ENVIRONMENTAL MODELLING OF LAND USE CHANGES IN THE NEIGHBOURHOOD OF COAL MINES WITH THE GIS Abstract Human society causes an increasing pressure on land and its use. The requirements and demands of humanity has significantly changed in the last few decades. This is the foundation of continuous environmental impacts, particularly in those areas where mining companies exploit natural resources on a large scale for personal and economic well-being, and thus significantly transform the land surface. The objective of this thesis is to refer to changes in land use in the vicinity of surface coal mines in the districts of Chomutov, Most, Teplice and Sokolov where these coal mines take up large areas. We do so with the help of remote-sensing-based documentation and GIS applications. Mining dramatically transforms the appearance of surrounding landscapes and has a high impact on the environment. The thesis shows the change of land use based on both the images from the Landsat satellite and the inclusion in basic Corine categories in which was created layer of land cover for 1990, 2000, 2006 and 2012, and further shows the ecological stability of the landscape from 1986 up to now. The evolution and changes of ecological stability are analyzed with the help of ecological coefficient, cluster analysis, linear...

Due to the inappropriate planning and explosive population growth in urban areas, especially in developing countries, sustainable and disaster-safe urbanization has become the most important challenge for governments. Urbanization presents benefits in different ways but has led simultaneously to changes in land use/land cover (LULC), impacting soil quality, runoff, surface temperature, water quality, and promoting climate change. The environmental implications of LULC changes cannot be understood well enough to take precautions without the knowledge of LULC change. This reality is the driving force behind my research, which focuses on impacts of urbanization on flood and soil erosion hazards in Istanbul, Turkey. Istanbul is the biggest city in Turkey with its almost 15.000.000 population. In 1999 the Marmara earthquake destroyed the city especially the newly developed zones. Every year Istanbul suffers also from flood damages. Istanbul has been experiencing uncontrolled migration, chiefly from rural areas, since the economic reform policies took place in the second half of the 20th century. These policies forced the city to expand towards the agricultural land and to the coastal areas. Istanbul has been faced with illegal housing and uncontrolled development since then. This development has produced significant decreases inproductive agricultural lands and created more impervious areas. Infrastructure development has not matched the rate of the population increase and uncontrolled urbanization, making the city vulnerable increasingly to natural disasters. This dissertation aims to understand the impacts of urbanization on flood and erosion hazards in Istanbul by examining changes in the city using remote sensing (RS) and geographical information systems (GIS) methods. LULC was examined first: Two change detection methods were applied to choose the best performer for Istanbul. The post-classification comparison (PCC) method produced better results than the principal component analysis (PCA). PCC utilized 1984, 1997, 2001, 2007 and 2010 Landsat images of the study area. These Landsat images were corrected atmospherically and radiometrically using COST Model (Markham and Barker, 1986). After the corrections geometric rectification was performed with the help of 1987 topographic map, 1995 orthophotos, 2005 GPS data. Location and nature of the change were derived for the time periods. Results show that since 1984, agricultural land have been replaced increasingly by urbanization. Flooding and related soil erosion are both natural events. Yet these events can be hazardous; they can harm/destroy lives and property. In recent years these events have become disasters for Istanbul. We investigated the role of urban growth in such disasters. To understand the urbanization and flood relation better, flood events for each time period were examined using LULC change, runoff information and watershed analysis. Soil erosion events occur slowly and in Istanbul they do not happen frequently (yearly) as with flooding. But some of the locations of erosion that occurred in the past are now urbanized areas. It is thus important to understand how the built environment affects soil erosion. We applied the Revised Universal Soil Loss Equation (RUSLE) method for each year in the time series. Prior erosion locations digitized from General Directorate of Mineral Research and Exploration were compared to predicted locations. The resultant maps indicates that European side of Istanbul is more prone to erosion than Anatolian side.