MARSOL - UPC...Demo Sites (including infiltration ponds and deep injection wells). We expect ......

The MARSOL project has received funding from the European Union's Seventh Framework Programme for Research, Technological Development and Demonstration under grant agreement no 619120.

MARSOL

Demonstrating Managed Aquifer Recharge as a Solution to Water Scarcity and Drought

MAR-RISKAPP. Assessment tool for risk evaluation of Managed Aquifer Recharge facilities

Deliverable No. Deliverable 16.4

Version Version 1

Version Date 19.09.2016

Author(s) Paula Rodríguez-Escales, Arnau Canelles

Xavier Sanchez-Vila, Albert Folch, Daniel

Fernàndez-Garcia, Carme Barba

Hydrogeology Group (UPC)

Contact: [email protected]

Dissemination Level PU

Status Final

MARSOL Deliverable D16.4

2

Contents:

1 Introduction ......................................................................................................................... 6

1.1 Objectives .................................................................................................................... 6

1.2 Outline .......................................................................................................................... 6

2 MAR-RISKAPP development ............................................................................................. 7

3 Application to the MARSOL sites ................................................................................... 17

3.1 Algarve (Portugal) ...................................................................................................... 18

3.2 Los Arenales (Spain) ................................................................................................. 21

3.3 Llobregat (Spain)........................................................................................................ 24

3.4 Brenta River (Italy) ..................................................................................................... 27

3.5 Serchio River (Italy) ................................................................................................... 30

3.6 Menashe (Israel) ........................................................................................................ 32

3.7 South Malta ................................................................................................................ 36

4 Evaluation if the risk perception of MARSOL demos sites .......................................... 39

5 Extension to risk evaluations: Llobregat site ................................................................ 44

5.1 Prior values ................................................................................................................ 44

5.2 Real values and comparison with risk perception ...................................................... 49

6 Conclusions ...................................................................................................................... 54

APPENDIX A: Technical issues of MAR-RISK APP. The code and developing issues...... 55

6.1 Macro usage .............................................................................................................. 56

6.2 Macro programming code (theoretical explanation) .................................................. 57

6.3 Macro programming code practical application ......................................................... 58

6.4 Non-VBA programming Excel functions .................................................................... 62

APPENDIX B: STATE OF ART OF REPORTED MAR PROBLEMS ........................................ 64


3

List of Figures and Tables

Figure 2.1. Flowchart for the main program of the MAR-RISKAPP. .............................. 8

Figure 2.2. Home layout visualization. .......................................................................... 9

Figure 2.3. Input layout visualization. .......................................................................... 10

Figure 2.4. Non-technical constraints - Design and construction, sheet visualization. . 10

Figure 2.5. Technical constraints - Design and construction, sheet visualization. ........ 11

Figure 2.6. Non-technical constraints – Operation, sheet visualization. ....................... 11

Figure 2.7. Technical constraints – Operation, sheet visualization. ............................. 12

Figure 2.8. Results (upper part) sheet visualization..................................................... 13

Figure 2.9. Results (bottom part) sheet visualization. .................................................. 13

Figure 2.10. Graphical results sheet visualization. ...................................................... 14

Figure 2.11. Operational pivot-table results sheet visualization. .................................. 15

Figure 2.12. Design and construction pivot-table results sheet visualization. .............. 15

Figure 2.13. Operational fault-tree results sheet visualization. .................................... 16

Figure 2.14. Design and construction sheet visualization. ........................................... 16

Figure 3.1. Operational survey part 1, Demo Site 2, Algarve (Portugal). ..................... 18



Figure 3.4. Operational survey part 1, Demo Site 3, Los Arenales (Spain). ................. 21



Figure 3.7. Operational survey part 1, Demo Site 4, Llobregat (Spain). ...................... 24



Figure 3.10. Operational survey part 1, Demo Site 5, Brenta River (Italy). .................. 27



Figure 3.13. Operational survey part 1, Demo Site 6, Serchio River (Italy). ................. 30


4



Figure 3.16. Operational survey part 1, Demo Site 7, Menashe (Israel). ..................... 33



Figure 3.19. Operational survey part 1, Demo Site 8, South Malta. ............................. 36



Figure 4.1. Fault tree with the risk perception of Algarve Demo Sites. ........................ 41

Figure 4.2. Fault tree with the risk perception of Arenales Demo Sites........................ 41

Figure 4.3. Fault tree with the risk perception of Brenta Demo Site. ............................ 42

Figure 4.4. Fault tree with the risk perception of Serchio Demo Site. .......................... 42

Figure 4.5. Fault tree with the risk perception of Menashe Demo Site. ........................ 43

Figure 4.6. Fault tree with the risk perception of South Malta Demo Site. ................... 43

Figure 5.1. Results of the failure risk of Llobregat Demo Site at operation. ................. 51

Table 5. 1. Priority criteria for Llobregat Demo Site at design and construction ........... 45

Table 5. 2. Priority criteria for Llobregat Demo Site at operation ................................. 46

Table 5. 3. Comparison of perception of risk (high/medium/low) with calculated risk... 52


5

EXECUTIVE SUMMARY

In this Deliverable we finalize the work on the development of an assessment

tool for risk evaluation linked to Managed Aquifer Recharge activities. The tool

is devised to be applicable to existing as well as to sites that are only in the

stage of design. The tool consists of a user-friendly tool, programmed in

Microsoft Excel®. Based on the general configuration of the site and the suite of

objectives, the tool develops first the potential failure paths and tells the

managers which are the relevant topics to address in order to properly evaluate

risk associated to MAR practices. The tool presents all the possible failure paths

in a color code, which indicates the facility manager the areas to concentrate

efforts and resources upon in order to design potential mitigation effort and

eventually to reduce such probability to acceptable values.

The tool has been applied to all MARSOL Demo Sites. We have collected the

questionnaires that were presented in Deliverable 16.3 duly filled by some

representative of each individual Demo Site. The direct application of the tool

provides a visualization of the most significant elements that constitute the

larger contribution to risk of each individual facility.

Finally, and as a visualization example, we provide a quantitative assessment of

risk corresponding to the Sant Vicenç dels Horts Test Site based on the

extension of the tool to provide an estimate of risk from site knowledge.


6

1 Introduction

1.1 Objectives

This is the fourth and final product (Deliverable 16.4) in the Work Package entitled Technology Assessment and Risk. It can be synthesized in one main

objective: Developing a Risk Assessment Tool (MAR-RISKAPP) to evaluate the

risk of failure in a Managed Aquifer Recharge (MAR) facility. This risk

assessment tool is based on the previous fault trees developed in Deliverable

16.1 and in the survey forms developed in Deliverable 16.3. The MAR-

RISKAPP is aimed at creating an interactive framework for evaluating the

perception of the risk (and eventually the risk itself) of a MAR facility. The tool is

general and can be applied in any recharge facility existing or to be

implemented in the future (that is, still in the phase of design).

The tool has been applied to all the recharge facilities constituting the MARSOL

Demo Sites (including infiltration ponds and deep injection wells). We expect

that the final user of the tool will be the water manager of each facility, but it can

also be used by stakeholders or scientists to understand and to analyze the

most critical points in each facility that could contribute to risk perception.

1.2 Outline

In Section 2, we explain the main technical issues of the MAR-RISKAPP

application, as well as the main instructions for users. This includes a thorough

explanation of the input/output (User’s Guide). Section 3 compiles the results of

the surveys of the MARSOL Demo Sites, based on the questionnaires provided

in Deliverable 16.3. These surveys are then used to provide the risk perception

of the individual Demo Sites. Finally, Section 4 provides the results of risk

assessment applied to the Llobregat site, where the qualitative description is

transferred to a quantitative evaluation.


7

2 MAR-RISKAPP development

The MAR-RISKAPP was developed using Microsoft Excel®, specifically the

module Developer. This module is based mainly on the usage of Excel macros,

which are usually short programing code lines that are used to give some kind

of orders to the program in order to do some specific calculations or to set

automatically some kind of properties for the working environment (among other

kind of possibilities). Macros are programmed with the Visual Basic Editor

(VBA) tool.

The MAR-RISKAPP has been structured in four main steps (Excel Worksheets):

1) HOME, 2) INPUT, 3) RESULTS and 4) GRAPHICAL RESULTS. The main

flowchart of the application is summarized in Figure 2.1.

The application stars with the step HOME. The program uses a worksheet

based layout. This means that the program uses an interface that works by

changing hiding and blocking properties of the cell present in the sheet (also by,

inserting shapes, changing cell colors, etc.). This first stage shows the tool

name, the creators and the main institutions involved in it, with a clear indication

that the tool was developed within the framework of project MARSOL. From this

starting point there are two possible ways to proceed: 1) HELP (which sends

the user to an Excel sheet where a general explanation of the tool and its

operational set can be found), and 2) START (which sends the user to the

second step of the tool – INPUT).


8

Figure 2.1. Flowchart for the main program of the MAR-RISKAPP.

HOME (BEGGINING)

INPUT (PROCESS)

INPUT FILLED? (DECISION)

NON-TECH.CONSTRAINTS DC (MANUAL INPUT)

TECHNICAL CONSTRAINTS DC (MANUAL INPUT)

NON-TECH. CONSTRAINTS OP (MANUAL INPUT)

TECHNICAL CONSTRAINTS OP (MANUAL INPUT)

A PRIORI CRITERIA (STORED DATA)

HELP (DOCUMENT)

RESULTS (PROCESS)

RESULTS (OUTPUT)

GRAPHICAL RESULTS (ENDING)

AUTOMATIC RESULTS

ADECUATE? (DECISION)

RESULTS (MANUAL INPUT)

AUTOMATIC RESULTS NOT ADECUATE BECAUSE USER

WANTS TO MANUALLY

INTRODUCE THEM (DECISION)

TABLE RESULTS OP (OUTPUT)

TABLE RESULTS DC (OUTPUT)

FAULT TREE RESULTS OP (OUTPUT)

FAULT TREE RESULTS DC (OUTPUT)

YES

YES

YES NO

NO

NO


9

Figure 2.2. Home layout visualization.

The second step of the tool is the INPUT. At this point, the user has to fill-up the

different risk perception of non-technical and technical issues (the Input sheet

can be seen in Figure 2.2). This step implies that data has to be filled in four

different sheets: 1) NON-TECHNICAL CONSTRAINTS - DESIGN AND

CONSTRUCTION (Figure 2.3), 2) TECHNICAL CONSTRAINTS - DESIGN

AND CONSTRUCTION (Figure 2.4), 3) NON-TECHNICAL CONSTRAINTS –

OPERATION (Figure 2.5) and 4) TECHNICAL CONSTRAINTS – OPERATION

(Figure 2.6). These four sheets have a similar format (identical to the survey

from provided in Deliverable 16.3), where the user has to answer the different

points of the survey by writing an “X” on the corresponding boxes.

