Water Quality Monitoring - Science topic

Dear Julius Riese

Thank you for your answer!

It's quite hard to distinguish in this area what's tributary and what's not, as it's a coastal area, an inner archipelago. However, the northern stream is generally considered to be a main stem. The western eutrophicated bay is a flad (as they usually call such coastal lagoons in Finland). The characteristics of a flad are usually that they are under some kind of protection because of their unique ecosystem and the "entrance" to the flad is usually very narrow and very shallow (however inside a flad it's usually 2-8m deep).

As you can see on the maps, this flad is connected to the other bigger bay (fjärden) through a small ditch that goes through wetlands. The coordinates of the central bay of interest are 59°58'00.9"N 23°40'09.7"E.

There is basically no tide in that area of the Baltic sea. The central bay is something like 9-14km from the open sea (areas of the outer archipelago) depending on what route to choose through all these islands.

Basically, we have made a GAM analysis for that area based on our other parameters, and we have a predicted "normal level" for turbidity and a map, which shows SD from that normal level for every occasion (approx. 6 occasions during the non-ice period). So, basically, we were thinking about if it's possible to understand which source has a greater influence on this high positive SD turbidity in the bay and to which spatial extent. Like the spatial influence of a "point-source pollution". We have lots of high-resolution data, so we were thinking that probably it's possible indirectly calculate the strength and direction of influence. Kind of to draw the area where this particular point of pollution has influence, and where it stops having significant influence, being too diluted. But now thinking more about it, it seems that it's not really possible to predict such things without knowing velocities.

All the best,

Maria

Md. Mamunur Rashid Have a look https://github.com/pkErbynn/IoT-WQMS

Converting COD to regular COD concentrations can be seen in the link am sharing and apart from this easy way would be edivining the number by 1000 as to converting COD from m/l to o2/l and this is a very simple technique of conversion of the overall COD from mg/l to go2/l as this involves the oxygen as well

https://iwaponline.com/wpt/article-abstract/11/4/838/20801/A-simplified-method-for-estimating-chemical-oxygen?redirectedFrom=fulltext

muchas gracias por sus respuestas

Modern coupling techniques are widely used for the determination of chemical contaminants, for example: GC / SM-SM; HPLC / MS; IRTF / MS, UV-VIS

Dear Kelly,

the quickest and easiest (but still with high sensitivity) would be using a plankton fluorometer. Most of these will also provide an estimate of phycocyanin and phycoerythrin, which might be useful for your cyanobacteria-related question.

Good luck

Marco

You can obtain this s data from the Central Groundwater Board, local office at Kakinada Or Rajahmundry.

For this type of data, usually state Groundwater Department (Govt of Andhra Pradesh) is the custodian. To obtain this, data you may have to visit them in person with a letter endorsed by your HoD and wait until they release the data. It takes time usually....you may also try thier websites if by chance the data is loaded to the web.

Bluetooth allows a cell phone or two to attach to the stm32

using board for nucleo P-NUCLEO-WB55

There is a temp / humidity . 3 axis accel sensor board

When using the STM2IDE project manager (tutorials on line) the user can select the inclusion of the add on board software driver during project initialization. The HAL code will be added to the project for basic interface.

Water quality is tricky, easiest method

turbidity (nephalometer) measures water cloudiness ,you need a 980 nm LED an photo diode pair with filter, maybe and IRDA transceiver can be subbed , connect the LED to a PWM GPIO output for pulse light , and add a transconductance (ti.com) amplifier with integrating cap to the photo diode and then that output to an ADC channel. The idea here is the IRDA sensor immersed in water will illuminate the water and any particles or dirt etc will cause a reflection of the otherwise clear water. The photo diode is integrated over time look uop leaky bucket integrator circuit for detail. The average reflection is an indication of the suspended dirt cloudiness and there fore turbidity. Google turbidometer

This wont detect cryptospiridia or giardia or other pathogens as you will need a particle counter for that, way past normal student project.

This is the website of EPA National Service Center for Environmental Publications: nepis.epa.gov. There you can find all the procedures by the number. The following references (websites) can help you: https://www.standardmethods.org/

https://beta-static.fishersci.com/content/dam/fishersci/en_US/documents/programs/scientific/technical-documents/white-papers/apha-water-testing-standard-methods-white-paper.pdf

https://www.edgeanalytical.com/wp-content/uploads/Waste_SM4500-NO3-.pdf

As a solution to this problem, I will only be using spectral signature of water at 675 nm with the AAQ Rinko chl-a measurements.

