scholarly journals Estimating the impacts and uncertainty of changing spatial input data resolutions on streamflow simulations in two basins

2012 ◽  
Vol 14 (4) ◽  
pp. 902-917 ◽  
Author(s):  
X. Zhang ◽  
G. Hörmann ◽  
N. Fohrer ◽  
J. Gao
Keyword(s):  
Spatial Data ◽  
Input Data ◽  
Distribution Patterns ◽  
Parameter Distribution ◽  
Model Parameters ◽  
Site Analysis ◽  
Daily Streamflow ◽  
Model Efficiency ◽  
Rainfall Runoff Model ◽  
The Impact

The impact of different grid resolutions of spatial input data on modelled river runoff are investigated using the simple rainfall-runoff model KIDS (Kielstau Discharge Simulations) in PCRaster modelling language for two watersheds – Kielstau and XitaoXi. In this study, the grid-based spatial data are aggregated to coarser resolutions to support the multi-resolution, multi-calibration and multi-site analysis for grid-scale investigations. Daily streamflow is simulated and model parameters are calibrated at each spatial resolution. The study suggests that re-calibration is critically needed when the grid resolution is changed. Altering grid sizes has an apparent impact on the parameter distribution patterns. Resolution uncertainty bands obtained by the overlapping hydrographs generated with different resolutions of input data are reported with a sufficient coverage of the observations for both basins. The analysis of model efficiency in terms of IC-ratio (a ratio between the input grid area and the catchment area) indicates that coarser resolutions with an IC-ratio of <0.001 may be used as an effective alternative for conducting preliminary analyses in streamflow simulation for the Kielstau basin. The modelling outputs are more sensitive to the spatial distribution of input data at the XitaoXi watershed, showing that accurate input data are required to achieve optimum modelling performance.

scholarly journals Regionalizing rainfall–runoff model parameters to predict the daily streamflow of ungauged catchments in the dry tropics

2009 ◽  
Vol 40 (5) ◽  
pp. 433-444 ◽  
Author(s):  
David A. Post
Keyword(s):  
Input Data ◽  
Water Yield ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Wet Season ◽  
Daily Streamflow ◽  
Total Length ◽  
Dry Tropics ◽  
Rainfall Runoff Model ◽  
Runoff Model

A methodology has been derived which allows an estimate to be made of the daily streamflow at any point within the Burdekin catchment in the dry tropics of Australia. The input data requirements are daily rainfall (to drive the rainfall–runoff model) and mean average wet season rainfall, total length of streams, percent cropping and percent forest in the catchment (to regionalize the parameters of the rainfall–runoff model). The method is based on the use of a simple, lumped parameter rainfall–runoff model, IHACRES (Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow data). Of the five parameters in the model, three have been set to constants to reflect regional conditions while the other two have been related to physio-climatic attributes of the catchment under consideration. The parameter defining total catchment water yield (c) has been estimated based on the mean average wet season rainfall, while the streamflow recession time constant (τ) has been estimated based on the total length of streams, percent cropping and percent forest in the catchment. These relationships have been shown to be applicable over a range of scales from 68–130,146 km2. However, three separate relationships were required to define c in the three major physiographic regions of the Burdekin: the upper Burdekin, Bowen and Suttor/lower Burdekin. The invariance of the relationships with scale indicates that the dominant processes may be similar across a range of scales. The fact that different relationships were required for each of the three major regions indicates the geographic limitations of this regionalization approach. For most of the 24 gauged catchments within the Burdekin the regionalized rainfall–runoff models were nearly as good as or better than the rainfall–runoff models calibrated to the observed streamflow. In addition, models often performed better over the simulation period than the calibration period. This indicates that future improvements in regionalization should focus on improving the quality of input data and rainfall–runoff model conceptualization rather than on the regionalization procedure per se.

scholarly journals The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1703 ◽  
Author(s):  
Shakti P. C. ◽  
Tsuyoshi Nakatani ◽  
Ryohei Misumi
Keyword(s):  
River Basin ◽  
Spatial Resolution ◽  
Hydrological Modeling ◽  
Distribution Patterns ◽  
Rainfall Data ◽  
Model Parameters ◽  
Radar Rainfall ◽  
Rain Events ◽  
The Impact ◽  
Hydrological Applications

