Kai Duan

Comparison of Meteorological, Hydrological and Agricultural Drought Responses to Climate Change and Uncertainty Assessment

A comparison study of meteorological, hydrological and agricultural drought responses to climate change resulting from different General Circulation Models (GCMs), emission scenarios and hydrological models is presented. Drought variations from 1961–2000 to 2061–2100 in Huai River basin above Bengbu station in China are investigated. Meteorological drought is recognized by the Standardized Precipitation Index (SPI) while hydrological drought and agricultural drought are indexed with a similar standardized procedure by the Standardized Runoff Index (SRI) and Standardized Soil Water Index (SSWI). The results generally approve that hydrological and agricultural drought could still pose greater threats to local water resources management in the future, even with a more steady background to meteorological drought. However, the various drought responses to climate change indicate that uncertainty arises in the propagation of drought from meteorological to hydrological and agricultural systems with respect to alternative climates. The uncertainty in hydrological model structure, as well as the uncertainties in GCM and emission scenario, are aggregated to the results and lead to much wider variations in hydrological and agricultural drought characteristics. Our results also reveal that the selection of hydrological models can induce fundamental differences in drought simulations, and the role of hydrological model uncertainty may become dominating among the three uncertainty sources while recognizing frequency of extreme drought and maximum drought duration.

Multi-scale analysis of meteorological drought risks based on a Bayesian interpolation approach in Huai River basin, China

A scheme for meteorological drought analysis at various temporal and spatial scales based on a spatial Bayesian interpolation of drought severity derived from Standardized Precipitation Index (SPI) values at observed stations is presented and applied to the Huai River basin of China in this paper, using monthly precipitation record from 1961 to 2006 in 30 meteorological stations across the basin. After dividing the study area into regular grids, drought condition in gauged sites are classified into extreme, severe, moderate and non drought according to SPIs at month, seasonal and annual time scales respectively while that in ungauged grids are explained as risks of various drought severities instead of single state by a Bayesian interpolation. Subsequently, temporal and spatial patterns of drought risks are investigated statistically. Main conclusions of the research are as follows: (1) drought at seasonal scale was more threatening than the other two time scales with a larger number of observed drought events and more notable variation; (2) results of the Mann–Kendall test revealed an upward trend of drought risk in April and September; (3) there were larger risks of extreme and severe drought in southern and northwestern parts of the basin while the northeastern areas tended to face larger risks of moderate drought. The case study in Huai River basin suggests that the proposed approach is a viable and flexible tool for monitoring meteorological drought at multiple scales with a more specific insight into drought characteristics at each severity level.

Impact of air pollution induced climate change on water availability and ecosystem productivity in the conterminous United States

Air pollution from greenhouse gases and atmospheric aerosols are the major driving force of climate change that directly alters the terrestrial hydrological cycle and ecosystem functions. However, most current Global Climate Models (GCMs) use prescribed chemical concentrations of limited species; they do not explicitly simulate the time-varying concentrations of trace gases and aerosols and their impacts on climate change. This study investigates the individual and combined impacts of climate change and air pollution on water availability and ecosystem productivity over the conterminous US (CONUS). An ecohydrological model is driven by multiple regional climate scenarios with and without taking into account the impacts of air pollutants on the climate system. The results indicate that regional chemistry-climate feedbacks may largely offset the future warming and wetting trends predicted by GCMs without considering air pollution at the CONUS scale. Consequently, the interactions of air pollution and climate change are expected to significantly reduce water availability by the middle of twenty-first century. On the other hand, the combined impact of climate change and air pollution on ecosystem productivity is less pronounced, but there may still be notable declines in eastern and central regions. The results suggest that air pollution could aggravate regional climate change impacts on water shortage. We conclude that air pollution plays an important role in affecting climate and thus ecohydrological processes. Overlooking the impact of air pollution may cause evident overestimation of future water availability and ecosystem productivity.

