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Table of Contents Frontmatter Chapter 1. Water resources management refers to all types of actions aiming at creating more favourable conditions for all water bodies in the future. This fundamental objective included in recent legislation, such as the Water Framework Directive of the European Union, brings water quality issues in the centre of interest of the water sector.

Monitoring systems are now built in all European countries to produce original water quality data characterising the water bodies. Modelling techniques are complementary tools of great importance for assessing management decisions, which aim to improve the health of the water bodies. This book gives emphasis on innovative and classical methods useful for devising new comprehensive water quality models.

Mathematical models are now essential tools in water resources management and are currently applied for the solution of environmental problems including those of polluting discharge into surface and underground water bodies. Following the development of computational facilities and mathematical procedures, the models can provide reliable solutions, provided that they use proper data and are operated by competent professionals.

The pollutant fate and transport in a river or stream is governed by some physical and chemical processes, which can be formally interpreted considering an elementary volume of the water body. Some principal expressions of pollutant concentration are formulated, which will be useful for the development of the mathematical models.

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Evaluating the pollutant concentration in the water volume assists in finding how the contact of pollutant with water controls its final quality. Considering a water elementary volume, the forms and mechanisms of pollutant transport allow for the formulation of an overall balance of the pollutant mass.

Hydrological and river water quality modelling - Helmholtz-Centre for Environmental Research

In an infinitesimal volume control volume , the fundamental differential equation of pollutant transport can be written, the integration of which can give at any instant the concentration of the pollutant at any point in the water body. For the application of the fundamental differential equation, the velocity field should be determined. For this purpose, river hydraulics provides answers produced through complex calculations. Simplified procedures are also proposed, able to speed up the calculation reaching sufficiently accurate results. The water quality problems of rivers and streams are controlled by the natural behaviour of the water body, which is interpreted by means of proper terms and expressions of free surface hydraulics.

Pollution transport is due primarily to advection, but there are many situations in which dispersion plays an important role and cannot be neglected. In the mathematical models, the effect of dispersion is accounted by means of the dispersion coefficient, for the evaluation of which several procedures are proposed, supported by experimental studies.

The pollutants affecting a surface water body originate from various sources. There is a wide variety of organic pollutants e. When decaying, organic pollution is introduced in a surface water body and the free oxygen is depleted in the water. Since aquatic life is suffocated by low oxygen content, the determination of biochemical oxygen demand BOD and dissolved oxygen DO is a principal indicator for the quality of the surface water body.

BOD and DO are often used to estimate the quantity of organic pollutants present in a surface water body, and they deserve a special attention when incorporated in a mathematical model. There are numerous pollutants of various nature that affect a water body. They can be chemicals, bacteria or radioactive substances.

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Many of them are nonconservative and undergo changes when they are in contact with the water. The most frequent pollutants are the compounds of oxygen, nitrogen and phosphorus, whose transformations can be described by means of specific biochemical processes. Their presence in the water quality models is realised in the form of local injection or first-order kinetics. Water temperature represents one of the most significant characteristics of a surface water body.

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It plays an important role in water quality modelling since it controls many physiological and biochemical processes and affects the solubility of gases and solids. With a simplified interpretation of the water body, the fundamental differential equation can be integrated in an analytical way, giving rise to expressions already available in the technical and scientific literature.

The obtained equation is shown below:. Calibrated Model.

In the Figs. Evaluation of scenarios. For the input data of this scenario, in some of the tributaries the percentage of sanitation according with the sanitation works projected in the PSMV for the year were assumed. Scenario "e2" represents the expectations in water quality in a five-year period. Scenario "e3" represents the expectations in water quality over a ten-year period. From these scenarios, it was possible to obtain the behavior of water quality. In the same graph, the actual scenario is presented.


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By comparing these scenarios, a notorious recovery in the water quality of the river is observed once the WWTP enters into operation. From this analysis it is clear the importance that the WWTP plays in the Sanitation Plan of the river to help in the recovery of the physicochemical water quality of it. Which can be explained with the large contribution of ISS that is being received from the tributaries and in many of them the origin is not from the domestic wastewater, but from mining in the tributaries and deforestation processes in their upper parts, so despite its removal in the proposed scenarios, concentrations remain high.

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For the evaluated scenarios OD profile along the river, is shown in Fig. In this graph it is possible to see a recovery near to the Moravia sector Kilometer 34 , this is due to the closure of the interceptors located in this point of the river and the startup of the WWTP of Bello. This situation is more evident in scenarios 2 and 3 i. The highest values of conductivity correspond to scenarios e0 and e1 current and year two due to the low remotion rates. The lowest values of conductivity were in scenarios e2 and e3 years five and ten where the WWTP of Bello is operating. Like the ISS parameter, there is not a significant recovery in conductivity, as it was obtained for BOD near to km 48 of the river.

This is due to the lack of real data about removal percentages for this variable with the WWTP of Bello operating. From this graph, a marked deterioration in km 10 is observed, which corresponds with the place where the tributaries Chuscala, La Miel y La Valeria enters into the river, then a recovery is achieved near km From this point, there is a constant trend in this variable in the more critical stretch of the river. In terms of BOD5, in the first 19 km, there are no significant changes in the behavior of this parameter between the current and proposed future scenarios, with a slight peak near Km 10, where tributaries La Miel, La Valeria and La Chuscala enter the river Fig.

