<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are an expert on climate change, human mobility and migration. Answer the question truthfully.<|eot_id|><|start_header_id|>user<|end_header_id|>Here are the title and abstract of a scientific paper probably related to climate change, human mobility and migration..
Title:"A novel spatiotemporal multi-attribute method for assessing flood risks in urban spaces under climate change and demographic scenarios."
Abstract:"The combined effects of global warming and population growth induce policymakers to enhance flood risk management practices in order to reduce substantially the causes of floods and to mitigate their future and multiple impacts simultaneously. This way, this paper puts forward a new multi-attribute and non-stationary decision model for managing flood risks in urban areas under climate demographic changes, which we call the Non-Stationary Multi-Attribute Utility Theory (NSMAUT). Under expected utilities, our model inserts time dependency into the decision-maker's (DM's) preference statements based on his/her trade-offs regarding psychological distance induced by delayed prospects. The NSMAUT analyzes flood risks under five attributes, linked to environmental, financial, human, mobility, and social concerns of society. By combining climate and demographic scenarios for this century, our findings make use of statistical, graphic, and risk performance measures that increase the DM's perception of risk in order to control and monitor the dynamism of circumstances of risk and thus to facilitate on what he/she should base future decisions on adapting cities for future adverse events arising from flooding. A numerical application in a Brazilian municipality from 2021 - 2100 is used to validate our approach. Moreover, the model can be replicated in other urban contexts.."
I have six questions you need to answer.
Q1: Is this article is about 'human migration mobility': 1 = yes; 0 = no. Answer with a number. Do not give a textual explanation.

Q2: What drivers of migration and mobility does the article study? 0 = 'other', 1 = 'climate', 2 = 'environment', 3 = 'economic', 4 = 'conflict', 5 = 'political', 6 = 'social', 7 = 'family'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q3: What is the overall sentiment of the article?:0 = 'neutral', 1 = 'negative', 2 = 'positive'. Answer with a number. Do not give a textual explanation.

Q4: What type of climate or environmental keywords are explicitly mentioned?:  0 = 'none', 1 = 'algal blooms', 2 = 'infestation', 3 = 'infectious diseases', 4 = 'ocean acidification', 5 = 'sea ice', 6 = 'acid rain', 7 = 'drought', 8 = 'cold wave', 9 = 'heat wave', 10 = 'glacial', 11 = 'wildfire', 12 = 'air pollution', 13 = 'biodiversity loss', 14 = 'coastal erosion', 15 = 'land degradation', 16 = 'deforestation', 17 = 'desertification', 18 = 'water pollution', 19 = 'diebacks', 20 = 'permafrost loss', 21 = 'sand mining', 22 = 'sea level rise', 23 = 'earthquake', 24 = 'tsunami', 25 = 'volcanic', 26 = 'flood', 27 = 'avalanche', 28 = 'landslide', 29 = 'downburst', 30 = 'thunderstorm', 31 = 'sandstorm', 32 = 'haze', 33 = 'storm', 34 = 'cyclone', 35 = 'blizzard', 36 = 'hail', 37 = 'snow', 38 = 'tornado', 39 = 'wind', 40 = 'hurricane', 41 = 'typhoon', 42 = 'other'. Answer with a number or a sequence of numbers separated by commas. Do not give a textual explanation. 

Q5: What discipline does the article belong to?: 0 = 'other', 1 = 'social science', 2 = 'natural science', 3 = 'arts and humanities', 4 = 'multidiscipline and interdiscipline'. Answer with a number. Do not give a textual explanation.

Q6: Does the article apply quantitative and/or statistical analysis?: 0 = 'no', 1 = 'yes'. Answer with a number. Do not give a textual explanation.

Use the following template: 

Q1 = [];
Q2 = [];
Q3 = [];
Q4 = [];
Q5 = [];
Q6 = [].<|eot_id|><|start_header_id|>assistant<|end_header_id|>Answer:
Q1 = [1];
Q2 = [1,2];
Q3 = [2];
Q4 = [26];
Q5 = [];
Q6 = [1].
A novel spatiotemporal multi-attribute method for assessing flood risks in urban spaces under climate change and demographic scenarios
The combined effects of global warming and population growth induce policymakers to enhance flood risk management practices in order to reduce substantially the causes of floods and to mitigate their future and multiple impacts simultaneously. This way, this paper puts forward a new multi-attribute and non-stationary decision model for managing flood risks in urban areas under climate demographic changes, which we call the Non-Stationary Multi-Attribute Utility Theory (NSMAUT). Under expected utilities, our model inserts time dependency into the decision-maker's (DM's) preference statements based on his/her trade-offs regarding psychological distance induced by delayed prospects. The NSMAUT analyzes flood risks under five attributes, linked to environmental, financial, human, mobility, and social concerns of society. By combining climate and demographic scenarios for this century, our findings make use of statistical, graphic, and risk performance measures that increase the DM's perception of risk in order to control and monitor the dynamism of circumstances of risk and thus to facilitate on what he/she should base future decisions on adapting cities for future adverse events arising from flooding. A numerical application in a Brazilian municipality from 2021 - 2100 is used to validate our approach. Moreover, the model can be replicated in other urban contexts.