Browsing by Author "Lu, Hui"

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A Global Data Analysis for Representing Sediment and Particulate Organic Carbon Yield in Earth System Models
(2017-12) Tan, Zeli; Leung, L. Ruby; Li, HongYi; Tesfa, Teklu; Vanmaercke, Matthias; Poesen, Jean; Zhang, Xuesong; Lu, Hui; Hartmann, Jens
Although sediment yield (SY) from water erosion is ubiquitous and its environmental consequences are well recognized, its impacts on the global carbon cycle remain largely uncertain. This knowledge gap is partly due to the lack of soil erosion modeling in Earth System Models (ESMs), which are important tools used to understand the global carbon cycle and explore its changes. This study analyzed sediment and particulate organic carbon yield (CY) data from 1,081 and 38 small catchments (0.1-200 km2), respectively, in different environments across the globe. Using multiple statistical analysis techniques, we explored environmental factors and hydrological processes important for SY and CY modeling in ESMs. Our results show clear correlations of high SY with traditional agriculture, seismicity and heavy storms, as well as strong correlations between SY and annual peak runoff. These highlight the potential limitation of SY models that represent only interrill and rill erosion because shallow overland flow and rill flow have limited transport capacity due to their hydraulic geometry to produce high SY. Further, our results suggest that SY modeling in ESMs should be implemented at the event scale to produce the catastrophic mass transport during episodic events. Several environmental factors such as seismicity and land management that are often not considered in current catchment-scale SY models can be important in controlling global SY. Our analyses show that SY is likely the primary control on CY in small catchments and a statistically significant empirical relationship is established to calculate SY and CY jointly in ESMs.
Hydrological Drought in the Anthropocene: Impacts of Local Water Extraction and Reservoir Regulation in the U.S.
(2017-12) Wan, Wenhua; Zhao, Jianshi; Li, HongYi; Mishra, Ashok; Leung, L. Ruby; Hejazi, Mohamad; Wang, Wei; Lu, Hui; Deng, Zhiqun; Demissisie, Yonus; Wang, Hao
Hydrological drought is a substantial negative deviation from normal hydrologic conditions and is influenced by climate and human activities such as water management. By perturbing the streamflow regime, climate change and water management may significantly alter drought characteristics in the future. Here we utilize a high‐resolution integrated modeling framework that represents water management in terms of both local surface water extraction and reservoir regulation and use the Standardized Streamflow Index to quantify hydrological drought. We explore the impacts of water management on hydrological drought over the contiguous U.S. in a warming climate with and without emissions mitigation. Despite the uncertainty of climate change impacts, local surface water extraction consistently intensifies drought that dominates at the regional to national scale. However, reservoir regulation alleviates drought by enhancing summer flow downstream of reservoirs. The relative dominance of drought intensification or relief is largely determined by the water demand, with drought intensification dominating in regions with intense water demand such as the Great Plains and California, while drought relief dominates in regions with low water demand. At the national level, water management increases the spatial extent of extreme drought despite some alleviations of moderate to severe drought. In an emissions mitigation scenario with increased irrigation demand for bioenergy production, water management intensifies drought more than the business‐as‐usual scenario at the national level, so the impacts of emissions mitigation must be evaluated by considering its benefit in reducing warming and evapotranspiration against its effects on increasing water demand and intensifying drought.
Nonlinear Filtering Effects of Reservoirs on Flood Frequency Curves at the Regional Scale
(2017-10) Wang, Wei; Li, HongYi; Leung, L. Ruby; Yigzaw, Wondmagegn; Zhao, Jianshi; Lu, Hui; Deng, Zhiqun; Demisie, Yonas; Bloschl, Gunter
Reservoir operations may alter the characteristics of Flood Frequency Curve (FFC) and challenge the basic assumption of stationarity used in flood frequency analysis. This paper presents a combined data-modeling analysis of reservoir as a nonlinear filter of runoff routing that alters the FFCs. A dimensionless Reservoir Impact Index (RII), defined as the total upstream reservoir storage capacity normalized by the annual streamflow volume, is used to quantify reservoir regulation effects. Analyses are performed for 388 river stations in the contiguous U.S. using the first two moments of the FFC, mean annual maximum flood (MAF) and coefficient of variations (CV), calculated for the pre and post-dam periods. It is found that MAF generally decreases with increasing RII but stabilizes when RII exceeds a threshold value, and CV increases with RII until a threshold value beyond which CV decreases with RII. Hence depending on the magnitude of RII, reservoir regulation acts as a filter to increase or reduce the nonlinearity of the natural runoff routing process and alters flood characteristics. The nonlinear relationships of MAF and CV with RII can be captured by three reservoir models with different levels of complexity, suggesting that they emerge from the basic flood control function of reservoirs. However, the threshold RII values in the nonlinear relationships depend on the more detailed reservoir operations and objectives that can only be captured by the more complex reservoir models. Our conceptual model may help improve flood-risk assessment and mitigation in regulated river systems at the regional scale.