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Full professor in Physical Geography. Leader of the Soil Erosion and Degradation Research Group. National and International project leader. Soil erosion and land degradation specialist
Project Goal: Fores fire and society
Current Stage: active
COVID-19 has infected over 163 million people and has resulted in over 3.9 million deaths. Regarding the tools and strategies to research the ongoing pandemic, spatial analysis has been increasingly utilized to study the impacts of COVID-19. This article provides a review of 221 scientific articles that used spatial science to study the pandemic published from June 2020 to December 2020. The main objectives are: to identify the tools and techniques used by the authors; to review the subjects addressed and their disciplines; and to classify the studies based on their applications. This contribution will facilitate comparisons with the body of work published during the first half of 2020, revealing the evolution of the COVID-19 phenomenon through the lens of spatial analysis. Our results show that there was an increase in the use of both spatial statistical tools (e.g., geographically weighted regression, Bayesian models, spatial regression) applied to socioeconomic variables and analysis at finer spatial and temporal scales. We found an increase in remote sensing approaches, which are now widely applied in studies around the world. Lockdowns and associated changes in human mobility have been extensively examined using spatiotemporal techniques. Another dominant topic studied has been the relationship between pollution and COVID-19 dynamics, which enhance the impact of human activities on the pandemic's evolution. This represents a shift from the first half of 2020, when the research focused on climatic and weather factors. Overall, we have seen a vast increase in spatial tools and techniques to study COVID-19 transmission and the associated risk factors.
Ivan Franch‐Pardo; Michael R. Desjardins; Isabel Barea‐Navarro; Artemi Cerdà. A review of GIS methodologies to analyze the dynamics of COVID‐19 in the second half of 2020. Transactions in GIS 2021, 1 .
AMA StyleIvan Franch‐Pardo, Michael R. Desjardins, Isabel Barea‐Navarro, Artemi Cerdà. A review of GIS methodologies to analyze the dynamics of COVID‐19 in the second half of 2020. Transactions in GIS. 2021; ():1.
Chicago/Turabian StyleIvan Franch‐Pardo; Michael R. Desjardins; Isabel Barea‐Navarro; Artemi Cerdà. 2021. "A review of GIS methodologies to analyze the dynamics of COVID‐19 in the second half of 2020." Transactions in GIS , no. : 1.
Water scarcity is increasing worldwide due to population growth and climate variability/change. As a supplementary water resource, Rainwater harvesting (RWH) is a possible solution for dealing with water scarcity, particularly in arid and semi-arid regions with considerable water demand and high variability in precipitation and unexpected extreme events (floods and droughts). The success of RWH systems significantly depends on the location of RWH structures and usually selecting suitable sites is challenging for decision-makers and managers. This paper presents an approach for mapping suitable sites for RWH structures using socio-environmental variables and artificial intelligence algorithms (AIAs). Based on FAO recommendations, the most important conditioning variables for RWH systems are elevation, slope, aspect, precipitation, temperature, distance from the river, curve number (CN), land use, geology, soil type, population density, distance from road, and distance from lakes. An ensemble model was developed based on AIAs, socio-environmental variables, and existing RWH projects, and used for RWH suitability mapping in the large Maharloo-Bakhtegan basin, Iran. Model performance was evaluated using receiver operating characteristic (ROC) and Kappa index. Using the best-performing model, threshold values for conditioning variables were determined from probability curves (PC). The results showed that land use, precipitation, soil type, CN and slope were the most important variables for RHW sites, with the lowest correlation and autocorrelation. The suitability map indicated that 9.7% (3070 km2) of Maharloo-Bakhtegan basin had very high suitability for RWH systems. Thus, in RWH suitability mapping for large area, climate, hydrological, geological, agricultural, topographical, human and socio-economic parameters should be considered to enable efficient RWH planning. Probability curves revealed that the optimum parameter range (α) in Maharloo-Bakhtegan basin was precipitation 357–428 mm, temperature 12.80–15.16 °C, slope 3–6%, elevation 1612–1975 m asl, distance from lake 32–45 km, distance from river 11.4–15.9 km, distance from road 2.59–4.80 km. The RWH suitability map presented can assist decision-makers, hydrologists, and natural resources planners in finding suitable locations for constructing RWH systems.
Hamid Darabi; Ehsan Moradi; Ali Akbar Davudirad; Mohammad Ehteram; Artemi Cerda; Ali Torabi Haghighi. Efficient rainwater harvesting planning using socio-environmental variables and data-driven geospatial techniques. Journal of Cleaner Production 2021, 311, 127706 .
AMA StyleHamid Darabi, Ehsan Moradi, Ali Akbar Davudirad, Mohammad Ehteram, Artemi Cerda, Ali Torabi Haghighi. Efficient rainwater harvesting planning using socio-environmental variables and data-driven geospatial techniques. Journal of Cleaner Production. 2021; 311 ():127706.
Chicago/Turabian StyleHamid Darabi; Ehsan Moradi; Ali Akbar Davudirad; Mohammad Ehteram; Artemi Cerda; Ali Torabi Haghighi. 2021. "Efficient rainwater harvesting planning using socio-environmental variables and data-driven geospatial techniques." Journal of Cleaner Production 311, no. : 127706.
The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model (DEM) data. The unique terrain characteristics of a particular landscape are derived from DEM, which are responsible for initiation and development of ephemeral gullies. As the topographic features of an area significantly influences on the erosive power of the water flow, it is an important task the extraction of terrain features from DEM to properly research gully erosion. Alongside, topography is highly correlated with other geo-environmental factors i.e. geology, climate, soil types, vegetation density and floristic composition, runoff generation, which ultimately influences on gully occurrences. Therefore, terrain morphometric attributes derived from DEM data are used in spatial prediction of gully erosion susceptibility (GES) mapping. In this study, remote sensing-Geographic information system (GIS) techniques coupled with machine learning (ML) methods has been used for GES mapping in the parts of Semnan province, Iran. Current research focuses on the comparison of predicted GES result by using three types of DEM i.e. Advanced Land Observation satellite (ALOS), ALOS World 3D-30m (AW3D30) and Advanced Space borne Thermal Emission and Reflection Radiometer (ASTER) in different resolutions. For further progress of our research work, here we have used thirteen suitable geo-environmental gully erosion conditioning factors (GECFs) based on the multi-collinearity analysis. ML methods of conditional inference forests (Cforest), Cubist model and Elastic net model have been chosen for modelling GES accordingly. Variable’s importance of GECFs was measured through sensitivity analysis and result show that elevation is the most important factor for occurrences of gullies in the three aforementioned ML methods (Cforest=21.4, Cubist=19.65 and Elastic net=17.08), followed by lithology and slope. Validation of the model’s result was performed through area under curve (AUC) and other statistical indices. The validation result of AUC has shown that Cforest is the most appropriate model for predicting the GES assessment in three different DEMs (AUC value of Cforest in ALOS DEM is 0.994, AW3D30 DEM is 0.989 and ASTER DEM is 0.982) used in this study, followed by elastic net and cubist model. The output result of GES maps will be used by decision-makers for sustainable development of degraded land in this study area.
