Effects of historical and projected land use/cover change on runoff and sediment yield in the Netravati river basin,Western Ghats,India

In this study, the effects of changes in historical and projected land use land cover (LULC) on monthly streamflow and sediment yield for the Netravati river basin in the Western Ghats of India are explored using land use maps from six time periods (1972, 1979, 1991, 2000, 2012, and 2030) and the soil and water assessment tool (SWAT). The LULC for 2030 is projected using the land change modeller with the assumption of normal growth. The sensitivity analysis, model calibration, and validation indicated that the SWAT model could reasonably simulate streamflow and sediment yield in the river basin. The results showed that the spatial extent of the LULC classes of urban (1.80–9.96%), agriculture (31.38–55.75%), and water bodies (1.48–2.66%) increased, whereas that of forest (53.04–27.03%), grassland (11.17–4.41%), and bare land (1.09–0.16%) decreased from 1972 to 2030. The streamflow increased steadily (7.88%) with changes in LULC, whereas the average annual sediment yield decreased (0.028%) between 1972 and 1991 and increased later (0.029%) until 2012. However, it may increase by 0.43% from 2012 to 2030. The results indicate that LULC changes in urbanization and agricultural intensification have contributed to the increase in runoff, amounting to 428.65 and 58.67 mm, respectively, and sediment yield, amounting to 348 and 43 ton/km², respectively, in the catchment area from 1972 to 2030. The proposed methodology can be applied to other river basins for which temporal digital LULC maps are available for better water resource management plans.     

Characterizing spatiotemporal dynamics of land cover with multi-temporal remotely sensed imagery in Beijing during 1978–2010

To facilitate urban planning and management in fast-growing metropolitan areas, it is highly necessary to detect the spatiotemporal changes of different land cover types. This study aimed at identifying Beijing’s land cover types and detecting the characteristics of their spatiotemporal changes using time series remote sensing and GIS techniques from 1978 to 2010. A total of 16 Landsat MSS/TM/ETM+ images were collected during the spring and late summer seasons. After preprocessing the dataset, artificial neural network was used to perform the land cover classification. Consequently, four maps were generated for 1978, 1992, 2000, and 2010, with six classes (agriculture, woodland, grassland, water, urban, and barren land) according to the level I classification scheme. Three transition matrices were constructed to represent all possible changes that occur in the landscape. The results showed that agriculture, barren land, and grassland had an increase in area, while urban, water, and woodland had a reduction within the study area. A total of 2,032.341 km² agriculture was reduced and 2,359.146 km² woodland was increased. In the three periods for 1978–1992, 1992–2000, 2000–2010, agriculture had the largest amount of transfer out primarily to urban class around central urban areas and woodland had the most transfer in mainly from barren land in mountainous areas. More importantly, the driving forces analysis including economic development, growth of population and construction areas, and institutional policies was conducted to find out the primary factors inducing the land cover change.     

Driving forces responsible for aeolian desertification in the source region of the Yangtze River from 1975 to 2005

The Yangtze River is the China’s longest river and the third-longest river in the world. The river’s source region in the Qinghai-Tibet Plateau is especially sensitive to global environmental change because of its high elevation and cold environment. Under the influence of global warming, aeolian desertified land has expanded rapidly in this area. To assess the trends in aeolian desertification from 1975 to 2005, remote-sensing and GIS technology were used to monitor the extent of aeolian desertification in 1975, 1990, 2000, and 2005. The data sources included Landsat multi-spectral scanner images acquired in 1975, Enhanced Thematic Mapper (ETM+) images acquired in 2000, and Thematic Mapper (TM) images acquired in 1990 and 2005. Images recorded between June and October were selected, when vegetation grew well, because aeolian desertified land was more easily recognized during this period. Thematic maps, including land use and geomorphologic maps, were used as supplementary data. Aeolian desertification maps (1:100000) were produced for each year from the Landsat images through visual interpretation. The area of aeolian desertified land increased by 2,678.43 km² from 1975 to 2005, accounting for 8.8% of the total area of aeolian desertified land in 1975, an increase of 89.28 km² a⁻¹. Increasing mean annual temperature and the combination of a dry, cold, and windy climate in winter and spring were mainly responsible for the expansion of desertified land.     

