Hydrology Newsletter

We all know that most of the hydrological variables are time-dependent. It changes with time. Artificial Neural Network on the other hand has been found to perform best for time-dependent problems. Whether there is any relationship between time-dependent variables and neural network is unknown but it can be assured that neural networks can be used to develop models for the prediction of hydrological variables with better accuracy compared to other hydrological models. The post below depicts the methodology for the application of neural networks in the development of hydrological models. This is reposted from my Water and Energy Nexus Blog : https://waterandenergynexus.blogspot.com/2013/04/how-to-predict-time-dependent-variables.html Thanking you, Mrinmoy  My ResearchGate Id : Mrinmoy_Majumder Home Page:  http://www.mrinmoymajumder.com   Author of: Lecture Notes on MCDM Indian Link  ;  Global Link :

The summer season can be utilized by the pursue of research on the following few ideas. The ideas are developed based on the type of audience that means whether  B.Tech. or M.Tech, Students or Teachers, etc. students will enjoy doing these topics to complete their PG or UG requirement. Title: Short Term Rainfall forecasting by ANN-MCDM Approach Pre-requisite : Various data of climatic parameters, land use pattern of the region, cloud type and density for 1 to 5 days before the day of forecast. Justification of the Study : Rainfall can impact the output of many industrial and agricultural processes. Even the energy output from the power sector is affected by the climatic parameter. Short term rainfall forecasting is an important concept as it can help the planners of this industry to adjust their input so that the required output will remain unaffected. Brief Methodology : A widescale expert and local survey followed by a literature review have to be conducted to identify the p...

"A flood is an overflow of water on normally dry ground". This is most commonly due to an overflowing river, a dam break, snow-melt, or heavy rainfall. Tsunamis, storm surge, or coastal flooding are some of the examples of common flooding whereas instances of extreme flooding includes the flood  in 1931 at China which killed between 2,000,000 and 4,000,000 people.In 2002, Texas flood which was caused by a reservoir overflow. In just three days, the floodwaters carved canyons measuring 1.4 mile (2.2 kilometres) long and  20-foot-(6 meters)-deep. Floods can be measured for height, peak discharge, area inundated, and volume of flow. Due to the ability of this extreme event to cause disasters, it is important to predict the event well in advance or at the time of designing flood control structures.Flood is a result of a discharge;generally peak discharge;which the drainage network can not hold and eventually overflows and causes inundation.  There are various methods to estim...

Senior Research Fellow opportunity in BITS Pilani

Journal Title : International Journal of Water and Informatics Keywords : water resource management, informatics, soft computing tools,optimal management of water resources,artificial neural networks, Group method of data handling, statistical charts, decision making, predictive modeling, geographical information systems, image processing. About the Journal : In the recent years, the problem of water scarcity is solved by the application of various soft computing tools and innovative managerial decisions.The emphasis is now placed in the optimal management of the existing resources rather than providing options to generate new sources.The measures like prevention of wastage and pollution along with the intelligent allocation of the resources are stressed to mitigate the climatic impact on the available water sources.The journal accepts original research works related to the application of soft computing tools and nature based algorithms for optimal utilization of water resources.R...

The selection of ideal conceptual hydrologic model for prediction of surface runoff from any type of watershed is useful for the estimation of future hydrologic conditions of the basin.The predicted runoff is also important for design of hydraulic structure,preparation of watershed management plans ,disaster management etc. related activities.The future runoff will give an idea of future uncertainties that may trouble the watershed and its inhabitants.The hydrologic models which follows the basic physical laws of water balance to estimate the desired output cannot exactly estimate the runoff.There will be some differences with the actual situation and the predicted one.The deviations between the two is allowable but to a certain extent.There are many factors for this deviation.Some models are suitable for some specific types of watersheds.The availability of required dataset is also another important issue.The equalizing constants that are used to linearize interrelationships are also...