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Drought is one of the most frequent meteorological disasters, and has exerted significant impacts on the livelihoods and economy of the Koshi River Basin (KRB). In this study, we assessed drought patterns using the Crop Water Shortage Index (CWSI) based on the MOD16 product for the period between 2000 and 2014. The results revealed that the CWSI based on the MOD16 product can be act as an indicator to monitor the characteristics of the drought. Significant spatial heterogeneity of drought was observed in the basin, with higher CWSI values downstream and upstream than in the midstream. The midstream of the KRB was dominated by light drought, moderate drought occurred in the upstream, and the downstream was characterized by severe drought. The monthly CWSI during one year in KRB showed the higher CWSI between March to May (pre-monsoon) and October to December (post-monsoon) rather than June to September (monsoon), and the highest was observed in the month of April, suggesting that precipitation plays the most important role in the mitigation of CWSI. Additionally, the downstream and midstream showed a higher variation of drought compared to the upstream in the basin. This research indicates that the downstream suffered severe drought due to seasonal water shortages, especially during the pre-monsoon, and water-related infrastructure should be implemented to mitigate losses caused by drought.

Purpose Soil erosion is a major threat to agricultural sustainability in the hills of Nepal. However, little is known about the soil erosion rates at a small catchment scale in this region. Materials and methods In this study, the soil redistribution rates in a typical small hilly catchment in the Ramechhap District of Nepal were evaluated using the 137 Cs and 210 Pb ex tracer techniques. Nine representative slopes under three land uses and a reference site from the gentle sloping forest land within the catchment were selected as sample plots. A downhill transect was built in each sample plot, and soil samples were collected at 5-m intervals along the transects. Results and discussion The results showed that the spatial variations in radionuclide inventory and soil erosion rates measured by 137 Cs measurements were highly consistent with equivalent estimates from 210 Pb ex measurements, suggesting the potential for using 137 Cs and 210 Pb ex measurements to estimate soil redistribution rates. All 137 Cs and 210 Pb ex inventories on the slopes were less than the reference values, indicating that net soil loss has occurred at all of the sampling points. The net erosion rates from sloping farmland (37.08 t ha −1 year −1) and shrub land (32.52 t ha −1 year −1) were significantly higher than those from forest land (14.91 t ha −1 year −1). Furthermore, the soil erosion rates obtained from 210 Pb ex measurements were higher than those obtained from 137 Cs measurements, which implies that soil erosion in the catchment was accelerated during the last two decades. The net soil loss from the study catchment was estimated to be 31.29 t ha −1 year −1 , which is mainly contributed by shrub land (55.08%) and sloping farmland (37.68%). Conclusions These results indicate that shrub land and sloping farmland are vulnerable to erosion, which should be specifically considered in the sustainable management of small agricultural catchments in the mid-hills of Nepal, especially in dry valley regions.

Soil erosion in the agricultural area of a hill slope is a fundamental issue for crop productivity and environmental sustainability. Building terrace is a very popular way to control soil erosion, and accurate assessment of the soil erosion rate is important for sustainable agriculture and environmental management. Currently, many soil erosion estimations are mainly based on the freely available medium or coarse resolution digital elevation model (DEM) data that neglect micro topographic modification of the agriculture terraces. The development of unmanned aerial vehicle (UAV) technology enables the development of high-resolution (centimeter level) DEM to present accurate topographic features. To demonstrate the sensitivity of soil erosion estimates to DEM resolution at this high-resolution level, this study tries to evaluate soil erosion estimation in the Middle Hill agriculture terraces in Nepal based on UAV derived high-resolution (5 × 5 cm) DEM data and make a comparative study for the estimates by using the DEM data aggregated into different spatial resolutions (5 × 5 cm to 10 × 10 m). Firstly, slope gradient, slope length, and topographic factors were calculated at different resolutions. Then, the revised universal soil loss estimation (RUSLE) model was applied to estimate soil erosion rates with the derived LS factor at different resolutions. The results indicated that there was higher change rate in slope gradient, slope length, LS factor, and soil erosion rate when using DEM data with resolution from 5 × 5 cm to 2 × 2 m than using coarser DEM data. A power trend line was effectively used to present the relationship between soil erosion rate and DEM resolution. The findings indicated that soil erosion estimates are highly sensitive to DEM resolution (from 5 × 5 cm to 2 × 2 m), and the changes become relatively stable from 2 × 2 m. The use of DEM data with pixel size larger than 2 × 2 m cannot detect the micro topography. With the insights about the influencing mechanism of DEM resolution on soil erosion estimates, this study provides important suggestions for appropriate DEM data selection that should be investigated first for accurate soil erosion estimation.

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