Temporal Rainfall Patterns Research Articles

Temporal rainfall patterns with water partitioning impacts on maize yield in a freeze–thaw zone

Understanding all components of the water balance, especially temporal rainfall patterns, is essential to optimize water use in rain-fed agriculture area. The effect of temporal rainfall patterns on water balance, evapotranspiration (ET), and crop growth was evaluated by considering root water extraction of plants in a rain-fed maize field. Soil water contents at depths of 15, 30, 60, and 90 cm were measured daily in 2-year growth seasons. A soil water balance approach was applied to estimate changes in daily soil water storage. For the detailed water partitioning of the water balance and root water extraction, the soil–water-atmosphere-plant (SWAP) model with water and crop modules was applied. Results suggested that the main depths of root water uptake occurred in the top 60 cm soil layer. Crop transpiration (T) can reach a level above 40% of the total water consumption during all growth stages, and its reduction was mainly due to the dry condition of soil. The crop yield in 2010 was 1125 kg ha−1 higher than that in 2011, although the rainfall amount in that year was 132 mm less than the rainfall amount in 2011. The water use efficiency (WUE) was also higher in 2010. Therefore, the influence of temporal rainfall patterns was clearly more important than rainfall amounts (water partitioning into evaporation (E), T, and soil water content). Growing season T/ET can be a potential parameter for maize productivity. The field can be irrigated at pivotal growth stages under dry conditions to obtain the optimal effect in improving WUE and increasing grain yield. The SWAP model was a useful tool to analyze water partitioning in the freeze–thaw zone.

Temporal variation in the dispersion patterns of metazoan parasites of a coastal fish species from the Gulf of Mexico

Global climate change (GCC) is expected to affect key environmental variables such as temperature and rainfall, which in turn influence the infection dynamics of metazoan parasites in tropical aquatic hosts. Thus, our aim was to determine how temporal patterns of temperature and rainfall influence the mean abundance and aggregation of three parasite species of the fish Cichlasoma urophthalmus from Yucatán, México. We calculated mean abundance and the aggregation parameter of the negative binomial distribution k for the larval digeneans Oligogonotylus manteri and Ascocotyle (Phagicola) nana and the ectoparasite Argulus yucatanus monthly from April 2005 to December 2010. Fourier analysis of time series and cross-correlations were used to determine potential associations between mean abundance and k for the three parasite species with water temperature and rainfall. Both O. manteri and A. (Ph.) nana exhibited their highest frequency peaks in mean abundance at 6 and 12 months, respectively, while their peak in k occurred every 24 months. For A. yucatanus the frequency peaks in mean abundance and k occurred every 12 months. We suggest that the level of aggregation at 24 months of O. manteri increases the likelihood of fish mortality. Such a scenario is less likely for A. (Ph.) nana and A. yucatanus, due to their low infection levels. Our findings suggest that under the conditions of GCC it would be reasonable to expect higher levels of parasite aggregation in tropical aquatic hosts, in turn leading to a potential increase in parasite-induced host mortality.

Temporal precipitation estimation from nearby radar reflectivity using dynamic factor analysis in the mountainous watershed - a case during Typhoon Morakot

The radar reflectivity (Z)–rain intensity (R) relationship fluctuates in both temporal and spatial scales. The dynamic factor analysis (DFA) and min/max autocorrelation factor analysis (MAFA) was specifically designed for considering various space–time integrations of gauge rainfall and radar reflectivity. We detect representative radar reflectivity observed around rainfall stations that were most responsible for rainfall intensity and identify the crucial patterns of the radar reflectivity in the Kaoping River watershed during Typhoon Morakot. Result shows that the MAFA and DFA can reduce the uncertainty of the dynamic Z-R relationship effectively. The MAFA separates an entire area into two subareas (southern and northern areas) according to the relationships between the radar reflectivity and min/max autocorrelation factor (MAF) axes. For both areas, the different extents of temporal rainfall correlated with the radar reflectivity were determined using DFA. Especially in the northern area, the radar reflectivity was significantly related to the rainfall intensity for most stations without mountain blockage. Mountain blockages associated with the presence of terrain and wind direction were inferred the major factors that affected the relationship between radar reflectivity and rainfall intensity in the mountainous watershed. Further study can consider the terrain effect and meteorological information, such as wind speed and direction in the DFA model, with the dominant radar reflectivity to estimate the temporal rainfall patterns. Copyright © 2012 John Wiley & Sons, Ltd.