Alireza Arabameri; Fatemeh Rezaie; Subodh Chandra Pal; Artemi Cerda; Asish Saha; Rabin Chakrabortty; Saro Lee. Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM. Geoscience Frontiers 2021, 12, 101230 .
AMA StyleAlireza Arabameri, Fatemeh Rezaie, Subodh Chandra Pal, Artemi Cerda, Asish Saha, Rabin Chakrabortty, Saro Lee. Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM. Geoscience Frontiers. 2021; 12 (6):101230.
Chicago/Turabian StyleAlireza Arabameri; Fatemeh Rezaie; Subodh Chandra Pal; Artemi Cerda; Asish Saha; Rabin Chakrabortty; Saro Lee. 2021. "Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM." Geoscience Frontiers 12, no. 6: 101230.
Agriculture is known to commonly cause soil degradation. In the Mediterranean, soil erosion is widespread due to the millennia-old farming, and new drip-irrigated plantations on slopes, such as the citrus ones, accelerate the process of soil degradation. Until now, the published data about soil erosion in citrus orchards is based on short-term measurements. Long-term soil erosion measurements are needed to assess the sustainability of drip-irrigated citrus production and to design new strategies to control high soil erosion rates. The objective of this study is to assess long-term soil erosion rates in citrus plantations and report the changes in soil bulk density as indicators of land degradation. We applied ISUM (Improved Stock-Unearthing Method) to 67 paired trees in an inter-row of 134 m (802 m2 plot) with 4080 measurements to determine the changes in soil topography from the plantation (2007) till 2020. Soil core samples (469) were collected (0–6 cm depth) to determine the soil bulk density at the time of plantation (2007) and in 2020. The results demonstrate an increase in soil bulk density from 1.05 g cm−3 to 1.33 g cm−3. Changes in soil bulk density were higher in the center of the row as a result of compaction due to passing machinery. Soil erosion was calculated to be 180 Mg ha−1 y−1 due to a mean soil lowering of 1.5 cm yearly. The highest soil losses were found in the center of the inter-row and the lowest underneath the trees. The extreme soil erosion rates measured in new drip-irrigated citrus plantations are due to soil lowering in the center of the inter-row and in the lower inter-row position where the incision reached 80 cm in 13 years. The whole field showed a lowering of the soil topography due to extreme soil erosion and no net sedimentation within the plantation. The results show the urgent need for soil erosion control strategies to avoid soil degradation, loss of crop production, and damages to off-site infrastructures.
Artemi Cerdà; Agata Novara; Ehsan Moradi. Long-term non-sustainable soil erosion rates and soil compaction in drip-irrigated citrus plantation in Eastern Iberian Peninsula. Science of The Total Environment 2021, 787, 147549 .
AMA StyleArtemi Cerdà, Agata Novara, Ehsan Moradi. Long-term non-sustainable soil erosion rates and soil compaction in drip-irrigated citrus plantation in Eastern Iberian Peninsula. Science of The Total Environment. 2021; 787 ():147549.
Chicago/Turabian StyleArtemi Cerdà; Agata Novara; Ehsan Moradi. 2021. "Long-term non-sustainable soil erosion rates and soil compaction in drip-irrigated citrus plantation in Eastern Iberian Peninsula." Science of The Total Environment 787, no. : 147549.
Soil erosion is a threat for the sustainability of agriculture and severely affects the Mediterranean crops. Olive groves are among the rainfed agriculture lands that exhibit soil and water losses due to the impact of unsustainable practices such as conventional tillage and herbicides abuse. To achieve a more sustainable olive oil production, alternative, greener crop management practices need to be tested in the field. Here, a weed cover (CW) treatment is tested at an olive tree plantation that has undergone conventional mechanical tillage for 20 years and results were compared against an adjacent control plantation that maintained tillage as a weed control strategy (CO). Both plantations were under the same tillage management for centuries and macroscopic analysis confirms they are otherwise comparable. Compared to the CO, where tilled soil cover was zero, 20 years of CW (weeds cover 64%; litter cover 5%) had led to significantly higher values of soil bulk density and soil organic matter. Results from rainfall simulation experiments at 55 mm h−1 on 0.25 m2 plots under CO (N = 25) and CW (N = 25) show that as a result of the improved soil structure, CW (i) reduced soil losses by two orders of magnitude (140 times), (ii) decreased runoff yield by one order of magnitude (from 2.65 till 27.6% of the rainfall), (iii) significantly reduced runoff sediment concentration (from 18.6 till 1.43 g l−1), and (iv) significantly delayed runoff generation (CO = 273 s; CW = 788 s). These results indicate that weed cover is a sustainable land management practice in Mediterranean olive groves and promotes sustainable agriculture production in mountainous areas under rainfed conditions, which are typically affected by high erosion rates such those found in the CO plots. Due to the spontaneous recovery of plant cover, we conclude that weed cover is an excellent nature-based solution to increase in the soil organic matter content and soil erosion reduction in rainfed olive orchards.
Artemi Cerdà; Enric Terol; Ioannis N. Daliakopoulos. Weed cover controls soil and water losses in rainfed olive groves in Sierra de Enguera, eastern Iberian Peninsula. Journal of Environmental Management 2021, 290, 112516 .
AMA StyleArtemi Cerdà, Enric Terol, Ioannis N. Daliakopoulos. Weed cover controls soil and water losses in rainfed olive groves in Sierra de Enguera, eastern Iberian Peninsula. Journal of Environmental Management. 2021; 290 ():112516.
