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Coupling Eco-Hydrology with Water Sustainability: Concepts and Applications

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".

Deadline for manuscript submissions: closed (20 September 2022) | Viewed by 18484

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Special Issue Editors

Prof. Dr. Fadong Li

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Guest Editor

Key Laboratory of Ecosytem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: agro-ecosystem processes; eco-hydrology and water environment; isotopic hydrology; surface-ground water interaction

Prof. Dr. Gang Chen

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Guest Editor

FAMU-FSU College of Engineering, Florida State University, Tallahassee, FL 32310, USA
Interests: land use; nutrient management; watershed modeling

Prof. Dr. Xinlin He

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Guest Editor

College of Water and Architectural Engineering, Shihezi University, Shihezi 832000, China
Interests: hydrology and water resources; water-saving irrigation technology; ecological hydrology

Prof. Dr. Guang Yang

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Guest Editor

1. College of Water and Architectural Engineering, Shihezi University, Shihezi 832000, China
2. Key Laboratory of Cold and Arid Regions Eco-Hydraulic Engineering of Xinjiang Production & Construction Corps, Shihezi 832000, China
Interests: ecological hydrology in arid areas; efficient utilization of water resources in arid areas; ecological hydrological models; unconventional water resource utilization in arid areas; hydrological cycle in inland river basins in arid areas
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Special Issue Information

Dear Colleagues,

This Special Issue was inspired by the increasing frequency and intensity of major hydrological extremes and the resulting water environment changes across our planet. Terrestrial and aquatic ecosystems are under increasing stress in the background of global change and ever-growing anthropogenic impacts in many regions, such as the drylands in Africa, Central Asia, Northwest China, and the U.S. It is anticipated that this will only be exacerbated in the future. Among hydrological extremes, droughts potentially challenge ecosystem resilience through propagating down the atmosphere–hydrosphere–land surface–biosphere cascade. The alteration of eco-hydrology processes leads to a changed water cycle and solute transportation within the natural and artificial ecosystems, leading to a reallocation of water resources, threatening sustainability. The water cycle is governed by complex and dynamic interactions and feedbacks between climate, soil, and vegetation. These interactions regulate the patterns of water utilization strategies across the biosphere–atmosphere interface at a wide range of scales. Therefore, we need to understand ecohydrological interactions during drought and the resistance and resilience of ecosystems to multiple, dynamic stressors, which would allow us to develop appropriate management interventions and adaptation strategies. In establishing the bridge between eco-hydrology and water sustainability, the discipline seeks to link different aspects of the environmental and ecological sciences, dealing with surface hydrology, soil hydrology, hydraulics, hydrogeology, geophysics, and ecology.

The Special Issue, “Coupling Eco-Hydrology with Water Sustainability: Concepts and Applications”, stems from the need to stimulate and collect the most recent results in this field with a specific focus on bringing together modelling applications and experimental experiences. The emphasis has necessarily been on marshalling the information that can be summarized in the following topics: soil moisture dynamics, soil–plant interaction, vegetation modelling, and the effects of climate change on ecosystems. Understanding the basic processes of ecohydrology will hopefully lead to the development of tools for a more sustainable use of water resources and the management of natural and artificial ecosystems.

Prof. Dr. Fadong Li
Prof. Dr. Gang Chen
Prof. Dr. Xinlin He
Prof. Dr. Guang Yang
Guest Editors

Manuscript Submission Information

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Keywords

eco-hydrological processes in dryland
ecosystem sensitivity to drought
hydrological extremes
salinization variability and global change
resilience and adaptation strategies
relationship between eco-hydrology and water environment
sustainable water use and SDGs
anthropogenic impacts on the hydrology and ecology of arid areas
agriculture and water use sustainability

Published Papers (6 papers)

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Research

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30 pages, 9104 KiB

Open AccessArticle

Distributed Hydrological Model Based on Machine Learning Algorithm: Assessment of Climate Change Impact on Floods

by Zafar Iqbal, Shamsuddin Shahid, Tarmizi Ismail, Zulfaqar Sa’adi, Aitazaz Farooque and Zaher Mundher Yaseen

