Research

Courses Undertaken During Ph.D

Course Code

CE 513
CE 551
CE 570
CE 593

Course Name

Statistical Methods in Civil Engineering
Surface Water Hydrology
River Engineering
Advanced Remote Sensing

Grade

AB
AA CPI
AS 9.77
AA

Teaching Experience

July-Nov 2022: Teaching Assistant for the course Surface Water Hydrology CE-551 in the Civil Engineering Department Indian Institute of Technology, Guwahati

Jan-May 2022:Teaching Assistant for the course Engineering Hydrology Lab CE-321 in the Civil Engineering Department Indian Institute of Technology, Guwahati

Jun-Nov 2020: Teaching Assistant for the course Engineering Graphics CE-101 in the Civil Engineering Department Indian Institute of Technology, Guwahati

Jan-May 2020: Teaching Assistant for the Hydrology Laboratory Course CE-321 in the Civil Engineering Department Indian Institute of Technology, Guwahati

2018-19: Teaching Assistant for the course Water Quality Engineering in the Civil Engineering Department National Institute of Technology, Rourkela

Teaching in the neighboring institute as per PMRF modalities

Nov 2022- Present: Teaching Assistant for the course Software Application Water Resources in the Civil Engineering Department Assam Engineering College, Guwahati

May-Sep 2022: Teaching Assistant for the course Software Application Water Resources in the Civil Engineering Department Assam Engineering College, Guwahati

Nov 21 - March 22: Teaching Assistant for the course Software Application Water Resources in the Civil Engineering Department Assam Engineering College, Guwahati

Workshops Attended

TEQIP III sponsored workshop on " Computer Application In Water Resources Engineering" conducted by NIT Rourkela in October 2018.
Author Workshop Organized by Wiley in collaboration with NIT Rourkela on November 21, 2018.
TEQIP III sponsored workshop on " Advances in Integrated Water Resources Management" conducted by IIT Guwahati in December 2019.
Workshop on "Artificial Intelligence for Detection and Attribution of Climate Extremes" by International Centre for Theoretical Physics (Italy) is virtually attended during the period 20 June 2022-1 July 2022.

Publications

Journal

Ashok, S. P., & Pekkat, S. (2022). A systematic quantitative review on the performance of some of the recent short-term rainfall forecasting techniques. Journal of Water and Climate Change, 13(8), 3004-3029.

Priya Shejule and Sreeja Pekkat (2022). Performance Assessment of Rainfall Forecasting Models Based on Machine Learning Techniques and Singular Spectrum Analysis. Expert Systems with Applications (Submitted)

Conference

Priya Shejule; Sreeja Pekkat (2022) "Rainfall Forecast by Identification of Characteristic Components of Rainfall Using Singular Spectrum Analysis" Asia Oceania Geosciences Society 2022, 01 Aug - 05 Aug, Singapore.

Priya Shejule; Sreeja Pekkat (2022), Oral presentation titled “ Short-term Rainfall Forecasting Module Using Singular Spectrum Analysis” at The American Geophysical Union (AGU) Fall Meeting 2022, 12-16 Dec.

Priya Shejule; Sreeja Pekkat (2022) “Analysis of Characteristics of Meteorological Parameters using Ensemble Empirical Mode Decomposition” paper presented at the International Conference Sustainable Technologies for River Erosion Alleviation and Management (STREAM) 14-15th Dec 2022.

Book Chapter

Shejule, P., Khuntia, J. R., & Khatua, K. K. (2022) "Calibrating coefficients of emerged vegetative open channel flow" In River Hydraulics (pp. 249-260). Springer, Cham.

Research Overview

Rainfall forecasting is one of the challenging research problems. It has a high impact on human beings, socio-economic status, global warming and global well-being. It is even associated with sustainable development goals put forth by the United Nations.
Rainfall disasters affect our economic progress, and therefore, rainfall forecasting has been an alluring topic for researchers throughout the country. An accurate forecast is crucial to minimize the impact of sudden and heavy rainfall by taking early actions regarding ongoing construction activities, flight operations and crop management. The northeast region of India is more prone to flash floods due to its location in the eastern Himalayas. Recently, Uttarakhand state faced a disastrous flash flood due to glacier burst. Every year, northeast India is exposed to extreme flood events, which indirectly affects the economy of our nation. It is therefore necessary to develop an innovative approach to predict urban flooding.
Rainfall is chaotic in nature. On account of its high temporal and spatial variation, the forecast process remains challenging. Rainfall forecasting at daily time step is still a difficult task for researchers. This research aims to create a powerful rainfall-forecasting model by combining different methods to forecast rainfall in real-time, improving the forecast limitations of earlier research.

Research Summary

The objective is to identify and make accurate daily rainfall forecasts without any lag effect, thereby overcoming the drawback of existing techniques.

Real-time forecast of rainfall helps in issuing an early warning and implementing resources to avoid the damage.
For the better forecast, it is necessary to understand the nature/ characteristics of rainfall series.
The rainfall process is composed of many sub-processes, and hence a single model cannot achieve the accurate forecast. Thus, there is a need to come up with a hybrid model to forecast rainfall.
Earlier researchers have applied hybrid models to rainfall forecast and obtained better performance than that of single model. This urges the application of hybrid models. This is one of the objectives of the research.
Nowadays urban flooding is gaining attention from the researchers all over, as it is a universal phenomenon and has several adverse effects.
Global climate change is responsible for changed weather patterns and extreme rainfall events. Thus, the incorporation of rainfall forecast in flood warning systems is recommended as it provides sufficient time for the flood control.

Fig 1. Flowchart depicting a systematic quantitative review of rainfall forecasting techniques

Review on short term rainfall forecasting techniques

Rainfall forecasting is a high-priority research problem due to the complex interplay of multiple factors. Extensive literature survey is performed on different rainfall forecasting techniques. A review paper written on different short-term rainfall forecasting methods and factors affecting the forecast accuracy. The impact of factors such as rainfall threshold, meteorological parameters, topography, algorithm techniques, geographic location, the horizontal resolution of the model, and lead-time affecting the rainfall forecast efficiency has been examined in this review. It also helps in mapping the findings related to rainfall forecasting at different time-scale.