Soil salinity assessment using geostatistical models in some parts of Kano River Irrigation Project Phase I (KRPI)

Yusuf, Binta Lawan; Mustapha, Adamu; Yusuf, Murtala; Ahmed, Md. Kawser

doi:10.1007/s40808-020-00841-7

Cited by 12 publications

(12 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Embora existam registros da aplicação satisfatória do modelo Pentaesférico para análise de precipitação (Júnior et al, 2020; Pirani e Modarres, 2020), este não é indicado para tal finalidade (Wong e Kwon, 2021). Tal modelo apresenta mais bem resultados para mapeamento de propriedades do solo (Neto et al, 2020a;Selmy et al, 2020;Yusuf et al, 2020;Behera et al, 2021;Selmy et al, 2022;Shashikumar et al, 2022), e qualidade de águas subterrâneas (Khorrami, 2019;Said e Yurtal, 2019;Salem et al, 2022).…”

Section: Modelounclassified

“…Esta baixa performance do modelo se dá por este ser mais aplicável em outras variáveis ambientais, destacando, assim como no modelo Pentaesférico, seu maior ajuste à análise de solos (Neto et al, 2020a;Selmy et al, 2020;Yusuf et al, 2020;Selmy et al, 2022;Shashikumar et al, 2022) e de qualidade de águas subterrâneas (Khorrami, 2019;Said e Yurtal, 2019;Salem et al, 2022).…”

Section: Modelounclassified

See 1 more Smart Citation

Comparação de modelos geoestatísticos para estimativa de precipitação em Minas Gerais, Brasil, entre os anos hidrológicos de 2000 e 2021

Guimarães

Alves²

2023

Rev. Bras. Geog. Fis.

View full text Add to dashboard Cite

A gestão integrada dos recursos hídricos no Brasil e no mundo tem passado por desafios provenientes de processos naturais e antrópicos. Assim, o conhecimento preciso das condições quantitativas e qualitativas dos recursos hídricos é de fundamental importância, sendo o monitoramento pluviométrico por estações pluviométricas distribuídas no estado um componente central deste, no que diz respeito ao entendimento da dinâmica espacial e temporal da precipitação. Em Minas Gerais, tais estações estão concentradas em determinadas áreas, dificultando o processo de tomada de decisão pelos agentes gestores. As técnicas de geoestatística têm se mostrado acuradas para estimativa de precipitação em espaços sem estações pluviométricas, sendo que tal trabalho visou aplicá-las no estado, nos anos hidrológicos de outubro de 2000 a setembro de 2021. Verificou-se o potencial dos modelos Circular, Gaussiano, Esférico, Tetraesférico, Pentaesférico e Exponencial, e o Grau de Dependência Espacial entre as variáveis, utilizando-se do tratamento de dados por linguagem de programação Python e R e por técnicas de geoprocessamento. Os resultados apontaram para maior aplicabilidade do modelo Gaussiano em toda série histórica, sendo sucedido pelo modelo Exponencial em períodos chuvosos, e pelo modelo Circular na estação seca. Os modelos Pentaesférico, Esférico e Tetraesférico foram os menos aplicados. Viu-se também uma relação irregular entre o desempenho dos modelos e o Grau de Dependência Espacial das variáveis.Palavras-chave: krigagem, dependência espacial, estações pluviométricas, gestão integrada dos recursos hídricos. Comparison of geostatistical models for rainfall forecast in Minas Gerais, Brazil, between 2000 and 2021 hydrological years A B S T R A C TThe integrated water resources management in Brazil and worldwide had been through challenges from anthropic activities and natural processes. In that regard, the precise knowledge of water resources quality and quantity conditions has major importance, with the rainfall monitoring network by rainfall stations as a core component for understanding the precipitation spatial and temporal dynamics. These stations are concentrated in a few sites within Minas Gerais, which makes the decision-making process difficult for the manager agents. Geostatistical analysis has been shown as an accurate method for rainfall forecast in spaces with lack of rainfall stations, and this work aimed to apply it in Minas Gerais, between October 2000 and September 2021 hydrological years. It was checked Circular, Gaussian, Spherical, Tetraspherical, Pentaspherical, and Exponential models potential, and the degree of spatial dependence, using data treatment by Python and R programming language and geoprocessing tools. The results showed that Gaussian model has greater applicability in the time series, being succeed by Exponential model in wet season, and Circular model in dry season. Pentaspherical, Spherical, and Tetraspherical models were the least applied. It was found an irregular relationship between models’ performance and the degree of spatial dependence.Keywords: kriging, degree of spatial dependence, rainfall stations, integrated water resources management.

show abstract

Section: Modelounclassified

Comparação de modelos geoestatísticos para estimativa de precipitação em Minas Gerais, Brasil, entre os anos hidrológicos de 2000 e 2021

Guimarães

Alves²

2023

Rev. Bras. Geog. Fis.

