Special Issue "Hydrological Modeling in Water Cycle Processes"

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

Deadline for manuscript submissions: closed (31 December 2020).

Special Issue Editors

Prof. Dr. Chong-Yu Xu
E-Mail Website
Guest Editor
Department of Geosciences, University of Oslo, N-0316 Oslo, Norway
Interests: hydrological modeling; flood forecasting, regionalization; uncertainty; impact of climate change and land use change; evapotranspiration
Special Issues and Collections in MDPI journals
Prof. Dr. Weiguang Wang
E-Mail Website
Guest Editor
State Key Laboratory of Hydrology, Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
Interests: evapotranspiration; hydrothermal coupling; remote sensing hydrology; hydrological processes; land–atmosphere interactions; land use and land cover change; hydrometeorology
Prof. Dr. Lu Chen
E-Mail Website
Guest Editor
College of Hydropower & Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: hydrological modeling; flood forecast; hydrological statistics; reservoir operation; risk analysis; stochastic simulation

Special Issue Information

Dear Colleagues,

Water cycle processes are complex and have been affected by climate change and human interferences. Modeling the water cycle processes is always a critical strategy for hydrologic research and has long been the goal of all hydrologists. Hydrological models have been developed for many different reasons and therefore have many different forms. However, they are in general designed to meet one of two primary objectives. One objective of hydrological modeling is to gain a better understanding of the hydrological phenomena operating in a catchment and of how changes in the catchment may affect these phenomena. Another objective of hydrological modeling is the generation of synthetic sequences of hydrological data (in both gauged and/or ungauged regions) for facility design or for use in forecasting. In past decades, they were also used to study the potential impacts of changes in land use or climate, reservoir operation, real-time hydrodynamic streamflow routing, real-time flood inundation evaluation, etc. Though great progress has been achieved, challenges still exist in this area—for example, the lack of a profound mechanism understanding of the impacts of a changing environment on water cycle processes, and corresponding effective modeling methodology, as well as uncertainty issues related to data, model parameters and structure—and further studies are required. Discussing these challenges, finding solutions, and presenting the latest achievements are the key purposes of this Special Issue.

This Special Issue welcomes articles dedicated to all aspects of hydrological element measurements and modeling in water cycle processes.

Prof. Dr. Chong-Yu Xu
Prof. Dr. Weiguang Wang
Prof. Dr. Lu Chen
Guest Editors

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Keywords

  • Hydrological forecast
  • Streamflow simulation
  • Hydrological model uncertainty
  • Runoff responses to climate change and human activities
  • Hydrological time series analysis
  • Implementation of ensemble hydrologic forecasting
  • Reservoir simulation
  • Hydrodynamic streamflow routing models
  • Evapotranspiration modeling
  • Hydrothermal coupling
  • Remote sensing and modeling

Published Papers (16 papers)

