Modeling the Hydrological Effect on Local Gravity at Moxa, Germany

2006 ◽  
Vol 7 (3) ◽  
pp. 346-354 ◽  
Author(s):  
Shaakeel Hasan ◽  
Peter A. Troch ◽  
J. Boll ◽  
C. Kroner
Keyword(s):  
Transfer Function ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Water Storage ◽  
Superconducting Gravimeter ◽  
Hydrological Processes ◽  
Earth Tides ◽  
Time Averaging ◽  
Distributed Hydrological Model ◽  
High Positive Correlation

Abstract A superconducting gravimeter has observed with high accuracy (to within a few nm s−2) and high frequency (1 Hz) the temporal variations in the earth’s gravity field near Moxa, Germany, since 1999. Hourly gravity residuals are obtained by time averaging and correcting for earth tides, polar motion, barometric pressure variations, and instrumental drift. These gravity residuals are significantly affected by hydrological processes (interception, infiltration, surface runoff, and subsurface redistribution) in the vicinity of the observatory. In this study time series analysis and distributed hydrological modeling techniques are applied to understand the effect of these hydrological processes on observed gravity residuals. It is shown that the short-term response of gravity residuals to medium- to high-rainfall events can be efficiently modeled by means of a linear transfer function. This transfer function exhibits an oscillatory behavior that indicates fast redistribution of stored water in the upper layers (interception store, root zone) of the catchment surrounding the instrument. The relation between groundwater storage and gravity residuals is less clear and varies according to the season. High positive correlation between groundwater and gravity exists during winter months when the freezing of the upper soil layers immobilizes water stored in the unsaturated zone of the catchment. To further explore the spatiotemporal dynamics of the relevant hydrological processes and their relation to observed gravity residuals, a GIS-based distributed hydrological model is applied for the Silberleite catchment. Driven by observed atmospheric forcings (precipitation and potential evapotranspiration), the model allows the authors to compute the variation of water storage in three different layers: the interception store, the snow cover store, and the soil moisture store. These water storage dynamics are then converted to predicted gravity variation at the location of the superconducting gravimeter and compared to observed gravity residuals. During most of the investigated period (January 2000 to January 2004) predictions are in good agreement with the observed patterns of gravity dynamics. However, during some winter months the distributed hydrological model fails to explain the observations, which supports the authors’ conclusion that groundwater variability dominates the hydrological gravity signal in the winter. More hydrogeological research is needed to include groundwater dynamics in the hydrological model.

scholarly journals Diagnostic calibration of a hydrological model in an alpine area

2014 ◽  
Vol 11 (1) ◽  
pp. 1253-1300 ◽  
Author(s):  
Z. He ◽  
F. Tian ◽  
H. C. Hu ◽  
H. V. Gupta ◽  
H. P. Hu
Keyword(s):  
Hydrological Modeling ◽  
Hydrological Model ◽  
Generation Mechanism ◽  
Spatiotemporal Variability ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Runoff Generation ◽  
Alpine Area ◽  
Long Time ◽  
Tailan River Basin

Abstract. Hydrological modeling depends on single- or multiple-objective strategies for parameter calibration using long time sequences of observed streamflow. Here, we demonstrate a diagnostic approach to the calibration of a hydrological model of an alpine area in which we partition the hydrograph based on the dominant runoff generation mechanism (groundwater baseflow, glacier melt, snowmelt, and direct runoff). The partitioning reflects the spatiotemporal variability in snowpack, glaciers, and temperature. Model parameters are grouped by runoff generation mechanism, and each group is calibrated separately via a stepwise approach. This strategy helps to reduce the problem of equifinality and, hence, model uncertainty. We demonstrate the method for the Tailan River basin (1324 km2) in the Tianshan Mountains of China with the help of a semi-distributed hydrological model (THREW).

Combined integrated hydrological modeling and particle tracking algorithms to infer the temporal variability of transit and residence time distributions within the Strengbach catchment (Vosges mountains, France)

2020 ◽  
Author(s):  
Sylvain Weill ◽  
Nolwenn Lesparre ◽  
Benjamin Jeannot ◽  
Frederick Delay
Keyword(s):  
Transit Time ◽  
Residence Time ◽  
Particle Tracking ◽  
Temporal Variability ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Water Storage ◽  
Tracking Algorithms ◽  
Residence Time Distributions ◽  
Strengbach Catchment

