Methods, quality assurance, and data for assessing atmospheric deposition of pesticides in the Central Valley of California

USGS Publications Warehouse

Zamora, Celia; Majewski, Michael S.; Foreman, William T.

2013-01-01

The U.S. Geological Survey monitored atmospheric deposition of pesticides in the Central Valley of California during two studies in 2001 and 2002–04. The 2001 study sampled wet deposition (rain) and storm-drain runoff in the Modesto, California, area during the orchard dormant-spray season to examine the contribution of pesticide concentrations to storm runoff from rainfall. In the 2002–04 study, the number and extent of collection sites in the Central Valley were increased to determine the areal distribution of organophosphate insecticides and other pesticides, and also five more sample types were collected. These were dry deposition, bulk deposition, and three sample types collected from a soil box: aqueous phase in runoff, suspended sediment in runoff, and surficial-soil samples. This report provides concentration data and describes methods and quality assurance of sample collection and laboratory analysis for pesticide compounds in all samples collected from 16 sites. Each sample was analyzed for 41 currently used pesticides and 23 pesticide degradates, including oxygen analogs (oxons) of 9 organophosphate insecticides. Analytical results are presented by sample type and study period. The median concentrations of both chloryprifos and diazinon sampled at four urban (0.067 micrograms per liter [μg/L] and 0.515 μg/L, respectively) and four agricultural sites (0.079 μg/L and 0.583 μg/L, respectively) during a January 2001 storm event in and around Modesto, Calif., were nearly identical, indicating that the overall atmospheric burden in the region appeared to be fairly similar during the sampling event. Comparisons of median concentrations in the rainfall to those in the McHenry storm-drain runoff showed that, for some compounds, rainfall contributed a substantial percentage of the concentration in the runoff; for other compounds, the concentrations in rainfall were much greater than in the runoff. For example, diazinon concentrations in rainfall were about 70 percent of the diazinon concentration in the runoff, whereas the chlorpyrifos concentration in the rain was 1.8 times greater than in the runoff. The more water-soluble pesticides—carbaryl, metolachlor, napropamide, and simazine—followed the same pattern as diazinon and had lower concentrations in rain compared to runoff. Similar to chlorpyrifos,compounds with low water solubilities and higher soil-organic carbon partition coefficients, including dacthal, pendimethalin, and trifluralin, were found to have higher concentrations in rain than in runoff water and were presumed to partition to the suspended sediments and organic matter on the ground. During the 2002–04 study period, the herbicide dacthal had the highest detection frequencies for all sample types collected from the Central Valley sites (67–100 percent). The most frequently detected compounds in the wet-deposition samples were dacthal, diazinon, chlorpyrifos, and simazine (greater than 90 percent). The median wet-deposition amounts for these compounds were 0.044 micrograms per square meter per day (μg/m2/day), 0.209 μg/m2/day, 0.079 μg/m2/day, and 0.172 μg/m2/day, respectively. For the dry-deposition samples, detection frequencies were greater than 73 percent for the compounds dacthal, metolachor, and chlorpyrifos, and median deposition amounts were an order of magnitude less than for wet deposition. The differences between wet deposition and dry deposition appeared to be closely related to the Henry’s Law (H) constant of each compound, although the mass deposited by dry deposition takes place over a much longer time frame. Pesticides detected in rainfall usually were detected in the aqueous phase of the soil-box runoff water, and the runoff concentrations were generally similar to those in the rainfall. For compounds detected in the aqueous phase and suspended-sediment samples of soil-box runoff, concentrations of pesticides in the aqueous phase generally were detected in low concentrations and had few corresponding detections in the suspended- sediment samples. Dacthal, diazinon, chlorpyrifos, and simazine were the most frequently detected pesticides (greater than 83 percent) in the aqueous-phase samples, with median concentrations of 0.010 μg/L, 0.045 μg/L, 0.016 μg/L, and 0.077 μg/L, respectively. Simazine was the most frequently detected compound in the suspended-sediment samples (69 percent), with a median concentration of 0.232 μg/L. Results for compounds detected in the surficial-soil samples collected throughout the study period showed that there was an increase in concentration for some compounds, indicating atmospheric deposition of these compounds onto the soil-box surface. In the San Joaquin Valley, the compounds chlorpyrifos, dacthal, and iprodione were detected at higher concentrations (between 1.4 and 2 times greater) than were found in the background samples collected from the San Joaquin Valley soil-box sites. In the Sacramento Valley, the compounds chlorpyrifos, dacthal, iprodione, parathionmethyl, and its oxygen analog, paraoxon-methyl, were detected in samples collected during the study period in low concentrations, but were not detected in the background concentration of the Sacramento Valley soil mix.

The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

2015-07-01

This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2017-03-01

The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the total flow variability in the response of the urban drainage systems to heavy rainfall events.

Remote rainfall sensing for landslide hazard analysis

USGS Publications Warehouse

Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay

2001-01-01

Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

Estimation of synthetic flood design hydrographs using a distributed rainfall-runoff model coupled with a copula-based single storm rainfall generator

NASA Astrophysics Data System (ADS)

Candela, A.; Brigandì, G.; Aronica, G. T.

2014-07-01

In this paper a procedure to derive synthetic flood design hydrographs (SFDH) using a bivariate representation of rainfall forcing (rainfall duration and intensity) via copulas, which describes and models the correlation between two variables independently of the marginal laws involved, coupled with a distributed rainfall-runoff model, is presented. Rainfall-runoff modelling (R-R modelling) for estimating the hydrological response at the outlet of a catchment was performed by using a conceptual fully distributed procedure based on the Soil Conservation Service - Curve Number method as an excess rainfall model and on a distributed unit hydrograph with climatic dependencies for the flow routing. Travel time computation, based on the distributed unit hydrograph definition, was performed by implementing a procedure based on flow paths, determined from a digital elevation model (DEM) and roughness parameters obtained from distributed geographical information. In order to estimate the primary return period of the SFDH, which provides the probability of occurrence of a hydrograph flood, peaks and flow volumes obtained through R-R modelling were treated statistically using copulas. Finally, the shapes of hydrographs have been generated on the basis of historically significant flood events, via cluster analysis. An application of the procedure described above has been carried out and results presented for the case study of the Imera catchment in Sicily, Italy.

Evaluating rainfall errors in global climate models through cloud regimes

NASA Astrophysics Data System (ADS)

Tan, Jackson; Oreopoulos, Lazaros; Jakob, Christian; Jin, Daeho

2017-07-01

Global climate models suffer from a persistent shortcoming in their simulation of rainfall by producing too much drizzle and too little intense rain. This erroneous distribution of rainfall is a result of deficiencies in the representation of underlying processes of rainfall formation. In the real world, clouds are precursors to rainfall and the distribution of clouds is intimately linked to the rainfall over the area. This study examines the model representation of tropical rainfall using the cloud regime concept. In observations, these cloud regimes are derived from cluster analysis of joint-histograms of cloud properties retrieved from passive satellite measurements. With the implementation of satellite simulators, comparable cloud regimes can be defined in models. This enables us to contrast the rainfall distributions of cloud regimes in 11 CMIP5 models to observations and decompose the rainfall errors by cloud regimes. Many models underestimate the rainfall from the organized convective cloud regime, which in observation provides half of the total rain in the tropics. Furthermore, these rainfall errors are relatively independent of the model's accuracy in representing this cloud regime. Error decomposition reveals that the biases are compensated in some models by a more frequent occurrence of the cloud regime and most models exhibit substantial cancellation of rainfall errors from different regimes and regions. Therefore, underlying relatively accurate total rainfall in models are significant cancellation of rainfall errors from different cloud types and regions. The fact that a good representation of clouds does not lead to appreciable improvement in rainfall suggests a certain disconnect in the cloud-precipitation processes of global climate models.

Estimating rainfall time series and model parameter distributions using model data reduction and inversion techniques

NASA Astrophysics Data System (ADS)

Wright, Ashley J.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.

2017-08-01

Floods are devastating natural hazards. To provide accurate, precise, and timely flood forecasts, there is a need to understand the uncertainties associated within an entire rainfall time series, even when rainfall was not observed. The estimation of an entire rainfall time series and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of entire rainfall input time series to be considered when estimating model parameters, and provides the ability to improve rainfall estimates from poorly gauged catchments. Current methods to estimate entire rainfall time series from streamflow records are unable to adequately invert complex nonlinear hydrologic systems. This study aims to explore the use of wavelets in the estimation of rainfall time series from streamflow records. Using the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia, it is shown that model parameter distributions and an entire rainfall time series can be estimated. Including rainfall in the estimation process improves streamflow simulations by a factor of up to 1.78. This is achieved while estimating an entire rainfall time series, inclusive of days when none was observed. It is shown that the choice of wavelet can have a considerable impact on the robustness of the inversion. Combining the use of a likelihood function that considers rainfall and streamflow errors with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

Rain-fed fig yield as affected by rainfall distribution

NASA Astrophysics Data System (ADS)

Bagheri, Ensieh; Sepaskhah, Ali Reza

2014-08-01

Variable annual rainfall and its uneven distribution are the major uncontrolled inputs in rain-fed fig production and possibly the main cause of yield fluctuation in Istahban region of Fars Province, I.R. of Iran. This introduces a considerable risk in rain-fed fig production. The objective of this study was to find relationships between seasonal rainfall distribution and rain-fed fig production in Istahban region to determine the critical rainfall periods for rain-fed fig production and supplementary irrigation water application. Further, economic analysis for rain-fed fig production was considered in this region to control the risk of production. It is concluded that the monthly, seasonal and annual rainfall indices are able to show the effects of rainfall and its distribution on the rain-fed fig yield. Fig yield with frequent occurrence of 80 % is 374 kg ha-1. The internal rates of return for interest rate of 4, 8 and 12 % are 21, 58 and 146 %, respectively, that are economically feasible. It is concluded that the rainfall in spring especially in April and in December has negatively affected fig yield due to its interference with the life cycle of Blastophaga bees for pollination. Further, it is concluded that when the rainfall is limited, supplementary irrigation can be scheduled in March.

Encounter risk analysis of rainfall and reference crop evapotranspiration in the irrigation district

NASA Astrophysics Data System (ADS)

Zhang, Jinping; Lin, Xiaomin; Zhao, Yong; Hong, Yang

2017-09-01

Rainfall and reference crop evapotranspiration are random but mutually affected variables in the irrigation district, and their encounter situation can determine water shortage risks under the contexts of natural water supply and demand. However, in reality, the rainfall and reference crop evapotranspiration may have different marginal distributions and their relations are nonlinear. In this study, based on the annual rainfall and reference crop evapotranspiration data series from 1970 to 2013 in the Luhun irrigation district of China, the joint probability distribution of rainfall and reference crop evapotranspiration are developed with the Frank copula function. Using the joint probability distribution, the synchronous-asynchronous encounter risk, conditional joint probability, and conditional return period of different combinations of rainfall and reference crop evapotranspiration are analyzed. The results show that the copula-based joint probability distributions of rainfall and reference crop evapotranspiration are reasonable. The asynchronous encounter probability of rainfall and reference crop evapotranspiration is greater than their synchronous encounter probability, and the water shortage risk associated with meteorological drought (i.e. rainfall variability) is more prone to appear. Compared with other states, there are higher conditional joint probability and lower conditional return period in either low rainfall or high reference crop evapotranspiration. For a specifically high reference crop evapotranspiration with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is increased with the decrease in frequency. For a specifically low rainfall with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is decreased with the decrease in frequency. When either the high reference crop evapotranspiration exceeds a certain frequency or low rainfall does not exceed a certain frequency, the higher conditional joint probability and lower conditional return period of various combinations likely cause a water shortage, but the water shortage is not severe.

Temporal distribution of rainfall in Virginia : final report.

DOT National Transportation Integrated Search

1984-01-01

The temporal distribution of Virginia rainstorms was examined by statistically analyzing approximately 1,400 storm events recorded throughout the state. Rainfall time distribution curves were constructed and were compared with several nationally reco...

Universal inverse power-law distribution for temperature and rainfall in the UK region

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2014-06-01

Meteorological parameters, such as temperature, rainfall, pressure, etc., exhibit selfsimilar space-time fractal fluctuations generic to dynamical systems in nature such as fluid flows, spread of forest fires, earthquakes, etc. The power spectra of fractal fluctuations display inverse power-law form signifying long-range correlations. A general systems theory model predicts universal inverse power-law form incorporating the golden mean for the fractal fluctuations. The model predicted distribution was compared with observed distribution of fractal fluctuations of all size scales (small, large and extreme values) in the historic month-wise temperature (maximum and minimum) and total rainfall for the four stations Oxford, Armagh, Durham and Stornoway in the UK region, for data periods ranging from 92 years to 160 years. For each parameter, the two cumulative probability distributions, namely cmax and cmin starting from respectively maximum and minimum data value were used. The results of the study show that (i) temperature distributions (maximum and minimum) follow model predicted distribution except for Stornowy, minimum temperature cmin. (ii) Rainfall distribution for cmin follow model predicted distribution for all the four stations. (iii) Rainfall distribution for cmax follows model predicted distribution for the two stations Armagh and Stornoway. The present study suggests that fractal fluctuations result from the superimposition of eddy continuum fluctuations.

Asymmetric impact of rainfall on India's food grain production: evidence from quantile autoregressive distributed lag model

NASA Astrophysics Data System (ADS)

Pal, Debdatta; Mitra, Subrata Kumar

2018-01-01

This study used a quantile autoregressive distributed lag (QARDL) model to capture asymmetric impact of rainfall on food production in India. It was found that the coefficient corresponding to the rainfall in the QARDL increased till the 75th quantile and started decreasing thereafter, though it remained in the positive territory. Another interesting finding is that at the 90th quantile and above the coefficients of rainfall though remained positive was not statistically significant and therefore, the benefit of high rainfall on crop production was not conclusive. However, the impact of other determinants, such as fertilizer and pesticide consumption, is quite uniform over the whole range of the distribution of food grain production.

Time distribution of heavy rainfall events in south west of Iran

NASA Astrophysics Data System (ADS)

Ghassabi, Zahra; kamali, G. Ali; Meshkatee, Amir-Hussain; Hajam, Sohrab; Javaheri, Nasrolah

2016-07-01

Accurate knowledge of rainfall time distribution is a fundamental issue in many Meteorological-Hydrological studies such as using the information of the surface runoff in the design of the hydraulic structures, flood control and risk management, and river engineering studies. Since the main largest dams of Iran are in the south-west of the country (i.e. South Zagros), this research investigates the temporal rainfall distribution based on an analytical numerical method to increase the accuracy of hydrological studies in Iran. The United States Soil Conservation Service (SCS) estimated the temporal rainfall distribution in various forms. Hydrology studies usually utilize the same distribution functions in other areas of the world including Iran due to the lack of sufficient observation data. However, we first used Weather Research Forecasting (WRF) model to achieve the simulated rainfall results of the selected storms on south west of Iran in this research. Then, a three-parametric Logistic function was fitted to the rainfall data in order to compute the temporal rainfall distribution. The domain of the WRF model is 30.5N-34N and 47.5E-52.5E with a resolution of 0.08 degree in latitude and longitude. We selected 35 heavy storms based on the observed rainfall data set to simulate with the WRF Model. Storm events were scrutinized independently from each other and the best analytical three-parametric logistic function was fitted for each grid point. The results show that the value of the coefficient a of the logistic function, which indicates rainfall intensity, varies from the minimum of 0.14 to the maximum of 0.7. Furthermore, the values of the coefficient B of the logistic function, which indicates rain delay of grid points from start time of rainfall, vary from 1.6 in south-west and east to more than 8 in north and central parts of the studied area. In addition, values of rainfall intensities are lower in south west of IRAN than those of observed or proposed by the SCS values in the US.

On the distributions of annual and seasonal daily rainfall extremes in central Arizona and their spatial variability

NASA Astrophysics Data System (ADS)

Mascaro, Giuseppe

2018-04-01

This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.

Stochastic characteristics of different duration annual maximum rainfall and its spatial difference in China based on information entropy

NASA Astrophysics Data System (ADS)

Li, X.; Sang, Y. F.

2017-12-01

Mountain torrents, urban floods and other disasters caused by extreme precipitation bring great losses to the ecological environment, social and economic development, people's lives and property security. So there is of great significance to floods prevention and control by the study of its spatial distribution. Based on the annual maximum rainfall data of 60min, 6h and 24h, the paper generate long sequences following Pearson-III distribution, and then use the information entropy index to study the spatial distribution and difference of different duration. The results show that the information entropy value of annual maximum rainfall in the south region is greater than that in the north region, indicating more obvious stochastic characteristics of annual maximum rainfall in the latter. However, the spatial distribution of stochastic characteristics is different in different duration. For example, stochastic characteristics of 60min annual maximum rainfall in the Eastern Tibet is smaller than surrounding, but 6h and 24h annual maximum rainfall is larger than surrounding area. In the Haihe River Basin and the Huaihe River Basin, the stochastic characteristics of the 60min annual maximum rainfall was not significantly different from that in the surrounding area, and stochastic characteristics of 6h and 24h was smaller than that in the surrounding area. We conclude that the spatial distribution of information entropy values of annual maximum rainfall in different duration can reflect the spatial distribution of its stochastic characteristics, thus the results can be an importantly scientific basis for the flood prevention and control, agriculture, economic-social developments and urban flood control and waterlogging.

Numerical Study of Groundwater Flow and Salinity Distribution Cycling Controlled by Seawater/Freshwater Interaction in Karst Aquifer Using SEAWAT

NASA Astrophysics Data System (ADS)

Xu, Z.; Hu, B.

2017-12-01

The interest to predict seawater intrusion and salinity distribution in Woodville Karst Plain (WKP) has increased due to the huge challenge on quality of drinkable water and serious environmental problems. Seawater intrudes into the conduit system from submarine karst caves at Spring Creek Spring due to density difference and sea level rising, nowadays the low salinity has been detected at Wakulla Spring which is 18 km from coastal line. The groundwater discharge at two major springs and salinity distribution in this area is controlled by the seawater/freshwater interaction under different rainfall conditions: during low rainfall periods, seawater flow into the submarine spring through karst windows, then the salinity rising at the submarine spring leads to seawater further intrudes into conduit system; during high rainfall periods, seawater is pushed out by fresh water discharge at submarine spring. The previous numerical studies of WKP mainly focused on the density independent transport modeling and seawater/freshwater discharge at major karst springs, in this study, a SEAWAT model has been developed to fully investigate the salinity distribution in the WKP under repeating phases of low rainfall and high rainfall periods, the conduit system was simulated as porous media with high conductivity and porosity. The precipitation, salinity and discharge at springs were used to calibrate the model. The results showed that the salinity distribution in porous media and conduit system is controlled by the rainfall change, in general, the salinity distribution inland under low rainfall conditions is much higher and wider than the high rainfall conditions. The results propose a prediction on the environmental problem caused by seawater intrusion in karst coastal aquifer, in addition, provide a visual and scientific basis for future groundwater remediation.

Reclaimed mineland curve number response to temporal distribution of rainfall

USGS Publications Warehouse

Warner, R.C.; Agouridis, C.T.; Vingralek, P.T.; Fogle, A.W.

2010-01-01

The curve number (CN) method is a common technique to estimate runoff volume, and it is widely used in coal mining operations such as those in the Appalachian region of Kentucky. However, very little CN data are available for watersheds disturbed by surface mining and then reclaimed using traditional techniques. Furthermore, as the CN method does not readily account for variations in infiltration rates due to varying rainfall distributions, the selection of a single CN value to encompass all temporal rainfall distributions could lead engineers to substantially under- or over-size water detention structures used in mining operations or other land uses such as development. Using rainfall and runoff data from a surface coal mine located in the Cumberland Plateau of eastern Kentucky, CNs were computed for conventionally reclaimed lands. The effects of temporal rainfall distributions on CNs was also examined by classifying storms as intense, steady, multi-interval intense, or multi-interval steady. Results indicate that CNs for such reclaimed lands ranged from 62 to 94 with a mean value of 85. Temporal rainfall distributions were also shown to significantly affect CN values with intense storms having significantly higher CNs than multi-interval storms. These results indicate that a period of recovery is present between rainfall bursts of a multi-interval storm that allows depressional storage and infiltration rates to rebound. ?? 2010 American Water Resources Association.

Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

NASA Astrophysics Data System (ADS)

Narulita, Ida; Ningrum, Widya

2018-02-01

Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

Combining spray nozzle simulators with meshes: characterization of rainfall intensity and drop properties

NASA Astrophysics Data System (ADS)

Carvalho, Sílvia C. P.; de Lima, João L. M. P.; de Lima, M. Isabel P.

2013-04-01

Rainfall simulators can be a powerful tool to increase our understanding of hydrological and geomorphological processes. Nevertheless, rainfall simulators' design and operation might be rather demanding, for achieving specific rainfall intensity distributions and drop characteristics. The pressurized simulators have some advantages over the non-pressurized simulators: drops do not rely on gravity to reach terminal velocity, but are sprayed out under pressure; pressurized simulators also yield a broad range of drop sizes in comparison with drop-formers simulators. The main purpose of this study was to explore in the laboratory the potential of combining spray nozzle simulators with meshes in order to change rainfall characteristics (rainfall intensity and diameters and fall speed of drops). Different types of spray nozzles were tested, such as single full-cone and multiple full-cone nozzles. The impact of the meshes on the simulated rain was studied by testing different materials (i.e. plastic and steel meshes), square apertures and wire thicknesses, and different vertical distances between the nozzle and the meshes underneath. The diameter and fall speed of the rain drops were measured using a Laser Precipitation Monitor (Thies Clima). The rainfall intensity range and coefficients of uniformity of the sprays and the drop size distribution, fall speed and kinetic energy were analysed. Results show that when meshes intercept drop trajectories the spatial distribution of rainfall intensity and the drop size distribution are affected. As the spray nozzles generate typically small drop sizes and narrow drop size distributions, meshes can be used to promote the formation of bigger drops and random their landing positions.

Modelling rainfall amounts using mixed-gamma model for Kuantan district

NASA Astrophysics Data System (ADS)

Zakaria, Roslinazairimah; Moslim, Nor Hafizah

2017-05-01

An efficient design of flood mitigation and construction of crop growth models depend upon good understanding of the rainfall process and characteristics. Gamma distribution is usually used to model nonzero rainfall amounts. In this study, the mixed-gamma model is applied to accommodate both zero and nonzero rainfall amounts. The mixed-gamma model presented is for the independent case. The formulae of mean and variance are derived for the sum of two and three independent mixed-gamma variables, respectively. Firstly, the gamma distribution is used to model the nonzero rainfall amounts and the parameters of the distribution (shape and scale) are estimated using the maximum likelihood estimation method. Then, the mixed-gamma model is defined for both zero and nonzero rainfall amounts simultaneously. The formulae of mean and variance for the sum of two and three independent mixed-gamma variables derived are tested using the monthly rainfall amounts from rainfall stations within Kuantan district in Pahang Malaysia. Based on the Kolmogorov-Smirnov goodness of fit test, the results demonstrate that the descriptive statistics of the observed sum of rainfall amounts is not significantly different at 5% significance level from the generated sum of independent mixed-gamma variables. The methodology and formulae demonstrated can be applied to find the sum of more than three independent mixed-gamma variables.

Extreme Precipitation and High-Impact Landslides

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Huffman, George; Peters-Lidard, Christa

2012-01-01

It is well known that extreme or prolonged rainfall is the dominant trigger of landslides; however, there remain large uncertainties in characterizing the distribution of these hazards and meteorological triggers at the global scale. Researchers have evaluated the spatiotemporal distribution of extreme rainfall and landslides at local and regional scale primarily using in situ data, yet few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This research uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from Tropical Rainfall Measuring Mission (TRMM) data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurence of precipitation and rainfall-triggered landslides globally. The GLC, available from 2007 to the present, contains information on reported rainfall-triggered landslide events around the world using online media reports, disaster databases, etc. When evaluating this database, we observed that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This research also considers the sources for this extreme rainfall, citing teleconnections from ENSO as likely contributors to regional precipitation variability. This work demonstrates the potential for using satellite-based precipitation estimates to identify potentially active landslide areas at the global scale in order to improve landslide cataloging and quantify landslide triggering at daily, monthly and yearly time scales.

Impact of climate change on runoff pollution in urban environments

NASA Astrophysics Data System (ADS)

Coutu, S.; Kramer, S.; Barry, D. A.; Roudier, P.

2012-12-01

Runoff from urban environments is generally contaminated. These contaminants mostly originate from road traffic and building envelopes. Facade envelopes generate lead, zinc and even biocides, which are used for facade protection. Road traffic produces particles from tires and brakes. The transport of these pollutants to the environment is controlled by rainfall. The interval, duration and intensity of rainfall events are important as the dynamics of the pollutants are often modeled with non-linear buildup/washoff functions. Buildup occurs during dry weather when pollution accumulates, and is subsequently washed-off at the time of the following rainfall, contaminating surface runoff. Climate predictions include modified rainfall distributions, with changes in both number and intensity of events, even if the expected annual rainfall varies little. Consequently, pollutant concentrations in urban runoff driven by buildup/washoff processes will be affected by these changes in rainfall distributions. We investigated to what extent modifications in future rainfall distributions will impact the concentrations of pollutants present in urban surface runoff. The study used the example of Lausanne, Switzerland (temperate climate zone). Three emission scenarios (time horizon 2090), multiple combinations of RCM/GCM and modifications in rain event frequency were used to simulate future rainfall distributions with various characteristics. Simulated rainfall events were used as inputs for four pairs of buildup/washoff models, in order to compare future pollution concentrations in surface runoff. In this way, uncertainty in model structure was also investigated. Future concentrations were estimated to be between ±40% of today's concentrations depending on the season and, importantly, on the choice of the RCM/GCM model. Overall, however, the dominant factor was the uncertainty inherent in buildup/washoff models, which dominated over the uncertainty in future rainfall distributions. Consequently, the choice of a proper buildup/washoff model, with calibrated site-specific coefficients, is a major factor in modeling future runoff concentrations from contaminated urban surfaces.

The Microphysical Structure of Extreme Precipitation as Inferred from Ground-Based Raindrop Spectra.

NASA Astrophysics Data System (ADS)

Uijlenhoet, Remko; Smith, James A.; Steiner, Matthias

2003-05-01

The controls on the variability of raindrop size distributions in extreme rainfall and the associated radar reflectivity-rain rate relationships are studied using a scaling-law formalism for the description of raindrop size distributions and their properties. This scaling-law formalism enables a separation of the effects of changes in the scale of the raindrop size distribution from those in its shape. Parameters controlling the scale and shape of the scaled raindrop size distribution may be related to the microphysical processes generating extreme rainfall. A global scaling analysis of raindrop size distributions corresponding to rain rates exceeding 100 mm h1, collected during the 1950s with the Illinois State Water Survey raindrop camera in Miami, Florida, reveals that extreme rain rates tend to be associated with conditions in which the variability of the raindrop size distribution is strongly number controlled (i.e., characteristic drop sizes are roughly constant). This means that changes in properties of raindrop size distributions in extreme rainfall are largely produced by varying raindrop concentrations. As a result, rainfall integral variables (such as radar reflectivity and rain rate) are roughly proportional to each other, which is consistent with the concept of the so-called equilibrium raindrop size distribution and has profound implications for radar measurement of extreme rainfall. A time series analysis for two contrasting extreme rainfall events supports the hypothesis that the variability of raindrop size distributions for extreme rain rates is strongly number controlled. However, this analysis also reveals that the actual shapes of the (measured and scaled) spectra may differ significantly from storm to storm. This implies that the exponents of power-law radar reflectivity-rain rate relationships may be similar, and close to unity, for different extreme rainfall events, but their prefactors may differ substantially. Consequently, there is no unique radar reflectivity-rain rate relationship for extreme rain rates, but the variability is essentially reduced to one free parameter (i.e., the prefactor). It is suggested that this free parameter may be estimated on the basis of differential reflectivity measurements in extreme rainfall.

Demographic patterns of a widespread long-lived tree are associated with rainfall and disturbances along rainfall gradients in SE Australia

PubMed Central

Cohn, Janet S; Lunt, Ian D; Bradstock, Ross A; Hua, Quan; McDonald, Simon

2013-01-01

Predicting species distributions with changing climate has often relied on climatic variables, but increasingly there is recognition that disturbance regimes should also be included in distribution models. We examined how changes in rainfall and disturbances along climatic gradients determined demographic patterns in a widespread and long-lived tree species, Callitris glaucophylla in SE Australia. We examined recruitment since 1950 in relation to annual (200–600 mm) and seasonal (summer, uniform, winter) rainfall gradients, edaphic factors (topography), and disturbance regimes (vertebrate grazing [tenure and species], fire). A switch from recruitment success to failure occurred at 405 mm mean annual rainfall, coincident with a change in grazing regime. Recruitment was lowest on farms with rabbits below 405 mm rainfall (mean = 0–0.89 cohorts) and highest on less-disturbed tenures with no rabbits above 405 mm rainfall (mean = 3.25 cohorts). Moderate levels of recruitment occurred where farms had no rabbits or less disturbed tenures had rabbits above and below 405 mm rainfall (mean = 1.71–1.77 cohorts). These results show that low annual rainfall and high levels of introduced grazing has led to aging, contracting populations, while higher annual rainfall with low levels of grazing has led to younger, expanding populations. This study demonstrates how demographic patterns vary with rainfall and spatial variations in disturbances, which are linked in complex ways to climatic gradients. Predicting changes in tree distribution with climate change requires knowledge of how rainfall and key disturbances (tenure, vertebrate grazing) will shift along climatic gradients. PMID:23919160

Fires, storms, and water supplies: a case of compound extremes?

NASA Astrophysics Data System (ADS)

Sheridan, G. J.; Nyman, P.; Langhans, C.; Jones, O.; Lane, P. N.

2013-12-01

Intense rainfall events following fire can wash sediment and ash into streams and reservoirs, contaminating water supplies for cities and towns. Post fire flooding and debris flows damage infrastructure and endanger life. These kinds of risks which are associated with a combination of two or more events (which may or may not be extreme when occurring independently) are an example of what the IPCC recently referred to as ';compound extremes'. Detailed models exist for modeling fire and erosion events separately, however there have been few attempts to integrate these models so as to estimate the water quality and infrastructure risks associated with combined fire and rainfall regimes. This presentation will articulate the issues associated with modeling the compound effects of fire and subsequent rainfall events on erosion, debris flows and water quality, and will describe and contrast several new approaches to modeling this problem developed and applied to SE Australian fire prone landscapes under the influence of climate change.

Probability analysis for consecutive-day maximum rainfall for Tiruchirapalli City (south India, Asia)

NASA Astrophysics Data System (ADS)

Sabarish, R. Mani; Narasimhan, R.; Chandhru, A. R.; Suribabu, C. R.; Sudharsan, J.; Nithiyanantham, S.

2017-05-01

In the design of irrigation and other hydraulic structures, evaluating the magnitude of extreme rainfall for a specific probability of occurrence is of much importance. The capacity of such structures is usually designed to cater to the probability of occurrence of extreme rainfall during its lifetime. In this study, an extreme value analysis of rainfall for Tiruchirapalli City in Tamil Nadu was carried out using 100 years of rainfall data. Statistical methods were used in the analysis. The best-fit probability distribution was evaluated for 1, 2, 3, 4 and 5 days of continuous maximum rainfall. The goodness of fit was evaluated using Chi-square test. The results of the goodness-of-fit tests indicate that log-Pearson type III method is the overall best-fit probability distribution for 1-day maximum rainfall and consecutive 2-, 3-, 4-, 5- and 6-day maximum rainfall series of Tiruchirapalli. To be reliable, the forecasted maximum rainfalls for the selected return periods are evaluated in comparison with the results of the plotting position.

Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

NASA Astrophysics Data System (ADS)

Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

2017-04-01

In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a-priori information (topography, lithology, …) and rainfall metrics available from meteorological forecast may allow to better anticipate and mitigates landsliding associated with extreme rainfall events.

Can we improve streamflow simulation by using higher resolution rainfall information?

NASA Astrophysics Data System (ADS)

Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles

2013-04-01

The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.

Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia

NASA Astrophysics Data System (ADS)

Alahmadi, F.; Rahman, N. A.; Abdulrazzak, M.

2014-09-01

Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events. This study analyses the application of rainfall partial duration series (PDS) in the vast growing urban Madinah city located in the western part of Saudi Arabia. Different statistical distributions were applied (i.e. Normal, Log Normal, Extreme Value type I, Generalized Extreme Value, Pearson Type III, Log Pearson Type III) and their distribution parameters were estimated using L-moments methods. Also, different selection criteria models are applied, e.g. Akaike Information Criterion (AIC), Corrected Akaike Information Criterion (AICc), Bayesian Information Criterion (BIC) and Anderson-Darling Criterion (ADC). The analysis indicated the advantage of Generalized Extreme Value as the best fit statistical distribution for Madinah partial duration daily rainfall series. The outcome of such an evaluation can contribute toward better design criteria for flood management, especially flood protection measures.

Cooling, degassing and compaction of rhyolitic ash flow tuffs: a computational model

USGS Publications Warehouse

Riehle, J.R.; Miller, T.F.; Bailey, R.A.

1995-01-01

Previous models of degassing, cooling and compaction of rhyolitic ash flow deposits are combined in a single computational model that runs on a personal computer. The model applies to a broader range of initial and boundary conditions than Riehle's earlier model, which did not integrate heat and mass flux with compaction and which for compound units was limited to two deposits. Model temperatures and gas pressures compare well with simple measured examples. The results indicate that degassing of volatiles present at deposition occurs within days to a few weeks. Compaction occurs for weeks to two to three years unless halted by devitrification; near-emplacement temperatures can persist for tens of years in the interiors of thick deposits. Even modest rainfall significantly chills the upper parts of ash deposits, but compaction in simple cooling units ends before chilling by rainwater influences cooling of the interior of the sheet. Rainfall does, however, affect compaction at the boundaries of deposits in compound cooling units, because the influx of heat from the overlying unit is inadequate to overcome heat previously lost to vaporization of water. Three density profiles from the Matahina Ignimbrite, a compound cooling unit, are fairly well reproduced by the model despite complexities arising from numerous cooling breaks. Uncertainties in attempts to correlate in detail among the profiles may be the result of the non-uniform distribution of individual deposits. Regardless, it is inferred that model compaction is approximately valid. Thus the model should be of use in reconstructing the emplacement history of compound ash deposits, for inferring the depositional environments of ancient deposits and for assessing how long deposits of modern ash flows are capable of generating phreatic eruptions or secondary ash flows. ?? 1995 Springer-Verlag.

Power-law scaling in daily rainfall patterns and consequences in urban stream discharges

NASA Astrophysics Data System (ADS)

Park, Jeryang; Krueger, Elisabeth H.; Kim, Dongkyun; Rao, Suresh C.

2016-04-01

Poissonian rainfall has been frequently used for modelling stream discharge in a catchment at the daily scale. Generally, it is assumed that the daily rainfall depth is described by memoryless exponential distribution which is transformed to stream discharge, resulting in an analytical pdf for discharge [Gamma distribution]. While it is true that catchment hydrological filtering processes (censored by constant rate ET losses, and first-order recession) increases "memory", reflected in 1/f noise in discharge time series. Here, we show that for urban watersheds in South Korea: (1) the observation of daily rainfall depths follow power-law pdfs, and spectral slopes range between 0.2 ~ 0.4; and (2) the stream discharge pdfs have power-law tails. These observation results suggest that multiple hydro-climatic factors (e.g., non-stationarity of rainfall patterns) and hydrologic filtering (increasing impervious area; more complex urban drainage networks) influence the catchment hydrologic responses. We test the role of such factors using a parsimonious model, using different types of daily rainfall patterns (e.g., power-law distributed rainfall depth with Poisson distribution in its frequency) and urban settings to reproduce patterns similar to those observed in empirical records. Our results indicate that fractality in temporally up-scaled rainfall, and the consequences of large extreme events are preserved as high discharge events in urbanizing catchments. Implications of these results to modeling urban hydrologic responses and impacts on receiving waters are discussed.

Entropy of stable seasonal rainfall distribution in Kelantan

NASA Astrophysics Data System (ADS)

Azman, Muhammad Az-zuhri; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Radi, Noor Fadhilah Ahmad

2017-05-01

Investigating the rainfall variability is vital for any planning and management in many fields related to water resources. Climate change can gives an impact of water availability and may aggravate water scarcity in the future. Two statistics measurements which have been used by many researchers to measure the rainfall variability are variance and coefficient of variation. However, these two measurements are insufficient since rainfall distribution in Malaysia especially in the East Coast of Peninsular Malaysia is not symmetric instead it is positively skewed. In this study, the entropy concept is used as a tool to measure the seasonal rainfall variability in Kelantan and ten rainfall stations were selected. In previous studies, entropy of stable rainfall (ESR) and apportionment entropy (AE) were used to describe the rainfall amount variability during years for Australian rainfall data. In this study, the entropy of stable seasonal rainfall (ESSR) is suggested to model rainfall amount variability during northeast monsoon (NEM) and southwest monsoon (SWM) seasons in Kelantan. The ESSR is defined to measure the long-term average seasonal rainfall amount variability within a given year (1960-2012). On the other hand, the AE measures the rainfall amounts variability across the months. The results of ESSR and AE values show that stations in east coastline are more variable as compared to other stations inland for Kelantan rainfall. The contour maps of ESSR for Kelantan rainfall stations are also presented.

Deforestation and rainfall recycling in Brazil: Is decreased forest cover connectivity associated with decreased rainfall connectivity?

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2017-12-01

In the Brazilian rainforest-savanna transition zone, deforestation has the potential to significantly affect rainfall by disrupting rainfall recycling, the process by which regional evapotranspiration contributes to regional rainfall. Understanding rainfall recycling in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching, agriculture, hydropower generation, and drinking water management. Simulations in previous studies suggest complex, scale-dependent interactions between forest cover connectivity and rainfall. For example, the size and distribution of deforested patches has been found to affect rainfall quantity and spatial distribution. Here we take an empirical approach, using the spatial connectivity of rainfall as an indicator of rainfall recycling, to ask: as forest cover connectivity decreased from 1981 - 2015, how did the spatial connectivity of rainfall change in the Brazilian rainforest-savanna transition zone? We use satellite forest cover and rainfall data covering this period of intensive forest cover loss in the region (forest cover from the Hansen Global Forest Change dataset; rainfall from the Climate Hazards Infrared Precipitation with Stations dataset). Rainfall spatial connectivity is quantified using transfer entropy, a metric from information theory, and summarized using network statistics. Networks of connectivity are quantified for paired deforested and non-deforested regions before deforestation (1981-1995) and during/after deforestation (2001-2015). Analyses reveal a decline in spatial connectivity networks of rainfall following deforestation.

Spatiotemporal variability of rainfall extremes in monsoonal climates - examples from the South American Monsoon and the Indian Monsoon Systems (Invited)

NASA Astrophysics Data System (ADS)

Bookhagen, B.; Boers, N.; Marwan, N.; Malik, N.; Kurths, J.

2013-12-01

Monsoonal rainfall is the crucial component for more than half of the world's population. Runoff associated with monsoon systems provide water resources for agriculture, hydropower, drinking-water generation, recreation, and social well-being and are thus a fundamental part of human society. However, monsoon systems are highly stochastic and show large variability on various timescales. Here, we use various rainfall datasets to characterize spatiotemporal rainfall patterns using traditional as well as new approaches emphasizing nonlinear spatial correlations from a complex networks perspective. Our analyses focus on the South American (SAMS) and Indian (ISM) Monsoon Systems on the basis of Tropical Rainfall Measurement Mission (TRMM) using precipitation radar and passive-microwave products with horizontal spatial resolutions of ~5x5 km^2 (products 2A25, 2B31) and 25x25 km^2 (3B42) and interpolated rainfall-gauge data for the ISM (APHRODITE, 25x25 km^2). The eastern slopes of the Andes of South America and the southern front of the Himalaya are characterized by significant orographic barriers that intersect with the moisture-bearing, monsoonal wind systems. We demonstrate that topography exerts a first-order control on peak rainfall amounts on annual timescales in both mountain belts. Flooding in the downstream regions is dominantly caused by heavy rainfall storms that propagate deep into the mountain range and reach regions that are arid and without vegetation cover promoting rapid runoff. These storms exert a significantly different spatial distribution than average-rainfall conditions and assessing their recurrence intervals and prediction is key in understanding flooding for these regions. An analysis of extreme-value distributions of our high-spatial resolution data reveal that semi-arid areas are characterized by low-frequency/high-magnitude events (i.e., are characterized by a ';heavy tail' distribution), whereas regions with high mean annual rainfall have a less skewed distribution. In a second step, an analysis of the spatial characteristics of extreme rainfall synchronicity by means of complex networks reveals patterns of the propagation of extreme rainfall events. These patterns differ substantially from those obtained from the mean annual rainfall distribution. In addition, we have developed a scheme to predict rainfall extreme events in the eastern Central Andes based on event synchronization and spatial patterns of complex networks. The presented methods and result will allow to critically evaluate data and models in space and time.

Modified retrieval algorithm for three types of precipitation distribution using x-band synthetic aperture radar

NASA Astrophysics Data System (ADS)

Xie, Yanan; Zhou, Mingliang; Pan, Dengke

2017-10-01

The forward-scattering model is introduced to describe the response of normalized radar cross section (NRCS) of precipitation with synthetic aperture radar (SAR). Since the distribution of near-surface rainfall is related to the rate of near-surface rainfall and horizontal distribution factor, a retrieval algorithm called modified regression empirical and model-oriented statistical (M-M) based on the volterra integration theory is proposed. Compared with the model-oriented statistical and volterra integration (MOSVI) algorithm, the biggest difference is that the M-M algorithm is based on the modified regression empirical algorithm rather than the linear regression formula to retrieve the value of near-surface rainfall rate. Half of the empirical parameters are reduced in the weighted integral work and a smaller average relative error is received while the rainfall rate is less than 100 mm/h. Therefore, the algorithm proposed in this paper can obtain high-precision rainfall information.

A comparison of methods for determining soil water availability in two sites in Panama with similar rainfall but distinct tree communities

Treesearch

Thomas A. Kursar; Bettina M. J. Engelbrecht; Melvin T. Tyree

2005-01-01

Plant productivity, distribution and diversity in tropical rain forests correlate with water availability. Water availability is determined by rainfall and also by the available water capacity of the soil. However, while rainfall is recognized as important, linkages between plant distribution and differences among soils in available water capacity have not been...

Application of Radar-Based Accumulated Rainfall Products for Early Detection of Heavy Rainfall Occurrence

NASA Astrophysics Data System (ADS)

Nishiyama, K.; Wakimizu, K.; Yokota, I.; Tsukahara, K.; Moriyama, T.

2016-12-01

In Japan, river and debris flow disasters have been frequently caused by heavy rainfall occurrence under the influence of the activity of a stationary front and associated inflow of a large amount of moisture into the front. However, it is very difficult to predict numerically-based heavy rainfall and associated landslide accurately. Therefore, the use of meteorological radar information is required for enhancing decision-making ability to urge the evacuation of local residents by local government staffs prior to the occurrence of the heavy rainfall disaster. It is also desirable that the local residents acquire the ability to determine the evacuation immediately after confirming radar information by themselves. Actually, it is difficult for untrained local residents and local government staffs to easily recognize where heavy rainfall occurs locally for a couple of hours. This reason is that the image of radar echoes is equivalent to instant electromagnetic distribution measured per a couple of minutes, and the distribution of the radar echoes moves together with the movement of a synoptic system. Therefore, in this study, considering that the movement of radar echoes also may stop in a specific area if stationary front system becomes dominant, radar-based accumulated rainfall information is defined here. The rainfall product is derived by the integration of radar intensity measured every ten minutes during previous 1 hours. Using this product, it was investigated whether and how the radar-based accumulated rainfall displayed at an interval of ten minutes can be applied for early detection of heavy rainfall occurrence. The results are summarized as follows. 1) Radar-based accumulated rainfall products could confirm that some of stationary heavy rainfall systems had already appeared prior to disaster occurrence, and clearly identify the movement of heavy rainfall area. 2) Moreover, accumulated area of rainfall could be visually and easily identified, compared with time-series (movie) of real-time radar-based rainfall intensity. Therefore, the accumulated rainfall distribution provides effective information for early detection of heavy rainfall causing disasters through the training of local residents and local government staffs who have no meteorologically-technical knowledge.

Attributing Asymmetric Productivity Responses to Internal Ecosystem Dynamics and External Drivers Using Probabilistic Models

NASA Astrophysics Data System (ADS)

Parolari, A.; Goulden, M.

2017-12-01

A major challenge to interpreting asymmetric changes in ecosystem productivity is the attribution of these changes to external climate forcing or to internal ecophysiological processes that respond to these drivers (e.g., photosynthesis response to drying soil). For example, positive asymmetry in productivity can result from either positive skewness in the distribution of annual rainfall amount or from negative curvature in the productivity response to annual rainfall. To analyze the relative influences of climate and ecosystem dynamics on both positive and negative asymmetry in multi-year ANPP experiments, we use a multi-scale coupled ecosystem water-carbon model to interpret field experimental results that span gradients of rainfall skewness and ANPP response curvature. The model integrates rainfall variability, soil moisture dynamics, and net carbon assimilation from the daily to inter-annual scales. From the underlying physical basis of the model, we compute the joint probability distribution of the minimum and maximum ANPP for an annual ANPP experiment of N years. The distribution is used to estimate the likelihood that either positive or negative asymmetry will be observed in an experiment, given the annual rainfall distribution and the ANPP response curve. We estimate the total asymmetry as the mode of this joint distribution and the relative contribution attributable to rainfall skewness as the mode for a linear ANPP response curve. Applied to data from several long-term ANPP experiments, we find that there is a wide range of observed ANPP asymmetry (positive and negative) and a spectrum of contributions from internal and external factors. We identify the soil water holding capacity relative to the mean rain event depth as a critical ecosystem characteristic that controls the non-linearity of the ANPP response and positive curvature at high rainfall. Further, the seasonal distribution of rainfall is shown to control the presence or absence of negative curvature at low rainfall. Therefore, a combination of rooting depth, soil texture, and climate seasonality contribute to ANPP response curvature and its contribution to overall observed asymmetry.

Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

NASA Astrophysics Data System (ADS)

Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka

2016-04-01

Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our hierarchical MC model with the semi-parametric model in preserving rainfall variability in daily, monthly, and multi-year scales. To calibrate the parameters of both models and assess their ability to preserve observed statistics, we have used ground based data from 15 raingauge stations around Australia, which consist a wide range of climate zones including coastal, monsoonal, and arid climate characteristics. In preliminary results, both models show comparative performances in preserving the multi-year variability of rainfall depth and occurrence. However, the semi-parametric model shows a tendency of overestimating the mean rainfall depth, while our model shows a tendency of overestimating the number of wet days. We will discuss further the relative merits of the both models for hydrology simulation in the presentation.

Extreme rainfall-induced landslide changes based on landslide susceptibility in China, 1998-2015

NASA Astrophysics Data System (ADS)

Li, Weiyue; Liu, Chun; Hong, Yang

2017-04-01

Nowadays, landslide has been one of the most frequent and seriously widespread natural hazards all over the world. Rainfall, especially heavy rainfall is a trigger to cause the landslide occurrence, by increasing soil pore water pressures. In China, rainfall-induced landslides have risen up over to 90% of the total number. Rainfall events sometimes generate a trend of extremelization named rainfall extremes that induce the slope failure suddenly and severely. This study shows a method to simulate the rainfall-induced landslide spatio-temporal distribution on the basis of the landslide susceptibility index. First, the study on landslide susceptibility in China is introduced. We set the values of the index to the range between 0 and 1. Second, we collected TRMM 3B42 precipitation products spanning the years 1998-2015 and extracted the daily rainfall events greater than 50mm/day as extreme rainfall. Most of the rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours. The combination of these two aspects can be exploited to simulate extreme rainfall-induced landslide distribution and illustrate the changes in 17 years. This study shows a useful tool to be part of rainfall-induced landslide simulation methodology for landslide early warning.

Impacts of the seasonal distribution of rainfall on vegetation productivity across the Sahel

NASA Astrophysics Data System (ADS)

Zhang, Wenmin; Brandt, Martin; Tong, Xiaoye; Tian, Qingjiu; Fensholt, Rasmus

2018-01-01

Climate change in drylands has caused alterations in the seasonal distribution of rainfall including increased heavy-rainfall events, longer dry spells, and a shifted timing of the wet season. Yet the aboveground net primary productivity (ANPP) in drylands is usually explained by annual-rainfall sums, disregarding the influence of the seasonal distribution of rainfall. This study tested the importance of rainfall metrics in the wet season (onset and cessation of the wet season, number of rainy days, rainfall intensity, number of consecutive dry days, and heavy-rainfall events) for growing season ANPP. We focused on the Sahel and northern Sudanian region (100-800 mm yr-1) and applied daily satellite-based rainfall estimates (CHIRPS v2.0) and growing-season-integrated normalized difference vegetation index (NDVI; MODIS) as a proxy for ANPP over the study period: 2001-2015. Growing season ANPP in the arid zone (100-300 mm yr-1) was found to be rather insensitive to variations in the seasonal-rainfall metrics, whereas vegetation in the semi-arid zone (300-700 mm yr-1) was significantly impacted by most metrics, especially by the number of rainy days and timing (onset and cessation) of the wet season. We analysed critical breakpoints for all metrics to test if vegetation response to changes in a given rainfall metric surpasses a threshold beyond which vegetation functioning is significantly altered. It was shown that growing season ANPP was particularly negatively impacted after > 14 consecutive dry days and that a rainfall intensity of ˜ 13 mm day-1 was detected for optimum growing season ANPP. We conclude that the number of rainy days and the timing of the wet season are seasonal-rainfall metrics that are decisive for favourable vegetation growth in the semi-arid Sahel and need to be considered when modelling primary productivity from rainfall in the drylands of the Sahel and elsewhere.

A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall

NASA Astrophysics Data System (ADS)

Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto; Marrocu, Marino

2017-03-01

Distribution mapping has been identified as the most efficient approach to bias-correct climate model rainfall, while reproducing its statistics at spatial and temporal resolutions suitable to run hydrologic models. Yet its implementation based on empirical distributions derived from control samples (referred to as nonparametric distribution mapping) makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of climate model results, and may lead to biases, especially in extreme rainfall estimation. To address these shortcomings, we propose a methodology for simultaneous bias correction and high-resolution downscaling of climate model rainfall products that uses: (a) a two-component theoretical distribution model (i.e., a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates), and (b) proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data. We assess the performance of the suggested parametric approach relative to the nonparametric one, using daily raingauge measurements from a dense network in the island of Sardinia (Italy), and rainfall data from four GCM/RCM model chains of the ENSEMBLES project. The obtained results shed light on the competitive advantages of the parametric approach, which is proved more accurate and considerably less sensitive to the characteristics of the calibration period, independent of the GCM/RCM combination used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available data.

Parameter Estimation for a Model of Space-Time Rainfall

NASA Astrophysics Data System (ADS)

Smith, James A.; Karr, Alan F.

1985-08-01

In this paper, parameter estimation procedures, based on data from a network of rainfall gages, are developed for a class of space-time rainfall models. The models, which are designed to represent the spatial distribution of daily rainfall, have three components, one that governs the temporal occurrence of storms, a second that distributes rain cells spatially for a given storm, and a third that determines the rainfall pattern within a rain cell. Maximum likelihood and method of moments procedures are developed. We illustrate that limitations on model structure are imposed by restricting data sources to rain gage networks. The estimation procedures are applied to a 240-mi2 (621 km2) catchment in the Potomac River basin.

Effects of Raindrop Shape Parameter on the Simulation of Plum Rains

NASA Astrophysics Data System (ADS)

Mei, H.; Zhou, L.; Li, X.; Huang, X.; Guo, W.

2017-12-01

The raindrop shape parameter of particle distribution is generally set as constant in a Double-moment Bulk Microphysics Scheme (DBMS) using Gama distribution function though which suggest huge differences in time and space according to observations. Based on Milbrandt 2-mon(MY) DBMS, four cases during Plum Rains season are simulated coupled with four empirical relationships between shape parameter (μr) and slope parameter of raindrop which have been concluded from observations of raindrop distributions. The analysis of model results suggest that μr have some influences on rainfall. Introducing the diagnostic formulas of μr may have some improvement on systematic biases of 24h accumulated rainfall and show some correction ability on local characteristics of rainfall distribution. Besides,the tendency to improve strong rainfall could be sensitive to μr. With the improvement of the diagnosis of μr using the empirically diagnostic formulas, μr increases generally in the middle- and lower-troposphere and decreases with the stronger rainfall. Its conclued that, the decline in raindrop water content and the increased raindrop mass-weighted average terminal velocity directly related to μr are the direct reasons of variations in the precipitation.On the other side, the environmental conditions including relative humidity and dynamical parameters are the key indirectly causes which has close relationships with the changes in cloud particles and rainfall distributions.Furthermore,the differences in the scale of improvement between the weak and heavy rainfall mainly come from the distinctions of response features about their variable fields respectively. The extent of variation in the features of cloud particles in warm clouds of heavy rainfall differs greatly from that of weak rainfall, though they share the same trend of variation. On the conditions of weak rainfall, the response of physical characteristics to μr performed consistent trends and some linear features. However, environmental conditions of relative humidity and dynamical parameters perform strong and vertically deep adjustments in the heavy precipitation with vigorous cloud systems. In this case, the microphysical processes and environmental conditions experience complex interactions with each other and no significant laws could be concluded.

Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.

1990-01-01

Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.

Sub-seasonal behaviour of Asian summer monsoon under a changing climate: assessments using CMIP5 models

NASA Astrophysics Data System (ADS)

Sooraj, K. P.; Terray, Pascal; Xavier, Prince

2016-06-01

Numerous global warming studies show the anticipated increase in mean precipitation with the rising levels of carbon dioxide concentration. However, apart from the changes in mean precipitation, the finer details of daily precipitation distribution, such as its intensity and frequency (so called daily rainfall extremes), need to be accounted for while determining the impacts of climate changes in future precipitation regimes. Here we examine the climate model projections from a large set of Coupled Model Inter-comparison Project 5 models, to assess these future aspects of rainfall distribution over Asian summer monsoon (ASM) region. Our assessment unravels a north-south rainfall dipole pattern, with increased rainfall over Indian subcontinent extending into the western Pacific region (north ASM region, NASM) and decreased rainfall over equatorial oceanic convergence zone over eastern Indian Ocean region (south ASM region, SASM). This robust future pattern is well conspicuous at both seasonal and sub-seasonal time scales. Subsequent analysis, using daily rainfall events defined using percentile thresholds, demonstrates that mean rainfall changes over NASM region are mainly associated with more intense and more frequent extreme rainfall events (i.e. above 95th percentile). The inference is that there are significant future changes in rainfall probability distributions and not only a uniform shift in the mean rainfall over the NASM region. Rainfall suppression over SASM seems to be associated with changes involving multiple rainfall events and shows a larger model spread, thus making its interpretation more complex compared to NASM. Moisture budget diagnostics generally show that the low-level moisture convergence, due to stronger increase of water vapour in the atmosphere, acts positively to future rainfall changes, especially for heaviest rainfall events. However, it seems that the dynamic component of moisture convergence, associated with vertical motion, shows a strong spatial and rainfall category dependency, sometimes offsetting the effect of the water vapour increase. Additionally, we found that the moisture convergence is mainly dominated by the climatological vertical motion acting on the humidity changes and the interplay between all these processes proves to play a pivotal role for regulating the intensities of various rainfall events in the two domains.

Modelling Ecuador's rainfall distribution according to geographical characteristics.

NASA Astrophysics Data System (ADS)

Tobar, Vladimiro; Wyseure, Guido

2017-04-01

It is known that rainfall is affected by terrain characteristics and some studies had focussed on its distribution over complex terrain. Ecuador's temporal and spatial rainfall distribution is affected by its location on the ITCZ, the marine currents in the Pacific, the Amazon rainforest, and the Andes mountain range. Although all these factors are important, we think that the latter one may hold a key for modelling spatial and temporal distribution of rainfall. The study considered 30 years of monthly data from 319 rainfall stations having at least 10 years of data available. The relatively low density of stations and their location in accessible sites near to main roads or rivers, leave large and important areas ungauged, making it not appropriate to rely on traditional interpolation techniques to estimate regional rainfall for water balance. The aim of this research was to come up with a useful model for seasonal rainfall distribution in Ecuador based on geographical characteristics to allow its spatial generalization. The target for modelling was the seasonal rainfall, characterized by nine percentiles for each one of the 12 months of the year that results in 108 response variables, later on reduced to four principal components comprising 94% of the total variability. Predictor variables for the model were: geographic coordinates, elevation, main wind effects from the Amazon and Coast, Valley and Hill indexes, and average and maximum elevation above the selected rainfall station to the east and to the west, for each one of 18 directions (50-135°, by 5°) adding up to 79 predictors. A multiple linear regression model by the Elastic-net algorithm with cross-validation was applied for each one of the PC as response to select the most important ones from the 79 predictor variables. The Elastic-net algorithm deals well with collinearity problems, while allowing variable selection in a blended approach between the Ridge and Lasso regression. The model fitting produced explained variances of 59%, 81%, 49% and 17% for PC1, PC2, PC3 and PC4, respectively, backing up the hypothesis of good correlation between geographical characteristics and seasonal rainfall patterns (comprised in the four principal components). With the obtained coefficients from the regression, the 108 rainfall percentiles for each station were back estimated giving very good results when compared with the original ones, with an overall 60% explained variance.

Temporal and spatial variations of rainfall erosivity in Southern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Ming-Hsi; Lin, Huan-Hsuan; Chu, Chun-Kuang

2014-05-01

Soil erosion models are essential in developing effective soil and water resource conservation strategies. Soil erosion is generally evaluated using the Universal Soil Loss Equation (USLE) with an appropriate regional scale description. Among factors in the USLE model, the rainfall erosivity index (R) provides one of the clearest indications of the effects of climate change. Accurate estimation of rainfall erosivity requires continuous rainfall data; however, such data rarely demonstrate good spatial and temporal coverage. The data set consisted of 9240 storm events for the period 1993 to 2011, monitored by 27 rainfall stations of the Central Weather Bureau (CWB) in southern Taiwan, was used to analyze the temporal-spatial variations of rainfall erosivity. The spatial distribution map was plotted based on rainfall erosivity by the Kriging interpolation method. Results indicated that rainfall erosivity is mainly concentrated in rainy season from June to November typically contributed 90% of the yearly R factor. The temporal variations of monthly rainfall erosivity during June to November and annual rainfall erosivity have increasing trend from 1993 to 2011. There is an increasing trend from southwest to northeast in spatial distribution of rainfall erosivity in southern Taiwan. The results further indicated that there is a higher relationship between elevation and rainfall erosivity. The method developed in this study may also be useful for sediment disasters on Climate Change.

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia

2018-03-01

Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.

Mapping the rainfall distribution for irrigation planning in dry season at pineapple plantation, Lampung Province, Indonesia (Study case at Great Giant Pineapple Co. Ltd.)

NASA Astrophysics Data System (ADS)

Cahyono, P.; Astuti, N. K.; Purwito; Rahmat, A.

2018-03-01

One of the problems caused by climate change is unpredictable of the dry season. Understanding when the dry season will start is very important to planning the irrigation schedule especially on large plantation. Data of rainfall for 30 years in Lampung, especially in Pineapple Plantation show that dry month occurs from June to October. If in two decadals (ten days period) rainfall less than 100 mm then it is predicted that next decadal will be dry season. Great Giant Pineapple Co. Ltd. has 32,000 hectares plantation area and located in three regencies at Lampung Province, Indonesia with varies rainfall between regions within a plantation. Therefore, monitoring the rainfall distribution by using ombrometer installed at 10 representative location points can be used to determine irrigation period at the beginning of dry season. Mapping method using the server program and data source is from 10 monitoring rainfall stations installed at the observed points. Preparation of rainfall distribution mapping is important to know the beginning of the dry season and thus planning the irrigation. The results show that 2nd decadal of April is indicated as the starting time of dry season, which is similar with Indonesian government for climate agency’s result.

Rainfall Data Simulation

Treesearch

T.L. Rogerson

1980-01-01

A simple simulation model to predict rainfall for individual storms in central Arkansas is described. Output includes frequency distribution tables for days between storms and for storm size classes; a storm summary by day number (January 1 = 1 and December 31 = 365) and rainfall amount; and an annual storm summary that includes monthly values for rainfall and number...

Some analysis on the diurnal variation of rainfall over the Atlantic Ocean

NASA Technical Reports Server (NTRS)

Gill, T.; Perng, S.; Hughes, A.

1981-01-01

Data collected from the GARP Atlantic Tropical Experiment (GATE) was examined. The data were collected from 10,000 grid points arranged as a 100 x 100 array; each grid covered a 4 square km area. The amount of rainfall was measured every 15 minutes during the experiment periods using c-band radars. Two types of analyses were performed on the data: analysis of diurnal variation was done on each of grid points based on the rainfall averages at noon and at midnight, and time series analysis on selected grid points based on the hourly averages of rainfall. Since there are no known distribution model which best describes the rainfall amount, nonparametric methods were used to examine the diurnal variation. Kolmogorov-Smirnov test was used to test if the rainfalls at noon and at midnight have the same statistical distribution. Wilcoxon signed-rank test was used to test if the noon rainfall is heavier than, equal to, or lighter than the midnight rainfall. These tests were done on each of the 10,000 grid points at which the data are available.

A Bayesian beta distribution model for estimating rainfall IDF curves in a changing climate

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; Kwon, Hyun-Han; Kim, Jin-Young

2016-09-01

The estimation of intensity-duration-frequency (IDF) curves for rainfall data comprises a classical task in hydrology studies to support a variety of water resources projects, including urban drainage and the design of flood control structures. In a changing climate, however, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to poor estimates of rainfall intensity quantiles. Climate change scenarios built on General Circulation Models offer a way to access and estimate future changes in spatial and temporal rainfall patterns at the daily scale at the utmost, which is not as fine temporal resolution as required (e.g. hours) to directly estimate IDF curves. In this paper we propose a novel methodology based on a four-parameter beta distribution to estimate IDF curves conditioned on the observed (or simulated) daily rainfall, which becomes the time-varying upper bound of the updated nonstationary beta distribution. The inference is conducted in a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters when building the IDF curves. The proposed model is tested using rainfall data from four stations located in South Korea and projected climate change Representative Concentration Pathways (RCPs) scenarios 6 and 8.5 from the Met Office Hadley Centre HadGEM3-RA model. The results show that the developed model fits the historical data as good as the traditional Generalized Extreme Value (GEV) distribution but is able to produce future IDF curves that significantly differ from the historically based IDF curves. The proposed model predicts for the stations and RCPs scenarios analysed in this work an increase in the intensity of extreme rainfalls of short duration with long return periods.

Rainfall Morphology in Semi-Tropical Convergence Zones

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Ferrier, Brad S.; Ray, Peter S.

2000-01-01

Central Florida is the ideal test laboratory for studying convergence zone-induced convection. The region regularly experiences sea breeze fronts and rainfall-induced outflow boundaries. The focus of this study is the common yet poorly-studied convergence zone established by the interaction of the sea breeze front and an outflow boundary. Previous studies have investigated mechanisms primarily affecting storm initiation by such convergence zones. Few have focused on rainfall morphology yet these storms contribute a significant amount precipitation to the annual rainfall budget. Low-level convergence and mid-tropospheric moisture have both been shown to correlate with rainfall amounts in Florida. Using 2D and 3D numerical simulations, the roles of low-level convergence and mid-tropospheric moisture in rainfall evolution are examined. The results indicate that time-averaged, vertical moisture flux (VMF) at the sea breeze front/outflow convergence zone is directly and linearly proportional to initial condensation rates. This proportionality establishes a similar relationship between VMF and initial rainfall. Vertical moisture flux, which encompasses depth and magnitude of convergence, is better correlated to initial rainfall production than surface moisture convergence. This extends early observational studies which linked rainfall in Florida to surface moisture convergence. The amount and distribution of mid-tropospheric moisture determines how rainfall associated with secondary cells develop. Rainfall amount and efficiency varied significantly over an observable range of relative humidities in the 850- 500 mb layer even though rainfall evolution was similar during the initial or "first-cell" period. Rainfall variability was attributed to drier mid-tropospheric environments inhibiting secondary cell development through entrainment effects. Observationally, 850-500 mb moisture structure exhibits wider variability than lower level moisture, which is virtually always present in Florida. A likely consequence of the variability in 850-500 moisture is a stronger statistical correlation to rainfall, which observational studies have noted. The study indicates that vertical moisture flux forcing at convergence zones is critical in determining rainfall in the initial stage of development but plays a decreasing role in rainfall evolution as the system matures. The mid-tropospheric moisture (e.g. environment) plays an increasing role in rainfall evolution as the system matures. This suggests the need to improve measurements of magnitude/depth of convergence and mid-tropospheric moisture distribution. It also highlights the need for better parameterization of entrainment and vertical moisture distribution in larger-scale models.

Congo Basin rainfall climatology: can we believe the climate models?

PubMed

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

The Variation of Tropical Cyclone Rainfall within the North Atlantic and Pacific as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward; Pierce, Harold; Adler, Robert

1999-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations in the North Atlantic and in three equal geographical regions of the North Pacific (i.e., Western, Central, and Eastern North Pacific). These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the 1987-1989, 1991-1998 North Atlantic and Pacific rainfall during June-November when tropical cyclones are most abundant. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from the Defence Meteorological Satellite Program (DMSP) Special Sensor Microwave/ Radiometer (SSM/I) observations within 444 km radius of the center of those North Atlantic and Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are then multiplied by the number of hours in a given month. Mean monthly rainfall amounts are also constructed for all the other North Atlantic and Pacific raining systems during this eleven year period for the purpose of estimating the geographical distribution and intensity of rainfall contributed by non-tropical cyclone systems. Further, the combination of the non-tropical cyclone and tropical cyclone (i.e., total) rainfall is constructed to delineate the fractional amount that tropical cyclones contributed to the total North Pacific rainfall.

Comparisons of Rain Estimates from Ground Radar and Satellite Over Mountainous Regions

NASA Technical Reports Server (NTRS)

Lin, Xin; Kidd, Chris; Tao, Jing; Barros, Ana

2016-01-01

A high-resolution rainfall product merging surface radar and an enhanced gauge network is used as a reference to examine two operational surface radar rainfall products over mountain areas. The two operational rainfall products include radar-only and conventional-gauge-corrected radar rainfall products. Statistics of rain occurrence and rain amount including their geographical, seasonal, and diurnal variations are examined using 3-year data. It is found that the three surface radar rainfall products in general agree well with one another over mountainous regions in terms of horizontal mean distributions of rain occurrence and rain amount. Frequency of rain occurrence and fraction of rain amount also indicate similar distribution patterns as a function of rain intensity. The diurnal signals of precipitation over mountain ridges are well captured and joint distributions of coincident raining samples indicate reasonable correlations during both summer and winter. Factors including undetected low-level precipitation, limited availability of gauges for correcting the Z-R relationship over the mountains, and radar beam blocking by mountains are clearly noticed in the two conventional radar rainfall products. Both radar-only and conventional-gauge-corrected radar rainfall products underestimate the rain occurrence and fraction of rain amount at intermediate and heavy rain intensities. Comparison of PR and TMI against a surface radar-only rainfall product indicates that the PR performs equally well with the high-resolution radar-only rainfall product over complex terrains at intermediate and heavy rain intensities during the summer and winter. TMI, on the other hand, requires improvement to retrieve wintertime precipitation over mountain areas.

Holocene cyclic climatic variations and the role of the Pacific Ocean as recorded in varved sediments from northeastern China

NASA Astrophysics Data System (ADS)

Chu, Guoqiang; Sun, Qing; Xie, Manman; Lin, Yuan; Shang, Wenyu; Zhu, Qingzen; Shan, Yabing; Xu, Deke; Rioual, Patrick; Wang, Luo; Liu, Jiaqi

2014-10-01

We present an n-alkane and compound-specific carbon isotope record of the past 9 ka from the annually laminated sedimentary sequence of Lake Xiaolongwan, northeastern China. The n-alkane distribution suggests that Lake Xiaolongwan has undergone a shift from an oligotrophic state with low algal production and little emergent/submerged macrophytes in the early Holocene, to a eutrophic state with high algal production and abundant emergent/submerged macrophytes since the middle Holocene. The pattern of variation observed in the biomarker proxies ACL (the n-alkane average chain length), Paq (aquatic macrophyte versus aquatic macrophyte and terrestrial plant ratio), and LPTP (lake productivity/terrigenous organic production) is throughout the record similar to that of the total organic carbon. The variation of compound-specific carbon isotopic values in the middle- and short-chain alkanes was mainly regulated by lake productivity and the accumulating organic pool through time. In this forested region, where the vegetation is dominated by C3 plants, the long-chain n-alkanes (C27-C31) are predominantly derived from leaf wax lipids. The compound-specific δ13C27-31 value is sensitive to effective precipitation, and therefore represents a useful indicator of regional monsoonal precipitation. Spectral analysis on the δ13C27-31 time series reveals significant periodicities of 87-89, 205-212, 1020-1050 and 1750-2041 years. On the centennial timescale, the quasi-periodicities around 88 and 210 years suggest a strong link between solar activity and monsoon rainfall. The millennial monsoon cycle in northeastern China is associated with sea surface temperature (SST) variations in two active centers of the summer monsoon, the western Pacific Subtropical High (WPSH) and the Okhotsk High. Increasing SST in the subtropical sea may cause a northwards shift of the WPSH, which extends the monsoon rain band (Meiyu) to northeastern China, and thus increasing rainfall in that region. Meanwhile, decreasing SST in the Okhotsk Sea may strengthen the Okhotsk high, bringing more moisture into northeastern China. We suggest that the Pacific Ocean is a main regulator for summer monsoon rainfall in northeastern China at present and at different time scales during the Holocene.

Modelling soil erosion in rainfed vineyards of northeast of Spain under climate change: effects of increasing rainfall intensity

NASA Astrophysics Data System (ADS)

Concepción Ramos, Maria

2017-04-01

This aim of the research was to analyse the effect of rainfall distribution and intensity on soil erosion in vines cultivated in the Mediterranean under the projected climate change scenario. The simulations were done at plot scale using the WEPP model. Climatic data for the period 1996-2014 were obtained from a meteorological station located 6km far from the plot. Soil characteristics such as texture, organic matter content, water retention capacity and infiltration were analysed. Runoff and soil losses were measured at four locations within the plot during 4 years and used to calibrate and validate the model. According to evidences recorded in the area, changes of rainfall intensities of 10 and 20% were considered for different rainfall distributions. The simulations were extended to the predicted changes for 2030, 2050 and 2070 based on the HadGEM2-CC under the Representative Concentration Pathways (RCPs) 8.5 scenario. WEPP model provided a suitable prediction of the seasonal runoff and erosion as simulated relatively well the runoff and erosion of the most important events although some deficiencies were found for those events that produced low runoff. The simulation confirmed the contribution of the extreme events to annual erosion rates in 70%, on average. The model responded to changes in precipitation predicted under a climate change scenario with a decrease of runoff and erosion, and with higher erosion rates for an increase in rainfall intensity. A 10% increase may imply erosion rates up to 22% greater for the scenario 2030, and despite the predicted decrease in precipitation for the scenario 2050, soil losses may be up to 40% greater than at present for some rainfall distributions and intensity rainfall increases of 20%. These findings show the need of considering rainfall intensity as one of the main driven factors when soil erosion rates under climate change are predicted. Keywords: extreme events, rainfall distribution, runoff, soil losses, wines, WEPP.

On the Relationship of Rainfall and Temperature across Amazonia

NASA Astrophysics Data System (ADS)

Ribeiro Lima, C. H.; AghaKouchak, A.

2017-12-01

Extreme droughts in Amazonia seem to become more frequent and have been associated with local and global impacts on society and the ecosystem. The understanding of the dynamics and causes of Amazonia droughts have attracted some attention in the last years and pose several challenges for the scientific community. For instance, in previous work we have identified, based on empirical data, a compounding effect during Amazonia droughts: periods of low rainfall are always associated with positive anomalies of near surface air temperature. This inverse relationship of temperature and rainfall appears at multiple time scales and its intensity varies across Amazonia. To our knowledge, these findings have not been properly addressed in the literature, being not clear whether there is a causal relationship between these two variables, and in this case, which one leads the other one, or they are just responding to the same causal factor. Here we investigate the hypothesis that high temperatures during drought periods are a major response to an increase in the shortwave radiation (due to the lack of clouds) not compensating by an expected increase in the evapotranspiration from the rainforest. Our empirical analysis is based on observed series of daily temperature and rainfall over the Brazilian Amazonia and reanalysis data of cloud cover, outgoing longwave radiation (OLR) and moisture fluxes. The ability of Global Circulation Models (GCMs) to reproduce such compounding effect is also investigated for the historical period and for future RCP scenarios of global climate change. Preliminary results show that this is a plausible hypothesis, despite the complexity of land-atmosphere processes of mass and energy fluxes in Amazonia. This work is a step forward in better understanding the compounding effects of rainfall and temperature on Amazonia droughts, and what changes one might expect in a future warming climate.

Rainfall continuous time stochastic simulation for a wet climate in the Cantabric Coast

NASA Astrophysics Data System (ADS)

Rebole, Juan P.; Lopez, Jose J.; Garcia-Guzman, Adela

2010-05-01

Rain is the result of a series of complex atmospheric processes which are influenced by numerous factors. This complexity makes its simulation practically unfeasible from a physical basis, advising the use of stochastic diagrams. These diagrams, which are based on observed characteristics (Todorovic and Woolhiser, 1975), allow the introduction of renewal alternating processes, that account for the occurrence of rainfall at different time lapses (Markov chains are a particular case, where lapses can be described by exponential distributions). Thus, a sequential rainfall process can be defined as a temporal series in which rainfall events (periods in which rainfall is recorded) alternate with non rain events (periods in which no rainfall is recorded). The variables of a temporal rain sequence have been characterized (duration of the rainfall event, duration of the non rainfall event, average intensity of the rain in the rain event, and a temporal distribution of the amount of rain in the rain event) in a wet climate such as that of the coastal area of Guipúzcoa. The study has been performed from two series recorded at the meteorological stations of Igueldo-San Sebastián and Fuenterrabia / Airport (data every ten minutes and for its hourly aggregation). As a result of this work, the variables satisfactorily fitted the following distribution functions: the duration of the rain event to a exponential function; the duration of the dry event to a truncated exponential mixed distribution; the average intensity to a Weibull distribution; and the distribution of the rain fallen to the Beta distribution. The characterization was made for an hourly aggregation of the recorded interval of ten minutes. The parameters of the fitting functions were better obtained by means of the maximum likelihood method than the moment method. The parameters obtained from the characterization were used to develop a stochastic rainfall process simulation model by means of a three states Markov chain (Hutchinson, 1990), performed in an hourly basis by García-Guzmán (1993) and Castro et al. (1997, 2005 ). Simulation process results were valid in the hourly case for all the four described variables, with a slightly better response in Fuenterrabia than in Igueldo. In summary, all the variables were better simulated in Fuenterrabia than in Igueldo. Fuenterrabia data series is shorter and with longer sequences without missing data, compared to Igueldo. The latter shows higher number of missing data events, whereas its mean duration is longer in Fuenterrabia.

Exploratory analysis of rainfall events in Coimbra, Portugal: variability of raindrop characteristics

NASA Astrophysics Data System (ADS)

Carvalho, S. C. P.; de Lima, M. I. P.; de Lima, J. L. M. P.

2012-04-01

Laser disdrometers can monitor efficiently rainfall characteristics at small temporal scales, providing data on rain intensity, raindrop diameter and fall speed, and raindrop counts over time. This type of data allows for the increased understanding of the rainfall structure at small time scales. Of particular interest for many hydrological applications is the characterization of the properties of extreme events, including the intra-event variability, which are affected by different factors (e.g. geographical location, rainfall generating mechanisms). These properties depend on the microphysical, dynamical and kinetic processes that interact to produce rain. In this study we explore rainfall data obtained during two years with a laser disdrometer installed in the city of Coimbra, in the centre region of mainland Portugal. The equipment was developed by Thies Clima. The data temporal resolution is one-minute. Descriptive statistics of time series of raindrop diameter (D), fall speed, kinetic energy, and rain rate were studied at the event scale; for different variables, the average, maximum, minimum, median, variance, standard deviation, quartile, coefficient of variation, skewness and kurtosis were determined. The empirical raindrop size distribution, N(D), was also calculated. Additionally, the parameterization of rainfall was attempted by investigating the applicability of different theoretical statistical distributions to fit the empirical data (e.g. exponential, gamma and lognormal distributions). As expected, preliminary results show that rainfall properties and structure vary with rainfall type and weather conditions over the year. Although only two years were investigated, already some insight into different rain events' structure was obtained.

Climate Change Impact on Variability of Rainfall Intensity in Upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Worku, L. Y.

2015-12-01

Extreme rainfall events are major problems in Ethiopia with the resulting floods that usually could cause significant damage to agriculture, ecology, infrastructure, disruption to human activities, loss of property, loss of lives and disease outbreak. The aim of this study was to explore the likely changes of precipitation extreme changes due to future climate change. The study specifically focuses to understand the future climate change impact on variability of rainfall intensity-duration-frequency in Upper Blue Nile basin. Precipitations data from two Global Climate Models (GCMs) have been used in the study are HadCM3 and CGCM3. Rainfall frequency analysis was carried out to estimate quantile with different return periods. Probability Weighted Method (PWM) selected estimation of parameter distribution and L-Moment Ratio Diagrams (LMRDs) used to find the best parent distribution for each station. Therefore, parent distributions for derived from frequency analysis are Generalized Logistic (GLOG), Generalized Extreme Value (GEV), and Gamma & Pearson III (P3) parent distribution. After analyzing estimated quantile simple disaggregation model was applied in order to find sub daily rainfall data. Finally the disaggregated rainfall is fitted to find IDF curve and the result shows in most parts of the basin rainfall intensity expected to increase in the future. As a result of the two GCM outputs, the study indicates there will be likely increase of precipitation extremes over the Blue Nile basin due to the changing climate. This study should be interpreted with caution as the GCM model outputs in this part of the world have huge uncertainty.

