Winter rainfall interception by two mature open‐grown trees in Davis,California

A rainfall interception measuring system was developed and tested for open‐grown trees. The system includes direct measurements of gross precipitation, throughfall and stemflow, as well as continuous collection of micrometeorological data. The data were sampled every second and collected at 30‐s time steps using pressure transducers monitoring water depth in collection containers coupled to Campbell CR10 dataloggers. The system was tested on a 9‐year‐old broadleaf deciduous tree (pear, Pyrus calleryana ‘Bradford’) and an 8‐year‐old broadleaf evergreen tree (cork oak, Quercus suber) representing trees having divergent canopy distributions of foliage and stems. Partitioning of gross precipitation into throughfall, stemflow and canopy interception is presented for these two mature open‐grown trees during the 1996–1998 rainy seasons. Interception losses accounted for about 15% of gross precipitation for the pear tree and 27% for the oak tree. The fraction of gross precipitation reaching the ground included 8% by stemflow and 77% by throughfall for the pear tree, as compared with 15% and 58%, respectively, for the oak tree. The analysis of temporal patterns in interception indicates that it was greatest at the beginning of each rainfall event. Rainfall frequency is more significant than rainfall rate and duration in determining interception losses. Both stemflow and throughfall varied with rainfall intensity and wind speed. Increasing precipitation rates and wind speed increased stemflow but reduced throughfall. Analysis of rainfall interception processes at different time‐scales indicates that canopy interception varied from 100% at the beginning of the rain event to about 3% at the maximum rain intensity for the oak tree. These values reflected the canopy surface water storage changes during the rain event. The winter domain precipitation at our study site in the Central Valley of California limited our opportunities to collect interception data during non‐winter seasons. This precipitation pattern makes the results more specific to the Mediterranean climate region. Copyright © 2000 John Wiley & Sons, Ltd.     

Seasonal evaluation of rainfall estimation by four cumulus parameterization schemes and their sensitivity analysis

Sustainable water resources management require scientifically sound information on precipitation, as it plays a key role in hydrological responses in a catchment. In recent years, mesoscale weather models in conjunction with hydrological models have gained great attention as they can provide high‐resolution downscaled weather variables. Many cumulus parameterization schemes (CPSs) have been developed and incorporated into three‐dimensional Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) mesoscale model 5 (MM5). This study has performed a comprehensive evaluation of four CPSs (the Anthes–Kuo, Grell, Betts–Miller and Kain–Fritsch93 schemes) to identify how their inclusion influences the mesoscale model's precipitation estimation capabilities. The study has also compared these four CPSs in terms of variability in rainfall estimation at various horizontal and vertical levels. For this purpose, the MM5 was nested down to resolution of 81 km for Domain 1 (domain span 21 × 81 km) and 3 km for Domain 4 (domain span 16 × 3 km), respectively, with vertical resolutions at 23, 40 and 53 vertical levels. The study was carried out at the Brue catchment in Southwest England using both the ERA‐40 reanalysis data and the land‐based observation data. The performances of four CPs were evaluated in terms of their ability to simulate the amount of cumulative rainfall in 4 months in 1995 representing the four seasonal months, namely, January (winter), March (spring), July (summer) and October (autumn). It is observed that the Anthes–Kuo scheme has produced inferior precipitation values during spring and autumn seasons while simulations during winter and summer were consistently good. The Betts–Miller scheme has produced some reasonable results, particularly at the small‐scale domain (3 km grid size) during winter and summer. The KF2 scheme was the best scheme for the larger‐scale (81 km grid size) domain during winter season at both 23 and 53 vertical levels. This scheme tended to underestimate rainfall for other seasons including the small‐scale domain (3 km grid size) in the mesoscale. The Grell scheme was the best scheme in simulating rainfall rates, and was found to be superior to other three schemes with consistently better results in all four seasons and in different domain scales. Copyright © 2011 John Wiley & Sons, Ltd.     

