Streamflow Response Research Articles

Modeling streamflow variability at the regional scale: (2) Development of a bespoke distributed conceptual model

Regional scale distributed conceptual models are typically developed with a bottom-up approach, which is process-inclusive but prone to over-parameterization. Here we demonstrate a proof of concept top-down approach for distributed conceptual model development, intended to emphasize dominant streamflow generating processes and to fulfill the principle of model parsimony. A key challenge in applying the top-down approach to distributed model development is devising a model comparison experiment that is both informative and limited to a few model alternatives. Here, we show how such model comparisons can be informed by a perceptual model of key processes that control streamflow response variability at the regional scale. We demonstrate our approach for the 27,100 km2 Moselle catchment, using the perceptual model developed in Part 1 of this two-part paper. We develop 5 distributed model structures for simulating daily streamflow at 26 subcatchments, and validate them on subcatchments that are not used during the calibration process. Our model comparisons illustrate how the spatial distribution of precipitation, lithology and topography affect the simulation of key signatures of streamflow response variability in the Moselle catchment, providing a basis to justify model decisions. Our analyses show how a minimally parameterized distributed model, with 12 calibration parameters, matches signatures of streamflow average (r = 0.96), baseflow index (r = 0.86), and hydrograph lag time (correct at 22 out of 26 subcatchments). Our proposed top-down approach contributes to improving distributed model development strategies, and can be used to develop parsimonious process based regional models elsewhere.

Modeling streamflow variability at the regional scale: (1) perceptual model development through signature analysis

Perceptual catchment models are a key first step towards hydrologic synthesis and provide the process foundation of predictive models. However, their development is usually limited to the headwater catchment scale where field work can be done. Here we develop a perceptual model approach for a regional scale catchment. We use a systematic “top-down” approach based on an expert-driven interpretation of the streamflow responses of nested subcatchments. This approach complements the traditional “bottom-up” perceptual model development based on fieldwork observations, which is impractical at the regional scale due to measurement limitations. As an example to illustrate our approach and demonstrate its feasibility, we use the 27,100 km2 Moselle catchment, with 26 gauged subcatchments. Our perceptual model of the Moselle catchment presents a description of dominant processes that we consider a-posteriori reasonable, but not a-priori obvious: where precipitation, much more than evaporation or groundwater exchange controls the spatial variability of average streamflow, lithology influences the partitioning between baseflow and quickflow, and topography and land use control hydrograph lag times. A striking feature of our analysis is the rather minor role that vegetation and soil appear to play in streamflow spatial variability at the scale of our inquiry. We use our perceptual model to build a distributed yet parsimonious hydrological model in Part 2 of this paper series. Although the perceptual model is specific for the Moselle, we hope that the perceptual model approach used here can be helpful to others working in large catchments in different hydroclimates, where other factors will dominate.

Improving flood forecasting using conditional bias-aware assimilation of streamflow observations and dynamic assessment of flow-dependent information content

We describe an adaptive extension of the conditional bias-penalized ensemble Kalman filter for conditional bias (CB)-aware data assimilation (DA) and comparatively evaluate with the ensemble Kalman filter (EnKF) for 6 headwater basins in Texas using the operational lumped hydrologic models from the National Weather Service. We then use CB-aware DA and the degrees of freedom for signal to assess the marginal information content of observations. We show that CB arises very frequently in varying magnitudes when assimilating streamflow observations during the catchment’s response to precipitation and subsequent drainage, and that, in general, larger discharges are associated with larger CB. CB-aware DA improves over EnKF by varying margins in times of significant flow, and the improvement is particularly large during sharp rises of the outlet hydrograph with large peak flows. For the 6 study basins, the average relative reduction in root mean square error of the ensemble mean streamflow analysis by CB-aware DA over EnKF is 31.5% for all ranges of observed flow and 32.1% for observed flow exceeding 200 cms. The flow-dependent marginal information content of the observations varies very significantly with the streamflow response of the catchment and the magnitude of CB, and tends to decrease and increase in the rising and falling phases of the hydrograph, respectively. The findings indicate that CB-aware DA with information content analysis offers an objective framework for dynamically balancing the predictive skill of hydrologic models, quality and frequency of hydrologic observation, and scheduling of DA cycles toward improving operational flood forecasting cost-effectively.

