广东雷州半岛土壤氮、磷、钾元素地球化学特征及其土壤肥力评价          下载免费PDF全文

汪实  朱鑫  黎旭荣  罗思亮 《中国地质》2021,48(4):1177-1187

广东雷州半岛位于中国大陆最南端,是中国菠萝、香蕉、甘蔗等农产品重要产地。土壤氮、磷、钾等养分是作物生长需要最多的营养元素,对农业发展至关重要。文章通过对雷州半岛土壤取样,首次对该地区土壤氮磷钾的背景特征进行了分析,研究了不同成土母质、不同土地利用类型氮磷钾的含量水平,探讨了氮磷钾人为影响因素和时空演化规律,并进行了土壤肥力评价。研究发现,雷州半岛土壤中氮、磷、钾分布受地质背景制约,并受人为活动干扰强烈,氮、磷受人类活动影响显著,钾受人为扰动程度较轻。与20世纪90年代相比,表层土壤磷元素含量增幅较大,钾元素含量与前期相当。土壤肥力评价结果表明,雷州半岛土壤富磷,缺钾,局部缺氮。  相似文献   

1961—2017年新疆积雪期时空变化特征及其与气象因子的关系   总被引：2，自引：2，他引：0  

王慧  王梅霞  王胜利  余行杰 《冰川冻土》2021,43(1):61-69

利用新疆89个地面站逐日积雪深度观测资料,研究探讨了1961—2017年新疆区域积雪期、积雪初日、积雪终日的时空变化规律,分析了北疆和天山山区积雪期的年代际和周期变化特征及其与气温、降水的关系。结果表明：新疆各地积雪期、积雪初日和终日存在明显的差异,积雪期以天山为界北多南少;从空间分布看,天山山区和新疆北部阿勒泰、塔城和伊犁河谷的大部地区是新疆积雪最丰富的地区,也是积雪期相对较长的区域。近57年来,北疆和天山山区78%气象站积雪期呈减少趋势,其中塔城地区和阿勒泰东部以及中天山一带的部分地区减少显著;67%气象站积雪初日推迟,显著推迟区域与积雪期显著减少的区域基本一致;积雪终日变化趋势不明显。北疆和天山山区积雪期存在2~3 a的短周期、14~15 a的长周期;积雪初日分别以12 a、15 a长周期振荡为主,但3~5 a短周期振荡出现的时段有所差异,两个区域积雪终日周期信号均较弱。北疆和天山山区积雪期、积雪初日和终日受气温的影响大于降水,其中积雪初日、终日出现的早晚与其所处季节的平均气温显著相关。  相似文献   

1996—2015年黄河源区植被覆盖度提取和时空变化分析   总被引：2，自引：2，他引：0  

王俊奇  王广军  梁四海  杜海波  彭红明 《冰川冻土》2021,43(2):662-674

研究黄河源区植被覆盖度时空变化对于深入理解青藏高原多年冻土区在气候变化和人类活动双重作用下的植被响应,以及为黄河源区生态环境保护和治理提供决策具有重要的意义。以陆地卫星（Landsat）影像为主要数据源,利用多端元混合像元分解模型（Multiple Endmember Spectral Mixture Analysis,MESMA）,完成了1996—2015年黄河源区4.4万km²、7个时相的植被覆盖度提取,并基于转移矩阵和一元线性回归趋势法分析了植被覆盖度变化情况。结果表明：黄河源区东南部植被覆盖度较高,西北部植被覆盖度较低,且植被覆盖度在空间上由东南向西北呈递减趋势。1996—2004年植被覆盖度整体呈下降趋势,2004—2015年植被覆盖度呈增加趋势。1996—2015年植被覆盖度呈增加趋势的区域占57.25%,基本不变的区域占16.02%,植被覆盖度呈下降趋势的区域占26.73%。植被覆盖度下降的主要原因是黄河源头及一些河谷地带、环湖地区受人类影响较大,且东南部海拔较低地区受到过度放牧的影响。尽管黄河源区1996—2015年植被覆盖度总体呈改善趋势,但毒杂草的面积也由1996年的16 060 km²增加到2015年的22 942 km²,20年间增加了6 882 km²,毒杂草面积的增加对黄河源区局部地区畜牧业的发展有不利影响。  相似文献   

