Fluoride occurrence and mobilization in geo-environment of semi-arid Granite watershed in southern peninsular India

Plausible forms of fluoride (F) responsible for the persistence of fluoride toxicity in ground water of a granitic terrain of semi-arid region, which is the main source of drinking water, have been studied. The study area in Anantapur District of Andhra Pradesh, India, is one of the chronic regions with excess fluoride in groundwater and the region is under transformation into aridity due to poor rainfall and over-exploitation of groundwater. Geochemical analysis of soil, groundwater, and rock samples of the study area revealed the presence of other toxic elements also in addition to fluoride which need to be addressed in drinking water sector in near future. Soil fluoride leaching experiments demonstrated the probable mode of mobilization of F into the groundwater through natural recharge process during monsoon. Analysis of saturation indices indicates that the fluorite solubility alone is not attributable to the high fluoride content in groundwater. The groundwater flow controls fluoride mobilization in the study area as it is evidenced through fluoride concentration and electrical conductivity increase from catchment to downstream region. Creation of lesser fluoride groundwater sources through rainwater harvesting and artificial recharge of groundwater in catchment areas is suggested as a long-term sustainable safe drinking water strategy.     

整合陆地表面温度与植被指数信息进行地表覆盖变化研究

利用植被指数(NDVI)的多时相或时序资料进行地表覆盖研究已取得了大量成果。随着陆地表面温度(LST)遥感反演精度的不断提高,将LST与NDVI结合起来进行地表植被动态变化的监测已成为可能。选择我国北方草地及其东南部毗邻的农牧交错带(farmingpastoralzone)为研究区。该区位于内蒙古高原东南边缘和黄土高原北部,半干旱气候,经纬度范围为:35°～50°N,100°～125°E。     

Long term changes in forest cover and land use of Similipal Biosphere Reserve of India using satellite remote sensing data

The spatial changes in forest cover of Similipal biosphere reserve, Odisha, India over eight decades (1930–2012) has been quantified by using multi-temporal data from different sources. Over the period, the forest cover reduced by 970.8 km² (23.6% of the total forest), and most significantly during the period, 1930–1975. Human-induced activities like conversion of forest land for agriculture, construction of dams and mining activities have been identified as major drivers of deforestation. Spatial analysis indicates that 399 grids (1 grid = 1 × 1 km) have undergone large-scale changes in forest cover (>75 ha) during 1930–1975, while only 3 grids have shown >75 ha loss during 1975–1990. Annual net rate of deforestation was 0.58 during 1930–1975, which has been reduced substantially during 1975–1990 (0.04). Annual gross rate of deforestation in 2006–2012 is indeed low (0.01) as compared to the national and global average. This study highlights the impact and effectiveness of conservation practices in minimizing the rate of deforestation and protecting the Similipal Biosphere Reserve.     

The impact of land use and land cover changes on soil erosion in western Iran

Natural Hazards - Analysis of long-term land use and land cover (LULC) changes requires up-to-date remotely sensed data to assess their effects on erosion. This is a particularly important...     

Monitoring and prediction of land use/land cover changes using CA-Markov model: a case study of Ravansar County in Iran

Human‐induced land use/land cover (LULC) changes are among the most important processes that shape the dynamics of the earth’s surface. This phenomenon, which is occurring at an astonishing rate, and its consequential environmental impacts have become an important area of research for scientists.Therefore, a wide range of methods and models have been developed to detect and predict these alterations, among which cellular automata (CA) models such as the CA‐Markov model, due to their affinity to geographic information system (GIS) and remote sensing (RS), are appropriate for detailed resolution modelling and simulating dynamic spatial processes. In Iran, the district of Ravansar has undergone severe LULC changes recently, thus to take the necessary precautions, decision‐makers need to predict and determine the extent of these changes. In this study, using spatial analysis methods the LULC changes in Ravansar were investigated from 1992 to 2015. Subsequently, the CA‐Markov model was applied to simulate the spatial pattern changes of LULC until 2030. Our results indicated that from 1992 to 2015, this region has witnessed a noticeable increase in the areas of the built‐up and agricultural lands (both aquatic and non‐aquatic), resulting in the decrease of the gardens, range, and bare lands. The simulated LULC map showed that this trend will continue due to more urbanization and development of agricultural areas.     

Co-kriging for modeling shallow groundwater level changes in consideration of land use/land cover pattern

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.     