Long‐Term Changes in Runoff Generation Mechanisms for Two Proglacial Areas in the Swiss Alps I: Overland Flow

AbstractIn many areas of the world, the surface of the earth is changing rapidly. This can affect the partitioning of precipitation into overland flow (OF) and infiltration. OF can reach the stream quickly and thus strongly influences the streamflow response to precipitation. It can also cause surface erosion. However, our knowledge of the changes in OF responses during landscape evolution is still limited. To investigate how hillslope aging effects OF, we studied three plots on four different aged moraines (several decades to ∼13.5 thousand years old) at a silicate and carbonate proglacial area in the Swiss Alps. We used sprinkling experiments to determine OF characteristics (such as the runoff ratio and timing) and used tracers (δ2H and NaCl) to identify the mixing of rainfall and soil water. Sediment concentrations and turbidity measurements provided an estimate of OF‐driven soil erosion rates. The OF ratios were largest (42%) for the oldest moraines because the clay‐rich layer at 20–40 cm below the surface caused saturated OF. However, OF occurred more frequently on the youngest moraines due to the high stone cover. Soil and vegetation development increase the soil water retention capacity and the pre‐event water fractions in OF for the old moraines, but decreased the suspended sediment yield. The results show that OF characteristics and sediment transport change markedly during landscape evolution. This needs to be taken into account when simulating runoff and erosion responses for rapidly changing Alpine areas, and can—together with the outcomes for subsurface flow (see companion paper Maier et al., 2021, https://doi.org/10.1029/2021WR030223)—be used to improve landscape evolution models.

Possible Linkages of Hydrological Variables to Ocean–Atmosphere Signals and Sunspot Activity in the Upstream Yangtze River Basin

Profiling the hydrological response of watershed precipitation and streamflow to large-scale circulation patterns and astronomical factors provides novel information into the scientific management and prediction of regional water resources. Possible contacts of El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), sunspot activity to precipitation and streamflow in the upper Yangtze River basin (UYRB) were investigated in this work. Monthly precipitation and streamflow were utilized as well as contemporaneous same-scale teleconnections time series spanning a total of 70 years from 1951 to 2020 in precipitation and 121 years from 1900 to 2020 in streamflow. The principal component analysis (PCA) method was applied so as to characterize the dominant variability patterns over UYRB precipitation time series, with the temporal variability of first two modes explaining more than 80% of total variance. Long-term evolutionary pattern and periodic variation characteristics of precipitation and streamflow are explored by applying continuous wavelet transform (CWT), cross-wavelet transform (XWT) and wavelet coherence (WTC), analyzing multi-scale correlation between hydrological variables and teleconnections in the time-frequency domain. The results manifest that ENSO exhibits multiple interannual period resonance with precipitation and streamflow, while correlations are unstable in time and phase. PDO and sunspot effects on precipitation and streamflow at interannual scales vary with time-frequency domains, yet significant differences are exhibited in their effects at interdecadal scales. PDO exhibits a steady negative correlation with streamflow on interdecadal scales of approximately 10 years, while the effect of sunspot on streamflow exhibits extremely steady positive correlation on longer interdecadal scales of approximately 36 years. Analysis reveals that both PDO and sunspot have significantly stronger effects on streamflow variability than precipitation, which might be associated with the high spatiotemporal variability of precipitation.

The Response of Streamflow to Climate Change in Gumera Watershed, Blue Nile River Basin, Ethiopia

Change in water hydrology is caused by climate change. This study evaluates the response of stream flow to climate change. A study of the impact of climate change on streamflow and direct runoff in the Gumera watershed was carried out using the hydrologic model HEC-HMS. Climate change impact analysis was performed using a down scaled Regional Climate Model (RCM) called the Hadley Center Earth System Model (Had GEM-ES). In this model, bias correction was done for 365 days using power transformation for rainfall correction. The study showed that for the RCP2.6 scenario, streamflow decreases annually by 0.001% in the 2050’s. It decreases annually with change of 0.01% for RCP4.5. The RCP8.5 scenario reveals an annual decrease in streamflow of 0.002%. The study provides a broad perspective on probable hydrologic alterations in the region, and the results provide useful input for sustainable water resource development.

