subsequent requirement of optimal reservoir operation. The increasing importance of hydrologic predictions necessitates that traditional forecasting systems be re-evaluated periodically to assure continued evolution of the operational systems given scientific advancements in hydrology. The National Weather Service (NWS) SNOW17, a conceptually based model used for operational prediction of snowmelt, has been relatively unchanged for decades. In this study, the Snow–Atmosphere–Soil Transfer (SAST) model, which employs the energy balance method, is evaluated against the SNOW17 for the simulation of seasonal snowpack (both accumulation and melt) and basin discharge. We investigate model performance over a 13-year period using data from two basins within the Reynolds Creek Experimental Watershed located in southwestern Idaho. Both models are coupled to the NWS runoff model [SACramento Soil Moisture Accounting model (SACSMA)] to simulate basin streamflow. Results indicate that while in many years simulated snowpack and streamflow are similar between the two modeling systems, the SAST more often overestimates SWE during the spring due to a lack of mid-winter melt in the model. The SAST also had more rapid spring melt rates than the SNOW17, leading to larger errors in the timing and amount of discharge on average. In general, the simpler SNOW17 performed consistently well, and in several years, better than, the SAST model. Input requirements and related uncertainties, and to a lesser extent calibration, are likely to be primary factors affecting the implementation of an energy balance model in operational streamflow prediction.     

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.     

Sensitivity of streamflow simulation in the Delaware River Basin to forecasted land‐cover change for 2030 and 2060

In order to simulate the potential effect of forecasted land‐cover change on streamflow and water availability, there has to be confidence that the hydrologic model used is sensitive to small changes in land cover (<10%) and that this land‐cover change exceeds the inherent uncertainty in forecasted conditions. To investigate this, a 26‐year streamflow record was simulated for 33 basins (54–928 km²) in the Delaware River Basin using three dates of land cover: the 2011 National Land‐Cover Dataset (Homer, Fry, & Barnes, 2012 ), 2030 land‐cover conditions representing median values from 101 equally‐likely forecasts, and 2060 land‐cover conditions corresponding to the same iterations used to represent 2030. Streamflow was simulated using a process‐based hydrologic model that includes both pervious and impervious methods as parameterized by three land‐cover‐based hydrologic response units (HRUs)—forested, agricultural, and developed land. Small, but significant differences in streamflow magnitude, variability, and seasonality were seen among the three time periods—2011, 2030, and 2060. Temporal differences were discernible from the range of conditions simulated with 101 equally likely forecasts for 2030. Development was co‐located with the most frequent landscape components, as characterized by topographic wetness index, resulting in a change in hydrology for each HRU, highlighting that knowing the location of disturbance is key to understanding potential streamflow changes. These results show that streamflow simulation using regional calibration that incorporates land‐cover‐based HRUs can be sensitive to relatively small changes in land‐cover and that temporal trends resulting from land‐cover change can be isolated in order to evaluate other changes that might affect water resources.     

Hydrological responses to climatic variability in a cold agricultural region

Extended severe dry and wet periods are frequently observed in the northern continental climate of the Canadian Prairies. Prairie streamflow is mainly driven by spring snowmelt of the winter snowpack, whilst summer rainfall is an important control on evapotranspiration and thus seasonality affects the hydrological response to drought and wet periods in complex ways. A field‐tested physically based model was used to investigate the influences of climatic variability on hydrological processes in this region. The model was set up to resolve agricultural fields and to include key cold regions processes. It was parameterized from local and regional measurements without calibration and run for the South Tobacco Creek basin in southern Manitoba, Canada. The model was tested against snow depth and streamflow observations at multiple scales and performed well enough to explore the impacts of wet and dry periods on hydrological processes governing the basin scale hydrological response. Four hydro‐climatic patterns with distinctive climatic seasonality and runoff responses were identified from differing combinations of wet/dry winter and summer seasons. Water balance analyses of these patterns identified substantive multiyear subsurface soil moisture storage depletion during drought (2001–2005) and recharge during a subsequent wet period (2009–2011). The fractional percentage of heavy rainfall days was a useful metric to explain the contrasting runoff volumes between dry and wet summers. Finally, a comparison of modeling approaches highlights the importance of antecedent fall soil moisture, ice lens formation during the snowmelt period, and peak snow water equivalent in simulating snowmelt runoff.     

