Soil moisture is a key control on runoff generation and biogeochemical processes on hillslopes. Precipitation events can evoke different soil moisture responses with depth through the soil profile, ...and responses can differ among landscape positions along a hillslope. We sought to elucidate the nature of these responses by estimating changes in water content, response time between peak precipitation and peak soil moisture, and wetting front velocities for 43 storms at 45 locations on three adjacent hillslopes within a headwater catchment of the southern Appalachian Mountains (NC, USA). We used a multivariate modeling approach to quantify the relative influences and the predictability of soil moisture responses by a combination of landscape and storm characteristics. We quantified the lag correlations between hillslope mean soil moisture and catchment runoff to demonstrate how storm properties and hillslope‐scale characteristics may influence runoff at the catchment outlet. Soil moisture responses varied widely, and no consistent patterns were observed among response metrics laterally or vertically along hillslopes. In contrast to other studies, we found that the relative influence of hillslope properties and storm characteristics varied with soil moisture responses and during storms. Antecedent conditions and storm depths influenced the strength of lag correlations between soil moisture and runoff, whereas storm mean intensity was correlated with the lag times. These results highlight the utility of intensive observations for characterizing heterogeneity in soil moisture responses, suggesting, among other things, a need for better representation of the subsurface processes in rainfall‐runoff models. Identifying the relative importance of drivers can be beneficial in building parsimonious hydrological models.
Key Points
No consistent patterns in soil moisture responses among landscape positions laterally along hillslopes
Dominant controls on soil moisture responses to storms varied with individual response metrics and during storms
Storm depth, mean intensity, and antecedent conditions mediated the soil moisture‐runoff relationships in space and time
Most current long‐term (decadal and longer) hydrological predictions implicitly assume that hydrological processes are stationary even under changing climate. However, in practice, we suspect that ...changing climatic conditions may affect runoff generation processes and cause changes in the rainfall‐runoff relationship. In this article, we investigate whether temporary but prolonged (i.e., of the order of a decade) shifts in rainfall result in changes in rainfall‐runoff relationships at the catchment scale. Annual rainfall and runoff records from south‐eastern Australia are used to examine whether interdecadal climate variability induces changes in hydrological behavior. We test statistically whether annual rainfall‐runoff relationships are significantly different during extended dry periods, compared with the historical norm. The results demonstrate that protracted drought led to a significant shift in the rainfall‐runoff relationship in ∼46% of the catchment‐dry periods studied. The shift led to less annual runoff for a given annual rainfall, compared with the historical relationship. We explore linkages between cases where statistically significant changes occurred and potential explanatory factors, including catchment properties and characteristics of the dry period (e.g., length, precipitation anomalies). We find that long‐term drought is more likely to affect transformation of rainfall to runoff in drier, flatter, and less forested catchments. Understanding changes in the rainfall‐runoff relationship is important for accurate streamflow projections and to help develop adaptation strategies to deal with multiyear droughts.
Key Points:
Multiyear droughts can change catchment hydrological behavior
Long dry periods can result in higher runoff reductions than single year droughts
Drier, flatter, and less forested catchments are more susceptible to change
To accurately project future water availability under a drying climate, it is important to understand how precipitation is partitioned into other terrestrial water balance components, such as fluxes ...(evaporation, transpiration, runoff) and changes in storage (soil moisture, groundwater). Many studies have reported unexpected large runoff reductions during drought, particularly for multi‐year events, and some studies report a persistent change in partitioning even after the meteorological drought has ended. This study focused on understanding how actual evapotranspiration (AET) and change in subsurface storage (ΔS) respond to climate variability and change, examining Australia's Millennium Drought (MD, 1997–2009). The study initially conducted a catchment‐scale water balance analysis to investigate interactions between ΔS and AET. Then the water balance analysis was extended to regional scale to investigate ΔS using interpolated rainfall and discharge with remotely sensed AET. Lastly, we evaluated conceptual rainfall‐runoff model performance of two commonly used models against these water balance estimates. The evaluation of water‐balance‐derived ΔS against Gravity Recovery and Climate Experiment (GRACE) estimates shows a significant multiyear storage decline; however, with different rates. In contrast, AET rates (annualized) remained approximately constant before and during the MD, contrasting with some reports of evapotranspiration enhancement elsewhere. Overall, given AET remained approximately constant, drought‐induced precipitation reductions were partitioned into ΔS and streamflow. The employed conceptual rainfall‐runoff models failed to realistically represent AET during the MD, suggesting the need for improved conceptualization of processes. This study provides useful implications for explaining future hydrological changes if similar AET behavior is observed under a drying climate.