Divergence of ecosystem services in U.S. National Forests and Grasslands under a changing climate

The 170 National Forests and Grasslands (NFs) in the conterminous United States are public lands that provide important ecosystem services such as clean water and timber supply to the American people. This study investigates the potential impacts of climate change on two key ecosystem functions (i.e., water yield and ecosystem productivity) using the most recent climate projections derived from 20 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project phase 5 (CMIP5). We find that future climate change may result in a significant reduction in water yield but an increase in ecosystem productivity in NFs. On average, gross ecosystem productivity is projected to increase by 76 ~ 229 g C m−2 yr−1 (8% ~ 24%) while water yield is projected to decrease by 18 ~ 31 mm yr−1 (4% ~ 7%) by 2100 as a result of the combination of increased air temperature (+1.8 ~ +5.2 °C) and precipitation (+17 ~ +51 mm yr−1). The notable divergence in ecosystem services of water supply and carbon sequestration is expected to intensify under higher greenhouse gas emission and associated climate change in the future, posing greater challenges to managing NFs for both ecosystem services.

Copula-Based Bivariate Flood Frequency Analysis in a Changing Climate—A Case Study in the Huai River Basin, China

Copula-based bivariate frequency analysis can be used to investigate the changes in flood characteristics in the Huai River Basin that could be caused by climate change. The univariate distributions of historical flood peak, maximum 3-day and 7-day volumes in 1961–2000 and future values in 2061–2100 projected from two GCMs (CSIRO-MK3.5 and CCCma-CGCM3.1) under A2, A1B and B1 emission scenarios are analyzed and compared. Then, bivariate distributions of peaks and volumes are constructed based on the copula method and possible changes in joint return periods are characterized. Results indicate that the Clayton copula is more appropriate for historical and CCCma-CGCM3.1 simulating flood variables, while that of Frank and Gumbel are better fitted to CSIRO-MK3.5 simulations. The variations of univariate and bivariate return periods reveal that flood characteristics may be more sensitive to different GCMs than different emission scenarios. Between the two GCMs, CSIRO-MK3.5 evidently predicts much more severe flood conditions in future, especially under B1 scenario, whereas CCCma-CGCM3.1 generally suggests contrary changing signals. This study corroborates that copulas can serve as a viable and flexible tool to connect univariate marginal distributions of flood variables and quantify the associated risks, which may provide useful information for risk-based flood control.

Parallel dynamic programming based on stage reconstruction and its application in reservoir operation

Dynamic programming is a classisc method to solve reservoir optimized operation. However, with the increasing number of reservoir power stations, computation amount is increasing exponentially, resulting in a dramatic decrease in the timeliness of solving and even causing “curse of dimensionality”. In response to this, we improved the serial recursion calculation process of dynamic programming and introduced parallel dynamic programming based on stage reconstruction. Through the proposed algorithm a multistage decision problem can be repeatedly reconstructed in a parallel environment and gradually transferred to a single stage issue. This algorithm was then applied to solve the optimized operation of cascade reservoirs in the lower reach of Yalong River in China. Analog computation was carried out to evaluate the effects of parameter control on the parallel calculation performance of the algorithm. Results indicate that the calculating efficiency, compared with serial dynamic programming, can be significantly improved without sacrificing the accuracy with parallel dynamic programming based on stage reconstruction.

Implications of Upstream Flow Availability for Watershed Surface Water Supply Across the Conterminous United States

Although it is well established that the availability of upstream flow (AUF) affects downstream water supply, its significance has not been rigorously categorized and quantified at fine resolutions. This study aims to fill this gap by providing a nationwide inventory of AUF and local water resource, and assessing their roles in securing water supply across the 2,099 8-digit hydrologic unit code watersheds in the conterminous United States (CONUS). We investigated the effects of river hydraulic connectivity, climate variability, and water withdrawal, and consumption on water availability and water stress (ratio of demand to supply) in the past three decades (i.e., 1981– 2010). The results show that 12% of the CONUS land relied on AUF for adequate freshwater supply, while local water alone was sufficient to meet the demand in another 74% of the area. The remaining 14% highly stressed area was mostly found in headwater areas or watersheds that were isolated from other basins, where stress levels were more sensitive to climate variability. Although the constantly changing water demand was the primary cause of escalating/diminishing stress, AUF variation could be an important driver in the arid south and southwest. This research contributes to better understanding of the significance of upstream–downstream water nexus in regional water availability, and this becomes more crucial under a changing climate and with intensified human activities. (KEY TERMS: water supply; runoff; rivers/streams; simulation; time series analysis; planning.) Duan, Kai, Ge Sun, Peter V. Caldwell, Steven G. McNulty, and Yang Zhang, 2018. Implications of Upstream Flow Availability for Watershed Surface Water Supply across the Conterminous United States. Journal of the American Water Resources Association (JAWRA) 54(3): 694–707. https://doi.org/10.1111/1752-1688.12644

