Land Evaluation and Suitability
Sina Bigdeli; Heidar Ghafari; Mojtaba Norouzi Masir; Abdolamir Moezzi
Abstract
Introduction: Today, the concept of soil quality (SQ) has been widely used to know the capacity and limitations of soils in different environmental systems. The degree of suitability of land is determined by its capacity to provide services and its flexibility against external conditions. Production ...
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Introduction: Today, the concept of soil quality (SQ) has been widely used to know the capacity and limitations of soils in different environmental systems. The degree of suitability of land is determined by its capacity to provide services and its flexibility against external conditions. Production of plant biomass is one of the most important functions of soil in relation to food security. The share of dry land in Iran's agricultural production, especially wheat, is very significant. So that in terms of area, about half of the total area of agricultural lands, in terms of volume of production, about 10% of all agricultural products and about 30% of the country's wheat production are related to these lands. Therefore, maintaining the soil quality of these lands is very important. The main goal of this research is to model and quantify the soil quality of part of the rainfed agricultural lands of Dezpart city using integrated multivariate analysis and also to determine the minimum effective data set.Materials and methods: This study was carried out in a part of the rainfed agricultural area of Dezpart County. First, 119 soil samples were prepared using the composite method from the soil depth of 0-30 cm. Soil sampling was done in a stratified random manner to include all the different geomorphological units. The geographic location of the sampling points was also recorded. The samples were transferred to the laboratory and their chemical-fertility and physical characteristics include reaction (pH), electrical conductivity (EC), organic matter (OM), total nitrogen, available potassium, absorbable phosphorus, calcium carbonate equivalent (CCE), texture, bulk density, mean weight diameter (MWD) of soil aggregates, soil gravel content and cation exchange capacity (CEC) were measured. Then the soil quality was determined using two datasets of total (TDS) and minimum (MDS), and multivariate analysis method. In this method, by using appropriate scoring functions, a score between zero and one was considered for each member of the data set. Also, a weight coefficient was calculated for each member, and finally, the soil quality index, which indicates its degree of desirability, was obtained by three indices including Nemero (NQI), cumulative weighted index (IQI) and simple cumulative index (AQI). Finally, a spatial variation map of soil quality was prepared using the Inverse Distance Weighting (IDW) method in geographic information system (GIS) software.Results and Discussion: The results of the principal component analysis (PCA) test indicated that there are three main components that cover 78% of the total variance changes. The first component alone accounts for about 41% and the second and third components account for 25% and 12% of the total data variance, respectively. Based on the correlation analysis between soil components and characteristics, five characteristics including organic matter (OM), silt content, gravel, pH and EC were selected as MDS members. Became in the TDS collection, the highest weights related to silt and sand (0.093 and 0.095, respectively) and the lowest weight with 0.050 was assigned to bulk density (BD). In the MDS set, the highest weight was related to organic matter and silt and the lowest weight was related to pH. The soil quality of the region was generally classified as medium based on the two indexes of AQI and WQI. However, the NQI method indicated that the soil quality was low. Among the three selected indices with different functions and data sets, the weighted soil quality index with the minimum data set and nonlinear function (WQI_MDS_NL) was chosen as the superior model due to having a higher sensitivity index (or a larger standard deviation). The spatial soil quality map, which was prepared for this study, showed that approximately 50% of the lands in the region had an average soil quality and 50% had a low soil quality.Conclusion: Organic matter, silt, pH, gravel and EC are the main characteristics to determine the soil quality of the region. In addition, stability of soil aggregates, bulk density and lime are the most important limiting factors of soil quality in the region. Therefore, it is suggested to use appropriate management practices such as conservation tillage and use of organic fertilizers to improve these characteristics.
Land Evaluation and Suitability
foziyeh kohani; Hamid Reza Matinfar; Mahmod Rostamtnia; Alireza Amirian-Chakan
Abstract
Introduction: Assessing land suitability and determining its production potential to manage soil and land resources is one of the best sustainable agricultural policies. Barley is the second most cultivated crop in Iran after wheat. However, all soils in Iran are equally suitable for barley production. ...