Key Points
For a multiyear drought, we investigated the impact of precipitation reductions on water balance fluxes and change in storage
Actual evapotranspiration was approximately unchanged even under prolonged droughts in a water‐limited region
Because of this, precipitation reduction during the multiyear drought was partitioned into reductions in streamflow and subsurface storage
Modelling hydrological process in the critical zone not only contributes to a better understanding of interactions across different Earth surface spheres but also holds significant practical ...implications for water resource management and disaster prevention. Rainfall‐runoff simulation in critical zones is particularly challenging due to the amalgamation of temporal and spatial complexity, rainfall variability, and data limitations. As a pivotal input variable of hydrological models, accurate estimation of areal rainfall is critical to successful runoff simulation. However, most estimation methods ignore temporal information, thereby increasing uncertainty in rainfall estimation and constraining the precision of rainfall‐runoff simulation. In this study, the matrix decomposition‐based estimation method (F‐SVD), which considers the spatial and temporal correlation of the rainfall process is employed to estimate areal rainfall. The superiority of the method in producing two‐dimensional rainfall information is evaluated through its application in runoff simulation with the Xin'anjiang model. The simulation results of selected flood events in the Jianxi basin in southeast China, spanning from 2009 to 2019, are compared with those of two widely used rainfall estimation methods, namely Arithmetical Mean (AM) and Thiessen Polygons (TP). The results show that (1) F‐SVD not only produces the highest Pearson correlation coefficient between rainfall and runoff series but also reduces the number of flood events with abnormal rainfall‐runoff relationships; (2) the Xin'anjiang model based on F‐SVD achieves the highest Nash‐Sutcliffe efficiency and lowest Relative Error, and performs best in simulating peak flow and its occurrence time as compared to AM and TP. This study contributes to a finer characterization of watershed rainfall distribution, enhancing the accuracy and sharpness of runoff simulation. It provides reliable data support for critical zone research and offers a scientific foundation for rationally allocating and managing water resources.
A spatiotemporal rainfall estimation method based on Funk‐SVD is applied to rainfall‐runoff simulation to explore whether considering the spatiotemporal information of the rainfall process can more truly express the physical relationship between rainfall and runoff, and improve the accuracy of the runoff simulation in the critical zone.
Landscape differences induced by urbanization have prompted hydrologists to define a fuzzy boundary between rural‐ and urban‐specific hydrological models. We addressed the validity of establishing ...this boundary, by testing two rural models on a large sample of 175 French and United States (US) urbanized catchments, and their 175 rural neighbours. The impact of urbanization on the hydrological behaviour was checked using four metrics. Using a split‐sample test, we have compared the performances, parameter distributions, and internal fluxes of GR4H and IHACRES, two conceptual and continuous models running at the hourly time step. Both model structures are based on soil moisture accounting reservoirs (infiltration, runoff, and actual evapotranspiration) and quick flow/slow flow routing components, with no consideration of any specific feature related to urbanization. Results showed: (a) Except for the ratio of streamflow flashiness to precipitation flashiness, the range of hydrological signature metrics in rural catchments encompassed the specificities of urbanized ones. Overall, the urbanized catchments showed higher ratios of mean streamflow to mean precipitation (median values: 0.39 vs. 0.27) and streamflow flashiness to precipitation flashiness (0.13 vs. 0.03), besides lower baseflow index (0.42 vs. 0.62) and shorter characteristic response time (3 vs. 14 hr). (b) The performances of GR4H revealed no significant distinction between rural and urbanized catchments in terms of Kling–Gupta Efficiency (KGE), whereas IHACRES better simulated urbanized catchments, especially during summer. (c) With respect to differences in urbanization level, the GR4H and IHACRES parameters showed different distributions. The differences in parameters were consistent with the differences in hydrological behaviour, which is promising for a model‐based assessment of the impact of urbanization. (d) The models agreed less in reproducing the internal fluxes over the urbanized catchments than over the rural ones. These results demonstrate the flexibility of conceptual models to handle the specificities of urbanized catchments.
175 French and United States urbanized catchments are compared with their 175 rural neighbours. This comparison illustrates the impact of urbanization on hydrological behaviour. Using two hourly rural conceptual models, GR4H and IHACRES, we demonstrate the flexibility of rural models in reproducing the behaviour of urbanized catchments. Differences in hydrological behaviour between urbanized and rural catchments resulted in different distributions of model parameters.
Environmental flow assessment frameworks have begun to consider changes to flow regimes resulting from land-use change. Urban stormwater runoff, which degrades streams through altered volume, pattern ...and quality of flow, presents a problem that challenges dominant approaches to stormwater and water resource management, and to environmental flow assessment. We used evidence of ecological response to different stormwater drainage systems to develop methods for input to environmental flow assessment. We identified the nature of hydrologic change resulting from conventional urban stormwater runoff, and the mechanisms by which such hydrologic change is prevented in streams where ecological condition has been protected. We also quantified the increase in total volume resulting from urban stormwater runoff, by comparing annual streamflow volumes from undeveloped catchments with the volumes that would run off impervious surfaces under the same rainfall regimes. In catchments with as little as 5-10% total imperviousness, conventional stormwater drainage, associated with poor in-stream ecological condition, reduces contributions to baseflows and increases the frequency and magnitude of storm flows, but in similarly impervious catchments in which streams retain good ecological condition, informal drainage to forested hillslopes, without a direct piped discharge to the stream, results in little such hydrologic change. In urbanized catchments, dispersed urban stormwater retention measures can potentially protect urban stream ecosystems by mimicking the hydrologic effects of informal drainage, if sufficient water is harvested and kept out of the stream, and if discharged water is treated to a suitable quality. Urban stormwater is a new class of environmental flow problem: one that requires reduction of a large excess volume of water to maintain riverine ecological integrity. It is the best type of problem, because solving it provides an opportunity to solve other problems such as the provision of water for human use.