Changes in the frequency of global high mountain rain-on-snow events due to climate warming

Rain-on-snow (ROS) events can trigger severe floods in mountain regions. There is high uncertainty about how the frequency of ROS events (ROS) and associated floods will change as climate warms. Previous research has found considerable spatial variability in ROS responses to climate change. Detailed global assessments have not been conducted. Here, atmospheric reanalysis data was used to drive a physically based snow hydrology model to simulate the snowpack and the streamflow response to climate warming of a 5.25 km2 virtual basin (VB) applied to different high mountain climates around the world. Results confirm that the sensitivity of ROS to climate warming is highly variable among sites, and also with different elevations, aspects and slopes in each basin. The hydrological model predicts a decrease in the frequency of ROS with warming in 30 out 40 of the VBs analyzed; the rest have increasing ROS. The dominant phase of precipitation, duration of snow cover and average temperature of each basin are the main factors that explain this variation in the sensitivity of ROS to climate warming. Within each basin, the largest decreases in ROS were predicted to be at lower elevations and on slopes with sunward aspects. Although the overall frequency of ROS drops, the hydrological importance of ROS is not expected to decline. Peak streamflows due to ROS are predicted to increase due to more rapid melting from enhanced energy inputs, and warmer snowpacks during future ROS.

Relationship between rainfall and streamflow in the La Plata Basin: annual cycles, interdecadal and multidecadal variability

The aim of this study is to understand the interaction between rainfall and streamflow variability in the La Plata basin (LPB) along a wide range of timescales. LPB is divided in six sub-basins associated to the main rivers (Paraguay, Paraná, Uruguay and Iguazú). The amplification of the streamflow response is addressed in order to evaluate to what extent river discharges variability can be explained by precipitation fluctuations. Mean annual cycles corresponding to 1931-2010 period and to each of the decades comprising it are analyzed. Streamflow interdecadal changes are observed in most of the gauging stations. In addition, an 11-year moving-average filter is applied to the normalized annual time series. Results exhibit a considerable higher percentage of explained variance in the streamflow filtered series, highlighting the predominance of low frequency variability present in these compared to those of precipitation. Consistently, river discharges show higher spectral density over decadal/interdecadal frequencies compared to precipitation analysis. A simple statistical approach to advance in the understanding of the complex rainfall-streamflow physical relationship is addressed with promising results: streamflow spectrums are derived directly from the precipitation spectrum, transformed by a 'basin' operator, characteristic of the basin itself. It is assumed that watersheds acts on precipitation as spatio-temporal integrators operating as low-pass filters, like a moving average. Streamflow power spectrums are simulated assuming that the underlying process is an autoregressive moving average (ARMA). Considering as the only input the sub-basin areal-averaged precipitation timeseries, results show that simulated streamflow spectrums fits effectively the observations at the sub-basin scale.

Tile drainage causes flashy streamflow response in Ohio watersheds

AbstractArtificial subsurface (tile) drainage is used to increase trafficability and crop yield in much of the Midwest due to soils with naturally poor drainage. Tile drainage has been researched extensively at the field scale, but knowledge gaps remain on how tile drainage influences the streamflow response at the watershed scale. The purpose of this study is to analyse the effect of tile drainage on the streamflow response for 59 Ohio watersheds with varying percentages of tile drainage and explore patterns between the Western Lake Erie Bloom Severity Index to streamflow response in heavily tile‐drained watersheds. Daily streamflow was downloaded from 2010 to 2019 and used to calculated mean annual peak daily runoff, mean annual runoff ratio, the percent of observations in which daily runoff exceeded mean annual runoff (TQmean), baseflow versus stormflow percentages, and the streamflow recession constant. Heavily‐drained watersheds (>40% of watershed area) consistently reported flashier streamflow behaviour compared to watersheds with low percentages of tile drainage (<15% of watershed area) as indicated by significantly lower baseflow percentages, TQmean, and streamflow recession constants. The mean baseflow percent for watersheds with high percentages of tile drainage was 20.9% compared to 40.3% for watersheds with low percentages of tile drainage. These results are in contrast to similar research regionally indicating greater baseflow proportions and less flashy hydrographs (higher TQmean) for heavily‐drained watersheds. Stormflow runoff metrics in heavily‐drained watersheds were significantly positively correlated to western Lake Erie algal bloom severity. Given the recent trend in more frequent large rain events and warmer temperatures in the Midwest, increased harmful algal bloom severity will continue to be an ecological and economic problem for the region if management efforts are not addressed at the source. Management practices that reduce the streamflow response time to storm events, such as buffer strips, wetland restoration, or drainage water management, are likely to improve the aquatic health conditions of downstream communities by limiting the transport of nutrients following storm events.