Only one “X” has to be written at each line, as the person filling the sheet must

select one of the following four categories of risk: no risk, high risk, medium risk,

or low risk. In the Input worksheet, there is a button of instructions; when this

button is clicked a pop-up text box is shown (which indicates the order that the

four input sheets should be filled and some explanation about their meaning). In

addition, each input sheet has its own instruction button, which explains the

user by using text and images, how to fill the surveys from each input

worksheet. Finally, when all the input sheets have been filled, the user can run

the Results button in order to go the RESULTS sheet (or if the user need help,


10

the Help button can bring him/her to the Help sheet, or if the user wants to go

back to the HOME sheet, he/she can press the BACK TO HOME button).

Figure 2.3. Input layout visualization.

Figure 2.4. Non-technical constraints - Design and construction, sheet

visualization.


11

Figure 2.5. Technical constraints - Design and construction, sheet visualization.

Figure 2.6. Non-technical constraints – Operation, sheet visualization.


12

Figure 2.7. Technical constraints – Operation, sheet visualization.

The third step is the RESULTS. This part shows the user the numerical results

of the risk assessment (Figure 2.7). The risk assessment is calculated within the

same Results sheet and by applying the values present in the A PRIORI

CRITERIA sheet. Note that the a priori criteria are site dependent. For that, the MAR facility manager must define each a priori criteria based on his/her

knowledge about the site and its particular idiosyncrasies. As a default, a priori

values are provided in MAR-RISKAPP based on experience from a number of

sites worldwide. The prior values are probability numbers (ranging in the interval

[0,1]) that indicate the probability that the MAR facility fails due to that particular

individual event.

The initial prior values are presented in the DEFAULT VALUE column, and are

blocked to changes (i.e., the user cannot update them). Next to this column,

there is the CATEGORY DEFAULT VALUES column, which indicates the risk

category that the user selected in the INPUT sheets. There is also a third

column called USER VALUES, that can be (and indeed should be) modified by

the user in order to change the specific risk values (from the DEFAULT

VALUES column) if the user has better data than the default calculations for a

specific study site. This third column is the one that will be used in the following


13

calculations, so the user has to be fully aware that its modification has direct

consequences on the results. The tool indicates the user if these USER

VALUES have been modified or not from the default ones (this is done by filling

the USER VALUES cells with red color, to indicate that both columns have the

same values). Similarly to the other steps, a HELP button can be found, and

also some instructions pop-up (Figure 2.8) if the instructions button is clicked.

The user can change some data from the INPUT by clicking the BACK TO

INPUT button. If everything is correct, the user can go to the next step by

clicking the GRAPHICAL RESULTS button.

Figure 2.8. Results (upper part) sheet visualization.

Figure 2.9. Results (bottom part) sheet visualization.


14

The fourth step of the MAR-RISKAPP is the graphical results (Figure 2.9),

displaying the numerical results shown in the previous step into graphs and

tables. This step is divided into four points: 1) Operational pivot-table results

(Figure 2.10), 2) Design and construction pivot-table results (Figure 2.11), 3)

Operational fault tree (Figure 2.12) and 4) Design and construction fault tree

(Figure 2.13). As in the other steps, there is a button with instructions, only if the

user needs some help or orientation with the results from this step. For both

pivot-tables, the results are structured in four categories of risk (high, medium,

low, and no-risk). Inside each category, risk values are displayed in decreasing

order (from high to low risk values). Also, both pivot-tables have a button to go

back to the graphical results main sheet. For both fault trees, each point from

the survey is presented by using a rectangle. For each point, risk value is

showed on the bottom-left part of the rectangle and also is colored according to

risk categories. Finally, both fault-trees have a button to go back to the

graphical results main sheet and a button to print the fault tree in a PDF file.

Figure 2.10. Graphical results sheet visualization.


15

Figure 2.11. Operational pivot-table results sheet visualization.

Figure 2.12. Design and construction pivot-table results sheet visualization.


16

Figure 2.13. Operational fault-tree results sheet visualization.

Figure 2.14. Design and construction sheet visualization.


17

3 Application to the MARSOL sites

The surveys provided in Appendix 4 of Deliverable 16.3 were distributed and

filled by representative persons for each MARSOL Demo Site. Gathering

information from experts in each one of the sites ensures the optimal knowledge

about these places. For completeness and visibility, the filled surveys from all

the demonstration sites have been gathered together in this deliverable (only

current phase, mostly operation).


18

3.1 Algarve (Portugal)

Operational:

Figure 3.1. Operational survey part 1, Demo Site 2, Algarve (Portugal). From the survey, CF represents Campina de Faro and QS represents Querença – Silves.


19

Figure 3.2. Operational survey part 2, Demo Site 2, Algarve (Portugal).


20

Figure 3.3. Operational survey part 3, Demo Site 2, Algarve (Portugal).


21

3.2 Los Arenales (Spain)

Operational:

Figure 3.4. Operational survey part 1, Demo Site 3, Los Arenales (Spain).


22



23



24

3.3 Llobregat (Spain)

Operational:

Figure 3.7. Operational survey part 1, Demo Site 4, Llobregat (Spain).


25



26



27

3.4 Brenta River (Italy)

Operational:

Figure 3.10. Operational survey part 1, Demo Site 5, Brenta River (Italy).


28



29



30

3.5 Serchio River (Italy)

Operational:

Figure 3.13. Operational survey part 1, Demo Site 6, Serchio River (Italy).


31



32


3.6 Menashe (Israel)

Operational:


33

Figure 3.16. Operational survey part 1, Demo Site 7, Menashe (Israel).


34



35



36

3.7 South Malta

Operational:

Figure 3.19. Operational survey part 1, Demo Site 8, South Malta.


37



38



39

4 Evaluation if the risk perception of MARSOL Demo Sites

Once the surveys were answered, we compared the risk perception of MAR

failure in the different MARSOL Demo sites. The sites were evaluated in its

current phase (mainly operation). The Llobregat Demo site (Spain) is fully

discussed (the risk perception and the calculated risk) in section 5.

In the Algarve Demo sites (in operation, Figure 4.1), the failure risk perception

of the recharge site was between medium and high. The order of the risk

perception was legal constraints, not enough water to recharge, structural

damage, governance, social unacceptance, and economical constraints. On the

other hand, there is no perception of risk in the chemical/biological quality of

recharged water, neither in the potential pollution due to recharge.

In the Arenales Demo sites (in operation, Figure 4.2), the general risk

perception of MAR failure is high. This is because both perception of non-

technical and technical issues is high. The most critical issues are the legal

aspects (mainly at national level), the risk of droughts increasing and the risk of

pollution due to nutrients (mainly nitrate). On the other hand, the main issue of

medium risk perception is related to clogging aspects.

In the Brenta Demo site (in operation, Figure 4.3), the general risk perception of

MAR failure is between medium and high. The highest risk perception is related

to non-technical issues: non-technical knowledge, lack of coordination among

stakeholders, and problems related to health legislation. On the other hand, a

low perception of risk is related to the other aspects of legislation. The rest of

evaluated issues do not have any risk perception.

In the Serchio Demo Site (in operation, Figure 4.4), the general risk perception

of MAR failure is high. The highest perception of risk is in non-technical issues

(health legislation aspects, non-technical knowledge and lack of coordination

among stakeholders) and chemical quality aspects of recharged water and

groundwater (mainly related to Emerging Organic Compounds). Medium risk


40

perception is mainly about other aspects of quality (nutrients and metals), and

low perception about other legislation aspects, flooding and clogging.

In the Menashe Demo Site (in operation, Figure 4.5), the general risk perception

of MAR failure is medium. The highest risk is only related to the potential use of

recharged water by domestic use. Medium perception risk is related to aspects

of terrorism/vandalism and high installation cost. Low risk is associated to non-

technical knowledge, social risk about bad perception of MAR (cost and

effectiveness), clogging risk by compaction, chemical risk by Emerging Organic

Compounds, flooding, and aquifer dissolution.

In the South-Malta Demo Site (in operation, Figure 4.6), the risk perception of

MAR failure is medium. The highest perception is related to legislation aspects

and with specific targets as the correct operation of seawater barriers. Low risk

perceptions are related to structural damages (like pipe breakage), with the lack

of coordination among stakeholders and with the physical clogging.

After the review of the different perceptions, we can conclude that the general

perception of risk in non-technical issues are related to legal aspects (mainly

health legislation), also to the lack of technical knowledge and to the lack of

coordination among stakeholders. Related to the technical aspects the most

important aspect is about clogging risk but also about chemical aspects like

nutrients or Emerging Organic Compounds.


41

Figure 4.1. Fault tree with the risk perception of Algarve Demo Sites.

Figure 4.2. Fault tree with the risk perception of Arenales Demo Sites.


42

Figure 4.3. Fault tree with the risk perception of Brenta Demo Site.

Figure 4.4. Fault tree with the risk perception of Serchio Demo Site.


43

Figure 4.5. Fault tree with the risk perception of Menashe Demo Site.

Figure 4.6. Fault tree with the risk perception of South Malta Demo Site.


44

5 Extension to risk evaluations: Llobregat Site

5.1 Prior values In order to calculate the failure risk (in probabilistic terms) of Llobregat MAR

facility, we have defined a priori criteria. As a first step, these priors were

defined by an interdisciplinary expert team that has been working in this Demo

Site for a time of 2 to 6 years. The team was formed by civil engineers,

geotechnical engineers, geologists, and environmental scientists. Furthermore,

after the expert decision, these values were checked and benchmarked to a

large list of problems described in international literature (see Appendix B).

These priors can be defined using other tools like numerical models, historical

review etc. The MAR-RISKAPP can be adapted to these other tools by

modifying the priors manually or by coupling the output of numerical models

with the tool1.

The a priori criteria (adapted from those in the Llobregat site) are displayed in

Table 5.1 (Design and Construction) and Table 5.2 (Operational). Note that

there is a value for each event described and answered in the survey (see

section 3), with a total of 40 for design and construction phase and 66 for

operation. The expert decision was only focused on the lower events

participating in the fault tree; risk values for higher levels (those implying two or

more events and upper) have been computed from Boolean algebra (see

Deliverable 16.1).

We want to remark that these criteria are site specific and should be defined

by an interdisciplinary expert team. After answering the survey, users should

evaluate and define their own criteria. In case that the default values are

accepted by the user, no action is needed and then MAR-RISKAPP will

highlight these values in red (as a warning that the value was unchanged on

purpose). Expert decision should only be applied to the lower events in the fault

tree.

1 Currently, the coupling is not developed. The coupling of numerical models developed by Excel to MAR-RISKAPP is not expected to be difficult, the coupling to other codes would require more developing efforts.


