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Water Quality and Ecosystems in Times of Climate Change
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Water Quality and Ecosystems in Times of Climate Change

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".

Deadline for manuscript submissions: closed (31 March 2019) | Viewed by 38293

Special Issue Editor

Prof. Dr. Jim Perry

E-Mail Website
Guest Editor
Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota System, St. Paul, MN 55108, USA
Interests: climate change adaptation; ecosystem management; world heritage; watershed management; decision making
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

I would like to invite you contribute to an important Special Issue of Water focused on water quality and ecosystems in times of climate change. Papers in the Special Issue will focus on water quality management in ecosystems managed at the watershed scale. Ecosystem management takes an integrated approach, focusing on decisions to sustain ecosystem services. Water quality is a core ecosystem service from such watersheds. A watershed is a reasonable and effective scale for implementing ecosystem management. Land uses within a watershed often conflict in their delivery of ecosystem services. Ecosystem management attempts to bring together representative stakeholders to select future ecosystem services for which the watershed will be managed. The discussion with stakeholders requires consideration of trade-offs, requiring stakeholders to make sacrifices for the greater good. Inherent in such a consideration are several concerns. Ecosystem management requires careful consideration of the ways managers find representative stakeholders, consider how future climate conditions will influence or control water quality and how uncertainty will control our ability to manage for the future. Papers in this Special Issue will advance our understanding of decisions to be made and actions to be taken in the near term (e.g., five years) that will best prepare water quality and watershed managers for conditions that will occur in 2050.

Prof. Dr. Jim Perry
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Keywords

  • Ecosystem management
  • Watershed management
  • Climate change
  • Water quality
  • Decision making
  • Trade-offs
  • Future watershed conditions

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Published Papers (7 papers)

