Dang An Tran

Nghiên cứu đánh giá và phân vùng nguy cơ sạt lở khu vực Bàu Trắng, huyện Bắc Bình, tỉnh Bình Thuận

The Mekong Delta, an important agricultural and economic hub in Vietnam, has suffered from severe water quality issues caused by both natural and anthropogenic forces. This paper aims to conduct a rational statistical approach to evaluate the current situation of surface water quality in the Mekong Delta, applying Factor Analysis (FA), Principal Component Analysis (PCA), and Agglomerative Hierarchical Clustering (AHC) to a database of 3117 samples collected by national and provincial monitoring stations. The results revealed significant contamination with organic pollutants (BOD5: 3.50–172.870 mg/L, COD: 6.493–472.984 mg/L), pesticides (e.g., DDTs: n.d to 1.227 mg/L), trace metals (As: 0.006–0.046 mg/L, Cr: n.d–1.960 mg/L), and microbial indicators (Coliforms: n.d–45,100 MPN/100 mL), often higher than the WHO drinking water threshold. PCA/AHC analysis identified the following five major pollution components: (1) organic pollution and sewage/industrial and deposited chemicals (PCA1—23.08% variance); (2) pesticide and agricultural runoff derived contamination with Hg (PCA2—15.44%); (3) microbial pollution of the water was found to correlate positively with Zn and Cu content (PCA3—8.90%); (4) salinity was found to mobilize As and Cr (PCA4—8.00%); (5) nutrient/microbial pollution presumably from agricultural and sewage inputs (PCA5—7.22%). AHC showed some spatial variability that grouped samples in urban/industrial (Cluster 1), rural/agricultural (Cluster 2), and a highly contaminated one, where water was toxic and presented with microbial and Cd contamination (Cluster 3). Levels of pesticides, Cr, and microbial pollution were higher than reported in previous Mekong Delta studies and exceeded regional trends. These results emphasize the importance of holistic water management strategies, including better wastewater treatment, pesticide control, sustainable farming, and climate-adaptive measures to reduce saltwater intrusion and safeguard drinking water quality for the Mekong Delta.

Nghiên cứu phân vùng mức độ thích nghi đối với các loại rừng trồng trong vùng đất bán ngập lòng hồ Srok Phu Miêng, tỉnh Bình Phước, Việt Nam

Evaluating the spatial and temporal model performance of distributed hydrological models is necessary to ensure that the simulated spatial and temporal patterns are meaningful. In recent years, spatial and temporal remote sensing data have been increasingly used for model performance evaluation. Previous studies, however, have focused on either the temporal or spatial model performance evaluation. In addition, temporal (or spatial) model performance evaluation is often conducted in a spatially (or temporally) lumped approach. Here, we evaluated (1) the temporal model performance evaluation in a spatially distributed approach (spatiotemporal) and (2) the spatial model performance in a temporally distributed approach (temporospatial). We further demonstrated that both spatiotemporal and temporospatial model performance evaluations are necessary since they provide different aspects of the model performance. For this, a case study was developed using the Soil and Water Assessment Tool (SWAT) for the Upper Baitarani catchment in India, and the spatiotemporal and temporospatial model performance was evaluated against three different remotely based actual evapotranspiration (ETa) products (MOD16 A2, SSEBop, and TerraClimate). The results showed that an increase in the spatiotemporal model performance would not necessarily lead to an increase in the temporospatial model performance and vice versa, depending on the evaluation statistics. Overall, this study has highlighted the necessity of a joint spatiotemporal and temporospatial model performance evaluation to understand/improve spatial and temporal model behavior/performance.