Seven Techniques that you will learn when you enrol forMTech in Hydroinformatics Engineering

Hydro informatics is the study of the application of data science and information technology to the development of water resources. The Master's program is a two-year interdisciplinary degree that accepts applications from Civil, Electrical, Mechanical, and other disciplines. Admission is available via CCMT 2023 and DASA 2023.

After completing the course, you will have learned the following techniques:

Techniques for Multi-Criteria Decision Making such as AHP, ANP, ELECTRE, PROMETHEE, and others.

River Surveyor, Micro ADV, and Multi-Parameter Water Quality Sensor are examples of water-related instruments.

Algorithms Based on Decision Trees

Image Processing and Geographical Information System

Optimization Methods, including Bio-Inspired Optimisation Methods

Polynomial Neural Networks are a type of Artificial Neural Network (ANN).

The Internet of Things (IoT)

and their applications in the development of water resources.

The program also includes a one-year real-world project opportunity.

Five open source free hydrologic models that you can use to model runoff of micro to macro watersheds

The principal objective of hydrologic models is to forecast the runoff of a surface water body, especially dendritic systems like rivers, streams, etc. The inputs to these models are generally Rainfall/Precipitation, Soil Characteristics, and other Climatic parameters like evapotranspiration, humidity, etc. LULC and geo-morphology are also used as the required input parameters of the hydrologic models. Both input and output of these models are temporally as well as spatially variable. Now the resolution varies with different models. Some models consider all the sub-basins to be a single watershed and determine the output based on the characteristics of this single watershed(lumped).In contrast, some other models will consider the {impact|effect} of each of the sub-basins on the central outflow of the watershed(distributed).In a few models, the entire watershed is divided into grids or units of uniform dimension. However, the accuracy is highest for the models, which considers the {impa...

Autocorrelation in Water Resource Development

A new article was posted in HydroGeek : Five Most Recent Research Works on Autocorrelation in Water Resource Management Autocorrelation is the correlation between two part of a single data series and is useful when the trendability of a parameter is approximated with the help of data. Most used in water research study. This article highlights the most recent research works on the application of autocorrelation on water resource development studies. Click here to read it in HydroGeek @Mrinmoy's Page @data_hydrology , @Merchandise or @ @products_sustainability Add to Listy /

First Edition of HydroGeek Newsletter for the year 2023 Launched

First Edition of HydroGeek Launched You will be happy to know that the first edition of the HydroGeek Newsletter of the year 2023 is launched The content of the first edition is as given below : Cover Feature: The Free Software for Water Resource Management Feature 1: A case study of the ELECTRE Decision-Making Method in Water Resource: How to use the technique in the selection of the best solution among the available many. Feature 2: Project Idea on Climate Change Impact Studies Feature 3: Instrument Recommendation: An instrument that can monitor more than seven water quality parameters in real-time Regular Features: News and Views, Recommended New and Old Books, More Project Ideas, etc. Click here to access it. #hydrology #hydroinformatics #newsletter @data_hydrology , @Merchandise or @ @products_sustainability Add to Listy /