جستجوی مقالات مرتبط با کلیدواژه « land use changes » در نشریات گروه « آب و خاک »

Reducing the water level of Urmia Lake and its effects on the environment around the lake has been one of the important national and international issues and challenges in the last two decades. In accord with the studies, one of the critical factors affecting this declining trend has been the rise in harvest, especially for agriculture. Accordingly, the purpose of this study is to simulate the future status of water resources in the Urmia Lake basin, influenced by the area of agricultural land uses.

  For this purpose, Landsat satellite image data for the period 2000 to 2020 are firstly classified using the SVM algorithm in ENVI5.3 software and the classification accuracy is analyzed using the Kappa Coefficient algorithm.In the following, the statistics and information related to the change of cultivation pattern (from arable to garden) and water sources discharging Lake Urmia are calculated. In the next step, the simulation of land use changes for 2030 and 2040 is done using two LCM and CA-MARKOV methods. And finally, after determining the amount of changes in each land use, the amount of water required for agricultural affairs in the catchment is simulated using NETWAT model.

The results show that the area of two uses, irrigated agriculture and garden will increase from 1450 and 395 square kilometers in 2000 to more than 3600 and 1650 square kilometers in 2040, respectively, This will increase the amount of water Needed or agriculture from 1,500 million cubic meters in 2000 to more than 4,100 million cubic meters in 2040.

From 2000 to 2020, water consumption in irrigated agriculture has increased by 1253.05 Km2; which according to Markov's prediction method, this amount will reach 2049.54 Km2 in 2040 that raises the amount of water consumption by 1 billion and 473 million cubic meters. The gardens land use has increased by 688.02 Km2 from 2000 to 2020, and according to Markov's prediction method, this amount will reach 1276.14 Km2 in 2040, which raises the amount of water consumption by 703 million cubic meters. From 2000 to 2020, 367.06 Km2 has been added to the drayland farming, which according to the prediction of Markov method, this amount will reach 531 Km2 in 2040, which soars the amount of water consumption by 253 MCM.

Land use changes identifying to assess and monitor sensitive areas for sustainable planning and land management is essential. Remote sensing and the use of GIS technology as some of the most common methods in the world in monitoring land changes, especially, in the study of large areas. In this study, the trend of spatial land use changes in the area of Karun 3 dam was investigated. in the before and after the construction periods and dam intake using remote sensing and GIS over 27 years. In this study, the satellite imagery of Landsat 5 TM sensors from 1991 and 2008 and Landsat 8 OLI sensors in 2018 were analyzed and processed. Using object-oriented classification with land use maps for the three periods 1991, 2008, and 2018 with the overall accuracy of the Kappa index of 0.93 and 0.89 percent for 1991, 0.94, and 0.88 percent in 2008 and 0.93, respectively, and 0.86% in 2018 was prepared. The results showed that the water use of the region with an area of 37.68 square kilometers is increasing and agricultural lands and residential areas with an area of 1349.04 and 226.56, respectively, forest lands with an area of 1041.49 remained as the dominant cover of the region and rangelands by going through a decreasing trend of increase in both periods after forest use, with an area of 878.87, they had the largest area. According to the obtained results, it can be said that the construction of the Karun 3 dam has caused the flooding of agricultural lands and their conversion to another use, as a result of which the villagers were forced to migrate due to losing their jobs and abandoned residential areas become other uses.

Forest fires and land use change have become a major global concern due to their significant role in environmental degradation and climate change. Meanwhile, the soil of forests and pastures has always been considered due to its relatively high organic matter and suitable structure. But fires and changes in the management of these ecosystems and the application of tillage have had detrimental effects on soil structure and loss of organic matter of the natural ecosystems. Therefore, this study investigates the effect of wildfires and land use change to vineyard on soil organic carbon (SOC) content and its soil organic carbon decomposition rate (SDR) in aggregate size fraction in an Oak Forest in Northern Zagros.