The answer is clear: only the gravimetrically determined method provides reliable results. The EC/TDS method is a calculation using a conversion factor which ranges from 0.25 to 1.34 [µS/cm and mg/L] . If – and only if – you predetermined the conversion factor for a given site THEN you can use the EC/TDS ratio and it will also be reliable. Please see my paper

Hubert, E. & Wolkersdorfer, C. (2015): Establishing a conversion factor between electrical conductivity and total dissolved solids in South African mine waters. – Water SA, 41(4):490-500, 6 fig., 8 tab.; doi:10.4314/wsa.v41i4.08.

for details and more references.

So, to answer the last part of your question: determine the EC (at 25 °C = κ / TDS ratio for several samples of your site(s) using the gravimetrical method (ensure you calibrate your EC meter) and then use this factor f to calculate TDS as follows:

TDS [mg/L] = f × κ [µS/cm]

We have several index for assessing the pollution in the river, both standard and local method.

Many thanks toyou all:

W.f.hansen

K.M Ashar

A. Zekri

and A.M. carmen ilie

Good information but it is unpublished.

So many things to consider before you even attempt to do that kind of analysis. I'm already making an assumption the data has been quality screened (a serious issue for large programs / data sets). What is the purpose of the monitoring  (are you looking for change or interested in actual quality for some particular use?), what data is most important for this purpose, are all the bores from the same aquifer / geological unit (this would be your first level of grouping - no need for stats), major ion balance (this is generally how hydrogeologists group waters - ie Trilinear / Piper or Stiff diagrams - Piper plots will show clusters again without need for much stats), is quality changing in some bores and thus they may be important to keep - even if they are not representative (a good paper on assessing change has recently been published by colleagues - attached). So just relying in stats to consolidate your bores is unlikely to be helpful. 

Dear Pawan Whig

thanks for  your answer ,with my Greetings.

I do not know. Please try asking Colin Price and/or Earle Williams. Kind regards and wishes for Merry Xmas. Christos

The only way that the value could be negative is if oxygen increased in your incubation. This could result from several errors, but most likely light was allowed to penetrate your bottle allowing photosynthesis to occur, otherwise you have to check the calibration of the instrument.

Just divide each ion (in milliequivalents per liter) by the total summation of ions (either cations or anions) and then multiply by 100

Did you visit this link?

 Dear Saeed Taji,

The market is literally flooded with water treatment options. Reverse osmosis systems, loose granular activated carbon, solid carbon block filters, and distillers all promise sparkling, clean water, but how do you know which one is really best? With a little research, you can find the ideal water treatment system for you.The UV treatment is best and low cost. Scientists have known for nearly a century that ultraviolet light of certain wavelengths is an effective germicidal agent.

One application where ultraviolet disinfection is used is in recirculating delivery systems. In a recalculating system, water flows constantly from a storage tank, out to the pressure stations (or through the stations and through the piping in the animal rooms), then flows back to the storage tank. These installations use in-line UV units in the recirculating loop to provide control of bacterial growth.

Please have a look at this useful researchgate link.

This is a nice dataset that I use for this kind of information. I hope it helps!

Hi Vineet,

as Siraj has stated, we need a bit more information before we can give you a definite answer.

Of course it depends on the size and complexity of the river catchment - is it a single river course or are you monitoring a whole river network including tributaries?

But it also depends on the land use, the relief and the geology of your catchment. Is anthropgenic discharge (urban or industrial waste water, water from mining areas, agricultural drainage) the only source of pollutants or will there also be a geogenic component from the mountaineous parts of the catchment? Are there identifyable point sources (waste water treatment plants, drainage water dump sites)? Is there agricultural land use close to the river that could lead to a non-point pollution (nutrients) or to (bank) erosion (input of sediments which could e.g. contain heavy metals or phosphates).

Based on the characteristics of your research area you need to set-up your sampling network. Have one sampling point upstream of each point source and one sampling point immediately downstream of each point source. The same goes for the tributaries - have sampling points up- and downstream of each (major) tributary and a third one within the tributary (a kilometer or so upstream of the inflow point). In areas without point sources, have the sampling points spread out along the river and - if applicable - try to include different land use and relief types (if the river crosses a forest, have a point upstream and downstream of that forest and one or more points within).

Ideally you will end up with a dense network of sampling points that willk allow you to monitor the changes of the water chemistry, detect sources of pollution and e.g. evaluate the self-purification effects.

