Predicting Debris Yield From Burned Watersheds: Comparison of Statistical and Artificial Neural Network Models1

Abstract: Alluvial fans in southern California are continuously being developed for residential, industrial, commercial, and agricultural purposes. Development and alteration of alluvial fans often require consideration of mud and debris flows from burned mountain watersheds. Accurate prediction of sediment (hyper‐concentrated sediment or debris) yield is essential for the design, operation, and maintenance of debris basins to safeguard properly the general population. This paper presents results based on a statistical model and Artificial Neural Network (ANN) models. The models predict sediment yield caused by storms following wildfire events in burned mountainous watersheds. Both sediment yield prediction models have been developed for use in relatively small watersheds (50‐800 ha) in the greater Los Angeles area. The statistical model was developed using multiple regression analysis on sediment yield data collected from 1938 to 1983. Following the multiple regression analysis, a method for multi‐sequence sediment yield prediction under burned watershed conditions was developed. The statistical model was then calibrated based on 17 years of sediment yield, fire, and precipitation data collected between 1984 and 2000. The present study also evaluated ANN models created to predict the sediment yields. The training of the ANN models utilized single storm event data generated for the 17‐year period between 1984 and 2000 as the training input data. Training patterns and neural network architectures were varied to further study the ANN performance. Results from these models were compared with the available field data obtained from several debris basins within Los Angeles County. Both predictive models were then applied for hind‐casting the sediment prediction of several post 2000 events. Both the statistical and ANN models yield remarkably consistent results when compared with the measured field data. The results show that these models are very useful tools for predicting sediment yield sequences. The results can be used for scheduling cleanout operation of debris basins. It can be of great help in the planning of emergency response for burned areas to minimize the damage to properties and lives.     

Snowmelt Runoff and Water Yield Along Elevation and Temperature Gradients in California’s Southern Sierra Nevada1

Hunsaker, Carolyn T., Thomas W. Whitaker, and Roger C. Bales, 2012. Snowmelt Runoff and Water Yield Along Elevation and Temperature Gradients in California’s Southern Sierra Nevada. Journal of the American Water Resources Association (JAWRA) 48(4): 667‐678. DOI: 10.1111/j.1752‐1688.2012.00641.x Abstract: Differences in hydrologic response across the rain‐snow transition in the southern Sierra Nevada were studied in eight headwater catchments – the Kings River Experimental Watersheds – using continuous precipitation, snowpack, and streamflow measurements. The annual runoff ratio (discharge divided by precipitation) increased about 0.1 per 300 m of mean catchment elevation over the range 1,800‐2,400 m. Higher‐elevation catchments have lower vegetation density, shallow soils with rapid permeability, and a shorter growing season when compared with those at lower elevations. Average annual temperatures ranged from 6.8°C at 2,400 m to 8.6 at 1,950 m elevation, with annual precipitation being 75‐95% snow at the highest elevations vs. 20‐50% at the lowest. Peak discharge lagged peak snow accumulation on the order of 60 days at the higher elevations and 20 to 30 days at the lower elevations. Snowmelt dominated the daily streamflow cycle over a period of about 30 days in higher elevation catchments, followed by a 15‐day transition to evapotranspiration dominating the daily streamflow cycle. Discharge from lower elevation catchments was rainfall dominated in spring, with the transition to evapotranspiration dominance being less distinct. Climate warming that results in a longer growing season and a shift from snow to rain would result in earlier runoff and a lower runoff ratio.     

喀斯特高原山区的景观格局变化垂直分异性——以贵州省普定后寨地下河流域中下游为例

利用多时相多数据源遥感影像数据(航片、TM影像及SPOT-5影像),采用GIS空间分析技术和数理统计分析相结合的方法,以贵州省普定县后寨地下河流域中下游地区为例,从海拔和坡位2个方面来探讨喀斯特地区的景观格局变化的垂直分异特征.结果表明:林地斑块在海拔范围为1 300～1 350 m及1 450～1 550 m的区域内,变化是最大的;水田和旱地斑块在海拔范围为1 219～1 300 m及1 350～1 450 m的区域内,变化最大.景观格局在山脊和谷底内变化相对较大,其中变化最大的是林地斑块;景观格局在陡坡和缓坡地区的变化相对较小,但是也存在一定的变化.该区域中变化较大的为水田和旱地斑块.在海拔范围为1 300～1 500 m的山脊和谷底区域内,景观斑块类型发生的变化较大.该区域应作为喀斯特高原山区的生态环境保护特别关注的区域.     

