Thesis submitted in fulfilment of the requirements for the degree Doctor of Technology: Biomedical Technology in the Faculty of Health and Wellness Sciences at the Cape Peninsula University of Technology 2008 / River systems can become contaminated with micro-organisms and metals and the routine monitoring of these rivers is essential to control the occurrence of these contaminants in water bodies. This study was aimed at investigating the metal contamination levels in the Berg-, Plankenburg- and Diep Rivers in the Western Cape, South Africa, followed by the remediation of these rivers, using bioreactor systems. Sampling sites were identified and samples [water, sediment and biofilm (leaves, rocks and glass, etc.)] were collected along the Berg- and Plankenburg Rivers from May 2004 to May 2005 and for the Diep River, from February 2005 to November 2005. The concentrations of aluminium (Al), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb) and zinc (Zn) were determined using the nitric acid digestion method and analysed by Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). For the Berg River, the highest concentrations in water samples were recorded for Al, Mn and Fe at the agricultural area (Site A – chapter 2). In the sediment and biofilm samples, the highest metal concentrations were once again recorded for Al and Fe. The concentrations of Al and Fe were significantly higher (p < 0.05) than than Cu, Zn, Pb, Ni and Mn in water, sediment and biofilm samples, and were mostly higher than the quality guidelines recommended by the Department of Water Affairs and Forestry (DWAF, 1996) and the Canadian Council for the Ministers of the Environment (CCME, 2001). Possible sources of contamination in the Berg River could be due to the leaching or improper discarding of household waste from the informal- and established residential areas, as well as the improper discarding of pesticides at the agricultural area. For both the Plankenburg and Diep Rivers the Al and Fe concentrations were higher than all the other metals analysed for in sediment and water samples. The highest concentrations recorded in the Plankenburg River was 13.6 mg.l-1 (water - Week 18, Site B) and 15 018 mg.kg-1 (sediment - Week 1, Site C) for Al and 48 mg.l-1 (water - Week 43, Site A) and 14 363.8 mg.kg-1 (sediment - Week 1, Site A) for Fe. The highest concentrations recorded in the Diep River was 4 mg.l-1 (water - Week 1, Site A) and 19 179 mg.kg-1 (sediment - Week 1, Site C) for Al and 513 mg.l-1 (water - Week 27, Site A) and 106 379.5 mg.kg-1 (sediment - Week 9, Site C) for Fe. For most of the metals analysed the concentrations were higher than the recommended water quality guidelines as stipulated by the Department of Water Affairs and Forestry (DWAF, 1996b), the Canadian Council for the Ministers of the Environment (CCME, 2001) and the ‘World average’ (Martin and Windom, 1991). Point sources of pollution could not conclusively be identified, but the industrial and residential areas could have influenced the increased concentrations. Metal concentrations should be routinely monitored and the guidelines should be updated and revised based on the current state of the rivers and pollution influences. Micro-organisms isolated from flow cells after exposure to varying metal concentrations were investigated for possible metal-tolerance. A site where high metal concentrations were recorded along the Plankenburg River was investigated. The micro-organisms isolated from the flow cells were cultured and identified using the Polymerase Chain Reaction (PCR) technique, in conjunction with universal 16SrRNA primers. The phylogeny of the representative organisms in GenBank, were analysed using the Neighbour-joining algorithm in Clustal X. After exposure, the channels were stained with the LIVE/DEAD BacLightTM viability probe and visualised using Epifluorescence Microscopy. The results revealed that when exposed to the highest concentrations of Al (900 mg.l-1), Fe (1000 mg.l-1), Cu (10 mg.l-1) and Mn (80 mg.l-1), the percentage of dead cells increased, and when exposed to the lowest concentrations of Al (10 mg.l-1), Cu (0.5 mg.l-1), Mn (1.5 mg.l-1) and Zn (0.5 mg.l-1), no significant differences could be distinguished between live an dead cells. When exposed to the highest concentrations of Zn (40 mg.l-1) and Ni (20 mg.l-1), no significant differences between the live and dead cell percentages, were observed. The phylogenetic tree showed that a diverse group of organisms were isolated from the flow cells and that some of the isolates exhibited multiple metal resistance (Stenotrophomonas maltophilia strain 776, Bacillus sp. ZH6, Staphylococcus sp. MOLA:313, Pseudomonas sp. and Delftia tsuruhatensis