scholarly journals Trend analysis of selected hydro-meteorological variables for the Rietspruit sub-basin, South Africa

2021 ◽  
Author(s):  
Vincent Dzulani Banda ◽  
Rimuka Bloodless Dzwairo ◽  
Sudhir Kumar Singh ◽  
Thokozani Kanyerere
Keyword(s):  
South Africa ◽  
Kendall Test ◽  
Rainfall Data ◽  
Discharge Data ◽  
Stream Discharge ◽  
Discharge Temperature ◽  
Rainfall Trends ◽  
Starting Point ◽  
Slope Estimator ◽  
Climate Station

Abstract Identifying hydro-meteorological trends is critical for assessing climate change and variability both at a basin and regional level. This study examined the long- and short-term trends from stream discharge, temperature, and rainfall data around the Rietspruit sub-basin in South Africa. The data were subjected to homogeneity testing before performing the trend tests. Inhomogeneity was widely detected in discharge data, hence no further analyses were performed on such data. Temperature and rainfall trends and their magnitudes at yearly, seasonal, and monthly time steps were identified after applying the non-parametric Mann-Kendall and Sen's slope estimator. The possible starting point of a trend was determined by performing the sequential Mann-Kendall test. This study revealed a combination of upward and downward trends in both temperature and rainfall data for the time steps under observation. For rainfall on an annual basis, there were no statistically significant monotonic trends detected, although non-significant downward trends were dominant. However, significant decreasing rainfall trends were observed in dry and low rainfall months, which were April, August, September, and November. In contrast, significant upward temperature trends were detected at the Vereeniging climate station at an annual scale and in October, November, spring, and winter. The findings are critical for climate risk management and reduction decisions for both near and long-term timescales.

scholarly journals Rainfall trend and variability over Opak River basin, Yogyakarta, Indonesia

2020 ◽  
Vol 1000 (1000) ◽  
Author(s):  
Wakhidatik Nurfaida ◽  
Hendra Ramdhani ◽  
Takenori Shimozono ◽  
Indri Triawati ◽  
Muhammad Sulaiman
Keyword(s):  
River Basin ◽  
Water Resource ◽  
Rainfall Intensity ◽  
Kendall Test ◽  
Rainfall Data ◽  
Positive Trend ◽  
Sen’S Slope Estimator ◽  
Sen’S Slope ◽  
Slope Estimator

Rainfall intensity seems to be increasing nowadays due to climate change as presented in many studies of both global and regional scale. Consequently, cities worldwide are now more vulnerable to flooding. In Indonesia, increasing frequency of floods was reported for the past decades by The National Agency for Disaster Countermeasure (BNPB). To understand the rainfall changes, long-term trend evaluation over a specific area is then crucial due to the large variability of spatial and temporal rainfall distribution. This study investigates the homogeneity and trend of rainfall data from 20 stations over the Opak River basin, Yogyakarta, Indonesia. A long-term ground observation rainfall data whose period varies from 1979 to 2019 were analyzed. Non-parametric Mann – Kendall test was applied to assess the trend, while the magnitude was calculated using the Sen’s slope estimator. An increasing annual maximum of daily rainfall intensity was observed at four stations on a 0.95 confidence level based on the Mann – Kendall test, while the Sen’s slope estimator shows a positive trend at almost all stations. The trend of heavy rainfall frequency was also found to be significantly increased, with only one station showed a decreasing trend. Furthermore, this paper also described the spatial and temporal rainfall variability. Positive trend was mostly found during the rainy season, while the negative trend occurred during the dry season. This could pose a challenge for water resource management engineering and design, such as water supply systems or reservoir management. Understanding this phenomena will benefit hydrologists in preparing future water resource engineering and management.

scholarly journals Rainfall Trend and Its Relationship with Normalized Difference Vegetation Index in a Restored Semi-Arid Wetland of South Africa

2020 ◽  
Vol 12 (21) ◽  
pp. 8919
Author(s):  
Florence M. Murungweni ◽  
Onisimo Mutanga ◽  
John O. Odiyo
Keyword(s):  
South Africa ◽  
Quantile Regression ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rainfall Data ◽  
Ecosystem Change ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Vegetation Productivity ◽  
Rainfall Trends