A comparative study of mixed exponential and Weibull distributions in a stochastic model replicating a tropical rainfall process

NASA Astrophysics Data System (ADS)

Abas, Norzaida; Daud, Zalina M.; Yusof, Fadhilah

2014-11-01

A stochastic rainfall model is presented for the generation of hourly rainfall data in an urban area in Malaysia. In view of the high temporal and spatial variability of rainfall within the tropical rain belt, the Spatial-Temporal Neyman-Scott Rectangular Pulse model was used. The model, which is governed by the Neyman-Scott process, employs a reasonable number of parameters to represent the physical attributes of rainfall. A common approach is to attach each attribute to a mathematical distribution. With respect to rain cell intensity, this study proposes the use of a mixed exponential distribution. The performance of the proposed model was compared to a model that employs the Weibull distribution. Hourly and daily rainfall data from four stations in the Damansara River basin in Malaysia were used as input to the models, and simulations of hourly series were performed for an independent site within the basin. The performance of the models was assessed based on how closely the statistical characteristics of the simulated series resembled the statistics of the observed series. The findings obtained based on graphical representation revealed that the statistical characteristics of the simulated series for both models compared reasonably well with the observed series. However, a further assessment using the AIC, BIC and RMSE showed that the proposed model yields better results. The results of this study indicate that for tropical climates, the proposed model, using a mixed exponential distribution, is the best choice for generation of synthetic data for ungauged sites or for sites with insufficient data within the limit of the fitted region.

Global Distribution of Extreme Precipitation and High-Impact Landslides in 2010 Relative to Previous Years

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Adler, David; Peters-Lidard, Christa; Huffman, George

2012-01-01

It is well known that extreme or prolonged rainfall is the dominant trigger of landslides worldwide. While research has evaluated the spatiotemporal distribution of extreme rainfall and landslides at local or regional scales using in situ data, few studies have mapped rainfall-triggered landslide distribution globally due to the dearth of landslide data and consistent precipitation information. This study uses a newly developed Global Landslide Catalog (GLC) and a 13-year satellite-based precipitation record from TRMM data. For the first time, these two unique products provide the foundation to quantitatively evaluate the co-occurrence of precipitation and landslides globally. Evaluation of the GLC indicates that 2010 had a large number of high-impact landslide events relative to previous years. This study considers how variations in extreme and prolonged satellite-based rainfall are related to the distribution of landslides over the same time scales for three active landslide areas: Central America, the Himalayan Arc, and central-eastern China. Several test statistics confirm that TRMM rainfall generally scales with the observed increase in landslide reports and fatal events for 2010 and previous years over each region. These findings suggest that the co-occurrence of satellite precipitation and landslide reports may serve as a valuable indicator for characterizing the spatiotemporal distribution of landslide-prone areas in order to establish a global rainfall-triggered landslide climatology. This study characterizes the variability of satellite precipitation data and reported landslide activity at the globally scale in order to improve landslide cataloging, forecasting and quantify potential triggering sources at daily, monthly and yearly time scales.

Regional analysis of annual maximum rainfall using TL-moments method

NASA Astrophysics Data System (ADS)

Shabri, Ani Bin; Daud, Zalina Mohd; Ariff, Noratiqah Mohd

2011-06-01

Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments.

Interpolating Non-Parametric Distributions of Hourly Rainfall Intensities Using Random Mixing

NASA Astrophysics Data System (ADS)

Mosthaf, Tobias; Bárdossy, András; Hörning, Sebastian

2015-04-01

The correct spatial interpolation of hourly rainfall intensity distributions is of great importance for stochastical rainfall models. Poorly interpolated distributions may lead to over- or underestimation of rainfall and consequently to wrong estimates of following applications, like hydrological or hydraulic models. By analyzing the spatial relation of empirical rainfall distribution functions, a persistent order of the quantile values over a wide range of non-exceedance probabilities is observed. As the order remains similar, the interpolation weights of quantile values for one certain non-exceedance probability can be applied to the other probabilities. This assumption enables the use of kernel smoothed distribution functions for interpolation purposes. Comparing the order of hourly quantile values over different gauges with the order of their daily quantile values for equal probabilities, results in high correlations. The hourly quantile values also show high correlations with elevation. The incorporation of these two covariates into the interpolation is therefore tested. As only positive interpolation weights for the quantile values assure a monotonically increasing distribution function, the use of geostatistical methods like kriging is problematic. Employing kriging with external drift to incorporate secondary information is not applicable. Nonetheless, it would be fruitful to make use of covariates. To overcome this shortcoming, a new random mixing approach of spatial random fields is applied. Within the mixing process hourly quantile values are considered as equality constraints and correlations with elevation values are included as relationship constraints. To profit from the dependence of daily quantile values, distribution functions of daily gauges are used to set up lower equal and greater equal constraints at their locations. In this way the denser daily gauge network can be included in the interpolation of the hourly distribution functions. The applicability of this new interpolation procedure will be shown for around 250 hourly rainfall gauges in the German federal state of Baden-Württemberg. The performance of the random mixing technique within the interpolation is compared to applicable kriging methods. Additionally, the interpolation of kernel smoothed distribution functions is compared with the interpolation of fitted parametric distributions.

Sources, transport and deposition of terrestrial organic material: A case study from southwestern Africa

NASA Astrophysics Data System (ADS)

Herrmann, Nicole; Boom, Arnoud; Carr, Andrew S.; Chase, Brian M.; Granger, Robyn; Hahn, Annette; Zabel, Matthias; Schefuß, Enno

2016-10-01

Southwestern Africa's coastal marine mudbelt, a prominent Holocene sediment package, provides a valuable archive for reconstructing terrestrial palaeoclimates on the adjacent continent. While the origin of terrestrial inorganic material has been intensively studied, the sources of terrigenous organic material deposited in the mudbelt are yet unclear. In this study, plant wax derived n-alkanes and their compound-specific δ13C in soils, flood deposits and suspension loads from regional fluvial systems and marine sediments are analysed to characterize the origin of terrestrial organic material in the southwest African mudbelt. Soils from different biomes in the catchments of the Orange River and small west coast rivers show on average distinct n-alkane distributions and compound-specific δ13C values reflecting biome-specific vegetation types, most notably the winter rainfall associated Fynbos Biome of the southwestern Cape. In the fluvial sediment samples from the Orange River, changes in the n-alkane distributions and compound-specific δ13C compositions reveal an overprint by local vegetation along the river's course. The smaller west coast rivers show distinct signals, reflecting their small catchment areas and particular vegetation communities. Marine surface sediments spanning a transect from the northern mudbelt (29°S) to St. Helena Bay (33°S) reveal subtle, but spatially coherent, changes in n-alkane distributions and compound-specific δ13C, indicating the influence of Orange River sediments in the northern mudbelt, the increasing importance of terrigenous input from the adjacent western coastal biomes in the central mudbelt, and contributions from the Fynbos Biome to the southern mudbelt. These findings indicate the different sources of terrestrial organic material deposited in the mudbelt, and highlight the potential the mudbelt has to preserve evidence of environmental change from the adjacent continent.

Tropical Cyclones Feed More Heavy Rain in a Warmer Climate

NASA Technical Reports Server (NTRS)

Lau, K.-M.; Zhou, Y. P.; Wu, H.-T.

2007-01-01

The possible linkage of tropical cyclones (TC) to global warming is a hotly debated scientific topic, with immense societal impacts. Most of the debate has been focused on the issue of uncertainty in the use of non-research quality data for long-term trend analyses, especially with regard to TC intensity provided by TC forecasting centers. On the other hand, it is well known that TCs are associated with heavy rain during the processes of genesis and intensification, and that there are growing evidences that rainfall characteristics (not total rainfall) are most likely to be affected by global warming. Yet, satellite rainfall data have not been exploited in any recent studies of linkage between tropical cyclones (TC) and global warming. This is mostly due to the large uncertainties associated with detection of long-term trend in satellite rainfall estimates over the ocean. This problem, as we demonstrate in this paper, can be alleviated by examining rainfall distribution, rather than rainfall total. This paper is the first to use research-quality, satellite-derived rainfall from TRMM and GPCP over the tropical oceans to estimate shift in rainfall distribution during the TC season, and its relationships with TCs, and sea surface temperature (SST) in the two major ocean basins, the northern Atlantic and the northern Pacific for 1979-2005. From the rainfall distribution, we derive the TC contributions to rainfall in various extreme rainfall categories as a function to time. Our results show a definitive trend indicating that TCs are contributing increasingly to heavier rain events, i.e., intense TC's are more frequent in the last 27 years. The TC contribution to top 5% heavy rain has nearly doubled in the last two decades in the North Atlantic, and has increased by about 10% in the North Pacific. The different rate of increase in TC contribution to heavy rain may be related to the different rates of different rate of expansion of the warm pool (SST >2S0 C) area in the two oceans.

Ensemble flood simulation for a small dam catchment in Japan using 10 and 2 km resolution nonhydrostatic model rainfalls

NASA Astrophysics Data System (ADS)

Kobayashi, Kenichiro; Otsuka, Shigenori; Apip; Saito, Kazuo

2016-08-01

This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.

Effect of radar rainfall time resolution on the predictive capability of a distributed hydrologic model

NASA Astrophysics Data System (ADS)

Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.

2010-10-01

The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.

An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment

NASA Astrophysics Data System (ADS)

Smitha, P. S.; Narasimhan, B.; Sudheer, K. P.; Annamalai, H.

2018-01-01

Regional climate models (RCMs) are used to downscale the coarse resolution General Circulation Model (GCM) outputs to a finer resolution for hydrological impact studies. However, RCM outputs often deviate from the observed climatological data, and therefore need bias correction before they are used for hydrological simulations. While there are a number of methods for bias correction, most of them use monthly statistics to derive correction factors, which may cause errors in the rainfall magnitude when applied on a daily scale. This study proposes a sliding window based daily correction factor derivations that help build reliable daily rainfall data from climate models. The procedure is applied to five existing bias correction methods, and is tested on six watersheds in different climatic zones of India for assessing the effectiveness of the corrected rainfall and the consequent hydrological simulations. The bias correction was performed on rainfall data downscaled using Conformal Cubic Atmospheric Model (CCAM) to 0.5° × 0.5° from two different CMIP5 models (CNRM-CM5.0, GFDL-CM3.0). The India Meteorological Department (IMD) gridded (0.25° × 0.25°) observed rainfall data was considered to test the effectiveness of the proposed bias correction method. The quantile-quantile (Q-Q) plots and Nash Sutcliffe efficiency (NSE) were employed for evaluation of different methods of bias correction. The analysis suggested that the proposed method effectively corrects the daily bias in rainfall as compared to using monthly factors. The methods such as local intensity scaling, modified power transformation and distribution mapping, which adjusted the wet day frequencies, performed superior compared to the other methods, which did not consider adjustment of wet day frequencies. The distribution mapping method with daily correction factors was able to replicate the daily rainfall pattern of observed data with NSE value above 0.81 over most parts of India. Hydrological simulations forced using the bias corrected rainfall (distribution mapping and modified power transformation methods that used the proposed daily correction factors) was similar to those simulated by the IMD rainfall. The results demonstrate that the methods and the time scales used for bias correction of RCM rainfall data have a larger impact on the accuracy of the daily rainfall and consequently the simulated streamflow. The analysis suggests that the distribution mapping with daily correction factors can be preferred for adjusting RCM rainfall data irrespective of seasons or climate zones for realistic simulation of streamflow.

Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications

USGS Publications Warehouse

Husak, Gregory J.; Michaelsen, Joel C.; Funk, Christopher C.

2007-01-01

Evaluating a range of scenarios that accurately reflect precipitation variability is critical for water resource applications. Inputs to these applications can be provided using location- and interval-specific probability distributions. These distributions make it possible to estimate the likelihood of rainfall being within a specified range. In this paper, we demonstrate the feasibility of fitting cell-by-cell probability distributions to grids of monthly interpolated, continent-wide data. Future work will then detail applications of these grids to improved satellite-remote sensing of drought and interpretations of probabilistic climate outlook forum forecasts. The gamma distribution is well suited to these applications because it is fairly familiar to African scientists, and capable of representing a variety of distribution shapes. This study tests the goodness-of-fit using the Kolmogorov–Smirnov (KS) test, and compares these results against another distribution commonly used in rainfall events, the Weibull. The gamma distribution is suitable for roughly 98% of the locations over all months. The techniques and results presented in this study provide a foundation for use of the gamma distribution to generate drivers for various rain-related models. These models are used as decision support tools for the management of water and agricultural resources as well as food reserves by providing decision makers with ways to evaluate the likelihood of various rainfall accumulations and assess different scenarios in Africa. 

Annual Rainfall Maxima: Theoretical Estimation of the GEV Shape Parameter k Using Multifractal Models

NASA Astrophysics Data System (ADS)

Veneziano, D.; Langousis, A.; Lepore, C.

2009-12-01

The annual maximum of the average rainfall intensity in a period of duration d, Iyear(d), is typically assumed to have generalized extreme value (GEV) distribution. The shape parameter k of that distribution is especially difficult to estimate from either at-site or regional data, making it important to constraint k using theoretical arguments. In the context of multifractal representations of rainfall, we observe that standard theoretical estimates of k from extreme value (EV) and extreme excess (EE) theories do not apply, while estimates from large deviation (LD) theory hold only for very small d. We then propose a new theoretical estimator based on fitting GEV models to the numerically calculated distribution of Iyear(d). A standard result from EV and EE theories is that k depends on the tail behavior of the average rainfall in d, I(d). This result holds if Iyear(d) is the maximum of a sufficiently large number n of variables, all distributed like I(d); therefore its applicability hinges on whether n = 1yr/d is large enough and the tail of I(d) is sufficiently well known. One typically assumes that at least for small d the former condition is met, but poor knowledge of the upper tail of I(d) remains an obstacle for all d. In fact, in the case of multifractal rainfall, also the first condition is not met because, irrespective of d, 1yr/d is too small (Veneziano et al., 2009, WRR, in press). Applying large deviation (LD) theory to this multifractal case, we find that, as d → 0, Iyear(d) approaches a GEV distribution whose shape parameter kLD depends on a region of the distribution of I(d) well below the upper tail, is always positive (in the EV2 range), is much larger than the value predicted by EV and EE theories, and can be readily found from the scaling properties of I(d). The scaling properties of rainfall can be inferred also from short records, but the limitation remains that the result holds under d → 0 not for finite d. Therefore, for different reasons, none of the above asymptotic theories applies to Iyear(d). In practice, one is interested in the distribution of Iyear(d) over a finite range of averaging durations d and return periods T. Using multifractal representations of rainfall, we have numerically calculated the distribution of Iyear(d) and found that, although not GEV, the distribution can be accurately approximated by a GEV model. The best-fitting parameter k depends on d, but is insensitive to the scaling properties of rainfall and the range of return periods T used for fitting. We have obtained a default expression for k(d) and compared it with estimates from historical rainfall records. The theoretical function tracks well the empirical dependence on d, although it generally overestimates the empirical k values, possibly due to deviations of rainfall from perfect scaling. This issue is under investigation.

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

2012-01-01

Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

NASA Astrophysics Data System (ADS)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2017-11-01

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

Nonstationary Intensity-Duration-Frequency Curves for Drainge Infrastructure Coping with Climate Change

NASA Astrophysics Data System (ADS)

Kim, Byung Sik; Jeung, Se Jin; Lee, Dong Seop; Han, Woo Suk

2015-04-01

As the abnormal rainfall condition has been more and more frequently happen and serious by climate change and variabilities, the question whether the design of drainage system could be prepared with abnormal rainfall condition or not has been on the rise. Usually, the drainage system has been designed by rainfall I-D-F (Intensity-Duration-Frequency) curve with assumption that I-D-F curve is stationary. The design approach of the drainage system has limitation not to consider the extreme rainfall condition of which I-D-F curve is non-stationary by climate change and variabilities. Therefore, the assumption that the I-D-F curve is stationary to design drainage system maybe not available in the climate change period, because climate change has changed the characteristics of extremes rainfall event to be non-stationary. In this paper, design rainfall by rainfall duration and non-stationary I-D-F curve are derived by the conditional GEV distribution considering non-stationary of rainfall characteristics. Furthermore, the effect of designed peak flow with increase of rainfall intensity was analyzed by distributed rainfall-runoff model, S-RAT(Spatial Runoff Assessment Tool). Although there are some difference by rainfall duration, the traditional I-D-F curves underestimates the extreme rainfall events for high-frequency rainfall condition. As a result, this paper suggest that traditional I-D-F curves could not be suitable for the design of drainage system under climate change condition. Keywords : Drainage system, Climate Change, non-stationary, I-D-F curves This research was supported by a grant 'Development of multi-function debris flow control technique considering extreme rainfall event' [NEMA-Natural-2014-74] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of KOREA

Trends and spatial distribution of annual and seasonal rainfall in Ethiopia

USGS Publications Warehouse

Cheung, W.H.; Senay, G.B.; Singh, A.

2008-01-01

As a country whose economy is heavily dependent on low-productivity rainfed agriculture, rainfall trends are often cited as one of the more important factors in explaining various socio-economic problems such as food insecurity. Therefore, in order to help policymakers and developers make more informed decisions, this study investigated the temporal dynamics of rainfall and its spatial distribution within Ethiopia. Changes in rainfall were examined using data from 134 stations in 13 watersheds between 1960 and 2002. The variability and trends in seasonal and annual rainfall were analysed at the watershed scale with data (1) from all available years, and (2) excluding years that lacked observations from at least 25% of the gauges. Similar analyses were also performed at the gauge, regional, and national levels. By regressing annual watershed rainfall on time, results from the one-sample t-test show no significant changes in rainfall for any of the watersheds examined. However, in our regressions of seasonal rainfall averages against time, we found a significant decline in June to September rainfall (i.e. Kiremt) for the Baro-Akobo, Omo-Ghibe, Rift Valley, and Southern Blue Nile watersheds located in the southwestern and central parts of Ethiopia. While the gauge level analysis showed that certain gauge stations experienced recent changes in rainfall, these trends are not necessarily reflected at the watershed or regional levels.

Requirements for future development of small scale rainfall simulators

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Ries, Johannes B.; Seeger, Manuel

2013-04-01

Rainfall simulation with small scale simulators is a method used worldwide to assess the generation of overland flow, soil erosion, infiltration and interrelated processes such as soil sealing, crusting, splash and redistribution of solids and solutes. Following the outcomes of the project "Comparability of simulation results of different rainfall simulators as input data for soil erosion modelling (Deutsche Forschungsgemeinschaft - DFG, Project No. Ri 835/6-1)" and the "International Rainfall Simulator Workshop 2011" in Trier, the necessity for further technical improvements of simulators and strategies towards an adaption of designs and methods becomes obvious. Uniform measurements of artificially generated rainfall and comparative measurements on a prepared bare fallow with rainfall simulators used by European research groups showed limitations of the comparability of the results. The following requirements, essential for small portable rainfall simulators, were identified: (I) Low and efficient water consumption for use in areas with water shortage, (II) easy handling and control of test conditions, (III) homogeneous spatial rainfall distribution, (IV) best possible drop spectrum (physically), (V) reproducibility and knowledge of spatial distribution and drop spectrum, (VI) easy and fast training of operators to obtain reproducible experiments and (VII) good mobility and easy installation for use in remote areas and in regions where highly erosive rainfall events are rare or irregular. The presentation discusses possibilities for a common use of identical plot designs, rainfall intensities and nozzles.

Evaluation of Rainfall-induced Landslide Potential

NASA Astrophysics Data System (ADS)

Chen, Y. R.; Tsai, K. J.; Chen, J. W.; Chue, Y. S.; Lu, Y. C.; Lin, C. W.

2016-12-01

Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assessed rainfall-induced landslide potential and spatial distribution in some watersheds of Southern Taiwan to configure reasonable assessment process and methods for landslide potential. This study focused on the multi-year multi-phase heavy rainfall events after 2009 Typhoon Morakot and applied the analysis techniques for the classification of satellite images of research region before and after rainfall to obtain surface information and hazard log data. GIS and DEM were employed to obtain the ridge and water system and to explore characteristics of landslide distribution. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various hazard factors. Furthermore, the interaction between rainfall characteristic, slope disturbance and landslide mechanism was analyzed. The results of image classification show that the values of coefficient of agreement are at medium-high level. The agreement of landslide potential map is at around 80% level compared with historical disaster sites. The relations between landslide potential level, slope disturbance degree, and the ratio of number and area of landslide increment corresponding heavy rainfall events are positive. The ratio of landslide occurrence is proportional to the value of instability index. Moreover, for each rainfall event, the number and scale of secondary landslide sites are much more than those of new landslide sites. The greater the slope land disturbance, the more likely it is that the scale of secondary landslide become greater. The spatial distribution of landslide depends on the interaction of rainfall patterns, slope, and elevation of the research area.

Simulation of precipitation by weather pattern and frontal analysis

NASA Astrophysics Data System (ADS)

Wilby, Robert

1995-12-01

Daily rainfall from two sites in central and southern England was stratified according to the presence or absence of weather fronts and then cross-tabulated with the prevailing Lamb Weather Type (LWT). A semi-Markov chain model was developed for simulating daily sequences of LWTs from matrices of transition probabilities between weather types for the British Isles 1970-1990. Daily and annual rainfall distributions were then simulated from the prevailing LWTs using historic conditional probabilities for precipitation occurrence and frontal frequencies. When compared with a conventional rainfall generator the frontal model produced improved estimates of the overall size distribution of daily rainfall amounts and in particular the incidence of low-frequency high-magnitude totals. Further research is required to establish the contribution of individual frontal sub-classes to daily rainfall totals and of long-term fluctuations in frontal frequencies to conditional probabilities.

Application of spatial Poisson process models to air mass thunderstorm rainfall

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.

1987-01-01

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

Biochars impact on soil moisture storage in an Ultisol and two Aridisols

USDA-ARS?s Scientific Manuscript database

Droughts associated with low or erratic rainfall distribution can cause detrimental crop moisture stress. This problem is exacerbated in the USA’s arid western and southeastern Coastal Plain due to poor rainfall distribution, poor soil water storage, or poorly-aggregated, subsurface hard layers that...

Descriptive Statistics and Cluster Analysis for Extreme Rainfall in Java Island

NASA Astrophysics Data System (ADS)

E Komalasari, K.; Pawitan, H.; Faqih, A.

2017-03-01

This study aims to describe regional pattern of extreme rainfall based on maximum daily rainfall for period 1983 to 2012 in Java Island. Descriptive statistics analysis was performed to obtain centralization, variation and distribution of maximum precipitation data. Mean and median are utilized to measure central tendency data while Inter Quartile Range (IQR) and standard deviation are utilized to measure variation of data. In addition, skewness and kurtosis used to obtain shape the distribution of rainfall data. Cluster analysis using squared euclidean distance and ward method is applied to perform regional grouping. Result of this study show that mean (average) of maximum daily rainfall in Java Region during period 1983-2012 is around 80-181mm with median between 75-160mm and standard deviation between 17 to 82. Cluster analysis produces four clusters and show that western area of Java tent to have a higher annual maxima of daily rainfall than northern area, and have more variety of annual maximum value.

Congo Basin rainfall climatology: can we believe the climate models?

PubMed Central

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M.; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models. PMID:23878328

On the use of satellite-based estimates of rainfall temporal distribution to simulate the potential for malaria transmission in rural Africa

NASA Astrophysics Data System (ADS)

Yamana, Teresa K.; Eltahir, Elfatih A. B.

2011-02-01

This paper describes the use of satellite-based estimates of rainfall to force the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a hydrology-based mechanistic model of malaria transmission. We first examined the temporal resolution of rainfall input required by HYDREMATS. Simulations conducted over Banizoumbou village in Niger showed that for reasonably accurate simulation of mosquito populations, the model requires rainfall data with at least 1 h resolution. We then investigated whether HYDREMATS could be effectively forced by satellite-based estimates of rainfall instead of ground-based observations. The Climate Prediction Center morphing technique (CMORPH) precipitation estimates distributed by the National Oceanic and Atmospheric Administration are available at a 30 min temporal resolution and 8 km spatial resolution. We compared mosquito populations simulated by HYDREMATS when the model is forced by adjusted CMORPH estimates and by ground observations. The results demonstrate that adjusted rainfall estimates from satellites can be used with a mechanistic model to accurately simulate the dynamics of mosquito populations.

Trend Detection and Bivariate Frequency Analysis for Nonstrationary Rainfall Data

NASA Astrophysics Data System (ADS)

Joo, K.; Kim, H.; Shin, J. Y.; Heo, J. H.

2017-12-01

Multivariate frequency analysis has been developing for hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula has been used as a useful tool for multivariate probability model which has no limitation on deciding marginal distributions. The time-series rainfall data can be characterized to rainfall event by inter-event time definition (IETD) and each rainfall event has a rainfall depth and rainfall duration. In addition, nonstationarity in rainfall event has been studied recently due to climate change and trend detection of rainfall event is important to determine the data has nonstationarity or not. With the rainfall depth and duration of a rainfall event, trend detection and nonstationary bivariate frequency analysis has performed in this study. 62 stations from Korea Meteorological Association (KMA) over 30 years of hourly recorded data used in this study and the suitability of nonstationary copula for rainfall event has examined by the goodness-of-fit test.

Rainfall: State of the Science

NASA Astrophysics Data System (ADS)

Testik, Firat Y.; Gebremichael, Mekonnen

Rainfall: State of the Science offers the most up-to-date knowledge on the fundamental and practical aspects of rainfall. Each chapter, self-contained and written by prominent scientists in their respective fields, provides three forms of information: fundamental principles, detailed overview of current knowledge and description of existing methods, and emerging techniques and future research directions. The book discusses • Rainfall microphysics: raindrop morphodynamics, interactions, size distribution, and evolution • Rainfall measurement and estimation: ground-based direct measurement (disdrometer and rain gauge), weather radar rainfall estimation, polarimetric radar rainfall estimation, and satellite rainfall estimation • Statistical analyses: intensity-duration-frequency curves, frequency analysis of extreme events, spatial analyses, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products The book is tailored to be an indispensable reference for researchers, practitioners, and graduate students who study any aspect of rainfall or utilize rainfall information in various science and engineering disciplines.

Mobilization and distribution of lead originating from roof dust and wet deposition in a roof runoff system.

PubMed

Yu, Jianghua; Yu, Haixia; Huang, Xiaogu

2015-12-01

In this research, the mobilization and distribution of lead originating in roof dust and wet deposition were investigated within a roof dust-rooftop-runoff system. The results indicated that lead from roof dust and wet deposition showed different transport dynamics in runoff system and that this process was significantly influenced by the rainfall intensity. Lead present in the roof dust could be easily washed off into the runoff, and nearly 60 % of the total lead content was present in particulate form. Most of the lead from the roof dust was transported during the late period of rainfall; however, the lead concentration was higher for several minutes at the rainfall beginning. Even though some of the lead from wet deposition, simulated with a standard isotope substance, was adsorbed onto adhered roof dust and/or retained on rooftop in runoff system, most of it (50-82 %) remained as dissolved lead in the runoff for rainfall events of varying intensity. Regarding the distribution of lead in the runoff system, the results indicated that it could be carried in the runoff in dissolved and particulate form, be adsorbed to adhered roof dust, or remain on the rooftop because of adsorption to the roof material. Lead from the different sources showed different distribution patterns that were also related to the rainfall intensity. Higher rainfall intensity resulted in a higher proportion of lead in the runoff and a lower proportion of lead remaining on the rooftop.

The relationship between extreme precipitation events and landslides distributions in 2009 in Lower Austria

NASA Astrophysics Data System (ADS)

Katzensteiner, H.; Bell, R.; Petschko, H.; Glade, T.

2012-04-01

The prediction and forecast of widespread landsliding for a given triggering event is an open research question. Numerous studies tried to link spatial rainfall and landslide distributions. This study focuses on analysing the relationship between intensive precipitation and rainfall-triggered shallow landslides in the year 2009 in Lower Austria. Landslide distributions were gained from the building ground register, which is maintained by the Geological Survey of Lower Austria. It contains detailed information of landslides, which were registered due to damage reports. Spatially distributed rainfall estimates were extracted from INCA (Integrated Nowcasting through Comprehensive Analysis) precipitation analysis, which is a combination of station data interpolation and radar data in a spatial resolution of 1km developed by the Central Institute for Meteorology and Geodynamics (ZAMG), Vienna, Austria. The importance of the data source is shown by comparing rainfall data based on reference gauges, spatial interpolation and INCA-analysis for a certain storm period. INCA precipitation data can detect precipitating cells that do not hit a station but might trigger a landslide, which is an advantage over the application of reference stations for the definition of rainfall thresholds. Empirical thresholds at regional scale were determined based on rainfall-intensity and duration in the year 2009 and landslide information. These thresholds are dependent on the criteria which separate the landslide triggering and non-triggering precipitation events from each other. Different approaches for defining thresholds alter the shape of the threshold as well. A temporarily threshold I=8,8263*D^(-0.672) for extreme rainfall events in summer in Lower Austria was defined. A verification of the threshold with similar events of other years as well as following analyses based on a larger landslide database are in progress.

Characterization and disaggregation of daily rainfall in the Upper Blue Nile Basin in Ethiopia

NASA Astrophysics Data System (ADS)

Engida, Agizew N.; Esteves, Michel

2011-03-01

SummaryIn Ethiopia, available rainfall records are mainly limited to daily time steps. Though rainfall data at shorter time steps are important for various purposes like modeling of erosion processes and flood hydrographs, they are hardly available in Ethiopia. The objectives of this study were (i) to study the temporal characteristics of daily rains at two stations in the region of the Upper Blue Nile Basin (UBNB) and (ii) to calibrate and evaluate a daily rainfall disaggregation model. The analysis was based on rainfall data of Bahir Dar and Gonder Meteorological Stations. The disaggregation model used was the Modified Bartlett-Lewis Rectangular Pulse Model (MBLRPM). The mean daily rainfall intensity varied from about 4 mm in the dry season to 17 mm in the wet season with corresponding variation in raindays of 0.4-26 days. The observed maximum daily rainfall varied from 13 mm in the dry month to 200 mm in the wet month. The average wet/dry spell length varied from 1/21 days in the dry season to 6/1 days in the rainy season. Most of the rainfall occurs in the afternoon and evening periods of the day. Daily rainfall disaggregation using the MBLRPM alone resulted in poor match between the disaggregated and observed hourly rainfalls. Stochastic redistribution of the outputs of the model using Beta probability distribution function improved the agreement between observed and calculated hourly rain intensities. In areas where convective rainfall is dominant, the outputs of MBLRPM should be redistributed using relevant probability distributions to simulate the diurnal rainfall pattern.

Flood risk assessment in France: comparison of extreme flood estimation methods (EXTRAFLO project, Task 7)

NASA Astrophysics Data System (ADS)

Garavaglia, F.; Paquet, E.; Lang, M.; Renard, B.; Arnaud, P.; Aubert, Y.; Carre, J.

2013-12-01

In flood risk assessment the methods can be divided in two families: deterministic methods and probabilistic methods. In the French hydrologic community the probabilistic methods are historically preferred to the deterministic ones. Presently a French research project named EXTRAFLO (RiskNat Program of the French National Research Agency, https://extraflo.cemagref.fr) deals with the design values for extreme rainfall and floods. The object of this project is to carry out a comparison of the main methods used in France for estimating extreme values of rainfall and floods, to obtain a better grasp of their respective fields of application. In this framework we present the results of Task 7 of EXTRAFLO project. Focusing on French watersheds, we compare the main extreme flood estimation methods used in French background: (i) standard flood frequency analysis (Gumbel and GEV distribution), (ii) regional flood frequency analysis (regional Gumbel and GEV distribution), (iii) local and regional flood frequency analysis improved by historical information (Naulet et al., 2005), (iv) simplify probabilistic method based on rainfall information (i.e. Gradex method (CFGB, 1994), Agregee method (Margoum, 1992) and Speed method (Cayla, 1995)), (v) flood frequency analysis by continuous simulation approach and based on rainfall information (i.e. Schadex method (Paquet et al., 2013, Garavaglia et al., 2010), Shyreg method (Lavabre et al., 2003)) and (vi) multifractal approach. The main result of this comparative study is that probabilistic methods based on additional information (i.e. regional, historical and rainfall information) provide better estimations than the standard flood frequency analysis. Another interesting result is that, the differences between the various extreme flood quantile estimations of compared methods increase with return period, staying relatively moderate up to 100-years return levels. Results and discussions are here illustrated throughout with the example of five watersheds located in the South of France. References : O. CAYLA : Probability calculation of design floods abd inflows - SPEED. Waterpower 1995, San Francisco, California 1995 CFGB : Design flood determination by the gradex method. Bulletin du Comité Français des Grands Barrages News 96, 18th congress CIGB-ICOLD n2, nov:108, 1994. F. GARAVAGLIA et al. : Introducing a rainfall compound distribution model based on weather patterns subsampling. Hydrology and Earth System Sciences, 14, 951-964, 2010. J. LAVABRE et al. : SHYREG : une méthode pour l'estimation régionale des débits de crue. application aux régions méditerranéennes françaises. Ingénierie EAT, 97-111, 2003. M. MARGOUM : Estimation des crues rares et extrêmes : le modèle AGREGEE. Conceptions et remières validations. PhD, Ecole des Mines de Paris, 1992. R. NAULET et al. : Flood frequency analysis on the Ardèche river using French documentary sources from the two last centuries. Journal of Hydrology, 313:58-78, 2005. E. PAQUET et al. : The SCHADEX method: A semi-continuous rainfall-runoff simulation for extreme flood estimation, Journal of Hydrology, 495, 23-37, 2013.

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

NASA Astrophysics Data System (ADS)

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago; Giangrande, Scott; Silva Dias, Maria A. F.; Cecchini, Micael A.; Albrecht, Rachel; Andreae, Meinrat O.; Araujo, Wagner F.; Artaxo, Paulo; Borrmann, Stephan; Braga, Ramon; Burleyson, Casey; Eichholz, Cristiano W.; Fan, Jiwen; Feng, Zhe; Fisch, Gilberto F.; Jensen, Michael P.; Martin, Scot T.; Pöschl, Ulrich; Pöhlker, Christopher; Pöhlker, Mira L.; Ribaud, Jean-François; Rosenfeld, Daniel; Saraiva, Jaci M. B.; Schumacher, Courtney; Thalman, Ryan; Walter, David; Wendisch, Manfred

2018-05-01

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. This study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weighted mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.

A Broadband Microwave Radiometer Technique at X-band for Rain and Drop Size Distribution Estimation

NASA Technical Reports Server (NTRS)

Meneghini, R.

2005-01-01

Radiometric brightess temperatures below about 12 GHz provide accurate estimates of path attenuation through precipitation and cloud water. Multiple brightness temperature measurements at X-band frequencies can be used to estimate rainfall rate and parameters of the drop size distribution once correction for cloud water attenuation is made. Employing a stratiform storm model, calculations of the brightness temperatures at 9.5, 10 and 12 GHz are used to simulate estimates of path-averaged median mass diameter, number concentration and rainfall rate. The results indicate that reasonably accurate estimates of rainfall rate and information on the drop size distribution can be derived over ocean under low to moderate wind speed conditions.

Rainfall extremes from TRMM data and the Metastatistical Extreme Value Distribution

NASA Astrophysics Data System (ADS)

Zorzetto, Enrico; Marani, Marco

2017-04-01

A reliable quantification of the probability of weather extremes occurrence is essential for designing resilient water infrastructures and hazard mitigation measures. However, it is increasingly clear that the presence of inter-annual climatic fluctuations determines a substantial long-term variability in the frequency of occurrence of extreme events. This circumstance questions the foundation of the traditional extreme value theory, hinged on stationary Poisson processes or on asymptotic assumptions to derive the Generalized Extreme Value (GEV) distribution. We illustrate here, with application to daily rainfall, a new approach to extreme value analysis, the Metastatistical Extreme Value Distribution (MEVD). The MEVD relaxes the above assumptions and is based on the whole distribution of daily rainfall events, thus allowing optimal use of all available observations. Using a global dataset of rain gauge observations, we show that the MEVD significantly outperforms the Generalized Extreme Value distribution, particularly for long average recurrence intervals and when small samples are available. The latter property suggests MEVD to be particularly suited for applications to satellite rainfall estimates, which only cover two decades, thus making extreme value estimation extremely challenging. Here we apply MEVD to the TRMM TMPA 3B42 product, an 18-year dataset of remotely-sensed daily rainfall providing a quasi-global coverage. Our analyses yield a global scale mapping of daily rainfall extremes and of their distributional tail properties, bridging the existing large gaps in ground-based networks. Finally, we illustrate how our global-scale analysis can provide insight into how properties of local rainfall regimes affect tail estimation uncertainty when using the GEV or MEVD approach. We find a dependence of the estimation uncertainty, for both the GEV- and MEV-based approaches, on the average annual number and on the inter-annual variability of rainy days. In particular, estimation uncertainty decreases 1) as the mean annual number of wet days increases, and 2) as the variability in the number of rainy days, expressed by its coefficient of variation, decreases. We tentatively explain this behavior in terms of the assumptions underlying the two approaches.

Perceptible changes in Indian summer monsoon rainfall in relation to Indian Monsoon Index

NASA Astrophysics Data System (ADS)

Naidu, C. V.; Dharma Raju, A.; Vinay Kumar, P.; Satyanarayana, G. Ch.

2017-10-01

The changes in the summer monsoon rainfall over 30 meteorological subdivisions of India with respect to changes in circulation and the Indian Monsoon Index (IMI) have been studied for the period 1953-2012. The relationship between the IMIs in different months and whole season and the corresponding summer monsoon rainfall is studied and tested. The positive and negative extremes are evaluated basing on the normalized values of the deviations from the mean of the IMI. Composite rainfall distributions over India and the zonal wind distributions in the lower and upper troposphere of IMI's both positive and negative extremes are evaluated separately and discussed. In the recent three decades of global warming, the negative values of IMI in July and August lead to weakening of the monsoon system over India. It is observed that the rainfall variations in the Northeast India are different from the rest of India except Tamil Nadu in general.

Research on the semi-distributed monthly rainfall runoff model at the Lancang River basin based on DEM

NASA Astrophysics Data System (ADS)

Liu, Gang; Zhao, Rong; Liu, Jiping; Zhang, Qingpu

2007-06-01

The Lancang River Basin is so narrow and its hydrological and meteorological information are so flexible. The Rainfall, evaporation, glacial melt water and groundwater affect the runoff whose replenishment forms changing notable with the season in different areas at the basin. Characters of different kind of distributed model and conceptual hydrological model are analyzed. A semi-distributed hydrological model of relation between monthly runoff and rainfall, temperate and soil type has been built in Changdu County based on Visual Basic and ArcObject. The way of discretization of distributed hydrological model was used in the model, and principles of conceptual model are taken into account. The sub-catchment of Changdu is divided into regular cells, and all kinds of hydrological and meteorological information and land use classes and slope extracted from 1:250000 digital elevation models are distributed in each cell. The model does not think of the rainfall-runoff hydro-physical process but use the conceptual model to simulate the whole contributes to the runoff of the area. The affection of evapotranspiration loss and underground water is taken into account at the same time. The spatial distribute characteristics of the monthly runoff in the area are simulated and analyzed with a few parameters.

Rainfall Downscaling Conditional on Upper-air Atmospheric Predictors: Improved Assessment of Rainfall Statistics in a Changing Climate

NASA Astrophysics Data System (ADS)

Langousis, Andreas; Mamalakis, Antonis; Deidda, Roberto; Marrocu, Marino

2015-04-01

To improve the level skill of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in reproducing the statistics of rainfall at a basin level and at hydrologically relevant temporal scales (e.g. daily), two types of statistical approaches have been suggested. One is the statistical correction of climate model rainfall outputs using historical series of precipitation. The other is the use of stochastic models of rainfall to conditionally simulate precipitation series, based on large-scale atmospheric predictors produced by climate models (e.g. geopotential height, relative vorticity, divergence, mean sea level pressure). The latter approach, usually referred to as statistical rainfall downscaling, aims at reproducing the statistical character of rainfall, while accounting for the effects of large-scale atmospheric circulation (and, therefore, climate forcing) on rainfall statistics. While promising, statistical rainfall downscaling has not attracted much attention in recent years, since the suggested approaches involved complex (i.e. subjective or computationally intense) identification procedures of the local weather, in addition to demonstrating limited success in reproducing several statistical features of rainfall, such as seasonal variations, the distributions of dry and wet spell lengths, the distribution of the mean rainfall intensity inside wet periods, and the distribution of rainfall extremes. In an effort to remedy those shortcomings, Langousis and Kaleris (2014) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables, which accurately reproduces the statistical character of rainfall at multiple time-scales. Here, we study the relative performance of: a) quantile-quantile (Q-Q) correction of climate model rainfall products, and b) the statistical downscaling scheme of Langousis and Kaleris (2014), in reproducing the statistical structure of rainfall, as well as rainfall extremes, at a regional level. This is done for an intermediate-sized catchment in Italy, i.e. the Flumendosa catchment, using climate model rainfall and atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com). In doing so, we split the historical rainfall record of mean areal precipitation (MAP) in 15-year calibration and 45-year validation periods, and compare the historical rainfall statistics to those obtained from: a) Q-Q corrected climate model rainfall products, and b) synthetic rainfall series generated by the suggested downscaling scheme. To our knowledge, this is the first time that climate model rainfall and statistically downscaled precipitation are compared to catchment-averaged MAP at a daily resolution. The obtained results are promising, since the proposed downscaling scheme is more accurate and robust in reproducing a number of historical rainfall statistics, independent of the climate model used and the length of the calibration period. This is particularly the case for the yearly rainfall maxima, where direct statistical correction of climate model rainfall outputs shows increased sensitivity to the length of the calibration period and the climate model used. The robustness of the suggested downscaling scheme in modeling rainfall extremes at a daily resolution, is a notable feature that can effectively be used to assess hydrologic risk at a regional level under changing climatic conditions. Acknowledgments The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State. CRS4 highly acknowledges the contribution of the Sardinian regional authorities.

Rift Valley fever in a zone potentially occupied by Aedes vexans in Senegal: dynamics and risk mapping

NASA Astrophysics Data System (ADS)

Tourre, Y. M.; Vignolles, C.; Lacaux, J.-P.; Bigeard, G.; Ndione, J.-A.; Lafaye, M.

2009-09-01

This paper presents an analysis of the interaction between the various variables associated with Rift Valley fever (RVF) such as the mosquito vector, available hosts and rainfall distribution. To that end, the varying zones potentially occupied by mosquitoes (ZPOM), rainfall events and pond dynamics, and the associated exposure of hosts to the RVF virus by Aedes vexans, were analyzed in the Barkedji area of the Ferlo, Senegal, during the 2003 rainy season. Ponds were identified by remote sensing using a high-resolution SPOT-5 satellite image. Additional data on ponds and rainfall events from the Tropical Rainfall Measuring Mission were combined with in-situ entomological and limnimetric measurements, and the localization of vulnerable ruminant hosts (data derived from QuickBird satellite). Since "Ae. vexans productive events” are dependent on the timing of rainfall for their embryogenesis (six days without rain are necessary to trigger hatching), the dynamic spatio-temporal distribution of Ae. vexans density was based on the total rainfall amount and pond dynamics. Detailed ZPOM mapping was obtained on a daily basis and combined with aggressiveness temporal profiles. Risks zones, i.e. zones where hazards and vulnerability are combined, are expressed by the percentages of parks where animals are potentially exposed to mosquito bites. This new approach, simply relying upon rainfall distribution evaluated from space, is meant to contribute to the implementation of a new, operational early warning system for RVF based on environmental risks linked to climatic and environmental conditions.

The Impact of Spatial and Temporal Resolutions in Tropical Summer Rainfall Distribution: Preliminary Results

NASA Astrophysics Data System (ADS)

Liu, Q.; Chiu, L. S.; Hao, X.

2017-10-01

The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

On the asymmetric distribution of shear-relative typhoon rainfall

NASA Astrophysics Data System (ADS)

Gao, Si; Zhai, Shunan; Li, Tim; Chen, Zhifan

2018-02-01

The Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation, the National Centers for Environmental Prediction (NCEP) Final analysis and the Regional Specialized Meteorological Center (RSMC) Tokyo best-track data during 2000-2015 are used to compare spatial rainfall distribution associated with Northwest Pacific tropical cyclones (TCs) with different vertical wind shear directions and investigate possible mechanisms. Results show that the maximum TC rainfall are all located in the downshear left quadrant regardless of shear direction, and TCs with easterly shear have greater magnitudes of rainfall than those with westerly shear, consistent with previous studies. Rainfall amount of a TC is related to its relative position and proximity from the western Pacific subtropical high (WPSH) and the intensity of water vapor transport, and low-level jet is favorable for water vapor transport. The maximum of vertically integrated moisture flux convergence (MFC) are located on the downshear side regardless of shear direction, and the contribution of wind convergence to the total MFC is far larger than that of moisture advection. The cyclonic displacement of the maximum rainfall relative to the maximum MFC is possibly due to advection of hydrometeors by low- and middle-level cyclonic circulation of TCs. The relationship between TC rainfall and the WPSH through water vapor transport and vertical wind shear implies that TC rainfall may be highly predictable given the high predictability of the WPSH.

Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

2017-04-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

A New Look at Rainfall Fluctuations and Scaling Properties of Spatial Rainfall Using Orthogonal Wavelets.

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1993-02-01

It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

A new look at rainfall fluctuations and scaling properties of spatial rainfall using orthogonal wavelets

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1993-01-01

It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

Evaluating rainfall kinetic energy - intensity relationships with observed disdrometric data

NASA Astrophysics Data System (ADS)

Angulo-Martinez, Marta; Begueria, Santiago; Latorre, Borja

2016-04-01

Rainfall kinetic energy is required for determining erosivity, the ability of rainfall to detach soil particles and initiate erosion. Its determination relay on the use of disdrometers, i.e. devices capable of measuring the drop size distribution and velocity of falling raindrops. In the absence of such devices, rainfall kinetic energy is usually estimated with empirical expressions relating rainfall energy and intensity. We evaluated the performance of 14 rainfall energy equations in estimating one-minute rainfall energy and event total energy, in comparison with observed data from 821 rainfall episodes (more than 100 thousand one-minute observations) by means of an optical disdrometer. In addition, two sources of bias when using such relationships were evaluated: i) the influence of using theoretical terminal raindrop fall velocities instead of measured values; and ii) the influence of time aggregation (rainfall intensity data every 5-, 10-, 15-, 30-, and 60-minutes). Empirical relationships did a relatively good job when complete events were considered (R2 > 0.82), but offered poorer results for within-event (one-minute resolution) variation. Also, systematic biases where large for many equations. When raindrop size distribution was known, estimating the terminal fall velocities by empirical laws produced good results even at fine time resolution. The influence of time aggregation was very high in the estimated kinetic energy, although linear scaling may allow empirical correction. This results stress the importance of considering all these effects when rainfall energy needs to be estimated from more standard precipitation records. , and recommends the use of disdrometer data to locally determine rainfall kinetic energy.

Probabilistic clustering of rainfall condition for landslide triggering

NASA Astrophysics Data System (ADS)

Rossi, Mauro; Luciani, Silvia; Cesare Mondini, Alessandro; Kirschbaum, Dalia; Valigi, Daniela; Guzzetti, Fausto

2013-04-01

Landslides are widespread natural and man made phenomena. They are triggered by earthquakes, rapid snow melting, human activities, but mostly by typhoons and intense or prolonged rainfall precipitations. In Italy mostly they are triggered by intense precipitation. The prediction of landslide triggered by rainfall precipitations over large areas is commonly based on the exploitation of empirical models. Empirical landslide rainfall thresholds are used to identify rainfall conditions for the possible landslide initiation. It's common practice to define rainfall thresholds by assuming a power law lower boundary in the rainfall intensity-duration or cumulative rainfall-duration space above which landslide can occur. The boundary is defined considering rainfall conditions associated to landslide phenomena using heuristic approaches, and doesn't consider rainfall events not causing landslides. Here we present a new fully automatic method to identify the probability of landslide occurrence associated to rainfall conditions characterized by measures of intensity or cumulative rainfall and rainfall duration. The method splits the rainfall events of the past in two groups: a group of events causing landslides and its complementary, then estimate their probabilistic distributions. Next, the probabilistic membership of the new event to one of the two clusters is estimated. The method doesn't assume a priori any threshold model, but simple exploits the real empirical distribution of rainfall events. The approach was applied in the Umbria region, Central Italy, where a catalogue of landslide timing, were obtained through the search of chronicles, blogs and other source of information in the period 2002-2012. The approach was tested using rain gauge measures and satellite rainfall estimates (NASA TRMM-v6), allowing in both cases the identification of the rainfall condition triggering landslides in the region. Compared to the other existing threshold definition methods, the prosed one (i) largely reduces the subjectivity in the choice of the threshold model and in how it is calculated, and (ii) it can be easier set-up in other study areas. The proposed approach can be conveniently integrated in existing early-warning system to improve the accuracy of the estimation of the real landslide occurrence probability associated to rainfall events and its uncertainty.

Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

2017-12-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic precipitation, fed into a rainfall-runoff model to derive the flood frequency in the Tirolean Alps in Austria. Given the number of generated events, the simulation framework is able to generate a large variety of rainfall patterns, as well as reproduce the variograms of relevant extreme rainfall events in the region of interest.

Regional frequency analysis of extreme rainfall for the Baltimore Metropolitan region based on stochastic storm transposition

NASA Astrophysics Data System (ADS)

Zhou, Z.; Smith, J. A.; Yang, L.; Baeck, M. L.; Wright, D.; Liu, S.

2017-12-01

Regional frequency analyses of extreme rainfall are critical for development of engineering hydrometeorology procedures. In conventional approaches, the assumptions that `design storms' have specified time profiles and are uniform in space are commonly applied but often not appropriate, especially over regions with heterogeneous environments (due to topography, water-land boundaries and land surface properties). In this study, we present regional frequency analyses of extreme rainfall for Baltimore study region combining storm catalogs of rainfall fields derived from weather radar and stochastic storm transposition (SST, developed by Wright et al., 2013). The study region is Dead Run, a small (14.3 km2) urban watershed, in the Baltimore Metropolitan region. Our analyses build on previous empirical and modeling studies showing pronounced spatial heterogeneities in rainfall due to the complex terrain, including the Chesapeake Bay to the east, mountainous terrain to the west and urbanization in this region. We expand the original SST approach by applying a multiplier field that accounts for spatial heterogeneities in extreme rainfall. We also characterize the spatial heterogeneities of extreme rainfall distribution through analyses of rainfall fields in the storm catalogs. We examine the characteristics of regional extreme rainfall and derive intensity-duration-frequency (IDF) curves using the SST approach for heterogeneous regions. Our results highlight the significant heterogeneity of extreme rainfall in this region. Estimates of IDF show the advantages of SST in capturing the space-time structure of extreme rainfall. We also illustrate application of SST analyses for flood frequency analyses using a distributed hydrological model. Reference: Wright, D. B., J. A. Smith, G. Villarini, and M. L. Baeck (2013), Estimating the frequency of extreme rainfall using weather radar and stochastic storm transposition, J. Hydrol., 488, 150-165.

Climatological characteristics of raindrop size distributions within a topographically complex area

NASA Astrophysics Data System (ADS)

Suh, S.-H.; You, C.-H.; Lee, D.-I.

2015-04-01

Raindrop size distribution (DSD) characteristics within the complex area of Busan, Korea (35.12° N, 129.10° E) were studied using a Precipitation Occurrence Sensor System (POSS) disdrometer over a four-year period from 24 February 2001 to 24 December 2004. Average DSD parameters in Busan, a mid-latitude site, were compared with corresponding parameters recorded in the high-latitude site of Järvenpää, Finland. Mean values of median drop diameter (D0) and the shape parameter (μ) in Busan are smaller than those in Järvenpää, whereas the mean normalized intercept parameter (Nw) and rainfall rate (R) are higher in Busan. To analyze the climatological DSD characteristics in more detail, the entire period of recorded rainfall was divided into 10 categories with different temporal and spatial scales. When only convective rainfall was considered, mean Dm and Nw values for all these categories converged around a maritime cluster, except for rainfall associated with typhoons. The convective rainfall of a typhoon showed much smaller Dm and larger Nw compared with the other rainfall categories. In terms of diurnal DSD variability, we observe maritime (continental) precipitation during the daytime (DT) (nighttime, NT), which likely results from sea (land) breeze identified through wind direction analysis. These features also appeared in the seasonal diurnal distribution. The DT and NT Probability Density Function (PDF) during the summer was similar to the PDF of the entire study period. However, the DT and NT PDF during the winter season displayed an inverse distribution due to seasonal differences in wind direction.

Bivariate copula in fitting rainfall data

NASA Astrophysics Data System (ADS)

Yee, Kong Ching; Suhaila, Jamaludin; Yusof, Fadhilah; Mean, Foo Hui

2014-07-01

The usage of copula to determine the joint distribution between two variables is widely used in various areas. The joint distribution of rainfall characteristic obtained using the copula model is more ideal than the standard bivariate modelling where copula is belief to have overcome some limitation. Six copula models will be applied to obtain the most suitable bivariate distribution between two rain gauge stations. The copula models are Ali-Mikhail-Haq (AMH), Clayton, Frank, Galambos, Gumbel-Hoogaurd (GH) and Plackett. The rainfall data used in the study is selected from rain gauge stations which are located in the southern part of Peninsular Malaysia, during the period from 1980 to 2011. The goodness-of-fit test in this study is based on the Akaike information criterion (AIC).

Influence of rainfall data scarcity on non-point source pollution prediction: Implications for physically based models

NASA Astrophysics Data System (ADS)

Chen, Lei; Xu, Jiajia; Wang, Guobo; Liu, Hongbin; Zhai, Limei; Li, Shuang; Sun, Cheng; Shen, Zhenyao

2018-07-01

Hydrological and non-point source pollution (H/NPS) predictions in ungagged basins have become the key problem for watershed studies, especially for those large-scale catchments. However, few studies have explored the comprehensive impacts of rainfall data scarcity on H/NPS predictions. This study focused on: 1) the effects of rainfall spatial scarcity (by removing 11%-67% of stations based on their locations) on the H/NPS results; and 2) the impacts of rainfall temporal scarcity (10%-60% data scarcity in time series); and 3) the development of a new evaluation method that incorporates information entropy. A case study was undertaken using the Soil and Water Assessment Tool (SWAT) in a typical watershed in China. The results of this study highlighted the importance of critical-site rainfall stations that often showed greater influences and cross-tributary impacts on the H/NPS simulations. Higher missing rates above a certain threshold as well as missing locations during the wet periods resulted in poorer simulation results. Compared to traditional indicators, information entropy could serve as a good substitute because it reflects the distribution of spatial variability and the development of temporal heterogeneity. This paper reports important implications for the application of Distributed Hydrological Models and Semi-distributed Hydrological Models, as well as for the optimal design of rainfall gauges among large basins.

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

Rainfall Induced Landslides in Puerto Rico (Invited)

NASA Astrophysics Data System (ADS)

Lepore, C.; Kamal, S.; Arnone, E.; Noto, V.; Shanahan, P.; Bras, R. L.

2009-12-01

Landslides are a major geologic hazard in the United States, typically triggered by rainfall, earthquakes, volcanoes and human activity. Rainfall-induced landslides are the most common type in the island of Puerto Rico, with one or two large events per year. We performed an island-wide determination of static landslide susceptibility and hazard assessment as well as dynamic modeling of rainfall-induced shallow landslides in a particular hydrologic basin. Based on statistical analysis of past landslides, we determined that reliable prediction of the susceptibility to landslides is strongly dependent on the resolution of the digital elevation model (DEM) employed and the reliability of the rainfall data. A distributed hydrology model capable of simulating landslides, tRIBS-VEGGIE, has been implemented for the first time in a humid tropical environment like Puerto Rico. The Mameyes basin, located in the Luquillo Experimental Forest in Puerto Rico, was selected for modeling based on the availability of soil, vegetation, topographical, meteorological and historic landslide data. .Application of the model yields a temporal and spatial distribution of predicted rainfall-induced landslides, which is used to predict the dynamic susceptibility of the basin to landslides.

Spatial and temporal variability in the R-5 infiltration data set: Déjà vu and rainfall-runoff simulations

NASA Astrophysics Data System (ADS)

Loague, Keith; Kyriakidis, Phaedon C.

1997-12-01

This paper is a continuation of the event-based rainfall-runoff model evaluation study reported by Loague and Freeze [1985[. Here we reevaluate the performance of a quasi-physically based rainfall-runoff model for three large events from the well-known R-5 catchment. Five different statistical criteria are used to quantitatively judge model performance. Temporal variability in the large R-5 infiltration data set [Loague and Gander, 1990] is filtered by working in terms of permeability. The transformed data set is reanalyzed via geostatistical methods to model the spatial distribution of permeability across the R-5 catchment. We present new estimates of the spatial distribution of infiltration that are in turn used in our rainfall-runoff simulations with the Horton rainfall-runoff model. The new rainfall-runoff simulations, complicated by reinfiltration impacts at the smaller scales of characterization, indicate that the near-surface hydrologic response of the R-5 catchment is most probably dominated by a combination of the Horton and Dunne overland flow mechanisms.

Calibration and verification of a rainfall-runoff model and a runoff-quality model for several urban basins in the Denver metropolitan area, Colorado

USGS Publications Warehouse

Lindner-Lunsford, J. B.; Ellis, S.R.

1984-01-01

The U.S. Geological Survey 's Distributed Routing Rainfall-Runoff Model--Version II was calibrated and verified for five urban basins in the Denver metropolitan area. Land-use types in the basins were light commerical, multifamily housing, single-family housing, and a shopping center. The overall accuracy of model predictions of peak flows and runoff volumes was about 15 percent for storms with rainfall intensities of less than 1 inch per hour and runoff volume of greater than 0.01 inch. Predictions generally were unsatisfactory for storm having a rainfall intensity of more than 1 inch per hour, or runoff of 0.01 inch or less. The Distributed Routing Rainfall-Runoff Model-Quality, a multievent runoff-quality model developed by the U.S. Geological Survey, was calibrated and verified on four basins. The model was found to be most useful in the prediction of seasonal loads of constituents in the runoff resulting from rainfall. The model was not very accurate in the prediction of runoff loads of individual constituents. (USGS)

RainyDay: An Online, Open-Source Tool for Physically-based Rainfall and Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Wright, D.; Yu, G.; Holman, K. D.

2017-12-01

Flood frequency analysis in ungaged or changing watersheds typically requires rainfall intensity-duration-frequency (IDF) curves combined with hydrologic models. IDF curves only depict point-scale rainfall depth, while true rainstorms exhibit complex spatial and temporal structures. Floods result from these rainfall structures interacting with watershed features such as land cover, soils, and variable antecedent conditions as well as river channel processes. Thus, IDF curves are traditionally combined with a variety of "design storm" assumptions such as area reduction factors and idealized rainfall space-time distributions to translate rainfall depths into inputs that are suitable for flood hydrologic modeling. The impacts of such assumptions are relatively poorly understood. Meanwhile, modern precipitation estimates from gridded weather radar, grid-interpolated rain gages, satellites, and numerical weather models provide more realistic depictions of rainfall space-time structure. Usage of such datasets for rainfall and flood frequency analysis, however, are hindered by relatively short record lengths. We present RainyDay, an open-source stochastic storm transposition (SST) framework for generating large numbers of realistic rainfall "scenarios." SST "lengthens" the rainfall record by temporal resampling and geospatial transposition of observed storms to extract space-time information from regional gridded rainfall data. Relatively short (10-15 year) records of bias-corrected radar rainfall data are sufficient to estimate rainfall and flood events with much longer recurrence intervals including 100-year and 500-year events. We describe the SST methodology as implemented in RainyDay and compare rainfall IDF results from RainyDay to conventional estimates from NOAA Atlas 14. Then, we demonstrate some of the flood frequency analysis properties that are possible when RainyDay is integrated with a distributed hydrologic model, including robust estimation of flood hazards in a changing watershed. The U.S. Bureau of Reclamation is supporting the development of a web-based variant of RainyDay, a "beta" version of which is available at http://her.cee.wisc.edu/projects/rainyday/.

Implications of climate change on landslide hazard in Central Italy.

PubMed

Alvioli, Massimiliano; Melillo, Massimo; Guzzetti, Fausto; Rossi, Mauro; Palazzi, Elisa; von Hardenberg, Jost; Brunetti, Maria Teresa; Peruccacci, Silvia

2018-07-15

The relation between climate change and its potential effects on the stability of slopes remains an open issue. For rainfall induced landslides, the point consists in determining the effects of the projected changes in the duration and amounts of rainfall that can initiate slope failures. We investigated the relationship between fine-scale climate projections obtained by downscaling and the expected modifications in landslide occurrence in Central Italy. We used rainfall measurements taken by 56 rain gauges in the 9-year period 2003-2011, and the RainFARM technique to generate downscaled synthetic rainfall fields from regional climate model projections for the 14-year calibration period 2002-2015, and for the 40-year projection period 2010-2049. Using a specific algorithm, we extracted a number of rainfall events, i.e. rainfall periods separated by dry periods of no or negligible amount of rain, from the measured and the synthetic rainfall series. Then, we used the selected rainfall events to forcethe Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model TRIGRS v. 2.1. We analyzed the results in terms of variations (or lack of variations) in the rainfall thresholds for the possible initiation of landslides, in the probability distribution of landslide size (area), and in landslide hazard. Results showed that the downscaled rainfall fields obtained by RainFARM can be used to single out rainfall events, and to force the slope stability model. Results further showed that while the rainfall thresholds for landslide occurrence are expected to change in future scenarios, the probability distribution of landslide areas are not. We infer that landslide hazard in the study area is expected to change in response to the projected variations in the rainfall conditions. We expect our results to contribute to regional investigations of the expected impact of projected climate variations on slope stability conditions and on landslide hazards. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Hassan, Zulkarnain; Haidir, Ahmad; Saad, Farah Naemah Mohd; Ayob, Afizah; Rahim, Mustaqqim Abdul; Ghazaly, Zuhayr Md.

2018-03-01

The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

Incorporating rainfall uncertainty in a SWAT model: the river Zenne basin (Belgium) case study

NASA Astrophysics Data System (ADS)

Tolessa Leta, Olkeba; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

2013-04-01

The European Union Water Framework Directive (EU-WFD) called its member countries to achieve a good ecological status for all inland and coastal water bodies by 2015. According to recent studies, the river Zenne (Belgium) is far from this objective. Therefore, an interuniversity and multidisciplinary project "Towards a Good Ecological Status in the river Zenne (GESZ)" was launched to evaluate the effects of wastewater management plans on the river. In this project, different models have been developed and integrated using the Open Modelling Interface (OpenMI). The hydrologic, semi-distributed Soil and Water Assessment Tool (SWAT) is hereby used as one of the model components in the integrated modelling chain in order to model the upland catchment processes. The assessment of the uncertainty of SWAT is an essential aspect of the decision making process, in order to design robust management strategies that take the predicted uncertainties into account. Model uncertainty stems from the uncertainties on the model parameters, the input data (e.g, rainfall), the calibration data (e.g., stream flows) and on the model structure itself. The objective of this paper is to assess the first three sources of uncertainty in a SWAT model of the river Zenne basin. For the assessment of rainfall measurement uncertainty, first, we identified independent rainfall periods, based on the daily precipitation and stream flow observations and using the Water Engineering Time Series PROcessing tool (WETSPRO). Secondly, we assigned a rainfall multiplier parameter for each of the independent rainfall periods, which serves as a multiplicative input error corruption. Finally, we treated these multipliers as latent parameters in the model optimization and uncertainty analysis (UA). For parameter uncertainty assessment, due to the high number of parameters of the SWAT model, first, we screened out its most sensitive parameters using the Latin Hypercube One-factor-At-a-Time (LH-OAT) technique. Subsequently, we only considered the most sensitive parameters for parameter optimization and UA. To explicitly account for the stream flow uncertainty, we assumed that the stream flow measurement error increases linearly with the stream flow value. To assess the uncertainty and infer posterior distributions of the parameters, we used a Markov Chain Monte Carlo (MCMC) sampler - differential evolution adaptive metropolis (DREAM) that uses sampling from an archive of past states to generate candidate points in each individual chain. It is shown that the marginal posterior distributions of the rainfall multipliers vary widely between individual events, as a consequence of rainfall measurement errors and the spatial variability of the rain. Only few of the rainfall events are well defined. The marginal posterior distributions of the SWAT model parameter values are well defined and identified by DREAM, within their prior ranges. The posterior distributions of output uncertainty parameter values also show that the stream flow data is highly uncertain. The approach of using rainfall multipliers to treat rainfall uncertainty for a complex model has an impact on the model parameter marginal posterior distributions and on the model results Corresponding author: Tel.: +32 (0)2629 3027; fax: +32(0)2629 3022. E-mail: otolessa@vub.ac.be

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

DOE PAGES

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago; ...

2018-05-07

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. Here, this study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weightedmore » mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.« less

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. Here, this study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weightedmore » mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.« less

Local influence of south-east France topography and land cover on the distribution and characteristics of intense rainfall cells

NASA Astrophysics Data System (ADS)

Renard, Florent

2017-04-01

The Greater Lyon area is strongly built up, grouping 58 communes and a population of 1.3 million in approximately 500 km2. The flood risk is high as the territory is crossed by two large watercourses and by streams with torrential flow. Floods may also occur in case of runoff after heavy rain or because of a rise in the groundwater level. The whole territory can therefore be affected, and it is necessary to possess in-depth knowledge of the depths, causes and consequences of rainfall to achieve better management of precipitation in urban areas and to reduce flood risk. This study is thus focused on the effects of topography and land cover on the occurrence, intensity and area of intense rainfall cells. They are identified by local radar meteorology (C-band) combined with a processing algorithm running in a geographic information system (GIS) which identified 109,979 weighted mean centres of them in a sample composed of the five most intense rainfall events from 2001 to 2005. First, analysis of spatial distribution at an overall scale is performed, completed by study at a more detailed scale. The results show that the distribution of high-intensity rainfall cells is spread in cluster form. Subsequently, comparison of intense rainfall cells with the topography shows that cell density is closely linked with land slope but that, above all, urbanised zones feature nearly twice as many rainfall cells as farm land or forest, with more intense intensity.

How extreme is extreme hourly precipitation?

NASA Astrophysics Data System (ADS)

Papalexiou, Simon Michael; Dialynas, Yannis G.; Pappas, Christoforos

2016-04-01

The importance of accurate representation of precipitation at fine time scales (e.g., hourly), directly associated with flash flood events, is crucial in hydrological design and prediction. The upper part of a probability distribution, known as the distribution tail, determines the behavior of extreme events. In general, and loosely speaking, tails can be categorized in two families: the subexponential and the hyperexponential family, with the first generating more intense and more frequent extremes compared to the latter. In past studies, the focus has been mainly on daily precipitation, with the Gamma distribution being the most popular model. Here, we investigate the behaviour of tails of hourly precipitation by comparing the upper part of empirical distributions of thousands of records with three general types of tails corresponding to the Pareto, Lognormal, and Weibull distributions. Specifically, we use thousands of hourly rainfall records from all over the USA. The analysis indicates that heavier-tailed distributions describe better the observed hourly rainfall extremes in comparison to lighter tails. Traditional representations of the marginal distribution of hourly rainfall may significantly deviate from observed behaviours of extremes, with direct implications on hydroclimatic variables modelling and engineering design.

Interpretation of heavy rainfall spatial distribution in mountain watersheds by copula functions

NASA Astrophysics Data System (ADS)

Grossi, Giovanna; Balistrocchi, Matteo

2016-04-01

The spatial distribution of heavy rainfalls can strongly influence flood dynamics in mountain watersheds, depending on their geomorphologic features, namely orography, slope, land covers and soil types. Unfortunately, the direct observation of rainfall fields by meteorological radar is very difficult in this situation, so that interpolation of rain gauge observations or downscaling of meteorological predictions must be adopted to derive spatial rainfall distributions. To do so, various stochastic and physically based approaches are already available, even though the first one is the most familiar in hydrology. Indeed, Kriging interpolation procedures represent very popular techniques to face this problem by means of a stochastic approach. A certain number of restrictive assumptions and parameter uncertainties however affects Kriging. Many alternative formulations and additional procedures were therefore developed during the last decades. More recently, copula functions (Joe, 1997; Nelsen, 2006; Salvadori et al. 2007) were suggested to provide a more straightforward solution to carry out spatial interpolations of hydrologic variables (Bardossy & Pegram; 2009). Main advantages lie in the possibility of i) assessing the dependence structure relating to rainfall variables independently of marginal distributions, ii) expressing the association degree through rank correlation coefficients, iii) implementing marginal distributions and copula functions belonging to different models to develop complex joint distribution functions, iv) verifying the model reliability by effective statistical tests (Genest et al., 2009). A suitable case study to verify these potentialities is provided by the Taro River, a right-bank tributary of the Po River (northern Italy), whose contributing area amounts to about 2˙000 km2. The mountain catchment area is divided into two similar watersheds, so that spatial distribution is crucial in extreme flood event generation. A quite well diffused hydro-meteorological network, consisting of about 30 rain gauges and 10 hydrometers, monitors this medium-size watershed. A decade of rainfall-runoff event observations are available. Severe rainfall events were identified with reference to a main raingauge station, by using an interevent time definition and a depth threshold. Rainfall depths were thus derived and the spatial variability of their association degree was represented by using the Kendall coefficient. A unique copula model based on Gumbel copula function was finally found to be suitable to represent the dependence structure relating to rainfall depths observed in distinct raingauges. Bardossy A., Pegram G. (2009), Copula based multisite model for daily precipitation simulation, Hydrol. Earth Syst. Sci., 13, 2299-2314. Genest C., Rémilland B., Beaudoin D. (2009), Goodness-of-fit tests for copulas: a review and a power study, Insur. Math. Econ., 44(2), 199-213. Joe H. (1997), Multivariate models and dependence concepts, Chapman and Hall, London. Nelsen R. B. (2006), An introduction to copulas, second ed., Springer, New York. Salvadori G., De Michele C., Kottegoda N. T., Rosso R. (2007), Extremes in nature: an approach using copulas, Springer, Dordrecht, The Nederlands.

An improved rainfall disaggregation technique for GCMs

NASA Astrophysics Data System (ADS)

Onof, C.; Mackay, N. G.; Oh, L.; Wheater, H. S.

1998-08-01

Meteorological models represent rainfall as a mean value for a grid square so that when the latter is large, a disaggregation scheme is required to represent the spatial variability of rainfall. In general circulation models (GCMs) this is based on an assumption of exponentiality of rainfall intensities and a fixed value of areal rainfall coverage, dependent on rainfall type. This paper examines these two assumptions on the basis of U.K. and U.S. radar data. Firstly, the coverage of an area is strongly dependent on its size, and this dependence exhibits a scaling law over a range of sizes. Secondly, the coverage is, of course, dependent on the resolution at which it is measured, although this dependence is weak at high resolutions. Thirdly, the time series of rainfall coverages has a long-tailed autocorrelation function which is comparable to that of the mean areal rainfalls. It is therefore possible to reproduce much of the temporal dependence of coverages by using a regression of the log of the mean rainfall on the log of the coverage. The exponential assumption is satisfactory in many cases but not able to reproduce some of the long-tailed dependence of some intensity distributions. Gamma and lognormal distributions provide a better fit in these cases, but they have their shortcomings and require a second parameter. An improved disaggregation scheme for GCMs is proposed which incorporates the previous findings to allow the coverage to be obtained for any area and any mean rainfall intensity. The parameters required are given and some of their seasonal behavior is analyzed.

Modeling landslide recurrence in Seattle, Washington, USA

USGS Publications Warehouse

Salciarini, Diana; Godt, Jonathan W.; Savage, William Z.; Baum, Rex L.; Conversini, Pietro

2008-01-01

To manage the hazard associated with shallow landslides, decision makers need an understanding of where and when landslides may occur. A variety of approaches have been used to estimate the hazard from shallow, rainfall-triggered landslides, such as empirical rainfall threshold methods or probabilistic methods based on historical records. The wide availability of Geographic Information Systems (GIS) and digital topographic data has led to the development of analytic methods for landslide hazard estimation that couple steady-state hydrological models with slope stability calculations. Because these methods typically neglect the transient effects of infiltration on slope stability, results cannot be linked with historical or forecasted rainfall sequences. Estimates of the frequency of conditions likely to cause landslides are critical for quantitative risk and hazard assessments. We present results to demonstrate how a transient infiltration model coupled with an infinite slope stability calculation may be used to assess shallow landslide frequency in the City of Seattle, Washington, USA. A module called CRF (Critical RainFall) for estimating deterministic rainfall thresholds has been integrated in the TRIGRS (Transient Rainfall Infiltration and Grid-based Slope-Stability) model that combines a transient, one-dimensional analytic solution for pore-pressure response to rainfall infiltration with an infinite slope stability calculation. Input data for the extended model include topographic slope, colluvial thickness, initial water-table depth, material properties, and rainfall durations. This approach is combined with a statistical treatment of rainfall using a GEV (General Extreme Value) probabilistic distribution to produce maps showing the shallow landslide recurrence induced, on a spatially distributed basis, as a function of rainfall duration and hillslope characteristics.

How certain is desiccation in west African Sahel rainfall (1930-1990)?

NASA Astrophysics Data System (ADS)

Chappell, Adrian; Agnew, Clive T.

2008-04-01

Hypotheses for the late 1960s to 1990 period of desiccation (secular decrease in rainfall) in the west African Sahel (WAS) are typically tested by comparing empirical evidence or model predictions against "observations" of Sahelian rainfall. The outcomes of those comparisons can have considerable influence on the understanding of regional and global environmental systems. Inverse-distance squared area-weighted (IDW) estimates of WAS rainfall observations are commonly aggregated over space to provide temporal patterns without uncertainty. Spatial uncertainty of WAS rainfall was determined using the median approximation sequential indicator simulation. Every year (1930-1990) 300 equally probable realizations of annual summer rainfall were produced to honor station observations, match percentiles of the observed cumulative distributions and indicator variograms and perform adequately during cross validation. More than 49% of the IDW mean annual rainfall fell outside the 5th and 95th percentiles for annual rainfall realization means. The IDW means represented an extreme realization. Uncertainty in desiccation was determined by repeatedly (100,000) sampling the annual distribution of rainfall realization means and by applying Mann-Kendall nonparametric slope detection and significance testing. All of the negative gradients for the entire period were statistically significant. None of the negative gradients for the expected desiccation period were statistically significant. The results support the presence of a long-term decline in annual rainfall but demonstrate that short-term desiccation (1965-1990) cannot be detected. Estimates of uncertainty for precipitation and other climate variables in this or other regions, or across the globe, are essential for the rigorous detection of spatial patterns and time series trends.

Estimation of rainfall using remote sensing for Riyadh climate, KSA

NASA Astrophysics Data System (ADS)

AlHassoun, Saleh A.

2013-05-01

Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

Intra-seasonal rainfall variability during the maize growing season in the northern lowlands of Lesotho

NASA Astrophysics Data System (ADS)

Tongwane, Mphethe Isaac; Moeletsi, Mokhele Edmond

2015-05-01

Intra-seasonal rainfall distribution was identified as a priority gap that needs to be addressed for southern Africa to cope with agro-meteorological risks. The region in the northwest of Lesotho is appropriate for crop cultivation due to its relatively favourable climatic conditions and soils. High rainfall variability is often blamed for poor agricultural production in this region. This study aims to determine the onset of rains, cessation of rains and rainy season duration using historical climate data. Temporal variability of these rainy season characteristics was also investigated. The earliest and latest onset dates of the rainy season are during the last week of October at Butha-Buthe and the third week of November at Mapoteng, respectively. Cessation of the season is predominantly in the first week of April making the season approximately 137-163 days long depending on the location. Average seasonal rainfall ranged from 474 mm at Mapoteng to 668 mm at Butha-Buthe. Onset and cessation of the rainfall season vary by 4-7 weeks and 1 week, respectively. Mean coefficient of variation of seasonal rainfall is 39 %, but monthly variations are higher. These variations make annual crop management and planning difficult each year. Trends show a decrease in the rainfall amounts but improvements in both the temporal distribution of annual rainfall, onset and cessation dates.

Climatic controls on the global distribution, abundance, and species richness of mangrove forests

USGS Publications Warehouse

Osland, Michael J.; Feher, Laura C.; Griffith, Kereen; Cavanaugh, Kyle C.; Enwright, Nicholas M.; Day, Richard H.; Stagg, Camille L.; Krauss, Ken W.; Howard, Rebecca J.; Grace, James B.; Rogers, Kerrylee

2017-01-01

Mangrove forests are highly productive tidal saline wetland ecosystems found along sheltered tropical and subtropical coasts. Ecologists have long assumed that climatic drivers (i.e., temperature and rainfall regimes) govern the global distribution, structure, and function of mangrove forests. However, data constraints have hindered the quantification of direct climate-mangrove linkages in many parts of the world. Recently, the quality and availability of global-scale climate and mangrove data have been improving. Here, we used these data to better understand the influence of air temperature and rainfall regimes upon the distribution, abundance, and species richness of mangrove forests. Although our analyses identify global-scale relationships and thresholds, we show that the influence of climatic drivers is best characterized via regional range limit-specific analyses. We quantified climatic controls across targeted gradients in temperature and/or rainfall within 14 mangrove distributional range limits. Climatic thresholds for mangrove presence, abundance, and species richness differed among the 14 studied range limits. We identified minimum temperature-based thresholds for range limits in eastern North America, eastern Australia, New Zealand, eastern Asia, eastern South America, and southeast Africa. We identified rainfall-based thresholds for range limits in western North America, western Gulf of Mexico, western South America, western Australia, Middle East, northwest Africa, east central Africa, and west central Africa. Our results show that in certain range limits (e.g., eastern North America, western Gulf of Mexico, eastern Asia), winter air temperature extremes play an especially important role. We conclude that rainfall and temperature regimes are both important in western North America, western Gulf of Mexico, and western Australia. With climate change, alterations in temperature and rainfall regimes will affect the global distribution, abundance, and diversity of mangrove forests. In general, warmer winter temperatures are expected to allow mangroves to expand poleward at the expense of salt marshes. However, dispersal and habitat availability constraints may hinder expansion near certain range limits. Along arid and semi-arid coasts, decreases or increases in rainfall are expected to lead to mangrove contraction or expansion, respectively. Collectively, our analyses quantify climate-mangrove linkages and improve our understanding of the expected global- and regional-scale effects of climate change upon mangrove forests.

