Explore the vast range of titles available.

Determining rainfall runoff responses of catchments to unprecedented climate conditions is an issue which has largely eluded the hydrologic community for many years. Conceptual rainfall runoff models are used globally to predict runoff for regional water resources management and planning. However, obtaining parameter values suitable for future climate conditions requires approaches that consider conditions beyond historical periods. This paper takes advantage of data from 207 Australian catchments to determine model parameters that most closely produce expected rainfall runoff coefficients (ratio of runoff to rainfall) for a wide range of environmental conditions. This was done for two popular rainfall runoff models, GR4J and Sacramento. In a two‐step process, parameters were first selected that could adequately reproduce observed runoff coefficients across the 207 catchments. Acceptable parameter sets were stored in a library from which, in the second step, parameters were selected for each individual catchment according to various goodness‐of‐fit metrics. Performance of this calibration approach was compared with a classical optimization employed for each catchment (DELO—Differential Evolution Local Optimization). The study found performance trade‐offs using the parameter library based calibration compared to DELO for metrics such as Nash‐Sutcliffe Efficiency and percentage bias. The library‐based calibration exhibited behavior that more closely aligned with expectations under perturbed climate conditions, compared to DELO parameters. Results also showed tolerable estimates of rainfall runoff coefficient using DELO parameters at many sites when rainfall is reduced by no more than 25%. However, there is a high risk of under‐ or over‐estimating runoff coefficients at larger reductions.

The rational method is commonly used to estimate the design floods in catchments. An accurate estimation of surface runoff and the related design floods depends on the runoff coefficient precision, which is associated with several factors such as rainfall and soil infiltration rate. In the rational method, the design runoff coefficient ( C T ) is defined as a function of land use, soil type, slope, and return period. A technique is proposed here to compute C T based on the regional analysis of daily rainfall and soil conservation service curve number (SCS-CN) infiltration parameters. Daily rainfall data of 83 rain gauge stations in Sothern Iran (Fars province) were used to calculate the C T for various land uses and return periods for four rainfall rate categories. Equations were introduced to determine C T as a function of the return period and curve number in different catchments of the world. The regression correlation coefficient was calculated to be above 0.99 for the suggested equations. Based on the suggested method, for design purpose, the CN standard tables in the SCS method were converted into C T tables for the return period 10–500 years in Fars province, Iran.

The event runoff coefficient ( ) and the recession coefficient ( ) are of theoretical importance for understanding catchment response and of practical importance in hydrological design. We analyse 57 event periods in the period 2013 to 2015 in the 66 ha Austrian Hydrological Open Air Laboratory (HOAL), where the seven subcatchments are stratified by runoff generation types into wetlands, tile drainage and natural drainage. Three machine learning algorithms (Random forest (RF), Gradient Boost Decision Tree (GBDT) and Support vector machine (SVM)) are used to estimate and from 22 event based explanatory variables representing precipitation, soil moisture, groundwater level and season. The model performance of the SVM algorithm in estimating and is generally higher than that of the other two methods, measured by the coefficient of determination , and the performance for is higher than that for . The relative importance of the explanatory variables for the predictions, assessed by a heatmap, suggests that of the tile drainage systems is more strongly controlled by the weather conditions than by the catchment state, while the opposite is true for natural drainage systems. Overall, model performance strongly depends on the runoff generation type.

