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.     

S patio-temporal pattern of land use and land cover and its effects on land surface temperature using remote sensing and GIS techniques: a case study of Bhubaneswar city,Eastern India (1991–2021)

Urbanization produces substantial land use changes by causing the construction of different urban infrastructures in the city region for habitation, transportation, industry, and other reasons. As a result, it has a significant impact on Land Surface Temperature (LST) by disrupting the surface energy balance. The objective of this paper is to assess the impact of land-use/land-cover (LU/LC) dynamics on urban land surface temperature (LST) of Bhubaneswar City in Eastern India during 30 years (1991–2021) using Landsat data (TM, ETM + , and OLI/TIRS) and machine learning algorithms (MLA). The finding reveals that the mean LST over the entire study domain grows significantly between 1991 and, 2021due to urbanization (β coefficient 0.400, 0.195, 0.07, and 0.06 in 1991, 2001, 2011, and 2021 respectively) and loss of green space (β coefficient − 0.295, − 0.025, − 0.125 and − 0.065 in 1991, 2001, 2011 and 2021 respectively). The highest class recorded for agricultural land (49.60 km², accounting for 33.94% of the total land area) was in 1991 followed by vegetation (41.27 km², 28.19% of the total land area), and built-up land (27.59 km², 18.84% of the total land area). The sharp decline of vegetation cover will continue until 2021 due to increasing built-up areas (r = − 0.531, − 0.329, − 0.538, and − 0.063 in the 1991, 2001, 2011 and 2021 respectively). Built-up land (62.60 km², accounting for 42.76% of the total land area, an increase of 35.01 km² from 1991) as the highest class followed by water bodies (21.57%, 32.60 km² of the land area), and agricultural land (31.57 km², 21.57% of the land area) in 2021. Remote sensing techniques proved to be an important tool to urban planners and policymakers to take adequate steps to promote sustainable development and minimize urbanization influence on LST. Urban green space (UGS) can help improve the overall liveability and environmental sustainability of Bhubaneswar city.

     

Land cover change dynamics mapping and predictions using EO data and a GIS-cellular automata model: the case of Al-Baha region,Kingdom of Saudi Arabia

The present study designed to monitor and predict land cover change (LCC) in addition to characterizing LCC and its dynamics over Al-Baha region, Kingdom of Saudi Arabia, by utilizing remote sensing and GIS-cellular automata model (Markov-CA). Moreover, to determine the effect of rainwater storage reservoirs as a driver to the expansion of irrigated cropland. Eight Landsat 5/7 TM/ETM images from 1975 to 2010 were analyzed and ultimately utilized in categorizing LC. The LC maps classified into four main classes: bare soil, sparsely vegetated, forest and shrub land, and irrigated cropland. The quantification of LCC for the analyzed categories showed that bare soil and sparsely vegetated was the largest classes throughout the study period, followed by forest, shrubland, and irrigated cropland. The processes of LCC in the study area were not constant, and varied from one class to another. There were two stages in bare soil change, an increase stage (1975–1995) and decline stage (1995–2010), and the construction of 25 rainwater-harvesting dams in the region was the turning point in bare soil change. The greatest increase was observed in irrigated cropland after 1995 in the expense of the other three categories as an effect of extensive rainwater harvesting practices. Losses were evident in forest and shrubland and sparsely vegetated land during the first stage (1975–1995) with 5.4 and 25.6 % of total area in 1995, while in 1975, they covered more than 13.8 and 32.7 % of total area. During the second stage (1995–2010), forest and shrubland witnessed a significant increase from 1569.17 km² in 1975 to 1840.87 km² in 2010. Irrigated cropland underwent the greatest growth (from 422.766 km² in 1975 to 1819.931 km² in 2010) during the entire study period, and this agriculture expansion reached its zenith in the 2000s. Markov-CA simulation in 2050 predicts a continuing upward trend in irrigated cropland and forest and shrubland areas, as well as a downward trend in bare soil and sparsely vegetated areas; the spatial distribution prediction indicates that irrigated cropland will expand around reservoirs and the mountain areas. The validation result showed that the model successfully identified the state of land cover in 2010 with 97 % agreement between the actual and projected cover. The output of this study would be useful for decision makers and LC/land use planners in Saudi Arabia and similar arid regions.     