Chicago/Turabian StyleArtemi Cerdà; Enric Terol; Ioannis N. Daliakopoulos. 2021. "Weed cover controls soil and water losses in rainfed olive groves in Sierra de Enguera, eastern Iberian Peninsula." Journal of Environmental Management 290, no. : 112516.
Soil erosion is a key concern for the environment and natural resources since it leads to a decline in-field productivity and soil quality, resulting in land degradation. In this study, assessment of uncertainty in soil erosion modelling of the Karso watershed, India, was carried out by employing the revised universal soil loss equation (RUSLE) and geospatial technologies to evaluate the effect of multi-source digital elevation models (DEMs) [Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Cartosat and Shuttle Radar Topography Mission (SRTM)] with resampled multi-resolution grids. The rainfall erosivity factor (R) was computed using the mean monthly Tropical Rainfall Measuring Mission rainfall estimates for 1998 to 2012. The slope length factor was derived using the ASTER and Cartosat DEMs at grid sizes of 30 m, 50 m, 100 m, 150 m, 200 m, and 250 m, and for the SRTM DEM at 100 m, 150 m, 200 m and 250 m resolutions for the Karso watershed, Jharkhand, India. Significant differences were obtained in the soil loss estimates across the different DEM sources and resampled grid sizes. The Cartosat DEM with a 200 m grid was found to estimate the soil loss the best out of all the DEM combinations considered. The Cartosat DEM proved to be more reliable than the ASTER and SRTM DEMs. The results indicated that the RUSLE is a scale-dependent model since the model estimates were affected not only by the DEM source but also by its resolution. The prediction of erosion potential by employing the multisource, multiresolution DEMs and the RUSLE helped to identify the soil erosion's spatial pattern within the watershed. The study provided an impact analysis of the uncertainties when selecting the multisource, multiresolution DEMs for soil erosion modelling.
Ashish Pandey; Amar Kant Gautam; V. M. Chowdary; C. S. Jha; Artemi Cerdà. Uncertainty Assessment in Soil Erosion Modelling Using RUSLE, Multisource and Multiresolution DEMs. Journal of the Indian Society of Remote Sensing 2021, 49, 1689 -1707.
AMA StyleAshish Pandey, Amar Kant Gautam, V. M. Chowdary, C. S. Jha, Artemi Cerdà. Uncertainty Assessment in Soil Erosion Modelling Using RUSLE, Multisource and Multiresolution DEMs. Journal of the Indian Society of Remote Sensing. 2021; 49 (7):1689-1707.
Chicago/Turabian StyleAshish Pandey; Amar Kant Gautam; V. M. Chowdary; C. S. Jha; Artemi Cerdà. 2021. "Uncertainty Assessment in Soil Erosion Modelling Using RUSLE, Multisource and Multiresolution DEMs." Journal of the Indian Society of Remote Sensing 49, no. 7: 1689-1707.
Understanding spatiotemporal geomorphological and pedological changes as a consequence of wildfires can allow stakeholders, land planners, and policymakers to design efficient fire safety-based afforestation and restoration programs of forest lands. The use of remote sensing techniques is a key tool to achieve this goal. The suitable combination of Sentinel-2 MSI data for mapping of different spectral indices related to burn severity and their relationship with other morphometric and soil properties can contribute to a better understanding of the impact of fire, and this is relevant in regions where is still scarce fire-related research such as Turkey. In this investigation, the use of NDVI (Normalized Difference Vegetation Index), dNDVI (Difference Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), NBR (Normalized Burn Ratio), dNBR (Difference Normalized Burn Ratio), RBR (Relativized Burn Ratio), SBI (Soil Bare Index), As (Upslope area), CTI (Compound Topographic Index), TCI (Terrain Characterization Index), SPI (Stream Power Index) and Curvature (Standard Curvature) were combined. As a study case, 47.43 ha in a burned area of Çınarpınar forest unit, Andırın, Kahramanmaraş in Turkey was selected. The results showed that dNDVI, dNBR, RBR, SBI contribute to relevant information about the effect of the wildfire. According to the dNBR fire severity classification, 75% of the total area has been exposed to high-severity fire. The relationship of Sentinel MSI satellite images with some soil and morphometric features have been found meaningful to understand the impact of forest fire in Mediterranean ecosystems. The information collected in the Turkish forest areas affected by wildfires should be relevant for planning and represent a key contribution to the selection of restoration programs and afforestation techniques for a future fire-safe forest.
Turgay Dindaroglu; Emre Babur; Tugrul Yakupoglu; Jesús Rodrigo-Comino; Artemi Cerdà. Evaluation of geomorphometric characteristics and soil properties after a wildfire using Sentinel-2 MSI imagery for future fire-safe forest. Fire Safety Journal 2021, 122, 103318 .
AMA StyleTurgay Dindaroglu, Emre Babur, Tugrul Yakupoglu, Jesús Rodrigo-Comino, Artemi Cerdà. Evaluation of geomorphometric characteristics and soil properties after a wildfire using Sentinel-2 MSI imagery for future fire-safe forest. Fire Safety Journal. 2021; 122 ():103318.
Chicago/Turabian StyleTurgay Dindaroglu; Emre Babur; Tugrul Yakupoglu; Jesús Rodrigo-Comino; Artemi Cerdà. 2021. "Evaluation of geomorphometric characteristics and soil properties after a wildfire using Sentinel-2 MSI imagery for future fire-safe forest." Fire Safety Journal 122, no. : 103318.