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Introduction: Assessing land suitability and determining its production potential to manage soil and land resources is one of the best sustainable agricultural policies. Barley is the second most cultivated crop in Iran after wheat. However, all soils in Iran are equally suitable for barley production. This study was conducted with the aim of evaluating the suitability of land for barley cultivation using a spatial model integrated with Geographical Information System (GIS).Materials and Methods: The suitability of the land for barley cultivation is affected by various factors including (percentage of sand, percentage of silt, percentage of clay, percentage of saturated moisture, structure, percentage of surface gravel, water retention capacity, organic matter, nitrogen, phosphorus, potassium, EC, CEC, SAR, CaCO3 and pH) that were identified in the study area. In order to evaluate the suitability of land for the production of barley crops, Cumulative Quality Index (IQI) and Numerical Quality Index (NQI) were used with two series of data sets including: Total Data Set (TDS) and Minimum Data Set (MDS) and the results of this The indices were compared with two indices, storie and square root.Results and Discussion: 17 measured parameters were used as the total data set (TDS) and 5 parameters (sand percentage, clay percentage, silt percentage, saturated moisture and pH) were used as the minimum data set (MDS). Also, the results showed that using the data set The minimum (MDS) provides a closer estimate to the storied and square-root methods compared to using the total data set (TDS), thus even considering a limited number of effective soil properties with respect to spending less time and money on quality assessment. Soil and agricultural management can provide better results.Conclusion: By calculating various indices and comparing them with the more common storie and square root methods, it becomes possible to survey and monitor land using new techniques. This helps validate the accuracy of the index performance. With the square root and storie techniques, the value of each parameter is categorised based on sources and conducted studies, and the requirements of the barley plant. Each parameter receives a specific grade. Considering the assigned grades and comparing them with the estimated values from the ground experiments, it is possible to identify which areas of land are more or less suitable for the intended purpose. Satellite images combined with ground observation data provide valuable information for land evaluation. The results showed that most of the units in the storie model and the square root were placed in the medium suitability class (S2) for barley production. Comparing the correlation between land suitability assessment methods and measuring soil quality indices method showed that there is the highest correlation between the NQIMDS method and the square root. In general, it can be said that the soil quality index can provide better results with minimum data set and less time and cost for soil quality assessment and agricultural management. The soil maps produced for agricultural suitability analysis in this research can serve as an effective aid in decision-making processes. Subsequent research should concentrate on employing new predictive tools to enhance forecasting abilities. Most studies have used fundamental GIS techniques for resource allocation. GIS is a potent tool for spatial analysis in resource allocation. Since land resources are decreasing rapidly, land use planning should be accomplished efficiently to recognize new areas for crop production. The use of advanced simulation software assists in the reduction of redundancy within other processes while simultaneously increasing their accuracy. Consequently, researchers must concentrate on carrying out studies concerning new and developed GIS software. Unmanned aerial vehicles (UAVs) could enhance accessibility, and therefore improve the effectiveness of resource allocation (Yu et al., 2014). Modelling techniques can be employed to evaluate the practical impact of resources.The results of this research can be useful in managerial decisions. In future studies, the use of new predictive tools should be considered. As land resources are rapidly decreasing, effective land use planning should be considered to identify new crop production areas. The use of advanced simulation software helps to eliminate the redundancy of other processes and increase accuracy (82, 93). Therefore, researchers should focus on conducting studies related to new and improved GIS software. Unmanned aerial vehicles (UAVs) may increase access to increase the effectiveness of resource allocation (103). Modeling techniques can be used to assess the practical impact of resources.
Land Evaluation and Suitability
Nikrooz Bagheri; Alireza Sabzevari; Ali Rajabipour
Abstract
Introduction: One of the decision-making methods using quantitative data is multi-criteria decision-making, which helps the manager make rational decisions by considering different conflicting criteria. Planning for the optimal use of water and soil resources, in addition to their conservation, involves ...
