An ensemble approach for the analysis of extreme rainfall under climate change in Naples (Italy)

In the present paper, an ensemble approach is proposed to estimate possible modifications caused by climate changes in the extreme precipitation regime, with the rain gauge Napoli Servizio Idrografico (Naples, Italy) chosen as test case. The proposed research, focused on the analysis of extremes on the basis of climate model simulations and rainfall observations, is structured in several consecutive steps. In the first step, all the dynamically downscaled EURO‐CORDEX simulations at about 12 km horizontal resolution are collected for the current period 1971–2000 and the future period 2071–2100, for the RCP4.5 and the RCP8.5 concentration scenarios. In the second step, the significance of climate change effects on extreme precipitation is statistically tested by comparing current and future simulated data and bias‐correction is performed by means of a novel approach based on a combination of simple delta change and quantile delta mapping, in compliance with the storm index method. In the third step, two different ensemble models are proposed, accounting for the variabilities given by the use of different climate models and for their hindcast performances. Finally, the ensemble models are used to build novel intensity–duration–frequency curves, and their effects on the early warning system thresholds for the area of interest are evaluated.     

Assessing basin storage: Comparison of hydrometric- and tracer-based indices of dynamic and total storage

Storage is a fundamental but elusive component of drainage basin function, influencing synchronization between precipitation input and streamflow output and mediating basin sensitivity to climate and land use/land cover (LULC) change. We compare hydrometric and isotopic approaches to estimate indices of dynamic and total basin storage, respectively, and assess inter-basin differences in these indices across the Oak Ridges Moraine (ORM) region of southern Ontario, Canada. Dynamic storage indices for the 20 study basins included the ratio of baseflow to total streamflow (baseflow index BFI), Q ₉₉ flow and flow duration curve (FDC) slope. Ratios of the standard deviation of the streamflow stable isotope signal relative to that of precipitation were determined for each basin from a 1 year bi-weekly sampling program and used as indicators of total storage. Smaller ratios imply longer water travel times, smaller young water fractions (F _yw, < ~2–3 months in age) in streamflow and greater basin storage. Ratios were inversely related to BFI and Q ₉₉, and positively related to FDC slope, suggesting longer travel times and smaller F _yw for basins with stable baseflow-dominated streamflow regimes. Inter-basin differences in all indices reflected topographic, hydrogeologic and LULC controls on storage, which was greatest in steep, forest-covered headwaters underlain by permeable deposits with thick and relatively uniform unsaturated zones. Nevertheless, differential sensitivity of indices to controls on storage indicates the value of using several indices to capture more completely how basin characteristics influence storage. Regression relationships between storage indices and basin characteristics provided reasonable predictions of aspects of the streamflow regime of test basins in the ORM region. Such relationships and the underlying knowledge of controls on basin storage in this landscape provide the foundation for initial predictions of relative differences in streamflow response to regional changes in climate and LULC.     

Prediction of vegetation anomalies over an inland river basin in north‐western China

Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.     

吉林省村域尺度下居民点空间分布特征及优化重组模式

乡村聚落的空间优化与重构是提高土地资源利用效率,改善农村生产生活条件,促进乡村可持续发展的重要手段。以吉林省为例,采用核密度估计方法和景观形状指数分析了农村居民点空间分布特征,基于农户调查数据估算了吉林省不同区域的农村宅基地闲置情况,将农村居民点长期存在的“破碎化”和日益突出的“空心化”相结合,提出了在行政村尺度下农村居民点优化重组的“整小填大”新模式。结果表明：① 吉林省农村居民点规模小且零散分布,尤其中部呈破碎化分布,形态不规则,具有较大的整治潜力;② 吉林省农村宅基地平均闲置率为18.32%,西部地区最高（24.48%）,分别高于东部和中部地区约6%和12%;③“整小填大”模式可使农村居民点数量减少44.6%,增加有效耕地面积1 046.66 km²。     

Unraveling the multi-scalar residential segregation and socio-spatial differentiation in China: A comparative study based on Nanjing and Hangzhou

Residential segregation is a dual process of socio-spatial differentiation in residents and spatio-temporal heterogeneity in dwelling.However,most of the existing studies are es-tablished from the single perspective of urban residents based on demographic data,which is difficult to reveal the dynamics and complex spatial reconstruction within and between cities.With the characteristics of both stability and timeliness,the rapidly changing housing market is one of the processes and results of socio-spatial reconfiguration,and it is undoubtedly a better lens to observe residential segregation.This paper adopts methods such as multi-group segregation index,multi-scalar segregation profiles,and decomposition of segregation index,with Nanjing and Hangzhou as case cities,and establishes multi-scalar segregation profiles and comparative models based on three geographical scales of census tract,block and grid,and different residential types.A quantitative study was conducted on the degree and pattern of multi-scalar residential segregation in Nanjing and Hangzhou from 2009 to 2018.The pa-per found that the spatial segregation index is an improvement of the non-spatial segregation index.There are differences between Nanjing and Hangzhou in the evolution process of residential segregation.Nanjing has a higher degree of spatial differentiation as a whole,among which spatial components have a more significant impact.     

