Xianli Xu

Is southwestern China experiencing more frequent precipitation extremes

Climate extremes have and will continue to cause severe damages to buildings and natural environments around the world. A full knowledge of the probability of the climate extremes is important for the management and mitigation of natural hazards. Based on Mann–Kendall trend test and copulas, this study investigated the characteristics of precipitation extremes as well as their implications in southwestern China (Yunnan, Guangxi and Guizhou Province), through analyzing the changing trends and probabilistic characteristics of six indices, including the consecutive dry days, consecutive wet days, annual total wet day precipitation, heavy precipitation days (R25), max 5 day precipitation amount (Rx5) and the rainy days (RDs). Results showed that the study area had generally become drier (regional mean annual precipitation decreased by 11.4 mm per decade) and experienced enhanced precipitation extremes in the past 60 years. Relatively higher risk of drought in Yuanan and flood in Guangxi was observed, respectively. However, the changing trends of the precipitation extremes were not spatially uniform: increasing risk of extreme wet events for Guangxi and Guizhou, and increasing probability of concurrent extreme wet and dry events for Yunnan. Meanwhile, trend analyses of the 10 year return levels of the selected indices implied that the severity of droughts decreased in Yunnan but increased significantly in Guangxi and Guizhou, and the severity of floods increased in Yunnan and Guangxi in the past decades. Hence, the policy-makers need to be aware of the different characterizations and the spatial heterogeneity of the precipitation extremes.

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Development of multi-metamodels to support surface water quality management and decision making

Abstract Watershed management and planning is a complex decision-making process, which not only involves deliberation using one or more watershed models, but also requires collaboration among multiple stakeholder groups with different ideologies, interests, and demographics. Web-based decision support tools have great potentials to enhance the transparency and participation of such decision making processes. Although physically based surface water quality models are well suited for offline water quality analyses, they are often too computationally demanding to be deployed in a web-based environment. In this work, three metamodels are developed to support decision-making activities related to surface water quality management at Arroyo Colorado Watershed, a coastal watershed located in Texas, US. All three metamodels are trained using an existing Soil and Water Assessment Tool (SWAT) model developed for the watershed. The main objectives of the metamodels are to support web-based decision support, including near-term nutrient load forecasting, online sensitivity study, and long-term load reduction planning. All metamodels either replicate or extend the capabilities of the original SWAT model and, thus, provide proxies for regulators and stakeholders to examine and discuss model results interactively. The novel, multi-metamodel methodology taken here is not only useful for supporting multigroup decision making and public education, but also provides a more effective way to leverage existing investment on watershed models.

Biogeographical patterns of biomass allocation in leaves, stems, and roots in China’s forests

To test whether there are general patterns in biomass partitioning in relation to environmental variation when stand biomass is considered, we investigated biomass allocation in leaves, stems, and roots in China’s forests using both the national forest inventory data (2004–2008) and our field measurements (2011–2012). Distribution patterns of leaf, stem, and root biomass showed significantly different trends according to latitude, longitude, and altitude, and were positively and significantly correlated with stand age and mean annual precipitation. Trade-offs among leaves, stems, and roots varied with forest type and origin and were mainly explained by stand biomass. Based on the constraints of stand biomass, biomass allocation was also influenced by forest type, origin, stand age, stand density, mean annual temperature, precipitation, and maximum temperature in the growing season. Therefore, after stand biomass was accounted for, the residual variation in biomass allocation could be partially explained by stand characteristics and environmental factors, which may aid in quantifying carbon cycling in forest ecosystems and assessing the impacts of climate change on forest carbon dynamics in China.

