جستجوی مقالات مرتبط با کلیدواژه « daily rainfall » در نشریات گروه « جغرافیا »

Daily Rainfall estimation usually performed with classical interpolation methods (Dingman,2002).To have a responsible accuracy in using new geostatistical methods, and neural networks methods we need a dense distributed stations (Goovaerts,2000º Rahimi-BondarAbadi and Saghafian, 2007). However, Modified Inverse Distance Method(MIDW) can be used in mountainous areas with low density (LO,1992(.Elevation to the distance ratio (with equal power) appears in MIDW. MIDW-F is the advanced version of MIDW that considers the elevation and distance as the inverse with unequal power (m and n). It is analyzed with fuzzy mathematics and is optimized with Genetic Algorithm (GA) (Chang et al, 2005). The purpose and innovation of this paper is to provide MIDW-F with a new alignment of MIDW-F which named GMIDW-F.
2 - 2.1 Study area and data :The study area is Mashhad Drainage basin (dry and semi-dry climate) with longitude 58° ,20´ to 60°,8' Easting and Latitude 36°-0' to 37°-5' Northing(North East of Iran) with total area of ​​9909.4 km2. Number of rain gauges within and adjacent the area are 49 with over a period of 16 years combined(1993-2009). 215daily rainfall (at least 50% of the stations have rainy day at the same time) was used for modeling in this study.
2-2 Modified inverse distance method Based on Fuzzy Mathematics
MIDW method considers the ratio of elevation(h) to distance(d) with equal power (LO, 1992). Advanced version of this is MIDW-F (Eq.8) that powers are unequal (Chang et al, 2005. The weights of elevation and distance(Eqs.1 and 2) are fuzzy. and are the Fuzzy membership functions d,and. and are the membership degrees. They can be integrated with the fuzzy operators, minimum, maximum, multiplied and sum of squares (Eqs.3 to 7) (Vahidian-Kamyad and Tarqyan, 2002). The phrase is integrated weight. We can consider the role of elevation directly in these area . We applied two different alignments to MIDW-F which named GMIDW-F method (Eq.8). If weights(h and d) appear in reverse (as), it was named GMIDW-F(1). The caseis named GMIDW-F(2).(1)(2) (3) (4) (5) (6) (7) (8) GMIDW-F equation
2.3 Genetic Algorithms:The GA is useful to estimate and optimize the parameters m and n of equation 8. The error function is regional sum of absolute errors(RSAE).
2.4 Data screening and normalization :Reforming data due to wrong registration, incorrect transmission, system failure, etc. is called screening. The normalization is for unification the scales of elevation and distance (Eqs 9 and 11). If the role of elevation is assumed to be negative, normalized by Eq.(10) and in direct mode can be done with Eq.(11) (Chang et al, 2006). (9) (10) (11)
3 - The MIDW-F considers elevation and distance inversely with unequal powers (m and n) in MIDW. We added a new alignment elevation to the distance ratio (GMIDW-F). Optimization of m and n was conducted for 215 daily rainfalls. Rainfalls were classified into 5-10, 10- 20, 30-40, 40-50 etc (in mm). Screening and normalization were also performed. Integration was examined with five fuzzy functions(Eqs. 4 to 8). GA is applied to optimize the parameters.
RSAE for each equation and for each category was calculated(Eq. 10, Tables 1 and 2). This classification did not show any specific results. Contribution of minimum and multiply operators is more frequenty (Table 2). Some statistical features of RSAE increase with rainfall classification(Table 3).
Without classification the optimum function was obtained in 66% of cases with and 34% of cases with. The Best operator was minimized (57%) and then multiplied (31%) (Tables 1, 2 and 4). The multiplication operator showed that in 76% of cases the effect of elevation and distance are inversed when and in 24% of the cases the effect of distance is direct while elevation effect is inverse when (Tables 2 and 4). The zoning of a daily precipitation (11/04/2009) by GMIDW-F and IDW methods were compared in a graph with RSAE values of 213 and 252 (in mm) respectively. By using IDW method, precipitation was estimated zero when it was at least 7(in mm), so it is overestimate, while it was estimated 1.5 mm by at the same values. It could be concluded that zoning by GMIDW-F provides better results than IDW method.
4 - The results of analysis showed that the minimum and multiplication operators are the best (Table1). Type of alignment is effective. Function improved in 66% of cases by applying GMIDW-F(1) and 44% of cases by applying GMIDW-F(2). The best function and alignment is determined by h and d. The classification does not affect for choosing the Fuzzy operator (Table1). It can be concluded that there is no restriction for parameters, classification is ineffective, the minimum and multiplication operators have priority and the alignment of h and d should be considered.

Rainfall is one of the most important natural sources of water used by mankind foragricultural and industrial applications. Because of the difficulty of rainfall monitoring,which has high spatial and temporal variability, our knowledge of both the its synopticand climatological distribution over most of the country is not well known.Climatological investigations in Iran lack adequate meteorological observations tounderstand and interpret diverse climatic features. In the country as a whole, theground observation network is not dense enough to provide the detailed informationrequired, especially in rugged regions. Combined with this is the problem of pooraccessibility to the mountainous regions, which has resulted in the areal distribution ofrainfall being poorly known. In addition, the data collected by the existingmeteorological stations, with a few exceptions, are mostly discontinuous, nonhomogenousand short period observations. Such limited data sets, make it difficult toboth accurately delimit different climatic regimes across the country and identifysignificant departures from normal conditions, whereas many climatologicalapplications and investigations should ideally be based on the data collected at givenpoints over long periods and should have a good spatial and temporal coverage.Perhaps the most urgent problem facing rainfall measurement at the present time isdata collection - one of the most costly areas in meteorology and hydrology.In this paper, the central aim is to investigate the potential of GeographicalInformation System for monitoring Fars province’s rainfall with special reference toKriging and IDW (Inverse Distance Weighting), to describe pre-processingapproaches, including relative calibration, and to examine various techniques for bothrainfall monitoring.Analyses of the GIS techniques provided very useful information on both thespatial and temporal distributions of rainfall over regional space, although datacollected by Kriging technique showed more accurate than IDW technique. In order toexplore the appropriate method, the accuracy of the obtained results from differentmethods using RMS was examined. The results showed that among different usedkriging methods, the circular and exponential ordinary had lowest error.