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1.
Gully erosion in the Black Soil Region of China has posed a threat to food security. This study aimed to determine the spatial distribution and morphologic characteristics of gullies in the region and their topographic thresholds. A 28 km2 watershed was surveyed and 117 gullies measured. The results showed that: (1) Gullies were distributed equally on both hillslope and valley floor positions, with a total gully density of .66 km/km2. (2) The mean depth, width, and cross-sectional area of gullies were .74 m, 2.39 m, and 2.43 m2, respectively. These characteristics varied among gullies according to their topographic positions and slope gradients. Individual gully volume (V) was well predicted from gully length (L) by V = 2.08L0.96 (r2 = .66). Total gully volume (V) of each sub-watershed was predicted from mean slope gradient (S) and drainage area (A) as V = 275800S ? 8600A (r2 = .73). (3) Gully erosion was more serious in steeper sub-watersheds and steeper hillslope positions. Gullies were wider in regions with relatively larger drainage areas, except for those developed in the main valley. The topographic threshold for gully initiation was S = .10A?0.34, which indicated gully erosion was dominated by surface runoff. (4) Human activities, such as road construction, played a significant role in gully erosion.  相似文献   

2.
We investigated relationships among modern diatom species composition and physical and chemical characteristics of high-elevation lakes of the Sierra Nevada (California), to develop transfer functions that can be used to infer historic lake conditions. Data were collected from 50 lakes in National Parks and Forests of the central and southern Sierra Nevada. Multivariate statistical methods revealed that acid neutralizing capacity (ANC) and nitrate accounted for significant variation in diatom taxa. A training set with 242 modern diatom taxa from a subset of 41 lakes was used to develop transfer functions for ANC and nitrate using weighted averaging techniques. ANC and nitrate calibration ranges were 23.0–137 μEq/L and 0.18–9.5 μM, respectively. Coefficients of determination for the models were: ANC: R2 = 0.76, and R jackknife 2  = 0.44; NO3: R2 = 0.67, and R jackknife 2  = 0.27. The ANC model was applied to the top 50 cm of sediments in Moat Lake to reconstruct ANC from ca. AD 350 to 2005. The reconstruction suggests that ANC declined by about 40 % (101–60 μEq/L) between the 1920s and the 1960s and then recovered to pre-1920s levels during 1980–2000. The magnitude of this ANC excursion was the largest observed during the past 1,600 years. We hypothesize that temporal variations in ANC were influenced by: (1) changes in rates of acid deposition, especially nitric acid and (2) variations in the timing and magnitude of snowmelt runoff.  相似文献   

3.

Ground vibration induced by rock blasting is one of the most crucial problems in surface mines and tunneling projects. Hence, accurate prediction of ground vibration is an important prerequisite in the minimization of its environmental impacts. This study proposes hybrid intelligent models to predict ground vibration using adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) and genetic algorithms (GAs). To build prediction models using ANFIS, ANFIS–GA, and ANFIS–PSO, a database was established, consisting of 86 data samples gathered from two quarries in Iran. The input parameters of the proposed models were the burden, spacing, stemming, powder factor, maximum charge per delay (MCD), and distance from the blast points, while peak particle velocity (PPV) was considered as the output parameter. Based on the sensitivity analysis results, MCD was found as the most effective parameter of PPV. To check the applicability and efficiency of the proposed models, several traditional performance indices such as determination coefficient (R2) and root-mean-square error (RMSE) were computed. The obtained results showed that the proposed ANFIS–GA and ANFIS–PSO models were capable of statistically predicting ground vibration with excellent levels of accuracy. Compared to the ANFIS, the ANFIS–GA model showed an approximately 61% decrease in RMSE and 10% increase in R2. Also, the ANFIS–PSO model showed an approximately 53% decrease in RMSE and 9% increase in R2 compared to ANFIS. In other words, the ANFIS performance was optimized with the use of GA and PSO.

