Hafez Mirzapour; Ali Haghizadeh; Naser Tahmasebipour; Hossein Zeinivand
Volume 6, Issue 20 , December 2019, , Pages 79-99
Abstract
1- IntroductionAccurate detection of changes land use in Accurate and timely, Basis for a better understanding of the relationships and interactions of human and natural phenomena to manage and provides better use of resources. Principal land use management requires accurate and timely information in ...
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1- IntroductionAccurate detection of changes land use in Accurate and timely, Basis for a better understanding of the relationships and interactions of human and natural phenomena to manage and provides better use of resources. Principal land use management requires accurate and timely information in the form of a map. Regarding the widespread and unsustainable changes in land use, including the destruction of natural resources in recent years, Investigating how landslide changes during time periods are essential for satellite imagery. Since conservation of natural resources requires monitoring and continuous monitoring of an area, Land-use change models are now used to identify and predict land-change trends and land degradation one of the most widely used models in predicting land use change is the Auto-Markov cell model. the aim of present study is to monitor land use changes in the past years and predict changes in the coming years in Badavar-Nurabad watershed in the Lorestan province with an area of 71600 hectares. 2- MethodologyThe Markov chain method analyzes a pair of land cover images and outputs a transition probability matrix, a transition area matrix, and a set of conditional probability images. The transition probability matrix shows the probability that one land-use class will change to the others . The transition area matrix tells the number of pixels that are expected to change from one class to the others over the specified period (Ahadnejad 2010). Automatic cells are models in which adjacent and continuous cells, such as cells that may include a quadrilateral network, change their state or attributes through simple application of simple rules. CA models can be based on cells that are defined in several dimensions. The rules for changing the state of a cell from one mode to another can be either a combination of growth or decrease, such as a change to a developed cell or without development. This change is the source of the change that occurs in the adjacent cell. Neighborhood usually occurs in adjacent cells or in cells that are close together(Ghorbani et al, 2013). In order to detect land use changes in the studied area, TM , ETM+ and OLI satellite images of Landsat were used during three time periods of 1991, 2004 and 2016. After applying geometric and atmospheric corrections to images, the land use map for each year was prepared using the maximum probability method. The Kappa coefficient for the classified images of 1991, 2004 and 2016was 0.81, 0.85 And 0.90 obtained. Then, to model land use changes using the Auto-Markov cell model for 2028 horizons, First, in the Idrisi Selva software using Markov chain, the map was selected as input from the years 1991 and 2004, the 12-year prediction of the changes was considered by 2016 to determine the likelihood of a change in application. Then, using the CA-Markov method, the data from the Markov chain and the map of 2016 were used as input data for the automated-Markov cell method. 3- ResultsAssessment of the match between simulated and actual map of 2016 with 0.97 kappa index showed that this model is an appropriate model for simulating of land use change. The results from monitoring satellite imagery that in 1991 to 2016, the extent of residential areas, land is Dry farming, garden and irrigated farming land added in front of vast pastures, shrubbery and other is reduced. After verifying the model's accuracy, a 2028 map was prepared to predict the changes over the coming years. Well as the results show that the vast pastures of the forecast is reduced in the amount of 659.89hectares and 395.47 hectares will be added to the extent of irrigated farming. 4- Discussion and conclusionThe results of the Auto-Markov cell model showed that if the current trend continues, the size of the ranges will decrease sharply. Comparison of simulated map of 2016 by model and actual map with Kappa index showed that Auto-Markov cell model is a suitable model for predicting land use change and can accurately assess the future status of land use and vegetation to predict. Therefore, it is suggested protective measures and make appropriate management decisions to control non-normative changes continue to apply more than ever.
Mahin Naderi; Alireza Ildoromi; Hamid Nouri; Soheila Aghabeigi Amin; Hossein Zeinivand
Volume 5, Issue 16 , December 2018, , Pages 61-79
Abstract
Abstract Intr4oduction Changing the environmental conditions of a natural ecosystem influences the hydrological responses such as flooding and the extent of erosion and sedimentation of the area. One of the models used to investigate the effect of land use change and climate change on runoff is SWAT ...
