Modeling nitrogen loading in a small watershed in southwest China using a DNDC model with hydrological enhancements

The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed\u27s 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced

Modeling nitrogen loadings from agricultural soils in southwest China with modified DNDC

Degradation of water quality has been widely observed in China, and loadings of nitrogen (N) and other nutrients from agricultural systems play a key role in the water contamination. Process‐based biogeochemical models have been applied to quantify nutrient loading from nonpoint sources at the watershed scale. However, this effort is often hindered by the fact that few existing biogeochemical models of nutrient cycling are able to simulate the two‐dimensional soil hydrology. To overcome this challenge, we launched a new attempt to incorporate two fundamental hydrologic features, the Soil Conservation Service curve and the Modified Universal Soil Loss Equation functions, into a biogeochemistry model, Denitrification‐Decomposition (DNDC). These two features have been widely utilized to quantify surface runoff and soil erosion in a suite of hydrologic models. We incorporated these features in the DNDC model to allow the biogeochemical and hydrologic processes to exchange data at a daily time step. By including the new features, DNDC gained the additional ability to simulate both horizontal and vertical movements of water and nutrients. The revised DNDC was tested against data sets observed in a small watershed dominated by farmlands in a mountainous area of southwest China. The modeled surface runoff flow, subsurface drainage flow, sediment yield, and N loading were in agreement with observations. To further observe the behaviors of the new model, we conducted a sensitivity test with varied climate, soil, and management conditions. The results indicated that precipitation was the most sensitive factor determining the rate of N loading from the tested site. A Monte Carlo test was conducted to quantify the potential uncertainty derived by variations in four selected input parameters. This study demonstrates that it is feasible and effective to use enhanced biogeochemical models such as DNDC for quantifying N loadings by incorporating basic hydrological features into the model framework

Single point positioning using GPS, GLONASS and BeiDou satellites

This paper introduces the Chinese BeiDou satellite system and its comparison with the actual completed American GPS and the Russian GLONASS systems. The actual BeiDou system consists of 14 satellites covering totally the Asia -Pacific area. A Single Point Positioning (SPP) test has been realised in Changsha, Hunan province, China, to show the advantage of using combined pseud o- range solutions from these 3 satellite navigation systems especially in obstructed sites. The test shows that, with an elevation mask angle of 10 ° , the accuracy is improved by about 20% in hor i- zontal coordinates and nearly 50% in the vertical component using the simultaneous observa tions of the 3 systems compared to the GPS/GLONASS solution. For the processing with an elev ation mask angle of 30 ° , most of the time less than 4 GPS satellites were available for the GPS- only case and no solution was possible. However, in this difficult situation, the combined GPS/GLON ASS/ BeiDou solutions provided an accuracy (rms values) of about 5 m

ANAct: Adaptive Normalization for Activation Functions

In this paper, we investigate the negative effect of activation functions on forward and backward propagation and how to counteract this effect. First, We examine how activation functions affect the forward and backward propagation of neural networks and derive a general form for gradient variance that extends the previous work in this area. We try to use mini-batch statistics to dynamically update the normalization factor to ensure the normalization property throughout the training process, rather than only accounting for the state of the neural network after weight initialization. Second, we propose ANAct, a method that normalizes activation functions to maintain consistent gradient variance across layers and demonstrate its effectiveness through experiments. We observe that the convergence rate is roughly related to the normalization property. We compare ANAct with several common activation functions on CNNs and residual networks and show that ANAct consistently improves their performance. For instance, normalized Swish achieves 1.4\% higher top-1 accuracy than vanilla Swish on ResNet50 with the Tiny ImageNet dataset and more than 1.2\% higher with CIFAR-100.Comment: 14 pages, 6 figure