西南岩溶石山区石漠化成因探讨及其防治对策

分析了西南岩溶石山区石漠化形成的原因,着重从地质、水文地质及气象等方面对石漠化的形成机制进行了探讨,并在总结前人治理石漠化成果的基础上,提出了现阶段较为可行的治理思路及方法。     

土地利用及退耕对喀斯特山区土壤活性有机碳的影响

以西南喀斯特山区几种典型土地利用方式为对象,研究了土地利用及退耕对全土、团聚体活性有机碳及其恢复能力的影响.结果表明,随土壤深度的增加,土壤活性有机碳含量及其离散程度呈下降趋势,其中0~10 cm土壤活性有机碳含量与10~20 cm和20~30 cm两个剖面层次达极显著(P<0.01)差异水平;活性有机碳含量在0~10 cm范围内以<0.25 mm团聚体粒径最高,然而在10~20 cm和20~30 cm活性有机碳在各粒径中的分布并不明显;不同土地利用方式下,水田中无论全土还是团聚体中活性有机碳均表现出较高水平,灌从次之,而以退耕3 a草丛最低.组内-组间主成分分析表明,土地利用方式与土壤活性有机碳的累积特征表现为水田>灌丛>退耕15 a草丛≈旱地>退耕3 a草丛,其中退耕15 a草丛在0~10 cm深度下较旱地增加了20.3%,且达到灌丛土壤活性有机碳的80%,表明喀斯特山区土地退耕初期土壤有机碳恢复速度相对缓慢,而随退耕时间的推移,土壤碳汇效应逐步显现.     

山地城市地表径流源区水质特征监测研究

2010年通过对山地城市重庆江北城区10个地表源区5次地表径流过程水样的采集与分析,研究城区地表径流水质特征及其影响因素,以期为地表径流污染源区控制提供科学依据.结果表明,山地城市重庆地表径流污染过程具有明显的初期冲刷效应,降雨强度影响地表径流水质的变化,地表径流水质的波动同雨强的变化呈同步趋势,雨强增加,污染物浓度下降,表现出水质变化的随机性.山地城市重庆地表径流COD、TP与TSS具有显著的正相关性.悬浮物是城市地表径流污染的主要污染物,而且是有机物质和磷素的载体.有机物质与磷素主要以颗粒态的形式存在,而氮素以溶解态的氨和硝酸盐为主.山地城市地表径流水质TSS、COD、TN、TP和NH4+-N在各个源区的差异显著,商业区和城市交通主干道TSS、COD和TP的浓度最高,其次为城市支路、居民区道路、停车场和屋顶.不透水地表功能、交通流量、人流量和卫生管理是影响地表径流水质的主要因素.城市商业区、交通干道和人流量高的居民区道路是城市地表径流污染的关键源区.     

大别山东南麓薄皮构造及地体碰撞拼贴

大别山东南麓有两套薄皮构造,以韧性剪切带为代表的韧性-半韧性薄皮构造和以逆冲推覆为特征的半脆性-脆性薄皮构造.后者可划分出六个一级薄皮层片体,总体上呈倒序迭瓦状结构.地球物理资料等证实大别地体仰冲于扬子地体之上.两者是以缓倾角断裂为边界的斜接碰撞,其南界为郯庐断裂南端、襄广断裂南东段及其间的隐伏拆离断层,主拼贴断裂在地表分枝为数条层滑-逆冲断裂.主体碰撞时代为225-75Ma,最终拼贴时代可延续到33～23Ma.韧性-半韧性薄皮构造形成于碰撞中、晚期,而半脆性-脆性薄皮构造则形成于碰撞末期及后造山期.在扬子地体俯冲过程中,俯冲于大别地体之下的盖层层片体被逐片“铲出”,呈上老下新的迭瓦状结构.广泛发育的薄皮构造调节了地体碰撞拼贴造成的强烈压缩变形.     

