CWP Côte d'Ivoire (PNECI) requested and obtained an audience with the UNDP Resident Representative in Côte d'Ivoire. The audience enabled PNECI to inform the UNDP representative about the IWRM operationalisation process in Côte d'Ivoire and to request his support for its implementation.
In a collaborative effort to ensure the integrity and reliability of essential water infrastructure, GWP-C teamed up with Daniel and Daniel Engineering Inc. to conduct a comprehensive site inspection at the intake structure/dam and transmission/Distribution mains located in Mt. Granby, St. John. The seven-man technical team, assembled by Daniel and Daniel Engineering Inc., carried out the inspection under the expert guidance of retiree Michael “Freshy” Fleming.
Drought resilience and biodiversity conservation are closely interlinked. Conservation efforts that protect and restore biodiversity help maintain ecosystem services, such as water retention and soil health, which are crucial for mitigating the impacts of drought. Healthy and diverse ecosystems can also withstand and recover from droughts more easily. Thus, preserving biodiversity strengthens ecosystems’ natural ability to endure drought conditions and enhances long-term sustainability.
On May 31, 2024, the Ministry of Natural Resources and Environment (MONRE) of Lao PDR, represented by the CREWS Project's Focal Point, and GWP SEA, through the GWP Lao PDR, held a Hybrid Kick-off Meeting on the Development of Drought Management and IWRM Action Plan at the Vientiane Plaza Hotel in Lao PDR.
On November 12, 2024, Liang Jun, the Party Committee Secretary and Chairman of China Malaysia Investment Holding Group, engaged in a discussion with Shen Biao, the Vice Chairman and Secretary General of the GWP China Belt and Road Working Committee (BRWC), along with his delegation.
While Bamako, the capital of Mali, is being hit hard by flooding, a workshop is being held on the subject of real-time mapping of the risk of flooding in Mali on the basis of rainfall forecasts, remote sensing and deep learning (AFCIA-Mali Project).
