Special Issue "Advances in Hydrologic and Water Quality Modeling of Water Systems"

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 12854

Special Issue Editors

Dr. Saurav Kumar
E-Mail Website1 Website2
Guest Editor
Texas A&M AgriLife Research and Department of Biological and Agricultural Engineering, Texas A&M University, 1380 A&M Circle, El Paso, TX 79912, USA
Interests: watershed management; hydroinformatics; water system modeling; remote sensing
Dr. Vamsi Krishna Sridharan
E-Mail Website
Guest Editor
1. University of California, Santa Cruz, CA 95060, USA
2. Affiliated with Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, Santa Cruz, CA 95060, USA
Interests: hydrodynamic modelling; nonlinear system dynamics; signal processing; TMDL analysis; decision support
Special Issues, Collections and Topics in MDPI journals
Dr. Ebrahim Ahmadisharaf
E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, FAMU-FSU College of Engineering, 2525 Pottsdamer St, Tallahassee, FL 32310, USA
Interests: floods; surface hydrology; watersheds; uncertainty/risk; urban stormwater; environmental sustainability; integrated water resources management

Special Issue Information

Dear Colleagues,

Hydrologic and water quality modeling are critical for water systems management objectives such as mitigation of the risks from climatic extremes, regional planning, and pollution control. Contemporary water resources management approaches incorporate ecological needs, food and energy resources, and resilience and sustainability of the system along with conventional quantity, flow, and quality considerations. New computing, modeling, information technology, and data acquisition methods are becoming available that have significantly improved our understanding and the ability to tackle challenges. These changes require us to revisit the modeling practice and developing integrated simulation-optimization frameworks for tackling increasingly complex and wicked problems.

This Special Issue invites a broad range of papers related to advances in hydrologic, hydrodynamic, and water quality modeling in watersheds. Of particular interest are innovations in the application of remote sensing (e.g., aerial or satellite) at any stage of model development and use, model calibration, validation, sensitivity & uncertainty analysis, assessment of ecological and socioeconomic challenges, trans-jurisdictional water system modeling, impacts of climate change and other nonstationary stressors, and integrated system modeling (e.g., hydrologic/ecological/social/economic systems interactions). Articles on basic research, reviews, and case studies are invited. Articles should highlight or suggest advances from the current state-of-practice. The Special Issue is of interest to a broad range of audiences, including hydrologists, scientists, practitioners, regulators, engineers, geologists, policymakers, and modelers.

Dr. Saurav Kumar
Dr. Vamsi Krishna Sridharan
Dr. Ebrahim Ahmadisharaf
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 submissions that pass pre-check are 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. Land 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 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • remote Sensing applications
  • model calibration and validation
  • sensitivity and uncertainty analysis
  • fate and transport
  • ecological and socioeconomic implications
  • trans-jurisdictional water systems
  • integrated system modeling
  • nonstationarity process impacts
  • integrated process modeling

Published Papers (8 papers)