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Introduction: One of the decision-making methods using quantitative data is multi-criteria decision-making, which helps the manager make rational decisions by considering different conflicting criteria. Planning for the optimal use of water and soil resources, in addition to their conservation, involves increasing production, income growth for farmers, and rural economic prosperity. Given the limited resources, the optimal cropping pattern should be appropriate and effective for each region. The selection of an appropriate cropping pattern and, if necessary, adjusting the cultivation based on regional and national needs and the relative advantage of products in different regions is of great importance. So far, many studies have been conducted to optimize cropping patterns. The main reasons for the low productivity in agricultural production are the inappropriate allocation of resources and production factors. Although farmers are faced with various options for agricultural activities and crop selection, their production factors are limited. By formulating and implementing an optimal cropping pattern in a region, it is possible to familiarize farmers with the available potentials while considering the constraints of production resources, reducing risk, ensuring system stability, improving income in production, and creating the groundwork for the growth and prosperity of agricultural regions. This leads to agricultural development, increased profitability, and profitability. Decision-making is one of the most important and fundamental tasks of management, and the quality of decision-making determines the achievement of organizational goals. However, the main focus of research has been on improving the productivity of crops based on water and soil resources, with little attention given to the subject of agricultural mechanization and the criteria of regional operators. Considering the criteria of farmers in decision-making processes increases the acceptance of programs and better collaboration in implementing them. Additionally, most studies have only used one decision-making method, but each decision-support method provides a unique outcome and may differ from the results of other methods. Therefore, in this study, multiple decision-making methods were evaluated and compared to determine the best method to be used. Based on the given explanation, the objective of this research is to prioritize the factors influencing the determination of suitable cropping patterns for agricultural products using four different decision-making methods and introduce the best method. Materials and Methods:The research area is sited in Silakhour Plain, in Lorestan Province, between the cities of Doroud and Borujerd, at geographical coordinates 38 degrees 36 minutes north and 48 degrees 31 minutes east, in coordinate zone 39. In this study, Analytic Hierarchy Process (AHP), TOPSIS, VIKOR, and Simple Weighted Average methods were used for decision-making. The parameters investigated in this study included technical-agricultural, economic, macro-governmental, soil and climate, social, and production support factors. These factors included sub-factors such as the presence of mechanized planting and harvesting equipment, farming unit larger than one hectare, water requirements of plants, distance from the place of consumption, farming unit smaller than one hectare, crop profitability, required capital, suitable market for the product, customs and farmer habits, farmer education, crop cultivation experience, guaranteed purchase of the product, government incentive policies, physical characteristics of the soil in the region, chemical characteristics of the soil in the region, average temperature during the growing season, elevation of the region, average rainfall in the region, insurability of the product, sustainability of crop production, availability of seeds compatible with regional conditions, and prevalent pests in the region. To validate all judgments made in the analytic hierarchy process method, the inconsistency ratio was calculated using Expert Choice11 software. Based on this, the inconsistency ratio was calculated to be less than 0.1 in all steps of this method. If the consistency ratio is 0.1 or less, it indicates consistency in the comparisons and confirms the validity of the judgments. To reach a general consensus on the ranking of parameters, the method of merging average ranks was used. Results and Discussion: In this study, 22 indicators were identified, including the presence of mechanized planting and harvesting equipment (0.061), operational unit larger than one hectare (0.021), crop water requirement (0.014), distance from consumption site (0.008), operational unit smaller than one hectare (0.006), product profitability (0.125), required cash capital (0.116), suitable market for the product (0.020), agricultural customs and habits (0.028), education of the farmer (0.006), crop cultivation experience (0.130), guaranteed purchase of the product (0.3), government incentive policy (0.122), physical characteristics of the soil in the region (0.075), chemical characteristics of the soil in the region (0.022), average temperature during the growth season (0.022), elevation of the region (0.008), average precipitation in the region (0.006), insurability of the product (0.013), stability of crop production (0.007), availability of seeds compatible with the regional conditions (.0004), and common pests in the region (0.0002). Among the mentioned parameters, cash capital (0.236), water requirement for cultivation (0.233), product profitability (0.098), and operational unit larger than one hectare (0.039) are considered the most important factors. Certain purchase of the product (0.3), product profitability (0.0125), government incentive policy for products (0.122), and required cash capital for cultivation (0.116) were identified as the most important factors influencing the cropping pattern, respectively, using the hierarchical weighted method. product profitability and required cash capital are among the influential factors in the design of cropping patterns for agricultural products. The results showed that the ranking of agricultural products for inclusion in the regional cropping pattern differs in each decision-making method. Although grains and sugar beets have high rankings in all groups, it is necessary to validate and finalize these methods with integrated approaches to reach a general conclusion. In a multi-criteria decision-making problem, multiple decision-making methods may be used because decision-makers do not limit themselves to one decision-making method, and they may obtain different results using different methods. In fact, in such situations where the results of different methods of multi-criteria decision-making are not the same, the question is which option should be chosen. To reach a general conclusion, it is necessary to validate and finalize these methods with integrated validation and finalization approaches. Among the integration methods,
Land Evaluation and Suitability
Nazanin Khakipour
Abstract
Introduction: Soil is a dynamic natural system and interface between land, air, water, and life, which performs vital services for human sustenance. The increasing population growth has led to the excessive use of this natural resource to provide food, clothing and other human needs. This has led farmers ...
