Faculty Publications

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Mapping of 2018 Flood and Estimation of Future Flood Inundation Region for Vembanad Lake System in Kerala, India Using Sentinel-1 SAR Imagery
(Springer Science and Business Media Deutschland GmbH, 2024) Kulithalai Shiyam Sundar, K.S.S.; Kundapura, S.
Floods have claimed the lives of countless people and caused significant property damage, jeopardizing their livelihoods. The study area is the Vembanad Lake System in Kerala, India has faced severe flooding in 2018 due to torrential rainfall. Considering that Google Earth Engine (GEE) streamlines and simplifies the complex and time-consuming pre-processing of SAR images, this paper evaluates flood inundation mapping using Sentinel-1 SAR data for 2018. The flood inundation zone for the study is calculated using the Land Use Land Cover (LULC) map for 2018 and the forecasted LULC for 2035 and 2050. Hence, the research assesses the areas affected by floods in 2018 and those that may experience flooding of a similar degree in the near future. Thus, the extent of flood inundation during the 2018 floods and the potential flood inundation region for future LULC in 2035 and 2050 are determined. From the analysis, 14.7 km2 of built-up area was inundated during the 2018 floods. The 2018 flood event is used to quantify the flood that may inundate the future LULC in 2035 and 2050; it is found that the flood will affect about 19.87 km2 and 23.32 km2 of the built-up region, respectively. According to the study, the built-up area impacted by the flooding will increase by 34.99% and 58.4% from 2018 to 2035 and 2050, respectively. Examining the flood-prone areas and potential flood-affected areas in the future will be of great use to planners in their efforts to forewarn of an impending tragedy. Â© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Recent Changes in Hydrometeorological Extremes in the Bilate River Basin of Rift Valley, Ethiopia
(American Society of Civil Engineers (ASCE), 2023) Lambe, B.T.; Kundapura, S.
The hydroclimatic extremes such as floods and droughts have been causing damage and losses with rising frequency than ever before. The human-induced and internal climate variability create extreme events and local hydrometeorological changes influencing climate-sensitive sectors. This research is aimed at analyzing the recent changes in the hydrometeorological extremes using indices over the Bilate basin in Ethiopia. Mann-Kendall and Sen's slope estimator were used to examine changes in hydrometeorological extreme indices. The rainy days' rate of change falls between þ10.64 mm in the downstream to −10.67 mm in the upstream north. The wet day rainfall and heavy rainfall day indices were stronger in the basin's southwest, implying more likely flood events. The consecutive dry days show a rising tendency with more variability, while the consecutive wet days show no trend with less variability. The change point analysis revealed inconsistencies for the majority of the extreme indices. The stations' average warmest nights and days significantly increased at a rate of 0.0358°C and 0.0320°C per annum, respectively. The coldest nights in most of the stations show a significant and negligible rise in the basin while on the coldest days more than half of the stations declining. The peak flow in the annual and seasonal time series shows a rising trend and a dominant rise in most low flow indices, which possibly flashes downstream flooding. The global and local climate anomalies revealed a weak correlation, but with overlap of wet and drought years. Basin water resource plans may benefit from identified overlap cross of threshold years for improved flood control and drought monitoring. © 2018 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
Temporal Assessment of Meteorological Drought Events Using Stationary and Nonstationary Drought Indices for Two Climate Regions in India
(American Society of Civil Engineers (ASCE), 2023) Sajeev, A.; Kundapura, S.
This study attempts to build nonstationary indices for assessing meteorological drought in two different climate zones in India: the arid Saurashtra and Kutch and humid-tropical Coastal Karnataka. Time and climate indices are considered as covariates to develop nonstationary models using the generalized additive model in location, scale, and shape (GAMLSS) for the period, 1951-2004. A comparative study has been conducted to assess the statistical performance of stationary and nonstationary models on various time scales (3, 6, 12, and 24 months). The best model is selected to conduct copula-based bivariate drought analysis. For this purpose, drought properties such as drought severity, duration, and peak are calculated. The annual and seasonal rainfall departures are also analyzed, and more rainfall-deficient years are detected in Saurashtra and Kutch regions than in Coastal Karnataka. The nonstationary index performed better in capturing drought properties in statistical analysis over both the study areas at all time scales. The nonstationary drought index shows better consistency with historical drought and flood events than the stationary index. Cooccurrence and joint return periods are calculated and compared with univariate return periods. A significant difference is observed between bivariate and univariate return periods, and more risk is detected in Saurashtra and Kutch than in Coastal Karnataka. The impacts of rainfall and drought on the yield of major crops in study areas are also analyzed. The yield loss rate of bajra significantly correlates with the nonstationary standardized precipitation index (NSPI) in Saurashtra and Kutch, whereas rice yield has no significant correlation with the index in Coastal Karnataka. This new aspect of drought analysis provides feasible results in both arid and humid regions in a changing environment. © 2023 American Society of Civil Engineers.

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