Satellite animal tracking feasibility studies

NASA Technical Reports Server (NTRS)

Buechner, H. K.

1975-01-01

A study was initiated in Tsavo National Park to determine movements and home ranges of individual elephants and their relations to overall distribution patterns and environmental factors such as rainfall. Methods used were radio tracking and observations of visually identifiable individuals. Aerial counts provided data on overall distribution. Two bulls and two cows were radio-tagged in Tsavo West and two bulls and four cows in Tsavo East, providing home range and movement data. The movements of individuals were useful in interpreting relatively major shifts in elephant distribution. Results point to the following preliminary conclusions: (1) elephants in the Tsavo area undertook long distance movements in fairly direct response to localized rainfall; (2) a subdivision of the overall population into locally distinct units may exist during the dry season but did not occur after significant rainfall; and (3) food appears to be the primary factor governing movements and distribution of elephants in the area.

Extreme flood estimation by the SCHADEX method in a snow-driven catchment: application to Atnasjø (Norway)

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel; Lawrence, Deborah

2013-04-01

The SCHADEX method for extreme flood estimation was developed by Paquet et al. (2006, 2013), and since 2008, it is the reference method used by Electricité de France (EDF) for dam spillway design. SCHADEX is a so-called "semi-continuous" stochastic simulation method in that flood events are simulated on an event basis and are superimposed on a continuous simulation of the catchment saturation hazard usingrainfall-runoff modelling. The MORDOR hydrological model (Garçon, 1999) has thus far been used for the rainfall-runoff modelling. MORDOR is a conceptual, lumped, reservoir model with daily areal rainfall and air temperature as the driving input data. The principal hydrological processes represented are evapotranspiration, direct and indirect runoff, ground water, snow accumulation and melt, and routing. The model has been intensively used at EDF for more than 15 years, in particular for inflow forecasts for French mountainous catchments. SCHADEX has now also been applied to the Atnasjø catchment (463 km²), a well-documented inland catchment in south-central Norway, dominated by snowmelt flooding during spring/early summer. To support this application, a weather pattern classification based on extreme rainfall was first established for Norway (Fleig, 2012). This classification scheme was then used to build a Multi-Exponential Weather Pattern distribution (MEWP), as introduced by Garavaglia et al. (2010) for extreme rainfall estimation. The MORDOR model was then calibrated relative to daily discharge data for Atnasjø. Finally, a SCHADEX simulation was run to build a daily discharge distribution with a sufficient number of simulations for assessing the extreme quantiles. Detailed results are used to illustrate how SCHADEX handles the complex and interacting hydrological processes driving flood generation in this snow driven catchment. Seasonal and monthly distributions, as well as statistics for several thousand simulated events reaching a 1000 years return level value and assessment of snowmelt role in extreme floods are presented. This study illustrates the complexity of the extreme flood estimation in snow driven catchments, and the need for a good representation of snow accumulation and melting processes in simulations for design flood estimations. In particular, the SCHADEX method is able to represent a range of possible catchment conditions (representing both soil moisture and snowmelt) in which extreme flood events can occur. This study is part of a collaboration between NVE and EDF, initiated within the FloodFreq COST Action (http://www.cost-floodfreq.eu/). References: Fleig, A., Scientific Report of the Short Term Scientific Mission Anne Fleig visiting Électricité de France, FloodFreq COST action - STSM report, 2012 Garavaglia, F., Gailhard, J., Paquet, E., Lang, M., Garçon, R., and Bernardara, P., Introducing a rainfall compound distribution model based on weather patterns sub-sampling, Hydrol. Earth Syst. Sci., 14, 951-964, doi:10.5194/hess-14-951-2010, 2010 Garçon, R. Modèle global pluie-débit pour la prévision et la prédétermination des crues, La Houille Blanche, 7-8, 88-95. doi: 10.1051/lhb/1999088 Paquet, E., Gailhard, J. and Garçon, R. (2006), Evolution of the GRADEX method: improvement by atmospheric circulation classification and hydrological modeling, La Houille Blanche, 5, 80-90. doi: 10.1051/lhb/2006091 Paquet, E., Garavaglia, F., Garçon, R. and Gailhard, J. (2012), The SCHADEX method: a semi-continuous rainfall-runoff simulation for extreme food estimation, Journal of Hydrology, under revision

Rainfall-induced soil aggregate breakdown in field experiments at different rainfall intensities and initial soil moisture conditions

NASA Astrophysics Data System (ADS)

Shi, Pu; Thorlacius, Sigurdur; Keller, Thomas; Keller, Martin; Schulin, Rainer

2017-04-01

Soil aggregate breakdown under rainfall impact is an important process in interrill erosion, but is not represented explicitly in water erosion models. Aggregate breakdown not only reduces infiltration through surface sealing during rainfall, but also determines the size distribution of the disintegrated fragments and thus their availability for size-selective sediment transport and re-deposition. An adequate representation of the temporal evolution of fragment mass size distribution (FSD) during rainfall events and the dependence of this dynamics on factors such as rainfall intensity and soil moisture content may help improve mechanistic erosion models. Yet, little is known about the role of those factors in the dynamics of aggregate breakdown under field conditions. In this study, we conducted a series of artificial rainfall experiments on a field silt loam soil to investigate aggregate breakdown dynamics at different rainfall intensity (RI) and initial soil water content (IWC). We found that the evolution of FSD in the course of a rainfall event followed a consistent two-stage pattern in all treatments. The fragment mean weight diameter (MWD) drastically decreased in an approximately exponential way at the beginning of a rainfall event, followed by a further slow linear decrease in the second stage. We proposed an empirical model that describes this temporal pattern of MWD decrease during a rainfall event and accounts for the effects of RI and IWC on the rate parameters. The model was successfully tested using an independent dataset, showing its potential to be used in erosion models for the prediction of aggregate breakdown. The FSD at the end of the experimental rainfall events differed significantly among treatments, indicating that different aggregate breakdown mechanisms responded differently to the variation in initial soil moisture and rainfall intensity. These results provide evidence that aggregate breakdown dynamics needs to be considered in a case-specific manner in modelling sediment mobilization and transport during water erosion events.

Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

NASA Astrophysics Data System (ADS)

Lucero, Omar A.; Rozas, Daniel

Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of this research could have further geographical validity.

A new perspective on the raindrop size distribution and its implications for retrievals of light rainfall

NASA Astrophysics Data System (ADS)

Gatlin, P. N.; Thurai, M.; Petersen, W. A.; Bringi, V. N.

2017-12-01

As GPM facilitates precipitation estimation at higher latitudes where light rainfall is more common it becomes more important that we can fully describe the raindrop size distribution (RSD) across the continuum of observed raindrop sizes. An adequate understanding and the capability to represent the RSD in light rain and drizzle extends from GPM radar algorithms into radiometer-based algorithms, where auto-conversion from cloud to rainwater contents and size distributions becomes important for light rain/drizzle estimation. This study provides insights into the effect of small raindrops on our ability to accurately map rainfall. The RSD has been widely defined using a gamma distribution—the assumption often being verified and approach being reinforced using measurements that imperfectly measure the small end of the RSD. However, we find that the gamma model as it is applied in its current form, to include commonly used disdrometer measurements to define it, is not capable of accurately describing the small raindrops we have observed during light rainfall. We demonstrate the difficulty encountered at light rain rates (e.g., 0.5 mm/hr or less) and for drops typically < 0.6 - 0.7 mm in diameter using a disdrometer with a pixel resolution of 50 microns operated alongside a 2DVD, with both instruments inside a small DFIR wind fence. Measurements were made in two locations with different climates—Greely, Colorado and Huntsville, Alabama. The resultant comparison reveals that the gamma RSD model overestimates the characteristic raindrop diameter (Dm), especially for light rainfall. A generalized gamma distribution provides a closer fit to the RSD observations across the continuum of raindrop sizes and highlights a drizzle mode of the RSD exists that would otherwise not be described with the commonly used gamma RSD model. Our analysis also suggests that RSD-based separation of stratiform and convective rainfall requires special consideration for light rainfall cases, especially those with small mass-weighted mean diameters (Dm < 0.6 mm).

Rainfall erosivity in Central Chile

NASA Astrophysics Data System (ADS)

Bonilla, Carlos A.; Vidal, Karim L.

2011-11-01

SummaryOne of the most widely used indicators of potential water erosion risk is the rainfall-runoff erosivity factor ( R) of the Revised Universal Soil Loss Equation (RUSLE). R is traditionally determined by calculating a long-term average of the annual sum of the product of a storm's kinetic energy ( E) and its maximum 30-min intensity ( I30), known as the EI30. The original method used to calculate EI30 requires pluviograph records for at most 30-min time intervals. Such high resolution data is difficult to obtain in many parts of the world, and processing it is laborious and time-consuming. In Chile, even though there is a well-distributed rain gauge network, there is no systematic characterization of the territory in terms of rainfall erosivity. This study presents a rainfall erosivity map for most of the cultivated land in the country. R values were calculated by the prescribed method for 16 stations with continuous graphical record rain gauges in Central Chile. The stations were distributed along 800 km (north-south), and spanned a precipitation gradient of 140-2200 mm yr -1. More than 270 years of data were used, and 5400 storms were analyzed. Additionally, 241 spatially distributed R values were generated by using an empirical procedure based on annual rainfall. Point estimates generated by both methods were interpolated by using kriging to create a map of rainfall erosivity for Central Chile. The results show that the empirical procedure used in this study predicted the annual rainfall erosivity well (model efficiency = 0.88). Also, an increment in the rainfall erosivities was found as a result of the rainfall depths, a regional feature determined by elevation and increasing with latitude from north to south. R values in the study area range from 90 MJ mm ha -1 h -1 yr -1 in the north up to 7375 MJ mm ha -1 h -1 yr -1 in the southern area, at the foothills of the Andes Mountains. Although the map and the estimates could be improved in the future by generating additional data points, the erosivity map should prove to be a good tool for land-use planners in Chile and other areas with similar rainfall characteristics.

Pharmaceuticals and consumer products in four wastewater treatment plants in urban and suburb areas of Shanghai.

PubMed

Sui, Qian; Wang, Dan; Zhao, Wentao; Huang, Jun; Yu, Gang; Cao, Xuqi; Qiu, Zhaofu; Lu, Shuguang

2015-04-01

Ten pharmaceuticals and two consumer products were investigated in four wastewater treatment plants (WWTPs) in Shanghai, China. The concentrations of target compounds in the wastewater influents ranged from below the limit of quantification (LOQ) to 9340 ng/L, with the frequency of detection of 31-100%, and the removal efficiencies were observed to be -82 to 100% in the four WWTPs. Concentrations of most target compounds (i.e. diclofenac, caffeine, metoprolol, sulpiride) in the wastewater influents were around three to eight times higher in urban WWTPs than in suburb ones, probably due to the different population served and lifestyles. Mean concentrations of target compounds in the wastewater influent generally decreased by 5-76% after rainfall due to the dilution of raw sewage by rainwater, which infiltrated into the sewer system. In the WWTPs located in the suburb area, the increased flow of wastewater influent led to a shortened hydraulic retention time (HRT) and decreased removal efficiencies of some compounds. On the contrary, the influence of rainfall was not significant on the removal efficiencies of investigated compounds in urban WWTPs, probably due to the almost unchanged influent flow, good removal performance, or bypass system employed.

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations

PubMed Central

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998–2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002–2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability. PMID:27010692

Modelling Hydrologic Processes in the Mekong River Basin Using a Distributed Model Driven by Satellite Precipitation and Rain Gauge Observations.

PubMed

Wang, Wei; Lu, Hui; Yang, Dawen; Sothea, Khem; Jiao, Yang; Gao, Bin; Peng, Xueting; Pang, Zhiguo

2016-01-01

The Mekong River is the most important river in Southeast Asia. It has increasingly suffered from water-related problems due to economic development, population growth and climate change in the surrounding areas. In this study, we built a distributed Geomorphology-Based Hydrological Model (GBHM) of the Mekong River using remote sensing data and other publicly available data. Two numerical experiments were conducted using different rainfall data sets as model inputs. The data sets included rain gauge data from the Mekong River Commission (MRC) and remote sensing rainfall data from the Tropic Rainfall Measurement Mission (TRMM 3B42V7). Model calibration and validation were conducted for the two rainfall data sets. Compared to the observed discharge, both the gauge simulation and TRMM simulation performed well during the calibration period (1998-2001). However, the performance of the gauge simulation was worse than that of the TRMM simulation during the validation period (2002-2012). The TRMM simulation is more stable and reliable at different scales. Moreover, the calibration period was changed to 2, 4, and 8 years to test the impact of the calibration period length on the two simulations. The results suggest that longer calibration periods improved the GBHM performance during validation periods. In addition, the TRMM simulation is more stable and less sensitive to the calibration period length than is the gauge simulation. Further analysis reveals that the uneven distribution of rain gauges makes the input rainfall data less representative and more heterogeneous, worsening the simulation performance. Our results indicate that remotely sensed rainfall data may be more suitable for driving distributed hydrologic models, especially in basins with poor data quality or limited gauge availability.

Do differences in understory light contribute to species distributions along a tropical rainfall gradient?

PubMed

Brenes-Arguedas, T; Roddy, A B; Coley, P D; Kursar, Thomas A

2011-06-01

In tropical forests, regional differences in annual rainfall correlate with differences in plant species composition. Although water availability is clearly one factor determining species distribution, other environmental variables that covary with rainfall may contribute to distributions. One such variable is light availability in the understory, which decreases towards wetter forests due to differences in canopy density and phenology. We established common garden experiments in three sites along a rainfall gradient across the Isthmus of Panama in order to measure the differences in understory light availability, and to evaluate their influence on the performance of 24 shade-tolerant species with contrasting distributions. Within sites, the effect of understory light availability on species performance depended strongly on water availability. When water was not limiting, either naturally in the wetter site or through water supplementation in drier sites, seedling performance improved at higher light. In contrast, when water was limiting at the drier sites, seedling performance was reduced at higher light, presumably due to an increase in water stress that affected mostly wet-distribution species. Although wetter forest understories were on average darker, wet-distribution species were not more shade-tolerant than dry-distribution species. Instead, wet-distribution species had higher absolute growth rates and, when water was not limiting, were better able to take advantage of small increases in light than dry-distribution species. Our results suggest that in wet forests the ability to grow fast during temporary increases in light may be a key trait for successful recruitment. The slower growth rates of the dry-distribution species, possibly due to trade-offs associated with greater drought tolerance, may exclude these species from wetter forests.

Radio Wave Propagation over Salem

NASA Astrophysics Data System (ADS)

Jaiswal, R. S.; Uma, S.; Raj, M. V. A.

2007-07-01

In this paper study of rainfall has been carried out over Salem, a place in Southern India. Rainfall rate values have been recorded using a fast response rain gauge installed at Sona College of Technology. The derived rainfall rates have been used to estimate attenuation in the 10-100 GHz frequency range. Using the estimated co-polar attenuation cross polar discriminations (XPD) have been computed using ITU-R(2002) model in the 10-35 GHz range. The study shows that attenuation and cross polarization vary with frequency, elevation angle and rainfall rate. The study also depicts the cumulative distribution of rainfall rate, attenuation and XPD.

Monsoon Rainfall and Landslides in Nepal

NASA Astrophysics Data System (ADS)

Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

2009-12-01

A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of antecedent rainfall in triggering landslides. It is noticed that a moderate correlation exists between the antecedent rainfalls of 3 to 10 days and the daily rainfall at failure in the Nepal Himalaya. The rainfall thresholds are utilized to develop early warning systems. Taking reference of the intensity-duration threshold and normalized rainfall intensity threshold, two proto-type models of early warning systems (RIEWS and N-RIEWS) are proposed. Early warning models show less time for evacuation in the case of short duration and high intensity rainfall, whereas for long duration rainfall, warning time is enough and when warning information disseminate to the people, people will aware to possible landslide risk. In the meantime, they will be mentally ready to tackle with possible disaster of coming hours or days and will avoid the consequences. On the basis of coarse hydro-meteorological data of developing country like Nepal, this simple and rather easy model of early warning will certainly help to reduce fatalities from landslides.

Tree cover in sub-Saharan Africa: rainfall and fire constrain forest and savanna as alternative stable states.

PubMed

Staver, A Carla; Archibald, Sally; Levin, Simon

2011-05-01

Savannas are known as ecosystems with tree cover below climate-defined equilibrium values. However, a predictive framework for understanding constraints on tree cover is lacking. We present (a) a spatially extensive analysis of tree cover and fire distribution in sub-Saharan Africa, and (b) a model, based on empirical results, demonstrating that savanna and forest may be alternative stable states in parts of Africa, with implications for understanding savanna distributions. Tree cover does not increase continuously with rainfall, but rather is constrained to low (<50%, "savanna") or high tree cover (>75%, "forest"). Intermediate tree cover rarely occurs. Fire, which prevents trees from establishing, differentiates high and low tree cover, especially in areas with rainfall between 1000 mm and 2000 mm. Fire is less important at low rainfall (<1000 mm), where rainfall limits tree cover, and at high rainfall (>2000 mm), where fire is rare. This pattern suggests that complex interactions between climate and disturbance produce emergent alternative states in tree cover. The relationship between tree cover and fire was incorporated into a dynamic model including grass, savanna tree saplings, and savanna trees. Only recruitment from sapling to adult tree varied depending on the amount of grass in the system. Based on our empirical analysis and previous work, fires spread only at tree cover of 40% or less, producing a sigmoidal fire probability distribution as a function of grass cover and therefore a sigmoidal sapling to tree recruitment function. This model demonstrates that, given relatively conservative and empirically supported assumptions about the establishment of trees in savannas, alternative stable states for the same set of environmental conditions (i.e., model parameters) are possible via a fire feedback mechanism. Integrating alternative stable state dynamics into models of biome distributions could improve our ability to predict changes in biome distributions and in carbon storage under climate and global change scenarios.

Mean Excess Function as a method of identifying sub-exponential tails: Application to extreme daily rainfall

NASA Astrophysics Data System (ADS)

Nerantzaki, Sofia; Papalexiou, Simon Michael

2017-04-01

Identifying precisely the distribution tail of a geophysical variable is tough, or, even impossible. First, the tail is the part of the distribution for which we have the less empirical information available; second, a universally accepted definition of tail does not and cannot exist; and third, a tail may change over time due to long-term changes. Unfortunately, the tail is the most important part of the distribution as it dictates the estimates of exceedance probabilities or return periods. Fortunately, based on their tail behavior, probability distributions can be generally categorized into two major families, i.e., sub-exponentials (heavy-tailed) and hyper-exponentials (light-tailed). This study aims to update the Mean Excess Function (MEF), providing a useful tool in order to asses which type of tail better describes empirical data. The MEF is based on the mean value of a variable over a threshold and results in a zero slope regression line when applied for the Exponential distribution. Here, we construct slope confidence intervals for the Exponential distribution as functions of sample size. The validation of the method using Monte Carlo techniques on four theoretical distributions covering major tail cases (Pareto type II, Log-normal, Weibull and Gamma) revealed that it performs well especially for large samples. Finally, the method is used to investigate the behavior of daily rainfall extremes; thousands of rainfall records were examined, from all over the world and with sample size over 100 years, revealing that heavy-tailed distributions can describe more accurately rainfall extremes.

Occurrence of aromatic amines and N-nitrosamines in the different steps of a drinking water treatment plant.

PubMed

Jurado-Sánchez, Beatriz; Ballesteros, Evaristo; Gallego, Mercedes

2012-09-15

The occurrence of 24 amines within a full scale drinking water treatment plant that used chlorinated agents as disinfectants was evaluated for the first time in this research. Prior to any treatment (raw water), aniline, 3-chloroaniline, 3,4-dichloroaniline and N-nitrosodimethylamine were detected at low levels (up to 18 ng/L) but their concentration increased ∼10 times after chloramination while 9 new amines were produced (4 aromatic amines and 5 N-nitrosamines). Within subsequent treatments, there were no significant changes in the amine levels, although the concentrations of 2-nitroaniline, N-nitrosodimethylamine and N-nitrosodiethylamine increased slightly within the distribution system. Eleven of the 24 amines studied were undetected either in the raw and in the treatment plant samples analysed. There is an important difference in the behaviour of the aromatic amines and N-nitrosamines with respect to water temperature and rainfall events. Amine concentrations were higher in winter due to low water temperatures, this effect being more noticeable for N-nitrosamines. Aromatic amines were detected at their highest concentrations (especially 3,4-dichloroaniline and 2-nitroaniline) in treated water after rainfall events. These results may be explained by the increase in the levels of amine precursors (pesticides and their degradation products) in raw water since the rainfall facilitated the transport of these compounds from soil which was previously contaminated as a result of intensive agricultural practices. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

[Ecological suitability regionalization for Gastrodia elata in Zhaotong based on Maxent and ArcGIS].

PubMed

Shi, Zi-Wei; Ma, Cong-Ji; Kang, Chuan-Zhi; Wang, Li; Zhang, Zhi-Hui; Chen, Jun-Fei; Zhang, Xiao-Bo; Liu, Da-Hui

2016-09-01

In this paper, the potential distribution information and ecological suitability regionalization for Gastrodia elata in Zhaotong were studied based on the climate, terrain, soil and vegetation factors analysis by Maxent and ArcGIS. The results showed that the highly potential distribution (suitability index>0.6) mainly located in Zhaotong, Yunnan province（Zhenxiong,Yiliang and Daguan county, with an area of 2 872 km²）, and Bijie, Guizhou province （Hezhang,Bijie,Weining county, 1 251 km²）. The AUC of ROC curve was above 0.99, indicating that the predictive results with the Maxent model were highly precise. The main ecological factors determining the potential distribution were the altitude, average rainfall in November, average rainfall in October, vegetation types, average rainfall in March, average rainfall in April,soil types,isothermal characteristic and average rainfall in June. The environmental variables in the highly potential areas were determined as altitude around 1 450-2 200 m,annual average temperature around 18.0-20.4 ℃,annual average precipitation around 900 mm,yellow soil or yellow brown soil,and acid sandy loam or slightly acidic sandy loam.The results will provide valuable references for plantation regionalization and the siting for imitation wild planting of G. elata in Zhaotong. Copyright© by the Chinese Pharmaceutical Association.

Counting Raindrops and the Distribution of Intervals Between Them.

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Ten Veldhuis, M. C.; Hut, R.; Pape, J. J.

2017-12-01

Drop size distributions are often assumed to follow a generalized gamma function, characterized by one parameter, Λ, [1]. In principle, this Λ can be estimated by measuring the arrival rate of raindrops. The arrival rate should follow a Poisson distribution. By measuring the distribution of the time intervals between drops arriving at a certain surface area, one should not only be able to estimate the arrival rate but also the robustness of the underlying assumption concerning steady state. It is important to note that many rainfall radar systems also assume fixeddrop size distributions, and associated arrival rates, to derive rainfall rates. By testing these relationships with a simple device, we will be able to improve both land-based and space-based radar rainfall estimates. Here, an open-hardware sensor design is presented, consisting of a 3D printed housing for a piezoelectric element, some simple electronics and an Arduino. The target audience for this device are citizen scientists who want to contribute to collecting rainfall information beyond the standard rain gauge. The core of the sensor is a simple piezo-buzzer, as found in many devices such as watches and fire alarms. When a raindrop falls on a piezo-buzzer, a small voltage is generated , which can be used to register the drop's arrival time. By registering the intervals between raindrops, the associated Poisson distribution can be estimated. In addition to the hardware, we will present the first results of a measuring campaign in Myanmar that will have ran from August to October 2017. All design files and descriptions are available through GitHub: https://github.com/nvandegiesen/Intervalometer. This research is partially supported through the TWIGA project, funded by the European Commission's H2020 program under call SC5-18-2017 `Novel in-situ observation systems'. Reference [1]: Uijlenhoet, R., and J. N. M. Stricker. "A consistent rainfall parameterization based on the exponential raindrop size distribution." Journal of Hydrology 218, no. 3 (1999): 101-127.

The multi-parameter remote measurement of rainfall

NASA Technical Reports Server (NTRS)

Atlas, D.; Ulbrich, C. W.; Meneghini, R.

1982-01-01

The measurement of rainfall by remote sensors is investigated. One parameter radar rainfall measurement is limited because both reflectivity and rain rate are dependent on at least two parameters of the drop size distribution (DSD), i.e., representative raindrop size and number concentration. A generalized rain parameter diagram is developed which includes a third distribution parameter, the breadth of the DSD, to better specify rain rate and all possible remote variables. Simulations show the improvement in accuracy attainable through the use of combinations of two and three remote measurables. The spectrum of remote measurables is reviewed. These include path integrated techniques of radiometry and of microwave and optical attenuation.

Application of Archimedean copulas to the impact assessment of hydro-climatic variables in semi-arid aquifers of western India

NASA Astrophysics Data System (ADS)

Wable, Pawan S.; Jha, Madan K.

2018-02-01

The effects of rainfall and the El Niño Southern Oscillation (ENSO) on groundwater in a semi-arid basin of India were analyzed using Archimedean copulas considering 17 years of data for monsoon rainfall, post-monsoon groundwater level (PMGL) and ENSO Index. The evaluated dependence among these hydro-climatic variables revealed that PMGL-Rainfall and PMGL-ENSO Index pairs have significant dependence. Hence, these pairs were used for modeling dependence by employing four types of Archimedean copulas: Ali-Mikhail-Haq, Clayton, Gumbel-Hougaard, and Frank. For the copula modeling, the results of probability distributions fitting to these hydro-climatic variables indicated that the PMGL and rainfall time series are best represented by Weibull and lognormal distributions, respectively, while the non-parametric kernel-based normal distribution is the most suitable for the ENSO Index. Further, the PMGL-Rainfall pair is best modeled by the Clayton copula, and the PMGL-ENSO Index pair is best modeled by the Frank copula. The Clayton copula-based conditional probability of PMGL being less than or equal to its average value at a given mean rainfall is above 70% for 33% of the study area. In contrast, the spatial variation of the Frank copula-based probability of PMGL being less than or equal to its average value is 35-40% in 23% of the study area during El Niño phase, while it is below 15% in 35% of the area during the La Niña phase. This copula-based methodology can be applied under data-scarce conditions for exploring the impacts of rainfall and ENSO on groundwater at basin scales.

Satellite-observed latent heat release in a tropical cyclone

NASA Technical Reports Server (NTRS)

Adler, R. F.; Rodgers, E. B.

1976-01-01

Data from the Nimbus 5 electrically scanning microwave radiometer (ESMR) are used to make calculations of the latent heat release (L.H.R.) and the distribution of rainfall rate in a tropical cyclone as it grows from a tropical disturbance to a typhoon. The L.H.R. (calculated over a circular area of 4 deg latitude radius) increases during the development and intensification of the storm from a magnitude of 2.7 X 10 to the 21st power ergs/s (in the disturbance stage) to 8.8 X 10 to the 21st power ergs (typhoon stage). The latter value corresponds to a mean rainfall rate of 2.0 mm hr/s. The more intense the cyclone and the greater the L.H.R., the greater the percentage contribution of the larger rainfall rates to the L.H.R. In the disturbance stage the percentage contribution of rainfall rates less than or minus 6 mm hr/s is typically 8%; for the typhoon stage, the value is 38%. The distribution of rainfall rate as a function of radial distance from the center indicates that as the cyclone intensifies, the higher rainfall rates tend to concentrate toward the center of the circulation.

Scale effect challenges in urban hydrology highlighted with a Fully Distributed Model and High-resolution rainfall data

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2017-04-01

Nowadays, there is a growing interest on small-scale rainfall information, provided by weather radars, to be used in urban water management and decision-making. Therefore, an increasing interest is in parallel devoted to the development of fully distributed and grid-based models following the increase of computation capabilities, the availability of high-resolution GIS information needed for such models implementation. However, the choice of an appropriate implementation scale to integrate the catchment heterogeneity and the whole measured rainfall variability provided by High-resolution radar technologies still issues. This work proposes a two steps investigation of scale effects in urban hydrology and its effects on modeling works. In the first step fractal tools are used to highlight the scale dependency observed within distributed data used to describe the catchment heterogeneity, both the structure of the sewer network and the distribution of impervious areas are analyzed. Then an intensive multi-scale modeling work is carried out to understand scaling effects on hydrological model performance. Investigations were conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model was implemented at 17 spatial resolutions ranging from 100 m to 5 m and modeling investigations were performed using both rain gauge rainfall information as well as high resolution X band radar data in order to assess the sensitivity of the model to small scale rainfall variability. Results coming out from this work demonstrate scale effect challenges in urban hydrology modeling. In fact, fractal concept highlights the scale dependency observed within distributed data used to implement hydrological models. Patterns of geophysical data change when we change the observation pixel size. The multi-scale modeling investigation performed with Multi-Hydro model at 17 spatial resolutions confirms scaling effect on hydrological model performance. Results were analyzed at three ranges of scales identified in the fractal analysis and confirmed in the modeling work. The sensitivity of the model to small-scale rainfall variability was discussed as well.

Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China)

NASA Astrophysics Data System (ADS)

Li, Dan; Christakos, George; Ding, Xinxin; Wu, Jiaping

2018-01-01

Spatial rainfall data is an essential input to Distributed Hydrological Models (DHM), and a significant contributor to hydrological model uncertainty. Model uncertainty is higher when rain gauges are sparse, as is often the case in practice. Currently, satellite-based precipitation products increasingly provide an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment is required before implementation. Accordingly, the twofold objective of this work paper was the real-world assessment of both (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, and (b) the TRMM product's role in forcing data for hydrologic simulations in the area of the Tiaoxi catchment (Taihu lake basin, China). The TRMM rainfall products used in this study are the Version-7 real-time 3B42RT and the post-real-time 3B42. It was found that the TRMM rainfall data showed a superior performance at the monthly and annual scales, fitting well with surface observation-based frequency rainfall distributions. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) and the relative bias ratio (BIAS) were used to evaluate hydrologic model performance. The satisfactory performance of the monthly runoff simulations in the Tiaoxi study supports the view that the implementation of real-time 3B42RT allows considerable room for improvement. At the same time, post-real-time 3B42 can be a valuable tool of hydrologic modeling, water balance analysis, and basin water resource management, especially in developing countries or at remote locations in which rainfall gauges are scarce.

Characteristics of Atmospheric Pollutants Distribution and Removal Effect of Rainfall on Atmospheric Pollutants in Mining Cities

NASA Astrophysics Data System (ADS)

Wen-feng, Tang; You-biao, Hu

2018-05-01

This paper studies the characteristics of atmospheric pollutant (SO2, NO2, PM2.5 and PM10) and the effects of rainfall on the removal of atmospheric pollutants. The results show atmospheric pollutants concentration vary in different seasons and functional area: atmospheric pollutants concentration in summer and autumn is lower than that in winter and spring; the concentration of SO2 and NO2 in coal-chemical industry areas and light industrial areas is higher, the concentration difference of PM2.5 and PM10 in different functional areas is very small, the removal efficiency of rainfall on atmospheric pollutant is gradually improved with the increasing of daily rainfall, rainfall intensity and rainfall duration, the ability of rainfall to remove pollutants tends to be stable after daily rainfall and rainfall intensity exceeds 30mm and 20mm/h respectively, the effect of rainfall on the removal of PM2.5 was slightly worse than the effect of rainfall on other atmospheric pollutants, the rainfall duration should be 60min, 60min and 80min respectively when the effect of rainfall on NO2, PM10 and SO2 tends to be stable.

[Infiltration characteristics of soil water on loess slope land under intermittent and repetitive rainfall conditions].

PubMed

Li, Yi; Shao, Ming-An

2008-07-01

Based on the experiments of controlled intermittent and repetitive rainfall on slope land, the infiltration and distribution characteristics of soil water on loess slope land were studied. The results showed that under the condition of intermittent rainfall, the cumulative runoff during two rainfall events increased linearly with time, and the wetting front also increased with time. In the interval of the two rainfall events, the wetting front increased slowly, and the infiltration rate was smaller on steeper slope than on flat surface. During the second rainfall event, there was an obvious decreasing trend of infiltration rate with time. The cumulative infiltration on 15 degrees slope land was larger than that of 25 degrees slope land, being 178 mm and 88 mm, respectively. Under the condition of repetitive rainfall, the initial infiltration rate during each rainfall event was relatively large, and during the first rainfall, both the infiltration rate and the cumulative infiltration at various stages were larger than those during the other three rainfall events. However, after the first rainfall, there were no obvious differences in the infiltration rate among the next three rainfall events. The more the rainfall event, the deeper the wetting front advanced.

Systematic errors in the simulation of the Asian summer monsoon: the role of rainfall variability on a range of time and space scales

NASA Astrophysics Data System (ADS)

Martin, Gill; Levine, Richard; Klingaman, Nicholas; Bush, Stephanie; Turner, Andrew; Woolnough, Steven

2015-04-01

Despite considerable efforts worldwide to improve model simulations of the Asian summer monsoon, significant biases still remain in climatological seasonal mean rainfall distribution, timing of the onset, and northward and eastward extent of the monsoon domain (Sperber et al., 2013). Many modelling studies have shown sensitivity to convection and boundary layer parameterization, cloud microphysics and land surface properties, as well as model resolution. Here we examine the problems in representing short-timescale rainfall variability (related to convection parameterization), problems in representing synoptic-scale systems such as monsoon depressions (related to model resolution), and the relationship of each of these with longer-term systematic biases. Analysis of the spatial distribution of rainfall intensity on a range of timescales ranging from ~30 minutes to daily, in the MetUM and in observations (where available), highlights how rainfall biases in the South Asian monsoon region on different timescales in different regions can be achieved in models through a combination of the incorrect frequency and/or intensity of rainfall. Over the Indian land area, the typical dry bias is related to sub-daily rainfall events being too infrequent, despite being too intense when they occur. In contrast, the wet bias regions over the equatorial Indian Ocean are mainly related to too frequent occurrence of lower-than-observed 3-hourly rainfall accumulations which result in too frequent occurrence of higher-than-observed daily rainfall accumulations. This analysis sheds light on the model deficiencies behind the climatological seasonal mean rainfall biases that many models exhibit in this region. Changing physical parameterizations alters this behaviour, with associated adjustments in the climatological rainfall distribution, although the latter is not always improved (Bush et al., 2014). This suggests a more complex interaction between the diabatic heating and the large-scale circulation than is indicated by the intensity and frequency of rainfall alone. Monsoon depressions and low pressure systems are important contributors to monsoon rainfall over central and northern India, areas where MetUM climate simulations typically show deficient monsoon rainfall. Analysis of MetUM climate simulations at resolutions ranging from N96 (~135km) to N512 (~25km) suggests that at lower resolution the numbers and intensities of monsoon depressions and low pressure systems and their associated rainfall are very low compared with re-analyses/observations. We show that there are substantial increases with horizontal resolution, but resolution is not the only factor. Idealised simulations, either using nudged atmospheric winds or initialised coupled hindcasts, which improve (strengthen) the mean state monsoon and cyclonic circulation over the Indian peninsula, also result in a substantial increase in monsoon depressions and associated rainfall. This suggests that a more realistic representation of monsoon depressions is possible even at lower resolution if the larger-scale systematic error pattern in the monsoon is improved.

Statistical description of large datasets of Cumulated and Duration values related to shallow landslides initiated by rainfalls

NASA Astrophysics Data System (ADS)

Pisano, Luca; Vessia, Giovanna; Vennari, Carmela; Parise, Mario

2015-04-01

Empirical rainfall thresholds are a well established method to draw information about Duration (D) and Cumulated (E) values of the rainfalls that are likely to initiate shallow landslides. To this end, rain-gauge records of rainfall heights are commonly used. Several procedures can be applied to address the calculation of the Duration-Cumulated height and, eventually, the Intensity values related to the rainfall events responsible for shallow landslide onset. A large number of procedures are drawn from particular geological settings and climate conditions based on an expert identification of the rainfall event. A few researchers recently devised automated procedures to reconstruct the rainfall events responsible for landslide onset. In this study, 300 pairs of D, E couples, related to shallow landslides that occurred in a ten year span 2002-2012 on the Italian territory, have been drawn by means of two procedures: the expert method (Brunetti et al., 2010) and the automated method (Vessia et al., 2014). The two procedures start from the same sources of information on shallow landslides occurred during or soon after a rainfall. Although they have in common the method to select the date (up to the hour of the landslide occurrence), the site of the landslide and the choice of the rain-gauge representative for the rainfall, they differ when calculating the Duration and Cumulated height of the rainfall event. Moreover, the expert procedure identifies only one D, E pair for each landslide whereas the automated procedure draws 6 possible D,E pairs for the same landslide event. Each one of the 300 D, E pairs calculated by the automated procedure reproduces about 80% of the E values and about 60% of the D values calculated by the expert procedure. Unfortunately, no standard methods are available for checking the forecasting ability of both the expert and the automated reconstruction of the true D, E pairs that result in shallow landslide. Nonetheless, a statistical analysis on marginal distributions of the seven samples of 300 D and E values are performed in this study. The main objective of this statistical analysis is to highlight similarities and differences in the two sets of samples of Duration and Cumulated values collected by the two procedures. At first, the sample distributions have been investigated: the seven E samples are Lognormal distributed, whereas the D samples are all distributed Weibull like. On E samples, due to their Lognormal distribution, statistical tests can be applied to check two null hypotheses: equal mean values through the Student test, equal standard deviations through the Fisher test. These two hypotheses are accepted for the seven E samples, meaning that they come from the same population, at a confidence level of 95%. Conversely, the preceding tests cannot be applied to the seven D samples that are Weibull distributed with shape parameters k ranging between 0.9 to 1.2. Nonetheless, the two procedures calculate the rainfall event through the selection of the E values; after that the D is drawn. Thus, the results of this statistical analysis preliminary confirms the similarities of the two D,E pair set of values drawn from the two different procedures. References Brunetti, M.T., Peruccacci, S., Rossi, M., Luciani, S., Valigi, D., and Guzzetti, F.: Rainfall thresholds for the possible occurrence of landslides in Italy, Nat. Hazards Earth Syst. Sci., 10, 447-458, doi:10.5194/nhess-10-447-2010, 2010. Vessia G., Parise M., Brunetti M.T., Peruccacci S., Rossi M., Vennari C., and Guzzetti F.: Automated reconstruction of rainfall events responsible for shallow landslides, Nat. Hazards Earth Syst. Sci., 14, 2399-2408, doi: 10.5194/nhess-14-2399-2014, 2014.

The analysis of the possibility of using 10-minute rainfall series to determine the maximum rainfall amount with 5 minutes duration

NASA Astrophysics Data System (ADS)

Kaźmierczak, Bartosz; Wartalska, Katarzyna; Wdowikowski, Marcin; Kotowski, Andrzej

2017-11-01

Modern scientific research in the area of heavy rainfall analysis regarding to the sewerage design indicates the need to develop and use probabilistic rain models. One of the issues that remains to be resolved is the length of the shortest amount of rain to be analyzed. It is commonly believed that the best time is 5 minutes, while the least rain duration measured by the national services is often 10 or even 15 minutes. Main aim of this paper is to present the difference between probabilistic rainfall models results given from rainfall time series including and excluding 5 minutes rainfall duration. Analysis were made for long-time period from 1961-2010 on polish meteorological station Legnica. To develop best fitted to measurement rainfall data probabilistic model 4 probabilistic distributions were used. Results clearly indicates that models including 5 minutes rainfall duration remains more appropriate to use.

Using the raindrop size distribution to quantify the soil detachment rate at the laboratory scale

NASA Astrophysics Data System (ADS)

Jomaa, S.; Jaffrain, J.; Barry, D. A.; Berne, A.; Sander, G. C.

2010-05-01

Rainfall simulators are beneficial tools for studying soil erosion processes and sediment transport for different circumstances and scales. They are useful to better understand soil erosion mechanisms and, therefore, to develop and validate process-based erosion models. Simulators permit experimental replicates for both simple and complex configurations. The 2 m × 6 m EPFL erosion flume is equipped with a hydraulic slope control and a sprinkling system located on oscillating bars 3 m above the surface. It provides a near-uniform spatial rainfall distribution. The intensity of the precipitation can be adjusted by changing the oscillation interval. The flume is filled to a depth of 0.32 m with an agricultural loamy soil. Raindrop detachment is an important process in interrill erosion, the latter varying with the soil properties as well as the raindrop size distribution and drop velocity. Since the soil detachment varies with the kinetic energy of raindrops, an accurate characterization of drop size distribution (DSD, measured, e.g., using a laser disdrometer) can potentially support erosion calculations. Here, a laser disdrometer was used at different rainfall intensities in the EPFL flume to quantify the rainfall event in terms of number of drops, diameter and velocity. At the same time, soil particle motion was measured locally using splash cups. These cups measured the detached material rates into upslope and downslope compartments. In contrast to previously reported splash cup experiments, the cups used in this study were equipped at the top with upside-down funnels, the upper part having the same diameter as the soil sampled at the bottom. This ensured that the soil detached and captured by the device was not re-exposed to rainfall. The experimental data were used to quantify the relationship between the raindrop distribution and the splash-driven sediment transport.

Interaction between the effects of evaporation rate and amount of simulated rainfall on development of the free-living stages of Haemonchus contortus.

PubMed

O'Connor, Lauren J; Kahn, Lewis P; Walkden-Brown, Stephen W

2008-08-17

A factorial experiment (3 x 4 x 2 x 3) was conducted in programmable incubators to investigate interaction between the effects of rainfall amount, rainfall distribution and evaporation rate on development of Haemonchus contortus to L3. Sheep faeces containing H. contortus eggs were incubated on sterilised soil under variable temperatures typical of summer in the Northern Tablelands of NSW, Australia. Simulated rainfall was applied in 1 of 3 amounts (12, 24 or 32 mm) and 4 distributions (a single event on the day after deposition, or the same total amount split in 2, 3 or 4 equal events over 2, 3 or 4 days, respectively). Samples were incubated at either a Low or High rate of evaporation (Low: 2.1-3.4 mm/day and High: 3.8-6.1 mm/day), and faeces and soil were destructively sampled at 4, 7 and 14 days post-deposition. Recovery of L3 from the soil (extra-pellet L3) increased over time (up to 0.52% at day 14) and with each increment of rainfall (12 mm: <0.01%; 24 mm: 0.10%; 32 mm: 0.45%) but was reduced under the High evaporation rate (0.01%) compared with the Low evaporation rate (0.31%). All rainfall amounts yielded significantly different recoveries of L3 under Low evaporation rates but there was no difference between the 12 and 24 mm treatments under the High evaporation rate. The distribution of simulated rainfall did not significantly affect recovery of infective larvae. Faecal moisture content was positively associated with L3 recovery, as was the ratio of cumulative precipitation and cumulative evaporation (P/E), particularly when measured in the first 4 days post-deposition. The results show that evaporation rate plays a significant role in regulating the influence of rainfall amount on the success of L3 transmission.

A Study on Regional Rainfall Frequency Analysis for Flood Simulation Scenarios

NASA Astrophysics Data System (ADS)

Jung, Younghun; Ahn, Hyunjun; Joo, Kyungwon; Heo, Jun-Haeng

2014-05-01

Recently, climate change has been observed in Korea as well as in the entire world. The rainstorm has been gradually increased and then the damage has been grown. It is very important to manage the flood control facilities because of increasing the frequency and magnitude of severe rain storm. For managing flood control facilities in risky regions, data sets such as elevation, gradient, channel, land use and soil data should be filed up. Using this information, the disaster situations can be simulated to secure evacuation routes for various rainfall scenarios. The aim of this study is to investigate and determine extreme rainfall quantile estimates in Uijeongbu City using index flood method with L-moments parameter estimation. Regional frequency analysis trades space for time by using annual maximum rainfall data from nearby or similar sites to derive estimates for any given site in a homogeneous region. Regional frequency analysis based on pooled data is recommended for estimation of rainfall quantiles at sites with record lengths less than 5T, where T is return period of interest. Many variables relevant to precipitation can be used for grouping a region in regional frequency analysis. For regionalization of Han River basin, the k-means method is applied for grouping regions by variables of meteorology and geomorphology. The results from the k-means method are compared for each region using various probability distributions. In the final step of the regionalization analysis, goodness-of-fit measure is used to evaluate the accuracy of a set of candidate distributions. And rainfall quantiles by index flood method are obtained based on the appropriate distribution. And then, rainfall quantiles based on various scenarios are used as input data for disaster simulations. Keywords: Regional Frequency Analysis; Scenarios of Rainfall Quantile Acknowledgements This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

A stationary criterion to identify the duration of efficient rainfalls to trigger shallow landslide

NASA Astrophysics Data System (ADS)

Vessia, G.; Parise, M.

2012-04-01

Even though rainfall is considered a well known trigger of natural slope instability, its effective role in initiating landsliding phenomena cannot be easily distinguished due to many time- and space- variable interactions among several factors (i.e. slope geometry, mechanical and hydraulic characters of superficial layers and the basin, etc.). A common approach to relate rainfall to the onset of shallow landslides is to plot effective rainfall intensity vs duration to draw intensity threshold lines. Since the earliest work by Caine (1980) on this topic, several researchers have tried to establish intensity thresholds by means of deterministic and probabilistic approaches from a number of worldwide and regional rainfall-landslide inventories. With respect to this intensity-duration threshold approach, information about rainfall-induced landslides are generally collected from chronicles or historical landslide time series, whilst no data about the hydraulic and geometric features of soils and rocks involved into the natural slope instability is commonly taken into account. On the contrary, rainfall heights at different time lag (even every 30 min) are available at different stations by rain gauges. As rain gauge measurements are concerned, these can suffer many problems such as temporary saturation, temporary lack of data transmission and anomalous geographical distribution of the rainfall. Recently, satellite data have been employed to quantify the rainfall event related to landslide occurrence but their correlation to the effective rainfall height at a site is not guaranteed yet. So far, rain gauge measures still represent the most used option. Moreover, the physical simplification introduced by such "rainfall based" approach on landslide prediction can be accepted due to the assumption that only shallow landslides are considered for drawing a regional intensity-duration threshold from the considered data. Starting from the above considerations, and within the framework of a nationwide project by CNR-IRPI, under funds from the National Civil Department, the authors propose in this article a new criterion to identify from rain gauge measures the duration of the rainfalls triggering shallow landslides. The new criterion represents an attempt to identify the duration of the "effective rainfall event" responsible for the landslide occurrence, as reported by newspaper clips and/or in real time web newspapers. At this regard, antecedent precipitations are not taken into account, since the model considers only that amount of rainfall that effectively triggers the slope failure. The model analyses the hourly rainfall time series for at least one month before occurrence of the shallow landslide, using a historical landslide archive covering the time range between 2002 and 2011 in the Lazio Region, central Italy. This archive was obtained by a procedure consisting of the following steps: i) critical scrutiny of chronicles, ii) identification of the landslide site, and iii) retrieval of the rainfall data from the nearest rain gauge station within the pluviometric network provided by the National Department of Civil Protection. The proposed method, for each reported landslide, uses the cumulative function of the rainfall heights and rainfall intensity calculated for different time lag. Then, in order to identify the beginning of the effective rainfall event, two conditions have to be satisfied: (1) the difference in rainfall intensity between two adjacent windows must be very low, and (2) the time series of lack of rainfall must be stationary. When these conditions are met, the initial time of the efficient rainfall necessary to trigger the landslide is established. Such criterion is statistically based according to the rainfall time distribution only. No assumption is needed on the probabilistic distributions of time series of rain/not rain. Such approach has been successfully applied to medium-to-long rainfalls, for which rain/not rain datasets are statistically significant. Very short rainfall durations (i.e. a few hours), due to the small number of data, are not suitable to this approach, but, on the other hand, their onset is generally easily recognizable by visual inspection of the height pluviometric trends.

Climatological determinants of woody cover in Africa.

PubMed

Good, Stephen P; Caylor, Kelly K

2011-03-22

Determining the factors that influence the distribution of woody vegetation cover and resolving the sensitivity of woody vegetation cover to shifts in environmental forcing are critical steps necessary to predict continental-scale responses of dryland ecosystems to climate change. We use a 6-year satellite data record of fractional woody vegetation cover and an 11-year daily precipitation record to investigate the climatological controls on woody vegetation cover across the African continent. We find that-as opposed to a relationship with only mean annual rainfall-the upper limit of fractional woody vegetation cover is strongly influenced by both the quantity and intensity of rainfall events. Using a set of statistics derived from the seasonal distribution of rainfall, we show that areas with similar seasonal rainfall totals have higher fractional woody cover if the local rainfall climatology consists of frequent, less intense precipitation events. Based on these observations, we develop a generalized response surface between rainfall climatology and maximum woody vegetation cover across the African continent. The normalized local gradient of this response surface is used as an estimator of ecosystem vegetation sensitivity to climatological variation. A comparison between predicted climate sensitivity patterns and observed shifts in both rainfall and vegetation during 2009 reveals both the importance of rainfall climatology in governing how ecosystems respond to interannual fluctuations in climate and the utility of our framework as a means to forecast continental-scale patterns of vegetation shifts in response to future climate change.

Grain size indicators of sedimentary coupling between hillslopes and channels in a dryland basin

NASA Astrophysics Data System (ADS)

Hollings, Rory; Michealides, Katerina; Bliss Singer, Michael

2017-04-01

In dryland landscapes, heterogeneous and short-lived rainstorms generate runoff on slopes and streamflow in channels, which drive sediment movement from hillslope surfaces to channels and the transport of bed material sediment within channels. Long-term topographic evolution of drainage basins is partly determined by the relative balance of hillslope sediment supply to channels and the evacuation of channel sediment. However, it is not clear whether supply or evacuation is dominant over longer timescales (>>100 y) within dryland basins. One important indicator of local cumulative sediment transport is grain size (GS). On dryland hillslopes, grain size is governed over long timescales by weathering, but on short time scales (events to decades), is controlled by event-driven transport of the debris mantle. In the channel, GS reflects the input of hillslope sediment and the selective transport of particles along the bed. It is currently unknown how these two processes are expressed systematically within GS distributions on slopes and in channels within drylands, but this information could be useful to explain the history of the relative balance between hillslope sediment supply to channels and net sediment transport in the channel. We investigate this problem by combining field measurements of surface sediment grain size distributions in channels and on hillslopes with 1m LiDAR topography, >60 years of rainfall and channel discharge data from the Walnut Gulch Experimental Watershed (WGEW) in Arizona, and simple calculations of grain-sized based local stress distributions for various rainfall and discharge events. Hydrological scenarios of overland flow on hillslopes and channel flow conditions were derived from distributions of historic data at WGEW and were selected to reflect the wide range of storm intensities and durations, and channel discharges. 1) We used three quartiles of the entire distribution of measured discharge values for 80 locations throughout the channel network to represent low, medium and high flows. 2) For rainfall we used three quartiles of the entire distribution of measured rainfall intensity and duration from 85 rain gauges spanning the basin, to derive low, medium and high rainfall durations. We then calculated the corresponding rainfall intensities based on four intensity-duration curves that were characteristic of different parts of the phase space of the measured data-points. 3) The derived rainfall intensities and durations were converted into hillslope overland flow using Coup2D (a hillslope rainfall-runoff model) for 44 hillslopes within WGEW for which we have GS and topographic data. We employ the median grain size (D50) to compare stress metrics on hillslopes and in channel for each location. Typically, low-order streams experience greater influxes of hillslope derived sediment than is evacuated by the channel. However, the main channel stem is characterised by sediment removal in most scenarios including low discharge, long duration rainfall, suggesting most hillslope supplied sediment is balanced by channel evacuation. Near tributary junctions, and close to the mouth of the basin there are fluctuations in net balance of sediment transport from evacuation- to supply-dominance for different scenarios. These fluctuations could influence channel bed GS distribution and longitudinal profile development.

The Influence of Soil Moisture and Wind on Rainfall Distribution and Intensity in Florida

NASA Technical Reports Server (NTRS)

Baker, R. David; Lynn, Barry H.; Boone, Aaron; Tao, Wei-Kuo

1998-01-01

Land surface processes play a key role in water and energy budgets of the hydrological cycle. For example, the distribution of soil moisture will affect sensible and latent heat fluxes, which in turn may dramatically influence the location and intensity of precipitation. However, mean wind conditions also strongly influence the distribution of precipitation. The relative importance of soil moisture and wind on rainfall location and intensity remains uncertain. Here, we examine the influence of soil moisture distribution and wind distribution on precipitation in the Florida peninsula using the 3-D Goddard Cumulus Ensemble (GCE) cloud model Coupled with the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. This study utilizes data collected on 27 July 1991 in central Florida during the Convection and Precipitation Electrification Experiment (CaPE). The idealized numerical experiments consider a block of land (the Florida peninsula) bordered on the east and on the west by ocean. The initial soil moisture distribution is derived from an offline PLACE simulation, and the initial environmental wind profile is determined from the CaPE sounding network. Using the factor separation technique, the precise contribution of soil moisture and wind to rainfall distribution and intensity is determined.

Required spatial resolution of hydrological models to evaluate urban flood resilience measures

NASA Astrophysics Data System (ADS)

Gires, A.; Giangola-Murzyn, A.; Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.

2012-04-01

During a flood in urban area, several non-linear processes (rainfall, surface runoff, sewer flow, and sub-surface flow) interact. Fully distributed hydrological models are a useful tool to better understand these complex interactions between natural processes and man built environment. Developing an efficient model is a first step to improve the understanding of flood resilience in urban area. Given that the previously mentioned underlying physical phenomenon exhibit different relevant scales, determining the required spatial resolution of such model is tricky but necessary issue. For instance such model should be able to properly represent large scale effects of local scale flood resilience measures such as stop logs. The model should also be as simple as possible without being simplistic. In this paper we test two types of model. First we use an operational semi-distributed model over a 3400 ha peri-urban area located in Seine-Saint-Denis (North-East of Paris). In this model, the area is divided into sub-catchments of average size 17 ha that are considered as homogenous, and only the sewer discharge is modelled. The rainfall data, whose resolution is 1 km is space and 5 min in time, comes from the C-band radar of Trappes, located in the West of Paris, and operated by Météo-France. It was shown that the spatial resolution of both the model and the rainfall field did not enable to fully grasp the small scale rainfall variability. To achieve this, first an ensemble of realistic rainfall fields downscaled to a resolution of 100 m is generated with the help of multifractal space-time cascades whose characteristic exponents are estimated on the available radar data. Second the corresponding ensemble of sewer hydrographs is simulated by inputting each rainfall realization to the model. It appears that the probability distribution of the simulated peak flow exhibits a power-law behaviour. This indicates that there is a great uncertainty associated with small scale rainfall. Second we focus on a 50 ha catchment of this area and implement Multi-Hydro, a fully distributed urban hydrological model currently being developed at Ecole des Ponts ParisTech (El Tabach et al., 2009). The version used in this paper consists in an interactive coupling between a 2D model representing infiltration and surface runoff (TREX, Two dimensional Runoff, Erosion and eXport model, Velleux et al., 2011) and a 1D model of sewer networks (SWMM, Storm Water Management Model, Rossman, 2007). Spatial resolution ranging from 2 m to 50 m for land use, topography and rainfall are tested. A special highlight on the impact of small scales rainfall is done. To achieve this the previously mentioned methodology is implemented with rainfall fields downscaled to 10 m in space and 20 s in time. Finally, we will discuss the gains generated by the implementation of the fully distributed model.

Using organic biomarkers to trace the transport pathways of livestock-derived organic matter in the soil subsurface.

NASA Astrophysics Data System (ADS)

Lloyd, Charlotte; Michaelides, Katerina; Evershed, Richard; Chadwick, David; Dungait, Jennifer

2010-05-01

We explore the use of organic biomarkers as tracers for different components of livestock-derived organic matter (LD-OM) at two different spatial scales. We conducted six small-scale rainfall simulation experiments on a 30 × 30 × 30 cm soil lysimeter, following an application of bovine slurry at a rate of 5 l m-2. Throughout the experiment timed samples of leachate from the base of the lysimeter were collected, then soil cores were taken following the rainfall simulation. These samples were analysed in order to identify the most suitable biomarkers to trace dissolved and sediment-bound LD-OM respectively. The results showed that ammonium was an important tracer compound for dissolved LD-OM, along with other key low molecular weight compounds such as carbohydrates and amino acids. Analysis of the soil cores confirmed that compounds 5-β sigmastanol and 5-β epistigmastanol (5-β stanols) could be used very effectively to trace the sediment-bound and colloidal component of LD-OM. These specific organic compounds, which are identifiable by GC/MS analysis, only occur due to biohydrogenation of plant sterols in a ruminant gut, providing a unique opportunity to trace bovine faecal matter via sediment pathways. These tracers were then applied to a larger 3-D hillslope system by using University of Bristol's TRACE (Test Rig for Advancing Connectivity Experiments) facility. TRACE is a large-scale dual axis soil-slope measuring 6 m long × 2.5 m wide × 0.3 m deep accompanied by a 6-nozzle rainfall simulator. In these experiments slurry was only applied to the top 1 m section of the hillslope, in order to trace how the LD-OM was transported in the soil system. The slope allows the collection of leachate from the soil surface, from lateral through-flow and infiltrated water which reached the soil base (indicating deeper pathways). This enabled the distinction between LD-OM transported via different hydrological pathways. Soil cores were also taken across the soil surface and analysed for 5-β stanols, this allowed the spatial distribution of LD-OM to be determined following the rainfall event. The results showed that not only is LD-OM transported on the surface of the hillslope via overland flow, but the dissolved component infiltrates through the soil profile and is transported via deeper hydrological flowpaths. 5-β stanol analysis showed that soil erosion processes were extremely important, as LD-OM was found downslope of the application area and in eroded material lost from the base of the experimental hillslope. These experiments provided new insights into how LD-OM interacts with the soil-water system and allows quantification of the contamination risk posed. This is important as 90 million tonnes of LD-OM is applied to land annually in the UK. It is well known that there is a potential for contamination of water courses by nitrate, ammonium and other faecal-derived pollutants such as E. Coli through runoff from treated land. Pollution from LD-OM has now been shown to extend to the contamination of subsurface pathways and potentially groundwater resources.

Ability of WRF to Simulate Rainfall Distribution Over West Africa: Role of Horizontal Resolution and Dynamical Processes

NASA Astrophysics Data System (ADS)

Kouadio, K.; Konare, A.; Bastin, S.; Ajayi, V. O.

2016-12-01

This research work focused on the thorny problem of the representation of rainfall over West Africa and particularly in the Gulf of Guinea and its surroundings by Regional Climate Models (RCMs). The sensitivities of Weather Research and Forecasting (WRF) Model are tested for changes in horizontal resolution (convective permitting versus parameterized) on the replication of West African Climate in year 2014 and also changes in microphysics (MP) and planetary boundary layer (PBL) schemes on June 2014. The sensitivity to horizontal resolution study show that both runs at 24km and 4km (explicit convection) resolution fairly replicate the general distribution of the rainfall over West African region. The analysis also reveals a good replication of the dynamical features of West African monsoon system including Tropical Easterly Jet (TEJ), African Easterly Jet (AEJ), monsoon flow and the West African Heat Low (WAHL). Some differences have been noticed between WRF and ERA-interim outputs irrespective to the spectral nudging used in the experiment which then suggest strong interactions between scales. The link between the seasonal displacement of the WAHL and the spatial distribution of the rainfall and the Sahelian onset is confirmed in this study. The results also show an improvement on the replication of rainfall with the very high resolution run observed at daily scale over the Sahel while a dry bias is observed in WRF simulations of the rainfall over Ivorian Coast and in the Gulf of Guinea. Generally, over the Guinean coast the high resolution run did not provide subsequent improvement on the replication of rainfall. The sensitivity of WRF to MP and PBL on rainfall replication study reveals that the most significant added value over the Guinean coast and surroundings area is provided by the configurations that used the PBL Asymmetric Convective Model V2 (ACM2) suggesting more influence of the PBL compared to MP. The change on microphysics and planetary boundary layer schemes in general, seems to have less effect on the explicit runs into the replication of the rainfall over the Gulf of Guinea and the surroundings seaboard.

Stochastic generation of hourly rainstorm events in Johor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nojumuddin, Nur Syereena; Yusof, Fadhilah; Yusop, Zulkifli

2015-02-03

Engineers and researchers in water-related studies are often faced with the problem of having insufficient and long rainfall record. Practical and effective methods must be developed to generate unavailable data from limited available data. Therefore, this paper presents a Monte-Carlo based stochastic hourly rainfall generation model to complement the unavailable data. The Monte Carlo simulation used in this study is based on the best fit of storm characteristics. Hence, by using the Maximum Likelihood Estimation (MLE) and Anderson Darling goodness-of-fit test, lognormal appeared to be the best rainfall distribution. Therefore, the Monte Carlo simulation based on lognormal distribution was usedmore » in the study. The proposed model was verified by comparing the statistical moments of rainstorm characteristics from the combination of the observed rainstorm events under 10 years and simulated rainstorm events under 30 years of rainfall records with those under the entire 40 years of observed rainfall data based on the hourly rainfall data at the station J1 in Johor over the period of 1972–2011. The absolute percentage error of the duration-depth, duration-inter-event time and depth-inter-event time will be used as the accuracy test. The results showed the first four product-moments of the observed rainstorm characteristics were close with the simulated rainstorm characteristics. The proposed model can be used as a basis to derive rainfall intensity-duration frequency in Johor.« less

Toward an operational tool to simulate green roof hydrological impact at the basin scale: a new version of the distributed rainfall-runoff model Multi-Hydro.

PubMed

Versini, Pierre-Antoine; Gires, Auguste; Tchinguirinskaia, Ioulia; Schertzer, Daniel

2016-10-01

Currently widespread in new urban projects, green roofs have shown a positive impact on urban runoff at the building scale: decrease and slow-down of the peak discharge, and decrease of runoff volume. The present work aims to study their possible impact at the catchment scale, more compatible with stormwater management issues. For this purpose, a specific module dedicated to simulating the hydrological behaviour of a green roof has been developed in the distributed rainfall-runoff model (Multi-Hydro). It has been applied on a French urban catchment where most of the building roofs are flat and assumed to accept the implementation of a green roof. Catchment responses to several rainfall events covering a wide range of meteorological situations have been simulated. The simulation results show green roofs can significantly reduce runoff volume and the magnitude of peak discharge (up to 80%) depending on the rainfall event and initial saturation of the substrate. Additional tests have been made to assess the susceptibility of this response regarding both spatial distributions of green roofs and precipitation. It appears that the total area of greened roofs is more important than their locations. On the other hand, peak discharge reduction seems to be clearly dependent on spatial distribution of precipitation.

High temporal resolution of extreme rainfall rate variability and the acoustic classification of rainfall

NASA Astrophysics Data System (ADS)

Nystuen, Jeffrey A.; Amitai, Eyal

2003-04-01

The underwater sound generated by raindrop splashes on a water surface is loud and unique allowing detection, classification and quantification of rainfall. One of the advantages of the acoustic measurement is that the listening area, an effective catchment area, is proportional to the depth of the hydrophone and can be orders of magnitude greater than other in situ rain gauges. This feature allows high temporal resolution of the rainfall measurement. A series of rain events with extremely high rainfall rates, over 100 mm/hr, is examined acoustically. Rapid onset and cessation of rainfall intensity are detected within the convective cells of these storms with maximum 5-s resolution values exceeding 1000 mm/hr. The probability distribution functions (pdf) for rainfall rate occurrence and water volume using the longer temporal resolutions typical of other instruments do not include these extreme values. The variance of sound intensity within different acoustic frequency bands can be used as an aid to classify rainfall type. Objective acoustic classification algorithms are proposed. Within each rainfall classification the relationship between sound intensity and rainfall rate is nearly linear. The reflectivity factor, Z, also has a linear relationship with rainfall rate, R, for each rainfall classification.

[Rainfall and soil moisture redistribution induced by xerophytic shrubs in an arid desert ecosystem].

PubMed

Wang, Zheng Ning; Wang, Xin Ping; Liu, Bo

2016-03-01

Rainfall partitioning by desert shrub canopy modifies the redistribution of incident rainfall under the canopy, and may affect the distribution pattern of soil moisture around the plant. This study examined the distribution of rainfall and the response of soil moisture beneath the canopy of two dominant desert shrubs, Caragana korshinskii and Artemisia ordosica, in the revegetation area at the southeastern edge of the Tengger Desert. The results showed that throughfall and stemflow ave-ragely occupied 74.4%, 11.3% and 61.8%, 5.5% of the gross precipitation for C. korshinskii and A. ordosica, respectively. The mean coefficients of variation (CV) of throughfall were 0.25 and 0.30, respectively. C. korshinski were more efficient than A. ordosica on stemflow generation. The depth of soil wetting front around the stem area was greater than other areas under shrub canopy for C. korshinski, and it was only significantly greater under bigger rain events for A. ordosica. The shrub canopy could cause the unevenness of soil wetting front under the canopy in consequence of rainfall redistribution induced by xerophytic shrub.

Calibration of a distributed routing rainfall-runoff model at four urban sites near Miami, Florida

USGS Publications Warehouse

Doyle, W. Harry; Miller, Jeffrey E.

1980-01-01

Urban stormwater data from four Miami, Fla. catchments were collected and compiled by the U.S. Geological Survey and were used for testing the applicability of deterministic modeling for characterizing stormwater flows from small land-use areas. A description of model calibration and verification is presented for: (1) A 40.8 acre single-family residential area, (2) a 58.3-acre highway area, (3) a 20.4-acre commercial area, and (4) a 14.7-acre multifamily residential area. Rainfall-runoff data for 80, 108, 114, and 52 storms at sites, 1, 2, 3, and 4, respectively, were collected, analyzed, and stored on direct-access files. Rainfall and runoff data for these storms (at 1-minute time intervals) were used in flow-modeling simulation analyses. A distributed routing Geological Survey rainfall-runoff model was used to determine rainfall excess and route overland and channel flows at each site. Optimization of soil-moisture- accounting and infiltration parameters was performed during the calibration phases. The results of this study showed that, with qualifications, an acceptable verification of the Geological Survey model can be achieved. (Kosco-USGS)

Heating Structures Derived from Satellite

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Adler, R.; Haddad, Z.; Hou, A.; Kakar, R.; Krishnamurti, T. N.; Kummerow, C.; Lang, S.; Meneghini, R.; Olson, W.

2004-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid, and solid water. The Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan space project, was launched in November 1997. It provides an accurate measurement of rainfall over the global tropics which can be used to estimate the four-dimensional structure of latent heating over the global tropics. The distributions of rainfall and inferred heating can be used to advance our understanding of the global energy and water cycle. This paper describes several different algorithms for estimating latent heating using TRMM observations. The strengths and weaknesses of each algorithm as well as the heating products are also discussed. The validation of heating products will be exhibited. Finally, the application of this heating information to global circulation and climate models is presented.

On the properties of stochastic intermittency in rainfall processes.

PubMed

Molini, A; La, Barbera P; Lanza, L G

2002-01-01

In this work we propose a mixed approach to deal with the modelling of rainfall events, based on the analysis of geometrical and statistical properties of rain intermittency in time, combined with the predictability power derived from the analysis of no-rain periods distribution and from the binary decomposition of the rain signal. Some recent hypotheses on the nature of rain intermittency are reviewed too. In particular, the internal intermittent structure of a high resolution pluviometric time series covering one decade and recorded at the tipping bucket station of the University of Genova is analysed, by separating the internal intermittency of rainfall events from the inter-arrival process through a simple geometrical filtering procedure. In this way it is possible to associate no-rain intervals with a probability distribution both in virtue of their position within the event and their percentage. From this analysis, an invariant probability distribution for the no-rain periods within the events is obtained at different aggregation levels and its satisfactory agreement with a typical extreme value distribution is shown.

A Model Based on Environmental Factors for Diameter Distribution in Black Wattle in Brazil

PubMed Central

Sanquetta, Carlos Roberto; Behling, Alexandre; Dalla Corte, Ana Paula; Péllico Netto, Sylvio; Rodrigues, Aurelio Lourenço; Simon, Augusto Arlindo

2014-01-01

This article discusses the dynamics of a diameter distribution in stands of black wattle throughout its growth cycle using the Weibull probability density function. Moreover, the parameters of this distribution were related to environmental variables from meteorological data and surface soil horizon with the aim of finding a model for diameter distribution which their coefficients were related to the environmental variables. We found that the diameter distribution of the stand changes only slightly over time and that the estimators of the Weibull function are correlated with various environmental variables, with accumulated rainfall foremost among them. Thus, a model was obtained in which the estimators of the Weibull function are dependent on rainfall. Such a function can have important applications, such as in simulating growth potential in regions where historical growth data is lacking, as well as the behavior of the stand under different environmental conditions. The model can also be used to project growth in diameter, based on the rainfall affecting the forest over a certain time period. PMID:24932909

Mixed memory, (non) Hurst effect, and maximum entropy of rainfall in the tropical Andes

NASA Astrophysics Data System (ADS)

Poveda, Germán

2011-02-01

Diverse linear and nonlinear statistical parameters of rainfall under aggregation in time and the kind of temporal memory are investigated. Data sets from the Andes of Colombia at different resolutions (15 min and 1-h), and record lengths (21 months and 8-40 years) are used. A mixture of two timescales is found in the autocorrelation and autoinformation functions, with short-term memory holding for time lags less than 15-30 min, and long-term memory onwards. Consistently, rainfall variance exhibits different temporal scaling regimes separated at 15-30 min and 24 h. Tests for the Hurst effect evidence the frailty of the R/ S approach in discerning the kind of memory in high resolution rainfall, whereas rigorous statistical tests for short-memory processes do reject the existence of the Hurst effect. Rainfall information entropy grows as a power law of aggregation time, S( T) ˜ Tβ with < β> = 0.51, up to a timescale, TMaxEnt (70-202 h), at which entropy saturates, with β = 0 onwards. Maximum entropy is reached through a dynamic Generalized Pareto distribution, consistently with the maximum information-entropy principle for heavy-tailed random variables, and with its asymptotically infinitely divisible property. The dynamics towards the limit distribution is quantified. Tsallis q-entropies also exhibit power laws with T, such that Sq( T) ˜ Tβ( q) , with β( q) ⩽ 0 for q ⩽ 0, and β( q) ≃ 0.5 for q ⩾ 1. No clear patterns are found in the geographic distribution within and among the statistical parameters studied, confirming the strong variability of tropical Andean rainfall.

Extreme rainfall events: Learning from raingauge time series

NASA Astrophysics Data System (ADS)

Boni, G.; Parodi, A.; Rudari, R.

2006-08-01

SummaryThis study analyzes the historical records of annual rainfall maxima recorded in Northern Italy, cumulated over time windows (durations) of 1 and 24 h and considered paradigmatic descriptions of storms of both short and long duration. Three large areas are studied: Liguria, Piedmont and Triveneto (Triveneto includes the Regions of Veneto, Trentino Alto Adige and Friuli Venezia Giulia). A regional frequency analysis of annual rainfall maxima is carried out through the Two Components Extreme Value (TCEV) distribution. A hierarchical approach is used to define statistically homogeneous areas so that the definition of a regional distribution becomes possible. Thanks to the peculiar nature of the TCEV distribution, a frequency-based threshold criterion is proposed. Such criterion allows to distinguish the observed ordinary values from the observed extra-ordinary values of annual rainfall maxima. A second step of this study focuses on the analysis of the probability of occurrence of extra-ordinary events over a period of one year. Results show the existence of a four month dominant season that maximizes the number of occurrences of annual rainfall maxima. Such results also show how the seasonality of extra-ordinary events changes whenever a different duration of events is considered. The joint probability of occurrence of extreme storms of short and long duration is also analyzed. Such analysis demonstrates how the joint probability of occurrence significantly changes when all rainfall maxima or only extra-ordinary maxima are used. All results undergo a critical discussion. Such discussion seems to lead to the point that the identified statistical characteristics might represent the landmark of those mechanisms causing heavy precipitation in the analyzed regions.

Comparison between Pludix and impact/optical disdrometers during rainfall measurement campaigns

NASA Astrophysics Data System (ADS)

Caracciolo, Clelia; Prodi, Franco; Uijlenhoet, Remko

2006-11-01

The performances of two couples of disdrometers based on different measuring principles are compared: a classical Joss-Waldvogel disdrometer and a recently developed device, called the Pludix tested in Ferrara, Italy, and Pludix and the two-dimensional video disdrometer (2DVD) tested in Cabauw, The Netherlands. First, the measuring principles of the different instruments are presented and compared. Secondly, the performances of the two pairs of disdrometers are analysed by comparing their rain amounts with nearby tipping bucket rain gauges and the inferred drop size distributions. The most important rainfall integral parameters (e.g. rain rate and radar reflectivity) and drop size distribution parameters are also analysed and compared. The data set for Ferrara comprises 13 rainfall events, with a total of 20 mm of rainfall and a maximum rain rate of 4 mm h - 1 . The data set for Cabauw consists of 9 events, with 25-50 mm of rainfall and a maximum rain rate of 20-40 mm h - 1 . The Pludix tends to underestimate slightly the bulk rainfall variables in less intense events, whereas it tends to overestimate with respect to the other instruments in heavier events. The correspondence of the inferred drop size distributions with those measured by the other disdrometers is reasonable, particularly with the Joss-Waldvogel disdrometer. Considering that the Pludix is still in a calibration and testing phase, the reported results are encouraging. A new signal inversion algorithm, which will allow the detection of rain drops throughout the entire diameter interval between 0.3 and 7.0 mm, is under development.

Rainfall over Friuli-Venezia Giulia: High amounts and strong geographical gradients

NASA Astrophysics Data System (ADS)

Ceschia, M.; Micheletti, St.; Carniel, R.

1991-12-01

The precipitation distribution over Friuli-Venezia Giulia — the easternmost region of Northern Italy extending from the Adriatic Sea to the Alps — has been studied. Monthly rainfall data over the region and the bordering areas of Veneto and Slovenia during the period from 1951 to 1986 have been analyzed by standard statistical methods, including cluster analysis. The overall results emphasize a distribution with rainfall increasing from the sea to the prealpine areas. The highest precipitations were recorded over the Musi-Canin range, with average values exceeding 3 200 mm per year. Noteworthy is the unforeseen subdivision of the region by the clustering procedure by means of the Angot index.

A web service and android application for the distribution of rainfall estimates and Earth observation data

NASA Astrophysics Data System (ADS)

Mantas, V. M.; Liu, Z.; Pereira, A. J. S. C.

2015-04-01

The full potential of Satellite Rainfall Estimates (SRE) can only be realized if timely access to the datasets is possible. Existing data distribution web portals are often focused on global products and offer limited customization options, especially for the purpose of routine regional monitoring. Furthermore, most online systems are designed to meet the needs of desktop users, limiting the compatibility with mobile devices. In response to the growing demand for SRE and to address the current limitations of available web portals a project was devised to create a set of freely available applications and services, available at a common portal that can: (1) simplify cross-platform access to Tropical Rainfall Measuring Mission Online Visualization and Analysis System (TOVAS) data (including from Android mobile devices), (2) provide customized and continuous monitoring of SRE in response to user demands and (3) combine data from different online data distribution services, including rainfall estimates, river gauge measurements or imagery from Earth Observation missions at a single portal, known as the Tropical Rainfall Measuring Mission (TRMM) Explorer. The TRMM Explorer project suite includes a Python-based web service and Android applications capable of providing SRE and ancillary data in different intuitive formats with the focus on regional and continuous analysis. The outputs include dynamic plots, tables and data files that can also be used to feed downstream applications and services. A case study in Southern Angola is used to describe the potential of the TRMM Explorer for SRE distribution and analysis in the context of ungauged watersheds. The development of a collection of data distribution instances helped to validate the concept and identify the limitations of the program, in a real context and based on user feedback. The TRMM Explorer can successfully supplement existing web portals distributing SRE and provide a cost-efficient resource to small and medium-sized organizations with specific SRE monitoring needs, namely in developing and transition countries.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; ...

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ˜25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

An assessment of the feasibility of the use of satellite-only rainfall estimates for the hydrological monitoring in central Italy

NASA Astrophysics Data System (ADS)

Campo, Lorenzo; Caparrini, Francesca

2013-04-01

The need for accurate distributed hydrological modelling has constantly increased in last years for several purposes: agricultural applications, water resources management, hydrological balance at watershed scale, floods forecast. The main input for the hydrological numerical models is rainfall data that present, at the same time, a large availability of measures (in gauged regions, with respect to other micro-meteorological variables) and the most complex spatial patterns. While also in presence of densely gauged watersheds the spatial interpolation of the rainfall is a non-trivial problem, due to the spatial intermittence of the variable (especially at finer temporal scales), ungauged regions need an alternative source of rainfall data in order to perform the hydrological modelling. Such source can be constituted by the satellite-estimated rainfall fields, with reference to both geostationary and polar-orbit platforms. In this work the rainfall product obtained by the Aqua-AIRS sensor were used in order to assess the feasibility of the use of satellite-based rainfall as input for distributed hydrological modelling. The MOBIDIC (MOdello di BIlancio Distribuito e Continuo) model, developed at the Department of civil and Environmental Engineering of the University of Florence and operationally used by Tuscany Region and Umbria Region for flood prediction and management, was used for the experiments. In particular three experiments were carried on: a) hydrological simulation with the use of rain-gauges data, b) simulation with the use of satellite-only rainfall estimates, c) simulation with the combined use of the two sources of data in order to obtain an optimal estimate of the actual rainfall fields. The domain of the study was the central Italy. Several critical events occurred in the area were analyzed. A discussion of the results is provided.

Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

NASA Astrophysics Data System (ADS)

Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

2018-01-01

The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

What rainfall events trigger landslides on the West Coast US?