La Chuscala tributary receives the discharge of a collector of wastewater in the Mandaly neighborhood municipality of Caldas , which has a high concentration of organic matter as a product of the agricultural and domestic activities that occur in this watershed. Therefore, all the efforts in these kilometers should be directed towards the completion of the collectors of domestic wastewater [3], which are planned by the municipality of Caldas and with actions focused on water resource protection.

Future scenarios show a significant decrease in the concentrations of BOD5, compared with the current conditions scenario e0. It is remarkable the reduction that is observe between km 33 and km 48, as a result of the connection of the sewer interceptors of EPM with the projected WWTP of Bello. The increase in solids that occurs around km 10, can be explained as a result of the arrival into the river of the tributaries La Minita, La Miel, La Valeria and The Chuscala Fig.

These tributaries introduce large amounts of suspended solids into the water as a result of erosive processes generated in the upper parts of these watersheds and from the direct input of wastewater from the municipality of Caldas through collectors, which are still disconnected from the WWTP in San Fernando. The increase in the Inorganic Suspended Solids ISS , close to km 29, is a response of the tributaries that arrive in this section of the river, such as Altavista, La Picacha and La Hueso, which are very important tributaries in terms of distributing solid loads into the river.

The high content of solids in these tributaries is not only due to erosive phenomena in the streams but is also related with poor land planning as well as soil uses in the catchments, also in these tributaries the mining to extract construction materials is high. In Km 33, the simulation for future scenarios specially e3 shows a clear reduction in the load of solids. In addition, the reduction can be explained due to the significant reductions in discharges in the tributaries. In the base scenario e0 , there is no change in the model for the amount of solids in the river.

In these tributaries, despite the fact they are modeled with a reduction in pollutants, the reduction is not enough to make a significant change in the water quality, due to the high concentrations of solids that they have. Such concentrations are not mainly associated to the domestic wastewater, but with the mining in order to extract construction materials.

Despite discharges of wastewater from the municipality of Caldas, dissolved oxygen is presented in the river until km 15 Fig. This is because the slope of the river in this segment promotes the oxygenation of the water body. Later, in the river a reduction in the oxygen concentration is observed, with the lowest concentrations around the location of the discharges of the interceptors, which transports much of the wastewater of the region near km 33 Metro's Caribe Station.

From that point, a slight recovery occurs and then decreases again due to an increased load that does not allow re-oxygenation, despite the fact that the slope at this point is still significant and the presence of hydraulic jumps in this part of the river.

Between km 33 and km 48 the most critical section of the river is located, which is consistent with the behavior of BOD5 and solids, reflecting the impact of the income of wastewaters into the water body, which deteriorates its quality [17,21]. It is necessary to remark on the fact that despite the improvement of sanitation in the tributaries as it was set up in the model for scenarios e2 and e3, a significant recovery for future values of dissolved oxygen in the critical section of the river is not seen. Scenarios e0 and e1 return the highest values of electric conductivity along the river, due to the low removal percentages for this variable Fig.

These results show a sustained increase in the concentration value that occurs from km 15 to km 33 near the location of the interceptors. Results that can be associated in large part to the city domestic discharges , which are not yet transported into a WWTP. It is also important to note that the electrical conductivity is a dynamic parameter with a different peak in time for each monitoring station depending on the time of day and it is closely related to human activity in the city.

Scenarios e2 and e3 show a decrease in electrical conductivity, due to the projected connection of the interceptors to the WWTP of Bello, demonstrating the recovery that the river would have in this segment with the implementation of the PSMV. However, for these two scenarios, the most critical conditions are given by the discharge of the WWTP of Bello, which because of the significant volume of water to be discharged in this plant generates a significant impact on the river.

To recover the diversity and abundance of macro invertebrates biological quality in the channelized segment of the river, it is necessary not only to recover the water quality of the river and its tributaries, it is also necessary to implement other strategies associated with the hydraulics of the channel [22,23]. Measurements such as the reduction of the water velocity a variable that was not considered in the calculations due to the lack of information must be implemented.

What is concluded here is that despite the operation of the WWTP there is still a missing component to improve and it is the availability of natural habitats and colonization substrates and to have structures to protect them [24].

River modelling

Analyzing the results of the model in terms of BOD5, the reduction of this parameter is clear, the highest reductions are achieved when the interceptors were simulated to be connected to the future WWTP in Bello, this was done in scenarios 2 and 3. Scenario 1 only presents a small reduction in concentration of BOD5 due to the sanitation in the tributaries according to the PSMV until the year This reflects the right decision of EPM to prioritize investment to the construction of the treatment plant to improve the quality of the river.

The calculation time step used for the calculations was fixed at 1. We performed the integration using Euler's method; for the pH modeling, we used the Newton-Raphson method.

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To simulate exchanges in the hyporheic zone, we chose level I in the model, because it included zero-order and first-order oxidation of the fast-reacting dissolved components of BOD. To obtain the best adjustment, the modeling system assigns standard weights to various parameters so as to minimize the error between the observed and simulated data. The genetic algorithm was run for a population size of , with 50 generations of evolution, until we obtained only minor differences between the simulated results and the observed data. To test the model's ability to predict the water quality conditions during different hydrological periods, we ran the model again for the dry period, without changing the parameters that were calibrated for the rainy period.


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  7. Next, we used the model to simulate the water quality under different assumed changes scenarios in the watershed's inputs during the rainy period.