Streamflow response to native forest restoration in former Eucalyptus plantations in south central Chile

AbstractGlobal increases in intensive forestry have raised concerns about forest plantation effects on water, but few studies have tested the effects of plantation forest removal and native forest restoration on catchment hydrology. We describe results of a 14‐year paired watershed experiment on ecological restoration in south central Chile which documents streamflow response to the early stages of native forest restoration, after clearcutting of plantations of exotic fast‐growing Eucalyptus, planting of native trees, and fostering natural regeneration of native temperate rainforest species. Precipitation, streamflow, and vegetation were measured starting in 2006 in four small (3 to 5 ha) catchments with Eucalyptus globulus plantations and native riparian buffers in the Valdivian Coastal Reserve. Mean annual precipitation is 2500 mm, of which 11% occurs in summer. Streamflow increased, and increases persisted, throughout the first 9 years of vigorous native forest regeneration (2011 to 2019). Annual streamflow increased by 40% to >100% in most years and >150% in fall and summer of some years. Streamflow was 50% to 100% lower than before treatment in two dry summers. Base flow increased by 28% to 87% during the restoration period compared to pre‐treatment, and remained elevated in later years despite low summer precipitation. Overall, these findings indicate that removal of Eucalyptus plantations immediately increased streamflow, and native forest restoration gradually restored deep soil moisture reservoirs that sustain base flow during dry periods, increasing water ecosystem services. To our knowledge this is the first study to assess catchment streamflow response to native forest restoration in former forest plantations. Therefore, the results of this study are relevant to global efforts to restore native forest ecosystems on land currently intensively managed with fast‐growing forest plantations and may inform policy and decision‐making in areas experiencing a drying trend associated with climate change.

Impacts of a regional multiyear insect defoliation event on growing‐season runoff ratios and instantaneous streamflow characteristics

AbstractRepeated moderate severity forest disturbances can cause short‐ and long‐term shifts in ecosystem processes. Prior work has found that stand‐replacing disturbances (e.g., clear‐cutting) increase streamflow in temperate forests, but streamflow responses to repeated moderate severity disturbances are more equivocal. This study examined a moderate disturbance caused by an unexpected population irruption of the invasive insect Lymantria dispar (common name: gypsy moth) in 2015–2017. This irruption resulted in defoliation that was locally severe in some areas but spatially heterogeneous at a regional scale. L. dispar larvae consume leaves during the summer growing season, which effectively reduces tree leaf area and associated evapotranspiration. Our regional approach in Southern New England, USA, used data from 83 US Geological Survey (USGS) stream gages to assess whether changes in growing‐season watershed runoff ratios and instantaneous streamflow characteristics during the 2015–2017 L. dispar irruption were associated with satellite‐derived metrics of changes in forest condition (i.e., defoliation), compared to a 20‐year baseline streamflow period. We found a small, linear increase in growing‐season runoff ratio anomalies that was associated with defoliation intensity. The association between defoliation intensity and runoff ratio anomalies was magnified in less anthropogenically impacted reference watersheds. We also found that defoliation intensity was associated with larger volumes of high and medium instantaneous streamflows compared to baseline mean flow conditions. This study provided important insights into the impacts of moderate disturbance on ecohydrology in mesic temperate forests with a unique methodological approach that assessed the impacts of spatially heterogeneous and repeated moderate disturbance at a regional scale.

