Critical rainfall statistics for predicting watershed flood responses: rethinking the design storm concept

Recent advances have been made to modernize estimates of probable precipitation scenarios; however, researchers and engineers often continue to assume that rainfall events can be described by a small set of event statistics, typically average intensity and event duration. Given the easy availability of precipitation data and advances in desk‐top computational tools, we suggest that it is time to rethink the ‘design storm’ concept. Design storms should include more holistic characteristics of flood‐inducing rain events, which, in addition to describing specific hydrologic responses, may also be watershed or regionally specific. We present a sensitivity analysis of nine precipitation event statistics from observed precipitation events within a 60‐year record for Tompkins County, NY, USA. We perform a two‐sample Kolmogorov–Smirnov (KS) test to objectively identify precipitation event statistics of importance for two related hydrologic responses: (1) peak outflow from the Six Mile Creek watershed and (2) peak depth within the reservoir behind the Six Mile Creek Dam. We identify the total precipitation depth, peak hourly intensity, average intensity, event duration, interevent duration, and several statistics defining the temporal distribution of precipitation events to be important rainfall statistics to consider for predicting the watershed flood responses. We found that the two hydrologic responses had different sets of statistically significant parameters. We demonstrate through a stochastic precipitation generation analysis the effects of starting from a constrained parameter set (intensity and duration) when predicting hydrologic responses as opposed to utilizing an expanded suite of rainfall statistics. In particular, we note that the reduced precipitation parameter set may underestimate the probability of high stream flows and therefore underestimate flood hazard. Copyright © 2016 John Wiley & Sons, Ltd.     

Distinguishing streamflow trends caused by changes in climate,forest cover,and permafrost in a large watershed in northeastern China

Understanding how rivers respond to changes in land cover, climate, and subsurface conditions is critical for sustainably managing water resources and ecosystems. In this study, long‐term hydrologic, climate, and satellite data (1973–2012) from the Upper Tahe River watershed (2359 km²) in the Da Hinggan Mountains of northeast China were analysed to quantify the relative hydrologic effects of climate variability (system input) and the combined influences of forest cover change and permafrost thaw (system characteristics) on average annual streamflow (system response) using 2 methods: the sensitivity‐based method and the Kendall–Theil robust line method. The study period was subdivided into a forest harvesting period (1973–1987), a forest stability period (1988–2001), and a forest recovery period (2002–2012). The results indicated that the combined effects of forest harvesting and permafrost thaw on streamflow (+ 47.0 mm) from the forest harvesting period to the forest stability period was approximately twice as large as the effect associated with climate variability (+20.2 mm). Similarly, from the forest stability period to the forest recovery period, the decrease in average annual streamflow attributed to the combined effects of forest recovery and permafrost thaw (?38.0 mm) was much greater than the decrease due to climate variability (?22.2 mm). A simple method was used to separate the distinct impacts of forest cover change and permafrost thaw, but distinguishing these influences is difficult due to changes in surface and subsurface hydrologic connectivity associated with permafrost thaw. The results highlight the need to consider multiple streamflow drivers in future watershed and aquatic ecosystem management. Due to the ecological and hydrological susceptibility to disturbances in the Da Hinggan Mountains, forest harvesting will likely negatively impact ecohydrological processes in this region, and the effects of forest species transition in the forest recovery process should be further investigated.     

Exploration of remotely sensed forest structure and ultrasonic range sensor metrics to improve empirical snow models

Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta‐analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables – obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper – and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR‐derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP‐derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically significant relationships between snow indicators and structural metrics by increasing mean r² by 20% when compared to manual surveys. The relationships between vegetation and spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size helped to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing technologies, and better represent spatial and temporal variations of snow. Copyright © 2013 John Wiley & Sons, Ltd.     