Runoffs in the Yellow River and Yangtze River basins, China, have been changing constantly during the last half century. In this paper, data from eight river gauging stations and 529 meteorological stations, inside and adjacent to the study basins, were analyzed and compared to quantify the hydrological processes involved, and to evaluate the role of human activities in chang- ing river discharges. The Inverse Distance Weighted （IDW） interpolation method was used to obtain climatic data coverage from station observations. According to the runoff coefficient equation, the effect of human activities and climate can be ex- pressed by changes in runoff coefficients and changes in precipitation, respectively. Annual runoff coefficients were calculated for the period 1950-2008, according to the correlation between respective hydrological series and regional precipitation. An- nual precipitation showed no obvious trend in the upper reaches of the Yellow River but a marked downward trend in the mid- dle and downstream reaches, with declines of 8.8 and 9.8 ram/10 a, respectively. All annual runoff series for the Yellow River basin showed a significant downward trend. Runoff declined by about 7.8 mm/10 a at Sanmenxia and 10.8 ram/10 a at Lijin. The series results indicated that an abrupt change occurred in the late 1980s to early 1990s. The trend of correlations between annual runoff and precipitation decreased significantly at the Yellow River stations, with rates ranging from 0.013/10 a to 0.019/10 a. For the hydrologic series, all precipitation series showed a downward trend in the Yangtze River basin with de- clines ranging from about 24.7 mm/10 a at Cuntan to 18.2 mm/10 a at Datong. Annual runoff series for the upper reaches of the Yangtze River decreased significantly, at rates ranging from 9.9 to 7.2 mm/10 a. In the middle and lower reaches, the run- off series showed no significant trend, with rates of change ranging from 2.1 to 2.9 ram/10 a. Human activities had the greatest influence on changes in the hydrological series of runoff, regardless of whether the effect was negative or positive. During 1970-2008, human activities contributed to 83% of the reduction in runoff in the Yellow River basin, and to 71% of the in- crease in runoff in the Yangtze River basin. Moreover, the impacts of human activities across the entire basin increased over time. In the 2000s, the impact of human activities exceeded that of climate change and was responsible for 84% of the decrease and 73% of the increase in runoff in the Yellow River and Yangtze River basins, respectively. The average annual runoff from 1980 to 2008 fell by about 97%, 83%, 83%, and 91%, compared with 1951-1969, at the Yellow River stations Lanzhou, San- menxia, Huayuankou and Lijin, respectively. Most of the reduction in runoff was caused by human activities. Changes in pre- cipitation also caused reductions in runoff of about 3%, 17%, 17%, and 9% at these four stations, respectively. Falling precipi- tation rates were the main explanation for runoff changes at the Yangtze River stations Cuntan, Yichang, Hankou, and Datong, causing reductions in runoff of 89%, 74%, 43%, and 35%, respectively. Underlying surface changes caused decreases in runoff in the Yellow River basin and increases in runoff in the Yangtze River basin. Runoff decreased in arid areas as a result of in- creased water usage, but increased in humid and sub-humid areas as a result of land reclamation and mass urbanization leading to decreases in evaporation and infiltration.

The Poyang Lake ungauged area (PLUA) is an essential hydrology buffer surrounding Poyang Lake. For such a data-scarce area, a novel spatially distributed runoff coefficient model (SDRCM) was developed based on the underlying surface properties using remotely sensed precipitation and reanalysis data after their validation. The runoff simulated by the SDRCM based on both sets of gridded precipitation data were validated in a subbasin where R2 and ENS are larger than 0.87. In addition, a hydrodynamic model was applied to validate the proposed model further by considering the estimated water yield for PLUA that involves boundary inputs, in which the result more closely aligns to the monthly observed discharge. On an annual basis, the PLUA water flow accounted for 12%–19% of the total annual water flow within the watershed, which was approximately equal to the proportion of the area of PLUA in relation to the entire watershed. Finally, the water balance between inflow and outflow of Poyang Lake was investigated, with relative errors observed at the Hukou gauging station all being less than 10% from 1998 to 2009. The proposed model will be helpful in understanding the significance of water yields of such ungauged plain area when evaluating the water balance.

While there are many factors, including climatology, geography, topography, vegetation and soil, that afect hydrologic processes, understanding the role of forests seems most essential, due to their manageable nature. In this study, a holistic approach was taken, and possible factors afecting streamflow, including tree, sapling, shrub, herb and soil strata, were measured for 29 small catchments/stream basins located in Turkey. Linear regression models were developed in order to estimate water flow (m³ ·ha−1). Several models were suggested for use in practice. These models were based on the data on hand and displayed a suficient level of explained variance in the dependent variable. Model 5, based on the variables of catchment area (ha), drainage density, ratio of coniferous stand areas in the catchment (%), tree volume (m³·ha−1), leaf area index, number of short saplings (number·ha−1), and topsoil sand rate (%), was recommended for flow estimation, achieving a 0.73 adjR² value for test data. These variables can be obtained as part of a survey and water managers can use them to estimate water flow of the catchment. The generated models can be used in multiple-use planning of forests, e.g. in adjusting the volume of stands to get optimum benefit from wood and water production. One of the most interesting results and one that was opposite to that documented in the general literature, was the positive correlation between tree volume and flow per hectare, which suggests a strategy of growing older tree stands to enable greater water production.