Bayesian Detection of Streamflow Response to Earthquakes

AbstractDetecting whether and how river discharge responds to strong earthquake shaking can be time‐consuming and prone to operator bias when checking hydrographs from hundreds of gauging stations. We use Bayesian piecewise regression models to show that up to a fifth of all gauging stations across Chile had their largest change in daily streamflow trend on the day of the Mw 8.8 Maule earthquake in 2010. These stations cluster distinctly in the near field though the number of detected streamflow changes varies with model complexity and length of time window considered. Credible seismic streamflow changes at several stations were the highest detectable in eight months, with an increased variance of discharge surpassing the variance of discharge following rainstorms. We conclude that Bayesian piecewise regression sheds new and unbiased insights on the duration, trend, and variance of streamflow response to strong earthquakes, and on how this response compares to that following rainstorms.

Hydrological response to warm and dry weather: do glaciers compensate?

Abstract. Warm and dry summer days can lead to low streamflow due to a lack of rainfall and increased evaporation. In glacierized catchments, however, such periods can lead to a very different hydrological response as glaciers can supply an increased amount of meltwater, thereby compensating for the rainfall deficits. Here, we analyzed glacier-fed streamflow responses to warm and dry (WD) periods in long-term streamflow observations (>50 years). WD events during summer (June–September) were analyzed for catchments with varying glacier cover in western Canada, southwestern Norway, and the European Alps. WD events were defined by days with temperatures above a daily varying threshold, based on the 80th percentile of the respective long-term temperature data for that day in the year, and daily precipitation sums below a fixed threshold (<2 mm d−1) for a minimum duration of 7 d. Streamflow responses to these WD events were expressed as level of compensation (C) and were calculated as the event streamflow relative to the long-term streamflow regime. C≥100 % indicates that increased melt and other catchment storages could compensate, or even overcompensate, the rainfall deficit and increased evaporation. Results showed a wide range of compensation levels, both between catchments and between different WD events in a particular catchment. C was, in general, higher than 100 % for catchments with a relative glacier cover higher than 5 %–15 %, depending on region and month. June was the month with highest compensation levels, but this was likely more influenced by snowmelt than by glacier melt. For WD events in September, C was still higher than 100 % in many catchments, which likely indicates the importance of glacier melt as a streamflow contributor in late summer. There was a considerable range in C of different WD events for groups of catchments with similar glacier cover. This could be partly explained by antecedent conditions, such as the amount of snow fallen in the previous winter and the streamflow conditions 30 d before the WD event. Some decreasing trends in C were evident, especially for catchments in western Canada and the European Alps. Overall, our results suggest that glaciers do not compensate straightforwardly, and the range in compensation levels is large. The different streamflow components – glacier, snow and rain – and their variations are important for the buffering capacity and the compensating effect of glaciers in these high mountain water systems.

A longer‐term perspective on soil moisture, groundwater and stream flow response to the 2018 drought in an experimental catchment in the Scottish Highlands

AbstractThe drought of summer 2018, which affected much of Northern Europe, resulted in low river flows, biodiversity loss and threats to water supplies. In some regions, like the Scottish Highlands, the summer drought followed two consecutive, anomalously dry, winter periods. Here, we examine how the drought, and its antecedent conditions, affected soil moisture, groundwater storage, and low flows in the Bruntland Burn; a sub‐catchment of the Girnock Burn long‐term observatory in the Scottish Cairngorm Mountains. Fifty years of rainfall‐runoff observations and long‐term modelling studies in the Girnock provided unique contextualisation of this extreme event in relation to more usual summer storage dynamics. Whilst summer precipitation in 2018 was only 63% of the long‐term mean, soil moisture storage across much of the catchment were less than half of their summer average and seasonal groundwater levels were 0.5 m lower than normal. Hydrometric and isotopic observations showed that ~100 mm of river flows during the summer (May‐Sept) were sustained almost entirely by groundwater drainage, representing ~30% of evapotranspiration that occurred over the same period. A key reason that the summer drought was so severe was because the preceding two winters were also dry and failed to adequately replenish catchment soil moisture and groundwater stores. As a result, the drought had the biggest catchment storage deficits for over a decade, and likely since 1975–1976. Despite this, recovery was rapid in autumn/winter 2018, with soil and groundwater stores returning to normal winter values, along with stream flows. The study emphasizes how long‐term data from experimental sites are key to understanding the non‐linear flux‐storage interactions in catchments and the “memory effects” that govern the evolution of, and recovery from, droughts. This is invaluable both in terms of (a) giving insights into hydrological behaviours that will become more common water resource management problems in the future under climate change and (b) providing extreme data to challenge hydrological models.

