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The Impact of Extreme Weather on Land Degradation and Conservation

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A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land–Climate Interactions".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 13350

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Special Issue Editors

Dr. Vesna Zupanc

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Guest Editor

Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia
Interests: agricultural soil; agrohydrology; soil conservation; groundwater pollution; irrigation management
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Dr. Nejc Bezak

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Guest Editor

Faculty of Civil and Geodetic Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia
Interests: hydrology; sediment transport; soil erosion; rainfall; runoff; modelling; engineering applications; floods
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Dr. Carla Sofia Santos Ferreira

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Polytechnic Institute of Coimbra, Applied Research Institute, Rua da Misericórdia, Lagar dos Cortiços—S. Martinho do Bispo, 3045-093 Coimbra, Portugal
Interests: anthropogenic impacts on land degradation; water resource management; nature-based solutions; sustainable urban planning
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Special Issue Information

Dear Colleagues,

Land degradation, particularly soil erosion, is a major environmental problem involving the degradation of topsoil and a reduced ability of soil to provide ecosystem services. Several forms of land degradation have been recorded worldwide, from mountainous regions to floodplains. In recent years, floods and droughts have become major drivers of this phenomenon due to their increasing frequency, highly erosive runoff and the changing nature of sediments, which now are now contaminated by an abundance of pollutants (e.g., metals, plastics, organic compounds) from upstream watersheds. Studies on land degradation processes are critical for evaluating the success of prevention efforts and subsequent planning of control and prevention measures to ensure land degradation neutrality targets. This Special Issue will present priority actions and issues for sustainable land management and soil erosion control strategies.

This Special Issue is aimed at gathering contributions in the form of case studies and review studies on methods and modelling applications for land degradation reduction and soil conservation in the context of extreme weather events, such as floods and droughts.

Topics of interest include:

Soil conservation in agriculture;
Integrating soil erosion prevention and flood mitigation measures into system-based solutions;
Scaling soil erosion prevention and flood mitigation measures;
Societal approaches to land erosion prevention measures, practices of landowners, farmers and indigenous people;
Land degradation under climate change and adaptation measures;
Coupled nature-based solutions to protect against soil erosion and measures to mitigate flooding.

Dr. Vesna Zupanc
Dr. Nejc Bezak
Dr. Carla Sofia Santos Ferreira
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 2600 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

soil degradation
soil conservation
agricultural land
climate change
weather extremes
land degradation

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Published Papers (8 papers)

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Research

16 pages, 7250 KiB

Open AccessArticle

Spatial-Temporal Assessment of Dust Events and Trend Analysis of Sand Drift Potential in Northeastern Iran, Gonabad

by Mohammad Reza Rahdari, Rasoul Kharazmi, Jesús Rodrigo-Comino and Andrés Rodríguez-Seijo

Land 2024, 13(11), 1906; https://doi.org/10.3390/land13111906 - 14 Nov 2024

Cited by 2 | Viewed by 997

Abstract

In recent years, northeastern Iran, particularly Khorasan Razavi province, has experienced wind erosion and dust storms, although large-scale studies are limited. To assess wind patterns, sand drift, and dust events, hourly wind data were analyzed using Fryberger’s method, along with trend analysis through the Mann–Kendall and Sen’s slope tests. Additionally, MODIS satellite data and Google Earth Engine helped identify event frequency and spatial patterns. The results show that east (12%) and southeast winds (9.6%) are the most frequent, with an average annual wind speed of 4.39 knots. Sand drift potential (DP = 96, RDP = 21.6) indicates sand movement from southeast to northwest, with a multi-directional wind system (unidirectional index of 0.22). The results of the AOD index show that the amount of dust in the north and northwest part is more than other locations, and more than 500 events with dust has been registered over the last two decades. These findings suggest that policymakers should monitor these trends to mitigate the environmental and infrastructural damage caused by blowing sand. Full article

(This article belongs to the Special Issue The Impact of Extreme Weather on Land Degradation and Conservation)

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24 pages, 1596 KiB

Open AccessArticle

Integrated Assessment of Metal Contamination of Soils, Sediments, and Runoff Water in a Dry Riverbed from a Mining Area Under Torrential Rain Events

by José Cuevas, Ángel Faz, Silvia Martínez-Martínez, Juan Beltrá and José A. Acosta