In the northwest Ethiopian highlands, Fagita Lekoma district, farmers’ are practicing different land use systems such as crop land use, fodder land use, tree based land use and a combination these land use systems. Acacia decurrens based small-scale agroforestry (SSA) land use system is commonly practiced. However, the economic advantage of the A. decurrens based SSA land use system is not yet investigated. Therefore, this study was conducted to investigate the productivity and economic benefit of the A. decurrens based SSA land use system. Within the district, five investigation sites were selected where A. decurrens based SSA land use system (LUS) widely applied. The study was designed in five treatments with five replications and the test crop was Teff (Eragrostis teff, E. abyssinica) and the test agroforestry tree was A. decurrens. The treatments were; (1) Sole crop (Teff) LUS, (2) Sole fodder LUS, (3) Crop—A. decurrens intercropped LUS, (4) Fodder—A. decurrens intercropped LUS, and (5) Sole A. decurrens LUS. The result shows that the Teff—A. decurrens intercropped, fodder—A. decurrens intercropped, and sole A. decurrens LUSs, respectively, were found to provide better income for small-holder farmers. The Teff—A. decurrens intercropped LUS provided 1.3 and 1.2 times more income than the sole Teff and sole Acacia LUSs, respectively. The fodder—A. decurrens intercropped LUS provided 11 times more income than the sole fodder LUS. These are the main reasons motivating farmers to change the sole Teff and sole fodder LUSs to mixed/intercropped LUS. In general, A. decurrens intercropped based SSA land use system was found to provide better income for small-holder farmers. Hence, the mixed land use system is recommended to be practiced by farmers and could be up-scaled to other areas having similar agro-ecological situations.
Mulatie Mekonnen; Tigist Worku; Birru Yitaferu; Artemi Cerdà; Saskia Keesstra. Economics of agroforestry land use system, Upper Blue Nile Basin, northwest Ethiopia. Agroforestry Systems 2021, 1 -13.
AMA StyleMulatie Mekonnen, Tigist Worku, Birru Yitaferu, Artemi Cerdà, Saskia Keesstra. Economics of agroforestry land use system, Upper Blue Nile Basin, northwest Ethiopia. Agroforestry Systems. 2021; ():1-13.
Chicago/Turabian StyleMulatie Mekonnen; Tigist Worku; Birru Yitaferu; Artemi Cerdà; Saskia Keesstra. 2021. "Economics of agroforestry land use system, Upper Blue Nile Basin, northwest Ethiopia." Agroforestry Systems , no. : 1-13.
Moving towards sustainable products and services in regions with fragile ecosystems needs plant species such as Moringa peregrina (Forssk) that will contribute to the restoration of the land and the development of the societies. This tree species is known as a source of income for local people via preparing medicine, food, industrial oil, livestock feed, and an effective role in water and soil conservation. In recent years, the reduction of M. peregrina has damaged ecosystem services in south-eastern Iran. According, the main objective of this study is to use new Machine Learning (ML) models include: Support Vector Machine (SVM), Multivariate Discriminant Analysis (MDA), Random Forest (RF), and Classification and Regression Trees (CART) to predict the regions susceptible to M. peregrine recovery. South Baluchistan in Iran was selected as a study area due to its location in a represent amen region where sustainable environmental production is threatened by land degradation processes. The location of 83-plant mass of M. peregrina was recorded in field visits by a global positioning system (GPS) device to recognize the relationship between them and thirteen meteorological, morphometric, and geological indicators. Within the 83 selected sites, 70% of them were used for training and 30% used for ML models calibration to predict the susceptible growth regions of M. peregrina to determine the most important indicators affecting his presence and to determine the prediction accuracy for ML models, the Jackknife test method and the area under the receiver operating characteristics curve (AUC) were used, respectively. The results showed that rainfall was the key indicator that determines the success of the plant establishment. So that, it had the most value of the percentage of relative decrease (PRD) as the following was 20.68, 30, 24.52, and 14 for the SVM, MDA, RF, and CART models, respectively. Models validation showed that the RF model with an AUC value of 0.882, is an efficient and reliable model to predict the regions susceptible to growth M. peregrina. It followed by the CART (0.849), MDA (0.832), and SVM (0.827). The final map of the RF method demonstrated that the area with a higher probability for growing M. peregrina is the wettest one. The results of this investigation are the potential map of M. peregrina growth that will contribute to the restoration of the land and will increase primary production, water, and soil protection, increase local people's income and achieve the Sustainable Development Goals (SDGs).
Ehsan Moradi; Mahsa Abdolshahnejad; Moslem Borji Hassangavyar; Ghasem Ghoohestani; Alexandre Marco da Silva; Hassan Khosravi; Artemi Cerdà. Machine learning approach to predict susceptible growth regions of Moringa peregrina (Forssk). Ecological Informatics 2021, 62, 101267 .
AMA StyleEhsan Moradi, Mahsa Abdolshahnejad, Moslem Borji Hassangavyar, Ghasem Ghoohestani, Alexandre Marco da Silva, Hassan Khosravi, Artemi Cerdà. Machine learning approach to predict susceptible growth regions of Moringa peregrina (Forssk). Ecological Informatics. 2021; 62 ():101267.
Chicago/Turabian StyleEhsan Moradi; Mahsa Abdolshahnejad; Moslem Borji Hassangavyar; Ghasem Ghoohestani; Alexandre Marco da Silva; Hassan Khosravi; Artemi Cerdà. 2021. "Machine learning approach to predict susceptible growth regions of Moringa peregrina (Forssk)." Ecological Informatics 62, no. : 101267.
Raindrop size, rainfall intensity and runoff discharge affect the detachment and transportation of soil particles. Among these three factors, the rainfall intensity seems to be more important because it can change other two factors. Storm patterns can be determined by changing the rainfall intensity during the storm. Therefore, the objective of this research is to test the influence of storm pattern on runoff, soil erosion and sediment concentration on a rangeland soil slope under field rainfall simulation. Four storm rainfall intensity patterns were selected for examining the effects of variations in storm event characteristics on soil erosion processes. The selected storm patterns were: I (45, 55 and 70 mm h−1); II (45, 70 and 55 mm h−1); III: (70, 55 and 45 mm h−1); and IV (55, 45 and 70 mm h−1). The last pattern is a new one instead of the uniform pattern which has been sufficiently studied in previous researches. The experiments were conducted in field plots (in Kojour watershed, Mazandaran Province, Iran) with an area of one square meter and an constant slope gradient of 18%, surrounded by galvanised sheets. Following the non-uniform prioritization of the storm patterns for the studied variables, time to runoff (I>II>IV>III), runoff volume (III>IV>II>I), sediment concentration (IV>III>I>II) and soil erosion (III>IV>II>I)), it can be generally inferred that each pattern has specific effect on soil erosion processes during a storm. The results of the general linear model (GLM) test indicated that the effects of storm pattern on time to runoff, total runoff volume, runoff coefficient and soil erosion were significant at a level of 99%. The Duncan test showed that the storm patterns can be divided into three groups of III, IV; II; I (for time to runoff), I, II; IV, III (for runoff coefficient), and I; II; IV, III (for runoff volume and soil erosion).
