scholarly journals DYNAMICS PATTERNS OF INFLOW IN THE RESERVOIR THAT OPERATED FOR TWO DECADES

2021 ◽  
Vol 56 (4) ◽  
pp. 92-103
Author(s):  
Heriantono Waluyadi ◽  
Pitojo Tri Juwono ◽  
Widandi Soetopo ◽  
Rispiningtati ◽  
Lily Montarcih Limantara ◽  
...  
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Rainfall Data ◽  
Operation Pattern ◽  
The Pacific ◽  
Ocean Region ◽  
Reservoir Watershed ◽  
June July

Climate change in the past 20 years brings significant alteration in the earth surface. It affects extremely anomaly temperature, such as the ENSO, IOD, and SOI phenomena. The Pacific Ocean Region, the Indian Ocean Region, and the Darwin – Tahiti Region undergo an increase and a decrease in the sea surface temperatures (SST); thus, it can lead to seasonal change in Indonesia. Due to ENSO, IOD, and SOI, climate change also highly affects the operation pattern of reservoirs, food production, and other commodities. This research used SST data (Nino 1.2, Nino 3, Nino 3.4, Nino 4, IOD West, IOD East, and SOI) from National Oceanic and Atmospheric Administration (NOAA) and rainfall data from 1998 to 2018 of nine stations at Wonogiri Reservoir watershed. Trend analysis of the SST index indicated an increase in trend SST index. Trend analysis of monthly rainfall average at Wonogiri Watershed area indicated a decrease in January, March, April, May, June, July, August, and October, while it increased in February, September, November, and December. Multiple linear regression analysis with the stepwise regression method indicated that during the rainy season, the rainfall at Wonogiri Watershed and Inflow at Wonogiri reservoir were influenced by the SST index (Nino 1.2, Nino 3, Nino 3.4, Nino 4). Meanwhile, during the dry season, the rainfall at Wonogiri Watershed and the Inflow at Wonogiri reservoir were influenced by the SST index (IOD West, IOD East, and SOI). With monthly correlations between SST and rainfall data that have a dynamic characteristic, it can be used to calculate the inflow probability distribution in optimizing reservoir operation patterns.

scholarly journals Optimization Model of Reservoir Operating Pattern Based on the Adaptive Inflow for Climate Change

2021 ◽  
Vol 56 (2) ◽  
pp. 491-511
Author(s):  
Heriantono Waluyadi ◽  
Pitojo Tri Juwono ◽  
Widandi Soetopo ◽  
Rispiningtati ◽  
Lily Montarcih Limantara ◽  
...  
Keyword(s):  
Climate Change ◽  
Optimization Model ◽  
Stepwise Regression ◽  
Linear Regression Analysis ◽  
Urban Climate ◽  
Multiple Linear Regression Analysis ◽  
Raw Water ◽  
The Past ◽  
Operation Pattern ◽  
Reservoir Watershed

Urban Climate change in the past 40 years carries significant effects on the earth's surface. It shows an effect of extremely anomaly temperature because of such phenomenons as ENSO, IOD, and SOI. Thus, it can lead to seasonal change in Indonesia that affects the reservoir inflow and impacts the reservoir's operation pattern for managing power plant, irrigation, and raw water supply. This research used the relation between SST data (Nino 1.2, Nino 3, Nino 3.4, Nino 4, IOD West, IOD East, and SOI index) from NOAA and rainfall data from 1998 to 2018 in 9 stations at Wonogiri Reservoir Watershed from BBWS Bengawan Solo. With multiple linear regression analysis with a stepwise regression method, it indicated that the rainfall at Wonogiri Watershed and Inflow at Wonogiri reservoir was influenced by the SST index (Nino 1.2, Nino 3, Nino 3.4, Nino 4). Meanwhile, during the dry season, the rainfall at Wonogiri Watershed and the Inflow at Wonogiri reservoir were influenced by the SST index (IOD West, IOD East, and SOI). The rainfall and SST are related to being modeled for the probability of inflow distribution in each period (every 15 days). This inflow model influenced by climate change is to be used for the optimization model of reservoir operating pattern with Stochastic Model. The result that scenario 6 have the highest benefit, highest performance in the reliability and resiliency value in the simulation for a period between years 1979-2018.