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Research

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8 pages, 1542 KiB  
Article
A Model to Forecast Methane Emissions from Topical and Subtropical Reservoirs on the Basis of Artificial Neural Networks
by Tabassum-Abbasi, Tasneem Abbasi, Chirchom Luithui and S. A. Abbasi
Water 2020, 12(1), 145; https://doi.org/10.3390/w12010145 - 2 Jan 2020
Cited by 15 | Viewed by 3352
Abstract
In view of the great paucity of information on the exact contributions of different causes which lead to different extents of emission of the greenhouse gas methane (CH4) form reservoirs, it is tremendously challenging to develop statistical or analytical models for [...] Read more.
In view of the great paucity of information on the exact contributions of different causes which lead to different extents of emission of the greenhouse gas methane (CH4) form reservoirs, it is tremendously challenging to develop statistical or analytical models for forecasting such emissions. Artificial neural networks (ANNs) have the ability to discern linear or non-linear relationships despite very limited data inputs and can recognize even complex patterns in a data set without a priori understating of the underlying mechanism. Hence, we have used ANNs to develop a model linking CH4 emissions to five of the reservoir parameters about which data is most commonly available in the prior art. Using a compendium of all available data on these parameters, of which a small part was kept aside for use in model validation, it has been possible to develop a model which is able to forecast CH4 emissions with a root mean square error of 37. It indicates a precision significantly better than the ones achieved in previous reports. The model provides a means to estimate CH4 emissions from reservoirs of which age, mean depth, surface area, latitude and longitude are known. Full article
(This article belongs to the Special Issue Water Quality and Ecosystems in Times of Climate Change)
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16 pages, 2671 KiB  
Article
Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs)
by Tabassum Abbasi, Tasneem Abbasi, Chirchom Luithui and Shahid Abbas Abbasi
Water 2019, 11(10), 2169; https://doi.org/10.3390/w11102169 - 18 Oct 2019
Cited by 14 | Viewed by 4432 | Correction
Abstract
Paddy fields, which are shallow man-made wetlands, are estimated to be responsible for ~11% of the total methane emissions attributed to anthropogenic sources. The role of water use in driving these emissions, and the apportioning of the emissions to individual countries engaged in [...] Read more.
Paddy fields, which are shallow man-made wetlands, are estimated to be responsible for ~11% of the total methane emissions attributed to anthropogenic sources. The role of water use in driving these emissions, and the apportioning of the emissions to individual countries engaged in paddy cultivation, are aspects that have been mired in controversy and disagreement. This is largely due to the fact that methane (CH4) emissions not only change with the cultivar type but also regions, climate, soil type, soil conditions, manner of irrigation, type and quantity of fertilizer added—to name a few. The factors which can influence these aspects also encompass a wide range, and have origins in causes which can be physical, chemical, biological, and combinations of these. Exceedingly complex feedback mechanisms, exerting different magnitudes and types of influences on CH4 emissions under different conditions, are operative. Similar is the case of nitrous oxide (N2O); indeed, the present level of understanding of the factors which influence the quantum of its emission is still more patchy. This makes it difficult to even understand precisely the role of the myriad factors, less so model them. The challenge is made even more daunting by the fact that accurate and precise data on most of these aspects is lacking. This makes it nearly impossible to develop analytical models linking causes with effects vis a vis CH4 and N2O emissions from paddy fields. For situations like this the bioinspired artificial intelligence technique of artificial neural network (ANN), which can model a phenomenon on the basis of past data and without the explicit understanding of the mechanism phenomena, may prove useful. However, no such model for CH4 or N2O has been developed so far. Hence the present work was undertaken. It describes ANN-based models developed by us to predict CH4 and N2O emissions using soil characteristics, fertilizer inputs, and rice cultivar yield as inputs. Upon testing the predictive ability of the models with sets of data not used in model development, it was seen that there was excellent agreement between model forecasts and experimental findings, leading to correlations coefficients of 0.991 and 0.96, and root mean square error (RMSE) of 11.17 and 261.3, respectively, for CH4 and N2O emissions. Thus, the models can be used to estimate CH4 and N2O emissions from all those continuously flooded paddy wetlands for which data on total organic carbon, soil electrical conductivity, applied nitrogen, phosphorous and potassium, NPK, and grain yield is available. Full article
(This article belongs to the Special Issue Water Quality and Ecosystems in Times of Climate Change)
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24 pages, 4430 KiB  
Article
Predicting Lake Quality for the Next Generation: Impacts of Catchment Management and Climatic Factors in a Probabilistic Model Framework
by S. Jannicke Moe, Raoul-Marie Couture, Sigrid Haande, Anne Lyche Solheim and Leah Jackson-Blake
Water 2019, 11(9), 1767; https://doi.org/10.3390/w11091767 - 24 Aug 2019
Cited by 17 | Viewed by 4794
