Flood Risk - Science topic

You are welcome, Professor

Dear Doctor

"The science of climate change is well established:

Inhibitors generally have a negative effect, but few people take advantage of them for a new start

Other adverse effects include an increase in the frequency and intensity of tropical cyclones, for instance, Cyclone Idai and Kenneth which devastated Mozambique, Malawi, Zambia and Madagascar. Duration and intensity of heat waves are also on the increase all over Africa, especially in the Sahel region.

Greetings, Naser Dehghanian,

Indeed, flood risk mapping in urban and rural areas is feasible by integrating diverse data sources, innovative tools, and advanced techniques.

Several data sources such as topographic maps, hydrological models, rainfall data, land use and land cover data, and historical flood data can be used with remote sensing, Geographic Information Systems (GIS) and field observations to generate accurate and comprehensive flood risk maps.

Furthermore, community engagement and participation hold significant importance in flood risk mapping as local knowledge and expertise can offer valuable insights into a particular area's specific flood risks and vulnerabilities.

I recommend reviewing the literature to enhance your understanding and knowledge in this field. Numerous high-quality research papers provide insightful perspectives on urban flood risk mapping and assessment.

Please find below a selection of potential sources for your consideration:

Ali YOUNES,

Helpful to your analysis would be LiDAR coverage taken during low flow to obtain some channel morphology and as well as topographic detail. Dr. David Rosgen has developed a stream classification system that uses features as gradient, entrenchment, bankfull elevation (top of point bars that might be visible with LiDAR), braided vs non-braided channels, sinuosity, etc. The infrared aerial photos are often useful in separating upland and bottomland species if forested. The LiDAR very helpful in obtaining channel detail that is obscured by dense forest vegetation. Soil scientists familiar with mapping soil types on landscapes in your area would be helpful as they are used to reading landform, vegetation and hydrology indicators. But they too need experience and ground truthing (checking, transects, site visits, etc.).

As suggested by Dr. Klebs, securing available rainfall and stream/river data for your physiographic area(s), developing detailed DEM, classifying vegetation and channel types, Watershed sizes for areas of interest, land use practices, land cover types can also be helpful. Braided and highly sinuous streams almost always have significant flooding. Highly entrenched and high gradient streams tend to have no or narrow floodplain. If a flat area is adjacent to a stream or river, it could be floodplain, unless the channel is deeply entrenched, then it is likely a terrace (abandoned floodplain). Braided streams are typically a result of excess sediment loading, which fills channel capacity and aggrades channel, resulting in more frequent flooding and channel instability.

Due to the potential for land valuation and regulation, as well as human hazards, it may be best to have licensed engineer and appropriate agency review and approval before publishing results that potentially could have legal or human ramifications. If not, perhaps publishing as guideline or remote estimates needing field checking and verification would help limit liability for misinterpretation. Without LiDAR, there are certainly things one can obtain from aerial photos and photo pair interpretation, such as landform, vegetation type and some channel indicators perhaps. Soil maps if available typically separate out flood prone and hydric soils that would be useful information.

Respected Fatema Miah,

It is good to write on such important issues. Also keep an eye on your own country. If you want to write on Pakistan, you must read about Pakistan. And the most important, a writer must think positively and highlight positive aspects of an event and development.

I think that it is important that "residual flood risk" and "flood risk" are recognised as separate terms. Although they are both conceptually calculated using the same equation i.e. flood risk = probability of flood occurring x consequences, the processes used for estimating residual flood risk are different from calculating flood risk. Residual flood risk is not necessarily the same thing as "flood risk" and the term residual flood risk does add value because it takes into account all the ways in which flood defences can fail which a simple calculation of "flood risk" may not.

These paper will hopefully explain a bit more as to why residual flood risk is important as a concept:

Identifying the bioclimatic regime of the areas under threat to fires is one of the foremost requirements for an efficient forest fire management strategy. These days Google Earth Engine provides one of the fastest ways to prioritize vulnerable areas within the forests. Janaki Sandamali William F. Hansen and others have provided useful information regarding it.

