An investigation into observational characteristics of rainfall and temperature in Central Northeast India—a historical perspective 1889–2008

Mann–Kendall non-parametric test was employed for observational trend detection of monthly, seasonal and annual precipitation of five meteorological subdivisions of Central Northeast India (CNE India) for different 30-year normal periods (NP) viz. 1889–1918 (NP1), 1919–1948 (NP2), 1949–1978 (NP3) and 1979–2008 (NP4). The trends of maximum and minimum temperatures were also investigated. The slopes of the trend lines were determined using the method of least square linear fitting. An application of Morelet wavelet analysis was done with monthly rainfall during June– September, total rainfall during monsoon season and annual rainfall to know the periodicity and to test the significance of periodicity using the power spectrum method. The inferences figure out from the analyses will be helpful to the policy managers, planners and agricultural scientists to work out irrigation and water management options under various possible climatic eventualities for the region. The long-term (1889–2008) mean annual rainfall of CNE India is 1,195.1 mm with a standard deviation of 134.1 mm and coefficient of variation of 11%. There is a significant decreasing trend of 4.6 mm/year for Jharkhand and 3.2 mm/day for CNE India. Since rice crop is the important kharif crop (May– October) in this region, the decreasing trend of rainfall during themonth of July may delay/affect the transplanting/vegetative phase of the crop, and assured irrigation is very much needed to tackle the drought situation. During themonth of December, all the meteorological subdivisions except Jharkhand show a significant decreasing trend of rainfall during recent normal period NP4. The decrease of rainfall during December may hamper sowing of wheat, which is the important rabi crop (November–March) in most parts of this region. Maximum temperature shows significant rising trend of 0.008°C/year (at 0.01 level) during monsoon season and 0.014°C/year (at 0.01 level) during post-monsoon season during the period 1914– 2003. The annual maximum temperature also shows significant increasing trend of 0.008°C/year (at 0.01 level) during the same period. Minimum temperature shows significant rising trend of 0.012°C/year (at 0.01 level) during postmonsoon season and significant falling trend of 0.002°C/year (at 0.05 level) during monsoon season. A significant 4– 8 years peak periodicity band has been noticed during September over Western UP, and 30–34 years periodicity has been observed during July over Bihar subdivision. However, as far as CNE India is concerned, no significant periodicity has been noticed in any of the time series.

Rainfall-runoff modeling and preliminary regional flood characteristics of small rural watersheds in the Arkansas River basin in Colorado /

Mode of access: Internet.

Rainfall infiltration and soil hydrological characteristics below ancient forest, planted forest and grassland in a temperate northern climate

How rainfall infiltration rate and soil hydrological characteristics develop over time under forests of different ages in temperate regions is poorly understood. In this study, infiltration rate and soil hydrological characteristics were investigated under forests of different ages and under grassland. Soil hydraulic characteristics were measured at different scales under a 250-year-old grazed grassland (GL), 6-year-old (6yr) and 48-year-old (48yr) Scots pine (Pinus sylvestris) plantations, remnant 300-year-old individual Scots pine (OT) and a 4000-year-old Caledonian Forest (AF). In situ field-saturated hydraulic conductivity (Kfs) was measured, and visible root:soil area was estimated from soil pits. Macroporosity, pore structure and macropore connectivity were estimated from X-ray tomography of soil cores, and from water-release characteristics. At all scales, the median values for Kfs, root fraction, macroporosity and connectivity values tended to AF>OT>48yr>GL>6yr, indicating that infiltration rates and water storage increased with forest age. The remnant Caledonian Forest had a huge range of Kfs (12 to >4922mmh-1), with maximum Kfs values 7 to 15 times larger than those of 48-year-old Scots pine plantation, suggesting that undisturbed old forests, with high rainfall and minimal evapotranspiration in winter, may act as important areas for water storage and sinks for storm rainfall to infiltrate and transport to deeper soil layers via preferential flow. The importance of the development of soil hydrological characteristics under different aged forests is discussed.

Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.