Abstract
Lake ecosystems across the world are under combined pressures of eutrophication and climate change, which increase the risk of harmful cyanobacteria blooms, reduced ecological status, and degraded ecosystem services. In Europe, the third cycle of river basin management plans (2021–2027) according to the [...] Read more.
Lake ecosystems across the world are under combined pressures of eutrophication and climate change, which increase the risk of harmful cyanobacteria blooms, reduced ecological status, and degraded ecosystem services. In Europe, the third cycle of river basin management plans (2021–2027) according to the Water Framework Directive must take into account the potential impacts of climate change on water quality, including effects on relevant biological indicators. Here, we applied a Bayesian network as a meta-model for linking future climate and land-use scenarios for the time horizon 2050–2070, via process-based catchment and lake models, to cyanobacteria abundance and ecological status of a eutrophic lake. Building upon previous applications of the model, a new version was developed to include relevant climatic variables such as wind speed. Explorative scenarios showed that the combination of low wind and high temperature gave the most synergistic effects on cyanobacteria under high levels of eutrophication (Chl-a concentration). Considering the management target of good ecological status, however, the climate-related promotion of cyanobacteria blooms contributed most to degrading the ecological status at intermediate levels of eutrophication. Future developments of this model will aim to strengthen the link between climate variables and ecological responses, to make the model also useful for seasonal forecasting. Full article
(This article belongs to the Special Issue Water Quality and Ecosystems in Times of Climate Change)
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19 pages, 2259 KiB  
Communication
Making Sense of “Day Zero”: Slow Catastrophes, Anthropocene Futures, and the Story of Cape Town’s Water Crisis
by Nick Shepherd
Water 2019, 11(9), 1744; https://doi.org/10.3390/w11091744 - 21 Aug 2019
Cited by 27 | Viewed by 10643
Abstract
What form do the current and future catastrophes of the Anthropocene take? Adapting a concept from Rod Nixon, this communication makes a case for the notion of slow catastrophes, whose unfolding in space and time is uneven and entangled. Taking the events of [...] Read more.
What form do the current and future catastrophes of the Anthropocene take? Adapting a concept from Rod Nixon, this communication makes a case for the notion of slow catastrophes, whose unfolding in space and time is uneven and entangled. Taking the events of Cape Town’s Day Zero drought as a case study, this paper examines the politics and poetics of water in the Anthropocene, and the implications of Anthropogenic climate change for urban life. It argues that rather than being understood as an inert resource, fresh drinking water is a complex object constructed at the intersection between natural systems, cultural imaginaries, and social, political and economic interests. The extraordinary events of Day Zero raised the specter of Mad Max-style water wars. They also led to the development of new forms of solidarity, with water acting as a social leveler. The paper argues that the events in Cape Town open a window onto the future, to the extent that it describes something about what happens when the added stresses of climate change are mapped onto already-contested social and political situations. Full article
(This article belongs to the Special Issue Water Quality and Ecosystems in Times of Climate Change)
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28 pages, 3442 KiB  
Article
Impact of Urban Stormwater Runoff on Cyanobacteria Dynamics in A Tropical Urban Lake
by Talita F. G. Silva, Brigitte Vinçon-Leite, Bruno J. Lemaire, Guido Petrucci, Alessandra Giani, Cléber C. Figueredo and Nilo de O. Nascimento
Water 2019, 11(5), 946; https://doi.org/10.3390/w11050946 - 5 May 2019
Cited by 31 | Viewed by 5173
Abstract
Worldwide, eutrophication and cyanobacteria blooms in lakes and reservoirs are a great concern for water resources management. Coupling a catchment hydrological model and a lake model has been a strategy to assess the impact of land use, agricultural practices and climate change on [...] Read more.
Worldwide, eutrophication and cyanobacteria blooms in lakes and reservoirs are a great concern for water resources management. Coupling a catchment hydrological model and a lake model has been a strategy to assess the impact of land use, agricultural practices and climate change on water quality. However, research has mainly focused on large lakes, while urban reservoirs and their catchments, especially in tropical regions, are still poorly studied despite the wide range of ecosystem services they provide. An integrated modelling approach coupling the hydrological model Storm Water Management Model SWMM and the lake ecological model DYRESM-CAEDYM is proposed for Lake Pampulha (Brazil). Scenarios of increased imperviousness of the catchment and of reduction in the load of nutrients and total suspended solids (TSS) in dry weather inflow were simulated. Runoff water quality simulations presented a fair performance for TSS and ammonium (NH4+) while the dynamics of total phosphorus (TP) and nitrate (NO3−) were poorly captured. Phytoplankton dynamics in the lake were simulated with good accuracy (Normalized Mean Absolute Error, NMAE = 0.24 and r = 0.89 in calibration period; NMAE = 0.55 and r = 0.54 in validation period). The general trends of growth, decline and the magnitude of phytoplankton biomass were well represented most of the time. Scenario