用小时降雨资料估算降雨侵蚀力的方法

降雨侵蚀力是进行土壤流失量预报的基本因子,EI₃₀是迄今得到广泛应用的定量指标,但它的计算需要降雨过程资料,使其推广应用受到很大限制。用自动气象观测提供的高精度等间隔降雨资料,代替降雨过程资料,是估算降雨侵蚀力指标的首选。国际上对此已有研究,发现有很大的地区差异性。为此,本文在水蚀严重的中国东部季风区选择5个代表站点,共456次降雨过程资料,建立了用60 min等间隔雨量资料估算次降雨侵蚀力的计算方法。研究结果表明:直接用60 min等间隔资料计算的降雨侵蚀力指标值,与用降雨过程资料计算的结果相比,降雨动能E差异较小,主要差异体现在最大30 min雨强I₃₀上,由此导致降雨侵蚀力指标EI₃₀的差异也十分明显。利用自动气象观测小时雨量资料计算降雨侵蚀力指标值,通过公式(EI₃₀)_bp=1.730(EI₃₀)₆₀转换,可以较精确地估算全国降雨侵蚀力,与用日、月和年降雨量资料的估算值相比,能够提高土壤侵蚀预报精度。     

1960-2009年中国降雨侵蚀力的时空变化趋势

降雨侵蚀力反映了降雨对土壤侵蚀的潜在能力,因此降雨侵蚀力已经成为土壤侵蚀、产沙和水环境建模的主要参数之一。利用中国590个气象站1960-2009年逐日降雨量资料估算了中国每个气象站的降雨侵蚀力,并使用趋势系数、气候倾向率和Kriging空间插值方法分析了中国降雨侵蚀力的时空变化趋势。结果表明:我国年均降雨侵蚀力从东南沿海向西北内陆逐渐递减,与年均降水量空间分布基本一致;近50年来我国大部分地区年降雨侵蚀力呈现不显著的上升趋势,存在四个明显的上升区域和两个明显的下降区域;59个气象站年降雨侵蚀力变化趋势通过了0.05显著水平的置信度检验,年降雨侵蚀力显著增加的气象站主要分布在青藏高原中东部、东缘、天山山脉以及东南沿海区域。青海省的诺木洪-都兰-曲麻莱-伍道梁一带近50年来年降雨侵蚀力增加趋势最为显著,有可能加剧长江、黄河源头土壤侵蚀的风险。     

基于CLDAS融合降水的中国降雨侵蚀力研究

气象站和卫星降雨资料估算降雨侵蚀力时存在无法反映空间异质性且精度差的问题,基于CLDAS多源融合降水,利用EI₆₀模型从不同的时空尺度对中国的降雨侵蚀力进行评估,并结合降雨量、侵蚀性降雨次数、侵蚀密度等指标,探讨降雨对土壤侵蚀的潜在作用。结果表明：（1） CLDAS降雨侵蚀力与地面实测数据在不同的时间尺度均有良好的回归关系,相关系数达到0.8以上,与CMORPH降雨侵蚀力相比,其相对误差显著降低,可以准确反映全国范围的降雨侵蚀力季节性变异。（2） 在2001—2020年,不同雨量区的降雨侵蚀力、降雨量和侵蚀性降雨次数的变化趋势基本一致,高雨量区的年际变化波动剧烈,侵蚀性降雨次数和暴雨过程协同影响降雨侵蚀力的大小。（3） 空间上,中国的降雨侵蚀力值的特点为东南沿海地区高、西北内陆地区低。时间上,侵蚀性降雨集中在5—8月,夏、秋两季对土壤造成的侵蚀影响更大。（4） 通过对年降雨量、年侵蚀密度和年暴雨量进行分区定量分析,结果表明暴雨量与侵蚀密度成正相关关系,即年降雨量一定,暴雨事件越多,降雨侵蚀密度越大。     

