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Climate change is perceived to be the primary reason for the amplification of extreme climatic phenomena. Estimation of changes in extreme values under climate change thus plays an important role in disaster risk assessment and management. However, the different changes in extremes in two distinct regions: inland and coast under climate change are yet to be investigated meticulously. This study is intended to assess the changes in frequency of rainfall and temperature extremes under the impact of climate change in two distinct locations: coast and inland of Bengal delta, a region highly vulnerable to climate change. The multi-model ensemble (projections from CMIP6 framework) technique with the application of frequency analysis was employed to appraise the impact in two future time horizons. Results suggest that the inland estimate of extreme rainfall by the end of this century is barely able to exceed the coastal estimate of extreme rainfall in present conditions. The rate of increase of warm extremes is almost similar; however, with the cold extreme, the increase rate is a little higher inland than on the coast. In both regions, a greater rise in climate extremes is expected in the far future than in the near future. Overall, the coastal area is expected to be more vulnerable to flooding while the inland to drought under climate change in the Bengal delta region. [ABSTRACT FROM AUTHOR]

Assessing the impact of climate change on streamflow is critical to understanding the changes to water resources and to improve water resource management. The use of hydrological models is a common practice to quantify and assess water resources in such situations. In this study, two hydrological models with different structures, e.g., a physically-based distributed model Liuxihe (LXH) and a lumped conceptual model Xinanjiang (XAJ) are employed to simulate the daily runoff in the Xijiang basin in South China, under historical (1964-2013) and future (2014-2099) climate conditions. The future climate series are downscaled from a global climate model (Beijing Climate Centre-Climate System Model, BCC-CSM version 1.1) by a high-resolution regional climate model under two representative concentration pathways--RCP4.5 and RCP8.5. The hydrological responses to climate change via the two rainfall-runoff models with different mathematical structures are compared, in relation to the uncertainties in hydrology and meteorology. It is found that the two rainfall-runoff models successfully simulate the historical runoff for the Xijiang basin, with a daily runoff Nash-Sutcliffe Efficiency of 0.80 for the LXH model and 0.89 for the XAJ model. The characteristics of high flow in the future are also analysed including their frequency (magnitude-return-period relationship). It shows that the distributed model could produce more streamflow and peak flow than the lumped model under the climate change scenarios. However the difference of the impact from the two climate scenarios is marginal on median monthly streamflow. The flood frequency analysis under climate change suggests that flood magnitudes in the future will be more severe than the historical floods with the same return period. Overall, the study reveals how uncertain it can be to quantify water resources with two different but well calibrated hydrological models. [ABSTRACT FROM AUTHOR]

• Characteristic change of regional estimate of extreme rainfall under climate change is investigated. • Projections from CMIP6 GCMs under two emission scenarios were employed to assess the change in Bangladesh context. • A significant increase in index value is detected under climate change. • The change in growth curve is region specific and a lesser influence is perceived. • An increased value of 22% in 100-year return value is expected under climate change. Climate change is perceived to be the main reason in affecting global rainfall patterns. The estimation of rainfall extremes based on historical data, hence, might undervalue the risk related to the design of water infrastructure system. Bangladesh, a tropical monsoon region, is highly vulnerable to climate change; however, little is investigated in the changes of extreme rainfall under climate change. Also, the impact of climate change on the behavioural changes of regional estimate of extreme estimation is understudied. The goal of this study is to examine the characteristic changes of regional estimate of extreme rainfall at the daily time scale under the backdrop of climate change in Bangladesh. The multi-model ensemble method consists of several global climate models (CMIP6 GCMs) and two emission scenarios were employed to assess the effect of climate change in two time horizons: 2021–2060 and 2061–2100. The regional index-flood approach comprised of index value and growth curve (estimated using generalized extreme value, GEV, distribution) was used to quantify the return period values of extreme rainfall. The above approach was applied to observed as well as simulated rainfall data to quantify the changes in extreme quantiles. There is a significant increase of index value under climate change. There is a tendency to have a higher estimate of index value in the far future than the immediate future. The higher estimate is also detected under the higher emission scenario compared to the medium emission scenario. The changes in growth curves are region specific and do not follow the same characteristics as the index value. A similar behaviour of shape of GEV is noticed at present and future conditions. Overall, an increased value of about 22% in 100-year return level is expected by the end of this century under the changing conditions of climate. [ABSTRACT FROM AUTHOR]