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第17880号 / 工博第3789号 / 新制||工||1579(附属図書館) / 30700 / 京都大学大学院工学研究科都市環境工学専攻 / (主査)教授 松岡 譲, 教授 米田 稔, 准教授 倉田 学児 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Student Number : 9612464Y - MSc dissertation - School of Mining Engineering - Faculty of Engineering and the Built Environment / This study was conducted at the West Rand Region, part of South African-based AngloGold operations. The study assesses the impacts of gold mining on the water quality and the change in landuse resulting from the mining activities on the West Rand Region. This was achieved by collecting historical data relating to the tailings dams and both surface and groundwater qualities between 1998 and 2003. The landuse information was gathered from the topographic map of Carltonville and remotely sensed data in the form of aerial photographs, landsat data and ASTER images. The data was analysed in a GIS ILWIS. The sizes of the tailings dams have not changed significantly during the study period. The size of the plantation also shows a decreasing trend due to pollution from the tailings dams. The area surrounding the Anglo Gold mining operations is sparsely-vegetated due to both poor soils and the impacts of mining activities. The surface water quality is poor and this water has negative impacts on the environment following accidental discharges and has potential negative impacts from seepage through the unlined dams. The quality of the groundwater is generally good with the exceptions of BH 18, MBH 8, MBH 5 and MBH 3 whose pollution arises from North mine tailings dams and North boundary dam. MBH 5 shows an improvement in water quality over time. The potential generation of AMD from the tailings dams is inhibited by the neutral pH of the tailings. In order to improve the environment in the West Rand Region and to prevent further pollution, planting of indigenous trees to make up for shrinking plantation and lining of the dams be undertaken. Stricter maintenance and monitoring of both the sewage plants and the dams be implemented to avoid accidental discharges of poor quality water into the environment. A study to accurately quantify the groundwater pollution arising from both the tailings dams and other surface water bodies should be undertaken.

Recent developments in commercial satellite products have resulted in a broader range of high quality image data, enabling detailed analysis. Transportation features have historically been difficult to accurately identify and structure into coherent networks; prior analyses have demonstrated problems in locating smaller features. One problem is that roadways in urban environments are often partly obscured by proximity to land cover or impervious objects. Ongoing research has focused on object-based methods for classification and different segmentation techniques key to this approach. For this application, software packages such as eCognition have shown encouraging results in assessing spatial and spectral patterns at varied scales in intelligent classification of aerial and satellite imagery. In this study 2.44m QuickBird and 4m Ikonos multispectral imagery for a 7.5' quad near the Mississippi Gulf Coast are examined. Challenges in analysis include intricate networks of smaller roads in residential zones and regions of tall/dense tree cover. Both spectral and object-based approaches are implemented for pre-classification, and road features are extracted using various techniques, after which the results are compared based on a ?Raster Completeness? model developed.

In Jordan, the fourth driest country in the world, demand for water exceeds available water resources. The annual per capita water availability is 145 Cubic Meter (CM) per year, which is below the international poverty line of 500 CM/year. The increasing water deficit year-on-year poses serious future threat that will impact many sectors. Water quantity and quality are essential issues in Jordan and more efforts are needed to find new water resources, and to protect and improve the available resources. This research seeks to study the relationship between Landuse/cover change and water quality in reservoirs in Jordan. Landuse changes were detected by using Landsat Thematic Mapper (TM) images obtained for King Talal reservoir in 1990 and 2006 and for Karameh reservoir in 1998 and 2006. Geometric correction and supervised classification were utilized in ERDAS software. Turbidity levels within the two reservoirs were estimated by the chromaticity technique and were compared to measured data from previous reports for both reservoirs. Remote sensing was successful in detecting the changes in landuse in both areas. The estimated turbidity levels correlated moderately well with measured data from previous reports for the same reservoirs; it was difficult to directly relate a specific Landuse/cover for turbidity levels. Limitations were defined as data collection and quality problems, in addition to some theoretical issues about using Landsat for this study. / Master of Science

