An integrated model chain for future flood risk prediction under land-use changes.
暂无分享,去创建一个
Yangbo Chen | Yu Gu | J. Xiong | Jun Liu | Huaizhang Sun | Xueqiang Zhao | Fengmiao Tu
[1] Yu Chen. Flood hazard zone mapping incorporating geographic information system (GIS) and multi-criteria analysis (MCA) techniques , 2022, Journal of Hydrology.
[2] Zhongliang Cai,et al. A Population Spatialization Model at the Building Scale Using Random Forest , 2022, Remote. Sens..
[3] Jinyao Lin,et al. Predicting future urban waterlogging-prone areas by coupling the maximum entropy and FLUS model , 2022, Sustainable Cities and Society.
[4] Fei Fu,et al. Research on the Spatiotemporal Evolution of Land Use Landscape Pattern in a County Area Based on CA-Markov Model , 2022, Sustainable Cities and Society.
[5] Nan Wang,et al. Dynamic Assessment of the Flood Risk at Basin Scale under Simulation of Land-Use Scenarios and Spatialization Technology of Factor , 2021, Water.
[6] Zhifeng Yang,et al. Dynamic simulation of coastal wetlands for Guangdong-Hong Kong-Macao Greater Bay area based on multi-temporal Landsat images and FLUS model , 2021 .
[7] Zhifeng Liu,et al. Evaluating the Impacts of Future Urban Expansion on Surface Runoff in an Alpine Basin by Coupling the LUSD-Urban and SCS-CN Models , 2020, Water.
[8] Jim W. Hall,et al. The effects of changing land use and flood hazard on poverty in coastal Bangladesh , 2020 .
[9] D. Bui,et al. Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran , 2020 .
[10] H. Moradi,et al. Using machine learning models, remote sensing, and GIS to investigate the effects of changing climates and land uses on flood probability , 2020 .
[11] P. Tarolli,et al. Identifying dominant factors of waterlogging events in metropolitan coastal cities: The case study of Guangzhou, China. , 2020, Journal of environmental management.
[12] Zhaoli Wang,et al. Scenario-based flood risk assessment for urbanizing deltas using future land-use simulation (FLUS): Guangzhou Metropolitan Area as a case study. , 2020, The Science of the total environment.
[13] Xiaohong Chen,et al. Flood Risk Assessment and Regionalization from Past and Future Perspectives at Basin Scale , 2020, Risk analysis : an official publication of the Society for Risk Analysis.
[14] Rui Zhang,et al. China’s population spatialization based on three machine learning models , 2020 .
[15] Jean-Michel Guldmann,et al. Carbon Dynamics in the Northeastern Qinghai-Tibetan Plateau from 1990 to 2030 Using Landsat Land Use/Cover Change Data , 2020, Remote. Sens..
[16] Longqian Chen,et al. Spatiotemporal Dynamics of Ecosystem Service Value Determined by Land-Use Changes in the Urbanization of Anhui Province, China , 2019, International journal of environmental research and public health.
[17] Romulus Costache,et al. Spatial prediction of flood potential using new ensembles of bivariate statistics and artificial intelligence: A case study at the Putna river catchment of Romania. , 2019, The Science of the total environment.
[18] Shanlin Yang,et al. Land use efficiency and influencing factors of urban agglomerations in China , 2019, Land Use Policy.
[19] A. Petroselli,et al. Flood inundation mapping in small and ungauged basins: sensitivity analysis using the EBA4SUB and HEC-RAS modeling approach , 2019, Hydrology Research.
[20] Yangbo Chen,et al. Risk Assessment of Flood Disaster Induced by Typhoon Rainstorms in Guangdong Province, China , 2019, Sustainability.
[21] Simon D. Jones,et al. Identifying the essential flood conditioning factors for flood prone area mapping using machine learning techniques , 2019, CATENA.
[22] Juan Du,et al. Different Flooding Behaviors Due to Varied Urbanization Levels within River Basin: A Case Study from the Xiang River Basin, China , 2018, International Journal of Disaster Risk Science.
[23] Zaijian Yuan,et al. Urban stormwater management based on an analysis of climate change: A case study of the Hebei and Guangdong provinces , 2018, Landscape and Urban Planning.
[24] H. Shahabi,et al. Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping. , 2018, Journal of environmental management.
[25] Ewa Grabska,et al. Impact of forecasted land use changes on flood risk in the Polish Carpathians , 2018, Natural Hazards.
