|
[1]
|
Challenges of groundwater pollution and management in transboundary basins at the African scale
Proceedings of the International Association of Hydrological Sciences,
2021
DOI:10.5194/piahs-384-69-2021
|
|
|
|
|
[2]
|
Source identification of nitrate contamination in the urban aquifer of Mashhad, Iran
Journal of Hydrology: Regional Studies,
2019
DOI:10.1016/j.ejrh.2019.100618
|
|
|
|
|
[3]
|
Low Cost Sensor Networks: How Do We Know the Data Are Reliable?
ACS Sensors,
2019
DOI:10.1021/acssensors.9b01455
|
|
|
|
|
[4]
|
Spatial filtering and Bayesian data fusion for mapping soil properties: A case study combining legacy and remotely sensed data in Iran
Geoderma,
2019
DOI:10.1016/j.geoderma.2019.02.031
|
|
|
|
|
[5]
|
Bayesian data fusion for combining maps of predicted soil classes: A case study using legacy soil profiles and DEM covariates in Iran
CATENA,
2019
DOI:10.1016/j.catena.2019.104138
|
|
|
|
|
[6]
|
Improving the reliability of groundwater monitoring networks using combined numerical, geostatistical and neural network-based simulation models
Hydrological Sciences Journal,
2019
DOI:10.1080/02626667.2019.1676429
|
|
|
|
|
[7]
|
Low Cost Sensor Networks: How Do We Know the Data Are Reliable?
ACS Sensors,
2019
DOI:10.1021/acssensors.9b01455
|
|
|
|
|
[8]
|
Application of random forest regression and comparison of its performance to multiple linear regression in modeling groundwater nitrate concentration at the African continent scale
Hydrogeology Journal,
2018
DOI:10.1007/s10040-018-1900-5
|
|
|
|
|
[9]
|
Modelling nitrate pollution pressure using a multivariate statistical approach: the case of Kinshasa groundwater body, Democratic Republic of Congo
Hydrogeology Journal,
2016
DOI:10.1007/s10040-015-1337-z
|
|
|
|
|
[10]
|
A meta-analysis and statistical modelling of nitrates in groundwater at the African scale
Hydrology and Earth System Sciences,
2016
DOI:10.5194/hess-20-2353-2016
|
|
|
|
|
[11]
|
Index-based groundwater vulnerability mapping models using hydrogeological settings: A critical evaluation
Environmental Impact Assessment Review,
2015
DOI:10.1016/j.eiar.2015.02.001
|
|
|
|