A hybrid stochastic-weather-generation method for temporal disaggregation of precipitation with consideration of seasonality and within-month variations

Linking atmospheric and hydrological models is challenging because of a mismatch of spatial and temporal resolutions in which the models operate: dynamic hydrological models need input at relatively fine temporal (daily) scale, but the outputs from general circulation models are usually not realistic at the same scale, even though fine scale outputs are available. Temporal dimension downscaling methods called disaggregation are designed to produce finer temporal-scale data from reliable larger temporal-scale data. Here, we investigate a hybrid stochastic weather-generation method to simulate a high-frequency (daily) precipitation sequence based on lower frequency (monthly) amounts. To deal with many small precipitation amounts and capture large amounts, we divide the precipitation amounts on rainy days (with non-zero precipitation amounts) into two states (named moist and wet states, respectively) by a pre-defined threshold and propose a multi-state Markov chain model for the occurrences of different states (also including non-rain days called dry state). The truncated Gamma and censored extended Burr XII distributions are then employed to model the precipitation amounts in the moist and wet states, respectively. This approach avoids the need to deal with discontinuity in the distribution, and ensures that the states (dry, moist and wet) and corresponding amounts in rainy days are well matched. The method also considers seasonality by constructing individual models for different months, and monthly variation by incorporating the low-frequency amounts as a model predictor. The proposed method is compared with existing models using typical catchment data in Australia with different climate conditions (non-seasonal rainfall, summer rainfall and winter rainfall patterns) and demonstrates better performances under several evaluation criteria which are important in hydrological studies.     

Seasonal and spatial variations in the scaling and correlation structure of streamflow data

Seasonal and spatial variability in scaling, correlation and wavelet variance parameter of daily streamflow data were investigated using 56 gauging stations from five basins located in two different climate zones. Multifractal temporal scaling properties were detected using a multiplicative cascade model. The wavelet variance parameter yielded persistence properties of the streamflow time series. Seasonal variations were found to be significant in that winter and spring seasons where large‐scale frontal events are dominant showed higher long‐term correlations and less multifractality than did summer and fall seasons. Coherent spatial variations were apparent. The Neches River basin located in a subtropic humid climate zone exhibited high persistence and long‐term correlation as well as less multifractality as compared with other basins. It is found that larger drainage areas tend to have smaller multifractality and higher persistence structure, and this tendency becomes apparent in regions that receive large amounts of precipitation and decreases towards arid regions. Copyright © 2012 John Wiley & Sons, Ltd.     

Relations between rainfall–runoff‐induced erosion and aeolian deposition at archaeological sites in a semi‐arid dam‐controlled river corridor

Process dynamics in fluvial‐based dryland environments are highly complex with fluvial, aeolian, and alluvial processes all contributing to landscape change. When anthropogenic activities such as dam‐building affect fluvial processes, the complexity in local response can be further increased by flood‐ and sediment‐limiting flows. Understanding these complexities is key to predicting landscape behavior in drylands and has important scientific and management implications, including for studies related to paleoclimatology, landscape ecology evolution, and archaeological site context and preservation. Here we use multi‐temporal LiDAR surveys, local weather data, and geomorphological observations to identify trends in site change throughout the 446‐km‐long semi‐arid Colorado River corridor in Grand Canyon, Arizona, USA, where archaeological site degradation related to the effects of upstream dam operation is a concern. Using several site case studies, we show the range of landscape responses that might be expected from concomitant occurrence of dam‐controlled fluvial sand bar deposition, aeolian sand transport, and rainfall‐induced erosion. Empirical rainfall‐erosion threshold analyses coupled with a numerical rainfall–runoff–soil erosion model indicate that infiltration‐excess overland flow and gullying govern large‐scale (centimeter‐ to decimeter‐scale) landscape changes, but that aeolian deposition can in some cases mitigate gully erosion. Whereas threshold analyses identify the normalized rainfall intensity (defined as the ratio of rainfall intensity to hydraulic conductivity) as the primary factor governing hydrologic‐driven erosion, assessment of false positives and false negatives in the dataset highlight topographic slope as the next most important parameter governing site response. Analysis of 4+ years of high resolution (four‐minute) weather data and 75+ years of low resolution (daily) climate records indicates that dryland erosion is dependent on short‐term, storm‐driven rainfall intensity rather than cumulative rainfall, and that erosion can occur outside of wet seasons and even wet years. These results can apply to other similar semi‐arid landscapes where process complexity may not be fully understood. Published 2015. This article is a U.S. Government work and is in the public domain in the USA     

A new magnitude category disaggregation approach for temporal high‐resolution rainfall intensities

