Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
by
Ramos, Tiago Brito
, Oliveira, Ana Ramos
, Pinto, Lígia
, Neves, Ramiro
in
Analysis
/ Catchments
/ Dams
/ Dry season
/ Hydrologic models
/ Hydrology
/ Hydrometric stations
/ Inflow
/ Long short-term memory
/ Modelling
/ Natural flow
/ Neural networks
/ Nonlinear control
/ Outflow
/ Rainy season
/ Reservoirs
/ River basins
/ Rivers
/ Stream discharge
/ Stream flow
/ Streamflow
/ Streamflow estimation
/ Time series
/ Water inflow
/ Water outflow
/ Watershed management
/ Watersheds
/ Wet season
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
by
Ramos, Tiago Brito
, Oliveira, Ana Ramos
, Pinto, Lígia
, Neves, Ramiro
in
Analysis
/ Catchments
/ Dams
/ Dry season
/ Hydrologic models
/ Hydrology
/ Hydrometric stations
/ Inflow
/ Long short-term memory
/ Modelling
/ Natural flow
/ Neural networks
/ Nonlinear control
/ Outflow
/ Rainy season
/ Reservoirs
/ River basins
/ Rivers
/ Stream discharge
/ Stream flow
/ Streamflow
/ Streamflow estimation
/ Time series
/ Water inflow
/ Water outflow
/ Watershed management
/ Watersheds
/ Wet season
2023
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
by
Ramos, Tiago Brito
, Oliveira, Ana Ramos
, Pinto, Lígia
, Neves, Ramiro
in
Analysis
/ Catchments
/ Dams
/ Dry season
/ Hydrologic models
/ Hydrology
/ Hydrometric stations
/ Inflow
/ Long short-term memory
/ Modelling
/ Natural flow
/ Neural networks
/ Nonlinear control
/ Outflow
/ Rainy season
/ Reservoirs
/ River basins
/ Rivers
/ Stream discharge
/ Stream flow
/ Streamflow
/ Streamflow estimation
/ Time series
/ Water inflow
/ Water outflow
/ Watershed management
/ Watersheds
/ Wet season
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
Journal Article
Direct integration of reservoirs' operations in a hydrological model for streamflow estimation: coupling a CLSTM model with MOHID-Land
2023
Request Book From Autostore
and Choose the Collection Method
Overview
Knowledge about streamflow regimes and values is essential for different activities and situations in which justified decisions must be made. However, streamflow behavior is commonly assumed to be non-linear, being controlled by various mechanisms that act on different temporal and spatial scales, making its estimation challenging. An example is the construction and operation of infrastructures such as dams and reservoirs in rivers. The challenges faced by modelers to correctly describe the impact of dams on hydrological systems are considerable. In this study, an already implemented solution of the MOHID-Land (where MOHID stands for HYDrodinamic MOdel, or MOdelo HIDrodinâmico in Portuguese) model for a natural flow regime in the Ulla River basin was considered as a baseline. The watershed referred to includes three reservoirs. Outflow values were estimated considering a basic operation rule for two of them (run-of-the-river dams) and considering a data-driven model of a convolutional long short-term memory (CLSTM) type for the other (high-capacity dam). The outflow values obtained with the CLSTM model were imposed in the hydrological model, while the hydrological model fed the CLSTM model with the level and the inflow of the reservoir. This coupled system was evaluated daily using two hydrometric stations located downstream of the reservoirs, resulting in an improved performance compared with the baseline application. The analysis of the modeled values with and without reservoirs further demonstrated that considering dams' operations in the hydrological model resulted in an increase in the streamflow during the dry season and a decrease during the wet season but with no differences in the average streamflow. The coupled system is thus a promising solution for improving streamflow estimates in modified catchments.
This website uses cookies to ensure you get the best experience on our website.