Special Issue "Climate Change Effects on Water Resources Management"

A special issue of Hydrology (ISSN 2306-5338).

Deadline for manuscript submissions: 30 December 2021.

Special Issue Editor

Dr. Abdullah Gokhan Yilmaz
E-Mail Website
Guest Editor
Senior Lecturer, La Trobe University, School of Engineering and Mathematical Sciences, Victoria 3552, Australia
Interests: climate change; hydrological modelling; flood and drought analysis; water infrastructure design and operation; water quality management

Special Issue Information

Dear Colleagues,

Climate change is one of the most severe challenges in the 21st century. Humanity faces significant socio-economic impacts from climate change across several sectors. Climate change affects cities and the built environment, coasts, agriculture, water resources and natural ecosystems all over the world. Among those, water resources management is one of the most affected fields due to the strong relationship between climate and water resources. Climate change alters timing and magnitude of precipitation, evapotranspiration, runoff and soil moisture. Such changes have significant consequences on water resources planning and management.  In several regions over the world, freshwater is already limited, and climate change causes additional stress on available freshwater resources in terms of both quantity and quality. Therefore, there is an urgent need to better understand the impacts, adaptation and mitigation measures of climate change on water resources management.

This Special Issue aims to gather contributions on climate change impact, adaptation and mitigation with a particular focus on water resources management. The contributions to this Special Issue will encompass a broad range of topics, including, but not limited to:

  • Climate change impacts on flood and drought management
  • Hydro-meteorological time series analysis
  • Climate change effects on water infrastructure design and operation
  • Watershed modelling using wide range of hydrological models
  • Climate change impacts on groundwater management
  • Climate change adaptation in water resources planning and management
  • Urban water management under climate change effects.

Dr. Abdullah Gokhan Yilmaz
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. Hydrology is an international peer-reviewed open access quarterly 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 1600 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

  • Climate change
  • hydrological modelling
  • flood and drought management
  • water infrastructure design and operation
  • water quality management

Published Papers (4 papers)