Effect of Hydrologic Alteration on the Community Succession of Macrophytes at Xiangyang Site, Hanjiang River, China

With the intensification of human activities over the past three decades in China, adverse effects on river ecosystem become more serious especially in the Hanjiang River. Xiangyang site is an important spawn ground for four domestic fishes in the downstream region of Hanjiang River. Based on the field survey results of macrophytes during 1997–2000 and 2013-2014, community succession of aquatic macrophytes at Xiangyang site was evaluated and discussed. Two-key ecologic-related hydrologic characteristics, flow regime and water level, were identified as the main influence factors. The EFC (environmental flow components) parameters were adopted to evaluate the alteration of flow regimes at Xiangyang site during 1941–2013. Evaluation results demonstrate a highly altered flow process after being regulated by reservoir. The flow patterns tend to be an attenuation process with no large floods occurring but a higher monthly low flow. Furthermore, the water level decreased and fluctuation reduced after the dam was built, which caused the decrease of biomass but favored the submerged macrophytes during 1995–2009. However, with the water level increasing after 2010 and gently fluctuating, due to uplift by the hydraulic projects downstream as well as the flow attenuation, the dominant position of submerged macrophytes will be weakened.

Impacts of forest biomass removal on water yield across the United States

With the expected increase in demand for woody biomass to help meet renewable energy needs, one principal sustainability question has been whether this material can be removed from forest stands while still conserving biological diversity and retaining ecosystem functioning (Hecht et al. 2009; Berch, Morris, and Malcolm 2011; Ridley et al. 2013). In general, biodiversity is the variety of life and can be considered at the genetic, population, species, community, and ecosystem levels (Berch, Morris, and Malcolm 2011). Biodiversity is often character- ized as the number of species (or other taxonomic entity) and the relative abundance of each species in a defined space at a given time. A larger species pool is generally believed to indicate improved ecosystem functioning (i.e., health, resilience, goods, and services), especially in landscapes with intensified use (Loreau et al. 2001). Indices of species richness and evenness of their distribution (e.g., common or rare) are often used to measure local diversity and to compare the diversity across geographic areas. Relative abundance metrics, however, are not always good predictors of species importance for multiple reasons, but the scale of observation often dictates results (Godfray and Lawton 2001). More emphasis is being placed on understanding biodiversity through functional shifts in species assemblages in response to changing environments (i.e., ecosystem functioning) (Loreau et al. 2001; Hooper et al. 2005). Uncertainties exist on whether shifts in species assemblages, each with their own set of traits, influence ecosystem functioning even when biodiversity metrics may be similar.

Parallel dynamic programming based on stage ReConstruction and its application in reservoir operation

Dynamic programming is a classisc method to solve reservoir optimized operation. However, with the increasing number of reservoir power stations, computation amount is increasing exponentially, resulting in a dramatic decrease in the timeliness of solving and even causing “curse of dimensionality”. In response to this, we improved the serial recursion calculation process of dynamic programming and introduced parallel dynamic programming based on stage reconstruction. Through the proposed algorithm a multistage decision problem can be repeatedly reconstructed in a parallel environment and gradually transferred to a single stage issue. This algorithm was then applied to solve the optimized operation of cascade reservoirs in the lower reach of Yalong River in China. Analog computation was carried out to evaluate the effects of parameter control on the parallel calculation performance of the algorithm. Results indicate that the calculating efficiency, compared with serial dynamic programming, can be significantly improved without sacrificing the accuracy with parallel dynamic programming based on stage reconstruction.