Special Issue "River Flow in Cold Climate Environments"

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

Deadline for manuscript submissions: 28 February 2022.

Special Issue Editors

Dr. Masoud Irannezhad
E-Mail Website
Guest Editor
Institute for Water Security and Global Change (iWatch), School of Environmental Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen 518055, China
Interests: atmosphere- climate- & water interactions; water-related extreme events; hydrological processes in cold climate regions; satellite remote sensing for water resources; big environmental data analysis (>20 tb) and pattern recognition; artificial intelligence and deep learning
Dr. David Gustafsson
E-Mail Website
Guest Editor
Swedish Meteorological and Hydrological Institute (SMHI), Sweden
Interests: Observations and modelling of hydrological systems; Cold climate hydrology; Coupled modelling (hydrological-meteorological-climate models); Earth observations and data assimilation

Special Issue Information

Dear Colleagues,

In cold climate environments on Earth, river flow plays a crucial role in sustainable development by providing drinking water to over one billion people, strongly supporting crop production, generating hydropower energy, comforting urbanization, and preserving different unique ecosystems. Impacting snow, glacier, and permafrost hydrological processes, both of climate change and anthropogenic activities generally alter cold-regions river flows and thereby poses different ecological, economic, and social challenges for humanity. Hence, improving our knowledge about observed and projected modifications in the river flows in cold climate environments under climate change and/or human interventions is substantially important for addressing such challenges. This special issue aims at bringing together pure theoretical and applied researches on a wide range of topics related to the river flow, but with a focus primarily on cold climate environments. We especially encourage submissions on:

  • Observed and projected changes in river flow
  • Natural and regulated river flow
  • Climate change impacts on river discharge regime
  • Effects of anthropogenic activities (e.g. damming, land use-land cover changes, etc.) on river flows
  • Snowmelt floods
  • Snow droughts
  • Environmental river flow
  • River flow modelling
  • Upstream-downstream interactions in response to river flow changes
  • Influential climate teleconnections (e.g. NAO) for river discharge fluctuations
  • Water quality assessment under river flow alterations
  • Application of remote sensing and data assimilation
  • Changes in river ice regimes

Dr. Masoud Irannezhad
Dr. David Gustafsson
Guest Editors

Manuscript Submission Information

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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. Water 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 2000 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

  • Cold-regions river flow
  • Snow, glacier, and permafrost hydrological processes
  • Hydrological extremes
  • Climate change
  • Human interventions
  • Remote sensing
  • Water quality
  • Upstream and downstream
  • Basin characteristics
  • Climate teleconnections
  • River ice regime

Published Papers (4 papers)

