Future changes in urban drainage pressure caused by precipitation extremes in 285 cities across China based on CMIP6 models

High pressure on urban drainage systems caused by extreme precipitation events would lead to an increase risk of urban floods. Across China, future changes in urban drainage pressure (UDP) and its response to global-scale climate mitigation and local adaptation, have seldom been studied. Here, based on climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we assessed UDP changes from 2020 to 2099 under different scenarios in 285 cities across China. Under the shared socioeconomic pathway (SSP) 5–8.5 scenario, 30% larger increase of UDP relative to the baseline level (1985–2014), would occur in 22.80% and 79.65% cities over 2020–2049 and 2050–2099, respectively. Under climate mitigation (SSP2–4.5 scenario), UDP in northern China would decrease by 10–30% over 2020–2049. On this basis, 10% enhancement of underlying surface retention capacity (LID10% scenario) would reduce UDP by more than 10% particularly in northern and northeastern China (23.51% cities). Pipe enlargement adaptation (Pipe10% scenario) would benefit UDP mainly in eastern China (46.31% cities), by postponing the first decade with 30% larger pressure relative to the baseline level by 1-3 decades.</p

Analysis of geothermal potential in Hangjiahu area based on remote sensing and geographic information system

Geothermal resources are one of the most valuable renewable energy sources because of their stability, reliability, cleanliness, safety and abundant reserves. Efficient and economical remote sensing and GIS (Geographic Information System) technology has high practical value in geothermal resources exploration. However, different study areas have different geothermal formation mechanisms. In the process of establishing the model, which factors are used for modeling and how to quantify the factors reasonably are still problems to be analyzed and studied. Taking Hangjiahu Plain of Zhejiang Province as an example, based on geothermal exploration and remote sensing interpretation data, the correlation between the existing geothermal hot spots and geothermal related factors was evaluated in this paper, such as lithology, fault zone distance, surface water system and its distance, seismic point distance, magmatic rock and volcanic rock distance, surface water, farmland, woodland temperature and so on. The relationship between geothermal potential and distribution characteristics of surface thermal environment, fault activity, surface water system and other factors was explored. AHP (Analytic Hierarchy Process) and BP (Back Propagation) neural network were used for establishing geothermal potential target evaluation models. The potential geothermal areas of Hangjiahu Plain were divided into five grades using geothermal exploration model, and most geothermal drilling sites were distributed in extremely high potential areas and high potential areas. The results show that it is feasible to analyze geothermal potential targets using remote sensing interpretation data and geographic information system analysis databased on analytic hierarchy process analytic hierarchy process and back propagation neural network, and the distribution characteristics of surface thermal environment, fault activity, surface water system and other related factors are also related to geothermal distribution. The prediction results of the model coincide with the existing geothermal drilling sites, which provides a new idea for geothermal exploration

The Impact of Hurricane Maria on the Vegetation of Dominica and Puerto Rico Using Multispectral Remote Sensing

As the worst natural disaster on record in Dominica and Puerto Rico, Hurricane Maria in September 2017 had a large impact on the vegetation of these islands. In this paper, multitemporal Landsat 8 OLI and Sentinel-2 data are used to investigate vegetation damage on Dominica and Puerto Rico by Hurricane Maria, and related influencing factors are analyzed. Moreover, the changes in the normalized difference vegetation index (NDVI) in the year 2017 are compared to reference years (2015 and 2016). The results show that (1) there is a sudden drop in NDVI values after Hurricane Maria’s landfall (decreased about 0.2) which returns to near normal vegetation after 1.5 months; (2) different land cover types have different sensitivities to Hurricane Maria, whereby forest is the most sensitive type, then followed by wetland, built-up, and natural grassland; and (3) for Puerto Rico, the vegetation damage is highly correlated with distance from the storm center and elevation. For Dominica, where the whole island is within Hurricane Maria’s radius of maximum wind, the vegetation damage has no obvious relationship to elevation or distance. The study provides insight into the sensitivity and recovery of vegetation after a major land-falling hurricane, and may lead to improved vegetation protection strategies

Effects of Land Use on Stream Water Quality in the Rapidly Urbanized Areas: A Multiscale Analysis