Constraining water table depth simulations in a land surface model using estimated baseflow

Several recent studies have shown the significance of representing groundwater in land surface hydrologic simulations. However, optimal methods for model parameter calibration in order to realistically simulate baseflow and groundwater depth have received little attention. Most studies still use globally constant groundwater parameters due to the lack of available datasets for calibration. Moreover, when models are calibrated, various parameter combinations are found to exhibit equifinality in simulated total runoff due to model parameter interactions. In this study, a simple lumped groundwater model is incorporated into the Community Land Model (CLM), in which the water table is interactively coupled to soil moisture through the groundwater recharge fluxes. The coupled model (CLMGW) is successfully validated in Illinois using a 22-year (1984–2005) monthly observational dataset. Baseflow estimates from the digital recursive filter technique are used to calibrate the CLMGW parameters. The advantage obtained from incorporating baseflow calibration in addition to traditional calibration based on measured streamflow alone is demonstrated by a Monte Carlo-type simulation analysis. Using the optimal parameter sets identified from baseflow calibration, flow partitioning and water table depth simulations using CLMGW are improved, and the equifinality problem is alleviated. For other regions that lack observations of water table depth, the baseflow calibration approach can be used to enhance parameter estimation and constrain water table depth simulations.     

Effects of Linking a Soil‐Water‐Balance Model with a Groundwater‐Flow Model

A previously published regional groundwater‐flow model in north‐central Nebraska was sequentially linked with the recently developed soil‐water‐balance (SWB) model to analyze effects to groundwater‐flow model parameters and calibration results. The linked models provided a more detailed spatial and temporal distribution of simulated recharge based on hydrologic processes, improvement of simulated groundwater‐level changes and base flows at specific sites in agricultural areas, and a physically based assessment of the relative magnitude of recharge for grassland, nonirrigated cropland, and irrigated cropland areas. Root‐mean‐squared (RMS) differences between the simulated and estimated or measured target values for the previously published model and linked models were relatively similar and did not improve for all types of calibration targets. However, without any adjustment to the SWB‐generated recharge, the RMS difference between simulated and estimated base‐flow target values for the groundwater‐flow model was slightly smaller than for the previously published model, possibly indicating that the volume of recharge simulated by the SWB code was closer to actual hydrogeologic conditions than the previously published model provided. Groundwater‐level and base‐flow hydrographs showed that temporal patterns of simulated groundwater levels and base flows were more accurate for the linked models than for the previously published model at several sites, particularly in agricultural areas.     

Towards a simple dynamic process conceptualization in rainfall–runoff models using multi‐criteria calibration and tracers in temperate,upland catchments

Empirically based understanding of streamflow generation dynamics in a montane headwater catchment formed the basis for the development of simple, low‐parameterized, rainfall–runoff models. This study was based in the Girnock catchment in the Cairngorm Mountains of Scotland, where runoff generation is dominated by overland flow from peaty soils in valley bottom areas that are characterized by dynamic expansion and contraction of saturation zones. A stepwise procedure was used to select the level of model complexity that could be supported by field data. This facilitated the assessment of the way the dynamic process representation improved model performance. Model performance was evaluated using a multi‐criteria calibration procedure which applied a time series of hydrochemical tracers as an additional objective function. Flow simulations comparing a static against the dynamic saturation area model (SAM) substantially improved several evaluation criteria. Multi‐criteria evaluation using ensembles of performance measures provided a much more comprehensive assessment of the model performance than single efficiency statistics, which alone, could be misleading. Simulation of conservative source area tracers (Gran alkalinity) as part of the calibration procedure showed that a simple two‐storage model is the minimum complexity needed to capture the dominant processes governing catchment response. Additionally, calibration was improved by the integration of tracers into the flow model, which constrained model uncertainty and improved the hydrodynamics of simulations in a way that plausibly captured the contribution of different source areas to streamflow. This approach contributes to the quest for low‐parameter models that can achieve process‐based simulation of hydrological response. Copyright © 2009 John Wiley & Sons, Ltd.     

Hydrologic response of a Hawaiian watershed to future climate change scenarios

The impact of potential future climate change scenarios on streamflow and evapotranspiration (ET) in a mountainous Hawaii watershed was studied using the distributed hydrology soil vegetation model (DHSVM). The hydrologic response of the watershed was simulated for 43 years for different levels of atmospheric CO₂ (330, 550, 710 and 970 ppm), temperature (+1.1 and + 6.4 °C) and precipitation (±5%, ±10% and ±20%) on the basis of the Intergovernmental Panel on Climate Change (IPCC) AR4 projections under current, B1, A1B1 and A1F1 emission scenarios. Vegetation leaf conductance and leaf area index were modified to reflect the increase in CO₂ concentration. The relative departure of streamflow and ET from their levels during the reference scenarios was calculated on a monthly and annual basis. Results of this study indicate that the streamflow and ET are less sensitive to changes in temperature compared with changes in precipitation. However, temperature increase coupled with precipitation showed significant effect on ET and streamflow. Changes in leaf conductance and leaf area index with increasing CO₂ concentration under A1F1 scenario had a significant effect on ET and subsequently on streamflow. Evapotranspiration is less sensitive than streamflow for a similar level of change in precipitation. On the basis of a range of climate change scenarios, DHSVM predicted a change in ET by ±10% and streamflow between ?51% and 90%. From the six ensemble mean scenarios for AR4 A1B, simulations suggest reduction in streamflow by 6.7% to 17.2%. These reductions would produce severe impact on water availability in the region. Copyright © 2011 John Wiley & Sons, Ltd.     

