Climate change amplifies plant invasion hotspots in Nepal

Aim Climate change has increased the risk of biological invasions, particularly by increasing the climatically suitable regions for invasive alien species. The distribution of many native and invasive species has been predicted to change under future climate. We performed species distribution modelling of invasive alien plants (IAPs) to identify hotspots under current and future climate scenarios in Nepal, a country ranked among the most vulnerable countries to biological invasions and climate change in the world. Location Nepal. Methods We predicted climatically suitable niches of 24 out of the total 26 reported IAPs in Nepal under current and future climate (2050 for RCP 6.0) using an ensemble of species distribution models. We also conducted hotspot analysis to highlight the geographic hotspots for IAPs in different climatic zones, land cover, ecoregions, physiography and federal states. Results Under future climate, climatically suitable regions for 75% of IAPs will expand in contrast to a contraction of the climatically suitable regions for the remaining 25% of the IAPs. A high proportion of the modelled suitable niches of IAPs occurred on agricultural lands followed by forests. In aggregation, both extent and intensity (invasion hotspots) of the climatically suitable regions for IAPs will increase in Nepal under future climate scenarios. The invasion hotspots will expand towards the high‐elevation mountainous regions. In these regions, land use is rapidly transforming due to the development of infrastructure and expansion of tourism and trade. Main conclusions Negative impacts on livelihood, biodiversity and ecosystem services, as well as economic loss caused by IAPs in the future, may be amplified if preventive and control measures are not immediately initiated. Therefore, the management of IAPs in Nepal should account for the vulnerability of climate change‐induced biological invasions into new areas, primarily in the mountains

Flood Mapping of Recent Major Hurricane Events with Synthetic Aperture Radar, Commercial Imaging, and Aerial Observations

Floodwater mapping is an important remote sensing process that is used for disaster response, recovery, and damage assessment practices. Developing a system to read in Synthetic Aperture Radar (SAR) data and perform land cover classification will allow for the production of near real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of the situation. SAR is a unique remote sensing tool. Data in this project was obtained by NASA Jet Propulsion Laboratorys Uninhabited Aerial Vehicle SAR (UAVSAR), an L-band radar mounted to a Gulfstream III jet. Data collected by UAVSAR is similar to what will be available from the NASA-Indian Space Research Organization (NISAR) mission starting in early 2022. Using Python and ArcGIS applications, a model was developed using training samples taken from NOAA post-event aerial photography and UAVSAR data gathered in the aftermath of Hurricane Florence in September 2018

Tied-Back Top-Down Wall to Support I-295 Ramp

Woodrow Wilson Replacement Bridge Project included widening the Washington Beltway (I-95/I-495) Outer Loop from three lanes to six-lanes. This required supporting two existing ramps that connect I-295 and MD 210 as well as the existing Mechanically Stabilized Earth (MSE) wall that supports the ramps. The MSE is about 17-ft tall, about 570-ft long, and at the top of a slope. A tied-back soldier pile and lagging wall with cast-in-place facing was selected to support the MSE and the ramps. The new wall will be about 1,376-ft long and will be as high as 37-ft. The closest approach of the wall to the existing MSE is about 3-ft. Laboratory testing was supplemented with Dilatometer Test (DMT) and Cone Penetration Test (CPT) soundings. PYWall and PLAXIS were used to estimate wall deflections and bending moments in the soldier piles. This paper reviews the analysis techniques, describes the design and the construction methods, and the instrumentation used to monitor the wall and MSE movements. The results of the computer simulations were compared to the inclinometer results. As work progressed simulations were updated by modifying the soil parameters to obtain calculated results that are more nearly consistent with the instrumentation readings

Implementation of a process-based catchment model in a poorly gauged, highly glacierized Himalayan headwater

