Aiming at the method of solving the optimization scheme for urban tidal drainage pumping stations during heavy rainfall below the urban drainage design standard, and the problems such as the mismatch between the head and water level of pumping stations at each divided time period during the solution process, a nonlinear mathematical model for optimal operation of urban tidal drainage pumping station was constructed which took the minimal operation cost of drainage pumping station during given operating period as the study target, and the blade angle of each pump unit in each divided time period as decision variables with the constraints of total water quantity of target drainage, matched motor power of each pump unit, water level of in the drainage area, number of switches and the shortest operation time of pump unit. For the problem of head-water level mismatch at each divided time period of pumping station, the genetic algorithm of coupled head-water level successive approximation is proposed, which can make the optimization scheme realize the matching of river network water level and pumping station operating head. Taking Guazhou Pumping Station in Yangzhou City of Jiangsu Province encountering 10% frequency designed rainfall as an example, optimization schemes under typical working conditions which included different starting drainage water levels and peak-valley electricity prices was obtained, as well as the influence of electricity price of divided time period, average head of each divided time period and inflow on the optimization scheme was carried out. The unit optimal operation drainage costs of Guazhou Pumping Station is 45.46 yuan/10⁴ m³ and 51.32 yuan/10⁴ m³ respectively when the starting drainage water level is set as 4.8 m and 4.6 m, which has the corresponding operation benefit of 15.34% and 4.40% less than that of conventional operation, and the water level variation of river network has dropped 6.61% and 7.85% than that of conventional operation. The constructed optimal operation model of urban tidal drainage pumping station and the proposed solution method can effectively improve the matching degree of pumping head and water level variation, and effectively make a compromise of economic operation of drainage pumping station and the safety requirements of water level control of river network in drainage area. The obtained optimization schemes can offer decision-making reference for relevant dispatching and management departments of drainage pumping stations.

A nonlinear mathematical model for the optimal operation of a parallel pumping station group was established with the objective of minimizing the operation costs of the station group considering the target quantity of water extraction and flow unevenness between units of each station as constraints. The original model is decomposed into several sub-models with a single station multi-objective optimization operation with the target water lifting capacity of a single pump station as the coordinating variable. This constructed model was solved using a large-scale system decomposition dynamic programming aggregation method based on sub-system multi-objective genetic algorithm optimization. Taking the Jiangdu parallel pumping station group in the Chinese East Route of the South-to-North Water Diversion Project as a case study, the results show that under the condition of 80% water lifting load of parallel stations and 7.8 m daily average lift, the unit water lifting cost of the optimal operation of each station decreases by 4.81%, 4.81%, 19.83% and 11.06% compared with the constant speed operation at the specified angle. The unevenness of the flow of each station is 2.16 m³/s, 2.16 m³/s, 0.60 m³/s and 14.10 m³/s. The erosion of the outlet pool is small. This article provides theoretical reference for the optimal operation of the same type of large-scale inter-basin water transfer parallel pumping station groups.

Extreme rainfall-induced events adversely affect agriculture, infrastructure, and socioeconomic development in a region. Therefore, a comprehensive understanding of their occurrences and past and future variability in the context of global warming is imperative, especially at the fine temporal (sub-daily) and spatial (local to regional) scales for better contextualizing inferences from a policymaking perspective. This study provides a detailed analysis of global warming’s impacts on extreme rainfall in Jiangsu Province, utilizing the latest high-resolution ERA5-Land reanalysis data and the latest climate models. A novel temporal disaggregation model was developed to predict future hourly extreme rainfall. The results show that the bias-corrected model reduced the overestimation of extremes by as much as ~7.4% for the location parameter and accurately reproduced the spatial variability of rainfall. Projections from eight climate models indicate a future increase in rainfall intensity by an average of over 7%. Moreover, the projections indicate two contrasting trends for different event durations: short-duration events (e.g., 1 h) show a 7.1% increase at the 5-year return period and a more pronounced 8.9% increase at the 50-year return period. Conversely, long-duration events (e.g., 24 h) experience an 8.4% increase at the 5-year return period and a smaller 6.0% increase at the 50-year return period. This suggests that rarer, short-duration events are expected to increase more than less rare ones, while rarer, long-duration events show a smaller increase than their less rare counterparts. Addressing spatial heterogeneity in extreme rainfall patterns provides actionable insights for climate adaptation and mitigation, supporting initiatives like the ‘Jiangsu Province Climate Change Adaptation Action Plan’. This study underscores the need for policy-driven, community-led climate actions to mitigate flood risks and enhance resilience in a region vulnerable to flooding amidst global warming and increasing human interventions.

