A new approach to evaluate spatiotemporal dynamics of controlling parameters in distributed environmental models

Chen, Zhao; Hartmann, Andreas; Goldscheider, Nico

doi:10.1016/j.envsoft.2016.10.005

Cited by 37 publications

(31 citation statements)

References 46 publications

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“…In a previous comprehensive sensitivity analysis we demonstrated that the controlling parameters exhibit varying sensitivity for different hydrodynamic conditions and for different spatially-distributed model outlets (Chen et al, 2017). Based on this information, we designed four steps to calibrate the model using different hydrodynamic system conditions and the observed time series for different outlets.…”

Section: Calibration Strategy 20mentioning

confidence: 99%

“…The 15 simultaneous minimization of the sum of the squared errors (SSE) of multiple observed time series was applied to constrain the model parameter space (described in section 3.4.2), which was defined based on our previous experience in the study region (Chen and Goldscheider, 2014;Chen et al, 2017). The DREAM algorithm allows an initial population of parameter sets to converge to a stationary sample.…”

Section: Model Optimizationmentioning

confidence: 99%

“…Here, we expanded an existing model (Chen and Goldscheider, 2014) by adding a snow accumulation/melting routine with high spatiotemporal resolution. We also developed a tailored calibration strategy, building on a previous sensitivity analysis by Chen et al (2017), to calibrate the proposed catchment model reasonably and effectively.…”

Section: Introductionmentioning

confidence: 99%

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Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions

Chen¹,

Hartmann²,

Wagener³

et al. 2017

Preprint

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Abstract. Climate change projections indicate significant changes to precipitation and temperature regimes in European karst regions. Alpine karst systems can be especially vulnerable under changing hydro-meteorological conditions since snowmelt in mountainous environments is an important controlling process for aquifer recharge, and is highly sensitive to 10 varying climatic conditions. The current study presents an investigation of present and future water fluxes and storages at an Alpine karst catchment using a distributed numerical model. A delta approach combined with random sampling was used to assess the potential impacts of climate changes. The study site is characterized by high permeability (karstified) limestone formations and low permeability (non-karst) sedimentary flysch. The model simulation under current conditions demonstrates that a large proportion of precipitation infiltrates into the karst aquifer as autogenic recharge. Surface runoff in 15 the adjacent non-karst areas partly infiltrates into the karst aquifer as allogenic point recharge. Moreover, the result shows that surface snow storage is dominant from November to April, while subsurface water storage in the karst aquifer dominates from May to October. The climate scenario runs demonstrate that varied climate conditions significantly affect the spatiotemporal distribution of water fluxes and storages: (1) the total catchment discharge decreases under all evaluated future climate conditions. (2) The spatiotemporal discharge pattern is strongly controlled by temperature variations, which 20 can shift the seasonal snowmelt pattern, with snow storage in the cold season (December to April) decreasing significantly under all change scenarios. (3) Increased karst aquifer recharge in winter and spring, and decreased recharge in summer and autumn, partly offset each other. (4) Impacts on the karst springs are distinct; the permanent spring presents a "robust" discharge behavior, while the estavelle is highly sensitive to changing climate. This analysis effectively demonstrates that the impacts on subsurface flow dynamics are regulated by the characteristic dual flow and spatially heterogeneous distributed 25 drainage structure of the karst aquifer. Overall, our study suggests that bespoke hydrological models tailored to the specific subsurface characteristics of an Alpine karst catchment are needed to understand climate change impact.

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Section: Calibration Strategy 20mentioning

confidence: 99%

Section: Model Optimizationmentioning

confidence: 99%

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Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions

Chen¹,

Hartmann²,

Wagener³

et al. 2017

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Despite the widespread application and advancement of physically based, fully distributed (cell-by-cell basis) models, one of the foremost challenges in distributed model application continues to be parameter estimation (Beven and Binley, 1992;Gupta et al, 1998;Wagener and Gupta, 2005;Beven, 2006;Gharari et al, 2014;Chen et al, 2017). Model simulations and predictions require specification of parameter set(s) or ranges; selecting these set(s) and appropriate ranges is especially challenging given that fully distributed models, where inputs such as soil or vegetation are distributed across the watershed, require a larger number of model parameters (∼ 50-100 or more) and longer model run times than conceptual or lumped models.…”

Section: Introductionmentioning

confidence: 99%

Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding

Kelleher

McGlynn

Wagener

2017

Hydrol. Earth Syst. Sci.

