Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
10 results
Search Results
Item Bias correction methods for hydrologic impact studies over India's Western Ghat basins(American Society of Civil Engineers (ASCE) onlinejls@asce.org, 2018) Mudbhatkal, A.; Mahesha, M.The regional climate models (RCMs) used in the analysis of the impact of climate variables on the hydrology of river basins needs appropriate preprocessing (bias correction) to represent and reproduce future climate with a fair degree of accuracy. The performance of bias corrections methods was assessed in this investigation on the basis of their ability to minimize error on climate variables and streamflow. This work compares the performance of five bias correction methods applied for precipitation and four methods for temperature in modeling the hydrology of the river catchments of theWestern Ghats of India. TheWestern Ghats are a mountainous forest range along the entire west coast of India that plays a major role in the distribution of Indian monsoon rains. Simulations were used to evaluate the performance of the bias correction methods. Using raw RCM, bias corrected precipitation and temperature time series, streamflows were estimated by the soil and water assessment tool (SWAT) hydrological model. The results indicated that the raw RCM-simulated precipitation was biased by 42% and the temperature was biased by 12% across the catchments investigated. Subsequently, a bias of 65% was found in the streamflow. The performance of the delta change correction method was consistently better for precipitation (with Nash-Sutcliffe efficiency, NSE > 0.75 for 5 catchments) and temperature (NSE = 1) compared with other methods. Good performance was observed between the observed and bias corrected streamflow (daily time scale) for the catchments Purna (NSE = 0.97), Ulhas (NSE = 0.64), Aghanashini (NSE = 0.82), Netravathi (NSE = 0.89), and Chaliyar (NSE = 0.90); low performance with an NSE of 0.3 was observed for the catchments Kajvi and Vamanapuram. The methods failed for Malaprabha and Tunga catchments. The results indicate that the delta change correction method performed best in analyzing the hydrological impact of climate variables on the windward side of Western Ghats of India. © 2017 American Society of Civil Engineers.Item Trend and variability of hydrometeorological variables of Tikur Wuha watershed in Ethiopia(Springer, 2020) Ketema, A.; Dwarakish, G.S.The study assessed monthly, seasonal, and annual variability and trend of hydrometeorological variables for 1978–2017 of Tikur Wuha watershed in Ethiopia. The Mann-Kendall trend test and Sen’s slope estimator were employed for the trend and size of the trend, respectively. Besides, the coefficient of variation has been computed for variability analysis. The areal average annual rainfall exhibited an insignificant declining trend with a magnitude of 20.8 mm/decade at a watershed scale. The watershed has been suffering from irregular and erratic rainfall during the dry season. Temperature exhibited a statistically significant rising trend with minimum temperature rises faster than that of the maximum temperature. The streamflow of the Tikur Wuha River was found to be increasing at the rate of 21.16 MCM/decade. The increasing trend of streamflow without the corresponding increase of rainfall in the watershed needs further investigation. © 2020, Saudi Society for Geosciences.Item Long-Term Climate Variability and Drought Characteristics in Tropical Region of India(American Society of Civil Engineers (ASCE), 2021) Vijay, A.; Sivan, S.D.; Mudbhatkal, A.; Mahesha, A.This work reports climate change signals and long-Term trend analysis of climate variables, meteorological drought, and extreme climate indexes over the tropical state of Kerala in India. The trend analysis reveals statistically significant decrease of annual and southwest monsoon rainfall (as much as 63 mm and 55 mm per decade, respectively). A decrease in number of annual rainy days (up to 2.8 days/decade) is also reported. Temperature trend analysis indicates an increasing trend with as high as 1.3°C/decade. The spatio-Temporal variation of extreme climate indexes across Kerala shows a decreasing trend of extreme precipitation indexes and an increasing trend of extreme temperature indexes. R95 and R95p decreased in northern and southern Kerala whereas R5 index increased in central and southern regions. Warm days have significantly increased whereas cold days exhibit a decreasing trend across the state. The increase in warmer nights is statistically significant whereas colder nights are decreasing in central and southern regions. Meteorological drought using Standardized Precipitation Index (SPI) reveals increasing occurrence of droughts in Kerala with higher frequencies over southern and central Kerala. © 2021 American Society of Civil Engineers.Item Machine learning–based assessment of long-term climate variability of Kerala(Springer Science and Business Media Deutschland GmbH, 2022) Vijay, A.; Varija, K.Studies on historical patterns of climate variables and climate indices have attained significant importance because of the increasing frequency and severity of extreme events worldwide. While the recent events in the tropical