Development of Temporal Rainfall Pattern for Southern Region of Sarawak

In the process of a design rainfall, information on rainfall duration, average rainfall intensity and temporal rainfall pattern is important. This study focuses on developing a temporal rainfall pattern for the Southern region of Sarawak since temporal pattern for Sarawak is yet to be available in the Malaysian Urban Storm Water Management Manual (MSMA), which publishes temporal pattern for design storms only for Peninsular Malaysia. The recommended technique by the Australian Rainfall and Runoff (AR&R) known as the ‘Average Variability Method’ and method in Hydrological Procedure No.1-1982 are used to derive design rainfall temporal pattern for the study. Rainfall data of 5 minutes interval from year 1998 to year 2006 for 7 selected rainfall stations in the selected region is obtained from Department of Irrigation and Drainage (DID). The temporal rainfall patterns developed are for 10 minutes,15 minutes, 30 minutes, 60 minutes, 120 minutes, 180 minutes and 360 minutes duration. The results show that Southern region of Sarawak has an exclusive rainfall pattern, which is different from the pattern developed for Peninsular Malaysia.

Within-Storm Rainfall Distribution Effect on Soil Erosion Rate

This study investigates the effect of rainfall temporal distribution pattern within a storm event on soil erosion rate and the possibility of using rain power type model for rainfall erosivity. Various rainfall distribution patterns, simulated by rainfall simulator, were used on 1.0 m2 plot of silica sand and loam soil with a minimum of three replications. The results show that the soil erosion rates spiked following every sharp increase in rainfall intensity followed by a gradual decline to a steady erosion rate. Transient effects resulted in the soil erosion rates for an oscillatory rainfall distribution to be more than two fold higher than those obtained for a steady-state rainfall intensity event with same duration and same average rainfall intensity. The 3-parameter and 4-parameter rain power models were developed for a process-based measure of rainfall erosivity. The 4 parameter model yielded better match with the observed data and predicted soil erosion rates more accurately for silica sand under all rainfall distributions, and good results for loam soil under low intensity rainfall. More research is necessary to improve the accuracy of soil erosion prediction models for a wider range of rainfall distributions.

The influence of Indian Ocean sea surface temperature on the variability of monsoon rainfall over India

This study focuses on the spatial and temporal variability of southwest monsoon (SWM) and northeast monsoon (NEM) rainfall over India, after the 1976–1977 regime shift. Through wavelet analysis the dominant mode of variability in the SWM and NEM rainfall is found to be in the 2–8-year scale (ENSO band). Therefore, scale-averaged wavelet power (SAP) of SWM (SAPSWM) and NEM (SAPNEM) rainfall obtained from a high-resolution dataset for the period 1977–2001 was subjected to empirical orthogonal function analysis, in order to understand the homogenous regions of rainfall variability. As the study utilizes SAP, the decadal variability is observed in the spatial and temporal patterns of rainfall. The maximum variability of SAPSWM rainfall is found to be in the 2–4-year period, whereas, for the SAPNEM rainfall, the biennial mode explains the variability over the core region of NEM rainfall. Significant power is also observed in the 4-year period. The evolution of the principal components (PCs) is consistent with the above/below normal rainfall received over the region. Similar analysis has been carried out also for the SAP of monthly sea surface temperature (SAPSST) over Indian Ocean for the months from January to September. Compared with any other month, the decadal changes of the PCs of SAPSWM and SAPNEM rainfall are highly correlated with the decadal variations of PC1 of SAPSST for the month of March. Therefore, the relation between the rainfall and SST was explained using SAPSST for the month of March. Significant biennial power is also observed in March SST over southeast Indian Ocean (85–110°E and 5–40°S) after the climate shift of 1976. In order to identify any change in the relation between NEM rainfall and SAPSST (March) before and after 1976, a correlation between NEM rainfall and PC1 of SAPSST (March) was found for the period 1951–1975 and 1977–2001. Results show that correlation has increased after 1976. Therefore, this PC can be made use of in the prediction of NEM rainfall. Copyright © 2012 Royal Meteorological Society

Variation in monsoon precipitation drives spatial and temporal patterns of Larrea tridentata growth in the Sonoran Desert

