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Special Issue "Climate Variability and Climate Change Impacts on Land Surface, Hydrological Processes and Water Management"

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

Deadline for manuscript submissions: closed (31 March 2019).

Special Issue Editors

Guest Editor
Prof. Yongqiang Zhang

Institute of Geographic Sciences and Natural Resources Research, The Chinese Academy of Sciences, Beijing, China
Website | E-Mail
Phone: +61 2 6246 5761
Interests: remote sensing; hydrology; climate change; evapotranspiration; runoff; predictions; catchment
Guest Editor
Dr. Hongxia Li

State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, 610065, China
E-Mail
Interests: hydrology; climate change; evapotranspiration; runoff forecast
Guest Editor
Prof. Paolo Reggiani

Department of Civil Engineering, University of Siegen, 57068 Siegen, Germany
Website | E-Mail
Interests: Water Resources, Hydrology

Special Issue Information

Dear Colleagues,

It is well recognised that the Earth is experiencing dramatic climate variability and climate change, because of global warming caused by human being over the last 60 years. This is strongly influencing hydrological processes, from catchment to regional and to global scales. As a result, each country needs to establish efficient water management strategies to cope with and adapt to these changes. To better understand on the mechanism and responses to the climate variability and climate change, it is crucial to have multidisciplinary studies that involve hydrology, meteorology, remote sensing, ecology, engineering, agriculture, etc.

We invite original research articles that contribute to the continuing efforts of understanding hydrological processes and to engage in more efficient water management strategies in changing environment at a scale from catchment, to region and to globe. We are particularly interested in following topics, but this Special Issue is not limited to only these topics:

  • Detecting trends and variation of hydrological variables, such as runoff, actual evapotranspiration and soil moisture;
  • Separating climate change and land use change impacts on water balance components;
  • Measuring or estimating hydrological variables, such as precipitation, evapotranspiration and soil moisture in data-sparse regions;
  • Predicting catchment and regional water availability in a changing climate;
  • Detecting eco-hydrological response to climate variability and climate change;
  • Water management strategies under climate variability and climate change;
  • Human activities (forestation, deforestation, agricultural practice, mining, etc.) influencing water availability;
  • Engineering interventions, such as damming, to adapt climate variability and climate change

Dr. Yongqiang Zhang
Dr. Hongxia Li
Prof. Paolo Reggiani
Guest Editors

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. Water is an international peer-reviewed open access monthly 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
  • Climate variability
  • Streamflow
  • Evapotranspiration
  • Water management
  • Catchment
  • Remote sensing
  • Hydrological change
  • Nonstationarity

Published Papers (25 papers)

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Editorial

Jump to: Research, Review

Open AccessEditorial
Climate Variability and Climate Change Impacts on Land Surface, Hydrological Processes and Water Management
Water 2019, 11(7), 1492; https://doi.org/10.3390/w11071492
Received: 16 July 2019 / Accepted: 17 July 2019 / Published: 18 July 2019
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Abstract
During the last several decades, Earth´s climate has undergone significant changes due to anthropogenic global warming, and feedbacks to the water cycle. Therefore, persistent efforts are required to understand the hydrological processes and to engage in efficient water management strategies under changing environmental [...] Read more.
During the last several decades, Earth´s climate has undergone significant changes due to anthropogenic global warming, and feedbacks to the water cycle. Therefore, persistent efforts are required to understand the hydrological processes and to engage in efficient water management strategies under changing environmental conditions. The twenty-four contributions in this Special Issue have broadly addressed the issues across four major research areas: (1) Climate and land-use change impacts on hydrological processes, (2) hydrological trends and causality analysis faced in hydrology, (3) hydrological model simulations and predictions, and (4) reviews on water prices and climate extremes. The substantial number of international contributions to the Special Issue indicates that climate change impacts on water resources analysis attracts global attention. Here, we give an introductory summary of the research questions addressed by the papers and point the attention of readers toward how the presented studies help gaining scientific knowledge and support policy makers. Full article

