scholarly journals Quantifying sensitivity to droughts – an experimental modeling approach

2014 ◽  
Vol 11 (7) ◽  
pp. 7659-7688 ◽  
Author(s):  
M. Staudinger ◽  
M. Weiler ◽  
J. Seibert
Keyword(s):  
Hydrological Model ◽  
Initial Conditions ◽  
Hydrological Drought ◽  
Rainfall Runoff ◽  
Discharge Time ◽  
Low Levels ◽  
Rainfall Runoff Model ◽  
Steep Slopes ◽  
Runoff Model ◽  
Meteorological Droughts

Abstract. Meteorological droughts like those in summer 2003 or spring 2011 in Europe are expected to become more frequent in the future. Although the spatial extent of these drought events was large, not all regions were affected in the same way. Many catchments reacted strongly to the meteorological droughts showing low levels of streamflow and groundwater, while others hardly reacted. The extent of the hydrological drought for specific catchments was also different between these two historical events due to different initial conditions and drought propagation processes. This leads to the important question of how to detect and quantify the sensitivity of a catchment to meteorological droughts. To assess this question we designed hydrological model experiments using a conceptual rainfall–runoff model. Two drought scenarios were constructed by selecting precipitation and temperature observations based on certain criteria: one scenario was a modest but constant progression of drying based on sorting the years of observations according to annual precipitation amounts. The other scenario was a more extreme progression of drying based on selecting months from different years, forming a year with the wettest months through to a year with the driest months. Both scenarios retained the typical intra-annual seasonality for the region. The sensitivity of 24 Swiss catchments to these scenarios was evaluated by analyzing the simulated discharge time series and modeled storages. Mean catchment elevation, slope and size were found to be the main controls on the sensitivity of catchment discharge to precipitation. Generally, catchments at higher elevation and with steeper slopes seemed to be less sensitive to meteorological droughts than catchments at lower elevations with less steep slopes.

scholarly journals Quantifying sensitivity to droughts – an experimental modeling approach

2015 ◽  
Vol 19 (3) ◽  
pp. 1371-1384 ◽  
Author(s):  
M. Staudinger ◽  
M. Weiler ◽  
J. Seibert
Keyword(s):  
Hydrological Model ◽  
Initial Conditions ◽  
Hydrological Drought ◽  
Rainfall Runoff ◽  
Discharge Time ◽  
Low Levels ◽  
Rainfall Runoff Model ◽  
Steep Slopes ◽  
Runoff Model ◽  
Meteorological Droughts

Abstract. Meteorological droughts like those in summer 2003 or spring 2011 in Europe are expected to become more frequent in the future. Although the spatial extent of these drought events was large, not all regions were affected in the same way. Many catchments reacted strongly to the meteorological droughts showing low levels of streamflow and groundwater, while others hardly reacted. Also, the extent of the hydrological drought for specific catchments was different between these two historical events due to different initial conditions and drought propagation processes. This leads to the important question of how to detect and quantify the sensitivity of a catchment to meteorological droughts. To assess this question we designed hydrological model experiments using a conceptual rainfall-runoff model. Two drought scenarios were constructed by selecting precipitation and temperature observations based on certain criteria: one scenario was a modest but constant progression of drying based on sorting the years of observations according to annual precipitation amounts. The other scenario was a more extreme progression of drying based on selecting months from different years, forming a year with the wettest months through to a year with the driest months. Both scenarios retained the observed intra-annual seasonality for the region. We evaluated the sensitivity of 24 Swiss catchments to these scenarios by analyzing the simulated discharge time series and modeled storage. Mean catchment elevation, slope and area were the main controls on the sensitivity of catchment discharge to precipitation. Generally, catchments at higher elevation and with steeper slopes appeared less sensitive to meteorological droughts than catchments at lower elevations with less steep slopes.

scholarly journals Calibration of hydrological model parameters for ungauged catchments