Pressurized tree-type water distribution network (WDN) is widely used in rural water supply projects. Optimization of this network has direct practical significance to reduce the capital cost. This paper developed a discrete nonlinear model to obtain the minimum equivalent annual cost (EAC) of pressurized tree-type WDN. The pump head and pipe diameter were taken into account as the double decision variables, while the pipe head loss and flow velocity were the constraint conditions. The model was solved by using the improved decomposition–dynamic programming aggregation (DDPA) algorithm and applied to a real case. The optimization results showed that the annual investment, depreciation and maintenance cost (W₁) were reduced by 22.5%; however, the pumps’ operational cost (p) increased by 17.9% compared to the actual layout. Overall, the optimal EAC was reduced by 15.2% with the optimized pump head and optimal diameter distribution of the network. This method demonstrated an intrinsic trade-off between investment and operational cost, and provided an efficient decision support tool for least-cost design of pressurized tree-type WDN.

The widespread use of nanoplastics inevitably contributes to pollution in aquatic environments and soils. Therefore, it is crucial to understand how these particles migrate in soils with diverse organic matter. This study investigated the effects of low-molecular-weight organic acids (LMWOAs) on the migration of polystyrene nanoplastics (PS-NPs) in goethite-coated quartz sand. The experiments utilized two organic acids, propanoic acid (PA) and tartaric acid (TA), under varying aqueous conditions, including pH levels (4.0, 7.0), ionic strengths (1 mM, 10 mM), and cations (Na⁺, Ca²⁺, Ba²⁺). The experimental results indicated that with the presence of Na⁺, organic acids promoted the migration of PS-NPs through electrostatic forces and steric hindrance, with TA having a greater effect than PA. When pH < pH_pzc, increased concentrations of positively charged goethite coating provided favorable deposition sites for the negatively charged PS-NPs, thereby increasing their deposition. Using the DLVO theory, low pH and high ionic strength (IS) decreased the energy barriers between PS-NPs and porous media, whereas high pH and low IS increased these barriers, thus enhancing PS-NPs transport. Divalent cations Ca²⁺ and Ba²⁺ enhanced the migration of PS-NPs through complex-forming and -bridging agents. These findings offered significant insights for predicting and analyzing the migration behavior of plastic nanoparticles.

The mathematical model of optimal water quantity allocation for a single main canal in a large-scale irrigation area was constructed that took the minimal sum of the squared deviation of water shortage for water receiving areas controlled by the single main canal in one given irrigation period as the study target, and the total irrigation quantity of the single main canal as a constraint condition. Taking the optimal allocation of water quantity of each branch canal as decision variables, and several branch canals under the irrigation sequence of the main canal as a state variable, this model was solved by the one-dimensional dynamic programming (DP) method, by which the minimal water shortage and corresponding optimal water quantity allocation of each branch canal was calculated. The proposed method could provide a decision-making reference for optimal water resources allocation of single main canal irrigation areas, and also provide the theoretical basis for optimal water quantity allocation of a main canal with rotation irrigation by strips or with segmented rotation irrigation mode in China’s large-scale irrigation areas. Taking Hengliu Main Canal of Zhouqiao Irrigation Area in Jiangsu Province as a study case, optimization results showed that in a medium drought year (p = 75%) and a special drought year (p = 95%), minimal water shortage for water receiving areas controlled by Hengliu Main Canal was respectively 2.57 × 10⁴ m³ and 23.31 × 10⁴ m³ during the ponding period of rice. The corresponding water quantity allocation for each branch canal has reflected a compellent model solution precision and efficiency.