1960—2017年河西地区降水时空变化特征     

王秀娜  丁永建  王建  赵传成 《冰川冻土》2021,43(4):1179-1189

利用1960—2017年日降水量资料,采用线性倾向趋势分析、滑动分析和泰森多边形法等,对河西地区多年降水时空变化特征及不同量级降水日数及降水强度的变化趋势进行了研究。结果表明：河西地区年均降水量为99.0 mm,呈现明显的逐年上升趋势,平均倾向率为8.72 mm?（10a）^-1,月降水量为单峰分布,5—10月夏秋汛期降水量占年降水量的89.2%,各季节降水量均呈现显著上升趋势;年均降水日数为36.7天,呈现明显的上升趋势,增幅为3.18 d?（10a）^-1,降水日数主要分布在夏季,约占总降水日数的54.6%;平均降水强度为2.70 mm?d^-1,呈现减弱趋势,变化速率为-0.04 mm?d^-1?（10a）^-1;零星小雨和小雨降水日数均呈现增加趋势,而二者平均降水强度均为下降趋势,小到中雨降水日数和降水强度呈现增加趋势,中雨及以上的降水变化趋势不明显。  相似文献   

基于离散元模拟的二元颗粒柱坍塌特性研究     

崔溦  魏杰  张贵科  李宏璧 《岩土力学》2021,(1):280-290

常见的地质灾害如滑坡、泥石流、岩崩等通常都涉及不同形状的颗粒物质运动,这些形状不同的颗粒又多具有不同的尺寸和含量。基于典型的颗粒柱坍塌试验,首先根据试验方法确定了离散元模拟所需的各项参数,然后采用随机多面体方法生成了可控制长细比的大颗粒,利用离散元法就不同大颗粒含量下形态变化对二元颗粒柱坍塌特性的影响开展研究,研究结果表明:(1)利用离散元法可以较好地重现室内试验中小球和多面体组成的二元颗粒系统的颗粒柱坍塌过程;(2)在不同长细比的不规则大颗粒和小球组成的二元颗粒柱系统中,当大颗粒含量高于临界含量值20%时,二元颗粒柱坍塌持续的时间随非球形大颗粒长细比的增加而增加;(3)在不同长细比的不规则大颗粒和小球组成的二元颗粒柱中,当大颗粒含量高于临界含量值20%时,在相同百分比的大颗粒含量下,大颗粒长细比的增加会提高大颗粒平均配位数以及降低颗粒的运动能力,大颗粒间形成更强的互锁作用,降低了颗粒柱的整体流动性,使其最终堆积高度更高、最大跑出距离更短以及更小的归一化动能峰值。(4)在不同长细比的不规则大颗粒和小球组成的二元颗粒柱中,小颗粒可以较为明显降低大颗粒间摩擦及互锁作用,增加流动性,降低大骨料形态对坍塌过程的影响。  相似文献   

确定砂土动剪切模量和阻尼比的方法对比     

宋东松  冯震  金红山  孙逸涵 《吉林大学学报(地球科学版)》2021,51(5):1366-1380

确定土体动剪切模量的常用方法有规范法、Kumar法和自相关函数法,确定相应阻尼比的方法有规范法、Das and Luo法、Kokusho法、Kumar法和互相关函数法,为了分析不同方法所产生差异,实现定量化对比分析,笔者以福建标准砂（粒径为0.5~1.0 mm）为研究对象,采用不排水的应力控制动三轴试验,探讨不同的确定土体动剪切模量和阻尼比方法的差异性,并给出了不同土体条件建议选用的方法。结果表明：1）3种方法确定动剪切模量的结果有一定的差异,随剪应变的增大结果的差异逐渐增大,有效围压对结果的差异性有所影响,当剪应变为4×10^-3,有效围压为100 kPa时,3种方法差异显著,相对误差最大接近20%;2）而5种方法确定阻尼比的结果差异显著,随着剪应变的增大,5种方法确定的阻尼比相对误差大体上均在迅速减小,只有规范法在有效围压为100 kPa时,其相对误差有较小的增大趋势;5种方法中,Kumar法确定的阻尼比最接近平均阻尼比,互相关函数法远高于平均阻尼比,Das and Luo法和Kokusho法确定的阻尼比基本一致但低于平均阻尼比。建议以后的工程应用中,加载方式为应力控制时,可采用自相关函数法确定动剪切模量,采用Kumar法确定阻尼比,二者确定的动剪切模量和阻尼比均最接近平均值。  相似文献   

Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer   总被引：1，自引：0，他引：1  

Wei Chen  Xi Chen  Jianbing Peng  Mahdi Panahi  Saro Lee 《地学前缘(英文版)》2021,12(1):93-107

As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.  相似文献   

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management   总被引：1，自引：0，他引：1  

Zizheng Guo  Yu Shi  Faming Huang  Xuanmei Fan  Jinsong Huang 《地学前缘(英文版)》2021,12(6):243-261

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.  相似文献   

Arsenic contamination caused by roxarsone transformation with spatiotemporal variation of microbial community structure in a column experiment          下载免费PDF全文

Liu Ya-ci  Zhang Zhao-ji  Zhao Xin-yi  Wen Meng-tuo  Cao Sheng-wei  Li Ya-song 《地下水科学与工程》2021,9(4):304-316

Arsenic contamination from roxarsone in livestock manure is common, and livestock manure continuously accumulates in the open environment. Evaluations of the environmental processes of As mobilization and transformation are critical for predicting the fate of As compounds after roxarsone degradation. In this study, spatiotemporal variations in As species and microbial community structure were characterized using laboratory column experiments with background soil collected from Yanggu County (northern Shandong Plain, China), a region of intense poultry production. Organic and inorganic arsenic were detected by high-performance liquid chromatography (HPLC) and HPLC with hydride generation atomic fluorescence spectrometry (HPLC-HG-AFS), respectively. High-throughput sequencing technology was used to describe microbial diversity. Results showed that roxarsone was transformed completely within 7 days, and As(Ⅲ) and As(Ⅴ) were the major degradation products. The concentration of As(Ⅲ) was much lower than that of As(Ⅴ). The As(Ⅲ) concentration increased significantly after Day 14, whereas the As(Ⅴ) concentration increased significantly after Day 84, indicating that As(Ⅲ) was initially produced. The microbial community structure changed significantly as roxarsone transformed into various As compounds. A critical and dominant bacterial strain, norank_f__Family_XVⅢ, was found to be related to the degradation of roxarsone into As(Ⅲ). This study improves our understanding of the fate of As species released from poultry litter to soil and groundwater, which is a threat to human health and environment.  相似文献   

基于监测数据的全国地下水质动态变化特征     

殷秀兰  李圣品 《地质学报》2021,95(5):1356-1365

地下水质动态变化及其趋势研判是区域水资源调配决策的重要依据.本文以全国2007～2017年国家级地下水监测网水质数据为基础,结合典型地区的代表性监测组分超标特征及动态趋势,开展了地下水质动态变化过程研究,结果表明:全国地下水监测中以Ⅳ类水质点占比最大,其次为Ⅱ类水质点;Ⅰ～Ⅲ类水质点数量较少,而且占比以降低为主,Ⅳ和Ⅴ类地下水监测点逐渐增加,其中Ⅳ类水质点的比例由40.50％增加至51.45％;全国地下水质主要的超标组分为pH、总硬度、总溶解性固体、硫酸盐、氯化物、高锰酸钾指数、铁、锰、氟化物、"三氮".以华北地区、华东地区、西南地区和西北地区为代表,分析研究典型地区地下水质的动态变化过程及其影响因素,结果显示,在地下水位变化较大的地区,地下水质状况随着地下水位变化明显,在地下水位波动较小的地区,地下水质状况也基本上变化较小.研究成果对于科学评价地下水资源、合理制定区域地下水开发利用规划、防治地下水污染等具有一定的指导作用.  相似文献