ABSTRACT Due to the present climate change scenario, it is necessary to interpret return period, ... more ABSTRACT Due to the present climate change scenario, it is necessary to interpret return period, risk, and reliability of hydrological extremes under non-stationary conditions. The present study aims to understand the crucial design parameters by introducing physically based covariates in the location parameter of the Generalized Extreme Value (GEV) distribution. The analysis is carried out over 30 streamflow gauging stations located across the Godavari River basin, India. To compare the return period, risk and reliability between the stationary and non-stationary conditions, the Expected Waiting Time (EWT) approach is used. The analysis reveals that half of the gauging stations are impacted by large-scale modes/oscillations and regional hydrological variability, primarily by the Indian Summer Monsoon Index (ISMI) and precipitation. The EWT interpretation estimates that the non-stationary return period, risk, and reliability are significantly different from under the stationary condition. Hence, a non-stationary approach can be useful to water managers and policymakers in order to devise sustainable and resilient water resource infrastructure under a climate change scenario.
Abstract Recent studies report that the extreme rainfall characteristics in most parts of the glo... more Abstract Recent studies report that the extreme rainfall characteristics in most parts of the globe exhibit temporal non-stationarity. Therefore, modeling the nonstationary behavior of extreme rainfall for different water resources applications is vital. When modeling non-stationarity in extreme rainfall series, previous studies consider a single threshold value in the peaks over threshold (POT) approach to extract extreme rainfall series. However, extreme rainfall series extracted with different threshold values may have a different degree of non-stationarity. Consequently, it is essential to understand the effect of threshold selection in modeling peaks over threshold based nonstationary extreme rainfall series. This study aims at quantifying the threshold uncertainty (i.e., uncertainty in extreme rainfall return levels due to the choice of the threshold) in modeling peaks over threshold based nonstationary extreme rainfall series using the Generalized Pareto Distribution (GPD). To study the threshold uncertainty, extreme rainfall series over India from the India Meteorological Department’s high-resolution gridded (0.25° Longitude × 0.25° Latitude) daily rainfall dataset is used. For modeling non-stationarity in extreme rainfall series, different indices representing four physical processes, namely, global warming, El Nino–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and local temperature anomaly are linked with the scale parameter of the GPD. Uncertainties in extreme rainfall return levels calculated over India indicate that the uncertainty created due to the choice of threshold is 54% higher under the nonstationary condition when compared to the stationary condition.
In the present study, three Stochastic Dynamic Programming (SDP) models with different objective ... more In the present study, three Stochastic Dynamic Programming (SDP) models with different objective functions were used to develop the operating policy for an irrigation reservoir, namely, Sri Rama Sagar Reservoir on the River Godavari in Andhra Pradesh, India. The reservoir is a major project, meeting the irrigation requirements over a large command area. The three SDP models model the objectives of the reservoir with different levels of mathematical complexity. The performance of the reservoir under these three operating policies is compared through simulation. Three criteria, namely reliability, resilience and average annual deficit of water supply are used to evaluate the performance of the reservoir under the alternative operating policies developed.
In the present study, three Stochastic Dynamic Programming (SDP) models with different objective ... more In the present study, three Stochastic Dynamic Programming (SDP) models with different objective functions were used to develop the operating policy for an irrigation reservoir, namely, Sri Rama Sagar Reservoir on the River Godavari in Andhra Pradesh, India. The reservoir is a major project, meeting the irrigation requirements over a large command area. The three SDP models model the objectives of the reservoir with different levels of mathematical complexity. The performance of the reservoir under these three operating policies is compared through simulation. Three criteria, namely reliability, resilience and average annual deficit of water supply are used to evaluate the performance of the reservoir under the alternative operating policies developed.
The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curve... more The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curves and the current IDF curves are based on the concept of stationary extreme value theory (i.e. occurrence probability of extreme precipitation is not expected to change significantly over time). But, the extreme precipitation events are increasing due to global climate change and questioning the reliability of our current infrastructure design. In this study, the trend in Hyderabad city 1-, 2-, 3-, 6-, 12-, 24- and 48-h duration annual maximum rainfall series are analyzed using the Mann–Kendall (M–K) test, and a significant increasing trend is observed. Further, based on recent theoretical developments in the extreme value theory (EVT), non-stationary rainfall IDF curve for the Hyderabad city is developed by incorporating linear trend in the location parameter of the generalized extreme value (GEV) distribution. The study results indicate that the IDF curves developed under the stationar...