The land use and land cover changes in rapidly urbanized regions is one of the main causes of water quality deterioration. However, due to the heterogeneity of urban land use patterns and spatial scale effects, a clear understanding of the relationships between land use and water quality remains elusive. The primary purpose of this study is to investigate the effects of land use on water quality across multi scales in a rapidly urbanized region in Hangzhou City, China. The results showed that the response characteristics of stream water quality to land use were spatial scale-dependent. The total nitrogen (TN) was more closely related with land use at the circular buffer scale, whilst stronger correlations could be found between land use and algae biomass at the riparian buffer scales. Under the circular buffer scale, the forest and urban greenspace were more influential to the TN at small buffer scales, whilst significant positive or negative correlations could be found between the TN and the areas of industrial land or the wetland and river as the buffer scales increased. The redundancy analysis (RDA) showed that more than 40% variations in water quality could be explained by the landscape metrics at all circular and riparian buffer scales, and this suggests that land use pattern was an important factor influencing water quality. The variation in water quality explained by landscape metrics increased with the increase of buffer size, and this implies that land use pattern could have a closer correlation with water quality at larger spatial scales

Urban flood susceptibility mapping based on social media data in Chengdu city, China

Increase in urban flood hazards has become a major threat to cities, causing considerable losses of life and in the economy. To improve pre-disaster strategies and to mitigate potential losses, it is important to make urban flood susceptibility assessments and to carry out spatiotemporal analyses. In this study, we used standard deviation ellipse (SDE) to analyze the spatial pattern of urban floods and find the area of interest (AOI) based upon related social media data that were collected in Chengdu city, China. We used the social media data as the response variable and selected 10 urban flood-influencing factors as independent variables. We estimated the susceptibility model using the Naïve Bayes (NB) method. The results show that the urban flood events are concentrated in the northeast-central part of Chengdu city, especially around the city center. Results of the susceptibility model were checked by the Receiver Operating Characteristic (ROC) curve, showing that the area under the curve (AUC) was equal to 0.8299. This validation result confirmed that the susceptibility model can predict urban flood with a satisfactory accuracy. The urban flood susceptibility map in the city center area provides a realistic reference for flood monitoring and early warning

Numerical Simulation of the Diurnal Cycle of a Precipitation System during KWAJEX by 2D and 3D Cloud-Resolving Models

Two-dimensional (2D) and three-dimensional (3D) cloud-resolving model (CRM) results from the Tropical Rainfall Measuring Mission Kwajalein Experiment (KWAJEX) were applied to analyze the diurnal cycle of cloud development in the tropics. Cloud development is intimately associated with the growth of secondary circulation, which can be analyzed in the budget of perturbation kinetic energy (PKE). The ice and liquid water path (IWP+LWP) is a fundamental parameter for estimating clouds, with the analyzed results suggesting that (1) the ice and liquid water path (IWP+LWP) and PKE values attained in convective regions were higher during the nighttime than during the daytime and that the maxima of IWP+LWP and PKE occurred at midnight in the lower troposphere in the 3D model run, and that (2) the IWP+LWP and PKE values in stratiform regions were much higher in the afternoon than in the morning, while the maxima of IWP+LWP and PKE occurred in the afternoon in the middle troposphere in the 2D model run. Further analysis demonstrated that both the high IWP+LWP and PKE values in the lower troposphere at midnight were mainly associated with the warm–humid lower troposphere in convective regions. However, those in the middle troposphere in the afternoon were primarily linked to the dry–cold upper troposphere and moist–warm lower troposphere in stratiform regions. The results further revealed that (1) both IWP+LWP and PKE exhibited shorter time scales in the 2D model runs than in the 3D model runs and that (2) the maximum IWP+LWP values occurred in the afternoon in the 2D model runs and at midnight in the 3D model runs