Excellent! Thanks very much for contributing Christian.

Hello, I have the same problem with HEC RAS ​​V6.0.0; Beta 6.0 did not have the problem but final version 6.0.0 has a lot of bugs. it looks like Ras Mapper is not related to HEC RAS ​​that means if you create your geometry on ras mapper and set your boundary condition HEC RAS ​​cannot detect them. even if you restart HEC RAS, they will disappear. Hope they will fix this problem as soon as possible .

Hasret Sahin - thank you for the clarification. It wasn't really clear from the instructions - some surveys highlight items that need to be filled in yet. I did see that the survey had been around for a while, so I won't argue with the intent. I do think that more information can often be gleaned when comparable questions indicate a possible misunderstanding or conflict in a respondent's answers than 'guiding' them to make changes. But, I'll leave it there.

Salim M. Zaki Thanks for the recommendation. I'll explore it

Wish you good health

Dear Amin Sadeqi

I found the good reference for your problems:

Jonas Bhend,* Irina Mahlstein and Mark A. Liniger

Thank you.

look for NASA aqua and terra

Dear Mr. Lumbroso - Thank you for your detailed feedback. I see that you have done substantial work in this area. After I have a chance to read this material, I may get back to the discussion.

Niklas Schwiersch , yes, guidelines like the CCPS (https://www.aiche.org/ccps) and OSHA (https://www.osha.gov/) or HSE (https://www.hse.gov.uk/pubns/ohindex.htm) define levels of risk quite explicitly. The real problem for any model (or standard) is that the ACCEPTABLE risk will necessarily be different for different people, organizations, or industries. A "Risk" (consequence vs. probability) can be defined fairly directly. BUT how that will influence a design (avoidance, prevention, mitigation, costs) remains a management decision. ONCE a decision has been made relative to risk acceptance, many standards exist to define how to meet the desired criteria, like SIS or building codes (ANSI, ASTM, others). Sometimes, industry or government REGULATIONS may define specific standards to use, but those regulations are not "standards".

Manning's n or roughness coefficient is actually a measure of energy or head loss along a channel reach. The roughness of the channel, bank and floodplain is a major determinant of Manning's n. However, all mechanisms that contribute to energy loss should be considered in selecting its proper value. For example, flow velocity and associated turbulence are important (e.g., if velocity is near zero, the Manning's n will be zero even when the river has high roughness). Similarly flow depth is important. So is the season (e.g., more vegetation and thus higher roughness in summer).

I think engineers should think of Manning's n as more related to energy loss under specific flow conditions than to only roughness.

I suggested you these papers, see the link below :

I Hope that this Can help you ...

Sincerely,

GWR is a good method to take into account heterogeneity at the local level. I have used GWR quite a bit since it provides local regression coefficients. Try Geoda program also developed by Prof Anselin.

Highland is an area of elevation as against low plains or lowland. They are not necessarily flood plains. Its surface (topsoil) or subsurface soil may have high infiltration tendency that is, low runoff coefficient which may reduce flood risk. It may as well consist impermeable (mountainous) surface with large runoff coefficient which will increase flood risk as well. Basically runoff coefficient factor is essential as it relates the amount of runoff to the amount of precipitation received. However, with topographical variation either with steep or gentle gradient the low plains will be susceptible to flooding if adequate storm water channels are not implemented.

Hence, conduct flood risk assessment as suggested by Bayan Hussien and then classify your study area. Source for contour map or generate a topo survey using GIS software.

Consider whether you might decompose your sea-level data to separate the "shorter-term surge" (with hourly/daily type timescales), the tides (perhaps from predictions?), and the seasonal and longer-term sea-level changes. If that makes sense in your site, then you could model the relation of the 'shorter-term surge' on rainfall with a copula, free from issues of long-term sea-level rise. Then for applications you could combine the joint statistics of rainfall/short-term-surge with a longer-term sea-level rise component.