Research

Jump to: Editorial, Review

Open AccessArticle
Human-Induced Alterations to Land Use and Climate and Their Responses for Hydrology and Water Management in the Mekong River Basin
Water 2019, 11(6), 1307; https://doi.org/10.3390/w11061307
Received: 26 April 2019 / Revised: 7 June 2019 / Accepted: 19 June 2019 / Published: 25 June 2019
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Abstract
The Mekong River Basin (MRB) is one of the significant river basins in the world. For political and economic reasons, it has remained mostly in its natural condition. However, with population increases and rapid industrial growth in the Mekong region, the river has [...] Read more.
The Mekong River Basin (MRB) is one of the significant river basins in the world. For political and economic reasons, it has remained mostly in its natural condition. However, with population increases and rapid industrial growth in the Mekong region, the river has recently become a hotbed of hydropower development projects. This study evaluated these changing hydrological conditions, primarily driven by climate as well as land use and land cover change between 1992 and 2015 and into the future. A 3% increase in croplands and a 1–2% decrease in grasslands, shrublands, and forests was evident in the basin. Similarly, an increase in temperature of 1–6 °C and in precipitation of 15% was projected for 2015–2099. These natural and climate-induced changes were incorporated into two hydrological models to evaluate impacts on water budget components, particularly streamflow. Wet season flows increased by up to 10%; no significant change in dry season flows under natural conditions was evident. Anomaly in streamflows due to climate change was present in the Chiang Saen and Luang Prabang, and the remaining flow stations showed up to a 5% increase. A coefficient of variation <1 suggested no major difference in flows between the pre- and post-development of hydropower projects. The results suggested an increasing trend in streamflow without the effect of dams, while the inclusion of a few major dams resulted in decreased river streamflow of 6% to 15% possibly due to irrigation diversions and climate change. However, these estimates fall within the range of uncertainties in natural climate variability and hydrological parameter estimations. This study offers insights into the relationship between biophysical and anthropogenic factors and highlights that management of the Mekong River is critical to optimally manage increased wet season flows and decreased dry season flows and handle irrigation diversions to meet the demand for food and energy production. Full article
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Open AccessArticle
Quantifying the Impacts of Climate Change, Coal Mining and Soil and Water Conservation on Streamflow in a Coal Mining Concentrated Watershed on the Loess Plateau, China
Water 2019, 11(5), 1054; https://doi.org/10.3390/w11051054
Received: 21 March 2019 / Revised: 25 April 2019 / Accepted: 28 April 2019 / Published: 21 May 2019
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Abstract
The streamflow has declined significantly in the coal mining concentrated watershed of the Loess Plateau, China, since the 1970s. Quantifying the impact of climate change, coal mining and soil and water conservation (SWC), which are mainly human activities, on streamflow is essential not [...] Read more.
The streamflow has declined significantly in the coal mining concentrated watershed of the Loess Plateau, China, since the 1970s. Quantifying the impact of climate change, coal mining and soil and water conservation (SWC), which are mainly human activities, on streamflow is essential not only for understanding the mechanism of hydrological response, but also for water resource management in the catchment. In this study, the trend of annual streamflow series by Mann-Kendall test has been analyzed, and years showing abrupt changes have been detected using the cumulative anomaly curves and Pettitt test. The contribution of climate change, coal mining and SWC on streamflow has been separated with the monthly water-balance model (MWBM) and field investigation. The results showed: (1) The streamflow had an statistically significant downward trend during 1955–2013; (2) The two break points were in 1979 and 1996; (3) Relative to the baseline period, i.e., 1955–1978, the mean annual streamflow reduction in 1979–1996 was mainly affected by climate change, which was responsible for a decreased annual streamflow of 12.70 mm, for 70.95%, while coal mining and SWC resulted in a runoff reduction of 2.15 mm, 12.01% and 3.05mm, 17.04%, respectively; (4) In a recent period, i.e., 1997–2013, the impact of coal mining on streamflow reduction was dominant, reaching 29.88 mm, 54.24%. At the same time, the declining mean annual streamflow induced through climate change and SWC were 13.01 mm, 23.62% and 12.20 mm, 22.14%, respectively. Full article
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Open AccessArticle
A Statistical–Distributed Model of Average Annual Runoff for Water Resources Assessment in DPR Korea
Water 2019, 11(5), 965; https://doi.org/10.3390/w11050965
Received: 26 March 2019 / Revised: 3 May 2019 / Accepted: 6 May 2019 / Published: 8 May 2019
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Abstract
Water resource management is critical for the economic development of the Democratic People’s Republic of Korea (DPRK), where runoff plays a central role. However, long and continuous runoff data at required spatial and temporal scales are generally not available in many regions in [...] Read more.
Water resource management is critical for the economic development of the Democratic People’s Republic of Korea (DPRK), where runoff plays a central role. However, long and continuous runoff data at required spatial and temporal scales are generally not available in many regions in DPRK, the same as in many countries around the world. A common practice to fill the gaps is to use some kind of interpolation or data-infilling methods. In this study, the gaps in annual runoff data were filled using a distributed runoff map. A novel statistical–distributed model of average annual runoff was derived from 50 years’ observation on 200 meteorological observation stations in DPRK, considering the influence of climatic factors. Using principal component analysis, correlation analysis and residual error analysis, average annual precipitation, average annual precipitation intensity, average annual air temperature, and hot seasonal air temperature were selected as major factors affecting average annual runoff formation. Based on the water balance equation and assumptions, the empirical relationship for runoff depth and impact factors was established and calibrated. The proposed empirical model was successfully verified by 93 gauged stations. The cartography of the average annual runoff map was automatically implemented in ArcGIS. A case study on the Tumen River Basin illustrated the applicability of the proposed model. This model has been widely used for the development and management of water resources by water-related institutes and design agencies in DPRK. The limitation of the proposed model and future works are also discussed, especially the impacts of climate changes and topology changes and the combination with the physical process of runoff formation. Full article
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Open AccessArticle
Climate Change and Intense Irrigation Growth in Western Bahia, Brazil: The Urgent Need for Hydroclimatic Monitoring
Water 2019, 11(5), 933; https://doi.org/10.3390/w11050933
Received: 29 March 2019 / Revised: 21 April 2019 / Accepted: 30 April 2019 / Published: 2 May 2019
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Abstract
In Western Bahia, one of the most active agricultural frontiers of the world, cropland area and irrigated area are increasing at fast rates, and water conflicts have been happening at least since 2010. This study makes a hydroclimatic analysis of the water resources [...] Read more.