Land 2024, 13(11), 1892; https://doi.org/10.3390/land13111892 - 12 Nov 2024

Cited by 1 | Viewed by 657

Abstract

Dry riverbeds can transport mining waste during torrential rain events, disseminating pollutants from mining areas to natural ecosystems. This study evaluates the impact of these mine wastes on soils, sediments, and runoff/pore water in the La Carrasquilla dry riverbed (southeastern Spain). An integrated approach utilizing geochemical and mineralogical techniques was employed, analyzing water, soil, and sediment samples from both the headwater and mouth of the riverbed. Soil profiles and pore water were collected at 30 cm, 60 cm, and 90 cm deep, alongside sediment and runoff water samples. The assessment of metal(loid) contamination focused on arsenic, cadmium, chromium, copper, iron, nickel, manganese, zinc, and lead, utilizing sequential extraction to evaluate metal partitioning across soil phases. Various pollution indices, including the contamination factor (Cf), pollution load index (PLI), potential ecological risk index (RI), and metal(loid) evaluation index (MEI), were employed to classify contamination levels. The highest level of contamination was reported in the headwater, which suggested anthropogenic activities linked to the presence of mining residues as the major source of metal(loid)s. However, an active deposition of As, Cd, Cu, Fe, Mn, and Zn was reported in the topsoil at the mouth. In the headwater, a quartz and muscovite-rich zone exhibited the highest Cf for Pb (1022), primarily bound to the soil residual fraction (62.8%). At the headwater and mouth, pore water showed higher concentrations of sulfate, Ca, Na, Cl, Mg, and Mn and higher salinity than acceptable limits for drinking water or irrigation established by the World Health Organization. Runoff-water metal concentrations surpassed established guidelines, with MEI values indicating significant contamination by cadmium (36.1) and manganese (19.0). These findings highlight the considerable ecological risk of Pb and underscore the need for targeted remediation strategies to mitigate environmental impacts in the Mar Menor coastal lagoon. Full article

(This article belongs to the Special Issue The Impact of Extreme Weather on Land Degradation and Conservation)

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16 pages, 8350 KiB

Open AccessArticle

Soil Organic Carbon May Decline Under Climate Change: A Case Study in Mexican Forests

by Leticia Citlaly López-Teloxa and Alejandro Ismael Monterroso-Rivas

Land 2024, 13(10), 1711; https://doi.org/10.3390/land13101711 - 18 Oct 2024

Viewed by 1090

Abstract

Soil organic carbon is essential for ecosystem health, influencing water retention, soil fertility and biodiversity. However, climate change and deforestation are reducing SOC globally. This study models and projects changes in the SOC of Mexican forest soils under different climate scenarios. Over 100 models were developed relating SOC to the Lang index (precipitation and temperature), altitude, slope, bulk density, texture and soil depth. The results indicate that SOC can be effectively modelled to assess scenarios for decision making. The highest SOC levels were found in tropical rainforests and mesophyll forests and the lowest in broadleaved forests of the Sonoran plain. Climate change is projected to reduce SOC in forest ecosystems by up to 11%, especially in temperate forests. Conversely, mesophyll forests are expected to experience a slight increase in SOC of 3% due to rising temperatures and changing precipitation patterns. This decline could lead to increased HGH and reduced carbon storage capacity. This study highlights the need for sustainable management practices and multidisciplinary research to mitigate these impacts and emphasises the importance of comprehensive strategies for long-term environmental sustainability. Full article

(This article belongs to the Special Issue The Impact of Extreme Weather on Land Degradation and Conservation)

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21 pages, 3827 KiB

Open AccessArticle

Machine Learning Models for the Spatial Prediction of Gully Erosion Susceptibility in the Piraí Drainage Basin, Paraíba Do Sul Middle Valley, Southeast Brazil

by Jorge da Paixão Marques Filho, Antônio José Teixeira Guerra, Carla Bernadete Madureira Cruz, Maria do Carmo Oliveira Jorge and Colin A. Booth