Retrieval of Sea Surface Wind Fields Using Multi-Source Remote Sensing Data

Timely and accurate sea surface wind field (SSWF) information plays an important role in marine environmental monitoring, weather forecasting, and other atmospheric science studies. In this study, a piecewise linear model is proposed to retrieve SSWF information based on the combination of two different satellite sensors (a microwave scatterometer and an infrared scanning radiometer). First, the time series wind speed dataset, extracted from the HY-2A satellite, and the brightness temperature dataset, extracted from the FY-2E satellite, were matched. The piecewise linear regression model with the highest R2 was then selected as the best model to retrieve SSWF information. Finally, experiments were conducted with the Usagi, Fitow, and Nari typhoons in 2013 to evaluate accuracy. The results show that: (1) the piecewise linear model is successfully established for all typhoons with high R2 (greater than 0.61); (2) for all three cases, the root mean square error () and mean bias error (MBE) are smaller than 2.2 m/s and 1.82 m/s, which indicates that it is suitable and reliable for SSWF information retrieval; and (3) it solves the problem of the low temporal resolution of HY-2A data (12 h), and inherits the high temporal resolution of the FY-2E data (0.5 h). It can provide reliable and high temporal SSWF products

Unveiling spatiotemporal dynamics and factors influencing the provision of urban wetland ecosystem services using high-resolution images

Although extensive studies have investigated changes in regional ecosystem services (ESs) under rapid urbanization, few analyses have used high-resolution image data to investigate urban wetlands. Taking the Xixi wetland region as a case area, this study aimed to investigate the temporal and spatial variation and influencing factors of typical ESs during 1984–2018 using high-resolution images. The results showed that the Xixi wetland region underwent substantial changes of land use as well as in different ESs. While carbon storage presented an increasing trend from 223.25 t/ha to 368.11 t/ha from 1984 to 2018, the changes of other services illustrated an overall degradation in this important urban wetland. Evident trade-off and synergy effects were observed between water yield and carbon storage and between biodiversity protection and recreation and cultural services. Redundancy analysis revealed the detrimental impacts of impervious cover on the provision of ESs in this urban wetland area. The results obtained in this study highlight the great challenges that urban wetland parks face in balancing wetland conservation and sustainable use

Future urban waterlogging simulation based on LULC forecast model: A case study in Haining City, China

As a consequence of rapid urbanization, the pattern of Land Use and Land Cover (LULC) has changed, resulting in a significant increase in the risk of waterlogging. Understanding the relationship between LULC change and urban waterlogging plays an important role in disaster mitigation and prevention. Taking Haining City as an example, the LULC prediction model (CLUMondo) was used to obtain LULC simulation results for 2030.The hydrodynamic model (InfoWorks ICM) was used to simulate future urban waterlogging. The results were as follows: 1) Between 2005 and 2030, the changes in cultivated land and construction land were predicted to be the most obvious. The area of cultivated land was predicted to decrease by 26.62 km2, and the construction land was predicted to increase by 25.17 km2. 2) The overall distribution of waterlogged areas and the identified at-risk areas in Haining were shown to be relatively scattered. In 2030, urban waterlogging is predicted to be more serious than in 2020. 3) The reasons for the predicted change in waterlogging are closely related to the transformation of LULC, especially the transformation of cultivated land to construction land. The results provide a basis for scientific research and urban planning to reduce the risk of waterlogging

Urban Inundation under Different Rainstorm Scenarios in Lin&rsquo;an City, China

Under the circumstances of global warming and rapid urbanization, damage caused by urban inundation are becoming increasingly severe, attracting the attention of both researchers and governors. The accurate simulation of urban inundation is essential for the prevention of inundation hazards. In this study, a 1D pipe network and a 2D urban inundation coupling model constructed by InfoWorks ICM was used to simulate the inundation conditions in the typical urbanized area in the north of Lin&rsquo;an. Two historical rainfall events in 2020 were utilized to verify the modeling results. The spatial&ndash;temporal variation and the causes of urban inundation under different designed rainfalls were studied. The results were as follows: (1) The constructed model had a good simulation accuracy, the Nash&ndash;Sutcliffe efficiency coefficient was higher than 0.82, R2 was higher than 0.87, and the relative error was &plusmn;20%. (2) The simulation results of different designed rainfall scenarios indicated that the maximum inundation depth and inundation extent increased with the increase in the return period, rainfall peak position coefficient, and rainfall duration. According to the analysis results, the urban inundation in Lin&rsquo;an is mainly affected by topography, drainage network (spatial distribution and pipe diameter), and rainfall patterns. The results are supposed to provide technical support and a decision-making reference for the urban management department of Lin&rsquo;an to design inundation prevention measures