Terms Of Rainfall Research Articles

Precipitation Forecast Based on WA-SVM Theory

In order to improve the precision of medium-long term rainfall forecast, the rainfall estimation model was set up based on wavelet analysis and support vector machine (WA-SVM). It decomposed the original rainfall series to different layers through wavelet analysis, forecasted each layer by means of SVM, and finally obtained the forecast results of the original time series by composition. The model was used to estimate the monthly rainfall sequence in the watershed. Comparing with other method which only uses support vector machine(SVM), it indicates that the estimated accuracy was improved obviously.

Performance Analysis of a PV Pump Harvesting Rain Water in the Drought Prone Area of Bangladesh

In this paper the performance of a PV driven water pump, without battery storage, for supplemental irrigation by harvesting rainwater is analyzed. A brushless DC motor is used in this work. The worst day, in terms of rainfall, of the month of July has been chosen for data collection. The variation of the flow rate as a function of the PV array power is found to be linear. Head loss is calculated and found greater at higher flow rate. Lower trend of the subsystem efficiency is observed with the increment of the array power. Considering the module efficiency of the manufacturer, the system efficiency is also calculated and found 3.2% as the highest. The amount of water lifted is found to be quite satisfactory for supplemental irrigation.DOI: http://dx.doi.org/10.3329/dujs.v60i1.10333 Dhaka Univ. J. Sci. 60(1): 37-41, 2012 (January)

Changing Agro - Ecological Scenario with Climate Change as Perceived by Farmers in Bundelkhand, India

Climate change in the form of increased climatic variability at intra- and inter-annual and decadal time scales is the most talked problem that we are hearing today particularly in agricultural production. This study examines how farmers in the Bundelkhand of India perceive climatic change and an attempt has been made to analyze the temporal changes in agro ecology in terms of crops, cropping pattern, their productivity, animal population, irrigation systems, available water resources, vegetation cover, etc. over last 5-6 decades with reference to prevailing climate. This research used a “bottom-up” approach, which seeks to gain insights from the farmers themselves through household surveys, group interviews with key informants and following an open-ended approach when asking questions. The accuracy of the perceptions in deviations observed in the idealized local weather cycle was measured by analyzing the climatic data from 1975–2007 obtained from the nearest observatory. The communities at study area are highly aware of changes in climate and see a strong change in the ideal local weather calendar in terms of rainfall, rainy days, winter rains, droughts, temperature and wind. Further, they perceived a definite change in agro ecology of the region and see climate, though not sole, but an important cause of it.

Plant-parasitic nematodes associated with weeds in subsistence agriculture in South Africa

Twenty-nine plant-parasitic nematode species belonging to 15 genera, as well as two fungus-feeding nematode genera and one species, were identified from soil and root samples of weeds collected from 67 localities situated in subsistence production regions of South Africa during a survey from 2005-2006. Of these, 16 nematode species from four genera were reported for the first time to infect or to be associated with weeds. The predominant endo- and semi-endoparasites identified both from soil and root samples were Meloidogyne species, Pratylenchus zeae, Helicotylenchus dihystera and Rotylenchus unisexus. Based on PCR technology, three Meloidogyne species, M. hapla, M. incognita and M. javanica, have been identified in roots of weeds sampled. Thirty weed species representing 26 genera were identified as hosts of Meloidogyne species, while 38 belonging to 35 genera were associated with various other plant-parasitic nematodes. Meloidogyne species were predominant in the roots of Chloris virgata, Cynodon dactylon and Amaranthus hybridus. The frequency of occurrence of Meloidogyne species, H. dihystera and R. unisexus was significantly and positively correlated with localities in terms of % clay and % silt. The same trend was evident for these three taxa in terms of rainfall, while the opposite was observed in terms of their frequency of occurrence and pH. Principal component analysis results substantiated the latter. It also suggested that all four predominant plant-parasitic nematode species tend to occur more frequently at localities where maize was mono-cropped as well as where maize and vegetables were planted in rotation. Cynodon dactylon, Cyperus rotundus, Datura stramonium, Tagetes minuta and Eleusine corocana had the highest frequency of occurrence of weeds sampled. Identification of weeds that maintain plant-parasitic nematodes, particularly Meloidogyne species, suggested that these pathogens can have a negative impact on crop production when not controlled timely and effectively.

