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1.
Hürlimann  Marcel  Guo  Zizheng  Puig-Polo  Carol  Medina  Vicente 《Landslides》2022,19(1):99-118

It is widely accepted that future environmental changes will affect rainfall-induced shallow slides in high-mountain areas. In this study, the Val d’Aran region located in the Central Pyrenees was selected to analyze and quantify the impacts of land use and land cover (LULC) and climate changes on regional landslides susceptibility. We analyzed 26 climate models of the EURO-CORDEX database focussing on the future rainfall conditions. The IDRISI TerrSet software suite was used to create the future LULC maps. These two inputs were analyzed individually and in a combined way defining 20 different scenarios. All these scenarios were incorporated in a physically based stability model to compute landslides susceptibility maps. The results showed that both environmental conditions will considerably change in the future. The daily rainfall will increase between 14 and 26% assuming a return period of 100 years. This intensification of precipitation will produce an overall decrease of the stability condition in the study area. Regarding the LULC prediction, the forest area will significantly increase, while in particular grassland, but also shrubs decrease. As a consequence, the overall stability condition improves, because the root strength is higher in forest than in grassland and shrubs. When we analyzed the combined impacts, the results showed that the positive effect of LULC changes is larger than the negative influence of rainfall changes. Hence, when combining the two aspects in the future scenarios, the stability condition in the study area will improve.

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2.
The present study focuses on an assessment of the impact of future water demand on the hydrological regime under land use/land cover (LULC) and climate change scenarios. The impact has been quantified in terms of streamflow and groundwater recharge in the Gandherswari River basin, West Bengal, India. dynamic conversion of land use and its effects (Dyna-CLUE) and statistical downscaling model (SDSM) are used for quantifying the future LULC and climate change scenarios, respectively. Physical-based semi-distributed model Soil and Water Assessment Tool (SWAT) is used for estimating future streamflow and spatiotemporally distributed groundwater recharge. Model calibration and validation have been performed using discharge data (1990–2016). The impacts of LULC and climate change on hydrological variables are evaluated with three scenarios (for the years 2030, 2050 and 2080). Temperature Vegetation Dyrness Index (TVDI) and evapotranspiration (ET) are considered for estimation of water-deficit conditions in the river basin. Exceedance probability and recurrence interval representation are considered for uncertainty analysis. The results show increased discharge in case of monsoon season and decreased discharge in case of the non-monsoon season for the years 2030 and 2050. However, a reverse trend is obtained for the year 2080. The overall increase in groundwater recharge is visible for all the years. This analysis provides valuable information for the irrigation water management framework.  相似文献   

3.
Flooding is a major environmental hazard in Poland with risks that are likely to increase in the future. Land use and land cover (LULC) have a strong influencing on flood risk. In the Polish Carpathians, the two main projected land use change processes are forest expansion and urbanization. These processes have a contradictory impact on flood risk, which makes the future impact of LULC changes on flooding in the Carpathians hard to estimate. In this paper, we investigate the impact of the projected LULC changes on future flood risk in the Polish Carpathians for the test area of Ropa river basin. We used three models of spatially explicit future LULC scenarios for the year 2060. We conduct hydrological simulations for the current state and for the three projected land use scenarios (trend extrapolation, ‘liberalization’ and ‘self-sufficiency’). In addition, we calculated the amount of flood-related monetary losses, based on the current flood plain area and both actual and projected land use maps under each of the three scenarios. The results show that in the Ropa river, depending on scenario, either peak discharge decreases due to the forest expansion or the peak discharge remains constant—the impact of LULC changes on the hydrology of such mountainous basins is relatively low. However, the peak discharges are very diverse across sub-catchments within the modeling area. Despite the overall decrease of peak discharge, there are areas of flow increase and there is a substantial projected increase in flood-related monetary losses within the already flood-prone areas, related to the projected degree of urbanization.  相似文献   