Impact of model development,calibration and validation decisions on hydrological simulations in West Lake Erie Basin

Watershed simulation models are used extensively to investigate hydrologic processes, landuse and climate change impacts, pollutant load assessments and best management practices (BMPs). Developing, calibrating and validating these models require a number of critical decisions that will influence the ability of the model to represent real world conditions. Understanding how these decisions influence model performance is crucial, especially when making science‐based policy decisions. This study used the Soil and Water Assessment Tool (SWAT) model in West Lake Erie Basin (WLEB) to examine the influence of several of these decisions on hydrological processes and streamflow simulations. Specifically, this study addressed the following objectives (1) demonstrate the importance of considering intra‐watershed processes during model development, (2) compare and evaluated spatial calibration versus calibration at outlet and (3) evaluate parameter transfers across temporal and spatial scales. A coarser resolution (HUC‐12) model and a finer resolution model (NHDPlus model) were used to support the objectives. Results showed that knowledge of watershed characteristics and intra‐watershed processes are critical to produced accurate and realistic hydrologic simulations. The spatial calibration strategy produced better results compared to outlet calibration strategy and provided more confidence. Transferring parameter values across spatial scales (i.e. from coarser resolution model to finer resolution model) needs additional fine tuning to produce realistic results. Transferring parameters across temporal scales (i.e. from monthly to yearly and daily time‐steps) performed well with a similar spatial resolution model. Furthermore, this study shows that relying solely on quantitative statistics without considering additional information can produce good but unrealistic simulations. Copyright © 2015 John Wiley & Sons, Ltd.     

Hydrologic simulation of clay‐settling areas in the phosphate mining district,Florida

Clay‐settling areas (CSAs) are one of the most conspicuous and development‐limiting landforms remaining after phosphate mining. Many questions are asked by the mining and regulatory communities with regard to the correct modelling (predictive) methods and assumptions that should be used to yield viable hydrologic post‐reclamation landforms within CSAs. Questions as to the correct methodology to use in modelling/predicting long‐term CSA hydrologic performance have historically been difficult to answer because the data and analysis to support popular hypotheses did not exist. The goal of this paper was to substantially improve the data, analysis and predictive methodology necessary to return CSAs to viable hydrologic units, and moreover, to develop better understanding of the hydrology of CSAs and their ability to support wetlands. The study site is located at the Fort Meade Mine in Polk County, Florida. In this paper, continuous model simulation and calibration of study site were conducted for the hydrologic model, Hydrological Simulation Program – FORTRAN, which was generally selected on the basis of its popularity in predicting the hydrologic behaviour of CSAs. The objective of this study was to simulate streamflow discharges and stage to estimate runoff response from these areas on the basis of the observed rainfall within the CSA. A set of global hydrologic parameters was selected and tested during the calibration by the parameter estimation software PEST. A comparison of the simulated and observed flow data indicates that the model calibration adequately reproduces the hydrologic response of the CSAs. The estimated parameters can be used as references for future application of the model. Copyright © 2012 John Wiley & Sons, Ltd.     

Internal catchment process simulation in a snow‐dominated basin: performance evaluation with spatiotemporally variable runoff generation and groundwater dynamics

Hydrologic models have increasingly been used in forest hydrology to overcome the limitations of paired watershed experiments, where vegetative recovery and natural variability obscure the inferences and conclusions that can be drawn from such studies. Models are also plagued by uncertainty, however, and parameter equifinality is a common concern. Physically‐based, spatially‐distributed hydrologic models must therefore be tested with high‐quality experimental data describing a multitude of concurrent internal catchment processes under a range of hydrologic regimes. This study takes a novel approach by not only examining the ability of a pre‐calibrated model to realistically simulate watershed outlet flows over a four year period, but a multitude of spatially‐extensive, internal catchment process observations not previously evaluated, including: continuous groundwater dynamics, instantaneous stream and road network flows, and accumulation and melt period spatial snow distributions. Many hydrologic model evaluations are only on the comparison of predicted and observed discharge at a catchment outlet and remain in the ‘infant stage’ in terms of model testing. This study, on the other hand, tests the internal spatial predictions of a distributed model with a range of field observations over a wide range of hydroclimatic conditions. Nash‐Sutcliffe model efficiency was improved over prior evaluations due to continuing efforts in improving the quality of meteorological data collection. Road and stream network flows were generally well simulated for a range of hydrologic conditions, and snowpack spatial distributions were well simulated for one of two years examined. The spatial variability of groundwater dynamics was effectively simulated, except at locations where strong stream–groundwater interactions exist. Model simulations overall were quite successful in realistically simulating the spatiotemporal variability of internal catchment processes in the watershed, but the premature onset of simulated snowmelt for one of the simulation years has prompted further work in model development. Copyright © 2011 John Wiley & Sons, Ltd.     

