The efficient use of agricultural water is the key for Yangtze River Economic Zone (YREZ) to realize ecological green development. Taking the panel data on 11 YREZ regions in 2011-2018 as the object, this paper establishes an evaluation indicator system for green agricultural water use efficiency (GAWUE) containing undesired output, and adopts the epsilon-based measure (EBM) model to evaluate YREZ’s GAWUE. After analyzing the regional differences in YREZ’s GAWUE, the Tobit model was introduced to verify the drivers of GAWUE. The results show that: In the study period, YREZ’s GAWUE exhibits some regional differences. The mean GAWUEs of Shanghai, Jiangsu, Zhejiang, and Sichuan were optimized; those of Guizhou, Yunnan, Chongqing, and Hubei were relatively desirable, leaving a small room for improvement, the mean GAWUEs of Hunan, Jiangxi, and Anhui were undesirable, waiting for major improvement in future. Overall, the lower reaches had the highest GAWUE, followed by the upper reaches, while the middle reaches had the minimum GAWUE. The Tobit model shows that agricultural technological growth (ATG) and agricultural water intensity (AWI) greatly promote GAWUE, while farmer income level (FIL), water resources endowment (WRE), agricultural planting structure (APS), and farmland irrigation area (FIA) significantly suppress GAWUE.
This work attempts to recover digital signals from a few stochastic samples in time domain. The target signal is the linear combination of one-dimensional complex sine components with R different but continuous frequencies. These frequencies control the continuous values in the domain of normalized frequency [0, 1), contrary to the previous research into compressed sensing. To recover the target signal, the problem was transformed into the completion of a low-rank structured matrix, drawing on the linear property of the Hankel matrix. Based on the completion of the structured matrix, the authors put forward a feasible-point algorithm, analyzed its convergence, and speeded up the convergence with the fast iterative shrinkage-thresholding (FIST) algorithm. The initial algorithm and the speed up strategy were proved effective through repeated numerical simulations. The research results shed new lights on the signal recovery in various fields.
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