In Western Bahia, one of the most active agricultural frontiers of the world, cropland area and irrigated area are increasing at fast rates, and water conflicts have been happening at least since 2010. This study makes a hydroclimatic analysis of the water resources in Western Bahia, from both supply and demand viewpoints. Time series of precipitation for the period 1980–2015 and river discharge for the period 1978–2015 are analyzed, indicating a significant reduction of up to 12% in rainfall since the 1980s, and a reduction in river discharge in all stations studied, in both the rainy season and the dry season. Combined with that, irrigated area has increased over 150-fold in 30 years, and in the most irrigated regions, has increased by 90% in the last eight years only. Seven regions in Western Bahia have been identified where the potential for water use conflicts is critical. Moreover, the combination of reduced availability and increased demand of water resources indicates that, if current trends are maintained, conflicts over water may become more frequent in the next years or decades. A short-term alternative to avoid such conflicts is to largely avoid irrigation during the months with low discharge. However, a monitoring system in which the availability and demand of water resources for irrigation are actually measured and monitored, is the safest path to provide water security to this region. Full article
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Open AccessArticle
Influence of Power Operations of Cascade Hydropower Stations under Climate Change and Human Activities and Revised Optimal Operation Strategies: A Case Study in the Upper Han River, China
Water 2019, 11(5), 895; https://doi.org/10.3390/w11050895
Received: 29 March 2019 / Revised: 16 April 2019 / Accepted: 24 April 2019 / Published: 28 April 2019
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Abstract
Climate change and human activities are two driving factors that affect the hydrological cycle of watersheds and water resource evolution. As a pivotal input to hydropower stations, changes in runoff processes may reduce the effectiveness of existing operation procedures. Therefore, it is important [...] Read more.
Climate change and human activities are two driving factors that affect the hydrological cycle of watersheds and water resource evolution. As a pivotal input to hydropower stations, changes in runoff processes may reduce the effectiveness of existing operation procedures. Therefore, it is important to analyze the influences of cascade hydropower stations under climate change and human activities and to propose revised optimal operation strategies. For the present study, three runoff series conditions including: Initial runoff, affected by only climate change, and affected by both climate change and human activities are examined by a simulation model to analyze the influence on power generation with four schemes. Additionally, an optimal operation model of cascade power stations is proposed based on the simulation model to generate single and joint optimal operation charts for future hydrological scenarios. The paper also proposes to change human activities based on optimizing operation rules to reduce its influence on downstream power stations. This procedure is theoretically applied and varied for three power stations in the upper Han River, China. The results show that the influence of climate change is greater than that of human activities in that power generation decreased by 17.95% and 12.83%, respectively, whereas combined, there is a reduction of 25.71%. Under existing hydrological conditions, the modified single and joint operation charts would increase power generation by about 32 million and 47 million kWh. Furthermore, after optimizing the upstream project, the abandoned water and power generation of these cascade power stations would reduce by 150 million m3 and 5 million kWh, respectively. This study has practical significance for the efficient operation of cascade hydropower stations and is helpful for developing reservoir operation theory under changing environments. Full article
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Open AccessArticle
Comparative Study of Two State-of-the-Art Semi-Distributed Hydrological Models
Water 2019, 11(5), 871; https://doi.org/10.3390/w11050871
Received: 17 April 2019 / Accepted: 21 April 2019 / Published: 26 April 2019
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Abstract
Performance of a newly developed semi-distributed (grid-based) hydrological model (satellite-based hydrological model (SHM)) has been compared with another semi-distributed soil and water assessment tool (SWAT)—a widely used hydrological response unit (HRU)-based hydrological model at a large scale (12,900 km2) river basin [...] Read more.
Performance of a newly developed semi-distributed (grid-based) hydrological model (satellite-based hydrological model (SHM)) has been compared with another semi-distributed soil and water assessment tool (SWAT)—a widely used hydrological response unit (HRU)-based hydrological model at a large scale (12,900 km2) river basin for monthly streamflow simulation. The grid-based model has a grid cell size of 25 km2, and the HRU-based model was set with an average HRU area of 25.2 km2 to keep a balance between the discretization of the two models. Both the model setups are calibrated against the observed streamflow over the period 1977 to 1990 (with 1976 as the warm-up period) and validated over the period 1991 to 2004 by comparing simulated and observed hydrographs as well as using coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) as statistical indices. Result of SHM simulation (NSE: 0.92 for calibration period; NSE: 0.92 for validation period) appears to be superior in comparison to SWAT simulation (NSE: 0.72 for calibration period; NSE: 0.50 for validation period) for both calibration and validation periods. The models’ performances are also analyzed for annual peak flow, monthly flow variability, and for different flow percentiles. SHM has performed better in simulating annual peak flows and has reproduced the annual variability of observed streamflow for every month of the year. In addition, SHM estimates normal, moderately high, and high flows better than SWAT. Furthermore, total uncertainties of models’ simulation have been analyzed using quantile regression technique and eventually quantified with scatter plots between P (measured data bracketed by the 95 percent predictive uncertainty (PPU) band) and R (the relative length of the 95PPU band with respect to the model simulated values)-values, for calibration and validation periods, for both the model simulations. The analysis confirms the superiority of SHM over its counterpart. Differences in data interpolation techniques and physical processes of the models are identified as the probable reasons behind the differences among the models’ outputs. Full article
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Open AccessArticle
The Use of Large-Scale Climate Indices in Monthly Reservoir Inflow Forecasting and Its Application on Time Series and Artificial Intelligence Models
Water 2019, 11(2), 374; https://doi.org/10.3390/w11020374
Received: 30 October 2018 / Revised: 2 January 2019 / Accepted: 13 February 2019 / Published: 21 February 2019
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Abstract
Climate variability is strongly influencing hydrological processes under complex weather conditions, and it should be considered to forecast reservoir inflow for efficient dam operation strategies. Large-scale climate indices can provide potential information about climate variability, as they usually have a direct or indirect [...] Read more.
Climate variability is strongly influencing hydrological processes under complex weather conditions, and it should be considered to forecast reservoir inflow for efficient dam operation strategies. Large-scale climate indices can provide potential information about climate variability, as they usually have a direct or indirect correlation with hydrologic variables. This study aims to use large-scale climate indices in monthly reservoir inflow forecasting for considering climate variability. For this purpose, time series and artificial intelligence models, such as Seasonal AutoRegressive Integrated Moving Average (SARIMA), SARIMA with eXogenous variables (SARIMAX), Artificial Neural Network (ANN), Adaptive Neural-based Fuzzy Inference System (ANFIS), and Random Forest (RF) models were employed with two types of input variables, autoregressive variables (AR-) and a combination of autoregressive and exogenous variables (ARX-). Several statistical methods, including ensemble empirical mode decomposition (EEMD), were used to select the lagged climate indices. Finally, monthly reservoir inflow was forecasted by SARIMA, SARIMAX, AR-ANN, ARX-ANN, AR-ANFIS, ARX-ANFIS, AR-RF, and ARX-RF models. As a result, the use of climate indices in artificial intelligence models showed a potential to improve the model performance, and the ARX-ANN and AR-RF models generally showed the best performance among the employed models. Full article
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Open AccessArticle
Land Use and Climate Change Effects on Surface Runoff Variations in the Upper Heihe River Basin