In this study eight residential development scenarios are created for the mostly undeveloped Back Creek Watershed outside Roanoke, Virginia. The development scenarios include low, medium (cluster), medium (conventional), and high density development with and without development restrictions. These scenarios represent a large range of development as the land use imperviousness varies from 1% for the baseline condition to 34% for the most developed scenario. The hydrologic model HSPF is used to generate overland and channel flows from 43 years of rainfall. Hydrologic output from HSPF of the various landuse patterns from the eight scenarios are evaluated using Post Processor, a Visual Basic program. The results show that increased development causes a reduction in Back Creek's baseflow and an increase in the occurrence of both high and low flow extreme events. Overall, these results indicate that increased development will increase the variability of flowrate in Back Creek. Stream health impacts from flow variability were also analyzed with the Post Processor. First, hydrologic statistical variables with ecological relationships were used to gage the level of stream health impacts from flow variability. The averaged stream health index for the development scenarios was found to closely follow the amount of development, represented by the percent of impervious landuse. Second, the amount of velocity, depth, and both depth and velocity habitat available for three habitat guild representative species was evaluated for each scenario. The results indicated that increased development would lead to a substantial reduction in available riffle species habitat (represented by the fantail darter) and a moderate reduction in run and pool species habitat (represented by the central stoneroller and smallmouth bass, respectively). Overall, increased development has been found to have a negative impact on stream health. This impact should be considered in any future expansion of the Roanoke suburbs into this watershed. / Master of Science

O mapeamento do risco de erosão é uma ferramenta essencial para o planejamento de uso da terra. Este trabalho testa quatro modelos de predição do risco de erosão e capacidade de uso da terra: Risco de Erosão Natural, Risco de Erosão Simulado, Expectativa de Erosão e Capacidade de Uso da Terra. Esses modelos permitem diagnosticar as áreas potenciais e restritas ao uso agrícola em uma microbacia hidrográfica localizada na região do oeste paulista, utilizando recursos de geoprocessamento. O trabalho envolveu as seguintes etapas: i) caracterização da microbacia através de um banco de dados de atributos físicos construído com o auxílio de três sistemas de informações geográfica (SIG): Idrisi, Ilwis e ArcView; ii) elaboração dos mapas de risco de erosão gerados através dos três modelos derivados da Equação Universal de Perdas de Solo (EUPS) e da Capacidade de Uso da Terra; iii) validação do modelo de risco de erosão através da análise comparativa das erosões com os fatores erosivos e o grau de risco indicado pelo modelo. Foram definidos 33 setores para identificar e classificar as áreas mais críticas da microbacia. O risco de erosão foi analisado por 3 índices: de erosão natural (e), de erosão simulado (es) e expectativa de erosão (ee). Foi constatado que o índice de expectativa de erosão não é sensível a valores altos de potencial natural de erosão (PNE). Na microbacia há predomínio das classes de risco de erosão natural moderado a alto em 65,7% da área (3.649,2ha). Para condições simuladas de pastagem degradada, a área da microbacia que apresenta perda de solo em níveis toleráveis corresponde a 65,4% da área (3.634,6ha) para fator topográfico (LS) obtido pelo método das rampas e 83,1% (4.623,2ha) para o método automatizado. A estimativa de perda de solo média anual por setor variou de 7 a 40 toneladas por hectare para as condições simuladas e considerando-se os valores de LS do método automatizado. O uso com pastagem e reflorestamento é indicado como o mais adequado para 90,1% (5.022,7ha) da microbacia, segundo a classificação de Capacidade de Uso da Terra e 0,3% (16,0ha) da área total é recomendada para fins de preservação da vida silvestre. O modelo de risco de erosão simulado, utilizando valores de LS automatizado, foi o que apresentou a melhor correlação visual com os processos