2007 ◽  
Vol 11 (2) ◽  
pp. 703-710 ◽  
Author(s):  
A. Bárdossy
Keyword(s):  
Hydrological Model ◽  
Model Performance ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Rainfall Runoff Model ◽  
Climate Statistics ◽  
Runoff Model ◽  
German Part

Abstract. The parameters of hydrological models for catchments with few or no discharge records can be estimated using regional information. One can assume that catchments with similar characteristics show a similar hydrological behaviour and thus can be modeled using similar model parameters. Therefore a regionalisation of the hydrological model parameters on the basis of catchment characteristics is plausible. However, due to the non-uniqueness of the rainfall-runoff model parameters (equifinality), a workflow of regional parameter estimation by model calibration and a subsequent fit of a regional function is not appropriate. In this paper a different approach for the transfer of entire parameter sets from one catchment to another is discussed. Parameter sets are considered as tranferable if the corresponding model performance (defined as the Nash-Sutclife efficiency) on the donor catchment is good and the regional statistics: means and variances of annual discharges estimated from catchment properties and annual climate statistics for the recipient catchment are well reproduced by the model. The methodology is applied to a set of 16 catchments in the German part of the Rhine catchments. Results show that the parameters transfered according to the above criteria perform well on the target catchments.

scholarly journals Calculating the hydrological response of a mountain catchment using conventional and unconventional (CML) rainfall observations: the case study of Mallero catchment

2020 ◽  
Author(s):  
Greta Cazzaniga ◽  
Carlo De Michele ◽  
Cristina Deidda ◽  
Michele D'Amico ◽  
Antonio Ghezzi ◽  
...  
Keyword(s):  
Hydrological Model ◽  
Hydrological Modelling ◽  
Rainfall Runoff ◽  
Signal Attenuation ◽  
Large Variability ◽  
Field Reconstruction ◽  
Rain Gauges ◽  
Weather Radars ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>Rainfall plays a critical role in the hydrological cycle, being the main downward forcing. It is well known that rainfall exhibits large variability in space and time due to the storm dynamics and its interaction with the topography. It is a difficult task to reconstruct the rainfall over an area accurately. Rainfall is usually collected through rain gauges, disdrometers, and weather radars. Rain gauges and disdrometers provide quite accurate measurements of rainfall on the ground, but at a single site, while weather radars provide an indication of rainfall field variability in space, even if their use is restricted to plain areas.</p><p>Recently, unconventional observations have been considered for the monitoring of rainfall. These consist in signal attenuation measurements induced by rain on a mesh of point-to-point commercial microwave links (CML). These data, integrated with the ones collected by a network of conventional rain gauges, can provide further information about rainfall dynamics leading to improvements in hydrological modelling, which requires accurate description of the rainfall field.</p><p>The work we are going to describe is part of MOPRAM (MOnitoring Precipitation through a Network of RAdio links at Microwaves), a scientific project funded by Fondazione Cariplo (see also the EGU abstract of Nebuloni et al., 2020). Here we use rainfall data, obtained both from a rain gauge network and from signal attenuation measurements, into a hydrological model in order to evaluate the improvement in the hydrological modelling due to a better description of the rainfall field. We consider a semi-distributed rainfall-runoff model and we apply it to the Mallero catchment (Western Rhaetian Alps, Northern Italy), with the outlet located in Sondrio. This catchment is equipped with 13 microwave links and a network of 13 rain gauges.</p><p>Firstly, we implement and test the Rain field Reconstruction Algorithm (RRA), which retrieves the 2D rainfall field from CML data through a tomographic inversion technique, developed by D’Amico et al., 2016. By RRA we generate synthetic rainfall maps from attenuation data measured by 13 links located in the Mallero basin, for a few historical events in the period 2016-2019. To improve the accuracy of rainfall field reconstruction, we also integrate the reconstructed maps with on ground data from 13 rain gauges. These maps are used as input to the hydrological rainfall-runoff model. Finally, we compare the observed discharge with the calculated one using the hydrological model and different rainfall inputs.</p>

scholarly journals A coupled stochastic rainfall-evapotranspiration model for hydrological impact analysis