strain A90 exhibited tolerance to Zn, Ni, Cu, Al, Fe), while other isolates were resistant to specific metals (Comamonas testosteroni WDL7, Microbacterium sp. PAO-12 and Sphingomonas sp. 8b-1 exhibited tolerance to Cu, Ni and Zn, respectively, while Kocuria kristinae strain 6J-5b and Micrococcus sp. TPR14 exhibited tolerance to Mn). The efficiency of two laboratory-scale and one on-site bioreactor system was evaluated to determine their ability to reduce metal concentrations in river water samples. The laboratory-scale bioreactors were run for a two-week and a three-week period and the on-site bioreactor for a period of ten weeks. Water (all three bioreactors) and bioballs (bioreactor two and on-site bioreactor) were collected, digested with 55% nitric acid and analysed using ICP-AES. The final concentrations for Al, Ni and Zn (bioreactor one) and Mn (bioreactor two), decreased to below their recommended concentrations in water samples. In the on-site, six-tank bioreactor system, the concentrations for Fe, Cu, Mn and Ni decreased, but still exceeded the recommended concentrations. The concentrations recorded in the biofilm suspensions removed from the bioballs collected from bioreactor two and the on-site bioreactor, revealed concentrations higher than those recorded in the corresponding water samples for all the metals analysed, except Fe. The bioballs were shown to be efficient for biofilm attachment and subsequent metal accumulation. The species diversity of the organisms isolated from the bioreactor (bioreactor two) experiment after three days (initial) differed from the organisms isolated after 15 days (final). Hydrogenophaga sp., Ochrobactrum sp, Corynebacterium sp., Chelatobater sp. and Brevundimonas sp. were present only at the start of the bioreactor experiment. The surviving populations present both in the beginning and at the end of the bioreactor experiment belonged predominantly to the genera, Pseudomonas and Bacillus. Metal-tolerant organisms, such as Bacillus, Pseudomonas, Micrococcus and Stenotrophomonas, amongst others, could possibly be utilised to increase the efficiency of the bioreactors. The bioreactor system should however, be optimised further to improve its efficacy.

Le bassin versant de l’Escaut (20 000 km²) est caractérisé par forte densité de population (plus de 500 habitants par km2) et une activité agro-pastorale intensive. Les rivières de ce bassin sont sévèrement affectées par les rejets d’eaux usées domestiques, les effluents d’élevage et les eaux de ruissellement des sols agricoles. Le but de cette étude est :(i) d’évaluer la qualité microbiologique de ces rivières ;(ii) d'identifier et de quantifier les différentes sources de contamination fécale à l’échelle du bassin de l’Escaut; (iii) d’étudier les processus qui contrôlent le devenir des bactéries fécales en rivière; (iv) de développer des modèles numériques sur la base des travaux expérimentaux permettant de prédire la concentration des bactéries indicatrices dans les rivières du bassin de l’Escaut.<p>L’évaluation de la qualité microbiologique des principales rivières du bassin est basée sur le dénombrement de deux indicateurs de contamination fécale (Escherichia coli et entérocoques intestinaux). Les abondances des deux indicateurs dans les principales rivières du bassin indiquent très clairement que les eaux et les sédiments de ces rivières sont fortement contaminés par des micro-organismes entériques. Les sources prédominantes de la pollution fécale de ces rivières sont les rejets des effluents des stations d’épuration. Les niveaux de contamination les plus élevés sont observés dans la Senne en aval de Bruxelles et s’expliquent par le faible débit de la Senne comparé aux débits des effluents des deux stations d’épuration de Bruxelles. Les niveaux de contamination atteignent leur maxima à l’aval de Bruxelles par temps de pluie en raison des surverses de réseaux unitaires.<p>Les connaissances acquises sur les apports des bactéries indicatrices par les sources ponctuelles et les sources diffuses et sur le devenir des bactéries indicatrices ont permis de développer un module décrivant la dynamique des E. coli dans les rivières. Ce module est original par le fait de considérer trois compartiments de bactéries fécales (libres, attachées aux particules dans la colonne d’eau et présentes dans les sédiments) qui sont affectés différemment par les processus de transport et de disparition. Ce module a été couplé à deux modèles décrivant l’hydrodynamique respectivement de l’ensemble des rivières du bassin (SENEQUE-EC) et de la partie fluviale de l’Escaut sous l’influence de la marée et son estuaire (SLIM-EC2). Ces deux modèles permettent de décrire la distribution temporelle et spatiale des E. coli dans les eaux de surfaces et de prévoir les modifications de la qualité microbiologique des eaux suite à des changements de gestion des eaux usées. <p> / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

