Climate change projection and drought characterization in Bangladesh

One of the biggest threats of the climatic change is aberrant pattern or distribution of rainfall that results to drought. The main objective of this research was to develop a methodological framework to assess the impacts of climate change on seasonal drought characteristics with uncertainty. Bangladesh, one of the most vulnerable countries in the world to climate change was considered as the study area for implementation of the framework. An ensemble of general circulation models (GCMs) of Coupled Model Intercomparison Project phase 5 (CMIP5) were used for downscaling and projection of rainfall and temperature under different Representative Concentration Pathways (RCP) scenarios. Two state of art data mining approaches known as Random Forest (RF) and Support Vector Machine (SVM) were used for the development of downscaling models and Quantile Mapping (QM) approach was used to remove biases in GCMs. The observed and future projected rainfall data were used to characterize the seasonal droughts using Severity-Area-Frequency (SAF) curves developed for different climatic and major crop growing seasons. The results revealed superior performance of SVM in downscaling rainfall and temperature in tropical climate in terms of all standard statistics. Downscaling of CMIP5 GCMs projections revealed a change in annual average rainfall in Bangladesh in the range of -8.6% in the northeast to +11.9% in the northwest, which indicates that spatial distribution of rainfall of Bangladesh will be more homogeneous in future. The maximum and minimum temperatures of Bangladesh were projected to increase in the range of 0.8 to 4.3ºC and 1.0 to 4.8ºC, respectively under different RCPs. Future projection of droughts revealed that affected areas will increase for higher severity and higher return period droughts. Overall, the country will be more affected by higher return period Kharif (May- October) and monsoon droughts, and lower return period pre-monsoon and postmonsoon droughts due to climate change

Predictors and their domain for statistical downscaling of climate in Bangladesh

Reliable projection of future rainfall in Bangladesh is very important for the assessment of possible impacts of climate change and implementation of necessary adaptation and mitigation measures. Statistical downscaling methods are widely used for downscaling coarse resolution general circulation model (GCM) output at local scale. Selection of predictors and their spatial domain is very important to facilitate downscaling future climate projected by GCMs. The present paper reports the finding of the study conducted to identify the GCM predictors and demarcate their climatic domain for statistical downscaling in Bangladesh at local or regional scale. Twenty-six large scale atmospheric variables which are widely simulated GCM predictors from 45 grid points around the country were analysed using various statistical methods for this purpose. The study reveals that large-scale atmospheric variables at the grid points located in the central-west part of Bangladesh have the highest influence on rainfall. It is expected that the finding of the study will help different meteorological and agricultural organizations of Bangladesh to project rainfall and temperature at local scale in order to provide various agricultural or hydrological services

Transfer function models for statistical downscaling of monthly precipitation

Three transfer function based statistical downscaling namely, linear regression model (LM), generalized linear model (GLM), generalized additive model (GAM) have been developed to assess their performance in downscaling monthly rainfall. Previous studies reported that performance of downscaling model depends on climate region and characteristics of climatic variable being downscaled. This has motivated to assess the performance of these three statistical downscaling models to identify most suitable model for downscaling monthly rainfall in the East coast of Peninsular Malaysia. Assessment of model performance using standard statistical measures revealed that LM model performs best in downscaling monthly precipitation in the study area. The Nash–Sutcliffe efficiency (NSE) for LM was found always greater than 0.9 and 0.7 with predictor set selected using stepwise multiple regression method during model calibration and validation, respectively. The finding opposes the general conception of better performance of non-linear models compared to linear models in downscaling rainfall. The near normal distribution of monthly rainfall in the tropical region has made the LM model much stronger compared to other models which assume that distribution of dependent variable is not norma