A multi-objective calibration approach using in-situ soil moisture data for improved hydrological simulation of the Prairies

ABSTRACT

Traditionally, hydrological models are only calibrated to reproduce streamflow regime without considering other hydrological state variables, such as soil moisture and evapotranspiration. Limited studies have been performed on constraining the model parameters, despite the fact that the presence of a large number of parameters may provide large degree of freedom, resulting in equifinality and poor model performance. In this study, a multi-objective optimization approach is adopted, and both streamflow and soil moisture data are calibrated simultaneously for an experimental study basin in the Saskatchewan Prairies in western Canada. The results of this study show that the multi-objective calibration improves model fidelity compared to the single objective calibration. Moreover, the study demonstrates that single objective calibration performed against only streamflow can fairly mimic the streamflow hydrograph but does not yield realistic estimation of other fluxes such as evapotranspiration and soil moisture (especially in deeper soil layers).     

Simulated water budget of a small forested watershed in the continental/maritime hydroclimatic region of the United States

Annual streamflows have decreased across mountain watersheds in the Pacific Northwest of the United States over the last ~70 years; however, in some watersheds, observed annual flows have increased. Physically based models are useful tools to reveal the combined effects of climate and vegetation on long‐term water balances by explicitly simulating the internal watershed hydrological fluxes that affect discharge. We used the physically based Simultaneous Heat and Water (SHAW) model to simulate the inter‐annual hydrological dynamics of a 4 km² watershed in northern Idaho. The model simulates seasonal and annual water balance components including evaporation, transpiration, storage changes, deep drainage, and trends in streamflow. Independent measurements were used to parameterize the model, including forest transpiration, stomatal feedback to vapour pressure, forest properties (height, leaf area index, and biomass), soil properties, soil moisture, snow depth, and snow water equivalent. No calibrations were applied to fit the simulated streamflow to observations. The model reasonably simulated the annual runoff variations during the evaluation period from water year 2004 to 2009, which verified the ability of SHAW to simulate the water budget in this small watershed. The simulations indicated that inter‐annual variations in streamflow were driven by variations in precipitation and soil water storage. One key parameterization issue was leaf area index, which strongly influenced interception across the catchment. This approach appears promising to help elucidate the mechanisms responsible for hydrological trends and variations resulting from climate and vegetation changes on small watersheds in the region. Copyright © 2015 John Wiley & Sons, Ltd.     

Quantifying watershed surface depression storage: determination and application in a hydrologic model

Hydrologic models often require correct estimates of surface macro‐depressional storage to accurately simulate rainfall–runoff processes. Traditionally, depression storage is determined through model calibration or lumped with soil storage components or on an ad hoc basis. This paper investigates a holistic approach for estimating surface depressional storage capacity (DSC) in watersheds using digital elevation models (DEMs). The methodology includes implementing a lumped DSC model to extract geometric properties of storage elements from DEMs of varying grid resolutions and employing a consistency zone criterion to quantify the representative DSC of an isolated watershed. DSC obtained using the consistency zone approach is compared to DSC estimated by “brute force” (BF) optimization method. The BF procedure estimates optimal DSC by calibrating DRAINMOD, a quasi‐process based hydrologic model, with observed streamflow under different climatic conditions. Both methods are applied to determine the DSC for relatively low‐gradient coastal plain watersheds on forested landscape with slopes less than 3%. Results show robustness of the consistency zone approach for estimating depression storage. To test the adequacy of the calculated DSC values obtained, both methods are applied in DRAINMOD to predict the daily watershed flow rates. Comparison between observed and simulated streamflow reveals a marginal difference in performance between BF optimization and consistency zone estimated DSCs during wet periods, but the latter performed relatively better in dry periods. DSC is found to be dependent on seasonal antecedent moisture conditions on surface topography. The new methodology is beneficial in situations where data on depressional storage is unavailable for calibrating models requiring this input parameter. Copyright © 2012 John Wiley & Sons, Ltd.