erosivos levantados na microbacia com equipamento GPS. As terras ocupadas com pastagem encontram-se em intenso estado de degradação devido a interação entre as condições naturais favoráveis e ao manejo inadequado. A ocorrência de erosões lineares (sulcos, ravinas e voçorocas) estão relacionadas ao caminhamento do gado e dimensionamento incorreto dos terraços, que intensificaram os efeitos erosivos da concentração do escoamento superficial. Os setores 28 e 12 foram os que apresentaram o nível mais crítico de risco de erosão. Os recursos de geoprocessamento, especificamente o SIG, foram importantes ferramentas de diagnóstico para o planejamento ambiental, simulando e analisando diversos cenários com agilidade. / The mapping of the erosion risk is an essential tool for the planning of land use. This work tests four models to predict erosion risk and land use capacity: Natural Erosion Risk, Simulated Risk of Erosion, Erosion Expectation and Land Use Capability. These models allowed the mapping of potential and restricted areas for agricultural use in a watershed located in the west side of the State of São Paulo, using geoprocessing resources. The work involved the following phases: i) characterization of the watershed based on a database of physical attributes constructed with the aid of three geographic information systems (GIS): Idrisi, Ilwis and ArcView; II) elaboration of the maps of erosion risk based on three models derived from the Universal Soil Loss Equation (USLE) and the Capability of Land Use; III) validation of the model of erosion risk through the comparative analysis of the erosions with the erosion factors and the level indicated in the erosion risk model. Thirty three sectors were defined to identify and to classify the most critical areas in the watershed. The erosion risk was analyzed by 3 indexes: natural erosion risk (e), simulated erosion risk (es) and erosion expectation (ee). It was observed that the index of erosion expectation does not respond to high values of natural potential of erosion (PNE). In the watershed prevailed moderate to high categories of natural erosion risk in 65,7% of the area (3.649,2ha). For simulated conditions of degraded pasture, the area of the watershed that presents soil loss tolerance in tolerable levels corresponds 65,4% of the area (3.634,6ha) for topographical factor (LS) calculated by the manual method and 83,1% (4.623,2ha) for the automatic method (USLE-2D). The estimate of annual soil loss average for each sector varied from 7 to 40 tons per hectare on the simulated conditions and considering the LS-values of automatic method. Pasture and reforestation is the most indicated use suitable in 90.1% (5.022,7ha) of the watershed, according to the Capacity of Use of Land indicator, and 0,3% (16,0ha) of the total area are assigned to the preservation of the wildlife. The simulated erosion risk model, using automatized LS-values, presented the best visual correlation with the erosion processes surveyed on the field with GPS. The lands used with pasture present high degree of degradation due to the interaction of favorable natural conditions and inadequate management. The occurrence of linear erosions (rill and gully) is related to the cattle tracking and incorrect dimensioning of the terraces, that had intensified the erosive effect of the concentrated flow. Sectors 28 and 12 were the ones with the most critical level of erosion risk. The geoprocessing resources, specifically GIS proved to be an important tool to generate enviromentally adequate plans simulating and analyzing diferent scenarious with agility.

O mapeamento do risco de erosão é uma ferramenta essencial para o planejamento de uso da terra. Este trabalho testa quatro modelos de predição do risco de erosão e capacidade de uso da terra: Risco de Erosão Natural, Risco de Erosão Simulado, Expectativa de Erosão e Capacidade de Uso da Terra. Esses modelos permitem diagnosticar as áreas potenciais e restritas ao uso agrícola em uma microbacia hidrográfica localizada na região do oeste paulista, utilizando recursos de geoprocessamento. O trabalho envolveu as seguintes etapas: i) caracterização da microbacia através de um banco de dados de atributos físicos construído com o auxílio de três sistemas de informações geográfica (SIG): Idrisi, Ilwis e ArcView; ii) elaboração dos mapas de risco de erosão gerados através dos três modelos derivados da Equação Universal de Perdas de Solo (EUPS) e da Capacidade de Uso da Terra; iii) validação do modelo de risco de erosão através da análise comparativa das erosões com os fatores erosivos e o grau de risco indicado pelo modelo. Foram definidos 33 setores para identificar e classificar as áreas mais críticas da microbacia. O risco de erosão foi analisado