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4.
We set up an automatic weather station over a playa (the flat floor of an undrained desert basin that becomes at times a shallow lake), approximately 65 km east–west by 130 km north–south, located at the U.S. Army Dugway Proving Ground (40°08′N, 113°27′W, 1124 m above mean sea level) in north-western Utah, U.S.A., in 1999. This station measured the incoming (Rsi) and outgoing (Rso) solar or shortwave radiation using two CM21 Kipp & Zonen pyranometers (one inverted), the incoming (Rli or atmospheric) and outgoing (Rlo or terrestrial) longwave radiation, using two CG1 KippZonen pyrgeometers (one inverted), and the net (Rn) radiation using a Q*7 net radiometer (Radiation Energy Balance System, REBS). We also measured the 10-m wind speed (U10) and direction (R.M. Young wind monitor) and precipitation (Campbell Sci., Inc.). The measurements were taken every 2 s, averaged into 20-min, continuously, throughout the year. The annual (August 1999 – August 2000) comparisons of global or solar radiation and windiness with two other stations in central (Hunter) and northern (Logan) Utah, indicate higher solar radiation (Rsi,Dugway=7797 MJ m−2 period−1vs. Rsi, Hunter=7021 MJ m−2 period−1 and Rsi, Logan=6865 MJ m−2 period−1) and much higher annual mean windiness (UDugway=387 km day−1vs. UHunter=275 km day−1 and ULogan=174 km day−1) throughout the period over the playa. These data reveal the possibility of simultaneously harvesting these two sources of clean energies at this vast and uniform playa.  相似文献   

5.

Innovation efforts in developing soft computing models (SCMs) of researchers and scholars are significant in recent years, especially for problems in the mining industry. So far, many SCMs have been proposed and applied to practical engineering to predict ground vibration intensity (BIGV) induced by mine blasting with high accuracy and reliability. These models significantly contributed to mitigate the adverse effects of blasting operations in mines. Despite the fact that many SCMs have been introduced with promising results, but ambitious goals of researchers are still novel SCMs with the accuracy improved. They aim to prevent the damages caused by blasting operations to the surrounding environment. This study, therefore, proposed a novel SCM based on a robust meta-heuristic algorithm, namely Hunger Games Search (HGS) and artificial neural network (ANN), abbreviated as HGS–ANN model, for predicting BIGV. Three benchmark models based on three other meta-heuristic algorithms (i.e., particle swarm optimization (PSO), firefly algorithm (FFA), and grasshopper optimization algorithm (GOA)) and ANN, named as PSO–ANN, FFA–ANN, and GOA–ANN, were also examined to have a comprehensive evaluation of the HGS–ANN model. A set of data with 252 blasting operations was collected to evaluate the effects of BIGV through the mentioned models. The data were then preprocessed and normalized before splitting into individual parts for training and validating the models. In the training phase, the HGS algorithm with the optimal parameters was fine-tuned to train the ANN model to optimize the ANN model's weights. Based on the statistical criteria, the HGS–ANN model showed its best performance with an MAE of 1.153, RMSE of 1.761, R2 of 0.922, and MAPE of 0.156, followed by the GOA–ANN, FFA–ANN and PSO–ANN models with the lower performances (i.e., MAE?=?1.186, 1.528, 1.505; RMSE?=?1.772, 2.085, 2.153; R2?=?0.921, 0.899, 0.893; MAPE?=?0.231, 0.215, 0.225, respectively). Based on the outstanding performance, the HGS–ANN model should be applied broadly and across a swath of open-pit mines to predict BIGV, aiming to optimize blast patterns and reduce the environmental effects.

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6.
Natural runoff changes in the Yellow River Basin   总被引：3，自引：1，他引：3  
1IntroductionThe driving factors of runoff changes can be divided into precipitation factor and non-precipitation factor, and they can also be divided into natural factor and human activity factor. The influence of the natural factor includes precipitation reduction, precipitation features (for example, spatio-temporal distribution and intensity), landuse natural changes and so forth. All of these can cause runoff changes. Temperature, evaporation, topography, soil and geological environment i…  相似文献   

7.
The localized rain rate maxima (RM) of the inner core region of intense tropical cyclones (TCs) are investigated using Version 6 of the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis data-set from 1998 to 2010. Specifically, this study examines the probabilities of RM exceeding 25 mm h?1 (P25) in intense TCs. The 25 mm h?1 RM is the 90th percentile of all RM observations during the study period. The descending order of P25 observed from intense TCs for the six major ocean basins is: the North Indian Ocean, the Atlantic Ocean, the Northwest Pacific Ocean, the South Pacific Ocean, the South Indian Ocean, and the East-central Pacific Ocean. The six major basins have been subdivided into 29 sub-basins to discern regional variability of RM. P25 increases with increasing TC category in all major basins, except for the South Pacific. Sub-basins with intense TCs that produce extreme rainfall rate maxima include the Bay of Bengal, the South Philippine Sea, the East China Sea, the north coast of Australia, southeast Melanesia, and the Northwest Atlantic. Sub-basins with a higher proportion of category 5 (CAT5) observations than category 3 (CAT3) observations tend to have a greater P25 beyond 60 km from the storm center.  相似文献   