Summary 1. Broad-scale patterns of above-ground net primary production (ANPP) are closely coupled to climate features, particularly the distribution and magnitude of rainfall. In arid and semi-arid regions, however, the precipitation regime, together with local geomorphology and plant life history traits, combine to regulate soil water availability and patterns of growth, complicating simple correlations with climatic variables. 2. To better understand the drivers of plant growth in desert ecosystems, we characterized the rates and spatial heterogeneity of stem elongation by the dominant perennial shrub, creosote bush (Larrea tridentata) in the northern Sonoran Desert of Arizona (USA). Estimates of stem growth were made over a 5-year period (2006–2010) from 60 plots at 15 sites spanning c. 120 km across the Central Arizona–Phoenix (CAP) Long-term Ecological Research (LTER) area. 3. We observed both the highest and lowest rates of stem growth during summer, and these patterns were related to the amount of monsoon rainfall and local rates of water infiltration. The relationship between growth and precipitation in the summer was nonlinear, with rates increasing more than eightfold at plots receiving more than 100 mm of seasonal rainfall. Conversely, growth during the winter/spring was intermediate in magnitude, similar among years and poorly correlated with seasonal precipitation. 4. The spatial heterogeneity of stem growth also differed markedly between seasons and was greater both within and among sites during summer compared to winter/spring growing periods. At broad scales, spatial heterogeneity of shrub growth was correlated with seasonal changes in the spatial variability of rainfall across the study area. At small spatial scales, greater heterogeneity during the summer appears linked to local soil properties that influence infiltration and water availability following monsoon storms. 5. Overall, the strong, nonlinear growth response by L. tridentata to monsoon rainfall suggests that the recurrence interval of wet summer seasons is an important driver of ANPP for this long-lived shrub. More generally, our results illustrate how regional climate variability and local soil properties can interact to influence the rates and heterogeneity of desert plant growth at multiple scales.

Dynamics of evapotranspiration partitioning in a semi-arid forest as affected by temporal rainfall patterns

We extend our recent study of the effects of tree density on evapotranspiration (ET) partitioning in a semi-arid pine forest by examining the influence of the temporal patterns in rainfall (P) on the dynamic contributions of tree transpiration (Tt), soil evaporation (Es) and rainfall interception (IP) to total ET. Soil evaporation accounted for 39% of average annual ET over the four-year period, and was associated with soil moisture content in the upper 5cm and solar radiation, therefore peaking during the wetting and drying seasons (up to 0.75mmday−1). In the dry summer, Es diminished and as much as 50% of the residual flux was due to re-evaporation of moisture condensed at night (adsorption). Tree transpiration accounted for 49% of average annual ET, and was associated with soil moisture at a depth of 10–20cm. Transpiration peaked only in late spring (1.5mmday−1), after the accumulation of large storms allowing infiltration below the topsoil. Moisture at these depths was maintained for longer periods and was even carried over between rain seasons following a high precipitation year. Interception was 12% of annual ET but was larger than 20% during the rainy period. The results indicated that both Tt/ET and Es/ET could vary between 30% and 60% due to their differential response to seasonal environmental drivers. Annual Tt/ET, a major parameter indicating forest productivity and survival, was more influenced by the occurrence of large storms (>30mm; P30/P ratio) than by P itself. In an assessment of the potential warming and drying trends predicted for the Mediterranean region in the next century, changes in both total precipitation and in its temporal patterns must be considered.

Design Rainfall Temporal Patterns in Australian Rainfall And Runoff: Durations Exceeding One Hour

The current edition of Australian Rainfall and Runoff espouses the design event approach in which a single food is the “event” with which the hydraulic structure is expected to cope during its working life. The uniform rainfall of the selected average recurrence interval requires a temporal pattern before input to a catchment model. Australian Rainfall and Runoff provides temporal patterns for each of eight def ned zones, with 20 specific durations and two classes of average recurrence interval. These patterns are inconvenient to use, especially for other than specif ed storm durations, and at zone boundaries when differently-shaped patterns apply. This paper shows that distinctions between zones and average recurrence intervals are not signif cant. Only two of the 144 temporal patterns for durations 1.5 to 24 h are significant in food design practice, and these are replaced with continuous equations that allow design storm durations to be divided into any number of increments.

Design rainfall temporal patterns in Australian Rainfall and Runoff: Durations exceeding one hour

AbstractThe current edition of Australian Rainfall and Runoff espouses the design event approach in which a single food is the “event” with which the hydraulic structure is expected to cope during its working life. The uniform rainfall of the selected average recurrence interval requires a temporal pattern before input to a catchment model. Australian Rainfall and Runoff provides temporal patterns for each of eight def ned zones, with 20 specific durations and two classes of average recurrence interval. These patterns are inconvenient to use, especially for other than specif ed storm durations, and at zone boundaries when differently-shaped patterns apply. This paper shows that distinctions between zones and average recurrence intervals are not signif cant. Only two of the 144 temporal patterns for durations 1.5 to 24 h are significant in food design practice, and these are replaced with continuous equations that allow design storm durations to be divided into any number of increments.