Land 2024, 13(10), 1665; https://doi.org/10.3390/land13101665 - 13 Oct 2024

Viewed by 1036

Abstract

Soil erosion is a global issue—with gully erosion recognized as one of the most important forms of land degradation. The purpose of this study is to compare and contrast the outcomes of four machine learning models, Classification and Regression (CART), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Machine (SVM), used for mapping susceptibility to soil gully erosion. The controlling factors of gully erosion in the Piraí Drainage Basin, Paraíba do Sul Middle Valley were analysed by image interpretation in Google Earth and gully erosion samples (n = 159) were used for modelling and spatial prediction. The XGBoost and RF models achieved identical results for the area under the receiver operating characteristic curve (AUROC = 88.50%), followed by the SVM and CART models, respectively (AUROC = 86.17%; AUROC = 85.11%). In all models analysed, the importance of the main controlling factors predominated among Lineaments, Land Use and Cover, Slope, Elevation and Rainfall, highlighting the need to understand the landscape. The XGBoost model, considering a smaller number of false negatives in spatial prediction, was considered the most appropriate, compared to the Random Forest model. It is noteworthy that the XGBoost model made it possible to validate the hypothesis of the study area, for susceptibility to gully erosion and identifying that 9.47% of the Piraí Drainage Basin is susceptible to gully erosion. Furthermore, replicable methodologies are evidenced by their rapid applicability at different scales. Full article

(This article belongs to the Special Issue The Impact of Extreme Weather on Land Degradation and Conservation)

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18 pages, 12011 KiB

Open AccessFeature PaperArticle

Windthrow Impact on Alpine Forest Humipedon: Soil Microarthropod Communities and Humus Dynamics Five Years after an Extreme Windstorm Event

by Francesca Visentin, Sara Remelli, Augusto Zanella and Cristina Menta

Land 2024, 13(9), 1458; https://doi.org/10.3390/land13091458 - 7 Sep 2024

Cited by 1 | Viewed by 1030

Abstract

The ecological impact of windthrow disturbance on humipedons and soil microarthropod communities is examined in two areas of the Italian Alps (Val di Fassa and Cansiglio) five years after the Vaia Storm. The following soil coverage conditions were identified: herbaceous vegetation (G), decaying wood (W), no vegetation (B) in windthrow areas; and these were compared with conditions in adjacent undisturbed intact forests (IF) and, only in Val di Fassa, with permanent meadows (M). Soil pH, soil organic matter content (SOM), humus systems and microarthropod communities were analyzed. In Val di Fassa, SOM loss was observed in windthrow areas vs. IF, moving toward a Mull humus system, while G evolved toward M-like conditions, W maintained a thicker O horizon and lower pH and B exhibited severe soil erosion and the lowest SOM. In Cansiglio, windthrow areas showed a slower transition to a Mull system, with a trend toward increasing pH and decreasing SOM. A clear relationship between microarthropod communities and humus systems could not be established because the consistency and biological origins of the humus diagnostic horizons were not considered. Microarthropod communities under different conditions exhibited significant dissimilarity, with varying responses across groups; Shannon and QBS-ar indices remained stable except for a significant decrease in B. Community dissimilarity thus appears to be enhanced by post-windthrow disturbance, suggesting that destructive windstorms may also present an opportunity for enriched microarthropod diversity. Full article

(This article belongs to the Special Issue The Impact of Extreme Weather on Land Degradation and Conservation)

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28 pages, 27613 KiB

Open AccessArticle

Influence of Cumulative Geotechnical Deterioration on Mass Movement at a Medium-Scale Regional Analysis (Cortinas Sector, Toledo, Colombia)

by Carlos Andrés Buenahora Ballesteros, Antonio Miguel Martínez-Graña and Mariano Yenes

Land 2024, 13(7), 1000; https://doi.org/10.3390/land13071000 - 6 Jul 2024

Cited by 2 | Viewed by 812

Abstract

Landslides in Colombia represent a serious threat to the safety of local communities and the surrounding infrastructure, especially in the mountain range zone. These events occur due to the variation and correlation of endogenous conditions existing in each area, such as geology, geomorphology and coverage, which are triggered by rainfall, seismic events or anthropic activities. This article aims to analyze the geoenvironmental conditions between 2016 and 2021 in the sector known as Cortinas (Toledo, Colombia), applying, for this purpose, the innovative concept of “accumulated geotechnical deterioration” in order to explain the evolution of susceptibility over time from the perspective of prediction, which under traditional methodologies is not properly considered, since unlike what has been thought, the conditioning factors do change in the short and medium term, especially in tropical areas. As a result of this part of the research, the hypothesis was validated that it is necessary for the terrain to be under certain specific conditions for an instability event to occur, which does not depend only on certain critical thresholds of rainfall and earthquakes. Full article