Estimating recharge distribution using remote sensing: A case study from the West Bank

Summary Estimating groundwater recharge to the aquifer system is a very important element in assessing the water resources in regions of the world with poorly developed hydrological measurement stations such as the West Bank. Previous studies have developed analytical recharge models that are based on the long-term annual rainfall data. These models have been shown to be inadequate and changes over shorter periods, e.g. monthly estimates, must be known in order to study the temporal distribution of recharge. The approach used in this research integrates data derived from satellite images (e.g. land cover, evapotranspiration, precipitation, and digital elevation model) with hydrogeological data in a Geographic Information System (GIS) model to identify surface recharge areas on a pixel-by-pixel basis. The Surface Energy Balance Algorithm for Land (SEBAL) is applied to time series of MODerate Resolution Imaging Spectroradiometer (MODIS) Level 3 data of reflectance and surface temperature measurements to estimate monthly evapotranspiration; precipitation is derived from the monthly data sets of the Tropical Rainfall Measuring Mission (TRMM); runoff is given assumed values of 1.0 mm month −1 and 0.5 mm month −1 for the months of January and February, respectively. Recharge is quantified from November until March by applying the water balance method where evapotranspiration estimates and runoff are subtracted from precipitation. Results show good agreement between available numbers reported in literature and the remote sensing-based analysis. Empirical models that are based on long term rainfall measurements result values between 800 and 836 MCM yr −1 while the remote sensing based model results a recharge estimate of between 650 and 750 MCM yr −1 .

Results Regarding the Growing Marigold (Calendula Officinalis L.) in Climatic Conditions from Jucu, Cluj

In the experimental field of UASVM Cluj-Napoca from Jucu we performed, between 2008-2010, a series of research on the behavior of eight varieties of marigold, in three conditions of soil fertilization with manure. The average yearly air temperature is 10.71 º C Jucu in 2008, 11.12 º C in 2009 and 11.21 º C in 2010 and during the growing season (aprilie-sept.) of 17.70 ° C 19.07 ° C and 18, 08 ° C. In terms of rainfall, 2008 was very dry (less than 150 mm from the annual average), 2009 excessively dry (less than 250 mm annual average) and 2010 was very wet (83 mm more than the annual average). Climatic conditions were favorable to grow marigolds.
 A series of biometric measurements have been conducted on the eight varieties of marigold, such as waist measurement of the average plant, the production of flowers and drying efficiency, the correlation between average plant size and production.
 Average plant size in eight varieties of marigold, in 2008-2010 was between 67.44 and 84.78 cm. Production of fresh flowers was between 7400 and 8507 kg / ha.
 The biggest production of inflorescences was obtained from varieties of ”Belezza del Pacifico”, ”Cluj 2” and ”Starsem 922”, with over 9.000 kg / ha of fresh flowers. Production of Marigold is strongly influenced by genotype and fertilization. The average yield of drying was 6 / 1.
 Between the average height of marigold plant and production there's a direct link. The increase of production is influenced by the average size of marigold plant.

Time series analysis of ground water table fluctuations due to temperature and rainfall change in Shiraz plain

This research aims at forecasting ground water fluctuations due to temperature and rainfall effects using time series and cross-correlation analysis. Box Jenkins’s time series model was analyzed and the best one for Shiraz plain proved to be multiplicative seasonal. This model was used to forecast the future ground water fluctuations as affected by long term temperature and rainfall data. Results showed that the average annual water table elevation was 1499.31 for year 2021. The elevation for the year 2007 was 1501.03 showing 1.72 meter decline. Among 29 wells, statistical analysis showed that 89% of the wells had a negative correlation with monthly temperature but 86% of them showed a positive correlation with monthly rainfall. A cross-correlation analysis using individual wells showed 44.8% of wells had a delay time due to temperature changes between zero to 2 months, 51% between 10 to 14 months and only 3.5% of 26 months. Also, 72.4% of wells had a response time due to rainfall of zero to 2 months, 24.1% between 11 to 23 months and the response of 3.5% was 38 months. On average, the delay time of water table fluctuation due to temperature changes for Shiraz plain was 13 months and due to rainfall was 1 month. Key words: Box Jenkings model, temperature, rainfall, cross-correlation, water table level, plain, correlation, time delay, change, multiplicative seasonal model.

