scholarly journals From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution

2014 ◽  
Vol 11 (12) ◽  
pp. 13259-13309 ◽  
Author(s):  
M. Herrnegger ◽  
H. P. Nachtnebel ◽  
K. Schulz
Keyword(s):  
Temporal Resolution ◽  
Numerical Experiments ◽  
Inverse Model ◽  
High Temporal Resolution ◽  
Rainfall Runoff ◽  
Time Step ◽  
Areal Rainfall ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Rainfall Estimates

Abstract. This paper presents a novel technique to calculate mean areal rainfall in a high temporal resolution of 60 min on the basis of an inverse conceptual rainfall–runoff model and runoff observations. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. The most reliable hydrological information available refers to runoff, which in the presented work is used as input for a rainfall–runoff model. Thereby a conceptual, HBV-type model is embedded in an iteration algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value that corresponds to the observation. To verify the existence, uniqueness and stability of the inverse rainfall, numerical experiments with synthetic hydrographs as inputs into the inverse model are carried out successfully. The application of the inverse model with runoff observations as driving input is performed for the Krems catchment (38.4 km2), situated in the northern Austrian Alpine foothills. Compared to station observations in the proximity of the catchment, the inverse rainfall sums and time series have a similar goodness of fit, as the independent INCA rainfall analysis of Austrian Central Institute for Meteorology and Geodynamics (ZAMG). Compared to observations, the inverse rainfall estimates show larger rainfall intensities. Numerical experiments show, that cold state conditions in the inverse model do not influence the inverse rainfall estimates, when considering an adequate spin-up time. The application of the inverse model is a feasible approach to obtain improved estimates of mean areal rainfall. These can be used to enhance interpolated rainfall fields, e.g. for the estimation of rainfall correction factors, the parameterisation of elevation dependency or the application in real-time flood forecasting systems.

scholarly journals From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution

2015 ◽  
Vol 19 (11) ◽  
pp. 4619-4639 ◽  
Author(s):  
M. Herrnegger ◽  
H. P. Nachtnebel ◽  
K. Schulz
Keyword(s):  
Daily Rainfall ◽  
Inverse Model ◽  
High Temporal Resolution ◽  
Rainfall Runoff ◽  
Time Step ◽  
Lumped Model ◽  
Additional Information ◽  
Mountainous Regions ◽  
Hourly Data ◽  
Areal Rainfall

Abstract. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. In contrast, the most reliable hydrological information available refers to runoff, which in the presented work is used as input for an inverted HBV-type rainfall–runoff model that is embedded in a root finding algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value closely matching the observed runoff. The inverse model is applied and tested to the Schliefau and Krems catchments, situated in the northern Austrian Alpine foothills. The correlations between inferred rainfall and station observations in the proximity of the catchments are of similar magnitude compared to the correlations between station observations and independent INCA (Integrated Nowcasting through Comprehensive Analysis) rainfall analyses provided by the Austrian Central Institute for Meteorology and Geodynamics (ZAMG). The cumulative precipitation sums also show similar dynamics. The application of the inverse model is a promising approach to obtain additional information on mean areal rainfall. This additional information is not solely limited to the simulated hourly data but also includes the aggregated daily rainfall rates, which show a significantly higher correlation to the observed values. Potential applications of the inverse model include gaining additional information on catchment rainfall for interpolation purposes, flood forecasting or the estimation of snowmelt contribution. The application is limited to (smaller) catchments, which can be represented with a lumped model setup, and to the estimation of liquid rainfall.

scholarly journals Sensitivity of the performance of a conceptual rainfall–runoff model to the temporal sampling of calibration data

2012 ◽  
Vol 44 (3) ◽  
pp. 484-494 ◽  
Author(s):  
Satish Bastola ◽  
Conor Murphy
Keyword(s):  
Temporal Resolution ◽  
Model Calibration ◽  
Flood Frequency Analysis ◽  
Calibration Data ◽  
Rainfall Runoff ◽  
Time Step ◽  
Scaling Relationship ◽  
Simple Scaling ◽  
Rainfall Runoff Model ◽  
Runoff Model

The effect of the time step of calibration data on the performance of a hydrological model is examined through a numerical experiment where HYMOD, a rainfall–runoff model, is calibrated with data of varying temporal resolution. A simple scaling relationship between the parameters of the model and modelling time step is derived which enables information from daily hydrological records to be used in modelling at time steps much shorter than daily. Model parameters were found to respond differently depending upon the degree of aggregation of calibration data. A loss in performance, especially in terms of the Nash–Sutcliffe measure, is evident when behavioural simulators derived with one modelling time step are used for simulation at another time step. The loss in performance is greater when parameters derived from a longer time step were used for simulating flow with a shorter time step. The application of a simple scaling relationship derived from a multi-time step model calibration significantly decreased the loss in model performance. Such an approach may offer the prospect of conducting higher temporal resolution flood frequency analysis when finer scale data for model calibration are not available or limited.

