University of KashanDesert Ecosystem Engineering Journal2538-63365120230801Determining the Relationship between NDVI/Leaf Area Index and Plant Production in Vegetation Cover Studies using Remote Sensing11411368910.22052/jdee.2023.248303.1082ENAfsanehAfzaliDepartment of Environment, Faculty of Natural Resources and Earth Sciences, University of Kashan, Kashan, IranFatemehHadianDepartment of Natural Resources, Isfahan University of Technology, Isfahan, IranLeilaYaghmaeiDepartment of Natural Resources, Isfahan University of Technology, Isfahan, IranHosseinVahidiDepartment of Environment, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, IranJournal Article20220912Plant production is one of the most important living elements in ecosystems for example in the food cycle. In arid and desert areas, due to the fragility of these ecosystems, vegetation cover is of particular importance in reducing wind and water erosion. Therefore, the main purpose of this study is to study vegetation cover and plant production in desert and semi-desert climates of Khuzestan as a coastal province. In this study, while separating climatic classes, vegetation type and determining the status of rangeland, the relationship between vegetation cover, plant production, and NDVI/ Leaf Area Index (MODIS image products with the resolution of 250*250 m<sup>2</sup>) in the separated layers of vegetation was calculated. The results showed that among the studied climates, the relationship between vegetation cover and satellite images decreases in semi-arid, arid, and ultra-arid climates, respectively, and in a climatic classification with vegetation type degradation, the relationship between vegetation and NDVI index weakens. The amount of leaf area index in this research was between 0.13 to 0.002, and <em>Quercus brantii</em> and <em>Scirpus </em>spp. showed the highest and lowest values, respectively. A comparison of the relationship between plant production and leaf area index shows that this relationship is stronger in the leaf area index than plant production as the main factor of plant production. Therefore, considering the importance of plant reflectivity, remote sensing studies and reduction of leaf area index, dry conditions and destruction of plant types can be the main reasons for reducing the relationship between vegetation and NDVI index.https://jdee.kashanu.ac.ir/article_113689_43685145ff2bf4bfd59c75842999f435.pdfUniversity of KashanDesert Ecosystem Engineering Journal2538-63365120230801Investigating the effects of human activities and climate change on land degradation and Jazmurian wetland dryness153211390010.22052/jdee.2023.248434.1084ENSaeedBarkhoriDepartment of Ecological Engineering, Faculty of Natural Resources, University of Jiroft, Kerman, Jiroft, IranElhamRafiei-SardooiDepartment of Ecological Engineering, Faculty of Natural Resources, University of Jiroft, Kerman, Jiroft, Iran;HamedEskandari DamenehPostdoctoral researcher, Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, IranHadiEskandari DamanehPostdoctoral researcher, Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, IranFarzanehGhaderi NasabWater Resources Engineer at Kerman Regional Water Company. PhD in Water Science and Engineering Shahid Bahonar University of KermanJournal Article20221012Adopting appropriate management practices and preventing the constant destructive factors involved in such practices requires the protection and monitoring of wetlands. On the other hand, land use and climate change play an important role in the degradation of wetlands. Therefore, this study sought to assess Jazmurian<strong> </strong>wetland conditions during the pre-and post-dam construction periods and under different climate change scenarios, taking into account land use and climate change as two significant relevant factors. To this end, Landsat images collected from TM 1991, ETM + 2008, and OLI 2021 sensors were used to investigate the trends of land use changes. Finally, predictive land use maps were prepared for 2040 using the Land Change Modeler (LCM). Moreover, the changes in minimum and maximum temperature and precipitation rates were both investigated in the past and predicted for the future using different climate change scenarios and the Statistical Downscaling Model (SDSM). The results of the land use investigation revealed that the area of wetland lake has decreased by 1611.45 km<sup>2</sup> from 1991 to 2021 and that the trend of land use changes in the future is considerable, leading to an increase in the area of agricultural lands and salt lands, and thus to complete wetland dryness. Moreover, it was found that the average annual precipitation rate had a decreasing trend in the past and that it will decrease in the future compared to the base period. On the other hand, the results of minimum and maximum temperature rate analysis indicated an increasing trend by 3 and 2.56 °C under the RCP 8.5, respectively, compared to the base period. Therefore, the reduced precipitation and increased temperature in the past and future, and the construction of the Jiroft dam can be considered as factors causing a decrease in the wetland area and its water supply, and changes in the wetland’s surrounding ecosystems.https://jdee.kashanu.ac.ir/article_113900_d170b8195f9c96bec3fa2aca2d233057.pdfUniversity of KashanDesert Ecosystem Engineering Journal2538-63365120230801Assessing Drought Hazard Via Combined Drought Index Using Machine Learning Techniques: A Case Study of Ilam Province334811390110.22052/jdee.2023.246432.1079ENZahedehHeidarizadiPh.D. student of Combat Desertification, Gorgan University of Agricultural Science and Natural Resources,MajidOwneghProfessor, Department of Watershed and Arid Zone Management,
