With the development of the economy, the contradiction of water resources in the lower Yellow River area is becoming increasingly serious. Economic development not only increases the socio-economic water demand, but also causes damage to the environment. In order to ensure the safety of the vast plains along the lower Yellow River, protect the environment of the lower Yellow River and estuaries, and achieve environmental sustainability of the lower Yellow River, a model was established to optimize the allocation of water resources with the goal of ecological, safety, and social benefits, combining the uncertainty of water resources, the uncertainty of the water demand during the flood season under different water and sediment conditions, and the water requirements of different water users. An improved ecological footprint method considering soil water was applied during the allocation. Thirty different scenarios were set up, and appropriate scenarios for 2025 and 2030 in wet, normal, and dry years were calculated, providing a reference for decision makers. Results show that: 1) The water supply is affected by the amount of water resources and water demand for sediment transport in the lower Yellow River. The satisfaction of sediment transport and the water supply rate during wet years can reach a high level of satisfaction. 2) When the regional water resources ecological footprint is the smallest, the allocation of water resources tends to the section or unit with a smaller ecological footprint. Therefore, the river sections with the lowest water shortage rates are Lijin-Hekou and Sunkou-Aishan, and the unit with a low water shortage is ecological and industrial water.

Water sources carry chemicals that can have a significant impact on the water environment of a river network, and understanding the contribution of different water sources to the river network can help to manage the pollution of the river network at its source. Hydrological connectivity of a river network affects the self-purification capacity and flood prevention capacity of the river. Thus an isotope tracer approach was applied to figure out the contribution rate of different water bodies to a river network and hydrological connectivity was quantified by introducing retention rate. Changzhou city was selected as the study area because it is an urbanized city with the characteristics of plain river network and it is faced with poor hydrological connectivity due to artificial constructions (dams and pumps) and human activity (urbanization). River water, well water (shallow groundwater), lake water and rainfall were collected during the flood season and nonflood season, and hydrogen and oxygen isotopes were determined. The temporal and spatial variations in hydrogen and oxygen isotopes in different water bodies and the state of the water cycle in different water bodies were analyzed. IsoSource and MixSIAR models were established to analyze the contribution rate of river network water sources in the study area, and their effectiveness was compared. Results of MixSIAR model were selected to evaluate the hydrological connectivity of the river network in the study area, providing a method to quantify the hydrological connectivity of specific river of the river network in Changzhou. This method could also be applied to other urban plain river network area to study its river connectivity.

Water sources carry chemicals that can have a significant impact on the water environment of a river network, and understanding the contribution of different water sources to the river network can help to manage the pollution of the river network at its source. The hydrological connectivity of a river network affects the self‐purification capacity and flood prevention capacity of the river. Therefore, an isotope tracer approach was applied to determine the contribution rate of different water bodies to a river network and hydrological connectivity was quantified by introducing the retention rate. Changzhou city was selected as the study area because it is an urbanized city with the characteristics of a plain river network and it is faced with poor hydrological connectivity due to artificial constructions (dams and pumps) and human activity (urbanization). River water, well water (shallow groundwater), lake water and rainfall were collected during the flood season and nonflood season, and hydrogen and oxygen isotopes were determined. The temporal and spatial variations in hydrogen and oxygen isotopes in different water bodies and the state of the water cycle in different water bodies were analysed. IsoSource and MixSIAR models were established to analyse the contribution rate of river network water sources in the study area, and their effectiveness was compared. The results of the MixSIAR model were selected to evaluate the hydrological connectivity of the river network in the study area, providing a method to quantify the hydrological connectivity of specific rivers of the river network in Changzhou city. This method could also be applied to other urban plain river network areas to study river connectivity.

No abstract

Economic development and large amounts of industrial production have led to environmental deterioration. The assessment and prediction of water environment capacity (WEC) are crucial supports for water quality target management. Therefore, this study aims to improve WEC via changes in the industrial structure and to analyze the economic changes. For this purpose, the economic efficiency (EE), water use efficiency (WUE), and water treatment efficiency (WTE) are estimated by the EE–SBM (slack-based measure)–DEA (data envelopment analysis) model. Based on the proposed model, the industry is divided into three types: green enterprises, yellow enterprises, and red enterprises. Yellow enterprises and red enterprises are the major supervision subjects, and the spatial distribution of different environmental risks is identified. The WECs of the main canals are analyzed based on dynamic changes in the industrial structure by integrating the 0-D and MIKE11 models. The results showed that after adjusting the industrial structure, the maximum added values of the WEC of chemical oxygen demand (COD), total nitrogen (TN), ammonia nitrogen (NH3–N), and total phosphorus (TP) are 1,744.66 t/a, 536.14 t/a, 24.81 t/a, and 4.16 t/a, respectively. The results show that the canals (R40, R41, R20, R19, and R17) are overloaded with pollutants and indicate that TN is included as a water environment quality assessment target. Furthermore, after the optimization of the industrial structure, the loss of industrial output value is 174.44 million yuan, and the added value of the environmental economy is 232.12 million yuan. The findings provide important technical support for achieving industrial upgrading and sustainable development.