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Öğe An integrated framework to identify and map gullies in a Mediterranean region of Turkey(Taylor & Francis Ltd, 2022) Kilic, Mirac; Gundogan, Recep; Gunal, Hikmet; Budak, MesutThis research introduces a scientific methodology to identify areas affected by gully erosion using Geographic Object Based Image Analysis (GEOBIA) and Random Forest (RF) supervised machine learning. The GEOBIA and RF were applied in Besni district, which has a Mediterranean climate, of Adiyaman province in Turkey by including many factors in the model. Estimation Scale Parameter (ESPII) algorithm was used in the segmentation phase. The novelty of this study is the implementation of RF supervised classification algorithm to classify a large number of objects determined after the segmentation process, due to the large size of the study area. Therefore, open access data has been evaluated with high classification accuracy without the need for labor. Precision, Recall and F1-Score values were calculated using true positive (TP), true negative (TN), false positive (FP) and false negative (FN) values based on field observations and Google Earth images of the study area. The TP, TN, FP and FN values were 0.90, 0.95 and 0.92, respectively. In addition, a Kappa-index was calculated as 0.88. The gully erosion map obtained using aforementioned methodology can be used to take necessary measures to prevent further degradation and plan sustainable land uses.Öğe Combining spatial autocorrelation with artificial intelligence models to estimate spatial distribution and risks of heavy metal pollution in agricultural soils(Springer, 2023) Gunal, Elif; Budak, Mesut; Kilic, Mirac; Cemek, Bilal; Sirri, MesutInformation on spatial distribution and potential sources of heavy metals in agricultural lands is very important for human health and food safety. In this study, pollution degree of lead (Pb), cadmium (Cd), and nickel (Ni) in Yuksekova Plain, located on the border in the southeastern part of Turkey, was evaluated by geoaccumulation index (Igeo), modified contamination factor (mCdeg), and Nemerow pollution index (PINemerow) combined with spatial autocorrelation using deep learning algorithms. A total of 304 soil samples were collected from two different depths (0-20 and 20-40 cm) in the study area, which covered 17.5 thousand ha land. Covariates were determined for spatial distribution models of Pb, Cd, and Ni by factor analysis (FA). Spatial distribution models for surface soils were developed using pedovariables (silt, sand, clay lime, organic matter, electrical conductivity, pH, Ca, and Na) determined by the FA and Igeo and mCdeg values by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models. The estimation success of models for different depths was assessed by root mean square error (RMSE), mean absolute percent error (MAPE), and Taylor diagrams. The RMSE and MAPE values showed a strong correlation between heavy metal contents and the covariates. The RMSE values of ANN-Ni0-20, ANN-Ni20-40, ANN-Pb0-20, ANN-Cd0-20, and ANN-Cd20-40 models (0.01240, 0.07257, 0.0039, 0.00045, 0.00044, and 0.04607, respectively) confirmed the success of the models. Likewise, the MAPE values between 0.2 and 8.5% indicated that all models were very good predictors. In addition, the Taylor diagrams showed that the estimation performance of ANFIS and ANN models are compatible. The Igeo(Ni) and Igeo(Pb) values in both models at both depths indicated that strongly to extremely polluted (4-5) areas are quite high in the study area, while the Igeo(Cd) values revealed that unpolluted areas are widespread. The mC(deg) index value showed a moderate to high contamination at the first depth, while very high contamination at the second depth in most of the study area. Spatial distribution of PINemerow revealed that moderate pollution (2-3) is common in both soil depths of the study area. The PINemerow of subsurface layer was between 0.91 and 1 (warning limit class) in a small part of the study area. The results showed that vertical mobility of heavy metals is closely related to pedovariables. In addition, the ANN and ANFIS models are capable of exhibiting the heterogeneity in the spatial distribution pattern of high variation in the data. Thus, the locations with extreme contamination have been accurately determined. The pollution indices calculated considering the commonly used international reference values revealed that heavy metal pollution in some part of the study area reached the detrimental levels for human health and food safety. The results suggested that the pollution indices were more successful than simple heavy metal concentrations in interpreting the pollution risk levels. High-resolution spatial information reported in this study can help policy makers and authorities to reduce heavy metal emissions of pollutants or, if possible, to eliminate the pollution.