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Research

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Article
Responses of Hydrological Processes under Different Shared Socioeconomic Pathway Scenarios in the Huaihe River Basin, China
Water 2021, 13(8), 1053; https://doi.org/10.3390/w13081053 - 12 Apr 2021
Viewed by 363
Abstract
The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides more scenarios and reliable climate change results for improving the accuracy of future hydrological parameter change analysis. This study uses five CMIP6 global climate models (GCMs) to drive the variable infiltration capacity (VIC) model, [...] Read more.
The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides more scenarios and reliable climate change results for improving the accuracy of future hydrological parameter change analysis. This study uses five CMIP6 global climate models (GCMs) to drive the variable infiltration capacity (VIC) model, and then simulates the hydrological response of the upper and middle Huaihe River Basin (UMHRB) under future shared socioeconomic pathway scenarios (SSPs). The results show that the five-GCM ensemble improves the simulation accuracy compared to a single model. The climate over the UMHRB likely becomes warmer. The general trend of future precipitation is projected to increase, and the increased rates are higher in spring and winter than in summer and autumn. Changes in annual evapotranspiration are basically consistent with precipitation, but seasonal evapotranspiration shows different changes (0–18%). The average annual runoff will increase in a wavelike manner, and the change patterns of runoff follow that of seasonal precipitation. Changes in soil moisture are not obvious, and the annual soil moisture increases slightly. In the intrayear process, soil moisture decreases slightly in autumn. The research results will enhance a more realistic understanding of the future hydrological response of the UMHRB and assist decision-makers in developing watershed flood risk-management measures and water and soil conservation plans. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Changes of Flow and Sediment Transport in the Lower Min River in Southeastern China under the Impacts of Climate Variability and Human Activities
Water 2021, 13(5), 673; https://doi.org/10.3390/w13050673 - 02 Mar 2021
Viewed by 536
Abstract
The Min River is the largest river in Fujian Province in southeastern China. The construction of a series of dams along the upper reaches of the Min River, especially the Shuikou Dam, which started filling in 1993, modified the flow processes at the [...] Read more.
The Min River is the largest river in Fujian Province in southeastern China. The construction of a series of dams along the upper reaches of the Min River, especially the Shuikou Dam, which started filling in 1993, modified the flow processes at the lower Min River, leading to the significant increase in low-flows and slightly decrease in flood-flows. At the same time, reservoirs have more effects on the sediment transport process than flow process by trapping most sediment in the reservoirs, and greatly reduced the amount of sediment transporting downstream. Increase in vegetation cover also contributes to the decrease in sediment yield. The reduction in sediment together with excessive sand mining in the lower Min River resulted in the severe downward erosion of the riverbed. Using a reformulated elasticity approach to quantifying climatic and anthropogenic contributions to sediment changes, the relative contribution of precipitation variability and human activities to sediment reduction in the lower Min River are quantified, which shows that the sediment reduction is fully caused by human activities (including land use/land cover changes and dam construction). Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Stepwise Identification of Influencing Factors and Prediction of Typhoon Precipitation in Anhui Province Based on the Back Propagation Neural Network Model
Water 2021, 13(4), 550; https://doi.org/10.3390/w13040550 - 21 Feb 2021
Viewed by 518
Abstract
Typhoon is one of the most frequent meteorological phenomena that covers most of central-eastern China during the summer. Typhoon-induced precipitation is one of the most important water resources, but it often leads to severe flood disasters. Accurate typhoon precipitation prediction is crucial for [...] Read more.
Typhoon is one of the most frequent meteorological phenomena that covers most of central-eastern China during the summer. Typhoon-induced precipitation is one of the most important water resources, but it often leads to severe flood disasters. Accurate typhoon precipitation prediction is crucial for mitigating typhoon disasters and managing water resources. Anhui Province, located in East China, is a typhoon affected region. Typhoon-related disasters are its major natural disasters. This study aims at developing a new back propagation (BP) neural network model to predict both the typhoon precipitation event and the typhoon precipitation amount. The predictors in the model are identified through correlation analysis of the above two target variables and a large set of candidate variables. We further improve the predictor selection through an iterative approach, which proposes new predictors for the BP model in each iteration by analyzing the differences of candidate predictors between the years with large prediction errors and the normal years. The results show that the accuracy of the BP-based summer typhoon event prediction model in the simulation period from 1957 to 2006 is 100%, and its accuracy in the validation period from 2007 to 2016 is 90%. In addition, the absolute value of the mean relative error predicted by the typhoon precipitation amount model for the simulation period is 20.9%. A significant error can be found in 2000 as the mechanism of typhoon precipitation in this year is different from that of other normal years. The error in 2000 is probably caused by the impact of vertical shear anomalies over the western Pacific which hinders the development of typhoon embryos. Additionally, the absolute value of the mean relative error predicted by the typhoon precipitation amount model in the validation period is 14.2%. A significant error also can be found in 2009, probably due to the influence of the asymmetry in the typhoon cloud system. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Nonstationary Ecological Instream Flow and Relevant Causes in the Huai River Basin, China
