Tongtiegang Zhao

How Suitable is Quantile Mapping For Postprocessing GCM Precipitation Forecasts

AbstractGCMs are used by many national weather services to produce seasonal outlooks of atmospheric and oceanic conditions and fluxes. Postprocessing is often a necessary step before GCM forecasts can be applied in practice. Quantile mapping (QM) is rapidly becoming the method of choice by operational agencies to postprocess raw GCM outputs. The authors investigate whether QM is appropriate for this task. Ensemble forecast postprocessing methods should aim to 1) correct bias, 2) ensure forecasts are reliable in ensemble spread, and 3) guarantee forecasts are at least as skillful as climatology, a property called “coherence.” This study evaluates the effectiveness of QM in achieving these aims by applying it to precipitation forecasts from the POAMA model. It is shown that while QM is highly effective in correcting bias, it cannot ensure reliability in forecast ensemble spread or guarantee coherence. This is because QM ignores the correlation between raw ensemble forecasts and observations. When raw foreca...

Adaptive Reservoir Operation Model Incorporating Nonstationary Inflow Prediction

AbstractLong-term changes in reservoir inflow due to climate change and human interferences have caused doubts on the assumption of hydrologic stationarity in reservoir design and operation. Incorporating uncertain predictions that consider nonstationarity into an adaptive reservoir operation is a promising strategy for handling the challenges that result from nonstationarity. This study proposes rules for multistage optimal hedging operations that incorporate uncertain inflow predictions for large reservoirs with multiyear flow regulation capacities. Three specific rules for determining the optimal numerical solution are derived. A solution algorithm is then developed based on the optimality conditions and the three rules. The optimal hedging rules and the solution algorithm are applied to the Miyun Reservoir in China, which exhibited a statistically significant decline in reservoir inflow trend from 1957 to 2009, to determine an annual operating schedule from 1996 to 2009. Nonstationary inflows are pred...

Source of atmospheric moisture and precipitation over China＇s major river basins

Oceanic evaporation via the East Asian Monsoon (EAM) has been regarded as the major source of precipitation over China, but a recent study estimated that terrestrial evaporation might contribute up to 80% of the precipitation in the country. To explain the contradiction, this study presents a comprehensive analysis of the contribution of oceanic and terrestrial evaporation to atmospheric moisture and precipitation in China’s major river basins. The results show that from 1980 to 2010, the mean annual atmospheric moisture (precipitable water) over China was 13.7 mm, 39% of which originates from oceanic evaporation and 61% from terrestrial evaporation. The mean annual precipitation was 737 mm, 43% of which originates from oceanic evaporation and 57% from terrestrial evaporation. Oceanic evaporation makes a greater contribution to atmospheric moisture and precipitation in the East Asian Monsoon Region in South and East China than terrestrial evaporation does. Particularly, for the Pearl River and southeastern rivers, oceanic evaporation contributes approximately 65% of annual precipitation and more than 70% of summer precipitation. Meanwhile, terrestrial evaporation contributes more precipitation in northwest China due to the westerly wind. For the northwestern rivers, terrestrial evaporation from the Eurasian continents contributes more than 70% of precipitation. There is a linear relation between mean annual precipitation and the contribution of oceanic evaporation to precipitation, with a correlation coefficient of 0.92, among the ten major river basins in China.

Optimizing Operation of Water Supply Reservoir: The Role of Constraints

This paper presents a mathematical analysis of water supply reservoir operation. The analysis illustrates one-stage, two-stage, and three-stage formulations of multiple-period reservoir operation depending on the effects of operational constraints. There is a one-stage model when storage capacity constraints are nonbinding. Release decisions depend on total water availability and exhibit equal marginal utilities. Binding upper (lower) storage capacity constraint blocks the effect of decreased (increased) water availability in the subsequent stages on release decisions in the preceding stages. When one storage capacity constraint is binding, multiple periods become two stages and a gap occurs between marginal utilities of water. When there are one upper and one lower binding storage capacity constraints, reservoir operation is characterized as a three-stage model. Effects of forecast uncertainty and ending storage on reservoir operation are affected by reservoir storage capacity. When the storage capacity constraints are nonbinding, the reservoir can regulate streamflow in an extended timeframe, and current release decision is affected by forecast uncertainty of total streamflow and ending storage. When the storage capacity constraints are binding, the reservoir can regulate streamflow only in a short timeframe, and current release decision is primarily affected by forecast uncertainty of streamflow in the current stage.

Optimal Pre-storm Flood Hedging Releases for a Single Reservoir

Flood hedging reservoir operation is when a pre-storm release creates a small flood downstream to reduce the likelihood of a more damaging but uncertain larger flood in the future. Such pre-storm releases before a flood can increase reservoir storage capacity available to capture more severe flood flows, but also can immediately increase downstream flood damage and reduce stored water supply. This study develops an optimization model for pre-storm flood hedging releases and examines some necessary theoretical conditions for optimality, considering hydrologic uncertainty from flood forecasts and engineering uncertainty from flood failures. Theoretically, the ideal optimality condition for pre-storm flood hedging releases is where the current marginal damage from the hedging release equals the future expected marginal damage from storm releases. Additional water supply losses due to pre-storm releases tend to reduce pre-storm flood hedging releases. The overall flood damage cost to be minimized must be a convex function of pre-storm hedging releases for flood hedging to be optimal. Such convexity is determined by the overall flood risk together with the probability distribution of storm forecasts. Increasing the convexity of the failure probability function can induce more pre-storm hedging release. Categorized by flood risk likelihood downstream, forecasted storms that are large, but not yet overwhelming flood management systems, drive optimal flood hedging operation. A wide range of near-optimal hedging releases is observed in numerical examples, providing options for more rational water resources management decisions.