The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curve... more The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curves and the current IDF curves are based on the concept of stationary extreme value theory (i.e. occurrence probability of extreme precipitation is not expected to change significantly over time). But, the extreme precipitation events are increasing due to global climate change and questioning the reliability of our current infrastructure design. In this study, the trend in Hyderabad city 1-, 2-, 3-, 6-, 12-, 24- and 48-h duration annual maximum rainfall series are analyzed using the Mann–Kendall (M–K) test, and a significant increasing trend is observed. Further, based on recent theoretical developments in the extreme value theory (EVT), non-stationary rainfall IDF curve for the Hyderabad city is developed by incorporating linear trend in the location parameter of the generalized extreme value (GEV) distribution. The study results indicate that the IDF curves developed under the stationar...
Proceedings of 2nd Asia Pacific Association of …, 2004
... Shrestha et al [2] constructed a fuzzy-rule based model to derive operation rules for a multi... more ... Shrestha et al [2] constructed a fuzzy-rule based model to derive operation rules for a multipurpose reservoir. ... The project provides irrigation for 155,635 hectares during kharif season (June to October) and for 108,385 hectares during rabi season (November to February) in the ...
AbstractIn the continually climate change scenario, it is of great concern to revisit, rethink, a... more AbstractIn the continually climate change scenario, it is of great concern to revisit, rethink, and improve the existing computational aspects of drought indexes. In general, the commonly used drou...
Multipurpose reservoir operation involves various interactions and trade-offs between purposes, w... more Multipurpose reservoir operation involves various interactions and trade-offs between purposes, which are sometimes complementary but often competitive or conflicting. Reservoir operation may be based on the conflicting objectives of maximizing the amount of water available for conservation purposes and maximizing the amount of empty space for storing future flood waters to reduce the downstream damages. A major complicating factor in water resources system management is handling uncertainty. Reservoir management is one of the such complex problems which involves the uncertainty. Various models have been reported in literature for developing optimal operation policy for a reservoir. Most of these models consider the uncertainty caused due to variability of inflows. However uncertainty caused because of imprecise objectives and goals is also an factor in developing operation policy of a reservoir. In recent years fuzzy optimization models have generated considerable interest. In the ...
AbstractRecently, human intervention and climate change have been proposed as the causes of chang... more AbstractRecently, human intervention and climate change have been proposed as the causes of changes in extreme water levels, which impact the likelihood of flooding, especially in coastal areas. In...
ABSTRACT Flood modelling inputs used to create flood hazard maps are normally based on the assump... more ABSTRACT Flood modelling inputs used to create flood hazard maps are normally based on the assumption of data stationarity for flood frequency analysis. However, changes in the behaviour of climate systems can lead to nonstationarity in flood series. Here, we develop flood hazard maps for Ho Chi Minh City, Vietnam, under nonstationary conditions using extreme value analysis, a coupled 1D–2D model and high-resolution topographical data derived from LiDAR (Light Detection and Ranging) data. Our findings indicate that ENSO (El Niño Southern Oscillation) and PDO (Pacific Decadal Oscillation) influence the magnitude and frequency of extreme rainfall, while global sea-level rise causes nonstationarity in local sea levels, having an impact on flood risk. The detailed flood hazard maps show that areas of high flood potential are located along river banks, with 0.60 km2 of the study area being unsafe for people, vehicles and buildings (H5 zone) under a 100-year return period scenario.
AbstractThe present study analyzes the various uncertainties and nonstationarity in the streamflo... more AbstractThe present study analyzes the various uncertainties and nonstationarity in the streamflow projections over the Wainganga River Basin, India, under representative concentration pathways (RC...
Journal of environmental science & engineering, 2004
River Krishna in the Southern Peninsula of India is a typical receiving water body of both point ... more River Krishna in the Southern Peninsula of India is a typical receiving water body of both point and non-point discharges. Comparisons between upstream and downstream monitoring sites reveal changes in the concentrations and load to the river. This information is used to discriminate between point and non-point source contribution to pollution. The pre-monsoon and post-monsoon water quality and flow data are used to assess river pollution loads. The resulting differential loads, if adjusted for uncharacterized non-point source contribution may represent the total point loads to the river minus losses due to volatilization, sedimentation, adsorption and other physical, chemical and biological phenomena. The results of the mass balances indicate that non-point sources to be major contributors to the pollutant loads. The non-point sources in the study area predominantly include pollution due to agricultural practices and activities, soil erosion, dissolution of soil minerals or combina...