state of Kerala (India) have drawn attention to the catastrophic impacts of extreme rainfall events leading to landslides and loss of human lives, a comprehensive and long-term spatiotemporal assessment of climate variables is still lacking. This study investigates the long-term trend analysis (119 years) of climate variables at 5% significance level over the state using gridded datasets of daily rainfall (0.25° × 0.25° spatial resolution) and temperature (1° × 1° spatial resolution) at annual and seasonal scales (south-west monsoon, north-east monsoon, winter and summer). Five trend analysis techniques including the Mann–Kendall test (MK), three modified Mann–Kendall tests and innovative trend analysis (ITA) test were performed in the study. It is evident from the trend analysis results that more than 83% of grid points were showing negative trends in annual and south-west monsoon season rainfall series (at a mean rate of 39.70 mm and 28.30 mm per decade respectively). All the trend analysis tests identified statistically significant increasing trends in mean and maximum temperature at annual and seasonal scales (0.10 to 0.20 °C/decade) for all grids. The K-means clustering algorithm delineated 59 grid points into five clusters for annual rainfall, illustrating a clear geographical pattern over the study area. There is a clear gradient in rainfall distribution and concentration inside the state at annual as well as seasonal scales. The majority of annual rainfall is concentrated in a few months of the year. That may lead the state vulnerable to water scarcity in non-rainy seasons. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Item Quantification of change in land cover and rainfall variability impact on flood hydrology using a hydrological model in the Ethiopian river basin(Springer Science and Business Media Deutschland GmbH, 2023) Tola, S.Y.; Shetty, A.Changes in land cover and climate are the dominant factors that significantly impact the hydrological process. However, the impact on flood response behaviour varies spatiotemporally. This study quantitatively assessed the effects of individual and coupled changes in land cover and climate on peak and high flows in the upstream and downstream parts of the Upper Awash River basin. Two time periods were chosen for comparison: baseline (1988–2001) and evaluation (2002–2015). The Soil Water and Assessment Tool (SWAT) was used to estimate the impact of these changes. The model satisfactorily simulated daily and extreme flows. The evaluation of annual maximal discharge variability between 1985 and 2015 at upstream and downstream stations showed significant positive and insignificant negative trends, respectively. However, the sub-basin’s annual wet day rainfall (PRCPTOT) showed a downward trend. The annual maximal discharge–PRCPTOT relationship was significant during the baseline but later had no significance. The SWAT model showed that the main factor that affected the changes in upstream flow was the land cover change, increasing peak and high flow by 38.69% and 11.95%, respectively, compared to the baseline period. However, combined changes resulted in downstream peak and high flow reductions of 19.55% and 50.33%, respectively. As a result, changes in flood characteristics are strong functions of land cover, especially in the upstream sub-basin and land cover and climate in the downstream sub-basin. Overall, the impact of changes in the cropland-dominated basin was noticeably different. The study assists water resource managers in understanding the causes of hydrological dynamics and developing mitigation strategies. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Item 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.Item Extreme hydroclimatic variability and impact of local and global climate system anomalies on extreme flow in the Upper Awash River basin(Springer, 2023) Tola, S.Y.; Shetty, A.Extreme hydroclimatic variability in a changing climate and the possible causes of extreme hydrological variability are essential for effectively mitigating floods. The study aims to investigate the variability of extreme hydroclimatic conditions and the relationship between anomalies in extreme local precipitation, ENSO indicators (Southern Oscillation index (SOI), Niño 3.4, and multivariate ENSO index (MEI)), and extreme flow indices in the Upper Awash River basin, Ethiopia. The analysis used standardized anomaly index and coefficient of variation statistics to examine variability, the modified Mann-Kendall and Pettitt tests for trend and change point analysis, and Spearman’s correlation test to explore relationships. The study revealed that the basin-wise extreme precipitation indices had less variability but higher variability spatially, while the extreme flow indices showed high variability. Furthermore, the basin experienced extreme wet to normal wet conditions in the 1990s compared to the 2000s. The maximum temperature increased significantly, while the minimum temperature decreased significantly (except at a few northwest stations), with a considerable shift in the 1990s and 2000s. Anomalies, extreme to normal wet conditions, and a decrease in extreme precipitation were consistent with the extreme flow at the basin outlet, Hombole station. However, the extreme flow indices at Melka Kunture increased significantly and shifted upward (2003/2005), and the anomalies in extremely wet and very wet precipitation in the northwest were possibly responsible for this change. The study also revealed that the annual wet and very wet days of precipitation strongly affected the extreme flow in the basin. The effect of annual wet day precipitation, annual maximum precipitation, and ENSO anomalies on extreme flow at the Hombole was significant. These findings enhance the understanding of extreme hydroclimatic variability and prospective flood predictability and aid flood risk management. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.Item 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.Item Climate indices and drought characteristics in the river catchments of Western Ghats of India(Springer Science and Business Media Deutschland GmbH, 2024) Shetty, S.; Umesh, P.; Shetty, A.The study addresses the long-term trend in rainfall, minimum and maximum temperature, and the climate indices for the river catchments located in the diverse climate of the Western Ghats of India. The dry sub-humid Chaliyar catchment and humid Kajvi catchment have shown a dramatic change in the decadal rainfall, with the decade 1950–1960 being the point of change. The monsoon rainfall has decreased in the Chaliyar and Netravati catchments and increased insignificantly in the Kajvi catchment. With the increase in mean temperature, the number of rainy days is decreasing, and intense rainfall is increasing in the pre-monsoon. The increase in minimum temperature is more severe in all three catchments, irrespective of the region’s climate. The decline in rainy days is more figurative in the humid and per-humid catchments and has seen a 16–20% decrease in R×1 day, R×3 day, and R×5 day in the past six decades with an insignificant increase in the dry sub-humid catchment. The frightful increase in warm days/nights with a decrease in cool days/nights has been alarming for the extremity of temperature in future years. The significant changes in the forest area in Chaliyar and Kajvi catchment and the increase in a built-up area in Netravati may have a decisive role in the nonseasonal variability in rainfall and temperature along with increasing greenhouse gases. In the case of meteorological drought studied using the Standardized Precipitation Index (SPI), moderate droughts have occurred over the Chaliyar and Kajvi, and extreme droughts over the Netravati catchments with no reduction in the frequency or severity of short-duration extreme rainfall events. The geographical location of the catchment has a greater impact on the characteristics of the rainfall and meteorological drought, and these changes in the hydrological regimes of the catchment have a significant bearing on the water availability in the catchments in the future years. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2023.Item Revitalizing temperature records: A novel framework towards continuous data reconstruction using univariate and multivariate imputation techniques(Elsevier Ltd, 2024) Yashas Kumar, H.K.; Varija, K.Data gaps are a recurring challenge in climate research, hindering effective time series analysis and modeling. This study proposes a novel two-step data imputation framework to address temperature time series with a long continuous gap surrounded by predictor stations with sporadic missingness. The method leverages iterative gap-filling Singular Spectrum Analysis (SSA) for the small sporadic gaps, followed by multivariate techniques like Inverse Distance Weightage (IDW), Kriging, Spatial Regression Test (SRT), Point Estimation method of Biased Sentinel Hospital-based Area Disease Estimation (P-BSHADE), Random Forest (RF), Support Vector Machines (SVM), and MissForest (MF) for the longer gap. Once the sporadic gaps are effectively addressed with SSA, the method carefully applies multivariate techniques to impute the long continuous gap. Prioritizing accuracy, comprehensive cross-validation with class-based statistical indicators are employed to minimize any potential biases introduced by the imputation process. The study shows the effectiveness of SSA in filling small sporadic gaps using an optimal window length (M ? 365 days) and eigentriple grouping (ET = 30). Notably, for maximum temperature, P-BSHADE and SVM achieve an impressive accuracy (e.g., Legates's Coefficient of Efficiency (LCE), 0.75?0.44, Combined Performance Index (CPI), 6.3%?19.1%) attributed to their ability to capture spatial and/or temporal heterogeneity. While SRT and P-BSHADE offers acceptable performance for minimum temperature (e.g., LCE, 0.51?0.27, CPI, 0.7%?23.7%), the study also uncovers a complex interplay between missing data, predictor stations, and autocorrelation affecting imputation accuracy. This suggests that the reduced performance of certain techniques likely stems from the decline in spatial and spatiotemporal autocorrelation between the target station and its predictors. Overall, this study presents a promising framework for handling complex missing data scenarios often encountered in climate time series analysis, paving the way for more robust and reliable analysis and modeling. © 2024 Elsevier B.V.