Effect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model

Minet, Julien; Laloy, Eric; Lambot, Sébastien; Vanclooster, Marnik

doi:10.5194/hess-15-1323-2011

Cited by 37 publications

(31 citation statements)

References 51 publications

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“…In this study, we transferred parameters based on the partitioning of climate types, as set out in Table 1. However, the spatial variation of soil moisture is large (Liu et al, 2001;Minet et al, 2011) and it is sensitive to precipitation (P ), radiation and temperature; in other words, it is related to P and evapotranspiration (P -ET), but it is not merely equal to P -ET multiplied by a simple scale factor because it is also closely related to the soil processes, vegetation processes and other input information that can be manipulated by CLM3.5. As an example, Fig.…”

Section: Discussionmentioning

confidence: 99%

“…This model is a modified version of CLM3.0 (Oleson et al, 2004), and has significantly improved the simulation of many variables in the hydrological cycle and the spatial distribution of vegetation. A new surface dataset was introduced to improve land surface representation and improve the simulation of surface albedo, near-surface temperature and precipitation (Lawrence and Chase, 2007).…”

Section: Land Surface Model Clm35mentioning

confidence: 99%

“…A detailed description of the physical processes, modification and performance of CLM3.5 was given in Oleson et al (2004Oleson et al ( , 2008 and .…”

Section: Land Surface Model Clm35mentioning

confidence: 99%

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Improving simulation of soil moisture in China using a multiple meteorological forcing ensemble approach

Liu

Xie

2013

Hydrol. Earth Syst. Sci.

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Abstract. The quality of soil-moisture simulation using land surface models depends largely on the accuracy of the meteorological forcing data. We investigated how to reduce the uncertainty arising from meteorological forcings in a simulation by adopting a multiple meteorological forcing ensemble approach. Simulations by the Community Land Model version 3.5 (CLM3.5) over mainland China were conducted using four different meteorological forcings, and the four sets of soil-moisture data related to the simulations were then merged using simple arithmetical averaging and Bayesian model averaging (BMA) ensemble approaches. BMA is a statistical post-processing procedure for producing calibrated and sharp predictive probability density functions (PDFs), which is a weighted average of PDFs centered on the biascorrected forecasts from a set of individual ensemble members based on their probabilistic likelihood measures. Compared to in situ observations, the four simulations captured the spatial and seasonal variations of soil moisture in most cases with some mean bias. They performed differently when simulating the seasonal phases in the annual cycle, the interannual variation and the magnitude of observed soil moisture over different subregions of mainland China, but no individual meteorological forcing performed best for all subregions. The simple arithmetical average ensemble product outperformed most, but not all, individual members over most of the subregions. The BMA ensemble product performed better than simple arithmetical averaging, and performed best for all fields over most of the subregions. The BMA ensemble approach applied to the ensemble simulation reproduced anomalies and seasonal variations in observed soil-moisture values, and simulated the mean soil moisture. It is presented here as a promising way for reproducing long-term, highresolution spatial and temporal soil-moisture data.

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Section: Discussionmentioning

confidence: 99%

Section: Land Surface Model Clm35mentioning

confidence: 99%

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Improving simulation of soil moisture in China using a multiple meteorological forcing ensemble approach

Liu

Xie

2013

Hydrol. Earth Syst. Sci.

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“…The percentage change of daily values of total soil moisture was calculated by Equation (4). (4) where PC, Dn,i and Dn+1,i are the percentage change, the total soil moisture at day i of year n and n+1, respectively.…”

Section: Definition Of Model Spin-up Timementioning

confidence: 99%

“…Even a single model could produce diverse outputs and achieve different accuracies due to variations in calibrations. A great deal of the literature discusses the effect of model initial conditions to its outputs [1][2][3][4][5][6][7]. These studies highlighted the complex interaction among soil moisture initial conditions, climatic factors and soil properties.…”

Section: Introductionmentioning

confidence: 99%

Model Spin-Up Behavior for Wet and Dry Basins: A Case Study Using the Xinanjiang Model

Rahman

2015

Water

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Model spin-up is an adjustment process where its internal stores move from an initial state of unusual conditions to one of equilibrium. Model outputs during this spin-up process are often unrealistic and misleading. This study investigates some primary factors affecting spin-up time using the Xinanjiang model for 22 river basins throughout the United States. A 10-year recursive simulation with three data sets indicates that time required for model equilibrium is not only a function of initial conditions, but also is affected by input data sets (precipitation and evaporation). The model requires less time to be equilibrated under wetter initial conditions (lowest under saturated initial condition). Moreover, model spin-up time shows distinct variations with the dryness of the input data sets. Analysis suggests that wet basins (ratio of evaporation over precipitation <0.9) require less time (55 days) for model equilibrium in comparison to that of dry basins (298 days). The spin-up time displayed an exponential relationship with the basin aridity index (r 2 = 0.85). This relationship could provide a way to predict the maximum model spin-up time using the precipitation and evaporation information only. Predicting maximum model spin-up time based on this relationship could be valuable to reduce uncertainty, particularly under data scarce situations.

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Spin‐up behavior and effects of initial conditions for an integrated hydrologic model

Seck

Welty

Maxwell

2015

Water Resources Research

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Initial conditions have been shown to have a strong effect on outputs of surface water models, but their impact on integrated hydrologic models is not well documented. We investigated the effects of initial conditions on an integrated hydrologic model of a 5632 km 2 domain in the northeastern U.S. Simulations were run for the year 1980 using four initial conditions spanning a range of average depth to water table, including 1 m (''wet''), 3m, 5m, and 7 m (''dry'') below land surface. Model outputs showed significant effects of initial conditions on basin-averaged variables such as subsurface storage, surface storage, and surface runoff, with the greatest impact observed on surface storage and runoff. Effects of initial conditions were related to meteorological conditions, with precipitation reducing the effects of initial conditions on surface storage and runoff. Additionally, feedbacks between soil moisture and land-energy fluxes affected the impacts of initial conditions: higher temperatures magnified the differences in storage, recharge, and discharge among the four initial-condition scenarios. Ten year recursive runs were conducted for the wet and dry scenarios. Spin-up times varied by model components and were considerably smaller for landsurface states and fluxes. Spin-up for dry initial conditions was slower than for wet initial conditions, indicating longer system memory for dry initial conditions. These variations in persistence of initial conditions should be taken into consideration when designing model initialization approaches. More broadly, this behavior is indicative of increased persistence of the effects of dry years as opposed to wet years in hydrologic systems.

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Effect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model

Cited by 37 publications

References 51 publications

Improving simulation of soil moisture in China using a multiple meteorological forcing ensemble approach

Improving simulation of soil moisture in China using a multiple meteorological forcing ensemble approach

Model Spin-Up Behavior for Wet and Dry Basins: A Case Study Using the Xinanjiang Model

Spin‐up behavior and effects of initial conditions for an integrated hydrologic model

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