GIS‐Based Spatial Precipitation Estimation: A Comparison of Geostatistical Approaches1

Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km², which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

玻璃减薄蚀刻液中氟硅酸的选择性脱除方法

光电玻璃减薄蚀刻液中氟硅酸(H2SiF6)的累积,是导致蚀刻液无法连续使用而转化为废液的主要原因。尝试对蚀刻废液中氟硅酸进行选择性脱除工艺,探索刻蚀液循环利用的有效处理方法。鉴于氟硅酸的碱金属盐具有溶解度较低的特点,研究考察了利用钠盐或钾盐为沉淀剂,将废液中的H2SiF6以氟硅酸盐的形式沉淀去除,为实现蚀刻液的循环利用提供可能。结果表明,KCl相比NaCl对H2SiF6处理效果更好,但生成的K2SiF6的结晶颗粒过细,难以自然沉降,过滤效果较差;而Na2SiF6结晶沉降特性较好,且使用NaCl为沉淀剂具有价廉易得等特点,可作为氟硅酸的理想沉淀剂。H2SiF6去除率与碱金属盐H2SiF6摩尔计量比正相关,当摩尔计量比NaCl/H2SiF6=2,H2SiF6含量10%的模拟废液,其H2SiF6去除率可达到90%以上。     

沉淀——吸附法处理果胶工艺废水

利用果胶废水中的Al（Ⅲ）和石灰乳沉淀,并用炉渣、活性碳脱色的方法,处理盐板法提取果胶的工艺废水。通过正效实验,研究了最佳工艺条件。该工艺处理后的废水,Al（Ⅲ）去除率96.8％,CODCr去除率为92.7％,SO4^2－去除率为61.5％,且废渣产出量少。     

基于GIS的新疆年降水量空间插值精度比较研究

以新疆具有完整资料的90个气象站点中的75个站点的基本地理信息和1995—2008年平均降水数据资料为基础,以ArcGIS为数据处理平台,分别采用反距离加权法、径向基函数法、普通克里格法、协克里格法对新疆降水空间分布进行插值,并通过没有参与插值的15个气象站点的实际降水量与插值结果进行相对误差分析。研究结果表明:在年降水量插值的4种算法中,普通克里格法(Kriging)的计算精度最高。利用最优的插值方法的栅格降水空间数据库建立的多年降水资源信息系统,可快速计算研究区内任一地域单元中降水的总量及其空间变化,对降水资源模拟、工程规划、发展战略及决策管理均具有重要的意义。     

巢湖水华遥感监测与年度统计分析研究

介绍了巢湖蓝藻水华的日常遥感监测方法与流程,开展了基于日常监测的年度统计分析,为水华环境管理提供了科学依据。首先分析了蓝藻水华与正常水体的光谱差异,利用蓝藻水华在近红外波段的"陡坡效应",基于NDVI方法开展水华日常遥感监测。基于日常监测开展水华年度统计分析,获得水华最早发生日期、最晚发生日期、最大发生面积等,并以水华发生频率、水华起始日期和水华持续时间来分析巢湖一年内高发区、发展趋势及持续时间等时空分布规律。研究表明,2010年巢湖水华的高发区域在巢湖西北部水域,水华持续天数最长的区域是巢湖西北和中部部分区域,水华先在西部沿岸聚集,随时间推移向东部和中部扩散,巢湖西南、中部和东南沿岸是最后新增的水华区域。     

上海市浦东新区大气降水化学组分及其相关性分析

依据上海市浦东新区2010—2015年2个代表性采样点的142份监测数据,对降水中的化学组成及各组分间的相关性进行了分析。结果表明,监测期间单次降雨的pH值为3.85~6.09,平均值为5.09,属硫酸型/硝酸型复合污染酸雨。其中SO_4~(2-)和NO_3~-为主要离子,平均值分别为4.55和3.31 mg/L。通过SPSS统计分析得出,人类生活和生产过程以及海洋源是浦东新区大气降水化学组分的主要来源,但仍存在不同的区域特征。     

近38年安徽省夏季降水日数和强度的分布与变化特征

选用1971～2008年安徽省78个地面气象站的观测资料,分析夏季降水和暴雨的气候变化规律。从结果来看安徽省夏季降水主要受到地理位置、地形地貌和风、温、湿等气象因素的影响。根据主要影响因子的不同,按照降水特性以及行政边界将安徽省划分成了10个区,不同区域内降水特征和分布结构各有差异。在时间变化上,雨日出现概率有下降的趋势,但暴雨日比重和降水量均有升高的变化特征。综合而言,安徽省的降水朝着具有局地性、突发性的强降水过程方面发展,从而导致部分区域内突发性暴雨过程频发     

土壤侵蚀对土地利用和降雨变化响应和空间分布特征——以金沙江一级支流小江流域为例

全球变化引起了一系列环境效应,土壤侵蚀是全球变化最为敏感环境效应之一。选择生态极其脆弱区小江流域作为研究对象,通过遥感影像和雨量站点获取3期土地利用和降雨变化信息,结合区域基础地理信息数据,利用通用土壤流失方程（USLE模型）对该区域土壤侵蚀对土地利用和降雨变化的响应进行了分析。研究表明：（1）降雨量在1981~1990年为降雨量较小年份,1991~2000年为降雨量较大时间段,2001~2005年降雨量开始急剧减少;（2）1987、1995和2005年的平均侵蚀量分别为：7058、8008和7981 t/（hm2〖DK1〗·a),中度侵蚀以上面积分别占总面积的2992%、3383%和3318%,其中极强度侵蚀分别占915%、1281%和1263%;（3）在分布特征上,强度侵蚀和极强度侵蚀主要分布在小江流域的中下游地段。极强度侵蚀主要分布在中海拔区域（1 600~2 800 m）,所占的比例呈持续下降的趋势,但在高海拔区域,极强度侵蚀呈增加趋势;同时,极强度侵蚀集中分布在高坡度段（>35°）上,占其面积的85%以上,且呈持续增加趋势,在中坡度段（15°~35°）上,极强度侵蚀呈现明显的减少趋势。USLE模型可以较好的反映出全球变化条件下土壤侵蚀效应,为合理开发土地资源和人类经济活动提供科学依据     

利用某尾矿制备纳米SiO2

采用固相熔融法从尾矿中提取SiO2,利用超声辅助化学沉淀法制备纳米SiO2。分别研究了NaOH与尾矿质量比、反应温度、反应时间对SiO2提取率的影响,以及溶解水量、HCl浓度、终点pH、超声波功率和超声波频率对纳米SiO2性能的影响,研究表明,当NaOH与尾矿的质量比为1.4∶1,温度为325℃时灼烧25 min后用100 mL水溶解,滴加1.6 mol/LHCl酸化沉淀,终点pH调至8.5,在超声功率100 W,超声频率28 Hz的条件下,尾矿中SiO2提取率达到98.0%,产物中SiO2含量为98.40%,平均粒度为18 nm,得到的产品符合国家标准。