댐 설계홍수량 산정방법에 관한 비교연구

본 연구에서는 국내의 다목적 댐을 대상으로 강우-유출 모형에 의한 과거의 홍수량 산정방식과 최근의 홍수량 산정방식을 유역 면적 규모별로 분류하여 비교 분석하였다. 홍수량에 영향을 미치는 기본인자로 강우량, 강우의 시간분포, 유효우량 산정방법, 강우-유출 모형, 매개변수 추정 및 기저유량 등을 선정하여 각 인자별 민감도 분석을 수행함으로써 홍수량에 미치는 영향을 정량적으로 분석하였다. 분석결과 최근의 방법으로 산정한 홍수량과 과거의 방법으로 산정한 홍수량이 유역면적 규모에 따라 다양한 변동폭으로 증가하거나 감소하였는데, 강우의 시간분포 변경이 홍수량을 감소시키는 원인으로 분석되었고, 최근 기상이변에 의한 강우량의 증가와 단위도의 매개변수 추정방법의 변경이 홍수량을 증가시키는 가장 큰 원인으로 분석되었다. In this study, past method and recent method for flood discharge with domestic multi-purpose dams in Korea were compared and analyzed with respect to the scale of watershed. Rainfall depth, temporal pattern, rainfall excess, rainfall-runoff model, parameter estimation and base flow were selected as the principal factors affecting flood discharge and effects on flood discharge were analyzed quantitatively by using sensitivity analysis. The results showed that the flood discharges calculated by past and recent method increased and decreased with a wide range of discharge with respect to the scale of watershed. The reason for decrease of flood discharge is the exchange of temporal pattern of rainfall and the principal reasons for increase of flood discharge are the increase of rainfall depth by unusual weather phenomena and the difference of estimation method for parameters of unit hydrograph.

Rainfall Regime of a Mountainous Mediterranean Region: Statistical Analysis at Short Time Steps

AbstractThis paper presents an analysis of the rainfall regime of a Mediterranean mountainous region of southeastern France. The rainfall regime is studied on temporal scales from hourly to yearly using daily and hourly rain gauge data of 43 and 16 years, respectively. The domain is 200 × 200 km2 with spatial resolution of hourly and daily rain gauges of about 8 and 5 km, respectively. On average, yearly rainfall increases from about 0.5 m yr−1 in the large river plain close to the Mediterranean Sea to up to 2 m yr−1 over the surrounding mountain ridges. The seasonal distribution is also uneven: one-third of the cumulative rainfall occurs during the autumn season and one-fourth during the spring. At finer time scales, rainfall is studied in terms of rain–no-rain intermittency and nonzero intensity. The monthly intermittency (proportion of dry days per month) and the daily intermittency (proportion of dry hours per day) is fairly well correlated with the relief. The higher the rain gauges are, the lower the monthly and daily intermittencies are. The hourly and daily rainfall intensities are analyzed in terms of seasonal variability, diurnal cycle, and spatial pattern. The difference between regular and heavy-rainfall event is depicted by using both central parameters and maximum values of intensity distributions. The relationship between rain gauge altitudes and rainfall intensity is grossly inverted relative to intermittency and is also far more complex. The spatial and temporal rainfall patterns depicted from rain gauge data are discussed in the light of known meteorological processes affecting the study region.

Spatial Analysis of Monthly and Annual Precipitation Trends in Turkey

Global climate change could have important effects on various environmental variables in many countries around the world. Changes in precipitation regime directly affect water resources management. So that, it is important to analyze the changes in the spatial and temporal rainfall pattern in order to improve water resources management policies. For this reason, non-parametric Mann-Kendall rank correlation test is used in order to examine the existence of trends in annual and monthly rainfall distribution. To understand the regional differences of precipitation in Turkey, the detected trends are spatially interpolated using geostatistical techniques in a GIS environment. The main objective of this paper is to evaluate three interpolation methods, concerning their suitability for spatial prediction of temporal trends of Turkey’s monthly and annual rainfall data. The study used a dense and homogeneous monthly precipitation database comprising 120 rain-gauge stations over a 32 years testing period of 1975–2009. The results conclusively show that significant positive trends are both infrequent and found only in outlying stations during March, April and October. In order to estimate and characterize the magnitude of observed changes at unmeasured locations, Ordinary Kriging, Inverse Distance Weighted and Completely Regularized Spline interpolation methods were employed and compared. A comparative analysis of interpolation techniques shows that Ordinary Kriging with having RMSE of 0.148 is the best choice. This is followed by Inverse Distance Weighted (RMSE 0.151), and Splines (RMSE 0.152). Cross validation of the results shows the largest over prediction at Kars rainfall station and largest under prediction at Burdur station. Upon for the examination of the cross-validation and spatial error clustering results, the Ordinary Kriging method was concluded to be the best algorithm in the interpolation process.