simulations suggest that TP reduction will decrease cyanobacteria biomass and delay its peaks as a consequence of orthophosphate (PO43−) concentration reduction in the lake surface layers. However, even decreasing TP load into Lake Pampulha by half would not be sufficient to achieve the water quality objective of a maximum concentration of 60 µg chla L−1. Increased imperviousness in the catchment will raise runoff volume, TSS, TP and NO3− loads into Lake Pampulha and promote greater cyanobacteria biomass, mainly in the beginning of the wet season, because of additional nutrient input from catchment runoff. Recovering Lake Pampulha water quality will require the improvement of the sanitation system. The lake water quality improvement will also require more sustainable and nature-based solutions for urban drainage in order to reduce non-point pollution through infiltration and retention of stormwater and to enhance natural processes, such as chemical sorption, biodegradation and phytoremediation. The integrated modelling approach here proposed can be applied for other urban reservoirs taking advantage of existing knowledge on Lake Pampulha. Full article
(This article belongs to the Special Issue Water Quality and Ecosystems in Times of Climate Change)
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18 pages, 5887 KiB  
Article
Potential Changes of Annual-Averaged Nutrient Export in the South Saskatchewan River Basin under Climate and Land-Use Change Scenarios
by Luis Morales-Marín, Howard Wheater and Karl-Erich Lindenschmidt
Water 2018, 10(10), 1438; https://doi.org/10.3390/w10101438 - 12 Oct 2018
Cited by 18 | Viewed by 4742
Abstract
Climate and land-use changes modify the physical functioning of river basins and, in particular, influence the transport of nutrients from land to water. In large-scale basins, where a variety of climates, topographies, soil types and land uses co-exist to form a highly heterogeneous [...] Read more.
Climate and land-use changes modify the physical functioning of river basins and, in particular, influence the transport of nutrients from land to water. In large-scale basins, where a variety of climates, topographies, soil types and land uses co-exist to form a highly heterogeneous environment, a more complex nutrient dynamic is imposed by climate and land-use changes. This is the case of the South Saskatchewan River (SSR) that, along with the North Saskatchewan River, forms one of the largest river systems in western Canada. The SPAtially Referenced Regression On Watershed (SPARROW) model is therefore implemented to assess water quality in the basin, in order to describe spatial and temporal patterns and identify those factors and processes that affect water quality. Forty-five climate and land-use change scenarios comprehended by five General Circulation Models (GCMs) and three Representative Concentration Pathways (RCPs) were incorporated into the model to explain how total nitrogen (TN) and total phosphorus (TP) export could vary across the basin in 30, 60 and 90 years from now. According to model results, annual averages of TN and TP export in the SSR are going to increase in the range 0.9–1.28 kg km − 2 year − 1 and 0.12–0.17 kg km − 2 year − 1 , respectively, by the end of the century, due to climate and land-use changes. Higher increases of TP compared to TN are expected since TP and TN are going to increase ∼36% and ∼21%, respectively, by the end of the century. This research will support management plans in order to mitigate nutrient export under future changes of climate and land use. Full article
(This article belongs to the Special Issue Water Quality and Ecosystems in Times of Climate Change)
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11 pages, 1020 KiB  
Commentary
Empowering the Next Generation of Watershed Decision-Makers: A Pedagogical Design
by Jim Perry and Louise Thompson
Water 2019, 11(4), 662; https://doi.org/10.3390/w11040662 - 31 Mar 2019
Cited by 4 | Viewed by 4382
Abstract
Watershed management is the art and practice of understanding stakeholder values for ecosystem services within a watershed and instituting management practices that consider trade-offs to sustain these goods and services. Effective watershed management practices are hydrologically defined, ecosystem-based, inclusive, and integrate biophysical as [...] Read more.
Watershed management is the art and practice of understanding stakeholder values for ecosystem services within a watershed and instituting management practices that consider trade-offs to sustain these goods and services. Effective watershed management practices are hydrologically defined, ecosystem-based, inclusive, and integrate biophysical as well as socioeconomic decisions. The uncertainties and unpredictability of climate change create an ambiguous backdrop to the increasingly social problem of water resource management. Inequities in watershed decision-making processes often lead to the reinforcement of power and resource imbalances. Future watershed managers must be able to engage across socioeconomic and cultural boundaries to support decisions that advance water as a human right in an uncertain future. We offer a design for a graduate level, 15-week university course that uses publicly available resources to help emerging watershed leaders prepare for an uncertain future. The design is interactive and constructivist, engaging the refereed literature and leading to an increased understanding of ecosystem-based watershed management under climate scenarios, with special attention to vulnerable populations. Full article
(This article belongs to the Special Issue Water Quality and Ecosystems in Times of Climate Change)
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