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Introduction: Soil is a dynamic natural system and interface between land, air, water, and life, which performs vital services for human sustenance. The increasing population growth has led to the excessive use of this natural resource to provide food, clothing and other human needs. This has led farmers in different parts of the world to improper exploitation of inferior and marginal lands such as pastures and forests located on sloping lands. However, on the one hand, these lands have low potential and on the other hand, they have a high potential for erosion. Soil quality is usually introduced as the ability of the soil to interact with the ecosystem maintain the productivity of the quality of different parts of the environment and thus improve the health of plants, animals and humans. The quality of soil and its importance for the development of sustainable agriculture are more important nowadays. Land use change is one of the most important current problems of our country, especially in the Hyrcanian forest lands in the north of the Iran. The objectives of this study were to evaluate the effects of land use change on some soil quality indicators in north of Iran. Materials and Methods : A part area in the south of Lahijan was selected including 3 land uses: Natural Forest (NF), Tea plantation (TP) and paddy rice (PR) cultivation. In each land use 10 soil samples were collected at 0-20 cm depth and transferred to the laboratory. Undisturbed soils samples by core was taken for measurement of bulk density. A part of sample passed through the 4 mm sieve for measurement of aggregate stability and three indices comprised mean weight diameter: MWD, geometric mean diameter: GMD and water stable aggregates: WSA were calculated. Other soil properties such as pH, Calcium carbonate equivalent (CCE), soil organic matter (SOM), particulate organic carbon (POC), and soil respiration also measured.Results and Discussion: The statistical results in this study showed that due to the change of land use from forest to tea and rice cultivation, the amount of organic carbon decreased, while the amount of pH and calcium carbonate increased. As a result of changing the use of forest land to other two land uses, the indicators of stability of soil aggregates (MWD, GMD and WSA) have significantly decreased, and as a result, the bulk density of the soil has increased. The amount of MWD was 1.95 mm in the forest, 1.2 mm in the tea plantation, and 0.45 mm in the rice cultivation. The amount of particulate organic carbon as one of the indicators of soil quality in forest lands was observed in the maximum amount. In addition to the reduction of particulate organic matter, this change is also caused by the excessive traffic of machines. Soil microbial respiration was analyzed as a soil biological indicator. The results showed that the average microbial respiration in the natural forest was equal to 300 mg C/ day.g soil, and in the two other land uses of tea and rice cultivation, it was calculated as 200 and 120 mg C/ day.g soil, respectively. Positive and significant relationship between SOM and MWD confirmed that soil organic matter had high contribution for soil aggregate formation and its stability. Conclusion: This research was conducted to investigate the impacts of land use changes in the north of Iran in Gilan province on some soil quality indicators. The results of this research showed that the soil’s chemical, physical, and biological characteristics have shown significant differences due to land use change. In forest soils, the highest amount of organic carbon, and the lowest amount of pH was observed, which is due to the high accumulation of organic matter and high leaching of cations. Due to the degradation of organic carbon in the other two uses, the bulk density and aggregate stability indicators have decreased. The intense cultivation operations in the other two uses, especially in the paddy fields, have destroyed the soil structure. Also, more organic carbon in forest soils has led to more microbial respiration. In total, all soil quality indicators have decreased with the change in land use in the study area. Therefore, land conversion and especially deforestation in the studied region should be avoided. In total, the results showed that land use change in the study area has caused land degradation and reduced the soil quality and soil health indicators, and it is necessary to consider it in land use planning, land improvement, and sustainable land management.
Land Evaluation and Suitability
Behnam Kamkar; Parysa Alizadeh Dehkordi; Pooya Aalaee Bazkiaee; Omid Abdi
Abstract
Introduction: Understanding the suitability of the lands is very important in terms of the ability to cultivation a particular crop. Having information in this field helps us to act more intelligently in prioritizing land allocation for the cultivation of various crops. Also, adapting the current-grown ...