scholarly journals Investigating ENSO and its teleconnections under climate change in an ensemble view – a new perspective

2020 ◽  
Vol 11 (1) ◽  
pp. 267-280 ◽  
Author(s):  
Tímea Haszpra ◽  
Mátyás Herein ◽  
Tamás Bódai
Keyword(s):  
Climate Change ◽  
Southern Oscillation ◽  
Time Instant ◽  
African Region ◽  
The Pacific ◽  
Community Earth System Model ◽  
Leading Mode ◽  
New Perspective ◽  
June July ◽  
Enso Phases

Abstract. The changes in the El Niño–Southern Oscillation (ENSO) phenomenon and its precipitation-related teleconnections over the globe under climate change are investigated in the Community Earth System Model Large Ensemble from 1950 to 2100. For the investigation, a recently developed ensemble-based method, the snapshot empirical orthogonal function (SEOF) analysis, is used. The instantaneous ENSO pattern is defined as the leading mode of the SEOF analysis carried out at a given time instant over the ensemble. The corresponding principal components (PC1s) characterize the ENSO phases. By considering sea surface temperature (SST) regression maps, we find that the largest changes in the typical amplitude of SST fluctuations occur in the June–July–August–September (JJAS) season, in the Niño3–Niño3.4 (5∘ N–5∘ S, 170–90∘ W; NOAA Climate Prediction Center) region, and the western part of the Pacific Ocean; however, the increase is also considerable along the Equator in December–January–February (DJF). The Niño3 amplitude also shows an increase of about 20 % and 10 % in JJAS and DJF, respectively. The strength of the precipitation-related teleconnections of the ENSO is found to be nonstationary, as well. For example, the anticorrelation with precipitation in Australia in JJAS and the positive correlation in central and northern Africa in DJF are predicted to be more pronounced by the end of the 21th century. Half-year-lagged correlations, aiming to predict precipitation conditions from ENSO phases, are also studied. The Australian and Indonesian precipitation and that of the eastern part of Africa in both JJAS and DJF seem to be well predictable based on the ENSO phase, while the southern Indian precipitation relates to the half-year previous ENSO phase only in DJF. The strength of these connections increases, especially from the African region to the Arabian Peninsula.

scholarly journals Trend Analysis of Flood Peaks in Lower Reaches of Satluj River, Himachal Pradesh, India

2015 ◽  
Vol 46 ◽  
pp. 60-75
Author(s):  
Sandeep Kumar ◽  
Santosh
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Hydrological Cycle ◽  
Linear Regression Analysis ◽  
Data Series ◽  
Large Variability ◽  
The Past ◽  
Mitigation And Adaptation ◽  
Flood Peaks ◽  
Satluj River

Climate change arising from anthropogenic driven emissions of greenhouse gases has emerged as one of the most important environmental issues in the last two decades. One of the most significant potential consequences of climate change may be alteration in regional hydrological cycle and river flow regimes. Increased temperature is expected to increase the peak flows in snow-fed rivers of Himalayas. The changing pattern of regional temperature on flood peaks deserves urgent and systematic attention over a basin which provides an insight view of historical trends. Lower reaches of Satluj River is selected for the present study. Testing the significance of observed trends in flood peaks has received a great attention recently, especially in connection with climate change. The data series available was 48 years (1967-2010). The records were subjected to trend analysis by using both non-parametric (Mann-Kendall test) and parametric (linear regression analysis) procedures. For better understanding of the observed trends, flood peaks were computed into standardised flood peak indices (SFPI). These standardised data series were plotted against time and the linear trends observed were represented graphically. The analysis of flood peaks at different observation stations in lower reaches of Satluj River showed a large variability in the trends and magnitudes. The trend analysis results of flood peaks and gauge heights indicate that the flood peaks at all sites i.e. Rampur, Suni and Kasol show increasing but statistically insignificant trends. The trends in gauge height at all sites are also showing increasing trend but Kasol is statistically significant at 95% confidence level. The fast melting of glaciers, incessant monsoon rainfall and the synchronisation of the discharge peaks are the main causes of river floods. The past flood peaks will help us to observe the frequency of occurrence of floods in certain region and to determine whether the flood peaks in the past have been same with that of the present or whether there is any deviation in the trend in relation to climate change. Such studies will help in designing mitigation and adaptation strategies towards extreme hydrological events.

