The Vietnamese Mekong Delta (VMD) is one of the largest rice-growing areas in Vietnam, and exports a huge amount of rice products to destinations around the world. Multi-dike protection systems have been built to prevent flooding, and have supported agricultural intensification since the early 1990s. Semi-dike and full-dike systems have been used to grow double and triple rice, respectively. Only a small number of studies have been conducted to evaluate the water quality in the VMD. This study aimed to analyze the spatiotemporal variation of water quality inside the dike-protected area. Surface water samples were collected in the dry and wet seasons at 35 locations. We used multivariate statistical analyses to examine various water quality parameters. The mean concentrations of COD, NH₄⁺, NO₃⁻, PO₄³⁻, EC, and turbidity were significantly higher in water samples inside the full-dike system than in water samples from outside the full-dike systems and inside the semi-dike systems in both seasons. High concentrations of PO₄³⁻ were detected in most of the primary canals along which residential, tourist areas and local markets were settled. However, NO₃⁻ was mainly found to be higher in secondary canals, where chemical fertilizers were used for rice intensification inside the dike system. Water control infrastructures are useful for preventing flood hazards. However, this has an adverse effect on maintaining water quality in the study area.

A few studies have evaluated the impact of land use land cover (LULC) change on surface water quality in the Vietnamese Mekong Delta (VMD), one of the most productive agricultural deltas in the world. This study aims to evaluate water quality parameters inside full- and semi-dike systems and outside of the dike system during the wet and dry season in An Giang Province. Multivariable statistical analysis and weighted arithmetic water quality index (WAWQI) were used to analyze 40 water samples in each seasons. The results show that the mean concentrations of conductivity (EC), phosphate (PO₄³⁻), ammonium (NH₄⁺), chemical oxygen demand (COD), and potassium (K⁺) failed to meet the World Health Organization (WHO) and Vietnamese standards for both seasons. The NO₂⁻ concentration inside triple and double rice cropping systems during the dry season exceeds the permissible limit of the Vietnamese standard. The high concentration of COD, NH₄⁺ were found in the urban area and the main river (Bassac River). The WAWQI showed that 97.5 and 95.0% of water samples fall into the bad and unsuitable, respectively, for drinking categories. The main reason behind this is direct discharge of untreated wastewater from the rice intensification and urban sewerage lines. The finding of this study is critically important for decision-makers to design different mitigation or adaptation measures for water resource management in lieu of rapid global changes in a timely manner in An Giang and the VMD.

With population growth and resource depletion, maximizing the efficiency of soybean (Glycine max [L.] Merr.) and rice (Oryza sativa L.) cropping systems is urgently needed. The goal of this study was to shed light on precise irrigation amounts and optimal agronomic practices via simulating rice–rice and soybean–rice crop rotations in the Agricultural Policy/Environmental eXtender (APEX) model. The APEX model was calibrated using observations from five fields under soybean–rice rotation in Arkansas from 2017 to 2019 and remote sensing leaf area index (LAI) values to assess modeled vegetation growth. Different irrigation practices were assessed, including conventional flooding (CVF), known as cascade, multiple inlet rice irrigation with polypipe (MIRI), and furrow irrigation (FIR). The amount of water used differed between fields, following each field’s measured or estimated input. Moreover, fields were managed with either continuous flooding (CF) or alternate wetting and drying (AWD) irrigation. Two 20-year scenarios were simulated to test yield changes: (1) between rice–rice and soybean–rice rotation and (2) under reduced irrigation amounts. After calibration with crop yield and LAI, the modeled LAI correlated to the observations with R² values greater than 0.66, and the percent bias (PBIAS) values were within 32%. The PBIAS and percent difference for modeled versus observed yield were within 2.5% for rice and 15% for soybean. Contrary to expectation, the rice–rice and soybean–rice rotation yields were not statistically significant. The results of the reduced irrigation scenario differed by field, but reducing irrigation beyond 20% from the original amount input by the farmers significantly reduced yields in all fields, except for one field that was over-irrigated.