Temporal patterns of net CO2exchange for a tropical semideciduous forest of the southern Amazon Basin

[1] The carbon cycling of tropical ecosystems has received considerable attention over the last 1–2 decades; however, interactions between climate variation and tropical forest net ecosystem CO2 exchange (NEE) are still uncertain. To reduce this uncertainty, and assess the biophysical controls on NEE, we used the eddy covariance method over a 3 year period (2005–2008) to measure the CO2 flux and energy balance for a 25–28 m tall, mature tropical semideciduous forest located near Sinop Mato Grosso, Brazil. The study period encompassed warm-dry, cool-wet, and cool-dry climate conditions, and based on previous research, we hypothesized that the net CO2 accumulation of the semideciduous forest would be lower during periods of drought. Using time series of the enhanced vegetation index (EVI), a NEE-light-use model, and path analysis, we found that the estimated quantum yield (a′, μmol CO2μmol photons−1) was directly affected by temporal variations in the EVI, precipitation, and photosynthetically active radiation (PAR), while the optimal rate of gross primary production (FGPP,opt, μmol m−2 s−1) was directly affected by the EVI and PAR. However, indirect effects of precipitation on the a′ and FGPP,opt were stronger than direct effects because variations in precipitation also lead to variations in the EVI and the atmospheric vapor pressure deficit (VPD). Daytime ecosystem respiration (FRE,day, μmol m−2 s−1) was directly affected by temporal variations in temperature and VPD and indirect effects of other variables were of lesser importance. Net ecosystem CO2 uptake was often higher in the dry season than the wet season, not because of a dry season “green-up” but because rates of ecosystem respiration declined relatively more than rates of canopy photosynthesis. Over interannual timescales, average daily NEE increased over the 3 year study period and was highest in 2007–2008, which was also the driest year in terms of rainfall. However, 2007–2008 was also the coolest year during the 3 year study period, and the low temperature appeared to compensate for the low rainfall. Overall, our data suggest that the NEE of tropical semideciduous forests is sensitive to temporal variations in surface water availability but that indirect effects of other variables, such as temperature and VPD, are important in controlling CO2 gain and loss. Such interactions will be important for the future NEE under warmer and drier conditions that are anticipated with anthropogenic climate change.

Effect of subsampling tropical cyclone rainfall on flood hydrograph response in a subtropical mountainous catchment

Summary Accurate rainfall input is a prerequisite for simulations that aim to generate accurate hydrographs, which are crucial for flood forecasting, particularly in regions that are prone to frequent typhoon (tropical cyclone) invasions, such as Southern Asia. Few studies have investigated the effect of spatial resolution in typhoon rainfall monitoring on modeled hydrographs. Eight typhoon cases were examined in a mountainous watershed (335 km2) featuring hourly radar-based 1.3-km resolution rainfall estimates. Radar-based hourly rainfall was subsampled at various densities in space, and then re-interpolated to full scale for modeling. The highest resolution rainfall datasets were taken as an ideal input in TOPMODEL for calibration and to derive the reference hydrographs, which were further used to examine the response of modeled hydrographs to imperfect rainfall. The correlation between rainfall similarities (compared with radar-based) and corresponding hydrograph similarities (compared with reference) were identified. The two most important findings were as follows: (1) in predicting flood peak timing in mesoscale watershed, high spatial resolution is not required because typhoon-induced rainfall is less variable in space and more concentrated in the temporal scale and (2) satisfactory hydrographs with EC > 0.8 were obtained in 96% test cases, indicating that even a totally biased rainfall (in terms of total amount and rainfall field) may produce a plausible hydrograph. Hydrologic models transfer the spatiotemporal rainfall input into time-series discharge, in which the spatial dimension is converted into travel time. Those positive and negative rainfall biases in space may compensate once allocated in the same arrival time frame in the hydrograph. This explains why in many cases sparsely gauged rainfall input also generates promising hydrographs. In other words, as discussing the effect of other distributed factors on simulated hydrographs, the highly accurate rainfall input is an essential prerequisite to prevent the compensation.