冬季山谷风和海陆风对京津冀地区大气污染分布的影响

为了弄清冬季山谷风、海陆风对京津冀地区大气污染时空分布的影响,利用2016年12月地面加密自动气象站逐时观测数据和中国环境监测总站发布的逐时PM_(2.5)浓度数据,计算平均风矢量场和平均PM_(2.5)浓度场,分析山谷风、海陆风变化规律及其对PM_(2.5)浓度分布的影响.结果表明,在山谷风日,中午至下午谷风将位于河北太行山东部地区的污染物向北输送.傍晚以后,在北京西部、北部,以及河北太行山山前出现的山风与偏南风构成"人字形"辐合线,辐合线的汇聚作用使北京地区、廊坊,以及保定、石家庄、邢台等地大气污染加重.在海陆风日,下午至前半夜,河北中东部沿海地区出现东南向海风,深入内陆到达天津东南部地区,海风前缘区域大气污染加重;通过对中国科学院大气物理研究所铁塔0～325 m风向风速与PM_(2.5)浓度时间变化关系分析,以及利用Cressman法插值得到的地面风向风速和PM_(2.5)浓度二维格点场,分析北京地区重霾污染过程中近地层山谷风和海陆风对大气污染形成的影响:中午至下午,谷风将大气污染物向北京输送.傍晚以后,大气污染物在山风与偏南风形成的辐合线附近汇聚,在北京地区及以南地区形成PM_(2.5)高污染区.凌晨至早晨北京被山风控制,大气污染物被吹离北京、滞留在北京以南至天津西北地区.冬季,山谷风的输送和汇聚作用使大气污染物以日为周期不断循环和累积,对北京地区至北京以南地区、河北太行山东部地区的大气重污染形成起重要作用.     

基于454高通量测序的黄土高原不同乔木林土壤细菌群落特征

选取黄土高原不同乔木林（辽东栎,LDL;侧柏,CB;刺槐,CH;油松,YS）表层土壤为研究对象,利用第二代高通量测序技术罗氏454平台对其进行16S rRNA基因V1~V3可变区测序,通过分析其Alpha多样性、物种组成和丰度、群落结构,结合土壤的理化性质研究其对细菌群落结构的影响.结果表明：所有土壤样品共检测到36个门,84个纲,187个目.不同乔木林土壤中优势菌来自变形菌门（Proteobacteria）、放线菌门（Actinobacteria）、酸杆菌门（Acidobacteria）、绿弯菌（Chloroflexi）和浮霉菌门（Planctomycetes）,主要的优势菌纲为放线杆菌纲（Actinobacteria）、α-变形菌纲（Alphaproteobacteria）、酸杆菌（Acidobacteria）、β-变形菌纲（Betaproteobacteria）、浮霉菌纲（Planctomycetacia）.不同乔木林土壤中绿弯菌门（Chloroflexi）与pH值呈极显著的正相关,总磷和蓝细菌（Cyanobacteria）呈极显著的正相关,微生物生物量碳与芽单胞菌门（Gemmatimonadetes）呈极显著的负相关,土壤总磷含量可能为CB样地区别于其他土样群落组成的主要因素.LDL样地细菌群落受环境影响较小.     

山区城市土地利用动态空间分布特征——以贵州省六盘水市为例

运用地形位指数和分布指数,借助遥感和地理信息系统技术,对贵州省六盘水市区1990-2010年间土地利用变化空间特征进行定量分析。结果表明:①20 a间土地利用空间分布结构发生了一定的改变,建设用地在低地形位的优势性增强且有向高地形位扩展的趋势,水田的优势分布范围缩小,但在低地形位优势增强,建设用地、 水田在低地形位的优势增强导致旱地、 灌木林地优势分布区间上移并收缩;②研究时段内工作区土地利用变化的空间分布未出现明显的分化,各类型相间分布,未形成明显的以建设用地为中心的带状分布格局;③1990年研究区各土地利用类型在地形位梯度上的分布已经分异成高、 中、 低三段式格局且20 a间未发生明显改变,各土地利用类型的地形适应弹性已经被拉大。