The 23rd October 2002 dust storm in eastern Australia: characteristics and meteorological conditions

The dust storm of 23 October 2002 covered most of eastern Australia and carried one of the largest recorded dust loads in Australia. In the 6 months leading up to the event, severe drought conditions in eastern Australia, plus above average maximum temperatures resulted in high potential evapo-transpiration rates, producing severe soil moisture deficits and reduced vegetation cover. Although increased wind speeds associated with a fast moving cold front were the meteorological driving force, these winds speeds were lower than those for the previously documented large dust storms. The dust storm was 2400 km long, up to 400 km across and 1.5-2.5 km in height. The plume area was estimated at 840,860 km 2 and the dust load at 0900 h was 3.35-4.85 million tones (Mt). These dust load estimates are highly sensitive to assumptions, regarding visibility-dust concentration relationships, vertical dust concentration profiles and dust ceilings. The event is examined using meteorological records, remote sensing and air quality monitoring. (C) 2004 Elsevier Ltd. All rights reserved.

Spatial-temporal analyses of climate elements, vegetation characteristics and sea surface temperature anomaly. A Case study in Gojam, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Derivation of soil-specific streaming potential electrical parameters from hydrodynamic characteristics of partially saturated soils

Water movement in unsaturated soils gives rise to measurable electrical potential differences that are related to the flow direction and volumetric fluxes, as well as to the soil properties themselves. Laboratory and field data suggest that these so-called streaming potentials may be several orders of magnitudes larger than theoretical predictions that only consider the influence of the relative permeability and electrical conductivity on the self potential (SP) data. Recent work has improved predictions somewhat by considering how the volumetric excess charge in the pore space scales with the inverse of water saturation. We present a new theoretical approach that uses the flux-averaged excess charge, not the volumetric excess charge, to predict streaming potentials. We present relationships for how this effective excess charge varies with water saturation for typical soil properties using either the water retention or the relative permeability function. We find large differences between soil types and the predictions based on the relative permeability function display the best agreement with field data. The new relationships better explain laboratory data than previous work and allow us to predict the recorded magnitudes of the streaming potentials following a rainfall event in sandy loam, whereas previous models predict values that are three orders of magnitude too small. We suggest that the strong signals in unsaturated media can be used to gain information about fluxes (including very small ones related to film flow), but also to constrain the relative permeability function, the water retention curve, and the relative electrical conductivity function.

Characteristics of the bological cycle of Lutzomyia evandroi Costa Lima & Antunes, 1936 (Diptera: Psychodidae) under experimental conditions

Lutzomyia evandroi Costa Lima and Antunes, 1936 is found in Rio Grande do Norte, northeastern Brazil, in areas of visceral and mucocutaneous leishmaniasis and follows the same geographic distribution of L. longipalpis. The biological cycle, oviposition, morphological and behavioral characteristics of the species were studied under experimental conditions. The average number of eggs per wild caught female varied from 21 to 50 eggs along the year, with a peak occurring between January and March and another in August, with oviposition lasting for 4 to 12 days. The mean larval phase was 24 days. Ovipositing rates were influenced by rainfall and temperature indexes, with an increase of eggs per oviposition at the beginning and at the end of the rainy season, and a decrease at the peak of the rainy season.

Kernel-based mapping of orographic rainfall enhancement in the Swiss Alps as detected by weatherradar

In this paper, we develop a data-driven methodology to characterize the likelihood of orographic precipitation enhancement using sequences of weather radar images and a digital elevation model (DEM). Geographical locations with topographic characteristics favorable to enforce repeatable and persistent orographic precipitation such as stationary cells, upslope rainfall enhancement, and repeated convective initiation are detected by analyzing the spatial distribution of a set of precipitation cells extracted from radar imagery. Topographic features such as terrain convexity and gradients computed from the DEM at multiple spatial scales as well as velocity fields estimated from sequences of weather radar images are used as explanatory factors to describe the occurrence of localized precipitation enhancement. The latter is represented as a binary process by defining a threshold on the number of cell occurrences at particular locations. Both two-class and one-class support vector machine classifiers are tested to separate the presumed orographic cells from the nonorographic ones in the space of contributing topographic and flow features. Site-based validation is carried out to estimate realistic generalization skills of the obtained spatial prediction models. Due to the high class separability, the decision function of the classifiers can be interpreted as a likelihood or susceptibility of orographic precipitation enhancement. The developed approach can serve as a basis for refining radar-based quantitative precipitation estimates and short-term forecasts or for generating stochastic precipitation ensembles conditioned on the local topography.

