Assessment of CMIP5 historical simulations of rainfall over Southeast Asia

Theoretical and Applied Climatology - We present preliminary analyses of the historical (1986–2005) climate simulations of a ten-member subset of the Coupled Model Inter-comparison Project...     

Regional climate simulations over Vietnam using the WRF model

Time-irreversible symmetry is a fundamental property of nonlinear time series. Time-irreversible behaviors of mean temperature measured on 182 stations over China from 1960 to 2012 are analyzed by directed horizontal visibility graph (DHVG for short), and significance of results has been estimated by Monte Carlo simulations. It is found that dominated time irreversibility emerges in nearly all daily temperature anomaly variations over China. Further studies indicate that these time-irreversible behaviors result from asymmetric distributions of persistent daily temperature increments and decrements, and this kind of symmetry can be quantified by distributions of consecutive daily mean temperature increasing or decreasing steps. At the same time, the findings above have been confirmed by artificially generated time series with given value of multiscale asymmetry.     

Possible Impacts of Global Warming on the Hydrology of the Ogallala Aquifer Region

The Ogallala or High Plains aquifer provides water for about 20% of the irrigated land in the United States. About 20 km³ (16.6 million acre-feet) of water are withdrawn annually from this aquifer. In general, recharge has not compensated for withdrawals since major irrigation development began in this region in the 1940s. The mining of the Ogallala has been pictured as an analogue to climate change in that many GCMs predict a warmer and drier future for this region. In this paper we attempt to anticipate the possible impacts of climate change on the sustainability of the aquifer as a source of water for irrigation and other purposes in the region. We have applied HUMUS, the Hydrologic Unit Model of the U.S. to the Missouri and Arkansas-White-Red water resource regions that overlie the Ogallala. We have imposed three general circulation model (GISS, UKTR and BMRC) projections of future climate change on this region and simulated the changes that may be induced in water yields (runoff plus lateral flow) and ground water recharge. Each GCM was applied to HUMUS at three levels of global mean temperature (GMT) to represent increasing severity of climate change (a surrogate for time). HUMUS was also run at three levels of atmospheric CO₂ concentration (hereafter denoted by [CO₂]) in order to estimate the impacts of direct CO₂ effects on photosynthesis and evapotranspiration. Since the UKTR and GISS GCMs project increased precipitation in the Missouri basin, water yields increase there. The BMRC GCM predicts sharply decreased precipitation and, hence, reduced water yields. Precipitation reductions are even greater in the Arkansas basin under BMRC as are the consequent water yield losses. GISS and UKTR climates lead to only moderate yield losses in the Arkansas. CO₂-fertilization reverses these losses and yields increase slightly. CO₂ fertilization increases recharge in the base (no climate change) case in both basins. Recharge is reduced under all three GCMs and severities of climate change.     

Evaluation of global optimization algorithms for parameter calibration of a computationally intensive hydrologic model

With the popularity of complex hydrologic models, the time taken to run these models is increasing substantially. Comparing and evaluating the efficacy of different optimization algorithms for calibrating computationally intensive hydrologic models is becoming a nontrivial issue. In this study, five global optimization algorithms (genetic algorithms, shuffled complex evolution, particle swarm optimization, differential evolution, and artificial immune system) were tested for automatic parameter calibration of a complex hydrologic model, Soil and Water Assessment Tool (SWAT), in four watersheds. The results show that genetic algorithms (GA) outperform the other four algorithms given model evaluation numbers larger than 2000, while particle swarm optimization (PSO) can obtain better parameter solutions than other algorithms given fewer number of model runs (less than 2000). Given limited computational time, the PSO algorithm is preferred, while GA should be chosen given plenty of computational resources. When applying GA and PSO for parameter optimization of SWAT, small population size should be chosen. Copyright © 2008 John Wiley & Sons, Ltd.     

Glacier mass balance simulation using SWAT distributed snow algorithm

Application of a temperature-index melt model incorporated into the Soil and Water Assessment Tool (SWAT) is presented to simulate mass balance (MB) and equilibrium line altitude (ELA) of three glaciers. The snow accumulation/melt parameters were adjusted to glacierized and free glacier areas, respectively. The SWAT snow algorithm enabled us to consider spatial variation of snow parameters by elevation bands across the sub-basins, while in the previous studies using SWAT, the related parameters were constant for an entire basin. The results show slight improvement in runoff simulation and significant improvement in simulated MB when considering ELA in model calibration. The results showed that SWAT can be applied to simulate MB, vertical MB distribution and annual ELA, with light calibration efforts for data-scarce catchments. The accuracy of the results depends on the modelled area of ablation zone from which most of the meltwater is released.     

Simulating sub-daily hydrological process with SWAT: a review

ABSTRACT

The Soil and Water Assessment Tool (SWAT) is a watershed-scale hydrologic model that integrates water quantity and quality modules. Despite the large amount of knowledge on the SWAT model, specific understanding of sub-daily applications remains limited. In this review, we identify the shortcomings and possible ways forward in simulating sub-daily processes with the model. A literature review was conducted, along with a participatory method based on a questionnaire. We reviewed 28 scientific articles and categorized them into: (i) model development, (ii) streamflow methods comparison, (iii) water quality, and (iv) other applications. We found that using sub-daily data improves hydrograph peak simulation, while for medium flows use of daily data was better. From all the reviewed studies, a 1-hour time step was the most suitable time scale for the sub-daily model application. The participatory questionnaire confirmed the hypothesis that the main challenge for using the sub-daily routine was the lack of high-resolution data.     

Calibration and uncertainty analysis of the SWAT model using Genetic Algorithms and Bayesian Model Averaging

In this paper, the Genetic Algorithms (GA) and Bayesian Model Averaging (BMA) were used to simultaneously conduct calibration and uncertainty analysis for the Soil and Water Assessment Tool (SWAT). In this combined method, several SWAT models with different structures are first selected; next GA is used to calibrate each model using observed streamflow data; finally, BMA is applied to combine the ensemble predictions and provide uncertainty interval estimation. This method was tested in two contrasting basins, the Little River Experimental Basin in Georgia, USA, and the Yellow River Headwater Basin in China. The results obtained in the two case studies show that this combined method can provide deterministic predictions better than or comparable to the best calibrated model using GA. The 66.7% and 90% uncertainty intervals estimated by this method were analyzed. The differences between the percentage of coverage of observations and the corresponding expected coverage percentage are within 10% for both calibration and validation periods in these two test basins. This combined methodology provides a practical and flexible tool to attain reliable deterministic simulation and uncertainty analysis of SWAT.     

Lineament analysis of Cannanore district and their implication on the tectonic evolution of the area

The Cannanore district and the adjoining areas mainly comprise of charnokites, gniesses, high and low-grade schists and various types of igneous intrusives. The lineament fabric of the region indicates that the NNW-SSE, NW-SE, ENE-WSW and NE-SW lineament directions are prominent. It is suggested that the area has undergone at least three distinct phases of tectonic activity. The NW-SE and ENE-WSW lineaments appear to have formed during the phase of NW-SE folding. The NE-SW lineaments may be the result of the cross-folding of the earlier folds. The NNW-SSE lineaments have been related to the Precambrian tectonic activity in South India.