Comparison of two methodologies for long term rainfall monitoring using a commercial microwave communication system

Rainfall measurements have been investigated worldwide because of their important implications in meteorology, hydrology, flood warnings and fresh water resource management. Recently a new way of measuring rainfall based on commercial microwave radio links that form cellular communication networks has been proposed, in which the path-integrated rainfall intensity is estimated from the received signal level. This method can reveal fine-scale evolution of rainfall in space and time and allows observation of near-surface rainfall at a spatial resolution of up to 1×1km2 and a temporal resolution of up to 1min, with no additional installation and maintenance costs. Here we examine two different methodologies for calculating instantaneous rainfall from microwave links. The study region covers a 1600km2 area in central Israel which includes up to 70 commercial microwave links, and 7 rain gauges installed in the vicinity of the links. 19 rainstorm events over a two year period covering about a 676h overall period, are evaluated. The first methodology uses data from the nearest microwave link while the second uses data interpolated at the point of the rain gauge from multiple nearby links. Results are compared to results from nearby rain gauges. At temporal resolutions of 1min correlations of 0.65 and .77, with biases of −0.08 and −0.06mmh−1 were attained for the first and second methods, respectively. At the temporal resolution of 10min, the correlations of 0.84 and 0.85, with biases of −0.11 and −0.06mmh−1 were attained. On average, application of the interpolation point methodology underestimated accumulated rainfall by only 3% as compared to nearby rain gauges. The single link method overestimated rainfall by 6%. Both methodologies improved (worsened) as the density of the microwave link grid increased (decreased).

Trend detection in rainfall and evaluation of standardized precipitation index as a drought assessment index for rice–wheat productivity over IGR in India

AbstractThe frequency and intensity of meteorological droughts over the Indo‐Gangetic Region (IGR) of India pertaining to the rice crop during kharif season (June to July to October to November) and the wheat crop during the rabi season (November to December to March) were assessed using the standardized precipitation index (SPI). The monthly distribution of rainfall is more crucial than the cumulative seasonal rainfall on rice–wheat (RW) productivity. Consequently, an attempt was made to measure the effectiveness of using monthly SPI from June to September to assess drought on RW productivity over five major RW growing states of IGR in India. An attempt is also made to test the use of monthly SPI for the early kharif rice and rabi wheat forecasts for these states. The long‐term (1906–2005) mean annual rainfall of IGR is 1099.1 mm with a standard deviation of 115.7 mm and a coefficient of variation of 10.5%. It was observed that the kharif rice productivity index and monthly SPI from June to September have a significant (R2 = 0.44) multiple regression at 0.001 level over IGR. It was also observed that in the Indo‐Gangetic Region, the wheat productivity index and monthly SPI (June to September) have an insignificant (R2 = 0.21) multiple regression. It indicated that the monthly distribution of monsoon rainfall in terms of the SPI accounted for 44% yield variability in rice and 21% yield variability in wheat. Thus, these indices may be used for forecasting the productivity of the RW system over IGR states in India. Copyright © 2010 Royal Meteorological Society