scholarly journals An Analysis of Tropical Cold-Point Tropopause Warming in 1999

2017 ◽  
Vol 2017 ◽  
pp. 1-11
Author(s):  
Yuanyuan Han ◽  
Fei Xie ◽  
Shiyan Zhang ◽  
Ruhua Zhang ◽  
Feiyang Wang ◽  
...  
Keyword(s):  
Deep Convection ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Quasi Biennial Oscillation ◽  
Tropical Tropopause ◽  
Rate Of Increase ◽  
Two Factors ◽  
June July ◽  
Cold Point ◽  
Tropopause Temperature

Using reanalysis datasets, the warming of the tropical tropopause in 1999 and its evolution are investigated. It is found that there is a strong rate of increase in tropical cold-point tropopause temperature (CPTT) in June 1999, with negative CPTT anomalies before June (March-April-May) and large positive anomalies after June (July-August-September). Multiple linear regression analysis shows that deep convection, the quasi-biennial oscillation (QBO), and tropical upwelling associated with the Brewer-Dobson circulation (BDC) largely explain the variations of CPTT in 1999. Before June, enhanced deep convection resulting from increased sea surface temperature (SST) over the western Pacific and enhanced tropical upwelling of the BDC lead to a higher and colder tropopause. Those two factors explain 22% and 17% of the variance in CPTT, respectively. In June, the transformation of the east phase of QBO to the west phase contributes up to more than 50% of the variance in CPTT changes. After June, reduced tropical upwelling induced by weakened wave activity results in the warmer tropical tropopause temperatures to a large extent.

scholarly journals Effect of Time-Resolution of Rainfall Data on Trend Estimation for Annual Maximum Depths with a Duration of 24 Hours

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3264
Author(s):  
Renato Morbidelli ◽  
Carla Saltalippi ◽  
Jacopo Dari ◽  
Alessia Flammini
Keyword(s):  
Climate Change ◽  
Least Squares ◽  
Trend Analysis ◽  
Time Resolution ◽  
Linear Trend ◽  
Rainfall Data ◽  
Annual Maximum ◽  
Maximum Rainfall ◽  
Climatic Trend ◽  
Sen’S Method

The main challenge of this paper is to demonstrate that one of the most frequently conducted analyses in the climate change field could be affected by significant errors, due to the use of rainfall data characterized by coarse time-resolution. In fact, in the scientific literature, there are many studies to verify the possible impacts of climate change on extreme rainfall, and particularly on annual maximum rainfall depths, Hd, characterized by duration d equal to 24 h, due to the significant length of the corresponding series. Typically, these studies do not specify the temporal aggregation, ta, of the rainfall data on which maxima rely, although it is well known that the use of rainfall data with coarse ta can lead to significant underestimates of Hd. The effect of ta on the estimation of trends in annual maximum depths with d = 24 h, Hd=24 h, over the last 100 years is examined. We have used a published series of Hd=24 h derived by long-term historical rainfall observations with various temporal aggregations, due to the progress of recording systems through time, at 39 representative meteorological stations located in an inland region of Central Italy. Then, by using a recently developed mathematical relation between average underestimation error and the ratio ta/d, each Hd=24 h value has been corrected. Successively, commonly used climatic trend tests based on different approaches, including least-squares linear trend analysis, Mann–Kendall, and Sen’s method, have been applied to the “uncorrected” and “corrected” series. The results show that the underestimation of Hd=24 h values with coarse ta plays a significant role in the analysis of the effects of climatic change on extreme rainfalls. Specifically, the correction of the Hd=24 h values can change the sign of the trend from positive to negative. Furthermore, it has been observed that the innovative Sen’s method (based on a graphical approach) is less sensitive to corrections of the Hd values than the least-squares linear trend and the Mann–Kendall method. In any case, the analysis of Hd series containing potentially underestimated values, especially when d = 24 h, can lead to misleading results. Therefore, before conducting any trend analysis, Hd values determined from rainfall data characterized by coarse temporal resolution should always be corrected.

