The runoff coefficient as the key to moisture recycling

doi:10.1016/0022-1694(95)02776-9

Journal of Hydrology

Volume 176, Issues 1–4, 1 March 1996, Pages 219-225

https://doi.org/10.1016/0022-1694(95)02776-9 Get rights and content

Abstract

Moisture recycling by evapotranspiration from vegetation is probably the most important mechanism sustaining rainfall on continental catchments, particularly in semiarid areas. A very simple and very useful parameter to evaluate moisture recycling is the annual runoff coefficient C_R. On continents, the proportion of rainfall recycled equals 1 — C_R, whereas the average number of times that a moisture particle returns as rainfall equals $1 C_{R}$ . Since the runoff coefficient is widely mapped, it is a very handy indicator to evaluate the importance of land-use practices in rainfall recycling. It is further stated that the idea of some water resources engineers that a high runoff coefficient is an asset for water resources development is a misconception. For the water resources management of continental areas, the most efficient use of water is made by minimizing runoff.

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Neural network models have been widely used in runoff forecasting, but are often criticized for their lack of physical interpretability. In this study, we present a simple but useful approach to developing hydrological models by designing neural networks based on the principles of runoff generation and concentration, which we refer to as a Hydrological Process-based Neural Network (HPNN) model. The Convolutional neural network (CNN) and softmax function are used because of their similar formula to the conventional runoff generation and unit hydrograph approach used in hydrology. We apply the HPNN model and four other benchmark models to forecast runoff in two catchments (Yutan and Chenda) in China. Results show that the HPNN model has higher computational efficiency, its parameters are interpretable and closely linked to the processes of runoff generation and concentration, and the HPNN model outperforms conventional GRU-based models.
Climate and landuse change enhance spatio-temporal variability of Dongjiang river flow and ammonia nitrogen
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The adverse impacts of climate and landuse change are threatening the availability of water quantity and its quality, yet there are limited understandings in the response of water availability to changing environment at different spatio-temporal scales. Aimed at quantifying the individual and superimposed effects of climate and landuse change on streamflow and ammonia nitrogen (NH₃−N) load in the Dongjiang River Basin (DRB), we dynamically simulated the historical (1981–2010) and future (2030–2070) variation of runoff depth and NH₃-N load coupling multiple regional climate model and landuse data. The increase in runoff depth (avg. +233.9 mm) due to climate change was about 33 times greater than that caused by landuse change (avg. -7.2 mm). Especially in the downstream of DRB (Hong Kong, Shenzhen and Dongguan cities, etc.), the maximum rise of runoff depth under climate change was near twice compared with baseline period, indicating the dominant control of climate change on runoff. Also there existed higher coefficient of variation (C_v) value of runoff in the dry season of downstream DRB, contributing potential great fluctuation in runoff. Besides, the variation of NH₃-N load was jointly influenced by climate and landuse change, revealing an offset or amplification effect. Moreover, the variability of NH₃-N load (C_v value as the metric) increased from 2030, reached a maximum in 2050, following decreased to 2070. The spatial distribution of NH₃-N load, in general, presented a downward trend and concentrated near the water body, while the monthly average NH₃-N load showed distinct peaks in spring and late summer temporally. Overall, the results highlight the significance of investigating the water availability under changing environment and more adaptive strategies should be proposed for better basin water management.
Can seawater desalination be a win-win fix to our water cycle?
2020, Water Research
Citation Excerpt :
We may assume that evaporation of water added to the water cycle through desalination is subject to the same recycling rate (see Supplementary Material, Note 1, for additional discussion). Subsequent cycles of evaporation and precipitation yield a total incremental precipitation inversely related to the ratio between annual runoff and precipitation (Savenije, 1996). This incremental precipitation can be estimated between about 800 (when runoff is 50% of precipitation) and 1300 liters per m3 (when runoff is 0%) at global average evapotranspiration recycling rates (see Fig. 1).
While we increasingly turn to desalination as a secure water supply, it is still perceived as an expensive and environmentally damaging solution, affordable only for affluent societies. In this contribution, we recast desalination from one of a last resort to a far-reaching, climate change mitigating, water security solution.
First, we argue that the benefits of desalination go beyond the single-use value of the water produced. If coupled with water reuse for irrigation, desalination reduces groundwater abstraction and augments the water cycle. As such, it may support both adaptation to, and mitigation of climate change impacts by deploying plentiful water for human use, with all the benefits that entails, while helping preserve and restore ecosystems.
Second, we counter two arguments commonly raised against desalination, namely its environmental impact and high cost.
The environmental impact can be fully controlled so as not to pose long-term threats, if driven by renewable energy. Desalination may then have a zero carbon footprint. Moreover, appropriately designed outfalls make the disposal of brine at sea compatible with marine ecosystems.. Recovery of energy, minerals and more water from brine reject (particularly in the form of vapour for cooling to enable more crops and vegetation to grow), while possible, is often hardly economically justified. However, resource recovery may become more attractive in the future, and help reduce the brine volumes to dispose of.
When fresh water becomes scarce, its cost tends to go up, making desalination increasingly economic. Moreover, desalination can have virtually no environmental costs. Considering the environmental costs of over-abstraction of freshwater, desalination tilts the balance in its favour.
Impacts of multi-purpose reservoir construction, land-use change and climate change on runoff characteristics in the Poyang Lake basin, China
