Input data resolution analysis for distributed hydrological modeling

Shrestha, R.; Tachikawa, Yasuto; Takara, Kaoru

doi:10.1016/j.jhydrol.2005.04.025

Cited by 56 publications

(54 citation statements)

References 30 publications

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“…That is, instead of establishing a critical scale for optimal prediction [Wood et al, 1988;Famiglietti and Wood, 1994;Bruneau et al, 1995;Woods et al, 1995;Liang et al, 2004;Shrestha et al, 2006], we evaluate the ability of the two modeling approaches to produce robust predictions across multiple spatial scales. For this purpose, we systematically compare the two modeling approaches: (1) to determine if they differ in their scalability in hydrologic flux simulations across multiple spatial resolutions; (2) to explore the sources of their scalability differences; and (3) to determine the significance of their scalability differences.…”

Section: 1002/2013jd020493mentioning

confidence: 99%

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

Tesfa

Leung

Huang

et al. 2014

J. Geophys. Res. Atmos.

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This paper investigates the relative merits of grid-and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., ability to perform consistently across spatial resolutions) in simulating runoff generation. Simulations are produced by the grid-and subbasin-based Community Land Model at 0.125°, 0.25°, 0.5°, and 1°spatial resolutions over the U.S. Pacific Northwest. Using the 0.125°simulation as the "reference" solution, statistical metrics are calculated by comparing simulations at 0.25°, 0.5°, and 1°resolutions with the 0.125°simulation for each approach. Statistical significance test results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach. Basin level annual average relative errors of surface runoff at 0.25°, 0.5°, and 1°r esolutions compared to the 0.125°simulation are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/ rainfall partitioning because of scalability related to air temperature and surface elevation. Scalability of a topographic parameter used in runoff parameterization also contributes to improved scalability of the rain-driven saturated surface runoff component, particularly during winter. Hence, this study demonstrates the importance of spatial structure for multiscale modeling of hydrological processes.

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Section: 1002/2013jd020493mentioning

confidence: 99%

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

Tesfa

Leung

Huang

et al. 2014

J. Geophys. Res. Atmos.

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“…However, most modeling studies mainly focused on examining the effects of different spatial resolutions of input data on hydrologic model predictions (Wolock and Price, 1994;Haddeland et al, 2002;Sridhar et al, 2003;Boone et al, 2004;Cerdan et al, 2004), and on identifying a critical spatial resolution for optimal model predictions (Wood et al, 1988;Famiglietti and Wood, 1994;Bruneau et al, 1995;Woods et al, 1995;Liang et al, 2004;Shrestha et al, 2006). While these are important, given the significance of scalable modeling approaches for providing reliable hydrologic predictions under changing climate and environmental Koster et al (2000) and Goteti et al (2008), we implement another attempt on the use of subbasin-based representation in a land surface model and systematically compared it with the grid-based representation.…”

Section: T K Tesfa Et Al: a Subbasin-based Frameworkmentioning

confidence: 99%

A subbasin-based framework to represent land surface processes in an Earth system model

Tesfa

Leung

et al. 2014

Geosci. Model Dev.

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Abstract. Realistically representing spatial heterogeneity and lateral land surface processes within and between modeling units in Earth system models is important because of their implications to surface energy and water exchanges. The traditional approach of using regular grids as computational units in land surface models may lead to inadequate representation of subgrid heterogeneity and lateral movements of water, energy and carbon fluxes. Here a subbasin-based framework is introduced in the Community Land Model (CLM), which is the land component of the Community Earth System Model (CESM). Local processes are represented in each subbasin on a pseudo-grid matrix with no significant modifications to the existing CLM modeling structure. Lateral routing of water within and between subbasins is simulated with the subbasin version of a recently developed physically based routing model, Model for Scale Adaptive River Transport (MOSART). The framework is implemented in two topographically and climatically contrasting regions of the US: the Pacific Northwest and the Midwest. The relative merits of this modeling framework, with greater emphasis on scalability (i.e., ability to perform consistently across spatial resolutions) in streamflow simulation compared to the grid-based modeling framework are investigated by performing simulations at 0.125 • , 0.25 • , 0.5 • , and 1 • spatial resolutions. Comparison of the two frameworks at the finest spatial resolution showed that a small difference between the averaged forcing could lead to a larger difference in the simulated runoff and streamflow because of nonlinear processes. More systematic comparisons conducted using statistical metrics calculated between each coarse resolution and the corresponding 0.125 • -resolution simulations showed superior scalability in simulating both peak and mean streamflow for the subbasin based over the grid-based modeling framework. Scalability advantages are driven by a combination of improved consistency in runoff generation and the routing processes across spatial resolutions.

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“…However, the process of calibration is difficult and subjective [1]. This is partly as a result of modeling errors stemming from different sources such as: correctness and adequacy of the input data [2,3], the model's lack of accounting of relevant physical processes in the watershed [4,5], and also the experience of the modeler in manual calibration [6,7].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

Kamali

Abbaspour

Yang

2017

Water

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A large number of local and global databases for soil, land use, crops, and climate are now available from different sources, which often differ, even when addressing the same spatial and temporal resolutions. As the correct database is unknown, their impact on estimating water resource components (WRC) has mostly been ignored. Here, we study the uncertainty stemming from the use of multiple databases and their impacts on WRC estimates such as blue water and soil water for the Karkheh River Basin (KRB) in Iran. Four climate databases and two land use maps were used to build multiple configurations of the KRB model using the soil and water assessment tool (SWAT), which were similarly calibrated against monthly river discharges. We classified the configurations based on their calibration performances and estimated WRC for each one. The results showed significant differences in WRC estimates, even in models of the same class i.e., with similar performance after calibration. We concluded that a non-negligible level of uncertainty stems from the availability of different sources of input data. As the use of any one database among several produces questionable outputs, it is prudent for modelers to pay more attention to the selection of input data.

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Input data resolution analysis for distributed hydrological modeling

Cited by 56 publications

References 30 publications

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

A subbasin-based framework to represent land surface processes in an Earth system model

Assessing the Uncertainty of Multiple Input Datasets in the Prediction of Water Resource Components

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