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.     

Linkage of urban expansion and land surface temperature using geospatial techniques for Jaipur City,India

The aim of this study is to understand the land use change and urban expansion of Jaipur City of Rajasthan (India). Landsat 5 TM and Landsat 8 OLI satellite data of 4 years, i.e., 1993, 2000, 2010, and 2015 are used for land use and land surface temperature (LST) analysis. ERDAS Imagine and ArcGIS software are used to conduct the analysis. Urban settlement increased from 13.5 to 57.3% in the study period. Open land is mainly changed to urban areas. Urban settlement is also expanded to peri-urban area of Jaipur City. Jaipur City expanded along three directions i.e., north, west, and south and less development is found in the east direction. Based on radial analysis, it is observed there is not much development within the periphery of 2 km (close to city center) but maximum growth is observed within the distance from 4 to 6 km radius of city center. Expansion intensity was observed highest in the period 2015–2010 from 6 km onwards and reached to a maximum value close to 17 km²/year. In LST analysis, there is less change in extreme temperature, but more areal increase in average temperature range (30–35 °C). Urbanization is the main driving process of land cover changes and consequently changes in LST.     

A monitoring framework for land use around kaolin mining areas through Landsat TM images

Sustainable management of land requires regular acquisition of qualitative information regarding the status of its use. It is especially important to track the changes relating to the land’s competitive development needs such as mining. The field-based monitoring of a mine with a wide footprint is expensive and time-consuming. Remote sensing techniques have been developed and demonstrated as cost-effective alternatives for the conventional methods of land use/land cover (LULC) monitoring. In this study, the land cover changes that occurred between the year of 2000 and 2009 in a kaolin mining and processing area in the Kutch region of India are mapped using two Landsat-5 Thematic Mapper (TM) images. For this purpose, the spectral signature of the land covers including vegetation cover and kaolin were determined and matched filtering (MF) method was applied to classify the images. The overall accuracy of the classified 2009 image was estimated for the kaolin and the vegetation cover to 89.5 and 86.0 % respectively. The change in the land use which occurred from 2000 to 2009 were quantified and analysed for both classes. This study provided a practical framework for rapid mapping of the land cover changes around open-cut kaolin mining area using freely available Landsat data.     

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).     

Analyzing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model

Historical and exact information about the land use/land cover change is very important for regional sustainable development. The aim of this paper is to determine the rapid changes in land use/land cover (LULC) pattern due to agriculture expansion, environmental calamities such as flood and government policies over Upper Narmada basin, India. Multi-temporal Landsat satellite images for years 1990, 2000, 2010 and 2015 were used to analyze and monitor the changes in LULC with an overall accuracy of more than 85%. Results revealed a potential decrease in natural vegetation (? 9.52%) due to the expansion of settlement (+ 0.52%) and cropland (+ 9.43%) from 1990 to 2015. In the present study, Cellular Automata and Markov (CA–Markov), an integrated tool was used to project the short-term LULC map of year 2030. The projected LULC (2030) indicated the expansion of built-up area along with the cropland and degradation in the vegetation area. The outcomes from the study can help as a guiding tool for protection of natural vegetation and the management of the built-up area. Additionally, it will help in devising the strategies to utilize every bit of land in the study area for decision makers.     

Land subsidence and earth fissures in south-central and southern Arizona,USA

Land subsidence due to groundwater overdraft has been an ongoing problem in south-central and southern Arizona (USA) since the 1940s. The first earth fissure attributed to excessive groundwater withdrawal was discovered in the early 1950s near Picacho. In some areas of the state, groundwater-level declines of more than 150 m have resulted in extensive land subsidence and earth fissuring. Land subsidence in excess of 5.7 m has been documented in both western metropolitan Phoenix and Eloy. The Arizona Department of Water Resources (ADWR) has been monitoring land subsidence since 2002 using interferometric synthetic aperture radar (InSAR) and since 1998 using a global navigation satellite system (GNSS). The ADWR InSAR program has identified more than 25 individual land subsidence features that cover an area of more than 7,300 km². Using InSAR data in conjunction with groundwater-level datasets, ADWR is able to monitor land subsidence areas as well as identify areas that may require additional monitoring. One area of particular concern is the Willcox groundwater basin in southeastern Arizona, which is the focus of this paper. The area is experiencing rapid groundwater declines, as much as 32.1 m during 2005–2014 (the largest land subsidence rate in Arizona State—up to 12 cm/year), and a large number of earth fissures. The declining groundwater levels in Arizona are a challenge for both future groundwater availability and mitigating land subsidence associated with these declines. ADWR’s InSAR program will continue to be a critical tool for monitoring land subsidence due to excessive groundwater withdrawal.     