휴대용 TDR 함수량계로 측정한 현장 함수비를 이용한 현장 상온 재활용 아스팔트 포장의 수분 감소계수 개발

최근 10년간 전세계적으로 아스팔트 포장을 재활용하는 기술이 급속도로 확산되고 있으며 노후 아스팔트 포장을 폼드 아스팔트 또는 유화 아스팔트를 사용하여 현장에서 바로 100% 재활용하는 현장 상온 재생 아스팔트 포장기술이 다양하게 적용되고 있다. 특히, 아이오와 주에서는 교통량이 적은 지방도로에서 기존 포장의 수명을 연장 시켜주는 현장 상온 재생 아스팔트 공법을 많이 적용하고 있다. 일반적으로 현장 상온 재생 아스팔트 포장층은 수분의 침투나 교통하중으로부터 보호하거나 포장설계를 만족시키기 위해 가열 아스팔트 포장으로 덧씌우기를 한다. 일반적으로 현장 상온 재생 아스팔트 포장층 위에 가열 아스팔트 포장으로 덧씌우기 할 시기는 대부분에 감독자들은 일정한 양생기간 또는 최대 함수비에 근거하여 결정하고 있다. 따라서, 본 연구에서는 감독자가 최적에 덧씌우기 아스팔트 포장 시기를 결정할 수 있도록 현장 상온 재생 아스팔트 포장층의 현장 함수비를 간단하게 측정하여 덧씌우기 시기를 결정할 수 있는 수분 감소계수를 개발하는 것이다. 먼저, 현장 상온 재생 아스팔트 포장층의 함수비를 TDR 함수량계를 사용하여 측정하였고 현장 상온 재생 아스팔트 포장이 시공되는 기간 동안에 강우량, 대기온도, 습도, 바람속도 등 기상정보를 수집하였다. 마지막으로 현장 상온 재생 아스팔트 포장의 초기 함수비, 대기온도, 습도, 바람속도를 변수로 하는 수분 감소계수를 개발하였다. 실제 현장 상온 재생 아스팔트 포장에서 측정한 값을 사용하여 개발한 수분 감소계수는 감독자가 연속적으로 현장 상온 재생 아스팔트 포장층의 함수비를 측정하지 않고 최적의 덧씌우기 포장 시점을 결정할 수 있다. The practice of asphalt pavement recycling has grown rapidly over the decade, one of which is the cold in-place recycling with the foamed asphalt (CIR-foam) or the emulsified asphalt (CIR-emulsion). Particularly, in Iowa, the CIR has been widely used in rehabilitating the rural highways because it significantly increases the service life of the existing pavement. The CIR layer is typically overlaid by the hot mix asphalt (HMA) to protect it from water ingress and traffic load and obtain the required pavement structure and texture. Most public agencies have different curing requirements based on the number of curing days or the maximum moisture contents for the CIR before placing the overlay. The main objective of this study is to develop a moisture loss index that the public agency can use to monitor the moisture content of CIR layers in preparation for a timely placement of the wearing surface. First, the moisture contents were measured in the field using a portable time domain reflectometry (TDR) device. Second, the weather information in terms of rain fall, air temperature, humidity and wind speed was collected from the same location. Finally, a moisture loss index was developed as a function of initial moisture content, air temperature, humidity and wind speed. The developed moisture loss index based on the field measurements would help the public agency to determine an optimum timing of an overlay placement without continually measuring moisture conditions in the field.

Soil seed bank dynamics in relation to land management and soil types in the semi-arid savannas of Swaziland

In the semi-arid savannas of Swaziland, communal grazing, commercial ranches and game reserves are the main land management systems for animal production. These land uses can have different ecological effects on the rangelands. This study was conducted to investigate the differences in soil seed bank characteristics between three land management systems having high (communal land), low (government ranch) and medium (game reserve) stocking rates, and soil types (lithosol and vertisol or raw mineral). Two grazing areas (Bigbend and Simunye) each with the three land management systems and soil types were selected for this study. A total of 40 plant species were identified in the seed bank of both grazing areas. Panicum maximum dominated both grazing areas. Cencrhus ciliaris was dominant in Bigbend area, while Digitaria eriantha was dominant in Simunye area. Seedling density varied (P<0.05) among the land management systems and soil types. The difference in past and recent grazing pressure may be the primary cause of the observed differences. In all study sites, the soil seed bank was a poor reflection of the aboveground vegetation as revealed by weak similarity. In Bigbend, P. maximum and Urochloa mosambicensis were well represented in the seed bank. In Simunye, however, these two species were comparatively under-represented. Whereas the regeneration of the aforementioned two species from the seed bank may be high and have a profound effect in restoration of rangelands after disturbance, this may be affected by spatial differences in terms of rainfall and soil. Valuable species under-represented in the seed bank can be prone to extinction under heavy utilization and therefore, in situ conservation within certain localities should receive high priority.

The Effect of Satellite Rainfall Error Modeling on Soil Moisture Prediction Uncertainty