scholarly journals Farmers' adaptation choices to climate change: a case study of wheat growers in Western Iran

2018 ◽  
Vol 10 (1) ◽  
pp. 102-116 ◽  
Author(s):  
Yousof Azadi ◽  
Masoud Yazdanpanah ◽  
Masoumeh Forouzani ◽  
Hossein Mahmoudi
Keyword(s):  
Climate Change ◽  
Financial Management ◽  
Negative Impact ◽  
Linear Regression Analysis ◽  
Principal Component ◽  
Multiple Linear Regression Analysis ◽  
Adaptation Measures ◽  
Western Iran ◽  
Multi Stage ◽  
Three Components

AbstractClimate change is expected to disproportionately affect farmers by further exacerbating the risks that they face. These risks have a huge negative impact on their livelihood. However, mounting evidence has revealed that farmers can effectively manage this negative impact by adapting their farming practices to climate change. The objectives of this study were to evaluate the farmers' ongoing adaptation measures, and to identify factors that influence their choice of adaptation methods in wheat production in the Kermanshah district in Western Iran. A sample of 350 farmers living in this region was selected through a multi-stage stratified and random sampling method. Principal component analysis revealed that three components play a role in the farmers' decisions on adaptation methods, namely, farm production practices, farm financial management, and government programs and insurance. The relative influence of the factors listed under each of the three components was assessed using a multiple linear regression analysis. Our analysis showed that these factors accounted for 50%, 25%, and 40% of the adaptation responses analyzed, respectively. In sum, our findings yield recommendations for agriculture extension and risk communication strategies that could promote adaptation behavior among Iranian farmers.

Climate Change Vulnerability of Marginal and Small Farmers in Nuapada District, Odisha

2021 ◽  
Vol 14 (12) ◽  
pp. 23-32
Author(s):  
Damodar Jena ◽  
Nibal Dibiat ◽  
Nishith Ranjan Parida ◽  
Pani Saswat Kumar
Keyword(s):  
Climate Change ◽  
Linear Regression Analysis ◽  
Secondary Data ◽  
Multiple Linear Regression Analysis ◽  
Vulnerability Index ◽  
Small Farmers ◽  
Level Of Education ◽  
Access To Credit ◽  
Income Sources ◽  
Vulnerability To Climate Change

This study attempts to measure the level of livelihood vulnerability of farmers to climate change in Nuapada. Both descriptive and inferential statistics were used based on primary and secondary data. The study found that marginal and small farmers in the study area have different differential livelihood vulnerability to climate change. The study has used composite approach in which seven dimensions including 34 indicators were studied. Composite of factors such as low level of education, lack of access to credit, lack of access to critical irrigation were associated with the relatively higher Livelihood Vulnerability Index (LVI) values. The multiple linear regression analysis revealed that seven socio-economic variables account for 44% of variation in livelihood vulnerability index; three variables among them viz. number of household income sources, landholding size and highest level of education in household were found to have significant impact on LVI. The findings of the study conclude that there is differential vulnerability to climate change in the same context which was mostly determined by various socioeconomic factors. Thus climate change related studies and policies (which mostly limit district as the measuring unit) must expand their scope to understand and act on differential vulnerabilities in the same district.