A large river system typically derives the majority of its biomass from production within the floodplain. The Neches River in the Big Thicket National Preserve is a large blackwater river that has an extensive forested floodplain. Organic carbon was analyzed within the floodplain waters and the river (upstream and downstream of the floodplain) to determine the amount of organic carbon from the floodplain that is contributing to the nutrient dynamics in the river. Dissolved organic carbon was significantly higher at downstream river locations during high discharge. Higher organic carbon levels in the floodplain contributed to increases in organic carbon within the Neches River downstream of the floodplain when Neches River discharges exceeded 10,000 cfs. Hurricane Rita passed through the Big Thicket National Preserve in September 2005. Dissolved organic carbon concentrations recorded after Hurricane Rita in the Neches River downstream of the floodplain were significantly higher than upstream of the floodplain. Dissolved organic carbon was twice as high after the hurricane than levels prior to the hurricane, with floodplain concentrations exceeding 50 ppm C. The increase in organic carbon was likely due to nutrients leached from leaves, which were swept from the floodplain trees prior to normal abscission in the fall. A continuum of leaf breakdown rates was observed in three common floodplain species of trees: Sapium sebiferum, Acer rubrum, and Quercus laurifolia. Leaves collected from blowdown as a result of Hurricane Rita did not break down significantly faster than leaves collected prior to abscission in the fall. Processing coefficients for leaf breakdown in a continuously wet area of the floodplain were significantly higher than processing coefficients for leaf breakdown on the floodplain floor. The forested floodplain of the Neches River is the main contributor of organic carbon. When flow is greater than 10,000 csf, the floodplain transports organic carbon directly to the river, providing a source of nutrition for riverine organisms and contributing to the overall health of the ecosystem.

Translational ecology and adaptive management strategies were incorporated into the Fordville Dam Nutrient Total Maximum Daily Load (TMDL) case study to determine if these two techniques were compatible to the North Dakota TMDL Program. A case study summary of the Fordville Dam Nutrient TMDL was discussed to provide contrast and comparison of the current TMDL program strategy and systematic improvements that could be made with the incorporation of translational ecology and adaptive management. Translational ecology is an effective way to bridge the information barrier through open communication between the stakeholders and scientists while creating a mutual learning experience. Adaptive management is beneficial to a TMDL implementation plan because it allows stakeholders and resource managers to become involved in management decisions and develop a better understanding of the ecosystem. Therefore, combining translational ecology and adaptive management would make the TMDL process more effective, through better communication and a flexible management plan.

Pathogens, such as Escherichia coli and fecal coliforms, are causing the majority of water quality impairments in U.S., making up ~87% of this grouping's violations. Predicting and characterizing source, transport processes, and microbial survival rates is extremely challenging, due to the dynamic nature of each of these components. This research built upon current analytical methods that are used as exploratory tools to predict pathogen indicator counts across regional scales. Using a series of non-parametric methodologies, with spatially explicit predictors, 6657 samples from non-estuarine lotic streams were analyzed to make generalized predictions of regional water quality. 532 frequently sampled sites in the Oregon Coast Range Ecoregion, were parsed down to 93 pathogen sampling sites in effect to control for spatial and temporal biases. This generalized model was able to provide credible results in assessing regional water quality, using spatial techniques, and applying them to infrequently or unmonitored catchments. This model's 56.5% explanation of variation, was comparable to other researchers' regional assessments. This research confirmed linkages to land uses related to anthropogenic activities such as animal operations and agriculture, and general riparian conditions.

