scholarly journals Hydrological Modelling of the Cascina Scala Catchment

10.29007/d2g9 ◽  
2018 ◽  
Author(s):  
Enrico Creaco ◽  
Sara Todeschini ◽  
Marco Franchini
Keyword(s):  
Water Discharge ◽  
Hydrological Modelling ◽  
Model Parameters ◽  
Hydrological Response ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Clark Model ◽  
Rain Events ◽  
Event Based ◽  
Optimal Set

This paper presents results about the hydrological modelling of the Cascina Scala catchment. Following a preliminary analysis that proved the Nash cascade of reservoirs superior to the Clark model in the event-based rainfall-runoff simulation for this catchment, a new analysis was carried out to compare two different parameterization approaches applicable in gauged rain events. The former is based on estimating the optimal set of model parameters in each gauged event and then obtaining the ultimate set by averaging the values obtained over the whole group of events; the latter is based on estimating the optimal set of parameters directly on the whole group of gauged events. The results of the analysis proved the better performance of the latter, which enables better representation of the hydrological response of the catchment, evaluated in terms of water discharge pattern at the outlet.

scholarly journals INFLUENCE OF MODEL PARAMETERS' SPATIAL DISTRIBUTIONS ON RAINFALL-RUNOFF SIMULATION RESULTS

2000 ◽  
Vol 44 ◽  
pp. 217-222
Author(s):  
Y. TACHIKAWA ◽  
M. FUKUMITSU ◽  
Y. ICHIKAWA ◽  
M. SHIIBA ◽  
K. TAKARA
Keyword(s):  
Model Parameters ◽  
Spatial Distributions ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Simulation Results

scholarly journals Hydrological response to climate change of the Brahmaputra basin using CMIP5 general circulation model ensemble

2017 ◽  
Vol 9 (3) ◽  
pp. 434-448 ◽  
Author(s):  
A. K. M. Saiful Islam ◽  
Supria Paul ◽  
Khaled Mohammed ◽  
Mutasim Billah ◽  
Md. Golam Rabbani Fahad ◽  
...  
Keyword(s):  
Climate Change ◽  
Fresh Water ◽  
General Circulation ◽  
Water Discharge ◽  
Model Parameters ◽  
Projection Data ◽  
Hydrological Response ◽  
Model Ensemble ◽  
Brahmaputra Basin ◽  
Monsoon Flow

Abstract The Ganges–Brahmaputra–Meghna river system carries the world's third-largest fresh water discharge and Brahmaputra alone carries about 67% of the total annual flow of Bangladesh. Climate change will be expected to alter the hydrological cycles and the flow regime of these basins. Assessment of the fresh water availability of the Brahmaputra Basin in the future under climate change condition is crucial for both society and the ecosystem. SWAT, a semi-distributed physically based hydrological model, has been applied to investigate hydrological response of the basin. However, it is a challenging task to calibrate and validate models over this ungauged and poor data basin. A model derived by using gridded rainfall data from the Tropical Rainfall Measuring Mission (TRMM) satellite and temperature data from reanalysis product ERA-Interim provides acceptable calibration and validation. Using the SWAT-CUP with SUFI-2 algorithm, sensitivity analysis of model parameters was examined. A calibrated model was derived using new climate change projection data from the multi-model ensemble CMIP5 Project over the South Asia CORDEX domain. The uncertainty of predicting monsoon flow is less than that of pre-monsoon flow. Most of the regional climate models (RCMs) show an increasing tendency of the discharge of Brahmaputra River at Bahadurabad station during monsoon, when flood usually occurs in Bangladesh.

scholarly journals Mathematical Model of Hydrological Processes METQ98 and its Applications

1999 ◽  
Vol 30 (2) ◽  
pp. 109-128 ◽  
Author(s):  
A. Ziverts ◽  
I. Jauja
Keyword(s):  
Mathematical Model ◽  
River Basin ◽  
Input Data ◽  
Meteorological Data ◽  
Vapour Pressure Deficit ◽  
Model Parameters ◽  
Hydrological Response ◽  
Runoff Simulation ◽  
Mean Values ◽  
The Mathematical Model