I appreciate the request to comment, Rmm, but I don't think I know enough about your particular problem domain.

That's the thing about applying weights to survey respondents - making responses from one person, or a group of people, more important than those of another. You would do this if you have a legitimate reason to think that one group is severely under-represented in your sampling frame, or in your final sample. Or if you have a theoretical reason for giving greater value to the responses of some, and lesser value to others.

You need to have a theory, and/or good evidence, to support the use of weights in the first place and some ideas about how much those weights should apply.

Thinking about it some more, the purpose of your research is likely to be important too. If you're interested only in the value of real estate affected by floods then your weights may apply to the value associated with the people/organisations you survey. If you are interested in the effects on people's homes then you may minimise commercial real estate and apply weights based on the sizes of families.

It is India-WRIS: http://indiawris.gov.in/wris/#/DataDownload

They have updated website, from where you can download data year-wise.

Hi Sina

My response is based on experience. But, I have googled and found the following for you:

Best regards

Ravi

https://www.brisbane.qld.gov.au/planning-and-building/planning-guidelines-and-tools/brisbane-city-plan-2014/fact-sheets/flood-planning-provisions

http://www.charim.net/use/322

Construction of dykes is a straightforward solution. However, other than the cost, there are some problems associated with dykes. What will happen when the designed flood level (return period) is exceeded. We are maintaining a scheme with 10-yr protection and the dykes were over-topped several times. In each time, we had to cut open the dykes since evacuation (by pumping or gravity outlets) takes more time. Further, it is not suitable for tropical countries where the volume of water to be pumped is high and the cost is unbearable. There are many alternative methods for flood protection. Each method has its advantages and drawbacks. Selection of most appropriate method lies in the hands of experts. It is true that, there are occasions where 'nothing' is better than halfway solutions.

https://www.bristol.ac.uk/media-library/sites/geography/migrated/documents/lisflood-manual-v5.9.6.pdf

The causes of flooding, relative environmental impacts, root causes and corrective measures are likely to vary among nations. However, it is important to identify the unique characteristics of the area of subject as they relate to flooding. With this, potent flood risk management actions could be taken.

Tahnk you Mr J. C. Tarafdar for your help

Dear Hsang

There are a number of ways in which dams fail. For earth embankment dams these can be broadly categorised as:

- Hydraulic (e.g. overtopping of the dam, wave erosion of the upstream face of the dam by wave action, erosion of downstream toe of the earth slope caused by misdirected spillway flows, gullying which can be caused by rainfall erosion of embankment slopes and also traffic)

- Seepage failures where fine soil material is eroded from the downstream slope or foundation and moves towards the upstream slope to form a “pipe” that can lead to the complete failure of the embankment. This is known as “piping” and is a common mode via which earth embankment dams fail

- Structural failures e.g. failure at spillways, abutments and foundations

- Other e.g. Tree growth and animals burrowing in earth dams can lead to failure

When assessing the probability of failure of a dam all the various modes should be considered.

Here is some work from a research project we did on dam break modelling see http://eprints.hrwallingford.co.uk/577/1/CADAM.pdf which also explains how to model dam failures and the causes.

This more recent paper is also useful see: http://eprints.hrwallingford.co.uk/1469/1/HRPP770-A-guide-to-breach-prediction.pdf

This paper may also be of help: https://www.researchgate.net/publication/232941358_Analysis_of_earth_dam_failures_A_database_approach

We have also developed a number of software tools and methods to look at dam breaks see: http://www.hrwallingford.com/expertise/dams-and-reservoirs

To compute the probability of failure of your dams under climate change for a particular design return period (e.g. 1 in 100 year, 1 in 1,000 year of probable maximum flood) you need to:

1. Produce design hydrographs for the design return period and climate change scenario

2. Route the hydrograph through the reservoir

3. Assess the probability of the different modes of failure of the dam for each scenario.

I hope that this is of help.