Simulation of quick runoff components such as surface runoff and associated soil erosion requires temporal high‐resolution rainfall intensities. However, these data are often not available because such measurements are costly and time consuming. Current rainfall disaggregation methods have shortcomings, especially in generating the distribution of storm events. The objectives of this study were to improve point rainfall disaggregation using a new magnitude category rainfall disaggregation approach. The procedure is introduced using a coupled disaggregation approach (Hyetos and cascade) for multisite rainfall disaggregation. The new procedure was tested with ten long‐term precipitation data sets of central Germany using summer and winter precipitation to determine seasonal variability. Results showed that dividing the rainfall amount into four daily rainfall magnitude categories (1–10, 11–25, 26–50, >50 mm) improves the simulation of high rainfall intensity (convective rainfall). The Hyetos model category approach (Hyetos_Cat) with seasonal variation performs representative to observed hourly rainfall compared with without categories on each month. The mean absolute percentage accuracy of standard deviation for hourly rainfall is 89.7% in winter and 95.6% in summer. The proposed magnitude category method applied with the coupled Hyetos_Cat–cascade approach reproduces successfully the statistical behaviour of local 10‐min rainfall intensities in terms of intermittency as well as variability. The root mean square error performance statistics for disaggregated 10‐min rainfall depth ranges from 0.20 to 2.38 mm for summer and from 0.12 to 2.82 mm for the winter season in all categories. The coupled stochastic approach preserves the statistical self‐similarity and intermittency at each magnitude category with a relatively low computational burden. Copyright © 2014 John Wiley & Sons, Ltd.     

Particle‐size evidence of barrier estuary regime as a new proxy for ENSO climate variability

We investigate a new proxy for ENSO climate variability based on particle‐size data from long‐term, coastal sediment records preserved in a barrier estuary setting. Corresponding ~4–8 year periodicities identified from Wavelet analysis of particle‐size data from Pescadero Marsh in Central Coast California and rainfall data from San Francisco reflect established ENSO periodicity, as further evidenced in the Multivariate ENSO Index (MEI), and thus confirms an important ENSO control on both precipitation and barrier regime variability. Despite the fact that barrier estuary mean particle size is influenced by coastal erosion, precipitation and streamflow, balanced against barrier morphology and volume, it is encouraging that considerable correspondence can also be observed in the time series of MEI, regional rainfall and site‐based mean particle size over the period 1871–2008. This correspondence is, however, weakened after c.1970 by temporal variation in sedimentation rate and event‐based deposition. These confounding effects are more likely when: (i) accommodation space may be a limiting factor; and (ii) particularly strong El Niños, e.g. 1982/1983 and 1997/1998, deposit discrete >cm‐thick units during winter storms. The efficacy of the sediment record of climate variability appears not to be compromised by location within the back‐barrier setting, but it is limited to those El Niños that lead to barrier breakdown. For wider application of this particle size index of ENSO variability, it is important to establish a well‐resolved chronology and to sample the record at the appropriate interval to characterize deposition at a sub‐annual scale. Further, the sample site must be selected to limit the influence of decreasing accommodation space through time (infilling) and event‐based deposition. It is concluded that particle‐size data from back‐barrier sediment records have proven potential for preserving evidence of sub‐decadal climate variability, allowing researchers to explore temporal and spatial patterns in phenomena such as ENSO. Copyright © 2017 John Wiley & Sons, Ltd.     

Effects of temporal scales and space mismatches on the TRMM 3B42 v7 precipitation product in a remote mountainous area

The accurate measurement of precipitation is essential to understanding regional hydrological processes and hydrological cycling. Quantification of precipitation over remote regions such as the Tibetan Plateau is highly unreliable because of the scarcity of rain gauges. The objective of this study is to evaluate the performance of the satellite precipitation product of tropical rainfall measuring mission (TRMM) 3B42 v7 at daily, weekly, monthly, and seasonal scales. Comparison between TRMM grid precipitation and point‐based rain gauge precipitation was conducted using nearest neighbour and bilinear weighted interpolation methods. The results showed that the TRMM product could not capture daily precipitation well due to some rainfall events being missed at short time scales but provided reasonably good precipitation data at weekly, monthly, and seasonal scales. TRMM tended to underestimate the precipitation of small rainfall events (less than 1 mm/day), while it overestimated the precipitation of large rainfall events (greater than 20 mm/day). Consequently, TRMM showed better performance in the summer monsoon season than in the winter season. Through comparison, it was also found that the bilinear weighted interpolation method performs better than the nearest neighbour method in TRMM precipitation extraction.     