2017 ◽  
Author(s):  
Minh Tu Pham ◽  
Hilde Vernieuwe ◽  
Bernard De Baets ◽  
Niko E. C. Verhoest
Keyword(s):  
Time Series ◽  
Impact Analysis ◽  
Hydrological Model ◽  
Hydrological Cycle ◽  
Rainfall Runoff ◽  
Hydrological Impact ◽  
Long Time ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract. A hydrological impact analysis concerns the study of the consequences of certain scenarios on one or more variables or fluxes in the hydrological cycle. In such exercise, discharge is often considered, as especially extreme high discharges often cause damage due to the coinciding floods. Investigating extreme discharges generally requires long time series of precipitation and evapotranspiration that are used to force a rainfall-runoff model. However, such kind of data may not be available and one should resort to stochastically-generated time series, even though the impact of using such data on the overall discharge, and especially on the extreme discharge events is not well studied. In this paper, stochastically-generated rainfall and coinciding evapotranspiration time series are used to force a simple conceptual hydrological model. The results obtained are comparable to the modelled discharge using observed forcing data. Yet, uncertainties in the modelled discharge increase with an increasing number of stochastically-generated time series used. Notwithstanding this finding, it can be concluded that using a coupled stochastic rainfall-evapotranspiration model has a large potential for hydrological impact analysis.

scholarly journals Regionalization of hydrological model parameters using data depth

2011 ◽  
Vol 42 (5) ◽  
pp. 356-371 ◽  
Author(s):  
András Bárdossy ◽  
Shailesh Kumar Singh
Keyword(s):  
Hydrological Model ◽  
Data Depth ◽  
Model Parameters ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Catchment Characteristics ◽  
Rainfall Runoff Model ◽  
Using Data ◽  
Runoff Model

The parameters of hydrological models with no or short discharge records can only be estimated using regional information. We can assume that catchments with similar characteristics show a similar hydrological behaviour. A regionalization of hydrological model parameters on the basis of catchment characteristics is therefore plausible. However, due to the non-uniqueness of the rainfall/runoff model parameters (equifinality), a procedure of a regional parameter estimation by model calibration and a subsequent fit of a regional function is not appropriate. In this paper, a different procedure based on the depth function and convex combinations of model parameters is introduced. Catchment characteristics to be used for regionalization can be identified by the same procedure. Regionalization is then performed using different approaches: multiple linear regression using the deepest parameter sets and convex combinations. The assessment of the quality of the regionalized models is also discussed. An example of 28 British catchments illustrates the methodology.

scholarly journals Quantitative analysis of runoff reduction in the Laohahe basin

2012 ◽  
Vol 43 (1-2) ◽  
pp. 38-47 ◽  
Author(s):  
Liliang Ren ◽  
Xiaofan Liu ◽  
Fei Yuan ◽  
Jing Xu ◽  
Wei Liu
Keyword(s):  
Climate Change ◽  
Human Activity ◽  
Hydrological Model ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Runoff Reduction ◽  
Runoff Series ◽  
Drastic Effect ◽  
Rainfall Runoff Model ◽  
Runoff Model

In order to determine the reason for runoff reduction, daily natural runoff series were restored using a conceptual rainfall–runoff model. The period of 1970–1979 was regarded as a base period with little human activity; model parameters for each subcatchment within the Laohahe basin were calibrated for this period. The effects of human activity and climate change on runoff were quantified by comparing the observed runoff and the natural runoff simulated by the hydrological model. The results show that the observed annual mean runoffs in the 1980s and especially in the 2000s are smaller than those of the 1970s. Although runoff reduction in the 1980s and 2000s is mainly caused by climate change, human activity also plays an important role on the runoff reduction. Taking the 2000 as an example, human activity and climate change are responsible for 45.6 and 54.4% of the runoff reduction in Laohahe basin, respectively. The effect of human activity on runoff reduction in the Laohahe basin is increasingly intensive from the 1980s to the 2000s. Human activity in the Dianzi catchment has the most drastic effect within the Laohahe basin.

regionalization of the potential to increase rainfall-runoff model performance by multi-objective calibration using modis data over Austria