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Abstract. Distributed catchment models are widely used tools for predicting hydrologic behavior. While distributed models require many parameters to describe a system, they are expected to simulate behavior that is more consistent with observed processes. However, obtaining a single set of acceptable parameters can be problematic, as parameter equifinality often results in several "behavioral" sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modeling application. We outline a hierarchical approach to reduce the number of behavioral sets based on regional, observation-driven, and expert-knowledge-based constraints. For our application, we explore how each of these constraint classes reduced the number of "behavioral" parameter sets and altered distributions of spatiotemporal simulations, simulating a well-studied headwater catchment, Stringer Creek, Montana, using the distributed hydrology-soil-vegetation model (DHSVM). As a demonstrative exercise, we investigated model performance across 10 000 parameter sets. Constraints on regional signatures, the hydrograph, and two internal measurements of snow water equivalent time series reduced the number of behavioral parameter sets but still left a small number with similar goodness of fit. This subset was ultimately further reduced by incorporating pattern expectations of groundwater table depth across the catchment. Our results suggest that utilizing a hierarchical approach based on regional datasets, observations, and expert knowledge to identify behavioral parameter sets can reduce equifinality and bolster more careful application and simulation of spatiotemporal processes via distributed modeling at the catchment scale.

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“…Regional sensitivity analysis has been widely used to show this relationship of karst spring discharge with different hydrological processes in a local karst catchment (Chang et al, 2017). Chen et al (2017) and Hartmann et al (2015) applied Sobol's global sensitivity method to evaluate parameters using different objective functions under different hydrodynamic conditions. However, very few studies have addressed the parameters' sensitivities for modeling seawater intrusion in a coastal karst aquifer.…”

Section: Introductionmentioning

confidence: 99%

Numerical modeling and sensitivity analysis of seawater intrusion in a dual-permeability coastal karst aquifer with conduit networks

2018

Hydrol. Earth Syst. Sci.

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Abstract. Long-distance seawater intrusion has been widely observed through the subsurface conduit system in coastal karst aquifers as a source of groundwater contaminant. In this study, seawater intrusion in a dual-permeability karst aquifer with conduit networks is studied by the two-dimensional density-dependent flow and transport SEAWAT model. Local and global sensitivity analyses are used to evaluate the impacts of boundary conditions and hydrological characteristics on modeling seawater intrusion in a karst aquifer, including hydraulic conductivity, effective porosity, specific storage, and dispersivity of the conduit network and of the porous medium. The local sensitivity analysis evaluates the parameters' sensitivities for modeling seawater intrusion, specifically in the Woodville Karst Plain (WKP). A more comprehensive interpretation of parameter sensitivities, including the nonlinear relationship between simulations and parameters, and/or parameter interactions, is addressed in the global sensitivity analysis. The conduit parameters and boundary conditions are important to the simulations in the porous medium because of the dynamical exchanges between the two systems. The sensitivity study indicates that salinity and head simulations in the karst features, such as the conduit system and submarine springs, are critical for understanding seawater intrusion in a coastal karst aquifer. The evaluation of hydraulic conductivity sensitivity in the continuum SEA-WAT model may be biased since the conduit flow velocity is not accurately calculated by Darcy's equation as a function of head difference and hydraulic conductivity. In addition, dispersivity is no longer an important parameter in an advectiondominated karst aquifer with a conduit system, compared to the sensitivity results in a porous medium aquifer. In the end, the extents of seawater intrusion are quantitatively evaluated and measured under different scenarios with the variabilities of important parameters identified from sensitivity results, including salinity at the submarine spring with rainfall recharge, sea level rise, and a longer simulation time under an extended low rainfall period.

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A new approach to evaluate spatiotemporal dynamics of controlling parameters in distributed environmental models

Cited by 37 publications

References 46 publications

Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions

Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions

Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding

Numerical modeling and sensitivity analysis of seawater intrusion in a dual-permeability coastal karst aquifer with conduit networks

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