黄土高原塬面保护区降雨侵蚀力时空分布特征及其影响因素研究

通过采用Mann-Kendall趋势分析法、小波分析方法、地统计插值等方法,基于黄土高原塬面保护区及临近的21个站点的逐日降水量数据,对区域内降雨侵蚀力的时空变化,趋势及主要影响因素进行了分析。结果表明:(1)黄土塬面保护区1960—2017年多年平均降雨量为599.2 mm;多年平均降雨侵蚀力为1 871.91 MJ·mm·hm^-2·h^-1·a^-1,降雨侵蚀力在过去60 a来呈微弱上升趋势且变化的季节差异显著。(2)黄土高原塬面保护区降雨侵蚀力的空间分布大体呈由南部向两侧递减的趋势,Mann-Kendall Z值除研究区北部、东部呈下降趋势,其余区域都为上升趋势。(3)黄土高原塬面保护区降雨侵蚀力多年存在32 a的大周期,在大周期内还存在13 a、52 a的小周期。(4)影响北半球中高纬度地区的主要的大气环流因子中仅Cold&Warm Episodes by Season因子的波动对整个区域和陕西塬区的降雨侵蚀力有一定影响,二者存在一定的负相关性,其余环流指数与降雨侵蚀力没有显著的关联性;此外太阳黑子与陕西塬区...     

A model study on seasonal spatial-temporal variability of the Lagrangian Residual Circulations in the Bohai Sea

The spatial distribution and seasonal variation of the tide-induced Lagrangian Residual Circulations (LRC hereafter), wind-driven LRC, and the coupling dynamic characteristics were simulated using ECOM, given the Hellerman and Rosenstein global monthly-mean wind stresses. The results showed that the tide-induced LRC of the harmonic constituent m2 bears an identical pattern in four seasons in the Bohai Sea: the surface one is weak with random directions; however, there exist a southeast current from the Bohai Strait to the Laizhou bay, and a weakly anticlockwise gyre in the south of the Bohai Strait for the bottom layer LRC. The magnitude of bottom layer tide-induced LRC is larger than the surface one, and moreover, it contributes significantly to the whole LRC in the Bohai Sea. Unlike the identical structure of the tide-induced LRC, the wind driven LRC varies seasonally under the prevailing monsoon. It forms a distinct gyre under the summer and winter monsoons in July and January respectively, but it seems weak and non-directional in April and September.     

A model, study on seasonal spatial-temporal variability of the Lagrangian Residual Circulations in the Bohai Sea

1 IntroductionThe BohaiSea is a sem i-closed shallow sea w ith a m ean depth ofaround 20 m ,com posed oftheLiaodong Bay,the BohaiBay,the Laizhou Bay and the BohaiBasin,and connected to the N orthY ellow Sea through a latitudinal strait. The tidal dynam ic…     

渤海风驱-潮致Lagrange余流的数值模拟与季相时空变异

The spatial distribution and seasonal variation of the tide-induced Lagrangian Residual Circulations (LRC hereafter), wind-driven LRC, and the coupling dynamic characteristics were simulated using ECOM, given the Hellerman and Rosenstein global monthly-mean wind stresses. The results showed that the tide-induced LRC of the harmonic constituent M2 bears an identical pattern in four seasons in the Bohai Sea: the surface one is weak with random directions; however, there exist a southeast current from the Bohai Strait to the Laizhou bay, and a weakly anticlockwise gyre in the south of the Bohai Strait for the bottom layer LRC. The magnitude of bottom layer tide-induced LRC is larger than the surface one, and moreover, it contributes significantly to the whole LRC in the Bohai Sea. Unlike the identical structure of the tide-induced LRC, the wind driven LRC varies seasonally under the prevailing monsoon. It forms a distinct gyre under the summer and winter monsoons in July and January respectively, but it seems weak and non-directional in April and September.     