Gaussian-distribution-based hyetographs and their relationships with debris flow initiation

Summary Although sophisticated models for predicting spatial and temporal rainstorm patterns have been proposed in past decades, the temporal patterns of extreme rainstorm events are still unknown, and the performance of natural and man-made slopes and debris flow mitigation measures have never been assessed from the viewpoint of temporal rainfall patterns. To this end, three methods were used to simulate the hyetograph of an extreme rainstorm, namely, typhoon Morakot, which resulted in a maximum rainfall of 2884 mm in Taiwan from August 6–11, 2009. It was found that Gaussian-based hyetographs better simulated the rainstorm patterns recorded in the study area than conventional triangular and instantaneous intensity methods. Based on a satellite image investigation, a total of 32 events of reported debris flow disasters were identified with accurate times of debris flow strike and clear causative source slope failures adjacent to the disaster sites. Fundamental statistical parameters, namely the simulated time of peak rainfall intensity, t p , and the standard deviation of rainfall duration, σ t , were used to correlate the time of debris flow initiation. It was found that 94% (30 out of 32 events) of the investigated debris flows occurred between t p − 0.5 σ t and t p + 1.0 σ t , suggesting that intensive slope failures and debris flows occurred around the peak of hourly rainfall, associated with the steepest segment of the mass curve. It was also found that sites with larger source slope failure areas tended to have a longer delay between the time of peak hourly rainfall and the occurrence of debris flow. Results of the analyses revealed the potential of improving the accuracy of debris flow predictions using the proposed hyetograph method.

Can a simple stochastic model generate rich patterns of rainfall events?

Summary Several of the existing rainfall models involve diverse assumptions, a variety of uncertain parameters, complicated mechanistic structures, use of different model schemes for different time scales, and possibly classifications of rainfall patterns into different types. However, the parsimony of a model is recognized as an important desideratum as it improves its comprehensiveness, its applicability and possibly its predictive capacity. To investigate the question if a single and simple stochastic model can generate a plethora of temporal rainfall patterns, as well as to detect the major characteristics of such a model (if it exists), a data set with very fine timescale rainfall is used. This is the well-known data set of the University of Iowa comprising measurements of seven storm events at a temporal resolution of 5–10 s. Even though only seven such events have been observed, their diversity can help investigate these issues. An evident characteristic resulting from the stochastic analysis of the events is the scaling behaviors both in state and in time. Utilizing these behaviors, a stochastic model is constructed which can represent all rainfall events and all rich patterns, thus suggesting a positive reply to the above question. In addition, it seems that the most important characteristics of such a model are a power-type distribution tail and an asymptotic power-type autocorrelation function. Both power-type distribution tails and autocorrelation functions can be viewed as properties enhancing randomness and uncertainty, or entropy.

Rainfall trends in Nigeria, 1901–2000

There is the need to evaluate changes in the spatial and temporal patterns of rainfall in order to improve water management strategies of a given region. In this study, standard tests are used to examine the existence of trend in annual and monthly rainfall of Nigeria over the last century. Rainfall variability index was estimated as standardized rainfall departure while autocorrelation spectral analysis is used to obtain the periodicities inherent therein. Rainfall spatial distribution was highly latitudinal dependent (r2 > 0.90) and had no clearly linear relations with the longitude. Rainfall variability index showed that 1950s was the wettest decade (+0.84) while 1980s was the driest (−1.19), with the two decades between 1970 and 1990 being drier than any other comparable period in the last century. Observed rainfall changes varied between −3.46 and +0.76 mm yr−2. About 90% of the entire landscape exhibited negative trends but only 22% showed significant changes at 5% level. There was a sharp difference between changes in rainfalls in 1931–1960 and 1961–1990 periods. Annual precipitation reduced by 7% between the two periods. While more than 90% of the landscape showed no significant rainfall change in the first period, about 57% of Nigeria showed a significant (P < 0.05) decrease in the second. The dominant peaks can be classified into four distinct rainfall cycles with periods 2–3, 5–7, 10–15 and 30 yr. These cycles may be associated with the stratospheric Quasi-Biennial Oscillation (QBO), the El-Nino Southern Oscillation (ENSO); the sunspot cycles and the Atlantic Multi-Decadal Oscillation (AMO) sea surface temperature, respectively.

