Trends in Raindrop Kinetic Energy with Modeled Climate Warming in the Lake Tahoe Basin

Two means by which climate change may increase surface soil erosion in mountainous terrain are: (1) increasing the frequency of extreme rainfall events and (2) decreasing the duration of snow cover on bare soil. We used output from four general circulation models (GCMs) and two greenhouse gas trajectories to produce a suite of hydrologic variables at a daily time‐step for historic and projected 21st Century conditions. We statistically disaggregated the daily rainfall to hourly, using hourly rainfall from a network of nine weather stations in the Tahoe Basin, and filtered out rain falling on a snowpack. We applied published equations to convert hourly intensity to raindrop kinetic energy (KE) for each day and grid cell in the Basin, averaged across grid cells, and created time series of total annual and maximum annual hourly kinetic energy (TKE and MKE) on snow‐free ground. Using the Generalized Extreme Value distribution, we calculated the significance of long‐term trends in KE on snow‐free ground, and estimated energy levels for return periods of 2, 20, and 100 years. We then detrended the snowpack data and compared the resulting trends in KE with the trends resulting from changes in both rainfall energy and snowpack under two GCMs. Principal findings include (1) upward trends in MKE, (2) stronger upward trends in TKE; and (3) an effect of increasing rainfall intensities on KE in some cases, and a strong effect of reduced snowpack in all cases examined.     

A spatially explicit empirical model of structural development processes in natural forests based on climate and topography

Stand structure develops with stand age. Old-growth forests with well-developed stand structure support many species. However, development rates of stand structure likely vary with climate and topography. We modeled structural development of 4 key stand variables and a composite old-growth index as functions of climatic and topographic covariates. We used a hierarchical Bayesian method for analysis of extensive snap-shot National Forest Inventory (NFI) data in Japan (n = 9244) to account for differences in stand age. Development rates of structural variables and the old-growth index exhibited curvilinear responses to environmental covariates. Flat sites were characterized by high rates of structural development. Approximately 150 years were generally required to attain high values (approximately 0.8) of the old-growth index. However, the predicted age to achieve specific values varied depending on environmental conditions. Spatial predictions highlighted regional variation in potential structural development rates. For example, sometimes there were differences of >100 years among sites, even in the same catchment, in attainment of a medium index value (0.5) after timber harvesting. The NFI data suggested that natural forests, especially old natural forests (>150 years), remain generally on unproductive ridges, steep slopes, or areas with low temperature and deep snow, where many structural variables show slow development rates. We suggest that maintenance and restoration of old natural forests on flat sites should be prioritized for conservation due to the likely rapid development of stand structure, although remaining natural forests on low-productivity sites are still important and should be protected.     

APPLICATION OF THE SNOWMELT RUNOFF MODEL USING MULTIPLE-PARAMETER LANDSCAPE ZONES ON THE TOWANDA CREEK BASIN,PENNSYLVANIA1

ABSTRACT: The Snowmelt Runoff Model (SRM) is designed to compute daily stream discharge using satellite snow cover data for a basin divided into elevation zones. For the Towanda Creek basin, a Pennsylvania watershed with relatively little relief, analysis of snow cover images revealed that both elevation and land use affected snow accumulation and melt on the landscape. The distribution of slope and aspect on the watershed was also considered; however, these landscape features were not well correlated with the available snow cover data. SRM streamflow predictions for 1990, 1993 and 1994 snowmelt seasons for the Towanda Creek basin using a combination of elevation and land use zones yielded more precise streamflow estimates than the use of standard elevation zones alone. The use of multiple-parameter zones worked best in non-rain-on-snow conditions such as in 1990 and 1994 seasons where melt was primarily driven by differences in solar radiation. For seasons with major rain-on-snow events such as 1993, only modest improvements were shown since melt was dominated by rainfall energy inputs, condensation and sensible heat convection. Availability of GIS coverages containing satellite snow cover data and other landscape attributes should permit similar reformulation of multiple-parameter watershed zones and improved SRM streamflow predictions on other basins.     

Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model1

Harshburger, Brian J., Von P. Walden, Karen S. Humes, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2012. Generation of Ensemble Streamflow Forecasts Using an Enhanced Version of the Snowmelt Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(4): 643‐655. DOI: 10.1111/j.1752‐1688.2012.00642.x Abstract: As water demand increases in the western United States, so does the need for accurate streamflow forecasts. We describe a method for generating ensemble streamflow forecasts (1‐15 days) using an enhanced version of the snowmelt runoff model (SRM). Forecasts are produced for three snowmelt‐dominated basins in Idaho. Model inputs are derived from meteorological forecasts, snow cover imagery, and surface observations from Snowpack Telemetry stations. The model performed well at lead times up to 7 days, but has significant predictability out to 15 days. The timing of peak flow and the streamflow volume are captured well by the model, but the peak‐flow value is typically low. The model performance was assessed by computing the coefficient of determination (R²), percentage of volume difference (Dv%), and a skill score that quantifies the usefulness of the forecasts relative to climatology. The average R² value for the mean ensemble is >0.8 for all three basins for lead times up to seven days. The Dv% is fairly unbiased (within ±10%) out to seven days in two of the basins, but the model underpredicts Dv% in the third. The average skill scores for all basins are >0.6 for lead times up to seven days, indicating that the ensemble model outperforms climatology. These results validate the usefulness of the ensemble forecasting approach for basins of this type, suggesting that the ensemble version of SRM might be applied successfully to other basins in the Intermountain West.     