The paper presents a catchment modeling approach for remote glacierized Himalayan catchments. The distributed catchment model TAC^D, which is widely based on the HBV model, was further developed for the application in highly glacierized catchments on a daily timestep and applied to the Nepalese Himalayan headwater Langtang Khola (360 km²). Low laying reference stations are taken for temperature extrapolation applying a second order polynomial function. Probability based statistical methods enable bridging data gaps in daily precipitation time series and the redistribution of cumulated precipitation sums over the previous days. Snow and ice melt was calculated in a distributed way based on the temperature-index method employing calculated daily potential sunshine durations. Different melting conditions of snow and ice and melting of ice under debris layers were considered. The spatial delineation of hydrological response units was achieved by taking topographic and physiographic information from maps and satellite images into account, and enabled to incorporate process knowledge into the model. Simulation results demonstrated that the model is able to simulate daily discharge for a period of 10 years and point glacier mass balances observed in the research area with an adequate reliability. The simple but robust data pre-processing and modeling approach enables the determination of the components of the water balance of a remote, data scarce catchment with a minimum of input data

Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites

In this study, the snow physics of a distributed biosphere hydrological model, referred to as the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) is significantly improved by incorporating the three-layer physically based energy balance snowmelt model of Simplified Simple Biosphere 3 (SSiB3) and the Biosphere-Atmosphere Transfer Scheme (BATS) albedo scheme. WEB-DHM with improved snow physics is hereafter termed WEB-DHM-S. Since the in-situ observations of spatially-distributed snow variables with high resolution are currently not available over large regions, the new distributed system (WEB-DHM-S) is at first rigorously tested with comprehensive point measurements. The stations used for evaluation comprise the four open sites of the Snow Model Intercomparison Project (SnowMIP) phase 1 with different climate characteristics (Col de Porte in France, Weissfluhjoch in Switzerland, Goose Bay in Canada and Sleepers River in USA) and one open/forest site of the SnowMIP phase 2 (Hitsujigaoka in Japan). The comparisons of the snow depth, snow water equivalent, surface temperature, snow albedo and snowmelt runoff at the SnowMIP1 sites reveal that WEB-DHM-S, in general, is capable of simulating the internal snow process better than the original WEB-DHM. Sensitivity tests (through incremental addition of model processes) are performed to illustrate the necessity of improvements over WEB-DHM and indicate that both the 3-layer snow module and the new albedo scheme are essential. The canopy effects on snow processes are studied at the Hitsujigaoka site of the SnowMIP2 showing that the snow holding capacity of the canopy plays a vital role in simulating the snow depth on ground. Through these point evaluations and sensitivity studies, WEB-DHM-S has demonstrated the potential to address basin-scale snow processes (e.g., the snowmelt runoff), since it inherits the distributed hydrological framework from the WEB-DHM (e.g., the slope-driven runoff generation with a grid-hillslope scheme, and the flow routing in the river network)

Effects of climatic factors on diarrheal diseases among children below 5 years of age at national and subnational levels in Nepal: an ecological study

INTRODUCTION: The incidence of diarrhea, a leading cause of morbidity and mortality in low-income countries such as Nepal, is temperature-sensitive, suggesting it could be associated with climate change. With climate change fueled increases in the mean and variability of temperature and precipitation, the incidence of water and food-borne diseases are increasing, particularly in sub-Saharan Africa and South Asia. This national-level ecological study was undertaken to provide evidence linking weather and climate with diarrhea incidence in Nepal. METHOD: We analyzed monthly diarrheal disease count and meteorological data from all districts, spanning 15 eco-development regions of Nepal. Meteorological data and monthly data on diarrheal disease were sourced, respectively, from the Department of Hydrology and Meteorology and Health Management Information System (HMIS) of the Government of Nepal for the period from 2002 to 2014. Time-series log-linear regression models assessed the relationship between maximum temperature, minimum temperature, rainfall, relative humidity, and diarrhea burden. Predictors with p-values < 0.25 were retained in the fitted models. RESULTS: Overall, diarrheal disease incidence in Nepal significantly increased with 1 degrees C increase in mean temperature (4.4%; 95% CI: 3.95, 4.85) and 1 cm increase in rainfall (0.28%; 95% CI: 0.15, 0.41). Seasonal variation of diarrheal incidence was prominent at the national level (11.63% rise in diarrheal cases in summer (95% CI: 4.17, 19.61) and 14.5% decrease in spring (95% CI: -18.81, -10.02) compared to winter season). Moreover, the effects of temperature and rainfall were highest in the mountain region compared to other ecological regions of Nepal. CONCLUSION: Our study provides empirical evidence linking weather factors and diarrheal disease burden in Nepal. This evidence suggests that additional climate change could increase diarrheal disease incidence across the nation. Mountainous regions are more sensitive to climate variability and consequently the burden of diarrheal diseases. These findings can be utilized to allocate necessary resources and envision a weather-based early warning system for the prevention and control of diarrheal diseases in Nepal