scholarly journals Preliminary Study of Computational Time Steps in a Physically Based Distributed Rainfall–Runoff Model

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1269 ◽  
Author(s):  
Yun Choi ◽  
Mun-Ju Shin ◽  
Kyung Kim
Keyword(s):  
Optimal Parameter ◽  
Computational Time ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Stream Network ◽  
Time Step ◽  
Simulation Results ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model

The choice of the computational time step (dt) value and the method for setting dt can have a bearing on the accuracy and performance of a simulation, and this effect has not been comprehensively researched across different simulation conditions. In this study, the effects of the fixed time step (FTS) method and the automatic time step (ATS) method on the simulated runoff of a distributed rainfall–runoff model were compared. The results revealed that the ATS method had less peak flow variability than the FTS method for the virtual catchment. In the FTS method, the difference in time step had more impact on the runoff simulation results than the other factors such as differences in the amount of rainfall, the density of the stream network, or the spatial resolution of the input data. Different optimal parameter values according to the computational time step were found when FTS and ATS were used in a real catchment, and the changes in the optimal parameter values were smaller in ATS than in FTS. The results of our analyses can help to yield reliable runoff simulation results.

scholarly journals The Wageningen Lowland Runoff Simulator (WALRUS): a lumped rainfall–runoff model for catchments with shallow groundwater

2014 ◽  
Vol 7 (1) ◽  
pp. 1357-1411 ◽  
Author(s):  
C. C. Brauer ◽  
A. J. Teuling ◽  
P. J. J. F. Torfs ◽  
R. Uijlenhoet
Keyword(s):  
Surface Water ◽  
Water Reservoir ◽  
Shallow Groundwater ◽  
Source Model ◽  
Rainfall Runoff ◽  
Time Step ◽  
Model Code ◽  
Distributed Models ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract. We present the Wageningen Lowland Runoff Simulator (WALRUS), a novel rainfall–runoff model to fill the gap between complex, spatially distributed models which are often used in lowland catchments and simple, parametric (conceptual) models which have mostly been developed for mountainous catchments. WALRUS explicitly accounts for processes that are important in lowland areas, notably (1) groundwater-unsaturated zone coupling, (2) wetness-dependent flow routes, (3) groundwater-surface water feedbacks and (4) seepage and surface water supply. WALRUS consists of a coupled groundwater-vadose zone reservoir, a quickflow reservoir and a surface water reservoir. WALRUS is suitable for operational use because it is computationally efficient and numerically stable (achieved with a flexible time step approach). In the open source model code default relations have been implemented, leaving only four parameters which require calibration. For research purposes, these defaults can easily be changed. Numerical experiments show that the implemented feedbacks have the desired effect on the system variables.

Spatial representation of stochastically generated rainfall for derived flood frequency analysis

2021 ◽  
Author(s):  
Luisa-Bianca Thiele ◽  
Ross Pidoto ◽  
Uwe Haberlandt
Keyword(s):  
Time Series ◽  
Spatial Representation ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Multiple Point ◽  
Rainfall Time Series ◽  
Rainfall Runoff ◽  
Areal Rainfall ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>For derived flood frequency analyses, stochastic rainfall models can be linked with rainfall-runoff models to improve the accuracy of design flood estimations when the length of observed rainfall and runoff data is not sufficient. The stochastic rainfall time series, which are used as input for the rainfall-runoff model, can be generated with different spatial resolution: (a) Point rainfall, which is stochastically generated rainfall at a single site. (b) Areal rainfall, which is catchment rainfall averaged over multiple sites before using the single-site stochastic rainfall model. (c) Multiple point rainfall, which is stochastically generated at multiple sites with spatial correlation before averaging to catchment rainfall. To find the most applicable spatial representation of stochastically generated rainfall for derived flood frequency analysis, simulated and observed runoff time series will be compared based on runoff statistics. The simulated runoff time series are generated utilizing the rainfall-runoff model HBV-IWW with an hourly time step. The rainfall-runoff model is driven with point, areal and multiple point stochastic rainfall time series generated by an Alternating Renewal rainfall model (ARM). In order to take into account the influence of catchment size on the results, catchments of different sizes within Germany are considered in this study.  While point rainfall may be applicable for small catchments, it is expected that above a certain catchment size a more detailed spatial representation of stochastically generated rainfall is necessary. Here, it would be advantageous if the results based on areal rainfall are comparable to those of the multiple point rainfall. The stochastically generation of areal rainfall is less complex compared to the stochastically generation of multiple point rainfall and extremes at the catchment scale may also be better represented by areal rainfall.    </p>

scholarly journals Impact of the Mean Areal Rainfall Calculation on a Modular Rainfall-Runoff Model