NASA Astrophysics Data System (ADS)

Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

2016-04-01

A dataset of landslide occurrences compiled by collating google news reports covers 9 full years of data. We show that, while this compilation cannot provide consistent and widespread monitoring everywhere, it is adequate to capture the distribution of events in the major urban areas of the West Coast US and it can be used to provide a quantitative relationship between landslides and rainfall events. The case of the Seattle metropolitan area is presented as an example. The landslide dataset shows a clear seasonality in landslide occurrence, corresponding to the seasonality of rainfall, modified by the accumulation of soil moisture as winter progresses. Interannual variability of landslide occurrences is also linked to interannual variability of monthly rainfall. In most instances, landslides are clustered on consecutive days or at least within the same pentad and correspond to days of large rainfall accumulation at the regional scale. A joint analysis of the landslide data and of the high-resolution PRISM daily rainfall accumulation shows that on days when landslides occurred, the distribution of rainfall was shifted, with rainfall accumulation higher than 10mm/day being more common. Accumulations above 50mm/day much increase the probability of landslides, including the possibility of a major landslide event (one with multiple landslides in a day). The synoptic meteorological conditions associated with these major events show a mid-tropospheric ridge to the south of the target area steering a surface low and bringing enhanced precipitable water towards the Pacific North West. The interaction of the low-level flow with the local orography results in instances of a strong Puget Sound Convergence Zone, with widespread rainfall accumulation above 30mm/day and localized maxima as high as 100mm/day or more.

Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; Burt, Melissa A.; ...

2016-02-01

This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization—Super-Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual-mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double-ITCZ bias. However, unfolding intensity distributions reveal several improvementsmore » in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden-Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM’s low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved-scale processes in CAM, few differences discriminate the rainfall properties of the two models. Lastly, these results are discussed in light of their implication for future rainfall changes in response to climate forcing.« less

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present‐Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

PubMed Central

Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-01-01

Abstract Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large‐scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large‐scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large‐scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large‐scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale‐aware parameterizations, but also reveal unrecognized trade‐offs from the entanglement of precipitation frequency and total amount. PMID:29861837

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Hong, Yang; Huffman, George J.

2006-01-01

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Temporal and spatial characteristics of annual and seasonal rainfall in Malawi

NASA Astrophysics Data System (ADS)

Ngongondo, Cosmo; Xu, Chong-Yu; Gottschalk, Lars; Tallaksen, Lena M.; Alemaw, Berhanu

2010-05-01

An understanding of the temporal and spatial characteristics of rainfall is central to water resources planning and management. However, such information is often limited in many developing countries like Malawi. In an effort to bridge the information gap, this study examined the temporal and spatial charecteristics of rainfall in Malawi. Rainfall readings from 42 stations across Malawi from 1960 to 2006 were analysed at monthly, annual and seasonal scales. The Malawian rainfall season lasts from November to April. The data were firstly subjected to quality checks through the cumulative deviations test and the Standard Normal Homogeinity Test (SNHT). Monthly distribution in a typical year, called heterogeneity, was investigated using the Precipitation Concentration Index (PCI). Further, normalized precipitation anomaly series of annual rainfall series (AR) and the PCI (APCI) were used to test for interannual rainfall variability. Spatial variability was characterised by fitting the Spatial Correlation function (SCF). The nonparametric Mann-Kendall statistic was used to investigate the temporal trends of the various rainfall variables. The results showed that 40 of the stations passed both data quality tests. For the two stations that failed, the data were adjusted using nearby stations. Annual and seasonal rainfall were found to be characterised by high spatial variation. The country mean annual rainfall was 1095 mm with mean interannual variability of 26%. The highland areas to the north and southeast of the country exhibited the highest rainfall and lowest interannual variability. Lowest rainfall coupled with high interannual variability was found in the Lower Shire basin, in the southern part of Malawi. This simillarity is the pattern of annual and seasonal rainfall should be expected because all stations had over 90% of their observed annual rainfall in the six month period between November and April. Monthly rainfall was found to be highly variable both temporally and spatially. None of the stations have stable monthly rainfall regimes (mean PCI of less than 10). Stations with the highest mean rainfall were found to have a lower interannual variability. The rainfall stations showed low spatial correlations for annual, monthly as well as seasonal timescales indicating that the data may not be suitable for spatial interpolation. However, some structure (i.e. lower correlation with distance) could be observed when aggregating the data at 50 mile intervals. The annual and seasonal rainfall series were dominated by negative trends. The spatial distribution of the trends can be described as heterogeneous, although most of the stations in the southern region have negative trends. At the monthly timescale, 37 of the stations show a negative trend with four of the stations, all in the south, showing significant negative trends. On the other hand, only 5 stations show positive trends with only one significant trend in the south. Keywords: Malawi, rainfall trends, spatial variation

Utilizing the Vertical Variability of Precipitation to Improve Radar QPE

NASA Technical Reports Server (NTRS)

Gatlin, Patrick N.; Petersen, Walter A.

2016-01-01

Characteristics of the melting layer and raindrop size distribution can be exploited to further improve radar quantitative precipitation estimation (QPE). Using dual-polarimetric radar and disdrometers, we found that the characteristic size of raindrops reaching the ground in stratiform precipitation often varies linearly with the depth of the melting layer. As a result, a radar rainfall estimator was formulated using D(sub m) that can be employed by polarimetric as well as dual-frequency radars (e.g., space-based radars such as the GPM DPR), to lower the bias and uncertainty of conventional single radar parameter rainfall estimates by as much as 20%. Polarimetric radar also suffers from issues associated with sampling the vertical distribution of precipitation. Hence, we characterized the vertical profile of polarimetric parameters (VP3)-a radar manifestation of the evolving size and shape of hydrometeors as they fall to the ground-on dual-polarimetric rainfall estimation. The VP3 revealed that the profile of ZDR in stratiform rainfall can bias dual-polarimetric rainfall estimators by as much as 50%, even after correction for the vertical profile of reflectivity (VPR). The VP3 correction technique that we developed can improve operational dual-polarimetric rainfall estimates by 13% beyond that offered by a VPR correction alone.

Adequacy of satellite derived rainfall data for stream flow modeling

USGS Publications Warehouse

Artan, G.; Gadain, Hussein; Smith, Jodie; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.

2007-01-01

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

Monitoring the Vertical Distribution of Rainfall-Induced Strain Changes in a Landslide Measured by Distributed Fiber Optic Sensing With Rayleigh Backscattering

NASA Astrophysics Data System (ADS)

Kogure, Tetsuya; Okuda, Yudai

2018-05-01

Distributed fiber optic sensing with Rayleigh backscattering, which has been recognized as a novel technique for measuring differences in temperature or strain, was adopted in a borehole to a depth of 16 m in an actual landslide to detect a vertical profile of strain changes. Strain changes were measured every 6 hr from 19 June 2017 to 18 October 2017 with a spatial resolution of 10 cm and strain resolution of 1.87 μɛ. The measurements provided a clear-cut vertical profile of the strain changes caused by rainfalls that cannot be detected by conventional methods. The results show that there are two types of deformation in the landslide mass: (1) sliding at the boundary between tuff and mudstone and (2) creep in mudstone layers. Activation of deeper sections of the landslide by heavy rainfalls has also been detected.

The assessment of Global Precipitation Measurement estimates over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Murali Krishna, U. V.; Das, Subrata Kumar; Deshpande, Sachin M.; Doiphode, S. L.; Pandithurai, G.

2017-08-01

Accurate and real-time precipitation estimation is a challenging task for current and future spaceborne measurements, which is essential to understand the global hydrological cycle. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing the global precipitation characteristics. The purpose of the GPM is to enhance the spatiotemporal resolution of global precipitation. The main objective of the present study is to assess the rainfall products from the GPM, especially the Integrated Multi-satellitE Retrievals for the GPM (IMERG) data by comparing with the ground-based observations. The multitemporal scale evaluations of rainfall involving subdaily, diurnal, monthly, and seasonal scales were performed over the Indian subcontinent. The comparison shows that the IMERG performed better than the Tropical Rainfall Measuring Mission (TRMM)-3B42, although both rainfall products underestimated the observed rainfall compared to the ground-based measurements. The analyses also reveal that the TRMM-3B42 and IMERG data sets are able to represent the large-scale monsoon rainfall spatial features but are having region-specific biases. The IMERG shows significant improvement in low rainfall estimates compared to the TRMM-3B42 for selected regions. In the spatial distribution, the IMERG shows higher rain rates compared to the TRMM-3B42, due to its enhanced spatial and temporal resolutions. Apart from this, the characteristics of raindrop size distribution (DSD) obtained from the GPM mission dual-frequency precipitation radar is assessed over the complex mountain terrain site in the Western Ghats, India, using the DSD measured by a Joss-Waldvogel disdrometer.

High-Resolution Simulation of Hurricane Bonnie (1998). Part 1; The Organization of Vertical Motion

NASA Technical Reports Server (NTRS)

Braun, Scott A.; Montgomery, Michael T.; Pu, Zhaoxia

2003-01-01

Hurricanes are well known for their strong winds and heavy rainfall, particularly in the intense rainband (eyewall) surrounding the calmer eye of the storm. In some hurricanes, the rainfall is distributed evenly around the eye so that it has a donut shape on radar images. In other cases, the rainfall is concentrated on one side of the eyewall and nearly absent on the other side and is said to be asymmetric. This study examines how the vertical air motions that produce the rainfall are distributed within the eyewall of an asymmetric hurricane and the factors that cause this pattern of rainfall. We use a sophisticated numerical forecast model to simulate Hurricane Bonnie, which occurred in late August of 1998 during a special NASA field experiment designed to study hurricanes. The simulation results suggest that vertical wind shear (a rapid change in wind speed or direction with height) caused the asymmetric rainfall and vertical air motion patterns by tilting the hurricane vortex and favoring upward air motions in the direction of tilt. Although the rainfall in the hurricane eyewall may surround more than half of the eye, the updrafts that produce the rainfall are concentrated in very small-scale, intense updraft cores that occupy only about 10% of the eyewall area. The model simulation suggests that the timing and location of individual updraft cores are controlled by intense, small-scale vortices (regions of rapidly swirling flow) in the eyewall and that the updrafts form when the vortices encounter low-level air moving into the eyewall.

Impact of the rainfall pattern on synthetic pesticides and copper runoff from a vineyard catchment

NASA Astrophysics Data System (ADS)

Payraudeau, Sylvain; Meite, Fatima; Wiegert, Charline; Imfeld, Gwenaël

2017-04-01

Runoff is a major process of pesticide transport from agricultural land to downstream aquatic ecosystems. The impact of rainfall characteristics on the transport of runoff-related pesticide is rarely evaluated at the catchment scale. Here, we evaluate the influence of rainfall pattern on the mobilization of synthetic pesticides and copper fungicides in runoff from a small vineyard catchment, both at the plot and catchment scales. During two vineyard growing seasons in 2015 and 2016 (from March to October), we monitored rainfall, runoff, and concentrations of copper and 20 fungicides and herbicides applied by winegrowers at the Rouffach vineyard catchment (France, Alsace; 42.5 ha). Rainfall data were recorded within the catchment while runoff measurement and flow-proportional water sampling were carried out at the outlet of the plot (1486 m2; 87.5 × 17 m) and the catchment. In total, discharges of the 14 runoff events were continuously monitored between March and October 2015 using bubbler flow modules combined with Venturi channels. Detailed and distributed dataset on pesticide applications were extracted from survey (copper formulations and type of pesticides, amount and application dates). Pools of copper and synthetic pesticides were quantified weekly in the topsoil (0-3 cm) by systematic sampling across the catchment. The concentrations of copper (10 mg.kg-1 dried soil) and synthetic pesticides (close to the quantification limit, i.e. 0.05 µg.L-1) available in the top soil for off-site transport largely differed over time. Between March and October, an accumulation of copper of 10% was observed in the top-soil while pesticide concentration decreased below the quantification limits after a few days or weeks following application, depending of the compounds. The average runoff generated at the plot scale was very low (0.13% ± 0.30). The maximum runoff reached 1.37% during the storm of July 22, 2015. Synthetic pesticides exported by runoff was less than 1‰ of the applications. The copper mass exported represented about 1% (i.e. 2,085 g at the plot's scale) of the seasonal input, and mainly occurred during the major storm event. Copper were mainly exported in association with suspended particulate matter (SPM) (>80% of the total load). The partitioning between dissolved and SPM phases differs for the synthetic pesticides as expected by their properties. The rainfall pattern influences concentrations and loads of copper and the pesticides. Dissolved pesticide loads normalized by the pesticide mass in soil varied with larger rainfall intensities, runoff discharges and volumes. Contrasted relationships between rainfall characteristics (i.e. intensity, duration and total amount) and the load exported suggest that mechanisms of contaminant delivery from the vineyard soil differs among the pesticides and for copper. The results support the idea that, even in small catchment areas, the rainfall pattern (i.e. rainfall intensity and duration) partly controls the transport of pesticide and copper loads in runoff. Though other factors, such as the chemical characteristics and the amount and timing of applications, are important drivers for pesticide runoff, the rainfall patterns also determine the transport of pesticides from catchment to downstream aquatic ecosystems, and thus the ecotoxicological risk.

Size distributions of manure particles released under simulated rainfall.

PubMed

Pachepsky, Yakov A; Guber, Andrey K; Shelton, Daniel R; McCarty, Gregory W

2009-03-01

Manure and animal waste deposited on cropland and grazing lands serve as a source of microorganisms, some of which may be pathogenic. These microorganisms are released along with particles of dissolved manure during rainfall events. Relatively little if anything is known about the amounts and sizes of manure particles released during rainfall, that subsequently may serve as carriers, abode, and nutritional source for microorganisms. The objective of this work was to obtain and present the first experimental data on sizes of bovine manure particles released to runoff during simulated rainfall and leached through soil during subsequent infiltration. Experiments were conducted using 200 cm long boxes containing turfgrass soil sod; the boxes were designed so that rates of manure dissolution and subsequent infiltration and runoff could be monitored independently. Dairy manure was applied on the upper portion of boxes. Simulated rainfall (ca. 32.4 mm h(-1)) was applied for 90 min on boxes with stands of either live or dead grass. Electrical conductivity, turbidity, and particle size distributions obtained from laser diffractometry were determined in manure runoff and soil leachate samples. Turbidity of leachates and manure runoff samples decreased exponentially. Turbidity of manure runoff samples was on average 20% less than turbidity of soil leachate samples. Turbidity of leachate samples from boxes with dead grass was on average 30% less than from boxes with live grass. Particle size distributions in manure runoff and leachate suspensions remained remarkably stable after 15 min of runoff initiation, although the turbidity continued to decrease. Particles had the median diameter of 3.8 microm, and 90% of particles were between 0.6 and 17.8 microm. The particle size distributions were not affected by the grass status. Because manure particles are known to affect transport and retention of microbial pathogens in soil, more information needs to be collected about the concurrent release of pathogens and manure particles during rainfall events.

Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

NASA Astrophysics Data System (ADS)

Mandal, S.; Choudhury, B. U.

2015-07-01

Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

The influence of natural factors on the spatio-temporal distribution of Oncomelania hupensis.

PubMed

Cheng, Gong; Li, Dan; Zhuang, Dafang; Wang, Yong

2016-12-01

We analyzed the influence of natural factors, such as temperature, rainfall, vegetation and hydrology, on the spatio-temporal distribution of Oncomelania hupensis and explored the leading factors influencing these parameters. The results will provide reference methods and theoretical a basis for the schistosomiasis control. GIS (Geographic Information System) spatial display and analysis were used to describe the spatio-temporal distribution of Oncomelania hupensis in the study area (Dongting Lake in Hunan Province) from 2004 to 2011. Correlation analysis was used to detect the natural factors associated with the spatio-temporal distribution of O. hupensis. Spatial regression analysis was used to quantitatively analyze the effects of related natural factors on the spatio-temporal distribution of snails and explore the dominant factors influencing this parameter. (1) Overall, the spatio-temporal distribution of O. hupensis was governed by the comprehensive effects of natural factors. In the study area, the average density of living snails showed a downward trend, with the exception of a slight rebound in 2009. The density of living snails showed significant spatial clustering, and the degree of aggregation was initially weak but enhanced later. Regions with high snail density and towns with an HH distribution pattern were mostly distributed in the plain areas in the northwestern and inlet and outlet of the lake. (2) There were space-time differences in the influence of natural factors on the spatio-temporal distribution of O. hupensis. Temporally, the comprehensive influence of natural factors on snail distribution increased first and then decreased. Natural factors played an important role in snail distribution in 2005, 2006, 2010 and 2011. Spatially, it decreased from the northeast to the southwest. Snail distributions in more than 20 towns located along the Yuanshui River and on the west side of the Lishui River were less affected by natural factors, whereas relatively larger in areas around the outlet of the lake (Chenglingji) were more affected. (3) The effects of natural factors on the spatio-temporal distribution of O. hupensis were spatio-temporally heterogeneous. Rainfall, land surface temperature, NDVI, and distance from water sources all played an important role in the spatio-temporal distribution of O. hupensis. In addition, due to the effects of the local geographical environment, the direction of the influences the average annual rainfall, land surface temperature, and NDVI had on the spatio-temporal distribution of O. hupensis were all spatio-temporally heterogeneous, and both the distance from water sources and the history of snail distribution always had positive effects on the distribution O. hupensis, but the direction of the influence was spatio-temporally heterogeneous. (4) Of all the natural factors, the leading factors influencing the spatio-temporal distribution of O. hupensis were rainfall and vegetation (NDVI), and the primary factor alternated between these two. The leading role of rainfall decreased year by year, while that of vegetation (NDVI) increased from 2004 to 2011. The spatio-temporal distribution of O. hupensis was significantly influenced by natural factors, and the influences were heterogeneous across space and time. Additionally, the variation in the spatial-temporal distribution of O. hupensis was mainly affected by rainfall and vegetation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

PubMed Central

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2018-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions. PMID:29657544

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania

PubMed Central

Tumbo, S. D.; Kihupi, N. I.; Rwehumbiza, Filbert B.

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly. PMID:28536708

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

PubMed

Msongaleli, Barnabas M; Tumbo, S D; Kihupi, N I; Rwehumbiza, Filbert B

2017-01-01

Rainfall variability has a significant impact on crop production with manifestations in frequent crop failure in semiarid areas. This study used the parameterized APSIM crop model to investigate how rainfall variability may affect yields of improved sorghum varieties based on long-term historical rainfall and projected climate. Analyses of historical rainfall indicate a mix of nonsignificant and significant trends on the onset, cessation, and length of the growing season. The study confirmed that rainfall variability indeed affects yields of improved sorghum varieties. Further analyses of simulated sorghum yields based on seasonal rainfall distribution indicate the concurrence of lower grain yields with the 10-day dry spells during the cropping season. Simulation results for future sorghum response, however, show that impacts of rainfall variability on sorghum will be overridden by temperature increase. We conclude that, in the event where harms imposed by moisture stress in the study area are not abated, even improved sorghum varieties are likely to perform poorly.

Bias adjustment of infrared-based rainfall estimation using Passive Microwave satellite rainfall data

NASA Astrophysics Data System (ADS)

Karbalaee, Negar; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2017-04-01

This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the Integrated Multisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards.

PubMed

Wright, Daniel B; Mantilla, Ricardo; Peters-Lidard, Christa D

2017-04-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

NASA Technical Reports Server (NTRS)

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2017-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, Rainy Day can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, Rainy Day can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. Rainy Day can be useful for hazard modeling under nonstationary conditions.

Impact of rainfall spatial variability on Flash Flood Forecasting

NASA Astrophysics Data System (ADS)

Douinot, Audrey; Roux, Hélène; Garambois, Pierre-André; Larnier, Kevin

2014-05-01

According to the United States National Hazard Statistics database, flooding and flash flooding have caused the largest number of deaths of any weather-related phenomenon over the last 30 years (Flash Flood Guidance Improvement Team, 2003). Like the storms that cause them, flash floods are very variable and non-linear phenomena in time and space, with the result that understanding and anticipating flash flood genesis is far from straightforward. In the U.S., the Flash Flood Guidance (FFG) estimates the average number of inches of rainfall for given durations required to produce flash flooding in the indicated county. In Europe, flash flood often occurred on small catchments (approximately 100 km2) and it has been shown that the spatial variability of rainfall has a great impact on the catchment response (Le Lay and Saulnier, 2007). Therefore, in this study, based on the Flash flood Guidance method, rainfall spatial variability information is introduced in the threshold estimation. As for FFG, the threshold is the number of millimeters of rainfall required to produce a discharge higher than the discharge corresponding to the first level (yellow) warning of the French flood warning service (SCHAPI: Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations). The indexes δ1 and δ2 of Zoccatelli et al. (2010), based on the spatial moments of catchment rainfall, are used to characterize the rainfall spatial distribution. Rainfall spatial variability impacts on warning threshold and on hydrological processes are then studied. The spatially distributed hydrological model MARINE (Roux et al., 2011), dedicated to flash flood prediction is forced with synthetic rainfall patterns of different spatial distributions. This allows the determination of a warning threshold diagram: knowing the spatial distribution of the rainfall forecast and therefore the 2 indexes δ1 and δ2, the threshold value is read on the diagram. A warning threshold diagram is built for each studied catchment. The proposed methodology is applied on three Mediterranean catchments often submitted to flash floods. The new forecasting method as well as the Flash Flood Guidance method (uniform rainfall threshold) are tested on 25 flash floods events that had occurred on those catchments. Results show a significant impact of rainfall spatial variability. Indeed, it appears that the uniform rainfall threshold (FFG threshold) always overestimates the observed rainfall threshold. The difference between the FFG threshold and the proposed threshold ranges from 8% to 30%. The proposed methodology allows the calculation of a threshold more representative of the observed one. However, results strongly depend on the related event duration and on the catchment properties. For instance, the impact of the rainfall spatial variability seems to be correlated with the catchment size. According to these results, it seems to be interesting to introduce information on the catchment properties in the threshold calculation. Flash Flood Guidance Improvement Team, 2003. River Forecast Center (RFC) Development Management Team. Final Report. Office of Hydrologic Development (OHD), Silver Spring, Mary-land. Le Lay, M. and Saulnier, G.-M., 2007. Exploring the signature of climate and landscape spatial variabilities in flash flood events: Case of the 8-9 September 2002 Cévennes-Vivarais catastrophic event. Geophysical Research Letters, 34(L13401), doi:10.1029/2007GL029746. Roux, H., Labat, D., Garambois, P.-A., Maubourguet, M.-M., Chorda, J. and Dartus, D., 2011. A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments. Nat. Hazards Earth Syst. Sci. J1 - NHESS, 11(9), 2567-2582. Zoccatelli, D., Borga, M., Zanon, F., Antonescu, B. and Stancalie, G., 2010. Which rainfall spatial information for flash flood response modelling? A numerical investigation based on data from the Carpathian range, Romania. Journal of Hydrology, 394(1-2), 148-161.

Evaluation of rainfall structure on hydrograph simulation: Comparison of radar and interpolated methods, a study case in a tropical catchment

NASA Astrophysics Data System (ADS)

Velasquez, N.; Ochoa, A.; Castillo, S.; Hoyos Ortiz, C. D.

2017-12-01

The skill of river discharge simulation using hydrological models strongly depends on the quality and spatio-temporal representativeness of precipitation during storm events. All precipitation measurement strategies have their own strengths and weaknesses that translate into discharge simulation uncertainties. Distributed hydrological models are based on evolving rainfall fields in the same time scale as the hydrological simulation. In general, rainfall measurements from a dense and well maintained rain gauge network provide a very good estimation of the total volume for each rainfall event, however, the spatial structure relies on interpolation strategies introducing considerable uncertainty in the simulation process. On the other hand, rainfall retrievals from radar reflectivity achieve a better spatial structure representation but with higher uncertainty in the surface precipitation intensity and volume depending on the vertical rainfall characteristics and radar scan strategy. To assess the impact of both rainfall measurement methodologies on hydrological simulations, and in particular the effects of the rainfall spatio-temporal variability, a numerical modeling experiment is proposed including the use of a novel QPE (Quantitative Precipitation Estimation) method based on disdrometer data in order to estimate surface rainfall from radar reflectivity. The experiment is based on the simulation of 84 storms, the hydrological simulations are carried out using radar QPE and two different interpolation methods (IDW and TIN), and the assessment of simulated peak flow. Results show significant rainfall differences between radar QPE and the interpolated fields, evidencing a poor representation of storms in the interpolated fields, which tend to miss the precise location of the intense precipitation cores, and to artificially generate rainfall in some areas of the catchment. Regarding streamflow modelling, the potential improvement achieved by using radar QPE depends on the density of the rain gauge network and its distribution relative to the precipitation events. The results for the 84 storms show a better model skill using radar QPE than the interpolated fields. Results using interpolated fields are highly affected by the dominant rainfall type and the basin scale.

Effects of variable regolith depth, hydraulic properties, and rainfall on debris-flow initiation during the September 2013 northern Colorado Front Range rainstorm

NASA Astrophysics Data System (ADS)

Baum, R. L.; Coe, J. A.; Kean, J. W.; Jones, E. S.; Godt, J.

2015-12-01

Heavy rainfall during 9 - 13 September 2013 induced about 1100 debris flows in the foothills and mountains of the northern Colorado Front Range. Weathered bedrock was partially exposed in the basal surfaces of many of the shallow source areas at depths ranging from 0.2 to 5 m. Typical values of saturated hydraulic conductivity of soils and regolith units mapped in the source areas range from about 10-4 - 10-6 m/s, with a median value of 2.8 x 10-5 m/s based on number of source areas in each map unit. Rainfall intensities varied spatially and temporally, from 0 to 2.5 x 10-5 m/s (90 mm/hour), with two periods of relatively heavy rainfall on September 12 - 13. The distribution of debris flows appears to correlate with total storm rainfall, and reported times of greatest landslide activity coincide with times of heaviest rainfall. Process-based models of rainfall infiltration and slope stability (TRIGRS) representing the observed ranges of regolith depth, hydraulic conductivity, and rainfall intensity, provide additional insights about the timing and distribution of debris flows from this storm. For example, small debris flows from shallower source areas (<2 m) occurred late on September 11 and in the early morning of September 12, whereas large debris flows from deeper (3 - 5 m) source areas in the western part of the affected area occurred late on September 12. Timing of these flows can be understood in terms of the time required for pore pressure rise depending on regolith depth and rainfall intensity. The variable hydraulic properties combined with variable regolith depth and slope angles account for much of the observed range in timing in areas of similar rainfall intensity and duration. Modeling indicates that the greatest and most rapid pore pressure rise likely occurred in areas of highest rainfall intensity and amount. This is consistent with the largest numbers of debris flows occurring on steep canyon walls in areas of high total storm rainfall.

Cluster analysis for characterization of rainfalls and CSO behaviours in an urban drainage area of Tokyo.

PubMed

Yu, Yang; Kojima, Keisuke; An, Kyoungjin; Furumai, Hiroaki

2013-01-01

Combined sewer overflow (CSO) from urban areas is recognized as a major pollutant source to the receiving waters during wet weather. This study attempts to categorize rainfall events and corresponding CSO behaviours to reveal the relationship between rainfall patterns and CSO behaviours in the Shingashi urban drainage areas of Tokyo, Japan where complete service by a combined sewer system (CSS) and CSO often takes place. In addition, outfalls based on their annual overflow behaviours were characterized for effective storm water management. All 117 rainfall events recorded in 2007 were simulated by a distributed model InfoWorks CS to obtain CSO behaviours. The rainfall events were classified based on two sets of parameters of rainfall pattern as well as CSO behaviours. Clustered rainfall and CSO groups were linked by similarity analysis. Results showed that both small and extreme rainfalls had strong correlations with the CSO behaviours, while moderate rainfall had a weak relationship. This indicates that important and negligible rainfalls from the viewpoint of CSO could be identified by rainfall patterns, while influences from the drainage area and network should be taken into account when estimating moderate rainfall-induced CSO. Additionally, outfalls were finally categorized into six groups indicating different levels of impact on the environment.

Using CHIRPS Rainfall Dataset to detect rainfall trends in West Africa

NASA Astrophysics Data System (ADS)

Blakeley, S. L.; Husak, G. J.

2016-12-01

In West Africa, agriculture is often rain-fed, subjecting agricultural productivity and food availability to climate variability. Agricultural conditions will change as warming temperatures increase evaporative demand, and with a growing population dependent on the food supply, farmers will become more reliant on improved adaptation strategies. Development of such adaptation strategies will need to consider West African rainfall trends to remain relevant in a changing climate. Here, using the CHIRPS rainfall product (provided by the Climate Hazards Group at UC Santa Barbara), I examine trends in West African rainfall variability. My analysis will focus on seasonal rainfall totals, the structure of the rainy season, and the distribution of rainfall. I then use farmer-identified drought years to take an in-depth analysis of intra-seasonal rainfall irregularities. I will also examine other datasets such as potential evapotranspiration (PET) data, other remotely sensed rainfall data, rain gauge data in specific locations, and remotely sensed vegetation data. Farmer bad year data will also be used to isolate "bad" year markers in these additional datasets to provide benchmarks for identification in the future of problematic rainy seasons.

Bivariate frequency analysis of rainfall intensity and duration for urban stormwater infrastructure design

NASA Astrophysics Data System (ADS)

Jun, Changhyun; Qin, Xiaosheng; Gan, Thian Yew; Tung, Yeou-Koung; De Michele, Carlo

2017-10-01

This study presents a storm-event based bivariate frequency analysis approach to determine design rainfalls in which, the number, intensity and duration of actual rainstorm events were considered. To derive more realistic design storms, the occurrence probability of an individual rainstorm event was determined from the joint distribution of storm intensity and duration through a copula model. Hourly rainfall data were used at three climate stations respectively located in Singapore, South Korea and Canada. It was found that the proposed approach could give a more realistic description of rainfall characteristics of rainstorm events and design rainfalls. As results, the design rainfall quantities from actual rainstorm events at the three studied sites are consistently lower than those obtained from the conventional rainfall depth-duration-frequency (DDF) method, especially for short-duration storms (such as 1-h). It results from occurrence probabilities of each rainstorm event and a different angle for rainfall frequency analysis, and could offer an alternative way of describing extreme rainfall properties and potentially help improve the hydrologic design of stormwater management facilities in urban areas.

Simulation of extreme rainfall event of November 2009 over Jeddah, Saudi Arabia: the explicit role of topography and surface heating

NASA Astrophysics Data System (ADS)

Almazroui, Mansour; Raju, P. V. S.; Yusef, A.; Hussein, M. A. A.; Omar, M.

2018-04-01

In this paper, a nonhydrostatic Weather Research and Forecasting (WRF) model has been used to simulate the extreme precipitation event of 25 November 2009, over Jeddah, Saudi Arabia. The model is integrated in three nested (27, 9, and 3 km) domains with the initial and boundary forcing derived from the NCEP reanalysis datasets. As a control experiment, the model integrated for 48 h initiated at 0000 UTC on 24 November 2009. The simulated rainfall in the control experiment depicts in well agreement with Tropical Rainfall Measurement Mission rainfall estimates in terms of intensity as well as spatio-temporal distribution. Results indicate that a strong low-level (850 hPa) wind over Jeddah and surrounding regions enhanced the moisture and temperature gradient and created a conditionally unstable atmosphere that favored the development of the mesoscale system. The influences of topography and heat exchange process in the atmosphere were investigated on the development of extreme precipitation event; two sensitivity experiments are carried out: one without topography and another without exchange of surface heating to the atmosphere. The results depict that both surface heating and topography played crucial role in determining the spatial distribution and intensity of the extreme rainfall over Jeddah. The topography favored enhanced uplift motion that further strengthened the low-level jet and hence the rainfall over Jeddah and adjacent areas. On the other hand, the absence of surface heating considerably reduced the simulated rainfall by 30% as compared to the observations.

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

Climate changes effects on vegetation in Mediterranean areas

NASA Astrophysics Data System (ADS)

Viola, F.; Pumo, D.; Noto, L. V.

2009-04-01

The Mediterranean ecosystems evolved under climatic conditions characterized by precipitations markedly out of phase with the growing period for the vegetation there established. In such environments, deep and shallow rooted species cohabit and compete each other. The formers, being characterized by deeper root, are able to utilize the water stored during the dormant season, while the conditions of shallow rooted plant are closely related to the intermittence of the precipitations. A numerical model has been here used in order to carry out an analysis of the potential climate changes influence on the vegetation state in a typical Mediterranean environment, such as Sicilian one. The most important consequences arising from climate changes in the Mediterranean area, due to the CO2 increase, are the temperatures raise and the contemporaneous rainfall reduction. Probably, this reduction could be accompanied by an increase in events intensity and, at the same time, by a decrease in the number of annual events. There are very few information about possible changes in the distribution of the rainfall events over the year. However, according to the analysis of the recorded trend, it is possible to predict that the rainfall reduction will be mainly concentrated during the autumnal and wintry months. The goal of this work is a quantitative evaluation of the effects due to the climatic forcing changes, on vegetation water stress. In particular, great attention is paid to the effects that rainfall decrease may have on vegetation, by itself or coupled with the temperature increase. A detailed investigation on the influence of the variations in rainfall seasonality, frequency and intensity is carried out. In this work two vegetation covers, with shallow and deep rooting depth (grass and tree) laying on three different soil types (loamy sand, sandy loam and clay) are considered. Simulations on Mediterranean ecosystems have lead to recognize the role of the rainfall amount, frequency and temporal distribution. Rainfall decrease increases the vegetation water stress much more than temperature increase do. Intense and rare rainfall events, as they are expected to be, could attenuate the effects of rainfall reduction because of the less interception correlated to them. The future rainfall distribution over the year is also crucial for vegetation water stress. If the current ratio between the growing season and the dormant season rainfall will be kept, trees and grasses will suffer a common increase of water stress, which seems more severe for trees than for grasses. Otherwise, if the rainfall reduction will be concentrated during the wintry periods, as emerges from literature, grasses will have some advantages over the trees species. In this conditions grasses will keep the water stress similar to the nowadays value, while trees will suffer for the lack of the winter recharge increasing their water stress.

Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

NASA Astrophysics Data System (ADS)

Noh, Hui-seong; Shin, Hyun-seok; Kang, Na-rae; Lee, Choong-Ke; Kim, Hung-soo

2013-04-01

Recently, the necessity for rainfall estimation and forecasting using the radar is being highlighted, due to the frequent occurrence of torrential rainfall resulting from abnormal changes of weather. Radar rainfall data represents temporal and spatial distributions properly and replace the existing rain gauge networks. It is also frequently applied in many hydrologic field researches. However, the radar rainfall data has an accuracy limitation since it estimates rainfall, by monitoring clouds and precipitation particles formed around the surface of the earth(1.5-3km above the surface) or the atmosphere. In a condition like Korea where nearly 70% of the land is covered by mountainous areas, there are lots of restrictions to use rainfall radar, because of the occurrence of beam blocking areas by topography. This study is aiming at analyzing runoff and examining the applicability of (R(Z), R(ZDR) and R(KDP)) provided by the Han River Flood Control Office(HRFCO) based on the basin elevation of Nakdong river watershed. For this purpose, the amount of radar rainfall of each rainfall event was estimated according to three sub-basins of Nakdong river watershed with the average basin elevation above 400m which are Namgang dam, Andong dam and Hapcheon dam and also another three sub-basins with the average basin elevation below 150m which are Waegwan, Changryeong and Goryeong. After runoff analysis using a distribution model, Vflo model, the results were reviewed and compared with the observed runoff. This study estimated the rainfall by using the radar-rainfall transform formulas, (R(Z), R(Z,ZDR) and R(Z,ZDR,KDP) for four stormwater events and compared the results with the point rainfall of the rain gauge. As the result, it was overestimated or underestimated, depending on rainfall events. Also, calculation indicates that the values from R(Z,ZDR) and R(Z,ZDR,KDP) relatively showed the most similar results. Moreover the runoff analysis using the estimated radar rainfall is performed. Then hydrologic component of the runoff hydrographs, peak flows and total runoffs from the estimated rainfall and the observed rainfall are compared. The results show that hydrologic components have high fluctuations depending on storm rainfall event. Thus, it is necessary to choose appropriate radar rainfall data derived from the above radar rainfall transform formulas to analyze the runoff of radar rainfall. The simulated hydrograph by radar in the three basins of agricultural areas is more similar to the observed hydrograph than the other three basins of mountainous areas. Especially the peak flow and shape of hydrograph of the agricultural areas is much closer to the observed ones than that of mountainous areas. This result comes from the difference of radar rainfall depending on the basin elevation. Therefore we need the examination of radar rainfall transform formulas following rainfall event and runoff analysis based on basin elevation for the improvement of radar rainfall application. Acknowledgment This study was financially supported by the Construction Technology Innovation Program(08-Tech-Inovation-F01) through the Research Center of Flood Defence Technology for Next Generation in Korea Institute of Construction & Transportation Technology Evaluation and Planning(KICTEP) of Ministry of Land, Transport and Maritime Affairs(MLTM)

Modelling of extreme rainfall events in Peninsular Malaysia based on annual maximum and partial duration series

NASA Astrophysics Data System (ADS)

Zin, Wan Zawiah Wan; Shinyie, Wendy Ling; Jemain, Abdul Aziz

2015-02-01

In this study, two series of data for extreme rainfall events are generated based on Annual Maximum and Partial Duration Methods, derived from 102 rain-gauge stations in Peninsular from 1982-2012. To determine the optimal threshold for each station, several requirements must be satisfied and Adapted Hill estimator is employed for this purpose. A semi-parametric bootstrap is then used to estimate the mean square error (MSE) of the estimator at each threshold and the optimal threshold is selected based on the smallest MSE. The mean annual frequency is also checked to ensure that it lies in the range of one to five and the resulting data is also de-clustered to ensure independence. The two data series are then fitted to Generalized Extreme Value and Generalized Pareto distributions for annual maximum and partial duration series, respectively. The parameter estimation methods used are the Maximum Likelihood and the L-moment methods. Two goodness of fit tests are then used to evaluate the best-fitted distribution. The results showed that the Partial Duration series with Generalized Pareto distribution and Maximum Likelihood parameter estimation provides the best representation for extreme rainfall events in Peninsular Malaysia for majority of the stations studied. Based on these findings, several return values are also derived and spatial mapping are constructed to identify the distribution characteristic of extreme rainfall in Peninsular Malaysia.

Temporal sequencing of throughfall drop generation as revealed by use of a large-scale rainfall simulator

NASA Astrophysics Data System (ADS)

Nanko, K.; Levia, D. F., Jr.; Iida, S.; SUN, X.; Shinohara, Y.; Sakai, N.

2017-12-01

Scientists have been interested in throughfall drop size and its distribution because of its importance to soil erosion and the forest water balance. An indoor experiment was employed to deepen our understanding of throughfall drop generation processes to promote better management of forested ecosystems. The indoor experiment provides a unique opportunity to examine an array of constant rainfall intensities that are ideal conditions to pick up the effect of changing intensities and not found in the fields. Throughfall drop generation was examined for three species- Cryptomeria japonica D. Don (Japanese cedar), Chamaecyparis obtusa (Siebold & Zucc.) Endl. (Japanese cypress), and Zelkova serrata Thunb. (Japanese zelkova)- under both leafed and leafless conditions in the large-scale rainfall simulator in the National Research Institute for Earth Science and Disaster Resilience (Tsukuba, Japan) at varying rainfall intensities ranging from15 to 100 mm h-1. Drop size distributions of the applied rainfall and throughfall were measured simultaneously by 20 laser disdrometers. Utilizing the drop size dataset, throughfall was separated into three components: free throughfall, canopy drip, and splash throughfall. The temporal sequencing of the throughfall components were analyzed on a 1-min interval during each experimental run. The throughfall component percentage and drop size of canopy drip differed among tree species and rainfall intensities and by elapsed time from the beginning of the rainfall event. Preliminary analysis revealed that the time differences to produce branch drip as compared to leaf (or needle) drip was partly due to differential canopy wet-up processes and the disappearance of branch drips due to canopy saturation, leading to dissimilar throughfall drop size distributions beneath the various tree species examined. This research was supported by JSPS Invitation Fellowship for Research in Japan (Grant No.: S16088) and JSPS KAKENHI (Grant No.: JP15H05626).

Use of microwave satellite data to study variations in rainfall over the Indian Ocean

NASA Technical Reports Server (NTRS)

Hinton, Barry B.; Martin, David W.; Auvine, Brian; Olson, William S.

1990-01-01

The University of Wisconsin Space Science and Engineering Center mapped rainfall over the Indian Ocean using a newly developed Scanning Multichannel Microwave Radiometer (SMMR) rain-retrieval algorithm. The short-range objective was to characterize the distribution and variability of Indian Ocean rainfall on seasonal and annual scales. In the long-range, the objective is to clarify differences between land and marine regimes of monsoon rain. Researchers developed a semi-empirical algorithm for retrieving Indian Ocean rainfall. Tools for this development have come from radiative transfer and cloud liquid water models. Where possible, ground truth information from available radars was used in development and testing. SMMR rainfalls were also compared with Indian Ocean gauge rainfalls. Final Indian Ocean maps were produced for months, seasons, and years and interpreted in terms of historical analysis over the sub-continent.

Incident rainfall in Rome and its relation to biodeterioration of buildings

NASA Astrophysics Data System (ADS)

Caneva, G.; Gori, E.; Danin, A.

Intensity and distribution of incident rainfall in Rome, and degree of lithobiont cover of building walls, were estimated, and their correlation was discussed. Rainfall and wind data over 10 years for the Rome Meteorological Observatory of Torre Calandrelli (UCEA) were used to calculate the actual hydrocontribution received over walls at various exposures. The biological colonization by lithobionts was evaluated on a sample of 14 buildings in various places of the city, using a phytosociological scale for quantifying their total cover. During all seasons the rainfall shows a significant peak in the south and the southeast exposures, where the highest cover of lithobionts is found. These results show the role of incident rainfall in the climatic conditions of Rome as the main driving factor for the growth of lithobionts on walls where rainfall is their principal source of water.

Characterizing multiscale variability of zero intermittency in spatial rainfall

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1994-01-01

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

Variability in the microcanonical cascades parameters among gauges of urban precipitation monitoring network

NASA Astrophysics Data System (ADS)

Licznar, Paweł; Rupp, David; Adamowski, Witold

2013-04-01

In the fall of 2008, Municipal Water Supply and Sewerage Company (MWSSC) in Warsaw began operating the first large precipitation monitoring network dedicated to urban hydrology in Poland. The process of establishing the network as well as the preliminary phase of its operation, raised a number of questions concerning optimal gauge location and density and revealed the urgent need for new data processing techniques. When considering the full-field precipitation as input to hydrodynamic models of stormwater and combined sewage systems, standard processing techniques developed previously for single gauges and concentrating mainly on the analysis of maximum rainfall rates and intensity-duration-frequency (IDF) curves development were found inadequate. We used a multifractal rainfall modeling framework based on microcanonical multiplicative random cascades to analyze properties of Warsaw precipitation. We calculated breakdown coefficients (BDC) for the hierarchy of timescales from λ=1 (5-min) up to λ=128 (1280-min) for all 25 gauges in the network. At small timescales histograms of BDCs were strongly deformed due to the recording precision of rainfall amounts. A randomization procedure statistically removed the artifacts due to precision errors in the original series. At large timescales BDC values were sparse due to relatively short period of observations (2008-2011). An algorithm with a moving window was proposed to increase the number of BDC values at large timescales and to smooth their histograms. The resulting empirical BDC histograms were modeled by a theoretical "2N-B" distribution, which combined 2 separate normal (N) distributions and one beta (B) distribution. A clear evolution of BDC histograms from a 2N-B distribution for small timescales to a N-B distributions for intermediate timescales and finally to a single beta distributions for large timescales was observed for all gauges. Cluster analysis revealed close patterns of BDC distributions among almost all gauges and timescales with exception of two gauges located at the city limits (one gauge was located on the Okęcie airport). We evaluated the performance of the microcanonical cascades at disaggregating 1280-min (quasi daily precipitation totals) into 5-min rainfall data for selected gauges. Synthetic time series were analyzed with respect to their intermittency and variability of rainfall intensities and compared to observational series. We showed that microcanonical cascades models could be used in practice for generating synthetic rainfall time series suitable as input to urban hydrology models in Warsaw.

The Forecast Interpretation Tool—a Monte Carlo technique for blending climatic distributions with probabilistic forecasts

USGS Publications Warehouse

Husak, Gregory J.; Michaelsen, Joel; Kyriakidis, P.; Verdin, James P.; Funk, Chris; Galu, Gideon

2011-01-01

Probabilistic forecasts are produced from a variety of outlets to help predict rainfall, and other meteorological events, for periods of 1 month or more. Such forecasts are expressed as probabilities of a rainfall event, e.g. being in the upper, middle, or lower third of the relevant distribution of rainfall in the region. The impact of these forecasts on the expectation for the event is not always clear or easily conveyed. This article proposes a technique based on Monte Carlo simulation for adjusting existing climatologic statistical parameters to match forecast information, resulting in new parameters defining the probability of events for the forecast interval. The resulting parameters are shown to approximate the forecasts with reasonable accuracy. To show the value of the technique as an application for seasonal rainfall, it is used with consensus forecast developed for the Greater Horn of Africa for the 2009 March-April-May season. An alternative, analytical approach is also proposed, and discussed in comparison to the first simulation-based technique.

The temporal variability of a rainfall synthetic hyetograph for the dimensioning of stormwater retention tanks in small urban catchments

NASA Astrophysics Data System (ADS)

Pochwat, Kamil; Słyś, Daniel; Kordana, Sabina

2017-06-01

The paper presents issues relating to the influence of time distribution of rainfall on the required storage capacity of stormwater reservoirs. The research was based on data derived from simulations of existing drainage systems. The necessary models of catchments and the drainage system were prepared using the hydrodynamic modelling software SWMM 5.0 (Storm Water Management Model). The research results obtained were used to determine the critical rainfall distribution in time which required reserving the highest capacity of stormwater reservoir. In addition, it can be confirmed based on the research that dimensioning of enclosed structures should rely on using the critical precipitation generated as the characteristics of a synthetically developed rainfall vary dynamically in time. In the final part of the paper, the results of the analyses are compared and followed with the ensuing conclusions. The results of the research will have impact on the development of methodologies for dimensioning retention facilities in drainage systems.

Statistical bias correction modelling for seasonal rainfall forecast for the case of Bali island

NASA Astrophysics Data System (ADS)

Lealdi, D.; Nurdiati, S.; Sopaheluwakan, A.

2018-04-01

Rainfall is an element of climate which is highly influential to the agricultural sector. Rain pattern and distribution highly determines the sustainability of agricultural activities. Therefore, information on rainfall is very useful for agriculture sector and farmers in anticipating the possibility of extreme events which often cause failures of agricultural production. This research aims to identify the biases from seasonal forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) rainfall forecast and to build a transfer function in order to correct the distribution biases as a new prediction model using quantile mapping approach. We apply this approach to the case of Bali Island, and as a result, the use of bias correction methods in correcting systematic biases from the model gives better results. The new prediction model obtained with this approach is better than ever. We found generally that during rainy season, the bias correction approach performs better than in dry season.

Derivation of debris flow critical rainfall thresholds from land stability modeling

NASA Astrophysics Data System (ADS)

Papa, M. N.; Medina, V.; Bateman, A.; Ciervo, F.

2012-04-01

The aim of the work is to develop a system capable of providing debris flow warnings in areas where historical events data are not available as well as in the case of changing environments and climate. For these reasons, critical rainfall threshold curves are derived from mathematical and numerical simulations rather than the classical derivation from empirical rainfall data. The operational use of distributed model, based on the stability analysis for each grid cell of the basin, is not feasible in the case of warnings due to the long running time required for this kind of model as well as the lack of detailed information on the spatial distribution of the properties of the material in many practical cases. Moreover, with the aim of giving debris flow warnings, it is not necessary to know the distribution of instable elements along the basin but only if a debris flow may affect the vulnerable areas in the valley. The capability of a debris flow of reaching the downstream areas depends on many factors linked with the topography, the solid concentration, the rheological properties of the debris mixture and the flow discharge as well as the occurrence of liquefaction of the sliding mass. In relation to a specific basin, many of these factors may be considered as not time dependent. The most rainfall dependent factors are flow discharge and correlated total debris volume. In the present study, the total volume that is instable, and therefore available for the flow, is considered as the governing factor from which it is possible to assess whether a debris flow will affect the downstream areas or not. The possible triggering debris flow is simulated, in a generic element of the basin, by an infinite slope stability analysis. The groundwater pressure is calculated by the superposition of the effect of an "antecedent" rainfall and an "event" rainfall. The groundwater pressure response to antecedent rainfall is used as the initial condition for the time-dependent computation of the groundwater pressure response to the event rainfall. Antecedent rainfall response is estimated in the hypotheses of low intensity and long duration, thus assuming steady state conditions and slope parallel groundwater flux. The short term response to rainfall is assessed in the hypothesis of vertical infiltration. The simulations are performed in a virtual basin, representative of the one studied, taking into account the uncertainties linked with the definition of the characteristics of the soil. The approach presented is based on the simulation of a large number of cases covering the entire range of the governing input dynamic variables. For any possible combination of rainfall intensity, duration and antecedent rain, the total debris volume, available for the flow, is estimated. The resulting database is elaborated in order to obtain rainfall threshold curves. When operating in real time, if the observed and forecasted rainfall exceeds a given threshold, the corresponding probability of debris flow occurrence may be estimated.

Statistical Analysis of 30 Years Rainfall Data: A Case Study

NASA Astrophysics Data System (ADS)

Arvind, G.; Ashok Kumar, P.; Girish Karthi, S.; Suribabu, C. R.

2017-07-01

Rainfall is a prime input for various engineering design such as hydraulic structures, bridges and culverts, canals, storm water sewer and road drainage system. The detailed statistical analysis of each region is essential to estimate the relevant input value for design and analysis of engineering structures and also for crop planning. A rain gauge station located closely in Trichy district is selected for statistical analysis where agriculture is the prime occupation. The daily rainfall data for a period of 30 years is used to understand normal rainfall, deficit rainfall, Excess rainfall and Seasonal rainfall of the selected circle headquarters. Further various plotting position formulae available is used to evaluate return period of monthly, seasonally and annual rainfall. This analysis will provide useful information for water resources planner, farmers and urban engineers to assess the availability of water and create the storage accordingly. The mean, standard deviation and coefficient of variation of monthly and annual rainfall was calculated to check the rainfall variability. From the calculated results, the rainfall pattern is found to be erratic. The best fit probability distribution was identified based on the minimum deviation between actual and estimated values. The scientific results and the analysis paved the way to determine the proper onset and withdrawal of monsoon results which were used for land preparation and sowing.

Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

NASA Astrophysics Data System (ADS)

Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

2017-12-01

This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

Regional intensity-duration-frequency analysis in the Eastern Black Sea Basin, Turkey, by using L-moments and regression analysis

NASA Astrophysics Data System (ADS)

Ghiaei, Farhad; Kankal, Murat; Anilan, Tugce; Yuksek, Omer

2018-01-01

The analysis of rainfall frequency is an important step in hydrology and water resources engineering. However, a lack of measuring stations, short duration of statistical periods, and unreliable outliers are among the most important problems when designing hydrology projects. In this study, regional rainfall analysis based on L-moments was used to overcome these problems in the Eastern Black Sea Basin (EBSB) of Turkey. The L-moments technique was applied at all stages of the regional analysis, including determining homogeneous regions, in addition to fitting and estimating parameters from appropriate distribution functions in each homogeneous region. We studied annual maximum rainfall height values of various durations (5 min to 24 h) from seven rain gauge stations located in the EBSB in Turkey, which have gauging periods of 39 to 70 years. Homogeneity of the region was evaluated by using L-moments. The goodness-of-fit criterion for each distribution was defined as the ZDIST statistics, depending on various distributions, including generalized logistic (GLO), generalized extreme value (GEV), generalized normal (GNO), Pearson type 3 (PE3), and generalized Pareto (GPA). GLO and GEV determined the best distributions for short (5 to 30 min) and long (1 to 24 h) period data, respectively. Based on the distribution functions, the governing equations were extracted for calculation of intensities of 2, 5, 25, 50, 100, 250, and 500 years return periods (T). Subsequently, the T values for different rainfall intensities were estimated using data quantifying maximum amount of rainfall at different times. Using these T values, duration, altitude, latitude, and longitude values were used as independent variables in a regression model of the data. The determination coefficient ( R 2) value indicated that the model yields suitable results for the regional relationship of intensity-duration-frequency (IDF), which is necessary for the design of hydraulic structures in small and medium sized catchments.

Developing Methods For Linking Surficial Aquifers With Localized Rainfall Data

NASA Astrophysics Data System (ADS)

Lafrenz, W. B.; van Gaalen, J. F.

2008-12-01

Water level hydrographs of the surficial aquifer can be evaluated to identify both the cause and consequence of water supply development. Rainfall, as a source of direct recharge and as a source of delayed or compounded recharge, is often the largest influence on surficial aquifer water level responses. It is clear that proximity of the rain gauge to the observation well is a factor in the degree of correlation, but in central Florida, USA, rainfall patterns change seasonally, with latitude, and with distance from the coast . Thus, for a location in central Florida, correlation of rain events with observed hydrograph responses depends on both distance and direction from an observation well to a rain gauge. In this study, we examine the use of extreme value analysis as a method of selecting the best rainfall data set for describing a given surficial aquifer monitor well. A surficial aquifer monitor well with a substantial suite of data is compared to a series of rainfall data sets from gauges ranging from meters to tens of kilometers in distance from the monitor well. The gauges vary in a wide range of directions from the monitor well in an attempt to identify both a method for rainfall gauge selection to be associated with the monitor well. Each rainfall gauge is described by a correlation coefficient with respect to the surficial aquifer water level data.

Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains.

PubMed

Nolan, Bernard T; Dubus, Igor G; Surdyk, Nicolas; Fowler, Hayley J; Burton, Aidan; Hollis, John M; Reichenberger, Stefan; Jarvis, Nicholas J

2008-09-01

Key climatic factors influencing the transport of pesticides to drains and to depth were identified. Climatic characteristics such as the timing of rainfall in relation to pesticide application may be more critical than average annual temperature and rainfall. The fate of three pesticides was simulated in nine contrasting soil types for two seasons, five application dates and six synthetic weather data series using the MACRO model, and predicted cumulative pesticide loads were analysed using statistical methods. Classification trees and Pearson correlations indicated that simulated losses in excess of 75th percentile values (0.046 mg m(-2) for leaching, 0.042 mg m(-2) for drainage) generally occurred with large rainfall events following autumn application on clay soils, for both leaching and drainage scenarios. The amount and timing of winter rainfall were important factors, whatever the application period, and these interacted strongly with soil texture and pesticide mobility and persistence. Winter rainfall primarily influenced losses of less mobile and more persistent compounds, while short-term rainfall and temperature controlled leaching of the more mobile pesticides. Numerous climatic characteristics influenced pesticide loss, including the amount of precipitation as well as the timing of rainfall and extreme events in relation to application date. Information regarding the relative influence of the climatic characteristics evaluated here can support the development of a climatic zonation for European-scale risk assessment for pesticide fate.

Monsoon variability, crop water requirement, and crop planning for kharif rice in Sagar Island, India.

PubMed

Mandal, S; Choudhury, B U; Satpati, L N

2015-12-01

In the Sagar Island of Bay of Bengal, rainfed lowland rice is the major crop, grown solely depending on erratic distribution of southwest monsoon (SM) rainfall. Lack of information on SM rainfall variability and absence of crop scheduling accordingly results in frequent occurrence of intermittent water stress and occasional crop failure. In the present study, we analyzed long period (1982-2010) SM rainfall behavior (onset, withdrawal, rainfall and wetness indices, dry and wet spells), crop water requirement (CWR, by Food and Agriculture Organization (FAO) 56), and probability of weekly rainfall occurrence (by two-parameter gamma distribution) to assess the variability and impact on water availability, CWR, and rice productivity. Finally, crop planning was suggested to overcome monsoon uncertainties on water availability and rice productivity. Study revealed that the normal onset and withdrawal weeks for SM rainfall were 22nd ± 1 and 43rd ± 2 meteorological weeks (MW), respectively. However, effective monsoon rainfall started at 24th MW (rainfall 92.7 mm, p > 56.7 % for 50 mm rainfall) and was terminated by the end of 40th MW (rainfall 90.7 mm, p < 59.6 % for 50 mm rainfall). During crop growth periods (seed to seed, 21st to 45th MW), the island received an average weekly rainfall of 65.1 ± 25.9 mm, while the corresponding weekly CWR was 47.8 ± 5.4 mm. Despite net water surplus of 353.9 mm during crop growth periods, there was a deficit of 159.5 mm water during MW of 18-23 (seedling raising) and MW of 41-45 (flowering to maturity stages). Water stress was observed in early lag vegetative stage of crop growth (32nd MW). The total dry spell frequency during panicle initiation and heading stage was computed as 40 of which 6 dry spells were >7 days in duration and reflected a significant (p < 0.05) increasing trend (at 0.22 days year(-1)) over the years (1982-2010). The present study highlights the adaptive capacity of crop planning including abiotic stress-tolerant cultivars to monsoon rainfall variability for sustaining rainfed rice production vis-à-vis food and livelihood security in vulnerable islands of coastal ecosystem.

Regional frequency analysis of observed sub-daily rainfall maxima over eastern China

NASA Astrophysics Data System (ADS)

Sun, Hemin; Wang, Guojie; Li, Xiucang; Chen, Jing; Su, Buda; Jiang, Tong

2017-02-01

Based on hourly rainfall observational data from 442 stations during 1960-2014, a regional frequency analysis of the annual maxima (AM) sub-daily rainfall series (1-, 2-, 3-, 6-, 12-, and 24-h rainfall, using a moving window approach) for eastern China was conducted. Eastern China was divided into 13 homogeneous regions: Northeast (NE1, NE2), Central (C), Central North (CN1, CN2), Central East (CE1, CE2, CE3), Southeast (SE1, SE2, SE3, SE4), and Southwest (SW). The generalized extreme value performed best for the AM series in regions NE, C, CN2, CE1, CE2, SE2, and SW, and the generalized logistic distribution was appropriate in the other regions. Maximum return levels were in the SE4 region, with value ranges of 80-270 mm (1-h to 24-h rainfall) and 108-390 mm (1-h to 24-h rainfall) for 20- and 100 yr, respectively. Minimum return levels were in the CN1 and NE1 regions, with values of 37-104 mm and 53-140 mm for 20 and 100 yr, respectively. Comparing return levels using the optimal and commonly used Pearson-III distribution, the mean return-level differences in eastern China for 1-24-h rainfall varied from -3-4 mm to -23-11 mm (-10%-10%) for 20-yr events, reaching -6-26 mm (-10%-30%) and -10-133 mm (-10%-90%) for 100-yr events. In view of the large differences in estimated return levels, more attention should be given to frequency analysis of sub-daily rainfall over China, for improved water management and disaster reduction.

Rainfall-triggered shallow landslides at catchment scale: Threshold mechanics-based modeling for abruptness and localization

NASA Astrophysics Data System (ADS)

von Ruette, J.; Lehmann, P.; Or, D.

2013-10-01

Rainfall-induced shallow landslides may occur abruptly without distinct precursors and could span a wide range of soil mass released during a triggering event. We present a rainfall-induced landslide-triggering model for steep catchments with surfaces represented as an assembly of hydrologically and mechanically interconnected soil columns. The abruptness of failure was captured by defining local strength thresholds for mechanical bonds linking soil and bedrock and adjacent columns, whereby a failure of a single bond may initiate a chain reaction of subsequent failures, culminating in local mass release (a landslide). The catchment-scale hydromechanical landslide-triggering model (CHLT) was applied to results from two event-based landslide inventories triggered by two rainfall events in 2002 and 2005 in two nearby catchments located in the Prealps in Switzerland. Rainfall radar data, surface elevation and vegetation maps, and a soil production model for soil depth distribution were used for hydromechanical modeling of failure patterns for the two rainfall events at spatial and temporal resolutions of 2.5 m and 0.02 h, respectively. The CHLT model enabled systematic evaluation of the effects of soil type, mechanical reinforcement (soil cohesion and lateral root strength), and initial soil water content on landslide characteristics. We compared various landslide metrics and spatial distribution of simulated landslides in subcatchments with observed inventory data. Model parameters were optimized for the short but intense rainfall event in 2002, and the calibrated model was then applied for the 2005 rainfall, yielding reasonable predictions of landslide events and volumes and statistically reproducing localized landslide patterns similar to inventory data. The model provides a means for identifying local hot spots and offers insights into the dynamics of locally resolved landslide hazards in mountainous regions.

Exploring the Variability of Short-term Precipitation and Hydrological Response of Small Czech Watersheds

NASA Astrophysics Data System (ADS)

Kavka, Petr; Strouhal, Ludek; Weyskrabova, Lenka; Müller, Miloslav; Kozant, Petr

2017-04-01

The short-term rainfall temporal distribution is known to have a significant effect on the small watersheds' hydrological response. In Czech Republic there are limited publicly available data on rainfall patterns of short-term precipitation. On one side there are catalogues of very short-term synthetic rainfalls used in urban drainage planning and on the other side hourly distribution of daily totals of rainfalls with long return period for larger catchments analyses. This contribution introduces the preliminary outcomes of a running three years' project, which should bridge this gap and provide such data and methodology to the community of scientists, state administration as well as design planners. Six generalized 6-hours hyetographs with 1 minute resolution were derived from 10 years of radar and gauging stations data. These hyetographs are accompanied with information concerning the region of occurrence as well as their frequency related to the rainfall amount. In the next step these hyetographs are used in a complex sensitivity analysis focused on a rainfall-runoff response of small watersheds. This analysis takes into account the uncertainty related to type of the hydrological model, watershed characteristics and main model routines parameterization. Five models with different methods and structure are considered and each model is applied on 5 characteristic watersheds selected from a classification of 7700 small Czech watersheds. For each combination of model and watershed 30, rainfall scenarios were simulated and other scenarios will be used to address the parameters uncertainty. In the last step the variability of outputs will be assessed in the context of economic impacts on design of landscape water structures or mitigation measures. The research is supported by the grant QJ1520265 of the Czech Ministry of Agriculture, rainfall data were provided by the Czech Hydrometeorological Institute.

The Effects of Rainfall Inhomogeneity on Climate Variability of Rainfall Estimated from Passive Microwave Sensors

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Poyner, Philip; Berg, Wesley; Thomas-Stahle, Jody

2007-01-01

Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (T(sub b)) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km X 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global mean monthly errors introduced by not explicitly accounting for rainfall inhomogeneity do not exceed 0.5% if the beam-filling error is allowed to be a function of rainfall rate and freezing level and does not exceed 2% if a universal beam-filling correction is applied that depends only upon the freezing level. Monthly regional errors can be significantly larger. Over the Indian Ocean, errors as large as 8% were found if the beam-filling correction is allowed to vary with rainfall rate and freezing level while errors of 15% were found if a universal correction is used.

Distribution of polycyclic aromatic hydrocarbons in urban stormwater in Queensland, Australia.

PubMed

Herngren, Lars; Goonetilleke, Ashantha; Ayoko, Godwin A; Mostert, Maria M M

2010-09-01

This paper reports the distribution of Polycyclic Aromatic Hydrocarbons (PAHs) in wash-off in urban stormwater in Gold Coast, Australia. Runoff samples collected from residential, industrial and commercial sites were separated into a dissolved fraction (<0.45 microm), and three particulate fractions (0.45-75 microm, 75-150 microm and >150 microm). Patterns in the distribution of PAHs in the fractions were investigated using Principal Component Analysis. Regardless of the land use and particle size fraction characteristics, the presence of organic carbon plays a dominant role in the distribution of PAHs. The PAHs concentrations were also found to decrease with rainfall duration. Generally, the 1- and 2-year average recurrence interval rainfall events were associated with the majority of the PAHs and the wash-off was a source limiting process. In the context of stormwater quality mitigation, targeting the initial part of the rainfall event is the most effective treatment strategy. The implications of the study results for urban stormwater quality management are also discussed. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Atmospheric water distribution in a midlatitude cyclone observed by the Seasat Scanning Multichannel Microwave Radiometer

NASA Technical Reports Server (NTRS)

Mcmurdie, L. A.; Katsaros, K. B.

1985-01-01

Patterns in the horizontal distribution of integrated water vapor, integrated liquid water and rainfall rate derived from the Seasat Scanning Multichannel Microwave Radiometer (SMMR) during a September 10-12, 1978 North Pacific cyclone are studied. These patterns are compared with surface analyses, ship reports, radiosonde data, and GOES-West infrared satellite imagery. The SMMR data give a unique view of the large mesoscale structure of a midlatitude cyclone. The water vapor distribution is found to have characteristic patterns related to the location of the surface fronts throughout the development of the cyclone. An example is given to illustrate that SMMR data could significantly improve frontal analysis over data-sparse oceanic regions. The distribution of integrated liquid water agrees qualitatively well with corresponding cloud patterns in satellite imagery and appears to provide a means to distinguish where liquid water clouds exist under a cirrus shield. Ship reports of rainfall intensity agree qualitatively very well with SMMR-derived rainrates. Areas of mesoscale rainfall, on the order of 50 km x 50 km or greater are detected using SMMR derived rainrates.

RAINDROP DISTRIBUTIONS AT MAJURO ATOLL, MARSHALL ISLANDS.

DTIC Science & Technology

RAINDROPS, MARSHALL ISLANDS), (*ATMOSPHERIC PRECIPITATION, TROPICAL REGIONS), PARTICLE SIZE, SAMPLING, TABLES(DATA), WATER , ATTENUATION, DISTRIBUTION, VOLUME, RADAR REFLECTIONS, RAINFALL, PHOTOGRAPHIC ANALYSIS, COMPUTERS

Water Budget for the Island of Kauai, Hawaii

USGS Publications Warehouse

Shade, Patricia J.

1995-01-01

A geographic information system model was created to calculate a monthly water budget for the island of Kauai. Ground-water recharge is the residual component of a monthly water budget calculated using long-term average rainfall, streamflow, and pan-evaporation data, applied irrigation-water estimates, and soil characteristics. The water-budget components are defined seasonally, through the use of the monthly water budget, and spatially by aquifer-system areas, through the use of the geographic information system model. The mean annual islandwide water-budget totals are 2,720 Mgal/d for rainfall plus irrigation; 1,157 Mgal/d for direct runoff; 911 Mgal/d for actual evapotranspiration; and 652 Mgal/d for ground-water recharge. Direct runoff is 43 percent, actual evapotranspiration is 33 percent, and ground-water recharge is 24 percent of rainfall plus irrigation. Ground-water recharge in the natural land-use areas is spatially distributed in a pattern similar to the rainfall distribution. Distinct seasonal variations in the water-budget components are apparent from the monthly water-budget calculations. Rainfall and ground-water recharge peak during the wet winter months with highs in January of 3,698 Mgal/d (million gallons per day) and 981 Mgal/d, respectively; a slight peak in July and August relative to June and September is caused by increased orographic rainfall. Recharge is lowest in June (454 Mgal/d) and November (461 Mgal/d).

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2010-01-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

Intra-storm temporal patterns of rainfall in China using Huff curves

USDA-ARS?s Scientific Manuscript database

The intra-storm temporal distributions of precipitation are important to infiltration, runoff and erosion processes and models. A convenient and established method for characterizing precipitation hyetographs is with the use of Huff curves. In this study, 11,801 erosive rainfall events with one-mi...

Improving predictive power of physically based rainfall-induced shallow landslide models: a probablistic approach

USGS Publications Warehouse

Raia, S.; Alvioli, M.; Rossi, M.; Baum, R.L.; Godt, J.W.; Guzzetti, F.

2013-01-01

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are deterministic. These models extend spatially the static stability models adopted in geotechnical engineering and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the existing models is the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of shallow rainfall-induced landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a stochastic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs of several model runs obtained varying the input parameters are analyzed statistically, and compared to the original (deterministic) model output. The comparison suggests an improvement of the predictive power of the model of about 10% and 16% in two small test areas, i.e. the Frontignano (Italy) and the Mukilteo (USA) areas, respectively. We discuss the computational requirements of TRIGRS-P to determine the potential use of the numerical model to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides in very large areas, extending for several hundreds or thousands of square kilometers. Parallel execution of the code using a simple process distribution and the Message Passing Interface (MPI) on multi-processor machines was successful, opening the possibly of testing the use of TRIGRS-P for the operational forecasting of rainfall-induced shallow landslides over large regions.

Challenges with space-time rainfall in urban hydrology highlighted with a semi-distributed model using C-band and X-band radar data

NASA Astrophysics Data System (ADS)

da Silva Rocha Paz, Igor; Ichiba, Abdellah; Skouri-Plakali, Ilektra; Lee, Jisun; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2017-04-01

Climate change and global warming are expected to make precipitation events more frequent, more severe and more local. This may have serious consequences for human health, the environment, cultural heritage, economic activities, utilities and public service providers. Then precipitation risk and water management is a key challenge for densely populated urban areas. Applications derived from high (time and space) resolution observation of precipitations are to make our cities more weather-ready. Finer resolution data available from X-band dual radar measurements enhance engineering tools as used for urban planning policies as well as protection (mitigation/adaptation) strategies to tackle climate-change related weather events. For decades engineering tools have been developed to work conveniently either with very local rain gauge networks, or with mainly C-band weather radars that have gradually been set up for space-time remote sensing of precipitation. Most of the time, the C-band weather radars continue to be calibrated by the existing rain gauge networks. Inhomogeneous distributions of rain gauging networks lead to only a partial information on the rainfall fields. In fact, the statistics of measured rainfall is strongly biased by the fractality of the measuring networks. This fractality needs to be properly taken in to account to retrieve the original properties of the rainfall fields, in spite of the radar data calibration. In this presentation, with the help of multifractal analysis, we first demonstrate that the semi-distributed hydrological models statistically reduce the rainfall fields into rainfall measured by a much scarcer network of virtual rain gauges. For this purpose, we use C-band and X-band radar data. The first has a resolution of 1 km in space and 5 min in time and is in fact a product provided by RHEA SAS after treating the Météo-France C-band radar data. The latter is measured by the radar operated at Ecole des Ponts and has a resolution of 250 m in space and 3.4 min in time. The obtained results suggest that a proper rainfall data re-normalisation is needed either when comparing gauged rainfall with the radar data, or when quantifying the impacts of space-time variability within hydrological modelling. Then, we used the semi-distributed hydrological model InfoWorks CS operated by Veolia over the Bièvre catchment (Paris region) with the same two types of rainfall data as inputs. We simulated six events and analysed the hydrographs resulted from simulations with both data types to show the impacts of initially different resolutions of rainfall fields over the same catchment, especially in respect to the small-scale variability not measured by the C-band radar data. These results encourage us not only to argue the use of higher resolution rainfall data, compare to that has been so claimed in the literature, but also to emphasise the important role of nonlinear geophysics' methods in taking reliable decisions.

Scale-dependency of effective hydraulic conductivity on fire-affected hillslopes

NASA Astrophysics Data System (ADS)

Langhans, Christoph; Lane, Patrick N. J.; Nyman, Petter; Noske, Philip J.; Cawson, Jane G.; Oono, Akiko; Sheridan, Gary J.

2016-07-01

Effective hydraulic conductivity (Ke) for Hortonian overland flow modeling has been defined as a function of rainfall intensity and runon infiltration assuming a distribution of saturated hydraulic conductivities (Ks). But surface boundary condition during infiltration and its interactions with the distribution of Ks are not well represented in models. As a result, the mean value of the Ks distribution (KS¯), which is the central parameter for Ke, varies between scales. Here we quantify this discrepancy with a large infiltration data set comprising four different methods and scales from fire-affected hillslopes in SE Australia using a relatively simple yet widely used conceptual model of Ke. Ponded disk (0.002 m2) and ring infiltrometers (0.07 m2) were used at the small scales and rainfall simulations (3 m2) and small catchments (ca 3000 m2) at the larger scales. We compared KS¯ between methods measured at the same time and place. Disk and ring infiltrometer measurements had on average 4.8 times higher values of KS¯ than rainfall simulations and catchment-scale estimates. Furthermore, the distribution of Ks was not clearly log-normal and scale-independent, as supposed in the conceptual model. In our interpretation, water repellency and preferential flow paths increase the variance of the measured distribution of Ks and bias ponding toward areas of very low Ks during rainfall simulations and small catchment runoff events while areas with high preferential flow capacity remain water supply-limited more than the conceptual model of Ke predicts. The study highlights problems in the current theory of scaling runoff generation.

Trends and homogeneity of monthly, seasonal, and annual rainfall over arid region of Rajasthan, India

NASA Astrophysics Data System (ADS)

Meena, Hari Mohan; Machiwal, Deepesh; Santra, Priyabrata; Moharana, Pratap Chandra; Singh, D. V.

2018-05-01

Knowledge of rainfall variability is important for regional-scale planning and management of water resources in agriculture. This study explores spatio-temporal variations, trends, and homogeneity in monthly, seasonal, and annual rainfall series of 62 stations located in arid region of Rajasthan, India using 55 year (1957-2011) data. Box-whisker plots indicate presence of outliers and extremes in annual rainfall, which made the distribution of annual rainfall right-skewed. Mean and coefficient of variation (CV) of rainfall reveals a high inter-annual variability (CV > 200%) in the western portion where the mean annual rainfall is very low. A general gradient of the mean monthly, seasonal, and annual rainfall is visible from northwest to southeast direction, which is orthogonal to the gradient of CV. The Sen's innovative trend test is found over-sensitive in evaluating statistical significance of the rainfall trends, while the Mann-Kendall test identifies significantly increasing rainfall trends in June and September. Rainfall in July shows prominently decreasing trends although none of them are found statistically significant. Monsoon and annual rainfall show significantly increasing trends at only four stations. The magnitude of trends indicates that the rainfall is increasing at a mean rate of 1.11, 2.85, and 2.89 mm year-1 in August, monsoon season, and annual series. The rainfall is found homogeneous over most of the area except for few stations situated in the eastern and northwest portions where significantly increasing trends are observed. Findings of this study indicate that there are few increasing trends in rainfall of this Indian arid region.

Warm season heavy rainfall events over the Huaihe River Valley and their linkage with wintertime thermal condition of the tropical oceans

NASA Astrophysics Data System (ADS)

Li, Laifang; Li, Wenhong; Tang, Qiuhong; Zhang, Pengfei; Liu, Yimin

2016-01-01

Warm season heavy rainfall events over the Huaihe River Valley (HRV) of China are amongst the top causes of agriculture and economic loss in this region. Thus, there is a pressing need for accurate seasonal prediction of HRV heavy rainfall events. This study improves the seasonal prediction of HRV heavy rainfall by implementing a novel rainfall framework, which overcomes the limitation of traditional probability models and advances the statistical inference on HRV heavy rainfall events. The framework is built on a three-cluster Normal mixture model, whose distribution parameters are sampled using Bayesian inference and Markov Chain Monte Carlo algorithm. The three rainfall clusters reflect probability behaviors of light, moderate, and heavy rainfall, respectively. Our analysis indicates that heavy rainfall events make the largest contribution to the total amount of seasonal precipitation. Furthermore, the interannual variation of summer precipitation is attributable to the variation of heavy rainfall frequency over the HRV. The heavy rainfall frequency, in turn, is influenced by sea surface temperature anomalies (SSTAs) over the north Indian Ocean, equatorial western Pacific, and the tropical Atlantic. The tropical SSTAs modulate the HRV heavy rainfall events by influencing atmospheric circulation favorable for the onset and maintenance of heavy rainfall events. Occurring 5 months prior to the summer season, these tropical SSTAs provide potential sources of prediction skill for heavy rainfall events over the HRV. Using these preceding SSTA signals, we show that the support vector machine algorithm can predict HRV heavy rainfall satisfactorily. The improved prediction skill has important implication for the nation's disaster early warning system.

Contributions of Tropical Cyclones to the North Atlantic Climatological Rainfall as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The tropical cyclone rainfall climatology study that was performed for the North Pacific was extended to the North Atlantic. Similar to the North Pacific tropical cyclone study, mean monthly rainfall within 444 km of the center of the North Atlantic tropical cyclones (i.e., that reached storm stage and greater) was estimated from passive microwave satellite observations during, an eleven year period. These satellite-observed rainfall estimates were used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Atlantic total rainfall during, June-November when tropical cyclones were most abundant. The main results from this study indicate: 1) that tropical cyclones contribute, respectively, 4%, 3%, and 4% to the western, eastern, and entire North Atlantic; 2) similar to that observed in the North Pacific, the maximum in North Atlantic tropical cyclone rainfall is approximately 5 - 10 deg poleward (depending on longitude) of the maximum non-tropical cyclone rainfall; 3) tropical cyclones contribute regionally a maximum of 30% of the total rainfall 'northeast of Puerto Rico, within a region near 15 deg N 55 deg W, and off the west coast of Africa; 4) there is no lag between the months with maximum tropical cyclone rainfall and non-tropical cyclone rainfall in the western North Atlantic, while in the eastern North Atlantic, maximum tropical cyclone rainfall precedes maximum non-tropical cyclone rainfall; 5) like the North Pacific, North Atlantic tropical cyclones Of hurricane intensity generate the greatest amount of rainfall in the higher latitudes; and 6) warm ENSO events inhibit tropical cyclone rainfall.

Measurements of Water Vapor Profiles with Compact DIAL in the Tokyo Metropolitan Area

NASA Astrophysics Data System (ADS)

Abo, Makoto; Sakai, Tetsu; Le Hoai, Phong Pham; Shibata, Yasukuni; Nagasawa, Chikao

2018-04-01

In recent years, the frequency of occurrence of locally heavy rainfall that can cause extensive damages, has been increasing in Japan. For early prediction of heavy rainfall, it is useful to measure the water vapor vertical distribution upwind cumulus convection beforehand. For that purpose, we have been developing compact water vapor differential absorption lidar (DIAL). We show the results of the measurements with lidar in summer when the local heavy rainfall frequently occurs in Japan. We also show the preliminary result of the assimilation of the lidar data to the numerical model and impact on the heavy rainfall prediction.

Reconstructing missing information on precipitation datasets: impact of tails on adopted statistical distributions.

