Impacts of Climate Change on Water Quality

Copetti, Diego; Carniato, Luca; Crise, A.; Guyennon, Nicolas; Palmeri, Luca; Pisacane, Giovanna; Struglia, Maria Vittoria; Tartari, Gianni

doi:10.1007/978-94-007-5781-3_10

Cited by 11 publications

(5 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the other three river basins, significant trends were detected essentially in summer, a season where the decline of the runoff was counterbalanced by an increased flow irregularity. An overall reduction of the runoff is expected in Southern Europe in a scenario of climatic warming, due to the increase of evapotranspiration and to the reduction of snow cover and precipitation [32], but present results support the importance of a higher resolution assessment of the related environmental and socio-economic impacts on river drainage basins [47]. Similarly, reliable streamflow simulations at regional scales are of basic importance to study these differences, but they have to be obtained applying appropriate downscaling techniques to global precipitation models [61,62].…”

Section: Seasonal To Decadal Trends Of River Flows and Coastal Hydrologymentioning

confidence: 49%

“…The Po is the largest river in Italy, with a drainage basin that hosts urban and industrial settlements and large areas devoted to intensive cropping and livestock activities [46]. As a consequence, nutrient transport by Po River is mainly of anthropogenic origin and it is due to rain-driven diffuse sources (20% for TN, 20% for TP), point sources (40% for TN, 80% for TP) and groundwater, springs and tributaries (40% for TN) [29,47]. Freshwater loads of the Po have shown a complex and partially unresolved long-term variability, which included strong multi-year oscillations [34] and a shift towards early spring peaks of the runoff [37].…”

Section: Geographical Settings Of River Basinsmentioning

confidence: 99%

See 1 more Smart Citation

Flow Regime and Nutrient-Loading Trends from the Largest South European Watersheds: Implications for the Productivity of Mediterranean and Black Sea’s Coastal Areas

Cozzi

Ibáñez

Lazăr

et al. 2018

Water

View full text Add to dashboard Cite

In the last century, large watersheds in Southern Europe have been impacted by a combination of anthropogenic and climatic pressures, which have rapidly evolved to change the ecological status of freshwater and coastal systems. A comparative analysis was performed for Ebro, Rhône, Po and Danube rivers, to investigate if they exhibited differential dynamics in hydrology and water quality that can be linked to specific human and natural forces acting at sub-continental scales. Flow regime series were analyzed from daily to multi-decadal scales, considering frequency distributions, trends (Mann–Kendall and Sen tests) and discontinuities (SRSD Method). River loads of suspended matter, nutrients and organic matter and the eutrophication potential of river nutrients were estimated to assess the impact of river loads on adjacent coastal areas. The decline of freshwater resources largely impacted the Ebro watershed on annual (−0.139 km3 yr−1) and seasonal (−0.4% yr−1) scales. In the other rivers, only spring–summer showed significant decreases of the runoff coupled to an exacerbated flow variability (0.1–0.3% yr−1), which suggested the presence of an enhanced regional climatic instability. Discontinuities in annual runoff series (every 20–30 years) indicated a similar long-term evolution of Rhône and Po rivers, differently from Ebro and Danube. Higher nutrient concentrations in the Ebro and Po (+50%) compared to Rhône and Danube and distinct stoichiometric nutrient ratios may exert specific impacts on the growth of plankton biomass in coastal areas. The overall decline of inorganic phosphorus in the Rhône and Po (since the 1980s) and the Ebro and Danube (since the 1990s) mitigated the eutrophication in coastal ecosystems inducing, however, a phase in which the role of organic phosphorus loads (Po > Danube > Rhône > Ebro) on coastal productivity could be more relevant. Overall, the study showed that the largest South European watersheds are differently impacted by anthropogenic and climatic forces and that this will influence their vulnerability to future changes of flow regime and water quality.

show abstract

Section: Seasonal To Decadal Trends Of River Flows and Coastal Hydrologymentioning

confidence: 49%

Section: Geographical Settings Of River Basinsmentioning

confidence: 99%

Flow Regime and Nutrient-Loading Trends from the Largest South European Watersheds: Implications for the Productivity of Mediterranean and Black Sea’s Coastal Areas

Cozzi

Ibáñez

Lazăr

et al. 2018

Water

View full text Add to dashboard Cite

show abstract

“…The inclusion in the model of a subsurface inflow based on available groundwater data effectively improved the reproduction of the observed water temperature profile. Bueche and Vetter (2014b) last analysed model performances under synthetic variations of the meteorological variables, concluding that DYRESM can reproduce long-term changes in water temperature due to climate change (see also Copetti et al, 2013).…”

Section: Hydrodynamic Modelsmentioning

confidence: 98%

Modelling physical and ecological processes in medium-to-large deep European perialpine lakes: a review

