[1] Quantifying partitioning of precipitation into evapotranspiration (ET) and runoff is the key to assessing water availability globally. Here we develop a universal model to predict water-energy partitioning (ϖ parameter for the Fu's equation, one form of the Budyko framework) which spans small to large scale basins globally. A neural network (NN) model was developed using a data set of 224 small U.S. basins (100-10,000 km 2 ) and 32 large, global basins (~230,000-600,000 km 2 ) independently and combined based on both local (slope, normalized difference vegetation index) and global (geolocation) factors. The Budyko framework with NN estimated ϖ reproduced observed mean annual ET well for the combined 256 basins. The predicted mean annual ET for~36,600 global basins is in good agreement (R 2 = 0.72) with an independent global satellite-based ET product, inversely validating the NN model. The NN model enhances the capability of the Budyko framework for assessing water availability at global scales using readily available data. Citation: Xu, X., W. Liu, B. R. Scanlon, L. Zhang, and M. Pan (2013), Local and global factors controlling water-energy balances within the Budyko framework, Geophys.

Soil erodibility (the K factor in the Universal Soil Loss Equation, USLE) is an important index to measure soil susceptibility to water erosion, and an essential parameter needed for soil erosion prediction. To evaluate the appropriateness of the nomograph and other methods for estimating the K factor for the USLE and to develop a relationship for soil erodibility estimation for Chinese soils, a set of soil erodibility values was calculated using soil loss data from natural runoff plots at 13 sites in eastern China. The definition of soil erodibility in relation to the USLE was strictly followed. Comparing these measured values to those estimated using the nomograph method, the method adopted for the EPIC model and the formula of Shirazi and Boersma, we found that all these estimated soil erodibility values were considerably higher than the measured soil erodibility for these sites in eastern China. Soil erodibility for these Chinese sites is typically in the range from 0.007 to 0.02 t h (MJ mm)À1 and consistently lower in comparison to the measured K values from the USLE database for the conterminous United States. Strong linear relationship between the estimated and measured K values were used to develop empirical formulas for soil erodibility estimation from soil survey data for sites in eastern China. r

No abstract

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.

No abstract

Abstract:This article presents the results of a field investigation of saturated hydraulic conductivity K sat and bulk density (r bd ) in an Atlantic blanket bog in the southwest of Ireland. Starting at a peatland stream and moving along an uphill transect toward the peatland interior, r bd and K sat were examined at regular intervals. Saturated horizontal hydraulic conductivity (Kh sat ) and vertical (Kv sat ) was estimated at two depths: 10-20 and 30-40 cm below the peat surface, whereas r bd was estimated for the full profile. We consider two separate zones, one a riparian zone extending 10 m from the stream and a second zone in the bog interior. We found that the K sat was higher (~10 -5 m s -1 ) in the bog interior than that in the riparian zone (~10 -6 m s), whereas the converse applied to bulk density, with lowest density (~0.055 g cm -3 ) at the interior and highest (~0.11 g cm -3 ) at the riparian zone. In general, we found Kh sat to be approximately twice the Kv sat . These results support the idea that the lower K sat at the margins control the hydrology of blanket peatlands. It is therefore important that the spatial variation of these two key properties be accommodated in hydrological models if the correct rainfall runoff characteristics are to be correctly modelled. Stream flow analysis over 3 years at the peatland catchment outlet showed that the stream runoff was composed of 8% base flow and 92% flood flow, suggesting that this blanket peatland is a source rather than a sink for floodwaters.

No abstract

Understanding of the relationships between vegetation and soil and topography would be very important for ecosystem restoration and management efforts in the dry valleys of Himalayan region but how to clarify the complicated relationships and figure out key factors for practical purpose is a challenge. The main objective of this research was to propose a four-staged procedure by combining several multivariate statistical techniques to detect the relationships between vegetation and soil and topography, and thereby identify the key factors for the degraded ecosystem restoration and management. Forty-three plots (5 m × 5 m) were selected for the field survey of the vegetation, soil and topography variables in the dry warm river valley of the upper Minjiang River, Sichuan Province, China. Cluster analysis (CA) demonstrated that high plant diversity, cover and height were associated with good soil quality and favorable topographic positions with lower solar incident radiation, runoff and soil erosion potential. Correlation analysis (simple correlation analysis and canonical correlation analysis) and multiple linear stepwise regression analysis affirmed that plant diversity was mainly correlated with soil water content, and soil water content was mainly determined by soil texture (clay content). Soil clay content alone could explain about 70% of the total variance. Identifying the favorable topographic position and the distribution pattern of soil texture and its controlling mechanisms is thus very important for restoration practices. In the process of ecosystem restoration, we should promote the co-evolution of vegetation and soil, and follow the natural succession sequence. Some relevant conservation polices are also needed to reduce human disturbance on ecosystem.