Thesis (Ph.D.)--Joint Program in Oceanography (Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2002. / Includes bibliographical references. / This thesis addresses the sources and transport of nuclear weapons related contamination in the Ob River region, Siberia. In addition to being one of the largest rivers flowing into the Arctic Ocean, the bulk of the former Soviet Union's nuclear fuel reprocessing and weapons testing facilities (i.e. Mayak, Tomsk-7, and Semipalitinsk) are located within the Ob drainage basin. The atom ratios 240Pu/239Pu, 237Np/239Pu, and 137Cs/240Pu, measured by magnetic-sector ICP-MS, are used to distinguish between contamination derived from global fallout and contamination derived from local sources. Deposition chronologies estimated for sediment cores are used to construct a record of weapons related contamination at the sites sampled. Contaminant records indicate that in addition to debris from atmospheric weapons tests, materials derived from local sources have also played a role in nuclear weapons related contamination of the Ob region. Isotopic data presented in this study clearly demonstrate that non-fallout contamination has been transported the full length of the Tobol, Irtysh, and Ob Rivers (i.e. the tributaries draining Mayak, Semipalitinsk, and Tomsk-7, respectively). In several instances, unique isotopic compositions are observed in sediments collected from tributaries draining each of the suspected non-fallout sources. In such cases, these materials and their deposition ages have been used to link contamination in the Ob delta to Mayak, Tomsk-7, or Semipalitinsk. Linear transport rate estimates (km yr-1) indicate that contaminated sediments transit between source tributaries and the Ob delta on time-scales of [less than or equal to] l year. / (cont.) These estimates suggest that a catastrophic release of contamination due to dam failure at one of the many reservoirs located at both Mayak and Tomsk-7 that contain high levels of radioactive waste would result in measurable levels of contamination in the delta within as little as 1 year. Isotopic concentrations in sequentially extracted sediments containing weapons related contamination reveal that the majority of plutonium and neptunium (80 to 90 percent) behaves in a similar fashion regardless of the source and is removed by treating the sediments with citrate-dithionite. This indicates that plutonium and neptunium are not truly refractory and likely associate with redox sensitive sedimentary components. Isotopic ratios measured in extracted fractions suggest that only a minor fraction of contamination is associated with acid leachable or acid digestible sedimentary phases. / by Timothy Cope Kenna. / Ph.D.

No description available.

Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Environmental Health in the Faculty of Applied Sciences at the Cape Peninsula University of Technology, 2013 / Water is an important daily requirement and in a clean, pure form, it promotes health and well-being. In addition to South Africa being one of the driest countries in the world, water availability is also being compromised by massive pollution of remaining water sources. The Berg- and Plankenburg Rivers are two of the surface water sources in the Western Cape, South Africa, which are highly polluted by sewage, industrial and agricultural run-off. The current investigation was aimed at comparing diagnostic tools, which are employed by municipalities and food industries, and molecular based techniques to routinely monitor water for indicator organisms in time- and cost-effective manner. These rivers were sampled twice a month (July 2010 to January 2011) at the sites closest to the informal settlements of Kayamandi in Stellenbosch (Plankenburg River) and Mbekweni in Paarl (Berg River). The contamination levels of the two river systems were evaluated by the enumeration of Escherichia coli and coliforms using the Colilert 18® system, Membrane Filtration (MF) and Multiple Tube Fermentation (MTF) techniques. The highest faecal coliform count of 9.2 × 106 microorganisms/100 ml was obtained in weeks 21 and 28 from the Plankenburg River system by the MTF technique, while the lowest count of 1.1 × 103 microorganisms/100 ml was obtained in week one for both river systems by the MTF technique. The highest E. coli count of 1.7 × 106 microorganisms/100 ml was obtained from the Berg River system (week 9) using the MTF