Water 2019, 11(2), 344; https://doi.org/10.3390/w11020344
Received: 8 January 2019 / Revised: 2 February 2019 / Accepted: 13 February 2019 / Published: 18 February 2019
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Abstract
The runoff in the upper reaches of the Heihe River has been continuously abundant for more than a decade, and this has not happened previously in history. Quantitative analysis of runoff variation and its influencing factors are of great significance for the ecological [...] Read more.
The runoff in the upper reaches of the Heihe River has been continuously abundant for more than a decade, and this has not happened previously in history. Quantitative analysis of runoff variation and its influencing factors are of great significance for the ecological protection of the basin. In this paper, the soil and water assessment tool model was used to simulate runoff in the study area, and the method of scenario simulation was used to quantitatively analyze the runoff response with respect to land use and climate change. According to the abruptness of the runoff sequence, the years before 2004 are categorized as belonging to the reference period, and after 2004 is categorized as the interference period. According to the analysis, compared with the reference period, the contribution rate of climate change is 87.15%, while the contribution rate of land use change is only 12.85%. The climate change scenario simulation analysis shows that the change in runoff is positively correlated with the change in precipitation. The relationship with the change in temperature is more complicated, but the influence of precipitation change is stronger than the change in temperature. According to the land use scenario simulation analysis, under the economic development scenario, the runoff decreased, whereas under the historical trend and ecological protection scenario, the runoff increased. Additionally, the runoff increased more under the ecological protection scenario. Full article
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Open AccessArticle
Meteorological Factors Affecting Pan Evaporation in the Haihe River Basin, China
Water 2019, 11(2), 317; https://doi.org/10.3390/w11020317
Received: 16 December 2018 / Revised: 1 February 2019 / Accepted: 10 February 2019 / Published: 13 February 2019
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Abstract
Pan evaporation (Epan) is an important indicator of regional evaporation intensity and degree of drought. However, although more evaporation is expected under rising temperatures, the reverse trend has been observed in many parts of the world, known as the “pan [...] Read more.
Pan evaporation (Epan) is an important indicator of regional evaporation intensity and degree of drought. However, although more evaporation is expected under rising temperatures, the reverse trend has been observed in many parts of the world, known as the “pan evaporation paradox”. In this paper, the Haihe River Basin (HRB) is divided into six sub-regions using the Canopy and k-means (The process for partitioning an N-dimensional population into k sets on the basis of a sample is called “k-means”) to cluster 44 meteorological stations in the area. The interannual and seasonal trends and the significance of eight meteorological indicators, including average temperature, maximum temperature, minimum temperature, precipitation, relative humidity, sunshine duration, wind speed, and Epan, were analyzed for 1961 to 2010 using the trend-free pre-whitening Mann-Kendall (TFPW-MK) test. Then, the correlation between meteorological elements and Epan was analyzed using the Spearman correlation coefficient. Results show that the average temperature, maximum temperature, and minimum temperature of the HRB increased, while precipitation, relative humidity, sunshine duration, wind speed and Epan exhibited a downward trend. The minimum temperature rose 2 and 1.5 times faster than the maximum temperature and average temperature, respectively. A significant reduction in sunshine duration was found to be the primary factor in the Epan decrease, while declining wind speed was the secondary factor. Full article
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Open AccessFeature PaperArticle
Effects of the Three Gorges Project on Runoff and Related Benefits of the Key Regions along Main Branches of the Yangtze River
Water 2019, 11(2), 269; https://doi.org/10.3390/w11020269
Received: 8 January 2019 / Revised: 30 January 2019 / Accepted: 31 January 2019 / Published: 4 February 2019
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Abstract
The Three Gorges Project (TGP) is the largest hydroelectric project in the world. It is crucial to understand the relationship between runoff regime changes and TGP’s full operation after 2009 in the Yangtze River Basin (YRB). This paper defines core, extended and buffer [...] Read more.
The Three Gorges Project (TGP) is the largest hydroelectric project in the world. It is crucial to understand the relationship between runoff regime changes and TGP’s full operation after 2009 in the Yangtze River Basin (YRB). This paper defines core, extended and buffer areas of YRB, analyzes the effects of TGP on runoff anomaly (RA), runoff variation (RV) and change of coefficient of variation (CCV) between two periods (2003–2008 and 2009–2016), takes percentage of runoff anomaly (PRA) as the evaluation standard, assures alleviation effect on severe dry and wet years of the research area, and finally summarizes related benefits of flood control from TGP. Our results indicate the inter-annual fluctuation of runoff in the core and extended areas expanded, but reduced in the buffer areas, and the frequencies of severe dry and wet years alleviated in the buffer, core and extended areas. Generally, the extended and core areas become less wet, and the buffer areas become less dry. The RV and CCV are both strengthened in the extended and core areas, but are weakened in the buffer areas, and RV is well positively correlated (R2 = 0.80) to CCV. Furthermore, the main benefits of TGP on flood control are remarkable in the reduction of disaster affected population, the decrease of agricultural disaster-damaged area, and the decline of direct economic loss. However, due to torrentially seasonal and non-seasonal precipitation, the sharp rebounds of three standards for Hubei and Anhui occurred in 2010 and 2016, and the percentage of agricultural damage area of five regions in the core and extended areas did not decline synchronously and performed irregularly. Our results suggest that the five key regions along the main branches of the Yangtze River should establish a flood control system and promote the connectivity of infrastructures at different levels to meet the significant functions of TGP. It is a great challenge for TGP operation to balance the benefits and conflicts among flood control, power generation and water resources supply in the future. Full article
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Open AccessArticle
Analysis of the Recent Trends of Two Climate Parameters over Two Eco-Regions of Ethiopia
Water 2019, 11(1), 161; https://doi.org/10.3390/w11010161
Received: 23 December 2018 / Revised: 9 January 2019 / Accepted: 15 January 2019 / Published: 17 January 2019
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Abstract
The changes in climatic variables in Ethiopia are not entirely understood. This paper investigated the recent trends of precipitation and temperature on two eco-regions of Ethiopia. This study used the observed historical meteorological data from 1980 to 2016 to analyze the trends. Trend [...] Read more.
The changes in climatic variables in Ethiopia are not entirely understood. This paper investigated the recent trends of precipitation and temperature on two eco-regions of Ethiopia. This study used the observed historical meteorological data from 1980 to 2016 to analyze the trends. Trend detection was done by using the non-parametric Mann-Kendall (MK), Sen’s slope estimator test, and Innovative Trend Analysis Method (ITAM). The results showed that a significant increasing trend was observed in the Gondar, Bahir Dar, Gewane, Dembi-Dolo, and Negele stations. However, a slightly decreasing trend was observed in the Sekoru, Degahabur, and Maichew stations regarding precipitation trends. As far as the trend of temperature was concerned, an increasing trend was detected in the Gondar, Bahir Dar, Gewane, Degahabur, Negele, Dembi-Dolo, and Maichew stations. However, the temperature trend in Sekoru station showed a sharp decreasing trend. The effects of precipitation and temperature changes on water resources are significant after 1998. The consistency in the precipitation and temperature trends over the two eco-regions confirms the robustness of the changes. The findings of this study will serve as a reference for climate researchers, policy and decision makers. Full article
