Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development.

Water is undoubtedly the most valuable resource of human society and an essential component of the ecosystem

As an essential part of the hydrological cycle, precipitation is usually associated with floods and droughts and is increasingly being paid attention to in the context of global warming. Analyzing the change trends and correlation of temperature and extreme precipitation indicators can effectively identify natural disasters. This study aimed to detect the correlation and change trends of temperature and extreme precipitation indicators in Inner Mongolia from 1960 to 2019. Panel vector autoregression (PVAR) models based on Stata software were used to detect the correlation between temperature and extreme precipitation indicators at 35 climatological stations throughout Inner Mongolia. The temperature and extreme precipitation indicator trends were analyzed using the Mann–Kendall test and Sen’s slope method. The spatial distribution characteristics of the annual precipitation and rainfall intensity were more significant in the southeast and more minor in the northwest, while an increase in the annual wet days was noticeable to the northeast. The Granger cause tests of the temperature and the extreme precipitation indicators showed a correlation between each indicator and temperature at the significance level of 1%. The temperature positively correlated with only the rainfall intensity while negatively correlating with the remaining indicators. There is no doubt that trend analysis showed significant increasing trends in rainfall intensity at all stations, which means increased risk in extreme precipitation events. By contrast, the annual precipitation and annual wet days showed significant decreasing trends, which means that the precipitation is concentrated, and it is easier to form extreme precipitation events. The study can provide a basis for decision-making in water resources and drought/flood risk management in Inner Mongolia, China.

As a result of urbanization and climate change, urban areas are increasingly vulnerable to flooding, which can have devastating effects on the loss of life and property. Remote sensing technology can provide practical help for urban flood disaster management. This research presents a review of urban flood-related remote sensing to identify research trends and gaps, and reveal new research opportunities. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), the systematic literature search resulted in 347 documents classified as geography, disaster management application, and remote sensing data utilization. The main results include 1. most of the studies are located in high-income countries and territories and inland areas; 2. remote sensing for observing the environment was more popular than observing the building; 3. the most often applied disaster management activities were vulnerability assessment and risk modeling (mitigation) and rapid damage assessment (response); 4. DEM is often applied to simulate urban floods as software inputs. We suggest that future research directions include 1. coastal urban study areas in non-high-income countries/territories to help vulnerable populations; 2. understudied disaster management activities, which often need to observe the buildings in more urban areas; 3. data standardization will facilitate integration with international standard methods for assessing urban floods.