8.
The euryhaline ostracod Cyprideis torosa lives in Akyatan Lagoon, Turkey, which is exposed to large spatial and seasonal variations in water salinity, δ18O, and temperature. Hydrogen and oxygen isotope measurements of waters reveal that the large range of salinity (15–80 g L?1) in the lagoon results from a combination of evaporation and mixing between Mediterranean seawater and Seyhan River input. Round sieve-pore relative abundance in C. torosa provides a robust proxy for water salinity (S) from 15 to 80 g L?1, according to the equation: S = 161.41 (±4.52) * log10(% rounded pores) ? 94.04 (±3.44) (R2 = 0.937; p = 10?31). Seasonal sampling and isotope analysis of C. torosa in waters of known δ18O values (?4.7 to +6.9 ‰ V-PDB) and temperatures (15–35 °C) yielded a weak positive correlation (r = 0.71) between 1000 lnα(calcite–water) ‰ V-SMOW) and 103 * T?1. Specimens of C. torosa collected during the mild and warm seasons have oxygen isotope compositions close to those of inorganic calcite precipitated in equilibrium with ambient water. The large oxygen-isotope variability observed during any season of the year most likely results from shell calcification in water bodies of highly variable salinity, alkalinity, Mg/Ca and water saturation relative to calcite. Indeed, distinct water bodies in the Akyatan Lagoon are generated by mixing of fresh and marine waters, which are exposed to different evaporation rates at the seasonal scale.  相似文献   

9.
Bui  Xuan-Nam  Nguyen  Hoang  Le  Hai-An  Bui  Hoang-Bac  Do  Ngoc-Hoan 《Natural Resources Research》2020,29(2):571-591

Air over-pressure (AOp) is one of the products of blasting operations for rock fragmentation in open-pit mines. It can cause structural vibration, smash glass doors, adversely affect the surrounding environment, and even be fatal to humans. To assess its dangerous effects, seven artificial intelligence (AI) methods for predicting specific blast-induced AOp have been applied and compared in this study. The seven methods include random forest, support vector regression, Gaussian process, Bayesian additive regression trees, boosted regression trees, k-nearest neighbors, and artificial neural network (ANN). An empirical technique was also used to compare with AI models. The degree of complexity and the performance of the models were compared with each other to find the optimal model for predicting blast-induced AOp. The Deo Nai open-pit coal mine (Vietnam) was selected as a case study where 113 blasting events have been recorded. Indicators used for evaluating model performances include the root-mean-square error (RMSE), determination coefficient (R2), and mean absolute error (MAE). The results indicate that AI techniques provide better performance than the empirical method. Although the relevance of the empirical approach was acceptable (R2?=?0.930) in this study, its error (RMSE?=?7.514) is highly significant to guarantee the safety of the surrounding environment. In contrast, the AI models offer much higher accuracies. Of the seven AI models, ANN was the most dominant model based on RMSE, R2, and MAE. This study demonstrated that AI techniques are excellent for predicting blast-induced AOp in open-pit mines. These techniques are useful for blasters and managers in controlling undesirable effects of blasting operations on the surrounding environment.

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10.
This study was conducted to investigate technical and socio-political attributes that lead to the underperformance of two selected irrigation schemes (Shina and Bebeks) in the Lake Tana floodplains, Ethiopia. Irrigation application efficiency (AE) at nine experimental fields showed a wide range, from 20 to 80%, but was mostly between 40 and 60%. Irrigation water-use efficiency (IWUE) varied from 1.9 to 7.2 kg m?3 for onion and 0.9 to 1.2 kg m?3 for maize. The lined and earthen canal conveyance losses in Bebeks were 0.037 and 0.047 l s?1 m?1, whereas in Shina they were 0.033 and 0.044 l s?1 m?1, respectively. The overall consumed ratio (OCR) of water was 0.58 for Bebeks and varied from 0.73 to 1.2 in Shina. Both schemes are performing below the standard based on technical performance indicators. Irrigation water user associations (WUAs) were not implemented, but irrigation committees (ICs), composed of local political leaders, are managing both schemes. Canal and reservoir sedimentation from erosion of upstream catchment areas during the rainy season was the major problem.  相似文献   