This study proposes using a Turing-like test for model evaluations and invalidations based on evidence of epistemic uncertainties in event runoff coefficients. Applying the consequent “limits of acceptability” results in all the 100 000 model parameter sets being rejected. However, applying the limits, together with an allowance for timing errors, to time steps ranked by discharge, results in an ensemble of 2064 models that can be retained for predicting discharge peaks. These do not include any of the models with the highest (> 0.9) efficiencies. The analysis raises questions about the impact of epistemic errors on model simulations, and the need for both better observed data and better models.

Climate change combined with urbanization increases the performance demand on urban drainage systems. Green roofs are one of the most used green infrastructure measures to alleviate the pressure on the urban drainage system through the detention and retention of runoff. The rational method with the runoff coefficient (C) is one of the most commonly used design tools for stormwater design in Norway. This method relies on a runoff coefficient being available for green roofs, which is typically not the case. This paper compares laboratory and experimental field studies to investigate runoff coefficients from different types of detention-based roofs. The methodology described in the German ‘FLL Guideline’, one of the world's most commonly used green roof standards, was used to measure the runoff coefficients for the different components making up a typical green roof. The contribution from each layer is reflected in the runoff coefficients. The runoff coefficients from the field experiments were calculated using observed precipitation and runoff from existing green roofs in Oslo, Trondheim, Sandnes, and Bergen, Norway. Events that had a cumulative precipitation comparable to the laboratory events, but longer durations, were selected. These events gave significantly lower and varying runoff coefficients, clearly demonstrating the limitation of choosing a suitable runoff coefficient for a given roof. However, laboratory experiments are important in understanding the underlying flow processes in the different layers in a detention-based roof.

Hydrologic response of a catchment with the most common expression through runoff coefficient reflects a complex response of interaction between the rainfall and catchment physical properties. In this study, an attempt has been made through the mean rainfall–runoff polygon method to explore the impact of land use change on the mean monthly runoff coefficient estimated from 27 years of the hydrology and land use records of a tropical catchment located in the east coast of Peninsular Malaysia. Specifically, the land use and flow records are divided into three intervals: (1982–1990), (1992–2000) and (2002–2010). The mean monthly rainfall–runoff polygon plotted is rendered to the three time intervals. The results have shown that contrasting shapes were computed which demonstrate the significant variability in the rainfall–runoff response characteristics under the linkage of land use changes. Ample information describing the hydrological responses of the study area has been attained through the quantitative approaches. The study has concluded that the rainfall–runoff polygon method can be used as a simple alternative method for assessing the impact of land use changes on the hydrological response.

Rainwater tanks are increasingly adopted in Australia to reduce potable water demand and are perceived to reduce the volume of stormwater discharge from developments. This paper investigates the water balance of rainwater tanks, in particular the possible impacts these tanks could have in controlling the stormwater discharge volume. The study collected water quantity data from two sites in the Hawkesbury City Council area, New South Wales, Australia and utilised the collected data in a simple water balance model to assess the effectiveness of rainwater tanks in reducing the stormwater discharge volume. The results indicate that a significant reduction in discharge volume from a lot scale development can be achieved if the rainwater tank is connected to multiple end-uses, but is minimal when using irrigation alone. In addition, the commonly used volumetric runoff coefficient of 0.9 was found to over-estimate the runoff from the roof areas and to thereby under-estimate the available volume within the rainwater tanks for retention or detention. Also, sole reliance on the water in the rainwater tanks can make the users aware of their water use pattern and water availability, resulting in significant reductions in water use as the supply dwindles, through self-imposed water restrictions.