Leila Gholami; Abdulavahed Khaledi Darvishan; Veliber Spalevic; Artemi Cerdà; Ataollah Kavian. Effect of storm pattern on soil erosion in damaged rangeland; field rainfall simulation approach. Journal of Mountain Science 2021, 18, 706 -715.
AMA StyleLeila Gholami, Abdulavahed Khaledi Darvishan, Veliber Spalevic, Artemi Cerdà, Ataollah Kavian. Effect of storm pattern on soil erosion in damaged rangeland; field rainfall simulation approach. Journal of Mountain Science. 2021; 18 (3):706-715.
Chicago/Turabian StyleLeila Gholami; Abdulavahed Khaledi Darvishan; Veliber Spalevic; Artemi Cerdà; Ataollah Kavian. 2021. "Effect of storm pattern on soil erosion in damaged rangeland; field rainfall simulation approach." Journal of Mountain Science 18, no. 3: 706-715.
Earthquake hazards cause changes in landforms, economic losses, and human casualties. Seismic Vulnerability Mapping (SVM) is key information to prevent and predict the damage of earthquakes. The purpose of this study is to train and compare the results of the Classification Tree Analysis (CTA) learner model with three Gini, Entropy, Ratio split algorithms, and Fuzzy ARTMAP (FAM) model by the development of hybrid models for SVM. The Seismic Vulnerability Conditioning Factors (SVCFs) such as environmental, physical, and social were selected using experts' opinions and experience. Thirteen factors were edited and prepared as the seismic vulnerability conditioning factors (SVCFs) used in this study. In order to seismic vulnerability mapping and models training, a database of training sites was created by the Multi-Criteria Decision Analysis-Multi-Criteria Evaluation (MCDA-MCE) hybrid process. Then, 70% of the points were used for training and 30% were used to validate the models' results based on the holdout method. Moreover, Relative Operating Characteristics (ROC), Seismic Relative Index (SRI), and Frequency Ratio (FR) were used to validate the results. The Area under the curve (AUC) for the algorithms Gini, Entropy, Ratio, and FAM model are 0.895, 0.890, 0.876, and 0.783, respectively. The results of the three validation methods show the highest performance for the Gini splitting algorithm. Accordingly, the percentage of social and physical vulnerability of Sanandaj city was determined based on the MCE-Gini optimal model: 27% of the area and 62% of the population of Sanandaj are under high vulnerability to earthquakes. So that, various factors such as worn urban texture, high population density and environmental factors were among the most important factors affecting seismic vulnerability.
Peyman Yariyan; Rahim Ali Abbaspour; Alireza Chehreghan; Mohammadreza Karami; Artemi Cerdà. GIS-based seismic vulnerability mapping: a comparison of artificial neural networks hybrid models. Geocarto International 2021, 1 -24.
AMA StylePeyman Yariyan, Rahim Ali Abbaspour, Alireza Chehreghan, Mohammadreza Karami, Artemi Cerdà. GIS-based seismic vulnerability mapping: a comparison of artificial neural networks hybrid models. Geocarto International. 2021; ():1-24.
Chicago/Turabian StylePeyman Yariyan; Rahim Ali Abbaspour; Alireza Chehreghan; Mohammadreza Karami; Artemi Cerdà. 2021. "GIS-based seismic vulnerability mapping: a comparison of artificial neural networks hybrid models." Geocarto International , no. : 1-24.
Since December 2019, the world has witnessed the stringent effect of an unprecedented global pandemic, coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of January 29,2021, there have been 100,819,363 confirmed cases and 2,176,159 deaths reported. Among the countries affected severely by COVID-19, the United States tops the list. Research has been conducted to discuss the causal associations between explanatory factors and COVID-19 transmission in the contiguous United States. However, most of these studies focus more on spatial associations of the estimated parameters, yet exploring the time-varying dimension in spatial econometric modeling appears to be utmost essential. This research adopts various relevant approaches to explore the potential effects of driving factors on COVID-19 counts in the contiguous United States. A total of three global spatial regression models and two local spatial regression models, the latter including geographically weighted regression (GWR) and multiscale GWR (MGWR), are performed at the county scale to take into account the scale effects. For COVID-19 cases, ethnicity, crime, and income factors are found to be the strongest covariates and explain most of the variance of the modeling estimation. For COVID-19 deaths, migration (domestic and international) and income factors play a critical role in explaining spatial differences of COVID-19 deaths across counties. Such associations also exhibit temporal variations from March to July, as supported by better performance of MGWR than GWR. Both global and local associations among the parameters vary highly over space and change across time. Therefore, time dimension should be paid more attention to in the spatial epidemiological analysis. Among the two local spatial regression models, MGWR performs more accurately, as it has slightly higher Adj. R2 values (for cases, R2 = 0.961; for deaths, R2 = 0.962), compared to GWR’s Adj. R2 values (for cases, R2 = 0.954; for deaths, R2 = 0.954). To inform policy-makers at the nation and state levels, understanding the place-based characteristics of the explanatory forces and related spatial patterns of the driving factors is of paramount importance. Since it is not the first time humans are facing public health emergency, the findings of the present research on COVID-19 therefore can be used as a reference for policy designing and effective decision making.
Arabinda Maiti; Qi Zhang; Srikanta Sannigrahi; Suvamoy Pramanik; Suman Chakraborti; Artemi Cerda; Francesco Pilla. Exploring spatiotemporal effects of the driving factors on COVID-19 incidences in the contiguous United States. Sustainable Cities and Society 2021, 68, 102784 -102784.
AMA StyleArabinda Maiti, Qi Zhang, Srikanta Sannigrahi, Suvamoy Pramanik, Suman Chakraborti, Artemi Cerda, Francesco Pilla. Exploring spatiotemporal effects of the driving factors on COVID-19 incidences in the contiguous United States. Sustainable Cities and Society. 2021; 68 ():102784-102784.
Chicago/Turabian StyleArabinda Maiti; Qi Zhang; Srikanta Sannigrahi; Suvamoy Pramanik; Suman Chakraborti; Artemi Cerda; Francesco Pilla. 2021. "Exploring spatiotemporal effects of the driving factors on COVID-19 incidences in the contiguous United States." Sustainable Cities and Society 68, no. : 102784-102784.