Kinematic Absolute Positioning with Quad-Constellation GNSS

The absolute positioning technique is based on a point positioning mode with a single Global Navigation Satellite System (GNSS) receiver, which has been widely used in many fields such as vehicle navigation and kinematic surveying. For a long period, this positioning technique mainly relies on a single GPS system. With the revitalization of Global Navigation Satellite System (GLONASS) constellation and two newly emerging constellations of BeiDou Navigation Satellite System (BDS) and Galileo, it is now feasible to carry out the absolute positioning with quad-constellation of GPS, GLONASS, BDS, and Galileo. A combination of multi-constellation observations can offer improved reliability, availability, and accuracy for position solutions. In this chapter, combined GPS/GLONASS/BDS/Galileo point positioning models for both traditional single point positioning (SPP) and precise point positioning (PPP) are presented, including their functional and stochastic components. The traditional SPP technique has a positioning accuracy at a meter level, whereas the PPP technique can reach an accuracy of a centimeter level. However, the later relies on the availability of precise ephemeris and needs a long convergence time. Experiments were carried out to assess the kinematic positioning performance in the two different modes. The positioning results are compared among different constellation combinations to demonstrate the advantages of quad-constellation GNSS

Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision

Action recognition in videos has attracted a lot of attention in the past decade. In order to learn robust models, previous methods usually assume videos are trimmed as short sequences and require ground-truth annotations of each video frame/sequence, which is quite costly and time-consuming. In this paper, given only video-level annotations, we propose a novel weakly supervised framework to simultaneously locate action frames as well as recognize actions in untrimmed videos. Our proposed framework consists of two major components. First, for action frame localization, we take advantage of the self-attention mechanism to weight each frame, such that the influence of background frames can be effectively eliminated. Second, considering that there are trimmed videos publicly available and also they contain useful information to leverage, we present an additional module to transfer the knowledge from trimmed videos for improving the classification performance in untrimmed ones. Extensive experiments are conducted on two benchmark datasets (i.e., THUMOS14 and ActivityNet1.3), and experimental results clearly corroborate the efficacy of our method

Vibration control for active magnetic bearing high-speed flywheel rotor system with modal separation and velocity estimation strategy

The active magnetic bearing (AMB) high-speed flywheel rotor system is a multivariable, nonlinear, and strongly coupled system with significant gyroscopic effect, which puts a strain on its stability and control performances. It is very difficult for traditional decentralized controllers, such as proportional-derivative controller (PD controller), to deal with such complex system. In order to improve the stability, control performances and robustness against noise of the AMB high-speed flywheel rotor system, a new control strategy was proposed based on the mathematical model of the AMB high-speed flywheel rotor system in this paper. The proposed control strategy includes two key subsystems: the modal separation subsystem, which allows direct control over the rotor rigid modes, and the velocity estimation controller, which improves the robustness against noise. Integration of modeling results into the final controller was also described. Its ability and effectiveness to control the AMB high-speed flywheel rotor system was investigated by simulations and experiments. The results show that proposed control strategy can separately regulate the stiffness and the damping of conical mode and parallel mode of the AMB high-speed flywheel rotor system, and obviously improve the stability, dynamic behaviors and robustness against noise of the AMB high-speed flywheel rotor system in the high rotating speed region

Vibration control for active magnetic bearing high-speed flywheel rotor system with modal separation and velocity estimation strategy

The active magnetic bearing (AMB) high-speed flywheel rotor system is a multivariable, nonlinear, and strongly coupled system with significant gyroscopic effect, which puts a strain on its stability and control performances. It is very difficult for traditional decentralized controllers, such as proportional-derivative controller (PD controller), to deal with such complex system. In order to improve the stability, control performances and robustness against noise of the AMB high-speed flywheel rotor system, a new control strategy was proposed based on the mathematical model of the AMB high-speed flywheel rotor system in this paper. The proposed control strategy includes two key subsystems: the modal separation subsystem, which allows direct control over the rotor rigid modes, and the velocity estimation controller, which improves the robustness against noise. Integration of modeling results into the final controller was also described. Its ability and effectiveness to control the AMB high-speed flywheel rotor system was investigated by simulations and experiments. The results show that proposed control strategy can separately regulate the stiffness and the damping of conical mode and parallel mode of the AMB high-speed flywheel rotor system, and obviously improve the stability, dynamic behaviors and robustness against noise of the AMB high-speed flywheel rotor system in the high rotating speed region