Annual Runoff is Highly Linked to Precipitation Extremes in Karst Catchments of Southwest China

AbstractKarst landforms cover 7%–12% of the Earth’s continental area and provide water resources for 25% of the global population. Climate, particularly frequent climate extremes, may greatly affect the annual runoff, especially in climate-sensitive regions such as a karst area of southwest China. Knowledge of the linkage between climate and runoff is urgently needed for smart water resources management. This study therefore selected five catchments that have different carbonized rock coverage (from 11% to 64%) to detect the dominant climatic variables driving changes in annual runoff for the period of 1957–2011 in southwest China. Because climatic variables are highly codependent, a partial least squares regression (PLSR) was used to elucidate the linkages between runoff and 17 climatic variables. Results indicated that the dominant climatic factors driving annual runoff are annual total precipitation, rainy days, heavy precipitation amount, heavy precipitation days, rainstorm amount, and rainstorm days....

The global distribution of Earth's critical zone and its controlling factors

The near-surface layer of Earth which provides essential elements for supporting life is now recognized as the critical zone (CZ). This study provides the first global assessment of the CZ thickness (CZT) and its controlling factors by combining data sets of climate, vegetation height (VH), water table depth (WTD), groundwater thickness (GWT), topography, and lithologic data. The analysis shows that CZT ranges from 0.7 to 223.5 m with an average value of 36.8 m across continental areas; CZT is thickest in midlatitudes (subtropical to temperate zones). The proportion of aboveground part (VH) to CZT is 19.9 ± 16.7% (mean ±one standard deviation), while it is 80.1 ± 16.7% for the underground part (WTD + GWT). A generalized linear model shows that compound topographic index (ln(a/tan(b)), where a is the upslope contributing area and b is the slope degree of the landscape) and potential evapotranspiration are the first two major controlling factors on the variations in CZT. This study opens opportunities for further advancing CZ science by providing one of its most important properties—its thickness.

Effects of vegetation restoration on soil quality in degraded karst landscapes of southwest China

Vegetation restoration was implemented to control soil erosion in the karst regions of southwest China. It is essential to assess the soil function and quality scientifically during this process and to adopt suitable management practices for this area. However, few studies have been conducted to comprehensively evaluate the effect of vegetation restoration on soil quality in this severely eroded karst area. By taking 302 soil samples from 11 vegetation types, this study investigated the influence of different types of vegetation restoration on soil quality using an integrated soil quality index (SQI) and a generalized linear model (GLM). Vegetation types had significant effects on soil properties and thus on soil quality. SQI was developed by using TN, TP, TK, AP, and clay content; TN had highest weighting values (0.58), which indicated that it contributed the most to final SQI. The highest and lowest SQI values were observed for primary forest and cropland, respectively. Overall, vegetation restoration (e.g., natural restoration, artificial forests and artificial grassland) improved soil quality significantly. A GLM model explained 73.20% of the total variation in SQI, and vegetation type explained the largest proportion (46.39%) of the variation, which implies that the vegetation restoration practices can greatly enhance the soil quality in karst landscapes of southwest China. The results of this study may be used to improve implication of ecological restoration and management in degraded regions.

Prediction of profile soil moisture for one land use using measurements at a soil depth of other land uses in a karst depression

PurposeInformation on root-zone soil water content (SWC) is essential for vegetation restoration, irrigation scheduling, and hydrological modeling. However, measurements of SWC within a variety of land uses may be time-consuming and labor-costing. This study tested whether SWC at a depth of a land use can be used to predict profile SWC of other land uses in terms of temporal stability analysis at a karst depression area in southwest China.Materials and methodsA total of 30 datasets of root-zone SWC from 0.1- to 0.5-m depths were collected by time domain reflectometry probes for three typical land uses from March 12 to November 8, 2015.Results and discussionResults showed that the profile mean SWC and its associated standard deviation (SDP) and coefficient of variation (CVP) differed significantly (P < 0.05) among the grassland, farmland, and forestland. The profile SWC was more temporally stable according to the apparently lower CVT in comparison with CVP. The similarities of the vertical patterns of SWC were strong for the same land uses, while were relatively weak between the different land uses. The SWC measurements of the most temporally stable depth can be used to accurately predict profile SWC for both the same land use and other land uses.ConclusionsThis study further expands the application of the temporal stability analysis and can aid water resource management in areas with diverse land uses.