Darren

Dear Javed

The question that you pose is quite broad. These references may be of use:

https://www.nat-hazards-earth-syst-sci-discuss.net/nhess-2018-407/nhess-2018-407.pdf

https://file.scirp.org/pdf/GEP_2017021510474668.pdf

I hope that these are of help.

Best regards

Darren

Please have a look at this useful RG link.

I am totally agree with you ( Richard Fielding ).

I am just curious to know, how others are thinking about Climate Risk. As a practitioner and researcher, when I do typical risk assessment, I never give extra attention to Hazard. Rather, i treat all parameters (hazard, vulnerability and exposure) equally.

However, when we talk Climate Risk, it seems that we are giving extraordinary focus on climate change. And sometimes intentionally or unintentionally we are blaming climate change for the ultimate risk.

As you mentioned "It depends what we mean by "Risk", we also need to make it clear what we a meaning by "Climate Risk".

Must have field experience

Please have a look at some interesting PDFs....

Hi Javed! A recently published paper I've co-authored might be of interest:

Hi Omar,

I would suggest looking at GPM data in addition to TRMM, GPM being a much newer product with a higher spatiotemporal resolution. NASA's Giovanni web portal (https://giovanni.gsfc.nasa.gov/giovanni/) is a great resource to download information from both missions, since you can do it in gridded format or with post-processing that allow things like obtaining area-averaged time series.

Also, since you are interested in flash floods, aren't daily estimates too coarse for that purpose? TRMM has an hourly resolution product and GPM has one with a resolution of 30 minutes (also available from Giovanni).

May be I can help.

1) Both of these methods belong to the same group of MADM methods, but they are based on different algorithms.

2) VIKOR as well as TOPSIS takes into consideration negative aspects of evaluation through R value (minimum individual regret) so this cannot be considered as difference.

But to answer (or not) to your question related to selection of more appropriate MADM method for problem solving. There is just no simple answer to that question, as it is raised so many times. You cannot say which method is better if they are yielding different results applied to the same problem, simply because you do not have a reference point for comparison of methods. The only thing that you can be sure about is that there are differences between methods. Generally speaking, the problem that you are solving is the one which will determine preferred method. In order to do so, you have to be familiar with different methods and their specificity.

So, I gave you a rather philosophic answer, certainly the one you did not hope for. But that is the reality.

Best luck in your work.

Dear Francis

This is a concept in AHP (Analytical hierarchy process), and is defined as CR where CR = CI/RI.

You can see this subject in attached file (page 13).

Regrards

I forgot to mention, many low gradient rivers deposit a sand levee adjacent to channel.  Small tributaries sometimes lack sufficient power to join the river directly, and deposit their waters onto floodplain or terrace, increasing the local saturation and flooding frequency, even though severity is not necessarily an issue from the shallow flooding typical.  Sometimes these local areas have wetland features in moist climates.

Thank you for sharing these recent papers Wouter. So, it seems we can conclude that there are not consistent trends of increasing flood magnitudes across the globe. In fact, climate oscillations like the NAO are stronger drivers of flood peaks than are any consistent long-term changes in climate. But what do we expect in the future? What advice can hydrologists offer to those who design bridges, culverts, and dams? I am still struggling with these questions. There seems to be a growing body of published literature that is finding that extreme precipitation does scale with temperature across the globe (perhaps with the exception of the tropics), indicating we should expect larger precipitation events as the global climate continues to warm. In fact, there is growing evidence that convective storms may scale at a greater rate, about 2X Clausius-Clapeyron. This increase in storms of small spatial extent does raise the question of whether the current network of river gages is of a sufficient enough density to detect a trend in floods at small spatial scales. Admittedly, precipitation does not equal discharge, but the patterns that are emerging suggest an increased risk of floods in the future.