Assessing the impacts of changing land cover and climate on Hokersar wetland in Indian Himalayas

Monitoring the spatiotemporal changes in wetlands and assessing their causal factors is critical for developing robust strategies for the conservation and restoration of these ecologically important ecosystems. In this study, the spatiotemporal changes in the land cover system within a Himalayan wetland and its catchment were assessed and correlated using a time series of satellite, historical, and field data. Significant changes in the spatial extent, water depth, and the land system of the Hokersar wetland were observed from the spatiotemporal analysis of the data from 1969 to 2008. The wetland area has shrunk from 18.75 km² in 1969 to 13 km² in 2008 with drastic reduction in the water depth of the wetland. The marshy lands, habitat of the migratory birds, have shrunk from 16.3 km² in 1969 to 5.62 km² in 2008 and have been colonized by various other land cover types. The land system and water extent changes within the wetland were related to the spatiotemporal changes in the land cover and hydrometeorological variables at the catchment scale. Significant changes in the forest cover (88.33–55.78 km²), settlement (4.63–15.35 km²), and water bodies (1.75–0.51 km²) were observed in the catchment. It is concluded that the urbanization, deforestation, changes in the hydrologic and climatic conditions, and other land system changes observed in the catchment are the main causes responsible for the depleting wetland extent, water depth, and biodiversity by adversely influencing the hydrologic erosion and other land surface processes in the catchment. All these causes and effects are manifest in the form of deterioration of the water quality, water quantity, the biodiversity changes, and the decreasing migratory bird population in the wetland.     

Assessment of soil erosion risk using SWAT model

Soil erosion is one of the most serious land degradation problems and the primary environmental issue in Mediterranean regions. Estimation of soil erosion loss in these regions is often difficult due to the complex interplay of many factors such as climate, land uses, topography, and human activities. The purpose of this study is to apply the Soil and Water Assessment Tool (SWAT) model to predict surface runoff generation patterns and soil erosion hazard and to prioritize most degraded sub-catchment in order to adopt the appropriate management intervention. The study area is the Sarrath river catchment (1,491 km²), north of Tunisia. Based on the estimated soil loss rates, the catchment was divided into four priority categories for conservation intervention. Results showed that a larger part of the watershed (90 %) fell under low and moderate soil erosion risk and only 10 % of the watershed was vulnerable to soil erosion with an estimated sediment loss exceeding 10 t?ha^?1?year^?1. Results indicated that spatial differences in erosion rates within the Sarrath catchment are mainly caused by differences in land cover type and gradient slope. Application of the SWAT model demonstrated that the model provides a useful tool to predict surface runoff and soil erosion hazard and can successfully be used for prioritization of vulnerable areas over semi-arid catchments.     

Impact of LULC change on the runoff,base flow and evapotranspiration dynamics in eastern Indian river basins during 1985–2005 using variable infiltration capacity approach

As a catchment phenomenon, land use and land cover change (LULCC) has a great role in influencing the hydrological cycle. In this study, decadal LULC maps of 1985, 1995, 2005 and predicted-2025 of the Subarnarekha, Brahmani, Baitarani, Mahanadi and Nagavali River basins of eastern India were analyzed in the framework of the variable infiltration capacity (VIC) macro scale hydrologic model to estimate their relative consequences. The model simulation showed a decrease in ET with 0.0276% during 1985–1995, but a slight increase with 0.0097% during 1995–2005. Conversely, runoff and base flow showed an overall increasing trend with 0.0319 and 0.0041% respectively during 1985–1995. In response to the predicted LULC in 2025, the VIC model simulation estimated reduction of ET with 0.0851% with an increase of runoff by 0.051%. Among the vegetation parameters, leaf area index (LAI) emerged as the most sensitive one to alter the simulated water balance. LULC alterations via deforestation, urbanization, cropland expansions led to reduced canopy cover for interception and transpiration that in turn contributed to overall decrease in ET and increase in runoff and base flow. This study reiterates changes in the hydrology due to LULCC, thereby providing useful inputs for integrated water resources management in the principle of sustained ecology.     