2020, Journal of Hydrology: Regional Studies
Citation Excerpt :
Our current study seeks to improve the understanding of the changing water balance dynamics in the basin, which is essential for management of its water resources, and can also contribute to improve generic understanding of similar processes in many other world regions subject to complex and overlapping pressures from different human activities and climate change. We use a water balance approach and evapotranspiration modelling in combination with analyses of runoff coefficients (RC, a dimensionless ratio of total runoff over total precipitation; McNamara et al., 1998; Savenije, 1996), to access causes behind observed changes in runoff on various time scales. More specifically, this study considers all five main sub-catchments of the Poyang Lake basin under pre-dam and post-dam conditions, aiming at detecting impacts of climate change and anthropogenic activities including multi-purpose reservoir construction on:
The Poyang Lake basin at the Yangtze River, China.
Impacts of multi-purpose reservoirs on runoff are investigated through the lens of spatio-temporal shifts in runoff coefficients (RC) before and after reservoir construction. We furthermore use evapotranspiration (ET) modelling to interpret possible additional impacts of climate change and other ambient changes since the 1950s within the Poyang Lake basin, comprising one of China’s most important freshwater resources.
New Hydrological Insights for the Region: Results show that annual average RC and ET remain essentially unchanged despite reservoir constructions and irrigation development. We show that simultaneous, basin-wide implementation of lake-to-land transitions (including wetland drainage) has had a dampening effect on ET, contributing to unexpectedly weak ET trends. Our model furthermore shows that the observed (modest) ET increases since the 1950s can be fully attributed to the warmer climate in the region. Furthermore, the intra-annual distribution of the monthly RC used to be almost identical in all sub-basins during the pre-dam period. We show that the different operation schedules of multi-purpose reservoirs, which reflect location-specific differences in water need over the year, have resulted in pronounced temporal differences in sub-basin runoff characteristics (including RC-values). The present analysis contributes to process understanding, relevant for water management decisions in the Poyang Lake basin and other major multi-purpose dam regions across the world.
Using storage of coal-mining subsidence area for minimizing flood
2019, Journal of Hydrology
Citation Excerpt :
Including the runoff coefficient and the recharge coefficient. The runoff coefficient is the key to hydrological cycle (Savenije, 1996). The average annual precipitation in the HRB is about 894 mm, and the average annual runoff is about 230 mm (Zhang et al., 2012a,b).
Floods are one of the most devastating natural disasters, especially in the midstream plain area of the Huaihe River Basin (HRB) in China, where it is densely populated. This region has suffered from serious backwater flood problems due to its topography and geomorphology. Additional storage space is critical for this region in order to control flood. The middle reach of the Huaihe River is a coal-rich region. The large subsidence areas caused by coal mining may help reduce the issue of insufficient flood storage space, and therefore evaluation of the flood storage capacity in the subsidence areas becomes necessary. A distributed coupled surface water - groundwater model, MODCYCLE, was redeveloped to simulate the interaction between the rivers, the water in the subsidence areas and groundwater. The model was used to simulate maximum flood storage capacity in the subsidence areas and the ability to reduce flood peaks. Two scenarios were created for land subsidence conditions in 2010 and 2030 where typical flood events in 2003 were used. It is revealed that for the 2010 scenario, there was flood overflow even with the maximum storage space used, whereas for the 2030 scenario, the subsidence areas could completely contain the flood water, and therefore eliminate the backwater flood problem. Compared with the 2010 subsidence scenario, the water levels in the depressions can also be significantly reduced in the 2030 subsidence scenario. Our results, from an integrated hydrological modeling’s perspective, suggest that using the subsidence areas caused by coal mining for flood storage has the potential to alleviate the problem of backwater flood in the study area, and in the meantime provides an alternative management approach for handling the subsidence areas.
Sensitivity of drought resilience-vulnerability- exposure to hydrologic ratios in contiguous United States
2018, Journal of Hydrology
The atmospheric water supply and demand dynamics determine a region’s potential water resources. The hydrologic ratios, such as, aridity index, evaporation ratio and runoff coefficients are useful indicators to quantify the atmospheric water dynamics at watershed to regional scales. In this study, we developed a modeling framework using a machine learning approach to predict hydrologic ratios for watersheds located in contiguous United States (CONUS) by utilizing a set of climate, soil, vegetation, and topographic variables. Overall, the proposed modeling framework is able to simulate the hydrologic ratios at watershed scale with a considerable accuracy. The concept of non-parametric elasticity was applied to study the potential influence of the estimated hydrologic ratios on various drought characteristics (resilience, vulnerability, and exposure) for river basins located in CONUS. Spatial sensitivity of drought indicators to hydrologic ratios suggests that an increase in hydrologic ratios may result in augmentation of magnitude of drought indicators in majority of the river basins. Aridity index seems to have higher influence on drought characteristics in comparison to other hydrologic ratios. It was observed that the machine learning approach based on random forests algorithm can efficiently estimate the spatial distribution of hydrologic ratios provided sufficient data is available. In addition to that, the non-parametric based elasticity approach can identify the potential influence of hydrologic ratios on spatial drought characteristics.

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Research paperThe runoff coefficient as the key to moisture recycling

Abstract

J. Hydrol.

Estimation of continental precipitation recycling

J. Clim.

Climate and Life

Research paper
The runoff coefficient as the key to moisture recycling