Deriving Flood-Mediated Connectivity between River Channels and Floodplains: Data-Driven Approaches

The flood-mediated connectivity between river channels and floodplains plays a fundamental role in flood hazard mapping and exerts profound ecological effects. The classic nearest neighbor search (NNS) fails to derive this connectivity because of spatial heterogeneity and continuity. We develop two novel data-driven connectivity-deriving approaches, namely, progressive nearest neighbor search (PNNS) and progressive iterative nearest neighbor search (PiNNS). These approaches are illustrated through a case study in Northern Australia. First, PNNS and PiNNS are employed to identify flood pathways on floodplains through forward tracking. That is, progressive search is performed to associate newly inundated cells in each time step to previously inundated cells. In particular, iterations in PiNNS ensure that the connectivity is continuous – the connection between any two cells along the pathway is built through intermediate inundated cells. Second, inundated floodplain cells are collectively connected to river channel cells through backward tracing. Certain river channel sections are identified to connect to a large number of inundated floodplain cells. That is, the floodwater from these sections causes widespread floodplain inundation. Our proposed approaches take advantage of spatial–temporal data. They can be applied to achieve connectivity from hydro-dynamic and remote sensing data and assist in river basin planning and management.

Relating anomaly correlation to lead time: Clustering analysis of CFSv2 forecasts of summer precipitation in China

GCM forecasts are an integral part of long-range hydro-climatic forecasting. We propose to use hierarchical clustering to explore anomaly correlation, which indicates the performance of raw GCM forecasts, in the three-dimensional space of latitude, longitude and initialisation time. Focusing on a certain period of the year, correlations for forecasts initialised at different preceding periods form a vector. The vectors of anomaly correlation across different GCM grid cells are clustered to reveal how GCM forecasts perform as time progresses. Through the case study of CFSv2 forecasts of summer precipitation in China, we observe that the correlation at a certain cell oscillates with lead time and can become negative. The use of clustering reveals two meaningful patterns that characterize the relationship between anomaly correlation and lead time. For some grid cells in Central and Southwest China, CFSv2 forecasts exhibit positive correlations with observations and they tend to improve as time progresses. This result suggests that CFSv2 forecasts tend to capture the summer precipitation induced by the East Asian monsoon and the South Asian monsoon. It also indicates that CFSv2 forecasts can potentially be applied to improving hydrological forecasts in these regions. For some other cells, the correlations are generally close to zero at different lead times. This outcome implies that CFSv2 forecasts still have plenty of room for further improvement. The robustness of the patterns has been tested using both hierarchical clustering and k-means clustering and examined with the Silhouette score.

Annual shifts of flow regime alteration: new insights from the Chaishitan Reservoir in China

Reservoir regulation is variable for flow regime alterations and mainly depends on operational objectives and hydro-meteorological conditions. In this study, the flow regime metrics (i.e., magnitude, variability and frequency, duration, timing and rate of change) are adopted to describe variations in both long-term inflow and outflow series of the Chaishitan Reservoir in China. Deviations between the inflow and outflow metrics are calculated to assess the flow regime alterations at annual scale. Further, dimensions of both time and flow regimes are reduced by multivariate statistical analysis, and the regulation patterns and their annual shifts are identified. Results show that: four regulation patterns are identified from 2004 to 2015. The regulation is gradually enhanced over time with typical features of different hydrological years. In dry years, the pattern is slightly regulated flow regimes with slightly discharging stored water and flattening outflow, moderate stability and intermittency. In normal years, the pattern is slightly regulated flow regimes with extremely increasing flow magnitude in the pre-nonflood season, high stability and slight intermittency. In wet years, the pattern is moderately regulated flow regimes with moderately decreasing flow magnitude in the flood season but extremely increasing flow magnitude in the nonflood season, slight stability and high intermittency.

Multi-Reservoir System Operation Theory and Practice

The state-of-the-art on operation of multi-reservoir system is reviewed and multi-reservoir construction and management practice in China are introduced at the beginning. Considering the impact of human activity on the reservoir inflow, multi-reservoir operation is studied within theory framework of dualistic water cycle. The reservoir operation rule form and derivation method are the most important elements for deriving optimal multi-reservoir operation policy. Different rule curves and multi-objective optimization algorithms are discussed in this chapter. Inter-basin water transfer project becomes one of effective measures to mitigate imbalance between water supply and water demand. The multi-reservoir operation problem in inter-basin water transfer project is illustrated mainly on deriving the water transfer rule and water supply rule using bi-level model. Reservoir inflow is important information for multi-reservoir operation. The effect of inflow forecast uncertainty on real-time reservoir operation, effective forecast horizon identification and generalized marginal model of the uncertainty evolution of inflow forecast are discussed in details.