BUT, depending on the size/length of your catchment/river, this might not be feasible for you, as you might not have the logistical and financial capabilities to operate 20+ sampling points. Maybe you even only want to measure the summarized water quality at the outlet of a river catchment, so you only have a single sampling point?

Both is possible, as this is only the first part of the answer to your question - the spatial quantity. There is also, and at least as important, the temporal quantity of the samples:

How many samples do you need to take at each sampling point? Well, again, it depends. Do you have clearly defined point sources with a steady inflow of waste water (industrial or urban sewage)? Then maybe a couple of samples will be sufficient. But as soon as you have non point sources (agriculture) or highly variable climatic conditions (e.g. dry and wet season), you need a more systematic approach, as a single sample is just a snapshot of the water chemistry and you might just miss that crucial pollution peak by a day or two. How long do you plan the measure the water quality? For a year? Than I would go for at least 24 samples per point (two per month). Or just for a couple of weeks? Then go for daily samples (and make sure that the short duration you pick for your sampling is representative for the whole year).

The Bottom line is - the more samples the better, as more samples will help you catching those peaks without making them too prominent. Statistically speaking you need at least 11 samples before you can even start thinking about averages and such, but try to take as many samples as possible.

If necessary, find a balance between having more points and having more samples so that you do not get spread out too thinly in either of the two.

And keep in mind: Whenever you take samples from differnet points and want to compare them, collect some samples in as small a timeframe as possible in order to have comparable conditions (discharge, pollution, water temperature). This will lead to you driving around from point to point, quickly taking the samples, so that you have them all together within an hour or two. If you do not do that but rather take your samples for , e.g. May 2016 spread out from the 3rd of May (sample 1) to the 16th of May (sample 30) you will end up comparing apples and oranges as in between the 3rd and the 16th all kinds of things could have and will have happened (a heavy rainfall, some farmers applying fertilizers, a dramatic increase of the temperature etc.)

I hope that helps you getting started.

All the best,

Michael

I agree with the comment by Dr. Contreras. Additionally it can be interesting to know if the TOC analyser is using heat+oxygen or UV+persulphate to convert the organic matter to CO2.

I have experienced some problems with chloride in samples with the  UV+persulphate method, but it wasn't increased values.

Hi Vitalii,

Just a bit of additional material to complement what Tad added above; the National Hydrology Dataset (NHD) and the Watershed Boundary Dataset (WBD), are both vector datasets that will show you the rivers/streams, lakes, and glaciers (NHD) and the basins for those rivers/streams down to a hydrologic unit code (HUC) of 12, which is pretty small. Some areas, if I'm not mistaken, are even working on HUC16s, which is getting really small for basin delineation, but in some areas, it may be practical to make them that small (urban areas?). Neither of these datasets provides water quantity nor quality, but you can try StreamStats instead, if you don't want only data from USGS gage sites as delivered through NWIS. While not fully implemented for the entire USA, it is showing how the coupling of the NHD, WBD, and NWIS can begin to show how multiple datasets can be integrated and a potential wealth of calculated results using these three datasets for a gage, as well as modeled data for ungaged basins of one's choosing, based off of the regional regression equations for estimating flood flows. I'm sure the future will bring with it greater maturity and openness everywhere, but for now, you can even get data for ungaged basins (caveats included, of course) in certain areas. For example, I randomly picked a USGS gaging station, number 01548005, on Bald Eagle Creek near Beech Creek Station, Pa., and I am not from Pennsylvania, just to maintain a sense of fairness, ( http://streamstatsags.cr.usgs.gov/v3_beta/viewer.htm?stabbr=PA ), and received http://streamstatsags.cr.usgs.gov/gagepages/html/01548005.htm , a StreamStats Data-Collection Station Report, that contains a wealth of information about this gage and the upstream basin. Back on the map page, you can continue zooming in until you see the raster cells that make up the modeled stream network, basically a function of the DEM, and then click the new icon (you'll have to play with the map service...it's too much to explain in type), which is a circle with a "+" sign, at which point it will generate the basin for the gage, as well as a "Q" state that will compute flow statistics. The further you zoom in, the more options you will have. When you see gages (triangles), that's the place to start

Things are moving along. Some areas have more resources and better data than others. Most of this data, modeled and real, is downloadable. Sometimes it works better in some area than in others, but as you will see on the StreamStats home page, http://water.usgs.gov/osw/streamstats/ssonline.html , there are some holes where states have not begun the process, to states that are highly developed that have completed the process through one method or another. It is a constantly evolving organism at the moment, always looking for the best way to present both the gaged data and the modeled data. If you have any questions, please feel free to contact me and I'll be happy to answer questions as possible or pass you on to someone further up the proverbial food chain. Time to get back to work...Cheers, Bob 

I agree with both Mikhail and Thomas.  They will last quite a bit longer than the year specified by most manufacturers.  As long as they are well cared for, they will last several years.  Our current sondes (YSI EXO1) have 3 year old caps and the calibrations and DO gains are all still good. 

