Regional Parameter Estimation of the VIC Land Surface Model: Methodology and Application to River Basins in China

2007 ◽  
Vol 8 (3) ◽  
pp. 447-468 ◽  
Author(s):  
Zhenghui Xie ◽  
Fei Yuan ◽  
Qingyun Duan ◽  
Jing Zheng ◽  
Miaoling Liang ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
River Basin ◽  
Land Surface ◽  
Land Surface Model ◽  
River Basins ◽  
Large River ◽  
Surface Model ◽  
Parameter Estimates ◽  
Climatic Zones ◽  
Streamflow Simulation

Abstract This paper presents a methodology for regional parameter estimation of the three-layer Variable Infiltration Capacity (VIC-3L) land surface model with the goal of improving the streamflow simulation for river basins in China. This methodology is designed to obtain model parameter estimates from a limited number of calibrated basins and then regionalize them to uncalibrated basins based on climate characteristics and large river basin domains, and ultimately to continental China. Fourteen basins from different climatic zones and large river basins were chosen for model calibration. For each of these basins, seven runoff-related model parameters were calibrated using a systematic manual calibration approach. These calibrated parameters were then transferred within the climate and large river basin zones or climatic zones to the uncalibrated basins. To test the efficiency of the parameter regionalization method, a verification study was conducted on 19 independent river basins in China. Overall, the regionalized parameters, when evaluated against the a priori parameter estimates, were able to reduce the model bias by 0.4%–249.8% and relative root-mean-squared error by 0.2%–119.1% and increase the Nash–Sutcliffe efficiency of the streamflow simulation by 1.9%–31.7% for most of the tested basins. The transferred parameters were then used to perform a hydrological simulation over all of China so as to test the applicability of the regionalized parameters on a continental scale. The continental simulation results agree well with the observations at regional scales, indicating that the tested regionalization method is a promising scheme for parameter estimation for ungauged basins in China.

scholarly journals Hydrological recurrence as a measure for large river basin classification and process understanding

2014 ◽  
Vol 11 (7) ◽  
pp. 8191-8238 ◽  
Author(s):  
R. Fernandez ◽  
T. Sayama
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Fourier Transforms ◽  
Land Surface Model ◽  
Arctic Region ◽  
River Basins ◽  
Large River ◽  
Global Scale ◽  
Surface Model ◽  
Monsoon Area

Abstract. Hydrologic functions of river basins are summarized as water collection, storage and discharge, which can be characterized by the dynamics of hydrological variables including precipitation, evaporation, storage and runoff. In some situations these four variables behave more in a recurrent manner by repeating in a similar range year after year or in other situations they exhibit more randomness with higher variations year by year. The degree of recurrence in runoff is important not only for water resources management but also for hydrologic process understandings, especially in terms of how the other three variables determine the degree of recurrence in runoff. The main objective of this paper is to propose a simple hydrologic classification framework applicable to global scale and large basins based on the combinations of recurrence in the four variables. We evaluate it by Lagged Autocorrelation, Fast Fourier Transforms and Colwell's Indices of variables obtained from EU-WATCH dataset composed by eight hydrologic and land surface model outputs. By setting a threshold to define high or low recurrence in the four variables, we classify each river basin into 16 possible classes. The overview of recurrence patterns at global scale suggested that precipitation is recurrent mainly in the humid tropics, Asian Monsoon area and part of higher latitudes with oceanic influence. Recurrence in evaporation was mainly dependent on the seasonality of energy availability, typically high in the tropics, temperate and subarctic regions. Recurrence in storage at higher latitudes depends on energy/water balances and snow, while that in runoff is mostly affected by the different combinations of these three variables. According to the river basin classification 10 out of the 16 possible classes were present in the 35 largest river basins in the world. In humid tropic region, the basins belong to a class with high recurrence in all the variables, while in subtropical region many of the river basins have low recurrence. In temperate region, the energy limited or water limited in summer characterizes the recurrence in storage, but runoff exhibits generally low recurrence due to the low recurrence in precipitation. In the subarctic and arctic region, the amount of snow also influences the classes; more snow yields higher recurrence in storage and runoff. Our proposed framework follows a simple methodology that can aid in grouping river basins with similar characteristics of water, energy and storage cycles. The framework is applicable at different scales with different datasets to provide useful insights into the understanding of hydrologic regimes based on the classification.