Characterizing spatial and temporal variation in 18O and 2H content of New Zealand river water for better understanding of hydrologic processes

Time series of hydrogen and oxygen stable isotope ratios (δ²H and δ¹⁸O) in rivers can be used to quantify groundwater contributions to streamflow, and timescales of catchment storage. However, these isotope hydrology techniques rely on distinct spatial or temporal patterns of δ²H and δ¹⁸O within the hydrologic cycle. In New Zealand, lack of understanding of spatial and temporal patterns of δ²H and δ¹⁸O of river water hinders development of regional and national-scale hydrological models. We measured δ²H and δ¹⁸O monthly, together with river flow rates at 58 locations across New Zealand over a two-year period. Results show: (a) general patterns of decreasing δ²H and δ¹⁸O with increasing latitude were altered by New Zealand's major mountain ranges; δ²H and δ¹⁸O were distinctly lower in rivers fed from higher elevation catchments, and in eastern rain-shadow areas of both islands; (b) river water δ²H and δ¹⁸O values were partly controlled by local catchment characteristics (catchment slope, PET, catchment elevation, and upstream lake area) that influence evaporation processes; (c) regional differences in evaporation caused the slope of the river water line (i.e., the relationship between δ²H and δ¹⁸O in river water) for the (warmer) North Island to be lower than that of the (cooler, mountain-dominated) South Island; (d) δ²H seasonal offsets (i.e., the difference between seasonal peak and mean values) for individual sites ranged from 0.50‰ to 5.07‰. Peak values of δ¹⁸O and δ²H were in late summer, but values peaked 1 month later at the South Island sites, likely due to greater snow-melt contributions to streamflow. Strong spatial differences in river water δ²H and δ¹⁸O caused by orographic rainfall effects and evaporation may inform studies of water mixing across landscapes. Generally distinct seasonal isotope cycles, despite the large catchment sizes of rivers studied, are encouraging for transit time analysis applications.     

Hammond Hill Research Catchment: Supporting hydrologic investigations of rooting zone and vegetation water dynamics under climate change

The Hammond Hill Research Catchment (HH) is a small (120 ha), temperate, second order tributary to Six Mile Creek, Cayuga Lake, and the Great Lakes (42.42°, −76.32°). The HH has been monitored since January 2017 for the purpose of understanding how recent infiltration mixes with antecedent soil water on hillslope forest floors and the spatial and temporal patterns of Root Water Uptake (RWU) by temperate northeastern US tree species (eastern hemlock [Tsuga canadensis], American beech [Fagus grandifolia], and sugar maple [Acer saccharum]). These data are informing us about the hydrologic consequences of anticipated tree species composition change and supporting the development of more refined ecohydrological models. The glaciated catchment is underlain by a shallow confining siltstone layer (1–1.5 m depth) and densely covered with an approximately 60 year old regrowth mixed species forest of hemlock, beech, and other deciduous tree species common to the northeastern US. Current datasets from the HH include precipitation snow water equivalent, discharge, and associated isotopic water compositions, δ²H & δ¹⁸O. Measurements of (top 10 cm) soil water content, as well as bulk soil water and hemlock and beech xylem isotopic compositions are made at several locations across a topographic wetness gradient. The near-term role of the HH is to support an understanding of the environmental and ecological drivers of plant RWU competition. All data from the HH are publicly available.     

Hydrologic responses to land cover change: the case of Jedeb mesoscale catchment,Abay/Upper Blue Nile basin,Ethiopia

The objective of this study was to quantify the impacts of land use/land cover (LULC) change on the hydrology of the Jedeb, an agricultural dominated mesoscale catchment, in the Abay/Upper Blue Nile basin, Ethiopia. Two methods have been used. First, the trends of certain daily flow variability parameters were evaluated to detect statistical significance of the change of the hydrologic response. Second, a conceptual monthly hydrological model was used to detect changes in the model parameters over different periods to infer LULC change. The results from the statistical analysis of the daily flows between 1973 and 2010 reveal a significant change in the response of the catchment. Peak flow is enhanced, i.e. response appears to be flashier. There is a significant increase in the rise and fall rates of the flow hydrograph, as well as the number of low‐flow pulses below a threshold level. The discharge pulses show a declining duration with time. The model result depicts a change in model parameters over different periods, which could be attributed to an LULC change. The model parameters representing soil moisture conditions indicated a gradual decreasing trend, implying limited storage capacity likely attributed to increasing agricultural farming practices in the catchment. This resulted in more surface runoff and less infiltration into the soil layers. The results of the monthly flow duration curve analysis indicated large changes of the flow regime. The high flow has increased by 45% between the 1990s and 2000s, whereas the reduction in low flows was larger: a 15% decrease between 1970s and 1980s, 39% between 1980s and 1990s and up to 71% between 1990s and 2000s. These results, could guide informed catchment management practices to reduce surface runoff and augment soil moisture level in the Jedeb catchment. Copyright © 2013 John Wiley & Sons, Ltd.     

