ORCID Profile
0000-0003-2331-4996
Current Organisation
Center of Water Manangement and Climate Change
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Publisher: Elsevier BV
Date: 02-2023
Publisher: Elsevier BV
Date: 07-2018
Publisher: Informa UK Limited
Date: 06-01-2020
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 08-2019
Publisher: Elsevier BV
Date: 04-2021
Publisher: Copernicus GmbH
Date: 16-03-2018
DOI: 10.5194/HESS-22-1875-2018
Abstract: Abstract. Recent flood dynamics of the Mekong Delta have raised concerns about an increased flood risk downstream in the Vietnamese Mekong Delta. Accelerated high dike building on the floodplains of the upper delta to allow triple cropping of rice has been linked to higher river water levels in the downstream city of Can Tho. This paper assesses the hydraulic impacts of upstream dike construction on the flood hazard downstream in the Vietnamese Mekong Delta. We combined the existing one-dimensional (1-D) Mekong Delta hydrodynamic model with a quasi-two-dimensional (2-D) approach. First we calibrated and validated the model using flood data from 2011 and 2013. We then applied the model to explore the downstream water dynamics under various scenarios of high dike construction in An Giang Province and the Long Xuyen Quadrangle. Calculations of water balances allowed us to trace the propagation and distribution of flood volumes over the delta under the different scenarios. Model results indicate that extensive construction of high dikes on the upstream floodplains has had limited effect on peak river water levels downstream in Can Tho. Instead, the model shows that the impacts of dike construction, in terms of peak river water levels, are concentrated and lified in the upstream reaches of the delta. According to our water balance analysis, river water levels in Can Tho have remained relatively stable, as greater volumes of floodwater have been erted away from the Long Xuyen Quadrangle than the retention volume lost due to dike construction. Our findings expand on previous work on the impacts of water control infrastructure on flood risk and floodwater regimes across the delta.
Publisher: Elsevier BV
Date: 07-2018
DOI: 10.1016/J.JENVMAN.2018.03.116
Abstract: Large areas of the Vietnamese Mekong Delta floodplains (VMDF) are protected by high dikes to facilitate three rice crops per year. While this has increased rice production, there is evidence that triple rice systems have negative long-term effects, both environmental and economic. Double rice cropping, or other alternatives, may be more advantageous. We analyzed the costs and benefits of intensive rice systems over time and compared these with alternatives farming systems, based on data collected via field surveys and interviews with farmers in two provinces in the VMDF. Results show that farmers in areas with dikes high enough for triple rice production incurred rising production costs over time. Production costs were 58%-91% higher in high-dike, triple crop areas, than in low-dike double rice crop areas. Higher production costs are mainly the result of increased fertilizer and pesticide use. Profitability of triple rice farming systems was initially 57% more compared to double crop systems. After about 15 years, however, triple rice farmers earned only 6% more than double crop counterparts. Our results indicate that alternative farming systems, such as rice combined with vegetables, fisheries or other flood-based livelihood, could offer greater benefits than intensive rice monocultures. Importantly, these higher benefits can be obtained without the environmental costs and impact currently endured across the delta with triple rice cultivation in high dikes.
Publisher: MDPI AG
Date: 24-04-2019
DOI: 10.3390/W11040853
Abstract: The primary goal of this study is to investigate the classification capability of several artificial intelligence techniques, including the decision tree (DT), multilayer perceptron (MLP) network, Naïve Bayes, radial basis function (RBF) network, and support vector machine (SVM) for evaluating spatial and temporal variations in water quality. The application case is the Song Quao-Ca Giang (SQ-CG) water system, a main domestic water supply source of the city of Phan Thiet in Binh Thuan province, Vietnam. To evaluate the water quality condition of the source, the government agency has initiated an extensive s ling project, collecting s les from 43 locations covering the SQ reservoir, the main canals, and the surrounding areas during 2015–2016. Different classifying models based on artificial intelligence techniques were developed to analyze the s ling data after the performances of the models were evaluated and compared using the confusion matrix, accuracy rate, and several error indexes. The results show that machine-learning techniques can be used to explicitly evaluate spatial and temporal variations in water quality.
No related grants have been discovered for Dung Duc Tran.