We explore the current situation in a viticultural region in Eastern Spain from a holistic and multifaceted research approach, which allowed us to understand the biophysical conditions, economic cost, social impact, and perception of the farmers’ community to the use of catch crops. A survey of the perception of the farmers, and an assessment of the biophysical impact of catch crops (CC) and tillage (C = Control plot) on soil organic matter, bulk density, infiltration capacity (single ring infiltrometer), and runoff generation and soil erosion (rainfall simulation experiments) was carried out. Two representative fields as study sites were selected in Les Alcusses valley, within Els Alforins wine production region. The results show that the use of CC increased soil organic matter, favored higher infiltration rates and runoff generation was delayed. Moreover, runoff rates and soil erosion were lowered. The perception of the farmers was mainly against the use of catch crops due to their view as it being ‘dirty’, their cost, and the loss of their reputation and respect by other farmers. Our survey proves that the farmers would accept the catch crops if a subsidy of 76.56 € ha−1 on average would be paid. Farmers see the use of a catch crop more as a benefit for the health of the Planet than for themselves. To achieve land degradation neutrality, education and dissemination programs should be developed to teach and inform the farmers of their key role in the proper management of vineyards.
Artemi Cerdà; Jesús Rodrigo-Comino. Regional Farmers’ Perception and Societal Issues in Vineyards Affected by High Erosion Rates. Land 2021, 10, 205 .
AMA StyleArtemi Cerdà, Jesús Rodrigo-Comino. Regional Farmers’ Perception and Societal Issues in Vineyards Affected by High Erosion Rates. Land. 2021; 10 (2):205.
Chicago/Turabian StyleArtemi Cerdà; Jesús Rodrigo-Comino. 2021. "Regional Farmers’ Perception and Societal Issues in Vineyards Affected by High Erosion Rates." Land 10, no. 2: 205.
Early season fruit production for the northern European market is highly intensive in fertilization, machinery, irrigation and the use of herbicides. Those conditions increase the soil losses and soil compaction and threaten the Sustainable Goals for Development of the United Nations by 2030. Long-term soil erosion measurements are necessary to determine the sustainability of agriculture managements. Moreover, soil erosion on flood irrigation land is a topic that request more surveys and research as rainfed sloping terrains attracted all the attention of scientists and research investment. Improved Stock Unearthing Method (ISUM) was applied to two 15 years-old herbicide treated fields of Saturn peaches (Prunus persica var. platycarpa) to determine long-term soil erosion rates (2004–2019). Using ISUM, a 1 mm thick nylon rope (700 mm length) was used to connect trees perpendicular to the direction of rows at the height of the graft. To detection soil lowering, the vertical distance of the rope to the soil surface was measured at 10 cm intervals along the rope. The ring method (264 samples at 0–6 cm) was used to determine the soil bulk density, which was in average 1.15 gr cm−3 for both plots. There was found a compaction in the centre of both plots due to the pass of machinery with mean bulk density values of 1.23 gr cm−3, meanwhile underneath of the trees, the soil bulk density was 1.05 gr cm−3. The topography survey carried out with ISUM (2508 sampling points) informed that flood irrigation redistributed the soil from the upper to the lower field position, where a sedimentation layer was measured. We found that the two studied fields showed a contrasted response, with low soil erosion values in Benimodo and high in L'Alcúdia study sites. Soil erosion rates were in average 1.46 Mg ha−1 yr−1 and 8.02 Mg ha−1 yr−1 for Benimodo and L'Alcúdia, respectively. However, the maps development using ISUM allow to inform that the pattern of soil redistribution is similar for both fields as the highest soil lowering was found in the upper field part, where the flood discharge detach soil particles. In the lower field position sedimentation takes place. The dataset allows us to conclude that soil erosion in Saturn peaches fields is non-sustainable and more soil conservation management should be applied to reduce the soil erosion rates due to the bare soils as a consequence of the use of herbicides. This research informs that soil erosion in flood irrigated fields is a relevant process that needs more investigations around the world, where 94% of the irrigated land is under flood or furrow irrigation, and where irrigation is growing year after year.
Artemi Cerdà; Ioannis N. Daliakopoulos; Enric Terol; Agata Novara; Yalda Fatahi; Ehsan Moradi; Luca Salvati; Manuel Pulido. Long-term monitoring of soil bulk density and erosion rates in two Prunus Persica (L) plantations under flood irrigation and glyphosate herbicide treatment in La Ribera district, Spain. Journal of Environmental Management 2021, 282, 111965 .
AMA StyleArtemi Cerdà, Ioannis N. Daliakopoulos, Enric Terol, Agata Novara, Yalda Fatahi, Ehsan Moradi, Luca Salvati, Manuel Pulido. Long-term monitoring of soil bulk density and erosion rates in two Prunus Persica (L) plantations under flood irrigation and glyphosate herbicide treatment in La Ribera district, Spain. Journal of Environmental Management. 2021; 282 ():111965.
Chicago/Turabian StyleArtemi Cerdà; Ioannis N. Daliakopoulos; Enric Terol; Agata Novara; Yalda Fatahi; Ehsan Moradi; Luca Salvati; Manuel Pulido. 2021. "Long-term monitoring of soil bulk density and erosion rates in two Prunus Persica (L) plantations under flood irrigation and glyphosate herbicide treatment in La Ribera district, Spain." Journal of Environmental Management 282, no. : 111965.