45

Table 5. 1. Priority criteria for the Llobregat Demo Site at design and construction

DESIGN AND CONSTRUCTION OF A MAR FACILITY

DEFAULT VALUES

CATEGORY DEFAULT VALUES

USER VALUES

1. NON-TECHNICAL CONSTRAINTS 0.92 FALSE 0.92 1.1 Legal constraints 0.78 FALSE 0.78 1.1.1 Territorial constraints 0.56 FALSE 0.56 1.1.1.1 European 0.10 LOW RISK 0.10 1.1.1.2 National 0.30 MEDIUM RISK 0.30 1.1.1.3 Regional/Local 0.30 MEDIUM RISK 0.30 1.1.2 Scope of legislation 0.50 FALSE 0.50 1.1.2.1 Health legislation 0.50 HIGH RISK 0.50 1.1.2.2 Others 0.00 NO RISK 0.00 1.2 Economic constraints 0.30 FALSE 0.30 1.2.1 Macroeconomic constraints 0.10 MEDIUM RISK 0.10 1.2.2 Microeconomic constraints 0.22 FALSE 0.22 1.2.2.1 Not enough water to recharge due to other economical uses 0.07 FALSE 0.07

1.2.2.1.1 Industrial use 0.01 LOW RISK 0.01 1.2.2.1.2 Agricultural use 0.05 MEDIUM RISK 0.05 1.2.2.1.3 Domestic use 0.01 LOW RISK 0.01 1.2.2.2 Cost restriction 0.07 FALSE 0.07 1.2.2.2.1 Low price of water 0.01 LOW RISK 0.01 1.2.2.2.2 High installation cost 0.01 LOW RISK 0.01 1.2.2.2.3 High maintenance cost/maintenance requirements 0.05 MEDIUM RISK 0.05

1.2.2.3 Lack of private/public funding 0.10 MEDIUM RISK 0.10 1.3 Social unacceptance 0.12 FALSE 0.12 1.3.1 Health risk perception 0.01 LOW RISK 0.01 1.3.2 High cost perception 0.05 MEDIUM RISK 0.05 1.3.3 Behavioral requirements 0.01 LOW RISK 0.01 1.3.4 Children surveillance 0.05 MEDIUM RISK 0.05 1.3.5 Fair distribution of treated water 0.01 LOW RISK 0.01 1.3.6 Perception of effectiveness 0.00 NO RISK 0.00 1.4 Governance 0.43 FALSE 0.43 1.4.1 Lack of coordination 0.40 HIGH RISK 0.40 1.4.2 Non-technical knowledge 0.05 LOW RISK 0.05

2. TECHNICAL CONSTRAINTS 0.41 FALSE 0.41 2.1 Source water availability and right of access (if YES continue) 0.41 FALSE 0.41

2.1.1 Low quality input water (if YES continue) 0.27 FALSE 0.27 2.1.1.1 Sanitary/biological restrictions (e.g. due the pathogens) 0.05 LOW RISK 0.05

2.1.1.2 Physical restrictions (if YES continue) 0.40 FALSE 0.40


46

Table 5. 1. Priority criteria for the Llobregat Demo Site at design and construction

DESIGN AND CONSTRUCTION OF A MAR FACILITY

DEFAULT VALUES


USER VALUES

2.1.1.2.1 Turbidity/particles 0.40 HIGH RISK 0.40 2.1.1.3 Chemical restrictions (if YES continue) 0.11 FALSE 0.11 2.1.1.3.1 Metals (e.g. arsenic, manganese) 0.00 NO RISK 0.00 2.1.1.3.2 Salinity and sodicity 0.01 LOW RISK 0.01 2.1.1.3.3 Nutrients (nitrogen, phosphorous) 0.05 MEDIUM RISK 0.05 2.1.1.3.4 Organic chemicals (pollutants, EOCs) 0.05 MEDIUM RISK 0.05 2.1.1.3.5 Radionuclides 0.00 NO RISK 0.00 2.1.2 Water scarcity (if YES continue) 0.14 FALSE 0.14 2.1.2.1 River regulation 0.05 LOW RISK 0.05 2.1.2.2 Climate (if YES continue) 0.05 FALSE 0.05 2.1.2.2.1 Droughts and Rainfall event periodicity 0.05 LOW RISK 0.05 2.1.2.3 Availability of water from waste water treatment plant 0.05 LOW RISK 0.05

2.1.2.4 Availability of water from desalination plant 0.00 NO RISK 0.00 2.1.3 Right of access 0.05 LOW RISK 0.05 2.2 Hydrogeological assessment (if YES continue) FALSE 2.2.1 Hydraulic properties FALSE 2.2.1.1 Risk of clogging 0.40 HIGH RISK 0.40 2.2.1.2 Risk of low water storage 0.05 LOW RISK 0.05 2.2.1.3 Risk of low infiltration rate 0.40 HIGH RISK 0.40 2.2.2 High thickness and not shallow aquifer 0.00 NO RISK 0.00 2.2.3 Regional hydrogeology (does the regional balance allow the MAR facility?) LOW RISK 2.3 Lack of infrastructures 0.30 FALSE 0.30 2.3.1 Lack of potential available land 0.30 MEDIUM RISK 0.30 2.3.2 Lack of structure for capturing the water 0.00 LOW RISK 0.00 2.3.3 Lack of water pre-treatment infrastructures 0.00 LOW RISK 0.00 2.3.3 Lack of recovery wells

Table 5. 2. Priority criteria for the Llobregat Demo Site at operation

OPERATIONAL PROCESSES DEFAULT VALUES


USER VALUES

1. NON-TECHNICAL CONSTRAINTS 0.80 FALSE 0.80 1.1 Legal constraints 0.23 FALSE 0.23 1.1.1 Territorial constraints 0.14 FALSE 0.14 1.1.1.1 European 0.05 LOW RISK 0.05 1.1.1.2 National 0.05 LOW RISK 0.05 1.1.1.3 Regional/Local 0.05 LOW RISK 0.05


47




USER VALUES

1.1.2 Scope of legislation 0.10 FALSE 0.10 1.1.2.1 Health legislation 0.05 LOW RISK 0.05 1.1.2.2 Others 0.05 LOW RISK 0.05 1.2 Economic constraints 0.33 FALSE 0.33 1.2.1 Macroeconomic constraints 0.05 LOW RISK 0.05 1.2.2 Microeconomic constraints 0.29 FALSE 0.29 1.2.2.1 Not enough water to recharge due to other economical uses 0.11 FALSE 0.11

1.2.2.1.1 Industrial use 0.05 MEDIUM RISK 0.05 1.2.2.1.2 Agricultural use 0.05 MEDIUM RISK 0.05 1.2.2.1.3 Domestic use 0.01 LOW RISK 0.01 1.2.2.2 Cost restriction 0.21 FALSE 0.21 1.2.2.2.1 Low price of water 0.01 MEDIUM RISK 0.01 1.2.2.2.2 High installation cost 0.01 MEDIUM RISK 0.01 1.2.2.2.3 High maintenance cost/maintenance requirements 0.20 HIGH RISK 0.20

1.2.2.3 Lack of private/public funding FALSE LOW RISK FALSE 1.3 Social unacceptance 0.34 FALSE 0.34 1.3.1 Health risk perception 0.05 LOW RISK 0.05 1.3.2 High cost perception 0.05 LOW RISK 0.05 1.3.3 Behavioral requirements 0.05 LOW RISK 0.05 1.3.4 Children surveillance 0.10 MEDIUM RISK 0.10 1.3.5 Fair distribution of treated water 0.10 MEDIUM RISK 0.10 1.3.6 Perception of effectiveness 0.05 LOW RISK 0.05 1.4 Governance 0.43 FALSE 0.43 1.4.1 Lack of coordination 0.40 HIGH RISK 0.40 1.4.2 Non-technical knowledge 0.05 LOW RISK 0.05

2. TECHNICAL CONSTRAINTS 1.00 FALSE 1.00 2.1 Structural Damages (if YES continue) 0.12 FALSE 0.12 2.1.1 Flooding 0.01 LOW RISK 0.01 2.1.2 Natural hazards (e.g. earthquake) 0.00 LOW RISK 0.00 2.1.3 Terrorism activities/Vandalism 0.05 LOW RISK 0.05 2.1.4 Civil work failures (if YES continue) 0.07 FALSE 0.07 2.1.4.1 Slope stability 0.01 LOW RISK 0.01 2.1.4.2 Pipe breakage 0.05 LOW RISK 0.05 2.1.4.3 Others 0.01 LOW RISK 0.01 2.1.5 Aquifer dissolution (e.g. in karstic aquifer) 0.00 NO RISK 0.00 2.2 Not enough water recharged (if YES continue) 0.91 FALSE 0.91 2.2.1 Low quality water (if YES continue) 0.50 FALSE 0.50 2.2.1.1 Sanitary/biological restrictions (e.g. due the 0.10 MEDIUM RISK 0.10


48




USER VALUES

pathogens) 2.2.1.2 Physical restrictions (if YES continue) 0.40 FALSE 0.40 2.2.1.2.1 Turbidity/particles 0.40 HIGH RISK 0.40 2.2.1.3 Chemical restrictions (if YES continue) 0.07 FALSE 0.07 2.2.1.3.1 Metals (e.g. arsenic, manganese) 0.00 NO RISK 0.00 2.2.1.3.2 Salinity and sodicity 0.01 LOW RISK 0.01 2.2.1.3.3 Nutrients (nitrogen, phosphorous) 0.01 LOW RISK 0.01 2.2.1.3.4 Organic chemicals (pollutants, EOCs) 0.05 MEDIUM RISK 0.05 2.2.1.3.5 Radionuclides 0.00 NO RISK 0.00 2.2.2 Water scarcity (if YES continue) 0.59 FALSE 0.59 2.2.2.1 Climate (if YES continue) 0.20 FALSE 0.20 2.2.2.1.1 Droughts and Rainfall event periodicity 0.20 MEDIUM RISK 0.20 2.2.2.2 Waste water treatment plant failure 0.20 MEDIUM RISK 0.20 2.2.2.3 Desalination plant failure 0.20 MEDIUM RISK 0.20 2.2.2.4 River regulation 0.20 MEDIUM RISK 0.20 2.2.3 Clogging (if YES continue) 0.54 FALSE 0.54 2.2.3.1 Physical clogging (if YES continue) 0.40 FALSE 0.40 2.2.3.1.1 Failure deposition pond (particles from diverted water) 0.00 FALSE 0.00 2.2.3.1.1.1 Pipe filter fails 0.00 NO RISK 0.00 2.2.3.1.1.2 Residence time 0.00 NO RISK 0.00 2.2.3.1.2 Source fine particles (generation inside MAR facility) 0.40 HIGH RISK 0.40