Water 2021, 13(4), 484; https://doi.org/10.3390/w13040484 - 13 Feb 2021
Viewed by 612
Abstract
Based on the daily precipitation data during 1960–2016 at 72 stations and the daily streamflow data during 1956–2016 at 7 hydrological stations in the Huai River Basin (HRB), China, eco-surplus and eco-deficit under influences of abrupt streamflow behaviors were analyzed using Flow Duration [...] Read more.
Based on the daily precipitation data during 1960–2016 at 72 stations and the daily streamflow data during 1956–2016 at 7 hydrological stations in the Huai River Basin (HRB), China, eco-surplus and eco-deficit under influences of abrupt streamflow behaviors were analyzed using Flow Duration Curve (FDC). The relations between indicators of hydrological alteration (IHA) and ecological indicators (Shannon Index, SI) were quantified, investigating impacts of altered hydrological processes on the evaluations of the ecological instream flow. Besides, we also quantified fractional contributions of climatic indices to nonstationary ecological instream flow using the Generalized Additive Models for Location Scale and Shape (GAMLSS) framework. While the possible impact of human activities on ecological instream flow will be revealed based on land use changes data. The results indicated that: (1) FDC is subject to general decrease due to hydrological alterations, and most streamflow components are lower than 25% FDC. We found increased eco-deficit and decreased eco-surplus due to altered hydrological processes. The FDC of the streamflow in the main stream of the HRB is lower than that along the tributaries of the HRB. Eco-surplus (eco-deficit) changes are in good line with precipitation anomaly changes during the Spring, Autumn and Winter periods. However, the hydrological alterations due to hydrological regulations by the reservoirs are the primary cause behind the mismatch between ecological instream flow and precipitation anomalies during summer; (2) Annual and seasonal eco-surplus (eco-deficit) is decreasing (increasing) and that during winter season is an exception. Although higher eco-surplus in winter than in other seasons, the eco-surplus is decreasing persistently and the 21st century witnessed the lowest eco-surplus along the main stream of the HRB. Meanwhile, the Shannon index indicated decreased ecological diversity across the HRB; (3) The ecological instream flow is highly sensitive to The Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Niño 3.4 Sea Surface Temperature Index (Nino3.4). Meanwhile, the ecological instream flow along the mainstream of the HRB is highly sensitive to climate indices. While the ecological instream flow by GAMLSS model has better fitting performance in describing the extreme values and local trends. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Uncertainty Analysis of SWAT Modeling in the Lancang River Basin Using Four Different Algorithms
Water 2021, 13(3), 341; https://doi.org/10.3390/w13030341 - 29 Jan 2021
Viewed by 580
Abstract
The hydrological model is the primary tool for regional water resources management, allocation, and prediction. However, these models always suffer from large uncertainties from multiple sources. Therefore, it is necessary to conduct an uncertainty analysis before performing hydrological simulation. Sequential Uncertainty Fitting (SUFI-2), [...] Read more.
The hydrological model is the primary tool for regional water resources management, allocation, and prediction. However, these models always suffer from large uncertainties from multiple sources. Therefore, it is necessary to conduct an uncertainty analysis before performing hydrological simulation. Sequential Uncertainty Fitting (SUFI-2), Parameter Solution (ParaSol), Generalized Likelihood Uncertainty Estimation (GLUE), and Particle Swarm Optimization (PSO) integrated with the SWAT-CUP software were used to calibrate the Soil and Water Assessment Tool (SWAT) model and quantify the parameter sensitivity and prediction uncertainty of the SWAT in the Lancang River (LR) Basin, which is located in the southwest of China. This model was calibrated and validated using the four algorithms both at the daily scale, and the optimal simulation results derived by the four methods showed that the SWAT model performed well over the Yunjinghong station with Nash–Sutcliffe efficiency coefficient (NSE) and coefficient of determination (R2) values greater than 0.8 both in the calibration (1975 to 1989) and validation (1990 to 2004) periods. Among the four algorithms, the ParaSol algorithm produced the best simulation result at the daily scale with NSE values of 0.89 and 0.90 for the calibration and validation periods, respectively. Furthermore, the ParaSol algorithm has the greatest proportion of simulations (94%) with an NSE greater than 0.5. Parameter sensitivity analysis results demonstrated that the four methods all can be used for parameter sensitivity analysis in streamflow simulation, and they all identified that the base flow factor for bank storage (ALPHA_BNK) and effective