Precipitation. 2.3.3 Leachate Generation Quantities
Precipitation. Precipitation was measured using a Climatronics 100097-1-G0 tipping bucket. The manufacturer- reported accuracy is ±1% up to 5.1 cm/hr and ±5% up to 25 cm/hr.
Precipitation. Phosphorus content should be determined in bulk and wet fall (rain-containing phosphorus in dry and wet forms. Review of data collected in the fall from the October 1st through March 31st will be used to forecast volume and intensity of rainfall events throughout this monitoring period. One location for a unit to monitor wet and dry fall (use a rain gage) on a weekly- or twice- monthly basis should be adequate. The rainfall patterns measured during the proposed monitoring period will provide perspective on the amount of airborne phosphorus that might be expected to be loading into the Basin and the receiving stream (Rock Creek).
Precipitation. One of the questions posed in the ESE Research Strategy is: “How are global precipitation, evaporation, and the cycling of water changing? “ Global Precipitation is the principal indicator of the rate of change of the global water cycle, and can also be used effectively as an input for numerical weather forecasting. Space-based global observations have been significantly improved by the on-going Tropical Rainfall Measuring Mission (TRMM.) Successful experience with the tropical precipitation data has led NASA to embark on an Integrated Precipitation Data System, as a SEEDS prototype for this systematic measurement. Clearly the existence of a global trend can only be established on the basis of global rainfall observations. To this end, NASA is establishing a Global Precipitation Science Team. The transition from mission-oriented measurements to systematic precipitation measurements will occur throughout the transfer from the TRMM mission to the Global Precipitation Mission being planned for 2008 timeframe, and be done in consultation with members of the soon-to-be-solicited Precipitation Science Team. NASA would like to begin fusing data from multiple sources into the data streams, increasing the spatial and temporal coverage. The concept is not to build a system as a single-point mission system, but instead to incorporate a rolling-wave of capabilities, scalable to handle satellites/instruments’ data added, deleted, replaced as required, and associated tools for their management. Partners are a key part of the concept. Ability of other existing and/or future precipitation sites to tie into data and services is envisioned. NASA encourages proposals for innovative solutions focused on creation, use and manipulation of global precipitation data. Proposals are encouraged in a number of areas not only related to precipitation data transformation and combination but also for data and information tools that can assist the Earth System science community in using existing and anticipated precipitation products in new and flexible ways. Also encouraged are proposals to help NASA hone down the concepts of thematic and systematic-parameter-oriented research systems in support of current and future precipitation missions. Such systems are assumed to be offered by providers demonstrating the capability to offer services or products that are specialized and go beyond the normal standard data products offered traditionally by a satellite mission. These services and produ...
Precipitation. Mean monthly rainfall recorded at Muzaffarabad and the numbers of rainy days are given in Table-1.The average annual rainfall of the area is about 1443 mm. The maximum rainfall occurs during the months of July, August and September, which is about 20 % of the annual rainfall. Precipitation in the study area is characterized by the monsoon season. Winter rains generally occur during the months of January, February and March. April, May, October and November are normally the months of least precipitation.
