Using raw regional climate model outputs for quantifying climate change impacts on hydrology

General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.     

Quantifying the impact of landscape changes on hydrological variables in the alpine and cold region using hydrological model and remote sensing data

Quantifying the impact of landscape on hydrological variables is essential for the sustainable development of water resources. Understanding how landscape changes influence hydrological variables will greatly enhance the understanding of hydrological processes. Important vegetation parameters are considered in this study by using remote sensing data and VIC-CAS model to analyse the impact of landscape changes on hydrology in upper reaches of the Shule River Basin (URSLB). The results show there are differences in the runoff generation of landscape both in space and time. With increasing altitude, the runoff yields increased, with approximately 79.9% of the total runoff generated in the high mountains (4200–5900 m), and mainly consumed in the mid-low mountain region. Glacier landscape produced the largest runoff yields (24.9% of the total runoff), followed by low-coverage grassland (LG; 22.5%), alpine cold desert (AL; 19.6%), mid-coverage grassland (MG; 15.6%), bare land (12.5%), high-coverage grassland (HG; 4.5%) and shrubbery (0.4%). The relative capacity of runoff generation by landscapes, from high to low, was the glaciers, AL, LG, HG, MG, shrubbery and bare land. Furthermore, changes in landscapes cause hydrological variables changes, including evapotranspiration, runoff and baseflow. The study revealed that HG, MG, and bare land have a positive impact on evapotranspiration and a negative impact on runoff and baseflow, whereas AL and LG have a positive impact on runoff and baseflow and a negative impact on evapotranspiration. In contrast, glaciers have a positive impact on runoff. After the simulation in four vegetation scenarios, we concluded that the runoff regulation ability of grassland is greater than that of bare land. The grassland landscape is essential since it reduced the flood peak and conserved the soil and water.     

Evaluation of NLDAS‐2 evapotranspiration against tower flux site observations

The North American Land Data Assimilation System project phase 2 (NLDAS‐2) has run four land surface models for a 30‐year (1979–2008) retrospective period. Land surface evapotranspiration (ET) is one of the most important model outputs from NLDAS‐2 for investigating land–atmosphere interaction or to monitor agricultural drought. Here, we evaluate hourly ET using in situ observations over the Southern Great Plains (Atmospheric Radiation Measurement/Cloud and Radiation Testbed network) for 1 January 1997–30 September 1999 and daily ET u‐sing in situ observations at the AmeriFlux network over the conterminous USA for an 8‐year period (2000–2007). The NLDAS‐2 models compare well against observations, with the National Centers for Environmental Prediction's Noah land surface model performing best, followed, in order, by the Variable Infiltration Capacity, Sacramento Soil Moisture Accounting, and Mosaic models. Daily evaluation across the AmeriFlux network shows that for all models, performance depends on season and vegetation type; they do better in spring and fall than in winter or summer and better for deciduous broadleaf forest and grasslands than for croplands or evergreen needleleaf forest. Copyright © 2014 John Wiley & Sons, Ltd.     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.     

Balancing trade‐off issues in land use change and the impact on streamflow and salinity management

The south‐west region of the Goulburn–Broken catchment in the south‐eastern Murray–Darling Basin in Australia faces a range of natural resource challenges. A balanced strategy is required to achieve the contrasting objectives of remediation of land salinization and reducing salt export, while maintaining water supply security to satisfy human consumption and support ecosystems. This study linked the Catchment Analysis Tool (CAT), comprising a suite of farming system models, to the catchment‐scale CATNode hydrological model to investigate the effects of land use change and climate variation on catchment streamflow and salt export. The modelling explored and contrasted the impacts of a series of different revegetation and climate scenarios. The results indicated that targeted revegetation to only satisfy biodiversity outcomes within a catchment is unlikely to have much greater impact on streamflow and salt load in comparison with simple random plantings. Additionally, the results also indicated that revegetation to achieve salt export reduction can effectively reduce salt export while having a disproportionately smaller affect on streamflows. Furthermore, streamflow declines can be minimized by targeting revegetation activities without significantly altering salt export. The study also found that climate change scenarios will have an equal if not more significant impact on these issues over the next 70 years. Uncertainty in CATNode streamflow predictions was investigated because of the effect of parameter uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.     