hydraulic conductivity in the main channel alluvium (CH_K2) were more sensitive. The uncertainty analysis of model parameters showed that the parameter 95PPU (95% prediction uncertainty) width yielded by the ParaSol algorithm was the smallest compared with that of the other methods, followed by PSO, SUFI-2, and GLUE. The uncertainty analysis of the model simulation indicated that the SUFI-2 and PSO methods can achieve satisfactory results (with P-factor > 0.7 and R-factor < 1.5) at the daily scale; among them, SUFI-2 (P-factor = 0.93, R-factor = 1.17) performed much better than PSO (P-factor = 0.78, R-factor = 1.14). In general, by comparing its evaluation criteria (NSE, R2, RE, P-factor, and R-factor) to other methods, ParaSol stood out as the most efficient tool for model calibration. However, SUFI-2 remains the most robust method to perform uncertainty analysis considering its uncertainties of model structure, model inputs, and parameters. This study provides insight into hydrological simulation of the LR Basin using the appropriate algorithm to calibrate the model and implement the uncertainty analysis. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Spatial and Temporal Characteristics of Precipitation and Potential Influencing Factors in the Loess Plateau before and after the Implementation of the Grain for Green Project
Water 2021, 13(2), 234; https://doi.org/10.3390/w13020234 - 19 Jan 2021
Viewed by 539
Abstract
Since the implementation of the Grain for Green Project (GFGP) in the 1990s, the warming and wetting trend in the Loess Plateau is becoming statistically significant in the context of climate change. However, the correlation between precipitation increase and the regional vegetation restoration [...] Read more.
Since the implementation of the Grain for Green Project (GFGP) in the 1990s, the warming and wetting trend in the Loess Plateau is becoming statistically significant in the context of climate change. However, the correlation between precipitation increase and the regional vegetation restoration is still controversial. To explore the main factors influencing the regional precipitation change, this study selected five potential influencing factors including potential evapotranspiration (PET), normalized difference vegetation index (NDVI), precipitable water (PW), surface temperature (ST), and water vapor transport (WVT). We used the statistical methods to analyze the spatial-temporal distribution of precipitation before and after the GFGP and to quantify the relative influence degree of different factors to precipitation change. The results show that: (1) The precipitation increased significantly (95% confidence level) after the GFGP, with an increase rate of 4.96 mm a−1; (2) from the perspective of spatial-temporal distribution, the precipitation in the southern part of the Loess plateau was significantly increasing with an increase rate of 20–50 mm in the period of 2000–2014; (3) the relative influence degree of NDVI to precipitation increased after the GFGP, and the annual precipitation (PREA) and summer precipitation (PRES) was more influenced by NDVI (relative influence degree of 30.18% and 31.37%, respectively) compared with winter precipitation. In winter, the PW and the PET are the main influencing factors for the precipitation change with relative influence degrees of 30.13% and 27.64%, respectively. Based on this study, we speculate that the warming and wetting trend of the Loess Plateau in recent years is not only closely related to global climate change, but also significantly affected by local climate change brought by vegetation restoration. The above conclusions are important for future ecological restoration and water resources management in the water-scarce Loess Plateau. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Investigating Hydrological Variability in the Wuding River Basin: Implications for Water Resources Management under the Water–Human-Coupled Environment
Water 2021, 13(2), 184; https://doi.org/10.3390/w13020184 - 14 Jan 2021
Viewed by 493
Abstract
Understanding and quantifying changes in hydrological systems due to human interference are critical for the implementation of adaptive management of global water resources in the changing environment. To explore the implications of hydrological variations for water resources management, the Wuding River Basin (WRB) [...] Read more.
Understanding and quantifying changes in hydrological systems due to human interference are critical for the implementation of adaptive management of global water resources in the changing environment. To explore the implications of hydrological variations for water resources management, the Wuding River Basin (WRB) in the Loess Plateau, China, was selected as a case study. Based on the Budyko-type equation with a time-varying parameter n, a human-induced water–energy balance (HWEB) model was proposed to investigate the hydrological variability in the WRB. The investigation showed that runoff continuously reduced by 0.424 mm/a during 1975–2010, with weakly reducing precipitation and increasing groundwater exploitation causing a decrease in groundwater storage at a rate of 1.07 mm/a, and actual evapotranspiration accounting for more than 90% of precipitation having an insignificantly decreasing trend with a rate of 0.53 mm/a under climate change (decrease) and human impact (increase). Attribution analysis indicated that human-induced underlying surface condition change played a dominant role in runoff reduction by driving an increase in actual evapotranspiration, and that mainly impacted the overall decrease in runoff compounded by climate change during the entire period. It is suggested that reducing the watershed evapotranspiration and controlling groundwater exploitation should receive greater attention in future basin management. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Quantitative Lasting Effects of Drought Stress at a Growth Stage on Soybean Evapotranspiration and Aboveground BIOMASS