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Research

Article
Streamflow Changes of Small and Large Rivers in the Aldan River Basin, Eastern Siberia
Water 2021, 13(19), 2747; https://doi.org/10.3390/w13192747 - 03 Oct 2021
Viewed by 294
Abstract
The flow of large northern rivers has increased, but regional patterns of changes are not well understood. The aim of this study is the estimation of monthly discharge changes of the 11 river catchments in the Aldan River basin in Eastern Siberia, the [...] Read more.
The flow of large northern rivers has increased, but regional patterns of changes are not well understood. The aim of this study is the estimation of monthly discharge changes of the 11 river catchments in the Aldan River basin in Eastern Siberia, the largest Lena River tributary and the sixth largest river in Russia. We considered the trend dependence on month, number of years in the sample, finish and start years, and basin area. The median fraction of samples with no trend, positive and negative trends are 70.5%, 28.5%, and 1%, respectively. Longer samples tend to show more positive trends than shorter ones. There is an increasing fraction of samples with positive trends as a function of later sample end year, whereas the start year does not result in a similar pattern. The larger basins, with one exception, have more positive trends than smaller ones. The trends in monthly streamflow have prominent seasonality with absence of positive trends in June and increasing fraction of samples with positive trends from October till April. The study reports the recent streamflow changes on the rarely analyzed rivers in Eastern Siberia, where air temperature rises faster than in average on the globe. The study results are important for water resources management in the region and better understanding of current environmental changes. Full article
(This article belongs to the Special Issue River Flow in Cold Climate Environments)
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Article
Streamflow Changes in the Headwater Area of Yellow River, NE Qinghai-Tibet Plateau during 1955–2040 and Their Implications
Water 2021, 13(10), 1360; https://doi.org/10.3390/w13101360 - 14 May 2021
Viewed by 559
Abstract
Human activities have substantially altered present-day flow regimes. The Headwater Area of the Yellow River (HAYR, above Huanghe’yan Hydrological Station, with a catchment area of 21,000 km2 and an areal extent of alpine permafrost at ~86%) on the northeastern Qinghai-Tibet Plateau, Southwest [...] Read more.
Human activities have substantially altered present-day flow regimes. The Headwater Area of the Yellow River (HAYR, above Huanghe’yan Hydrological Station, with a catchment area of 21,000 km2 and an areal extent of alpine permafrost at ~86%) on the northeastern Qinghai-Tibet Plateau, Southwest China has been undergoing extensive changes in streamflow regimes and groundwater dynamics, permafrost degradation, and ecological deterioration under a warming climate. In general, hydrological gauges provide reliable flow records over many decades and these data are extremely valuable for assessment of changing rates and trends of streamflow. In 1998–2003, the damming of the Yellow River by the First Hydropower Station of the HAYR complicated the examination of the relations between hydroclimatic variables and streamflow dynamics. In this study, the monthly streamflow rate of the Yellow River at Huanghe’yan is reconstructed for the period of 1955–2019 using the double mass curve method, and then the streamflow at Huagnhe’yan is forecasted for the next 20 years (2020–2040) using the Elman neural network time-series method. The dam construction (1998–2000) has caused a reduction of annual streamflow by 53.5–68.4%, and a more substantial reduction of 71.8–94.4% in the drier years (2003–2005), in the HAYR. The recent removal of the First Hydropower Station of the HAYR dam (September 2018) has boosted annual streamflow by 123–210% (2018–2019). Post-correction trends of annual maximum (QMax) and minimum (QMin) streamflow rates and the ratio of the QMax/QMin of the Yellow River in the HAYR (0.18 and 0.03 m3·s−1·yr−1 and −0.04 yr−1, respectively), in comparison with those of precorrection values (−0.11 and −0.004 m3·s−1·yr−1 and 0.001 yr−1, respectively), have more truthfully revealed a relatively large hydrological impact of degrading permafrost. Based on the Elman neural network model predictions, over the next 20 years, the increasing trend of flow in the HAYR would generally accelerate at a rate of 0.42 m3·s−1·yr−1. Rising rates of spring (0.57 m3·s−1·yr−1) and autumn (0.18 m3·s−1·yr−1) discharge would see the benefits from an earlier snow-melt season and delayed arrival of winter conditions. This suggests a longer growing season, which indicates ameliorating phonology, soil nutrient availability, and hydrothermal environments for vegetation in the HAYR. These trends for hydrological and ecological changes in the HAYR may potentially improve ecological safety and water supplies security in the HAYR and downstream Yellow River basins. Full article
(This article belongs to the Special Issue River Flow in Cold Climate Environments)
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Article
Short-Term River Flow Forecasting Framework and Its Application in Cold Climatic Regions
Water 2020, 12(11), 3049; https://doi.org/10.3390/w12113049 - 30 Oct 2020
Viewed by 628
Abstract
Catchments located in cold weather regions are highly influenced by the natural seasonality that dictates all hydrological processes. This represents a challenge in the development of river flow forecasting models, which often require complex software that use multiple explanatory variables and a large [...] Read more.
Catchments located in cold weather regions are highly influenced by the natural seasonality that dictates all hydrological processes. This represents a challenge in the development of river flow forecasting models, which often require complex software that use multiple explanatory variables and a large amount of data to forecast such seasonality. The Athabasca River Basin (ARB) in Alberta, Canada, receives no or very little rainfall and snowmelt during the winter and an abundant rainfall–runoff and snowmelt during the spring/summer. Using the ARB as a case study, this paper proposes a novel simplistic method for short-term (i.e., 6 days) river flow forecasting in cold regions and compares existing hydrological modelling techniques to demonstrate that it is possible to achieve a good level of accuracy using simple modelling. In particular, the performance of a regression model (RM), base difference model (BDM), and the newly developed flow difference model (FDM) were evaluated and compared. The results showed that the FDM could accurately forecast river flow (ENS = 0.95) using limited data inputs and calibration parameters. Moreover, the newly proposed FDM had similar performance to artificial intelligence (AI) techniques, demonstrating the capability of simplistic methods to forecast river flow while bypassing the fundamental processes that govern the natural annual river cycle. Full article
(This article belongs to the Special Issue River Flow in Cold Climate Environments)
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Article
Contemporary Snow Changes in the Karakoram Region Attributed to Improved MODIS Data between 2003 and 2018
Water 2020, 12(10), 2681; https://doi.org/10.3390/w12102681 - 25 Sep 2020
Cited by 3 | Viewed by 1639
Abstract
Snowmelt significantly contributes to meltwater in most parts of High Mountain Asia. The Karakoram region is one of these densely glacierized and snow-covered regions. Several studies have reported that glaciers in the Karakoram region remained stable or experience slight mass loss. This trend [...] Read more.
Snowmelt significantly contributes to meltwater in most parts of High Mountain Asia. The Karakoram region is one of these densely glacierized and snow-covered regions. Several studies have reported that glaciers in the Karakoram region remained stable or experience slight mass loss. This trend has called for further investigation to understand changes in other components of the cryosphere. This study estimates the comparative snow cover area (SCA) and snowline altitude (SLA) changes between 2003 and 2018 in the Karakoram region and its subbasins, including Hunza, Shigar, and Shyok. We used three different 8-day composite snow products of the Moderate Resolution Imaging Spectroradiometer (MODIS) in this study including (1) Original Aqua (MYD10A2), (2) Original Terra (MOD10A2), and (3) Improved Terra-Aqua (MOYDGL06*) snow products from 2003 to 2018. We used Mann–Kendall and Sen Slope methods to assess trends in the SCA and SLA. Our results show that the original snow products are significantly biased when investigating seasonal and annual trends. However, discarding a cloud cover of >20% in the original products improves the results and makes them more comparable to our improved snow product. The original products (without cloud removal) overestimate the SCA during summer and underestimate the SCA during winter and year-round throughout the Karakoram region. The bias in the mean annual SCA between improved and Aqua and Terra cloud threshold products for the Karakoram region is found to be −1.67% and 1.1%, respectively. The improved (MOYDGL06*) product reveals a statistically insignificant decreasing trend of the SCA on the annual scale between 2003 and 2018 in the Karakoram region and all three subbasins. The annual trends decreased at −0.13%, −0.1%, −0.08%, and −0.05% in the Karakoram, Hunza, Shigar, and Shyok, respectively. The monthly trends were slightly positive overall in December. The annual maximum SLA shows a statistically significant upward trend of 13 m above sea level (m a.s.l.) per year for the entire Karakoram region. This finding suggests a significant uncertainty in water resource planning based on the original snow data, and this study recommends the use of the improved snow product for a better understanding. Full article
(This article belongs to the Special Issue River Flow in Cold Climate Environments)
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