Sustainability 2022, 14(11), 6620; https://0-doi-org.brum.beds.ac.uk/10.3390/su14116620 - 28 May 2022

Cited by 6 | Viewed by 2446

Abstract

Rapid population growth, economic development, land-use modifications, and climate change are the major driving forces of growing hydrological disasters like floods and water stress. Reliable flood modelling is challenging due to the spatiotemporal changes in precipitation intensity, duration and frequency, heterogeneity in temperature rise and land-use changes. Reliable high-resolution precipitation data and distributed hydrological model can solve the problem. This study aims to develop a distributed hydrological model using Machine Learning (ML) algorithms to simulate streamflow extremes from satellite-based high-resolution climate data. Four widely used bias correction methods were compared to select the best method for downscaling coupled model intercomparison project (CMIP6) global climate model (GCMs) simulations. A novel ML-based distributed hydrological model was developed for modelling runoff from the corrected satellite rainfall data. Finally, the model was used to project future changes in runoff and streamflow extremes from the downscaled GCM projected climate. The Johor River Basin (JRB) in Malaysia was considered as the case study area. The distributed hydrological model developed using ML showed Nash–Sutcliffe efficiency (NSE) values of 0.96 and 0.78 and Root Mean Square Error (RMSE) of 4.01 and 5.64 during calibration and validation. The simulated flow analysis using the model showed that the river discharge would increase in the near future (2020–2059) and the far future (2060–2099) for different Shared Socioeconomic Pathways (SSPs). The largest change in river discharge would be for SSP-585. The extreme rainfall indices, such as Total Rainfall above 95th Percentile (R95TOT), Total Rainfall above 99th Percentile (R99TOT), One day Max Rainfall (R × 1day), Five-day Max Rainfall (R × 5day), and Rainfall Intensity (RI), were projected to increase from 5% for SSP-119 to 37% for SSP-585 in the future compared to the base period. The results showed that climate change and socio-economic development would cause an increase in the frequency of streamflow extremes, causing larger flood events. Full article

(This article belongs to the Special Issue Coupling Eco-Hydrology with Water Sustainability: Concepts and Applications)

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22 pages, 8586 KiB

Open AccessArticle

A Three-Dimensional Coupled Hydrodynamic-Ecological Modeling to Assess the Planktonic Biomass in a Subalpine Lake

by Wen-Cheng Liu, Hong-Ming Liu and Rita Sau-Wai Yam

Sustainability 2021, 13(22), 12377; https://0-doi-org.brum.beds.ac.uk/10.3390/su132212377 - 09 Nov 2021

Cited by 4 | Viewed by 1585

Abstract

In this study, a coupled three-dimensional hydrodynamic-ecological model was developed to comprehensively understand the interaction between the hydrodynamics and ecological status of a lake. The coupled model was utilized to explore the hydrodynamics, water quality, and ecological status in an ecologically rich subalpine lake (i.e., Tsuei-Feng Lake (TFL), located in north-central Taiwan). The measured data of water depth, water temperature, water quality, and planktonic biomass were gathered to validate the coupled model. The simulated results with a three-dimensional hydrodynamic and water quality-ecological model reasonably reproduced the variations in observed water depth, water temperature, water quality, and phytoplankton and zooplankton biomass. Sensitivity analysis was implemented to determine the most influential parameter affecting the planktonic biomass. The results of sensitivity analysis indicated that the predation rate on phytoplankton (PRP) significantly affects the phytoplankton biomass, while the basal metabolism rate of zooplankton (BMZ) importantly affects the zooplankton biomass. Furthermore, inflow discharge was the most important environmental factor dominating the phytoplankton and zooplankton biomass of TFL. This implies that the runoff in the catchment area caused by rainfall and the heavy rainfall induced by climate change may affect the planktonic biomass of the lake. Full article

(This article belongs to the Special Issue Coupling Eco-Hydrology with Water Sustainability: Concepts and Applications)