The streamflow trend in Tangwang River basin in northeast China and its difference response to climate and land use change in sub-basins

In this study, the hydro-climatic trends (1964–2006) of Tangwang River basin (TRB) were examined using the Kendall’s test. Moreover, the impacts of climate variability and land use change on streamflow in each sub-basin were assessed using the Soil and Water Assessment Tools (SWAT) model. The results indicated that annual mean flow and peak flow showed insignificant decreasing trends (?0.14 m³ s^?1 year^?1, 1 %; ?8.67 m³ s^?1 year^?1, 40 %), while annual low flow exhibited a slightly increasing trend (0.02 m³ s^?1 year^?1, 11 %). Correspondingly, the annual precipitation for the entire basin decreased by 0.02 mm year^?2, while the annual means of daily mean, maximum and minimum temperature increased significantly by 0.07, 0.10 and 0.02 °C year^?1, respectively. On the other hand, with the implementation of “Natural Forest Protection Project” and “Grain for Green Project”, the forests in TRB totally increased by 744.5 km² (4.00 %) from 1980 to 2000. Meanwhile, the grasslands and the farmlands decreased by 378.0 km² (?1.98 %) and 311.9 km² (?1.63 %), respectively. Overall, land use changes played a more important role for the streamflow reduction than climate change for SUB1, SUB2 and SUB3, in which the primary conversions were from grassland, farmland and bare land to forests. Conversely, in SUB4, the influence of climate variability was predominant. The results obtained could be a reference for water resources planning and management under changing environment.     

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.     

Hazard assessment at Mount Etna using a hybrid lava flow inundation model and satellite-based land classification

Using a lava flow emplacement model and a satellite-based land cover classification, we produce a map to allow assessment of the type and quantity of natural, agricultural and urban land cover at risk from lava flow invasion. The first step is to produce lava effusion rate contours, i.e., lines linking distances down a volcano??s flank that a lava flow will likely extend if fed at a given effusion rate from a predetermined vent zone. This involves first identifying a vent mask and then running a downhill flow path model from the edge of every pixel around the vent mask perimeter to the edge of the DEM. To do this, we run a stochastic model whereby the flow path is projected 1,000 times from every pixel around the vent mask perimeter with random noise being added to the DEM with each run so that a slightly different flow path is generated with each run. The FLOWGO lava flow model is then run down each path, at a series of effusion rates, to determine likely run-out distance for channel-fed flow extending down each path. These results are used to plot effusion rate contours. Finally, effusion rate contours are projected onto a land classification map (produced from an ASTER image of Etna) to assess the type and amount of each land cover class falling within each contour. The resulting maps are designed to provide a quick look-up capability to assess the type of land at risk from lava extending from any location at a range of likely effusion rates. For our first (2,000 m) vent zone case used for Etna, we find a total of area of ~680 km² is at risk from flows fed at 40 m³ s^?1, of which ~6 km² is urban, ~150 km² is agriculture and ~270 km² is grass/woodland. The model can also be run for specific cases, where we find that Etna??s 1669 vent location, if active today, would likely inundate almost 11 km² of urban land, as well as 15.6 km² of agricultural land, including 9.5 km² of olive groves and 5.2 km² of vineyards and fruit/nut orchards.     