For this purpose, topsoil (0-5 cm depth) was sampled in a natural oak forest from both inside (FI) and outside (FO) sprout clumps, a portion of the forest burned three years earlier from areas undergone high (BHI), moderate (BMI), or low (BLO) severity, and a vineyard planted thirty years earlier in place of the forest from both under the foliage of vines (VI) and outside it (VO). All soil samples were air-dried and sieved to obtain four aggregate size fractions (8–2, 2–1, 1–0.25, and

The results of this study showed that cultivation and fire, especially its severe type, cause significant damage to large aggregates and increase the fine aggregates. So that, the highest and lowest amounts of coarse aggregates (2–8 mm) were obtained in FI (61.6%) and VI (11.1%) treatments, respectively. Whereas, the highest and lowest amounts of fine aggregates (< 0.25 mm) were obtained in VI (12.4%) and FI (5.7%) treatments, respectively. The results also showed that in all the studied treatments, the amount of SOC increased with decreasing of the soil aggregates size. Furthermore, in compared to the virgin forest, cultivation in the vineyard resulted in a significant reduction in SOC, while no changes in this parameter were observed in the fire treatments. The results also showed that in all the studied treatments, the amount of SDR index increased with decreasing of the soil aggregates size and this index followed the trend: FI (7.2) > BHI (5.4) > FO (5.2) > BMI (4.7) > BLO (2.9) > VI (1.4) > VO (0.4).

Overall, thirty years of farming were more impacting on soil aggregates degradation than a single fire, although severe; nevertheless, severe fire appears to have been much more impacting on soil aggregates degradation than every single yearly plowing. The results also showed that the SDR in soils that are rich in organic matter (FI and BHI) could be more sensitive to warming and intensify global warming more strongly than arable lands (VI and VO).

In order to plan and manage the land and its changes, it is necessary to identify and evaluate the factors affecting it. Land use / cover changes are one of the main factors in global environmental change that is defined as a change in the type of land use; it is one of the major factors changing hydrologic flow, land erosion and destruction of biodiversity. The main purpose of this study was to assess the trends of land use changes in Beheshtabad Watershed of Chaharmahal and Bakhtiari Province with an area about 3847 square kilometers by using remote sensing and GIS during a 25-year period. In this research, first, analyzing and pre-processing the satellite images of Landsat 5 TM sensors from 1991 and 2008 were done, and Landsat 8 of OLI sensor of 2016 was applied. Then, by using the hybrid classification method, 5 land use classes including pasture lands, urban-building lands, agricultural lands, garden lands and bare lands, land use maps for the three time periods were prepared. The overall accuracy of the obtained land use maps for 1991, 2008 and 2016, was 92.17%, 94.29% and 93.41%, respectively, indicating the acceptable accuracy of the maps. Then, the process of land use change and the contribution of each land use classes and the percentage of changes in each land use class were determined in two study periods. The results of this study showed some changes occurred in the studied watershed. The total area of pasture lands during two periods indicated the decreasing trend, but urban-building and garden lands during two periods represented the increasing one. Agricultural lands during the first period indicated the decreasing trend and during the second period showed the increasing trend, while bare lands during the first period showed the increasing trend and during the second period, reflected the decreasing trend. In general, it should be noted that in the Beheshtabad watershed, we could see an increase in the replacement of pastures by urban-building class, rainfed agriculture, gardens, and bare lands, the incidence of destruction in the region.