2.2.3.1.3 Transport sedimentation (erosion or deposition from recharge pond) 0.00 FALSE 0.00 2.2.3.1.3.1 Deposition 0.00 NO RISK 0.00 2.2.3.1.3.2 Erosion 0.00 NO RISK 0.00 2.2.3.2 Bioclogging 0.10 HIGH RISK 0.10 2.2.3.3 Chemical clogging (if YES continue) 0.03 FALSE 0.03 2.2.3.3.1 Evaporation (excess) 0.01 LOW RISK 0.01 2.2.3.3.2 Water mixtures 0.01 LOW RISK 0.01 2.2.3.3.3 Microbial population catalysis 0.01 LOW RISK 0.01 2.2.3.4 Compaction 0.10 MEDIUM RISK 0.10 2.2.3.5 Generation of gas (e.g. bubble formation) (if YES continue) 0.03 FALSE 0.03 2.2.3.5.1 Physical Motives 0.00 LOW RISK 0.00 2.2.3.5.2 Bacterial processes 0.03 LOW RISK 0.03 2.2.3.5.3 Inappropriate design 0.00 LOW RISK 0.00 2.3 Unacceptable quality of water at sensitive location (if YES continue) 0.44 FALSE 0.44 2.3.1 Inefficient natural attenuation (if YES continue) 0.23 FALSE 0.23


49




USER VALUES

2.3.1.1 Organic matter 0.05 MEDIUM RISK 0.05 2.3.1.2 Emerging organic compounds 0.10 MEDIUM RISK 0.10 2.3.1.3 Nutrients 0.10 MEDIUM RISK 0.10 2.3.2 Generation of metabolites (if YES continue) 0.27 FALSE 0.27 2.3.2.1 Nitrogen cycle (NO2-, N2O…) 0.10 MEDIUM RISK 0.10 2.3.2.2 Emerging organic compounds 0.10 MEDIUM RISK 0.10 2.3.2.3 Other nutrient cycles (H2S) 0.10 MEDIUM RISK 0.10 2.3.3 Mobilization (if YES continue) 0.00 FALSE 0.00 2.3.3.1 Metals 0.00 MEDIUM RISK 0.00 2.4 Specific targets (is it important to you?) 0.00 FALSE 0.00 2.4.1 Seawater barriers 0.00 NO RISK 0.00 2.4.2 Protected water body 0.00 MEDIUM RISK 0.00 2.4.3 Water levels (if YES continue) 0.00 FALSE 0.00 2.4.3.1 River 0.00 MEDIUM RISK 0.00 2.4.3.2 Spring 0.00 MEDIUM RISK 0.00 2.4.3.3 Wetland 0.00 MEDIUM RISK 0.00 2.4.3.4 Groundwater 0.00 MEDIUM RISK 0.00

5.2 Real values and comparison with risk perception

After defining the value of priors and answering the surveys, we define the risk

of failure for the Llobregat Demo Site. Risk was defined in an operation fault

tree (see Figure 5.1), the design and construction fault tree was not presented

as the site has been in operation for years. Each individual risk of each

independent event, as well as the probability of higher events in the tree are

plotted in Figure 5.1. Furthermore, we have designed a palette color for each

event, being red for the events with high risk, orange for events of medium risk

and blue for events of low risk. The events with no risk are white. In order to

zoom the image, we recommend to check the file corresponding to the

Llobregat site in MAR-RISK APP.

The results show that the total risk of failure of Llobregat MAR Demo Site is

very high (close to 1). This risk is high due to non-technical (0.8) and technical

reasons (0.91). In the case of non-technical issues, the ranked risk values (from

higher to lower) are the following: 1) governance (0.43). 2) social unacceptance


50

(0.34), 3) economic reasons (0.33), and 4) legal constraints (0.23). Related to

technical issues, risk values are in order of importance: 1) not enough water to

recharge (0.91), 2) unacceptable quality (0.44) water and, 3) structural damage

(0.12).


51

Figure 5.1. Results of the failure risk of Llobregat Demo Site at operation.


52

We have also compared the perception of risk and the calculated risk in the

Llobregat Demo Site (Table 5.3). From this table, it can be observed that

clogging by particles and by biological process, the lack of coordination and the

high maintenance costs are the main risk of failure for the Llobregat site.

Table 5. 3. Comparison of perception of risk (high/medium/low) with calculated risk HIGH RISK CALCULATED RISK 2.2.3.1.2 Source fine particles (generation inside MAR facility) 0.4 1.4.1 Lack of coordination 0.40 2.2.1.2.1 Turbidity/particles 0.4 1.2.2.2.3 High maintenance cost/maintenance requirements 0.2 2.2.3.2 Bioclogging 0.10 MEDIUM RISK 0.08

2.2.2.1.1 Droughts and Rainfall event periodicity 0.2 2.2.2.4 River regulation 0.2 2.2.2.2 Waste water treatment plant failure 0.20 2.2.2.3 Desalination plant failure 0.20 1.3.5 Fair distribution of treated water 0.1 2.2.3.4 Compaction 0.1 2.3.1.3 Nutrients 0.10 2.3.2.3 Other nutrient cycles (H2S) 0.10 2.2.1.1 Sanitary/biological restrictions (e.g. due the

pathogens) 0.1

2.3.2.2 Emerging organic compounds 0.1 1.3.4 Children surveillance 0.10 2.3.2.1 Nitrogen cycle (NO2-, N2O…) 0.10 2.3.1.2 Emerging organic compounds 0.1 1.2.2.1.1 Industrial use 0.05 1.2.2.1.2 Agricultural use 0.05 2.3.1.1 Organic matter 0.05 2.2.1.3.4 Organic chemicals (pollutants, EOCs) 0.05 1.2.2.2.2 High installation cost 0.005 1.2.2.2.1 Low price of water 0.005 2.4.3.4 Groundwater 0.001 2.4.3.2 Spring 0.00 2.4.3.1 River 0.001 2.4.2 Protected water body 0.001 2.3.3.1 Metals 0.00 2.4.3.3 Wetland 0.001

LOW RISK 0.03 1.3.1 Health risk perception 0.05

1.1.1.3 Regional/Local 0.05 1.1.2.2 Others 0.05


53

2.1.4.2 Pipe breakage 0.05 1.3.2 High cost perception 0.05

1.1.1.1 European 0.05 1.2.1 Macroeconomic constraints 0.05 1.4.2 Non-technical knowledge 0.05

1.1.2.1 Health legislation 0.05 1.3.6 Perception of effectiveness 0.05 1.1.1.2 National 0.05 1.3.3 Behavioral requirements 0.05 2.1.3 Terrorism activities/Vandalism 0.05 2.2.3.5.2 Bacterial processes 0.025 2.2.3.3.1 Evaporation (excess) 0.01 2.2.3.3.3 Microbial population catalysis 0.01 2.1.4.1 Slope stability 0.01 2.1.4.3 Others 0.01 2.2.3.3.2 Water mixtures 0.01

1.2.2.1.3 Domestic use 0.01 2.2.1.3.2 Salinity and sodicity 0.01

2.2.1.3.3 Nutrients (nitrogen, phosphorous) 0.01 2.1.1 Flooding 0.01 2.2.3.5.1 Physical Motives 0.0001 2.2.3.5.3 Inappropriate design 0.0001 2.1.2 Natural hazards (e.g. earthquake) 0.00

NO RISK 0.00 2.1.5 Aquifer dissolution (e.g. in karstic aquifer) 0 2.2.1.3.5 Radionuclides 0 2.2.3.1.1.1 Pipe filter fails 0 2.2.3.1.3.2 Erosion 0 2.2.1.3.1 Metals (e.g. arsenic, manganese) 0 2.2.3.1.3.1 Deposition 0 2.4.1 Seawater barriers 0 2.2.3.1.1.2 Residence time 0


54

6 Conclusions In this deliverable, we have developed the MAR-RISKAPP, an interactive

framework that allows evaluating and comparing the perception of risk and the

failure risk of Managed Aquifer Recharge. This MAR-RISKAPP is based on the

previous fault trees developed in Deliverable 16.1 and in the survey forms

developed in Deliverable 16.3.

The MAR-RISKAPP has been developed in Microsoft Excel®, allowing its wide

use since it is a known and available platform. The final user of MAR-RISKAPP

is expected to be the manager of each recharge facility.

We have evaluated the perception of the risk at the MARSOL Demo Sites.

Furthermore, we have developed a complete risk assessment using MAR-

RISKAPP of the Llobregat site.

After the review of the different perceptions in the MARSOL Demo Sites, we

can conclude that the general perception of risk in non-technical issues is

related to legal aspects (mainly health legislation), also about the lack of

technical knowledge, and the lack of coordination among stakeholders. Related

to the technical aspects the most important aspect is about clogging risk but

also by chemical aspects like the presence of nutrients or Emerging Organic

Compounds in the supplied water. After the definition of priors in each MARSOL

Demo Site, we will be able to compare the perception of risk with the actual

calculated risk.

To evaluate the risk of the Llobregat Demo Site, we have defined the value of

the probability of all the independent events defined in the lower level within the

fault tree. These priors were defined by an interdisciplinary expert team. The

results show that the total risk of failure of Llobregat MAR Demo Site is very

high. This risk is high due to non-technical (0.8) and technical reasons (0.91). In

the case of non-technical issues the most critical events are: governance, social

unacceptance, economic reasons, and legal constraints. The most critical ones

within the technical side are: lack of recharge water, unacceptable quality, and

structural damage of the facility.


55

APPENDIX A: Technical issues of MAR-RISK APP. The code and developing issues.

The tool that is being presented has been programmed using Microsoft Excel®,

specifically its Developer module. This well-known module is used for advanced

Excel users in order to program more complex functions that the base program

calculations are not able to do. This module is based mainly on the usage of

macros, in the case of Excel the macros are usually short programing code

lines that are used to give some kind of orders to the program in order to do

some specific calculations or to set automatically some kind of properties for the

working environment (among other possibilities). The programming writing of

the macros is usually done in the Visual Basic Editor (VBA) tool. When this tool

is opened, a new window in Excel is opened; in this window three types of sub-

windows (there are more but these three are the most important ones in general

terms) are present: 1) the project explorer window (where you can see the

different objects, forms and modules present in the Excel file that the user is

working with), 2) the properties window (where the user can visualize the

properties of objects, forms and modules presented in the project explorer

window) and 3) the code window (this window is the one where the user

programs the different macros and its code lines).

From the project explorer window, the objects are defined as entities that are

part of an Excel workbook, such as sheets, rows, columns, cells, etc. Generally

speaking, in this window, only the workbook and the Excel sheets will be

present. Then the forms appear below the objects, these forms are a user-

created surface where the user can create more complex applications (with

buttons, lists, etc.) that are not based in the typical excel working environment.

Finally, the modules, these are the structures where the VBA code is stored,

this modules can contain information (programing code lines) from different

objects at the same time (depending on the order and structure that the

developer had decided).

The properties window shows, from every object present in the project explorer

window, their properties (name, display, with, etc.).


56

Finally, the code window, this one shows the different programming code lines

from the objects (usually for automatic macros) or from the modules (usually for

click dependent macros related to buttons, among others).

6.1 Macro usage

In this program, the macros are utilized in two kinds of way: 1) when the

program is opened (the macro is automatically activated) and 2) when the

macro is attached to a button and it is activated when the user clicks the button.

