Method to identify composition and production phases of spring runoff in high-latitude mid-temperate regions: a case study in the Second Songhua River Basin, China

Simulation and forecasting of runoff play an important role in the early warning and prevention of drought and flood disasters. To improve the accuracy of spring runoff simulations, it is important to identify spring runoff production patterns under the combined effect of snow and frozen soil. Based on the theory of the hydrological cycle, three important parameters, which include surface and subsurface runoff, precipitation and temperature, were selected for this study. The trend analysis, statistical analysis and Eckhardt's recursive numerical filtering method were used to qualitatively identify the production patterns of spring runoff, the start and end dates and stage periods of the production patterns. Based on the qualitative identification results, the contribution of each production runoff to the total annual runoff and the total annual spring runoff is quantitatively assessed. The results of the study show that the spring runoff production patterns in the Second Songhua River Basin can be divided into snowmelt runoff, frozen soil conditions of snowmelt–rainfall runoff and rainfall runoff under frozen soil conditions; the snowmelt production is from 21 March, the frozen soil conditions production is from 21 April and the frozen soil ablation ended on 15 June; the shortest phases of each production pattern last 28, 20 and 18 days and the longest last 31, 26 and 24 days. This research provides the basis for improving the principles of production runoff calculation in spring runoff simulation methods.

Multi-decadal retreat of marine-terminating outlet glaciers in northwest and central-west Greenland

The retreat and acceleration of marine-terminating outlet glaciers in Greenland over the past two decades has been widely attributed to climate change. Here we present a comprehensive annual record of glacier terminus positions in northwest and central-west Greenland and compare it against local and regional climatology to assess the regional sensitivity of glacier termini to different climatic factors. This record is derived from optical and radar satellite imagery and spans 87 marine-terminating outlet glaciers from 1972 through 2021. We find that in this region, most glaciers have retreated over the observation period, and widespread regional retreat accelerated around 1996. The acceleration of glacier retreat coincides with the timing of sharp shifts in ocean surface temperatures, duration of sea-ice season, ice-sheet surface mass balance, and meltwater and runoff production. Our findings suggest that a variety of processes – such as ocean-interface melting, mélange presence and rigidity, and hydrofracture-induced calving – contribute to, but do not conclusively dominate, the observed regional retreat.

Prediction of factors affecting activation of soil erosion by mathematical modeling at pedon scale under laboratory conditions

Soil degradation due to erosion is a significant worldwide problem at different spatial (from pedon to watershed) and temporal scales. All stages and factors in the erosion process must be detected and evaluated to reduce this environmental issue and protect existing fertile soils and natural ecosystems. Laboratory studies using rainfall simulators allow single factors and interactive effects to be investigated under controlled conditions during extreme rainfall events. In this study, three main factors (rainfall intensity, inclination, and rainfall duration) were assessed to obtain empirical data for modeling water erosion during single rainfall events. Each factor was divided into three levels (− 1, 0, + 1), which were applied in different combinations using a rainfall simulator on beds (6 × 1 m) filled with soil from a study plot located in the arid Sistan region, Iran. The rainfall duration levels tested were 3, 5, and 7 min, the rainfall intensity levels were 30, 60, and 90 mm/h, and the inclination levels were 5, 15, and 25%. The results showed that the highest rainfall intensity tested (90 mm/h) for the longest duration (7 min) caused the highest runoff (62 mm3/s) and soil loss (1580 g/m2/h). Based on the empirical results, a quadratic function was the best mathematical model (R2 = 0.90) for predicting runoff (Q) and soil loss. Single-factor analysis revealed that rainfall intensity was more influential for runoff production than changes in time and inclination, while rainfall duration was the most influential single factor for soil loss. Modeling and three-dimensional depictions of the data revealed that sediment production was high and runoff production lower at the beginning of the experiment, but this trend was reversed over time as the soil became saturated. These results indicate that avoiding the initial stage of erosion is critical, so all soil protection measures should be taken to reduce the impact at this stage. The final stages of erosion appeared too complicated to be modeled, because different factors showed differing effects on erosion.

Stormflow behaviour in blanket peat catchments affected by severe wildfire: implications for natural flood management

<p>The restoration of damaged UK peatlands is a major conservation concern, and landscape-scale restoration is extensive in areas of upland Britain. Peatland headwater catchments are important areas of hillslope runoff production, and over the last decade there has been increasing focus on how restoration schemes can reduce downstream flood risk through natural flood management (NFM). Stormflow in degraded catchments can be incredibly flashy, as water is quickly evacuated from hillslopes across bare peat surfaces and through erosional gullies, but there is increasing evidence that restoration by revegetation and damming of channels can significantly slow the flow of water.</p><p>Recent major peatland wildfires in the UK have focused attention on the effects of wildfire and post-wildfire restoration on the hydrology of peatland catchments, but to date, relatively little is known about the effects of wildfire on peatland flood hydrology. Current understanding is largely drawn from process studies, with evidence suggesting that severely burnt peatlands will have flashier hydrograph responses to rainfall events, with higher peak flows relative to unburnt peatlands. This assumption is based on three key factors which promote rapid overland flow: (i) the development of hydrophobic crusts due to high intensity fires, (ii) the clogging of peat pores by ash, and (iii) removal of vegetation cover reducing surface roughness. Further influences on runoff production could result from changes in water table or post-fire peat shrinkage and cracking.</p><p>This paper details stormflow characteristics from nine gullies in an area of peatland affected by the high-severity Saddleworth wildfire which burned over 1000 hectares of UK peatland in June and July 2018. This field area is upstream of the community of Stalybridge, which the Environment Agency had highlighted as a priority community at risk of flooding. We compare this behaviour to catchments that were unaffected by the fire. Preliminary findings suggest that the fire affected gullies produce highly variable stormflow behaviour, with some sites producing discharges similar to bare peat sites, while others are more similar to relatively intact catchments. The planned restoration of this area has great potential to provide NFM benefits.</p>

