A. K. M. Saiful Islam

Implications of agricultural land use change to ecosystem services in the Ganges delta

Ecosystems provide the basis for human civilization and natural capital for green economy and sustainable development. Ecosystem services may range from crops, fish, freshwater to those that are harder to see such as erosion regulation, carbon sequestration, and pest control. Land use changes have been identified as the main sources of coastal and marine pollution in Bangladesh. This paper explores the temporal variation of agricultural land use change and its implications with ecosystem services in the Ganges delta. With time agricultural lands have been decreased and wetlands have been increased at a very high rate mainly due to the growing popularity of saltwater shrimp farming. In a span of 28 years, the agricultural lands have been reduced by approximately 50%, while the wetlands have been increased by over 500%. A large portion (nearly 40%) of the study area is covered by the Sundarbans which remained almost constant which can be attributed to the strict regulatory intervention to preserve the Sundarbans. The settlement & others land use type has also been increased to nearly 5%. There is a gradual uptrend of shrimp and fish production in the study area. The findings suggest that there are significant linkages between agricultural land use change and ecosystem services in the Ganges delta in Bangladesh. The continuous decline of agricultural land (due to salinization) and an increase of wetland have been attributed to the conversion of agricultural land into shrimp farming in the study area. Such land use change requires significant capital, therefore, only investors and wealthier land owners can get the higher profit from the land conversion while the poor people is left with the environmental consequences that affect their long-term lives and livelihood. An environmental management plan is proposed for sustainable land use in the Ganges delta in Bangladesh.

Changes of rainfall extremes around the haor basin areas of Bangladesh using multi-member ensemble RCM

Haors are large, round-shaped floodplain depressions located in the North-Eastern region of Bangladesh. Extreme events such as heavy rainfall routinely affect the haor basin with flash floods. These haors are predicted to experience severe stress because of changes in rainfall and temperature patterns. The biotic community of the wetlands may not have enough time to adjust itself in such varying temperature and rainfall extremes. This paper evaluates various aspects of the future projections of rainfall and temperature extremes, including magnitudes and frequencies thereof. The impacts of extreme events are examined using Hadley Centre’s high-resolution regional climate model known as PRECIS (Providing REgional Climates for Impact Studies). Daily temperature and rainfall simulations of the 17-member ensembles are generated through Hadley Centre Coupled Model (HadCM3). These simulations are used in Rclimdex—a software specially designed for this study. A total of 12 core climate indices are computed, analyzed, and statistically examined (Mann–Whitney U test) over the space of three time slices—(1) short (2020s, i.e., 2011–2040), (2) medium (2050s, i.e., 2041–2070), and (3) long (2080s, i.e., 2071–2098). Here, the 1980s (1971–2000) are considered as the baseline period. The study has found that the highest significant variability in both rainfalls and temperatures was during the pre-monsoon season when flash floods normally occur. Also, rainy days are projected to be less frequent albeit more intense where the deeply flooded haors are located. Though the annual total rainfall does not show any difference in spatial distribution (except for in magnitude), the seasonal patterns of most extreme events show that the probable affected areas have shifted from North-east to further North. In addition, a significant increase in both RX1 (1-day maximum rainfall) and RX5 (5-day maximum rainfall) are projected during the 2080’s pre-monsoon season near Sunamganj. This projection also indicates the possible frequent occurrence of flash floods with high volumes. Probability distribution frequencies (PDF) show a rightward shift in time indicating an increase in the amount of total rainfall in the future. Exceptions are, however, found in case of PDFs for consecutive dry days (CDD) and consecutive wet days (CWD). The decrease in CWD is found to be more pronounced than that of CDD. All these projections made in this study are expected to contribute further in the advancements of the Master Planning of the haor area that was done by the government of Bangladesh in 2012.

Analyzing the Future Monthly Precipitation Pattern in Bangladesh from Multi-Model Projections using both GCM and RCM

ABSTRACT It is very much essential to comprehend the inter-relationship of future possible trend of precipitation with the water-stress problems in a small country like Bangladesh, since enormous challenges associated with water supply are already present in this region. A major dimension of climate change for Bangladesh includes the expectation of more intensive and variability of precipitation events in future times. There are a number of mathematical models of global circulation that indicate expectations of future climate scenarios. But one particular model does not produce a perfect projection of future climatology or observations as the inherent physics and associated underlying assumptions of the model-components might be different for different climate models. As such, it is best to combine several climate models to enable a choice to produce the most appropriate projection to be used in climate-scenario generation for a small geographical area. This paper features the development of Multi-Model combination of future precipitation projections for Bangladesh on monthly basis, for each of the year from 2011 to 2100, using both global and regional climate models. Four selected IPCC ensemble Global Climate Models (GCMs), namely CGCM3.1, CCSM3, MIROC3.2 and HadGEM1 as well as a Regional Climate Model (RCM) called PRECIS have been applied in this regard. The multi-model average precipitation changes for Bangladesh at SRES A1B scenario indicate that the precipitation might continue to increase in all the months in future years. Percentage of precipitation increment is expected to be quite higher for dry and pre-monsoon months compared to the monsoon season. Also, the large

Assessment of Salinity Distributions and Residual Currents at the Northern Bay of Bengal considering Climate Change Impacts

The overall objective of the study is to investigate the future salinity distributions and residual flow scenarios in the northern Bay of Bengal taking into consideration of the change in hydrological and meteorological parameters. Observed and projected meteorological data are employed to generate present and future scenarios in the Northern Bay of Bengal. Numerical experiments through a 3D hydrodynamic model show that both during the monsoon as well as during winter periods, residual currents in the Northern Bay of Bengal display an anti-clockwise circulation concentrating at the eastern part of the bay. The Swatch of No Ground appears to have an important influence on the circulation patterns. Future salinity distributions are calculated through employment of projected meteorological data from regional climate model (RCM) experiments. It shows considerable increase in salinity level which may hamper the freshwater availability and ecological balance in the region in future.

Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data

In the era of global warning, the insight of future climate and their changing extremes is critical for climate-vulnerable regions of the world. In this study, we have conducted a robust assessment of Regional Climate Model (RCM) results in a monsoon-dominated region within the new Coupled Model Intercomparison Project Phase 5 (CMIP5) and the latest Representative Concentration Pathways (RCP) scenarios. We have applied an advanced bias correction approach to five RCM simulations in order to project future climate and associated extremes over Bangladesh, a critically climate-vulnerable country with a complex monsoon system. We have also generated a new gridded product that performed better in capturing observed climatic extremes than existing products. The bias-correction approach provided a notable improvement in capturing the precipitation extremes as well as mean climate. The majority of projected multi-model RCMs indicate an increase of rainfall, where one model shows contrary results during the 2080s (2071–2100) era. The multi-model mean shows that nighttime temperatures will increase much faster than daytime temperatures and the average annual temperatures are projected to be as hot as present-day summer temperatures. The expected increase of precipitation and temperature over the hilly areas are higher compared to other parts of the country. Overall, the projected extremities of future rainfall are more variable than temperature. According to the majority of the models, the number of the heavy rainy days will increase in future years. The severity of summer-day temperatures will be alarming, especially over hilly regions, where winters are relatively warm. The projected rise of both precipitation and temperature extremes over the intense rainfall-prone northeastern region of the country creates a possibility of devastating flash floods with harmful impacts on agriculture. Moreover, the effect of bias-correction, as presented in probable changes of both bias-corrected and uncorrected extremes, can be considered in future policy making.

Evaluation of Microphysics and Cumulus Schemes of WRF for Forecasting of Heavy Monsoon Rainfall over the Southeastern Hilly Region of Bangladesh

Accurate forecasting of heavy rainfall is crucial for the improvement of flood warning to prevent loss of life and property damage due to flash-flood-related landslides in the hilly region of Bangladesh. Forecasting heavy rainfall events is challenging where microphysics and cumulus parameterization schemes of Weather Research and Forecast (WRF) model play an important role. In this study, a comparison was made between observed and simulated rainfall using 19 different combinations of microphysics and cumulus schemes available in WRF over Bangladesh. Two severe rainfall events during 11th June 2007 and 24–27th June 2012, over the eastern hilly region of Bangladesh, were selected for performance evaluation using a number of indicators. A combination of the Stony Brook University microphysics scheme with Tiedtke cumulus scheme is found as the most suitable scheme for reproducing those events. Another combination of the single-moment 6-class microphysics scheme with New Grell 3D cumulus schemes also showed reasonable performance in forecasting heavy rainfall over this region. The sensitivity analysis confirms that cumulus schemes play a greater role than microphysics schemes for reproducing the heavy rainfall events using WRF.

Topography of the intertidal zone along the shoreline of Chittagong (Bangladesh) using PROBA-V imagery

ABSTRACT Across the oceans shorelines, monitoring the topography of the intertidal zone is generally challenging. The present study is motivated by the recognized role of the intertidal topography in the near-shore hydrodynamics. We consider the region of Chittagong (northern Bay of Bengal) because of its propensity to powerful cyclone surges and associated inundation hazard. So as to curb the lack of in situ knowledge of intertidal topography, we present an original procedure relying on spaceborne optical imagery. Our method essentially amounts to a water line detection performed at various tidal levels. We apply our procedure to the recent PROBA-V (Project for On-Board Autonomy-Vegetation) multi-spectral imagery mission. The first step of our procedure concerns the shoreline extraction. PROBA-V imagery consists of four bands (Red, Blue, near-infrared – NIR, short-wave infrared – SWIR), which are then combined to generate an artificial red-green-blue (RGB) image. This RGB image is then converted into the hue-saturation-value (HSV) colour space. A simple thresholding is applied to hue and value channels to separate water masses from land masses. This process is applied to several images taken at different water levels (i.e. different parts of the tidal cycle) and the corresponding water lines are inferred. To estimate the altitude level of the water lines, we rely on tidal observations from two gauges located at Chittagong and Cox’s Bazar. We operate an ad-hoc extrapolation of the point-wise gauge data to generate a synthetic tidal water level record all along the shoreline. These synthetic tidal heights are then combined with the shorelines to generate the final digital elevation model (DEM). The DEM we generated covers a 40-km long stretch of shoreline around Chittagong city. We assessed this DEM by comparison with two independent data sets based on in situ surveys as well as on Pléiades spaceborne stereoscopy. We conclude that our DEM is accurate within 1 m to 2 m, which is within the error bar of these validation data sets. Our procedure being essentially objective, it is easy to automate, for processing of other imagery satellite, including at high resolution and/or in real time.