2021

Self Cite

View full text Add to dashboard Cite

In this paper we review a significant sample of the modelling studies carried out on medium-to-large deep European perialpine lakes (MLDEPLs). The reviewed bibliographic corpus was obtained querying Elsevier’s Scopus® database with a tailored search string on 8 January 2021. Results were filtered, accepting only journal papers written in English dealing with natural lakes having surface area > 10 km2. A list of 75 works was obtained, published between 1986 and 2021. Most studies have been carried out on Swiss lakes (44 out of 75 papers), Lake Geneva being the most investigated environment. A significant positive correlation was found between lake surface area and volume and the number of dedicated papers, suggesting that scientific attention is higher for environments characterised by large dimensions and relevant socio-economic interests. Both the number of papers and their citation count have experienced an exponential growth in time, pointing to a rising interest in quantitative modelling applications, but also to the increasing availability and ease of use of numerical modelling tools. Among the 75 selected papers, 55 employ a hydrodynamic driver, used alone or coupled with an ecological module, while the remnant 20 works adopt an ecological-only model. Among the papers employing hydrodynamic models, the use of three-dimensional (3D) drivers is surprisingly slightly more frequent (28 papers) than that of one-dimensional (1D) ones (26 papers), with most 3D applications having been published in the last 2011-2020 decade (24 papers). This reflects the interest on the hydrodynamic processes leading to the observed spatial heterogeneities in the biochemical properties of the MLDEPLs. However, coupling of ecological modules with 3D hydrodynamic drivers, to directly simulate these phenomena, is still restricted (2 papers) compared to that of 1D hydrodynamic drivers (8 papers), due to calibration and computational difficulties, which could be strongly reduced by future research achievements. Nevertheless, 1D models allow performing long-term prognoses considering multiple climate change and watershed management scenarios, due to their much smaller computational burden. The largest group of works dealing with ecological-only models (6 papers) is dedicated to applications of phosphorus budget models, which can above all be used to forecast variations in lake productivity in response to changes in the availability of the limiting nutrient. Graphical abstract

show abstract

“…There were certain protective measures along the whole SNWDPC MR. However, as an open canal, the water quality can be influenced by various factors [46]. According to previous research, many environmental factors such as land management, untreated flow, rainfall, air temperature, wind speed, sunshine duration, and water vapor pressure would possibly affect the processes of transport and fate of nitrogen, phosphorus, and other elements, or the biochemical reaction rate of algae, which will directly or indirectly affect dissolved oxygen, chlorophyll content, pH and other water quality indicators in water bodies [47].…”

Section: Data Descriptionmentioning

confidence: 99%

Daily Water Quality Forecast of the South-To-North Water Diversion Project of China Based on the Cuckoo Search-Back Propagation Neural Network

Shao

Nong

Tan

et al. 2018

Water

View full text Add to dashboard Cite

Water quality forecast is a critical part of water security management. Spatiotemporal and multifactorial variations make water quality very complex and changeable. In this article, a novel model, which was based on back propagation neural network that was optimized by the Cuckoo Search algorithm (hereafter CS-BP model), was applied to forecast daily water quality of the Middle Route of South-to-North Water Diversion Project of China. Nine water quality indicators, including conductivity, chlorophyll content, dissolved oxygen, dissolved organic matter, pH, permanganate index, turbidity, total nitrogen, and water temperature were the predictand. Seven external environmental factors, including air temperature, five particulate matter (PM2.5), rainfall, sunshine duration, water flow, wind velocity, and water vapor pressure were the default predictors. A data pre-processing method was applied to select pertinent predictors. The results show that the CS-BP model has the best forecast accuracy, with the Mean Absolute Percentage Errors (MAPE) of 0.004%–0.33%, and the lowest Root Mean Square Error (RMSE) of each water quality indicator in comparison with traditional Back Propagation (BP) model, General Regression Neural Network model and Particle Swarm Optimization-Back Propagation model under default data proportion, 150:38 (training data: testing data). When training data reduced from 150 to 140, and from 140 to 130, the CS-BP model still produced the best forecasts, with the MAPEs of 0.014%–0.057% and 0.004%–1.154%, respectively. The results show that the CS-BP model can be an effective tool in daily water quality forecast with limited observed data. The improvement of the Cuckoo Search algorithm such as calculation speed, the forecast errors reduction of the CS-BP model, and the large-scale impacts such as land management on different water quality indicators, will be the focus of future research.

show abstract

Impacts of Climate Change on Water Quality

Cited by 11 publications

References 50 publications

Flow Regime and Nutrient-Loading Trends from the Largest South European Watersheds: Implications for the Productivity of Mediterranean and Black Sea’s Coastal Areas

Flow Regime and Nutrient-Loading Trends from the Largest South European Watersheds: Implications for the Productivity of Mediterranean and Black Sea’s Coastal Areas

Modelling physical and ecological processes in medium-to-large deep European perialpine lakes: a review

Daily Water Quality Forecast of the South-To-North Water Diversion Project of China Based on the Cuckoo Search-Back Propagation Neural Network

Contact Info

Product

Resources

About