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91.
Surface roughness and slope gradient are two important factors influencing soil erosion. The objective of this study was to investigate the interaction of surface roughness and slope gradient in controlling soil loss from sloping farmland due to water erosion on the Loess Plateau, China. Following the surface features of sloping farmland in the plateau region, we manually prepared rough surfaces using four tillage practices (contour drilling, artificial digging, manual hoeing, and contour plowing), with a smooth surface as the control measure. Five slope gradients (3°, 5°, 10°, 15°, and 20°) and two rainfall intensities (60 and 90 mm/hr) were considered in the artificial rainfall simulation experiment. The results showed that the runoff volume and sediment yield increased with increasing slope gradient under the same tillage treatment. At gentle slope gradients (e.g., 3° and 5°), the increase in surface roughness prevented the runoff and sediment production, that is, the surface roughness reduced the positive effect of slope gradient on the runoff volume and sediment yield to a certain extent. At steep slope gradients, however, the enhancing effect of slope gradient on soil erosion gradually increased and surpassed the reduction effect of surface roughness. This study reveals the existence of a critical slope gradient that influences the interaction of surface roughness and slope gradient in controlling soil erosion on sloping farmland. If the slope gradient is equal to or less than the critical value, an increase in surface roughness would decrease soil erosion. Otherwise, the increase in surface roughness would be ineffective for preventing soil erosion. The critical slope gradient would be smaller under higher rainfall intensity. These findings are helpful for us to understand the process of soil erosion and relevant for supporting soil and water conservation in the Loess Plateau region of China. 相似文献
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Generation of continuous surface soil moisture dataset using combined optical and thermal infrared images
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Surface soil moisture (SSM) is a critical variable for understanding water and energy flux between the atmosphere and the Earth's surface. An easy to apply algorithm for deriving SSM time series that primarily uses temporal parameters derived from simulated and in situ datasets has recently been reported. This algorithm must be assessed for different biophysical and atmospheric conditions by using actual geostationary satellite images. In this study, two currently available coarse‐scale SSM datasets (microwave and reanalysis product) and aggregated in situ SSM measurements were implemented to calibrate the time‐invariable coefficients of the SSM retrieval algorithm for conditions in which conventional observations are rare. These coefficients were subsequently used to obtain SSM time series directly from Meteosat Second Generation (MSG) images over the study area of a well‐organized soil moisture network named REMEDHUS in Spain. The results show a high degree of consistency between the estimated and actual SSM time series values when using the three SSM dataset‐calibrated time‐invariable coefficients to retrieve SSM, with coefficients of determination (R2) varying from 0.304 to 0.534 and root mean square errors ranging from 0.020 m3/m3 to 0.029 m3/m3. Further evaluation with different land use types results in acceptable debiased root mean square errors between 0.021 m3/m3 and 0.048 m3/m3 when comparing the estimated MSG pixel‐scale SSM with in situ measurements. These results indicate that the investigated method is practical for deriving time‐invariable coefficients when using publicly accessed coarse‐scale SSM datasets, which is beneficial for generating continuous SSM dataset at the MSG pixel scale. 相似文献
95.
研究了移动测量系统宽幅影像的拼接与量测算法。通过建立三幅影像柱面全景投影的几何关系,能够直接拼接完成宽幅影像。利用宽幅影像和原始影像间反投影变换关系以及三幅原始影像的同、异步立体像对,可建立宽幅影像与物方空间坐标间一一对应关系,从而实现宽幅影像目标的量测算法。宽幅影像的投影拼接和量测实验表明,利用柱面全景投影拼接得到宽幅影像的方法可应用于移动测量平台宽幅影像序列的拼接;在原始影像具备同步立体像对的条件下,宽幅影像量测的绝对精度可达1 m以内,相对精度可达0.2 m以内,满足城市环境实景目标量测的精度需求。 相似文献
96.
祁连山北缘-河西走廊西段位于青藏高原东北缘,是新生代陆内构造活动最强烈地区。基于野外构造观测、横跨山前及前陆盆地区的三维地震构造分析与解释,结合地震地质属性提取分析,识别出祁连山北缘-酒泉盆地西段窟窿山-柳沟庄带隐伏的弧形褶皱-逆冲带,该弧形构造是造山带基底逆冲构造楔体垂向差异抬升与向前陆方向差异运动的产物;该弧形结构控制本区下白垩统地层裂缝发育、分布与破裂强度,并与本区先期断裂、裂缝带产生构造叠加效应,形成弧形构造“中央强裂缝发育带”,是形成构造裂缝型油气藏的有利区域。 相似文献
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A timescale decomposed threshold regression(TSDTR) downscaling approach to forecasting South China early summer rainfall(SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR.The two models are developed based on the partial least squares(PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915–84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation(PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985–2006, compared to other simpler approaches. This study suggests that the TSDTR approach,considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions. 相似文献
99.
基于FY3A/MERSI资料分析广东省气溶胶光学厚度分布 总被引:3,自引:3,他引:0
利用国产极轨气象卫星FY3A的MERSI AOD产品分析2010—2013年广东省气溶胶光学厚度的分布规律。结果表明:MERSI AOD产品与地面太阳光度计实测数据的相关系数为0.72,其平均绝对值误差为0.12,均方根误差为0.15,数据精度可满足研究需要;从AOD的空间分布看,珠三角西翼东翼山区五市,其中佛山市、东莞市、中山市为广东省AOD均值最高的地区,梅州市、河源市为广东省AOD均值最低的地区;从AOD的时间分布看,2010—2013年间,AOD呈现先升高后降低的趋势,2011年为拐点,与此同时,AOD还表现出明显的季节变化特征,春季为AOD高值期,夏季、秋季次之,冬季最低。 相似文献
100.
利用黄淮海区域90个站点1971—2000年逐日气象资料以及国家气候中心发布的未来气候变化情景(A1B)下区域气候模式(Reg CM3)模拟的黄淮海区域1951—2070年0.25°×0.25°格点气象资料,结合夏玉米主要生育期对温度的需求,构建了黄淮海区域的温度适宜度和变异系数模型,并对1951—2070年黄淮海区域热量资源、夏玉米主要生育期的温度适宜度及其变异系数的时空变化特征进行分析。结果表明:1)黄淮海区域≥10℃积温和80%保证率下日平均温度≥10℃的初日均呈现由北向南依次增加的趋势,且随时间推移,分别呈增加和提前趋势。2)黄淮海区域夏玉米播种—出苗期的温度适宜度随时间整体呈逐渐上升的变化趋势、其变异系数随时间呈降—升—降的变化趋势;出苗—抽雄期的温度适宜度随时间呈先降后升的变化趋势、其变异系数呈降—升—降—升的变化趋势;抽雄—成熟期的温度适宜度空间上呈现2010年前北低南高、未来情景下中部低四周高的分布趋势,时间上呈2010年前稳定、未来情景下先降后升的变化趋势,其变异系数呈相反变化趋势;3)黄淮海区域夏玉米温度适宜度及其变异系数从播种—出苗期—出苗—抽雄期—抽雄—成熟期均呈反相位的变化关系。 相似文献