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Research

Article
Method for Environmental Flows Regulation and Early Warning with Remote Sensing and Land Cover Data
Land 2021, 10(11), 1216; https://doi.org/10.3390/land10111216 - 10 Nov 2021
Viewed by 733
Abstract
Environmental flows play a vital role in ecosystem and water resource management. The regulation and management of environmental flows can improve the function and stability of river and lake ecosystems. However, current methods for assessing environmental flows mainly emphasize water management, and there [...] Read more.
Environmental flows play a vital role in ecosystem and water resource management. The regulation and management of environmental flows can improve the function and stability of river and lake ecosystems. However, current methods for assessing environmental flows mainly emphasize water management, and there is no complete set of regulations or early warning systems, especially in arid and semiarid basins. In this study, we proposed a method for environmental flows regulation and early warning with remote sensing and land cover data and carried out a case study in the Yongding River Basin, which is a basin typical of arid and semiarid areas. The results show that from 2001 to 2014 the mean precipitation was 17.90 × 109 m3, and the mean water consumption was 19.42 × 109 m3, indicating that the basin water budget was clearly unbalanced and that there was an overall deficiency. Notably, from 2005 to 2014 and in 2014, the available consumable water was less than the water consumption required for human activities, which both showed a trend of further reduction; therefore, long-term and annual early warnings should have been issued. The methods applied in this study and the study outcomes could help in the development of comprehensive management and ecological restoration plans, further improving the ecological environments of river basins. Full article
(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)
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Article
Modelling the Event-Based Hydrological Response of Mediterranean Forests to Prescribed Fire and Soil Mulching with Fern Using the Curve Number, Horton and USLE-Family (Universal Soil Loss Equation) Models
Land 2021, 10(11), 1166; https://doi.org/10.3390/land10111166 - 31 Oct 2021
Viewed by 986
Abstract
The SCS-CN, Horton, and USLE-family models are widely used to predict and control runoff and erosion in forest ecosystems. However, in the literature there is no evidence of their use in Mediterranean forests subjected to prescribed fire and soil mulching. To fill this [...] Read more.
The SCS-CN, Horton, and USLE-family models are widely used to predict and control runoff and erosion in forest ecosystems. However, in the literature there is no evidence of their use in Mediterranean forests subjected to prescribed fire and soil mulching. To fill this gap, this study evaluates the prediction capability for runoff and soil loss of the SCS-CN, Horton, MUSLE, and USLE-M models in three forests (pine, chestnut, and oak) in Southern Italy. The investigation was carried out at plot and event scales throughout one year, after a prescribed fire and post-fire soil mulching with fern. The SCS-CN and USLE-M models were accurate in predicting runoff volume and soil loss, respectively. In contrast, poor predictions of the modelled hydrological variables were provided by the models in unburned plots, and by the Horton and MUSLE models for all soil conditions. This inaccuracy may have been due to the fact that the runoff and erosion generation mechanisms were saturation-excess and rainsplash, while the Horton and MUSLE models better simulate infiltration-excess and overland flow processes, respectively. For the SCS-CN and USLE-M models, calibration was needed to obtain accurate predictions of surface runoff and soil loss; furthermore, different CNs and C factors must be input throughout the year to simulate the variability of the hydrological response of soil after fire. After calibration, two sets of CNs and C-factor values were suggested for applications of the SCS-CN and USLE-M models, after prescribed fire and fern mulching in Mediterranean forests. Once validated in a wider range of environmental contexts, these models may support land managers in controlling the hydrology of Mediterranean forests that are prone to wildfire risks. Full article
(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)
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Article
Watershed Response to Legacy Phosphorus and Best Management Practices in an Impacted Agricultural Watershed in Florida, U.S.A.
Land 2021, 10(9), 977; https://doi.org/10.3390/land10090977 - 16 Sep 2021
Cited by 1 | Viewed by 1928
Abstract
Soil phosphorus (P) built up due to past management practices, legacy P, in the Lake Okeechobee Watershed (LOW) in south-central Florida, U.S.A., is often discussed as the root cause of lake eutrophication. Improvement of the lake’s water quality requires the identification of critical [...] Read more.