NASA Astrophysics Data System (ADS)

Pedretti, Daniele; Beckie, Roger Daniel

2014-05-01

Missing data in hydrological time-series databases are ubiquitous in practical applications, yet it is of fundamental importance to make educated decisions in problems involving exhaustive time-series knowledge. This includes precipitation datasets, since recording or human failures can produce gaps in these time series. For some applications, directly involving the ratio between precipitation and some other quantity, lack of complete information can result in poor understanding of basic physical and chemical dynamics involving precipitated water. For instance, the ratio between precipitation (recharge) and outflow rates at a discharge point of an aquifer (e.g. rivers, pumping wells, lysimeters) can be used to obtain aquifer parameters and thus to constrain model-based predictions. We tested a suite of methodologies to reconstruct missing information in rainfall datasets. The goal was to obtain a suitable and versatile method to reduce the errors given by the lack of data in specific time windows. Our analyses included both a classical chronologically-pairing approach between rainfall stations and a probability-based approached, which accounted for the probability of exceedence of rain depths measured at two or multiple stations. Our analyses proved that it is not clear a priori which method delivers the best methodology. Rather, this selection should be based considering the specific statistical properties of the rainfall dataset. In this presentation, our emphasis is to discuss the effects of a few typical parametric distributions used to model the behavior of rainfall. Specifically, we analyzed the role of distributional "tails", which have an important control on the occurrence of extreme rainfall events. The latter strongly affect several hydrological applications, including recharge-discharge relationships. The heavy-tailed distributions we considered were parametric Log-Normal, Generalized Pareto, Generalized Extreme and Gamma distributions. The methods were first tested on synthetic examples, to have a complete control of the impact of several variables such as minimum amount of data required to obtain reliable statistical distributions from the selected parametric functions. Then, we applied the methodology to precipitation datasets collected in the Vancouver area and on a mining site in Peru.

Optimization of rainfall networks using information entropy and temporal variability analysis

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-04-01

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

Goddard Cumulus Ensemble (GCE) Model: Application for Understanding Preciptation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Einaudi, Franco (Technical Monitor)

2000-01-01

The global hydrological cycle is central to climate system interactions and the key to understanding their behavior. Rainfall and its associated precipitation processes are a key link in the hydrologic cycle. Fresh water provided by tropical rainfall and its variability can exert a large impact upon the structure of the upper ocean layer. In addition, approximately two-thirds of the global rain falls in the Tropics, while the associated latent heat release accounts for about three-fourths of the total heat energy for the Earth's atmosphere. Precipitation from convective cloud systems comprises a large portion of tropical heating and rainfall. Furthermore, the vertical distribution of convective latent-heat releases modulates large-scale tropical circulations (e.g., the 30-60-day intraseasonal oscillation), which, in turn, impacts midlatitude weather through teleconnection patterns such as those associated with El Nino. Shifts in these global circulations can result in prolonged periods of droughts and floods, thereby exerting a tremendous impact upon the biosphere and human habitation. And yet, monthly rainfall over the tropical oceans is still not known within a factor of two over large (5 degrees latitude by 5 degrees longitude) areas. Hence, the Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan space project, can provide a more accurate measurement of rainfall as well as estimate the four-dimensional structure of diabatic heating over the global tropics. The distributions of rainfall and inferred heating can be used to advance our understanding of the global energy and water cycle. In addition, this information can be used for global circulation and climate models for testing and improving their parameterizations.

A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall

NASA Astrophysics Data System (ADS)

Lombardo, F.; Volpi, E.; Koutsoyiannis, D.; Serinaldi, F.

2017-06-01

Generating fine-scale time series of intermittent rainfall that are fully consistent with any given coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.

Effect of spatial variability of storm on the optimal placement of best management practices (BMPs).

PubMed

Chang, C L; Chiueh, P T; Lo, S L

2007-12-01

It is significant to design best management practices (BMPs) and determine the proper BMPs placement for the purpose that can not only satisfy the water quantity and water quality standard, but also lower the total cost of BMPs. The spatial rainfall variability can have much effect on its relative runoff and non-point source pollution (NPSP). Meantime, the optimal design and placement of BMPs would be different as well. The objective of this study was to discuss the relationship between the spatial variability of rainfall and the optimal BMPs placements. Three synthetic rainfall storms with varied spatial distributions, including uniform rainfall, downstream rainfall and upstream rainfall, were designed. WinVAST model was applied to predict runoff and NPSP. Additionally, detention pond and swale were selected for being structural BMPs. Scatter search was applied to find the optimal BMPs placement. The results show that mostly the total cost of BMPs is higher in downstream rainfall than in upstream rainfall or uniform rainfall. Moreover, the cost of detention pond is much higher than swale. Thus, even though detention pond has larger efficiency for lowering peak flow and pollutant exports, it is not always the determined set in each subbasin.

Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

NASA Astrophysics Data System (ADS)

Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

2018-05-01

Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

Hydrograph simulation models of the Hillsborough and Alafia Rivers, Florida: a preliminary report

USGS Publications Warehouse

Turner, James F.

1972-01-01

Mathematical (digital) models that simulate flood hydrographs from rainfall records have been developed for the following gaging stations in the Hillsborough and Alafia River basins of west-central Florida: Hillsborough River near Tampa, Alafia River at Lithia, and north Prong Alafia River near Keysville. These models, which were developed from historical streamflow and and rainfall records, are based on rainfall-runoff and unit-hydrograph procedures involving an arbitrary separation of the flood hydrograph. These models assume the flood hydrograph to be composed of only two flow components, direct (storm) runoff, and base flow. Expressions describing these two flow components are derived from streamflow and rainfall records and are combined analytically to form algorithms (models), which are programmed for processing on a digital computing system. Most Hillsborough and Alafia River flood discharges can be simulated with expected relative errors less than or equal to 30 percent and flood peaks can be simulated with average relative errors less than 15 percent. Because of the inadequate rainfall network that is used in obtaining input data for the North Prong Alafia River model, simulated peaks are frequently in error by more than 40 percent, particularly for storms having highly variable areal rainfall distribution. Simulation errors are the result of rainfall sample errors and, to a lesser extent, model inadequacy. Data errors associated with the determination of mean basin precipitation are the result of the small number and poor areal distribution of rainfall stations available for use in the study. Model inadequacy, however, is attributed to the basic underlying theory, particularly the rainfall-runoff relation. These models broaden and enhance existing water-management capabilities within these basins by allowing the establishment and implementation of programs providing for continued development in these areas. Specifically, the models serve not only as a basis for forecasting floods, but also for simulating hydrologic information needed in flood-plain mapping and delineating and evaluating alternative flood control and abatement plans.

Integrating a Linear Signal Model with Groundwater and Rainfall time-series on the Characteristic Identification of Groundwater Systems

NASA Astrophysics Data System (ADS)

Chen, Yu-Wen; Wang, Yetmen; Chang, Liang-Cheng

2017-04-01

Groundwater resources play a vital role on regional supply. To avoid irreversible environmental impact such as land subsidence, the characteristic identification of groundwater system is crucial before sustainable management of groundwater resource. This study proposes a signal process approach to identify the character of groundwater systems based on long-time hydrologic observations include groundwater level and rainfall. The study process contains two steps. First, a linear signal model (LSM) is constructed and calibrated to simulate the variation of underground hydrology based on the time series of groundwater levels and rainfall. The mass balance equation of the proposed LSM contains three major terms contain net rate of horizontal exchange, rate of rainfall recharge and rate of pumpage and four parameters are required to calibrate. Because reliable records of pumpage is rare, the time-variant groundwater amplitudes of daily frequency (P ) calculated by STFT are assumed as linear indicators of puamage instead of pumpage records. Time series obtained from 39 observation wells and 50 rainfall stations in and around the study area, Pintung Plain, are paired for model construction. Second, the well-calibrated parameters of the linear signal model can be used to interpret the characteristic of groundwater system. For example, the rainfall recharge coefficient (γ) means the transform ratio between rainfall intention and groundwater level raise. The area around the observation well with higher γ means that the saturated zone here is easily affected by rainfall events and the material of unsaturated zone might be gravel or coarse sand with high infiltration ratio. Considering the spatial distribution of γ, the values of γ decrease from the upstream to the downstream of major rivers and also are correlated to the spatial distribution of grain size of surface soil. Via the time-series of groundwater levels and rainfall, the well-calibrated parameters of LSM have ability to identify the characteristic of aquifer.

Simulation of radar reflectivity and surface measurements of rainfall

NASA Technical Reports Server (NTRS)

Chandrasekar, V.; Bringi, V. N.

1987-01-01

Raindrop size distributions (RSDs) are often estimated using surface raindrop sampling devices (e.g., disdrometers) or optical array (2D-PMS) probes. A number of authors have used these measured distributions to compute certain higher-order RSD moments that correspond to radar reflectivity, attenuation, optical extinction, etc. Scatter plots of these RSD moments versus disdrometer-measured rainrates are then used to deduce physical relationships between radar reflectivity, attenuation, etc., which are measured by independent instruments (e.g., radar), and rainrate. In this paper RSDs of the gamma form as well as radar reflectivity (via time series simulation) are simulated to study the correlation structure of radar estimates versus rainrate as opposed to RSD moment estimates versus rainrate. The parameters N0, D0 and m of a gamma distribution are varied over the range normally found in rainfall, as well as varying the device sampling volume. The simulations are used to explain some possible features related to discrepancies which can arise when radar rainfall measurements are compared with surface or aircraft-based sampling devices.

Elevated CO2 compensates for water stress in northern red oak

Treesearch

Patricia T. Tomlinson; Paul D. Anderson

1996-01-01

Global climate change models predict decreased rainfall in association with elevated CO2 in the western Lakes States region. Currently, the western edge of northern red oak (Quercus rubra L.) distribution coincides with the most xeric conditions of its ecological range. Decreased rainfall and water availability could alter...

Synthetic generation of spatially high resolution extreme rainfall in Japan using Monte Carlo simulation with AMeDAS analyzed rainfall data sets

NASA Astrophysics Data System (ADS)

Haruki, W.; Iseri, Y.; Takegawa, S.; Sasaki, O.; Yoshikawa, S.; Kanae, S.

2016-12-01

Natural disasters caused by heavy rainfall occur every year in Japan. Effective countermeasures against such events are important. In 2015, a catastrophic flood occurred in Kinu river basin, which locates in the northern part of Kanto region. The remarkable feature of this flood event was not only in the intensity of rainfall but also in the spatial characteristics of heavy rainfall area. The flood was caused by continuous overlapping of heavy rainfall area over the Kinu river basin, suggesting consideration of spatial extent is quite important to assess impacts of heavy rainfall events. However, the spatial extent of heavy rainfall events cannot be properly measured through rainfall measurement by rain gauges at observation points. On the other hand, rainfall measurements by radar observations provide spatially and temporarily high resolution rainfall data which would be useful to catch the characteristics of heavy rainfall events. For long term effective countermeasure, extreme heavy rainfall scenario considering rainfall area and distribution is required. In this study, a new method for generating extreme heavy rainfall events using Monte Carlo Simulation has been developed in order to produce extreme heavy rainfall scenario. This study used AMeDAS analyzed precipitation data which is high resolution grid precipitation data made by Japan Meteorological Agency. Depth area duration (DAD) analysis has been conducted to extract extreme rainfall events in the past, considering time and spatial scale. In the Monte Carlo Simulation, extreme rainfall event is generated based on events extracted by DAD analysis. Extreme heavy rainfall events are generated in specific region in Japan and the types of generated extreme heavy rainfall events can be changed by varying the parameter. For application of this method, we focused on Kanto region in Japan. As a result, 3000 years rainfall data are generated. 100 -year probable rainfall and return period of flood in Kinu River Basin (2015) are obtained using generated data. We compared 100-year probable rainfall calculated by this method with other traditional method. New developed method enables us to generate extreme rainfall events considering time and spatial scale and produce extreme rainfall scenario.

A dependence modelling study of extreme rainfall in Madeira Island

NASA Astrophysics Data System (ADS)

Gouveia-Reis, Délia; Guerreiro Lopes, Luiz; Mendonça, Sandra

2016-08-01

The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.

Significant Features of Warm Season Water Vapor Flux Related to Heavy Rainfall and Draught in Japan

NASA Astrophysics Data System (ADS)

Nishiyama, Koji; Iseri, Yoshihiko; Jinno, Kenji

2009-11-01

In this study, our objective is to reveal complicated relationships between spatial water vapor inflow patterns and heavy rainfall activities in Kyushu located in the western part of Japan, using the outcomes of pattern recognition of water vapor inflow, based on the Self-Organizing Map. Consequently, it could be confirmed that water vapor inflow patterns control the distribution and the frequency of heavy rainfall depending on the direction of their fluxes and the intensity of Precipitable water. Historically serious flood disasters in South Kyushu in 1993 were characterized by high frequency of the water vapor inflow patterns linking to heavy rainfall. On the other hand, severe draught in 1994 was characterized by inactive frontal activity that do not related to heavy rainfall.

Design of the primary pre-TRMM and TRMM ground truth site

NASA Technical Reports Server (NTRS)

Garstang, Michael

1988-01-01

The primary objective of the Tropical Rain Measuring Mission (TRMM) were to: integrate the rain gage measurements with radar measurements of rainfall using the KSFC/Patrick digitized radar and associated rainfall network; delineate the major rain bearing systems over Florida using the Weather Service reported radar/rainfall distributions; combine the integrated measurements with the delineated rain bearing systems; use the results of the combined measurements and delineated rain bearing systems to represent patterns of rainfall which actually exist and contribute significantly to the rainfall to test sampling strategies and based on the results of these analyses decide upon the ground truth network; and complete the design begun in Phase 1 of a multi-scale (space and time) surface observing precipitation network centered upon KSFC. Work accomplished and in progress is discussed.

Rainfall simulators in hydrological and geomorphological sciences: benefits, applications and future research directions

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Cerdà, Artemi; Fister, Wolfgang; Seitz, Steffen; Keesstra, Saskia; Green, Daniel; Gabriels, Donald

2017-04-01

Rainfall simulators are used extensively within the hydrological and geomorphological sciences and provide a useful investigative tool to understand many processes, such as: (i) plot-scale runoff, infiltration and erosion; (ii) irrigation and crop management, and; (iii) investigations into flooding within a laboratory setting. Although natural rainfall is desirable as it represents actual conditions in a given geographic location, data acquisition relying on natural rainfall is often hindered by its unpredictable nature. Furthermore, rainfall characteristics such as the intensity, duration, drop size distribution and kinetic energy cannot be spatially or temporally regulated or repeated between experimentation. Rainfall simulators provide a suitable method to overcome the issues associated with depending on potentially erratic and unpredictable natural rainfall as they allow: (i) multiple measurements to be taken quickly without waiting for suitable natural rainfall conditions; (ii) the simulation of spatially and/or temporally controlled rainfall patterns over a given plot area, and; (iii) the creation of a closed environment, allowing simplified measurement of input and output conditions. There is no standardisation of rainfall simulation and as such, rainfall simulators differ in their design, rainfall characteristics and research application. Although this impedes drawing meaningful comparisons between studies, this allows researchers to create a bespoke and tailored rainfall simulator for the specific research application. This paper summarises the rainfall simulators used in European research institutions (Universities of Trier, Valencia, Basel, Tuebingen, Wageningen, Loughborough and Ghent) to investigate a number of hydrological and geomorphological issues and includes details on the design specifications (such as the extent and characteristics of simulated rainfall), as well as a discussion of the purpose and application of the rainfall simulator.

A 507-year rainfall and runoff reconstruction for the Monsoonal North West, Australia derived from remote paleoclimate archives

NASA Astrophysics Data System (ADS)

Verdon-Kidd, Danielle C.; Hancock, Gregory R.; Lowry, John B.

2017-11-01

The Monsoonal North West (MNW) region of Australia faces a number of challenges adapting to anthropogenic climate change. These have the potential to impact on a range of industries, including agricultural, pastoral, mining and tourism. However future changes to rainfall regimes remain uncertain due to the inability of Global Climate Models to adequately capture the tropical weather/climate processes that are known to be important for this region. Compounding this is the brevity of the instrumental rainfall record for the MNW, which is unlikely to represent the full range of climatic variability. One avenue for addressing this issue (the focus of this paper) is to identify sources of paleoclimate information that can be used to reconstruct a plausible pre-instrumental rainfall history for the MNW. Adopting this approach we find that, even in the absence of local sources of paleoclimate data at a suitable temporal resolution, remote paleoclimate records can resolve 25% of the annual variability observed in the instrumental rainfall record. Importantly, the 507-year rainfall reconstruction developed using the remote proxies displays longer and more intense wet and dry periods than observed during the most recent 100 years. For example, the maximum number of consecutive years of below (above) average rainfall is 90% (40%) higher in the rainfall reconstruction than during the instrumental period. Further, implications for flood and drought risk are studied via a simple GR1A rainfall runoff model, which again highlights the likelihood of extremes greater than that observed in the limited instrumental record, consistent with previous paleoclimate studies elsewhere in Australia. Importantly, this research can assist in informing climate related risks to infrastructure, agriculture and mining, and the method can readily be applied to other regions in the MNW and beyond.

An initial-abstraction, constant-loss model for unit hydrograph modeling for applicable watersheds in Texas

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2007-01-01

Estimation of representative hydrographs from design storms, which are known as design hydrographs, provides for cost-effective, riskmitigated design of drainage structures such as bridges, culverts, roadways, and other infrastructure. During 2001?07, the U.S. Geological Survey (USGS), in cooperation with the Texas Department of Transportation, investigated runoff hydrographs, design storms, unit hydrographs,and watershed-loss models to enhance design hydrograph estimation in Texas. Design hydrographs ideally should mimic the general volume, peak, and shape of observed runoff hydrographs. Design hydrographs commonly are estimated in part by unit hydrographs. A unit hydrograph is defined as the runoff hydrograph that results from a unit pulse of excess rainfall uniformly distributed over the watershed at a constant rate for a specific duration. A time-distributed, watershed-loss model is required for modeling by unit hydrographs. This report develops a specific time-distributed, watershed-loss model known as an initial-abstraction, constant-loss model. For this watershed-loss model, a watershed is conceptualized to have the capacity to store or abstract an absolute depth of rainfall at and near the beginning of a storm. Depths of total rainfall less than this initial abstraction do not produce runoff. The watershed also is conceptualized to have the capacity to remove rainfall at a constant rate (loss) after the initial abstraction is satisfied. Additional rainfall inputs after the initial abstraction is satisfied contribute to runoff if the rainfall rate (intensity) is larger than the constant loss. The initial abstraction, constant-loss model thus is a two-parameter model. The initial-abstraction, constant-loss model is investigated through detailed computational and statistical analysis of observed rainfall and runoff data for 92 USGS streamflow-gaging stations (watersheds) in Texas with contributing drainage areas from 0.26 to 166 square miles. The analysis is limited to a previously described, watershed-specific, gamma distribution model of the unit hydrograph. In particular, the initial-abstraction, constant-loss model is tuned to the gamma distribution model of the unit hydrograph. A complex computational analysis of observed rainfall and runoff for the 92 watersheds was done to determine, by storm, optimal values of initial abstraction and constant loss. Optimal parameter values for a given storm were defined as those values that produced a modeled runoff hydrograph with volume equal to the observed runoff hydrograph and also minimized the residual sum of squares of the two hydrographs. Subsequently, the means of the optimal parameters were computed on a watershed-specific basis. These means for each watershed are considered the most representative, are tabulated, and are used in further statistical analyses. Statistical analyses of watershed-specific, initial abstraction and constant loss include documentation of the distribution of each parameter using the generalized lambda distribution. The analyses show that watershed development has substantial influence on initial abstraction and limited influence on constant loss. The means and medians of the 92 watershed-specific parameters are tabulated with respect to watershed development; although they have considerable uncertainty, these parameters can be used for parameter prediction for ungaged watersheds. The statistical analyses of watershed-specific, initial abstraction and constant loss also include development of predictive procedures for estimation of each parameter for ungaged watersheds. Both regression equations and regression trees for estimation of initial abstraction and constant loss are provided. The watershed characteristics included in the regression analyses are (1) main-channel length, (2) a binary factor representing watershed development, (3) a binary factor representing watersheds with an abundance of rocky and thin-soiled terrain, and (4) curve numb

The Use of Radar-Based Products for Deriving Extreme Rainfall Frequencies Using Regional Frequency Analysis with Application in South Louisiana

NASA Astrophysics Data System (ADS)

Eldardiry, H. A.; Habib, E. H.

2014-12-01

Radar-based technologies have made spatially and temporally distributed quantitative precipitation estimates (QPE) available in an operational environmental compared to the raingauges. The floods identified through flash flood monitoring and prediction systems are subject to at least three sources of uncertainties: (a) those related to rainfall estimation errors, (b) those due to streamflow prediction errors due to model structural issues, and (c) those due to errors in defining a flood event. The current study focuses on the first source of uncertainty and its effect on deriving important climatological characteristics of extreme rainfall statistics. Examples of such characteristics are rainfall amounts with certain Average Recurrence Intervals (ARI) or Annual Exceedance Probability (AEP), which are highly valuable for hydrologic and civil engineering design purposes. Gauge-based precipitation frequencies estimates (PFE) have been maturely developed and widely used over the last several decades. More recently, there has been a growing interest by the research community to explore the use of radar-based rainfall products for developing PFE and understand the associated uncertainties. This study will use radar-based multi-sensor precipitation estimates (MPE) for 11 years to derive PFE's corresponding to various return periods over a spatial domain that covers the state of Louisiana in southern USA. The PFE estimation approach used in this study is based on fitting generalized extreme value distribution to hydrologic extreme rainfall data based on annual maximum series (AMS). Some of the estimation problems that may arise from fitting GEV distributions at each radar pixel is the large variance and seriously biased quantile estimators. Hence, a regional frequency analysis approach (RFA) is applied. The RFA involves the use of data from different pixels surrounding each pixel within a defined homogenous region. In this study, region of influence approach along with the index flood technique are used in the RFA. A bootstrap technique procedure is carried out to account for the uncertainty in the distribution parameters to construct 90% confidence intervals (i.e., 5% and 95% confidence limits) on AMS-based precipitation frequency curves.

Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length

NASA Astrophysics Data System (ADS)

Guan, Kaiyu; Good, Stephen P.; Caylor, Kelly K.; Medvigy, David; Pan, Ming; Wood, Eric F.; Sato, Hisashi; Biasutti, Michela; Chen, Min; Ahlström, Anders; Xu, Xiangtao

2018-02-01

There is growing evidence of ongoing changes in the statistics of intra-seasonal rainfall variability over large parts of the world. Changes in annual total rainfall may arise from shifts, either singly or in a combination, of distinctive intra-seasonal characteristics -i.e. rainfall frequency, rainfall intensity, and rainfall seasonality. Understanding how various ecosystems respond to the changes in intra-seasonal rainfall characteristics is critical for predictions of future biome shifts and ecosystem services under climate change, especially for arid and semi-arid ecosystems. Here, we use an advanced dynamic vegetation model (SEIB-DGVM) coupled with a stochastic rainfall/weather simulator to answer the following question: how does the productivity of ecosystems respond to a given percentage change in the total seasonal rainfall that is realized by varying only one of the three rainfall characteristics (rainfall frequency, intensity, and rainy season length)? We conducted ensemble simulations for continental Africa for a realistic range of changes (-20% ~ +20%) in total rainfall amount. We find that the simulated ecosystem productivity (measured by gross primary production, GPP) shows distinctive responses to the intra-seasonal rainfall characteristics. Specifically, increase in rainfall frequency can lead to 28% more GPP increase than the same percentage increase in rainfall intensity; in tropical woodlands, GPP sensitivity to changes in rainy season length is ~4 times larger than to the same percentage changes in rainfall frequency or intensity. In contrast, shifts in the simulated biome distribution are much less sensitive to intra-seasonal rainfall characteristics than they are to total rainfall amount. Our results reveal three major distinctive productivity responses to seasonal rainfall variability—‘chronic water stress’, ‘acute water stress’ and ‘minimum water stress’ - which are respectively associated with three broad spatial patterns of African ecosystem physiognomy, i.e. savannas, woodlands, and tropical forests.

Droughts, rainfall and rural water supply in northern Nigeria

NASA Astrophysics Data System (ADS)

Tarhule, Aondover Augustine

Knowledge concerning various aspects of drought and water scarcity is required to predict, and to articulate strategies to minimize the effects of future events. This thesis investigated different aspects of droughts and rainfall variability at several time scales and described the dynamics of water supply and use in a rural village in northeastern Nigeria. The parallel existence of measured climatic records and information on famine/folklore events is utilized to calibrate the historical information against the measured data. It is shown that famines or historical droughts occurred when the cumulative deficit of rainfall fell below 1.3 times the standard deviation of the long-term mean rainfall. The study demonstrated that famine chronologies are adequate proxy for drought events, providing a means for the reconstruction of the drought/climatic history of the region. Analysis of recent changes in annual rainfall characteristics show that the series of annual rainfall and number of rain days experienced a discontinuity during the 1960's, caused largely by the decrease in the frequency of moderate to high intensity rain events. The periods prior to and after the change point are homogenous and provide an objective basis for the estimation of changes in rainfall characteristics, drought parameters and for demarcating the region into sub-zones. Rainfall variability was unaffected by the abrupt change. Furthermore, the variability is independently distributed and adequately described by the normal distribution. This allows estimates of the probability of various magnitudes or thresholds of variability. The effects of droughts and rainfall variability are most strongly felt in rural areas. Analysis of the patterns of water supply and use in a typical rural village revealed that the hydrologic system is driven by the local rainfall. Perturbations in the rains propagate through the system with short lag time between the various components. Where fadama aquifers occur, they offer a major supplement of water for six to seven months during the dry season. Under traditional systems, the pattern of water withdrawal from the fadama aquifers is designed to accommodate the diverse interests of different groups and to minimize the potential for conflict. The results contribute to our understanding of drought and water scarcity and are useful in various practical applications.

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

PubMed

van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

2015-05-01

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

Re-assessing Rainwater Harvesting Volume by CHIRPS Satellite in Semarang Settlement Area

NASA Astrophysics Data System (ADS)

Prihanto, Yosef; Koestoer, Raldi H.; Sutjiningsih, Dwita

2017-12-01

Semarang City is one of the most influential coastal cities in Java Island. The city is facing increasingly-high water demand due to its development and water problems due to climate change. The spatial physiography and landscape of Semarang City are also exposed the city to water security problem. Hence, rainwater harvesting treatment is an urgent effort to meet the city’s water needs. However, planning, implementation and management of rainwater harvesting are highly depended on multitemporal rainfall data. It has not yet been fully compiled due to limited rain stations. This study aims to examine the extent to which CHIRPS satellite data can be utilized in estimating volume of rainwater harvesting 16 sub-districts in Semarang and determine the water security status. This study uses descriptive statistical method based on spatial analyses. Such method was developed through spatial modeling for rainfall using isohyetal model. The parameters used are rainfall, residential rooftop area, administrative area, population, physiographic and altitude units. Validation is carried out by using monthly 10 rain stations data. The results show level of validity by utilizing CHIRPS Satellite data and mapping rainfall distribution. This study also produces a potential map of distribution rainfall volume that can be harvested in 16 sub-districts of Semarang.

Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil.

PubMed

Santos, Celso Augusto Guimarães; Brasil Neto, Reginaldo Moura; Passos, Jacqueline Sobral de Araújo; da Silva, Richarde Marques

2017-06-01

In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).

Influences of the MJO on the space-time organization of tropical convection

NASA Astrophysics Data System (ADS)

Dias, Juliana; Sakaeda, Naoko; Kiladis, George N.; Kikuchi, Kazuyoshi

2017-08-01

The fact that the Madden-Julian Oscillation (MJO) is characterized by large-scale patterns of enhanced tropical rainfall has been widely recognized for decades. However, the precise nature of any two-way feedback between the MJO and the properties of smaller-scale organization that makes up its convective envelope is not well understood. Satellite estimates of brightness temperature are used here as a proxy for tropical rainfall, and a variety of diagnostics are applied to determine the degree to which tropical convection is affected either locally or globally by the MJO. To address the multiscale nature of tropical convective organization, the approach ranges from space-time spectral analysis to an object-tracking algorithm. In addition to the intensity and distribution of global tropical rainfall, the relationship between the MJO and other tropical processes such as convectively coupled equatorial waves, mesoscale convective systems, and the diurnal cycle of tropical convection is also analyzed. The main findings of this paper are that, aside from the well-known increase in rainfall activity across scales within the MJO convective envelope, the MJO does not favor any particular scale or type of organization, and there is no clear signature of the MJO in terms of the globally integrated distribution of brightness temperature or rainfall.

Precipitation intensity probability distribution modelling for hydrological and construction design purposes

NASA Astrophysics Data System (ADS)

Koshinchanov, Georgy; Dimitrov, Dobri

2008-11-01

The characteristics of rainfall intensity are important for many purposes, including design of sewage and drainage systems, tuning flood warning procedures, etc. Those estimates are usually statistical estimates of the intensity of precipitation realized for certain period of time (e.g. 5, 10 min., etc) with different return period (e.g. 20, 100 years, etc). The traditional approach in evaluating the mentioned precipitation intensities is to process the pluviometer's records and fit probability distribution to samples of intensities valid for certain locations ore regions. Those estimates further become part of the state regulations to be used for various economic activities. Two problems occur using the mentioned approach: 1. Due to various factors the climate conditions are changed and the precipitation intensity estimates need regular update; 2. As far as the extremes of the probability distribution are of particular importance for the practice, the methodology of the distribution fitting needs specific attention to those parts of the distribution. The aim of this paper is to make review of the existing methodologies for processing the intensive rainfalls and to refresh some of the statistical estimates for the studied areas. The methodologies used in Bulgaria for analyzing the intensive rainfalls and produce relevant statistical estimates: The method of the maximum intensity, used in the National Institute of Meteorology and Hydrology to process and decode the pluviometer's records, followed by distribution fitting for each precipitation duration period; As the above, but with separate modeling of probability distribution for the middle and high probability quantiles. Method is similar to the first one, but with a threshold of 0,36 mm/min of intensity; Another method proposed by the Russian hydrologist G. A. Aleksiev for regionalization of estimates over some territory, improved and adapted by S. Gerasimov for Bulgaria; Next method is considering only the intensive rainfalls (if any) during the day with the maximal annual daily precipitation total for a given year; Conclusions are drown on the relevance and adequacy of the applied methods.

Effects of Climate Change and Fisheries Bycatch on Shy Albatross (Thalassarche cauta) in Southern Australia

PubMed Central

2015-01-01

The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change. PMID:26057739

Effects of Climate Change and Fisheries Bycatch on Shy Albatross (Thalassarche cauta) in Southern Australia.

PubMed

Thomson, Robin B; Alderman, Rachael L; Tuck, Geoffrey N; Hobday, Alistair J

2015-01-01

The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change.

MAJOR TRANSPORT MECHANISMS OF PYRETHROIDS IN RESIDENTIAL SETTINGS AND EFFECTS OF MITIGATION MEASURES

PubMed Central

Davidson, Paul C; Jones, Russell L; Harbourt, Christopher M; Hendley, Paul; Goodwin, Gregory E; Sliz, Bradley A

2014-01-01

The major pathways for transport of pyrethroids were determined in runoff studies conducted at a full-scale test facility in central California, USA. The 6 replicate house lots were typical of front lawns and house fronts of California residential developments and consisted of stucco walls, garage doors, driveways, and residential lawn irrigation sprinkler systems. Each of the 6 lots also included a rainfall simulator to generate artificial rainfall events. Different pyrethroids were applied to 5 surfaces—driveway, garage door and adjacent walls, lawn, lawn perimeter (grass near the house walls), and house walls above grass. The volume of runoff water from each house lot was measured, sampled, and analyzed to determine the amount of pyrethroid mass lost from each surface. Applications to 3 of the house lots were made using the application practices typically used prior to recent label changes, and applications were made to the other 3 house lots according to the revised application procedures. Results from the house lots using the historic application procedures showed that losses of the compounds applied to the driveway and garage door (including the adjacent walls) were 99.75% of total measured runoff losses. The greatest losses were associated with significant rainfall events rather than lawn irrigation events. However, runoff losses were 40 times less using the revised application procedures recently specified on pyrethroid labels. Environ Toxicol Chem 2014;33:52–60. © 2013 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited. PMID:24105831

Stormwater runoff pollutant loading distributions and their correlation with rainfall and catchment characteristics in a rapidly industrialized city.

PubMed

Li, Dongya; Wan, Jinquan; Ma, Yongwen; Wang, Yan; Huang, Mingzhi; Chen, Yangmei

2015-01-01

Fast urbanization and industrialization in developing countries result in significant stormwater runoff pollution, due to drastic changes in land-use, from rural to urban. A three-year study on the stormwater runoff pollutant loading distributions of industrial, parking lot and mixed commercial and residential catchments was conducted in the Tongsha reservoir watershed of Dongguan city, a typical, rapidly industrialized urban area in China. This study presents the changes in concentration during rainfall events, event mean concentrations (EMCs) and event pollution loads per unit area (EPLs). The first flush criterion, namely the mass first flush ratio (MFFn), was used to identify the first flush effects. The impacts of rainfall and catchment characterization on EMCs and pollutant loads percentage transported by the first 40% of runoff volume (FF40) were evaluated. The results indicated that the pollutant wash-off process of runoff during the rainfall events has significant temporal and spatial variations. The mean rainfall intensity (I), the impervious rate (IMR) and max 5-min intensity (Imax5) are the critical parameters of EMCs, while Imax5, antecedent dry days (ADD) and rainfall depth (RD) are the critical parameters of FF40. Intercepting the first 40% of runoff volume can remove 55% of TSS load, 53% of COD load, 58% of TN load, and 61% of TP load, respectively, according to all the storm events. These results may be helpful in mitigating stormwater runoff pollution for many other urban areas in developing countries.

Seasonality on the rainfall partitioning of a fast-growing tree plantation under Mediterranean conditions

NASA Astrophysics Data System (ADS)

molina, antonio; llorens, pilar; biel, carme

2014-05-01

Studies on rainfall interception in fast-growing tree plantations are less numerous than those in natural forests. Trees in these plantations are regularly distributed, and the canopy cover is clumped but changes quickly, resulting on high variability in the volume and composition of water that reach the soil. In addition, irrigation supply is normally required in semiarid areas to get optimal wood production; consequently, knowing rainfall interception and its yearly evolution is crucial to manage the irrigation scheme properly. This work studies the rainfall partitioning seasonality in a cherry tree (Prunus avium) plantation orientated to timber production under Mediterranean conditions. The monitoring design started on March 2012 and consists of a set of 58 throughfall tipping buckets randomly distributed (based on a 1x1 m2 grid) in a plot of 128 m2 with 8 trees. Stemflow is measured in all the trees with 2 tipping buckets and 6 accumulative collectors. Canopy cover is regularly measured throughout the study period, in leaf and leafless periods, by mean of sky-orientated photographs taken 50 cm above the center of each tipping bucket. Others tree biometrics are also measured such as diameter and leaf area index. Meteorological conditions are measured at 2 m above the forest cover. This work presents the first analyses describing the rainfall partitioning and its dependency on canopy cover, distance to tree and meteorological conditions. The modified Gash' model for rainfall interception in dispersed vegetation is also preliminary evaluated.

A Multiplicative Cascade Model for High-Resolution Space-Time Downscaling of Rainfall

NASA Astrophysics Data System (ADS)

Raut, Bhupendra A.; Seed, Alan W.; Reeder, Michael J.; Jakob, Christian

2018-02-01

Distributions of rainfall with the time and space resolutions of minutes and kilometers, respectively, are often needed to drive the hydrological models used in a range of engineering, environmental, and urban design applications. The work described here is the first step in constructing a model capable of downscaling rainfall to scales of minutes and kilometers from time and space resolutions of several hours and a hundred kilometers. A multiplicative random cascade model known as the Short-Term Ensemble Prediction System is run with parameters from the radar observations at Melbourne (Australia). The orographic effects are added through multiplicative correction factor after the model is run. In the first set of model calculations, 112 significant rain events over Melbourne are simulated 100 times. Because of the stochastic nature of the cascade model, the simulations represent 100 possible realizations of the same rain event. The cascade model produces realistic spatial and temporal patterns of rainfall at 6 min and 1 km resolution (the resolution of the radar data), the statistical properties of which are in close agreement with observation. In the second set of calculations, the cascade model is run continuously for all days from January 2008 to August 2015 and the rainfall accumulations are compared at 12 locations in the greater Melbourne area. The statistical properties of the observations lie with envelope of the 100 ensemble members. The model successfully reproduces the frequency distribution of the 6 min rainfall intensities, storm durations, interarrival times, and autocorrelation function.

Stormwater Runoff Pollutant Loading Distributions and Their Correlation with Rainfall and Catchment Characteristics in a Rapidly Industrialized City

PubMed Central

Li, Dongya; Wan, Jinquan; Ma, Yongwen; Wang, Yan; Huang, Mingzhi; Chen, Yangmei

2015-01-01

Fast urbanization and industrialization in developing countries result in significant stormwater runoff pollution, due to drastic changes in land-use, from rural to urban. A three-year study on the stormwater runoff pollutant loading distributions of industrial, parking lot and mixed commercial and residential catchments was conducted in the Tongsha reservoir watershed of Dongguan city, a typical, rapidly industrialized urban area in China. This study presents the changes in concentration during rainfall events, event mean concentrations (EMCs) and event pollution loads per unit area (EPLs). The first flush criterion, namely the mass first flush ratio (MFFn), was used to identify the first flush effects. The impacts of rainfall and catchment characterization on EMCs and pollutant loads percentage transported by the first 40% of runoff volume (FF40) were evaluated. The results indicated that the pollutant wash-off process of runoff during the rainfall events has significant temporal and spatial variations. The mean rainfall intensity (I), the impervious rate (IMR) and max 5-min intensity (Imax5) are the critical parameters of EMCs, while Imax5, antecedent dry days (ADD) and rainfall depth (RD) are the critical parameters of FF40. Intercepting the first 40% of runoff volume can remove 55% of TSS load, 53% of COD load, 58% of TN load, and 61% of TP load, respectively, according to all the storm events. These results may be helpful in mitigating stormwater runoff pollution for many other urban areas in developing countries. PMID:25774922

Modelling urban rainfall-runoff responses using an experimental, two-tiered physical modelling environment

NASA Astrophysics Data System (ADS)

Green, Daniel; Pattison, Ian; Yu, Dapeng

2016-04-01

Surface water (pluvial) flooding occurs when rainwater from intense precipitation events is unable to infiltrate into the subsurface or drain via natural or artificial drainage channels. Surface water flooding poses a serious hazard to urban areas across the world, with the UK's perceived risk appearing to have increased in recent years due to surface water flood events seeming more severe and frequent. Surface water flood risk currently accounts for 1/3 of all UK flood risk, with approximately two million people living in urban areas at risk of a 1 in 200-year flood event. Research often focuses upon using numerical modelling techniques to understand the extent, depth and severity of actual or hypothetical flood scenarios. Although much research has been conducted using numerical modelling, field data available for model calibration and validation is limited due to the complexities associated with data collection in surface water flood conditions. Ultimately, the data which numerical models are based upon is often erroneous and inconclusive. Physical models offer a novel, alternative and innovative environment to collect data within, creating a controlled, closed system where independent variables can be altered independently to investigate cause and effect relationships. A physical modelling environment provides a suitable platform to investigate rainfall-runoff processes occurring within an urban catchment. Despite this, physical modelling approaches are seldom used in surface water flooding research. Scaled laboratory experiments using a 9m2, two-tiered 1:100 physical model consisting of: (i) a low-cost rainfall simulator component able to simulate consistent, uniformly distributed (>75% CUC) rainfall events of varying intensity, and; (ii) a fully interchangeable, modular plot surface have been conducted to investigate and quantify the influence of a number of terrestrial and meteorological factors on overland flow and rainfall-runoff patterns within a modelled urban setting. Terrestrial factors investigated include altering the physical model's catchment slope (0°- 20°), as well as simulating a number of spatially-varied impermeability and building density/configuration scenarios. Additionally, the influence of different storm dynamics and intensities were investigated. Preliminary results demonstrate that rainfall-runoff responses in the physical modelling environment are highly sensitive to slight increases in catchment gradient and rainfall intensity and that more densely distributed building layouts significantly increase peak flows recorded at the physical model outflow when compared to sparsely distributed building layouts under comparable simulated rainfall conditions.

Expected irrigation reductions using multiple-inlet rice irrigation under rainfall conditions in the lower Mississippi River Valley.

USDA-ARS?s Scientific Manuscript database

A model was developed to compare irrigation applications made using single-inlet and multiple-inlet rice flood distribution practices commonly used in the Lower Mississippi River Valley. The model was used to determine potential irrigation reductions under a wide range of natural rainfall amounts an...

Influence of different rates of rainfall in the basin of the Uruguay River

NASA Astrophysics Data System (ADS)

Bohrer, M.; Zaparoli, B.; Saldanha, C. B.

2013-04-01

In the state of Rio Grande do Sul, the rainfall pattern is fairly regular and precipitation is well distributed throughout the year. The aim of this study was to evaluate the spatial and temporal distribution of precipitation in the Uruguay River basin from the determination of homogeneous regions based on the rainfall pattern. Values of 47 meteorological stations of the ANA (National Water Agency) from 1975 to 2005 were used, and values of Pacific sea surface temperature were collected from the National Oceanic and Atmospheric Administration, which is based on observed anomalies for different regions' niños (1 + niño 2, 3 niño, niño 4, niño 3 + 4). From the analysis of the results it was found that the study region showed five homogeneous regions. Knowing the time series of each region, it was possible to verify the regional variability in precipitation, indicating which regions have values above and below the climatological normal, and how the different indexes influence the rainfall pattern in the region.

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

NASA Astrophysics Data System (ADS)

Gaitan, S.; ten Veldhuis, J. A. E.

2015-06-01

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

[Particle Size Distribution and Pollutant Speciation Analyses of Stormwater Runoff in the Ancient Town of Suzhou].

PubMed

Li, Huai; Wu, Wei; Tian, Yong-jing; Huang, Tian-yin

2016-02-15

The particle size distribution (PSD) and its transformation processes in the stormwater runoffs in the ancient town of Suzhou were studied based on the particles size analyses, the water-quality monitoring data and the parameters of the rainfall-runoff models. The commercial districts, the modern residential area, the old residential area, the traffic area and the landscape tourist area were selected as the five functional example areas in the ancient town of Suzhou. The effects of antecedent dry period, the rainfall intensity and the amount of runoffs on the particle size distributions were studied, and the existing forms of the main pollutants in different functional areas and their possible relations were analyzed as well. The results showed that the particle size distribution, the migration processes and the output characteristics in the stormwater runoffs were greatly different in these five functional areas, which indicated different control measures for the pollution of the runoffs should be taken in the design process. The antecedent dry period, the rainfall intensity and the amount of runoffs showed significant correlations with the particle size distribution, showing these were the important factors. The output of the particles was greatly influenced by the flow scouring in the early period of the rainfall, and the correlations between the amount of runoffs and the particle migration ability presented significant difference in 30% (early period) and 70% (later period) of the runoff volume. The major existence form of the output pollutants was particle, and the correlation analyses of different diameter particles showed that the particles smaller than 150 microm were the dominant carrier of the pollutants via adsorption and accumulation processes.

An analytic solution of the stochastic storage problem applicable to soil water

USGS Publications Warehouse

Milly, P.C.D.

1993-01-01

The accumulation of soil water during rainfall events and the subsequent depletion of soil water by evaporation between storms can be described, to first order, by simple accounting models. When the alternating supplies (precipitation) and demands (potential evaporation) are viewed as random variables, it follows that soil-water storage, evaporation, and runoff are also random variables. If the forcing (supply and demand) processes are stationary for a sufficiently long period of time, an asymptotic regime should eventually be reached where the probability distribution functions of storage, evaporation, and runoff are stationary and uniquely determined by the distribution functions of the forcing. Under the assumptions that the potential evaporation rate is constant, storm arrivals are Poisson-distributed, rainfall is instantaneous, and storm depth follows an exponential distribution, it is possible to derive the asymptotic distributions of storage, evaporation, and runoff analytically for a simple balance model. A particular result is that the fraction of rainfall converted to runoff is given by (1 - R−1)/(eα(1−R−1) − R−1), in which R is the ratio of mean potential evaporation to mean rainfall and a is the ratio of soil water-holding capacity to mean storm depth. The problem considered here is analogous to the well-known problem of storage in a reservoir behind a dam, for which the present work offers a new solution for reservoirs of finite capacity. A simple application of the results of this analysis suggests that random, intraseasonal fluctuations of precipitation cannot by themselves explain the observed dependence of the annual water balance on annual totals of precipitation and potential evaporation.

Soil Infiltration Characteristics in Agroforestry Systems and Their Relationships with the Temporal Distribution of Rainfall on the Loess Plateau in China

PubMed Central

Wang, Lai; Zhong, Chonggao; Gao, Pengxiang; Xi, Weimin; Zhang, Shuoxin

2015-01-01

Many previous studies have shown that land use patterns are the main factors influencing soil infiltration. Thus, increasing soil infiltration and reducing runoff are crucial for soil and water conservation, especially in semi-arid environments. To explore the effects of agroforestry systems on soil infiltration and associated properties in a semi-arid area of the Loess Plateau in China, we compared three plant systems: a walnut (Juglans regia) monoculture system (JRMS), a wheat (Triticum aestivum) monoculture system (TAMS), and a walnut-wheat alley cropping system (JTACS) over a period of 11 years. Our results showed that the JTACS facilitated infiltration, and its infiltration rate temporal distribution showed a stronger relationship coupled with the rainfall temporal distribution compared with the two monoculture systems during the growing season. However, the effect of JTACS on the infiltration capacity was only significant in shallow soil layer, i.e., the 0–40 cm soil depth. Within JTACS, the speed of the wetting front’s downward movement was significantly faster than that in the two monoculture systems when the amount of rainfall and its intensity were higher. The soil infiltration rate was improved, and the two peaks of soil infiltration rate temporal distribution and the rainfall temporal distribution coupled in rainy season in the alley cropping system, which has an important significance in soil and water conservation. The results of this empirical study provide new insights into the sustainability of agroforestry, which may help farmers select rational planting patterns in this region, as well as other regions with similar climatic and environmental characteristics throughout the world. PMID:25893832

Soil Infiltration Characteristics in Agroforestry Systems and Their Relationships with the Temporal Distribution of Rainfall on the Loess Plateau in China.

PubMed

Wang, Lai; Zhong, Chonggao; Gao, Pengxiang; Xi, Weimin; Zhang, Shuoxin

2015-01-01

Many previous studies have shown that land use patterns are the main factors influencing soil infiltration. Thus, increasing soil infiltration and reducing runoff are crucial for soil and water conservation, especially in semi-arid environments. To explore the effects of agroforestry systems on soil infiltration and associated properties in a semi-arid area of the Loess Plateau in China, we compared three plant systems: a walnut (Juglans regia) monoculture system (JRMS), a wheat (Triticum aestivum) monoculture system (TAMS), and a walnut-wheat alley cropping system (JTACS) over a period of 11 years. Our results showed that the JTACS facilitated infiltration, and its infiltration rate temporal distribution showed a stronger relationship coupled with the rainfall temporal distribution compared with the two monoculture systems during the growing season. However, the effect of JTACS on the infiltration capacity was only significant in shallow soil layer, i.e., the 0-40 cm soil depth. Within JTACS, the speed of the wetting front's downward movement was significantly faster than that in the two monoculture systems when the amount of rainfall and its intensity were higher. The soil infiltration rate was improved, and the two peaks of soil infiltration rate temporal distribution and the rainfall temporal distribution coupled in rainy season in the alley cropping system, which has an important significance in soil and water conservation. The results of this empirical study provide new insights into the sustainability of agroforestry, which may help farmers select rational planting patterns in this region, as well as other regions with similar climatic and environmental characteristics throughout the world.

A statistical model of extreme storm rainfall

NASA Astrophysics Data System (ADS)

Smith, James A.; Karr, Alan F.

1990-02-01

A model of storm rainfall is developed for the central Appalachian region of the United States. The model represents the temporal occurrence of major storms and, for a given storm, the spatial distribution of storm rainfall. Spatial inhomogeneities of storm rainfall and temporal inhomogeneities of the storm occurrence process are explicitly represented. The model is used for estimating recurrence intervals of extreme storms. The parameter estimation procedure developed for the model is based on the substitution principle (method of moments) and requires data from a network of rain gages. The model is applied to a 5000 mi2 (12,950 km2) region in the Valley and Ridge Province of Virginia and West Virginia.

Organic carbon fluxes in stemflow, throughfall and rainfall in an olive orchard

NASA Astrophysics Data System (ADS)

Lombardo, L.; Vanwalleghem, T.; Gomez, J. A.

2012-04-01

The importance of rainfall distribution under the vegetation canopy for nutrient cycling of forest ecosystems has been widely studied (e.g. Kolkai et al., 1999, Bath et al., 2011). It has been demonstrated how throughfall and stemflow reach the soil as chemically-enriched water, by incorporating soluble organic and inorganic particles deriving from plant exudates and from atmospheric depositions (dryfall and wetfall) present on the surfaces of the plant (leaves, bark, fruits). Dissolved (DOC) and particulate (POC) organic carbon inputs from stem- and canopy-derived hydrologic fluxes are small but important components of the natural carbon cycle. DOC has also the capability to form complexes that control the transport and solubility of heavy metals in surface and ground waters, being composed for the most part (75-90%) of fulvic, humic or tanninic compounds, and for the resting part of molecules like carbohydrates, hydrocarbons, waxes, fatty acids, amino and hydroxy acids. However, very little data is available for agricultural tree crops, especially olive trees. In this sense, the objective of this work is to investigate the concentration and fluxes of organic carbon in rainfall, throughfall, and stemflow in a mature olive orchard located in Cordoba, in Southern Spain and to relate them to rainfall characteristics and tree physiology. The measurements started in October 2011. Four high density polyethylene bottles with 18-cm-diameter polyethylene funnels for throughfall collection were placed beneath the canopy of each of the three selected olive trees; four more collectors were placed in open spaces in the same orchard for rainfall sampling. Stemflow was collected through PVC spiral tubes wrapped around the trunks and leading into collection bins. The throughflow sampling points were chosen randomly. Total and dissolved organic carbon concentrations in unfiltered (TOC) and filtered (0.45 µm membrane filter, DOC) collected waters were measured using a TOC analyzer with a high temperature combustion system and infrared detection of the evolved CO2. The difference in concentration between TOC and DOC defined the POC concentration. Leaf area density (LAD) and leaf area index (LAI) of olive trees were calculated using the LAI-2000 plant canopy analyzer (PCA) (Li-Cor). Stemflow and throughfall resulted both influenced by the characteristics of precipitations (amount, time of the year), canopy volume and leaf characteristics, with stemflow showing, in average, higher DOC and POC concentration values compare to throughfall. Throughfall resulted between 4 and 17 times more concentrated DOC than rainfall, but highlighted a high site-specific variability related to the canopy architecture.

Uncertainty Analysis of Radar and Gauge Rainfall Estimates in the Russian River Basin

NASA Astrophysics Data System (ADS)

Cifelli, R.; Chen, H.; Willie, D.; Reynolds, D.; Campbell, C.; Sukovich, E.

2013-12-01

Radar Quantitative Precipitation Estimation (QPE) has been a very important application of weather radar since it was introduced and made widely available after World War II. Although great progress has been made over the last two decades, it is still a challenging process especially in regions of complex terrain such as the western U.S. It is also extremely difficult to make direct use of radar precipitation data in quantitative hydrologic forecasting models. To improve the understanding of rainfall estimation and distributions in the NOAA Hydrometeorology Testbed in northern California (HMT-West), extensive evaluation of radar and gauge QPE products has been performed using a set of independent rain gauge data. This study focuses on the rainfall evaluation in the Russian River Basin. The statistical properties of the different gridded QPE products will be compared quantitatively. The main emphasis of this study will be on the analysis of uncertainties of the radar and gauge rainfall products that are subject to various sources of error. The spatial variation analysis of the radar estimates is performed by measuring the statistical distribution of the radar base data such as reflectivity and by the comparison with a rain gauge cluster. The application of mean field bias values to the radar rainfall data will also be described. The uncertainty analysis of the gauge rainfall will be focused on the comparison of traditional kriging and conditional bias penalized kriging (Seo 2012) methods. This comparison is performed with the retrospective Multisensor Precipitation Estimator (MPE) system installed at the NOAA Earth System Research Laboratory. The independent gauge set will again be used as the verification tool for the newly generated rainfall products.

Improving the accuracy of flood forecasting with transpositions of ensemble NWP rainfall fields considering orographic effects

NASA Astrophysics Data System (ADS)

Yu, Wansik; Nakakita, Eiichi; Kim, Sunmin; Yamaguchi, Kosei

2016-08-01

The use of meteorological ensembles to produce sets of hydrological predictions increased the capability to issue flood warnings. However, space scale of the hydrological domain is still much finer than meteorological model, and NWP models have challenges with displacement. The main objective of this study to enhance the transposition method proposed in Yu et al. (2014) and to suggest the post-processing ensemble flood forecasting method for the real-time updating and the accuracy improvement of flood forecasts that considers the separation of the orographic rainfall and the correction of misplaced rain distributions using additional ensemble information through the transposition of rain distributions. In the first step of the proposed method, ensemble forecast rainfalls from a numerical weather prediction (NWP) model are separated into orographic and non-orographic rainfall fields using atmospheric variables and the extraction of topographic effect. Then the non-orographic rainfall fields are examined by the transposition scheme to produce additional ensemble information and new ensemble NWP rainfall fields are calculated by recombining the transposition results of non-orographic rain fields with separated orographic rainfall fields for a generation of place-corrected ensemble information. Then, the additional ensemble information is applied into a hydrologic model for post-flood forecasting with a 6-h interval. The newly proposed method has a clear advantage to improve the accuracy of mean value of ensemble flood forecasting. Our study is carried out and verified using the largest flood event by typhoon 'Talas' of 2011 over the two catchments, which are Futatsuno (356.1 km2) and Nanairo (182.1 km2) dam catchments of Shingu river basin (2360 km2), which is located in the Kii peninsula, Japan.

Effect of rainfall seasonality on carbon storage in tropical dry ecosystems

NASA Astrophysics Data System (ADS)

Rohr, Tyler; Manzoni, Stefano; Feng, Xue; Menezes, Rômulo S. C.; Porporato, Amilcare

2013-07-01

seasonally dry conditions are typical of large areas of the tropics, their biogeochemical responses to seasonal rainfall and soil carbon (C) sequestration potential are not well characterized. Seasonal moisture availability positively affects both productivity and soil respiration, resulting in a delicate balance between C deposition as litterfall and C loss through heterotrophic respiration. To understand how rainfall seasonality (i.e., duration of the wet season and rainfall distribution) affects this balance and to provide estimates of long-term C sequestration, we develop a minimal model linking the seasonal behavior of the ensemble soil moisture, plant productivity, related C inputs through litterfall, and soil C dynamics. A drought-deciduous caatinga ecosystem in northeastern Brazil is used as a case study to parameterize the model. When extended to different patterns of rainfall seasonality, the results indicate that for fixed annual rainfall, both plant productivity and soil C sequestration potential are largely, and nonlinearly, dependent on wet season duration. Moreover, total annual rainfall is a critical driver of this relationship, leading at times to distinct optima in both production and C storage. These theoretical predictions are discussed in the context of parameter uncertainties and possible changes in rainfall regimes in tropical dry ecosystems.

Convective and nonconvective rainfall partitioning over a mixed Sudanian Savanna Agriculture Catchment: Use of a distributed sensor network

NASA Astrophysics Data System (ADS)

Ceperley, N. C.; Mande, T.; Barrenetxea, G.; Repetti, A.; Yacouba, H.; Tyler, S. W.; Parlange, M. B.

2011-12-01

A hydro-meteorological field campaign (joint EPFL-2iE) in a mixed agricultural and forest region in the southern Burkina Faso Savanna aims to identify and understand convective rainfall processes and the link to soil moisture. A simple slab Mixed Layer and Lifting Condensation Level model is implemented to separate convective and nonconvective rainfall. Data for this research were acquired during the 2010 rainy season using an array of wireless weather stations (SensorScope) as well as surface energy balance stations that based upon eddy correlation heat flux measurements. The precipitation was found to be variable over the basin with some 200 mm of difference in total seasonal rainfall between agricultural fields and savanna forest. Convective rainfall represents more than 30% of the total rainfall. The convective rainfall events are short (less than hour), intense (greater than 3 mm/minute) and occur both in the early morning and in the afternoons. These events can have an important impact on soil erosion, which we discuss in more detail along with seasonal stream-aquifer interactions.

Hydrological control of large hurricane-induced lahars: evidence from rainfall-runoff modeling, seismic and video monitoring

NASA Astrophysics Data System (ADS)

Capra, Lucia; Coviello, Velio; Borselli, Lorenzo; Márquez-Ramírez, Víctor-Hugo; Arámbula-Mendoza, Raul

2018-03-01

The Volcán de Colima, one of the most active volcanoes in Mexico, is commonly affected by tropical rains related to hurricanes that form over the Pacific Ocean. In 2011, 2013 and 2015 hurricanes Jova, Manuel and Patricia, respectively, triggered tropical storms that deposited up to 400 mm of rain in 36 h, with maximum intensities of 50 mm h -1. The effects were devastating, with the formation of multiple lahars along La Lumbre and Montegrande ravines, which are the most active channels in sediment delivery on the south-southwest flank of the volcano. Deep erosion along the river channels and several marginal landslides were observed, and the arrival of block-rich flow fronts resulted in damages to bridges and paved roads in the distal reaches of the ravines. The temporal sequence of these flow events is reconstructed and analyzed using monitoring data (including video images, seismic records and rainfall data) with respect to the rainfall characteristics and the hydrologic response of the watersheds based on rainfall-runoff numerical simulation. For the studied events, lahars occurred 5-6 h after the onset of rainfall, lasted several hours and were characterized by several pulses with block-rich fronts and a maximum flow discharge of 900 m3 s -1. Rainfall-runoff simulations were performer using the SCS-curve number and the Green-Ampt infiltration models, providing a similar result in the detection of simulated maximum watershed peaks discharge. Results show different behavior for the arrival times of the first lahar pulses that correlate with the simulated catchment's peak discharge for La Lumbre ravine and with the peaks in rainfall intensity for Montegrande ravine. This different behavior is related to the area and shape of the two watersheds. Nevertheless, in all analyzed cases, the largest lahar pulse always corresponds with the last one and correlates with the simulated maximum peak discharge of these catchments. Data presented here show that flow pulses within a lahar are not randomly distributed in time, and they can be correlated with rainfall peak intensity and/or watershed discharge, depending on the watershed area and shape. This outcome has important implications for hazard assessment during extreme hydro-meteorological events, as it could help in providing real-time alerts. A theoretical rainfall distribution curve was designed for Volcán de Colima based on the rainfall and time distribution of hurricanes Manuel and Patricia. This can be used to run simulations using weather forecasts prior to the actual event, in order to estimate the arrival time of main lahar pulses, usually characterized by block-rich fronts, which are responsible for most of the damage to infrastructure and loss of goods and lives.

Changes to Sub-daily Rainfall Patterns in a Future Climate

NASA Astrophysics Data System (ADS)

Westra, S.; Evans, J. P.; Mehrotra, R.; Sharma, A.

2012-12-01

An algorithm is developed for disaggregating daily rainfall into sub-daily rainfall 'fragments' (continuous high temporal-resolution rainfall sequences whose total depth sums to the daily rainfall amount) under a future, warmer climate. The basis of the algorithm is to re-sample sub-daily fragments from the historical record conditional on the total daily rainfall amount and a range of temperature-based atmospheric predictors. The logic is that as the atmosphere warms, future rainfall patterns will be more reflective of historical rainfall patterns which occurred on warmer days at the same location, or at locations which have an atmospheric temperature profile more representative of expected future atmospheric conditions. It was found that the daily to sub-daily scaling relationship varied significantly by season and by location, with rainfall patterns on warmer seasons or at warmer locations typically exhibiting higher rainfall intensity occurring over shorter periods within a day, compared with cooler seasons and locations. Importantly, by regressing against temperature-based atmospheric covariates, this effect was substantially reduced, suggesting that the approach also may be valid when extrapolating to a future climate. An adjusted method of fragments algorithm was then applied to nine stations around Australia, with the results showing that when holding total daily rainfall constant, the maximum intensity of short duration rainfall increased by a median of about 5% per degree for the maximum 6 minute burst, and 3.5% for the maximum one hour burst, whereas the fraction of the day with no rainfall increased by a median of 1.5%. This highlights that a large proportion of the change to the distribution of rainfall is likely to occur at sub-daily timescales, with significant implications for many hydrological systems.

The Eastern Pacific ITCZ during the Boreal Spring

NASA Technical Reports Server (NTRS)

Gu, Guojun; Adler, Robert F.; Sobel, Adam H.

2004-01-01

The 6-year (1998-2003) rainfall products from the Tropical Rainfall Measuring Mission (TRMM) are used to quantify the Intertropical Convergence Zone (ITCZ) in the eastern Pacific (defined by longitudinal averages over 90 degrees W-130 degrees W) during boreal spring (March-April). The double ITCZ phenomenon, represented by the occurrence of two maxima with respect to latitude in monthly mean rainfall, is observed in most but not all of the years studied. The relative spatial locations of maxima in sea surface temperature (SST), rainfall, and surface pressure are examined. Interannual and weekly variability are characterized in SST, rainfall, surface convergence, total column water vapor, and cloud water. There appears to be a competition for rainfall between the two hemispheres during this season. When one of the two rainfall maxima is particularly strong, the other tends to be weak, with the total rainfall integrated over the two varying less than does the difference between the rainfall integrated over each separately. There is some evidence for a similar competition between the SST maxima in the two hemispheres, but this is more ambiguous, and there is evidence that some variations in the relative strengths of the two rainfall maxima may be independent of SST. Using a 25-year (1979-2003) monthly rainfall dataset from the Global Precipitation Climatology Project (GPCP), four distinct ITCZ types during March-April are defined, based on the relative strengths of rainfall peaks north and south of, and right over the equator. Composite meridional profiles and spatial distributions of rainfall and SST are documented for each type. Consistent with previous studies, an equatorial cold tongue is essential to the existence of the double ITCZs. However, too strong a cold tongue may dampen either the southern or northern rainfall maximum, depending on the magnitude of SST north of the equator.

Pests vs. drought as determinants of plant distribution along a tropical rainfall gradient.

PubMed

Brenes-Arguedas, Tania; Coley, Phyllis D; Kursar, Thomas A

2009-07-01

Understanding the mechanisms that shape the distribution of organisms can help explain patterns of local and regional biodiversity and predict the susceptibility of communities to environmental change. In the species-rich tropics, a gradient in rainfall between wet evergreen and dry seasonal forests correlates with turnover of plant species. The strength of the dry season has previously been shown to correlate with species composition. Herbivores and pathogens (pests) have also been hypothesized to be important drivers of plant distribution, although empirical evidence is lacking. In this study we experimentally tested the existence of a gradient in pest pressure across a rainfall gradient in the Isthmus of Panama and measured the influence of pests relative to drought on species turnover. We established two common gardens on the dry and wet sides of the Isthmus using seedlings from 24 plant species with contrasting distributions along the Isthmus. By experimentally manipulating water availability and insect herbivore access, we showed that pests are not as strong a determinant of plant distributions as is seasonal drought. Seasonal drought in the dry site excluded wet-distribution species by significantly increasing their seedling mortality. Pathogen mortality and insect herbivore damage were both higher in the wet site, supporting the existence of a gradient in pest pressure. However, contrary to predictions, we found little evidence that dry-distribution species suffered significantly more pest attack than wet-distribution species. Instead, we hypothesize that dry-distribution species are limited from colonizing wetter forests by their inherently slower growth rates imposed by drought adaptations. We conclude that mechanisms limiting the recruitment of dry-distribution species in wet forests are not nearly as strong as those limiting wet-distribution species from dry forests.

Probability density functions for use when calculating standardised drought indices

NASA Astrophysics Data System (ADS)

Svensson, Cecilia; Prosdocimi, Ilaria; Hannaford, Jamie

2015-04-01

Time series of drought indices like the standardised precipitation index (SPI) and standardised flow index (SFI) require a statistical probability density function to be fitted to the observed (generally monthly) precipitation and river flow data. Once fitted, the quantiles are transformed to a Normal distribution with mean = 0 and standard deviation = 1. These transformed data are the SPI/SFI, which are widely used in drought studies, including for drought monitoring and early warning applications. Different distributions were fitted to rainfall and river flow data accumulated over 1, 3, 6 and 12 months for 121 catchments in the United Kingdom. These catchments represent a range of catchment characteristics in a mid-latitude climate. Both rainfall and river flow data have a lower bound at 0, as rains and flows cannot be negative. Their empirical distributions also tend to have positive skewness, and therefore the Gamma distribution has often been a natural and suitable choice for describing the data statistically. However, after transformation of the data to Normal distributions to obtain the SPIs and SFIs for the 121 catchments, the distributions are rejected in 11% and 19% of cases, respectively, by the Shapiro-Wilk test. Three-parameter distributions traditionally used in hydrological applications, such as the Pearson type 3 for rainfall and the Generalised Logistic and Generalised Extreme Value distributions for river flow, tend to make the transformed data fit better, with rejection rates of 5% or less. However, none of these three-parameter distributions have a lower bound at zero. This means that the lower tail of the fitted distribution may potentially go below zero, which would result in a lower limit to the calculated SPI and SFI values (as observations can never reach into this lower tail of the theoretical distribution). The Tweedie distribution can overcome the problems found when using either the Gamma or the above three-parameter distributions. The Tweedie is a three-parameter distribution which includes the Gamma distribution as a special case. It is bounded below at zero and has enough flexibility to fit most behaviours observed in the data. It does not always outperform the three-parameter distributions, but the rejection rates are similar. In addition, for certain parameter values the Tweedie distribution has a positive mass at zero, which means that ephemeral streams and months with zero rainfall can be modelled. It holds potential for wider application in drought studies in other climates and types of catchment.

Predicting rainfall erosivity by momentum and kinetic energy in Mediterranean environment

NASA Astrophysics Data System (ADS)

Carollo, Francesco G.; Ferro, Vito; Serio, Maria A.

2018-05-01

Rainfall erosivity is an index that describes the power of rainfall to cause soil erosion and it is used around the world for assessing and predicting soil loss on agricultural lands. Erosivity can be represented in terms of both rainfall momentum and kinetic energy, both calculated per unit time and area. Contrasting results on the representativeness of these two variables are available: some authors stated that momentum and kinetic energy are practically interchangeable in soil loss estimation while other found that kinetic energy is the most suitable expression of rainfall erosivity. The direct and continuous measurements of momentum and kinetic energy by a disdrometer allow also to establish a relationship with rainfall intensity at the study site. At first in this paper a comparison between the momentum-rainfall intensity relationships measured at Palermo and El Teularet by an optical disdrometer is presented. For a fixed rainfall intensity the measurements showed that the rainfall momentum values measured at the two experimental sites are not coincident. However both datasets presented a threshold value of rainfall intensity over which the rainfall momentum assumes a quasi-constant value. Then the reliability of a theoretically deduced relationship, linking momentum, rainfall intensity and median volume diameter, is positively verified using measured raindrop size distributions. An analysis to assess which variable, momentum or kinetic energy per unit area and time, is the best predictor of erosivity in Italy and Spain was also carried out. This investigation highlighted that the rainfall kinetic energy per unit area and time can be substituted by rainfall momentum as index for estimating the rainfall erosivity, and this result does not depend on the site where precipitation occurs. Finally, rainfall intensity measurements and soil loss data collected from the bare plots equipped at Sparacia experimental area were used to verify the reliability of some rainfall erosivity indices and their ability to distinguish the type of involved soil erosion processes.

Detecting surface runoff location in a small catchment using distributed and simple observation method

NASA Astrophysics Data System (ADS)

Dehotin, Judicaël; Breil, Pascal; Braud, Isabelle; de Lavenne, Alban; Lagouy, Mickaël; Sarrazin, Benoît

2015-06-01

Surface runoff is one of the hydrological processes involved in floods, pollution transfer, soil erosion and mudslide. Many models allow the simulation and the mapping of surface runoff and erosion hazards. Field observations of this hydrological process are not common although they are crucial to evaluate surface runoff models and to investigate or assess different kinds of hazards linked to this process. In this study, a simple field monitoring network is implemented to assess the relevance of a surface runoff susceptibility mapping method. The network is based on spatially distributed observations (nine different locations in the catchment) of soil water content and rainfall events. These data are analyzed to determine if surface runoff occurs. Two surface runoff mechanisms are considered: surface runoff by saturation of the soil surface horizon and surface runoff by infiltration excess (also called hortonian runoff). The monitoring strategy includes continuous records of soil surface water content and rainfall with a 5 min time step. Soil infiltration capacity time series are calculated using field soil water content and in situ measurements of soil hydraulic conductivity. Comparison of soil infiltration capacity and rainfall intensity time series allows detecting the occurrence of surface runoff by infiltration-excess. Comparison of surface soil water content with saturated water content values allows detecting the occurrence of surface runoff by saturation of the soil surface horizon. Automatic records were complemented with direct field observations of surface runoff in the experimental catchment after each significant rainfall event. The presented observation method allows the identification of fast and short-lived surface runoff processes at a small spatial and temporal resolution in natural conditions. The results also highlight the relationship between surface runoff and factors usually integrated in surface runoff mapping such as topography, rainfall parameters, soil or land cover. This study opens interesting prospects for the use of spatially distributed measurement for surface runoff detection, spatially distributed hydrological models implementation and validation at a reasonable cost.

Evaluation and correction of uncertainty due to Gaussian approximation in radar - rain gauge merging using kriging with external drift

NASA Astrophysics Data System (ADS)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2016-12-01

It is widely recognised that merging radar rainfall estimates (RRE) with rain gauge data can improve the RRE and provide areal and temporal coverage that rain gauges cannot offer. Many methods to merge radar and rain gauge data are based on kriging and require an assumption of Gaussianity on the variable of interest. In particular, this work looks at kriging with external drift (KED), because it is an efficient, widely used, and well performing merging method. Rainfall, especially at finer temporal scale, does not have a normal distribution and presents a bi-modal skewed distribution. In some applications a Gaussianity assumption is made, without any correction. In other cases, variables are transformed in order to obtain a distribution closer to Gaussian. This work has two objectives: 1) compare different transformation methods in merging applications; 2) evaluate the uncertainty arising when untransformed rainfall data is used in KED. The comparison of transformation methods is addressed under two points of view. On the one hand, the ability to reproduce the original probability distribution after back-transformation of merged products is evaluated with qq-plots, on the other hand the rainfall estimates are compared with an independent set of rain gauge measurements. The tested methods are 1) no transformation, 2) Box-Cox transformations with parameter equal to λ=0.5 (square root), 3) λ=0.25 (square root - square root), and 4) λ=0.1 (almost logarithmic), 5) normal quantile transformation, and 6) singularity analysis. The uncertainty associated with the use of non-transformed data in KED is evaluated in comparison with the best performing product. The methods are tested on a case study in Northern England, using hourly data from 211 tipping bucket rain gauges from the Environment Agency and radar rainfall data at 1 km/5-min resolutions from the UK Met Office. In addition, 25 independent rain gauges from the UK Met Office were used to assess the merged products.

A new hydrological model for estimating extreme floods in the Alps

NASA Astrophysics Data System (ADS)

Receanu, R. G.; Hertig, J.-A.; Fallot, J.-M.

2012-04-01

Protection against flooding is very important for a country like Switzerland with a varied topography and many rivers and lakes. Because of the potential danger caused by extreme precipitation, structural and functional safety of large dams must be guaranteed to withstand the passage of an extreme flood. We introduce a new distributed hydrological model to calculate the PMF from a PMP which is spatially and temporally distributed using clouds. This model has permitted the estimation of extreme floods based on the distributed PMP and the taking into account of the specifics of alpine catchments, in particular the small size of the basins, the complex topography, the large lakes, snowmelt and glaciers. This is an important evolution compared to other models described in the literature, as they mainly use a uniform distribution of extreme precipitation all over the watershed. This paper presents the results of calculation with the developed rainfall-runoff model, taking into account measured rainfall and comparing results to observed flood events. This model includes three parts: surface runoff, underground flow and melting snow. Two Swiss watersheds are studied, for which rainfall data and flow rates are available for a considerably long period, including several episodes of heavy rainfall with high flow events. From these events, several simulations are performed to estimate the input model parameters such as soil roughness and average width of rivers in case of surface runoff. Following the same procedure, the parameters used in the underground flow simulation are also estimated indirectly, since direct underground flow and exfiltration measurements are difficult to obtain. A sensitivity analysis of the parameters is performed at the first step to define more precisely the boundary and initial conditions. The results for the two alpine basins, validated with the Nash equation, show a good correlation between the simulated and observed flows. This good correlation shows that the model is valid and gives us the confidence that the results can be extrapolated to phenomena of extreme rainfall of PMP type.

A single scaling parameter as a first approximation to describe the rainfall pattern of a place: application on Catalonia

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Llabrés-Brustenga, Alba; Rius, Anna; Rodríguez-Solà, Raúl; Navarro, Xavier

2018-02-01

As well as in other natural processes, it has been frequently observed that the phenomenon arising from the rainfall generation process presents fractal self-similarity of statistical type, and thus, rainfall series generally show scaling properties. Based on this fact, there is a methodology, simple scaling, which is used quite broadly to find or reproduce the intensity-duration-frequency curves of a place. In the present work, the relationship of the simple scaling parameter with the characteristic rainfall pattern of the area of study has been investigated. The calculation of this scaling parameter has been performed from 147 daily rainfall selected series covering the temporal period between 1883 and 2016 over the Catalonian territory (Spain) and its nearby surroundings, and a discussion about the relationship between the scaling parameter spatial distribution and rainfall pattern, as well as about trends of this scaling parameter over the past decades possibly due to climate change, has been presented.

Rainfall estimation using microwave links. Results from an experimental setup in Luxembourg

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Matgen, Patrick; Pfister, Laurent

2010-05-01

Microwave links represent a valid alternative to traditional rainfall estimation methods. They are commonly used in mobile phone communication, and they constitute built-in widely distributed networks. Due to their ability of providing high temporal and spatial resolution measurements, their use is particularly suitable in urban settings. We here show results from an experimental setup in Luxembourg City, where two dual frequency links have been installed. The links cover a distance of about 4km, and measure power attenuation at 1 min. timestep. The links have been equipped with several recording raingauges, which measure rainfall in real-time communicating through a wireless connection. This set-up has been used to analyze in detail the mapping between attenuation and rainfall intensity, and gain insights into the potential accuracy of these instruments. In addition, we investigated the relation between rainfall and discharge response of the urban area of Luxembourg, which shows the potential utility of high frequency rainfall measurements for urban environments.

Analysis of water-level fluctuations of Lakes Winona and Winnemissett-- two landlocked lakes in a karst terrane in Volusia County, Florida

USGS Publications Warehouse

Hughes, G.H.

1979-01-01

The water levels of Lakes Winona and Winnemissett in Volusia County, Fla., correlate reasonably well during dry spells but only poorly during wet spells. Disparities develop mostly at times when the lake levels rise abruptly owing to rainstorms passing over the lake basins. The lack of correlation is attributed to the uneven distribution of the storm rainfall, even though the average annual rainfall at National Weather Service gages in the general area of the lakes is about the same. Analyses of the monthly rainfall data show that the rainfall variability between gages is sufficient to account for most of the disparity between monthly changes in the levels of the two lakes. The total annual rainfall at times may differ between rainfall gages by as much as 15 to 20 inches. Such differences tend to balance over the long term but may persist in the same direction for two or more years, causing apparent anomalies in lake-level fluctuations. (Woodard-USGS)

Analysis of water-level fluctuations of the US Highway 90 retention pond, Madison, Florida

USGS Publications Warehouse

Bridges, W.C.

1985-01-01

A closed basin stormwater retention pond, located 1 mile west of Madison, Florida, has a maximum storage capacity of 134.1 acre-feet at the overtopping altitude of 100.2 feet. The maximum observed altitude (July 1982 to March 1984) was 99.52 feet (126.7 acre-feet) on March 28, 1984. This report provides a technique for simulating net monthly change-in-altitude in response to rainfall and evaporation. A regression equation was developed which relates net monthly change in altitude (dependent variable) to rainfall and evaporation (independent variables). Rainfall frequency curves were developed using a log-Pearson Type III distribution of the annual, January through April, June through August, and July monthly rainfall totals for the years 1908-72, 1974, 1976-82. The altitude of the retention pond increased almost 7 feet during the 4-month period January through April 1983. The rainfall total was 35.1 inches, and the recurrence interval exceeded the 100-year January-April rainfall. (USGS)

Rain Check Application: Mobile tool to monitor rainfall in remote parts of Haiti

NASA Astrophysics Data System (ADS)

Huang, X.; Baird, J.; Chiu, M. T.; Morelli, R.; de Lanerolle, T. R.; Gourley, J. R.

2011-12-01

Rainfall observations performed uniformly and continuously over a period of time are valuable inputs in developing climate models and predicting events such as floods and droughts. Rain-Check is a mobile application developed in Google App Inventor Platform, for android based smart phones, to allow field researchers to monitor various rain gauges distributed though out remote regions of Haiti and send daily readings via SMS messages for further analysis and long term trending. Rainfall rate and quantity interact with many other factors to influence erosion, vegetative cover, groundwater recharge, stream water chemistry and runoff into streams impacting agriculture and livestock. Rainfall observation from various sites is especially significant in Haiti with over 80% of the country is mountainous terrain. Data sets from global models and limited number of ground stations do not capture the fine-scale rainfall patterns necessary to describe local climate. Placement and reading of rain gauges are critical to accurate measurement of rainfall.

The Use of Radar to Improve Rainfall Estimation over the Tennessee and San Joaquin River Valleys

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Gatlin, Patrick N.; Felix, Mariana; Carey, Lawrence D.

2010-01-01

This slide presentation provides an overview of the collaborative radar rainfall project between the Tennessee Valley Authority (TVA), the Von Braun Center for Science & Innovation (VCSI), NASA MSFC and UAHuntsville. Two systems were used in this project, Advanced Radar for Meteorological & Operational Research (ARMOR) Rainfall Estimation Processing System (AREPS), a demonstration project of real-time radar rainfall using a research radar and NEXRAD Rainfall Estimation Processing System (NREPS). The objectives, methodology, some results and validation, operational experience and lessons learned are reviewed. The presentation. Another project that is using radar to improve rainfall estimations is in California, specifically the San Joaquin River Valley. This is part of a overall project to develop a integrated tool to assist water management within the San Joaquin River Valley. This involves integrating several components: (1) Radar precipitation estimates, (2) Distributed hydro model, (3) Snowfall measurements and Surface temperature / moisture measurements. NREPS was selected to provide precipitation component.

