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Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling

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

Deadline for manuscript submissions: 20 July 2025 | Viewed by 3844

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Special Issue Editors

Prof. Dr. Carmen Maftei

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Guest Editor

Civil Engineering Faculty, Transilvania University of Brasov, Brasov, USA
Interests: hydrology; hazard and risk assessment; GIS, soil erosion, water quality

Prof. Dr. Ashok Vaseashta

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Guest Editor

Applied Research, International Clean Water Institute, Manassas, VA, USA
Interests: water; risk assessment; nanotechnology; sensors; cyber-physical systems; IoTs; AI; foresight
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Special Issue Information

Dear Colleagues,

Environmental and human threats affect both hydrological processes and ecosystems' functions and services. Their integrity degradation leads to a decrease in water resources and ecosystem services.

This Special Issue focuses on the latest research on ecohydrological processes and water balance, climate change and ecosystem responses, carbon storage and nutrient transfer, and sustainable solutions.

Research topics may include, but are not limited to, the following:

Understanding the role of hydroecological services;
Water and soil resource management;
Ecohydrology solutions;
Climate change impacts on hydrological cycle;
Effects of hydrology on soil erosion;
Ecosystem sensitivity to extreme events such as drought and flood;
Mathematical modeling aspects;
Urban ecohydrology;
Water quality assessment;
Strategies for management, monitoring and modeling.

Prof. Dr. Carmen Maftei
Prof. Dr. Ashok Vaseashta
Guest Editors

Manuscript Submission Information

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Keywords

ecohydrology
hydrological cycle
ecosystems services
drought and floods
soil erosion

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Published Papers (4 papers)

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Research

21 pages, 2330 KiB

Open AccessArticle

Hydrochemical Characterization, Source Identification, and Irrigation Water Quality Assessment in the Voghji River Catchment Area, Southern Armenia

by Gor Gevorgyan, Gor Khachatryan, Anita Varagyan, Vahagn Varagyan and Ashok Vaseashta

Water 2025, 17(6), 854; https://doi.org/10.3390/w17060854 - 17 Mar 2025

Viewed by 785

Abstract

Water quality is a fundamental parameter for assessing the suitability of surface waters. Likewise, the hydrochemical behavior is critically important to understand for rivers used in irrigation. This study aims to evaluate and characterize the surface water quality of the Voghji River catchment basin for irrigation, as it reveals the hydrochemical origins in the catchment basin. Nine key parameters, including EC, Cl⁻, SO₄²⁻, Ca²⁺, Mg²⁺, Na⁺, K⁺, CO₃²⁻, and HCO₃⁻, were measured at seven sampling points in July and September 2017. The ion concentration patterns in July followed the sequence: Ca²⁺ > Na⁺ > K⁺ > Mg²⁺ and HCO₃⁻ > SO₄²⁻ > Cl⁻ > CO₃²⁻, while in September, they were Ca²⁺ > Na⁺ > Mg²⁺ > K⁺ and HCO₃⁻ > SO₄²⁻ > Cl⁻ > CO₃²⁻. The sequences were almost similar between the two months, with minor differences in cation distribution, particularly between Mg²⁺ and K⁺. Overall, Ca²⁺ and HCO₃⁻ were the dominant ions in the studied surface water samples. The concentrations of K⁺, Na⁺, Mg²⁺, Ca²⁺, Cl⁻, SO₄²⁻, and HCO₃⁻ were found to be well below the FAO irrigation water standards, indicating that the waters of the Voghji River and its tributaries (Achanan, Vachagan, and Geghi) were generally safe for irrigation. However, the FAO threshold value was exceeded only for CO₃²⁻ in the Vachagan River in Kapan Town. The chemical analysis of surface waters in the Voghji River catchment basin revealed dominant Ca²⁺-HCO₃⁻ and mixed Ca²⁺-K⁺-SO₄²⁻-Cl⁻ facies, with key geochemical processes including carbonate and gypsum dissolution, silicate weathering, and cation exchange. Ionic correlations indicated that Na⁺ and Cl⁻ sources were influenced by both natural (e.g., halite dissolution, weathering) and anthropogenic inputs, while Ca²⁺ and Mg²⁺ primarily originated from carbonate dissolution. The Gibbs diagram suggested that rock–water interactions were the primary natural mechanism controlling the water chemistry, with evaporation also playing a significant role. Various indices, including the Kelly index, magnesium adsorption ratio, sodium percentage, sodium adsorption ratio, permeability index, potential salinity, residual sodium carbonate, soluble sodium percentage, and irrigation water quality index, were applied, along with US Salinity Laboratory diagram and Wilcox diagram, to further assess the irrigation suitability. Most indices confirmed the suitability of the waters for irrigation; however, the Achanan River near the mouth and the Voghji River downstream of Kapan Town exhibited moderate salinity levels, underscoring the need for water management to prevent potential soil degradation. Full article

