To solve the flood drainage conflict among different regions of the water basin when the flood occurs, it is of great significance to study the allocation of flood drainage rights. The allocation of flood drainage rights requires flood management departments to consider the influences of socioeconomic differences among different regions on flood control operations to realize sustainable development. Under the pattern of the total amount allocation of “watershed–administrative regions”, the evaluation index system of flood drainage rights allocation incorporated four aspects: natural conditions, level of social development, level of economic development, and technology and management. The fuzzy analytic hierarchy process (FAHP) was used to calculate the weight coefficient of each allocation index and the initial distribution’s proportion of the total amount in each region. Land area, population, gross domestic product (GDP), and sewage treatment capacity were selected as the evaluation indexes of the environmental Gini coefficient, and the environmental Gini coefficient method was used to evaluate and adjust the initial allocation of each region. Taking the allocation of flood drainage rights in the Taihu Basin as a case study, the final allocation results were obtained after initial allocation and feedback optimization. By evaluating the environmental Gini coefficient of each evaluation index, it is concluded that the final allocation could meet the requirements of fair allocation in each administrative region and be effectively implemented. Optimal allocation of the flood drainage rights in the Taihu Basin can contribute to overall flood control management, the reduction of flood disasters, and the stable development of society in the basin.

Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) data has the shortcomings of discontinuous and pixel saturation effect. It was also incompatible with the Soumi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) data. In view those shortcomings, this research put forward the WorldPop and the enhanced vegetation index (EVI) adjusted nighttime light (WEANTL) using EVI and WorldPop data to achieve intercalibration and saturation correction of DMSP/OLS data. A long time series of nighttime light images of china from 2001 to 2018 was constructed by fitting the DMSP/OLS data and NPP/VIIRS data. Corrected nighttime light images were examined to discuss the estimation ability of gross domestic product (GDP) and electric power consumption (EPC) on national and provincial scales, respectively. The results indicated that, (1) after correction, the nighttime light (NTL) data can guarantee the growth trend on national and regional scales, and the interannual volatility of the corrected NTL data is lower than that of the uncorrected NTL data; (2) on the national scale, compared with the established model of NTL data and GDP data (NTL-GDP), the determination coefficient (R²) and the mean absolute relative error (MARE) are 0.981 and 8.518%. The R² and MARE of the established model of NTL data and EPC data (NTL-EPC) were 0.990 and 4.655%; (3) on the provincial scale, the R² and MARE of NTL-GDP model under the provincial units are 0.7386 and 38.599%. The R² value and MARE of NTL-EPC model are 0.8927 and 29.319%; (4) on the provincial scale, the R² and MARE of NTL-GDP model on time series are 0.9667 and 10.877%. The R² and MARE of NTL-GDP model on time series are 0.9720 and 6.435%; the established TNL-GDP and TNL-EPC models with 30 provinces data all passed the F-test at the 0.001 level; (5) the prediction accuracy of GDP and EPC on time series was nearly 100%. Therefore, the correction method provided in this research can be applied in estimating the GDP and EPC on multiple scales reliably and accurately.

Environmental problems - specifically relating to water - have become the key factors restricting sustainable development. To evaluate the performance of water environment, this study takes 31 provinces in China as the research area and constructs a water environment performance evaluation index system based on a DPSIR framework (Drivers, Pressures, State, Impact and Response). The undesirable output slack measure model (SBM) is used to calculate the water environment performance of 31 provinces from 2005 to 2017. According to the study, the performance of the water environment in China shows a trend of decline, and the overall performance is low. The water environment performance in different provinces shows obvious differences. The Tobit model is then introduced to analyze the influence of indicators on water environment efficiency. The driving force indicators have significant negative effects on water environment performance. The pressure indicators have significant positive effects on the water environment performance. The state indicators play a significant role in promoting the improvement of water environment performance. With regard to the impact indicators, both industrial added value water consumption and GDP growth rate have significant negative effects on water environment performance. The impact of different response measures on water environment performance is inconsistent.

Purpose: – The purpose of this paper is to analyze the effects of public investment in agricultural R&D and extension on broadacre farming productivity in Australia.Design/methodology/approach: – An autoregressive integrated moving average (ARIMA) regression model is applied to estimate the effects of public investment in agricultural R&D and extension on Australian braodacre productivity.Findings: – The study reveals that public investment in agricultural R&D and extension has contributed almost two-thirds of average annual broadacre productivity growth between 1952-1953 and 2006-2007, the average internal rate of return to public investment in agricultural R&D and extension was 28.4 and 47.5 per cent a year, respectively, and overseas spill-ins is an important source of domestic agricultural productivity growth.Practical implications: – Policy implications: the findings suggest that increasing public investment in agricultural R&D and extension and maintaining agricultural R&D policy stability are equally important to have a sustained long-term agricultural productivity growth, and maintaining an open trade and investment regime is important to benefit from foreign knowledge spillovers which is especially important for developing countries.Originality/value: – This paper contributes to the existing literature by employing more sophisticated econometric techniques with an extended data set for the period from 1952-1953 to 2006-2007. The study separates the contribution of public R&D investment and the extension investment, and also takes into account the contribution of overseas public investment on the TFP growth in the Australian broadacre sector.

To reduce flood disasters and optimize of the comprehensive benefit of the water basin, the allocation of regional flood drainage rights is of great significance. Using the “top-down” allocation mode, we consider the influence of the social, economic, and ecological environments, flood drainage demand and efficiency, and other factors on the allocation of flood drainage rights. A bi-level multi-objective programming model from the perspective of fairness and efficiency is established for the allocation. The Sunan Canal is taken as a typical case study. The model is solved by the multi-objective optimal allocation method and the master–slave hierarchical interactive iteration algorithm. After three iterations of the initial solution, the allocation of flood drainage rights in six flood control regions finally reach an effective state. The results of the model were compared with results based on historical allocation principles, showing that the bi-level multi-objective programming model, based on the principles of fairness and efficiency, is more in line with the current social and economic development of the canal. In view of the institutional background of water resources management in China and the flood drainage pressure faced by various regions, the allocation of flood drainage rights should be comprehensively considered in combination with various factors, and the market mechanism should be utilized to optimize the allocation.