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19 pages, 6328 KiB

Open AccessFeature PaperArticle

A Simple Way to Increase the Prediction Accuracy of Hydrological Processes Using an Artificial Intelligence Model

by Ieva Meidute-Kavaliauskiene, Milad Alizadeh Jabehdar, Vida Davidavičienė, Mohammad Ali Ghorbani and Saad Sh. Sammen

Sustainability 2021, 13(14), 7752; https://0-doi-org.brum.beds.ac.uk/10.3390/su13147752 - 12 Jul 2021

Cited by 1 | Viewed by 1673

Abstract

Rainfall and evaporation, which are known as two complex and unclear processes in hydrology, are among the key processes in the design and management of water resource projects. The application of artificial intelligence, in comparison with physical and empirical models, can be effective in the face of the complexity of hydrological processes. The present study was prepared with the aim of increasing the accuracy in monthly prediction of rainfall (R) and pan evaporation (EP) by providing a simple solution to determining new inputs for forecasting scenarios. Initially, the prediction of two parameters, R and EP, for the current and one–three lead times, by determining the different input modes, was developed with the SVM model. Then, in order to increase the accuracy of the predictions, the month number (τ) was added to all scenarios in predicting both the R and EP parameters. The results of the intelligent model using several statistical indices (i.e., root mean square error (RMSE), Kling–Gupta (KGE) and correlation coefficient (CC)), with the help of case visual indicators, were compared. The month number (τ) was able to greatly improve the prediction accuracy of both the R and EP parameters under the SVM model and overcome the complexities within these two hydrological processes that the scenarios were not initially able to solve with high accuracy. This is proven in all time steps. According to the RMSE, KGE and CC indices, the highest increase in the forecast accuracy for the upcoming two months of rainfall (R_t+2) for Ardabil station in scenario 2 (SVM-2) was 19.1, 858 and 125%, and for the current month of pan evaporation (EP_t) for Urmia station in scenario 6 (SVM-6), this occurred at the rates of 40.2, 11.1 and 7.6%, respectively. Finally, in order to investigate the characteristic of the month number in the SVM model under special conditions such as considering the highest values of the R and EP time series, it was proved that by using the month number of the SVM model, again, the accuracy could be improved (on average, 17% improvement for rainfall, and 13% for pan evaporation) in almost all time steps. Due to the wide range of effects of the two variables studied in the hydrological discussion, the results of the present study can be useful in agricultural sciences and in water management in general and will help owners. Full article

(This article belongs to the Special Issue Coupling Eco-Hydrology with Water Sustainability: Concepts and Applications)

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22 pages, 8506 KiB

Open AccessArticle

Insights on Water and Climate Change in the Greater Horn of Africa: Connecting Virtual Water and Water-Energy-Food-Biodiversity-Health Nexus

by Hubert Hirwa, Qiuying Zhang, Yunfeng Qiao, Yu Peng, Peifang Leng, Chao Tian, Sayidjakhon Khasanov, Fadong Li, Alphonse Kayiranga, Fabien Muhirwa, Auguste Cesar Itangishaka, Gabriel Habiyaremye and Jean Ngamije

Sustainability 2021, 13(11), 6483; https://0-doi-org.brum.beds.ac.uk/10.3390/su13116483 - 07 Jun 2021

Cited by 21 | Viewed by 4645

Abstract

Water is the key limiting factor in socioeconomic and ecological development, but it is adversely affected by climate change. The novel virtual water (VW) concept and water, energy, food, biodiversity, and human health (WEFBH) nexus approach are powerful tools to assess the sustainability of a region through the lens of climate change. Climate change-related challenges and water are complex and intertwined. This paper analyzed the significant WEFBH sectors using the multicriteria decision-making (MCDM) and analytic hierarchy process (AHP) model. The AHP model demonstrated quantitative relationships among WEFBH nexus sustainability indicators in the Greater Horn of Africa countries. Besides, the net VW imports and water footprints of major staple crops were assessed. The composite WEFBH nexus indices varied from 0.10 to 0.14. The water footprint of crops is increasing period by period. The results also revealed that most countries in the study area are facing WEFBH domains unsustainability due to weak planning or improper management strategies. The strong policy constancy among the WEFBH sector is vital for dissociating the high-water consumption from crop production, energy, environmental, and human health system. Thus, this study enhances insights into the interdependencies, interconnectedness, and interactions of sectors thereby strengthening the coordination, complementarities, and synergies among them. To attain sustainable development, we urgently call all public and private entities to value the amount of VW used in their daily activities and design better policies on the complex WEFBH nexus and future climate change. Full article