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Abstract Intr4oduction Changing the environmental conditions of a natural ecosystem influences the hydrological responses such as flooding and the extent of erosion and sedimentation of the area. One of the models used to investigate the effect of land use change and climate change on runoff is SWAT model which is a hydrological simulator and a continuous and semi-distributive time-space model with a physical base. Understanding the relationship between land use change and its causative factors and its secondary effects on hydrologic regimes provides essential information for land use planning and sustainable management of natural resources. Investigating the amount and trend of the changes and its effect on the hydrological processes in the basin is a way to predict the state of future changes and provide more effective plans for the sustainable development of the water resources in the basin. The construction of the Garin Dam in the Garin Basin, the risk of filling the sediment reservoir with sediment, reducing its useful life due to seasonal floods, and the effect of basin land use and climate change were the reasons for choosing this area for this research. The purpose of this study was to study the land use and climate change in the studied watershed and determine the effect of these changes on the runoff rate of this watershed in order to better it correctly. Garin Dam is located in the Zagros in the province of Hamedan. It includes the catchment area of the Sarab Gamasiab River to the Garin Reservoir Dam and its area is up to the 22,000 m2. The Garin land basin is mainly mountainous and its range of height ranges from 1833.9 to 3429.2229 m above sea level. Materials and Methods SWAT model input data included climatic and hydrological data (daily precipitation, maximum and minimum temperature, relative humidity, wind speed, dew point, and solar radiation). In this study, the ten year data of Nahavand synoptic station was uased. Topographic maps, digital elevation model (DEM), soil and land use were also used as the input of the model. A digital elevation model (DEM) was extracted using a topographic map of 1: 250,000 of the Garin River basin. SWAT CUP software was used for the calibration and validation of the SWAT model. The calibration data was from the years 2002 to 2007, but the validation data was from 2008 to 2010. In order to determine the degree of the sensitivity of the flow parameters in the SWAT model, SUFI2 software SWAT CUP were used and the sensitivity of the selected 24 parameters were measured. The Elimination of the parameters which had less sensitivity, was based on the calibration process. According to the P-value and T-Stat criteria, the sensitivity of the parameters were determined. The land use maps of 1986, 2000, and 2014 were prepared at the previous stages, and the Markov chain and the CA Markov filter were used to map the land use in 2042. In this research, the outputs of the Hadcm3 model were used to predict Garin's future climate. In addition, the SDSM statistical method was used to fine-scale the output of the general atmospheric circulation models. The SWAT model was also used in the range of calibrated parameters to simulate runoff caused by climate change in Garin basin under two A2 and B2 scenarios. After micro-sampling, the SWAT model was converted and t analyzed for the scenarios. Then, the results of the model implementation with different scenarios and the results of model implementation with the current climate conditions were compared Results and Discussion Regarding the results of the statistical indices, NS index was 0.95. P and R factors were respectively 0.47 and 0.03, and the coefficient of determination (R2) for observed and simulated floodguns was 0.6. Accordingly, the results were confirmed in the calibration phase. The validation phase was conducted to verify the correctness of the selection of the parameters during the calibration period between 2008 and 2010. Given that the Nashatcliff coefficient for Garin's catchment area at the calibration and validation stages were respectively 0.95 and 0.66, , the results were satisfactory and the SWAT model was able to simulate surface runoff in Garin River Basin. In general, due to an increased forest use, an increased permeability and water drainage to the surface and deep water aquifers, and an increased evaporation and transpiration, the amount of runoff has decreased. Regarding the results of temperature, rainfall, and runoff of the next period, it can be seen that in months when rainfall is reduced and the temperature increased, the amount of runoff in the coming period also decreases. The main reasons for this discrepancy can be attributed to the difference in the intensity of land use change as well as the extent of the altered land area, which, given the mountainous nature of the area in the Garin land basin, can be compared to other areas with flat lands with agricultural uses. It is concluded that the effect of climate change in the Garin dam basin is greater than the change in land use due to its mountainous nature. Conclusion The results of the study of the effect of land use change on runoff in the Garin basin indicated that there was a daily and monthly decline in the amount of runoff. The results of the study of the effect of climate change on runoff in the Garin western basin also indicated that there was a daily and monthly decline in the amount of runoff. In both A2 and B2 scenarios, the monthly average temperature, especially in the first and last months of the year, had an increasing trend and rainfall decreased in the spring and winter. It can be attributed to the increased temperature and evaporation, and decreased rainfall. It can also be seen that there was a decline in the average monthly runoff in January, February, April, May and December, with a decreased rainfall, but there was an increase in the average monthly runoff in June, July, August and September, with an increased rainfall. In addition, the effect of land use change on the reduction of runoff in the upcoming period is lower compared to the change effect under A2 and B2 scenarios. It will affect the climate change of the runoff more flatly and the reduction of runoff is more affected by climate change. According to the information obtained from these predictions, it is possible to properly manage the watershed and adopt appropriate management measures in accordance with the conditions of this watershed, prevent unauthorized land use changes, and reduce the damage caused by the phenomenon of the climate change.
Mahin Naderi; Alireza Ildoromi; Hamid Nouri; Soheila Aghabeigi Amin; Hossein Zeinivand
Volume 5, Issue 14 , June 2018, , Pages 23-42
Abstract
Introduction
In a natural ecosystem, changing the environmental conditions of that ecosystem influences hydrological responses such as flooding and the extent of erosion and sedimentation of the area. One of the models used to investigate the effect of land use change and climate change on SWAT runoff, ...