As stated before, these two types of macros are written in different parts of the

VBA tool windows. The explanation of these two macros is present right below:

Automatically executed macros. These types of macros are executed whenever

the Excel workbook or worksheet is opened. These kinds of macros include

automatic size setting, toolbar hiding, etc. In this case, the excel program

utilizes only one kind of macro, the size type macro (specifically the full screen

one). As stated before, these macros are written inside the project explorer

window, in the object section (specifically, “this workbook”).

Click on button macros. These types of macros are executed whenever the user

clicks a button with the mouse left click. Before explaining the different macros

that appear in this group, is important to make some comments about the

buttons that contain these macros. A button is any shape that is present in the

Excel program sheet that has a macro attached to it. Any shape can become a

button if it is correctly designed, this means that the developer has to right-click

the shape and select the option “assign macro” and then choose(or create a

new one) from the scrolling list that appears. After briefly explaining the button-

macro relationship, the different click on button macros used in this Excel

program can be summarized as: 1) make visible (true or false), 2) activate sheet

and 3) display color. These three types of macros can have different

combinations and formats but in the end can be grouped in the three categories

expressed before. Each of these macros has its own name and it can be

applied to act on entire sheets or even only images or text boxes (like in the

instructions case, which will be explained later).


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6.2 Macro programming code (theoretical explanation)

In this part the basics (for the understanding of the Excel program discussed) of

macro programming will be explained. Before entering in the details of the code

analysis, a brief explanation of the programming structure should be realized. In

the code window from the VBA tool, the developer has to write the programming

code using the following structure (each part written in different lines, separated

using the enter button from the keyboard):

1- Sub <Name of the macro, without using spaces>(), colored green in the

examples.

2- Code line (will be explained later), colored red in the examples or

statement (will be explained later), colored yelllow in the examples.

3- End <statement name>, colored yellow in the examples.

4- End Sub, colored green in the examples.

For example, a code for a macro called TUTORIAL could be:

Sub TUTORIAL()

With ActiveSheet.Shapes("Picture 2")

If ActiveSheet.Shapes("Picture 2").Visible = True Then

ActiveSheet.Shapes("Picture 2").Visible = False

Else

ActiveSheet.Shapes("Picture 2").Visible = True

End If

End With

End Sub

As can be seen in the example, there are two parts from the macro design that

need explanation, the code line and the statement.


58

- A code line is the programing language text that is responsible for the

specific actions that the macro is going to do. In the example presented

above, the code lines are the text parts indicated with the red color.

- A statement is a type of connector that modifies the meaning or the

application of the code lines. In the above example, the statements are

the yellow text parts.

- The green text is the general beginning or ending of the whole macro.

6.3 Macro programming code practical application

In the Excel program the following macros can be seen in the programming

code:

Automatically executed macros. From these type of macros only the

DisplayFullScreen one will be discussed. In order to fully understand the

ongoing explanation, the code for this kind of macro is presented in the end of

this section. The first code line shows that this macro is an indirect or occult one

(therefore the reason for being a “Private Sub”), which name is

“Workbook_Open”. The second code line simply means that the order

“Aplication” and its specific command to use “DisplayFullScreen” is true and

therefore has to be applied. Finally the third line indicates the end of the macro.

Finally, is important to highlight that in this case, the macro was written in the

section “This Workbook” from the object browser window in VBA, which means

that whatever macro is written there, has to be applied in the whole Excel file

program.

Private Sub Workbook_Open()

Application.DisplayFullScreen = True

End Sub

Click on button macros. In this section there are different types of macros and

structures that were used in the development of the tool.


59

o Open/close window button. This kind of button is used to send the user

from one sheet of the Workbook to another with one simple click. If we take

a look on the example presented, we will see that the first and last code

line were already explained before, the middle code lines represent two

actions: the activation of the sheet “HOME” (objective sheet, new sheet to

be visualized by the user) and its visualization (it can be understood as if it

was opened) with the closure (or making the visualization false) of the

“INPUT” sheet which was the origin sheet (the one that has to be closed

by the user). The code uses the command “Activate” and “Visible”, is

important to notice that the “INPUT” sheet has not been deactivated. This

is because its deactivation is not necessary for the correct functioning of

the “HOME” sheet. However it is necessary to both activate and make

visible the “HOME” sheet (objective sheet) in order to make it work

properly.

Sub BACK_TO_HOME()

Worksheets("HOME").Activate

Worksheets("HOME").Visible = True

Worksheets("INPUT").Visible = False

End Sub

o Show & hide on the same button text/image. This type of button is

designed in order to hide and unhide text/images with a mouse left click

(the first click makes it appear and the second one makes it disappear). In

the example presented for this button, we can the first and last lines as the

beginning and ending of the macro (respectively). In this case the macro’s

name is INSTRUCTIONS_INPUT, the name of the specific worksheet

where is located is not specified. That’s because this macro is only applied

to the active sheet where the text or image (that are implied in the macro,

in this case an image called “OVAL 2”) are located. The code in this macro

uses the same command presented on the open/close window button


60

(.Visible =True/False). However in this case, the macro also uses some

statements (If, Then, With and Else) these statements are utilized in order

to make a double direction button (so with the same button the user can

unhide and hide the image/text). Generally speaking this macro tells us

that if “OVAL 2” is unhidden and the button is clicked, then it has to be

hidden. On the situation that “OVAL 2” is already hidden and the button is

clicked, the image will be unhidden.

Sub INSTRUCTIONS_INPUT()

With ActiveSheet.Shapes("OVAL 2")

If ActiveSheet.Shapes("OVAL 2").Visible = True Then

ActiveSheet.Shapes("OVAL 2").Visible = False

Else

ActiveSheet.Shapes("OVAL 2").Visible = True

End If

End With

End Sub

o Open/close window button with color display. This macro is very similar to

the one referred in the “Open/close window button” section. The main

difference is that in this case the macro also has the command

“.DisplayFormat.Interior.Color”. This command has a structure where first

of all there’s the reference of the Worksheet that the macro is located (in

this case the Worksheet “FAULT TREE RESULTS OP”), thereafter goes

the cells from that worksheet that the macro has to be applied (Range).

After that part the command “Interior.Color =” which means that the color

from the cell selected has to be copied to the range of cells selected

before. Finally the command “.DisplayFormat.Interior.Color” goes, which is


61

necessary in order to complete the macro and to show the color change.

The example of this macro is presents below:

Sub FAULT_TREE_RESULTS_OP()

Worksheets("FAULT TREE RESULTS OP").Activate

Worksheets("FAULT TREE RESULTS OP").Visible = True

Worksheets("GRAPHICAL RESULTS").Visible = False

Worksheets("FAULT TREE RESULTS

OP").Range("CD7:CJ9").Interior.Color =

Range("CJ9").DisplayFormat.Interior.Color

End Sub

o Print in PDF file button. This macro is completely different from the ones

presented above, because in this case the macro does not bring the user

to an external worksheet, neither opens a text box/image. In this case, the

macro is used to generate a PDF document with the information and

images presented in the worksheet that the user is working with. The

programming code presented below, shows that the name of the macro is

“PRINT_PDF”. Also it shows that from the active window and the selected

sheet (the one that is open and active) it has to be printed (saving into a

document).

Sub PRINT_PDF()

ActiveWindow.SelectedSheets.PrintOut Copies:=1,

Collate:=True,_

IgnorePrintAreas:=True

End Sub


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6.4 Non-VBA programming Excel functions

For the most part of the Excel tool, its functions are user friendly and do not

imply a high degree of difficulty. However, from these simple functions, it could

be helpful to highlight the ones that have been more used or the ones that have

a major importance in the design of the tool.

IF function. In this case, one of main Excel functions that has been used. For

the most part in the INPUT or RESULTS sections in order to link the answers of

the surveys with the RESULTS calculations (and the program default database

present in the A PRIORI CRITERIA). Here, just below the text, we present an

example of this type of function.

=IF('NON-TECHNICAL DC'!B7="X";0;IF('NON-TECHNICAL DC'!C7="X";'A

PRIORI CRITERIA'!B7;IF('NON-TECHNICAL DC'!D7="X";'A PRIORI

CRITERIA'!C7;IF('NON-TECHNICAL DC'!E7="X";'A PRIORI CRITERIA'!D7))))

In this example what we are trying to do is to link the answers of the user in the

input of NON-TECHNICAL DC (DC meaning design and construction). This

linkage implies that the user has to use the letter “X” in order to apply the values

correctly. From the code we can distinguish 2 types of sheets: the user filling

one and the default values one. The user writes the letter “X” on the first type of

sheet and therefore the function selects one cell (with its value) from the A

PRIORI CRITERIA (default database), the cell selected has the same risk

category for both sheets.

Conditional formatting. This type of function does not imply certain code writing;

instead it implies the usage of the Excel tool CONDITIONAL FORMATTING.

This tool is used in order to change the color fill of the cells depending on the

value of the own cell or another one. From the CONDITIONAL FORMATTING

the COLOR SCALES is used. Then the FORMAT ALL CELLS BASED ON

THEIR VALUES selecting 3 colors scale, each color with one value (blue = 0;

yellow = 0,5 and red = 1).

Probabilistic risk assessment. Despite the fact that this is not properly an Excel

function per se, it is highly important for the tool development. The probabilistic

risk assessment (PRA) is a well know subject, discussed by many authors (the


63

developers of the tool recommend the work written by Tartakovsky 2007). In

this tool, the PRA approach has been used to calculate the probability of having

a problem with the MAR facility. This probability is calculated by taking into

account two types of situations: 1) AND; 2) OR. The AND situation implies that

the probability of a risk category to take place is the same as the intersection of

all the subcategories that conform it. For example, the category Failure

deposition pond has two subcategories (Piper filter fails and Residence time),

so the risk probability of Failure disposition pond is the union of the two

subcategories (Piper filter fails + Residence time – (Piper filter fails * Residence

time)). The OR situation implies that the probability of a risk category to take

place is the same as the union of all the subcategories that conform it. For

example, Territorial constraints has three subcategories (European - Eu,

National - Nat and Regional/Local - RegLoc), so the risk probability of Territorial

constraints is the same as the intersection of these three subcategories

(Eu+Nat+RegLoc-(Eu*Nat)-(Nat *RegLoc)-(Eu*RegLoc)+(Eu*Nat*RegLoc).


64

APPENDIX B: STATE OF ART OF REPORTED MAR PROBLEMS TITLE RECHARGE

TYPE PLACE &

TIME DURATION OF THE PROJECT MAIN PROBLEMS REF.