Water 2021, 13(1), 18; https://doi.org/10.3390/w13010018 - 24 Dec 2020
Cited by 1 | Viewed by 643
Abstract
Quantifying the lasting effects of drought stress on crop growth is a theoretical basis for revealing agricultural drought risk mechanism and formulating adaptive irrigation strategies. Based on two-season pot experiments of soybean in the Huaibei Plain, quantitative responses of plant evapotranspiration and aboveground [...] Read more.
Quantifying the lasting effects of drought stress on crop growth is a theoretical basis for revealing agricultural drought risk mechanism and formulating adaptive irrigation strategies. Based on two-season pot experiments of soybean in the Huaibei Plain, quantitative responses of plant evapotranspiration and aboveground biomass at each growth stage from a drought were carried out. The results showed that drought stress at a certain stage of soybean not only significantly reduced the current evapotranspiration and aboveground biomass accumulation during this stage, compared with full irrigation, but also generated the after-effects, which resulted in the reductions of evapotranspiration and biomass accumulation at the subsequent periods. Furthermore, the damaged transpiration and growth mechanism caused by drought gradually recovered through the rewatering later, and the compensation phenomenon even occurred. Nevertheless, the specific recovery effect was decided by both the degree and period of drought before. It is practical to implement deficit irrigation at the seedling and branching stages, but the degree should be controlled. Meanwhile, it is crucial to ensure sufficient water supply during the reproductive growth phase, especially at the flowering and pod-enlargement stage, to guarantee a normal transpiration function and a high biomass yield for soybeans in the Huaibei Plain. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Quantifying the Impacts of Climate Change and Human Activities on Runoff in the Lancang River Basin Based on the Budyko Hypothesis
Water 2020, 12(12), 3501; https://doi.org/10.3390/w12123501 - 13 Dec 2020
Cited by 1 | Viewed by 556
Abstract
Based on the Lancang River Basin (LRB) hydro–meteorological data from 1961 to 2015, this study uses the Mann–Kendall trend test and mutation test to analyze the trend of hydro–meteorological variables, as well as which year the runoff series changes, respectively. We applied the [...] Read more.
Based on the Lancang River Basin (LRB) hydro–meteorological data from 1961 to 2015, this study uses the Mann–Kendall trend test and mutation test to analyze the trend of hydro–meteorological variables, as well as which year the runoff series changes, respectively. We applied the Choudhury–Yang equation to calculate the climate and catchment landscape elasticity of runoff. Then we quantified the impact of climate change and human activities on runoff change. The results show that: (1) the mean annual precipitation (P) in LRB showed an insignificant decline, the annual potential evapotranspiration (E0) showed a significant increase, and the runoff depth (R) showed a significant decrease; (2) the abrupt change of the R occurred in 2005. Both the climate and catchment landscape elasticity of runoff increased, which means that the hydrological process of LRB became more sensitive to climate changes and human activities; (3) compared with the base period (1961–2004), the reduction of P was the leading cause of runoff reduction, with a contribution of 45.64%. The contribution of E0 and human activities to runoff changes are 13.91% and 40.45%, respectively. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Evaluation of TMPA Satellite Precipitation in Driving VIC Hydrological Model over the Upper Yangtze River Basin
Water 2020, 12(11), 3230; https://doi.org/10.3390/w12113230 - 18 Nov 2020
Viewed by 582
Abstract
Although the Tropical Rainfall Measurement Mission (TRMM) has come to an end, the evaluation of TRMM satellite precipitation is still of great significance for the improvement of the Global Precipitation Measurement (GPM). In this paper, the hydrological utility of TRMM Multi-satellite Precipitation Analysis [...] Read more.
Although the Tropical Rainfall Measurement Mission (TRMM) has come to an end, the evaluation of TRMM satellite precipitation is still of great significance for the improvement of the Global Precipitation Measurement (GPM). In this paper, the hydrological utility of TRMM Multi-satellite Precipitation Analysis (TMPA) 3B42 RTV7/V7 precipitation products was evaluated using the variable infiltration capacity (VIC) hydrological model in the upper Yangtze River basin. The main results show that (1) TMPA 3B42V7 had a reliable performance in precipitation estimation compared with the gauged precipitation on both spatial and temporal scales over the upper Yangtze River basin. Although TMPA 3B42V7 slightly underestimated precipitation, TMPA 3B42RTV7 significantly overestimated precipitation at daily and monthly time scales; (2) the simulated runoff by the VIC hydrological model showed a high correlation with the gauged runoff and lower bias at daily and monthly time scales. The Nash–Sutcliffe coefficient of efficiency (NSCE) value was as high as 0.85, the relative bias (RB) was −6.36% and the correlation coefficient (CC) was 0.93 at the daily scale; (3) the accuracy of the 3B42RTV7-driven runoff simulation had been greatly improved by using the hydrological calibration parameters obtained from 3B42RTV7 compared with that of gauged precipitation. A lower RB (14.38% vs. 66.58%) and a higher CC (0.87 vs. 0.85) and NSCE (0.71 vs. −0.92) can be found at daily time scales when we use satellite data instead of gauged precipitation data to calibrate the VIC model. However, the performance of the 3B42V7-driven runoff simulation did not improve in the same operation accordingly. The cause might be that the 3B42V7 satellite products have been adjusted by gauged precipitation. This study suggests that it might be better to calibrate the parameters using satellite data in hydrological simulations, especially for unadjusted satellite data. This study is not only helpful for understanding the assessment of multi-satellite precipitation products in large-scale and complex areas in the upper reaches of the Yangtze River, but also can provide a reference for the hydrological utility of the satellite precipitation products in other river basins of the world. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Variation of Melt Water and Rainfall Runoff and Their Impacts on Streamflow Changes during Recent Decades in Two Tibetan Plateau Basins
Water 2020, 12(11), 3112; https://doi.org/10.3390/w12113112 - 06 Nov 2020
Viewed by 551
Abstract
To fully understand potential changes in hydrological regime over the Lhasa River Basin (LRB) and the upstream of Niyang River Basin (UNRB) in Tibetan Plateau under global warming, the VIC-glacier model was employed to analyze the responses of rainfall runoff and melt water [...] Read more.
To fully understand potential changes in hydrological regime over the Lhasa River Basin (LRB) and the upstream of Niyang River Basin (UNRB) in Tibetan Plateau under global warming, the VIC-glacier model was employed to analyze the responses of rainfall runoff and melt water to recent climate change, and we also quantify their roles in controlling the trend of river streamflow during 1963–2012. The hydrological model was calibrated using the observed streamflow, glacier mass balance, and MODIS snow cover. The simulations indicate that there is a significant increasing trend in glacier runoff for both basins during 1963–2012, especially in the period of 2000s when it exhibits a large increment up to about 45% relative to baseline period. Rainfall runoff suggests a rising tendency whereas snowmelt runoff displays a general decreasing tendency. For both basins, increasing rainfall runoff was identified as the dominant driver for the upward trend in total runoff during 1963–2012. The role of glacier runoff in controlling the trend of total runoff is also obvious, especially in the more glaciated UNRB where increased glacier runoff accounts for up to 41% of the tendency in river discharge. Snowmelt runoff plays a minor role in affecting the trend of total runoff. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Statistical and Hydrological Evaluations of Multiple Satellite Precipitation Products in the Yellow River Source Region of China
Water 2020, 12(11), 3082; https://doi.org/10.3390/w12113082 - 03 Nov 2020
Cited by 1 | Viewed by 617
Abstract
Comprehensively evaluating satellite precipitation products (SPPs) for hydrological simulations on watershed scales is necessary given that the quality of different SPPs varies remarkably in different regions. The Yellow River source region (YRSR) of China was chosen as the study area. Four SPPs were [...] Read more.
Comprehensively evaluating satellite precipitation products (SPPs) for hydrological simulations on watershed scales is necessary given that the quality of different SPPs varies remarkably in different regions. The Yellow River source region (YRSR) of China was chosen as the study area. Four SPPs were statistically evaluated, namely, the Tropical Rainfall Measurement Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42V7, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR), Integrated Multisatellite Retrievals for Global Precipitation Measurement final run (IMERG-F), and gauge-corrected Global Satellite Mapping of Precipitation (GSMaP-Gauge) products. Subsequently, the hydrological utility of these SPPs was assessed via the variable infiltration capacity hydrological model on a daily temporal scale. Results show that the four SPPs generally demonstrate similar spatial distribution pattern of precipitation to that of the ground observations. In the period of January 1998 to December 2016, 3B42V7 outperforms PERSIANN-CDR on basin scale. In the period of April 2014 to December 2016, GSMaP-Gauge demonstrates the highest precipitation monitoring capability and hydrological utility among all SPPs on grid and basin scales. In general, 3B42V7, IMERG-F, and GSMaP-Gauge show a satisfactory hydrological performance in streamflow simulations in YRSR. IMERG-F has an improved hydrological utility than 3B42V7 in YRSR. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
MIDAS: A New Integrated Flood Early Warning System for the Miño River
Water 2020, 12(9), 2319; https://doi.org/10.3390/w12092319 - 19 Aug 2020
Cited by 3 | Viewed by 1079
Abstract
Early warning systems have become an essential tool to mitigate the impact of river floods, whose frequency and magnitude have increased during the last few decades as a consequence of climate change. In this context, the Miño River Flood Alert System (MIDAS) early [...] Read more.