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Open AccessArticle
Evaluating Future Flood Scenarios Using CMIP5 Climate Projections
Water 2018, 10(12), 1866; https://doi.org/10.3390/w10121866
Received: 30 October 2018 / Revised: 7 December 2018 / Accepted: 13 December 2018 / Published: 17 December 2018
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Abstract
Frequent flooding events in recent years have been linked with the changing climate. Comprehending flooding events and their risks is the first step in flood defense and can help to mitigate flood risk. Floodplain mapping is the first step towards flood risk analysis [...] Read more.
Frequent flooding events in recent years have been linked with the changing climate. Comprehending flooding events and their risks is the first step in flood defense and can help to mitigate flood risk. Floodplain mapping is the first step towards flood risk analysis and management. Additionally, understanding the changing pattern of flooding events would help us to develop flood mitigation strategies for the future. This study analyzes the change in streamflow under different future carbon emission scenarios and evaluates the spatial extent of floodplain for future streamflow. The study will help facility managers, design engineers, and stakeholders to mitigate future flood risks. Variable Infiltration Capacity (VIC) forcing-generated Coupled Model Intercomparison Project phase 5 (CMIP5) streamflow data were utilized for the future streamflow analysis. The study was done on the Carson River near Carson City, an agricultural area in the desert of Nevada. Kolmogorov–Smirnov and Pearson Chi-square tests were utilized to obtain the best statistical distribution that represents the routed streamflow of the Carson River near Carson City. Altogether, 97 projections from 31 models with four emission scenarios were used to predict the future flood flow over 100 years using a best fit distribution. A delta change factor was used to predict future flows, and the flow routing was done with the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) model to obtain a flood inundation map. A majority of the climate projections indicated an increase in the flood level 100 years into the future. The developed floodplain map for the future streamflow indicated a larger inundation area compared with the current Federal Emergency Management Agency’s flood inundation map, highlighting the importance of climate data in floodplain management studies. Full article
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Open AccessArticle
Analyzing the Impacts of Climate Variability and Land Surface Changes on the Annual Water–Energy Balance in the Weihe River Basin of China
Water 2018, 10(12), 1792; https://doi.org/10.3390/w10121792
Received: 27 October 2018 / Revised: 1 December 2018 / Accepted: 3 December 2018 / Published: 6 December 2018
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Abstract
The serious soil erosion problems and decreased runoff of the Loess Plateau may aggravate the shortage of its local water resources. Understanding the spatiotemporal influences on runoff changes is important for water resource management. Here, we study this in the largest tributary of [...] Read more.
The serious soil erosion problems and decreased runoff of the Loess Plateau may aggravate the shortage of its local water resources. Understanding the spatiotemporal influences on runoff changes is important for water resource management. Here, we study this in the largest tributary of the Yellow River, the Weihe River Basin. Data from four hydrological stations (Lin Jia Cun (LJC), Xian Yang (XY), Lin Tong (LT), and Hua Xian (HX)) and 10 meteorological stations from 1961–2014 were used to analyze changes in annual runoff. The Mann–Kendall test and Pettitt abrupt change point test diagnosed variations in runoff in the Weihe River basin; the time periods before and after abrupt change points are the base period (period I) and change period (period II), respectively. Within the Budyko framework, the catchment properties (ω in Fu’s equation) represent land surface changes; climate variability comprises precipitation (P) and potential evapotranspiration (ET0). All the stations showed a reduction in annual runoff during the recording period, of which 22.66% to 50.42% was accounted for by land surface change and 1.97% to 53.32% by climate variability. In the Weihe River basin, land surface changes drive runoff variation in LT and climate variability drives it in LJC, XY, and HX. The contribution of land surface changes to runoff reduction in period I was less than that in period II, indicating that changes in human activity further decreased runoff. Therefore, this study offers a scientific basis for understanding runoff trends and driving forces, providing an important reference for social development, ecological construction, and water resource management. Full article
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Open AccessArticle
Quantifying the Impact of Climate Change and Human Activities on Streamflow in a Semi-Arid Watershed with the Budyko Equation Incorporating Dynamic Vegetation Information
Water 2018, 10(12), 1781; https://doi.org/10.3390/w10121781
Received: 13 November 2018 / Revised: 1 December 2018 / Accepted: 1 December 2018 / Published: 4 December 2018
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Abstract
Understanding hydrological responses to climate change and land use and land cover change (LULCC) is important for water resource planning and management, especially for water-limited areas. The annual streamflow of the Wuding River Watershed (WRW), the largest sediment source of the Yellow River [...] Read more.
Understanding hydrological responses to climate change and land use and land cover change (LULCC) is important for water resource planning and management, especially for water-limited areas. The annual streamflow of the Wuding River Watershed (WRW), the largest sediment source of the Yellow River in China, has decreased significantly over the past 50 years at a rate of 5.2 mm/decade. Using the Budyko equation, this study investigated this decrease with the contributions from climate change and LULCC caused by human activities, which have intensified since 1999 due to China’s Grain for Green Project (GFGP). The Budyko parameter that represents watershed characteristics was more reasonably configured and derived to improve the performance of the Budyko equation. Vegetation changes were included in the Budyko equation to further improve its simulations, and these changes showed a significant upward trend due to the GFGP based on satellite data. An improved decomposition method based on the Budyko equation was used to quantitatively separate the impact of climate change from that of LULCC on the streamflow in the WRW. Our results show that climate change generated a dominant effect on the streamflow and decreased it by 72.4% in the WRW. This climatic effect can be further explained with the drying trend of the Palmer Severity Drought Index, which was calculated based only on climate change information for the WRW. In the meantime, although human activities in this watershed have been very intense, especially since 1999, vegetation cover increase contributed a 27.6% decline to the streamflow, which played a secondary role in affecting hydrological processes in the WRW. Full article
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Open AccessArticle
Spatiotemporal Variation of Snowfall to Precipitation Ratio and Its Implication on Water Resources by a Regional Climate Model over Xinjiang, China
Water 2018, 10(10), 1463; https://doi.org/10.3390/w10101463
Received: 13 September 2018 / Revised: 4 October 2018 / Accepted: 15 October 2018 / Published: 17 October 2018
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Abstract
Snow contributes one of the main water sources to runoff in the arid region of China. A clear understanding of the spatiotemporal variation of snowfall is not only required for climate change assessment, but also plays a critical role in water resources management. [...] Read more.
