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Climate Change Effects at Watershed, Estuary and In-Stream Scales: Implications...
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Special Issue "Climate Change Effects at Watershed, Estuary and In-Stream Scales: Implications on Water Quality and Water Management"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (15 December 2020).

Special Issue Editor

Dr. Vladimir J. Alarcon
E-Mail Website
SciProfiles
Guest Editor
Civil Engineering Department, Universidad Diego Portales, Vergara 210, Santiago, Región Metropolitana, Chile
Interests: water resources management; Hydrologic, water quality, and hydrodynamic modeling using the HSPF, EFDC, ADH, and WASP computer models; the incorporation of remote sensing information into water resources models

Special Issue Information

Dear Colleagues,

Understanding how environmental variables subjected to increased climatic variability (attributed to climate change) affect the hydrologic and hydrodynamic regimes of watersheds and water bodies, and their related water quality processes, is of paramount importance. Current and future water management strategies to be implemented depend on having practical methods for predicting the involved phenomena. However, climate change effects on the hydrologic, hydrodynamic, and water quality processes occurring at watershed, estuary, and in-stream scales are difficult to assess and predict. Issues such as forcing and state variables measurement, spatial and temporal data downscaling, and linking global and local models are topics that are just beginning to be studied. This Special Issue aims to collect scientific and review papers addressing all of these topics. Papers that discuss the implications of climate change for water quality and sustainable water management are also welcomed, as long as the geographical container in which the research was undertaken is at the watershed, estuary, or in-stream scale.

Dr. Vladimir Jose Alarcon Calderon
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 papers will be 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.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Sediments
  • nutrients
  • water quality
  • hydrodynamics
  • hydrology
  • watershed
  • estuary
  • in-stream

Published Papers (1 paper)

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Research

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Article
Hindcasting and Forecasting Total Suspended Sediment Concentrations Using a NARX Neural Network
by
Vladimir J. Alarcon
Sustainability 2021, 13(1), 363; https://doi.org/10.3390/su13010363 - 03 Jan 2021
Viewed by 557
Abstract
Estimating and forecasting suspended sediments concentrations in streams constitutes a valuable asset for sustainable land management. This research presents the development of a non-linear autoregressive exogenous neural network (NARX) for forecasting sediment concentrations at the exit of Francia Creek watershed (Valparaiso, Chile). Details [...] Read more.
Estimating and forecasting suspended sediments concentrations in streams constitutes a valuable asset for sustainable land management. This research presents the development of a non-linear autoregressive exogenous neural network (NARX) for forecasting sediment concentrations at the exit of Francia Creek watershed (Valparaiso, Chile). Details are presented on input data selection, data splitting, selection of model architecture, determination of model structure, NARX training (optimization of model parameters), and model validation (hindcasting and forecasting). The study explored if the developed artificial neural network model is valid for forecasting daily suspended sediment concentrations for a complete year, capturing seasonal trends, and maximum and baseflow concentrations. Francia Creek watershed covers approximately 3.24 km2. Land cover within the catchment consists mainly of native and exotic vegetation, eroded soil, and urban areas. Input data consisting of precipitation and stream flow time-series were fed to a NARX network for forecasting daily suspended sediments (SST) concentrations for years 2013–2014, and hindcasting for years 2008–2010. Training of the network was performed with daily SST, precipitation, and flow data from years 2012 and 2013. The resulting NARX net consisted of an open-loop, 12-node hidden layer, 100 iterations, using Bayesian regularization backpropagation. Hindcasting of daily and monthly SST concentrations for years 2008 through 2010 was successful. Daily SST concentrations for years 2013 and 2014 were forecasted successfully for baseflow conditions (R2 = 0.73, NS = 0.71, and Kling-Gupta efficiency index (K-G) = 0.84). Forecasting daily SST concentrations for year 2014 was within acceptable statistical fit and error margins (R2 = 0.53, NS = 0.47, K-G = 0.60, d = 0.82). Forecasting of monthly maximum SST concentrations for the two-year period (2013 and 2014) was also successful (R2 = 0.69, NS = 0.60, K-G = 0.54, d = 0.84). Full article
(This article belongs to the Special Issue Climate Change Effects at Watershed, Estuary and In-Stream Scales: Implications on Water Quality and Water Management)
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