scholarly journals Satellite-Based Evapotranspiration in Hydrological Model Calibration

2020 ◽  
Vol 12 (3) ◽  
pp. 428 ◽  
Author(s):  
Lulu Jiang ◽  
Huan Wu ◽  
Jing Tao ◽  
John S. Kimball ◽  
Lorenzo Alfieri ◽  
...  
Keyword(s):  
Land Surface ◽  
Model Calibration ◽  
Hydrological Model ◽  
Land Surface Model ◽  
River Basins ◽  
Global Scale ◽  
Surface Model ◽  
Model Parameters ◽  
Spatially Distributed ◽  
Streamflow Simulation

Hydrological models are usually calibrated against observed streamflow (Qobs), which is not applicable for ungauged river basins. A few studies have exploited remotely sensed evapotranspiration (ETRS) for model calibration but their effectiveness on streamflow simulation remains uncertain. This paper investigates the use of ETRS in the hydrological calibration of a widely used land surface model coupled with a source–sink routing scheme and global optimization algorithm for 28 natural river basins. A baseline simulation is a setup based on the latest model developments and inputs. Sensitive parameters are determined for Qobs and ETRS-based model calibrations, respectively, through comprehensive sensitivity tests. The ETRS-based model calibration results in a mean Kling–Gupta Efficiency (KGE) value of 0.54 for streamflow simulation; 61% of the river basins have KGE > 0.5 in the validation period, which is consistent with the calibration period and provides a significant improvement over the baseline. Compared to Qobs, the ETRS calibration produces better or similar streamflow simulations in 29% of the basins, while further significant improvements are achieved when either better ET or precipitation observations are used. Furthermore, the model results show better or similar performance in 68% of the basins and outperform the baseline simulations in 90% of the river basins using model parameters from the best ETRS calibration runs. This study confirms that with reasonable precipitation input, the ETRS-based spatially distributed calibration can efficiently tune parameters for better ET and streamflow simulations. The application of ETRS for global scale hydrological model calibration promises even better streamflow accuracy as the satellite-based ETRS observations continue to improve.

scholarly journals Evaluating terrestrial CO<sub>2</sub> flux diagnoses and uncertainties from a simple land surface model and its residuals

2014 ◽  
Vol 11 (2) ◽  
pp. 217-235 ◽  
Author(s):  
T. W. Hilton ◽  
K. J. Davis ◽  
K. Keller
Keyword(s):  
Carbon Dioxide ◽  
Parameter Estimation ◽  
North American ◽  
Land Surface ◽  
Atmospheric Carbon Dioxide ◽  
Ecosystem Respiration ◽  
Land Surface Model ◽  
Net Ecosystem Exchange ◽  
Surface Model ◽  
Considerable Uncertainty

Abstract. Global terrestrial atmosphere–ecosystem carbon dioxide fluxes are well constrained by the concentration and isotopic composition of atmospheric carbon dioxide. In contrast, considerable uncertainty persists surrounding regional contributions to the net global flux as well as the impacts of atmospheric and biological processes that drive the net flux. These uncertainties severely limit our ability to make confident predictions of future terrestrial biological carbon fluxes. Here we use a simple light-use efficiency land surface model (the Vegetation Photosynthesis Respiration Model, VPRM) driven by remotely sensed temperature, moisture, and phenology to diagnose North American gross ecosystem exchange (GEE), ecosystem respiration, and net ecosystem exchange (NEE) for the period 2001 to 2006. We optimize VPRM parameters to eddy covariance (EC) NEE observations from 65 North American FluxNet sites. We use a separate set of 27 cross-validation FluxNet sites to evaluate a range of spatial and temporal resolutions for parameter estimation. With these results we demonstrate that different spatial and temporal groupings of EC sites for parameter estimation achieve similar sum of squared residuals values through radically different spatial patterns of NEE. We also derive a regression model to estimate observed VPRM errors as a function of VPRM NEE, temperature, and precipitation. Because this estimate is based on model-observation residuals it is comprehensive of all the error sources present in modeled fluxes. We find that 1 km interannual variability in VPRM NEE is of similar magnitude to estimated 1 km VPRM NEE errors.

