Guobin Fu

Impacts of precipitation and temperature changes on annual streamflow in the Murray–Darling Basin

The relationship between the interannual changes in streamflow, precipitation and temperature of the Murray–Darling basin is investigated by using a two-parameter climate elasticity of streamflow approach. The non-linear relationship between streamflow and both precipitation and temperature indicates a greater streamflow sensitivity to precipitation than to temperature but a more significant impact of temperature change on streamflow than previously reported. The physical mechanisms producing high streamflow sensitivity to temperature change are not well understood, but may relate to concurrent changes in sub-annual precipitation characteristics such as seasonality, spatial distribution and intensity. Thus these characteristics need to be assessed and accounted for when attempting to project how streamflow, and hence water availability, may change in a future warmer world.

The streamflow trend in Tangwang River basin in northeast China and its difference response to climate and land use change in sub-basins

In this study, the hydro-climatic trends (1964–2006) of Tangwang River basin (TRB) were examined using the Kendall’s test. Moreover, the impacts of climate variability and land use change on streamflow in each sub-basin were assessed using the Soil and Water Assessment Tools (SWAT) model. The results indicated that annual mean flow and peak flow showed insignificant decreasing trends (−0.14xa0m3xa0s−1xa0year−1, 1xa0%; −8.67xa0m3xa0s−1xa0year−1, 40xa0%), while annual low flow exhibited a slightly increasing trend (0.02xa0m3xa0s−1xa0year−1, 11xa0%). Correspondingly, the annual precipitation for the entire basin decreased by 0.02xa0mmxa0year−2, while the annual means of daily mean, maximum and minimum temperature increased significantly by 0.07, 0.10 and 0.02xa0°Cxa0year−1, respectively. On the other hand, with the implementation of “Natural Forest Protection Project” and “Grain for Green Project”, the forests in TRB totally increased by 744.5xa0km2 (4.00xa0%) from 1980 to 2000. Meanwhile, the grasslands and the farmlands decreased by 378.0xa0km2 (−1.98xa0%) and 311.9xa0km2 (−1.63xa0%), respectively. Overall, land use changes played a more important role for the streamflow reduction than climate change for SUB1, SUB2 and SUB3, in which the primary conversions were from grassland, farmland and bare land to forests. Conversely, in SUB4, the influence of climate variability was predominant. The results obtained could be a reference for water resources planning and management under changing environment.

Projection of future rainfall for the North China Plain using two statistical downscaling models and its hydrological implications

This study projected the future rainfall (2046–2065 and 2081–2100) for the North China Plain (NCP) using two stochastic statistical downscaling models, the non-homogeneous hidden Markov model and the generalized linear model for daily climate time series, conditioned by the large-scale atmospheric predictors from six general circulation models for three emission scenarios (A1B, A2 and B1). The results indicated that the annual total rainfall, the extreme daily rainfall and the maximum length of consecutive wet/dry days would decline, while the number of annual rainfall days would slightly increase (correspondingly rainfall intensity would decrease) in the NCP, in comparison with the base period (1961–2010). Moreover, the summer monsoon rainfall, which accounted for 50–75xa0% of the total annual rainfalls in NCP, was projected to decrease in the latter half of twenty-first century. The spatial patterns of change showed generally north–south gradients with relatively larger magnitude decrease in the northern NCP and less decrease (or even slightly increase) in the southern NCP. This could result in decline of the annual runoff by −5.5xa0% (A1B), −3.3xa0% (A2) and −4.1xa0% (B1) for 2046–2065 and −5.3xa0% (A1B), −4.6xa0% (A2) and −1.9xa0% (B1) decrease for 2081–2100. These rainfall changes, combined with the warming temperature, could lead to drier catchment soil profiles and further reduce runoff potential, would hence provide valuable references for the water availability and related climate change adaption in the NCP.

Probability models of fire risk based on forest fire indices in contrasting climates over China

Abstract: Fire weather indices have been widely applied to predict fire risk in many regions of the world. The objectives of this study were to establish fire risk probability models based on fire indices over different climatic regions in China. We linked the indices adopted in Canadian, US, and Australia with location, time, altitude, vegetation and fire characteristics during 1998–2007 in four regions using semi— parametric logistic (SPL) regression models. Different combinations of fire risk indices were selected as explanatory variables for specific regional probability model. SPL regression models of probability of fire ignition and large fire events were established to describe the non—linear relationship between fire risk indices and fire risk probabilities in the four regions. Graphs of observed versus estimated probabilities, fire risk maps, graphs of numbers of large fire events were produced from the probability models to assess the skill of these models. Fire ignition in all regions showed a significant link with altitude and NDVI. Indices of fuel moisture are important factors influencing fire occurrence in northern China. The fuel indices of organic material are significant indicators of fire risk in southern China. Besides the well skill of predicting fire risk, the probability models are a useful method to assess the utility of the fire risk indices in estimating fire events. The analysis presents some of the dynamics of climate-fire interactions and their value for management systems.