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Polydisperse particles are ubiquitous in both the natural and engineered environment, and the precise prediction of the transport and capture of polydisperse particles in a saturated medium is crucial. Several efforts (Yao model, RT model, TE model, MPFJ model, NG model, MHJ model, and MMS model) were developed to obtain accurate correlation equations for the particle capture probability (single-collector removal efficiency), but the applicability of the existing models to the entire porous medium and the retention characteristic of the polydisperse particles are still unclear. In this study, sand column experiments were undertaken to investigate the transport and capture processes of the polydisperse particles in the saturated medium. The mass density was employed to quantize the effects of particle polydispersity and incorporated into the depth-dependent deposition rate. The experimental results showed that the polydisperse particles formed a hyper-exponential retention profile even under favorable conditions (no repulsion). The excellent agreement between the results obtained from the MMS model and the experimentally observed results of the breakthrough curves (BTCs), as well as the retention profiles demonstrated the validation of the MMS model, as the correlation coefficient and the standard average relative error were 0.99 and 0.005, respectively. The hyper-exponential retention profile is caused by the uneven capture of the polydisperse particles by the porous medium. This study highlights the influences of particle polydispersity on particle transport and capture in a saturated porous medium.

To overcome the difficulty that existing hydrological models cannot accurately simulate hydrological processes with limited information in irrigated paddy areas in southern China, this paper presents a prediction model combining the Ensemble Empirical Mode Decomposition (EEMD) method and the Long Short-Term Memory (LSTM) network. Meteorological factors were set as the multivariate input to the model. Rainfall, regarded as the main variable affecting runoff, was decomposed and reconstructed into a combination of new series with stronger regularity by using the EEMD and K-means algorithm. The LSTM was used to explore the data laws and then to simulate and predict the runoff of the irrigated paddy areas. The Yangshudang (YSD) watershed of the Zhanghe Irrigation System (ZIS) in Hubei Province, China was taken as the study area. Compared with the other models, the results show that the EEMD-LSTM multivariate model had better simulation performance, with an NSE above 0.85. Among them, the R2, NSE, RMSE and RAE of the EEMD-LSTM(3) model were the best, and they were 0.85, 0.86, 1.106 and 0.35, respectively. The prediction accuracy of peak flows was better than other models, as well as the performance of runoff prediction in rainfall and nonrainfall events, while improving the NSE by 0.05, 0.24 and 0.24, respectively, compared with the EEMD-LSTM(1) model. Overall, the EEMD-LSTM multivariations model is suited for simulating and predicting the daily-scale rainfall–runoff process of irrigated paddy areas in southern China. It can provide technical support and help decision making for efficient utilization and management of water resources.

The artificial recharge of stormwater is an effective approach for replenishing aquifer and reduce urban waterlogging, but prone to clogging by suspended particles (SP) that are highly heterogeneously sized. In this paper, the transport and deposition of SP in a sand column were investigated under a constant flow condition, for five stormwater concentrations. A depth-dependent initial filter coefficient is incorporated into the conventional filtration model. This modified model considers the heterogeneity of the particle population by lumping the capture of heterogeneous SP into a capture probability. The good agreement between the results of the modified model and the experimental results of measured outlet concentration and average specific deposit validated the modified model. The experiment data and the simulation results both indicate that the highly hyper-exponential retention profiles are caused by non-uniform deposition of heterogeneous SP, and, the conventional model was found to homogenize the spatial distribution of SP retention and overestimate retention of the porous medium. Local and overall permeability reductions were assessed by an empirical relationship and the Kozeny-Carman model, respectively. It is shown that consideration of polydisperse suspended particles is of primary importance. This study highlights the effects of polydisperse particles on SP deposition in a saturated porous medium.

A laboratory study was undertaken to investigate the physical clogging of a sand medium by injecting suspended particles (SP), with diameters ranging from 0.03 to 63.41 &mu, m, into an infiltration basin, which was installed in a sand tank under the condition of constant head. The hydraulic conductivity (K) of the saturated porous medium was found to have decreased by 27% because of re-arrangement over the seven days of self-filtration. A clogging layer was observed on the infiltration basin bottom, probably due to straining over the stormwater infiltration stage. Particle-size analyses also indicate that retention of bigger SP led to faster straining of smaller SP, despite the small fraction of bigger SP. The clogging layer weakened the hydraulic connection between the water level in the basin and the water table of the unconfined aquifer until nearly no water could infiltrate into the aquifer. The deposition of finer SP that entered into the aquifer are governed by the hydrodynamic forces. These finer SP caused non-uniform permeability reduction of the porous medium, with an estimated 35% of permeability reduction occurring beneath the infiltration basin. However, the reduction appears to be reversible, as the fine SP deposited on the pore surfaces of the porous medium can be released or detached by the continuous horizontal hydraulic gradient. Extended tailing of the outlet breakthrough curve (BTC) also strongly supported the detachment of SP. This study focused on the effects of particles&rsquo, polydispersity and hydrodynamic forces on the hydraulic characteristics of the porous medium.

Karst aquifers produce the world&rsquo, s largest springs and supply the water resources to about a quarter of the global population while being influenced by high-intensity human activities. Knowledge about spring discharge hydrographs driven by the effects of artificial regulation is essential to develop practical strategies for the management of karst groundwater. Based on hydrogeological conditions of the karst aquifer in Jinan, a two-dimensional laboratory tank was constructed, and a corresponding numerical simulation model was developed to explore how artificial regulation drives spring hydrographs in northern China. The results showed that the spring hydrographs were significantly changed under the effects of artificial regulation. The recession coefficient increased with pumping and decreased with increasing injection rates. The late sub-recession of spring discharge did not obey the exponential recession under the influence of injection. Pumping and injection in conduit zones showed more obvious effects on the recession coefficient in the late sub-recession curves. Groundwater exchange between conduits and fissure zones differed totally for different artificial regulation modes. With continuing rainfall, the flow fields were gradually controlled by rainfall. There was a time lag in the flow fields caused by rainfall. Under the stress of exploitation at different positions, stagnation points appeared at different locations in fissure zones, and locations of stagnation points were highly dependent on the positions of pumping wells. These findings are essential for better management of karst groundwater and karst spring protection.