A retrospective streamflow ensemble forecast for an extreme hydrologic event: a case study of Hurricane Irene and on the Hudson River basin

This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River basin ( ∼ 36 000 km2) in the United States using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were forced into HEC-HMS to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 h pre-event by utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modeling framework was implemented on the Hudson River basin, it is flexible and applicable in other parts of the world where atmospheric reanalysis products and streamflow data are available.

A Retrospective Streamflow Ensemble Forecast for an Extreme Hydrologic Event: a Case Study of Hurricane Irene and on the Hudson River basin

This paper investigates the uncertainties in hourly streamflow ensemble forecasts for an extreme hydrological event using a hydrological model forced with short-range ensemble weather prediction models. A state-of-the art, automated, short-term hydrologic prediction framework was implemented using GIS and a regional scale hydrological model (HEC-HMS). The hydrologic framework was applied to the Hudson River Basin, USA (~ 36,000 km2) using gridded precipitation data from the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) and was validated against streamflow observations from the United States Geologic Survey (USGS). Finally, 21 precipitation datasets reforecast by the 21 ensemble members of the latest Global Ensemble Forecast System (GEFS/R) were used to generate a retrospective streamflow ensemble forecast for an extreme hydrological event, Hurricane Irene. The work shows that ensemble stream discharge forecasts provide improved predictions and useful information about associated uncertainties, thus improving the assessment of risks when compared with deterministic forecasts. The uncertainties in weather inputs may result in false warnings and missed river flooding events, reducing the potential to effectively mitigate flood damage. The findings demonstrate how errors in the ensemble median streamflow forecast and time of peak, as well as the ensemble spread (uncertainty) are reduced 48 hours pre-event utilizing the ensemble framework. The methodology and implications of this work benefit efforts of short-term streamflow forecasts at regional scales, notably regarding the peak timing of an extreme hydrologic event when combined with a flood threshold exceedance diagram. Although the modelling framework was implemented on the Hudson River basin, it is flexible and re-locatable in other parts of the world.

Groundwater sapping as the cause of irreversible desertification of Hunshandake Sandy Lands, Inner Mongolia, northern China

In the middle-to-late Holocene, Earth’s monsoonal regions experienced catastrophic precipitation decreases that produced green to desert state shifts. Resulting hydrologic regime change negatively impacted water availability and Neolithic cultures. Whereas mid-Holocene drying is commonly attributed to slow insolation reduction and subsequent nonlinear vegetation–atmosphere feedbacks that produce threshold conditions, evidence of trigger events initiating state switching has remained elusive. Here we document a threshold event ca. 4,200 years ago in the Hunshandake Sandy Lands of Inner Mongolia, northern China, associated with groundwater capture by the Xilamulun River. This process initiated a sudden and irreversible region-wide hydrologic event that exacerbated the desertification of the Hunshandake, resulting in post-Humid Period mass migration of northern China’s Neolithic cultures. The Hunshandake remains arid and is unlikely, even with massive rehabilitation efforts, to revert back to green conditions.

Long-term declines in phosphorus export from forested catchments in south-central Ontario

Total phosphorus (TP) levels in many Canadian Shield lakes in central Ontario have declined over recent decades, despite increases in human activity in most watersheds. To investigate the contribution of changes in catchment export to long-term declines in lake TP, we examined temporal and spatial patterns in TP concentrations and export (1980–1981 to 2001–2002) across 11 subcatchments that drain into three lakes in which average ice-free TP levels have declined by approximately 35%. Annual stream export of TP decreased significantly by 30%–89% in eight of the 11 subcatchments, and decreases in export were driven by declines in TP concentration, not changes in stream flow. Annual average TP concentrations varied fivefold among adjacent subcatchments, and temporal patterns in annual average TP concentrations were poorly correlated. Seasonal patterns of TP concentration were most similar among streams in the spring (March–April–May), and TP export in the spring declined significantly in 10 of the 11 subcatchments. Because spring melt is the principal hydrologic event in these seasonally snow-covered basins, decreases in TP export during the spring were primarily responsible for declines observed in annual export. The drivers of changes in TP over time are unclear at this point but are the focus of current research.