Climate change events significantly impact the food production chain by damaging crops in their most fragile phenological states. Furthermore, increasing human population and excess food waste present agricultural systems with the challenge of closing the yield gap and securing food demands in the future as well as protect the soil health and biodiversity. Biostimulants are a novel alternative in agriculture that can effectively use inputs, enhance crop resilience to abiotic stresses and improve food quality. Additionally, biostimulants offer a promising and eco-friendly solution for reducing the use of chemical fertilizers, as they have the potential to increase crop nutrient use efficiency and yield. Because of their effects on plant growth, a wide range of products can be marketed as biostimulants. Presented in this review is an overview of recent literature on the use of plant growth-promoting microbes and microalgae-derived extracts obtained from either waste streams or recycled substrates. Starting from their source material, extraction technologies and application modalities, a view of their factors shaping the composition and activity of biostimulants is provided to elucidate a mechanistic model of action which leads to increased stress resilience in crops. This work further sets out to understand if the biostimulants can be used to transform waste into a valuable product that can accelerate the transition to sustainable agriculture.This article is part of the theme issue 'Crops under stress: can we mitigate the impacts of climate change on agriculture and launch the 'Resilience Revolution'?'.

Global climate change and the decreasing availability of high-quality water lead to an increase in the salinization of agricultural lands. This rising salinity represents a significant abiotic stressor that detrimentally influences plant physiology and gene expression. Consequently, critical processes such as seed germination, growth, development, and yield are adversely affected. Salinity severely impacts crop yields, given that many crop plants are sensitive to salt stress. Plant growth-promoting microorganisms (PGPMs) in the rhizosphere or the rhizoplane of plants are considered the second genome of plants as they contribute significantly to improving the plant growth and fitness of plants under normal conditions and when plants are under stress such as salinity. PGPMs are crucial in assisting plants to navigate the harsh conditions imposed by salt stress. By enhancing water and nutrient absorption, which is often hampered by high salinity, these microorganisms significantly improve plant resilience. They bolster the plant's defenses by increasing the production of osmoprotectants and antioxidants, mitigating salt-induced damage. Furthermore, PGPMs supply growth-promoting hormones like auxins and gibberellins and reduce levels of the stress hormone ethylene, fostering healthier plant growth. Importantly, they activate genes responsible for maintaining ion balance, a vital aspect of plant survival in saline environments. This review underscores the multifaceted roles of PGPMs in supporting plant life under salt stress, highlighting their value for agriculture in salt-affected areas and their potential impact on global food security.

Floods in southwestern Saudi Arabia, especially in the Asir region, are among the major natural disasters caused by natural and human factors. In this region, flash floods that occur in the Wadi Hail Basin greatly affect human life and activities, damaging property, the built environment, infrastructure, landscapes, and facilities. A previous study carried out for the same basin has effectively revealed zones of flood risk using such an approach. However, the utilization of the HEC-HMS (Hydrologic Engineering Center-Hydrologic Modeling System) model and IMERG data for delineating areas prone to flash floods remain unexplored. In response to this advantage, this work primarily focused on flood generation assessment in the Wadi Hail Basin, one of the major basins in the region that is frequently prone to severe flash flood damage, from a single extreme rainfall event. We employed a fully physical-based, distributed hydrological model run with HEC-HMS software version 4.11 and Integrated Multi-satellite Retrievals of Global Precipitation Measurement (IMERG V.06) data, as well as other geo-environmental variables, to simulate the water flow within the Wadi Basin, and predict flash flood hazard. Discharge from the wadi and its sub-basins was predicted using 1 mm rainfall over an 8-h occurrence time. Significant peak discharge (3.6 m3/s) was found in eastern and southern upstream sub-basins and crossing points, rather than those downstream, due to their high-density drainage network (0.12) and CNs (88.4). Generally, four flood hazard levels were identified in the study basin: 'low risk', 'moderate risk', 'high risk', and 'very high risk'. It was found that 43.8% of the total area of the Wadi Hail Basin is highly prone to flooding. Furthermore, medium- and low-hazard areas make up 4.5-11.2% of the total area, respectively. We found that the peak discharge value of sub-basin 11 (1.8 m3/s) covers 13.2% of the total Wadi Hail area; so, it poses more flood risk than other Wadi Hail sub-basins. The obtained results demonstrated the usefulness of the methods used to develop useful hydrological information in a region lacking ungagged data. This study will play a useful role in identifying the impact of extreme rainfall events on locations that may be susceptible to flash flooding, which will help authorities to develop flood management strategies, particularly in response to extreme events. The study results have potential and valuable policy implications for planners and decision-makers regarding infrastructural development and ensuring environmental stability. The study recommends further research to understand how flash flood hazards correlate with changes at different land use/cover (LULC) classes. This could refine flash flood hazards results and maximize its effectiveness.

