LEADER 02671nam 2200373 450 001 9910729782003321 005 20230729085911.0 035 $a(CKB)4960000000469009 035 $a(NjHacI)994960000000469009 035 $a(EXLCZ)994960000000469009 100 $a20230729d2023 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aArtificial Intelligence Techniques in Hydrology and Water Resources Management /$fFi-John Chang, Li-Chiu Chang, Jui-Fa Chen, editors 210 1$aBasel :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2023. 215 $a1 online resource (302 pages) 311 $a3-0365-7784-X 320 $aIncludes bibliographical references. 330 $aThe sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices. The thirteen research papers published in this Special Issue make significant contributions to long- and short-term hydrological modeling and water resources management under changing environments using AI techniques coupled with various analytics tools. These contributions, which cover hydrological forecasting, microclimate control, and climate adaptation, can promote hydrology research and direct policy making toward sustainable and integrated water resources management. 606 $aHydrology 615 0$aHydrology. 676 $a551.48 702 $aChen$b Jui-Fa 702 $aChang$b Fi-John 702 $aChang$b Li-Chiu 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910729782003321 996 $aArtificial Intelligence Techniques in Hydrology and Water Resources Management$93391981 997 $aUNINA