View full text Add to dashboard Cite

show abstract

“…As indicated in Figure 3, the project utilizes Tiga Dam to provide irrigation water to three local government areas in Kano state: Kura, Bunkure, and Garun Malam. The study area is located between 11 • 38 59" and 11 • 37 53" north latitude, and 8 • 25 28" and 8 • 27 26" east longitude [21].…”

Section: Study Areamentioning

confidence: 99%

“…This is evidenced by the country's annual consumption, which has increased from less than 1.0 million metric tons (MT) in the 1960s to more than 6.9 million MT in 2019 [20]. The country's yearly rice intake per capita is 46 kilograms [21]. Nonetheless, during the previous two decades, consumption has expanded at a rate close to four times that of the global consumption growth [22].…”

Section: Introductionmentioning

confidence: 99%

Water Use Efficiency and Productivity of Irrigated Rice Cultivation in Nigeria: An Application of the Stochastic Frontier Approach

et al. 2023

View full text Add to dashboard Cite

In the face of declining water resources and low agricultural water productivity, it is vital to increase agricultural production efficiency and efficiency of water usage. The efficacy of irrigating rice fields in Nigeria is evaluated here using a stochastic frontier analysis. This is a parametric frontier that is assumed to have half-normal distribution, allowing the model to be separated from normal errors in a composite error model. Samples of 382 surveys were used in the study; out of the total number, 361 surveys were retrieved and used for the analysis. The analytical tools used in the study are: gross margin, water productivity analysis, and stochastic frontier approach. The results indicate an average yield of 4.69 and 4.94 tons/hectare, and net farm income of $415 and $364 for the farmers using canal irrigation and farmers using tube wells, respectively. The results also showed physical and economic water productivity of 0.51 kg/m3 and $0.11/m3 for canal water users, and 0.568 kg/m3 and $0.10/m3 for tube well users. The canal water users had a mean irrigation water use efficiency of 0.76, compared to 0.70 for the tube well users. The study recommends that effective extension services and their coverage be enhanced to provide adequate training to rice farmers on water use efficiency and the transfer of innovations and farming technologies to farmers.

show abstract

“…The Kano River Irrigation Project (KRIP) is one of the pioneer projects established by the Federal government of Nigeria in 1970 (Ahmad, 2018). The project aimed at increasing food production and productivity, improve the beneficiaries' income, provide employment opportunities and reduce food insecurity (Yusuf et al, 2020). The study purposively used rice farmers for the study because rice is cultivated in more than 70% of the cropped area (Wudil et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Determinants of food security in Nigeria: Empirical evidence from beneficiaries and non-beneficiaries rice farmers of the Kano River Irrigation Project

Wudil

Ali

Aderinoye-Abdulwahab

et al. 2023

Front. Sustain. Food Syst.

View full text Add to dashboard Cite

IntroductionWhile the prevalence of hunger decreased globally, it has risen in sub-Saharan Africa in recent years mainly due to rapid population growth, low agricultural productivity, and economic downturns. This study was conducted to examine food security determinants at the household levels among the beneficiaries and non-beneficiaries rice farmers of the Kano river irrigation project in Nigeria.MethodsCross-sectional data were used for the analysis while multi-stage sampling technique was used to obtain data from 382 respondents, out of which 217 were project beneficiaries and 165 non-beneficiaries; using a semi-structured questionnaire. Data were analyzed using Household food security index and Logit regression model.Results and discussionThe results showed that 72.6% of the beneficiaries' households were food secure, against the non-beneficiaries, who had 65.4% food secure households. The findings also revealed that the beneficiaries have 11 and 4% food insecurity depth and severity respectively. Non-beneficiaries, on the other hand, had 17 and 8% food insecurity depth and severity, respectively. Extension contact, farm size, rice output, and educational attainment were the positive determinants of food security. Similarly, determinants that could increase food insecurity identified were; credit constraints and household size. It is recommended that the design of a food security strategy should be multi-dimensional and should encompass social, institutional and economic transformation of small scale farmers. Addressing the identified determinants is also crucial for enhancing the food security status in the study area.

show abstract

Soil salinity assessment using geostatistical models in some parts of Kano River Irrigation Project Phase I (KRPI)

Cited by 12 publications

References 17 publications

Comparação de modelos geoestatísticos para estimativa de precipitação em Minas Gerais, Brasil, entre os anos hidrológicos de 2000 e 2021

Comparação de modelos geoestatísticos para estimativa de precipitação em Minas Gerais, Brasil, entre os anos hidrológicos de 2000 e 2021

Water Use Efficiency and Productivity of Irrigated Rice Cultivation in Nigeria: An Application of the Stochastic Frontier Approach

Determinants of food security in Nigeria: Empirical evidence from beneficiaries and non-beneficiaries rice farmers of the Kano River Irrigation Project

Contact Info

Product

Resources

About