渤海风驱-潮致拉格朗日余流的数值模拟与季相时空变异

利用HellermanandRosenstein全球风应力资料中的多年月平均风场资料驱动ECOM模型,设计了潮致、纯风生以及风与潮两者叠加三个数值实验对渤海海域风驱-潮致拉格朗日(Lagrange)余流的逐月时空分布与季节变化进行了模拟。研究结果表明,季风的大小和方向决定了渤海风驱-潮致拉格朗日余流的大小和方向,是影响余流流向和流速的重要因素。冬季,从渤海西岸到莱州湾海域风驱-潮致拉格朗日余流表现出一个大逆时针环流,辽东湾呈现顺时针方向流动,渤海中部存在一个弱的顺时针流环。夏季,整个渤海海域呈现顺时针流况,渤海海盆存在一微弱的逆时针涡旋,一支西南向流沿辽东湾东岸穿越渤海海盆,与起自渤海湾的东向流一起进入莱州湾。风驱-潮致拉格朗日余流主要受风的控制,潮汐则起到一定的调整作用。     

An analysis of seasonal biases in satellite and reanalysis rainfall products in the Savannah River basin

Satellite-based precipitation data are a viable source of information in data-sparse regions and are particularly valuable for hydrological modelling applications. Several studies of satellite-based precipitation focus on monthly or greater timescales, but a relatively fewer number have been done on the daily or sub-daily scales. Also, biases in satellite-based precipitation data are often region-specific and such information is important for quantifying input errors in hydrological models. Our study builds upon these needs by examining biases in daily precipitation data for a watershed in the southeastern United States. We observed biases that occur seasonally and by magnitude. Seasonally, precipitation correlates well in most seasons but summer, likely due to the sporadic nature of convective precipitation that is a common precipitation mechanism in this region during the summer. Daily precipitation biases are around 5?mm, but the sign of the bias varies by season, with positive biases in all seasons but fall. Additionally, we found that satellite-based data tend to overestimate light precipitation relative to the multi-gauge average, which more often records no precipitation.     

Urban growth simulation by incorporating planning policies into a CA-based future land-use simulation model

Urban land-use change is affected by urban planning and government decision-making. Previous urban simulation methods focused only on planning constraints that prevent urban growth from developing in specific regions. However, regional planning produces planning policies that drive urban development, such as traffic planning and development zones, which have rarely been considered in previous studies. This study aims to design two mechanisms based on a cellular automata-based future land-use simulation model to integrate different planning drivers into simulations. The first update mechanism considers the influence of traffic planning, while the second mechanism can model the guiding effect of planning development zones. The proposed mechanisms are applied to the Pearl River Delta region, which is one of the fastest growing areas in China. The first mechanism is validated using simulations from 2000–2013 and demonstrates that simulation accuracy is improved by the consideration of traffic planning. In the simulation from 2013–2052, the two mechanisms are implemented and yield more realistic urban spatial patterns. The simulation outcomes can be employed to identify potential urban expansion inside the master plan. The proposed methods can serve as a useful tool that assists planners in their evaluation of urban evolvement under the impact of different planning policies.     

Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China

The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission (TRMM) data with rain gauge data and further to use this TRMM data to drive a Distributed Time-Variant Gain Model (DTVGM) to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year (2001-2010) daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R² varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years (2001-2007) of data on daily hydrological processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamflow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.     

基于FloodArea模型新疆山洪淹没模拟及致灾临界雨量阈值的研究——以皮里青河流域为例

以皮里青河流域为研究区,运用小时降水、土地利用类型、数字高程（DEM）、实测淹没深度等数据,基于FloodArea模型对研究区2010年5月2日、2012年6月3日、2016年5月9日、2016年6月17日洪水过程进行再现模拟,通过精度验证并建立了降水－淹没深度的关系,在此基础上确定了4个淹没等级对应的致灾临界雨量。相关分析得出喀拉亚尕奇乡累计8 h降雨量与模拟洪水淹没深度的相关性最好,达到了0.96,潘津乡降雨累计5 h的相关性最好,为0.99;通过实测数据对模拟淹没深度进行精度检验得出,喀拉亚尕奇乡和潘津乡两个考察点相对误差分别为0.47 m和0.1 m,误差率分别为31.33%和7.69%,FloodArea模型对研究区洪水过程模拟的效果较好,可以反映出该区域的洪水淹没情况,能为无水文资料的山区流域的山洪过程进行较为精准的模拟;按照山洪灾害等级划分标准和降水-淹没深度的关系得出,预警点累计5 h降水得到对应4个等级的致灾临界雨量阈值分别为：四级17.84 mm、三级32.39 mm、二级54.21 mm、一级76.04 mm。     

