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The Koshi River Basin is in the middle of the Himalayas, a tributary of the Ganges River and a very important cross-border watershed. Across the basin there are large changes in altitude, habitat complexity, ecosystem integrity, land cover diversity and regional difference and this area is sensitive to global climate change. Based on Landsat TM images, vegetation mapping, field investigations and 3S technology, we compiled high-precision land cover data for the Koshi River Basin and analyzed current land cover characteristics. We found that from source to downstream, land cover in the Koshi River Basin in 2010 was composed of water body (glacier), bare land, sparse vegetation, grassland, wetland, shrubland, forest, cropland, water body (river or lake) and built-up areas. Among them, grassland, forest, bare land and cropland are the main types, accounting for 25.83%, 21.19%, 19.31% and 15.09% of the basin's area respectively. The composition and structure of the Koshi River Basin land cover types are different between southern and northern slopes. The north slope is dominated by grassland, bare land and glacier; forest, bare land and glacier are mainly found on northern slopes. Northern slopes contain nearly seven times more grassland than southern slopes; while 97.13% of forest is located on southern slopes. Grassland area on northern slope is 6.67 times than on southern slope. The vertical distribution of major land cover types has obvious zonal characteristics. Land cover types from low to high altitudes are cropland, forest, Shrubland and mixed cropland, grassland, sparse vegetation, bare land and water bodies. These results provide a scientific basis for the study of land use and cover change in a critical region and will inform ecosystem protection, sustainability and management in this and other alpine transboundary basins. [ABSTRACT FROM AUTHOR]

In recent decades, human activities have significantly transformed land use and land cover (LULC) and the environment of the Central Himalayas region. LULC is a major component of environmental and climatic research. The aim of this study was to determine the changes in cropland status and its drivers in the Koshi River Basin (KRB) of the Central Himalayas region of Nepal between 1978 and 2010. The cropland status in 1978 was obtained from the Land Resources Mapping Project (LRMP) datasets. The cropland status in 1992 and 2010 was determined on the basis of satellite imagery, with an object-oriented classification method, together with field investigations. Advanced geographical tools were used for data processing and binary logistic regression models were used for the statistical analysis of potential driving factors of cropland change. A noticeable overall change in cropland area was found, with rapid increases from 1978 onward at differing rates and to different extents. The cropland area covered 7165 km2 in 1978. It peaked at 7867.49 km2 in 1992, and had reduced slightly (by 90 km2 ) to 7776.66 km2 by 2010. The change in cropland area was mainly related to four potential driving factors: topography (elevation, slope, and soil types), socioeconomics (population and foreign labor migration), climate (annual mean temperature and precipitation), and neighborhood factors (roads, rivers, and settlements). However, the effects of the different variables have occurred over various stages and at different rates. An understanding of long-term changes in cropland status in the KRB would be useful, and this could be extended to spatial reconstructions with the help of historical data, including cropland and climatic archives. [ABSTRACT FROM AUTHOR]

Globally, there is a noticeable increasing trend in farmland abandonment, which directly affects farmers' livelihood and food security. The abandonment status, its determinants and impact vary by spatial and socioeconomic context. In order to study this important issue, we selected three different villages representing three ecological regions (Mountain, Hill, and Tarai) in the Koshi River Basin (KRB), and applied two methods: the Unmanned Aerial Vehicle (UAV) and a social survey. The UAV captured 3711 images and we carried out 162 households' survey with structured questionnaires. Pix4Dmapper and ArcGIS tools were used for combining and processing the images. On-screen digitalization and binary logistic regression (BLR) were applied to examine the status and determinants of farmland abandonment. The results show a higher proportion of farmland abandonment in the villages located in the Hill and Mountain regions compared to those in the Tarai region. Almost 10.3% area of total land and 22.3% area of total farmland was abandoned in the Hill village. The Tarai village had the least farm abandonment (3.7%). Farmers perceived that climate change (less precipitation, increasing temperatures, and drought), shifting occupations, crops damaged by wildlife, migration, lack of irrigation, and a labor shortage are the leading determinants of farmland abandonment. These factors varied slightly across the different ecological regions. The BLR model was a good fit with Nagelkerke's R 2 = 0.776, with a correct model prediction (87.7%) and p = 0.032. The results from the regression model suggest that an increase in temperature (p = 0.000), decrease in rainfall (p = 0.001), lack of machinery used for farm-work (p = 0.000), lack of irrigation (p = 0.000), and reduction of labor-force (p = 0.000) are the main contributing determinants of farmland abandonment. This synergy of high-resolution remote sensing and farmers' perception-based findings facilitates the improvement of land-use governmental policies to improve farmers' quality of life and build sustainable farmland management. Image 1 • Status and determinants of farmland abandonment vary by regions in the Koshi basin. • Biophysical attributes and farm characteristics were the important determinants. • Farmers' livelihood in Mountain and Hill regions is highly affected by this issue. • Improving policies is key to reduce farm abandonment and ensure food security. [ABSTRACT FROM AUTHOR]

Vegetation forms a main component of the terrestrial biosphere owing to its crucial role in land cover and climate change, which has been of wide concern for experts and scholars. In this study, we used MODIS (moderate-resolution imaging spectroradiometer) NDVI (Normalized Difference Vegetation Index) data, land cover data, meteorological data, and DEM (Digital Elevation Model) data to do vegetation change and its relationship with climate change. First, we investigated the spatio-temporal patterns and variations of vegetation activity in the Koshi River Basin (KRB) in the central Himalayas from 2000 to 2018. Then, we combined NDVI change with climate factors using the linear method to examine their relationship, after that we used the literature review method to explore the influence of human activities to vegetation change. At the regional scale, the NDVIGS (Growth season NDVI) significantly increased in the KRB in 2000–2018, with significant greening over croplands in KRB in India. Further, the croplands and forest in the KRB in Nepal were mainly influenced by human interference. For example, improvements in agricultural fertilization and irrigation facilities as well as the success of the community forestry program in the KRB in Nepal increased the NDVIGS of the local forest. Climate also had a certain impact on the increase in NDVIGS. A significant negative correlation was observed between NDVIGS trend and the annual minimum temperature trend (TMN) in the KRB in India, but an insignificant positive correlation was noted between it and the total annual precipitation trend (PRE). NDVIGS significantly decreased over a small area, mainly around Kathmandu, due to urbanization. Increases in NDVIGS in the KRB have thus been mainly affected by human activities, and climate change has helped increase it to a certain extent. [ABSTRACT FROM AUTHOR]