Clearance of terrestrial wetland vegetation and rainfall variations affect biodiversity. The rainfall trend–NDVI (Normalized Difference Vegetation Index) relationship was examined to assess the extent to which rainfall affects vegetation productivity within Nylsvley, Ramsar site in Limpopo Province, South Africa. Daily rainfall data measured from eight rainfall stations between 1950 and 2016 were used to generate seasonal and annual rainfall data. Mann-Kendall and quantile regression were applied to assess trends in rainfall data. NDVI was derived from satellite images from between 1984 and 2003 using Zonal statistics and correlated with rainfall of the same period to assess vegetation dynamics. Mann-Kendall and Sen’s slope estimator showed only one station had a significant increasing rainfall trend annually and seasonally at p < 0.05, whereas all the other stations showed insignificant trends in both rainfall seasons. Quantile regression showed 50% and 62.5% of the stations had increasing annual and seasonal rainfall, respectively. Of the stations, 37.5% were statistically significant at p < 0.05, indicating increasing and decreasing rainfall trends. These rainfall trends show that the rainfall of Nylsvley decreased between 1995 and 2003. The R2 between rainfall and NDVI of Nylsvley is 55% indicating the influence of rainfall variability on vegetation productivity. The results underscore the impact of decadal rainfall patterns on wetland ecosystem change.

scholarly journals Trend Analysis of Rainfall Data in Magelang District Using Mann-Kendall Test and Modification Mann-Kendall Variation

AGRIFOR ◽  
2018 ◽  
Vol 17 (2) ◽  
pp. 293 ◽  
Author(s):  
Joko Suryanto ◽  
Joko Krisbiyantoro
Keyword(s):  
Kendall Test ◽  
Significant Trend ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Partial Sums ◽  
Trend Test ◽  
Positive Trend ◽  
Mk Test ◽  
Rainfall Trends ◽  
Negative Significant Trend

The objective of the research was to analyzed rainfall trends from 6 rainfall stations Kajoran, Mendut, Muntilan, Ngablak, Salaman and Tempuran rainfall station in different time scales (monthly, 3-months periodicityand annual). Identification homogenity of the rainfall data period 1986-2016 for Magelang district using Rescaled Adjusted Partial Sums (RAPS) methode. The three non-parametric tests, Mann-Kendall (MK), modified Mann-Kendall (MMK), trend free prewhitening Mann-Kendall (TFPW-MK) and Sen’s slope wereemployed to assess significance of trends and detecting magnitude of trends.The results shows that monthly rainfall have no significant trend using MK, MMK, and TFPW-MK test at 0.05 level significance. Rainfall 3-month based January-February-March (JFM) period Kajoran station have negative significant trend with magnitude 19.4 mm/3-month. Mendut station have positive trend for April-May-June (AMJ) period with magnitude 6.75 mm/3-month. No significant trends at 0.05 level significance using MK trend test were detected in annual rainfall for 6 rainfall stations.

scholarly journals Rainfall Trend Analysis in Tehsils of Palghar District, Maharashtra State, India

2021 ◽  
Vol 9 (11) ◽  
pp. 238-253
Author(s):  
Dr. Sumit M. Dhak
Keyword(s):  
Trend Analysis ◽  
Linear Trend ◽  
Daily Rainfall ◽  
Kendall Test ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Department Of Agriculture ◽  
Increasing Trend ◽  
Slope Estimator

Abstract: A detailed trend analysis of monthly and annual rainfall for Tehsils of Palghar district were carried out using 22 years (1998-2019) daily rainfall data taken from Department of Agriculture, Maharashtra State. In this study, to analyse the trend, the non-parametric test (Mann-Kendall test) and Sen’s slope estimator were used. For developing a functional relationship between variables, a linear trend of rainfall data for the studied area evaluated using the linear regression. The results showed that the trend analysis of monthly rainfall has a varied trend of rainfall in the rainy months in tehsil of Palghar District. The month of July significant increasing trend was observed at Jawhar (42.91 mm/year), Vikramgad (29.90 mm/year), Wada (24.06 mm/year), Talasari (31.36 mm/year), Palghar (25.299 mm/year), Mokhada (29.96 mm/year) and Dahanu (38.14 mm/year), whereas non-significant increasing trend 2.76 mm/year was observed at Vasai tehsil of Palghar District during 1998-2019. The month of June, August, September and October rainfall did not show any significant trend in tehsil of Palghar District and non significant decreasing as well as non significant increasing trend was observed in tehsil of Palghar District during 1998 – 2019. The result concluded that annual rainfall trend was increased in Jawhar, Vikramgad, Wada, Talasari, Palghar, Mokhada and Dahanu; whereas Vasai tehsil rainfall trend was decreased in tehsil of Palghar District during 1998 -2019. Keywords: Rainfall, Trend Analysis, Mann Kendall’s Test, Sen Slopes, Regression

scholarly journals RAINFALL TRENDS ANALYSIS IN TÂRGU MUREȘ CITY, ROMÂNIA

2021 ◽  
Vol 31 (1) ◽  
pp. 45-56
Author(s):  
Ion BUGLEA ◽  
Keyword(s):  
Standard Deviation ◽  
Trend Analysis ◽  
Coefficient Of Variation ◽  
Kendall Test ◽  
Precipitation Data ◽  
Monthly Average ◽  
Maximum Value ◽  
Rainfall Trends ◽  
Trends Analysis ◽  
Slope Estimator