ABSTRACT Due to the present climate change scenario, it is necessary to interpret return period, ... more ABSTRACT Due to the present climate change scenario, it is necessary to interpret return period, risk, and reliability of hydrological extremes under non-stationary conditions. The present study aims to understand the crucial design parameters by introducing physically based covariates in the location parameter of the Generalized Extreme Value (GEV) distribution. The analysis is carried out over 30 streamflow gauging stations located across the Godavari River basin, India. To compare the return period, risk and reliability between the stationary and non-stationary conditions, the Expected Waiting Time (EWT) approach is used. The analysis reveals that half of the gauging stations are impacted by large-scale modes/oscillations and regional hydrological variability, primarily by the Indian Summer Monsoon Index (ISMI) and precipitation. The EWT interpretation estimates that the non-stationary return period, risk, and reliability are significantly different from under the stationary condition. Hence, a non-stationary approach can be useful to water managers and policymakers in order to devise sustainable and resilient water resource infrastructure under a climate change scenario.
Abstract Recent studies report that the extreme rainfall characteristics in most parts of the glo... more Abstract Recent studies report that the extreme rainfall characteristics in most parts of the globe exhibit temporal non-stationarity. Therefore, modeling the nonstationary behavior of extreme rainfall for different water resources applications is vital. When modeling non-stationarity in extreme rainfall series, previous studies consider a single threshold value in the peaks over threshold (POT) approach to extract extreme rainfall series. However, extreme rainfall series extracted with different threshold values may have a different degree of non-stationarity. Consequently, it is essential to understand the effect of threshold selection in modeling peaks over threshold based nonstationary extreme rainfall series. This study aims at quantifying the threshold uncertainty (i.e., uncertainty in extreme rainfall return levels due to the choice of the threshold) in modeling peaks over threshold based nonstationary extreme rainfall series using the Generalized Pareto Distribution (GPD). To study the threshold uncertainty, extreme rainfall series over India from the India Meteorological Department’s high-resolution gridded (0.25° Longitude × 0.25° Latitude) daily rainfall dataset is used. For modeling non-stationarity in extreme rainfall series, different indices representing four physical processes, namely, global warming, El Nino–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and local temperature anomaly are linked with the scale parameter of the GPD. Uncertainties in extreme rainfall return levels calculated over India indicate that the uncertainty created due to the choice of threshold is 54% higher under the nonstationary condition when compared to the stationary condition.
In the present study, three Stochastic Dynamic Programming (SDP) models with different objective ... more In the present study, three Stochastic Dynamic Programming (SDP) models with different objective functions were used to develop the operating policy for an irrigation reservoir, namely, Sri Rama Sagar Reservoir on the River Godavari in Andhra Pradesh, India. The reservoir is a major project, meeting the irrigation requirements over a large command area. The three SDP models model the objectives of the reservoir with different levels of mathematical complexity. The performance of the reservoir under these three operating policies is compared through simulation. Three criteria, namely reliability, resilience and average annual deficit of water supply are used to evaluate the performance of the reservoir under the alternative operating policies developed.
In the present study, three Stochastic Dynamic Programming (SDP) models with different objective ... more In the present study, three Stochastic Dynamic Programming (SDP) models with different objective functions were used to develop the operating policy for an irrigation reservoir, namely, Sri Rama Sagar Reservoir on the River Godavari in Andhra Pradesh, India. The reservoir is a major project, meeting the irrigation requirements over a large command area. The three SDP models model the objectives of the reservoir with different levels of mathematical complexity. The performance of the reservoir under these three operating policies is compared through simulation. Three criteria, namely reliability, resilience and average annual deficit of water supply are used to evaluate the performance of the reservoir under the alternative operating policies developed.
The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curve... more The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curves and the current IDF curves are based on the concept of stationary extreme value theory (i.e. occurrence probability of extreme precipitation is not expected to change significantly over time). But, the extreme precipitation events are increasing due to global climate change and questioning the reliability of our current infrastructure design. In this study, the trend in Hyderabad city 1-, 2-, 3-, 6-, 12-, 24- and 48-h duration annual maximum rainfall series are analyzed using the Mann–Kendall (M–K) test, and a significant increasing trend is observed. Further, based on recent theoretical developments in the extreme value theory (EVT), non-stationary rainfall IDF curve for the Hyderabad city is developed by incorporating linear trend in the location parameter of the generalized extreme value (GEV) distribution. The study results indicate that the IDF curves developed under the stationar...
