Near surface air temperature (Ta) is one of the key input parameters in land surface models and hydrological models as it affects most biogeophysical and biogeochemical processes of the earth surface system. For distributed hydrological modeling over glacierized basins, obtaining high resolution Ta forcing is one of the major challenges. In this study, we proposed a new high resolution daily Ta estimation scheme under both clear and cloudy sky conditions through integrating the moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) and China Meteorological Administration (CMA) land data assimilation system (CLDAS) reanalyzed daily Ta. Spatio-temporal continuous MODIS LST was reconstructed through the data interpolating empirical orthogonal functions (DINEOF) method. Multi-variable regression models were developed at CLDAS scale and then used to estimate Ta at MODIS scale. The new Ta estimation scheme was tested over the Langtang Valley, Nepal as a demonstrating case study. Observations from two automatic weather stations at Kyanging and Yala located in the Langtang Valley from 2012 to 2014 were used to validate the accuracy of Ta estimation. The RMSEs are 2.05, 1.88, and 3.63 K, and the biases are 0.42, −0.68 and −2.86 K for daily maximum, mean and minimum Ta, respectively, at the Kyanging station. At the Yala station, the RMSE values are 4.53, 2.68 and 2.36 K, and biases are 4.03, 1.96 and −0.35 K for the estimated daily maximum, mean and minimum Ta, respectively. Moreover, the proposed scheme can produce reasonable spatial distribution pattern of Ta at the Langtang Valley. Our results show the proposed Ta estimation scheme is promising for integration with distributed hydrological model for glacier melting simulation over glacierized basins.

Cotton is highly sensitive to potassium, and Xinjiang, China’s leading cotton-producing region, faces a severe challenge due to reduced soil potassium availability. Biofertilizers, particularly potassium-solubilizing rhizobacteria (KSR), convert insoluble potassium into plant-usable forms, offering a sustainable solution for evergreen agriculture. This study isolated and characterized KSR from cotton, elucidated their potassium solubilization mechanisms, and evaluated the effects of inoculating KSR strains on cotton seedlings. Twenty-three KSR strains were isolated from cotton rhizosphere soil using modified Aleksandrov medium. Their solubilizing capacities were assessed in a liquid medium. Strain A10 exhibited the highest potassium solubilization capacity (21.8 ppm) by secreting organic acids such as lactic, citric, acetic, and succinic acid, lowering the pH and facilitating potassium release. A growth curve analysis and potassium solubilization tests of A10 under alkali stress showed its vigorous growth and maintained solubilization ability at pH 8–9, with significant inhibition at pH 10. Furthermore, 16S rRNA sequencing identified strain A10 as Pseudomonas aeruginosa. Greenhouse pot experiments showed that inoculating cotton plants with strain A10 significantly increased plant height and promoted root growth. This inoculation also enhanced dry biomass accumulation in both the aerial parts and root systems of the plants, while reducing the root–shoot ratio. These results suggest that Pseudomonas aeruginosa A10 has potential as a biofertilizer, offering a new strategy for sustainable agriculture.

The Diurnal Temperature Range (DTR) profoundly affects human health, agriculture, eco-system, and socioeconomic systems. In this study, we analyzed past and future changes in DTR using gridded Climate Research Unit (CRU) datasets for the years 1950–2020 and an ensemble means of thirteen bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) models under different Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) scenarios for the rest of the 21st century over the southern slope of Central Himalaya, Nepal. Furthermore, the potential drivers (precipitation and cloud cover) of seasonal and annual DTR were studied using correlation analysis. This study found that the DTR trends generally declined; the highest decrease was observed in the pre-monsoon and winter at a rate of 0.09 °C/decade (p ≤ 0.01). As expected, DTR demonstrated a significant negative correlation with cloudiness and precipitation in all four seasons. Further, the decreased DTR was weakly related to the Sea Surface Temperature variation (SST) in the tropical Pacific and Indian Oceans. We found that the projected DTR changes in the future varied from a marginal increase under the SSP1-2.6 (only pre-monsoon) scenario to continued significant decreases under SSP2-4.5 and SSP5-8.5. Insights based on retrospective and prospective evaluation help to understand the long-term evolution of diurnal temperature variations.