Observed trends of climate and land cover changes in Lake Baikal basin

Land cover and vegetation in Lake Baikal basin (LBB) are considered to be highly susceptible to climate change. However, there is less information on the change trends in both climate and land cover in LBB and thus less understanding of the watershed sensitivity and adaptability to climate change. Here we identified the spatial and temporal patterns of changes in climate (from 1979 to 2016), land cover, and vegetation (from 2000 to 2010) in the LBB. During the past 40 years, there was a little increase in precipitation while air temperature has increased by 1.4 °C. During the past 10 years, land cover has changed significantly. Herein grassland, water bodies, permanent snow, and ice decreased by 485.40 km², 161.55 km² and 2.83 km², respectively. However, forest and wetland increased by 111.40 km² and 202.90 km², respectively. About 83.67 km² area of water bodies has been converted into the wetland. Also, there was a significant change in Normalized Difference Vegetation Index (NDVI), the NDVI maximum value was 1 in 2000, decreased to 0.9 in 2010. Evidently, it was in the mountainous areas and in the river basin that the vegetation shifted. Our findings have implications for predicting the safety of water resources and water eco-environment in LBB under global change.     

Changing land use/land cover patterns and growing human population in Wular catchment of Kashmir Valley,India

GeoJournal - The profound increase in human activities and the degrading scenario in fragile ecosystems of the western Himalayas like that of Wular Lake have highlighted the need to analyze the...     

Impacts of land use and land cover changes upon organic productivity values in Karst ecosystems: a case study of Northwest Guangxi, China

Karst areas are one of the most fragile regions in the world. The Karst environment is very common in southwest China with severe poverty and environmental degradation. Therefore, it is necessary to monitor the Karst ecosystem and its ability to provide goods and services for society. In this paper, we analyzed the spatial distribution of organic productivity values (OPV) in Northwest Guangxi, China in 1985, 1990, 2000, and 2005 using remote sensing and geographic information system techniques. OPV showed a decreasing trend in the last 20 years though there were fluctuations. OPV was 184.85, 117.53, 163.66 and 177.25 million Yuan in 1985, 1990, 2000 and 2005, respectively. Woodland and shrub were the two largest contributors to total OPV. They accounted for 70.51%, 69.13%, 73.92% and 66.23%, respectively, in those four years. Conversely, OPVof residential and barren rock was low with a percentage of 0.70%, 0.56%, 0.57% and 0.90%, respectively. Spatially, OPVis higher in the west than in the east. However, OPV increased in typical Karst areas but decreased in non-Karst areas. Our study indicates that ecosystem conditions in Karst areas had improved because of the application of rocky desertification control policies.     

Effects on runoff caused by changes in land cover in a Brazilian southeast basin: evaluation by HEC-HMS and HEC-GEOHMS

The Southeast Region of Brazil has undergone major changes in land cover, especially after the eighteenth century. It is currently the most populous region of the country, highly urbanized, with a high degree of industrial and agricultural development. Extensive areas of native vegetation have been replaced by pastures, crops and urban areas, which have increased runoff, causing environmental, economic and social problems related to flooding. The objective of this study was to analyze effects of land cover changes in a basin with rural and urban characteristics on the flow of its main river. Hydrological data, orbital images, soils and topographical maps were used for this purpose. Based on the land cover maps for the years of 1989, 2001 and 2015, and on the hydrological modeling performed using the Hec-HMS 4.1 software, scenarios were simulated and showed that the land cover changes in this basin significantly affect the flow behavior of the main river. The simulated runoff was calibrated using the data observed in the field during 2001, and validation was performed using data from 1989. After the calibration and validation processes, a scenario was simulated where the rainiest month of the whole series measured by the rainfall station (during December 1989) acted on the land cover of 2015. There was an increase in pasture areas and impermeable spaces in the basin, which caused a decrease in infiltration and an increase in surface runoff, and also an increase in the flow peaks and a reduction in the time of concentration. The hydrological modeling was satisfactory, since the uncertainties related to the simulation were low.     

猫跳河流域土地覆被变化及其驱动力定量研究

应用RS、GIS以及GPS集成技术,以黔中喀斯特地区的猫跳河流域为对象,研究了这一地区从1973—2002年间土地利用／覆被的变化过程,并利用典型相关分析法研究了形成这种变化的驱动因素。研究表明,从1973—1990年,猫跳河流域耕地、建设用地、有林地、水域以及裸岩地呈增长趋势,而灌木林和灌草地趋于减少,流域生态环境质量下降。进入20世纪90年代后,有林地、灌草地、建设用地、水域持续增加,灌草地总量变化不大,耕地总量和裸岩地减少,流域生态环境质量趋于好转。定量分析表明,1990年以前,驱动建设用地变化的因素是总人口的变化,1990年以后则是农业产值;1990年以前驱动耕地变化的是农业人口的增长,1990年以后则和粮食产量的提高有关。      