Prediction of the South China Sea Dipole Using SSA-MEM

ABSTRACT

A dipole structure appears in the sea surface height off the central coast of Vietnam during boreal summer in the South China Sea. This dipole, which possesses a chlorophyll signature associated with higher phytoplankton concentrations arising from nutrient upwelling, is important for the productivity of local fisheries. Multi-satellite sea level anomalies are used to investigate the life cycle of the dipole structure. By applying empirical orthogonal function (EOF) analysis, the third EOF mode (EOF 3) is found to represent the major variations of the dipole structure. By removing the temporal noise of EOF 3, a South China Sea dipole index is defined. This index captures the life cycle of the dipole including its generation, mature strength, and final termination. Both one-dimensional and two-dimensional forecasts are generated using a statistical forecasting method that combines singular-spectrum analysis and the maximum entropy method. The appearance of the dipole structure can be predicted with an accuracy of 78% at one-month lead times and an accuracy of 61% at one-year lead times.     

Root‐zone moisture replenishment in a native vegetated catchment under Mediterranean climate

The root‐zone moisture replenishment mechanisms are key unknowns required to understand soil hydrological processes and water sources used by plants. Temporal patterns of root‐zone moisture replenishment reflect wetting events that contribute to plant growth and survival and to catchment water yield. In this study, stable oxygen and hydrogen isotopes of twigs and throughfall were continuously monitored to characterize the seasonal variations of the root‐zone moisture replenishment in a native vegetated catchment under Mediterranean climate in South Australia. The two studied hillslopes (the north‐facing slope [NFS] and the south‐facing slope [SFS]) had different environmental conditions with opposite aspects. The twig and throughfall samples were collected every ~20 days over 1 year on both hillslopes. The root‐zone moisture replenishment, defined as percentage of newly replenished root‐zone moisture as a complement to antecedent moisture for plant use, calculated by an isotope balance model, was about zero (±25% for the NFS and ± 15% for the SFS) at the end of the wet season (October), increased to almost 100% (±26% for the NFS and ± 29% for the SFS) after the dry season (April and May), then decreased close to zero (±24% for the NFS and ± 28% for the SFS) in the middle of the following wet season (August). This seasonal pattern of root‐zone moisture replenishment suggests that the very first rainfall events of the wet season were significant for soil moisture replenishment and supported the plants over wet and subsequent dry seasons, and that NFS completed replenishment over a longer time than SFS in the wet season and depleted the root zone moisture quicker in the dry season. The stable oxygen isotope composition of the intraevent samples and twigs further confirms that rain water in the late wet season contributed little to root‐zone moisture. This study highlights the significant role of the very first rain events in the early wet season for ecosystem and provides insights to understanding ecohydrological separation, catchment water yield, and vegetation response to climate changes.     

Carboniferous eclogite and garnet–omphacite granulite from northeastern Hainan Island,South China: Implications for the evolution of the eastern Palaeo‐Tethys

High‐P (HP) eclogite and associated garnet–omphacite granulite have recently been discovered in the Mulantou area, northeastern Hainan Island, South China. These rocks consist mainly of garnet, omphacite, hornblende, quartz and rutile/ilmenite, with or without zoisite and plagioclase. Textural relationships, mineral compositions and thermobarometric calculations demonstrate that the eclogite and garnet–omphacite granulite share the same three‐stage metamorphic evolution, with prograde, peak and retrograde P?T conditions of 620–680°C and 8.7–11.1 kbar, 820–860°C and 17.0–18.2 kbar, and 700–730°C and 7.1–8.5 kbar respectively. Sensitive high‐resolution ion microprobe U–Pb zircon dating, coupled with the identification of mineral inclusions in zircon, reveals the formation of mafic protoliths before 355 Ma, prograde metamorphism at c. 340–330 Ma, peak to retrograde metamorphism at c. 310–300 Ma, and subsequent pegmatite intrusion at 295 Ma. Trace element geochemistry shows that most of the rocks have a MORB affinity, with initial ε_Nd values of +2.4 to +6.7. As with similar transitional eclogite–HP granulite facies rocks in the thickened root in the European Variscan orogen, the occurrence of relatively high P?T metamorphic rocks of oceanic origin in northeastern Hainan Island suggests Carboniferous oceanic subduction leading to collision of the Hainan continental block, or at least part of it, with the South China Block in the eastern Palaeo‐Tethyan tectonic domain.