Assessing and monitoring the human influence on water quality in response to land transformation within Wular environs of Kashmir Valley

Wular Lake is the largest freshwater lake of India located in north western Himalayas of Kashmir Valley which has got deteriorated over the period of time due to the enough human interference within its catchment areas. The purpose of the present research study is to identify the changes in land use and land cover in the Wular catchment as well as its transformation into other classes and its impact on the overall water quality of the lake. For the present study Landsat (TM) image of 1992 and Landsat-8 (OLI) of 2015 have been used for assessing the changes in land use/land cover. Supervised classification technique was used to generate LULC maps of different categories pertaining to study area for years 1992 and 2015. Regarding water quality, water samples were collected from five different spots of the lake in four different seasons of the year—from December 2014 to September 2015. The sites from which samples were collected are Vintage Park, Ashtungo, Watlab, Makhdomyari and Ningal as site 1, 2, 3, 4, and 5 respectively. Some parameters of water like temperature, transparency, depth, conductivity and pH were examined on the spot during the sample collection by their respective measuring instruments. The rest of the parameters were examined in hydrological laboratory within 24 h after collection following the standard methods of APHA (Standard methods for the examination of water and wastewater, 21st edn. American Public Health Association, Washington, DC, 2005). The relationship between the LULC classes and water quality parameters has been calculated with the help of SHDI which has shown both positive and as well as negative results.     

Investigation of land use changes on soil erosion process using geographical information system

Land use change quantified for the last 50 years within and near a fast growing agricultural land in Neka River Basin, using geographic information systems. Land cover and land use change was projected for the next decade using topography, geology, land use maps and remote sensing data of the study area. The study explored the relationships between agricultural land growth and landscape changes. The land use changes assessed among the different land cover classes. It is important to mention that conducting of the present study a very severe land cover changes taken place as the result of agricultural land development. These changes in land cover led to the forest degradation of the study area. Relationship between land-use changes and agricultural growth offered a more robust prediction of soil erosion in Neka watershed. This study aims to find the relationships between land use pattern, erosion and the sediment yield in the study area. The land use coefficient has applied in the model of erosion potential method to forecast the effect of the land type to reduce the erosion. The results of this study indicated that the total sediment yield of the study area has notably decreased to 89.24 % after an appropriate land use/cover alteration. The estimated special erosion for the southern Neka Basin is about 144465.1 m³/km² where after management policy is predicted 15542.9 m³/km²/y. Therefore, the total difference for the study area has estimated about 128922.2 m3/km2/y.     

Land use/cover change and driving force analyses in parts of northern Iran using RS and GIS techniques

To accomplish integrated watershed management and land use planning, it is necessary to study the dynamic spatial pattern of land use and cover change related to socioeconomical and physical parameters. In this study, land use and cover change detection was applied to the Lajimrood Drainage Basin in northern parts of Iran, an area characterized by rich and diversified agricultural and forest mosaic. The main of changes in the study area were forest–arable land transformation, which was only considered in this study. In order to detect these changes, at first, based on 1:25,000 digital topographic maps dated 1967 and 1994 and ETM⁺ satellite image dated 2002, land use map in these three dates were prepared. The results showed that the area with forest land use decreased about 3.2% in transition 1967–2002. Also, arable land increased about 36.9%. We suggested a method to analyze the driving forces and the spatial distribution of land use change. The maps of elevation, slope, and aspect were derived and classified by using digital elevation model (DEM). Also, the maps of distance from road, drainage network, and building area were selected as socioeconomical factors. These maps were overlaid and crossed with land use change map and land use change area ratio was computed. The results showed that the elevation, slope, and aspect were physical effective factors in land use changing. Also, by increasing the distance from building area and roads, deforestation rate was reduced.     

Assessment of the effects of climate and land cover changes on river discharge and sediment yield,and an adaptive spatial planning in the Jakarta region

In Jakarta, climate change has been detected through rising air temperatures, increased intensity of rainfall in the wet season, and sea level rise. The coupling of such changes with local anthropogenic driven modifications in the environmental setting could contribute to an increased probability of flooding, due to increase in both extreme river discharge and sedimentation (as a result of erosion in the watersheds above Jakarta and as indicated by sediment yield in the downstream area). In order to respond to the observed and projected changes in river discharge and sediment yield, and their secondary impacts, adaptation strategies are required. A possible adaptation strategy is through policy making in the field of spatial planning. For example, in Indonesia, presidential regulation number 54 year 2008 (Peraturan Presiden Nomor 54 Tahun 2008—Perpres 54/2008) was issued as a reference for the implementation of water and soil conservation. This paper assesses the impact of climate and land cover change on river discharge and sediment yield, as well as the effects of Perpres 54/2008 on that river discharge and sediment yield. The spatial water balance model Spatial Tools for River Basins and Environmental and Analysis of Management Option was used for the runoff computations, whilst the Spatial Decision Assistance of Watershed Sedimentation model was used to simulate erosion, Sediment Delivery Ratio, and sediment yield. The computation period is from January 1901 to December 2005, at the scale of the following watersheds: Ciujung, Cisadane, Ciliwung, and Citarum. During the twentieth century, computed average discharge in the downstream area (near Jakarta) increased between 2.5 and 35 m³/s/month, and sediment yield increased between 1 × 10³ and 42 × 10³ tons/year. These changes were caused by changes in both land cover and climate, with the former playing a stronger role. Based on a computation under a theoretical full implementation of the spatial plan proposed by Perpres 54/2008, river discharge would decrease by up to 5 % in the Ciliwung watershed and 26 % in the Cisadane watershed. The implementation of Perpres 54/2008 could also decrease the sediment yield, by up to 61 and 22 % in the Ciliwung and Cisadane watersheds, respectively. These findings show that the implementation of the spatial plan of Perpres 54/2008 could significantly improve watershed response to runoff and erosion. This study may serve as a tool for assessing the reduction in climate change impacts and evaluating the role of spatial planning for adaptation strategies.     

