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245		0	_aAdvances in Hydrologic Forecasts and Water Resources Management
546			_aEnglish[eng]
650			_awater resources management||landslide||dammed lake||flood risk||time-varying parameter||GR4J model||changing environments||temporal transferability||western China||cascade hydropower reservoirs||multi-objective optimization||TOPSIS||gravitational search algorithm||opposition learning||partial mutation||elastic-ball modification||Snowmelt Runoff Model||parameter uncertainty||data-scarce deglaciating river basin||climate change impacts||generalized likelihood uncertainty estimation||Yangtze River||cascade reservoirs||impoundment operation||GloFAS-Seasonal||forecast evaluation||small and medium-scale rivers||highly urbanized area||flood control||whole region perspective||coupled models||flood-risk map||hydrodynamic modelling||Sequential Gaussian Simulation||urban stormwater||probabilistic forecast||Unscented Kalman Filter||artificial neural networks||Three Gorges Reservoir||Mahalanobis-Taguchi System||grey entropy method||signal-to-noise ratio||degree of balance and approach||interval number||multi-objective optimal operation model||feasible search space||Pareto-front optimal solution set||loss–benefit ratio of ecology and power generation||elasticity coefficient||empirical mode decomposition||Hushan reservoir||data synthesis||urban hydrological model||Generalized Likelihood Uncertainty Estimation (GLUE)||Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)||uncertainty analysis||NDVI||Yarlung Zangbo River||machine learning model||random forest||Internet of Things (IoT)||regional flood inundation depth||recurrent nonlinear autoregressive with exogenous inputs (RNARX)||artificial intelligence||machine learning||multi-objective reservoir operation||hydrologic forecasting||uncertainty||risk
700			_aChang, Fi-John||Guo, Shenglian
856			_uhttps://mdpi.com/books/pdfview/book/2725
942			_cEB
999			_c29213 _d29213