2020 ◽  
Author(s):  
Martin Kubáň ◽  
Patrik Sleziak ◽  
Adam Brziak ◽  
Kamila Hlavčová ◽  
Ján Szolgay
Keyword(s):  
Soil Moisture ◽  
Hydrological Model ◽  
Snow Water Equivalent ◽  
Model Performance ◽  
State Variables ◽  
Rainfall Runoff ◽  
Multi Objective ◽  
Snow Water ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>A multi-objective calibration of the parameters of conceptual hydrologic models has the potential to improve the consistency of the simulated model states, their representativeness with respect to catchment states and thereby to reduce the uncertainty in the estimation of hydrological model outputs. Observed in-situ or remotely sensed state variables, such as the snow cover distribution, snow depth, snow water equivalent and soil moisture were often considered as additional information in such calibration strategies and subsequently utilized in data assimilation for operational streamflow forecasting. The objective of this paper is to assess the effects of the inclusion of MODIS products characterizing soil moisture and the snow water equivalent in a multi-objective calibration strategy of an HBV type conceptual hydrological model under the highly variable physiographic conditions over the whole territory of Austria.</p><p>The methodology was tested using the Technical University of Vienna semi-distributed rainfall-runoff model (the TUW model), which was calibrated and validated in 213 Austrian catchments. For calibration we use measured data from the period 2005 to 2014. Subsequently, we simulated discharges, soil moisture and snow water equivalents based on parameters from the multi-objective calibration and compared these with the respective MODIS values. In general, the multi-objective calibration improved model performance when compared to results of model parametrisation calibrated only on discharge time series. Sensitivity analyses indicate that the magnitude of the model efficiency is regionally sensitive to the choice of the additional calibration variables. In the analysis of the results we indicate ranges how and where the runoff, soil moisture and snow water equivalent simulation efficiencies were sensitive to different setups of the multi-objective calibration strategy over the whole territory of Austria. It was attempted to regionalize the potential to increase of the overall model performance and the improvement in the consistency of the simulation of the two-state variables. Such regionalization may serve model users in the selection which remotely sensed variable or their combination is to be preferred in local modelling studies.</p>

scholarly journals The Impact of the Variability of Precipitation and Temperatures on the Efficiency of a Conceptual Rainfall-Runoff Model

2016 ◽  
Vol 24 (4) ◽  
pp. 1-7 ◽  
Author(s):  
P. Sleziak ◽  
J. Szolgay ◽  
K. Hlavčová ◽  
J. Parajka
Keyword(s):  
Hydrological Model ◽  
Differential Evolution Algorithm ◽  
Rainfall Runoff ◽  
University Of Technology ◽  
Wide Range ◽  
Evolution Algorithm ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
The Relationship ◽  
Runoff Model

AbstractThe main objective of the paper is to understand how the model’s efficiency and the selected climatic indicators are related. The hydrological model applied in this study is a conceptual rainfall-runoff model (the TUW model), which was developed at the Vienna University of Technology. This model was calibrated over three different periods between 1981-2010 in three groups of Austrian catchments (snow, runoff, and soil catchments), which represent a wide range of the hydroclimatic conditions of Austria. The model’s calibration was performed using a differential evolution algorithm (Deoptim). As an objective function, we used a combination of the Nash-Sutcliffe coefficient (NSE) and the logarithmic Nash-Sutcliffe coefficient (logNSE). The model’s efficiency was evaluated by Volume error (VE). Subsequently, we evaluated the relationship between the model’s efficiency (VE) and changes in the climatic indicators (precipitation ΔP, air temperature ΔT). The implications of findings are discussed in the conclusion.

scholarly journals The Wageningen Lowland Runoff Simulator (WALRUS): application to the Hupsel Brook catchment and Cabauw polder