The main aim of this research was to determine the potential effects of different tillage systems (TT: traditional tillage and RT: reduced tillage) on runoff and erosion at two different locations (Kahramanmaras and Tarsus, Southern Turkey) under (i) fallow, (ii) wheat (Triticumaestivum L.), and (iii) sainfoin (Onobrychissativa L.) crops. Rainfall simulations with intensity of 120 mm h−1 and 30-min duration, representing a typical extreme thunderstorm in this area, were used. We quantified the elapsed time to runoff generation (ET), total runoff volume (R), soil loss (SL), sediment concentration (SC), and runoff coefficient (RC). At both locations, the fallow plots indicated the first runoff response ranging between 1.2 and 3.1 min, while the range was between 9.4 and 8.9 min for the sainfoin plots. The highest runoff coefficient was recorded for the fallow parcel in Tarsus (57.7%), and the lowest runoff coefficient was recorded for the sainfoin parcel in Kahramanmaras (4%). For both study sites, the fallow plots showed higher soil erosion rates (871 and 29.21 g m−2) compared with the wheat plots (307 and 11.25 g m−2), while sainfoin recorded the lowest soil losses (93.68 and 3.45 g m−2), for Tarsus and Kahramanmaras, respectively. Runoff and sediment yield generated from sainfoin and wheat parcels under the RT system were less than under the TT system at the Kahramanmaras location. At the Tarsus location, the effect of soil tillage on soil and water losses was insignificant on the sainfoin planted plots. The reduced tillage system was successful in reducing sediment yield and runoff generated from parcels growing wheat and sainfoin compared to traditional tillage in Tarsus location, but runoff and soil loss were found to be very high compared to parcels constructed in the Kahramanmaras location.
Tugrul Yakupoglu; Recep Gundogan; Turgay Dindaroglu; Kadir Kusvuran; Veysel Gokmen; Jesus Rodrigo-Comino; Yeboah Gyasi-Agyei; Artemi Cerdà. Tillage Impacts on Initial Soil Erosion in Wheat and Sainfoin Fields under Simulated Extreme Rainfall Treatments. Sustainability 2021, 13, 789 .
AMA StyleTugrul Yakupoglu, Recep Gundogan, Turgay Dindaroglu, Kadir Kusvuran, Veysel Gokmen, Jesus Rodrigo-Comino, Yeboah Gyasi-Agyei, Artemi Cerdà. Tillage Impacts on Initial Soil Erosion in Wheat and Sainfoin Fields under Simulated Extreme Rainfall Treatments. Sustainability. 2021; 13 (2):789.
Chicago/Turabian StyleTugrul Yakupoglu; Recep Gundogan; Turgay Dindaroglu; Kadir Kusvuran; Veysel Gokmen; Jesus Rodrigo-Comino; Yeboah Gyasi-Agyei; Artemi Cerdà. 2021. "Tillage Impacts on Initial Soil Erosion in Wheat and Sainfoin Fields under Simulated Extreme Rainfall Treatments." Sustainability 13, no. 2: 789.
Land Degradation threatens the sustainability of the human societies due to the loss of resources, services and goods. To assess land degradation, models are useful and fruitful due to the complex and multidisciplinary processes acting. The present research attempts to design and develop a new model to assess land degradation based on biophysical and socioeconomic parameters to determine the land affected by a high risk of degradation. The use of models can shed light on the land degradation processes and will contribute to better design restoration and rehabilitation processes. The identification of regions that are more vulnerable to degradation can improve the land planning and enhance development. The Fars Province, in Southern Iran, was selected as a test area to assess risk of land degradation by means of the Risk Assessment of Land Degradation (RALDE) model. Data gathered from the different governmental offices of Fars Province and MODIS satellite data were used for this purpose. The hazard maps of natural, human and degradation trend were produced with a Geographical Information System tool. The final land degradation risk map was developed by first overlaying all three natural, human and degradation trend layers, and then it was compared with current state layer of degradation in GIS. Moreover, areas under risk were classified to subclasses with different probability level to show a statistical picture of risk. In RALDE, the percentage of risk probability is evaluated according to trend and potential of degradation. Results show that degradation risk probability range between 6 to 58%. The areas under different subclasses of severe to very severe risk cover about 67% of the study area. RALDE shows higher threats of land degradation for these zones, and we propose immediate attention to this region with related conservational and reclamation works. The Fars province has been used successfully to apply the RALDE model and his use for other regions will contribute to improve the Land Degradation assessment and promote Development programs.
Masoud Masoudi; Maryam Vahedi; Artemi Cerdà. Risk assessment of land degradation (RALDE) model. Land Degradation & Development 2021, 32, 2861 -2874.
AMA StyleMasoud Masoudi, Maryam Vahedi, Artemi Cerdà. Risk assessment of land degradation (RALDE) model. Land Degradation & Development. 2021; 32 (9):2861-2874.
Chicago/Turabian StyleMasoud Masoudi; Maryam Vahedi; Artemi Cerdà. 2021. "Risk assessment of land degradation (RALDE) model." Land Degradation & Development 32, no. 9: 2861-2874.
The Sustainable Development Goals of the United Nations call for applying soil management practices that contribute land degradation neutrality. Our objectives were to investigate the effect of (i) soil management—conventional tillage (CT under crop) and no-tillage (NT under grass)—and (ii) an amendment (polyacrylamide (PAM)) application on the structure stability indices of soils from a semi-arid region. Two sets of experiments were conducted using the high-energy moisture characteristic (HEMC) method for the assessment of (i) land-use type (CT vs. NT) in soils (30 samples) varying in texture, and (ii) the effect of six PAM concentrations (0, 10, 25, 50, 100, and 200 mg L−1) on three typical soils (sandy clay loam, clay loam, and clay) under CT management; then, the contributions of PAM concentration (CT) and NT were compared. Water retention curves of samples were obtained at a matric potential from 0 to −5.0 J kg−1 and characterized by a modified van Genuchten model that yields (i) model parameters α and n, and (ii) a soil structure stability index (SI). The treatments affected the shape of the water retention curves. Change of land use from CT to NT and PAM application to CT soil increased the SI and ɑ, and decreased n compared to CT-managed soils. The magnitude of the NT and PAM effect was inversely related to soil clay content. CT-managed soils treated with a low PAM rate (10–25 mg L−1) gave SI comparable to that obtained for the NT-managed soils, while CT-managed soils treated with a high PAM rate (50–200 mg L−1) yielded 1.3–2.0 and 2–4 times higher SI than that for NT and CT-managed soils, respectively. Our findings suggest that both the change of land use to NT or the addition of small amounts of PAM are viable alternatives for stabilizing CT-managed weakly alkaline semi-arid soils, whose soil structure stability is a priori limited.
Amrakh I. Mamedov; Atsushi Tsunekawa; Mitsuru Tsubo; Haruyuki Fujimaki; Imanverdi Ekberli; Cevdet Şeker; Hasan S. Öztürk; Artemi Cerdà; Guy J. Levy. Structure Stability of Cultivated Soils from Semi-Arid Region: Comparing the Effects of Land Use and Anionic Polyacrylamide Application. Agronomy 2020, 10, 2010 .
