Abstract. Forest fire is one of the key drivers of forest degradation in Nepal. Most of the forest fires are human-induced and occur during the dry season, with ,89% occurring in March, April and May. The inaccessible mountainous terrain and narrow time window of occurrence complicate suppression efforts. In this paper, forest fire patterns are analysed based on historical fire incidence data to explore the spatial and temporal patterns of forest fires in Nepal. Three main factors are involved in the ignition and spread of forest fires, namely fuel availability, temperature and ignition potential. Using these factors a spatially distributed fire risk index was calculated for Nepal based on a linear model using weights and ratings. The input parameters for the risk assessment model were generated using remote sensing based land cover, temperature and active fire data, and topographic data. A relative risk ranking was also calculated for districts and village development committees (VDCs). In total, 18 out of 75 districts were found with high risk of forest fires. The district and VDC level fire risk ranking could be utilised by the Department of Forest for prioritisation, preparedness and resource allocation for fire control and mitigation.Additional keywords: fire behaviour, fire danger, fire management, fire risk.

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h i g h l i g h t s• Temporal change in land cover and forest fragmentation were analyzed.• The results showed 9% decrease in forest cover and 12% increase in cropland.• A further 4% decline in forest cover and 5% increase in cropland were predicted. • 10% decrease in large core forest and 10.6% decline in core forest was predicted.• Expansions of cropland coupled with high dependency on forests are the drivers. a b s t r a c tLand cover change is one of the most important drivers of forest ecosystem change. The Hindu Kush Himalayan region (HKH) has experienced severe forest degradation but data and documentation are limited. We undertook this study in the Nepalese part of the Kailash Sacred Landscape (KSL), an important transboundary region known for its biodiversity and the scared values. Forest is an important ecosystem within the landscape and provides various goods and services including habitat for many keystone species. However, precise information on forest change and overall land cover change in the area is limited. We analyzed land cover change and forest fragmentation between 1990 and 2009, and the predicted change for 2030. There was a 9% decrease in forest cover and 12% increase in cropland between 1990 and 2009. A further 4% decline in forest cover and 5% increase in cropland was predicted by 2030, together with a slight increase in grassland and barren area. Fragmentation analysis showed a 10% decrease in large core forest between 1990 and 2009, accompanied by an increase in patch forest. A further 10.6% decline in core forest was predicted by 2030, accompanied by an increase in patch, perforated, small-sized core, and mediumsized core areas. The study suggests that expansions of cropland coupled with high dependency on forests are the major drivers of the observed forest change. Recommendations are made based on the results of the study that will help to maintain and restore forest, and support biodiversity conservation and livelihoods.

High levels of water-induced erosion in the transboundary Himalayan river basins are contributing to substantial changes in basin hydrology and inundation. Basin-wide information on erosion dynamics is needed for conservation planning, but field-based studies are limited. This study used remote sensing (RS) data and a geographic information system (GIS) to estimate the spatial distribution of soil erosion across the entire Koshi basin, to identify changes between 1990 and 2010, and to develop a conservation priority map. The revised universal soil loss equation (RUSLE) was used in an ArcGIS environment with rainfall erosivity, soil erodibility, slope length and steepness, cover-management, and support practice factors as primary parameters. The estimated annual erosion from the basin was around 40 million tonnes (40 million tonnes in 1990 and 42 million tonnes in 2010). The results were within the range of reported levels derived from isolated plot measurements and model estimates. Erosion risk was divided into eight classes from very low to extremely high and mapped to show the spatial pattern of soil erosion risk in the basin in 1990 and 2010. The erosion risk class remained unchanged between 1990 and 2010 in close to 87% of the study area, but increased over 9.0% of the area and decreased over 3.8%, indicating an overall worsening of the situation. Areas with a high and increasing risk of erosion were identified as priority areas for conservation. The study provides the first assessment of erosion dynamics at the basin level and provides a basis for identifying conservation priorities across the Koshi basin. The model has a good potential for application in similar river basins in the Himalayan region.