4.
The questions of how land use change affects climate, and how climate change affects land use, require examination of societal and environmental systems across space at multiple scales, from the global climate to regional vegetative dynamics to local decision making by farmers and herders. It also requires an analysis of causal linkages and feedback loops between systems. These questions and the conceptual approach of the research design of the Climate-Land Interaction Project (CLIP) are rooted in the classical human-environment research tradition in Geography.This paper discusses a methodological framework to quantify the two-way interactions between land use and regional climate systems, using ongoing work by a team of multi-disciplinary scientists examining climate-land dynamics at multiple scales in East Africa. East Africa is a region that is undergoing rapid land use change, where changes in climate would have serious consequences for people’s livelihoods, and requiring new coping and land use strategies. The research involves exploration of linkages between two important foci of global change research, namely, land use/land cover (LULC) and climate change. These linkages are examined through modeling agricultural systems, land use driving forces and patterns, the physical properties of land cover, and the regional climate. Both qualitative and quantitative methods are being used to illustrate a diverse pluralism in scientific discovery.  相似文献   

5.
对全球气候变化对地质灾害的响应关系,尤其是对滑坡和泥石流灾害的响应关系进行了综述。工业化革命以来,特别是近几十年来全球气候发生着重要的变化,全球几乎所有地区都经历着升温过程。全球气候变化对极端天气事件(极端降雨、气温升高、强风和洪水灾害)的影响尤为强烈,并且增加了地质灾害的发生风险。其中,水循环和气温的变化是影响地质灾害发生的直接因素。气温上升会导致大气层含水量升高、冰川冻土退化、海平面上升、蒸发作用增强;水循环变化会导致降雨频率、降水周期、降水强度的改变。日益增加的极端天气与同岩土体相互作用,导致了不同类型地质灾害的发生,严重威胁着人类的生活起居。  相似文献   

6.
The assessment of land use land cover (LULC) and climate change over the hydrology of a catchment has become inevitable and is an essential aspect to understand the water resources-related problems within the catchment. For large catchments, mesoscale models such as variable infiltration capacity (VIC) model are required for appropriate hydrological assessment. In this study, Ashti Catchment (sub-catchment of Godavari Basin in India) is considered as a case study to evaluate the impacts of LULC changes and rainfall trends on the hydrological variables using VIC model. The land cover data and rainfall trends for 40 years (1971–2010) were used as driving input parameters to simulate the hydrological changes over the Ashti Catchment and the results are compared with observed runoff. The good agreement between observed and simulated streamflows emphasises that the VIC model is able to evaluate the hydrological changes within the major catchment, satisfactorily. Further, the study shows that evapotranspiration is predominantly governed by the vegetation classes. Evapotranspiration is higher for the forest cover as compared to the evapotranspiration for shrubland/grassland, as the trees with deeper roots draws the soil moisture from the deeper soil layers. The results show that the spatial extent of change in rainfall trends is small as compared to the total catchment. The hydrological response of the catchment shows that small changes in monsoon rainfall predominantly contribute to runoff, which results in higher changes in runoff as the potential evapotranspiration within the catchments is achieved. The study also emphasises that the hydrological implications of climate change are not very significant on the Ashti Catchment, during the last 40 years (1971–2010).  相似文献   

7.
Global change is expected to result in worldwide increases in temperature and alteration of rainfall patterns. Such changes have the potential to modify stability of slopes, both natural and constructed. This paper discusses the potential effect of global climate change on reactivation of landslides through examination of predicted changes in rainfall pattern on the active landslide at Mam Tor, Derbyshire, UK. This landslide is of Pleistocene origin and is crossed by a road that is now abandoned. Damaging winter movement is known to occur when precipitation reaches both 1-month triggering and 6-month antecedent thresholds. Return periods for threshold exceedence is modelled statistically, and the climate change data from the UKCIP 2002 report (Hulme et al. 2002) is applied to this model. For the predicted changes in precipitation, it is shown that the instability threshold could decrease from 4 to 3.5 years by the 2080s for the medium–high climate change scenario. However, predicted temperature changes could influence the response of the landslide through increased evapotranspiration leading to a change in the triggering precipitation thresholds, and this will help counter the impact of changes in precipitation. Analysis of sources of uncertainty in the model has been used to establish the factors that contribute to the predicted changes in stability. Assessment of these factors can provide an indication of the potential impact of climate change on landslides in other areas of the UK.  相似文献   