<p>The temporal variability of transit-time distributions (TTDs) and residence-time distributions (RTDs) in hydrological systems has received particular attention recently because of their ability to inform on elementary processes impacting geochemical signatures and water fluxes in ecosystems. To date, these distributions and their temporal variability have been mainly investigated through concentration measurements of conservative geochemical or isotopic tracers. Even though physically-based and distributed hydrological models can render interpretations of TTDs/RTDs in terms of processes and physical controls, the variability of TTDs and RTDs has barely been studied using distributed hydrological modeling. In this study, an integrated hydrological model has been coupled with particle tracking algorithms and applied to the Strengbach Catchment – a small mountainous catchment belonging to the French network of critical zone observatories – to investigate the eventual link between water storage in the catchment and the temporal variability of TTDs and RTDs. The model calibration is performed relying upon both classical streamflow measurements and magnetic resonance sounding, a geophysical measure sensible to the water content in the subsurface. The model is then run over a 10-year period for which time distributions are calculated at various deadlines. The results show that the response of the Strengbach catchment is uncommon with short mean transit times (approximately 150-200 days) and a weak variability of TTDs and RTDs with the water storage. This specific behavior is mainly linked to the small size of the system and specific climatic and topographic conditions. Because the hydrological model was calibrated on the basis of unusual data (local water contents inferred via MRS measurements), ongoing investigations target the evaluation of the sensitivity of transit time distributions with respect to uncertainties plaguing calibrating data.</p>

scholarly journals Informing a hydrological model of the Ogooué with multi-mission remote sensing data

2018 ◽  
Vol 22 (2) ◽  
pp. 1453-1472 ◽  
Author(s):  
Cecile M. M. Kittel ◽  
Karina Nielsen ◽  
Christian Tøttrup ◽  
Peter Bauer-Gottwein
Keyword(s):  
Remote Sensing ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Water Storage ◽  
Total Water ◽  
Support Tool ◽  
River Stage ◽  
Satellite Missions ◽  
Storage Change

Abstract. Remote sensing provides a unique opportunity to inform and constrain a hydrological model and to increase its value as a decision-support tool. In this study, we applied a multi-mission approach to force, calibrate and validate a hydrological model of the ungauged Ogooué river basin in Africa with publicly available and free remote sensing observations. We used a rainfall–runoff model based on the Budyko framework coupled with a Muskingum routing approach. We parametrized the model using the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) and forced it using precipitation from two satellite-based rainfall estimates, FEWS-RFE (Famine Early Warning System rainfall estimate) and the Tropical Rainfall Measuring Mission (TRMM) 3B42 v.7, and temperature from ECMWF ERA-Interim. We combined three different datasets to calibrate the model using an aggregated objective function with contributions from (1) historical in situ discharge observations from the period 1953–1984 at six locations in the basin, (2) radar altimetry measurements of river stages by Envisat and Jason-2 at 12 locations in the basin and (3) GRACE (Gravity Recovery and Climate Experiment) total water storage change (TWSC). Additionally, we extracted CryoSat-2 observations throughout the basin using a Sentinel-1 SAR (synthetic aperture radar) imagery water mask and used the observations for validation of the model. The use of new satellite missions, including Sentinel-1 and CryoSat-2, increased the spatial characterization of river stage. Throughout the basin, we achieved good agreement between observed and simulated discharge and the river stage, with an RMSD between simulated and observed water amplitudes at virtual stations of 0.74 m for the TRMM-forced model and 0.87 m for the FEWS-RFE-forced model. The hydrological model also captures overall total water storage change patterns, although the amplitude of storage change is generally underestimated. By combining hydrological modeling with multi-mission remote sensing from 10 different satellite missions, we obtain new information on an otherwise unstudied basin. The proposed model is the best current baseline characterization of hydrological conditions in the Ogooué in light of the available observations.

scholarly journals Assessing parameter uncertainty in semi-distributed hydrological model based on type-2 fuzzy analysis: a case study of Kaidu River Basin

2015 ◽  
Vol 46 (6) ◽  
pp. 969-983 ◽  
Author(s):  
C. X. Wang ◽  
Y. P. Li ◽  
J. L. Zhang ◽  
G. H. Huang
Keyword(s):  
River Basin ◽  
Hydrological Modeling ◽  
Simulation Method ◽  
Hydrological Processes ◽  
Uncertain Parameters ◽  
Distributed Hydrological Model ◽  
Fuzzy Analysis ◽  
Kaidu River ◽  
Slurp Model