Soil phosphorus (P) built up due to past management practices, legacy P, in the Lake Okeechobee Watershed (LOW) in south-central Florida, U.S.A., is often discussed as the root cause of lake eutrophication. Improvement of the lake’s water quality requires the identification of critical P sources and quantifying their contributions. We performed a global sensitivity analysis of the Watershed Assessment Model (WAM), a common evaluation tool in LOW environmental planning, using the Morris method. A pre-calibrated WAM setup (Baseline) of the LOW sub-watershed, Taylor Creek Nubbin Slough (TCNS), was used as a test case. Eight scenarios were formulated to estimate the contributions of various P sources. The Morris analysis indicated that total phosphorus (TP) loads were highly sensitive to legacy P in improved pastures, the major land use covering 46.2% of TCNS. The scenario modeling revealed that legacy P, inorganic fertilizers, and other sources contribute 63%, 10%, and 32%, respectively, to the Baseline TP load of 111.3 metric tons/y to the lake. Improved pastures, dairies, citrus, and field crops are the top TP load contributors. Our results have important implications for water quality improvement plans in the LOW and highlighted the need for accurate spatial mapping of legacy P and incorporation of such information in modeling efforts for watersheds demonstrating legacy P problems. Full article
(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)
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Article
Forecasts of Opportunity for Northern California Soil Moisture
Land 2021, 10(7), 713; https://doi.org/10.3390/land10070713 - 06 Jul 2021
Viewed by 1176
Abstract
Soil moisture anomalies underpin a number of critical hydrological phenomena with socioeconomic consequences, yet systematic studies of soil moisture predictability are limited. Here, we use a data-adaptive technique, Linear Inverse Modeling, which has proved useful as an indication of predictability in other fields, [...] Read more.
Soil moisture anomalies underpin a number of critical hydrological phenomena with socioeconomic consequences, yet systematic studies of soil moisture predictability are limited. Here, we use a data-adaptive technique, Linear Inverse Modeling, which has proved useful as an indication of predictability in other fields, to investigate the predictability of soil moisture in northern California. This approach yields a model of soil moisture at 10 stations in the region, with results that indicate the possibility of skillful forecasts at each for lead times of 1–2 weeks. An important advantage of this model is the a priori identification of forecasts of opportunity—conditions under which the model’s forecasts may be expected to have particularly high skill. Given that forecast errors (and inversely, their skill) can be estimated in advance, these findings have the potential to greatly increase the utility of soil moisture forecasts for practical applications including drought and flood forecasting. Full article
(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)
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Article
Quantifying the Relative Contribution of Climate Change and Anthropogenic Activities on Runoff Variations in the Central Part of Tajikistan in Central Asia
Land 2021, 10(5), 525; https://doi.org/10.3390/land10050525 - 14 May 2021
Cited by 4 | Viewed by 1498
Abstract
Quantifying the relative contribution of climate change and anthropogenic activities to runoff alterations are essential for the sustainable management of water resources in Central Asian countries. In the Kofarnihon River Basin (KRB) in Central Asia, both changing climate conditions and anthropogenic activities are [...] Read more.
Quantifying the relative contribution of climate change and anthropogenic activities to runoff alterations are essential for the sustainable management of water resources in Central Asian countries. In the Kofarnihon River Basin (KRB) in Central Asia, both changing climate conditions and anthropogenic activities are known to have caused changes to the hydrological cycle. Therefore, quantifying the net influence of anthropogenic contribution to the runoff changes is a challenge. This study applied the original and modified Mann–Kendall trend test, including the Sen’s slope test, Pettitt’s test, double cumulative curve, and elasticity methods. These methods were applied to determine the historical trends, magnitude changes and change points of the temperature, precipitation, potential evapotranspiration, and runoff from 1950 to 2016. In addition, the contributions of climate change and anthropogenic activities to runoff changes in the KRB were evaluated. The trend analysis showed a significant increasing trend in annual temperature and potential evapotranspiration, while the annual precipitation trend showed an insignificant decreasing trend during the 1950–2016 time period. The change point in runoff occurred in 1986 in the upstream region and 1991 in the downstream region. Further, the time series (1950–2016) is separated into the prior impacted period (1950–1986 and 1950–1991) and post impacted period (1987–2016 and 1992–2016) for the upstream and downstream regions, respectively. During the post impacted period, climate change and anthropogenic activities contributed to 87.96% and 12.04% in the upstream region and 7.53% and 92.47% in the downstream region of the KRB. The results showed that in runoff changes, the anthropogenic activities played a dominant role in the downstream (97.78%) and the climate change impacts played a dominant factor in the upstream region (87.96%). In the land-use type changes, the dominant role was played by construction land, which showed that the area from 248.63 km2 in 1990 increased to 685.45 km2 (175.69%) in 2015. These findings suggest that it is essential to adopt effective steps for the sustainable development of the ecological, hydrological, and social order in the KRB in Central Asia. Full article
