Preliminary investigation of emerging suburban landsliding in Gisborne, New Zealand

Recently uplifted, soft Pleistocene sediments in northern New Zealand are particularly vulnerable to landsliding because they are often underlain by less permeable, clay-rich Neogene mudstone/siltstone rocks. Typically, instability is rainfall-induced, often due to a high intensity rainfall event from extra-tropical cyclones, following wetter months when antecedent soil moisture has increased. Using remote sensing, field surveys and laboratory testing, we report on some emerging slope instability hazards in the eastern suburbs of the coastal city of Gisborne, on the North Island. Retrogressive failure of the main landslide (at Wallis Road) is ongoing and has already led to the abandonment of one home, while an adjacent landslide (at Titirangi Drive) appears to be in an incipient phase of failure. The Wallis Road landslide has been particularly active from mid-2017, with slumping of the headscarp area transitioning to a constrained mudflow downslope, which then descends a cliff before terminating on the beach. In contrast, the incipient Titirangi Drive landslide at present displays much more subtle effects of deformation. While activity at both landslides appears to be linked to rainfall-induced increases in soil moisture, this is due to the effects of prolonged periods of rainfall rather than the passage of high intensity cyclonic storms.

The relative importance of antecedent soil moisture and precipitation in flood generation in the middle and lower Yangtze River basin

Floods have caused severe environmental and social economic losses worldwide in human history, and are projected to exacerbate due to climate change. Many floods are caused by heavy rainfall with highly saturated soil, however, the relative importance of rainfall and antecedent soil moisture and how it changes from place to place has not been fully understood. Here we examined annual floods from more than 200 hydrological stations in the middle and lower Yangtze River basin. Our results indicate that the dominant factor of flood generation shifts from rainfall to antecedent soil moisture with the increase of watershed area. The ratio of the relative importance of antecedent soil moisture and daily rainfall (SPR) is positively correlated with topographic wetness index and has a negative correlation with the magnitude of annual floods. This linkage between watershed characteristics that are easy to measure and the dominant flood generation mechanism provides a quantitative method for flood control and early warnings in ungauged watersheds in the middle and lower Yangtze River basin.

GRACE Follow-On revealed Bangladesh was flooded early in the 2020 monsoon season due to premature soil saturation

The overall size and timing of monsoon floods in Bangladesh are challenging to measure. The inundated area is extensive in low-lying Bangladesh, and observations of water storage are key to understanding floods. Laser-ranging instruments on Gravity Recovery and Climate Experiment (GRACE) Follow-On spacecraft detected the peak water storage anomaly of 75 gigatons across Bangladesh in late July 2020. This is in addition to, and three times larger than, the maximum storage anomaly in soil layers during the same period. A flood propagation model suggested that the water mass, as shown in satellite observations, is largely influenced by slow floodplain and groundwater flow processes. Independent global positioning system measurements confirmed the timing and total volume of the flood water estimates. According to land surface models, the soils were saturated a month earlier than the timing of the peak floodplain storage observed by GRACE Follow-On. The cyclone Amphan replenished soils with rainfall just before the monsoon rains started, and consequently, excessive runoff was produced and led to the early onset of the 2020 flooding. This study demonstrated how antecedent soil moisture conditions can influence the magnitude and duration of flooding. Continuous monitoring of storage change from GRACE Follow-On gravity measurements provides important information complementary to river gauges and well levels for enhancing hydrologic flood forecasting models and assisting surface water management.

Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map

Hydrologic events can be characterized as particular combinations of hydrological processes on a hillslope scale. To configure hydrological mechanisms, we analyzed a dataset using an unsupervised machine learning algorithm to cluster the hydrologic events based on the dissimilarity distances between the weighting components of a self-organizing map (SOM). The time series of soil moisture was measured at 30 points (at 10 locations with three different depths) for 356 rainfall events on a steep, forested hillslope between 2007 and 2016. The soil moisture features for hydrologic events can be effectively represented by the antecedent soil moisture, soil moisture difference index, and standard deviation of the peak-to-peak time between rainfall and soil moisture response. Five clusters were delineated for hydrologically meaningful event classifications in the SOM representation. The two-dimensional spatial weighting patterns in the SOM provided more insights into the relationships between rainfall characteristics, antecedent wetness, and soil moisture response at different locations and depths. The distinction of the classified events could be explained by several rainfall features and antecedent soil moisture conditions that resulted in different patterns attributable to combinations of hillslope hydrological processes, vertical flow, and lateral flow along either surface or subsurface boundaries for the upslope and downslope areas.