Uncertainties in downscaled relative humidity for a semi-arid region in India

Monthly scenarios of relative humidity (R _H) were obtained for the Malaprabha river basin in India using a statistical downscaling technique. Large-scale atmospheric variables (air temperature and specific humidity at 925 mb, surface air temperature and latent heat flux) were chosen as predictors. The predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis dataset for the period 1978–2000, and (2) simulations of the third generation Canadian Coupled Global Climate Model for the period 1978–2100. The objective of this study was to investigate the uncertainties in regional scenarios developed for R _H due to the choice of emission scenarios (A1B, A2, B1 and COMMIT) and the predictors selected. Multi-linear regression with stepwise screening is the downscaling technique used in this study. To study the uncertainty in the regional scenarios of R _H, due to the selected predictors, eight sets of predictors were chosen and a downscaling model was developed for each set. Performance of the downscaling models in the baseline period (1978–2000) was studied using three measures (1) Nash–Sutcliffe error estimate (E _f), (2) mean absolute error (MAE), and (3) product moment correlation (P). Results show that the performances vary between 0.59 and 0.68, 0.42 and 0.50 and 0.77 and 0.82 for E _f, MAE and P. Cumulative distribution functions were prepared from the regional scenarios of R _H developed for combinations of predictors and emission scenarios. Results show a variation of 1 to 6% R _H in the scenarios developed for combination of predictor sets for baseline period. For a future period (2001–2100), a variation of 6 to 15% R _H was observed for the combination of emission scenarios and predictors. The variation was highest for A2 scenario and least for COMMIT and B1 scenario.     

SWAT manual calibration and parameters sensitivity analysis in a semi-arid watershed in North-western Morocco

Being a laborious approach, manual calibration of hydrologic model in a semi-arid context requires in-depth knowledge of the watershed and as much as possible field input data to obtain reliable simulations. In this study, manual calibration and relative sensitivity analysis approaches of the SWAT model (Soil and Water Assessment Tool) were applied for water balance in a 1993 km² watershed (on the R’dom river) located in North-western Morocco. The watershed is located in a semi-arid area dominated by agro-forestry activities. The objectives of this study were (i) to perform a local sensitivity analysis of the SWAT model taking into consideration the watershed characteristics and (ii) to implement a detailed methodology of manual calibration and validation of the model in a semi-arid context. Sensitivity analysis has been carried out on 12 different SWAT input parameters, and has revealed that 4 input parameters only were the most influential ones on flow components of the R’dom watershed. Model manual calibration was conducted along 2006 and 2007 by comparing measured and predicted monthly and daily discharges and taking Nash-Sutcliffe coefficient (NSE), determination coefficient (R ²), and percent bias (PBIAS) as goodness-of-fit indicators. Validation has been performed by the same approach through 2008 and 2009 period. All final NSE values were above 0.5, R ² values exceeded 0.7, and PBIAS lower than 25% demonstrating satisfactory model performances over the study watershed conditions. The SWAT model set-up with measured input data, manually calibrated and validated, reflects well the real hydrologic processes occurring in the R’dom watershed and can be used to assess current and future conditions and to evaluate alternative management practices.     

Land use and land cover change and implication to watershed degradation by using GIS and remote sensing in the Koga watershed,North Western Ethiopia

Information on use/land cover change is important for planners and decision makers to implement sustainable use and management of resources. This study was intended to assess the land use land cover (LULC) change in the Koga watershed. The MSS of 1973, TM images of 1986, 1995 and 2011 were used together with survey and demographic data to detect the drivers of land cover changes. The result revealed that a remarkable LULC change occurred in the study area for the past thirty eight years. The area of cultivated and settlement has increased by 7054.6 ha, while, grass and bush lands decreased by 4846.5 and 3376 ha respectively. Wetland also declined from 580.2 ha to 68.3 ha. The growing demand for cultivable land and fuel wood were the major causes to the deterioration of grass and bush lands. Hence, the appropriate land use policy should be employed to sustain available resource in the watershed.     

Assessing the impacts of land use changes on watershed hydrology using MIKE SHE

A fully distributed, physically-based hydrologic modeling system, MIKE SHE, was used in this study to investigate whole-watershed hydrologic response to land use changes within the Gyeongancheon watershed in Korea. A grid of 200 × 200 m was established to represent spatial variations in geology, soil, and land use. Initial model performance was evaluated by comparing observed and simulated streamflow from 1988 to 1991. Results indicated that the calibrated MIKE SHE model was able to predict streamflow well during the calibration and validation periods. Proportional changes in five classes of land use within the watershed were derived from multi-temporal Landsat TM imageries taken in 1980, 1990 and 2000. These imageries revealed that the watershed experienced conversion of approximately 10% non-urban area to urban area between 1980 and 2000. The calibrated MIKE SHE model was then programmed to repeatedly analyze an artificial dataset under the various land use proportions identified in the Landsat TM imageries. The analysis was made to quantitatively assess the impact of land use changes (predominantly urbanization) on watershed hydrology. There were increases in total runoff (5.5%) and overland flow (24.8%) as a response to the land use change.     