8.
The purpose of this study is to produce a landslide susceptibility map for the lower Mae Chaem watershed, northern Thailand using a Geographic Information System (GIS) and remotely sensed images. For this purpose, past landslide locations were identified from satellite images and aerial photographs accompanied by the field surveys to create a landslide inventory map. Ten landslide-inducing factors were used in the susceptibility analysis: elevation, slope angle, slope aspect, lithology, distance from lineament, distance from drainage, precipitation, soil texture, land use/land cover (LULC), and NDVI. The first eight factors were prepared from their associated database while LULC and NDVI maps were generated from Landsat-5 TM images. Landslide susceptibility was analyzed and mapped using the frequency ratio (FR) model that determines the level of correlation between locations of past landslides and the chosen factors and describes it in terms of frequency ratio index. Finally, the output map was validated using the area under the curve (AUC) method where the success rate of 80.06% and the prediction rate of 84.82% were achieved. The obtained map can be used to reduce landslide hazard and assist with proper planning of LULC in the future.  相似文献   

9.
Arid regions in Asia are commonly characterized by rapidly growing populations with limited land resources and varying rainfall frequencies under climatic change. Despite being one of the most important environmental challenges in Asia, the changing aridity in this region, particularly due to large-scale land cover change, has not been well documented. In this study, we used rainfall data and a new land heterogeneity index to identify recent trend in land cover changes in the Asian arid regions. The result indicates a significant decreasing trend of barren lands and an increasing trend of vegetated lands. Although the potential land cover change is commonly believed to be strongly sensitive to rainfall change, such sensitivity has not been observed during the nine-year period (2001–2009) analyzed. Through the analyses of two separate periods (2001–2005 and 2005–2009), the sensitivity of rainfall to land cover change in arid regions is found to be dependent on the initial spatial heterogeneity of vegetated land cover. The approach used and the findings in this study represent an important step toward better understanding of large-scale land cover change in the Asian arid regions, and have the potential to predict future land cover change under various climate change scenarios.  相似文献   

10.
This study aimed at clarifying the relationship between the dynamics of land use/land cover (LULC) changes and decline in the groundwater levels, and specifying an LULC category strongly affecting such decline in a Quaternary sedimentary basin. Groundwater level data recorded at 26 observation wells for a 14-year period in the Kumamoto Plain, central Kyushu, southwest Japan, were used for the analysis. The general trends of LULC were detected by a satellite image classification technique and surface spline method, which highlighted the decreases in groundwater-recharge materials. As the next step, those trends of groundwater levels that were closely correlated with rainfall were removed from the level data set, and the resultant residual component levels were applied to co-kriging analysis with LULC categories. Co-kriging provided a detailed map of groundwater level variability. Furthermore, we propose a method, prediction of residual of groundwater level (PWL), to infer future residual groundwater levels from the supposed LULC pattern by co-kriging-based modeling. PWL was demonstrated to be effective because it clearly represented the decrease and increase in negative residual level areas, depending on the extent of rice fields in the past and in predicted future distribution scenarios.  相似文献   