Evidence suggests that catchment state variables such as groundwater can exhibit multiyear trends. This means that their state may reflect not only recent climatic conditions but also climatic ...conditions in past years or even decades. Here we demonstrate that five commonly used conceptual “bucket” rainfall‐runoff models are unable to replicate multiyear trends exhibited by natural systems during the “Millennium Drought” in south‐east Australia. This causes an inability to extrapolate to different climatic conditions, leading to poor performance in split sample tests. Simulations are examined from five models applied in 38 catchments, then compared with groundwater data from 19 bores and Gravity Recovery and Climate Experiment data for two geographic regions. Whereas the groundwater and Gravity Recovery and Climate Experiment data decrease from high to low values gradually over the duration of the 13‐year drought, the model storages go from high to low values in a typical seasonal cycle. This is particularly the case in the drier, flatter catchments. Once the drought begins, there is little room for decline in the simulated storage, because the model “buckets” are already “emptying” on a seasonal basis. Since the effects of sustained dry conditions cannot accumulate within these models, we argue that they should not be used for runoff projections in a drying climate. Further research is required to (a) improve conceptual rainfall‐runoff models, (b) better understand circumstances in which multiyear trends in state variables occur, and (c) investigate links between these multiyear trends and changes in rainfall‐runoff relationships in the context of a changing climate.
Key Points
Environmental state variables such as groundwater display multiyear trends in response to sustained climate anomalies
We show that five commonly used conceptual “bucket” rainfall runoff models are unable to replicate such trends
Because of this, the models fail to extrapolate realistically to different climatic conditions, compromising runoff projections
Plain Language Summary
It is common in science to use a mental picture or metaphor that simplifies a complex phenomenon. A common metaphor used for a water supply catchment is that of a leaky bucket. When it rains, the bucket fills up; when it does not rain for a while, the bucket empties due to evaporation and water used by trees; and leaking water is like river flow. Computer models based on variants of this metaphor are common and can provide predictions of how much streamflow might occur under future scenarios. This paper explores limitations of the bucket metaphor and associated models. Recently, during a 13‐year drought in Australia, river catchments gradually started to dry up. With each passing year, the depth to groundwater increased gradually as the water used by trees was not replenished by rainfall. We compare this long, slow behavior to that of five commonly used “bucket” models. The models do not show the long, slow drying up—they only show the seasonal ups and downs, and their predictions of streamflow over the drought are poor. This is surprising, and it means we should choose our models carefully and seek out models that can simulate this behavior and its impact on streamflow.
River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific ...and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first collect an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 11) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950--December 2014) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring. The newly derived data are made publicly available at doi:10.1594/PANGAEA.845725.
In this study, satellite meteorological products were used as important data sources to achieve rainfall-runoff simulation and flood dynamic monitoring in the Songhua River basin (below the Sancha ...estuary) in northeastern China. Satellite precipitation products CHIRPS (the Climate Hazards Group Infrared Precipitation with Stations) and satellite evapotranspiration products MODIS-ET (the Moderate Resolution Imaging Spectroradiometer-Evapotranspiration) were collected for the study area during 2010-2015. The accuracy of satellite meteorological products was validated by ground observation data in the same period. Then, combined with satellite meteorological products, a daily-scale rainfall-runoff model suitable for the study area was established. The daily river runoff (RR) and surface runoff depth (SRD) of the study area were obtained through this model. It is found that the overall performance of satellite meteorological products is good through verification. The annual average deviation of MODIS-ET and observation data is less than 1 mm. In tertiary basins of the study area, the correlation coefficient (CC) between CHIRPS and observation data is in the range from 0.59 to 0.71, and the root-mean-square error (RMSE) varies from 3.75 to 4.50 mm. The rainfall-runoff model based on satellite meteorological products can well simulate the variation characteristics of observed RR: the CC reach 0.83, and the Nash-Sutcliffe efficiency coefficient (NSE) reach 0.72. The established model was used to analyse a flood event in 2013. And the simulation results showed the changing process of the RR accurately. The dynamic changing process of the SRD was monitored by the established model during the flooding period. The model can be used to reflect the spatial distribution of potential inundation areas. This study validates the performance and deviation of CHIRPS and MODIS-ET, and proves that these satellite meteorological products have good applicability in rainfall-runoff simulation and flood dynamic monitoring. The output results, daily RR and SRD data with 0.05
°
grid unit, can provide the decision support for hydrological information monitoring and flood forecasting.
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