Centennial scale benthic foraminiferal record of late Holocene oceanographic variability in Disko Bugt,West Greenland

A new centennial scale benthic foraminiferal record of late Holocene climate variability and oceanographic changes off West Greenland (Disko Bugt) highlights substantial subsurface water mass changes (e.g. temperature and salinity) of the West Greenland Current (WGC) over the past 3.6 ka BP. Benthic foraminifera reveal a long-term late Holocene cooling trend, which may be attributed to increased advection of cold, low-salinity water masses derived from the East Greenland Current (EGC). Cooling becomes most pronounced from c. 1.7 ka BP onwards. At this point the calcareous Atlantic benthic foraminiferal fauna decrease significantly and is replaced by an agglutinated Arctic fauna. Superimposed on this cooling trend, centennial scale variability in the WGC reveals a marked cold phase at c. 2.5 ka BP, which may correspond to the 2.7 ka BP cooling-event recorded in marine and terrestrial archives elsewhere in the North Atlantic region. A warm phase recognized at c. 1.8 ka BP is likely to correspond to the ‘Roman Warm Period’ and represents the warmest bottom water conditions. During the time period of the ‘Medieval Climate Anomaly’ we observe only a slight warming of the WGC. A progressively more dominant cold water contribution from the EGC on the WGC is documented by the prominent rise in abundance of agglutinated Arctic water species from 0.9 ka BP onwards. This cooling event culminates at c. 0.3 ka BP and represents the coldest episode of the ‘Little Ice Age’.Gradually increased influence of cold, low-salinity water masses derived from the EGC may be linked to enhanced advection of Polar and Arctic water by the EGC. These changes are possibly associated with a reported shift in the large-scale North Atlantic Oscillation atmospheric circulation pattern towards a more frequent negative North Atlantic Oscillation mode during the late Holocene.     

Predicting the dependency of a degree of saturation on void ratio and suction using effective stress principle for unsaturated soils

The paper presents an approach to predicting variation of a degree of saturation in unsaturated soils with void ratio and suction. The approach is based on the effective stress principle for unsaturated soils and several underlying assumptions. It focuses on the main drying and wetting processes and does not incorporate the effects of hydraulic hysteresis. It leads to the dependency of water retention curve (WRC) on void ratio, which does not require any material parameters apart from the parameters specifying WRC for the reference void ratio. Its validity is demonstrated by comparing predictions with the experimental data on four different soils taken over from the literature. Good correlation between the measured and predicted behaviour indirectly supports applicability of the effective stress principle for unsaturated soils. Copyright © 2009 John Wiley & Sons, Ltd.     

The data‐driven approach as an operational real‐time flood forecasting model

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.     

Dams on the Mekong River: Lost fish protein and the implications for land and water resources

Proposed dam construction in the Lower Mekong Basin will considerably reduce fish catch and place heightened demands on the resources necessary to replace lost protein and calories. Additional land and water required to replace lost fish protein with livestock products are modelled using land and water footprint methods. Two main scenarios cover projections of these increased demands and enable the specific impact from the main stem dam proposals to be considered in the context of basin-wide hydropower development. Scenario 1 models 11 main stem dams and estimates a 4–7% increase overall in water use for food production, with much higher estimations for countries entirely within the Basin: Cambodia (29–64%) and Laos (12–24%). Land increases run to a 13–27% increase. In scenario 2, covering another 77 dams planned in the Basin by 2030 and reservoir fisheries, projections are much higher: 6–17% for water, and 19–63% for land. These are first estimates of impacts of dam development on fisheries and will be strongly mediated by cultural and economic factors. The results suggest that basic food security is potentially at a high risk of disruption and therefore basin stakeholders should be fully engaged in strategies to offset these impacts.