Journal of Hydro-environment Research最新文献

In the context of climate change and urbanization, urban floods have been one of the major issues around the world, causing significant impacts on the society and environment. To effectively handle these floods, an appropriate design of the urban drainage system (UDS) is highly important as its function can significantly influence the flooding severity and distribution. In recent years, evolutionary algorithms (EAs) have been increasingly used to design UDS due to their great ability in identifying optimal solutions. However, low computational efficiency and low solution practicality (i.e. the final solutions do not satisfy the design criteria) are major challenges for the majority of EA-based methods. To this end, this paper proposes an improved ant colony optimization (ACO, a typical type of EAs) based method to enhance the UDS design effectiveness, where the optimization efficiency is enhanced by initializing the ACO using an approximate design solution identified by the engineering design method, and the solution practicality is improved by explicitly accounting for the design criteria within the optimization using a proposed sampling method. The utility of the proposed method is demonstrated using two real-world UDSs with different system complexities. Results show that the proposed method can identify design solutions with significantly improved efficiency and solution practicality compared to the traditional design approach, with advantages being more prominent for larger UDS design problems. The proposed method can be used by researchers/ practitioners to explore and develop better understanding of the UDS design alternatives under various challenges of climate change and rapid urbanization.

The use of a sunken lawn is an emerging Low Impact Development (LID) technique to effectively control storm runoffs. However, the random infiltration of rainwater that occurs due to the construction of a sunken lawn in an area of collapsible loess seriously threatens the safety of buildings around it. Setting up a vertical soil sand layer (VSSL) structure next to a sunken lawn as an anti-permeate method has been proposed in this study. To analyze the lateral anti-seepage effects of a VSSL, a sunken lawn model around a building was established based on soil physical parameters, and water seepage in the sunken lawn was investigated using a infiltration experiment and HYDRUS-2D software. The results show that the anti-seepage effects of a VSSL can significantly reduce the average wetting front migration length and water content at the observation points behind the sand layer. The Nash-Sutcliff Efficiency (NSE) index was used to evaluate the accuracy and reliability of the HYDRUS-2D model. The values of the NSE index obtained were greater than 0.82 (varied between 0.82 and 0.98) which confirmed the applicability of the HYDRUS-2D software in accurately describing the hydraulic behavior of the lateral anti-seepage effects of the VSSL in a sunken lawn. Simulation infiltration tests showed that, on the side of the VSSL, the wetting front migration length was reduced by 55.5% on average, and the water content of the observation points behind the sand layer was reduced by 40.5%, increasing the stability of the loess around the building infrastructure. The results are of value in practical applications, such as for devising engineering or non-engineering measures to avoid loess collapsibility around sunken lawns.

This paper proposes an introductory review of the historical evolution of urban stormwater management, as well as of current trends, challenges, and changes of paradigm. It reminds us first that most of the existing urban stormwater infrastructures in developed cities are based on the modern urban sewer systems developed in the second half of the 19^th century in Europe. They have been built and for decades managed almost solely by urban sanitation and water specialists, relatively independently of other technical services and, more generally, of other stakeholders in cities. They contributed significantly to public health and fast conveyance of stormwater outside the cities. However, at the turn of the 1970s, it became evident with increasing urbanisation that they also had drawbacks: artificialisation of soils, reduction of aquifer recharge, pollution of surface water and ecological impacts, etc. The paper indicates how new concepts and paradigms thereafter emerged to manage stormwater by means of more sustainable and integrated approaches, aiming to solve the problems engendered by the previous approaches. This integration embraces more and more disciplines and issues, far beyond the traditional field of urban water engineers and specialists. The paper attempts to explain the need for this evolution, making urban stormwater management more much complex, dealing and interacting with ecology, biodiversity, bioinspiration, architecture, landscape and water values, citizens’ well-being, history, culture, and socio-economic aspects.