Targeting seasonal climate forecasts for integration into household level decisions: the case of smallholder farmers in Lesotho

Seasonal climate forecasts have been promoted as a means to increase the resilience of marginal groups in Africa. The manifestations of this are still to be seen. This paper argues that successful dissemination and adoption of the forecast requires an in-depth profile of the characteristics and needs of user groups. The case study of a mountainous village in southern Lesotho is used to highlight the decisions which one group of marginal users – smallholder farmers – might make in response to the forecast. A participatory role-play exercise explores what information households presently receive and how new climate forecast information could be integrated into seasonal decision making. Results show that there are a number of low-input options available to these farmers for responding to the forecast. Adoption, however, is going to require repeated exposure to the forecast in conjunction with forecast development that is suited to users' needs. The case study is linked back to the larger scale by suggesting paths that seasonal climate forecast development could take if it is to contribute to improving livelihood sustainability among marginal groups.     

基于地理探测器的喀斯特不同地貌形态类型区土壤侵蚀定量归因

土壤侵蚀形成机制与影响因素识别是当前研究的核心与前沿议题,然而从多因素综合作用的角度进行定量归因仍需加强。以喀斯特典型峰丛洼地流域为研究区,基于GIS手段和RUSLE模型模拟土壤侵蚀,综合土地利用、坡度、降雨、高程、岩性、植被覆盖度等影响因子,应用地理探测器方法针对喀斯特不同地貌形态类型区进行土壤侵蚀的定量归因研究。结果表明,各影响因子对土壤侵蚀的解释力及因子间耦合作用程度在不同地貌形态类型区差异显著,其中土地利用和坡度是决定土壤侵蚀空间异质的主导因子,但在山地丘陵区,随着地形起伏度的升高,坡度的控制作用下降,即地理探测器q值表现为中海拔丘陵>小起伏中山>中起伏中山;生态探测器显示土地利用对土壤侵蚀的影响相比于其他因子有显著差异;双因子交互作用有助于增强对土壤侵蚀的解释力,土地利用与坡度的协同作用对土壤侵蚀的解释力达到70%以上;对于土壤侵蚀空间分布的差异性检验,风险探测器显示在小起伏中山、中起伏中山等地貌形态类型中,具有显著差异的影响因子分层组合数占比至少55%。因而,喀斯特地区土壤侵蚀的治理应综合考虑不同地貌形态类型区土壤侵蚀影响机制的空间异质性。     

Study on potential evapotranspiration and wet-dry condition in the seasonal frozen soil region of northern Tibetan Plateau

This study was based on the CEOP/CAMP-Tibet observed data at AWS (Automatic Weather Station) of MS3478 in the seasonal frozen soil region of northern Tibetan Plateau from March 2007 to February 2008. The variation characteristics of PE (potential evapotranspiration) were analyzed based on the Penman-Monteith method recommended by FAO (the Food and Agriculture Organization of the United Nations). The contributions of dynamic, thermal and water factors to PE were discussed, and the wet-dry condition of the plateau region was further studied. The results indicated that daily PE was between 0.52 mm and 6.46 mm for the whole year. Monthly PE was over 107 mm from May to September, but decreased to less than 41 mm from November to February. Annual PE was 1,037.8 mm. In the summer, thermal PE was significantly more than dynamic PE, but conversely in the winter. Annual variation of thermal PE was of sine wave pattern. In addition, drought and semi-drought climate lasted for a long time while semi-humid climate was short. The effect of water and dynamic factors on PE varied considerably with the seasons. Annual variation of thermal PE was of sine wave pattern.     