The evaluation of soil particle composition and salt dynamics is essential for promoting the sustainable development of oasis agriculture in arid regions under long-term mulched drip irrigation (MDI). In this study, we employed the space-for-time substitution method to investigate the long-term effects of MDI on soil particle composition and salinity. Additionally, seven fields, with MDI durations ranging from 0 to 16 years, were selected to represent the primary successional sequence though time in Northwest China. Soil samples were collected from three soil depths (0–30 cm, 30–60 cm, and 60–100 cm) and then analyzed in the laboratory for soil particle composition and salt content. Our findings demonstrated that influenced by the depth of mechanical cultivation and the maximum wetting front depth, the long-term application of MDI significantly altered both the structure of soil layers and the composition of soil particles after 8 years. Soil sand content and soil salinity gradually decreased, whereas the content of soil silt and clay increased with increasing MDI duration throughout 0–100 cm soil depth. Furthermore, the rates of soil desalination stabilized after 10 years of MDI application, with desalination levels exceeding 90% in the 0–100 cm soil layer. Additionally, the soil mass fractal dimension (Dm) exhibited an upward trend across 0–100 cm soil depth. The changes in soil particle composition indirectly influenced the variations in Dm and salt content. Our study demonstrated that long-term application of MDI effectively mitigated soil salinity, changed soil structure, and ultimately enhanced soil quality and cotton yield.

The contamination of trace elements (TEs) in freshwater sources has become an alarming issue globally. This study evaluates the contamination level of TEs, their spatial distributions, and the health risks in the Ghodaghodi Lake complex, Nepal. Altogether, ten water samples were collected, and As, Ba, Cd, Co, Cr, Cs, Cu, Li, Mn, Ni, Pb, Rb, Sc, Sr, Ti, Tl, V, Y, and Zn were determined by inductively coupled plasma mass spectrometry. The results revealed that Sr, Zn, Cu, As, Sc, and Rb were dominated TEs, contributing to the contamination. The principal component analysis and correlation matrices demonstrated both the geogenic and anthropic origin of the TEs in the lake. The water quality index (WQI=10.08) and hazard indices <1 exhibited that the TEs pose a low risk to human health and, hence the water of the lake was suitable for drinking purposes. However, exposure risk assessment results suggested that children are relatively more vulnerable compared to adults. The outcome of this study will provide new insights to local people and the concerned authorities for the sustainable management of Ramsar listed Ghodaghodi Lake complex.

A predominantly mountainous country Nepal has a complex climatic pattern that varies from tropical in the south (Terai region) to arctic in the north (Himalayas). The gradual rise in temperature in the mountainous region has attracted great interest among the scientific community in general over recent years. However, recent warming in Nepal’s east-west and south-north temperature gradients and its implications for ecology and society based on facts and figures are still lacking. In this context, temperature data (1970–2016) of 76 meteorological stations from the Terai region to the Mountains were used in this study to analyze the annual and seasonal warming trends in the different physiographic regions of Nepal. We performed a hybrid analytical approach i.e. integrated statistical and theoretical tools to detect the warming trend and its ecological and societal implications across the country. The Eastern part of the country was found to be more warming than the Central and Western parts, showing an increased climatic sensitivity across the Khumbu (Mt. Everest region). The increasing trends of temperature have been found in all physiographic regions along an altitude gradient, i.e. Terai, Siwaliks, Lower Hills, and Upper Hills observed 0.15, 0.26, 0.68, and 0.57 °C per decade, respectively. Higher warming trend in Lower Hills than the Upper Hills showed that higher elevations experienced lesser degrees of warming trends than the lower elevations in the mountainous regions. Further, a higher warming trend was observed in the winter season than the other seasons in all regions except for Terai. Based on the warming trends in different physiographic regions, we also found a similar pattern of ecological impacts, where a higher warming region also experienced higher ecological impacts such as changes in water resources, phenology, etc. Lower Hills, Upper Hills, and Mountains experienced higher adverse impacts than the Terai and Siwaliks in the current global warming scenarios.