Screening of representative rainfall event series for long-term hydrological performance evaluation of grassed swales.

Evaluation of the hydrological performance of grassed swales usually needs long-term monitoring data. At present, suitable techniques for simulating the hydrological performance using limited monitoring data are not available. Therefore, current study aims to investigate the relationship between saturated hydraulic conductivity (Ks) fitting results and rainfall characteristics of various events series length. Data from a full-scale grassed swale (Enschede, the Netherlands) were utilized as long-term rainfall event series length (95 rainfall events) on the fitting outcomes. Short-term rainfall event series were extracted from these long-term series and used as input in fitting into a multivariate nonlinear model between Ks and its influencing rainfall indicators (antecedent dry days, temperature, rainfall, rainfall duration, total rainfall, and seasonal factor (spring, summer, autumn, and winter, herein refer as 1, 2, 3, and 4). Comparison of short-term and long-term rainfall event series fitting results allowed to obtain a representative short-term series that leads to similar results with those using long-term series. A cluster analysis was conducted based on the fitting results of the representative rainfall event series with their rainfall event characteristics using average values of influencing rainfall indicators. The seasonal index (average value of seasonal factors) was found to be the most representative short rainfall event series indicator. Furthermore, a Bayesian network was proposed in the current study to predict if a given short-term rainfall event series is representative. It was validated by a data series (58 rainfall events) from another full-scale grassed swale located in Utrecht, the Netherlands. Results revealed that it is quite promising and useful to evaluate the representativeness of short-term rainfall event series used for long-term hydrological performance evaluation of grassed swales.

Time-varying characteristics of saturated hydraulic conductivity in grassed swales based on the ensemble Kalman filter algorithm -A case study of two long-running swales in Netherlands.

Saturated hydraulic conductivity (Ks) of the filler layer in grassed swales are varying in the changing environment. In most of the hydrological models, Ks is assumed as constant or decrease with a clogging factor. However, the Ks measured on site cannot be the input of the hydrological model directly. Therefore, in this study, an Ensemble Kalman Filter (EnKF) based approach was carried out to estimate the Ks of the whole systems in two monitored grassed swales at Enschede and Utrecht, the Netherlands. The relationship between Ks and possible influencing factors (antecedent dry period, temperature, rainfall, rainfall duration, total rainfall and seasonal factors) were studied and a Multivariate nonlinear function was established to optimize the hydrological model. The results revealed that the EnKF method was satisfying in the Ks estimation, which showed a notable decrease after long-term operation, but revealed a recovery in summer and winter. After the addition of Multivariate nonlinear function of the Ks into hydrological model, 63.8% of the predicted results were optimized among the validation events, and compared with constant Ks. A sensitivity analysis revealed that the effect of each influencing factors on the Ks varies depending on the type of grassed swale. However, these findings require further investigation and data support.

A comprehensive review on the long-term performance of stormwater biofiltration systems (SBS): Operational challenges and future directions.

Stormwater biofiltration systems (SBS) are a popular technology for mitigating the negative effects of urbanization on the hydrological processes and water quality in urban areas. However, little is known about SBS's long-term performance in actual field conditions. The findings of a review of the scientific literature on the long-term performance of SBS are presented in this paper. The findings show that only a few studies have investigated the performance of SBS and its change over time, and that the results of laboratory and field experiments differed due to the presence of plants, regular maintenance, and some uncertain environmental factors. Based on the existing knowledge gaps in this field, the main challenges observed was the lack of long-term field data series, and the existing mathematical models are not able to accurately forecast the long-term performance of SBS. This could be owing to the difficulties in monitoring activities, the high costs involved and the unpredictability around the operational timeframe. Future study should concentrate on the implementation of simulation and modeling-based research in pilot and full-scale SBS, and the inclusion of new performance indicators should be considered as a priority.