Evaluating the Effect of Rainfall Infiltration on the Slope Stability of T16 tower of Taipei Mao-kong Gondola by Numerical Methods

NASA Astrophysics Data System (ADS)

RUNG, J.

2013-12-01

In this study, a series of rainfall-stability analyses were performed to simulate the failure mechanism and the function of remediation works of the down slope of T-16 tower pier, Mao-Kong gondola (or T-16 Slope) at the hillside of Taipei City using two-dimensional finite element method. The failure mechanism of T-16 Slope was simulated using the rainfall hyetograph of Jang-Mi typhoon in 2008 based on the field investigation data, monitoring data, soil/rock mechanical testing data and detail design plots of remediation works. Eventually, the numerical procedures and various input parameters in the analysis were verified by comparing the numerical results with the field observations. In addition, 48 hrs design rainfalls corresponding to 5, 10, 25 and 50 years return periods were prepared using the 20 years rainfall data of Mu-Zha rainfall observation station, Central Weather Bureau for the rainfall-stability analyses of T-16 Slope to inspect the effect of the compound stabilization works on the overall stability of the slope. At T-16 Slope, without considering the longitudinal and transverse drainages on the ground surface, there totally 4 types of stabilization works were installed to stabilize the slope. From the slope top to the slope toe, the stabilization works of T-16 Slope consists of RC-retaining wall with micro-pile foundation at the up-segment, earth anchor at the up-middle-segment, soil nailing at the middle-segment and retaining pile at the down-segment of the slope. The effect of each individual stabilization work on the slope stability under rainfall condition was examined and evaluated by raising field groundwater level.

Seasonal cycles, phylogenetic assembly, and functional diversity of orchid bee communities.

PubMed

Ramírez, Santiago R; Hernández, Carlos; Link, Andres; López-Uribe, Margarita M

2015-05-01

Neotropical rainforests sustain some of the most diverse terrestrial communities on Earth. Euglossine (or orchid) bees are a diverse lineage of insect pollinators distributed throughout the American tropics, where they provide pollination services to a staggering diversity of flowering plant taxa. Elucidating the seasonal patterns of phylogenetic assembly and functional trait diversity of bee communities can shed new light into the mechanisms that govern the assembly of bee pollinator communities and the potential effects of declining bee populations. Male euglossine bees collect, store, and accumulate odoriferous compounds (perfumes) to subsequently use during courtship display. Thus, synthetic chemical baits can be used to attract and monitor euglossine bee populations. We conducted monthly censuses of orchid bees in three sites in the Magdalena valley of Colombia - a region where Central and South American biotas converge - to investigate the structure, diversity, and assembly of euglossine bee communities through time in relation to seasonal climatic cycles. In particular, we tested the hypothesis that phylogenetic community structure and functional trait diversity changed in response to seasonal rainfall fluctuations. All communities exhibited strong to moderate phylogenetic clustering throughout the year, with few pronounced bursts of phylogenetic overdispersion that coincided with the transition from wet-to-dry seasons. Despite the heterogeneous distribution of functional traits (e.g., body size, body mass, and proboscis length) and the observed seasonal fluctuations in phylogenetic diversity, we found that functional trait diversity, evenness, and divergence remained constant during all seasons in all communities. However, similar to the pattern observed with phylogenetic diversity, functional trait richness fluctuated markedly with rainfall in all sites. These results emphasize the importance of considering seasonal fluctuations in community assembly and provide a glimpse to the potential effects that climatic alterations may have on both pollinator communities and the ecosystem services they provide.

High resolution modeling in urban hydrology: comparison between two modeling approaches and their sensitivity to high rainfall variability

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Bompard, Philippe; Schertzer, Daniel

2015-04-01

Urban water management is becoming increasingly complex, due to the rapid increase of impervious areas, and the potential effects of climate change. The large amount of water generated in a very short period of time and the limited capacity of sewer systems increase the vulnerability of urban environments to flooding risk and make it necessary to implement specific devices in order to handle the volume of water generated. This complex situation in urban environments makes the use of hydrological models as well as the implementation of more accurate and reliable tools for flow and rainfall measurements essential for a good pluvial network management, the use of decision support tools such as real-time radar forecasting system, the developpement of general public communication and warning systems, and the implementation of management strategy participate on limiting the flood damages. The very high spatial variability characteristic of urban environments makes it necessary to integrate the variability of physical properties and precipitation at fine scales in modeling processes, suggesting a high resolution modeling approach. In this paper we suggest a comparison between two modeling approaches and their sensitivity to small-scale rainfall variability on a 2.15 km2 urban area located in the County of Val-de-Marne (South-East of Paris, France). The first model used in this study is CANOE, which is a semi-distributed model widely used in France by practitioners for urban hydrology and urban water management. Two configurations of this model are be used in this study, the first one integrate 9 sub-catchments with sizes range from (1ha to 76ha), in the second configuration, the spatial resolution of this model has been improved with 45 sub-catchments with sizes range from (1ha to 14ha), the aim is to see how the semi-distributed model resolution affects it sensitivity to rainfall variability. The second model is Multi-Hydro fully distributed model developed at the Ecole des Ponts ParisTech. It is an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. Multi-Hydro has been set up at two resolutions, 10m and 5m. The validation of these two models is performed using 5 rainfall events that occurred between 2010 and 2013. Radar data comes from the Météo-France radar mosaic and the resolution is 1 km in space and 5 min in time. Raingauge and flow measurements data comes from the General Council of Val-de-Marne County. In this validation part, the hydrological responses given by two models and the different configurations are compared to flow measurements. It appears that CANOE gives better results than Multi-Hydro model, especially when using raingauge data. For some events, we noticed that model responses given when using raingauge and radar data are different, suggesting a sign of sensitivity to the spatial variability of rainfall. 10 high-resolution rainfall events are used in the second part to study the sensitivity of each modeling approach to high rainfall variability. Radar data was available at four spatial resolutions (100, 200, 500 and 1000m) and two temporal resolutions (1min and 5min), for each event, two rainfall directions (parallel and perpendicular) are used, meaning that 16 hydrological responses are simulated for each event and the variability within it analyzed. First results suggest that the fully distributed model is more sensitive to high rainfall variability than the semi-distributed one, the increase of both hydrological model spatial resolution improves their sensitivity to rainfall variability. This study highlights some technical challenges facing the high-resolution modeling, especially the difficulty to obtain reliable input data at an acceptable resolution and also the high computation time noticed particularly for the semi-distributed model making it difficult to use it in real time. The authors greatly acknowledge partial financial support from the project RainGain (http://www.raingain.eu) of the EU Interreg program.

Impact of a Single Unusually Large Rainfall Event on the Level of Risk Used for Infrastructure Design

NASA Astrophysics Data System (ADS)

Dhakal, N.; Jain, S.

2013-12-01

Rare and unusually large events (such as hurricanes and floods) can create unusual and interesting trends in statistics. Generalized Extreme Value (GEV) distribution is usually used to statistically describe extreme rainfall events. A number of the recent studies have shown that the frequency of extreme rainfall events has increased over the last century and as a result, there has been change in parameters of GEV distribution with the time (non-stationary). But what impact does a single unusually large rainfall event (e.g., hurricane Irene) have on the GEV parameters and consequently on the level of risks or the return periods used in designing the civil infrastructures? In other words, if such a large event occurs today, how will it influence the level of risks (estimated based on past rainfall records) for the civil infrastructures? To answer these questions, we performed sensitivity analysis of the distribution parameters of GEV as well as the return periods to unusually large outlier events. The long-term precipitation records over the period of 1981-2010 from 12 USHCN stations across the state of Maine were used for analysis. For most of the stations, addition of each outlier event caused an increase in the shape parameter with a huge decrease on the corresponding return period. This is a key consideration for time-varying engineering design. These isolated extreme weather events should simultaneously be considered with traditional statistical methodology related to extreme events while designing civil infrastructures (such as dams, bridges, and culverts). Such analysis is also useful in understanding the statistical uncertainty of projecting extreme events into future.

Transport and solubility of Hetero-disperse dry deposition particulate matter subject to urban source area rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Ying, G.; Sansalone, J.

2010-03-01

SummaryWith respect to hydrologic processes, the impervious pavement interface significantly alters relationships between rainfall and runoff. Commensurate with alteration of hydrologic processes the pavement also facilitates transport and solubility of dry deposition particulate matter (PM) in runoff. This study examines dry depositional flux rates, granulometric modification by runoff transport, as well as generation of total dissolved solids (TDS), alkalinity and conductivity in source area runoff resulting from PM solubility. PM is collected from a paved source area transportation corridor (I-10) in Baton Rouge, Louisiana encompassing 17 dry deposition and 8 runoff events. The mass-based granulometric particle size distribution (PSD) is measured and modeled through a cumulative gamma function, while PM surface area distributions across the PSD follow a log-normal distribution. Dry deposition flux rates are modeled as separate first-order exponential functions of previous dry hours (PDH) for PM and suspended, settleable and sediment fractions. When trans-located from dry deposition into runoff, PSDs are modified, with a d50m decreasing from 331 to 14 μm after transport and 60 min of settling. Solubility experiments as a function of pH, contact time and particle size using source area rainfall generate constitutive models to reproduce pH, alkalinity, TDS and alkalinity for historical events. Equilibrium pH, alkalinity and TDS are strongly influenced by particle size and contact times. The constitutive leaching models are combined with measured PSDs from a series of rainfall-runoff events to demonstrate that the model results replicate alkalinity and TDS in runoff from the subject watershed. Results illustrate the granulometry of dry deposition PM, modification of PSDs along the drainage pathway, and the role of PM solubility for generation of TDS, alkalinity and conductivity in urban source area rainfall-runoff.

Framework for event-based semidistributed modeling that unifies the SCS-CN method, VIC, PDM, and TOPMODEL

NASA Astrophysics Data System (ADS)

Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.

2016-09-01

Hydrologists and engineers may choose from a range of semidistributed rainfall-runoff models such as VIC, PDM, and TOPMODEL, all of which predict runoff from a distribution of watershed properties. However, these models are not easily compared to event-based data and are missing ready-to-use analytical expressions that are analogous to the SCS-CN method. The SCS-CN method is an event-based model that describes the runoff response with a rainfall-runoff curve that is a function of the cumulative storm rainfall and antecedent wetness condition. Here we develop an event-based probabilistic storage framework and distill semidistributed models into analytical, event-based expressions for describing the rainfall-runoff response. The event-based versions called VICx, PDMx, and TOPMODELx also are extended with a spatial description of the runoff concept of "prethreshold" and "threshold-excess" runoff, which occur, respectively, before and after infiltration exceeds a storage capacity threshold. For total storm rainfall and antecedent wetness conditions, the resulting ready-to-use analytical expressions define the source areas (fraction of the watershed) that produce runoff by each mechanism. They also define the probability density function (PDF) representing the spatial variability of runoff depths that are cumulative values for the storm duration, and the average unit area runoff, which describes the so-called runoff curve. These new event-based semidistributed models and the traditional SCS-CN method are unified by the same general expression for the runoff curve. Since the general runoff curve may incorporate different model distributions, it may ease the way for relating such distributions to land use, climate, topography, ecology, geology, and other characteristics.

Realistic sampling of anisotropic correlogram parameters for conditional simulation of daily rainfields

NASA Astrophysics Data System (ADS)

Gyasi-Agyei, Yeboah

2018-01-01

This paper has established a link between the spatial structure of radar rainfall, which more robustly describes the spatial structure, and gauge rainfall for improved daily rainfield simulation conditioned on the limited gauged data for regions with or without radar records. A two-dimensional anisotropic exponential function that has parameters of major and minor axes lengths, and direction, is used to describe the correlogram (spatial structure) of daily rainfall in the Gaussian domain. The link is a copula-based joint distribution of the radar-derived correlogram parameters that uses the gauge-derived correlogram parameters and maximum daily temperature as covariates of the Box-Cox power exponential margins and Gumbel copula. While the gauge-derived, radar-derived and the copula-derived correlogram parameters reproduced the mean estimates similarly using leave-one-out cross-validation of ordinary kriging, the gauge-derived parameters yielded higher standard deviation (SD) of the Gaussian quantile which reflects uncertainty in over 90% of cases. However, the distribution of the SD generated by the radar-derived and the copula-derived parameters could not be distinguished. For the validation case, the percentage of cases of higher SD by the gauge-derived parameter sets decreased to 81.2% and 86.6% for the non-calibration and the calibration periods, respectively. It has been observed that 1% reduction in the Gaussian quantile SD can cause over 39% reduction in the SD of the median rainfall estimate, actual reduction being dependent on the distribution of rainfall of the day. Hence the main advantage of using the most correct radar correlogram parameters is to reduce the uncertainty associated with conditional simulations that rely on SD through kriging.

How is rainfall interception in urban area affected by meteorological parameters?

NASA Astrophysics Data System (ADS)

Zabret, Katarina; Rakovec, Jože; Mikoš, Matjaž; Šraj, Mojca

2017-04-01

Rainfall interception is part of the hydrological cycle. Precipitation, which hits vegetation, is retained on the leaves and branches, from which it eventually evaporates into the atmosphere (interception) or reaches the ground by dripping from the canopy, falling through the gaps (throughfall) and running down the stems (stemflow). The amount of rainfall reaching the ground depends on various meteorological and vegetation parameters. Rainfall, throughfall and stemflow have been measured in the city of Ljubljana, Slovenia since the beginning of 2014. Manual and automatic measurements are performed regularly under Betula pendula and Pinus nigra trees in urban area. In 2014, there were detected 178 rainfall events with total amount of 1672.1 mm. In average B. pendula intercepted 44% of rainfall and P. nigra intercepted 72% of rainfall. In 2015 we have detected 117 events with 1047.4 mm of rainfall, of which 37% was intercepted by B. pendula and 60% by P. nigra. The effect of various meteorological parameters on the rainfall interception was analysed in the study. The parameters included in the analysis were rainfall rate, rainfall duration, drop size distribution (average drop velocity and diameter), average wind speed, and average temperature. The results demonstrate decreasing rainfall interception with longer rainfall duration and higher rainfall intensity although the impact of the latter one is not statistically significant. In the case of very fast or very slow rainfall drops, the interception is higher than for the mean rain drop velocity values. In the case of P. nigra the impact of the rain drop diameter on interception is similar to the one of rain drop velocity while for B. pendula increasing of drop diameter also increases the interception. As expected, interception is higher for warmer events. This trend is more evident for P. nigra than for B. pendula. Furthermore, the amount of intercepted rainfall also increases with wind although it could be relatively high in case of very low wind speeds.

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2018-01-01

Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

USGS Publications Warehouse

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

1997-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an eleven year period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444 km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are converted to monthly rainfall amounts and then compared to those for non-tropical cyclone systems. The main results of this study indicate that: 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maxima in tropical cyclone rainfall are poleward (5 deg to 10 deg latitude depending on longitude) of the maxima in non-tropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% of the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the ITCZ; and 5) in general, tropical cyclone rainfall is enhanced during the El Nino years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites.

NASA Astrophysics Data System (ADS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

2000-10-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an 11-yr period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and interannual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important.To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444-km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain-rate observations are converted to monthly rainfall amounts and then compared with those for nontropical cyclone systems.The main results of this study indicate that 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maximum tropical cyclone rainfall is poleward (5°-10° latitude depending on longitude) of the maximum nontropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% off the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the Intertropical Convergence Zone; and 5) in general, tropical cyclone rainfall is enhanced during the El Niño years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

2005-01-01

Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

Effects of shifting seasonal rainfall patterns on net primary productivity and carbon storage in tropical seasonally dry ecosystems

NASA Astrophysics Data System (ADS)

Rohr, T.; Manzoni, S.; Feng, X.; Menezes, R.; Porporato, A. M.

2013-12-01

Although seasonally dry ecosystems (SDEs), identified by prolonged drought followed by a short, but intense, rainy season, cover large regions of the tropics, their biogeochemical response to seasonal rainfall and soil carbon (C) sequestration potential are not well characterized. Both productivity and soil respiration are positively affected by seasonal soil moisture availability, creating a delicate balance between C deposition through litterfall and C losses through heterotrophic respiration. As climate change projections for the tropics predict decreased annual rainfall and increased dry season length, it is critical to understand how variations in seasonal rainfall distributions control this balance. To address this question, we develop a minimal model linking the seasonal behavior of the ensemble soil moisture, plant productivity, the related soil C inputs through litterfall, and soil C dynamics. The model is parameterized for a case study from a drought-deciduous caatinga ecosystem in northeastern Brazil. Results indicate that when altering the seasonal rainfall patterns for a fixed annual rainfall, both plant productivity and soil C sequestration potential are largely, and nonlinearly, dependent on wet season duration. Moreover, total annual rainfall plays a dominant role in describing this relationship, leading at times to the emergence of distinct optima in both primary production and C sequestration. Examining these results in the context of climate-driven changes to wet season duration and mean annual precipitation indicate that the initial hydroclimatic regime of a particular ecosystem is an important factor to predict both the magnitude and direction of the effects of shifting seasonal distributions on productivity and C storage. Although highly productive ecosystems will likely experience declining C storage with predicted climate shifts, those currently operating well below peak production can potentially see improved C stocks with the onset of declining rainfall due to reduced soil respiration. a) Annual average net primary productivity and b) the temporally averaged ensemble soil carbon concentration <(C_yr )> are plotted against the length of the wet season T_W, for six annual rainfall rates (m yr-1).

Rainfall and crop modeling-based water stress assessment for rainfed maize cultivation in peninsular India

NASA Astrophysics Data System (ADS)

Manivasagam, V. S.; Nagarajan, R.

2018-04-01

Water stress due to uneven rainfall distribution causes a significant impact on the agricultural production of monsoon-dependent peninsular India. In the present study, water stress assessment for rainfed maize crop is carried out for kharif (June-October) and rabi (October-February) cropping seasons which coincide with two major Indian monsoons. Rainfall analysis (1976-2010) shows that the kharif season receives sufficient weekly rainfall (28 ± 32 mm) during 26th-39th standard meteorological weeks (SMWs) from southwest monsoon, whereas the rabi season experiences a major portion of its weekly rainfall due to northeast monsoon between the 42nd and 51st SMW (31 ± 42 mm). The later weeks experience minimal rainfall (5.5 ± 15 mm) and thus expose the late sown maize crops to a severe water stress during its maturity stage. Wet and dry spell analyses reveal a substantial increase in the rainfall intensity over the last few decades. However, the distribution of rainfall shows a striking decrease in the number of wet spells, with prolonged dry spells in both seasons. Weekly rainfall classification shows that the flowering and maturity stages of kharif maize (33rd-39th SMWs) can suffer around 30-40% of the total water stress. In the case of rabi maize, the analysis reveals that a shift in the sowing time from the existing 42nd SMW (16-22 October) to the 40th SMW (1-7 October) can avoid terminal water stress. Further, AquaCrop modeling results show that one or two minimal irrigations during the flowering and maturity stages (33rd-39th SMWs) of kharif maize positively avoid the mild water stress exposure. Similarly, rabi maize requires an additional two or three lifesaving irrigations during its flowering and maturity stages (48th-53rd SMWs) to improve productivity. Effective crop planning with appropriate sowing time, short duration crop, and high yielding drought-resistant varieties will allow for better utilization of the monsoon rain, thus reducing water stress with an increase in rainfed maize productivity.

Vertical Variability of Rain Drop Size Distribution from Micro Rain Radar Measurements during IFloodS

NASA Astrophysics Data System (ADS)

Adirosi, Elisa; Tokay, Ali; Roberto, Nicoletta; Gorgucci, Eugenio; Montopoli, Mario; Baldini, Luca

2017-04-01

Ground based weather radars are highly used to generate rainfall products for meteorological and hydrological applications. However, weather radar quantitative rainfall estimation is obtained at a certain altitude that depends mainly on the radar elevation angle and on the distance from the radar. Therefore, depending on the vertical variability of rainfall, a time-height ambiguity between radar measurement and rainfall at the ground can affect the rainfall products. The vertically pointing radars (such as the Micro Rain Radar, MRR) are great tool to investigate the vertical variability of rainfall and its characteristics and ultimately, to fill the gap between the ground level and the first available radar elevation. Furthermore, the knowledge of rain Drop Size Distribution (DSD) variability is linked to the well-known problem of the non-uniform beam filling that is one of the main uncertainties of Global Precipitation Measurement (GPM) mission Dual frequency Precipitation Radar (DPR). During GPM Ground Validation Iowa Flood Studies (IFloodS) field experiment, data collected with 2D video disdrometers (2DVD), Autonomous OTT Parsivel2 Units (APU), and MRR profilers at different sites were available. In three different sites co-located APU, 2DVD and MRR are available and covered by the S-band Dual Polarimetric Doppler radar (NPOL). The first elevation height of the radar beam varies, among the three sites, between 70 m and 1100 m. The IFloodS set-up has been used to compare disdrometers, MRR and NPOL data and to evaluate the uncertainties of those measurements. First, the performance of disdrometers and MRR in determining different rainfall parameters at ground has been evaluated and then the MRR based parameters have been compared with the ones obtained from NPOL data at the lowest elevations. Furthermore, the vertical variability of DSD and integral rainfall parameters within the MRR bins (from ground to 1085 m each 35 m) has been investigated in order to provide some insight on the variability of the rainfall microphysical characteristics within about 1 km above the ground.

Effects of soil type and rainfall intensity on sheet erosion processes and sediment characteristics along the climatic gradient in central-south China.

PubMed

Wu, Xinliang; Wei, Yujie; Wang, Junguang; Xia, Jinwen; Cai, Chongfa; Wei, Zhiyuan

2018-04-15

Soil erosion poses a major threat to the sustainability of natural ecosystems. The main objective of this study was to investigate the effects of soil type and rainfall intensity on sheet erosion processes (hydrological, erosional processes and sediment characteristics) from temperate to tropical climate. Field plot experiments were conducted under pre-wetted bare fallow condition for five soil types (two Luvisols, an Alisol, an Acrisol and a Ferralsol) with heavy textures (silty clay loam, silty clay and clay) derived separately from loess deposits, quaternary red clays and basalt in central-south China. Rainfall simulations were performed at two rainfall intensities (45 and 90mmh -1 ) and lasted one hour after runoff generation. Runoff coefficient, sediment concentration, sediment yield rate and sediment effective size distribution were determined at 3-min intervals. Runoff temporal variations were similar at the high rainfall intensity, but exhibited a remarkable difference at the low rainfall intensity among soil types except for tropical Ferralsol. Illite was positively correlated with runoff coefficient (p<0.05). Rainfall intensity significantly contributed to the erosional process (p<0.001). Sediment concentration and yield rate were the smallest for the tropical Ferralsol and sediment concentration was the largest for the temperate Luvisol. The regimes (transport and detachment) limiting erosion varied under the interaction of rainfall characteristics (intensity and duration) and soil types, with amorphous iron oxides and bulk density jointly enhancing soil resistance to erosive forces (Adj-R 2 >88%, p<0.001). Sediment size was dominated by <0.1mm size fraction for the Luvisols and bimodally distributed with the peaks at <0.1mm and 1-0.5mm size for the other soil types. Exchangeable sodium decreased sediment size while rainfall intensity and clay content increased it (Adj-R 2 =96%, p<0.01). These results allow to better understand the climate effect on erosion processes at the spatial-temporal scale from the perspective of soil properties. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-model trends in East African rainfall associated with increased CO2

NASA Astrophysics Data System (ADS)

McHugh, Maurice J.

2005-01-01

Nineteen coupled ocean-atmosphere general circulation models participating in the Coupled Model Intercomparison Program (CMIP) were used to analyze future rainfall conditions over East Africa under enhanced CO2 conditions. 80 year control runs of these models indicated that four models produced mean annual rainfall distributions closely resembling climatological means and all four models had normalized root mean square errors well within the bounds of observed variability. East African (10°N-20°S, 25°-50°E) rainfall data from transient 80 year experiments which featured CO2 increases of 1% per year were compared with 80 year control simulations. Results indicate enhanced annual and seasonal rainfall rates, and increased extreme wet period frequency. These results indicate that East Africa may face a future in which mosquito-borne diseases such as malaria and Rift Valley fever proliferate resulting from increased CO2.

Geographic Information System and Remote Sensing Approach with Hydrologic Rational Model for Flood Event Analysis in Jakarta

NASA Astrophysics Data System (ADS)

Aditya, M. R.; Hernina, R.; Rokhmatuloh

2017-12-01

Rapid development in Jakarta which generates more impervious surface has reduced the amount of rainfall infiltration into soil layer and increases run-off. In some events, continuous high rainfall intensity could create sudden flood in Jakarta City. This article used rainfall data of Jakarta during 10 February 2015 to compute rainfall intensity and then interpolate it with ordinary kriging technique. Spatial distribution of rainfall intensity then overlaid with run-off coefficient based on certain land use type of the study area. Peak run-off within each cell resulted from hydrologic rational model then summed for the whole study area to generate total peak run-off. For this study area, land use types consisted of 51.9 % industrial, 37.57% parks, and 10.54% residential with estimated total peak run-off 6.04 m3/sec, 0.39 m3/sec, and 0.31 m3/sec, respectively.

Predictive susceptibility analysis of typhoon induced landslides in Central Taiwan

NASA Astrophysics Data System (ADS)

Shou, Keh-Jian; Lin, Zora

2017-04-01

Climate change caused by global warming affects Taiwan significantly for the past decade. The increasing frequency of extreme rainfall events, in which concentrated and intensive rainfalls generally cause geohazards including landslides and debris flows. The extraordinary, such as 2004 Mindulle and 2009 Morakot, hit Taiwan and induced serious flooding and landslides. This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the adopted Wu River watershed in Central Taiwan. To assess the spatial hazard of the landslides, landslide susceptibility analysis was also applied. Different types of rainfall factors were tested in the susceptibility models for a better accuracy. In addition, the routes of typhoons were also considered in the predictive analysis. The results of predictive analysis can be applied for risk prevention and management in the study area.

Modification of a rainfall-runoff model for distributed modeling in a GIS and its validation

NASA Astrophysics Data System (ADS)

Nyabeze, W. R.

A rainfall-runoff model, which can be inter-faced with a Geographical Information System (GIS) to integrate definition, measurement, calculating parameter values for spatial features, presents considerable advantages. The modification of the GWBasic Wits Rainfall-Runoff Erosion Model (GWBRafler) to enable parameter value estimation in a GIS (GISRafler) is presented in this paper. Algorithms are applied to estimate parameter values reducing the number of input parameters and the effort to populate them. The use of a GIS makes the relationship between parameter estimates and cover characteristics more evident. This paper has been produced as part of research to generalize the GWBRafler on a spatially distributed basis. Modular data structures are assumed and parameter values are weighted relative to the module area and centroid properties. Modifications to the GWBRafler enable better estimation of low flows, which are typical in drought conditions.

Sensitivity of effective rainfall amount to land use description using GIS tool. Case of a small mediterranean catchment

NASA Astrophysics Data System (ADS)

Payraudeau, S.; Tournoud, M. G.; Cernesson, F.

Distributed modelling in hydrology assess catchment subdivision to take into account physic characteristics. In this paper, we test the effect of land use aggregation scheme on catchment hydrological response. Evolution of intra-subcatchment land use is studied using statistic and entropy methods. The SCS-CN method is used to calculate effective rainfall which is here assimilated to hydrological response. Our purpose is to determine the existence of a critical threshold-area appropriate for the application of hydrological modelling. Land use aggregation effects on effective rainfall is assessed on small mediterranean catchment. The results show that land use aggregation and land use classification type have significant effects on hydrological modelling and in particular on effective rainfall modelling.

A Canonical Response in Rainfall Characteristics to Global Warming: Projections by IPCC CMIP5 Models

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, H. T.; Kim, K. M.

2012-01-01

Changes in rainfall characteristics induced by global warming are examined based on probability distribution function (PDF) analysis, from outputs of 14 IPCC (Intergovernmental Panel on Climate Change), CMIP (5th Coupled Model Intercomparison Project) models under various scenarios of increased CO2 emissions. Results show that collectively CMIP5 models project a robust and consistent global and regional rainfall response to CO2 warming. Globally, the models show a 1-3% increase in rainfall per degree rise in temperature, with a canonical response featuring large increase (100-250 %) in frequency of occurrence of very heavy rain, a reduction (5-10%) of moderate rain, and an increase (10-15%) of light rain events. Regionally, even though details vary among models, a majority of the models (>10 out of 14) project a consistent large scale response with more heavy rain events in climatologically wet regions, most pronounced in the Pacific ITCZ and the Asian monsoon. Moderate rain events are found to decrease over extensive regions of the subtropical and extratropical oceans, but increases over the extratropical land regions, and the Southern Oceans. The spatial distribution of light rain resembles that of moderate rain, but mostly with opposite polarity. The majority of the models also show increase in the number of dry events (absence or only trace amount of rain) over subtropical and tropical land regions in both hemispheres. These results suggest that rainfall characteristics are changing and that increased extreme rainfall events and droughts occurrences are connected, as a consequent of a global adjustment of the large scale circulation to global warming.

Using molecular-scale tracers to investigate transport of agricultural pollutants in soil and water

NASA Astrophysics Data System (ADS)

Lloyd, C.; Michaelides, K.; Chadwick, D.; Dungait, J.; Evershed, R. P.

2012-12-01

We explore the use of molecular-scale tracers to investigate the transport of potential pollutants due to the application of slurry to soil. The molecular-scale approach allows us to separate the pollutants which are moved to water bodies through sediment-bound and dissolved transport pathways. Slurry is applied to agricultural land to as a soil-improver across a wide-range of topographic and climatic regimes, hence a set of experiments were designed to assess the effect of changing slope gradient and rainfall intensity on the transport of pollutants. The experiments were carried out using University of Bristol's TRACE (Test Rig for Advancing Connectivity Experiments) facility. The facility includes a dual axis soil slope (6 x 2.5 x 0.3 m3) and 6-nozzle rainfall simulator, which enables the manipulation of the slope to simulate different slope gradient and rainfall scenarios. Cattle slurry was applied to the top 1 metre strip of the experimental soil slope followed by four rainfall simulations, where the gradient (5° & 10°) and the rainfall intensity (60 & 120 mm hr-1) were co-varied. Leachate was sampled from different flow pathways (surface, subsurface and percolated) via multiple outlets on the slope throughout the experiments and soil cores were taken from the slope after each experiment. Novel tracers were used to trace the pollutants in both dissolved and sediment-bound forms. Fluorescence spectroscopy was used to trace dissolved slurry-derived material via water flow pathways, as the slurry was found to have a distinct signature compared with the soil. The fluorescence signatures of the leachates were compared with those of many organic compounds in order to characterise the origin of the signal. This allowed the assessment of the longevity of the signal in the environment to establish if it could be used as a robust long-term tracer of slurry material in water or if would be subject to transform processes through time. 5-βstanols, organic compounds unique to ruminant faeces, were used to trace the transport of sediment-bound pollutants from the slurry which could be transported into water bodies via erosion processes. The results showed that contributions of potential pollutants from the surface and subsurface flow pathways and from the eroded sediment differ according to slope gradient and rainfall intensity. Therefore, as the contribution of each of these pathways changes in response to rainfall and slope gradient, the pollution risk also changes accordingly, as different organic compounds are mobilised at varying rates. Rapid hydrological response to rainfall results in erosion and surface transport of sediment-bound and dissolved pollutants, creating an immediate contamination threat. However, conditions resulting in a slower hydrological response and the predominance of flow percolation over surface runoff results in higher rates of dissolved pollutant transport through the soil layers which risks contamination of subsurface and deeper ground-water systems. These experiments provide insight into the pathways and timing of contaminant transport with potential implications for understanding contamination risk from the transfer of slurry from land to water bodies. Understanding this threat is critical at a time when pressure is on to develop land-management strategies to reduce pollution alongside maintaining food security.

Rainfall changes affect the algae dominance in tank bromeliad ecosystems.

PubMed

Pires, Aliny Patricia Flauzino; Leal, Juliana da Silva; Peeters, Edwin T H M

2017-01-01

Climate change and biodiversity loss have been reported as major disturbances in the biosphere which can trigger changes in the structure and functioning of natural ecosystems. Nonetheless, empirical studies demonstrating how both factors interact to affect shifts in aquatic ecosystems are still unexplored. Here, we experimentally test how changes in rainfall distribution and litter diversity affect the occurrence of the algae-dominated condition in tank bromeliad ecosystems. Tank bromeliads are miniature aquatic ecosystems shaped by the rainwater and allochthonous detritus accumulated in the bases of their leaves. Here, we demonstrated that changes in the rainfall distribution were able to reduce the chlorophyll-a concentration in the water of bromeliad tanks affecting significantly the occurrence of algae-dominated conditions. On the other hand, litter diversity did not affect the algae dominance irrespective to the rainfall scenario. We suggest that rainfall changes may compromise important self-reinforcing mechanisms responsible for maintaining high levels of algae on tank bromeliads ecosystems. We summarized these results into a theoretical model which suggests that tank bromeliads may show two different regimes, determined by the bromeliad ability in taking up nutrients from the water and by the total amount of light entering the tank. We concluded that predicted climate changes might promote regime shifts in tropical aquatic ecosystems by shaping their structure and the relative importance of other regulating factors.

Transient deterministic shallow landslide modeling: Requirements for susceptibility and hazard assessments in a GIS framework

USGS Publications Warehouse

Godt, J.W.; Baum, R.L.; Savage, W.Z.; Salciarini, D.; Schulz, W.H.; Harp, E.L.

2008-01-01

Application of transient deterministic shallow landslide models over broad regions for hazard and susceptibility assessments requires information on rainfall, topography and the distribution and properties of hillside materials. We survey techniques for generating the spatial and temporal input data for such models and present an example using a transient deterministic model that combines an analytic solution to assess the pore-pressure response to rainfall infiltration with an infinite-slope stability calculation. Pore-pressures and factors of safety are computed on a cell-by-cell basis and can be displayed or manipulated in a grid-based GIS. Input data are high-resolution (1.8??m) topographic information derived from LiDAR data and simple descriptions of initial pore-pressure distribution and boundary conditions for a study area north of Seattle, Washington. Rainfall information is taken from a previously defined empirical rainfall intensity-duration threshold and material strength and hydraulic properties were measured both in the field and laboratory. Results are tested by comparison with a shallow landslide inventory. Comparison of results with those from static infinite-slope stability analyses assuming fixed water-table heights shows that the spatial prediction of shallow landslide susceptibility is improved using the transient analyses; moreover, results can be depicted in terms of the rainfall intensity and duration known to trigger shallow landslides in the study area.

Tropical Rainfall Measuring Mission (TRMM). Phase B: Data capture facility definition study

NASA Technical Reports Server (NTRS)

1990-01-01

The National Aeronautics and Aerospace Administration (NASA) and the National Space Development Agency of Japan (NASDA) initiated the Tropical Rainfall Measuring Mission (TRMM) to obtain more accurate measurements of tropical rainfall then ever before. The measurements are to improve scientific understanding and knowledge of the mechanisms effecting the intra-annual and interannual variability of the Earth's climate. The TRMM is largely dependent upon the handling and processing of the data by the TRMM Ground System supporting the mission. The objective of the TRMM is to obtain three years of climatological determinations of rainfall in the tropics, culminating in data sets of 30-day average rainfall over 5-degree square areas, and associated estimates of vertical distribution of latent heat release. The scope of this study is limited to the functions performed by TRMM Data Capture Facility (TDCF). These functions include capturing the TRMM spacecraft return link data stream; processing the data in the real-time, quick-look, and routine production modes, as appropriate; and distributing real time, quick-look, and production data products to users. The following topics are addressed: (1) TRMM end-to-end system description; (2) TRMM mission operations concept; (3) baseline requirements; (4) assumptions related to mission requirements; (5) external interface; (6) TDCF architecture and design options; (7) critical issues and tradeoffs; and (8) recommendation for the final TDCF selection process.

A Comparison Study of Summer Season Raindrop Size Distribution Between Palau and Taiwan, Two Islands in Western Pacific

NASA Astrophysics Data System (ADS)

Seela, Balaji Kumar; Janapati, Jayalakshmi; Lin, Pay-Liam; Reddy, K. Krishna; Shirooka, Ryuichi; Wang, Pao K.

2017-11-01

Raindrop size distribution (RSD) characteristics in summer season rainfall of two observational sites (Taiwan (24°58'N, 121°10'E) and Palau (7°20'N, 134°28'E)) in western Pacific are studied by using five years of impact type disdrometer data. In addition to disdrometer data, Tropical Rainfall Measuring Mission, Moderate Resolution Imaging Spectroradiometer, and ERA-Interim data sets are used to illustrate the dynamical and microphysical characteristics associated with summer season rainfall of Taiwan and Palau. Taiwan and Palau's raindrop spectra showed a significant difference, with a higher concentration of middle and large drops in Taiwan than Palau rainfall. RSD stratified on the basis of rain rate showed a higher mass-weighted mean diameter (Dm) and a lower normalized intercept parameter (log10Nw) in Taiwan than Palau rainfall. Precipitation classification into stratiform and convective regimes showed higher Dm values in Taiwan than Palau. Furthermore, for both the locations, the convective precipitation has a higher Dm value than stratiform precipitation. The radar reflectivity-rain rate relations (Z = A*Rb) of Taiwan and Palau showed a clear variation in the coefficient and a less variation in exponent values. Terrain-influenced clouds extended to higher altitudes over Taiwan resulted with higher Dm and lower log10Nw values as compared to Palau.

Rainfall changes affect the algae dominance in tank bromeliad ecosystems

PubMed Central

Pires, Aliny Patricia Flauzino; Leal, Juliana da Silva; Peeters, Edwin T. H. M.

2017-01-01

Climate change and biodiversity loss have been reported as major disturbances in the biosphere which can trigger changes in the structure and functioning of natural ecosystems. Nonetheless, empirical studies demonstrating how both factors interact to affect shifts in aquatic ecosystems are still unexplored. Here, we experimentally test how changes in rainfall distribution and litter diversity affect the occurrence of the algae-dominated condition in tank bromeliad ecosystems. Tank bromeliads are miniature aquatic ecosystems shaped by the rainwater and allochthonous detritus accumulated in the bases of their leaves. Here, we demonstrated that changes in the rainfall distribution were able to reduce the chlorophyll-a concentration in the water of bromeliad tanks affecting significantly the occurrence of algae-dominated conditions. On the other hand, litter diversity did not affect the algae dominance irrespective to the rainfall scenario. We suggest that rainfall changes may compromise important self-reinforcing mechanisms responsible for maintaining high levels of algae on tank bromeliads ecosystems. We summarized these results into a theoretical model which suggests that tank bromeliads may show two different regimes, determined by the bromeliad ability in taking up nutrients from the water and by the total amount of light entering the tank. We concluded that predicted climate changes might promote regime shifts in tropical aquatic ecosystems by shaping their structure and the relative importance of other regulating factors. PMID:28422988

Carbon and nitrogen accumulation and fluxes on Landscape Evolution Observatory (LEO) slopes

NASA Astrophysics Data System (ADS)

Dontsova, K.; Volk, M.; Webb, C.; Hunt, E.; Tfaily, M. M.; Van Haren, J. L. M.; Sengupta, A.; Chorover, J.; Troch, P.; Ruiz, J.

2017-12-01

Carbon accumulation on the landscapes in organic and inorganic forms is an important sink of CO2 from the atmosphere. Formation and preservation of organic compounds is accompanied by N fixation from the atmosphere and cycling in the soil. Model slopes of Landscape Evolution Observatory present unique opportunity to examine carbon and nitrogen buildup on the landscapes during soil formation processes, such as weathering of primary minerals and microbial activity, due to low original levels of C and N, tight control over environmental conditions, and high spatial and temporal density of measurements. This presents results of inorganic and organic C and N measurements in the cores collected in LEO slopes after several years of exposure to the rainfall, as well as soil solution measurements collected through 496 samplers on each of three model slopes and in seepage. We observed significant spatially distributed accumulation of both C (organic and inorganic) and N in soil profiles. We also observed differences in the composition of organic compounds in the solid and solution phases depending on location on the slope indicating formation of heterogeneity as soils develop. This works indicates potential of physical models to help understand accumulation and fluxes of C and N on natural landscapes.

Multi-catchment rainfall-runoff simulation for extreme flood estimation

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel

2017-04-01

The SCHADEX method (Paquet et al., 2013) is a reference method in France for the estimation of extreme flood for dam design. The method is based on a semi-continuous rainfall-runoff simulation process: hundreds of different rainy events, randomly drawn up to extreme values, are simulated independently in the hydrological conditions of each day when a rainy event has been actually observed. This allows generating an exhaustive set of crossings between precipitation and soil saturation hazards, and to build a complete distribution of flood discharges up to extreme quantiles. The hydrological model used within SCHADEX, the MORDOR model (Garçon, 1996), is a lumped model, which implies that hydrological processes, e.g. rainfall and soil saturation, are supposed to be homogeneous throughout the catchment. Snow processes are nevertheless represented in relation with altitude. This hypothesis of homogeneity is questionable especially as the size of the catchment increases, or in areas of highly contrasted climatology (like mountainous areas). Conversely, modeling the catchment with a fully distributed approach would cause different problems, in particular distributing the rainfall-runoff model parameters trough space, and within the SCHADEX stochastic framework, generating extreme rain fields with credible spatio-temporal features. An intermediate solution is presented here. It provides a better representation of the hydro-climatic diversity of the studied catchment (especially regarding flood processes) while keeping the SCHADEX simulation framework. It consists in dividing the catchment in several, more homogeneous sub-catchments. Rainfall-runoff models are parameterized individually for each of them, using local discharge data if available. A first SCHADEX simulation is done at the global scale, which allows assigning a probability to each simulated event, mainly based on the global areal rainfall drawn for the event (see Paquet el al., 2013 for details). Then the rainfall of each event is distributed through the different sub-catchments using the spatial patterns calculated in the SPAZM precipitation reanalysis (Gottardi et al., 2012) for comparable situations of the 1948-2005 period. Corresponding runoffs are calculated with the hydrological models and aggregated to compute the discharge at the outlet of the main catchment. A complete distribution of flood discharges is finally computed. This method is illustrated with the example of the Durance at Serre-Ponçon catchment (south of French Alps, 3600 km2) which has been divided in four sub-catchements. The proposed approach is compared with the "classical" SCHADEX approach applied on the whole catchment. References: Garçon, R. (1996). Prévision opérationnelle des apports de la Durance à Serre-Ponçon à l'aide du modèle MORDOR. Bilan de l'année 1994-1995. La Houille Blanche, (5), 71-76. Gottardi, F., Obled, C., Gailhard, J., & Paquet, E. (2012). Statistical reanalysis of precipitation fields based on ground network data and weather patterns: Application over French mountains. Journal of Hydrology, 432, 154-167. Paquet, E., Garavaglia, F., Garçon, R., & Gailhard, J. (2013). The SCHADEX method: A semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 495, 23-37.

Agricultural Spray Drift Concentrations in Rainwater, Stemflow ...

EPA Pesticide Factsheets

In order to study spray drift contribution to non-targeted habitats, pesticide concentrations were measured in stemflow (water flowing down the trunk of a tree during a rain event), rainfall, and amphibians in an agriculturally impacted wetland area near Tifton, Georgia, USA. Agricultural fields and sampling locations were located on the University of Georgia's Gibbs research farm. Samples were analyzed for >150 pesticides and over 20 different pesticides were detected in these matrices. Data indicated that herbicides (metolachlor and atrazine) and fungicides (tebuconazole) were present with the highest concentrations in stemflow, followed by those in rainfall and amphibian tissue samples. Metolachlor had the highest frequency of detection and highest concentration in rainfall and stemflow samples. Higher concentrations of pesticides were observed in stemflow for a longer period than rainfall. Furthermore, rainfall and stemflow concentrations were compared against aquatic life benchmarks and environmental water screening values to determine if adverse effects would potentially occur for non-targeted organisms. Of the pesticides detected, several had concentrations that exceeded the aquatic life benchmark value. The majority of the time mixtures were present in the different matrices, making it difficult to determine the potential adverse effects that these compounds will have on non-target species, due to unknown potentiating effects. These data help assess the

Statistical analysis of trends in monthly precipitation at the Limbang River Basin, Sarawak (NW Borneo), Malaysia

NASA Astrophysics Data System (ADS)

Krishnan, M. V. Ninu; Prasanna, M. V.; Vijith, H.

2018-05-01

Effect of climate change in a region can be characterised by the analysis of rainfall trends. In the present research, monthly rainfall trends at Limbang River Basin (LRB) in Sarawak, Malaysia for a period of 45 years (1970-2015) were characterised through the non-parametric Mann-Kendall and Spearman's Rho tests and relative seasonality index. Statistically processed monthly rainfall of 12 well distributed rain gauging stations in LRB shows almost equal amount of rainfall in all months. Mann-Kendall and Spearman's Rho tests revealed a specific pattern of rainfall trend with a definite boundary marked in the months of January and August with positive trends in all stations. Among the stations, Limbang DID, Long Napir and Ukong showed positive (increasing) trends in all months with a maximum increase of 4.06 mm/year (p = 0.01) in November. All other stations showed varying trends (both increasing and decreasing). Significant (p = 0.05) decreasing trend was noticed in Ulu Medalam and Setuan during September (- 1.67 and - 1.79 mm/year) and October (- 1.59 and - 1.68 mm/year) in Mann-Kendall and Spearman's Rho tests. Spatial pattern of monthly rainfall trends showed two clusters of increasing rainfalls (maximas) in upper and lower part of the river basin separated with a dominant decreasing rainfall corridor. The results indicate a generally increasing trend of rainfall in Sarawak, Borneo.

Assessment of landslide hazards induced by extreme rainfall event in Jammu and Kashmir Himalaya, northwest India

NASA Astrophysics Data System (ADS)

Kumar, Amit; Asthana, AKL; Priyanka, Rao Singh; Jayangondaperumal, R.; Gupta, Anil K.; Bhakuni, SS

2017-05-01

In the Indian Himalayan region (IHR), landslide-driven hazards have intensified over the past several decades primarily caused by the occurrence of heavy and extreme rainfall. However, little attention has been given to determining the cause of events triggered during pre- and post-Indian Summer Monsoon (ISM) seasons. In the present research, detailed geological, meteorological, and remote sensing investigations have been carried out on an extreme rainfall landslide event that occurred in Sadal village, Udhampur district, Jammu and Kashmir Himalaya, during September 2014. Toward the receding phase of the ISM (i.e., in the month of September 2014), an unusual rainfall event of 488.2 mm rainfall in 24 h took place in Jammu and Kashmir Himalaya in contrast to the normal rainfall occurrence. Geological investigations suggest that a planar weakness in the affected region is caused by bedding planes that consist of an alternate sequence of hard, compact sandstone and weak claystone. During this extreme rainfall event, the Sadal village was completely buried under the rock slides, as failure occurred along the planar weakness that dips toward the valley slope. Rainfall data analysis from the Tropical Rainfall Measuring Mission (TRMM) for the preceding years homogeneous time series (July-September) indicates that the years 2005, 2009, 2011, 2012, and 2014 (i.e., closely spaced and clustering heavy rainfall events) received heavy rainfalls during the withdrawal of the ISM; whereas the heaviest rainfall was received in the years 2003 and 2013 at the onset of the ISM in the study region. This suggests that no characteristic cyclicity exists for extreme rainfall events. However, we observe that either toward the onset of the ISM or its retreat, the extreme rainfall facilitates landslides, rockfall, and slope failures in northwestern Himalaya. The spatiotemporal distribution of landslides caused by extreme rainfall events suggests its confinement toward the windward side of the Himalayan front.

A regression-kriging model for estimation of rainfall in the Laohahe basin

NASA Astrophysics Data System (ADS)

Wang, Hong; Ren, Li L.; Liu, Gao H.

2009-10-01

This paper presents a multivariate geostatistical algorithm called regression-kriging (RK) for predicting the spatial distribution of rainfall by incorporating five topographic/geographic factors of latitude, longitude, altitude, slope and aspect. The technique is illustrated using rainfall data collected at 52 rain gauges from the Laohahe basis in northeast China during 1986-2005 . Rainfall data from 44 stations were selected for modeling and the remaining 8 stations were used for model validation. To eliminate multicollinearity, the five explanatory factors were first transformed using factor analysis with three Principal Components (PCs) extracted. The rainfall data were then fitted using step-wise regression and residuals interpolated using SK. The regression coefficients were estimated by generalized least squares (GLS), which takes the spatial heteroskedasticity between rainfall and PCs into account. Finally, the rainfall prediction based on RK was compared with that predicted from ordinary kriging (OK) and ordinary least squares (OLS) multiple regression (MR). For correlated topographic factors are taken into account, RK improves the efficiency of predictions. RK achieved a lower relative root mean square error (RMSE) (44.67%) than MR (49.23%) and OK (73.60%) and a lower bias than MR and OK (23.82 versus 30.89 and 32.15 mm) for annual rainfall. It is much more effective for the wet season than for the dry season. RK is suitable for estimation of rainfall in areas where there are no stations nearby and where topography has a major influence on rainfall.

Mixing the Green-Ampt model and Curve Number method as an empirical tool for rainfall excess estimation in small ungauged catchments.

NASA Astrophysics Data System (ADS)

Grimaldi, S.; Petroselli, A.; Romano, N.

2012-04-01

The Soil Conservation Service - Curve Number (SCS-CN) method is a popular rainfall-runoff model that is widely used to estimate direct runoff from small and ungauged basins. The SCS-CN is a simple and valuable approach to estimate the total stream-flow volume generated by a storm rainfall, but it was developed to be used with daily rainfall data. To overcome this drawback, we propose to include the Green-Ampt (GA) infiltration model into a mixed procedure, which is referred to as CN4GA (Curve Number for Green-Ampt), aiming to distribute in time the information provided by the SCS-CN method so as to provide estimation of sub-daily incremental rainfall excess. For a given storm, the computed SCS-CN total net rainfall amount is used to calibrate the soil hydraulic conductivity parameter of the Green-Ampt model. The proposed procedure was evaluated by analyzing 100 rainfall-runoff events observed in four small catchments of varying size. CN4GA appears an encouraging tool for predicting the net rainfall peak and duration values and has shown, at least for the test cases considered in this study, a better agreement with observed hydrographs than that of the classic SCS-CN method.

Determining the precipitable water vapor thresholds under different rainfall strengths in Taiwan

NASA Astrophysics Data System (ADS)

Yeh, Ta-Kang; Shih, Hsuan-Chang; Wang, Chuan-Sheng; Choy, Suelynn; Chen, Chieh-Hung; Hong, Jing-Shan

2018-02-01

Precipitable Water Vapor (PWV) plays an important role for weather forecasting. It is helpful in evaluating the changes of the weather system via observing the distribution of water vapor. The ability of calculating PWV from Global Positioning System (GPS) signals is useful to understand the special weather phenomenon. In this study, 95 ground-based GPS and rainfall stations in Taiwan were utilized from 2006 to 2012 to analyze the relationship between PWV and rainfall. The PWV data were classified into four classes (no, light, moderate and heavy rainfall), and the vertical gradients of the PWV were obtained and the variations of the PWV were analyzed. The results indicated that as the GPS elevation increased every 100 m, the PWV values decreased by 9.5 mm, 11.0 mm, 12.2 mm and 12.3 mm during the no, light, moderate and heavy rainfall conditions, respectively. After applying correction using the vertical gradients mentioned above, the average PWV thresholds were 41.8 mm, 52.9 mm, 62.5 mm and 64.4 mm under the no, light, moderate and heavy rainfall conditions, respectively. This study offers another type of empirical threshold to assist the rainfall prediction and can be used to distinguish the rainfall features between different areas in Taiwan.

A national-scale seasonal hydrological forecast system: development and evaluation over Britain

NASA Astrophysics Data System (ADS)

Bell, Victoria A.; Davies, Helen N.; Kay, Alison L.; Brookshaw, Anca; Scaife, Adam A.

2017-09-01

Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better) rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts) from the GloSea5 model (1996 to 2009) are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean) rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region). Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 %) in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows), whereas for the 3-month ahead lead time, GloSea5 forecasts account for ˜ 70 % of the forecast skill (mostly in areas of high rainfall to the north and west) and only 30 % of the skill arises from hydrological memory (typically groundwater-dominated areas). Given the high spatial heterogeneity in typical patterns of UK rainfall and evaporation, future development of skilful spatially distributed seasonal forecasts could lead to substantial improvements in seasonal flow forecast capability, potentially benefitting practitioners interested in predicting hydrological extremes, not only in the UK but also across Europe.

A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland

NASA Astrophysics Data System (ADS)

Panziera, Luca; Gabella, Marco; Zanini, Stefano; Hering, Alessandro; Germann, Urs; Berne, Alexis

2016-06-01

This paper presents a regional extreme rainfall analysis based on 10 years of radar data for the 159 regions adopted for official natural hazard warnings in Switzerland. Moreover, a nowcasting tool aimed at issuing heavy precipitation regional alerts is introduced. The two topics are closely related, since the extreme rainfall analysis provides the thresholds used by the nowcasting system for the alerts. Warm and cold seasons' monthly maxima of several statistical quantities describing regional rainfall are fitted to a generalized extreme value distribution in order to derive the precipitation amounts corresponding to sub-annual return periods for durations of 1, 3, 6, 12, 24 and 48 h. It is shown that regional return levels exhibit a large spatial variability in Switzerland, and that their spatial distribution strongly depends on the duration of the aggregation period: for accumulations of 3 h and shorter, the largest return levels are found over the northerly alpine slopes, whereas for longer durations the southern Alps exhibit the largest values. The inner alpine chain shows the lowest values, in agreement with previous rainfall climatologies. The nowcasting system presented here is aimed to issue heavy rainfall alerts for a large variety of end users, who are interested in different precipitation characteristics and regions, such as, for example, small urban areas, remote alpine catchments or administrative districts. The alerts are issued not only if the rainfall measured in the immediate past or forecast in the near future exceeds some predefined thresholds but also as soon as the sum of past and forecast precipitation is larger than threshold values. This precipitation total, in fact, has primary importance in applications for which antecedent rainfall is as important as predicted one, such as urban floods early warning systems. The rainfall fields, the statistical quantity representing regional rainfall and the frequency of alerts issued in case of continuous threshold exceedance are some of the configurable parameters of the tool. The analysis of the urban flood which occurred in the city of Schaffhausen in May 2013 suggests that this alert tool might have complementary skill with respect to radar-based thunderstorm nowcasting systems for storms which do not show a clear convective signature.

Modeling the probability distribution of peak discharge for infiltrating hillslopes

NASA Astrophysics Data System (ADS)

Baiamonte, Giorgio; Singh, Vijay P.

2017-07-01

Hillslope response plays a fundamental role in the prediction of peak discharge at the basin outlet. The peak discharge for the critical duration of rainfall and its probability distribution are needed for designing urban infrastructure facilities. This study derives the probability distribution, denoted as GABS model, by coupling three models: (1) the Green-Ampt model for computing infiltration, (2) the kinematic wave model for computing discharge hydrograph from the hillslope, and (3) the intensity-duration-frequency (IDF) model for computing design rainfall intensity. The Hortonian mechanism for runoff generation is employed for computing the surface runoff hydrograph. Since the antecedent soil moisture condition (ASMC) significantly affects the rate of infiltration, its effect on the probability distribution of peak discharge is investigated. Application to a watershed in Sicily, Italy, shows that with the increase of probability, the expected effect of ASMC to increase the maximum discharge diminishes. Only for low values of probability, the critical duration of rainfall is influenced by ASMC, whereas its effect on the peak discharge seems to be less for any probability. For a set of parameters, the derived probability distribution of peak discharge seems to be fitted by the gamma distribution well. Finally, an application to a small watershed, with the aim to test the possibility to arrange in advance the rational runoff coefficient tables to be used for the rational method, and a comparison between peak discharges obtained by the GABS model with those measured in an experimental flume for a loamy-sand soil were carried out.

Uncertainties of flood frequency estimation approaches based on continuous simulation using data resampling

NASA Astrophysics Data System (ADS)

Arnaud, Patrick; Cantet, Philippe; Odry, Jean

2017-11-01

Flood frequency analyses (FFAs) are needed for flood risk management. Many methods exist ranging from classical purely statistical approaches to more complex approaches based on process simulation. The results of these methods are associated with uncertainties that are sometimes difficult to estimate due to the complexity of the approaches or the number of parameters, especially for process simulation. This is the case of the simulation-based FFA approach called SHYREG presented in this paper, in which a rainfall generator is coupled with a simple rainfall-runoff model in an attempt to estimate the uncertainties due to the estimation of the seven parameters needed to estimate flood frequencies. The six parameters of the rainfall generator are mean values, so their theoretical distribution is known and can be used to estimate the generator uncertainties. In contrast, the theoretical distribution of the single hydrological model parameter is unknown; consequently, a bootstrap method is applied to estimate the calibration uncertainties. The propagation of uncertainty from the rainfall generator to the hydrological model is also taken into account. This method is applied to 1112 basins throughout France. Uncertainties coming from the SHYREG method and from purely statistical approaches are compared, and the results are discussed according to the length of the recorded observations, basin size and basin location. Uncertainties of the SHYREG method decrease as the basin size increases or as the length of the recorded flow increases. Moreover, the results show that the confidence intervals of the SHYREG method are relatively small despite the complexity of the method and the number of parameters (seven). This is due to the stability of the parameters and takes into account the dependence of uncertainties due to the rainfall model and the hydrological calibration. Indeed, the uncertainties on the flow quantiles are on the same order of magnitude as those associated with the use of a statistical law with two parameters (here generalised extreme value Type I distribution) and clearly lower than those associated with the use of a three-parameter law (here generalised extreme value Type II distribution). For extreme flood quantiles, the uncertainties are mostly due to the rainfall generator because of the progressive saturation of the hydrological model.

Toward a Global Map of Raindrop Size Distributions. Part 1; Rain-Type Classification and Its Implications for Validating Global Rainfall Products

NASA Technical Reports Server (NTRS)

L'Ecuyer, Tristan S.; Kummerow, Christian; Berg,Wesley

2004-01-01

Variability in the global distribution of precipitation is recognized as a key element in assessing the impact of climate change for life on earth. The response of precipitation to climate forcings is, however, poorly understood because of discrepancies in the magnitude and sign of climatic trends in satellite-based rainfall estimates. Quantifying and ultimately removing these biases is critical for studying the response of the hydrologic cycle to climate change. In addition, estimates of random errors owing to variability in algorithm assumptions on local spatial and temporal scales are critical for establishing how strongly their products should be weighted in data assimilation or model validation applications and for assigning a level of confidence to climate trends diagnosed from the data. This paper explores the potential for refining assumed drop size distributions (DSDs) in global radar rainfall algorithms by establishing a link between satellite observables and information gleaned from regional validation experiments where polarimetric radar, Doppler radar, and disdrometer measurements can be used to infer raindrop size distributions. By virtue of the limited information available in the satellite retrieval framework, the current method deviates from approaches adopted in the ground-based radar community that attempt to relate microphysical processes and resultant DSDs to local meteorological conditions. Instead, the technique exploits the fact that different microphysical pathways for rainfall production are likely to lead to differences in both the DSD of the resulting raindrops and the three-dimensional structure of associated radar reflectivity profiles. Objective rain-type classification based on the complete three-dimensional structure of observed reflectivity profiles is found to partially mitigate random and systematic errors in DSDs implied by differential reflectivity measurements. In particular, it is shown that vertical and horizontal reflectivity structure obtained from spaceborne radar can be used to reproduce significant differences in Z(sub dr) between the easterly and westerly climate regimes observed in the Tropical Rainfall Measuring Mission Large-scale Biosphere-Atmosphere (TRMM-LBA) field experiment as well as the even larger differences between Amazonian rainfall and that observed in eastern Colorado. As such, the technique offers a potential methodology for placing locally observed DSD information into a global framework.

Bias correction method for climate change impact assessment at a basin scale

NASA Astrophysics Data System (ADS)

Nyunt, C.; Jaranilla-sanchez, P. A.; Yamamoto, A.; Nemoto, T.; Kitsuregawa, M.; Koike, T.

2012-12-01

Climate change impact studies are mainly based on the general circulation models GCM and these studies play an important role to define suitable adaptation strategies for resilient environment in a basin scale management. For this purpose, this study summarized how to select appropriate GCM to decrease the certain uncertainty amount in analysis. This was applied to the Pampanga, Angat and Kaliwa rivers in Luzon Island, the main island of Philippine and these three river basins play important roles in irrigation water supply, municipal water source for Metro Manila. According to the GCM scores of both seasonal evolution of Asia summer monsoon and spatial correlation and root mean squared error of atmospheric variables over the region, finally six GCM is chosen. Next, we develop a complete, efficient and comprehensive statistical bias correction scheme covering extremes events, normal rainfall and frequency of dry period. Due to the coarse resolution and parameterization scheme of GCM, extreme rainfall underestimation, too many rain days with low intensity and poor representation of local seasonality have been known as bias of GCM. Extreme rainfall has unusual characteristics and it should be focused specifically. Estimated maximum extreme rainfall is crucial for planning and design of infrastructures in river basin. Developing countries have limited technical, financial and management resources for implementing adaptation measures and they need detailed information of drought and flood for near future. Traditionally, the analysis of extreme has been examined using annual maximum series (AMS) adjusted to a Gumbel or Lognormal distribution. The drawback is the loss of the second, third etc, largest rainfall. Another approach is partial duration series (PDS) constructed using the values above a selected threshold and permit more than one event per year. The generalized Pareto distribution (GPD) has been used to model PDS and it is the series of excess over a threshold. In this study, the lowest value of AMS of observed is selected as threshold and simultaneously same frequency is considered as extremes in corresponding GCM gridded series. After fitting to GP distribution, bias corrected GCM extreme is found by using the inverse function of observed extremes. The results show it can remove bias effectively. For projected climate, the same transfer function between historical observed and GCM was applied. Moreover, frequency analysis of maximum extreme intensity estimation was done for validation and then approximate for near future by using identical function as past. To fix the error in the number of no rain days of GCM, ranking order statistics is used and define in GCM same as the frequency of wet days in observed station. After this rank, GCM output will be zero and identify same threshold for future projection. Normal rainfall is classified as between threshold of extreme and no rain day. We assume monthly normal rainfall follow gamma distribution. Then, we mapped the CDF of GCM normal rainfall to station's one in each month and bias corrected rainfall is available. In summary, bias of GCM have been addressed efficiently and validated at point scale by seasonal climatology and at all stations for evaluating downscaled rainfall performance. The results show bias corrected and downscaled scheme is good enough for climate impact study.

How rainfall, relative humidity and temperature influence volatile emissions from apple trees in situ.

PubMed

Vallat, Armelle; Gu, Hainan; Dorn, Silvia

2005-07-01

Headspace volatiles from apple-bearing twigs were collected in the field with a Radiello sampler during three different diurnal periods over the complete fruit growing season. Analyses by thermal desorption-GC-MS identified a total of 62 compounds in changing quantities, including the terpenoids alpha-pinene, camphene, beta-pinene, limonene, beta-caryophyllene and (E,E)-alpha-farnesene, the aldehydes (E)-2-hexenal, benzaldehyde and nonanal, and the alcohol (Z)-3-hexen-1-ol. The variations in emission of these plant odours were statistically related to temperature, humidity and rainfall in the field. Remarkably, rainfall had a significant positive influence on changes in volatile release during all three diurnal periods, and further factors of significance were temperature and relative humidity around noon, relative humidity in the late afternoon, and temperature and relative humidity during the night. Rainfall was associated consistently with an increase in the late afternoon in terpene and aldehyde volatiles with a known repellent effect on the codling moth, one of the key pests of apple fruit. During the summer of 2003, a season characterized by below-average rainfall, some postulated effects of drought on trees were tested by establishing correlations with rainfall. Emissions of the wood terpenes alpha-pinene, beta-pinene and limonene were negatively correlated with rainfall. Another monoterpene, camphene, was only detected in this summer but not in the previous years, and its emissions were negatively correlated with rainfall, further supporting the theory that drought can result in higher formation of secondary metabolites. Finally, the two green leaf volatiles (E)-2-hexenal and (Z)-3-hexen-1-ol were negatively correlated with rainfall, coinciding well with the expectation that water deficit stress increases activity of lipoxygenase. To our knowledge, this work represents the first empirical study concerning the influence of abiotic factors on volatile emissions from apple trees in situ.

Critical review and hydrologic application of threshold detection methods for the generalized Pareto (GP) distribution

NASA Astrophysics Data System (ADS)

Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto

2016-04-01

Estimation of extreme rainfall from data constitutes one of the most important issues in statistical hydrology, as it is associated with the design of hydraulic structures and flood water management. To that extent, based on asymptotic arguments from Extreme Excess (EE) theory, several studies have focused on developing new, or improving existing methods to fit a generalized Pareto (GP) distribution model to rainfall excesses above a properly selected threshold u. The latter is generally determined using various approaches, such as non-parametric methods that are intended to locate the changing point between extreme and non-extreme regions of the data, graphical methods where one studies the dependence of GP distribution parameters (or related metrics) on the threshold level u, and Goodness of Fit (GoF) metrics that, for a certain level of significance, locate the lowest threshold u that a GP distribution model is applicable. In this work, we review representative methods for GP threshold detection, discuss fundamental differences in their theoretical bases, and apply them to 1714 daily rainfall records from the NOAA-NCDC open-access database, with more than 110 years of data. We find that non-parametric methods that are intended to locate the changing point between extreme and non-extreme regions of the data are generally not reliable, while methods that are based on asymptotic properties of the upper distribution tail lead to unrealistically high threshold and shape parameter estimates. The latter is justified by theoretical arguments, and it is especially the case in rainfall applications, where the shape parameter of the GP distribution is low; i.e. on the order of 0.1 ÷ 0.2. Better performance is demonstrated by graphical methods and GoF metrics that rely on pre-asymptotic properties of the GP distribution. For daily rainfall, we find that GP threshold estimates range between 2÷12 mm/d with a mean value of 6.5 mm/d, while the existence of quantization in the empirical records, as well as variations in their size, constitute the two most important factors that may significantly affect the accuracy of the obtained results. Acknowledgments The research project was implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and co-financed by the European Social Fund (ESF) and the Greek State. The work conducted by Roberto Deidda was funded under the Sardinian Regional Law 7/2007 (funding call 2013).

Performance of bias corrected MPEG rainfall estimate for rainfall-runoff simulation in the upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Worqlul, Abeyou W.; Ayana, Essayas K.; Maathuis, Ben H. P.; MacAlister, Charlotte; Philpot, William D.; Osorio Leyton, Javier M.; Steenhuis, Tammo S.

2018-01-01

In many developing countries and remote areas of important ecosystems, good quality precipitation data are neither available nor readily accessible. Satellite observations and processing algorithms are being extensively used to produce satellite rainfall products (SREs). Nevertheless, these products are prone to systematic errors and need extensive validation before to be usable for streamflow simulations. In this study, we investigated and corrected the bias of Multi-Sensor Precipitation Estimate-Geostationary (MPEG) data. The corrected MPEG dataset was used as input to a semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning (HBV) for simulation of discharge of the Gilgel Abay and Gumara watersheds in the Upper Blue Nile basin, Ethiopia. The result indicated that the MPEG satellite rainfall captured 81% and 78% of the gauged rainfall variability with a consistent bias of underestimating the gauged rainfall by 60%. A linear bias correction applied significantly reduced the bias while maintaining the coefficient of correlation. The simulated flow using bias corrected MPEG SRE resulted in a simulated flow comparable to the gauge rainfall for both watersheds. The study indicated the potential of MPEG SRE in water budget studies after applying a linear bias correction.

Precipitation Processes Derived from TRMM Satellite Data, Cloud Resolving Model and Field Campaigns

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle and is a primary heat source for the atmosphere. The vertical distribution of latent-heat release, which is accompanied by rainfall, modulates the large-scale circulations of the tropics and in turn can impact midlatitude weather. This latent heat release is a consequence of phase changes between vapor, liquid. and solid water. Present large-scale weather and climate models can simulate cloud latent heat release only crudely thus reducing their confidence in predictions on both global and regional scales. In this paper, NASA Tropical Rainfall Measuring (TRMM) precipitation radar (PR) derived rainfall information and the Goddard Convective and Stratiform Heating (CSH) algorithm used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to October 2000. Rainfall latent heating and radar reflectively structure between ENSO (1997-1998 winter) and non-ENSO (1998-1999 winter) periods are examined and compared. The seasonal variation of heating over various geographic locations (i.e. Indian ocean vs west Pacific; Africa vs S. America) are also analyzed. In addition, the relationship between rainfall latent heating maximum heating level), radar reflectively and SST are examined.

Numerical modeling of rainfall thresholds for shallow landsliding in the Seattle, Washington, area

USGS Publications Warehouse

Godt, Jonathan W.; McKenna, Jonathan P.

2008-01-01

The temporal forecasting of landslide hazard has typically relied on empirical relations between rainfall characteristics and landslide occurrence to identify conditions that may cause shallow landslides. Here, we describe an alternate, deterministic approach to define rainfall thresholds for landslide occurrence in the Seattle, Washington, area. This approach combines an infinite slope-stability model with a variably saturated flow model to determine the rainfall intensity and duration that leads to shallow failure of hillside colluvium. We examine the influence of variation in particle-size distribution on the unsaturated hydraulic properties of the colluvium by performing capillary-rise tests on glacial outwash sand and three experimental soils with increasing amounts of fine-grained material. Observations of pore-water response to rainfall collected as part of a program to monitor the near-surface hydrology of steep coastal bluffs along Puget Sound were used to test the numerical model results and in an inverse modeling procedure to determine the in situ hydraulic properties. Modeling results are given in terms of a destabilizing rainfall intensity and duration, and comparisons with empirical observations of landslide occurrence and triggering rainfall indicate that the modeling approach may be useful for forecasting landslide occurrence.

Event-based rainfall-runoff modelling of the Kelantan River Basin

NASA Astrophysics Data System (ADS)

Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.

2014-02-01

Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.

Modelling of Rainfall Induced Landslides in Puerto Rico

NASA Astrophysics Data System (ADS)

Lepore, C.; Arnone, E.; Sivandran, G.; Noto, L. V.; Bras, R. L.

2010-12-01

We performed an island-wide determination of static landslide susceptibility and hazard assessment as well as dynamic modeling of rainfall-induced shallow landslides in a particular hydrologic basin. Based on statistical analysis of past landslides, we determined that reliable prediction of the susceptibility to landslides is strongly dependent on the resolution of the digital elevation model (DEM) employed and the reliability of the rainfall data. A distributed hydrology model, Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator with VEGetation Generator for Interactive Evolution (tRIBS-VEGGIE), tRIBS-VEGGIE, has been implemented for the first time in a humid tropical environment like Puerto Rico and validated against in-situ measurements. A slope-failure module has been added to tRIBS-VEGGIE’s framework, after analyzing several failure criterions to identify the most suitable for our application; the module is used to predict the location and timing of landsliding events. The Mameyes basin, located in the Luquillo Experimental Forest in Puerto Rico, was selected for modeling based on the availability of soil, vegetation, topographical, meteorological and historic landslide data. Application of the model yields a temporal and spatial distribution of predicted rainfall-induced landslides.

Sensitivity of goodness-of-fit statistics to rainfall data rounding off

NASA Astrophysics Data System (ADS)

Deidda, Roberto; Puliga, Michelangelo

An analysis based on the L-moments theory suggests of adopting the generalized Pareto distribution to interpret daily rainfall depths recorded by the rain-gauge network of the Hydrological Survey of the Sardinia Region. Nevertheless, a big problem, not yet completely resolved, arises in the estimation of a left-censoring threshold able to assure a good fitting of rainfall data with the generalized Pareto distribution. In order to detect an optimal threshold, keeping the largest possible number of data, we chose to apply a “failure-to-reject” method based on goodness-of-fit tests, as it was proposed by Choulakian and Stephens [Choulakian, V., Stephens, M.A., 2001. Goodness-of-fit tests for the generalized Pareto distribution. Technometrics 43, 478-484]. Unfortunately, the application of the test, using percentage points provided by Choulakian and Stephens (2001), did not succeed in detecting a useful threshold value in most analyzed time series. A deeper analysis revealed that these failures are mainly due to the presence of large quantities of rounding off values among sample data, affecting the distribution of goodness-of-fit statistics and leading to significant departures from percentage points expected for continuous random variables. A procedure based on Monte Carlo simulations is thus proposed to overcome these problems.

Evaluation of radar rainfall estimates and nowcasts to prevent flash flood in real time by using a road submersion warning tool

NASA Astrophysics Data System (ADS)

Versini, Pierre-Antoine; Sempere-Torres, Daniel

2010-05-01

Important damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions. These are major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods and different kinds of rainfall observations are available in real time: radar rainfall estimates and nowcasts from METEO FRANCE and the CALAMAR system from SPC (state authority in charge of flood forecasting). An application devoted to the road network, has also been recently developed for this region. It combines distributed hydro-meteorological very short range forecasts and vulnerability analysis to provide warnings of road submersions. The first results demonstrate that it is technically possible to provide distributed short-term forecasts for a large number of sites. The study also demonstrates that a reliable estimation of the spatial distribution of rainfall is essential. For this reason, the road submersion warning system can be used to evaluate the quality of rainfall estimates and nowcasts. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, more than 300mm dropped on the South part of the Gard and many roads were submerged. Each of the mentioned rainfall datasets (i.e. estimates and nowcasts) was available in real time. They have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. The results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and a reasonable false alarm ratio. It demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall nowcasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding one hour.

Effects of climate change on the wash-off of volatile organic compounds from urban roads.

PubMed

Mahbub, Parvez; Goonetilleke, Ashantha; Ayoko, Godwin A; Egodawatta, Prasanna

2011-09-01

The predicted changes in rainfall characteristics due to climate change could adversely affect stormwater quality in highly urbanised coastal areas throughout the world. This in turn will exert a significant influence on the discharge of pollutants to estuarine and marine waters. Hence, an in-depth analysis of the effects of such changes on the wash-off of volatile organic compounds (VOCs) from urban roads in the Gold Coast region in Australia was undertaken. The rainfall characteristics were simulated using a rainfall simulator. Principal Component Analysis (PCA) and Multicriteria Decision tools such as PROMETHEE and GAIA were employed to understand the VOC wash-off under climate change. It was found that low, low to moderate and high rain events due to climate change will affect the wash-off of toluene, ethylbenzene, meta-xylene, para-xylene and ortho-xylene from urban roads in Gold Coast. Total organic carbon (TOC) was identified as predominant carrier of toluene, meta-xylene and para-xylene in <1 μm to 150 μm fractions and for ethylbenzene in 150 μm to >300 μm fractions under such dominant rain events due to climate change. However, ortho-xylene did not show such affinity towards either TOC or TSS (total suspended solids) under the simulated climatic conditions. Copyright © 2011 Elsevier B.V. All rights reserved.

Rainfall Stochastic models

NASA Astrophysics Data System (ADS)

Campo, M. A.; Lopez, J. J.; Rebole, J. P.

2012-04-01

This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series were recorded every ten minutes and hourly, aggregated. Preliminary results show adequate simulation of the main features of rain. Main variables are well simulated for time series of ten minutes, also over one hour precipitation time series, which are those that generate higher rainfall hydrologic design. For coarse scales, less than one hour, rainfall durations are not appropriate under the simulation. A hypothesis may be an excessive number of simulated events, which causes further fragmentation of storms, resulting in an excess of rain "short" (less than 1 hour), and therefore also among rain events, compared with the ones that occur in the actual series.

Variability in rainfall at monitoring stations and derivation of a long-term rainfall intensity record in the Grand Canyon Region, Arizona, USA

USGS Publications Warehouse

Caster, Joshua J.; Sankey, Joel B.

2016-04-11

In this study, we examine rainfall datasets of varying temporal length, resolution, and spatial distribution to characterize rainfall depth, intensity, and seasonality for monitoring stations along the Colorado River within Marble and Grand Canyons. We identify maximum separation distances between stations at which rainfall measurements might be most useful for inferring rainfall characteristics at other locations. We demonstrate a method for applying relations between daily rainfall depth and intensity, from short-term high-resolution data to lower-resolution longer-term data, to synthesize a long-term record of daily rainfall intensity from 1950–2012. We consider the implications of our spatio-temporal characterization of rainfall for understanding local landscape change in sedimentary deposits and archaeological sites, and for better characterizing past and present rainfall and its potential role in overland flow erosion within the canyons. We find that rainfall measured at stations within the river corridor is spatially correlated at separation distances of tens of kilometers, and is not correlated at the large elevation differences that separate stations along the Colorado River from stations above the canyon rim. These results provide guidance for reasonable separation distances at which rainfall measurements at stations within the Grand Canyon region might be used to infer rainfall at other nearby locations along the river. Like other rugged landscapes, spatial variability between rainfall measured at monitoring stations appears to be influenced by canyon and rim physiography and elevation, with preliminary results suggesting the highest elevation landform in the region, the Kaibab Plateau, may function as an important orographic influence. Stations at specific locations within the canyons and along the river, such as in southern (lower) Marble Canyon and eastern (upper) Grand Canyon, appear to have strong potential to receive high-intensity rainfall that can generate runoff which may erode alluvium. The characterization of past and present rainfall variability in this study will be useful for future studies that evaluate more spatially continuous datasets in order to better understand the rainfall dynamics within this, and potentially other, deep canyons.

