Urban agglomeration polders type of flood control pattern (UAPFCP) is an extensively used pattern for urban flood control in plain water system areas. Urbanization and polders are two main factors that affect the runoff process in these regions. The Qinhuai River basin, one of the representative watersheds of this flood control pattern in East China, was selected to perform the study. Five urbanization scenarios (the historical, current, and three assumed future urbanization scenarios) of the basin were defined in this paper. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) was used to simulate basin runoff. The results indicate that the UAPFCP increased the flood volume (Q_v) and peak flow (Q_p) compared to the results under the condition without polders. With the constant improvement of the urbanization level of the basin, Q_v and Q_p under the with polder condition increased correspondingly, and the potential changes show a linear relationship. The urbanization and urban agglomeration polders have interactions with flood events. The effect of urbanization on the flood process is weakened because of the existence of urban agglomeration polders. With the constant improvement of the urbanization level, the effect on the flood process caused by urban agglomeration polders becomes gradually weaker.

The Hydrologic Modeling System (HEC-HMS) and statistical analysis method were used to analyze the relationship between flood eigenvalues (i.e., flood volume and peak flow) and landscape pattern metrics. Then, the flood-landscape ecological risk index (ERI_FL) was proposed and constructed to quantitatively assess the flood-landscape ecological risk (FLER). The semivariogram method was used to spatialize the ERI_FL values. Lastly, this study analyzed the spatial–temporal change of FLER at watershed scale and at sub-basin scale, respectively. Two historical landscape distributions (i.e., 2003 and 2017) of Qinhuai River basin were used to perform this study. The results showed that there were certain relationships between landscape pattern and flood eigenvalues, and for different landscapes, the response metrics and degrees were different. FLER increased as urbanization increased. FLER change magnitude had a positive relationship with urban land percentage change magnitude. The distribution of FLER and the distribution of FLER change both showed spatial differences at watershed scale. The structural features of landscape pattern had significant effects on regional floods. In the urbanization process, avoiding forming large-scale landscape patches, improving landscape abundance, and increasing contact area between different types of landscape patches were helpful to reduce the negative effects caused by the increase of urban landscape area on flood.

Various regression models are currently applied to derive functional forms of operating rules for hydropower reservoirs. It is necessary to analyze and evaluate the model selecting uncertainty involved in reservoir operating rules for efficient hydropower generation. Moreover, selecting the optimal input variables from a large number of candidates to characterize an output variable can lead to a more accurate operation simulation. Therefore, this paper combined the Grey Relational Analysis (GRA) method and the Bayesian Model Averaging (BMA) method to select input variables and derive the monthly optimal operating rules for a hydropower reservoir. The monthly input variables were first filtered according to the relationship between the preselected output and input variables based on the reservoir optimal deterministic trajectory using GRA. Three models, Particle Swarm Optimization-Least Squares Support Vector Machine (PSO-LSSVM), Adaptive Neural Fuzzy Inference System (ANFIS), and Multiple Linear Regression Analysis (MLRA) model, were further implemented to derive individual monthly operating rules. BMA was applied to determine the final monthly operating rules by analyzing the uncertainty of selecting individual models with different weights. A case study of Xinanjiang Reservoir in China shows that the combination of the two methods can achieve high-efficiency hydropower generation and optimal utilization of water resources.

In the published article [¹], the authors realized some errors in the Funding Section, and thus wish to replace the Funding Section with the paragraph below: Funding: This research was funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) and the Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYZZ16_0287).