Evaluation of Cover Aggregate Stripping Characteristics, HR-182, 1979

The purpose of Research Project HR-182 was to identify those aggregate types which would perform satisfactorily as seal coat aggregates. Aggregates were chosen from across the State to represent the various types normally encountered and were used with two different types of binder bitumens. A water spray treatment was also included to simulate the effects of rainfall. The evaluation was based upon aggregate retention. Due to the influence of unexpected variables upon the field samples, the laboratory data are reliable for only the most general observations. Namely, that gravels as a group appear to be retained better than carbonates and rain-fall shortly after seal coat placement can affect aggregate retention. The subsequent field observations and analysis of skid resistance data permit the following conclusions: 1. Aggregate retention is influenced by lithologic type with the gravels, quartzite, haydite, dolomites, and medium grained limestones performing best. 2. Aggregate retention is not influenced by binder bitumen type. 3. Friction values of seal coats are influ-enced by aggregate retention and/or lithologic type. The following recommendations have been determined: The aggregate used for cover aggregate/seal coat projects should be Type 4 or better skid resistance as identified in Iowa DOT Materials Instructional Memorandum T-203. This will result in maximizing the possibility of good aggregate retention and skid resistance.

Characteristics of 2D convective structures in Catalonia (NE Spain): an analysis using radar data and GIS

Flood simulation studies use spatial-temporal rainfall data input into distributed hydrological models. A correct description of rainfall in space and in time contributes to improvements on hydrological modelling and design. This work is focused on the analysis of 2-D convective structures (rain cells), whose contribution is especially significant in most flood events. The objective of this paper is to provide statistical descriptors and distribution functions for convective structure characteristics of precipitation systems producing floods in Catalonia (NE Spain). To achieve this purpose heavy rainfall events recorded between 1996 and 2000 have been analysed. By means of weather radar, and applying 2-D radar algorithms a distinction between convective and stratiform precipitation is made. These data are introduced and analyzed with a GIS. In a first step different groups of connected pixels with convective precipitation are identified. Only convective structures with an area greater than 32 km2 are selected. Then, geometric characteristics (area, perimeter, orientation and dimensions of the ellipse), and rainfall statistics (maximum, mean, minimum, range, standard deviation, and sum) of these structures are obtained and stored in a database. Finally, descriptive statistics for selected characteristics are calculated and statistical distributions are fitted to the observed frequency distributions. Statistical analyses reveal that the Generalized Pareto distribution for the area and the Generalized Extreme Value distribution for the perimeter, dimensions, orientation and mean areal precipitation are the statistical distributions that best fit the observed ones of these parameters. The statistical descriptors and the probability distribution functions obtained are of direct use as an input in spatial rainfall generators.

Rainfall erosivity for the State of Rio de Janeiro estimated by artificial neural network

The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.

Determination of total accumulated rainfall, global radiation, evapotranspiration and degree-days originated from the ECMWF model to sugar cane crop

The climate variability between the growth and harvesting of sugar cane is very important because it directly affects yield. The MODIS sensor has characteristics like spatial and temporal resolution that can be applied to monitoring of vegetative vigor variability in the land surface and then, temporal profiles generation. Agro meteorological data from ECMWF model are free and easy to access and have a good representation of reality. In this study, we used the period between sugar cane growth and harvest in the state of Sao Paulo, Brazil, from temporal profiles selecting of NDVI behavior. For each period the precipitation, evapotranspiration, global radiation, length (days) and degree-days were accumulated. The periods were presented in a map format on MODIS spatial resolution of 250 meters. The results showed the spatial variability of climate variables and the relationship to the reality presented by official data.

Distribution pattern, surface tension and contact angle of herbicides associated to adjuvants on spraying and control of Ipomoea hederifolia under rainfall incidence

ABSTRACTScarlet Morning Glory is considered to be an infesting weed that affects several crops and causes serious damage. The application of chemical herbicides, which is the primary control method, requires a broad knowledge of the various characteristics of the solution and application technology for a more efficient phytosanitary treatment. Therefore this study aimed to characterize the effect of rainfall incidence on the control of Ipomoea hederifolia, considering droplet size, surface tension, contact angle of droplets formed by herbicides liquid on vegetal and artificial surfaces, associated to adjuvants and the volumetric distribution profile of the spray jet. The addition of the adjuvants to the herbicide spraying liquid improved the application quality, as it influenced the angle formed by the spray by broadening the deposition band of the spray nozzle and thus the possible distance between the nozzles on spray boom and due the changes at droplet size, which contribute to a safety application. The rainfall occurrence affected negatively the weed control with the different spraying liquids and also the dry matter weight, suggesting that the phytosanitary product applied was washed off.