Snow contributes one of the main water sources to runoff in the arid region of China. A clear understanding of the spatiotemporal variation of snowfall is not only required for climate change assessment, but also plays a critical role in water resources management. However, in-situ observations or gridded datasets hardly meet the requirement and cannot provide precise spatiotemporal details on snowfall across the region. This study attempted to apply the Weather Research and Forecasting (WRF) model to clarify the spatiotemporal variation of snowfall and the ratio of snowfall to total precipitation over Xinjiang in China during the 1979–2015 period. The results showed that the snowfall increased in the southern edge of the Tarim Basin, the Ili Valley, and the Altay Mountains, but decreased in the Tianshan Mountains and the Kunlun Mountains. The snowfall/precipitation (S/P) ratio revealed the opposite trends in low-elevation regions and mountains in the study area. The S/P ratio rose in the Tarim Basin and the Junggar Basin, but declined in the Altay Mountains, the Tianshan Mountains, and the west edge of the Junggar Basin. The study area comprises two major rivers in the middle of the Tianshan Mountains. Both the runoff magnitude increase and earlier occurrence of snowmelt recharge in runoff identified for the 1980s were compared with the 2000s level in decreasing S/P ratio regions. Full article
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Open AccessArticle
Observed Trends of Climate and River Discharge in Mongolia’s Selenga Sub-Basin of the Lake Baikal Basin
Water 2018, 10(10), 1436; https://doi.org/10.3390/w10101436
Received: 11 September 2018 / Revised: 1 October 2018 / Accepted: 9 October 2018 / Published: 12 October 2018
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Abstract
Mongolia’s Selenga sub-basin of the Lake Baikal basin is spatially extensive, with pronounced environmental gradients driven primarily by precipitation and air temperature on broad scales. Therefore, it is an ideal region to examine the dynamics of the climate and the hydrological system. This [...] Read more.
Mongolia’s Selenga sub-basin of the Lake Baikal basin is spatially extensive, with pronounced environmental gradients driven primarily by precipitation and air temperature on broad scales. Therefore, it is an ideal region to examine the dynamics of the climate and the hydrological system. This study investigated the annual precipitation, air temperature, and river discharge variability at five selected stations of the sub-basin by using Mann-Kendall (MK), Innovative trend analysis method (ITAM), and Sen’s slope estimator test. The result showed that the trend of annual precipitation was slightly increasing in Ulaanbaatar (Z = 0.71), Erdenet (Z = 0.13), and Tsetserleg (Z = 0.26) stations. Whereas Murun (Z = 2.45) and Sukhbaatar (Z = 1.06) stations showed a significant increasing trend. And also, the trend of annual air temperature in Ulaanbaatar (Z = 5.88), Erdenet (Z = 3.87), Tsetserleg (Z = 4.38), Murun (Z = 4.77), and Sukhbaatar (Z = 2.85) was sharply increased. The average air temperature has significantly increased by 1.4 °C in the past 38 years. This is very high in the semi-arid zone of central Asia. The river discharge showed a significantly decreasing trend during the study period years. It has been apparent since 1995. The findings of this paper could help researchers to understand the annual variability of precipitation, air temperature, and river discharge over the study region and, therefore, become a foundation for further studies. Full article
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Open AccessArticle
Multiple Linear Regression Models for Predicting Nonpoint-Source Pollutant Discharge from a Highland Agricultural Region
Water 2018, 10(9), 1156; https://doi.org/10.3390/w10091156
Received: 25 July 2018 / Revised: 26 August 2018 / Accepted: 27 August 2018 / Published: 29 August 2018
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Abstract
Sediment runoff from dense highland field areas greatly affects the quality of downstream lakes and drinking water sources. In this study, multiple linear regression (MLR) models were built to predict diffuse pollutant discharge using the environmental parameters of a basin. Explanatory variables that [...] Read more.
Sediment runoff from dense highland field areas greatly affects the quality of downstream lakes and drinking water sources. In this study, multiple linear regression (MLR) models were built to predict diffuse pollutant discharge using the environmental parameters of a basin. Explanatory variables that influence the sediment and pollutant discharge can be identified with the model, and such research could play an important role in limiting sediment erosion in the dense highland field area. Pollutant load per event, event mean concentration (EMC), and pollutant load per area were estimated from stormwater survey data from the Lake Soyang basin. During the wet season, heavy rains cause large amounts of suspended sediment and the occurrence of such rains is increasing due to climate change. The explanatory variables used in the MLR models are the percentage of fields, subbasin area, and mean slope of subbasin as topographic parameters, and the number of preceding dry days, rainfall intensity, rainfall depth, and rainfall duration as rainfall parameters. In the MLR modeling process, four types of regression equations with and without log transformation of the explanatory and response variables were examined to identify the best performing regression model. The performance of the MLR models was evaluated using the coefficient of determination (R2), root mean square error (RMSE), coefficient of variation of the root mean square error (CV(RMSE)), the ratio of the RMSE to the standard deviation of the observed data (RSR) and the Nash–Sutcliffe model efficiency (NSE). The performance of the MLR models of pollutant load except total nitrogen (TN) was good under the condition of RSR, and satisfactory for the NSE and R2. In the EMC and load/area models, the performance for suspended solids (SS) and total phosphorus (TP) was good for the RSR, and satisfactory for the NSE and R2. The standardized coefficients for the models were analyzed to identify the influential explanatory variables in the models. In the final performance evaluation, the results of jackknife validation indicate that the MLR models are robust. Full article
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Open AccessArticle
Analysis of Natural Streamflow Variation and Its Influential Factors on the Yellow River from 1957 to 2010
Water 2018, 10(9), 1155; https://doi.org/10.3390/w10091155
Received: 10 July 2018 / Revised: 20 August 2018 / Accepted: 24 August 2018 / Published: 29 August 2018
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Abstract
In this study, variation characteristics of hydrometeorological factors were explored based on observed time-series data between 1957 and 2010 in four subregions of the Yellow River Basin. For each region, precipitation–streamflow models at annual and flood-season scales were developed to quantify the impact [...] Read more.
In this study, variation characteristics of hydrometeorological factors were explored based on observed time-series data between 1957 and 2010 in four subregions of the Yellow River Basin. For each region, precipitation–streamflow models at annual and flood-season scales were developed to quantify the impact of annual precipitation, temperature, percentage of flood-season precipitation, and anthropogenic interference. The sensitivities of annual streamflow to these three climatic factors were then calculated using a modified elasticity coefficient model. The results presented the following: (1) Annual streamflow exhibited a negative trend in all regions; (2) The reduction of annual streamflow was mainly caused by a precipitation decrease and temperature increase for all regions before 2000, whereas the contribution of anthropogenic interference increased significantly—more than 45%, except for Tang-Tou region after 2000. The percentage of flood-season precipitation variation can also be responsible for annual streamflow reduction with a range of 7.36% (Tang-Tou) to 21.88% (Source); (3) Annual streamflow was more sensitive to annual precipitation than temperature in the humid region, and the opposite situation was observed in the arid region. The sensitivities to intra-annual climate variation increased after 2000 for all regions, and the increase was more significant in Tou-Long and Long-Hua regions. Full article
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Open AccessArticle
Four Decades of Estuarine Wetland Changes in the Yellow River Delta Based on Landsat Observations Between 1973 and 2013
Water 2018, 10(7), 933; https://doi.org/10.3390/w10070933
Received: 30 April 2018 / Revised: 28 June 2018 / Accepted: 3 July 2018 / Published: 13 July 2018
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Abstract