Water Factory 21, Coastal Barrier Seawater

Intrusion

Deep Wells

ORANGE COUNTY

(USA), 1977 4 YEARS

Problems - Microbiological, Meteorological (Excess of Rain Diminishes the Amount of Water Injected), Design and Construction Costs (16 Million $),

Operation Costs (2 Milion $/year), Clogging, Wastewater Treatment Plant Failure, Salinity/Sodicity (Water Intrusion), Geological Heterogeneity (Different

Geological Material Layers Present), Not Shallow Aquifer or High Thickness (Wells are Really Deep 850 - 1150 Feet)

Takashi Asano, 1985

Operations At The Cedar Creek Wastewater

Reclamation-Recharge Facilities

Deep Wells

NASSAU COUNTY,

NEW YORK, (1979)

3 YEARS (4 INCLUDING CONSTRUC-

TION)

Problems - Design And Construction Costs (22 Million Dollars), Civil Work Failures “Very Likely” (Others - Underdrain Systems, Dual-Media Filter System, Carbon Adsorbers, Mechanical/Electronic Problems), Operational Costs (8 Million $),

Wastewater Treatment Plant Failure

Takashi Asano, 1985

Proposed Groundwater Recharge

Deep Wells

EL PASO, TEXAS (1985)

UNKNOWN Problems - Construction Cost (Over 22 Million Dollars), Nutrients (Nitrogen and

Phosporus), Salinity And Sodicity, Wastewater Treatment Plant Failure, Suspended Solids, Gas Generation (Physical Motives and Bad Design)

Takashi Asano, 1985

Groundwater Recharge For

Wastewater Reuse In The Dan Region Project

Infiltration Basins /

Spreading Basins

ISRAEL, (1977) 5 YEARS

Problems - Land Use (30 Ha), Low Infiltration Rates, Climatic Conditions, And The Frequency Of Basin Cleaning, Salinity, Nutrients (N And P Higher In Winter),

Suspended Solids (Higher In Winter), Organic Chemical Compounds, Wastewater Treatment Plant Failure, Geological Heterogeneity (Different Geological Material

Layers), Trace Elements (Mainly Metals, but also Manganese and Potassium)

Takashi Asano, 1985

Soil Deposition Of Trace Metals During Groundwater

Recharge Using Surface Spreading

Surface Spreading

CALIFORNIA (USA) 20 YEARS

Problems - Salinity And Sodicity, Suspended Solids, Trace Elements (Others but Mainly Metals), Clogging (Not Specified), Organic Chemicals, Water Scarcity

(Climate) Takashi Asano, 1985

Issues In Artificial Recharge General NA NA

Problems - Long Time, Chemical Quality Issues

Not A Problem – Has Good Social Acceptance

Herman Bouwer, 1996

Issues In Artificial Recharge

Infiltration Basins NA NA

Problems – Land Use, Water Quality, Clogging, Suspended Solids Content, Organic Compounds, Flooding, Drying, Nutrients (Nitrogen Mainy), Bad Soil Infiltration

Rate and Compaction

Herman Bouwer, 1996


65

TITLE RECHARGE TYPE

PLACE & TIME

DURATION OF THE PROJECT MAIN PROBLEMS REF.


Deep Wells NA NA

Problems – Main Problem Is Clogging, Suspended Solids, Microorganisms, Nutrients (N And P), Design And Construction Costs, Corrosion

Not A Problem – Can Be Done In Zones Where Permeable Soils Are Not Available

Herman Bouwer, 1996


Vadose Zone Wells NA NA

Problems – Clogging, Suspended Solids, Nutrients, Microorganisms, Organic Compounds, Low Infiltration Rates

Not A Problem - Cheaper

Herman Bouwer, 1996


Seepage Trenches NA NA

Problems – Suspended Solids Are Usually A Problem,

Not A Problem - Cheaper

Herman Bouwer, 1996

Artificial Recharge of Groundwater:

Hydrogeology and Engineering

Surface Infiltration NA NA

Problems – Flood Danger, Civil Work Failures (Others And Slope), Land Use, Water Quality Problems, Suspended Solids, Clogging (Biological, Mineral And

Sedimental), Gas Formation (Mainly Bacterial), Nutrients, Organic Compounds, Risk Of Low Infiltration Rate, Contaminant Spreading

Herman Bouwer, 2002



Vadose-Zone

Infiltration NA NA

Problems – Very Likely Risk of Insuficient Soil Infiltration Rate, Land Use, Pipeline Failure, Gas Accumulation (Physical), Pipe Failure, Mainly Disadvantage is Clogging

(Biological and Sedimental), Suspended Solids Content,

Not Problem - Cheaper

Herman Bouwer, 2002



Wells NA NA

Problems – Compaction, Clogging (Most Typicall Problem, Due to Sediments but Also Other Reasons Like Bacteria or Precipitation), Water Quality, Nutrients,

Salinity, Microbiological Problems,

Not Problem – Land Use, Infiltration Rate

Herman Bouwer, 2002



General Artificial Recharge Systems

NA NA The Main Issue In Artificial Recharge Is Clogging, Availability Of Water Resources Is Also A Problem With Climatic Issues, Social Costs, Environmental Costs, Land Use,

Civil Work Problems (In General, Corrosion),

Herman Bouwer, 2002

Artificial Recharge of Aquifers

Infiltration Basins and

Canals

SAN JUAN RIVER BASIN (ARGENTINA

NA Problems – Sedimentation of Fine Material (Clogging, Turbidity), Flooding Risk

(Floods may Interfere with the Infiltration Basin), Deposition Problems, Corrosion, Erosion, Civil Damage (Others), Vandalism), Drought Problems (Water Shortage),

United Nations Environment

Programme, 1997


66

TITLE RECHARGE TYPE

PLACE & TIME


) Lack of Incentives (Legislative and Economical) for Maintenance, Problem with Nutrients (N And P), Risk of Aquifer Dissolution, Legislation Problems (Related to

Landscape Environmental Impact), Thickness of the Aquifer

Not Problem – Low Maintenance Costs, Low Design and Construction Costs, Usually the Technical Knowledge of this Technology is High,

Investigating The Causes Of Water-Well Failure In

The Gaotlhobogwe Wellfield

Deep Wells

SOUTHEAST BOTSWANA 8 YEARS

Problems – Water Quality (Metals, Salinity/Sodicity, Nitrogen, Phosphorus, Etc.), Low Quantity Of Water Resources, Problems With Infiltration Rate, Risk Of Low

Water Storage, Chemical Clogging (Precipitation Of Calcite Due To Water Mixture), Problems With The Design And Operation Of The Wells

Chaoka et al. 2006

Aquifer Storage And Recovery

Deep Wells

CALIFORNIA (USA) NA

Problems – Water Quality (Suspended Solids, Salinity/Sodicity, Social Unacceptance (Taste In Water), Legal Constraints (Not Accomplishing Drinking Standards) , Movilisation Of Trace Elements, Precipitation (Chemical Clogging),

Clogging (Sediment And Microbiological), In General Clogging Is The Most Typicall Problem, Infiltration Problems, Civil Work Failures (Liquefaction), Natural Hazards

(Earthquake), Terrorists Attacks

USGS, 2012

Troubleshooting Water Well

Problems

Deep Wells NA NA

Problems – Improper Well Design And Operation, Incomplete Well Development, Borehole Stability Problems, Incrustation Build-Up (Clogging Due To Chemical

Issues With Water), Biofouling Clogging Due To Microbiological Issues), Corrosion, Aquifer Problems, Over Pumping (Sediment Particle Moving, Sedimentation,

Erosion, Compaction), Nutrient Problems (N And P), Gas Generation (Bacterial And Inapropiate Design), Lack Of Recharge, Climate Issues, Drough Periods, Civil Work

Failure (Pipes Breakage And Others), Low Infiltration, Water Quality Issues (Metals, Nutrients And Organic Compounds)

Alberta – Agriculture and Forestry

Ministry, 2001

Australian Guidelines For Water Recycling: Managed Aquifer

Recharge

Deep Wells AUSTRALIA NA

NOT PROBLEM - Low Capital Costs (Managed Recharge Is Often The Most Economic Form Of New Water Supply), No Evaporation Loss, Not Algae Or

Mosquitoes (Unlike Dams), No Loss Of Prime Valley Floor Land (Erosion), Ability To Use Saline Aquifers That Could Not Be Directly Used For Supplies, Potential

Location Close To New Water Sources, And Where Demand For Water Is High, Aquifers Providing Treatment As Well As Storage, Low Greenhouse Gas Emissions Compared To Remote Pumped Storages, Able To Be Built To The Size Required For

Australian Government –

Department of the Environment and

Energy


67

TITLE RECHARGE TYPE

PLACE & TIME


Incremental Growth In Water Demand, Provision Of Emergency And Strategic Reserves, Improved Reliability Of Existing Supplies, Improved Environmental Flows

In Water Supply Catchments For Urban Areas


Recharge


AUSTRALIA NA

Deep Wells – Preferably Used When There Are Confined Aquifers Or Superficial Clay Levels, Can Work With Low Infiltration Rate, Low Land Use/Cost, Ease Of

Traffic Access, Compatibility Of Land Use, Suspended Solids And Nutrients Usually Lead To Clogging Problems

Infiltration Ponds – Prefered When Land Cost/Use Is Cheap General Info - Usually Artificial Recharge Has Good Social Acceptance And Suficient

Residence Times For Water, This Residence Time Implies Less Treatment For The Water And Less Risk For Pathogens



Energy


Recharge


AUSTRALIA NA

General Info – Artifial Recharge Depends Mainly On The Availability Of Apropiate Aquifers, Sufficient Volumes Of Water Are Needed To Justify The Costs Of The

Project, Places With Surface Aquifers Cause Structural Problems, Salinisation And Waterlogging.



