ABSTRACT
Climate change-induced saline intrusion into both surface and groundwater, extreme weather events, and unregulated water usage are serious threats to the drinking water supply in coastal areas worldwide, especially in least-developed countries. This research developed a data-driven decision-making methodology to evaluate the performance of rainwater harvesting (RWH) systems in the saline-prone southwestern coastal region of Bangladesh. Twenty-five community managed RWH systems, recently piloted in two major coastal districts, were considered the case study to develop and validate this evaluation tool. The evaluation methodology integrates daily water models, lifetime cost analysis, Geographic Information System (GIS)-based parameters supported by the Analytical Hierarchy Process (AHP), and field observation. While the meteorological parameters as well as the hydrological and economic performance were found to be highly suitable, 36 % of the systems showed moderate performance, as challenges remain in ensuring proper operation and maintenance practices at the community level. However, 40 % of the systems showed high performance, with two systems showing very high suitability, which suggests community managed RWH systems as a sustainable adaptation for coastal water supply.
ABSTRACT
Bangladesh, known for its remarkable ecological diversity, is faced with the pressing challenges of contemporary climate change. It is crucial to understand how vegetation dynamics respond to different climatic factors. Hence, this study aimed to investigate the spatio-temporal variations of vegetation and their interconnectedness with a range of hydroclimatic factors. The majority of the dataset used in this study relies on MODIS satellite imagery. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), precipitation (PPT), evapotranspiration (ET), and land surface temperature (LST) data from the years 2001 to 2020 have been obtained from Google Earth Engine (GEE). In this study, the temporal variations of the NDVI, EVI, PPT, ET, and LST have been investigated. The findings of the Mann-Kendall trend test indicate noticeable trends in both the NDVI and the EVI. Sen's slope value for NDVI and EVI is 0.00424/year and 0.00256/year, respectively. Compared to NDVI, EVI has shown a stronger connection with hydroclimatic factors. In particular, EVI exhibits a better relationship with ET, as indicated by a r2 value of 0.37 and a P-value of 6.81 × 10-26, whereas NDVI exhibits a r2 value of 0.17 and a P-value of 2.96 × 10-11. Furthermore, ET can explain 17% of the fluctuation in NDVI, and no correlation between NDVI and PPT has been found. The results clarify the significant relationship between the EVI and hydroclimatic factors and highlight the efficiency of the EVI for detecting vegetation changes.