Yellow River Delta wetlands are essential for the migration of endangered birds and breeding. The wetlands, however, have been severely damaged during recent decades, partly due to the lack of wetland ecosystem protection by authorities. To have a better historical understanding of the [...] Read more.
Yellow River Delta wetlands are essential for the migration of endangered birds and breeding. The wetlands, however, have been severely damaged during recent decades, partly due to the lack of wetland ecosystem protection by authorities. To have a better historical understanding of the spatio-temporal dynamics of the wetlands, this study aims to map and characterize patterns of the loss and degradation of wetlands in the Yellow River Delta using a time series of remotely sensed images (at nine points in time) based on object-based image analysis and knowledge transfer learning technology. Spatio-temporal analysis was conducted to document the long-term changes taking place in different wetlands over the four decades. The results showed that the Yellow River Delta wetlands have experienced significant changes between 1973 and 2013. The total area of wetlands has been reduced by 683.12 km2 during the overall period and the trend of loss continues. However, the rates and trends of change for the different types of wetlands were not the same. The natural wetlands showed a statistically significant decrease in area during the overall period (36.04 km2·year−1). Meanwhile, the artificial wetlands had the opposite trend and showed a statistically significant increase in area during the past four decades (18.96 km2·year−1). According to the change characteristics revealed by the time series wetland classification maps, the evolution process of the Yellow River Delta wetlands could be divided into three stages: (1) From 1973–1984, basically stable, but with little increase; (2) from 1984–1995, rapid loss; and (3) from 1995–2013, slow loss. The area of the wetlands reached a low point around 1995, and then with a little improvement, the regional wetlands entered a slow loss stage. It is believed that interference by human activities (e.g., urban construction, cropland creation, and oil exploitation) was the main reason for wetland degradation in the Yellow River Delta over the past four decades. Climate change also has long-term impacts on regional wetlands. In addition, due to the special geographical environment, the hydrological and sediment conditions and the location of the Yellow River mouth also have a significant influence on the evolution process of the wetlands. Full article
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Open AccessArticle
The Effects of Litter Layer and Topsoil on Surface Runoff during Simulated Rainfall in Guizhou Province, China: A Plot Scale Case Study
Water 2018, 10(7), 915; https://doi.org/10.3390/w10070915
Received: 25 May 2018 / Revised: 25 June 2018 / Accepted: 9 July 2018 / Published: 11 July 2018
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Abstract
Litter layers and topsoil have important effects on surface runoff. To investigate these effects at the plot scale, artificial rainfall experiments were conducted on micro-runoff plots in Guizhou Province, China. Three types of plots were selected, the thin litter layer with low soil [...] Read more.
Litter layers and topsoil have important effects on surface runoff. To investigate these effects at the plot scale, artificial rainfall experiments were conducted on micro-runoff plots in Guizhou Province, China. Three types of plots were selected, the thin litter layer with low soil bulk density type (T-L type), the thick litter layer with high soil bulk density type (T-H type), and the moderate litter depth and soil bulk density type (M type), and three artificial rainfall intensities (30 mm/h, 70 mm/h, 120 mm/h) were used. The runoff volume was largest in the T-H type plot at different rainfall intensities and durations. Runoff in the M type plot had characteristics of both the T-L and T-H type plots. The runoff yielding speed was significantly higher and the runoff yielding time was significantly lower in the T-H type plot. In general, the runoff coefficient was the smallest in the T-L type plot and largest in the T-H type plot. The variations in the runoff coefficient were 15.6%, 19.3%, and 5.8% for the T-L, T-H, and M type plots respectively. The results of this study can improve the understanding of surface runoff processes at the plot scale under different litter and surface soil conditions. Full article
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Open AccessArticle
Integrating Field Experiments with Modeling to Evaluate the Freshwater Availability at Ungauged Sites: A Case Study of Pingtan Island (China)
Water 2018, 10(6), 740; https://doi.org/10.3390/w10060740
Received: 7 May 2018 / Revised: 29 May 2018 / Accepted: 30 May 2018 / Published: 6 June 2018
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Abstract
Predictions in ungauged basins (PUB) has been always a focus of hydrological research. The problem presented by ungauged basins is how to reasonably estimate water resource availability. To solve the issues of data scale, this study combines field experiments and hydrological models to [...] Read more.
Predictions in ungauged basins (PUB) has been always a focus of hydrological research. The problem presented by ungauged basins is how to reasonably estimate water resource availability. To solve the issues of data scale, this study combines field experiments and hydrological models to estimate freshwater availability in a typical ungauged sea island located in southeastern China. The free parameters in the hydrological model were derived from the point-scale rainfall-runoff experiments rather than calibration using river discharge observations. The rainfall-runoff experiments were performed on six sites covering 11 land cover types. Model validation at a sub-catchment showed that the combined method could successfully reproduce monthly streamflow, with a Nash–Sutcliffe Efficiency of 0.82, correlation coefficient of 0.85, and flow volume error of 6.5%. The simulation results indicate high heterogeneity and distinct seasonal dynamics in freshwater availability across the entire island. This pioneering PUB study for Chinese islands could provide reference for planning and management of freshwater in a water shortage area. Full article
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Open AccessArticle
Assessing the Influence of the Three Gorges Dam on Hydrological Drought Using GRACE Data
Water 2018, 10(5), 669; https://doi.org/10.3390/w10050669
Received: 17 April 2018 / Revised: 19 May 2018 / Accepted: 19 May 2018 / Published: 22 May 2018
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Abstract
With worldwide economic and social development, more dams are being constructed to meet the increasing demand for hydropower, which may considerably influence hydrological drought. Here, an index named the “Dam Influence Index” (DII) is proposed to assess the influence of the Three Gorges [...] Read more.
With worldwide economic and social development, more dams are being constructed to meet the increasing demand for hydropower, which may considerably influence hydrological drought. Here, an index named the “Dam Influence Index” (DII) is proposed to assess the influence of the Three Gorges Dam (TGD) on hydrological drought in the Yangtze River Basin (YRB) in China. First, the total terrestrial water storage (TTWS) is derived from Gravity Recovery and Climate Experiment data. Then, the natural-driven terrestrial water storage (NTWS) is predicted from the soil moisture, precipitation, and temperature data based on an artificial neural network model. Finally, the DII is derived using the empirical (Kaplan-Meier) cumulative distribution function of the differences between the TTWS and the NTWS. The DIIs of the three sub-basins in the YRB were 1.38, −4.66, and −7.32 between 2003 and 2008, which indicated an increase in TTWS in the upper sub-basin and a reduction in the middle and lower sub-basins. According to the results, we concluded that impoundments of the TGD between 2003 and 2008 slightly alleviated the hydrological drought in the upper sub-basin and significantly aggravated the hydrological drought in the middle and lower sub-basins, which is consistent with the Palmer Drought Severity Index. This study provides a new perspective for estimating the effects of large-scale human activities on hydrological drought and a scientific decision-making basis for the managing water resources over the operation of the TGD. Full article
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Review

