Runoff sensitivity to snow depletion curve representation within a continental scale hydrologic model

Abstract A common term in the continental and oceanic components of the global water cycle is freshwater discharge to the oceans. Many estimates of the annual average global discharge have been made over the past 100 yr with a surprisingly wide range. As more observations have become available and continental-scale land surface model simulations of runoff have improved, these past estimates are cast in a somewhat different light. In this paper, a combination of observations from 839 river gauging stations near the outlets of large river basins is used in combination with simulated runoff fields from two implementations of the Variable Infiltration Capacity land surface model to estimate continental runoff into the world’s oceans from 1950 to 2008. The gauges used account for ~58% of continental areas draining to the ocean worldwide, excluding Greenland and Antarctica. This study estimates that flows to the world’s oceans globally are 44 200 (±2660) km3 yr−1 (9% from Africa, 37% from Eurasia, 30% from South America, 16% from North America, and 8% from Australia–Oceania). These estimates are generally higher than previous estimates, with the largest differences in South America and Australia–Oceania. Given that roughly 42% of ocean-draining continental areas are ungauged, it is not surprising that estimates are sensitive to the land surface and hydrologic model (LSM) used, even with a correction applied to adjust for model bias. The results show that more and better in situ streamflow measurements would be most useful in reducing uncertainties, in particular in the southern tip of South America, the islands of Oceania, and central Africa.

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Assessment of the ParFlow–CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States

Geoscientific Model Development ◽

10.5194/gmd-14-7223-2021 ◽

2021 ◽

Vol 14 (12) ◽

pp. 7223-7254

Author(s):

Mary M. F. O'Neill ◽

Danielle T. Tijerina ◽

Laura E. Condon ◽

Reed M. Maxwell

Keyword(s):

United States ◽

High Resolution ◽

Water Balance ◽

Water Table ◽

Performance Metrics ◽

System Modeling ◽

Hydrologic Model ◽

Surface Model ◽

Water Balance Components ◽

Continental Scale

Abstract. Recent advancements in computational efficiency and Earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific, and operational benefits. The coupled hydrology–land surface model ParFlow–CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-dependent connections between water table depth, topography, recharge, and evapotranspiration, as well as to explore impacts of anthropogenic aquifer depletion to the water and energy balance. These studies have allowed for an unprecedented process-based understanding of the continental water cycle at high resolution. Here, we provide the most comprehensive evaluation of PFCONUS version 1.0 (PFCONUSv1) performance to date by comparing numerous modeled water balance components with thousands of in situ observations and several remote sensing products and using a range of statistical performance metrics for evaluation. PFCONUSv1 comparisons with these datasets are a promising indicator of model fidelity and ability to reproduce the continental-scale water balance at high resolution. Areas for improvement are identified, such as a positive streamflow bias at gauges in the eastern Great Plains, a shallow water table bias over many areas of the model domain, and low bias in seasonal total water storage amplitude, especially for the Ohio, Missouri, and Arkansas River basins. We discuss several potential sources for model bias and suggest that minimizing error in topographic processing and meteorological forcing would considerably improve model performance. Results here provide a benchmark and guidance for further PFCONUS model development, and they highlight the importance of concurrently evaluating all hydrologic components and fluxes to provide a multivariate, holistic validation of the complete modeled water balance.

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Assessment of the ParFlow-CLM CONUS 1.0 integrated hydrologic model: Evaluation of hyper-resolution water balance components across the contiguous United States

10.5194/gmd-2020-364 ◽

2020 ◽

Author(s):

Mary M. F. O'Neill ◽

Danielle T. Tijerina ◽

Laura E. Condon ◽

Reed M. Maxwell

Keyword(s):

United States ◽

High Resolution ◽

Water Balance ◽

Water Table ◽

Performance Metrics ◽

System Modeling ◽

Hydrologic Model ◽

Surface Model ◽

Water Balance Components ◽

Continental Scale

Abstract. Recent advancements in computational efficiency and earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific and operational benefits. The coupled hydrology-land surface model ParFlow-CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-dependent connections between water table depth, topography, recharge, and evapotranspiration, as well as to explore impacts of anthropogenic aquifer depletion to the water and energy balance. These studies have allowed for an unprecedented, process-based understanding of the continental water cycle at high resolution. Here, we provide the most comprehensive evaluation of PFCONUS version 1.0 (PFCONUSv1) performance to date, comparing numerous modeled water balance components with thousands of in situ observations and several remote sensing products, and using a range of statistical performance metrics for evaluation. PFCONUSv1 comparisons with these datasets are a promising indicator of model fidelity and ability to appropriately reproduce the continental-scale water balance at high resolution. Areas for improvement are identified, such as a positive streamflow bias at gauges in the eastern Great Plains, a shallow water table bias over many areas of the model domain, and low bias in seasonal total water storage amplitude especially for the Ohio, Missouri and Arkansas river basins. We discuss several potential sources for model bias and suggest that minimizing error in topographic processing and meteorological forcing would considerably improve model performance. Results here provide a benchmark and guidance for further PFCONUS model development, and they highlight the importance of concurrently evaluating all hydrologic components and fluxes to provide a multivariate, holistic validation of the complete modeled water balance.