11.
The effects of climate and land use/land cover (LULC) dynamics have directly affected the surface runoff and flooding events. Hence, current study proposes a full-packaged model to monitor the changes in surface runoff in addition to forecast of the future surface runoff based on LULC and precipitation variations. On one hand, six different LULC classes were extracted from Spot-5 satellite image. Conjointly, land transformation model (LTM) was used to detect the LULC pixel changes from 2000 to 2010 as well as predict the 2020 ones. On the other hand, the time series-autoregressive integrated moving average (ARIMA) model was applied to forecast the amount of rainfall in 2020. The ARIMA parameters were calibrated and fitted by latest Taguchi method. To simulate the maximum probable surface runoff, distributed soil conservation service-curve number (SCS-CN) model was applied. The comparison results showed that firstly, deforestation and urbanization have been occurred upon the given time, and they are anticipated to increase as well. Secondly, the amount of rainfall has non-stationary declined since 2000 till 2015 and this trend is estimated to continue by 2020. Thirdly, due to damaging changes in LULC, the surface runoff has been also increased till 2010 and it is forecasted to gradually exceed by 2020. Generally, model calibrations and accuracy assessments have been indicated, using distributed-GIS-based SCS-CN model in combination with the LTM and ARIMA models are an efficient and reliable approach for detecting, monitoring, and forecasting surface runoff.  相似文献   

12.
Landslides every year impose extensive damages to human beings in various parts of the world; therefore, identifying prone areas to landslides for preventive measures is essential. The main purpose of this research is applying different scenarios for landslide susceptibility mapping by means of combination of bivariate statistical (frequency ratio) and computational intelligence methods (random forest and support vector machine) in landslide polygon and point formats. For this purpose, in the first step, a total of 294 landslide locations were determined from various sources such as aerial photographs, satellite images, and field surveys. Landslide inventory was randomly split into a testing dataset 70% (206 landslide locations) for training the different scenarios, and the remaining 30% (88 landslides locations) was used for validation purposes. To providing landslide susceptibility maps, 13 conditioning factors including altitude, slope angle, plan curvature, slope aspect, topographic wetness index, lithology, land use/land cover, distance from rivers, drainage density, distance from fault, distance from roads, convergence index, and annual rainfall are used. Tolerance and the variance inflation factor indices were used for considering multi-collinearity of conditioning factors. Results indicated that the smallest tolerance and highest variance inflation factor were 0.31 and 3.20, respectively. Subsequently, spatial relationship between classes of each landslide conditioning factor and landslides was obtained by frequency ratio (FR) model. Also, importance of the mentioned factors was obtained by random forest (RF) as a machine learning technique. The results showed that according to mean decrease accuracy, factors of altitude, aspect, drainage density, and distance from rivers had the greatest effect on the occurrence of landslide in the study area. Finally, the landslide susceptibility maps were produced by ten scenarios according to different ensembles. The receiver operating characteristics, including the area under the curve (AUC), were used to assess the accuracy of the models. Results of validation of scenarios showed that AUC was varying from 0.668 to 0.749. Also, FR and seed cell area index indicators show a high correlation between the susceptibility classes with the landslide pixels and field observations in all scenarios except scenarios 10RF and 10SVM. The results of this study can be used for landslides management and mitigation and development activities such as construction of settlements and infrastructure in the future.  相似文献   