A medium scale mobile rainfall simulator for experiments on soil erosion and soil hydrology

NASA Astrophysics Data System (ADS)

Kavka, Petr; Dostál, Tomáš; Iserloh, Thomas; Davidová, Tereza; Krása, Josef; David, Václav; Vopravil, Jan; Khel, Tomáš; Bauer, Miroslav

2015-04-01

Numerous types of rainfall simulators (RS) have been used to the study the behaviour of surface runoff and sediment transport caused by rainfall. It has been documented, that reproducibility and the knowledge of test conditions are essential for gathering necessary and comparable data. Therefore medium, to large scale field rainfall simulators are very desirable. Such devices are nevertheless very much time and laboratory consuming and their weakness is especially a high water consumption. A new, compact and mobile medium scale rainfall simulator has been developed under close cooperation of CTU Prague and Research Institute of Soil Conservation. The main idea was to develop a device, which is easily to handle by 4 persons, transportable with trailer behind an off-road car and independent of additional water sources and energy. Therefore, a special construction fixed on a standard trailer has been developed. It consists of an aggregate to produce power, an electric pump and a water tank with a capacity up to 1000 l. The pump can work in reverse mode, what allows filling the water tank from any source, including stream or pond. The capacity of the tank is normally sufficient for experiments with duration up to 30 minutes. The RS itself consist of a folding arm, which carries 4 nozzles (SS Full Jet 40WSQ), controlled by electromagnetic valves, which allow to set up desired rainfall intensity by opening intervals. A simple logical unit allows programming various schemes of operation of individual nozzles, to keep low pressure fluctuation in the system. The arm is first unfolded into total length of 9.6 m and then lifted up, using simple crab to its operation position which is 2.3 - 2.65 m above terrain surface. The distance between individual nozzles had been optimized based on number of calibrating experiments on 2.4 m. There is also special space at the trailer for transportation of metal sheets and collector (for experimental plot), additional equipment, tools and measurement devices. To prevent the wind effect, whole construction can be easily covered by tarpaulin. The experimental plot has a basic size of 9.5 x 2 m, however, we usually use only 8 x 2 m. The nozzles are fed with a water pressure of about 0.8 bars. Various schemes of opened nozzles allow varying rainfall intensities between 40 and 80 mm.h-1. Rainfall collectors were used to measure spatial rainfall distribution. The spatial rainfall distribution on the entire plot is higher than 80% (Christiansen-Uniformity Coefficient). Drop size distribution and drop fall velocities were analyzed by means of a Laser Precipitation Monitor (by Thies) with satisfactory results. The mean drop sizes ranging between 0.75 - 2.00 mm depending on applied intensity. Resulting kinetic energies ranging from 188 - 582 J m-2 mm-1. The measured rainfall variables show low fluctuations throughout the tests and are therefore reproducible in field investigations. The research has been supported by the research projects SGS14/180/OHK1/3T/11 and QJ330118.

A Novel Analysis Of The Connection Between Indian Monsoon Rainfall And Solar Activity

NASA Astrophysics Data System (ADS)

Bhattacharyya, S.; Narasimha, R.

2005-12-01

The existence of possible correlations between the solar cycle period as extracted from the yearly means of sunspot numbers and any periodicities that may be present in the Indian monsoon rainfall has been addressed using wavelet analysis. The wavelet transform coefficient maps of sunspot-number time series and those of the homogeneous Indian monsoon rainfall annual time series data reveal striking similarities, especially around the 11-year period. A novel method to analyse and quantify this similarity devising statistical schemes is suggested in this paper. The wavelet transform coefficient maxima at the 11-year period for the sunspot numbers and the monsoon rainfall have each been modelled as a point process in time and a statistical scheme for identifying a trend or dependence between the two processes has been devised. A regression analysis of parameters in these processes reveals a nearly linear trend with small but systematic deviations from the regressed line. Suitable function models for these deviations have been obtained through an unconstrained error minimisation scheme. These models provide an excellent fit to the time series of the given wavelet transform coefficient maxima obtained from actual data. Statistical significance tests on these deviations suggest with 99% confidence that the deviations are sample fluctuations obtained from normal distributions. In fact our earlier studies (see, Bhattacharyya and Narasimha, 2005, Geophys. Res. Lett., Vol. 32, No. 5) revealed that average rainfall is higher during periods of greater solar activity for all cases, at confidence levels varying from 75% to 99%, being 95% or greater in 3 out of 7 of them. Analysis using standard wavelet techniques reveals higher power in the 8--16 y band during the higher solar activity period, in 6 of the 7 rainfall time series, at confidence levels exceeding 99.99%. Furthermore, a comparison between the wavelet cross spectra of solar activity with rainfall and noise (including those simulating the rainfall spectrum and probability distribution) revealed that over the two test-periods respectively of high and low solar activity, the average cross power of the solar activity index with rainfall exceeds that with the noise at z-test confidence levels exceeding 99.99% over period-bands covering the 11.6 y sunspot cycle (see, Bhattacharyya and Narasimha, SORCE 2005 14-16th September, at Durango, Colorado USA). These results provide strong evidence for connections between Indian rainfall and solar activity. The present study reveals in addition the presence of subharmonics of the solar cycle period in the monsoon rainfall time series together with information on their phase relationships.

Storm Identification and Tracking for Hydrologic Modeling Using Hourly Accumulated NEXRAD Precipitation Data

NASA Astrophysics Data System (ADS)

Olivera, F.; Choi, J.; Socolofsky, S.

2006-12-01

Watershed responses to storm events are strongly affected by the spatial and temporal patterns of rainfall; that is, the spatial distribution of the precipitation intensity and its evolution over time. Although real storms are moving entities with non-uniform intensities in both space and time, hydrological applications often synthesize these attributes by assuming storms that are uniformly distributed and have variable intensity according to a pre-defined hyetograph shape. As one considers watersheds of greater size, the non-uniformity of rainfall becomes more important, because a storm may not cover the watershed's entire area and may not stay in the watershed for its full duration. In order to incorporate parameters such as storm area, propagation velocity and direction, and intensity distribution in the definition of synthetic storms, it is necessary to determine these storm characteristics from spatially distributed precipitation data. To date, most algorithms for identifying and tracking storms have been applied to short time-step radar reflectivity data (i.e., 15 minutes or less), where storm features are captured in an effectively synoptic manner. For the entire United States, however, the most reliable distributed precipitation data are the one-hour accumulated 4 km × 4 km gridded NEXRAD data of the U.S. National Weather Service (NWS) (NWS 2005. The one-hour aggregation level of the data, though, makes it more difficult to identify and track storms than when using sequences of synoptic radar reflectivity data, because storms can traverse over a number of NEXRAD cells and change size and shape appreciably between consecutive data maps. In this paper, we present a methodology to overcome the identification and tracking difficulties and to extract the characteristics of moving storms (e.g. size, propagation velocity and direction, and intensity distribution) from one-hour accumulated distributed rainfall data. The algorithm uses Gaussian Mixture Models (GMM) for storm identification and image processing for storm tracking. The method has been successfully applied to Brazos County in Texas using the 2003 Multi-sensor Precipitation Estimator (MPE) NEXRAD rainfall data.

Spatially distributed groundwater recharge estimated using a water-budget model for the Island of Maui, Hawai`i, 1978–2007

USGS Publications Warehouse

Johnson, Adam G.; Engott, John A.; Bassiouni, Maoya; Rotzoll, Kolja

2014-12-14

Demand for freshwater on the Island of Maui is expected to grow. To evaluate the availability of fresh groundwater, estimates of groundwater recharge are needed. A water-budget model with a daily computation interval was developed and used to estimate the spatial distribution of recharge on Maui for average climate conditions (1978–2007 rainfall and 2010 land cover) and for drought conditions (1998–2002 rainfall and 2010 land cover). For average climate conditions, mean annual recharge for Maui is about 1,309 million gallons per day, or about 44 percent of precipitation (rainfall and fog interception). Recharge for average climate conditions is about 39 percent of total water inflow consisting of precipitation, irrigation, septic leachate, and seepage from reservoirs and cesspools. Most recharge occurs on the wet, windward slopes of Haleakalā and on the wet, uplands of West Maui Mountain. Dry, coastal areas generally have low recharge. In the dry isthmus, however, irrigated fields have greater recharge than nearby unirrigated areas. For drought conditions, mean annual recharge for Maui is about 1,010 million gallons per day, which is 23 percent less than recharge for average climate conditions. For individual aquifer-system areas used for groundwater management, recharge for drought conditions is about 8 to 51 percent less than recharge for average climate conditions. The spatial distribution of rainfall is the primary factor determining spatially distributed recharge estimates for most areas on Maui. In wet areas, recharge estimates are also sensitive to water-budget parameters that are related to runoff, fog interception, and forest-canopy evaporation. In dry areas, recharge estimates are most sensitive to irrigated crop areas and parameters related to evapotranspiration.

Validation of satellite-based rainfall in Kalahari

NASA Astrophysics Data System (ADS)

Lekula, Moiteela; Lubczynski, Maciek W.; Shemang, Elisha M.; Verhoef, Wouter

2018-06-01

Water resources management in arid and semi-arid areas is hampered by insufficient rainfall data, typically obtained from sparsely distributed rain gauges. Satellite-based rainfall estimates (SREs) are alternative sources of such data in these areas. In this study, daily rainfall estimates from FEWS-RFE∼11 km, TRMM-3B42∼27 km, CMOPRH∼27 km and CMORPH∼8 km were evaluated against nine, daily rain gauge records in Central Kalahari Basin (CKB), over a five-year period, 01/01/2001-31/12/2005. The aims were to evaluate the daily rainfall detection capabilities of the four SRE algorithms, analyze the spatio-temporal variability of rainfall in the CKB and perform bias-correction of the four SREs. Evaluation methods included scatter plot analysis, descriptive statistics, categorical statistics and bias decomposition. The spatio-temporal variability of rainfall, was assessed using the SREs' mean annual rainfall, standard deviation, coefficient of variation and spatial correlation functions. Bias correction of the four SREs was conducted using a Time-Varying Space-Fixed bias-correction scheme. The results underlined the importance of validating daily SREs, as they had different rainfall detection capabilities in the CKB. The FEWS-RFE∼11 km performed best, providing better results of descriptive and categorical statistics than the other three SREs, although bias decomposition showed that all SREs underestimated rainfall. The analysis showed that the most reliable SREs performance analysis indicator were the frequency of "miss" rainfall events and the "miss-bias", as they directly indicated SREs' sensitivity and bias of rainfall detection, respectively. The Time Varying and Space Fixed (TVSF) bias-correction scheme, improved some error measures but resulted in the reduction of the spatial correlation distance, thus increased, already high, spatial rainfall variability of all the four SREs. This study highlighted SREs as valuable source of daily rainfall data providing good spatio-temporal data coverage especially suitable for areas with limited rain gauges, such as the CKB, but also emphasized SREs' drawbacks, creating avenue for follow up research.

Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

NASA Astrophysics Data System (ADS)

Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

2015-12-01

Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is the analysis of rainfall fields via first-order statistical properties, scaling functions, structure functions and spectral analysis, taking into account cloud-motion directions over mountainous slopes (windward/leeward side) and timing of the diurnal cycle. The analysis is developed for some Colombia's locations.

Assessing future changes in the occurrence of rainfall-induced landslides at a regional scale.

PubMed

Gariano, S L; Rianna, G; Petrucci, O; Guzzetti, F

2017-10-15

According to the fifth report of the Intergovernmental Panel on Climate Change, an increase in the frequency and the intensity of extreme rainfall is expected in the Mediterranean area. Among different impacts, this increase might result in a variation in the frequency and the spatial distribution of rainfall-induced landslides, and in an increase in the size of the population exposed to landslide risk. We propose a method for the regional-scale evaluation of future variations in the occurrence of rainfall-induced landslides, in response to changes in rainfall regimes. We exploit information on the occurrence of 603 rainfall-induced landslides in Calabria, southern Italy, in the period 1981-2010, and daily rainfall data recorded in the same period in the region. Furthermore, we use high-resolution climate projections based on RCP4.5 and RCP8.5 scenarios. In particular, we consider the mean variations between a 30-year future period (2036-2065) and the reference period 1981-2010 in three variables assumed as proxy for landslide activity: annual rainfall, seasonal cumulated rainfall, and annual maxima of daily rainfall. Based on reliable correlations between landslide occurrence and weather variables estimated in the reference period, we assess future variations in rainfall-induced landslide occurrence for all the municipalities of Calabria. A +45.7% and +21.2% average regional variation in rainfall-induced landslide occurrence is expected in the region for the period 2036-2065, under the RCP4.5 and RCP8.5 scenario, respectively. We also investigate the future variations in the impact of rainfall-induced landslides on the population of Calabria. We find a +80.2% and +54.5% increase in the impact on the population for the period 2036-2065, under the RCP4.5 and RCP8.5 scenario, respectively. The proposed method is quantitative and reproducible, thus it can be applied in similar regions, where adequate landslide and rainfall information is available. Copyright © 2017 Elsevier B.V. All rights reserved.

Runoff process in the Miyake-jima Island after Eruption in 2000

NASA Astrophysics Data System (ADS)

Tagata, Satoshi; Itoh, Takahiro; Miyamoto, Kuniaki; Ishizuka, Tadanori

2014-05-01

Hydrological environment in a basin can be changed completely due to volcanic eruption. Huge volume of tephra was yielded due to eruptions in 2000 in the Miyake-jima Island, Japan. Hydrological monitoring was conducted at four observation sites with several hundred m2 in a basin. Those were decided by the distribution of thickness and the grain size of the tephra. Rainfall intensity was measured by a tipping bucket type raingauge and flow discharge was calculated by the over flow depth in a flow gauging weir in the monitoring. However, the runoff rate did not relate to the grain size of tephra and the thickness of tephra deposition, according to measured data of rainfall intensity and runoff discharge. Supposing that if total runoff in one rainfall event is equal to the summation of rainfall over a threshold, the value of the threshold must be the loss rainfall intensity, the value of the threshold corresponds to the infiltration for the rainfall intensity. The relationships between loss rainfall intensity and the antecedent precipitation are calculated using measured rainfall and runoff data in every rainfall event, focusing on that the antecedent precipitation before occurrence of surface runoff approximately corresponds to the water contents under the slope surface. In present study, the results obtained through data analyses are summarized as follows: (1) There are some values for the threshold values, and the loss rainfall intensity approaches to some constant value if the value of the antecedent precipitation increases. The constant value corresponds to the saturated infiltration. (2) The loss rainfall intensity must be vertical unsaturated infiltration, and observed data for water runoff can express that the runoff is given by the excess rainfall intensity more than the loss rainfall intensity. (3) There are two antecedent times for rainfall with several hours and several days, and the saturation ratio before antecedent time at four observation sites can be predicted in the range from sixty to ninety percentages by the water retention curve.

Statistical characterization of spatial patterns of rainfall cells in extratropical cyclones

NASA Astrophysics Data System (ADS)

Bacchi, Baldassare; Ranzi, Roberto; Borga, Marco

1996-11-01

The assumption of a particular type of distribution of rainfall cells in space is needed for the formulation of several space-time rainfall models. In this study, weather radar-derived rain rate maps are employed to evaluate different types of spatial organization of rainfall cells in storms through the use of distance functions and second-moment measures. In particular the spatial point patterns of the local maxima of rainfall intensity are compared to a completely spatially random (CSR) point process by applying an objective distance measure. For all the analyzed radar maps the CSR assumption is rejected, indicating that at the resolution of the observation considered, rainfall cells are clustered. Therefore a theoretical framework for evaluating and fitting alternative models to the CSR is needed. This paper shows how the "reduced second-moment measure" of the point pattern can be employed to estimate the parameters of a Neyman-Scott model and to evaluate the degree of adequacy to the experimental data. Some limitations of this theoretical framework, and also its effectiveness, in comparison to the use of scaling functions, are discussed.

Evaluation of NU-WRF Rainfall Forecasts for IFloodS

NASA Technical Reports Server (NTRS)

Wu, Di; Peters-Lidard, Christa; Tao, Wei-Kuo; Petersen, Walter

2016-01-01

The Iowa Flood Studies (IFloodS) campaign was conducted in eastern Iowa as a pre- GPM-launch campaign from 1 May to 15 June 2013. During the campaign period, real time forecasts are conducted utilizing NASA-Unified Weather Research and Forecasting (NU-WRF) model to support the everyday weather briefing. In this study, two sets of the NU-WRF rainfall forecasts are evaluated with Stage IV and Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation (QPE), with the objective to understand the impact of Land Surface initialization on the predicted precipitation. NU-WRF is also compared with North American Mesoscale Forecast System (NAM) 12 kilometer forecast. In general, NU-WRF did a good job at capturing individual precipitation events. NU-WRF is also able to replicate a better rainfall spatial distribution compare with NAM. Further sensitivity tests show that the high-resolution makes a positive impact on rainfall forecast. The two sets of NU-WRF simulations produce very close rainfall characteristics. The Land surface initialization do not show significant impact on short term rainfall forecast, and it is largely due to the soil conditions during the field campaign period.

Rainfall Across the Globe: Precipitation. The Role of Landmass in Monsoon Development. The Relationship Between Precipitation and Sea Surface Temperature on Decadal Time Scales

NASA Technical Reports Server (NTRS)

Chao, Winston; Schubert, Siegfried; Suarez, Max; Pegion, Philip

2000-01-01

The numerical simulation of precipitation helps scientists understand the complex mechanisms that determine how and why rainfall is distributed across the globe. Simulation aids in the development of forecastin,g efforts that inform policies regarding the management of water resources. Precipitation modeling also provides short-term warnings, for emergencies such as flash floods and mudslides. Just as precipitation modeling can warn of an impending abundance of rainfall, it can help anticipate the absence of rainfall in drought. What constitutes a drought? A meteorological drought simply means that an area is getting a significantly lower amount of rain than usual over a prolonged period of time and an agricultural drought is based on the level of soil moisture.

Technical Report Series on Global Modeling and Data Assimilation. Volume 12; Comparison of Satellite Global Rainfall Algorithms

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Chang, Alfred T. C.; Chiu, Long S.

1997-01-01

Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates.

Beamwidth effects on Z-R relations and area-integrated rainfall

NASA Technical Reports Server (NTRS)

Rosenfeld, Daniel; Atlas, David; Wolff, David B.; Amitai, Eyal

1992-01-01

The effective radar reflectivity Ze measured by a radar is the convolution of the actual distribution of reflectivity with the beam radiation pattern. Because of the nonlinearity between Z and rain rate R, Ze gives a biased estimator of R whenever the reflectivity field is nonuniform. In the presence of sharp horizontal reflectivity gradients, the measured pattern of Ze extends beyond the actual precipitation boundaries to produce false precipitation echoes. When integrated across the radar image of the storm, the false echo areas contribute to the sum to produce overestimates of the areal rainfall. As the range or beamwidth increases, the ratio of measured to actual rainfall increases. Beyond some range, the normal decrease of reflectivity with height dominates and the measured rainfall underestimates the actual amount.

Estimated probabilities, volumes, and inundation areas depths of potential postwildfire debris flows from Carbonate, Slate, Raspberry, and Milton Creeks, near Marble, Gunnison County, Colorado

USGS Publications Warehouse

Stevens, Michael R.; Flynn, Jennifer L.; Stephens, Verlin C.; Verdin, Kristine L.

2011-01-01

During 2009, the U.S. Geological Survey, in cooperation with Gunnison County, initiated a study to estimate the potential for postwildfire debris flows to occur in the drainage basins occupied by Carbonate, Slate, Raspberry, and Milton Creeks near Marble, Colorado. Currently (2010), these drainage basins are unburned but could be burned by a future wildfire. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of postwildfire debris-flow occurrence and debris-flow volumes for drainage basins occupied by Carbonate, Slate, Raspberry, and Milton Creeks near Marble. Data for the postwildfire debris-flow models included drainage basin area; area burned and burn severity; percentage of burned area; soil properties; rainfall total and intensity for the 5- and 25-year-recurrence, 1-hour-duration-rainfall; and topographic and soil property characteristics of the drainage basins occupied by the four creeks. A quasi-two-dimensional floodplain computer model (FLO-2D) was used to estimate the spatial distribution and the maximum instantaneous depth of the postwildfire debris-flow material during debris flow on the existing debris-flow fans that issue from the outlets of the four major drainage basins. The postwildfire debris-flow probabilities at the outlet of each drainage basin range from 1 to 19 percent for the 5-year-recurrence, 1-hour-duration rainfall, and from 3 to 35 percent for 25-year-recurrence, 1-hour-duration rainfall. The largest probabilities for postwildfire debris flow are estimated for Raspberry Creek (19 and 35 percent), whereas estimated debris-flow probabilities for the three other creeks range from 1 to 6 percent. The estimated postwildfire debris-flow volumes at the outlet of each creek range from 7,500 to 101,000 cubic meters for the 5-year-recurrence, 1-hour-duration rainfall, and from 9,400 to 126,000 cubic meters for the 25-year-recurrence, 1-hour-duration rainfall. The largest postwildfire debris-flow volumes were estimated for Carbonate Creek and Milton Creek drainage basins, for both the 5- and 25-year-recurrence, 1-hour-duration rainfalls. Results from FLO-2D modeling of the 5-year and 25-year recurrence, 1-hour rainfalls indicate that the debris flows from the four drainage basins would reach or nearly reach the Crystal River. The model estimates maximum instantaneous depths of debris-flow material during postwildfire debris flows that exceeded 5 meters in some areas, but the differences in model results between the 5-year and 25-year recurrence, 1-hour rainfalls are small. Existing stream channels or topographic flow paths likely control the distribution of debris-flow material, and the difference in estimated debris-flow volume (about 25 percent more volume for the 25-year-recurrence, 1-hour-duration rainfall compared to the 5-year-recurrence, 1-hour-duration rainfall) does not seem to substantially affect the estimated spatial distribution of debris-flow material. Historically, the Marble area has experienced periodic debris flows in the absence of wildfire. This report estimates the probability and volume of debris flow and maximum instantaneous inundation area depths after hypothetical wildfire and rainfall. This postwildfire debris-flow report does not address the current (2010) prewildfire debris-flow hazards that exist near Marble.

Simulation of polycyclic aromatic hydrocarbons transport in multimedia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, L.; Chu, C.J.

1999-07-01

Many studies have indicated that the threat from toxic air pollutants such as VOCs comes not through inhalation by humans while the pollutants are in a gaseous state but through absorption when the pollutants are in a solid state such as in an aerosol or particulate form. Pollutants such as Polycyclic Aromatic Hydrocarbons (PAHs) usually exist in a semi-volatile state. To assess the risk of the PAHs, one needs to estimate the dose of the pollutants to which a human would be exposed through various pathways. In this study, the authors modified a Spatial Multimedia Compartmental Model (SMCM) originally developedmore » by UCLA Professor Cohen to predict the PAHs distribution among multimedia such as air, water, soil and sediment in the Taipei metropolitan area. Three PAHs were considered in this study. They are Benzo(a)pyrene, Pyrene and Chrysene. When PAHs are emitted into atmosphere, physical and chemical mechanisms may redistribute the PAHs among multimedia. Five cases of PAHs distribution in multimedia were simulated: (1) PAHs distribution in a dry condition, (2) PAHs distribution when there are different dry deposition velocities, (3) PAHs distribution under a single rainfall event, (4) PAHs distribution when there are different soil properties, (5) PAHs distribution under a random rainfall case. The simulation results are concluded: (1) In the dry case, the PAHs accumulate mostly in soil and air compartments, (2) Different dry depositing velocities will affect the PAHs distribution among compartments. (3) Different soil properties affect the PAHs concentration in the soil and sediment compartments, (4) The soil PAHs concentrations usually increase for those PAHs with a high solid/gas ratio. (5) The random rainfall only affects the PAHs concentration in the soil.« less

Stochastic rainfall synthesis for urban applications using different regionalization methods

NASA Astrophysics Data System (ADS)

Callau Poduje, A. C.; Leimbach, S.; Haberlandt, U.

2017-12-01

The proper design and efficient operation of urban drainage systems require long and continuous rainfall series in a high temporal resolution. Unfortunately, these time series are usually available in a few locations and it is therefore suitable to develop a stochastic precipitation model to generate rainfall in locations without observations. The model presented is based on an alternating renewal process and involves an external and an internal structure. The members of these structures are described by probability distributions which are site specific. Different regionalization methods based on site descriptors are presented which are used for estimating the distributions for locations without observations. Regional frequency analysis, multiple linear regressions and a vine-copula method are applied for this purpose. An area located in the north-west of Germany is used to compare the different methods and involves a total of 81 stations with 5 min rainfall records. The site descriptors include information available for the whole region: position, topography and hydrometeorologic characteristics which are estimated from long term observations. The methods are compared directly by cross validation of different rainfall statistics. Given that the model is stochastic the evaluation is performed based on ensembles of many long synthetic time series which are compared with observed ones. The performance is as well indirectly evaluated by setting up a fictional urban hydrological system to test the capability of the different methods regarding flooding and overflow characteristics. The results show a good representation of the seasonal variability and good performance in reproducing the sample statistics of the rainfall characteristics. The copula based method shows to be the most robust of the three methods. Advantages and disadvantages of the different methods are presented and discussed.

Atmospheric circulation feedback on west Asian dust and Indian monsoon rainfall

NASA Astrophysics Data System (ADS)

Kaskaoutis, Dimitris; Houssos, Elias; Gautam, Ritesh; Singh, Ramesh; Rashki, Alireza; Dumka, Umesh

2016-04-01

Classification of the atmospheric circulation patterns associated with high aerosol loading events over the Ganges valley, via the synergy of Factor and Cluster analysis techniques, has indicated six different synoptic weather patterns, two of which mostly occur during late pre-monsoon and monsoon seasons (May to September). The current study focuses on examining these two specific clusters that are associated with different mean sea level pressure (MSLP), geopotential height at 700 hPa (Z700) and wind fields that seem to affect the aerosol (mostly dust) emissions and precipitation distribution over the Indian sub-continent. Furthermore, the study reveals that enhanced aerosol presence over the Arabian Sea is positively associated with increased rainfall over the Indian landmass. The increased dust over the Arabian Sea and rainfall over India are associated with deepening of the northwestern Indian and Arabian lows that increase thermal convection and convergence of humid air masses into Indian landmass, resulting in larger monsoon precipitation. For this cluster, negative MSLP and Z700 anomalies are observed over the Arabian Peninsula that enhance the dust outflow from Arabia and, concurrently, the southwesterly air flow resulting in increase in monsoon precipitation over India. The daily precipitation over India is found to be positively correlated with the aerosol loading over the Arabian Sea for both weather clusters, thus verifying recent results from satellite observations and model simulations concerning the modulation of the Indian summer monsoon rainfall by the Arabian dust. The present work reveals that in addition to the radiative impacts of dust on modulating the monsoon rainfall, differing weather patterns favor changes in dust emissions, accumulation as well as rainfall distribution over south Asia.

Attribution of Extreme Rainfall Events in the South of France Using EURO-CORDEX Simulations

NASA Astrophysics Data System (ADS)

Luu, L. N.; Vautard, R.; Yiou, P.

2017-12-01

The Mediterranean region regularly undergoes episodes of intense precipitation in the fall season that exceed 300mm a day. This study focuses on the role of climate change on the dynamics of the events that occur in the South of France. We used an ensemble of 10 EURO-CORDEX model simulations with two horizontal resolutions (EUR-11: 0.11° and EUR-44: 0.44°) for the attribution of extreme rainfall in the fall in the Cevennes mountain range (South of France). The biases of the simulations were corrected with simple scaling adjustment and a quantile correction (CDFt). This produces five datasets including EUR-44 and EUR-11 with and without scaling adjustment and CDFt-EUR-11, on which we test the impact of resolution and bias correction on the extremes. Those datasets, after pooling all of models together, are fitted by a stationary Generalized Extreme Value distribution for several periods to estimate a climate change signal in the tail of distribution of extreme rainfall in the Cévenne region. Those changes are then interpreted by a scaling model that links extreme rainfall with mean and maximum daily temperature. The results show that higher-resolution simulations with bias adjustment provide a robust and confident increase of intensity and likelihood of occurrence of autumn extreme rainfall in the area in current climate in comparison with historical climate. The probability (exceedance probability) of 1-in-1000-year event in historical climate may increase by a factor of 1.8 under current climate with a confident interval of 0.4 to 5.3 following the CDFt bias-adjusted EUR-11. The change of magnitude appears to follow the Clausius-Clapeyron relation that indicates a 7% increase in rainfall per 1oC increase in temperature.

Use of radar QPE for the derivation of Intensity-Duration-Frequency curves in a range of climatic regimes

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2015-12-01

Intensity-Duration-Frequency (IDF) curves are widely used in flood risk management because they provide an easy link between the characteristics of a rainfall event and the probability of its occurrence. Weather radars provide distributed rainfall estimates with high spatial and temporal resolutions and overcome the scarce representativeness of point-based rainfall for regions characterized by large gradients in rainfall climatology. This work explores the use of radar quantitative precipitation estimation (QPE) for the identification of IDF curves over a region with steep climatic transitions (Israel) using a unique radar data record (23 yr) and combined physical and empirical adjustment of the radar data. IDF relationships were derived by fitting a generalized extreme value distribution to the annual maximum series for durations of 20 min, 1 h and 4 h. Arid, semi-arid and Mediterranean climates were explored using 14 study cases. IDF curves derived from the study rain gauges were compared to those derived from radar and from nearby rain gauges characterized by similar climatology, taking into account the uncertainty linked with the fitting technique. Radar annual maxima and IDF curves were generally overestimated but in 70% of the cases (60% for a 100 yr return period), they lay within the rain gauge IDF confidence intervals. Overestimation tended to increase with return period, and this effect was enhanced in arid climates. This was mainly associated with radar estimation uncertainty, even if other effects, such as rain gauge temporal resolution, cannot be neglected. Climatological classification remained meaningful for the analysis of rainfall extremes and radar was able to discern climatology from rainfall frequency analysis.

Stemflow-induced processes of soil water storage

NASA Astrophysics Data System (ADS)

Germer, Sonja

2013-04-01

Compared to stemflow production studies only few studies deal with the fate of stemflow at the near-stem soil. To investigate stemflow contribution to the root zone soil moisture by young and adult babassu palms (Attalea speciosa Mart.), I studied stemflow generation, subsequent soil water percolation and root distributions. Rainfall, stemflow and perched water tables were monitored on an event basis. Perched water tables were monitored next to adult palms at two depths and three stem distances. Dye tracer experiments monitored stemflow-induced preferential flow paths. Root distributions of fine and coarse roots were related to soil water redistribution. Average rainfall-collecting area per adult palm was 6.4 m², but variability between them was high. Funneling ratios ranged between 16-71 and 4-55 for adult and young palms, respectively. Nonetheless, even very small rainfall events of 1 mm can generate stemflow. On average, 9 liters of adult palm stemflow were intercepted and stemflow tended to decrease for-high intensity rainfall events. Young babassu palms funneled rainfall via their fronds, directly to their subterranean stems. The funneling of rainfall towards adult palm stems, in contrast, led to great stemflow fluxes down to the soil and induced initial horizontal water flows through the soil, leading to perched water tables next to palms, even after small rainfall events. The perched water tables extended, however, only a few decimeters from palm stems. After perched water tables became established, vertical percolation through the soil dominated. To my knowledge, this process has not been described before, and it can be seen as an addition to the two previously described stemflow-induced processes of Horton overland flow and fast, deep percolation along roots. This study has demonstrated that Babassu palms funnel water to their stems and subsequently store it in the soil next to their stems in areas where coarse root length density is very high. This might partly explain the competitive position of babassu palms on pastures or secondary forests.

How effective is the new generation of GPM satellite precipitation in characterizing the rainfall variability over Malaysia?

NASA Astrophysics Data System (ADS)

Mahmud, Mohd Rizaludin; Hashim, Mazlan; Reba, Mohd Nadzri Mohd

2017-08-01

We investigated the potential of the new generation of satellite precipitation product from the Global Precipitation Mission (GPM) to characterize the rainfall in Malaysia. Most satellite precipitation products have limited ability to precisely characterize the high dynamic rainfall variation that occurred at both time and scale in this humid tropical region due to the coarse grid size to meet the physical condition of the smaller land size, sub-continent and islands. Prior to the status quo, an improved satellite precipitation was required to accurately measure the rainfall and its distribution. Subsequently, the newly released of GPM precipitation product at half-hourly and 0.1° resolution served an opportunity to anticipate the aforementioned conflict. Nevertheless, related evidence was not found and therefore, this study made an initiative to fill the gap. A total of 843 rain gauges over east (Borneo) and west Malaysia (Peninsular) were used to evaluate the rainfall the GPM rainfall data. The assessment covered all critical rainy seasons which associated with Asian Monsoon including northeast (Nov. - Feb.), southwest (May - Aug.) and their subsequent inter-monsoon period (Mar. - Apr. & Sep. - Oct.). The ability of GPM to provide quantitative rainfall estimates and qualitative spatial rainfall patterns were analysed. Our results showed that the GPM had good capacity to depict the spatial rainfall patterns in less heterogeneous rainfall patterns (Spearman's correlation, 0.591 to 0.891) compared to the clustered one (r = 0.368 to 0.721). Rainfall intensity and spatial heterogeneity that is largely driven by seasonal monsoon has significant influence on GPM ability to resolve local rainfall patterns. In quantitative rainfall estimation, large errors can be primarily associated with the rainfall intensity increment. 77% of the error variation can be explained through rainfall intensity particularly the high intensity (> 35 mm d-1). A strong relationship between GPM rainfall and error was found from heavy ( 35 mm d-1) to violent rain (160 mm d-1). The output of this study provides reference regarding the performance of GPM data for respective hydrology studies in this region.

Rainfall simulation in education

NASA Astrophysics Data System (ADS)

Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

2016-04-01

Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain occurs. The MSc level course 'Fundamentals of Land Management' students carry out a hands-on practical in which they compare soil type and design and evaluate the effect of soil and water conservation measures. Also, MSc thesis research is being carried out using this facility. For instance, the distribution and movement of pesticide Glyphosate with sediment transportation was being quantified using the rainfall simulation facility.

Experimental Investigation of Rainfall Impact on Overland Flow Driven Erosion Processes and Flow Hydrodynamics on a Steep Hillslope

NASA Astrophysics Data System (ADS)

Tian, P.; Xu, X.; Pan, C.; Hsu, K. L.; Yang, T.

2016-12-01

Few attempts have been made to investigate the quantitative effects of rainfall on overland flow driven erosion processes and flow hydrodynamics on steep hillslopes under field conditions. Field experiments were performed in flows for six inflow rates (q: 6-36 Lmin-1m-1) with and without rainfall (60 mm h-1) on a steep slope (26°) to investigate: (1) the quantitative effects of rainfall on runoff and sediment yield processes, and flow hydrodynamics; (2) the effect of interaction between rainfall and overland flow on soil loss. Results showed that the rainfall increased runoff coefficients and the fluctuation of temporal variations in runoff. The rainfall significantly increased soil loss (10.6-68.0%), but this increment declined as q increased. When the interrill erosion dominated (q=6 Lmin-1m-1), the increment in the rill erosion was 1.5 times that in the interrill erosion, and the effect of the interaction on soil loss was negative. When the rill erosion dominated (q=6-36 Lmin-1m-1), the increment in the interrill erosion was 1.7-8.8 times that in the rill erosion, and the effect of the interaction on soil loss became positive. The rainfall was conducive to the development of rills especially for low inflow rates. The rainfall always decreased interrill flow velocity, decreased rill flow velocity (q=6-24 Lmin-1m-1), and enhanced the spatial uniformity of the velocity distribution. Under rainfall disturbance, flow depth, Reynolds number (Re) and resistance were increased but Froude number was reduced, and lower Re was needed to transform a laminar flow to turbulent flow. The rainfall significantly increased flow shear stress (τ) and stream power (φ), with the most sensitive parameters to sediment yield being τ (R2=0.994) and φ (R2=0.993), respectively, for non-rainfall and rainfall conditions. Compared to non-rainfall conditions, there was a reduction in the critical hydrodynamic parameters of mean flow velocity, τ, and φ by the rainfall. These findings provide a better understanding on the influence mechanism of rainfall impact on hillslope erosion processes.

Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

NASA Astrophysics Data System (ADS)

Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara

2015-09-01

Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis.

Effects of Drought, Pest Pressure and Light Availability on Seedling Establishment and Growth: Their Role for Distribution of Tree Species across a Tropical Rainfall Gradient

PubMed Central

Gaviria, Julian; Engelbrecht, Bettina M. J.

2015-01-01

Tree species distributions associated with rainfall are among the most prominent patterns in tropical forests. Understanding the mechanisms shaping these patterns is important to project impacts of global climate change on tree distributions and diversity in the tropics. Beside direct effects of water availability, additional factors co-varying with rainfall have been hypothesized to play an important role, including pest pressure and light availability. While low water availability is expected to exclude drought-intolerant wet forest species from drier forests (physiological tolerance hypothesis), high pest pressure or low light availability are hypothesized to exclude dry forest species from wetter forests (pest pressure gradient and light availability hypothesis, respectively). To test these hypotheses at the seed-to-seedling transition, the potentially most critical stage for species discrimination, we conducted a reciprocal transplant experiment combined with a pest exclosure treatment at a wet and a dry forest site in Panama with seeds of 26 species with contrasting origin. Establishment success after one year did not reflect species distribution patterns. However, in the wet forest, wet origin species had a home advantage over dry forest species through higher growth rates. At the same time, drought limited survival of wet origin species in the dry forest, supporting the physiological tolerance hypothesis. Together these processes sort species over longer time frames, and exclude species outside their respective home range. Although we found pronounced effects of pests and some effects of light availability on the seedlings, they did not corroborate the pest pressure nor light availability hypotheses at the seed-to-seedling transition. Our results underline that changes in water availability due to climate change will have direct consequences on tree regeneration and distributions along tropical rainfall gradients, while indirect effects of light and pests are less important. PMID:26619138

The impact of annual and seasonal rainfall patterns on growth and phenology of emergent tree species in Southeastern Amazonia, Brazil

Treesearch

James Grogan; Mark Schulze

2012-01-01

Understanding tree growth in response to rainfall distribution is critical to predicting forest and species population responses to climate change. We investigated inter-annual and seasonal variation in stem diameter by three emergent tree species in a seasonally dry tropical forest in southeast Pará, Brazil. Annual diameter growth rates by Swietenia macrophylla...

Accuration of Time Series and Spatial Interpolation Method for Prediction of Precipitation Distribution on the Geographical Information System

NASA Astrophysics Data System (ADS)

Prasetyo, S. Y. J.; Hartomo, K. D.

2018-01-01

The Spatial Plan of the Province of Central Java 2009-2029 identifies that most regencies or cities in Central Java Province are very vulnerable to landslide disaster. The data are also supported by other data from Indonesian Disaster Risk Index (In Indonesia called Indeks Risiko Bencana Indonesia) 2013 that suggest that some areas in Central Java Province exhibit a high risk of natural disasters. This research aims to develop an application architecture and analysis methodology in GIS to predict and to map rainfall distribution. We propose our GIS architectural application of “Multiplatform Architectural Spatiotemporal” and data analysis methods of “Triple Exponential Smoothing” and “Spatial Interpolation” as our significant scientific contribution. This research consists of 2 (two) parts, namely attribute data prediction using TES method and spatial data prediction using Inverse Distance Weight (IDW) method. We conduct our research in 19 subdistricts in the Boyolali Regency, Central Java Province, Indonesia. Our main research data is the biweekly rainfall data in 2000-2016 Climatology, Meteorology, and Geophysics Agency (In Indonesia called Badan Meteorologi, Klimatologi, dan Geofisika) of Central Java Province and Laboratory of Plant Disease Observations Region V Surakarta, Central Java. The application architecture and analytical methodology of “Multiplatform Architectural Spatiotemporal” and spatial data analysis methodology of “Triple Exponential Smoothing” and “Spatial Interpolation” can be developed as a GIS application framework of rainfall distribution for various applied fields. The comparison between the TES and IDW methods show that relative to time series prediction, spatial interpolation exhibit values that are approaching actual. Spatial interpolation is closer to actual data because computed values are the rainfall data of the nearest location or the neighbour of sample values. However, the IDW’s main weakness is that some area might exhibit the rainfall value of 0. The representation of 0 in the spatial interpolation is mainly caused by the absence of rainfall data in the nearest sample point or too far distance that produces smaller weight.

Estimation of Rainfall Rates from Passive Microwave Remote Sensing.

NASA Astrophysics Data System (ADS)

Sharma, Awdhesh Kumar

Rainfall rates have been estimated using the passive microwave and visible/infrared remote sensing techniques. Data of September 14, 1978 from the Scanning Multichannel Microwave Radiometer (SMMR) on board SEA SAT-A and the Visible and Infrared Spin Scan Radiometer (VISSR) on board GOES-W (Geostationary Operational Environmental Satellite - West) was obtained and analyzed for rainfall rate retrieval. Microwave brightness temperatures (MBT) are simulated, using the microwave radiative transfer model (MRTM) and atmospheric scattering models. These MBT were computed as a function of rates of rainfall from precipitating clouds which are in a combined phase of ice and water. Microwave extinction due to ice and liquid water are calculated using Mie-theory and Gamma drop size distributions. Microwave absorption due to oxygen and water vapor are based on the schemes given by Rosenkranz, and Barret and Chung. The scattering phase matrix involved in the MRTM is found using Eddington's two stream approximation. The surface effects due to winds and foam are included through the ocean surface emissivity model. Rainfall rates are then inverted from MBT using the optimization technique "Leaps and Bounds" and multiple linear regression leading to a relationship between the rainfall rates and MBT. This relationship has been used to infer the oceanic rainfall rates from SMMR data. The VISSR data has been inverted for the rainfall rates using Griffith's scheme. This scheme provides an independent means of estimating rainfall rates for cross checking SMMR estimates. The inferred rainfall rates from both techniques have been plotted on a world map for comparison. A reasonably good correlation has been obtained between the two estimates.

Mechanisms for Diurnal Variability of Global Tropical Rainfall Observed from TRMM

NASA Technical Reports Server (NTRS)

Yang, Song; Smith, Eric A.

2004-01-01

The behavior and various controls of diurnal variability in tropical-subtropical rainfall are investigated using Tropical Rainfall Measuring Mission (TRMM) precipitation measurements retrieved from: (1) TRMM Microwave Imager (TMI), (2) Precipitation Radar (PR), and (3) TMI/PR Combined, standard level 2 algorithms for the 1998 annual cycle. Results show that the diurnal variability characteristics of precipitation are consistent for all three algorithms, providing assurance that TRMM retrievals are providing consistent estimates of rainfall variability. As anticipated, most ocean areas exhibit more rainfall at night, while over most land areas rainfall peaks during daytime ,however, various important exceptions are found. The dominant feature of the oceanic diurnal cycle is a rainfall maximum in late-evening/early-morning (LE-EM) hours, while over land the dominant maximum occurs in the mid- to late-afternoon (MLA). In conjunction with these maxima are pronounced seasonal variations of the diurnal amplitudes. Amplitude analysis shows that the diurnal pattern and its seasonal evolution are closely related to the rainfall accumulation pattern and its seasonal evolution. In addition, the horizontal distribution of diurnal variability indicates that for oceanic rainfall there is a secondary MLA maximum, co-existing with the LE-EM maximum, at latitudes dominated by large scale convergence and deep convection. Analogously, there is a preponderance for an LE-EM maximum over land, co-existing with the stronger MLA maximum, although it is not evident that this secondary continental feature is closely associated with the large scale circulation. The ocean results clearly indicate that rainfall diurnal variability associated with large scale convection is an integral part of the atmospheric general circulation.

The Role of Rainfall Patterns in Seasonal Malaria Transmission

NASA Astrophysics Data System (ADS)

Bomblies, A.

2010-12-01

Seasonal total precipitation is well known to affect malaria transmission because Anopheles mosquitoes depend on standing water for breeding habitat. However, the within-season temporal pattern of the rainfall influences persistence of standing water and thus rainfall patterns also affect mosquito population dynamics. In this talk, I show that intraseasonal rainfall pattern describes 40% of the variance in simulated mosquito abundance in a Niger Sahel village where malaria is endemic but highly seasonal, demonstrating the necessity for detailed distributed hydrology modeling to explain the variance from this important effect. I apply a field validated, high spatial- and temporal-resolution hydrology model coupled with an entomology model. Using synthetic rainfall time series generated using a stationary first-order Markov Chain model, I hold all variables except hourly rainfall constant, thus isolating the contribution of rainfall pattern to variance in mosquito abundance. I further show the utility of hydrology modeling to assess precipitation effects by analyzing collected water. Time-integrated surface area of pools explains 70% of the variance in mosquito abundance, and time-integrated surface area of pools persisting longer than seven days explains 82% of the variance, showing an improved predictive ability when pool persistence is explicitly modeled at high spatio-temporal resolution. I extend this analysis to investigate the impacts of this effect on malaria vector mosquito populations under climate shift scenarios, holding all climate variables except precipitation constant. In these scenarios, rainfall mean and variance change with climatic change, and the modeling approach evaluates the impact of non-stationarity in rainfall and the associated rainfall patterns on expected mosquito activity.

Calibration of three rainfall simulators with automatic measurement methods

NASA Astrophysics Data System (ADS)

Roldan, Margarita

2010-05-01

CALIBRATION OF THREE RAINFALL SIMULATORS WITH AUTOMATIC MEASUREMENT METHODS M. Roldán (1), I. Martín (2), F. Martín (2), S. de Alba(3), M. Alcázar(3), F.I. Cermeño(3) 1 Grupo de Investigación Ecología y Gestión Forestal Sostenible. ECOGESFOR-Universidad Politécnica de Madrid. E.U.I.T. Forestal. Avda. Ramiro de Maeztu s/n. Ciudad Universitaria. 28040 Madrid. margarita.roldan@upm.es 2 E.U.I.T. Forestal. Avda. Ramiro de Maeztu s/n. Ciudad Universitaria. 28040 Madrid. 3 Facultad de Ciencias Geológicas. Universidad Complutense de Madrid. Ciudad Universitaria s/n. 28040 Madrid The rainfall erosivity is the potential ability of rain to cause erosion. It is function of the physical characteristics of rainfall (Hudson, 1971). Most expressions describing erosivity are related to kinetic energy or momentum and so with drop mass or size and fall velocity. Therefore, research on factors determining erosivity leds to the necessity to study the relation between fall height and fall velocity for different drop sizes, generated in a rainfall simulator (Epema G.F.and Riezebos H.Th, 1983) Rainfall simulators are one of the most used tools for erosion studies and are used to determine fall velocity and drop size. Rainfall simulators allow repeated and multiple measurements The main reason for use of rainfall simulation as a research tool is to reproduce in a controlled way the behaviour expected in the natural environment. But in many occasions when simulated rain is used in order to compare it with natural rain, there is a lack of correspondence between natural and simulated rain and this can introduce some doubt about validity of data because the characteristics of natural rain are not adequately represented in rainfall simulation research (Dunkerley D., 2008). Many times the rainfall simulations have high rain rates and they do not resemble natural rain events and these measures are not comparables. And besides the intensity is related to the kinetic energy which determines the rainfall erosivity (Dunkerley D., 2008). A special attention must be paid to the experimental design and the understanding of the measurements obtained. The objective of this study is the calibration of simulated rain. In order to achieve this objective a rainfall simulator and disdrometer have been used. The first one is a nozzle type and its sprinkler system was located at different heights, three different spray nozzles supplied the water with known pressure. The simulated rainfall presented different intensities, drop diameters distribution and so different kinetic energy. The instrument of measurement for registering data is the disdrometer (Joss and Waldvogel, 1967) which provides the total number of impacts of raindrops, minute after minute, grouped in 20 classes according to their size which allows the real time measurements of the drop diameter distributions, kinetic energy per minute and intensity per minute. Disdrometer registers data in supposing drops fall down with terminal velocity but this velocity can reach up to 7-9 m of height in natural raindrop, depending on drop diameters. If the height of simulator is high enough the drops could recuperate their terminal velocities and their kinetic energies could be true. The nozzles were located to different heights in order to achieve these terminal velocities. These heights vary depending on the nozzles used, when the drops supplied by the nozzle are smaller the terminal velocity is reached sooner than when the drops are bigger. The physical characteristics of simulated rainfall in the three nozzles, intensity, drop diameter distributions and kinetic energy, are known and steady when the drops supplied by the nozzles reach terminal velocities.

Comparison between intensity- duration thresholds and cumulative rainfall thresholds for the forecasting of landslide

NASA Astrophysics Data System (ADS)

Lagomarsino, Daniela; Rosi, Ascanio; Rossi, Guglielmo; Segoni, Samuele; Catani, Filippo

2014-05-01

This work makes a quantitative comparison between the results of landslide forecasting obtained using two different rainfall threshold models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds in an area of northern Tuscany of 116 km2. The first methodology identifies rainfall intensity-duration thresholds by means a software called MaCumBA (Massive CUMulative Brisk Analyzer) that analyzes rain-gauge records, extracts the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram, and identifies thresholds that define the lower bounds of the I-D values. A back analysis using data from past events can be used to identify the threshold conditions associated with the least amount of false alarms. The second method (SIGMA) is based on the hypothesis that anomalous or extreme values of rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations in the proposed methodology. The definition of intensity-duration rainfall thresholds requires the combined use of rainfall measurements and an inventory of dated landslides, whereas SIGMA model can be implemented using only rainfall data. These two methodologies were applied in an area of 116 km2 where a database of 1200 landslides was available for the period 2000-2012. The results obtained are compared and discussed. Although several examples of visual comparisons between different intensity-duration rainfall thresholds are reported in the international literature, a quantitative comparison between thresholds obtained in the same area using different techniques and approaches is a relatively undebated research topic.

Missing pieces of the puzzle: understanding decadal variability of Sahel Rainfall

NASA Astrophysics Data System (ADS)

Vellinga, Michael; Roberts, Malcolm; Vidale, Pier-Luigi; Mizielinski, Matthew; Demory, Marie-Estelle; Schiemann, Reinhard; Strachan, Jane; Bain, Caroline

2015-04-01

The instrumental record shows that substantial decadal fluctuations affected Sahel rainfall from the West African monsoon throughout the 20th century. Climate models generally underestimate the magnitude of decadal Sahel rainfall changes compared to observations. This shows that the processes that control low-frequency Sahel rainfall change are misrepresented in most CMIP5-era climate models. Reliable climate information of future low-frequency rainfall changes thus remains elusive. Here we identify key processes that control the magnitude of the decadal rainfall recovery in the Sahel since the mid-1980s. We show its sensitivity to model resolution and physics in a suite of experiments with global HadGEM3 model configurations at resolutions between 130-25 km. The decadal rainfall trend increases with resolution and at 60-25 km falls within the observed range. Higher resolution models have stronger increases of moisture supply and of African Easterly wave activity. Easterly waves control the occurrence of strong organised rainfall events which carry most of the decadal trend. Weak rainfall events occur too frequently at all resolutions and at low resolution contribute substantially to the decadal trend. All of this behaviour is seen across CMIP5, including future scenarios. Additional simulations with a global 12km version of HadGEM3 show that treating convection explicitly dramatically improves the properties of Sahel rainfall systems. We conclude that interaction between convective scale and global scale processes is key to decadal rainfall changes in the Sahel. This work is distributed under the Creative Commons Attribution 3.0 Unported License together with an author copyright. This license does not conflict with the regulations of the Crown Copyright.Crown Copyright

Dynamic Rainfall Patterns and the Simulation of Changing Scenarios: A behavioral watershed response

NASA Astrophysics Data System (ADS)

Chu, M.; Guzman, J.; Steiner, J. L.; Hou, C.; Moriasi, D.

2015-12-01

Rainfall is one of the fundamental drivers that control hydrologic responses including runoff production and transport phenomena that consequently drive changes in aquatic ecosystems. Quantifying the hydrologic responses to changing scenarios (e.g., climate, land use, and management) using environmental models requires a realistic representation of probable rainfall in its most sensible spatio-temporal dimensions matching that of the phenomenon under investigation. Downscaling projected rainfall from global circulation models (GCMs) is the most common practice in deriving rainfall datasets to be used as main inputs to hydrologic models which in turn are used to assess the impacts of climate changes on ecosystems. Downscaling assumes that local climate is a combination of large-scale climatic/atmospheric conditions and local conditions. However, the representation of the latter is generally beyond the capacity of current GCMs. The main objective of this study was to develop and implement a synthetic rainfall generator to downscale expected rainfall trends to 1 x 1 km rainfall daily patterns that mimic the dynamic propagation of probability distribution functions (pdf) derived from historic rainfall data (rain-gauge or radar estimated). Future projections were determined based on actual and expected changes in the pdf and stochastic processes to account for variability. Watershed responses in terms of streamflow and nutrients loads were evaluated using synthetically generated rainfall patterns and actual data. The framework developed in this study will allow practitioners to generate rainfall datasets that mimic the temporal and spatial patterns exclusive to their study area under full disclosure of the uncertainties involved. This is expected to provide significantly more accurate environmental models than is currently available and would provide practitioners with ways to evaluate the spectrum of systemic responses to changing scenarios.

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

NASA Astrophysics Data System (ADS)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

USGS Publications Warehouse

Friedel, M.J.

2008-01-01

A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2-26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias. ?? Springer Science+Business Media B.V. 2007.

Effects of episodic rainfall on a subterranean estuary

NASA Astrophysics Data System (ADS)

Yu, Xiayang; Xin, Pei; Lu, Chunhui; Robinson, Clare; Li, Ling; Barry, D. A.

2017-07-01

Numerical simulations were conducted to examine the effect of episodic rainfall on nearshore groundwater dynamics in a tidally influenced unconfined coastal aquifer, with a focus on both long-term (yearly) and short-term (daily) behavior of submarine groundwater discharge (SGD) and seawater intrusion (SWI). The results showed nonlinear interactions among the processes driven by rainfall, tides, and density gradients. Rainfall-induced infiltration increased the yearly averaged fresh groundwater discharge to the ocean but reduced the extents of the saltwater wedge and upper saline plume as well as the total rate of seawater circulation through both zones. Overall, the net effect of the interactions led to an increase of the SGD. The nearshore groundwater responded to individual rainfall events in a delayed and cumulative fashion, as evident in the variations of daily averaged SGD and salt stored in the saltwater wedge (quantifying the extent of SWI). A generalized linear model (GLM) along with a Gamma distribution function was developed to describe the delayed and prolonged effect of rainfall events on short-term groundwater behavior. This model validated with results of daily averaged SGD and SWI from the simulations of groundwater and solute transport using independent rainfall data sets, performed well in predicting the behavior of the nearshore groundwater system under the combined influence of episodic rainfall, tides, and density gradients. The findings and developed GLM form a basis for evaluating and predicting SGD, SWI, and associated mass fluxes from unconfined coastal aquifers under natural conditions, including episodic rainfall.

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

NASA Astrophysics Data System (ADS)

Leonarduzzi, Elena; Molnar, Peter; McArdell, Brian W.

2017-08-01

A high-resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity-duration ID curves and validated their performance. The best predictive performance was obtained by the intensity-duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country-wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high-quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack-knife and cross-validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

The variability of the rainfall rate as a function of area

NASA Astrophysics Data System (ADS)

Jameson, A. R.; Larsen, M. L.

2016-01-01

Distributions of drop sizes can be expressed as DSD = Nt × PSD, where Nt is the total number of drops in a sample and PSD is the frequency distribution of drop diameters (D). Their discovery permitted remote sensing techniques for rainfall estimation using radars and satellites measuring over large domains of several kilometers. Because these techniques depend heavily on higher moments of the PSD, there has been a bias toward attributing the variability of the intrinsic rainfall rates R over areas (σR) to the variability of the PSDs. While this variability does increase up to a point with increasing domain dimension L, the variability of the rainfall rate R also depends upon the variability in the total number of drops Nt. We show that while the importance of PSDs looms large for small domains used in past studies, it is the variability of Nt that dominates the variability of R as L increases to 1 km and beyond. The PSDs contribute to the variability of R through the relative dispersion of χ = D3Vt, where Vt is the terminal fall speed of drops of diameter D. However, the variability of χ is inherently limited because drop sizes and fall speeds are physically limited. In contrast, it is shown that the variance of Nt continuously increases as the domain expands for physical reasons explained below. Over domains larger than around 1 km, it is shown that Nt dominates the variance of the rainfall rate with increasing L regardless of the PSD.

[Advance to the research of the climate factor effect on the distribution of plague].

PubMed

Zhang, A P; Wei, R J; Xiong, H M; Wang, Z Y

2016-05-01

Plague is an anthropozoonotic disease caused by the Yersinia pestis ,which developed by many factors including local climate factors. In recent years, more and more studies on the effects of climate on plague were conducted. According to the researches, climate factors (mainly the rainfall and temperature) affected the development and distribution of plague by influencing the abundance of plague host animals and fleas index. The climate also affected the epidemic dynamics and the scope of plague. There were significant differences existing in the influence of climate on the palgue developed in the north and south China. In the two different plague epidemic systems, the solitary Daurian ground squirrel-flea-plague and the social Mongolian gerbil-flea-plague, the obvious population differences existed among the responses of the host animal to the climate changes. Although the internal relationship between the rainfall, the flea index, the density of rodents and the plague supported the nutritional cascade hypothesis, it can not prove that there is a clear causality between the occurrence of plague and rainfall. So the influence of climate factors on plague distribution can only be used for early forecasting and warning of the plague.

Integrating Agent Models of Subsistence Farming With Dynamic Models of Water Distribution

NASA Astrophysics Data System (ADS)

Bithell, M.; Brasington, J.

2004-12-01

Subsistence farming communities are dependent on the landscape to provide the resource base upon which their societies can be built. A key component of this is the role of climate, and the feedback between rainfall, crop growth and land clearance, and their coupling to the hydrological cycle. Temporal fluctuations in rainfall on timescales from annual through to decadal and longer, and the associated changes in in the spatial distribution of water availability mediated by the soil-type, slope and landcover determine the locations within the landscape that can support agriculture, and control sustainability of farming practices. We seek to make an integrated modelling system to represent land use change by coupling an agent based model of subsistence farming, and the associated exploitation of natural resources, to a realistic representation of the hydrology at the catchment scale, using TOPMODEL to map the spatial distribution of crop water stress for given time-series of rainfall. In this way we can, for example, investigate how demographic changes and associated removal of forest cover influence the possibilities for field locations within the catchment, through changes in ground water availability. The framework for this modelling exercise will be presented and preliminary results from this system will be discussed.

Improved estimation of heavy rainfall by weather radar after reflectivity correction and accounting for raindrop size distribution variability

NASA Astrophysics Data System (ADS)

Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

2015-04-01

Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z-R) and radar reflectivity-specific attenuation (Z-k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.

Regional patterns of the change in annual-mean tropical rainfall under global warming

NASA Astrophysics Data System (ADS)

Huang, P.

2013-12-01

Projection of the change in tropical rainfall under global warming is a major challenge with great societal implications. The current study analyzes the 18 models from the Coupled Models Intercomparison Project, and investigates the regional pattern of annual-mean rainfall change under global warming. With surface warming, the climatological ascending pumps up increased surface moisture and leads rainfall increase over the tropical convergence zone (wet-get-wetter effect), while the pattern of sea surface temperature (SST) increase induces ascending flow and then increasing rainfall over the equatorial Pacific and the northern Indian Ocean where the local oceanic warming exceeds the tropical mean temperature increase (warmer-get-wetter effect). The background surface moisture and SST also can modify warmer-get-wetter effect: the former can influence the moisture change and contribute to the distribution of moist instability change, while the latter can suppress the role of instability change over the equatorial eastern Pacific due to the threshold effect of convection-SST relationship. The wet-get-wetter and modified warmer-get-wetter effects form a hook-like pattern of rainfall change over the tropical Pacific and an elliptic pattern over the northern Indian Ocean. The annual-mean rainfall pattern can be partly projected based on current rainfall climatology, while it also has great uncertainties due to the uncertain change in SST pattern.

Exploring the relationship between malaria, rainfall intermittency, and spatial variation in rainfall seasonality

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Wimberly, M. C.; Henebry, G. M.; Senay, G. B.

2014-12-01

Malaria is a major public health problem throughout tropical regions of the world. Successful prevention and treatment of malaria requires an understanding of the environmental factors that affect the life cycle of both the malaria pathogens, protozoan parasites, and its vectors, anopheline mosquitos. Because the egg, larval, and pupal stages of mosquito development occur in aquatic habitats, information about the spatial and temporal distribution of rainfall is critical for modeling malaria risk. Potential sources of hydrological data include satellite-derived rainfall estimates (TRMM and GPM), evapotranspiration derived from a simplified surface energy balance, and estimates of soil moisture and fractional water cover from passive microwave imagery. Previous studies have found links between malaria cases and total monthly or weekly rainfall in areas where both are highly seasonal. However it is far from clear that monthly or weekly summaries are the best metrics to use to explain malaria outbreaks. It is possible that particular temporal or spatial patterns of rainfall result in better mosquito habitat and thus higher malaria risk. We used malaria case data from the Amhara region of Ethiopia and satellite-derived rainfall estimates to explore the relationship between malaria outbreaks and rainfall with the goal of identifying the most useful rainfall metrics for modeling malaria occurrence. First, we explored spatial variation in the seasonal patterns of both rainfall and malaria cases in Amhara. Second, we assessed the relative importance of different metrics of rainfall intermittency, including alternation of wet and dry spells, the strength of intensity fluctuations, and spatial variability in these measures, in determining the length and severity of malaria outbreaks. We also explored the sensitivity of our results to the choice of method for describing rainfall intermittency and the spatial and temporal scale at which metrics were calculated. Results demonstrate that information about the seasonality and intermittency of rainfall has the potential to improve our understanding of malaria epidemiology and improve our ability to forecast malaria outbreaks.

Disaggregating from daily to sub-daily rainfall under a future climate

NASA Astrophysics Data System (ADS)

Westra, S.; Evans, J.; Mehrotra, R.; Sharma, A.

2012-04-01

We describe an algorithm for disaggregating daily rainfall into sub-daily rainfall 'fragments' (continuous fine-resolution rainfall sequences whose total depth sums to the daily rainfall amount) under a future, warmer climate. The basis of the algorithm is re-sample sub-daily fragments from the historical record conditional on the total daily rainfall amount and a range of atmospheric predictors representative of the future climate. The logic is that as the atmosphere warms, future rainfall patterns will be more reflective of historical rainfall patterns which occurred on warmer days at the same location, or at locations which have an atmospheric profile more reflective of expected future conditions. When looking at the scaling from daily to sub-daily rainfall over the historical record, it was found that the relationship varied significantly by season and by location, with rainfall patterns on warmer seasons or at warmer locations typically showing more intense rain falling over shorter periods compared with cooler seasons and stations. Importantly, by regressing against atmospheric covariates such as temperature this effect was almost entirely eliminated, providing a basis for suggesting the approach may be valid when extrapolating sub-daily sequences to a future climate. The method of fragments algorithm was then applied to nine stations around Australia, and showed that when holding the total daily rainfall constant, the maximum intensity of a short duration (6 minute) rainfall increased by between 4.1% and 13.4% per degree change in temperature for the maximum six minute burst, between 3.1% and 6.8% for the maximum one hour burst, and between 1.5% and 3.5% for the fraction of the day with no rainfall. This highlights that a large proportion of the change to the distribution of precipitation in the future is likely to occur at sub-daily timescales, with significant implications for many hydrological systems.

A gridded hourly rainfall dataset for the UK applied to a national physically-based modelling system

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Blenkinsop, Stephen; Quinn, Niall; Freer, Jim; Coxon, Gemma; Woods, Ross; Bates, Paul; Fowler, Hayley

2016-04-01

An hourly gridded rainfall product has great potential for use in many hydrological applications that require high temporal resolution meteorological data. One important example of this is flood risk management, with flooding in the UK highly dependent on sub-daily rainfall intensities amongst other factors. Knowledge of sub-daily rainfall intensities is therefore critical to designing hydraulic structures or flood defences to appropriate levels of service. Sub-daily rainfall rates are also essential inputs for flood forecasting, allowing for estimates of peak flows and stage for flood warning and response. In addition, an hourly gridded rainfall dataset has significant potential for practical applications such as better representation of extremes and pluvial flash flooding, validation of high resolution climate models and improving the representation of sub-daily rainfall in weather generators. A new 1km gridded hourly rainfall dataset for the UK has been created by disaggregating the daily Gridded Estimates of Areal Rainfall (CEH-GEAR) dataset using comprehensively quality-controlled hourly rain gauge data from over 1300 observation stations across the country. Quality control measures include identification of frequent tips, daily accumulations and dry spells, comparison of daily totals against the CEH-GEAR daily dataset, and nearest neighbour checks. The quality control procedure was validated against historic extreme rainfall events and the UKCP09 5km daily rainfall dataset. General use of the dataset has been demonstrated by testing the sensitivity of a physically-based hydrological modelling system for Great Britain to the distribution and rates of rainfall and potential evapotranspiration. Of the sensitivity tests undertaken, the largest improvements in model performance were seen when an hourly gridded rainfall dataset was combined with potential evapotranspiration disaggregated to hourly intervals, with 61% of catchments showing an increase in NSE between observed and simulated streamflows as a result of more realistic sub-daily meteorological forcing.

Mimic expert judgement through automated procedure for selecting rainfall events responsible for shallow landslide: A statistical approach to validation

NASA Astrophysics Data System (ADS)

Giovanna, Vessia; Luca, Pisano; Carmela, Vennari; Mauro, Rossi; Mario, Parise

2016-01-01

This paper proposes an automated method for the selection of rainfall data (duration, D, and cumulated, E), responsible for shallow landslide initiation. The method mimics an expert person identifying D and E from rainfall records through a manual procedure whose rules are applied according to her/his judgement. The comparison between the two methods is based on 300 D-E pairs drawn from temporal rainfall data series recorded in a 30 days time-lag before the landslide occurrence. Statistical tests, employed on D and E samples considered both paired and independent values to verify whether they belong to the same population, show that the automated procedure is able to replicate the expert pairs drawn by the expert judgment. Furthermore, a criterion based on cumulated distribution functions (CDFs) is proposed to select the most related D-E pairs to the expert one among the 6 drawn from the coded procedure for tracing the empirical rainfall threshold line.

Tropical Rainfall Measuring Mission: Monitoring the Global Tropics for 3 Years and Beyond. 1.1

NASA Technical Reports Server (NTRS)

Shepherd, Marshall; Starr, David OC. (Technical Monitor)

2001-01-01

The Tropical Rainfall Measuring Mission (TRMM) was launched in November 1997 as a joint U.S.-Japanese mission to advance understanding of the global energy and water cycle by providing distributions of rainfall and latent heating over the global tropics. As a part of NASA's Earth System Enterprise, TRMM seeks to understand the mechanisms through which changes in tropical rainfall influence global circulation. Additionally, a goal is to improve the ability to model these processes in order to predict global circulations and rainfall variability at monthly and longer time scales. Such understanding has implications for assessing climate processes related to El Nino/La Nina and Global Warming. TRMM has also provided unexpected and exciting new knowledge and applications in areas related to hurricane monitoring, lightning, pollution, hydrology, and other areas. This CD-ROM includes a self-contained PowerPoint presentation that provides an overview of TRMM and significant science results; a set of data movies or animation; and listings of current TRMM-related publications in the literature.

Comparison between fully distributed model and semi-distributed model in urban hydrology modeling

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Giangola-Murzyn, Agathe; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe

2013-04-01

Water management in urban areas is becoming more and more complex, especially because of a rapid increase of impervious areas. There will also possibly be an increase of extreme precipitation due to climate change. The aims of the devices implemented to handle the large amount of water generate by urban areas such as storm water retention basins are usually twofold: ensure pluvial flood protection and water depollution. These two aims imply opposite management strategies. To optimize the use of these devices there is a need to implement urban hydrological models and improve fine-scale rainfall estimation, which is the most significant input. In this paper we suggest to compare two models and their sensitivity to small-scale rainfall variability on a 2.15 km2 urban area located in the County of Val-de-Marne (South-East of Paris, France). The average impervious coefficient is approximately 34%. In this work two types of models are used. The first one is CANOE which is semi-distributed. Such models are widely used by practitioners for urban hydrology modeling and urban water management. Indeed, they are easily configurable and the computation time is reduced, but these models do not take fully into account either the variability of the physical properties or the variability of the precipitations. An alternative is to use distributed models that are harder to configure and require a greater computation time, but they enable a deeper analysis (especially at small scales and upstream) of the processes at stake. We used the Multi-Hydro fully distributed model developed at the Ecole des Ponts ParisTech. It is an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. Four heavy rainfall events that occurred between 2009 and 2011 are analyzed. The data comes from the Météo-France radar mosaic and the resolution is 1 km in space and 5 min in time. The closest radar of the Météo-France network is a C-band one located at 37 km West. In this work we compare the hydrological response of two models for the 4 rainfall events first with the available radar data. Then a particular focus is made on the impact of small-scale unmeasured rainfall variability (i.e. occurring at scales below the available one). More precisely scaling properties of rainfall are used to generate an ensemble of downscaled rainfall fields (simply by continuing the underlying cascade process whose relevant parameters are estimated on the available range of scales). An ensemble of hydrological responses is then simulated, and the variability within it analyzed. It appears that the associated uncertainty is significant and should be taken into account. Finally we will discuss the interest of deploying X-band radars (which provide an hectometric resolution) in urban environment and the potential benefits of using these models and small-scale rainfall data for the management of sewerage and retentions basin. Further analysis on these issues will be carried out next year with the installation of an X-band radar near Marne-la-Vallée (located at roughly 10 Km of the studied catchment) in the framework of the RainGain project (European project financed by the Interreg IVB funds).

Regional extreme rainfalls observed globally with 17 years of the Tropical Precipitation Measurement Mission

NASA Astrophysics Data System (ADS)

Takayabu, Yukari; Hamada, Atsushi; Mori, Yuki; Murayama, Yuki; Liu, Chuntao; Zipser, Edward

2015-04-01

While extreme rainfall has a huge impact upon human society, the characteristics of the extreme precipitation vary from region to region. Seventeen years of three dimensional precipitation measurements from the space-borne precipitation radar equipped with the Tropical Precipitation Measurement Mission satellite enabled us to describe the characteristics of regional extreme precipitation globally. Extreme rainfall statistics are based on rainfall events defined as a set of contiguous PR rainy pixels. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile in each 2.5degree x2.5degree horizontal resolution grid. First, regional extreme rainfall is characterized in terms of its intensity and event size. Regions of ''intense and extensive'' extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of ''intense but less extensive'' extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of ''extensive but less intense'' extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones. Secondly, regional extremes in terms of surface rainfall intensity and those in terms of convection height are compared. Conventionally, extremely tall convection is considered to contribute the largest to the intense rainfall. Comparing probability density functions (PDFs) of 99th percentiles in terms of the near surface rainfall intensity in each regional grid and those in terms of the 40dBZ echo top heights, it is found that heaviest precipitation in the region is not associated with tallest systems, but rather with systems with moderate heights. Interestingly, this separation of extremely heavy precipitation from extremely tall convection is found to be quite universal, irrespective of regions. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Thus it is demonstrated that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. Third, the size effect of rainfall events on the precipitation intensity is investigated. Comparisons of normalized PDFs of foot-print size rainfall intensity for different sizes of rainfall events show that footprint-scale extreme rainfall becomes stronger as the rainfall events get larger. At the same time, stratiform ratio in area as well as in rainfall amount increases with the size, confirming larger sized features are more organized systems. After all, it is statistically shown that organization of precipitation not only brings about an increase in extreme volumetric rainfall but also an increase in probability of the satellite footprint scale extreme rainfall.

TRIGRS - A Fortran Program for Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis, Version 2.0

USGS Publications Warehouse

Baum, Rex L.; Savage, William Z.; Godt, Jonathan W.

2008-01-01

The Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS) is a Fortran program designed for modeling the timing and distribution of shallow, rainfall-induced landslides. The program computes transient pore-pressure changes, and attendant changes in the factor of safety, due to rainfall infiltration. The program models rainfall infiltration, resulting from storms that have durations ranging from hours to a few days, using analytical solutions for partial differential equations that represent one-dimensional, vertical flow in isotropic, homogeneous materials for either saturated or unsaturated conditions. Use of step-function series allows the program to represent variable rainfall input, and a simple runoff routing model allows the user to divert excess water from impervious areas onto more permeable downslope areas. The TRIGRS program uses a simple infinite-slope model to compute factor of safety on a cell-by-cell basis. An approximate formula for effective stress in unsaturated materials aids computation of the factor of safety in unsaturated soils. Horizontal heterogeneity is accounted for by allowing material properties, rainfall, and other input values to vary from cell to cell. This command-line program is used in conjunction with geographic information system (GIS) software to prepare input grids and visualize model results.

Runoff prediction using rainfall data from microwave links: Tabor case study.

PubMed

Stransky, David; Fencl, Martin; Bares, Vojtech

2018-05-01

Rainfall spatio-temporal distribution is of great concern for rainfall-runoff modellers. Standard rainfall observations are, however, often scarce and/or expensive to obtain. Thus, rainfall observations from non-traditional sensors such as commercial microwave links (CMLs) represent a promising alternative. In this paper, rainfall observations from a municipal rain gauge (RG) monitoring network were complemented by CMLs and used as an input to a standard urban drainage model operated by the water utility of the Tabor agglomeration (CZ). Two rainfall datasets were used for runoff predictions: (i) the municipal RG network, i.e. the observation layout used by the water utility, and (ii) CMLs adjusted by the municipal RGs. The performance was evaluated in terms of runoff volumes and hydrograph shapes. The use of CMLs did not lead to distinctively better predictions in terms of runoff volumes; however, CMLs outperformed RGs used alone when reproducing a hydrograph's dynamics (peak discharges, Nash-Sutcliffe coefficient and hydrograph's rising limb timing). This finding is promising for number of urban drainage tasks working with dynamics of the flow. Moreover, CML data can be obtained from a telecommunication operator's data cloud at virtually no cost. That makes their use attractive for cities unable to improve their monitoring infrastructure for economic or organizational reasons.

THRESH—Software for tracking rainfall thresholds for landslide and debris-flow occurrence, user manual

USGS Publications Warehouse

Baum, Rex L.; Fischer, Sarah J.; Vigil, Jacob C.

2018-02-28

Precipitation thresholds are used in many areas to provide early warning of precipitation-induced landslides and debris flows, and the software distribution THRESH is designed for automated tracking of precipitation, including precipitation forecasts, relative to thresholds for landslide occurrence. This software is also useful for analyzing multiyear precipitation records to compare timing of threshold exceedance with dates and times of historical landslides. This distribution includes the main program THRESH for comparing precipitation to several kinds of thresholds, two utility programs, and a small collection of Python and shell scripts to aid the automated collection and formatting of input data and the graphing and further analysis of output results. The software programs can be deployed on computing platforms that support Fortran 95, Python 2, and certain Unix commands. The software handles rainfall intensity-duration thresholds, cumulative recent-antecedent precipitation thresholds, and peak intensity thresholds as well as various measures of antecedent precipitation. Users should have predefined rainfall thresholds before running THRESH.

A dam-reservoir module for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

de Lavenne, Alban; Thirel, Guillaume; Andréassian, Vazken; Perrin, Charles; Ramos, Maria-Helena

2017-04-01

Developing modeling tools that help to assess the spatial distribution of water resources is a key issue to achieve better solutions for the optimal management of water availability among users in a river basin. Streamflow dynamics depends on (i) the spatial variability of rainfall, (ii) the heterogeneity of catchment behavior and response, and (iii) local human regulations (e.g., reservoirs) that store and control surface water. These aspects can be successfully handled by distributed or semi-distributed hydrological models. In this study, we develop a dam-reservoir module within a semi-distributed rainfall-runoff model (de Lavenne et al. 2016). The model runs at the daily time step, and has five parameters for each sub-catchment as well as a streamflow velocity parameter for flow routing. Its structure is based on two stores, one for runoff production and one for routing. The calibration of the model is performed from upstream to downstream sub-catchments, which efficiently uses spatially-distributed streamflow measurements. In a previous study, Payan et al. (2008) described a strategy to implement a dam module within a lumped rainfall-runoff model. Here we propose to adapt this strategy to a semi-distributed hydrological modelling framework. In this way, the specific location of existing reservoirs inside a river basin is explicitly accounted for. Our goal is to develop a tool that can provide answers to the different issues involved in spatial water management in human-influenced contexts and at large modelling scales. The approach is tested for the Seine basin in France. Results are shown for model performance with and without the dam module. Also, a comparison with the lumped GR5J model highlights the improvements obtained in model performance by considering human influences more explicitly, and by facilitating parameter identifiability. This work opens up new perspectives for streamflow naturalization analyses and scenario-based spatial assessment of water resources under global change. References de Lavenne, A.; Thirel, G.; Andréassian, V.; Perrin, C. & Ramos, M.-H. (2016), 'Spatial variability of the parameters of a semi-distributed hydrological model', PIAHS 373, 87-94. Payan, J.-L.; Perrin, C.; Andréassian, V. & Michel, C. (2008), 'How can man-made water reservoirs be accounted for in a lumped rainfall-runoff model?', Water Resour. Res. 44(3), W03420.

On the Use of the Log-Normal Particle Size Distribution to Characterize Global Rain

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Rincon, Rafael; Liao, Liang

2003-01-01

Although most parameterizations of the drop size distributions (DSD) use the gamma function, there are several advantages to the log-normal form, particularly if we want to characterize the large scale space-time variability of the DSD and rain rate. The advantages of the distribution are twofold: the logarithm of any moment can be expressed as a linear combination of the individual parameters of the distribution; the parameters of the distribution are approximately normally distributed. Since all radar and rainfall-related parameters can be written approximately as a moment of the DSD, the first property allows us to express the logarithm of any radar/rainfall variable as a linear combination of the individual DSD parameters. Another consequence is that any power law relationship between rain rate, reflectivity factor, specific attenuation or water content can be expressed in terms of the covariance matrix of the DSD parameters. The joint-normal property of the DSD parameters has applications to the description of the space-time variation of rainfall in the sense that any radar-rainfall quantity can be specified by the covariance matrix associated with the DSD parameters at two arbitrary space-time points. As such, the parameterization provides a means by which we can use the spaceborne radar-derived DSD parameters to specify in part the covariance matrices globally. However, since satellite observations have coarse temporal sampling, the specification of the temporal covariance must be derived from ancillary measurements and models. Work is presently underway to determine whether the use of instantaneous rain rate data from the TRMM Precipitation Radar can provide good estimates of the spatial correlation in rain rate from data collected in 5(sup 0)x 5(sup 0) x 1 month space-time boxes. To characterize the temporal characteristics of the DSD parameters, disdrometer data are being used from the Wallops Flight Facility site where as many as 4 disdrometers have been used to acquire data over a 2 km path. These data should help quantify the temporal form of the covariance matrix at this site.

