A copy of Guangbo jiemu bao [Broadcast Program Report] was being passed from hand to hand among a group of young people eager to be the first to read the article introducing the program "What Is Revolutionary Love?" It said: "… Young friends, you are certainly very concerned about this problem'. So, we would like you to meet the young women workers Meng Xiaoyu and Meng Yamei and the older cadre Miss Feng. They are the three leading characters in the short story ‘The Place of Love.’ Through the description of the love lives of these three, the story induces us to think deeply about two questions that merit further examination.

This is How the Discussion Started

. A traditional metric used in hydrology to summarize model
performance is the Nash–Sutcliffe efficiency (NSE). Increasingly an
alternative metric, the Kling–Gupta efficiency (KGE), is used instead. When
NSE is used, NSE  =  0 corresponds to using the mean flow as a benchmark
predictor. The same reasoning is applied in various studies that use KGE as
a metric: negative KGE values are viewed as bad model performance, and only
positive values are seen as good model performance. Here we show that using
the mean flow as a predictor does not result in KGE  =  0, but instead KGE  = 1 - √ 2 ≈ - 0.41 . Thus, KGE values greater than −0.41 
indicate that a model improves upon the mean flow benchmark – even if the
model's KGE value is negative. NSE and KGE values cannot be directly
compared, because their relationship is non-unique and depends in part on
the coefficient of variation of the observed time series. Therefore,
modellers who use the KGE metric should not let their understanding of NSE
values guide them in interpreting KGE values and instead develop new
understanding based on the constitutive parts of the KGE metric and the
explicit use of benchmark values to compare KGE scores against. More
generally, a strong case can be made for moving away from ad hoc use of
aggregated efficiency metrics and towards a framework based on
purpose-dependent evaluation metrics and benchmarks that allows for more
robust model adequacy assessment.

/pdf/technical-note-inherent-benchmark-or-not-comparing-nash-2pevwhaxzz.pdf

Technical note: Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores

Operational medium range flood forecasting systems are increasingly moving towards the adoption of ensembles of numerical weather predictions (NWP), known as ensemble prediction systems (EPS), to drive their predictions. We review the scientific drivers of this shift towards such ‘ensemble flood forecasting’ and discuss several of the questions surrounding best practice in using EPS in flood forecasting systems. We also review the literature evidence of the ‘added value’ of flood forecasts based on EPS and point to remaining key challenges in using EPS successfully.

Ensemble flood forecasting: A review

This paper reviews recent progress in the study and understanding of extreme seasonal events in the Amazon region, focusing on drought and floods. The review includes a history of droughts and floods in the past, in the present and some discussions on future extremes in the context of climate change and its impacts on the Amazon region. Several extreme hydrological events, some of them characterized as ‘once in a century’, have been reported in the Amazon region during the last decade. While abundant rainfall in various sectors of the basin has determined extreme floods along the river's main stem in 1953, 1989, 1999, 2009, 2012–2015, deficient rainfall in 1912, 1926, 1963, 1980, 1983, 1995, 1997, 1998, 2005 and 2010 has caused anomalously low river levels, and an increase in the risk and number of fires in the region, with consequences for humans. This is consistent with changes in the variability of the hydrometeorology of the basin and suggests that extreme hydrological events have been more frequent in the last two decades. Some of these intense/reduced rainfalls and subsequent floods/droughts were associated (but not exclusively) with La Nina/El Nino events. In addition, moisture transport anomalies from the tropical Atlantic into Amazonia, and from northern to southern Amazonia alter the water cycle in the region year-to-year. We also assess the impacts of such extremes on natural and human systems in the region, considering ecological, economic and societal impacts in urban and rural areas, particularly during the recent decades. In the context of the future climate change, studies show a large range of uncertainty, but suggest that drought might intensify through the 21st century.