Öğe CONCENTRATION OF HEAVY METALS IN SOILS ALONG THREE MAJOR ROADS OF SULAIMANI, NORTHEAST IRAQ(Carpathian Journal of Earth and Environmental Sciences, 2018-04-23) Sürücü, Abdulkadir; MOHAMMAD, Dler Mustafa; Günal, Elif; Budak, MesutHeavy metal contamination of agricultural soils resulting from vehicle emissions is a cause of serious concern due to the potential health impacts of transferring to food chain. In this study, heavy metal concentration of roadside soils along three major roads connecting the city of Sulaimani to surrounding cities were determined. Twenty soil samples from each side of three roads were collected at 1 m, 15 m, 25 m and 50 m distances from road edges. The heavy metals of Cr, Co, Pb, Cd and Ni were analyzed by acid digestion. Heavy metal pollution of roadside soils was assessed using three different environmental indices; enrichment factor (EF), contaminant factor (CF) and contamination degree (CD). Heavy metals concentrations of roadside soils were significantly different (P?0.01) among three major roads and usually decreased with increased distance from the roads. The highest concentrations were 268.56, 9.56, 134.16, 3.99 and 179.20 mg kg-1 for Cr, Co, Pb, Cd and Ni, respectively. The results showed that mean concentrations of all heavy metals determined were significantly higher than the global background values of heavy metals. The order of heavy metal contamination based on CF values in Arbat road was Cr?Ni?Pb?Cd?Co, in Kirkuk road Ni?Cr?Cd?Pb?Co, and in Mergapan road Pb?Ni?Cr?Cd?Co. Significant positive correlations between Ni and Co in Arbat (r=089) and Kirkuk (r=0.58) roads, Ni and Pb in Mergapan road (r=0.70), and Cd and Pb in Kirkuk road (r=0.76) revealed their common source in the studied environments. The roadside soils in the region are being extensively used for agricultural production. Therefore, the increased concentration of Cr, Pb, Cd and Ni in roadside soils should be carefully monitored and necessary precautions should be taken to prevent further accumulation in roadside soils.Öğe Dicle Havzası Toprak Özelliklerinin Yersel Değişimlerinin Jeoistatistik ve Coğrafi Bilgi Sistemleri ile Belirlenmesi ve Haritalanması(Türkiye Tarımsal Araştırmalar Dergisi, 2018-03-12) Budak, Mesut; Günal, Hikmet; Çelik, İsmail; Acar, Nurullah; Sirri, MesutToprak özelliklerinin mesafeye bağlı değişkenliklerinin belirlenmesi, incelenmesi ve haritalanması yoğun tarımsal üretim yapılan arazilerde uygun amenajmanların geliştirilmesi ve üretimin sürdürülebilirliğinin sağlanması açısından son derece önemlidir. Bu çalışmada ülkemizin su rezervlerinin büyük bir kısmının yer aldığı, önemli sulama projelerinin gerçekleşmekte olduğu Dicle Havzası’nda bir kısım fiziksel ve kimyasal toprak özellikleri belirlenmiş, mesafeye bağlı değişkenlikleri modellenmiş ve haritalanmıştır. Toprak örneklemeleri, Diyarbakır ile Siirt illeri arasında 5 x 5 km gridlere ayrılmış 4.341 km2’lik alanda her gridin yaklaşık köşesinden toplam 175 noktada 0-20 cm derinlikten alınmıştır. Toprak özelliklerinin 5 km’den kısa mesafelerdeki değişimlerinin daha doğru tahmin edilebilmesi amacıyla ardışık iki gridin köşe noktaları arasında 250 m, 750 m ve 1750 m mesafelerden de 33 toprak örneği alınmıştır. Alınan bozulmuş örneklerin tekstür (kum, kil ve silt), organik madde, kireç, toprak reaksiyonu, elektriksel iletkenlik, alınabilir fosfor ve potasyum analizleri yapılmıştır. Mesafeye bağlı değişkenliğin modellenmesi ile örneklenme yapılmayan noktaların ilgili özellikleri tahmin edilmiş ve yersel değişim haritaları oluşturulmuştur. Çalışma alanında en düşük değişkenliğin pH (% VK= 3.9) ve en yüksek değişkenliğin ise alınabilir fosfor (% VK= 137.77) konsantrasyonunda olduğu görülmüştür. En yüksek range değerine sahip toprak özelliği elektriksel iletkenlik (135.4 km) iken en küçük range değeri pH (4.74 km) için elde edilmiştir. Her bir özelliğin en düşük ve en yüksek olduğu yerlerin rahatlıkla tespit edilebildiği toprak haritaları, uygun amenajman yöntemlerinin belirlenmesi, sorunların giderilmesi ve girdilerin en uygun kullanımı açısından son derece yararlı araçlardır.Öğe Effects of long-term conventional and conservational tillage systems on biochemical soil health indicators in the Mediterranean region(Taylor & Francis Ltd, 2022) Acir, Nurullah; Gunal, Hikmet; Celik, Ismail; Barut, Zeliha Bereket; Budak, Mesut; Kilic, SerefImproved soil health is essential to sustain agricultural production. Therefore, understanding the effects of management on soil health is crucial to implement new agricultural practices. This study aimed to assess the effects of long-term tillage systems on biochemical indicators of a Typic Haploxerert soil under winter wheat-soybean-corn rotation in the Mediterranean region of Turkey. The experiment consisted of two conventional (CT), three reduced (RT), no-tillage (NT), and a strategic tillage practice. The biochemical indicators were total nitrogen (TN), total carbon (TC), soil organic carbon (SOC), microbial biomass carbon (MBC), potential mineralizable nitrogen (PMN), microbial quotient (qM), beta-glucosidase enzyme activity (BGA), and carbon sequestration (Cs) potential. The SOC significantly decreased with the increased tillage intensity, while the tillage had a little effect on PMN, with its highest concentration (78.2 mg kg(-1)) occurring in the NT. The qM was the only indicator found to be higher under CT than RT and similar to the NT. The BGA peaked in NT which was 460.2 and 536.3% higher than that of the CT. The results showed that SOC, MBC, PMN, BGA and Cs were enhanced with the NT and RT systems which favor sustainability of agricultural production.