Precipitation. Work may continue up to October 31, 2020 if no rain events measuring a tenth of an inch or greater are reported by the National Weather Service Oxnard. If a rain event for a tenth of an inch or greater is forecast within 72 hours, all suction operations must stop and all equipment must be removed from the bed, bank and channel so as not to be swept into the Santa Xxxxx River. Placement of In-stream Structures and Fish Passage
Precipitation. Lusaka District receives an appreciable volume of rainfall, however almost exclusively during the rainy season. On average there is a total of 70 rain days per season. However, the monthly average number of rain days range from 6 to 15 days. The months of December, January and February receive over 70% of the rainfall in any given year as shown in Figure 5-2. In addition, long dry periods are also experienced. In the rainy season from October to April, the monthly average rainfall is 114 mm, and the average annual rainfall over the past 30 years (period 1976/77 to 2005/06) was 802 mm (JICA 2009). Figure 5-2: Monthly average rainfall and rainfall days in Lusaka Source: JICA (2009): The Study on Comprehensive Urban Development Plan for the City of Lusaka 5.2.5.3 Temperature Mean monthly temperatures for Lusaka District range from 14°C in the cold season to about 28°C in the hot season when humidity is comparatively high. Minimum temperatures which are as low as 9°C have been recorded in the month of July. While the coldest month of the year with temperatures of 30°C and above are recorded in October. Figure 5-3 shows the average maximum and minimum monthly temperatures for Lusaka District recorded for the period of 1976/77 to 2005/06. Figure 5-3 indicates an average temperature throughout the year of 20.9°C. The average monthly maximum temperature reaches the highest of 35°C in October, and drops to a lowest of 10°C in July. Figure 5-3: Monthly temperatures in the City of Lusaka Source: Zambian Meteorological Department (2006)
Precipitation. In the landslide hazard model produced for 2010 in D2.10, a monthly global dataset for the precipitation was used to estimate the expected extreme monthly precipitation (Global Precipitation Climatology Centre, Deutscher Wetterdienst, Offenbach, Germany). This dataset is now replaced with model results of the REMO model operated by the Xxx Xxxxxx Institute in Hamburg (Xxxxx 2001, Xxxxx et al. 2001). The model was first used in a control run to recalculate the current climate in the period 1981 to 2000. The same model was then applied to estimate the climate evolution in Europe until 2100. The model uses the A1B scenario defined by the IPCC (IPCC, 2007) and the boundary conditions for the regional model are defined by the global ECHAM5 model. Spatial resolution of the model is 25 × 25km. The model is described in detail in D3.1. The IPCC A1 scenarios are based on the assumptions of continuing and rapid economic growth, a global population that peaks in mid-century and rapid introduction of new and more efficient technologies. A1 is divided into three groups that describe alternative directions of technological change where (A1B) presents a balance between fossil intensive and non-fossil energy resources. To get an estimate of the extreme precipitation events, the 99.9% percentile of daily precipitation was calculated for 20 year periods from 1981-2100. This value represents the amount of daily precipitation that is exceeded every 50 years in the grid cell, and ranges from 26 mm to 1557 mm. The data are reclassified to be used in the landslide hazard model (Table 2-1) using a logarithmic classification scale. Figure 2-1 shows the development of the 99.9% percentile of precipitation in Europe for 20-year intervals from 2000 to 2100. 0.1% of all precipitation events in a 20-year period are higher than the pixel values in the maps. Table 2-1: Reclassification for 99.9% percentile of precipitation extremes in Europe Daily (24h) precipitation in millimeters Susceptibility Tp1 0 – 60 Low 1 61 – 75 Moderate 2 76 – 95 Medium 3 96 – 120 High 4 > 120 Very high 5 Figure 2-1: Absolute value of the 99.9% percentile of precipitation in Europe. 0.1% of all precipitation events in a 20 year period are higher than the pixel values in the maps. Each map represents a 20 year period (e.g. 2000-2020 is represented by 2010). Highest precipitation extremes are found in the Mediterranean, Iceland and Norway. The trend in the future is towards more extreme events in the south, whi...
Precipitation. To calculate hazard from susceptibility a trigger process is needed. In this study only precipitation as a trigger is considered. Both the normal mean and extreme precipitation events influence the triggering of landslides. Figure 3-2 shows the evolution of the 99.9% percentile of daily precipitation relative to the 2010 situation. There is a clear positive trend in the daily precipitation extremes on Iberia, central Europe and Greece. Here, precipitation of short duration and high intensity will increase, while the changes further north are much less obvious. Decreasing annual precipitation seems to lead to more extreme events. This can also be seen in the more continental areas of Ukraine, Belarus and Russia. The model predicts very little change in other countries, for example Hungary. Also the total amount of rainfall (Figure 3-3) shows a similar trend. More rain in the north and less in the southern parts of Europe is expected from climate model results. It should be noted that this analysis is based on daily precipitation values that do not always represent intensive convective showers with only short duration such as thunder storms. Figure 3-2: Changes in the 99.9% percentile 2010 – 2090 relative to the 2010 situation. More extreme events can be expected mostly on Iberia, central Europe and Greece.
Precipitation. Chromium precipitation is modeled using geochemical reaction equilibria in UTCHEM. Cr(III) precipitates in the form of chromium hydroxide complex. Cr3+ + H2O = Cr(OH)2+ + H+ (6.7) Cr3+ + 2 H2O = Cr(OH)+ + 2 H+ (6.8)