Recently, the use of gridded rainfall data with high spatial resolutions in hydrological applications has greatly increased. Various types of radar rainfall data with varying spatial resolutions are available in different countries worldwide. As a result of the variety in spatial resolutions of available radar rainfall data, the hydrological community faces the challenge of selecting radar rainfall data with an appropriate spatial resolution for hydrological applications. In this study, we consider the impact of the spatial resolution of radar rainfall on simulated river runoff to better understand the impact of radar resolution on hydrological applications. Very high-resolution polarimetric radar rainfall (XRAIN) data are used as input for the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) to simulate runoff from the Tsurumi River Basin, Japan. A total of 20 independent rainfall events from 2012–2015 were selected and categorized into isolated/convective and widespread/stratiform events based on their distribution patterns. First, the hydrological model was established with basin and model parameters that were optimized for each individual rainfall event; then, the XRAIN data were rescaled at various spatial resolutions to be used as input for the model. Finally, we conducted a statistical analysis of the simulated results to determine the optimum spatial resolution for radar rainfall data used in hydrological modeling. Our results suggest that the hydrological response was more sensitive to isolated or convective rainfall data than it was to widespread rain events, which are best simulated at ≤1 km and ≤5 km, respectively; these results are applicable in all sub-basins of the Tsurumi River Basin, except at the river outlet.

scholarly journals Uncertainty and sensitivity analysis of GIS based continuous hydrological modelling

2021 ◽  
Author(s):  
Harry R. Manson
Keyword(s):  
Sensitivity Analysis ◽  
Curve Number ◽  
Monte Carlo Analysis ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Daily Average ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

The impact of uncertainty in spatial and a-spatial lumped model parameters for a continuous rainfall-runoff model is evaluated with respect to model prediction. The model uses a modified SCS-Curve Number approach that is loosely coupled with a geographic information system (GIS). The rainfall-runoff model uses daily average inputs and is calibrated using a daily average streamflow record for the study site. A Monte Carlo analysis is used to identify total model uncertainty while sensitivity analysis is applied using both a one-at-a-time (OAT) approach as well as through application of the extended Fourier Amplitude Sensitivity Technique (FAST). Conclusions suggest that the model is highly followed by model inputs and finally the Curve Number. While the model does not indicate a high degree of sensitivity to the Curve Number at present conditions, uncertainties in Curve Number estimation can potentially be the cause of high predictive errors when future development scenarios are evaluated.

scholarly journals A comparison of regionalisation methods for catchment model parameters

2005 ◽  
Vol 2 (2) ◽  
pp. 509-542 ◽  
Author(s):  
J. Parajka ◽  
R. Merz ◽  
G. Blöschl
Keyword(s):  
Snow Cover ◽  
Predictive Accuracy ◽  
Model Parameters ◽  
Stream Network ◽  
Ungauged Catchments ◽  
Verification Period ◽  
Model Efficiency ◽  
Complete Set ◽  
Rainfall Runoff Model ◽  
Catchment Model

Abstract. In this study we examine the relative performance of a range of methods for transposing catchment model parameters to ungauged catchments. We calibrate 11 parameters of a semi-distributed conceptual rainfall-runoff model to daily runoff and snow cover data of 320 Austrian catchments in the period 1987-1997 and verify the model for the period 1976-1986. We evaluate the predictive accuracy of the regionalisation methods by jack-knife cross-validation against daily runoff and snow cover data. The results indicate that two methods perform best. The first is a kriging approach where the model parameters are regionalised independently from each other based on their spatial correlation. The second is a similarity approach where the complete set of model parameters is transposed from a donor catchment that is most similar in terms of its physiographic attributes (mean catchment elevation, stream network density, lake index, areal proportion of porous aquifers, land use, soils and geology). For the calibration period, the median Nash-Sutcliffe model efficiency ME of daily runoff is 0.67 for both methods as compared to ME=0.72 for the at-site simulations. For the verification period, the corresponding efficiencies are 0.62 and 0.66. All regionalisation methods perform similar in terms of simulating snow cover.

scholarly journals A Modified IHACRES Rainfall-Runoff Model for Predicting the Hydrologic Response of a River Basin Connected with a Deep Groundwater Aquifer

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2031 ◽  
Author(s):  
Iolanda Borzì ◽  
Brunella Bonaccorso ◽  
Aldo Fiori
Keyword(s):  
Flow Regime ◽  
River Basin ◽  
Cross Section ◽  
Slow Component ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Daily Streamflow ◽  
Groundwater Aquifer ◽  
Rainfall Runoff Model ◽  
Runoff Model