11.
Successfully rehabilitating drained wetlands through hydrologic restoration is dependent on defining restoration targets, a process that is informed by pre-drainage conditions, as well as understanding linkages between hydrology and ecosystem structure. Paleoecological records can inform restoration goals by revealing long-term patterns of change, but are dependent on preservation of biomarkers that provide meaningful interpretations of environmental change. In the Florida Everglades, paleohydrological hind-casting could improve restoration forecasting, but frequent drying of marsh soils leads to poor preservation of many biomarkers. To determine the effectiveness of employing siliceous subfossils in paleohydrological reconstructions, we examined diatoms, plant and sponge silico-sclerids from three soil cores in the central Everglades marshes. Subfossil quality varied among cores, but the abundance of recognizable specimens was sufficient to infer 1,000–3,000 years of hydrologic change at decadal to centennial resolution. Phytolith morphotypes were linked to key marsh plant species to indirectly measure fluctuations in water depth. A modern dataset was used to derive diatom-based inferences of water depth and hydroperiod (R2 = 0.63, 0.47; RMSE = 14 cm, 120 days, respectively). Changes in subfossil quality and abundances at centennial time-scales were associated with mid-Holocene climate events including the Little Ice Age and Medieval Warm Period, while decadal-scale fluctuations in assemblage structure during the twentieth century suggested co-regulation of hydrology by cyclical climate drivers (particularly the Atlantic Multidecadal Oscillation) and water management changes. The successful reconstructions based on siliceous subfossils shown here at a coarse temporal scale (i.e., decadal to centennial) advocate for their application in more highly resolved (i.e., subdecadal) records, which should improve the ability of water managers to target the quantity and variability of water flows appropriate for hydrologic restoration.  相似文献   

12.
Artificial neural networks were applied to simulate runoff from the glacierized part of the Waldemar River catchment (Svalbard) based on hydrometeorological data collected in the summer seasons of 2010, 2011 and 2012. Continuous discharge monitoring was performed at about 1 km from the glacier snout, in the place where the river leaves the marginal zone. Averaged daily values of discharge and selected meteorological variables in a number of combinations were used to create several models based on the feed‐forward multilayer perceptron architecture. Due to specific conditions of melt water storing and releasing, two groups of models were established: the first is based on meteorological inputs only, while second includes the preceding day's mean discharge. Analysis of the multilayer perceptron simulation performance was done in comparison to the other black‐box model type, a multivariate regression method based on the following efficiency criteria: coefficient of determination (R2) and its adjusted form (adj. R2), weighted coefficient of determination (wR2), Nash–Sutcliffe coefficient of efficiency, mean absolute error, and error analysis. Moreover, the predictors' importance analysis for both multilayer perceptron and multivariate regression models was done. The performed study showed that the nonlinear estimation realized by the multilayer perceptron gives more accurate results than the multivariate regression approach in both groups of models.  相似文献   

13.
XiaoDuo Pan  Xin Li 《寒旱区科学》2011,3(4):0344-0357
The research of coupling WRF (Weather Research and Forecasting Model) with a land surface model is enhanced to explore the interaction of the atmosphere and land surface; however, regional applicability of WRF model is questioned. In order to do the validation of WRF model on simulating forcing data for the Heihe River Basin, daily meteorological observation data from 15 stations of CMA (China Meteorological Administration) and hourly meteorological observation data from seven sites of WATER (Watershed Airborne Telemetry Experimental Research) are used to compare with WRF simulations, with a time range of a whole year for 2008. Results show that the average MBE (Mean Bias Error) of daily 2-m surface temperature, surface pressure, 2-m relative humidity and 10-m wind speed were ?0.19 °C, ?4.49 hPa, 4.08% and 0.92 m/s, the average RMSE (Root Mean Square Error) of them were 2.11 °C, 5.37 hPa, 9.55% and 1.73 m/s, and the average R (correlation coefficient) of them were 0.99, 0.98, 0.80 and 0.55, respectively. The average MBE of hourly 2-m surface temperature, surface pressure, 2-m relative humidity, 10-m wind speed, downward shortwave radiation and downward longwave were ?0.16 °C, ?6.62 hPa, ?5.14%, 0.26 m/s, 33.0 W/m2 and ?6.44 W/m2, the average RMSE of them were 2.62 °C, 17.10 hPa, 20.71%, 2.46 m/s, 152.9 W/m2 and 53.5 W/m2, and the average R of them were 0.96, 0.97, 0.70, 0.26, 0.91 and 0.60, respectively. Thus, the following conclusions were obtained: (1) regardless of daily or hourly validation, WRF model simulations of 2-m surface temperature, surface pressure and relative humidity are more reliable, especially for 2-m surface air temperature and surface pressure, the values of MBE were small and R were more than 0.96; (2) the WRF simulating downward shortwave radiation was relatively good, the average R between WRF simulation and hourly observation data was above 0.9, and the average R of downward longwave radiation was 0.6; (3) both wind speed and rainfall simulated from WRF model did not agree well with observation data.  相似文献   