Low impact development (LID) systems have potential to make urban cities more sustainable and resilient, particularly under challenging climate conditions. To quantify performance capabilities, modeling results for an array of combinations of LIDs are described using PCSWMM at lot-level to examine performance of individual LIDs on volume and peak flow reductions. Among the four LIDs studied: rain barrel (RB), vegetative swale (VS), bioretention cell (BC), and permeable pavement (PP), PP at lot-level demonstrated the best capability for reducing surface runoff volumes and peak runoff rates under historical weather conditions, while BC showed similar capability for reduction of runoff volumes but minimal peak flow reduction. With PP as the controlling method at lot-level, the maximum percentage reduction of runoff volume for a 2-year storm is 58% whereas for a 100-year storm, the runoff volume reduction is 20%. These results mean the extent of flooding that may arise from the 100-year storm is reduced, but not eliminated. Effectively, the 100-year storm volumes with LID are devolved to have flooding equivalent to a 25-year storm. Under climate change scenarios, performance for all LIDs declined at various levels, where BC was the most resilient LID for a climate change scenario, such that projected 2-year or 5-year storms with climate change will have its impact devolved with LID in place, to result in similar volumes and peaks without LID under historical conditions. Furthermore, even with an assembly of lot-level LIDs distributed throughout the community, there is not attenuation to substantial degrees of flooding for major events, but there can be effective control for water quantity for small (2- to 5-years in particular) storm events.

Adverse impacts of climate change on the ecosystem have been a significant concern in the last decades. However, the studies related to the impacts of climate change on water resources, especially in northern Pakistan are of great importance as this region is the main supplier of freshwater to the downstream areas. So, the present study was carried out in Chitral River Basin (CRB) to investigate the long term climatic and topographic changes. Spatiotemporal datasets from MODIS Land Cover Type product (MCD12Q1) from 2001 to 2018, ground-based observational climatic and hydrological data were used. Moreover, the Mann-Kendall trend test, linear regression analysis, correlation, and Sen’s slope values for the mean annual and seasonal flows were assessed. The acquired results show that land use changes are the key non-natural factors in transforming the ecological and hydrological processes of CRB. The mixed and evergreen forest, shrubland, savannas, and barren land respectively decreased from 0.07 to 0.03%, 0.07 to 0.05%, 3.64 to 3.25%, and 70.10 to 67.17%, from 2001 to 2018. In addition, a considerable increment in snow cover from 8.79% to 10.71%, and slight increment in grasslands, wetlands, and croplands were also found between the period of observation. In addition, total annual precipitation and mean annual stream flow showed slight upward trends. Annual increment in total rainfall and snow covered area could be the possible reasons for the observed increased river flow.

The dissolved oxygen (DO) concentration is an important index of water quality. It has a significant impact on the biodegradation process in water and the survival of aquatic organisms. Low DO concentrations often exist and may result in a deterioration in water quality and an increase in wastewater treatment expenses. An analysis of the oxygen transfer efficiency as correlated with the flow characteristics of a falling jet could help to solve these problems. Experiments related to oxygen transfer along a falling water jet were conducted, and the effects of the flowrate ($Q$), falling height ($H$) and initial DO concentration ($c_u$) were considered. The results demonstrated that a falling jet in air could be an effective way of improving the DO concentration. The results also indicated that the oxygen transfer efficiency is linearly dependent on $c_u$ and has a negative exponential relation with $H$. To deeply analyze the oxygen transfer process, the jet disturbance process was divided into 3 parts for the first time based on flow features: a smooth zone, turbulent zone and breakup zone. The results showed that the jet outlet velocity had a limited influence on the smooth zone height but assisted in jet breakup. Thereafter, a correlation modeling DO reaeration along the falling jet considering jet disturbance characteristics was obtained. This correlation was also applied to predict the aeration efficiency in experimental cases from the literature and showed good agreement with the reported results.

Information and communication technologies combined with in-situ sensors are increasingly being used in the management of urban drainage systems. The large amount of data collected in these systems can be used to train a data-driven soft sensor, which can supplement the physical sensor. Artificial Neural Networks have long been used for time series forecasting given their ability to recognize patterns in the data. Long Short-Term Memory (LSTM) neural networks are equipped with memory gates to help them learn time dependencies in a data series and have been proven to outperform other type of networks in predicting water levels in urban drainage systems. When used for soft sensing, neural networks typically receive antecedent observations as input, as these are good predictors of the current value. However, the antecedent observations may be missing due to transmission errors or deemed anomalous due to errors that are not easily explained. This study quantifies and compares the predictive accuracy of LSTM networks in scenarios of limited or missing antecedent observations. We applied these scenarios to an 11-month observation series from a combined sewer overflow chamber in Copenhagen, Denmark. We observed that i) LSTM predictions generally displayed large variability across training runs, which may be reduced by improving the selection of hyperparameters (non-trainable parameters); ii) when the most recent observations were known, adding information on the past did not improve the prediction accuracy; iii) when gaps were introduced in the antecedent water depth observations, LSTM networks were capable of compensating for the missing information with the other available input features (time of the day and rainfall intensity); iv) LSTM networks trained without antecedent water depth observations yielded larger prediction errors, but still comparable with other scenarios and captured both dry and wet weather behaviors. Therefore, we concluded that LSTM neural network may be trained to act as soft sensors in urban drainage systems even when observations from the physical sensors are missing.