Spatial distribution and temporal trends of mean precipitation and extremes in the arid region,northwest of China,during 1960–2010

On the basis of daily precipitation records at 76 meteorological stations in the arid region, northwest of China, the spatial and temporal distribution of mean precipitation and extremes were analysed during 1960–2010. The Mann–Kendall trend test and linear least square method were utilized to detect monotonic trends and magnitudes in annual and seasonal mean precipitation and extremes. The results obtained indicate that both the mean precipitation and the extremes have increased except in consecutive dry days, which showed the opposite trend. The changes in amplitude of both mean precipitation and extremes show seasonal variability. On an annual basis, the number of rain days (R0.1) has significantly increased. Meanwhile, the precipitation intensity as reflected by simple daily intensity index (SDII), number of heavy precipitation days (R10), very wet days (R95p), max 1‐day precipitation amount (RX1day) and max 5‐day precipitation amount (RX5day) has also significantly increased. This suggests that the precipitation increase in the arid region is due to the increase in both precipitation frequency and intensity. Trends in extremes are very highly correlated with mean trends of precipitation. The spatial correlation between trends in extremes and trends in the mean is stronger for winter (DJF) than for annual and other seasons. The regional annual and seasonal precipitation and extremes are observed the step jump in mean in the late 1980s. Overall, the results of this study are good indicators of local climate change, which will definitely enhance human mitigation to natural hazards caused by precipitation extremes. Copyright © 2012 John Wiley & Sons, Ltd.     

Use of the Connectivity of Runoff Model (CRUM) to investigate the influence of storm characteristics on runoff generation and connectivity in semi‐arid areas

Much attention has been given to the surface controls on the generation and transmission of runoff in semi‐arid areas. However, the surface controls form only one part of the system; hence, it is important to consider the effect that the characteristics of the storm event have on the generation of runoff and the transmission of flow across the slope. The impact of storm characteristics has been investigated using the Connectivity of Runoff Model (CRUM). This is a distributed, dynamic hydrology model that considers the hydrological processes relevant to semi‐arid environments at the temporal scale of a single storm event. The key storm characteristics that have been investigated are the storm duration, rainfall intensity, rainfall variability and temporal structure. This has been achieved through the use of a series of defined storm hydrographs and stochastic rainfall. Results show that the temporal fragmentation of high‐intensity rainfall is important for determining the travel distances of overland flow and, hence, the amount of runoff that leaves the slope as discharge. If the high‐intensity rainfall is fragmented, then the runoff infiltrates a short distance downslope. Longer periods of high‐intensity rainfall allow the runoff to travel further and, hence, become discharge. Therefore, storms with similar amounts of high‐intensity rainfall can produce very different amounts of discharge depending on the storm characteristics. The response of the hydrological system to changes in the rainfall characteristics can be explained using a four‐stage model of the runoff generation process. These stages are: (1) all water infiltrating, (2) the surface depression store filling or emptying without runoff occurring, (3) the generation and transmission of runoff and (4) the transmission of runoff without new runoff being generated. The storm event will move the system between the four stages and the nature of the rainfall required to move between the stages is determined by the surface characteristics. This research shows the importance of the variable‐intensity rainfall when modelling semi‐arid runoff generation. The amount of discharge may be greater or less than the amount that would have been produced if constant rainfall intensity is used in the model. Copyright © 2006 John Wiley & Sons, Ltd.     

The relationship between rainfall inputs and flood generation in south–east Spain

