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Straw burning is a significant source of atmospheric pollutants, releasing particulate matter and trace gases. Capturing the characteristics of straw burning and understanding its influencing factors are important prerequisites for regulating straw burning. Based on the fire points detected by the Moderate-resolution Imaging Spectroradiometer (MODIS) in Hunan province, China, from 2010 to 2020, this study analyzed the spatiotemporal variations of straw burning and employed Geographically Weighted Regression (GWR) models to investigate the underlying forces driving straw burning. The results show that the spatiotemporal characteristics of straw burning in Hunan Province can be categorized into two distinct periods: 2010 to 2014 and 2015 to 2020. The period from 2010 to 2014 witnessed a rapid increase, while the period from 2015 to 2020 experienced fluctuating decreases. The shift is closely linked to the implementation of the straw burning ban policy in 2015. Spatially, the areas with a high number of fire points are primarily located in the southern regions, especially in the border regions between Chenzhou, Yongzhou, Hengyang, and Shaoyang cities. A significant change was found in the impact of economic development and human activity factors on straw burning before and after 2015. These factors include crop yield, Gross Domestic Product (GDP), and road network development. From the implementation of the straw burning ban policy, increases in GDP and settlement density will have a dampening effect on straw burning in a region. Straw burning locations may shift towards regions with relatively slow economic development. The results could serve as a foundation for decision-making to address the issue of straw burning. [ABSTRACT FROM AUTHOR]

Hydrologic sciences depend on data monitoring, analyses, and simulations of hydrologic processes to ensure safe, sufficient, and equal water distribution. These hydrologic data come from but are not limited to primary (lab, plot, and field experiments) and secondary sources (remote sensing, UAVs, hydrologic models) that typically follow FAIR Principles (Findable, Accessible, Interoperable, and Reusable: (go-fair.org)). Easy availability of FAIR data has become possible because the hydrology‐oriented organizations have pushed the community to increase coordination of the protocols for generating data and sharing model platforms. In addition, networking at all levels has emerged with an invigorated effort to activate community science efforts that complement conventional data collection methods. However, it has become difficult to decipher various complex hydrologic processes with increasing data. Machine learning, a branch of artificial intelligence, provide more accurate and faster alternatives to better understand different hydrological processes. The Integrated, Coordinated, Open, Networked (ICON) framework provides a pathway for water users to include and respect diversity, equity, and inclusivity. In addition, ICONs support the integration of peoples with historically marginalized identities into this professional discipline of water sciences. This article comprises three independent commentaries about the state of ICON principles in hydrology and discusses the opportunities and challenges of adopting them. Plain Language Summary: The Integrated, Coordinated, Open, Networked (ICON) perspective in the discipline of hydrological sciences helps integrate remote sensing, numerical modeling, data science, and different digital concepts, including machine learning to understand simple to complex hydrological processes at diverse temporal and spatial scales. Other benefits of incorporating the ICON framework include but are not limited to open, shareable, and easy to interpret, accurate, and timely generated monitored/observed or/and simulated water sciences information. Moreover, participation of the community and stakeholders help establish a network where research, education, and collaboration become easy and accessible. Besides, the ICON framework promotes innovation, equality, diversity, inclusion, and open access research in the discipline of hydrology that involves and supports early career, marginalized racial groups, women, lesbian, gay, bisexual, transgender and queer or questioning (LGBTQ+), and/or disabled researchers. Key Points: Hydrology simulations can be trusted, shared, reproduced, and improved using the Integrated, Coordinated, Open, Networked (ICON) frameworkOpen and networking Hydrology‐oriented community science bridges the gap between the public and scientistsICON principles can strengthen inclusive, equitable, and accessible science in the hydrological community [ABSTRACT FROM AUTHOR]

Water bodies (WBs), such as lakes, ponds, and impoundments, provide essential ecosystem services for human society, yet their characteristics and changes over large areas remain elusive. Here we used unprecedented data layers derived from all Landsat images available between 1984 and 2015 to understand the overall characteristics and changes of WBs between 2 epochs (i.e., 1984 to 1999 and 2000 to 2015) in China. Results show that the abundance estimate of WBs greater than 1 km² and the total WB surface area were 0.3 to 1.5 times and 0.2 to 0.5 times more than the previous estimates, respectively. The size-abundance and shoreline-area relationships of WBs in China conformed to the classic power scaling law, in contradiction to most previous studies. WB changes with various occurrence probabilities show widespread coexistence of disappearance of existent and emergence of new WBs across China driven primarily by human activities and climate change. Our results highlight the importance of using appropriate long-term satellite data to reveal the true properties and dynamics of WBs over large areas, which is essential for developing scaling theories and understanding the relative impacts of human activities and climate change on water resources in the world. [ABSTRACT FROM AUTHOR]

The objective of this study was to analyze patterns, dynamics and processes of land-use/cover changes in the transboundary Mara River Basin in East Africa. We specifically focused on deforestation and expansion of agriculture in the watershed. The intensity analysis approach was used to analyze data from satellite imagery-derived land-use/cover maps. Results indicate that swap change accounted for more than 50% of the overall change, which shows a very dynamic landscape transformation. Transition from closed forest to open forest was found to be a dominant landscape change, as opposed to a random change. Similarly, transition from open forest to small-scale agriculture was also found to be a dominant transition. This suggests a trend (pathway) of deforestation from closed forest to small-scale agriculture, with open forest as a transitional land cover. The observed deforestation may be attributed to continuous encroachment and a series of excisions of the forest reserve. Transition from rangeland to mechanized agriculture was found to be a dominant land-use change, which was attributed to change in land tenure. These findings are crucial for designing strategies and integrated watershed management policies to arrest further deforestation in the forest reserves as well as to sustainably control expansion of agriculture. [ABSTRACT FROM AUTHOR]

Compaction of upper soil layers by intensive sheep grazing has been connected with increased local flood risk in silvopastoral systems. A 12-week field study was conducted at the Henfaes Research Station near Bangor, Wales to compare canopy interception, soil water infiltration, and bulk density between a control pasture and two silvopastoral tree planting configurations: trees clumped in fenced-off ungrazed plots and trees planted evenly and grazed. The study's aim was to characterize the potential of these tree planting configurations to reduce local flood risk. Automated throughfall gauges were installed in each silvopastoral treatment along with a similarly designed control gauge located in the grazed control pasture. Soil water infiltration and bulk density were measured 20 times in a stratified random design for each treatment and control. Results showed that the mean soil infiltration capacity in clumped configuration was 504% greater than the control pasture and 454% greater than the even spaced configuration. Average canopy interception was higher in the clumped configuration (34%) than in the even spaced configuration (28%). Soil bulk density was lower in the clumped configuration (0.87 Mg/m3) than in the control pasture (0.93 Mg/m3) and even spaced configuration (1 Mg/m3). Results suggest that silvopastoral systems are more likely to benefit from clumped and ungrazed tree configurations than from evenly-spaced and grazed tree configurations because of enhanced infiltration, lower soil compaction, and increased canopy interception. Our findings support the growing evidence base that fenced-off tree areas in silvopastoral settings can increase infiltration and thus reduce local flood risk. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

We implement a spatially lumped hydrologic model to predict daily streamflow at 88 catchments within the state of Oregon and analyze its performance using the Oregon Hydrologic Landscape ( OHL) classification. OHL is used to identify the physio-climatic conditions that favor high (or low) streamflow predictability. High prediction catchments (Nash-Sutcliffe efficiency of [ABSTRACT FROM AUTHOR]