Abstract This study assesses the impact of satellite rainfall error structure on soil moisture simulations with the NASA Catchment land surface model. Specifically, the study contrasts a complex satellite rainfall error model (SREM2D) with the standard rainfall error model used to generate ensembles of rainfall fields as part of the Land Data Assimilation System (LDAS) developed at the NASA Global Modeling and Assimilation Office. The study is conducted in the Oklahoma region, which offers good coverage by weather radars and in situ meteorological and soil moisture measurement stations. The authors used high-resolution (25 km, 3-hourly) satellite rainfall fields derived from the NOAA/Climate Prediction Center morphing (CMORPH) global satellite product and rain gauge–calibrated radar rainfall fields (considered as the reference rainfall). The LDAS simulations are evaluated in terms of rainfall and soil moisture error. Comparisons of rainfall ensembles generated by SREM2D and LDAS against reference rainfall show that both rainfall error models preserve the satellite rainfall error characteristics across a range of spatial scales. The error structure in SREM2D is shown to generate rainfall replicates with higher variability that better envelop the reference rainfall than those generated by the LDAS error model. Likewise, the SREM2D-generated soil moisture ensemble shows slightly higher spread than the LDAS-generated ensemble and thus better encapsulates the reference soil moisture. Soil moisture errors, however, are less sensitive than precipitation errors to the complexity of the precipitation error modeling approach because soil moisture dynamics are dissipative and nonlinear.

Using probabilistic radar rainfall nowcasts and NWP forecasts for flow prediction in urban catchments

The use of Quantitative Precipitation Forecasts (QPFs) to model run-off and flow processes in urban areas is a challenging problem, as rainfall data with high spatial and temporal resolutions are required. Many attempts have been made to use weather radar to produce rainfall forecasts with lead times of a few hours ahead. The UK Met Office in collaboration with the Australian Bureau of Meteorology has developed a stochastic probabilistic precipitation forecasting scheme (STEPS), which merges an extrapolation radar rainfall forecast with a high-resolution Numerical Weather Prediction (NWP) rainfall forecast. This paper assesses the application of this model in a small urban area (town of Yorkshire). Three precipitation events that occurred during 2007 and 2008 with different meteorological characteristics were simulated. The STEPS model was used to produce both deterministic and ensemble precipitation forecasts with spatial and temporal scales of 2 km and 15 min respectively and 6-hour lead time. The precipitation forecasts were coupled to an Infoworks CSmodel of the sewer system of a town in Yorkshire to produce flow predictions. The simulated precipitation events were analyzed in terms of rainfall and flow predictions at the urban scale of the study area. The results show that the overall performance of the rainfall forecasting system decreases with increasing rainfall intensities, and that the ensemble rainfall forecasts have a higher skill than the deterministic forecasts in predicting lower rainfall intensities. The results also show that stratiform precipitation is forecasted better than convective precipitation. More events need to be evaluated in order to define whether ensemble rainfall forecasts improve flow predictions on the urban scale and the analysis in terms of flow at this stage only supports a potential application for qualitative flood warnings in the small urban catchment considered.

Long term rainfall forecasting by integrated artificial neural network-fuzzy logic-wavelet model in Karoon basin

Physical, mathematical models and statistical distribution are applied to forecasting, whereas in natural resources, it is difficult to choose models that are closed to reality. Rainfall forecasting as an important dynamic process is ever favored by the researchers. Analyzing the behavior of these phenomena by intelligent systems is completely better than classical methods, because of high non-linear dynamic atmospheric phenomena. In this paper, a long term forecasting method is presented by a combination of intelligent methods with the use of the past month rainfall in karoon basin and global meteorological signals such as southern oscillation index (SOI), north athletics oscillation (NAO), sea level pressure (SLP), sea surface temperature (SST) and 41 years historical data. This method is obtained by the combination of artificial neural network, fuzzy logic and wavelet functions. In this model, several scenarios have been examined for the karoon basin of Iran, through the signals. SST and NAO signals show the best results, and then, the long-term forecasts are done for periods of six months, one year and two years. The results of the integrated model showed superior results when compared to the two-year forecasts to predict the six-month and annual periods. As a result of the root mean squared error, predicting the two-year and annual periods is 6.22 and 7.11, respectively. However, the predicted six months shows 13.15. Key words: Intelligent networks, long-term prediction, meteorological signals, artificial neural network, fuzzy logic, wavelet function.