14.
气候变化对河北省海河流域径流量的影响   总被引：2，自引：0，他引：2  
邵爱军  左丽琼  王丽君 《地理研究》2010,29(8):1502-1509
利用河北省境内海河流域51个气象站、68个水文站1956~2000年近50年的气象、径流量数据,分析了气象要素和径流量的变化规律。河北省境内海河流域多年平均地表径流量为67.0×108m3,从20世纪 50 年代至 90 年代地表径流量呈逐渐减小的趋势,50年代为105.3×108m3,90年代为54.7×108m3。地表径流量随降水量的减少而减小,随气温的升高而下降,用回归方法建立的径流量与气象要素之间的模型为对数模型。根据未来气候变化情景对河北省海河流域径流量的预测:2030年为70.0~76.8×108m3,2050年为69.8~76.9×108m3。  相似文献   

15.
Simulation and analysis of river runoff in typical cold regions   总被引：1，自引：0，他引：1  
It is generally agreed that global warming is taking place, which has caused runoff generation processes and apparently total runoff amount changes in cold regions of Northwestern China. It is absolutely necessary to quantify and analyze earth surface hydrological processes by numerical models for formulating scientific sustainable development of water resources. Hydrological models became established tools for studying the hydrological cycle, but did not consider frozen soil or glacier hydrology. Thus, they should be improved to satisfy the simulation of hydrological processes in cold regions. In this paper, an energy balance glacier melt model was successfully coupled to the VIC model with frozen soil scheme, thus improving the models performance in a cold catchment area. We performed the improved VIC model to simulate the hydrological processes in the Aksu River Basin, and the simulated results are in good agreement with observed data. Based on modeling hydrological data, the runoff components and their response to climate change were analyzed. The results show: (1) Glacial meltwater recharge accounts for 29.2% of runoff for the Toxkan River, and 58.7% for the Kunma Like River. (2) The annual total runoff of two branches of the Aksu River show increasing trends, increased by about 43.1%, 25.95×106 m3 per year for the Toxkan River and by 13.1%, 14.09×106 m3 per year for the Kunma Like River during the latter 38 years. (3) The annual total runoff of the Toxkan River increased simply due to the increase of non-glacial runoff, while the increase of annual total runoff of the Kunma Like River was the result of increasing glacial (42%) and non-glacial runoff (58%).  相似文献   

16.
Monitoring during three meteorologically different spring seasons in 2012, 2013, and 2014 revealed that temperature increase in spring, which influences spring lake mixing duration, markedly affected nutrient availability and diatom deposition in a sediment trap close to the bottom of deep Tiefer See, NE Germany. Deposition of Stephanodiscus taxa and small Cyclotella taxa was much higher after late ice out and a deep, short lake mixing period in spring 2013, compared to that after gradual warming and lengthy lake mixing periods in spring 2012 and 2014, when only brief or marginal ice cover occurred. Availability of dissolved Si and P was 33 and 20 % higher, respectively, in 2013 compared to 2014. The observed relation between high (low) diatom deposition and short (lengthy) mixing duration in spring was applied to varved sediments deposited between AD 1924 and 2008. Low detrital Si content in trapped material and a sediment core enabled use of µXRF-counts of Si as a proxy for diatom silica. The spring mixing duration for 1951–2008 was derived from FLake-model calculations. The spring warming duration related to lake mixing was approximated from air temperatures for 1924–2008 using the dates when daily mean air temperature exceeded 5 °C (start) and 10 °C (end). Diatom silica deposition showed a significant (p < 0.0001) inverse linear relationship with the modeled spring mixing duration (R2 = 0.36) and the spring warming duration (R2 = 0.28). In both cases, the relationship is strengthened when data from the period of low diatom production (1987–2005) is excluded (R2 = 0.59 and R2 = 0.35). Part of this low diatom production is related to external nutrient supply that favored growth of cyanobacteria at the expense of diatoms. This approach shows that diatom Si deposition was strongly influenced by the availability of light and nutrients, related to the duration of lake mixing and warming in spring, during most of the studied period. The remaining unexplained variability, however, indicates that additional factors influence Si deposition. Further tests in other deep, temperate lakes are necessary to verify if this relation is a common feature and consequently, if diatom Si can be used as a proxy for spring mixing duration in such lakes.  相似文献   