Conrad Wasko has published on this topic, see these papers and others:

Also a recent paper on super Clausius scaling by Lenderdink:

THANK YOU ALL

Dear Prof. Domsta,

Thank you for your attention. 

I'm a newcomer and need to have the relationship between bedrock acceleration and it's distance to epicenter during earthquake.

If there's something not appropriate, I'm grateful to have your instruction.

Thank you professor!

Bowei

You might check out the software program "Indicators of Hydrologic Alteration" - developed by the Nature Conservancy. 

I am positive there are tools in that package for comparing flows between two different time periods, but I am not sure if there is a tool for identification of separate/similar regimes or periods. If not perhaps you could use one of the techniques described above to identify the periods or hydrologic difference or similarity, and then use the IHA software (or analogue in R) to quantify hydrologic variations between periods in more detail. Worth investigating perhaps.

Dear Kazunori

I will give a partial answer explaining the situation in two Australian States.

Land law in the six Australian States follows a similar pattern but there are unique characteristics in each. From earliest European settlement (began in 1788, but accelerated in the second half of the 1800s) the concern about river boundaries was not so much flooding, but first to protect rivers from pollution and riverbanks from degradation by grazing stock; and second, to allow general public access - for public purposes and also for travelling stock purposes in the sparsely populated inland. (Remember that most of Australia is dry and except in the coastal rivers, water is precious). For these reasons land was often reserved along rivers to ensure that the neighbouring landowners did  not exclude the public.

For example, in 1881, the State of Victoria reserved a land frontage of usually 1 chain (about 20m) along most named creeks and rivers from alienation (that is, sale from the State). While frequently leased back to adjoining landowners (to avoid costs of fencing), they remain State land.

In the State of Queensland, with much larger distances and much larger landholdings (commonly thousands or tens of thousands of hectares, reservation of a frontage was less common. However in the early 1900s, legislation was passed to compulsorily acquire (expropriate) the bed and banks of boundary watercourses (forming the boundary between two titles), without compensation. Since then there has been much controversy within the surveying profession about what "bed and banks" means. Some hold that it always meant the "high bank", the top of the topographical feature containing the river; others hold that it meant only the land covered by ordinary winter flow. An aberrant court case (Kedron Brook) complicated matters. The Government delayed for many years the amending legislation to make the situation clear.

The issues are explained in two departmental guidelines, attached. Please note first that although authoritative at the time, these were only ever internal working documents and never officially published by the Department; and second they are now old and superseded and cannot be relied upon as a guide to current legislation.

Hi Ben,

One of the very important things to consider - you may like to refer to my publications on this topic - is DEM elevation accuracy. Accuracies are often not at all as good as may be suggested by quoted accuracy statistics from DEM providers. This is the case for more or less all sources of DEM data. This will impact on your flood prediction results. However, you can minimise this effect (before you get to doing anything in ArcGIS) by choosing the most suitable DEM for your given location if this is possible.

Each source of DEM data (LiDAR, SAR, airborne or UAV photogrammetry or ground based methods such as TLS and GPS) all have their strengths and weaknesses. LiDAR for example often works exceptionally well in paved areas, but less well in vegetated areas - even last returns data, which can retain a residual vegetation component. SAR tends to work poorly in urban areas, and can work comparably better in vegetated areas. All methods of DEM acquisition have their own shortcomings. Knowing a bit about the data you intend to use will help to give you a clear picture of locations where your DEM may perform well, or not so well.

It may sound a bit OTT o tlak about accuracy. However, if your DEM records elevation at 1m of elevation, and if the slope in your flood prone area is 1:100 for example, this might result in a 100m horizontal mis-classification of flood risk.

If you are working with irregularly spaced sampling data, or low resolution ground sampling data then the interpolation method that you apply will be important too. Some interpolation methods introduce a lot of error. In terms of ArcGIS, if you have access to Geostatistical Analyst, that offers a good toolset to help you to optimise the interpolation to minimise inaccuracies in your flood prediction model, particularly using Universal Kriging.