The uncertainty of passive microwave retrievals of snowfall is notoriously high where high-frequency surface emissivity is significantly reduced and varies markedly in response to the changes in snowpack physical properties. Using the dense media radiative transfer theory, this article studies the potential effects of terrestrial snow-cover depth, density, and grain size on high-frequency channels 89 and 166 GHz of the radiometer onboard the Global Precipitation Measurement (GPM) core satellite, which are commonly used to capture snowfall scattering signals. Integrating the inference across all feasible grain sizes, ranges of snowpack density and depth are identified over which snowfall scattering signatures can be time-varying and potentially obscured. Using ten years of reanalysis data, the seasonal vulnerability of snowfall retrievals to the changes in snowpack emissivity in the Northern Hemisphere is mapped in a probabilistic sense and connections are made with the uncertainties of the GPM passive microwave snowfall retrievals. It is found that among different snow classes, relatively light Arctic tundra snow in fall, with a density below 260 kg m(-3), and shallow prairie snow during the winter, with a depth of less than 40 cm, can reduce the surface emissivity and obscure the snowfall passive microwave signatures. It is demonstrated that during winter, the highly vulnerable areas are over Kazakhstan and Mongolia with taiga and prairie snow. In the fall, these areas are largely over tundra and taiga snow in north of Russia and the Arctic Archipelagos as well as prairies in Canada and the Great Plains in the United States.

降水是地表及地下水资源的根本补给源,直接影响水资源的时空分布格局以及山地冰冻圈的分布和发育。祁连山高寒山区是降水和产流高值区,降水特征受地形影响较大,但现有的降水观测网络还无法合理反映降水特征在地形垂直梯度上的变化。为了确定降水变化如何影响高寒山区的水文和生态过程,需要从流域垂直梯度观测降水形态和降水量的变化。本文概述了由T-200BM3组成的祁连山高山区降水格网化、梯度化、自动化观测网络,并在八一冰川冰缘区建立高寒山区降水标准校正场,采用世界气象组织(WMO)推荐的降水/降雪观测标准(DFIR)校正八一冰川区域降水量。在八一冰川区域对地面降水数据产品作初步分析,并利用高海拔站点数据评估了GPM和TRMM降水数据产品在祁连山区的适用性。该降水观测网络的建设对进一步认识高寒山区不同海拔雨雪和水汽变化规律,精细化评估高寒山区降水资源具有重要意义,并可为全国的降水资源综合观测和评估提供方法和降水数据产品。

降水是地表及地下水资源的根本补给源,直接影响水资源的时空分布格局以及山地冰冻圈的分布和发育。祁连山高寒山区是降水和产流高值区,降水特征受地形影响较大,但现有的降水观测网络还无法合理反映降水特征在地形垂直梯度上的变化。为了确定降水变化如何影响高寒山区的水文和生态过程,需要从流域垂直梯度观测降水形态和降水量的变化。本文概述了由T-200BM3组成的祁连山高山区降水格网化、梯度化、自动化观测网络,并在八一冰川冰缘区建立高寒山区降水标准校正场,采用世界气象组织(WMO)推荐的降水/降雪观测标准(DFIR)校正八一冰川区域降水量。在八一冰川区域对地面降水数据产品作初步分析,并利用高海拔站点数据评估了GPM和TRMM降水数据产品在祁连山区的适用性。该降水观测网络的建设对进一步认识高寒山区不同海拔雨雪和水汽变化规律,精细化评估高寒山区降水资源具有重要意义,并可为全国的降水资源综合观测和评估提供方法和降水数据产品。