I'm assuming that there is a black paint covering the exposed end of your cap?  As long as that paint is still substantially intact and your calibrations are good, then your cap should still be good.  If you are deploying for long periods of time and there is a wiper sweeping debris off the cap then you may get some degradation of the light protectant black paint over time.  From what I understand, light exposure will degrade the dye pretty rapidly so you want to make sure that paint is intact.

Also, if you are storing your sensor/sonde between uses (rather than constant long term deployments in water), make sure that it's properly stored in a moist environment to keep the dye gel from dehydrating.  A dehydrated cap can be rehydrated and still be good but it's an iffy proposition and I don't like running that risk so I make sure my gear is properly stored.

I have been using a fairly simple database design that I think may work for your applications.  It's just a Microsoft Access database with an Event and Result table as well as two other reference tables.  The design is based on the data reporting format for the Texas Commission on Environmental Quality (TCEQ).  The Event table lists information about where and when the samples were collected.  The Result table lists all the parameter results collected for that event.  These two tables are related by a "Tag Number" that is unique for each event. The two reference tables are a station ID list and a "storet code" list.

For example, tag number TR00001 was used for a water sample collected at station 12345 on 3/15/2016 at 10:00 at a depth of 0.3 meters (Event info). A point to remember here is that each matrix and/or depth is a unique event.  So if I were collecting water, sediment, and benthic macroinvertebrates at site 12345 on the same date and time, each of these three sample types would have a different tag number.  Sediment would be TR00002, benthics would be TR00003 and so on.  A profile sample taken at 1 meter could be TR00004.

For that "event" TR00001, DO, pH, temperature, specific conductivity, chlorophyll-a, TP, NO2, and NO3 were collected.  So there will be eight Results with the tag number TR00001 and the reported value for each parameter.  The parameter codes (what we call storet codes-a 5 digit code) provide all the information about the sample matrix and unit and in some cases the analytical method.  The storet code for chlorophyll-a is 32211 and indicates that it is a water sample reported in ug/L by the spectrophotometric method.  Storet code 70953 is also chlorophyll-a in water reported in ug/L but it's by the fluorometric method.  Total Phosphorus in water reported in mg/L as P is 00665 while TP in sediments reported in mg/kg dry weight is 00668.  There's a code for pretty much everything. 

The beauty of using a storet code is that you don't have to look for all possible spelling combinations of a parameter.  For example, if I wanted to look up dissolved oxygen in water (mg/L), I look up 00300.  I don't have to find all records for "DO", "D.O.", "Dissolved Oxygen", "Dissolved O2", etc. 

As far as querying, I can pull all data ever collected for any sample matrix for site 12345 or I can drill down and ask for only water samples, only sediment samples, only specific parameters, or whatever else I want.

Here is the link to the TCEQ webpage where the Data Management Reference Guide lives.  This explains in more detail a lot of what I have described above.  https://www.tceq.texas.gov/waterquality/monitoring/data-management/dmrg_index.html

http://www.tceq.state.tx.us/waterquality/monitoring/txwaterdata.html   This is the link to the webpage where the "Sampling Station" and "Monitoring Parameter Descriptions" can be seen.  I save these lists in ASCII text and import them into my database.  Obviously, the station list is unique to Texas and each basin within the state.  The Monitoring Parameter Descriptions table may be a good place to start for you unless you already have a list.  This list was adapted from the federal Environmental Protection Agency STOrage-RETreival (STORET) code list. 

I hope this helps.  Feel free to message me if you have any questions about this.

Each genus/species needs to be rated as to pollution tolerance.  Then you can use presence, absence, relative abundance of the species present.  So you need a numbering scheme for tolerance to pollution to intolerant.  Then a relative abundance numeral rating from 0 (not present) to high numbers.  Your ratings can go to 5 or 10, depending on categories you set.  So if intolerant is 1, tolerant is 5.  If not found, it gets 0, if infrequent 1, ... , abundant, 5.  Then take the tolerance times abundance value for each species present.  Add the total of all, divide by (number of species evaluated times 5).  Lower numbers good water quality, higher numbers bad.  You develop categories.