13.
The sustainability of water resources mainly depends on planning and management of land use; a small change in it may affect water yield largely, as both are linked through relevant hydrological processes, explicitly. However, human activities, especially a significant increase in population, in-migration and accelerated socio-economic activities, are constantly modifying the land use and land cover (LULC) pattern. The impact of such changes in LULC on the hydrological regime of a basin is of widespread concern and a great challenge to the water resource engineers. While studying these impacts, the issue that prevails is the selection of a hydrological model that may be able to accommodate spatial and temporal dynamics of the basin with higher accuracy. Therefore, in the present study, the capabilities of variable infiltration capacity hydrological model to hydrologically simulate the basin under varying LULC scenarios have been investigated. For the present analysis, the Pennar River Basin, Andhra Pradesh, which falls under a water scarce region in India, has been chosen. The water balance components such as runoff potential, evapotranspiration (ET) and baseflow of Pennar Basin have been simulated under different LULC scenarios to study the impact of change on hydrological regime of a basin. Majorly, increase in built-up (13.94% approx.) and decrease in deciduous forest cover (2.44%) are the significant changes observed in the basin during the last three decades. It was found that the impact of LULC change on hydrology is balancing out at basin scale (considering the entire basin, while routing the runoff at the basin outlet). Therefore, an analysis on spatial variation in each of the water balance components considered in the study was done at grid scale. It was observed that the impact of LULC is considerable spatially at grid level, and the maximum increase of 265 mm (1985–2005) and the decrease of 48 mm (1985–1995) in runoff generation at grid were estimated. On the contrary, ET component showed the maximum increase of 400 and decrease of 570 mm under different LULC change scenario. Similarly, in the base flow parameter, an increase of 70 mm and the decrease of 100 mm were observed. It was noticed that the upper basin is showing an increasing trend in almost all hydrological components as compared to the lower basin. Based on this basin scale study, it was concluded that change in the land cover alters the hydrology; however, it needs to be studied at finer spatial scale rather than the entire basin as a whole. The information like the spatial variation in hydrological components may be very useful for local authority and decision-makers to plan mitigation strategies accordingly.  相似文献   

14.
This study investigates how extreme flows in the Grote Nete watershed located in the Flanders region of Belgium will respond to climate change and urban growth using the hydrological model WetSpa. Three climate change scenarios (low, mean and high), three urban development scenarios (low, medium and high) and the nine combined climate–urban change scenarios are considered. The results indicate that extreme low flows would decrease noticeably by climate change, while they would be less sensitive to urban development. On the other hand, extreme peak flows are predicted to increase considerably due to both climate change and urban growth. It is concluded that coupling the effects of land use change with climate change may lead to severe increase in the frequency river floods in winter as well as the frequency of extreme river low flows in summer.  相似文献   

15.
Effective information regarding environmental responses to future land-use and climate change scenarios provides useful support for decision making in land use planning, management and policies. This study developed an approach for modeling and examining the impacts of future land-use and climate change scenarios on streamflow, surface runoff and groundwater discharge using an empirical land-use change model, a watershed hydrological model based on various land use policies and climate change scenarios in an urbanizing watershed in Taiwan. The results of the study indicated that various demand and conversion policies had different levels of impact on hydrological components in all land-use scenarios in the study watershed. Climate changes were projected to have a greater impact in increasing surface runoff and reducing groundwater discharge than are land use changes. Additionally, the spatial distributions of land-use changes also influenced hydrological processes in both downstream and upstream areas, particularly in the downstream watershed. The impacts on hydrological components when considering both land use and climate changes exceeded those when only considering land use changes or climate changes, particularly on surface runoff and groundwater discharge. However, the proposed approach provided a useful source of information for assessing the responses of land use and hydrological processes to future land use and climate changes.  相似文献   