Soil Moisture Influence on the Incidence of Summer Mesoscale Convective Systems in the U.S. Great Plains

Mesoscale convective systems (MCS) are known to develop under ideal conditions of temperature and humidity profiles and large-scale dynamic forcing. Recent work, however, has shown that summer MCS events can occur under weak synoptic forcing or even unfavorable large-scale environments. When baroclinic forcing is weak, convection may be triggered by anomalous conditions at the land surface. This work evaluates land surface conditions for summer MCS events forming in the U.S. Great Plains using an MCS database covering the contiguous United States east of the Rocky Mountains, in boreal summers 2004-2016. After isolating MCS cases where synoptic-scale influences are not the main driver of development (i.e. only non-squall line storms), antecedent soil moisture conditions are evaluated over two domain sizes (1.25° and 5° squares) centered on the mean position of the storm initiation. A negative correlation between soil moisture and MCS initiation is identified for the smaller domain, indicating that MCS events tend to be initiated over patches of anomalously dry soils of ~100-km scale, but not significantly so. For the larger domain, soil moisture heterogeneity, with anomalously dry soils (anomalously wet soils) located northeast (southwest) of the initiation point, is associated with MCS initiation. This finding is similar to previous results in the Sahel and Europe that suggest that induced meso-β circulations from surface heterogeneity can drive convection initiation.

Peak flood volume and its suspended sediment at various rainfall in Kedungbulus catchment in Gombong, Central Java, Indonesia

Flood is a natural disaster that frequently happens and causes many material and immaterial losses. During flooding, the suspended sediment is carried along by the streamflow. The amount of sediment transported varies and depends on natural and anthropogenic factors. Limited studies have been conducted regarding the relationship between peak flood volume and its sediment content. Therefore, a study with the purpose to understand the relationship of rainfall characteristics, peak flood volume, and suspended sediment was undertaken in Kedungbulus Catchment in Gombong, Central Java, Indonesia. The size of Kedungbulus catchment is 37.8 km2. To collect the required data, an automatic stream water level recorder was installed in the outlet of the catchment. In addition, an automatic and two conventional rain gauges were set up inside the catchment. Hydrograph and statistical analysis were conducted on 2016-2017 data. The results showed that during the study period, the highest peak flood volume occurred on October 8, 2016. The flood duration was 490 minutes, with the time to peak was 135 minutes. At the highest peak flood volume, the stream water was 5,091,221 m3, and the suspended sediment was around 2,394 tons. Rainfall depth significantly affects the peak flood volume and its suspended sediment. The rainfall intensity and Antecedent Soil Moisture Content (ASMC) weakly correlate with peak flood volume and its suspended sediment content.

Can the re-infiltration process be ignored for flood inundation mapping and prediction during extreme storms?

Coupled Hydrologic & Hydraulic (H&H) models have been widely applied to simulate both discharge and flood inundation due to their complementary advantages, yet the H&H models oftentimes suffer from one-way and weak coupling and particularly disregarded run-on infiltration or re-infiltration. This could compromise the model accuracy, such as under-prediction (over-prediction) of subsurface water contents (surface runoff). In this study, we examine the H&H model performance differences between the scenarios with and without re-infiltration process in extreme events¬ – 100-year design rainfall and 500-year Hurricane Harvey event – from the perspective of flood depth, inundation extent, and timing. Results from both events underline that re-infiltration manifests discernable impacts and non-negligible differences for better predicting flood depth and extents, flood wave timings, and inundation durations. Saturated hydraulic conductivity and antecedent soil moisture are found to be the prime contributors to such differences. For the Hurricane Harvey event, the model performance is verified against stream gauges and high water marks, from which the re-infiltration scheme increases the Nash Sutcliffe Efficiency score by 140% on average and reduces maximum depth differences by 17%. This study highlights that the re-infiltration process should not be disregarded even in extreme flood simulations. Meanwhile, the new version of the H&H model – the Coupled Routing and Excess STorage inundation MApping and Prediction (CREST-iMAP) Version 1.1, which incorporates such two-way coupling and re-infiltration scheme, is released for public access.

Spatiotemporal impact of antecedent drought on hot extremes from the nonstationary risk perspective: A case study in eastern China

Hot extremes may adversely impact human health and agricultural production. Owing to anthropogenic and climate changes, the close and dynamic interaction between drought and hot extremes in most areas of China need to be revisited from the perspective of nonstationarity. This study therefore proposes a time-varying Copula-based model to describe the nonstationary dependence structure of extreme temperature (ET) and antecedent soil moisture condition to quantify the dynamic risk of hot extremes conditioned on dry/wet condition. This study proposed a new approach to identify the soil moisture driving law over extreme temperature from the point view of tail monotonicity and nonstationary risk assessment. Owing to the LTI-RTD (left tail increasing and right tail decreasing) tail monotonicity for dependence structure of these two extremes derived from most areas, the driving laws of soil moisture over ET follows DDL1-WDL1 laws (DDL1: drier antecedent soil moisture condition would trigger a higher risk of ET; WDL1: wetter antecedent soil moisture condition would alleviate the occurrence risk of ET). Because of the spatiotemporal divergence of sensitivity index derived from tail monotonicity (SITM), we can conclude that the spatial and temporal heterogeneity of response degree of ET over the variations of antecedent dry/wet conditions is evident. Incorporation of nonstationarity and tail monotonicity helps identify the changes of driving mechanism (laws) between soil moisture and hot extremes. From the comparison of different kinds of nonstationary behaviours over the spatial distribution of conditional probability of ET (CP1), the dependence nonstationarity can impose greater variations on the spatial distribution of conditional risk of ET given antecedent dry condition (CP1).