Historical trends and future projection of climate at Dhaka city of Bangladesh

Dhaka, the capital city of Bangladesh is considered as one of the most vulnerable cities of the world to climate change. A study has been carried out to assess the historical changes as well as future changes in the climate of Dhaka city in order to propose necessary mitigation and adaptation measures. Statistical downscaling model (SDSM) was used for the projection of future changes in daily rainfall and temperature and non-parametric trend analysis was used to assess the changes in rainfall, temperature and related extremes. The impacts of projected changes in climate on urban infrastructure and livelihood in Dhaka city was finally assessed to propose necessary adaptation measures. The study revealed that night time temperature in Dhaka city has increased significantly at a rate of 0.22ºC/decade in last fifty year, which is support to increase continually in the future. Different temperature related extreme events are also found to increase significantly in Dhaka. On the other hand, no significant change in rainfall or rainfall related extremes are observed. Therefore, it can be remarked that imminent impacts of climate change will be due to the increase in temperature and temperature related extremes. The public health and the water and energy supply are likely to be imminent affected sector in the city due to climate change

Prediction in ungauged river basin in the west coast of peninsular Malaysia using linear regression model

A linear multiple regression based regionalization method has been proposed in this study to simulate streamflow in ungauged catchment in the east coast of peninsular Malaysia. Identification of unit Hydrographs And Component flows from Rainfall, Evapotranspiration and Streamflow (IHACRES) rainfall-runoff model was used to develop the relationship between model parameters and physical catchment descriptors of eight gauged catchments distributed over the west coast of peninsular Malaysia. The IHACRES model was calibrated and validated individually for each catchment with the available data for the time periods varying between three to sixteen years. The Nash-Sutcliffe efficiency index was used as criteria to evaluate the model performance. As the relationships between the physical catchment descriptors and hydrologic response characteristics are not necessarily linear, different forms of transformations were performed in order to find the most appropriate relationship. Finally, the obtained regression equations were used for simulating stream discharge in Sg Layang catchment located in the south of peninsular Malaysia. The result of the regional model was compared with observed monthly stream flow data of the catchment to assess the ability of regional model. The obtained results revealed that the regional model was able to replicate the historical monthly average flow. However, the relationship between the catchment area and hydrologic response characteristics were not fully understood by regional model which emphasize the need of consideration of other dominant catchment factors for prediction in ungauged basin

Regime shift in monsoon rainfall of Bangladesh: a sequential data processing approach

As the economy and livelihoods of Bangladesh heavily depends on agriculture, any changes in monsoon rainfall have severe implications for the country. There is a growing concern on monsoon rainfall pattern change in Bangladesh in recent years like other parts of Indian summer monsoon region. A study has been carried out in this paper to analyze the monsoon rainfall time series of Bangladesh to decipher if there any shift in monsoon rainfall regime of Bangladesh. Sixty four years rainfall data recorded at twenty-nine locations distributed over Bangladesh were analyzed using a sequential regime shift detection method for this purpose. The proposed method employed Student’s t-test to detect difference between two subsequent regimes with a cut-off length of one to determine the regime shift. The result shows that monsoon rainfall has increased, mostly in recent years in many locations of Bangladesh. Though increased monsoon rainfall will be helpful for rain-fed agriculture in Bangladesh, at the same time it will also cause more frequent floods, urban water logging, water-borne diseases, etc

Bivariate frequency analysis of flood variables using copula in Kelantan river basin

A copula-based methodology is presented in this study for bivariate flood frequency analysis of Kelantan river basin located in Northeast Malaysia. The joint dependence structures of three flood characteristics, namely, peak flow (Q), flood volume (V) and flood duration (D) were modelled using t-Copula. Various univariate distribution functions of flood variables were fitted with observed flood variables to find the best distributions. Cumulative joint distribution functions (CDF) of peak flow and volume (Q-F), peak flow and duration (Q-D) and volume and duration (V-D) revealed that return period of joint return periods are much higher compared to univariate return period. The joint probabilities of occurrence of 0.8, 0.6, 0.4, 0.2 and 0 can be expected when flood duration greater than 65 h, 54 h, 46 h, and 32 h, and the flood volume higher than 0.62 km3, 0.33 km3, 0.25 km3, and 0.22 km3 respectively