The mathematical model METQ98 for runoff simulation is described. The METQ98 is developed from the model METUL (Krams and Ziverts 1993). Input data for the model are daily mean values of air temperature, precipitation and vapour pressure deficit. The spatial variability of surface processes is represented by dividing the river basin into hydrological response units (HRUs) depending on the land cover. The analysis of the model parameters is based on hydrological and meteorological data of the Vienziemite Brook basin. Also the influence of drainage on the model parameters is analysed. The results of application of the model to the Daugava River basin are presented.

scholarly journals Rainfall-runoff simulations in the Lukovska River Basin with the HEC-HMS model

2019 ◽  
pp. 33-60
Author(s):  
Ranka Eric ◽  
Andrijana Todorovic ◽  
Jasna Plavsic ◽  
Vesna Djukic
Keyword(s):  
River Basin ◽  
Optimal Parameter ◽  
Hydrologic Model ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Runoff Generation ◽  
Hydrologic Models ◽  
Generation Mechanisms ◽  
Event Based

Hydrologic models are important for effective water resources management at a basin level. This paper describes an application of the HEC-HMS hydrologic model for simulations of flood hydrographs in the Lukovska River basin. Five flood events observed at the Mercez stream gauge were available for modelling purposes. These events are from two distinct periods and two seasons with different prevailing runoff generation mechanisms. Hence the events are assigned to either ?present? or ?past?, and ?spring? or ?summer? group. The optimal parameter sets of each group are obtained by averaging the optimal parameters for individual events within the group. To assess model transferability, its applicability for simulation of flood events which are not considered in the model calibration, a cross-validation is performed. The results indicate that model parameters vary across the events, and that parameter transfer generally leads to considerable errors in hydrograph peaks and volumes, with the exception of simulation of summer events with ?spring? parameters. Based on these results, recommendations for event-based modeling are given.

A new hybrid data-driven model for event-based rainfall–runoff simulation

2016 ◽  
Vol 28 (9) ◽  
pp. 2519-2534 ◽  
Author(s):  
Guangyuan Kan ◽  
Jiren Li ◽  
Xingnan Zhang ◽  
Liuqian Ding ◽  
Xiaoyan He ◽  
...  
Keyword(s):  
Data Driven ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Hybrid Data ◽  
Event Based

scholarly journals Rainfall-runoff modelling using adaptive neuro-fuzzy inference system

2020 ◽  
Vol 17 (2) ◽  
pp. 1117
Author(s):  
Nurul Najihah Che Razali ◽  
Ngahzaifa Ab. Ghani ◽  
Syifak Izhar Hisham ◽  
Shahreen Kasim ◽  
Nuryono Satya Widodo ◽  
...  
Keyword(s):  
Time Series Data ◽  
Fuzzy Inference ◽  
Water Discharge ◽  
Series Data ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Inference System ◽  
Runoff Forecasting ◽  
Neuro Fuzzy ◽  
Pros And Cons

<span lang="EN-GB">This paper discusses the working mechanism of ANFIS, the flow of research, the implementation and evaluation of ANFIS models, and discusses the pros and cons of each option of input parameters applied, in order to solve the problem of rainfall-runoff forecasting. The rainfall-runoff modelling considers time-series data of rainfall amount (in mm) and water discharge amount (in m<sup>3</sup>/s). For model parameters, the models apply three triangle membership functions for each input. Meanwhile, the accuracy of the data is measured using the Root Mean Square Error (RMSE). Models with good performance in training have low values of RMSE. Hence, the 4-input model data is the best model to measure prediction accurately with the value of RMSE as 22.157. It is proven that ANFIS has the potential to be used for flood forecasting generally, or rainfall-runoff modelling specifically.</span>

scholarly journals Effects of Land Use Changes on the Runoff in the Landscape Based on Hydrological Simulation in HEC-HMS and HEC-RAS Using Different Elevation Data

2016 ◽  
Vol 64 (3) ◽  
pp. 759-768
Author(s):  
Josef Divín ◽  
Tomáš Mikita
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Hydrological Modelling ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Hydrological Simulation ◽  
Software Interface ◽  
Elevation Data ◽  
Data Source ◽  
Effects Of Land Use