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Open AccessReview
Explaining Water Pricing through a Water Security Lens
Water 2018, 10(9), 1173; https://doi.org/10.3390/w10091173
Received: 8 July 2018 / Revised: 6 August 2018 / Accepted: 27 August 2018 / Published: 1 September 2018
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Abstract
Can water security serve as a platform for developing a long-term solution to ongoing water crises? Many regions around the world are experiencing severe water problems, including water scarcity, water-borne diseases, water-related natural hazards, and water conflicts. These issues are expected to increase [...] Read more.
Can water security serve as a platform for developing a long-term solution to ongoing water crises? Many regions around the world are experiencing severe water problems, including water scarcity, water-borne diseases, water-related natural hazards, and water conflicts. These issues are expected to increase and intensify in the future. Both developed and developing economies face a water supply and demand imbalance that will potentially influence their water pricing structures. Institutions and policies that govern the pricing of this natural capital remain crucial for driving food production and providing services. The complex and multifaceted issues of sustainable water management call for a standard set of tools that can capture and create desired water security scenarios. Water pricing is an important contributing factor for achieving these scenarios. In this paper, we analyze how water pricing can be used as a tool to enact the water security agenda. This paper addresses these issues from three facets: (1) Economic aspects—the multiple processes through which water is conceptualized and priced; (2) analysis of water pricing considering its effect in water consumption; and (3) arguments for assessing the potential of water pricing as a tool to appraise water security. Full article
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Open AccessReview
Compound Extremes in Hydroclimatology: A Review
Water 2018, 10(6), 718; https://doi.org/10.3390/w10060718
Received: 24 April 2018 / Revised: 28 May 2018 / Accepted: 30 May 2018 / Published: 1 June 2018
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Abstract
Extreme events, such as drought, heat wave, cold wave, flood, and extreme rainfall, have received increasing attention in recent decades due to their wide impacts on society and ecosystems. Meanwhile, the compound extremes (i.e., the simultaneous or sequential occurrence of multiple extremes at [...] Read more.
Extreme events, such as drought, heat wave, cold wave, flood, and extreme rainfall, have received increasing attention in recent decades due to their wide impacts on society and ecosystems. Meanwhile, the compound extremes (i.e., the simultaneous or sequential occurrence of multiple extremes at single or multiple locations) may exert even larger impacts on society or the environment. Thus, the past decade has witnessed an increasing interest in compound extremes. In this study, we review different approaches for the statistical characterization and modeling of compound extremes in hydroclimatology, including the empirical approach, multivariate distribution, the indicator approach, quantile regression, and the Markov Chain model. The limitation in the data availability to represent extremes and lack of flexibility in modeling asymmetric/tail dependences of multiple variables/events are among the challenges in the statistical characterization and modeling of compound extremes. Major future research endeavors include probing compound extremes through both observations with improved data availability (and statistical model development) and model simulations with improved representation of the physical processes to mitigate the impacts of compound extremes. Full article
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