2020 ◽  
Vol 8 (12) ◽  
pp. 980
Author(s):  
Jose Valles ◽  
Gerald Corzo ◽  
Dimitri Solomatine
Keyword(s):  
Divide And Conquer ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
The Mean ◽  
Areal Rainfall ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
The Relationship ◽  
Runoff Model

Hydrological models are based on the relationship between rainfall and discharge, which means that a poor representation of rainfall produces a poor streamflow result. Typically, a poor representation of rainfall input is produced by a gauge network that is not able to capture the rainfall event. The main objective of this study is to evaluate the impact of the mean areal rainfall on a modular rainfall-runoff model. These types of models are based on the divide-and-conquer approach and two specialized hydrological models for high and low regimes were built and then combined to form a committee of model that takes the strengths of both specialized models. The results show that the committee of models produces a reasonable reproduction of the observed flow for high and low flow regimes. Furthermore, a sensitivity analysis reveals that Ilopango and Jerusalem rainfall gauges are the most beneficial for discharge calculation since they appear in most of the rainfall subset that produces low Root Mean Square Error (RMSE) values. Conversely, the Puente Viejo and Panchimalco rainfall gauges are the least beneficial for the rainfall-runoff model since these gauges appear in most of the rainfall subset that produces high RMSE value.

scholarly journals Flood modelling with a distributed event-based parsimonious rainfall-runoff model: case of the karstic Lez river catchment

2012 ◽  
Vol 12 (4) ◽  
pp. 1119-1133 ◽  
Author(s):  
M. Coustau ◽  
C. Bouvier ◽  
V. Borrell-Estupina ◽  
H. Jourde
Keyword(s):  
Statistical Prediction ◽  
Storm Event ◽  
Initial Condition ◽  
Rainfall Runoff ◽  
Time Step ◽  
Radar Rainfall ◽  
Flood Modelling ◽  
Rainfall Runoff Model ◽  
Event Based ◽  
Runoff Model

Abstract. Rainfall-runoff models are crucial tools for the statistical prediction of flash floods and real-time forecasting. This paper focuses on a karstic basin in the South of France and proposes a distributed parsimonious event-based rainfall-runoff model, coherent with the poor knowledge of both evaporative and underground fluxes. The model combines a SCS runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The efficiency of the model is discussed not only to satisfactorily simulate floods but also to get powerful relationships between the initial condition of the model and various predictors of the initial wetness state of the basin, such as the base flow, the Hu2 index from the Meteo-France SIM model and the piezometric levels of the aquifer. The advantage of using meteorological radar rainfall in flood modelling is also assessed. Model calibration proved to be satisfactory by using an hourly time step with Nash criterion values, ranging between 0.66 and 0.94 for eighteen of the twenty-one selected events. The radar rainfall inputs significantly improved the simulations or the assessment of the initial condition of the model for 5 events at the beginning of autumn, mostly in September–October (mean improvement of Nash is 0.09; correction in the initial condition ranges from −205 to 124 mm), but were less efficient for the events at the end of autumn. In this period, the weak vertical extension of the precipitation system and the low altitude of the 0 °C isotherm could affect the efficiency of radar measurements due to the distance between the basin and the radar (~60 km). The model initial condition S is correlated with the three tested predictors (R2 > 0.6). The interpretation of the model suggests that groundwater does not affect the first peaks of the flood, but can strongly impact subsequent peaks in the case of a multi-storm event. Because this kind of model is based on a limited amount of readily available data, it should be suitable for operational applications.

scholarly journals Calibration of a rainfall-runoff model using radar and raingauge data

2005 ◽  
Vol 2 ◽  
pp. 41-46 ◽  
Author(s):  
V. Lopez ◽  
F. Napolitano ◽  
F. Russo
Keyword(s):  
Measurement System ◽  
Small Scale ◽  
Rainfall Runoff ◽  
Radar Rainfall ◽  
Measurement Systems ◽  
Raingauge Data ◽  
Temporal And Spatial ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Rainfall Estimates

Abstract. Since raingauges give pointwise measurements the small scale variability of rainfall fields leads to biases on the estimation for the rainfall over the whole basin. In this context meteorological radars have several advantages since a single site is able to obtain coverage over a wide area with high temporal and spatial resolution. The purpose of this study is to compare the capability of the two different measurement systems in order to give correct input to drive rainfall-runoff models. Therefore a geomorphological model was calibrated, using firstly raingauge data and secondly radar rainfall estimates, for the Treja river basin. In this way it is possible to determine different sets of parameters and the influence of measurement system in hydrological modelling. The results shown that radar rainfall data is able to improve significantly hydrographs reconstructions.

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