Multivariate Dam-Site Flood Frequency Analysis of the Three Gorges Reservoir Considering Future Reservoir Regulation and Precipitation

Under a changing environment, the current hydrological design values derived from historical flood data for the Three Gorges Reservoir (TGR) might be no longer applicable due to the newly-built reservoirs upstream from the TGR and the changes in climatic conditions. In this study, we perform a multivariate dam-site flood frequency analysis for the TGR considering future reservoir regulation and summer precipitation. The Xinanjiang model and Muskingum routing method are used to reconstruct the dam-site flood variables during the operation period of the TGR. Then the distributions of the dam-site flood peak and flood volumes with durations of 3, 7, 15, and 30 days are built by Pearson type III (PIII) distribution with time-varying parameters, which are expressed as functions of both reservoir index and summer precipitation anomaly (SPA). The multivariate joint distribution of the dam-site flood variables is constructed by a 5-D C-vine copula. Finally, by using the criteria of annual average reliability (AAR) associated with the exceedance probabilities of OR, AND and Kendall, we derive the multivariate dam-site design floods for the TGR from the predicted flood distributions during the future operation period of the reservoir. The results indicate that the mean values of all flood variables are positively linked to SPA and negatively linked to RI. In the future, the flood mean values are predicted to present a dramatic decrease due to the regulation of the reservoirs upstream from the TGR. As the result, the design dam-site floods in the future will be smaller than those derived from historical flood distributions. This finding indicates that the TGR would have smaller flood risk in the future.

Modeling Spatial Patterns of Dissolved Oxygen and the Impact Mechanisms in a Cascade River

Dissolved oxygen (DO) concentration is an essential indicator for assessment of river ecosystems. A hydrodynamic and water quality mathematical model coupling one-dimensional and two-dimensional models is developed in this study. The characteristics of study area, flow velocity, temperature, and organic contamination are taken as consideration in the scenario setting. The changing processes of DO concentration are simulated in different scenarios, and the effects on DO concentration are discussed. Results indicate that: 1) A negative relation was present between DO concentration in Yongjiang River and releasing discharge of the Laokou hydro-project, since reoxygenation is greater than oxygen consumption along the river, DO concentration increases from upstream to downstream. 2) DO concentration increases with the releasing of DO in the water, which also varies along with the releasing of biochemical oxygen demand (BOD) concentration. Laokou exhibits the greatest increase of BOD, which ranges from 0.1 mg/L to 0.75 mg/L 3) The increasing of water temperature results in increased reoxygenation and a decrease in oxygen consumption. Our study shows that the water temperature increased from 19°C to 29 °C, and correspondingly saturated DO decreased from 9.25 mg/L to 7.54 mg/L. The study provides scientific support for ecology operation in the cascade river, and is expected to improve the water environment by reservoir regulation.

Reservoir regulation affects droughts and floods at local and regional scales

Hydrological extremes can be particularly impactful in catchments with high human presence where they are modulated by human intervention such as reservoir regulation. Still, we know little about how reservoir operation affects droughts and floods, particularly at a regional scale. Here, we present a large data set of natural and regulated catchment pairs in the United States and assess how reservoir regulation affects local and regional drought and flood characteristics. Our results show that (1) reservoir regulation affects drought and flood hazard at a local scale by reducing severity (i.e. intensity/magnitude and deficit/volume) but increasing duration; (2) regulation affects regional hazard by reducing spatial flood connectedness (i.e. number of catchments a catchment co-experiences flood events with) in winter and by increasing spatial drought connectedness in summer; (3) the local alleviation effect is only weakly affected by reservoir purpose for both droughts and floods. We conclude that both local and regional flood and drought characteristics are substantially modulated by reservoir regulation, an aspect that should neither be neglected in hazard nor climate impact assessments.

Detection, attribution and frequency analysis of non-stationary flood peaks in 32 big rivers worldwide

<p>Due to climate variability and reservoir regulation worldwide, it is fundamentally challenging to implement holistic assessments of detection, attribution and frequency analysis on non-stationary flood peaks. In this study, we proposed an integrated approach that combines the prewhitening Mann-Kendall test technique, Partial Mutual Information-Partial Weights (PMI-PW) method and Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS) method to achieve reliable non-stationary flood frequency analysis. Firstly, the prewhitening Mann-Kendall test was employed to detect the trend change of flood peaks. Secondly, the PMI-PW was employed to attribute the contribution of climate change and reservoir regulation to non-stationarity of flood peaks. Lastly, the GAMLSS method was employed to quantify the change in flood risks under the non-stationary condition. The applicability of the proposed approach was investigated by long-term (1931-2017) flood series collected from 32 big river catchments globally. The results suggested that global flood trends varied from increasing +19.3%/decade to decreasing −31.6%/decade. Taking the stationary flood frequency analysis as the benchmark, the comparative results revealed that the flood risk in 5 rivers under the non-stationary condition in response to warming climate significantly increased over the historical period whereas the flood risk in 7 rivers in response to increasing reservoir storage largely reduced. Despite the spatiotemporal heterogeneity of observations, the changes in flood peaks evaluated here were explicitly associated with the changing climate and reservoir storage, supporting the demand for considering the non-stationarity of flood peaks in the best interest of social sustainability.</p><p><strong>Keywords:</strong> Flood peaks; Large catchments; Non-stationarity; Frequency analysis</p><p>*This work was supported by the Research Council of Norway (FRINATEK Project 274310).</p><p> </p><p> </p><p> </p>

Regionalization of Reservoir regulation parameters using physiographic and climatological predictors

<p>Present regional and global scale hydrology has to account for man-made reservoirs that impart significant regulation signature into the downstream streamflow regime. Optimization of domains with large number of reservoirs would incur multitude of reservoir regulation parameters. Such parameter-set-per-reservoir approach not only results in excessive computational costs but also, by principle, lacks effective constraining of the parameter space. We propose an approach to derive single set of parameters for all the reservoirs and lakes in the modelling domain. The hypothesis is that reservoir regulation parameters can be regionalized using physiography and climatology at lakes and their catchments.<br><br>To test this hypothesis, we setup a modeling domain for the São Francisco basin of Northeast Brazil in the mesoscale hydrological model (mHM, www.ufz.de/mhm). The domain consists of climatology ranging from tropical (As) to semi-arid (BSh) and reservoirs with catchment area varying from less than 500 km<sup>2</sup> to greater than 500,000 km<sup>2</sup>. We carried out correlation analysis between selected physiographical and climatological predictors and the reservoir parameters of the multiscale lake module, mLM, of the mHM model (https://presentations.copernicus.org/EGU2020/EGU2020-6047_presentation.pdf). For an instance, the reservoir rule curves in mLM are estimated based on inflow and position of water level. The predictors here are inflow and water level which are normalized using catchment area and the shape of the reservoir, respectively. Similarly, the timing and shape parameters of rule curves were plotted against the climatological characteristics of the upstream catchment. The preliminary results reveal significant trends between the mLM parameters and the normalized predictors. These mathematical relationships, better known as transfer functions, can now be used to generate a single global reservoir parameter set.</p><p>The demonstrated hypothesis helps to optimize regulated hydrology using a single parameter set, irrespective of size, location and inherent climatology of reservoirs involved. This is inline with the pre-existing paradigm of multiscale parameter regionalization (MPR) of mHM. The findings contribute to the contemporary effort of hydrological modeling society towards improved global scale hydrological modeling.</p>