Öğe Ekosistem Servislerinde Toprağın Rolü(2022) Bülbül, Safiye; Sürücü, Abdulkadir; Günal, Hikmet; Budak, MesutEkosistemin yapısının ve işlevlerinin insan refahına katkıları ekosistem servisleri olarak tanımlanmaktadır. Toprak, “ekosistem servisleri” olarak adlandırılan, tedarik etme (örneğin tatlı su, odun, yiyecek ve lif), düzenleme (örneğin iklim, erozyon ve sel), kültürel (örneğin estetik veya manevi değerler) ve destekleme (örneğin bitkilere, hayvanlara ve insan altyapısına fiziksel destek) gibi insan refahı ve sürdürülebilir sosyo-ekonomik kalkınma için önemli olan çok çeşitli mal ve hizmetlerin sağlanmasına katkı sunmaktadır. Litosfer, biyosfer, hidrosfer ve atmosfer arasında ara yüz olan toprağın ekosistem servislerinin yerine getirilmesindeki çok fonksiyonlu rolünü anlamak son derece önemlidir. Topraklar ekosistem servislerinin yerine getirilmesinde diğer ekosistemler ile birlikte görev almaktadır. Ekosistem servisleri, çoklu ekosistemler arasındaki etkileşimin sonucu olduklarından, ekosistem servislerini sadece toprağa bağlı olarak tanımlamak yeterli olmayacaktır. Tarımsal faaliyetler ile gıdanın üretilmesi, toprak özelliklerinin yanında, yağış, güneş ışığı ve sıcaklık gibi iklimsel değişkenler ve ekim veya gübreleme gibi insan müdahaleleri ile mümkün olabilir. Bu nedenle, ekosistem servislerinin sağlanmasında topraklar ancak bazı servislerin ne kadar iyi sağlanacağını belirleyen önemli bir ekosistem olarak görev yapmaktadır. Bu çalışmada, diğer ekosistemler ile birlikte insan refahına katkı sağlayan toprağın ekosistem servislerinin gerçekleşmesindeki önemi, yayınlanan güncel araştırmalardan derlenerek ortaya konulmuştur.Öğe Environmental sensitivity to desertification in northern Mesopotamia; application of modified MEDALUS by using analytical hierarchy process(Arabian Journal of Geosciences, 2018-08-09) Budak, Mesut; Günal, Hikmet; Çelik, İsmail; Yıldız, Hakan; Acir, Nurullah; Acar, MertPoor management, low vegetation cover, and severe erosion are undermining the stability and sustainability of lands. In this study, modified Mediterranean Desertification and Land Use (MEDALUS) method was used to identify environmentally sensitive areas (ESA) to desertification in Tigris Basin, Turkey. Soil samplings (0–20 cm) and field observations were conducted within 3.752 km2 land. Biophysical and anthropogenic parameters of sampling locations have been integrated and processed by geographic information systems obtaining soil, climate, vegetation, and management quality indexes. Additional six parameters for soil quality and one for management quality were used to adopt MEDALUS to the context of Tigris Basin. The weights for parameters and indicators were calculated using analytical hierarchy process (AHP). Tigris Basin was classified into one fragile and two critical areas using original method, whereas one fragile and three critical classes were defined with the modified method. In the original method, fragile areas represented 5.65% and low-degree critical areas 24.49% and moderate critical areas 69.86% of the study area, which are needed to be monitored for severe land degradation. Modifying MEDALUS allowed to define highly critical areas (51.41%) which have not been detected in the original method. The critical areas are primarily used for field crops with extensive tillage, medium degree of plant cover, low drought resistance, and erosion along with low management quality due to the lack of required environmental protection. The results revealed that adaptation of new parameters and weighting in MEDALUS improved the ability of classifying ESAs for a regional scale to desertification.Öğe Evaluating the long-term effects of tillage systems on soil structural quality using visual assessment and classical methods(Wiley, 2020) Celik, Ismail; Gunal, Hikmet; Acar, Mert; Acir, Nurullah; Barut, Zeliha Bereket; Budak, MesutCurrent agricultural practices and their impacts on the sustainability of crop production can be evaluated by simple and reliable soil structure assessment tools. The study was conducted to determine the effects of long-term (2006-2017) tillage systems on structural quality of a clayey soil using the visual evaluation of soil structure (VESS) and classical field and laboratory measurements. A field experiment with seven tillage systems, representing both traditional and conservation tillage methods, was conducted on a clayey soil in the Cukurova region, Turkey. Soil samples from 0-10, 10-20 and 20-25 cm depths were analysed for mean weight diameter (MWD), porosity and organic carbon. Penetration resistance (PR) was determined in each treatment plot. The VESS scores (<2) of upper 0-5 cm indicated a good structural quality for all tillage systems. The VESS scores were positively related to PR and MWD and negatively to macroporosity (MaP) and total porosity. In reduced and no-till systems, poorer soil structures were observed in subsurface layers where firm platy and angular blocky structures were defined. Mean VESS score (3.29) in 20-25 cm depth where PR was 3.01 MPa under no-till indicated a deterioration of soil structural quality; thus, immediate physical interventions would be needed. Lower VESS scores and PR values under strategic tillage which was created by ploughing half of no-till plots in November 2015 indicated successful correction of compaction caused by long-term no-till. The results suggest that the VESS approach is sensitive and useful in distinguishing compacted layers within the topsoil.