Other things to consider... Take care (whether in ArcGIS or elsewhere) when transforming between orthometric heights, ellipsoidal heights, elevation units etc when you are integrating flood gauge data, DEMs, and other sources of elevation data.

I hope this helps...

It is not uncommon for 60-90% percent of rainfall to be absorbed into soil with grass or forest cover, avoiding substantial direct runoff.  Imperveous surfaces are almost all runoff, very little infiltration.  Urban stormwater can become a major issue to deal with, and an area of study over the last few decades.

Thank you. Will have a look at these.

Dear kadir,

There are some studies i share to you, that may be useful

Mohomed,

indeed, you are describing a tricky aspect of science - perfect knowledge (by scientists or decision  makers) alone is not enough. There are typically 3 types of stakeholders here, and all need to be involved and play their part well for things to improve: scientists need to develop solid understanding of a problem, e.g., flooding, but then also need to communicate this appropriately to decision makers. That means first of all they need to find adequate ways to communicate complex issues, ideally by working with those decision makers from the very beginning to make sure it's clear what those decision makers need and what they understand (and what they don't understand). Only then are those decision makers able to make decisions and also communicate them to the public. In my view it's the decision makers that should be responsible for the bulk of the communication with the people, although scientists themselves can play a useful role, by going into schools, writing for newspapers or non-scientific publications, etc. Still the hard part is to translate flood properties into understandable and meaningful language. A typical people living in a flood-prone area will not understand return periods, flood probabilities, measures of uncertainty in predictions, etc. Even understanding simple parameters such as flood depth,ad n relating them to their own personal circumstances will be challenging for most people. One useful way can thus be to associate scientific information such as a flood depth/duration/energy map with clear, representative illustrations of the effects of such an expected/possible event (a house flooded to 1 m, 2 m, or more, crops of type x being flooded by a few cm vs. 1 m, or for a day vs for a  month, or by a  ' slow flood' vs a flash flood. People respond to visual cues, and to things they are familiar with. Involving people from the communities in selecting or designing such effective illustrations will also be helpful.

Regards, Norman

Thanks Kleomenis, I will definitely try what you suggest!

Predicting rain and runoff, flooding is largely based on limited records, and in many instances you are not going everything you want.  Models will typically use all the data you can muster, and be wanting for more.  You need a combination of recording rain guage stations preferred and recording stream gauges and have an absolute minimum of 10 years record for any predictive capability or comparisons with the old data stations, however even 100 years is probably not enough for some things.  Consider the rainfall event we had in October near Charleston, SC.  Using the available data, we had the 1000 year event on the national forest, but as soon as we insert this data into the total and recalibrate, perhaps it may be the 500 year event.  Weather specialists do a reasonable good job now with their data and tools for predicting weather within the next few days, weeks or maybe as far as months, that is pushing it.  However, the predictive tools rely on spatial data, and a lot of it.  In areas with a lot of topographical relief, adding more rainguages can help coverage of individual storms or help locate areas that then to get more rain, but they are not necessarily going to improve prediction but may help with years of data.  Weather patterns shift, the jet stream shifts, you can have wet years, dry years, and individual event severity is dependent on a lot more than a truck load of data.  It is best to model and predict as best as we can, but identify the uncertainty and build infrastructure, homes, etc. accordingly.  If you are in the floodplain, elevate your structure above the 100 year or more elevation, and such as put your garage on the lower level and accept your car may or may not be flooded in your lifetime.  Most people don't have the information at all so that they can consider it as an option. 

From what I know the FLEMO uses discrete values up to 6-7 meters, while the curve that interests me should go up to values of 9-10 meters.

Dear Randolph

The KAP study should generally invite a large set of variables ranging from Ordinal to ratio scale; discrete to continuous data and dependent and independent nature. 

For the dependent vs independent issues, the best way will be use of regression (logistic regression).