The aim of this study is the detection of trends of precipitation from (1986-2020) over Târgu Mureș city. Precipitation data for 35 years were processed with MS Excel spreadsheets to find monthly, seasonal and annual variability of rainfall. The Mann-Kendall test was used for trend analysis of precipitation and the Sen’s slope estimator was used for the magnitude of variation. The calculations of the two methods were performed using the MAKESENS program. The standard deviation and the coefficient of variation were used to highlight the dispersion. Results show that all three scales (annual, seasonal and monthly show a tendency to increase rainfall. The highest monthly average of precipitation is 227.70 mm (August, 2005), and the lowest monthly average of precipitation is 0.80 mm (November, 2011). The maximum value of annual precipitation is 852.60 mm and was registered in 2005, and the minimum value was 408.70 mm registered in 2000.

Stasis Anxiety

2017 ◽  
Author(s):  
Andrew van der Vlies
Keyword(s):  
South Africa ◽  
Civil War ◽  
Black Writers ◽  
Political Rights ◽  
Ancient Greek ◽  
Individual Subject ◽  
Starting Point ◽  
The Individual ◽  
Past Experiences ◽  
Contemporary Writing

Two recent debut novels, Songeziwe Mahlangu’s Penumbra (2013) and Masande Ntshanga’s The Reactive (2014), reflect the experience of impasse, stasis, and arrested development experienced by many in South Africa. This chapter uses these novels as the starting point for a discussion of writing by young black writers in general, and as representative examples of the treatment of ‘waithood’ in contemporary writing. It considers (spatial and temporal) theorisations of anxiety, discerns recursive investments in past experiences of hope (invoking Jennifer Wenzel’s work to consider the afterlives of anti-colonial prophecy), assesses the usefulness of Giorgio Agamben’s elaboration of the ancient Greek understanding of stasis as civil war, and asks how these works’ elaboration of stasis might be understood in relation to Wendy Brown’s discussion of the eclipsing of the individual subject of political rights by the neoliberal subject whose very life is framed by its potential to be understood as capital.

scholarly journals Testing Possible Scenario-Based Responses of Vegetation Under Expected Climatic Changes in Khuzestan Province

2021 ◽  
Vol 14 ◽  
pp. 117862212110133
Author(s):  
Hadi Eskandari Damaneh ◽  
Meysam Jafari ◽  
Hamed Eskandari Damaneh ◽  
Marjan Behnia ◽  
Asadollah Khoorani ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Kendall Test ◽  
Baseline Period ◽  
System Model ◽  
Future Period ◽  
Khuzestan Province ◽  
Ecosystem Planning ◽  
Slope Estimator ◽  
Precipitation And Temperature

Projections of future scenarios are scarce in developing countries where human activities are increasing and impacting land uses. We present a research based on the assessment of the baseline trends of normalized difference vegetation index (NDVI), precipitation, and temperature data for the Khuzestan Province, Iran, from 1984 to 2015 compiled from ground-based and remotely sensed sources. To achieve this goal, the Sen’s slope estimator, the Mann-Kendall test, and Pearson’s correlation test were used. After that, future trends in precipitation and temperature were estimated using the Canadian Earth System Model (CanESM2) model and were then used to estimate the NDVI trend for two future periods: from 2016 to 2046 and from 2046 to 2075. Our results showed that during the baseline period, precipitation decreased at all stations: 33.3% displayed a significant trend and the others were insignificant ones. Over the same period, the temperature increased at 66.7% of stations while NDVI decreased at all stations. The NDVI–precipitation relationship was positive while NDVI–temperature showed an inverse trend. During the first of the possible future periods and under the RCP2.6, RCP4.5, and RCP8.5 scenarios, NDVI and precipitation decreased, and temperatures significantly increased. In addition, the same trends were observed during the second future period; most of these were statistically significant. We conclude that much assessments are valuable and integral components of effective ecosystem planning and decisions.

