Distribution Of Rain Events Research Articles

Spatial and Temporal Distribution of Soil Moisture at the Catchment Scale Using Remotely-Sensed Energy Fluxes

Despite playing a critical role in the division of precipitation between runoff and infiltration, soil moisture (SM) is difficult to estimate at the catchment scale and at frequent time steps, as is required by many hydrological, erosion and flood simulation models. In this work, an integrated methodology is described to estimate SM at the root zone, based on the remotely-sensed evaporative fraction (Λ) and ancillary information on soil and meteorology. A time series of Terra MODIS satellite images was used to estimate SM maps with an eight-day time step at a 250-m spatial resolution for three diverse catchments in Europe. The study of the resulting SM maps shows that their spatial variability follows the pattern of land cover types and the main geomorphological features of the catchment, and their temporal pattern follows the distribution of rain events, with the exception of irrigated land. Field surveys provided in situ measurements to validate the SM maps’ accuracy, which proved to be variable according to site and season. In addition, several factors were analyzed in order to explain the variation in the accuracy, and it was shown that the land cover type, the soil texture class, the temporal difference between the datasets’ acquisition and the presence of rain events during the measurements played a significant role, rather than the often referred to scale difference between in situ and satellite observations. Therefore, the proposed methodology can be used operationally to estimate SM maps at the catchment scale, with a 250-m spatial resolution and an eight-day time step.

Rainfall variability drives interannual variation in N2O emissions from a humid, subtropical pasture

Variations in interannual rainfall totals can lead to large uncertainties in annual N2O emission budget estimates from short term field studies. The interannual variation in nitrous oxide (N2O) emissions from a subtropical pasture in Queensland, Australia, was examined using continuous measurements of automated chambers over 2 consecutive years. Nitrous oxide emissions were highest during the summer months and were highly episodic, related more to the size and distribution of rain events than soil water content. Over 48% of the total N2O emitted was lost in just 16% of measurement days.Interannual variation in annual N2O estimates was high, with cumulative emissions increasing with decreasing rainfall. Cumulative emissions averaged 1826.7±199.9gN2O-Nha−1yr−1 over the two year period, though emissions from 2008 (2148±273gN2O-Nha−1yr−1) were 42% higher than 2007 (1504±126gN2O-Nha−1yr−1). This increase in annual emissions coincided with almost half of the summer precipitation from 2007 to 2008. Emissions dynamics were chiefly driven by the distribution and size of rain events which varied on a seasonal and annual basis.Sampling frequency effects on cumulative N2O flux estimation were assessed using a jackknife technique to inform future manual sampling campaigns. Test subsets of the daily measured data were generated for the pasture and two adjacent land-uses (rainforest and lychee orchard) by selecting measured flux values at regular time intervals ranging from 1 to 30days. Errors associated with weekly sampling were up to 34% of the sub-daily mean and were highly biased towards overestimation if strategically sampled following rain events. Sampling time of day also played a critical role. Morning sampling best represented the 24hour mean in the pasture, whereas sampling at noon proved the most accurate in the shaded rainforest and lychee orchard.

Assessing the impact of climate change on representative field crops in Israeli agriculture: a case study of wheat and cotton

Climate changes, associated with accumulation of greenhouse gases, are ex- pected to have a profound influence on agricultural sustainability in Israel, a semi-arid area characterized by a cold wet winter and a dry warm summer. Accordingly this study explored economic aspects of agricultural production under projected climate-change scenarios by the "production function" approach, as applied to two representative crops: wheat, as the major crop grown in Israel's dry southern region, and cotton, representing the more humid climate in the north. Adjusting outputs of the global climate model HadCM3 to the specific research locations, we generated projections for 2070-2100 temperatures and precipitations for two climate change scenarios. Results for wheat vary among climate scenarios; net revenues become negative under the severe scenario (change from �145 to �273%), but may increase under the moderate one (�43 to +35%), depending on nitrogen applied to the crop. Distribution of rain events was found to play a major role in determining yields. By contrast, under both scenarios cotton experiences a considerable decrease in yield with significant economic losses (�240 and �173% in A2 and B2 scenarios, respectively). Additional irrigation and nitrogen may reduce farming losses, unlike changes in seeding dates.

A sandpile model for the distribution of rainfall?

Recently, Peters et al. (Phys. Rev. Lett. 88 (2002) 018701)) have found power-law behaviour in the distribution of rain events. Here it is shown that the observed self-similar features in both the reservoir level and the distribution of rain events, can quantitatively be reproduced from an extension to two dimensions of the Oslo-model developed to describe the dynamics of a pile of rice. Furthermore, it is argued that the sandpile model may be able to reproduce more detailed features such as the shape of cumulus clouds. In addition, many other systems, which show self-similarity in their time variations with the same quantitative characterizations, are discussed.

POTENTIAL EFFECTS OF CHANGED CLIMATES ON HEAVY RAINFALL FREQUENCIES IN TIlE MIDWEST

: An important question posed by potential future shifts in climate relates to possible shifts in heavy rainfall events (intensity and/or frequency) used to design hydraulic structures. Heavy rain events were defined as those producing amounts having average recurrence intervals of two years or longer for a specific storm period at a given location. Estimates of such heavy rainfall shifts in the humid continental climate of the midwest were derived by using spatial and temporal analogs. Comparisons in areas of relatively warm, wet conditions were made with those having measurably cooler, drier average conditions. The spatial-temporal analogs provided comparative differences in precipitation and temperature similar to the magnitude of changes obtained from GCM estimates. Spatial analogs/analyses indicated 10 to 15 percent increases in the frequency distribution of rain events having recurrence intervals of 5 to 50 years. Two periods of notably drier and warmer conditions during the past 90 years revealed 5 to 15 percent decreases in the number of 2- to 10-year heavy rain events. The suppression percentages showed a strong tendency to increase with increasing recurrence interval from 2 to 10 years.