According to "Standards for Effluent Discharge Regulations General Notice No.44.of 2003 THE ENVIRONMENT PROTECTION ACT 2002 Regulations made by the Minister under sections 39 and 96 of the Environment Protection Act 2002", it states that the maximum permissible temperature for discharges into the aquatic environment is 40oC.

Also according to an environmental agency (United Utilities water/wastewater emergency) " Temperature  is limited by statute to a maximum of 43.3°C" (http://www.unitedutilities.com/documents/Trade_Effluent_Information_PACK.pdf)

I know these are not specific for UK, but I hope it helps your judgement

 Dear Dr. Saravanamuttu Subramaniam Sivakumar,

Yes, it is possible by installing costly treatment units consisting of special filters or air strippers. At low cost level through use of carbon filter or a reverse osmosis filter.

As I understand, all you have is historical water quality data.  No streamflow date for nearby streams, no rainfall data.  It may depend on the types of water quality data.  Some high high direct or indirect associations with flow as per with karst springs in Missouri.  But if you don't have flow data along with water quality data, accuracy is problematic.  Some parameters are directly, some inversely related to flow.  A lot depends on geology, soils, land use, etc.  Some are going to leave a strong signature with varying flow, others not.  Not a great answer, but I am out of time and maybe this will be of some help. I would plot flow on x axis and the various combinations of potential indicators on the Y axis.  Those with high correlations based on linear, log and exponential relationships, I would bring forward as possible indicators, singly or several. Present the table with the r squared for each water quality component related to flow.  

Hi!

This is a very complicated issue, You should try to find out whether you deal with a set with "continuous" change or a step change, caused by a new or closed outlet to the stream (I guess you work with running water). As somebody pointed out; any statistical method to find/exclude outliers should only be applied for real extremes; and with care.

Don't expect a linear change with time, frequently there is a more or less periodical variation, which you may be able to follow if you have flow data. Lacking flow, perhaps water level is recorded somwhere. And, of course rainfall can be used as an indicator.

I would suggest that you try to find a correlation between your studied parameter and other related. E.g. nitrogen and phosphorus compounds may be correlated. Conductivity and major constituents certainly are correlated.

Also try to check monthly data for the observation period. I am convinced that you will find large variation during some months and less during other.

Good luck

Anders Wilander

I agree with my predecessors remarks, burning plant litter is a well-recognised means to release nutrients held in organic matrix to succeeding crop use a sort of man-induced mineralisation. Volatile nutrients are however lost permanently. The ashes produce also alleviate soil acidification, ashes having a basic pH.

Burning has also a curative effect on soil borne diseases and insects even though this is not the issue  being discussed.

Therefore as a means to address this pollution, a free buffer zone is recommended that can trap particulate matter in the fly ashes from reaching water bodies as well as those in the soluble form transported in water during surface and base-flow runoff.   

dear researchers, thanks for your valuable comments and if you  have any more ideas when you are reading literature please suggest... thanks

Laser intensity in nephelometry play an important rôle in particle detection. At low intensity you increase the background, so very small particles are included in this background but you can measure a very concentrate suspension. Each different particles have a specific impact in nephelometry because of form. Nephelometric unit is RNU for relative nephelometric unity  

ON THE BASIS of only above data it is impossible to know the answer. 

Dear Hansman. I appreciate your answer. My University wishes to purchase the equipment possibly if it can get a used version at a much reduced price. I'll also appreciate if you also have any information regarding that. However, I will send a mail to the company to inquire if there's any special package for University. Many thanks. 

Are there available data sets for streams in your area?  This could give you a picture for what is typical in your region.  From there you could do something as easy as a 1-sample t test asking if your stream differs from the population of streams in your area.  If there's a good data source you could ask if your stream falls in with the typical urban streams or is closer to the more protected streams. 

It is not always necessary for you to provide the control if somebody else has generated data you can access.

I agree with Penny. Silicate is the most likely interference.

Check pH-value, which is crusial and the development time (which should be relatively short to reduce development of the molybdosilicate.

Gerald, you may be interested in research which is durrently being conducted at the Dept. of Remote Sensing and Photogrammetry of the Military University of Technology in Poland. We are using hyperspectral imaging techniques to detect and identify physical, biological and chemical water pollutants. Spectral reflectance curves can be obtained from such images and then compared with spectral characteristics obtained in laboratory conditions of a wide range of pollutants. We have a few publications from the first stages of this project (A review on remote sensing methods of detecting physical water pollutants (Walczykowski et al.)  and Using XEVA video sensors in acquiring spectral reflectance coefficients(Orych et al.)) with more publications to come later on this year on the further developments we made over the past few months.

These may help:

Ballard et al (2007) 'Site handbook for the construction of SUDS' CIRIA C698 London 2007

Thanks all for your input.  I now have found a source of preserved spiny water fleas.

Hi

Maybe could you have a look on Christian Perret's or Alain Poirel's publications. They are on Research Gate. For Christian: https://www.researchgate.net/profile/C_Perret/publications. Some papers are in French, but you can also ask them, they are good specialists of the water resources monitoring in France.

Best regards

I note the need for work on metals, and the following maybe useful on this:

Neal, Colin; Reynolds, Brian; Kirchner, James W.; Rowland, Phil; Norris, Dave; Sleep, Darren; Lawlor, Alan; Woods, Clive; Thacker, Sarah; Guyatt, Hayley; Vincent, Colin; Lehto, Kathryn; Grant, Simon; Williams, Jeremy; Neal, Margaret; Wickham, Heather; Harman, Sarah; Armstrong, Linda. 2013 High-frequency precipitation and stream water quality time series from Plynlimon, Wales: an openly accessible data resource spanning the periodic table. Hydrological Processes, 27 (17). 2531-2539. 10.1002/hyp.9814

Neal, Colin; Reynolds, Brian; Rowland, Philip; Norris, David; Kirchner, James W.; Neal, Margaret; Sleep, Darren; Lawlor, Alan; Woods, Clive; Thacker, Sarah; Guyatt, Hayley; Vincent, Colin; Hockenhull, Kathryn; Wickham, Heather; Harman, Sarah; Armstrong, Linda. 2012 High-frequency water quality time series in precipitation and streamflow: from fragmentary signals to scientific challenge. Science of the Total Environment, 434. 3-12. 10.1016/j.scitotenv.2011.10.072

Kirchner JW and Neal C. 2013. Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection

PNAS 2013 110: 12213-12218.

Halliday SJ, Wade AJ, Skeffington RA, Neal C, Reynolds B, Rowland P, Neal M, Norris D. 2012. New inferences from long term trends, seasonality and shifts in phase and amplitude observed in upland hydrochemistry: Plynlimon, Wales. Science of the Total Environment. 434: 186-200. doi 10.1016/j.scitotenv.2011.10.052. (includes Al and Fe)

Other work on continuous, sub-daily sampling includes:

Wade AJ, Palmer-Felgate EJ, Halliday SJ, Skeffington RA, Loewenthal M, Jarvie HP, Bowes MJ, Greenway GM, Haswell SJ, Bell IM, Joly E, Fallatah A, Neal C, Williams RJ, Gozzard E, Newman JR, 2012, Hydrochemical processes in lowland rivers: insights from in situ, high-resolution monitoring, Hydrol. Earth Syst. Sci., 16, 4323-4342, doi:10.5194/hess-16-4323-2012.

Jordan, P., Arnscheidt, J., McGrogan, H., and McCormick, S.: High-resolution phosphorus transfers at the catchment scale: the hidden importance of non-storm transfers, Hydrol. Earth Syst. Sc., 9, 685-691, doi:10.5194/hess-9-685-2005, 2005.

Jordan, P., Arnscheidt, A., McGrogan, H., and McCormick, S.: Characterising phosphorus transfers in rural catchments using a continuous bank-side analyser, Hydrol. Earth Syst. Sc., 11, 372-381, doi:10.5194/hess-11-372-2007, 2007.

Jordan, P., and Cassidy, R.: Technical note: Assessing a 24/7 solution for monitoring water quality loads in small river catchments, Hydrol. Earth Syst. Sc., 15, 3093-3100, doi:10.5194/hess-15-3093-2011, 2011.

Rozemeijer, J. C., Van der Velde, Y., Van Geer, F., De Rooij G. H., Torfs P. J. J. F. and Broers, H. P. Improving load estimates for NO3 and P in surface waters by characterising the concentration response to rainfall events. Environ.. Sci. Technol., 44, 6305-6312.

Halliday SJ, Skeffington RA, Bowes MJ, Gozzard E, Newman JR, Loewenthal M, Palmer-Felgate EJ, Jarvie HP, Wade AJ. 2014. The Water Quality of the River Enborne, UK: Observations from High-Frequency Monitoring in a Rural, Lowland River System. Water 6, 150-180

Halliday SJ, Skeffington RA, Wade AJ, Neal C, Reynolds B, Norris D and Kirchner JW. 2013. Upland streamwater nitrate dynamics across decadal to sub-daily timescales: a case study of Plynlimon, Wales. Biogeosciences 10: 8013-8038

One crucial condition to watershed development programs is the inclusion of the watershed users since the beginning of the planning process. This will ensure that the effort is not only a governmental program. When the watershed users participate in the planning process, they will feel confidence in that their opinion it was considered to arrive to a consensual decision. Next, within the follow up of the program technicians should meet with the users to discuss the ongoing activities as well as the results. If the program considers conservation of natural resources the “before and after” results are very important; that is, to have exclusions areas that may show what will happen when certain practices are undergone within the watershed. Users should be clear that watershed management considers the splitting of benefits but also the split of risks. The activities should be driven by conviction more than by law. There is the challenge of the planners.

Hi Mohammad Al Farajat; Yes it can be but only tooth pastes are not only sources for polluting sewage waters. In Asian countries fluoride in tooth paste is not very common yet. As in many parts of our country India fluoride i drinking ground waters are already high and creating fluorosis. But of course it can be.  Regards

We've had very good luck with Astoria Pacific rapid flow analyzers (see http://www.astoria-pacific.com/industrial/product-applications/water/) having used them for more than 25 years. Here's the link to our lab SOPs (which include methods for various forms of N, P and Cl - sorry no silicate) http://www.uri.edu/ce/wq/ww/Publications/LabSOPs.pdf.     Good luck

Hi Amin Mahdipour Varnousfaderani; Following links may be useful to you Dear

Thanks

Dear Ana,

Hi

I am interested for cooperation. Please explain more about this issue. Is your work an experimental or you use from numerical method analyze? I can help you in numerical method. I have some experience in simulation of transition of flow with pollution through porous media. It is a great pleasure to collaborate with scientists from Romania.You can reach me through  Mohamadi.zadeh.m@gmail.com

Regards,

Mehdi

Dear Sherif

you can measure Dissolved Oxygen (DO) by DO meter probe or by winkler method.

Dissolved CO2 Could be measured by Gas Sensing Electrode or Coulometric Titration method according ASTM D513.

dissolved H2S could be measured by Hach's hydrogen sulfide test kits.

Hey, Tharanga,

Mariane makes a good point about matrix matching of standards and samples. This allows for comparable behavior of your standards and samples in the plasma and ensures acceptable analytical results.

With regards to addition of acid beyond the acid that comes from your stock standards, we pretty much always add acid beyond the amount that's in the stocks. This provides greater stability of your standards and samples by ensuring that the analytes remain in solution for longer periods of time. This is particularly important with the transition metal analytes, which are prone to hydrolysis and precipitation at lower acid concentrations. The less acid you have in solution, the more likely it is that you will lose some of your analyte to adsorption onto container walls or precipitation. If you rely only on the acid that is in the stock solutions, there may not be enough to ensure long-term (or even short-term, depending on the analyte) stability of your standards and samples. We pretty much always add enough acid to make it at least 2% acid, either nitric or hydrochloric depending on the analyte.

Hope this answer helps!

In most surface waters there will be a correlation between iron and colour and DOC. In these waters the iron is "complexed" with NOM (natural organic matter). In clasic reports this iron is suggested to be in the ferrous state!

Egil Gjessing

My answer is related to mangroves

Perhaps you need to highlight to authorities about the goods and services provide by mangroves. I know there are programmes being implemented (e.g. Vietnam, Bangladesh) to restore mangroves for the following reasons: (a) as livelihood option of many coastal poor; (b) climate change mitigation (carbon sinks); (c) barrier (shield) against disasters (cyclones, tsunami, and storm surges). Mangroves are nursery ground of fish and shrimps, which support fishers and local communities. Most importantly, mangrove forests store up to four times more carbon than most other tropical forests around the world (climate change mitigation). Mangroves reduce the force of wave energy and protect coastal areas from erosion. There are reports that during 2004 tsunami (that also affected Sri Lanka) had cause less impacts where mangroves were intact but suffered most where mangroves have been converted to shrimp farms or where mangroves were lost or cleared or absent.

More details can be found in the following report:

Potential impacts of climate change on river water quality, Science Report – SC070043/SR1, © Environment Agency – May 2008

Some highlights in the mentioned report:

There is considerable uncertainty associated with a cascade of issues. For example, there is uncertainty over the quantification of the driving global climate processes, over the procedures for downscaling from global to local riverine situations, over the processes controlling behavior in freshwater systems and over the complex interactions between hydrology, chemistry and biology.

- Water quality will be affected by changes in flow regime.

- Lower minimum flows imply less volume for dilution and hence higher concentrations downstream of point discharges.

- Enhanced growth of algal blooms in rivers and reservoirs could affect levels of dissolved oxygen and the costs of treating water for potable supply.

- Increased storm events, especially in summer, could cause more frequent incidence of combined sewer overflows, discharging highly polluted waters into receiving water bodies. The potential impacts on urban water quality will be largely driven by these changes in short duration rainfall intensity overwhelming drainage systems, as well as rising sea levels affecting combined sewerage outfalls.

- The most immediate reaction to climate change is expected to be an increase in river and lake water temperatures.

- More intense rainfall and flooding could result in increased suspended solids, sediment yields and associated contaminant metal fluxes.

- Nutrient loads are expected to increase.

- In shallow lakes, oxygen levels may decline and cyanobacteria blooms may become more extensive.

- In the UK, there has been relatively little research on toxins in streams, lakes and sediments, as the problems are thought to be limited. However, climate change may alter this perception.

I also want to get educated on this big social isssue as in Patna at the bank of river Ganga we are used to of unsafe drinking water as well as high arsenic content containing water. I would be grateful, if easily implementable solutions and training programs to the drinking water suppliers is/are suggested.

If this is due to fertilizer run-off from fields upstream, you may need to look at land uses above the sampling site, dominant patterns of fertilizer use for the crops grown there, and the relevant hydrological drivers. If this is due to urban sources of N and P, rather than agricultural, then you need to look at these patterns (I don't know what they could be).

I would guess that the answer to your question lies with the specific rivers that people have studied. There are bound to be differences from one place to another. To take two extreme cases, I would guess that temporal patterns of N and P in monsoon-influenced rivers in India will be different from monsoon-influenced rivers in Australia; and a river running from densely forested headwaters in Indonesia will be different from a river running out of the plains in India. This answer is "off the top of my head" because I have never made these measurements, but I am not very surprised that there's a difference. I would be surprised if there are large inter-annual differences for any particular site on a specific river, and if it was so, I would look for a point source, rather than the expected non-point sources.

Wow that a very nice paper! Thank you. Just like i needed, the anthropogenic and seasonal on benthic macroinvertebrate

Thanks to both of you for the suggestions. Difficult for me to try David's personally as our labs are affectively a separate organisation. These human gut bacteria do not flourish in the sea or rivers because of the temp and salinity issues, though I.E. can propagate if sheltered in clumps of beach stranded seaweed. I'm guess the gut of a fish would be a bit higher than ambient temp due to metabolic processes (muscle activity, liver etc) but perhaps not enough for human-specific I.E. or E.coli to thrive. I originally asked the question as I read a paper showing that river water flowing into a fish farm can suffer an increase in faecal indicator organisms by the time it flows out the othe side.

Also, another studies also found human & bird specific FIOs in the gut of fish: http://www.seagrant.umn.edu/newsletter/2008/08/scientists_find_bird_and_human_e_coli_in_wild_fish.html

None of these studies found fish to be a huge source of FIOs. I think I'm safer focusing on misconnected sewerage and road drain overflows!

I agree that there are limitations with PCA in environments with temporal variation, but most sampling is limited to seasonal anyway. It that case the combination of HCA and PCA can be very useful. I offer the attachment as an example of identifying the sources of temporal variation in an active watershed. In this case we had samples from the streams and nearby wells in spring and fall.

Continous aeration with some oxidising agents like KMnO4, may help you...

What type of spatial data distribution index do you want to create. If you want to know the spatial pattern of quality of data and its change over time, i would like to say that your sample over space is very very small to generate a pattern using any method. If you want to know change in quality of data over time from these five sampling stations, then it is possible either take the average of each parameter of quality of water measured from the five station, then subject it to factor or principal component analysis. Alternatively, you standardize all parameters from five stations using one of several standardization procedure and add each property from each of five stations year-wise. In this way you will have as many variables as there are parameters of quality of water for the number of years you have taken sample. Either, driving objectively weights for each parameter sum them up over years or again subject theses parameters to FA/PCA to obtain weight prom the first factor or principal components in the form of loadings and construct an index showing change over the years. However, it is important that number of years for which observation is made are samples are analyzed should be larger than the number of the parameters f the quality of water.