Rainfall and flood data are relatively sparse in semi‐arid areas; hence there have been relatively few investigations into the relationships between rainfall inputs and flood generation in these environments. Previous work has shown that flood properties are influenced by a combination of precipitation characteristics including amount, intensity, duration and spatial distribution. Therefore floods may be produced by high intensity, short duration storms, or longer duration, low intensity rainfall. Most of this research has been undertaken in small catchments in either hyper‐arid or relatively high rainfall Mediterranean climates. This paper presents results from a 6 year data record in south‐east Spain from research conducted in two basins, the Rambla Nogalte (171 km²) and the Rambla de Torrealvilla (200 km²). Data cover an area of approximately 500 km² and an annual average rainfall of 300 mm. At coarse temporal resolutions gauges spread over large areas record similar patterns of rainfall, although spells of rain show much more complexity; pulses of rain within storms can vary considerably in total rainfall, intensity and duration over the same area. The analysis for south‐east Spain shows that most storms occur over a period of less than 24 h, but that the number of rainfall events declines as the duration exceeds 8 h. This is at odds with data on floods for the study area suggesting that they are produced by storms lasting longer than 18 h. However, one flood event was produced by a very short (15 min) storm with high intensity rainfall. Most floods tended to occur in May/June or September, which coincides with wetter months of the year (September, October, December and May). Floods are also more highly related to the total rainfall occurring in a spell of rain, than to intensity. The complexity of storm rainfall increases with the storm total, which makes it difficult to generalize on the importance of rainfall intensity for flood generation. Copyright © 2007 John Wiley & Sons, Ltd.     

Spatial and temporal characteristics of droughts in the western part of Bangladesh

Spatial and temporal characteristics of droughts in the western part of Bangladesh have been analysed. Standardized precipitation index method is used to compute the severity of droughts from the rainfall data recorded in 12 rainfall gauge stations for the period of 1961–1999. An artificial neural network is used to estimate missing rainfall data. Geographic Information System (GIS) is used to map the spatial extent of droughts of different severities in multiple time scales. Critical analysis of rainfall is also carried to find the minimum monsoon and dry months rainfall require in different parts of the study area to avoid rainfall deficit. The study shows that the north and north‐western parts of Bangladesh are most vulnerable to droughts. A significant negative relationship between multiple ENSO index and rainfall is observed in some stations. Analysis of seasonal rainfall distribution, rainfall reliability and long‐term rainfall trend is also conducted to aid prediction of future droughts in the area. Copyright © 2007 John Wiley & Sons, Ltd.     

Analysis and modelling of rainfall fields at different resolutions in southern Italy

Abstract

The spatial and temporal variability of the scaling properties and correlation structure of a data set of rainfall time series, aggregated over different temporal resolutions, and observed in 70 raingauges across the Basilicata and Calabria regions of southern Italy, is investigated. Two types of random cascade model, namely canonical and microcanonical models, were used for each raingauge and selected season. For both models, different hypotheses concerning dependency of parameters on time scale and rainfall height can be adopted. In particular, a new approach is proposed which consists of several combinations of models with a different scale dependence of parameters for different temporal resolutions. The goal is to improve the modelling of the main features of rainfall time series, especially for cases where the variability of rainfall changes irregularly with temporal aggregation. The results obtained with the new methodology showed good agreement with the observed data, in particular, for the summer months. In fact, during this season, rainfall heights aggregated at fine temporal resolutions (from 5 to 20 min) are more similar (relative to the winter season) to the values cumulated on 1 or 3 h (due to convective phenomena) and, consequently, the process of rainfall breakdown is nearly stationary for a range of finer temporal resolutions.

Editor D. Koutsoyiannis; Associate editor A. Montanari     

Soil detachment and transport on field‐ and laboratory‐scale interrill areas: erosion processes and the size‐selectivity of eroded sediment

Field‐ and laboratory‐scale rainfall simulation experiments were carried out in an investigation of the temporal variability of erosion processes on interrill areas, and the effects of such variation upon sediment size characteristics. Poorly aggregated sandy soils from the semi‐arid environment of Senegal, West Africa, were used on both a 40 m² field plot and a 0·25 m² laboratory plot; rainfall intensity for all experiments was 70 mm h^?1 with a duration of 1 to 2 hours. Time‐series measurements were made of the quantity and the size distribution of eroded material: these permitted an estimate of the changing temporal balance between the main erosion processes (splash and wash). Results from both spatial scales showed a similar temporal pattern of runoff generation and sediment concentration. For both spatial scales, the dominant erosional process was detachment by raindrops; this resulted in a dynamic evolution of the soil surface under raindrop impact, with the rapid formation of a sieving crust followed by an erosion crust. However, a clear difference was observed between the two scales regarding the size of particles detached by both splash and wash. While all measured values were lower than the mean weight diameter (MWD) value of the original soil (mean 0·32 mm), demonstrating the size‐selective nature of wash and splash processes, the MWD values of washed and splashed particles at the field scale ranged from 0·08 to 0·16 mm and from 0·12 to 0·30 mm respectively, whereas the MWD values of washed and splashed particles at the laboratory scale ranged from 0·13 to 0·29 mm and from 0·21 to 0·32 mm respectively. Thus only at the field scale were the soil particles detached by splash notably coarser than those transported by wash. This suggests a transport‐limited erosion process at the field scale. Differences were also observed between the dynamics of the soil loss by wash at the two scales, since results showed wider scatter in the field compared to the laboratory experiments. This scatter is probably related to the change in soil surface characteristics due to the size‐selectivity of the erosion processes at this spatial scale. Copyright © 2006 John Wiley & Sons, Ltd.     