Gauging ungauged catchments – Active learning for the timing of point discharge observations in combination with continuous water level measurements

Hydrological models have traditionally been used for the prediction in ungauged basins despite the related challenge of model parameterization. Short measurement campaigns could be a way to obtain some basic information that is needed to support model calibration in these catchments. This study explores the potential of such field campaigns by i) testing the relative value of continuous water-level time series and point discharge observations for model calibration, and by ii) evaluating the value of point discharge observations collected using expert knowledge and active learning to guide when to measure streamflow. The study was based on 100 gauged catchments across the contiguous United States for which we pretended to have only limited hydrological observations, i.e., continuous daily water levels and ten daily point discharge observations from different hypothetical field trips conducted within one hydrological year. Water level data were used as a single source of information, as well as in addition to point discharge observations, for calibrating the HBV model. Calibration against point discharge observations was conducted iteratively by continually adding new observations from one of the ten field measurements. Our results suggested that the information contained in point discharge observations was especially valuable for constraining the annual water balance and streamflow response at the event scale, improving predictions based solely on water levels by up to 50% after ten field observations. In contrast, water levels were valuable to increase the accuracy of simulated daily streamflow dynamics. Informative discharge sampling dates were similar when selected with either active learning or expert knowledge and typically clustered during seasons with high streamflow.

Monitoring and Forecasting Kenya’s Fluctuating Hydroclimate

AbstractThis study reviews Kenya’s fluctuating hydroclimate (3°S–4°N, 35°–40°E) and evaluates products that describe its area-averaged daily rainfall during 2008–18, monthly evaporation during 2000–18, and catchment hydrology via gauge, satellite, and model hindcast/forecast. Using the correlation of rainfall as a metric of skill we found daily satellite versus model hindcasts achieved 75%, while model forecasts at 2–6-day lead achieved 55%–58%. The daily satellite versus model soil moisture had a significant correlation (84%), and model runoff versus gauge streamflow reached 61%. A 2-day delay was noted between rainfall and streamflow response in recent flood events; however, long-range predictability was found to be poor (35%). These outcomes were considered at a local workshop, and ways to sustainably improve the real-time reporting of key hydroclimate parameters for operational data assimilation were suggested as steps toward better monitoring and forecast services in Kenya.

Statistical Significance Assessment of Streamflow Elasticity of Major Rivers

Impacts of climate change on streamflow have long been an issue of concern for water experts. The main aim of this study is to assess the response of streamflow to precipitation and air temperature. In this study elasticity model was used to compute the precipitation and air temperature elasticity of 6 major rivers in Khyber-Pakhtunkhwa (KP) Province, Pakistan. In contrast to temperature elasticity estimator, box plots of precipitation elasticity estimator have low range and standard deviation leading to greater central affinity which produces valid, appropriate, and statistically significant elasticity results. Precipitation is positively correlated with streamflow while the air temperature is both positively and negatively linked with streamflow. 10% variation in precipitation and air temperature produces 12 to 20% and 8 to 18% change in streamflow, respectively. The sensitivity of streamflow to air temperature is higher as compared to precipitation. This research work shows that precipitation elasticity results are statistically valid and realistic as compared to temperature elasticity results. Moreover, it is suggested to support elasticity results by statistical correlation to avoid misleading and unrealistic results. Results of the current study can be used in formulating long term policies regarding streamflow sensitivity in the study region. Doi: 10.28991/cej-2021-03091698 Full Text: PDF