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Research

Article
Climate Change Impacts on Inflows into Lake Eppalock Reservoir from Upper Campaspe Catchment
Hydrology 2021, 8(3), 108; https://doi.org/10.3390/hydrology8030108 (registering DOI) - 24 Jul 2021
Abstract
Climate change has significant effects on societies and ecosystems. Due to the strong link between climate and the hydrological cycle, water resources is one of the most affected fields by climate change. It is of great importance to investigate climate change effects on [...] Read more.
Climate change has significant effects on societies and ecosystems. Due to the strong link between climate and the hydrological cycle, water resources is one of the most affected fields by climate change. It is of great importance to investigate climate change effects on streamflows by producing future streamflow projections under different scenarios to create adaptation measures and mitigate potential impacts of climate change. The Upper Campaspe Catchment (UCC), located at North Central Victoria in Australia, is a significant catchment as it provides a large portion of total inflow to the Lake Eppalock Reservoir, which supplies irrigation to the Campaspe Irrigation district and urban water to Bendigo, Heathcote, and Ballarat cities. In this study, climate change effects on monthly streamflows in the UCC was investigated using high resolution future climate data from CSIRO and MIROC climate models in calibrated IHACRES hydrological model. The IHACRES model was found to be very successful to simulate monthly streamflow in UCC. Remarkable streamflow reductions were projected based on the climate input from both models (CSIRO and MIROC). According to the most optimistic scenario (with the highest projected streamflows) by the MIROC-RCP4.5 model in near future (2035–2064), the Upper Campaspe River will completely dry out from January to May. The worst scenario (with the lowest streamflow projection) by the CSIRO-RCP8.5 model in the far future (2075–2104) showed that streamflows will be produced only for three months (July, August, and September) throughout the year. Findings from this study indicated that climate change will have significant adverse impacts on reservoir inflow, operation, water supply, and allocation in the study area. Full article
(This article belongs to the Special Issue Climate Change Effects on Water Resources Management)
Article
Impacts of Climate Change on Irrigation Water Management in the Babai River Basin, Nepal
Hydrology 2021, 8(2), 85; https://doi.org/10.3390/hydrology8020085 - 24 May 2021
Viewed by 746
Abstract
The diminishing spring discharge in the Middle Mountain Zone (MMZ) in Nepal is a matter of concern because it directly affects the livelihoods of low-income farmers in the region. Therefore, understanding the impacts of changes in climate and land-use patterns on water demand [...] Read more.
The diminishing spring discharge in the Middle Mountain Zone (MMZ) in Nepal is a matter of concern because it directly affects the livelihoods of low-income farmers in the region. Therefore, understanding the impacts of changes in climate and land-use patterns on water demand and availability is crucial. We investigated the impact of climate change on streamflow and environmental flow, and the demand for spring-fed river water for irrigation using the limited meteorological data available for the Babai River Basin, Nepal. SWAT and CROPWAT8.0 were used to respectively calculate present and future streamflow and irrigation water demand. Three general circulation models under two representative concentration pathways (RCPs 4.5 and 8.5) for the periods of 2020–2044, 2045–2069, and 2070–2099 were used to investigate the impact of climate change. Results indicate that the catchment is likely to experience an increase in rainfall and temperature in the future. The impact of the increment in rainfall and rise in temperature are replicated in the annual river flow that is anticipated to increase by 24–37%, to the historical data of 1991–2014. Despite this increase, projections show that the Babai River Basin will remain a water deficit basin from January to May in future decades. Full article
(This article belongs to the Special Issue Climate Change Effects on Water Resources Management)
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Article
Assessment of the Impact of Climate Change on Snow Distribution and River Flows in a Snow-Dominated Mountainous Watershed in the Western Hindukush–Himalaya, Afghanistan
Hydrology 2020, 7(4), 74; https://doi.org/10.3390/hydrology7040074 - 06 Oct 2020
Cited by 3 | Viewed by 1140
Abstract
Projected snow cover and river flows are important for planning and managing water resources in snow-dominated basins of the Himalayas. To quantify the impacts of climate change in the data scarce Panjshir River basin of Afghanistan, this study simulated present and future snow [...] Read more.
Projected snow cover and river flows are important for planning and managing water resources in snow-dominated basins of the Himalayas. To quantify the impacts of climate change in the data scarce Panjshir River basin of Afghanistan, this study simulated present and future snow cover area (SCA) distributions with the snow model (SM), and river flows with the snowmelt runoff model (SRM). The SRM used the degree-day factor and precipitation gradient optimized by the SM to simulate river flows. Temperature and precipitation data from eight kinds of general circulation models (GCMs) were used for bias correction. The SM and SRM were first calibrated and validated using 2009–2015 data, and then bias-corrected future climate data were input to the models to simulate future SCA and river flows. Under both the representative concentration pathways (RCP) 4.5 and 8.5, the annual average SCA and river flow were projected to decrease in the mid and late 21st century, although seasonal increases were simulated in some instances. Uncertainty ranges in projected SCA and river flow under RCP 8.5 were small in the mid 21st century and large in the late 21st century. Therefore, climate change is projected to alter high-altitude stream sources in the Hindukush mountains and reduce the amount of water reaching downstream areas. Full article
(This article belongs to the Special Issue Climate Change Effects on Water Resources Management)
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Article
An Evaluation of Statistical Downscaling Techniques for Simulating Daily Rainfall Occurrences in the Upper Ping River Basin
Hydrology 2020, 7(3), 63; https://doi.org/10.3390/hydrology7030063 - 02 Sep 2020
Viewed by 635
Abstract
This study presents an exhaustive evaluation of the performance of three statistical downscaling techniques for generating daily rainfall occurrences at 22 rainfall stations in the upper Ping river basin (UPRB), Thailand. The three downscaling techniques considered are the modified Markov model (MMM), a [...] Read more.
This study presents an exhaustive evaluation of the performance of three statistical downscaling techniques for generating daily rainfall occurrences at 22 rainfall stations in the upper Ping river basin (UPRB), Thailand. The three downscaling techniques considered are the modified Markov model (MMM), a stochastic model, and two variants of regression models, statistical models, one with single relationship for all days of the year (RegressionYrly) and the other with individual relationships for each of the 366 days (Regression366). A stepwise regression is applied to identify the significant atmospheric (ATM) variables to be used as predictors in the downscaling models. Aggregated wetness state indicators (WIs), representing the recent past wetness state for the previous 30, 90 or 365 days, are also considered as additional potential predictors since they have been effectively used to represent the low-frequency variability in the downscaled sequences. Grouping of ATM and all possible combinations of WI is used to form eight predictor sets comprising ATM, ATM-WI30, ATM-WI90, ATM-WI365, ATM-WI30&90, ATM-WI30&365, ATM-WI90&365 and ATM-WI30&90&365. These eight predictor sets were used to run the three downscaling techniques to create 24 combination cases. These cases were first applied at each station individually (single site simulation) and thereafter collectively at all sites (multisite simulations) following multisite downscaling models leading to 48 combination cases in total that were run and evaluated. The downscaling models were calibrated using atmospheric variables from the National Centers for Environmental Prediction (NCEP) reanalysis database and validated using representative General Circulation Models (GCM) data. Identification of meaningful predictors to be used in downscaling, calibration and setting up of downscaling models, running all 48 possible predictor combinations and a thorough evaluation of results required considerable efforts and knowledge of the research area. The validation results show that the use of WIs remarkably improves the accuracy of downscaling models in terms of simulation of standard deviations of annual, monthly and seasonal wet days. By comparing the overall performance of the three downscaling techniques keeping common sets of predictors, MMM provides the best results of the simulated wet and dry spells as well as the standard deviation of monthly, seasonal and annual wet days. These findings are consistent across both single site and multisite simulations. Overall, the MMM multisite model with ATM and wetness indicators provides the best results. Upon evaluating the combinations of ATM and sets of wetness indicators, ATM-WI30&90 and ATM-WI30&365 were found to perform well during calibration in reproducing the overall rainfall occurrence statistics while ATM-WI30&365 was found to significantly improve the accuracy of monthly wet spells over the region. However, these models perform poorly during validation at annual time scale. The use of multi-dimension bias correction approaches is recommended for future research. Full article
(This article belongs to the Special Issue Climate Change Effects on Water Resources Management)
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