16.
为了探索极端气候事件引发重大地质灾害的综合减灾防灾战略,提高主动减灾防灾的科技能力与管理水平,积极应对全球变化条件下中国地质灾害防治面临的挑战,本文在"全球灾变事件与重大地质灾害减灾战略研究会"与会专家汇报和讨论的基础上,结合近年来国内重大地质灾害事件,从新构造与地震活动,气候变化,人口与城镇化进程三个方面开展分析,试图探讨我国2010年重大地质灾害多发,群发的原因,并对我国地质灾害今后面临的总体形势做出宏观研判。综合分析认为:①近年来全球构造运动和地震活动进入一个新的相对活跃期,我国处于欧亚地震带和环太平洋地震带的交汇区,是现今构造地震活动强烈响应区,尤其是印度板块的强烈活动,使青藏高原周缘地区的地震活动频繁,断裂活动增强,内外动力耦合作用下的地质灾害频发是总体趋势;②全球气候变化引起的极端气候异常条件使地质灾害的成灾模式趋于多样化和复杂化,由于中国大陆是全球最大大陆性气候和海洋性气候交汇地带,也是地貌高差气候变化最大的地区,特别是2010年长时间干旱,汛期集中的高强度、长持时的降雨、局部强暴雨导致大规模滑坡泥石流灾害,尤其是在青藏高原周缘等内动力作用强烈地区,导致地质灾害频发;③人口增长、城镇化进程及工程经济活动是地质灾害发生不可忽视的重要因素,城镇化建设和工程经济活动规模大,且逐步向生态地质环境相对脆弱的地区转移,城镇人口密度快速增加,特别是山区城镇自主防灾减灾意识薄弱,直接导致地质灾害伤亡和损失程度加重。为了应对全球变化条件下的中国地质灾害形势,提高我国地质灾害防灾科技能力与管理水平,从我国地质灾害防灾减灾的现状分析入手,充分借鉴国际自然灾害综合减灾与风险管理的成功经验与策略,从推进中国地质灾害风险管理的角度提出了7点综合减灾建议,以期起到抛砖引玉的作用,推动政府管理部门、专业技术人员参与地质灾害综合减灾的广泛交流与讨论,促进防灾减灾科技与策略在实践中应用,为应对全球变化的中国地质灾害综合减灾集思广益。  相似文献   

17.
In this study, the future landslide population amount risk (LPAR) is assessed based on integrated machine learning models (MLMs) and scenario simulation techniques in Shuicheng County, China. Firstly, multiple MLMs were selected and hyperparameters were optimized, and the generated 11 models were cross-integrated to select the best model to calculate landslide susceptibility; by calculating precipitation for different extreme precipitation recurrence periods and combining the susceptibility results to assess the landslide hazard. Using the town as the basic unit, the exposure and vulnerability of the future landslide population under different Shared Socioeconomic Pathways (SSPs) scenarios in each town were assessed, and then combined with the hazard to estimate the LPAR in 2050. The results showed that the integrated model with the optimized random forest model as the combination strategy had the best comprehensive performance in susceptibility assessment. The distribution of hazard classes is similar to susceptibility, and with an increase in precipitation, the low-hazard area and high-hazard decrease and shift to medium-hazard and very high-hazard classes. The high-risk areas for future landslide populations in Shuicheng County are mainly concentrated in the three southwestern towns with high vulnerability, whereas the northern towns of Baohua and Qinglin are at the lowest risk class. The LPAR increased with the intensity of extreme precipitation. The LPAR differs significantly among the SSPs scenarios, with the lowest in the “fossil-fueled development (SSP5)” scenario and the highest in the “regional rivalry (SSP3)” scenario. In summary, the landslide susceptibility model based on integrated machine learning proposed in this study has a high predictive capability. The results of future LPAR assessment can provide theoretical guidance for relevant departments to cope with future socioeconomic development challenges and make corresponding disaster prevention and mitigation plans to prevent landslide risks from a developmental perspective.  相似文献   