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MPR 1.0: A stand-alone Multiscale Parameter Regionalization Tool for Improved Parameter Estimation of Land Surface Models

10.5194/gmd-2021-103 ◽

2021 ◽

Author(s):

Robert Schweppe ◽

Stephan Thober ◽

Matthias Kelbling ◽

Rohini Kumar ◽

Sabine Attinger ◽

...

Keyword(s):

Parameter Estimation ◽

Parameter Space ◽

Land Surface ◽

Hydrologic Model ◽

Model Parameters ◽

Land Surface Models ◽

Continental Scale ◽

Environmental Models ◽

Surface Models

Abstract. Distributed environmental models such as land surface models (LSM) require model parameters in each spatial modelling unit (e.g. grid cell), thereby leading to a high-dimensional parameter space. One approach to decrease the dimen- sionality of parameter space in these models is to use regularization techniques. One such highly efficient technique is the Multiscale Parameter Regionalization (MPR) framework that translates high-resolution predictor variables (e.g., soil textural properties) into model parameters (e.g., porosity) via transfer functions (TFs) and upscaling operators that are suitable for every modeled process. This framework yields seamless model parameters at multiple scales and locations in an effective manner. However, integration of MPR into existing modeling workflows has been hindered thus far by hard-coded configurations and non-modular software designs. For these reasons, we redesigned MPR as a model-agnostic, stand-alone tool. It is a useful software for creating graphs of netCDF variables, wherein each node is a variable and the links consist of TFs and/or upscaling operators. In this study, we present and verify our tool against a previous version, which was implemented in the mesoscale hydrologic model mHM (www.ufz.de/mhm). By using this tool for the generation of continental-scale soil hydraulic param- eters applicable to different models (Noah-MP and HTESSEL), we showcase its general functionality and flexibility. Further, using model parameters estimated by the MPR tool leads to significant changes in long-term estimates of evapotranspiration, as compared to their default parameterizations. For example, a change of up to 25 % in long-term evapotranspiration flux is observed in Noah-MP and HTESSEL in the Mississippi River basin. We postulate that use of the stand-alone MPR tool will considerably increase the transparency and reproducibility of the parameter estimation process in distributed (environmental) models. It will also allow a rigorous uncertainty estimation related to the errors of the predictors (e.g., soil texture fields), transfer function and its parameters, and remapping (or upscaling) algorithms.

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Exploring Hydrologic Model Process Connectivity at the Continental Scale Through an Information Theory Approach

Water Resources Research ◽

10.1029/2020wr027340 ◽

2020 ◽

Vol 56 (10) ◽

Author(s):

Goutam Konapala ◽

Shih‐Chieh Kao ◽

Nans Addor

Keyword(s):

Information Theory ◽

Hydrologic Model ◽

Theory Approach ◽

Continental Scale

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A high-resolution simulation of groundwater and surface water over most of the continental US with the integrated hydrologic model ParFlow v3

Geoscientific Model Development ◽

10.5194/gmd-8-923-2015 ◽

2015 ◽

Vol 8 (3) ◽

pp. 923-937 ◽

Cited By ~ 108

Author(s):

R. M. Maxwell ◽

L. E. Condon ◽

S. J. Kollet

Keyword(s):

High Resolution ◽

Large Scale ◽

Numerical Models ◽

Subsurface Flow ◽

Hydrologic Model ◽

Grand Challenge ◽

Flow Equations ◽

Continental Scale ◽

Integrated Hydrologic Model ◽

Surface And Subsurface Flow

Abstract. Interactions between surface and groundwater systems are well-established theoretically and observationally. While numerical models that solve both surface and subsurface flow equations in a single framework (matrix) are increasingly being applied, computational limitations have restricted their use to local and regional studies. Regional or watershed-scale simulations have been effective tools for understanding hydrologic processes; however, there are still many questions, such as the adaptation of water resources to anthropogenic stressors and climate variability, that can only be answered across large spatial extents at high resolution. In response to this grand challenge in hydrology, we present the results of a parallel, integrated hydrologic model simulating surface and subsurface flow at high spatial resolution (1 km) over much of continental North America (~ 6.3 M km2). These simulations provide integrated predictions of hydrologic states and fluxes, namely, water table depth and streamflow, at very large scale and high resolution. The physics-based modeling approach used here requires limited parameterizations and relies only on more fundamental inputs such as topography, hydrogeologic properties and climate forcing. Results are compared to observations and provide mechanistic insight into hydrologic process interaction. This study demonstrates both the feasibility of continental-scale integrated models and their utility for improving our understanding of large-scale hydrologic systems; the combination of high resolution and large spatial extent facilitates analysis of scaling relationships using model outputs.