Land use land cover dynamics as a function of changing demography and hydrology

This paper describes the spatiotemporal changes pertaining to land use land cover (LULC) and the driving forces behind these changes in Doodhganga watershed of Jhelum Basin. An integrated approach utilizing remote sensing and geographic information system (GIS) was used to extract information pertaining to LULC change. Multi-date LULC maps were generated by analyzing remotely sensed images of three dates which include LandSat TM 1992, LandSat ETM+ 2001 and IRS LISS-III 2005. The LULC information was extracted by adopting on-screen image interpretation technique in a GIS environment at 1:25,000 scale. Based on the analysis, changes were observed in the spatial extent of different LULC types over a period of 13 years. Significant changes were observed in the spatial extent of forest, horticulture, built-up and agriculture. Forest cover in the watershed has decreased by 1.47 %, Agricultural by 0.93 % while as built-up area has increased by 0.92 %. The net decrease in forest cover and agriculture land indicate the anthropogenic interference into surrounding natural ecosystems. From the study it was found that the major driving forces for these changes were population growth and changes in the stream discharge. The changes in the stream discharge were found responsible for the conversion of agricultural land into horticulture, as horticulture has increased by 1.14 % in spatial extent. It has been found that increasing human population together with decreasing stream discharge account for LULC changes in the watershed. Therefore, the existing policy framework needs to focus upon mitigating the impacts of forces responsible for LULC change so as to ensure sustainable development of land resources.     

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.     

Snow cover depletion under changed climate with the help of remote sensing and temperature data

Snow cover depletion curve (SDC) is one of the important variables in snow hydrological applications, and these curves are very much required for snowmelt runoff modeling in a snowfed catchment. Remote sensing is an important source of snow cover area which is used for preparation of SDC. Snow cover maps produced by Moderate Resolution Imaging Spectroradiometer (MODIS) satellites are one of the best source of satellite-based snow cover area at a regular interval. Therefore, in this study, snow cover maps have been prepared for the years 2000?C2005 using MODIS data. The study area chosen viz. Beas basin up to Pandoh dam falls in western Himalayan region. For snowmelt runoff modeling, catchment is divided into number of elevation zones and SDC is required for each zone. When sufficient satellite data are not available due to cloud cover or due to some other reasons, then SDC can to be generated using temperature data. Under changed climate conditions also, modified SDC is required. Therefore, to have SDC under such situations, a relationship between snow cover area and cumulative mean temperature has been developed for each zone of the catchment. This procedure of having snow cover maps has two main purposes. First, it could potentially be used to generate snow cover maps when cloud-free satellite data are not available. Second, it can be used to generate snow-covered area in a new climate to see the impact of climate change on snowmelt runoff studies.     

Assessment of LULC and climate change on the hydrology of Ashti Catchment,India using VIC model

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).     

Forecasting areas vulnerable to forest conversion using artificial neural network and GIS (case study: northern Ilam forests,Ilam province,Iran)

Forest conversion due to illegal logging and agricultural expansion is a major problem that is hampering biodiversity conservation efforts in the Zagros region. Yet, areas vulnerable to forest conversion are unknown. This study aims to predict the spatial distribution of deforestation in western Iran. Landsat images dated 1988, 2001, and 2007 are classified in order to generate digital deforestation maps which locate deforestation and forest persistence areas. Meanwhile, in order to examine deforestation factors’ investigation, deforestation maps with physiographic and human spatial variables are entered into the model. Areas vulnerable to forest changes in the Zagros forest region are predicted by a multilayer perceptron neural network (MLPNN) with a Markov chain model. The results show that about 19,294 ha forest areas are deforested in the last 19 years. The predictive performance of the model appears successful, which is validated using the actual land cover map of the same year from Landsat data. The validated map is found to be 94 % accurate. The validation is also tested using the relative operating characteristic approach which yielded a value of 0.96. The model is then further extended to predict forest cover losses for 2020. The MLPNN approach was found to have a great potential to predict land use/land cover changes because it permits developing complex, nonlinear models.     