Early warning systems have become an essential tool to mitigate the impact of river floods, whose frequency and magnitude have increased during the last few decades as a consequence of climate change. In this context, the Miño River Flood Alert System (MIDAS) early warning system has been developed for the Miño River (Galicia, NW Spain), whose flood events have historically caused severe damage in urban areas and are expected to increase in intensity in the next decades. MIDAS is integrated by a hydrologic (HEC-HMS) and a hydraulic (Iber+) model using precipitation forecast as input data. The system runs automatically and is governed by a set of Python scripts. When any hazard is detected, an alert is issued by the system, including detailed hazards maps, to help decision makers to take precise and effective mitigation measures. Statistical analysis supports the accuracy of hydrologic and hydraulic modules implemented to forecast river flow and flooded critical areas during the analyzed period of time, including some of the most extreme events registered in the Miño River. In fact, MIDAS has proven to be capable of predicting most of the alert situations occurred during the study period, showing its capability to anticipate risk situations. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
Water Balance Backward: Estimation of Annual Watershed Precipitation and Its Long-Term Trend with the Help of the Calibration-Free Generalized Complementary Relationship of Evaporation
Water 2020, 12(6), 1775; https://doi.org/10.3390/w12061775 - 22 Jun 2020
Cited by 1 | Viewed by 818
Abstract
Watershed-scale annual evapotranspiration (ET) is routinely estimated by a simplified water balance as the difference in catchment precipitation (P) and stream discharge (Q). With recent developments in ET estimation by the calibration-free generalized complementary relationship, the water balance equation [...] Read more.
Watershed-scale annual evapotranspiration (ET) is routinely estimated by a simplified water balance as the difference in catchment precipitation (P) and stream discharge (Q). With recent developments in ET estimation by the calibration-free generalized complementary relationship, the water balance equation is employed to estimate watershed/basin P at an annual scale as ET + Q on the United States (US) Geological Survey’s Hydrologic Unit Code (HUC) 2- and 6-level watersheds over the 1979–2015 period. On the HUC2 level, mean annual PRISM P was estimated with a correlation coefficient (R) of 0.99, relative bias (RB) of zero, root-mean-squared-error (RMSE) of 54 mm yr−1, ratio of standard deviations (RS) of 1.08, and Nash–Sutcliffe efficiency (NSE) of 0.98. On the HUC6 level, R, RS, and NSE hardly changed, RB remained zero, while RMSE increased to 90 mm yr−1. Even the long-term linear trend values were found to be fairly consistent between observed and estimated values with R = 0.97 (0.81), RMSE = 0.63 (1.63) mm yr−1, RS = 0.99 (1.05), NSE = 0.92 (0.59) on the HUC2 and HUC6 (in parentheses) levels. This calibration-free water-balance method demonstrates that annual watershed precipitation can be estimated with an acceptable accuracy from standard atmospheric/radiation and stream discharge data. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Article
An Evaluation Study of the Fully Coupled WRF/WRF-Hydro Modeling System for Simulation of Storm Events with Different Rainfall Evenness in Space and Time
Water 2020, 12(4), 1209; https://doi.org/10.3390/w12041209 - 24 Apr 2020
Cited by 1 | Viewed by 1443
Abstract
With the aim of improving the understanding of water exchanges in medium-scale catchments of northern China, the spatiotemporal characteristics of rainfall and several key water cycle elements e.g., soil moisture, evapotranspiration and generated runoff, were investigated using a fully coupled atmospheric-hydrologic modeling system [...] Read more.
With the aim of improving the understanding of water exchanges in medium-scale catchments of northern China, the spatiotemporal characteristics of rainfall and several key water cycle elements e.g., soil moisture, evapotranspiration and generated runoff, were investigated using a fully coupled atmospheric-hydrologic modeling system by integrating the Weather Research and Forecasting model (WRF) and its terrestrial hydrologic component WRF-Hydro (referred to as the fully coupled WRF/WRF-Hydro). The stand-alone WRF model (referred to as WRF-only) is also used as a comparison with the fully coupled system, which was expected to produce more realistic simulations, especially rainfall, by allowing the redistribution of surface and subsurface water across the land surface. Six storm events were sorted by different spatial and temporal distribution types, and categorical and continuous indices were used to distinguish the applicability in space and time between WRF-only and the fully coupled WRF/WRF-Hydro. The temporal indices showed that the coupled WRF-Hydro could improve the time homogeneous precipitation, but for the time inhomogeneous precipitation, it might produce a larger false alarm than WRF-only, especially for the flash storm that occurred in July, 2012. The spatial indices showed a lower mean bias error in the coupled system, and presented an enhanced simulation of both space homogeneous and inhomogeneous storm events than WRF-only. In comparison with WRF-only, the fully coupled WRF/WRF-Hydro had a closer to the observations particularly in and around the storm centers. The redistributions fluctuation of spatial precipitation in the fully coupled system was highly correlated with soil moisture, and a low initial soil moisture could lead to a large spatial fluctuated range. Generally, the fully coupled system produced slightly less runoff than WRF-only, but more frequent infiltration and larger soil moisture. While terrestrial hydrologic elements differed with relatively small amounts in the average of the two catchments between WRF-only and the fully coupled WRF/WRF-Hydro, the spatial distribution of elements in the water cycle before and after coupling with WRF-Hydro was not consistent. The soil moisture, runoff and precipitation in the fully coupled system had a similar spatial trend, but evapotranspiration did not always display the same. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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Review