Energy


Recharge

Deep Wells

Northern Adelaide

Plains (AUSTRALIA)

NA

Problems – Salinity, Aquifer Heterogenity, Water Mixture, Need To Have A Water Treatment Plant (Design And Construction Costs, Operational Costs)

Not Problems – Meet Drinkig Water Requeriments



Energy


Recharge


AUSTRALIA NA

Problems – Pathogens, Inorganic Chemicals, Salinity And Sodicity, Nutrients, Organic Chemicals, Turbidity And Particulates, Radionuclides, Pressure/Flow

Rates/Volumes/Levels Of Water, Contaminant Migration In Fractured And Carstic Aquifers, Aquifer Dissolution, Well Stability, Impact On Groundwater Ecosystems,

Greenhouse Gases Generation (Microbiological Issues)



Energy


Recharge


AUSTRALIA NA Problems – Increase Iron, Manganese, Arsenic, Trace Species And Hydrogen Sulfide, Sodicity/Salinity Probems, Ntrient Issues,



Energy Mobilization Of Arsenic Deep FLORIDA NA Problems – Arsenic, Manganese, Uranium (Radionuclides), Organic Compounds, USGS, 2002


68

TITLE RECHARGE TYPE

PLACE & TIME


And Other Trace Elements During Aquifer Storage And Recovery,

Southwest Florida

Wells (USA) Water Residence Time, Aquifer And Input Water Chemistry Problems (Do, Ph, Etc.), Aquifer Matrix Chemistry/Mineralogy, Site Specific

Hidrogeology/Hidrochemistry, Water Mixture


Recharge


AUSTRALIA NA

General Info – About Clogging There’s Info From 14 Injection Places That Sufered Clogging Problems. From The 14 Sites, 8 Were Biological Clogging, 9 Physical Clogging And 1 Was Chemical Clogging (In Some Cases There Was A Mixture

Between Two Tyupes Of Clogging)



Energy Sources Of High-Chloride Water To Wells, Eastern

San Joaquin Ground-Water

Subbasin, California

Deep Wells

CALIFORNIA (USA) NA Problems – Salinity/Sodicity, Chloride, Metals (Arsenic, Manganese, Etc.),

Nutrients (Nitrates), Water Mixture, Water Evaporation USGS, 2006

Aquifer Storage And Recovery For The City Of

Roseville: A Conjunctive Use Pilot

Project

Deep Wells

CALIFORNIA (USA) NA

Problems – Organic Chemicals (Thm, Dbp), Design And Construction Costs (Projects Of Water Recharge With A Cost Of More Than 215 Million $), Legislation Issues (National And Lack Of Coordination), Trace Elements (Metals), Mechanical

Complications (Civil Work Failure – Others), Sodicity/Salinity, Microbiological Issues (Legislation About Bacteria Input In The Recharge Water), Water Mixture, Quality Issues (In General, It Doesnn’t Specify), Aquifer Thickness And Aquifer

Depth, Water Scarcity (Drought)

Not Problem – Natural Atenuation,

Water Environmental

Federation, 2005

San Gorgonio Pass Artificial Recharge

Investigation

Deep Wells

CALIFORNIA (USA) 1997 6 YEARS Problems – Low Infiltration Rate, High Thickness/Not Shallow Aquifer, Natural

Hazards (Earthquakes), Nutrients (Nitrogen Due To Wastewater Leakage) Alan L. Flint and

Kevin M. Ellett. 2004

The Effects Of Artificial Recharge On

Groundwater Levels And Water Quality In The West Hydrogeologic Unit

Of The

Deep Wells

CALIFORNIA (USA) 2004 5 YEARS

Problems – Low Infiltration Rate, Residence Time, Land Use, Risk Of Nutrient Mobilisation, Water Level Decline, Nutrients (Nitrogen), Organic Chemicals,

Water Scarcity (Droughts And Rainfall Periodicity), Evaporation, Sedimentation, Erosion, Regional Hydrogeology Water Imbalance,

No Problem – Natural Atenuation

USGS, 2013


69

TITLE RECHARGE TYPE

PLACE & TIME


Warren Subbasin, San Bernardino County,

California Hydro-Logic Effects Of Artificial-Re Charge Experiments With Reclaimed Water At East Meadow, Long Island, New York

Infiltration Basins

NEW YORK (USA) 1982

2 YEARS Problems – Land Use, Gas Generation (Physical Motives And Bad Design), Low Infiltration Rates, Suspended Solids, Clogging (Physical And Biological), Mechanical Failures, Ponding (Unwanted Water Accumulation), Microbiological Issues, Development Of Insect Populations, Water Quality Issues (Mainly Microbiological, Nutrients And Maybe Other Water Chemical Compounds), Salinity/Sodicity, Metals, Slope Factor Issues (Mounding), Water Mixing, Organic Chemicals (Organic Matter), Inorganic Chemicals, Ineficient Natural Attenuation (Due To Short Residence Time, Not Enough Reaction Of The Geological Materials Or Due To The High Treatment Of The Injected Water)

USGS, 1987

Hydro-Logic Effects Of Artificial-Re Charge Experiments With Reclaimed Water At East Meadow, Long Island, New York

Deep Wells

NEW YORK (USA) 1982

2 YEARS Problems – Suspended Solids (Turbidity), Clogging (Bacterial, Physical And Chemical), Metals (Iron), Salinity/Sodicity, Less Efficient To Move Large Quantities Of Water Than The Infiltration Basins, Clogging Is More A Problem In Wells Than In Basins, Slope Factor Issues (Mounding), Ineficient Natural Attenuation (Due To Short Residence Time, Not Enough Reaction Of The Geological Materials Or Due To The High Treatment Of The Injected Water)

USGS, 1987

The Atlantis Water Resource Management Scheme: 30 Years Of Artificial Groundwater Recharge

Infiltration Basins

SOUTH AFRICA (1980)

30 YEARS Problems – Clogging (Physical, Biological And Chemical), Metal Content (Iron), Not Enough Water Quantity, Organic Matter, Low Infiltration Rate, High Maintenance Costs, Groundwater Pollution, Appereance Of Alien Vegetal Species, Microbiological Issues, Land Ownership Problems (Is Not Under The Same Legal Management Than The Rest Of The Recharge Facility) Not Problem – Low Salinity

Republic of South Africa – Department

of Water Affairs, 2010

The Atlantis Water Resource Management Scheme: 30 Years Of Artificial Groundwater Recharge

Deep Wells

SOUTH AFRICA (1980)

30 YEARS Problems – Clogging (Physical, Biological And Chemical), Metal Content (Iron), Not Enough Water Quantity, Organic Matter, Low Infiltration Rate, High Maintenance Costs, Drough Conditions, Overpumping Water (Imbalance Between The Water Injection And Pumping), Gas Generation (Due To Physical Properties And Ineficient Design), Groundwater Pollution, Salinity/Sodicity Problems, Microbiological Issues, Land Ownership Problems (Is Not Under The Same Legal Management Than The Rest Of The Recharge Facility)




70

TITLE RECHARGE TYPE

PLACE & TIME


Recycling Polokwane’s Treated Wastewater

Infiltration Ponds

SOUTH AFRICA

NA Problems – High Thickness And Not Shallow Aquifer, Evaporation Of Water (Water Loss), Nutrient Problems (Mainly Nitrogen)



Small-Scale Borehole Injection In Namaqualand

Deep Wells

SOUTH AFRICA (1999)

3 YEARS Problems – Low Infiltration Rate, Salinity/Sodicity, Clogging (Physical) Republic of South Africa – Department


Calvinia: Trial Borehole Injection Tests And Water Quality Assessment In Fractured Mudstones

Deep Wells

SOUTH AFRICA

NA Problems – Low Water Storage Time (Residence Time), High Water Ph (Water Quality Problems), High Fluoride Concentrations, High Arsenic Concentrations, High Sulfate Concentrations, Oxygen Penetration (Redox Processes), Entrancve Of Gas From The Athmosphere (Due To Physical Motives And Bad Design).



Prince Albert: Borehole Injection Feasibility Study In Fractured Sandstones

Deep Wells

SOUTH AFRICA

NA Problems – Microbiological Issues, High Fluoride Concentrations, Nutrients (Mainly Nitrogen), Clogging (Biological And Chemical), Iron Content, Low Quantity Water Available (Climate), Low Permeability Rates,



Bitou Municipality Groundwater Management And Artificial Recharge Feasibility Study

Deep Wells

SOUTH AFRICA

2 YEARS Problems – Water Scarcity (Wwtp Failure Or Too Low Supply Limit), Salinity/Sodicity, Iron Content, And Organic Matter, Water Mixture (Chemical Reactions), Clogging (Chemical And Biological), Water Imbalance Between Injection And Water Input (Not Enough Water From Regional Hydrogeology), Legal Constraints (Others – Environmental)



Artificial Recharge Of The Windhoek Aquifer, Namibia: Water Quality Considerations

Deep Wells

NAMIBIA NA Problems – Sodicity/Salinity, High Sulfate Concentrations, High Iron Concentrations, Presence Of A Disposal Site Which Is The Source Of Organic Pollutants Infiltration

Tredoux, G. Et al. 2009

In The Face Of Changing Climate: Groundwater Development Through Artificial Recharge In Hard Rock Terrain Of Kumaun Lesser

Infiltration Basins

KUMAUN LESSER HIMALAYA

NA Problems - Low Conductivity Of The Water, Floods, Droughs, High Thickness And Not Shallow Aquifer, Civil Work Failures (Others – High Steep Slopes), Water Scarcity (Climate, Due To The Fact That Rainfall Is The Only Source Of Water For The Recharge)

M. Tripathi. 2016


71

TITLE RECHARGE TYPE

PLACE & TIME


Himalaya Assessing Risk Of Clogging In Community Scale Managed Aquifer Recharge Sites For Drinking Water In The Coastal Plain Of South-West Bangladesh

Infiltration Ponds And Infiltration Wells

BANGLADESH

NA Problems – Low Infiltration Rate, Civil Work Failure (Others – Mainly Related To The Minarology Of The Terrain), High Turbidity (Suspended Solids), High Sulfates, High Nutrients (Phosphorus Mainly), Microbiological Issues, Clogging (Physical Type Mainly), Organic Matter Content, Filter Efficiency Issues, Residence Time, Nutrients (Nitrogen), Clogging (Biological), Aquifer Heterogeneicity (Different Geological Material Layers On The Aquifer), Water Mixture, Salinity/Sodicity Issues

Sultana and Matin Ahmed, 2014

Investigation of recharge dynamics and flow paths in a fractured crystalline aquifer in semi-arid India using borehole logs: implications for managed aquifer recharge

Percolation Tank

INDIA (HYDERABAD)

NA Problems – Geologigal Heterogeneicity (Different Geological Material Layers Present), Low Infiltration Rate, Floods, Droughs, Not Shallow Aquifer/Geology Thickness, Not Enough Water (Climate), Water Mixing

Alazard et al. 2016

Impact of a Storm-Water Infiltration Basin on the Recharge Dynamics in a Highly Permeable Aquifer

Infiltration Basin

ITALY NA Problems – Legal Constraints, Clogging (Physical And Biological), Suspended Solids, Not Problem – High Recharge Rate (Precipitation), High Amount Of Water Available, High Infiltration Rate

Masetti et al. 2016

An innovative artificial recharge system to enhance groundwater storage in basaltic terrain: example from Maharashtra, India

Recharge Shafts And Subsurface Dams

INDIA NA Problem – Low Infiltration Rate, Excesive Withdrawal, Water Imbalance (Input/Output Of Water), Water Scarcity (Climate), Droughs, Erosion Issues, Suspended Solids

Bhusari et al. 2016

Integrated frameworks for assessing and managing health risks in the context of managed aquifer recharge with river water

Surface Water From A River (Infiltration Basins)

FINLAND NA Problems – Microbiological Issues, Nutrients, Contaminants (Organic And Inorganic), Lack Of Coordination (Political Concerns), Economic Costs (Design/Construction And Operation), Organic Matter, Persistent Organic Polutants, Lack Of Knowledge, Cost-Benefit Imbalace Related To Other Water Resources Options (Which Would Be Better Or Cheaper),

Assmuth et al. 2016


72

TITLE RECHARGE TYPE

PLACE & TIME


The effects of artificial recharge of groundwater on controlling land subsi-dence and its influence on GW quality and aquifer energy storage in Shanghai, China