Uncertainty in soil hydraulic properties limits the predictability of global water and carbon dynamics

<p>Water transport at the land surface and in the soil – the critical zone - is highly dependent on the soil hydraulic properties. Such properties influence simultaneously the terrestrial water and carbon cycles as they determine the water fluxes in the soil and the soil’s water holding capacity, ultimately affecting runoff production, groundwater recharge, and the amount and temporal variability of plant available water (i.e. plant water stress). Despite their paramount importance, limited global information concerning the spatial distribution of soil hydraulic properties currently exists. Information at the global scale, commonly used in Earth System Models, mostly originates from pedotransfer functions (PTFs). PFTs are empirical relations that express the dependence of soil hydraulic properties on easily measured attributes as soil properties. Several PFTs currently exist, which adopt different formulations, spanning from simple linear regressions to elaborate machine learning, and are trained with different datasets, yielding different soil hydraulic properties for the same soil texture.   </p><p>The question we ask in this study is: how does uncertainty in the soil hydraulic parameters propagate in global ecosystem responses? To achieve this, we deploy a numerical experiment covering many different ecosystems. The terrestrial ecosystem model T&C is used to model energy, water, and carbon dynamics at 80 locations worldwide, spanning all climatological regimes, major biomes and soil types. Soil hydraulic properties at each site were estimated using six widely used PTFs starting from local soil textural information. Uncertainty propagation from soil hydraulic properties to modelled ecosystem dynamics was evaluated for all sites and its dependence on soil textural properties and local topography was quantified.</p><p>Our results highlight that uncertainty propagation from hydraulic properties to ecosystem dynamics is much stronger for hydrological fluxes (e.g. infiltration, groundwater recharge and runoff production) than carbon dynamics (e.g. gross and net primary productivity and leaf area dynamics) or energy fluxes (net radiation, sensible and latent heat). Uncertainty in hydrological fluxes can be up to 400% using different PTFs, whereas uncertainties in carbon and energy fluxes are typically less than 20%. The largest uncertainties were observed for slow draining soils, containing large fractions of clay, located in regions with intermediate values of wetness (i.e. annual precipitation ≈ annual potential evapotranspiration). Complex topographic features further enhance the role of uncertainty in soil hydraulic properties. Lateral water redistribution affects both runoff production and soil moisture dynamics increasing the effects on both hydrological and carbon dynamics.</p>

Exploring potential of remotely sensed data in parameterization of hydrologic model

<p>Recent observation-based studies have shown that satellite-based antecedent soil moisture can provide useful information on runoff production. The patterns uncovered can be used to benchmark the degree of coupling between antecedent soil moisture, rainfall totals and runoff production, and to determine if hydrologic models can reproduce these patterns for a particular model parameterization of their rainfall-runoff processes. The goal of our study is twofold; First, it derives the relationships between runoff ratio and its major controls, including rainfall total, antecedent soil moisture, and vegetation using remotely sensed data products. Second, it aims to determine if the model is capable to reproduce these relationships and use them to validate model parameters and streamflow predictions. For this purpose, SMAP (Soil Moisture Active Passive) satellite-based soil moisture, S-band radar rainfall, MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation index, and USGS (United States Geological Survey) daily streamflow observations are used. The study domain consists of thirty-eight basins less than 1000 km<sup>2</sup> located in an agricultural region in the United States Midwest. For each basin, daily streamflow predictions, before and after adjustments to the hydrologic model are compared with observations. The comparisons are done for four years (2015-2018) using multiple performance metrics. This study could serve as a data-driven approach for parameterization of rainfall-runoff partitioning in hydrologic models using remotely sensed observations. </p>

Investigating the role of antecedent SMAP satellite soil moisture, radar rainfall and MODIS vegetation on runoff production in an agricultural region

Following results by Crow et al. (2017) [Geophys. Res. Lett. 44, 5495-5503] on the impact of antecedent soil moisture on runoff production, we investigate total runoff production during individual rainfall-runoff events in agricultural landscapes as a function of antecedent soil moisture, total rainfall, and vegetation cover for catchments with drainage areas ranging from 80-1000 km2 in the state of Iowa, USA. For our study, we use Enhanced SMAP soil moisture estimates, the MODIS enhanced vegetation index (EVI), gauge-corrected Stage IV radar rainfall, and USGS streamflow data. We analyze the event runoff ratio as a function of event-scale rainfall, antecedent SMAP soil moisture and soil-moisture-deficit-normalized rainfall for the events in a period from March 31, 2015 to October 31, 2018. Our goal is to confirm the relationships identified by Crow et al. (2017) in heavily managed agricultural landscapes and to refine some of their methodological steps to quantify the role of additional variables controlling runoff production. To this end, we define three different strategies to identify rainfall-runoff events and add a baseflow separation step to better insulate event scale stormflow runoff. We test the effects of antecedent soil moisture, rainfall, and vegetation on the event-scale runoff ratio. The antecedent SMAP soil moisture and event-scale rainfall are found to have significant predictive power in estimating event runoff ratio. Soil moisture deficit-normalized rainfall, introduced as the ratio of event-scale rainfall to available space in top soil before initiation of the event, exhibited a more distinct relationship with runoff ratio. The long-term analysis of runoff ratio, rainfall, and MODIS EVI indicated that, in an agricultural region, vegetation plays a significant role in determining event-scale runoff ratios. The methodology and outcome of our study have direct implications on real-time flood forecasting and long-term hydrologic assessments.