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Review
Review: Sources of Hydrological Model Uncertainties and Advances in Their Analysis
Water 2021, 13(1), 28; https://doi.org/10.3390/w13010028 - 25 Dec 2020
Cited by 2 | Viewed by 1175
Abstract
Despite progresses in representing different processes, hydrological models remain uncertain. Their uncertainty stems from input and calibration data, model structure, and parameters. In characterizing these sources, their causes, interactions and different uncertainty analysis (UA) methods are reviewed. The commonly used UA methods are [...] Read more.
Despite progresses in representing different processes, hydrological models remain uncertain. Their uncertainty stems from input and calibration data, model structure, and parameters. In characterizing these sources, their causes, interactions and different uncertainty analysis (UA) methods are reviewed. The commonly used UA methods are categorized into six broad classes: (i) Monte Carlo analysis, (ii) Bayesian statistics, (iii) multi-objective analysis, (iv) least-squares-based inverse modeling, (v) response-surface-based techniques, and (vi) multi-modeling analysis. For each source of uncertainty, the status-quo and applications of these methods are critiqued in gauged catchments where UA is common and in ungauged catchments where both UA and its review are lacking. Compared to parameter uncertainty, UA application for structural uncertainty is limited while input and calibration data uncertainties are mostly unaccounted. Further research is needed to improve the computational efficiency of UA, disentangle and propagate the different sources of uncertainty, improve UA applications to environmental changes and coupled human–natural-hydrologic systems, and ease UA’s applications for practitioners. Full article
(This article belongs to the Special Issue Hydrological Modeling in Water Cycle Processes)
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