Do long-lived ants affect soil microbial communities?

This study was designed to test the hypothesis that desert ant species that build nests that remain viable at a particular point in space for more than a decade produce soil conditions that enhance microbial biomass and functional diversity. We studied the effects of a seed-harvester ant, Pogonomyrmex rugosus, and two generalist ant species, Aphaenogaster cockerelli and Myrmecocystus depilis, on soil microbial communities. Microbial biomass was higher in P. rugosus-modified soils than in reference soils when soil water content was higher than 3%. Microbial biomass was either higher in reference soils or exhibited no difference in reference soils and nest-modified soils of A. cockerelli and M. depilis. There were differences in microbial functional diversity and microbial community level physiological profiles (MicroResp method) between ant-nest-modified and reference soils of the three ant species on some sampling dates. Temporal patterns of soil microbial communities associated with the ant species resulted from differences in soil moisture, density, and species composition of the annual plant communities associated with the ant nests and in reference areas. Differences in annual plant communities associated with ant nests and surrounding areas resulted in different chemical inputs into the soil organic-matter pools. This study shows that generalizations about the effects of long-lived ant nests on soil biota in arid regions must consider feeding behaviors of the ant species and temporal patterns of rainfall.

Regionalization of the probability of wet spells and rainfall persistence in the Basque Country (Northern Spain)

AbstractThe following paper deals with the modelling of a 30‐year‐long daily rainfall time series (1965–1994) from 39 weather stations in the Basque Country region in Northern Spain. Markov chain models are used to explore the temporal rainfall patterns in the area and to characterize the persistence of daily rain in terms of the order of the discrete Markov process. The Markov models—theoretical probabilities—are fitted to the empirical probability of wet spells lasting one more day than a specific length in the time series under the assumption of three different values (1, 5 and 10 mm) of a minimum threshold. Markovian orders that first fit the empirical distributions are used to map the theoretical persistence of daily rainfall in the Basque Country area through the use of geostatistical interpolators. Markovian orders have been confirmed as remarkable stochastic models for fitting empirical distributions of wet spells in this area, ultimately being shown as a spatial representation of theoretical persistence. Copyright © 2011 Royal Meteorological Society

Relationships between rainfall intensity, duration and suspended particle washoff from an urban road surface

A basic understanding of the relationships between rainfall intensity, duration of rainfall and the amount of suspended particles in stormwater runoff generated from road surfaces has been gained mainly from past washoff experiments using rainfall simulators. Simulated rainfall was generally applied at constant intensities, whereas rainfall temporal patterns during actual storms are typically highly variable. This paper discusses a rationale for the application of the constant-intensity washoff concepts to actual storm event runoff. The rationale is tested using suspended particle load data collected at a road site located in Toowoomba, Australia. Agreement between the washoff concepts and measured data is most consistent for intermediate-duration storms (duration &amp;lt;5 h and &amp;gt;1 h). Particle loads resulting from these storm events increase linearly with average rainfall intensity. Above a threshold intensity, there is evidence to suggest a constant or plateau particle load is reached. The inclusion of a peak discharge factor (maximum 6 min rainfall intensity) enhances the ability to predict particle loads.

The influence of spatio-temporal resource fluctuations on insular rat population dynamics

Local spatio-temporal resource variations can strongly influence the population dynamics of small mammals. This is particularly true on islands which are bottom-up driven systems, lacking higher order predators and with high variability in resource subsidies. The influence of resource fluctuations on animal survival may be mediated by individual movement among habitat patches, but simultaneously analysing survival, resource availability and habitat selection requires sophisticated analytical methods. We use a Bayesian multi-state capture-recapture model to estimate survival and movement probabilities of non-native black rats (Rattus rattus) across three habitats seasonally varying in resource availability. We find that survival varies most strongly with temporal rainfall patterns, overwhelming minor spatial variation among habitats. Surprisingly for a generalist forager, movement between habitats was rare, suggesting individuals do not opportunistically respond to spatial resource subsidy variations. Climate is probably the main driver of rodent population dynamics on islands, and even substantial habitat and seasonal spatial subsidies are overwhelmed in magnitude by predictable annual patterns in resource pulses. Marked variation in survival and capture has important implications for the timing of rat control.