(This article belongs to the Special Issue Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling)

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30 pages, 9187 KiB

Open AccessArticle

Spatiotemporal Drought Analysis Using the Composite Drought Index (CDI) over Dobrogea, Romania

by Cristina Serban and Carmen Maftei

Water 2025, 17(4), 481; https://doi.org/10.3390/w17040481 - 8 Feb 2025

Viewed by 909

Abstract

This paper discusses a study that examined the severity of droughts and their changes in the Dobrogea region in southeastern Romania between 2001 and 2021 and develops a high-resolution (1 km) Composite Drought Index (CDI) dataset. To explore the effectiveness of the index, we carried out a correlation analysis between the CDI, the Standardized Precipitation Index (SPI), and the Standardized Precipitation Evapotranspiration Index (SPEI), which shows a strong positive relationship among these indices. Analysis of the CDI time series reveals an increase in drought frequency for the study period, due to high temperature and below-normal rainfall. Most parts of the region were affected by moderate, severe, or extreme droughts, except for the years 2002–2005 and 2013. The worst drought events were in 2011, 2012, and 2020, when the region was under severe land surface temperature stress, with values up to 39.13 °C. The central and northern areas of the region had the longest period of drought, at 22 months, which started in 2018 and culminated in 2020 when extreme drought covered over 70% of the region. Another major event was in 2015 when 95% of the region experienced severe drought. These results show the potential of the CDI as one of the significant indices in the assessment of drought and provide useful insights into drought monitoring in the future. More than that, we consider that the GPM IMERG satellite product can be used in the implementation of Drought Management Plans in Dobrogea in order to calculate drought indices derived from remote sensing data. Full article

(This article belongs to the Special Issue Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling)

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18 pages, 3208 KiB

Open AccessArticle

Simulating the Vegetation Gross Primary Productivity by the Biome-BGC Model in the Yellow River Basin of China