Öğe Gökhöyük Tarım İşletmesi Arazilerinin İdaresinde Jeoistatistik ve Coğrafi Bilgi Sistemleri Tekniklerinin Kullanımı(Türkiye Tarımsal Araştırmalar Dergisi, 2019-02-26) Budak, Mesut; Budak, NurullahArazi kullanımı, ana materyal ve topoğrafyaya bağlı olarak büyük değişkenlik gösteren toprak özelliklerinin mesafeye bağlı değişkenlikleri; toprağın verimliliği, kalitesi ve genel olarak sürdürülebilirliğini önemli düzeyde etkilemektedir. Bu çalışma; yaklaşık 1900 hektar genişliğindeki Gökhöyük Tarım İşletmesi arazilerinin bir kısım toprak özelliklerinin mesafeye bağlı değişkenliklerini belirlemek, haritalamak ve işletme arazilerinin sürdürülebilir kullanımlarını etkileyecek sorunların tespit edilerek çözüm önerilerini ortaya koymak amacı ile gerçekleştirilmiştir. Bu amaçla, çalışma alanını temsil edecek şekilde 63 noktadan ve 4 farklı derinlikten (0-30, 30-60, 60-90 ve 90-120 cm) toprak ve 19 noktadan da taban suyu örnekleri alınmıştır. Toprak örneklerinde elektriksel iletkenlik (EC), pH, kil, kum ve silt içerikleri ile hidrolik iletkenlik değerleri; taban suyu örneklerinde ise pH ve EC değerleri belirlenmiştir. Klasik istatistik ve jeoistatistik yöntemler ile çalışılan özelliklerin, arazideki genel durumu ve mesafeye bağlı değişkenlikleri karakterize edilmiştir. Araştırma sonucuna göre, yüksek kil içeriğine sahip olan hem yüzey hem de yüzey altı topraklarında hidrolik iletkenlik değerleri (<20 mm h-1) oldukça düşük bulunmuştur. Bitki besin elementi alımı üzerine önemli bir etkisi olan pH değerlerinin tüm derinliklerde ve arazinin önemli bir kısmında 8.5’in üzerinde; çalışma alanının orta kısmında bir hatta yer alan toprakların 60-120 cm derinliğinde EC değerleri (>4 dS m-1) sorun oluşturabilecek düzeylerde olduğu tespit edilmiştir. Bu bölgedeki su örneklerinin de EC değerleri 20 dS m-1’nin üzerinde olduğu görülmüştür. Kurak ve sıcak dönemlerde tuz içeriği yüksek taban suyunun kapilarite ile yüzeye taşınması, toprağın üretkenlik fonksiyonuna zarar verebilir. Toprak özelliklerinin mesafeye bağlı değişimini gösteren haritaların kullanımı ile çiftlik arazisinde bitkisel üretimin geliştirilmesine ve toprak kalitesinin iyileştirilmesine katkı sağlayacak kararların doğru bir şekilde alınması mümkün olabilecektir.Öğe IMPORTANCE OF SPATIAL SOIL VARIABILITY FOR LAND USE PLANNING OF A FARMLAND IN A SEMI-ARID REGION(Fresenius Enivromental Bulletin, 2018-04-15) Budak, MesutAssessing the spatial variability of soil properties is vital in proper planning of agricultural farmlands. The aim of this study is to determine and map the spatial variability of important physical and chemical soil properties using geoistatistical models for land use planning of a farm located in Thrace region of Turkey. Two hundred fifty-four surface and subsurface soil samples were collected from at approximately the corners of 150m x 150m size grids cells. The land area of study area was 557 ha and used for what and sunflower production. Soil samples were analyzed for particle size distribution, soil reaction (pH), electrical conductivity (EC), organic matter (OM), lime content (CaCO3), available phosphorus (P) and extractable potassium (K). Penetration resistance was also measured at each sampling point. Soil pH ranged from 4.46 to 8.20 in surface and 4.01 to 8.30 in subsurface soils. Sand content was the least variable (CV=11.5% and 13.9% for surface and subsurface) soil property, while the variability of P content (CV=105.9 and 119.8%) was higher than the rest of the soil properties. The lowest range value was obtained for P content (113 and 134 m) and the longest-range value was for available K content (5899 and 6099 m) of soils. Spatial distribution maps helped to identify and deliniate the zones need to be limed, deficient in available P and compacted zones within the study area. Sustainable management strategies in a farm can be planned and implemented using the information obtained from spatial structures and maps of major soil characterics.Öğe Improvement of spatial estimation for soil organic carbon stocks in Yuksekova plain using Sentinel 2 imagery and gradient descent-boosted regression tree(Springer Heidelberg, 2023) Budak, Mesut; Gunal, Elif; Kilic, Mirac; Celik, Ismail; Sirri, Mesut; Acir, NurullahCarbon sequestration in earth surface is higher than the atmosphere, and the amount of carbon stored in wetlands is much greater than all other land surfaces. The purpose of this study was to estimate soil organic carbon stocks (SOCS) and investigate spatial distribution pattern of Yuksekova wetlands and surrounding lands in Hakkari province of Turkey using machine learning and remote sensing data. Disturbed and undisturbed soil samples were collected from 10-cm depth in 50 locations differed with land use and land cover. Vegetation, soil, and moisture indices were calculated using Sentinel 2 Multispectral Sensor Instrument (MSI) data. Significant correlations (p <= 0.01) were obtained between the indices and SOCS; thus, the remote sensing indices (ARVI 0.43, BI -0.43, GSI -0.39, GNDI 0.44, NDVI 0.44, NDWI 0.38, and SRCI 0.51) were used as covariates in multi-layer perceptron neural network (MLP) and gradient