Lithologically constrained rainfall (LCR) method for estimating spatio-temporal recharge distribution in crystalline rocks

► We developed lithologically constrained rainfall method to estimate recharge. ► Soil resistivity and vadose zone thickness represents the lithological variability. ► This determines the spatio-temporal natural recharge distribution in hard rock terrain. ►LCR method is applicable at local as well as regional scale. A lithologically constrained rainfall (LCR) method has been developed to estimate the spatial and temporal natural recharge distribution, a complex and high variable hydrological parameter in hard rocks. The lithological constraints are coupled to the rainfall in terms of soil resistivity ( ρ s ) and vadose zone thickness ( H ). In the absence of a bore-well in an over-exploited area with deep water table, it is difficult to get the water table precisely from any surface exploration methods such as remote sensing and geophysics. However, water table variation being close to the basement in this situation, depth-to-basement was used as an alternative to the vadose zone thickness, which yielded equally reliable estimate. The method facilitates to estimate temporal due to time varying rainfall and spatial due to lithological variability, distribution of natural recharge for many numbers of years (say ±50) by inputting the precipitation of corresponding years, provided once hydrogeophysical ( ρ s and H ) parameters are known. The method has been successfully validated and applied to study the watershed scale in a granitic terrain and found that the variability is much higher than otherwise expected or estimated by a single method.

The behavior of some winter barley varieties in the climatic conditions of the central Moldavian plateau

This paper presents the enviromental testing research results of seven romania varieties of winter barley, experienced on Agricultural Research and Development Station (ARDS) of Secuieni, Neamţ county, Romania, during 2007 - 2010. By this was followed the zoning of the most adjusted and efficient genotypes, increasing their biodiversity so that to reduce the genetic and ecological vulnerability of the agroecosystems. In the last three years (2007 - 2010) was revealed the tendency of large fluctuations occurrence, both in terms of rainfall and temperature, from a normal crop year (2007 - 2008) in a dry year (2008 - 2009) and a rainy year (2009 2010). In the crop year 2009 - 2010, because of spring weather conditions that favored the installation of pathogen agents (Erysiphe graminis f.sp. hordei, Pyrenophora graminea, Pyrenophora teres, Puccinia hordei), but especially of the rainfall fallen in the last decade of June, which negatively influenced the evolution of the barley crop and contributed to the quantity (by shaking the beans in the ear) and quality deteriorating of

SEDIMENT HAZARD ANALYSIS BASED ON ANTECEDENT RECIPITATION INDEX AND REGIONAL DATA IN TOKYO

We have evaluated relationship between sediment hazard, regional geomorphic properties and heavy rainfall in Tokyo. It tried to clarify regional characteristic of the sediment hazard by using spatial numeric information. The antecedent precipitation index was used sediment analysis as heavy rainfall condition. The results obtained are as follows; 1) It was clarified that the sediment hazard have a greater tendency to long term rainfall than short term heavy rainfall. 2) It shows a regular relationship between relief energy and antecedent precipitation index in case of sediment hazard evaluation excepting the complex geo geological condition.

The climate of cloud forests

AbstractThis chapter analyses the climatic conditions prevailing at sites where tropical montane cloud forests (TMCF) have been reported. Spatial data‐sets of climate were used to describe the climate at 477 cloud forest sites identified by United Nations Environment Program (UNEP)‐WCMC. Some 85% of the sites are found at altitudes between 400 and 2800 m a.s.l., with an average altitude of 1700 m. The range of altitudes at which cloud forests are found is extensive (220–5005 m). The climate of cloud forests is highly variable from site to site, with an average rainfall of ∼2000 mm year−1 and an average temperature of 17·7 °C. In addition, cloud forests are found in seasonal and aseasonal environments alike, both in terms of rainfall and temperature. There are some clear differences in the climates of cloud forests found in Africa, Latin America and the Caribbean, and those in Asia. Cloud forests are found to be wetter (with incident rainfall being 184 mm year−1 higher on average), cooler (by 4·2 °C on average), and less seasonally variable than other montane forests not affected significantly by fog and low cloud. Cloud forests are also almost completely confined to a zone within 350 km from the nearest coast. Finally, the climatic representativity of 14 intensively studied cloud forest sites (ISS) was analysed, as a group, the sites provided a fair representation of the climates found in cloud forests, evenly covering the ranges in temperature and rainfall. The majority of cloud forest sites occur in regions with 2000–2600 mm of rainfall and annual mean temperatures (Tmean) of 14–18 °C. Relatively dry cloud forest sites (&lt;1000 mm of rain year−1) are under‐represented in the UNEP‐WCMC data‐base. Copyright © 2010 John Wiley &amp; Sons, Ltd.