by Lige Jia and Bo Zhang

Water 2024, 16(23), 3468; https://doi.org/10.3390/w16233468 - 2 Dec 2024

Viewed by 893

Abstract

In terrestrial ecosystems, the quantification of carbon absorption is primarily represented by the gross primary productivity (GPP), which signifies the initial substances and energy acquired by the ecosystem. The GPP also serves as the foundation for the carbon cycle within the entire terrestrial ecosystem. The Biome-BGC model is a widely used biogeochemical process model for simulating the stocks and fluxes of water, carbon, and nitrogen between ecosystems and the atmosphere. However, it is the abundance of eco-physiological parameters that lead to challenges in calibrating the model. The parameter optimization method of coupling the differential evolution algorithm (DE) with the Biome-BGC model was used to calibrate and validate the eco-physiological parameters of the seven typical vegetation types in the Yellow River Basin (YRB). And then we used the calibrated parameters to simulate the GPP by way of grid-based simulation. Finally, we conducted model adaptability testing and spatiotemporal analysis of GPP variations in the YRB. The results of the validation (R², RMSE) were: temperate grasses (0.94, 24.33 g C m⁻²), alpine meadows (0.94, 18.13 g C m⁻²), shrubs (0.94, 29.20 g C m⁻²), evergreen needle leaf forests (0.96, 27.88 g C m⁻²), deciduous broad leaf forests (0.94, 32.09 g C m⁻²), one crop a year (0.96, 16.19 g C m⁻²), and two crops a year (0.90, 38.15 g C m⁻²). After adaptability testing, the average R² value between the simulated GPP values and the GPP product values in the YRB was 0.85, and the average RMSE value was as low as 50.92 g C m⁻². Overall, the model exhibited strong simulation accuracy. Therefore, after calibrating the model with the DE algorithm, the Biome-BGC model could effectively adapt to the ecologically complex YRB. Moreover, it was able to accurately estimate the GPP, which establishes a foundation for analyzing the spatiotemporal trends of the GPP in the YRB. This study provides a reference for optimizing Biome-BGC model parameters and simulating diverse vegetation types on a large scale. Full article

(This article belongs to the Special Issue Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling)

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19 pages, 3985 KiB

Open AccessArticle

Characteristics of Stable Carbon and Nitrogen Isotopes in Different Ecological Plant Groups and Sediments Collected from 14 Softwater Lakes in Poland

by Eugeniusz Pronin, Krzysztof Banaś, Rafał Chmara, Rafał Ronowski, Marek Merdalski, Anne-Lise Santoni and Olivier Mathieu

Water 2024, 16(23), 3403; https://doi.org/10.3390/w16233403 - 26 Nov 2024

Cited by 1 | Viewed by 794

Abstract

Softwater lakes with specific, rare, and protected aquatic plant vegetation are very sensitive to increased trophic and water chemical changes, especially alkalization. These changes might be reflected in the stable carbon and nitrogen isotopes of the organic matter (OM) of those plants (δ¹³C_ORG and δ¹⁵N_ORG) and sediments (δ¹³C_ORG and δ¹⁵N_TN) which they cocreated. To recognize the relationship between OM in the aquatic plants of softwater lakes and the cocreated sediments, we analyzed the plants δ¹³C_ORG and δ¹⁵N_ORG in light of four ecological groups (as well as the sediments δ¹³C_ORG and δ¹⁵N_TN in which these plants thrived). Studies were performed in July 2020 on 14 softwater lakes in northern Poland with varying pH gradients from 4.86 to 9.20. For each lake, a single stand was examined for each species detected. The goal was to investigate each species at 10 sites, but this target was not reached for several species. Among the investigated ecological groups, isoetids and mosses showed the least variation in obtained values. In contrast, elodeids exhibited the highest variation in δ¹³C results due to their diverse carbon uptake strategies, involving both CO₂ and HCO₃⁻ forms. Moreover, the δ¹³C values of charophytes and elodeids were highly related to the increasing pH of water. The slight differences between the δ¹³C results of plants and sediments in isoetid stands further support this finding. Furthermore, we noticed an increase in sediment δ¹³C_ORG values along the alkalization gradient, suggesting that macrophytes were the primary source of OM for the sediments. The positive correlation between the δ¹³C values of plants and sediments (r = 0.69, p < 0.05) might also confirm that the macrophytes were a significant source of OM in sediments. Regarding δ¹⁵N values, we did not find significant differentiation between plants and sediments across ecological groups. However, sediment consistently exhibited ¹⁵N-enrichment compared to plant material. This enrichment is likely attributed to the accumulation of ¹⁵N during the decomposition of the deposited material. This study confirms the possibility of tracking changes in the aquatic vegetation of softwater lakes based primarily on the sediment δ¹³C_ORG values along the alkalization gradient. Full article

(This article belongs to the Special Issue Ecohydrology in the Context of Climate Change: Strategies for Management, Monitoring, and Modeling)

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