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Introduction: Understanding the suitability of the lands is very important in terms of the ability to cultivation a particular crop. Having information in this field helps us to act more intelligently in prioritizing land allocation for the cultivation of various crops. Also, adapting the current-grown lands under cultivation of a crop selected by the farmer to the final layer of land suitability can give us an overview of the right or wrong choice of land use. This information will help agricultural policymakers to replace crops when necessary and to replace crops that have been misallocated in disproportionately desirable lands with other crops or to improve their crop management. Therefore, this study was conducted to assess the land suitability of Golestan province agricultural lands for soybean cultivation and the degree of adaptation of current soybean-grown fields to the obtained suitability layers.Materials and Methods: This study was carried out in the agricultural lands of Golestan province with an area of 821 thousand hectares. First, the real lands under cultivation of soybean were separated using 1674 land samples taken from different crops and object-based image analysis (OBIA) method. To separate the lands under soybean cultivation in Golestan province, sentinel 2 satellite images with a spatial accuracy of 10 meters related to planting to harvesting time in 2018 were used. Then, the layers of soil, climate, and topography characteristics were provided to investigate land suitability for soybean cultivation. Climatic components including minimum, optimum, maximum temperatures, and rainfall were estimated using long-term statistics of synoptic stations in the province (maximum available statistics). Data of soil texture, nitrogen, organic matter, phosphorus and potassium, soil pH, and salinity were also received from the provincial agricultural and natural resources research center, and from the data, the soil properties map was obtained. The digital land elevation map (DEM) of the province with a spatial resolution of 20 meters was used to extract slope, elevation, and aspect maps. The process of interpolation of climatic and soil layers was performed using ordinary kriging method. The relative importance of each factor was determined through the Analytic Hierarchy Process (AHP). This was done by designing questionnaires based on AHP paired matrices and completing it by agricultural specialists. After extracting the weights from the questionnaires and preparing the classified raster layers, these layers were imported in GIS version 10.3. Combining and overlaying the layers was done by assigning AHP weight to each layer. Finally, a land suitability map was prepared for the cultivation of the soybean in the study area which, in turn, was used to determine the adaptation of current soybean fields with determined suitability classes.Results and Discussion: The accuracy of classification by object-oriented method using kappa coefficient and overall Accuracy coefficient (0.87 and 90%, respectively) shows the acceptable accuracy of soybean land separation in this study. In the study of land suitability for soybean cultivation, the results obtained from hierarchical analysis showed that the soil criterion had the greatest effect on the site selection of soybean cultivation with a coefficient of 0.52 with respect to both climate and topography factors. The results showed that most of the fields (about 87% of total) placed in suitable class and 13% placed in a relatively suitable class. In suitable areas for cultivation, despite having the best conditions for factors such as maximum temperature, average temperature, slope, aspect, height, soil texture, soil pH, phosphorus and soil salinity, soybean production is limited by factors such as precipitation (400 to 500 mm per year), minimum temperature (10 to 12 °C), phosphorus (8 to 10, 15 to 20 mg/kg soil). In these areas, maximum yield can be achieved by managing the mentioned factors and applying desirable agricultural management. In relatively suitable areas, limitations of nitrogen deficiency (less than 0.5 mg/kg soil), organic matter (less than 2%), salinity (above 6 dS/m), slope (more than 5%), restriction of soybean cultivation due to heavy soil texture (high percentage of soil clay), potassium (less than 100 mg/kg soil), phosphorus (more than 20 or less than 8 mg/kg soil), precipitation (less than 400 mm per year), minimum temperature (less than 10 °C), slope (more than 8%) and aspect (west and north) caused relatively high land restrictions for soybean cultivation. Compatibility analysis of the current soybean fields with the suitability maps indicated that about 99% of total cultivated lands are located in a suitable class, which demonstrates the proper selection of farm locations by the farmers. Conclusion: By considering the position of Golestan province in the production and area under soybean cultivation in the country, if it is possible to identify suitable soybean cultivation areas according to the environmental requirements of this product and identify the limitations created by the environment, more yield per area can be achieved, which will improve the agricultural economy and the level of income of the country.
Land Evaluation and Suitability
Moslem Zarrini Bahador; Javad Givi; Ruhollah Taghizadeh Mehrjerdi
Abstract
IntroductionWheat is one of the key cereals that provides a nutrition source to millions of people around the world. By conducting applied studies, the limitations of soil and climate that reduce the yield per unit area must be understood and solutions should be provided to address these limitations. ...