Demarcation of fluoride vulnerability zones in granitic aquifer,semi-arid region,Telengana, India

This study has been carried out in the granitic aquifer of Maheshwaram watershed, Telengana, India. In this study, groundwater sample data of 8 years were analyzed for the fluoride content with other chemical quality parameters. The correlation and factor analysis were employed to understand the mechanisms for fluoride (F) enrichment as well as the hydrochemistry of the area. These analyses addressed that the observed groundwater quality was due to water-rock interaction in the aquifer and fluoride is coming from the dissolution of fluorite and other silicate minerals like biotite and hornblende by the groundwater. Land use/land cover (LULC) study from 2002 to 2008 revealed there were significant positive changes in build-up land and negative changes in vegetation cover after 2003. The main agriculture (paddy) has been reduced to 0.97 km² in 2008 from 2.39 km² in 2003. The studied watershed has been characterized on the basis of F concentration into safe, transition, and unsafe groups following the WHO and BIS guidelines. The temporal variation of the three groups showed that 57.6% area of the watershed was in unsafe zone in 2000–2003, but 69.2% of the area became safe in 2006–2009. It has been found that F concentration reduced in 12.59% of the area (became safe from unsafe) accompanied by the reduction of paddy field area. After validation with present (2016) fluoride concentrations, it was found that 16.28% are vulnerable in near future. The results of this study showed that (a) the safe and unsafe zones of fluoride concentrations vary with time with the changes in other parameters associated with it like crop pattern and (b) vulnerable zone can be identified based on the susceptibility to change of safe and unsafe zones. Such studies are useful for planning and management purposes.     

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.     

Relationship in metastasis of coal fire and land use/cover using thermal imagery and support vector machine classifier

The objective of the present study was to delineate temporal and spatial changes in the coal fire and land use/cover within Bastacolla area of Jharia coal field. Studying this variation helped to decipher interconnection among the dynamics of the coal fire and concomitant changes in land use/cover. The detection of coal fires during a span of 14 years along with transitioning land use/cover was cost-effective and enabled planning for management of coal resources and environment. Landsat series of satellite data of 2002, 2009, 2013, and 2016 were processed for generating land surface temperature profiles vis-a-vis classified land use/cover of the study area. A single cut-off temperature was derived for mapping of coal fires using land surface temperature profile from 2002 to 2016. The satellite images were classified using support vector machines, and for depicting land use/cover change, post-classification change detection was done. Classification accuracy obtained was excellent with kappa coefficient ranging from 0.897 for classified image of 2002 to 0.799 for classified image of 2016. Results revealed that coal fires had shifted to the central west part of the area. Furthermore, pockets of coal fire from northern and eastern part of the study area have diminished. OB dumps and coal quarry/coal dump may be attributed towards the spatial change in coal fire while; OB dumps showed connotation with the highest temperature zones. Ground verifications for temperature profiles and coal fires were carried out using thermal camera which enunciated good agreement with results.     

Impact of city expansion on hydrological regime of Rispana Watershed,Dehradun, India

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.

     

Assessment of land use/land cover dynamics vis-à-vis hydrometeorological variability in Wular Lake environs Kashmir Valley,India using multitemporal satellite data

Wular Lake, one of the largest freshwater lakes of Jhelum River Basin, is showing signs of deterioration due to the anthropogenic impact and changes in the land use/land cover (LULC) and hydrometeorological climate of the region. The present study investigated the impacts of temporal changes in LULC and meteorological and hydrological parameters to evaluate the current status of Wular Lake environs using multisensor, multitemporal satellite and observatory data. Satellite images acquired for the years 1992, 2001, 2005, and 2008 were used for determining changes in the LULC in a buffer area of 5 km² around the Wular Lake. LULC mapping and change analysis using the visual interpretation technique indicated significant changes around the Wular Lake during the last two decades. Reduction in lake area from 24 km² in 1992 to 9 km² in 2008 (?62.5 %) affected marshy lands, the habitat of migratory birds, which also exhibited drastic reduction from 85 km² in 1992 to 5 km² in 2008 (?94.117 %). Marked development of settlements (642.85 %) in the peripheral area of the Wular Lake adversely affected its varied aquatic flora and fauna. Change in climatic conditions, to a certain extent, is also responsible for the decrease in water level and water spread of the lake as witnessed by decreased discharge in major tributaries (Erin and Madhumati) draining into the Wular Lake.     