descent-boosted regression tree (GBDT) machine learning models. Mean absolute error, root mean square error, and mean absolute percentage error were 3.94 (Mg C ha (-1)), 6.64 (Mg C ha(-1)), and 9.97%, respectively. The simple ratio clay index (SRCI), which represents the soil texture, was the most important factor in the SOCS estimation variance. In addition, the relationship between SRCI and Topsoil Grain Size Index revealed that topsoil clay content is a highly important parameter in spatial variation of SOCS. The spatial SOCS values obtained using the GBDT model and the mean SOCS values of the CORINE land cover classes were significantly different. The land cover has a significant effect on SOC in Yuksekova plain. The mean SOCS for continuously ponded fields was 45.58 Mg C ha(-1), which was significantly different from the mean SOCS of arable lands. The mean SOCS in arable lands, with significant areas of natural vegetation, was 50.22 Mg C ha(-1) and this amount was significantly higher from the SOCS of other land covers (p<0.01). The wetlands had the highest SOCS (61.46 Mg C ha(-1)), followed by the lands principally occupied by natural vegetation and used as rangelands around the wetland (50.22 Mg C ha(-1)). Environmental conditions had significant effect on SOCS in the study area. The use of remote sensing indices instead of using single bands as estimators in the GBDT algorithm minimized radiometric errors, and reliable spatial SOCS information was obtained by using the estimators. Therefore, the spatial estimation of SOCS can be successfully determined with up-to-date machine learning algorithms only using remote sensing predictor variables. Reliable estimation of SOCS in wetlands and surrounding lands can help understand policy and decision makers the importance of wetlands in mitigating the negative impacts of global warming.Öğe Land suitability assessment for rapeseed potential cultivation in upper Tigris basin of Turkiye comparing fuzzy and boolean logic(Elsevier, 2024) Budak, Mesut; Kilic, Mirac; Gunal, Hikmet; Celik, Ismail; Sirri, MesutAssessment of land suitability is a prerequisite for the conservation and maintenance of land productivity and the improvement of land use and management systems. This study assessed land suitability for rapeseed (Brassica napus L.) production using topography, climate, and soil data by analytical hierarchy process (AHP) and the Mamdani Fuzzy Inference System (MFIS). The study area covers 3737 km2 of land in the Diyarbakir province of southeastern Turkiye. The weights of topography, soil and climate factors in AHP were determined by expert opinions and the information in related literature. They were included in the whole process, mainly membership functions and rule base stages in the MFIS. The highest weighted factor was slope (0.264), followed by altitude (0.121), annual average temperature (0.114) and soil texture (0.112). The MFIS-based land suitability assessment indicated that the proportions of moderately (S2), marginally (S3) and currently not suitable (N1) land classes in the study area were 71.35%, 18.75% and 9.9%, respectively. The AHP results showed that 98.94% of the land was S3, and 1.06% was N1. The compatibility of AHP and MFIS methods in N1 land units was 96.05%, while the agreement for S2 and S3 land classes was not sufficiently high. The suitability of rapeseed cultivation has been more sensitively assessed by the fuzzy continuous classification obtained by the MFIS method.Öğe MEDALUS Modelinin Çölleşmeye Hassas Alanların Belirlenmesi Ve İzlenmesinde Dicle Havzasına Adaptasyonu(2018) Budak, Mesut; Acir, Nurullah; Yıldız, Hakan; Cemek, Bilal; Çelik, İsmail; Gültekin, UfukArazi bozulması ve çölleşmeye karşı hassas alanların belirlenmesinde kullanılan modellere bölgeye özgü indikatör ve parametrelerin ilave edilmesinde bölgeyi tanıyan uzmanların görüşlerinin dâhil edilmesi çıktıların güvenilirliğini artırmak için oldukça önemlidir. Bu çalışmanın amaçları, i.) yarı kurak iklime sahip yukarı Dicle Havzası'nın çevreye hassas alanların belirlenmesi için Akdeniz Çölleşme ve Arazi Kullanımı (MEDALUS) modeline havzaya özgü yeni indikatör/parametrelerin ilave etmek, ii.) uzman görüşü içeren Analitik Hiyerarşi Süreci (AHP) yaklaşımını modele entegre etmek ve iii.) çevreye hassas alan indeksi ve indikatörlerin yersel değişim haritalarını oluşturmaktır. Çalışma, toplam genişliği 9847.29 km2 olan binlerce yıldır gıda ve giyecek gereksinimini karşılamak amacı ile kullanılan ve önemli düzeyde arazi bozulması problemlerinin olduğu Dicle Havzasının kuzey-batı bölümünü kapsamaktadır. Arazilerin bozulmaya hassasiyeti, esnekliği, uygulamanın düşük maliyetli ve kolay uygulanabilirliği nedeni ile tüm dünyada yaygın olarak kullanılan modifiye edilmiş MEDALUS modeli ile tahmin edilmiştir. Toprak kalitesi (TK), iklim kalitesi (İK), vejetasyon kalitesi (VK), amenajman kalitesi (AK) ve yer altı suyu kalitesi (YSK) indikatörleri arazi bozulmasının temel bileşenleri olarak tanımlanmıştır. Arazi çalışmaları için çalışma alanı 5km * 5km kare gridlere ayrılmıştır. Gridlerin köşe noktaları arası mesafede olan 5 km’den daha kısa mesafelerdeki değişkenlikleri tanımlayabilmek için grid köşeleri arasında 250m, 750m ve 1750m mesafelerde örnekleme noktası olacak şekilde toplam 22 adet örnekleme hattı