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IntroductionWheat is one of the key cereals that provides a nutrition source to millions of people around the world. By conducting applied studies, the limitations of soil and climate that reduce the yield per unit area must be understood and solutions should be provided to address these limitations. One of these strategies is a detailed study and spatial prediction of yield at points with different soil and climate characteristics. Models that predict crop yield can estimate the yield regarding climate, landscape, soil and management constraints. Considering the arid and semi-arid climate of Iran, the shortage of yield per unit area and the growing population, the country needs new research and strategies to increase yield per unit area. For this purpose, the first step is to examine the spatial variations of the yield. In the present study, the factors affecting the rainfed wheat yield in order of importance and efficiency of different methods of estimating spatial variations were investigated and the predicted yield of this crop was mapped digitally. Materials and MethodsThe study area, with an area of 6700 hectares is located in Badr watershed, around Ghorveh city, Kurdistan province, west of Iran. The mean annual air temperature is 12.1oC and the average annual precipitation is 345.8 mm. The soils of the area were classified in the orders of Entisols, Inceptisols and Mollisols and in 32 soil families, according to the last version of Keys to Soil Taxonomy. Based on hypercube technique, 125 observation points were selected, soil profiles were dug and described at these points and soil samples were collected from horizons of the profiles. Some physical and chemical characteristics of the soils were determined according to the standard laboratory methods. Rainfed wheat yield was measured at each side of one soil profile in a 1m×1m quadrangle. In the present study, in addition to geomorphological data, different types of auxiliary variables such as some of the primary and secondary derivatives of digital elevation model (DEM) and Landsat satellite image data were used. To find out the affecting auxiliary topographic and plantcover data on rainfed wheat yield prediction in order of importance,ReliefAttributeEval algorithm of WEKA software was used. Artificial neural network, decision tree Analysis, discriminant analysis, and averaging k-nearest neighbors are the models that were used in this research for prediction of rainfed wheat yield. Results and Discussion Calcium carbonate, organic carbon and coarse fragments, respectively with variability coefficients of 174.4, 62.4 and 61.3%, had the highest variation and pH, CEC and sand, respectively with 3.6, 16.9 and 20.3% variability coefficients showed the least variability in the soils of the studied area. In addition to geomorphological data, the parameters that were taken from the digital elevation model include elevation, slope percentage, slope aspect, slope curvature, slope surface curvature, longitudinal curvature, slope relative position, wetness index, multiresolution valley bottom flatness index, multiresolution ridge top flatness index, valley depth, channel network base level, modified catchment area, catchment slope, catchment slope aspect and catchment height. The environmental parameters that were taken from the Landsat 8 satellite imagery, include the normalized differential vegetation and the soil-adjusted vegetation indices. The ReliefAttributeEval algorithm in Weka software, in order of decreasing importance, identified geomorphology, relative slope position, longitudinal curvature, multi-resolution ridge top flatness index, slope, normalized differential vegetation index and soil-adjusted vegetation index as the most important factors affecting rainfed wheat production in the studied area. The amount of rainfed wheat yield was predicted by the models of artificial neural network, decision tree analysis, discriminant analysis, and averaging k-nearest neighbors. The error criteria for this prediction and a significant correlation between measured and estimated values of the rainfed wheat yield, indicate a higher accuracy for the averaging k-nearest neighbors model, compared to other models. The spatial distribution of the rainfed wheat yield, predicted by the averaging k-nearest neighbors model, was mapped. In the Badr watershed, the yields are continuously reduced towards the mountains. In this landscape, as the slope increases, depth and water storage capacity of the soil decrease mainly in the presence of Entisols. These soils are seen in the eastern, southern and western parts of the watershed. At lower elevations, the soils are deeper and are mainly Inceptisols. Rainfed wheat yield increases in the piedmont landscape, including hill, glacie and alluvial fan. Conclusion In order of decreasing importance, geomorphology, relative slope position, longitudinal curvature, multi-resolution ridge top flatness index, slope, normalized differential vegetation index and soil-adjusted vegetation index are the most important factors affecting rainfed wheat production in the studied area. The averaging k-nearest neighbors model has a higher accuracy for rainfed wheat yield prediction, compared to other models. In the Badr watershed, the rainfed wheat yield is continuously reduced towards the mountains in the eastern, southern and western parts, where mainly Entisols are present. The yield increases in the Inceptisols, located on the piedmont landscape.
Land Evaluation and Suitability
Javad Givi; Hojat Dialami; Mehdi Naderi Khorasgani
Abstract
Background and objective: In the assessment of land suitability, the land-production capacity is identified and the type of use is determined in proportion to that capacity. In this regard, the FAO approach has been used by many scholars in different parts of the world and Iran in land suitability assessment ...