SAR polarimetric decomposition with ALOS PALSAR-1 for agricultural land and other land use/cover classification: case study in Rajasthan,India

Synthetic aperture radar (SAR) has operational applications in crop mapping and monitoring in many countries due to the distinct backscatter signature at various stages of crop growth. Polarimetric analysis of SAR data from different satellites was used for information extraction from different types of scatters in imaged terrain. The scattering processes were analyzed through the received scatter matrix derived from the target decomposition of SAR data. Three decomposition techniques, namely Freeman–Durden, Cloude–Pottier and Touzi decomposition of the ALOS PALSAR-1 data, were used in this study to extract land use/cover information with a specific emphasis on agriculture. The decomposed output parameters from these techniques were classified with supervised classifier of support vector machine (SVM) using region of interest (ROI) selected land use/cover classes. An accuracy assessment for the classified output was carried out using the ROI. The Ramgarh village in Jaisalmer district of Rajasthan with the predominance of agricultural land, sand dunes and settlements was chosen as the study area. Freeman–Durden decomposition resulted in the highest overall accuracy of about 85% in the land use/cover classification among the three decomposition techniques adopted in the study. It was also observed that the accuracy of land use/cover mapping derived from Cloude–Pottier and Touzi decompositions improved with the use of eigenvalues in the SVM classification. Higher accuracies in the classification of agriculture land were noted with all the three decomposition techniques. The four parameters of Cloude–Pottier (H, A, α, β) and Touzi (α _s, Φ _s, ψ, τ) decompositions improved the classification accuracy for all the classes due to eigenvalues. The overall classification accuracy was above 88% for both the decomposition techniques with four parameters. The soil moisture values for agriculture land and sand dunes were validated through soil moisture maps generated using Oh 1992 and 2004 models.     

Confronting scale in watershed development in India

The issue of scale is examined in the context of a watershed development policy (WSD) in India. WSD policy goals, by improving the natural resource base, aim to improve the livelihoods of rural communities through increased sustainable production. It has generally been practiced at a micro-level of less than 500?ha, as this was seen to be a scale that would encourage participative management. There has been some concern that this land area may be too small and may lead to less than optimal hydrological, economic and equity outcomes. As a result there has been a move to create guidelines for meso-scale WSD of above 5,000?ha in an endeavour to improve outcomes. A multidisciplinary team was assembled to evaluate the proposed meso-scale approach. In developing an adequate methodology for the evaluation it soon became clear that scale in itself was not the only determinant of success. The effect of geographical scale (or level) on WSD is determined by the variation in other drivers that will influence WSD success such as hydrological conditions, land use and available institutional structures. How this should be interpreted at different levels in the light of interactions between biophysical and socio-economic scales is discussed.     

Analysing land and vegetation cover dynamics during last three decades in Katerniaghat wildlife sanctuary,India

The change in the tropical forests could be clearly linked to the expansion of the human population and economies. An understanding of the anthropogenic forcing plays an important role in analyzing the impacts of climate change and the fate of tropical forests in the present and future scenario. In the present study, we analyze the impact of natural and anthropogenic factors in forest dynamics in Katerniaghat wildlife sanctuary situated along the Indo-Nepal border in Uttar Pradesh state, India. The study site is under tremendous pressure due to anthropogenic factors from surrounding areas since last three decades. The vegetation cover of the sanctuary primarily comprised of Shorea robusta forests, Tectona grandis plantation, and mixed deciduous forest; while the land cover comprised of agriculture, barren land, and water bodies. The classification accuracy was 83.5%, 91.5%, and 95.2% with MSS, IKONOS, and Quickbird datasets, respectively. Shorea robusta forests showed an increase of 16 km²; while Tectona grandis increased by 63.01 km² during 1975–2010. The spatial heterogeneity in these tropical vegetation classes surrounded by the human dominated agricultural lands could not be addressed using Landsat MSS data due to coarse spatial resolution; whereas the IKONOS and Quickbird satellite datasets proved to advantageous, thus being able to precisely address the variations within the vegetation classes as well as in the land cover classes and along the edge areas. Massive deforestation during 1970s along the adjoining international boundary with Nepal has led to destruction of the wildlife corridor and has exposed the wildlife sanctuary to human interference like grazing and poaching. Higher rates of forest dynamics during the 25-year period indicate the vulnerability of the ecosystem to the natural and anthropogenic disturbances in the proximity of the sanctuary.