Soil is one of the main non-renewable natural resources that today its destruction is considered one of the most severe problems all over the world. In recent decades, rapid and unsustainable changes and land use due to the urban development activities and increasing population created a great deal of modifications in land cover and land use and has been increasing the environmental degradation including soil degradation. Therefore, reviewing these changes through satellite images, evaluating and forecasting their potentialities via modeling can help managers and planners to make more effective decisions. The aim of this study was to assess the changes in land use during the period 1992 to 2015 via using satellite images to calculate the rate of land use changes to each other and predict possible changes in land use in the years 2020, 2025, 2030 and 2035, using cellular automata - Markov model (CA-Markov) in Joupar plain, Kerman province.
In order to prepare land use plans the three periods of Landsat satellite images including Landsat 5 satellite TM (1992), Landsat 7 ETM (2000) and Landsat 8 satellite OLI (2015) were used in this study. To prepare land use maps through satellite images, initially the mentioned images were exposed to primary pre-processing such as geometric and atmospheric corrections. In addition, via providing training samples the satellite images were classified and their accuracy were evaluated using Idrisi imagery software through maximum probability algorithm. The developed land use maps of different periods were transited to CA-Markov model in order to produce transition probability matrix. Ultimately, the transition probability matrix was produced that shows the likelihood of transition of one land use to others. Then the chain analysis of cellular automata – Markov on the basis of land use plans and transition probability matrix in CA-Markov model with an emphasis on land use changes were expected in 2020, 2025, 2030 and 2035 were implemented in Idrisi software with various numbers of repetitions and steps. Based on the survey results, changes in land use and the level of current land use changes calculated, compared and evaluated and the future land use changes were predicted.
Results and The results of the detection of changes in the first period (1992-2000) revealed the highest increase in land area which was attributed to the use of pasture, grassland, irrigated agriculture and orchard and the highest decrease in land area was related to bed stream. In the second period (2000-2015) the greatest increase in land area was associated to the use of irrigated agriculture, orchards and bed stream and the greatest reduction was in pasture and grassland use. The results obtained from the prediction of future user changes of the region based on CA-Markov showed decreasing levels of land use attributed to orchard and irrigated agriculture and increasing levels of land use associated to pasture, grassland and bed stream comparing to 2015. Also the results obtained from the prediction of the findings regarding the years 2020, 2025, 2030 and 2035 revealed a reduction in land use related to bed stream, pasture and grassland due to the lack of rainfall and temperature rise and this will lead in the destruction of vegetation cover as wellas the more soil degradation. Also, due to the lack of rainfall, the recent droughts and previous studies we can conclude that the approach of CA-Markov model is more compatible with the conditions of the region.

Effect of land use type on soil functioning within an ecosystem can be assessed by soil quality indices. Such studies that are carried out to improve land resources quality, lead to control the land degradation and help us to identify the sustainable management. In order to study the effect of land use change from pasture to agriculture on soil quality and clay mineralogy, Valarude region of Zanjan province was selected. Composite soil samples were taken from 0 – 30 and 30 – 60 cm depths of both land uses with three replicates and totally 60 soil samples were prepared. Important soil quality indicators such as bulk density, weighted mean diameter of aggregates, quantities of organic carbon, and total nitrogen, soil microbial respiration rate, amount of microbial biomass C and urease and alkaline phosphatase activities were measured. Results revealed that the land use change from pasture to agriculture, led to a significant reduction in the amounts of organic carbon (62%), total nitrogen (70%), mean weight diameter of aggregates (32%), microbial respiration rate 75%) and microbial biomass C quantity (47%). The assay of enzyme activities showed that alkaline phosphatase activity did not change significantly but urease activity decreased in agriculture land (87%). Mineralogical studies showed that the both land uses had illite, kaolinite; chlorite, smectite and mixed layer minerals and change of land use did not have a significant effect on soil clay minerals. Overall, it can be concluded that a change in land use from pasture to agriculture with widespread agricultural practices, especially intensive tillage activities, may lead to decrease soil quality.

Surface water quality is influenced by land use changes over time. Taleghan River is one of the branches of Sefidrood, which its water quality is important due to the use of its water in various urban and agricultural lands. Mutually, mentioned land uses have an important influence in water quality of the river over the time. In present study the land use changes during the period 1970 to 2002 in the Taleghan watershed was investigated. Results showed the reduction of irrigated and non-irrigated agricultural lands, by 60.86% and 73.23%, respectively. Rangelands were increased 20.62% in the studied basin. Then, in the study period the process of changing water quality factors were investigated. The results showed that the overall trend of changes were decreasing in TDS, EC, SAR and also amount of anions and cations within the study period.. Assessment of water discharge of the river during the study period with an annual average rate trend, presented no significant change. This issue indicates that there was no effect of water discharge on improving the quality of water trend.. Therefore it could be said that improving water quality in Taleghan River during the study period is attributed to land use changes in the basin.