por 3 índices: de erosão natural (e), de erosão simulado (es) e expectativa de erosão (ee). Foi constatado que o índice de expectativa de erosão não é sensível a valores altos de potencial natural de erosão (PNE). Na microbacia há predomínio das classes de risco de erosão natural moderado a alto em 65,7% da área (3.649,2ha). Para condições simuladas de pastagem degradada, a área da microbacia que apresenta perda de solo em níveis toleráveis corresponde a 65,4% da área (3.634,6ha) para fator topográfico (LS) obtido pelo método das rampas e 83,1% (4.623,2ha) para o método automatizado. A estimativa de perda de solo média anual por setor variou de 7 a 40 toneladas por hectare para as condições simuladas e considerando-se os valores de LS do método automatizado. O uso com pastagem e reflorestamento é indicado como o mais adequado para 90,1% (5.022,7ha) da microbacia, segundo a classificação de Capacidade de Uso da Terra e 0,3% (16,0ha) da área total é recomendada para fins de preservação da vida silvestre. O modelo de risco de erosão simulado, utilizando valores de LS automatizado, foi o que apresentou a melhor correlação visual com os processos erosivos levantados na microbacia com equipamento GPS. As terras ocupadas com pastagem encontram-se em intenso estado de degradação devido a interação entre as condições naturais favoráveis e ao manejo inadequado. A ocorrência de erosões lineares (sulcos, ravinas e voçorocas) estão relacionadas ao caminhamento do gado e dimensionamento incorreto dos terraços, que intensificaram os efeitos erosivos da concentração do escoamento superficial. Os setores 28 e 12 foram os que apresentaram o nível mais crítico de risco de erosão. Os recursos de geoprocessamento, especificamente o SIG, foram importantes ferramentas de diagnóstico para o planejamento ambiental, simulando e analisando diversos cenários com agilidade. / The mapping of the erosion risk is an essential tool for the planning of land use. This work tests four models to predict erosion risk and land use capacity: Natural Erosion Risk, Simulated Risk of Erosion, Erosion Expectation and Land Use Capability. These models allowed the mapping of potential and restricted areas for agricultural use in a watershed located in the west side of the State of São Paulo, using geoprocessing resources. The work involved the following phases: i) characterization of the watershed based on a database of physical attributes constructed with the aid of three geographic information systems (GIS): Idrisi, Ilwis and ArcView; II) elaboration of the maps of erosion risk based on three models derived from the Universal Soil Loss Equation (USLE) and the Capability of Land Use; III) validation of the model of erosion risk through the comparative analysis of the erosions with the erosion factors and the level indicated in the erosion risk model. Thirty three sectors were defined to identify and to classify the most critical areas in the watershed. The erosion risk was analyzed by 3 indexes: natural erosion risk (e), simulated erosion risk (es) and erosion expectation (ee). It was observed that the index of erosion expectation does not respond to high values of natural potential of erosion (PNE). In the watershed prevailed moderate to high categories of natural erosion risk in 65,7% of the area (3.649,2ha). For simulated conditions of degraded pasture, the area of the watershed that presents soil loss tolerance in tolerable levels corresponds 65,4% of the area (3.634,6ha) for topographical factor (LS) calculated by the manual method and 83,1% (4.623,2ha) for the automatic method (USLE-2D). The estimate of annual soil loss average for each sector varied from 7 to 40 tons per hectare on the simulated conditions and considering the LS-values of automatic method. Pasture and reforestation is the most indicated use suitable in 90.1% (5.022,7ha) of the watershed, according to the Capacity of Use of Land indicator, and 0,3% (16,0ha) of the total area are assigned to the preservation of the wildlife. The simulated erosion risk model, using automatized LS-values, presented the best visual correlation with the erosion processes surveyed on the field with GPS. The lands used with pasture present high degree of degradation due to the interaction of favorable natural conditions and inadequate management. The occurrence of linear erosions (rill and gully) is related to the cattle tracking and incorrect dimensioning of the terraces, that had intensified the erosive effect of the concentrated flow. Sectors 28 and 12 were the ones with the most critical level of erosion risk. The geoprocessing resources, specifically GIS proved to be an important tool to generate enviromentally adequate plans simulating and analyzing diferent scenarious with agility.