In this study, a type-2 fuzzy simulation method (TFSM) is developed for modeling hydrological processes associated with vague information through coupling type-2 fuzzy analysis technique with the semi-distributed land use based runoff processes (SLURP) model. TFSM can handle fuzzy sets with uncertain membership function related to hydrological modeling parameters and reveal the effects of such uncertain parameters on the hydrological processes. Streamflow calibration and verification are performed using the hydrological data for the Kaidu River Basin, China. The statistical values of Nash–Sutcliffe efficiency, determination coefficient, and deviation of volume indicate a good performance of SLURP in describing the streamflow at the outlet of the Kaidu River Basin. Based on TFSM, the effects of four uncertain parameters such as precipitation factor (PF), maximum capacity for fast store, retention constant for fast store (RF), and retention constant for slow store, on the hydrological processes are analyzed under different α-cut levels. Results demonstrate that the uncertainty associated with PF has significant effect on the simulated streamflow, while the uncertainty associated with RF has slight effect among the four parameters. These findings are helpful for improving efficiency in hydrological prediction and enhancing the model applicability.

scholarly journals Hybrid Gravimetry to Map Water Storage Dynamics in a Mountain Catchment

2022 ◽  
Vol 3 ◽  
Author(s):  
Quentin Chaffaut ◽  
Nolwenn Lesparre ◽  
Frédéric Masson ◽  
Jacques Hinderer ◽  
Daniel Viville ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Local Population ◽  
Water Storage ◽  
Time Lapse ◽  
Temporal Changes ◽  
Distributed Hydrological Model ◽  
Topographic Wetness Index ◽  
Mountain Areas ◽  
Physically Based ◽  
Spatio Temporal

In mountain areas, both the ecosystem and the local population highly depend on water availability. However, water storage dynamics in mountains is challenging to assess because it is highly variable both in time and space. This calls for innovative observation methods that can tackle such measurement challenge. Among them, gravimetry is particularly well-suited as it is directly sensitive–in the sense it does not require any petrophysical relationship–to temporal changes in water content occurring at surface or underground at an intermediate spatial scale (i.e., in a radius of 100 m). To provide constrains on water storage changes in a small headwater catchment (Strengbach catchment, France), we implemented a hybrid gravity approach combining in-situ precise continuous gravity monitoring using a superconducting gravimeter, with relative time-lapse gravity made with a portable Scintrex CG5 gravimeter over a network of 16 stations. This paper presents the resulting spatio-temporal changes in gravity and discusses them in terms of spatial heterogeneities of water storage. We interpret the spatio-temporal changes in gravity by means of: (i) a topography model which assumes spatially homogeneous water storage changes within the catchment, (ii) the topographic wetness index, and (iii) for the first time to our knowledge in a mountain context, by means of a physically based distributed hydrological model. This study therefore demonstrates the ability of hybrid gravimetry to assess the water storage dynamics in a mountain hydrosystem and shows that it provides observations not presumed by the applied physically based distributed hydrological model.

Calibration of a semi-distributed hydrological model adding constrains from remotely sensed snow cover and soil moisture products

2020 ◽  
Author(s):  
Rui Tong ◽  
Juraj Parajka ◽  
Jürgen Komma ◽  
Günter Blöschl
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Snow Melt ◽  
Distributed Hydrological Model ◽  
Calibration Methods ◽  
Discharge Simulation ◽  
Normalized Difference Snow Index ◽  
Discharge Modeling

<p>Remote sensing products have been widely applied in hydrological modeling for more realistic representations of hydrological processes. In this study, in addition to gauged discharge, the combined MODIS snow cover maps and ERS scatterometer based soil moisture products were added to constrain a semi-distributed conceptual hydrological model. The latest version of MODIS snow cover images provides a daily Normalized Difference Snow Index (NDSI) in a 500-meter resolution. We derived the snow cover maps by using a new NDSI thresholding method from the MODIS Aqua (MYD10A1) and Terra (MOD10A1) daily snow cover products. Furthermore, the newest ERS soil moisture product also provided a finer spatial resolution of 500-meter over Austria. The semi-distributed TUW-model was tested in 213 catchments using both single and multiple object calibration methods. We found that the semi-distributed TUW-model performed well in discharge modeling. Moreover, applying the MODIS snow cover maps improved the accuracy in the snow-melt season, while the soil moisture product helped the discharge simulation in the no-snow period.</p>

A meta-model assisted framework of optimization of the Hydrological model parameters for accurate calibration

2020 ◽  
Author(s):  
Ammara Nusrat ◽  
Hamza Farooq Gabriel ◽  
Sajjad Haider ◽  
Muhammad Shahid
Keyword(s):  
Sensitivity Analysis ◽  
Parameter Optimization ◽  
Hydrological Modeling ◽  
Hydrological Model ◽  
Flood Forecasting ◽  
Large River ◽  
Model Parameters ◽  
Distributed Hydrological Model ◽  
Dimensional Parameter ◽  
Input Parameters