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Background and objective: In the assessment of land suitability, the land-production capacity is identified and the type of use is determined in proportion to that capacity. In this regard, the FAO approach has been used by many scholars in different parts of the world and Iran in land suitability assessment studies. In this approach, the most commonly used method is the parametric method. The FAO approach uses Boolean logic to assess land suitability. This logic has been criticized by a number of land evaluation researchers. Because it does not take into account the continuous nature of the soil variations along the earth's surface and the uncertainty in the measurements. To overcome these shortcomings, the fuzzy analytical hierarchy process (FAHP) was presented to determine the land suitability classes. Land suitability should be determined based on a fuzzy analytical hierarchy process, in which, unlike the FAO method, unequal importance for different land characteristics and continuity of soil variations are considered. This research was carried out with the aim of qualitative land suitability evaluation in Dashtestan area, Bushehr province for Kabkab date palm (Phoenix dactylifera L. cv Kabkab) plantation, using two methods of FAO parametric (second root formula) and fuzzy analytical hierarchy process (FAHP) and comparing these two methods. Materials and methods: The study area is located in Dashtestan region, Bushehr province, Iran; between latitudes 29º 12΄ and 29º 31΄ N and longitudes 51º 09΄ and 51º 59΄ E. Its surface area is 23000 ha. The mean annual rainfall in the area is 250 mm and its mean annual temperature is 27 °C. The soil temperature and moisture regimes are hyperthermic and ustic, respectively. The physiographic unit which is river alluvial plain is very gently sloping. 80 % of the Kabkab date palm plantation is present in the study area. In order to achieve the objectives of this research, 50 date palm groves, each with an area of at least 0.5 ha and a palm of Kababab cultivar, aged 20 to 25 years, with the same management level and having different soil, were selected as observation points. Then a soil profile was dug randomely in each date palm grove, with dimensions of 1.5 (length), 1 (width) and 1.5 (depth) meters and described, using soil profile description guide. Soils were sampled from different horizons of the profiles and the required physical and chemical analyses were carried out on the samples, according to the standard laboratory methods. The drilling site was chosen to have a date palm tree in each of the four corners of the profile. The yield of the four trees located in four corners of each profile was measured and their average yield was considered as the final yield for the corresponding profile. Meteorological data was collected for a 10 year period from the nearest synoptic station (Borazjan station, Borazjan, Bushehr). Land indices were calculated, using soil and climatic data and parametric (second root formula) and fuzzy AHP methods. Weighted average of the climatic and the soil data was used and finally a land index was calculated for each soil profile. In the fuzzy AHP method, relative weight of each of the studied criteria was determined by analytical hierarchy analysis with establishment of pair wise matrix. Degree of membership for each soil and climatic criteria was also determined through membership functions and finally, land suitability classes were determined. At the end, accuracy of the methods was also compared. Landscape characteristics such as slope, drainage and soil depth were not considered in the land evaluation, because these characteristics did not show any limitation for the date production in the study area.Results: The results of qualitative land suitability evaluation based on fuzzy AHP method showed that 96.6 and 3.4 percent of the studied area are classified as S2 and S3, respectively. This is in the case that based on parametric (second root formula) method, 82 and 18 percent of the studied area are marginally suitable and non-suitable, respectively. According to these results, higher land suitability classes were obtained, based on fuzzy AHP than through parametric method. Correlation between the calculated land index and the measured yield, determined for the fuzzy AHP method was higher than the one obtained for the parametric method. This proves that the fuzzy AHP is a more appropriate method for land suitability assessment for Kabkab date palm plantation in the studied area than the parametric method (second root formula).Conclusion: According to the results of this research, the fuzzy AHP is a more appropriate method for qualitative land suitability evaluation than the parametric method (second root formula) for Kabkab date palm plantation in the studied area in Bushehr province.
Land Evaluation and Suitability
Anahid Salmanpour; Mohammad Hassan Salehi; Jahangard Mohammadi; Abdolmohammad Mehnatkesh; Sayyed-Hassan Tabatabaei
Abstract
Introduction One of the objectives of land evaluation method is determining the land suitability degree and class in case of making any changes, including causing elimination or limitation. Thus, as an example, if it could be possible to predict changes in soil salinity for the future, any changes in ...
