ABSTRACT The conventional method monitoring and adequateness of underground dams requires invasive investigatory actions with in their interior structure and only provides specific information for small volumes. On the contrary, application of non-invasive sensing techniques, such as ground penetrating radar (GPR), makes it possible to investigate and explore underground without affecting their structure. A GRP 3D profile was acquired with the aim to allot and monitor an underground dam in the Brazilian semiarid region in the alluvial sub-watershed of the Riacho Pau Lavrado in the Sertão Central de Lajes region of the state of Rio Grande do Norte in Brazil. The GPR profile records were acquired along an alluvial section, processed using the Reflex 5 software and exported into the Opendetec 4.4.0 software in order to obtain a virtual 3D model. The GPR 3D profile of the alluvial deposits shows irregularities of the crystalline basement and external topographical surface (soil). The interpretation of the alluvial GPR profile allows precise adequateness of the underground dam, which supports an increase in the area of hydric accumulation and promotes low-cost building due to the allocation selected with minor sedimentation. | RESUMO Os métodos de investigação convencionais para alocação e manejo de barragens subterrâneas requerem ações invasivas no interior da estrutura investigadas, fornecendo apenas informações pontuais para pequenos volumes. Já, a aplicação de técnica de detecção não invasiva como, por exemplo, o Ground Penetrating Radar (GPR), possibilita investigar e explorar o sub-superficie sem destruir a estrutura. Com o objetivo de avaliar a inclusão da técnica Ground Penetrating Radar para estudos de alocação e monitoramento de barragens subterrânea no semiárido brasileiro, realizou-se a aquisição de perfil com Ground-Penetrating Radar no corpo aluvionar na sub-bacia do riacho Pau Lavrado, região Sertão Central de Lajes, Estado do Rio Grande do Norte do Brasil. O dados de registro do perfil Ground-Penetrating Radar foram adquiridos ao longo do trecho do corpo aluvionar selecionado, processado no software Reflex 5 e exportadas para o software Opendetec 4.4.0, obtendo-se um modelo virtual 3D do corpo aluvionar. A análise do perfil Ground-Penetrating Radar com modelagem 3D do corpo aluvionar indicaram as irregularidades do embasamento cristalino e da superfície topográfica externa (solo). A interpretação do perfil GPR do corpo aluvionar permitiu a alocação precisa da barragem subterrânea, aumentando a sua área de acumulação hídrica com custo construtivo reduzido devido à escolha de locais com menores pacotes sedimentares.

ABSTRACT Water scarcity is one of the main problems in the Semiarid region of Brazil, which can be mitigated by water resource management strategies. The objective of this work was to classify waters of a watershed in the Semiarid region of Brazil and select the water attributes that most affect the quality of waters used for irrigation (QWI), using multivariate statistics. The study area was the Riacho da Bica watershed, which is between the municipalities of Portalegre and Viçosa, Rio Grande do Norte, Brazil. The QWI was determined using water samples from 15 collections carried out from 2016 to 2018, in five specific points of the watershed, starting in the spring and following the water course. The water attributes evaluated were: electrical conductivity (EC), potential hydrogen (pH), and sodium (Na+), potassium (K+), magnesium (Mg2+), calcium (Ca2+), carbonate (CO32-), chloride (Cl-), and bicarbonate (HCO3-) contents. The water quality data were subjected to multivariate statistics through factorial analysis (FA) and principal component analysis (PCA). The application of multivariate statistics through FA-PCA generated four principal components. The attributes that most explained the QWI variation were potassium, calcium, and pH for Factor 01, and sodium and RAS for Factor 02. The watershed waters were classified as low risk of salinity and medium risk of sodicity (C1S2) for irrigation purposes.