If you wish to study the association of a response for two factors at different levels, chi-square may provide solution.

For linear relationship between two interdependent variables, you may use spear man correlation coefficient (for discrete data).

I would suggest you to evaluate each and every variables and also hypothesized the relationship between/among variables.

Hi Randolph

The theory of planned behaviour may be useful to you. It is a well used theory and information inputs to the model should be well studied as well. 

kindly find attachment pdf, it will help full fore u 

Hi there,

as far as I know studies from Africa are pretty rare in flood research. by a fast check I have found a couple of articles that may lead you further:

Perhaps you may also be interested in flood risk perception & preparedness studies from Asian countries (I would advise to look at numerous studies from the region, including Bangladesh, Vietnam, Jakarta and others)

See also a Primer on Disaster Risk Management in Asia: http://www.adpc.net/udrm/primer/pdf/primer_volume1.pdf

another document (looks like part two of the previous one) is entitled  a Primer on Integrated Flood Risk Management in Asia (pdf to be found via google).

I hope that helps.

Cheers, Marija

Dear Abdulatheem, thanks for your question. Actually you should try to avoid building in risk areas, because even using building materials which are more resistant to floods, when they are very serious, no matter what sort of material you use, they might be damaged by a heavy flood. Therefore, the best way is to avoid risky areas, where floods occur frequently. In Brazil, according to our environmental legislation one can not build close to a river and the minimum distance to the river bank is 30 metres.

The SCS-CN methodology is widely used. As previous collegues wrote you need the following:

- soil hydrological groups

- land use categories

- tables with CN values (available e.g. in the works of Chow VT (1964) Handbook of Applied Hydrology. McGraw-Hill Book Company, New York or Urban Hydrology for Small Watersheds (TR-55). Natural Resources Conservation Service, Washington)

- define designed rainfall or measured rainfall

- define Antecedent Moisture Condition (AMC) 5 days prior to designed rainfall or measured rainfall and modify CN values according to AMC I, II or III

- use e.g. ArcGIS and HEC-GeoHMS extension to create CN-grid

- them you can create rasters of potential retention, surface runoff depth, contributing areas, surface runoff volume, etc. according to the formulas presented e.g. in the cited works

- compare the results for different time horizons with relevant land use

- you can quantify changes using map algebra in ArcGIS

see this paper of a colleague of mine. It may help, 

In general, fragility curve is plotted probability of certain damage state of an or a group of Element of Risk Vs hazard intensity. In case of flood as you want to know, assume a town near the flood plain which has a probability of damage (buildings) is 50% for a 2 meter depth flood (you can also consider velocity as a flood hazard intensity, or depth+velocity+duration of flood). You can easily plot fragility curve. You can also consider absolute damage cost as a probability of damage state.

visit following web pages or simply google for further reading. I hope this will help you.

yes

is known that low-resolution DEM produce artefacts and reduce the slopes in DEM's.... you can try using Tandem-X topography..., all Europe is covered

Dear Claudiu ,

As indicators I emphasize the relationships:

- economic development vs. pollution;

- social housing vs. property speculation;

-demographic growth vs. health and education

Some studies in Brazil (in portuguese):

Urban and commercial resilience in central areas:

Resilience of urban systems:

Urban sustainability indicators for urban resilience:

Building resilient cities:

I hope it helps.

Best Regards,

Vanessa

The book Visualizing the Data City by Paolo Ciuccarelli,Giorgia Lupi,

and Luca Simeone may guide you in this regard. Here's the ISBN: 978-3-319-02194-2.

I consider it necessary analyze the relationship of the parameters of rainfall and snowmelt with those of flow. In the analysis of the parameters, other statistical flow models and programs have to be considered. It is also important the calibration and sensitivity analysis. The quality of numerical and statistical model depends on the maturity of the conceptual model. You will find free flow models in the website of Valencia University in Spain and also in the website of the US Army.