Influence of the Predictive Rainfall/Runoff Model Accuracy on an Optimal Water Resource Management Strategy

2019 ◽  
pp. 168-192
Author(s):  
Baya Hadid ◽  
Eric Duviella
Keyword(s):  
Resource Management ◽  
Water Resource ◽  
Management Strategy ◽  
Water Resource Management ◽  
Rainfall Runoff ◽  
Model Accuracy ◽  
Rainfall Runoff Model ◽  
Runoff Model

scholarly journals Rainfall-runoff modelling in small and middle-large catchments - an overview

Geografie ◽  
2006 ◽  
Vol 111 (3) ◽  
pp. 305-313
Author(s):  
Michal Jeníček
Keyword(s):  
Information Technologies ◽  
Water Resource Management ◽  
Base Flow ◽  
Rainfall Runoff ◽  
Effective Protection ◽  
Typical Structure ◽  
Linear Cascade ◽  
Modelling Techniques ◽  
Rainfall Runoff Model ◽  
Runoff Model

A rainfall-runoff modelling is nowadays a dynamically developing department of hydrology and water management. This development is caused by a rapid progress of computers and information technologies. This evolution provides the mankind with new possibilities to use water as its basic need and at the same time to evolve an effective protection against it. The aim of this article is to give some basic information about rainfall-runoff modelling, various approaches to it, methods and possibilities of application. This kind of information may help the user with the choice of the suitable rainfall-runoff model. Rainfall-runoff or hydraulic models have many different applications, e.g. in operational hydrology, water resource management or in research. Typical structure of any rainfall-runoff model, come out from a simplified catchment structure as a system of vertical ordered reservoirs, which form a linear cascade model. The main reservoirs are precipitation, evapotranspiration (together with interception), direct runoff, runoff in unsaturated zone (interflow), base flow and channel flow. For computation of processes running in each of these reservoirs (filling or drainage), many equations (model techniques) are applied. This structure and presented modelling techniques are used in the most common models like HEC-HMS, MIKE-SHE, Sacramento (SAC-SMA), NASIM, HBV and many others.

Effect of input variables on rainfall-runoff modeling using a deep learning method

2021 ◽  
Author(s):  
Kazuki yokoo ◽  
Kei ishida ◽  
Takeyoshi nagasato ◽  
Ali Ercan
Keyword(s):  
Deep Learning ◽  
Air Temperature ◽  
Meteorological Variables ◽  
Learning Method ◽  
Rainfall Runoff ◽  
Model Accuracy ◽  
Runoff Modeling ◽  
Input Variables ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>In recent years, deep learning has been applied to various issues in natural science, including hydrology. These application results show its high applicability. There are some studies that performed rainfall-runoff modeling by means of a deep learning method, LSTM (Long Short-Term Memory). LSTM is a kind of RNN (Recurrent Neural Networks) that is suitable for modeling time series data with long-term dependence. These studies showed the capability of LSTM for rainfall-runoff modeling. However, there are few studies that investigate the effects of input variables on the estimation accuracy. Therefore, this study, investigated the effects of the selection of input variables on the accuracy of a rainfall-runoff model by means of LSTM. As the study watershed, this study selected a snow-dominated watershed, the Ishikari River basin, which is in the Hokkaido region of Japan. The flow discharge was obtained at a gauging station near the outlet of the river as the target data. For the input data to the model, Meteorological variables were obtained from an atmospheric reanalysis dataset, ERA5, in addition to the gridded precipitation dataset. The selected meteorological variables were air temperature, evaporation, longwave radiation, shortwave radiation, and mean sea level pressure. Then, the rainfall-runoff model was trained with several combinations of the input variables. After the training, the model accuracy was compared among the combinations. The use of meteorological variables in addition to precipitation and air temperature as input improved the model accuracy. In some cases, however, the model accuracy was worsened by using more variables as input. The results indicate the importance to select adequate variables as input for rainfall-runoff modeling by LSTM.</p>

Application of snowmelt runoff model for water resource management

2011 ◽  
Vol 25 (24) ◽  
pp. 3735-3747 ◽  
Author(s):  
Mohsin Jamil Butt ◽  
Muhammad Bilal
Keyword(s):  
Resource Management ◽  
Water Resource ◽  
Water Resource Management ◽  
Snowmelt Runoff ◽  
Runoff Model

scholarly journals Combining a rainfall–runoff model and a regionalization approach for flood and water resource assessment in the western Po Valley, Italy

2019 ◽  
Vol 65 (3) ◽  
pp. 348-370 ◽  
Author(s):  
Alessio Cislaghi ◽  
Daniele Masseroni ◽  
Christian Massari ◽  
Stefania Camici ◽  
Luca Brocca
Keyword(s):  
Water Resource ◽  
Resource Assessment ◽  
Rainfall Runoff ◽  
Po Valley ◽  
Rainfall Runoff Model ◽  
Water Resource Assessment ◽  
Runoff Model

Considerations in managing the fill rate of the Grand Ethiopian Renaissance Dam Reservoir using a system dynamics approach

2016 ◽  
Vol 14 (1) ◽  
pp. 33-43 ◽  
Author(s):  
Bruce Keith ◽  
David N Ford ◽  
Radley Horton
Keyword(s):  
Climate Change ◽  
Resource Management ◽  
System Dynamics ◽  
River Basin ◽  
Water Resource ◽  
Stream Flow ◽  
Management Strategy ◽  
Water Resource Management ◽  
Nile River ◽  
Fill Rate

The purpose of this study is to evaluate simulated fill rate scenarios for the Grand Ethiopian Renaissance Dam while taking into account plausible climate change outcomes for the Nile River Basin. The region lacks a comprehensive equitable water resource management strategy, which creates regional security concerns and future possible conflicts. We employ climate estimates from 33 general circulation models within a system dynamics model as a step in moving toward a feasible regional water resource management strategy. We find that annual reservoir fill rates of 8–15% are capable of building hydroelectric capacity in Ethiopia while concurrently ensuring a minimum level of stream flow disruption into Egypt before 2039. Insofar as climate change estimates suggest a modest average increase in stream flow into the Aswan, climate changes through 2039 are unlikely to affect the fill rate policies. However, larger fill rates will have a more detrimental effect on stream flow into the Aswan, particularly beyond a policy of 15%. While this study demonstrates that a technical solution for reservoir fill rates is feasible, the corresponding policy challenge is political. Implementation of water resource management strategies in the Nile River Basin specifically and Africa generally will necessitate a national and regional willingness to cooperate.

Sustainable Wastewater Reuse Technique for Irrigation

2014 ◽  
Vol 955-959 ◽  
pp. 2419-2422
Author(s):  
Shou Gang Zhao ◽  
Na Li ◽  
Bojin Hao
Keyword(s):  
Resource Management ◽  
Health Risk ◽  
Environmental Impacts ◽  
Water Resource ◽  
Management Strategy ◽  
Water Resource Management ◽  
Environmental Awareness ◽  
Wastewater Reuse ◽  
Human Being ◽  
Agriculture Irrigation

Wastewater reuse has drawn increasing attention worldwide as an integral part of water resource management due to increasing scarcity of freshwater resources and growing environmental awareness. At present, wastewater was mainly applied in agriculture irrigation in many countries. But wastewater reuse also will bring with a series of issues, such as environmental impacts and human being health risk. How to ensure sustainable wastewater reuse for irrigation is a very important issue. The essay analysed technique support and management strategy of sustainable wastewater reuse for irrigation.

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