Your search found 4 records
1 Reis, J.; Lacombe, Guillaume; Hoanh, Chu Thai; McCartney, Matthew; Douangsavanh, S.; Leticia, M.; Teoh, S. J.; Kam, S. P.; Senaratna Sellamuttu, Sonali. 2011. Adjusting hydropower dam operation to compliment livelihood strategies in the Lower Mekong Basin. [Abstract only]. Paper presented at the 3rd International Forum on Water and Food, Tshwane, South Africa, 14-17 November 2011. 2p.
(Location: IWMI HQ Call no: e-copy only Record No: H044564)
(0.51 MB) (518.64KB)
(Location: IWMI HQ Call no: e-copy only Record No: H046639)
(0.51 MB)
Hydropower and irrigation developments to address rising demand for food and energy are modifying the water balance of the Mekong Basin. Infrastructure investment decisions are also frequently made from a sub-catchment perspective. This paper compares river flows with irrigation development stages in the Nam Ngum sub-basin where the potential for irrigation and hydropower expansion is largely untapped. It shows that full hydropower development in this basin allows irrigation water use to triple, even as it reduces competition with environmental flow requirements. The implications for the wider Mekong are, however, unclear, particularly given uncertainty over parallel transformations elsewhere in the basin.
(Location: IWMI HQ Call no: e-copy only Record No: H046640)
(0.88 MB) (898.20 KB)
Study region: Increasing demographic pressure and economic development in the Mekong Basin result in greater dependency on river water resources and increased vulnerability to streamflow variations.
Study focus: Improved knowledge of flow variability is therefore paramount, especially in remote catchments, rarely gauged, and inhabited by vulnerable populations. We present simple multivariate power-law relationships for estimating streamflow metrics in ungauged areas, from easily obtained catchment characteristics. The relations were derived from weighted least square regression applied to streamflow, climate, soil, geographic, geomorphologic and land-cover characteristics of 65 gauged catchments in the Lower Mekong Basin. Step-wise and best subset regressions were used concurrently to maximize the prediction R-squared computed by leave-one-out cross-validations, thus ensuring parsimonious, yet accurate relationships.
New hydrological insights for the region: A combination of 3–6 explanatory variables – chosen among annual rainfall, drainage area, perimeter, elevation, slope, drainage density and latitude – is sufficient to predict a range of flow metrics with a prediction R-squared ranging from 84 to 95%. The inclusion of forest or paddy percentage coverage as an additional explanatory variable led to slight improvements in the predictive power of some of the low-flow models (lowest prediction R-squared = 89%). A physical interpretation of the model structure was possible for most of the resulting relationships. Compared to regional regression models developed in other parts of the world, this new set of equations performs reasonably well.
(Location: IWMI HQ Call no: e-copy only Record No: H048455)
(7.44 MB)
Groundwater recharge remains almost totally unknown across the Mekong River Basin, hindering the evaluation of groundwater potential for irrigation. A regional regression model was developed to map groundwater recharge across the Lower Mekong Basin where agricultural water demand is increasing, especially during the dry season. The model was calibrated with baseflow computed with the local-minimum flow separation method applied to streamflow recorded in 65 unregulated sub-catchments since 1951. Our results, in agreement with previous local studies, indicate that spatial variations in groundwater recharge are predominantly controlled by the climate (rainfall and evapotranspiration) while aquifer characteristics seem to play a secondary role at this regional scale. While this analysis suggests large scope for expanding agricultural groundwater use, the map derived from this study provides a simple way to assess the limits of groundwater-fed irrigation development. Further data measurements to capture local variations in hydrogeology will be required to refine the evaluation of recharge rates to support practical implementations.
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