Impact of tidal dynamics and typhoon-induced inundation on saltwater intrusion in coastal farms.

The increase in storm surge events caused by climate change exacerbates adverse effects on seawater inundation in coastal areas. An accurate description of the water level curve is crucial for understanding the process of saltwater intrusion (SWI) resulting from storm surge. Most studies involving empirical surges as inputs to groundwater models, often simplify spatial and temporal seawater inundation processes, which may increase the uncertainty in vertical seawater intrusion. To address this gap, we employed a comprehensive modeling approach using storm surge model ADCIRC and numerical simulator HydroGeoSphere to reveal SWI dynamics during a historical storm surge event in a coastal farm, considering varying tidal-surge phases and typhoon intensities. Our findings indicate pronounced SWI variations even with consistently highest water level during a storm surge, contingent on prior tidal processes. The timing of typhoon landfall on an hourly scale yielded diverse water level curves, altering the function of SWI. Intriguingly, SWI exacerbates following a high tide with 31.2 % average salinity higher, highlighting the profound modulation effect of tidal levels on SWI. Local topography significantly influenced SWI dynamics. Ponds, for instance, retained elevated salinity levels for over 15 h, indicating a more prolonged exposure to salinity than roads. These findings underscore the importance of considering both tidal influences and topographical factors in understanding and mitigating SWI in coastal agricultural management.

Meta-analysis of microbial source tracking for the identification of fecal contamination in aquatic environments based on data-mining.

Microbial source tracking (MST) technology represents an innovative approach employed to trace fecal contamination in environmental water systems. The performance of primers may be affected by amplification techniques, target primer categories, and regional differences. To investigate the influence of these factors on primer recognition performance, a meta-analysis was conducted on the application of MST in water environments using three databases: Web of Science, Scopus, and PubMed (n = 2291). After data screening, 46 studies were included in the final analysis. The investigation encompassed Polymerase Chain Reaction (PCR)/quantitative PCR (qPCR) methodologies, dye-based (SYBR)/probe-based (TaqMan) techniques, and geographical differences of a human host-specific (HF183) primer and other 21 additional primers. The results indicated that the primers analyzed were capable of differentiating host specificity to a certain degree. Nonetheless, by comparing sensitivity and specificity outcomes, it was observed that virus-based primers exhibited superior specificity and recognition capacity, as well as a stronger correlation with human pathogenicity in water environments compared to bacteria-based primers. This finding highlights an important direction for future advancements. Moreover, within the same category, qPCR did not demonstrate significant benefits over conventional PCR amplification methods. In comparing dye-based and probe-based techniques, it was revealed that the probe-based method's advantage lay primarily in specificity, which may be associated with the increased propensity of dye-based methods to produce false positives. Furthermore, the heterogeneity of the HF183 primer was not detected in China, Canada, and Singapore respectively, indicating a low likelihood of regional differences. The variation among the 21 other primers may be attributable to regional differences, sample sources, detection techniques, or alternative factors. Finally, we identified that economic factors, climatic conditions, and geographical distribution significantly influence primer performance.

Exploring sustainable solutions for the water environment in Chinese and Southeast Asian cities.

Water is essential for human activities and economic development, and the water environment significantly influences ecological balance and global climate. China and Southeast Asia are the most populous areas in the world, and their water resources are deteriorating day by day. We focus on five representative cities such as, Beijing, Jakarta, Hanoi, Kathmandu and Manila to investigate water-environmental problems with the ultimate goal of providing recommendations for sustainable urban water management. The study found that (1) the water environment of all cities has been polluted to varying levels, while the pollution has improved in Beijing and Jakarta, and the situation in other regions is severe. (2) The aquatic biodiversity has reduced, and its pollution is mainly caused by organic pollutants and decreasing river flow. In addition, numerous people live in megacities without access to clean surface water or piped drinking water, which greatly increases the use of groundwater. Further, frequent floods in the world leads to serious damage to urban infrastructure and further deterioration of water environment quality. To address these problems, countries and organizations have begun to construct wastewater treatment plants and develop water-saving technology to ensure healthy and sustainable development of water environment. The results and practical recommendations of this study can provide scientific insights for future research and management strategies to address water quality challenges during ongoing policy debates and decision-making processes.

Comparison of gridded precipitation datasets for rainfall-runoff and inundation modeling in the Mekong River Basin.

Precipitation, as a primary hydrological variable in the water cycle plays an important role in hydrological modeling. The reliability of hydrological modeling is highly related to the quality of precipitation data. Accurate long-term gauged precipitation in the Mekong River Basin, however, is limited. Therefore, the main objective of this study is to assess the performances of various gridded precipitation datasets in rainfall-runoff and flood-inundation modeling of the whole basin. Firstly, the performance of the Rainfall-Runoff-Inundation (RRI) model in this basin was evaluated using the gauged rainfall. The calibration (2000-2003) and validation (2004-2007) results indicated that the RRI model had acceptable performance in the Mekong River Basin. In addition, five gridded precipitation datasets including APHRODITE, GPCC, PERSIANN-CDR, GSMaP (RNL), and TRMM (3B42V7) from 2000 to 2007 were applied as the input to the calibrated model. The results of the simulated river discharge indicated that TRMM, GPCC, and APHRODITE performed better than other datasets. The statistical index of the annual maximum inundated area indicated similar conclusions. Thus, APHRODITE, TRMM, and GPCC precipitation datasets were considered suitable for rainfall-runoff and flood inundation modeling in the Mekong River Basin. This study provides useful guidance for the application of gridded precipitation in hydrological modeling in the Mekong River basin.

Evaluation of low impact development approach for mitigating flood inundation at a watershed scale in China.

Low impact development (LID) has attracted growing attention as an important approach for urban flood mitigation. Most studies evaluating LID performance for mitigating floods focus on the changes of peak flow and runoff volume. This paper assessed the performance of LID practices for mitigating flood inundation hazards as retrofitting technologies in an urbanized watershed in Nanjing, China. The findings indicate that LID practices are effective for flood inundation mitigation at the watershed scale, and especially for reducing inundated areas with a high flood hazard risk. Various scenarios of LID implementation levels can reduce total inundated areas by 2%-17% and areas with a high flood hazard level by 6%-80%. Permeable pavement shows better performance than rainwater harvesting against mitigating urban waterlogging. The most efficient scenario is combined rainwater harvesting on rooftops with a cistern capacity of 78.5 mm and permeable pavement installed on 75% of non-busy roads and other impervious surfaces. Inundation modeling is an effective approach to obtaining the information necessary to guide decision-making for designing LID practices at watershed scales.