(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)
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Article
Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT
Land 2021, 10(4), 421; https://doi.org/10.3390/land10040421 - 15 Apr 2021
Cited by 15 | Viewed by 2073
Abstract
The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the [...] Read more.
The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December. Full article
(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)
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Article
Optical Spectral Tools for Diagnosing Water Media Quality: A Case Study on the Angara/Yenisey River System in the Siberian Region
Land 2021, 10(4), 342; https://doi.org/10.3390/land10040342 - 27 Mar 2021
Cited by 8 | Viewed by 1647
Abstract
This paper presents the results of spectral optical measurements of hydrochemical characteristics in the Angara/Yenisei river system (AYRS) extending from Lake Baikal to the estuary of the Yenisei River. For the first time, such large-scale observations were made as part of a joint [...] Read more.
This paper presents the results of spectral optical measurements of hydrochemical characteristics in the Angara/Yenisei river system (AYRS) extending from Lake Baikal to the estuary of the Yenisei River. For the first time, such large-scale observations were made as part of a joint American-Russian expedition in July and August of 1995, when concentrations of radionuclides, heavy metals, and oil hydrocarbons were assessed. The results of this study were obtained as part of the Russian hydrochemical expedition in July and August, 2019. For in situ measurements and sampling at 14 sampling sites, three optical spectral instruments and appropriate software were used, including big data processing algorithms and an AYRS simulation model. The results show that the water quality in AYRS has improved slightly due to the reasonably reduced anthropogenic industrial impact. Chemical concentrations in water have been found to vary along the Angara River depending on the location of the dams. The results of in situ measurements and modeling evaluations are given. To overcome the uncertainties in the data caused by the large monitoring area, it is recommended to use the combined AYRS simulation model and the universal 8-channel spectrophotometer installed on a fixed platform for continuous monitoring. Full article
(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)
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Article
Development of Flood Damage Regression Models by Rainfall Identification Reflecting Landscape Features in Gangwon Province, the Republic of Korea
Land 2021, 10(2), 123; https://doi.org/10.3390/land10020123 - 27 Jan 2021
Cited by 2 | Viewed by 1401
Abstract
Torrential rainfall events associated with rainstorms and typhoons are the main causes of flood-related economic losses in Gangwon Province, Republic of Korea. The frequency and severity of flood damage have been increasing due to frequent extreme rainfall events as a result of climate [...] Read more.
Torrential rainfall events associated with rainstorms and typhoons are the main causes of flood-related economic losses in Gangwon Province, Republic of Korea. The frequency and severity of flood damage have been increasing due to frequent extreme rainfall events as a result of climate change. Rainfall is a major cause of flood damage for the study site, given a strong relationship between the probability of flood damage over the last two decades and the maximum rainfall for 6 and 24 h durations in the 18 administrative districts of Gangwon Province. This study aims to develop flood damage regression models by rainfall identification for use in a simplified and efficient assessment of flood damage risk in ungauged or poorly gauged regions. Optimal simple regression models were selected from four types of non-linear functions with one of five composite predictors averaged for the two rainfall datasets. To identify appropriate predictor rainfall variables indicative of regional landscape features, the relationships between the composite rainfall predictor and landscape characteristics such as district size, topographic features, and urbanization rate were interpreted. The proposed optimal regression models may provide governments and policymakers with an efficient flood damage risk map simply using a regression outcome to design or forecast rainfall data. Full article
(This article belongs to the Special Issue Advances in Hydrologic and Water Quality Modeling of Water Systems)
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