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Introduction One of the objectives of land evaluation method is determining the land suitability degree and class in case of making any changes, including causing elimination or limitation. Thus, as an example, if it could be possible to predict changes in soil salinity for the future, any changes in land suitability class can be investigated based on the predicted variations over time.The most important crops in Neyriz area are wheat and barley. Unfortunately, over the past two decades, improper agricultural management caused reduction and salinization of irrigation water in this region. To this end, the present study was performed to investigate the possibility of changes in the class or degree of land suitability in case of variations in soil electrical conductivity due to irrigation with saline water in Neyriz, for the next 10 years. Materials and Methods In three soil map units in three regions consisting of Deh-Fazel, Tal-Mahtabi and Nasir Abad, wheat and barley fields were selected and representative pedons were excavated, described and classified. Soil and water samples were obtained and necessary analyses and soil humidity and salinity, hydraulic conductivity and bulk density and water electrical conductivity were determined. Crop yields were evaluated by 1×1 quadrate, soil surface layer hydraulic conductivity was carried out by guelph permeameter and the volume of irrigation water was measured according to pipe discharge in each farm. Soil retention curve was calculated for all soil layers using sand box and pressure plate. van Genuchten equation parameters were gained using RETC software. Afterward, solute transport modeling was done using the software Hydrus and its results were validated using four statistical parameters including Coefficient of determination (R2), Root Mean Square Error (RMSE), Model efficiency (EF) and Coefficient of Residual Mass (CRM) to investigate the possible variation in soil salinity during the next 10 years, the data of the studied period of the crop year between 1392 and 1393 was repeated for 10 years. Qualitative and quantitative land evaluation was performed by standards methods. Finally, the Hydrus results were compared with salinity maps of Neyriz area which were calculated and obtained in the previous research from Landsat images bands for the past 20 years. Results and Discussion Based on the results, climate suitability class in Neyriz area was suitable (S1) for wheat and relatively suitable (S2) for barley. The limiting factor for barley was the average of maximum temperature in the coldest month for barley. The soil suitability class was suitable (S1) for both crops (wheat and barley) in all farms. Therefore, the land suitability in the studied farmlands was S1 for the wheat and S2 for the barley. Results also revealed that the values for potential production were 10723 and 8677.5 Kg(grain)ha-1 for wheat and barley and for critical production were 1167 and 1297.6 Kg(grain) ha-1 for wheat and barley, respectively in the farms. Amongst the farmlands, only a barley farm which was located in Tal-Mahtabi had the S1 quantitative suitability class and others had S2. The results also showed that if all other conditions like volume and the quality of the irrigation water, precipitation, temperature and evaporation remain constant over the next 10 years, land suitability class will not change but land suitability degree will decrease gradually over time. The validation of the Hydrus model, based on the RMSE values, revealed that the predicted soil salinity and the observed value were very similar and the model had good ability in estimating and modeling soil salinity in the studied area. Comparing the results of modeling and soil salinity maps over the last 20 years have confirmed this trend. Based on the satellite salinity maps, the soil salinity of the studied fields has increased slightly from 2 to 4 dSm-1 between the years 1374 and 1393. Hence it can be concluded that the prediction of Hydrus model about gradual rise in predicted soil salinity and land suitability degree during the next 10 years is acceptable. Conclusion The present study showed that climate and land suitability class in Neyriz area was suitable and relatively suitable for wheat and barley, respectively. Solute transport modeling showed that land suitability degree will decrease gradually and soil quality will decline over time by assuming constant irrigation and precipitation condition over the next 10 years. Therefore, preventing the expansion of soil salinity and degrading agricultural lands require serious considerations of the authorities in the crisis Managements.
Land Evaluation and Suitability
V. Shahrokh; S. Ayoubi
Volume 37, Issue 1 , September 2014, , Pages 77-92
Abstract
This study was conducted to evaluate land suitability in Zarinshahr and Mobarakeh areas located in Isfahan Province using Analytical Hierarchy Process (AHP) technique. The hierarchy structure for evaluation was established to select the proper land use for 32 land units. Two alternative land utilization ...
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This study was conducted to evaluate land suitability in Zarinshahr and Mobarakeh areas located in Isfahan Province using Analytical Hierarchy Process (AHP) technique. The hierarchy structure for evaluation was established to select the proper land use for 32 land units. Two alternative land utilization types (the cultivation of wheat and rice) were selected at the lowest level. The intermediate levels of the hierarchy were comprised of seven criteria for evaluating the alternative land uses including soil, climate, gross income, water resources, market, physical environmental impacts and chemical environmental impacts. The weight for each element was calculated using 30 questionnaires which were completed by experts and software EXPERT CHOICE 2000. Then the overall weight for each land use was obtained by multiplying standardized attributes and local weights. The results showed that maximum and minimum calculated land indices for wheat cultivation were 77.4 (unit 2-3) and 18.86 (unit 4-9) and for rice 26.85 (unit 4-10) and 7.43 (unit 4-11), respectively. The climate suitability was the most important factor for selecting the proper land use, followed by soil suitability. The least importance was contributed to market accessibility. The inconsistency ratio related for all the matrices was 9 percent. The results of this study showed that the cultivation of wheat has higher performance for production in all land units.