<p> Increase in frequency of the floods is one of the noticeable climate change impacts. The efficient and optimized flood analysis system needs to be used for the reliable flood forecasting. The credibility and the reliability of the flood forecasting system is depending upon the framework used for its parameter optimization. Comprehensive framework has been presented to optimize the input parameters of the computationally extensive distributed hydrological model. A large river basin has the high spatio-temporal heterogeneity of aquifer and surface properties.  Estimating the parameters in fully distributed hydrological model is a challenging task. The parameter optimization becomes computationally more demanding when the model input parameters (30 to 100 even greater) have multi-dimensional parameter space, many output parameters which make the optimization problem multi-objective and large number of model simulations requirement for the optimization. Aforementioned challenges are met by introducing the methodology to optimize the input parameters of fully distributed hydrological model, following steps are included (1) screening of the parameters through Morris sensitivity analysis method in different flow periods, so that optimization would be performed for sensitive parameters, different scalar output functions are used in this regard (2) to emulate the hydrologic response of the dynamic model, surrogate models or meta-models are used (3) sampling of parameters values using the optimized ranges obtained from the meta-models; the results are evident that the parameter optimization using the proposed framework is efficient can be effectively performed.  The effectiveness and efficiency of the proposed framework has been demonstrated through the accurate calibration of the model with fewer model runs. This study also demonstrates the importance and use of scalar functions in calculating sensitivity indices, when the model output is temporally variable. In addition, the parameter optimization using the proposed framework is efficient and present study can be used as reference for optimization of distributed hydrological model. </p><p> </p><p><strong>Keywords: </strong>Calibration, parameter ranking, Sensitivity analysis, Hydrological modeling, optimization</p>

Development of a distributed hydrological model based on urban databanks – production processes of URBS

2005 ◽  
Vol 52 (5) ◽  
pp. 241-248 ◽  
Author(s):  
F. Rodriguez ◽  
F. Morena ◽  
H. Andrieu
Keyword(s):  
Land Use ◽  
Transfer Function ◽  
Hydrological Model ◽  
Urban Runoff ◽  
Distributed Hydrological Model ◽  
Production Processes ◽  
Urban Modelling ◽  
Direct Infiltration ◽  
Urban Catchments ◽  
Hydrological Variables

The objective of this study is to present a distributed hydrological model especially dedicated to urban catchments, and able to represent hydrological processes usually neglected in urban modelling, such as evapotranspiration, infiltration in roads, or direct infiltration of soil water in sewers. This model, called URBS (as Urban Runoff Branching Structure) is distributed considering the spatial variability of land use which is well known thanks to urban databanks managed by GIS. The production function is detailed at each cadastral parcel scale, and the runoff produced is routed by a simple transfer function. The estimation of the input parameters of the model is mostly based on physical considerations, and the model is applied on a suburban catchment in Nantes (France) in order to evaluate the interest of the distribution of the hydrological variables.

scholarly journals Identifying Key Hydrological Processes in Highly Urbanized Watersheds for Flood Forecasting with a Distributed Hydrological Model

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1641 ◽  
Author(s):  
Huanyu Wang ◽  
Yangbo Chen
Keyword(s):  
Water Content ◽  
Parameter Uncertainty ◽  
Hydrological Model ◽  
Flood Forecasting ◽  
Hydrological Processes ◽  
Model Parameters ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Physically Based ◽  
Distributed Hydrological Models

The world has experienced large-scale urbanization in the past century, and this trend is ongoing. Urbanization not only causes land use/cover (LUC) changes but also changes the flood responses of watersheds. Lumped conceptual hydrological models cannot be effectively used for flood forecasting in watersheds that lack long time series of hydrological data to calibrate model parameters. Thus, physically based distributed hydrological models are used instead in these areas, but considerable uncertainty is associated with model parameter derivation. To reduce model parameter uncertainty in physically based distributed hydrological models for flood forecasting in highly urbanized watersheds, a procedure is proposed to control parameter uncertainty. The core concept of this procedure is to identify the key hydrological and flood processes in the highly urbanized watersheds and the sensitive model parameters related to these processes. Then, the sensitive model parameters are adjusted based on local runoff coefficients to reduce the parameter uncertainty. This procedure includes these steps: collecting the latest LUC information or estimating this information using satellite remote sensing images, analyzing LUC spatial patterns and identifying dominant LUC types and their spatial structures, choosing and establishing a distributed hydrological model as the forecasting tool, and determining the initial model parameters and identifying the key hydrological processes and sensitive model parameters based on a parameter sensitivity analysis. A highly urbanized watershed called Shahe Creek in the Pearl River Delta area was selected as a case study. This study finds that the runoff production processes associated with both the ferric luvisol and acric ferralsol soil types and the runoff routing process on urban land are key hydrological processes. Additionally, the soil water content under saturated conditions, the soil water content under field conditions and the roughness of urban land are sensitive parameters.

Sign in / Sign up

Export Citation Format

Share Document