scholarly journals Reconciling Simulated Moisture Fluxes Resulting from Alternate Hydrologic Model Time Steps and Energy Budget Closure Assumptions

2006 ◽  
Vol 7 (3) ◽  
pp. 355-370 ◽  
Author(s):  
Ingjerd Haddeland ◽  
Dennis P. Lettenmaier ◽  
Thomas Skaugen
Keyword(s):  
Energy Balance ◽  
Water Balance ◽  
Surface Temperature ◽  
Hydrologic Model ◽  
Model Parameters ◽  
Energy Balance Closure ◽  
Infiltration Capacity ◽  
Time Step ◽  
Effective Surface ◽  
Moisture Fluxes

Abstract Hydrological model predictions are sensitive to model forcings, input parameters, and the parameterizations of physical processes. Analyses performed for the Variable Infiltration Capacity model show that the resulting moisture fluxes are sensitive to the time step and energy balance closure assumptions. In addition, the model results are sensitive to the method of spatial and temporal disaggregation of precipitation. For parameter estimation purposes, it is desirable to do parameter searches in water balance mode (meaning that the effective surface temperature is assumed equal to the surface air temperature; hence no iteration for energy balance closure is performed) at daily time steps. However, transferring these parameters directly to other model modes (e.g., energy balance, in which an iteration for effective surface temperature is performed, and/or different model time steps) results in changes in the simulated moisture fluxes. The simulated differences in moisture fluxes are mainly a result of the parameterization of evapotranspiration at different time steps and model modes. A simple scheme that calculates correction factors for some model parameters is developed. The scheme is used to match simulated moisture fluxes in hourly and 3-hourly energy balance mode to the daily water balance simulation results, and to match hourly energy balance runs using spatially and temporally disaggregated precipitation to 3-hourly energy balance runs using uniformly disaggregated precipitation. For both approaches, the corrected simulations match the baseline simulations quite closely, both over transects across much of the continental United States and for test applications in the Ohio and Arkansas–Red River basins.

High-resolution pan-European multi-model simulations of hydrologic states and fluxes

2020 ◽  
Author(s):  
Bibi S Naz ◽  
Wendy Sharples ◽  
Klaus Goergen ◽  
Stefan Kollet
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Groundwater Flow ◽  
Hydrologic Model ◽  
Hydrological Processes ◽  
Model Parameters ◽  
Time Step ◽  
European Continent ◽  
Model Simulations ◽  
Community Land Model

<p> <span>High-resolution large-scale predictions of hydrologic states and fluxes are important for many regional-scale applications and water resource management. However, because of uncertainties related to forcing data, model structural errors arising from simplified representations of hydrological processes or uncertain model parameters, model simulations remain uncertain. To quantify this uncertainty, multi-model simulations were performed at 3km resolution over the European continent using the Community Land Model (CLM3.5) and the ParFlow hydrologic model. While Parflow uses a similar approach as CLM in simulating the snow, vegetation and land-atmosphere exchange processes, it simulates three-dimensional variably saturated groundwater flow solving Richards equation and overland flow with a two-dimensional kinematic wave approximation. </span><span>The </span><span>CLM</span><span>3.5</span><span> uses a simple groundwater model to account for groundwater recharge and discharge processes. Both models were driven with the COSMO-REA6 reanalysis dataset at 6km resolution for the time period from 2000 to 2006 at an hourly time step, and both used the same datasets for the static input variables (such as topography, vegetation and soil properties). The performance of both models was analyzed through comparisons with independent observations including satellite-derived and in-situ soil moisture, evapotranspiration, river discharge, water table depth and total water storage datasets. Overall, both models capture the interannual variability in the hydrologic states and fluxes well, however differences in performance between models showed the uncertainty associated with the representation of hydrological processes, such as groundwater flow and soil moisture and its control on latent and sensible heat fluxes at the surface.</span></p>

Scale analysis of evapotranspiration estimates from an energy-water balance model and remotely sensed LST

2021 ◽  
Author(s):  
Nicola Paciolla ◽  
Chiara Corbari ◽  
Giuseppe Ciraolo ◽  
Antonino Maltese ◽  
Marco Mancini
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Water Balance ◽  
Surface Temperature ◽  
Remotely Sensed ◽  
Water Balance Model ◽  
Balance Model ◽  
Source Surface ◽  
Scale Analysis ◽  
Energy Fluxes