(This article belongs to the Special Issue Coupling Eco-Hydrology with Water Sustainability: Concepts and Applications)

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18 pages, 2075 KiB

Open AccessArticle

Study on the Farmland Improvement Effect of Drainage Measures under Film Mulch with Drip Irrigation in Saline–Alkali Land in Arid Areas

by Li Zhao, Tong Heng, Lili Yang, Xuan Xu and Yue Feng

Sustainability 2021, 13(8), 4159; https://0-doi-org.brum.beds.ac.uk/10.3390/su13084159 - 08 Apr 2021

Cited by 15 | Viewed by 2147

Abstract

Water scarcity and imbalances in irrigation and drainage are the main factors leading to soil salinization in arid areas. There is a recognized need for effective drainage measures to prevent and improve saline−alkali land. The principal objective of this project was to investigate the effects of drainage measures on soil desalination and farmland drainage in the process of improving saline–alkali soils; these measures included subsurface pipe drainage (SPD) and open ditch drainage (ODD). The results of the tests, conducted over two years, revealed that the soil desalination rate in the SPD test area was between 25.8% and 35.2%, the cotton emergence rate was 36.7%, and a 3.8 t hm⁻² seed cotton yield could be obtained. The soil electrolytic conductivity (EC) decreased step by step over time, and the average annual decrease reached 10 dS m⁻¹. The degree of soil salinization was reduced from a moderately saline soil level (8−15 dS m⁻¹) to a weakly saline soil level (4–8 dS m⁻¹). Thus, the phased goal of improving saline–alkali land was achieved. The soil desalination rate in the ODD test area was only 1/10 of the SPD area; high soil EC (9−12 dS m⁻¹) and groundwater level (2–3 m) were the most limiting factors affecting cotton growth in the ODD test area. The current results show that the critical depth of groundwater level affecting farmland secondary salinization is 4 m. In order to improve the salt discharge standard, SPD technology should be used on the basis of ODD. For salt that has accumulated in the soil for a long time, the technical mode of drip irrigation and leaching, followed by SPD drainage, in combination with the current irrigation system can achieve the goal of sustainable agriculture development. Full article

(This article belongs to the Special Issue Coupling Eco-Hydrology with Water Sustainability: Concepts and Applications)

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Review

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10 pages, 1314 KiB

Open AccessReview

Dryland Food Security in Ethiopia: Current Status, Opportunities, and a Roadmap for the Future

by Yu Peng, Hubert Hirwa, Qiuying Zhang, Guoqin Wang and Fadong Li

Sustainability 2021, 13(11), 6503; https://0-doi-org.brum.beds.ac.uk/10.3390/su13116503 - 07 Jun 2021

Cited by 13 | Viewed by 4655

Abstract

Given the impact of COVID-19 and the desert locust plague, the Ethiopian food security issue has once again received widespread attention. Its food crisis requires comprehensive and systematic research to achieve the United Nations Sustainable Development Goal of zero hunger. This review discusses the current situation and the causes of food security in Ethiopia. We focus on the challenges in the food security assessment field. The article lists seven typical causes of food insecurity and three roots of food security in Ethiopia. Long-term food security assessment and a comprehensive understanding and manageability for food security causes are considered as the main existing research challenges. Climate-resilient management, water management, and long-term ecosystem network monitoring and data mining are suggested as potential roadmap for future research. Full article

(This article belongs to the Special Issue Coupling Eco-Hydrology with Water Sustainability: Concepts and Applications)

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