1368-1948年山西霜雪灾害的特征与周期规律研究

通过对山西1368-1948年历史文献资料的搜集、整理和数学分析,对该区霜雪灾害等级、阶段、周期及其成因进行了研究。在这期间,山西共发生霜雪灾害419次,轻度106次、中度228次、重度85次。灾害变化可分为4个阶段,1368-1579年为第1阶段,1580-1699年为第2阶段,1700-1819年为第3阶段,1820-1948年为第4阶段。第1、3阶段距平值主要为负值,灾害频次较低,以轻、中度灾害为主。第2、4阶段距平值主要为正值,灾害频次较高,以中度和重度霜雪灾为主。小波分析表明,灾害存在着4个明显的周期,即10～13年、20年左右、45～50年和120年左右的周期。降雪或寒流引起的气温骤降至0℃以下是造成山西霜雪灾害的主要原因。共发生6次寒冷气候事件,分别出现在1578-1588、1591-1607、1631-1642、1669-1672、1690-1699和1830-1836年。出现3次异常寒冷灾害年,分别是1653、1892和1929年。     

低温复合条件下救灾帐篷环境适应性试验与评价

目的研究救灾帐篷性能受恶劣环境的影响。方法建立多灾复合环境试验平台,利用其平台开展救灾帐篷不同工况下的试验研究,探究不同环境下救灾帐篷内部热环境分布和保温性能的变化。结果帐篷内部热环境分层现象只发生在温度上升阶段,而在附加风载后,分层现象减弱,在下降阶段,各内表面温度变化情况表现基本一致,当附加雪载环境温度低于–10℃时,救灾帐篷的保温性变差。利用价值函数法建立了救灾帐篷耦合环境适应性评价指标体系,提出了风&低温、雨雪复合环境下救灾帐篷适应性评价方法,得出评价得分,并与试验结果相印证。结论低温复合环境下,帐篷内环境受外界影响较大,保温性能不佳,易出现“冷室效应”,应积极寻找新型材料改善帐篷在恶劣环境下的环境适应性。     

中国代表性滑雪场网络关注度时空演变及影响因素

基于百度指数数据,运用指数测度、空间地理分析、回归模型和地理探测器,对2011—2019年中国大陆26个代表性滑雪场网络关注度的时空演变特征及影响因素进行分析。结果表明：（1）时间演化上,网络关注度呈先增后减且逐渐平稳的规律。2015年、2016年为峰值年份,季节性差异明显,共两个波动峰值且为“南北为单,中东为双”的分布格局。（2）空间特性上,全国和地区均为先增后减特征,地区差异显著;变异程度先降后增并趋于稳定,全国分布相对稳定平衡,地区分布呈不稳定集聚特性。省区冷热区域分布总体呈“东北热—西南冷”格局,层级变化以稳定型为主。（3）滑雪场层面上,滑雪场总体偏好层级变动较大,高偏好保持稳定领先,其余层级以下降变动为主。滑雪场冷热点分级呈“北热南冷”的格局,东北、华北两个热点集聚区域演变较为稳定。（4）影响因素上,需求侧影响因素排序为滑雪消费吸引力>受教育程度>经济发展水平>信息化水平>滑雪场建设水平。供给侧的滑雪人次占比、滑雪经济贡献、客运承载力、冰雪旅游资源丰度、官方媒体建设水平解释力较强,其他因素影响并不显著。     

基于RS和GIS的2008年长江中下游雪灾监测——以湖北省为例

2008年1月中旬至2月初，我国长江中下游地区出现了大范围持续低温、雨雪、冰冻天气气候事件，造成了特大积雪灾害。以湖北省为例，基于RS和GIS技术对这次雪灾进行了动态的监测评估。利用连续多天的卫星遥感资料和积雪深度观测资料，在GIS的支持下，计算归一化差分积雪指数（NDSI），提取积雪分布信息，并根据不同海拔高度，确定了积雪深度的NDSI分层阈值，实现了3层积雪深度(0～10、10～20 和20～30 cm)的判识。针对积雪区内不同的土地利用类型，统计了不同深度的积雪面积。结果表明：湖北省近90%面积被雪覆盖，其中江汉平原、鄂东北和鄂东南等地雪灾最为严重，部分地区积雪深度在20 cm以上；水田、旱地等农业用地以及湖泊、水库、河渠等水系积雪最为严重，居民点用地也有较大范围的积雪，居民生活受较大影响；2月2日以后积雪面积逐日减少，到2月8日，积雪基本融化。在上述研究基础上形成了基于RS和GIS的长江中下游积雪监测的业务流程.     

iTree‐Hydro: Snow Hydrology Update For The Urban Forest Hydrology Model1

Yang, Yang, Theodore A. Endreny, and David J. Nowak, 2011. iTree‐Hydro: Snow Hydrology Update for the Urban Forest Hydrology Model. Journal of the American Water Resources Association (JAWRA) 47(6):1211–1218. DOI: 10.1111/j.1752‐1688.2011.00564.x Abstract: This article presents snow hydrology updates made to iTree‐Hydro, previously called the Urban Forest Effects—Hydrology model. iTree‐Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process‐based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate hydrology routines presented in this update to iTree‐Hydro include: (1) snow interception to simulate the capture of snow by the vegetation canopy, (2) snow unloading to simulate the release of snow triggered by wind, (3) snowmelt to simulate the solid to liquid phase change using a heat budget, and (4) snow sublimation to simulate the solid to gas phase via evaporation. Cold climate hydrology routines were tested with research‐grade snow accumulation and weather data for the winter of 1996‐1997 at Umpqua National Forest, Oregon. The Nash‐Sutcliffe efficiency for open area snow accumulation was 0.77 and the Nash‐Sutcliffe efficiency for under canopy was 0.91. The USDA Forest Service offers iTree‐Hydro for urban forest hydrology simulation through http://www.iTreetools.org .