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Indarto, I
Universitas Muhammadiyah Surakarta
Earth & Planetary Sciences

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Aplikasi Model SMAR pada Dua DAS Identik Indarto, I
Forum Geografi Vol 26, No 1 (2012): July 2012
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v26i1.5048

Abstract

This paper shows the evaluation process (calibration and validation) of SMAR (The Soil Moisture Accounting Rainfall-Runoff) model at two identical catchment areas (Rawatamtu and Kloposawit) in East Java – Indonesia. Daily discharge, rainfall data and meteorological data were collected from measurement stations located at the catchments areas. Potential evapotranspiration (PET) was calculated from meteorological data extracted from existing stations located inside of the catchments. Calibration was conducted for periods of: 1991 to 1994, while validation was tested for periode of: 1995 to 2000. Model performance was evaluated by means of: (1) Nash-Sutcliffe coefficient, (2) correlation coefficient and (3) graphical comparation of calculated and measured flow. The result show the Nash-Sutcliffe coeffient = 0,73 and correlation coefficient = 0,86 for calibration period at Rawatamtu, while the same coefficients for Kloposawit are 0,54 and 0,74. Validation periode produce Nash-sutcliffe and correlation coefficients = 0,35 and 0,64 for Rawatamtu. While for Kloposawit the values are 0,48 and 0,81.
Aplikasi ESDA untuk Studi Variabilitas Spasial Hujan Bulanan di Jawa Timur Indarto, I
Forum Geografi Vol 25, No 2 (2011): December 2011
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v25i2.5044

Abstract

This article expose the spatial variability of monthly-rainfall (MR) in East Java region. Monthly rainfall data were collected from 943 pluviometres spread around the regions. Spatial statistics analysed by means of ESDA (Exploratory Spatial Data Analysis) techniques available on Geostatistical Analyst extention of ArcGIS (9.3). Statistical tools exploited to analise the data include: (1) Histogram, (2) Voronoi Map, and (3) QQ-Plot. The result show that histogram and QQ-Plot of Monthly Rainfall data are leptocurtosis. Statistical value obtained from the analysis are: minimum = 54 mm/month, average = 155,5 mm/month, maximum = 386 mm/month, and median = 150 mm/month. Other statistical value summarised are: standard deviation = 44,2 ; skewness = 0,95; and curtosis = 5,09. Finally, monthly rainfall-maps are produced by interpolating the data using Inverse Distance Weighed (IDW) interpolation method. The research demonstrate the capability and benefit of those statistical tool to describe detailed spatial variability of rainfall.
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