The aim of this paper is to determine the effects of land use changes on the runoff in the landscape by means of hydrological modelling. Our partial aim is also to determine the effect of different elevation data and define optimal data sources for this modelling. The research was conducted on the Starozuberský stream experimental watershed. For comparing elevation models, three scenarios were developed with different input data. Based on a comparison of these models an optimal data source for hydrological modelling was selected. To simulate the change in land use, we have created two scenarios based either upon the current land use and historical data from the fifties of the twentieth century. Comparison was carried out using the HEC-HMS software interface for rainfall-runoff simulation and HEC-RAS for the flooding simulation. Data for the simulation were prepared using the ESRI ArcGIS extensions, namely HEC- GeoHMS and HEC-GeoRAS.

scholarly journals A Review on Rainfall Runoff Simulation at Ungauged Catchment

2018 ◽  
Vol 7 (4.35) ◽  
pp. 162
Author(s):  
W.N.C.W. Zanial ◽  
M.A. Malek ◽  
M.N.M. Reba
Keyword(s):  
Alternative Methods ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Ungauged Catchments ◽  
Ungauged Catchment ◽  
Rain Gauges ◽  
Other Information ◽  
Physically Based ◽  
Set Up

Ungauged catchment occurs when no runoff data are available or when very few ground rain gauges are located in a huge catchment.  For these catchments, the parameters to be used in rainfall‐runoff models cannot be attained just by adjusting runoff information and thus should be procured by different techniques. Show parameters that require orientation are normally transposed from comparable measured catchments. The rainfall runoff simulation is very important to estimate and predict the flow in ungauged catchment. This investigation reviews ideas to differentiate hydrological comparability for transposing parameters from a gauged to an ungauged catchment. Model parameters that are physically based are generally derived from other information close to the ungauged catchment of intrigue. The primary challenge with rainfall‐runoff demonstrating in ungauged catchments is the absence of neighborhood ground precipitation and streamflow information to be utilized in aligning the proposed show parameters. Parameter alignment is useful since adjustment can represent the impacts of hydrological set up in a specific catchment. Since hydrological models are especially reliant on their limit conditions, the alignment practice directed can modify the predispositions of info information utilized. Parameters' adjustment can fundamentally improve the execution of rainfall‐runoff models since it included media properties of soil and vegetation which are exceptionally heterogeneous and basically are in every case inadequately known. Alternative methods for ungauged catchments are required which are the subject of this study. This study summarizes the important methods used in an ungauged catchments, discusses the issues of using satellite data as a substitute input to rainfall‐runoff models and its comparison with point scale ground data.

scholarly journals Hydrological modelling under climate change considering nonstationarity and seasonal effects

2015 ◽  
Vol 47 (2) ◽  
pp. 260-273 ◽  
Author(s):  
Kue Bum Kim ◽  
Hyun-Han Kwon ◽  
Dawei Han
Keyword(s):  
Hydrological Model ◽  
Hydrological Modelling ◽  
Seasonal Effects ◽  
Model Parameters ◽  
Observation Data ◽  
Rainfall Runoff ◽  
Climate Condition ◽  
The Future ◽  
Rainfall Runoff Model ◽  
Runoff Model

Traditional hydrological modelling assumes that the catchment does not change with time. However, due to changes of climate and catchment conditions, this stationarity assumption may not be valid in the future. It is a challenge to make the hydrological model adaptive to the future climate and catchment conditions. In this study IHACRES, a conceptual rainfall–runoff model, is applied to a catchment in southwest England. Long observation data (1961–2008) are used and seasonal calibration (only the summer) has been done since there are significant seasonal rainfall patterns. Initially, the calibration is based on changing the model parameters with time by adapting the parameters using the step forward and backward selection schemes. However, in the validation, both models do not work well. The problem is that the regression with time is not reliable since the trend may not be in a monotonic linear relationship with time. Therefore, a new scheme is explored. Only one parameter is selected for adjustment while the other parameters are set as the fixed and the regression of one optimised parameter is made not only against time but climate condition. The result shows that this nonstationary model works well both in the calibration and validation periods.

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