<p>Remote Sensing (RS) information has progressively found, in recent years, more and more applications in hydrological modelling as a valuable tool for easy and frequent collection of geophysical data. However, this kind of data should be handled carefully, minding its characteristics, spatial resolution and the heterogeneity of the target area.</p><p>In this work, a scale analysis on evapotranspiration estimates over heterogeneous crops is performed combining a distributed energy-water balance model (FEST-EWB) and high-resolution remotely-sensed Land Surface Temperature (LST) and vegetation data.</p><p>The FEST-EWB model is calibrated on measured LST, based on a procedure where every single pixel is modified independently one from the other; hence in each pixel of the analysed domain the minimum of the pixel difference between modelled RET and satellite observed LST is searched over the period of calibration.</p><p>The case study is a Sicilian vineyard, with test dates in the summer of 2008. Meteorological and energy fluxes data are available from an eddy-covariance station, while LST and vegetation data are obtained from low-altitude flights at the high resolution of 1.7 metres.</p><p>After a preliminary calibration on LST data and validation on energy fluxes, the scale analysis is performed in two ways: model input aggregation and model output aggregation. Four coarser scales are selected in reference to some common satellite products resolution: 10.2 m (in reference to Sentinel’s 10 m), 30.6 m (Landsat, 30 m), 244.8 m (MODIS visible, 250 m) and 734.4 m (MODIS, 1000 m). First, modelled surface temperature and evapotranspiration are aggregated to each scale by progressive averaging. Then, model inputs are upscaled to the same spatial resolutions and the model is calibrated anew, obtaining independent results directly at the target scale.</p><p>The results of the two procedures are found to be quite similar, testifying to the capacity of the model to provide accurate products for a heterogeneous area even at low resolutions. The robustness of the analysis is strengthened by a further comparison with two well-established energy-balance algorithms: the one source Surface Energy Balance Algorithm for Land (SEBAL) and the Two-Source Energy Balance (TSEB) model.</p>

A Long-Term Land Surface Hydrologic Fluxes and States Dataset for China

2014 ◽  
Vol 15 (5) ◽  
pp. 2067-2084 ◽  
Author(s):  
Xue-Jun Zhang ◽  
Qiuhong Tang ◽  
Ming Pan ◽  
Yin Tang
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Snow Cover ◽  
Land Surface ◽  
Hydrologic Model ◽  
Reliable Estimate ◽  
Time Step ◽  
Snow Cover Extent ◽  
Monthly Streamflow

Abstract A long-term consistent and comprehensive dataset of land surface hydrologic fluxes and states will greatly benefit the analysis of land surface variables, their changes and interactions, and the assessment of land–atmosphere parameterizations for climate models. While some offline model studies can provide balanced water and energy budgets at land surface, few of them have presented an evaluation of the long-term interaction of water balance components over China. Here, a consistent and comprehensive land surface hydrologic fluxes and states dataset for China using the Variable Infiltration Capacity (VIC) hydrologic model driven by long-term gridded observation-based meteorological forcings is developed. The hydrologic dataset covers China with a 0.25° spatial resolution and a 3-hourly time step for 1952–2012. In the dataset, the simulated streamflow matches well with the observed monthly streamflow at the large river basins in China. Given the water balance scheme in the VIC model, the overall success at runoff simulations suggests that the long-term mean evapotranspiration is also realistically estimated. The simulated soil moisture generally reproduces the seasonal variation of the observed soil moisture at the ground stations where long-term observations are available. The modeled snow cover patterns and monthly dynamics bear an overall resemblance to the Northern Hemisphere snow cover extent data from the National Snow and Ice Data Center. Compared with global product of a similar nature, the dataset can provide a more reliable estimate of land surface variables over China. The dataset, which will be publicly available via the Internet, may be useful for hydroclimatological studies in China.

scholarly journals Benchmarking of a Physically Based Hydrologic Model

2017 ◽  
Vol 18 (8) ◽  
pp. 2215-2225 ◽  
Author(s):  
Andrew J. Newman ◽  
Naoki Mizukami ◽  
Martyn P. Clark ◽  
Andrew W. Wood ◽  
Bart Nijssen ◽  
...  
Keyword(s):  
Land Surface ◽  
Model Performance ◽  
Hydrologic Model ◽  
Complex Model ◽  
Model Parameters ◽  
Infiltration Capacity ◽  
Large Sample ◽  
Variable Infiltration Capacity Model ◽  
Capacity Model ◽  
Physically Based

Abstract The concepts of model benchmarking, model agility, and large-sample hydrology are becoming more prevalent in hydrologic and land surface modeling. As modeling systems become more sophisticated, these concepts have the ability to help improve modeling capabilities and understanding. In this paper, their utility is demonstrated with an application of the physically based Variable Infiltration Capacity model (VIC). The authors implement VIC for a sample of 531 basins across the contiguous United States, incrementally increase model agility, and perform comparisons to a benchmark. The use of a large-sample set allows for statistically robust comparisons and subcategorization across hydroclimate conditions. Our benchmark is a calibrated, time-stepping, conceptual hydrologic model. This model is constrained by physical relationships such as the water balance, and it complements purely statistical benchmarks due to the increased physical realism and permits physically motivated benchmarking using metrics that relate one variable to another (e.g., runoff ratio). The authors find that increasing model agility along the parameter dimension, as measured by the number of model parameters available for calibration, does increase model performance for calibration and validation periods relative to less agile implementations. However, as agility increases, transferability decreases, even for a complex model such as VIC. The benchmark outperforms VIC in even the most agile case when evaluated across the entire basin set. However, VIC meets or exceeds benchmark performance in basins with high runoff ratios (greater than ~0.8), highlighting the ability of large-sample comparative hydrology to identify hydroclimatic performance variations.

scholarly journals At which timescale does the complementary principle perform best in evaporation estimation?