AMA StyleAmrakh I. Mamedov, Atsushi Tsunekawa, Mitsuru Tsubo, Haruyuki Fujimaki, Imanverdi Ekberli, Cevdet Şeker, Hasan S. Öztürk, Artemi Cerdà, Guy J. Levy. Structure Stability of Cultivated Soils from Semi-Arid Region: Comparing the Effects of Land Use and Anionic Polyacrylamide Application. Agronomy. 2020; 10 (12):2010.
Chicago/Turabian StyleAmrakh I. Mamedov; Atsushi Tsunekawa; Mitsuru Tsubo; Haruyuki Fujimaki; Imanverdi Ekberli; Cevdet Şeker; Hasan S. Öztürk; Artemi Cerdà; Guy J. Levy. 2020. "Structure Stability of Cultivated Soils from Semi-Arid Region: Comparing the Effects of Land Use and Anionic Polyacrylamide Application." Agronomy 10, no. 12: 2010.
Forest land affected by deforestation yields high soil and water losses. Suitable management practices need to be found that can reduce these losses and achieve ecological and hydrological sustainability of the deforested areas. Mulch has been found to be effective in reducing soil losses; straw mulch is easy to apply, contributes soil organic matter, and is efficient since the day of application. However, the complex effects of rice straw mulch with different application rates and lengths on surface runoff and soil loss have not been clarified in depth. The current paper evaluates the efficiency of rice straw mulch in reducing the hydrological response of a silty clay loam soil under high intensity and low frequency rainfall events (tap water with total depth of 49 mm and intensity of 98 mm/h) simulated in the laboratory. Surface runoff and soil loss at three lengths of the straw (10, 30, and 200 mm) and three application rates (1, 2, and 3 Mg/ha) were measured in 50 cm (width) × 100 cm (length) × 10 cm (depth) plots with disturbed soil samples (aggregate soil size < 4 mm) collected in a deforested area. Bare soil was used as control experiment. Runoff volume and erosion were significantly (at p < 0.05) lower in mulched soils compared to control plots. These reductions were ascribed to the water absorption capacity of the rice straw and the protection cover of the mulch layer. The minimum runoff was observed for a mulch layer of 3 Mg/ha of straw with a length of 200 mm. The lowest soil losses were found with straw length of 10 mm. The models developed predict runoff and erosion based on simple linear functions of mulch application rate and length, and can be used for a suitable hydrological management of soil. It is concluded that, thanks to rice straw mulch used as an organic soil conditioner, soil erosion and surface runoff are significantly (at p < 0.05) reduced, and the mulch protection contributes to reduce the risk of soil degradation. Further research is, however, needed to analyze the upscaling of the hydrological effects of mulching from the plot to the hillslope scale.
Misagh Parhizkar; Mahmood Shabanpour; Manuel Esteban Lucas-Borja; Demetrio Antonio Zema; Siyue Li; Nobuaki Tanaka; Artemio Cerdà. Effects of length and application rate of rice straw mulch on surface runoff and soil loss under laboratory simulated rainfall. International Journal of Sediment Research 2020, 36, 468 -478.
AMA StyleMisagh Parhizkar, Mahmood Shabanpour, Manuel Esteban Lucas-Borja, Demetrio Antonio Zema, Siyue Li, Nobuaki Tanaka, Artemio Cerdà. Effects of length and application rate of rice straw mulch on surface runoff and soil loss under laboratory simulated rainfall. International Journal of Sediment Research. 2020; 36 (4):468-478.
Chicago/Turabian StyleMisagh Parhizkar; Mahmood Shabanpour; Manuel Esteban Lucas-Borja; Demetrio Antonio Zema; Siyue Li; Nobuaki Tanaka; Artemio Cerdà. 2020. "Effects of length and application rate of rice straw mulch on surface runoff and soil loss under laboratory simulated rainfall." International Journal of Sediment Research 36, no. 4: 468-478.
Sustainability in orchard crops is an important goal for farmers, decision-makers and consumers. The United Nations Sustainable Development Goals emphasize the importance of the soils in the Earth System to achieve sustainability and accomplish the Land Degradation Neutrality Challenge. Within the world agriculture land, olive and vineyards are within the eldest crops in the world, and they are also the ones with the highest degree of soil degradation. Cover crops (CC) are widely accepted as sustainable crop management that reduces soil and water losses, restores organic matter, increases biodiversity and fertility in degraded agriculture soils. The agriculture land must shift into a more sustainable agricultural practices for achieving soil and water conservation targets, and CC are of help, but not widely applied by farmers that usually expect subsidies. Runoff and soil water storage are two key processes that determine the crop production, plant health and sustainability. However, after four decades of use, there is not a consistent State-of-the-Art that clarifies the impact of service crops. Our review highlights, in quantitative terms, the role of CC exerted in vineyard and olive grove in runoff reduction and soil water status. Statistical differences were found between the average values of RC (7.37 % and 10.05 % for CC and conventional tillage (CT) management, respectively). For the soil water conservation, the ratio SWCCT/SWCCC is always higher than 1. Water competition was more pronounced in spring and decreased after blooming. The use of CC is a strategy can have a positive influence on water use efficiency, through the reduction of the excessive vine vigour in fertile soils or favouring the growth of roots in deeper layers. In low vigour vineyards, low fertile soils and in dry environment, the water competition should be correctly monitored to avoid negative effect in grape yields. Cover crops are a positive contribution to the agriculture sustainability, although Mediterranean ecosystems, where most of the olive oil and wine is produced should pay attention to their impact on water availability
Agata Novara; Artemi Cerda; Ettore Barone; Luciano Gristina. Cover crop management and water conservation in vineyard and olive orchards. Soil and Tillage Research 2020, 208, 104896 .
AMA StyleAgata Novara, Artemi Cerda, Ettore Barone, Luciano Gristina. Cover crop management and water conservation in vineyard and olive orchards. Soil and Tillage Research. 2020; 208 ():104896.
Chicago/Turabian StyleAgata Novara; Artemi Cerda; Ettore Barone; Luciano Gristina. 2020. "Cover crop management and water conservation in vineyard and olive orchards." Soil and Tillage Research 208, no. : 104896.