The Kings River Experimental Watersheds: Infrastructure and data

AbstractThe Kings River Experimental Watersheds (KREW) were established in 2002 to expand our knowledge of catchment physical, chemical, and biological processes in Sierra Nevada headwater forests, and to better understand the impacts of prescribed burning and forest thinning on these processes. Two elevation strata (high and low) were selected for the KREW sites, with four independent catchments and one nested catchment within each stratum. Both high and low elevation study areas were instrumented for continuous measurements of meteorology, streamflow, and turbidity. Atmospheric and stream chemistry, suspended sediment concentration, and bedload sediment delivery were measured on a regular schedule. Soil chemical and physical properties and vegetation were systematically sampled before and after the initial thinning and prescribed burning treatments, which were implemented between 2012 and 2016. Post‐treatment data collection continues today as we explore opportunities for the second round of possible treatments. The critical research infrastructure and long‐term baseline data collection has been instrumental in building partnerships with downstream managers, end users, non‐governmental organizations, academic researchers, and national research programmes. Contributions to date include fundamental understanding of magnitude and variability of nutrient deposition; carbon, nutrient, and major ion dynamics in headwater streams; aquatic algae and macroinvertebrate populations; vegetation composition and structure; and streamflow responses to precipitation in the two elevation strata. Data from the experimental watersheds also support calibration and validation of diverse hydrologic models used for water resources planning.

The effect of veld fires on the hydrological response of streamflow

Veld fires are natural occurrences with the potential to impact thousands of hectares of vegetation, and in doing so, changes soil characteristics, for both urban and rural areas. It is therefore reasonable to assume that the hydrological response of a catchment could be affected by fire. The main aim of this research was to investigate the hydrological changes caused by fire on a catchment scale using a case study. On 9 March 2015, a wildfire which started in Jonkershoek nature reserve destroyed indigenous fynbos vegetation and afforested areas. Within the nature reserve, there are multiple rainfall and runoff stations, which provided a means of measuring any possible hydrological changes due to these fire events. Four catchments were used for this research, one main catchment (fynbos area) and three sub-catchments (afforested areas). Fifty-six percent of the main catchment burned, while two sub-catchments were completely burned and the other primarily unaffected by the fire. The main catchment’s hydrological response was analysed by comparing the hydrographs of comparable pre- and post-fire runoff events. Eighteen comparable events were used for the analysis. The mean runoff volume increased by approximately 7% after the fire and mean peak flow by 50%. The change was even more noticeable when comparing the two sub-catchments affected by the veld fire and the unburned sub-catchment with each other. All the sub-catchments were similar in size and were located close enough to each other to be represented by one rainfall station. Before the fire, the average daily streamflows between the unburned (control) and burned catchments were similar; however after the fire the average daily streamflow of the two burned catchments in comparison to the control catchment increased by 45% and 50%, respectively. The mean runoff volume from the two affected/burned catchments, after the fire, for individual events increased by approx. 72% and 52% in comparison to the control catchment. The mean peak flows increased by approximately 173% and 110% in comparison to the control catchment.

Benefits from high-density rain gauge observations for hydrological response analysis in a small alpine catchment

Abstract. Spatial rainfall patterns exert a key control on the catchment-scale hydrologic response. Despite recent advances in radar-based rainfall sensing, rainfall observation remains a challenge, particularly in mountain environments. This paper analyzes the importance of high-density rainfall observations for a 13.4 km2 catchment located in the Swiss Alps, where rainfall events were monitored during 3 summer months using a network of 12 low-cost, drop-counting rain gauges. We developed a data-based analysis framework to assess the importance of high-density rainfall observations to help predict the hydrological response. The framework involves the definition of spatial rainfall distribution metrics based on hydrological and geomorphological considerations and a regression analysis of how these metrics explain the hydrologic response in terms of runoff coefficient and lag time. The gained insights on dominant predictors are then used to investigate the optimal rain gauge network density for predicting the streamflow response metrics, including an extensive test of the effect of down-sampled rain gauge networks and an event-based rainfall–runoff model to evaluate the resulting optimal rain gauge network configuration. The analysis unravels that, besides rainfall amount and intensity, the rainfall distance from the outlet along the stream network is a key spatial rainfall metric. This result calls for more detailed observations of stream network expansions and the parameterization of along-stream processes in rainfall–runoff models. In addition, despite the small spatial scale of this case study, the results show that an accurate representation of the rainfall field (with at least three rain gauges) is of prime importance for capturing the key characteristics of the hydrologic response in terms of generated runoff volumes and delay for the studied catchment (0.22 rain gauges per square kilometer). The potential of the developed rainfall monitoring and analysis framework for rainfall–runoff analysis in small catchments remains to be fully unraveled in future studies, potentially also including urban catchments.