The efficient control of water usage is one of the core goals of the strictest water resources management system in China. Therefore, the objective and reasonable evaluation of the effects of implementing this system is crucial. Based on the natural and social water cycle theories and the mechanism of the influence of agricultural, industrial, domestic and ecological water utilization, this paper proposes an evaluation index system through the qualitative and quantitative analysis of external and internal factors affecting the efficiency of water usage. Then, a matter-element model is developed on the basis of game theory weight to evaluate the effects of the implementation of efficiency control measures for regional water usage. By calculating the comprehensive correlation, this model can directly indicate the level of regional water use efficiency control. The model is applied to water usage in Jiangxi Province for the period 2011–2014. The results indicate a gradual improvement in the efficiency of water usage in this province. The matter-element extension evaluation model is simple and practical, and the evaluation results are in agreement with the facts. In summary, this method can provide a new theoretical basis for controlling the efficiency of regional water usage.

Maritime search and rescue is a crucial component of the national emergency response system, which mainly relies on unmanned aerial vehicles (UAVs) to detect objects. Most traditional object detection methods focus on boosting the detection accuracy while neglecting the detection speed of the heavy model. However, improving the detection speed is essential, which can provide timely maritime search and rescue. To address the issues, we propose a lightweight object detector named Shuffle-GhostNet-based detector (SG-Det). First, we construct a lightweight backbone named Shuffle-GhostNet, which enhances the information flow between channel groups by redesigning the correlation group convolution and introducing the channel shuffle operation. Second, we propose an improved feature pyramid model, namely BiFPN-tiny, which has a lighter structure capable of reinforcing small object features. Furthermore, we incorporate the Atrous Spatial Pyramid Pooling module (ASPP) into the network, which employs atrous convolution with different sampling rates to obtain multi-scale information. Finally, we generate three sets of bounding boxes at different scales—large, medium, and small—to detect objects of different sizes. Compared with other lightweight detectors, SG-Det achieves better tradeoffs across performance metrics and enables real-time detection with an accuracy rate of over 90% for maritime objects, showing that it can better meet the actual requirements of maritime search and rescue.

Multi‐source remote sensing precipitation products are being used more and more frequently for rainfall analysis and hydrological applications around the world. The aim of the present study was to assess the variances and uncertainty of long‐term precipitation and corresponding hydrological simulations from 1984 to 2016 using rain gauge measurements, two satellite rainfall products retrieved from the Climate Prediction Center (CPC) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Climate Data Record (PERSIANN‐CDR) respectively, along with rainfall reanalysis data from the ERA‐Interim over the lower Yangtze River basin, China. The results indicated overestimation from ERA‐Interim and PERSIANN‐CDR on seasonal rainfall. CPC rainfall estimation had marginal bias with rain gauge measurements among all the remote sensing rainfall products on a daily scale, while the ERA‐Interim tended to overestimate when the rainfall rate was less than 50 mm. On a monthly scale, CPC rainfall estimations were very close to the rain gauge measurements, with a correlation coefficient of 0.96, whilst the ERA‐Interim rainfall products showed significant overestimation in February, March and September. Nevertheless, all remote sensing rainfall products achieved good performance in June and July, showing promising potential to be an alternative to rainfall data for long‐term water resource analysis. Furthermore, ERA‐Interim rainfall products did not perform as well as the other rainfall sources in flow simulations, as evidenced by the large root‐mean‐square error and bias. CPC rainfall products outperformed all other rainfall sources in terms of the Nash–Sutcliffe coefficient at all temporal scales. In addition, the skill scores suggested that the performance of the streamflow simulation improved significantly on a monthly scale, with a higher Nash–Sutcliffe coefficient and smaller total streamflow errors.

Over the past two decades, various satellite‐based precipitation products have been released to provide uninterrupted time‐series precipitation with quasi‐global coverage. The latest Chinese merged satellite–gauge (CMS) rainfall product developed by the China Meteorological Administration (CMA) may reduce the errors in near real time by combining the Climate Prediction Centre's (CPC) morphing algorithm (CMORPH) rainfall estimates with over 30,000 weather station measurements, which therefore offer a potential alternative or supplement to ground‐based rainfall estimates for hydrometeorological applications in sparsely gauged or ungauged basins. In the present study, the characteristics of the CMS precipitation product were comprehensively evaluated for the period 2008–2012 over Danjiangkou basin, central China, and used to drive the Liuxihe (LXH)‐distributed hydrological model for detailed streamflow simulations. The results show that most of the small–median rainfall with an intensity < 25 mm·day^–1 can be well captured by the CMS, and the simulated streamflow had relatively better agreement with observations for peak flow in the lower part of the basin. However, the total water amount was 15.7% less than the streamflow driven by rain gauges, on average. In addition, the depths of surface flow and groundwater forced by the CMS rainfall were 22.05% and 21.10% less than rain gauge, respectively. Overall, the study provides new insight into and experience of the hydrological applicability of the high spatiotemporal‐resolution satellite–gauge rainfall product for driving a distributed hydrological model at a daily resolution. This product has the potential to be an alternative data source for data‐sparse or ungauged basins for water resource management and hydrological simulation/prediction purposes.