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Introduction
In a natural ecosystem, changing the environmental conditions of that ecosystem influences hydrological responses such as flooding and the extent of erosion and sedimentation of the area. One of the models used to investigate the effect of land use change and climate change on SWAT runoff, the SWAT model is a hydrological simulator and a continuous and semi-distributive time-space model with a physical base. Understanding the relationship between land use change and its causative factors and its secondary effects on hydrologic regimes provides essential information for land use planning and sustainable management of natural resources. Investigating the amount and trend of the changes and its effect on hydrological processes in the basin is a way to predict the state of future changes and provide more effective plans for sustainable development of water resources in the basin. The construction of the Garin Dam in the Garin Basin and the risk of filling the sediment reservoir with sediment and reducing its useful life due to seasonal floods and the effect of basin land use and climate change on the reason for choosing this area for this research. The purpose of this study was to study the land use and climate change in the studied watershed and determine the effect of these changes on the runoff rate of this watershed in order to better manage it.
Study of Area
Garin dam dam is located in the province of Hamedan and is located in the mountain range of Zagros mountains. This area includes the catchment area of Sarab Gamasiab River to the Garin Reservoir Dam and its area is up to the 22,000-square-meter Garin Garin Dam, the Garinland basin is mainly mountainous and its range of elevation ranges from 1833.9 to 3429.2229 meters above sea level.
Materials and Methods
SWAT model input data include climatic and hydrological data (daily precipitation, maximum and minimum temperature, relative humidity, wind speed, dew point and solar radiation), which is ten years in the study of statistics related to the synoptic stations Skinheads Became Topographic maps, digital elevation model (DEM), soil and land use are also needed as model inputs. A digital elevation model (DEM) was extracted using a topography map of 1: 250,000 Garin River basin. Calibration and validation of the SWAT model in SWAT CUP software. The study used calibration data from 2002 to 2007 and 2008 to 2010 for validating the model. In order to determine the degree of sensitivity of flow parameters in the model SWAT using SUFI2 software SWAT CUP sensitivity analysis for 24 parameters election, the results of the sensitivity analysis on the Elimination of parameters that has the less sensitive they are, the calibration process decision It is accepted. According to the P-value and T-Stat criteria, the sensitivity of the parameters is determined. Land use maps of 1986, 2000, and 2014 were prepared in the previous stages, and the Markov chain and the CA Markov filter were used to map the land use in 2042. In this research, the outputs of the Hadcm3 model were used to predict Garin's future climate. In this research, the SDSM statistical method was used to fine-scale the output of the general atmospheric circulation models. The SWAT model was used in the range of calibrated parameters to simulate runoff from climate change in Garin basin under two scenarios A2 and B2. After micro-sampling, the SWAT model was converted and the model was analyzed for the scenarios. Then, the results of model implementation with different scenarios and the results of model implementation with the current climate conditions were compared
Discussion and results
Regarding the results of statistical indices, NS index is equal to 0.95, P factor and R factor were respectively 0.47 and 0.03 respectively, and the coefficient of determination (R2) for simulated and simulated floodguns was 60 / 0. Accordingly, the results were confirmed in the calibration phase. The validation phase was conducted to verify the correctness of the selection of parameters during the calibration period for the period 2008-2010. Given that the Nashatcliff coefficient for Garin's catchment area at calibration and validation stage was equal to 0.95 and 0.66, respectively, the results were satisfactory and the SWAT model was able to simulate surface runoff in Garin River Basin. In general, due to increased forest use due to increased permeability and water drainage to the surface and deep water aquifers and increased evapotranspiration, the amount of runoff has decreased. Regarding the results of temperature, rainfall and runoff of the next period, it can be seen that in the months when rainfall is reduced and the temperature increased, the amount of runoff in the coming period also decreases. The main reasons for this discrepancy can be attributed to the difference in the intensity of land use change as well as the extent of the altered land area, which, given the mountainous nature of the area in the Garinland basin, can be compared to other areas with flat lands with agricultural uses. It is concluded that the effect of climate change in the Garin dam basin is greater than the change in land use due to its mountainous nature.
Conclusion
The results of the study of the effect of land use change on runoff in the Garin basin indicate that the amount of runoff is decreasing daily and monthly in this catchment area. Also, the results of the study on the effect of climate change on runoff in the Garinwestern basin indicate that the amount of runoff is daily and monthly in this catchment area. Considering that in both scenarios A2 and B2 the monthly average temperature, especially in the first and last months of the year, has an increasing trend and rainfall has decreased in the spring and winter, this decrease can be attributed to the increase in temperature which Following this, evaporation also increases and decreases in rainfall in this catchment area. Regarding the results, it can be seen that the average monthly runoff in months when rainfall decreased in January, February, February, April, May and December, and in the months when rainfall increased As of June, July, August and September, the amount of runoff will increase compared to the current period. It is also observed that the effect of land use change on the reduction of runoff in the upcoming period is lower compared to the change effect under A2 and B2 scenarios and will affect the climate change of the runoff more flatly and the reduction of runoff is more affected by climate change. According to the information obtained from these predictions, it is possible to properly manage the watershed and adopt appropriate management measures in accordance with the conditions of this watershed and to prevent unauthorized land use changes and reduce the damage caused by The phenomenon of climate change.