Estimating the count of completeness errors in geographic data sets by means of a generalized Waring regression model

In this article, we propose a statistical model for estimating the probable number of completeness errors (omissions plus commissions) in a cell (a map tile or cluster) of a data set to guide updating or improvement efforts. The number of completeness errors is a count data variable related to some exogenous covariates that may also be known for each cell (e.g. count of features, rural or urban typology, etc.) and to other unknown variation sources. We propose and adjust a generalized Waring regression model for counting these errors in cells of 1 × 1 km² on the Topographic Map of Andalusia (Spain). This model is compared with the Poisson regression model and the negative binomial regression model and performs better. The empirical relationship established by the model indicates that the number of completeness errors is related to the following exogenous covariates: the number of cartographic features of the data set, the fact that the cell covers a littoral or urban zone and the spatial division of the contracted suppliers. For cells having less than 5 errors, most of the variability corresponds to unknown external factors (liability), but when the number of errors rises, the greater part of the variability is due to unknown internal characteristics of each cell (proneness). With these estimations, the producer can derivate statistical summaries and spatial representations and develop better planning of production activities such as actualization.     

基于FSDAF模型的干旱区典型绿洲城市夏季地表热岛效应时空演变研究

全球城市化进程加快引起的干旱区绿洲城市热岛效应变化及其生态环境问题已成为当前国内外城市气候、环境和生态等领域的研究热点之一.基于遥感热红外通道反演的地表温度(Land surface temperature,LST)是开展城市地表热岛(Surface urban heat island,SUHI)效应监测研究的关键参数...     

多因素耦合下三峡库区土地利用未来情景模拟

模型模拟和情景变化分析是未来土地利用变化研究的核心内容,本文以2000年三峡库区土地利用现状为基期数据,利用Binary Logistic模型回归分析驱动因子与土地利用间的关系,利用CLUE-S模型对2010年土地利用进行模拟,校验并确定影响库区土地利用驱动因素的主要参数后,基于自然增长、粮食安全、移民建设和生态保护对2020年、2030年库区土地利用情景予以模拟。结果表明：① 通过Binary Logistic模型分析和检验,水田、旱地、林地、草地、建设用地和水域的ROC曲线下面积值均大于0.8,表明所选驱动因子对土地利用的解释能力较强,可用来估算土地利用概率分布;② 2010年各地类模拟结果经验证得Kappa系数分别为水田0.9、旱地0.92、林地0.97、草地0.84、建设用地0.85和水域0.77,总体上能满足模拟与预测需求;③ 多情景模拟显示库区不同土地利用类型在空间上的竞争关系,以及所带来的对库区粮食安全、移民建设、生态保护的影响,包括水田大量转换为旱地（“水改旱”）、耕地与林草地被建设占用、林草地开垦为耕地、陡坡耕地退为林草地等行为,需要在土地利用优化中平衡各方面的需求;④ 多因素、多情景模拟能为库区土地利用提供更为清晰的、可供抉择的政策调控思路。     

基于主观心理视角的游客环境行为意愿影响因素研究——以西溪国家湿地公园为例

以公众环境行为 “价值-信念-规范”理论（VBN）以及计划行为论（TPB）为基本借鉴理论,融合旅游活动特性,构建游客环境行为意愿影响因素模型,以西溪国家湿地公园为案例地,以结构方程方法进行数据分析验证理论模型。研究发现：游客环境行为意愿受到特定环境态度、感知行为控制以及旅游地意象3方面因素的直接影响,其中特定环境态度的影响最突出,感知行为控制次之,旅游地意象略弱;主观规范作为中介变量在受到环境价值观影响的同时作用于游客特定的环境态度与感知行为控制;旅游地意象要素直接影响特定环境态度与游客环境行为意愿。