Indian Himalayas are home to numerous glacial lakes, which can pose serious threat to downstream communities and lead to catastrophic socioeconomic disasters in case of a glacial lake outburst flood (GLOF). This study first identified 329 glacial lakes of size greater than 0.05 km 2 in the Indian Himalayas, and then a remote sensing-based hazard and risk assessment was performed on these lakes. Different factors such as avalanche, rockfall, upstream GLOF, lake expansion, identification of the presence of ice cores, and assessment of the stability of moraine were considered for the hazard modeling. Further, a stochastic inundation model was applied to quantify the potential number of buildings, bridges, and hydropower systems that could be inundated by GLOF in each lake. Finally, the hazard parameters and downstream impact were collectively considered to determine the risk linked with each lake. A total of 23 lakes were identified as very high risk lakes and 50 as high-risk lakes. The potential flood volumes associated with various triggering mechanisms were also measured and were used to identify the lakes with the most considerable risk, such as Shakho Cho and Khangchung Tso. This study is anticipated to support stakeholders and decision-makers in identifying critical glacial lakes and make well-informed decisions related to future modeling efforts, field studies, and risk mitigation measures.
Field experiments were conducted in three consecutive summer seasons of 2005 to 2007 to study the effect of integrated nutrient management on soil health and productivity of potato (Solanum tuberosum L.) under rainfed condition. The experiment was laid out in a split plot design with eight nutrient management practices (combinations of organic manures viz, farm yard manure (FYM), poultry manure (PM), vermicompost (VC) and inorganic fertilizers in main plots and seed tuber treatment with three biofertilizers (Azotobactor, phosphorus solubilizing bacteria (PSB) and Azotobactor + PSB) in sub plots. The results showed that 50 % of the recommended dose of NPK through inorganic + 50% recommended dose of nitrogen (RDN) through organic manures (FYM, PM or VC) or 100% recommended dose of NPK through inorganic fertilizers alone favorably influenced the tuber yield, nutrient uptake, soil fertility and paid higher returns compared to other treatments. Seed treatment with Azotobactor + PSB proved better in tuber yield, nutrient uptake and recorded higher returns as compared to sole treatment of either Azotobactor or PSB. Three years pooled result revealed that integrated application of 50 % of recommended NPK through inorganic and 50 % RDN through PM recorded significantly highest tuber yield (22.73 t/ha) closely followed by 100 % recommended NPK through inorganic (22.20 t/ha) which were 228 % and 223 % respectively, higher than control. Integrated application of inorganic and organic fertilizers and seed treatment with Azotobactor + PSB biofertilizers improved tuber yield, nutrient uptake, and gave higher return as compared to other treatment combinations. Total organic carbon (TOC), soil microbial biomass carbon (SMBC), available N, P, and K status of the soil after 3 years were maximum when 50 % recommended dose of NPK were applied through inorganic and remaining 50 % RDN through PM.
Monthly mean precipitation estimates of seven products (TerraClimate, TRMM, CHIRPS, PERSIANN‐CDR, GPM‐IMERG, ERA5 and CFSR) available on Google earth engine (GEE) are evaluated against gridded gauge‐based precipitation product available from Indian Meteorological Department (IMD) for their skills and presence of systematic biases (during 2001–2018). All these products represent the climatological features reasonably well. Presence of systematic biases in these products is also observed from their evaluation. Biases across the periphery of the country are relatively on the higher side in comparison to the central regions. The magnitude of spatial variability is represented better for winter precipitation in comparison to summer precipitation. During both winter and summer, ensemble mean of various products outperforms individual products in terms of both RMSE and correlation. Performance of these products is also assessed across various Indian states, elevation bands and climate zones. The ability of these products to represent the seasonality was observed to be highest for the states with mid‐ranged peaks (10–20 mm·day−1) which tend to decrease with both increasing and decreasing peaks. Ability of the precipitation products to resemble the annual cycle does not vary with the amount of precipitation, although individual disparity among the products exists. Additionally, an alternative approach for data evaluation using Multiple Triple Collocation (MTC) was performed for the period 2001–2015 using an additional dataset obtained from soil‐moisture‐based rainfall estimates (SM2RAIN). Results from MTC convey that ERA5 performs relatively poor in comparison to the other products for central India followed by CFSR. In brief, the comprehensive evaluation of precipitation products reported herein will act a valuable reference for the researchers as well as decision makers to select the optimal product for their intended application and will inform the users about the various uncertainties in the foundations and specification of these products.
The present study is the analysis of large scale data (31949 ha area and 79873 farmers) generated through the CFLD on pulses across the major pulses growing states under the ICAR-ATARIs of Kanpur, Jodhpur, Pune, Jabalpur, Kolkata, Guwahati, Hyderabad, Bangalore and Patna. The present analysis represented the pulse crops of kharif (pigeon pea-5556 ha, black gram-6067 ha and green gram-2689 ha), rabi (chickpea-8376 ha, lentil 3747 ha and field pea-1890 ha) and summer (green gram-3624 ha) seasons. The average performance data of CFLD were obtained for the above states during the cropping seasons of 2016-17 and 2017-18. Thus, CFLD data were analyzed from across minimum of 13 states (green gram) and maximum of 19 states (black gram). The major variables analyzed were average yield obtained from the check plots and demonstrations plots. These yields were computed for yield advantages and also compared with the reported district level, state level, National level yields and the potential yields of the respective crops in the given states (data procured from secondary sources for the year 2017-18). Accordingly the yield gaps and yield gap minimized at various levels were analyzed using appropriate methods and their degree of variation was also computed for the seasons and crops.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.