Current Work

The theme of my doctoral work is Modelling Evolution of River Drainage Networks Patterns. I am studying Randomness and Self-organization in drainage network morphology and landscape evolution modelling.

Motivation and Objective:

River networks have been studied in geosciences and hydrology for many theoretical and practical purposes. It is important to have a quantitative understanding of drainage network morphology for modelling the processes involved in landscape evolution and modelling the landscape’s hydrological response. I am trying to model the River network evolution process and explain why river networks organize themselves into self-similar tree-like patterns which follow certain scaling laws. 

We have proposed a new modeling framework that explains drainage network evolution considering certain key physical processes associated with randomness. We call it "Probabilistic Model to Explain Drainage Network Evolution" 

1. The probabilistic Network Evolution Model

The model follows the growth of drainage networks in the headward direction based on probabilistic decisions. The model has two free parameters and is demonstrated considering a planar matrix. The two parameters direct the probability for network growth from outlet boundaries. The network evolution can be demonstrated as below for a 250*250 matrix:

Results Achieved

• It was shown that drainage network evolution can be modelled considering certain key physical processes associated with randomness. 

• The two parameters of the proposed model provide flexibility to generate networks with different shapes and characteristics.

• Modelled Networks follow the power-law scaling relationships as observed in natural networks.

• The modelled drainage networks also follow the similar distribution of independent basin areas.

• We have shown that the approach of randomness coupled with key physical processes for modeling complex systems has been effective for modeling drainage network evolution.

• The work is published in Advances in Water Resources: https://doi.org/10.1016/j.advwatres.2022.104342

• The modelled networks can be used as realistic networks for other modelling studies

2. Efficient Channel Network Evolution Model

Channel networks across fluvial landscapes, traditionally viewed as evolving to minimize energy, are actually emerging due to a hierarchical role of randomness in landscape evolution, as elucidated by our study. Our model shows that efficient channel formation is more a consequence of adaptive processes involving heterogeneity rather than indented optimization process. 

Evolution of a sample random network towards efficient networks is shown below.  Most efficient networks are obtained when randomness parameter  𝜂 is  0.5 highlighting the importance of balance between randomness and stability to reach most optimal conditions.

Highlights and future scope:

• The model provides a way to generate optimal channel networks (as efficient as the ones generated by optimization algorithm) without using any optimization algorithm. Hence the model can be utilized in other network problems as well where optimization is required.

• Currently we are applying similar ideas for designing optimal water distribution network  and we are getting positive preliminary results

Preprint  of this work is available here:  https://doi.org/10.22541/essoar.169833417.71840079/v1

3. Power Law Distribution of Independent Basin Areas in Fluvial Landscapes

With the analysis of 25 islands, we show the power law behavior in distribution of areas of independent basins of islands draining to oceans. We further show that the power law exponent is dependent on the island's boundary, characterized by the fractal dimension and Gravelius compactness coefficient, both of which exhibit a positive correlation with the basin distribution exponent. Furthermore we employ our initial probabilistic model to show that how headward growth mechanism is probably responsible for the emergence of power law in basin area distribution.  

Preprint for this work is available here: https://doi.org/10.22541/essoar.170916081.14067477/v1

Past Projects

B Tech Project: (2018-19)

Watershed Analysis and Water demand modelling for village Chhagola using water budgeting model developed by CTARA 

Guide-Prof. Milind Sohoni CTARA IITB,  Prof. Basudev Biswal, Civil Department IITB

>The project aimed to provide a water budget for water conservation solutions for Chhagola village in Jhabua district of M.P. which is suffering from water scarcity issues being on most upstream side of the watershed.

>Carried out morphological analysis of Chhagola watershed and estimated surface water balance for project area for the Kharip season accessing cropping pattern of previous years which gave idea for Rabi water balance in project area and suggested the cropping patterns

Other Projects:

Psychological Analysis of 16 Samskaras in Indian Tradition through developmental psychology perspective   (May-June 2018)

Guide-Prof Ashish Pandey SJM SOM IITB  

>Research discovered the psychological significance behind the Samskaras or the rituals performed in Hindu tradition and gazed on how and why they serve any purpose at different developmental stages of life

Time Perception -Literature Review  (Nov-Dec 2018)

Guide- Prof. Rashmi Gupta IIT Bombay

> Reviewed Literature on how time perception is affected in human being with more focus on effect of emotions on time perception

Crowd Controller (2015)

Electronics Department, MES Garware College, Pune Guide- Prof Sudhir Bhosale

>Developed a device with electronic printed circuit board to implement logic which measures the inflow  and outflow of crowd and gives indication for further allowance of entry and exit of crowd