Soluble organic matter represent less than 1% of total soil organic matter (SOM) - but it contributes to many terrestrial ecosystem processes, due to its high mobility and reactivity in soil. Although it has been suggested that soluble organic matter (OM) may serve as an early indicator of soil quality changes as a result of shifts in land-use and management practices, only a few studies have addressed the dynamics of soluble OM in relation to land-use and specifically soil depth. This study focuses on two aspects of soluble OM. In the first part, I hypothesized that extractable OM obtained by aqueous solutions is a continuum of substances that depending on the extraction method can be separated into two operationally different fractions. The size and properties of these fractions may consistently differ among different land uses and at different soil depths. The objective of this part of the study was then to assess dynamics (size and properties, biodegradability and seasonality) of water extractable organic matter (WEOM) and salt extractable organic matter (SEOM) in a sequence of human dominated land-uses at topsoil and subsoil. At the second part of the study, I tested the regulatory gate hypothesis –abiotic solubilization of OM- as a primary controlling factor in soluble OM production. The objective of this study was to evaluate the impact of the microbial activity on the net production of dissolved organic matter (DOM) from the native SOM in the presence of added DOM and plant residue. For the first part of the experiment, the soil samples were collected from four land-uses under bog pine (Halocarpus bidwillii) woodland, tussock grassland (Festuca novae-zelandiae and Heiracium pilosella), cropland (Medicago sativa) and plantation forest (Pinus nigra). The selected land uses were located in the Mackenzie Basin, Canterbury, New Zealand and occurring on the same soils, topography and experienced similar climates. Soil samples were obtained from topsoil (0-20 cm) and subsoil (60-80 cm) at the end of each season (November, February, May and August) during 2007-2008. The sampled soils were adjusted to the same water status prior to extraction. While WEOM was obtained during a mild extraction procedure and using 0.01M CaCl2, SEOM was extracted with 0.5M K2SO4 at high temperature (75οC for 90 min). Both extracts were filtered through a 0.45 μm filter size. In the first part of the study, I assessed the biodegradation dynamics of WEOM and SEOM (spring samples), using a double-exponential decay model. The WEOM and SEOM were inoculated and incubated at 22°C for 90d under aerobic conditions. Subsamples were removed on days 1, 3, 7, 12, 16, 30, 42, 60, 75, and 90, filtered (0.22 μm), and analyzed for organic C and N content, UV absorption, and 13C natural abundance (δ13C). The results of the biodegradation experiment indicated a similar pattern for both C and N of SEOM and WEOM as that of previously shown for soil DOM. However, C and N mineralization rate were considerably larger in the WEOM than SEOM. The parameters of the double-exponential model suggested that regardless of the land-use and soil depth, both the WEOM and SEOM can be modeled in two biological pools, with a largely similar “fast decomposable” but different “slowly decomposable” pools. However, since the extraction was not sequentially followed, a very small portion of the SEOM was comprised of the WEOM and given the greater observed biodegradability of the WEOM, the overall biodegradable portion of the SEOM would be lower than the observed. Despite a greater biodegradability of the organic N than C of both WEOM and SEOM; mainly due to a longer HL of the slowly biodegradable pool of C; the C/N ratio of the samples did not change very much during the biodegradation. This led us to conclude that the biodegradation of soluble OM may occur as a function of N availability. Parallel to C and N loss, a considerable increase in SUVA254 of SEOM, and particularly WEOM occurred during the incubation period. The greater increase in the proportion of aromatic compounds (assessed by SUVA) in the WEOM than SEOM, implied consumption of simple compounds (vs. very humified) during decomposition and further supported the observed faster biodegradation rate of the WEOM. The data indicated a relatively strong correlation (R2=0.66 and 0.74 for the WEOM and SEOM, respectively) between the amount of biodegraded C and the increase in SUVA254. This suggested that SUVA254 can be used as a simple, low-cost but reliable approach for describing the biodegradability of soluble OM, as previously suggested by others. At the end of the bioassay, the 13C natural abundance of the WEOM was significantly depleted, and showed a clear relationship with the proportion of the biodegraded C. This confirmed the previously suggested preferential biodegradation of simple organic constituents (13C enriched), resulting in the accumulation of more depleted 13C compounds (often recalcitrant compounds). Moreover, the results of the δ13C technique revealed that the relatively greater 13C enrichment of the WEOM obtained from subsoil, seems to be due to the presence of root exudates (often highly 13C enriched). In contrast, a proportionally greater 13C depletion observed in the SEOM particularly at subsoil samples, suggests that there is a close relationship between the SEOM and the typically 13C depleted humified SOM. The results of the biodegradation model (half-life of both C and N), in addition to dynamics of SUVA254 and δ13C of the WEOM and SEOM were very comparable between top and subsoil