Fruit Characterization of Different Avocado (Persea Americana Mill.) Genotypes in Eastern Mid-hills of Nepal

The total of thirteen different avocado (Persea americana Mill.) genotypes were collected for evaluating the fruit characteristics in the laboratory of Agricultural Research Station, Pakhribas during November 2017. The fully matured fruits from the farmer's field at Patle, Dhankuta were collected. The criteria for selecting the genotypes were fruit weight, fruit length, fruit diameter, seed weight, pulp weight, pulp to fruit ratio and the seed weight percentage. The result suggests the potentiality of the genotypes PAKAV002 and PAKAV010 in most of the evaluated characters as compared to the tested genotypes. The genotypes PAKAV008 and PAKAV007 were disliked as they have 32.59% and 28.39% of seed weight to the total fruit weight. The genotypes PAKAV002 and PAKAV010 had the average fruit weight ranging (307.1 g and 346.8 g), maximum of pulp to fruit ratio 62.34% and 56.97%. Similarly, genotypes PAKAV010 (11.425%), PAKAV013 (11.96%) and PAKAV002 (14.47%) had low seed weight to the total fruit weight which is regarded important factor for avocado selection and evaluation. This result shows that the genotypes PAKAV002 and PAKAV010 should be further evaluated for fruit characteristics and the quality

Retinal nerve fiber layer thickness in glaucomatous Nepalese eyes and its relation with visual field sensitivity.

BACKGROUND: To evaluate peripapillary retinal nerve fiber layer (RNFL) thickness in glaucomatous Nepalese eyes using spectral domain optical coherence tomography (SD-OCT) and study its relationship with visual field sensitivity. METHODS: A total of 120 eyes comprising primary open angle glaucoma (POAG), glaucoma suspects (GS), normal tension glaucoma (NTG) and healthy subjects (n=30 cases in each group) underwent a complete ophthalmic examination, including optic nerve head (ONH) evaluation and standard automated perimetry (SAP). RNFL thickness measurements around the optic disk were taken with circular spectral domain optical coherence tomography (SD-OCT) scans. Analysis of variance (ANOVA) was used for comparison of RNFL parameters among various study groups. The relationship of RNFL parameters with visual field (VF) global indices was evaluated with regression analysis. RESULTS: The mean pRNFL thickness was significantly less in the POAG (64.30±14.45μm, p<0.01), NTG (85.43±9.79μm, p<0.001) and GS (102.0±9.37μm, p<0.001) groups than in the healthy group (109.8±8.32μm). The RNFL was significantly thinner across all quadrants in all study group pairs (p<0.05) except for normal vs. GS (only superior and inferior quadrant, significant). Linear regression plots with RNFL thickness as a predictor of MD and LV demonstrated a strong and statistically significant degree of determination in the POAG group (R(2)=0.203 and 0.175, p=0.013 and 0.021). CONCLUSION: The RNFL thickness measurements with SD-OCT are lower in glaucomatous eyes as compared to age-matched GS and normal eyes in the Nepalese population. A high resolution SD-OCT could aid significantly in the early diagnosis of glaucoma in Nepal