yerleştirilmiştir. Toplamda 452 noktadan 0-20 cm derinlikten toprak örneği alınmıştır. Her indikatör/parametre için 1.0 ile 2.0 (çölleşmeye karşı düşük, orta düzeyde ve yüksek düzeyde hassasiyeti ifade eden) arasında değişen skorlar verilmiştir. Her bir indikatör/parametrenin çölleşmeye olan katkısını ifade etmek için uzman görüşü ile AHP yöntemi kullanılarak ağırlıklar hesaplanmıştır. Ağırlık ilaveli skorlara göre arazi bozulması ve çölleşme bakımından çevreye hassas alanlar belirlenmiştir. Bu çalışmada, bölge için önemli olduğundan YSK modele yeni bir indikatör olarak ilave edilmiştir. Ayrıca, bölgesel koşullar ile ilişkili oldukları için TK ve AK içerisine de bazı alt indikatörler ilave edilmiştir. Beş indikatör ile birlikte 28 alt-indikatörün analizi ile çalışma alanının %1.95’inin yüksek, % 55.17’sinin orta ve % 21.64’ünün ise düşük kritik düzeyde çölleşmeye hassas olduğu belirlenmiştir. Geri kalan alanın tamamı neredeyse bozulmaya karşı kırılgan (% 11.64’ü yüksek, % 6.64 orta ve % 2.75’i düşük düzeyde kırılgan) olarak tanımlanmıştır. Kritik düzeyde hassas olan araziler genellikle çalışma alanının güney kısmında ve tarımsal üretimin yoğun bir şekilde yapıldığı bölgelerde yer almaktadır. Bulgular modifiye edilmiş MEDALUS yaklaşımının çölleşmeye hassas alanları belirlenmede etkin olduğunu göstermiştir. Bu çalışma ile arazi bozulması bakımından öncelikli olarak izlenmesi gereken yerlerin nereler olduğu belirlenmiş ve aynı zamanda bölgede arazi bozulması ve çölleşmenin nedenlerini de ortaya koymuştur.Öğe Modeling and mapping of spatial variability of soil micro nutirient elements in research and application areas of Bingol University(2019) Sürücü, Abdulkadir; Gökmen, Veysel; Gündoğan, Recep; Budak, MesutLack of microelements in the soil negatively affects the yields in areas where intensive plant production is performed. Studies on spatial variability of essential micronutrients in Turkey's agriculturally intensive areas were limited. The aim of this study is to determine the amount of microelement contents of soils of the research and application farm of Bingöl University under different land uses, and to model and map the distance. depended spatial variability The total area of the study field is 67 ha. The study area was divided into 100 X 100 m grids and soil samples were taken from 0-30 cm depth at the corner of from grids at 64 sites. In addition, 24 of soil samples were taken from 5, 25 and 60 m intermediate intersections in order to determine the change of soil properties at distances less than 100 m. The contents of soil extractable zinc (Zn), copper (Cu), manganese (Mn) and iron (Fe) were analyzed, and semivariograms were prepared for each micro element content, and distribution maps were generated by using kriking methods. According to obtained results, it was determined that iron (CV = 31.25%) and copper (CV = 27.38%) showed modest variability while Manganese (CV = 44.30) and Zinc (CV = 47.72) showed high variability. Spatial distributions maps for each micronutrients determined were obtained after semivariograms were formed using suitable model parameters. The distrubitons maps showed that all microelements had a important varaibility depending on the distance, especially as the microelement contents of the soil increased relatively from the south-east to the north-west directions.Öğe Modeling and mapping the spatial variability of soil micronutrients in the Tigris basin(Elsevier, 2023) Gokmen, Veysel; Surucu, Abdulkadir; Budak, Mesut; Bilgili, Ali VolkanBackground: Crop production is negatively impacted by excess and lack of soil micronutrients. Due to anthropogenic and natural factors, soil micronutrients vary greatly in space, necessitating time- and money-consuming large-scale sampling. Therefore, modeling their spatial distributions and forecasting in non-sampled areas are essential for high crop production. Methods: In this study, regional variations in soil micronutrient content of the Upper Tigris Basin were modeled to produce local change maps for the development of site-specific nutrient management systems. The concentrations of extractable zinc (Zn), copper (Cu), manganese (Mn), and iron (Fe) in soil samples taken at 388 different sites between 0 and 20 cm deep were determined. Using variogram and kriging analyses, the spatial distribution of the micro element concentrations was modeled and mapped in a GIS environment. Results: The micronutrients demonstrated significant variability with a high coefficient of variation (CV > 35%). It was found that the spatial dependence of the samples ranged from low for Fe and Cu to high for Zn and Mn. The spatial distribution of soil micronutrients was influenced by soil texture in addition to distance. Overall, the results demonstrated that the management of site-specific micronutrients may be aided by the integration of geostatistics and GIS, which is particularly beneficial in terms of effective management of the lands and the optimal use of inputs. Conclusion: Overall, the findings showed that the integration of geostatistics and GIS may be helpful in the management of site-specific micronutrients, which is especially advantageous in terms of efficient management of the lands and the best use of inputs.(c) 2023 The Author(s). Published by Elsevier B.V. on behalf of King Saud University.