2021 ◽  
Vol 25 (1) ◽  
pp. 375-386
Author(s):  
Liming Wang ◽  
Songjun Han ◽  
Fuqiang Tian
Keyword(s):  
Energy Balance ◽  
Uncertainty Analysis ◽  
Eddy Covariance ◽  
Energy Balance Closure ◽  
Time Step ◽  
Multiple Timescales ◽  
Monthly Scale ◽  
Independent Variable ◽  
Closure Method

Abstract. The complementary principle has been widely used to estimate evaporation under different conditions. However, it remains unclear at which timescale the complementary principle performs best. In this study, evaporation estimations were conducted at 88 eddy covariance (EC) monitoring sites at multiple timescales (daily, weekly, monthly, and yearly) by using sigmoid and polynomial generalized complementary functions. The results indicate that the generalized complementary functions exhibit the highest skill in estimating evaporation at the monthly scale. The uncertainty analysis shows that this conclusion is not affected by ecosystem type or energy balance closure method. Through comparisons at multiple timescales, we found that the slight difference between the two generalized complementary functions only exists when the independent variable (x) in the functions approaches 1. The results differ for the two models at daily and weekly scales. However, such differences vanish at monthly and annual timescales, with few high x values occurring. This study demonstrates the applicability of generalized complementary functions across multiple timescales and provides a reference for choosing a suitable time step for evaporation estimations in relevant studies.

scholarly journals A weather dependent approach to estimate the annual course of vegetation parameters for water balance simulations on the meso- and macroscale

2012 ◽  
Vol 32 ◽  
pp. 15-21 ◽  
Author(s):  
K. Förster ◽  
M. Gelleszun ◽  
G. Meon
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Hydrologic Model ◽  
Climate Change Scenarios ◽  
Time Step ◽  
Area Index ◽  
Vegetation Height ◽  
Current Climate ◽  
Vegetation Parameters

Abstract. In order to simulate long-term water balances hydrologic models have to be parameterized for several types of vegetation. Furthermore, a seasonal dependence of vegetation parameters has to be accomplished for a successful application. Many approaches neglect inter-annual variability and shifts due to climate change. In this paper a more comprehensive approach from literature was evaluated and applied to long-term water balance simulations, which incorporates temperature, humidity and maximum bright sunshine hours per day to calculate a growing season index (GSI). A validation of this threshold-related approach is carried out by comparisons with normalized difference vegetation index (NDVI) data and observations from the phenological network in the state of Lower Saxony. The annual courses of GSI and NDVI show a good agreement for numerous sites. A comparison with long-term observations of leaf onset and offset taken from the phenological network also revealed a good model performance. The observed trends indicating a shift toward an earlier leaf onset of 3 days per decade in the lowlands were reproduced very well. The GSI approach was implemented in the hydrologic model Panta Rhei. For the common vegetation parameters like leaf area index, vegetated fraction, albedo and the vegetation height a minimum value and a maximum value were defined for each land surface class. These parameters were scaled with the computed GSI for every time step to obtain a seasonal course for each parameter. Two simulations were carried out each for the current climate and for future climate scenarios. The first run was parameterized with a static annual course of vegetation parameters. The second run incorporates the new GSI approach. For the current climate both models produced comparable results regarding the water balance. Although there are no significant changes in modeled mean annual evapotranspiration and runoff depth in climate change scenarios, mean monthly values of these water balance components are shifted toward a lower runoff in spring and higher values during the winter months.

scholarly journals Multi-objective regionalisation for lake level simulation, the case of Lake Tana in the Upper Blue Nile, Ethiopia

2010 ◽  
Vol 7 (5) ◽  
pp. 7341-7381
Author(s):  
T. H. M. Rientjes ◽  
B. U. J. Perera ◽  
A. T. Haile ◽  
P. Reggiani
Keyword(s):  
Water Balance ◽  
Lake Level ◽  
Ad Hoc ◽  
Relative Volume ◽  
Model Parameters ◽  
Lake Levels ◽  
Ungauged Catchments ◽  
Time Step ◽  
Lake Tana ◽  
Multi Objective

Abstract. The aim in this study is to simulate lake levels of Lake Tana by solving the water balance at daily time step. Since 42% of the basin is ungauged regionalisation procedures are applied. We examine the predictive capability of a regionalisation approach that combines multi-objective calibration of a simple conceptual model and multi regression analyses to establish relations between model parameters and catchment characteristics. Recently few studies are presented on lake level simulation of Lake Tana. In these studies the water balance of the lake is closed by estimation of runoff contributions from ungauged catchments. Studies partly relied on simple ad-hoc procedures of area comparison to estimate runoff from ungauged catchments. In this study a regional model is developed that relies on principles of similarity of catchments. For runoff modelling the HVB-96 model is selected while multi-objective model calibration is by a Monte Carlo procedure. Assessment of the lake water balance was established by comparing measured to estimated lake levels. Results of daily lake level simulation show a water balance closure term of 85 mm and a relative volume error of 2.17%. Results show runoff from ungauged catchments of 527 mm per year for the simulation period 1994 to 2003 that is approximately 30% of Lake Tana stream flow inflow. Compared to previous works this closure term is smallest.

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