scholarly journals Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
L. Rahimi ◽  
C. Deidda ◽  
C. De Michele
Keyword(s):  
Catchment Area ◽  
Hydrological Model ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Daily Discharge ◽  
Pairwise Dependence ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Flood Characteristics ◽  
Conceptual Hydrological Model

AbstractFloods are among the most common and impactful natural events. The hazard of a flood event depends on its peak (Q), volume (V) and duration (D), which are interconnected to each other. Here, we used a worldwide dataset of daily discharge, two statistics (Kendall’s tau and Spearman’s rho) and a conceptual hydrological rainfall-runoff model as model-dependent realism, to investigate the factors controlling and the origin of the dependence between each couple of flood characteristics, with the focus to rainfall-driven events. From the statistical analysis of worldwide dataset, we found that the catchment area is ineffective in controlling the dependence between Q and V, while the dependencies between Q and D, and V and D show an increasing behavior with the catchment area. From the modeling activity, on the U.S. subdataset, we obtained that the conceptual hydrological model is able to represent the observed dependencies between each couple of variables for rainfall-driven flood events, and for such events, the pairwise dependence of each couple is not causal, is of spurious kind, coming from the “Principle of Common Cause”.

Snow-Hydrological modeling using remote sensing data in Vilcanota basin, Peru

2020 ◽  
Author(s):  
Eber Risco ◽  
Waldo Lavado ◽  
Pedro Rau
Keyword(s):  
Hydrological Modeling ◽  
Remote Sensing Data ◽  
Time Consistency ◽  
Rain Gauge ◽  
Rainfall Runoff ◽  
Direct Evaluation ◽  
Daily Discharge ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Trmm 3B42

<p>Water resources availability in the southern Andes of Peru is being affected by glacier and snow retreat. This problem is already perceived in the Vilcanota river basin, where hydro-climatological information is scarce. In this particular mountain context, any water plan represents a great challenge. To cope with these limitations, we propose to assess the space-time consistency of 10 satellite-based precipitation products (CMORPH–CRT v.1, CMORPH–BLD v.1, CHIRP v.2, CHIRPS v.2, GSMaP v.6, GSMaP correction, MSWEP v.2.1, PERSIANN, PERSIANN–CDR, TRMM 3B42) with 25 rain gauge stations in order to select the best product that represents the variability in the Vilcanota basin. For this purpose, through a direct evaluation of sensitivity analysis via the GR4J parsimonious hydrological model over the basin. GSMap v.6, TRMM 3B42 and CHIRPS were selected to represent rainfall spatial variability according with different statistical criteria, such as correlation coefficient (CC), standard deviation (SD), percentage of bias (%B) and centered mean square error (CRMSE). To facilitate the interpretation of statistical results, Taylor's diagram was used to represent the CC statistics, normalized values of SD and CRMSE.</p><p>A distributed degree-day model was chosen to analyse the sensitivity of snow cover simulations and hydrological contribution. The GR4J rainfall-runoff model was calibrated (using global optimization) and applied to simulate the daily discharge and compared with the Distributed Hydrology and Vegetation Model with Glacier Dynamics (DHSVM-GDM) over the 2001-2018 period. Furthermore, the simulated streamflow was evaluated through comparisons with observations at the hydrological stations using Nash–Sutcliffe efficiency and Kling Gupta Efficiency (KGE). The results show that the snow-runoff have increased in recent years, so new water management and planning strategies should be developed in the basin. This research is part of the multidisciplinary collaboration between British and Peruvian scientists (Newton Fund, Newton-Paulet) through RAHU project.</p>

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 Use of the KINFIL rainfall-runoff model on the Hukava catchment

2009 ◽  
Vol 4 (No. 1) ◽  
pp. 1-9
Author(s):  
P. Kovář ◽  
V. Kadlec
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Practical Implementation ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Event Duration ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Runoff Events ◽  
Small Catchments

The paper reports on the flood events on the forested Hukava catchment. It describes practical implementation of the KINFIL rainfall-runoff model. This model has been used for the reconstruction of the rainfall-runoff events and thus for the calibration of its parameters. The model was subsequently used to simulate the design discharges with an event duration of t<sub>d</sub> = 30, 60, and 300 min in the period of recurrence of 100 years, and during the scenario simulations of the land use change when 40% and 80% of the forest in the catchment had been cleared out and then replaced by permanent grasslands. The implementation of the KINFIL model supported by GIS proved to be a proper method for the flood runoff assessment on small catchments, during which different scenarios of the land use changes were tested.

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

&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

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.

Rainfall-Discharge Simulation in Bah Bolon Catchment Area by Mock Method, NRECA Method, and GR2M Method

2016 ◽  
Vol 845 ◽  
pp. 24-29 ◽  
Author(s):  
Hadiani Rintis ◽  
Suyanto ◽  
Yosephina Puspa Setyoasri
Keyword(s):  
Catchment Area ◽  
The Other ◽  
Series Data ◽  
Flow Duration Curve ◽  
Rainfall Runoff ◽  
Flow Duration ◽  
Discharge Simulation ◽  
Rainfall Runoff Model ◽  
North Sumatra ◽  
Runoff Model

Rainfall-discharge simulation is a process transformation from rainfall to discharge in a catchment area by modelling. The most popular models are Mock method and NRECA method. It is according to the handbook of irrigation that is written by government (Indonesia). GR2M (Global Rainfall-Runoff Model) is a new model that is not usual to be used in Indonesia. GR2M is a simulation model that needs less parameter than Mock and NRECA methods. This research was conducted in the Bah Bolon catchment area, Simalungun, North Sumatra. It will analyze the simulation of rainfall-discharge by three methods, Mock, NRECA, and GR2M without considering whether the watershed was wet or dry watershed. The analysis was computed the dependable discharge by flow duration curve (fdc) in a series data on each method. The parameter that compared was the dependable discharge, i.e. the discharge with probability 70% (Q70), probability 80% (Q80), and probability 90% (Q90). GR2M will compared with Mock, then compared with NRECA. The results show that the discharge simulation by GR2M methods and the discharge simulation by Mock method has correlation 0.968. The discharge simulation by GR2M method and the discharge simulation by NRECA method has correlation 0,955. It means that GR2M close to the both of them, but GR2M can used easily because it has less parameter than the other. Based on the graphic, GR2M close to the Mock method for probability more than 50%. So, if the probability is 70%, 80%, and 90%, then GR2M method close to Mock method.

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