A flow regime is influenced by the degree of hydrologic connection between surface water and groundwater. As this connection becomes more transient and the basin’s runoff response more non-linear, such as for intermittent streams, the need for explicit representation of the groundwater component increases. The present study investigates the connection between Northern Etna groundwater system and the Alcantara river basin in Sicily (Italy). In particular, the upstream part of the basin, whose flow regime is essentially intermittent, is modeled through a modified version of the IHACRES rainfall-runoff model. The structure of the model includes a routing module formulated as a two-store model, with the upper store simulating the quick component of the runoff and recharging the lower store which, in turn, describes the slow component of the runoff and the groundwater extraction and losses. Both stores are conceptualized as simple linear reservoirs, with the lower one that maintains a continuous water balance account of groundwater storage volumes for the upstream basin area with respect to a control cross-section, assumed to be the stream gauging station. The model is calibrated at Moio Alcantara cross-section, where daily streamflow data are available. Model calibration and validation are carried out for the period 1980–1984 and 1986–1988, respectively. A first-order analysis is also performed to assess the sensitivity of model parameters. The adopted configuration is shown to improve model performance with respect to the original IHACRES model, with the proposed formulation able to better capture the interactions between the aquifer and the river.

scholarly journals Assessing the Impact of Uncertainty Parameters on Forcasting Production Parameters

2020 ◽  
Vol 20 (4) ◽  
pp. 356-368
Author(s):  
Nikita D. Nikita D. ◽  
◽  
Aleksey Yu. Vishnyakov ◽  
Ivan S. Putilov ◽  
◽  
...  
Keyword(s):  
Input Data ◽  
Approximate Algorithm ◽  
Economic Evaluations ◽  
Model Parameters ◽  
Reservoir Model ◽  
Hydrodynamic Simulation ◽  
Production Parameters ◽  
Uncertainty Parameters ◽  
The Impact ◽  
Selection Of

At the stage of developing a geological and hydrodynamic reservoir model, uncertainties in input data may lead to errors in simulation results and subsequent inaccurate economic evaluations of oil or gas field potentials. In order to improve predictive reliability, a study was completed to assess how input data of a hydrodynamic model influence forecasts of main parameters of a production using the example of the Tournaisian site of the Soldatovskoye field. The study presents an approximate algorithm reducing uncertainties and improving the forecast reliability of the production parameters obtained using a geological and hydrodynamic reservoir model. The algorithm includes a substantiated selection of the initial sensitivity parameters, an evaluation of the impact of the initial parameters on the hydrodynamic reservoir model using the sensitivity analysis, as well as a selection of an optimal range of variations of the uncertainty parameters as a result of the multivariant hydrodynamic simulation adaptation, calculation and analysis of the multivariant hydrodynamic reservoir model forecast. The study aims to clarify the design process parameters of the development, assess the risks of non-confirmation of the hydrodynamic simulation forecasting, and make recommendations and proposals to study those uncertainty parameters, which influence most on certain predicted production parameters of an asset. As a result, a block diagram of the approach is presented in order to generalize and replicate it on potential and important oil and gas fields. The described approach of the model adaptation and calculations of the predicted options in conditions of uncertainty of the initial model parameters make it possible to obtain a more accurate and less arbitrary hydrodynamic reservoir model, which reduces probability of an incorrect evaluation of potentials of a young field or a field at an early production stage.

scholarly journals Application of the Frier Distributed Model for Estimating the Impact of Land use Changes on the Water Balance in Selected Basins in Slovakia

2009 ◽  
Vol 57 (4) ◽  
pp. 213-225 ◽  
Author(s):  
Oliver Horvát ◽  
Kamila Hlavčová ◽  
Silvia Kohnová ◽  
Michal Danko
Keyword(s):  
Land Use ◽  
Water Balance ◽  
Land Use Changes ◽  
Hydrological Regime ◽  
Distributed Model ◽  
Model Parameters ◽  
Hydrologic Processes ◽  
Rainfall Runoff Model ◽  
Using Data ◽  
The Impact

Application of the Frier Distributed Model for Estimating the Impact of Land use Changes on the Water Balance in Selected Basins in SlovakiaIn this study, the FRIER rainfall-runoff model with distributed parameters was developed to assess changes in runoff and water balance due to changes in land use and climate. The water balance was calculated at 3 levels: on the surface and in unsaturated and saturated zones. Six basins from the central and eastern parts of Slovakia were selected on the basis of their similar size, but different topography, land use, soil texture and climate: the upper Hornád, the upper Hron, the Poprad, the Rimava, the Slaná and the Torysa River basins. Model parameters were estimated using data from the period from June 1998 to May 2000 in daily time steps. The differences and similarities of the hydrologic processes in individual basins were investigated during the calibration period. Several scenarios of changes in land use and two simple scenarios of changes in climate were developed to estimate the impact of these changes on water balance and runoff. The changes in the hydrological regime were compared and discussed.

scholarly journals Uncertainty and sensitivity analysis of GIS based continuous hydrological modelling

2021 ◽  
Author(s):  
Harry R. Manson
Keyword(s):  
Sensitivity Analysis ◽  
Curve Number ◽  
Monte Carlo Analysis ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Lumped Model ◽  
Daily Average ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

