Rainwater as a resource has been underrated due to scientific misunderstandings about its quality, the lack of hydrologic design tools for small catchments, such as roofs, the preference for large ...infrastructures, and the small number of successful cases reported. This book summarizes 17 years of scientific research, operational monitoring, and practical demonstration projects made at Seoul National University Rainwater Research Center. A new paradigm of rainwater is proposed, which is to collect rainwater and use it, instead of draining it. Based on conventional hydrology and methodology, a hydrologic modelling method for micro-catchment is suggested. By incorporating several controllable measures into the design, the system can solve several water-related problems such as flooding, water conservation, emergency water storage, and groundwater recharge. Now is the time to adapt. Many good examples are reported from around the world, including South Korea. Fifty-nine South Korean cities have announced regulations and commitment to become ‘Rain Cities’ by offering financial incentives to rainwater management systems or subsidizing them. This book is written to give hope to those who seek to transform their community from a ‘Drain City’ to a ‘Rain City’. It has been prepared to clear the ambiguity about rainwater management and transform the experts as well as the citizens to become active proponents of rainwater. This book can be a guide to transform the world into Rain Cities, and become a viable solution toward Sustainable Development Goal Number 6.
A precise estimation of seasonal runoff and accurate quantification of discharge components is imperative for understanding the hydroclimatic regimes in mountainous regions. This study aimed to ...investigate daily discharge processes and seasonal runoff composition by employing a temperature-index Snowmelt Runoff Model (SRM) using in-situ hydro-meteorological data and limited field observations with a combination of remote sensing data in the debris-covered and clean-ice glaciers. This analysis showed that meltwater production was reduced by 26.5% considering clean-ice and debris-cover ice scenarios necessitating the importance of incorporating debris cover and debris thickness information in temperature-index and snowmelt runoff models. The simulation of daily discharge shows satisfactory agreement with the coefficient of determination (0.89–0.91) and the Nash–Sutcliffe Efficiency (0.85–0.88) for the calibration (2001–02) and validation (2003–10) periods, respectively. Decadal analysis of supraglacial debris-covered area changes shows a 0.37% increase per year on average exhibiting negligible effect on glacier melting and associated flow regimes. Analysis of MODIS snow cover data revealed that the seasonal snow cover varies between 80% in winter and 30% in summer. Negative trends in the snow cover were observed during winter and slightly increasing trends during summers indicated a decreasing influence of westerlies and a strengthening of the Indian summer monsoon system over the region.
Rainfall-runoff modelling has always been of great importance in hydrology. Recently, the Event-Based Approach for Small and Ungauged Basins (EBA4SUB) model, based on the instantaneous unit ...hydrograph (IUH) formulation, was released. The EBA4SUB model was originally developed considering only the surface flow, and in this work it has been generalized considering also the subsurface flow. The aim is to make EBA4SUB applicable both for Hortonian and/or for Dunne-Black mechanisms, proposing the so-called Generalized EBA4SUB model (GEBA4SUB). Here, GEBA4SUB and EBA4SUB are compared at the event scale, using observed rainfall-runoff events, and in estimating design discharge, using extreme value observations. In both cases, the results suggest that GEBA4SUB could outperform EBA4SUB, with improvements from 15% to over 100%.
Identification and pairing of hydrologic events form the basis of various analyses, from identifying events for the calibration of hydrologic models, to calculation of event runoff coefficients for ...catchment characterization. Despite this, there is no unified approach for identifying hydrologic events. Here, using the R package, hydroEvents (https://CRAN.R-project.org/package=hydroEvents), we compare multiple methods of extracting and pairing hydrologic events focussing on the relationship between rainfall and runoff. We find the four common analytical approaches used to identify runoff events—based on either event threshold, local maxima/minima, or proportion of baseflow contribution, give similar results. However, when rainfall events are paired to runoff, the type of algorithm and the direction of pairing (either from rainfall to runoff, or runoff to rainfall) make a considerable difference to the final event pairs identified and resulting analyses. Here, we demonstrate the value of automated event extraction and pairing algorithms for large‐sample hydrology analysis by calculating event runoff coefficients across Australia. Our results show that climatology is a key driver of catchment rainfall‐runoff response with much of Australia dominated by excess rainfall runoff generation. However, our results also show that the variability due to pairing method can introduce a variability equal to that of the climatology due to biasing the runoff mechanism within the sample. With this analysis we demonstrate the importance of systematic and consistent approaches to hydrologic characterization when identifying and pairing hydrological events.
Using the R package hydroEvents we compare multiple methods of extracting and pairing hydrologic events focussing on the relationship between rainfall and runoff. We calculate event runoff coefficients across Australia showing climatology is a key driver of catchment rainfall‐runoff response. However, our results also show that the variability due to pairing method can introduce a variability equal to that of the climatology. This demonstrates the importance of systematic and consistent approaches to hydrologic characterization when using different rainfall‐runoff pairing approaches.
Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models ...tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282347 cases of apparent model failure under the split sample test using the lower higher of two model performance criteria trialed, 155120 were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results.
Key Points:
Models may be more capable under changing climatic conditions than previously thought
Common calibration methods often fail to identify parameter sets that are robust
Caution is needed when interpreting the results of split sample testing
Understanding the nature of streamflow response to precipitation inputs is at the core of hydrological applications and water resource management. Indices such as the base flow index, recession ...constant, and response lag of a watershed retain an important place in hydrology as metrics to compare watersheds and understand the impact of human activity, geology, geomorphology, soils, and climate on precipitation–runoff relations. Extracting characteristics of the hyetograph–hydrograph relationship is often done manually, which is time consuming and may result in subjective and potentially inconsistent outcomes. Here, we present a MATLAB‐based toolbox, called HydRun, for rapid and flexible rainfall–runoff analysis. HydRun uses a series of flexible routines to extract base flow from the hydrograph and then computes commonly used time instants of the rainfall–runoff relationship. HydRun provides users the flexibility to decide thresholds and limits of analysis, but objectively computes hydrometric indices. The toolkit includes a graphical user interface and example files. In this paper, we apply HydRun to 4 watersheds, 3 in Scotland and 1 in Canada, to demonstrate the software functions and highlight important decisions the user must make in its application.
Snowmelt‐dominated runoff regimes have defined northern Alaskan rivers. Discharge records from three watersheds within the National Petroleum Reserve in Alaska (NPR‐A) span 19 years and capture three ...notable periods of changing runoff. In the first, 2001–2008, mean annual runoff (MAR) averaged 90 mm, characterized by sharp snowmelt runoff and summer drought. Over the next 7 years, larger MAR averaged 120 mm driven by high and early snowmelt runoff. The most recent 4 years, 2016–2019, had even higher MAR of 163 mm with high and sustained late summer flows. Hydrograph analysis suggests a shift toward rainfall‐dominated runoff in the most recent period compared to snowmelt‐dominated hydrographs in the previous two. Declining sea ice appears closely linked to increasing late summer precipitation and a shift toward rainfall runoff. Future development in the NPR‐A will require continued hydrological monitoring and planning to mitigate flood and erosion hazards, permafrost degradation, and ecosystem impairment.
Plain Language Summary
Water is expected to cycle more rapidly as the Arctic climate warms, yet it is uncertain whether conditions will get wetter or dryer. Watershed runoff, measured in the form of river flow, captures the balance of precipitation and evaporation over wide land areas to detect how the water cycle is changing. Historically, arctic river flows are supplied mainly by spring snowmelt and become quite low during summers with limited rainfall. River flow records from three watersheds in northern Alaska over the last 19 years provide evidence that total water inputs from snow and rain are increasing relative to water losses from evaporation. Most recently, contributions from rainfall have increased greatly, and this may be related to enhanced moisture supply from more ice‐free conditions of the Arctic Ocean. Higher river flows that come later in the summer may affect erosion and sedimentation, frozen soils, fish habitat, and human infrastructure.
Key Points
Arctic Coastal Plain watershed runoff regimes are traditionally snowmelt‐dominated
Discharge records show increasing annual runoff over the past 19 years and much higher rainfall runoff contributions over the last 4 years
Increasing ice‐free ocean conditions correspond to higher rainfall runoff, yet attribution of hydrologic responses remain uncertain
Increased nitrogen (N) from urban stormwater runoff aggravates the deterioration of aquatic ecosystems as urbanisation develops. The sources and transport of nitrate (NO
3
−
) in urban stormwater ...runoff were investigated by analysing different forms of N, water isotopes (δD-H
2
O and δ
18
O-H
2
O), and NO
3
−
isotopes (δ
15
N-NO
3
−
and δ
18
O-NO
3
−
) in urban stormwater runoff in a residential area in Hangzhou, China. The results showed that the concentrations of total N and nitrate N in road runoff were higher than those in roof runoff. Moreover, high concentrations of dissolved organic N and particulate N led to high total nitrogen (TN) concentrations in road runoff (mean: 3.76 mg/L). The high δ
18
O-NO
3
−
values (mean: + 60 ± 13.1‰) indicated that atmospheric deposition was the predominant NO
3
−
source in roof runoff, as confirmed by the Bayesian isotope mixing model (SIAR model), contributing 84–98% to NO
3
−
. Atmospheric deposition (34–92%) and chemical fertilisers (6.2–54%) were the main NO
3
−
sources for the road runoff. The proportional contributions from soil and organic N were small in the road runoff and roof runoff. For the initial period, the NO
3
−
contributions from atmospheric deposition and chemical fertilisers were higher and lower, respectively, than those in the middle and late periods in road runoff during storm events 3 and 4, while an opposite trend of road runoff in storm event 7 highlighted the influence of short antecedent dry weather period. Reducing impervious areas and more effective management of fertiliser application in urban green land areas were essential to minimize the presence of N in urban aquatic ecosystems.
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