Vegetation response to rainfall seasonality and interannual variability in tropical dry forests

Projected changes in rainfall seasonality and interannual variability are expected to have severe impacts on arid and semi‐arid tropical vegetation, which is characterized by a fine‐tuned adaptation to extreme rainfall seasonality. To study the response of these ecosystems and the related changes in hydrological processes to changes in the amount and seasonality of rainfall, we focused on the caatinga biome, the typical seasonally dry forest in semi‐arid Northeast Brazil. We selected four sites across a gradient of rainfall amount and seasonality and analysed daily rainfall and biweekly Normalized Difference Vegetation Index (NDVI) data for hydrological years 2000 to 2014. Rainfall seasonal and interannual statistics were characterized by recently proposed metrics describing duration, timing and intensity of the wet season and compared to similar metrics of NDVI time series. The results show that the caatinga tends to have a more stable response with longer and less variable growing seasons (3.1 ± 0.1 months) compared to the duration wet seasons (2.0 ± 0.5 months). The ecosystem ability to buffer the interannual variability of rainfall is also evidenced by the stability in the timing of the growing season compared to the wet season, which results in variable delays (ranging from 0 to 2 months) between the peak of the rainfall season and the production of leaves by the ecosystem. The analyses show that the shape and size of the related hysteresis loops in the rainfall–NDVI relations are linked to the buffering effects of soil moisture and plant growth dynamics. Finally, model projections of vegetation response to different rainfall scenarios reveal the existence of a maximum in ecosystem productivity at intermediate levels of rainfall seasonality, suggesting a possible trade‐off in the effects of intensity (i.e. amount) and duration of the wet season on vegetation growth and related soil moisture dynamics and transpiration rates. Copyright © 2016 John Wiley & Sons, Ltd.     

Vegetation response to rainfall intermittency in drylands: Results from a simple ecohydrological box model

Vegetation in arid and semi-arid regions is affected by intermittent water availability. We discuss a simple stochastic model describing the coupled dynamics of soil moisture and vegetation, and study the effects of rainfall intermittency. Soil moisture dynamics is described by a ecohydrological box model, while vegetation is represented by site occupancy dynamics in a spatially-implicit model. We show that temporal rainfall intermittency allows for vegetation persistence at low values of annual rainfall volume, whereas it would go extinct if rainfall were constant. Rainfall intermittency also generates long-term fluctuations in vegetation cover, even in the absence of significant inter-annual variations in the statistical properties of precipitation.     

Comparison of event‐specific rainfall–runoff responses and their controls in contrasting geographic areas

Numerous studies have examined the event‐specific hydrologic response of hillslopes and catchments to rainfall. Knowledge gaps, however, remain regarding the relative influence of different meteorological factors on hydrologic response, the predictability of hydrologic response from site characteristics, or even the best metrics to use to effectively capture the temporal variability of hydrologic response. This study aimed to address those knowledge gaps by focusing on 21 sites with contrasting climate, topography, geology, soil properties, and land cover. High‐frequency rainfall and discharge records were analysed, resulting in the delineation of over 1,600 rainfall–runoff events, which were described using a suite of hydrologic response metrics and meteorological factors. Univariate and multivariate statistical techniques were then applied to synthesize the information conveyed by the computed metrics and factors, notably measures of central tendency and variability, variation partitioning, partial correlations, and principal component analysis. Results showed that some response magnitude metrics generally reported in the literature (e.g., runoff ratio and area‐normalized peak discharge) did not vary significantly among sites. The temporal variability in site‐specific hydrologic response was often attributable to the joint influence of storage‐driven (e.g., total event rainfall and antecedent precipitation) and intensity‐driven (e.g., rainfall intensity and antecedent potential evapotranspiration) meteorological factors. Mean annual temperature and potential evapotranspiration at a given site appeared to be good predictors of hydrologic response timing (e.g., response lag and lag to peak). Response timing metrics, particularly those associated with response initiation, were also identified as the metrics most critical for capturing intrasite response variability. This study therefore contributes to the growing knowledge on event‐specific hydrologic response by highlighting the importance of response timing metrics and intensity‐driven meteorological factors, which are infrequently discussed in the literature. As few correlations were found between physiographic variables and response metrics, more data‐driven studies are recommended to further our understanding of landscape–hydrology interactions.     