Extreme seasonal droughts and floods in Amazonia: causes, trends and impacts

Abstract. We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000–2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized (

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

. Extreme flooding impacts millions of people that live within the
Amazon floodplain. Global hydrological models (GHMs) are frequently used to
assess and inform the management of flood risk, but knowledge on the skill
of available models is required to inform their use and development. This
paper presents an intercomparison of eight different GHMs freely available
from collaborators of the Global Flood Partnership (GFP) for simulating
floods in the Amazon basin. To gain insight into the strengths and
shortcomings of each model, we assess their ability to reproduce daily and
annual peak river flows against gauged observations at 75 hydrological
stations over a 19-year period (1997–2015). As well as highlighting regional variability in the accuracy of simulated streamflow, these results indicate that (a) the meteorological input is the dominant control on the accuracy of both daily and annual maximum river flows, and (b) groundwater and routing calibration of Lisflood based on daily river flows has no impact on the ability to simulate flood peaks for the chosen river basin. These findings have important relevance for applications of large-scale hydrological models, including analysis of the impact of climate variability, assessment of the influence of long-term changes such as land-use and anthropogenic climate change, the assessment of flood likelihood, and for flood forecasting systems.

/pdf/assessing-the-performance-of-global-hydrological-models-for-3tmg59a2o6.pdf

Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin

Anomalous conditions in the oceans and atmosphere have the potential to be used to enhance the predictability of flood events, enabling earlier warnings to reduce risk. In the Amazon basin, extreme flooding is consistently attributed to warmer or cooler conditions in the tropical Pacific and Atlantic Oceans, with some evidence linking floods to other hydroclimatic drivers such as the Madden-Julian Oscillation (MJO). This review evaluates the impact of several hydroclimatic drivers on rainfall and river discharge regimes independently, aggregating all of the information of previous studies to provide an up to date depiction of what we currently know and do not know about how variations in climate impact flooding in the Amazon. Additionally, 34 major flood events that have occurred since 1950 in the Amazon and their attribution to climate anomalies are documented and evaluated. This review finds that despite common agreement within the literature describing the relationship between phases of climate indices and hydrometeorological variables, results linking climate anomalies and flood hazard is often limited to correlation rather than causation, while the understanding on their usefulness for flood forecasting is weak. There is a need to better understand the ocean-atmosphere response mechanisms that led to previous flood events. In particular, examining the oceanic and atmospheric conditions preceding individual hydrological extremes as opposed to composite analysis, could provide insightful information into the magnitude and spatial distribution of anomalous SSTs required to produce extreme floods. Importantly, such analysis could provide meaningful thresholds on which to base seasonal flood forecasts.

Attribution of Amazon floods to modes of climate variability: A review

. Flooding in the Amazon basin is frequently attributed to modes of
large-scale climate variability, but little attention is paid to how these
modes influence the timing and duration of floods despite their importance
to early warning systems and the significant impacts that these flood
characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (GloFAS 2.1) and observed data at 58 gauging stations are used to examine whether positive or negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (1979–2015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative El Nino–Southern Oscillation (ENSO) phases when the sea surface temperature (SST) anomaly is positioned in the central tropical Pacific. This response is not identified for the eastern Pacific index, highlighting how the response can differ between ENSO types. Although flood magnitude and duration were found to be highly correlated, the impacts of large-scale climate variability on these characteristics are non-linear; some increases in annual flood maxima coincide with decreases in flood duration. The impact of flood timing, however, does not follow any notable pattern for all indices analysed. Finally, observed and simulated changes are found to be much more highly correlated for negative ENSO phases compared to the positive phase, meaning that GloFAS struggles to accurately simulate the differences in flood characteristics between El Nino and neutral years. These results have important implications for both the social and physical sectors working towards the improvement of early warning action systems for floods.

/pdf/influence-of-enso-and-tropical-atlantic-climate-variability-bifctmvypd.pdf

Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin

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Papers

Assessing the performance of global hydrological models for capturing peak river flows in the Amazon basin

Attribution of Amazon floods to modes of climate variability: A review

Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin