Problem Statement

Surface water has been used for drinking purpose at wide scale. There has been a wide range of microbial and chemical constituents in the drinking water and causing chronic diseases. Therefore, various development strategies have been introduced including Water Sensitive Urban Design (WSUD) in Australia, Low Impact Urban Development and Design (LIUDD) in New Zealand. These approaches have been helping restoring storm water flows and quality predevelopment levels. Clogging of infiltration systems has been helping in decreasing permeability of a filtration system. Storm water has been a big problem for the human beings due to harmful chemical constituents in drinking water. Poor quality of drinking water has been causing various harmful disease to human beings. It has been also creating issues in economic perspective as a resource directing towards the beneficial of the human health. Pathogens present on surface waters have been originating from both sources.

Various sources for pathogens have been including municipal wastewater discharges polluted particles in the system (Sihag, Jain & Kumar 2018).  Therefore, there have been problems in maintaining a proper approach in the development of the systems for purification of storm water. Storm water has been a huge source of water fir the ground. Therefore, it has been necessary for filtering this water before proper use. Analytical regression models are required for purifying this storm water for filtering storm water into purified water. For producing high quality drinking water from surface water, several contaminants need to be removed using various regression models. The performance of the water treatment plant need to be managed in order to add filters in the system. Analytical tools have been developed in order to evaluate water quality and adapt management practices. Regression model has been widely used in finance, sociology, hydrology and pharmacology. The use of the storm water filters have been helping creating a keen approach in the development if he model for purifying the storm water. Storm water has been stagnated with several harmful microbiological organism due to pollution and creating health issues. Multiple linear regression models have been developed for estimating microbial load in raw sources (Huang et al. 2016). The explanatory variables has been examined in regression analysis for raw water and hydro-climatic data. Discharges and runoff of storm water has been creating pollution and water stagnant problem in the environment. Many water borne diseases have been causing health diseases in humans. These diseases have been harmful and dangerous for health. Therefore, there is a huge requirement for filtering and drainage system of storm water.   The information from inserted weight transducers demonstrates that as it downpours and the water penetrates into the controls, the deliberate water level ascents rapidly and after that it falls step by step as the water exfiltrates into the fundamental and encompassing soil layers.

A spreadsheet demonstrate is created by using each control’s waste region, pressure driven conductivity esteems for encompassing soil layers, and measurements of each GI control (Piccolroaz et al. 2016). The model figures the inflow and surge volumes and predicts the water level inside the control for each rain occasion. The model’s anticipated water levels are contrasted with the recorded water levels by the inserted weight transducers. The created model predicts the GI control’s underlying execution and when contrasted with recorded information, evaluates the movement of stopping up at the surface and at the interface of capacity layer and hidden soil layer. The created model is likewise used to survey and track long haul and regular changes in both surface invasion limit and sub-surface exfiltration execution of porous asphalts amid the initial multi year of their administration lives. This was finished by isolating the ascent and drop of the watched water level into autonomous occasions. The model was reset before every occasion and the outcomes toward the finish of occasions are utilized to break down hydrological execution (Granata, Gargano & de Marinis 2016). The ascent and drop of water level are utilized for surveying the penetration and exfiltration process, individually. Figuring the aggregate surface spillover volume caught by each control was mind boggling. The ascent in water level couldn’t be utilized alone since a portion of the caught volume was exfiltrating as more stormwater was penetrating into the capacity display amid the precipitation occasion. This marvels is alluded to as intra-occasion exfiltration. When the model was set up also, aligned, it was utilized to ascertain the caught spillover volume by considering the intraevent exfiltration process. 

Literature Review

Drinking water originates from surface water and ground water sources. Substantial scale water supply frameworks will in general depend on surface water assets, and littler water frameworks will in general utilize ground water. Surface water incorporates streams, lakes, and stores. Then again, ground water is pumped from wells that are bored into aquifers. Normally surface water needs to experience numerous more filtration ventures than groundwater to wind up suited to drink (Paule-Mercado et al. 2016). The most well-known and broad wellbeing hazard related with drinking water sources are defilement, either specifically or in a roundabout way through human, creature and infrequently winged creature dung and with the microorganisms contained in their defecation.

Defilement issues too emerge from inappropriately structured, coming up short, or over-burden squander water treatment frameworks, counting septic frameworks from private homes, and releasing sterile sewer funnels. Floodwater usually contains elevated amounts of microscopic organisms from various sources. (Mohammadi et al. 2015). An comprehension of microbial nature of source waters is basic, since it encourages determination of the most noteworthy quality water hotspot for drinking-water supply, and gives a premise to setting up treatment prerequisites to meet wellbeing based targets. The event of pathogens what’s more, pointer creatures in crude water sources relies upon various components, including inborn physical and concoction attributes of the catchment territory and the size and scope of human exercises and creature sources that discharge pathogens to the earth. In surface waters, potential pathogen sources incorporate point sources, for example, civil sewerage what’s more, urban tempest water floods, and also non-point sources, for example, debased spillover from horticultural regions and regions with sanitation through on location septic frameworks and restrooms.

Different sources are untamed life and direct access of domesticated animals to surface water bodies. Numerous pathogens in surface water bodies will decrease in focus because of weakening, settling and cease to exist because of natural impacts (warm, daylight, predation, and so on.) (Mueller et al. 2016). In an offer to alleviate such dangers to human wellbeing by polluted surface waters, checking, evaluating, and overseeing microbiological nature of surface waters is an unending procedure. Such evaluation and checking of the microbiological nature of surface waters include distinguishing the primary wellsprings of fecal microorganisms by examining waterway water tests for customary fecal marker microbes; Escherichia coli, intestinal enterococci, and spores of Clostridium perfringens, and at times the test targets particular pathogen (Loperfido et al. 2014). The pathogenic living beings of concern incorporate microscopic organisms, infections and protozoa. The infections they cause change in seriousness from gentle gastroenteritis, to extreme and at times lethal looseness of the bowels, looseness of the bowels, hepatitis, cholera, typhoid fever and campylo-bacteriosis (Farkas et al. 2013). The different boundary way to deal with giving safe drinking water incorporates source water assurance, treatment, and support of appropriation framework trustworthiness. Improvement of watershed administration methodologies depends on a comprehension of the effect of watershed exercises and land utilizes on accepting water quality. Controlling the dangers identified with these pathogens is a lasting test for the water business. The supply of safe drinking-water includes the utilization of various hindrances to keep the passage and transmission of pathogens. The adequacy of these numerous hindrances ought to be checked by a program dependent on operational attributes and testing for microbial pointers of fecal defilement and in a few conditions real pathogens (Bell et al. 2016). Notwithstanding the always advancing scope of pathogens to consider, evaluating and overseeing such dangers requires the joining of data issued by an extensive variety of orders.

Research

Different structure manuals have utilized distinctive terms and characterizations to characterize diverse kinds of GI stormwater controls. In this examination we utilized the wording as utilized by the Environmental Protection Agency (EPA). The EPA records the accompanying as various kinds of GI Stormwater controls that can be utilized all through a watershed: Rain Gardens otherwise called bioretention cells, are shallow vegetated surfaces with a permeable inlay that gather and retain overflow from housetops, parking garages and roads. The vegetated surface is once in a while underlain by a layer of sand or rock that goes about as a capacity and invasion bed.

Bioswales are vegetated or mulched stormwater transport frameworks that give treatment and maintenance to the caught overflow. Bisowales are as a rule in type of an expansive, shallow, and delicately inclined channel with profound established vegetation that assistance in sifting the overflow water (Kennedy et al. 2015). The bioswales advance invasion and lessen the stream speed of stormwater overflow.

 Downspout Disconnection alludes to rerouting downspouts that pass on housetop overflows to deplete the gathered stormwater to different kinds of GI stormwater controls, for example, rain barrels, storages, or rain gardens (Tokarczyk et al. 2015). This GI control practice could have an extraordinary advantage for networks with consolidated sewer frameworks by preventing the stormwater from achieving sewer frameworks.

 Rainwater gathering are frameworks utilized for gathering and putting away stormwater for future reuse. These frameworks are regularly utilized with downspout separation to catch the housetop overflow in a rain barrel or reservoir. The put away water can be utilized for scene watering, or flushing toilets.

Planter Boxes are fundamentally the same as rain cultivate in their structure reason and they give stormwater administration advantages to keep, channel and penetrate the caught spillover. They may have open bottoms to permit moderate invasion of gathered stormwater to the basic soil layers. Grower boxes are particularly reasonable for space-restricted thick urban regions.

Green Roofs are building rooftops that are planted over a waterproof layer with developing media and vegetation. The vegetation gives precipitation penetration and evapotranspiration of gathered stormwater (Baldwin et al. 2017). Green rooftops are more appropriate for urban regions and can be utilized to diminish stormwater overflow from business, modern, and private structures. Green rooftops’ benefits are not constrained to stormwater administration as they can be useful in lessening the housetop temperatures also.

Urban Tree Canopy otherwise called urban ranger service, are utilized in urban zones to reestablish a portion of the advantages given by trees. Trees help to decrease and moderate stormwater by blocking precipitation in their leaves and branches. Non-stormwater administration advantages of tree coverings include: decrease of the warmth island impact, decrease of soil disintegration, soil adjustment, and decreasing the air contamination.

 Permeable Pavements are asphalt surfaces that penetrate, treat, and some of the time store stormwater overflow. Porous asphalts are built from a few materials, for example, pervious concrete, permeable black-top, and, porous solid pavers. Penetrable asphalts are utilized to invade the precipitation that falls straightforwardly on it or spillover from contiguous impenetrable surfaces (Fassman and Blackbourn 2012). Notwithstanding decreasing surface stormwater overflow, penetrable asphalts can trap suspended solids and channels contaminations from the overflow stormwater. In the following area porous asphalt frameworks are talked about in additional detail.

Scope of the Proposed Project

The most pervasive upkeep worry for porous asphalt frameworks is the potential stopping up of the pervious solid pores. As the stormwater penetrates into the penetrable asphalt surface, the fine materials and residue existing in the surface spillover are caught between the pores and openings of the asphalt surfaces. Stopping up will increment with age and utilize. The Stopping up limits the penetration execution of porous asphalt frameworks, yet can be reestablished by cleaning and keeping up of the surface (Belayneh et al. 2016). Stopping up is more effortlessly expelled not long after framing and before the fine dregs are compacted or moved to the voids at lower profundities, which are harder to clean. Diverse examinations report distinctive surface upkeep strategies and results in reestablishing the penetration limit of porous asphalts, yet all in all they demonstrate that a successful surface upkeep treatment can somewhat, or even completely, reestablish the underlying penetration limit. Distinctive surface cleaning strategies explored in past investigations incorporate clearing, vacuuming (or suction), utilizing high weight water fly, sonication, or a blend of these strategies. A consolidated high weight washing and vacuum cleaning technique was utilized to reestablish the penetration limit of two obstructed permeable black-top frameworks, matured 18 and 24 a long time. The connected strategy could halfway reestablish the penetration rates for 18-year-old permeable black-top yet had no impact that on the other framework (Piotrowski et al. 2015). Fassman and Blackbourn (2012) additionally report that weight washing effectively reestablished the invasion rates of a penetrable asphalt framework (PICP) by in excess of a request of extent. It must be noticed that weight washing could bring about washing the residue into the framework and in the long run dirtying the accepting waters Fassman & Blackbourn 2012).

The weight washing was likewise utilized on pervious solid frameworks that were stopped up by dirt and sand in a research facility think about. The outcomes demonstrate no critical increment on the penetration rates of asphalts, regardless of the visual investigation that inferred something else (Coughlin et al. 2012). Sansalone et al. report that vacuuming and sonication both can be utilized as compelling support techniques in recouping the surface penetration rates of porous asphalt frameworks (Sansalone et al. 2012). Liang et al. (2015) explored the viability of various support techniques in reestablishing the invasion limits of stopped up pervious solid areas. The strategies utilized in this examination included vacuum clearing, weight washing, and vacuum clearing pursued by weight washing. The results demonstrate that weight washing is more powerful than vacuum clearing and a mix of both gives off an impression of being the best (Chopra et al. 2010). Aftereffects of different investigations show that surface invasion limits of penetrable asphalt frameworks can in part or completely be reestablished, with choice of right cleaning technique. The adequacy of these strategies generally relies upon how stopped up the penetrable asphalts are and which surface upkeep strategy is chosen (Baladès et al. 1995). Normal support medicines are proposed as the most critical measures in holding the long haul penetration limit of porous asphalts (Al-Rubaei et al. 2013).

Research Methodology

To create cleanly safe drinking water from surface water sources, pathogens in the crude water must be essentially expelled or potentially inactivated by the water treatment forms. To advance the treatment forms for pathogen expulsion, and consequently give great quality consumable water in a temperate way, the capacity to screen and conceivably foresee the pathogen content of crude water is wanted by the water treatment industry. It could permit guidance ahead of time of changes in microbial fixations that require modification of process conditions. Accordingly, there are something like two conceivable advantages to be picked up from a measurable model that relates microbial and physicochemical information: (1) It gives data that the treatment plant could use to streamline its activity in the shortterm also, (2) it can offer pieces of information to the wellsprings of microbial tainting in the catchment, and henceforth give valuable data to long haul catchment administration hones.

There is an expanding center around enhancing water quality at the catchment scale with the end goal to guarantee safe drinking water at sensible treatment costs (Herrig et al. 2015). In any case, couple of methodical considers have been attempted to show what’s more, anticipate microbial crude water quality dependent on accessible physicochemical parameters. Among displaying approaches, various direct relapse investigation is a moderately straightforward factual technique used to inspect the relationship among factors. The present examination is pointed at creating relapse models that can conveniently gauge the substance of pointer creatures and norovirus/adenovirus in the crude water dependent on physicochemical information from the crude water admission at a treatment plant and the adjacent catchment region.

Following are the research questions:

• What are the issues faced by environment due to poor management of storm water?
• How regression model might help in checking performance of storm water filter?

This research include a model that might help in clogging behavior of non-vegetated filters for storm water filters with the help of experimental data. This might help in estimating life of the filter maintenance. Evaluating the hydrological execution of the penetrable asphalt frameworks was finished through gathered information from implanted electronic sensors and field estimations. Displaying methods were utilized to anticipate the progressions of water level inside the capacity layer under asphalt areas. The created model was utilized as an evaluation device to screen the hydrological execution of the two GI controls. At last the outcomes from the created model and other information investigation systems were utilized to track changes in penetration and exfiltration exhibitions of both porous asphalt frameworks. The penetration execution was seen to be a key segment influencing the hydrological execution of a porous asphalt framework. The penetration limit is constrained by stopping up shaped on the surface of the porous asphalt segment yet can be reestablished subsequent to applying an appropriate support treatment. The demonstrating exertion given comprehension of the exfiltration forms as the GI controls exchanged the caught stormwater overflow to basic and encompassing soil layers. Regular changes in framework execution were watched and ascribed to changes in unique thickness of water caused by variety of temperature. It was additionally seen that exfiltration execution is influenced by invasion limit of the framework.

Research reasoning is an idea of information assembling, utilized and investigated. Gathered information and data has been a wonder portrayed by the exploration rationality. Research logic has been of two sorts including positivism and interpretivism. Positivism logic manages real information and learning that has been picked up by perception and estimation. Positivism has been relied upon quantifiable perception prompting factual investigation. It has been centered around the empirics perspective of the human experience. It has been atomistic, ontological view for the world depending in the perception in a calculative view. Be that as it may, positivism has been autonomous type of concentrate that is not quite the same as human interests. It relies upon the theoretical methodology to the investigation (Ghosh, Das & Sinha 2015). It depends in rationale question of the analyst that includes appropriate logical estimation in the investigation. Then again, interpretivism manages the human enthusiasm for the investigation. Improvement in the interpretivism ponder has been dependably a scrutinize to positivism think about. It has been related with the philosophical activity of vision promotion can be utilized with assorted methodologies. There has no real perception dependent on figuring. In this logic, analyst goes about as a social mediator and discovering contrasts in human methodologies and perceptions. This exploration has utilized positivism reasoning over interpretivism. The determination has been founded on the prerequisites of the investigation. Positivism rationality has been relied upon the logical and verifiable way to deal with the information and data identified with the examination. Interpretivism has not been chosen in the examination as there is no true perception in the exploration.

Scientific Theory on Which Methodology is Based

The exploration approach has been concentrating on specific strides of gathering information with wide suppositions. Research approach has been relying upon different strategy that aides in helping information gathering and examination. Subsequently has been founded on nature of the exploration issue. Be that as it may, investigate approach has been partitioned into two sorts including deductive and inductive research approach (Ulrich et al. 2016). Deductive methodology has been centered around the speculation of the examination consider. It has been founded on existing hypotheses and models on the examination think about. It helps in making a connection between existing hypotheses and current writing. Deductive methodology helps in keeping up a basic way to deal with the advancement of the speculation in the exploration. The utilization of the deductive methodology has been keeping up a connection among variable and ideas of the examination think about. Deductive methodology has been helping in finishing the examination contemplate in a brief timeframe period. Inductive methodology helps in furnishing inductive thinking and is started with the hypotheses and perception towards the finish of research. It includes looking for examples that may help in giving a sharp way to deal with the exploration. The clarifications of the goals can’t be acquired with the assistance of inductive methodology. Inductive process does not centers around dismissing hypotheses and models dependent on the exploration point (?ojbaši? et al. 2016). It doesn’t depend in the exploration questions and destinations. This methodology goes for creating implications shape information gathering with the end goal to distinguish a few examples for building a hypothesis. It doesn’t rely upon existing hypotheses and models. Inductive methodology depends on learning knowledge.

Research configuration has been an orderly methodology that is utilized for leading logical investigation of the examination. It helps in synchronizing recognized segments of information and data with appropriate results. Research configuration has been of three kinds including logical, exploratory and graphic plan. Exploratory research configuration has been centering in investigating research questions and does not center in inferring any end and results from that. This structure has been utilized for characterizing the issues in the examination questions. It additionally helps in improving learning about research issues and questions. It doesn’t give appropriate convincing responses to the exploration questions. It has been noticed that exploratory research is the underlying examination, which shapes the premise of more indisputable research. It can even help in deciding the examination configuration, testing technique and information gathering strategy. Logical research configuration helps in endeavoring a few thoughts and associate them with legitimate thoughts and perspectives. Unmistakable research configuration has been a logical strategy that incorporate portraying and watching the conduct of research theme. Different logical techniques have been engaged with the clear strategy. It centers around the exploration targets and questions associated with the investigation. It helps in giving elucidating investigation of the exploration point including change administration and business process administration. Engaging examination plan strategy centers around the reason for the exploration. The examination has been following all the moral thought and qualities (Wu et al. 2015).

All information and data with respect to the examination has been remained careful and anchored. Information and data has been gathered from distributed diaries for guaranteeing the unwavering quality and legitimacy of the diaries. Diaries have appropriate creator names and distributing year. Information and data anchored under Data Protection Act 1998. The scientist has pursue the exploration morals and has not unveil personality of the members if the examination. There has been no cash taken from members through any frame. The specialist has done whatever it takes not to keep any sort of biasness in the exploration contemplate. The exploration theme has nt hurt any social and social convictions of the general public of any sort of networks. Information and data has been kept private and anchored. There has not been any sort of changes in the innovation of information and data of research.

Various Linear Regression (MLR) examination is a measurable technique that is utilized to analyze more nearly the connection between various autonomous (logical) factors and the subordinate (reaction) variable by fitting a straight (in the parameters) condition to watched information. The objective of MLR is to discover a condition that can anticipate the reliant variable as a component of a few autonomous factors (Mohammadi et al. 2015). The MLR condition, given n perceptions, is given by:

where y is the reliant variable (marker microorganisms furthermore, infections), x1, x2…, xk are the free factors (physicochemical parameters), furthermore, I files the n test perceptions, β0 is the y capture (the estimation of y when the majority of the informative factors x1, x2…, xk are equivalent to zero), β1, β2,  βk are the assessed various relapse coefficients (every relapse coefficient speaks to the adjustment in the needy variable with respect to a unit change in the separate free factor), also, the term ? is an irregular mistake term (Feitosa & Wilkinson, 2016). In the wake of fitting an MLR show (i.e. assessing the parameters from information), certain trial of theories about the model parameters are helpful in estimating model sufficiency. The general noteworthiness of the fitted MLR display can be tried with the alleged F-proportion of the disclosed to the unexplained fluctuation. The F-test tests whether the relapse show in general is critical or not through the investigation of differences (ANOVA). The F-proportion pursues a F dispersion with k-1 (model) and n-k (mistake) degrees of opportunity for the nominator and denominator separately, where n is number of perceptions what’s more, k is the quantity of parameters assessed. The test insights (F-test) is given by: where MSR is the mean square mistake of the relapse and MSE the mean square mistake of the residuals (Jayasooriya 2014). The theories for the F-test in MLR are: Invalid theory, H0: every one of the coefficients are equivalent to zero: β1 = β2 = … = βk = 0 This suggests none of the free factors are critical indicators of the reaction variable. Elective theory, HA: something like one coefficient isn’t equivalent to zero: βj ≠ 0 for somewhere around one j. This suggests something like one of the free factors is a critical indicator of the reaction variable. Translating results: If we dismiss H0, we finish up that the connection is noteworthy, which implies the model has logical or prescient control. In the event that we neglect to dismiss H0, we finish up that there isn’t any proof of logical control, which recommends that there is no reason for utilizing this model. The level of noteworthiness (α) was picked as 0.05.

These tests are valuable in deciding the prescient intensity of every one of the informative factors in the relapse demonstrate. The relapse show may be more valuable with the incorporation of extra logical factors or maybe similarly as helpful with the expulsion of at least one of the logical factors by and by in the model. A t-test on an individual relapse coefficient is a trial of its essentialness, given the nearness of all the other logical factors in the model. The t-test measurement is given by:

where Sβj is the standard mistake of the individual coefficient βj (Radcliffe et al. 2015). The measurement pursues a t-dissemination with n – p degrees of opportunity, where n is the quantity of perceptions furthermore, p is the quantity of indicators. The theories for the t-test in MLR are: Invalid theory, H0: The variable does not contribute in this model and ought to be avoided from the model, which is communicated as: βj = 0. Elective theory, HA: The option is that the logical variable does contribute and ought to stay in the model: βj ≠ 0. Translating results: If H0 rejected, one can finish up that the autonomous variable xj has illustrative or prescient power in the model. On the off chance that H0 isn’t rejected, one can infer that there isn’t any proof of informative intensity of free variable xj. That shows that there is no point in having xj in the model and one ought to consider evacuating it and re-running the relapse investigation. The level of importance (α) for the incorporation as well as evacuation of a logical variable in the model was set to 0.05.

The degree to which the autonomous factors clarify the conduct of the reliant variable can be inspected by utilizing two factual measures, to be specific R squared (R2) and balanced R squared (R2 adj). In relapse examination, the coefficient of assurance R2 is a factual measure of how great the relapse line assesses the genuine information focuses. The balanced R2 is an adjustment of R2 that alters for the quantity of autonomous factors in the model. In contrast to R2, the balanced R2 increments just if the new term really progresses the model. The R2 expect that each informative variable in the model clarifies variety in the needy variable. Along these lines, it might be deciphered as the level of clarified variety expecting that every single illustrative variable in the model effect the reliant variable (Weyhenmeyer et al. 2016). Conversely, the balanced R2 gives the level of variety clarified by just those illustrative factors that genuinely influence the reliant variable (just those informative factors that breeze through the t-test) and punishes the expansion of free factors that don’t have a place in the model. The Mean Squared Error (MSE) and its square root, Root Mean Squared Error (RMSE), measure the separation between the fitted line and information focuses. R squared, balanced R squared, MSE, and RMSE are figured by:

Task Name	Duration	Start	Finish
Regression modelling to predict performance of storm water filter	168 days	Mon 6/4/18	Wed 10/10/18
Study Initiation	11 days	Mon 6/4/18	Fri 6/29/18
Study Requirements Analysis	2 days	Mon 6/4/18	Tue 6/5/18
Approval of Research Topic from Supervisor	1 day	Wed 6/6/18	Wed 6/6/18
Development of Research Plan Charter / Document	9 days	Thu 6/7/18	Tue 6/19/18
Development of Research Framework	4 days	Mon 6/11/18	Thu 6/14/18
Prepare Draft Research Proposal	2 days	Fri 6/15/18	Mon 6/18/18
Research Planning	21 days	Tue 6/19/18	Tue 7/17/18
Formation of Research Team	2 days	Tue 6/19/18	Wed 6/20/18
Analysis of Research Requirement	1 day	Thu 6/21/18	Thu 6/21/18
Identification of Research Questions	4 days	Fri 6/22/18	Wed 6/27/18
Identify Scope of Research	4 days	Thu 6/28/18	Tue 7/3/18
Estimate Research Timeline	4 days	Wed 7/4/18	Mon 7/9/18
Allocation of Resources and Time for the Research	2 days	Tue 7/10/18	Wed 7/11/18
Initiation of Research	4 days	Thu 7/12/18	Tue 7/17/18
Research Development	26 days	Wed 7/18/18	Wed 8/22/18
Determination of Research Problems	4 days	Wed 7/18/18	Mon 7/23/18
Access to Necessary Media	1 day	Tue 7/24/18	Tue 7/24/18
Access to Online Library	1 day	Tue 7/24/18	Tue 7/24/18
Selection of Literary Sources	2 days	Wed 7/25/18	Thu 7/26/18
Literature Review	4 days	Fri 7/27/18	Wed 8/1/18
Collection of Necessary Data	10 days	Thu 8/2/18	Wed 8/15/18
Collection of Secondary Data	5 days	Thu 8/16/18	Wed 8/22/18
Data Analysis	8 days	Thu 8/23/18	Mon 9/3/18
Analysis of Primary Data	4 days	Thu 8/23/18	Tue 8/28/18
Analysis of Secondary Data	4 days	Wed 8/29/18	Mon 9/3/18
Research Evaluation	13 days	Tue 9/4/18	Thu 9/20/18
Evaluation of Data	6 days	Tue 9/4/18	Tue 9/11/18
Reflection on Research Undertaken	2 days	Wed 9/12/18	Thu 9/13/18
Documentation of Learning Outcomes	2 days	Wed 9/12/18	Thu 9/13/18
Issues Identification and Future Planning	5 days	Fri 9/14/18	Thu 9/20/18
Research Closure	14 days	Fri 9/21/18	Wed 10/10/18
Complete All Acitvities in Research	1 day	Fri 9/21/18	Fri 9/21/18
Documentation of Entire Research	10 days	Mon 9/24/18	Fri 10/5/18
Validation of the Research and Learning	2 days	Mon 10/8/18	Tue 10/9/18
Team Sign Off	1 day	Wed 10/10/18	Wed 10/10/18

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Paule-Mercado, M. A., Ventura, J. S., Memon, S. A., Jahng, D., Kang, J. H., & Lee, C. H. (2016). Monitoring and predicting the fecal indicator bacteria concentrations from agricultural, mixed land use and urban stormwater runoff. Science of the Total Environment, 550, 1171-1181.

Piccolroaz, S., Calamita, E., Majone, B., Gallice, A., Siviglia, A., & Toffolon, M. (2016). Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches. Hydrological Processes, 30(21), 3901-3917.

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Radcliffe, D. E., Reid, D. K., Blombäck, K., Bolster, C. H., Collick, A. S., Easton, Z. M., … & Larsbo, M. (2015). Applicability of models to predict phosphorus losses in drained fields: A review. Journal of environmental quality, 44(2), 614-628.

Schenone, A. V., Conte, L. O., Botta, M. A., & Alfano, O. M. (2015). Modeling and optimization of photo-Fenton degradation of 2, 4-D using ferrioxalate complex and response surface methodology (RSM). Journal of environmental management, 155, 177-183.

Sihag, P., Jain, P., & Kumar, M. (2018). Modelling of impact of water quality on recharging rate of storm water filter system using various kernel function based regression. Modeling earth systems and environment, 4(1), 61-68.

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Ulrich, W., Zaplata, M. K., Winter, S., Schaaf, W., Fischer, A., Soliveres, S., & Gotelli, N. J. (2016). Species interactions and random dispersal rather than habitat filtering drive community assembly during early plant succession. Oikos, 125(5), 698-707.

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Wu, H., Yang, R., Li, R., Long, C., Yang, H., & Li, A. (2015). Modeling and optimization of the flocculation processes for removal of cationic and anionic dyes from water by an amphoteric grafting chitosan-based flocculant using response surface methodology. Environmental Science and Pollution Research, 22(17), 13038-13048.