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Simulation of groundwater and surface water over the continental US using a hyperresolution, integrated hydrologic model

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-7317-2014 ◽

2014 ◽

Vol 7 (6) ◽

pp. 7317-7349 ◽

Cited By ~ 4

Author(s):

R. M. Maxwell ◽

L. E. Condon ◽

S. J. Kollet

Keyword(s):

High Resolution ◽

Large Scale ◽

Numerical Models ◽

Subsurface Flow ◽

Hydrologic Model ◽

Grand Challenge ◽

Flow Equations ◽

Continental Scale ◽

Integrated Hydrologic Model ◽

Surface And Subsurface Flow

Abstract. Interactions between surface and groundwater systems are well-established theoretically and observationally. While numerical models that solve both surface and subsurface flow equations in a single framework (matrix) are increasingly being applied, computational limitations have restricted their use to local and regional studies. Regional or watershed, scale simulations have been effective tools in understanding hydrologic processes, however there are still many questions, such as the adaptation of water resources to anthropogenic stressors and climate variability, that need to be answered across large spatial extents at high resolution. In response to this "grand challenge" in hydrology, we present the results of a parallel, integrated hydrologic model simulating surface and subsurface flow at high spatial resolution (1 km) over much of continental North America (~ 6 300 000 or 6.3 million km2). These simulations provide predictions of hydrologic states and fluxes, namely water table depth and streamflow, at unprecedented scale and resolution. The physically-based modeling approach used here requires limited parameterizations and relies only on more fundamental inputs, such as topography, hydrogeologic properties and climate forcing. Results are compared to observations and provide mechanistic insight into hydrologic process interaction. This study demonstrates both the feasibility of continental scale integrated models and their utility for improving our understanding of large-scale hydrologic systems; the combination of high resolution and large spatial extent facilitates novel analysis of scaling relationships using model outputs.

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Sensitivity of hydrological fluxes and states to groundwater representation in continental scale simulations over Europe.

10.5194/egusphere-egu21-4341 ◽

2021 ◽

Author(s):

Bibi S. Naz ◽

Wendy Sharples ◽

Klaus Goergen ◽

Stefan Kollet

Keyword(s):

Soil Moisture ◽

Groundwater Recharge ◽

Water Storage ◽

Hydrologic Model ◽

Richards Equation ◽

Total Water ◽

Time Step ◽

Continental Scale ◽

Community Land Model

<p>This study explores the influence of groundwater representation on soil moisture, evapotranspiration, total water storage, water table depth and groundwater recharge/discharge through the comparison of multi-model simulations using the stand-alone Community Land Model (CLM3.5) and the ParFlow hydrologic model. ParFlow simulates three-dimensional variably saturated groundwater flow solving Richards equation and overland flow with a two-dimensional kinematic wave approximation, whereas CLM3.5 applies a simple approach to simulate groundwater recharge and discharge processes via the connection of bottom soil layer and an unconfined aquifer. Over Europe with a lateral resolution of 3km, both models were driven with the COSMO-REA6 reanalysis dataset for the time period from 1997 to 2006 at an hourly time step using the same datasets for the static input variables (such as topography, vegetation and soil properties). Evaluation against independent observations including satellite-derived and in-situ soil moisture, evapotranspiration, and total water storage datasets show that both models capture the interannual and seasonal variations well at the regional scale, however ParFlow performs better in simulating surface soil moisture in comparison with in-situ data. Moreover, juxtaposition of both models shows that simulations of water fluxes and sates in both space and time are sensitive to the differences in groundwater representation in the model. For example, simulations with ParFlow have overall wetter soil moisture than CLM, particularly in humid and cold regions and driest soil moisture in the arid and semi-arid regions. Seasonally, ParFlow simulates wetter soil moisture in winter and driest in summer than CLM model. This study helps to understand and quantify uncertainties in groundwater related processes in hydrologic simulations and resulting implications for water resources assessment at regional to continental scales.</p>

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