Impact of climatic parameters on statistical stream flow sensitivity analysis for hydro power

Large area of Himalayas covered with seasonal snow during winter are rapidly changing during summer, significantly affects the stream flow of many rivers originating from Himalayas. This necessitates the efficient time series monitoring of seasonal snow cover in the rugged mountainous region throughout the winter and summer periods for weekly/monthly as well as seasonal forecast of stream run-off for water management and other developmental activities.     

A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation

ABSTRACT

The temporal nature of humans interaction with Points of Interest (POIs) in cities can differ depending on place type and regional location. Times when many people are likely to visit restaurants (place type) in Italy, may differ from times when many people are likely to visit restaurants in Lebanon (i.e. regional differences). Geosocial data are a powerful resource to model these temporal differences in cities, as traditional methods used to study cross-cultural differences do not scale to a global level. As cities continue to grow in population and economic development, research identifying the social and geophysical (e.g., climate) factors that influence city function remains important and incomplete. In this work, we take a quantitative approach, applying dynamic time warping and hierarchical clustering on temporal signatures to model geosocial temporal patterns for Retail and Restaurant Facebook POIs hours of operation for more than 100 cities in 90 countries around the world. Results show cities’ temporal patterns cluster to reflect the cultural region they represent. Furthermore, temporal patterns are influenced by a mix of social and geophysical factors. Trends in the data suggest social factors influence unique drops in temporal signatures, and geophysical factors influence when daily temporal patterns start and finish.     

Analysis of groundwater levels for detection of trend in Sagar district,Madhya Pradesh

Groundwater being an important component of the hydrological cycle as it sustains the streamflow during precipitation free periods and is a major source of water supply. The dependence on the groundwater has increased drastically over the years leading to over exploitation of the aquifers. Therefore, it is imperative to assess the extent of exploitation and analyse the groundwater level scenarios in the area of interest. The existence of a trend in a hydrological time series can be detected by statistical tests. The present study investigates the application of various methods for identification of trends in groundwater levels in few blocks of Sagar district, which faces severe water scarcity owing to the declining groundwater levels. The non-parametric Kendal rank correlation test as well as the parametric linear regression test has been used for trend detection based on the analysis of the seasonal groundwater levels. Kendal’s rank correlation test, has been applied to identify the trend persisting in the data and the linear regression test is used to identify the significance of the slope. The analysis indicates that the time series of groundwater levels are cyclical with characteristics of seasonal variation in all the blocks coupled with a declining trend at Sagar, Khurai and Bina.     

A review of recent urban geographic studies in India

This paper reviews the changing nature of the growing specialized trends of urban geography in India since independence, with a particular emphasis to the 1980s and early 1990s. Urban geography has emerged as a major academic sub-field in India with active researchers at its frontier. The 1980s and early 1990s are characterized by a diversified and growing trend of specialization both in inter-urban and intra-urban research in urban geography. This diversification is most clear and pronounced in intra-urban studies where the emphasis is directed towards socio-cultural aspects of the city. Conversely, inter-urban research is concerned both with analysis of patterns and trends of macro level urbanization and the processes. Although model building is in its infancy, a few static, deterministic, probabilistic and dynamic models have been constructed. There has been severe limitations in the use of computers in India, particularly the large-frame ones, so the researcher there cannot use the large scale data on national level.     

Economic Contribution of Forestry Sector to National Economy in Nepal

Forests are major sources of energy, timber and non-timber forest products, medicinal and aromatic plants, hydrological functions, biodiversity conservation, and also fundamental sources of revenue collection to the nation. Studies indicate that forests could significantly enhance economic growth and create employment opportunities for local communities under intensive management. This paper aims to predict the contribution of the forest sector to the national economy. The economic facets of forestry considered in this paper are revenue generated from timber, non-timber forest products (NTFPs) and medicinal and aromatic plants (MAPs), and protected areas. The ARIMA model was used to forecast the economic contribution of the forestry sector. The study found that the total revenue generated from the selling of timber and fuelwood (USD 50.19 million) was higher than the total revenue collected from protected areas (USD 37.58 million) and NTFPs/MAPs (USD 6.9 million) in the past 15 years. The model projected that the mean revenue for the timber and fuelwood sale will USD 3.5 million for the next ten years. Similarly, the mean revenue will be generated about USD 0.5 million and USD 6.2 million from NTFPs/MAPs and protected areas, respectively, for the next ten years. The study limits to take account the in-kind use of forest products such as timber, fodder, fuelwood, etc., as used by community people within a forest users’ groups. Thus, practicing sustainable forest management, enabling policy documents, establishing forest-based industries, establishing forestry nurseries, conducting agroforestry practices, and tenure security could enhance the forestry sector's economic aspects.     

Morphometric analysis of Morar River Basin, Madhya Pradesh, India, using remote sensing and GIS techniques

Hydrogeological mapping and drainage analysis can form an important tool for groundwater development. Assessment of drainage and their relative parameters have been quantitatively carried out for the Morar River Basin, which has made positive scientific contribution for the local people of area for the sustainable water resource development and management. Geographical Information System has been used for the calculation and delineation of the morphometric characteristics of the basin. The dendritic type drainage network of the basin exhibits the homogeneity in texture and lack of structural control. The stream order ranges from first to sixth order. The drainage density in the area has been found to be low which indicates that the area possesses highly permeable soils and low relief. The bifurcation ratio varies from 2.00 to 5.50 and the elongation ratio (0.327) reveals that the basin belongs to the elongated shaped basin category. The results of this analysis would be useful in determining the effect of catchment characteristics such as size, shape, slope of the catchment and distribution of stream net work within the catchment.     

Snow Cover Area Mapping Using Synthetic Aperture Radar in Manali Watershed of Beas River in the Northwest Himalayas

The current study has used Synthetic Aperture Radar (SAR) satellite data to estimate the Snow Cover Area (SCA) in Manali watershed of Beas River in Northwest Himalayas of Himachal Pradesh, India. SAR data used in this study is of Radarsat-2 (RS2) and Environmental Satellite (ENVISAT), Advanced Synthetic Aperture Radar (ASAR). The SAR preprocessing was done with SAR image processing tools for converting raw SAR images into calibrated geo-coded backscatter images. Maps for forest, built area, layover and shadow were created and used for masking snow cover in these areas. The backscattering ratio of wet snow to reference image threshold method with value range from ?2 to ?3 db was used to estimate wet SCA for study area. In this technique, if the threshold is too high (≥-2 db) wet SCA is overestimated and if it is too low (≤-3db), this method underestimates the SCA. The wet SCA is under/over estimated (+6 % to?8 % on average) in late spring season due to the inherent terrain and SAR imaging effects of layover/foreshortening and shadow and also due to the masking of forest areas. Overall, the SCA derived from SAR data matches well when compared with total SCA derived from cloud free optical remote sensing data products, especially during wet season.     

A Review of “Politics and Practice in Economic Geography”

Abstract

This study examines the spatial distribution and enforcement of air polluting facilities in the state of New Jersey, as listed in the U.S. Environmental Protection Agency's Aerometric Information Retrieval System. Results show that air-polluting facilities tend to concentrate near minority neighborhoods, although this relationship is partially explained by factors of population density, manufacturing employment, and land use. Other results suggest that facilities in areas with a relatively high percentage of minority population tend to have a weaker record of environmental enforcement as compared to other facilities. Of the socioeconomic variables considered, employment in manufacturing appears to be the most strongly related to environmental enforcement.