scholarly journals Rainfall Distribution in the Upper East Region of Ghana, 1976 – 2016

2020 ◽  
Vol 6 (2) ◽  
pp. 45-59
Author(s):  
Boateng AMPADU ◽  
Isaac SACKEY ◽  
Eugene CUDJOE
Keyword(s):  
Agricultural Sector ◽  
Moving Average ◽  
Monthly Rainfall ◽  
Rainfall Distribution ◽  
East Region ◽  
Dry Spells ◽  
Early Maturing ◽  
Upper East Region ◽  
The Mean ◽  
High Precipitation

The knowledge and understanding of rainfall distribution of a region are very essential and useful in determining the overall impacts of climate change, especially to the agricultural sector. Monthly rainfall data from 1976-2016 for five selected stations were acquired and subjected to various statistical techniques namely coefficient of variation, 5-year moving average and departure from the mean to obtain the variability and trends in the data. The results showed that the selected stations have uni-modal rainfall distribution and that the rain mostly starts in May and ends in September. High precipitation occurs in July, August and September, with August recording the highest amount with a low variability, indicating the reliable occurrence of precipitation within this period of the year. This is of high importance to farmers and the recharging of aquifers. The wettest station was Zuarungu, with a mean total monthly rainfall of 89.55 mm followed by Navrongo, Bolgatanga, Garu and Manga-Bawku with their respective mean total monthly rainfall as 81.08 mm, 80.59 mm, 79.64 mm and 78.86 mm. High annual variability was found in all the stations and long dry spells were observed from November to March. The rainfall season wet period is between July and September at all the stations and it is recommended that farmers should cultivate early-maturing crops and adopt irrigation farming practices as well as practices which utilize water efficiently.

scholarly journals Causes of Marital satisfaction and the criteria of choosing partners for marriage as Perceived by the People of Navrongo in The Upper East Region of Ghana

2020 ◽  
Vol 8 (9) ◽  
pp. 310-320
Author(s):  
Joseph Akpadago
Keyword(s):  
Marital Satisfaction ◽  
Married Couples ◽  
General Evaluation ◽  
East Region ◽  
The People ◽  
Marital Satisfaction Inventory ◽  
Upper East Region ◽  
The Mean ◽  
Quota Sampling ◽  
Sampling Procedures

The study examined the causes of marital satisfaction and the criteria of choosing marriage partners as perceived by the people of Navrongo in the Upper East Region of Ghana. Data were gathered through the use of Marital Satisfaction Inventory (MSI). The sample size was 384 participants comprising 192 males and 192 females who responded to the Marital Satisfaction Inventory. The stratified and quota sampling procedures were used to select the respondents for the study. The study showed that some couples in Navrongo were not satisfied with their marriages as indicated by respondents to the MSI.  Seven scales were used as indicators for marital satisfaction. These included, relationship, affection, love and appreciation, character, temperament, in-law issues, marital roles, and general evaluation. Couples would have been satisfied if the mean scores of the various scales were high enough to fall within the specified satisfied range. The study showed that many married couples chose their partners through courtship than those who were married through betrothal. In Navrongo, more females are betrothed than males and males prefer courtship to betrothal. On the other hand, many men chose their partners through courtship than their female counterpart. Marital satisfaction and the criteria of choosing a partner for marriage by respondents also showed that 86.17% of those who married through betrothal were not satisfied with their marriages whereas 90% of respondents who married through courtship were also not satisfied with their marriages. Only about 13.8% and 10% for respondents of betrothal and courtship were satisfied with their marriages respectively.

Postharvest Losses and Mitigating Technologies: Evidence from Upper East Region of Ghana

2021 ◽  
pp. 100048
Author(s):  
Issah Sugri ◽  
Mutari Abubakari ◽  
Robert Kwasi Owusu ◽  
John Kamburi Bidzakin
Keyword(s):  
Postharvest Losses ◽  
East Region ◽  
Upper East Region

scholarly journals Reservoir Sizing at Draft Level of 75% of Mean Annual Flow Using Drought Magnitude Based Method on Canadian Rivers

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 79
Author(s):  
Tribeni C. Sharma ◽  
Umed S. Panu
Keyword(s):  
Standard Deviation ◽  
Time Scale ◽  
Moving Average ◽  
Flow Data ◽  
Truncation Level ◽  
Drought Intensity ◽  
Error Margin ◽  
Reservoir Volume ◽  
The Mean ◽  
Reservoir Sizing

On a global basis, there is trend that a majority of reservoirs are sized using a draft of 75% of the mean annual flow (0.75 MAF). The reservoir volumes based on the proposed drought magnitude (DM) method and the sequent peak algorithm (SPA) at 0.75 MAF draft were compared at the annual, monthly and weekly scales using the flow sequences of 25 Canadian rivers. In our assessment, the monthly scale is adequate for such analyses. The DM method, although capable of using flow data at any time scale, has been demonstrated using monthly standardized hydrological index (SHI) sequences. The moving average (MA) smoothing of the monthly SHI sequences formed the basis in the DM method for estimating the reservoir volume through the use of the extreme number theorem, and the hypothesis that drought magnitude is equal to the product of the drought intensity and drought length. The truncation level in the SHI sequences was found as SHIo [ = (0.75 ‒ 1) µo/σo], where µo and σo are the overall mean and standard deviation of the monthly flows. The DM-based estimates for the deficit volumes and the SPA-based reservoir volumes were found comparable within an error margin of ±18%.