2014 ◽  
Vol 11 (2) ◽  
pp. 2091-2148 ◽  
Author(s):  
C. C. Brauer ◽  
P. J. J. F. Torfs ◽  
A. J. Teuling ◽  
R. Uijlenhoet
Keyword(s):  
Surface Water ◽  
Initial Conditions ◽  
Companion Paper ◽  
Water Levels ◽  
Rainfall Runoff ◽  
Wetness Index ◽  
Temporal And Spatial Variability ◽  
Rainfall Runoff Model ◽  
One Year ◽  
Runoff Model

Abstract. The Wageningen Lowland Runoff Simulator (WALRUS) is a new parametric (conceptual) rainfall-runoff model which accounts explicitly for processes that are important in lowland areas, such as groundwater-unsaturated zone coupling, wetness-dependent flowroutes, groundwater–surface water feedbacks, and seepage and surface water supply (see companion paper by Brauer et al., 2014). Lowland catchments can be divided into slightly sloping, freely draining catchments and flat polders with controlled water levels. Here, we apply WALRUS to two contrasting Dutch catchments: the Hupsel Brook catchment and Cabauw polder. In both catchments, WALRUS performs well: Nash–Sutcliffe efficiencies obtained after calibration on one year of discharge observations are 0.87 for the Hupsel Brook catchment and 0.83 for the Cabauw polder, with values of 0.74 and 0.76 for validation. The model also performs well during floods and droughts and can forecast the effect of control operations. Through the dynamic division between quick and slow flowroutes controlled by a wetness index, temporal and spatial variability in groundwater depths can be accounted for, which results in adequate simulation of discharge peaks as well as low flows. The performance of WALRUS is most sensitive to the parameter controlling the wetness index and the groundwater reservoir constant, and to a lesser extent to the quickflow reservoir constant. The effects of these three parameters can be identified in the discharge time series, which indicates that the model is not overparameterised (parsimonious). Forcing uncertainty was found to have a larger effect on modelled discharge than parameter uncertainty and uncertainty in initial conditions.

scholarly journals Commercial microwave links as rainfall input data in urban hydrological modelling

2021 ◽  
Author(s):  
Greta Cazzaniga ◽  
Carlo De Michele ◽  
Cristina Deidda ◽  
Michele D'Amico ◽  
Antonio Ghezzi ◽  
...  
Keyword(s):  
River Discharge ◽  
Hydrological Model ◽  
Warning System ◽  
Signal Propagation ◽  
Rainfall Data ◽  
Data Availability ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Commercial Microwave Links

<p>Many studies in literature have showed that hydrological models are highly sensitive to spatial variability of the rainfall field. Limited and inaccurate rainfall observations can negatively affect flood forecasting and the decision-making processes based on warning system. This problem becomes much more evident in urban catchments which usually covers huge areas and where the runoff process is faster, due to the highly impervious surfaces. Given this, it is a priority to develop always new operational instruments which can improve rainfall data availability and accurately quantify rainfall variability in space. To face this challenge, in the recent years, it has been investigated the use of commercial microwave links (CML) as opportunistic rainfall sensors which could be integrated with traditional rainfall observations in areas lacking sensors. The technique relies on the well-established relationship between CML's signal attenuation and rainfall intensity across the signal propagation path. Here, we assess the operational potential of a CML network, located in the northern area of Lambro river (Lombardia region, Italy). This urbanized region is of great hydrological interest, since it is often subjected to flash floods, hence it requires a robust and accurate warning system. We considered a set of about 80 CMLs distributed quite uniformly over the entire study area and we assessed if and how rainfall data collected by them can improve river discharge predictions. To this aim, we implemented a semi-distributed rainfall-runoff model, which reproduces the river flow at the outlet section in Lesmo (Monza e Brianza), and we fed the hydrological model with CML rainfall data. We tested the use of CML rainfall data as input to the hydrological model. In particular, we used path-averaged rainfall intensities, calculated from CML path attenuation, as point measurements with a weight inversely proportional to CML length. To check the suitability of CML data as input to our urban rainfall-runoff model, we compared the observed river discharge with the predicted one, obtained using different rainfall data layouts. Indeed, we tested CML data but also rain gauges measurements and a combination of CML and rain gauge observations.</p>

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