Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Developing Sustainable Groundwater for Agriculture: Approach for a Numerical Groundwater Flow Model in Data-Scarce Sia Kouanza, Niger
The area of Sia Kouanza in the Sahel of southwestern Niger is a potential location for expanding agriculture through irrigation with groundwater. Agriculture is key to supporting smallholders and promoting food security. As plans proceed, questions include how much water is available, how is groundwater replenished, many hectares to develop, and where to locate the wells. While these questions can be addressed with a model, it is difficult to find detailed procedures, especially when data are scarce. How can we use existing information to develop a model of a natural system where groundwater development will take place? We describe an approach that can be employed in data-scarce areas where similar questions are being asked. The approach includes setting details; conceptual model development; water balance; numerical code MODFLOW; model construction, calibration, and statistics; and result interpretation. Conceptual model component estimates are derived from field data: recharge, evapotranspiration, wetlands discharge, existing extraction, and river stages. When field data are not available or scarce, we employ other sources and describe how they are validated with field data or analog sites. The calibrated steady-state model gives a water balance of 22 × 106 m3/yr with inflows (recharge 22 × 106 m3/yr) and outflows (extraction 7.2 × 105 m3/yr, wetlands 5.7 × 106 m3/yr, evapotranspiration 11.9 × 106 m3/yr). The model is a point of departure; approaches for transient and predictive models, which can be used to simulate changes in irrigation pumping volumes and drought, for example, will be described subsequently.
Developing Sustainable Groundwater for Agriculture: Approach for a Numerical Groundwater Flow Model in Data-Scarce Sia Kouanza, Niger
The area of Sia Kouanza in the Sahel of southwestern Niger is a potential location for expanding agriculture through irrigation with groundwater. Agriculture is key to supporting smallholders and promoting food security. As plans proceed, questions include how much water is available, how is groundwater replenished, many hectares to develop, and where to locate the wells. While these questions can be addressed with a model, it is difficult to find detailed procedures, especially when data are scarce. How can we use existing information to develop a model of a natural system where groundwater development will take place? We describe an approach that can be employed in data-scarce areas where similar questions are being asked. The approach includes setting details; conceptual model development; water balance; numerical code MODFLOW; model construction, calibration, and statistics; and result interpretation. Conceptual model component estimates are derived from field data: recharge, evapotranspiration, wetlands discharge, existing extraction, and river stages. When field data are not available or scarce, we employ other sources and describe how they are validated with field data or analog sites. The calibrated steady-state model gives a water balance of 22 × 106 m3/yr with inflows (recharge 22 × 106 m3/yr) and outflows (extraction 7.2 × 105 m3/yr, wetlands 5.7 × 106 m3/yr, evapotranspiration 11.9 × 106 m3/yr). The model is a point of departure; approaches for transient and predictive models, which can be used to simulate changes in irrigation pumping volumes and drought, for example, will be described subsequently.
Developing Sustainable Groundwater for Agriculture: Approach for a Numerical Groundwater Flow Model in Data-Scarce Sia Kouanza, Niger
Alexandra Lutz (Autor:in) / Yahaya Nazoumou (Autor:in) / Adamou Hassane (Autor:in) / Diafarou Moumouni Ali (Autor:in) / Abdou Guero (Autor:in) / Susan Rybarski (Autor:in) / David Kreamer (Autor:in)
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
Estimation of spatially distributed groundwater recharge in data-scarce regions
| DOAJ | 2024
Estimation of spatially distributed groundwater recharge in data-scarce regions
| Elsevier | 2024