Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China

Despite the significant role of precipitation in the hydrological cycle, few studies have been conducted to evaluate the impacts of the temporal resolution of rainfall inputs on the performance of SWAT (soil and water assessment tool) models in large-sized river basins. In this study, both daily and hourly rainfall observations at 28 rainfall stations were used as inputs to SWAT for daily streamflow simulation in the Upper Huai River Basin. Study results have demonstrated that the SWAT model with hourly rainfall inputs performed better than the model with daily rainfall inputs in daily streamflow simulation, primarily due to its better capability of simulating peak flows during the flood season. The sub-daily SWAT model estimated that 58% of streamflow was contributed by baseflow compared to 34 % estimated by the daily model. Using the future daily and three-hour precipitation projections under the RCP (Representative Concentration Pathways) 4.5 scenario as inputs, the sub-daily SWAT model predicted a larger amount of monthly maximum daily flow during the wet years than the daily model. The differences between the daily and sub-daily SWAT model simulation results indicated that temporal rainfall resolution could have much impact on the simulation of hydrological process, streamflow, and consequently pollutant transport by SWAT models. There is an imperative need for more studies to examine the effects of temporal rainfall resolution on the simulation of hydrological and water pollutant transport processes by SWAT in river basins of different environmental conditions

Identifying high-impact sub-structures for convolution kernels in document-level sentiment classification

Convolution kernels support the modeling of complex syntactic information in machine-learning tasks. However, such models are highly sensitive to the type and size of syntactic structure used. It is therefore an important challenge to automatically identify high impact sub-structures relevant to a given task. In this paper we present a systematic study investigating (combinations of) sequence and convolution kernels using different types of substructures in document-level sentiment classification. We show that minimal sub-structures extracted from constituency and dependency trees guided by a polarity lexicon show 1.45 point absolute improvement in accuracy over a bag-of-words classifier on a widely used sentiment corpus

Otolith morphology and total length relationships in <em>Schizothorax grahami</em>

Otolith is important for studying fish populations and life histories. In this study, the dominant species of Schizothorax grahami in the source section of the Chishui River was taken to understand the relationships between otolith morphology and total length (TL). Results showed a large difference between the four TL groups (A/B/C/D), except group B is similar to group C. The combined discrimination success rate of linear discriminant analysis was 62.2%. Group A and D's success rate is the highest, at around 75%. Meanwhile, the success rate for Group B and Group C is below 65%. The one-way ANOVA of the Shape Index and the Canonical analysis of Principal Coordinates with two coefficients (Fourier coefficients and Wavelet coefficients) showed that Group B is similar to Group C, with a large difference from the other two groups. When TL was greater than 100 mm (the pearl organs appearing), the otolith growth was lower changing. Otolith morphology still changes with growth after sexual maturity in fish, so the larger fish is more useful for conducting otolith morphology studies for accurate evaluation and management of local fishery resources

Application of EMD-Based SVD and SVM to Coal-Gangue Interface Detection

Coal-gangue interface detection during top-coal caving mining is a challenging problem. This paper proposes a new vibration signal analysis approach to detecting the coal-gangue interface based on singular value decomposition (SVD) techniques and support vector machines (SVMs). Due to the nonstationary characteristics in vibration signals of the tail boom support of the longwall mining machine in this complicated environment, the empirical mode decomposition (EMD) is used to decompose the raw vibration signals into a number of intrinsic mode functions (IMFs) by which the initial feature vector matrices can be formed automatically. By applying the SVD algorithm to the initial feature vector matrices, the singular values of matrices can be obtained and used as the input feature vectors of SVMs classifier. The analysis results of vibration signals from the tail boom support of a longwall mining machine show that the method based on EMD, SVD, and SVM is effective for coal-gangue interface detection even when the number of samples is small

Assessment of the spatial and temporal variations of water quality for agricultural lands with crop rotation in China by using a HYPE model

Many water quality models have been successfully used worldwide to predict nutrient losses from anthropogenically impacted catchments, but hydrological and nutrient simulations with little data are difficult considering the transfer of model parameters and complication of model calibration and validation. This study aims (i) to assess the performance capabilities of a new and relatively more advantageous model-hydrological predictions for the environment (HYPE) to simulate stream flow and nutrient load in ungauged agricultural areas by using a multi-site and multi-objective parameter calibration method and (ii) to investigate the temporal and spatial variations of total nitrogen (TN) and total phosphorous (TP) concentrations and loads with crop rotation using the model for the first time. A parameter estimation tool (PEST) was used to calibrate parameters, which shows that the parameters related to the effective soil porosity were most sensitive to hydrological modeling. N balance was largely controlled by soil denitrification processes, whereas P balance was influenced by the sedimentation rate and production/decay of P in rivers and lakes. The model reproduced the temporal and spatial variations of discharge and TN/TP relatively well in both calibration (2006–2008) and validation (2009–2010) periods. The lowest NSEs (Nash-Suttclife Efficiency) of discharge, daily TN load, and daily TP load were 0.74, 0.51, and 0.54, respectively. The seasonal variations of daily TN concentrations in the entire simulation period were insufficient, indicated that crop rotation changed the timing and amount of N output. Monthly TN and TP simulation yields revealed that nutrient outputs were abundant in summer in terms of the corresponding discharge. The area-weighted TN and TP load annual yields in five years showed that nutrient loads were extremely high along Hong and Ru rivers, especially in agricultural lands