scholarly journals Evaluating Multiple WRF Configurations and Forcing over the Northern Patagonian Icecap (NPI) and Baker River Basin

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 815
Author(s):  
Marcelo Somos-Valenzuela ◽  
Francisco Manquehual-Cheuque
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Weather Prediction ◽  
Wrf Model ◽  
Land Surface Model ◽  
Short Wave ◽  
Reanalysis Data ◽  
Wave Radiation ◽  
Surface Model ◽  
Nwp Model

The use of numerical weather prediction (NWP) model to dynamically downscale coarse climate reanalysis data allows for the capture of processes that are influenced by land cover and topographic features. Climate reanalysis downscaling is useful for hydrology modeling, where catchment processes happen on a spatial scale that is not represented in reanalysis models. Selecting proper parameterization in the NWP for downscaling is crucial to downscale the climate variables of interest. In this work, we are interested in identifying at least one combination of physics in the Weather Research Forecast (WRF) model that performs well in our area of study that covers the Baker River Basin and the Northern Patagonian Icecap (NPI) in the south of Chile. We used ERA-Interim reanalysis data to run WRF in twenty-four different combinations of physics for three years in a nested domain of 22.5 and 4.5 km with 34 vertical levels. From more to less confident, we found that, for the planetary boundary layer (PBL), the best option is to use YSU; for the land surface model (LSM), the best option is the five-Layer Thermal, RRTM for longwave, Dudhia for short wave radiation, and Thompson for the microphysics. In general, the model did well for temperature (average, minimum, maximum) for most of the observation points and configurations. Precipitation was good, but just a few configurations stood out (i.e., conf-9 and conf-10). Surface pressure and Relative Humidity results were not good or bad, and it depends on the statistics with which we evaluate the time series (i.e., KGE or NSE). The results for wind speed were inferior; there was a warm bias in all of the stations. Once we identify the best configuration in our experiment, we run WRF for one year using ERA5 and FNL0832 climate reanalysis. Our results indicate that Era-interim provided better results for precipitation. In the case of temperature, FNL0832 gave better results; however, all of the models’ performances were good. Therefore, working with ERA-Interim seems the best option in this region with the physics selected. We did not experiment with changes in resolution, which may have improved results with ERA5 that has a better spatial and temporal resolution.

scholarly journals River basin hydrology in a global off-line land-surface model

1999 ◽  
Vol 104 (D16) ◽  
pp. 19661-19673 ◽  
Author(s):  
Michael G. Bosilovich ◽  
Runhua Yang ◽  
Paul R. Houser
Keyword(s):  
River Basin ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Basin Hydrology

scholarly journals River Network Routing on the NHDPlus Dataset

2011 ◽  
Vol 12 (5) ◽  
pp. 913-934 ◽  
Author(s):  
Cédric H. David ◽  
David R. Maidment ◽  
Guo-Yue Niu ◽  
Zong-Liang Yang ◽  
Florence Habets ◽  
...  
Keyword(s):  
Information System ◽  
Mississippi River ◽  
Land Surface ◽  
River Flow ◽  
Land Surface Model ◽  
River Basins ◽  
Network Routing ◽  
River Network ◽  
Surface Model ◽  
Muskingum Method

Abstract The mapped rivers and streams of the contiguous United States are available in a geographic information system (GIS) dataset called National Hydrography Dataset Plus (NHDPlus). This hydrographic dataset has about 3 million river and water body reaches along with information on how they are connected into networks. The U.S. Geological Survey (USGS) National Water Information System (NWIS) provides streamflow observations at about 20 thousand gauges located on the NHDPlus river network. A river network model called Routing Application for Parallel Computation of Discharge (RAPID) is developed for the NHDPlus river network whose lateral inflow to the river network is calculated by a land surface model. A matrix-based version of the Muskingum method is developed herein, which RAPID uses to calculate flow and volume of water in all reaches of a river network with many thousands of reaches, including at ungauged locations. Gauges situated across river basins (not only at basin outlets) are used to automatically optimize the Muskingum parameters and to assess river flow computations, hence allowing the diagnosis of runoff computations provided by land surface models. RAPID is applied to the Guadalupe and San Antonio River basins in Texas, where flow wave celerities are estimated at multiple locations using 15-min data and can be reproduced reasonably with RAPID. This river model can be adapted for parallel computing and although the matrix method initially adds a large overhead, river flow results can be obtained faster than with the traditional Muskingum method when using a few processing cores, as demonstrated in a synthetic study using the upper Mississippi River basin.