17.
塔里木河流域水资源变化的特点与趋势   总被引：1，自引：1，他引：0  
The Tarim RiverBasin islocated in NorthwestChina,which is known in the world forits rich natural resources and fragile eco-environment.W ater resource rational distribution and highly effective utilization isthe key pointsto solve the severe eco-environm …  相似文献   

18.
We explored the possibility of using artificial neural networks (ANN) to develop quantitative inference models in paleolimnology. ANNs are dynamic computer systems able to learn the relations between input and output data. We developed ANN models to infer pH from fossil diatom assemblages using a calibration data set of 76 lakes in Quebec. We evaluated the predictive power of these models in comparison with the two most commonly methods used in paleolimnology: Weighted Averaging (WA) and Weighted Averaging Partial Least Squares (WA-PLS). Results show that the relationship between species assemblages and environmental variables of interest can be modelled by a 3-layer back-propagation network, with apparent R2 and RMSE of 0.9 and 0.24 pH units, respectively. Leave-one-out cross-validation was used to access the reliabilities of the WA, WA-PLS and ANN models. Validation results show that the ANN model (R2 jackknife = 0.63, RMSEjackknife = 0.45, mean bias = 0.14, maximum bias = 1.13) gives a better predictive power than the WA model (R2 jackknife = 0.56, RMSEjackknife = 0.5, mean bias = –0.09, maximum bias = –1.07) or WA-PLS model (R2 jackknife = 0.58, RMSEjackknife = 0.48, mean bias = –0.15, maximum bias = –1.08). We also evaluated whether the removal of certain taxa according to their tolerance changed the performance of the models. Overall, we found that the removal of taxa with high tolerances for pH improved the predictive power of WA-PLS models whereas the removal of low tolerance taxa lowered its performance. However, ANN models were generally much less affected by the removal of taxa of either low or high pH tolerance. Moreover, the best model was obtained by averaging the predictions of WA-PLS and ANN models. This implies that the two modelling approaches capture and extract complementary information from diatom assemblages. We suggest that future modelling efforts might achieve better results using analogous multi-model strategies.  相似文献   

19.
Abstract

Characterizing gully cross sections (GCs) is essential for calculating the volume and erosion rate of the gully. However, little research has focused on modeling the morphology of GCs. This study investigated 456 GCs with a laser distance meter located at the mouth, middle, and head of 152 gullies in the Yuanmou Dry-hot Valley of China; mapped them with AutoCAD software; fitted them with 2nd–6th degree polynomial functions, and discussed the correlation between the coefficients and the morphology of GCs. The results showed that: (1) using a 2nd-degree polynomial function (y = ax2 + bx + c) to describe the morphology of GCs produced a better result than other polynomial functions; (2) the coefficient a of 2nd-degree polynomial function was correlated with depth (r = ?0.226, p < 0.01), gradient (r = 0.545, p < 0.01), and activities; and (3) the symmetry axis (?b/2a) of 2nd-degree polynomial function increased with gully change from left-deflection to right-skewed, and the absolute value showed the asymmetrical degree (r = 0.216, p < 0.01). This study will not only help to understand the morphology and evolution of gullies, but will also provide a scientific basis for prevention of gully erosion.  相似文献   

20.
Reproducibility is a cornerstone of science and thus for geographic research as well. However, studies in other disciplines such as biology have shown that published work is rarely reproducible. To assess the state of reproducibility, specifically computational reproducibility (i.e. rerunning the analysis of a paper using the original code), in geographic research, we asked geoscientists about this topic using three methods: a survey (n = 146), interviews (n = 9), and a focus group (n = 5). We asked participants about their understanding of open reproducible research (ORR), how much it is practiced, and what obstacles hinder ORR. We found that participants had different understandings of ORR and that there are several obstacles for authors and readers (e.g. effort, lack of openness). Then, in order to complement the subjective feedback from the participants, we tried to reproduce the results of papers that use spatial statistics to address problems in the geosciences. We selected 41 open access papers from Copernicus and Journal of Statistical Software and executed the R code. In doing so, we identified several technical issues and specific issues with the reproduced figures depicting the results. Based on these findings, we propose guidelines for authors to overcome the issues around reproducibility in the computational geosciences.  相似文献   

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