18.
Garg  Vaibhav  Anand  Aishwarya 《GeoJournal》2022,87(4):973-997

Rispana River flows through the heart of Dehradun, the capital city of Uttarakhand State, India. Uttarakhand had separated from Uttar Pradesh State in the year 2000; since then, Dehradun City has witnessed numerous changes. Both urban sprawl and densification were noticed, with around a 32% increase in population. The city had faced recurrent high runoff and urban flood situations in these last 2 decades. Therefore, the study was conducted to detect the change in land use/land cover (LULC), especially urbanization, through remote sensing data; and later to determine the impacts of such changes on the Rispana watershed hydrology. The LULC maps for the year 2003 and the 2017 were generated through supervised classification technique using the Landsat Series satellite datasets. The LULC change analysis depicted that mainly the urban settlement class increased with significant area among other classes from the year 2003–2017. It was noticed that majorly agriculture and fallow land (8.18 km2, which is 13.52% of total watershed area) converted to urban, increasing the impervious area. Almost all the municipal wards, falling in the Rispana watershed, showed urbanization during the said period, with an increase of as high as 71%. The change in LULC or effect of urbanization on the hydrological response of the watershed was assessed using the most widely used Natural Resources Conservation Services Curve Number method. It was noticed that the area under moderated runoff potential (approx. 10.23 km2) steeply increased during the lean season, whereas, high runoff potential zones (5 km2) increased significantly under wet season. Therefore, it was concluded that an increase in impervious surface resulted in high runoff generation. Further, such LULC change along with climate might lead to high runoff within the watershed, which the present storm drainage network could not withstand. The situation generally led to urban floods and affected urban dwellers regularly. Therefore, it is critical to assess the hydrological impacts of LULC change for land use planning and water resource management. Furthermore, under the smart city project, the local government has various plans to improve present infrastructure; therefore, it becomes necessary to incorporate such observations in the policies.

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19.
The human influence on environmental processes has been described for many types of land use. One of the oldest tools to modify people’s environment is fire, which has dominated fire regimes in many regions over long time scales. This paper focuses on a German case study region, where 80–90% of the fires are human-caused. The objectives of this study are the application of the Regional Fire Model (Reg-FIRM), a process-based fire model that is incorporated into the LPJ Dynamic Global Vegetation Model, to temperate forests under historic climate conditions and to explore ranges of potential impacts of future climate change on fire and vegetation dynamics. Simulation experiments are designed to simulate historic fire pattern and to explore influences of vegetation on fire. Simulated fire pattern reproduced the observed average fire conditions reasonably well although with a smaller amplitude. This leads to underestimation of extreme fire years as well as an overestimation of low fire years. Vegetation composition influenced fire spread conditions in the temperate forest and had little impact on fire ignition potentials, except when only broad-leaved deciduous forests were assumed. Fire is likely to change under climate change conditions. Simulated experiments were conducted to explore the effects of climate change and rising CO2 concentration given the potential natural vegetation as the best-case for Brandenburg. Three GCM scenarios predicting different future climatic changes were applied, and resulted in quantitatively different future fire patterns. Depending on future precipitation pattern and the influence of the CO2 effect on canopy conductance and thus litter moisture, fire was predicted to either decrease or slightly increase in Brandenburg forests, but the burnt area would not exceed current, extreme fire years. Generally, fire changes had no implication for vegetation composition in Brandenburg, but reduced vegetation carbon gain after 2050. In the HadCM3 application, simulated increase in grass cover due to a large burnt area after 2075 accelerated fire spread conditions, thus still increasing the burnt area, while climatic fire danger and number of fires already began to decline. These interactions underline the importance to consider the full range of fire processes and interactions with vegetation dynamics in a simulation model.  相似文献   

20.
Heavy rainfall triggered landslides are on the rise along the Western Ghats making it a matter of priority to identify landslide-prone areas well in advance. The present effort is aimed at identifying landslide susceptible villages (LSV) around the Kalsubai region of Deccan volcanic province (DVP), Maharashtra, India from 8 weighted landslide parameters- rainfall, slope, lithology, land use and land cover (LULC), soil properties, relative relief, aspect and lineament. These parameters were combined with advanced remote sensing (RS) data and processed in geographical information system (GIS) as well as in image processing software, which are an integral part of geospatial techniques. Out of the total 59 villages, the study identified 9 villages are situated in very high, 13 in high, 12 in moderate, 11 in low and 14 in very low risk zones. Our data reveals incessant heavy rains and steep slopes are the dominant factors in triggering landslides, exacerbated by anthropogenic activity prevalent in the study area. The spatial and non-spatial database created will help to take effective steps in preventing and/or mitigating landslide disasters in the study area. The methodology can be applied to identify other landslide prone areas in a cost effective way.  相似文献   

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