On the Local-Scale Spatial Variability of Daily Rainfall in the Highlands of the Blue Nile: Observational Evidence

Author(s):  
Menberu M. Bitew ◽  
M. Gebremichael ◽  
F. A. Hirpa ◽  
Y. Michael ◽  
Y. Seleshi ◽  
...  
2009 ◽  
pp. n/a-n/a ◽  
Author(s):  
Menberu M. Bitew ◽  
M. Gebremichael ◽  
F. A. Hirpa ◽  
Y. M. Gebrewubet ◽  
Y. Seleshi ◽  
...  

2006 ◽  
Vol 36 (11) ◽  
pp. 2794-2802 ◽  
Author(s):  
Ben Bond-Lamberty ◽  
Karen M Brown ◽  
Carol Goranson ◽  
Stith T Gower

This study analyzed the spatial dependencies of soil moisture and temperature in a six-stand chronosequence of boreal black spruce (Picea mariana (Mill.) BSP) stands. Spatial variability of soil temperature (TSOIL) was evaluated twice during the growing season using four transects in each stand, employing a cyclic sampling design with measurements spaced 2–92 m apart. Soil moisture (θg) was measured on one occasion. A spherical model was used to analyze the geostatistical correlation structure; θg and TSOIL at the 7- and 21-year-old stands did not exhibit stable ranges or sills. The fits with stable ranges and sills modeled the spatial patterns in the older stands reasonably well, although unexplained variability was high. Calculated ranges varied from 3 to 150 m for these stands, lengths probably related to structural characteristics influential in local-scale energy transfer. Transect-to-transect variability was significant and typically 5%–15% of the mean for TSOIL and 10%–70% for θg. TSOIL and θg were negatively correlated for most stands and depths, with TSOIL dropping 0.5–0.9 °C for every 1% rise in θg. The results reported here provide initial data to assess the spatial variability of TSOIL and θg in a variety of boreal forest stand ages.


2020 ◽  
Vol 8 ◽  
Author(s):  
Benjamin Bois ◽  
Basile Pauthier ◽  
Luca Brillante ◽  
Olivier Mathieu ◽  
Jean Leveque ◽  
...  

2009 ◽  
Vol 22 (5) ◽  
pp. 1313-1324 ◽  
Author(s):  
Romain Marteau ◽  
Vincent Moron ◽  
Nathalie Philippon

Abstract The spatial coherence of boreal monsoon onset over the western and central Sahel (Senegal, Mali, Burkina Faso) is studied through the analysis of daily rainfall data for 103 stations from 1950 to 2000. Onset date is defined using a local agronomic definition, that is, the first wet day (>1 mm) of 1 or 2 consecutive days receiving at least 20 mm without a 7-day dry spell receiving less than 5 mm in the following 20 days. Changing either the length or the amplitude of the initial wet spell, or both, or the length of the following dry spell modifies the long-term mean of local-scale onset date but has only a weak impact either on its interannual variability or its spatial coherence. Onset date exhibits a seasonal progression from southern Burkina Faso (mid-May) to northwestern Senegal and Saharian edges (early August). Interannual variability of the local-scale onset date does not seem to be strongly spatially coherent. The amount of common or covariant signal across the stations is far weaker than the interstation noise at the interannual time scale. In particular, a systematic spatially consistent advance or delay of the onset is hardly observed across the whole western and central Sahel. In consequence, the seasonal predictability of local-scale onset over the western and central Sahel associated, for example, with large-scale sea surface temperatures, is, at best, weak.


Author(s):  
Indarto Indarto

This study aims to analyze trends,  shift and spatial variability of extreme-rainfall in the area of UPT PSDA Pasuruan. The daily rainfall data from 64 stations from 1980 until 2015 were used as main input. The 1-day extreem rainfall data is determined as the maximum annual of 24-hour rainfall events.  The statistical  analysis using Mann-Kendall, Rank-Sum, and Median Crossing Test using significance level α = 0,05. The spatial variability of extrem rainfall data is described using average annual 24-hour rainfall during the periods of record. Each station is represented by one value. The values are then interpolated using IDW interpolation methods to maps the spatial variability of extreem rainfall event.  The results show the value of statistical test for each stations that show the existing  trend, shift, or randomness of data. The result also produce thematic maps show the spatial variability of extreme rainfall and the value of each trend.


Land ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 348
Author(s):  
Marie Perennes ◽  
C. Sylvie Campagne ◽  
Felix Müller ◽  
Philip Roche ◽  
Benjamin Burkhard

Spatially explicit assessments of ecosystem services (ES) potentials are a key component in supporting a sustainable land use management. The ES matrix method is a commonly used approach as it allows for a comparably fast, comprehensible and accessible ES assessment. As it is often based on land use/land cover data (LULC) with no spatial variability, a main critique is that the results fail to assess spatial variability at landscape levels, which limits the reliability of the outputs for spatial planning applications. By using the case study area of Bornhöved in northern Germany, we analyzed three assessment methods that combine expert judgments, LULC data with different resolutions and ecosystem condition indicators, in order to find the required resolution and data for ES assessment and mapping at a local scale. To quantify map discrepancies, we used the structural similarity index (SSIM) and analyzed the differences in local mean, variance and covariance between the maps. We found that using different spatial resolutions led to a relatively small difference in the outcomes, in which regulation and maintenance services are more affected than the other services categories. For most regulation, maintenance and cultural ES, our results indicate that assessments based only on LULC proxies are not suitable for a local quantitative assessment of ES, as they cannot sufficiently cover the spatial heterogeneity of ES capacities that arise from different ecosystem conditions.


1995 ◽  
Vol 52 (1) ◽  
pp. 43-49 ◽  
Author(s):  
K. Reichardt ◽  
L.R. Angelocci ◽  
O.O.S. Bacchi ◽  
J.E. Pilotto

Daily rainfall variability at a local scale (1,000 ha) was studied at Piracicaba, SP, Brazil, for the period of one year (1993-1994), in order to better understand the process of soil water recharge. Coefficients of variation of daily data for ten observation points varied from 2.2 to 169.3% and the variability was independent of rain type, i.e. whether convective, frontal or of other origin. Data were not related to separation distances between observation points and it is concluded that one observation point does not represent areas as far as 1,000 to 2,500 m apart, for daily, monthly or even quarterly averages. Yearly totals for the ten observation points presented a coefficient of variation as low as 3.06%, indicating that all points can replace each other in annual terms.


2013 ◽  
Vol 54 (62) ◽  
pp. 273-281 ◽  
Author(s):  
Kjetil Melvold ◽  
Thomas Skaugen

AbstractThis study presents results from an Airborne Laser Scanning (ALS) mapping survey of snow depth on the mountain plateau Hardangervidda, Norway, in 2008 and 2009 at the approximate time of maximum snow accumulation during the winter. The spatial extent of the survey area is >240 km2. Large variability is found for snow depth at a local scale (2 m2), and similar spatial patterns in accumulation are found between 2008 and 2009. The local snow-depth measurements were aggregated by averaging to produce new datasets at 10, 50, 100, 250 and 500 m2 and 1 km2 resolution. The measured values at 1 km2 were compared with simulated snow depth from the seNorge snow model (www.senorge.no), which is run on a 1 km2 grid resolution. Results show that the spatial variability decreases as the scale increases. At a scale of about 500 m2 to 1 km2 the variability of snow depth is somewhat larger than that modeled by seNorge. This analysis shows that (1) the regional-scale spatial pattern of snow distribution is well captured by the seNorge model and (2) relatively large differences in snow depth between the measured and modeled values are present.


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