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

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

Two-dimensional simulation of nitrate transport in an agriculture-intensive region

A two-dimensional steady-state solute transport model is developed to simulate movement of non-point sources of pollution in anisotropic porous media. The migration of chemicals dissolved in groundwater is governed by advective-dispersive processes which are also affected by the velocity of the flowing groundwater. Therefore, groundwater flow equation is solved for hydraulic gradient and hydraulic conductivity to approximate the average linear velocity of the fluid. The advection-dispersion is used to approximate the spatial and temporal distribution of non-reactive dissolved chemical in a flowing groundwater. A computer code is developed in MATLAB to solve the groundwater flow and solute transports equations by finite difference methods. The developed program is verified with soil-tank experimental data. The solute transport model is used to simulate non-point source of nitrate pollution in an agriculture-intensive region. Finally, the model outputs are analyzed to understand the factors that influence the pollution transport in the study area

Nitrate Adsorption on Clay Kaolin: Batch Tests

Soils possessing kaolin, gibbsite, goethite, and hematite particles have been found to have a natural capacity to attenuate pollution in aqueous phase. On the other hand, the hydroxyl group in soil increases anion exchange capacity under a low pH condition. The main objective of this paper was to evaluate effects of kaolin on nitrate reduction under acidic condition. In order to analyze the kaolin adsorption behaviour under various conditions, four different concentrations of nitrate, 45, 112.5, 225, and 450 mgNO3-/L, with a constant pH equal to 2, constant temperature equal to 25°C, and exposure period varying from 0 to 150 minutes were considered. The capacity of nitrate adsorption on kaolin has also been studied involving two well-known adsorption isotherm models, namely, Freundlich and Longmuir. The results revealed that approximately 25% of the nitrate present in the solution was adsorbed on clay kaolin. The laboratory experimental data revealed that Freundlich adsorption isotherm model was more accurate than Longmuir adsorption model in predicting of nitrate adsorption. Furthermore, the retardation factor of nitrate pollution in saturated zone has been found to be approximately 4 in presence of kaolin, which indicated that kaolin can be used for natural scavenger of pollution in the environment

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

Effects of El Nino Southern Oscillation on the Discharge of Kor River in Iran

The objective of the study was to investigate the El Nino forcing on the discharge of Kor River located in Maharloo-Bakhtegan basin in the Fars province of Iran. Thirty-one-year (1965-1995) and twenty-year (1975-1995) monthly mean river discharge data recorded at two stations, namely, Chamriz and Dehkadeh-Sefid, respectively, were chosen in the present study. Fourier analysis was used to extract harmonic information of time series data such as amplitude and phase angle to show the maximum effect and the time of effect of El Nino on river discharge. The study revealed that El Nino events caused increase of discharge in Kor River by 15% to 20% and the maximum influence was in the months of February and March in El Nino year

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

Changes in monsoon rainfall distribution of Bangladesh using quantile regression model

Climate change is supposed to alter not only the mean and variability but also the distribution of rainfall. Changes in rainfall distribution during the monsoon months (June to September) of Bangladesh are evaluated in this study using quantile regression. Monthly rainfall data for the period 1961–2014 recorded at 18 locations distributed over the country were used for this purpose. Distributional changes of monthly rainfall showed downward convergent lines are dominant in peak monsoon months of June, July and August at 28%, 50% and 28% stations, respectively, followed by horizontally divergent lines at 17% of stations during those months. The dominating category of last monsoon month (September) rainfall was found upward divergent lines at 50% stations. The results revealed a decrease in many rainfall quantiles from June to August and increase in September in most of the stations. The increasing trend lines of September rainfall quantiles were found to become more diverse with time, which indicates an increase in rainfall extremes and the possibility of more floods which are already very common in the last month of monsoon in Bangladesh. The decrease in lower quantiles of rainfall in most of the monsoon months may cause an increase in the probability of droughts in the country. The study provided more insight on monsoon rainfall changes and improved understanding of climate change impacts on monsoon rainfall regime which can help in planning climate change adaptations in Bangladesh

Changing pattern of droughts during cropping seasons of Bangladesh

There has been a growing concern on temporal variations on drought characteristics due to climate change. This study compares meteorological drought characteristics for two different periods to quantify the temporal changes in seasonal droughts of 18 weather stations of the country. Fifty-five years rainfall and temperature data are divided into two different thirty-year periods, 1961–1990 and 1985–2014 and standardized precipitation evapotranspiration index (SPEI) for those periods are calculated to assess the changes. Four seasons in this study are selected as two major crop growing seasons namely, Rabi (November to April) and Kharif (May to October) and two critical periods for crop growth in term of water supply namely critical Rabi (March–April) and critical Kharif (May). Results show that moderate, extreme, and severe Rabi droughts has increased in 11, 9, and 4 stations out of 18 stations, respectively, and Kharif severe and extreme droughts has increased in 8 and 9 stations, respectively, In addition, the frequency analysis shows that the return periods have decreased during 1985–2014 at the stations where it was high during 1961–1990 and vice versa. This has made the spatial distribution of return periods of droughts more uniform over the country for most of the seasons. Increased return period of droughts in highly drought prone north and northwest Bangladesh has caused decrease in average frequency of droughts. Consequently, this result corresponds that Bangladesh experiences fewer droughts in recent years. Trend analysis of rainfall and temperature data reveals that significant increase of mean temperature and no significant change in rainfall in almost all months have increased the frequency of droughts in the regions where droughts were less frequent

Potential impact of climate change on residential energy consumption in Dhaka city

This study aimed to assess the impacts of climate change on residential energy consumption in Dhaka city of Bangladesh. The monthly electricity consumption data for the period 2011–2014 and long-term climate variables namely monthly rainfall and temperature records (1961–2010) were used in the study. An ensemble of six global circulation models (GCMs) of coupled model intercomparison project phase 5 (CMIP5) namely, BCCCSM1-1, CanESM2, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, and NorESM1-M under four representative concentration pathway (RCP) scenarios were used to project future changes in rainfall and temperature. The regression models describing the relationship between historical energy consumption and climate variables were developed to project future changes in energy consumptions. The results revealed that daily energy consumption in Dhaka city increases in the range of 6.46–11.97 and 2.37–6.25 MkWh at 95% level of confidence for every increase of temperature by 1 °C and daily average rainfall by 1 mm, respectively. This study concluded that daily total residential energy demand and peak demand in Dhaka city can increase up to 5.9–15.6 and 5.1–16.7%, respectively, by the end of this century under different climate change scenarios