The use of bioretention areas is common in urban stormwater management, but their performance varies significantly depending on rainfall characteristics and design conditions. In this study, a pilot experiment using bioretention columns with different media (commercial activated carbon and river sediment-derived biochar) investigated the influence of rainfall on bioretention performance. The results indicated that the runoff volume retention ratio (R_v), which included the runoff purified and discharged at the bottom of the column, and the runoff retained in media during rainfall event, decreased significantly with increases in the rainfall event return period (p < 0.05). The R_v of the activated carbon and biochar columns decreased with a 2-yr return period and then fell further with a 50-yr return period. Porous material has been shown to improve the water-holding capacity of bioretention media, but it did not result in an improved R_v under heavy rain that exceeded the 2-yr return period. With the increase of the return period from two to 50 yr, the mass removal efficiency (R_L) of total phosphorus and phosphate illustrated a clear decreasing trend in all columns. The total nitrogen, ammonia and nitrate removal did not show a clear trend with return periods because of transformations among different forms of nitrogen and similar saturation periods during the different rainfall events. The influence of the return period on chemical oxygen demand (COD) removal was related to whether the inflow COD reached maximum COD removal capacity of the bioretention media. Under a rainfall event with a specific return period, there were no significant differences in the R_L of all nitrogen species and COD among the different columns (p > 0.05). The addition of adsorptive material, such as activated carbon and biochar, may not be the key factor for improving nitrogen and COD removal under heavy rain that exceeds the 2-yr return period. The bioretention performance of phosphorus removal from urban stormwater runoff could be improved by replacing or adding media with high adsorption capacity, but these improvements would not be significant under heavy rain that exceeds the 2-yr return period. The results provide some reference for evaluating bioretention performance and optimizing bioretention design in the future.

Typhoon Aere in 2004 induced severe sedimentation and loss of storage capacity of the Shihmen Reservoir in northern Taiwan. The resulting dramatic increase in the turbidity of the water seriously affected the water supply. To effectively maintain the stability of the water supply and maintain the reservoir’s storage capacity, the government of Taiwan began to plan and construct a series of improvement measures, such as a sediment flushing tunnel, the JhongJhuang Bank-Side Reservoir, and the Amuping Desilting Tunnel. However, previous studies only focused on the impact of the sediment flushing tunnel and the Amuping Desilting Tunnel on the downstream riverbed, and did not consider the possibility of increasing sediment discharge after the completion of the JhongJhuang Bank-Side Reservoir. In addition, climate change will cause the intensity of extreme rainfall to increase enormously in the future. That rainfall and extra sediment flushing will challenge the existing flood prevention facilities. Therefore, this study considered that the JhongJhuang Bank-Side Reservoir will increase sediment discharge of the Shihmen Reservoir, and used dynamical downscaling extreme typhoon data of climate change under the RCP 8.5 scenario to explore the flood prevention and riverbed migration of the main channels of the Dahan and Tamsui Rivers in the future. We used the rainfall–runoff model of Hydrologic Modeling System to simulate rainfall and runoff, and used the hydraulic and sediment transport model of CCHE1D to holistically simulate flood events and consequent river scouring and deposition behaviors. Our results showed that the projected peak discharge during the late 21st century (2075 to 2099) will be at least 50% higher than that during the baseline (1979 to 2003) period. In terms of flood prevention, the potential of overbank flooding will increase in the downstream area, and the trend of long-term change in the riverbed will be dominated by degradation (-0.489 ± 0.743 m) in the future. The improvement measures will have a limited impact on riverbed migration (0.011 ± 0.094 m) in the Dahan and Tamsui Rivers. After the operation of the JhongJhuang Bank-Side Reservoir, the Shihmen Reservoir is expected to increase the sediment discharge ratio by 70% during floods, and it will not cause excessive water turbidity that may affect downstream water supply.