Gorgan University of Agricultural Sciences and Natural Resources (GUASNR)Chooghi BairamKomakiAssistant prof, Department of Watershed and Arid Zone Management,
Gorgan University of Agricultural Sciences and Natural Resources (GUASNR),Journal Article20220528As one of the most important natural hazards worldwide, drought increases the vulnerability of the agricultural sector, raises economic loss, and threatens human life, making the characterization of drought and its hazard assessment to be of great significance. Therefore, this study used twelve various remotely sensed indices derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and digital elevation model (DEM) to monitor drought throughout the 2000–2018 growing season. Moreover, the Standardized Precipitation Index (SPI) was used as reference data, with the relevant time scales ranging from 1 to 12 months. Finally, the correlation between thirteen indices and SPI in Ilam Province was modulated using three machine learning approaches, including random forest, boosted regression trees, and Cubist. The results indicated that among the three approaches mentioned above, random forest delivered the best performance (R<sup>2</sup> = 0.88) in terms of SPI prediction. It was also found that Land Surface Temperature (LST) and Evapotranspiration (ET) had higher relative significance in terms of short-term meteorological drought, whereas Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) had higher relative significance in terms of long-term meteorological drought when treated by random forest approach. In the next step, relative soil moisture, Standardized Precipitation Evapotranspiration Index (SPEI), and crop yield data were used to validate the collected data. Finally, the Drought Hazard Index (DHI) was generated based on the probability occurrences of drought using the comprehensive drought model made in the previous step. Accordingly, the results of the DHI map indicated that 65% and 18% of the study area fell under the very high and high classes of drought hazard, respectively. Overall, the results of this study provide a comprehensive method for assessing regional drought.https://jdee.kashanu.ac.ir/article_113901_4d0f9bae4ff1baa7771f12f6a20496aa.pdfUniversity of KashanDesert Ecosystem Engineering Journal2538-63365120230801Developing a Framework for Ecosystem Health Assessment in Arid Lands based on the CVOR Model: A Case Study of Abarkuh, Iran496611390210.22052/jdee.2023.248502.1085ENMohammad HasanDadkhodaeiEnvironmental planning MSc graduated, Environmental Sciences Department, Natural Resources and Desert Studies Faculty, Yazd UniversityParastooParivarEnvironmental Sciences Department, Natural Resources and Desert Studies Faculty, Yazd UniversityHamid RezaAzimzadehEnvironmental Sciences Department, Natural Resources and Desert Studies Faculty, Yazd UniversityAhadSotoudehEnvironmental Sciences Department, Natural Resources and Desert Studies Faculty, Yazd University0000-0003-3636-7560AliZareYazd Province Natural Resources and Watershed Management, Carbon Sequestration ServiceJournal Article20221101Being highly vulnerable, arid ecosystems require conscious management worldwide. Therefore, as health assessment studies on such ecosystems can help landscape planners develop effective strategies in this regard, the current study sought to localize an ecosystem health assessment model for arid lands using the CVOR model to assess the health of Abarkuh city, an arid (desert) region located in the central part of the Iranian plateau. To this end, a set of criteria reflecting the ecological conditions of the study area in particular and arid lands, in general, was selected, including C (Water and wind erosion, quantity and quality of water resources), V (the amount of primary production under natural conditions and soil organic carbon), O (landscape heterogeneity and connectivity), R (vegetation percentage, changes in underground water level, and soil salinity).
The results of the study revealed that the quantity and quality of groundwater, water erosion, and wind erosion were of greatest importance in the health status of arid ecosystems. On the other hand, the result of the ecosystem health assessment in the study area specifically showed that the development of land uses in the area had posed great challenges to its ecosystem’s health conditions, with 48% and 9% of the region's area being marked with a relatively unhealthy condition and unhealthy condition, respectively. Moreover, the status of land use in the region indicated that many gardens and agricultural lands had been left under the influence of such an unhealthy ecosystem, aggravating the health of the region. Therefore, the region has turned into the origin of dust phenomenon at the local level. https://jdee.kashanu.ac.ir/article_113902_889efabf3c75ae1db57761b06ef0b4e3.pdf