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Accurate quantification of wetland depression water storage capacity (WDWSC) is imperative for comprehending the wetland hydrological regulation functions to support integrated water resources management. Considering the challenges posed by the high acquisition cost of high-resolution LiDAR DEM or the absence of field measurements for most wetland areas, urgent attention is required to develop an accurate estimation framework for WDWSC using open-source, low-cost, multi-source remote sensing data. In response, we developed a novel framework, WetlandSCB, utilizing coarse-resolution terrain data for accurate estimation of WDWSC. This framework overcame several technical difficulties, including biases in above-water topography, incompleteness and inaccuracy of wetland depression identification, and the absence of bathymetry. Validation and application of the framework were conducted in two national nature reserves of northeast China. The study demonstrated that integrating priority-flood algorithm, morphological operators and prior information can accurately delineate the wetland depression distribution with overall accuracy and Kappa coefficient both exceeding 0.95. The use of water occurrence map can effectively correct numerical biases in above-water topography with Pearson coefficient and R2 increasing by 0.33 and 0.38 respectively. Coupling spatial prediction and modeling with remote sensing techniques yielded highly accurate bathymetry estimates, with <3 % relative error compared to filed measurements. Overall, the WetlandSCB framework achieved estimation of WDWSC with <10 % relative error compared to field topographic and bathymetric measurements. The framework and its concept are transferable to other wetland areas globally where field measurements and/or high-resolution terrain data are unavailable, contributing to a major technical advancement in estimating WDWSC in river basins. [ABSTRACT FROM AUTHOR]

Wetlands and reservoirs are important water flow and storage regulators in a river basin; therefore, they can play a crucial role in mitigating flood and hydrological drought risks. Despite the advancement of river basin theory and modeling, our knowledge is still limited about the extent that these two regulators could have in performing such a role, especially under future climate extremes. To improve our understanding, we first developed a framework coupling wetlands and reservoir operations with a semi-spatially explicit hydrological model and then applied it in a case study involving a large river basin in Northeast China. The projection of future floods and hydrological droughts was performed using this framework during different periods (near-future: 2026–2050, mid-century: 2051–2075, and end-century: 2076–2100) under five future climate change scenarios. We found that the risk of future floods and hydrological droughts can vary across different periods, in particular, will experience relatively large increases and slight decreases. This large river basin will experience longer duration, larger peak flows and volume, and enhanced flashiness flood events than the historical period. Simultaneously, the hydrological droughts will be much more frequent with longer duration and more serious deficit. Therefore, the risk of floods and droughts will overall increase further under future climate change even under the combined influence of reservoirs and wetlands. These findings highlight the hydrological regulation function of wetlands and reservoirs and attest that the combining of wetlands with reservoir operation cannot fully eliminate the increasing future flood and drought risks. To improve a river basin's resilience to the risks under future climate change, we argue that implementation of wetland restoration and development of accurate forecasting systems for effective reservoir operation are of great importance. Furthermore, this study demonstrated a wetland-reservoir integrated modeling and assessment framework that is conducive to risk assessment of floods and hydrological droughts, which can be used for other river basins in the world. [ABSTRACT FROM AUTHOR]