A passive microwave technique for estimating rainfall and vertical structure information from space. Part 1: Algorithm description

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Giglio, Louis

1994-01-01

This paper describes a multichannel physical approach for retrieving rainfall and vertical structure information from satellite-based passive microwave observations. The algorithm makes use of statistical inversion techniques based upon theoretically calculated relations between rainfall rates and brightness temperatures. Potential errors introduced into the theoretical calculations by the unknown vertical distribution of hydrometeors are overcome by explicity accounting for diverse hydrometeor profiles. This is accomplished by allowing for a number of different vertical distributions in the theoretical brightness temperature calculations and requiring consistency between the observed and calculated brightness temperatures. This paper will focus primarily on the theoretical aspects of the retrieval algorithm, which includes a procedure used to account for inhomogeneities of the rainfall within the satellite field of view as well as a detailed description of the algorithm as it is applied over both ocean and land surfaces. The residual error between observed and calculated brightness temperatures is found to be an important quantity in assessing the uniqueness of the solution. It is further found that the residual error is a meaningful quantity that can be used to derive expected accuracies from this retrieval technique. Examples comparing the retrieved results as well as the detailed analysis of the algorithm performance under various circumstances are the subject of a companion paper.

Combined effects of constant versus variable intensity simulated rainfall and reduced tillage management on cotton preemergence herbicide runoff.

PubMed

Potter, Thomas L; Truman, Clint C; Strickland, Timothy C; Bosch, David D; Webster, Theodore M; Franklin, Dorcas H; Bednarz, Craig W

2006-01-01

Pesticide runoff research relies heavily on rainfall simulation experiments. Most are conducted at a constant intensity, i.e., at a fixed rainfall rate; however, large differences in natural rainfall intensity is common. To assess implications we quantified runoff of two herbicides, fluometuron and pendimethalin, and applied preemergence after planting cotton on Tifton loamy sand. Rainfall at constant and variable intensity patterns representative of late spring thunderstorms in the Atlantic Coastal Plain region of Georgia (USA) were simulated on 6-m2 plots under strip- (ST) and conventional-tillage (CT) management. The variable pattern produced significantly higher runoff rates of both compounds from CT but not ST plots. However, on an event-basis, runoff totals (% applied) were not significantly different, with one exception: fluometuron runoff from CT plots. There was about 25% more fluometuron runoff with the variable versus the constant intensity pattern (P = 0.10). Study results suggest that conduct of simulations using variable intensity storm patterns may provide more representative rainfall simulation-based estimates of pesticide runoff and that the greatest impacts will be observed with CT. The study also found significantly more fluometuron in runoff from ST than CT plots. Further work is needed to determine whether this behavior may be generalized to other active ingredients with similar properties [low K(oc) (organic carbon partition coefficient) approximately 100 mL g(-1); high water solubility approximately 100 mg L(-1)]. If so, it should be considered when making tillage-specific herbicide recommendations to reduce runoff potential.

Set-up and calibration of an indoor nozzle-type rainfall simulator for soil erosion studies

NASA Astrophysics Data System (ADS)

Lassu, T.; Seeger, M.

2012-04-01

Rainfall simulation is one of the most prevalent methods used in soil erosion studies on agricultural land. In-situ simulators have been used to relate soil surface characteristics and management to runoff generation, infiltration and erosion, eg. the influence of different cultivation systems, and to parameterise erosion models. Laboratory rainfall simulators have been used to determine the impact of the soil surface characteristics such as micro-topography, surface roughness, and soil chemistry on infiltration and erosion rates, and to elucidate the processes involved. The purpose of the following study is to demonstrate the set-up and the calibration of a large indoor, nozzle-type rainfall simulator (RS) for soil erosion, surface runoff and rill development studies. This RS is part of the Kraijenhoff van de Leur Laboratory for Water and Sediment Dynamics in Wageningen University. The rainfall simulator consists from a 6 m long and 2,5 m wide plot, with metal lateral frame and one open side. Infiltration can be collected in different segments. The plot can be inclined up to 15.5° slope. From 3,85 m height above the plot 2 Lechler nozzles 460.788 are sprinkling the water onto the surface with constant intensity. A Zehnder HMP 450 pump provides the constant water supply. An automatic pressure switch on the pump keeps the pressure constant during the experiments. The flow rate is controlled for each nozzle by independent valves. Additionally, solenoid valves are mounted at each nozzle to interrupt water flow. The flow is monitored for each nozzle with flow meters and can be recorded within the computer network. For calibration of the RS we measured the rainfall distribution with 60 gauges equally distributed over the plot during 15 minutes for each nozzle independently and for a combination of 2 identical nozzles. The rainfall energy was recorded on the same grid by measuring drop size distribution and fall velocity with a laser disdrometer. We applied 2 different flow rates (4,5 l/min and 5,5 l/min), resulting in different rainfall intensities and made 2 repetitions each. The average rainfall intensity was 36,8 mm/h at the first and 37,6 mm/h at the second repetition with the lower flow rate (4,5 l/min). With the higher flow rate (5,5 l/min) at the first repetition it was 44,4 mm/h and 46 mm/h at the second one. The maximum and minimum values were 22 mm and 2 mm at the lower (4,5 l/min) flow rate, respectively 26 mm and 4 mm at the higher one (5,5 l/min). In this latter case, the resulting average kinetic energy reached 7 J m-2 mm-1, with a maximum 31,3 J m-2 mm-1 of and a minimum of 2,9 J m-2 mm-1. The Christiansen Uniformity coefficient (CU) for the lower intensities was 66% and 69%, respectively, with the higher intensities slightly better (70% and 72%). The data of the rainfall simulator in Wageningen make it a promising tool for research in soil erosion processes.

The climatic characteristics of extreme precipitations for short-term intervals in the watershed of Lake Maggiore

NASA Astrophysics Data System (ADS)

Saidi, Helmi; Ciampittiello, Marzia; Dresti, Claudia; Ghiglieri, Giorgio

2013-07-01

Alpine and Mediterranean areas are undergoing a profound change in the typology and distribution of rainfall. In particular, there has been an increase in consecutive non-rainy days, and an escalation of extreme rainy events. The climatic characteristic of extreme precipitations over short-term intervals is an object of study in the watershed of Lake Maggiore, the second largest freshwater basin in Italy (located in the north-west of the country) and an important resource for tourism, fishing and commercial flower growing. The historical extreme rainfall series with high-resolution from 5 to 45 min and above: 1, 2, 3, 6, 12 and 24 h collected at different gauges located at representative sites in the watershed of Lake Maggiore, have been computed to perform regional frequency analysis of annual maxima precipitation based on the L-moments approach, and to produce growth curves for different return-period rainfall events. Because of different rainfall-generating mechanisms in the watershed of Lake Maggiore such as elevation, no single parent distribution could be found for the entire study area. This paper concerns an investigation designed to give a first view of the temporal change and evolution of annual maxima precipitation, focusing particularly on both heavy and extreme events recorded at time intervals ranging from few minutes to 24 h and also to create and develop an extreme storm precipitation database, starting from historical sub-daily precipitation series distributed over the territory. There have been two-part changes in extreme rainfall events occurrence in the last 23 years from 1987 to 2009. Little change is observed in 720 min and 24-h precipitations, but the change seen in 5, 10, 15, 20, 30, 45, 60, 120, 180 and 360 min events is significant. In fact, during the 2000s, growth curves have flattened and annual maxima have decreased.

El Niño, Rainfall, and the Shifting Geography of Cholera in Africa

NASA Astrophysics Data System (ADS)

Moore, S.; Azman, A. S.; Zaitchik, B. F.; McKay, H.; Lessler, J.

2017-12-01

The El Niño Southern Oscillation (ENSO) and other climate patterns can have profound impacts on the occurrence of infectious diseases. Because of the key role of water supplies in cholera transmission, a relationship between El Niño events and cholera incidence is highly plausible, and previous research has shown a link between El Niño patterns and cholera in Bangladesh. However, there is little systematic evidence for this link in Africa where many cholera cases and deaths are reported. To understand how ENSO affects the geographic distribution of cholera incidence in Africa, we used a hierarchical Bayesian approach to integrate over 17,000 annual observations of cholera incidence from 2000-2014 in over 3,000 unique locations of varying spatial extent, ranging from entire countries to neighborhoods. The resulting maps reflect modeled cholera incidence at a fine spatial resolution using reported counts of cholera cases, key explanatory variables, and a spatially-dependent covariance term. We then examined the potential mechanistic association between ENSO-related changes in cholera incidence and several environmental variables including rainfall. El Niño profoundly changed the annual geographic distribution of cholera in Africa from 2000-2014, shifting the burden to continental East Africa, where almost 50,000 additional cases occur during El Niño years. Cholera incidence during El Niño years was higher in regions of East Africa with increased rainfall, but incidence was also higher in some areas with decreased rainfall suggesting a complex relationship between rainfall and cholera incidence. Here we show clear evidence for a shift in the distribution of cholera incidence throughout Africa in El Niño and non-El Niño years, likely mediated by El Niño's impact on local climatic factors. Knowledge of this relationship between cholera and climate patterns coupled with El Niño forecasting could be used to notify countries in Africa when they are likely to see a major shift in their cholera risk.

Characterization of rainfall-runoff response and estimation of the effect of wetland restoration on runoff, Heron Lake Basin, southwestern Minnesota, 1991-97

USGS Publications Warehouse

Jones, Perry M.; Winterstein, Thomas A.

2000-01-01

The U.S. Geological Survey (USGS), in cooperation with the Minnesota Department of Natural Resources and the Heron Lake Watershed District, conducted a study to characterize the rainfall-runoff response and to examine the effects of wetland restoration on the rainfall-runoff response within the Heron Lake Basin in southwestern Minnesota. About 93 percent of the land cover in the Heron Lake Basin consists of agricultural lands, consisting almost entirely of row crops, with less than one percent consisting of wetlands. The Hydrological Simulation Program – Fortran (HSPF), Version 10, was calibrated to continuous discharge data and used to characterize rainfall-runoff responses in the Heron Lake Basin between May 1991 and August 1997. Simulation of the Heron Lake Basin was done as a two-step process: (1) simulations of five small subbasins using data from August 1995 through August 1997, and (2) simulations of the two large basins, Jack and Okabena Creek Basins, using data from May 1991 through September 1996. Simulations of the five small subbasins was done to determine basin parameters for the land segments and assess rainfall-runoff response variability in the basin. Simulations of the two larger basins were done to verify the basin parameters and assess rainfall-runoff responses over a larger area and for a longer time period. Best-fit calibrations of the five subbasin simulations indicate that the rainfall-runoff response is uniform throughout the Heron Lake Basin, and 48 percent of the total rainfall for storms becomes direct (surface and interflow) runoff. Rainfall-runoff response variations result from variations in the distribution, intensity, timing, and duration of rainfall; soil moisture; evapotranspiration rates; and the presence of lakes in the basin. In the spring, the amount and distribution of rainfall tends to govern the runoff response. High evapotranspiration rates in the summer result in a depletion of moisture from the soils, substantially affecting the rainfall-runoff relation. Five wetland restoration simulations were run for each of five subbasins using data from August 1995 through August 1997, and for the two larger basins, Jack and Okabena Creek Basins, using data from May 1991 through September 1996. Results from linear regression analysis of total simulated direct runoff and total rainfall data for simulated storms in the wetland-restoration simulations indicate that the portion of total rainfall that becomes runoff will be reduced by 46 percent if 45 percent of current cropland is converted to wetland. The addition of wetlands reduced peak runoff in most of the simulations, but the reduction varied with antecedent soil moisture, the magnitude of the peak flow, and the presence of current wetlands and lakes. Reductions in the simulated total and peak runoff from the Jack Creek Basin for most of the simulated storms were greatest when additional wetlands were simulated in the North Branch Jack Creek or the Upper Jack Creek Subbasins. In the Okabena Creek Basin, reductions in simulated peak runoff for most of the storms were greatest when additional wetlands were simulated in the Lower Okabena Creek Subbasin.

An Experimental Study of Small-Scale Variability of Raindrop Size Distribution

NASA Technical Reports Server (NTRS)

Tokay, Ali; Bashor, Paul G.

2010-01-01

An experimental study of small-scale variability of raindrop size distributions (DSDs) has been carried out at Wallops Island, Virginia. Three Joss-Waldvogel disdrometers were operated at a distance of 0.65, 1.05, and 1.70 km in a nearly straight line. The main purpose of the study was to examine the variability of DSDs and its integral parameters of liquid water content, rainfall, and reflectivity within a 2-km array: a typical size of Cartesian radar pixel. The composite DSD of rain events showed very good agreement among the disdrometers except where there were noticeable differences in midsize and large drops in a few events. For consideration of partial beam filling where the radar pixel was not completely covered by rain, a single disdrometer reported just over 10% more rainy minutes than the rainy minutes when all three disdrometers reported rainfall. Similarly two out of three disdrometers reported5%more rainy minutes than when all three were reporting rainfall. These percentages were based on a 1-min average, and were less for longer averaging periods. Considering only the minutes when all three disdrometers were reporting rainfall, just over one quarter of the observations showed an increase in the difference in rainfall with distance. This finding was based on a 15-min average and was even less for shorter averaging periods. The probability and cumulative distributions of a gamma-fitted DSD and integral rain parameters between the three disdrometers had a very good agreement and no major variability. This was mainly due to the high percentage of light stratiform rain and to the number of storms that traveled along the track of the disdrometers. At a fixed time step, however, both DSDs and integral rain parameters showed substantial variability. The standard deviation (SD) of rain rate was near 3 mm/h, while the SD of reflectivity exceeded 3 dBZ at the longest separation distance. These standard deviations were at 6-min average and were higher at shorter averaging periods. The correlations decreased with increasing separation distance. For rain rate, the correlations were higher than previous gauge-based studies. This was attributed to the differences in data processing and the difference in rainfall characteristics in different climate regions. It was also considered that the gauge sampling errors could be a factor. In this regard, gauge measurements were simulated employing existing disdrometer dataset. While a difference was noticed in cumulative distribution of rain occurrence between the simulated gauge and disdrometer observations, the correlations in simulated gauge measurements did not differ from the disdrometer measurements.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Global warming induced hybrid rainy seasons in the Sahel

NASA Astrophysics Data System (ADS)

Salack, Seyni; Klein, Cornelia; Giannini, Alessandra; Sarr, Benoit; Worou, Omonlola N.; Belko, Nouhoun; Bliefernicht, Jan; Kunstman, Harald

2016-10-01

The small rainfall recovery observed over the Sahel, concomitant with a regional climate warming, conceals some drought features that exacerbate food security. The new rainfall features include false start and early cessation of rainy seasons, increased frequency of intense daily rainfall, increasing number of hot nights and warm days and a decreasing trend in diurnal temperature range. Here, we explain these mixed dry/wet seasonal rainfall features which are called hybrid rainy seasons by delving into observed data consensus on the reduction in rainfall amount, its spatial coverage, timing and erratic distribution of events, and other atmospheric variables crucial in agro-climatic monitoring and seasonal forecasting. Further composite investigations of seasonal droughts, oceans warming and the regional atmospheric circulation nexus reveal that the low-to-mid-level atmospheric winds pattern, often stationary relative to either strong or neutral El-Niño-Southern-Oscillations drought patterns, associates to basin warmings in the North Atlantic and the Mediterranean Sea to trigger hybrid rainy seasons in the Sahel. More challenging to rain-fed farming systems, our results suggest that these new rainfall conditions will most likely be sustained by global warming, reshaping thereby our understanding of food insecurity in this region.

Impacts of rainfall spatial variability on hydrogeological response

NASA Astrophysics Data System (ADS)

Sapriza-Azuri, Gonzalo; Jódar, Jorge; Navarro, Vicente; Slooten, Luit Jan; Carrera, Jesús; Gupta, Hoshin V.

2015-02-01

There is currently no general consensus on how the spatial variability of rainfall impacts and propagates through complex hydrogeological systems. Most studies to date have focused on the effects of rainfall spatial variability (RSV) on river discharge, while paying little attention to other important aspects of system response. Here, we study the impacts of RSV on several responses of a hydrological model of an overexploited system. To this end, we drive a spatially distributed hydrogeological model for the semiarid Upper Guadiana basin in central Spain with stochastic daily rainfall fields defined at three different spatial resolutions (fine → 2.5 km × 2.5 km, medium → 50 km × 50 km, large → lumped). This enables us to investigate how (i) RSV at different spatial resolutions, and (ii) rainfall uncertainty, are propagated through the hydrogeological model of the system. Our results demonstrate that RSV has a significant impact on the modeled response of the system, by specifically affecting groundwater recharge and runoff generation, and thereby propagating through to various other related hydrological responses (river discharge, river-aquifer exchange, groundwater levels). These results call into question the validity of management decisions made using hydrological models calibrated or forced with spatially lumped rainfall.

Multifractal characterisation of a simulated surface flow: A case study with Multi-Hydro in Jouy-en-Josas, France

NASA Astrophysics Data System (ADS)

Gires, Auguste; Abbes, Jean-Baptiste; da Silva Rocha Paz, Igor; Tchiguirinskaia, Ioulia; Schertzer, Daniel

2018-03-01

In this paper we suggest to innovatively use scaling laws and more specifically Universal Multifractals (UM) to analyse simulated surface runoff and compare the retrieved scaling features with the rainfall ones. The methodology is tested on a 3 km2 semi-urbanised with a steep slope study area located in the Paris area along the Bièvre River. First Multi-Hydro, a fully distributed model is validated on this catchment for four rainfall events measured with the help of a C-band radar. The uncertainty associated with small scale unmeasured rainfall, i.e. occurring below the 1 km × 1 km × 5 min observation scale, is quantified with the help of stochastic downscaled rainfall fields. It is rather significant for simulated flow and more limited on overland water depth for these rainfall events. Overland depth is found to exhibit a scaling behaviour over small scales (10 m-80 m) which can be related to fractal features of the sewer network. No direct and obvious dependency between the overland depth multifractal features (quality of the scaling and UM parameters) and the rainfall ones was found.

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

NASA Astrophysics Data System (ADS)

Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.

2018-03-01

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

NASA Astrophysics Data System (ADS)

Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

2015-04-01

Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

Estimation of groundwater recharge via percolation outputs from a rainfall/runoff model for the Verlorenvlei estuarine system, west coast, South Africa

NASA Astrophysics Data System (ADS)

Watson, Andrew; Miller, Jodie; Fleischer, Melanie; de Clercq, Willem

2018-03-01

Wetlands are conservation priorities worldwide, due to their high biodiversity and productivity, but are under threat from agricultural and climate change stresses. To improve the water management practices and resource allocation in these complex systems, a modelling approach has been developed to estimate potential recharge for data poor catchments using rainfall data and basic assumptions regarding soil and aquifer properties. The Verlorenvlei estuarine lake (RAMSAR #525) on the west coast of South Africa is a data poor catchment where rainfall records have been supplemented with farmer's rainfall records. The catchment has multiple competing users. To determine the ecological reserve for the wetlands, the spatial and temporal distribution of recharge had to be well constrained using the J2000 rainfall/runoff model. The majority of rainfall occurs in the mountains (±650 mm/yr) and considerably less in the valley (±280 mm/yr). Percolation was modelled as ∼3.6% of rainfall in the driest parts of the catchment, ∼10% of rainfall in the moderately wet parts of the catchment and ∼8.4% but up to 28.9% of rainfall in the wettest parts of the catchment. The model results are representative of rainfall and water level measurements in the catchment, and compare well with water table fluctuation technique, although estimates are dissimilar to previous estimates within the catchment. This is most likely due to the daily timestep nature of the model, in comparison to other yearly average methods. These results go some way in understanding the fact that although most semi-arid catchments have very low yearly recharge estimates, they are still capable of sustaining high biodiversity levels. This demonstrates the importance of incorporating shorter term recharge event modeling for improving recharge estimates.

A note on the misuses of the variance test in meteorological studies

NASA Astrophysics Data System (ADS)

Hazra, Arnab; Bhattacharya, Sourabh; Banik, Pabitra; Bhattacharya, Sabyasachi

2017-12-01

Stochastic modeling of rainfall data is an important area in meteorology. The gamma distribution is a widely used probability model for non-zero rainfall. Typically the choice of the distribution for such meteorological studies is based on two goodness-of-fit tests—the Pearson's Chi-square test and the Kolmogorov-Smirnov test. Inspired by the index of dispersion introduced by Fisher (Statistical methods for research workers. Hafner Publishing Company Inc., New York, 1925), Mooley (Mon Weather Rev 101:160-176, 1973) proposed the variance test as a goodness-of-fit measure in this context and a number of researchers have implemented it since then. We show that the asymptotic distribution of the test statistic for the variance test is generally not comparable to any central Chi-square distribution and hence the test is erroneous. We also describe a method for checking the validity of the asymptotic distribution for a class of distributions. We implement the erroneous test on some simulated, as well as real datasets and demonstrate how it leads to some wrong conclusions.

Trend analysis for daily rainfall series of Barcelona

NASA Astrophysics Data System (ADS)

Ortego, M. I.; Gibergans-Báguena, J.; Tolosana-Delgado, R.; Egozcue, J. J.; Llasat, M. C.

2009-09-01

Frequency analysis of hydrological series is a key point to acquire an in-depth understanding of the behaviour of hydrologic events. The occurrence of extreme hydrologic events in an area may imply great social and economical impacts. A good understanding of hazardous events improves the planning of human activities. A useful model for hazard assessment of extreme hydrologic events in an area is the point-over-threshold (POT) model. Time-occurrence of events is assumed to be Poisson distributed, and the magnitude X of each event is modeled as an arbitrary random variable, whose excesses over the threshold x0, Y = X - x0, given X > x0, have a Generalized Pareto Distribution (GPD), ( ? )- 1? FY (y|β,?) = 1 - 1+ βy , 0 ? y < ysup , where ysup = +? if ? 0, and ysup = -β? ? if ? < 0. The limiting distribution for ? = 0 is an exponential one. Independence between this magnitude and occurrence in time is assumed, as well as independence from event to event. In order to take account for uncertainty of the estimation of the GPD parameters, a Bayesian approach is chosen. This approach allows to include necessary conditions on the parameters of the distribution for our particular phenomena, as well as propagate adequately the uncertainty of estimations to the hazard parameters, such as return periods. A common concern is to know whether magnitudes of hazardous events have changed in the last decades. Long data series are very appreciated in order to properly study these issues. The series of daily rainfall in Barcelona (1854-2006) has been selected. This is one of the longer european daily rainfall series available. Daily rainfall is better described using a relative scale and therefore it is suitably treated in a log-scale. Accordingly, log-precipitation is identified with X. Excesses over a threshold are modeled by a GPD with a limited maximum value. An additional assumption is that the distribution of the excesses Y has limited upper tail and, therefore, ? < 0, ysup = -β?. Such a long data series provides valuable information about the phenomena on hand, and therefore a very first step is to have a look to its reliability. The first part of the work focuses on the possible existence of abrupt changes in the parameters of the GPD. These abrupt changes may be due to changes in the location of the observatories and/or technological advances introduced in the measuring instruments. The second part of the work examines the possible existence of trends. The parameters of the model are considered as a function of time. A new parameterisation of the GPD distribution is suggested, in order to parsimoniously deal with this climate variation, ? = ln(-? ?;β) and ? = ln(-? ? β) The classical scale and shape parameters of the GPD (β,?) are reformulated as a location parameter ? "linked to the upper limit of the distribution", and a shape parameter ?. In this reparameterisation, the parsimonious choice is to consider shape as a linear function of time, ?(t) = ?0 + t? while keeping location fixed, ?(t) = ?0. Then, the climate change is assessed by checking the hypothesis ? 0. Results show no significant abrupt changes in excesses distribution of the Barcelona daily rainfall series but suggest a significant change for the parameters, and therefore the existence of a trend in daily rainfall for this period.

A Quantitative Analysis of the Effects of Human Activities and Climate Change on Rainfall-Runoff in Xiaoqing River Basin

NASA Astrophysics Data System (ADS)

Yang, Y.; Cao, S.; Liu, C.; Liu, Y.

2017-12-01

It is a hot topic to study the effects of human activities on the rainfall-runoff relationship and quantitatively analyze the influencing factors. According to the flexibility of Copula function to capture multivariate interdependent structure, the Copula structure between rainfall and runoff was analyzed by using the rainfall-runoff variation test method based on Archimedean Copula function to diagnose the variation of rainfall-runoff relationship. The correlation of rainfall-runoff relationship could be directly analyzed by Copula function, which could intuitively display the change of runoff in the same rainfall before and after the mutation period. The statistical method was used to simulate the underlying surface conditions before the abrupt point, and the effects of climate change and human activities on runoff changes were calculated. It can finally figure out the effects of human activities on the rainfall-runoff relationship. Taking xiaoqing river for example, the results showed that the rainfall-runoff relationship in the Xiaoqing River Basin variated in 1996 mainly due to the continuous increase of water consumption in the watershed and the change of the runoff attenuation caused by the large-scale water conservancy projects. And interannual or annual change of rainfall was not obvious; compared with the year before the variation , the runoff capacity of the basin was weakened under the same rainfall conditions after the variation ; Rainfall and runoff distribution were significantly changed and the same magnitude of rainfall and probability of runoff change were significantly different in different periods; The statistical method was used to simulate the runoff from 1996 to 2016. Compared with that from 1960 to 1995, the result showed that the contribution rate of human activities to runoff reduction was 46.8% and that of climate change was 53.2%. By relevant reference, rainfall-runoff correlation and analysis of human activities, the result was verified to be reasonable. The study can be applied to other watersheds, or used to diagnose the variation of the relationship between meteorological elements and hydrological elements so as to provide scientific basis for rational exploitation and utilization of river water resources, as well as soil and water conservation.

A dimensionless approach for the runoff peak assessment: effects of the rainfall event structure

NASA Astrophysics Data System (ADS)

Gnecco, Ilaria; Palla, Anna; La Barbera, Paolo

2018-02-01

The present paper proposes a dimensionless analytical framework to investigate the impact of the rainfall event structure on the hydrograph peak. To this end a methodology to describe the rainfall event structure is proposed based on the similarity with the depth-duration-frequency (DDF) curves. The rainfall input consists of a constant hyetograph where all the possible outcomes in the sample space of the rainfall structures can be condensed. Soil abstractions are modelled using the Soil Conservation Service method and the instantaneous unit hydrograph theory is undertaken to determine the dimensionless form of the hydrograph; the two-parameter gamma distribution is selected to test the proposed methodology. The dimensionless approach is introduced in order to implement the analytical framework to any study case (i.e. natural catchment) for which the model assumptions are valid (i.e. linear causative and time-invariant system). A set of analytical expressions are derived in the case of a constant-intensity hyetograph to assess the maximum runoff peak with respect to a given rainfall event structure irrespective of the specific catchment (such as the return period associated with the reference rainfall event). Looking at the results, the curve of the maximum values of the runoff peak reveals a local minimum point corresponding to the design hyetograph derived according to the statistical DDF curve. A specific catchment application is discussed in order to point out the dimensionless procedure implications and to provide some numerical examples of the rainfall structures with respect to observed rainfall events; finally their effects on the hydrograph peak are examined.

The rainfall plot: its motivation, characteristics and pitfalls.

PubMed

Domanska, Diana; Vodák, Daniel; Lund-Andersen, Christin; Salvatore, Stefania; Hovig, Eivind; Sandve, Geir Kjetil

2017-05-18

A visualization referred to as rainfall plot has recently gained popularity in genome data analysis. The plot is mostly used for illustrating the distribution of somatic cancer mutations along a reference genome, typically aiming to identify mutation hotspots. In general terms, the rainfall plot can be seen as a scatter plot showing the location of events on the x-axis versus the distance between consecutive events on the y-axis. Despite its frequent use, the motivation for applying this particular visualization and the appropriateness of its usage have never been critically addressed in detail. We show that the rainfall plot allows visual detection even for events occurring at high frequency over very short distances. In addition, event clustering at multiple scales may be detected as distinct horizontal bands in rainfall plots. At the same time, due to the limited size of standard figures, rainfall plots might suffer from inability to distinguish overlapping events, especially when multiple datasets are plotted in the same figure. We demonstrate the consequences of plot congestion, which results in obscured visual data interpretations. This work provides the first comprehensive survey of the characteristics and proper usage of rainfall plots. We find that the rainfall plot is able to convey a large amount of information without any need for parameterization or tuning. However, we also demonstrate how plot congestion and the use of a logarithmic y-axis may result in obscured visual data interpretations. To aid the productive utilization of rainfall plots, we demonstrate their characteristics and potential pitfalls using both simulated and real data, and provide a set of practical guidelines for their proper interpretation and usage.

Concentrations of Glyphosate, Its Degradation Product, Aminomethylphosphonic Acid, and Glufosinate in Ground- and Surface-Water, Rainfall, and Soil Samples Collected in the United States, 2001-06

USGS Publications Warehouse

Scribner, Elisabeth A.; Battaglin, William A.; Gilliom, Robert J.; Meyer, Michael T.

2007-01-01

The U.S. Geological Survey conducted a number of studies from 2001 through 2006 to investigate and document the occurrence, fate, and transport of glyphosate, its degradation product, aminomethylphosphonic acid (AMPA), and glufosinate in 2,135 ground- and surface-water samples, 14 rainfall samples, and 193 soil samples. Analytical methods were developed to detect and measure glyphosate, AMPA, and glufosinate in water, rainfall, and soil. Results show that AMPA was detected more frequently and occurred at similar or higher concentrations than the parent compound, glyphosate, whereas glufosinate was seldom found in the environment. Glyphosate and AMPA were detected more frequently in surface water than in ground water. Trace levels of glyphosate and AMPA may persist in the soil from year to year. The methods and data described in this report are useful to researchers and regulators interested in the occurrence, fate, and transport of glyphosate and AMPA in the environment.

Soil erosion under multiple time-varying rainfall events

NASA Astrophysics Data System (ADS)

Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.

2010-05-01

Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.

East Asian Summer Monsoon Rainfall: A Historical Perspective of the 1998 Flood over Yangtze River

NASA Technical Reports Server (NTRS)

Weng, H.-Y.; Lau, K.-M.

1999-01-01

One of the main factors that might have caused the disastrous flood in China during 1998 summer is long-term variations that include a trend indicating increasing monsoon rainfall over the Yangtze River Valley. China's 160-station monthly rainfall anomaly for the summers of 1955-98 is analyzed for exploring such long-term variations. Singular value decomposition (SVD) between the summer rainfall and the global sea surface temperature (SST) anomalies reveals that the rainfall over Yangtze River Valley is closely related to global and regional SST variabilities at both interannual and interdecadal timescales. SVD1 mode links the above normal rainfall condition in central China to an El Nino-like SSTA distribution, varying on interannual timescale modified by a trend during the period. SVD3 mode links positive rainfall anomaly in Yangtze River Valley to the warm SST anomaly in the subtropical western Pacific, varying on interannual timescales modified by interdecadal timescales. This link tends to be stronger when the Nino3 area becomes colder and the western subtropical Pacific becomes warmer. The 1998 summer is a transition season when the 1997/98 El Nino event was in its decaying phase, and the SST in the Nino3 area emerged below normal anomaly while the subtropical western Pacific SST above normal. Thus, the first and third SVD modes become dominant in 1998 summer, favoring more Asian summer monsoon rainfall over the Yangtze River Valley.

Effect of Spatio-Temporal Variability of Rainfall on Stream flow Prediction of Birr Watershed

NASA Astrophysics Data System (ADS)

Demisse, N. S.; Bitew, M. M.; Gebremichael, M.

2012-12-01

The effect of rainfall variability on our ability to forecast flooding events was poorly studied in complex terrain region of Ethiopia. In order to establish relation between rainfall variability and stream flow, we deployed 24 rain gauges across Birr watershed. Birr watershed is a medium size mountainous watershed with an area of 3000 km2 and elevation ranging between 1435 m.a.s.l and 3400 m.a.s.l in the central Ethiopia highlands. One summer monsoon rainfall of 2012 recorded at high temporal scale of 15 minutes interval and stream flow recorded at an hourly interval in three sub-watershed locations representing different scales were used in this study. Based on the data obtained from the rain gauges and stream flow observations, we quantify extent of temporal and spatial variability of rainfall across the watershed using standard statistical measures including mean, standard deviation and coefficient of variation. We also establish rainfall-runoff modeling system using a physically distributed hydrological model: the Soil and Water Assessment Tool (SWAT) and examine the effect of rainfall variability on stream flow prediction. The accuracy of predicted stream flow is measured through direct comparison with observed flooding events. The results demonstrate the significance of relation between stream flow prediction and rainfall variability in the understanding of runoff generation mechanisms at watershed scale, determination of dominant water balance components, and effect of variability on accuracy of flood forecasting activities.

Climate changes and technological disasters in the Russian Federation

NASA Astrophysics Data System (ADS)

Petrova, E. G.

2009-04-01

Global warming and climate change are responsible for many ecological, economic and other significant influences on natural environment and human society. Increasing in number and severity of natural and technological disasters (TD) around the world is among of such influences. Great changes in geographical distribution of disasters are also expected. The study suggested examines this problem by the example of the Russian Federation. Using data base of TD and na-techs (natural-technological disasters) happened in the Russian Federation in 1992-2008 the most important types of disasters caused by various natural hazards were identified and classified for Russian federal regions. In concept of this study na-techs are considered as TD produced by natural factors. 88 percent of all na-techs occurring in the Russian Federation during the observation period were caused by natural processes related to various meteorological and hydrological phenomena. The majority of them were produced by windstorms and hurricanes (37%), snowfalls and snowstorms (27%), rainfalls (16%), hard frost and icy conditions of roads (12%). 11 types of na-techs caused by meteorological and hydrological hazards were found. These types are: (1) accidents at power and heat supply systems caused by windstorms, cyclones, and hurricanes, snowfalls and sleets, hard frost, rainfalls, hailstones, icing, avalanches, or thunderstorms (more than 50% of all na-techs registered in the data base); (2) accidents at water supply systems caused by hard frost, rainfalls, or subsidence of rock (3%); (3) sudden collapses of constructions caused by windstorms, snowfalls, rainfalls, hard frost, subsidence of rock, or floods (12%); (4) automobile accidents caused by snowfalls and snowstorms, icy conditions of roads, rainfalls, fogs, mist, or avalanches (10%); (5) water transport accidents caused by storms, cyclones, typhoons, or fogs (9%); (6) air crashes caused by windstorms, snowfalls, icing, or fogs; (7) railway accidents caused by snowfalls and snowstorms, rainfalls, landslides, or avalanches; (8) fires and explosions caused by lightning or heat; (9) pipeline ruptures caused by windstorms, subsidence of rock, or landslides; (10) agricultural accidents caused by frost, snowfalls, rainfalls, or storm; (11) accidents with toxic emissions caused by floods and landslides The map of their distribution within the Russian Federation was created. Climate changes expected until the end of the XXI century will have important consequences for frequency increasing and change in spatial distribution of na-techs in the Russian Federation. The occurrence of na-techs caused by hydro- and meteorological hazards as well as by other natural hazards related to climate change will be more frequent to the end of this century. The area subjected to technological risk will be enlarged essentially.

Pollutant concentrations and pollution loads in stormwater runoff from different land uses in Chongqing.

PubMed

Wang, Shumin; He, Qiang; Ai, Hainan; Wang, Zhentao; Zhang, Qianqian

2013-03-01

To investigate the distribution of pollutant concentrations and pollution loads in stormwater runoff in Chongqing, six typical land use types were selected and studied from August 2009 to September 2011. Statistical analysis on the distribution of pollutant concentrations in all water samples shows that pollutant concentrations fluctuate greatly in rainfall-runoff, and the concentrations of the same pollutant also vary greatly in different rainfall events. In addition, it indicates that the event mean concentrations (EMCs) of total suspended solids (TSS) and chemical oxygen demand (COD) from urban traffic roads (UTR) are significantly higher than those from residential roads (RR), commercial areas (CA), concrete roofs (CR), tile roofs (TRoof), and campus catchment areas (CCA); and the EMCs of total phosphorus (TP) and NH3-N from UTR and CA are 2.35-5 and 3 times of the class-II standard values specified in the Environmental Quality Standards for Surface Water (GB 3838-2002). The EMCs of Fe, Pb and Cd are also much higher than the class-III standard values. The analysis of pollution load producing coefficients (PLPC) reveals that the main pollution source of TSS, COD and TP is UTR. The analysis of correlations between rainfall factors and EMCs/PLPC indicates that rainfall duration is correlated with EMCs/PLPC of TSS for TRoof and TP for UTR, while rainfall intensity is correlated with EMCs/PLPC of TP for both CR and CCA. The results of this study provide a reference for better management of non-point source pollution in urban regions.

El Niño and the shifting geography of cholera in Africa.

PubMed

Moore, Sean M; Azman, Andrew S; Zaitchik, Benjamin F; Mintz, Eric D; Brunkard, Joan; Legros, Dominique; Hill, Alexandra; McKay, Heather; Luquero, Francisco J; Olson, David; Lessler, Justin

2017-04-25

The El Niño Southern Oscillation (ENSO) and other climate patterns can have profound impacts on the occurrence of infectious diseases ranging from dengue to cholera. In Africa, El Niño conditions are associated with increased rainfall in East Africa and decreased rainfall in southern Africa, West Africa, and parts of the Sahel. Because of the key role of water supplies in cholera transmission, a relationship between El Niño events and cholera incidence is highly plausible, and previous research has shown a link between ENSO patterns and cholera in Bangladesh. However, there is little systematic evidence for this link in Africa. Using high-resolution mapping techniques, we find that the annual geographic distribution of cholera in Africa from 2000 to 2014 changes dramatically, with the burden shifting to continental East Africa-and away from Madagascar and portions of southern, Central, and West Africa-where almost 50,000 additional cases occur during El Niño years. Cholera incidence during El Niño years was higher in regions of East Africa with increased rainfall, but incidence was also higher in some areas with decreased rainfall, suggesting a complex relationship between rainfall and cholera incidence. Here, we show clear evidence for a shift in the distribution of cholera incidence throughout Africa in El Niño years, likely mediated by El Niño's impact on local climatic factors. Knowledge of this relationship between cholera and climate patterns coupled with ENSO forecasting could be used to notify countries in Africa when they are likely to see a major shift in their cholera risk.

Satellite techniques yield insight into devastating rainfall from Hurricane Mitch

NASA Astrophysics Data System (ADS)

Ferraro, R.; Vicente, G.; Ba, M.; Gruber, A.; Scofield, R.; Li, Q.; Weldon, R.

Hurricane Mitch may prove to be one of the most devastating tropical cyclones to affect the western hemisphere. Heavy rains over Central America from October 28, 1998, to November 1, 1998, caused widespread flooding and mud slides in Nicaragua and Honduras resulting in thousands of deaths and missing persons. News reports indicated entire towns being swept away, destruction of national economies and infrastructure, and widespread disease in the aftermath of the storm, which some estimates suggested dropped as much as 1300 mm of rain.However, in view of the widespread damage it is difficult to determine the actual amounts and distribution of rainfall. More accurate means of determining the rainfall associated with Mitch are vital for diagnosing and understanding the evolution of this disaster and for developing new mitigation strategies for future tropical cyclones. Satellite data may prove to be a reliable resource for accurate rainfall analysis and have yielded apparently reliable figures for Hurricane Mitch.

Rainfall Climatology over Asir Region, Saudi Arabia

NASA Astrophysics Data System (ADS)

Sharif, H.; Furl, C.; Al-Zahrani, M.

2012-04-01

Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

Analysis of rainfall characteristics and its related disasters of slag disposal pit of a certain Gold-Copper Deposit in Fujian province

NASA Astrophysics Data System (ADS)

Pan, Huali; Hu, Mingjian; Ou, Guoqiang

2017-04-01

According to the geological investigation in Fujian province, the total number of geological disasters was 9513, in which the number of landslide, collapse, unstable slope and surface collapse was 5816, 1888, 1591, 103 and 115 respectively. The main geological disaster was the landslide with 61.1% of total geological disasters. Among all these geological disasters, only 6.0% was relative stable, 17.0% was basic stable, nearly 76.0% was unstable. The slope disaster was the main geological disaster, if the unstable slope was the potential landslide or collapse; the slope collapse was 98.0% of all geological disasters. The rainfall, in particular the heavy rain, was direct dynamic factor for geological disasters, but the occurrence probability of geological disasters was different because of the sensitivity of the geological environment though of the same intensity rainfall. To obtain the characteristics of soil erosion under the rainfall condition, the rainfall characteristics and its related disasters of slag disposal pit of a certain Gold-Copper Deposit in Fujian province was analyzed by the meteorological and rainfall data. According to the distribution of monitoring stations of hydrological and rainfall in Longyan city of Fujian province and the location of gold-copper deposit, the Shanghang monitoring station of hydrological and rainfall was chosen, which is the nearest one to the gold-copper deposit. Then main parameters of the prediction model, the antecedent precipitation, the rainfall on the day and the rainfall threshold, were calculated by using the rainfall data from 2002 to 2010. And the relationship between geological disasters and the rainfall characteristics were analyzed. The results indicated that there was high risk for the debris flow with landslide collapse when either the daily rainfall was more than 100.0 mm, or the total rainfall was more than 136.0mm in the gold-copper deposit and the Shanghang region. At the same time, although there was few risk for the debris flow when the daily rainfall was between 50.0-100.0mm, once the soil was saturated or nearly saturated because of the continuous antecedent precipitation, debris flow disaster would occur even the daily rainfall was only 50.0mm. In addition, it was prone to trigger debris flow disaster when the daily heavy rainfall was more than 100.0mm or the torrential rainfall in 3 days was between 250.0 -300.0mm.

Changing character of rainfall in eastern China, 1951-2007.

PubMed

Day, Jesse A; Fung, Inez; Liu, Weihan

2018-02-27

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call "frontal rain events." In spring and early summer (known as "Meiyu Season"), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951-2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the "South Flood-North Drought" pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994-2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

Relating tree growth to rainfall in Bolivian rain forests: a test for six species using tree ring analysis.

PubMed

Brienen, Roel J W; Zuidema, Pieter A

2005-11-01

Many tropical regions show one distinct dry season. Often, this seasonality induces cambial dormancy of trees, particularly if these belong to deciduous species. This will often lead to the formation of annual rings. The aim of this study was to determine whether tree species in the Bolivian Amazon region form annual rings and to study the influence of the total amount and seasonal distribution of rainfall on diameter growth. Ring widths were measured on stem discs of a total of 154 trees belonging to six rain forest species. By correlating ring width and monthly rainfall data we proved the annual character of the tree rings for four of our study species. For two other species the annual character was proved by counting rings on trees of known age and by radiocarbon dating. The results of the climate-growth analysis show a positive relationship between tree growth and rainfall in certain periods of the year, indicating that rainfall plays a major role in tree growth. Three species showed a strong relationship with rainfall at the beginning of the rainy season, while one species is most sensitive to the rainfall at the end of the previous growing season. These results clearly demonstrate that tree ring analysis can be successfully applied in the tropics and that it is a promising method for various research disciplines.

Evaluating the use of different precipitation datasets in simulating a flood event

NASA Astrophysics Data System (ADS)

Akyurek, Z.; Ozkaya, A.

2016-12-01

Floods caused by convective storms in mountainous regions are sensitive to the temporal and spatial variability of rainfall. Space-time estimates of rainfall from weather radar, satellites and numerical weather prediction models can be a remedy to represent pattern of the rainfall with some inaccuracy. However, there is a strong need for evaluation of the performance and limitations of these estimates in hydrology. This study aims to provide a comparison of gauge, radar, satellite (Hydro-Estimator (HE)) and numerical weather prediciton model (Weather Research and Forecasting (WRF)) precipitation datasets during an extreme flood event (22.11.2014) lasting 40 hours in Samsun-Turkey. For this study, hourly rainfall data from 13 ground observation stations were used in the analyses. This event having a peak discharge of 541 m3/sec created flooding at the downstream of Terme Basin. Comparisons were performed in two parts. First the analysis were performed in areal and point based manner. Secondly, a semi-distributed hydrological model was used to assess the accuracy of the rainfall datasets to simulate river flows for the flood event. Kalman Filtering was used in the bias correction of radar rainfall data compared to gauge measurements. Radar, gauge, corrected radar, HE and WRF rainfall data were used as model inputs. Generally, the HE product underestimates the cumulative rainfall amounts in all stations, radar data underestimates the results in cumulative sense but keeps the consistency in the results. On the other hand, almost all stations in WRF mean statistics computations have better results compared to the HE product but worse than the radar dataset. Results in point comparisons indicated that, trend of the rainfall is captured by the radar rainfall estimation well but radar underestimates the maximum values. According to cumulative gauge value, radar underestimated the cumulative rainfall amount by % 32. Contrary to other datasets, the bias of WRF is positive due to the overestimation of rainfall forecasts. It was seen that radar-based flow predictions demonstrated good potential for successful hydrological modeling. Moreover, flow predictions obtained from bias corrected radar rainfall values produced an increase in the peak flows compared to the ones obtained from radar data itself.

Spatial structure of monthly rainfall measurements average over 25 years and trends of the hourly variability of a current rainy day in Rwanda.

NASA Astrophysics Data System (ADS)

Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

2013-04-01

Climate plays a vital role in a wide range of socio-economic activities of most nations particularly of developing countries. Climate (rainfall) plays a central role in agriculture which is the main stay of the Rwandan economy and community livelihood and activities. The majority of the Rwandan population (81,1% in 2010) relies on rain fed agriculture for their livelihoods, and the impacts of variability in climate patterns are already being felt. Climate-related events like heavy rainfall or too little rainfall are becoming more frequent and are impacting on human wellbeing.The torrential rainfall that occurs every year in Rwanda could disturb the circulation for many days, damages houses, infrastructures and causes heavy economic losses and deaths. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). Globally, the spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front» mechanism. What is the hourly variability in this mountainous area? Is there any correlation with the identified zones of the monthly average series (from 1965 to 1990 established by the Rwandan meteorological services)? Where could we have hazards with several consecutive rainy days (using forecasted datas from the Norwegian Meteorological Institute)? Spatio-temporal analysis allows for identifying and explaining large-scale anomalies which are useful for understanding hydrological characteristics and subsequently predicting these hydrological events. The objective of our current research (Rainfall variability) is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. Hybrid models - mixing geostatistics and machine learning, will be applied to study spatial non-stationarity of rainfall fields. The research will include rainfalls variability mapping and probabilistic analyses of extreme events. Key words: rainfall variability, Rwanda, extreme event, model, mapping, geostatistics.

Bivariate at-site frequency analysis of simulated flood peak-volume data using copulas

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Viglione, Alberto; Szolgay, Ján.; Blöschl, Günter; Bacigál, Tomáå.¡

2010-05-01

In frequency analysis of joint hydro-climatological extremes (flood peaks and volumes, low flows and durations, etc.), usually, bivariate distribution functions are fitted to the observed data in order to estimate the probability of their occurrence. Bivariate models, however, have a number of limitations; therefore, in the recent past, dependence models based on copulas have gained increased attention to represent the joint probabilities of hydrological characteristics. Regardless of whether standard or copula based bivariate frequency analysis is carried out, one is generally interested in the extremes corresponding to low probabilities of the fitted joint cumulative distribution functions (CDFs). However, usually there is not enough flood data in the right tail of the empirical CDFs to derive reliable statistical inferences on the behaviour of the extremes. Therefore, different techniques are used to extend the amount of information for the statistical inference, i.e., temporal extension methods that allow for making use of historical data or spatial extension methods such as regional approaches. In this study, a different approach was adopted which uses simulated flood data by rainfall-runoff modelling, to increase the amount of data in the right tail of the CDFs. In order to generate artificial runoff data (i.e. to simulate flood records of lengths of approximately 106 years), a two-step procedure was used. (i) First, the stochastic rainfall generator proposed by Sivapalan et al. (2005) was modified for our purpose. This model is based on the assumption of discrete rainfall events whose arrival times, durations, mean rainfall intensity and the within-storm intensity patterns are all random, and can be described by specified distributions. The mean storm rainfall intensity is disaggregated further to hourly intensity patterns. (ii) Secondly, the simulated rainfall data entered a semi-distributed conceptual rainfall-runoff model that consisted of a snow routine, a soil moisture routine and a flow routing routine (Parajka et al., 2007). The applicability of the proposed method was demonstrated on selected sites in Slovakia and Austria. The pairs of simulated flood volumes and flood peaks were analysed in terms of their dependence structure and different families of copulas (Archimedean, extreme value, Gumbel-Hougaard, etc.) were fitted to the observed and simulated data. The question to what extent measured data can be used to find the right copula was discussed. The study is supported by the Austrian Academy of Sciences and the Austrian-Slovak Co-operation in Science and Education "Aktion". Parajka, J., Merz, R., Blöschl, G., 2007: Uncertainty and multiple objective calibration in regional water balance modeling - Case study in 320 Austrian catchments. Hydrological Processes, 21, 435-446. Sivapalan, M., Blöschl, G., Merz, R., Gutknecht, D., 2005: Linking flood frequency to long-term water balance: incorporating effects of seasonality. Water Resources Research, 41, W06012, doi:10.1029/2004WR003439.

Effect of rain gauge density over the accuracy of rainfall: a case study over Bangalore, India.

PubMed

Mishra, Anoop Kumar

2013-12-01

Rainfall is an extremely variable parameter in both space and time. Rain gauge density is very crucial in order to quantify the rainfall amount over a region. The level of rainfall accuracy is highly dependent on density and distribution of rain gauge stations over a region. Indian Space Research Organisation (ISRO) have installed a number of Automatic Weather Station (AWS) rain gauges over Indian region to study rainfall. In this paper, the effect of rain gauge density over daily accumulated rainfall is analyzed using ISRO AWS gauge observations. A region of 50 km × 50 km box over southern part of Indian region (Bangalore) with good density of rain gauges is identified for this purpose. Rain gauge numbers are varied from 1-8 in 50 km box to study the variation in the daily accumulated rainfall. Rainfall rates from the neighbouring stations are also compared in this study. Change in the rainfall as a function of gauge spacing is studied. Use of gauge calibrated satellite observations to fill the gauge station value is also studied. It is found that correlation coefficients (CC) decrease from 82% to 21% as gauge spacing increases from 5 km to 40 km while root mean square error (RMSE) increases from 8.29 mm to 51.27 mm with increase in gauge spacing from 5 km to 40 km. Considering 8 rain gauges as a standard representative of rainfall over the region, absolute error increases from 15% to 64% as gauge numbers are decreased from 7 to 1. Small errors are reported while considering 4 to 7 rain gauges to represent 50 km area. However, reduction to 3 or less rain gauges resulted in significant error. It is also observed that use of gauge calibrated satellite observations significantly improved the rainfall estimation over the region with very few rain gauge observations.

A Machine Learning-based Rainfall System for GPM Dual-frequency Radar

NASA Astrophysics Data System (ADS)

Tan, H.; Chandrasekar, V.; Chen, H.

2017-12-01

Precipitation measurement produced by the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) plays an important role in researching the water circle and forecasting extreme weather event. Compare with its predecessor - Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), GRM DPR measures precipitation in two different frequencies (i.e., Ku and Ka band), which can provide detailed information on the microphysical properties of precipitation particles, quantify particle size distribution and quantitatively measure light rain and falling snow. This paper presents a novel Machine Learning system for ground-based and space borne radar rainfall estimation. The system first trains ground radar data for rainfall estimation using rainfall measurements from gauges and subsequently uses the ground radar based rainfall estimates to train GPM DPR data in order to get space based rainfall product. Therein, data alignment between space DPR and ground radar is conducted using the methodology proposed by Bolen and Chandrasekar (2013), which can minimize the effects of potential geometric distortion of GPM DPR observations. For demonstration purposes, rainfall measurements from three rain gauge networks near Melbourne, Florida, are used for training and validation purposes. These three gauge networks, which are located in Kennedy Space Center (KSC), South Florida Water Management District (SFL), and St. Johns Water Management District (STJ), include 33, 46, and 99 rain gauge stations, respectively. Collocated ground radar observations from the National Weather Service (NWS) Weather Surveillance Radar - 1988 Doppler (WSR-88D) in Melbourne (i.e., KMLB radar) are trained with the gauge measurements. The trained model is then used to derive KMLB radar based rainfall product, which is used to train GPM DPR data collected from coincident overpasses events. The machine learning based rainfall product is compared against the GPM standard products, which shows great potential of the machine learning concept in radar rainfall estimation.

Rainfall and hydrological stability alter the impact of top predators on food web structure and function.

PubMed

Marino, Nicholas A C; Srivastava, Diane S; MacDonald, A Andrew M; Leal, Juliana S; Campos, Alice B A; Farjalla, Vinicius F

2017-02-01

Climate change will alter the distribution of rainfall, with potential consequences for the hydrological dynamics of aquatic habitats. Hydrological stability can be an important determinant of diversity in temporary aquatic habitats, affecting species persistence and the importance of predation on community dynamics. As such, prey are not only affected by drought-induced mortality but also the risk of predation [a non-consumptive effect (NCE)] and actual consumption by predators [a consumptive effect (CE)]. Climate-induced changes in rainfall may directly, or via altered hydrological stability, affect predator-prey interactions and their cascading effects on the food web, but this has rarely been explored, especially in natural food webs. To address this question, we performed a field experiment using tank bromeliads and their aquatic food web, composed of predatory damselfly larvae, macroinvertebrate prey and bacteria. We manipulated the presence and consumption ability of damselfly larvae under three rainfall scenarios (ambient, few large rainfall events and several small rainfall events), recorded the hydrological dynamics within bromeliads and examined the effects on macroinvertebrate colonization, nutrient cycling and bacterial biomass and turnover. Despite our large perturbations of rainfall, rainfall scenario had no effect on the hydrological dynamics of bromeliads. As a result, macroinvertebrate colonization and nutrient cycling depended on the hydrological stability of bromeliads, with no direct effect of rainfall or predation. In contrast, rainfall scenario determined the direction of the indirect effects of predators on bacteria, driven by both predator CEs and NCEs. These results suggest that rainfall and the hydrological stability of bromeliads had indirect effects on the food web through changes in the CEs and NCEs of predators. We suggest that future studies should consider the importance of the variability in hydrological dynamics among habitats as well as the biological mechanisms underlying the ecological responses to climate change. © 2016 John Wiley & Sons Ltd.

Urban stormwater capture curve using three-parameter mixed exponential probability density function and NRCS runoff curve number method.

PubMed

Kim, Sangdan; Han, Suhee

2010-01-01

Most related literature regarding designing urban non-point-source management systems assumes that precipitation event-depths follow the 1-parameter exponential probability density function to reduce the mathematical complexity of the derivation process. However, the method of expressing the rainfall is the most important factor for analyzing stormwater; thus, a better mathematical expression, which represents the probability distribution of rainfall depths, is suggested in this study. Also, the rainfall-runoff calculation procedure required for deriving a stormwater-capture curve is altered by the U.S. Natural Resources Conservation Service (Washington, D.C.) (NRCS) runoff curve number method to consider the nonlinearity of the rainfall-runoff relation and, at the same time, obtain a more verifiable and representative curve for design when applying it to urban drainage areas with complicated land-use characteristics, such as occurs in Korea. The result of developing the stormwater-capture curve from the rainfall data in Busan, Korea, confirms that the methodology suggested in this study provides a better solution than the pre-existing one.

Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2018-02-01

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.

Characterization of urban runoff pollution between dissolved and particulate phases.

PubMed

Wei, Zhang; Simin, Li; Fengbing, Tang

2013-01-01

To develop urban stormwater management effectively, characterization of urban runoff pollution between dissolved and particulate phases was studied by 12 rainfall events monitored for five typical urban catchments. The average event mean concentration (AEMC) of runoff pollutants in different phases was evaluated. The AEMC values of runoff pollutants in different phases from urban roads were higher than the ones from urban roofs. The proportions of total dissolved solids, total dissolved nitrogen, and total dissolved phosphorus in total ones for all the catchments were 26.19%-30.91%, 83.29%-90.51%, and 61.54-68.09%, respectively. During rainfall events, the pollutant concentration at the initial stage of rainfall was high and then sharply decreased to a low value. Affected by catchments characterization and rainfall distribution, the highest concentration of road pollutants might appear in the later period of rainfall. Strong correlations were also found among runoffs pollutants in different phases. Total suspended solid could be considered as a surrogate for particulate matters in both road and roof runoff, while dissolved chemical oxygen demand could be regarded as a surrogate for dissolved matters in roof runoff.

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

USGS Publications Warehouse

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

NASA Astrophysics Data System (ADS)

von Ruette, Jonas; Lehmann, Peter; Fan, Linfeng; Bickel, Samuel; Or, Dani

2017-04-01

Landslides and subsequent debris-flows initiated by rainfall represent a ubiquitous natural hazard in steep mountainous regions. We integrated a landslide hydro-mechanical triggering model and associated debris flow runout pathways with a graphical user interface (GUI) to represent these natural hazards in a wide range of catchments over the globe. The STEP-TRAMM GUI provides process-based locations and sizes of landslides patterns using digital elevation models (DEM) from SRTM database (30 m resolution) linked with soil maps from global database SoilGrids (250 m resolution) and satellite based information on rainfall statistics for the selected region. In a preprocessing step STEP-TRAMM models soil depth distribution and complements soil information that jointly capture key hydrological and mechanical properties relevant to local soil failure representation. In the presentation we will discuss feature of this publicly available platform and compare landslide and debris flow patterns for different regions considering representative intense rainfall events. Model outcomes will be compared for different spatial and temporal resolutions to test applicability of web-based information on elevation and rainfall for hazard assessment.

Real-time adjusting of rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Bareš, Vojtěch

2017-04-01

Urban stormwater predictions require reliable rainfall information with space-time resolution higher than commonly provided by standard rainfall monitoring networks of national weather services. Rainfall data from commercial microwave links (CMLs) could fill this gap. CMLs are line-of-sight radio connections widely used by cellular operators which operate at millimeter bands, where radio waves are attenuated by raindrops. Attenuation data of each single CML in the cellular network can be remotely accessed in (near) real-time with virtually arbitrary sampling frequency and convert to rainfall intensity. Unfortunately, rainfall estimates from CMLs can be substantially biased. Fencl et al., (2017), therefore, proposed adjusting method which enables to correct for this bias. They used rain gauge (RG) data from existing rainfall monitoring networks, which would have otherwise insufficient spatial and temporal resolution for urban rainfall monitoring when used alone without CMLs. In this investigation, we further develop the method to improve its performance in a real-time setting. First, a shortcoming of the original algorithm which delivers unreliable results at the beginning of a rainfall event is overcome by introducing model parameter prior distributions estimated from previous parameter realizations. Second, weights reflecting variance between RGs are introduced into cost function, which is minimized when optimizing model parameters. Finally, RG data used for adjusting are preprocessed by moving average filter. The performance of improved adjusting method is evaluated on four short CMLs (path length < 2 km) located in the small urban catchment (2.3 km2) in Prague-Letnany (CZ). The adjusted CMLs are compared to reference rainfall calculated from six RGs in the catchment. The suggested improvements of the method lead on average to 10% higher Nash-Sutcliffe efficiency coefficient (median value 0.85) for CML adjustment to hourly RG data. Reliability of CML rainfall estimates is especially improved at the beginning of rainfall events and during strong convective rainfalls, whereas performance during longer frontal rainfalls is almost unchanged. Our results clearly demonstrate that adjusting of CMLs to existing RGs represents a viable approach with great potential for real-time applications in stormwater management. This work was supported by the project of Czech Science Foundation (GACR) No.17-16389S. References: Fencl, M., Dohnal, M., Rieckermann, J. and Bareš, V.: Gauge-Adjusted Rainfall Estimates from Commercial Microwave Links, Hydrol Earth Syst. Sci., 2017 (accepted).

Rainfall estimates for hydrological models: Comparing rain gauge, radar and microwave link data as input for the Wageningen Lowland Runoff Simulator (WALRUS)

NASA Astrophysics Data System (ADS)

Brauer, Claudia; Overeem, Aart; Uijlenhoet, Remko

2015-04-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of differences in rainfall estimates on discharge simulations in a lowland catchment by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in the Hupsel Brook catchment. We used two automatic rain gauges with hourly resolution, located inside the catchment (the base run) and 30 km northeast. Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. Traditionally, the precipitation research community places emphasis on quantifying spatial errors and uncertainty, but for hydrological applications, temporal errors and uncertainty should be quantified as well. Its memory makes the hydrologic system sensitive to missed or badly timed rainfall events, but also emphasizes the effect of a bias in rainfall estimates. Systematic underestimation of rainfall by the uncorrected operational radar product leads to very dry model states and an increasing underestimation of discharge. Using the rain gauge 30 km northeast of the catchment yields good results for climatological studies, but not for forecasting individual floods. Simulating discharge using the maps derived from microwave link data and the gauge-adjusted radar product yields good results for both events and climatological studies. This indicates that these products can be used in catchments without gauges in or near the catchment. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. Improving rainfall measurements can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

A method to combine spaceborne radar and radiometric observations of precipitation

NASA Astrophysics Data System (ADS)

Munchak, Stephen Joseph

This dissertation describes the development and application of a combined radar-radiometer rainfall retrieval algorithm for the Tropical Rainfall Measuring Mission (TRMM) satellite. A retrieval framework based upon optimal estimation theory is proposed wherein three parameters describing the raindrop size distribution (DSD), ice particle size distribution (PSD), and cloud water path (cLWP) are retrieved for each radar profile. The retrieved rainfall rate is found to be strongly sensitive to the a priori constraints in DSD and cLWP; thus, these parameters are tuned to match polarimetric radar estimates of rainfall near Kwajalein, Republic of Marshall Islands. An independent validation against gauge-tuned radar rainfall estimates at Melbourne, FL shows agreement within 2% which exceeds previous algorithms' ability to match rainfall at these two sites. The algorithm is then applied to two years of TRMM data over oceans to determine the sources of DSD variability. Three correlated sets of variables representing storm dynamics, background environment, and cloud microphysics are found to account for approximately 50% of the variability in the absolute and reflectivity-normalized median drop size. Structures of radar reflectivity are also identified and related to drop size, with these relationships being confirmed by ground-based polarimetric radar data from the North American Monsoon Experiment (NAME). Regional patterns of DSD and the sources of variability identified herein are also shown to be consistent with previous work documenting regional DSD properties. In particular, mid-latitude regions and tropical regions near land tend to have larger drops for a given reflectivity, whereas the smallest drops are found in the eastern Pacific Intertropical Convergence Zone. Due to properties of the DSD and rain water/cloud water partitioning that change with column water vapor, it is shown that increases in water vapor in a global warming scenario could lead to slight (1%) underestimates of a rainfall trends by radar but larger overestimates (5%) by radiometer algorithms. Further analyses are performed to compare tropical oceanic mean rainfall rates between the combined algorithm and other sources. The combined algorithm is 15% higher than the version 6 of the 2A25 radar-only algorithm and 6.6% higher than the Global Precipitation Climatology Project (GPCP) estimate for the same time-space domain. Despite being higher than these two sources, the combined total is not inconsistent with estimates of the other components of the energy budget given their uncertainties.

Global Climatic Indices Influence on Rainfall Spatiotemporal Distribution : A Case Study from Morocco

NASA Astrophysics Data System (ADS)

Elkadiri, R.; Zemzami, M.; Phillips, J.

2017-12-01

The climate of Morocco is affected by the Mediterranean Sea, the Atlantic Ocean the Sahara and the Atlas mountains, creating a highly variable spatial and temporal distribution. In this study, we aim to decompose the rainfall in Morocco into global and local signals and understand the contribution of the climatic indices (CIs) on rainfall. These analyses will contribute in understanding the Moroccan climate that is typical of other Mediterranean and North African climatic zones. In addition, it will contribute in a long-term prediction of climate. The constructed database ranges from 1950 to 2013 and consists of monthly data from 147 rainfall stations and 37 CIs data provided mostly by the NOAA Climate Prediction Center. The next general steps were followed: (1) the study area was divided into 9 homogenous climatic regions and weighted precipitation was calculated for each region to reduce the local effects. (2) Each CI was decomposed into nine components of different frequencies (D1 to D9) using wavelet multiresolution analysis. The four lowest frequencies of each CI were selected. (3) Each of the original and resulting signals were shifted from one to six months to account for the effect of the global patterns. The application of steps two and three resulted in the creation of 1225 variables from the original 37 CIs. (4) The final 1225 variables were used to identify links between the global and regional CIs and precipitation in each of the nine homogenous regions using stepwise regression and decision tree. The preliminary analyses and results were focused on the north Atlantic zone and have shown that the North Atlantic Oscillation (PC-based) from NCAR (NAOPC), the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the Western Mediterranean Oscillation (WMO) and the Extreme Eastern Tropical Pacific Sea Surface Temperature (NINO12) have the highest correlation with rainfall (33%, 30%, 27%, 21% and -20%, respectively). In addition the 4-months lagged NINO12 and the 6-months lagged NAOPC and WMO have a collective contribution of more than 45% of the rainfall signal. Low frequencies are also represented in the rainfall; especially the 5th and 4th components of the decomposed CIs (48% and 42% of the frequencies, respectively) suggesting their potential contribution in the interannual rainfall variability.

A simple stochastic rainstorm generator for simulating spatially and temporally varying rainfall

NASA Astrophysics Data System (ADS)

Singer, M. B.; Michaelides, K.; Nichols, M.; Nearing, M. A.

2016-12-01

In semi-arid to arid drainage basins, rainstorms often control both water supply and flood risk to marginal communities of people. They also govern the availability of water to vegetation and other ecological communities, as well as spatial patterns of sediment, nutrient, and contaminant transport and deposition on local to basin scales. All of these landscape responses are sensitive to changes in climate that are projected to occur throughout western North America. Thus, it is important to improve characterization of rainstorms in a manner that enables statistical assessment of rainfall at spatial scales below that of existing gauging networks and the prediction of plausible manifestations of climate change. Here we present a simple, stochastic rainstorm generator that was created using data from a rich and dense network of rain gauges at the Walnut Gulch Experimental Watershed (WGEW) in SE Arizona, but which is applicable anywhere. We describe our methods for assembling pdfs of relevant rainstorm characteristics including total annual rainfall, storm area, storm center location, and storm duration. We also generate five fitted intensity-duration curves and apply a spatial rainfall gradient to generate precipitation at spatial scales below gauge spacing. The model then runs by Monte Carlo simulation in which a total annual rainfall is selected before we generate rainstorms until the annual precipitation total is reached. The procedure continues for decadal simulations. Thus, we keep track of the hydrologic impact of individual storms and the integral of precipitation over multiple decades. We first test the model using ensemble predictions until we reach statistical similarity to the input data from WGEW. We then employ the model to assess decadal precipitation under simulations of climate change in which we separately vary the distribution of total annual rainfall (trend in moisture) and the intensity-duration curves used for simulation (trends in storminess). We demonstrate the model output through spatial maps of rainfall and through statistical comparisons of relevant parameters and distributions. Finally, discuss how the model can be used to understand basin-scale hydrology in terms of soil moisture, runoff, and erosion.

Identification of homogeneous regions for rainfall regional frequency analysis considering typhoon event in South Korea

NASA Astrophysics Data System (ADS)

Heo, J. H.; Ahn, H.; Kjeldsen, T. R.

2017-12-01

South Korea is prone to large, and often disastrous, rainfall events caused by a mixture of monsoon and typhoon rainfall phenomena. However, traditionally, regional frequency analysis models did not consider this mixture of phenomena when fitting probability distributions, potentially underestimating the risk posed by the more extreme typhoon events. Using long-term observed records of extreme rainfall from 56 sites combined with detailed information on the timing and spatial impact of past typhoons from the Korea Meteorological Administration (KMA), this study developed and tested a new mixture model for frequency analysis of two different phenomena; events occurring regularly every year (monsoon) and events only occurring in some years (typhoon). The available annual maximum 24 hour rainfall data were divided into two sub-samples corresponding to years where the annual maximum is from either (1) a typhoon event, or (2) a non-typhoon event. Then, three-parameter GEV distribution was fitted to each sub-sample along with a weighting parameter characterizing the proportion of historical events associated with typhoon events. Spatial patterns of model parameters were analyzed and showed that typhoon events are less commonly associated with annual maximum rainfall in the North-West part of the country (Seoul area), and more prevalent in the southern and eastern parts of the country, leading to the formation of two distinct typhoon regions: (1) North-West; and (2) Southern and Eastern. Using a leave-one-out procedure, a new regional frequency model was tested and compared to a more traditional index flood method. The results showed that the impact of typhoon on design events might previously have been underestimated in the Seoul area. This suggests that the use of the mixture model should be preferred where the typhoon phenomena is less frequent, and thus can have a significant effect on the rainfall-frequency curve. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

Recent and future rainfall erosivity on the territory of the Czech Republic

NASA Astrophysics Data System (ADS)

Krasa, Josef; Stredova, Hana; Stepanek, Petr; Hanel, Martin; Dostal, Tomas; Novotny, Ivan

2015-04-01

Water erosion is a main factor of degradation of soils used for agriculture in the Czech Republic. For landscape conservation purposes the soil erosion risk is defined here mostly by USLE (Wischmeier and Smith, 1978). Within USLE the precipitation impact on erosion is a function of rainfall kinetic energy and intensity represented by R-factor. In the Czech Republic historically and recently several research teams have analyzed rainfall data to assess R-factor. Till now not many European countries have performed detailed spatially distributed analyses of rain erosivities. Most studies use only simplified methods based on long-term rainfall averages or databases of only several station-datasets. The most recent study on rainfall erosivity spatial distribution over the Czech Republic was based on digital rain gauge data from automatic stations of the Czech Hydrometeorogical Institute. The erosive rains were derived from continuous 1 minute step 10-year rainfall data (2003-2012) from 245 stations. Based on the research recent annual R-factor values in the stations vary from 37 to 239 [N.h-1] (values over 100 are located in mountain regions with minimum of agricultural land). Average value is 69 [N.h-1.year-1]. For the Czech Republic the future prediction is based on 10km resolution ALADIN/CZ regional climate model. Within the EU FP6 project CECILIA it was coupled with GCM ARPEGE to provide a projection of future climate in two time slices, 2021-2050 and 2071-2100, according to the IPCC A1B emission scenario. Daily precipitation volumes and percentiles of maximal events allowed authors to develop R-factor maps of present and future scenarios. Based on the analyses we can conclude that average value for the whole territory of the Czech Republic will remain close to 70 [N.h-1.year-1] or even decrease for 2071-2100, but we can expect significant changes (30-40 % rise or decrease) for several large agricultural regions (eg. Southern Moravia). These changes will have impact on soil erosion dynamics of the specific areas. Details on the spatial distribution of recent and future rain erosivities over the Czech Republic and the consequences for the erosion risk will be presented. The paper was prepared within the projects NAZV QJ1230056 and BV VG 20122015092.

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data

PubMed Central

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-01-01

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363

Estimating urban flood risk - uncertainty in design criteria

NASA Astrophysics Data System (ADS)

Newby, M.; Franks, S. W.; White, C. J.

2015-06-01

The design of urban stormwater infrastructure is generally performed assuming that climate is static. For engineering practitioners, stormwater infrastructure is designed using a peak flow method, such as the Rational Method as outlined in the Australian Rainfall and Runoff (AR&R) guidelines and estimates of design rainfall intensities. Changes to Australian rainfall intensity design criteria have been made through updated releases of the AR&R77, AR&R87 and the recent 2013 AR&R Intensity Frequency Distributions (IFDs). The primary focus of this study is to compare the three IFD sets from 51 locations Australia wide. Since the release of the AR&R77 IFDs, the duration and number of locations for rainfall data has increased and techniques for data analysis have changed. Updated terminology coinciding with the 2013 IFD release has also resulted in a practical change to the design rainfall. For example, infrastructure that is designed for a 1 : 5 year ARI correlates with an 18.13% AEP, however for practical purposes, hydraulic guidelines have been updated with the more intuitive 20% AEP. The evaluation of design rainfall variation across Australia has indicated that the changes are dependent upon location, recurrence interval and rainfall duration. The changes to design rainfall IFDs are due to the application of differing data analysis techniques, the length and number of data sets and the change in terminology from ARI to AEP. Such changes mean that developed infrastructure has been designed to a range of different design criteria indicating the likely inadequacy of earlier developments to the current estimates of flood risk. In many cases, the under-design of infrastructure is greater than the expected impact of increased rainfall intensity under climate change scenarios.

Rainfall and sheet power model for interrill erosion in steep slope

NASA Astrophysics Data System (ADS)

Shin, Seung Sook; Deog Park, Sand; Nam, Myeong Jun

2015-04-01

The two-phase process of interrill erosion consist of the splash and detachment of individual particles from soil mass by impact of raindrops and the transport by erosive running water. Most experimental results showed that the effect of interaction between rainfall impact and surface runoff increases soil erosion in low or gentle slope. Especially, the combination of rain splash and sheet flow is the dominant runoff and erosion mechanism occurring on most steep hillslopes. In this study, a rainfall simulation was conducted to evaluate interrill erosion in steep slope with cover or non-cover. The kinetic energy of raindrops of rainfall simulator was measured by disdrometer used to measure the drop size distribution and velocity of falling raindrops and showed about 0.563 rate of that calculated from empirical equation between rainfall kinetic energy and rainfall intensity. Surface and subsurface runoff and sediment yield depended on rainfall intensity, gradient of slope, and existence of cover. Sediment from steep plots under rainfall simulator is greatly reduced by existence of the strip cover that the kinetic energy of raindrop approximates to zero. Soil erosion in steep slope with non-cover was nearly 4.93 times of that measured in plots with strip cover although runoff was only 1.82 times. The equation of a rainfall and sheet power was used to evaluate sediment yields in steep slope with cover or non-cover. The power model successfully explained physical processes for interrill erosion that combination of raindrop impact and sheet flow increases greatly soil erosion in steep slope. This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology(No. 2013R1A1A3011962).

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

PubMed

Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter

2016-06-15

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Latitudinal variation in summer monsoon rainfall over Western Ghat of India and its association with global sea surface temperatures.

PubMed

Revadekar, J V; Varikoden, Hamza; Murumkar, P K; Ahmed, S A

2018-02-01

The Western Ghats (WG) of India are basically north-south oriented mountains having narrow zonal width with a steep rising western face. The summer monsoon winds during June to September passing over the Arabian Sea are obstructed by the WG and thus orographically uplift to produce moderate-to-heavy precipitation over the region. However, it is seen that characteristic features of rainfall distribution during the season vary from north to south. Also its correlation with all-India summer monsoon rainfall increases from south to north. In the present study, an attempt is also made to examine long-term as well as short-term trends and variability in summer monsoon rainfall over different subdivisions of WG using monthly rainfall data for the period 1871-2014. Konkan & Goa and Coastal Karnataka show increase in rainfall from 1871 to 2014 in all individual summer monsoon months. Short-term trend analysis based on 31-year sliding window indicates that the trends are not monotonous, but has epochal behavior. In recent epoch, magnitudes of negative trends are consistently decreasing and have changed its sign to positive during 1985-2014. It has been observed that Indian Ocean Dipole (IOD) plays a dominant positive role in rainfall over entire WG in all summer monsoon months, whereas role of Nino regions are asymmetric over WG rainfall. Indian summer monsoon is known for its negative relationship with Nino SST. Negative correlations are also seen for WG rainfall with Nino regions but only during onset and withdrawal phase. During peak monsoon months July and August subdivisions of WG mostly show positive correlation with Nino SST. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimating Vegetation Rainfall Interception Using Remote Sensing Observations at Very High Resolution

NASA Astrophysics Data System (ADS)

Cui, Y.; Zhao, P.; Hong, Y.; Fan, W.; Yan, B.; Xie, H.

2017-12-01

Abstract: As an important compont of evapotranspiration, vegetation rainfall interception is the proportion of gross rainfall that is intercepted, stored and subsequently evaporated from all parts of vegetation during or following rainfall. Accurately quantifying the vegetation rainfall interception at a high resolution is critical for rainfall-runoff modeling and flood forecasting, and is also essential for understanding its further impact on local, regional, and even global water cycle dynamics. In this study, the Remote Sensing-based Gash model (RS-Gash model) is developed based on a modified Gash model for interception loss estimation using remote sensing observations at the regional scale, and has been applied and validated in the upper reach of the Heihe River Basin of China for different types of vegetation. To eliminate the scale error and the effect of mixed pixels, the RS-Gash model is applied at a fine scale of 30 m with the high resolution vegetation area index retrieved by using the unified model of bidirectional reflectance distribution function (BRDF-U) for the vegetation canopy. Field validation shows that the RMSE and R2 of the interception ratio are 3.7% and 0.9, respectively, indicating the model's strong stability and reliability at fine scale. The temporal variation of vegetation rainfall interception loss and its relationship with precipitation are further investigated. In summary, the RS-Gash model has demonstrated its effectiveness and reliability in estimating vegetation rainfall interception. When compared to the coarse resolution results, the application of this model at 30-m fine resolution is necessary to resolve the scaling issues as shown in this study. Keywords: rainfall interception; remote sensing; RS-Gash analytical model; high resolution

The issues of current rainfall estimation techniques in mountain natural multi-hazard investigation

NASA Astrophysics Data System (ADS)

Zhuo, Lu; Han, Dawei; Chen, Ningsheng; Wang, Tao

2017-04-01

Mountain hazards (e.g., landslides, debris flows, and floods) induced by rainfall are complex phenomena that require good knowledge of rainfall representation at different spatiotemporal scales. This study reveals rainfall estimation from gauges is rather unrepresentative over a large spatial area in mountain regions. As a result, the conventional practice of adopting the triggering threshold for hazard early warning purposes is insufficient. The main reason is because of the huge orographic influence on rainfall distribution. Modern rainfall estimation methods such as numerical weather prediction modelling and remote sensing utilising radar from the space or on land are able to provide spatially more representative rainfall information in mountain areas. But unlike rain gauges, they only indirectly provide rainfall measurements. Remote sensing suffers from many sources of errors such as weather conditions, attenuation and sampling methods, while numerical weather prediction models suffer from spatiotemporal and amplitude errors depending on the model physics, dynamics, and model configuration. A case study based on Sichuan, China is used to illustrate the significant difference among the three aforementioned rainfall estimation methods. We argue none of those methods can be relied on individually, and the challenge is on how to make the full utilisation of the three methods conjunctively because each of them only provides partial information. We propose that a data fusion approach should be adopted based on the Bayesian inference method. However such an approach requires the uncertainty information from all those estimation techniques which still need extensive research. We hope this study will raise the awareness of this important issue and highlight the knowledge gap that should be filled in so that such a challenging problem could be tackled collectively by the community.