Environmental changes have become a global issue of universal interest because of its influence sphere and effect level on humanity. The Mekong River Delta, in general, and Tien Giang Province, in particular, play a crucial role in providing food to Viet Nam and all over the world more broadly. However, there have been fluctuations in planted areas of rice and rice output in recent decades due to the damaging consequences of many natural and man-made agents. In this study, partial least-squares (PLS) regression was applied for quantitative analysis in the combined impact of dams upstream, climate change, drought, rising tide and sea level on change of paddy land; the geo-statistic was used for demonstrating the linear of variations among components in the mentioned nexus. Then, the impact factor, flowchart and equation were established for demonstrating their influences on the planted area of rice in the province. The results showed that the hydropower dams are the largest agent which create the variations of paddy land in the study area, by R2 = 0.726.
The main purpose of this study is to evaluate the performance of Sentinel - 2A and Landsat 8 data in monitoring coastline change from 1999 to 2018 at Cam Pha city, Quang Ninh province. Both data were collected under similar conditions of time and weather features to minimize the differences in interpretation results caused by these factors. The coastline was extracted from Sentinel-2A and Landsat 8 in 2018 by using the Normalized Difference Water Index (NDWI). Coastline map from Quang Ninh Department of Natural Resources and Environment with a scale of 1: 50.000 in 1999 was used as a reference of the same mask and overlaid on coastline maps in 2018 to identify the changes in the study area. The data from fieldwork and Google Earth was used to evaluate the accuracy and make comparative comments. The results presented that changes dramatically occurred between 1999 and 2018 with the accretion process prevailing. This process took place quite strongly on the East and Southeast coast while the erosion process only occurred with small areas at scattered points in the study area. The results also showed that the overall classification accuracy of Sentinel-2A imagery (95.0%) was slightly higher than that of Landsat-8 (87.5%). The combined use of Landsat-Sentinel-2 imagery is expected to generate reliable data records for continuous detecting of coastline changes.
Hai Duong is a province in the Red River Delta of northern Vietnam, with a GDP of 3020 USD/year. Its economy depends mainly on natural conditions, especially agriculture. In the context of climate change, drought will be a natural disaster that greatly affects the economy and agriculture is no exception. Using the Pearson correlation coefficient evaluation method and building multi-linear regression equations, a good correlation was found between total evaporation and total monthly rainfall, monthly mean temperature, monthly maximum temperature and monthly minimum temperature. This is the basis for calculating potential future evaporation based on climate change scenarios. Calculating the drought index K with the input data of climate change scenarios for Vietnam, this analysis has calculated the drought evolution for the three driest months of the year (12, first, 2) for the period 2021- 2050 in Hai Duong province. Results show that with both scenarios (RCP 4.5 and RCP 8.5), the drought index K is at drought and very high drought levels. The drought level in RCP 8.5 is higher than in RCP 4.5 while the drought level at Chi Linh meteorological station is 1.4-1.5 times higher than that at Hai Duong meteorological station. It emerges that drought is clearly cyclical with the drought scenario RCP 8.5 which reaches its maximum every 9-10 years.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.