scholarly journals Baseline evaluation of the impact of updates to the MIT Earth System Model on its model parameter estimates

2018 ◽  
Vol 11 (8) ◽  
pp. 3313-3325 ◽  
Author(s):  
Alex G. Libardoni ◽  
Chris E. Forest ◽  
Andrei P. Sokolov ◽  
Erwan Monier
Keyword(s):  
Land Surface ◽  
Probability Distributions ◽  
Land Surface Model ◽  
Response Surfaces ◽  
Surface Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Ocean Heat Uptake ◽  
Aerosol Forcing ◽  
Baseline Evaluation

Abstract. For over 20 years, the Massachusetts Institute of Technology Earth System Model (MESM) has been used extensively for climate change research. The model is under continuous development with components being added and updated. To provide transparency in the model development, we perform a baseline evaluation by comparing model behavior and properties in the newest version to the previous model version. In particular, changes resulting from updates to the land surface model component and the input forcings used in historical simulations of climate change are investigated. We run an 1800-member ensemble of MESM historical climate simulations where the model parameters that set climate sensitivity, the rate of ocean heat uptake, and the net anthropogenic aerosol forcing are systematically varied. By comparing model output to observed patterns of surface temperature changes and the linear trend in the increase in ocean heat content, we derive probability distributions for the three model parameters. Furthermore, we run a 372-member ensemble of transient climate simulations where all model forcings are fixed and carbon dioxide concentrations are increased at the rate of 1 % year−1. From these runs, we derive response surfaces for transient climate response and thermosteric sea level rise as a function of climate sensitivity and ocean heat uptake. We show that the probability distributions shift towards higher climate sensitivities and weaker aerosol forcing when using the new model and that the climate response surfaces are relatively unchanged between model versions. Because the response surfaces are independent of the changes to the model forcings and similar between model versions with different land surface models, we suggest that the change in land surface model has limited impact on the temperature evolution in the model. Thus, we attribute the shifts in parameter estimates to the updated model forcings.

scholarly journals Simulating Flash Floods Using Geostationary Satellite-Based Rainfall Estimation Coupled with a Land Surface Model

Hydrology ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 9 ◽  
Author(s):  
Dwi Prabowo Yuga Suseno ◽  
Tomohito J. Yamada
Keyword(s):  
Spatial Distribution ◽  
River Basin ◽  
Land Surface ◽  
River Flow ◽  
Flash Flood ◽  
Land Surface Model ◽  
Flash Floods ◽  
Flood Mitigation ◽  
Surface Model ◽  
Flow Simulations

Clarifying hydrologic behavior, especially behavior related to extreme events such as flash floods, is vital for flood mitigation and management. However, discharge and rainfall measurement data are scarce, which is a major obstacle to flood mitigation. This study: (i) simulated flash floods on a regional scale using three types of rainfall forcing implemented in a land surface model; and (ii) evaluated and compared simulated flash floods with the observed discharge. The three types of rainfall forcing were those observed by the Automated Meteorological Data Acquisition System (AMeDAS) (Simulation I), the observed rainfall from the Ministry of Land, Infrastructure and Transportation (MLIT) (Simulation II), and the estimated rainfall from the Multi-purpose Transport Satellite (MTSAT), which was downscaled by AMeDAS rainfall (Simulation III). MLIT rainfall observations have a denser station network over the Ishikari River basin (spacing of approximately 10 km) compared with AMeDAS (spacing of approximately 20 km), so they are expected to capture the rainfall spatial distribution more accurately. A land surface model, the Minimal Advance Treatments of Surface Interaction and Runoff (MATSIRO), was implemented for the flash flood simulation. The river flow simulations were run over the Ishikari river basin at a 1-km grid resolution and a 1-h temporal resolution during August 2010. The statistical performance of the river flow simulations during a flash flood event on 23 and 24 August 2010 demonstrated that Simulation I was reasonable compared with Simulation III. The findings also suggest that the advantages of the MTSAT-based estimated rainfall (i.e., good spatial distribution) can be coupled with the benefit of direct AMeDAS observations (i.e., representation of the true rainfall).

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