Synthesis and reactivity of some activated heterocyclic compounds

An alternate approach to the synthesis of calix[3]indoles has been demonstrated, but further attempted synthetic approaches to calixindoles using new leaving groups led to uncharacterized polymeric products. The synthesis of new 7,7'-diindolylmethane- 2,2'-dicarbaldehydes gives potential for further ligand design and metal complex formation. In addition, 4,6-dimethoxyindole-7- carbaldehydes have been effectively converted to a range of 6-methoxyindole-4,7-diones by Dakin oxidation.Various electrophilic substitution reactions have been performed on the 4,6-dimethoxybenzimidazoles. Formylation, acylation, acid catalyzed addition of formaldehyde and nitration revealed that the activated benzimidazoles are less reactive at the specified C-7 position compared to the analogous indoles. The key starting material for a potential calixbenzimidazole was synthesized by the selenium dioxide oxidation of 2-methyl-7-formyl-4,6-dimethoxybenzimidazole and by oxidative cleavage of 4,6-dimethoxy- 2-styrylbenzimidazole by Lemieux-Johnson reagent followed by reduction. Nevertheless, attempted preparation of calixbenzimidazole from 2-hydroxymethyl-4,6-dimethoxy benzimidazole led to formation of a dibenzimidazolyl ether. The synthesis of some novel activated bisbenzimidazoles has been developed. Furthermore, benzimidazoles were incorporated into new ligand systems which have led to a wide range of acyclic quadridentate neutral metal complexes.Activated benzimidazoles overall illustrate one electron irreversible oxidation to form a radical cation followed by multielectron oxidations. On the other hand, the nickelII and cobaltII benzimidazole metal complexes investigated showed one electron ligand centered reversible reduction. Irreversible radical cation oxidation followed by multielectron oxidation of the metal complexes further demonstrates the rich electrochemical nature of the 4,6-dimethoxybenzimidazoles.Some novel 7-(indol-2-yl)-4,6-dimethoxybenzimidazoles were prepared with indolin-2-one and triflic anhydride and an alternate procedure afforded 2-(4,6-dimethoxyindol-7-yl)-benzimidazoles from activated indoles and 2-benzimidazolinone.Two new isomeric series of 2-substituted-5,7-dimethoxybenzothiazoles and 2-substituted-4,6-dimethoxybenzothiazoles were synthesized via Jacobson cyclization. The two strategically placed electron donating methoxy groups activate these benzothiazoles to undergo various electrophilic substitutions at the 4- and 7- positions respectively

Efficiency of different organic surfactants on nitrate adsorption in water

Organoclays are modified clays in which the natural inorganic interlayer cations are replaced by organic cations. The net amount of organic cations adsorbed to the clay can exceed the cation exchange capacity of the clay, thus providing binding sites for exchangeable anions. Therefore, organic surfactants are efficient in the treatment of contaminated water. Here a review has been carried out to understand the efficiency of various organic surfactants, viz. hexadecyl trimethylammonium, hexadecyl pyridinium and benzethonium on nitrate reduction in drinking water. This study revealed that hexadecyl pyridinium are more efficient to remove nitrate in drinking water than other organic surfactants

Bivariate flood frequency analysis using gumbel copula

A copula based methodology is presented in this study for bivariate flood frequency analysis over a station over a Kelantan river basin located in Northeast Malaysia. The joint dependence structures of three flood characteristics, namely, peak flow, flood volume and flood duration were modelled using Gumble Copula. Various univariate distribution functions of flood variables were fitted with observed flood variables to find the best distributions (eg. generalized pareto, log-normal, exponential, gamma distribution, weibull, gumbel, cauchy). The results of study revealed that different variable fits with different distributions and the correlation analysis among variables showed a strong association. Cumulative joint distribution functions (CDF) of peakflow and volume, peakflow and duration and volume and duration revealed that return period of joint return periods are much higher