samples. This implied that the potential biodegradability of soluble OM under laboratory conditions does not necessary reflect the reported lower in situ biodegradability at soil depth, in agreement with recent evidence suggested by others. Instead, this may be largely due to the lack of optimum conditions (oxygen, nutrients, and moisture) for the decomposer community at soil depth. Although there was a tendency for a generally greater biodegradability of the samples from the soils under the crop land (both WEOC and SEOC), along with relatively greater increase in SUVA, there was not a consistent trend of the effect of land use on the biodegradation of either WEOM or SEOM. The lower C/N ratio of the soils under the crop land seemed to be related with the observed proportionally greater biodegradability of these soils. During the second part of the study, I assessed seasonal variations of the size and properties of the previously defined WEOM and SEOM, collected from top-and subsoil from the land-uses. I observed that 10-year after conversion of the degraded tussock grassland to cropland or plantation, the total C stock of topsoil (0-20 cm) when above- and below-ground plant biomass is excluded; has remained unchanged. This was attributed to the limited biomass production of the region, more likely as a result of low productivity of the soil, but also harsh climatic conditions. Not only soil depth, but land-use affected both C concentration and C/N ratio of soil organic matter (SOM), with the greatest C concentration of soils under grassland and plantation in topsoil and subsoil, respectively. Despite the WEOM, the size of SEOM was largely unaffected by land-use and soil depth; instead, the properties of SEOM was more consistent with the effect of soil depth. Given the observed large temporal and spatial variability of the WEOM, the study suggests that the SEOM more consistently reflects the influence of land use and soil depth. No consistent effect of seasonality was observed in terms of size or properties of the SOM and the WEOM and SEOM. Overall comparison of the size and properties of the WEOM and SEOM indicated that OM extraction efficiency may vary largely, depending on extraction conditions. Using more concentrated salt solutions consistently yielded greater amount of OM (N, and especially C) release from soil with properties resembling more those of total soil OM (more humified) compared to the WEOM. The SEOM was also less variable by time and space. The last part of the study was aimed to assess biotic vs. non-biotic solubilization of OM in the presence of added plant residue. Given the need to recognize the source of the solubilized OM during the experiment, I used enriched (13C) plant residue as the source of fresh OM. The above-ground part of ryegrass was added to soil either as plant residue or residue extract (extracted with CaCl2 followed by 0.45μm filtration) -termed DOM. These two forms of added OM (residue/DOM) were conceived to represent two levels of bioavailability for the decomposer community for further assessing possible biotic solubilization of OM. Two soils similar in their OM content and other properties, but different in mineralogy were selected for the experiment. Soils were incubated for 90d under sterilized vs. non-sterile conditions and leached regularly with a dilute aqueous solution (0.05M CaCl2). Plant residue was added to soil (1:100, residue: soil, w/w) prior to the start of the incubation, but DOM was frequently applied to the soils along with each leaching experiment. The greater C and N concentration in the leachates of both sterilized residue-amended and DOM-amended soils compared to that of living soils, indicated a high microbial activity, as determined by CO2 loss, in the living soils. However, the proportion of the solubilized C (determined by 13C) from sterilized soils was largely comparable to that of living soils. This supports the recently suggested “regulatory gate” hypothesis, stating that solubilisation of OM largely occurs independent of the size or community structure of microorganisms. In addition, I observed that even with the presence of adequate amount of added fresh OM (ryegrass residue), about 70% of the solubilized C consistently originated from the humified soil OM, highlighting the role of native soil OM as the source of soluble OM in soil. In addition, in the DOM-amended soils, there was strong evidence, indicating that in the sterilized soils, the added DOM was exchanged with the humified soil OM as observed by an increase in SUVA, and humification index (HI) of the leached OM. Although the results of the study did not show a considerable difference in the solubilisation rate of added OM as a function of biological activity (either in the residue- or DOM-amended soils), there was clear evidence that the presence of microbial activity has resulted in further decomposition of the solubilised OM through biological transformations. Together, the results suggested that the proposed fractionation method can be used to separate two operationally defined pools of soluble OM with consistent differences in their size (C and N), properties (δ13C, SUVA254, and C/N ratio) and biodegradability across the land-uses and soil depth. The second part of the study supported the primary role of abiotic factors on the production of soluble OM from native soil OM. Although the abiotic mechanisms involved in the solubilization remain to be addressed by future studies. Cons and pros of the methods with some suggestions for further works have been mentioned in the last chapter.