[26] Futao Wang,et al. Mapping population density in China between 1990 and 2010 using remote sensing , 2018, Remote Sensing of Environment.
[27] B. Pham,et al. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. , 2018, The Science of the total environment.
[28] Chao Ma,et al. Integrated flood vulnerability assessment approach based on TOPSIS and Shannon entropy methods , 2018, Ecological Indicators.
[29] B. Jongman. Effective adaptation to rising flood risk , 2018, Nature Communications.
[30] Hui Lin,et al. Land use projections in China under global socioeconomic and emission scenarios: Utilizing a scenario-based land-use change assessment framework , 2018 .
[31] Andreas Paul Zischg,et al. From global circulation to local flood loss: Coupling models across the scales. , 2018, The Science of the total environment.
[32] Xiaoping Liu,et al. A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects , 2017 .
[33] Fawen Li,et al. Evolvement rules of basin flood risk under low-carbon mode. Part II: risk assessment of flood disaster under different land use patterns in the Haihe basin , 2017, Environmental Monitoring and Assessment.
[34] Lujin Hu,et al. Adaptive Multi-Scale Population Spatialization Model Constrained by Multiple Factors: A Case Study of Russia , 2017 .
[35] Ana Deletic,et al. Assessment of Urban Pluvial Flood Risk and Efficiency of Adaptation Options Through Simulations – A New Generation of Urban Planning Tools , 2017 .
[36] M. Bakker,et al. Future bottlenecks in international river basins: where transboundary institutions, population growth and hydrological variability intersect , 2017 .
[37] Woonsup Choi,et al. Impacts of climate change and urban growth on the streamflow of the Milwaukee River (Wisconsin, USA) , 2017, Regional Environmental Change.
[38] Wei Chen,et al. Using fuzzy analytic hierarchy process for spatio-temporal analysis of eco-environmental vulnerability change during 1990–2010 in Sanjiangyuan region, China , 2017 .
[39] L. Feyen,et al. Global projections of river flood risk in a warmer world , 2017 .
[40] Bing Yang,et al. Flood risk zoning using a rule mining based on ant colony algorithm , 2016 .
[41] N. Arnell,et al. The impacts of climate change on river flood risk at the global scale , 2016, Climatic Change.
[42] Wenxin Zhang,et al. The prediction of interregional land use differences in Beijing: a Markov model , 2015, Environmental Earth Sciences.
[43] A. Thieken,et al. Estimating changes in flood risks and benefits of non-structural adaptation strategies - a case study from Tyrol, Austria , 2014, Mitigation and Adaptation Strategies for Global Change.
[44] Zhiji Huang,et al. Land use change and economic growth in urban China: A structural equation analysis , 2014 .
[45] Maurizio Mazzoleni,et al. Flooding hazard mapping in floodplain areas affected by piping breaches in the Po River, Italy , 2014 .
[46] Stefan Hochrainer-Stigler,et al. Increasing stress on disaster-risk finance due to large floods , 2014 .
[47] Philip B. Bedient,et al. Modeling Hydrologic Benefits of Low Impact Development: A Distributed Hydrologic Model of The Woodlands, Texas , 2013 .
[48] R. Nicholls,et al. Future flood losses in major coastal cities , 2013 .
[49] Verena Rieser,et al. Agent-based modelling of land use dynamics and residential quality of life for future scenarios , 2013, Environ. Model. Softw..
[50] P. Roy,et al. Modelling and analyzing the watershed dynamics using Cellular Automata (CA)–Markov model – A geo-information based approach , 2012, Journal of Earth System Science.
[51] N. Sriwongsitanon,et al. Effects of land cover on runoff coefficient , 2011 .
[52] J. Barredo. Normalised flood losses in Europe: 1970-2006 , 2009 .
[53] B. Pham,et al. Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam , 2021, Journal of Hydrology.
[54] Samuel D. Brody,et al. Characterizing urbanization impacts on floodplain through integrated land use, hydrologic, and hydraulic modeling , 2019, Journal of Hydrology.
[55] Diana Mitsova-Boneva,et al. Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio , 2014, ISPRS Int. J. Geo Inf..
[56] A. Wypych,et al. Spatial modeling of the climatic water balance index using GIS methods , 2014 .
[57] Zhang Jian-yun. The vital problems for the urbanization and urban hydrology today , 2012 .