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Snow governs interaction between atmospheric and land surface processes in high mountains, and is also source of fresh water. It is thus important to both climate scientists and local communities. However, our understanding of snow cover dynamics in terms of space and time is limited across the Hindu Kush Himalaya (HKH) region, which is known to be a climatically sensitive region. We used MODIS snow cover area (SCA) data (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012), APHRODITE temperature data (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007), and monthly long term in-situ river discharge data of the Gandaki (1968Gandaki ( -2010, Koshi (1977Koshi ( -2010 and Manas (1987Manas ( -2004 basins to analyse variations among four basins. We gained insights into short term SCA and temperature, long term discharge trends, and regional variability thereby. Strong correlations were observed among SCA, temperature and discharge thereby highlighting the strong nexus between them. Temporal and spatial snow cover variability across the basins is strongly coupled with the variability of two weather systems: Western Disturbances (WD) and Indian Monsoon System (IMS), and strongly influenced by topography. Manifestation of these variability in terms if downstream discharge can have repercussion to water based sectors: hydropower and agriculture, as low flow seasons is seen affected. This study adds to our knowledge of snow fall and melt dynamics in the HKH region, and intra-annual snow melt contributions to downstream discharges. The study is limited by short span of data and it is desirable to perform a similar study using data representing a much longer time span.

Extensive forest changes have occurred in monsoon Asia, substantially affecting climate, carbon cycle and biodiversity. Accurate forest cover maps at fine spatial resolutions are required to qualify and quantify these effects. In this study, an algorithm was developed to map forests in 2010, with the use of structure and biomass information from the Advanced Land Observation System (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) mosaic dataset and the phenological information from MODerate Resolution Imaging Spectroradiometer (MOD13Q1 and MOD09A1) products. Our forest map (PALSARMOD50 m F/NF) was assessed through randomly selected ground truth samples from high spatial resolution images and had an overall accuracy of 95%. Total area of forests in monsoon Asia in 2010 was estimated to be ~6.3 × 106 km2. The distribution of evergreen and deciduous forests agreed reasonably well with the median Normalized Difference Vegetation Index (NDVI) in winter. PALSARMOD50 m F/NF map showed good spatial and areal agreements with selected forest maps generated by the Japan Aerospace Exploration Agency (JAXA F/NF), European Space Agency (ESA F/NF), Boston University (MCD12Q1 F/NF), Food and Agricultural Organization (FAO FRA), and University of Maryland (Landsat forests), but relatively large differences and uncertainties in tropical forests and evergreen and deciduous forests.

Landslide is one of the most widely distributed mass movements in mountainous areas. With its wide spreading, abrupt, and seasonal characteristics, landslide always causes huge risks towards transportation, human settlements, industrial and mining plants, water resources facilities, and hydropower stations. Abe Barek landslide, which happened in the morning of May 2, 2014, in Ago District, Badakhshan Province, Afghanistan, buried 86 houses and took the lives of almost 2700 people. Many factors triggered the occurrence of this disaster. Firstly, the landslideimpacted area has a complex geologic structure that bears concentrated faults with mountain slopes covered by thick loess. Secondly, at the time of landslide, a continuous rainfall had deepened the level of moisture in the loess layer, which made the loess mass heavier and changed the soil body's mechanical properties. Thirdly, a similar landslide once happened on the same slope, which destroyed the land cover and transformed the topology of the slope. In addition, farming and irrigating activities may have also affected the stability of loess mass in this area. Upon an initial examination of landslide distribution in Badakhshan Province by using high-resolution remote sensing images from Google Earth, a total number of 609 landslide sites were identified in this area, and a landslide susceptibility assessment was completed by utilizing weight-of-evidence method. Several suggestions on landslide risk reduction in this remote mountainous area are proposed at the end of this paper.