Hydrological impacts of land use–land cover change and detention basins on urban flood hazard: a case study of Poisar River basin,Mumbai, India

Flooding in urban area is a major natural hazard causing loss of life and damage to property and infrastructure. The major causes of urban floods include increase in precipitation due to climate change effect, drastic change in land use–land cover (LULC) and related hydrological impacts. In this study, the change in LULC between the years 1966 and 2009 is estimated from the toposheets and satellite images for the catchment of Poisar River in Mumbai, India. The delineated catchment area of the Poisar River is 20.19 km². For the study area, there is an increase in built-up area from 16.64 to 44.08% and reduction in open space from 43.09 to 7.38% with reference to total catchment area between the years 1966 and 2009. For the flood assessment, an integrated approach of Hydrological Engineering Centre-Hydrological Modeling System (HEC-HMS), HEC-GeoHMS and HEC-River analysis system (HEC-RAS) with HEC-GeoRAS has been used. These models are integrated with geographic information system (GIS) and remote sensing data to develop a regional model for the estimation of flood plain extent and flood hazard analysis. The impact of LULC change and effects of detention ponds on surface runoff as well as flood plain extent for different return periods have been analyzed, and flood plain maps are developed. From the analysis, it is observed that there is an increase in peak discharge from 2.6 to 20.9% for LULC change between the years 1966 and 2009 for the return periods of 200, 100, 50, 25, 10 and 2 years. For the LULC of year 2009, there is a decrease in peak discharge from 10.7% for 2-year return period to 34.5% for 200-year return period due to provision of detention ponds. There is also an increase in flood plain extent from 14.22 to 42.5% for return periods of 10, 25, 50 and 100 years for LULC change between the year 1966 and year 2009. There is decrease in flood extent from 4.5% for 25-year return period to 7.7% for 100-year return period and decrease in total flood hazard area by 14.9% due to provisions of detention pond for LULC of year 2009. The results indicate that for low return period rainfall events, the hydrological impacts are higher due to geographic characteristics of the region. The provision of detention ponds reduces the peak discharge as well as the extent of the flooded area, flood depth and flood hazard considerably. The flood plain maps and flood hazard maps generated in this study can be used by the Municipal Corporation for flood disaster and mitigation planning. The integration of available software models with GIS and remote sensing proves to be very effective for flood disaster and mitigation management planning and measures.     

Evaluation of sediment yield and soil loss by the MPSIAC model using GIS at Golestan watershed, northeast of Iran

Watershed degradation due to soil erosion and sedimentation is considered to be one of the major environmental problems in Iran. In order to address the critical conditions of watershed degradation in arid and semiarid regions, a study based on the Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model was carried out at Golestan watershed, northeast of Iran. The model information layers comprising nine effective factors in erosion and sedimentation at the watershed site were obtained by digitalization and spatial interpolation of the basic information data in a GIS program. These factors are geology, soil, climate, runoff, topography, land cover, land use, channel, and upland erosion. The source data for the model were obtained from available records on rainfall and river discharge and sediment, topography, land use, geology, and soil maps as well as field surveys and laboratory analysis. The results of the MPSIAC model indicated that 60.75 % (194.4 km²) and 54.97 % (175.9 km²) of the total watershed area were classified in the heavy sedimentation and erosion classes, and the total basin sediment yield and erosion were calculated as 4,171.1 and 17,813.4 m³ km^?2 year^?1, respectively. In the sensitivity analysis, it was found that the most sensitive parameters of the model in order of importance were topography (slope), land cover and use, runoff, and channel erosion (R ²?=?0.92–0.94), while geology, climate (rainfall), soil, and upland erosion factors were found to have moderate effect to the model output (R ²?=?0.74–0.59).     