Spatial and temporal variability of annual and seasonal precipitation over the desert region of China during 1951–2005

The spatial and temporal variations of precipitation in the desert region of China (DRC) from 1951 to 2005 were investigated using a rotated empirical orthogonal function (REOF), the precipitation concentration index (PCI) and the Mann–Kendall trend test method (M‐K method). In addition, the association between variation patterns of precipitation and large‐scale circulation were also explored using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. The results indicated that the spatial pattern of precipitation was primarily the local climate effect significant type, with the first three EOFs explaining a total of 55·3% of the variance, and the large‐scale climate system effect type, which explained 9·8% of the variance. Prior to the 1970s, the East Asian summer monsoon was stronger, which resulted in abundant precipitation in the Inner Mongolia region. Conversely, the climate of the Xinjiang region was controlled by westerly circulation and had lower precipitation. However, this situation has been reversed since the 1980s. It is predicted that precipitation will decrease by 15–40 and 0–10 mm/year in the Inner Mongolia plateau and southern Xinjiang, respectively, whereas it will likely increase by 10–40 mm/year in northern Xinjiang. Additionally, 58–62% of the annual rainfall occurred during summer in the DRC, with precipitation increasing during spring and summer and decreasing in winter. The intra‐annual precipitation is becoming uniform, but the inter‐annual variability in precipitation has been increasing in the western portions of the DRC. The probability of precipitation during the study period increased by 30% and 22·2% in the extreme‐arid zones and arid zones, respectively. Conversely, the probability of precipitation during the study period decreased by 18·5% and 37·5% in the semi‐arid zones and semi‐wet zones, respectively. It is predicted that the northwest portion of the DRC will become warmer and wetter, while the central portion will become warmer and drier and the northeast portion will be subjected to drought. Copyright © 2010 John Wiley & Sons, Ltd.     

The implications of regional variations in rainfall for reconstructing rainfall patterns using tree rings

In Australia, multidecadal periods of floods and droughts have major economic consequences. Due to the short duration of Australian instrumental precipitation records, it is difficult to determine the patterns of these multidecadal periods. Proxy records can be used to create long‐term rainfall reconstructions for regions that are lacking instrumental data. However, the spatial extent over which single‐site proxy records can be applied is poorly understood. Southeast Queensland (SEQ) is an area where tree rings can be used to reconstruct long‐term rainfall patterns, but their regional representation is unknown. In this study, the spatial variability in rainfall across SEQ is investigated from 1908 to 2007 using 140 instrumental rainfall stations. Pearson correlation analysis between stations is used to create groups at the r = 0.80, 0.85, and 0.90 correlation levels, and then annual deviations from the mean are determined. These patterns indicate that rainfall is not uniform across SEQ but can be broken into 2 main spatially consistent groups. Each of these groups is broken down into several subgroups with higher correlation levels. Long‐term streamflow records are found to be correlated to rainfall patterns local to the streamflow stations, indicating that analysis of extreme events should consider spatial precipitation variability. Finally, the only currently available proxy rainfall reconstruction for the region, a 140‐year Toona ciliata tree ring width record from Lamington National Park, is compared to rainfall groups at different correlation levels across all of SEQ. The correlation between the reconstruction and the rainfall station groupings is best for the groups within which the tree‐ring record is spatially located, and this correlation improves as rainfall group correlation increases. Correlation is nearly nonexistent for groupings located at a distance from the tree‐ring site. These results demonstrate the importance of assessing the spatial variability of precipitation so that the spatial applicability of proxy records can be assessed.