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We investigated the merits of performing multi-scale flood simulations with nested two-dimensional flood simulation models for flood risk management applications over an extended period with infiltration and evapotranspiration. For nested calculations, (1) inter-district, (2) district, and (3) regional scales were arranged as three levels in the nested model. Because the nested method can be useful for flat land, the Gaibandha District in Bangladesh was chosen for the study area. This area is a typical flood-prone area that is inundated frequently by flood flow from the Jamuna River. First, we performed a year-round flooding simulation for the year 2007 by focusing on a monsoon flood, and validated the results via satellite images. Second, we evaluated the differences of floods in the case of 2.33- and 100-year return periods by using discharge data produced by a flood frequency analysis. We successfully simulated the flooding in each nested level for 2007, and this enabled us to evaluate the flood risks at different scales. In addition, we delineated the flood extent for different return periods and clarified the relationship between the peak water level of the river and the flood extent. The nested method proved to be advantageous because its implementation is not computationally demanding. [ABSTRACT FROM AUTHOR]

The global mean surface temperature is rising and under climate change it is expected to increase in the future. The changes are not uniform across the world and the impact assessment at a regional level is, thus, a necessity. Bangladesh, a tropical low-lying monsoon region, is greatly at risk under climate change. However, no attempt has been carried out to assess the changes in frequency of extreme temperatures (return period values) under the backdrop of climate change which is required in practical applications. The aim of this study is to investigate the changes in temperature extremes: maximum (Tx) and minimum (Tn) at the daily time scale under climate change in Bangladesh. The multi-model ensemble methodology comprised of five general circulation models and two emission scenarios from CMIP6 framework was used to evaluate the impact in two future time horizons: 2021–2060 and 2061–2100. The L-moment based frequency analysis with annual maxima (minima) data was used to quantify extreme temperatures in terms of return levels. With this approach, the identification of a probability distribution is one important aspect which is investigated in this study. We have found that the generalized normal (GNO) distribution is quite appropriate of describing the temperature extremes. There is a significant increase in location parameter which signifies a uniform shift for the extreme tail of the distribution. There are no appreciable overall changes in scale and shape parameter. The temperature extremes (both Tx and Tn) are expected to increase noticeably compared to the present observed condition. There is a tendency to have a greater estimate of extremes in the far future than the near future. The greater estimate is also perceived under the high emission scenario in comparison to the medium emission scenario. The country average change in 20-year return period value of Tx by the end of this century is about 3–4.7 °C compared to the corresponding changes of 2.4 to 3.7 °C for Tn. The findings are expected to assist in the evaluation of climate change impacts and adaptation strategies in Bangladesh. [ABSTRACT FROM AUTHOR]

The television medium has occupied a dominant place in Bangladesh. With the unprecedented expansion of the television industry, questions are being raised about a palpable rise in market-oriented journalism (MOJ) in the country. This article examines the theoretical and empirical relationship between MOJ and credibility of TV news. Three surrogate factors of MOJ including independence, social role, and objectivity, along with TV news credibility are analyzed for insights. The findings suggest that there is a complex relationship between the two constructs. To improve the perception of credibility of TV news, our findings suggest an important role of public journalism as an alternative to MOJ. [ABSTRACT FROM PUBLISHER]

Bangladesh is a flood prone country where huge damages take place every year. Therefore, to minimize flood extremes, it is important to control the flood peaks at the upstream area through suitable watershed management practices. The flood control management at the watershed scale requires good quality flood data. However, in developing countries like Bangladesh, such hydrological information is rarely available at the watershed level. Under such circumstances, it is important to use a hydrological model representing the rainfall-runoff process to arrive at the extreme flows in the rivers, which require extreme rainfall data as a major inflow to the hydrologic system. Furthermore, the density of rain gauges in Bangladesh is low and the quality of available flood data is poor. Considering this, it is important to develop regional extreme rainfall maps for the reliable estimation of flood flows in the river by using a suitable modeling approach. Therefore, in the present paper, an attempt has been made to derive the regional best fit extreme rainfall pattern for Bangladesh for the estimation of extreme rainfall quantiles. This study uses the annual maximum daily rainfall of 68 rain gauge stations. An autocorrelation test is applied to test the independency of the data. Later, considering the heterogeneity in the hydroclimatic and topographic details, entire rain gauge stations have been clustered into six hydroclimatically homogeneous regions; namely, northeast (NE), northwest (NW), southeast (SE), southwest (SW), coastal, and central regions, by using the -mean clustering technique. The stations that did not pass the discordant and heterogeneity test were discarded from the regional frequency analysis. For regional frequency analysis, the L-moment method was applied. Based on the goodness of fit test and the L-moment ratio diagram, the generalized extreme values distribution was identified as the best fit for the SE, NW, and coastal regions. However, for NE, central, SW regions, the best fit distributions were generalized logistic and generalized Pareto, respectively. Using the derived distributions, regional extreme rainfall quantiles were estimated, followed by geo-mapping in ArcGIS 9.2. [ABSTRACT FROM AUTHOR]

A case study was conducted in the Teesta subcatchment in Bangladesh for determining design flood flows and corresponding flood stages for different return periods using frequency analysis and MIKE 11 model. Different distribution functions of frequency analysis were tested for their goodness of fit. The observed discharge data at Kaunia on the river Teesta were used for estimation of design flood. The Pearson type-III distribution was found best fitted by the Kolmogorov-Smirnov, D-index, and L-moment diagram ratio tests, and accordingly 25-, 50-, and 100-year return period design floods were computed. The river network of Teesta River was extracted from SRTM 90-m digital elevation model. The river network of Teesta subcatchment was then simulated by MIKE 11 rainfall-runoff Nedbor-Afstromnings-Model (NAM) and HD model. The resultant time series of river stage was then compared with corresponding observed values. From the model, a stage-discharge relationship (Q-h) curve and respective equation were developed for Kaunia station on the river Teesta. The developed equation determines the corresponding flood stage of estimated flood flow of 25-, 50-, and 100-year return periods. The resulting flows and stages will be useful to design hydraulic structures, prepare flood extent maps, assess vulnerability of flood damage for different return periods, and provide flood forecasting for early warnings of floods. The approach presented would be applicable to similar river basin systems where data are limited and scarce. [ABSTRACT FROM AUTHOR]