Deep Wells

CHINA NA Problems – Surface Cover Of Hard And Low Infiltration Rate Geological Materials, Compaction, Subsidence Issues, Geological Layers Overlapping (Not A Continous Aquifer But The Disposition Of Different Geological Material Layers), Aquifer Too Deep, Contaminant Migration, Sulfates Increase, Organic Chemicals Increase (Organic Contaminants Pops), Nutrient Issues (Mainly Nitrogen), Organic Matter, Clogging (Chemical And Biological)

Shi et al. 2016

Impact of managed aquifer recharge on the chemical and isotopic composition of a karst aquifer, Wala reservoir, Jordan

Deep Wells

JORDAN, 40 KM NEAR AMMAN

NA Problems – Limited Knowledge About Hydraulic And Geologic Characteristics Of The Zone, Water Scarcity (Climate), Karstic Aquifer Issues (Dissolution), Hydrological Imbalance, Salinity Issues (But Not Due To Sodicity), Sulfate Issues, Nutrients, Chloride, Clogging (Physical), Suspended Solids, Low Infiltration Rate

Xanke et al. 2015

Natural attenuation of chlorobenzene in a deep confined aquifer during artificial recharge process

Na SOUTH-WEST CHINA

NA Problems – Organic Chemicals (Pops), Suspended Solids, Chloride, Land Use Problems (Uses Of Land For Agriculture, Industry And Residential Have Deteriorated Water Quality), Water Uses (Industry, Urban And Agriculture),

He et al. 2016

Artificial recharge of the phreatic aquifer in the upper Friuli plain, Italy, by a large infiltration basin

Infiltration Basin

ITALY NA Problems – Low Permeability, Nutrient Issues (Nitrogen Mainly), Sulfates, Overlapping Of Differend Geological Layers (With Clay), Geological/Hydraulic Information, Hydraulic Imbalance (Input Output Of The Recharge Is Negative) Not Problem – Low Salinity

Teatini et al. 2015

Water Quality of the Little Arkansas River and Equus Beds Aquifer Before and Concurrent with Large-Scale Artificial Recharge, South-Central Kansas, 1995–2012

Deep Wells

USA (KANSAS) 1995

6 YEARS Problems – Chloride, Nutrient Issues (Mainly Nitrogen), Trace Elements Problems (Metals Mainly), Not Enough Water Recharged (Water Input Is Too Low Compared To The Extraction And The Total Volume Of The Aquifer), Organic Chemicals (Pops), Microbiolofgical Issues (Fecal Bacteria)

Tappa et al. 2015

Artifical Recharge In Las Vegas Valley, Clark County Nevada

Injeection Wells / Deep

USA (LAS VEGAS)

NA Problems – High Thickness And Not Shallow Aquifer, Sulfate Content, Sodium Content, Chloride Content, Water Mixture, Low Well Recharge Yield (Probably Due To Clogging But Unknown Type), Economic Constraints (Operatonal)

Katzer and Brothers 1989


73

TITLE RECHARGE TYPE

PLACE & TIME


Wells Water Quality Changes Related to the Development of Anaerobic Conditions During Artificial Recharge

Infiltration Basins

USA (TEXAS) NA Problems – Low Infiltration Rate, Sodicity/Salinity Issues, High Sulfate, High Chloride, Vegetation/Algae Growth, Generation Of Metabolites (H2s), Low Ph, Clogging (Biological) Not Problem – Low Suspended Solids Content

Wood and Bassett 1975

A thirty year artificial recharge experiment in coastal aquifer in an arid zone: The Teboulba aquifer system (Tunisian Sahel)

Deep Wells / Injection Wells

TUNISIA (SAHEL) 1972 - 2002

30 years Problems – Water Scarcity (Due to Clime and Precipitation), Low Quantity of Water Resources Available For Recharge, High Salinity/Sodicity, Low Infiltration Rate, Low Porosity, Regional Problems (Negative Input/Output Ratio) Not Problem – Cheaper Water Prices (Compared to Other Technologies). Prices and Costs (Design/Construction and Operation) are lower in MAR

Bouri and Dhia 2010

Estimating groundwater recharge induced by engineering systems in a semiarid area (southeastern Spain)

Infiltration Basins (Via Dams And Gravel Pits)

SPAIN (ALMERIA)

NA Problems – High Slope, Water Scarcity (Climate), Clogging (Physical) Not Problem – Good Infiltration Rate

Martín-Rosales et al. 2007

Quantitative PCR Monitoring of Antibiotic Resistance Genes and Bacterial Pathogens in Three European Artificial Groundwater Recharge Systems

River Infiltration

SPAIN (SABADELL)

1 YEAR Problems – Microbiological Issues, Legal Constraints (Doesn’t Comply With Drinking Standards)

Böckelmann et al. 2009

Quantitative PCR Monitoring of Antibiotic Resistance Genes and Bacterial Pathogens in 3 European Artificial Groundwater Recharge Systems

Deep Wells

ITALY (NARDÒ)

1 YEAR Problems – Low Ph (Possibly Metal Dissolution And Mobilisation), Water Mixture, Microbiological Issues, Water Scarcity (Climate), Legal Constraints (Doesn’t Comply With Drinking Standards)



74

TITLE RECHARGE TYPE

PLACE & TIME


Quantitative PCR Monitoring of Antibiotic Resistance Genes and Bacterial Pathogens in Three European Artificial Groundwater Recharge Systems

Infiltration Basins

BELGIUM /TORREELE)

1 YEAR Problems – Water Mixture, Microbiological Issues, Design And Construction Costs, Operational Costs (Reverse Osmisis And Ultrafiltration Treatments),


Modeling Seasonal Redox Dynamics and the Corresponding Fate of the Pharmaceutical Residue Phenazone During Artificial Recharge of Groundwater

Deep Wells

GERMANY (BERLIN)

Problems – Clogging (Unknown Type), Low Infiltration Rate (Periodically Changing This Rate Due To Clogging Issues), Nutrients, Low Natural Atenuation

Greskowiak et al. 2006

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Alemaw, B. F., Chaoka, R. T., Molwalelfhe, L., & Moreomongwe, O. M. (2006). Investigating the causes of water-well failure in the Gaotlhobogwe wellfield in

southeast Botswana. Journal of Applied Sciences and Environmental Management, 10(3).

Aquifer Storage and Recovery for the City of Roseville: A Conjuctive Use Pilot Project (n.d.). Retrieved September 8, 2016, from

http://acwi.gov/swrr/Rpt_Pubs/wef_session107/107_xalt.pdf

Asano, T. (1985). Artificial recharge of groundwater. Boston: Butterworth.


75

Assmuth, T., Simola, A., Pitkänen, T., Lyytimäki, J. and Huttula, T. (2016) Integrated frameworks for assessing and managing health risks in the context of

managed aquifer recharge with river water. Integrated Environmental Assessment and Management 12(1), 160-173.

Australian Guidelines Water Recycling (Phase 2) - Managed Aquifer Recharge (n.d.). Retrieved September 8, 2016, from

https://www.clearwater.asn.au/resource-library/guidelines-and-strategy/australian-guidelines-water-recycling-phase-2-managed-aquifer-recharge.php

Bhusari, V., Katpatal, Y.B. and Kundal, P. (2016) An innovative artificial recharge system to enhance groundwater storage in basaltic terrain: example from

Maharashtra, India. Hydrogeology Journal 24(5), 1273-1286.

Böckelmann, U., Dörries, H.-H., Ayuso-Gabella, M.N., Salgot de Marçay, M., Tandoi, V., Levantesi, C., Masciopinto, C., Van Houtte, E., Szewzyk, U.,

Wintgens, T. and Grohmann, E. (2009) Quantitative PCR Monitoring of Antibiotic Resistance Genes and Bacterial Pathogens in Three European

Artificial Groundwater Recharge Systems. App. Environ. Microbiol. 75(1), 154-163.

Bouri, S. and Dhia, H.B. (2010) A thirty-year artificial recharge experiment in a coastal aquifer in an arid zone: The Teboulba aquifer system (Tunisian

Sahel). Comptes Rendus Geoscience 342(1), 60-74.

Bouwer, H. (1996). Issues in artificial recharge. Water Science and Technology, 33(10-11), 381-390.

Bouwer, H. (2002). Artificial recharge of groundwater: Hydrogeology and engineering. Hydrogeology Journal, 10(1), 121- 142.

Center, C. W. (n.d.). San Gorgonio Pass Artificial Recharge Investigation. Retrieved September 08, 2016, from

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G. Tredoux, B. van der Merwe and I. Peters. Artificial recharge of the Windhoek aquifer, Namibia: Water quality considerations. Boletín Geológico y Minero,

120 (2): 269-278.

Government of Alberta, Alberta Agriculture and Forestry, Policy and Environment Division, Irrigation and Farm Water Branch, Farm Water Supply Section.

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Greskowiak, J., Prommer, H., Massmann, G. and Nützmann, G. (2006) Modeling Seasonal Redox Dynamics and the Corresponding Fate of the

Pharmaceutical Residue Phenazone During Artificial Recharge of Groundwater. Environ. Sci. Technol. 40(21), 6615-6621.

He, H., Yu, X., Huan, Y. and Zhang, W. (2016) Natural attenuation of chlorobenzene in a deep confined aquifer during artificial recharge process.

International Journal of Environmental Science and Technology 13(1), 319-326.


76

Izbicki, J. A., Metzger, L. F., McPherson, K. R., Everett, R., & Bennett, G. L. (n.d.). Sources of High-Chloride Water to Wells, Eastern San Joaquin Ground-

Water Subbasin, California. Retrieved September 08, 2016, from https://pubs.er.usgs.gov/publication/ofr20061309

Katzer, T. and Brothers, K. (1989) Artificial Recharge in Las Vegas Valley, Clark County, Nevada. Ground Water 27(1), 50-56.

Martín-Rosales, W., Gisbert, J., Pulido-Bosch, A., Vallejos, A. and Fernández-Cortés, A. (2007) Estimating groundwater recharge induced by engineering

systems in a semiarid area (southeastern Spain). Environmental Geology 52(5), 985-995.

Masetti, M., Pedretti, D., Sorichetta, A., Stevenazzi, S., & Bacci, F. (2015). Impact of a Storm-Water Infiltration Basin on the Recharge Dynamics in a Highly

Permeable Aquifer. Water Resour Manage Water Resources Management, 30(1), 149-165. doi:10.1007/s11269-015-1151-3

Schneider, B., Ku, H., & Oaksford, E. (n.d.). Hydrologic effects of artificial-recharge experiments with reclaimed water at East Meadow, Long Island, New

York. Retrieved September 08, 2016, from https://pubs.er.usgs.gov/publication/wri854323

Shi, X., Jiang, S., Xu, H., Jiang, F., He, Z. and Wu, J. (2016) The effects of artificial recharge of groundwater on controlling land subsidence and its influence

on groundwater quality and aquifer energy storage in Shanghai, China. Environmental Earth Sciences 75(3), 1-18.

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