2001—2020年黄河流域植被覆盖变化及其影响因素

基于MODIS NDVI植被指数和气象数据集,以集合经验模态分解、趋势分析和随机森林回归分析等方法,分析了黄河流域2001—2020年植被覆盖时空变化特征,并对其气候驱动因素进行探讨。结果表明：（1）2001—2020年黄河流域植被覆盖整体呈显著增长趋势,增速为0.055/10a （P<0.05）,2010年之前增速（0.067/10a）大于2010年之后的增速（0.051/10a）。（2）空间上,植被覆盖增加区域主要分布在陕北黄土高原、甘肃省东南部、内蒙古自治区河套平原等退耕还林还草生态工程实施区域,而植被覆盖显著下降区域则集中在关中平原城市群、黄淮海平原以及青藏高原等区域。（3）气温、降水和CO₂浓度等对黄河流域植被生长起到正向促进作用,且绝对敏感性依次降低,而大气饱和水汽压差、太阳辐射等对植被生长起到抑制作用。本研究结果可为评估气候变化对黄河流域植被覆盖变化的综合影响提供参考依据。     

多源数据融合的城市体检评估

融合遥感影像、社会开放大数据、统计资料等多源数据,以长沙市为例,围绕生态宜居、健康舒适、安全韧性、交通便捷、风貌特色、整洁有序、多元包容、创新活力等8个方面构建城市体检指标体系,运用归一法和层次分析法对城市自然本底和运行体征展开计算评估,结果发现：1）长沙市人居环境整体良好,城市生态宜居和整洁有序度较高,交通便捷和安全韧性建设亟需加强,风貌特色、健康舒适、创新活力、多元包容等仍有改善空间。2）各区县专题发展水平不均,在保留区域功能特色的基础上,应该着重解决发展的短板。3）城市中心城区人口密度、空气质量优良天数、万车死亡率等指标达到最高水平,但在便民服务设施完整覆盖度、住宅建筑更新和开发、群体包容等方面与城市发展需求还有一定差距。根据多源数据城市体检结果可知,长沙市未来需要以问题和需求为导向,精准治理“城市病”,努力提高城市居民生活满意度、幸福感和归属感。     

人居环境气候舒适度对城市创新的影响分析

以中国创新水平较高的91个地级及以上城市为研究对象,探讨人居环境气候舒适度对城市创新的影响程度。以城市发明专利申请数代表城市创新水平,采用温湿指数和风效指数的组合模型,参照相应的分级标准计算各城市年气候舒适期,分析城市人居环境气候舒适度与城市创新的关系。结果表明:气候舒适期每增加1%,发明专利申请数仅平均增加0.012%,相对于GDP、R&D人员全时当量、R&D经费等影响城市创新的关键因素,城市人居环境气候舒适度对城市创新有一定影响,但影响并不十分显著。因此,创新政策的着眼点在于关注城市创新投入、人力资本、经济规模等影响城市创新的关键因素。在此基础上,创新布局也应考虑人居环境气候舒适度因素。     

基于因子分析和聚类分析的公众雾霾敏感度差异研究 ——以西安市为例

为研究公众的雾霾敏感度,以西安市13个区为案例地,运用因子分析法对公众的敏感度进行降维,引入潜在冲突指数(PCI)分析公众雾霾敏感度各维度的内部差异,并对公众进行分类。结果表明:(1)公众的雾霾敏感度可分为5个维度,分别是防护行为、降霾行为、雾霾关注度、生活影响感知和健康影响感知;(2)公众在防护行为、降霾行为、生活影响感知和健康影响感知方面意见一致,且敏感度较高;在雾霾关注度方面,公众之间的分歧较大,雾霾关注度小的公众敏感度较低;(3)基于以上5个维度,将公众分为防护敏感群体、关注度敏感群体、健康敏感群体和环保敏感群体。     

基于相关分析和自适应遗传算法的盐渍化建模变量和参数优选

机器学习结合遥感等其他数据反演土壤盐分含量（Soil Salt Content, SSC）较少关注对模型精度影响较大的建模特征变量和模型参数的优选。本文基于自适应遗传算法（Adaptive Genetic Algorithm, AGA）同步优选建模特征变量和模型参数的支持向量回归（Support Vector Regression, SVR）算法反演三工河流域2016年SSC,并分析其在不同土地利用类型的分布特征。建模特征变量和模型参数的同步优选及实验设计如下：首先基于Landsat 8 OLI和SRTM高程数据提取7类共40个盐渍化相关因子,经相关分析初步筛选出候选特征变量,分别代入AGA、遗传算法（Genetic Algorithm, GA）和格网搜索算法（Grid Search, GS）同步优选SVR的建模特征变量和模型参数,并建立盐渍化监测模型（AGA-SVR、GA-SVR、GS-SVR）。结果表明：① AGA-SVR精度最优,GA-SVR次之,GS-SVR最差,相较于GS-SVR,AGA-SVR的R²/RMSE提高了44.65%;② 三工河流域非、轻度、中度、重度盐渍地和盐土的面积占比分别为42.83%、11.02%、15.88%、9.22%、21.05%;③ 草地和未利用地主要以非盐渍地和盐土为主,耕地和林地中非盐渍地分布比例均为最大;不同土地利用类型的SSC均值和标准差均呈现未利用地>草地>耕地>林地的规律。本研究的建模特征变量和模型参数的优选方法可在一定程度上提高盐渍化监测的精度。关键词：盐渍化;遗传算法;机器学习;特征优选;参数优化;土壤盐分含量;土地利用;相关分析