(This article belongs to the Special Issue The Impact of Extreme Weather on Land Degradation and Conservation)

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19 pages, 4265 KiB

Open AccessArticle

Spatial Prediction and Mapping of Gully Erosion Susceptibility Using Machine Learning Techniques in a Degraded Semi-Arid Region of Kenya

by Kennedy Were, Syphyline Kebeney, Harrison Churu, James Mumo Mutio, Ruth Njoroge, Denis Mugaa, Boniface Alkamoi, Wilson Ng’etich and Bal Ram Singh

Land 2023, 12(4), 890; https://doi.org/10.3390/land12040890 - 15 Apr 2023

Cited by 6 | Viewed by 2617

Abstract

This study aimed at (i) developing, evaluating and comparing the performance of support vector machines (SVM), boosted regression trees (BRT), random forest (RF) and logistic regression (LR) models in mapping gully erosion susceptibility, and (ii) determining the important gully erosion conditioning factors (GECFs) in a Kenyan semi-arid landscape. A total of 431 geo-referenced gully erosion points were gathered through a field survey and visual interpretation of high-resolution satellite imagery on Google Earth, while 24 raster-based GECFs were retrieved from the existing geodatabases for spatial modeling and prediction. The resultant models exhibited excellent performance, although the machine learners outperformed the benchmark LR technique. Specifically, the RF and BRT models returned the highest area under the receiver operating characteristic curve (AUC = 0.89 each) and overall accuracy (OA = 80.2%; 79.7%, respectively), followed by the SVM and LR models (AUC = 0.86; 0.85 & OA = 79.1%; 79.6%, respectively). In addition, the importance of the GECFs varied among the models. The best-performing RF model ranked the distance to a stream, drainage density and valley depth as the three most important GECFs in the region. The output gully erosion susceptibility maps can support the efficient allocation of resources for sustainable land management in the area. Full article

(This article belongs to the Special Issue The Impact of Extreme Weather on Land Degradation and Conservation)

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26 pages, 37954 KiB

Open AccessArticle

Shifting Sands: Assessing Bankline Shift Using an Automated Approach in the Jia Bharali River, India

by Jatan Debnath, Dhrubajyoti Sahariah, Anup Saikia, Gowhar Meraj, Nityaranjan Nath, Durlov Lahon, Wajahat Annayat, Pankaj Kumar, Kesar Chand, Suraj Kumar Singh and Shruti Kanga

Land 2023, 12(3), 703; https://doi.org/10.3390/land12030703 - 17 Mar 2023

Cited by 31 | Viewed by 3324

Abstract

Bank erosion hazard is a frequent occurrence that poses threats to floodplain ecosystems. This analysis examined changes to the Jia Bharali River channel in India using the GIS-based Digital Shoreline Analysis System [DSAS]. The Jia Bharali’s future channel was predicted so as to identify the most erosion-susceptible zones. The rate of bankline movement was calculated using remotely sensed data collected over a period of 45 years (1976–2021). The results show that the river’s erosion and deposition rates were higher in the early years than towards the later part of the period under analysis. On the right and left banks of the river, the average shift rate was −9.22 and 5.8 m/y, respectively, which is comparatively high. The chosen portion of the river was evenly divided into three zones, A, B, and C. The most positively affected zone was zone A. The left bank of zone B exhibited a higher rate of erosion than the right bank, indicating that the river was moving to the left [eastward] in this zone. At the same time, the right bank was being eroded faster than the left, indicating a westward thrust at zone C. The predicted result demonstrates that the left bank of zone B and the right bank of zone C would have a higher average migration rate. Therefore, these banks were identified as being the most susceptible to bank erosion. The study evaluates the spatio-temporal change of the river in sensitive regions where neighboring settlements and infrastructure were at risk of changing channel dynamics. Using the actual and forecasted bankline, the degree of accuracy was confirmed. The results of the automated prediction approach could be useful for river hazard management in the Jia Bharali and in similar environmental settings with tropical high precipitation zones. Full article

(This article belongs to the Special Issue The Impact of Extreme Weather on Land Degradation and Conservation)

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