The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curve... more The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curves and the current IDF curves are based on the concept of stationary extreme value theory (i.e. occurrence probability of extreme precipitation is not expected to change significantly over time). But, the extreme precipitation events are increasing due to global climate change and questioning the reliability of our current infrastructure design. In this study, the trend in Hyderabad city 1-, 2-, 3-, 6-, 12-, 24- and 48-h duration annual maximum rainfall series are analyzed using the Mann–Kendall (M–K) test, and a significant increasing trend is observed. Further, based on recent theoretical developments in the extreme value theory (EVT), non-stationary rainfall IDF curve for the Hyderabad city is developed by incorporating linear trend in the location parameter of the generalized extreme value (GEV) distribution. The study results indicate that the IDF curves developed under the stationar...
Proceedings of 2nd Asia Pacific Association of …, 2004
... Shrestha et al [2] constructed a fuzzy-rule based model to derive operation rules for a multi... more ... Shrestha et al [2] constructed a fuzzy-rule based model to derive operation rules for a multipurpose reservoir. ... The project provides irrigation for 155,635 hectares during kharif season (June to October) and for 108,385 hectares during rabi season (November to February) in the ...
AbstractIn the continually climate change scenario, it is of great concern to revisit, rethink, a... more AbstractIn the continually climate change scenario, it is of great concern to revisit, rethink, and improve the existing computational aspects of drought indexes. In general, the commonly used drou...
Multipurpose reservoir operation involves various interactions and trade-offs between purposes, w... more Multipurpose reservoir operation involves various interactions and trade-offs between purposes, which are sometimes complementary but often competitive or conflicting. Reservoir operation may be based on the conflicting objectives of maximizing the amount of water available for conservation purposes and maximizing the amount of empty space for storing future flood waters to reduce the downstream damages. A major complicating factor in water resources system management is handling uncertainty. Reservoir management is one of the such complex problems which involves the uncertainty. Various models have been reported in literature for developing optimal operation policy for a reservoir. Most of these models consider the uncertainty caused due to variability of inflows. However uncertainty caused because of imprecise objectives and goals is also an factor in developing operation policy of a reservoir. In recent years fuzzy optimization models have generated considerable interest. In the ...
AbstractRecently, human intervention and climate change have been proposed as the causes of chang... more AbstractRecently, human intervention and climate change have been proposed as the causes of changes in extreme water levels, which impact the likelihood of flooding, especially in coastal areas. In...
ABSTRACT Flood modelling inputs used to create flood hazard maps are normally based on the assump... more ABSTRACT Flood modelling inputs used to create flood hazard maps are normally based on the assumption of data stationarity for flood frequency analysis. However, changes in the behaviour of climate systems can lead to nonstationarity in flood series. Here, we develop flood hazard maps for Ho Chi Minh City, Vietnam, under nonstationary conditions using extreme value analysis, a coupled 1D–2D model and high-resolution topographical data derived from LiDAR (Light Detection and Ranging) data. Our findings indicate that ENSO (El Niño Southern Oscillation) and PDO (Pacific Decadal Oscillation) influence the magnitude and frequency of extreme rainfall, while global sea-level rise causes nonstationarity in local sea levels, having an impact on flood risk. The detailed flood hazard maps show that areas of high flood potential are located along river banks, with 0.60 km2 of the study area being unsafe for people, vehicles and buildings (H5 zone) under a 100-year return period scenario.
AbstractThe present study analyzes the various uncertainties and nonstationarity in the streamflo... more AbstractThe present study analyzes the various uncertainties and nonstationarity in the streamflow projections over the Wainganga River Basin, India, under representative concentration pathways (RC...
Journal of environmental science & engineering, 2004
River Krishna in the Southern Peninsula of India is a typical receiving water body of both point ... more River Krishna in the Southern Peninsula of India is a typical receiving water body of both point and non-point discharges. Comparisons between upstream and downstream monitoring sites reveal changes in the concentrations and load to the river. This information is used to discriminate between point and non-point source contribution to pollution. The pre-monsoon and post-monsoon water quality and flow data are used to assess river pollution loads. The resulting differential loads, if adjusted for uncharacterized non-point source contribution may represent the total point loads to the river minus losses due to volatilization, sedimentation, adsorption and other physical, chemical and biological phenomena. The results of the mass balances indicate that non-point sources to be major contributors to the pollutant loads. The non-point sources in the study area predominantly include pollution due to agricultural practices and activities, soil erosion, dissolution of soil minerals or combina...
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Papers by Umamahesh Nanduri