scholarly journals Studying monthly rainfall over Dibrugarh, Assam: Use of SARIMA approach

MAUSAM ◽  
2021 ◽  
Vol 68 (2) ◽  
pp. 349-356
Author(s):  
J. HAZARIKA ◽  
B. PATHAK ◽  
A. N. PATOWARY
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Moving Average ◽  
Demand Management ◽  
Arima Model ◽  
Monthly Rainfall ◽  
Series Data ◽  
Data Set ◽  
Modeling And Forecasting ◽  
Moving Average Model

Perceptive the rainfall pattern is tough for the solution of several regional environmental issues of water resources management, with implications for agriculture, climate change, and natural calamity such as floods and droughts. Statistical computing, modeling and forecasting data are key instruments for studying these patterns. The study of time series analysis and forecasting has become a major tool in different applications in hydrology and environmental fields. Among the most effective approaches for analyzing time series data is the ARIMA (Autoregressive Integrated Moving Average) model introduced by Box and Jenkins. In this study, an attempt has been made to use Box-Jenkins methodology to build ARIMA model for monthly rainfall data taken from Dibrugarh for the period of 1980- 2014 with a total of 420 points.  We investigated and found that ARIMA (0, 0, 0) (0, 1, 1)12 model is suitable for the given data set. As such this model can be used to forecast the pattern of monthly rainfall for the upcoming years, which can help the decision makers to establish priorities in terms of agricultural, flood, water demand management etc.  

scholarly journals Bicluster CC Algoritm Analysis to Identify Patterns of Food Insecurity in Indonesia

2020 ◽  
Vol 17 (2) ◽  
pp. 325-338
Author(s):  
Raditya Novidianto ◽  
Rini Irfani
Keyword(s):  
Food Insecurity ◽  
Agricultural Sector ◽  
Parameter Tuning ◽  
Mean Square ◽  
Calorie Consumption ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
The Mean ◽  
Best Parameter ◽  
The One

Indonesia is known as an agricultural country. This means that most of the population work in the agricultural sector related to food. However, food insecurity still occurs in Indonesia. With the COVID-19 pandemic, the Food and Agriculture Organization (FAO) stated that there was a threat of food scarcity which had an impact on food insecurity conditions. This would undermine the second goal of the SDGs, which is to end hunger and create sustainable agriculture. The purpose of this study was to determine the spatial pattern of food insecurity in each province in Indonesia using the bicluster method. The data used are data from Susenas and Sakernas by BPS in 2019. Several studies show that the bicluster method with the CC algorithm shows that each province group has a different characteristic pattern. In the bicluster approach, the researcher runs parameter tuning to select the best parameter based on the Mean Square Residual in Volume (MSR / V). The CC algorithm tries to get a bicluster with a low MSR value, therefore the best parameter is the one that produces the smallest MSR / V value, in this study the smallest MSR / V is 0,01737 with δ = 0,01. The application of the CC biclustering algorithm to the food insecurity structure in Indonesia results in 5 bicluster. Bicluster 1 consists of 15 provinces with 8 variables, Bicluster 2 consists of 10 provinces with 5 variables, Bicluster 3 consists of 3 provinces with 7 variables, Bicluster 4 consists of 4 provinces with 4 variables and Bicluster 5 consists of 2 provinces with 5 variables. Biculster 4 represents a cluster of food insecurity areas with the characteristics of the bicluster P0, P1, P2 and calorie consumption of less than 1400 KKAL.

scholarly journals Occupational and environmental mercury exposure among small-scale gold miners in the Talensi–Nabdam District of Ghana's Upper East region

2010 ◽  
Vol 408 (24) ◽  
pp. 6079-6085 ◽  
Author(s):  
Yasaswi Paruchuri ◽  
Amanda Siuniak ◽  
Nicole Johnson ◽  
Elena Levin ◽  
Katherine Mitchell ◽  
...  
Keyword(s):  
Mercury Exposure ◽  
Small Scale ◽  
East Region ◽  
Gold Miners ◽  
Upper East Region

Survey of the Water Quality of the Bahar County Streams (Iran) by NSFWQI

2015 ◽  
Vol 16 (SE) ◽  
pp. 395-403
Author(s):  
Abbas Ghaffari Habib ◽  
Seyed Hadi Khatami
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Fecal Coliform ◽  
Agricultural Sector ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Biological Oxygen Demand ◽  
Dissolved Solids ◽  
The Mean

In Bahar County (Iran), rivers are among the important sources of water for the agricultural sector. Therefore, this research evaluated the parameters of temperature, pH, Total Dissolved Solids (TDS), turbidity, nitrate, total phosphate, dissolved oxygen (DO), Biological Oxygen Demand (BOD5), and fecal coliform at five stations for five months (from February 2015 to June 2015) to determine water quality in the rivers. Based on this evaluation, the NSFWQI index was calculated and, finally, the routes of the rivers were zoned. The best water quality was recorded at Station Number 3 with the NSFWQI Value of 80 in January, and the worst at Station Number 5 (latgah) with the NSFWQI Value of 37 in June. Based on the mean NSFWQI indices, water quality was Medium at Stations Number 1, 2, and 4, good at Station Number 3, and bad at Station number 5.

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