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Journal : Forum Geografi

Distribution of Accuracy of TRMM Daily Rainfall in Makassar Strait Giarno, G; Hadi, Muhammad Pramono; Suprayogi, Slamet; Murti, Sigit Heru
Forum Geografi Vol 32, No 1 (2018): July 2018
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

This research aims to evaluate rainfall estimates of satellite products in regions that have high variations of rainfall pattern. The surrounding area of Makassar Strait have chosen because of its distinctive rainfall pattern between the eastern and western parts of the Makassar Strait. For this purpose, spatial distribution of Pearson’s coefficient correlation and Root Mean Square Error (RMSE) is used to evaluate accuracy of rainfall in the eastern part of Kalimantan Island and the western part of Sulawesi Island. Moreover, we also used the contingency table to complete the parameter accuracy of the TRMM rainfall estimates. The results show that the performance of TRMM rainfall estimates varies depending on space and time. Overall, the coefficient correlation between TRMM and rain observed from no correlation was -0.06 and 0.78 from strong correlation. The best correlation is on the eastern coast of South West Sulawesi located in line with the Java Sea. While, no variation in the correlation was related to flatland such as Kalimantan Island. On the other hand, in the mountain region, the correlation of TRMM rainfall estimates and observed rainfall tend to decrease. The RMSE distribution in this region depends on the accumulation of daily rainfall. RMSE tends to be high where there are higher fluctuations of fluctuating rainfall in a location. From contingency indicators, we found that the TRMM rainfall estimates were overestimate. Generally, the absence of rainfall during the dry season contributes to improving TRMM rainfall estimates by raising accuracy (ACC) in the contingency table.
Estimation of Solar Radiation using Artificial Neural Network Suprayogi, Slamet
Forum Geografi Vol 18, No 1 (2004)
Publisher : Forum Geografi

Show Abstract | Original Source | Check in Google Scholar | Full PDF (668.428 KB)

Abstract

The solar radiation is the most important fator affeccting evapotranspiration, the mechanism of transporting the vapor from the water surface has also a great effect. The main objectives of this study were to investigate the potential of using Artificial Neural Network (ANN) to predict solar radiation related to temperature. The three-layer backpropagation were developed, trained, and tested to forecast solar radiation for Ciriung sub Cachment. Result revealed that the ANN were able to well learn the events they were trained to recognize. Moreover, they were capable of effecctively generalize their training by predicting solar radiation for sets unseen cases.
Contamination Vulnerability Analysis of Watershed for Water Quality Monitoring Widyastuti, Widyastuti; Suprayogi, Slamet
Forum Geografi Vol 20, No 1 (2006): July 2006
Publisher : Universitas Muhammadiyah Surakarta

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Abstract

This research is an early step to determine the location of rain gauge station for artificial neural network modeling. The implementation of this model is very useful for water quality monitoring. The objectives of this study are: 1) to study the distribution of watershed parameter, that are average annual precipitation, land use and land-surface slope, 2) to conduct vulnerability analysis of watershed contamination, 3) to determine the location of rain gauge station. The study was performed by weighing and rating method of watershed parameters. The vulnerability degree of watershedtocontaminationispresentedasvulnerabilityindex.Thisindexisdeterminedbyoverallsumofallmultiplication between score and weigh number of each parameter. All data manipulation and data analysis were performed by using Geographic Information System (ArcView version by 3.2). The vulnerability of watershed contamination map had been generated using overlay operation of parameters. The results show that vulnerability index are varies between 10 up to 40 intervals. Hence, the indexes were categorized into three levels of watershed vulnerability, namely low (10 – 20), moderate (20 – 30) and high (30 – 40). It is found that the study area covered more by high vulnerability of watershed to contamination. The zoning of watershed vulnerability meant to determine the rain gauge location. There are three rain gauge stations on the area that they are in a high vulnerability level, whereas the other vulnerability level area has one rain gauge station. Each level of vulnerability area is able to represent the source of contaminant that it maybe influence the water quality of Gajahwong river.
Estimation of Solar Radiation using Artificial Neural Network Suprayogi, Slamet
Forum Geografi Vol 18, No 1 (2004)
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Original Source | Check in Google Scholar | Full PDF (668.428 KB)

Abstract

The solar radiation is the most important fator affeccting evapotranspiration, the mechanism of transporting the vapor from the water surface has also a great effect. The main objectives of this study were to investigate the potential of using Artificial Neural Network (ANN) to predict solar radiation related to temperature. The three-layer backpropagation were developed, trained, and tested to forecast solar radiation for Ciriung sub Cachment. Result revealed that the ANN were able to well learn the events they were trained to recognize. Moreover, they were capable of effecctively generalize their training by predicting solar radiation for sets unseen cases.
Contamination Vulnerability Analysis of Watershed for Water Quality Monitoring Widyastuti, Widyastuti; Suprayogi, Slamet
Forum Geografi Vol 20, No 1 (2006): July 2006
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Original Source | Check in Google Scholar

Abstract

This research is an early step to determine the location of rain gauge station for artificial neural network modeling. The implementation of this model is very useful for water quality monitoring. The objectives of this study are: 1) to study the distribution of watershed parameter, that are average annual precipitation, land use and land-surface slope, 2) to conduct vulnerability analysis of watershed contamination, 3) to determine the location of rain gauge station. The study was performed by weighing and rating method of watershed parameters. The vulnerability degree of watershedtocontaminationispresentedasvulnerabilityindex.Thisindexisdeterminedbyoverallsumofallmultiplication between score and weigh number of each parameter. All data manipulation and data analysis were performed by using Geographic Information System (ArcView version by 3.2). The vulnerability of watershed contamination map had been generated using overlay operation of parameters. The results show that vulnerability index are varies between 10 up to 40 intervals. Hence, the indexes were categorized into three levels of watershed vulnerability, namely low (10 – 20), moderate (20 – 30) and high (30 – 40). It is found that the study area covered more by high vulnerability of watershed to contamination. The zoning of watershed vulnerability meant to determine the rain gauge location. There are three rain gauge stations on the area that they are in a high vulnerability level, whereas the other vulnerability level area has one rain gauge station. Each level of vulnerability area is able to represent the source of contaminant that it maybe influence the water quality of Gajahwong river.