scholarly journals STUDI PENGEMBANGAN MODEL HIDROGRAF SATUAN SISTETIS SNYDER UNTUK SUNGAI –SUNGAI DI SULAWESI SELATAN

GANEC SWARA ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 126
Author(s):  
MUHAMAD YAMIN
Keyword(s):  
Model Verification ◽  
Rainfall Data ◽  
Peak Time ◽  
Reliability Testing ◽  
Unit Hydrograph ◽  
Observation Unit ◽  
Discharge Data ◽  
Watershed Characteristics ◽  
Testing Model ◽  
South Sulawesi

This study aims to analyze the parameters that influence the Snyder synthetic unit hydrograph method. The study was conducted on 11 watersheds in South Sulawesi Province, 8 watersheds for modeling and 3 other watersheds for reliability testing (model verification).     With rainfall data, the discharge data and watershed characteristics obtained from each watershed were analyzed for parameters that affected the hydrograph breakdown of the Snyder HSS method. Then compared to the hydrograph of the observation unit which was analyzed by the Collins method.     After calibration was done with the NASH criteria obtained Peak Time (Tp) = 97.996%; Peak Discharge (Qp) = 98.331% and Basic Time (Tb) = 99.700%. The curved delineation of the hydrograph uses the auxiliary point W, which gives the result of volume deviation, namely: 7.980%, 9.227%; 6.855%; 4.966%; 10.972% and 9.843% are relatively small when compared to the model using Alexejeyev Arch with deviations: 22.362%; 29.991%; 26,319%; 19.602%; 29,786% and 17,633%.

scholarly journals Rainfall trend analysis using Mann-Kendall and Sen’s slope estimator test in West Kalimantan

2021 ◽  
Vol 893 (1) ◽  
pp. 012006
Author(s):  
F Aditya ◽  
E Gusmayanti ◽  
J Sudrajat
Keyword(s):  
Climate Change ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Sen’S Slope Estimator ◽  
West Kalimantan ◽  
Rainfall Analysis ◽  
Sen’S Slope ◽  
Rainfall Trends ◽  
Slope Estimator ◽  
The Impact

Abstract Climate change has been a prominent issue in the last decade. Climate change on a global scale does not necessarily have the same effect in different regions. Rainfall is a crucial weather element related to climate change. Rainfall trends analysis is an appropriate step in assessing the impact of climate change on water availability and food security. This study examines rainfall variations and changes at West Kalimantan, focusing on Mempawah and Kubu Raya from 2000-2019. The Mann-Kendall (MK) and Sen's Slope estimator test, which can determine rainfall variability and long-term monotonic trends, were utilized to analyze 12 rainfall stations. The findings revealed that the annual rainfall pattern prevailed in all locations. Mempawah region tends to experience a downward trend, while Kubu Raya had an upward trend. However, a significant trend (at 95% confidence level) was identified in Sungai Kunyit with a slope value of -33.20 mm/year. This trend indicates that Sungai Kunyit will become drier in the future. The results of monthly rainfall analysis showed that significant upward and downward trends were detected in eight locations. Rainfall trends indicate that climate change has occurred in this region.

Lithium-ion battery state of health estimation based on improved deep extreme learning machine

2021 ◽  
pp. 1-12
Author(s):  
Yu Zhang ◽  
Wanwan Zeng ◽  
Chun Chang ◽  
Qiyue Wang ◽  
Si Xu
Keyword(s):  
Extreme Learning Machine ◽  
Search Algorithm ◽  
Lithium Ion ◽  
Accurate Estimation ◽  
Time Interval ◽  
State Of Health ◽  
Discharge Data ◽  
Ergodic Method ◽  
Discharge Temperature ◽  
Learning Machine

Abstract Accurate estimation of the state of health (SOH) is an important guarantee for safe and reliable battery operation. In this paper, an online method based on indirect health features (IHF) and sparrow search algorithm fused with deep extreme learning machine (SSA-DELM) of lithium-ion batteries is proposed to estimate SOH. Firstly, the temperature and voltage curves in the battery discharge data are acquired, and the optimal intervals are obtained by ergodic method. Discharge temperature difference at equal time intervals (DTD-ETI) and discharge time interval with equal voltage difference (DTI-EVD) are extracted as IHF. Then, the input weights and hidden layer thresholds of the DELM algorithm are optimized using SSA, and the SSA-DELM model is applied to the estimation of battery's SOH. Finally, the established model is experimentally validated using the battery data, and the results show that the method has high prediction accuracy, strong algorithmic stability and good adaptability.

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