The impact of uncertainty in spatial and a-spatial lumped model parameters for a continuous rainfall-runoff model is evaluated with respect to model prediction. The model uses a modified SCS-Curve Number approach that is loosely coupled with a geographic information system (GIS). The rainfall-runoff model uses daily average inputs and is calibrated using a daily average streamflow record for the study site. A Monte Carlo analysis is used to identify total model uncertainty while sensitivity analysis is applied using both a one-at-a-time (OAT) approach as well as through application of the extended Fourier Amplitude Sensitivity Technique (FAST). Conclusions suggest that the model is highly followed by model inputs and finally the Curve Number. While the model does not indicate a high degree of sensitivity to the Curve Number at present conditions, uncertainties in Curve Number estimation can potentially be the cause of high predictive errors when future development scenarios are evaluated.

scholarly journals Considering rating curve uncertainty in water level predictions

2013 ◽  
Vol 17 (11) ◽  
pp. 4415-4427 ◽  
Author(s):  
A. E. Sikorska ◽  
A. Scheidegger ◽  
K. Banasik ◽  
J. Rieckermann
Keyword(s):  
Water Level ◽  
Bayesian Framework ◽  
Water Levels ◽  
Model Parameters ◽  
Calibration Data ◽  
Rainfall Runoff ◽  
Rating Curve ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract. Streamflow cannot be measured directly and is typically derived with a rating curve model. Unfortunately, this causes uncertainties in the streamflow data and also influences the calibration of rainfall-runoff models if they are conditioned on such data. However, it is currently unknown to what extent these uncertainties propagate to rainfall-runoff predictions. This study therefore presents a quantitative approach to rigorously consider the impact of the rating curve on the prediction uncertainty of water levels. The uncertainty analysis is performed within a formal Bayesian framework and the contributions of rating curve versus rainfall-runoff model parameters to the total predictive uncertainty are addressed. A major benefit of the approach is its independence from the applied rainfall-runoff model and rating curve. In addition, it only requires already existing hydrometric data. The approach was successfully demonstrated on a small catchment in Poland, where a dedicated monitoring campaign was performed in 2011. The results of our case study indicate that the uncertainty in calibration data derived by the rating curve method may be of the same relevance as rainfall-runoff model parameters themselves. A conceptual limitation of the approach presented is that it is limited to water level predictions. Nevertheless, regarding flood level predictions, the Bayesian framework seems very promising because it (i) enables the modeler to incorporate informal knowledge from easily accessible information and (ii) better assesses the individual error contributions. Especially the latter is important to improve the predictive capability of hydrological models.

scholarly journals Water budget, performance of evapotranspiration formulations, and their impact on hydrological modeling of a small boreal peatland-dominated watershed

2018 ◽  
Vol 55 (2) ◽  
pp. 206-220 ◽  
Author(s):  
Pierre-Erik Isabelle ◽  
Daniel F. Nadeau ◽  
Alain N. Rousseau ◽  
François Anctil
Keyword(s):  
Water Budget ◽  
Hydrological Modeling ◽  
Distributed Model ◽  
Model Parameters ◽  
Taylor Models ◽  
Physically Based ◽  
Model Efficiency ◽  
The Impact ◽  
Substantial Drop

Peatlands occupy around 13% of the land cover of Canada, and thus they play a key role in the water balance at high latitudes. They are well known for having substantial water loss due to evapotranspiration. Since measurements of evapotranspiration are scarce over these environments, hydrologists generally rely on models of varying complexity to evaluate these water exchanges in the global watershed balance. This study quantifies the water budget of a small boreal peatland-dominated watershed. We assess the performance of three evapotranspiration models in comparison with in situ observations and the impact of using these models in the hydrological modeling of the watershed. The study site (∼1 km2) is located in the eastern James Bay lowlands, Québec, Canada. During summer 2012, an eddy flux tower measured evapotranspiration continuously, while a trapezoidal flume monitored streamflow at the watershed outlet. We estimated evapotranspiration with a combinational model (Penman), a radiation-based model (Priestley–Taylor), and a temperature-based model (Hydro-Québec), and performed the hydrological modeling of the watershed with HYDROTEL, a physically based semi-distributed model. Our results show that the Penman and Priestley–Taylor models reproduce the observations with the highest precision, while a substantial drop in performance occurs with the Hydro-Québec model. However, these discrepancies did not appear to reduce the hydrological model efficiency, at least from what can be concluded from a 3-month modeling period. HYDROTEL appears sensitive to evapotranspiration inputs, but calibration of model parameters can compensate for the differences. These findings still need to be confirmed with longer modeling periods.

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