technique, while the lowest count of 3.6 × 102 microorganisms/100 ml was obtained by the MF technique from the Plankenburg River system. The coliform and E. coli counts obtained by the enumeration techniques thus significantly (p > 0.05) exceeded the guidelines of 2000 microorganisms/100 ml stipulated by the Department of Water Affairs and Forestry (DWAF, 1996) for water used in recreational purposes. Overall the results obtained in this study showed that the water in the Berg- and Plankenburg River systems is highly polluted, especially where these water sources are used for irrigational and recreational purposes. For the coliform and E. coli counts obtained using the three enumeration techniques, it was noted that the MTF technique was more sensitive and obtained higher counts for most of the sampling weeks. However, the media (Membrane lactose glucuronide agar) used in the MF technique also effectively recovered environmentally stressed microbial cells and it was also better for the routine selection and growth of coliforms and E. coli. While E. coli and total coliforms were detected utilising the Colilert 18® system, accurate enumeration values for these two indicator groups was not obtained for the entire sampling period for both river systems. It has previously been shown that dilutions (up to 10-3) of highly polluted waters increase the accuracy of the Colilert 18® system to enumerate colifoms and E. coli in marine waters. As the results obtained utilising the Colilert 18® system were also not comparable to the MF and MTF techniques it is recommended that highly polluted water samples be diluted to increase the accuracy of this system as a routine enumeration technique. Water samples were directly inoculated onto MacConkey, Vile Red Bile (VRB) agar and the Chromocult Coliform agar (CCA) and single colonies were inoculated onto nutrient agar. Chromocult coliform agar proved to be more sensitive than MacConkey and VRB agar for the culturing of E. coli and coliforms. Preliminary identification of these colonies was done using the RapID ONE and API 20 E systems. The most isolated Enterobacteriaceae species by both systems, included Klebsiella pneumoniae, Klebsiella oxytoca, Escherichia coli and Enterobacter cloacae in both river systems. The API 20 E system was more sensitive in the preliminary identification of the various isolates, as greater species diversity was obtained in comparison to the RapID ONE system. The Polymerase Chain Reaction (PCR) was firstly optimised using positive Enterobacteriaceae species. The optimised method was then applied to the analysis of river water samples, which were centrifuged to harvest the bacterial cells, with DNA extracted using the boiling method. The extracted DNA was amplified using conventional PCR with the aid of species specific primers. The Enterobacteriaceae species that were detected throughout the study period in both river systems include Serratia marcescens, Escherichia coli, Klebsiella pneumoniae and Bacillus cereus. Conventional PCR was the most reliable and sensitive technique to detect Enterobacteriaceae to species level in a short period of time when compared to RapID ONE and the API 20 E systems. Multiplex PCR was optimised using the positive pathogenic E. coli strains namely, Enteropathogenic E. coli (EPEC), Enteroinvasive E. coli (EIEC), Enterohaemorrhagic E. coli (EHEC) and Enteroaggregative E. coli (EAEC). It was then employed in river water sample analysis and enabled the detection of EAEC, EHEC, and EIEC strains in Berg River system, with only the EAEC detected in the Plankenburg River system. Real-time PCR was used to optimise the multiplex PCR in the amplification of E. coli strains and successfully reduced the time to obtain final results when using control organisms. Real-time PCR was found to be more sensitive and time-effective in the identification of E. coli strains, and also more pronounced DNA bands were observed in real-time PCR products compared to conventional-multiplex PCR amplicons. To sustain the services provided by the Berg- and Plankenburg Rivers in the Western Cape (South Africa), these water sources should frequently be monitored, results assessed and reported according to the practices acknowledged by responsible bodies. It is therefore recommended that the enumeration techniques be used in conjunction with the very sensitive PCR technique for the accurate detection of coliforms and E. coli in river water samples.