Changes in dissolved organic matter (DOM) amount and composition along nested headwater stream locations during baseflow and stormflow

Amount and composition of dissolved organic matter (DOM) were evaluated for multiple, nested stream locations in a forested watershed to investigate the role of hydrologic flow paths, wetlands and drainage scale. Sampling was performed over a 4‐year period (2008–2011) for five locations with drainage areas of 0.62, 3.5, 4.5, 12 and 79 ha. Hydrologic flow paths were characterized using an end‐member mixing model. DOM composition was determined using a suite of spectrofluorometric indices and a site‐specific parallel factor analysis model. Dissolved organic carbon (DOC), humic‐like DOM and fluorescence index were most sensitive to changes with drainage scale, whereas dissolved organic nitrogen, specific UV absorbance, Sr and protein‐like DOM were least sensitive. DOM concentrations and humic‐like DOM constituents were highest during both baseflow and stormflow for a 3.5‐ha catchment with a wetland near the catchment outlet. Whereas storm‐event concentrations of DOC and humic DOM constituents declined, the mass exports of DOC increased with increasing catchment scale. A pronounced dilution in storm‐event DOC concentration was observed at peak stream discharge for the 12‐ha drainage location, which was not as apparent at the 79‐ha scale, suggesting key differences in supply and transport of DOM. Our observations indicate that hydrologic flow paths, especially during storms, and the location and extent of wetlands in the catchment are key determinants of DOM concentration and composition. This study furthers our understanding of changes in DOM with drainage scale and the controls on DOM in headwater, forested catchments. Copyright © 2014 John Wiley & Sons, Ltd.     

Understanding the relative impacts of natural processes and human activities on the hydrology of the Central Rift Valley lakes,East Africa

Significant changes have been observed in the hydrology of Central Rift Valley (CRV) lakes in Ethiopia, East Africa as a result of both natural processes and human activities during the past three decades. This study applied an integrated approach (remote sensing, hydrologic modelling, and statistical analysis) to understand the relative effects of natural processes and human activities over a sparsely gauged CRV basin. Lake storage estimates were calculated from a hydrologic model constructed without inputs from human impacts such as water abstraction and compared with satellite‐based (observed) lake storage measurements to characterize the magnitude of human‐induced impacts. A non‐parametric Mann–Kendall test was used to detect the presence of climatic trends (e.g. a decreasing or increasing trends in precipitation), while the Standard Precipitation Index (SPI) analysis was used to assess the long‐term, inter‐annual climate variability within the basin. Results indicate human activities (e.g. abstraction) significantly contributed to the changes in the hydrology of the lakes, while no statistically significant climatic trend was seen in the basin, however inter‐annual natural climate variability, extreme dryness, and prolonged drought has negatively affected the lakes. The relative contributions of natural and human‐induced impacts on the lakes were quantified and evaluated by comparing hydrographs of the CRV lakes. Lake Abiyata has lost ~6.5 m in total lake height between 1985 and 2006, 70% (~4.5 m) of the loss has been attributed to human‐induced causes, whereas the remaining 30% is related to natural climate variability. The relative impact analysis utilized in this study could potentially be used to better plan and create effective water‐management practices in the basin and demonstrates the utility of this integrated methodology for similar studies assessing the relative natural and human‐induced impacts on lakes in data sparse areas. Copyright © 2015 John Wiley & Sons, Ltd.