Öğe Sayısal renk parametrelerinden bazı fiziksel ve kimyasal toprak özelliklerinin belirlenmesi(Harran Tarım ve Gıda Bilimleri Dergisi, 2018-04-17) Budak, Mesut; Günal, Hikmet; Süer, Mustafa; Süer, Mustafa; Akbaş, FevziTarım topraklarının fonksiyonlarının sürdürülebilirliği doğru tanımlanmaları, uygun idare edilmeleri ve toprak kalitesinde zaman içerisinde meydana gelen değişimin izlenmesi ile mümkün olabilir. Toprak özelliklerinin klasik yöntemlerle belirlenmeleri oldukça uzun zaman, maliyet ve iş gücü gerektirdiğinden, üreticiler çoğu zaman toprak analizi yaptırmaktan kaçınmaktadır. Bu çalışma, kolaylıkla belirlenebilen sayısal renk parametreleri ile geniş bir tarımsal araziden alınan toprakların bazı fiziksel ve kimyasal özellikleri arasındaki ilişkileri belirlemek ve sayısal renk parametrelerinin toprak özelliklerinin belirlenmesinde kullanılabilirliğini araştırmak için yürütülmüştür. Bu amaçla, yoğun tarımsal üretimin yapıldığı Kazova’da 63 noktadan 0-30 cm derinlikte toprak örnekleri alınmıştır. Toprak örneklerinin renk parametreleri (L, a ve b), kil, kum ve silt içeriği, toprak reaksiyonu (pH), elektriksel iletkenlik (EC), kireç içeriği, organik madde (OM), tarla kapasitesi (TK), solma noktası (SN), agregat stabilitesi (AS), değişebilir katyonlar (Na, K ve Ca), katyon değişim kapasitesi (KDK) ve demir (Fe) konsantrasyonları belirlenmiştir. Toprağın parlaklık (L) ve kırmızılık (a) değerleri ile kil, kireç, AS, SN, TK, KDK, Ca, Na, ve K arasında önemli düzeyde negatif (P<0.01) bir korelasyon tespit edilmiştir. Regresyon analizi sonucunda “L” parametresinin AS, kireç içeriği, KDK, EC ve değişebilir Na’un belirlenmesinde kullanılabileceğini, “a” parametresinin ise toprakların AS’si (R2=0.65), kireç içeriği (R2=0.64), değişebilir Ca (R2=0.58) ve değişebilir K (R2=0.51) kapsamlarının belirlenmesinde kullanılabileceği tespit edilmiştir. İstatistiksel analizler sayısal renk parametrelerinden L ve a’nın Kazova topraklarının bazı toprak özelliklerinin belirlenmelerinde güvenilir bir şekilde kullanılabileceklerini ortaya koymuştur.Öğe SOIL QUALITY ASSESMENT OF UPPER TIGRIS BASIN Mesut(Carpathian Journal of Earth and Environmental Sciences, 2017-10-12) Budak, Mesut; Günal, Hikmet; Çelik, İsmail; Yıldız, Hakan; Acir, Nurullah; Acar, MertEconomic life of the Tigris basin, part of the Mesopotamian depends heavily on agricultural production for thousands of years. Sustainability of agricultural production in this ancient region may only be possible by conserving and improving the ability of soils to function. Therefore, soil quality indexes were computed to evaluate and monitor functioning ability of pasture lands, forest lands, orchard and arable lands in the upper Tigris Basin of Mesopotamian. Soil samples were collected from (0–20 cm) at 134 locations from approximately the corners of 5km*5km size grid cells within 2.450 km2 research site. Twelve soil properties were measured as potential indicators of soil quality. A minimum data set (MDS) for each of land use was determined by means of principal component analysis (PCA) and expert opinion (EO) techniques. The weightages of each indicator were calculated using PCA and analytical hierarchy process (AHP). Soil quality index (SQI) for every sampling locations was calculated by weighted additive method following the use of linear scoring functions to obtain unitless indicator scores. The organic matter (OM), aggregate stability (AS) and slope were considered the most powerful and common soil attributes for distinguishing land uses in regard to soil quality and they can be used to monitor and assess the soil quality in this semi-arid environment. The SQI values of four land uses were significantly different (P?0.01) from each other. The highest SQI value was obtained for forest land with EO (SQIEO=0.974) and the lowest SQI value was for orchards with PCA (SQIAHP=0.793). The results indicated that PCA and EO methods produced comparable results in assessment of soil quality.Öğe Soil quality assessment to compare tillage systems in Cukurova Plain, Turkey(Elsevier B.V., 2021) Çelik, İsmail; Günal, Hikmet; Acir, Nurullah; Barut, Zeliha Bereket; Budak, MesutAgricultural practices should be carefully monitored for long-term impacts on soil quality to avoid further deterioration in ecosystem services provided by soils. The aim of this study was to evaluate and compare the effects of two conventional (CT), three reduced (RT) and two no-till (NT) tillage practices on soil quality of a clayey soil in a ten-year experiment using Soil Management Assessment Framework (SMAF). The field experiment was established in 2006 with six tillage methods, and winter wheat (Triticum aestivum L.), soybean (Glycine max. L.) – grain corn (Zea mays L.) crop rotation. The NT plots were divided into two parts, i.e., half of them were plowed with a moldboard plow during November 2015, and this practice was defined as strategic tillage (ST), while the remaining half was left undisturbed (NT). Disturbed and undisturbed soil samples were collected at three depths (0?10, 10?20 and 20?30 cm) from experimental plots in 2016. Fourteen soil quality indicators, including physical, chemical and biochemical properties were determined to assess soil quality. Soil productivity, water relations (WR), resistance