The increased demand for wood and fiber from a continually shrinking land base has resulted in the use of intensively managed forest plantations. The concentration of timber production on the most suitable sites allows the world's demand for forest products to be met on less land and enable native forests to be conserved. Because much of the water flowing in rivers in the U.S. originates as precipitation in forests, there is a justified concern about the impacts of forest management on water quality. Nutrient concentrations were measured in eight streams from October 2002 to September 2011 to assess nutrient response to contemporary forest practices at the Hinkle Creek Paired Watershed Study in the Oregon Cascades. This period of time included a two-year pre-treatment calibration between control and treatment watersheds, a fertilization treatment of both basins in October 2004, and a post-treatment period from 2005 to 2011. A treatment schedule comprised of two temporally explicit harvest entries was used to assess the effects of clearcutting at the non-fish-bearing headwater scale and the fish-bearing watershed scale. Stream water samples were analyzed for nitrogen, phosphorus, calcium, sodium, potassium, magnesium, sulfate, chloride, and silicon as well as specific conductance, pH, and alkalinity. Programmable water samplers were used to take water samples during fall freshets in November 2009 to assess the stream water discharge versus NO₃ + NO₂ concentration relationship. All treatment watersheds showed a statistically significant increase in NO₃ + NO₂ concentrations after clearcutting (p < 0.001). The slope of the streambed through the disturbance was a stronger predictor of the magnitude of the response than was the magnitude of disturbance. Ammonia and organic nitrogen displayed notable increases after harvest treatment, but these increases were attributed to increases in the control watersheds. Phosphorus showed a response to timber harvest in one headwater stream. The remaining nutrients showed a small decrease in the control and treatment watersheds for the period after harvest. There was some evidence to suggest that the addition of urea nitrogen to both basins may have caused an increase in in-stream biota uptake of these nutrients. The storm response results showed that NO₃ + NO₂ concentrations in stream water increase with discharge during small storms that occur after periods of negligible precipitation. Concentrations of NO₃ + NO₂ observed during the calibration period were similar to concentrations observed in an old-growth forest in the H.J. Andrews, suggesting that nutrient processing within the Hinkle Creek watershed had returned to levels that existed prior to its initial harvest sixty years ago. This finding helps to assess long-term impacts of shorter rotation timber harvest of regenerated Douglas-fir stands characteristic of industrialized timber harvest in Oregon. / Graduation date: 2012

Ongoing development of modern society, based on consumption of goods and services, leads to the increase of compulsoriness of economic agents to face market requirements by increasing the degree of local and regional industrialization. Establishment of new economic activities generates negative pressures on the environment and surface waters, generating increased pollution, manifested by vulnerability of aquatic ecosystems to stressors. Preliminary studies carried out within the doctoral thesis entitled 'Research on the evolution, magnitude and complexity of the impact of economic activities on the East Jiu' include information on characteristic elements of the East Jiu River basin, in accordance with the Water Framework Directive 2000/60/CE. The objectives of the field research aimed to identify economic activities in the eastern Jiu Valley generating an impact on the environment (especially the mining industry, but also timber exploitation and processing, local agriculture, animal husbandry and waste storage), establishing a quarterly monitoring program of the river basin, identification of flora and fauna species and identification of areas vulnerable to potential pollution. Based on observations made in situ and on information obtained from the evolution process of the monitoring program, the appropriate methodologies for assessing physical-chemical and ecological quality of the water were selected. Study of the evolution of the impact generated by economic activities on the East Jiu was carried out by mathematical modelling, with finite volumes, of the East Jiu River basin and plotting of pollutant dispersion maps. The magnitude and complexity of impact generated by economic activities was studied by using a complex system based on fuzzy logic, designed based on interactions between natural and artificial systems, between physical-chemical