scholarly journals Analyzing Trends in Rainfall and Their Impacts in Water Management in a Cerrado Region in Brazil

2021 ◽  
Author(s):  
welber Ferreira Alves ◽  
Henrique Roig ◽  
Latif Kalin ◽  
Luciana Figueiredo Prado ◽  
Frédéric Satgé ◽  
...  
Keyword(s):  
Water Management ◽  
Population Growth ◽  
Trend Analysis ◽  
Climatic Changes ◽  
Rainfall Data ◽  
Total Precipitation ◽  
Water Crisis ◽  
Rain Gauges ◽  
June July August ◽  
June July

Abstract This study presents a trend analysis related to a Cerrado Region in Brazil surrounded by multiple climatic influences and which lived a recent water crisis (2016-2018). This crisis could be associated with climatic changes or population growth. To verify the first possibility, an analysis was performed on a series of rainfall data (21 rain gauges spread throughout the region) divided by season periods (December/January/February – DJF, March/April/May – MAM, June/July/August – JJA, September/October/November – SON, and Water Year – WY) to provide information about the presence of trends or lack thereof. Four statistics tests were used in this procedure: Cox-Stuart, Mann-Kendall, Spearman, and Wald-Wolfowitz. The overall results indicate that the percentage of gauges/periods displaying trends by the Mann-Kendall was 10.48%, Cox-Stuart 9.52%, Spearman 12.38, and Wald-Wolfowitz 8.57%. Of these gauges/periods, 70% were classified as highly skewed, 10% as moderately skewed, and 20% as symmetric. Most of the trends are concentrated in the JJA period where it registered about 22 mm of rainfall average while the annual mean total precipitation is ~1500 mm.

Pengaruh Motivasi Kerja Dan Lingkungan Kerja Terhadap Kinerja Karyawan Bappeda Kabupaten Wonosobo Tahun 2013

2017 ◽  
Vol 1 (2) ◽  
pp. 135-147
Author(s):  
Ary Sutrischastini ◽  
Ratna Setyani
Keyword(s):  
Work Environment ◽  
Work Motivation ◽  
Employee Performance ◽  
Linear Regression Analysis ◽  
Test Validity ◽  
Multiple Linear Regression Analysis ◽  
Reliability Testing ◽  
Evaluation Influence ◽  
Environment Variables ◽  
Research Goal

This research goal is to identification and evaluation influence of work motivation and work environment to employee’s performance in BAPPEDA Kabupaten Wonosobo. The object of this research is 37 employees of Badan Perencanaan Pembangunan Kabupaten Wonosobo. And the location of this research is at Badan Perencanaan Pembangunan Kabupaten Wonosobo. The analysis used is test validity, reliability testing, and test the hypothesis, with the help of the computer program SPSS version 17, using multiple linear regression analysis. Based on calculations of data and analysis used, the regression equation is obtained: Y = 11.733 + 0.320 X1 +0.334 X2 + ε, by using the equation regression analytical method can conclude that (X1) take effect positively against employees performance. With t value in amount of 2,219 (bigger than t in table in amount of 1,690) and significance value in amount of 0,33. By applying significance limited value in amount of 0,05, it means, hypothesis that claim if work motivation take effect against employees performance can be accepted. There is a positive and significant correlation between work environment variables (X2) against employees. With t value in amount of 2,219 (bigger than t in table in amount of 1,690) and significance value in amount of 0,33 (smaller than 0,5). Simultaneously, work motivation take effect positively and significantly against employees performance with the F value in amount of 11,562 (bigger than 0.05), then obtained significance value 0.000. It can be concluded that the work motivation and work environment has a positive and significant influence on employee performance in BAPPEDA Kabupaten Wonosobo.

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