پديد آورندگان :
برومند ناصر نويسنده , جلالی وحیدرضا نويسنده استادیار گروه علوم خاك، دانشكده كشاورزی، دانشگاه شهیدباهنر كرمان jalali vahidreza , سنجری صالح نويسنده مربی گروه علوم خاك، دانشكده كشاورزی، دانشگاه جیرفت sanjari saleh
كليدواژه :
كريجينگ , نفوذسنج گلف , تغييرپذيري مكاني , جيرفت
چكيده فارسي :
ﭘﺎراﻣﺘﺮﻫﺎی ﻫﻴﺪروﻟﻴﻜﻲ ﺑﺮای درك ﺟﺮﻳﺎن رﻃﻮﺑﺖ در ﺧﺎك ﻏﻴﺮاﺷﺒﺎع ﺑﺴﻴﺎر ﻣﻬﻢ ﻣﻲﺑﺎﺷﻨﺪ و در ﻣﺪلسازی ﺟرﻳﺎن رطﻮﺑﺖ، آﻻﻳﻨﺪهها و عناصر غذایی در ﺧﺎك، اﺳﺘﻔﺎده میﮔﺮدﻧﺪ. مدیریت خاك و كاربری اراضی، با تأثیر بر ویژگیهای خاك میتوانند مستقیما خصوصیات هیدرولیكی خاك را تغییر دهند. هدف اصلی این پژوهش، ارزیابی اثر كاربریهای مختلف اراضی بر هدایت هیدرولیكی اشباع خاك (ks) بود. این پژوهش در 100 هكتار از اراضی منطقه خضرآباد در 25 كیلومتری جنوب شهرستان جیرفت انجام گردید. به كمك نرمافزار Google earth و Arc GIS، منطقه به بلوكهایی با ابعاد 1000×1000 متر شبكهبندی شد. مختصات جغرافیایی مراكز هر بلوك به عنوان محل نمونهبرداری انتخاب و (ks) توسط دستگاه نفوذسنج گلف تعیین گردید. برای انجام درونیابی و تهیه نقشههای مكانی، از روش كریجینگ استفاده شد. نتایج نشان داد كه (ks) با همبستگی مكانی قوی از تغییرپذیری مكانی بالایی برخوردار است كه این تغییرات در كاربری باغ بیشترین و در كاربری بایر كمترین مقدار را در برگرفتند و دلیل این امر نوع كاربری و تكنیك مدیریتی بسته به نوع كاربری و نشاندهنده تأثیر كاربری اراضی بر (ks) بود. الگوی پراكنش ks با متغیر شن همروند و با الگوی پراكنش رس در خلاف جهت دیده شد كه همین امر، تأثیر ویژگیهای فیزیكی خاك را بر (ks) نشان داد. با توجه به پارامترهای ارزیابی MBE (میانگین انحراف خطا)، MAE (میانگین قدر مطلق خطا) و CRM (ضریب جرم باقیمانده)، بهترین مدل برازش داده شده به ks، مدل گاوسی بود و ویژگیهای خاك نظیر ks، دارای تغییرپذیری مكانی وابسته به مقیاس نمونهبرداری بودند. به¬طور كلی مشخص گردید كه كاربریهای اراضی، بسته به نوع كاربری و تكنیك مدیریتی مورد استفاده، با تأثیر بر خصوصیات خاك، باعث تغییر در ks میشوند.
چكيده لاتين :
Introduction: The hydraulic parameters are very important for perception of water flow in unsaturated soil and using pollutants and nutrient flow modeling in the soil. The effect of soil management and land uses on soil parameters can directly alter soil hydraulic parameters. Because of interactive and tight relationship between soil and plant covering, studying the soil parameters and its changing during different land uses is vital. The main object of this study was evaluating the effects of different land uses on soil saturated hydraulic conductivity.
Materials and Methods: This study was performed in about 100 hectare fields of Khezrabad region in the 25 km south of the Jiroft county located in south eastern of Kerman province. The region gridded into 1000×1000 meter grids with use of Google earth and Arc GIS software, sampling places has been selected in the center of each grid. Measurement of soil saturated hydraulic conductivity done with the Guelph permeameter in the center of each grid. For the measurement of physical parameters such as bulk density, percent of sand, silt, clay in the laboratory, sampling done from 30cm depth so samples transferred to the laboratory. In this study in order to ensure the normal distribution of variables, the Kolmogorov-Smirnov test has been used with SPSS14 software. The Kriging method was used for interpolation and providing spatial maps.
Results and Discussion: Agriculture, garden and sterile lands were selected for the object of the present study. The study area includes garden, agriculture and sterile lands at the same time. The study area contains 3 classes of soil texture as: sandy, sandy-loamy and loamy-sand. The results showed that soil saturated hydraulic conductivity (ks) with strong spatial correlation had a high spatial variability. The fluctuation ranges of its values changes from 0.02 to 2325.71 cm per hour. The lowest value of ks was observed in garden land (by having the lowest value of soil bulk density) while the highest value was observed in sterile land (by having the highest value of soil bulk density). The results also showed that semi-variogram of garden, agriculture and sterile land were not the same, and it may gain from different types of agricultural operations, type of land use and various textures so that from garden land to sterile land, the soil texture becomes lighter and level of saturated hydraulic conductivity changes completely different. Several reasons maybe considered including soil different structures due to different type of agricultural operations and type of cultivation for every single land use. The change process of saturated hydraulic conductivity for garden and agricultural land was identical and for both the Gaussian model were fitted. According to the nugget effect ratio to the sill (C0/C0+C), variability of saturated hydraulic conductivity in agricultural land has a stronger spatial correlation (0.0006) and also has a higher radius of effect range (11740m) compared to garden land in which the ratio of the nugget effect ratio to sill is 0.28 and its radius of effect range is 8030 meters. the radius of effect range in sterile land had the lowest value among studied land uses, though having strong correlation, the effect range of this correlation is low and, compared to other lands, the changes process was more randomly obtained. To mention the reasons of this finding it is possible to refer to area of the sterile land, dispersion of the sampling points and long distance between pair points. The lowest spatial correlation belonged to garden land with middle spatial correlation class and the reason can be explained as due to increase of sand, decrease of clay and silt, bulk density of soil increases as well and leads to increase of coarse pores and consequently increasing saturated hydraulic conductivity of soil.
Results showed that soil saturated hydraulic conductivity (ks) with strong spatial correlation has high spatial variability and these variability consist lowest quantity in the garden lands and highest quantity in the sterile lands. The distribution pattern of Ks was seen similar to the sand and the soils bulk density, this pattern was opposite to the clay distribution pattern, this indicates the effect of soil physical parameters on saturated hydraulic conductivity.
Conclusion: According to the evaluation parameters CRM, MAE and MBA, Gaussian model is the best fitted model to soil saturated hydraulic conductivity data and soil parameters such as saturated hydraulic conductivity consist spatial variability related to sampling scale. The factors of land type and consequently type of land cultivation, lands management system, type of agricultural operations, soil particles size and bulk density of soil have the most impact on variability of Ks.