Integration of hydrological factors and demarcation of groundwater prospect zones: insights from remote sensing and GIS techniques

The study demonstrates the potential of geographical information system and statistical-based approaches to identify the hydrological processes and demarcate the groundwater prospect zones of the Gangolli basin, Karnataka State, India. The basin is situated in humid tropical climate and influenced by three major rivers viz. Kollur (6th order stream), Chakra (6th order stream) and Haladi (7th order stream) which cover an area of ~1,512 km² and cumulative length of ~84 km. Various thematic maps—drainage, geomorphology, geology, slope, soil, lineament and lineament density—were prepared using Survey of India topographic maps, Indian remote sensing (IRS-P6) images and other published maps. Hydrogeomorphologic characteristics were correlated with different morphometric parameters to identify the hydrological processes and demarcate the groundwater potential zones of the basin. All the hydrological units and morphometric parameters were assigned suitable weightages according to their relative importance to groundwater potentiality to identify the most deficit/surplus zones of groundwater. Based on hydrological characteristics, integrated thematic maps reveal that ~14 % (~217 km²) of basin area falls under very good, ~32 % (~486 km²) under good, ~23 % (~353 km²) under moderate, and 30 % (~443 km²) under poor zones for groundwater potential. From the sub-basin-wise prioritisation, it has been inferred that SB-III scored highest groundwater potential, followed by SB-X. Result of morphometric analyses with the hydrologic parameters indicates that ~99 % area of SB-III and SB-X are under very good to moderate groundwater potential zone. This study clearly demonstrates that hydrological parameters in relation with morphometric analyses are useful to demarcate the prospect zones of groundwater.     

Spatial change detection of glacial lakes in the Koshi River Basin,the Central Himalayas

Region warming and the resulting ongoing deglaciation have led to the formation of new glacial lakes and expansion of existing glacial lakes. For giving an overview of the distribution and expansion of glacial lakes in the Koshi River Basin (KRB) between the Central China and Nepal Himalayas in the recent 10 years, this paper aimed to analyze and assess recent spatial variability of glacial lake changes in the KRB, Central Himalayas using two inventory data of glacial lake in 2001 and 2010 in Nepal and Landsat TM/ETM+ data for the 1990s, 2000 and 2009 on the Chinese section of the KRB. The datasets show that there are 1,203 glacial lakes with a total area of 118.54 km² in the KRB in 2009, in which 599 lakes are mapped in the Nepalese section of the KRB with a total of 25.92 km², and 604 lakes in the Chinese section of the KRB with a total area of 92.62 km². From 2000 to 2009, the total number of glacial lakes decreased from 1,668 to 1,203 with a reduction of 45.86 % in the KRB, whereas the total lake areas expanded by 10.60 % (i.e. 0.72 km²/a), from 111.35 to 118.54 km² between 2000, 2001 and 2009, 2010. Especially, 17 lakes are identified as potentially dangerous glacial lakes (PDGLs) by International Centre for Integrated Mountain Development (ICIMOD) on the Nepalese section of the KRB in 2009. In the same period, 23 PDGLs are also identified on the Chinese section of the KRB and the total area increased by 77.46 % (i.e. 0.37 km²/a) from 1990 to 2010 and the expansion rate is significantly higher than 39 % (0.19 km²/a) of non-PDGLs. Therefore, there is a need for promoting the awareness of the hazard potential of glacier lakes to support proper planning of mitigation and adaptation strategies in this context.     

Identification of potential groundwater recharge zones in Vaigai upper basin,Tamil Nadu,using GIS-based analytical hierarchical process (AHP) technique

Groundwater recharge is an important process for the management of both surface and subsurface water resources. The present study utilizes the application of analytical hierarchical process (AHP) on geospatial analysis for the exploration of potential zones for artificial groundwater recharge along Vaigai upper basin in the Theni district, Tamil Nadu, India. The morphology of earth surface features such as geology, geomorphology, soil types, land use and land cover, drainage, lineament, and aquifers influence the groundwater recharge in either direct or indirect way. These thematic layers are extracted from Landsat ETM+ image, topographical map, and other collateral data sources. In this study, the multilayers were weighed accordingly to the magnitude of groundwater recharge potential. The AHP technique is a pair-wise matrix analytical method was used to calculate the geometric mean and normalized weight of individual parameters. Further, the normalized weighted layers are mathematically overlaid for preparation of groundwater recharge potential zone map. The results revealed that 21.8 km² of the total area are identified as high potential for groundwater recharge. The gentle slope areas in middle-east and central part have been moderately potential for groundwater recharge. Hilly terrains in south are considered as unsuitable zone for groundwater recharge processes.