Landslide susceptibility mapping using rough sets and back-propagation neural networks in the Three Gorges, China

In the Three Gorges of China, there are frequent landslides, and the potential risk of landslides is tremendous. An efficient and accurate method of generating landslide susceptibility maps is very important to mitigate the loss of lives and properties caused by these landslides. This paper presents landslide susceptibility mapping on the Zigui-Badong of the Three Gorges, using rough sets and back-propagation neural networks (BPNNs). Landslide locations were obtained from a landslide inventory map, supported by field surveys. Twenty-two landslide-related factors were extracted from the 1:10,000-scale topographic maps, 1:50,000-scale geological maps, Landsat ETM + satellite images with a spatial resolution of 28.5 m, and HJ-A satellite images with a spatial resolution of 30 m. Twelve key environmental factors were selected as independent variables using the rough set and correlation coefficient analysis, including elevation, slope, profile curvature, catchment aspect, catchment height, distance from drainage, engineering rock group, distance from faults, slope structure, land cover, topographic wetness index, and normalized difference vegetation index. The initial, three-layered, and four-layered BPNN were trained and then used to map landslide susceptibility, respectively. To evaluate the models, the susceptibility maps were validated by comparing with the existing landslide locations according to the area under the curve. The four-layered BPNN outperforms the other two models with the best accuracy of 91.53 %. Approximately 91.37 % of landslides were classified as high and very high landslide-prone areas. The validation results show sufficient agreement between the obtained susceptibility maps and the existing landslide locations.     

Soil erosion risk assessment of the Keiskamma catchment,South Africa using GIS and remote sensing

This paper examines the soil loss spatial patterns in the Keiskamma catchment using the GIS-based Sediment Assessment Tool for Effective Erosion Control (SATEEC) to assess the soil erosion risk of the catchment. SATEEC estimates soil loss and sediment yield within river catchments using the Revised Universal Soil Loss Equation (RUSLE) and a spatially distributed sediment delivery ratio. Vegetation cover in protected areas has a significant effect in curtailing soil loss. The effect of rainfall was noted as two pronged, higher rainfall amounts received in the escarpment promote vegetation growth and vigour in the Amatole mountain range which in turn positively provides a protective cover to shield the soil from soil loss. The negative aspect of high rainfall is that it increases the rainfall erosivity. The Keiskamma catchment is predisposed to excessive rates of soil loss due to high soil erodibility, steep slopes, poor conservation practices and low vegetation cover. This soil erosion risk assessment shows that 35% of the catchment is prone to high to extremely high soil losses higher than 25 ton ha⁻¹ year⁻¹ whilst 65% still experience very low to moderate levels of soil loss of less than 25 ton ha⁻¹ year⁻¹. Object based classification highlighted the occurrence of enriched valley infill which flourishes in sediment laden ephemeral stream channels. This occurrence increases gully erosion due to overgrazing within ephemeral stream channels. Measures to curb further degradation in the catchment should thrive to strengthen the role of local institutions in controlling conservation practice.     

Quantifying modern erosion rates and river-sediment contamination in the Bolivian Andes

We use petrographic, mineralogical and geochemical data on modern river sediments of the Tupiza basin in the Bolivian Andes to investigate the relationships among human activity, heavy-metal contamination of sediments and modern erosion rates in mountain fluvial systems. Forward mixing model was used to quantify the relative contributions from each main tributary to total sediment load of the Tupiza River. The absolute sediment load was estimated by using the Pacific Southwest Inter Agency Committee model (PSIAC, 1968) after two years of geological field surveys (2009; 2010), together with data obtained from the Instituto Nacional del Agua public authority (INA, 2007), and suspended-load data from Aalto et al. (2006).Our results indicate that the sediment yield in the drainage basin is 910 ± 752 ton/km²year and the mean erosion rate is 0.40 ± 0.33 mm/year. These values compare well with erosion rates measured by Insel et al. (2010) using ¹⁰Be cosmogenic radionuclide concentrations in Bolivian river sediments. More than 40% of the Tupiza river load is produced in the upper part of the catchment, where highly tectonized and weathered rocks are exposed and coupled with sporadic land cover and intense human activity (mines). In the Rio Chilco basin strong erosion of upland valleys produce an increase of erosion (∼10 mm/year) and the influx of large amounts of sediment by mass wasting processes. The main floodplain of the Tupiza catchment represents a significant storage site for the heavy metals (∼657 ton/year). Fluvial sediments contain zinc, lead, vanadium, chromium, arsenic and nickel. Since the residence time of these contaminants in the alluvial plain may be more than 100 years, they may represent a potential source of pollution for human health.