indicators of water and ecosystem. The research carried out substantiates in development of necessary technical measures to reduce the impact generated by economic activities located in eastern Jiu Valley, without significantly changing the hydrodynamics of the river basin. Following research, during different research stages, methods, techniques and tools were designed and accomplished with the help of which, water and aquatic ecosystems’ quality can be assessed, as well as the impact generated by human activity on the Jiu River, at a given moment and/or continuously.:CONTENT ACKNOWLEDGEMENTS SUMMARY LIST OF FIGURES LIST OF TABLES ABBREVIATIONS INTRODUCTION PURPOSE OF THE THESIS AND RESEARCH METHODOLOGY CHAPTER 1 THE EAST JIUL RIVER HYDROGRAPHIC BASIN 1.1. Soil and subsoil of the Eastern part of Jiu Valley 1.2. Climate description of the Eastern part of Jiu Valley 1.3. Geology particularities of the Eastern part of Jiu Valley 1.4. Groundwater features of the Eastern part of Jiu Valley 1.5. Flora and fauna of the Eastern part of Jiu Valley CHAPTER 2 SOURCES OF IMPACT ON THE QUALITY OF WATER, RIPARIAN, TERRESTRIAL AND AQUATIC ECOSYSTEMS 2.1. Mining industry 2.2. Wood processing industry in the Eastern part of Jiu Valley 2.3. Urban agriculture and local animal husbandry 2.4. Inappropriate urban household waste storage CHAPTER 3 MONITORING PROGRAM AND METHODS OF EVALUATION OF THE QUALITY OF THE EAST JIUL RIVER 3.1. Establishment of monitoring (control) sections 3.2. Monitoring program of the East Jiu River basin 3.3. Sampling, transport and analysis of water samples 3.4. Methodology used to establish the water quality CHAPTER 4 QUALITY ASSESSMENT OF WATER IN THE EASTERN JIU HYDROGRAPHIC BASIN 4.1. Section 1 - Jieț River - upstream of household settlements (blank assay) 4.2. Section 2 - East Jiu River - in the area of Tirici village 4.3. Section 3 - Răscoala brook - before the confluence with East Jiu River 4.4. Section 4 - East Jiu River - after the confluence with the Răscoala brook 4.5. Section 5 - Taia River - upstream of the confluence with East Jiu River 4.6. Section 6 - East Jiu River - before the confluence with the Taia River 4.7. Section 7 - East Jiu River - after the confluence with the Taia River 4.8. Section 8 - Jiet River downstream of household settlements 4.9. Section 9 - East Jiu River - after the confluence with the Jieț River 4.10. Section 10 - East Jiu River - before the confluence with Banița River 4.11. Section 11 - Roşia River - upstream of household settlements 4.12. Section 12 - Bănița River - after the confluence with the Roșia River 4.13. Section 13 - East Jiu River - after the confluence with the Banița River 4.14. Section 14 - Maleia River - before the confluence with East Jiu River 4.15. Section 15 - Slătioara River - before the confluence with East Jiu River 4.16. Section 16 – East Jiu River - before the confluence with West Jiu River CHAPTER 5 INFLUENCES OF PHYSICAL-CHEMICAL FACTORS ON AQUATIC ICHTHYOFAUNA IN THE EAST JIU RIVER BASIN 5.1. Total suspended solids and aquatic ecosystems 5.2. Acidity or basicity reaction of surface watercourses 5.3. Aquatic ecosystem requirements for gas oversaturation 5.4. Nitrogenous compounds in watercourse 5.5. Phenols, aquatic ecosystems and water quality CHAPTER 6 ANALYSIS OF THE IMPACT GENERATED BY ECONOMIC ACTIVITIES IN THE EASTERN PART OF JIU VALLEY 6.1. Impact analysis of mining industry in the Eastern Part of Jiu Valley 6.2. The general impact of Eastern Jiu Valley dumps to water quality 6.3. Research on effective infiltration in the Eastern part of Jiu Valley 6.4. Research on groundwater quality in the Eastern part of Jiu Valley 6.5. Analysis of the impact generated by local micro-agriculture 6.6. Analysis of the impact generated by deforestation and wood processing 6.7. Analysis of the impact generated by non-compliant landfilling of waste CHAPTER 7 EVOLUTION OF THE IMPACT GENERATED BY ECONOMIC ACTIVITIES IN THE EASTERN JIU VALLEY 7.1. Analysis of the dynamic elements of the watercourse - RMA2 mode 7.2. Analysis of pollutants concentration evolution in the water course - RMA4 module 7.3. Computational field and composition of the energy model of the East Jiu River 7.4. Extension and evolution of the impact generated by economic activities on the East Jiu River 7.5. Extension and evolution of the impact caused by organic pollution of the East Jiu River CHAPTER 8 MAGNITUDE AND COMPLEXITY OF THE IMPACT GENERATED BY ECONOMIC ACTIVITIES IN THE EASTERN JIU VALLEY 8.1. Definition of input linguistic variables 8.2. Linguistic outputs of the fuzzy interference system 8.3. Defining the Black Box set of rules 8.4. Proficiency testing of complex systems based on fuzzy logic 8.5. While it is all about the wheel do not forget about the cube CONCLUSIONS AND PERSONAL CONTRIBUTIONS REFERENCES