and resilience (RR), and physical stability and support (PSS) functions defined in SMAF were calculated. The RR and PSS function scores were significantly higher at 0?10 cm depth under conservational tillage methods (RT and NT) compared to CT methods. Low nutrient content, compaction, aggregate size and stability values in 10?30 cm depth decreased the functioning potential. The RR function at 0?10 cm depth in NT method was 103 % and 72 % higher than CT-1 and CT-2, respectively. All soil functions under RT and NT methods decreased with depth. The ST significantly increased PSS and WR functions in all sampling depths and overall soil quality in 10?20 and 20?30 cm depths compared to long-term NT method. The comparison of soil functions and overall soil quality indices helped to identify the effects of different tillage practices on functional potential of the soil. Furthermore, soil quality assessment using soil functions provides an overview to distinguish the pros and cons of tillage practices on sustainability of the crop production. © 2020 Elsevier B.V.Öğe Soil salinity assessment of a natural pasture using remote sensing techniques in central Anatolia, Turkey(Public Library Science, 2022) Kilic, Orhan Mete; Budak, Mesut; Gunal, Elif; Acir, Nurullah; Halbac-Cotoara-Zamfir, Rares; Alfarraj, Saleh; Ansari, Mohammad JavedSoil salinity is a major land degradation process reducing biological productivity in arid and semi-arid regions. Therefore, its effective monitoring and management is inevitable. Recent developments in remote sensing technology have made it possible to accurately identify and effectively monitor soil salinity. Hence, this study determined salinity levels of surface soils in 2650 ha agricultural and natural pastureland located in an arid region of central Anatolia, Turkey. The relationship between electrical conductivity (EC) values of 145 soil samples and the dataset created using Landsat 5 TM satellite image was investigated. Remote sensing dataset for 23 variables, including visible, near infrared (NIR) and short-wave infrared (SWIR) spectral ranges, salinity, and vegetation indices were created. The highest correlation between EC values and remote sensing dataset was obtained in SWIR1 band (r = -0.43). Linear regression analysis was used to reveal the relationship between six bands and indices selected from the variables with the highest correlations. Coefficient of determination (R-2 = 0.19) results indicated that models obtained using satellite image did not provide reliable results in determining soil salinity. Microtopography is the major factor affecting spatial distribution of soil salinity and caused heterogeneous distribution of salts on surface soils. Differences in salt content of soils caused heterogeneous distribution of halophytes and led to spectral complexity. The dark colored slickpots in small-scale depressions are common features of sodic soils, which are responsible for spectral complexity. In addition, low spatial resolution of Landsat 5 TM images is another reason decreasing the reliability of models in determining soil salinity.Öğe Spatial variability of some soil properties in an agricultural field of Halabja City of Sulaimani Governorate, Iraq(Fresenius Enivromental Bulletin, 2019-01-01) Sürücü, Abdulkadir; Ahmed, Tavan K; Günal, Elif; Budak, MesutThe soils of Sulaimani Governorate have been used to meet the food demand of northern Iraq. Longstanding wars and strict trade restrictions have caused people of region struggling to get more crops out of agricultural lands. Although soils have been subjected to agricultural production practices and are susceptible to degradation, reliable information on soils of the region is not available. This study has been carried out to characterize some physical and chemical soil properties and to determine the spatial structure of soil properties in a 100ha agricultural filed of Halabja at Sulaimani governorate, Iraq. The study area was divided into 100 × 100 m grid squares, 100 soil samples were collected from the corners of each grid representative of the surface (0–20 cm) horizons. In addition, a total of 16 soil samples were taken along four transects with sampling intervals of 5, 10, 40 and 50m. The measured properties were: clay, sand, silt, calcium carbonate and organic matter contents, exchangeable cation (Na, K, Ca, and Mg), micronutrient (Fe, Zn, Cu and Mn) and plant available phosphorus (P) concentrations, pH and electrical conductivity. The data were analyzed using classic statistics and geostatistics by constructing semivariograms and mapping by Ordinary Kriging. Semivariograms were calculated for soil characteristics and their spatial distributions were mapped. Soils were poor in available P and Zn contents. Soil organic matter showed significant positive correlations with the EC, concentrations of P, clay content, extractable Ca and Na concentrations whereas the correlation was negative with sand content and Zn concentration. Nugget/sill ratio for modelled variables indicated high and moderate spatial dependences in study area. The range of spatial dependence varied from 102 m (calcium carbonate) to 1248 m (pH). The distribution maps of soil attributes could be utilized as a guide for site-specific crop management in similar soils.
