Historical Analysis of Rationalizing South-West Coastal Polders of Bangladesh

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

The Bengal Water Machine: Quantified freshwater capture in Bangladesh

Global food security depends on the sustainability of irrigated agriculture. Rising groundwater withdrawals from seasonally humid, alluvial plains across tropical Asia have enabled dry-season rice cultivation. This groundwater pumpage increases available subsurface storage that under favorable conditions amplifies groundwater replenishment during the subsequent monsoon. We empirically quantified this nature-based solution to seasonal freshwater storage capture described as the "Bengal Water Machine," revealing its potential and limitations. On the basis of a million piezometric observations from 465 monitoring wells, we show that the collective operation of ~16 million smallholder farmers in the Bengal Basin of Bangladesh from 1988 to 2018 has induced cumulative freshwater capture that volumetrically (75 to 90 cubic kilometers) is equivalent to twice the reservoir capacity of the Three Gorges Dam

Uptake of climate change adaptation research results in South Asia

Climate Resilience and National Resilience programs focus on formulating the Bangladesh National Adaptation Plan (NAP) for long-term adaptation investments and enhancing the national capacity to integrate climate change adaptation (CCA) in planning, budgeting, and financial tracking process. However, these programs and projects need a system-level quantitative tool to assess the requirement for adaptations at different scales and consequently decide on adaptation financing for these programs and projects. The current project is built on the earlier findings of the DECCMA project to address the above issues, with the target to add the necessary refinement through incorporating the equity, accessibility, adequacy, and gender dimensions to be useful at different scales of adaptation for climate change. The Dynamic Adaptation Model (DAM) is a product that has been developed gradually. It can be applied at different scales that can support the different communities and sectorial agencies/departments to guide local and national planning to adaptations while prioritizing in selecting appropriate options in different programs and projects to ensure the efficient use of available resources. DAM is developed based on strong mathematical formulation supported by field evidence. The model is calibrated and validated using field data to quantify the present-day adaptation need and now is being tested for some of the proposed adaptations in the NAP processes to assess its usefulness at the national level. Moreover, it is the home-grown model; therefore, the required customized version for different communities and agencies is possible through updates in the future with its extension for new areal coverage in collaboration with the developers and the alignment of the recent national initiatives. These are the ongoing processes essential to make it worthwhile for the mainstream national adaptation plan that needs further work

Scale-Dependent Reliability of Projected Rainfalls over Bangladesh with the PRECIS Model

The regional climate model, Providing REgional Climates for Impact Studies (PRECIS), has been widely used throughout the world to generate climate change projections for impact studies and adaptations. Its recent application in South Asia also includes the projection of rainfall extremes. In spite of its wide application, a stringent validation of the model is yet to be reported. In this study, we assessed the performance of the model in simulating annual, monthly and extreme rainfalls over Bangladesh by using a number of statistical techniques, e.g., pattern (both spatial and temporal) correlation, root mean square difference (RMSD), mean absolute difference (MAD), Student’s t-test for significance, probability density functions, etc. The results indicated that the PRECIS model could capture the overall spatial pattern of mean annual and monthly rainfalls very well. However, the inter-annual variability was poorly simulated by the model. In addition, the model could not capture the rainfall extremes. A spatial aggregation of rainfall data did not improve the reliability of the model as far as variability and extremes are concerned. Therefore, further improvements of the model and/or its driving global climate model are warranted for its practical use in the generation of rainfall scenarios

Mechanisms and drivers of soil salinity in coastal Bangladesh

Determining soil salinity within the delta is crucial as it is the dominant factor determining crop productivity. There are numerous interacting drivers that influence soil salinity, including climate variability, saline river water inundation, storm surge inundation, depth to groundwater table, groundwater salinity, and shrimp farming (Bagda). For the study area, tidal river salinity appears to influence the soil salinity most, particularly in the south-west of the delta. In northern areas, high groundwater salinity levels, combined with a high groundwater table, are a major contributor to soil salinity. In addition, an increase in salinity of dry season irrigation water is expected to increase salt accumulation in soils, with a possibility of irrigation water salinity exceeding five parts per thousand